Historical range contractions can predict extinction risk in extant mammals

Borges, Christielly Mendonça; Terribile, Levi Carina; Oliveira, Guilherme de; Lima‐Ribeiro, Matheus S.; Dobrovolski, Ricardo

doi:10.1371/journal.pone.0221439

Cited by 6 publications

(7 citation statements)

References 71 publications

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“…When coupled with richness gradients, these physiographic factors are able to reconstruct the spatial distribution of endemism across the globe. Small‐ranged and endemic species (and mammals in particular) are disproportionately affected by habitat loss and both current and past climate change, making them more vulnerable to extinction than large‐ranged species (Borges et al, 2019; Fritz et al, 2009; Vargas et al, 2020). In our rapidly changing world, understanding these species' responses to both abiotic and biotic pressures is vital to the preservation of global biodiversity (Parmesan, 2006).…”

Section: Discussionmentioning

confidence: 99%

Disentangling the drivers of continental mammalian endemism

Shipley

McGuire

2023

Global Change Biology

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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.

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Section: Discussionmentioning

confidence: 99%

Disentangling the drivers of continental mammalian endemism

Shipley

McGuire

2023

Global Change Biology

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“…Nonetheless, our model cannot account for all existing factors that influence range size and that could potentially change our results. In particular, mammalian distributions today are largely shaped by their palaeoecological histories over the past thousands to millions of years (Borges et al, 2019). While our model includes a variable to address those histories (Table 1, purple shading), that alone does not encompass the variety of past climates, anthropogenic impacts and other factors that have determined where species occur today (Rowan et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

“…For each species, we collected data addressing its biological, climatic, anthropogenic, environmental and palaeoecological attributes (Table 1). We chose complementary attributes that were hypothesized drivers of mammalian movement, dispersal ability or range size in prior studies (see Appendix S1.3) (Borges et al, 2019; Di Marco et al, 2014; Di Marco & Santini, 2015; Gainsbury et al, 2018; Hirt et al, 2017; Kubo et al, 2019; Li et al, 2016; Newmark, 2008; Tucker et al, 2014; Whitmee & Orme, 2013). These attributes are important to consider, because they could confound the relationships of habitat and topographic heterogeneity with range size.…”

Section: Methodsmentioning

confidence: 99%

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Habitat and not topographic heterogeneity constrains the range sizes of African mammals

Lauer

Shipley

McGuire

2023

Journal of Biogeography

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Aim The extinction risks of species are influenced by their geographical range sizes, as species with smaller ranges are more likely to go extinct following disturbance events. Theoretically, heterogeneous landscapes can maintain small‐ranged species, because they facilitate the coexistence of taxa that are each constrained to distinct abiotic conditions. However, we do not fully understand whether this process is more attributable to variation in habitat types (habitat heterogeneity) or physical elevations (topographic heterogeneity) across landscapes. Here, we compare the influences of habitat versus topographic heterogeneity on mammalian range sizes in Africa. Location Africa. Taxon Mammalia. Methods We built a phylogenetic generalized least squares model to predict the range sizes of 1033 mammalian species from their functional traits and abiotic conditions. We assessed how the performance of the model changed when we incorporated measures of the local habitat and, separately, topographic heterogeneity that species experience. Results Habitat and topographic heterogeneity are weakly correlated across Africa (ρ = 0.14). Habitat heterogeneity is inversely related to range size (model coefficient = −0.88). Incorporating habitat heterogeneity significantly decreased the model's AICc, increased its likelihood and increased the proportion of variance that is explained in the range sizes of species. Conversely, topographic heterogeneity is not significantly related to range size and had no impact on the model's AICc, likelihood or predictive performance. This contrast between habitat and topographic heterogeneity is particularly prevalent in carnivorous mammalian clades. Results at multiple spatial resolutions differed minimally. Main Conclusions Our findings advance ecological theory by demonstrating that a landscape's variation in habitats, and not in elevations, relates inversely with mammalian range size and therefore facilitates the coexistence of small‐ranged mammals. Conservation efforts in regions of high habitat heterogeneity will be critical to prevent extinctions in Africa's biodiverse mammalian species.

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“…Climate change poses serious threats to biodiversity and ecosystems, as it imposes shifts in geographical distribution, biotic interactions, phenotypic plasticity and adaptation (Benito Garzón et al, 2019; Gárate‐Escamilla et al, 2019; Thompson et al, 2013). The ability to track climate changes and persist in suitable habitats is crucial for a species to avoid extinction, as future extinction risk is often associated with range contractions (Borges et al, 2019; Urban, 2015). Thus, accurately predicting the potential distributions of species under climate change is essential for designing conservation strategies to protect climate‐vulnerable species (Melo‐Merino et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Accounting for dispersal and intraspecific variation in forecasts of species distribution under climate change

Zhang,

Kubota

2023

Insect Conserv Diversity

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Dispersal and local adaptation play an important role in driving species distributions under climate change. Many studies aim to estimate relationships between species occurrences and environmental variables to predict range shift and biodiversity loss, ignoring dispersal and intraspecific variation contributing to complex spatial and temporal dynamics. We accounted for dispersal and intraspecific variation in forecasts of species distribution under climate change with species distribution models (SDMs) using two cold‐adapted, low‐dispersal Platycerus species (Coleoptera: Lucanidae), each with distinct subspecies distributions, as focus species. The results showed that the subspecies‐level model performed significantly better than the species‐level model when considering dispersal constraints in SDMs. Whether or not dispersal or intraspecific variation is accounted for, the predicted species range of Platycerus albisomni is expected to decrease in the future. For Platycerus takakuwai, accounting for dispersal constraints in SDMs indicated that its potential distribution area would increase at the subspecies level under climate change, but decrease at the species level. These divergent results show that SDMs at the subspecies level can detect impacts of climate change that may be overlooked in species‐level models. Therefore, models that consider intraspecific variation and dispersal constraints may provide a more realistic perspective on the impacts of climate change. Because accurate mapping of potential habitats is needed for conservation purposes, demographic studies should include dispersal explicitly and explore how and when intraspecific variation in dispersal affects local population dynamics. This approach could help evaluate species' habitat shifts, thus enabling suitable conservation strategies.

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Historical range contractions can predict extinction risk in extant mammals

Cited by 6 publications

References 71 publications

Disentangling the drivers of continental mammalian endemism

Disentangling the drivers of continental mammalian endemism

Habitat and not topographic heterogeneity constrains the range sizes of African mammals

Accounting for dispersal and intraspecific variation in forecasts of species distribution under climate change

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