Unveiling Ecological Dynamics Through Simulation and Visualization of Biodiversity Data Cubes

Description

Simulation studies offer numerous benefits due to their ability to mimic real-world scenarios in controlled and customisable environments. Ecosystems and biodiversity data are very complex and involve a multitude of interacting factors. Simulations allow researchers to model and understand the complexity of ecological systems by varying parameters such as spatial and/or temporal clustering, species prevalence, etc.

During the B-Cubed hackathon, we have created a simulation framework for biodiversity data cubes using the R programming language. The framework starts from simulating a species distributed in a landscape over a temporal scope. In a second phase, the simulation of a variety of observation processes and effort generates the actual occurrence datasets. Based on their (simulated) spatial uncertainty, occurrences can then be designated to a grid to form a data cube.

The simulation framework can be used to assess multiple research questions under different parameter settings, such as the effect of clustering on occurrence-to-grid designation and the effect of different patterns of missingness on data quality and indicator robustness. Simulation studies can incorporate scenarios with missing data, allowing researchers to assess the impact of data gaps on analyses.

In this workshop, we will go over the results from the B-Cubed hackathon regarding this framework, show how users can utilise the R code in practise, and we can discuss how we can still improve the framework.

Period	15-Apr-2024