In recent years, tree-ring databases have emerged as a remarkable resource for ecological research, allowing us to address ecological questions at unprecedented temporal and spatial scales. However, concerns regarding big tree-ring data limitations and risks have also surfaced, leading to questions about their potential to be representative of long-term forest responses. Here, we highlight three paths of action to improve on tree-ring databases in ecology: 1) Implementing consistent bias analyses in large dendroecological databases and promoting community-driven data to address data limitations, 2) Encouraging the integration of tree-ring data with other ecological datasets, and 3) Promoting theory-driven, mechanistic dendroecological research. These issues are increasingly important for tackling pressing cross-disciplinary research questions. Finally, although we focus here on tree ring databases, these points apply broadly across many aggregative databases in ecology.
Keywords: Big data; Data biases; Dendroecology; Ecology; Representativity; Tree-ring.
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