Related Experiment Video
Updated: Mar 26, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Spatially-Correlated Risk in Nature Reserve Site Selection
Heidi J Albers1, Gwenlyn M Busby2, Bertrand Hamaide3
1Haub School of Environment and Natural Resources, Department of Economics and Finance, University of Wyoming, Laramie, Wyoming, 82072, United States of America.
Conservation planning must account for spatially correlated threats like fires and pests to effectively protect species. This study optimizes reserve networks by comparing scenarios with and without correlated risks, improving species survival strategies.
Area of Science:
- Conservation Biology
- Ecology
- Environmental Management
Background:
- Nature reserves are crucial for species protection against habitat loss.
- Post-establishment threats like fires and pests can still endanger species within reserves.
- Reserve networks aim to maximize species survival through redundancy.
Purpose of the Study:
- To develop a reserve site selection framework incorporating spatially correlated risks.
- To compare optimal reserve networks with and without spatial risk correlation.
- To enhance conservation planning by addressing realistic post-establishment threats.
Main Methods:
- Developed an optimization framework for reserve site selection.
- Modeled reserve networks under scenarios with and without spatially correlated risks.
- Applied the framework to a stylized landscape and an Oregon landscape.
Main Results:
- Spatially correlated risks significantly impact optimal reserve network design.
- Ignoring spatial correlation can lead to suboptimal reserve selection and reduced species protection.
- The framework provides a feasible method for incorporating correlated risks.
Conclusions:
- Conservation planning must consider spatially correlated threats for effective reserve network design.
- The developed framework offers a valuable tool for future conservation efforts.
- Integrating realistic risk assessments enhances the resilience of protected areas.
More Related Videos
14:27Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
12:26Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
Published on: October 11, 2016
Related Concept Videos
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
Relative Risk
Conservation of Small Populations
Conservation of Declining Populations
Critical Region, Critical Values and Significance Level
In hypothesis testing, a sample statistic is converted to a test statistic using z, t, or chi-square distribution. A critical region is an area under the curve in probability distributions demarcated by the critical value. When the test statistic falls in this region, it suggests that the null hypothesis must be rejected. As this region contains all those values of the...
Distribution and Dispersion