Publication Date
2021
Journal or Book Title
Frontiers In Ecology And The Environment
Abstract
Data integration is a statistical modeling approach that incorporates multiple data sources within a unified analytical framework. Macrosystems ecology – the study of ecological phenomena at broad scales, including interactions across scales – increasingly employs data integration techniques to expand the spatiotemporal scope of research and inferences, increase the precision of parameter estimates, and account for multiple sources of uncertainty in estimates of multiscale processes. We highlight four common analytical challenges to data integration in macrosystems ecology research: data scale mismatches, unbalanced data, sampling biases, and model development and assessment. We explain each problem, discuss current approaches to address the issue, and describe potential areas of research to overcome these hurdles. Use of data integration techniques has increased rapidly in recent years, and given the inferential value of such approaches, we expect continued development and wider application across ecological disciplines, especially in macrosystems ecology.
DOI
https://doi.org/10.1002/fee.2290
Volume
19
Issue
1
Pages
30-38
Special Issue
Macrosystems Biology - Challenges and Successes
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
License
UMass Amherst Open Access Policy
Recommended Citation
Zipkin, Elise F.; Zylstra, Erin R.; Wright, Alexander D.; Saunders, Sarah P.; Finley, Andrew O.; Dietze, Michael C.; Itter, Malcom S.; and Tingley, Morgan W., "Addressing data integration challenges to link ecological processes across scales" (2021). Frontiers In Ecology And The Environment. 426.
https://doi.org/10.1002/fee.2290