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Recent work has shown that the idiosyncrasies of the observer can contribute more to the variance of social judgments of faces than the features of the faces. However, it is unclear what conditions determine the relative contributions of shared and idiosyncratic variance. Here, we examine two conditions: type of judgment and diversity of face stimuli. First, we show that for simpler, directly observable judgments that are consistent across observers (e.g., masculinity) shared exceeds idiosyncratic variance, whereas for more complex and less directly observable judgments (e.g., trustworthiness), idiosyncratic exceeds shared variance. Second, we show that judgments of more diverse face images increase the amount of shared variance. Finally, using machine-learning methods, we examine how stimulus (e.g., incidental emotion resemblance, skin luminosity) and observer variables (e.g., race, age) contribute to shared and idiosyncratic variance of judgments. Overall, our results indicate that an observer's age is the most consistent and best predictor of idiosyncratic variance contributions to face judgments measured in the current research. Public Significance Statement: Group-level models of judgment have provided important insights into how individuals view others. However, emerging evidence suggests that group-level averages explain only a portion of the reliable variance, necessitating models that represent the idiosyncrasies of the individual. Despite this evidence, little is known about the relative contributions of the stimulus and perceiver. In the current work, we provide evidence that the variance explained by the stimulus and perceiver is not fixed, but rather depends on theoretically and practically important factors, including the type of judgment being examined and the diversity of the stimulus set being evaluated. [ABSTRACT FROM AUTHOR]

The emergence of metacommunity theory has provided a framework for studying the spatial structure of biological communities. To unravel the underlying driving mechanisms of macroinvertebrate metacommunity structure and diversity, this paper evaluates macroinvertebrate data from a water body in eastern China using variance decomposition and stratified partitioning. The results suggest that spatial processes dominate macroinvertebrate metacommunity structure, while the combined effects of spatial processes, aquatic environment, and geoclimatic factors also explain part of the macroinvertebrate community structure. Spatial processes, aquatic environment, and geoclimatic factors significantly influenced macroinvertebrate alpha diversity and indirectly influenced beta diversity through alpha diversity. Therefore, the significant effects of spatial processes and geoclimatic variables cannot be ignored in biological assessments, especially biodiversity assessments. Our findings elucidate the metacommunity dynamics in the region and provide crucial information for conservation planning in riverine ecosystems. [ABSTRACT FROM AUTHOR]

The emergence of metacommunity theory has provided a framework for studying the spatial structure of biological communities. To unravel the underlying driving mechanisms of macroinvertebrate metacommunity structure and diversity, this paper evaluates macroinvertebrate data from a water body in eastern China using variance decomposition and stratified partitioning. The results suggest that spatial processes dominate macroinvertebrate metacommunity structure, while the combined effects of spatial processes, aquatic environment, and geoclimatic factors also explain part of the macroinvertebrate community structure. Spatial processes, aquatic environment, and geoclimatic factors significantly influenced macroinvertebrate alpha diversity and indirectly influenced beta diversity through alpha diversity. Therefore, the significant effects of spatial processes and geoclimatic variables cannot be ignored in biological assessments, especially biodiversity assessments. Our findings elucidate the metacommunity dynamics in the region and provide crucial information for conservation planning in riverine ecosystems. [ABSTRACT FROM AUTHOR]

Context: There has been a limited amount of research which comparatively examines the local and landscape scale ecological determinants of the community structure of both riparian and aquatic bird communities in floodplain ecosystems. Objectives: Here, we quantified the contribution of local habitat structure, land cover and spatial configuration of the sampling sites to the taxonomical and functional structuring of aquatic and terrestrial bird communities in a relatively intact floodplain of the river Danube, Hungary. Methods: We used the relative abundance of species and foraging guilds as response variables in partial redundancy analyses to determine the relative importance of each variable group. Results: Local-scale characteristics of the water bodies proved to be less influential than land cover and spatial variables both for aquatic and terrestrial birds and both for taxonomic and foraging guild structures. Purely spatial variables were important determinants, besides purely environmental and the shared proportion of variation explained by environmental and spatial variables. The predictability of community structuring generally increased towards the lowest land cover measurement scales (i.e., 500, 250 or 125 m radius buffers). Different land cover types contributed at each scale, and their importance depended on aquatic vs terrestrial communities. Conclusions: These results indicate the relatively strong response of floodplain bird communities to land cover and spatial configuration. They also suggest that dispersal dynamics and mass-effect mechanisms are critically important for understanding the structuring of floodplain bird communities, and should therefore be considered by conservation management strategies. [ABSTRACT FROM AUTHOR]

Abstract The aboveground biomass (AGB) of grassland, a crucial indicator of productivity, is anticipated to widespread changes in key ecosystem attributes, functions and dynamics. Variations in grassland AGB have been extensively documented across various spatial and temporal scales. However, a precise method to disentangle long-term effects from short-term effects on grassland AGB and assess the attribution of explanatory factors for AGB change remains elusive. This study aimed to quantify the impact of key climatic factors, soil properties, and grazing intensity on grassland AGB changes, utilizing data spanning the 1980s and the 2000s in Northern China. The Co-regression model was explored to separate the long-term effects and short-term effects of grassland AGB, while the Generalized Linear Model (GLM) was utilized to analyze the contributions of key variables to AGB. This approach effectively avoids issues related to regression to the mean and mathematical coupling. The results revealed that the influence of climatic variables, soil texture and grazing intensity on grassland AGB changes could be decomposed into long-term, short-term and random effects. Long-term effects explained 73.6% of AGB variation, whereas short-term effect only accounted for 5.9% of AGB change. Additionally, the short-term effect was divided into direct and indirect effects, with the direct effect explaining 1.3% of AGB variation, and the indirect effect explained 4.6% of AGB dynamics. The relative importance of key variables in grassland AGB was assessed, identifying soil parameters and precipitation as the main driving factors in the study area. This study introduces a robust methodology to enhance model performance in distinguishing long-term and short-term effects on grassland AGB, contributing to the sustainable development of grassland ecology in similar regions.

Different mechanisms act to structure metacommunities. Among them, the most studied are those related to environmental and spatial drivers. Also, most studies on metacommunities are based on data obtained in snapshot surveys, hindering the test of other potential mechanisms, including historical effects. Here, we quantified the relative importance of different sets of variables that could potentially structure zooplankton communities in 39 small reservoirs in Midwest Brazil. In addition to local environmental, spatial, and land use variables, as a proxy for potential priority effects, we tested the effect of earlier zooplankton composition on (later) zooplankton metacommunity structure. The relative importance of these sets of explanatory variables varied over time. However, earlier zooplankton community data were, in general, the most consistent predictors (especially for microcrustaceans) of zooplankton community structure. This result may indicate the role of historical effects on later zooplankton metacommunity structure. Our results highlight the importance of considering multiple surveys and past community data in spatiotemporal studies aiming to unveil the determinants of zooplankton metacommunity structure. [ABSTRACT FROM AUTHOR]

The aboveground biomass (AGB) of grassland, a crucial indicator of productivity, is anticipated to widespread changes in key ecosystem attributes, functions and dynamics. Variations in grassland AGB have been extensively documented across various spatial and temporal scales. However, a precise method to disentangle long-term effects from short-term effects on grassland AGB and assess the attribution of explanatory factors for AGB change remains elusive. This study aimed to quantify the impact of key climatic factors, soil properties, and grazing intensity on grassland AGB changes, utilizing data spanning the 1980s and the 2000s in Northern China. The Co-regression model was explored to separate the long-term effects and short-term effects of grassland AGB, while the Generalized Linear Model (GLM) was utilized to analyze the contributions of key variables to AGB. This approach effectively avoids issues related to regression to the mean and mathematical coupling. The results revealed that the influence of climatic variables, soil texture and grazing intensity on grassland AGB changes could be decomposed into long-term, short-term and random effects. Long-term effects explained 73.6% of AGB variation, whereas short-term effect only accounted for 5.9% of AGB change. Additionally, the short-term effect was divided into direct and indirect effects, with the direct effect explaining 1.3% of AGB variation, and the indirect effect explained 4.6% of AGB dynamics. The relative importance of key variables in grassland AGB was assessed, identifying soil parameters and precipitation as the main driving factors in the study area. This study introduces a robust methodology to enhance model performance in distinguishing long-term and short-term effects on grassland AGB, contributing to the sustainable development of grassland ecology in similar regions. Highlights: Co-regression model was effective to separate long- and short- terms impact of AGB. The effect of long-term factors on AGB was higher than that of short-term factors. Soil parameter and precipitation were major driving factors to affect AGB change. [ABSTRACT FROM AUTHOR]

The future trajectory of global forests is closely intertwined with tree demography, and a major fundamental goal in ecology is to understand the key mechanisms governing spatio‐temporal patterns in tree population dynamics. While previous research has made substantial progress in identifying the mechanisms individually, their relative importance among forests remains unclear mainly due to practical limitations. One approach to overcome these limitations is to group mechanisms according to their shared effects on the variability of tree vital rates and quantify patterns therein. We developed a conceptual and statistical framework (variance partitioning of Bayesian multilevel models) that attributes the variability in tree growth, mortality, and recruitment to variation in species, space, and time, and their interactions – categories we refer to as organising principles (OPs). We applied the framework to data from 21 forest plots covering more than 2.9 million trees of approximately 6500 species. We found that differences among species, the species OP, proved a major source of variability in tree vital rates, explaining 28–33% of demographic variance alone, and 14–17% in interaction with space, totalling 40–43%. Our results support the hypothesis that the range of vital rates is similar across global forests. However, the average variability among species declined with species richness, indicating that diverse forests featured smaller interspecific differences in vital rates. Moreover, decomposing the variance in vital rates into the proposed OPs showed the importance of unexplained variability, which includes individual variation, in tree demography. A focus on how demographic variance is organized in forests can facilitate the construction of more targeted models with clearer expectations of which covariates might drive a vital rate. This study therefore highlights the most promising avenues for future research, both in terms of understanding the relative contributions of groups of mechanisms to forest demography and diversity, and for improving projections of forest ecosystems. [ABSTRACT FROM AUTHOR]

Evidence from previous research suggests that frame-of-reference (FOR) training is effective at improving assessor ratings in many organizational settings. Yet no research has presented a thorough examination of systematic sources of variance (assessor-related effects, evaluation settings, and measurement design features) that might influence training effectiveness. Using a factorial ANOVA and variance components analyses on a database of four studies of frame-of-reference assessor training, we found that (a) training is most effective at identifying low levels of performance and (b) the setting of the training makes little difference with respect to training effectiveness. We also show evidence of the importance of rater training as a key determinant of the quality of performance ratings in general. Implications for FOR training theory and practice are discussed. [ABSTRACT FROM AUTHOR]

Forecasting invasion risk under future climate conditions is critical for the effective management of invasive species, and species distribution models (SDMs) are key tools for doing so. However, SDM‐based forecasts are uncertain, especially when correlative statistical models extrapolate to nonanalog environmental domains, such as future climate conditions. Different assumptions about the functional form of the temperature–suitability relationship can impact predicted habitat suitability under novel conditions. Hence, methods to understand the sources of uncertainty are critical when applying SDMs. Here, we use high‐resolution predictions of lake water temperatures to project changes in habitat suitability under future climate conditions for an invasive macrophyte (Myriophyllym spicatum). Future suitability was predicted using five global circulation models and three statistical models that assumed different species–temperature functional responses. The suitability of lakes for M. spicatum was overall predicted to increase under future climate conditions, but the magnitude and direction of change in suitability varied greatly among lakes. Variability was most pronounced for lakes under nonanalog temperature conditions, indicating that predictions for these lakes remained highly uncertain. Integrating predictions from SDMs that differ in their species–environment response function, while explicitly quantifying uncertainty across analog and nonanalog domains, can provide a more robust and useful approach to forecasting invasive species distribution under climate change. [ABSTRACT FROM AUTHOR]

Differences within species (Intraspecific trait variation - ITV) contribute substantially to overall trait variability and environmental harshness can reduce among-species variation. While aboveground traits have received considerable attention, knowledge about ITV in fine-root traits and how it differs from ITV in aboveground traits remains limited. This study examined the partitioning of trait variation aboveground and fine-root traits in 52 European herbaceous species and how such proportions change in response to drought, offering valuable insights for accurate functional species characterization and inter-species comparisons. We studied seven morphological aboveground and fine-root traits under drought and well-watered conditions in a greenhouse experiment. Linear mixed effect models and permutational multivariate analysis of variance (PERMANOVA) were employed to decompose trait variation, ensuring the robustness of our results. We also calculated variance partitioning for the combination of aboveground traits and the combination of fine-root traits, as well as pairs of analogous leaf and fine-root traits (i.e., traits that fulfill similar functions) for each treatment (control and drought). Among-species trait differences explained a greater proportion of overall variance than within-species variation, except for root dry matter content (RDMC). Height and leaf area stood out, with species' identity accounting for 87-90% of total trait variation. Drought had no significant effect on the proportions of variation in any of the traits. However, the combination of fine-root traits exhibited higher intraspecific variability (44-44%) than aboveground traits (19-21%) under both drought and control. Analogous root traits also showed higher ITV (51-50%) than analogous leaf traits (27-31%). Our findings highlight substantial within-species variation and the nuanced responses of fine-root traits, particularly RDMC, suggesting root traits' flexibility to soil heterogeneity that fosters less differentiation among species. Among-species trait differences, especially aboveground, may underscore distinct strategies and competitive abilities for resource acquisition and utilization. This study contributes to elucidate the mechanisms underlying the multifunctionality of the above- and belowground plants compartments. [ABSTRACT FROM AUTHOR]

The contrasting hydraulic traits observed among different plant life forms are shaped by entangled environmental and evolutionary processes. However, we lack understanding of the relative importance of life form, climate and phylogeny in explaining the variance of hydraulic traits.We analysed seven hydraulic traits and eleven climatic variables of 150 Fabaceae species representing three life forms from 62 sites worldwide, using phylogenetic comparative analyses and variance partitioning.The phylogenetic signal found in most traits disappeared after considering life form, indicating that phylogenetic conservatism in traits originated from the divergence among life forms. The trait‐climate relationships were also phylogenetically dependent, implying that trait responses are driven by climate and phylogeny together. Variance partitioning showed that phylogeny and climate explained greater trait variation than life form did.Synthesis. The climate‐driven hydraulic trait responses in Fabaceae still existed with phylogeny being considered, suggesting that this large family may be particularly sensitive to climate change. Our results emphasise the need to include phylogeny in plant hydraulic adaptation studies under future climate change. [ABSTRACT FROM AUTHOR]

The relative importance of abiotic and biotic factors in shaping forest biomass stocks and fluxes remains a controversial issue. Here, using data gathered from 39 1 ha plots located in flooded and terra firme mature tropical lowland forests of the Amazon and Orinoquia regions of Colombia, we evaluated the importance of climate, soil fertility, and flooding, as well as tree taxonomic/phylogenetic diversity and forest structural properties, in determining the aboveground biomass stocks (AGB; Mg ha−1) and aboveground woody productivity (AWP; Mg ha−1 year−1). Using information‐theoretic multimodel inference and variance partitioning we found that forest structural features such as the number of trees with diameter at breast height ≥ 70 cm, and wood density, are the main drivers of variation in AGB. However, taxonomic diversity also contributes to AGB because it is associated with more large trees in these forests. In contrast, the key drivers of AWP in these forests were soil P and Mg concentrations, with no significant effects of diversity indices. These findings emphasize the need to include major soil cations other than N and P (e.g. Mg) in experimental studies to improve our understanding about the extent to which soil fertility can modulate increases in forest AWP due to climate change. Terra firme forests had higher AGB stocks than flooded forests, but both had similar AWP; and we found similar results for the drivers of AGB and AWP between flooded and terra firme forests. Our results provide limited evidence for strong effects of plant diversity on AGB or AWP. Therefore, we call for caution on generalizations of nature‐based initiatives aiming to preserve diversity based on maximizing carbon stocks and productivity, due to the complex nature of the processes controlling carbon accumulation and carbon fluxes in tropical forests. [ABSTRACT FROM AUTHOR]

During ontogeny, the increase in body size forces species to make trade‐offs between their food requirements, the conditions necessary for growth and reproduction as well as the avoidance of predators. Ontogenetic changes are leading species to seek out habitats and food resources that meet their needs. To this end, ontogenetic changes in nocturnal habitat (vertical use of the water column) and in the type of food resources (based on stable isotopes of nitrogen) were investigated in 12 species of deep pelagic fish from the Bay of Biscay in the Northeast Atlantic. Our results revealed the existence of major differences in the ontogenetic strategies employed by deep pelagic fishes. Some species showed ontogenetic changes in both vertical habitat use and food resources (e.g. Jewel lanternfish (Lampanyctus crocodilus) and Atlantic soft pout (Melanostigma atlanticum)). In contrast, other species showed no ontogenetic change (e.g. Koefoed's searsid (Searsia koefoedi) and Lancet fish (Notoscopelus kroyeri)). Some species only changed food resources (e.g. Spotted lanternfish (Myctophum punctatum), Spotted barracudina (Arctozenus risso) and Stout sawpalate (Serrivomer beanii)), while others seemed to be influenced more by depth than by trophic features (e.g. Bluntsnout smooth‐head (Xenodermichthys copei) and Olfer's Hatchetfish (Argyropelecus olfersii)). These results suggest that to meet their increasing energy requirements during ontogeny, some species have adopted a strategy of shifting their food resources (larger prey or prey with a higher trophic level), while others seemed to maintain their food resources but are most likely increasing the quantity of prey ingested. As fish species can have different functional roles during their development within ecosystems, characterising ontogenetic changes in mesopelagic fish species is a crucial step to be considered in future research aimed at understanding and modelling the complexity of deep‐pelagic food webs. [ABSTRACT FROM AUTHOR]

Desiccation stress is lethal to most animals. However, some microinvertebrate groups have evolved coping strategies, such as the ability to undergo anhydrobiosis (i.e. survival despite the loss of almost all body water). Tardigrades are one such group, where the molecular mechanisms of anhydrobiosis have been more thoroughly studied. Despite the ecological, evolutionary and biotechnological importance of anhydrobiosis, little is known about its inter‐ and intra‐specific variability nor its relationship with natural habitat conditions or phylogenetic history.We developed a new index—anhydrobiotic recovery index (ARI)—to evaluate the anhydrobiotic performance of tardigrade populations from the family Macrobiotidae. Moreover, we compared the explanatory role of habitat humidity and phylogenetic history on this trait using a variance partitioning approach.We found that ARI is correlated with both microhabitat humidity and yearly rainfall, but it is mostly driven by phylogenetic niche conservatism (i.e. a high portion of ARI variation is explained by phylogeny alone). Finally, we showed that anhydrobiotic performance is highly variable, even between closely related species, and that their response to local ecological conditions is tightly linked to their phylogenetic history.This study not only presents key insights into an emerging model system, but also provides a new methodological approach for wider scale studies of the ecological and evolutionary implications of anhydrobiosis. [ABSTRACT FROM AUTHOR]

Abstract The demand for low-cost and time-efficient biomonitoring and ecological assessment strategies has increased due to threats to biodiversity. We evaluated the ability of surrogates (genera and biovolume classes) to access information provided by diatom species. Moreover, we investigated whether the relative importance of spatial and environment on diatom communities identified at the genus or classified at biovolume classes reflects the ecological responses at the species. We used biotic, environmental, and spatial data from Pampa streams. We employed Procrustes analysis to detect whether the spatial variation of communities at the species level was represented by the surrogates and variation partitioning to evaluate the relative importance of spatial and environment. We found high congruence between the surrogates and diatom species communities. Furthermore, whilst both spatial and environment were important to explain species composition, only the environment was important for both surrogates. We suggest that the use of genus-level determinations can provide information about the environmental relationships of species, whereas biovolume classes may be useful to detect changes in diatom communities. These results are a first step to seek for strategies aiming to simplify biological monitoring and assessments at pampean streams, especially considering the demand for the identification of organisms at the species.

Evidence is accumulating that foraging behaviour and diet link to personality traits, yet little is known about how these associations emerge during development. Behaviour is expected to become more consistent with age and with foraging experience. We compared exploratory behaviour and diet variances of juvenile and adult red knots, Calidris canutus islandica , shortly after migration to marine intertidal mudflats from terrestrial tundra breeding grounds. By identifying the timing of the switch from terrestrial to marine isotopic signatures, we were also able to ask whether juveniles that arrived earlier, and thus had longer experiences in a particular environment (nonbreeding grounds), were more consistent in exploration behaviour. We found that juveniles had a more diverse diet and were less repeatable in their exploratory behaviour than adults. This change in repeatability was largely driven by greater within-individual behavioural variance in the juveniles compared to the adults. The amount of time juveniles experienced in a marine environment did not affect the variation in their exploratory behaviour, suggesting that consistency in exploration was developed over a longer period than the 4 weeks of our study. Our findings suggest that after initial exploration of a novel habitat, juveniles likely try out foraging techniques which later develop into consistent behaviours that differ between individuals. This study illuminates how personality can develop with experience in a free-living animal. • Early foraging experiences can shape development of exploratory personalities. • Juvenile red knots have a more diverse diet than adults. • Juveniles are less repeatable in their exploratory behaviour than adults. • Juveniles have larger within-individual variance in behaviour than adults. [ABSTRACT FROM AUTHOR]

Metacommunity studies have demonstrated that local macroinvertebrate communities are structured not only by local environmental conditions but also by spatial processes. Effective bioassessment tools should account for spatial processes while doing so with the least amount of cost. In this study, we applied variance partition techniques based on redundancy analysis to assess the performance of three sets of benthic invertebrate metrics in detecting agricultural land-use effects in a SE Brazil rainforest watershed. Macroinvertebrate data were analyzed separately regarding their taxonomic, functional structure and bioindicator metrics developed for the study region. We stipulated that groups of metrics most sensitive to land-use effects should have the highest amount of variance explained by the joint effects of land use and environmental variation, independently of spatial structuring. Statistical analyses were repeated removing rare taxa in order to assess the effects of their inclusion in the responsiveness of each group of metrics. Traditional bioindicator metrics were more responsive to environmental variation associated with agriculture than taxa abundances and functional attributes. Furthermore, a few common taxa drove a high proportion of the variation observed in invertebrate communities, regardless of how invertebrate data were organized. Similar analytic approaches have the potential to be useful in curtailing sorting and identification efforts when developing macroinvertebrate-based biomonitoring protocols, especially in areas where information regarding the taxonomy of benthic communities is still poorly described. [ABSTRACT FROM AUTHOR]

Questions: Due to their high ecological and agronomical variability, borderland regions offer an excellent opportunity to study assembly patterns. In this study we compared the influence of various factors on summer annual weed communities consisting of both native and introduced species. Location: The borderland region of Austria and Hungary. Methods: We assessed the abundance of weed species in 300 fields of six summer annual crops, and collected information on 26 background variables for each plot. We applied redundancy analysis (RDA) to estimate multivariate species responses and variation partitioning to compare the relative importance of three groups of variables (environmental variables, management variables, and country as a singleton group), and we also checked for statistical association between country and the predictors of the other two groups. Results: The full RDA model explained 22.02% of the variance in weed species composition. Variation partitioning showed that environment and management had similarly high (~8%) influence on weeds, while country had a modest yet substantial (~1%) effect, and there was relatively little overlap between the variance attributable to the three groups. Comparing the individual variables, country ranked third (after preceding crop, and actual crop). The effects of 15 further variables were also significant, including seven management, and seven environmental variables, as well as the location of the sampling plots within the fields. Comparisons between the countries showed that farming type, preceding crops, tillage system, tillage depth and field size were significantly different between the countries. Conclusions: Country exhibited a small but significant influence on weed community composition, which could not be explained with easily accessible management and environmental variables. This suggests that the distinct historical agronomical background of the two countries, possibly involving some legacies of the former Iron Curtain period, still has an impact on the weed species composition of arable fields. [ABSTRACT FROM AUTHOR]

Stomatal density, stomatal length and carbon isotope composition can all provide insights into environmental controls on photosynthesis and transpiration. Stomatal measurements can be time-consuming; it is therefore wise to consider efficient sampling schemes. Knowing the variance partitioning at different measurement levels (i.e. among stands, plots, trees, leaves and within leaves) can aid in making informed decisions around where to focus sampling effort. In this study, we explored the effects of nitrogen (N), phosphorus (P) and calcium silicate (CaSiO3) addition on stomatal density, length and carbon isotope composition (δ13C) of sugar maple (Acer saccharum Marsh.) and yellow birch (Betula alleghaniensis Britton). We observed a positive but small (8%) increase in stomatal density with P addition and an increase in δ13C with N and CaSiO3 addition in sugar maple, but we did not observe effects of nutrient addition on these characteristics in yellow birch. Variability was highest within leaves and among trees for stomatal density and highest among stomata for stomatal length. To reduce variability and increase chances of detecting treatment differences in stomatal density and length, future protocols should consider pretreatment and repeated measurements of trees over time or measure more trees per plot, increase the number of leaf impressions or standardize their locations, measure more stomata per image and ensure consistent light availability. [ABSTRACT FROM AUTHOR]

glmm.hp is an R package designed to evaluate the relative importance of collinear predictors within generalized linear mixed models (GLMMs). Since its initial release in January 2022, it has been rapidly gained recognition and popularity among ecologists. However, the previous glmm.hp package was limited to work GLMMs derived exclusively from the lme4 and nlme packages. The latest glmm.hp package has extended its functions. It has integrated results obtained from the glmmTMB package, thus enabling it to handle zero-inflated generalized linear mixed models (ZIGLMMs) effectively. Furthermore, it has introduced the new functionalities of commonality analysis and hierarchical partitioning for multiple linear regression models by considering both unadjusted R 2 and adjusted R 2. This paper will serve as a demonstration for the applications of these new functionalities, making them more accessible to users. [ABSTRACT FROM AUTHOR]

Abstract During ontogeny, the increase in body size forces species to make trade‐offs between their food requirements, the conditions necessary for growth and reproduction as well as the avoidance of predators. Ontogenetic changes are leading species to seek out habitats and food resources that meet their needs. To this end, ontogenetic changes in nocturnal habitat (vertical use of the water column) and in the type of food resources (based on stable isotopes of nitrogen) were investigated in 12 species of deep pelagic fish from the Bay of Biscay in the Northeast Atlantic. Our results revealed the existence of major differences in the ontogenetic strategies employed by deep pelagic fishes. Some species showed ontogenetic changes in both vertical habitat use and food resources (e.g. Jewel lanternfish (Lampanyctus crocodilus) and Atlantic soft pout (Melanostigma atlanticum)). In contrast, other species showed no ontogenetic change (e.g. Koefoed's searsid (Searsia koefoedi) and Lancet fish (Notoscopelus kroyeri)). Some species only changed food resources (e.g. Spotted lanternfish (Myctophum punctatum), Spotted barracudina (Arctozenus risso) and Stout sawpalate (Serrivomer beanii)), while others seemed to be influenced more by depth than by trophic features (e.g. Bluntsnout smooth‐head (Xenodermichthys copei) and Olfer's Hatchetfish (Argyropelecus olfersii)). These results suggest that to meet their increasing energy requirements during ontogeny, some species have adopted a strategy of shifting their food resources (larger prey or prey with a higher trophic level), while others seemed to maintain their food resources but are most likely increasing the quantity of prey ingested. As fish species can have different functional roles during their development within ecosystems, characterising ontogenetic changes in mesopelagic fish species is a crucial step to be considered in future research aimed at understanding and modelling the complexity of deep‐pelagic food webs.

Question: In the current context of biodiversity erosion, functional approaches to the examination of community assembly mechanisms and better prediction of plant species fates have emerged. The assessment of trait variation patterns should be a powerful means of identifying community assembly mechanisms. However, most studies of trait variations and their consequences for individual performance (i.e., vegetative biomass) are usually incomplete as they focused on single ecological scales or filters, with no consideration of relationships between traits. Such research has provided a fragmented view of plant community assembly. Location: We examined macrophyte communities living in ponds of the sub‐Antarctic Iles Kerguelen. Methods: We measured traits related to resource acquisition and conservation in all occurring species, and examined their variation across temporal (years), spatial (sites), and taxonomic (between and within species) scales and in response to multiple abiotic and biotic habitat variables. The consequences of these trait variations and the effects of their correlation for plant individual performance were also explored. Results: Trait distributions were fairly conserved among sites, whereas we observed a large amount of intraspecific trait variation enabling individuals to resist filters. Responses to biotic and/or abiotic variables were trait‐dependent, and simultaneous trait responses should enable individual plants to face several simultaneous constraints. Almost all traits had direct or indirect effects on individual performance, indicating the need to consider trait relationships. Conclusion: The partitioning of trait variance is a relevant approach to the identification of the scale at which the most decisive processes for plant community assembly operate without the interference of scale dependency issues, and should orient further research. In addition, several biotic and abiotic variables should be considered in future studies to better understand the effects of environmental changes on plant communities. [ABSTRACT FROM AUTHOR]

The landscape scale response of ecological communities to environmental drivers can be challenging to efficiently summarise and differentiate from expected background turnover through time. Metacommunity structure can be encapsulated by fitting joint species distribution models (JSDMs) and partitioning the variance explained into environmental, spatial and species-codistribution components. Here we identify how these components respond through time with directed environmental change and propose these changes in metacommunity structure as an indicator of sustained directional pressure. Through simulations, we identify how declines in the variation explained by species codistribution could diagnose ecological disintegration, while increases in the explanatory power of environmental and spatial predictors may indicate losses in peripheral areas and dispersal limitations. We then test these results in two well-studied systems. Butterflies are known to be strongly responding to climate change, and we show that over 21 years the codistribution component declines for butterfly communities in southern England. By contrast, birds in the same region are thought to be responding less strongly to climatic pressure and, despite high occupancy turnover, do not show clear changes in metacommunity structure as measured by this approach. Our results suggest that these approaches could have a high potential to summarise and compare the impacts of external drivers on whole communities. [ABSTRACT FROM AUTHOR]

Premise: Although changes in plant phenology are largely attributed to changes in climate, the roles of other factors such as genetic constraints, competition, and self‐compatibility are underexplored. Methods: We compiled >900 herbarium records spanning 117 years for all eight nominal species of the winter‐annual genus Leavenworthia (Brassicaceae). We used linear regression to determine the rate of phenological change across years and phenological sensitivity to climate. Using a variance partitioning analysis, we assessed the relative influence of climatic and nonclimatic factors (self‐compatibility, range overlap, latitude, and year) on Leavenworthia reproductive phenology. Results: Flowering advanced by ~2.0 days and fruiting by ~1.3 days per decade. For every 1°C increase in spring temperature, flowering advanced ~2.3 days and fruiting ~3.3 days. For every 100 mm decrease in spring precipitation, each advanced ~6–7 days. The best models explained 35.4% of flowering variance and 33.9% of fruiting. Spring precipitation accounted for 51.3% of explained variance in flowering date and 44.6% in fruiting. Mean spring temperature accounted for 10.6% and 19.3%, respectively. Year accounted for 16.6% of flowering variance and 5.4% of fruiting, and latitude for 2.3% and 15.1%, respectively. Nonclimatic variables combined accounted for <11% of the variance across phenophases. Conclusions: Spring precipitation and other climate‐related factors were dominant predictors of phenological variance. Our results emphasize the strong effect of precipitation on phenology, especially in the moisture‐limited habitats preferred by Leavenworthia. Among the many factors that determine phenology, climate is the dominant influence, indicating that the effects of climate change on phenology are expected to increase. [ABSTRACT FROM AUTHOR]

At large scales, the mechanisms underpinning stability in natural communities may vary in importance due to changes in species composition, mean abundance, and species richness. Here we link species characteristics (niche positions) and community characteristics (richness and abundance) to evaluate the importance of stability mechanisms in 156 butterfly communities monitored across three European countries and spanning five bioclimatic regions. We construct niche‐based hierarchical structural Bayesian models to explain first differences in abundance, population stability, and species richness between the countries, and then explore how these factors impact community stability both directly and indirectly (via synchrony and population stability). Species richness was partially explained by the position of a site relative to the niches of the species pool, and species near the centre of their niche had higher average population stability. The differences in mean abundance, population stability, and species richness then influenced how much variation in community stability they explained across the countries. We found, using variance partitioning, that community stability in Finnish communities was most influenced by community abundance, whereas this aspect was unimportant in Spain with species synchrony explaining most variation; the UK was somewhat intermediate with both factors explaining variation. Across all countries, the diversity–stability relationship was indirect with species richness reducing synchrony which increased community stability, with no direct effects of species richness. Our results suggest that in natural communities, biogeographical variation observed in key drivers of stability, such as population abundance and species richness, leads to community stability being limited by different factors and that this can partially be explained due to the niche characteristics of the European butterfly assemblage. [ABSTRACT FROM AUTHOR]

Traits of organisms vary both at inter- and intraspecific levels. For macro-detritivores inhabiting lands and waters, there is only scattered information on the relative contribution of the intraspecific level for traits like litter consumption rates. This basic knowledge is nevertheless required to know how much the intraspecific level could matter to the study of macro-detritivore communities and ecosystem processes like leaf litter decomposition. We performed a laboratory experiment, where thirty individuals each of five abundant macro-detritivore species from a stream and a meadow ecosystem fed ash (Fraxinus excelsior) leaf litter in microcosms, twice at a 1-week interval. This nested and repeated design (individuals nested within species, species within ecosystems) was setup in controlled conditions and then analysed following a variance partitioning approach with linear mixed-effect models, to assess the variance attributable to different levels of biological organisation (i.e., inter- and intraspecific level). Then, we performed the same analysis, but separately on aquatic and terrestrial datasets. From the whole dataset, we demonstrated that half of the trait variation occurred at the interspecific level and a third at the intraspecific level. The variance found at the residual level, accounting for both measurement errors and for the variation of the same individuals between the two times (i.e., intra-individual variation), was significantly lower than what was observed at the other levels of biological organisation. Variance partitioning on separate aquatic and terrestrial datasets were consistent altogether, confirming the global pattern. With this study, we stress the relevance of the intraspecific level for future trait-based approaches applied to macro-detritivores.

Environmental factors act at multiple spatial scales in a hierarchical manner to shape the organization of biota. However, the relative influence of different scale-related factors is poorly known, especially in Atlantic Forest Blackwater streams. Therefore, we herein aimed to evaluate local, landscape and spatial factors that shape fish assemblages in 14 blackwater restinga coastal Atlantic Forest streams under natural conditions and verify species occurrence patterns among four sub-basins during the low-precipitation season. When we combined local, landscape and spatial factors, variance partitioning explained a high proportion of variation in species matrix. Local variables pH and Total Dissolved Solids explained most of the variability, and these were the most important factors in determining fish community structure. Significant differences in fish assemblage structure among the four sub-basins were observed, and Mimagoniates microlepis, Phalloceros harpagos, and Hollandichthys multifasciatus were the species that most contributed to this dissimilarity. The important contribution of local predictors, the high number of endemic species herein recorded, the presence of an endangered species (Spintherobolus broccae), and near pristine conditions, may be used as baseline conditions for the assessment of similar environments. [ABSTRACT FROM AUTHOR]

Aim: Area and environmental heterogeneity together explain most patterns of species diversity but disentangling their relative importance has been difficult. Here, we empirically examined this relationship and parsed their relative importance, and that of the heterogeneity—effective area trade‐off, at different spatial scales and in different spatial representations in simulations. Location: Alpine grasslands of 23 mountain ranges of southern and central Europe. Taxon: Vascular plants. Methods: We developed metrics of climatic and edaphic heterogeneity, using principal components analyses and the shoelace algorithm, and added elevation range. We applied commonality analysis to partition the unique and shared explanation of the observed vascular plant species richness among selected metrics. A simulation was developed to separate the relative importance of area and heterogeneity at different extents and representations of spatial nestedness, and the heterogeneity—effective area trade‐off was evaluated by altering spatial discreteness. Results: The explanation of the observed regional richness was shared by area and heterogeneity. The simulation revealed that heterogeneity was consistently more important, but less so among smaller areas. This qualitative pattern was maintained regardless of whether and how nestedness was represented. The heterogeneity–effective area trade‐off occurred in a few simulations of more discrete habitats. Main Conclusions: Scale dependence may account for discrepancies among past empirical studies wherein environmental heterogeneity has usually outweighed area in the explanation of species richness; and it is not affected by nestedness. The potential heterogeneity–effective area trade‐off may be limited to locations where the environmental heterogeneity is quite discrete or if the added environment is beyond the niches of any species in the potential pool. The significant importance of area per se in small territories indicates that microrefugia, even with an unlikely full range of heterogeneity, will suffer local extinctions in the face of climate change. [ABSTRACT FROM AUTHOR]

Research Summary: Hambrick and Quigley's (2014) "CEO in context" (CiC) technique leads to a much larger CEO effect than traditional ANOVA or multilevel modeling. We replicate H&Q's study, apply their CiC technique to a much more comprehensive U.S. sample, and assess the sensitivity of the model findings to variations in method and data. We generally confirm H&Q's finding of a high CEO effect, but find a smaller industry effect and a larger firm effect in our much larger sample. Applying the CiC technique with adjusted R2s has only a moderate impact on year, industry, and firm effects, but markedly reduces the CEO effect. We also document that CiC model findings are sensitive to sample characteristics, namely firm size and CEO tenure. Managerial Summary: Hambrick and Quigley (2014) introduced a new method to analyze the influence of CEOs on firm performance. The study's empirical analysis focused on large U.S. firms. We replicate the original study and extend it to a much larger, comprehensive sample of U.S. firms that is composed of 33,996 firm‐year observations, compared to 4,866 firm‐years in the original study. Controlling for the number of variables used in the estimations, the model attributes about a third of the total variance of firm performance (ROA) to the CEO. Further analyses show that the model findings differ for firms of different size and CEO tenure; the larger the firms and the longer the CEO tenures, the smaller tends to be the percentage of variance explained by the CEO. [ABSTRACT FROM AUTHOR]

Repeated social interactions with conspecifics and/or heterospecifics during early development may drive the differentiation of behavior among individuals. Competition is a major form of social interaction and its impacts can depend on whether interactions occur between conspecifics or heterospecifics and the directionality of a response could be specific to the ecological context that they are measured in. To test this, we reared tungara frog tadpoles (Engystomops pustulosus) either in isolation, with a conspecific tadpole or with an aggressive heterospecific tadpole, the whistling frog tadpole (Leptodactylus fuscus). In each treatment, we measured the body size and distance focal E. pustulosus tadpoles swam in familiar, novel and predator risk contexts six times during development. We used univariate and multivariate hierarchical mixed effect models to investigate the effect of treatment on mean behavior, variance among and within individuals, behavioral repeatability and covariance among individuals in their behavior between contexts. There was a strong effect of competition on behavior, with different population and individual level responses across social treatments. Within a familiar context, the variance in the distance swam within individuals decreased under conspecific competition but heterospecific competition caused more variance in the average distance swam among individuals. Behavioral responses were also context specific as conspecific competition caused an increase in the distance swam within individuals in novel and predator risk contexts. The results highlight that the impact of competition on among and within individual variance in behavior is dependent on both competitor species identity and context. [ABSTRACT FROM AUTHOR]

Summary: Background: Although the infant gut microbiota has been extensively studied, comprehensive assessment on the microbiota determinants including technical variables has not been performed in large infant cohorts. Methods: We studied the effect of 109 variables on the 16S rRNA gene amplicon-based gut microbiota profiles of infants sampled longitudinally from three weeks to two years of life in the Finnish HELMi birth cohort. Spot faecal samples from both parents were included for intra-family analyses, totalling to 7657 samples from 985 families that were evaluated for beta-diversity patterns using permutational multivariate analysis on Bray–Curtis distances, and differential abundance testing and alpha-diversity for variables of interest. We also assessed the effect of different taxonomic levels and distance methods. Findings: In time point-specific models, the largest share of variation explained, up to 2–6%, were seen in decreasing order for the DNA extraction batch, delivery mode and related perinatal exposures, defecation frequency and parity/siblings. Variables describing the infant gastrointestinal function were continuously important during the first two years, reflecting changes in e.g., feeding habits. The effect of parity/siblings on infant microbiota was modified by birth mode and exposure to intrapartum antibiotics, exemplifying the tight interlinkage of perinatal factors relevant for infant microbiota research. In total, up to 19% of the biological microbiota variation in the infant gut could be explained. Our results highlight the need to interpret variance partitioning results in the context of each cohort's characteristics and microbiota processing. Interpretation: Our study provides a comprehensive report of key factors associated with infant gut microbiota composition across the two first years of life in a homogenous cohort. The study highlights possible important future research areas and confounding factors to be considered. Funding: This research was supported by Business Finland, Academy of Finland, Foundation for Nutrition Research and the Doctoral Program in Microbiology and Biotechnology, University of Helsinki, Finland.

Abstract Environmental factors act at multiple spatial scales in a hierarchical manner to shape the organization of biota. However, the relative influence of different scale-related factors is poorly known, especially in Atlantic Forest Blackwater streams. Therefore, we herein aimed to evaluate local, landscape and spatial factors that shape fish assemblages in 14 blackwater restinga coastal Atlantic Forest streams under natural conditions and verify species occurrence patterns among four sub-basins during the low-precipitation season. When we combined local, landscape and spatial factors, variance partitioning explained a high proportion of variation in species matrix. Local variables pH and Total Dissolved Solids explained most of the variability, and these were the most important factors in determining fish community structure. Significant differences in fish assemblage structure among the four sub-basins were observed, and Mimagoniates microlepis, Phalloceros harpagos, and Hollandichthys multifasciatus were the species that most contributed to this dissimilarity. The important contribution of local predictors, the high number of endemic species herein recorded, the presence of an endangered species (Spintherobolus broccae), and near pristine conditions, may be used as baseline conditions for the assessment of similar environments.

Contemporary biological assemblage composition and biodiversity are often shaped by a range of natural environmental factors, human disturbances, and their interactions. It is critical to disentangle the effects of individual natural variables and human stressors in data analysis to support management decision-making. Many statistical approaches have been proposed and used to estimate the biological effects of individual predictors, which often correlated and interacted with one another. In this article, we review nine of those approaches in terms of their strengths, limitations, and related r packages. Among those are hierarchical partitioning, propensity score, the sum of AIC weights, structural equation modeling, and tree-based machine learning algorithms. As no approach is perfect, we offer two suggestions: (1) reducing the number of predictors as low as possible by carefully screening all candidate predictors based on biological and statistical considerations; (2) selecting two or more approaches based on the characteristics of the given dataset and specific research goals of a study, and using them in parallel or sequence. Our review could help ecologists to navigate through this challenging process. [ABSTRACT FROM AUTHOR]

A better understanding of responses to water limitation in woody species can help us to cope with the consequences of the progressing climate change. We focused on the putative transgenerational effects of water limitation in the maternal environment during reproduction. Water was restricted for cuttings of Frangula alnus Mill. in a common garden setting, with a Belgian (local), Italian and Swedish provenance, during the growing season of 2020 and mature berries were collected during the whole reproductive phase. Stones that were extracted from the berries were given a cold stratification. In the next spring, the germination percentage of the stones from the water restricted maternal environment was significantly higher than that of the stones from the normal maternal environment, for the three provenances, notwithstanding the fact that stone weight was not different. The timing of seedling emergence was advanced for the water-limited maternal environment, but only for the stones harvested when mature berry production was the highest (9th and 16th of July 2020). Population differentiation was observed for the timing of seedling emergence, which reflected population differentiation for bud burst of the mother plants in the common garden, including a counter-gradient effect for the Swedish provenance, and corroborating the suggestion that the timing of seedling emergence and leaf phenology may have a common genetic basis. In addition, the Swedish provenance displayed a somewhat more stable germination percentage over the whole berry collection period when the stones were harvested. A partitioning of variance analysis suggested that germination percentage is more genetically determined than timing of seedling emergence, probably reflecting the more important need to sense the environment for an adequate timing of emergence. [ABSTRACT FROM AUTHOR]

Understanding contributions of different environmental drivers to the structure and function of river biota is critical for biodiversity and environmental conservation. Yet, there is no consensus on which drivers have the greatest impact on fish diversity, especially in watersheds disturbed by multiple human activities. Fish taxonomic, phylogenetic, and functional diversity at both alpha and beta dimensions and their environmental drivers were studied in a total of 84 river sites from three watersheds, Huai River watershed (HRW), Sui River watershed (SRW), and Yishusi River watershed (YRW) in the Eastern Huai River Basin of China. Results showed that rivers in the three watersheds had no significant difference in both taxonomic and functional alpha diversity. Rivers in the HRW had significantly higher phylogenetic alpha diversity. For taxonomic and phylogenetic beta diversity, the overall beta diversity and turnover component were significant higher in the HRW. For functional beta diversity, the overall beta diversity was significantly lower in the HRW. Multiple linear regression (MLR) and redundancy analysis (RDA) showed that local (e.g., nutrients, dissolved oxygen, river width, transparency), regional (e.g., wetland), climate (e.g., temperature), and spatial variables structured alpha and beta fish diversity. Variation partitioning analysis indicated that the pure contributions of local and spatial variables were more important than that of climate and regional variables, which suggested that spatial effects and local environmental filtering were the main factors driving the beta diversity of fish assemblages in these rivers. The current study highlights the importance of considering multidimensional diversity and multiple environmental factors for conserving river fishes. [ABSTRACT FROM AUTHOR]

Generalized linear mixed models (GLMMs) have been widely used in contemporary ecology studies. However, determination of the relative importance of collinear predictors (i.e. fixed effects) to response variables is one of the challenges in GLMMs. Here, we developed a novel R package, glmm.hp, to decompose marginal R 2 explained by fixed effects in GLMMs. The algorithm of glmm.hp is based on the recently proposed approach 'average shared variance' i.e. used for multivariate analysis. We explained the principle and demonstrated the use of this package by simulated dataset. The output of glmm.hp shows individual marginal R 2s that can be used to evaluate the relative importance of predictors, which sums up to the overall marginal R 2. Overall, we believe the glmm.hp package will be helpful in the interpretation of GLMM outcomes. [ABSTRACT FROM AUTHOR]

An important objective of fish ecology is to understand pure and shared effects of abiotic, biotic, and spatial predictors of fish assemblages' structure on continental shelves. This study aims to assess the structure of the bottom-associated fish assemblage on the shallow inner continental shelf of Paraná, southern Brazil, in response to physicochemical, biological, and spatial factors. We hypothesize that this structure is associated with the benthic megafauna, particularly with the distribution of the Brazilian seabob shrimp Xiphopenaeus kroyeri , an abundant fishing resource on the shallow coast of Paraná. We used uni and multivariate analyses to examine the distribution of abundance, richness, and composition of ichthyofauna in the region. Using variance partitioning analysis, we determined the pure and shared effect of spatial (latitude and longitude), physicochemical, and spatiotemporal distribution patterns of crustaceans, echinoderms, and mollusks as potential predictors of the structure of the fish assemblage. The data were obtained monthly from a one-year bottom trawl survey, comprising five transects and four depths (six, nine, 12 and 15 m) in a 60 km long section of the inner continental shelf, under the influence of estuaries. We captured 57578 demersal fish, comprising 37 families and 88 species. The average abundance of fish per haul was 387 individuals at a depth of 6 m, decreasing to 114 individuals per haul at 15 m. Average richness also decreased along the bathymetric profile, from 15 to 10 species per haul. Fish abundance and richness responded positively to a seasonal estuarine discharge pattern that was stronger in summer and autumn. High biomass of juvenile seabob shrimp in shallower regions also explained the higher abundances and richness. The results also suggest the existence of two fish assemblages in the region, associated with the distribution of the megafauna and segregated by depth, water surface transparency, and sediment particle size composition. Despite significant seasonal variations, controlled by precipitation and bottom water temperature, the structure of fish assemblages responded to the pure and shared effects of the three predictive components in all seasons. In particular, local coastal hydrography and the prey-predator relationship between fish and seabob shrimp were ecologically relevant processes for structuring fish assemblages at the inner continental shelf of Paraná. This study highlights the complexity of ecological interactions within demersal fish assemblages and the importance of considering biotic and abiotic factors in understanding fish distribution patterns at the spatial scale of inner continental shelves that are influenced by estuaries. [Display omitted] • Variance partitioning shows pure and shared effects of spatial, biotic, and abiotic predictors on fish assemblage structure. • Two fish assemblages segregated by depth, transparency, sediment size, and megabenthos at the inner continental shelf scale. • Coastal hydrography and prey-predator relationship are ecologically relevant for structuring fish assemblages. [ABSTRACT FROM AUTHOR]

Knowledge concerning the relative importance of biotic and abiotic factors associated with the long-term settlement of large carnivores in human-dominated landscapes is important for effective species conservation. However, identifying the major drivers of large carnivore occurrences at a continental scale is challenging as several factors can act in concert to affect large carnivore distributions. Thus, we investigated the relationship between the permanent and sporadic occurrences of large carnivores (brown bear, Eurasian lynx, grey wolf and wolverine) and three groups of predictor variables (i.e., landscape attributes, human disturbance and prey availability) on the continental scale in Europe. Specifically, we used generalized linear models (GLMs) and variation partitioning to estimate the independent and cumulative effects of the three predictor groups on large carnivore occurrences. The explained variance for permanent vs. sporadic occurrence was highest for the wolverine (42.8% and 29.7%), followed by the brown bear (20.5% and 16.4%), Eurasian lynx (15.2% and 11.6%) and grey wolf (15.8% and 6.1%). Landscape attributes, such as forest cover, shrub-land cover, altitude and slope, were positively related to the occurrence of grey wolf, brown bear and Eurasian lynx, whereas human disturbance (human population density, distance to roads and to human settlements) was negatively related to wolverine occurrence. For all species, shared effects between landscape attributes and human disturbance accounted for a considerable portion of the explained variation in both permanent and sporadic occurrence, and landscape attributes were generally more important for explaining permanent than sporadic occurrence, except for the wolverine. Prey availability was marginally associated with the permanent occurrence of the grey wolf but we found no statistical effect of prey availability on the occurrence of the other large carnivores. In conclusion, the sporadic occurrence of large carnivores in Europe is more stochastic and less predictable than their permanent occurrence. Landscape attributes and their joint effects with human disturbance are the most important factors related to the recolonization dynamics of large carnivores, although wolverine distributions appear strongly limited by human disturbance itself. Domestic prey availability seems to play a subordinate role in driving the recent distribution dynamics of large carnivores at the continental scale. Thus, our results are relevant also in light of the ongoing recolonization of large carnivores which, in many rural areas, caused concerns among the locals, especially in relation to conflicts with human activities. For these reasons, we stress the need to continue and improve large carnivore monitoring across Europe. [ABSTRACT FROM AUTHOR]

The conversion of native forests into pastures is still a common practice in Brazil. Abandoned pastures have great potential for natural regeneration and therefore could play an important role in meeting the enormous demand for forest restoration. Few studies, however, have investigated the extent to which spatially-structured environmental variables and community structure are correlated with the variation in species abundance of regenerating forests on abandoned pastures. Therefore, we aimed to determine whether environmental and spatial variables were capable of explaining the variation in abundance of woody species on abandoned pastures in the subtropical Atlantic Forest. We systematically distributed 45 sample plots with size and inclusion criteria that changed according to the vegetation layer in three different abandoned pastures. In general, most of the variation in species abundance that our models were able to explain was correlated with spatially-unstructured physical-chemical soil properties. A smaller part of the variation was correlated with spatially-structured soil variables and topography-related variables. An even smaller portion of the variation was spatially-structured but was not correlated with spatially-structured environmental variables. Therefore, our results suggest that the variation in species abundance of regenerating subtropical Atlantic forests on abandoned pastures is more closely related to niche-based processes mediated by environmental variables than to stochastic spatial processes. [ABSTRACT FROM AUTHOR]

Summary: The analysis of plant elemental composition and the underlying factors affecting its variation are a current hot topic in ecology. Ecological adaptation to atypical soils may shift plant elemental composition. However, no previous studies have evaluated its relevance against other factors such as phylogeny, climate or individual soil conditions.We evaluated the effect of the phylogeny, environment (climate, soil), and affinity to gypsum soils on the elemental composition of 83 taxa typical of Iberian gypsum ecosystems. We used a new statistical procedure (multiple phylogenetic variance decomposition, MPVD) to decompose total explained variance by different factors across all nodes in the phylogenetic tree of target species (covering 120 million years of Angiosperm evolution).Our results highlight the relevance of phylogeny on the elemental composition of plants both at early (with the development of key preadaptive traits) and recent divergence times (diversification of the Iberian gypsum flora concurrent with Iberian gypsum deposit accumulation). Despite the predominant phylogenetic effect, plant adaptation to gypsum soils had a strong impact on the elemental composition of plants, particularly on sulphur concentrations, while climate and soil effects were smaller.Accordingly, we detected a convergent evolution of gypsum specialists from different lineages on increased sulphur and magnesium foliar concentrations. [ABSTRACT FROM AUTHOR]

Understanding the mechanisms of ecological community dynamics and how they could be affected by environmental changes is important. Population dynamic models have well known ecological parameters that describe key characteristics of species such as the effect of environmental noise and demographic variance on the dynamics, the long‐term growth rate, and strength of density regulation. These parameters are also central for detecting and understanding changes in communities of species; however, incorporating such vital parameters into models of community dynamics is challenging. In this paper, we demonstrate how generalized linear mixed models specified as intercept‐only models with different random effects can be used to fit dynamic species abundance distributions. Each random effect has an ecologically meaningful interpretation either describing general and species‐specific responses to environmental stochasticity in time or space, or variation in growth rate and carrying capacity among species. We use simulations to show that the accuracy of the estimation depends on the strength of density regulation in discrete population dynamics. The estimation of different covariance and population dynamic parameters, with corresponding statistical uncertainties, is demonstrated for case studies of fish and bat communities. We find that species heterogeneity is the main factor of spatial and temporal community similarity for both case studies. [ABSTRACT FROM AUTHOR]

• We assessed interspecific and intraspecific variation in litter consumption rate of aquatic and terrestrial macro-detritivores. • We observed a substantial amount of intraspecific variation (34%) relative to the interspecific variation (53%). • Intraspecific variation was repeatable among individuals, reflecting phenotypic features of individuals rather than inconsistent variation (13%). • Our study highlights the importance of the intraspecific level in trait-based ecological studies on macro-detritivores. Traits of organisms vary both at inter- and intraspecific levels. For macro-detritivores inhabiting lands and waters, there is only scattered information on the relative contribution of the intraspecific level for traits like litter consumption rates. This basic knowledge is nevertheless required to know how much the intraspecific level could matter to the study of macro-detritivore communities and ecosystem processes like leaf litter decomposition. We performed a laboratory experiment, where thirty individuals each of five abundant macro-detritivore species from a stream and a meadow ecosystem fed ash (Fraxinus excelsior) leaf litter in microcosms, twice at a 1-week interval. This nested and repeated design (individuals nested within species, species within ecosystems) was setup in controlled conditions and then analysed following a variance partitioning approach with linear mixed-effect models, to assess the variance attributable to different levels of biological organisation (i.e., inter- and intraspecific level). Then, we performed the same analysis, but separately on aquatic and terrestrial datasets. From the whole dataset, we demonstrated that half of the trait variation occurred at the interspecific level and a third at the intraspecific level. The variance found at the residual level, accounting for both measurement errors and for the variation of the same individuals between the two times (i.e., intra-individual variation), was significantly lower than what was observed at the other levels of biological organisation. Variance partitioning on separate aquatic and terrestrial datasets were consistent altogether, confirming the global pattern. With this study, we stress the relevance of the intraspecific level for future trait-based approaches applied to macro-detritivores. [ABSTRACT FROM AUTHOR]

The spatial heterogeneity on a regional scale of forest biomass is caused by multiple biotic and abiotic factors. However, the contributions of biotic and abiotic factors to the spatial heterogeneity of forest biomass remain unclear. Based on the data of the National Forest Continuous Inventory (NFCI), digital elevation model (DEM), and meteorological data of Guizhou Province in 2015, we studied the spatial heterogeneity of the aboveground forest biomass in Guizhou province and evaluated the contribution rates of its influencing factors using Moran's I, semivariogram, distance-based Moran's eigenvector maps (dbMEMs), and variance partitioning. The results showed that the forest biomass in Guizhou province had strong spatial heterogeneity. Biotic and abiotic factors explained 34.4% and 19.2% of the spatial variation in forest biomass, respectively. Among the biotic factors, the average height of the stand had the greatest influence on forest biomass, while annual precipitation had the greatest influence on forest biomass among abiotic factors. Spatial factors only explained 0.7% of the spatial variation of forest biomass, indicating that the contribution of spatial factors can be explained by some measured abiotic factors. This study provided an effective approach to understand the underlying mechanisms of spatial allocation of forest biomass. [ABSTRACT FROM AUTHOR]

In the context of urban warming associated with rapid urbanization, the relationship between urban landscape patterns and land surface temperature (LST) has been paid much attention. However, few studies have comprehensively explored the effects of two/three-dimensional (2D/3D) building patterns on LST, particularly by comparing their relative contribution to the spatial variety of LST. This study adopted the ordinary least squares regression, spatial autoregression and variance partitioning methods to investigate the relationship between 2D/3D building patterns and summertime LST across 2016–2017 in Shanghai. The 2D and 3D building patterns in this study were quantified by four 2D and six 3D metrics. The results showed that: (1) During the daytime, 2D/3D building metrics had significant correlation with LST. However, 3D building patterns played a significant role in predicting LST. They explained 51.0% and 10.2% of the variance in LST, respectively. (2) The building coverage ratio, building density, mean building projection area, the standard deviation of building height, and mean building height highly correlated with LST. Specifically, the building coverage ratio was the main predictor, which was obviously positively correlated with LST. The correlation of building density and average projected area with LST was positive and significant, while the correlation of building height standard deviation and average building height with LST was negative. The increase in average height and standard deviation of buildings and the decrease in building coverage ratio, average projected area, and density of buildings, can effectively improve the urban thermal environment at the census tract level. (3) Spatial autocorrelation analysis can elaborate the spatial relationship between building patterns and LST. The findings from our research will provide important insights for urban planners and decision makers to mitigate urban heat island problems through urban planning and building design. [ABSTRACT FROM AUTHOR]

Determining the patterns and drivers of the small‐scale species–area relationship (SAR) is crucial for improving our understanding of community assembly and biodiversity patterns. Niche‐based and stochastic processes are two principal categories of mechanisms potentially driving SARs. However, their relative importance has rarely been quantified rigorously owing to scale dependence and the simplified niche volumes often used.In a fully mapped, 24‐hm2 plot of a typical subtropical forest, we built the SARs and well‐defined niche hyper‐volumes of a broad range of environmental variables at scales of 10–70 m (cell sizes). We then simulated passive sampling and partitioned the variances of the SAR slopes to disentangle these two contrasting mechanisms.We found that the small‐scale SAR best followed a power‐law relationship, consistent with large‐scale SARs. The SAR slope declined with increasing scale; it was lower than expected under passive sampling at scales below 30 m and higher at larger scales. Environmental niches explained more (39%–64%) of the slope at larger scales, exceeding 50% at scales >30 m, and these niches always captured the majority of the structured slopes. Environmental position (environmental mean values) effects were steady in absolute strength across scales and explained most (98%–68%) of the niche effect, but this proportion decreased with increasing scale. The effect of environmental heterogeneity increased with spatial scales, starting to rise at the 30 m scale after controlling for environmental position. Excluding soil properties from analyses strongly reduced these niche effects, highlighting the importance of soils for structuring the small‐scale SAR. There was also substantial stochasticity in the SAR slopes, which was only partially explained by passive sampling.Synthesis. Our results show that the small‐scale SAR in the studied subtropical forest follows a power law, exhibits a scale shift in SAR slope at 30 m, and is strongly shaped by niche effects that are dominated by environmental position relative to heterogeneity. However, soil heterogeneity controls the increase in niche effect and the shift in the SAR slope with increasing spatial scales. Hence, edaphic factors can be responsible for scale dependence in small‐scale SARs, thereby linking small‐scale and large‐scale SARs. [ABSTRACT FROM AUTHOR]

Understanding the spatial scales at which environmental factors drive species richness patterns is a major challenge in ecology. Due to the trade‐off between spatial grain and extent, studies tend to focus on a single spatial scale, and the effects of multiple environmental variables operating across spatial scales on the pattern of local species richness have rarely been investigated.Here, we related variation in local species richness of ground beetles, landbirds and small mammals to variation in vegetation structure and topography, regional climate, biome diversity and glaciation history for 27 sites across the USA at two different spatial grains.We studied the relative influence of broad‐scale (landscape) environmental conditions using variables estimated at the site level (climate, productivity, biome diversity and glacial era ice cover) and fine‐scale (local) environmental conditions using variables estimated at the plot level (topography and vegetation structure) to explain local species richness. We also examined whether plot‐level factors scale up to drive continental scale richness patterns. We used Bayesian hierarchical models and quantified the amount of variance in observed richness that was explained by environmental factors at different spatial scales.For all three animal groups, our models explained much of the variation in local species richness (85%–89%), but site‐level variables explained a greater proportion of richness variance than plot‐level variables. Temperature was the most important site‐level predictor for explaining variance in landbirds and ground beetles richness. Some aspects of vegetation structure were the main plot‐level predictors of landbird richness. Environmental predictors generally had poor explanatory power for small mammal richness, while glacial era ice cover was the most important site‐level predictor.Relationships between plot‐level factors and richness varied greatly among geographical regions and spatial grains, and most relationships did not hold when predictors were scaled up to the continental scale. Our results suggest that the factors that determine richness may be highly dependent on spatial grain, geography, and animal group. We demonstrate that instead of artificially manipulating the resolution to study multiscale effects, a hierarchical approach that uses fine grain data at broad extents could help solve the issue of scale selection in environment‐richness studies. [ABSTRACT FROM AUTHOR]

Near‐term ecological forecasts provide resource managers advance notice of changes in ecosystem services, such as fisheries stocks, timber yields, or water quality. Importantly, ecological forecasts can identify where there is uncertainty in the forecasting system, which is necessary to improve forecast skill and guide interpretation of forecast results. Uncertainty partitioning identifies the relative contributions to total forecast variance introduced by different sources, including specification of the model structure, errors in driver data, and estimation of current states (initial conditions). Uncertainty partitioning could be particularly useful in improving forecasts of highly variable cyanobacterial densities, which are difficult to predict and present a persistent challenge for lake managers. As cyanobacteria can produce toxic and unsightly surface scums, advance warning when cyanobacterial densities are increasing could help managers mitigate water quality issues. Here, we fit 13 Bayesian state‐space models to evaluate different hypotheses about cyanobacterial densities in a low nutrient lake that experiences sporadic surface scums of the toxin‐producing cyanobacterium, Gloeotrichia echinulata. We used data from several summers of weekly cyanobacteria samples to identify dominant sources of uncertainty for near‐term (1‐ to 4‐week) forecasts of G. echinulata densities. Water temperature was an important predictor of cyanobacterial densities during model fitting and at the 4‐week forecast horizon. However, no physical covariates improved model performance over a simple model including the previous week's densities in 1‐week‐ahead forecasts. Even the best fit models exhibited large variance in forecasted cyanobacterial densities and did not capture rare peak occurrences, indicating that significant explanatory variables when fitting models to historical data are not always effective for forecasting. Uncertainty partitioning revealed that model process specification and initial conditions dominated forecast uncertainty. These findings indicate that long‐term studies of different cyanobacterial life stages and movement in the water column as well as measurements of drivers relevant to different life stages could improve model process representation of cyanobacteria abundance. In addition, improved observation protocols could better define initial conditions and reduce spatial misalignment of environmental data and cyanobacteria observations. Our results emphasize the importance of ecological forecasting principles and uncertainty partitioning to refine and understand predictive capacity across ecosystems. [ABSTRACT FROM AUTHOR]

Abstract Chromosomal inversions have long been recognized for their role in local adaptation. By suppressing recombination in heterozygous individuals, they can maintain coadapted gene complexes and protect them from homogenizing effects of gene flow. However, to fully understand their importance for local adaptation we need to know their influence on phenotypes under divergent selection. For this, the marine snail Littorina saxatilis provides an ideal study system. Divergent ecotypes adapted to wave action and crab predation occur in close proximity on intertidal shores with gene flow between them. Here, we used F2 individuals obtained from crosses between the ecotypes to test for associations between genomic regions and traits distinguishing the Crab‐/Wave‐adapted ecotypes including size, shape, shell thickness, and behavior. We show that most of these traits are influenced by two previously detected inversion regions that are divergent between ecotypes. We thus gain a better understanding of one important underlying mechanism responsible for the rapid and repeated formation of ecotypes: divergent selection acting on inversions. We also found that some inversions contributed to more than one trait suggesting that they may contain several loci involved in adaptation, consistent with the hypothesis that suppression of recombination within inversions facilitates differentiation in the presence of gene flow.

The metacommunity theory includes processes that contribute, at different scales, to the understanding of the distribution of organisms in space and aims to assess the relative importance of spatial and environmental factors in the structuring of communities. Fluvial ecosystems of the Argentine Pampas are characterized by their environmental heterogeneity from slow water courses and variable development of aquatic vegetation to faster courses. They are affected by the different land uses, which are among the main threats to biodiversity and alter the dispersal of the species. Forty‐four species of aquatic oligochaete assemblages from 15 streams of nine Pampean basins were seasonally analyzed. The assemblages were characterized through estimations of taxonomic richness, α and β diversity. No differences were found in the assemblages of the substrates (sediments and aquatic vegetation) within each stream, except for Juan Blanco stream. However, differences were found between streams, as well as between basins. The oligochaetes that contributed most to the dissimilarity among streams and basins were Nais communis, Limnodrilus hoffmeisteri, Dero obtusa, and Stylaria fossularis. Two groups of sites were identified through the analysis of canonical correspondence: those of mountain basins and those of lowland basins. The variance partitioning showed that local environmental conditions (acting as environmental filters) accounted for 15.64% in the ordering of the assemblages, while 14.60% was explained by altitude and geographic factors (as a dispersal limitation). These results help to understand the processes that organize the distribution of organisms at different scales, which could have important implications when making decisions regarding biomonitoring and conservation. [ABSTRACT FROM AUTHOR]