Literature DB >> 10600609

Finding the Missing Link between Landscape Structure and Population Dynamics: A Spatially Explicit Perspective.

Thorsten Wiegand, Kirk A Moloney, Javier Naves, Felix Knauer.   

Abstract

We construct and explore a general modeling framework that allows for a systematic investigation of the impact of changes in landscape structure on population dynamics. The essential parts of the framework are a landscape generator with independent control over landscape composition and physiognomy, an individual-based spatially explicit population model that simulates population dynamics within heterogeneous landscapes, and scale-dependent landscape indices that depict the essential aspects of landscape that interact with dispersal and demographic processes. Landscape maps are represented by a grid of [Formula: see text] cells and consist of good-quality, poor-quality, or uninhabitable matrix habitat cells. The population model was shaped in accordance to the biology of European brown bears (Ursus arctos), and demographic parameters were adjusted to yield a source-sink configuration. Results obtained with the spatially explicit model do not confirm results of earlier nonspatial source-sink models where addition of sink habitat resulted in a decrease of total population size because of dilution of high-quality habitat. Our landscape indices, which describe scale-dependent correlation between and within habitat types, were able to explain variations in variables of population dynamics (mean number of females with sink home ranges, mean number of females with source home ranges, and mean dispersal distance) caused by different landscape structure. When landscape structure changed, changes in these variables generally followed the corresponding change of an appropriate landscape index in a linear way. Our general approach incorporates source-sink dynamics as well as metapopulation dynamics, and the population model can easily be modified for other species groups.

Entities:  

Keywords:  habitat connectivity; heterogeneous landscapes; population dynamics; scale‐dependent landscape indices; source‐sink dynamics; spatially explicit population models

Year:  1999        PMID: 10600609     DOI: 10.1086/303272

Source DB:  PubMed          Journal:  Am Nat        ISSN: 0003-0147            Impact factor:   3.926


  17 in total

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7.  An approach to predict risks to wildlife populations from mercury and other stressors.

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Review 9.  Simple process-based simulators for generating spatial patterns of habitat loss and fragmentation: a review and introduction to the G-RaFFe model.

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10.  SEARCH: Spatially Explicit Animal Response to Composition of Habitat.

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Journal:  PLoS One       Date:  2013-05-22       Impact factor: 3.240

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