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Article

Silver Fir Decline in Pure and Mixed Stands at Western Edge of Spread in Croatian Dinarides Depends on Some Stand Structure and Climate Factors

by
Damir Ugarković
1,
Anamarija Jazbec
2,
Ivan Seletković
3,
Ivica Tikvić
1,
Vinko Paulić
1,*,
Mladen Ognjenović
3,
Mia Marušić
3 and
Nenad Potočić
3
1
Department of Ecology and Silviculture, Faculty of Forestry and Wood Technology, University of Zagreb, 10000 Zagreb, Croatia
2
Department of Forest Inventory and Management, Faculty of Forestry and Wood Technology, University of Zagreb, 10000 Zagreb, Croatia
3
Division for Forest Ecology, Croatian Forest Research Institute, 10450 Jastrebarsko, Croatia
*
Author to whom correspondence should be addressed.
Sustainability 2021, 13(11), 6060; https://doi.org/10.3390/su13116060
Submission received: 19 April 2021 / Revised: 24 May 2021 / Accepted: 25 May 2021 / Published: 27 May 2021
(This article belongs to the Special Issue Close to Nature Forestry – Hope for the European Green Deal)
Browse Figures
Versions Notes

Abstract

:
Silver fir is one of the most threatened conifer species in Croatia, especially at the western edge of its spread in Croatian Dinarides, where the decline in fir trees has resulted in significant ecological and economic issues. The aim of this study was to determine, over an 18-year monitoring period, the relationships of silver fir crown defoliation with climatic factors and structural attributes. We further analyzed the tree retention time in a given defoliation class and transition dynamics between defoliation classes, as well as the survival/mortality of trees. Data on silver fir defoliation were analyzed in two different forest types: in pure silver fir and in mixed silver fir and common beech stands. The climatic factors, primarily vegetation period air temperature, potential evapotranspiration, and dry season water deficit, were correlated with crown defoliation. Regarding the structural attributes, in the mixed stand with predominantly smaller trees, crown defoliation increased with reduced diameter at breast height, crown diameter, social class, and crown illumination. In the pure fir stand, crown defoliation increased with reduced crown diameter, greater crown asymmetry, greater crown illumination, and on trees with a stork’s nest crown. The retention time in defoliation classes differed for research sites. Transition dynamics were different only for trees in the highest defoliation class (dead trees). At the end of the study period, silver fir mortality was higher in the pure fir stand. Increased silver fir defoliation and mortality can be expected in the future, particularly in overmature stands under prolonged drought stress. Permanent forest monitoring could ensure the high-quality data needed for adaptive management of fir stands that could positively influence the structure of these stands and, thus, improve their health status.

1. Introduction

During their life cycle, trees are exposed to individual and combined stresses of varying intensity and duration. Tree vitality can be defined as the capability of a tree to assimilate, survive stress, and react to changes in environmental conditions [1]. Multiple factors influence tree vitality, and the reasons for the deterioration in the condition of certain tree species or stands must be sought in the specific interactions of numerous stress factors. In any case, long-term stress weakens trees, reducing their vitality [2].
Given that global changes include a modification of ecological factors, with simultaneous changes in the intensity of various stressors, understanding how plants adapt to stress is key in understanding the influence of climatic and habitat conditions on vegetation. In particular, climatic factors are considered critical for tree condition, as they determine the availability of water in terms of its uptake and transport in trees, while a lack of water causes a loss of vitality. Forest ecosystems today are under highly complex stand and ecological conditions, as evidenced by the disturbed stand structure and physiological weakening and dieback of trees [3,4]. The influence of stand structure on tree condition has not been the subject of research very often, but several authors have discussed the relation between various structural attributes and tree vitality. Spathelf [5] found a significant correlation between crown defoliation and diameter; Dobbertin and Brang [6] found that the crown defoliation of various forest tree species in Switzerland, among them silver fir, was related to the social position of the trees, and Oliva and Colinas [7] mentioned stork’s nest as one of the decline symptoms that coincides with defoliation in the silver fir decline process. Silver fir (Abies alba Mill.) is one of the most valued conifer species in Europe, both for historical and economic reasons [8,9,10]. This is also true for the Dinaric region [11], and therefore, the need to better understand the processes related to silver fir dieback arises. This species is sensitive to a number of unfavorable factors, such as increasing air temperature and lack of precipitation due to climate change [12,13], air pollution [14,15], unfavorable biotic factors [16,17], and inappropriate forest management [3,18]. Silver fir has a long history of decline in the Mediterranean region [7,19], particularly in southeast Europe [20] and in the Dinaric region [21,22,23]. The intensity of fir decline varies throughout east and southeast Europe due to the many combinations of causes of dieback [24]. With increasing warming and dryness, changes in the ecological niche of silver fir can be expected in the Dinarides [25,26], where a shift in silver fir distribution towards higher elevations is expected [27].
With regard to crown defoliation, silver fir is the most threatened conifer species in Croatia, and silver fir decline has resulted in significant ecological and economic issues in certain regions of Croatia. Studies in the Dinaric region of Croatia have indicated significant damage and deterioration of the silver fir stands [28,29,30].
According to the Manual of the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests) [31], defoliation is defined as the loss of leaves in the assessed part of the crown in comparison to a reference tree. Since tree defoliation is affected by abiotic [32,33,34,35] and biotic factors [34,36,37], it is applicable as an indicator for multiple stress factors [38]. Meanwhile, crown defoliation is the consequence of tree condition over the past few growth years, which may hinder the use of defoliation as a stress indicator for assessing current tree vitality [39]. Climate variability in the year preceding the assessment year was found to account for 79% of the variability of the current defoliation [40]. This implies that defoliation values do not reset every year; in fact, it takes several years after a significant stress (e.g., a drought year) for defoliation values to return to pre-stress levels, though this is also species-dependent. Defoliation of trees can change from year to year, and it can suddenly increase after a severe stress event (such as drought) [41]. Trees can recover from the loss of leaf mass, although the duration of recovery to pre-stress levels depends on both the species and the environmental conditions, and therefore, not every increase in defoliation can be associated with a permanent decline in vitality. Erdle and MacLean [42] confirmed that crown defoliation causes a reduction in the proportion of surviving trees. According to Manion [43], the mortality spiral illustrates the series of events that lead to tree mortality, and defoliation is one of these events. Crown defoliation is an important factor in the tree mortality model, as mortality increases with increasing crown defoliation [6,44]. Bigler et al. [45] reported that severe crown defoliation of silver fir is often associated with its decline. However, the nature of the relationship between defoliation and mortality, and the factors involved, are not yet fully understood. Our hypotheses were, thus, as follows:
(a)
Unfavorable climatic conditions, especially drought, have a detrimental impact on silver fir defoliation, leading to tree mortality;
(b)
Tree vitality and development depend on stand structure.
Trees in edge populations are likely to respond more dramatically to climate change than those in the main range of the species [46,47,48]. The aim of this study was to investigate, during a long-term observation period, the relations of climate and stand structural attributes with crown defoliation, tree mortality, and the duration of each defoliation stage through a comparison of the two most common silver fir forest types in the Dinaric region of Croatia. This insight is important for the consideration of various factors influencing silver fir vitality and development in the whole of Europe.

2. Materials and Methods

2.1. Study Site

The study was conducted in the Western Dinarides, in the mountainous region of Croatia, within beech-fir and fir forests. The study site has a moderately warm rainy climate without dry periods (Cfsbx climate type according to the Köppen Climate Classification). The average mean air temperature in the study area is 7.2 °C, and the mean annual precipitation is about 2000 mm [49]. In Croatia, silver fir occurs in two common types of forest communities: fir with hard fern (Blechno-Abietetum Ht. 1950) and the Dinaric beech-fir forests of the Western Dinarides (Omphalodo-Fagetum Marinček et al., 1993). The differences between them are reflected mainly in the site conditions and stand structure. In the association of silver fir with hard fern, silver fir is the main tree species growing in a selection group structure on silicate bedrock and dystric cambisol or podsol soils with low to very low pH, mostly in the altitudinal range of 650 to 900 m [50]. The Dinaric beech-fir forests of the Western Dinarides grow on limestone and dolomite, on shallow and skeletal cambisols, or illimerized soils, in the altitudinal range from 600 to 1300 m. The forest stands are selectively managed and have a single-tree structure [3].

2.2. Measurement of Structural Stand Attributes in the Experimental Plots

Two permanent experimental sites were established, representing the two most common silver fir forest types in Croatia: pure silver fir stands in association with hard fern at the Brloško site (site A, 45°20′06′′ N and 14°39′32′′ E) and beech-fir stands of the Western Dinarides at the Bitoraj site (site B, 45°16′47′′ N and 14°47′33′′ E) (Figure 1). Four experimental plots, 50 × 50 m in size, were set up at each site, for a total of eight experimental plots (2 ha). Experimental plots (repetitions) were chosen to represent each forest association in terms of the number of trees and growing stock (Table 1).
Since the establishment of these plots in 1996, permanent silver fir monitoring was carried out over a period of 18 years. At the beginning of the monitoring period, all silver fir trees with over 10 cm diameter at breast height (DBH) (N = 273) were counted and DBH and height were measured. Annual stem growth (diameter increment, DI) was calculated using the following equation:
DI = ( DBH 18 −   DBH 1 ) / T
where DBH1 is the DBH of a tree in the first year, DBH18 is the DBH of the same tree in the 18th year, and T is the number of monitoring years (Table 1).
The social status of the trees was assigned to one of four groups: 1—dominant; 2—codominant; 3—subdominant; 4—suppressed [51]. Crown length was assigned to the following classes: >50% tree length; between 25 and 50% tree length; <25% tree length [6]. A laser height meter was used to measure the length of the illuminated portion of the crown, which is expressed as a percentage (%) relative to total crown length. Crown shape was classified into three categories: 1—symmetrical; 2—less symmetrical; 3—highly asymmetrical [52]. The shape of the top of the crown (stork’s nest) was classified as one of the following: 0—none; 1—small; 2—moderate; 3—full stork’s nest [7].

2.3. Assessment of Crown Defoliation

During the monitoring period, two trained observers conducted a visual assessment of the crown defoliation of silver fir each year in late July or early August with the aid of binoculars [31] and using a photo guide [53] as a reference. Defoliation of each tree was assessed from at least two positions at the distance of one tree height. After assessment, trees were classified into one of seven defoliation classes: class 0 (0–10%); class 1 (11–25%); class 2 (26–40%); class 3 (41–60%); class 4 (61–80%); class 5 (81–99%); and class 6 (100%, dead trees). Defoliation was assessed regardless of the cause of needle loss. All measured silver fir trees were also assessed for crown defoliation.

2.4. Climate Data

To analyze the relationship of climatic factors (air temperature (°C) and precipitation (mm) in the period from April to September) with silver fir defoliation, data from the Vrelo Ličanke meteorological station were used. This station is located in close proximity to both experimental plots (45°19′48′′ N and 14°43′12′′ E, altitude 750 m). Dry season water deficit (DSWD) was calculated as the difference between the monthly sum of precipitation and the sum of potential evapotranspiration [54] using the KlimaSoft 2.0 program. Potential evapotranspiration (PET; mm) was calculated using the method of Thornthwaite [55].

2.5. Statistical Analysis

For all analyzed variables, descriptive statistics were calculated. For all analyses, the significance level was set at 5%. Nonparametric correlation analysis (Spearman rank correlation) was used for confirming the relationship between tree defoliation class and climate and structural attributes. The defoliation class of silver fir trees at the experimental plots on sites A and B was correlated with the values of climatic factors of that year. The analyzed tree attributes were correlated with the mean crown defoliation class of each tree during the observation period. To analyze how long a tree remained in a given defoliation class, the repeated measure analysis of variance (RM ANOVA) and post hoc Tukey test was used. Since trees went through multiple defoliation classes, measurements in individual defoliation classes were not independent, and therefore, an RM ANOVA model was used:
Y ijk = μ + S i + DC j + ( S × DC ) ij + ST k ( i ) + e ijk
where μ = overall mean; Si = effect of site, where i = 1, 2; DCj = effect of defoliation class, where j = 1, …, 5; (S × DC)ij = effect of interaction between site i and defoliation class j; STk(i) = effect of kth tree within ith site; eijk = random error ≈ N(0,σ2).
As assumption of sphericity was not met (chi2 = 715.33, df = 9, p < 0.001). The Greenhouse–Geisser epsilon correction was used for adjustment [56]. The percentage of overall tree survival during the monitoring period and the dynamics of tree transition between defoliation classes were assessed using the Kaplan–Meier estimation. Trees damaged by stem breakage were not included in the mortality calculation. The differences between sites A and B for overall survival and for the six defoliation classes were tested using the log-rank test [57]. For each defoliation class, the tree that entered that class in that year was coded as “complete”. In the survival analysis, which included the Kaplan–Meier estimation, we defined an event that occurred (in our case, the entry of a tree into a defoliation class) as complete, and if not, it was censored. The statistical analysis of data was performed using the package Statistica 13.1 [58] and SAS 9.4 [56].

3. Results

3.1. Crown Defoliation

Silver fir defoliation increased at both study sites during the study period. An increasing trend in the share of trees in defoliation classes 4 and 5 was recorded, while the proportion of healthy trees (classes 0 and 1) decreased (Figure 2).

3.2. Climatic Factors

Table 2 shows the mean, minimum, and maximum values of climatic factors (precipitation and air temperature) and indices (dry season water deficit and potential evapotranspiration) for the 18-year monitoring period, as measured during the growing season from April to September.
According to the results of the Spearman correlation, the correlation coefficient between defoliation class and precipitation in the growing season was r = 0.14 (p = 0.409); for air temperature in the growing season, it was r = 0.44 (p = 0.005); and for potential evapotranspiration, it was r = 0.35 (p = 0.03). The only significant correlation between defoliation class and dry season water deficit was calculated for the month of June (r = −0.55, p < 0.001).

3.3. Stand Structure and Tree Attributes

In the pure silver fir stand (site A), higher DBH values as well as higher increment rates, crown diameters, and crown illumination values were measured, while in the beech-fir stand (site B), the trees had longer crowns (Table 3).
Table 4 shows the Spearman rank correlations of defoliation and structural attributes. The crown defoliation and structural attributes (DBH, crown illumination, social position of the tree, and the shape of the top of the crown) showed different correlations in the studied stands. In both stands, increased crown defoliation led to a decrease in radial increment. Additionally, a significant correlation was found between crown defoliation and crown illumination in both stands, but here, the effects varied: in stand A, defoliation increased, and in stand B, defoliation was reduced with increased crown illumination (Table 4).

3.4. Retention Time in a Given Defoliation Class, Transition Dynamics, and Tree Mortality

The results of the RM ANOVA show that there was a statistically significant difference in the retention time (time trees spent in a given defoliation class) at both sites (Table 5 and Figure 3). The greatest difference was found for defoliation class 4 (61–80%), which had an average retention time of five years in the pure fir stand and seven years in the beech-fir stand (Figure 3). When the sites and retention times in all defoliation classes were considered together, the post hoc Tukey test showed that all defoliation classes except for classes 3 and 5 were significantly different. The statistically significant interaction shows that the retention time in defoliation classes was not the same at both sites; trees at site B remained in classes 3 and 4 longer than those at site A did.
A certain level of silver fir crown regeneration was also observed. At site A, a temporary recovery (lower defoliation class than in the previous year) was recorded in 12.3% of trees during the whole monitoring period, as opposed to 23.7% of trees at site B (data not shown).
Regardless of the structural differences and the differences in site conditions between the study sites, there was a statistically significant difference between the sites only for the transition of trees into class 6 (100% defoliation—dead trees). Silver fir trees at site A transitioned to class 6 significantly earlier than trees at the beech-fir site B did (Figure 4 and Table 6). Additionally, the majority of trees entered class 6 from class 5 (64.28% at site A, 72.72% at site B), while the remainder of the trees transitioned to class 6 directly from class 4.
There were no significant differences in the mortality dynamics for sites A and B, even though the number of dead trees at the end of the monitoring period was different: 13 trees (16.46%) at site A compared to 21 (10.82%) trees at site B (log-rank test results: chi2 = 2.067, p = 0.0654). Additionally, six trees at site A and five trees at site B suffered stem breakage due to strong winds.
Tree decline in the beech-fir stand (site B) was slower and more gradual in comparison with that in the pure fir stand (site A). At site A, tree mortality was most intense in the first 6 years and then stagnated until the 17th year of monitoring, while at site B, mortality was most present in the 16th monitoring year (Figure 5). At site A, the annual silver fir mortality was 0.94 N/ha, compared to 1.44 N/ha at site B. The maximum annual tree mortality was 8 trees/ha at site A and 6 trees/ha at site B.

4. Discussion

Continuous long-term monitoring allows for a better understanding of the tree decline processes in forest ecosystems. The percentage of trees in higher defoliation classes increased during the monitoring period at both experimental sites, which can be associated with their location near the southern edge of the silver fir distribution in Croatia, towards the warmer and dryer conditions of the Mediterranean climate. Poor vitality of silver fir has been observed in this area compared to the rest of the distribution range [22]. The percentage of significantly defoliated (>25% defoliation) silver fir trees in Croatia decreased constantly in the period 2003–2014 [59], although these numbers are difficult to compare directly. It is worth noting that, despite the declining trend, silver fir defoliation remained very high (62.4% of trees in 2014 were significantly defoliated). Although the trees at site A had better vitality in the first year of the study, their condition changed markedly over the 18-year period as the defoliation and mortality increased. This was particularly evident in comparison with site B, where the development of crown defoliation progressed more slowly. In contrast to the results of Bezak et al. [60], who observed no improvement in the crown condition of silver fir trees, a small portion of trees in this study experienced crown regeneration in certain years.
The results presented here suggest that increased defoliation of silver fir is associated with increasing air temperatures in the growing season, thus supporting the conclusions of Potočić et al. [30]. Increased amounts of potential evapotranspiration and reduced precipitation during the month of June also increased crown defoliation. Uhl et al. [61] consider silver fir to be drought-sensitive, while Vitasse et al. [62] concluded that silver fir has a high potential of success in western and central Europe despite the increasing air temperatures, as long as precipitation is sufficient. Dobrowolska et al. [9] and Čater and Levanič [63] found that unfavorable weather conditions, such as drought and increasing mean temperatures, reduce silver fir populations, while Tinner et al. [64] predicted that the future distribution range of silver fir will remain relatively unchanged, despite a warmer climate and increased air temperature levels, as long as mean precipitation remains above 800 mm per year. In this study, no significant effect of precipitation in the growing season was observed on crown defoliation. The amount of precipitation in the vegetation period ranged from 586 to 1525 mm, with a mean of 954 mm. However, under equal climatic conditions, the observed stands showed different responses in terms of development of defoliation and mortality. The roots of trees from the species Abies can be physiologically fused [65], and the formation of silver fir biogroups is more common on limestone substrates than on silicate substrates [66], which could have facilitated a better supply of nutrients and water to trees at site B.
Crown defoliation at both study sites showed a strong negative correlation with increment, which supports the findings of Erdle and MacLean [42], Bigler et al. [45], and Gazol et al. [67], who found differences in growth trends between trees with higher and lower degrees of defoliation.
Crown length is one of the most typical properties of fir trees [68]. The significant influence of crown length on tree vitality was described by Spathelf [5]. In this study, no correlation was found between crown length and crown defoliation. However, a significant correlation was found between crown defoliation and crown diameter, with smaller diameter crowns experiencing higher defoliation. A significant dependence of crown defoliation on crown illumination was also found. At site A, where trees had larger diameters and greater crown illumination, defoliation increased with increasing crown illumination. According to Prpić et al. [69], such crowns are more exposed to air pollution. Moreover, such trees had a pronounced stork’s nest crown, indicating older age and reduced vitality, in line with the findings of Oliva and Colinas [7].
Dobbertin and Brang [6] reported that crown defoliation correlated with the social position of trees and the degree of competition, which supports our results. Fir trees in the beech-fir stand (site B) were present at all layers, from dominant to suppressed, and a significantly positive correlation was found between defoliation class and the social position of trees, meaning that defoliation increased with reduced crown illumination. In contrast, fir tree crowns in the pure stand at site A were found only in the upper layer, and therefore, it was not possible to determine possible correlations of defoliation with tree social position.
Silver fir tree mortality over the 18-year monitoring period was 21.52% (average 1.2% per year) in the pure fir stand and 13.40% (0.74% per year) in the beech-fir stand. Bezak et al. [60] conducted a study in the beech-fir forests of the Western Dinarides on limestone substrate from 1969 to 1990 and found a mortality rate of 37% (1.23% per year). Senf et al. [70] reported that the average mortality in European temperate forests is 0.79% per year, with an increasing trend, while according to the data from the ICP Forests’ Technical Report, Forest Condition in Europe [71], total mortality of trees in 2019 was 0.9%.
The fourth (1999) and fifth (2000) years of the study were consecutive drought years; therefore, it can be assumed that this lasting climate stress further contributed to the increasing number of trees in defoliation class 6 in 2001.
The trees in the pure fir stand (site A) can be considered physiologically more mature, since this site had a significant number of trees with a prominent stork’s nest present. This would make the trees more susceptible to stress, and as a result, there was increased mortality at this site in comparison with site B in the study period. Similar conclusions were reached by Bigler et al. [45], who found that there was a greater risk of mortality for silver fir trees of greater height in higher defoliation classes. According to our results, the relationship between defoliation and mortality is not linear, but rather depends on a number of structural and site attributes that influence the onset of mortality. Therefore, it is not possible to determine how the vitality of a stand will evolve based on a single assessment. The results of this study confirm the necessity for permanent forest monitoring to ensure high-quality data, serving as the basis for more successful, up-to-date, adaptive forest management, including sanitary felling predictions.

5. Conclusions

This 18-year observational study in two types of silver fir stands examined the possible causes of crown defoliation in silver fir and its decline dynamics. Strong correlations were found between defoliation and structural attributes. More intense tree decline was found in the pure fir stands, which can be attributed to their presumed older age (trees with a stork nest), as deducted from the higher incidence of crown asymmetry coinciding with higher defoliation. Trees in the pure silver fir stand, which contained the most trees with a pronounced stork nest, died significantly earlier in comparison with the smaller silver fir trees in the mixed beech-fir stand. This suggests the possibility that adaptive management of fir stands could positively influence the structure of these stands and, thus, improve their health status.
Consistent with many previous studies, air temperature appears to have predominance over precipitation as a factor determining crown defoliation of silver fir, although the greatest transitions of trees to higher defoliation classes occurred after two consecutive years of drought.
Although this study is limited by design as it is a relatively local study, it was located at the southern edge of the silver fir distribution range, where climate change effects are expected earlier than in the rest of Europe. Despite the adaptations of local populations of silver fir, there is a legitimate risk that the thriving of silver fir at the southern edge of its distribution range will be hindered in the expected future climate conditions. In this region, increased silver fir defoliation and mortality can be expected, particularly in overmature stands facing prolonged drought stress.

Author Contributions

Conceptualization, D.U.; methodology, D.U., I.S. and N.P.; database management, M.M., M.O. and V.P.; statistical analyses, D.U., A.J. and V.P.; writing, D.U., I.T., I.S. and N.P.; technical editing, M.M. and M.O. All authors have read and agreed to the published version of the manuscript.

Funding

D.U. and V.P. were supported by the Ministry of Economy and Sustainable Development (Croatia) under the project KK.05.1.1.02.0009 (MEMORIE).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Brang, P. (Ed.) Sanasilva-Bericht 1997. Zustand und Gefahrdung des Schweizer Waldes—Eine Zwischenbilanz nach 15 Jahren Waldschadenforschung; Eidgenössische Forschungsanstalt für Wald Schnee und Landschaft: Birmensdorf, Switzerland, 1998; Volume 345, p. 102. [Google Scholar]
  2. Oszlányi, J. Forest health and environmental pollution in Slovakia. Environ. Pollut. 1997, 98, 389–392. [Google Scholar] [CrossRef]
  3. Matić, S. Uzgojni Radovi na Obnovi i Njezi Sastojina Hrasta Lužnjaka. In Hrast Lužnjak u Hrvatskoj; Klepac, D., Ed.; Hrvatska Akademija Znanosti i Umjetnosti: Vinkovci/Zagreb, Croatia, 1996; pp. 159–167. ISBN 53-154-079-9. [Google Scholar]
  4. Prpić, B. Utjecaj vodotehničkih zahvata nastabilnost sastojina hrasta lužnjaka (Quercus robur L.) u Hrvatskoj u primjeru HE Novo Virje. Šumar. List 2001, 7–8, 379. [Google Scholar]
  5. Spathelf, P. Reconstruction of crown length of Norway spruce (Picea abies (L.) Karst.) and Silver fir (Abies alba Mill.)—Technique, establishment of sample methods and application in forest growth analysis. Ann. For. Sci. 2003, 60, 833–842. [Google Scholar] [CrossRef]
  6. Dobbertin, M.; Brang, P. Crown defoliation improves tree mortality models. For. Ecol. Manag. 2001, 141, 271–284. [Google Scholar] [CrossRef]
  7. Oliva, J.; Colinas, C. Decline of silver fir (Abies alba Mill.) stands in the Spanish Pyrenees: Role of management, historic dynamics and pathogens. For. Ecol. Manag. 2007, 252, 84–97. [Google Scholar] [CrossRef]
  8. Mauri, A.; de Rigo, D.; Caudullo, G. Abies alba in Europe: Distribution, Habitat, Usage and Threats. In European Atlas of Forest Tree Species; San-Miguel-Ayanz, J., de Rigo, D., Caudullo, G., Houston Durrant, T., Mauri, A., Eds.; Publications Office of the EU: Luxembourg, 2016; pp. 48–49. ISBN 978-92-79-52833-0. [Google Scholar]
  9. Dobrowolska, D.; Bončina, A.; Klumpp, R. Ecology and silviculture of silver fir (Abies alba Mill.): A review. J. For. Res. 2017, 22, 326–335. [Google Scholar] [CrossRef]
  10. Caudullo, G.; Welk, E.; San-Miguel-Ayanz, J. Chorological maps for the main European woody species. Data Brief 2017, 12, 662–666. [Google Scholar] [CrossRef] [PubMed]
  11. Bončina, A. History, current status and future prospects of uneven-aged forest management in the Dinaric region: An overview. Forestry 2011, 84, 467–478. [Google Scholar] [CrossRef]
  12. Mihai, G.; Alexandru, A.M.; Stoica, E.; Birsan, M.V. Intraspecific Growth Response to Drought of Abies alba in the Southeastern Carpathians. Forests 2021, 12, 387. [Google Scholar] [CrossRef]
  13. Potočić, N.; Ćosić, T.; Pilaš, I. The influence of climate and soil properties on calcium nutrition and vitality of silver fir (Abies alba Mill.). Environ. Pollut. 2005, 137, 596–602. [Google Scholar] [CrossRef]
  14. Filipiak, M.; Napierala-Filipiak, A. Effect of canopy density on the defoliation of the European silver fir (Abies alba Mill.) due to heavy industrial pollution. Dendrobiology 2009, 62, 17–22. [Google Scholar]
  15. Diaci, J. Silver Fir Decline in Mixed Old-Growth Forests in Slovenia: An Interaction of Air Pollution, Changing Forest Matrix and Climate. In Air Pollution—New Developments; Moldoveanu, A., Ed.; InTech: Rijeka, Croatia, 2011; pp. 263–274. ISBN 978-953-307-527-3. [Google Scholar]
  16. Pernek, M.; Lackovic, N. The role of bark beetles in silver fir decline and possible use of pheromone traps for the monitoring. Šumar. List. 2011, 135, 114–121. [Google Scholar]
  17. Durand-Gillmann, M.; Cailleret, M.; Boivin, T.; Nageleisen, L.M.; Davi, H. Individual vulnerability factors of Silver fir (Abies alba Mill.) to parasitism by two contrasting biotic agents: Mistletoe (Viscum album L. ssp. abietis) and bark beetles (Coleoptera: Curculionidae: Scolytinae) during a decline process. Ann. For. Sci. 2014, 71, 659–673. [Google Scholar] [CrossRef]
  18. Becker, M.; Landmann, G.; Levy, G. Silver fir decline in the Vosges mountains (France): Role of climate and silviculture. Water Air Soil Pollut. 1989, 48, 77–86. [Google Scholar] [CrossRef]
  19. Cailleret, M.; Davi, H. Effects of climate on diameter growth of co-occurring Fagus sylvatica and Abies alba along an altitudinal gradient. Trees 2011, 25, 265–276. [Google Scholar] [CrossRef]
  20. Gazol, A.; Camarero, J.J.; Gutiérrez, E.; Popa, I.; Andreu-Hayles, L.; Motta, R.; Nola, P.; Ribas, M.; Sanguesa-Barreda, G.; Urbinati, C.; et al. Distinct effects of climate warming on populations of silver fir (Abies alba) across Europe. J. Biogeogr. 2015, 42, 1150–1162. [Google Scholar] [CrossRef] [Green Version]
  21. Ficko, A.; Poljanec, A.; Boncina, A. Do changes in spatial distribution, structure and abundance of silver fir (Abies alba Mill.) indicate its decline? For. Ecol. Manag. 2011, 261, 844–854. [Google Scholar] [CrossRef]
  22. Ugarković, D.; Tikvić, I.; Seletković, Z. Odnos stanišnih i strukturnih čimbenika prema odumiranju i prehrani stabala obične jele (Abies alba Mill.) u Gorskom kotaru. Croat. J. For. Eng. 2011, 32, 57–71. [Google Scholar]
  23. Čavlović, J.; Bonačina, A.; Božić, M.; Goršić, E.; Simončić, T.; Teslak, K. Depression and growth recovery of silver fir in uneven-aged Dinaric forests in Croatia from 1901 to 2001. For. Int. J. For. Res. 2015, 88, 586–598. [Google Scholar] [CrossRef] [Green Version]
  24. Diaci, J.; Rozenbergar, D.; Anić, I.; Mikac, S.; Saniga, M.; Kucbel, S.; Visnjic, C.; Ballian, D. Structural dynamics and synchronous silver fir decline in mixed old-growth mountain forests in Eastern and Southeastern Europe. Forestry 2011, 84, 479–491. [Google Scholar] [CrossRef] [Green Version]
  25. Anić, I.; Vukelić, J.; Mikac, S.; Bakšić, D.; Ugarković, D. Utjecaj globalnih klimatskih promjena na ekološku nišu obične jele (Abies alba Mill.) u Hrvatskoj. Šumar. List 2009, 3–4, 135–144. [Google Scholar]
  26. Begović, K.; Rydval, M.; Mikac, S.; Čupić, S.; Svobodova, K.; Mikoláš, M.; Kozák, D.; Kameniar, O.; Frankovič, M.; Pavlin, J.; et al. Climate-growth relationships of Norway Spruce and silver fir in primary forests of the Croatian Dinaric mountains. Agric. For. Meteorol. 2020, 288–289, 108000. [Google Scholar] [CrossRef]
  27. Klopčič, M.; Mina, M.; Bugmann, H.; Bončina, A. The prospects of silver fir (Abies alba Mill.) and Norway spruce (Picea abies (L.) Karst) in mixed mountain forests under various management strategies, climate change and high browsing pressure. Eur. J. For. Res. 2017, 136, 1071–1090. [Google Scholar] [CrossRef]
  28. Božić, M.; Čavlović, J.; Teslak, K. Modeliranje prirasta jelovih stabala na temelju sastojinskih čimbenika. Glas. Šumske Pokuse 2006, 5, 443. [Google Scholar]
  29. Tikvić, I.; Seletković, Z.; Ugarković, D.; Posavec, S.; Španjol, Ž. Dieback of Silver fir (Abies alba Mill.) on Northern Velebit (Croatia). Period. Biol. 2008, 110, 137–143. [Google Scholar]
  30. Potočić, N.; Seletković, I.; Ugarković, D.; Jazbec, A.; Mikac, S. The influence of climate properties on crown condition of Common beech (Fagus sylvatica L.) and Silver fir (Abies alba Mill.) on Velebit. Period. Biol. 2008, 110, 145–150. [Google Scholar]
  31. Eichhorn, J.; Roskams, P.; Potocic, N.; Timermann, V.; Ferretti, M.; Mues, V.; Szepesi, A.; Durrant, D.; Seletkovic, I.; Schröck, H.W.; et al. Part IV: Visual Assessment of Crown Condition and Damaging Agents. In Manual on Methods and Criteria for Harmonized Sampling, Assessment, Monitoring and Analysis of the Effects of Air Pollution on Forests; UNECE ICP Forests Programme Coordinating Centre, Thünen Institute of Forest Ecosystems: Eberswalde, Germany, 2016; p. 54. [Google Scholar]
  32. Bussotti, F.; Ferretti, M. Visible injury, crown condition, and growth responses of selected Italian forests in relation to ozone exposure. Environ. Pollut. 2009, 157, 1427–1437. [Google Scholar] [CrossRef]
  33. Drobyshev, I.; Anderson, S.; Sonesson, K. Crown condition dynamics of oak in southern Sweden 1988–1999. Environ. Monit. Assess. 2007, 134, 199–210. [Google Scholar] [CrossRef]
  34. Ferretti, M.; Nicolas, M.; Bacaro, G.; Brunialti, G.; Calderisi, M.; Croisé, L.; Frati, L.; Lanier, M.; Maccherini, S.; Santi, E.; et al. Plot-scale modelling to detect size, extent, and correlates of changes in tree defoliation in French high forests. For. Ecol. Manag. 2014, 311, 56–69. [Google Scholar] [CrossRef]
  35. Ferretti, M.; Waldner, P.; Verstraeten, A.; Schmitz, A.; Michel, A.; Žlindra, D.; Marchetto, A.; Hansen, K.; Pitar, D.; Gottardini, E.; et al. Criterion 2: Maintenance of Forest Ecosystem Health and Vitality. In State of Europe’s Forests 2020; Ministerial Conference on the Protection of Forests in Europe: Bratislava, Slovakia, 2020; pp. 52–86. [Google Scholar]
  36. Pollastrini, M.; Feducci, M.; Bonal, D.; Fotelli, M.; Gessler, A.; Grossiord, C.; Guyot, V.; Jactel, H.; Nguyen, D.; Radoglou, K.; et al. Physiological significance of forest tree defoliation: Results from a survey in a mixed forest in Tuscany (central Italy). For. Ecol. Manag. 2016, 361, 170–178. [Google Scholar] [CrossRef]
  37. Chen, C.; Wei, X.; Weiskittel, A.; Hayes, D.J. Above-ground carbon stock in merchantable trees not reduced between cycles of spruce budworm outbreaks due to changing species composition in spruce-fir forests of Maine, USA. For. Ecol. Manag. 2019, 453, 117590. [Google Scholar] [CrossRef]
  38. De Vries, W.; Klap, J.M.; Erisman, J.W. Effects of environmental stress on forest crown condition in Europe. Part I: Hypotheses and approach to the study. Water Air Soil Pollut. 2000, 119, 317–333. [Google Scholar] [CrossRef]
  39. Polak, T.; Rock, B.N.; Campbell, P.E.; Soukupova, J.; Solcova, B.; Zvara, K.; Albrechtova, J. Shoot growth processes, assessed by bud development types, reflect Norway spruce vitality and sink prioritization. For. Ecol. Manag. 2006, 225, 337–348. [Google Scholar] [CrossRef]
  40. Neirynck, J.; Roskams, P. Relationships between crown condition of beech (Fagus sylvatica L.) and throughfall chemistry. Water Air Soil Pollut. 1999, 116, 389–394. [Google Scholar] [CrossRef]
  41. Guada, G.; Camarero, J.J.; Sánchez-Salguero, R.; Cerrillo, R.M.N. Limited growth recovery after drought-induced forest dieback in very defoliated trees of two pine species. Front. Plant Sci. 2016, 7, 418. [Google Scholar] [CrossRef]
  42. Erdle, T.A.; MacLean, D.A. Stand growth model calibration for use in forest pest impact assessment. For. Chron. 1999, 75, 141–152. [Google Scholar] [CrossRef] [Green Version]
  43. Manion, P.D. Tree Disease Concepts; Prentice Hall: Englewood Cliffs, NJ, USA, 1981; ISBN 013930701X. [Google Scholar]
  44. Dobbertin, M. Tree growth as indicator of tree vitality and of tree reaction to environmental stress: A review. Eur. J. For. Res. 2005, 124, 319–333. [Google Scholar] [CrossRef]
  45. Bigler, C.; Gričar, J.; Bugmann, H.; Čufar, K. Growth patterns as indicators of impending tree death in silver fir. For. Ecol. Manag. 2004, 199, 183–190. [Google Scholar] [CrossRef]
  46. Brubaker, L.B. Responses of tree populations to climatic change. Vegetatio 1986, 67, 119–130. [Google Scholar] [CrossRef]
  47. Gaston, K.J. The Structure and Dynamics of Geographic Ranges; Oxford University Press: New York, NY, USA, 2003; pp. 31–136. [Google Scholar]
  48. Macias, M.; Andreu, L.; Bosch, O.; Camarero, J.J.; Gutierrez, E. Increasing Aridity is Enhancing Silver Fir (Abies Alba Mill.) Water Stress in its South-Western Distribution Limit. Clim. Chang. 2006, 79, 289–313. [Google Scholar] [CrossRef]
  49. Seletković, Z. Klima i Hidrološke Prilike u Dinarskim Jelovim Šumama u Hrvatskoj. In Obična Jela (Abies alba Mill.) u Hrvatskoj; Prpić, B., Ed.; Akademija Šumarskih Znanosti: Zagreb, Croatia, 2001; p. 133. [Google Scholar]
  50. Vukelić, J. Šumska Vegetacija Hrvatske; DZZP, Sveučilište u Zagrebu, Šumarski fakultet: Zagreb, Croatia, 2012; pp. 374–377. [Google Scholar]
  51. Crow, G.R.; Hicks, R.R. Predicting mortality in mixed oak stands following spring insect defoliation. For. Sci. 1990, 36, 831–841. [Google Scholar]
  52. Stierlin, H.R.; Brändli, U.B.; Herold, A.; Zinggeler, J. Schweizerisches Landesforstinventar. Anleitung für die Feldaufnahmen der Erhebung 1993–1995; Eidgenössischen Forschungsanstalt für Wald, Schnee und Landschaft: Zürich, Switzerland, 1994; p. 204. [Google Scholar]
  53. Müller, E.; Stierlin, H.R. Sanasilva Kronenbilder mit Nadel und Blattverlustprozenten; Eidgenössische Forschungsanstalt für Wald, Schnee und Landschaft: Zürich, Switzerland, 1990; p. 129. [Google Scholar]
  54. Dufour-Dror, J.M.; Ertas, A. Bioclimatic perspectives in the distribution of Quercus ithaburensid Decne. Subspecies in Turkey and in the Levant. J. Biogeogr. 2004, 31, 461–474. [Google Scholar] [CrossRef]
  55. Thornthwaite, C.W. An Approach toward a Relation Classification of Climate. Geogr. Rev. 1948, 32, 55–94. [Google Scholar] [CrossRef]
  56. SAS Institute Inc. SAS/STAT User’s Guide; SAS Institute Inc.: Cary, NC, USA, 2020; Available online: https://documentation.sas.com/api/collections/pgmsascdc/v_011/docsets/statug/content/glm.pdf?locale=en#nameddest=statug_glm_references (accessed on 17 May 2021).
  57. Kaplan, E.L.; Meier, P. Nonparametric estimation from incomplete observations. J. Am. Stat. Assoc. 1958, 53, 457–481. [Google Scholar] [CrossRef]
  58. TIBCO Software Inc. Statistica (Data Analysis Software System); Version 13; TIBCO Software Inc.: Palo Alto, CA, USA, 2018. [Google Scholar]
  59. Potočić, N.; Seletković, I.; Vrbek, B.; Jakovljević, T.; Marjanović, H.; Indir, K.; Medak, J.; Ostrogović, M.; Liović, B. Oštećenost Šumskih Ekosustava Republike Hrvatske. Izvješće za 2013. Godinu; Nacionalni Koordinacijski Centar za Procjenu i Motrenje Utjecaja Atmosferskog Onečišćenja i Drugih Čimbenika na Šumske Ekosustave, Hrvatski Šumarski Institut: Jastrebarsko, Croatia, 1958; p. 97. [Google Scholar]
  60. Bezak, K.; Krejči, V.; Vrbek, B. Propadanje jele praćeno promjenama vitalnosti i prirasta šume bukve i jele od 1969–1990.godine. Rad. Šumar. Inst. 1991, 26, 115–128. [Google Scholar]
  61. Uhl, E.; Ammer, C.; Spellmann, H.; Schölch, M.; Pretzsch, H. Zuwachstrend und Stressresilienz von Tanne und Fichte im Vergleich. Allg. Forst. Jagdztg. 2012, 184, 278–292. [Google Scholar]
  62. Vitasse, Y.; Bottero, A.; Rebetez, M.; Conedera, M.; Augustin, S.; Brang, P.; Tinner, W. What is the potential of silver fir to thrive under warmer and drier climate? Eur. J. For. Res. 2019, 138, 547–560. [Google Scholar] [CrossRef]
  63. Čater, M.; Levanič, T. Beech and silver fir’s response along the Balkan’s latitudinal gradient. Sci. Rep. 2019, 9. [Google Scholar] [CrossRef] [Green Version]
  64. Tinner, W.; Colombaroli, D.; Heiri, O.; Henne, P.D.; Steinacher, M.; Untenecker, J.; Vescovi, E.; Allen, J.R.M.; Carraro, G.; Conedera, M.; et al. The past ecology of Abies alba provides new perspectives on future responses of silver fir forests to global warming. Ecol. Monogr. 2013, 83, 419–439. [Google Scholar] [CrossRef] [Green Version]
  65. Quer, E.; Baldy, V.; DesRochers, A. Ecological drivers of root grafting in balsam fir natural stands. For. Ecol. Manag. 2020, 475. [Google Scholar] [CrossRef]
  66. Prpić, B.; Seletković, Z. Ekološka Konstitucija Obične Jele. In Obična Jela (Abies alba Mill.) u Hrvatskoj; Prpić, B., Ed.; Akademija Šumarskih Znanosti: Zagreb, Croatia, 2001; pp. 255–268. [Google Scholar]
  67. Gazol, A.; Sangüesa-Barreda, G.; Camarero, J.J. Forecasting forest vulnerability to drought in Pyrenean silver fir forests showing dieback. Front. For. Glob. Chang. 2020, 3, 1–13. [Google Scholar] [CrossRef]
  68. Bernadzki, E. Jodła Pospolita—Ekologia, Zagrożenia, Hodowla (Silver Fir—Ecology, Threatens, Silviculture); PWRiL: Warsaw, Poland, 2008; p. 210. [Google Scholar]
  69. Prpić, B.; Seletković, Z.; Jurjević, P. Sušenje Jele i Promjene “Kemijske” Klime. In Obična Jela (Abies alba Mill.) u Hrvatskoj; Prpić, B., Ed.; Akademija Šumarskih Znanosti: Zagreb, Croatia, 2001; pp. 299–307. [Google Scholar]
  70. Senf, C.; Pflugmacher, D.; Zhiqiang, Y.; Sebald, J.; Knorn, J.; Neumann, M.; Hostert, P.; Seidl, R. Canopy mortality has doubled in Europe’s temperate forests over the last three decades. Nat. Commun. 2018, 9, 4978. [Google Scholar] [CrossRef]
  71. Timmermann, V.; Potočić, N.; Ognjenović, M.; Kirchner, T. Tree Crown Condition in 2019. In Forest Condition in Europe: The 2020 Assessment ICP Forests Technical Report under the UNECE Convention on Long-Range Transboundary Air Pollution (Air Convention); Michel, A., Prescher, A.-K., Schwärzel, K., Eds.; Thünen Institute: Eberswalde, Germany, 2020; pp. 33–47. [Google Scholar] [CrossRef]
Sustainability 13 06060 g001 550
Figure 1. Locations of study sites and plots.
Figure 1. Locations of study sites and plots.
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Figure 2. Silver fir defoliation at sites (a) (Brloško) and (b) (Bitoraj) according to defoliation classes (class 0, up to 10% defoliation; class 1, 11–25%; class 2, 26–40%; class 3, 41–60%; class 4, 61–80%; class 5, 81–99%; class 6: 100%—dead tree).
Figure 2. Silver fir defoliation at sites (a) (Brloško) and (b) (Bitoraj) according to defoliation classes (class 0, up to 10% defoliation; class 1, 11–25%; class 2, 26–40%; class 3, 41–60%; class 4, 61–80%; class 5, 81–99%; class 6: 100%—dead tree).
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Figure 3. Retention time in a given defoliation class (in years) at research sites. Vertical bars denote 0.95 confidence intervals.
Figure 3. Retention time in a given defoliation class (in years) at research sites. Vertical bars denote 0.95 confidence intervals.
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Figure 4. Transition dynamics between defoliation classes as cumulative proportions of trees: (a) Transition to class 1; (b) Transition to class 2; (c) Transition to class 3; (d) Transition to class 4; (e) Transition to class 5; (f) Transition to class 6.
Figure 4. Transition dynamics between defoliation classes as cumulative proportions of trees: (a) Transition to class 1; (b) Transition to class 2; (c) Transition to class 3; (d) Transition to class 4; (e) Transition to class 5; (f) Transition to class 6.
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Figure 5. Annual mortality and cumulative proportion of surviving trees during 18 years at sites A (Brloško) and B (Bitoraj). Symbol “+” depicts mortality due to stem breakage.
Figure 5. Annual mortality and cumulative proportion of surviving trees during 18 years at sites A (Brloško) and B (Bitoraj). Symbol “+” depicts mortality due to stem breakage.
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Table
Table 1. Site and stand structure characteristics of the experimental plots at the beginning of the study period.
Table 1. Site and stand structure characteristics of the experimental plots at the beginning of the study period.
Site A—BrloškoSite B—Bitoraj
Plot 1Plot 2Plot 3Plot 4Plot 1Plot 2Plot 3Plot 4
CommunitySilver fir forest with hard fernDinaric beech-fir forest
BedrockSilicateLimestone
Soil typeDystric cambisolCalcocambisol
Altitude,
m a.s.l.		750760750770800850870820
Slope, °52010101510207
ExposureSouthwestSouthwest
Average height of dominant trees, m38.038.037.037.030.033.031.033.0
D (N ha−1)90969295398354375380
B (m2 ha−1)33.949.135.740.125.426.427.227.5
V (m3 ha−1)469.3595.9475.0512.0283.0293.0312.0310.3
Fr (%)8090908560707065
Cb (%)105101030302525
Sy (%)----10-510
Sp (%)105-5----
Abbreviations: D—density; B—basal area; V—growing stock; Fr—silver fir; Cb—common beech; Sy—sycamore maple; Sp—common spruce.
Table
Table 2. Descriptive statistics of climatic factors and indices in the study area during the 18-year observation period.
Table 2. Descriptive statistics of climatic factors and indices in the study area during the 18-year observation period.
Climatic FactorMeanMin–Max
Precipitation (mm)953.66585.60–1525.10
Air temperature (°C)13.1212.07–14.40
Dry season water deficit (mm)76.03−115.70–547.70
PET (mm)494.13468.50–529.10
Table
Table 3. Descriptive statistics of structural attributes in the study sites. All silver fir trees over 10 cm (DBH) (N = 273) were measured.
Table 3. Descriptive statistics of structural attributes in the study sites. All silver fir trees over 10 cm (DBH) (N = 273) were measured.
Structural AttributesSites
A—BrloškoB—Bitoraj
Mean (Min–Max)
DBH (cm)67.50 (18.45–114.75)31.66 (11.55–61.70)
Growth increment (cm)0.42 (0.02–1.11)0.26 (0.002–0.93)
Crown diameter (m)4.49 (1.70–7.75)3.26 (1.40–6.54)
Crown length (%)50.93 (37.50–75.00)65.27 (12.50–75.00)
Crown illumination (%)35.43 (0.00–80.00)16.53 (0.00–60.00)
Table
Table 4. Spearman rank correlation between defoliation and structural attributes.
Table 4. Spearman rank correlation between defoliation and structural attributes.
Structural AttributesSites
A—BrloškoB—Bitoraj
Defoliation
DBH (cm)0.11−0.45 *
Growth increment (cm)−0.45 *−0.53 *
Crown diameter (m)−0.26 *−0.59 *
Crown length (%)−0.030.05
Crown shape0.32 *0.10
Crown illumination0.29 *−0.43 *
Social status of the tree−0.140.40 *
Stork’s nest0.34 *−0.08
* Statistically significant at 5% level (p < 0.05).
Table
Table 5. Results of repeated measure ANOVA for tree retention time as a dependent variable for both sites, crown defoliation class, and interaction between site and defoliation class. Significant effects are bolded.
Table 5. Results of repeated measure ANOVA for tree retention time as a dependent variable for both sites, crown defoliation class, and interaction between site and defoliation class. Significant effects are bolded.
EffectdfMSFp
Site139.4113.1750.00034
Error a2712.99
Defoliation class4984.2335.765<0.0001
Site * defoliation class465.862.390.0489
Error b108427.52
Note: * adjustment with Greenhouse–Geisser epsilon 0.6054.
Table
Table 6. Transition dynamics of trees between crown defoliation classes, and results of the log-rank test.
Table 6. Transition dynamics of trees between crown defoliation classes, and results of the log-rank test.
Defoliation ClassA—Brloško (N = 79)B—Bitoraj (N = 194)Log-Rank Test
N *%N *%Chi2p
11417.722412.371.4770.2242
24759.499951.030.3560.5508
34253.169448.450.0500.8231
45468.3512966.493.7100.0541
53746.847136.630.0050.9456
61215.192110.827.4290.0064
Note: N * represents the number of trees that entered the given defoliation class during the 18-year observation period.
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Ugarković, D.; Jazbec, A.; Seletković, I.; Tikvić, I.; Paulić, V.; Ognjenović, M.; Marušić, M.; Potočić, N. Silver Fir Decline in Pure and Mixed Stands at Western Edge of Spread in Croatian Dinarides Depends on Some Stand Structure and Climate Factors. Sustainability 2021, 13, 6060. https://doi.org/10.3390/su13116060

AMA Style

Ugarković D, Jazbec A, Seletković I, Tikvić I, Paulić V, Ognjenović M, Marušić M, Potočić N. Silver Fir Decline in Pure and Mixed Stands at Western Edge of Spread in Croatian Dinarides Depends on Some Stand Structure and Climate Factors. Sustainability. 2021; 13(11):6060. https://doi.org/10.3390/su13116060

Chicago/Turabian Style

Ugarković, Damir, Anamarija Jazbec, Ivan Seletković, Ivica Tikvić, Vinko Paulić, Mladen Ognjenović, Mia Marušić, and Nenad Potočić. 2021. "Silver Fir Decline in Pure and Mixed Stands at Western Edge of Spread in Croatian Dinarides Depends on Some Stand Structure and Climate Factors" Sustainability 13, no. 11: 6060. https://doi.org/10.3390/su13116060

APA Style

Ugarković, D., Jazbec, A., Seletković, I., Tikvić, I., Paulić, V., Ognjenović, M., Marušić, M., & Potočić, N. (2021). Silver Fir Decline in Pure and Mixed Stands at Western Edge of Spread in Croatian Dinarides Depends on Some Stand Structure and Climate Factors. Sustainability, 13(11), 6060. https://doi.org/10.3390/su13116060

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