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Modelling Distributions of Rove Beetles in Mountainous Areas Using Remote Sensing Data

Dittrich, Andreas; Roilo, Stephanie; Sonnenschein, Ruth; Cerrato, Cristiana; Ewald, Michael 1; Viterbi, Ramona; Cord, Anna F.
1 Institut für Geographie und Geoökologie (IFGG), Karlsruher Institut für Technologie (KIT)


Mountain ecosystems are biodiversity hotspots that are increasingly threatened by climate and land use/land cover changes. Long-term biodiversity monitoring programs provide unique insights into resulting adverse impacts on plant and animal species distribution. Species distribution models (SDMs) in combination with satellite remote sensing (SRS) data offer the opportunity to analyze shifts of species distributions in response to these changes in a spatially explicit way. Here, we predicted the presence probability of three different rove beetles in a mountainous protected area (Gran Paradiso National Park, GPNP) using environmental variables derived from Landsat and Aster Global Digital Elevation Model data and an ensemble modelling approach based on five different model algorithms (maximum entropy, random forest, generalized boosting models, generalized additive models, and generalized linear models). The objectives of the study were (1) to evaluate the potential of SRS data for predicting the presence of species dependent on local-scale environmental parameters at two different time periods, (2) to analyze shifts in species distributions between the years, and (3) to identify the most important species-specific SRS predictor variables. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000117826
Veröffentlicht am 20.03.2020
DOI: 10.3390/rs12010080
Zitationen: 9
Web of Science
Zitationen: 6
Zitationen: 8
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Geographie und Geoökologie (IFGG)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 2072-4292
KITopen-ID: 1000117826
Erschienen in Remote sensing
Verlag MDPI
Band 12
Heft 1
Seiten Art. Nr.: 80
Vorab online veröffentlicht am 24.12.2019
Nachgewiesen in Dimensions
Web of Science
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