Comparison of Two Types of Metapopulation Models in Real and Artificial Landscapes

• Published in: Conservation biology 2001-08, Vol.15 (4), p.1102-1113
• Main Authors: Hokit, D. Grant, Stith, Bradley M., Branch, Lyn C.
• Format: Article
• Language: English
• Subjects: Animal, plant and microbial ecology; Applied ecology; Biological and medical sciences; Conservation biology; Conservation, protection and management of environment and wildlife; Demography; Ecological modeling; Fecundity; Fundamental and applied biological sciences. Psychology; Habitat conservation; Lizards; Metapopulation ecology; Modeling; Parametric models; Parks, reserves, wildlife conservation. Endangered species: population survey and restocking; Sceloporus woodi; Simulations
• ISSN: 0888-8892; 1523-1739
• DOI: 10.1046/j.1523-1739.2001.0150041102.x

Application of metapopulation models is becoming increasingly widespread in the conservation of species in fragmented landscapes. We provide one of the first detailed comparisons of two of the most common modeling techniques, incidence function models and stage-based matrix models, and test their accuracy in predicting patch occupancy for a real metapopulation. We measured patch occupancies and demographic rates for regional populations of the Florida scrub lizard (Sceloporus woodi) and compared the observed occupancies with those predicted by each model. Both modeling strategies predicted patch occupancies with good accuracy (77-80%) and gave similar results when we compared hypothetical management scenarios involving removal of key habitat patches and degradation of habitat quality. To compare the two modeling approaches over a broader set of conditions, we simulated metapopulation dynamics for 150 artificial landscapes composed of equal-sized patches (2-1024 ha) spaced at equal distances (50-750 m). Differences in predicted patch occupancy were small to moderate (50%. Incidence function models and stage-based matrix models differ in their approaches, assumptions, and requirements for empirical data, and our findings provide evidence that the two models can produce different results. We encourage researchers to use both techniques and further examine potential differences in model output. The feasibility of obtaining data for population modeling varies widely among species and limits the modeling approaches appropriate for each species. Understanding different modeling approaches will become increasingly important as conservation programs undertake the challenge of managing for multiple species in a landscape context.