Understanding how species ranges shift as climates rapidly change informs us how to effectively conserve vulnerable species. Species distribution models (SDMs) are an important method for examining these range shifts. The tools for performing SDMs are ever improving. Here, we present the megaSDM R package. This package facilitates realistic spatiotemporal SDM analyses by incorporating dispersal probabilities, creating time‐step maps of range change dynamics and efficiently handling large datasets and computationally intensive environmental subsampling techniques. Provided a list of species and environmental data, megaSDM synthesizes GIS processing, subsampling methods, MaxEnt modelling, dispersal rate restrictions and additional statistical tools to create a variety of outputs for each species, time period and climate scenario requested. For each of these, megaSDM generates a series of distribution maps and outputs visual representations of statistical data. megaSDM offers several advantages over other commonly used SDM tools. First, many of the functions in megaSDM natively implement parallelization, enabling the package to handle large amounts of data efficiently without the need for additional coding. megaSDM also implements environmental subsampling of occurrences, making the technique broadly available in a way that was not possible before due to computational considerations. Uniquely, megaSDM generates maps showing the expansion and contraction of a species range across all considered time periods (time‐maps), and constrains both presence/absence and continuous suitability maps of species ranges according to species‐specific dispersal constraints. The user can then directly compare non‐dispersal and dispersal‐limited distribution predictions. This paper discusses the unique features and highlights of megaSDM, describes the structure of the package and demonstrates the package's features and the model flow through examples.

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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.

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 endemismhave 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 (r 2 = .09), whereas the null model that incorporated both physiography and species richness did (r 2 = .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.

Cladonia is among the most species-rich genera of lichens globally. Species in this lineage, commonly referred to as reindeer lichens, are ecologically important in numerous regions worldwide. In some locations, species of Cladonia can comprise the dominant groundcover, and are a major food source for caribou and other mammals. Additionally, many species are known to produce substances with antimicrobial properties or other characteristics with potentially important medical applications. This exceptional morphological and ecological variation contrasts sharply with the limited molecular divergence often observed among species. As a new resource to facilitate ongoing and future studies of these important species, we analyse here the sequences of 11 Cladonia mitochondrial genomes, including new mitochondrial genome assemblies and annotations representing nine species: C. apodocarpa, C. caroliniana, C. furcata, C. leporina, C. petrophila, C. peziziformis, C. robbinsii, C. stipitata, and C. subtenuis. These 11 genomes varied in size, intron content, and complement of tRNAs. Genes annotated within these mitochondrial genomes include 15 protein-coding genes, the large and small ribosomal subunits (mtLSU and mtSSU), and 23-26 tRNAs. All Cladonia mitochondrial genomes contained atp9, an important energy transport gene that has been lost evolutionarily in some lichen mycobiont mitochondria. Using a concatenated alignment of five mitochondrial genes (nad2, nad4, cox1, cox2, and cox3), a Bayesian phylogeny of relationships among species was inferred and was consistent with previously published phylogenetic relationships, highlighting the utility of these regions in reconstructing phylogenetic history.ARTICLE HISTORY