Optimal Sampling Regimes for Estimating Population Dynamics

TL;DR

This paper introduces an optimized sampling strategy for ecological population studies that reduces field effort while maximizing data quality, based on population growth models.

Contribution

It proposes a novel sampling regime design tailored to population dynamics, improving efficiency over traditional regular sampling methods.

Findings

Reduced sampling effort without loss of data quality

Maximized information gained from fewer samples

Enhanced decision-making for environmental management

Abstract

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.