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opencc-by-4.0Jun 2024View details →

Data & codes for "Changes in abundance and distribution of European forest bird populations depend on biome, ecological specialisation and traits"

<h1>1.    Selection of European forest bird species and classification of their biome preferences</h1> We selected all species that are related to forest and woodland based on two data sources: Storchová & Hořák (2018) and Tobias et al. (2022), resulting in 107 bird species studied (Data S1). We defined forest bird species as those using environments ranging from closed-canopy forests to more open-canopy woodlands (A. Lehikoinen & Virkkala, 2018; Storchová & Hořák, 2018; Tobias et al., 2022). We determined their biome specialisation using breeding distribution centroids and the overall breeding distribution of each of the species, using the global map of terrestrial ecoregions from Olson et al. (2001) and range data from European Breeding Bird Atlas 1 and 2 (Hagemeijer & Blair, 1997; Keller et al., 2020). We categorised species as Mediterranean, temperate, or boreal based on their predominant biogeographic region. We considered species commonly occurring over several biomes as “generalists”. For instance, we reclassified the two typically boreal species Glaucidium passerinum Linnaeus and Strix uralensis Pallas as “generalists” due to significant range expansions into central and southern Europe in recent decades, therefore no longer restricted to the boreal region. For the complete list of species, biome specialisation, traits, and specialisation indices, refer to Data S1. <h1>2.    Changes in abundance and distribution of European forest bird species</h1> We assessed long-term changes in European forest bird populations through two approaches: (i) changes in estimated total European-level species abundance over a 40-year timeframe; and (ii) changes in species spatial distribution over a 30-year timeframe (Fig. 1). We utilized the estimated trends in European-level population size (i.e., the total number of individuals) for each common native European bird species from 1980 to 2017, as reported by Burns et al. (2021). Three species out of the 107 studied forest species were missing in the original manuscript and we used data generated with the same method from 1980 to 2018 from the European assessment, Article 12 (https://nature-art12.eionet.europa.eu/article12/). These abundance trends were calculated by Burns et al. (2021) using multi-sourced annual times series. For each species, they gathered population estimates and trends from each European country as well as European Union (EU)-level population trends. They analysed these data with a Bayesian hierarchical model to reconstruct EU-level smoothed species population time series. The model outputs include an average annual rate of abundance change and an associated 95% credible interval (Burns et al., 2021). Therefore, we did not directly use the average annual rate of abundance change, as this would have led us to consider species with low uncertainty as similar to those with high uncertainty. To account for the uncertainty, we categorised species as (i) declining, i.e., annual rates below one, (ii) increasing, i.e., annual rates above one and (iii) stable, i.e., annual rate whose 95% CI overlap one, i.e., no significant change. To better acknowledge the magnitude of the abundance change, significant changes with rates below 0.98 were labelled as “strongly declining” (i.e., 6.5% of the 107 species), while those above 1.02 were labelled as “strongly increasing” (i.e., 11% of the 107 species). To evaluate the sensitivity of the decision to categorised abundance change data, we also analysed abundance trend as continuous variable (see Supporting Information Fig. S8). To determine changes in species distributions, we used a comparison of species distributions between two periods (i.e., 1985-1988 and 2013-2017) using the European Breeding Bird Atlas 1 and 2 (EBBA 1 & 2; Hagemeijer & Blair, 1997; Howard et al., 2023; Keller et al., 2020). Howard et al. (2023) provided calculations of observed colonisation and extinction areas at a 50 x 50 km resolution across Europe. We measured changes in range as the difference between colonisations and extinctions of each species, with negative values indicating contracting ranges and positive values indicating expanding ranges. Additionally, we calculated the shift in the centre of gravity of the distribution range between the two periods, as a distance (km) along the south-north gradient for each species (Howard et al., 2023). <h1>3.    Trait and specialisation data for European forest bird species</h1> We extracted data for six functional traits from several sources (Table 1). (i) The species temperature index (STI)represents the long-term average temperature within the species’ breeding range (A. Lehikoinen et al., 2021). (ii) Diet data during the breeding season were obtained from Storchová & Hořák (2018), classifying species into binary variables as vertebrate carnivorous, invertebrate carnivorous, and herbivores (combining the leaf and seed eaters). Storchová & Hořák (2018) classified species into a diet category when the corresponding food resource represented at least 10% of the species diet throughout the breeding season. Therefore, one species can be in several categories (i.e., omnivores). (iii) We obtained nesting site data from Pearman et al. (2014), classifying species into binary variables as ground nesters, tree hole nesters, or elevated nesters (> 1 m in a tree or shrub). We also included data on (iv) species dependence on old-growth forests (Data S1; mostly from Fraixedas et al. (2015) and Mönkkönen et al. (2014), if present on both references, we classified them as “1” and if only in one reference as “0.5”), (v) migration distance (Howard et al., 2023), and (vi) body mass (Tobias et al., 2022). Finally, we extracted and developed seven species specialisation indices. (i) We used an overall specialisation index based on multiple traits (i.e., temperature, diet, foraging behaviour and substrate, habitat, and nesting site), and (ii) a nesting specialisation index, both obtained from Morelli et al. (2019). Both indices represent species specialization based on the dispersion of trait preferences for each species: e.g., nesting specialism equal 0 for species that nest in all habitat type and equal 1 for species that nest in only one habitat type). They are both calculated using the Gini index of inequality, which measures overall dispersion across, e.g., all traits for the overall specialization, based on data from Pearman et al. (2014) and Storchová & Hořák (2018). For additional information, see Morelli et al. (2019). We also used (iii) the diet specialisation index, (iv) the species distribution range during the breeding season (hereafter “breeding range area”) and (v) the climatic niche breadth from Reif et al. (2016). The diet specialisation index was calculated as the coefficient of variation for diet preferences for each species, where high values denotes specialized species (Reif et al., 2016). The breeding range area was evaluated as the number of 50-km squares in the distribution maps in Europe occupied by each species during the reproduction period, and is based on EBBA 1 (Hagemeijer & Blair, 1997). The climatic niche breadth was calculated as the difference between the 5% hottest and the 5% coldest mean temperature between April and June in which each species occurs, using EBBA 1 (Hagemeijer & Blair, 1997; Reif et al., 2016). Additionally, (vi) we calculated a broadleaf forest specialisation index based on binary forest habitat preferences (Storchová & Hořák, 2018), assigning values of one for species found only in broadleaf forests; zero for those in coniferous forests, and 0.5 for those found in both. Lastly, (vii) we created a forest specialisation index based on the species habitat preferences (Storchová & Hořák, 2018). The forest specialisation index was calculated as the mean of species affinity across habitats. We used increasing habitat weights along a gradient of tree dominance: open habitats as 1, shrubland as 1.5, woodland as 2 (i.e., species associated with habitats structured by trees in lower density than in forest), forest generalist (found in both coniferous and broadleaf dense forests) as 3, and forest specialist (found only either in coniferous or broadleaf dense forests) as 4. For instance, the index value for species occurring either in shrubland, woodland or both broadleaf and coniferous forests is 2.167. <h1>4.    Data analysis</h1> Data analyses were conducted with R software version 4.4.1. (R Core Team, 2024). Given the non-independence of species due to their genetic relatedness, we accounted for interspecific phylogenetic distance in all models. We constructed the phylogenetic tree for the 107 European forest bird species using ‘rotl’ and ‘ape’ R-packages (Michonneau et al., 2022; Paradis et al., 2023). We used rotl as an interface with the "Open Tree of Life", employing tol_induced_subtree R-function to generate the phylogenetic tree and compute.brlen R-function to set branch lengths using Grafen’s computation. We generated separate phylogenetic trees for boreal (17), temperate (15), Mediterranean (16) and “generalist” (59) species to perform biome-specific analysis (see Supplementary Information, Figs. S1 & S2). To investigate the effects of functional traits and specialisation indices on abundance, range changes, and distribution shift, we used two regression methods. All methods were based on the relationships between a measure of change and a functional trait or specialisation index. Our sample unit is an individual forest bird species (i.e., one value for each species, either abundance or range change, or distribution shift). Abundance change was a categorical variable (i.e., strong decline – decline – stable – increase – strong increase), while range change (i.e., difference between colonisation and extinction) and distribution shift (i.e., south-north shift) were continuous variables. Therefore, to study abundance changes, we used proportional-odds linear mixed effects model using (Phylo)clmm R-function from the ‘ordinal’ R-package (Christensen, 2022). Interspecific phylogenetic relatedness was included as a random effect, reflecting the correlation between species based on phylogenetic distances (see also Hagge et al. (2021) and Seibold et al. (2015)). For distribution changes, we employed phylogenetic generalised least squares regression (PGLS) using the gls R-function from the ‘nlme’ R-package (Pinheiro et al., 2023). The phylogenetic correlation structure was integrated into PGLS using Pagel’s lambda parameter (λ; Pagel (1999)) a widely used measured of phylogenetic signal strength (see, e.g., Hagge et al., 2021; Triviño et al., 2013). Furthermore, we included latitude, a key driver of bird communities at broad scales (Luoto et al., 2007), as a fixed covariable (centroid latitude of the species’ breeding distribution) in all global models (i.e., species from all biomes together), except for the STI model due to strong correlation. For biome-specific analysis, we included latitude only in boreal species models for range change and distribution shift, as it significantly improved model fit (ΔAIC < -2). We did not add latitude for models specific to temperate, Mediterranean, and generalist species since it did not improve model fits (ΔAIC > -2). Additionally, we included breeding range area in range change and distribution shift models, assuming that species with larger ranges would exhibit larger shifts. We scaled predictors to a mean of 0 and standard deviation of 1 to facilitate effect size comparisons. We adjusted p-values using the Holm method (for n=3) to account for multiple testing of traits and specialisation indices on three response variables.

opencc-zeroApr 2022View details →

Data from: Ecological genetics of Juglans nigra: differences in early growth patterns of natural populations

Many boreal and temperate forest tree species distributed across large geographic ranges are composed of populations adapted to the climate they inhabit. Forestry provenance studies and common gardens provide evidence of local adaptation to climate when associations between fitness traits and the populations' home climates are observed. Most studies that evaluate tree height as a fitness trait do so at a specific point in time. In this study, we elucidate differences in early growth patterns in black walnut (Juglans nigra L.) populations by modeling height growth from seed up to age 11. The data comprise tree height measurements between ages 2 to 11 for 52 natural populations of black walnut collected through its geographic range and planted in one or more of 3 common gardens. We use the Chapman-Richards growth model in a mixed-effects framework and test whether populations differ in growth patterns by incorporating populations' home climate into the model. In addition, we evaluate differences in populations' absolute growth and relative growth based on the fitted model. Models indicated that populations from warmer climates had the highest cumulative growth through time, with differences in average tree height between populations from home climates with a mean annual temperature (MAT) of 13 °C and of 7 °C estimated to be as high as 80% at age 3. Populations from warmer climates were also estimated to have higher and earlier maximum absolute growth rate than populations from colder climates. In addition, populations from warm climates were predicted to have higher relative growth rates at any given tree size. Results indicate that natural selection may shape early growth patterns of populations within a tree species, suggesting that fast early growth rates are likely selected for in relatively mild environments where competition rather than tolerance to environmental stressors becomes the dominant selection pressure.

opencc-zeroApr 2022View details →

Data from: Towards a better ecological understanding of metacommunity stability: A multiscale framework to disentangle population variability and synchrony effects

1. Despite great progress in our understanding of the mechanisms governing ecosystem stability in local communities, we still lack knowledge at a larger spatial scale. Studying the stability of metacommunities requires assessing the temporal stability and synchrony of populations across space and organizational levels. Previous attempts to disentangle these effects have provided limited ecological interpretations, and conceptual improvements are needed to identify the underlying ecological processes. 2. We propose an extended framework aiming at disentangling simultaneously the relative effects of population stability and different types of synchronies on metacommunity stability. We adapted previous methods of decomposing stability into a new set of indices associated with clearer ecological hypotheses. Particularly, we provide synchrony indices that are not affected by statistical properties of the metacommunity but focus on species responses to environment, demography, and interactions. We applied this framework to a unique dataset describing the sorted biomass of individual plant populations, across 12 communities of a species-rich meadow, and for 16 years. The communities were sampled in different treatments of fertilization and dominant removal to evaluate the effect of environmental heterogeneity on stability. 3. We found higher stability at a larger spatial scale, mainly due to statistical averaging (portfolio effect). The variability of individual populations was an important determinant of the stability of the whole metacommunity. Consistent with the hypothesis of a common response to environmental conditions, we found that the fluctuations of populations were mostly synchronized (within and between species) at a large spatial scale and tended to destabilize the metacommunity. On the other hand, opposite fluctuations (anti-synchrony) between populations occurred at the local scale, probably due to local species interactions. 4. Synthesis Our framework appears as a powerful tool to test how ecological processes occurring simultaneously at different spatial and organizational scales affect the stability of metacommunities. This study advances our ecological understanding of the processes underlying the stability of species-rich environments. --

opencc-zeroJun 2022View details →

Ecological and geographical marginality in rear edge populations of Palaearctic forest birds (data)

The centre–periphery hypothesis predicts that habitat suitability will decrease at the edge of a species' range, a pattern often questioned by empirical data. Here we explore if habitat suitability decreases southwards and shapes the abundance distribution of rear edge populations of forest birds within the restricted geographical setting of the south-western Palaearctic. We also test if birds endemic to the area fit more poorly to the latitudinal decrease of habitat suitability due to the putative effect of adaptations to regional conditions. Location: North-western Africa (Morocco) Time period: Present day Major taxa studied: Passerines (11 species) Methods: Bird occurrences were used to model species distribution and line transects were used to estimate bird abundance. Occurrence probabilities provided by species distribution models were used to display the spatial patterning of habitat suitability. Habitat suitability was employed to predict abundance after controlling for the effect of the distance to some regional source areas of forest birds (tree covered large areas). The species were classified as North African endemic according to an updated review of their taxonomic status. Results: Habitat suitability decreased southwards, supporting the predicted relationship between ecological and geographical marginality in most species. Abundance was positively correlated to habitat suitability and negatively correlated to distance to source areas. The taxonomic status of birds did not affect the patterns. Main conclusions: The southward decrease of habitat suitability predicted by the centre–periphery hypothesis shapes the distribution of rear edge populations of forest birds within the south-western Palaearctic. As most of these populations are endemic, the results suggest that they track the gradients in isolation within the geographical setting of north-western Africa. These results support the vulnerability of these isolated, peripheral populations of forest birds to large-scale environmental changes in a region under the effect of increasing drought and temperature.

opencc-zeroApr 2024View details →

Variation and plasticity in life-history traits and fitness of wild Arabidopsis thaliana populations are not related to their genotypic and ecological diversity

Despite its implications for population dynamics and evolution, the relationship between genetic and phenotypic variation in wild populations remains unclear. Here, we estimated variation and plasticity in life-history traits and fitness of the annual plant Arabidopsis thaliana in two common garden experiments that differed in environmental conditions. We used up to 306 maternal inbred lines from six Iberian populations characterized by low and high genotypic (based on whole-genome sequences) and ecological (vegetation type) diversity. Low and high genotypic and ecological diversity was found in edge and core Iberian environments, respectively. Given that selection is expected to be stronger in edge environments and that ecological diversity may enhance both phenotypic variation and plasticity, we expected genotypic diversity to be positively associated with phenotypic variation and plasticity. However, maternal lines, irrespective of the genotypic and ecological diversity of their population of origin, exhibited a substantial amount of phenotypic variation and plasticity for all traits. Furthermore, all populations harbored maternal lines with canalization (robustness) or sensitivity in response to harsher environmental conditions in one of the two experiments. Overall, we conclude that the environmental attributes of each population probably determine their genotypic diversity, but all populations maintain substantial phenotypic variation and plasticity for all traits, which represents an asset to endure in changing environments.

Figure 28 in Population ecology of Ctenolepisma (C.) udumalpetense (Insecta: Zygentoma: Lepismatidae) in a deciduous forest floor of the Trimurti Dam, Tamil Nadu, India

Figure 28. Regression of Temperature on C. (C.) udumalpetense population in third row.

Figure 21 in Population ecology of Ctenolepisma (C.) udumalpetense (Insecta: Zygentoma: Lepismatidae) in a deciduous forest floor of the Trimurti Dam, Tamil Nadu, India

Figure 21. Regression of humidity on C. (C.) udumalpetense population in first row.

Figure 20 in Population ecology of Ctenolepisma (C.) udumalpetense (Insecta: Zygentoma: Lepismatidae) in a deciduous forest floor of the Trimurti Dam, Tamil Nadu, India

Figure 20. Regression of Temperature on C. (C.) udumalpetense population in first row.

Figure 22 in Population ecology of Ctenolepisma (C.) udumalpetense (Insecta: Zygentoma: Lepismatidae) in a deciduous forest floor of the Trimurti Dam, Tamil Nadu, India

Figure 22 Regression of N (%) on C. (C.) udumalpetense population in first row.

opencc-by-4.0Feb 2024View details →

Population dynamics and socio-ecological trajectories explain the emergence of farming in Late Neolithic South-eastern Norway

The repository contains radiocarbon data and code for the paper "Population dynamics and socio-ecological trajectories explain the emergence of farming in Late Neolithic South-eastern Norway", published in the Journal of Neolithic Archaeology. <a href="https://www.jna.uni-kiel.de/index.php/jna/article/view/1562">Population Dynamics and Socio-ecological Trajectories Explain the Emergence of Farming in Late Neolithic Southeast Norway | Journal of Neolithic Archaeology</a>. Abstract This paper examines the emergence of farming in Late Neolithic Southeast Norway. A summed probability distribution of radiocarbon dates is used to infer population dynamics and together with a chronological model using dated samples from post-built houses, cultivation layers and cereal grains, it is argued that the introduction of farming was swift and caused by incoming farmers. It is further explored how a low population during the Middle Neolithic period, cause by shifting environmental conditions, was central to the rapid population shift and economic change seen in the Late Neolithic, from ca. 2200 cal BC.

opencc-by-4.0Oct 2019View details →

Figure 3 in The Population Ecology of (Kusn.) Woronow in the Highlands of the Republic of Adygea

Figure 3. The location of Oshten Mount populations of G. oschtenica.

opencc-by-4.0Oct 2019View details →

Figure. 2 in The Population Ecology of (Kusn.) Woronow in the Highlands of the Republic of Adygea

Figure. 2. The location of Lago-Naki Plateau populations of G. oschtenica.

opencc-by-4.0Oct 2019View details →

Figure 1 in The Population Ecology of (Kusn.) Woronow in the Highlands of the Republic of Adygea

Figure 1. Photo of G. oschtenica.

Fig. 1 in Morphological and ecological features of peripherial local populations of Bufo raddei Str. within the north western part of their habitat

Fig. 1. Sites of registration of Mongolian toad on the border the North-West of the area.

Fig. 3 in Morphological and ecological features of peripherial local populations of Bufo raddei Str. within the north western part of their habitat

Fig. 3. The age structure of the population of Mongolian toad, N=42 (East Pribaikalje).

Fig. 2 in Morphological and ecological features of peripherial local populations of Bufo raddei Str. within the north western part of their habitat

Fig. 2. The age structure of the population of Mongolian toad, N=41 (West Pribaikalje).

Fig. 4 in Morphological and ecological features of peripherial local populations of Bufo raddei Str. within the north western part of their habitat

Fig. 4. Dimensions of juveniles after metamorphosis, N=152 (West Pribaikalje).

opencc-by-4.0Nov 2017View details →

THE ORTHODOX CHURCH AND THE PRESERVATION OF THE ECOLOGICAL BALANCE OF THE POPULATION IN RUSSIA

The article analyzes ecological problems associated with religion and faith, which is especially noticeable among the inhabitants of megacities. It is shown that in order to preserve nature, it is necessary to include environmental education in the priority tasks of universal education. Particular attention is drawn to different approaches to environmental problems.

opencc-zeroAug 2021View details →

Codes: A new approach to interspecific synchrony in population ecology using tail association

Standard methods for studying the association between two ecologically important variables provide only a small slice of the information content of the association, but statistical approaches are available that provide comprehensive information. In particular, available approaches can reveal tail associations, i.e., accentuated or reduced associations between the more extreme values of variables. We here study the nature and causes of tail associations between phenological or population-density variables of co-located species, and their ecological importance. We employ a simple method of measuring tail associations which we call the partial Spearman correlation. Using multidecadal, multi-species spatiotemporal datasets on aphid first flights and marine phytoplankton population densities, we assess the potential for tail association to illuminate two major topics of study in community ecology: the stability or instability of aggregate community measures such as total community biomass and its relationship with the synchronous or compensatory dynamics of the community's constituent species; and the potential for fluctuations and trends in species phenology to result in trophic mismatches. We find that positively associated fluctuations in the population densities of co-located species commonly show asymmetric tail associations, i.e., it is common for two species' densities to be more correlated when large than when small, or vice versa. Ordinary measures of association such as correlation do not take this asymmetry into account. Likewise, positively associated fluctuations in the phenology of co-located species also commonly show asymmetric tail associations. We provide evidence that tail associations between two or more species' population density or phenology time series can be inherited from mutual tail associations of these quantities with an environmental driver. We argue that our understanding of community dynamics and stability, and of phenologies of interacting species, can be meaningfully improved in future work by taking into account tail associations.