@Article{NgSilRimAtzImm:2018:TuKe,
author = "Ng, Wai Tim and Silva, Alexsandro C{\^a}ndido de Oliveira and
Rima, Purity and Atzberger, Clement and Immitzer, Markus",
affiliation = "{University of Natural Resources and Life Sciences (BOKU)} and
{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Kenya
Forestry Research Institute (KEFRI)} and {University of Natural
Resources and Life Sciences (BOKU)} and {University of Natural
Resources and Life Sciences (BOKU)}",
title = "Ensemble approach for potential habitat mapping of invasive
Prosopis spp. in Turkana, Kenya",
journal = "Ecology and Evolution",
year = "2018",
volume = "8",
number = "23",
keywords = "ensemble modeling, expert knowledge, invasive alien species,
Prosopis, species distribution modeling.",
abstract = "Aim: Prosopis spp. are an invasive alien plant species native to
the Americas and well adapted to thrive in arid environments. In
Kenya, several remote\‐sensing studies conclude that the
genus is well established throughout the country and is rapidly in
\‐vading new areas. This research aims to model the
potential habitat of Prosopis spp.by using an ensemble model
consisting of four species distribution models. Furthermore,
environmental and expert knowledge\‐based variables are
assessed.Location: Turkana County, Kenya.Methods: We collected and
assessed a large number of environmental and expert
knowl\‐edge\‐based variables through variable
correlation, collinearity, and bias tests. The varia\‐bles
were used for an ensemble model consisting of four species
distribution models: (a) logistic regression, (b) maximum entropy,
(c) random forest, and (d) Bayesian networks. The models were
evaluated through a block cross\‐validation providing
statistical measures.Results: The best predictors for Prosopis
spp. habitat are distance from water and built\‐up areas,
soil type, elevation, lithology, and temperature seasonality. All
species distribution models achieved high accuracies while the
ensemble model achieved the highest scores. Highly and moderately
suitable Prosopis spp. habitat covers 6% and 9% of the study area,
respectively.Main conclusions: Both ensemble and individual models
predict a high risk of continuedinvasion, confirming local
observations and conceptions. Findings are valuable to
stake\‐holders for managing invaded area, protecting areas
at risk, and to raise awareness.",
doi = "10.1002/ece3.4649",
url = "http://dx.doi.org/10.1002/ece3.4649",
issn = "2045-7758",
language = "en",
targetfile = "ng_ensemble.pdf",
urlaccessdate = "27 abr. 2024"
}