Landscape Dynamics (landDX) an open-access spatial-temporal database for the Kenya-Tanzania borderlands

Land use drives differential resource selection by African elephants in the Greater Mara Ecosystem, Kenya

Understanding drivers of space use by African elephants is critical to their conservation and management, particularly given their large home-ranges, extensive resource requirements, ecological role as ecosystem engineers, involvement in human-elephant conflict and as a target species for ivory poaching. In this study we investigated resource selection by elephants inhabiting the Greater Mara Ecosystem in Southwestern Kenya in relation to three distinct but spatially contiguous management zones: (i) the government protected Maasai Mara National Reserve (ii) community-owned wildlife conservancies, and (iii) elephant range outside any formal wildlife protected area. We combined GPS tracking data from 49 elephants with spatial covariate information to compare elephant selection across these management zones using a hierarchical Bayesian framework, providing insight regarding how human activities structure elephant spatial behavior. We also contrasted differences in selection by zone across several data strata: sex, season and time-of-day. Our results showed that the strongest selection by elephants was for closed-canopy forest and the strongest avoidance was for open-cover, but that selection behavior varied significantly by management zone and selection for cover was accentuated in human-dominated areas. When contrasting selection parameters according to strata, variability in selection parameter values reduced along a protection gradient whereby elephants tended to behave more similarly (limited plasticity) in the human dominated, unprotected zone and more variably (greater plasticity) in the protected reserve. However, avoidance of slope was consistent across all zones. Differences in selection behavior was greatest between sexes, followed by time-of-day, then management zone and finally season (where seasonal selection showed the least differentiation of the contrasts assessed). By contrasting selection coefficients across strata, our analysis quantifies behavioural switching related to human presence and impact displayed by a cognitively advanced megaherbivore. Our study broadens the knowledge base about the movement ecology of African elephants and builds our capacity for both management and conservation.

Fencing amplifies individual differences in movement with implications on survival for two migratory ungulates

Fences have recently been recognized as one of the most prominent linear infrastructures on earth. As animals traverse fenced landscapes, they adjust movement behaviours to optimize resource access while minimizing energetic costs of coping with fences. Examining individual responses is key for connecting localized fence effects with population dynamics. We investigated the multi-scale effects of fencing on animal movements, space use and survival of 61 pronghorn and 96 mule deer on a gradient of fence density in Wyoming, USA. Taking advantage of the recently developed Barrier Behaviour Analysis, we classified individual movement responses upon encountering fences (i.e. barrier behaviours). We adopted the reaction norm framework to jointly quantify individual plasticity and behavioural types of barrier behaviours, as well as behaviour syndromes between barrier behaviours and animal space use. We also assessed whether barrier behaviours affect individual survival. Our results highlighted a high-level individual plasticity encompassing differences in the degree and direction of barrier behaviours for both pronghorn and mule deer. Additionally, these individual differences were greater at higher fence densities. For mule deer, fence density determined the correlation between barrier behaviours and space use and was negatively associated with individual survival. However, these relationships were not statistically significant for pronghorn. By integrating approaches from movement ecology and behavioural ecology with the emerging field of fence ecology, this study provides new evidence that an extraordinarily widespread linear infrastructure uniquely impacts animals at the individual level. Managing landscape for lower fence densities may help prevent irreversible behavioural shifts for wide-ranging animals in fenced landscapes.

Advancing fence datasets: Comparing approaches to map fence locations and specifications in southwest Montana

Fencing is a major anthropogenic feature affecting wildlife distributions and movements, but its impacts are difficult to quantify due to a widespread lack of spatial data. We created a fence model and compared outputs to a fence mapping approach using satellite imagery in two counties in southwest Montana, USA to advance fence data development for use in research and management. The model incorporated road, land cover, ownership, and grazing boundary spatial layers to predict fence locations. We validated the model using data collected on randomized road transects (n = 330). The model predicted ~34,700 km of fences with a mean fence density of 0.93 km/km2 and a maximum density of 14.9 km/km2. We also digitized fences using Google Earth Pro in a random subset of our study area in survey townships (n = 50). The Google Earth approach showed greater agreement (K = 0.76) with known samples than the fence model (K = 0.56) yet was unable to map fences in forests and was significantly more time intensive. We also compared fence attributes by land ownership and land cover variables to assess factors that may influence fence specifications (e.g., wire heights) and types (e.g., number of barbed wires). Private land fences had bottom wires that were closer to the ground and top wires higher from the ground when compared to fences on public lands, with sample means at ~22 cm and ~26 cm, and ~115 cm and ~111 cm, respectively. Both bottom wire means were well below recommended heights for ungulates navigating underneath fencing (≥ 46 cm), while top wire means were closer to the 107 cm maximum fence height recommendation. We found that both fence type and land ownership were correlated (χ2 = 45.52, df = 5, p = 0.001) as well as fence type and land cover type (χ2 = 140.73, df = 15, p = 0.001). We provide tools for estimating fence locations, and our novel fence type assessment demonstrates an opportunity for updated policy to encourage the adoption of “wildlife-friendlier” fencing standards to facilitate wildlife movement in the western U.S. while supporting rural livelihoods.

Increasing Anthropogenic Disturbance Restricts Wildebeest Movement Across East African Grazing Systems

The ability to move is essential for animals to find mates, escape predation, and meet energy and water demands. This is especially important across grazing systems where vegetation productivity can vary drastically between seasons or years. With grasslands undergoing significant changes due to climate change and anthropogenic development, there is an urgent need to determine the relative impacts of these pressures on the movement capacity of native herbivores. To measure these impacts, we fitted 36 white-bearded wildebeest (Connochaetes taurinus) with GPS collars across three study areas in southern Kenya (Amboseli Basin, Athi-Kaputiei Plains, and Mara) to test the relationship between movement (e.g., directional persistence, speed, home range crossing time) and gradients of vegetation productivity (i.e., NDVI) and anthropogenic disturbance. As expected, wildebeest moved the most (21.0 km day–1; CI: 18.7–23.3) across areas where movement was facilitated by low human footprint and necessitated by low vegetation productivity (Amboseli Basin). However, in areas with moderate vegetation productivity (Athi-Kaputiei Plains), wildebeest moved the least (13.3 km day–1; CI: 11.0–15.5). This deviation from expectations was largely explained by impediments to movement associated with a large human footprint. Notably, the movements of wildebeest in this area were also less directed than the other study populations, suggesting that anthropogenic disturbance (i.e., roads, fences, and the expansion of settlements) impacts the ability of wildebeest to move and access available resources. In areas with high vegetation productivity and moderate human footprint (Mara), we observed intermediate levels of daily movement (14.2 km day–1; CI: 12.3–16.1). Wildebeest across each of the study systems used grassland habitats outside of protected areas extensively, highlighting the importance of unprotected landscapes for conserving mobile species. These results provide unique insights into the interactive effects of climate and anthropogenic development on the movements of a dominant herbivore in East Africa and present a cautionary tale for the development of grazing ecosystems elsewhere.