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A remote sensing approach to understanding patterns of secondary succession in tropical forest
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dc.contributor.author | Chraibi, Eric | |
dc.contributor.author | Arnold, Haley | |
dc.contributor.author | Luque, Sandra | |
dc.contributor.author | Deacon, Amy | |
dc.contributor.author | Magurran, Anne E. | |
dc.contributor.author | Féret, Jean-Baptiste | |
dc.date.accessioned | 2021-09-29T12:30:01Z | |
dc.date.available | 2021-09-29T12:30:01Z | |
dc.date.issued | 2021-05-30 | |
dc.identifier | 274387920 | |
dc.identifier | 7ec68555-b552-4b58-b271-dd20660c0bc1 | |
dc.identifier | 000660611100001 | |
dc.identifier | 85107869711 | |
dc.identifier.citation | Chraibi , E , Arnold , H , Luque , S , Deacon , A , Magurran , A E & Féret , J-B 2021 , ' A remote sensing approach to understanding patterns of secondary succession in tropical forest ' , Remote Sensing , vol. 13 , no. 11 , 2148 . https://doi.org/10.3390/rs13112148 | en |
dc.identifier.issn | 2072-4292 | |
dc.identifier.other | Bibtex: rs13112148 | |
dc.identifier.other | Bibtex: rs13112148 | |
dc.identifier.other | ORCID: /0000-0002-0036-2795/work/101217916 | |
dc.identifier.uri | https://hdl.handle.net/10023/24047 | |
dc.description | Funding: E. Chraibi and J.-B. Féret acknowledge financial support from Agence Nationale de la Recherche (BioCop project—ANR-17-CE32-0001-01). A.E. Magurran acknowledges support from the Leverhulme Trust (RPG-2019-402). | en |
dc.description.abstract | Biodiversity monitoring and understanding ecological processes on a global scale is a major challenge for biodiversity conservation. Field assessments commonly used to assess patterns of biodiversity and habitat condition are costly, challenging, and restricted to small spatial scales. As ecosystems face increasing anthropogenic pressures, it is important that we find ways to assess patterns of biodiversity more efficiently. Remote sensing has the potential to support understanding of landscape-level ecological processes. In this study, we considered cacao agroforests at different stages of secondary succession, and primary forest in the Northern Range of Trinidad, West Indies. We assessed changes in tree biodiversity over succession using both field data, and data derived from remote sensing. We then evaluated the strengths and limitations of each method, exploring the potential for expanding field data by using remote sensing techniques to investigate landscape-level patterns of forest condition and regeneration. Remote sensing and field data provided different insights into tree species compositional changes, and patterns of alpha- and beta-diversity. The results highlight the potential of remote sensing for detecting patterns of compositional change in forests, and for expanding on field data in order to better understand landscape-level patterns of forest diversity. | |
dc.format.extent | 19 | |
dc.format.extent | 9324001 | |
dc.language.iso | eng | |
dc.relation.ispartof | Remote Sensing | en |
dc.subject | Diversity indices | en |
dc.subject | Agroforestry | en |
dc.subject | Sentinel-2 | en |
dc.subject | Biodiversity monitoring | en |
dc.subject | Patterns of alpha | en |
dc.subject | Beta-diversity | en |
dc.subject | GE Environmental Sciences | en |
dc.subject | QH301 Biology | en |
dc.subject | SD Forestry | en |
dc.subject | 3rd-DAS | en |
dc.subject.lcc | GE | en |
dc.subject.lcc | QH301 | en |
dc.subject.lcc | SD | en |
dc.title | A remote sensing approach to understanding patterns of secondary succession in tropical forest | en |
dc.type | Journal article | en |
dc.contributor.sponsor | The Leverhulme Trust | en |
dc.contributor.institution | University of St Andrews. School of Biology | en |
dc.contributor.institution | University of St Andrews. Centre for Biological Diversity | en |
dc.contributor.institution | University of St Andrews. Scottish Oceans Institute | en |
dc.contributor.institution | University of St Andrews. Institute of Behavioural and Neural Sciences | en |
dc.contributor.institution | University of St Andrews. St Andrews Sustainability Institute | en |
dc.contributor.institution | University of St Andrews. Centre for Research into Ecological & Environmental Modelling | en |
dc.contributor.institution | University of St Andrews. Fish Behaviour and Biodiversity Research Group | en |
dc.contributor.institution | University of St Andrews. Marine Alliance for Science & Technology Scotland | en |
dc.identifier.doi | 10.3390/rs13112148 | |
dc.description.status | Peer reviewed | en |
dc.identifier.url | https://www.mdpi.com/journal/remotesensing/special_issues/FP_SI_Ecological_Remote_Sensing | en |
dc.identifier.grantnumber | ORPG-8061 | en |
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