Plant–mycorrhizal fungus co‐occurrence network lacks substantial structure

The interactions between plants and arbuscular mycorrhizal fungi (AMF) maintain a crucial link between macroscopic organisms and the soil microbial world. These interactions are of extreme importance for the diversity of plant communities and ecosystem functioning. Despite this importance, only recently has the structure of plant–AMF interaction networks been studied. These recent studies, which used genetic data, suggest that these networks are highly structured, very similar to plant–animal mutualistic networks. However, the assembly process of plant–AMF communities is still largely unknown, and an important feature of plant–AMF interactions has not been incorporated: they occur at an extremely localized scale. Studying plant–AMF networks in a spatial context seems therefore a crucial step. This paper studies a plant–AMF spatial co‐occurrence network using novel methodology based on information theory and a unique set of spatially explicit species‐level data. We apply three null models of which only one accounts for spatial effects. We find that the data show substantial departures from null expectations for the two non‐spatial null models. However, for the null model considering spatial effects, there are few significant co‐occurrences compared with the other two null models. Thus, plant–AMF spatial co‐occurrences seem to be mostly explained by stochasticity, with a small role for other factors related to plant–AMF specialization. Furthermore, we find that the network is not significantly nested or modular. We conclude that this plant–AMF spatial co‐occurrence network lacks substantial structure and, therefore, plants and AMF species do not track each other over space. Thus, random encounters seem more important in the first step of the assembly of plant–AMF communities. Synthesis The symbiotic interaction between plants and arbuscular mycorrhizal fungi (AMF) is crucial for ecosystem functioning. However, the factors affecting the assembly of plant‐AMF communities are poorly understood. An important factor of the assembly of plant‐AMF communities has been overlooked: plant‐AMF interactions occur at a localized spatial scale. Our study investigated the importance of space in the structure of plant‐AMF communities. We studied a plant‐AMF spatial co‐occurrence network using a unique set of spatially explicit data and applied three null models. We found that plant‐AMF spatial co‐occurrences seem to be mostly explained by stochasticity. In particular, our study shows that this plant‐AMF spatial co‐occurrence network lacks substantial structure and, therefore, plants and AMF species do not track each other over space. Thus, random encounters seem to drive the assembly of plant‐AMF communities.     

Changes in the distribution of multispecies pest assemblages affect levels of crop damage in warming tropical Andes

Climate induced species range shifts might create novel interactions among species that may outweigh direct climatic effects. In an agricultural context, climate change might alter the intensity of competition or facilitation interactions among pests with, potentially, negative consequences on the levels of damage to crop. This could threaten the productivity of agricultural systems and have negative impacts on food security, but has yet been poorly considered in studies. In this contribution, we constructed and evaluated process‐based species distribution models for three invasive potato pests in the Tropical Andean Region. These three species have been found to co‐occur and interact within the same potato tuber, causing different levels of damage to crop. Our models allowed us to predict the current and future distribution of the species and therefore, to assess how damage to crop might change in the future due to novel interactions. In general, our study revealed the main challenges related to distribution modeling of invasive pests in highly heterogeneous regions. It yielded different results for the three species, both in terms of accuracy and distribution, with one species surviving best at lower altitudes and the other two performing better at higher altitudes. As to future distributions our results suggested that the three species will show different responses to climate change, with one of them expanding to higher altitudes, another contracting its range and the other shifting its distribution to higher altitudes. These changes will result in novel areas of co‐occurrence and hence, interactions of the pests, which will cause different levels of damage to crop. Combining population dynamics and species distribution models that incorporate interspecific trade‐off relationships in different environments revealed a powerful approach to provide predictions about the response of an assemblage of interacting species to future environmental changes and their impact on process rates.     

Historical climate‐change influences modularity and nestedness of pollination networks

The structure of species interaction networks is important for species coexistence, community stability and exposure of species to extinctions. Two widespread structures in ecological networks are modularity, i.e. weakly connected subgroups of species that are internally highly interlinked, and nestedness, i.e. specialist species that interact with a subset of those species with which generalist species also interact. Modularity and nestedness are often interpreted as evolutionary ecological structures that may have relevance for community persistence and resilience against perturbations, such as climate‐change. Therefore, historical climatic fluctuations could influence modularity and nestedness, but this possibility remains untested. This lack of research is in sharp contrast to the considerable efforts to disentangle the role of historical climate‐change and contemporary climate on species distributions, richness and community composition patterns. Here, we use a global database of pollination networks to show that historical climate‐change is at least as important as contemporary climate in shaping modularity and nestedness of pollination networks. Specifically, on the mainland we found a relatively strong negative association between Quaternary climate‐change and modularity, whereas nestedness was most prominent in areas having experienced high Quaternary climate‐change. On islands, Quaternary climate‐change had weak effects on modularity and no effects on nestedness. Hence, for both modularity and nestedness, historical climate‐change has left imprints on the network structure of mainland communities, but had comparably little effect on island communities. Our findings highlight a need to integrate historical climate fluctuations into eco‐evolutionary hypotheses of network structures, such as modularity and nestedness, and then test these against empirical data. We propose that historical climate‐change may have left imprints in the structural organisation of species interactions in an array of systems important for maintaining biological diversity.     

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.     

Incorporating phylogenetic metrics to microbial co‐occurrence networks based on amplicon sequences to discern community assembly processes

Co‐occurrence network analysis based on amplicon sequences is increasingly used to study microbial communities. Patterns of co‐existence or mutual exclusion between pairs of taxa are often interpreted as reflecting positive or negative biological interactions. However, other assembly processes can underlie these patterns, including species failure to reach distant areas (dispersal limitation) and tolerate local environmental conditions (habitat filtering). We provide a tool to quantify the relative contribution of community assembly processes to microbial co‐occurrence patterns, which we applied to explore soil bacterial communities in two dry ecosystems. First, we sequenced a bacterial phylogenetic marker in soils collected across multiple plots. Second, we inferred co‐occurrence networks to identify pairs of significantly associated taxa, either co‐existing more (aggregated) or less often (segregated) than expected at random. Third, we assigned assembly processes to each pair: patterns explained based on spatial or environmental distance were ascribed to dispersal limitation (2%–4%) or habitat filtering (55%–77%), and the remaining to biological interactions. Finally, we calculated the phylogenetic distance between taxon pairs to test theoretical expectations on the linkages between phylogenetic patterns and assembly processes. Aggregated pairs were more closely related than segregated pairs. Furthermore, habitat‐filtered aggregated pairs were closer relatives than those assigned to positive interactions, consistent with phylogenetic niche conservatism and cooperativism among distantly related taxa. Negative interactions resulted in equivocal phylogenetic signatures, probably because different competitive processes leave opposing signals. We show that microbial co‐occurrence networks mainly reflect environmental tolerances and propose that incorporating measures of phylogenetic relatedness to networks might help elucidate ecologically meaningful patterns.     

Species co‐occurrence networks show reptile community reorganization under agricultural transformation

Agricultural transformation represents one of the greatest threats to biodiversity, causing degradation and loss of habitat, leading to changes in the richness and composition of communities. These changes in richness and composition may, in turn, lead to altered species co‐occurrence, but our knowledge of this remains limited. We used a novel co‐occurrence network approach to examine the impact of agricultural transformation on reptile community structure within two large (> 172 000 km²; 224 sites) agricultural regions in southeastern Australia. We contrasted assemblages from sites surrounded by intact and modified landscapes and tested four key hypotheses that agricultural transformation leads to (H1) declines in species richness, (H2) altered assemblages, (H3) declines in overall co‐occurrence, and (H4) complex restructuring of pairwise associations. We found that modified landscapes differed in composition but not richness compared with intact sites. Modified landscapes were also characterized by differences in co‐occurrence network structure; with species sharing fewer sites with each other (reduced co‐occurrence connectance), fewer highly‐connected species (truncation of the frequency distribution of co‐occurrence degree) and increased modularity of co‐occurrence networks. Critically, overall loss of co‐occurrence was underpinned by complex changes to the number and distribution of pair‐wise co‐occurrence links, with 41–44% of species also gaining associations with other species. Change in co‐occurrence was not correlated with changes in occupancy, nor by functional trait membership, allowing a novel classification of species susceptibility to agricultural transformation. Our study reveals the value of using co‐occurrence analysis to uncover impacts of agricultural transformation that may be masked in conventional studies of species richness and community composition.     

Investigating microbial associations from sequencing survey data with co‐correspondence analysis

Microbial communities, which drive major ecosystem functions, consist of a wide range of interacting species. Understanding how microbial communities are structured and the processes underlying this is crucial to interpreting ecosystem responses to global change but is challenging as microbial interactions cannot usually be directly observed. Multiple efforts are currently focused to combine next‐generation sequencing (NGS) techniques with refined statistical analysis (e.g., network analysis, multivariate analysis) to characterize the structures of microbial communities. However, most of these approaches consider a single table of sequencing data measured for several samples. Technological advances now make it possible to collect NGS data on different taxonomic groups simultaneously for the same samples, allowing us to analyse a pair of tables. Here, an analytical framework based on co‐correspondence analysis (CoCA) is proposed to study the distributions, assemblages and interactions between two microbial communities. We show the ability of this approach to highlight the relationships between two microbial communities, using two data sets exhibiting various types of interactions. CoCA identified strong association patterns between autotrophic and heterotrophic microbial eukaryote assemblages, on the one hand, and between microalgae and viruses, on the other. We demonstrate also how CoCA can be used, complementary to network analysis, to reorder co‐occurrence networks and thus investigate the presence of patterns in ecological networks.     

High temporal variability in the occurrence of consumer–resource interactions in ecological networks

Ecological networks have been used to represent interactions between species as fixed linkages despite that populations naturally oscillate over time and space. As such, the influence of the persistence of linkages between species in communities has been overlooked. Unfortunately, empirical analysis of the temporal variation of trophic networks is constrained by the lack of data with high spatial, temporal and taxonomic resolution. Here, we evaluate the spatiotemporal variability of multiple consumer– resource interactions to quantify the relative dominance of highly persistent versus poorly persistent interactions, the commonness of the interaction persistence patterns, and the effect of biotic and abiotic conditions on these patterns. We took advantage of a dataset from four large marine intertidal rocky‐shore networks monitored seasonally for three years along 1000 km of the coast of northern Chile. Our results showed that the communities were characterized by few persistent interactions and a large number of transient trophic interactions, which was well described by a common exponential decay in the rank‐frequency relationship of consumer–resource interactions despite dissimilarities in environmental conditions among sites. These results were independent of the degree of consumer–resource co‐occurrence. Our results stress the need for more long‐term studies that evaluate the temporal variability of ecological networks.     

Seeing is believing? Comparing plant–herbivore networks constructed by field co‐occurrence and DNA barcoding methods for gaining insights into network structures

Plant–herbivore interaction networks provide information about community organization. Two methods are currently used to document pairwise interactions among plants and insect herbivores. One is the traditional method that collects plant–herbivore interaction data by field observation of insect occurrence on host plants. The other is the increasing application of newly developed molecular techniques based on DNA barcodes to the analysis of gut contents. The second method is more appealing because it documents realized interactions. To construct complete interaction networks, each technique of network construction is urgent to be assessed. We addressed this question by comparing the effectiveness and reliability of the two methods in constructing plant–Lepidoptera larval network in a 50 ha subtropical forest in China. Our results showed that the accuracy of diet identification by observation method increased with the number of observed insect occurrences on food plants. In contrast, the molecular method using three plant DNA markers were able to identify food residues for 35.6% larvae and correctly resolved 77.3% plant (diet) species. Network analysis showed molecular networks had threefold more unique host plant species but fewer links than the traditional networks had. The molecular method detected plants that were not sampled by the traditional method, for example, bamboos, bryophytes and lianas in the diets of insect herbivores. The two networks also possessed significantly different structural properties. Our study indicates the traditional observation of co‐occurrence is inadequate, while molecular method can provide higher species resolution of ecological interactions.     

Spatio-temporal variation in the structure of pollination networks

Pollination networks are representations of all interactions between co-existing plants and their flower visiting animals at a given site. Although the study of networks has become a distinct sub-discipline in pollination biology, few studies have attempted to quantify spatio-temporal variation in species composition and structure of networks. We here investigate patterns of year-to-year change in pollination networks from six different sites spanning a large latitudinal gradient. We quantified level of species persistence and interactions among years, and examined year-to-year variation of network structural parameters in relation to latitude and sampling effort. In addition, we tested for correlations between annual variation in network parameters and short and long-term climate change variables. Numbers of plant and animal species and interactions were roughly constant from one year to another at all sites. However, composition of species and interactions changed from one year to another. Turnover was particularly high for flower visitors and interactions. On the other hand, network structural parameters (connectance, nestedness, modularity and centralization) remained remarkably constant between years, regardless of network size and latitude. Inter-annual variation of network parameters was not related to short or long term variation in climate variables (mean annual temperature and annual precipitation). We thus conclude that pollination networks are highly dynamic and variable in composition of species and interactions among years. However, general patterns of network structure remain constant, indicating that species may be replaced by topologically similar species. These results suggest that pollination networks are to some extent robust against factors affecting species occurrences.     

Climate change has indirect effects on resource use and overlap among coexisting bird species with negative consequences for their reproductive success

Climate change can modify ecological interactions, but whether it can have cascading effects throughout ecological networks of multiple interacting species remains poorly studied. Climate‐driven alterations in the intensity of plant–herbivore interactions may have particularly profound effects on the larger community because plants provide habitat for a wide diversity of organisms. Here we show that changes in vegetation over the last 21 years, due to climate effects on plant–herbivore interactions, have consequences for songbird nest site overlap and breeding success. Browsing‐induced reductions in the availability of preferred nesting sites for two of three ground nesting songbirds led to increasing overlap in nest site characteristics among all three bird species with increasingly negative consequences for reproductive success over the long term. These results demonstrate that changes in the vegetation community from effects of climate change on plant–herbivore interactions can cause subtle shifts in ecological interactions that have critical demographic ramifications for other species in the larger community.     

Species importance in a heterospecific foraging association network

There is a growing recognition of the need to integrate non‐trophic interactions into ecological networks for a better understanding of whole‐community organization. To achieve this, the first step is to build networks of individual non‐trophic interactions. In this study, we analyzed a network of interdependencies among bird species that participated in heterospecific foraging associations (flocks) in an evergreen forest site in the Western Ghats, India. We found the flock network to contain a small core of highly important species that other species are strongly dependent on, a pattern seen in many other biological networks. Further, we found that structural importance of species in the network was strongly correlated to functional importance of species at the individual flock level. Finally, comparisons with flock networks from other Asian forests showed that the same taxonomic groups were important in general, suggesting that species importance was an intrinsic trait and not dependent on local ecological conditions. Hence, given a list of species in an area, it may be possible to predict which ones are likely to be important. Our study provides a framework for the investigation of other heterospecific foraging associations and associations among species in other non‐trophic contexts.     

Testing the link between species interactions and species co‐occurrence in a trophic network

Species interactions are dynamic processes that vary across environmental and ecological contexts, and operate across scale boundaries, making them difficult to quantify. Nevertheless, ecologists are increasingly interested in inferring species interactions from observational data using statistical analyses of their spatial co‐occurrence patterns. Trophic interactions present a particular challenge, as predators and prey may frequently or rarely co‐occur, depending on the spatial or temporal scale of observation. In this study, we investigate the accuracy of inferred interactions among species that both compete and trophically interact. We utilized a long‐term dataset of pond‐breeding amphibian co‐occurrences from Mt Rainier National Park (Washington, USA) and compiled a new dataset of their empirical interactions from the literature. We compared the accuracy of four statistical methods in inferring these known species interactions from spatial associations. We then used the best performing statistical method, the Markov network, to further investigate the sensitivity of interaction inference to spatial scale‐dependence and the presence of predators. We show that co‐occurrence methods are generally inaccurate when estimating trophic interactions. Further the strength and sign of inferred interactions were dependent upon the spatial scale of observation and predator presence influenced the detectability of competitive interactions among prey species. However, co‐occurrence analysis revealed new patterns of spatial association among pairs of species with known interactions. Overall, our study highlights a limiting frontier in co‐occurrence theory and the disconnect between widely implemented methodologies and their ability to accurately infer interactions in trophically‐structured communities.     

Dispersal network heterogeneity promotes species coexistence in hierarchical competitive communities

Understanding the mechanisms of biodiversity maintenance is a fundamental issue in ecology. The possibility that species disperse within the landscape along differing paths presents a relatively unexplored mechanism by which diversity could emerge. By embedding a classical metapopulation model within a network framework, we explore how access to different dispersal networks can promote species coexistence. While it is clear that species with the same demography cannot coexist stably on shared dispersal networks, we find that coexistence is possible on unshared networks, as species can surprisingly form self‐organised clusters of occupied patches with the most connected patches at the core. Furthermore, a unimodal biodiversity response to an increase in species colonisation rates or average patch connectivity emerges in unshared networks. Increasing network size also increases species richness monotonically, producing characteristic species–area curves. This suggests that, in contrast to previous predictions, many more species can co‐occur than the number of limiting resources.     

Anticipating changes to future connectivity within a network of marine protected areas

Continental boundary currents are projected to be altered under future scenarios of climate change. As these currents often influence dispersal and connectivity among populations of many marine organisms, changes to boundary currents may have dramatic implications for population persistence. Networks of marine protected areas (MPAs) often aim to maintain connectivity, but anticipation of the scale and extent of climatic impacts on connectivity are required to achieve this critical conservation goal in a future of climate change. For two key marine species (kelp and sea urchins), we use oceanographic modelling to predict how continental boundary currents are likely to change connectivity among a network of MPAs spanning over 1000 km of coastline off the coast of eastern Australia. Overall change in predicted connectivity among pairs of MPAs within the network did not change significantly over and above temporal variation within climatic scenarios, highlighting the need for future studies to incorporate temporal variation in dispersal to robustly anticipate likely change. However, the intricacies of connectivity between different pairs of MPAs were noteworthy. For kelp, poleward connectivity among pairs of MPAs tended to increase in the future, whereas equatorward connectivity tended to decrease. In contrast, for sea urchins, connectivity among pairs of MPAs generally decreased in both directions. Self‐seeding within higher‐latitude MPAs tended to increase, and the role of low‐latitude MPAs as a sink for urchins changed significantly in contrasting ways. These projected changes have the potential to alter important genetic parameters with implications for adaptation and ecosystem vulnerability to climate change. Considering such changes, in the context of managing and designing MPA networks, may ensure that conservation goals are achieved into the future.     

Effect of historical land‐use and climate change on tree‐climate relationships in the upper Midwestern United States

Contemporary forest inventory data are widely used to understand environmental controls on tree species distributions and to construct models to project forest responses to climate change, but the stability and representativeness of contemporary tree‐climate relationships are poorly understood. We show that tree‐climate relationships for 15 tree genera in the upper Midwestern US have significantly altered over the last two centuries due to historical land‐use and climate change. Realised niches have shifted towards higher minimum temperatures and higher rainfall. A new attribution method implicates both historical climate change and land‐use in these shifts, with the relative importance varying among genera and climate variables. Most climate/land‐use interactions are compounding, in which historical land‐use reinforces shifts in species‐climate relationships toward wetter distributions, or confounding, in which land‐use complicates shifts towards warmer distributions. Compounding interactions imply that contemporary‐based models of species distributions may underestimate species resilience to climate change.     

The dissimilarity of species interaction networks

In a context of global changes, and amidst the perpetual modification of community structure undergone by most natural ecosystems, it is more important than ever to understand how species interactions vary through space and time. The integration of biogeography and network theory will yield important results and further our understanding of species interactions. It has, however, been hampered so far by the difficulty to quantify variation among interaction networks. Here, we propose a general framework to study the dissimilarity of species interaction networks over time, space or environments, allowing both the use of quantitative and qualitative data. We decompose network dissimilarity into interactions and species turnover components, so that it is immediately comparable to common measures of β‐diversity. We emphasise that scaling up β‐diversity of community composition to the β‐diversity of interactions requires only a small methodological step, which we foresee will help empiricists adopt this method. We illustrate the framework with a large dataset of hosts and parasites interactions and highlight other possible usages. We discuss a research agenda towards a biogeographical theory of species interactions.     

Phenotypically similar but ecologically distinct: differences in competitive ability and predation risk among amphipods

Nature is often more diverse than expected with multiple species appearing to occupy the same niche. This observation is especially perplexing when the co‐occurring species are cryptic (i.e. only distinguishable via molecular markers), because phenotypic similarity is expected to correspond with strong niche overlap. One way that phenotypically similar species can coexist is if fine‐scale phenotypic differences affect how species interact with other members of the community that ultimately results in performance tradeoffs. An alternative explanation for co‐occurrence is that phenotypic similarity leads to ecological equivalence allowing species to co‐occur for long periods. We tested whether three phenotypically similar amphipod species that co‐occur exhibit performance tradeoffs that may allow them to stably coexist in lakes. We found that despite their similarity the three species differed in how well they performed in competition with each other and their ability to avoid predation by fish and invertebrate predators. In some species comparisons, performance tradeoffs were apparent with species that perform well against heterospecifics performing poorly against predators and vice versa. We also found evidence for direct antagonistic interactions among amphipod species, in the form of wounding, which may play a role in structuring amphipod assemblages. Finally, the two species with the most similar phenotypes showed comparable responses to competitors and predators, which suggests that long‐term co‐occurrence via ecological equivalence may also be important in this system. Collectively, our results suggest that a mix of performance tradeoffs and ecological equivalence may allow for higher diversity than expected in amphipod assemblages.     

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.     

A comprehensive framework for the study of species co‐occurrences,nestedness and turnover

Binary presence–absence matrices (rows = species, columns = sites) are often used to quantify patterns of species co‐occurrence, and to infer possible biotic interactions from these patterns. Previous classifications of co‐occurrence patterns as nested, segregated, or modular have led to contradictory results and conclusions. These analyses usually do not incorporate the functional traits of the species or the environmental characteristics of the sites, even though the outcomes of species interactions often depend on trait expression and site quality. Here we address this shortcoming by developing a method that incorporates realized functional and environmental niches, and relates them to species co‐occurrence patterns. These niches are defined from n‐dimensional ellipsoids, and calculated from the n eigenvectors and eigenvalues of the variance–covariance matrix of measured environmental or trait variables. Average niche overlap among species and the spatial distribution of niches define a triangle plot with vertices of species segregation (low niche overlap), nestedness (high niche overlap), and modular co‐occurrence (clusters of overlapping niches). Applying this framework to temperate understorey plant communities in southwest Poland, we found a consistent modular structure of species occurrences, a pattern not detected by conventional presence–absence analysis. These results suggest that, in our case study, habitat filtering is the most important process structuring understorey plant communities. Furthermore, they demonstrate how incorporating trait and environmental data into co‐occurrence analysis improves pattern detection and provides a stronger theoretical framework for understanding community structure.