Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring
Biodiversity includes multiscalar and multitemporal structures and processes, with different levels of functional organization, from genetic to ecosystemic levels. One of the mostly used methods to infer biodiversity is based on taxonomic approaches and community ecology theories. However, gathering...
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| Format: | Article |
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British Ecological Society
2017
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| Online Access: | https://eprints.nottingham.ac.uk/49142/ |
| _version_ | 1848797931744788480 |
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| author | Rocchini, Duccio Luque, Sandra Pettorelli, Nathalie Bastin, Lucy Doktor, Daniel Faedi, Nicolo Feilhauer, Hannes Feret, Jean-Baptiste Foody, Giles M. Gavish, Yoni Godinho, Sergio Kunin, William E. Lausch, Angela Leitao, Pedro J. Marcantonio, Matteo Neteler, Markus Ricotta, Carlo Schmidtlein, Sebastian Vihervaara, Petteri Wegmann, Martin Nagendra, Harini |
| author_facet | Rocchini, Duccio Luque, Sandra Pettorelli, Nathalie Bastin, Lucy Doktor, Daniel Faedi, Nicolo Feilhauer, Hannes Feret, Jean-Baptiste Foody, Giles M. Gavish, Yoni Godinho, Sergio Kunin, William E. Lausch, Angela Leitao, Pedro J. Marcantonio, Matteo Neteler, Markus Ricotta, Carlo Schmidtlein, Sebastian Vihervaara, Petteri Wegmann, Martin Nagendra, Harini |
| author_sort | Rocchini, Duccio |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Biodiversity includes multiscalar and multitemporal structures and processes, with different levels of functional organization, from genetic to ecosystemic levels. One of the mostly used methods to infer biodiversity is based on taxonomic approaches and community ecology theories. However, gathering extensive data in the field is difficult due to logistic problems, overall when aiming at modelling biodiversity changes in space and time, which assumes statistically sound sampling schemes. In this view, airborne or satellite remote sensing allow to gather information over wide areas in a reasonable time. Most of the biodiversity maps obtained from remote sensing have been based on the inference of species richness by regression analysis. On the contrary, estimating compositional turnover (beta-diversity) might add crucial information related to relative abundance of different species instead of just richness. Presently, few studies have addressed the measurement of species compositional turnover from space. Extending on previous work, in this manuscript we propose novel techniques to measure beta-diversity from airborne or satellite remote sensing, mainly based on: i) multivariate statistical analysis, ii) the spectral species concept, iii) self-organizing feature maps, iv) multi- dimensional distance matrices, and the v) Rao's Q diversity. Each of these measures allow to solve one or several issues related to turnover measurement. This manuscript is the first methodological example encompassing (and enhancing) most of the available methods for estimating beta-diversity from remotely sensed imagery and potentially relate them to species diversity in the field. |
| first_indexed | 2025-11-14T20:11:43Z |
| format | Article |
| id | nottingham-49142 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:11:43Z |
| publishDate | 2017 |
| publisher | British Ecological Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-491422020-05-04T19:17:15Z https://eprints.nottingham.ac.uk/49142/ Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring Rocchini, Duccio Luque, Sandra Pettorelli, Nathalie Bastin, Lucy Doktor, Daniel Faedi, Nicolo Feilhauer, Hannes Feret, Jean-Baptiste Foody, Giles M. Gavish, Yoni Godinho, Sergio Kunin, William E. Lausch, Angela Leitao, Pedro J. Marcantonio, Matteo Neteler, Markus Ricotta, Carlo Schmidtlein, Sebastian Vihervaara, Petteri Wegmann, Martin Nagendra, Harini Biodiversity includes multiscalar and multitemporal structures and processes, with different levels of functional organization, from genetic to ecosystemic levels. One of the mostly used methods to infer biodiversity is based on taxonomic approaches and community ecology theories. However, gathering extensive data in the field is difficult due to logistic problems, overall when aiming at modelling biodiversity changes in space and time, which assumes statistically sound sampling schemes. In this view, airborne or satellite remote sensing allow to gather information over wide areas in a reasonable time. Most of the biodiversity maps obtained from remote sensing have been based on the inference of species richness by regression analysis. On the contrary, estimating compositional turnover (beta-diversity) might add crucial information related to relative abundance of different species instead of just richness. Presently, few studies have addressed the measurement of species compositional turnover from space. Extending on previous work, in this manuscript we propose novel techniques to measure beta-diversity from airborne or satellite remote sensing, mainly based on: i) multivariate statistical analysis, ii) the spectral species concept, iii) self-organizing feature maps, iv) multi- dimensional distance matrices, and the v) Rao's Q diversity. Each of these measures allow to solve one or several issues related to turnover measurement. This manuscript is the first methodological example encompassing (and enhancing) most of the available methods for estimating beta-diversity from remotely sensed imagery and potentially relate them to species diversity in the field. British Ecological Society 2017-11-11 Article PeerReviewed Rocchini, Duccio, Luque, Sandra, Pettorelli, Nathalie, Bastin, Lucy, Doktor, Daniel, Faedi, Nicolo, Feilhauer, Hannes, Feret, Jean-Baptiste, Foody, Giles M., Gavish, Yoni, Godinho, Sergio, Kunin, William E., Lausch, Angela, Leitao, Pedro J., Marcantonio, Matteo, Neteler, Markus, Ricotta, Carlo, Schmidtlein, Sebastian, Vihervaara, Petteri, Wegmann, Martin and Nagendra, Harini (2017) Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring. Methods in Ecology and Evolution . ISSN 2041-210X (In Press) Beta-diversity Kohonen self-organising feature maps Rao's Q diversity index remote sensing satellite imagery Sparse Generalized Dissimilarity Model spectral species concept |
| spellingShingle | Beta-diversity Kohonen self-organising feature maps Rao's Q diversity index remote sensing satellite imagery Sparse Generalized Dissimilarity Model spectral species concept Rocchini, Duccio Luque, Sandra Pettorelli, Nathalie Bastin, Lucy Doktor, Daniel Faedi, Nicolo Feilhauer, Hannes Feret, Jean-Baptiste Foody, Giles M. Gavish, Yoni Godinho, Sergio Kunin, William E. Lausch, Angela Leitao, Pedro J. Marcantonio, Matteo Neteler, Markus Ricotta, Carlo Schmidtlein, Sebastian Vihervaara, Petteri Wegmann, Martin Nagendra, Harini Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring |
| title | Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring |
| title_full | Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring |
| title_fullStr | Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring |
| title_full_unstemmed | Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring |
| title_short | Measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring |
| title_sort | measuring beta-diversity by remote sensing: a challenge for biodiversity monitoring |
| topic | Beta-diversity Kohonen self-organising feature maps Rao's Q diversity index remote sensing satellite imagery Sparse Generalized Dissimilarity Model spectral species concept |
| url | https://eprints.nottingham.ac.uk/49142/ |