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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.

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

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.

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 specifi

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 specifi

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.

A fundamental focus in ecology is understanding interactions between environmental heterogeneity and ecological community structure, both of which are currently undergoing unprecedented alterations due to global change. In particular, many freshwater phytoplankton communities are experiencing multiple global change stressors, altering phytoplankton community composition, biomass, and spatial distribution. I used multiple approaches to characterize the interactions between spatial distribution and community structure of phytoplankton and quantify uncertainty in predictions of phytoplankton temporal dynamics. First, I analyzed data from 51 lakes to determine the environmental drivers of phytoplankton vertical distributions across the water column for different phytoplankton groups. I show that the relative importance of environmental drivers varies according to the functional traits of each phytoplankton group. Second, I conducted whole-ecosystem experiments in a reservoir to assess phytoplankton responses to surface water mixing events, which may become more prevalent as storms increase under global change. My results demonstrate that aggregated phytoplankton biomass has inconsistent responses to mixing over the short term, but responses of morphology-based functional groups of phytoplankton to mixing are more predictable. Third, I conducted a long-term whole-ecosystem experiment to assess phytoplankton responses to changes in water column thermal gradients which are predicted to increasingly occur under global change. I found that phytoplankton depth distributions responded similarly to thermal gradient disturbance over multiple years, and changes in depth distributions were related to changes in community composition. Fourth, I produced weekly hindcasts of phytoplankton density in a lake for two years to determine the dominant sources of uncertainty in phytoplankton density predictions. I found that better estimation of current phytoplankton density improved repres

ish assemblages vary through time in both abundance and diversity, often due to changes in climate. The potential consequences of these changes on the larval phase need to be considered. In the Eastern English Channel, fish larvae of 30 taxa, from surveys conducted during spring in the nineties and in 2017 with bongo nets, were used to investigate seasonal and interannual changes in larval assemblages with different statistical tests and multivariate analyses (Outlying Mean Index, Principal Coordinate Analysis and variance partitioning). The major change observed was significant lower abundances in 2017 (in April and May) compared to the nineties. Most of the dominant taxa were two to three-fold less abundant in 2017 than the 1990s. We suggest that the reduced larval abundances in 2017 could be a consequence of lower adult abundances in the area from a switch from a colder to a warmer phase of the Atlantic Multidecadal Oscillation.

ish assemblages vary through time in both abundance and diversity, often due to changes in climate. The potential consequences of these changes on the larval phase need to be considered. In the Eastern English Channel, fish larvae of 30 taxa, from surveys conducted during spring in the nineties and in 2017 with bongo nets, were used to investigate seasonal and interannual changes in larval assemblages with different statistical tests and multivariate analyses (Outlying Mean Index, Principal Coordinate Analysis and variance partitioning). The major change observed was significant lower abundances in 2017 (in April and May) compared to the nineties. Most of the dominant taxa were two to three-fold less abundant in 2017 than the 1990s. We suggest that the reduced larval abundances in 2017 could be a consequence of lower adult abundances in the area from a switch from a colder to a warmer phase of the Atlantic Multidecadal Oscillation.

ish assemblages vary through time in both abundance and diversity, often due to changes in climate. The potential consequences of these changes on the larval phase need to be considered. In the Eastern English Channel, fish larvae of 30 taxa, from surveys conducted during spring in the nineties and in 2017 with bongo nets, were used to investigate seasonal and interannual changes in larval assemblages with different statistical tests and multivariate analyses (Outlying Mean Index, Principal Coordinate Analysis and variance partitioning). The major change observed was significant lower abundances in 2017 (in April and May) compared to the nineties. Most of the dominant taxa were two to three-fold less abundant in 2017 than the 1990s. We suggest that the reduced larval abundances in 2017 could be a consequence of lower adult abundances in the area from a switch from a colder to a warmer phase of the Atlantic Multidecadal Oscillation.

Context: Community composition, environmental variation, and spatial structuring can influence ecosystem functioning, and ecosystem service delivery. While the role of space in regulating ecosystem functioning is well recognised in theory, it is rarely considered explicitly in empirical studies. Objectives: We evaluated the role of spatial structuring within and between regions in explaining the functioning of 36 reference and human-impacted streams. Methods: We gathered information on regional and local environmental variables, communities (taxonomy and traits), and used variance partitioning analysis to explain seven indicators of ecosystem functioning. Results: Variation in functional indicators was explained not only by environmental variables and community composition, but also by geographic position, with sometimes high joint variation among the explanatory factors. This suggests spatial structuring in ecosystem functioning beyond that attributable to species sorting along environmental gradients. Spatial structuring at the within-region scale potentially arose from movements of species and materials among habitat patches. Spatial structuring at the between-region scale was more pervasive, occurring both in analyses of individual ecosystem processes and of the full functional matrix, and is likely to partly reflect phenotypic variation in the traits of functionally important species. Characterising communities by their traits rather than taxonomy did not increase the total variation explained, but did allow for a better discrimination of the role of space. Conclusions: These results demonstrate the value of accounting for the role of spatial structuring to increase explanatory power in studies of ecosystem processes, and underpin more robust management of the ecosystem services supported by those processes.

Context: Community composition, environmental variation, and spatial structuring can influence ecosystem functioning, and ecosystem service delivery. While the role of space in regulating ecosystem functioning is well recognised in theory, it is rarely considered explicitly in empirical studies. Objectives: We evaluated the role of spatial structuring within and between regions in explaining the functioning of 36 reference and human-impacted streams. Methods: We gathered information on regional and local environmental variables, communities (taxonomy and traits), and used variance partitioning analysis to explain seven indicators of ecosystem functioning. Results: Variation in functional indicators was explained not only by environmental variables and community composition, but also by geographic position, with sometimes high joint variation among the explanatory factors. This suggests spatial structuring in ecosystem functioning beyond that attributable to species sorting along environmental gradients. Spatial structuring at the within-region scale potentially arose from movements of species and materials among habitat patches. Spatial structuring at the between-region scale was more pervasive, occurring both in analyses of individual ecosystem processes and of the full functional matrix, and is likely to partly reflect phenotypic variation in the traits of functionally important species. Characterising communities by their traits rather than taxonomy did not increase the total variation explained, but did allow for a better discrimination of the role of space. Conclusions: These results demonstrate the value of accounting for the role of spatial structuring to increase explanatory power in studies of ecosystem processes, and underpin more robust management of the ecosystem services supported by those processes.

Context: Community composition, environmental variation, and spatial structuring can influence ecosystem functioning, and ecosystem service delivery. While the role of space in regulating ecosystem functioning is well recognised in theory, it is rarely considered explicitly in empirical studies. Objectives: We evaluated the role of spatial structuring within and between regions in explaining the functioning of 36 reference and human-impacted streams. Methods: We gathered information on regional and local environmental variables, communities (taxonomy and traits), and used variance partitioning analysis to explain seven indicators of ecosystem functioning. Results: Variation in functional indicators was explained not only by environmental variables and community composition, but also by geographic position, with sometimes high joint variation among the explanatory factors. This suggests spatial structuring in ecosystem functioning beyond that attributable to species sorting along environmental gradients. Spatial structuring at the within-region scale potentially arose from movements of species and materials among habitat patches. Spatial structuring at the between-region scale was more pervasive, occurring both in analyses of individual ecosystem processes and of the full functional matrix, and is likely to partly reflect phenotypic variation in the traits of functionally important species. Characterising communities by their traits rather than taxonomy did not increase the total variation explained, but did allow for a better discrimination of the role of space. Conclusions: These results demonstrate the value of accounting for the role of spatial structuring to increase explanatory power in studies of ecosystem processes, and underpin more robust management of the ecosystem services supported by those processes.

Modern improvement of complex traits in agricultural species relies on successful associations of heritable molecular variation with observable phenotypes. Historically, this pursuit has primarily been based on easily measurable genetic markers. The recent advent of new technologies allows assaying and quantifying biological intermediates (hereafter endophenotypes) which are now readily measurable at a large scale across diverse individuals. The usefulness of endophenotypes for delineating the regulatory landscape of the genome and genetic dissection of complex trait variation remains underexplored in plants. The work presented here illustrated the utility of a large-scale (299-genotype and seven-tissue) gene expression resource to dissect traits across multiple levels of biological organization. Using single-tissue- and multi-tissue-based transcriptome-wide association studies (TWAS), we revealed that about half of the functional variation acts through altered transcript abundance for maize kernel traits, including 30 grain carotenoid abundance traits, 20 grain tocochromanol abundance traits, and 22 field-measured agronomic traits. Comparing the efficacy of TWAS with genome-wide association studies (GWAS) and an ensemble approach that combines both GWAS and TWAS, we demonstrated that results of TWAS in combination with GWAS increase the power to detect known genes and aid in prioritizing likely causal genes. Using a variance partitioning approach in the largely independent maize Nested Association Mapping (NAM) population, we also showed that the most strongly associated genes identified by combining GWAS and TWAS explain more heritable variance for a majority of traits than the heritability captured by the random genes and the genes identified by GWAS or TWAS alone. This not only improves the ability to link genes to phenotypes, but also highlights the phenotypic consequences of regulatory variation in plants.

Context: Community composition, environmental variation, and spatial structuring can influence ecosystem functioning, and ecosystem service delivery. While the role of space in regulating ecosystem functioning is well recognised in theory, it is rarely considered explicitly in empirical studies. Objectives: We evaluated the role of spatial structuring within and between regions in explaining the functioning of 36 reference and human-impacted streams. Methods: We gathered information on regional and local environmental variables, communities (taxonomy and traits), and used variance partitioning analysis to explain seven indicators of ecosystem functioning. Results: Variation in functional indicators was explained not only by environmental variables and community composition, but also by geographic position, with sometimes high joint variation among the explanatory factors. This suggests spatial structuring in ecosystem functioning beyond that attributable to species sorting along environmental gradients. Spatial structuring at the within-region scale potentially arose from movements of species and materials among habitat patches. Spatial structuring at the between-region scale was more pervasive, occurring both in analyses of individual ecosystem processes and of the full functional matrix, and is likely to partly reflect phenotypic variation in the traits of functionally important species. Characterising communities by their traits rather than taxonomy did not increase the total variation explained, but did allow for a better discrimination of the role of space. Conclusions: These results demonstrate the value of accounting for the role of spatial structuring to increase explanatory power in studies of ecosystem processes, and underpin more robust management of the ecosystem services supported by those processes.

Modern improvement of complex traits in agricultural species relies on successful associations of heritable molecular variation with observable phenotypes. Historically, this pursuit has primarily been based on easily measurable genetic markers. The recent advent of new technologies allows assaying and quantifying biological intermediates (hereafter endophenotypes) which are now readily measurable at a large scale across diverse individuals. The usefulness of endophenotypes for delineating the regulatory landscape of the genome and genetic dissection of complex trait variation remains underexplored in plants. The work presented here illustrated the utility of a large-scale (299-genotype and seven-tissue) gene expression resource to dissect traits across multiple levels of biological organization. Using single-tissue- and multi-tissue-based transcriptome-wide association studies (TWAS), we revealed that about half of the functional variation acts through altered transcript abundance for maize kernel traits, including 30 grain carotenoid abundance traits, 20 grain tocochromanol abundance traits, and 22 field-measured agronomic traits. Comparing the efficacy of TWAS with genome-wide association studies (GWAS) and an ensemble approach that combines both GWAS and TWAS, we demonstrated that results of TWAS in combination with GWAS increase the power to detect known genes and aid in prioritizing likely causal genes. Using a variance partitioning approach in the largely independent maize Nested Association Mapping (NAM) population, we also showed that the most strongly associated genes identified by combining GWAS and TWAS explain more heritable variance for a majority of traits than the heritability captured by the random genes and the genes identified by GWAS or TWAS alone. This not only improves the ability to link genes to phenotypes, but also highlights the phenotypic consequences of regulatory variation in plants.

Context: Community composition, environmental variation, and spatial structuring can influence ecosystem functioning, and ecosystem service delivery. While the role of space in regulating ecosystem functioning is well recognised in theory, it is rarely considered explicitly in empirical studies. Objectives: We evaluated the role of spatial structuring within and between regions in explaining the functioning of 36 reference and human-impacted streams. Methods: We gathered information on regional and local environmental variables, communities (taxonomy and traits), and used variance partitioning analysis to explain seven indicators of ecosystem functioning. Results: Variation in functional indicators was explained not only by environmental variables and community composition, but also by geographic position, with sometimes high joint variation among the explanatory factors. This suggests spatial structuring in ecosystem functioning beyond that attributable to species sorting along environmental gradients. Spatial structuring at the within-region scale potentially arose from movements of species and materials among habitat patches. Spatial structuring at the between-region scale was more pervasive, occurring both in analyses of individual ecosystem processes and of the full functional matrix, and is likely to partly reflect phenotypic variation in the traits of functionally important species. Characterising communities by their traits rather than taxonomy did not increase the total variation explained, but did allow for a better discrimination of the role of space. Conclusions: These results demonstrate the value of accounting for the role of spatial structuring to increase explanatory power in studies of ecosystem processes, and underpin more robust management of the ecosystem services supported by those processes.

Context: Community composition, environmental variation, and spatial structuring can influence ecosystem functioning, and ecosystem service delivery. While the role of space in regulating ecosystem functioning is well recognised in theory, it is rarely considered explicitly in empirical studies. Objectives: We evaluated the role of spatial structuring within and between regions in explaining the functioning of 36 reference and human-impacted streams. Methods: We gathered information on regional and local environmental variables, communities (taxonomy and traits), and used variance partitioning analysis to explain seven indicators of ecosystem functioning. Results: Variation in functional indicators was explained not only by environmental variables and community composition, but also by geographic position, with sometimes high joint variation among the explanatory factors. This suggests spatial structuring in ecosystem functioning beyond that attributable to species sorting along environmental gradients. Spatial structuring at the within-region scale potentially arose from movements of species and materials among habitat patches. Spatial structuring at the between-region scale was more pervasive, occurring both in analyses of individual ecosystem processes and of the full functional matrix, and is likely to partly reflect phenotypic variation in the traits of functionally important species. Characterising communities by their traits rather than taxonomy did not increase the total variation explained, but did allow for a better discrimination of the role of space. Conclusions: These results demonstrate the value of accounting for the role of spatial structuring to increase explanatory power in studies of ecosystem processes, and underpin more robust management of the ecosystem services supported by those processes.

Dung consumption and removal is a fundamental ecological process carried out by dung beetles that drive soil nutrient cycling and associated ecosystem services. In this study, the removal rate of small droppings by dung beetles was estimated in natural subtropical rainforests of southern Brazil located along an elevational gradient, in order to understand the factors influencing variation in dung removal. To do that, the comparative explanatory capacity of three main types of variables was quantified: assemblage characteristics, local climatic and habitat conditions, and seasonal variation. The complete disappearance of dung within 48 h after deposition occurs in 73% of occasions. The highest explanatory capacity correspond to the combined effects of the three types of variables; however, average air temperature during the sampling period, total volume of dung beetles collected in the traps in which dung removal was measured, and the seasonal transition from summer to winter were the most important and representative predictors of dung removal. Thus, the dung nutrient incorporation into the soil will most likely be greater during spring‐summer conditions, when the air temperature at the time of dung deposition is high and the biomass of the dung beetle assemblage is bigger.

Species Distribution Models (SDMs) constitute an important tool to assist decision-making in environmental conservation and planning. A popular application of these models is the projection of species distributions under climate change conditions. Yet there are still a range of methodological SDM factors which limit the transferability of these models, contributing significantly to the overall uncertainty of the resulting projections. An important source of uncertainty often neglected in climate change studies comes from the use of background data (a.k.a. pseudo-absences) for model calibration. Here, we study the sensitivity to pseudo-absence sampling as a determinant factor for SDM stability and transferability under climate change conditions, focusing on European wide projections of Quercus robur as an illustrative case study. We explore the uncertainty in future projections derived from ten pseudo-absence realizations and three popular SDMs (GLM, Random Forest and MARS). The contribution of the pseudo-absence realization to the uncertainty was higher in peripheral regions and clearly differed among the tested SDMs in the whole study domain, being MARS the most sensitive — with projections differing up to a 40% for different realizations — and GLM the most stable. As a result we conclude that parsimonious SDMs are preferable in this context, avoiding complex methods (such as MARS) which may exhibit poor model transferability. Accounting for this new source of SDM-dependent uncertainty is crucial when forming multi-model ensembles to undertake climate change projections.

Aim: Despite the huge diversity of soil animals and their recognized contribution to many ecosystem functions, little is known about the relative importance of factors controlling their abundance and distribution. We examined the relative importance of environmental and spatial factors in explaining the species and functional trait composition of terrestrial snail communities at the level of meta-communities (spatial extent c. 100 × 100 km) in a heterogeneous, intensively used landscape. We hypothesized that both spatial and environmental factors contribute to the variation in community structure across the landscape, but expected environmental variables describing local habitat conditions to be most important. Location: County of Skåne, south Sweden. Methods: We quantified community structure in terms of species composition and as functional trait composition, because functional traits directly link species performance to environmental conditions. To disentangle the unique and shared contribution of environmental and spatial factors to the variation in snail community structure (in terms of species and trait composition) we applied a partial redundancy analysis. Results: Species traits explained more of the variance in community composition than species identity. Snail traits such as tolerance to environmental stress (related to soil moisture content) and niche width were correlated with the main environmental gradient. Environmental variables (i.e. soil moisture content, vegetation characteristics and soil pH) contributed considerably more to variation in community composition (species: 11.4%; traits: 24.9%) than the spatial variables (species: 6.5%; traits: 4.2%). Main conclusions: The results highlight that both environmental and spatial variables are required to understand the relative importance of niche-based and intrinsic population processes as drivers of terrestrial snail community structure. However, at the scale of our study niche-based community stru

A large number of studies have tried to understand the determinants of local species richness, i.e. alpha-diversity. Studies dealing with beta-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 alpha- and beta-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 relev,s for vegetation, in 77 hay meadows distributed along 200 km of the Loire Valley (France). We found plant alpha-diversity to be driven by local factors, whereas spider and carabid alpha-diversities were mostly determined by landscape factors (by composition and connectivity, respectively). Nestedness was negligible for the three groups. Plant beta-diversity was also mainly influenced by local factors, whereas spider beta-diversity was driven by landscape factors (composition and connectivity, equally). Surprisingly, carabid beta-diversity was mainly influenced by local factors and landscape connectivity. Despite these differences, plant, spider, and carabid beta-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.

While there are now a number of theoretical models predicting how consistent individual differences in behaviour may be generated and maintained, so far, there are few empirical tests. The social niche specialization hypothesis predicts that repeated social interactions among individuals may generate among-individual differences and reinforce within-individual consistency through positive feedback mechanisms. Here, we test this hypothesis using groups of the social spider Stegodyphus mimosarum that differ in their level of familiarity. In support of the social niche specialization hypothesis, individuals in groups of spiders that were more familiar with each other showed greater repeatable among-individual variation in behaviour. Additionally, individuals that were more familiar with each other exhibited lower within-individual variation in behaviour, providing one of the first examples of how the social environment can influence behavioural consistency. Our study demonstrates the potential for the social environment to generate and reinforce consistent individual differences in behaviour and provides a potentially general mechanism to explain this type of behavioural variation in animals with stable social groups.

While there are now a number of theoretical models predicting how consistent individual differences in behaviour may be generated and maintained, so far, there are few empirical tests. The social niche specialization hypothesis predicts that repeated social interactions among individuals may generate among-individual differences and reinforce within-individual consistency through positive feedback mechanisms. Here, we test this hypothesis using groups of the social spider Stegodyphus mimosarum that differ in their level of familiarity. In support of the social niche specialization hypothesis, individuals in groups of spiders that were more familiar with each other showed greater repeatable among-individual variation in behaviour. Additionally, individuals that were more familiar with each other exhibited lower within-individual variation in behaviour, providing one of the first examples of how the social environment can influence behavioural consistency. Our study demonstrates the potential for the social environment to generate and reinforce consistent individual differences in behaviour and provides a potentially general mechanism to explain this type of behavioural variation in animals with stable social groups.

The study of the relationships between vascular aquatic macrophyte occurrence, species richness andthe local environment are central for suitable ecosystem quality assessments, freshwater bodies manage-ment and assistance for macrophyte restoration. Here we quantify the importance of the local factors, bothwater column and sediment, to provide tools for lentic water systems management and conservation in aMediterranean region. We surveyed 90 water bodies along a 2500 m altitudinal gradient in Catalonia (NESpain). Despite its relatively small scale, the area of study exhibits large-scale environmental gradientsmainly related to a diverse geology and climate. In consequence, the response of aquatic macrophytesto a broad range of environmental conditions can be studied without interference of biogeographicalclines. We identified all vascular aquatic macrophytes and analyzed 35 environmental variables at eachsite. Local environmental factors accounted for only 19% of variance in aquatic macrophyte distribution.Even though water column variables explained more variance than sediment variables in a variance par-titioning analysis (pCCA), a mixed model integrating variables of both compartments performed better.The most important variables driving aquatic macrophyte distribution were water conductivity, waterDOC, water K, water pH, water Na, sediment organic matter, sediment Na and water nitrate. CCA betweenspecies and water and sediment variables clearly segregated coastal lagoons, temporary pools and alpinelakes over two main gradients: ionic content and water body productivity. Species richness was low(4.2 species per water body on average) and GAM showed weak correlations with sediment and mostwater column variables. The best factor explaining species richness was the geomorphological typology,but only temporary pools were significantly different from the other types and had the highest speciesrichness. Thus, temporary pools were unique and displayed a high biodiversit

Invertebrate communities inhabiting different lake zones are expected to respond differently to natural environmental variation and anthropogenic stressors. We used multivariate statistical methods in order to quantify the effects of eutrophication and morphological pressures on the spatial structure of the invertebrate benthic communities at two depth zones (profundal and sublittoral) in subalpine lakes in Italy, Germany and Austria . In both lake zones, environmental variables related to eutrophication pressures (mid-lake total phosphorus and chlorophyll-a) were significant in structuring the invertebrate community (permutation test: p < 0.01). Three variables relating to morphological pressures (diversity of macrophyte growth forms, sum of pressures in the lake shore, and percentage of natural land cover within a 200 m stretch from the lake shore) were significant (permutation test: p < 0.01) in the sublittoral zone, while in the profundal zone none of the variables included in the analysis related to morphological pressures were significant in structuring the invertebrate community. Variance partitioning analysis showed that profundal communities were mainly affected by eutrophication (8.6 % of total variance; p = 0.005), while in the sublittoral zone eutrophication accounted for only 0.5 % (p = 0.04) of total variance. The effects of morphological pressures could be tracked only in the sublittoral zone, where it accounted for 0.8 % of total variance (p = 0.015). The spatial component was responsible for a large part of the total variance (58.7 % in the profundal, p = 0.005; 44.2 % in the sublittoral zone, p = 0.005) and had interactions with stressor variables in both lake zones. Therefore the analysis of spatial patterns should be included in assessment systems relating invertebrate assemblages to pressures.

A Araucaria angustifolia, conhecida como Pinheiro-do-Paraná é uma espécie ameaçada de extinção no Brasil, está inserida num bioma rico em biodiversidade, a Mata Atlântica, e muito pouco se conhece sobre os atributos microbiológicos dessas florestas. Este trabalho teve como objetivo avaliar potenciais atributos microbiológicos do solo e algumas variáveis ambientais (atributos químicos, físicos e efeito sazonal), a fim de estabelecer bioindicadores de qualidade do solo em Florestas de Araucária. Os estudos foram conduzidos em dois parques estaduais localizados em diferentes regiões do Estado de São Paulo, no município de Campos do Jordão (Parque Estadual de Campos do Jordão - PECJ), nos municípios de Apiaí e Iporanga (Parque Estadual Turístico do Alto Ribeira - PETAR) e também no município de Barra do Chapéu. Foram escolhidas três áreas no PETAR: FN floresta nativa de araucária, ND floresta de araucária com distúrbio antropogênico e PL plantio de araucária; e quatro áreas foram selecionadas no PECJ: FN floresta nativa de araucária, ND floresta de araucária com distúrbio antropogênico, PL plantio de araucária e PF plantio de araucária com ocorrência de fogo acidental. Ao acaso, foram selecionadas quinze árvores de araucária por área e sob a copa de cada uma delas foram retiradas amostras na profundidade de 0 a 20 cm, nas épocas seca e de chuva. Foram avaliados os atributos microbiológicos: arilsulfatase (ARIL), fosfatase ácida (FOSF), -glicosidase (GLIC), desidrogenase (DESID), nitrogênio (NBM) e carbono da biomassa microbiana (CBM), Número Mais Provável (NMP) de amonificantes (AMO), nitritadores (NITRI), nitratadores (NITRA) e desnitrificantes (DESN), respiração basal (RESP), respiração induzida por substrato (RIS), quociente metabólico (qCO2) e microbiano (qMIC). Além disso, foram estabelecidos perfis de ácidos graxos ligados a ésteres de fosfolipídios (EL-PLFAs) e o perfil de capacidade de utilização de substratos de carbono (Biolog). Alguns parâmetros químicos fora, Araucaria angustifolia, also called Brazil Pine, is an endangered species in Brazil. It is part of one of the richest ecosystems in biodiversity, the Atlantic Forest, and little is known about the soil microbiological attributes in this forest. The objective was to evaluate the potential of the soil microbiological attributes and some environmental variables (physical-chemical properties and seasonal effect) to act as bioindicators of soil quality in Araucaria Forests. This study was undertaken in two different state parks in the São Paulo State, in Campos do Jordão county (Campos do Jordão State Park - PECJ), and in Apiaí and Iporanga counties (Alto Ribeira Touristic State Park - PETAR) and also in Barra do Chapéu county. Three areas were surveyed in PETAR: FN Native Araucaria forest, ND Native Araucaria forest with anthropogenic disturbance, and PL Reforested Araucaria; and four areas in PECJ: FN Native Araucaria forest, ND Native Araucaria forest with anthropogenic disturbance; PL Reforested Araucaria, and PF Araucaria reforestation submitted to an accidental fire. Fifteen Araucaria trees were selected at random in each area and the soil and roots were sampled at 0 20 cm depth, in two contrasting seasons (dry and wet). The microbiological attributes evaluated were: arylsulfatase (ARIL), acid phosphatase (FOSF), -glucosidase (GLIC), dehydrogenase (DESID), carbon (CBM) and nitrogen microbial biomass (NBM), most probable number (NMP) of bacterial ammonium oxidizers (AMO), nitrite oxidizers (NITRI), nitrate oxidizers (NITRA) and denitrifiers (DESN), basal microbial respiration (RESP), substrate induced respiration (RIS), and metabolic (qCO2) and microbial quotient (qMIC). Additionally we determined the phospholipid fatty acid profiles (ELPLFA) and the community level physiological profile (Biolog). Some chemical attributes were evaluated (pH, H++Al3+, Al3+, Ca2+, Mg2+, K+, P, S, CEC, C/N ratio, total organic carbon (COT), total nitrogen (NT), as well as some physical

Understanding forces that structure plant communities is a key issue in plant community ecology. Traditionally, ecologists have focused on the absolute and the relative roles of competition and herbivory (Sih et al., 1985) and on the relative role of dispersal limitation vs biotic interactions (Huston, 1999), as well as on neutral models (Hubbell, 2001) and on their niche-based counterparts (Cadotte et al., 2008). Increasingly, mycorrhizal ecologists have argued that mycorrhizal fungi should also be considered as fundamentally important determinants of plant community composition. This conviction is motivated by a growing body of research which demonstrates that mycorrhizal fungi can have large effects on plant growth and may modify the strength of other interactions (van der Heijden, 2002), which is taken as proof that mycorrhizas should have a strong effect on plant community structure. We agree that the potential influence of mycorrhizal fungi on structuring plant communities has been conclusively shown. However, the realization of such potential under variable environmental conditions and complex biotic interactions, and the relative influence of the mycorrhizal symbiosis compared with other biotic and abiotic drivers, have only been addressed in a few studies (see Table 1) and remain uncertain for most systems. Interestingly, we find no studies where the relative influence of ectomycorrhizal or ericoid mycorrhizal fungi on plant community structure has been quantified. This may reflect the difficulty of measuring plant community outcomes (e.g. plant community diversity or evenness) in these symbioses, which tend to be formed by long-lived plants. Nonetheless, the widespread failure of ectomycorrhizal plants to establish in the absence of ectomycorrhizas suggests that the effect size of ectomycorrhizal fungi on plant community structure is likely to be large. Quantification, in this case, may only be possible through the creative utilization of individual-based

The distribution of different macroinvertebrate groups inhabiting the littoral zone of 82 mountain lakes in the Pyrenees was investigated in relation to the altitudinal environmental gradient. For each lake, altitude, longitude and latitude, together with 28 environmental variables, relating to chemical and physical characteristics and to lake general productivity, were considered. Using Principal Component Analysis (PCA) we showed that the altitudinal environmental gradient (i.e. altitude and altituderelated variables) represented the largest gradient of environmental variability. We found that incidence was related to altitude in about 50% of macroinvertebrate groups, most relationships being inverse, and also that the number of macroinvertebrate groups found per lake was better described by a second-order polynomial function than by simple linear regression. However, this relationship was linear for a subset of high-altitude lakes above 2,500 m a.s.l., suggesting an ecological threshold around this altitude. Redundancy Analyses (RDAs) showed the importance of environmental factors varying with altitude for the distribution of macroinvertebrate groups. Organic matter, salmonid presence, fine substrate dominance, macrophyte coverage, temperature and altitude by itself were, in this order, the most relevant factors. Partial RDAs showed that different combinations of these variables contributed to the explanation of the distribution of each group. However, the variable that uniquely explained most variability differed from group to group. We conclude that the altitudinal gradient is a multi-faceted ecological factor, which impinges on each group by means of some specific environmental variable(s) that are particularly relevant for the life history of that group.

Questions What influence do management practices and previous tree and shrub stand structure have on the occurrence and development of natural regeneration of Pinus sylvestris in Mediterranean mountain forests? How are the fine-scale and environmental patterns of resources affected and what impact does this have on the distribution of the regeneration? Location A Pinus sylvestris Mediterranean mountain forest in central Spain. Methods Upperstory trees and regeneration (seedlings and saplings) were mapped in four 0.5-ha plots located in two types of stand with different management intensities (even-aged and uneven-aged stands). Environmental variables were recorded at the nodes of a grid within the plots. The relationships between the upperstory and regeneration were evaluated by bivariate point pattern analysis; redundancy analysis ordination and variation partitioning were performed to characterize regeneration niches and the importance of the spatial component. Results Seedlings and saplings presented a clumped structure under both types of management and their distribution was found to be related to the spatial distribution of favourable microsites. Regeneration was positively related to conditions of partial cover with high soil water content during the summer. More than half of the explained variance was spatially structured in both types of stand. This percentage was particularly high in the even-aged stands where the pattern of regeneration was highly influenced by the gaps created by harvesting. Conclusions The spatial distribution of the tree and shrub upperstory strongly influences regeneration patterns of P. sylvestris. Current management practices, promoting small gaps, partial canopy cover and moderate shade in even-aged stands, or favouring tree and shrub cover in the case of uneven-aged stands, appears to provide suitable conditions for the natural regeneration of P. sylvestris in a Mediterranean climate. © 2009 International Association for Vegetatio

Flood and flow pulses are primary factors that regulate macroinvertebrate community structure in river-floodplain ecosystems. In order to assess the impacts of these important hydrological events in a regulated Mediterranean river, bimonthly water and macroinvertebrate samples were collected in 2006 in the Middle Ebro River channel and six floodplain wetlands (NE Spain).We found significant differences among the river sites (permanently connected), two constructed wetlands (groundwater seepage) and three natural oxbow lakes (surface connected at 400, 800 and 1200 m3/s). River sites were dominated by aquatic worms (e.g., Naididae) and showed a high degree of eutrophication. Constructed wetlands provided new habitat for predatory insects (e.g.,Coenagrion scitulum and Trithemis annulata) that benefited from the absence of fish. Natural oxbow lakes were dominated by crustaceans (e.g., Atyaephyra desmarestii, Procambarus clarkii) and were highly overlapped in Correspondence Analysis. Canonical Correspondence Analysis, coupled with variance partitioning, showed that hydrological connectivity accounted for 28% of the variability in the invertebrate community, followed by physicochemical (10%) and trophic (7%) factors. Differences in frequency and duration of flood pulses in natural oxbow lakes were not enough to generate distinctive macroinvertebrate assemblages in the different wetlands. Analysis of variance showed that richness and total abundance increased with hydrological connectivity, while diversity showed a rather unimodal distribution. Generalized Additive Models indicated that among the measured environmental variables, nitrate concentration strongly affected the composition, abundance and diversity of aquatic communities. Our data indicate that increasing the diversity of water body types in degraded floodplains enhances biodiversity and aids in the functional and ecological recovery of the riverine landscape.

The niche space of a species has been defined as the region in N-dimensional environmental hyperspace in which the fitness of the individuals is positive. In zooplankton assemblages, there has been little consideration of how different density-dependent (i.e. resources) and density-independent (i.e. conditions) environmental factors relate to fitness components in the field, namely survival and reproduction. We studied the abundance and reproduction (egg ratio) variability of seven species of pelagic rotifers living in a high-mountain lake and their relation to a number of environmental factors by means of partial canonical correspondence analyses. The generally higher explanatory capacity of conditions over resources suggests that habitat partitioning among species largely relies on historical processes, which are internalised in life history traits of spatial and temporal habitat use. However, the increase in the relevance of resources when considering reproduction, as compared to abundance, indicates that there is still an on-going interactive niche segregation process among rotifer species, which affects present and future rotifer assemblages in the lake. Our study shows the value of considering measurements close to fitness components (e.g. egg ratio) for detecting on-going niche segregation processes in zooplankton, which may help to resolve paradoxes in relation to species coexistence in natural assemblages.

This paper describes the relative influence of: (i) landscape scale environmental and hydrological factors; (ii) local scale environmental conditions including recent flow history, and; (iii) spatial effects (proximity of sites to one another) on the spatial and temporal variation in local freshwater fish assemblages in the Mary River, south-eastern Queensland, Australia. Using canonical correspondence analysis, each of the three sets of variables explained similar amounts of variation in fish assemblages (ranging from 44 to 52%). Variation in fish assemblages was partitioned into eight unique components: pure environmental, pure spatial, pure temporal, spatially structured environmental variation, temporally structured environmental variation, spatially structured temporal variation, the combined spatial/temporal component of environmental variation and unexplained variation. The total variation explained by these components was 65%. The combined spatial/temporal/environmental component explained the largest component (30%) of the total variation in fish assemblages, whereas pure environmental (6%), temporal (9%) and spatial (2%) effects were relatively unimportant. The high degree of intercorrelation between the three different groups of explanatory variables indicates that our understanding of the importance to fish assemblages of hydrological variation (often highlighted as the major structuring force in river systems) is dependent on the environmental context in which this role is examined.

The spatial patterns of recruits in a Mediterranean forest in Southwest Portugal were examined. We aimed to investigate how several environmental and canopy variables contribute to the observed patterns, and how relevant the spatial component is in explaining the variance in the density of recruits. We took a census of every recruit of four dominant woody species (Arbutus unedo, Quercus faginea, Q. suber, and Viburnum tinus), mapping their position inside two forest plots. For a total of 309 recruits, we measured the following variables: soil moisture, slope, canopy density, herbaceous and litter ground cover, overlying species and height, and distance to the nearest adult of the same and different species. Spatial pattern analysis, principal coordinate analysis of neighbor matrices, canonical correspondence analysis, and variance partitioning were performed to detect significant deviations from complete spatial randomness and identify conspecific and interspecific patterns, characterize regeneration niches, and evaluate the importance of the spatial component. Results showed the existence of significant community structure at the recruitment stage. The distance between recruits and the nearest conspecific adult was the main explanatory variable. Light availability, soil moisture, litter accumulation, and the overlying species were also significant factors in explaining the variance in the density of recruits. The best model accounted for 37% of the overall variance in the density of recruits, and most (80%) of the explained variance corresponded to spatially structured variance. This case study shows the importance of the spatial component in understanding the forest regeneration patterns under Mediterranean conditions and will contribute to the implementation of ecologically based management actions to preserve the remaining forest fragments.

[EN]: Forest ecosystems provide goods and services with inestimable value. In particular, well-preserved forests are extremely important as benchmarks for monitoring the effects of human-caused changes of the environment, and to measure the sustainability and ecological importance of disturbed ecosystems. However, the world is changing fast towards a less forested planet, because of the destruction, disturbance and change of primitive forests, which make them more rare and vulnerable to an equilibrium rupture and ecosystem disruption. At the south of Portugal, only small, rare and disperse patches of natural forests remain nowadays, due to the particularly long human activity typical of all the Mediterranean Basin., [PO]: Os ecossistemas florestais proporcionam ao Homem bens e serviços de valor inestimável. O estudo das florestas naturais (ou em bom estado de conservação) em particular, é extremamente importante e serve de situação de referência para a monitorização dos efeitos da acção do homem no ambiente e para avaliar a sustentabilidade e valor ecológico dos ecosistemas perturbados. No entanto, são profundas e rápidas as alterações que sucedem à escala planetária no que respeita à área ocupada pelos ecosistemas florestais: a destruição, perturbação ou alteração das florestas primitivas torna-as mais raras e vulneráveis a uma ruptura do seu equilíbrio ecológico e à perda de todo o ecossistema. No sul de Portugal, actualmente apenas persistem áreas pequenas, raras e dispersas de floresta natural, devido à imensa história de actividade humana, típica aliás de toda a Bacia Mediterrânica.

Assessing ecosystem dynamics beyond experimental time-scales is a prerequisite to understand effects of ongoing environmental change and essential to improve predictions of future conditions. In this study, we analyze a time series of an annually resolved sediment record from a boreal lake (Nylandssjön) in northern Sweden, consisting of diatom data since AD 1931 and geochemistry data since AD 1953. The aim of this paper is to quantify to which extent the main primary producers (i.e., diatom assemblage) in a typical boreal lake are related to processes in the lake catchment, sediment properties, and climate variables (temperature, precipitation, circulation patterns). The diatom assemblage consists mainly of Cyclotella taxa (C. glomerata, C. radiosa, and C. rossii), Asterionella formosa, Fragilaria delicatissima and other small Fragilaria taxa. Although the dominant taxa remain the same over the entire sediment record, their relative abundances exhibit some distinct shifts. We use ordination techniques and variance partitioning to quantify the explanatory power of environmental variables to explain shifts in the diatom assemblage composition. A series of redundancy analyses (RDA) using one sole constraining variable showed that both geochemical proxies and climate variables explained a statistically significant amount of the variance in the diatom data. The most powerful sediment proxy variables were Pb (ppm, 17.9%), C (%, 16.8%), N (%, 15.7%) and sedimentation rate (g cm-2 yr-1, 13.2%). For climate variables, temperature during winter/spring (April 6.4%, May 5.0%, February 4.6%) and the Northern Atlantic Oscillation index (NAO 6.4%) showed the highest predictive power, whereas precipitation data did not turn out to be a powerful predictor. Variance partitioning showed that sediment proxies (sedimentation rate, C, N; 20.8%), variables associated with pollution (Pb, Cu, P; 23.1%) and climate (winter/spring temperature, NOA; 10.4%) explained significant amounts of the