**Preface to "Ecology and Conservation of Freshwater Fishes Biodiversity"**

Freshwater fishes are the most diverse vertebrate group, with almost 36,000 species described so far, and more species are being discovered all the time, evenly distributed between marine and freshwater habitats. Freshwater ecosystems serve as a habitat for more than 18,000 fish species, occupying less than 1% of the Earth's surface. Among all ecosystems, inland waters are one of the most affected. Wetlands are disappearing three times faster than forests, and freshwater populations decrease faster than terrestrial biodiversity. Nowadays, freshwater fishes may be considered the most threatened vertebrate group.

Understanding the ecological subjects, environmental necessities, and pressures of freshwater fishes remains a key concern of their conservation biology. This reprint explores the relationships between environmental issues, freshwater fish biodiversity, and human impacts from different perspectives, but always focuses on the conservation biology of species and ecosystems.

A change in mindset is needed to protect biodiversity in the upcoming years. Conservation plans have failed because our current knowledge is deficient and needs to be improved. We need countries to commit to protecting biodiversity and develop realistic targets that can be met while compromising with conflicting needs and interests. The articles included in this reprint emphasize the necessity of having more knowledge to develop conservation strategies. Future conservation targets may be advanced in part based on the knowledge provided by these papers and similar studies to ensure the long-term protection of freshwater fish and other life forms.

> **Rafael Miranda** *Editor*

**Rafael Miranda 1,2, \* and Imanol Miqueleiz 1**


Freshwater fish represent one-fourth of all vertebrate species, despite freshwater occupying less than 1% of the Earth's surface [1]. They are among the most threatened vertebrates, as they are especially vulnerable to human alterations resulting from species introduction, overexploitation, fragmentation, the degradation of continental watercourses, and climate change [2]. Furthermore, freshwater fish show high levels of endemism because of the particular characteristics of their aquatic ecosystems and their evolutionary isolation; their loss could have irreparable consequences.

Knowledge regarding the conservation status and ecology of freshwater fish is less than that for terrestrial vertebrates due to biases in conservation research and management toward more charismatic species [1]. Research into the ecological subjects, environmental necessities, and pressures of freshwater fishes is considered crucial to develop effective management measures for freshwater ecosystems. Understanding these environmental features remains a key concern of freshwater fish's conservation biology.

This Special Issue of *Water* explores the relationships of environmental issues, freshwater fish biodiversity, and human impacts from different perspectives, but always focused on the conservation biology of species and ecosystems. This Special Issue comprises thirteen papers with contributions from seventy-one authors, including research studies from very diverse ecosystems, places, and countries, from the most extensive basins, such as Middle Rio Grande in New Mexico (USA) [3] or the Yangtze River Basin (China) [4], to remote areas in Andean Amazon piedmont (Peru) [5] or Lake Tana (Ethiopia) [6]. Analyzed ecosystems include basins, rivers and streams, lakes, and ponds from high mountain to estuarine places, from pristine to highly altered environments.

The articles include eleven research articles, one review and a short communication. The nature of studies included in this Special Issue is diverse, considering a variety of scientific approaches in a mixture of field topics. One of the published papers considers methodological approaches to studying freshwater fishes and their conservation status. The authors propose a methodological study and improvement on age estimation for four species of *Labeobarbus* genus using otoliths as a crucial tool for conserving these species. According to the authors, this kind of study is very relevant to Africa, particularly Ethiopia, in order to develop effective management strategies to conserve endemic species [6]. Similarly, Gebremedhin et al. review scientific methods, concepts, and processes related to stock assessment and population dynamics in Africa [7].

Three published papers present results on fish distribution, ecosystem explorations, and ecological features in unique places, using many different techniques. Perivolioti et al. [8] conduct hydroacoustic monitoring of the Lake Trichonis (Greece) fish diversity, with the aim of offering an updated assessment of this unique ecosystem and the associated endemic species, with a focus on management and conservation.

Tobes et al. [5] study the distribution of fish communities related to the environmental variables of the Alto Madre de Dios River, a poorly studied Andean–Amazon watershed

**Citation:** Miranda, R.; Miqueleiz, I. Ecology and Conservation of Freshwater Fishes Biodiversity: We Need More Knowledge to Develop Conservation Strategies. *Water* **2021**, *13*, 1929. https://doi.org/10.3390/ w13141929

Received: 2 July 2021 Accepted: 9 July 2021 Published: 13 July 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

of southern Peru. Results show a significant shift in fish diversity regarding altitude, separating headwater and middle-lowland communities. In the light of this scenario where no Andean–Amazon Basin will remain untouched, the studied basin still preserves healthy ecosystems, showing excellent environmental quality overall. This condition makes the basin a perfect candidate for serving as a reference basin for these endangered ecosystems. Schmitter-Soto et al. [9] investigate changes in a fish community during a long-term period, from 1999–2001 to 2015–2018. The results show that changes may be due to morphological changes in the channel. Still, other threats could condition these changes: illegal fishing outside the bay, and erosion in the innermost part, impacting native habitats. Li et al. analyze fish distribution, influencing factors, and habitat requirements in the East Tiaoxi River (a major tributary of the renowned Yangtze River). Results show differences in fish management and several severe threats to their conservation. Complete and continuous scientific research of fish diversity is crucial in order to develop efficient conservation and restoration plans in the Yangtze River Basin [4].

Several papers in this Special Issue explore, in more detail, applications of ecological and biological studies to improve monitoring of environmental changes and impacts on freshwater fishes. Sometimes biological studies permit us to detect reactions to environmental changes. Pastorino et al. [10] describe liver alterations observed in a bullhead population (*Cottus gobio* Linnaeus, 1758) from a mountain lake as an adaptation to extreme ecosystems and adverse conditions. Other studies highlight the interaction between ecological stress factors and biological traits and the use of sentinel species for the long-term monitoring of environmental status. This is the case with the study of Sánchez-Pérez et al. [11], where they analyze biological traits such as the growth, size structure, and somatic condition of the Southern Iberian barbel (*Luciobarbus sclateri* (Günther, 1868)) in a stressed Mediterranean river.

Some studies are focused on severely imperiled species, such as the Rio Grande Silvery Minnow (*Hybognathus amarus* (Girard, 1856)), catalogued as Endangered by the IUCN Red List of threatened species; the Spanish toothcarp (*Aphanius iberus* Valenciennes, 1846), catalogued as Endangered; or the Pyrenean Sculpin (*Cottus hispaniolensis* Bacescu-Master, 1964), included in the Spanish Catalogue of Threatened Species as Endangered [3,12,13]. Archdeacon et al. analyze the inefficiency of a specific conservation tool, the rescue of the Rio Grande Silvery Minnow during streamflow intermittency. Restoring natural flow regimes is the more effective action for species threatened by streamflow intermittency; re-establishment of the biological processes under which fishes evolved advances the conservation of this species [3].

Other species threatened by water quality have been studied in the Iberian Peninsula. Sgarzi et al. [13] examine abiotic and biotic factors that could influence the size structure and density of Spanish toothcarp in Mediterranean brackish ponds. They suggest that achieving a better pond ecological status may be necessary to conserve this endangered fish. Manubens et al. [12] describe the ex situ conservation plan for the endemic and rare Pyrenean sculpin (*Cottus hispaniolensis* Bacescu-Mester, 1964). The captive breeding process includes six consecutive phases: nesting behavior, courtship, egg fixation, parental care (incubation), hatching, and survival during juvenile development. The management plan implemented for this project has probably allowed the main impediments described in other similar programs to be largely overcome.

Conversely, some studies in this Special Issue are biological and ecological analyses of exotic invasive species, as the Pyrenean Gudgeon (*Gobio lozanoi* Doadrio & Madeira, 2004) in a Mediterranean river or the bleak (*Alburnus alburnus* (Linnaeus, 1758)) in the Iberian Peninsula. Both studies are focused on the significant role of plasticity in the success of these invasive alien species. Latorre et al. [14] assess the variability in dietary traits of the bleak in the Iberian Peninsula and compare the dietary characteristics of this species among the main Iberian rivers and a native bleak population from France. Similarly, Amat-Trigo et al. [15] evaluate other biological traits in addition to the diet. The results of both studies suggest that this wide interpopulation variability will contribute to the species' successful establishment throughout Mediterranean Europe, posing a severe risk to native fish fauna.

All the articles included in this Special Issue point in the same direction. The current status of freshwater fish must be brought to our attention in order to design and implement effective management measures to conserve freshwater fish. While we should maintain our interest in learning and know more about the conservation status of the imperiled freshwater fish, policy and administrations should invert inefficient plans in order to revert, or at least reduce, the current crisis in biodiversity.

A change in mindset is needed to protect biodiversity in the upcoming years. Conservation plans have failed because our current knowledge is deficient and needs to be improved. We need countries to commit to protecting biodiversity and develop realistic targets that can be met while compromising with conflicting needs and interests. The articles included in this Special Issue emphasize the necessity of having more knowledge to develop conservation strategies. Future conservation targets may be advanced in part based on the knowledge provided by these papers and similar studies to ensure the long-term protection of freshwater fish and other life forms [1].

**Funding:** This research received no external funding.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


## *Article* **Fish Ecology of the Alto Madre de Dios River Basin (Peru): Notes on Electrofishing Surveys, Elevation, Palm Swamp and Headwater Fishes**

**Ibon Tobes 1,2 , Adrián Ramos-Merchante 3 , Julio Araujo-Flores 4,5,6 , Andrea Pino-del-Carpio 2 , Hernán Ortega 7 and Rafael Miranda 2, \***


**Abstract:** Our study analyzes the distribution of fish communities related to the environmental variables of the Alto Madre de Dios River, an Andean-Amazon watershed of southern Peru, between 300 and 2811 m a.s.l. within the Manu Biosphere Reserve. We provide new ecological and diversity data on fishes for these poorly studied rivers and new data for palm swamp habitats. With electric fishing techniques, we collected a total of 1934 fish specimens belonging to 78 species, 42 genera and 15 families. To assess main patterns of diversity we combined SIMPER and ANOSIM with canonical correspondence analysis to obtain an overview of the community structure of fish and their distribution related to aquatic habitats. Our results show an important shift on fish diversity at 700 m a.s.l. separating headwater and middle-lowland communities. Electrofishing was a hindrance due to the depth, flow and low conductivity of the rivers, but also allowed us to capture fish not observed with other techniques. We also compared the use of elevation with slope as an alternative variable for statistical analysis. Our results show that slope offers a solid and equivalent explanation for fish distribution variability, avoids redundance, and instead of giving geographical data offers ecologically solid information.

**Keywords:** Tropical Andes; Manu Biosphere Reserve; *Astroblepus*; *Trichomycterus*; *Mauritia flexuosa*

#### **1. Introduction**

Freshwater ecosystems are often referenced among those that are most altered and threatened by anthropogenic impacts [1] and their fauna is at greater risk than any other animal and plant groups [2]. In this respect, precise knowledge of ecological aspects like species distribution and requirements are a key point for conservation strategies, especially when the focal species are threatened or endangered [3]. Unfortunately, our limited taxonomic knowledge and incomplete information on species distributions for broad territories is very high and represents an insurmountable obstacle for documentation of imperilment and extinction of freshwater biodiversity [4]. In particular, fish assemblage variations in mountain streams of the Andes are poorly understood [5,6].

**Citation:** Tobes, I.;

Ramos-Merchante, A.; Araujo-Flores, J.; Pino-del-Carpio, A.; Ortega, H.; Miranda, R. Fish Ecology of the Alto Madre de Dios River Basin (Peru): Notes on Electrofishing Surveys, Elevation, Palm Swamp and Headwater Fishes. *Water* **2021**, *13*, 1038. https://doi.org/10.3390/ w13081038

Academic Editor: José Luis Sánchez-Lizaso

Received: 8 February 2021 Accepted: 7 April 2021 Published: 9 April 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

The Tropical Andes is regarded as the richest of the 25 recognized global biodiversity "hotspots". It includes Andean ecosystems above 500 m a.s.l., extending from Chile and Argentina, through Bolivia, Peru, Ecuador, to Colombia and Venezuela. This hotspot supports an estimated 45,000 plant and 3400 vertebrate species (excluding fishes), which represents about 15% and 12% of all globally known species, respectively, being nearly half of them endemic to the area [7].

Peru is home to 1064 fish species [8], more than the 7% of all the globally known freshwater species. Most of them (more than 800) are found in the Amazonian Basin. Only during the first decade of the XXI century, 155 new species were named in Peru and the experts estimate the total number of Peruvian freshwater fishes at approximately 1200 species [8]. However, as seen before, there have been few ecological surveys focusing on fish and the majority point out the uneven level of knowledge for this group of vertebrates [9,10], with some taxa itemized at the species level, whereas others routinely are catalogued at family level, order or even phylum [4].

Reviewing research on the Department of Madre de Dios where our study was carried out (Figure 1), Pitman et al. [11] reported that all the scientific studies generated for the department found that only 2.8% of the analyzed manuscripts focus on fish or hydrobiology. Only lichens received less attention than fish. Other research works regarding plants or mammals comprise 21.3% and 16.6% of the total scientific literature, respectively.

Streams of the Tropical Andes are also ecologically important as the headwaters of the megadiverse lowland river systems in South America [12]. They are responsible of delivering major loads of inorganic sediment and organic carbon to lowlands [13] and play a key role in the ecological processes along the Andes-to-Amazon fluvial continuum [14]. Furthermore, the Andean flank of the Amazon hosts the highest biodiversity rates and has been least affected by historical climate variability and land use [15].

However, the Andean-Amazonian piedmont is a rapidly changing landscape, part of the "arc of deforestation" [16], caused foremost by the expansion of cattle and soybean production [17]. The recent growth of human populations, the exploitation of natural resources and the proliferation of hydroelectric dams are leading to extensive reductions in habitats and subsequent impacts on rivers [18–20]. Fortunately, many opportunities for protecting these habitats yet exist, particularly in Peru, where entire river systems are still relatively intact and where there are few large dams and other major structural changes to river channels [21].

Our study area, the Alto Madre de Dios River Basin, in the south west of Peru, is an almost pristine basin. It is located in the Andean-Amazonian piedmont, in the transition zone of the Manu Biosphere Reserve, bordered on the northwest by the Manu National Park, and on the southeast by the Amarakaeri Communal Reserve, two important protected areas of the Peruvian Amazon. This region has long been known to tropical biologists as a region high in species diversity, as well as some of the world's largest expanses of pristine tropical forest [22].

Given the pessimistic predictions for the sustainability and conservation of the Andean biodiversity due to environmental alterations [23,24], studies on the relationships among biotic and abiotic factors and the abundance and distribution of Andean fish are critical to document the primary characteristics of the original communities and thereby contribute to the delimitation of appropriate conservation areas and/or to recovery strategies.

One of the most frequent variables used for studying ecology and biodiversity distribution patterns is elevation. Ecologist all around the globe have demonstrated the strong correlation between altitude and changes in community composition, for plants [25], insects [26], amphibians [27], birds [28], and other organisms. Elevation is also commonly used for studying freshwater biodiversity distribution patterns along the watersheds [29], and together with the distance to the mouth or the distance to the source, they are among the most repeated variables for analyzing fish distribution patterns [10,30]. Nevertheless, the use of those geographical variables can be problematic. We aspire to discuss it and evaluate the use of slope as an alternative environmental variable.

**Figure 1.** Sampling sites in the Alto Madre de Dios River, Peru (white circles).

In the present study we examine the freshwater ecology for the Alto Madre de Dios River focusing on its ichthyofauna and evaluate the environmental integrity of the studied ecosystems. Our specific objectives are to (1) describe spatial variation of fish assemblage of an unstudied Andean-Amazonian stream, (2) to identify patterns of association between fish assemblages and habitat variables, and to (3) discuss the use of elevation for ecological and fish distribution analysis.

#### **2. Materials and Methods**

#### *2.1. Study Area*

The Manu National Park has been considered one of the world's most important tropical protected areas since its creation in 1973 (Shepard et al., 2010). Located in the southern Peruvian Amazon rainforest constitutes the core of the Manu Biosphere Reserve

and an IUCN World Heritage Site [31]. The southern buffer zone of Manu Biosphere Reserve includes the Alto Madre de Dios basin (11◦00′–13◦30′ S, 73◦30′–68◦30′ W) (Figure 1). The river flows, south to north, for 275 km through the rainforest of Cusco and Madre de Dios Departments, draining an area of approximately 1600 km<sup>2</sup> . The altitude in the basin varies from up to 3500 to 300 m a.s.l. in the Manu River junction, spanning five Andean vegetation zones: puna (4500–3500 m), upper cloud forest (3500–2500 m), lower cloud forest (2500–1000 m), piedmont (1000–400 m) and lowlands (400–50 m) [32]. Our highest sampling site was located at 2411 m a.s.l. while to lowest was at 398 m a.s.l., 80 kms downstream. Rivers flow through deep and narrow valleys and steep slopes from the source to around 700 m a.s.l., where the valleys open to wide and flat lowland floodplains. Flow regime is highly responsive to rainfall and presents the greatest discharge period from November to April, decreasing progressively in the dry season (from May to October). The rivers remain turbid through the year, with highest sediment loads during the rainy season.

Human population density in the Alto Madre de Dios valley is low, with scattered settlements that are under the administration of the village of Pilcopata in the District of Kosñipata (pop. 4790 in 2007, according to the Statistical National Institute of the Peruvian Government), Department of Cusco.

Nowadays, most of the land is still covered by primary Amazonian forest, although some areas have been deforested and are used for cattle raising. Tourism facilities—lodges and a network of forest trails—are used by a relatively low number of tourists in comparison with other lodges in Madre de Dios area [22].

#### *2.2. Field Sampling and Analysis*

Our survey was conducted on twenty-two sampling sites in June 2012, during the dry season (Figure 1). The following environmental variables were recorded at each site using a multiparametric probe (Hanna Instrument, HI 98129 Combo Waterproof, Woonsocket, RI, USA): conductivity (µS/cm), water temperature (◦C), and pH. Characterization of habitat structure was done using transects according to Armantrout (1998), and included depth (m), width (m), water velocity (m·s −1 ), percent tree canopy shading and dominant substrate categorized as fines (<2 mm), gravels (~2–64 mm), pebbles (~64–256 mm), boulders (>256 mm), or bedrock and concrete. Additionally, two habitat quality indices were measured: Qualitative Habitat Evaluation Index—QHEI (Rankin, 1989), and Andean adapted version of the riparian forest quality index QBR (Acosta et al., 2009) (Table 1). QHEI jointly considers different habitat parameters, such as bottom substrate and embeddedness, instream structure, velocity and depth regime, canopy cover, channel alteration and pool/riffle or run/bend ratios. QBR index includes aspects of the riparian forest such as total riparian vegetation cover, cover structure, cover quality and channel alterations.

Fish sampling was carried out in wadeable stream stretches (<1 m of height) by electrofishing surveys, using a backpack electrofishing gear (Hans Grassl model IG200/2D, 300–600 V, 0.2–2 A). Surveys was conducted following a single-run depletion methodology and estimating fish abundance based on catch per unit effort (CPUE) (Meador, McIntyre & Pollock, 2003). Collected fish were anesthetized and subsequently counted, measured to the nearest 0.1 cm total length (TL), weighed with a digital scale to an accuracy of 0.05 g and released after the survey, except for some voucher specimens kept to confirm identification.

Voucher specimens were deposited in the fish collection of the Natural History Museum of National University of San Marcos (Lima, Peru). In the laboratory, fish were preserved in alcohol (75%) and identified by Ana María Cortijo, Jessica Espino and Hernán Ortega, members of the Department of Ichthyology of Museum. Scientific names were validated according to W. N. Eschmeyer's Catalog of Fishes [33].


**Table 1.** Sampling sites and environmental variables in Alto Madre de Dios River, Peru.

Alt: Altitude (m), Ta: Air temperature (◦C), Tw: Water temperature (◦C), Cd: Water conductivity (µS·cm−<sup>1</sup> ), Wh: Mean width (m), Dh: Mean depth (cm), Vc: mean water velocity (m·s −1 ), QBR: riparian forest quality index and QHEI: qualitative habitat evaluation index.

#### *2.3. Data Analysis*

From fish community compositional data, richness (Margalef's index R = (S − 1)/ln N), and diversity (Shannon–Wiener index H' = −∑pi log2pi, and Simpson's index D = ∑pi<sup>2</sup> ) measures were calculated, where pi is the proportion of species "i" at a given site, N is the total number of collected specimens, and S is the number of species [34].

First, polynomial regressions were set among the mentioned indices and elevation, distance to the mouth or slope. We wanted to describe and compare patterns of diversity considering these three variables related to location along the basin.

Second, several multiparametric statistical approaches were used to establish the main spatial patterns in the fish community composition [35]. To detect patterns among fish communities, we used a permutation-based test with a nonparametric one-way analysis of similarity (ANOSIM) using a Bray–Curtis similarity index based on abundance data [36,37]. The ANOSIM statistic compares the mean of ranked dissimilarities among groups to the mean of ranked dissimilarities within groups. An R-value close to 1 suggests dissimilarity among groups while an R value close to 0 suggests an even distribution of high and low ranks within and among groups. Post-hoc tests with Bonferroni correction in *p*-values (which were multiplied by the number of comparisons) are done. This correction is very conservative (produces large *p*-values). The sequential Bonferroni option does not output corrected *p*-values, but significance is decided based on step-down sequential Bonferroni, which is slightly more powerful than simple Bonferroni. If ANOSIM revealed a statistically significant result, the relative contribution of each species to group dissimilarities was quantified using a similarity percentage analysis (SIMPER), with a cut-off criterion of 90% (Bray–Curtis similarity index), to identify subsets of the most important species [36]. SIMPER calculates the average Bray–Curtis dissimilarity among all pairs of inter-group samples, expressed in terms of the average contribution from each species. Previously, we created three categorical variables (type of mass of water (river vs. stream), elevation (upstream-downstream 700 m), and stream order). Fish assemblages were compared considering these three categories.

For the choice of linear or unimodal analysis, a preliminary DCA (Detrended Correspondence Analysis) was performed [38]. This analysis evaluates the species turnover (the length of gradients) through the first DCA axis. The criterion for choosing linear vs. unimodal ordinations models is to obtain a SD < 3 [39]. Our results showed a SD > 3

because of the large number of species and their frequency of occurrence. To examine relationships between community composition and several environmental variables a Canonical Correspondence Analysis (CCA, Unimodal response; length of gradient SD > 3) was used through the program CANOCO 4.5 [39,40] based on DCA results. To reduce the number of graphics and considering the similar patterns shown, altitude was selected over distance to mouth (r = 0.964, *p*-value < 0.01) as representant of the geographical variables, to compare it with slope. Two parallel CCA were carried out with altitude or slope as key variables related to location along the headwater-downstream gradient. This direct gradient analysis technique provides ordination axes linearly related to the explanatory variables. The main result is a scatterplot ordination diagram displaying the pattern of fish assemblage variation along the environmental variables shown as vectors. Vector direction and length indicate the relative magnitude and influence of a particular variable on fish assemblages. The significance of the analyses was assessed by a permutation test with 1000 random permutations. Habitat structure and water quality variables were also included in the analysis. To improve linearity, environmental variables were log transformed. Proportional data and abundance fish data were transformed (arcsine and root transformed, respectively). Peebles was removed to avoid a high variance inflation factor (VIF) [41].

All multiparametric analysis were done for species that were captured in more than two sites (i.e., 10% occurrence) and were performed using the R project software version 3.2.3 [42] with the package "vegan" version 2.3–3 [43] except in the case of CCA which had been developed in CANOCO 4.56 [40].

Finally, fish species have been classified according to their trophic specialization [6,44,45], with the aim to analyze the distribution of these trophic groups in the elevation gradient.

#### **3. Results**

A total of 1934 specimens were collected, and 78 fish taxa were identified belonging to 43 genera and 14 families (Dataset S1). Twenty-seven species were undetermined, ten were identified as species *affinis*, and 41 species were correctly identified. Characids were the most diverse family with 43% of the species, followed by loricarids (14%), trichomycterids (8%), astroblepids, cichlids and heptapterids (7% each one) and crenuchids (3%). The remaining fish belonged to ten families with only one represented species.

Regarding diversity indices, values presented a marked altitudinal pattern. Shannon– Wiener and Margalef's indices showed negative correlations with altitude, distance to the mouth and slope, whereas Simpson's index showed positive correlation (Figure 2). Site 13 presented the highest diversity and hosted alone 28% of the total fish species (22 species). On the other hand, highest sites, 21 and 20, only had two species (*Astroblepus* sp. and *Trichomycterus* sp.). Finally, site 15 significantly different from the rest of the sampling points. It was a swamp ecosystem isolated from the main river and due to its unique environmental characteristics, it was discarded for subsequent analysis.

Results of one-way ANOSIM showed significant differences in community composition as indicated the high R values (global R: 0.786, *p* < 0.001) with the cut-off point at 700 m a.s.l. This makes fish composition upstream and downstream 700 m a.s.l. well distinguishable. Mass of water and stream order showed not significant differences (global R: 0.04 and R: 0.22, respectively; *p* > 0.05). The SIMPER procedure indicated that using three species was possible to explain more than 38% of variation among elevation categories. *Astroblepus*, *Trichomycterus* and *Knodus* were the most important species explaining the variation in community composition (Table 2).

**Figure 2.** Estimates of the fish community diversity indices along the Alto Madre de Dios River, regarding to elevation, distance to the mouth and slope of sampling points. \*\*\* significative coefficient of determination (R<sup>2</sup> ).



The relationship between fish and environmental variables are shown in Figure 3 and Tables 3 and 4. The importance of environmental variables is indicated by the marginal effect values (λA): for both analysis conductivity (0.22), boulders (0.25), water velocity (0.25) and water temperature (0.38) were most significant. The variables with the highest marginal effect were slope (0.44) for the first CCA (Table 3a) and elevation (0.59) for the second CCA (Table 3b). λ

**Figure 3.** Triplot of results of canonical correspondence analysis carried out with slope (**a**) or elevation (**b**) as key variables related to location, showing site scores (circles), the environmental variables (vectors) and fish abundances (triangles) on the first two canonical axes. The code for site scores and environmental variables refers to sampling sites according to Table 1.

**Table 3.** Results of canonical correspondence analyses (CCA) carried out with slope (**a**) or elevation (**b**) as key variables related to location along the headwater-downstream gradient, showing canonical coefficients and weighted intraset correlation coefficients of explanatory variables with the first two axes of the CCA. Importance of environmental variables using marginal effects are shown λA.



**Table 4.** Summary statistics table for CCA ordination presented, with slope (**a**) or elevation (**b**) as key variables.

For (**a**) Significance of the axis by the Monte Carlo permutation test is given by F = 3.10 (*p* < 0.05). All canonical axes were significant. Values in bold indicate significant difference at *p* < 0.05. For (**b**) Significance of the axis by the Monte Carlo permutation test is given by F = 3.23 (*p* < 0.05). All canonical axes were significant. Values in bold indicate significant difference at *p* < 0.05.

Outcomes were equivalent using slope and elevation as main variables, therefore, only results for CCA with slope are described next. The inertia in the assemblage composition in the studied sites was 0.579 for axis 1, 0.264 for axis 2, 0.167 for axis 3 and 0.126 for axis 4. The CCA ordination revealed strong relationships between species abundances and measured environmental variables explaining 72.6% of species distribution. The first canonical axis (axis 1) accounted for 38.4% of the variation in the data set, the second axis (axis 2) accounted for 17.5% of the variation in the data set. An unrestricted Monte Carlo permutation test indicated that all canonical axes were significant (*p* < 0.05).

First Canonical Correspondence Analysis CCA1 eigenvalue accounts 0.579 and it is composed by slope, boulders and water velocity on the positive side and water temperature on the opposite side (Figure 3a). First Canonical Correspondence Analysis was interpreted as a longitudinal gradient from high to lowlands with sites above 700 m a.s.l. being distributed on the right area of the graph (except for site 12, slightly right from the axis) and sites below that altitude spread in the left area. Second Canonical Correspondence Analysis CCA2 (eigenvalue = 0.264) is dominated by conductivity on the positive side and pH and water temperature on the negative side. Second Canonical Correspondence Analysis was interpreted as hydrochemical parameters (Table 3a; Figure 3a).

On the right area of the graph (Figure 3a) a first species group composed by *Trichomycterus* (Figure 4) and *Astroblepus* genera (Figure 5) was separated from the remaining and it was positively related to headwaters showing distinctive features: high velocities of water, big boulders and lower temperatures. *Bryconamericus* genera species were also related to these headwater streams, although they do not appear so high in the altitudinal gradient. A second group of fish represented by *Serrapinnus*, *Prodontocharax*, *Astyanax*, *Astyanacinus* and *Knodus* genera, located on the top-left area of the graph, was positively related to still waters with low velocities, higher conductivities and fine substrates (mainly sands). A third cluster, located on the top-left area of the graph, included *Rineloricaria*, *Chaetostoma*, *Aphyocharax*, *Hemibrycon*, *Ancistrus*, *Creagrutus* and *Crossoloricaria*. They were related to open places with highest water temperatures and wide riverbeds. The rest of the genera were distributed between these two groups along the first axis on the left of the graph, including *Hoplias*, *Rhamdia*, *Chasmocranus* and *Characidium*.

Attending to fish distribution and trophic specialization [6] along the altitudinal gradient (Figure 6), no fish were found above 2200 m a.s.l. *Astroblepus* and *Trichomycterus* were the only genus found on highest reaches (above 1400 m a.s.l.), feeding exclusively on invertebrates. Even though they appear tightly related to headwaters, they were found all along the basin with occasional and scarce occurrence also in lowland streams. At 1400 m a.s.l. three new genera appeared: one invertivorous *Bryconamericus*, and the

first two herbivore-detritivores *Chaetostoma* and *Ancistrus* genera. Next invertivorous *Characidium* genus was found below 1100 m. Above the 700 m other three invertivorous genera were found: *Rhamdia*, *Creagrutus* and *Chasmocranus*. The rest of the fish taxa were found below 622 m, representing most of the diversity. The first piscivorous species, *Hoplias malabaricus* and *Crenicichla semicincta* were found at this altitude.

**Figure 4.** Species and morphotypes of genus *Trichomycterus* collected in the upper Madre de Dios River. (**A**,**B**) *Trichomycterus* sp.3 collected on Américo stream (21Q), (**C**) *Trichomycterus* sp.2 collected on Unión River (20R), (**D**) *Trichomycterus* sp.2 collected on San Pedro River (19R), (**E**) *Trichomycterus* sp.3 collected on Quitacalzon stream (17Q), (**F**,**G**) *Trichomycterus* sp.5 collected on Quitacalzon stream (17Q), (**H**) *Trichomycterus* sp.4 collected on Salvación River (12R), (**I**) *Trichomycterus* sp.6 collected on Kosñipata River (16R), and (**J**) *Trichomycterus* sp.1 collected on Queros River (13R).

**Figure 5.** Species and morphotypes of genus *Astroblepus* collected in the upper Madre de Dios River. (**A**) *Astroblepus* sp.2 collected on Américo stream (21Q), (**B**) *Astroblepus* sp.1 collected on Unión River (20R), (**C**) Reddish specimen of *Astroblepus* sp.1 collected on Unión River (20R), (**D**) *Astroblepus* sp.1 collected on San Pedro River (19R), (**E**) *Astroblepus mancoi* collected on San Pedro River (19R), (**F**) *Astroblepus* sp.2 collected on San Pedro River (19R), (**G**) *Astroblepus* sp.1 collected on Quitacalzon stream (17Q), (**H**) *Astroblepus aff. longifilis* collected on Kosñipata River (16R), (**I**) *Astroblepus mancoi* collected on Queros River (13R), and (**J**) *Astroblepus aff. trifasciatus* collected on Salvación River (12R).

**Figure 6.** Elevational ranges and trophic specializations of fish species occurring at elevations >400 m a.s.l. in tributary and main-channel sites within the Alto Madre de Dios watershed, south-eastern Peru.

#### **4. Discussion**

A gradual increase in species richness and diversity is expected along longitudinal gradients in lotic systems, associated with changes in resource availability, channel morphology, flow regime and substrate type [46,47]. Addition of species is usually related to an increase of habitats motivated for the structural diversification of the environment downstream [48]. Our study confirms this pattern (Figure 2), with the only exception of one sampling point 15, that does not fit the trend due to its low diversity values, explained by its peculiar features as discussed below.

All the studied environmental variables were correspondent with the values reported by other works for natural and unaltered streams of this territory [6,30,49]. Quality indices of riparian and fluvial habitat (QBR and QHEI) got very high scores in all the sampling points, highlighting the good environmental quality, with some remarkable exceptions (Table 1). Riparian forest (and adjacent jungle) on the right bank of the sampling point 13, in the Queros River, was lacking due to deforestation for extensive cattle raising.

Besides, sampling point 15, located at 622 m a.s.l., showed significant differences both in environmental and diversity features, as already mentioned. This site belongs to a special type of aquatic ecosystem of Amazon forest known as *aguajal*. They are back swamp forests, defined as forest on low-lying areas outside of streams courses, only connected to them during high flood season. They are usually dominated by palms (*Mauritia flexuosa*), although other tree species like figs (*Ficus* species) can be abundant as well [50]. They also tend to be clear and acidic, in contrast to the higher turbidity and circumneutral pH of the streams around [51,52]. This *aguajal* was confined by extensive cattle pastures surrounding it and was used as drinking reservoir for cattle, showing a remarkable eutrophication. Sampling point 15 presented the described characteristics

16

and showed low habitat quality indices (Table 1) and low diversity of fishes (Figure 2), with only three extant species: *Moenkhausia oligolepis* (70 specimens), *Crenicichla semicincta* (three specimens) and *Hoplias malabaricus* (one specimen). However, diversity might increase in the rainy season, when this habitat is connected to the river and other species present in the river could occupy this place. Species of genera *Astroblepus*, *Trichomycterus*, *Bryconamericus*, *Ceratobranchia*, *Creagutus* and *Rhamdia* are present in the nearest sampling points (Sites 14 and 16).

Because of its special and no-comparable characteristics, this peculiar sampling point has been excluded for the general comparative analysis. Although the importance of the *aguajales* has been widely recognized because of their ecological and social relevance [53,54], no fish species records are available on the literature. Our fish and ecological data throw some light on these poorly studied freshwater habitats.

When analyzing richness, diversity and dominance in relation with position from headwaters-downstream indicated by elevation, distance to mouth and slope, results were solid and similar for the three variables (Figure 2). The Canonical Correspondence Analyses through the marginal effect values (λA) highlighted principal role of elevation (0.59) or slope (0.44) for explaining fish distribution along the basin (Table 3). The resulting graphics were also analogous when using both variables (Figure 3). Elevation and distance to mouth are widely used for multivariate analysis [55,56]. Nevertheless, they do not give environmental information, they are geographical variables and indicate spatial position. Although they show strong correlation with ecologic changes, their use for ecological analysis together with environmental variables may be problematic. Instead, slope is a purely environmental variable that measures a geophysical characteristic of the site. Furthermore, it is strongly related to position along the basin but is independent from other variables, something that avoids "noise" on multivariate analyses. After validating its robustness for explaining fish distribution as well as elevation, we recommend the use of slope as alternative variable to elevation or distances to mouth/source.

Fish community composition along the basin presented two distinct groups with a clear cut-off point occurring at 700 m a.s.l as indicated by the ANOSIM, separating mountainous fish from piedmont communities. The boundary between both zones is marked by geomorphological changes on the basin, when it shifts from the steep mountainous streams flowing through narrow valleys, to flat and wide floodplains where river channels widen. As pointed out by SIMPER procedure *Astroblepus* and *Trichomycterus* are the most distinctive species from the mountainous streams, while *Knodus* was the most important species from lowlands explaining the variation in community composition (Table 2).

Fish abundance and distribution in response to environmental variables was represented using the CCA analysis and showed similar results using slope or elevation (Figure 3). The observed distribution of species along the longitudinal gradient of the basin was comparable to other fish assemblages found in rivers with similar characteristics in adjacent areas [10,30,49]. This biotic zonation corresponds to discontinuities in river geomorphology or abiotic conditions and are usually related to smooth transitions of abiotic factors contributing to nested patterns of assemblage composition along the altitudinal gradient [57]. The graph highlights this zonation, distributing headwater sites and their fish assemblages on the right of the diagram, related to fast running waters, steep slope, boulders and low water temperatures, opposed to middle and lowland streams on the left of the graph related to higher water temperatures, wider streams, low velocities, higher conductivity and fine substrates.

Genera *Astroblepus* and *Trichomycterus* co-occur in high reaches, being the unique species present on the sites above 1400 m a.s.l. These genera are adapted to headwaters, related to rocky substrates and cold, clean and well oxygenated water (Figure 3). They are benthonic species without scales and a powerful sucker mouth or opercular odontodes [58]. Nevertheless, they occasionally occur in lower areas, although their distribution is usually limited to elevations greater than 400 m.a.s.l. (Lujan et al., 2013). *Bryconamericus*, a rheophile genus, is the next genus joining the headwater assemblage at 1400 m a.s.l. (Figure 6). They prefer areas of moderate to strong current and present even in the torrential flows, occupying intermediate places between mountain upstream and jungle downstream [30,59]. We also found some *Chaetostoma* and *Ancistrus* fishes at these reaches, although they appeared closely related with lower middle section streams (Figure 3).

We found most of the species related to these middle-low reaches, distributed along the left area of the CCA (Figure 3): habitats with fine substrata, very slow water velocities, mild slope and more conductivity, related with *Serrapinus*, *Prodontocharax*, *Astyanancistrus*, *Astyanas*, *Knodus* and *Moenkhausia*, on the top-left area of the diagram (Figure 3b) [60]; other lotic sites presenting the widest habitats with highest temperature and higher pH, were distributed on the bottom left of the diagram, related with *Aphyocharax* and *Hemibrycon* genera characids and loricarids like *Rineloricaria*, *Chaetostoma* and *Ancistrus* [47,59,61].

We also observed a remarkable zonation related to trophic niches (Figure 6). Headwaters were dominated exclusively by invertivorous *Astroblepus* (Figure 5) and *Trichomycterus* (Figure 4) fishes due to the scarcity of other food resources in these clean waters [9,58]. Although the first herbivore-detritivore *Chaetostoma* and *Ancistrus* individuals were found starting at 1400 m a.s.l., they were more abundant below 1000 m a.s.l., once the river carries enough organic matter coming from the surrounding forest offering a new trophic niche [9,49]. The first piscivorous species, *Hoplias malabaricus* and *Crenicichla semicincta*, were distributed around 600 m a.s.l. and below, first found at site 15, the *aguajal*, where the *Moenkhausia oligolepis* community was very abundant providing enough biomass to feed the predators. This distribution pattern is according with the observations of Lujan et al. [6].

According to some ecological studies and inventories carried out in this area [8,62], more than 130 species of freshwater fishes have been reported for the Alto Madre de Dios Basin. In the present study, only 78 species were collected, due to two main reasons: (1) the highest biodiversity is found on the lowest reaches of the basin and our lowest sampling was at 398 m a.s.l.; (2) electrofishing technique has some limitations on these ecosystems.

Regarding electrofishing, only wadeable stretches were sampled, whereas larger courses or deep stretches were avoided. This limitation directed our sampling efforts to smaller rivers and tributaries where the electrofisher gained efficiency [63]. Although this represents a significant impediment for carrying out a complete biological survey, also brings up new opportunities. Most of the ichthyofaunal studies undertaken in Amazonia have focused on the large rivers and commercially valuable species, therefore small and noncommercial fishes and secondary streams have been usually overlooked [64]. Guided by our limitations, part of our surveying efforts was concentrated on this poorly studied ecosystems and species.

Besides the restrictions for choosing samplings sites, fish resistance to electrofishing was significant. This resistance was favored by low water conductivity and temperature, high velocities, shelter's abundance or low visibility [65]. Furthermore, capture efficiency depended on the mobility of species: little benthic fish were collected easily, in contrast to larger, strong-swimming species that escaped the electrofishers range. However, according to other authors [65,66] electrofishing is the best sampling method when your objectives are to estimate and quantify freshwater fish populations in streams and wadable rivers and to correlate these abundances with environmental features, habitat characteristics, hydrochemical parameters or other ecological measures. Besides, although electrofishing surveys have been widely achieved on the world, they have been scarce in remote places like the Alto Madre de Dios Basin due to the more complex logistics.

If we match our results with the survey carried out with seine nets by Araújo-Flores in 2013 [62] we find remarkable differences. Comparing the total 44 species reported by Araújo-Flores [62] with our 78 species only 17 of them were captured by both studies. Nevertheless, survey of Araújo-Flores focused on two rivers and its tributaries (Pilcopata and Piñi-Piñi Rivers), distributing ten sampling sites in a smaller area with a limited altitudinal range (500–600 m a.s.l.). If we compare our data for the three sites coinciding with the survey of Araújo-Flores (sites 7, 8 and 9), although our sampling effort was lower (3 vs. 10 sites) and our captured diversity smaller (26 vs. 44 species), we collected 15 species

missing in the survey of Araújo-Flores [62]. Therefore, although electrofishing is not as effective in tropical streams as it is for temperate streams, it may be more effective for capturing some species that seem to be underestimated by other techniques. Consequently, as we focused on understudied small rivers and streams, catching poorly known small fish, using an uncommon technique for tropical freshwaters, our study presents new and relevant taxonomic and ecological information, providing data for some fish never captured before by previous surveys in the area.

Although our results highlight the good conservation status of the Alto Madre de Dios Basin, the territory endures severe threats: logging [22,31], gold mining [67], climate change [15,23], fossil fuel extraction [68], and hydropower projects [20,23]. The development and implementation of management plans is crucial for anticipating and mitigating future impacts. Nevertheless, the principal threat for this peculiar area, with high endemic biodiversity and very good conservation status, is the lack of knowledge regarding its fauna and flora. Studies of the fish fauna are critical to document the primary characteristics of the original communities and thereby contribute to the delimitation of appropriate conservation areas and/or to recovery strategies for degraded streams [69]. Therefore, Peruvian freshwater fish faunal inventory (including the Alto Madre de Dios River Basin) is a priority [8,69]. There are many remote areas, with poor accessibility, where knowledge of freshwater fish fauna is negligible and for most fish taxa basic taxonomic work is still required, not only for this area, but for all the Amazon and adjacent basins [8]. Besides, there is even less information, in some cases null, on the ecology of many species. This knowledge gap highlights the necessity of basic taxonomic works and the creation of field guides providing new research projects an essential tool [70]. Fortunately, there are some remarkable guides for the Madre de Dios Basin [52,61] and adjacent areas [71,72] that offer inestimable material about freshwater fishes in this region, although, the information in these guides is incomplete for many species. In this sense, the lack of basic knowledge may hamper the development of community-level analyses [3,73]. Although fish diversity for the hotspot is unclear yet, some papers estimate fish richness for the Andean region more than 600 species [69], with more species found at low elevations compared to higher reaches [5]. Around 2700 species have been recognized for the hotspot inside the Amazon Basin territory [74]. In contrast to richness, endemism tends to increase at higher elevations and particularly concentrates in isolated patches of habitat such as valleys and mountain tops [7]. An IUCN report evaluated fish fauna conservation status for the Tropical Andes [75] considering 666 endemic species: 13 spp. critically endangered; 33 spp. vulnerable; 36 spp. near threatened; 341 spp. least concern; 215 spp. data deficient. One of the main conclusions points out the significant information gap: 32% of the evaluated fish were poorly known.

Concerning this taxonomic constraint, freshwater fishes of high headwaters demand special attention. All of them are Andean species and live on high altitudes, areas where human settlements and their subsequent impact has a longer and more intense presence, compared with Amazonian streams [23]. We found five different species of *Astroblepus* (Figure 5), two of them undetermined, five species of *Bryconamericus*, and six species of *Trichomycterus* all undetermined (Figure 4). Astroblepids and trichomycterids are typically restricted in their geographical distribution and endemic to single or adjacent river systems of the Andes, and their taxonomy is poorly known and in constant revision [76–78]. Advances on the taxonomic and ecological knowledge of these high mountain species, related to tropical montane cloud forests, are mandatory for the design of conservation and management plans in the area.

According to Ortega et al. [8], there is not an official national Peruvian red list of freshwater fishes because of this lack of knowledge (despite several attempts and proposals). Although conservation lists have their limitations and critics, they represent an essential tool required for protecting biodiversity [79]. Therefore, it is imperative to continue with the study of freshwater fish species in Peru with the aim of improving management actions and conservation plans.

In the light of this scenario where no Andean-Amazon Basin will remain untouched, the Alto Madre de Dios River Basin still preserves healthy ecosystems, with mild human impacts affecting some stretches, but showing a good environmental quality overall. Therefore, this makes the basin a perfect candidate for being preserved and considered as a reference basin for these seriously endangered ecosystems.

**Author Contributions:** Conceptualization, R.M. and I.T.; methodology, R.M., I.T. and A.R.-M.; formal analysis, A.R.-M. and I.T.; investigation, R.M., I.T., A.P.-d.-C. and J.A.-F.; data curation, I.T. and R.M.; writing—original draft preparation, I.T. and R.M.; writing—review and editing, R.M., I.T., A.P.-d.-C., A.R.-M., J.A.-F. and H.O.; visualization, J.A.-F. and I.T.; supervision, A.P.-d.-C. and R.M.; project administration, R.M. and A.P.-d.-C.; funding acquisition, R.M. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by Government of Spain, Ministry of Foreign Affairs and Cooperation, AECID (Code A1/040396/11) and Asociación de Amigos Universidad de Navarra.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available due to authors are preparing a dataset of these and another fish data from the Andean rivers that will be published in the next months.

**Acknowledgments:** Invaluable field assistance and friendship was provided by Américo Quispe. We are grateful for the unreserved cooperation of Hugo Pepper, who provided logistic and data support. Robin Van Loon helps us on the English revision. We are grateful to Miles Silman for their useful comments. We thank the members of the Department of Ichthyology of MUSM for their help and assistance. The Asociación para la Conservación de la Cuenca Amazónica (ACCA), kindly provided valuable information, collaboration and lodging during our fieldwork. We also wish to thank Ronald Mendoza for helping to prepare the map figure.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

#### **References**


### *Article* **Variability in Population Traits of a Sentinel Iberian Fish in a Highly Modified Mediterranean-Type River**

**Ana Sánchez-Pérez 1, \* , Francisco J. Oliva-Paterna 1 , Fátima Amat-Trigo <sup>2</sup> and Mar Torralva 1**


**Abstract:** Human pressures on water resources have been suggested as a driver of biological traits that induce changes in native fish populations. This study highlighted the interplay between environmental stress factors, mostly related to flow regulation, and the longitudinal river gradient in biological traits such as the growth, size structure and somatic condition of a sentinel fish, *Luciobarbus sclateri.* We found an increase in size-related metrics and somatic condition at population levels associated with downstream reaches, although fragmentation and habitat alteration, flow regime alteration and the abundance of non-native fish were also significantly involved in their variability. Age-related parameters and growth were only explained by flow regime alterations and the abundance of non-native fish species. The high plasticity observed in *L. sclateri* population traits suggests that this is a key factor in the species adaptability to resist in a strongly altered Mediterranean river basin. However, the interplay of multiple stressors plays an important role in fish population dynamics and could induce complex responses that may be essential for long-term monitoring in sentinel species.

**Keywords:** sentinel species; longitudinal gradient; human impacts; flow regime alteration; nonnative fish; fragmentation; habitat alteration; Mediterranean rivers; Segura River basin

#### **1. Introduction**

Freshwater ecosystems are considered among the most altered as a consequence of the historical pressure of human activities [1,2]. Hydraulic management to take advantage of water resources and the effects of climate change are inducing quantitative and qualitative changes in river systems [3,4]. These changes imply hydro-morphological, chemical and biological alterations which affect the freshwater fauna [2,5]. Hydraulic management is especially intense in Mediterranean regions where water resources are scarce [6]. Rivers in semi-arid regions, such as the Iberian Peninsula, are heavily impacted by the construction of a large number of dams and weirs [7,8].

Mediterranean regions are characterized by marked seasonality and inter-annual variability with severe periods of floods and droughts [9,10]. The native freshwater fauna is adapted to such natural variability and displays great resistance and resilience [11–13]; however, it is considered especially sensitive to human impacts [14,15]. Human pressures are particularly severe in Mediterranean regions and they coincide with high natural variability, causing severe alterations to fluvial ecosystems [8,16,17]. Despite the high adaptability of freshwater fauna, the expected increase in human impacts under future scenarios of global climate change could increase its vulnerability to such pressure, especially in Mediterranean regions [11,18,19].

The flow regime is considered one of the main driving forces of freshwater ecosystems, determining the structure and ecological dynamic of rivers [19,20]. In the Iberian Peninsula, the alteration of the natural flow regime by dam regulation is one of the most important

**Citation:** Sánchez-Pérez, A.; Oliva-Paterna, F.J.; Amat-Trigo, F.; Torralva, M. Variability in Population Traits of a Sentinel Iberian Fish in a Highly Modified Mediterranean-Type River. *Water* **2021**, *13*, 747. https:// doi.org/10.3390/w13060747

Academic Editor: Heiko L. Schoenfuss

Received: 9 February 2021 Accepted: 3 March 2021 Published: 10 March 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

stress factors that negatively affects the native fish fauna [21–23]. The effects of flow regime alteration have been widely documented in Mediterranean fish populations [24–27]. In addition, flow management infrastructures cause loss of connectivity and habitat alterations related to the fragmentation process (e.g., increase in lentic habitats, changes in water quality), which could facilitate the establishment and spread of non-native fish species, altering the composition of the community [28,29]. However, the effects of these stress factors have been poorly studied in Mediterranean rivers [30–32].

The Segura River basin is located in the southeast of the Iberian Peninsula and is characterized by a marked environmental variability and displays a wide variety of human impacts along its longitudinal gradient [33,34]. Furthermore, this basin shows a welldocumented range of impacts on the natural flow regime [35,36] and is considered one of the most regulated Mediterranean river systems [37]. Therefore, the Segura River offers an opportunity to study the effect of multiple human-induced stressors along an intensively altered basin. The fish assemblage in the Segura River basin is characterized by a low number of species where *Luciobarbus sclateri* (Günther, 1868) appears to be dominant [38]. This native species is an endemic potamodromous fish considered a sentinel species in the southern Iberian Peninsula [12], and its biology and ecology have been well documented [39–41], being the unique native fish widely distributed in the Segura River basin [42]. Therefore, *L. sclateri* populations in the Segura River could be considered a useful tool through which to assess the intra-specific variability along a wide longitudinal gradient strongly affected by environmental alterations mainly related to flow regulation. However, few authors have described the effects of multiple stressors on its populations, and nothing is known about its intra-specific variability along longitudinal gradients [43–45].

The main objective of the present study was to assess the variability of *L. sclateri* population traits in relation to different environmental stressors along the longitudinal gradient of a highly regulated river system. Our hypothesis was that *L. sclateri* would exhibit high phenotypic plasticity that enables populations to survive along the longitudinal gradient of a highly impacted river basin. *L. sclateri* has been evaluated as near threatened (NT) on a regional scale due to the intensification of human pressures which caused a decrease in habitat quality (mainly pollution and flow regime alteration) and an increase in the establishment and spread of several non-native fish species [46]. Furthermore, in recent years, a severe decline in *L. sclateri* populations has been documented in the Segura River basin [38,47]. The use of different biological traits provides ecological insights into how populations respond to multiple stress factors, allowing us to understand how species' traits could predispose species to local extinctions [48] and to establish more successful management and recovery programs [8,49].

#### **2. Materials and Methods**

#### *2.1. Study Area and Sampling Design*

This study was conducted in the Segura River basin, situated in the semi-arid Mediterranean climatic zone in the southeast of the Iberian Peninsula (Figure 1). The river basin drains an area of 18,870 km<sup>2</sup> and is characterized by a strong climatic and altitudinal gradient, and significant annual and inter-annual natural variation in the flow regime [6]. Multiple human activities—primarily related to agriculture, but also to electricity generation and human supply—have developed in the study area [33,34,37]. Irrigation accounts for 90% of the water demand and is considered the main pressure on the water resources. A total of 33 dams (>10 m height and >1 hm<sup>3</sup> of reservoir) and 170 smaller obstacles exist along the longitudinal gradient of the river with a capacity of regulation of approximately 1200 hm<sup>3</sup> . Since 1979, this basin has received an external water transfer from the Tajo River with an average of 350 hm3year−<sup>1</sup> , so the storage capacity increased by around 140% of the natural input (871 hm3year−<sup>1</sup> ) [37,50]. Furthermore, local agricultural practices add an artificial source of pollutant discharge (mainly phosphates and nitrates) into the river [51,52]. As a result, the fluvial and riparian habitats of the Segura River basin have been severely altered [33,53], in addition to strong modifications in the natural flow regime [54].

● **Figure 1.** Study area. Location of the Segura River basin in the southeast of the Iberian Peninsula. Sampling sites are marked (•): TAI (Taibilla River), TUS (Tus River), MU (Mundo River) and SE (Segura River). Names of large reservoirs are between parentheses [].

− We sampled a total of 25 sites in fluvial reaches distributed along upstream–downstream gradients from the upper Segura main stem (SE) to the middle Segura (195 km), from the upper Mundo River (MU) to the Mundo–Segura confluence (51 km) and in two upper tributaries (Tus and Taibilla) (Figure 1). The range in altitude is 112–809 m.a.s.l. in the study area; the water conductivity ranged from 316 to 1303 µs cm−<sup>1</sup> and the range of the mean annual water temperature was 13.9–16.9 ◦C during the study period. The distribution of sampling sites reflects the different hydrological flow regimes present in the study area. Sampling sites placed in areas with the most natural flow regime (e.g., MU01 and SE01; Figure 1) were characterized by a strong seasonal variation, alternating summer droughts and spring/autumn short-time flow peaks (Figure 2a). An impact gradient on the natural flow regime in the study area was described by Amat-Trigo [35] and Amat-Trigo et al. [36]. Impacted areas exhibit a seasonal inversion of the natural flow pattern (high flow levels in spring and summer, low flow levels in autumn and winter) due to the water demand for agricultural practices. Furthermore, impacted areas can be characterized by two extreme flow impacts: reaches downstream of the Cenajo reservoir (sampling sites SE06, SE07 and SE09; Figure 1) showed a high level of contingency and low variability, but also low predictability (Impact 1, Figure 2b), while other reaches (e.g., sampling sites MU09, SE12 and SE13; Figure 1) were characterized by more stable and high levels of base flow throughout the year, high values of temperature and spell peaks, in addition to the inversion in flow seasonality (Impact 2, Figure 2c).

− **Figure 2.** Flow variation (mean daily discharge; m<sup>3</sup> s −1 ) at three representative fluvial sectors in the study area. Repre-sentative flow regimes were measured at three gauging stations: (**a**) Natural flow regime at the upper part of the Mundo River, (**b**) Impact 1 just downstream of the Cenajo reservoir, and (**c**) Impact 2 downstream of the La Mulata dam (see location in Figure 1). Flow discharge data were obtained from the Segura Hydrographic Confederation.

The fish assemblage in the study area is composed of both native and non-native species [38]. Non-native species are dominant (90% of total species richness) and *L. sclateri* is the only widely distributed native species in the study area. The most abundant species are cyprinids: the native *L. sclateri* and the non-native species *Pseudochondrostoma polylepis* (Steindachner, 1864), *Gobio lozanoi* (Doadrio and Madeira, 2004) and *Alburnus alburnus* (Linnaeus, 1758). The non-natives *Cyprinus carpio* (Linnaeus, 1758) and *Lepomis gibbosus* (Linnaeus, 1758) are locally abundant. Furthermore, the natives *Squalius pyrenaicus* (Günther, 1868) and *Salmo trutta* (Linnaeus, 1758), as well as the non-natives *Gambusia holbrooki* Girard 1859, *Oncorhynchus mykiss* (Walbaum, 1792)*, Micropterus salmoides* (Lacépède, 1802), *Sander lucioperca* (Linnaeus, 1758) and *Esox lucius* (Linnaeus, 1758), are present in the study area.

#### *2.2. Environmental Variables*

We described a total of ten environmental variables and gradient descriptors in the study area (Table 1). Water conductivity was measured in situ using a multi-parameter (340i WTW), and ecological status was assessed according to the EU Water Framework Directive, Fluvial Habitat Index (IHF) [55], Riparian Quality Index (RQI) [56] and altitude [57]. The Longitudinal Connectivity Index (ICL) [58] and free reach (length of reach available for free movement) were calculated using databases available online from the official monitoring service of the Segura Hydrographic Confederation (CHS) (https://www.chsegura.es/ chs/cuenca/restauracionderios/obstaculos/visorjs.html; accessed on 12 September 2018). Water temperature and daily river discharge data were also obtained from the CHS online databases with data gathered by gauging stations distributed in the study area (https: //www.chsegura.es/chs/cuenca/redesdecontrol/estadisticashidrologicas/; accessed on 12 September 2018). Mean monthly values of water temperature for 2009 and 2010 were calculated. Mean daily discharge (m<sup>3</sup> s −1 ) over a 16-year period (1994–2010) was used to calculate the mean daily base flow (MDBF) as the total base flow component of the hydrograph divided by the number of recording days, and flow variability as the daily range between Q10% and Q90% discharge divided by the median value. These two flow metrics (MDBF and flow variability) were calculated using time series analysis (TSA) of the River Analysis Package (RAP version 3.0.7) [59].

**Table 1.** Environmental variables and gradient descriptors measured or calculated at sampling sites. Altitude (meters above sea level), ecological status (categorized as: 1 = high; 2 = good; 3 = moderate; 4 = poor), Fluvial Habitat Index (IHF) and Riparian Quality Index (RQI) (%), conductivity (µS cm−<sup>1</sup> ), free reach (km), Longitudinal Connectivity Index (ICL), water temperature (◦C), mean daily base flow (MDBF) (m<sup>3</sup> s −1 ) and flow variability ((Q10% − Q90%)/median).


#### *2.3. Fish Sampling and Population Traits*

Sites were sampled using electrofishing (working voltage between 200 and 350 V, 2–3 A), following the CEN standard protocol [60]. Each sampling site was considered an independent population, taking into account the distance between sampling sites, the presence of non-passable barriers (dams and weirs) and the biological characteristics of *L. sclateri*. Fish were collected in 100-m-long wadable sections blocked by nets that acted as barriers. Fish sampling sessions were carried out in 30–45 min. Sampling was conducted during October–November 2009 to prevent the capture of spawning fish [45] and to avoid variation in body condition due to gonad development [39,43,61]. Fish manipulation was carried out following the European Union Directive 2010/63/UE on the protection of animals used for scientific purposes and it was not necessary to obtain authorization from the research ethics commission. In concordance with administrative permits, a total of 1529 specimens of *L. sclateri* were caught, processed in the field and returned to their habitat. Fork length (FL ± 0.1 cm) and weight (TW ± 0.1 g) were measured. A subsample of scales (611 specimens) was taken and cleaned later in a laboratory to determine the age according to Herrera et al. [40] and Torralva et al. [45].

*L. sclateri* populations were evaluated at sampling sites to assess intra-specific variability. The fish population traits we studied were relative abundance, size-related parameters, age-related parameters, relative growth rates and somatic condition. Relative abundance was measured as the number of *L. sclateri* individuals caught per hour (catch per unit effort, CPUE) in a standardized sample area without significant differences in habitat complexity and, thus, assuming that catch efficiency remains constant. Size-related parameters included mean, maximum and range of fork length (FL), and a size diversity index calculated as a Shannon-Wiener modification using the number of size classes grouped in 2 cm length ranges. Age-related parameters included mean, maximum and range of age, determined for a subsample of *L. sclateri* scales. Back-calculated lengths were estimated by the Fraser-Lee equation following the methodology used by Torralva et al. [45] and Miñano et al. [62] based on the counting and measuring of scales' annuli, and checked according to Musk et al. [63]. Proportions (%) of back-calculated lengths for each age class were obtained from the Walford method [64] and used to calculate the mean individual growth index (GI). Relative growth rates at the site level were estimated from the mean individual growth index (GI). The methodology used to calculate the growth index (GI) is detailed in Masó et al. [65] and Amat-Trigo et al. [66], which followed the Hickley and Dexter procedure [67]. We used the mean values of GI at age 1 year, age 2 years and maturity (individuals older than 2 years) according to the age of maturity previously established for the species in the Segura River basin [43,45,61]. Somatic condition was expressed as predicted values of log-transformed weight (mean value at sampling site) obtained from the application of univariate analysis of covariance (ANCOVA) using total weight (WT) as the dependent variable and fork length (FL) as the covariate; differences in variation were tested by ANOVA and Tukey's HSD post hoc tests [68]. Individuals with an FL less than 75 mm were considered juveniles [43]. Bivariate relationships between population traits were analyzed using Spearman's rank correlations. Statistical analysis was performed with the SPSS software package v. 24.

#### *2.4. Effect of Environmental Stress Factors on Population Traits*

We conducted a model selection analysis based on the Akaike Information Criterion with a correction for small samples sizes (AICc) [69] to determine the stressors associated with the variability in *L. sclateri* population traits. To establish model ranking, the MuMIn (Multi-Model Inference) R Package was used [70]. Stress factors were obtained by the reduction in transformed environmental variables and gradient descriptors (log for numeric variables, arcsine square root for proportions) using principal component analysis (PCA) with varimax rotation [71] using R package *psych*. Spearman's rank correlation analysis was used to test the redundancy between the variables. Principal component axes scores were used as stressors. The ratio of the abundance of non-native fish species (abundance of non-native species/total abundance) was also considered a stressor. General linear model results (GLMs) for the best models (∆AICc < 2.0) were used to describe the response of *L. sclateri* biological traits to the stress factors. These analyses were performed in the R statistical environment (Version 1.40.4).

#### **3. Results**

#### *3.1. Relative Abundance and Population Traits*

The abundance of *L. sclateri* showed high spatial variation, ranging from 13.33 to 150.00 catches per unit of effort (CPUE, Supplementary Table S1). The highest value was found in the Taibilla tributary (sampling site TAI) and the lowest was found at SE04, downstream of the Fuensanta reservoir (Figure 1).

The mean size fork length in the whole study area was 18.3 ± 6.55 cm FL, with the maximum value detected at MU03 (58.2 cm). The maximum validated age was 15+ years, with individuals this old detected at sampling sites SE04, SE07 and SE09; however, the mean age at the population level was 4.9 ± 1.43 years. The population size/structure differed among sampling sites, although a polymodal distribution pattern was evident

in most sampling sites along the longitudinal gradient (Figure 3). Both size and age parameters displayed lower values in headwaters (Figure 3 and Table S1), with maximum fish sizes below 30 cm (FL), lower size ranges and lower size diversity index values (Figure 3a,b,c). The other sampling sites had specimens longer than 40 cm (FL), with higher values at sampling sites just downstream of non-passable obstacles (e.g., SE07, Figure 3) and upstream of large reservoirs (e.g., MU03, Figure 3).

Δ

**Figure 3.** Size distribution (2 cm fork length (FL) groups) of *L. sclateri* at sampling site. Plot distribution: (**a**) Mundo River (MU) sampling sites, (**b**) sampling sites placed from Segura (SE) riverbed to Mundo River confluence, (**c**) sampling sites at tributaries Tus and Taibilla (TAI) Rivers and (**d**) sampling sites from Segura–Mundo confluence to the latest downstream sampling site (SE14).

The growth index (GI) displayed high variability for individuals of each age class between sampling sites. The mean GI value at age 1 year across the study area was 66.74 ± 1.28, with a maximum value of 82.47 detected at sampling site SE01, while the mean value of GI at age 2 years was 39.34 ± 1.13, with a maximum of 53.52 at sampling site MU09. For mature fish, the mean GI value in the study area was 17.69 ± 1.57, with a maximum of 32.53 detected at site MU05. The lowest GI values were detected in the TUS tributary (age 1 year = 45.72; age 2 years = 19.26; mature = 0.03).

Somatic condition was higher in mature individuals and also showed greater variability among sampling sites. The mean of predicted values of log-transformed weight for mature individuals was 1.87 ± 0.03, with a maximum value of 2.43 at sampling site MU04, whereas the mean value for immature individuals was 0.63 ± 0.03, with a maximum of 0.90 at sampling site SE10. Generally, lower values of somatic condition were detected in headwaters for both mature (TUS = 1.28) and immature (SE01 = 0.44) individuals. Population traits at the site level are shown in Table S1 (Supplementary Material). The relationships among population traits are presented in Table S2 (Supplementary Material).

#### *3.2. Environmental Factors*

The first three PC axes obtained from the dimension reduction of environmental variables and gradient descriptors explained 79.7% of the total variance (Table 2). PC1 was associated with habitat alteration and fragmentation, which were directly related to poor ecological status and low RQI, high values of conductivity and water temperature and low connectivity (high values for ICL and low values of free reach). PC2 was associated with the longitudinal gradient, which was directly related to high altitude, IHF and low water temperatures. PC3 was associated with flow regime alteration, which was directly related to flow variability and MDBF.



#### *3.3. Effects of Environmental Factors on Population Traits*

Table 3 displays the best models obtained from the model selection analysis based on AICc. The longitudinal gradient (PC2) was significantly linked with size-related parameters and somatic condition metrics. The gradient from the upper sampling sites to the downstream sites was associated with increment in population traits including the size range, mean and maximum size, size diversity index and somatic condition metric (longitudinal gradient axis, Figure 4). The longitudinal gradient interplayed with other stressors such as the non-native fish species, showing a significant effect on size range and maximum size (size-related parameters, Table 3). In addition, this environmental factor interplayed with the flow regime alteration (PC3), displaying a significant effect on mean size (size-related parameters, Table 3) and somatic condition for mature individuals (somatic condition, Table 3). Finally, the longitudinal gradient also interplayed with habitat alteration and fragmentation (PC1), displaying a significant effect on the size diversity index (size-related parameters, Table 3) and somatic condition in immature individuals (somatic condition, Table 3).




**Table 3.** *Cont.*


**Table 3.** *Cont.*

In addition to the interplay with the longitudinal gradient, the flow regime alteration (PC3) was linked to variability in the age range (age-related parameters, Table 3) and the growth index (GI) for mature fish and fish aged 2 years (growth, Table 3). An increase in the PC3 axis implied high flow variability and base flow (Impact 2, Figure 2c) and was associated with increased mean size and somatic condition of mature individuals, and GI at age 2 years and for mature individuals (flow regime axis, Figure 4). In contrast, a decrease in the PC3 axis implied low base flow and variability (Impact 1, Figure 2b) and was associated with a decreased age range (flow regime alteration axis, Figure 4).

In addition to the interplay with the longitudinal gradient, non-native fish species were linked to the variability in the mean and maximum age (age-related parameters, Table 3). An increased relative abundance of non-native fish species was associated with an increase in these two age-related parameters (non-native fish species axis; Figure 4).

Finally, habitat alteration and fragmentation (PC1) were linked to the size diversity index (size-related parameters, Table 3) and somatic condition of immature individuals (somatic condition, Table 3) and always exhibited an interplay with the longitudinal gradient. An increase in habitat alteration and fragmentation was associated with increased size diversity index (habitat alteration and fragmentation axis, Figure 4). Furthermore, the only interaction found in this study occurred between this stressor and the longitudinal gradient, which was associated with increased somatic condition for immature individuals (longitudinal gradient axis, Figure 4). Finally, the model selection analysis did not find any stress factors among those considered in this study to explain the variability in the growth index (GI) of fish at age 1 year or abundance (CPUE).

**Figure 4.** *Cont*.

**Figure 4.** Relationship between environmental factors (longitudinal gradient, habitat alteration and fragmentation, flow regime alteration and non-native fish species) and *L. sclateri* population traits. Significant results (GLM *p*-value < 0.05) are represented with marked trend line on the plot. In x-axes, arrows pointing down indicate decrease in environmental variables (i.e., water temperature), and arrows pointing up indicate increase in environmental variables (i.e., altitude) and also increase in non-native abundance ratio.

#### **4. Discussion**

In this study, we analyzed the variation in population traits of *L. sclateri* in response to environmental factors in the fluvial reaches of the Segura River basin. Our results confirm significant variability in population traits along the longitudinal gradient due to the effect of human impacts, mostly those related to flow regulation such as fragmentation and habitat alteration, flow regime alteration and the relative abundance of non-native fish species. The use of biological traits related to size and age, relative abundance, growth and somatic condition allowed us to identify the population-level responses of this sentinel Iberian fish to different stressors and to verify the complex effect of multiple stressors in a heavily modified Mediterranean-type river.

The longitudinal gradient is a key factor in the structure and dynamic of freshwater ecosystems, so it is essential to consider its effects in the assessment of multiple stressors in river systems [72–75]. Environmental conditions along the longitudinal gradient determine the availability of resources such as food, refuges and breeding areas [34,76]. Consequently, a marked effect of the spatial variation on fish populations was expected, especially in Mediterranean-type rivers which exhibit a strong climatic and altitudinal gradient [10,77,78]. The increment of resources downstream along natural river systems promotes large sizes and a wider range of size classes in the fish fauna [73,76,79]. We found significant variability in the size parameters and somatic condition of *L. sclateri* populations associated with spatial variation, with an increase in these biological traits along the longitudinal gradient. The size population structure displayed a polymodal pattern, with high variability among sampling sites. The size distribution results highlighted a lack of some size groups, and this was more evident in sampling sites downstream of reservoirs. Small and medium-sized individuals were scarce downstream of operational dams (i.e., at sites MU09, SE04, SE09 and SE11). The GLM results (Table 3) showed that size and somatic condition parameters were significantly associated with the longitudinal gradient. In fact, habitat alteration and fragmentation, flow regime alteration and relative abundance of non-native fish species were all related to the variability of population parameters, reflecting the severe alterations that have affected the Segura River basin [34,37].

Human impacts increase along the longitudinal gradient as a consequence of the greater accessibility to water resources [77]. As a result, the interplay among spatial variation and human stress factors shaped the environmental conditions that act as a "filter" of biological traits [80]. The selected traits determine the biological responses of freshwater fauna to cope with altered conditions [18,75,81]. The Segura River basin shows a strong influence of human alterations mainly related to agricultural supply [33,37]. Agricultural practices involve strong hydraulic management that results in a loss of connectivity (habitat fragmentation), flow regime alteration and water quality and habitat degradation and encourages the establishment of non-native fish species [18,32,82,83]. Our results show the interplay between environmental stress factors, mostly those related to flow regulation, and the longitudinal gradient in some biological traits such as size and somatic condition. In addition, we found that age and growth variations were significantly associated with the isolated effect of the flow regime alteration and the relative abundance of non-native fish species. This finding suggests that the magnitude of human impacts in the study area could be masking some ecological responses to longitudinal gradients [84,85].

The flow regime is considered the main driver of freshwater ecosystems, defining the structure, function and dynamic of rivers, and affecting the individual fitness and growth rate of fish populations [80,86,87]. We found significant relationships between flow regime alteration and some population traits of *L. sclateri* including mean size, age range, somatic condition for mature individuals and growth variability. Our results show an increase in these population traits associated with fluvial sectors that had a high level of base flow throughout the year (reflected as Impact 2 in Figure 2) and a flow regime pattern that reduced the strong seasonal variability of Mediterranean-type rivers. Although these fluvial sectors display an inversion in flow seasonality related to agricultural water demands, they also provide an increased availability of water, refuge and food resources [25,76,88].

Furthermore, high flow levels promote changes in body shape and muscle development, which induce better swimming performance and increased somatic condition [89,90], a finding that was previously documented in the Segura River basin [43]. In contrast, we observed a decrease in population traits (mean size, age range, somatic condition for matures and growth variability) associated with strong inversion in flow seasonality and base flow reduction (Impact 1 in Figure 2). We found this flow pattern in sampling sites downstream of the Cenajo reservoir, a consequence of the operating characteristics of its dam [34,35,54]. The extreme hydrological conditions caused by this type of water regulation result in a poor-quality habitat, especially for adult barbels [91], and are considered a limiting factor for the growth of barbel species in the Iberian Peninsula [25,92]. These two contrasting results in the response of fish populations under different hydrological flow patterns have been described in other Iberian rivers as well [25,93].

Non-native fish species tend to be dominant in human-altered ecosystems, such as the Mediterranean rivers, where more stable environmental conditions that result from flow regulation measures encourage their establishment and spread [82,83,94]. Iberian fish communities have exhibited significant changes over recent decades as a consequence of the introduction of a wide range of non-native fish species [95–97], and these changes are especially evident in the Segura River basin [38]. The negative responses of native fish populations associated with the presence and abundance of non-native species in the fish assemblage are well documented [75,98,99]. Our results show an increase in the maximum size and size range, and the mean and maximum age of *L. Sclateri* populations associated with a higher ratio of non-native fish abundance. The proliferation of non-native species is generally a result of changes in the environmental conditions caused by flow regulation [4,8]. The lack of small size classes of fish at sampling sites placed downstream of reservoirs where the presence of non-natives is favored (i.e., SE04 in Figure 3) suggests an effect of the fish assemblage composition on the structure of *L. sclateri* populations. In general, predation by non-native fish could affect the population structures and dynamics of native fish species in the Iberian Peninsula [95]. Some studies from other Iberian rivers confirmed the inclusion of different barbel species in the diet of top predator fish such as *E. lucius* [100,101] and *S. Lucioperca* [102]. Predatory fish (*E. lucious, S. lucioperca* and *M. salmoides*) showed a higher occurrence in the lower reaches of the study area. They could be inducing higher predation pressure on certain size classes of *L. sclateri* and therefore affecting the population size structure as Bravo et al. [103] showed in the Palancar River, where *M. salmoides* predation was directly related to the lack of 0+ individuals of dominant species such as *L. sclateri*.

The results of this study highlight relevant associations between human impacts, most of which were related to flow regulation, and the population traits of *L. sclateri* along a longitudinal gradient, providing insights into the population-level responses of this sentinel Iberian fish to environmental conditions at the site level. The key role of the longitudinal gradient in driving the increase in human impacts as a result of greater accessibility related to the lower reaches of rivers is evident, since most of the stressors were related to the spatial variation, so this dependence makes it difficult to interpret the effect of isolated stressors. In addition, there is a wide variety of human impacts present in the study area that were not considered in this study. For example, pollution could be driving the response of *L. sclateri* to environmental conditions [32], or predatory mammals (*Lutra lutra*), whose predation on *L. sclateri* in the Segura River basin was recently confirmed [104].

The ability of this species to adapt to changes in local conditions has been shown by the variation in population size/structure along the longitudinal gradient. Although human impacts exerted significant effects on the biological traits we evaluated, our findings also suggest that the wide inter-population plasticity displayed by *L. sclateri* may be a mechanism for this species to successfully inhabit a highly modified Mediterranean-type river. Cyprinids in general show great adaptability to environmental alterations [12,25,92,105], and *L. sclateri* showed a tolerance to the effects of flow regulation previously studied in the same river basin [45,61].

In recent decades, declines in fish populations have been documented for several Iberian fish species and there have been drastic reductions in fish species that were previously widely distributed in the study area. Native fish species are vulnerable to the rapid increase in human pressure on the water resource; this is especially so in Mediterranean areas where an increase in the magnitude of extreme weather events is expected under climate change scenarios [106]. Therefore, the use of well-known and widely distributed sentinel species, such as *L. sclateri*, may prove a useful tool to increase the knowledge of the adaptability and population responses to gradients of single and multiple stressors, which is essential to establish and improve management actions to protect native fish species.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/2073-444 1/13/6/747/s1, Table S1: Population traits of *L. sclateri* at sampling site. Table S2. Coefficients of Spearman rank correlation between population traits.

**Author Contributions:** Project administration, F.J.O.-P. and M.T.; conceptualization, A.S.-P., F.J.O.-P. and M.T.; methodology and data collection, A.S.-P., F.J.O.-P., F.A.-T. and M.T.; formal analysis, A.S.-P.; writing—original draft preparation, A.S.-P.; writing—review and editing, A.S.-P., F.J.O.-P., F.A.-T. and M.T. All authors have read and agreed to the published version of the manuscript.

**Funding:** Financial support was provided by the Fundación Séneca (project 08728/PI/08); Regional Agency of Science and Technology, Autonomous Government of Murcia. A.S.P. was supported by a pre-doctoral contract (FPU14/03994) from the Spanish Ministry of Science and Education.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available within the article or supplementary material.

**Acknowledgments:** We would like to thank all the members of the UMU research group for their help and support with the field surveys.

**Conflicts of Interest:** The authors declare no conflict of interest. They have no known competing financial interests or personal relationships that could influence this paper. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

#### **References**


**Shewit Gebremedhin 1,2, \* , Stijn Bruneel 1 , Abebe Getahun 3 , Wassie Anteneh <sup>4</sup> and Peter Goethals 1**


**Abstract:** Fisheries play a significant role in the livelihoods of the world population, while the dependence on fisheries is acute in developing countries. Fisheries are consequently a critical element for meeting the sustainable development (SDG) and FAO goals to reduce poverty, hunger and improve health and well-being. However, 90% of global marine fish stocks are fully or overexploited. The amount of biologically unsustainable stocks increased from 10% in 1975 to 33% in 2015. Freshwater ecosystems are the most endangered ecosystems and freshwater fish stocks are worldwide in a state of crisis. The continuous fish stock decline indicates that the world is still far from achieving SDG 14 (Life Below Water), FAO's Blue Growth Initiative goal and SDG 15 (Life on Land, including freshwater systems). Failure to effectively manage world fish stocks can have disastrous effects on biodiversity and the livelihoods and socio-economic conditions of millions of people. Therefore, management strategies that successfully conserve the stocks and provide optimal sustainable yields are urgently needed. However, successful management is only possible when the necessary data are obtained and decision-makers are well informed. The main problem for the management of fisheries, particularly in developing countries, is the lack of information on the past and current status of the fish stocks. Sound data collection and validation methods are, therefore, important. Stock assessment models, which support sustainable fisheries, require life history traits as input parameters. In order to provide accurate estimates of these life history traits, standardized methods for otolith preparation and validation of the rate of growth zone deposition are essential. This review aims to assist researchers and fisheries managers, working on marine and freshwater fish species, in understanding concepts and processes related to stock assessment and population dynamics. Although most examples and case studies originate from developing countries in the African continent, the review remains of great value to many other countries.

**Keywords:** life history traits; methods comparison; population imbalance; stock assessment

#### **1. Introduction**

Human connections to fisheries have developed over thousands of years, underlining the notable contribution of fish and fisheries to human well-being. Globally, millions of people directly or indirectly depend on fisheries for their employment, income and food security [1–3]. This dependence is acute in developing countries, particularly for poor and marginalized people [4,5]. The opening up of global markets for fish and fisheries products have created multiple opportunities to increase employment and income from fisheries [6]. Total employment in fisheries grew increasingly from 28 million in 1995 to 39 million in 2010 [3] (Figure 1). In 2016, more than 40 million people were involved in fisheries, with 79% and 13% of these 40 million people living in Asia and Africa, respectively [3]. The

**Citation:** Gebremedhin, S.; Bruneel, S.; Getahun, A.; Anteneh, W.; Goethals, P. Scientific Methods to Understand Fish Population Dynamics and Support Sustainable Fisheries Management. *Water* **2021**, *13*, 574. https://doi.org/10.3390/ w13040574

Academic Editor: Rafael Miranda

Received: 31 December 2020 Accepted: 19 February 2021 Published: 23 February 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

involvement of people in fisheries in developing countries has been growing steadily, while it has been declining in most developed countries [7], indicating that fisheries play a significant role in developing countries. Whereas men are primarily involved in fishing, women are heavily involved in fisheries-related activities such as processing and trade [8]. In developing countries, particularly in Asia and Africa, millions of women are involved in fish processing, marketing, making and repairing nets, making baskets, pots, and baiting hooks [7].

**Figure 1.** The global role of the fisheries sector for employment (Source: [3]).

Fisheries have an important economic contribution worldwide. Fisheries products are among the most traded food items and play a vital role in the global and local economy. For example, in 2016, approximately 60 million tonnes of fish and fish products (35% of global fish production) entered international trade in various forms [3]. This represents a total increase of 245% compared to 1976, but if we consider the trade in fish for human consumption alone the increase is more than 500% [3]. The value of global fish products also grew significantly from USD 8 billion in 1976 to USD 152 billion in 2017 [3]. This value surpasses the combined value of the net exports of rice, coffee, tea, tobacco and meat of that same year [3]. Fisheries play an important role in the national economies of many developing countries through the generation of foreign exchange derived from international trade. Fish production exports from developing countries account for approximately 60% of the total fish production being traded internationally [7]. Fish trade by developing countries increased from less than USD 4 billion in 1980 to USD 18 billion in 2001 [9]. Thus, fisheries are playing an increasingly important role in the national economy of many developing countries. Additionally, since the majority of the people involved in fisheries are from developing countries, fisheries are essential to keep households and communities out of poverty and improved fisheries management has the potential to further reduce poverty. The rural poor and marginalized people employed in fisheries could use the income earned from the sector to buy basic needs for living and to send their children to school. Fisheries have several valuable socio-cultural aspects. Understanding the socio-cultural values

associated with fish and fisheries is, therefore, vital for effective management of the resources [10]. Ignoring these values could reduce the social acceptability of the management options [11].

Of the seven billion people in the world, one billion are officially designated as starving [12] and two billion people suffer from micronutrient deficiency [13]. Although the improvement of agriculture practices has been identified as essential to overcome the looming food security crisis, fisheries can also make a significant contribution [14]. Fish is an important and affordable source of protein, essential micronutrients, and fatty acids, especially for people in developing countries [15,16]. Fish consumption has been associated with various human benefits such as child mortality reduction, and maternal health improvement [7]. The annual global fish production for human consumption has increased from 67% of the total fish production in the 1960s to 88% in 2016 [3]. Fish accounted for 17% of animal protein consumed by the world population [3], the majority of which was consumed in low-income food-deficit countries [1,17,18]. Generally, fisheries are important to address hunger, micronutrient deficiencies and food insecurity [1], underlining its vital role in meeting the sustainable development goals (SDGs 1 = no poverty, 2 = zero hunger, 3 = good health and well-being) and FAO's goal of a world without hunger and malnutrition.

Despite the significant contribution of fisheries to livelihoods, employment and income, many of the global fish stocks have been declining drastically. Successful management of the fish resources is therefore crucial. Failure to effectively manage world fish stocks can have disastrous effects on biodiversity and the livelihoods and socio-economic conditions of millions of people who are strongly dependent on these resources. Management strategies that successfully conserve the stocks and provide optimal sustainable yields are urgently needed. Successful management is possible when the necessary data such as age, growth, mortality and maximum yield are obtained, processed and interpreted and decision-makers are well informed. Fisheries managers, particularly from developing countries, are faced with many challenges due to lack of information on the past and current status of fisheries and the fish stocks. Although stock assessment modelling is necessary (i) to provide answers to questions about the current status of the stock, (ii) to predict the effect of current and future management measures and (iii) to support sustainable fisheries by providing fisheries managers with necessary advice to make informed decisions (Figure 2), such studies are limited in developing countries. To understand the factors affecting fish population imbalance, a good understanding of the wide range of age determination and validation techniques is required. They provide valuable input parameters for further stock assessment evaluation. However, the majority of young researchers in developing countries have limited skills and knowledge on how to select and prepare ageing hard structures and to validate measurements. Although there have been several well-documented methodological studies in developed countries that can be used as a reference, most of them are not open access. This hinders fish resources managers and young researchers in developing countries from accessing these documents. Therefore, the aim of this study is to provide an accessible review to fisheries managers and young researchers from developing countries. The review focuses on the factors that affect fish population imbalance, the different ageing hard structures, optimal otolith preparation and age validation techniques and their limitations and advantages. The review provides essential information to illustrate the need for reliable methods for life history trait estimation and evidence-based fisheries management. Therefore, this review aims to assist researchers and fisheries managers, working on marine and freshwater fish species, in understanding concepts and processes related to stock assessment and population dynamics. Although most examples and case studies originate from developing countries in the African continent, the review remains of great value to many other countries.

**Figure 2.** The process of fisheries data collection for age determination methods and stock assessment modelling to provide important advice to develop regulations and policies for sustainable fisheries management.

#### **2. Global Fish Stock Status**

Global fish stocks have been declining drastically. This decline has been attributed to several pressures, particularly the rapid increase of fishing efforts to feed the rapidly increasing human population [3]. Currently, 90% of global marine fish stocks are fully or over-exploited [3]. The size of biologically sustainable marine fish stocks (i.e., maximally sustainably fished and underfished stocks) decreased from 90% in 1975 to 67% in 2015, while the size of biologically unsustainable stocks (i.e., overfished stocks) increased from 10% in 1975 to 33% in 2015 [3] (Figure 3). Since there are no new fishing grounds to be exploited [3,19] and the current world human population is predicted to exceed nine billion by 2050, there will likely be more pressure on the stocks.

**Figure 3.** The trend of the global marine fish stock (source: [3]).

Freshwater ecosystems, one of the most important life-support systems on Earth, are the most endangered ecosystems in the world [20]. Freshwater ecosystems are vulnerable to changes in the basin [21,22] originating from agriculture, mining, urbanization and dam and diversion weirs construction [23]. Anthropogenic pressures cause changes in the physical, chemical and/or biological components of the freshwater ecosystems when the carrying capacity of ecosystems decreases below the ability to absorb stress. Freshwater fish stocks are in a state of crisis worldwide [24]. The perceived increase is caused by changes in the monitoring and measuring rather than actual changes in fisheries production [3]. This is corroborated by the drastic decline in abundance and diversity of the different freshwater fish species due to the increased anthropogenic pressures [20,25–33]. Furthermore, ≥65% of the inland water habitats are moderately or highly threatened [27], suggesting that some of the fish species inhabiting these systems are at high risk of extinction. According to World Wide Fund for Nature (WWF [34]), the current rate of fish population decline in freshwater systems is two times the rate for marine systems.

There are many examples of excessive stressors with negative consequences. For example, the catches, diversity and composition of the fish communities, particularly the most commercially valuable species, in many African lakes such as Lake Malawi, Lake Tanganyika, Lake Victoria and Lake Tana have markedly declined due to overexploitation, illegal fishing, the introduction of exotic species and environmental degradation [31,33,35–38]. A recent assessment by the International Union for Conservation of Nature (IUCN) revealed that 9% of the 458 fish species inhabiting Lake Malawi are at high risk of extinction [39]. Studies indicated that in Lake Malawi, long-living, slow-growing and late-maturing species have been depleted [40–44] while the biomass of the endemic *Oreochromis* species (chambo), has been declining rapidly [45,46]. There are strong signs of overfishing for chambo, the most valuable component of the lake fishery [47]. The chambo fishery in Lake Malawi has declined from 5000 tonnes per year in 1992 to less than 2000 tonnes per year in 1999 [48]. Similarly, in response to intensified pressures, like eutrophication and overfishing, fish stocks in Lake Victoria have changed both in composition and abundance [49]. Currently, more than 76% of the fish species in Lake Victoria face extinction [50]. The abundance and diversity of fish species in Lake Turkana drastically declined due to degradation of the littoral habitats and flood pulse breeding areas caused by upstream development and climate change [51]. Fisheries in the major river basins such as the Zambezi River system have experienced drastic declines in catch rates, changes in fish communities and loss of valuable species [52]. Most of the fish communities in the inland waters of Ethiopia are showing signs of overfishing [25,53–55]. Anthropogenic pressures in and around the inland waters negatively affect the survival of fish species in Ethiopia. For example, the abundance and size of the fish populations in Lake Tana have been declining drastically due to overexploitation, agriculture and dam constructions [31–33]. As a result, the catch per unit effort (CPUE) of the endemic *Labeobarbus* in the lake decreased from 63 kg/trip in 1991–1993 [56] to 2 kg/trip in 2016–17 [55]. Currently, five *Labeobarbus* species are already reported as IUCN red-listed species [57]. This number will likely increase even more in the near future as the present status of many species have not been evaluated yet. Furthermore, the predominance of small-sized species with little economic importance over large-sized species with high economic importance has been reported [53]. This suggests overfishing of the system. Due to overfishing, the proportion of large and valuable species decreases in favour of small and less valuable species [58]. Therefore, the continuous fish stock decline, particularly in developing countries indicates that the world is far from achieving the SDGs. Especially, SDGs target 14.4 to end illegal, unreported and unregulated (IUU) fishing by 2020 will not be met at all. Additionally, the world human population is rapidly increasing, leading to a higher demand for fish, which poses a hurdle for the FAO's Blue Growth Initiative goal. This goal aims to maximize the goods and services provided by the different ecosystem types without compromising the social and economic benefits the systems offer [3].

#### **3. Dynamics in Fish Population Size and Life History Traits**

#### *3.1. Factors Affecting Fish Population Imbalance*

Fish population dynamics are primarily affected by three factors: (1) recruitment, (2) growth and (3) mortality rates [59]. The recruitment is defined as the number of individuals born within a given period. Growth is the increase in length and weight of the individuals of a population in a given period of time, and mortality is the number of individuals removed from the population within a given period of time (Figure 4). Recruitment and growth increase the fish population in number and biomass, while mortality, due to fishing and/or natural causes, decreases the population both in number and biomass. Illegal, unreported and unregulated (IUU) fishing increases fishing mortality and has adverse effects on the abundance and size composition of fish populations. Fishers often target the spawning biomass, causing high mortality rates which in turn leads to drastic reductions in the abundance of recruits and mega-spawners. Furthermore, small mesh sizes, typically used for illegal fishing, are known to have negative effects on the size distribution and maturation of fish [60,61]. For example, the majority of the specimens of *Labeobarbus* species in Lake Tana caught using ≤8 cm mesh size gillnets had fork length less than the size at first maturation (FL50%) [55]. The dominance of immature individuals (<FL50%) in the catch confirms the expected negative effect of small mesh size gillnets. Additionally, specimens of *Labeobarbus* with ≥40 cm fork length (FL) were more often recorded in the late 2000s [62,63] than in 2016/17 [55]. The absence of large-sized specimens (mega-spawners) is the result of destructive fishing activities targeting the spawning biomass and causing environmental degradation. Climate change also has the potential to affect freshwater fish resources, especially the mega spawners [64–67]. The reduction of mega-spawners in a stock is detrimental to the long-term survival of fish populations due to (i) their high fecundity, which creates a greater chance of survival to larvae [68,69], (ii) their ability to serve as reservoirs and distributors of desirable genes [70], and (iii) their ability to act as a natural safeguard against subsequent recruitment failure [71,72]. The presence of enough mega-spawners can be used as a simple estimator of the resilience of stocks against random disturbance events [70]. The presence of 30–40% of mega-spawners in stock indicates a healthy size and age structure of the population, while <20% could be a matter of concern [70]. In general, the fish population decreases if the addition to the population by recruitment and growth is smaller than the removal from the population due to mortality. Thus, the current drastic decrease in the global fish population suggests that mortality (fishing and/or natural) is exceeding recruitment and growth. Understanding the major factors that cause fish population imbalance is therefore vital for a sustainable exploitation of fisheries.

Size structure indices are useful to evaluate the status of the fish population and identify the pressures that affect the population dynamics [73–76]. For example, analysis of length-weight relationships for a species can provide fundamental insights into the ecology, population dynamics, and management of that species. Understanding how the weight of fish changes as a function of length is useful to predict weight from the length of the fish and determine the growth type and relative condition of the fish population. Use of the size structure indices as potential indicators of fish population imbalance has gained popularity because of their connections with recruitment, growth and mortality [73,75,77]. For example, the proportion of small size individuals in the population might be higher than the proportion of large size individuals due to high recruitment, slow growth and/or high mortality rates of large size classes and vice versa [73,74].

**Figure 4.** Illustration of the fish population dynamics. The "+" sign indicates an addition to the population, while the "–" sign indicates removal from the population.

#### *3.2. Life History Traits as a Basis for Stock Assessment and Fisheries Management*

The current world human population is rapidly increasing, although the world fish stocks have been declining drastically and there are no new fishing grounds to be exploited [3,19]. The rapid world human population increase will likely cause high fish consumption demand which in turn will increase the pressures on the stocks. Fisheries managers are facing many challenges as fish stocks continue to decline and IUU fishing undermines the sustainability of fisheries. The main problem of fisheries managers, particularly in developing countries, is the lack of appropriate fisheries data for accurate stock assessment modelling. Stock assessment models provide answers to questions about the current condition of the stock and allow for predictions about how the stock will respond to current and future management measures. Additionally, stock assessment supports sustainable fisheries by providing fisheries managers with vital advice to make informed decisions. However, stock assessment models require life history traits such as age, growth and mortality rates as input parameters [78–80]. In fisheries science, age is one of the most influential life history traits that is primarily used to estimate life history traits such as age at maturity, growth rate, mortality rate and population analysis [79]. The importance of life history traits for fisheries assessment and management is presented in Table 1 [59].

In fisheries science, the collection, preparation, and interpretation of different hard structures provide a means for age estimation [81]. Otoliths, scales and fin rays are the most commonly used hard structures for age estimation [79,82]. The choice of the most suitable hard structure for estimating age is guided by several factors: (1) the ease of obtaining the hard structure, (2) growth of the structure itself and the formation of growth zones on the structure, (3) difficulties in preparation of the hard structure and growth zones interpretation and (4) accuracy and precision of the age estimates derived from the hard structures [80]. Therefore, understanding the advantages and limitations of each structure (i.e., otoliths, scales and fin rays) is indispensable to make the correct choice. In the next sections these structures are discussed more in depth.


**Table 1.** The importance of life history traits for assessment and management use.

#### *3.3. Advantages and Limitations of the Hard Structures Used for Age Estimation* 3.3.1. Otoliths

Otoliths are calcium carbonate structures that aid in balance and hearing of fish [81]. Additionally, otoliths record a remarkable amount of information about the life history traits of the fish and the environments they are living in [83]. To better understand and manage the fish population, this information should be carefully assessed, interpreted and incorporated into fisheries management decision-making. Of the three existing types of otoliths, sagittal otoliths are used for the age estimation of most fish species [84–86], but asteriscus otoliths are the most suitable structure for the Cyprinidae family [87–89]. The calcium carbonate that is used to form the otoliths originates from the water and from the food of the fish. This process is influenced by fish metabolism. During seasons with adequate average temperatures and sufficient food availability, fish grow at a relatively fast rate causing formed rings to be widely spaced. However, during the colder months where there is limited food supply, particularly for fish species in temperate regions, growth is restricted leading to narrow ring formation. As a result, alternate opaque and translucent growth zones are formed, which are considered to have been formed in one year (i.e., annulus). The age estimates of the fish can be obtained by counting the number of annuli deposited on otoliths. Regardless of its effort and cost, ageing accuracy is much higher for analysis of growth zone deposition on otoliths compared to the length and otolith size-based methods [90].

The use of otoliths for precise and accurate age estimation has several advantages: (1) otoliths grow continuously and form annuli even when the body growth slows down and the asymptotic length has been reached, (2) metabolically they are inert and not subject to resorption, (3) otolith growth varies between seasons leading to the formation of annual increments that can be used for age estimation, and (4) annuli reabsorption does not appear to occur during periods of food limitation or stress [79,88,91]. However, the use of otoliths also has limitations [92]. Age estimation using otolith is laborious, time-consuming, expensive and is dependent on the skills and experience of readers, which limits the sample size and prevents researchers with limited skills and experience to use otolith for age estimation [93,94]. Additionally, otoliths require sacrificing fish, which makes this approach difficult to be applied for threatened species or small populations [95].

#### 3.3.2. Scales

The age of fish can also be determined by scales as the successive rings (circuli) are formed as the fish grow. The ctenoid and cycloid scales are most often used for estimating fish age [84]. Although scales from the whole part of the fish can be used, those that are

found on the shoulder between the head and the dorsal fin are generally the best because of their relatively large size and low sensitivity to damage [80,84]. Traditionally, due to their non-lethal nature, scales have long been considered the most efficient and suitable structure for age determination, but more recent studies have revealed them to be inaccurate [96–99]. The limitations of scales to yield precise and accurate age estimates have been found most severe for slow-growing and older fish [79,98,99]. Scales have various inconsistencies, which make them difficult to read and interpret visually [100]. For example, well-defined marks on one scale might be absent on the neighbouring scales of the same fish [100]. Scales have several additional limitations: The first limitation is the dependency of scale growth and patterns of the circuli formation on fish growth. The variability in fish growth (i.e., between young and old fish) affects the scale growth and the appearance of the circuli. Scale growth is minimal or non-existent after the onset of maturity, particularly when fish growth is very low or ceases [84]. Thus, this causes underestimation of the actual fish age, particularly in older fish. In older fish, the circuli at the edge of the scale can be crowded making the circuli interpretation difficult. The second limitation is resorption causing some reworking or breaking of the circuli, leading to misinterpretation. The third limitation is transparency, which makes the circuli difficult to observe. The fourth limitation is that damaged or removed scales can be regenerated, resulting in growth patterns that do not accurately reflect the age of fish. The fifth limitation is that either some fish have no recognizable pattern on their scales or entirely lack scales. Therefore, when scales are used for age determination, either the age of all groups in the population should be validated, which is difficult if not impossible, or an alternative aging method should be used for older individuals in the population [80,84].

#### 3.3.3. Fin Rays

Compared to otoliths and scales, fin rays are not frequently used for age estimation. However, the suitability of fin rays for some fish species is reported by some researchers [101–104]. The most commonly used fin rays are the dorsal, pectoral, and, pelvic fins [84]. Age estimates from fin rays have higher precision and accuracy compared to the estimates from scales [96,105,106]. Most importantly, using fin rays does not require the fish to be sacrificed [107,108] and the annuli remain representative for the age of older fish [109,110]. However, the low precision and accuracy of these structures have also been reported [111–113]. Fin rays provide inaccurate age estimates due to the following reasons: (1) difficult to read and interpret annular marks, (2) early marks are sometimes obscured by the vascular core of the fin rays, (3) irregular and unexpected spacing of annuli on the fin rays sections, which suggests resorption at different rates in different years, (4) difficult to distinguish between the true and false annulus and to correctly identify the first annulus, and (5) its preparation requires special technical skills [100,112,113].

#### **4. Precision and Accuracy of Otolith Preparation Methods**

Although there are several calcified structures available for age estimation [79,82], otoliths often provide the most precise and accurate age estimates [79,114]. However, age estimation based on the analysis of otolith growth zones involves judgment and subjective interpretation [79,81,115]. The subjective interpretation of otoliths contributes to two major sources of errors involving both processing and interpretation [79,116]. The first source of error relates directly to the nature of the otolith structure being interpreted. In this regard, otoliths must satisfy the criteria outlined in [117]: (1) otoliths must display growth increments that can be quantitatively resolved, (2) the formation of growth zones must conform to a regular and determinable time scale, and (3) otoliths must grow continuously throughout the lifespan of the fish. The second source of error can be traced back to the preparation of otoliths, interpretability of growth zones and reader experience [79,116,118,119]. The interpretation error can be minimized by describing a standardized, precise and accurate otolith preparation method and by training the age readers [79,116,118,119]. If the otolith images used for age estimation have the clearest view of the growth zones, core and edge,

the bias between age readers should be minimal. It is, therefore, useful to describe the most adequate preparation method for each species. To this end, different otolith preparation methods such as transverse sections, staining, burn-and-breaking, polishing and whole otolith submerging in different substances including water and glycerol have been compared in attempt to describe the best method. Additionally, bias among hard structures such as scales, otoliths and fin rays has been compared to select the most appropriate structure. Such comparisons are especially important to approximate the accuracy of age estimates [84,120]. The precision and bias among different aging methods and age readers are usually done using statistical methods, graphical approaches, precision indices and qualitative expressions. Average percentage error (APE) [121] and coefficient of variation (CV) [122] are widely used and the most suitable and statistically sound measurements of precision [79]. The APE and CV are computed by the following formula:

$$\text{APE} = \frac{100}{\text{N}} \sum\_{\text{J}=1}^{\text{N}} \left( \frac{1}{\text{R}} \sum\_{\text{i}=1}^{\text{R}} \frac{|\mathbf{X}\_{\text{ij}} - \mathbf{X}\_{\text{j}}|}{\mathbf{X}\_{\text{j}}} \right) \tag{1}$$

$$\text{CV} = \frac{100}{\text{N}} \sum\_{\text{J}=1}^{\text{N}} \left( \frac{\sqrt{\sum\_{i=1}^{R} \frac{\left(\mathbf{x}\_{\text{i}} - \mathbf{x}\_{\text{i}}\right)^{2}}{R-1}}}{\mathbf{x}\_{\text{j}}} \right) \tag{2}$$

where N is the number of fish aged, R is the number of times fish are aged, Xij is the ith age determination for the jth fish, and X<sup>j</sup> is the average estimated age of the jth fish.

Although there is no rule of thumb, Campana [79] suggested CV ≤ 7.6% and APE ≤ 5.5% as reference values. The method with the smallest APE and CV values is, therefore, the most optimal method. The systematic bias between age readers, aging structures and aging time (i.e., if the reading is made two times by the same reader) can be described using a test of symmetry and it is best described through an examination of an age-agreement table [123]. The age estimates from the most experienced reader or the structure thought to be the most accurate should be used as the column variable in the age-agreement table. If the reading is made two times by the same reader, the first reading should appear as the column variable. Although several statistical methods were capable of detecting systematic aging differences, they were incapable of detecting both linear and non-linear biases in aging [115]. Some statistical methods, for example, were not sensitive enough to detect if the ages of younger fish were systematically over-aged or if the ages of older fish were systematically under-aged. To address this problem, Campana, et al. [115] introduced the age-bias plot to visually assess the differences in paired age estimates from two structures, two readers, or one reader at two times. Later, Ogle [124] modified the original age-bias plot in several ways. For the age-bias plot, one set of age estimates serve as reference age (*x*-axis). The age estimates that are thought to be most accurate are usually used as reference age. Thus, when the bias between age readers has comparable age estimates, the estimates of the most experienced reader should be used as reference age, whereas if the bias between two preparation methods or structures is compared, age estimates from the method or structure that is thought to be the most accurate should be used as reference age. However, the first reading should be used as reference age, if two readings from the same reader are made. Additionally, other factors such as qualitative expression may be involved as well. A quality control criteria (i.e., Q1 = readable otoliths with minimum bias, Q2 = readable otoliths with moderate bias and Q3 = unreadable otoliths) should be used to analyse readers' confidence. The method with the highest number of otoliths under Q1 has a higher readers' confidence than the other methods. The processing time and reading time should also be recorded. If there is no difference in precision and accuracy, the method that has the shortest processing time, the shortest reading time and the highest reader's confidence should be considered as the most optimal method.

The process of growth zone deposition on otoliths is affected by biological and environmental factors [125]. The rate of growth zone deposition on otoliths is either annual

or biannual. Therefore, in age estimation studies, validation of the rate of growth zone deposition is essential. Although several methods to validate age or the rate of growth zone deposition are available, mainly marginal increment analysis and edge analysis are used [79]. For more detailed information, see literature elsewhere [79,81,84,115,124].

In developed countries, significant and extensive work has been done to standardize otolith preparation methods, validate age or the rate of growth zone deposition and estimate life history traits of fish [83,87,118,121,126–136]. Such studies are limited in developing countries such as African countries. Except for the limited efforts in South African and Ethiopian water bodies [85,86,89,137–146], many fish species in the African water bodies including the Great African Lakes remain poorly studied. Concerning the description of optimal otolith preparation methods, validation of the rate of growth zone deposition and estimation of life history traits. The present lack of information on life history traits of different fish species hinders scientists and fisheries managers from refining optimal strategies for their conservation. Thus, detailed information on the description of the optimal otolith preparation method and validation of the rate of growth zone deposition is crucial. The widely used methods to validate the rate of growth zone deposition are discussed in the next section.

#### **5. Validation of the Rate of Growth Zone Deposition**

Validation of the rate of growth zone deposition is indispensable for accurate age estimation. There are several validation methods including advanced methods such as radiochemical and bomb radiocarbon dating. However, since these advanced methods are very expensive and difficult to apply for short-living species, mark-recapture of chemically tagged fish, marginal increment analysis and edge analysis are often used to validate the rate of growth zone deposition [79]. In this section only these widely used methods are discussed, for information about the other validation methods see Campana [79], Green, et al. [81], Andrews, et al. [130] and Piddocke, et al. [147]. A summary of the different methods used to validate age or the rate of growth zone deposition is presented in Table 2.


**Table 2.** Advantages, limitations, precision, sample size and cost of the different methods used to validate age or the rate of growth zone deposition. Methods are listed regardless of any scientific value. (Source: [79,147]).

#### *5.1. Mark-Recapture of Chemically Tagged Fish*

At the moment this method is one of the best and most cost-effective methods available to validate the rate of growth zone formation [79]. It can be applied through various methods such as injection, immersion and feeding. Injection is the most common technique for tagging wild fish [148–150]. Fish species that are captured from the wild are injected with calcium-binding chemicals such as oxytetracycline (OTC), alizarine, calcein and strontium immediately at the time of tagging [125]. These chemicals are incorporated into otoliths shortly after injection. The permanent mark is visible under fluorescent light in the growth zone being formed at the time of tagging [79]. The rate of growth zone deposition can be determined based on the number of growth zones deposited distally to the mark in the recaptured fish and the time at liberty. If the difference in the time of injection and liberty is one year and one growth zone is deposited during this time, it means that the studied fish species deposited one growth zone per year. However, if two growth zones are deposited, it means the rate of growth zone deposition is biannual. This method has been applied to validate the periodicity of growth zone deposition in several fish species [141,143–145,151–154]. The growth zones being validated are formed while the fish is growing in the natural environment. This method is time-consuming, technically difficult to apply and the recovery rates of the tagged fish are usually low [155]. Additionally, since the numbers of growth zones formed after tagging are low, a wrong conclusion can be made on the rate of growth zone deposition, if one of the growth zones is misinterpreted.

#### *5.2. Marginal Increment Analysis*

Marginal increment analysis (MIA, linear-circular model) is the most widely used validation method due to its modest sampling requirements and low cost [79]. The MIA is based on the observed incremental patterns of growth zones throughout the year and assumes that the outermost increment displays a yearly sinusoidal cycle when plotted against months of capture [156,157]. It uses the ratio of the width of the last growing zone and the width of the last fully completed growth zone (MIR) as a dependent variable and months of capture as an independent variable [158–160]. The marginal increment ratio (MIR) is, therefore, computed as follows [161].

$$\text{MIR} = \frac{\text{R} - \text{r}\_{\text{R}}}{\text{r}\_{\text{R}} - \text{r}\_{\text{n}-1}} \tag{3}$$

where R is the distance from the core to the outermost of the edge, r<sup>n</sup> is the distance from the core to the end of the growing zone and rn-1 is the distance from the core to the end of the last fully formed growth zone.

When the MIR value is equal to one, it indicates the completion of growth zone formation. Although the MIA is a useful method, especially when supported by other validation methods [159], it is also susceptible to bias and misinterpretation if not applied rigorously [79]. The approach has several limitations. The extended time of sample collection (monthly at least for one year), high possibility to collect small sample size per size classes within each month, difficulties to objectively classify the edge types and substantial inter-individual variation in marginal increment appearance [79,147]. These limitations are more pronounced in older fish where growth increments become very thin and packed together [118,162]. Therefore, when MIA is applied as age validation, the following protocols should be applied. (1) samples must be completely randomized when assigned to the examiner, (2) a minimum of two complete cycles need to be examined, in accordance with accepted methods for detecting cycles, and (3) the results must be interpreted objectively [79]. All the described protocols and encountered limitations for this technique here are also applicable for the edge analysis approach described below [79].

#### *5.3. Edge Analysis*

Similar to the MIA, edge analysis (EA, binary-circular model) is also based on examination of the marginal increments. Its dependent variable is binary, the otolith edge types either opaque or translucent, while the month of capture is the independent variable. Analysis of the EA can, therefore, verify the hypothesis that growth zone deposition is either annual or biannual. This approach assumes that the density of the outermost margin (i.e., proportion of the translucent zone) exhibits a sinusoidal cycle when plotted against the months of capture [79]. Several researchers found this approach useful for validating the periodicity of growth zone deposition [89,143,161,163]. For example, the Edge analysis revealed an annual growth zone deposition for *Labeobarbus platydorsus* in Lake Tana [140] (Figure 5). Although the EA approach is cheap and logically simple, it is susceptible to bias and misinterpretation if not applied rigorously [79].

**Figure 5.** The proportion of asteriscus otoliths with a translucent growth zone on the edge for *Labeobarbus platydorsus* based on samples collected between May 2016 and April 2017 in Lake Tana, Ethiopia [140]. The bar graph denotes the proportion of the translucent growth zone and the open dot line represents the predicted model results. The numbers above the bars in the no cycle model are total sample size and the same sample size is used for the other models. The annual cycle mode best fit the data.

#### **6. Conclusions**

Fisheries management strategies must be developed to ensure that stocks are harvested at sustainable levels. Fisheries managers rely on age estimates to develop effective and sustainable management options. Accurate and precise age estimates can be obtained if and only if an appropriate otolith preparation method is described and the rate of growth zone deposition is properly validated. Age estimates combined with data such as fish length, weight and reproductive condition can be used to describe the structure and dynamics of the population considered to comprise the harvested stock. For example, longevity and growth rates are estimated using length and age data, while the combination of sex and reproductive condition with growth data are used to describe the age-fecundity relationship and sex-specific growth. Mortality rates are also computed by combining age estimates with counts of the number of fish per age class in a sample. These analyses provide researchers and fisheries managers with a range of information to derive sustainable harvest strategies through stock assessment evaluations. In order to avoid complete stock collapse, fisheries catch should not exceed the maximum sustainable yield of the stock (MSY). The MSY is an important tool to quantify the goal of a fishery and allows fisheries managers to evaluate the performance of the fishery. The comparison of the assessed state of the fish stock with the values of the fisheries reference points such as MSY supports the managers to make informed decisions. Thus, fisheries reference points should be calculated as correctly as possible. The most popular and widely used model to estimate the MSY is the yield-per-recruitment model, introduced by Beverton and Holt [164]. Understanding the population dynamics, age determination techniques, and the estimation of life history traits allow policymakers and fisheries managers to optimize future conservation strategies (Figure 6). Furthermore, monitoring and evaluating the effects of the major pressures such as pollution, habitat degradation and over utilization of aquatic resources is vital to provide insights into the changes of aquatic ecosystems and indicate their status (Figure 6).

**Figure 6.** Schematic representation of fish community monitoring, fish stock assessment and environmental modelling to develop science-based fisheries management.

**Author Contributions:** S.G. conceived the main idea and wrote the manuscript. S.B., A.G., W.A. and P.G. reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by the Critical Ecosystem Partnership Fund (CEPF) and special research fund (BOF), Ghent University.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


## *Article* **Plasticity in Reproductive Traits, Condition and Energy Allocation of the Non-Native Pyrenean Gudgeon** *Gobio lozanoi* **in a Highly Regulated Mediterranean River Basin**

**Fátima Amat-Trigo 1 , Mar Torralva 1 , Daniel González-Silvera 2 , Francisco Javier Martínez-López 2 and Francisco José Oliva-Paterna 1, \***


**Abstract:** The invasion success of non-native fish, such as Pyrenean gudgeon *Gobio lozanoi* in several Iberian rivers, is often explained by the expression of its life history traits. This study provides the first insights into the reproductive traits, fish condition, and energy allocation (protein and lipid contents of tissues) of this species, along a longitudinal gradient in one of the most regulated river basins in the Iberian Peninsula, the Segura river. Larger sizes of first maturity, higher fecundity and larger oocytes were found in fluvial sectors with the most natural flow regimes, characterised by a low base flow with high flow peaks in spring and autumn. A delay in the reproductive period, lower fish condition and no differences in sex-ratio were observed in fluvial sectors with a high increase in base flow and notable inversion in the seasonal pattern of flow regime. Lipid contents in the liver and gonads were stable during the reproductive cycle and decreases in muscle were noted, whereas ovarian and liver proteins increased. In relation to energy allocation for *G. lozanoi*, an intermediate energy strategy was observed between income and capital breeding. Our results support the hypothesis that the high plasticity of *G. lozanoi* population traits plays a significant role in its success in a highly regulated Mediterranean river basin. Understanding the mechanisms by which flow regulation shapes fish populations in Mediterranean type-rivers could inform management actions.

**Keywords:** energy allocation; fecundity; flow regulation; Mediterranean-type river cyprinids; invasive fish

#### **1. Introduction**

Flow regulation is one of the most widespread anthropogenic alterations in natural aquatic ecosystems and plays an important role in habitat development, food sources availability and the distribution of organisms [1,2]. There are many studies that confirm the impact of flow regulation (i.e., dams and weirs) on the structure and functioning of rivers, and in particular, how they affect populations of fish worldwide [3–5]. Stream flow is a factor which has been considered as an important force shaping fish population traits [6,7] and life-histories [8,9], and several flow alteration studies have already shown significant effects on population traits such as, for instance, growth and maturation [5], changes in the timing of spawning and spawning areas [10,11], recruitment failure [12,13] and even changes in reproductive traits [3,14].

In relation to reproductive strategies, nutrient acquisition and energy allocation to reproduction are essential for energy balance in order to meet survival, growth and reproduction demands and, consequently, to develop the most competitive strategy [7]. Thus, the management of energy reserves and allocation during the reproduction process determines the reproductive strategy [15]. Fish species that can use the energy previously stored

**Citation:** Amat-Trigo, F.; Torralva, M.; González-Silvera, D.; Martínez-López, F.J.; Oliva-Paterna, F.J. Plasticity in Reproductive Traits, Condition and Energy Allocation of the Non-Native Pyrenean Gudgeon *Gobio lozanoi* in a Highly Regulated Mediterranean River Basin. *Water* **2021**, *13*, 387. https://doi.org/10.3390/w13030387

Academic Editor: José Maria Santos Received: 18 December 2020 Accepted: 29 January 2021 Published: 2 February 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

in tissues for the development and maturation of reproductive features have been referred to as capital breeders [16,17], and this strategy is typical of total spawners or species with synchronous oocyte development [15]. Alternatively, income breeding strategists include species that are not able to store energy and where reproduction success is determined by the environmental resources at the time of reproduction [18]. This strategy is more common in many small, batch-spawning fishes with asynchronous oocyte development [15]. Between these two extreme strategies, some species show intermediate characteristics of both energy allocation strategies [19–21].

This study is focused on the reproductive strategy and energy allocation dynamics during the reproductive cycle of the Pyrenean gudgeon, *Gobio lozanoi* Doadrio and Madeira 2004 (Actinopterygii, Cyprinidae; Supplementary Material 1, Figure S1), which is an endemic species from the Iberian Peninsula and the south of France [22]. The species has been translocated into several Iberian catchments as live bait for angling and, nowadays, is widely distributed across the Iberian Peninsula, with established populations in many rivers [23,24]. Some authors consider this species as having a high capacity to spread and as being able to behave invasively, increasing its density rapidly and occupying new habitats [24]; a process which is probably favoured by river regulation and artificial impoundments [25]. It has already been suggested that this non-native species may have potential impacts on the environment and native species throughout several Iberian basins [23,25–27]. Some examples include interspecific competition for food resources [28,29] or disease transmission [30].

Freshwater biotas are especially vulnerable to new invasive fish, particularly in areas with high endemism, such as the Mediterranean basins [26,31,32]. The non-native populations of *G. lozanoi* have been previously classified as opportunistic strategists (sensu Winemiller and Rose [33]), but also as intermediate strategists because they use strategies ranging from periodic to opportunistic [34]. Thus, non-native populations of *G. lozanoi* are characterised by early maturity, low fecundity, multiple spawnings per year and have a long reproductive span [34]. However, there is a scarcity of studies that have dealt with the biology and reproductive traits of non-native populations of *G. lozanoi* [35–37]. Consequently, the negative effects of the species on native fish may not yet have been fully elucidated. In addition, no studies exist that have included a physiological approach to energy allocation dynamics in reproductive strategies.

A greater understanding of the phenotypic plasticity involved in the adaptation of non-native fishes to local conditions is an important tool for control programs [38]. According to Ribeiro and Leunda [39], there is a clear need for biological information about *G. lozanoi* population traits across the Iberian Peninsula and especially in its non-native river basins, which could be an important knowledge gap hampering effective control and management. Moreover, the life history variability of fish seems to play a key role in driving invasion success and significant intraspecific plasticity has often been observed in the process of acclimatization to new habitats [40,41]. However, nothing is known about the intraspecific variability of *G. lozanoi* along gradients in the same watershed or in terms of comparisons between populations located at different flow regimes. Taking into account that reproductive investment can be understood as the result of the energy balance between survival, growth and reproduction demands in order to achieve the most competitive strategy [7,15], the goal of this study was to analyse the reproductive traits and the energy balance of *G. lozanoi* in an invaded Mediterranean basin. The two main hypotheses proposed were: firstly, the reproduction strategy could show inter-population plasticity due to different flow scenarios and it is expected to be closer to an opportunistic strategy in fluvial sectors with the most unpredictable flow regimes. Secondly, energy allocation mechanisms should be closer to income breeding strategies according to its reproductive traits. For this purpose, the following specific objectives have been proposed: (a) to describe the reproductive and fish condition cycles of *G. lozanoi* in five fluvial sectors; (b) to describe the energy allocation (proteins and lipids contents) among tissues in this

target fish; and (c) to analyse the relationships among reproductive traits, fish condition and patterns of energy allocation.

#### **2. Materials and Methods**

#### *2.1. Ethical Information*

The care and use of experimental animals complied with University of Murcia and Spanish Law 32/2007 and RD 53/2013 animal welfare laws, guidelines and policies, as approved by Ministry of the Presidency, Relations with the Courts and Democratic Memory. The specific permit AUF20150077 was approved by the Regional Ministry of Water, Agriculture and Environment of Murcia and Castilla-La Mancha and it allowed us to sacrifice the non-native species of the Segura River Basin.

#### *2.2. Study Area*

This study was conducted in the upper and middle parts of the Segura River Basin (drainage area of 18,870 km<sup>2</sup> ), a highly regulated river located in the southeast of the Iberian Peninsula (Figure 1). The Segura River Basin is characterised by a typical Mediterranean climate with a pronounced spatial and seasonal hydrological variability. Currently, this basin is highly regulated in terms of irrigation supply and human water demands, which have greatly modified the natural flow regime, resulting in changes in flow magnitude and a reverse seasonal flow pattern in some areas [42,43]. Supplementary Material 1 provides an accurate description about the flow regime characteristics of the sampled streams.

**Figure 1.** Sampling sites location for *Gobio lozanoi* in the Segura River basin at south-eastern Iberian Peninsula, Spain.

Sampling fluvial sites were selected following flow regime criteria. They were located along the longitudinal gradient of the basin in different hydrological sectors separated by large dams (Figure 1; Table 1). The flow characteristics ranged from natural (TUS) to reverse flow regimes (SE3 and SE4) (Supplementary Material 1, Figure S1 and Table S1). Each sampling site was characterised by the following six environmental variables (Table 1): altitude (Alt) (meters above sea level), ecological status sensu EU Water Framework Directive (Status) (with the following categories: 1 = high; 2 = good; 3 = moderate; 4 = poor), conductivity (µS cm−<sup>1</sup> ), Fluvial Habitat Index (FHI) [44], Riparian Quality Index (RQI) [45] and 2015 mean monthly temperature (◦C). These six selected environmental variables are among the ecological drivers that play a significant role in the freshwater fish ecology, and also in biological invasion processes by fishes, of the Mediterranean-type rivers [39,40].

**Table 1.** Habitat variable values of each sampling site where *Gobio lozanoi* populations were assessed in the Segura River Basin.


Altitude (meters above sea level), ecological status (1–4); water conductivity (±0.1); Fluvial Habitat Index (IHF); Riparian Quality Index (RQI), and water temperature (Mean and 95% Cl Confidence limits).

> Since first recorded in the upper region in the 1980s, *G. lozanoi* has been registered in fluvial sectors and reservoirs along the Segura River Basin [23,27]. The ichthyofauna of this basin is characterised by low species richness and the fish assemblage composition is dominated by non-native species [27]. The studied species share resources and habitats with native cyprinids, such as the southern iberian barbel *Luciobarbus sclateri* (Günther, 1868) and the south iberian chub *Squalius pyrenaicus* (Günther, 1868), and with several nonnative fish to the basin, such as the pumpkinseed *Lepomis gibbosus* (Linnaeus, 1758), bleak *Alburnus alburnus* (Linnaeus, 1758), common carp *Cyprinus carpio* (Linnaeus, 1758), iberian straight-mouth nase *Pseudochondrostoma polylepis* (Steindachner, 1864), northern pike *Esox lucius* (Linnaeus, 1758), pike-perch *Sander lucioperca* (Linnaeus, 1758) and largemouth black bass *Micropterus salmoides* (Lacepèd, 1802).

#### *2.3. Field Sampling and Laboratory Procedures*

Fish were collected by electrofishing (1800 W DC generator at 200–300 V, 2–3 A) during a one-year study period (January–December 2015). One fisherman with an electric dip-net, supported by two assistants each with a non-electric dip-net, removed fish following a zigzagging and upstream direction of each sampling stretch (100 m long), which was blocked off with barrier nets (samplings were carried out between 10 a.m. and 4 p.m.). Samples were taken once every two weeks in spring and summer, and monthly during the rest of the year (Supplementary Material 1, Table S2). A total of 2333 *G. lozanoi* were caught (TUS: 437; SE1: 478; SE2: 385; SE3: 485 and SE4: 548) and, in accordance with Spanish regulations, immediately sacrificed in a water tank with an overdose of anaesthetic solution (1:10 solution of clove oil dissolved in ethanol 70%), before being placed on ice and then they were stored at −20 ◦C in the laboratory.

Fork length (*L*<sup>F</sup> ± 1 mm), total and eviscerated masses (*M*<sup>T</sup> and *M*<sup>E</sup> ± 0.1 g) and organ masses (hepatic and gonad, *M*<sup>H</sup> and *M*<sup>G</sup> ± 0.001 g) of a subsample of 1982 fish were recorded (TUS: 382; SE1: 403; SE2: 365; SE3: 366 and SE4: 466). Gonads were visually inspected for sex determination (male, female or immature), and also to determinate the reproductive stage (i.e., quiescence, maturation, spawning and postspawning). A subsample of 133 mature specimens (110 females, TUS: 20; SE1: 25; SE2: 24; SE3: 17 and SE4: 24, and 23 males, TUS: 13 and SE4: 10), with fork lengths ranging from 7.2 to 11.2 cm was used to estimate fecundity, oocyte size and physiological macronutrients (protein and lipid content in tissues). Due to protein and lipid quantification methods, there were not enough testis masses to perform physiological analysis in every sampling site. To quantify protein and lipid content in the muscle, liver and gonad, samples were weighed and protein levels were determined using the method of Bradford (1976) [46] and expressed

as percentages. Total lipids were extracted following the method of Folch et al. (1957) [47]. Samples were weighed and homogenized in 5 mL of chloroform/methanol (2:1 *v/v*) and washed with KCl (0.88% *w/v*). The weight of lipids was determined gravimetrically after evaporation of the solvent and expressed as percentages. Finally, these fish were aged, counting true annuli from scales taken between the lateral line and dorsal fin origin.

Ovarian development and fecundity were studied using the gravimetric method [48]. To make sure that the ovary was homogenous in structure (number and size of oocytes), small portions of anterior, middle and distal parts were compared, and no significant differences were found (ANOVA, *p* > 0.05). Therefore, all oocytes present in a subsample from the mid-region of the right ovarian lobe (5% of the total weight of the gonad) were placed in Gilson liquid, shaken periodically to soften gonadal tissue and to disperse oocytes, washed with distilled water and preserved in 70% ethanol for following analyses [37]. Image processing program ImageJ v1.80 (available at https://imagej.nih.gov/ij/) was used to count and measure oocytes. Fecundity was determined in 39 mature females caught from April to July. Fecundity was analysed at three levels: potential (FecPOT), absolute (FecABS) and batch fecundity (FecBAT). These levels were determined by counting the total number of opaque and vitellogenic oocytes, total number of vitellogenic oocytes and total number of vitellogenic oocytes of the last mode representing size before spawning, respectively [48,49]. Oocyte size at each level of fecundity (ØPOT, ØABS, ØBAT) and maximum diameter (ØMAX) were assessed.

#### *2.4. Statistical Analyses*

Sex-ratio was analysed for the whole population and in every sampling site. The degree of significance of the obtained results was established in χ <sup>2</sup> at a *p*-value of *p* < 0.05. Linear regressions of fecundity to fork length were fitted by least-squares method to log-transformed data.

Analyses of length-mass relationships were performed to study temporal variation in somatic condition (SC), hepatosomatic condition (HC) and gonadal activity (GSI) using the predicted values of *M*E, *M*<sup>H</sup> and *M*<sup>G</sup> from analysis of covariance, respectively. The statistical approach included the application of a covariance analysis (ANCOVA) using *M*E, *M*<sup>H</sup> and *M*<sup>G</sup> as dependent variables, *L*<sup>F</sup> as the covariate (log-transformed data) and reproductive stage (quiescence, maturation, spawning and postspawning stage) as a factor. The analysis was developed by sampling site and sex separately. Differences between dependent–covariate relationships were tested to check that the covariate by-factor interaction (homogeneity of slopes) was significant (*p* < 0.05). If the covariate by-factor interaction was not significant, standard ANCOVA was applied to obtain predicted values (predicted *M*E, *M*<sup>H</sup> and *M*<sup>G</sup> values). When differences were found, a post hoc Bonferroni test for multiple comparisons was performed. Student's *t*-test was used to evaluate differences in fish conditions (somatic and hepatosomatic condition), gonadal activity, and protein and lipid content between sexes.

Analyses of variance (ANOVA) were performed to determine differences in protein and lipid content among the different temporal phases and to evaluate differences among sampling sites at each reproductive stage in fish conditions, gonadal activity, fecundity, oocyte diameter and percentage of proteins and lipids in tissues, followed by the Tukey HSD (honestly significant difference) test post-hoc comparisons if significant differences among populations were found. When data did not show homogeneity of variances, Welch's analysis of variance (ANOVA) followed by T3 of Dunnett for pairwise multiple comparisons were used. The non parametric tests of the Kruskal–Wallis H-test and Mann– Whitney U-test were used when data did not fit normal distribution. Relations between fish condition, gonadal activity, fecundity, oocyte diameter and percentage of proteins and lipids by tissue were analysed using Spearman's correlation coefficients.

Size of first maturity was estimated after running binary logistic regressions (immaturemature individuals) for each sampling site by sex (Supplementary Material 2). Differences

in first maturity among sampling sites were tested using generalised estimating equations (GEE), with binomial errors and the logit link function.

#### **3. Results**

#### *3.1. Reproductive Cycle and Temporal Variation in Fish Condition*

The results of the ANCOVA test to estimate the effects of the factor on the *L*F-*M*E, *L*F–*M*<sup>H</sup> and *L*F–*M*<sup>G</sup> relationships are shown in the Supplementary Material 3, Tables S3 and S4. In both sexes, significant differences were observed among reproductive stages in the five sampling sites for fish SC, HC and GSI (Figure 2; Supplementary Material 3, Tables S3 and S4).

**Figure 2.** Temporal variation in gonad activity (predicted *M*<sup>G</sup> values, *M*<sup>G</sup> is gonad mass) along the study period for the five studied populations (TUS, SE1, SE2, SE3 and SE4) for both sexes of *Gobio lozanoi*. The lines represent the adjusted model *Loess* for each population.

The reproductive cycle was fitted by the ANCOVA predicted *M*<sup>G</sup> values as a Gonadosomatic index (GSI) showing significant temporal differences in the gonadal activity (Figure 2). Both sexes showed a similar reproductive cycle in which four temporal stages were identified based on the GSI values (Figure 2): (1) the quiescence stage, with low values of GSI in winter; (2) the maturation stage, when GSI values rise up steeply—especially in March—and reach the maximum values at the beginning of May in females (except females from SE2) and also in males from TUS, SE3 and SE4, however, in males from SE1 and SE2, maturation was observed in late May; (3) the spawning stage, when GSI values are steady or decreasing moderately until late summer or early fall, and (4) the regression stage or postspawning, when GSI continues to decrease and reaches minimum values (Figure 2). The female gonadosomatic index was significantly higher than the male's in all reproductive stages (Student's *t*-test; quiescence stage: t = −14.56 *p* < 0.001; maturation stage: t = −28.97 *p* < 0.001; spawning stage: t = −20.21 *p* < 0.001; postspawning stage: t = −11.54 *p* < 0.001). Significant differences in the gonadal activity among reproductive stages were found in the total population (Figure 3) and when sampling sites were analysed individually for both sexes (Table 2). The GSI was significantly different among sampling sites for the total of fish (both males and females) (females Kruskal–Wallis, χ <sup>2</sup> = 46.17, *p* < 0.001; males Kruskal–Wallis, χ <sup>2</sup> = 20.09, *p* < 0.001), SE1 and SE2 populations showing higher GSI values and SE4 the lowest values in both sexes (Table 2).

**Figure 3.** Mean predicted *M*G, *M*<sup>E</sup> and *M*<sup>H</sup> values by ANCOVA (*L*<sup>F</sup> as covariate) in each reproductive stage (quiescence, maturation, spawning and postspawning) for both sexes of *Gobio lozanoi*. Letters show significant differences (Welch's analysis of variance *p* < 0.05 and T3 of Dunnett post hoc tests) among reproductive stages in females (capital letters) and in males (lowercase letters).

**Table 2.** Mean predicted *M*E, *M*<sup>H</sup> and *M*<sup>G</sup> values by ANCOVA (*L*<sup>F</sup> as covariate) in each reproductive stage for both sexes of *Gobio lozanoi*. ANOVA results of comparison of somatic condition (SC), hepatosomatic condition (HC) and gonad activity (GSI) among reproductive stages in each sampling site are showed and significant *p*-values are included. Codes of sampling sites (TUS, SE1, SE2, SE3, and SE4) from the Segura River Basin were included.


† Means no normalised data and Kruskal–Wallis analysis of variance.

The somatic condition (SC) and hepatosomatic condition (HC) varied over the reproductive cycle with the exception of SC of males (Figure 3), and they showed significant differences among reproductive stages in both sexes in most sampling sites when they were analysed individually (Table 2). Male SC was significantly higher than for the females in most reproductive stages (Student's *t*-test; quiescence stage: t = 3.83, *p* < 0.001;

maturation stage: *t* = 4.01, *p* < 0.001; spawning stage: *t* = 4.29, *p* < 0.001), whereas female HC showed higher values than the males' during maturation and at spawning (Student's *t*-test; maturation stage: *t* = −7.13, *p* < 0.001; spawning stage: *t* = −5.49, *p* < 0.001). Fish conditions in all males showed significant differences among sampling sites (SC ANOVA, F(4, 598) = 15.56, *p* < 0.001; HC Welch ANOVA, F(4, 236.26) = 15.24, *p* = 0.001), SE3 and SE4 showed the lowest SC and HC values (Table 2). In all females, fish conditions also showed significant differences among sampling sites (SC Welch ANOVA, F(4, 327.68) = 39.99, *p* < 0.001; HC Kruskal–Wallis, χ <sup>2</sup> = 73.99, *p* < 0.001), SE1 showed the highest SC and HS values, while SE3 and SE4 showed the lowest in both conditions (Table 2).

#### *3.2. Population Structure and Reproduction Traits*

*Gobio lozanoi* fish ranged from 1.8 cm to a maximum *L*<sup>F</sup> of 12.3 cm (a male caught in SE3). Total males (*L*<sup>F</sup> 7.6 ± 1.6 cm) were significantly longer than females (*L*<sup>F</sup> 7.1 ± 1.5 cm) (Student's *t*-test, t = 5.55, *p* < 0.001). Both sexes show significant differences among sampling sites in the total data (females ANOVA, F(4, 922) = 16.99, *p* < 0.001; males Welch ANOVA, F(4, 308.18) = 2.57, *p* = 0.038). Shorter females were found in TUS (6.5 ± 0.2) and SE3 (6.8 ± 0.2) and larger ones in SE1, SE2 and SE4 (7.5 ± 0.2, 7.4 ± 0.2 and 7.4 ± 0.2, respectively), while in males individuals in SE2 (7.9 ± 0.3) were larger than in TUS (7.2 ± 0.3).

The overall sex-ratio (696 males, 928 females) was significantly skewed towards females (χ <sup>2</sup> = 33.14, *p* < 0.001) in the whole study period, with females being significantly more abundant in all sampling sites with the exception of SE3, which did not show differences between males and females (χ <sup>2</sup> = 1.43, *p* = 0.23).

Length at first maturity in males ranged between 3.55 cm *L*<sup>F</sup> in SE3 and 6.26 cm *L*<sup>F</sup> in SE2, while female range was between 4.28 cm *L*<sup>F</sup> in SE3 and 6.60 cm *L*<sup>F</sup> in TUS. Above these lengths all individuals were considered mature (Figure 4). However, only significant differences in length at first maturity were found among sites in males (GEE: Wald-χ 2 (4) = 13.57 *p* = 0.009), finding significantly larger fish at first maturity in TUS, SE1 and SE2 populations (Figure 4).

**Figure 4.** Predicted probability of maturity according to fork length for females and males for the five studied populations (TUS, SE1, SE2, SE3 and SE4) of *Gobio lozanoi*.

Oocytes larger than 0.25 mm in diameter were considered opaque and all oocytes above 0.55 mm of diameter were vitellogenic. Fecundity data from each sampling site are summarised in Table 3. No significant differences were found in fecundity and oocyte diameters by age (ANCOVA, *p* > 0.05) and fork length was not significant as a covariable when oocyte diameters were analysed, which indicates no effect of fish size on egg diameters in the studied fish. Significant differences were found in potential (ANCOVA F(1, 4, 39) = 3.27, *p* = 0.023) and absolute fecundity (ANCOVA F(1, 4, 39) = 2.90, *p* = 0.037) among sampling sites. SE1 showed the highest number of oocytes and SE3 showed the lowest ones at a given length (Bonferroni post hoc: *p* = 0.023 and *p* = 0.037, respectively). Only the diameter of batch fecundity showed significant differences among sampling sites (ANCOVA F(1, 4, 37) = 9.96, *p* < 0.001). Batch oocyte diameters in TUS and SE1 populations were larger than in SE2, SE3 and SE4 (Bonferroni post hoc: *p* < 0.001) (Figure 5).

**Table 3.** Mean, minimum and maximum values of potential fecundity (FecPOT), absolute fecundity (FecABS) and batch fecundity (FecBAT) of *Gobio lozanoi*. Linear regression of fecundities and fork length (*L*F) are shown (significant *p*-values are included). Codes of sampling sites (TUS, SE1, SE2, SE3, and SE4) from the Segura River Basin were included.


**Figure 5.** Estimated marginal means (by ANCOVA) ± IC 95% at 9.0 cm of fork length for oocyte number and diameter of opaque plus vitelogenic oocytes (potential fecundity; white bars), and of vitelogenic oocytes (absolute fecundity; grey bars) and oocytes of batch fecundity (dark grey bars). Letters show significant differences (ANCOVA, Bonferroni post hoc tests) among sampling sites.

#### *3.3. Protein and Lipid Contents*

Significant differences in the percentages of proteins and lipids were found in tissues during the whole period studied (Table 4). Females showed maximum protein values in the gonads and maximum lipid values in the liver, while males presented highest protein and lipid values in the liver (Table 4). Comparisons between sexes revealed that females showed significantly higher protein and lipid percentages than males in the muscles (Student's *t*-test, *t* = −4.46, *p* < 0.001; *t* = −3.97, *p* < 0.001, respectively), while the percentage of protein in the liver was higher in males (Student's *t*-test, *t* = 4.51, *p* < 0.001). In the gonads, the ovary protein content was higher (Student's *t*-test, *t* = −9.75, *p* < 0.001), but the testis showed higher values of lipid content (Student's *t*-test, *t* = 3.14, *p* = 0.005).

Percentages of protein and lipid content in tissues showed significant differences during the reproductive cycle and the lipid–protein dynamic was different between sexes (Figure 6). The lipid percentage in the muscle decreases from quiescence to spawning stages in both sexes (ANOVA: female F(3, 106) = 11.26, *p* < 0.001; male F(3, 19) = 6.33, *p* = 0.008) (Figure 5). In the liver, protein percentages in females reached higher values at spawning (ANOVA F(3, 104) = 5.32, *p* = 0.002), but no differences were found in the percentages of lipid contents in this tissue (Figure 6). No significant differences were found in the percentages of protein and lipid contents in the liver in males during the reproductive cycle. The protein percentage in the ovary increased until the spawning stage (ANOVA F(3, 103) = 8.73, *p* < 0.001), but decreased in testis (ANOVA F(2, 19) = 9.670, *p* = 0.001), whereas no significant differences were found in gonadal lipids during the reproductive cycle (Figure 6).

**Table 4.** Percentage of lipids and proteins in each tissue of *Gobio lozanoi.* All *p*-values in Kruskal–Wallis test are significant (<0.001).


*n*, Number of individuals, range of minimum and maximum values and Kruskal–Wallis test.

**Figure 6.** Mean and ± IC 95% percentages of proteins and lipids in muscle, liver and gonads by reproductive stages. White bars represent female values and grey bars represent the male ones. The letters show significant differences (ANOVA, *p* < 0.05) among reproductive stages by post hoc comparison Tukey test. Capital letters for female data and lower case letters for male data.

#### *3.4. Fish Metrics Relationships*

Fish conditions (SC and HC) and GSI were positively correlated with fecundity and the percentage of ovary proteins. SC had a positive relationship with batch oocyte diameter only, whereas HC and GSI were positively correlated with potential, absolute and maximum oocyte diameters (Table 5). Fish conditions and GSI were positively correlated with the percentage of ovary protein, whereas SC and HC had a negative relationship with the percentage of muscle lipids. Moreover, the percentages of ovary proteins and lipids were positively correlated with absolute fecundity and oocyte diameters (ØPOT, ØABS, ØBAT, ØMAX). Absolute oocyte diameter (ØABS) was positively related to the percentage of proteins in the liver and negatively related to the percentage of muscle lipids (Table 5).

**Table 5.** Correlation matrix of fish somatic condition (SC), hepatosomatic condition (HC), gonad activity (GSI), fecundity, oocyte size and proteins and lipids percentages by tissues in females of *Gobio lozanoi*. Spearman's coefficient above the diagonal and *p*-values below the diagonal.


FecPOT, potential fecundity; FecABS, absolute fecundity; FecBAT, batch fecundity; ØPOT, oocyte size at potential fecundity; ØABS, oocyte size at absolute fecundity; ØBAT, oocyte size at batch fecundity; ØMAX, maximum oocyte size; % PLIV, percentage of proteins in liver; % PMUS, percentage of proteins in muscle; % PGON, percentage of proteins in gonads; % LLIV, percentage of lipids in liver; % LMUS, percentage of lipids in muscle; % LGON, percentage of lipids in gonads; \*\* significance level of *p* < 0.01; \* significance level of *p* < 0.05.

#### **4. Discussion**

Reproductive cycles of freshwater fish depend on a set of environmental factors and rheophilic fish, such as the target species, usually need flow requirements to activate migration processes, gonadal maturation and spawning success [50]. Reproduction is

related to stream flow, photoperiod and temperature cues [8,51] and there must be optimal conditions for all these variables to coincide in time for gonadal activation to begin. Similar temporal dynamics of the gonadosomatic index were found in another studied population of *G. lozanoi* in an upper fluvial sector of the Segura River Basin [37]. However, in other non-native populations of *G. lozanoi* located more to the north of the Iberian Peninsula, where environmental factors are different, shorter maturation and spawning periods were observed [35,36].

During this study, several intraspecific differences in reproductive traits among populations inhabiting different hydrological sectors have been observed. Indeed, temporal dynamics of the gonadosomatic index showed two different patterns: one of them increased steeply, reaching a peak GSI value in April and May, just in the most upper sites, and the other one showed a slight GSI increase until June and July. The maturation delay, found mainly in SE2 and SE3 fluvial sectors, could be related to the lack of flow cues, such as spring peak flows present in TUS and SE1. Hydrological sector SE2 did not show any high flow peak during the year and SE3 is located right below the Cenajo dam which starts to release water in March, while other hydrological sectors showed high flows in early February (Supplementary Material 1; Figure S1). Thus, the increase in flow stability or reduction in natural flow disturbances, together with an imbalance between temperatures and flow peaks may be affecting the onset of the gonadal activation [8,52]. Furthermore, the spawning delay observed below the Cenajo dam (SE3) and the disruption of temperature increase (due to hypolimnetic cold water selective releases from the reservoir) may cause gonadal regression or failed oocyte development [9], which could explain the lower GSI values observed in fish inhabiting this fluvial sector.

Fish conditions (somatic and hepatosomatic) showed different patterns between sexes, suggesting that condition investment was not the same for both sexes during the reproductive cycle. The SC patterns of both sexes were not observed in other non-native populations of *G. lozanoi* in the Iberian Peninsula, which showed two peak values of somatic condition at the beginning and at the end of spawning, with minimum values in October [35]. Temporal dynamics of the HC of females were similar to the GSI pattern, increasing at the beginning of the activation stage and decreasing at the end of spawning. In indeterminate batch spawners such as *G. lozanoi* [35,36], oocyte recruitment is continuous during the spawning season and high liver mass (high HC) could confirm an intense liver activity for vitellogenesis, while in determinate batch spawners or total spawners the hepatosomatic activity decreases during the reproductive cycle due to the completion of vitellogenesis prior to spawning [53,54]. Moreover, fish conditions showed differences among different flow regimes during the reproductive cycle. In fact, only in the hydrological sector where flow was constant all year round (SE2) was no significant variability observed for these parameters. No drastic flow events and homogenization of flow conditions may favour the stability of fish investment because fish inhabiting unstable environments with seasonal flash floods may require high levels of energy reserves, such as high somatic and hepatosomatic conditions; a high investment to increase reproductive success [8,55,56]. On the other hand, the unnatural concurrence of very high flows during the reproductive event (maturation and spawning) implies energy redistribution in fish between survivals in suboptimal environments and reproductive investment [7], which could explain the lower values of fish conditions and GSI in these hydrological sectors (SE3 and SE4).

Previous studies of *G. lozanoi* in the Iberian peninsula observed maximum size ranges between 10.1 to 14.0 [23], whereas the population studied here showed a maximum length (FL) of 12.3 cm. The smallest individuals were observed in sampling sites located in the most natural flow conditions (TUS), and the largest ones were observed in SE4 and SE2. Larger maximum sizes of fish populations usually correlate with more stable environments, where abiotic fluctuations, such as flow peaks, are less significant and food sources are more readily available, so lower mortality rates can be observed [57]. Furthermore, low-flow periods, typical of dry summers in the Mediterranean basins, reduce food and habitat

availability and may be affecting growth rates as has been observed in other Mediterranean cyprinids [8].

Hydrologic conditions are, for sure, one of the main drivers responsible for shaping the reproductive success and reproductive strategy used [6]. In this study, the analysed reproductive traits showed significant intraspecific variability which could be related to flow conditions at the basin scale. There were a higher number of females in all populations, apart from directly below the Cenajo dam (SE3). Thus, very high flows could be increasing female mortality rates after reproductive investment, which was higher than male investment; this has been recorded in other non-native populations of *G. lozanoi* in the Iberian Peninsula [36]. In addition, variability in sexual maturity is a compensatory population response to different environmental factors [58,59]. Many studies relate high mortality in populations to early maturation in order to compensate the decrease observed in the number of adults and maximize the egg production capacity [59,60]. In general, sexual maturity of non-native populations of *G. lozanoi* in the Iberian Peninsula was reached at a young age and most of the individuals aged 2+ or greater than 7.0 cm in fork length were mature [35–37]. In this study, the shortest mature males were 3.55 cm (LF) and females were 4.28 cm (LF), representing the smallest sizes found in the whole Peninsula. Highly disturbed areas or extreme environmental conditions and unregulated flow conditions (natural hydrological sectors in this study) are expected to be associated with early maturation, which is typical of opportunistic strategies [3,33]. However, in this study, a shorter length of first maturation was observed in flow regulated sectors, where natural disturbances are buffered, although some other environmental perturbations may be acting as well.

The studied population showed a lower absolute fecundity compared to other populations of *G. lozanoi* in the Iberian Peninsula [35,36]. In spite of this, oocyte diameters (between 0.84 and 0.92 mm) were larger than in other Iberian populations, which scattered oocyte diameters of 0.76, 0.76 and 0.73 mm in the Matarraña, Moros and Ucero rivers, respectively [35,36]. These results could indicate that a trade-off between egg size and fecundity is established [58]. Furthermore, higher fecundity and larger oocytes were observed in more natural flow areas, while populations inhabiting more altered flows and with reverse regimes showed a lower number and size of oocytes. Production of larger oocytes could be a compensatory strategy to produce larger larvae which will be more resistant to low flow stress factors in dry summers, while the production of a high number of eggs can ensure the survival of the species against the high mortality rates of eggs and larvae in areas with very variable and unpredictable flows [58,59]. On the one hand, the first hypothesis of this study suggested an opportunistic life-history strategy (small size, short longevity, early maturity, low fecundity, multiple spawnings per year and long reproductive periods) (*sensu* Winemiller and Rose, 1992 [33]) in more natural flow conditions, because this strategy is more associated with Iberian native and non-native species inhabiting unregulated Mediterranean rivers with strong seasonal flow patterns [61]. On the other hand, characteristics closer to a periodic life-history strategy (large body size, late maturation, high fecundity and a reduced spawning period) would be expected in more predictable and hydrologically stable environments. However, later maturity and a higher number and size of oocytes were observed in more natural flow sectors; later maturity, higher fecundity and small oocytes were found in the most stable flow sector, and populations with earlier maturity and lower number and size of oocytes were found in hydrological sectors with reverse flow regimes. We hypothesised that our studied populations would show intermediate characteristics between opportunistic and periodic life-history strategies, as previously described [34]. The results were not conclusive enough to establish strong correlations between the life strategy of *G. lozanoi* and flow conditions. Although reproductive strategies and reproductive success are directly related to hydrologic conditions [6], the flow effect is probably not strong enough to drastically change the reproductive strategy of populations of *G. lozanoi* that live in the same basin and may share the same genetic pool. The intraspecific variability observed in some reproductive traits suggests a certain degree of effect caused by flow regimes, however, its plasticity

allows the species to survive flow regulation events at several scales, as well as to resist the long-term environmental stress typical of Mediterranean-type rivers [62].

Percentages of lipid contents in liver and gonads were stable during the reproductive cycle in both sexes. The increase in protein contents in females' livers at the beginning of reproduction could suggest synthesis activity in the liver of the yolk and eggshell proteins which are transported to the ovarian tissues for oocyte vitellogenesis and maturation [58,63]. Ovarian protein content also increased during the reproductive cycle in response to the oocyte development and maturation [64,65]. In females, during gonadal maturation ovarian and liver lipid contents did not vary and protein content increased in both tissues. This could indicate that enough energy was available during the spawning to develop gonads and store energy in the liver. Additionally, in the absence of other energy sources, feeding during the reproductive season might provide energy for vitellogenesis [66–68]. The reproduction investment of studied populations strongly depends on food availability and provides rapid transport from ecosystem productivity to reproduction, which may allow continuous adjustments of the reproductive effort to food intake [15,69]. These findings provide evidence of the energy intake of *G. lozanoi* during the reproductive season which is typical of income breeders. However, the decrease in lipid percentage content in muscles during the reproductive cycle in females could be suggesting energy allocation to reproduction from muscle. The use of muscle tissue as an energy source has been documented for several fish, such as salmonids [70]. This pattern could suggest that *G. lozanoi* exhibits an intermediate strategy (income–capital breeding strategy) in which stored energy in muscles is also required for reproduction [71,72].

Higher fecundity and oocyte diameter were correlated with better somatic and hepatosomatic condition, as well as gonadosomatic index, suggesting fish condition plays an important role during recruitment and development of oocytes [73]. Moreover, proteins and lipids of ovary tissue also showed a positive correlation with absolute fecundity and oocyte sizes supporting the fact that a greater mobilization of macronutrients to gonads favours recruitment and oocyte quality. Thus, food availability has an important influence on reserves of protein and lipid in the tissues and there is a food-dependent variation in stored lipid energy which affects the reproductive potential of individual fish [16,74].

#### **5. Conclusions**

In summary, flow conditions have an important effect on some reproductive traits of *G. lozanoi*, reflected as intraspecific variations in the most of studied parameters. However, this intraspecific variability was not conclusive enough to classify populations either as opportunistic strategists in unpredictable flow sectors, or as periodic strategists in areas that show stable flow regimes. Moreover, protein and lipid contents in tissues during the reproductive cycle provide some insight into the energy allocation during the reproduction of this species, which suggests that current food intake is the main—but not only—energy source for this species to reproduce, since they also use part of the energy supplement they store. Hence, *G. lozanoi* can be classified as an income–capital breeder. Comparative studies of reproductive traits and energy balance are a powerful approach to understanding life-history trade-offs of species, and they may serve as excellent models for studies of plasticity and adaptation of breeding strategies to new environmental conditions in exotic species. Further studies are needed to increase the knowledge about phenotypic plasticity in species that may be potential invaders since the lack of information could be hiding negative effects on other species, as well as on the environment.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/2073-444 1/13/3/387/s1. Supplementary Material 1: Flow Characterisation of Sampling Sites. Supplementary Material 2: Immature-Mature Determination. Supplementary Material 3: ANCOVA Results. Supplementary Material 4: Picture of the target species.

**Author Contributions:** F.A.-T. study design, data collection, data analysis and manuscript preparation; M.T. resources, study design, manuscript preparation and review; D.G.-S. data collection and data analysis; F.J.M.-L. resources and data analysis; F.J.O.-P. conceptualization, resources, study design, data collection, data analysis, manuscript preparation and review. All authors have read and agreed to the published version of the manuscript.

**Funding:** Financial support was partially provided by LIFE+ Segura Riverlink (Project LIFE12 ENV/1140). F.A.T. held a doctoral fellowship (FPU13/00235) from the Spanish Ministry of Education.

**Institutional Review Board Statement:** Ethical review and approval were waived for this study, due to the care and use of experimental animals complied with University of Murcia and Spanish Law 32/2007 and RD 53/2013 animal welfare laws.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data is contained within the article or supplementary material.

**Acknowledgments:** The authors would like to thank J.M. Zamora, A. Zamora, J. Franco, A. Guerrero and A. Sánchez for their participation in fish collecting and E. Martínez (EMC I Traducciones) and Catherine Gutmann Roberts for English review. We also are grateful to L. Gabaldón and E. Aledo for helping in the processing of sampling permits.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

#### **References**

