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Abstract Mammalian megafauna have been critical to the functioning of Earth’s biosphere for millions of years. However, since the Plio-Pleistocene, their biodiversity has declined concurrently with dramatic environmental change and hominin evolution. While these biodiversity declines are well-documented, their implications for the ecological function of megafaunal communities remain uncertain. Here, we adapt ecometric methods to evaluate whether the functional link between communities of herbivorous, eastern African megafauna and their environments (i.e., functional trait-environment relationships) was disrupted as biodiversity losses occurred over the past 7.4 Ma. Herbivore taxonomic and functional diversity began to decline during the Pliocene as open grassland habitats emerged, persisted, and expanded. In the mid-Pleistocene, grassland expansion intensified, and climates became more variable and arid. It was then that phylogenetic diversity declined, and the trait-environment relationships of herbivore communities shifted significantly. Our results divulge the varying implications of different losses in megafaunal biodiversity. Only the losses that occurred since the mid-Pleistocene were coincident with a disturbance to community ecological function. Prior diversity losses, conversely, occurred as the megafaunal species and trait pool narrowed towards those adapted to grassland environments. 

Abstract Environmental disturbances may prevent ecosystems from consistently performing their critical ecological functions. Two important properties of ecosystems are their resistance and stability, which respectively reflect their capacities to withstand and recover from disturbance events (e.g. droughts, wildfires, pests, etc). Theory suggests that resistant and stable ecosystems possess opposing characteristics, but this has seldom been established across diverse ecosystem attributes or broad spatial scales. Here, we compare the resistance and stability of >1000 protected area ecosystems in Africa to disturbance-induced losses in primary productivity from 2000 to 2019. We quantitatively evaluated each ecosystem such that following disturbances, an ecosystem is more resistant if it experiences lower-magnitude losses in productivity, and more stable if it returns more rapidly to pre-disturbance productivity levels. To compare the characteristics of resistant versus stable ecosystems, we optimized random forest models that use ecosystem attributes (representing their climatic and environmental conditions, plant and faunal biodiversity, and exposure to human impacts) to predict their resistance and, separately, stability values. We visualized each attribute’s relationship with resistance and stability after accounting for all other attributes in the model framework. Ecosystems that are more resistant to disturbances are less stable, and vice versa. The ecosystem attributes with the most predictive power in our models all exhibit contrasting relationships with resistance versus stability. Notably, highly resistant ecosystems are generally more arid and exhibit high habitat heterogeneity and mammalian biodiversity, while highly stable ecosystems are the opposite. We discuss the underlying mechanisms through which these attributes engender resistance or, conversely, stability. Our findings suggest that resistance and stability are fundamentally opposing phenomena. A balance between the two must be struck if ecosystems are to maintain their identity, structure, and function in the face of environmental change. 

Island mammals have influenced ecological and evolutionary theory since Darwin, and many of them provide textbook examples of the dramatic morphological evolution that often occurs in island communities. However, patterns of evolution in the climatic niches of island mammals have yet to be fully explored. Several hypotheses explaining niche divergence in island species have been introduced, linking niche evolution to increased competition among closely related or sympatric species, and as a by‐product of morphological evolution or geographical patterns. Here, we evaluate these hypotheses using closely related species pairs (sister taxa). We characterized the climatic niches of island endemic species and their closest relatives and calculated two metrics of niche divergence between the species (niche overlap and centroid distance). We compared these metrics between island endemics that have island‐dwelling sister taxa and those that have mainland‐dwelling sister taxa. We then related the degree of niche divergence to phylogenetic relatedness between the sister taxa, sympatry, morphological trait differences and island characteristics (isolation, size, age). Overall, despite significant niche divergence across species pairs, we found little evidence that competition or biotic interactions drive large‐scale climatic niche evolution in island mammals. Niche divergence in island‐endemic mammals is not driven by sympatry with their closest relatives, nor is it linked to phylogenetic relatedness. Furthermore, the phenotypic evolution of island‐endemic species does not lead to corresponding evolution in climatic niches. Instead, abiotic, geographical patterns appear to drive niche divergence in these species. Sister taxa that were more geographically isolated from each other had significantly lower niche overlaps. Island‐endemic mammals that live in montane regions likewise diverged from their closest relatives. These results suggest that competition between related species on islands may lead to niche partitioning only on local scales and that niche evolution in island‐endemic mammals may occur primarily in response to geographical patterns. 

Ecometric analyses use the relationships between functional traits and the environment at the community level to quantitatively estimate past climatic and environmental variables at fossil sites. Hypsodonty (tooth crown height) in North American rodent and lagomorph (Glires) communities is correlated with mean annual temperature and annual precipitation. Here, we examine the community hypsodonty of African Glires to test if this relationship translates to a continent with more extreme climates and to quantify paleoprecipitation at important fossil sites. Categorical hypsodonty values were gathered from the literature and museum collections for 94 modern African taxa (88%). We used maximum likelihood to model the ecometric relationship between hypsodonty and annual precipitation. We then produced trait-based estimates of paleoprecipitation for 26 well sampled fossil localities from eastern Africa over the last 5.7 Ma. We confirmed other regional studies by identifying increasing aridity and decreasing annual precipitation (824 mm to 480 mm) in the Late Miocene of Kenya. From the Ethiopian Shungura Formation, we estimated temporal fluctuations in precipitation that correspond with the presence or absence of paleolakes and rivers. Small mammal community hypsodonty illustrates that east African communities have converged towards mesodont means and high standard deviations in response to climate change. 

Endemic (small-ranged) species are distributed non-randomly across the globe. Regions of high topography and stable climates have higher endemism than flat, climatically unstable regions. However, it is unclear how these environmental conditions interact with and filter mammalian traits. Here, we characterize the functional traits of highly endemic mammalian assemblages in multiple ways, testing the hypothesis that these assemblages are trait-filtered (less functionally diverse) and dominated by species with traits associated with small range sizes. Compiling trait data for more than 5000 mammal species, we calculated assemblage means and multidimensional functional metrics to evaluate the distribution of traits across each assemblage. We then related these metrics to the endemism of global World Wildlife Fund ecoregions using linear models and phylogenetic fourth-corner regression. Highly endemic mammalian assemblages had small average body masses, low fecundity, short lifespans and specialized habitats. These traits relate to the stable climate and rough topography of endemism hotspots and to mammals' ability to expand their ranges, suggesting that the environmental conditions of endemism hotspots allowed their survival. Furthermore, species living in endemism hotspots clustered near the edges of their communities’ functional spaces, indicating that abiotic trait filtering and biotic interactions act in tandem to shape these communities. 

Species distribution models (SDMs), which relate recorded observations (presences) and absences or background points to environmental characteristics, are powerful tools used to generate hypotheses about the biogeography, ecology, and conservation of species. Although many researchers have examined the effects of presence and background point distributions on model outputs, they have not systematically evaluated the effects of various methods of background point sampling on the performance of a single model algorithm across many species. Therefore, a consensus on the preferred methods of background point sampling is lacking. Here, we conducted presence-background SDMs for 20 vertebrate species in North America under a variety of background point conditions, varying the number of background points used, the size of the buffer used to constrain the background points around the occurrences, and the percentage of background points sampled within the buffer (“spatial weighting”). We evaluated the accuracy and transferability of the models using Boyce index, overlap with expert-generated range maps, and area overpredicted and underpredicted by the SDM (and AUC for comparability with other studies). SDM performance is highly dependent on the species modelled but is affected by the number and spread of background points. Models with little spatial weighting had high accuracy (overlap values), but extreme extrapolation errors and overprediction. In contrast, SDMs with high transferability (high Boyce index values and low overprediction) had moderate-to-high spatial weighting. These results emphasize the importance of both background points and evaluation metric selection in SDMs. For other, more successful metrics, using many background points with spatial weighting may be preferred for models with large extents. These results can assist researchers in selecting the background point parameters most relevant for their research question, allowing them to fine-tune their hypotheses on the distribution of species through space and time. 

We are in a modern biodiversity crisis that will restructure community compositions and ecological functions globally. Large mammals, important contributors to ecosystem function, have been affected directly by purposeful extermination and indirectly by climate and land-use changes, yet functional turnover is rarely assessed on a global scale using metrics based on functional traits. Using ecometrics, the study of functional trait distributions and functional turnover, we examine the relationship between vegetation cover and locomotor traits for artiodactyl and carnivoran communities. We show that the ability to detect a functional relationship is strengthened when locomotor traits of both primary consumers (artiodactyls, n = 157 species) and secondary consumers (carnivorans, n = 138 species) are combined into one trophically integrated ecometric model. Overall, locomotor traits of 81% of communities accurately estimate vegetation cover, establishing the advantage of trophically integrated ecometric models over single-group models (58 to 65% correct). We develop an innovative approach within the ecometrics framework, using ecometric anomalies to evaluate mismatches in model estimates and observed values and provide more nuance for understanding relationships between functional traits and vegetation cover. We apply our integrated model to five paleontological sites to illustrate mismatches in the past and today and to demonstrate the utility of the model for paleovegetation interpretations. Observed changes in community traits and their associated vegetations across space and over time demonstrate the strong, rapid effect of environmental filtering on community traits. Ultimately, our trophically integrated ecometric model captures the cascading interactions between taxa, traits, and changing environments.