The Importance of the Human Footprint in Shaping the Global Distribution of Terrestrial, Freshwater and Marine Invaders

Abstract

Human activities such as transport, trade and tourism are likely to influence the spatial distribution of non-native species and yet, Species Distribution Models (SDMs) that aim to predict the future broad scale distribution of invaders often rely on environmental (e.g. climatic) information only. This study investigates if and to what extent do human activities that directly or indirectly influence nature (hereafter the human footprint) affect the global distribution of invasive species in terrestrial, freshwater and marine ecosystems. We selected 72 species including terrestrial plants, terrestrial animals, freshwater and marine invasive species of concern in a focus area located in NW Europe (encompassing Great Britain, France, The Netherlands and Belgium). Species Distribution Models were calibrated with the global occurrence of species and a set of high-resolution (9×9 km) environmental (e.g. topography, climate, geology) layers and human footprint proxies (e.g. the human influence index, population density, road proximity). Our analyses suggest that the global occurrence of a wide range of invaders is primarily limited by climate. Temperature tolerance was the most important factor and explained on average 42% of species distribution. Nevertheless, factors related to the human footprint explained a substantial amount (23% on average) of species distributions. When global models were projected into the focus area, spatial predictions integrating the human footprint featured the highest cumulative risk scores close to transport networks (proxy for invasion pathways) and in habitats with a high human influence index (proxy for propagule pressure). We conclude that human related information–currently available in the form of easily accessible maps and databases—should be routinely implemented into predictive frameworks to inform upon policies to prevent and manage invasions. Otherwise we might be seriously underestimating the species and areas under highest risk of future invasions.

Niche modelling of the Chilean recluse spider Loxosceles laeta and araneophagic spitting spider Scytodes globula and risk for loxoscelism in Chile

“…The human footprint was associated mainly with L. laeta , which agrees with the recognized synanthropy of this species, whereas S. globula is found in human dwellings and is also relatively frequent in natural environments (Taucare‐Ríos et al ., ). The human footprint explained 20.6% of the distribution of S. globula and 48.6% of the distribution of L. laeta ; the latter value is very high compared with the average of 21% (Gallardo et al ., ) reported for terrestrial invaders. This indicates that this species may be considered as highly invasive, like other Loxosceles species such as Loxosceles rufescens (Luo & Li, ), and agrees with reports of its introduction into North America, Central America, Finland and Australia (Gonçalves‐de‐Andrade & Tambourgi, ).…”

Machine Learning Model Analysis of Breeding Habitats for the Black-necked Crane in Central Asian Uplands under Anthropogenic Pressures

“…To provide an ecologically meaningful analysis of the conservation gaps of the black-necked crane’s breeding habitats, we used (i) the World Database on Protected Areas (http://www.protectedplanet.net/) to infer an area’s conservation status 32 and (ii) the Human Influence Index (HII; http://sedac.ciesin.columbia.edu/) to infer an area’s human population status 33 . We used HII because extensive unpopulated areas located in this region remain ecologically primitive and therefore should be excluded from conservation gaps, which are generated for revealing the priorities for future conservation efforts 32 .…”

Physiology in ecological niche modeling: using zebra mussel's upper thermal tolerance to refine model predictions through Bayesian analysis

“…Species' geographic distributions are increasingly influenced by climate change and human-mediated dispersal (Walther et al 2009, Keller et al 2014, Gallardo et al 2015 Physiology in ecological niche modeling: using zebra mussel's upper thermal tolerance to refine model predictions through Bayesian analysis Xiao Feng, Ye Liang, Belinda Gallardo and Monica Papeş ) ✉ (fengxiao@email.arizona.edu), Inst. of the Environment, Univ.…”