Prediction of Sites with a High Probability of Wild Mammal Roadkill Using a Favourability Function
Roads are one of the main causes of loss of biodiversity, with roadkill one of the main causes of mortality. The aim of this research was to identify sites with a high probability of roadkill of medium and large mammals, and the environmental variables that would explain it. We used the favourabilit...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Diversity |
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| Online Access: | https://www.mdpi.com/1424-2818/13/11/585 |
| _version_ | 1797510613422833664 |
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| author | Hugo Ignacio Coitiño Marcel Achkar José Carlos Guerrero |
| author_facet | Hugo Ignacio Coitiño Marcel Achkar José Carlos Guerrero |
| author_sort | Hugo Ignacio Coitiño |
| collection | DOAJ |
| description | Roads are one of the main causes of loss of biodiversity, with roadkill one of the main causes of mortality. The aim of this research was to identify sites with a high probability of roadkill of medium and large mammals, and the environmental variables that would explain it. We used the favourability function (F) to build the predictive models. There were 57 explanatory variables, and we collected 685 records of 10 species of medium and large native wild mammals from the ECOBIO Uruguay databases. They were grouped into native forest and grassland species, according to the main habitat. Two models were developed, one with all the variables and one with the anthropogenic variables. For both groups, the model obtained with all the variables was the most significant according to the evaluation indices used. This made it possible to identify the hot spots of roadkill (F > 0.6) for each of the groups. The anthropic variables were the ones that best explained these hot spots. This allowed the identification of sites where the probability of roadkill is high and requires a monitoring plan to implement mitigation measures in the future. |
| first_indexed | 2024-03-10T05:33:38Z |
| format | Article |
| id | doaj.art-c5b0fd4bcd8c4e12b6e0fbfdcdffd676 |
| institution | Directory Open Access Journal |
| issn | 1424-2818 |
| language | English |
| last_indexed | 2024-03-10T05:33:38Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diversity |
| spelling | doaj.art-c5b0fd4bcd8c4e12b6e0fbfdcdffd6762023-11-22T23:04:28ZengMDPI AGDiversity1424-28182021-11-01131158510.3390/d13110585Prediction of Sites with a High Probability of Wild Mammal Roadkill Using a Favourability FunctionHugo Ignacio Coitiño0Marcel Achkar1José Carlos Guerrero2NGO Ecología y Conservación de la Biodiversidad de Uruguay (ECOBIO Uruguay), Montevideo C.P. 11000, UruguayLaboratorio de Desarrollo Sustentable y Gestión Ambiental del Territorio, Facultad de Ciencias, Universidad de la República, Montevideo C.P. 11400, UruguayLaboratorio de Desarrollo Sustentable y Gestión Ambiental del Territorio, Facultad de Ciencias, Universidad de la República, Montevideo C.P. 11400, UruguayRoads are one of the main causes of loss of biodiversity, with roadkill one of the main causes of mortality. The aim of this research was to identify sites with a high probability of roadkill of medium and large mammals, and the environmental variables that would explain it. We used the favourability function (F) to build the predictive models. There were 57 explanatory variables, and we collected 685 records of 10 species of medium and large native wild mammals from the ECOBIO Uruguay databases. They were grouped into native forest and grassland species, according to the main habitat. Two models were developed, one with all the variables and one with the anthropogenic variables. For both groups, the model obtained with all the variables was the most significant according to the evaluation indices used. This made it possible to identify the hot spots of roadkill (F > 0.6) for each of the groups. The anthropic variables were the ones that best explained these hot spots. This allowed the identification of sites where the probability of roadkill is high and requires a monitoring plan to implement mitigation measures in the future.https://www.mdpi.com/1424-2818/13/11/585road mitigationpotential distribution modelsmortality hotspot |
| spellingShingle | Hugo Ignacio Coitiño Marcel Achkar José Carlos Guerrero Prediction of Sites with a High Probability of Wild Mammal Roadkill Using a Favourability Function Diversity road mitigation potential distribution models mortality hotspot |
| title | Prediction of Sites with a High Probability of Wild Mammal Roadkill Using a Favourability Function |
| title_full | Prediction of Sites with a High Probability of Wild Mammal Roadkill Using a Favourability Function |
| title_fullStr | Prediction of Sites with a High Probability of Wild Mammal Roadkill Using a Favourability Function |
| title_full_unstemmed | Prediction of Sites with a High Probability of Wild Mammal Roadkill Using a Favourability Function |
| title_short | Prediction of Sites with a High Probability of Wild Mammal Roadkill Using a Favourability Function |
| title_sort | prediction of sites with a high probability of wild mammal roadkill using a favourability function |
| topic | road mitigation potential distribution models mortality hotspot |
| url | https://www.mdpi.com/1424-2818/13/11/585 |
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