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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. 

Protected areas serve to preserve the remaining biodiversity on our planet. However, today, only about 14% of terrestrial lands are protected, which will not be sufficient to support the planet’s fabric of life into the future ( 1 , 2 ). Humans continue to encroach on the habitats of many plants and animals. Simultaneously, the environmental conditions within protected areas are changing because of shifting climates, pollution, and invasive species, which all fundamentally alter ecosystems globally. To effectively conserve biodiversity, researchers and policy-makers must critically reexamine both the lands being preserved and the protection strategies being used in conservation. On pages 1094 and 1101 of this issue, Allan et al. ( 3 ) and Brennan et al. ( 4 ), respectively, evaluate the preservation capacity of today’s protected areas in different but complementary ways. Allan et al. estimate the minimum land area necessary to support today’s terrestrial biodiversity, whereas Brennan et al. identify the connectedness necessary to allow wildlife to successfully adapt to global change. 

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.

 

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.