Design of reserve networks and the persistence of biodiversity

Cabeza, Mar; Moilanen, Atte

doi:10.1016/s0169-5347(01)02125-5

Cited by 408 publications

(302 citation statements)

References 40 publications

Supporting

Mentioning

286

Contrasting

Unclassified

Order By: Relevance

“…Indeed, the extensive literature on the development of methods for the selection of priority areas has focussed on finding the minimum set of areas that represent all species in occurrence locations (Williams 1998;Cabeza and Moilanen 2001), or, recently, on finding appropriate areas that maximise probabilities of species persistence (Rodrigues et al 2000;Williams and Araujo 2000;Araujo et al 2002;Bonn et al 2002). This view has become so predominant, that the performance of existing protected area systems is commonly measured in terms of the proportion of the regional, threatened or endemic species pool that it encompasses (Siegfried 1989;Lombard 1995;Eeley et al 2001;Moore et al 2003).…”

Section: Introductionmentioning

confidence: 99%

Capturing biodiversity: selecting priority areas for conservation using different criteria

2005

View full text Add to dashboard Cite

Abstract. International treaties call for the protection of biodiversity in all its manifestations, including ecosystem and species diversities. The selection of most priority area networks focuses, however, primarily on species richness and occurrence. The effectiveness of this approach in capturing higher order manifestations of biodiversity, that is ecosystem and environmental diversity patterns, remains poorly understood. Using a case study of birds and environmental data from South Africa and Lesotho, we test how complementary networks that maximise species diversity perform with regard to their representation of ecosystem and environmental diversity, and vice versa. We compare these results to the performance of the existing reserve network. We conclude that focusing on any single biodiversity component alone is insufficient to protect other components. We offer explanations for this in terms of the autocorrelation of species diversity in environmental space.

show abstract

Section: Introductionmentioning

confidence: 99%

Capturing biodiversity: selecting priority areas for conservation using different criteria

2005

View full text Add to dashboard Cite

show abstract

“…Faith and Walker 1996a;Ferrier 2002;Venevsky and Venevskaia 2005) or land class data (land types sensu Pressey 2004). However, most former Systematic Conservation Planning applications have been academic rather than practical, being the results of area selection methods generally ignored by conservation planners (Prendergast et al 1999;Cabeza and Moilanen 2001; but see Pressey and Cowling 2001;Cowling et al 2003b;or Airame et al 2003). Given the foregoing, Conservation Biogeography during the coming decades should strive to reconcile the need for a 'great synthesis,' to be presented as a unitary front to society and layman, with the possible scepticism that might arise from rapid science-based decision-taking in a field still in its infancy (Whittaker et al 2005).…”

Section: E Environment-based Approachmentioning

confidence: 99%

A synecological framework for systematic conservation planning

Hortal

Lobo

2006

Biodiv. Inf.

View full text Add to dashboard Cite

Abstract.− Biodiversity conservation design, though difficult with fragmentary or insufficient biological data, can be planned and evaluated with several methods. One of them, the complementarity criterion, is commonly used to account for the distributions of a number of species (i.e., an autoecological approach). At the same time, the patchiness and spatial bias of available distribution data has also been dealt with through distribution modelling. However, both the uncertainty of the ranges estimated and the changes in species' distributions in response to changing climates, limit the potential of single-species distributions as the biodiversity attribute to be used in complementarity strategies. Several technical and theoretical advantages of composite biodiversity variables (i.e., a synecological approach) may, however, make them ideal biodiversity indicators for conservation area selection. The drawbacks associated with current biodiversity data are discussed herein, along with the possible advantages and disadvantages of conservation planning through a synecological or autoecological approach.

show abstract

“…At present, many algorithms have already been developed to create a reserve network that maximizes regional biodiversity representation (see Cabeza & Moilanen, 2001, for a recent review). These methods can be based simply on occurrence data for a group of species (Church et al, 1996;Pressey et al, 1997;Araújo & Williams, 2000;Polasky et al, 2000;Briers, 2002).…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, there are now many sophisticated optimization algorithms based on either linear programming or more complex computational procedures (i.e., the MetropolisHasting networks) that find optimal, non-sequential solutions for an entire network (Possingham et al, 2000;Cabeza & Moilanen, 2001). Although heuristic algorithms usually produce sub-optimal solutions for the network (i.e., they usually have…”

mentioning

confidence: 99%

Priority areas for anuran conservation using biogeographical data: a comparison of greedy, rarity, and simulated annealing algorithms to define reserve networks in Cerrado

et al. 2005

View full text Add to dashboard Cite

Spatial patterns in biodiversity variation at a regional scale are rarely taken into account when a natural reserve is to be established, despite many available methods for determining them. In this paper, we used dimensions of occurrence of 105 species of Anura (Amphibia) in the cerrado region of central Brazil to create a regional system of potential areas that preserves all regional diversity, using three different algorithms to establish reserve networks: "greedy", rarity, and simulated annealing algorithms. These generated networks based on complementarity with 10, 12, and 8 regions, respectively, widely distributed in the biome, and encompassing various Brazilian states. Although the purpose of these algorithms is to find a small number of regions for which all species are represented at least once, the results showed that 67.6%, 76.2%, and 69.5% of the species were represented in two or more regions in the three networks. Simulated annealing produced the smallest network, but it left out three species (one endemic). On the other hand, while the greedy algorithm produce a smaller solution, the rarity-based algorithm ensured that more species were represented more than once, which can be advantageous because it takes into consideration the high levels of habitat loss in the cerrado. Although usually coarse, these macro-scale approaches can provide overall guidelines for conservation and are useful in determining the focus for more local and effective conservation efforts, which is especially important when dealing with a taxonomic group such as anurans, for which quick and drastic population declines have been reported throughout the world.

show abstract

Design of reserve networks and the persistence of biodiversity

Cited by 408 publications

References 40 publications

Capturing biodiversity: selecting priority areas for conservation using different criteria

Capturing biodiversity: selecting priority areas for conservation using different criteria

A synecological framework for systematic conservation planning

Priority areas for anuran conservation using biogeographical data: a comparison of greedy, rarity, and simulated annealing algorithms to define reserve networks in Cerrado

Contact Info

Product

Resources

About