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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., (© 2022 The Authors. Journal of Animal Ecology © 2022 British Ecological Society.)

Herbaceous plants are a key component of tropical forests. Previous work indicates that herbs contribute substantially to the species richness of tropical plant communities. However, the processes structuring tropical herb diversity, and how they contrast with woody communities, have been underexplored. Within the understory of a 50-ha forest dynamics plot in central Panama, we compared the diversity, distribution, and abundance of vascular herbaceous plants with woody seedlings (i.e., tree and lianas <1 cm DBH and ≥20 cm tall). Beta-diversity was calculated for each community using a null model approach. We then assessed the similarity in alpha and beta-diversity among herbs, tree seedlings, and liana seedlings. Strengths of habitat associations were measured using permutational ANOVA among topographic habitat-types. Variance partitioning was then used to quantify the amount of variation in species richness and composition explained by spatial and environmental variables (i.e., topography, soils, and shade) for each growth form. Species richness and diversity were highest for tree seedlings, followed by liana seedlings and then herbs. In contrast, beta-diversity was 16-127% higher for herbs compared to woody seedlings, indicating higher spatial variation in this stratum. We observed no correlation between local richness or compositional uniqueness of herbs and woody seedlings across sites, indicating that different processes control the spatial patterns of woody and herbaceous diversity and composition. Habitat associations were strongest for herbs, as indicated by greater compositional dissimilarity among habitat types. Likewise, environmental variables explained a larger proportion of the variation in species richness and composition for herbs than for woody seedlings (richness = 25%, 14%, 12%; composition = 25%, 9%, 6%, for herbs, trees, and lianas, respectively). These differences between strata did not appear to be due to differences in lifespan alone, based on data from adult trees. Our results point to contrasting assembly mechanisms for herbaceous and woody communities, with herbs showing stronger niche-derived structure. Future research on tropical herbaceous communities is likely to yield new insights into the many processes structuring diverse plant communities., (© 2016 by the Ecological Society of America.)

Beta diversity can be measured in different ways. Among these, the total variance of the community data table Y can be used as an estimate of beta diversity. We show how the total variance of Y can be calculated either directly or through a dissimilarity matrix obtained using any dissimilarity index deemed appropriate for pairwise comparisons of community composition data. We addressed the question of which index to use by coding 16 indices using 14 properties that are necessary for beta assessment, comparability among data sets, sampling issues and ordination. Our comparison analysis classified the coefficients under study into five types, three of which are appropriate for beta diversity assessment. Our approach links the concept of beta diversity with the analysis of community data by commonly used methods like ordination and anova. Total beta can be partitioned into Species Contributions (SCBD: degree of variation of individual species across the study area) and Local Contributions (LCBD: comparative indicators of the ecological uniqueness of the sites) to Beta Diversity. Moreover, total beta can be broken up into within- and among-group components by manova, into orthogonal axes by ordination, into spatial scales by eigenfunction analysis or among explanatory data sets by variation partitioning., (© 2013 John Wiley & Sons Ltd/CNRS.)

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]

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]

Aim: Predicting future changes in species richness in response to climate change is one of the key challenges in biogeography and conservation ecology. Stacked species distribution models (S‐SDMs) are a commonly used tool to predict current and future species richness. Macroecological models (MEMs), regression models with species richness as response variable, are a less computationally intensive alternative to S‐SDMs. Here, we aim to compare the results of two model types (S‐SDMS and MEMs), for the first time for more than 14,000 species across multiple taxa globally, and to trace the uncertainty in future predictions back to the input data and modelling approach used. Location: Global land, excluding Antarctica. Taxon: Amphibians, birds and mammals. Methods: We fitted S‐SDMs and MEMs using a consistent set of bioclimatic variables and model algorithms and conducted species richness predictions under current and future conditions. For the latter, we used four general circulation models (GCMs) under two representative concentration pathways (RCP2.6 and RCP6.0). Predicted species richness was compared between S‐SDMs and MEMs and for current conditions also to extent‐of‐occurrence (EOO) species richness patterns. For future predictions, we quantified the variance in predicted species richness patterns explained by the choice of model type, model algorithm and GCM using hierarchical cluster analysis and variance partitioning. Results: Under current conditions, species richness predictions from MEMs and S‐SDMs were strongly correlated with EOO‐based species richness. However, both model types over‐predicted areas with low and under‐predicted areas with high species richness. Outputs from MEMs and S‐SDMs were also highly correlated among each other under current and future conditions. The variance between future predictions was mostly explained by model type. Main conclusions: Both model types were able to reproduce EOO‐based patterns in global terrestrial vertebrate richness, but produce less collinear predictions of future species richness. Model type by far contributes to most of the variation in the different future species richness predictions, indicating that the two model types should not be used interchangeably. Nevertheless, both model types have their justification, as MEMs can also include species with a restricted range, whereas S‐SDMs are useful for looking at potential species‐specific responses. [ABSTRACT FROM AUTHOR]

Questions: What are the drivers that govern fern and lycophyte community composition across different elevation zones in the South Brazilian Atlantic Forest? Does explanatory power of the models increase when we consider substrate‐based life forms separately? Do terrestrial and epiphytic species respond similarly to environmental drivers? Study site: Four distinct elevation zones of the Atlantic Rain Forest sensu stricto in northeastern Rio Grande do Sul, Brazil. Method: Variation partitioning was used to investigate the role of climatic, edaphic and spatial variation on species composition at different spatial scales. We considered both the entire community and subsets with either only epiphytic or terrestrial species. Results: On the broad scale, environmental variables were the most important in shaping the fern and lycophyte community composition. Edaphic filters had a more important role for the terrestrial community, and climatic filters for epiphytic species. Considering epiphytic and terrestrial species separately increased the explanatory power of the models. Conclusions: Changes in community composition of ferns and lycophytes along an elevational gradient in the South Brazilian Atlantic Forest are primarily driven by niche processes. Ferns and lycophytes found on different substrates (epiphytic vs terrestrial species) show distinct responses to environmental factors and thus should be considered separately in ecological studies. Our study shows that changes in community composition of ferns and lycophytes along an elevational gradient are primarily driven by niche processes. Importantly, epiphytic and terrestrial species showed distinct responses to environmental factors. These distinct functional groups should thus be considered separately in studies on community response to environmental variation. [ABSTRACT FROM AUTHOR]

Numerous studies have focused on the relationship between landscape structure and plant diversity based on the patch-mosaic landscape paradigm, by deriving structural data from classified images. Since the use of discrete classes poses limitations for predicting biodiversity patterns in complex, low human-impacted ecosystems, two alternative methods have been used to analyze changes of landscape attributes in a continuum: moving-window metrics and surface metrics (image texture). Here, we compare these two approaches for predicting richness of all plant species, legume species, legume trees, legume shrubs, legume forbs, and legume climbers across a tropical landscape in Mexico, based on the records of vascular plants in 250 10 x 10 m plots. Multiple regression and variance partitioning methods were used to analyze the effects of the two landscape descriptors (moving-window and surface metrics), scale (400- and 200-m moving-window sides), and space (based on the extraction of principal coordinates of neighbor matrices' vectors) on species richness. The predictive power of all metrics was relatively small for total species richness, but generally higher for legume species. For legume forbs, surface metrics-based models indicated a direct association between species richness and landscape homogeneity. Moving-window metrics were highly sensitive to the biological group and to spatial scale, likely due to a leftover effect of image classification procedures. Conversely, surface metrics were more independent from scale and taxonomy. Attempts to predict species richness in highly diverse, low human-impacted tropical ecosystems more rapidly and accurately should better rely on surface metrics rather than on moving-window metrics, in line with the continuous landscape paradigm. [ABSTRACT FROM AUTHOR]

Identifying the key drivers of aquatic fauna structuring at multiple spatial scales is critical in reducing biodiversity loss. Macroinvertebrates are the most sensitive indicators of disturbance and they are used as a cost-effective tool for bioassessment at catchment and site scales. The focus of our study was to identify the key drivers from three classes of environmental variables (geophysical landscape, land use, and site habitat) that influence macroinvertebrate richness in different aquatic ecological function regions (AEFRs) of the Liaohe River Basin. We sampled macroinvertebrate assemblages, extracted geophysical and climate variables from geospatial data, and quantified physical and chemical habitats from 407 randomly distributed sites that belong to the three level-I AEFRs. We analyzed our data through multiple linear regression models by using the three classes of predicted variables alone and in combination. The models that were constructed in the first level-I AEFR explained similar amounts of macroinvertebrate richness and had the maximum ability to explain how macroinvertebrate richness distributed (denoted “explaining ability”; geophysical landscape: RGL2 ≈ 60%, land use and site habitat: RLU2 and RSH2 ≈ 50%, and combined: RCB2 ≈ 75%). The explaining abilities for the third level-I AEFR were as follows: RGL2 ≈ 11%, RLU2 ≈ 14%, RSH2 ≈ 25%, and RCB2 ≈ 38%. The explaining abilities for the 4th level-I AEFR were as follows: RGL2 ≈ 30%, RLU2 ≈ 7%, RSH2 ≈ 40%, and RCB2 ≈ 55%. We conclude that: (1) all of the combined models explained more interaction as compared with the single models; (2) the environmental variables differed among different level-I AEFRs; and, (3) variables in the site habitat scale were the most robust explainers when analyzing the relationship between environmental variables and macroinvertebrate richness and they can be recommended as the optimal candidate explainer. These results may provide cost-effective tools for distinguishing and identifying the drivers of sensitive aquatic organisms at regional scales.

Alpine meadows have been exposed to relevant management shifts in the last decades, with changes in plant species composition and biodiversity losses often occurring in favor of augmented foraging capabilities, especially in marginal rural contexts. In this study, we analyzed the relationships among the plant species composition, biodiversity and forage value of meadows and two sets of variables, environmental and management ones, in a dairy district of the Central Italian Alps. Results indicate that management variables could only explain limited variability of the meadows under study: for instance, the number of cuts per year is available to justify the plant species composition and biodiversity of such coenoses. Moreover, the environmental variables better described the variability of responses, due to the harsh environmental constraints of the area under examination, located at high altitudes. The shared effects of the two sets explained larger variance than the management set alone, due to the complex relationships of environmental and management factors in the context. The forage value of meadows, an indicator of hay quality, was found negatively associated with the Shannon Index. This behavior highlights a known dilemma which especially refers to high altitude communities as the ones under study, clearly highlighting trade-offs between their production and biodiversity. Some taxa as Anthriscus sylvestris , Heracleum sphondylium and others critically unbalance the species composition of meadows, thus their overall biodiversity, at low altitudes. This finding, explainable by the late first cuttings commonly adopted by all farmers, suggests the eutrophication of coenoses. The management choices inspected did not reflect on the wide variability of meadows, but indeed they made possible to understand how this farming system should be deeply revised, with respect to environmental constraints and meadows’ fodder capabilities. [ABSTRACT FROM AUTHOR]

Despite the introduction of agri-environmental schemes, no general increase of farmland biodiversity in Europe has been observed. Farmers take decisions about the implementation of agri-environmental schemes at the farm scale, and it is thus highly relevant to assess the relationship between farm management and biodiversity at this scale to increase the effectiveness of agri-environmental schemes. The present study quantifies to what extent and with which practices farmers can influence biodiversity on their farm and to what extent conditions outside farmers’ control may mediate biodiversity. We grouped 27 variables into four variable sets: (1) ecological compensation (mainly semi-natural habitats), (2) in-field options (e.g. no growth regulator, insecticide and herbicide treatment), and (3) farm characteristics, which can be influenced by farmers (e.g. land-use types) as well as (4) farm settings, which cannot be influenced by farmers (e.g. altitude). As biodiversity metrics, plant, grasshopper, butterfly and bird richness and abundance of farmland target species were assessed on 133 farms of the Swiss Central Plateau from 2009 to 2011. Variance partitioning and generalised linear mixed models were used to analyse the impact of each variable set on farmland species diversity. Our results provide evidence that farmers can indeed positively influence biodiversity by ecological compensation and in-field options. The variables of the ecological compensation set explained the highest proportion in the variation of plant richness and butterfly abundance. We found a significant positive relationship between in-field options and plant abundance. Our study illustrated that the effects of biodiversity-related farming practices differ between species and biodiversity metrics. Conditions outside farmers’ control explained a high variation in grasshopper and bird diversity. One variable within the set of farm settings, the degree of consolidation, had a significant negative impact on five out of eight biodiversity metrics (plant, butterfly and bird richness; plant and bird abundance). We demonstrate that farmers can substantially enhance biodiversity on their farms and provide knowledge on how such biodiversity improvements can be achieved by farmers. Further, we highlight the value of new biodiversity-related management practices such as in-field options. [ABSTRACT FROM AUTHOR]

Context dependency is an emerging topic that is challenging our understanding of the factors shaping biodiversity in metacommunities. River networks and other dendritic systems provide unique systems for examining variation in the processes shaping biodiversity between different metacommunities., We examined biodiversity patterns in five benthic invertebrate data sets, from two catchments in central Germany, with the aim of exploring context dependency in these systems. We used variance partitioning to disentangle the variation explained in three biodiversity metrics: taxonomic richness, Simpson's diversity and local contribution to beta diversity (LCBD; a measure of the uniqueness of a site). As explanatory variables, we used proxies of network position (i.e. catchment size and altitude) and habitat conditions., Contrary to our expectation, we found no evidence of a decline in LCBD downstream in our study. Local habitat conditions and catchment land use played a much stronger role than catchment size and altitude in explaining variation in the three biodiversity metrics. Observed patterns were highly variable between different data sets in our study. These findings suggest that factors shaping biodiversity patterns in these systems are highly context dependent and less related to their position along the river network than local habitat conditions., Given the clear context dependency between data sets, we urge researchers to focus on disentangling the factors driving the high levels of variability between individual systems through the study of a number of replicate, rather than single, metacommunities. [ABSTRACT FROM AUTHOR]

Land use effects are considered among the main stressors on freshwater biodiversity, with up to 80% of land in Europe under intensive use. Here, we address the impact of arable and urban landscapes on taxon richness, Shannon–Wiener diversity, taxon rareness and taxonomic distinctness of eleven organism groups encompassing vertebrates, invertebrates and plants, occurring in five freshwater ecosystem types across Europe: rivers, floodplains, lakes, ponds and groundwater. In addition, nine geo-climatic descriptors (e.g. latitude, longitude, precipitation) were used to disentangle land use effects from those of natural drivers of biodiversity. Using a variance partitioning scheme based on boosted regression trees and generalised linear regression modelling, we sought: (i) to partition the unique, shared and unexplained variation in the metrics explained by both groups of descriptor variables, (ii) to quantify the contribution of each descriptor variable to biodiversity variation in the most parsimonious regression model and (iii) to identify interactions of land use and natural descriptors. The variation in biodiversity uniquely described by land use was consistently low across both ecosystem types and organism groups. In contrast, geo-climatic descriptors uniquely, and jointly with land use, explained significantly more variance in all 39 biodiversity metrics tested. Regression models revealed significant interactions between geo-climatic descriptors and land use for a third of the models, with interactions accounting for up to 17% of the model's deviance. However, no consistent patterns were observed related to the type of biodiversity metric and organism group considered. Subdividing data according to the strongest geo-climatic gradient in each dataset aimed to reduce the strength of natural descriptors relative to land use. Although data sub-setting can highlight land use effects on freshwater biodiversity, sub-setting our data often failed to produce stronger land use effects. There was no increase in spatial congruence in the subsets, suggesting that the observed land use effects were not dependent on the spatial extent of the subsets. Our results confirm significant joint effects of, and interactions between, land use and natural environmental descriptors on freshwater biodiversity, across ecosystem types and organism groups. This has implications for biodiversity monitoring. First, the combined analysis of anthropogenic and natural descriptors is a prerequisite for the analysis of human threats to biodiversity. Second, geo-climatically, but not necessarily geographically more homogeneous datasets can help unmask the role of anthropogenic descriptors. And third, whole community-based biodiversity metrics (including taxon richness) are not ideal indicators of anthropogenic effects on biodiversity at broad scales. [ABSTRACT FROM AUTHOR]

A large number of studies have tried to understand the determinants of local species richness, i.e. α-diversity. Studies dealing with β-diversity are considerably less numerous but their number has increased in the recent years. In this study, we assessed the relative importance of local and landscape (i.e. composition and connectivity) variables in explaining α- and β-diversities (species turnover and nestedness) of three highly diverse groups, differing in mobility and dispersal: plants, spiders, and carabids. Sampling took place in 2013, using suction samplers for arthropods and phytosociological relevés for vegetation, in 77 hay meadows distributed along 200 km of the Loire Valley (France). We found plant α-diversity to be driven by local factors, whereas spider and carabid α-diversities were mostly determined by landscape factors (by composition and connectivity, respectively). Nestedness was negligible for the three groups. Plant β-diversity was also mainly influenced by local factors, whereas spider β-diversity was driven by landscape factors (composition and connectivity, equally). Surprisingly, carabid β-diversity was mainly influenced by local factors and landscape connectivity. Despite these differences, plant, spider, and carabid β-diversities were not different, suggesting comparable dispersal abilities and/or a low connectivity at large scale, which is in accordance with the high species turnover observed here. Managing biodiversity in meadows consequently necessitates acting at local and landscape scales, the first targeting plants and the second arthropods. [ABSTRACT FROM AUTHOR]

Seed dispersal effectiveness (SDE) is the contribution of dispersers to plant recruitment and is estimated as the product of the number of seeds dispersed (quantity) and the probability of recruitment of each dispersed seed (quality). Although SDE is a key concept in seed dispersal ecology, few studies estimate SDE and none has a community approach. Oceanic islands, with simple communities, are ideal for this purpose. In this study, we compared the SDE of the main types of dispersers (lizards and passerine birds) at the community level in a given habitat. We estimated SDE using a stochastic simulation model parameterized with empirical data on quantity and quality components measured throughout the recruitment process. Although lizards are highly frugivorous and their density was ;20 times higher than that of birds, lizards and birds dispersed a similar quantity of seeds. This may be due to lower intake of seeds by lizards due to their slower metabolism (;20 times lower than birds). This low metabolic rate limits the importance of lizards as seed dispersers, but it is compensated by extraordinarily high lizard densities in the study area (;9600 individuals/km2). High densities of lizards are typical of islands, and this helps to explain why dispersal by lizards seems mainly an island phenomenon. Birds and lizards showed functional complementarity, especially regarding seed dispersal distribution patterns. In fact, lizards dispersed more seeds in shrublands and open sites, and birds in woodlands and beneath canopies, with their joint contribution helping to maximize recruitment. Lizards provided higher SDE than birds for 7 out of 11 plant species. The disperser with a higher quantity for a given plant generally had the higher quality, and plants could be classified as bird- or lizarddependent for dispersal. This dependence increased when considering SDE instead of dispersal quantity only. Moreover, quality was a better predictor of SDE than quantity, which should be considered when parameterizing interaction networks, as this might affect inferences about their architecture. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim To test the Eltonian noise hypothesis ( ENH), that biotic interactions do not affect species distributions at large geographical scales. Location The Brazilian cerrado, a central South American savanna and biodiversity hotspot. Methods We modelled the distributions of 11 species of cerrado parrots using the software Maxent at four different spatial resolutions. We built models using abiotic variables, biotic variables (distribution of diet resources) and models combining abiotic and biotic variables. We compared model performance using the area under the curve of the receiver operating characteristic ( AUC), retrieved from test data. We partitioned the variance between sets of predictors using a generalized linear model ( GLM). Finally, we evaluated whether improvement in model performance (higher AUC values) in models with both abiotic and biotic variables, was related to the species' dietary niche breadth and/or spatial resolution of the models. Results We found that model performance was improved in most cases by the addition of biotic variables. Our variance-partitioning approach revealed that abiotic and biotic variables contribute independently to the final model. We found no relationship between model improvement and spatial resolution. We also found no relationship between dietary niche breadth and model improvement, indicating that dietary generalist and specialist species were not differently affected by the inclusion of biotic variables in the models. Main conclusions Our results did not support the ENH. In this study, we explicitly incorporated a biotic variable (diet resource distribution) into species distribution models ( SDMs), and we showed that these variables generally improve models and have independent contributions. These results agree with previous studies that incorporated biotic variables into SDMs. Ultimately, our results indicate that SDMs performed with abiotic variables only may depict only a partial representation of the geographical distribution of a species. [ABSTRACT FROM AUTHOR]

Abstract: Belowground communities support a great diversity of organisms, but the factors that maintain and regulate this diversity are poorly understood. Both abiotic and biotic factors affect the abundance, diversity and distribution of soil organisms, and the spatial heterogeneity in these factors is a key in explaining belowground biodiversity. However, a combined approach estimating the relative importance of spatial and environmental factors in small-scale structuring of soil communities is yet missing. Here, a semi-natural grassland in south-central Sweden with high diversity of plants was sampled at two spatial scales (10 and 60 cm intervals) with the aim to examine the relative roles of plant identity, abiotic environmental factors and spatial factors for the small-scale spatial patterns of nematodes. The data were analysed by variance partitioning with redundancy analysis. Space, vegetation and abiotics were of similar importance for variation in nematode community composition. However, the contribution of the different sets of variables differed between the different nematode feeding groups: plant-feeding nematodes were influenced more by spatial variables, fungal-feeding nematodes and omnivores/predators more by plants and bacterial-feeding nematodes more by abiotic variables. The ranges of spatial dependence for the different feeding groups were all of the same magnitude, around 1 m. The results add to the understanding of the factors that contribute to soil biodiversity, and they show that combining plant and abiotic variables into one set of environmental variables hide important information about the drivers for belowground community assembly. [Copyright &y& Elsevier]

Abstract: Proper classification of sites is critical for the use of biological indices that can distinguish between natural and human-induced variation in biological response. The macrophyte-based index of biotic integrity was developed to assess the condition of Minnesota lakes in relation to anthropogenic stressors, but macrophyte community composition varies naturally across the state. The goal of the study was to identify environmental characteristics that naturally influence macrophyte index response and establish a preliminary lake classification scheme for biological assessment (bioassessment). Using a comprehensive set of environmental variables, we identified similar groups of lakes by clustering using flexible beta classification. Variance partitioning analysis of IBI response indicated that evaluating similar lake clusters could improve the ability of the macrophyte index to identify community change to anthropogenic stressors, although lake groups did not fully account for the natural variation in macrophyte composition. Diagnostic capabilities of the index could be improved when evaluating lakes with similar environmental characteristics, suggesting the index has potential for accurate bioassessment provided comparable groups of lakes are evaluated. [Copyright &y& Elsevier]

Ancient woodlands are highly important for biodiversity. Flightless beetles and window traps may first appear to be incompatible as a study group and a study method. Little is known about the actual capability of window traps in monitoring of entire forest arthropod communities. We try to determine the possibility of using window traps (designed as tree traps) as an additional method to trap flightless beetles of the genera Carabus (Carabidae), Acalles and Trachodes (Curculionidae), as vulnerable representatives of wildlife forest fauna with high conservation value. From the environmental point of view, the occurrence of the studied flightless beetles was significantly more influenced by altitude than tree species as the studied environmental variables. Several beetles also showed positive significant species to species relationships during their observed phenological activity. Our results showed that the studied flightless beetles may reappear in secondary forests if these reach their optimal structure. On the other hand, they may be sensitive to large scale disturbances and not only to those caused by commercial forestry. The results also showed that window traps designed as tree traps could be used to successfully trap assemblages of forest fauna including flightless species. [ABSTRACT FROM AUTHOR]

In the current context of global habitat loss, a fundamental challenge is to understand how ecological processes interact to determine community composition. Despite the accumulating evidence base for global declines in bee populations, few studies have addressed the relative importance of local environmental and large-scale spatial factors in maintaining diverse bee communities outside of agricultural habitats, and particularly in areas protected for nature conservation., We analysed bee community data that we collected from 40 Special Areas of Conservation representing five distinct European Natura 2000 priority habitats in Ireland, quantifying local habitat features within each site and surrounding land-use. Species data were collected in a nested sampling design composed of three hierarchical levels such as 'site', 'habitat' and 'region' and analysed using diversity partitioning. The species-environment relationship was also decomposed into regional-, landscape- and local-scales by variance partitioning using partial canonical correspondence analysis., Wild bee species richness and abundance were highly dependent on habitat type, but the majority of regional diversity was contained within sites, as opposed to species turnover across sites and regions. Bee communities were primarily structured by local-scale factors associated with nesting resources and grazing regime, with non- Bombus taxa being more sensitive to landscape-scale differences in adjacent habitats than Bombus taxa. Regional-scale processes, such as species sorting along longitudinal gradients, were of minor importance in structuring bee communities in this system., Synthesis and applications. Within habitats, local species richness, rather than species turnover at higher spatial scales, accounted for the majority of regional bee diversity. Local environmental factors were powerful determinants of community composition. Therefore, management effort prioritising the maintenance of a diversity of high-quality habitats within a broad network of protected areas best facilitates bee conservation in this system. At a regional level, schemes for conserving and restoring important bee habitats must be habitat- and taxon-specific, as the impact of individual local-scale factors and surrounding land-use on community composition is highly habitat- and taxon-dependent. [ABSTRACT FROM AUTHOR]

Environmental factors and land-use are likely interacting to drive forest structure and species diversity, making it difficult to disentangle their separate impacts. Both components influence the resilience and stability of mountain forests in the Mediterranean Basin, since secular land-use has shaped stands structure and forests dynamics are constrained to the environment. Approaches covering environmental factors and contrasting land-uses are still needed to understand their implications on forest dynamics. We investigated patterns of environmental variables, stand structure and biodiversity in forest dominated by Abies pinsapo for 61 stands over their whole range. In addition, since land-use by local inhabitant could be a key factor, logging intensity was quantified by stumps basal area and recent land-use history was investigated. Partial redundancy analysis (pRDA) was conducted to assess to which degree the structural attributes are related to environmental characteristics and/or the land-use in the main A. pinsapo forests. Environmental characteristics accounted for 13% of the total variance, while the contrasting land-use (Spain vs. Morocco) and the stumps basal area, as indicator of human logging, accounted for 23% of the total variance. Trees species diversity was near 5 times higher in Moroccan stands than in stands from south Spain. According to recent human logging, Spanish stands have been strictly protected, but Moroccan stands showed widespread axe-logging by local inhabitant over the smaller tree sizes. Our results suggest that the preservation of a minor perturbation regimen by local populations enhance and help to preserve the whole biodiversity of this relict habitat. [ABSTRACT FROM AUTHOR]

The article presents a study which investigates the accuracy of LiDAR remote sensing in predicting spider distributions in remote forested and mountainous terrain. The study made uses of pitfall traps to capture over 2300 spiders across multiple transects in the Bavarian National Park in Germany. The result of the study shows that the LiDAR was capable of assisting species-specific conservation and biodiversity planning for vertebrates and invertebrates.

Abstract: Although the effect of forest management on lichens in temperate forests has been widely examined, little is known about the influence of management-related factors on their biodiversity relative to factors that cannot be altered by management. Here we determined whether forest structure or climate determines lichen diversity in the Bavarian Forest National Park in southeastern Germany, taking spatial variables into account. We investigated 517 single tree stems along 4 transects in 113 pre-stratified plots (8m in diameter) in this montane forest. We grouped environmental variables into three sets: climate (macroclimate, non-manageable), forest structure (manageable), and space. The explanatory powers of these sets of variables for lichen diversity were compared using variance partitioning for the lichen community, species density, and threatened species density. The relationships of single characteristics of forest structure with lichen species diversity were analyzed using generalized linear models (GLM). Lichen diversity was better explained by stand structures than by climate. Spatial effects influenced the number of species per plot. Among the structural features, the availability of dead wood and sycamore maple as well as forest continuity were most important for the enhancement of lichen diversity. Open canopy structures affected the total diversity positively. Although the availability of large trees was not an influential factor in the GLM at the plot level, high diversity levels were generally associated with large stem diameters at the level of single stems. We provide recommendations for sustainable forest-management practices that aim at specifically enhancing lichen diversity in temperate areas experiencing low levels of air pollution. [Copyright &y& Elsevier]

1. Characterisation of biodiversity is typically based on taxonomic approaches, while much less is known about other related aspects. Functional trait diversity is one such component of biodiversity that has not been addressed rigorously in ecological research until recently. We tested the congruence between taxonomic- and trait-based approaches, and examined how spatial configuration, local abiotic environmental factors and biotic effects interact to influence taxonomic- and trait-based characterisation of freshwater fish assemblages. 2. Fish assemblage data were compiled for 124 lakes in southern Finland. Variance partitioning in both linear regression analyses and redundancy analysis was used to quantify the relative contribution of spatial and environmental variables to taxonomic and functional trait diversity and structure. Additionally, a null model analysis was used to test for the potential effects of interspecific segregation and biotic interactions on the co-occurrence of species. 3. The species pool was relatively poor. However, trait-based classification of species indicated that most species belonged to unique functional entities, which suggested low redundancy in species composition. Correlation analysis indicated a very strong relationship between species richness (SR) and the number of unique trait combinations (UTC). Ecoregion-level heterogeneity in SR and UTC were well represented in a relatively small group of randomly selected lakes ( c. 30 lakes). Multiple regressions indicated moderate roles for abiotic environmental variables (i.e. lake surface area, depth, total phosphorous, colour and pH) in determining SR, UTC and the distribution of single trait categories, whereas geographical location was not generally influential. 4. Redundancy analysis revealed similar patterns to those of diversity analyses for taxonomic and associated trait-based structure, emphasising the effect of abiotic environmental variables and the negligible effect of geographical position. 5. Co-occurrence analysis indicated significant checkerboard distribution at the whole assemblage level, but interspecific segregation proved to be of relatively minor importance in the constrained analyses, where species pair combinations within trait category groups were evaluated. 6. Our results suggest that taxonomic- and trait-based patterns of boreal lake fish assemblages are strongly interrelated. Environmental filtering through the effects of local abiotic variables seems to have the most prominent role in determining trait-based assemblage patterns among lakes, which may also be secondarily shaped by biotic interactions. 7. From the applied perspective, it may not necessarily matter whether traditional taxonomic or more novel trait-based approaches are used in characterising spatial patterns in boreal fish assemblages. However, trait-based approaches may provide complementary information which cannot be directly revealed by taxonomic data. [ABSTRACT FROM AUTHOR]

Aim In this continental study, species richness at local (LSR) and regional (RSR) scales was correlated and examined as a function of stream (local) and watershed (regional) environment in an effort to elucidate what factors control diatom biodiversity across scales. Location Conterminous United States. Methods Data on diatom richness, stream conditions and watershed properties were generated by the US Geological Survey. In the present investigation, RSR was estimated as the total diatom richness in a hydrologic study unit and, together with stream and watershed characteristics, was included in stepwise multiple regressions of LSR. The unique and shared contributions of RSR, stream and watershed environment to the explained variance in LSR were determined by variance partitioning. RSR was regressed against stream and basin features averaged per study unit. Results LSR responded most strongly to variability in stream manganese concentration and RSR. Other predictors included stream discharge and iron concentration, soil organic matter content and fertilization, and proportions of open water, barren land and forest in the watershed. Variance partitioning revealed that RSR had the lowest independent contribution to explained variance in LSR. Multiple regressions identified average stream iron concentration as the most important predictor of RSR. Main conclusions Local micronutrient concentration was the major predictor of LSR, followed by RSR. Since average micronutrient supply in the region was the chief determinant of RSR, it is proposed that micronutrients had both a direct effect on LSR and an indirect effect through RSR. The same argument is extended to watershed features with an impact on stream trophic status, because of their substantial contributions to the explained variance in both LSR and RSR. Considering that the major proportion of LSR variance explained by RSR originated from the covariance of RSR with stream and watershed properties, it is concluded that the LSR–RSR relationship was mediated by the local and regional environment. [ABSTRACT FROM AUTHOR]

Abstract: Baseline information on the biodiversity of plantation forests, including how it varies with silvicultural methods and along geographic and edaphic gradients, is fundamental when designing conservation and enhancement programmes. Ground flora communities in Sitka spruce (Picea sitchensis), ash (Fraxinus excelsior) and Japanese larch (Larix kaempferi) forests at the main stages of stand structural development, and located across the Republic of Ireland on a range of varied site types, are examined. Using flexible beta clustering and indicator species analysis, eight distinct ground flora community types are identified, varying in composition, structure and/or diversity: (i) grassland, (ii) heath, (iii) basophilic forest, (iv) closed-canopy conifer forest: first stage, (v) closed-canopy conifer forest: second stage, (vi) acidophilic forest: bryophyte-dominated, (vii) acidophilic forest: grass-dominated, and (viii) bramble-dominated. Canonical correspondence analysis (CCA) and variance partitioning are used to assess the relative influence of silvicultural, geographic and edaphic factors on ground flora composition. While geographic (e.g. previous land-use, underlying geology, proximity to old woodland and elevation) and edaphic (e.g. soil pH, organic matter content and extractable Mg and P) factors are important influences, our results demonstrate considerable scope for manipulating ground flora communities through silvicultural operations. We show, in particular, the opportunity for managing stand structure as a means of enhancing ground flora diversity and composition at the plantation scale. [Copyright &y& Elsevier]

1. Biodiversity–environment relationships are increasingly well-understood in the context of species richness and species composition, whereas other aspects of biodiversity, including variability in functional diversity (FD), have received rather little rigorous attention. For streams, most studies to date have examined either taxonomic assemblage patterns or have experimentally addressed the importance of species richness for ecosystem functioning. 2. I examined the relationships of the functional biodiversity of stream macroinvertebrates to major environmental and spatial gradients across 111 boreal headwater streams in Finland. Functional biodiversity encompassed functional richness (FR – the number of functional groups derived from a combination of functional feeding groups and habit trait groups), FD – the number of functional groups and division of individuals among these groups, and functional evenness (FE – the division of individuals among functional groups). Furthermore, functional structure (FS) comprised the composition and abundance of functional groups at each site. 3. FR increased with increasing pH, with additional variation related to moss cover, total nitrogen, water colour and substratum particle size. FD similarly increased with increasing pH and decreased with increasing canopy cover. FE decreased with increasing canopy cover and water colour. Significant variation in FS was attributable to pH, stream width, moss cover, substratum particle size, nitrogen, water colour with the dominant pattern in FS being related to the increase of shredder-sprawlers and the decrease of scraper-swimmers in acidic conditions. 4. In regression analysis and redundancy analysis, variation in functional biodiversity was not only related to local environmental factors, but a considerable proportion of variability was also attributable to spatial patterning of environmental variables and pure spatial gradients. For FR, 23.4% was related to pure environmental effects, 15.0% to shared environmental and spatial effects and 8.0% to spatial trends. For FD, 13.8% was attributable to environmental effects, 15.2% to shared environmental and spatial effects and 5% to spatial trends. For FE, 9.0% was related to environmental variables, 12.7% to shared effects of environmental and spatial variables and 4.5% to spatial variables. For FS, 13.5% was related to environmental effects, 16.9% to shared environmental and spatial effects and 15.4% to spatial trends. 5. Given that functional biodiversity should portray variability in ecosystem functioning, one might expect to find functionally rather differing ecosystems at the opposite ends of major environmental gradients (e.g. acidity, stream size). However, the degree to which variation in the functional biodiversity of stream macroinvertebrates truly portrays variability in ecosystem functioning is difficult to judge because species traits, such as feeding roles and habit traits, are themselves strongly affected by the habitat template. 6. If functional characteristics show strong responses to natural environmental gradients, they also are likely to do so to anthropogenic environmental changes, including changes in habitat structure, organic inputs and acidifying elements. However, given the considerable degree of spatial structure in functional biodiversity, one should not expect that only the local environment and anthropogenic changes therein are responsible for this variability. Rather, the spatial context, as well as natural variability along environmental gradients, should also be explicitly considered in applied research. [ABSTRACT FROM AUTHOR]

To describe the spatial variation in pteridophyte species richness; evaluate the importance of macroclimate, topography and within-grid cell range variables; assess the influence of spatial autocorrelation on the significance of the variables; and to test the prediction of the mid-domain effect.The Iberian Peninsula.We estimated pteridophyte richness on a grid map withc. 2500 km2 cell size, using published geocoded data of the individual species. Environmental data were obtained by superimposing the grid system over isoline maps of precipitation, temperature, and altitude. Mean and range values were calculated for each cell. Pteridophyte richness was related to the environmental variables by means of nonspatial and spatial generalized least squares models. We also used ordinary least squares regression, where a variance partitioning was performed to partial out the spatial component, i.e. latitude and longitude. Coastal and central cells were compared to test the mid-domain effect.Both spatial and nonspatial models showed that pteridophyte richness was best explained by a second-order polynomial of mean annual precipitation and a quadratic elevation-range term, although the relative importance of these two variables varied when spatial autocorrelation was accounted for. Precipitation range was weakly significant in a nonspatial multiple model (i.e. ordinary regression), and did not remain significant in spatial models. Richness is significantly higher along the coast than in the centre of the peninsula.Spatial autocorrelation affects the statistical significance of explanatory variables, but this did not change the biological interpretation of precipitation and elevation range as the main predictors of pteridophyte richness. Spatial and nonspatial models gave very similar results, which reinforce the idea that water availability and topographic relief control species richness in relatively high-energy regions. The prediction of the mid-domain effect is falsified. [ABSTRACT FROM AUTHOR]

Identifying the key drivers of aquatic fauna structuring at multiple spatial scales is critical in reducing biodiversity loss. Macroinvertebrates are the most sensitive indicators of disturbance and they are used as a cost-effective tool for bioassessment at catchment and site scales. The focus of our study was to identify the key drivers from three classes of environmental variables (geophysical landscape, land use, and site habitat) that influence macroinvertebrate richness in different aquatic ecological function regions (AEFRs) of the Liaohe River Basin. We sampled macroinvertebrate assemblages, extracted geophysical and climate variables from geospatial data, and quantified physical and chemical habitats from 407 randomly distributed sites that belong to the three level-I AEFRs. We analyzed our data through multiple linear regression models by using the three classes of predicted variables alone and in combination. The models that were constructed in the first level-I AEFR explained similar amounts of macroinvertebrate richness and had the maximum ability to explain how macroinvertebrate richness distributed (denoted "explaining ability"; geophysical landscape: RGL2 ≈ 60%, land use and site habitat: RLU2 and RSH2 ≈ 50%, and combined: RCB2 ≈ 75%). The explaining abilities for the third level-I AEFR were as follows: RGL2 ≈ 11%, RLU2 ≈ 14%, RSH2 ≈ 25%, and RCB2 ≈ 38%. The explaining abilities for the 4th level-I AEFR were as follows: RGL2 ≈ 30%, RLU2 ≈ 7%, RSH2 ≈ 40%, and RCB2 ≈ 55%. We conclude that: (1) all of the combined models explained more interaction as compared with the single models; (2) the environmental variables differed among different level-I AEFRs; and, (3) variables in the site habitat scale were the most robust explainers when analyzing the relationship between environmental variables and macroinvertebrate richness and they can be recommended as the optimal candidate explainer. These results may provide cost-effective tools for distinguishing and identifying the drivers of sensitive aquatic organisms at regional scales. [ABSTRACT FROM AUTHOR]