4.7 Article

Increasing connectivity between metapopulation ecology and landscape ecology

期刊

ECOLOGY
卷 99, 期 5, 页码 1119-1128

出版社

WILEY
DOI: 10.1002/ecy.2189

关键词

Chiricahua leopard frog; conservation; landscape resistance; least-cost path; Markov Chain Monte Carlo; occupancy; spatially explicit; spatially realistic metapopulation theory

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资金

  1. U.S. Geological Survey

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Metapopulation ecology and landscape ecology aim to understand how spatial structure influences ecological processes, yet these disciplines address the problem using fundamentally different modeling approaches. Metapopulation models describe how the spatial distribution of patches affects colonization and extinction, but often do not account for the heterogeneity in the landscape between patches. Models in landscape ecology use detailed descriptions of landscape structure, but often without considering colonization and extinction dynamics. We present a novel spatially explicit modeling framework for narrowing the divide between these disciplines to advance understanding of the effects of landscape structure on metapopulation dynamics. Unlike previous efforts, this framework allows for statistical inference on landscape resistance to colonization using empirical data. We demonstrate the approach using 11 yr of data on a threatened amphibian in a desert ecosystem. Occupancy data for Lithobates chiricahuensis (Chiricahua leopard frog) were collected on the Buenos Aires National Wildlife Refuge (BANWR), Arizona, USA from 2007 to 2017 following a reintroduction in 2003. Results indicated that colonization dynamics were influenced by both patch characteristics and landscape structure. Landscape resistance increased with increasing elevation and distance to the nearest streambed. Colonization rate was also influenced by patch quality, with semi-permanent and permanent ponds contributing substantially more to the colonization of neighboring ponds relative to intermittent ponds. Ponds that only hold water intermittently also had the highest extinction rate. Our modeling framework can be widely applied to understand metapopulation dynamics in complex landscapes, particularly in systems in which the environment between habitat patches influences the colonization process.

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