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Recognizing trade‐offs in multi‐objective land management
Abstract
As natural resource management and conservation goals expand and evolve, practitioners and policy makers are increasingly seeking options that optimize benefits among multiple, often contradictory objectives. Here, we describe a simple approach for quantifying the consequences of alternative management options in terms of benefits and trade‐offs among multiple objectives. We examine two long‐term forest management experiments that span several decades of stand (forest tree community) development and identify substantial trade‐offs among carbon cycling and ecological complexity objectives. In addition to providing improved understanding of the long‐term consequences of various management options, the results of these experiments show that positive benefits resulting from some management options are often associated with large trade‐offs among individual objectives. The approach to understanding benefits and trade‐offs presented here provides a simple yet flexible framework for quantitatively assessing the consequences of different management options.
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Cited by
Thom, D., Golivets, M., Edling, L., Meigs, G. W., Gourevitch, J. D., Sonter, L. J., Galford, G. L., & Keeton, W. S. (2019) · Global Change Biology · doi:10.1111/gcb.14656 · Cited by 71
Metadata
- Authors
- Bradford, J. B., & D'Amato, A. W.
- Venue
- Frontiers in Ecology and the Environment
- Publisher
- Wiley
- Published
- 2011-12-02
- Volume
- 10
- Issue
- 4
- Pages
- 210-216
- ISSN
- 1540-9295 (ISSN-L)
- 1540-9309
- OpenAlex
- W2061069129
- Cited by
- 410
- References
- 0
- FWCI
- 4.36
- Type
- journal article
- Language
- en
- Open access
- closed
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- Bradford, J. B., & D'Amato, A. W. (2012). Recognizing trade‐offs in multi‐objective land management. Frontiers in Ecology and the Environment. https://doi.org/10.1890/110031
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.