Search

Nomadic movements are often a consequence of unpredictable resource dynamics. However, how nomadic ungulates select dynamic resources is still understudied. Here we examined resource selection of nomadic Mongolian gazelles (Procapra gutturosa) in the Eastern Steppe of Mongolia. We used daily GPS locations of 33 gazelles tracked up to 3.5 years. We examined selection for forage during the growing season using the Normalized Difference Vegetation Index (NDVI). In winter we examined selection for snow cover which mediates access to forage and drinking water. We studied selection at the population level using resource selection functions (RSFs) as well as on the individual level using step-selection functions (SSFs) at varying spatio-temporal scales from 1 to 10 days. Results from the population and the individual level analyses differed. At the population level we found selection for higher than average NDVI during the growing season. This may indicate selection for areas with more forage cover within the arid steppe landscape. In winter, gazelles selected for intermediate snow cover, which may indicate preference for areas which offer some snow for hydration but not so much as to hinder movement. At the individual level, in both seasons and across scales, we were not able to detect selection in the majority of individuals, but selection was similar to that seen in the RSFs for those individuals showing selection. Difficulty in finding selection with SSFs may indicate that Mongolian gazelles are using a random search strategy to find forage in a landscape with large, homogeneous areas of vegetation. The combination of random searches and landscape characteristics could therefore obscure results at the fine scale of SSFs. The significant results on the broader scale used for the population level RSF highlight that, although individuals show uncoordinated movement trajectories, they ultimately select for similar vegetation and snow cover. [ABSTRACT FROM AUTHOR]

Conservation of nomadic species presents significant conservation challenges because of unpredictability in their movements and space use. Long‐term studies on nomadic species offering insights into the variability in space use within and between years are largely missing but are necessary to develop effective conservation strategies.We examined the temporal variability in space‐use of Mongolian gazelle, a nomadic species. We tracked 22 individuals for 1–3 years with GPS and used the resulting movement patterns to evaluate conservation strategies associated with their nomadic movements in the intact open plain grasslands of Mongolia. Individuals exhibited a high degree of variability in space use within and between years, often using different wintering areas in different years. The individual range size varied as much as threefold between years, with an estimated average annual individual range size of ~19,000 km2 and a lifetime range of ~100,000 km2.Comparing simulated and empirical GPS trajectories for the Mongolian gazelle showed that they avoided disturbed areas (e.g. oil fields) and did not prefer protected areas. Importantly, no single protected area in the region was large enough to cover the annual range of any of the tracked gazelle.Because of their wide‐ranging movements, the presence of linear infrastructure and the resulting barrier effects are a particular concern. We found that fences along the national border were absolute barriers affecting movements of about 80% of all tracked individuals. When gazelle encounter the border fence, they moved a median distance of 11 km along fences, suggesting frequent crossing options are needed to make barriers permeable.Synthesis and applications. We show that for nomadic species whose space use varies greatly across years, multiyear movement data are essential for sound conservation planning. We emphasize that place‐based approaches alone are insufficient to conserve wide‐ranging nomadic species and that linear infrastructure, including fences, highways and railroads, is of particular concern. Because nomadic species lack defined movement corridors, we advocate integrated land use planning that prioritizes permeability across the entire landscape and facilitates long‐distance movements. We suggest that conservation strategies for nomadic species in arid and semi‐arid regions be reconsidered based on multiyear connectivity assessments at the landscape scale. We show that for nomadic species whose space use varies greatly across years, multiyear movement data are essential for sound conservation planning. We emphasize that place‐based approaches alone are insufficient to conserve wide‐ranging nomadic species and that linear infrastructure, including fences, highways and railroads, is of particular concern. Because nomadic species lack defined movement corridors, we advocate integrated land use planning that prioritizes permeability across the entire landscape and facilitates long‐distance movements. We suggest that conservation strategies for nomadic species in arid and semi‐arid regions be reconsidered based on multiyear connectivity assessments at the landscape scale. [ABSTRACT FROM AUTHOR]

Increasing habitat fragmentation and disturbance threaten long-distance movements of ungulates. While the effects of impermeable barriers on ungulate migrations have been well researched, quantitative evidence for gradual, long-term changes of mobility remains rare. We investigated changes in movement behavior of Mongolian gazelle Procapra gutturosa using GPS tracking data collected from 62 gazelle individuals between 2007 and 2021. We quantified 16-day displacement distances as a metric for long-distance movements before using linear mixed models, generalized additive models and quantile regressions to assess how anthropogenic and environmental factors affected gazelle movement behavior. Long-distance 16-day movements decreased by 36 %, from 142 km in 2007 to 92 km in 2021. Changes in mobility were affected by increasing vehicle numbers in Mongolia, but could not be explained by concurrent changes in other environmental factors like temperature, precipitation or vegetation greenness. Gazelle movement decreased close to roads, and gazelles stayed further away from roads during the snow-free season, when traffic likely is most intense. Conserving landscape permeability is essential for maintaining populations of highly mobile species. Our study provides evidence for a gradual decline in gazelle mobility over fifteen years as a response to increasing anthropogenic impact. The transportation infrastructure permeating the Eastern Steppe does not pose physical barriers, yet our findings suggest that increasing traffic volume may create semipermeable barriers to gazelle movement. As human activity is increasing, interactions between ungulates and vehicle traffic need to be closely monitored to identify and mitigate semipermeable barrier effects before landscape permeability is severely altered. [ABSTRACT FROM AUTHOR]

Understanding animal movement is a key challenge in ecology and conservation biology. Relocation data often represent a complex mixture of different movement behaviors, and reliably decomposing this mix into its component parts is an unresolved problem in movement ecology. Traditional approaches, such as composite random walk models, require that the timescales characterizing the movement are all similar to the usually arbitrary data-sampling rate. Movement behaviors such as long-distance searching and fine-scale foraging, however, are often intermixed but operate on vastly different spatial and temporal scales. An approach that integrates the full sweep of movement behaviors across scales is currently lacking. Here we show how the semivariance function (SVF) of a stochastic movement process can both identify multiple movement modes and solve the sampling rate problem. We express a broad range of continuous-space, continuous-time stochastic movement models in terms of their SVFs, connect them to relocation data via variogram regression, and compare them using standard model selection techniques. We illustrate our approach using Mongolian gazelle relocation data and show that gazelle movement is characterized by ballistic foraging movements on a 6-h timescale, fast diffusive searching with a 10-week timescale, and asymptotic diffusion over longer timescales.