The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake

Tulloch, Ayesha I. T., Tulloch, Vivitskaia J. D., Evans, Megan C. and Mills, Morena (2014) The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake. Conservation Biology, 28 6: 1462-1473. doi:10.1111/cobi.12403


Author Tulloch, Ayesha I. T.
Tulloch, Vivitskaia J. D.
Evans, Megan C.
Mills, Morena
Title The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake
Journal name Conservation Biology   Check publisher's open access policy
ISSN 0888-8892
1523-1739
Publication date 2014-12-01
Year available 2014
Sub-type Article (original research)
DOI 10.1111/cobi.12403
Open Access Status
Volume 28
Issue 6
Start page 1462
End page 1473
Total pages 12
Place of publication Hoboken, NJ United States
Publisher Blackwell Publishing
Collection year 2015
Language eng
Formatted abstract
Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple-use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders’ willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders’ decisions to engage in management. To test the utility of our best-supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost-effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost-effective for prioritizing management when social data collection costs were low (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost-efficient and effective manner.
Keyword Conservation opportunity
Critical weight range mammals
Incentive mechanisms
Invasive species control
Species distribution model
Threatened species management
Willingness to engage
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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