Biotic and abiotic factors predicting the global distribution and population density of an invasive large mammal

Abstract

Biotic and abiotic factors are increasingly acknowledged to synergistically shape broad-scale species distributions. However, the relative importance of biotic and abiotic factors in predicting species distributions is unclear. In particular, biotic factors, such as predation and vegetation, including those resulting from anthropogenic land-use change, are underrepresented in species distribution modeling, but could improve model predictions. Using generalized linear models and model selection techniques, we used 129 estimates of population density of wild pigs (Sus scrofa) from 5 continents to evaluate the relative importance, magnitude, and direction of biotic and abiotic factors in predicting population density of an invasive large mammal with a global distribution. Incorporating diverse biotic factors, including agriculture, vegetation cover, and large carnivore richness, into species distribution modeling substantially improved model fit and predictions. Abiotic factors, including precipitation and potential evapotranspiration, were also important predictors. The predictive map of population density revealed wide-ranging potential for an invasive large mammal to expand its distribution globally. This information can be used to proactively create conservation/management plans to control future invasions. Our study demonstrates that the ongoing paradigm shift, which recognizes that both biotic and abiotic factors shape species distributions across broad scales, can be advanced by incorporating diverse biotic factors.

Mixed ancestry from wild and domestic lineages contributes to the rapid expansion of invasive feral swine

“…The greater invasion potential of populations with admixed wild and domestic origins, relative to populations that descend from distinct lineages, has important implications for both the evolutionary dynamics and management of this IAS. As invasive feral swine are among the most broadly distributed mammals in the world, similar ancestry analyses in other regions could help inform whether the unique combination of phenotypes produced with the hybridization of domestic and wild lineages represents an essential evolutionary shift for free‐range populations of S. scrofa to become invasive (Lewis et al, 2017). Artificial selection exerted over the past 9,000 years has broadened phenotypic variation within S. scrofa beyond that typically found in natural systems.…”

An assessment of human impacts on endangered red pandas (Ailurus fulgens) living in the Himalaya

“…While numerous studies have been conducted to assess habitats, conservation threats, and diets of red pandas at local scales in Nepal (Bista et al, 2017;Bista, Panthi, & Weiskopf, 2018;Panthi et al, 2012Panthi et al, , 2015Panthi et al, , 2017Thapa & Basnet, 2015), few studies have investigated the species distribution and threats to their habitat at national and regional scales (Acharya et al, 2018;Kandel et al, 2015;Thapa et al, 2018). Anthropogenic factors play an important role in shaping the distribution of wildlife species and their habitats (Lewis et al, 2017), and understanding the influence of human activities on endangered species can be key to improving conservation efforts as well as the implementation of national strategies for sustainable development. Although the red panda is facing serious anthropogenic pressure (Acharya et al, 2018;Glatston et al, 2015;Panthi et al, 2017;, previous studies did not thoroughly consider anthropogenic factors when modeling the habitat of this species (Kandel et al, 2015;Thapa et al, 2018).…”

Links between prey assemblages and poison frog toxins: A landscape ecology approach to assess how biotic interactions affect species phenotypes

“…Therefore, it has been hard to predict the combinations of traits emerging from these interactions (Santos et al, 2016). The landscape ecology framework presented here approaches this problem by incorporating data on biotic interactions throughout the range of a focal species, a strategy that has also improved correlative models of species distributions (Lewis et al, 2017;Sanín & Anderson, 2018). Our framework can be extended to a range of systems that have similar structures, including other multitrophic interactions (Del-Claro, 2004;Scherber et al, 2010;Van der Putten, Vet, Harvey, & Wäckers, 2001), geographic coevolutionary mosaics (Greene & McDiarmid, 1981;Mallet & Gilbert, 1995;Symula, Schulte, & Summers, 2001), microbial assemblages (Landesman, Nelson, & Fitzpatrick, 2014;Zomorrodi & Maranas, 2012), and ecosystem services (Allison, 2012;Gossner et al, 2016;Moorhead & Sinsabaugh, 2006).…”