Vegetation canopy height shapes bats’ occupancy: a remote sensing approach
Anthropogenic activities have significantly altered land cover on a global scale. These changes often have a negative effect on biodiversity limiting the distribution of species. The extent of the effect on species’ distribution depends on the landscape composition and configuration at a local and l...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | GIScience & Remote Sensing |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/15481603.2024.2374150 |
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| author | F. C. Martins S. Godinho N. Guiomar D. Medinas H. Rebelo P. Segurado J. T. Marques |
| author_facet | F. C. Martins S. Godinho N. Guiomar D. Medinas H. Rebelo P. Segurado J. T. Marques |
| author_sort | F. C. Martins |
| collection | DOAJ |
| description | Anthropogenic activities have significantly altered land cover on a global scale. These changes often have a negative effect on biodiversity limiting the distribution of species. The extent of the effect on species’ distribution depends on the landscape composition and configuration at a local and landscape level. To better understand this effect on a large scale, we evaluated how land cover and vegetation structure shape bat species’ occurrence while considering species’ imperfect detection. We hypothesize that intensification of anthropogenic activities in agriculture, for example, reduces heterogeneity of land cover and vegetation structure, and thereby, limits bat occurrence. To investigate this, we conducted acoustic bat sampling across 59 locations in southern Portugal, each with three spatial replicates. We derived fine-scale vegetation structural metrics by combining spaceborne LiDAR (GEDI) and synthetic aperture radar data (Sentinel-1 and ALOS/PALSAR-2). Additionally, we included land cover metrics and high-resolution climate data from CHELSA. Our findings revealed an important relationship between bat species’ occupancy and vegetation structure, particularly with vegetation canopy height. Moreover, forest and shrubland proportions were the main land cover types influencing bat species responses. All species’ best-ranking occupancy models included at least one climatic variable (temperature, humidity, or potential evapotranspiration), demonstrating the importance of climate when predicting bat distribution. Our acoustic surveys had a species’ detection probability varying from 0.19 to 0.86, and it was influenced by night conditions. These findings underscore the importance of modeling imperfect detection, especially for highly vagile and elusive organisms like bats. Our results demonstrate the effectiveness of using vegetation and landscape metrics derived from high-resolution remote sensing data to model species distribution in the context of biodiversity monitoring and conservation. |
| format | Article |
| id | doaj-art-2ad8911a61284ecfb5150a3b9927fbf0 |
| institution | Kabale University |
| issn | 1548-1603 1943-7226 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | GIScience & Remote Sensing |
| spelling | doaj-art-2ad8911a61284ecfb5150a3b9927fbf02024-12-06T13:51:51ZengTaylor & Francis GroupGIScience & Remote Sensing1548-16031943-72262024-12-0161110.1080/15481603.2024.2374150Vegetation canopy height shapes bats’ occupancy: a remote sensing approachF. C. Martins0S. Godinho1N. Guiomar2D. Medinas3H. Rebelo4P. Segurado5J. T. Marques6MED (Instituto Mediterrâneo para a Agricultura, Ambiente e Desenvolvimento) and CHANGE – Global Change and Sustainability Institute, IIFA (Instituto de Investigação e Formação Avançada), Universidade de Évora, Évora, PortugalMED (Instituto Mediterrâneo para a Agricultura, Ambiente e Desenvolvimento) and CHANGE – Global Change and Sustainability Institute, IIFA (Instituto de Investigação e Formação Avançada), Universidade de Évora, Évora, PortugalMED (Instituto Mediterrâneo para a Agricultura, Ambiente e Desenvolvimento) and CHANGE – Global Change and Sustainability Institute, IIFA (Instituto de Investigação e Formação Avançada), Universidade de Évora, Évora, PortugalConservation Biology Lab, Department of Biology, University of Évora, Évora, PortugalCIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Universidade do Porto, Vila do Conde, PortugalCEF, Centro de Estudos Florestais, Laboratório Associado TERRA, Instituto Superior de Agronomia, Universidade de Lisboa, Lisbon, PortugalMED (Instituto Mediterrâneo para a Agricultura, Ambiente e Desenvolvimento) and CHANGE – Global Change and Sustainability Institute, IIFA (Instituto de Investigação e Formação Avançada), Universidade de Évora, Évora, PortugalAnthropogenic activities have significantly altered land cover on a global scale. These changes often have a negative effect on biodiversity limiting the distribution of species. The extent of the effect on species’ distribution depends on the landscape composition and configuration at a local and landscape level. To better understand this effect on a large scale, we evaluated how land cover and vegetation structure shape bat species’ occurrence while considering species’ imperfect detection. We hypothesize that intensification of anthropogenic activities in agriculture, for example, reduces heterogeneity of land cover and vegetation structure, and thereby, limits bat occurrence. To investigate this, we conducted acoustic bat sampling across 59 locations in southern Portugal, each with three spatial replicates. We derived fine-scale vegetation structural metrics by combining spaceborne LiDAR (GEDI) and synthetic aperture radar data (Sentinel-1 and ALOS/PALSAR-2). Additionally, we included land cover metrics and high-resolution climate data from CHELSA. Our findings revealed an important relationship between bat species’ occupancy and vegetation structure, particularly with vegetation canopy height. Moreover, forest and shrubland proportions were the main land cover types influencing bat species responses. All species’ best-ranking occupancy models included at least one climatic variable (temperature, humidity, or potential evapotranspiration), demonstrating the importance of climate when predicting bat distribution. Our acoustic surveys had a species’ detection probability varying from 0.19 to 0.86, and it was influenced by night conditions. These findings underscore the importance of modeling imperfect detection, especially for highly vagile and elusive organisms like bats. Our results demonstrate the effectiveness of using vegetation and landscape metrics derived from high-resolution remote sensing data to model species distribution in the context of biodiversity monitoring and conservation.https://www.tandfonline.com/doi/10.1080/15481603.2024.2374150Land coverspecies occurrenceGEDIbatsvegetation canopy height |
| spellingShingle | F. C. Martins S. Godinho N. Guiomar D. Medinas H. Rebelo P. Segurado J. T. Marques Vegetation canopy height shapes bats’ occupancy: a remote sensing approach GIScience & Remote Sensing Land cover species occurrence GEDI bats vegetation canopy height |
| title | Vegetation canopy height shapes bats’ occupancy: a remote sensing approach |
| title_full | Vegetation canopy height shapes bats’ occupancy: a remote sensing approach |
| title_fullStr | Vegetation canopy height shapes bats’ occupancy: a remote sensing approach |
| title_full_unstemmed | Vegetation canopy height shapes bats’ occupancy: a remote sensing approach |
| title_short | Vegetation canopy height shapes bats’ occupancy: a remote sensing approach |
| title_sort | vegetation canopy height shapes bats occupancy a remote sensing approach |
| topic | Land cover species occurrence GEDI bats vegetation canopy height |
| url | https://www.tandfonline.com/doi/10.1080/15481603.2024.2374150 |
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