Enhancing wildlife researchers on wildlife study techniques for efficient wildlife population monitoring and research
Over 20 foresters from the Department of Forests and Park Services (DoFPS) were trained on the use of advanced statistical technique and unmarked models for monitoring of wildlife population and effective wildlife research.
The Wildlife Statistical Training in Gelephu saw 21 wildlife researchers explore the fascinating world of wildlife monitoring using advanced statistical techniques and unmarked models.
The week-long training was held collaboration with the Department of Forests and Park Services from May 29 till June 3 in Gelephu, Sarpang. The training is expected to build the capacity of Bhutanese wildlife researchers on wildlife study techniques and create a good pool of trained professional in the country.
Wildlife biologists from WWF Tigers Alive Initiative and WWF-US Dr. Thomas Gray and Dr Arnaud Lyet facilitated the week-long training that aimed to enhance the capacity and of foresters to estimate abundance, density, and monitor wildlife population trends.
The participants were introduced to R programming and essential concepts in wildlife monitoring with camera traps. The participants gained insights into study design principles, detection probabilities, and considerations for cost-effective monitoring and models for monitoring.
Royle-Nichols and N Mixture models took center stage, offering robust approaches to estimate abundance from non-randomly deployed camera traps. Attendees engaged in practical sessions, implementing these models in R programing to gain hands-on experience.
The foresters explored the use of unmarked models to estimate densities covering included viewshed-based density estimators, measuring camera-trap detection areas, space to event models, and camera-trap distance sampling. Participants learned the statistical methods, assumptions, and limitations of these powerful density estimation techniques.
The following day focused on the practical implementation of camera-trap data analysis using camera trap distance sampling (CTDS) and space to event (STE) models in R. Attendees immersed themselves in analyzing real-world data, gaining proficiency in these techniques.
The training also featured sessions on advanced models such as spatially explicit capture-mark recapture (SECR) for estimating marked animals, individual-based spatial explicit models, and multi-state occupancy models. The participants gained insights into cutting-edge techniques for wildlife monitoring.
Additionally, the participants were introduced to the exciting world of environmental DNA (eDNA) and its applications in monitoring tiger and prey populations. The eDNA Atlas of Biodiversity showcased the potential of this innovative approach.
The participants are equipped with the knowledge and skills to contribute to wildlife conservation in Bhutan and beyond. The future holds great promise for the monitoring of tigers, prey, and other species in Bhutan, with advanced models and technology leading the way.
Sangay Rabten from Thimphu
