TY - JOUR
T1 - Mapping abundance distributions of allergenic tree species in urbanized landscapes
T2 - A nation-wide study for Belgium using forest inventory and citizen science data
AU - Dujardin, Sebastien
AU - Stas, Michiel
AU - Van Eupen, Camille
AU - Aerts, Raf
AU - Hendrickx, Marijke
AU - Delcloo, Andy W.
AU - Duchêne, François
AU - Hamdi, Rafiq
AU - Nawrot, Tim S.
AU - Van Nieuwenhuyse, An
AU - Aerts, Jean Marie
AU - Van Orshoven, Jos
AU - Somers, Ben
AU - Linard, Catherine
AU - Dendoncker, Nicolas
N1 - Funding Information:
Results presented in this study were carried out in the framework of the RespirIT project supported by a national grant from the Belgian Science Policy Office BELSPO (grant nr. BR/154/A1/RespirIT). It was also supported by the Flemish Research Foundation FWO–SB [grant number 1S92118N]. Authors would like to warmly thank S. Bauwens (BIOSE department - Biosytem Engineering, Forest Resources Management, Gembloux Agro-Bio Tech, Université de Liège) as well as L. Govaere (Cel Beheerplanning en Monitoring, Agentschap voor Natuur en Bos, Vlaams Gewest) for their many advices and feedback for selecting and processing forest inventory data. We are also very thankful to C. Visée (Geography Department, UNamur) for contributing to the development of the WebGis application and making abundance distribution maps readily available for download.
Funding Information:
Results presented in this study were carried out in the framework of the RespirIT project supported by a national grant from the Belgian Science Policy Office BELSPO (grant nr. BR/154/A1/RespirIT). It was also supported by the Flemish Research Foundation FWO?SB [grant number 1S92118N]. Authors would like to warmly thank S. Bauwens (BIOSE department - Biosytem Engineering, Forest Resources Management, Gembloux Agro-Bio Tech, Universit? de Li?ge) as well as L. Govaere (Cel Beheerplanning en Monitoring, Agentschap voor Natuur en Bos, Vlaams Gewest) for their many advices and feedback for selecting and processing forest inventory data. We are also very thankful to C. Vis?e (Geography Department, UNamur) for contributing to the development of the WebGis application and making abundance distribution maps readily available for download.
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2022/2
Y1 - 2022/2
N2 - Mapping the distribution of allergenic plants in urbanized landscapes is of high importance to evaluate its impact on human health. However, data is not always available for the allergy-relevant species such as alder, birch, hazel, especially within cities where systematic inventories are often missing or not readily available. This research presents an approach to produce high-resolution abundance maps of allergenic tree species using existing forest inventories and opportunistic open-access citizen science data. Following a two-step approach, we first built species distribution models (SDMs) to predict species habitat suitability, using environmental characteristics as predictors. Second, we used statistical regressions to model the relationships between abundance, the habitat suitability predicted by the SDMs, and additional vegetation cover covariates. The combination of forest inventory data with citizen science data improves the accuracy of abundance distribution models of allergenic tree species. This produces a continuous, 1-hectare resolution map of alder, birch, and hazel showing spatial variations of abundance distributions both within the urban fabric and along the urban–rural gradient. Species abundance modelling can offer a better understanding of the existing and potential future allergy risk posed by green spaces and pave the way for a wide variety of applications at fine-scale, which is indispensable for evidence-based urban green space policy and planning in support of public health.
AB - Mapping the distribution of allergenic plants in urbanized landscapes is of high importance to evaluate its impact on human health. However, data is not always available for the allergy-relevant species such as alder, birch, hazel, especially within cities where systematic inventories are often missing or not readily available. This research presents an approach to produce high-resolution abundance maps of allergenic tree species using existing forest inventories and opportunistic open-access citizen science data. Following a two-step approach, we first built species distribution models (SDMs) to predict species habitat suitability, using environmental characteristics as predictors. Second, we used statistical regressions to model the relationships between abundance, the habitat suitability predicted by the SDMs, and additional vegetation cover covariates. The combination of forest inventory data with citizen science data improves the accuracy of abundance distribution models of allergenic tree species. This produces a continuous, 1-hectare resolution map of alder, birch, and hazel showing spatial variations of abundance distributions both within the urban fabric and along the urban–rural gradient. Species abundance modelling can offer a better understanding of the existing and potential future allergy risk posed by green spaces and pave the way for a wide variety of applications at fine-scale, which is indispensable for evidence-based urban green space policy and planning in support of public health.
KW - Allergenic trees
KW - Citizen science
KW - Forest mapping
KW - Respiratory health
KW - Species distribution modelling
KW - Urban vegetation
UR - http://www.scopus.com/inward/record.url?scp=85118349235&partnerID=8YFLogxK
U2 - 10.1016/j.landurbplan.2021.104286
DO - 10.1016/j.landurbplan.2021.104286
M3 - Article
AN - SCOPUS:85118349235
SN - 0169-2046
VL - 218
JO - Landscape and Urban Planning
JF - Landscape and Urban Planning
M1 - 104286
ER -