Article ; Online: The case for research integration, from genomics to remote sensing, to understand biodiversity change and functional dynamics in the world's lakes.
2020 Volume 26, Issue 6, Page(s) 3230–3240
Abstract: ... including traditional taxonomic and newer types of data (e.g., eDNA, remote sensing), to more ... Freshwater ecosystems are heavily impacted by multiple stressors, and a freshwater biodiversity ... crisis is underway. This realization has prompted calls to integrate global freshwater ecosystem data ...
| Abstract | Freshwater ecosystems are heavily impacted by multiple stressors, and a freshwater biodiversity crisis is underway. This realization has prompted calls to integrate global freshwater ecosystem data, including traditional taxonomic and newer types of data (e.g., eDNA, remote sensing), to more comprehensively assess change among systems, regions, and organism groups. We argue that data integration should be done, not only with the important purpose of filling gaps in spatial, temporal, and organismal representation, but also with a more ambitious goal: to study fundamental cross-scale biological phenomena. Such knowledge is critical for discerning and projecting ecosystem functional dynamics, a realm of study where generalizations may be more tractable than those relying on taxonomic specificity. Integration could take us beyond cataloging biodiversity losses, and toward predicting ecosystem change more broadly. Fundamental biology questions should be central to integrative, interdisciplinary research on causal ecological mechanisms, combining traditional measures and more novel methods at the leading edge of the biological sciences. We propose a conceptual framework supporting this vision, identifying key questions and uncertainties associated with realizing this research potential. Our framework includes five interdisciplinary "complementarities." First, research approaches may provide comparative complementarity when they offer separate realizations of the same focal phenomenon. Second, for translational complementarity, data from one research approach is used to translate that from another, facilitating new inferences. Thirdly, causal complementarity arises when combining approaches allows us to "fill in" cause-effect relationships. Fourth, contextual complementarity is realized when together research methodologies establish the wider ecological and spatiotemporal context within which focal biological responses occur. Finally, integration may allow us to cross inferential scales through scaling complementarity. Explicitly identifying the modes and purposes of integrating research approaches, and reaching across disciplines to establish appropriate collaboration will allow researchers to address major biological questions that are more than the sum of the parts. |
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| MeSH term(s) | Biodiversity ; Ecosystem ; Genomics ; Lakes ; Remote Sensing Technology |
| Language | English |
| Publishing date | 2020-03-29 |
| Publishing country | England |
| Document type | Journal Article |
| ZDB-ID | 1281439-8 |
| ISSN | 1365-2486 ; 1354-1013 |
| ISSN (online) | 1365-2486 |
| ISSN | 1354-1013 |
| DOI | 10.1111/gcb.15045 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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