Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/31345
Title: An evaluation of species distribution models to estimate tree diversity at genus level in a heterogeneous urban-rural landscape
Authors: Stas, Michiel
AERTS, Raf 
Hendrickx, Marijke
Dendoncker, Nicolas
Dujardin, Sebastien
Linard, Catherine
NAWROT, Tim 
Van Nieuwenhuyse, An
Aerts, Jean-Marie
Van Orshoven, Jos
Somers, Ben
Issue Date: 2020
Publisher: ELSEVIER
Source: LANDSCAPE AND URBAN PLANNING, 198 (Art N° 103770)
Abstract: Trees provide ecosystem services that improve the environment and human health. The magnitude of these improvements may be related to tree diversity within green spaces, yet spatially explicit diversity data necessary to investigate such associations are often missing. Here, we evaluate two methods to model tree diversity at genus level based on environmental covariates and presence point data. We aimed to identify the drivers and suitable methods for urban and rural tree diversity models in the heterogeneous region of Flanders, Belgium. We stratified our research area into dominantly rural and dominantly urban areas and developed distribution models for 13 tree genera for both strata as well as for the area as a whole. Occurrence data were obtained from an open-access presence-only database of validated observations of vascular plants. These occurrence data were combined with environmental covariates in MaxEnt models. Tree diversity was modelled by adding up the individual species distribution models. Models in the dominantly rural areas were driven by soil characteristics (soil texture and drainage class). Models in the dominantly urban areas were driven by environmental covariates explaining urban heterogeneity. Nevertheless, the stratification into urban and rural did not contribute to a higher model quality. Generic tree diversity estimates were better when presences derived from distribution models were simply added up (binary stacking, True Positive Rate of 0.903). The application of macro-ecological constraints resulted in an underestimation of generic tree diversity (probability stacking, True Positive Rate of 0.533). We conclude that summing presences derived from species distribution models (binary stacking) is a suitable approach to increase knowledge on regional diversity.
Notes: Stas, M (reprint author), Katholieke Univ Leuven, Div Forest Nat & Landscape, Dept Earth & Environm Sci, Celestijnenlaan 200E-2411, BE-3001 Leuven, Belgium.
michiel.stas@kuleuven.be; raf.aerts@kuleuven.be;
marijke.hendrickx@sciensano.be; nicolas.dendoncker@unamur.be;
sebastien.dujardin@unamur.be; catherine.linard@unamur.be;
tim.nawrot@kuleuven.be; an.vannieuwenhuyse@kuleuven.be;
jean-marie.aerts@kuleuven.be; jos.vanorshoven@kuleuven.be;
ben.somers@kuleuven.be
Other: Stas, M (corresponding author), Katholieke Univ Leuven, Div Forest Nat & Landscape, Dept Earth & Environm Sci, Celestijnenlaan 200E-2411, BE-3001 Leuven, Belgium. michiel.stas@kuleuven.be; raf.aerts@kuleuven.be; marijke.hendrickx@sciensano.be; nicolas.dendoncker@unamur.be; sebastien.dujardin@unamur.be; catherine.linard@unamur.be; tim.nawrot@kuleuven.be; an.vannieuwenhuyse@kuleuven.be; jean-marie.aerts@kuleuven.be; jos.vanorshoven@kuleuven.be; ben.somers@kuleuven.be
Document URI: http://hdl.handle.net/1942/31345
ISSN: 0169-2046
e-ISSN: 1872-6062
DOI: 10.1016/j.landurbplan.2020.103770
ISI #: WOS:000528059000004
Rights: 2020 Elsevier B.V. All rights reserved.
Category: A1
Type: Journal Contribution
Validations: ecoom 2021
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
stas.pdf
  Restricted Access
Published version8.56 MBAdobe PDFView/Open    Request a copy
Stas et al 2020 LURP_OA.pdfPeer-reviewed author version1.2 MBAdobe PDFView/Open
Show full item record

WEB OF SCIENCETM
Citations

12
checked on Mar 21, 2024

Page view(s)

62
checked on Sep 7, 2022

Download(s)

8
checked on Sep 7, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.