An Integrated, Tentative Remote-Sensing Approach Based on NDVI Entropy to Model Canine Distemper Virus in Wildlife and to Prompt Science-Based Management Policies
Changes in land use and land cover as well as feedback on the climate deeply affect the landscape worldwide. This phenomenon has also enlarged the human–wildlife interface and amplified the risk of potential new zoonoses. The expansion of the human settlement is supposed to affect the spread and dis...
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Online Access: | https://doi.org/10.3390/ani12081049 |
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ftmdpi:oai:mdpi.com:/2076-2615/12/8/1049/ 2023-08-20T04:05:50+02:00 An Integrated, Tentative Remote-Sensing Approach Based on NDVI Entropy to Model Canine Distemper Virus in Wildlife and to Prompt Science-Based Management Policies Emanuele Carella Tommaso Orusa Annalisa Viani Daniela Meloni Enrico Borgogno-Mondino Riccardo Orusa agris 2022-04-18 application/pdf https://doi.org/10.3390/ani12081049 EN eng Multidisciplinary Digital Publishing Institute Wildlife https://dx.doi.org/10.3390/ani12081049 https://creativecommons.org/licenses/by/4.0/ Animals; Volume 12; Issue 8; Pages: 1049 CDV GIS remote sensing NDVI entropy Orfeo Toolbox Google Earth Engine (GEE) Sentinel-2 red foxes wolves badger beech marten PCR Aosta Valley region Text 2022 ftmdpi https://doi.org/10.3390/ani12081049 2023-08-01T04:47:28Z Changes in land use and land cover as well as feedback on the climate deeply affect the landscape worldwide. This phenomenon has also enlarged the human–wildlife interface and amplified the risk of potential new zoonoses. The expansion of the human settlement is supposed to affect the spread and distribution of wildlife diseases such as canine distemper virus (CDV), by shaping the distribution, density, and movements of wildlife. Nevertheless, there is very little evidence in the scientific literature on how remote sensing and GIS tools may help the veterinary sector to better monitor the spread of CDV in wildlife and to enforce ecological studies and new management policies in the near future. Thus, we perform a study in Northwestern Italy (Aosta Valley Autonomous Region), focusing on the relative epidemic waves of CDV that cause a virulent disease infecting different animal species with high host mortality. CDV has been detected in several mammalian from Canidae, Mustelidae, Procyonidae, Ursidae, and Viverridae families. In this study, the prevalence is determined at 60% in red fox (Vulpes vulpes, n = 296), 14% in wolf (Canis lupus, n = 157), 47% in badger (Meles meles, n = 103), and 51% in beech marten (Martes foina, n = 51). The detection of CDV is performed by means of real-time PCR. All the analyses are done using the TaqMan approach, targeting the chromosomal gene for phosphoprotein, gene P, that is involved in the transcription and replication of the virus. By adopting Earth Observation Data, we notice that CDV trends are strongly related to an altitude gradient and NDVI entropy changes through the years. A tentative model is developed concerning the ground data collected in the Aosta Valley region. According to our preliminary study, entropy computed from remote-sensing data can represent a valuable tool to monitor CDV spread as a proxy data predictor of the intensity of fragmentation of a given landscape and therefore also to monitor CDV. In conclusion, the evaluation from space of the landscape ... Text Canis lupus MDPI Open Access Publishing Animals 12 8 1049 |
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Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
CDV GIS remote sensing NDVI entropy Orfeo Toolbox Google Earth Engine (GEE) Sentinel-2 red foxes wolves badger beech marten PCR Aosta Valley region |
spellingShingle |
CDV GIS remote sensing NDVI entropy Orfeo Toolbox Google Earth Engine (GEE) Sentinel-2 red foxes wolves badger beech marten PCR Aosta Valley region Emanuele Carella Tommaso Orusa Annalisa Viani Daniela Meloni Enrico Borgogno-Mondino Riccardo Orusa An Integrated, Tentative Remote-Sensing Approach Based on NDVI Entropy to Model Canine Distemper Virus in Wildlife and to Prompt Science-Based Management Policies |
topic_facet |
CDV GIS remote sensing NDVI entropy Orfeo Toolbox Google Earth Engine (GEE) Sentinel-2 red foxes wolves badger beech marten PCR Aosta Valley region |
description |
Changes in land use and land cover as well as feedback on the climate deeply affect the landscape worldwide. This phenomenon has also enlarged the human–wildlife interface and amplified the risk of potential new zoonoses. The expansion of the human settlement is supposed to affect the spread and distribution of wildlife diseases such as canine distemper virus (CDV), by shaping the distribution, density, and movements of wildlife. Nevertheless, there is very little evidence in the scientific literature on how remote sensing and GIS tools may help the veterinary sector to better monitor the spread of CDV in wildlife and to enforce ecological studies and new management policies in the near future. Thus, we perform a study in Northwestern Italy (Aosta Valley Autonomous Region), focusing on the relative epidemic waves of CDV that cause a virulent disease infecting different animal species with high host mortality. CDV has been detected in several mammalian from Canidae, Mustelidae, Procyonidae, Ursidae, and Viverridae families. In this study, the prevalence is determined at 60% in red fox (Vulpes vulpes, n = 296), 14% in wolf (Canis lupus, n = 157), 47% in badger (Meles meles, n = 103), and 51% in beech marten (Martes foina, n = 51). The detection of CDV is performed by means of real-time PCR. All the analyses are done using the TaqMan approach, targeting the chromosomal gene for phosphoprotein, gene P, that is involved in the transcription and replication of the virus. By adopting Earth Observation Data, we notice that CDV trends are strongly related to an altitude gradient and NDVI entropy changes through the years. A tentative model is developed concerning the ground data collected in the Aosta Valley region. According to our preliminary study, entropy computed from remote-sensing data can represent a valuable tool to monitor CDV spread as a proxy data predictor of the intensity of fragmentation of a given landscape and therefore also to monitor CDV. In conclusion, the evaluation from space of the landscape ... |
format |
Text |
author |
Emanuele Carella Tommaso Orusa Annalisa Viani Daniela Meloni Enrico Borgogno-Mondino Riccardo Orusa |
author_facet |
Emanuele Carella Tommaso Orusa Annalisa Viani Daniela Meloni Enrico Borgogno-Mondino Riccardo Orusa |
author_sort |
Emanuele Carella |
title |
An Integrated, Tentative Remote-Sensing Approach Based on NDVI Entropy to Model Canine Distemper Virus in Wildlife and to Prompt Science-Based Management Policies |
title_short |
An Integrated, Tentative Remote-Sensing Approach Based on NDVI Entropy to Model Canine Distemper Virus in Wildlife and to Prompt Science-Based Management Policies |
title_full |
An Integrated, Tentative Remote-Sensing Approach Based on NDVI Entropy to Model Canine Distemper Virus in Wildlife and to Prompt Science-Based Management Policies |
title_fullStr |
An Integrated, Tentative Remote-Sensing Approach Based on NDVI Entropy to Model Canine Distemper Virus in Wildlife and to Prompt Science-Based Management Policies |
title_full_unstemmed |
An Integrated, Tentative Remote-Sensing Approach Based on NDVI Entropy to Model Canine Distemper Virus in Wildlife and to Prompt Science-Based Management Policies |
title_sort |
integrated, tentative remote-sensing approach based on ndvi entropy to model canine distemper virus in wildlife and to prompt science-based management policies |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2022 |
url |
https://doi.org/10.3390/ani12081049 |
op_coverage |
agris |
genre |
Canis lupus |
genre_facet |
Canis lupus |
op_source |
Animals; Volume 12; Issue 8; Pages: 1049 |
op_relation |
Wildlife https://dx.doi.org/10.3390/ani12081049 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/ani12081049 |
container_title |
Animals |
container_volume |
12 |
container_issue |
8 |
container_start_page |
1049 |
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1774716592792272896 |