Developing “asymmetrical” sampling strategies for networks

The idea of developing “asymmetrical” sampling strategies for networks that span large gradients in biodiversity is a really intriguing one and potentially very useful contribution, as these networks often have limited resources that need to be carefully and thoughtfully applied to maximize return on investment.

in this study we will develop and share the statistical tools (eg, multivariate SE, coverage-based stopping, etc) to allow others to optimize their own sampling.

Quality controlled data for this study is available at the network's drive.

The Data folder has QC'd data from several MBON Pole to Pole sites for test analysis.

Four parts are proposed for a manuscript:

1. History of networked ecology, problems facing large-scale coordinated efforts (eg, no money, limited resources)
2. Use of statistical techniques to optimize effort across biogeographic boundaries
3. Illustrated example using P2P data
4. Description of R toolkit to accompany paper