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BIOFRAG - a new database for analyzing BIOdiversity responses to forest FRAGmentation
Marion Pfeifer1, Veronique Lefebvre1, Toby A Gardner2
1Department of Life Sciences, Imperial College London Silwood Park Campus, Ascot, SL5 7PY, U.K.
Ecology and Evolution
|June 27, 2014
Summary
A new relational database consolidates biodiversity data from habitat fragmentation studies. This resource aids in synthesizing complex results and understanding land-use change impacts on species across diverse ecosystems.
Area of Science:
- Ecology
- Conservation Biology
- Biodiversity Science
Background:
- Habitat fragmentation research yields complex, inconsistent results due to varied methodologies and data.
- Synthesizing findings is challenging without standardized data collation and access.
- A unified approach is needed to analyze biodiversity responses to fragmentation.
Purpose of the Study:
- To present a novel relational database for collating and standardizing primary biodiversity data from habitat fragmentation studies.
- To link field data with taxonomic, spatial, temporal, and environmental information for robust analysis.
- To facilitate large-scale syntheses and re-examinations of fragmentation impacts.
Main Methods:
- Development of a relational database linking field data (species presence, abundance, ground cover) to plot attributes.
- Inclusion of taxonomic nomenclature, spatial and temporal plot details, and environmental characteristics.
- Data compilation from 58 landscapes across six biogeographic realms, encompassing diverse taxa.
Main Results:
- The database contains 9,830 unique species records from 58 landscapes.
- Includes data on mammals, birds, insects, plants, fungi, and more, with 711 species found in multiple landscapes.
- Features three long-term time-series datasets (>10 years).
Conclusions:
- The standardized database enables consistent data retrieval and analysis of biodiversity responses to fragmentation.
- Facilitates testing generalizations across diverse systems and taxa, and addressing methodological challenges like pseudo-replication.
- Supports broad syntheses of land-use effects and encourages ongoing data contributions for dynamic updates.
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