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Using a novel model approach to assess the distribution and conservation status of the endangered Baird's tapir

Schank, Cody J [autor] | Cove, Michael V [autor] | Kelly, Marcella J [autora] | Mendoza Ramírez, Eduardo [autor] | O´Farril Cruz, Elsa Georgina [autora] | Reyna Hurtado, Rafael Ángel [autor] | Meyer, Ninon France Victoire [autora] | Jordan, Christopher A [autor] | González Maya, José F [autor] | Lizcano, Diego J [autor] | Moreno, Ricardo [autor] | Dobbins, Michael T [autor] | Montalvo, Víctor [autor] | Sáenz Bolaños, Carolina [autora] | Carillo Jiménez, Eduardo [autor] | Estrada, Nereyda [autora] | Cruz Díaz, Juan Carlos [autor] | Sáenz, Joel [autor] | Spínola, Manuel [autor] | Carver, Andrew [autor] | Fort, Jessica [autora] | Nielsen, Clayton K [autor] | Botello, Francisco [autor] | Pozo Montuy, Gilberto [autor] | Rivero Hernández, Crysia Marina [autora] | De la Torre, José Antonio [autor] | Brenes Mora, Esteban [autor] | Godínez Gómez, Oscar [autor] | Wood, Margot A [autora] | Gilbert, Jessica [autora] | Miller, Jennifer A [autora].
Tipo de material: Artículo en línea Artículo en línea Tipo de contenido: Texto Tipo de medio: Computadora Tipo de portador: Recurso en líneaTema(s): Tapirus bairdii | Modelos de distribución de especies | Hábitat (Ecología) | Distribución de la poblaciónTema(s) en inglés: Tapirus bairdii | Species distribution models | Habitat (Ecology) | Population distributionDescriptor(es) geográficos: Veracruz de Ignacio de la Llave (México) | Oaxaca (México) | Chocó (Colombia) Nota de acceso: Disponible para usuarios de ECOSUR con su clave de acceso En: Diversity and Distributions. Volumen 23, número 12 (December 2017), páginas 1459-1471. --ISSN: 1809-127XNúmero de sistema: 6748Resumen:
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Aim: We test a new species distribution modelling (SDM) framework, while comparing results to more common distribution modelling techniques. This framework allows for the combination of presence-only (PO) and presence-absence (PA) data and accounts for imperfect detection and spatial bias in presence data. The new framework tested here is based on a Poisson point process model, which allows for predictions of population size. We compared these estimates to those provided by experts on the species. Species and Location: Presence data on Baird's tapir (Tapirus bairdii) throughout its range from southern México to northern Colombia were used in this research, primarily from the years 2000 to 2016. Methods: Four SDM frameworks are compared as follows: (1) Maxent, (2) a presence-only (PO) SDM based on a Poisson point process model (PPM), (3) a presence-absence (PA) SDM also based on a PPM and (4) an Integrated framework which combines the previous two models. Model averaging was used to produce a single set of coefficient estimates and predictive maps for each model framework. A hotspot analysis (Gi*) was used to identify habitat cores from the predicted intensity of the Integrated model framework. Results: Important variables to model the distribution of Baird's tapir included land cover, human pressure and topography. Accounting for spatial bias in the presence data affected which variables were important in the model. Maxent and the Integrated model produced predictive maps with similar patterns and were considered to be more in agreement with expert knowledge compared to the PO and PA models. Main conclusions: Total abundance as predicted by the model was higher than expert opinion on the species, but local density estimates from our model were similar to available independent assessments. We suggest that these results warrant further validation and testing through collection of independent test data, development of more precise predictor layers and improvements to the model framework.

Recurso en línea: http://onlinelibrary.wiley.com/doi/10.1111/ddi.12631/abstract
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Disponible para usuarios de ECOSUR con su clave de acceso

Aim: We test a new species distribution modelling (SDM) framework, while comparing results to more common distribution modelling techniques. This framework allows for the combination of presence-only (PO) and presence-absence (PA) data and accounts for imperfect detection and spatial bias in presence data. The new framework tested here is based on a Poisson point process model, which allows for predictions of population size. We compared these estimates to those provided by experts on the species. Species and Location: Presence data on Baird's tapir (Tapirus bairdii) throughout its range from southern México to northern Colombia were used in this research, primarily from the years 2000 to 2016. Methods: Four SDM frameworks are compared as follows: (1) Maxent, (2) a presence-only (PO) SDM based on a Poisson point process model (PPM), (3) a presence-absence (PA) SDM also based on a PPM and (4) an Integrated framework which combines the previous two models. Model averaging was used to produce a single set of coefficient estimates and predictive maps for each model framework. A hotspot analysis (Gi*) was used to identify habitat cores from the predicted intensity of the Integrated model framework. Results: Important variables to model the distribution of Baird's tapir included land cover, human pressure and topography. Accounting for spatial bias in the presence data affected which variables were important in the model. Maxent and the Integrated model produced predictive maps with similar patterns and were considered to be more in agreement with expert knowledge compared to the PO and PA models. Main conclusions: Total abundance as predicted by the model was higher than expert opinion on the species, but local density estimates from our model were similar to available independent assessments. We suggest that these results warrant further validation and testing through collection of independent test data, development of more precise predictor layers and improvements to the model framework. eng

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