Biological Conservation 143 (2010) 992–998

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Biological Conservation journal homepage: www.elsevier.com/locate/biocon

Avian conservation priorities in a top-ranked biodiversity hotspot Clinton N. Jenkins a,b,*, Maria Alice S. Alves c, Stuart L. Pimm b a

Department of Biology, 1210 Biology–Psychology Building, University of Maryland, College Park, MD 20742, USA Nicholas School of the Environment, Box 90328, Duke University, Durham, NC 27708, USA c Departamento de Ecologia, Universidade do Estado do Rio de Janeiro, Rua São Francisco Xavier 524, Rio de Janeiro, RJ CEP 20550-011, Brazil b

a r t i c l e

i n f o

Article history: Received 29 September 2009 Received in revised form 29 December 2009 Accepted 11 January 2010 Available online 6 February 2010 Keywords: Atlantic Forest Birds Biodiversity hotspot Endangered species Rio de Janeiro Priority setting

a b s t r a c t Rio de Janeiro state in Brazil has one of the most diverse and most endangered avifaunas in the continental Americas. Many of these endangered birds are endemic to the Atlantic Forest biodiversity hotspot, and some even endemic to Rio de Janeiro itself. As with all other forested hotspots, little original forest remains. Much of that is outside formal protected areas and faces the risk of deforestation. These factors create special circumstances for setting conservation priorities — ones common to hotspots in general — but typically not to many conservation priority setting exercises. We mapped the distribution of the remaining habitat for the 189 birds in Rio de Janeiro state that are officially endangered and/or endemic to the Atlantic Forest. Using those habitat maps, we calculated the amount of habitat currently within protected areas for each species. We then prioritized all non-protected parts of the state for their avian conservation value and their potential contribution to a comprehensive protected area system. This analysis identified 10% of the remaining unprotected part of the state as the highest priority for avian conservation. We further highlight specific locations where conservation actions could create a more comprehensive protected area system for the avifauna of Rio de Janeiro state. Ó 2010 Elsevier Ltd. All rights reserved.

1. Introduction The state of Rio de Janeiro, Brazil, is at the geographic center of one of the world’s most threatened biodiversity hotspots, the Atlantic Forest (Myers et al., 2000). The avian diversity of Rio de Janeiro is exceptional, with more than 730 species in the state (Gagliardi, 2009) in an area of only 43,700 km2, corresponding to 40% of the 1825 species in Brazil (CBRO, 2009). That diversity is highly threatened, with the state having the highest concentration of endangered bird species in all of the continental Americas (Manne et al., 1999; Harris et al., 2005; Jenkins and Pimm, 2006). The state and federal governments have made significant conservation efforts, with approximately 14.4% of the state under formal protection (Figs. 1 and 2). About 5.9% of the state has Integral protection, a formal designation that bans the use or harvest of natural resources for commercial purposes. The remaining protected areas allow sustainable use in various forms. As with many protected areas in the world though, those in Rio de Janeiro state are not necessarily in the most effective places for conserving biodiversity. Many are in mountains, where steep slopes often protect

* Corresponding author. Address: Department of Biology, 1210 Biology–Psychology Building, University of Maryland, College Park, MD 20742, USA. Tel.: +1 919 308 7044; fax: +1 301 314 9358. E-mail addresses: [email protected] (C.N. Jenkins), [email protected] (M.A.S. Alves), [email protected] (S.L. Pimm). 0006-3207/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.biocon.2010.01.014

the land as much as the legal protections (Fig. 2). Others protect important places for biodiversity, but are isolated from other forest. Perhaps they will protect their species long enough so that the isolated forest fragments can be reconnected in the future. To avoid extinctions though, every species must have sufficient habitat for its long-term survival. Protecting a large area will not be enough if that area does not include habitat for each species. For few species in the world do we actually know how much of their habitat remains or how much of it has protection. Without that information though, we will not know if existing protected areas are adequate to prevent their extinction. Here, we produce such information for the birds of Rio de Janeiro, demonstrating a clear and simple process to define conservation priorities in a data-limited environment. Using these data, we assessed how well the existing protected area system includes habitat for the state’s highly endangered avifauna. We then prioritized the remaining unprotected area of the state by its potential value for bird conservation, identifying particular places that would best complement the existing protected areas. The state government plans to double the area of Integral conservation units by 2010. This includes expansion of already protected areas (Reserva Biológica de Araras, Parque Estadual Serra da Concórdia, Parque Estadual do Desengano, Parque Estadual da Ilha Grande and Reserva Ecológica de Juatinga) and creation of new ones (Parque Estadual da Costa do Sol and Parque Estadual Restinga de Grussaí) (Eduardo Lardosa, personal communication).

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Fig. 1. Study area of Rio de Janeiro state with public protected areas.

Fig. 2. Topography of Rio de Janeiro with overlay of public protected areas.

Our analysis provides quantitative data for use in such conservation planning, and provides a guide for a more comprehensive protected area system for the avian diversity of Rio de Janeiro. This approach should also be replicable for other taxa in the state, and in other data-limited regions planning to expand their protected area system.

2. Methods For the analyses, we included all terrestrial bird species occurring in Rio de Janeiro state that are listed as threatened (vulnerable, in peril/endangered, critically in peril/critically endangered) on global (IUCN, 2007), national (Machado et al., 2005), or state (Alves et al., 2000) red lists, or that are Atlantic Forest endemics according to Bencke et al. (2006). We excluded species thought to be extinct in the state (Alves et al., 2000). The final list included 189 species, 67 of which were vulnerable or higher on one or more red lists (Appendix A). For each species, we modeled their potential distribution using elevation and land cover to identify remaining suitable habitat within the species’ range. Original geographic ranges were from NatureServe (Ridgely et al., 2005) and were converted to an ArcGIS

raster geodatabase at a 5 km resolution using ArcGIS 9.3 (ESRI, Redlands, California). These maps were then buffered by 15 km to insure that all coastal areas were included as the range maps did not always extend to the shoreline when it was obvious that they should. Habitat variables included the suitable land cover types and elevation range for a species, found in Parker et al. (1996). For species listed only as ‘‘lowland” in Parker et al. (1996), we used an elevation range of 0–300 m, which is the lowest numerical elevation listed in the database. Parker et al. (1996) does not always reflect the latest taxonomy and ecological research for every species, although it is the most recent treatment that includes consistent categories of habitat preference for all of the state’s species. To supplement Parker et al. (1996), we updated species entries using the Handbook of the Birds of the World series (del Hoyo et al., 1992) and the BirdLife Data Zone (http://www.birdlife.org/datazone/index.html). When more localized information was available for a species (e.g., specific to Rio de Janeiro or adjacent states), we modified the species requirements accordingly. Elevation data were from the Shuttle Radar Topography Mission (Rabus et al., 2003). Land cover data were from the Fundação CIDE IQM-Verde II database (Fundação CIDE, 2003). The state government of Rio de Janeiro produced these data by interpreting Landsat 7 satellite imag-

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ery from 2001. More recent comprehensive land cover data were not available. We matched each land cover class to one or more habitat codes (e.g., F1, F2, etc.) in our species database (Appendix A). In the land cover data, we considered the following classes as always unsuitable: degraded areas, salt ponds, urban areas, reforestation (exotics), exposed soil, and unclassified. We obtained digital maps of protected areas from the Brazilian Institute of the Environment (IBAMA, 2009). Protected areas are divided into Integral and Sustainable Use categories according to IBAMA. For the conservation planning analysis, we used the MARXAN software (Ball and Possingham, 2000; Possingham et al., 2000). The conservation targets were specific amounts of habitat protected for each species. To calculate a target for each species, we used a previously created endangerment index (described in Rocha et al., 2009) that is based on species’ official level of endangerment in state (Alves et al., 2000), national (Machado et al., 2005), and global (IUCN, 2007) red lists, and if the species is endemic to the state or to the Atlantic Forest (Table 1). This index is cumulative. For example, a species that is endemic to the Atlantic Forest (1 point), critically endangered in the state list (3 points), and vulnerable in the global list (1 point), would have an index value of 5 points. For progressively higher index values, we targeted a higher percentage of a species’ predicted habitat for protection, with each point worth 5% of a species’ habitat. To create planning units for the MARXAN analysis, we divided the state into 10 km2 hexagons, while maintaining the existing Integral protected areas as discrete planning units (4789 planning units total). Integral protected areas were included a priori as part of the resulting solutions. We used the simulated annealing algorithm plus normal iterative improvement, including a boundarylength modifier (BLM) and the lowest species penalty factor (SPF) where all targets were consistently met. The cost for each planning unit was the area of the unit. To obtain a measure of how essential any particular unit is to forming a comprehensive system, we ran the analysis 500 times and recorded the number of times each planning unit was included in the resulting solutions. More details of the MARXAN algorithm are available in Ball and Possingham (2000), Possingham et al. (2000), and Ardron and Klein (2008).

tened bird species, using any red list (Fig. 3). However, there is substantial variation across the state in terms of the number of threatened species, presenting a variety of choices for where to focus conservation efforts. The overall spatial pattern is that lowland forest, particularly the lowland forest south and east of the central mountain ranges, has the highest predicted numbers of threatened species (Fig. 3A–C). Conversely, the higher elevations tend to have fewer threatened species. The western part of the state in general tends to have fewer threatened species than other areas, although the magnitude of this difference depends on the specific red list considered, with the national list resulting in the largest variations across the state (Fig. 3B). The spatial pattern differs when considering only the species categorized as Near Threatened under the global IUCN criteria. Many of these species are at mid-elevations and in the interior of the state, north of the central mountain ranges (Fig. 3D). Much of the area with a high richness of threatened species, especially the lowlands, is outside of existing Integral protected areas (Fig. 4A). There are exceptions. União Biological Reserve consistently had among the highest number of threatened species based on any red list. It is a protected area known by the authors to have strong protection on the ground, although it is currently an isolated forest fragment (Fig. 4B). Recent efforts by the Golden Lion Tamarin Association and the Instituto Chico Mendes have begun to restore a forest corridor to the west, ending the isolation of this valuable Atlantic Forest fragment (Alves et al., 2009a,b; Pimm and Jenkins, 2005). The nearby Poço das Antas Biological Reserve is also lowland and isolated (Fig. 4B), but reconnecting it to other large areas of forest to its north is hindered by the adjacent BR101 highway. Guaxindiba State Ecological Station is the only lowland reserve in the eastern part of the state, but as of this writing, it had no management plan. The human pressure on the reserve is low, but there is a risk of increased pressure due to an increase of sugar cane production in the region for biofuels. A nearby port (Porto do Açú) under construction will likely increase pressure on the land (Alves et al., 2009a).

3.2. Conservation planning analysis 3. Results 3.1. Spatial patterns of threatened species Essentially all remaining natural land cover in Rio de Janeiro state has some potential to support a Threatened or Near Threa-

Table 1 Points awarded for each type of threat classification in calculating the overall threat index for a species. Endemism or red listing

Points

Endemic to Atlantic Forest Endemic to Rio de Janeiro state

1 2

State red listing Vulnerable In peril Critically in peril

1 2 3

National red listing Vulnerable In peril Critically in peril

1 2 3

Global (IUCN) red listing Vulnerable Endangered Critically endangered

1 2 3

Of the 189 species targeted in the analysis, we found that 164 had sufficient habitat within the existing Integral protected areas to meet their conservation targets. The remaining 25 species did not have adequate protection. While there is no single, optimal solution for which areas to add to the protected area system, general patterns emerged from the complementarity analysis. A map of irreplaceability, which combines the results of many single analyses, shows that certain areas are nearly always essential to a solution (oranges and red in 1Fig. 5). In particular, areas near some existing protected areas are often essential to a solution. These areas are included mainly because they tend to have more continuous forest than other areas, and this forest tends to be at lower elevations than the existing protected areas. Adding these areas also tends to reduce the boundary length of the reserve system, potentially reducing edge effects. The complementary analysis selected 12,536 km2 in at least one of its 500 runs (Table 2). A total of 1247 km2 (10%) was included in all 500 runs and we deem this to be ‘‘irreplaceable” and color it red in Fig. 5. Another 4305 km2 was included between 100 and 499 times, a relatively high irreplaceability score. 1 For interpretation of color in Figs. 2–5, the reader is referred to the web version of this article.

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Fig. 3. Threatened species richness using state (A), national (B), and global (C) red lists. (D) Richness of Near Threatened species according to the global IUCN red list. Gray areas are predicted to have no threatened species.

4. Discussion 4.1. Issues specific to Rio de Janeiro state Given that so little Atlantic Forest remains, all remaining forest has some conservation value (Ribeiro et al., 2009). Brazilian law reflects this by prohibiting the cutting of pristine forest, and the cutting of forest in medium or advanced stages of regeneration, when that forest contains species threatened with extinction at national or state levels (Lei N° 11.428, 22 de dezembro de 2006). Nevertheless, the reality of conservation dictates that even within a biodiversity hotspot such as this, we must still make choices, for the resources available are limited. Even when everything is important, some places are more important than others are. Rio de Janeiro is clearly a global conservation priority for bird diversity (Manne et al., 1999; Harris et al., 2005; Jenkins and Pimm, 2006). Across the state though, we found substantial variation in the relative contribution that specific areas could make to bird conservation. The lowlands, particularly the eastern portion of the state, are especially rich in threatened species. This conclusion holds regardless of the specific red list used. The interior of the state, as well as some middle elevation forest, is particularly rich in species considered Near Threatened by the IUCN. This suggests that future threatened species may concentrate in somewhat different areas than the currently threatened species. This is worrying, for the interior of the state has very little forest, almost none of it in protected areas (Alves et al., 2009a). Our complementarity analysis provides a guide to how much the protection of specific areas could contribute to the overall protected area system. Several specific places warrant discussion. Expansion of the Três Picos State Park to lower elevations would include a substantial area (630 km2) identified as irreplaceable (Fig. 5). In fact, this region has the largest areas of irreplaceable habitat in the state. Northeast of Três Picos is Desengano State Park (Fig. 5), which is mostly a middle and high elevation park. The region does however have a substantial amount (110 km2) of high value forest at lower

elevations, just outside the park boundaries. Expansion of Desengano State Park to the south and east, into the lowlands, would include most of this forest (Alves et al., 2009a). The northern and western part of the Macaé municipality has substantial areas of high value forest (280 km2), including some considered irreplaceable (Fig. 5). We recommend the creation of a protected area in this region. Protection of this area could also improve the connectivity of habitats in the central mountain ranges, where Três Picos and Desengano State Parks are currently separated by 70 km of fragmented landscape (Rocha et al., 2006). Much of the São João da Barra municipality (Fig. 5) in the east of the state is restinga (130 km2), a relatively rare habitat known for high levels of endemism (Alves et al., 2009a). Restinga in general is under high pressure from coastal development and we recommend efforts to protect the restingas of São João da Barra municipality. The area surrounding Cunhambebe State Park in the southwest of the state has substantial amounts of high value habitat (230 km2, Fig. 5). In addition, this forested area is contiguous with the Serra da Bocaina National Park to its west, a large wellprotected park. Expanded protection of this region could help maintain this large area as continuous forest. Implementing the recommendations above would produce a more comprehensive protected area system for the state in terms of bird diversity. There are caveats. (1) Scientific knowledge continues to improve, including the improvement of bird distribution maps. As scientists learn more, it will be possible to make more precise predictions and analyses, although this should not delay conservation actions today using current knowledge. (2) We know of no directly comparable studies for other taxonomic groups. Such studies would be valuable, as the evidence to date suggests that areas important for other taxa may differ from those for birds (e.g., Prendergast and Eversham, 1997; van Jaarsveld et al., 1998; Lawton et al., 1998; Reid, 1998; Hess et al., 2006). (3) Our analysis considers only the current land cover, not the possible restoration of degraded land. There may be cases where restoring a degraded area should be a high priority, particularly when such restoration might reconnect a fragmented landscape (Anderson and Jenkins,

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Fig. 4. (A) Integral protected area coverage of globally threatened species. (B) Two lowland reserves (União and Poço das Antas Biological Reserves) and the predicted richness of globally threatened birds. Both reserves are isolated from other forested areas.

2006). Incorporation of such values into the conservation planning process is encouraged. The use of state and national red lists in the endangerment index should proceed with caution, for it can potentially introduce a non-biological bias. For example, a species considered threatened in a state list may be widely distributed outside the state and so not threatened globally. As well, there are documented inconsistencies between lists in Brazil, partly due to varying levels of knowledge about species at different scales, including taxonomic status (Garcia and Marini, 2006). However, state and national lists also contribute important information. For example, Mimus gilvus is widely distributed in Central America and northern South America and so not considered threatened globally. In southeast Brazil, though, it is restricted to restinga. The Rio de Janeiro red list considers this taxon as a restinga-restricted form and lists it as threatened (Alves et al., 2000). State and national lists are also crucial in

terms of actual conservation actions, for they can determine legal requirements within the state and the nation. The endangerment index we use is already part of the state’s conservation planning process (see Bergallo et al., 2009). The federal government, through the Instituto Chico Mendes, encourages the production of state lists for reasons such as these. 4.2. General issues While our specific results and recommendations apply to Rio de Janeiro, this region shares features with other forested hotspots. First, by definition as a hotspot, only a fraction of the original vegetation remains — the criteria for being a hotspot is <30%, but for forests it is closer to <10% in practice (Myers et al., 2000). That means that any exercise in setting priorities must work with species distributions as they are in practice and not as they appear

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Fig. 5. Summary of 500 runs of the MARXAN algorithm using the species targets in Appendix A. Colors indicate the number of times a particular planning unit was part of a solution (i.e., irreplaceability). Red areas were included in every solution. Labels indicate key sites discussed in the main text. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Table 2 Summary of irreplaceability. Irreplaceability is the number of times a particular planning unit was part of a comprehensive solution. A value of 500 indicates the area was included in all 500 simulation runs, being irreplaceable for achieving a comprehensive system. Irreplaceability

Area (km2)

Integral protected areas (always included) 500 (irreplaceable) 100–499 2–99 1

3313 1247 4305 5580 1404

Total

15,849

Total selected area outside protected areas

12,536

Entire state

43,715

in field guides. The latter generally reflect historical ranges. Real distributions are much smaller and inevitably less certain. Modeling such distributions simply and sensibly is an obvious step, albeit one subject to uncertainties. Waiting for detailed field data on species distributions is usually not a viable alternative. Some assumptions in our analyses may affect the applicability of the results. One is that protected areas really do work. Our personal experience in this region is that some protected areas have far more resources for implementing protection than do others. Another assumption concerns the costs of conservation. The complementarity model does not consider the financial cost of land acquisition or protection. Land prices vary across the state, but we were unable to locate a consistent source of data on land prices to use in the analyses. There may be cases where protecting a large, but inexpensive area with relatively few species might be a better deal for conservation than protecting a small area of expensive but species rich land. Perhaps of even greater significance is that one must be guided by what has proven practical in protecting this region. Expanding existing reserves — and especially connecting isolated forest reserves — along with protecting areas already identified for sustainable use may be more likely to be effective than setting up large,

isolated reserves in hitherto unprotected areas. Such decisions cannot easily be reduced to simple optimizations. Nonetheless, the targets we suggest here can strongly inform where practical conservation actions are most needed. Acknowledgements We would like to thank the Fundação CIDE and IBAMA for providing their data and Eduardo Lardosa from INEA for information on legal references. M.A.S.A. received a CNPq Grant (Process # 302718/03-6) and a FAPERJ Grant (Process # E-102.868/2008) during this research. C.N.J. was supported in part by a National Science Foundation Graduate Research Fellowship. We would also like thank the American Philosophical Society and the University of Tennessee for funding during the initial stages of this study. Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.biocon.2010.01.014. References Alves, M.A.S., Pacheco, J.F., Gonzaga, L.A.P., Cavalcanti, R.B., Raposo, M.A., Yamashita, C., Maciel, N.C., Castanheira, M. Aves. In: Bergallo, H.G., Rocha, C.F.D., Alves, M.A.S., Van Sluys, M. (Orgs.), 2000. A fauna ameaçada de extinção do Estado do Rio de Janeiro. EdUERJ, Rio de Janeiro, vol. 1. pp. 113–124. Alves, M.A.S., Jenkins, C.N., Caramaschi, E.P., Scarano, F.R., Oliveira, F.J.G., Zalmon, I.R., Monteiro, R.F., Camargo, A.F., Pimm, S.L, 2009a. Região de Petróleo e Gás Natural. In: Bergallo, H.G, Fidalgo, E.C.C., Rocha, C.F.D., Uzêda, M.C., Costa, M.B., Alves, M.A.S., Van Sluys, M., Santos, M.A., Costa, T.C.C., Cozzolino, A.C.R. (Orgs.). Estratégias e ações para a conservação da biodiversidade no Estado do Rio de Janeiro, first ed. Instituto Biomas, Rio de Janeiro, vol. 1. pp. 303–312. Alves, M.A.S., Vecchi, M.B., Cordeiro, P., Jenkins, C.N., Raposo, M., Chaves, F.G., Almeida-Santos, P., 2009b. Aves nos remanescentes florestais de Mata Atlântica e ecossistemas associados do Rio de Janeiro. In: Bergallo, H.G, Fidalgo, E.C.C., Rocha, C.F.D., Uzêda, M.C., Costa, M.B., Alves, M.A.S., Van Sluys, M., Santos, M.A., Costa, T.C.C., Cozzolino, A.C.R. (Orgs.). Estratégias e ações para a conservação da biodiversidade no Estado do Rio de Janeiro, first ed. Instituto Biomas; Rio de Janeiro, vol. 1. pp. 193–208. Anderson, A., Jenkins, C.N., 2006. Applying Nature’s Design: Corridors as a Strategy for Biodiversity Conservation. Columbia University Press, New York.

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