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Article

Trends and Environmental Drivers of Marine Fish Landings in Cuba’s Most Productive Shelf Area

by
Yunier Olivera-Espinosa
1,2,
Yandy Rodríguez-Cueto
3,
Fabián Pina-Amargós
4,5,
Francisco Arreguín-Sánchez
1,
Manuel J. Zetina-Rejón
1,
Kendra Karr
6 and
Pablo del Monte-Luna
1,*
1
Instituto Politécnico Nacional, Centro Interdisciplinario de Ciencias Marinas, La Paz 23096, Baja California Sur, Mexico
2
Centro de Investigaciones de Ecosistemas Costeros, Cayo Coco 69400, Ciego de Ávila, Cuba
3
ProsperIA Social, Mexico City 01780, Mexico
4
Blue Sanctuary—Avalon, Havana 10700, Cuba
5
Centro de Investigaciones Marinas, Universidad de la Habana, Havana 11300, Cuba
6
Environmental Defense Fund, San Francisco, CA 94105, USA
*
Author to whom correspondence should be addressed.
Fishes 2024, 9(7), 246; https://doi.org/10.3390/fishes9070246
Submission received: 10 May 2024 / Revised: 2 June 2024 / Accepted: 20 June 2024 / Published: 23 June 2024
(This article belongs to the Special Issue Assessment and Management of Fishery Resources)
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Abstract

:
Marine finfish landings in Cuba have decreased during the last 30 years. However, in Cuba’s most productive fishing region, certain species, including rays, herrings, and snappers, have had increased landings over the past decade. Despite these anomalies, no comprehensive analysis of the interactions among multispecies landing dynamics, environmental factors, and fishing efforts has been carried out. This study estimates the dynamics of multispecies finfish landings between 1981 and 2017 on the southeastern coast of Cuba. A log-normal generalized additive model (GAM) was fit to evaluate the effects of various environmental and effort-related variables on the total landings. During the period analyzed, the finfish landings and fishing effort decreased by 46% and over 80%, respectively. Despite concerns about overfishing, landings per unit of effort (LPUE) increased by 2.8 times. The total fish landings were significantly related to changes in the fishing effort, coastal vegetation, rainfall, chlorophyll-a, and the Southern Oscillation Index (SOI). This study highlights the changing relationship between the landings and fishing effort, suggesting that LPUE may not accurately reflect true stock abundance. The findings of this study will assist in integrating the dynamics of finfish species, ecosystem status, and management actions for Cuba’s most productive fishing zone.
Keywords:
fisheries; fishing effort; overfishing; landings per unit of effort; generalized additive models
Key Contribution: This study reveals that the decline in multispecies finfish landings along the southeastern coast of Cuba over the past three decades is largely attributable to reduced fishing effort and shifts in local environmental variables and regional oceanographic processes rather than solely to overfishing. It highlights the importance for integrating informal and illegal fishing into management strategies and considering environmental and economic factors to ensure sustainable resource utilization and accurate stock assessments.

1. Introduction

The time series of Cuban marine finfish landings over the last 30 years show a similar pattern to that of Hilborn and Walters’ model of fisheries development, where the total catch increases, peaks, and then decreases [1,2]. The Cuban fishing industry underwent an industrialization phase in the early 1960s [3], accompanied by an increase in finfish landings until the late 1980s, after which landings fell from 29 thousand tons in 1987 to 13 thousand tons in 2015 (Figure S1), leading regional fisheries to a critical state [4,5]. Although primarily operated by state enterprises, the fishery sector is mainly artisanal or small-scale, accounting for 90% of the catches nationwide [6,7]. However, effective management is limited because of the fishery’s data-poor status and the diverse and numerous landing sites, vessel types, fishing gears, and target species.
There are different studies explaining such a pattern. It is argued that since the 1990s, most Cuban commercial fishing resources have been at high risk of overexploitation because fisheries shifted toward smaller, less-valuable species, causing a decrease in both the average trophic level and the size of catches, and even the collapse of several fishery resources [4,5,8]. The overall decline in landings can be attributed to several factors, including the high market value of the target species, the fishing on spawning aggregations, the use of non-selective fishing gear, and the low reproductive potential (e.g., sharks) or low growth rate (e.g., many reef fishes) of many of the exploited species [4]. Other non-fishing factors, such as habitat degradation, are also believed to have affected Cuba’s marine finfish landings [6,9,10]. For example, the construction of numerous dams on rivers to create water reservoirs and the reduction in the amount of nutrients entering the environment from agricultural fertilizers have been identified as significant causes of declining fish populations [5,6,11,12]. However, these conclusions have not been empirically verified.
Specifically, the decline in finfish catches since the 1980s is attributed to a reduction in primary production because of a decline in nutrients, affecting species that feed on plankton, such as herrings. Furthermore, the construction of dams has increased the salinity of shallow water areas and brackish lagoons along the Cuban coast, where most species’ recruitment and nursery areas are found [12,13]. Dam-induced oligotrophication, through sediment and nutrient trapping, can also severely alter the ecological functioning of coastal waters [14]. Mangroves are particularly susceptible to extreme salinity and sediment accretion due to lower freshwater discharge and less sediment flush [15,16]. Alterations in the natural coastal vegetation may have also disrupted the recruitment processes of important finfish species.
Climate variability is among the non-fishing factors that may potentially affect finfish landings. Studies in the wider Caribbean have found that changes in fishery landing compositions are likely related to significant shifts in regional climate processes [17]. Similarly, studies conducted in the Mexican Campeche Bank subarea have demonstrated that climate change and the Atlantic Multidecadal Oscillation (AMO) have significantly impacted fisheries. These studies have linked changes in the sea surface temperature (SST) to declines in key fishery stocks, including the collapse of the pink shrimp fishery and decreases in the annual yields and stock abundance of the red grouper [18,19,20]. In particular, the spiny lobster fishery in Cuba is affected by the cumulative, synergistic effects of human-induced impacts and changes in El Niño and tropical cyclone intensity and frequency [21,22,23,24]. Despite the well-documented impact of climate variability on marine ecosystems and fisheries [25] and its projected effects on fisheries, mainly by altering species’ life cycles, abundance, and distribution [26,27], this factor’s effects on fish species remain unexplored in Cuba.
Although regional trends indicate a continuous decrease, particularly in the southeast region, Cuba’s most productive fishing zone [6], the behaviors of individual species or groups of species present a more complex picture. Notably, landings of key species, like rays, herrings, and snappers, show increasing trends, contradicting the regional overall declining trend [28]. These inconsistencies underscore the complex interplay of factors other than the fishing effort driving finfish populations, which remains poorly understood. It is worth noting that previous studies that have identified non-fishery factors influencing finfish landings in Cuba lack statistically validated analyses that address the interaction of these different factors, particularly in the unique ecological and economic contexts of Cuba’s fisheries.
We hypothesize that local and regional environmental factors may play a significant role in finfish catch trends. Consequently, improvements in management actions could result from considering these factors. The current study aims to fill this gap by studying the temporal variations in historical finfish landings on the southeastern coast of Cuba. Through generalized additive models (GAMs) and considering multiple environmental factors and the fishing effort, this research seeks to provide a nuanced understanding of the drivers behind the current landing trends, aiming to inform more effective management strategies and underscore the necessity for further, rigorous research in this field.

2. Materials and Methods

2.1. Study Area

Cuba’s continental shelf is divided into four administrative fishing zones. The four coastal zones constitute relatively independent fishing areas for management purposes [6]. This study was conducted in the most productive fishing zone, the southeastern zone (Figure 1), which contributes 44% of the national fishing production [6]. Covering two gulfs—Ana María and Guacanayabo—the southeastern zone is dominated by muddy marine habitats interspersed with mixed seagrasses, patch reefs, and numerous small cays surrounded by mangroves [29]. To the north and east, the basin encompasses towns, agricultural areas, and Cuba’s longest river and largest dam. The zone limits to the south are the keys and marine ecosystems of the Jardines de la Reina National Park, one of the most important marine reserves in the Caribbean [30]. More than 55% of the endemic species of the Caribbean coexist on its insular platform, and it is home to some of the most extensive and best-preserved mangroves, seagrasses, and reefs in the region [28].
Fishing-related activities constitute the main sustenance for the coastal communities. However, they have been impacted by multiple stressors, like overfishing, mangrove deforestation, the use of destructive fishing gear, a reduction in the circulation of freshwater flows, and illegal fishing. Additionally, some studies have reported a reduction in fish consumption in Cuba because of extreme weather events and the loss of operational capacity resulting from economic constraints and the deterioration of the fishing fleet [31,32].

2.2. Data Collection

In Cuba, 90% of fishing is carried out by 14 state enterprises operating 705 vessels, 385 of which are between 15 and 20 m long, mainly targeting finfish [6]. Most Cuban fisheries, excluding shrimp fisheries, are considered as being artisanal or small-scale, based on various factors, like boat size, tonnage, and target species [7]. Cuba’s fishing operations are distinguished by the use of a diverse array of fishing gear and methods to target a varied range of resources [7,28].
Fish-landing data from between 1981 and 2017 for the nine fishing ports located in the southeastern zone were obtained from the Cuban Food Industry Ministry’s Fisheries Research Center, reflecting catches solely made and landed in this area. The data comprised 70 species (Table S1), landing port, year, and fishing effort as vessel days-at-sea. Catches in the region come mainly from seine nets, gillnets, traps, longlines, hooks, set nets (banned since 2008), and trawls (banned since 2012) [28].
The landing data were used to construct time series of annual landings per species by summing the landings of each species over the ports. Because of changes in technology and gear efficiency over the period and unreliable reporting of fishing data, days-at-sea may not be an optimal proxy for the fishing effort [33]. Despite these limitations, in Cuba’s data-poor fisheries context, days-at-sea remains the most uniformly recorded metric, offering continuous insight into fishing activities in the area. The minimal management interventions in finfish fisheries and the absence of significant technological advancements because of economic constraints imply that fishing practices have remained relatively stable during the study period [6].
We compiled a database of human-related and environmental variables that correspond to the same period. We used online databases and satellite data to analyze their effects as predictors of finfish landings. These variables include climate oscillations, sea surface temperature (SST) variations, ecological conditions, agricultural impacts, and fishing effort (Table 1, Supplementary Material 1,Figure S2). We selected variables reported in the scientific literature as being significant causes of the decline in finfish landings and that can impact the species’ population dynamics.

2.3. Data Analysis

We conducted exploratory analyses of the landing data to find possible patterns. We used the Hoeffding test to analyze the relationship between the fishing effort and the species compositions of the landings. The Hoeffding test is a non-parametric rank-based measure of association that detects more general departures from independence [36], including non-linear associations [37]. To further our analysis, we conducted exploratory analyses to evaluate the effects of various environmental and effort-related variables on the total landings. Because the total landings are a positive continuous variable and our preliminary explorations indicated non-linear relationships between the landings and predictors, we fit both a log-normal and a gamma generalized additive model (GAM). We retained the log-normal GAM because both models had the same fit.
Before proceeding with the analysis, we examined the data for outliers and multicollinearity. Collinearity was evaluated using the variance inflation factor (VIF), with a threshold of VIF > 3 [38]. As a result, the variables Fertilizers, ACE, Caribbean SST, and AMO, and the AMO 9- and 67-year cycles were excluded from the model.
The final model is specified as follows:
log ⁡ Landings = β 0 + s 1 Effort + s 2 Rainfall + s 3 Dams + s 4 Vegetation + s 5 Chl - a + s 6 SST + s 7 SOI + s 8 AMO _ 26 + ϵ
where s i ⋅ represents a smooth function for the i th predictor, and ϵ is the normally distributed error term. The model was estimated using the restricted maximum likelihood (REML) method.
A Shapiro–Wilk test indicated that the model residuals did not deviate significantly from normality (W = 0.98, p = 0.73). An autocorrelation function (ACF) analysis showed no evidence of temporal autocorrelation. Additional visual inspections of the residuals against fitted values revealed no significant issues (Figure S3).
All the analyses were conducted using R 4.4.0 [39], the Hoeffding test with the correlation 0.8.5 package [37], and the GAM with the mgcv 1.9.1 package [40]. Model predictions were extracted with the ggeffects 1.6.0 package [41].

3. Results

3.1. Exploratory Analysis of the Landings

Finfish landings in the southeastern region of Cuba decreased by 46% from 1981 to 2017, with 56 out of 70 species exhibiting negative changes (Table S1, Figure S4a). Landings went from 7 thousand tons in 1981, at the beginning of the time series, to just under 4 thousand tons in 2017 (Figure 2a). Likewise, the fishing effort decreased by over 80%, from over 47 thousand days-at-sea in 1981 to 9 thousand in 2017 (Figure 2b). Using the landing and effort values, we estimated that the landings per unit of effort (LPUE) increased 2.8 times during this period (Figure 2c). Notably, 37 out of 70 species showed positive trends in LPUE (Table S1, Figure S4b). Despite the decrease in the fishing effort, the number of landed species remained stable over time (rounded mean: 61 ± 2 species) (Figure 3), and no relationship between the fishing effort and the compositions of the landings was found (Hoeffding test: D = −0.004, p = 0.42). The most common landed species was the Atlantic thread herring (Opisthonema oglinum [Lesueur, 1818]), with the highest annual landings except for the years 2005 and 2007, when rays (Rajiformes) displaced it, and in 2017, when mojarras (Gerreidae) became the most-landed species.

3.2. Influences of Environmental Factors on Finfish Landings

The log-normal GAM explained 94% of the variance in the finfish landings’ time series. The model indicated statistically significant relationships between the total finfish landings and five environmental variables (Table 2, Figure 4). The results showed a direct relationship between the fishing effort and landings, with increasing landings as the effort increased. Furthermore, the model indicated a positive linear relationship between the natural vegetation area and landings. Similarly, the SOI exhibited a positive linear relationship with landings. Conversely, rainfall and chlorophyll-a had non-linear relationships with the total landings. The former had mainly negative effects, while the latter had positive effects up to a point, where higher index values had negative effects. Other variables, such as water reservoir (dam) area, SST, and the 26-year AMO cycle, had no statistically significant effects on the total landings in the region.

4. Discussion

4.1. Finfish Landings

A critical question in this study is whether the landings or LPUE serve as reliable indices of stock abundance, and if so, under what assumptions. Unfortunately, there is a lack of data for Cuban commercial marine finfish species against which to compare catches. The only information available is historical landings of target species (1981–2017) and a single fishing-effort time series. As shown in Figure 2 and corroborated by the GAM model, there is a consistent positive relationship between the total landings and fishing effort over the 37-year period, which contradicts the expected theoretical non-linear (parabolic) relationship. This discrepancy suggests that the LPUE may not accurately reflect the true stock abundance and could indicate that the fishery has been switching target species.
When the landings and fishing effort change together consistently through all the stages of a fishery’s development, it becomes difficult to discern whether changes in catches are driving changes in the fishing effort or vice versa. For example, the rapid declines in the landings and effort, beginning in 1987, coincided with a severe economic crisis in Cuba following the dissolution of the Soviet Union [31,42,43]. This crisis led to fuel shortages and a shift to primarily export-oriented fishing activities [44], suggesting that the fishing effort may be the primary driver of catches.
In addition, the crisis reduced the availability of fertilizer for agricultural purposes, leading to a reduction in nutrient runoff, which is likely to affect primary production and fish stocks [5,11]. Conversely, a critical environmental event occurred in 2005, when Hurricane Dennis, a category 4 storm, hit the region, causing significant runoff in coastal habitats [45,46]. However, fishing activities resumed shortly thereafter, increasing landings of Atlantic thread herring, the main species in the study area. Such an increase in landings could indicate a positive impact of the hurricane on the Atlantic herring population despite the widespread coastal damage. These two events suggest that catches may reflect the underlying abundance of the stock and influence the subsequent fishing effort.

4.2. Environmental Variables Affecting Finfish Landings

The reduction in Cuban finfish landings has also been attributed to the decrease in the nutrient load in coastal areas because of the damming of rivers and the reduction in fertilizers in agriculture [5,6,11,12]. Similar impacts caused by dam construction have been recorded in the Black Sea [47], cited in [12], the Mediterranean Sea [48,49], and the Gulf of Mexico [50]. In the 1960s, Cuban water resources were limited, and the government established a dam construction program to mitigate the intense and prolonged drought in 1961–1962 and the severe flooding caused by hurricanes [15]. Since then, most Cuban rivers have been dammed, with a total capacity of 9 billion m3 across 242 water reservoirs [51]. According to Baisre [52], cited in [11], Cuban marine coastal fisheries depend primarily on river discharge for nutrients because of Cuba’s location in the oligotrophic Caribbean Sea, lack of coastal upwelling processes, and minimal tidal range. Changes in freshwater input can affect sediment and nutrient fluxes, affecting coastal marine productivity [17]. However, in our study, changes in the water reservoir area had no statistical support as a plausible explanation for the landing trends. This is likely because the river damming began two decades before our landing time series and has remained stable since 1992 [15].
Although fertilizer use was not directly analyzed in this study because of the collinearity with the fishing effort, its influences on nutrient availability and marine productivity should be considered. According to similar patterns observed between the fertilizer use and fishing effort, the decline in landings may be caused by decreased fishing effort and diminished nutrient input in coastal waters. However, it is worth noting that the southeastern region appears to be more stable and shows fewer seasonal variations than Cuba’s other fishing zones, mainly because it is deeper and receives moderate river drainage [13,53]. Additionally, it is possible that domestic and industrial effluents partially compensate for the reduced river flow and decreased nutrient supply [15]. Nutrient imports may occur through (a) groundwater contributions facilitated by the limestone rocks that make up the soils; (b) enhanced rainwater drainage given by the orographic slopes along the longitudinal axis of the main island; (c) increases in untreated or partially treated urban and industrial effluents; (d) increases in fertilizer and irrigation in rice paddies, especially in estuarine areas, like the Cauto River swamp located in the basin of the current study area; and (e) the runoff of swamps [15]. These factors could explain why there was no evidence of lower inorganic nitrogen and phosphate concentrations in coastal waters after comparing 1972–1973 and 1990–2000 [15]. This may be why fast-growing plankton-feeder species, like the Atlantic thread herring, dominated most of the compositions of the landings between 1981 and 2017.
A positive relationship was observed between the fish landings and Southern Oscillation Index (SOI), a measure of large-scale oceanographic patterns. This relationship may be because of the favorable conditions for marine productivity during a shift toward La Niña events [54], characterized by higher SOI values [55]. Such events can increase nutrient availability by increasing winds and thickening the mixing layer, affecting nutrient distribution, potentially increasing primary productivity, and benefiting fish populations and landings [56,57]. Conversely, there have been observed declines in fish species’ richness, density, and biomass on reefs and mangroves in Cuba, which are attributed to fishing pressure and the negative effects of the El Niño weather pattern. This phenomenon is characterized by higher temperatures in the water, which cause coral bleaching and algal overgrowth, and is further compounded by increased nutrient loads [6,58,59].
Notably, the relationships among the landings, rainfall, and chlorophyll-a were non-linear. From low to moderate levels of these variables positively affect landings, likely because of optimal nutrient inputs and primary productivity. However, excessive rainfall or excessively high chlorophyll-a concentrations, which can indicate algal blooms or ecosystem imbalances, may have negative impacts on fish populations [60,61]. Similar non-linear relationships between fishing and chlorophyll-a concentrations have also been observed for the skipjack tuna, the yellowfin tuna, and the purpleback flying squid in Asia [62,63,64]. The positive relationship between natural vegetation areas and fish landings underscores the importance for preserving coastal habitats. It is likely that natural vegetation provides essential nursery areas, food sources, and shelter for fish, thus promoting recruitment processes and population growth [30,65,66,67].
The potential interactions among these predictors further highlight the complexity of the marine ecosystem. For example, the positive effects of natural vegetation may be mediated by its role in regulating coastal water quality and mitigating the effects of excessive rainfall or algal blooms [68,69,70]. Similarly, the influence of the SOI on landings may be modulated by its effects on local rainfall patterns and phytoplankton abundance [71,72]. The lack of significant relationships between landings and variables such as SST and AMO cycles suggests that further research is needed to explore other potential influences on fish landings. The spatial variability of fishing activities was not considered in this study because of the lack of precise definitions for fishing areas (except for shrimp trawling) and the relatively homogeneous regional habitat, which is characterized by shallow muddy bottoms, seagrass beds, and mangrove forests [7,29].

4.3. Management Considerations

It is important to consider the composition and condition of Cuba’s fishing fleet, which significantly impacts the fishing effort and productivity. Detailed fleet analyses, such as those provided by Adams and García-Álvarez [32], highlight that many vessels in use are remnants from the Soviet period, facing challenges because of a lack of spare parts and maintenance difficulties [3,44]. The fishing sector in Cuba comprises 3376 state-employed commercial fishers, 245 subsistence fishers, 17,600 recreational fishers, and 18,638 private commercial fishers, with an estimated 2500 fishers and 1000 vessels operating illegally [31].
The current fishing crisis in Cuba has prompted suggestions to reduce fishing efforts as a solution. However, this approach has increased informal and illegal fishing practices, as fishers struggle to supplement their income [31]. Therefore, a comprehensive management approach that considers estimating social factors and both informal and illegal fishing efforts and landings is necessary. Furthermore, it is essential to consider the impacts of climate change and extreme events on the fishing industry. Cuba’s aging population [73,74] and outdated fleet pose significant challenges to the sustainability of the fishing sector. The country may be experiencing a shortage of younger fishers entering the profession, leading to a decline in available labor, similar to trends observed in countries such as the United States and Japan [75,76,77]. The labor shortage, coupled with an aging fleet, could also result in a reduction in fishing efforts and catch levels, which will have detrimental impacts on the productivity and feasibility of Cuba’s fisheries. Cuba has been working toward ecosystem-based fisheries management (EBFM) since the 1990s. This approach recognizes the need to understand how shifts in ecosystems’ natural and human components impact the ecosystem’s function and scale. The state has declared marine protected areas (MPAs), special use areas, and integrated management areas [78]. Educational workshops and social programs have been developed to promote sustainable fishing practices [79,80]. Vulnerability analyses have been carried out on species of economic interest [6], and projections have been made under different management strategies [81]. The recent approval of the first Cuban fisheries law in 2020 is a significant milestone in this regard, which aims to establish fisheries management under the principles of conservation, sustainable use, precautionary approaches, and the implementation of scientific technological criteria.
It is important to note that regional oceanographic events can impact local Cuban fisheries, and, therefore, management strategies must be tailored to the specific ecosystem state. Because of the multispecies nature of Cuban fisheries [82], single-species management may not be sufficient to recover overexploited populations [6]. However, EBFM may only achieve satisfactory results if the data scarcity issue is addressed. Cuban fishing authorities should expand their cooperative efforts with universities and environmental research centers. New studies should expand catch-size composition measurements and prioritize fishery-independent stock assessments with traditional surveys as well as alternative methods, such as the MPA fish density ratio [83] and close-kin mark-recapture [84]. Additionally, incorporating economic viability measures, such as the fishery essentiality index [85] and bioeconomic models [86], can complement EBFM by accounting for the economic drivers behind fishers’ behavior, including informal and illegal fishing efforts.

5. Conclusions

This study investigated the contributions of fishing effort and environmental variables to the current trend of multispecies finfish landings on the southeastern coast of Cuba. Our findings indicate that the decline in finfish landings on the southeast coast of Cuba over the last 30 years is not solely attributed to overfishing and the reduction in nutrient imports in coastal areas. Instead, we found that the decrease in the fishing effort and changes in coastal vegetation, rainfall, chlorophyll-a, and oceanographic processes (SOI) were the main drivers of the landings in the region. These findings have important implications for fisheries management in the area, highlighting the need to include informal and illegal fishing effort and landings and the importance for performing stock assessments to not rely on the assumption that landings serve as a proxy for stock abundance. Moreover, our study underscores the need to recognize the effects of changing environmental patterns on fishery landings and develop reference points specifically tailored to each unique ecosystem state. These reference points can inform specific management actions that match stock dynamics and ecosystem conditions.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/fishes9070246/s1: Table S1: Overview of finfish landings in Southeastern Cuba (1981–2017), assessing trends in landing volumes and landings per unit of effort (LPUE); Supplementary Material 1: Processing of human-related and environmental variables; Figure S1: Changes in the total finfish landings and fishing effort between 1959 and 2015 in Cuba; Figure S2: Covariates added as predictors in generalized additive model (GAM); Figure S3: Residual inspection of a log-normal generalized additive model (GAM) of the total finfish landings; Figure S4: Changes in species landings (a) and landings per unit of effort (LPUE) (b) between 1981 and 2017 on the southeastern coast of Cuba. Reference [87] is cited in the Supplementary Materials.

Author Contributions

Conceptualization, Y.O.-E., Y.R.-C., F.P.-A., F.A.-S., M.J.Z.-R., K.K., and P.d.M.-L.; methodology, Y.O.-E., Y.R.-C., F.P.-A., F.A.-S., M.J.Z.-R., K.K., and P.d.M.-L.; software, Y.O.-E.; validation, Y.O.-E. and P.d.M.-L.; formal analysis, Y.O.-E. and Y.R.-C.; investigation, Y.O.-E., Y.R.-C. and F.P.-A.; resources, Y.O.-E. and P.d.M.-L.; data curation, Y.O.-E. and Y.R.-C.; writing—original draft preparation, Y.O.-E. and Y.R.-C.; writing—review and editing, Y.O.-E., Y.R.-C., F.P.-A., F.A.-S., M.J.Z.-R., K.K., and P.d.M.-L.; visualization, Y.O.-E., F.P.-A., F.A.-S., M.J.Z.-R., K.K., and P.d.M.-L.; supervision, K.K. and P.d.M.-L.; project administration, Y.O.-E.; funding acquisition, Y.O.-E., F.P.-A., and P.d.M.-L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by scholarships from CONACyT and BEIFI-IPN and funding from the NGO Idea Wild.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article.

Acknowledgments

We thank the Center for Fisheries Research (Centro de Investigaciones Pesqueras) of Cuba for providing the data. We also thank the NGOs Idea Wild and Environmental Defense Fund (EDF) for all the support. F.A.-S., M.J.Z.-R. and P.d.M.-L., thank COFAA and EDI from Instituto Politécnico Nacional. We extend our gratitude to the editor and the anonymous reviewers for their thorough evaluation and constructive feedback on earlier drafts of this manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Geographic location of the study area, with insets showing the two gulfs comprising Cuba’s southeastern administrative fishing zone.
Figure 1. Geographic location of the study area, with insets showing the two gulfs comprising Cuba’s southeastern administrative fishing zone.
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Figure 2. Time series of (a) the total finfish landings, (b) fishing effort, and (c) landings per unit of effort (LPUE) between 1981 and 2017 on the southeastern coast of Cuba.
Figure 2. Time series of (a) the total finfish landings, (b) fishing effort, and (c) landings per unit of effort (LPUE) between 1981 and 2017 on the southeastern coast of Cuba.
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Figure 3. Relationship between the compositions of finfish landings and fishing effort between 1981 and 2017 on the southeastern coast of Cuba.
Figure 3. Relationship between the compositions of finfish landings and fishing effort between 1981 and 2017 on the southeastern coast of Cuba.
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Figure 4. Predicted finfish landings from a log-normal generalized additive model (GAM) evaluating the influences of environmental and effort variables between 1981 and 2017 on the southeastern coast of Cuba. The solid line indicates the smoothed trend, and the shaded area represents the 95% confidence interval.
Figure 4. Predicted finfish landings from a log-normal generalized additive model (GAM) evaluating the influences of environmental and effort variables between 1981 and 2017 on the southeastern coast of Cuba. The solid line indicates the smoothed trend, and the shaded area represents the 95% confidence interval.
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Table 1. Variables evaluated for the generalized additive models. NOAA: National Oceanic and Atmospheric Administration; FAO: Food and Agriculture Organization.
Table 1. Variables evaluated for the generalized additive models. NOAA: National Oceanic and Atmospheric Administration; FAO: Food and Agriculture Organization.
VariableExtensionSource
North Atlantic multidecadal oscillation index (AMO)RegionalNOAA
AMO 9-, 26-, and 67-year cyclesRegionaldel Monte-Luna et al. [34]
Southern Oscillation Index (SOI)RegionalNOAA
Caribbean Sea Surface Temperature (SST)RegionalNOAA
Cuba’s southeast zone SSTLocalLandsat image time series
Southeast zone’s accumulated cyclonic energy (ACE)LocalHURDAT; Landsea and Franklin [35]
Natural coastal vegetation coverLocalLandsat image time series
Chlorophyll-a concentrationLocalLandsat image time series
Area of water reservoirs over landLocalLandsat image time series
Precipitations over landLocalERA5
Total nutrient nitrogen per area of croplandLocalFAO
Fishing effortLocalCuba’s Fisheries Research Center
Table 2. Results of a log-normal generalized additive model (GAM) evaluating the influences of environmental and effort variables on the total landings between 1981 and 2017 on the southeastern coast of Cuba; edf = estimated degrees of freedom; Ref. df = reference degrees of freedom.
Table 2. Results of a log-normal generalized additive model (GAM) evaluating the influences of environmental and effort variables on the total landings between 1981 and 2017 on the southeastern coast of Cuba; edf = estimated degrees of freedom; Ref. df = reference degrees of freedom.
ComponentTermEstimateStandard Errort-Valuep-Value
Parametric coefficient(Intercept)8.5580.017507.379<0.001
ComponentTermedfRef. dfF-valuep-value
Smooth termsEffort1.001.00114.37<0.001
Rainfall2.092.595.170.02
Dams1.001.000.050.828
Vegetation1.001.006.810.017
Chlorophyll-a3.424.117.380.001
SST1.001.003.420.079
SOI1.001.0013.640.001
AMO 261.001.000.40.533
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Olivera-Espinosa, Y.; Rodríguez-Cueto, Y.; Pina-Amargós, F.; Arreguín-Sánchez, F.; Zetina-Rejón, M.J.; Karr, K.; del Monte-Luna, P. Trends and Environmental Drivers of Marine Fish Landings in Cuba’s Most Productive Shelf Area. Fishes 2024, 9, 246. https://doi.org/10.3390/fishes9070246

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Olivera-Espinosa Y, Rodríguez-Cueto Y, Pina-Amargós F, Arreguín-Sánchez F, Zetina-Rejón MJ, Karr K, del Monte-Luna P. Trends and Environmental Drivers of Marine Fish Landings in Cuba’s Most Productive Shelf Area. Fishes. 2024; 9(7):246. https://doi.org/10.3390/fishes9070246

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Olivera-Espinosa, Yunier, Yandy Rodríguez-Cueto, Fabián Pina-Amargós, Francisco Arreguín-Sánchez, Manuel J. Zetina-Rejón, Kendra Karr, and Pablo del Monte-Luna. 2024. "Trends and Environmental Drivers of Marine Fish Landings in Cuba’s Most Productive Shelf Area" Fishes 9, no. 7: 246. https://doi.org/10.3390/fishes9070246

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