The shape of abundance distributions across temperature gradients in reef fishes

Improving predictions of ecological responses to climate change requires understanding how local abundance relates to temperature gradients, yet many factors influence local abundance in wild populations. We evaluated the shape of thermal‐abundance distributions using 98 422 abundance estimates of 702 reef fish species worldwide. We found that curved ceilings in local abundance related to sea temperatures for most species, where local abundance declined from realised thermal ‘optima’ towards warmer and cooler environments. Although generally supporting the abundant‐centre hypothesis, many species also displayed asymmetrical thermal‐abundance distributions. For many tropical species, abundances did not decline at warm distribution edges due to an unavailability of warmer environments at the equator. Habitat transitions from coral to macroalgal dominance in subtropical zones also influenced abundance distribution shapes. By quantifying the factors constraining species’ abundance, we provide an important empirical basis for improving predictions of community re‐structuring in a warmer world.     

Effects of biotic interactions on modeled species' distribution can be masked by environmental gradients

A fundamental goal of ecology is to understand the determinants of species' distributions (i.e., the set of locations where a species is present). Competition among species (i.e., interactions among species that harms each of the species involved) is common in nature and it would be tremendously useful to quantify its effects on species' distributions. An approach to studying the large‐scale effects of competition or other biotic interactions is to fit species' distributions models (SDMs) and assess the effect of competitors on the distribution and abundance of the species of interest. It is often difficult to validate the accuracy of this approach with available data. Here, we simulate virtual species that experience competition. In these simulated datasets, we can unambiguously identify the effects that competition has on a species' distribution. We then fit SDMs to the simulated datasets and test whether we can use the outputs of the SDMs to infer the true effect of competition in each simulated dataset. In our simulations, the abiotic environment influenced the effects of competition. Thus, our SDMs often inferred that the abiotic environment was a strong predictor of species abundance, even when the species' distribution was strongly affected by competition. The severity of this problem depended on whether the competitor excluded the focal species from highly suitable sites or marginally suitable sites. Our results highlight how correlations between biotic interactions and the abiotic environment make it difficult to infer the effects of competition using SDMs.     

BIODIVERSITY RESEARCH: Native‐exotic species richness relationships across spatial scales and biotic homogenization in wetland plant communities of Illinois,USA

Aim To examine native‐exotic species richness relationships across spatial scales and corresponding biotic homogenization in wetland plant communities. Location Illinois, USA. Methods We analysed the native‐exotic species richness relationship for vascular plants at three spatial scales (small, 0.25 m² of sample area; medium, 1 m² of sample area; large, 5 m² of sample area) in 103 wetlands across Illinois. At each scale, Spearman’s correlation coefficient between native and exotic richness was calculated. We also investigated the potential for biotic homogenization by comparing all species surveyed in a wetland community (from the large sample area) with the species composition in all other wetlands using paired comparisons of their Jaccard’s and Simpson’s similarity indices. Results At large and medium scales, native richness was positively correlated with exotic richness, with the strength of the correlation decreasing from the large to the medium scale; at the smallest scale, the native‐exotic richness correlation was negative. The average value for homogenization indices was 0.096 and 0.168, using Jaccard’s and Simpson’s indices, respectively, indicating that these wetland plant communities have been homogenized because of invasion by exotic species. Main Conclusions Our study demonstrated a clear shift from a positive to a negative native‐exotic species richness relationship from larger to smaller spatial scales. The negative native‐exotic richness relationship that we found is suggested to result from direct biotic interactions (competitive exclusion) between native and exotic species, whereas positive correlations likely reflect the more prominent influence of habitat heterogeneity on richness at larger scales. Our finding of homogenization at the community level extends conclusions from previous studies having found this pattern at much larger spatial scales. Furthermore, these results suggest that even while exhibiting a positive native‐exotic richness relationship, community level biotas can/are still being homogenized because of exotic species invasion.     

Strong species‐environment feedback shapes plant community assembly along environmental gradients

An aim of community ecology is to understand the patterns of competing species assembly along environmental gradients. All species interact with their environments. However, theories of community assembly have seldom taken into account the effects of species that are able to engineer the environment. In this modeling study, we integrate the species' engineering trait together with processes of immigration and local dispersal into a theory of community assembly. We quantify the species' engineering trait as the degree to which it can move the local environment away from its baseline state towards the optimum state of the species (species‐environment feedback). We find that, in the presence of immigration from a regional pool, strong feedback can increase local species richness; however, in the absence of continual immigration, species richness is a declining function of the strength of species‐environment feedback. This shift from a negative effect of engineering strength on species richness to a positive effect, as immigration rate increases, is clearer when there is spatial heterogeneity in the form of a gradient in environmental conditions than when the environment is homogeneous or it is randomly heterogeneous. Increasing the scale over which local dispersal occurs can facilitate species richness when there is no species‐environment feedback or when the feedback is weak. However, increases in the spatial scale of dispersal can reduce species richness when the species‐environment feedback is strong. These results expand the theoretical basis for understanding the effects of the strength of species‐environment feedback on community assembly.     

Density‐dependent survival varies with species life‐history strategy in a tropical forest

Species coexistence in diverse communities likely results from multiple interacting factors. Mechanisms such as conspecific negative density dependence (CNDD) and varying life‐history strategies related to resource partitioning are known to influence plant fitness, and thereby community composition and diversity. However, we have little understanding of how these mechanisms interact and how they vary across life stages. Here, we document the interaction between CNDD and life‐history strategy, based on growth‐mortality trade‐offs, from seedling to adult tree for 47 species in a tropical forest. Species’ life‐history strategies remained consistent across stages: fast‐growing species had higher mortality than slow‐growing species at all stages. In contrast, mean CNDD was strongest at early life stages (i.e. seedling, sapling). Fast‐growing species tended to suffer greater CNDD than slow‐growing species at several, but not all life stages. Overall, our results demonstrate that coexistence mechanisms interact across multiple life stages to shape diverse tree communities.     

Relationships among soil fertility,native plant diversity and exotic plant abundance inform restoration of forb‐rich eucalypt woodlands

Aim Water and nutrient availability are major limits to productivity in semi‐arid ecosystems; hence, ecological restoration often focuses on conserving or concentrating soil resources. By contrast, nutrient enrichment can promote invasion by exotic annuals, leading to restoration approaches that target reduction of soil nutrients. We aimed to explore potential biodiversity trade‐offs between these approaches by investigating relationships among soil nutrients, exotic annuals and native plant diversity and composition. In particular, we investigated the hypothesis that native plant diversity in semi‐arid to temperate woodlands reflects the productivity–diversity hypothesis, leading to hump‐backed relationships with soil nutrients such that (1) native plant diversity declines with increasing nutrient enrichment and (2) native diversity is limited at the lowest levels of soil fertility. Location Fragmented, long‐ungrazed Eucalyptus loxophleba subsp. loxophleba (York gum)–Acacia acuminata (jam) woodlands in the wheatbelt of South‐Western Australia. Methods We conducted stratified surveys of floristic composition and topsoil nutrient concentrations in 112 woodland patches. We used generalized linear models, structural equation models and ordinations to characterize relationships among soil nutrients, rainfall, exotic annuals and patch‐scale (100 m²) native plant composition and diversity. Results Patch‐scale native plant diversity declined strongly with increasing exotic abundance. This was partly related to elevated soil nutrient concentrations, particularly total nitrogen and available phosphorus. By contrast, there was little evidence for positive correlations between soil nutrients and native diversity, even at very low soil nutrient concentrations. Main conclusions Minimizing weed invasions is crucial for maximizing native plant diversity in E. loxophleba woodlands and could include nutrient‐depleting treatments without substantially compromising the functional capacity of soils to maintain native plant richness and composition. More broadly we emphasize that understanding relationships among ecosystem productivity, plant diversity and exotic invasions in the context of associated theoretical frameworks is fundamental for informing ecological restoration.     

Environmental niche conservatism explains the accumulation of species richness in Mediterranean‐hotspot plant genera

The causes of exceptionally high plant diversity in Mediterranean‐climate biodiversity hotspots are not fully understood. We asked whether a mechanism similar to the tropical niche conservatism hypothesis could explain the diversity of four large genera (Protea, Moraea, Banksia, and Hakea) with distributions within and adjacent to the Greater Cape Floristic Region (South Africa) or the Southwest Floristic Region (Australia). Using phylogenetic and spatial data we estimated the environmental niche of each species, and reconstructed the mode and dynamics of niche evolution, and the geographic history, of each genus. For three genera, there were strong positive relationships between the diversity of clades within a region and their inferred length of occupation of that region. Within genera, there was evidence for strong evolutionary constraint on niche axes associated with climatic seasonality and aridity, with different niche optima for hotspot and nonhotspot clades. Evolutionary transitions away from hotspots were associated with increases in niche breadth and elevated rates of niche evolution. Our results point to a process of “hotspot niche conservatism” whereby the accumulation of plant diversity in Mediterranean‐type ecosystems results from longer time for speciation, with dispersal away from hotspots limited by narrow and phylogenetically conserved environmental niches.     

Ecological niche models display nonlinear relationships with abundance and demographic performance across the latitudinal distribution of Astragalus utahensis (Fabaceae)

The potential for ecological niche models (ENMs) to accurately predict species' abundance and demographic performance throughout their geographic distributions remains a topic of substantial debate in ecology and biogeography. Few studies simultaneously examine the relationship between ENM predictions of environmental suitability and both a species' abundance and its demographic performance, particularly across its entire geographic distribution. Yet, studies of this type are essential for understanding the extent to which ENMs are a viable tool for identifying areas that may promote high abundance or performance of a species or how species might respond to future climate conditions. In this study, we used an ensemble ecological niche model to predict climatic suitability for the perennial forb Astragalus utahensis across its geographic distribution. We then examined relationships between projected climatic suitability and field‐based measures of abundance, demographic performance, and forecasted stochastic population growth (λ_s). Predicted climatic suitability showed a J‐shaped relationship with A. utahensis abundance, where low‐abundance populations were associated with low‐to‐intermediate suitability scores and abundance increased sharply in areas of high predicted climatic suitability. A similar relationship existed between climatic suitability and λ_s from the center to the northern edge of the latitudinal distribution. Patterns such as these, where density or demographic performance only increases appreciably beyond some threshold of climatic suitability, support the contention that ENM‐predicted climatic suitability does not necessarily represent a reliable predictor of abundance or performance across large geographic regions.     

Temperature‐dependent shifts in herbivore performance and interactions drive nonlinear changes in crop damages

Understanding how and to what extent the influence of temperature on physiological performance scales up to interspecific interactions and process rate patterns remains a major scientific challenge faced by ecologists. Here, we combined approaches developed by two conceptual frameworks in ecology, the stress‐gradient hypothesis (SGH), and the biodiversity–ecosystem functioning relationship (B‐EF), to test the hypothesis that interspecific difference in thermal performance modulates multiple species interactions along a thermal stress (SGH) and the subsequent richness effects on process rates (B‐EF). We designed an experiment using three species of herbivorous agricultural pests with different thermal optima for which we determined how temperature influences the direction and the strength of interaction and subsequent richness effects on crop damage (7 species interaction treatments × 6 temperature treatments × 10 replicates). We showed that both biotic interactions and species richness effects drive variations in crop damages along a thermal stress gradient, and thus have the potential to drive agro‐system responses to climate change. To help explain and generalize underlying mechanisms of richness effects on process rates, we further proposed a conceptual model that views interaction outcomes as shifting between positive and negative along a thermal stress depending on species thermal optima. Overall, our study demonstrates that nonlinear effects of temperature on process rates must be a major concern in terms of prediction and management of the consequences of global warming.     

Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents

Aim Biotic interactions – within guilds or across trophic levels – have widely been ignored in species distribution models (SDMs). This synthesis outlines the development of ‘species interaction distribution models’ (SIDMs), which aim to incorporate multispecies interactions at large spatial extents using interaction matrices. Location Local to global. Methods We review recent approaches for extending classical SDMs to incorporate biotic interactions, and identify some methodological and conceptual limitations. To illustrate possible directions for conceptual advancement we explore three principal ways of modelling multispecies interactions using interaction matrices: simple qualitative linkages between species, quantitative interaction coefficients reflecting interaction strengths, and interactions mediated by interaction currencies. We explain methodological advancements for static interaction data and multispecies time series, and outline methods to reduce complexity when modelling multispecies interactions. Results Classical SDMs ignore biotic interactions and recent SDM extensions only include the unidirectional influence of one or a few species. However, novel methods using error matrices in multivariate regression models allow interactions between multiple species to be modelled explicitly with spatial co‐occurrence data. If time series are available, multivariate versions of population dynamic models can be applied that account for the effects and relative importance of species interactions and environmental drivers. These methods need to be extended by incorporating the non‐stationarity in interaction coefficients across space and time, and are challenged by the limited empirical knowledge on spatio‐temporal variation in the existence and strength of species interactions. Model complexity may be reduced by: (1) using prior ecological knowledge to set a subset of interaction coefficients to zero, (2) modelling guilds and functional groups rather than individual species, and (3) modelling interaction currencies and species’ effect and response traits. Main conclusions There is great potential for developing novel approaches that incorporate multispecies interactions into the projection of species distributions and community structure at large spatial extents. Progress can be made by: (1) developing statistical models with interaction matrices for multispecies co‐occurrence datasets across large‐scale environmental gradients, (2) testing the potential and limitations of methods for complexity reduction, and (3) sampling and monitoring comprehensive spatio‐temporal data on biotic interactions in multispecies communities.     

The unfolding of plant growth form‐defence syndromes along elevation gradients

Understanding the functional economics that drives plant investment of resources requires investigating the interface between plant phenotypes and the variation in ecological conditions. While allocation to defence represents a large portion of the carbon budget, this axis is usually neglected in the study of plant economic spectrum. Using a novel geometrical approach, we analysed the co‐variation in a comprehensive set of functional traits related to plant growth strategies, as well as chemical defences against herbivores on all 15 Cardamine species present in the Swiss Alps. By extracting geometrical information of the functional space, we observed clustering of plants into three main syndromes. Those different strategies of growth form and defence were also distributed within distinct elevational bands demonstrating an association between the functional space and the ecological conditions. We conclude that plant strategies converge into clear syndromes that trade off abiotic tolerance, growth and defence within each elevation zone.     

Local‐scale biotic interactions embedded in macroscale climate drivers suggest Eltonian noise hypothesis distribution patterns for an invasive grass

A hierarchical view of niche relations reconciles the scale‐dependent effects of abiotic and biotic processes on species distribution patterns and underlies most current approaches to distribution modeling. A key prediction of this framework is that the effects of biotic interactions will be averaged out at macroscales – an idea termed the Eltonian noise hypothesis (ENH). We test this prediction by quantifying regional variation in local abiotic and biotic niche relations and assess the role of macroclimate in structuring biotic interactions, using a non‐native invasive grass, Microstegium vimineum, in its introduced range. Consistent with hierarchical niche relations and the ENH, macroclimate structures local biotic interactions, while local abiotic relations are regionally conserved. Biotic interactions suppress M. vimineum in drier climates but have little effect in wetter climates. A similar approach could be used to identify the macroclimatic conditions under which biotic interactions affect the accuracy of local predictions of species distributions.     

Disentangling scale dependencies in species environmental niches and distributions

Understanding species’ responses to environmental conditions, and how these ­species–environment associations shape spatial distributions, are longstanding goals in ecology and biogeography. However, an essential component of species–environment relationships – the spatial unit, or grain, at which they operate – remains unresolved. We identify three components of scale‐dependence in analyses of species–environment associations: 1) response grain, the grain at which species respond most strongly to their environment; 2) environment spatial structure, the pattern of spatial autocorrelation intrinsic to an environmental factor; and 3) analysis grain, the grain at which analyses are conducted and ecological inferences are made. We introduce a novel conceptual framework that defines these scale components in the context of analyzing species–environment relationships, and provide theoretical examples of their interactions for species with various ecological attributes. We then use a virtual species approach to investigate the impacts of each component on common methods of measuring and predicting species–environment relationships. We find that environment spatial structure has a substantial impact on the ability of even simple, univariate species distribution models (SDMs) to recover known species–­environment associations at coarse analysis grains. For simulated environments with ‘fine’ and ‘intermediate’ spatial structure, model explanatory power, and the frequency with which simple SDMs correctly estimated a virtual species’ response to the simulated environment, dramatically declined as analysis grain increased. Informed by these results, we use a scaling analysis to identify maximum analysis grains for individual environmental factors, and a scale optimization procedure to determine the grain of maximum predictive accuracy. Implementing these analysis grain thresholds and model performance standards in an example east African study system yields more accurate distribution predictions, compared to SDMs independently constructed at arbitrary analysis grains. Finally, we integrate our conceptual framework with virtual and empirical results to provide practical recommendations for researchers asking common questions about species–environment relationships.