Examining the link between competition and negative co‐occurrence patterns

Negative species co‐occurrence patterns have long intrigued ecologists because of their potential link to competition. Although manipulative field experiments have consistently revealed evidence of competition in natural communities, there is little evidence that this competition produces negative co‐occurrence patterns. Evidence does suggest that abiotic variation, dispersal limitation and herbivory can contribute to patterns of negative co‐occurrence among species; it is possible these influences have obscured a link with competition. Here, we test for a connection between negative co‐occurrence and competition by examining a small‐scale, relatively homogeneous old‐field plant community where the influence of abiotic variation was likely to be minimal and we accounted for the impact of herbivory with an herbivore exclosure treatment. Using three years of data (two biennial periods), we tested whether negatively co‐occurring pairs of species, when occasionally found together, experienced asymmetric abundance decline more frequently than positively co‐occurring pairs, for which there is no such expectation. We found no evidence that negatively co‐occurring pairs consistently suffered asymmetric abundance decline more frequently than positively co‐occurring pairs, providing no evidence that competition is a primary driver of negative co‐occurrence patterns in this community. Our results were consistent across control and herbivore exclosure treatments, suggesting that herbivores are not driving patterns of negative species co‐occurrence in this community. Any influence of competition or herbivory on co‐occurrence patterns is small enough that it is obscured by other factors such as substrate heterogeneity, dispersal and differential species responses to climatic variation through time. We interpret our results as providing evidence that competition is not responsible for producing negative co‐occurrence patterns in our study community and suggest that this may be the case more broadly.     

Factors shaping community assemblages and species co‐occurrence of different trophic levels

Species assemblages are the results of various processes, including dispersion and habitat filtering. Disentangling the effects of these different processes is challenging for statistical analysis, especially when biotic interactions should be considered. In this study, we used plants (producers) and leafhoppers (phytophagous) as model organisms, and we investigated the relative importance of abiotic versus biotic factors that shape community assemblages, and we infer on their biotic interactions by applying three‐step statistical analysis. We applied a novel statistical analysis, that is, multiblock Redundancy Analysis (mbRA, step 1) and showed that 51.8% and 54.1% of the overall variation in plant and leafhopper assemblages are, respectively, explained by the two multiblock models. The most important blocks of variables to explain the variations in plant and leafhopper assemblages were local topography and biotic factors. Variation partitioning analysis (step 2) showed that pure abiotic filtering and pure biotic processes were relatively less important than their combinations, suggesting that biotic relationships are strongly structured by abiotic conditions. Pairwise co‐occurrence analysis (step 3) on generalist leafhoppers and the most common plants identified 40 segregated species pairs (mainly between plant species) and 16 aggregated pairs (mainly between leafhopper species). Pairwise analysis on specialist leafhoppers and potential host plants clearly revealed aggregated patterns. Plant segregation suggests heterogeneous resource availability and competitive interactions, while leafhopper aggregation suggests host feeding differentiation at the local level, different feeding microhabitats on host plants, and similar environmental requirements of the species. Using the novel mbRA, we disentangle for the first time the relative importance of more than five distinct groups of variables shaping local species communities. We highlighted the important role of abiotic processes mediated by bottom‐up effects of plants on leafhopper communities. Our results revealed that in‐field structure diversification and trophic interactions are the main factors causing the co‐occurrence patterns observed.     

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.     

Overlapping trophic niches among co‐occurring amphipods from a cryptic species complex

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The pairwise approach to analysing species co‐occurrence

The analysis of species co‐occurrence patterns continues to be a main pursuit of ecologists, primarily because the coexistence of species is fundamentally important in evaluating various theories, principles and concepts. Examples include community assembly, equilibrium versus non‐equilibrium organization of communities, resource partitioning and ecological character displacement, the local–regional species diversity relationship, and the metacommunity concept. Traditionally, co‐occurrence has been measured and tested at the level of an entire species presence–absence matrix wherein various algorithms are used to randomize matrices and produce statistical null distributions of metrics that quantify structure in the matrix. This approach implicitly recognizes a presence–absence matrix as having some real ecological identity (e.g. a set of species exhibiting nestedness among a set of islands) in addition to being a unit of statistical analysis. An emerging alternative is to test for non‐random co‐occurrence between paired species. The pairwise approach does not analyse matrix‐level structure and thus views a species pair as the fundamental unit of co‐occurrence. Inferring process from pattern is very difficult in analyses of co‐occurrence; however, the pairwise approach may make this task easier by simplifying the analysis and resulting inferences to associations between paired species.     

Using co‐occurrence network topology in assessing ecological stress in benthic macroinvertebrate communities

Ecological monitoring of streams has often focused on assessing the biotic integrity of individual benthic macroinvertebrate (BMI) communities through local measures of diversity, such as taxonomic or functional richness. However, as individual BMI communities are frequently linked by a variety of ecological processes at a regional scale, there is a need to assess biotic integrity of groups of communities at the scale of watersheds. Using 4,619 sampled communities of streambed BMIs, we investigate this question using co‐occurrence networks generated from groups of communities selected within California watersheds under different levels of stress due to upstream land use. Building on a number of arguments in theoretical ecology and network theory, we propose a framework for the assessment of the biotic integrity of watershed‐scale groupings of BMI communities using measures of their co‐occurrence network topology. We found significant correlations between stress, as described by a mean measure of upstream land use within a watershed, and topological measures of co‐occurrence networks such as network size (r = ?.81, p < 10^–4), connectance (r = .31, p < 10^–4), mean co‐occurrence strength (r = .25, p < 10^–4), degree heterogeneity (r = ?.10, p < 10^–4), and modularity (r = .11, p < 10^–4). Using these five topological measures, we constructed a linear model of biotic integrity, here a composite of taxonomic and functional diversity known as the California Stream Condition Index, of groups of BMI communities within a watershed. This model can account for 66% of among‐watershed variation in the mean biotic integrity of communities. These observations imply a role for co‐occurrence networks in assessing the current status of biotic integrity for BMI communities, as well as their potential use in assessing other ecological communities.     

A network approach for inferring species associations from co‐occurrence data

Positive and negative associations between species are a key outcome of community assembly from regional species pools. These associations are difficult to detect and can be caused by a range of processes such as species interactions, local environmental constraints and dispersal. We integrate new ideas around species distribution modeling, covariance matrix estimation, and network analysis to provide an approach to inferring non‐random species associations from local‐ and regional‐scale occurrence data. Specifically, we provide a novel framework for identifying species associations that overcomes three challenges: 1) correcting for indirect effects from other species, 2) avoiding spurious associations driven by regional‐scale distributions, and 3) describing these associations in a multi‐species context. We highlight a range of research questions and analyses that this framework is able to address. We show that the approach is statistically robust using simulated data. In addition, we present an empirical analysis of > 1000 North American tree communities that gives evidence for weak positive associations among small groups of species. Finally, we discuss several possible extensions for identifying drivers of associations, predicting community assembly, and better linking biogeography and community ecology.     

Predictor species: Improving assessments of rare species occurrence by modeling environmental co‐responses

Designing an effective conservation strategy requires understanding where rare species are located. Because rare species can be difficult to find, ecologists often identify other species called conservation surrogates that can help inform the distribution of rare species. Species distribution models typically rely on environmental data when predicting the occurrence of species, neglecting the effect of species' co‐occurrences and biotic interactions. Here, we present a new approach that uses Bayesian networks to improve predictions by modeling environmental co‐responses among species. For species from a European peat bog community, our approach consistently performs better than single‐species models and better than conventional multi‐species approaches that include the presence of nontarget species as additional independent variables in regression models. Our approach performs particularly well with rare species and when calibration data are limited. Furthermore, we identify a group of “predictor species” that are relatively common, insensitive to the presence of other species, and can be used to improve occurrence predictions of rare species. Predictor species are distinct from other categories of conservation surrogates such as umbrella or indicator species, which motivates focused data collection of predictor species to enhance conservation practices.     

Pollinator‐mediated interactions between cultivated papaya and co‐flowering plant species

Many modern crop varieties rely on animal pollination to set fruit and seeds. Intensive crop plantations usually do not provide suitable habitats for pollinators so crop yield may depend on the surrounding vegetation to maintain pollination services. However, little is known about the effect of pollinator‐mediated interactions among co‐flowering plants on crop yield or the underlying mechanisms. Plant reproductive success is complex, involving several pre‐ and post‐pollination events; however, the current literature has mainly focused on pre‐pollination events in natural plant communities. We assessed pollinator sharing and the contribution to pollinator diet in a community of wild and cultivated plants that co‐flower with a focal papaya plantation. In addition, we assessed heterospecific pollen transfer to the stigmatic loads of papaya and its effect on fruit and seed production. We found that papaya shared at least one pollinator species with the majority of the co‐flowering plants. Despite this, heterospecific pollen transfer in cultivated papaya was low in open‐pollinated flowers. Hand‐pollination experiments suggest that heterospecific pollen transfer has no negative effect on fruit production or weight, but does reduce seed production. These results suggest that co‐flowering plants offer valuable floral resources to pollinators that are shared with cultivated papaya with little or no cost in terms of heterospecific pollen transfer. Although HP reduced seed production, a reduced number of seeds per se are not negative, given that from an agronomic perspective the number of seeds does not affect the monetary value of the papaya fruit.     

Thermal adaptation affects interactions between a range‐expanding and a native odonate species

1. Increasing temperature and invading species may interact in their effects on communities. In this study, we investigated how rising temperatures alter larval interactions between a naturally range‐expanding dragonfly, Crocothemis erythraea, and a native northern European species, Leucorrhinia dubia. Initial studies revealed that C. erythraea grow up to 3.5 times faster than L. dubia at temperatures above 16 °C. As a result, we hypothesised that divergent temperature responses would lead to rapid size differences between coexisting larvae and, consequently, to asymmetric intraguild predation at higher ambient temperatures. 2. Mortality and growth rates were measured in interaction treatments (with both species present) and non‐interaction controls (one species present) at four different temperature regimes: at an ambient temperature representative of central Germany, where both species overlap in distribution, and at temperatures increased by 2, 4 and 6 °C. 3. The mortality of C. erythraea did not differ between treatment and control. In contrast, mortality of L. dubia remained similar over all temperatures in the controls, but increased with temperature in the presence of the other species and was significantly higher there than in the controls. We concluded that L. dubia suffered asymmetric intraguild predation, particularly at increased temperature. Reduced growth rate of L. dubia in the interaction treatment at higher temperatures also suggested asymmetric competition for prey in the first phase of the experiment. 4. The results imply that the range expansion of C. erythraea may cause reduction in population size of syntopic L. dubia when temperature rises by more than 2 °C. The consequences for future range patterns, as well as other factors that may influence the interaction in nature, are discussed.     

Positive co‐occurrence between feeding‐associative savannah fishes depends on species and habitat

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Predatory interactions between a cyclopoid copepod and three sibling rotifer species

SUMMARY 1. Cyclopoid copepod predation on rotifers affects the dynamics and structure of zooplankton communities. We address the differential vulnerability of three sympatric rotifer sibling species belonging to the Brachionus plicatilis species complex. These co-occur with their cyclopoid predator, Diacyclops bicuspidatus odessanus .
2. Using video recording and tracking, we analysed the steps in predation including attack distance, attack angle, and rotifer species swimming in the presence and absence of the predator. Our results show the greater vulnerability of B. rotundiformis (the smallest species) to D. b. odessanus predation, which is associated with a high percentage of attacks after contact. Brachionus plicatilis (the biggest species) is the less vulnerable prey, with low percentage of attacks after contact and captures after attacks. Branchionus ibericus , the intermediate sized species, had also intermediate vulnerability.
3. The differential vulnerability provides insight into the coexistence and seasonal succession of these competing rotifer species. Our results show that the competitive superiority of B. rotundiformis may be balanced by its greater vulnerability to copepod predation.     

Co‐occurrence is not evidence of ecological interactions

There is a rich amount of information in co‐occurrence (presence–absence) data that could be used to understand community assembly. This proposition first envisioned by Forbes (1907) and then Diamond (1975) prompted the development of numerous modelling approaches (e.g. null model analysis, co‐occurrence networks and, more recently, joint species distribution models). Both theory and experimental evidence support the idea that ecological interactions may affect co‐occurrence, but it remains unclear to what extent the signal of interaction can be captured in observational data. It is now time to step back from the statistical developments and critically assess whether co‐occurrence data are really a proxy for ecological interactions. In this paper, we present a series of arguments based on probability, sampling, food web and coexistence theories supporting that significant spatial associations between species (or lack thereof) is a poor proxy for ecological interactions. We discuss appropriate interpretations of co‐occurrence, along with potential avenues to extract as much information as possible from such data.     

Species interactions weakly modify climate‐induced tree co‐occurrence patterns

Aims

Species distributions are hypothesized to be underlain by a complex association of processes that span multiple spatial scales including biotic interactions, dispersal limitation, fine‐scale resource gradients and climate. Species disequilibrium with climate may reflect the effects of non‐climatic processes on species distributions, yet distribution models have rarely directly considered non‐climatic processes. Here, we use a Joint Species Distribution Model (JSDM) to investigate the influence of non‐climatic factors on species co‐occurrence patterns and to directly quantify the relative influences of climate and alternative processes that may generate correlated responses in species distributions, such as species interactions, on tree co‐occurrence patterns.

Location

US Rocky Mountains.

Methods

We apply a Bayesian JSDM to simultaneously model the co‐occurrence patterns of ten dominant tree species across the Rocky Mountains, and evaluate climatic and residual correlations from the fitted model to determine the relative contribution of each component to observed co‐occurrence patterns. We also evaluate predictions generated from the fitted model relative to a single‐species modelling approach.

Results

For most species, correlation due to climate covariates exceeded residual correlation, indicating an overriding influence of broad‐scale climate on co‐occurrence patterns. Accounting for covariance among species did not significantly improve predictions relative to a single‐species approach, providing limited evidence for a strong independent influence of species interactions on distribution patterns.

Conclusions

Overall, our findings indicate that climate is an important driver of regional biodiversity patterns and that interactions between dominant tree species contribute little to explain species co‐occurrence patterns among Rocky Mountain trees.     

Disentangling biotic interactions,environmental filters,and dispersal limitation as drivers of species co‐occurrence

A key focus in ecology is to search for community assembly rules. Here we compare two community modelling frameworks that integrate a combination of environmental and spatial data to identify positive and negative species associations from presence–absence matrices, and incorporate an additional comparison using joint species distribution models (JSDM). The frameworks use a dichotomous logic tree that distinguishes dispersal limitation, environmental requirements, and interspecific interactions as causes of segregated or aggregated species pairs. The first framework is based on a classical null model analysis complemented by tests of spatial arrangement and environmental characteristics of the sites occupied by the members of each species pair (Classic framework). The second framework, (SDM framework) implemented here for the first time, builds on the application of environmentally‐constrained null models (or JSDMs) to partial out the influence of the environment, and includes an analysis of the geographical configuration of species ranges to account for dispersal effects. We applied these approaches to examine plot‐level species co‐occurrence in plant communities sampled along a wide elevation gradient in the Swiss Alps. According to the frameworks, the majority of species pairs were randomly associated, and most of the non‐random positive and negative species associations could be attributed to environmental filtering and/or dispersal limitation. These patterns were partly detected also with JSDM. Biotic interactions were detected more frequently in the SDM framework, and by JSDM, than in the Classic framework. All approaches detected species aggregation more often than segregation, perhaps reflecting the important role of facilitation in stressful high‐elevation environments. Differences between the frameworks may reflect the explicit incorporation of elevational segregation in the SDM framework and the sensitivity of JSDM to the environmental data. Nevertheless, all methods have the potential to reveal general patterns of species co‐occurrence for different taxa, spatial scales, and environmental conditions.     

Phylogeny and co‐occurrence of mammal species on Southeast Asian islands

Aim Islands have often been used as model systems in community ecology. The incorporation of information on phylogenetic relatedness of species in studies of island assemblage structure is still uncommon, but could provide valuable insights into the processes of island community assembly. We propose six models of island community assembly that make different predictions about the associations between co‐occurrences of species pairs on islands, phylogenetic relatedness and ecological similarity. We then test these models using data on mammals of Southeast Asian islands. Location Two hundred and forty islands of the Sundaland region of Southeast Asia. Methods We quantified the co‐occurrence of species pairs on islands, and identified pairs that co‐occur more frequently (positive co‐occurrence) or less frequently (negative co‐occurrence) than expected under null models. We then examined the distributions of these significantly deviating pairs with respect to phylogenetic relatedness and ecological differentiation, and compared these patterns with those predicted by the six community assembly models. We used permutation regression to test whether co‐occurrence patterns are predicted by relatedness, body size difference or difference in diet quality. Separate co‐occurrence matrices were analysed in this way for seven mammal families and four smaller subsets of the islands of Sundaland. Results In many matrices, average numbers of negative co‐occurrences were higher than expected under null models. This is consistent with assemblage structuring by competition, but may also result from low geographic overlap of species pairs, which contributes to negative co‐occurrences at the archipelago‐wide level. Distributions of species pairs within plots of phylogenetic distance × ecological differentiation were consistent with competition, habitat filtering or within‐island speciation models, depending on the taxon. Regressions indicated that co‐occurrence was more likely among closely related species pairs within the Viverridae and Sciuridae, but in most matrices phylogenetic distance was unrelated to co‐occurrence. Main conclusions Simple deterministic models linking co‐occurrence with phylogeny and ecology are a useful framework for interpreting distributions and assemblage structure of island species. However, island assemblages in Sundaland have probably been shaped by a complex idiosyncratic set of interacting ecological and evolutionary processes, limiting the predictive power of such models.