Photo by William Kleedehn, Wirestock / Getty Images
By Dr. Valli Fraser-Celin
Mukhopadhyay et al., (2024). Hierarchical Bayesian Integrated Modeling of Age- and Sex-Structured Wildlife Population Dynamics | Journal of Agricultural, Biological and Environmental Statistics
Climate change, habitat loss, and pollution are driving major biodiversity losses around the world, including large wild mammals. For example, close to 60% of large wild herbivores are faced with extinction. To develop conservation strategies, we need to understand how a population of animals is doing and what is driving them to decline.
Population models are used in conservation science to predict population variations and try to understand what is driving population changes. They can be used to list species into categories based on their population size, or can be used by wildlife managers to determine appropriate population mitigation strategies. However, data on large wild mammals is scarce and developing models is a complex task, meaning we have little information on the specific factors influencing large wild mammal declines.
Having reliable data and population dynamics models can help conservationists understand what is driving population declines for particular species. This is why a group of scientists developed a new population model that considers “how large mammal populations interact with each other and their environment while also incorporating their detailed biology” (Ogutu, 2024).
The model brings together various data to track and then estimate population trends. Data include biological data such as age, sex, and birth rates alongside environmental data like temperature and rainfall, as well as population sizes collected via aerial and ground surveys. The model can predict population decline in two ways:
- It examines how environmental factors (e.g. rainfall) affect populations (e.g. birth rates).
- It allows users to create different simulations of how changes in different factors affect population.
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The authors then tested this model on the topi, a large species of antelope experiencing population decline across Eastern Africa, of which the causes haven’t been completely determined yet. Based on long-term data on the species, like population survey data, ground survey data, life histories, predation risk, and environmental seasonality, the model found that topi population declines can be attributed to “environmental changes, human activities and predation” (Ogutu, 2024).
What is unique about this model is that it combines different kinds of data and examines large mammal population decline in a holistic way, while other models may only approach this issue through one type of data set. The group of scientists who developed this model are now working on making it more user friendly, increasing the capacity to integrate even more features, for example, livestock numbers, and applying the model to other species.
This newly developed model can assist policy makers and conservationists to develop accurate and appropriate conservation and management plans for wild mammal populations, saving valuable, and limited, time and resources.
About Dr. Valli Fraser-Celin
Dr. Valli Fraser-Celin holds a PhD in Geography from the University of Guelph where she studied human-African wild dog conflict and conservation in Botswana, Africa. Valli has always been interested in the human dimensions of wildlife, in particular, humans’ relationships with large carnivores, she collaborated with the Fur-Bearers on a research project exploring Canadians’ perceptions of and knowledge about wolves. Valli is also passionate about dogs, and advocates for dog welfare through her Instagram @thelivesofwilddogs. In her spare time, she runs a pet pantry at her local community centre for pet guardians experiencing pet food insecurity.
