Mechanistic understanding of human-wildlife conflict through a novel application of dynamic occupancy models

© 2015 Society for Conservation Biology.

Bibliographische Detailangaben
Veröffentlicht in:Conservation biology : the journal of the Society for Conservation Biology. - 1999. - 29(2015), 4 vom: 11. Aug., Seite 1100-1110
1. Verfasser: Goswami, Varun R (VerfasserIn)
Weitere Verfasser: Medhi, Kamal, Nichols, James D, Oli, Madan K
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2015
Zugriff auf das übergeordnete Werk:Conservation biology : the journal of the Society for Conservation Biology
Schlagworte:Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. ciencia ciudadana citizen science crop and livestock depredation depredación de cultivos y ganado detección de probabilidad detection probability elefantes mehr... elephants human-dominated landscapes modelado predictivo monitoreo monitoring predictive modeling terrenos dominados por humanos
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245 1 0 |a Mechanistic understanding of human-wildlife conflict through a novel application of dynamic occupancy models 
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520 |a Crop and livestock depredation by wildlife is a primary driver of human-wildlife conflict, a problem that threatens the coexistence of people and wildlife globally. Understanding mechanisms that underlie depredation patterns holds the key to mitigating conflicts across time and space. However, most studies do not consider imperfect detection and reporting of conflicts, which may lead to incorrect inference regarding its spatiotemporal drivers. We applied dynamic occupancy models to elephant crop depredation data from India between 2005 and 2011 to estimate crop depredation occurrence and model its underlying dynamics as a function of spatiotemporal covariates while accounting for imperfect detection of conflicts. The probability of detecting conflicts was consistently <1.0 and was negatively influenced by distance to roads and elevation gradient, averaging 0.08-0.56 across primary periods (distinct agricultural seasons within each year). The probability of crop depredation occurrence ranged from 0.29 (SE 0.09) to 0.96 (SE 0.04). The probability that sites raided by elephants in primary period t would not be raided in primary period t + 1 varied with elevation gradient in different seasons and was influenced negatively by mean rainfall and village density and positively by distance to forests. Negative effects of rainfall variation and distance to forests best explained variation in the probability that sites not raided by elephants in primary period t would be raided in primary period t + 1. With our novel application of occupancy models, we teased apart the spatiotemporal drivers of conflicts from factors that influence how they are observed, thereby allowing more reliable inference on mechanisms underlying observed conflict patterns. We found that factors associated with increased crop accessibility and availability (e.g., distance to forests and rainfall patterns) were key drivers of elephant crop depredation dynamics. Such an understanding is essential for rigorous prediction of future conflicts, a critical requirement for effective conflict management in the context of increasing human-wildlife interactions 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
650 4 |a Research Support, U.S. Gov't, Non-P.H.S. 
650 4 |a ciencia ciudadana 
650 4 |a citizen science 
650 4 |a crop and livestock depredation 
650 4 |a depredación de cultivos y ganado 
650 4 |a detección de probabilidad 
650 4 |a detection probability 
650 4 |a elefantes 
650 4 |a elephants 
650 4 |a human-dominated landscapes 
650 4 |a modelado predictivo 
650 4 |a monitoreo 
650 4 |a monitoring 
650 4 |a predictive modeling 
650 4 |a terrenos dominados por humanos 
700 1 |a Medhi, Kamal  |e verfasserin  |4 aut 
700 1 |a Nichols, James D  |e verfasserin  |4 aut 
700 1 |a Oli, Madan K  |e verfasserin  |4 aut 
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