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Biodiversity data integration—the significance of data resolution and domain
Author(s) -
Christian König,
Patrick Weigelt,
Julian Schrader,
Amanda Taylor,
Jens Kattge,
Holger Kreft
Publication year - 2019
Publication title -
plos biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.127
H-Index - 271
eISSN - 1545-7885
pISSN - 1544-9173
DOI - 10.1371/journal.pbio.3000183
Subject(s) - representativeness heuristic , biodiversity , data science , biology , data collection , global biodiversity , computer science , environmental resource management , ecology , psychology , social psychology , statistics , mathematics , environmental science
Recent years have seen an explosion in the availability of biodiversity data describing the distribution, function, and evolutionary history of life on earth. Integrating these heterogeneous data remains a challenge due to large variations in observational scales, collection purposes, and terminologies. Here, we conceptualize widely used biodiversity data types according to their domain (what aspect of biodiversity is described?) and informational resolution (how specific is the description?). Applying this framework to major data providers in biodiversity research reveals a strong focus on the disaggregated end of the data spectrum, whereas aggregated data types remain largely underutilized. We discuss the implications of this imbalance for the scope and representativeness of current macroecological research and highlight the synergies arising from a tighter integration of biodiversity data across domains and resolutions. We lay out effective strategies for data collection, mobilization, imputation, and sharing and summarize existing frameworks for scalable and integrative biodiversity research. Finally, we use two case studies to demonstrate how the explicit consideration of data domain and resolution helps to identify biases and gaps in global data sets and achieve unprecedented taxonomic and geographical data coverage in macroecological analyses.

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