A Dynamic Analysis of Northern Spotted Owl Viability in a Fragmented Forest Landscape*

Lamberson, Roland H.; McKelvey, Robert; Noon, Barry R.; Voss, Curtis

doi:10.1046/j.1523-1739.1992.06040505.x

Cited by 205 publications

(103 citation statements)

References 5 publications

(8 reference statements)

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“…A few studies have examined the impact of Allee effects on patch loss in metapopulations, finding an extinction threshold below which the metapopulation becomes extinct (Lande, 1987;Lamberson et al, 1992;Amarasekare, 1998;Groom, 1998). This paper will examine the impact of an Allee effect on the persistence time of a metapopulation with a fixed number of patches.…”

Section: Introductionmentioning

confidence: 99%

Mean time to extinction of a metapopulation with an Allee effect

Brassil

2001

Ecological Modelling

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The incorporation of Allee effects into a simple metapopulation extinction model reveals a large non-linear reduction in mean time to extinction with small changes in an Allee limit. The extent of this reduction is dependent on the level of migration in the metapopulation. With small amounts of migration, small changes in the Allee limit result in large changes in the mean time to extinction. With higher levels of migration, the mean time to extinction is not as sensitive to changes in the Allee limit, becoming more similar to the single population case. The metapopulation modeled here is a set of nine patches, driven to extinction by environmental stochasticity. A generalized Allee effect is incorporated by a modification of the standard logistic model. The sensitivity of the mean time to extinction to small changes in the Allee limit is especially relevant to population viability analysis, which uses estimates of extinction times for management decisions.

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Section: Introductionmentioning

confidence: 99%

Mean time to extinction of a metapopulation with an Allee effect

Brassil

2001

Ecological Modelling

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“…In contrast to island models, stepping-stone models have an explicit spatial dimension and can account for dispersal distances and environmental variability with a spatial structure. Recently, there have been dramatic increases in the level of sophistication in stepping-stone models and some results have had profound effects on the design of managed landscapes (e.g., Lamberson et al 1992). …”

Section: Keymentioning

confidence: 99%

“…Interpatch distance plays a critical role in island biogeographic theory (MacArthur and Wilson 1967) and metapopulation theory (Levins 1970, Gilpin andHanski 1991) and has been discussed in the context of conservation biology (e.g., Burkey 1989). The role of interpatch distance in metapopulations has had a preeminent role in recent conservation efforts for endangered species (e.g., Lamberson et al 1992). Clearly, nearest-neighbor distance can be an important characteristic of the landscape depending on the phenomenon under investigation.…”

Section: Nearest-neighbor Metricsmentioning

confidence: 99%

Modelling the susceptibility of pine stands to bark stripping by Chacma baboons (Papio ursinus) in the Mpumalanga Province of South Africa

2017

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PREFACE and 2.0 UPGRADE INFORMATIONAs the authors of FRAGSTATS, we are VERY concerned about the potential for misuse of this program. Like most tools, FRAGSTATS is only as "good" as the user. FRAGSTATS crunches out a lot of numbers about the input landscape. These numbers can easily become "golden" in the hands of uninformed users. Unfortunately, the "garbage in-garbage out" axiom applies here. We have done our best in the documentation to stress the importance of defining landscape, patch, matrix, and landscape context at a scale and in a manner that is relevant and meaningful to the phenomenon under consideration. Moreover, we have stressed the importance of understanding the exact meaning of each metric before it is used. These and other important considerations in any landscape structural analysis are discussed in the documentation. We strongly urge you to read the entire documentation, especially the section on Key Concepts and Terminology, before ever running FRAGSTATS.We wish to remind users that we are not in the commercial software marketing business. We are scientists who recognized the need for a tool like FRAGSTATS to assist us in our research on landscape ecological issues. Therefore, we do not wish to spend a great deal of time consulting on trivial matters concerning the use of FRAGSTATS. However, we do recognize an obligation to provide some level of information support. Of course, we welcome and encourage your criticisms and suggestions about the program at all times. We will welcome questions about how to run FRAGSTATS or interpret the output only after the user has read the entire documentation. This is only fair and will eliminate many trivial questions. Finally, we are always interested in learning about how others have applied FRAGSTATS in ecological investigations and management applications. Therefore, we encourage you to contact us and describe your application after using FRAGSTATS.This release of FRAGSTATS (version 2.0) differs from the previous version in only minor ways. Several "bugs" have been corrected. The most important change is the added option to treat a specified proportion of the landscape boundary and background edge (instead of just all or none) as true edge in the edge metrics (bound_wght option). This fraction also is used as the edge contrast weight for landscape boundary and background edge segments in the calculation of edge contrast metrics. In addition, the convention for naming the output file containing patch ID's in the raster version has been modified to comply with DOS requirements on a PC (id_image option). Similarly, the output file name extensions in the PC raster version have been shortened and renamed to comply with DOS requirements and to avoid conflicts with ERDAS conventions (out_file). The Nearest-neighbor algorithm has been modified slightly to compute actual edge-to-edge distance (previous version used cell midpoints rather than edge).We hope that FRAGSTATS is of great assistance in your work and we look forward to hearing about your applications. A...

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“…For example, Lamberson et al (1992) reported there is a significant threshold effect in the relationship between the northern spotted owl survival and suitable habitat. When suitable habitat is less than 10% of landscape, the chance for northern spotted owl to survive would be zero; however, when suitable habitat reaches 15% of the landscape, the chance of survival would reach 80%, and when suitable habitat reaches 20% of the landscape, the chance of survival would reach 95%.…”

Section: Threshold Effectsmentioning

confidence: 99%

Using Sciences to Improve the Economic Efficiency of Conservation Policies

2004

Agric. resour. econ. rev.

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In the last 20 years, both public and private expenditures on resource conservation and environmental protection have increased dramatically. However, there are numerous technical and political barriers to the efficient use of conservation funds. This paper discusses some of these barriers and approaches to overcoming them. It argues that ecosystem complexities such as threshold effects, ecosystem linkages, and spatial connections often mitigate against politically palatable criteria for resource allocation. Ignoring these complexities is likely to result in substantial efficiency losses. While challenges are daunting for the efficient management of conservation investments, payoff is potentially high for the use of sciences.

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A Dynamic Analysis of Northern Spotted Owl Viability in a Fragmented Forest Landscape*

Cited by 205 publications

References 5 publications

Mean time to extinction of a metapopulation with an Allee effect

Mean time to extinction of a metapopulation with an Allee effect

Modelling the susceptibility of pine stands to bark stripping by Chacma baboons (Papio ursinus) in the Mpumalanga Province of South Africa

Using Sciences to Improve the Economic Efficiency of Conservation Policies

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