Abstract
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.
| Original language | English (US) |
|---|---|
| Article number | 177244 |
| Journal | Science of the Total Environment |
| Volume | 955 |
| DOIs |
|
| State | Published - Dec 10 2024 |
| Externally published | Yes |
Keywords
- Big data
- Data biases
- Dendroecology
- Ecology
- Representativity
- Tree-ring
ASJC Scopus subject areas
- Environmental Engineering
- Environmental Chemistry
- Waste Management and Disposal
- Pollution
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