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.

A major focus in evolutionary biology is to understand how the evolution of organisms relates to changes in their physical environment. In the terrestrial realm, the interrelationships among climate, vegetation, and herbivores lie at the heart of this question. Here we introduce and test a scoring scheme for functional traits present on the worn surfaces of large mammalian herbivore teeth to capture their relationship to environmental conditions. We modeled local precipitation, temperature, primary productivity, and vegetation index as functions of dental traits of large mammal species in 13 national parks in Kenya over the past 60 y. We found that these dental traits can accurately estimate local climate and environment, even at small spatial scales within areas of relatively uniform climate (within two ecoregions), and that they predict limiting conditions better than average conditions. These findings demonstrate that the evolution of key functional properties of organisms may be more reflective of demands during recurring adverse episodes than under average conditions or during isolated severe events.herbivorous mammals | dental traits | ecometrics | Kenya | paleoecology

Large mammals are at high risk of extinction globally. To understand the consequences of their demise for community assembly, we tracked community structure through the end-Pleistocene megafaunal extinction in North America. We decomposed the effects of biotic and abiotic factors by analyzing co-occurrence within the mutual ranges of species pairs. Although shifting climate drove an increase in niche overlap, co-occurrence decreased, signaling shifts in biotic interactions. Furthermore, the effect of abiotic factors on co-occurrence remained constant over time while the effect of biotic factors decreased. Biotic factors apparently played a key role in continental-scale community assembly before the extinctions. Specifically, large mammals likely promoted co-occurrence in the Pleistocene, and their loss contributed to the modern assembly pattern in which co-occurrence frequently falls below random expectations.

Understanding how ecological communities are organized and how they change through time is critical to predicting the effects of climate change. Recent work documenting the co-occurrence structure of modern communities found that most significant species pairs co-occur less frequently than would be expected by chance. However, little is known about how co-occurrence structure changes through time. Here we evaluate changes in plant and animal community organization over geological time by quantifying the co-occurrence structure of 359,896 unique taxon pairs in 80 assemblages spanning the past 300 million years. Co-occurrences of most taxon pairs were statistically random, but a significant fraction were spatially aggregated or segregated. Aggregated pairs dominated from the Carboniferous period (307 million years ago) to the early Holocene epoch (11,700 years before present), when there was a pronounced shift to more segregated pairs, a trend that continues in modern assemblages. The shift began during the Holocene and coincided with increasing human population size and the spread of agriculture in North America. Before the shift, an average of 64% of significant pairs were aggregated; after the shift, the average dropped to 37%. The organization of modern and late Holocene plant and animal assemblages differs fundamentally from that of assemblages over the past 300 million years that predate the large-scale impacts of humans. Our results suggest that the rules governing the assembly of communities have recently been changed by human activity.

Interspecific spatial associations (ISA), which include co‐occurrences, segregations, or attractions among two or more species, can provide important insights into the spatial structuring of communities. However, ISA has primarily been examined in the context of understanding interspecific interactions, while other aspects of ISA, including its relations to other biodiversity facets and how it changes in the face of anthropogenic pressures, have been largely neglected. This is likely because it is unclear what makes ISA useful in a biodiversity context, little is known about the theoretical connections between ISA and other biodiversity facets, and there is a confusing variety of approaches to measuring ISA. Here, we first review the metrics of ISA. These include spatially implicit and explicit indices of association for binary, abundance, and point pattern data. We test and compare these approaches on empirical and simulated data, and we provide recommendations for how to use and interpret them in biodiversity science. We argue that measurements of ISA are more informative when they are spatially explicit (i.e., distance dependent). We then review links of ISA to other classical biodiversity facets, such as alpha, beta, and gamma diversity, and show that they mostly fail to reflect changes/variation in ISA, with the exception of average pairwise beta diversity. This underscores the need for a specific focus on ISA in large‐scale biodiversity assessments. Finally, we argue that there are important, and underappreciated, reasons to study ISA that are unrelated to its link to biotic interactions. Specifically, ISA can provide strong tests of biodiversity theories that require multiple patterns to benchmark against, and it can be explored for potentially predictive macroecological patterns.

Comparisons between modern death assemblages and their source communities have demonstrated fidelity to species diversity across a variety of environments and taxonomic groups. However, differential species preservation and collection (including body-size bias) in both modern and fossil death assemblages may still skew the representation of other important ecological characteristics. Here, we move beyond live-dead taxonomic fidelity and focus on the recovery of functional ecology (how species interact with their ecosystem) at the community level for a diverse non-volant mammal community (87 species; Amboseli, Kenya). We use published literature to characterize species, using four functional traits and their associated categorical attributes (i) dietary mode (11 attributes; e.g., browser, grazer), (ii) preferred feeding habitat (16 attributes; e.g., grassland, woodland), (iii) preferred sheltering habitat (17 attributes; e.g., grassland, underground cavity), and (iv) activity time (7 attributes; e.g., diurnal, nocturnal, nocturnally dominated crepuscular). For each functional ecological trait we compare the death assemblage's recovered richness and abundance structure of constituent functional attributes with those of the source community, using Jaccard similarity, Spearman's rho, and the Probability of Interspecific Encounter (evenness). We use Monte Carlo simulations to evaluate whether these empirical comparisons are significantly different from expectations calculated from randomized sampling of species from the source community. Results indicate that although the Amboseli death assemblage is significantly overrepresented by large-bodied species relative to the Amboseli source community, it captures many functional dimensions of the ecosystem within expectations of a randomized collection of species. Additional resampling simulations and logistic regressions further illustrate that the size bias inherent to the Amboseli death assemblage is not a major driver of deviations between the functional ecological properties of the death assemblage and its source community. Finally, the Amboseli death assemblage also enhances our understanding of the mammal community by adding nine species and two functional attributes previously unknown from the ecosystem.

Cities and agricultural fields encroach on the most fertile, habitable terrestrial landscapes, fundamentally altering global ecosystems. Today, 75% of terrestrial ecosystems are considerably altered by human activities, and landscape transformation continues to accelerate. Human impacts are one of the major drivers of the current biodiversity crisis, and they have had unprecedented consequences on ecosystem function and rates of species extinctions for thousands of years. Here we use the fossil record to investigate whether changes in geographic range that could result from human impacts have altered the climatic niches of 46 species covering six mammal orders within the contiguous United States. Sixty-seven percent of the studied mammals have significantly different climatic niches today than they did before the onset of the Industrial Revolution. Niches changed the most in the portions of the range that overlap with human-impacted landscapes. Whether by forcible elimination/introduction or more indirect means, large-bodied dietary specialists have been extirpated from climatic envelopes that characterize human-impacted areas, whereas smaller, generalist mammals have been facilitated, colonizing these same areas of the climatic space. Importantly, the climates where we find mammals today do not necessarily represent their past habitats. Without mitigation, as we move further into the Anthropocene, we can anticipate a low standing biodiversity dominated by small, generalist mammals.

Interspecific spatial associations (ISA), which include co-occurrences, segregations, or attractions among two or more species, can provide important insights into the spatial structuring of communities. However, ISA has primarily been examined in the context of understanding interspecific interactions, while other aspects of ISA, including its relations to other biodiversity facets and how it changes in the face of anthropogenic pressures, have been largely neglected. This is likely because it is unclear what makes ISA useful in a biodiversity context, little is known about the theoretical connections between ISA and other biodiversity facets, and there is a confusing variety of approaches to measuring ISA. Here, we first review the metrics of ISA. These include both spatially implicit and explicit indices of association for both binary and abundance data. We test and compare these approaches on empirical and simulated data, and we provide specific recommendations for how to use and interpret them in biodiversity science. We argue that measurements of ISA are more informative when they are spatially explicit (i.e. distance dependent). We then review links of ISA to other classical biodiversity facets, such as alpha, beta, and gamma diversity, and show that they mostly fail to reflect changes/variation in ISA, with the exception of average pair-wise beta diversity. This underscores the need for a specific focus on ISA in large-scale biodiversity assessments. Finally, we argue that there are important, and underappreciated, reasons to study ISA that are unrelated to its link to biotic interactions. Specifically, ISA can provide strong tests of biodiversity theories that require multiple patterns to benchmark against, and it can be explored for potentially predictive macroecological patterns.