2020/09/24 by Rebecca E. Atanga, Atanga, Rebecca E., Edward L. Boone +7
Computer Science · Environmental Science · Mathematics · #Data Analysis with R #Ecology and Vegetation Dynamics Studies #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Methods and Bayesian Inference #stat.ME
paper · pdf · doi:10.48550/arxiv.2009.11797
openalex publication_date 2020/09/24 · arxiv created 2021/02/02 · arxiv updated 2021/02/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Ecologists are interested in modeling the population growth of species in various ecosystems. Studying population dynamics can assist environmental managers in making better decisions for the environment. Traditionally, the sampling of species and tracking of populations have been recorded on a regular time frequency. However, sampling can be an expensive process due to available resources, money and time. Limiting sampling makes it challenging to properly track the growth of a population. Thus, we propose a new and novel approach to designing sampling regimes based on the dynamics associated with population growth models. This design study minimizes the amount of time ecologists spend in the field, while maximizing the information provided by the data.