The consequences of spatial structure for the design and analysis of ecological field surveys

In ecological field surveys, observations are gathered at different spatial locations. The purpose may be to relate biological response variables (e.g., species abundances) to explanatory environmental variables (e.g., soil characteristics). In the absence of prior knowledge, ecologists have been taught to rely on systematic or random sampling designs. If there is prior knowledge about the spatial patterning of the explanatory variables, obtained from either previous surveys or a pilot study, can we use this information to optimize the sampling design in order to maximize our ability to detect the relationships between the response and explanatory variables?
The specific questions addressed in this paper are: a) What is the effect (type I error) of spatial autocorrelation on the statistical tests commonly used by ecologists to analyse field survey data? b) Can we eliminate, or at least minimize, the effect of spatial autocorrelation by the design of the survey? Are there designs that provide greater power for surveys, at least under certain circumstances? c) Can we eliminate or control for the effect of spatial autocorrelation during the analysis? To answer the last question, we compared regular regression analysis to a modified t‐test developed by Dutilleul for correlation coefficients in the presence of spatial autocorrelation.
Replicated surfaces (typically, 1000 of them) were simulated using different spatial parameters, and these surfaces were subjected to different sampling designs and methods of statistical analysis. The simulated surfaces may represent, for example, vegetation response to underlying environmental variation. This allowed us 1) to measure the frequency of type I error (the failure to reject the null hypothesis when in fact there is no effect of the environment on the response variable) and 2) to estimate the power of the different combinations of sampling designs and methods of statistical analysis (power is measured by the rate of rejection of the null hypothesis when an effect of the environment on the response variable has been created).
Our results indicate that: 1) Spatial autocorrelation in both the response and environmental variables affects the classical tests of significance of correlation or regression coefficients. Spatial autocorrelation in only one of the two variables does not affect the test of significance. 2) A broad‐scale spatial structure present in data has the same effect on the tests as spatial autocorrelation. When such a structure is present in one of the variables and autocorrelation is found in the other, or in both, the tests of significance have inflated rates of type I error. 3) Dutilleul's modified t‐test for the correlation coefficient, corrected for spatial autocorrelation, effectively corrects for spatial autocorrelation in the data. It also effectively corrects for the presence of deterministic structures, with or without spatial autocorrelation.
The presence of a broad‐scale deterministic structure may, in some cases, reduce the power of the modified t‐test.     

What explains patterns of species richness? The relative importance of climatic‐niche evolution,morphological evolution,and ecological limits in salamanders

A major goal of evolutionary biology and ecology is to understand why species richness varies among clades. Previous studies have suggested that variation in richness among clades might be related to variation in rates of morphological evolution among clades (e.g., body size and shape). Other studies have suggested that richness patterns might be related to variation in rates of climatic‐niche evolution. However, few studies, if any, have tested the relative importance of these variables in explaining patterns of richness among clades. Here, we test their relative importance among major clades of Plethodontidae, the most species‐rich family of salamanders. Earlier studies have suggested that climatic‐niche evolution explains patterns of diversification among plethodontid clades, whereas rates of morphological evolution do not. A subsequent study stated that rates of morphological evolution instead explained patterns of species richness among plethodontid clades (along with “ecological limits” on richness of clades, leading to saturation of clades with species, given limited resources). However, they did not consider climatic‐niche evolution. Using phylogenetic multiple regression, we show that rates of climatic‐niche evolution explain most variation in richness among plethodontid clades, whereas rates of morphological evolution do not. We find little evidence that ecological limits explain patterns of richness among plethodontid clades. We also test whether rates of morphological and climatic‐niche evolution are correlated, and find that they are not. Overall, our results help explain richness patterns in a major amphibian group and provide possibly the first test of the relative importance of climatic niches and morphological evolution in explaining diversity patterns.     

Empirical evaluation of observation scale effects in community time series

Natural communities are highly complex and dynamic over time, with populations structured by numerous abiotic and biotic forces acting through direct and indirect pathways. Multispecies Autoregressive (MAR) modeling can be used to partition effects of variables that are interrelated and temporally autocorrelated in time series from natural systems. Here we address two main questions in applying MAR models to community time series. First, what is the effect of observation scale on interpretation of community dynamics? We used a 10‐year weekly planktonic time series from Lake Washington to construct multiple “biweekly” and “monthly” data sets, and compared resulting community interaction models. Direct abiotic effects and intraspecific autocorrelation were apparent using all data sets. Biotic interactions were more apparent using biweekly and monthly data, indicating that time lags longer than one week were necessary to detect numerical response to interspecific interactions. Second, we examined effects of dropping the winter months from our analyses to simulate the common practice of sampling only during the “growing season” in long‐term ecological studies. We found that biotic interactions remained similarly characterized in models using only non‐winter months, but that the importance of seasonal physical factors nearly disappeared in non‐winter models. Exclusion of winter data in sampling designs may therefore allow us to characterize biotic interactions, although it may not help us understand populations’ relationships to seasonal abiotic variables. The models supported many previous findings from experimental and qualitative investigations of Lake Washington community interactions, implying that MARs provided plausible characterizations of community dynamics, but some previously unconsidered relationships did emerge, such as the importance of cryptomonads and picoplankton for zooplankton growth. We conclude that explicit consideration of time lags in biotic response is necessary to understand relative importance of abiotic and biotic factors, and that sampling regime can therefore strongly influence our interpretations of community dynamics.     

Elevational patterns and hierarchical determinants of biodiversity across microbial taxonomic scales

Microbial biogeography is gaining increasing attention due to recent molecular methodological advance. However, the diversity patterns and their environmental determinants across taxonomic scales are still poorly studied. By sampling along an extensive elevational gradient in subarctic ponds of Finland and Norway, we examined the diversity patterns of aquatic bacteria and fungi from whole community to individual taxa across taxonomic coverage and taxonomic resolutions. We further quantified cross‐phylum congruence in multiple biodiversity metrics and evaluated the relative importance of climate, catchment and local pond variables as the hierarchical drivers of biodiversity across taxonomic scales. Bacterial community showed significantly decreasing elevational patterns in species richness and evenness, and U‐shaped patterns in local contribution to beta diversity (LCBD). Conversely, no significant species richness and evenness patterns were found for fungal community. Elevational patterns in species richness and LCBD, but not in evenness, were congruent across bacterial phyla. When narrowing down the taxonomic scope towards higher resolutions, bacterial diversity showed weaker and more complex elevational patterns. Taxonomic downscaling also indicated a notable change in the relative importance of biodiversity determinants with stronger local environmental filtering, but decreased importance of climatic variables. This suggested that niche conservatism of temperature preference was phylogenetically deeper than that of water chemistry variables. Our results provide novel perspectives for microbial biogeography and highlight the importance of taxonomic scale dependency and hierarchical drivers when modelling biodiversity and species distribution responses to future climatic scenarios.     

Tempo and mode of climatic niche evolution in Primates

Climatic niches have increasingly become a nexus in our understanding of a variety of ecological and evolutionary phenomena, from species distributions to latitudinal diversity gradients. Despite the increasing availability of comprehensive datasets on species ranges, phylogenetic histories, and georeferenced environmental conditions, studies on the evolution of climate niches have only begun to understand how niches evolve over evolutionary timescales. Here, using primates as a model system, we integrate recently developed phylogenetic comparative methods, species distribution patterns, and climatic data to explore primate climatic niche evolution, both among clades and over time. In general, we found that simple, constant‐rate models provide a poor representation of how climatic niches evolve. For instance, there have been shifts in the rate of climatic niche evolution in several independent clades, particularly in response to the increasingly cooler climates of the past 10 My. Interestingly, rate accelerations greatly outnumbered rate decelerations. These results highlight the importance of considering more realistic evolutionary models that allow for the detection of heterogeneity in the tempo and mode of climatic niche evolution, as well as to infer possible constraining factors for species distributions in geographical space.     

Estimating species – area relationships by modeling abundance and frequency subject to incomplete sampling

Models and data used to describe species–area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species–area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species‐level Poisson processes and estimate patch‐level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early‐successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species–area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density–area relationships and occurrence probability–area relationships can alter the form of species–area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.     

Spatial autocorrelation of assemblages of benthic invertebrates and its relationship to environmental factors in two upland rivers in southeastern Australia

The nature of spatial autocorrelation of biota may reveal much about underlying ecological and biological factors responsible for producing those patterns, especially dispersal processes (drift, adult flight, etc.). We report here on assemblage‐level autocorrelation in the benthic‐invertebrate assemblages (retained in sieves of 300 µm mesh) of riffles in two adjacent, relatively pristine rivers in southeastern Victoria, Australia (40‐km reaches of the Wellington and Wonnangatta Rivers). These are related to patterns of autocorrelation in physical and catchment conditions (‘environmental variables’) in the vicinity of the sampling points. Both the invertebrate assemblages and environmental variables were autocorrelated at small scales (= 8 km) in the Wellington River in one of the sampling years (1996). Dissimilarities of invertebrate assemblages were correlated with dissimilarities of environmental variables in both sampling years (1996 and 1997) in that river. Environmental variables were autocorrelated in the Wonnangatta River, but this was not expressed as autocorrelation in the assemblages of invertebrates, which were not autocorrelated at any scale studied. Individual environmental variables showed different spatial patterns between the two rivers. These results suggest that individual rivers have their own idiosyncratic patterns and one cannot assume that even similar, geographically adjacent rivers will have the same patterns, which is a difficulty for ecological assessment and restoration.     

Distribution and diversity of palms in a tropical biodiversity hotspot (Thailand) assessed by species distribution modeling

Species distribution modeling has been widely used to address questions related to ecology, biogeography and species conservation on global and regional scales. Here, we study palms (Arecaceae) in a tropical biodiversity hotspot (Thailand) using species distribution modeling to assess range‐limiting factors and estimate distribution and diversity patterns based on a comprehensive compilation of occurrence records. We focused on palms as a model group due to their key‐stone importance for ecosystem functioning and socio‐economics. Different combinations of climatic, non‐climatic environmental and spatial predictors were used. The most accurate models as indicated by the ‘area under the receiver operating characteristic curve’ (AUC) statistic were those that combined all predictors. The four strongest single predictors of palm species distributions were, in decreasing order of importance, 1) latitude, 2) precipitation of driest quarter, 3) annual precipitation, and 4) minimum temperature of the coldest month, suggesting rainfall patterns and latitudinal spatial constraints as the main range determinants. Overlaying the predicted distributions revealed that potential palm hotspots are situated in the provinces of Satun and Yala in southern Thailand where vast areas remain relatively open to the discovery of new palm records and perhaps even new species.     

Creating multithemed ecological regions for macroscale ecology: Testing a flexible,repeatable, and accessible clustering method

Understanding broad‐scale ecological patterns and processes often involves accounting for regional‐scale heterogeneity. A common way to do so is to include ecological regions in sampling schemes and empirical models. However, most existing ecological regions were developed for specific purposes, using a limited set of geospatial features and irreproducible methods. Our study purpose was to: (1) describe a method that takes advantage of recent computational advances and increased availability of regional and global data sets to create customizable and reproducible ecological regions, (2) make this algorithm available for use and modification by others studying different ecosystems, variables of interest, study extents, and macroscale ecology research questions, and (3) demonstrate the power of this approach for the research question—How well do these regions capture regional‐scale variation in lake water quality? To achieve our purpose we: (1) used a spatially constrained spectral clustering algorithm that balances geospatial homogeneity and region contiguity to create ecological regions using multiple terrestrial, climatic, and freshwater geospatial data for 17 northeastern U.S. states (~1,800,000 km²); (2) identified which of the 52 geospatial features were most influential in creating the resulting 100 regions; and (3) tested the ability of these ecological regions to capture regional variation in water nutrients and clarity for ~6,000 lakes. We found that: (1) a combination of terrestrial, climatic, and freshwater geospatial features influenced region creation, suggesting that the oft‐ignored freshwater landscape provides novel information on landscape variability not captured by traditionally used climate and terrestrial metrics; and (2) the delineated regions captured macroscale heterogeneity in ecosystem properties not included in region delineation—approximately 40% of the variation in total phosphorus and water clarity among lakes was at the regional scale. Our results demonstrate the usefulness of this method for creating customizable and reproducible regions for research and management applications.     

Scale as a lurking factor: incorporating scale-dependence in experimental ecology

Ecologists have recognized for decades the importance of spatial scale in ecological processes and patterns, as well as the complications scale poses for understanding ecological mechanisms. Here we highlight the opportunity attention to scale offers experimental ecology. Despite many advantages to considering scale, a review of the literature indicates that multi-scale experimental studies are rare. Although much work has focused on scale as a primary factor (e.g. island size), we draw attention to scale as a 'lurking' variable: one which influences the relationship between two or more variables that are not usually understood to be scale-dependent.
We highlight three basic observations from which scale-dependence arises: abundance increases with area, environmental conditions vary across space, and the effect of an organism on its environment is spatially limited. From these arise first-order scale-dependence, which relates an ecological variable of interest to a measure of scale. Combining first-order relationships together, we can produce second-order scale-dependencies, which occur when the relationship between two or more variables is mediated by scale. It is these relationships that are of particular interest, as they have the potential to confound experimental results.
Most ecological experiments have incorporated scale either implicitly or not at all. We suggest that an explicit consideration of scale could help resolve some long-standing debates when scale is turned from a lurking variable into a working variable. Finally, we review and evaluate four different experimental sampling designs and corresponding statistical analyses that can be used to address the effects of scale in ecological experiments.     

Disentangling how climate change can affect an aquatic food web by combining multiple experimental approaches

Predicting the biological effects of climate change presents major challenges due to the interplay of potential biotic and abiotic mechanisms. Climate change can create unexpected outcomes by altering species interactions, and uncertainty over the ability of species to develop in situ tolerance or track environmental change further hampers meaningful predictions. As multiple climatic variables shift in concert, their potential interactions further complicate ecosystem responses. Despite awareness of these complexities, we still lack controlled experiments that manipulate multiple climatic stressors, species interactions, and prior exposure of species to future climatic conditions. Particularly studies that address how changes in water availability interact with other climatic stressors to affect aquatic ecosystems are still rare. Using aquatic insect communities of Neotropical tank bromeliads, we combined controlled manipulations of drought length and species interactions with a space‐for‐time transplant (lower elevations represent future climate) and a common garden approach. Manipulating drought length and experiment elevation revealed that adverse effects of drought were amplified at the warmer location, highlighting the potential of climatic stressors to synergistically affect communities. Manipulating the presence of omnivorous tipulid larvae showed that negative interactions from tipulids, presumably from predation, arose under drought, and were stronger at the warmer location, stressing the importance of species interactions in mediating community responses to climate change. The common garden treatments revealed that prior community exposure to potential future climatic conditions did not affect the outcome. In this powerful experiment, we demonstrated how complexities arise from the interplay of biotic and abiotic mechanisms of climate change. We stress that single species can steer ecological outcomes, and suggest that focusing on such disproportionately influential species may improve attempts at making meaningful predictions of climate change impacts on food webs.     

The importance (or lack thereof) of niche divergence to the maintenance of a northern species complex: the case of the long‐toed salamander (Ambystoma macrodactylum Baird)

The relative importance of ecological vs. nonecological factors for the origin and maintenance of species is an open question in evolutionary biology. Young lineages – such as the distinct genetic groups that make up the ranges of many northern species – represent an opportunity to study the importance of ecological divergence during the early stages of diversification. Yet, few studies have examined the extent of niche divergence between lineages in previously glaciated regions and the role of ecology in maintaining the contact zones between them. In this study, we used tests of niche overlap in combination with ecological niche models to explore the extent of niche divergence between lineages of the long‐toed salamander (Ambystoma macrodactylum Baird) species complex and to determine whether contact zones correspond to (divergent) niche limits. We found limited evidence for niche divergence between the different long‐toed salamander lineages, substantial overlap in the predicted distribution of suitable climatic space for all lineages and range limits that are independent of niche limits. These results raise questions as to the importance of ecological divergence to the development of this widespread species complex and highlight the potential for non‐ecological factors to play a more important role in the maintenance of northern taxa.     

Relating Climatic Dynamics in Time and Space to Ecological Responses,with Application to Australian Waterbirds

Many animals move in response to climatic variations, with responses of highly mobile species such as waterbirds being especially dynamic. Climatic patterns are commonly quantified through static aggregation of meteorological variables, yet static analyses may only poorly relate to dynamic ecological responses. A technique is developed here to examine relationships between ecological responses and climatic dynamics through quantifying the dynamic structure of large-scale weather systems as they propagate through time and space. Analyses of localized climatic dynamics permit insight into the dependence of ecosystem responses not just upon spatial and temporal scales, but also upon frequencies and prevailing directions, of climatic variation. The technique is applied to the single variable of the aggregate abundance of all species of waterbirds counted in the annual Eastern Australian Aerial Waterbird Survey. The strongest climatic influence on avian abundance is shown to be the coherence of large-scale precipitation systems with spectral frequencies of around 15 days that propagate south-east into the interior of the continent from the tropical north. Directly aggregated rainfall presents a secondary influence. These comprehensively integrative analyses of localized weather are ultimately able to explain over 75% of the inter-annual variance in the aggregate abundance of over 90 species of waterbirds. These results provide a powerful demonstration of the techniques developed here, and reveal the profound extent to which environmental variability structures Australian ecosystems.     

Species co-occurrence: the case of congeneric species and a causal approach to patterns of species association

Aim To test whether congeneric species are significantly associated with one another in space, either positively or negatively. Also, to provide a framework for a causal investigation of co‐occurrence patterns by a parallel comparison of interactions in geographical and ecological data matrices. Location For the analysis of congeneric species’ co‐occurrences we used 30 matrices covering a wide range of taxa and geographical areas, while for the causal investigation we used the distribution of 50 terrestrial isopod species on 20 islands and 264 sampling stations in the central Aegean archipelago, as well as a number of ecological variables for each sampling station. Methods We developed a software program (cooc ) that incorporates the species‐by‐species approach to co‐occurrence analysis using EcoSim's output of prior null model analysis of co‐occurrence. We describe this program in detail, and use it to investigate one of the most common assembly rules, namely, the decreased levels of co‐occurrence among congeneric species pairs. For the causal analysis, we proceed likewise, cross‐checking the results from the geographical and the ecological matrices. There is only one possible combination of results that can support claims for direct competition among species. Results We do not get any strong evidence for widespread competition among congeneric species, while most communities investigated do not show significant patterns of species associations. The causal analysis suggests that the principal factors behind terrestrial isopod species associations are of historical nature. Some exceptional cases are also discussed. Main conclusions Presence/absence data for a variety of taxa do not support the assembly rule that congeneric species are under more intense competition compared to less related species. Also, these same data do not suggest strong interactions among species pairs, regardless of taxonomic status. When significant species associations can be seen in such matrices, they mainly reflect the effects of history or of habitat requirements.     

Forecasting range shifts of a cold‐adapted species under climate change: are genomic and ecological diversity within species crucial for future resilience?

Cold‐adapted taxa are experiencing severe range shifts due to climate change and are expected to suffer a significant reduction of their climatically suitable habitats in the next few decades. However, it has been proposed that taxa with sufficient standing genetic and ecologic diversity will better withstand climate change. These taxa are typically more broadly distributed in geographic and ecological niche space, therefore they are likely to endure higher levels of populations loss than more restricted, less diverse taxa before the effects of those losses impact their overall diversity and resilience. Here, we explore the potential relationship between intraspecific genetic and ecological diversity and future resilience, using the cold‐adapted plant Primula farinosa. We employ high‐throughput sequencing to assess the genomic diversity of phylogeographic lineages in P. farinosa. Additionally, we use current climatic variables to define niche breadth and niche differentiation across lineages. Finally, we calibrate species distribution models (SDMs) and project the climatic preferences of each lineage on future climate to predict lineage‐specific shifts in climatically suitable habitats. Our study predicts relative persistence of future suitable habitats for the most genetically and ecologically diverse lineages of the cold‐adapted P. farinosa, but significant reduction of them for two out of its four lineages. While we do not provide specific experiments aimed at identifying the causal links between genetic diversity and resilience to climate change, our results indicate that greater genetic diversity and wider ecological breadth may buffer species responses to rapid climatic changes. This study further highlights the importance of integrating knowledge of intraspecific diversity for predicting species fate in response to climate change.     

Multilocus phylogenetic and geospatial analyses illuminate diversification patterns and the biogeographic history of Malagasy endemic plated lizards (Gerrhosauridae: Zonosaurinae)

Although numerous studies have attempted to find single unifying mechanisms for generating Madagascar's unique flora and fauna, little consensus has been reached regarding the relative importance of climatic, geologic and ecological processes as catalysts of diversification of the region's unique biota. Rather, recent work has shown that both biological and physical drivers of diversification are best analysed in a case‐by‐case setting with attention focused on the ecological and life‐history requirements of the specific phylogenetic lineage under investigation. Here, we utilize a comprehensive analytical approach to examine evolutionary drivers and elucidate the biogeographic history of Malagasy plated lizards (Zonosaurinae). Data from three genes are combined with fossil information to construct time‐calibrated species trees for zonosaurines and their African relatives, which are used to test alternative diversification hypotheses. Methods are utilized for explicitly incorporating phylogenetic uncertainty into downstream analyses. Species distribution models are created for 14 of 19 currently recognized species, which are then used to estimate spatial patterns of species richness and endemicity. Spatially explicit analyses are employed to correlate patterns of diversity with both topographic heterogeneity and climatic stability through geologic time. We then use inferred geographic ranges to estimate the biogeographic history of zonosaurines within each of Madagascar's major biomes. Results suggest constant Neogene and Quaternary speciation with divergence from the African most recent common ancestor ~30 million years ago when oceanic currents and African rivers facilitated dispersal. Spatial patterns of diversity appear concentrated along coastal regions of northern and southern Madagascar. We find no relationship between either topographic heterogeneity or climatic stability and patterns of diversity. Ancestral state reconstructions suggest that western dry forests were important centres of origin with recent invasion into spiny and rain forest. These data highlight the power of combining multilocus phylogenetic and spatially explicit analyses for testing alternative diversification hypotheses within Madagascar's unique biota and more generally, particularly as applied to phylogenetically and biologically constrained systems.     

Are we selecting appropriate metrics to assess human impacts on biodiversity?

Biased and subjective choices of metrics to be used in ecological studies could lead researchers to reach misleading conclusions regarding patterns of biodiversity response to human disturbances. Nevertheless, little attention has been given to the choices of variables in the majority of studies published to date. Here, we used the literature concerning land use change effects on dung beetles to assess the extent to which variables commonly employed in ecological studies correspond to those deemed to be most important by researchers of the same studies. Specifically, we examined both biodiversity (response) and environmental (explanatory) metrics from a comprehensive literature review and compared their use with their relative importance, according to a survey of the authors of the studies. Our results highlight marked disparities between researchers opinion expressed in our survey and their choice of variables in published papers. We suggest that these disparities are due to the high costs of sampling and processing some variables, logistical constraints and different perceptions of importance amongst researchers. We highlight the importance of these issues for our understanding of the biodiversity consequences of land use change, and highlight some recommendations for alleviating this issue.     

Geographic variation in network structure of a nearctic aquatic food web

Aim The network structure of food webs plays an important role in the maintenance of diversity and ecosystem functioning in ecological communities. Previous research has found that ecosystem size, resource availability, assembly history and biotic interactions can potentially drive food web structure. However, the relative influence of climatic variables that drive broad‐scale biogeographic patterns of species richness and composition has not been explored for food web structure. In this study, we assess the influence of broad‐scale climatic variables in addition to known drivers of food web structure on replicate observations of a single aquatic food web, sampled from the leaves of the pitcher plant (Sarracenia purpurea), at different geographic sites across a broad latitudinal and climatic range. Location Using standardized sampling methods, we conducted an extensive ‘snapshot’ survey of 780 replicated aquatic food webs collected from the leaves of the pitcher plant S. purpurea at 39 sites from northern Florida to Newfoundland and westward to eastern British Columbia. Methods We examined correlations of 15 measures of food web structure at the pitcher and site scales with geographic variation in temperature and precipitation, concentrations of nutrients from atmospheric nitrogen deposition, resource availability, ecosystem size and the abundance of the pitcher plant mosquito (Wyeomyia smithii), a potential keystone species. Results At the scale of a single pitcher plant leaf, linkage density, species richness, measures of chain length and the proportion of omnivores in a web all increased with pitcher volume. Linkage density and species richness were greater at high‐latitude sites, which experience low mean temperatures and precipitation and high annual variation in both of these variables. At the site scale, variation in 8 of the 15 food web metrics decreased at higher latitudes, and variation in measures of chain length increased with the abundance of mosquitoes. Main conclusions Ecosystem size and climatic variables related to latitude were most strongly correlated with network structure of the Sarracenia food web. However, in spite of large sample sizes, thorough standardized sampling and the large geographic extent of the survey, even the best‐fitting models explained less than 40% of the variation in food web structure. In contrast to biogeographic patterns of species richness, food web structure was largely independent of broad‐scale climatic variables. The large proportion of unexplained variance in our analyses suggests that stochastic assembly may be an important determinant of local food web structure.     

Measures of precision for dissimilarity‐based multivariate analysis of ecological communities

Ecological studies require key decisions regarding the appropriate size and number of sampling units. No methods currently exist to measure precision for multivariate assemblage data when dissimilarity‐based analyses are intended to follow. Here, we propose a pseudo multivariate dissimilarity‐based standard error (MultSE) as a useful quantity for assessing sample‐size adequacy in studies of ecological communities. Based on sums of squared dissimilarities, MultSE measures variability in the position of the centroid in the space of a chosen dissimilarity measure under repeated sampling for a given sample size. We describe a novel double resampling method to quantify uncertainty in MultSE values with increasing sample size. For more complex designs, values of MultSE can be calculated from the pseudo residual mean square of a permanova model, with the double resampling done within appropriate cells in the design. R code functions for implementing these techniques, along with ecological examples, are provided.