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Updated: Jul 4, 2026
09:36
Measurement of Spatial Stability in Precision Grip
Published on: June 4, 2020
Sensitivity of population viability to spatial and nonspatial parameters using GRIP
J M R Curtis1, I Naujokaitis-Lewis
1Centre for Applied Conservation Research, University of British Columbia, Forest Sciences Building, 2424 Main Mall, Vancouver, British Columbia V6T 1Z4, Canada. janelle.curtis@pac.dfo-mpo.gc.ca
Summary
A new program, GRIP, enables sensitivity analysis for spatial population viability analysis (PVA) models. It efficiently ranks spatial and non-spatial parameters, revealing spatial factors as most influential for species conservation planning.
Area of Science:
- Ecology and Evolutionary Biology
- Conservation Biology
- Computational Biology
Background:
- Metapopulation dynamics are crucial for species conservation but are influenced by uncertain spatial parameters (habitat amount/arrangement).
- Population Viability Analysis (PVA) models assess extinction risk, but spatial PVAs often lack comprehensive sensitivity analyses for both spatial and non-spatial factors due to tool limitations.
Purpose of the Study:
- To develop GRIP, a computationally efficient program for sensitivity analysis of spatial and non-spatial parameters in RAMAS Metapop PVA models.
- To evaluate GRIP's effectiveness in identifying influential parameters and assess the impact of spatial parameters on conservation predictions.
Main Methods:
- GRIP generates random input files by varying PVA parameters (vital rates, dispersal, habitat configuration, catastrophes) based on specified distributions.
- Sensitivity analysis was performed on a published sand lizard (Lacerta agilis) PVA model using GRIP.
- Standardized Regression Coefficients (SRCs) and nonparametric correlation coefficients were used to quantify parameter influence on predicted conservation status.
Main Results:
- GRIP successfully ranked the relative influence of input parameters, identifying key factors with a single analysis.
- Sensitivity analyses revealed that spatial parameters were the most influential factors affecting the predicted conservation status of the sand lizard.
- The program demonstrated superior efficiency compared to previous multi-analysis approaches.
Conclusions:
- GRIP provides a valuable, efficient tool for conducting sensitivity analyses in spatial PVA, aiding conservation planning.
- Highlighting the significant impact of spatial parameters, the study emphasizes the need to prioritize their accurate estimation and management.
- The provided annotated code allows for customization and application to diverse species and complex spatial PVA models.
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