Coexistence between wildlife and humans at fine spatial scales

Abstract

Many wildlife species face imminent extinction because of human impacts, and therefore, a prevailing belief is that some wildlife species, particularly large carnivores and ungulates, cannot coexist with people at fine spatial scales (i.e., cannot regularly use the exact same point locations). This belief provides rationale for various conservation programs, such as resettling human communities outside protected areas. However, quantitative information on the capacity and mechanisms for wildlife to coexist with humans at fine spatial scales is scarce. Such information is vital, because the world is becoming increasingly crowded. Here, we provide empirical information about the capacity and mechanisms for tigers (a globally endangered species) to coexist with humans at fine spatial scales inside and outside Nepal's Chitwan National Park, a flagship protected area for imperiled wildlife. Information obtained from field cameras in 2010 and 2011 indicated that human presence (i.e., people on foot and vehicles) was ubiquitous and abundant throughout the study site; however, tiger density was also high. Surprisingly, even at a fine spatial scale (i.e., camera locations), tigers spatially overlapped with people on foot and vehicles in both years. However, in both years, tigers offset their temporal activity patterns to be much less active during the day when human activity peaked. In addition to temporal displacement, tiger-human coexistence was likely enhanced by abundant tiger prey and low levels of tiger poaching. Incorporating fine-scale spatial and temporal activity patterns into conservation plans can help address a major global challenge-meeting human needs while sustaining wildlife.

Fig. 1.

Schematic diagram of human–wildlife coexistence at different scales. Protected areas aim to facilitate coexistence between wildlife and humans at regional scales (A) by spatially segregating them into distinct zones. Community-managed areas, in which people can extract natural resources on a limited basis, such as pro-wildlife cattle ranches and community forests, encourage coexistence at comparatively smaller intermediate scales (B). Most conservation models, however, are based on the belief that some wildlife species, like large carnivores, cannot coexist with humans at fine spatial scales (C) because of a fundamental conflict over limited resources (e.g., food). We empirically test this prevailing belief using data from camera traps to quantify the capacity and mechanisms of tigers, a notoriously elusive carnivore, to coexist with humans at a fine spatial scale (i.e., exact same point locations) in Chitwan, Nepal.

Fig. 2.

Tiger detection probability with respect to human-related covariates. Predictions of tiger detection probability are based on model-averaged covariate coefficient estimates with respect to (A) location (i.e., inside or outside of the park), (B) distance to human settlement, (C) distance to forest road, and (D) local resident abundances (detections per 100 trap-d). Boxes in A represent the 25th and 75th percentiles, whiskers represent the 95% confidence limits, black lines within boxes represent medians, and circles outside the whiskers represent outlier values. B–D display detection probabilities by year (2010 values are indicated by circles and 2011 values are indicated by triangles), and they include linear regression lines (2010 linear regression line in green and 2011 linear regression line in yellow) with R² values shown inside.

Fig. 3.

Temporal overlap of tiger and human activity patterns in 2010. Activity patterns of tiger (dashed lines) and human (solid lines) presence types inside (A–E) and outside (F–J) Chitwan National Park, Nepal in 2010. (A and F) Total people on foot. (B and G) Local residents. (C and H) Tourists. (D and I) Army personnel. (E and J) Vehicles. The estimate of temporal overlap, (from zero [no overlap] to one [complete overlap]), is indicated by the orange area, and it is shown in each panel. Overlap was defined as the area under the curve formed by taking the minimum of the two activity patterns at each point in time. Approximate 95% bootstrap CIs of overlap estimates are indicated in parentheses. Average time of sunrise was 0600 hours, and average time of sunset was 1800 hours during the study.