Prioritizing global conservation efforts. Nature
ABSTRACT One of the most pressing issues facing the global conservation community is how to distribute limited resources between regions identified as priorities for biodiversity conservation. Approaches such as biodiversity hotspots, endemic bird areas and ecoregions are used by international organizations to prioritize conservation efforts globally. Although identifying priority regions is an important first step in solving this problem, it does not indicate how limited resources should be allocated between regions. Here we formulate how to allocate optimally conservation resources between regions identified as priorities for conservation--the 'conservation resource allocation problem'. Stochastic dynamic programming is used to find the optimal schedule of resource allocation for small problems but is intractable for large problems owing to the "curse of dimensionality". We identify two easy-to-use and easy-to-interpret heuristics that closely approximate the optimal solution. We also show the importance of both correctly formulating the problem and using information on how investment returns change through time. Our conservation resource allocation approach can be applied at any spatial scale. We demonstrate the approach with an example of optimal resource allocation among five priority regions in Wallacea and Sundaland, the transition zone between Asia and Australasia.
Full-textDOI: · Available from: Kerrie Ann Wilson, Sep 26, 2015
- SourceAvailable from: Peter Mumby
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- "Conservation of species richness alone may not always be appropriate (e.g. Wilson et al. 2006) as species identity and conservation goals are important, but conservation of reef structure may benefit ongoing functioning of coral reefs threatened by disturbance (Graham et al. 2015). Sampling Orbicella reefs which tend to have the highest benthic and fish diversity in the Caribbean (Mumby et al. 2008), and which retain substantial complexity, may overestimate the effects of persistent loss in habitat structure at metapopulation scales. "
ABSTRACT: There has been ongoing flattening of Caribbean coral reefs with the loss of habitat having severe implications for these systems. Complexity and its structural components are important to fish species richness and community composition, but little is known about its role for other taxa or species-specific responses. This study reveals the importance of reef habitat complexity and structural components to different taxa of macrofauna, total species richness, and individual coral and fish species in the Caribbean. Species presence and richness of different taxa were visually quantified in one hundred 25-m(2) plots in three marine reserves in the Caribbean. Sampling was evenly distributed across five levels of visually estimated reef complexity, with five structural components also recorded: the number of corals, number of large corals, slope angle, maximum sponge and maximum octocoral height. Taking advantage of natural heterogeneity in structural complexity within a particular coral reef habitat (Orbicella reefs) and discrete environmental envelope, thus minimizing other sources of variability, the relative importance of reef complexity and structural components was quantified for different taxa and individual fish and coral species on Caribbean coral reefs using boosted regression trees (BRTs). Boosted regression tree models performed very well when explaining variability in total (82·3%), coral (80·6%) and fish species richness (77·3%), for which the greatest declines in richness occurred below intermediate reef complexity levels. Complexity accounted for very little of the variability in octocorals, sponges, arthropods, annelids or anemones. BRTs revealed species-specific variability and importance for reef complexity and structural components. Coral and fish species occupancy generally declined at low complexity levels, with the exception of two coral species (Pseudodiploria strigosa and Porites divaricata) and four fish species (Halichoeres bivittatus, H. maculipinna, Malacoctenus triangulatus and Stegastes partitus) more common at lower reef complexity levels. A significant interaction between country and reef complexity revealed a non-additive decline in species richness in areas of low complexity and the reserve in Puerto Rico. Flattening of Caribbean coral reefs will result in substantial species losses, with few winners. Individual structural components have considerable value to different species, and their loss may have profound impacts on population responses of coral and fish due to identity effects of key species, which underpin population richness and resilience and may affect essential ecosystem processes and services.Journal of Animal Ecology 09/2015; DOI:10.1111/1365-2656.12429 · 4.50 Impact Factor
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- "Within the SCP framework, spatial conservation prioritization (Moilanen et al. 2009) is the process of using spatial analysis to identify locations for conservation investments. This can include data on threats, the costs of conservation actions and budget availability (Wilson et al. 2006); it can also account for social factors determining the feasibility of actions (Mills et al. 2013). "
ABSTRACT: World governments have committed to increase the global protected areas coverage by 2020, but the effectiveness of this commitment for protecting biodiversity depends on where new protected areas are located. Threshold-based and complementarity-based approaches have been independently used to identify important sites for biodiversity. Here we bring together these approaches by performing a complementarity-based analysis of irreplaceability in Important Bird and Biodiversity Areas (IBAs; which are sites identified using a threshold-based approach). We determined whether irreplaceability values are higher inside than outside IBAs, and whether any observed difference depends on known characteristics of the IBAs. We focussed on three regions having comprehensive IBAs inventories and bird distribution atlases: Australia, Southern Africa and Europe. Irreplaceability values were significantly higher inside than outside IBAs, although differences were much smaller in Europe than elsewhere. Higher irreplaceability values in IBAs were associated with: presence and number of restricted-range species; number of criteria under which the site was identified; and mean geographic range size of the species for which the site was identified ('trigger species'). In addition, IBAs were characterised by higher irreplaceability values when using proportional species representation targets, rather than fixed targets. There were broadly comparable results both when measuring irreplaceability for trigger species and when considering all bird species, indicating a good surrogacy effect of the former. Recently the International Union for Conservation of Nature has convened a consultation to consolidate global standards for the identification of Key Biodiversity Areas (KBAs), building from existing approaches like IBAs. Our results are important for informing this consultation, and in particular for a proposed irreplaceability criterion that will allow the new KBA standard to draw on the strengths of both threshold-based and complementarity-based approaches. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.Conservation Biology 08/2015; DOI:10.1111/cobi.12609 · 4.17 Impact Factor
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- "er et al . , 1998 ; Olson & Dinerstein , 1998 ; Myers et al . , 2000 ; O ' Connor , Marvier & Kareiva , 2003 ; Possingham & Wilson , 2005 ; Brooks et al . , 2006 ; Margules & Sarkar , 2006 ; Isaac et al . , 2007 ) . A large number of conservation priority - setting approaches have been documented in the literature ( e . g . Brooks et al . , 2006 ; Wilson et al . , 2006 ; Pressey et al . , 2007 ; bs_bs_banner Animal Conservation . Print ISSN 1367 - 9430 Treblico et al . , 2011 ; Selig et al . , 2014 ) . One species - based method considers the evolutionary relationships within a clade of target species ( Vane - Wright , Humphries & Williams , 1991 ; Faith , 1992 , 1996 , 2007 ) alongside threat status "
ABSTRACT: Assemblages of corals, sponges, foraminifera, sediment bacteria and sediment archaea were assessed at two depths in the Spermonde Archipelago. Our goal was to assess to what extent variation in composition could be explained by habitat and water quality variables. The habitat variables consisted of depth, substrate type and scleractinian coral cover while water quality variables were derived from ocean color satellite imagery, including the colored dissolved organic matter index (CDOM), chlorophyll-a (Chlor-a) and remote sensing reflectance at 645nm (Rrs_645). Together, habitat and water quality variables explained from 31% (sediment bacteria) to 80% (forams) of the variation in composition. The variation in composition of corals, sponges, forams and sediment archaea was primarily related to habitat variables, while the variation in composition of sediment bacteria was primarily related to water quality variables. Habitat and water quality variables explained similar amounts of variation in the composition of corals and sediment bacteria. CDOM (sponges, sediment bacteria and sediment archaea), Chlor-a (corals and forams) and Rrs_645 (sponges and forams) proved significant predictors of variation in composition for the studied taxa. In addition to water quality variables, all taxa responded to a range of habitat variables including depth and the percentage cover of various benthic life forms including coral cover variables, rubble and sand. Sand cover was the most important habitat variable for corals, sponges, sediment bacteria and sediment archaea. Coral life forms including the cover of branching and tabular corals were important habitat variables for sponges and forams. These results show marked differences in how various taxa respond to variation in habitat and water quality in the Spermonde Archipelago. Moreover, our results indicate that variables estimated from ocean color satellite imagery proved to be better predictors of variation in marine community composition than commonly-used proxies such as the distance offshore or distance to the nearest river. Copyright © 2015 Elsevier B.V. All rights reserved.Science of The Total Environment 08/2015; 537:139-151. DOI:10.1016/j.scitotenv.2015.07.102 · 4.10 Impact Factor