Publicado

2020-01-01

Can spatial distribution of ungulates be predicted by modeling camera trap data related to landscape indices? A case study in a fragmented Mediterranean landscape

¿Se puede predecir la distribución espacial de ungulados mediante la modelización de imágenes de fototrampeo relacionadas con índices del paisaje? Un estudio de caso en un paisaje mediterráneo fragmentado.

DOI:

https://doi.org/10.15446/caldasia.v42n1.76384

Palabras clave:

camera trap, discriminate analysis, landscape metrics, logistical analysis, multivariant analysis (en)
análisis discriminante, análisis logístico, análisis multivariado, fototrampeo, métricas del paisaje (es)

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Camera trap applications range from studying wildlife habits to detecting rare species, which are difficult to capture by more traditional techniques. In this work, we aimed at finding the best model to predict the distribution pattern of wildlife and to explain the relationship between environmental conditions with the species detected by camera traps. We applied two types of statistical models in a specific Mediterranean landscape case. The results of both models shown adjustments over 80 %. First, we ran a Principal Components Analysis (PCA). Discriminant, and logistic analyses were performed for ungulates in general, and three species in particular: Barbary sheep, mouflon, and wild boar. The same environmental conditions explained the presence of these species in all the proposed models. Hence, we proved the generally positive influence of patch size on the presence of ungulates and negative influence of the fractal dimension and density edge. We quantified the relationships between a suite of landscape metrics measured in different grids to test whether spatial heterogeneity plays a major role in determining the distribution of ungulates. We explained much of the variation in distribution with metrics, specifically related to habitat heterogeneity. That outcome highlighted the potential importance of spatial heterogeneity in determining the distribution of large herbivores. We discussed our results in the forestry conservation practices context and discuss potential ways to integrate ungulate management and forestry practices better.

Las aplicaciones del fototrampeo van desde el estudio de hábitos de la vida silvestre hasta la detección de especies raras, que son difíciles de capturar mediante técnicas tradicionales. El objetivo de este trabajo es proponer modelos predictivos para el comportamiento de la vida silvestre, explicando las relaciones entre las condiciones ambientales y las diferentes especies detectadas mediante cámaras trampa. Finalmente, proponemos dos tipos de modelos predictivos adaptados a un caso específico del paisaje mediterráneo. Los resultados de ambos modelos muestran ajustes superiores al 80 %. En primer lugar, se realizó un Análisis de Componentes Principales (ACP). Se emplearon análisis discriminantes y logísticos con ungulados en general, y para tres especies en particular: arruí, muflón y jabalí. Las condiciones ambientales explicaron la presencia de estas especies en todos los modelos propuestos. Probamos la influencia positiva general del tamaño de los parches sobre la presencia de ungulados. También detectamos una influencia negativa de la dimensión fractal y el borde de densidad. Cuantificamos las relaciones entre un conjunto de métricas de paisaje medidas en diferentes cuadrículas para probar si la heterogeneidad espacial juega un papel importante en la determinación de la distribución de los ungulados. Explicamos parte de la variación en la distribución con métricas específicamente relacionadas con la heterogeneidad del hábitat. Ese resultado destacó la importancia de la heterogeneidad espacial para determinar la distribución de los grandes herbívoros. Colocamos nuestros resultados en el contexto de las prácticas de conservación forestal y discutimos posibles formas de integrar mejor las prácticas de manejo y silvicultura.

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Cómo citar

APA

Belda, A., Oltra-Crespo, S., Miró-Martínez, P., & Zaragozí, B. (2020). Can spatial distribution of ungulates be predicted by modeling camera trap data related to landscape indices? A case study in a fragmented Mediterranean landscape. Caldasia, 42(1), 96-104. https://doi.org/10.15446/caldasia.v42n1.76384

ACM

[1]
Belda, A., Oltra-Crespo, S., Miró-Martínez, P. y Zaragozí, B. 2020. Can spatial distribution of ungulates be predicted by modeling camera trap data related to landscape indices? A case study in a fragmented Mediterranean landscape. Caldasia. 42, 1 (ene. 2020), 96-104. DOI:https://doi.org/10.15446/caldasia.v42n1.76384.

ACS

(1)
Belda, A.; Oltra-Crespo, S.; Miró-Martínez, P.; Zaragozí, B. Can spatial distribution of ungulates be predicted by modeling camera trap data related to landscape indices? A case study in a fragmented Mediterranean landscape. Caldasia 2020, 42, 96-104.

ABNT

BELDA, A.; OLTRA-CRESPO, S.; MIRÓ-MARTÍNEZ, P.; ZARAGOZÍ, B. Can spatial distribution of ungulates be predicted by modeling camera trap data related to landscape indices? A case study in a fragmented Mediterranean landscape. Caldasia, [S. l.], v. 42, n. 1, p. 96-104, 2020. DOI: 10.15446/caldasia.v42n1.76384. Disponível em: https://revistas.unal.edu.co/index.php/cal/article/view/76384. Acesso em: 3 dic. 2021.

Chicago

Belda, Antonio, Sandra Oltra-Crespo, Pau Miró-Martínez, y Benito Zaragozí. 2020. «Can spatial distribution of ungulates be predicted by modeling camera trap data related to landscape indices? A case study in a fragmented Mediterranean landscape». Caldasia 42 (1):96-104. https://doi.org/10.15446/caldasia.v42n1.76384.

Harvard

Belda, A., Oltra-Crespo, S., Miró-Martínez, P. y Zaragozí, B. (2020) «Can spatial distribution of ungulates be predicted by modeling camera trap data related to landscape indices? A case study in a fragmented Mediterranean landscape», Caldasia, 42(1), pp. 96-104. doi: 10.15446/caldasia.v42n1.76384.

IEEE

[1]
A. Belda, S. Oltra-Crespo, P. Miró-Martínez, y B. Zaragozí, «Can spatial distribution of ungulates be predicted by modeling camera trap data related to landscape indices? A case study in a fragmented Mediterranean landscape», Caldasia, vol. 42, n.º 1, pp. 96-104, ene. 2020.

MLA

Belda, A., S. Oltra-Crespo, P. Miró-Martínez, y B. Zaragozí. «Can spatial distribution of ungulates be predicted by modeling camera trap data related to landscape indices? A case study in a fragmented Mediterranean landscape». Caldasia, vol. 42, n.º 1, enero de 2020, pp. 96-104, doi:10.15446/caldasia.v42n1.76384.

Turabian

Belda, Antonio, Sandra Oltra-Crespo, Pau Miró-Martínez, y Benito Zaragozí. «Can spatial distribution of ungulates be predicted by modeling camera trap data related to landscape indices? A case study in a fragmented Mediterranean landscape». Caldasia 42, no. 1 (enero 1, 2020): 96-104. Accedido diciembre 3, 2021. https://revistas.unal.edu.co/index.php/cal/article/view/76384.

Vancouver

1.
Belda A, Oltra-Crespo S, Miró-Martínez P, Zaragozí B. Can spatial distribution of ungulates be predicted by modeling camera trap data related to landscape indices? A case study in a fragmented Mediterranean landscape. Caldasia [Internet]. 1 de enero de 2020 [citado 3 de diciembre de 2021];42(1):96-104. Disponible en: https://revistas.unal.edu.co/index.php/cal/article/view/76384

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