Patterns Of Species Association Research Articles

Functional diversity and spatial association analyses at different spatial scales reveal no changes in community assembly processes along an aridity gradient in the Atacama Desert

The structuring of plant assemblages along environmental gradients is typically explained by shifts from competition (limiting similarity) to environmental filtering as the environment becomes more stressful. However, facilitation, weaker-competitor exclusion, environmental heterogeneity, and the colonization-competition tradeoff can also structure plant assemblages along gradients. These assembly processes act on different plant traits and organs, and their prevalence varies with respect to the spatial scale. Using patterns of functional diversity, coupled with patterns of species association at two spatial scales, here we discern the assembly processes that structure shrub communities in four localities along an aridity gradient of the Atacama Desert. At each site, we calculated functional dispersion indexes for above- and below-ground traits, and patterns of species association at a patch and neighborhood scale. Our results revealed that at the patch scale in intermediate levels of aridity, the dominant assembly process was within-site environmental heterogeneity. At the neighborhood scale, communities are assembled mainly through random processes. Nonetheless, in some communities, the dominant assembly process was competition via limiting similarity or exclusion of the weaker competitor, and these did not change along the gradient. Together, these results reveal that environmental heterogeneity and competition are the main drivers of plant community assembly in a hyper-arid environment.

Patterns of Forest Species Association in a Broadleaf Forest in Romania

Ecological patterns of species distribution can reveal essential information on the spatial and functional relationship between species or species and their environment. Various approaches can be used to assess species associations, and our study aimed to compare three methods at different scales: the co-occurrence indices for binary presence–absence data, principal component analysis (PCA) on species abundance and point process analysis. Our goal was to gain a deeper understanding of the species’ co-occurrence patterns and notice if the three methods capture roughly the same spatial distribution trends. Our observational study of the analysed sapling community displayed several positive relationships between species (e.g., the association between ash and linden). However, many relationships were inconsistent across different scales. Furthermore, attraction between species was more prevalent than repulsion. Overall, there is a positive association trend, with more relationships being significantly positive across all scales. This trend is consistent with other recent studies of tree–species interaction. Nonetheless, the results suggest that the scale significantly influences spatial patterns of associations. Positive associations tend to be more prevalent on larger scales, while negative associations are more commonly found on smaller scales, regardless of the analysis method used. While the PCA results are less consistent, the point process analysis allowed us to detect more refined patterns of species associations based on the distance of their interaction. In addition, the binary presence–absence analysis provided solid results, with a coarser spatial perspective but with significantly less sampling effort.

Interkingdom Plant–Soil Microbial Ecological Network Analysis under Different Anthropogenic Impacts in a Tropical Rainforest

Plants and their associated soil microorganisms interact with each other and form complex relationships. The effects of slash-and-burn agriculture and logging on aboveground plants and belowground microorganisms have been extensively studied, but research on plant–microbial interkingdom ecological networks is lacking. In this study, using old growth forest as a control, we used metagenomic data (ITS and 16S rRNA gene amplified sequences) and plant data to obtain interdomain species association patterns for three different soil disturbance types (slash-and-burn, clear cutting and selective cutting) in a tropical rainforest based on interdomain ecological network (IDEN) analysis. Results showed that the soil bacterial–fungal and plant–microbe ecological networks had different topological properties among the three forest disturbance types compared to old growth forest. More nodes, links, higher modularity and negative proportion were found in the selective cutting stand, indicating higher stability with increasing antagonistic relationships and niche differentiation. However, the area of slash-and-burn forest yield opposite results. Network module analysis indicated that different keystone species were found in the four forest types, suggesting alternative stable states among them. Different plant species had more preferential associations with specific fungal taxa than bacterial taxa at the genus level and plant–microbe associations lagged behind bacterial–fungal associations. Overall, compared with old growth forests, the bacterial–fungal and plant–microbe ecological networks in the slash-and-burn and clear cutting stands were simpler, while the network in the selective cutting stand was more complex. Understanding the relationships between aboveground plants and belowground microorganisms under differing disturbance patterns in natural ecosystems will help in better understanding the surrounding ecosystem functions of ecological networks.

Metacommunity dynamics and the detection of species associations in co‐occurrence analyses: Why patch disturbance matters

Abstract Many statistical methods attempt to detect species associations—and so infer interspecific interactions—from species co‐occurrence patterns. Habitat heterogeneity and out‐of‐equilibrium colonization histories are well recognized as potentially causing species associations, even when interactions are absent. The potential for patch disturbance, a classical component of metacommunity dynamics, to also drive spurious species associations has however been overlooked. Using a new general metacommunity model, we derive mathematical predictions regarding how patch disturbance would affect the patterns of species associations detected in ‘null’ co‐occurrence matrices. We also conduct numerical simulations to test our predictions and to compare the performance of several widespread statistical methods, including direct tests of pairwise independence, matrix permutation approaches and joint species distribution modelling. We show how classical metacommunity dynamics can produce statistical associations, both positive and negative, even when species do not interact, when there is no habitat heterogeneity, and at equilibrium. This occurs as soon as there is some rate of patch disturbance (i.e. simultaneous extinction of several species in a patch) and/or a finite life span of patches, a common feature of a broad range of plant, animal or microbial systems. Patch disturbance can compromise species co‐occurrence analyses and cause the artefactual detection of species associations if not taken into account. Including patch age (i.e. the time since the last patch disturbance event) as a covariate in a joint species distribution model can resolve the artefact. However, this requires additional data that often are not available in practice. We argue that the consequences of patch disturbance should not be underestimated when analysing species distribution patterns in metacommunity‐like systems. Read the free Plain Language Summary for this article on the Journal blog.

Different spatiotemporal dynamics, ecological drivers and assembly processes of bacterial, archaeal and fungal communities in brackish-saline groundwater

The presence of brackish-saline groundwater (BSG) poses great harms for human health, agricultural and industrial activity. Understanding how the major environmental features in BSG determine microbiota coalescence is crucial for groundwater monitoring optimization. Based on metabarcoding analysis of 242 PCR-amplified samples, we provided the first blueprints about distinct spatiotemporal distributions, ecological drivers and assembly processes of bacterial, archaeal and fungal communities in BSG obtained from new-constructed wells at Xiong'an New Area, China. Our study demonstrated that bacterial and archaeal communities exhibited significant spatial turnovers, while fungal community displayed the most obvious seasonal variation. Environmental filtering drove bacterial compositions more than those of archaea and fungi. Total dissolved solids (TDS), one of the most critical hydrochemical factors for salinization, had a stronger effect on bacterial spatiotemporal turnover than on those of the other two taxonomic groups, while chemical oxygen demand (CODMn) was more significantly associated with prokaryotic community variations. Bacterial and archaeal taxa dominated the metacommunity network and connected closely, and TDS was mostly related to archaeal subnetwork topological features, suggesting a significant influence of TDS on species association patterns within archaea. Specific functional guilds like bacterial nitrite oxidation, anammox, and archaeal methanogenesis were enriched in lower-TDS habitats, while higher TDS favored bacterial communities involved in dark oxidation of sulfur compounds, fumarate respiration, and cellulolysis. Finally, we confirmed that bacterial and archaeal assembly processes were governed by determinism in each season, and that of fungi was more regulated by stochasticity. Higher TDS was speculated to lead bacterial assembly more deterministic and that of fungi more random. Together, these findings provided an integrate theoretical framework about the unique responses of the three life domains to brackish-saline stress, and had important implications for microbial ecological prediction in groundwater.

Biotic homogenisation in bird communities leads to large‐scale changes in species associations

The impact of global change on biodiversity is commonly assessed in terms of changes in species distributions, community richness and community composition. Whether and how much associations between species are also changing is much less documented. In this study, we quantify changes in large‐scale patterns of species associations in bird communities in relation to changes in species composition. We use network approaches to build three community‐aggregated indices reflecting complementary aspects of species association networks. We characterise the spatio–temporal dynamics of these indices using a large‐scale and high‐resolution dataset of bird co‐abundances of 109 species monitored for 17 years (2001–2017) from 1969 sites across France. We finally test whether spatial and temporal changes in species association networks are related to species homogenisation estimated as the spatio–temporal dynamics of species turnover (β‐diversity) and community generalism (community generalisation index). The consistency of these relationships is tested across three main habitats, namely woodland, grassland and human settlements. We document a directional change in association‐based indices in response to modifications in species turnover and community generalism in space and time. Weaker associations and sparser networks were related to lower spatial species turnover and higher community generalism, suggesting an overlooked aspect of biotic homogenisation affecting species associations and may also have an impact on species interactions. We report that this overall pattern is not constant across habitats, with opposite relationships between biotic homogenisation and change in species association networks in urban versus forest communities suggesting distinct homogenisation processes. Although species associations contain only partial signatures of species interactions, our study highlights that biotic homogenisation translates to finer changes in community structure by affecting the number, strength and type of species associations.

Environmental, anthropogenic, and spatial factors affecting species composition and species associations in helminth communities of water frogs (Pelophylax esculentus complex) in Latvia.

We investigated factors affecting species composition and patterns of species associations in parasite communities of water frogs (Pelophylax esculentus complex), applying the distance-based redundancy analysis for component communities (assemblages harboured by host populations) and Markov random fields modelling for infracommunities (assemblages harboured by individual hosts), respectively. We asked (a) What are the relative effects of variation in environmental, land use (i.e., anthropogenic), and spatial factors on the variation in the species composition of component communities (i.e., in a locality)? and (b) What is the dominant pattern of species associations in infracommunities (in a host individual), and how do these associations vary along environmental and/or anthropogenic gradients? In component communities, the greatest portion of variation in helminth species composition was explained by the combined effects of space, anthropogenic pressure, and NDVI, with the pure effect of the spatial predictor being much stronger than the effects of the remaining predictors. In infracommunities, the probability of occurrence of some, but not all, helminth species depended on the occurrence of another species, with the numbers of negative and positive co-occurrences being equal. The strength and/or sign of associations of some species pairs were spatially stable, whereas interactions between other species pairs varied along the gradient of the amount of green vegetation, from negative to positive and vice versa. We conclude that the processes in parasite infracommunities and component communities in frogs are intertwined, with both bottom-up and top-down effects acting at different hierarchical scales.

Seed trapping or a nurse effect? Disentangling the drivers of fine-scale plant species association patterns in a windy environment

Seed trapping or a nurse effect? Disentangling the drivers of fine-scale plant species association patterns in a windy environment

Spatiotemporal patterns of variability in the abundance and distribution of winter-spawned pelagic juvenile rockfish in the California Current.

Rockfish are an important component of West Coast fisheries and California Current food webs, and recruitment (cohort strength) for rockfish populations has long been characterized as highly variable for most studied populations. Research efforts and fisheries surveys have long sought to provide greater insights on both the environmental drivers, and the fisheries and ecosystem consequences, of this variability. Here, variability in the temporal and spatial abundance and distribution patterns of young-of-the-year (YOY) rockfishes are described based on midwater trawl surveys conducted throughout the coastal waters of California Current between 2001 and 2019. Results confirm that the abundance of winter-spawning rockfish taxa in particular is highly variable over space and time. Although there is considerable spatial coherence in these relative abundance patterns, there are many years in which abundance patterns are very heterogeneous over the scale of the California Current. Results also confirm that the high abundance levels of YOY rockfish observed during the 2014–2016 large marine heatwave were largely coastwide events. Species association patterns of pelagic YOY for over 20 rockfish taxa in space and time are also described. The overall results will help inform future fisheries-independent surveys, and will improve future indices of recruitment strength used to inform stock assessment models and marine ecosystem status reports.

Alterations of circulating bacterial DNA in colorectal cancer and adenoma: A proof-of-concept study.

The gut microbiota is closely associated with colorectal neoplasia. While most metagenomics studies utilized fecal samples, circulating bacterial DNA in colorectal neoplasia patients remained unexplored. This proof-of-concept study aims to characterize alterations of circulating bacterial DNA in colorectal neoplasia patients. We performed WGS of plasma samples from 25 colorectal cancer (CRC) patients, 10 colorectal adenoma (CRA) patients and 22 healthy controls (HC). Bacterial relative abundance was measured by removing the host genome and mapping reads into bacterial genomes. By diversity analysis, we found plasma samples required less sample size to approach saturation than fecal samples, and species diversity in HC was slightly higher compared with CRC/CRA patients. The majority of circulating bacterial DNA came from bacterial genera which commonly associated with gastrointestine and oral tract. By differential analysis, a total of 127 significant species between CRC patients and HC were identified, on which basis 28 species with top predictive ability were selected and showed promise in preliminary discrimination between CRC/CRA and HC. In CRA patients, relative abundance of the selected 28 species more closely resembled those in CRC patients than HC. By comparing with fecal metagenomics studies, we found there was moderate positive correlation between fold changes of the overlapped fecal and circulating bacterial DNA. Finally, species correlation analysis revealed that CRC and HC displayed distinct patterns of species association. In conclusion, this study demonstrated alterations of circulating bacterial DNA in colorectal neoplasia patients, which had the potential to become non-invasive biomarkers for colorectal neoplasia screening and early diagnosis.

Null model analyses of temporal patterns of bird assemblages and their foraging guilds revealed the predominance of positive and random associations.

Patterns of species associations have been commonly used to infer interactions among species. If species positively co‐occur, they may form predominantly neutral assemblages, and such patterns suggest a relatively weak role for compensatory dynamics. The main objective of this study was to test this prediction on temporal samples of bird assemblages (n = 19, 10–57 years) by the presence/absence and quantitative null models on assemblage and guild levels. These null model outcomes were further analyzed to evaluate the effects of various data set characteristics on the outcomes of the null models. The analysis of two binary null models in combination with three association indices revealed 20% with significant aggregations, 61% with random associations, and only 19% with significant segregations (n = 95 simulations). The results of the quantitative null model simulations detected more none‐random associations: 61% aggregations, 6% random associations, and 33% segregations (n = 114 simulations). Similarly, quantitative analyses on guild levels showed 58% aggregations, 20% segregations, and 22% random associations (n = 450 simulations). Bayesian GLMs detected that the outcomes of the binary and quantitative null models applied to the assemblage analyses were significantly related to census plot size, whereas the outcomes of the quantitative analyses were also related to the mean population densities of species in the data matrices. In guild‐level analyses, only 9% of the GLMs showed a significant influence of matrix properties (plot size, matrix size, species richness, and mean species population densities) on the null model outcomes. The results did not show the prevalence of negative associations that would have supported compensatory dynamics. Instead, we assume that a similar response of the majority of species to climate‐driven and stochastic factors may be responsible for the revealed predominance of positive associations.

A comparative evaluation of five common pairwise tests of species association.

Researchers have long viewed patterns of species association as key to understanding the processes that structure communities. Community-level tests of species association have received the most attention; however, pairwise species associations may offer greater opportunity for linking patterns to specific mechanisms. Although several tests of pairwise association have been developed, there remain gaps in our understanding of their performance. Consequently, it is unclear whether these methods reliably detect patterns of association, or if any one method is superior. We maximized association patterns for single species pairs in synthetic community matrices and examined how accurately five pairwise association tests found that pair, while not finding others (i.e., type I and II error rates). All tests are more likely to miss patterns of association than to falsely detect them. When we maximized association for a species pair that included one or more rare or common species, tests were frequently unable to identify that pair as significantly associated. Consequently, these tests are best suited for identifying significant associations between pairs of species that occur in an intermediate number of samples; for such pairs, three of the five tests considered here detected 100% of the pairs for which we maximized associations.

Homogenization of species composition and species association networks are decoupled

AbstractAimEcological communities are composed of both species and the biotic relationships (interactions or spatial associations) among them. Biotic homogenization in species composition (i.e., increased site‐to‐site similarity) is recognized as a common consequence of global change, but less is known about how the similarity of species relationships changes over space and time. Does homogenization of species composition lead to homogenization of species relationships or are the dynamics of species relationships decoupled from changes in species composition?LocationWisconsin, USA.Time period1950–2012.Major taxa studiedVascular plants.MethodsWe used long‐term resurvey data to analyse changes in plant species association patterns between the 1950s and 2000s at 266 sites distributed among three community types in Wisconsin, USA. We used species associations (quantified via local co‐occurrence patterns) to represent one type of relationship among species. Species pairs that co‐occur more or less than expected by chance have positive or negative associations, respectively. We then measured beta diversity in both species composition and species association networks over time and space.ResultsShifts in species associations consistently exceeded the shifts observed in species composition. Less disturbed forests of northern Wisconsin have converged somewhat in species composition but little in species associations. In contrast, forests in central Wisconsin succeeding from pine barrens to closed‐canopy forests have strongly homogenized in both species composition and species associations. More fragmented forests in southern Wisconsin also tended to converge in species composition and in the species’ negative associations, but their positive associations diverged over the last half century. Species composition and associations are generally affected by a similar set of environmental variables. Their relative importance, however, has changed over time.Main conclusionsLong‐term shifts in species relationships appear to be decoupled from shifts in species composition despite being affected by similar environmental variables.

Biotic interactions in species distribution modelling: 10 questions to guide interpretation and avoid false conclusions

AbstractAimRecent studies increasingly use statistical methods to infer biotic interactions from co‐occurrence information at a large spatial scale. However, disentangling biotic interactions from other factors that can affect co‐occurrence patterns at the macroscale is a major challenge.ApproachWe present a set of questions that analysts and reviewers should ask to avoid erroneously attributing species association patterns to biotic interactions. Our questions relate to the appropriateness of data and models, the causality behind a correlative signal, and the problems associated with static data from dynamic systems. We summarize caveats reported by macroecological studies of biotic interactions and examine whether conclusions on the presence of biotic interactions are supported by the modelling approaches used.FindingsIrrespective of the method used, studies that set out to test for biotic interactions find statistical associations in species’ co‐occurrences. Yet, when compared with our list of questions, few purported interpretations of such associations as biotic interactions hold up to scrutiny. This does not dismiss the presence or importance of biotic interactions, but it highlights the risk of too lenient interpretation of the data. Combining model results with information from experiments and functional traits that are relevant for the biotic interaction of interest might strengthen conclusions.Main conclusionsMoving from species‐ to community‐level models, including biotic interactions among species, is of great importance for process‐based understanding and forecasting ecological responses. We hope that our questions will help to improve these models and facilitate the interpretation of their results. In essence, we conclude that ecologists have to recognize that a species association pattern in joint species distribution models will be driven not only by real biotic interactions, but also by shared habitat preferences, common migration history, phylogenetic history and shared response to missing environmental drivers, which specifically need to be discussed and, if possible, integrated into models.

Co-occurrence patterns in a diverse arboreal ant community are explained more by competition than habitat requirements.

A major goal of community ecology is to identify the patterns of species associations and the processes that shape them. Arboreal ants are extremely diverse and abundant, making them an interesting and valuable group for tackling this issue. Numerous studies have used observational data of species co‐occurrence patterns to infer underlying assembly processes, but the complexity of these communities has resulted in few solid conclusions. This study takes advantage of an observational dataset that is unusually well‐structured with respect to habitat attributes (tree species, tree sizes, and vegetation structure), to disentangle different factors influencing community organization. In particular, this study assesses the potential role of interspecific competition and habitat selection on the distribution patterns of an arboreal ant community by incorporating habitat attributes into the co‐occurrence analyses. These findings are then contrasted against species traits, to explore functional explanations for the identified community patterns. We ran a suite of null models, first accounting only for the species incidence in the community and later incorporating habitat attributes in the null models. We performed analyses with all the species in the community and then with only the most common species using both a matrix‐level approach and a pairwise‐level approach. The co‐occurrence patterns did not differ from randomness in the matrix‐level approach accounting for all ant species in the community. However, a segregated pattern was detected for the most common ant species. Moreover, with the pairwise approach, we found a significant number of negative and positive pairs of species associations. Most of the segregated associations appear to be explained by competitive interactions between species, not habitat affiliations. This was supported by comparisons of species traits for significantly associated pairs. These results suggest that competition is the most important influence on the distribution patterns of arboreal ants within the focal community. Habitat attributes, in contrast, showed no significant influence on the matrix‐wide results and affected only a few associations. In addition, the segregated pairs shared more biological characteristic in common than the aggregated and random ones.

Relations of Alpine Plant Communities across Environmental Gradients: Multilevel versus Multiscale Analyses

Alpine plant communities vary, and their environmental covariates could influence their response to climate change. A single multilevel model of how alpine plant community composition is determined by hierarchical relations is compared to a separate examination of those relations at different scales. Nonmetric multidimensional scaling of species cover for plots in four regions across the Rocky Mountains created dependent variables. Climate variables are derived for the four regions from interpolated data. Plot environmental variables are measured directly and the presence of thirty-seven site characteristics is recorded and used to create additional independent variables. Multilevel and best subsets regressions are used to determine the strength of the hypothesized relations. The ordinations indicate structure in the assembly of plant communities. The multilevel analyses, although revealing significant relations, provide little explanation; of the site variables, those related to site microclimate are most important. In multiscale analyses (whole and separate regions), different variables are better explanations within the different regions. This result indicates weak environmental niche control of community composition. The weak relations of the structure in the patterns of species association to the environment indicates that either alpine vegetation represents a case of the neutral theory of biogeography being a valid explanation or that it represents disequilibrium conditions. The implications of neutral theory and disequilibrium explanations are similar: Response to climate change will be difficult to quantify above equilibrium background turnover.

Checkerboards and Missing Species Combinations: Are Ecological Communities Assembled by Chance?

How are communities of plants and animals organized in nature? This is a challenging question, because there are too many species in most communities to study this problem experimentally. For example, even with only three species (A, B, and C), eight different “communities” or distinct species combinations can be formed, based on the presence or absence of each species in the community: 0, A, B, C, AB, BC, AC, and ABC. With S species, 2S possible species combinations can be formed, which is far too many for a wieldy experiment. That is why ecologists have often taken a different tack. They use so-called “natural experiments” in which they let nature do the work and generate the replicates. Islands in an archipelago, for example, are often treated as statistical replicates. The patterns of species association among a set of islands may provide important clues for how species interact. The data for such an analysis can be represented as a binary matrix in which each row is a species, each column is an island (or site), and the matrix entries represent the presence (1) or absence (0) of a particular species on a particular island. For a matrix M with i = 1 to S species and j = 1 to R replicate islands, Mij indicates the presence or absence of species i on island j. It is too much work to identify all of the different species of vertebrates, invertebrates, plants, and microbes on a single island, much less in an entire archipelago. Instead, ecologists have usually restricted Checkerboards and Missing Species Combinations: Are Ecological Communities Assembled by Chance?

Seasonal patterns of mixed species groups in large East African mammals.

Mixed mammal species groups are common in East African savannah ecosystems. Yet, it is largely unknown if co-occurrences of large mammals result from random processes or social preferences and if interspecific associations are consistent across ecosystems and seasons. Because species may exchange important information and services, understanding patterns and drivers of heterospecific interactions is crucial for advancing animal and community ecology. We recorded 5403 single and multi-species clusters in the Serengeti-Ngorongoro and Tarangire-Manyara ecosystems during dry and wet seasons and used social network analyses to detect patterns of species associations. We found statistically significant associations between multiple species and association patterns differed spatially and seasonally. Consistently, wildebeest and zebras preferred being associated with other species, whereas carnivores, African elephants, Maasai giraffes and Kirk's dik-diks avoided being in mixed groups. During the dry season, we found that the betweenness (a measure of importance in the flow of information or disease) of species did not differ from a random expectation based on species abundance. In contrast, in the wet season, we found that these patterns were not simply explained by variations in abundances, suggesting that heterospecific associations were actively formed. These seasonal differences in observed patterns suggest that interspecific associations may be driven by resource overlap when resources are limited and by resource partitioning or anti-predator advantages when resources are abundant. We discuss potential mechanisms that could drive seasonal variation in the cost-benefit tradeoffs that underpin the formation of mixed-species groups.

New parasitoid-predator associations: female parasitoids do not avoid competition with generalist predators when sharing invasive prey.

Optimal habitat selection is essential for species survival in ecosystems, and interspecific competition is a key ecological mechanism for many observed species association patterns. Specialized animal species are commonly affected by resource and interference competition with generalist and/or omnivorous competitors, so avoidance behavior could be expected. We hypothesize that specialist species may exploit broad range cues from such potential resource competitors (i.e., cues possibly common to various generalist and/or omnivorous predators) to avoid costly competition regarding food or reproduction, even in new species associations. We tested this hypothesis by studying short-term interactions between a native larval parasitoid and a native generalist omnivorous predator recently sharing the same invasive host/prey, the leaf miner Tuta absoluta. We observed a strong negative effect of kleptoparasitism (food resource stealing) instead of classical intraguild predation on immature parasitoids. There was no evidence that parasitoid females avoided the omnivorous predator when searching for oviposition sites, although we studied both long- and short-range known detection mechanisms. Therefore, we conclude that broad range cue avoidance may not exist in our biological system, probably because it would lead to too much oviposition site avoidance which would not be an efficient and, thus, beneficial strategy. If confirmed in other parasitoids or specialist predators, our findings may have implications for population dynamics, especially in the current context of increasing invasive species and the resulting creation of many new species associations.

A framework for evaluating the influence of climate, dispersal limitation, and biotic interactions using fossil pollen associations across the late Quaternary

Environmental conditions, dispersal lags, and interactions among species are major factors structuring communities through time and across space. Ecologists have emphasized the importance of biotic interactions in determining local patterns of species association. In contrast, abiotic limits, dispersal limitation, and historical factors have commonly been invoked to explain community structure patterns at larger spatiotemporal scales, such as the appearance of late Pleistocene no‐analog communities or latitudinal gradients of species richness in both modern and fossil assemblages. Quantifying the relative influence of these processes on species co‐occurrence patterns is not straightforward. We provide a framework for assessing causes of species associations by combining a null‐model analysis of co‐occurrence with additional analyses of climatic differences and spatial pattern for pairs of pollen taxa that are significantly associated across geographic space.We tested this framework with data on associations among 106 fossil pollen taxa and paleoclimate simulations from eastern North America across the late Quaternary. The number and proportion of significantly associated taxon pairs increased over time, but only 449 of 56 194 taxon pairs were significantly different from random. Within this significant subset of pollen taxa, biotic interactions were rarely the exclusive cause of associations. Instead, climatic or spatial differences among sites were most frequently associated with significant patterns of taxon association. Most taxon pairs that exhibited co‐occurrence patterns indicative of biotic interactions at one time did not exhibit significant associations at other times. Evidence for environmental filtering and dispersal limitation was weakest for aggregated pairs between 16 and 11 kyr BP, suggesting enhanced importance of positive species interactions during this interval. The framework can thus be used to identify species associations that may reflect biotic interactions because these associations are not tied to environmental or spatial differences. Furthermore, temporally repeated analyses of spatial associations can reveal whether such associations persist through time.