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Résumé
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.
langue originale | Anglais |
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Numéro d'article | 104286 |
journal | Landscape and Urban Planning |
Volume | 218 |
Les DOIs | |
Etat de la publication | Publié - févr. 2022 |
Financement
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. 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.
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BRAIN-RespirIT: Evaluation des relations spatio-temporelles entre la santé respiratoire et la biodiversité à l'aide de la technologie portable individuelle
Dujardin, S. (Chercheur), Dendoncker, N. (Responsable du Projet) & Linard, C. (Responsable du Projet)
1/01/16 → 30/09/20
Projet: Recherche