A population is a group of organisms of the same species. Like canaries in the coalmine, changes in populations of organisms can be important indicators of environmental changes.
The data and model described here with the purpose of understanding controls over biodiversity. A multi-scale approach to understand how local and regional factors affect the community assembly processes that drive emergent patterns. These data allows us to examin a wide range of parameter settings representing ecologically relevant scenarios. We used artificial neural networks (ANNs) to assess the sensitivity of diversity and variation partitioning metrics (calculated from simulation outcomes) to metacommunity parameter settings. Here you will find metadata details, dor detailed information about the simulations results and conclusions, please visit the associated publication at http://onlinelibrary.wiley.com/doi/10.1111/oik.03690/abstract;jsessionid...
Related publications:
A simulation-based approach to understand how metacommunity characteristics influence emergent biodiversity patterns
This simulation is atemporal and non-localized. There is no physical geo-location or calendar time frame or specific season. However, simulations were performed in Aug 2016.