Effect of anthropogenic factors, landscape structure, land relief, soil and climate on risk of alien plant invasion at regional scale

Effect of anthropogenic factors, landscape structure, land relief, soil and climate on risk of... We compared the effectiveness of explanatory variables representing different environmental spheres on the risk of alien plant invasion. Using boosted regression trees (BRT), we assessed the effect of anthropogenic factors, soil variables, land relief, climate and landscape structure on neophyte richness (NR) (alien plant species introduced after the 15th century). Data on NR were derived from a 2 × 2 km grid covering a total area of 31,200 km2 of the Carpathian massif and its foreground, Central Europe. Each of the examined environmental spheres explained NR, but their explanatory ability varied more than two-folds. Climatic variables explained the highest fraction of deviation, followed by anthropogenic factors, soil type, land relief and landscape structure. The global model, which incorporated crucial variables from all studied environmental spheres, had the best explanatory ability. However, the explained deviation was far smaller than the sum of the deviations explained by the single-sphere models. The global model showed that the deviation that could be explained by variables representing particular spheres, overlapped. The variables representing landscape structure were not included in the global model as they were found to be redundant. Finally, the climatic variables explained a smaller fraction of the deviation than the anthropogenic factors. The partial dependency plots allowed the assessment of the course of dependencies between NR and particular explanatory variables after eliminating the average effect of all other variables. The relationships were usually curvilinear and revealed some values of environmental variables beyond which NR changed considerably. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Science of the Total Environment Elsevier

Effect of anthropogenic factors, landscape structure, land relief, soil and climate on risk of alien plant invasion at regional scale

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Publisher
Elsevier
Copyright
Copyright © 2018 Elsevier B.V.
ISSN
0048-9697
eISSN
1879-1026
D.O.I.
10.1016/j.scitotenv.2018.01.131
Publisher site
See Article on Publisher Site

Abstract

We compared the effectiveness of explanatory variables representing different environmental spheres on the risk of alien plant invasion. Using boosted regression trees (BRT), we assessed the effect of anthropogenic factors, soil variables, land relief, climate and landscape structure on neophyte richness (NR) (alien plant species introduced after the 15th century). Data on NR were derived from a 2 × 2 km grid covering a total area of 31,200 km2 of the Carpathian massif and its foreground, Central Europe. Each of the examined environmental spheres explained NR, but their explanatory ability varied more than two-folds. Climatic variables explained the highest fraction of deviation, followed by anthropogenic factors, soil type, land relief and landscape structure. The global model, which incorporated crucial variables from all studied environmental spheres, had the best explanatory ability. However, the explained deviation was far smaller than the sum of the deviations explained by the single-sphere models. The global model showed that the deviation that could be explained by variables representing particular spheres, overlapped. The variables representing landscape structure were not included in the global model as they were found to be redundant. Finally, the climatic variables explained a smaller fraction of the deviation than the anthropogenic factors. The partial dependency plots allowed the assessment of the course of dependencies between NR and particular explanatory variables after eliminating the average effect of all other variables. The relationships were usually curvilinear and revealed some values of environmental variables beyond which NR changed considerably.

Journal

Science of the Total EnvironmentElsevier

Published: Jun 1, 2018

References

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