Strategies of Reserve Selection

Abstract

Existing protected areas contain only a biased sample of the Earth's biodiversity. This is because conservation has to compete with other land‐uses. Limitations in space and budget highlight the importance of effective and efficient conservation strategies. In this context, questions like what elements of biodiversity should we focus on, and where to protect them, are difficult to answer. The field of spatial conservation planning has evolved to address these questions, with attention to cost‐efficiency, representativeness, adequacy, flexibility, threat and vulnerability. It encourages politicians and conservation planners to set quantitative conservation goals, and offers tools to prioritize among large sets of species, ecosystem types and areas. The implementation of this approach is becoming essential in order to halt the loss of biodiversity in a world of increasing human population and increasing demand for natural resources.

Key concepts

  • Protected areas have long been established opportunistically resulting in inefficient spending of conservation funds.

  • Scoring methods rank individual sites according to their conservation value, but cannot guide the design of networks efficiently.

  • Complementarity‐based approaches instead, evaluate the value of the network as a whole, thus achieving cost‐efficiency in reserve network design.

  • Aiming at representation of species or ecosystems in reserves is insufficient. Conservation goals and their derived targets should aim at persistence if biodiversity loss is to be halted.

  • To achieve cost‐efficiency, targets have to be explicit and quantitative.

  • A large suit of tools exists to aid conservation decision‐making under conditions where data is incomplete or of poor quality – typical for biodiversity data. More or better data is indispensable, but meanwhile decision‐making can proceed.

  • Although the perfect biodiversity surrogate does not exist, basing the design of reserve networks on information for a number of taxa produces promising results.

  • Connectivity of reserve networks promotes the persistence of species in fragmented landscapes.

  • One‐size‐fits‐all solutions do not always exist. Species or habitats may require different conservation actions, leading to inevitable trade‐offs.

  • Although spatial prioritization has been mostly used to locate protected areas, it can be used to assist the identification and location of most suitable management actions.

Keywords: biodiversity representation; cost‐efficiency; reserve network design; spatial prioritization; systematic conservation planning

Figure 1.

Conservation priority areas selected in waters of trawlable depth in New Zealand's Exclusive Economic Zone. The gradation in colours indicates different levels of priority, with lowest ranks being top priorities. (a) Analysis ignoring costs, aiming at maximizing the protection of 96 fish species; (b) including cost constraints, depending on fishing intensity as recorded by fishermen. The table reflects costs and benefits from the top 10% priorities (dark blue) in the two analyses. When maximizing the protection of species, highest conservation value is achieved, but results in a notable reduction of fishing opportunities (22%). When constraining the analysis with fishing costs, the spatial solution is markedly different, achieving however only moderately less conservation returns (23.4%) than the biodiversity approach, but without loss of current fishing activity. Modified from Leathwick et al..

Figure 2.

Effects of the use of weights to prioritize species differently on the average levels of representation, when applied to 75 vascular plant species characteristic of herb‐rich forest in Finland. Results are expressed as the mean percentage of populations represented for the species in each class (common, rare or red‐listed). When weights were used (dark grey), each species received a value depending upon regional rarity, threat status (re‐list classification) and taxonomic value. Courtesy of A. Arponen, based on Arponen et al..

Figure 3.

Predicted average representation for 3 groups of species in 45 mesic semi‐natural grassland sites (Finland), for which the intensity of habitat management is optimized (three management options by cattle grazing: annual grazing, biennial grazing and no grazing). The species (Lepidoptera and plant species) are grouped by their grazing intensity preference (panels). The grazing intensity is optimized for all sites for the joint set of species, for combinations of budget (y‐axis) and weights (x‐axis). Next, species representation was estimated from the predicted responses of species to management intensity and other site conditions, for each combination of budget and weight. Management cost increased with grazing intensity and site area. Weights refer to the weight assigned to the species that prefer annual grazing; the most expensive management option. Other species received a weight of one. Representation for each species was scaled to their maximum possible representation. The figure shows trade‐offs in representation between different species groups; only higher weights and sufficient budget can increase the representation of species depending on annual grazing, although this goes at the cost of representation of species preferring less intense grazing. See also Van Teeffelen et al..

close

References

Alagador D and Cerdeira JO (2007) Designing spatially explicit reserve networks in the presence of mandatory sites. Biological Conservation 137: 254–262.

Andelman SJ and Fagan WF (2000) Umbrellas and flagships: efficient conservation surrogates or expensive mistakes? Proceedings of the National Academy of Sciences of the USA 97: 5954–5959.

Araújo MB, Cabeza M, Thuiller W, Hannah L and Williams PH (2004) Would climate change drive species out of reserves? Testing the robustness of existing reserve‐selection methods in Europe. Global Change Biology 10: 1618–1626.

Araújo MB, Williams PH and Fuller RJ (2002) Dynamics of extinction and the selection of nature reserves. Proceedings of the Royal Society of London B Biological Sciences 269: 1971–1980.

Arponen A, Heikkinen RK, Thomas CD and Moilanen A (2005) The value of biodiversity in reserve selection: representation, species weighting, and benefit functions. Conservation Biology 19: 2009–2014.

Baillie JEM, Hilton‐Taylor C and Stuart SN (eds) (2004) 2004 IUCN Red List of Threatened Species. A Global Species Assessment. Gland, Switzerland: IUCN.

Bonn A, Rodrigues ASL and Gaston KJ (2002) Threatened and endemic species: are they good indicators of patterns of biodiversity on a national scale? Ecology Letters 5: 733–741.

Brooks TM, Bakarr MI, Boucher TIM et al. (2004) Coverage provided by the global protected‐area system: is it enough? BioScience 54: 1081–1091.

Brooks TM, Mittermeier RA, da Fonseca GAB et al. (2006) Global biodiversity conservation priorities. Science 313: 58–61.

Bruner AG, Gullison RE, Rice RE and da Fonseca GAB (2001) Effectiveness of parks in protecting tropical biodiversity. Science 291: 125–128.

Bryant D, Nielsen D and Tangley L (1997) Last Frontier Forests. Washington, DC: World Resources Institute.

Burgman MA, Possingham HP, Lynch AJJ et al. (2001) A method for setting the size of plant conservation target areas. Conservation Biology 15: 603–616.

Cabeza M (2003) Habitat loss and connectivity of reserve networks in probability approaches to reserve design. Ecology Letters 6: 665–672.

Cabeza M and Moilanen A (2001) Design of reserve networks and the persistence of biodiversity. Trends in Ecology & Evolution 16: 242–248.

Caro TM and O'Doherty G (1999) On the use of surrogate species in conservation biology. Conservation Biology 13: 805–814.

Diamond JM (1975) The island dilemma: lessons of modern biogeographic studies for the design of natural reserves. Biological Conservation 7: 129–146.

Drechsler M, Wätzold F, Johst K, Bergmann H and Settele J (2007) A model‐based approach for designing cost‐effective compensation payments for conservation of endangered species in real landscapes. Biological Conservation 140: 174–186.

Fischer DT and Church RL (2003) Clustering and compactness in reserve site selection: an extension of the Biodiversity Management Area Selection model. Forest Science 49: 555–565.

Frankel OH and Soulé ME (1981) Conservation and Evolution. Cambridge: Cambridge University Press.

Groombridge B and Jenkins MD (2002) World Atlas of Biodiversity: Earth's Living Resources in the 21st Century. Berkeley: University of California Press.

Hanski I (1999) Metapopulation Ecology. Oxford: Oxford University Press.

Hess GR, Bartel RA, Leidner AK et al. (2006) Effectiveness of biodiversity indicators varies with extent, grain, and region. Biological Conservation 132: 448–457.

Leathwick J, Moilanen A, Francis M et al. (2008) Novel methods for the design and evaluation of marine protected areas in offshore waters. Conservation Letters 1: 91–102.

Lomolino MV (2004) Conservation biogeography. In: Lomolino MV and Heaney LR (eds) Frontiers of Biogeography: New Directions in the Geography of Nature, pp. 293–296. Sunderland, MA: Sinauer Associates.

Lund MP and Rahbek C (2002) Cross‐taxon congruence in complementarity and conservation of temperate biodiversity. Animal Conservation 5: 163.

Margules CR and Pressey RL (2000) Systematic conservation planning. Nature 405: 243–253.

McDonnell MD, Possingham HP, Ball IR and Cousins EA (2002) Mathematical methods for spatially cohesive reserve design. Environmental Modeling and Assessment 7: 107–114.

Meir E, Andelman S and Possingham HP (2004) Does conservation planning matter in a dynamic and uncertain world? Ecology Letters 7: 615–622.

Millennium Ecosystem Assessment (2005) Ecosystems and Human Well‐being: Biodiversity Synthesis. Washington, DC: World Resources Institute.

Moilanen A (2005) Reserve selection using non‐linear species distribution models. The American Naturalist 165: 695–706.

Moilanen A and Cabeza M (2007) Accounting for habitat loss rates in sequential reserve selection: simple methods for large problems. Biological Conservation 136: 470–482.

Moilanen A, Franco AMA, Early RE et al. (2005) Prioritizing multiple‐use landscapes for conservation. Proceedings of the Royal Society of London Series B Biological Sciences 272: 1885–1891.

Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB and Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 403: 853–858.

Nalle DJ, Arthur JL and Sessions J (2002) Designing compact and contiguous reserve networks with a hybrid heuristic algorithm. Forest Science 48: 59–68.

Nicholls AO (1998) Integrating population abundance, dynamics and distribution into broad‐scale priority setting. In: Mace G, Balmford A and Ginsberg JR (eds) Conservation in a Changing World. Cambridge: Cambridge University Press.

Pharo EJ, Beattie AJ and Pressey RL (2000) Effectiveness of using vascular plants to select reserves for bryophytes and lichens. Biological Conservation 96: 371–378.

Possingham HP, Andelman SJ, Burgman MA et al. (2002) Limits to the use of threatened species lists. Trends in Ecology and Evolution 17: 503–507.

Prato T (2005) Accounting for uncertainty in making species protection decisions. Conservation Biology 19: 806–814.

Pressey RL (1990) Reserve selection in New South Wales: where to from here? Australian Zoologist 26: 70–75.

Pressey RL (1994) Ad hoc reservations: forward or backward steps in developing representative reserve systems? Conservation Biology 8: 662–668.

Pressey RL, Cowling RM and Rouget M (2003) Formulating conservation targets for biodiversity pattern and process in the Cape Floristic Region, South Africa. Biological Conservation 112: 99–127.

Pressey RL, Possingham HP and Day JR (1997) Effectiveness of alternative heuristic algorithms for identifying indicative minimum requirements for conservation reserves. Biological Conservation 80: 207–219.

Pressey RL, Watts ME and Barrett TW (2004) Is maximizing protection the same as minimizing loss? Efficiency and retention as alternative measures of the effectiveness of proposed reserves. Ecology Letters 7: 1035–1046.

Regan HM, Colyvan M and Burgman MA (2002) A taxonomy and treatment of uncertainty for ecology and conservation biology. Ecological Applications 12: 618–628.

Rodrigues ASL and Brooks TM (2007) Shortcuts for biodiversity conservation planning: the effectiveness of surrogates. Annual Review of Ecology, Evolution and Systematics 38: 713–737.

Runte A (1979) National Parks: The American Experience. Lincoln: University of Nebraska Press.

Scott JM, Anderson H, Davis F et al. (1993) Gap analysis: a geographic approach to protection of biological diversity. Wildlife Monographs 123: 1–41.

Scott JM, Murray M, Wright RG et al. (2001) Representation of natural vegetation in protected areas: capturing the geographic range. Biodiversity and Conservation 10: 1297–1301.

Simberloff D (1998) Flagships, umbrellas, and keystones: is single‐species management passe in the landscape era? Biological Conservation 83: 247–257.

Tear TH, Kareiva P, Angermeier PL et al. (2005) How much is enough? The recurrent problem of setting measurable objectives in conservation. BioScience 55: 835–849.

Van Teeffelen AJA, Cabeza M, Pöyry J, Raatikainen KM and Kuussaari M (2008) Maximising conservation benefit for grassland species with contrasting management requirements. Journal of Applied Ecology 45: 1401–1409.

Vane‐Wright RI, Humphries CJ and Williams PH (1991) What to protect? Systematics and the agony of choice. Biological Conservation 55: 235–254.

Westphal MI, Field SA and Possingham H (2007) Optimizing landscape configuration: a case study of woodland birds in the Mount Lofty Ranges, South Australia. Landscape and Urban Planning 81: 56–66.

World Commission on Protected Areas (2007) World database on protected areas. Available at http://www.unep‐wcmc.org/wdpa/.

Yip JY, Corlett RT and Dudgeon D (2004) A fine‐scale gap analysis of the existing protected area system in Hong Kong, China. Biodiversity and Conservation 13: 943–957.

Further Reading

Margules CR and Sarkar S (2007) Systematic Conservation Planning. Cambridge: Cambridge University Press.

Moilanen A, Possingham HP and Wilson K (eds) (2009) Spatial Conservation Prioritisation: Quantitative Methods and Computational Tools. Oxford: Oxford University Press.

Pressey RL, Cabeza M, Watts ME, Cowling RM and Wilson KA (2007) Conservation planning in a changing world. Trends in Ecology & Evolution 22: 583–592.

Contact Editor close
Submit a note to the editor about this article by filling in the form below.

* Required Field

How to Cite close
Cabeza, Mar, and van Teeffelen, Astrid(Mar 2009) Strategies of Reserve Selection. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0021224]