Changes in Patterns of Species Co‐occurrence across Two Tropical Cloud Forests Differing in Soil Nutrients and Air Temperature

Patterns of co‐occurrence of species are increasingly used to examine the contribution of biotic interactions to community assembly. We assessed patterns of co‐occurrence at four scales, in two types of tropical cloud forests in Hainan Island, China (tropical montane evergreen forests, TMEF and tropical dwarf forests, TDF) that varied significantly in soil nutrients and temperature. We tested if the patterns of co‐occurrence changed when we sorted species into classes by abundance and diameter at breast height (dbh). Co‐occurrence differed by forest type and with plot size, with significant species aggregation observed across larger plots in TDF and patterns of species segregation observed in smaller plots in TMEF. Analyses of differential abundance and dbh classes also showed that smaller plots in TMEF tend to have negative co‐occurrence patterns, but larger plots in TDF tend to show patterns of aggregation, suggesting competitive and facilitative interactions. This underscores the scale‐dependence of the processes contributing to community assembly. Furthermore, it is consistent with predictions of the stress gradient hypothesis that facilitation will be most important in biological systems subject to abiotic stress, while competition will be more important in less abiotically stressful habitats. Our results clearly demonstrate that these two types of tropical cloud forest exhibit different co‐occurrence patterns, and that these patterns are scale‐dependent, though independent of plant abundance and size class.     

Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking modelling approaches

Aim This study compares the direct, macroecological approach (MEM) for modelling species richness (SR) with the more recent approach of stacking predictions from individual species distributions (S‐SDM). We implemented both approaches on the same dataset and discuss their respective theoretical assumptions, strengths and drawbacks. We also tested how both approaches performed in reproducing observed patterns of SR along an elevational gradient. Location Two study areas in the Alps of Switzerland. Methods We implemented MEM by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S‐SDM was implemented by modelling each species distribution individually and then stacking the obtained prediction maps in three different ways – summing binary predictions, summing random draws of binomial trials and summing predicted probabilities – to obtain a final species count. Results The direct MEM approach yields nearly unbiased predictions centred around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by the S‐SDM approaches. This method also cannot provide any information on species identity and, thus, community composition. It does, however, accurately reproduce the hump‐shaped pattern of SR observed along the elevational gradient. The S‐SDM approach summing binary maps can predict individual species and thus communities, but tends to overpredict SR. The two other S‐SDM approaches – the summed binomial trials based on predicted probabilities and summed predicted probabilities – do not overpredict richness, but they predict many competing end points of assembly or they lose the individual species predictions, respectively. Furthermore, all S‐SDM approaches fail to appropriately reproduce the observed hump‐shaped patterns of SR along the elevational gradient. Main conclusions Macroecological approach and S‐SDM have complementary strengths. We suggest that both could be used in combination to obtain better SR predictions by following the suggestion of constraining S‐SDM by MEM predictions.     

From species distributions to meta‐communities

The extent that biotic interactions and dispersal influence species ranges and diversity patterns across scales remains an open question. Answering this question requires framing an analysis on the frontier between species distribution modelling (SDM), which ignores biotic interactions and dispersal limitation, and community ecology, which provides specific predictions on community and meta‐community structure and resulting diversity patterns such as species richness and functional diversity. Using both empirical and simulated datasets, we tested whether predicted occurrences from fine‐resolution SDMs provide good estimates of community structure and diversity patterns at resolutions ranging from a resolution typical of studies within reserves (250 m) to that typical of a regional biodiversity study (5 km). For both datasets, we show that the imprint of biotic interactions and dispersal limitation quickly vanishes when spatial resolution is reduced, which demonstrates the value of SDMs for tracking the imprint of community assembly processes across scales.     

Reconciling empirical interactions and species coexistence

Coexistence in ecological communities is governed largely by the nature and intensity of species interactions. Countless studies have proposed methods to infer these interactions from empirical data, yet models parameterised using such data often fail to recover observed coexistence patterns. Here, we propose a method to reconcile empirical parameterisations of community dynamics with species‐abundance data, ensuring that the predicted equilibrium is consistent with the observed abundance distribution. To illustrate the approach, we explore two case studies: an experimental freshwater algal community and a long‐term time series of displacement in an intertidal community. We demonstrate how our method helps recover observed coexistence patterns, capture the core dynamics of the system, and, in the latter case, predict the impacts of experimental extinctions. Collectively, these results demonstrate an intuitive approach for reconciling observed and empirical data, improving our ability to explore the links between species interactions and coexistence in natural systems.     

Spatial covariance of herbivorous and predatory guilds of forest canopy arthropods along a latitudinal gradient

In arthropod community ecology, species richness studies tend to be prioritised over those investigating patterns of abundance. Consequently, the biotic and abiotic drivers of arboreal arthropod abundance are still relatively poorly known. In this cross‐continental study, we employ a theoretical framework in order to examine patterns of covariance among herbivorous and predatory arthropod guilds. Leaf‐chewing and leaf‐mining herbivores, and predatory ants and spiders, were censused on > 1000 trees in nine 0.1 ha forest plots. After controlling for tree size and season, we found no negative pairwise correlations between guild abundances per plot, suggestive of weak signals of both inter‐guild competition and top‐down regulation of herbivores by predators. Inter‐guild interaction strengths did not vary with mean annual temperature, thus opposing the hypothesis that biotic interactions intensify towards the equator. We find evidence for the bottom‐up limitation of arthropod abundances via resources and abiotic factors, rather than for competition and predation.     

Variable interaction strengths stabilize marine community pattern

High variability in the strength of species interactions is usually considered a source of unstable or unpredictable community patterns. However, recent theoretical work suggests that some types of variance in interaction strength may actually promote stability. Here we provide the first empirical evidence that highly variable, context-dependent species interaction strengths and resilient community patterns can be two sides of the same coin. Field experiments show that a persistent rocky intertidal seascape is remarkably resilient to multiple sources of environmental stochasticity largely because of scale dependent and variable species interaction strengths. Biological interactions exert a stabilizing effect because their intensity varies systematically with changes in both physical sources of mortality of established species, as well as recruitment of new individuals. Strong variation in species interaction strengths with disturbance size and environmental conditions is ubiquitous in nature. Elucidating when this context dependency will be stabilizing is critical to predict community-level responses to anthropogenic disturbances.     

Integrating macroecological metrics and community taxonomic structure

We extend macroecological theory based on the maximum entropy principle from species level to higher taxonomic categories, thereby predicting distributions of species richness across genera or families and the dependence of abundance and metabolic rate distributions on taxonomic tree structure. Predictions agree with qualitative trends reported in studies on hyper‐dominance in tropical tree species, mammalian body size distributions and patterns of rarity in worldwide plant communities. Predicted distributions of species richness over genera or families for birds, arthropods, plants and microorganisms are in excellent agreement with data. Data from an intertidal invertebrate community, but not from a dispersal‐limited forest, are in excellent agreement with a predicted new relationship between body size and abundance. Successful predictions of the original species level theory are unmodified in the extended theory. By integrating macroecology and taxonomic tree structure, maximum entropy may point the way towards a unified framework for understanding phylogenetic community structure.     

Are stacked species distribution models accurate at predicting multiple levels of diversity along a rainfall gradient?

We use observed patterns of species richness and composition of ant communities along a 1000 mm rainfall gradient in northern Australian savanna to assess the accuracy of species richness and turnover predictions derived from stacked species distribution models (S‐SDMs) and constrained by macroecological models (MEMs). We systematically sampled ants at 15 sites at 50 km intervals along the rainfall gradient in 2012 and 2013. Using the observed data, we created MEMs of species richness, composition and turnover. We built distribution models for 135 of the observed species using data from museum collections and online databases. We compared two approaches of stacking SDMs and three modelling algorithms to identify the most accurate way of predicting richness and composition. We then applied the same beta diversity metrics to compare the observed versus predicted patterns. Stacked SDMs consistently over‐predicted local species richness, and there was a mismatch between the observed pattern of richness estimated from the MEM, and the pattern predicted by S‐SDMs. The most accurate richness and turnover predictions occurred when the stacked models were rank‐ordered by their habitat suitability and constrained by the observed MEM richness predictions. In contrast with species richness, the predictions obtained by the MEM of community similarity, composition and turnover matched those predicted by the S‐SDMs. S‐SDMs regulated by MEMs may therefore be a useful tool in predicting compositional patterns despite being unreliable estimators of species richness. Our results highlight that the choice of species distribution model, the stacking method used, and underlying macroecological patterns all influence the accuracy of community assembly predictions derived from S‐SDMS.     

Spatial predictions at the community level: from current approaches to future frameworks

A fundamental goal of ecological research is to understand and model how processes generate patterns so that if conditions change, changes in the patterns can be predicted. Different approaches have been proposed for modelling species assemblage, but their use to predict spatial patterns of species richness and other community attributes over a range of spatial and temporal scales remains challenging. Different methods emphasize different processes of structuring communities and different goals. In this review, we focus on models that were developed for generating spatially explicit predictions of communities, with a particular focus on species richness, composition, relative abundance and related attributes. We first briefly describe the concepts and theories that span the different drivers of species assembly. A combination of abiotic processes and biotic mechanisms are thought to influence the community assembly process. In this review, we describe four categories of drivers: (i) historical and evolutionary, (ii) environmental, (iii) biotic, and (iv) stochastic. We discuss the different modelling approaches proposed or applied at the community level and examine them from different standpoints, i.e. the theoretical bases, the drivers included, the source data, and the expected outputs, with special emphasis on conservation needs under climate change. We also highlight the most promising novelties, possible shortcomings, and potential extensions of existing methods. Finally, we present new approaches to model and predict species assemblages by reviewing promising ‘integrative frameworks’ and views that seek to incorporate all drivers of community assembly into a unique modelling workflow. We discuss the strengths and weaknesses of these new solutions and how they may hasten progress in community‐level modelling.     

Interaction network of vascular epiphytes and trees in a subtropical forest

The commensalistic interaction between vascular epiphytes and host trees is a type of biotic interaction that has been recently analysed with a network approach. This approach is useful to describe the network structure with metrics such as nestedness, specialization and interaction evenness, which can be compared with other vascular epiphyte-host tree networks from different forests of the world. However, in several cases these comparisons showed different and inconsistent patterns between these networks, and their possible ecological and evolutionary determinants have been scarcely studied. In this study, the interactions between vascular epiphytes and host trees of a subtropical forest of sierra de San Javier (Tucuman, Argentina) were analysed with a network approach. We calculated metrics to characterize the network and we analysed factors such as the abundance of species, tree size, tree bark texture, and tree wood density in order to predict interaction frequencies and network structure. The interaction network analysed exhibited a nested structure, an even distribution of interactions, and low specialization, properties shared with other obligated vascular epiphyte-host tree networks with a different assemblage structure. Interaction frequencies were predicted by the abundance of species, tree size and tree bark texture. Species abundance and tree size also predicted nestedness. Abundance indicated that abundant species interact more frequently; and tree size was an important predictor, since larger-diameter trees hosted more vascular epiphyte species than small-diameter trees. This is one of the first studies analyzing interactions between vascular epiphytes and host trees using a network approach in a subtropical forest, and taking the whole vascular epiphyte assemblage of the sampled community into account.     

Anthropogenic modification disrupts species co‐occurrence in stream invertebrates

The question of whether species co‐occurrence is random or deterministic has received considerable attention, but little is known about how anthropogenic disturbance mediates the outcomes. By combining experiments, field surveys and analysis against null models, we tested the hypothesis that anthropogenic habitat modification disrupts species co‐occurrence in stream invertebrates across spatial scales. Whereas communities in unmodified conditions were structured deterministically with significant species segregation, catchment‐scale conversion to agriculture and sediment deposition at the patch‐ or micro‐habitat scale apparently randomized species co‐occurrences. This shift from non‐random to random was mostly independent of species richness, abundance and spatial scale. Data on community‐wide life‐history traits (body size, dispersal ability and predatory habits) and beta‐diversity indicated that anthropogenic modification disrupted community assembly by affecting biotic interactions and, to a lesser extent, altering habitat heterogeneity. These data illustrate that the balance between predictable and stochastic patterns in communities can reflect anthropogenic modifications that not only transcend scales but also change the relative forces that determine species coexistence. Research into the effects of habitat modification as a key to understanding global change should extend beyond species richness and composition to include species co‐occurrence, species interactions and any functional consequences.     

On testing predictions of species relative abundance from maximum entropy optimisation

A randomisation test is described for assessing relative abundance predictions from the maximum entropy approach to biodiversity. The null model underlying the test randomly allocates observed abundances to species, but retains key aspects of the structure of the observed communities; site richness, species composition, and trait covariance. Three test statistics are used to explore different characteristics of the predictions. Two are based on pairwise comparisons between observed and predicted species abundances (RMSE, RMSE_Sqrt). The third statistic is novel and is based on community‐level abundance patterns, using an index calculated from the observed and predicted community entropies (E_Diff). Validation of the test to quantify type I and type II error rates showed no evidence of bias or circularity, confirming the dependencies quantified by Roxburgh and Mokany (2007) and Shipley (2007) have been fully accounted for within the null model. Application of the test to the vineyard data of Shipley et al. (2006) and to an Australian grassland dataset indicated significant departures from the null model, suggesting the integration of species trait information within the maximum entropy framework can successfully predict species abundance patterns. The paper concludes with some general comments on the use of maximum entropy in ecology, including a discussion of the mathematics underlying the Maxent optimisation algorithm and its implementation, the role of absent species in generating biased predictions, and some comments on determining the most appropriate level of data aggregation for Maxent analysis.     

Extinction cascades and the distribution of species interactions

The distribution of interaction strengths among community members has important consequences for assembly processes and community responses to perturbations. Species deletion from communities can trigger cascading extinction events, with strong evidence from empirical and theoretical work. I examined model competitive communities, sequentially assembled using species drawn from a global pool with interaction strengths described by different distribution shapes (uniform or beta), with the same mean and variance. As community size increased, it became harder to assemble communities drawn from a uniform distribution compared to a beta distribution. The distribution of interaction values in the assembled communities differed from the shape of the initial distribution. The distribution shape and the relative abundance of the deleted species also had strong impacts on the probability of extinction cascades following primary species removal. Extinction cascades occurred in communities with a higher mean and variance of interaction strengths before the primary extinction. Those species lost had negative equilibrium densities and tended to be the least abundant, when assessed following the reorganisation that occurred after the primary and subsequent extinctions. Knowledge of the shape of the distribution of interaction strengths from real communities will allow us to make better predictions about which species are most at risk in extinction cascades under natural circumstances.     

Predator diversity and environmental change modify the strengths of trophic and nontrophic interactions

Understanding the dependence of species interaction strengths on environmental factors and species diversity is crucial to predict community dynamics and persistence in a rapidly changing world. Nontrophic (e.g. predator interference) and trophic components together determine species interaction strengths, but the effects of environmental factors on these two components remain largely unknown. This impedes our ability to fully understand the links between environmental drivers and species interactions. Here, we used a dynamical modelling framework based on measured predator functional responses to investigate the effects of predator diversity, prey density, and temperature on trophic and nontrophic interaction strengths within a freshwater food web. We found that (i) species interaction strengths cannot be predicted from trophic interactions alone, (ii) nontrophic interaction strengths vary strongly among predator assemblages, (iii) temperature has opposite effects on trophic and nontrophic interaction strengths, and (iv) trophic interaction strengths decrease with prey density, whereas the dependence of nontrophic interaction strengths on prey density is concave up. Interestingly, the qualitative impacts of temperature and prey density on the strengths of trophic and nontrophic interactions were independent of predator identity, suggesting a general pattern. Our results indicate that taking multiple environmental factors and the nonlinearity of density‐dependent species interactions into account is an important step towards a better understanding of the effects of environmental variations on complex ecological communities. The functional response approach used in this study opens new avenues for (i) the quantification of the relative importance of the trophic and nontrophic components in species interactions and (ii) a better understanding how environmental factors affect these interactions and the dynamics of ecological communities.     

Effects of Seasonality and Dispersal on the Ciliate Community Inhabiting Bromeliad Phytotelmata in Riparian Vegetation of a Large Tropical River

This study evaluated the influence of rainfall amount on the abundance, species richness, and species occurrence and abundance distribution of the ciliate community associated with the bromeliad Aechmea distichantha. The plants were collected from a rock wall of about 10‐km long at the left bank of Paraná River. We assessed the effects of both spatial and temporal variables on the community attributes, as well as whether plants geographically closer have a similar abundance distribution and species composition. The ciliate community was substantially distinct between both hydrological periods, with greater values of species richness and abundance in the rainy period. No spatial structuring (differences in the species occurrence and abundance distribution among strata) or geographical similarity (similarity in ciliate species composition among the plants) was found. Multiple regression analysis showed a positive relationship only between the ciliate abundances and water volumes for both periods. Although few of the formulated predictions were confirmed, our study provides valuable information on the ecological aspects of the ciliate community inhabiting bromeliad phytotelmata.     

Landscape‐scale determinants of non‐native fish communities

Aim Predicting and preventing invasions depends on knowledge of the factors that make ecosystems susceptible to invasion. Current studies generally rely on non‐native species richness (NNSR) as the sole measure of ecosystem invasibility; however, species identity is a critical consideration, given that different ecosystems may have environmental characteristics suitable to different species. Our aim was to examine whether non‐native freshwater fish community composition was related to ecosystem characteristics at the landscape scale. Location United States. Methods We described spatial patterns in non‐native freshwater fish communities among watersheds in the Mid‐Atlantic region of the United States based on records of establishment in the U.S. Geological Survey’s Nonindigenous Aquatic Species Database. We described general relationships between non‐native species and ecosystem characteristics using canonical correspondence analysis. We clustered watersheds by non‐native fish community and described differences among clusters using indicator species analysis. We then assessed whether non‐native communities could be predicted from ecosystem characteristics using random forest analysis and predicted non‐native communities for uninvaded watersheds. We estimated which ecosystem characteristics were most important for predicting non‐native communities using conditional inference trees. Results We identified four non‐native fish communities, each with distinct indicator species. Non‐native communities were predicted based on ecosystem characteristics with an accuracy of 80.6%, with temperature as the most important variable. Relatively uninvaded watersheds were predicted to be invasible by the most diverse non‐native community. Main conclusions Non‐native species identity is an important consideration when assessing ecosystem invasibility. NNSR alone is an insufficient measure of invasibility because ecosystems with equal NNSR may not be equally invasible by the same species. Our findings can help improve predictions of future invasions and focus management and policy decisions on particular species in highly invasible ecosystems.     

Neutral processes and species sorting in benthic microalgal community assembly: effects of tidal resuspension

Benthic microalgae (BMA) provide vital food resources for heterotrophs and stabilize sediments with their extracellular secretions. A central goal in ecology is to understand how processes such as species interactions and dispersal, contribute to observed patterns of species abundance and distribution. Our objectives were to assess the effects of sediment resuspension on microalgal community structure. We tested whether taxa‐abundance distributions could be predicted using neutral community models (NCMs) and also specific hypotheses about passive migration: (i) As migration decreases in sediment patches, BMA α‐diversity will decrease, and (ii) As migration decreases, BMA community dissimilarity (β‐diversity) will increase. Co‐occurrence indices (checkerboard score and variance ratio) were also computed to test for deterministic factors, such as competition and niche differentiation, in shaping communities. Two intertidal sites (mudflat and sand bar) differing in resuspension regime were sampled throughout the tidal cycle. Fluorometry and denaturing gradient gel electrophoresis were utilized to investigate diatom community structure. Observed taxa‐abundances fit those predicted from NCMs reasonably well (R² of 0.68–0.93), although comparisons of observed local communities to artificial randomly assembled communities rejected the null hypothesis that diatom communities were assembled solely by stochastic processes. No co‐occurrence tests indicated a significant role for competitive exclusion or niche partitioning in microalgal community assembly. In general, predictions about relationships between migration and species diversity were supported for local community dynamics. BMA at low tide (lowest migration) exhibited reduced α‐diversity as compared to periods of immersion at both mudflat and sand bar sites. β‐diversity was higher during low tide emersion on the mudflat, but did not differ temporally at the sand bar site. In between‐site metacommunity comparisons, low‐ and high‐resuspension sites exhibited distinct community compositions while the low‐energy mudflats contained higher microalgal biomass and greater α‐diversity. To our knowledge this is the first study to test the relevance of neutral processes in structuring marine microalgal communities. Our results demonstrate a prominent role for stochastic factors in structuring local BMA community assembly, although unidentified nonrandom processes also appear to play some role. High passive migration, in particular, appears to help maintain species diversity and structure communities in both sand and muddy habitats.     

Seasonal strengths of the abiotic and biotic drivers of a zooplankton community

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Non-neutral community dynamics: empirical predictions for ecosystem function and diversity from linearized consumer–resource interactions

A general model of linearized species interactions, essentially Lotka–Volterra theory, applied to questions of biodiversity has previously been shown to be a powerful tool for understanding local species–abundance patterns and community responses to environmental change for a single trophic level. Here this approach is extended to predict community composition and responses to environmental changes in trophically structured systems. We show how resource and consumer species richness and their relative abundances vary with the means and variances in enrichment level and strengths of intra- and interspecific interactions. Also demonstrated are the responses of local resource and consumer species richness to the global species pools at both trophic levels, as well as the covariation with net resource productivity. These predictions for resource and consumer specific responses to changes in environmental enrichment and global biodiversity are directly testable.     

A dynamic model of facilitation on environmental stress gradients

Theories based on competition for resources in animals and other non‐sessile organisms rarely consider the role of facilitative interactions. Yet these interactions are important for community assembly, especially under stressful environments (e.g. the stress‐gradient hypothesis, SGH). To make an explicit link between species interaction theory and SGH patterns, I used a classic resource competition model promoting coexistence between a beneficiary and its facilitator sharing a common resource along a stress gradient. I compared model outcomes for two fundamentally different mechanisms of facilitation (alleviation of resource versus non‐resource stress), and also tested the effect of a reciprocal cost of facilitation from the beneficiary. I then tested model's biological relevance using experimental data from two tuber moth species (Lepidoptera, Gelechiidae) for which facilitation in resource access was previously established. Simulation outcomes revealed that both the mode of facilitation and the incorporation of facilitation costs affected the shape of the facilitation–stress relationship. These predictions are in line with current SGH observations and experiments on both plants and animals and reconcile the frequently reported variability of this relationship in nature. Moreover, a sensitivity analysis of model's parameters confirmed the robustness of the modelling framework to uncover the mechanisms responsible for observed species interaction–stress patterns. Finally, when parameterized with tuber moth demographic data, model's results corresponded to observed interaction outcomes along resource stress gradients. Overall, having a common model for plants and animals may simplify assumptions in SGH studies, allow contrasting the shapes of different consumer–resource relationships and specifying the conditions that favour one type of interaction outcome over another.