Through the eye of a Gobi khulan – Application of camera collars for ecological research of far-ranging species in remote and highly variable ecosystems

Abstract

The Mongolian Gobi-Eastern Steppe Ecosystem is one of the largest remaining natural drylands and home to a unique assemblage of migratory ungulates. Connectivity and integrity of this ecosystem are at risk if increasing human activities are not carefully planned and regulated. The Gobi part supports the largest remaining population of the Asiatic wild ass ( Equus hemionus ; locally called “khulan”). Individual khulan roam over areas of thousands of square kilometers and the scale of their movements is among the largest described for terrestrial mammals, making them particularly difficult to monitor. Although GPS satellite telemetry makes it possible to track animals in near-real time and remote sensing provides environmental data at the landscape scale, remotely collected data also harbors the risk of missing important abiotic or biotic environmental variables or life history events. We tested the potential of animal born camera systems (“camera collars”) to improve our understanding of the drivers and limitations of khulan movements. Deployment of a camera collar on an adult khulan mare resulted in 7,881 images over a one-year period. Over half of the images showed other khulan and 1,630 images showed enough of the collared khulan to classify the behaviour of the animals seen into several main categories. These khulan images provided us with: i) new insights into important life history events and grouping dynamics, ii) allowed us to calculate time budgets for many more animals than the collared khulan alone, and iii) provided us with a training dataset for calibrating data from accelerometer and tilt sensors in the collar. The images also allowed to document khulan behaviour near infrastructure and to obtain a day-time encounter rate between a specific khulan with semi-nomadic herders and their livestock. Lastly, the images allowed us to ground truth the availability of water by: i) confirming waterpoints predicted from other analyses, ii) detecting new waterpoints, and iii) compare precipitation records for rain and snow from landscape scale climate products with those documented by the camera collar. We discuss the added value of deploying camera collars on a subset of animals in remote, highly variable ecosystems for research and conservation.

Hidden treasure of the Gobi: understanding how water limits range use of khulan in the Mongolian Gobi

“…We identified a set of 53 waterpoints which must be considered as having population-level importance (key waterpoints). At the same time, there is clear evidence that khulan are negatively impacted by human activities and livestock presence 34,43,55,56 . To ensure the long-term survival of the khulan in the South Gobi Region, key waterpoints should receive some form of protection that at a minimum ensures unlimited access by wildlife and limits disturbance to the surrounding habitat.…”

“…Ground-truthing waterpoints. We opportunistically ground-truthed waterpoints for the presence of water or signs of recent khulan use (direct observations, tracks, dung) through: (1) field visits in March 2014 to inspect locations where many khulan tracks converged in the snowless winter of 2013/14, (2) field visits in July 2017 to waterpoints identified by the water finding algorithm that fell near our travel route, (3) photographs of waterpoints taken by a khulan with a camera collar at locations that overlapped with waterpoints identified by our water-finding algorithm 56 , and 4) a list of 45 waterpoints mapped by other researchers during field work 2013-2017 that overlapped with waterpoints identified by our water-finding algorithm.…”

“…We had previously found good agreement of this landscape-scale precipitation data with localized rain information from a weather station at the Oyu Tolgoi mine site (JP unpubl. data) and evidence of rain from camera collar images 56 . For each khulan, we calculated the daily rainfall as the mean of the grid values which were intersected by its hourly GPS positions.…”

Post-release Movement Behaviour and Survival of Kulan Reintroduced to the Steppes and Deserts of Central Kazakhstan

“…This point-in-time coincided with the normal birthing and mating period of kulan in the Altyn Emel source population, and the two mares which split off first had faecal oestrogen and progesterone levels which suggested that they were pregnant (Kaczensky et al, 2020). It is therefore quite possible that they left the group or stayed behind to give birth (Estep et al, 1995;Kaczensky et al, 2019).…”

Is water an important resource for the snow leopard (Panthera uncia) in periods when terrain is covered with snow?

“…However, further research based on rigorous study designs is required to understand the snow leopard's dependence on water across its habitat. Various methods can be used, including telemetry, high-intensity camera trapping with multiple units, and potentially even animal-mounted cameras (Rutz et al 2007;Kaczensky et al 2019).…”