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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. 

Abstract Endemic species and species with small ranges are ecologically and evolutionarily distinct and are vulnerable to extinction. Determining which abiotic and biotic factors structure patterns of endemism on continents can advance our understanding of global biogeographic processes, but spatial patterns of mammalian endemism have not yet been effectively predicted and reconstructed. Using novel null model techniques, we reconstruct trends in mammalian endemism and describe the isolated and combined effects of physiographic, ecological, and evolutionary factors on endemism. We calculated weighted endemism for global continental ecoregions and compared the spatial distribution of endemism to niche‐based, geographic null models of endemism. These null models distribute species randomly across continents, simulating their range sizes from their degree of climatic specialization. They isolate the effects of physiography (topography and climate) and species richness on endemism. We then ran linear and structural models to determine how topography and historical climate stability influence endemism. The highest rates of mammalian endemism were found in topographically rough, climatically stable ecoregions with many species. The null model that isolated physiography did not closely approximate the observed distribution of endemism (r² = .09), whereas the null model that incorporated both physiography and species richness did (r² = .59). The linear models demonstrate that topography and climatic stability both influenced endemism values, but that average climatic niche breadth was not highly correlated with endemism. Climate stability and topography both influence weighted endemism in mammals, but the spatial distribution of mammalian endemism is driven by a combination of physiography and species richness. Despite its relationship to individual range size, average climate niche breadth has only a weak influence on endemism. The results highlight the importance of historical biogeographic processes (e.g. centers of speciation) and geography in driving endemism patterns, and disentangle the mechanisms structuring species ranges worldwide. 

Abstract Resilient landscapes have helped maintain terrestrial biodiversity during periods of climatic and environmental change. Identifying the tempo and mode of landscape transitions and the drivers of landscape resilience is critical to maintaining natural systems and preserving biodiversity given today's rapid climate and land use changes. However, resilient landscapes are difficult to recognize on short time scales, as perturbations are challenging to quantify and ecosystem transitions are rare. Here we analyze two components of North American landscape resilience over 20,000 years: residence time and recovery time. To evaluate landscape dynamics, we use plant biomes, preserved in the fossil pollen record, to examine how long a biome type persists at a given site (residence time) and how long it takes for the biome at that site to reestablish following a transition (recovery time). Biomes have a median residence time of only 230–460 years. Only 64% of biomes recover their original biome type, but recovery time is 140–290 years. Temperatures changing faster than 0.5°C per 500 years result in much reduced residence times. Following a transition, biodiverse biomes reestablish more quickly. Landscape resilience varies through time. Notably, short residence times and long recovery times directly preceded the end‐Pleistocene megafauna extinction, resulting in regional destabilization, and combining with more proximal human impacts to deliver a one‐two punch to megafauna species. Our work indicates that landscapes today are once again exhibiting low resilience, foreboding potential extinctions to come. Conservation strategies focused on improving both landscape and ecosystem resilience by increasing local connectivity and targeting regions with high richness and diverse landforms can mitigate these extinction risks. 

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.