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The Rarest and Least Protected Forests in Biodiversity Hotspots

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The Rarest and Least Protected Forests in Biodiversity Hotspots Biodivers Conserv DOI 10.1007/s10531-012-0384-1 ORIGINAL PAPER The rarest and least protected forests in biodiversity hotspots Thomas W. Gillespie • Boris Lipkin • Lauren Sullivan • David R. Benowitz • Stephanie Pau • Gunnar Keppel Received: 20 March 2012 / Accepted: 4 October 2012 Ó Springer Science+Business Media Dordrecht 2012 Abstract The goal of biodiversity hotspots is to identify regions around the world where conservation priorities should be focused. We undertake a geographic information system and remote sensing analysis to identify the rarest and least protected forests in biodiversity hotspots. World Wildlife Fund ecoregions with terrestrial forest were subset from 34 biodiversity hotspots and forest cover calculated from GlobCover data at a 300 m pixel resolution. There were 276 ecoregions in 32 biodiversity hotspots classified as containing terrestrial forests. When the first quartile of forest ecoregions was subset based on smallest extent of forest cover in protected areas, there were 69 rare forests identified within 20 biodiversity hotspots. Most rare forest ecoregions (45) occurred on islands or island archipelagos and 47 rare forest ecoregions contained less than 10 % forest cover in pro- tected areas. San Fe´lix-San Ambrosio Islands Temperate Forests, Tubuai Tropical Moist Forests, Maldives-Lakshadweep-Chagos Archipelago Tropical Moist Forests, and Yap Electronic supplementary material The online version of this article (doi:10.1007/s10531-012-0384-1) contains supplementary material, which is available to authorized users. T. W. Gillespie (&) Á B. Lipkin Á L. Sullivan Á D. R. Benowitz Department of Geography, University of California Los Angeles, Los Angeles, CA 90095-1524, USA e-mail: [email protected] B. Lipkin e-mail: [email protected] L. Sullivan e-mail: [email protected] D. R. Benowitz e-mail: [email protected] S. Pau National Center for Ecological Analysis and Synthesis, Santa Barbara, CA 93101, USA e-mail: [email protected] G. Keppel Institute for Biodiversity and Climate, School of Science, Curtin University, GPO Box U1987, Perth, WA 6845, Australia e-mail: [email protected] 123 Biodivers Conserv Tropical Dry Forests were identified as the least protected and possibly most vulnerable forests within biodiversity hotspots. These ecoregions cover less than 500 km2, forest cover is less than 50 km2, and there are no protected areas. There is a need to update classifications and boundaries of protected areas, insure that islands are included in global land cover datasets, and identify levels of endemism and endangerment within forest ecoregions. This should improve our ability to compare, prioritize, and monitor forests in biodiversity hotspots. Keywords Biodiversity hotspots Á Forest conservation Á Geographic information systems Á ESA Globcover Á Protected areas Introduction Biodiversity hotspots are regions around the world with exceptional concentrations of endemic species that are experiencing an exceptional loss of habitat due to humans (Myers et al. 2000). The goal of biodiversity hotspots is to identify regions around the world where conservation priorities should be focused (Conservation International 2009; Mittermeier et al. 1999; Myers et al. 2000). The rationale is that the funding and resources available for conservation is inadequate to protect all threatened and endangered species in the world and therefore, it would be more effective to concentrate conservation efforts in areas with the highest levels of biodiversity and endangerment that are experiencing the greatest amount of habitat loss (Myers et al. 2000; Myers 2003). A total of 34 biodiversity hotspots have been identified that cover only 2.3 % of the earth’s land surface, but contain over 50 % of the world’s plant species and 42 % of all terrestrial vertebrate species (Conser- vation International 2009). Within these biodiversity hotspots, there are a diverse number of forests types that provide the foundation of biodiversity for a number of species due to their complex vertical structure (MacArthur and MacArthur 1961; Myers et al. 2000). Therefore, there is a need to classify forests as endangered (i.e. high risk of extinction in the wild), vulnerable (i.e. high risk of endangerment in the wild) or rare in biodiversity hotspots to facilitate prioritization of conservation resources (Gaston 1994; IUCN 2011). Several methods are available for classifying the risk status of forests. One method to identify endangered or vulnerable forests is to quantify the number and proportion of threatened taxa (i.e. plants, trees, birds, mammals) within forest types (Fa et al. 2004; Pau et al. 2009). Another method is to consider the entire forest type or forest ecosystem and identify forests that cover a small geographic region, forests that have a small extent of forest cover, and forests with few protected areas (Brooks et al. 2002; Fisher and Lin- denmayer 2007; IUCN 2010; MacArthur and Wilson 1967; Rodrı´guez et al. 2011). This approach takes advantage of recent advances in geographic information systems and satellite imagery that can be used to assess the area and status of forests at a global and regional spatial scale (Duro et al. 2007; Schmitt et al. 2009; Wright et al. 2007). There have been a growing number of studies utilizing remote sensing techniques to compare the extent of forests. Several studies utilize World Wild Life (WWF) ecoregions geographic information system polygons, which provide a standard and repeatable manner in which to classify and demarcate forests (Miles et al. 2006; Olson et al. 2001; Portillo- Quintero and Sa´nchez-Azofeifa 2010; Schmitt et al. 2009). Most recent remote sensing studies of forest cover have used MODIS Vegetation Continuous Fields at a 500 m pixel resolution to quantify forest extent within a region (Miles et al. 2006; Portillo-Quintero and Sa´nchez-Azofeifa 2010; Schmitt et al. 2009). However, there have also been advances in 123 Biodivers Conserv land cover classifications such as the European Space Agency’s GlobCover dataset that provides 22 land cover classes including forest classifications at a 300 m pixel resolution (ESA 2009). While the presence of protected areas does not always guarantee protection (e.g., Shearman and Bryan 2011), forests that contain few or no protected areas are likely to be more vulnerable and adversely affected by agriculture, anthropogenic disturbance such as fire, and non-native species invasions (Caujape´-Castells et al. 2010; Scho¨delbauerova´a et al. 2009; Wright et al. 2007). Most studies have used IUCN and UNEP-WCMC world database of protected areas to identify the extent of protected areas at a global spatial scale and within biodiversity hotspots (CBD 2009; IUCN/UNEP 2009; Duro et al. 2007). This database contains IUCN categories of protected areas that were assigned by governments for their national territory and submitted to the UNEP-WCMC. However, there have been no studies that examine forest cover and forest cover within protected areas in individual forest ecoregions for all biodiversity hotspots. Such integrated baseline data could be important for determining global conservation, research, and funding priorities (Gaston 1994; Schmitt et al. 2009). This research identifies the world’s rarest and least protected forests within biodiversity hotspots by integrating forest cover and extent of protected areas. First, we identify the extent of forest ecoregions within biodiversity hotspots and assess the extent of remaining forests and extent of forest in protected areas. Second, we identify which forest ecoregions are rare based on the extent of forest cover within protected areas for each forest ecoregion. Third, we identify rare forest ecoregions with no protected areas that may be vulnerable within biodiversity hotspots. Methods GIS and remote sensing data Geographic Information System layers were collected to identify forest ecoregions, eco- region extent, forest cover, and protected areas within biodiversity hotspots. Biodiversity hotspot polygons containing all 34 biodiversity hotspots were acquired from Conservation International (2009) (Fig. 1). This is an updated version of Myers et al. (2000) original 25 biodiversity hotspots (Conservation International 2009). WWF ecoregions polygons were acquired from the World Wildlife Fund (2009). The WWF has identified 825 terrestrial ecoregions defined as ‘‘large units of land and water containing a geographically distinct assemblage of species, natural communities, and environmental conditions’’ (Olson et al. 2001; Schmitt et al. 2009) (Fig. 1). The European Space Agency’s GlobCover Land Cover v2.1 dataset was created using the MERIS (MEdium Resolution Image Spectrometer) sensor on board the ENVISAT satellite. MERIS has fifteen spectral bands that can be selected by ground command at a 300 m pixel resolution. GlobCover Land Cover v2.1 contains 22 global land cover classes that were defined based on the United Nations Cover Classification Systems and was released to the public in September 2008 (ESA 2009). The GlobCover land cover product was based on data collected from January 2005 to June 2006 and it is considered one of the highest-resolution global land cover products with an the overall accuracy 70.7 % (Bontemps et al. 2011). However, the MERIS sensor lacks a short-wave infrared band that hampers discrimination among flooded forests (i.e. swamps or mangroves) (Bontemps et al. 2011). GlobCover includes six terrestrial forest land cover classifications [5 m tall: closed to open ([15 %) broadleaved evergreen
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