Limits...
The importance of the human footprint in shaping the global distribution of terrestrial, freshwater and marine invaders.

Gallardo B, Zieritz A, Aldridge DC - PLoS ONE (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Aquatic Ecology Group, Department of Zoology, Cambridge University, Cambridge, United Kingdom; Applied and Restoration Ecology Group, Department of Biodiversity and Restoration, Pyrenean Institute of Ecology (IPE-CSIC), Zaragoza, Spain.

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.

No MeSH data available.


Permutation importance of environmental and socio-economic predictors in species distribution models.Variables are ordered by their overall mean importance. T = temperature, PP = precipitation, HII = Human Influence Index, MHI = Marine Human Influence. Bars represent the standard deviation of the mean value. Insert pie-charts summarize the influence of major groups of variables on the distribution of the four taxon-habitat groups. Temperature related variables were most important in explaining invasive species distribution, followed by the human footprint.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4446263&req=5

pone.0125801.g001: Permutation importance of environmental and socio-economic predictors in species distribution models.Variables are ordered by their overall mean importance. T = temperature, PP = precipitation, HII = Human Influence Index, MHI = Marine Human Influence. Bars represent the standard deviation of the mean value. Insert pie-charts summarize the influence of major groups of variables on the distribution of the four taxon-habitat groups. Temperature related variables were most important in explaining invasive species distribution, followed by the human footprint.

Mentions: The AUC of models ranged between 0.90 and 0.99 (average 0.97±0.02), and sensitivity between 0.73 and 1.0 (average 0.91±0.05), thereby suggesting a relatively high performance. The analysis of model outputs grouped by four major habitat-taxon groups revealed certain generalities in the response of terrestrial plant and animal, freshwater and marine invasive species to global environmental and human gradients (see extended results from SDM in S7 and S8 Tables). As expected, temperature related variables explained the largest amount of the potential distribution of the invasive species investigated (average for terrestrial animals = 53.6%, terrestrial plants = 62.5%, freshwater = 45.4%, marine = 26.2%; Fig 1). Aquatic inland organisms, terrestrial plants and terrestrial animals showed a similar response to mean annual temperature (Fig 2A), peaking around 10°C; but different suitability optima at increasing minimum temperatures (Fig 2B). The response of marine invaders to minimum water temperature was variable although it generally peaked at 15°C (Fig 3A).


The importance of the human footprint in shaping the global distribution of terrestrial, freshwater and marine invaders.

Gallardo B, Zieritz A, Aldridge DC - PLoS ONE (2015)

Permutation importance of environmental and socio-economic predictors in species distribution models.Variables are ordered by their overall mean importance. T = temperature, PP = precipitation, HII = Human Influence Index, MHI = Marine Human Influence. Bars represent the standard deviation of the mean value. Insert pie-charts summarize the influence of major groups of variables on the distribution of the four taxon-habitat groups. Temperature related variables were most important in explaining invasive species distribution, followed by the human footprint.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4446263&req=5

pone.0125801.g001: Permutation importance of environmental and socio-economic predictors in species distribution models.Variables are ordered by their overall mean importance. T = temperature, PP = precipitation, HII = Human Influence Index, MHI = Marine Human Influence. Bars represent the standard deviation of the mean value. Insert pie-charts summarize the influence of major groups of variables on the distribution of the four taxon-habitat groups. Temperature related variables were most important in explaining invasive species distribution, followed by the human footprint.
Mentions: The AUC of models ranged between 0.90 and 0.99 (average 0.97±0.02), and sensitivity between 0.73 and 1.0 (average 0.91±0.05), thereby suggesting a relatively high performance. The analysis of model outputs grouped by four major habitat-taxon groups revealed certain generalities in the response of terrestrial plant and animal, freshwater and marine invasive species to global environmental and human gradients (see extended results from SDM in S7 and S8 Tables). As expected, temperature related variables explained the largest amount of the potential distribution of the invasive species investigated (average for terrestrial animals = 53.6%, terrestrial plants = 62.5%, freshwater = 45.4%, marine = 26.2%; Fig 1). Aquatic inland organisms, terrestrial plants and terrestrial animals showed a similar response to mean annual temperature (Fig 2A), peaking around 10°C; but different suitability optima at increasing minimum temperatures (Fig 2B). The response of marine invaders to minimum water temperature was variable although it generally peaked at 15°C (Fig 3A).

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Aquatic Ecology Group, Department of Zoology, Cambridge University, Cambridge, United Kingdom; Applied and Restoration Ecology Group, Department of Biodiversity and Restoration, Pyrenean Institute of Ecology (IPE-CSIC), Zaragoza, Spain.

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.

No MeSH data available.