Crop use structures resource selection strategies for African elephants in a human-dominated landscape.

To conserve wide-ranging species in degraded landscapes, it is essential to understand how the behavior of animals changes in relation to the degree and composition of modification. Evidence suggests that large inter-individual variation exists in the propensity for use of degraded areas and may be driven by both behavioral and landscape factors. The use of cultivated lands by wildlife is of particular interest, given the importance of reducing human-wildlife conflicts and understanding how such areas can function as biodiversity buffers. African elephant space use can be highly influenced by human activity and the degree to which individuals crop-raid. We analyzed GPS data from 56 free-ranging elephants in the Serengeti-Mara Ecosystem using resource selection functions (RSFs) to assess how crop use may drive patterns of resource selection and space use within a population. We quantified drivers of similarity in resource selection across individuals using proximity analysis of individual RSF coefficients derived from random forest models. We found wide variation in RSF coefficient values between individuals indicating strongly differentiated resource selection strategies. Proximity assessment indicated the degree of crop use in the dry season, individual repeatability, and time spent in unprotected areas drove similarity in resource selection patterns. Crop selection was also spatially structured in relation to agricultural fragmentation. In areas with low fragmentation, elephants spent less time in crops and selected most strongly for crops further from protected area boundaries, but in areas of high fragmentation, elephants spent twice as much time in crops and selected most strongly for crops closer to the protected area boundary. Our results highlight how individual differences and landscape structure can shape use of agricultural landscapes. We discuss our findings in respect to the conservation challenges of human-elephant conflict and incorporating behavioral variation into human-wildlife coexistence efforts.

Identifying conservation technology needs, barriers, and opportunities.

Amid accelerating threats to species and ecosystems, technology advancements to monitor, protect, and conserve biodiversity have taken on increased importance. While most innovations stem from adaptation of off-the-shelf devices, these tools can fail to meet the specialized needs of conservation and research or lack the support to scale beyond a single site. Despite calls from the conservation community for its importance, a shift to bottom-up innovation driven by conservation professionals remains limited. We surveyed practitioners, academic researchers, and technologists to understand the factors contributing to or inhibiting engagement in the collaborative process of technology development and adoption for field use and identify emerging technology needs. High cost was the main barrier to technology use across occupations, while development of new technologies faced barriers of cost and partner communication. Automated processing of data streams was the largest emerging need, and respondents focused mainly on applications for individual-level monitoring and automated image processing. Cross-discipline collaborations and expanded funding networks that encourage cyclical development and continued technical support are needed to address current limitations and meet the growing need for conservation technologies.

Risk perception and tolerance shape variation in agricultural use for a transboundary elephant population.

To conserve wide-ranging species in human-modified landscapes, it is essential to understand how animals selectively use or avoid cultivated areas. Use of agriculture leads to human-wildlife conflict, but evidence suggests that individuals may differ in their tendency to be involved in conflict. This is particularly relevant to wild elephant populations. We analysed GPS data of 66 free-ranging elephants in the Serengeti-Mara ecosystem to quantify their use of agriculture. We then examined factors influencing the level of agricultural use, individual change in use across years and differences in activity budgets associated with use. Using clustering methods, our data grouped into four agricultural use tactics: rare (<0.6% time in agriculture; 26% of population), sporadic (0.6%-3.8%; 34%), seasonal (3.9%-12.8%; 31%) and habitual (>12.8%; 9%). Sporadic and seasonal individuals represented two-thirds (67%) of recorded GPS fixes in agriculture, compared to 32% from habitual individuals. Increased agricultural use was associated with higher daily distance travelled and larger home range size, but not with age or sex. Individual tactic change was prevalent and the habitual tactic was maintained in consecutive years by only five elephants. Across tactics, individuals switched from diurnal to nocturnal activity during agricultural use, interpreted as representing similar risk perception of cultivated areas. Conversely, tactic choice appeared to be associated with differences in risk tolerance between individuals. Together, our results suggest that elephants are balancing the costs and benefits of crop usage at both fine (e.g. crop raid events) and long (e.g. yearly tactic change) temporal scales. The high proportion of sporadic and seasonal tactics also highlights the importance of mitigation strategies that address conflict arising from many animals, rather than targeted management of habitual crop raiders. Our approach can be applied to other species and systems to characterize individual variation in human resource use and inform mitigations for human-wildlife coexistence.

Tracking changes and preventing loss in critical tiger habitat.

The global population of wild tigers remains dangerously low at fewer than 3500 individuals. Habitat loss, along with poaching, can undermine the international target recovery of doubling the number of wild tigers by 2022. Using a new satellite-based monitoring system, we analyzed 14 years of forest loss data within the 76 landscapes (ranging from 278 to 269,983 km(2)) that have been prioritized for conservation of wild tigers. Our analysis provides an update of the status of tiger habitat and describes new applications of technology to detect precisely where forest loss is occurring in order to curb future habitat loss. Across the 76 landscapes, forest loss was far less than anticipated (79,597 ± 22,629 km(2), 7.7% of remaining habitat) over the 14-year study period (2001-2014). Habitat loss was unevenly distributed within a subset of 29 landscapes deemed most critical for doubling wild tiger populations: 19 showed little change (1.5%), whereas 10 accounted for more than 98% (57,392 ± 16,316 km(2)) of habitat loss. Habitat loss in source population sites within 76 landscapes ranged from no loss to 435 ± 124 km(2) ([Formula: see text], SD = 89, total = 1676 ± 476 km(2)). Doubling the tiger population by 2022 requires moving beyond tracking annual changes in habitat. We highlight near-real-time forest monitoring technologies that provide alerts of forest loss at relevant spatial and temporal scales to prevent further erosion.