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| Registros recuperados : 35 | |
| 6. |  | ALVAREZ, J. M.; DESBIEZ, A. L. J.; SANTOS, S. A. Caracterização anatômica de diafragmas em plantas forrageiras do Pantanal. In: CONGRESSO NACIONAL DE BOTÂNICA, 60.; REUNIÃO NORDESTINA DE BOTÂNICA, 32.; ERBOT - ENCONTRO REGIONAL DE BOTÂNICOS - MG, BA , ES, 29., 2009, Feira de Santana. Botânica brasileira: futuro e compromissos. Feira de Santana: SBB: UEFS, 2009.| Biblioteca(s): Embrapa Pantanal. |
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| 7. | | ALVAREZ, J. M.; DESBIEZ, A. L. J.; SANTOS, S. A. Características da epiderme foliar de Ludwigia spp. (Onagraceae) como auxílio na identificação da dieta de herbívoros do Pantanal. In: CONGRESSO NACIONAL DE BOTÂNICA, 60.; REUNIÃO NORDESTINA DE BOTÂNICA, 32.; ERBOT - ENCONTRO REGIONAL DE BOTÂNICOS - MG, BA , ES, 29., 2009, Feira de Santana. Botânica brasileira: futuro e compromissos. Feira de Santana: SBB: UEFS, 2009.| Biblioteca(s): Embrapa Pantanal. |
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| 19. | | DESBIEZ, A. L. J.; SANTOS, S. A.; KEUROGHLIAN, A.; BODMER, R. E. Niche partitioning among white-lipped peccaries (Tayassu pecari), collared peccaries (Pecari tajacu), and feral pigs (Sus scrofa). Journal of Mammalogy, v.90, n.1, p. 119-128, 2008.| Biblioteca(s): Embrapa Pantanal. |
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| 20. | | CAMPOS, Z. M. da S.; MUNIZ, F.; DESBIEZ, A. L. J.; MAGNUSSON, W. E. Predation on eggs of Schneider's Dwarf Caiman, Paleosuchus trigonatus (Schneider 1807), by armadillos and other predators. In: WORKING MEETING OF THE CROCODILE SPECIALIST GROUP, 25., 2018. Santa Fé, Argentina. Abstracts...[S.l]: IUCN/Species Survival Commission, 2018. p. 94-95. Na publicação: Zilca Campos.| Biblioteca(s): Embrapa Pantanal. |
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| Registros recuperados : 35 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Pantanal. Para informações adicionais entre em contato com cpap.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Pantanal. |
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Data corrente: |
15/08/2022 |
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Data da última atualização: |
03/01/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
ASCENSAO, f.; RIBEIRO, Y. G. G.; CAMPOS, Z.; YOGUI, D. R.; DESBIEZ, A. L. J. |
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Afiliação: |
FERNANDO ASCENSAO, cE3c - Centre for Ecology, Evolution and Environmental Changes & CHANGE; YURI GERALDO GOMES RIBEIRO, Instituto de Conservaçao de Animais Silvestre; ZILCA MARIA DA SILVA CAMPOS, CPAP; DEBORA REGINA YOGUI, Instituto de Conservaçao de Animais Silvestres (ICAS); ARNAUD L. J. DESBIEZ, Instituto de Conservaçao de Animais Silvestres (ICAS). |
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Título: |
Forecasting seasonal peaks in roadkill patterns for improving road management. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Journal of Environmental Management, v. 321, 115903, 2022. |
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Idioma: |
Inglês |
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Conteúdo: |
For several species, roadkill is not spatially aggregated on hotspots, having instead a more diffuse pattern along the roads. For such species, management measures such as road passages may be insufficient for effective mitigation, since a large part of the road crossings is likely to occur outside the influence of those structures. One complementary approach could be to implement temporary mitigation actions, such as traffic calming. This requires understanding when roadkill peaks may occur. We tested the feasibility of predicting seasonal peaks of roadkill using data from a 3-year systematic monitoring (78 surveys over ca. 960 km of roads) from eight non-flying vertebrate species from Mato Grosso do Sul, Brazil, with different body size and life history traits (ca. 6400 records from focal species). We modelled the time-series of the roadkill of these species at large scale (state level) using generalized additive mixed models (GAMMs). We used the data of the first 2 years as training datasets, and the information from the third year of surveys as testing datasets to evaluate the prediction performance of models. Overall, the models of species feed with a higher number of records were able to follow reasonably well the variations of roadkill over time, although they were not able to correctly predict the number of collisions. For species with fewer observations, the models presented a poorer goodness-of-fit and prediction ability. Our results suggest that, at least for those species with higher roadkill rates, it can be possible to forecast periods of higher probability of occurring hot-moments of mortality. Such models can provide valuable information to implement seasonal management actions. MenosFor several species, roadkill is not spatially aggregated on hotspots, having instead a more diffuse pattern along the roads. For such species, management measures such as road passages may be insufficient for effective mitigation, since a large part of the road crossings is likely to occur outside the influence of those structures. One complementary approach could be to implement temporary mitigation actions, such as traffic calming. This requires understanding when roadkill peaks may occur. We tested the feasibility of predicting seasonal peaks of roadkill using data from a 3-year systematic monitoring (78 surveys over ca. 960 km of roads) from eight non-flying vertebrate species from Mato Grosso do Sul, Brazil, with different body size and life history traits (ca. 6400 records from focal species). We modelled the time-series of the roadkill of these species at large scale (state level) using generalized additive mixed models (GAMMs). We used the data of the first 2 years as training datasets, and the information from the third year of surveys as testing datasets to evaluate the prediction performance of models. Overall, the models of species feed with a higher number of records were able to follow reasonably well the variations of roadkill over time, although they were not able to correctly predict the number of collisions. For species with fewer observations, the models presented a poorer goodness-of-fit and prediction ability. Our results suggest that, at least for thos... Mostrar Tudo |
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Thesagro: |
Comportamento Animal; Prevenção de Acidente. |
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Thesaurus NAL: |
Animal behavior; Road kills. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
|
Marc: |
LEADER 02365naa a2200217 a 4500
001 2145426
005 2023-01-03
008 2022 bl uuuu u00u1 u #d
100 1 $aASCENSAO, f.
245 $aForecasting seasonal peaks in roadkill patterns for improving road management.$h[electronic resource]
260 $c2022
520 $aFor several species, roadkill is not spatially aggregated on hotspots, having instead a more diffuse pattern along the roads. For such species, management measures such as road passages may be insufficient for effective mitigation, since a large part of the road crossings is likely to occur outside the influence of those structures. One complementary approach could be to implement temporary mitigation actions, such as traffic calming. This requires understanding when roadkill peaks may occur. We tested the feasibility of predicting seasonal peaks of roadkill using data from a 3-year systematic monitoring (78 surveys over ca. 960 km of roads) from eight non-flying vertebrate species from Mato Grosso do Sul, Brazil, with different body size and life history traits (ca. 6400 records from focal species). We modelled the time-series of the roadkill of these species at large scale (state level) using generalized additive mixed models (GAMMs). We used the data of the first 2 years as training datasets, and the information from the third year of surveys as testing datasets to evaluate the prediction performance of models. Overall, the models of species feed with a higher number of records were able to follow reasonably well the variations of roadkill over time, although they were not able to correctly predict the number of collisions. For species with fewer observations, the models presented a poorer goodness-of-fit and prediction ability. Our results suggest that, at least for those species with higher roadkill rates, it can be possible to forecast periods of higher probability of occurring hot-moments of mortality. Such models can provide valuable information to implement seasonal management actions.
650 $aAnimal behavior
650 $aRoad kills
650 $aComportamento Animal
650 $aPrevenção de Acidente
700 1 $aRIBEIRO, Y. G. G.
700 1 $aCAMPOS, Z.
700 1 $aYOGUI, D. R.
700 1 $aDESBIEZ, A. L. J.
773 $tJournal of Environmental Management$gv. 321, 115903, 2022.
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