STERGMs

STERGMs, or Spatially-Temporally Explicit Resident Generalised Markov Models, are a class of statistical models used in ecological research to analyze population dynamics. These models are designed to account for both the spatial distribution and temporal changes of individuals within a population, as well as incorporating environmental factors that can influence these dynamics. The "Generalised" aspect implies flexibility in how different states and transitions are defined, allowing for application to a wide range of ecological questions.

At their core, STERGMs are based on Markov chain principles, where the probability of transitioning to a future state depends only on the current state. However, STERGMs extend this by explicitly modeling these transitions as occurring in space and time. This means that the movement of individuals between different locations, their survival or death, and their reproduction are all considered within a structured spatio-temporal framework. Environmental covariates, such as habitat quality or resource availability, can be integrated into the model to explain observed patterns and predict future population changes.

The application of STERGMs is particularly valuable for understanding processes like habitat fragmentation, species dispersal, and the impact of climate change on populations. By providing a detailed and realistic representation of population dynamics, STERGMs aid in the development of more effective conservation and management strategies. Researchers use these models to simulate different scenarios and assess the potential outcomes of various interventions, ultimately contributing to a deeper understanding of ecological systems.