Uneven representation of biogeographical regions in Bolivia’s protected areas and indigenous territo

Ecología en Bolivia 51(2): 141-156. Septiembre 2016. ISSN 1605-2528.

Uneven representation of biogeographical regions in Bolivia’s protected areas and indigenous territories Representación desigual de las regiones biogeográficas en las áreas protegidas y territorios indígenas de Bolivia Daniel M. Larrea-Alcázar1*, Ramiro P. López2,3, Freddy S. Zenteno-Ruíz2, Indira Lafuente1,3 & Yara Fernández3 Asociación Boliviana para la Investigación y Conservación de Ecosistemas Andino-Amazónicos (ACEAA), Pasaje Flores Quintela (entre calles 13 y 14 de Calacoto), La Paz, Bolivia, Autor de correspondencia: larrea.alcazar@gmail.com, dlarrea@conservacionamazonica.org.bo 2 Herbario Nacional de Bolivia (LPB), Instituto de Ecología (IE), Universidad Mayor de San Andrés (UMSA), La Paz, Bolivia.

3Carrera de Biología, Universidad Mayor de San Andrés (UMSA), La Paz, Bolivia.

1

Abstract In this study, we evaluated the representation of biogeographical units in national (NPA) and subnational (SPA) protected areas, as well as in officially recognized indigenous territories (IT) of Bolivia. We compiled available cartographic information on Bolivia’s NPA, SPA and IT, and compared it with suggested proposal and hierarchization of biogeographic units (regions, provinces, and sectors). For each biogeographic unit, we calculated the representation target under the following three criteria: 1) the 17% target proposed by the Aichi targets of the CBD (Convention on Biological Diversity), b) the representation target expected by the cover of each biogeographic unit in relation to Bolivia`s total surface, and c) the expected representation target calculated for each biogeographic unit based on the relationship area – expected representation.

We detected a marked under-representation of the Tropical Andean and Brasilian-Paranaense regions in the NPA, whereas the Chaco Region is was notoriously over-represented. For the case of biogeographic provinces and sectors, we detected a general tendency towards underrepresentation in the NPA, SPA and IT. Our results suggest cautiousness in the use and interpretation of the 17% target recommended by the Aichi targets of the CDB. The results also highlight the potential importance of the SPA and the IT in the vegetation representation in Bolivia, the latter two being examples of “other efficient conservation measures based on areas” (OEABCM); however, we suggest cautiousness on the role of IT in the highlands.

Key words: Aichi targets, Bolivia, Conservation, Geobotany, Phytogeography.

Resumen En este estudio, evaluamos la representación de las unidades biogeográficas en áreas protegidas nacionales (APN) y sub-nacionales (APS), así como en territorios indígenas oficialmente reconocidos (TI) de Bolivia. Compilamos información cartográfica disponible sobre APN, APS y TI en Bolivia, y la comparamos con la propuesta sugerida de jerarquización de unidades biogeográficas (regiones, provincias y sectores). Para cada unidad biogeográfica, calculamos la meta de representación bajo los siguientes tres criterios: 1) la meta del 17%

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propuesta por las metas de Aichi de la CDB (Convención sobre la Diversidad Biológica), b) la meta de representación esperada por la cobertura de cada unidad biogeográfica con relación a la superficie total de Bolivia, y c) la meta de representación calculada para cada unidad biogeográfica basados en la relación área-representación esperada. Detectamos una marcada subrepresentación de las regiones de los Andes tropicales y la Brasileño-Paranense en las APN, mientras que la región chaqueña estuvo notoriamente sobre representada. Para el caso de las provincias y sectores biogeográficos, detectamos una tendencia general hacia la subrepresentación en APN, APS y TI. Nuestros resultados sugieren cautela en el uso e interpretación de la meta del 17% recomendada por las metas de Aichi de la CDB. Los resultados también resaltan la importancia de las APS y los TI en la representación de la vegetación en Bolivia, representando ejemplos de «otras medidas eficientes de conservación basadas en áreas» (OEABCM por sus siglas en inglés); sin embargo, sugerimos cautela sobre el papel de los TI en las tierras altas.

Palabras clave: Bolivia, Conservación, Fitogeografía, Geobotánica, Metas de Aichi,.

Introduction

identification of biogeographical elements.

Navarro and Ferreira (2009, 2011) proposed a hierarchical nomenclature and classification based on the identification of four large regions (Amazonia, Tropical Andean, Brasilian-Paranaense and Chaco), composed of 10 provinces and 27 biogeographical sectors, which include the so-called vegetation series (Navarro & Ferreira 2004, 2007, 2011).

Unlike previous classifications (Ribera et al.

1996, Ibisch et al. 2003), the hierarchical (thus, biogeographic) classification proposed by Navarro & Ferreira (2009) has allowed its use on conservation planning at different scales, from zonation of indigenous territories (e.g., Altamirano et al. 2012) to regional planning (Larrea-Alcázar et al. 2010).

At a global scale, protected areas represent the most successful conservation strategy of biodiversity (IUCN 1994, Bruner et al.

2001, Naughton-Treves et al. 2003, Chape et al. 2005); however, the debate on alternative strategies exists (e.g., Escobar 1998, Margules & Pressey 2000, Geldmann et al. 2013). In this sense, the role that indigenous territories play on biodiversity conservation has been highlighted (Finer et al. 2008), especially as reservoirs of Amazonian biomass (e.g.

Walker et al. 2015). The indigenous territories represent the geographic expression of the legal recognition of individual and collective

Bolivia is recognized as one of the biogeographically most diverse countries in the Americas (Beck 1998, Ribera et al.

1996, Ibisch 1998, Ibisch et al. 2003, López & Zambrana-Torrelio 2006, Jörgensen et al. 2014). Its tropical location (9-23° south latitude) and the presence of the Andes in a large part of its territory explain greatly this high level of species richness. Another reason for Bolivia’s high biodiversity is the fact that several biogeographic regions coincide in its territory (Moraes & Beck 1992, Ibisch & Beck 2003), like Yungas (Müller et al. 2003, Krömer et al. 2007), Amazonia (Mostacedo et al. 2006, Araujo-Mukarami et al. 2015), and the Cerrado (Beck & Moraes 1997, 2004, Larrea-Alcázar et al. 2010), among others.

Different authors have proposed biogeographical classifications for Bolivia from the identification and characterization of vegetation units. For example, Ellenberg (1981) was the first to propose the biogeographical division of Bolivia using ecoregions, identifying 12 of them. Later, Moraes & Beck (1992) recognized eight biogeographical areas, whereas, Ibisch et al. (2003) identified 23 ecological regions, among ecoregions and sub-ecoregions. These units were based more on vegetation and not on the explicit 142

Uneven representation of biogeographical regions in Bolivia’s protected areas and indigenous territories

rights of a given region by indigenous people (Gadgil et al. 1993, Stevens 1997); therefore, they do not have as its main objective the conservation of biological diversity, albeit they may indirectly contribute to this end (Arambiza & Painter 2006). In Bolivia, the importance of indigenous territories to reach the biodiversity conservation targets is still an open question.

Bolivia possesses a National System of Protected Areas (NSPA) which includes a total of 22 protected areas at a national level (from now on, NPA), and sub-national level (hereafter SPA), 27 of which are protected at a departmental level (i.e. departments are the main administrative divisions of the country) and 85at a municipal level (i.e. smaller administrative subdivision) (Araujo et al.

2010). At the same time, Bolivia recognizes the right of indigenous people to possess a territory, and has at least 298 indigenous territories (IT) with official recognition, formerly known as TCO’s o TIOC’s (see INRA 2012). Although the importance of NPA in the biogeographic representation has been evaluated (Pacheco et al. 1994, López & Zambrana-Torrelio 2006), studies on the importance of SPA are still scarce (AraujoMurakami et al. 2010, Larrea-Alcázar et al.

2010). On the other hand, the representation of biogeographical units (regions, provinces, sectors) in IT is unknown, especially if we consider them as “other efficient conservation measures based on areas” (OEABCM; CDB 2010, MacKinnon et al. 2015).

During the 10th Conference of the Parties (COP 10) held in Japan in 2010, the Convention on Biological Diversity (CBD) Secretariat proposed a 10-year framework for action called Strategic Plan for Biological Diversity 2011-2020 (see http://www.cbd.int), which was created because of a shared vision, one mission and 20 global targets, which have been called “Aichi targets”. Among the latter, target 11 proposes that at least 17% of the ecosystems that harbor high biological diversity values

must be conserved through protected areas. Studies that have examined the 17% representation target proposed by the CDB in Bolivia are scarce and have been focused on evaluating the representation of some floral groups (e.g., Poaceae, see Meneses et al. 2014). However, previous biogeographical evaluations were based on the calculation of the representation target in a percent cover of each biogeographical unit inside Bolivia (see Pacheco et al. 1994 and López & ZambranaTorrelio 2006). Rodrigues et al. (2004) proposed a way of calculation of the representation target based on the relationship area-expected representation, which was employed in Bolivia to evaluate the representation of the Beni’s pampas (which includes the Moxos Plains and the Beni Cerrado) at a subnational scale (see Larrea-Alcázar et al. 2010).

All these studies were conducted before a consensus was reached and approval of the Aichi targets (year 2010). An evaluation of the biogeographical representation on the protected areas and indigenous territories will allow us to relate the present biogeographical knowledge with the current policies on biodiversity conservation.

In this study, we evaluated how well represented are the biogeographical units (regions, provinces, sectors) proposed by Navarro & Ferreira (2009) in the NSPA and in the IT. We also conducted a methodological comparison by calculating the expected representation targets of each biogeographical unit under three criteria, specifically: the target 17% proposed for the CDB’s Aichi targets, the expected representation target based on proportional cover inside Bolivia of each biogeographical unit, and the expected representation target calculated for each unit based on the relationship area-expected representation proposed by Rodrigues et al.

(2004). This analysis allowed us to compare the situation of biogeographical representation now and 12 years ago, when a similar, albeit less detailed analysis, was conducted.

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Methods

or species turnover remain constant. In order to establish differences due to the method of calculation, we estimated the expected representation target for each biogeographical unit using the following three criteria: 1) the 17% representation target proposed by the CBD (target 11 Aichi targets); 2) the representation target of each biogeographic unit in direct proportion to their relative cover inside the country (e.g., if Amazonia represents 20% of the country, 20% of the protected area should be Amazonia; see, e.g., López & Zambrana-Torrelio 2006); and 3) the expected representation target calculated using the ratio area-expected representation proposed by Rodrigues et al.

(2004). In the representation target calculated in c), extensive biographical units should need moderate to low representation targets, while the small biogeographic units should tend to have very high representation targets (Fig. 1). Representation was defined as the percentage of natural cover that overlaps with protected areas (direct conservation areas) or indigenous territories (indirect conservation areas) in order for the biogeographic unit to be considered as covered. We estimated the current representation for each biogeographic unit (four regions, 10 provinces and, 27 biogeographic sectors) within the NPA, SPA, and IT compiled in the geodatabase.

We contrasted the total area of each biogeographic unit with the three calculated representation targets. We define over-, under- or adequate representation for each biogeographic unit using an arbitrary scale based on absolute values under the following thresholds: a) adequately represented: close to the expected representation target with a variation of ± 1%); b) slightly underrepresented: area slightly smaller (between 1 and 5% less) than the expected representation target; c) under-represented: area smaller (over 5%) than the expected representation target; d) slightly over-represented: area slightly larger (between 1 and 5% more) than the expected

Gathering and systematization of a geodatabase We gathered available cartographic information from the Bolivia’s Natural Resources Digital Center (CDRNB, www.cdrnbolivia.org) and GeoBolivia www.geo.gob.bo/). From the CDRNB we obtained a biogeographic map (regions, provinces, and sectors) proposed by Navarro & Ferreira (2009) in shape (.shp) format at a scale 1:7.000.000. From the GeoBolivia web portal we obtained the cartography proposed

by National Service of Protected Areas, SERNAP (2015) for the NSPA (both for NPA and SPA), in shape format at a scale 1:1.000.000.

We verified the information on the legal status, department, and management level of each protected area using a report published by the Water and Environmental Ministry (MMAyA 2012). We digitalized the cover of protected areas not included in the available GeoBolivia database, such as the Santos Reyes Integrated Management Natural Municipal Area from Beni Department. Finally, we download the IT map proposed by the INRA in 2012, available on the GeoBolivia website in shape format at a scale of 1:1,000,000. We verified the information on legal status, area cover, and name used in each IT by using the report published by the Fundación Tierra (2011). All information gathered was systematized in a geodatabase using ArcGis 10.1 (www.arcgis.com/).

Analysis of representation Using ArcGis 10.1tools, we assessed the representation of biogeographic units (regions, provinces and sectors) proposed

by Navarro & Ferreira (2009) in NPA, SPA and IT. We used as representation measure the cover of each biogeographical unit. We assumed that the distribution of biological diversity within each unit was homogeneous and other key processes, such as migration 144

Uneven representation of biogeographical regions in Bolivia’s protected areas and indigenous territories

Figure 1. Relationship between each biogeographic unit extent of occurrence and its representation target (based on Rodrigues et al. 2004). For small biogeographic units (extent of occurrence <1.000 km2), the representation target is 100%, while in extensive biogeographic units (<250.000 km2), the target is 10%. For biogeographic units of intermediate size, the target was interpolated between these two extremes. representation target; e) over-represented: area larger (more than 5%) than the expected target.

To define the final representation of each biogeographic unit, we defined an arbitrary criterium that at least two of the three targets should coincide in the threshold reported. We defined as ÂŤinconsistent representationÂť cases where the comparison of the three targets of representation presented different results.

for the Amazonian Region in the NPA, an under-representation in the SPA and overrepresentation in the IT. On the other hand, the four regions were under-represented in the SPA (Table 1, Fig. 2). The expected representation targets calculated from target 11 of the Aichi targets and the expected arearepresentation relationship were similar (183,000 km2 in total, approximately), whereas the expected representation target calculated in relation to the cover of each region was 1.7 times more (approx. 321,000 km2 in total).

In the case of the present representation of the biogeographical provinces, we detected that six out of 10 provinces were overrepresented in the NPA and four were underrepresented, whereas in the case of the SPA, we detected over-representation just in one case (the Central-Southern-Amazonian Province) and under-representation for nine (Table 2, Fig. 2). Finally, in the case of the IT, we recorded

Results We detected variations in the current representation of the biogeographical regions both in NPA, SPA, and IT. The BrasilianParanaense and Tropical Andean regions were slightly to completely under-represented in NPA and SPA, unlike the case with the Chaco Region, which was over-represented in the NPA and under-represented in the SPA and IT. We recorded an inconsistent representation 145

D. M. Larrea-Alcázar, R. P. López, F. S. Zenteno-Ruíz, I. Lafuente & Y. Fernández

over-representation for four provinces and under-representation for six cases (Table 2). In the Amazonian Region, the Central-Southern Amazonia Province was between slightly and completely over-represented in the NPA, SPA and IT. Meanwhile, the Southwestern Amazonian Province was over-represented in the NPA and IT, and under-represented in the SPA. Within the Tropical-Andean Region, the Bolivian-Tucuman and the mesophytic Puna were between slightly and completely under-represented within the NPA, SPA and IT, whereas the xerophytic Puna was underrepresented in the NPA and SPA, but overrepresented in the IT. The Peruvian-Bolivian

Yungas Province showed over-representation in the NPA, but was under-represented in the SPA and IT. In the Brasilian-Paranaense Region, the Beni Province was between slightly to completely under-represented in the NPA, SPA, and IT; the Western Cerrado and Pantanal provinces were slightly overrepresented in the NPA, under-represented in the SPA, while in the IT showed from slight to over-represented. The Pantanal Province is not represented in the NPA. Finally, within the Chaco Region, the Northern Chaco Province was over-represented in the NPA, but underrepresented in the SPA and IT (Table 2). The expected representation targets calculated

Table 1. Expected representation targets and present representation of the four biogeographic regions proposed by Navarro & Ferreira (2009) inside protected areas (NPA: national protected areas, SPA: sub-national protected areas) and indigenous territories officially recognized (IT).

The expected representation targets were calculated using three ways: Target1: 17% target proposed by the Target 11 of the Aichi Targets; Target2: target of proportional representation of the biogeographic regions inside Bolivia (i.e., representation in terms of their relative size within the country); and Target3: representation target calculated using the relationship areaexpected representation proposed by Rodrigues et al. (2004). Weighting of the representation = adequately represented, ↑ slightly over-represented, ↑↑ over-represented, ↓ slightly underrepresented, ↓↓ under-represented. The resulting weighting for each target is indicated by the subscript of each expected target. Values inside parentheses show the proportion in relation to total area of each case. Areas are in km2 in all cases.

Biogeographic region Amazonian

Tropical Andean

Total area

Target1 (%)

Target2 (%)

Target3 (%)

NPA (%)

SPA (%)

IT (%)

231,886.2

39,420.7 (17%)

49,448.5 (21.3%)

44,058.4 (19%)

45,916.4 (19.8%) ↑1, ↓2, =3

32,794.1 (14.1%)

↓1, ↓↓2, ↓3

55,535.8 (23.9%)

↑↑1, ↑2, ↑3

66,416.4 (17%

140,364.1 58,602.7 (35.9%) (15%)

44,801.1 (11.5%)

15,432.7 (4%)

99,358.3 (25.4%)

61,819.1 (17%)

121,604.8 58,182.7 (33.4%) (16%)

390,684.7

BrasilianParanaense

363,641.7

Chaco

101,206.0

Total

17,205.0 (17%)

9,419.2 (9.3%)

22,265.3 (22%)

1,087,418.5 184,861.2 320,836.6 183,109.1

146

↓↓1, ↓↓2, ↓3

↓↓1, ↓↓2, ↓↓3

↑↑1, ↓↓2, ↑↑3

48,152.2 (13.2%)

36,661.9 (10.1%)

49,836.9 (13.7%)

↓1, ↓↓2, ↓3

↓↓1, ↓↓2, ↓↓3

↓1, ↓↓2, ↓3

32,882.7 (32.5%)

301.0 (0.3%)

7,830.8 (7.7%)

↑↑1, ↑↑2, ↑3

↓↓1, ↓↓2, ↓↓3

↓↓1, ↓2, ↓↓3

171,752.4 (15.8%)

8,548.9 (7.8%)

212,561.8 (19.5%)

Uneven representation of biogeographical regions in Bolivia’s protected areas and indigenous territories

Table 2. Expected representation targets and present representation of the 10 biogeographic provinces proposed by Navarro & Ferreira (2009) inside protected areas (NPA: national protected areas, SPA: sub-national protected areas) and indigenous territories officially recognized (IT). The expected representation targets were calculated using three ways: Target1: 17% target proposed by the Target 11 of the Aichi Targets; Target2: target of proportional representation of the biogeographic regions inside Bolivia (i.e., representation in terms of their relative size within the country); and Target3: representation target calculated using the relationship area- expected representation proposed by Rodrigues et al. (2004). Weighting of the representation = adequately represented, ↑ slightly over-represented, ↑↑ over-represented, ↓ slightly under-represented, ↓↓ under-represented. The resulting weighting for each target is indicated by the subscript of each expected target. Values inside parentheses show the proportion in relation to total area of each case. Areas are in km2 in all cases.

Biogeographic provinces

Total area

Target1 (%)

Target2 (%)

Target3 (%)

NPA (%)

SPA (%)

IT (%)

Central-southern Amazonia (Madeira-Tapajós)

88,.815.3

15.098.6 (17%)

7.254.0 (8.2%)

26.644.6 (30%)

16.047.0 (18.1%) ↑1. ↑↑2. ↓↓3

25.990.9 (29.3%) ↑↑1. ↑↑2. =3

20.961.5 (23.6%) ↑↑1. ↑↑2. ↓3

Southwestern Amazonia (Acre-Madre de Dios)

143.070.9

24.322.1 (17%)

18.823.7 (13.2%)

28.614.2 (20%)

29.869.3 (20.9%) ↑↑1. ↑↑2. =3

6.803.2 (4.8%) ↓↓1. ↓↓2. ↓↓3

34.574.3 (24.2%) ↑↑1. ↑↑2. ↑3

Bolivian-Tucuman

101.867.8

17.317.5 (17%)

9.542.8 (9.4%)

20.373.6 (20%)

8.372.6 (8.2%) ↓↓1. ↓2. ↓↓3

11.009.2 (10.8%) ↓↓1. ↑2. ↓↓3

9.084.6 (8.9%) ↓↓1. =2. ↓↓3

Mesophytic Puna

34.663.3

5.892.8 (17%)

1.105.0 (3.2%)

18.024.9 (52%)

5.287.2 (15.3%) ↓1. ↑↑2. ↓↓3

552.4 (1.6%) ↓↓1. ↓2. ↓↓3

825.2 (2.4%) ↓↓1. =2. ↓↓3

Xerophytic Puna

189.381.4

32.194.8 (17%)

32.982.1 (17.4%)

35.982.5 (19%)

8.329.4 (4.4%) ↓↓1. ↓↓2. ↓↓3

3.551.9 (1.9%) ↓↓1. ↓↓2. ↓↓3

84.478.7 (44.6%) ↑↑1. ↑↑2. ↑↑3

Peruvian-Bolivian Yungas

64.772.2

11.011.3 (17%)

3.858.2 (5.9%)

22.670.3 (35%)

22.812.0 (35.2%) ↑↑1. ↑↑2. =3

319.2 (0.5%) ↓↓1. ↓↓2. ↓↓3

4.969.9 (7.7%) ↓↓1. ↑2. ↓↓3

Beni

186.730.1

31.744.1 (17%)

32.065.1 (17.2%)

35.478.7 (19%)

7.005.2 (3.8%) ↓↓1. ↓↓2. ↓↓3

28.593.3 (15.3%) ↓1. ↓2. ↓3

26.350.3 (14.1%) ↓1. ↓2. ↓3

Western Cerrado

162.888.2

27.691.0 (17%)

24.399.6 (14.9%)

30.948.8 (19%)

30.671.7 (18.8%) ↑1. ↑2. =3

8.068.6 (5.0%) ↓↓1. ↓↓2. ↓↓3

20.446.2 (12.6%) ↓1. ↓2. ↓↓3

Pantanal

14.023.3

2.384.0 (17%)

180.8 (1.3%)

8.414.0 (60%)

10.475.3 (74.7%) ↑↑1. ↑↑2..↑↑3

0 (0%) ↓↓1. ↓↓2. ↓↓3

3.040.4 (21.7%) ↑1. ↑↑2. ↓↓3

Northern Chaco

101.206.0

17.205.0 (17%)

9.419.2 (9.3%)

21.253.3 (21%)

32.882.7 (32.5%) ↑↑1. ↑↑2. ↑↑3

301 (0.3%) ↓↓1. ↓↓2. ↓↓3

7.830.8 (7.7%) ↓↓1. ↓2. ↓↓3

139.630.5

248.404.7

171.752.4 (15.8%)

85.189.8 (7.8%)

212.561.8 (19.5%)

Total

1.087.418.5 184.861.2

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D. M. Larrea-Alcázar, R. P. López, F. S. Zenteno-Ruíz, I. Lafuente & Y. Fernández

based on the three criteria oscillated between 139,000 km2 in total (target calculated in terms of the proportional representation of each region in Bolivia) and 248,000 km2 in total (expected representation target following the expected area-representation relationship).

In the case of the current representation of biogeographical sectors, in the NPA 11 sectors were over-represented, whereas we recorded under-representation for 16 sectors and six sectors were not represented at all (high Madeira, Uyuni Salar, San Juan del Oro Prepuna, Chiquitania transitional to Amazonia, Eastern Beni and Northern Beni (Table 3, Fig. 2). In the SPA, we detected over-representation for three sectors, under-representation for 24 and four sectors were not represented (Southwestern Lípez, Northwestern Pantanal, Southern Pantanal and Northeastern Chaco; Table 3). Finally, in the case of the IT, we recorded over-representation for eight sectors, under-representation for 17, inconsistent representation in two cases, and five sectors were not represented (Ichilo high basin, Bermejo, Santa Cruz Chiquitania, Southern Pantanal and Northeastern Chaco; Table 3). The expected representation targets calculated based on the three criteria fluctuated between 62 000 km2 (based on the region´s proportional cover in Bolivia) and 438 000 km2 (target proposed by the expected area-representation relationship).

the case of provinces and sectors, the highest representation target was that calculated using the area - expected representation relationship for each biogeographical unit (criterium 3), whereas in the case of regions, the target calculated based on the relative proportion of each region (criterium 2) was the most demanding. These data support the hypothesis that the conservation targets based on representation areas are based on political consensus and may underestimate the recommendations that conservation science can make (e.g., Locke 2014). The target 11 proposed by the CBD’s Aichi targets derives from a consensus and a political decision to increase at a global level the representation of terrestrial zones inside protected areas from 13 to 17% (CBD 2011). This last value has been used as a national indicator of the achievement of target 11 (e.g., see MacKinnon et al. 2015 for Canada). In this sense, the area covered by the NPA and SPA reaches 180,000 km2, which corresponds to near 17% of Bolivia`s territory, showing that, in terms of area, Bolivia would have reached the target 11 proposed by the CBD; however, the use of the 17% representation target at a sub-national scale could underestimate the representation of the biogeographical units present in Bolivia.

Using this criterium, the Amazonian region was slightly over-represented in NPA, unlike the tendencies detected with the use of the other two representation targets. However, using the classification of ecoregions proposed

by Ibisch et al. (2003), López & Zambrana (2006) reported that Southwestern Amazonia was slightly over-represented in the NPA existing in 2002. These data suggest that the creation of new areas in the Amazonian region would not be necessary, especially if we consider the contribution of the SPA and IT which, together with the NPA, represent 134 000 km2, i.e., 58% of the entire region.

In this sense, the total representation of the Brasilian-Paranaense and Tropical Andean in the NPA, SPA, and IT overcomes the expected

Discussion The analysis of gaps in the biogeographical representation vary from a spatial comparison of vegetation present in protected areas (e.g.

Pacheco et al. 1994, López & ZambranaTorrelio 2006, Larrea-Alcázar et al. 2010) to complex studies that require the detailed collection of field data, mapping, and use of existing software (e.g., Lourival et al.

2011). Both cases need the definition of representation targets that permit to contrast and analyze the available data. Our results show differences in the representation targets depending on which criteria were used. In 148

Uneven representation of biogeographical regions in Bolivia’s protected areas and indigenous territories

Table 3. Expected representation targets and present representation of the 27 biogeographic sectors proposed by Navarro & Ferreira (2009) inside protected areas (NPA: national protected areas, SPA: sub-national protected areas) and indigenous territories officially recognized (IT).

The expected representation targets were calculated using three ways: Target1: 17% target proposed by the Target 11 of the Aichi Targets; Target2: target of proportional representation of the biogeographic regions inside Bolivia (i.e., representation in terms of their relative size within the country); and Target3: representation target calculated using the relationship areaexpected representation proposed by Rodrigues et al. (2004). Weighting of the representation = adequately represented, ↑ slightly over-represented, ↑↑ over-represented, ↓ slightly underrepresented, ↓↓ under-represented. The resulting weighting for each target is indicated by the subscript of each expected target. Values inside parentheses show the proportion in relation to total area of each case. Areas are in km2 in all cases.

Biogeographic sector

Total area

Target1 (%)

Target2 (%)

Target3 (%)

NPA (%)

SPA (%)

IT (%)

Acre and Madre de Dios

74,664.0

12,692.9 (17%)

5,126.6

24,639.1 (33.0%)

7,476.5 (10.0%)

195.6 (0.3%)

12,398.3 (16.6%)

Heath and Low Madidi

18,895.7

3,212.3 (17%)

328.3 (1.7%)

11,148.4 (59.0%)

Pre-Andean from Northern Bolivia and Southern Peru

49,511.2

8,416.9 (17%)

2,254.3 (4.6%)

21,289.8 (43.0%)

High Madeira

19,240.5

3,270.9 (17%)

340.4 (1.8%)

11,351.9 (59.0%)

11,827.7 (17%)

4,451.5 (6.4%)

22,263.9 (32.0%)

9,301.8 (17%)

2,753.2 (5.0%)

21,886.5 (40.0%)

1,709.5 (17%)

93 (0.9%)

6,134.1 (61.0%)

5,892.8 (17%)

1,105.0 (3.2%)

17,331.6 (50.0%)

11,487.4 (17%)

4,199.0 (6.2%)

35,137.8 (52.0%)

8,356.1 (17%)

2,221.8 (4.5%)

21,627.5 (44.0%)

Guaporé

Beni High Basin

Ichilo High Basin

69,574.7

54,716.2

10,056.0

Southern Mesophytic

34,663.3

SajamaDesaguadero

67,572.7

Uyuni Salar

49,153.5

(6.9%)

149

↓↓1, ↑2, ↓↓3

↓↓1, ↓↓2, ↓↓3

=1, ↑↑2, ↓↓3

1,022.8 (5.4%)

1,991.6 (10.5%)

2,787.3 (14.8%)

↓↓1, ↑2, ↓↓3

↓↓1, ↑↑2, ↓↓3

↓1, ↑↑2, ↓↓3

21,370.1 (43.2%)

4,616.0 (9.3%)

19,388.8 (39.2%)

↑↑1, ↑↑2, =3

↓↓1, ↑2, ↓↓3

↑↑1, ↑↑2, ↓3

0 (0%)

716.3 (3.7%)

165.0 (0.9%)

↓↓1, ↓2, ↓↓3

↓↓1, ↑2, ↓↓3

↓↓1, ↓2, ↓↓3

16,047.0 (23.1%)

25,274.6 (36.3%)

20,796.5 (29.9%)

↑↑1, ↑↑2, ↓↓3

↑↑1, ↑↑2, ↑3

↑↑1, ↑↑2, ↓3

15,231.7 (27.8%)

242.8 (0.4%)

4,969.9 (9.1%)

↑↑1, ↑↑2, ↑↑3

↓↓1, ↓2, ↓↓3

↓↓1, ↑2, ↓↓3

7,580.2 (75.4%)

76.3 (0.8%)

0 (0%)

↑↑1, ↑↑2, ↑↑3

↓↓1, =2, ↓↓3

↓↓1, ↓2, ↓↓3

5,287.2 (15,3%)

552.4 (1.6%)

825.2 (2.4%)

↓1, ↑↑2, ↓↓3

↓↓1, ↓2, ↓↓3

↓↓1, =2, ↓↓3

958.3 (1.4%)

1,748.6 (2.6%)

23,187.5 (34.3%)

↓↓1, ↓↓2, ↓3

↓↓1, ↓2, ↓↓3

↑↑1, ↑↑2, ↓↓3

0 (0%)

765.3 (1.6%)

20,653.9 (42.0%)

↓↓1, ↓2, ↓↓3

↓↓1, ↓2, ↓↓3

↑↑1, ↑↑2, ↓3

D. M. Larrea-Alcázar, R. P. López, F. S. Zenteno-Ruíz, I. Lafuente & Y. Fernández

Potosí

46,482.8

Southwestern Lípez

26,172.4

Piray-Río Grande

50,993.3

Pilcomayo-High Parapetí

27,766.2

San Juan del Oro Prepuna

10,520.4

Bermejo

12,587.8

Chiquitania transitional to Amazonia

13,829.4

Central Chiquitania

104,950.9

Chiquitania transitional to Chaco

28,913.3

Santa Cruz Chiquitania

15,194.7

Western Beni

64,295.1

Eastern Beni

Northern Beni

95,179.9

27,255.2

Northwestern Pantanal (Curiche Grande Basin)

11,335.9

Southern Pantanal (CorumbáMiranda)

2,687.4

7,902.1 (17%)

1,987.0 (4.3%)

20,452.5 (44.0%)

4,449.3 (17%)

629.9 (2.4%)

14,133.1 (54.0%)

8,668.9 (17%)

2,391.3 (4.7%)

20,397.3 (40.0%)

4,720.3 (17%)

709 (2.6%)

14,438.4 (52.0%)

1,788.5 (17%)

101.8 (1.0%)

6,522.7 (62.0%)

2,139.9 (17%)

145.7 (1.2%)

7,552.7 (60.0%)

2,351.0 (17%)

175.9 (1.3%)

8,574.2 (62.0%)

17,841.6 10,129.2 24,138.7 (17%) (9.7%) (23.0%) 4,915.3 (17%)

768.8 (2.7%)

16,191.5 (56.0%)

2,583.1 (17%)

212.3 (1.4%)

9,268.8 (61.0%)

10,930.2 (17%)

3,801.5 (5.9%)

22,503.3 (35.0%)

16,180.6 (17%)

8,330.9 (8.8%)

26,650.4 (28.0%)

4,633.4 (17%)

683.1 (2.5%)

14,990.3 (55.0%)

1,927.1 (17%)

118.2 (1.0%)

7,028.3 (62.0%)

456.9 (17%)

6.6 (0.2%)

2,660.5 (99.0%)

150

565.2 (1.2%)

1,038.0 (2.2%)

15,560.1 (33.5%)

↓↓1, ↓2, ↓↓3

↓↓1, ↓2, ↓↓3

↑↑1, ↑↑2, ↓↓3

6,805.9 (26.0%)

0 (0%)

25,077.2 (95.8%)

↑↑1, ↑↑2, ↓↓3

↓↓1, ↓2, ↓↓3

↑↑1, ↑↑2, ↑↑3

4,395.0 (8.6%)

9,380.3 (18.4%)

2,972.8 (5.8%)

↓↓1, ↑2, ↓↓3

↑1, ↑↑2, ↓↓3

↓↓1, ↑2, ↓↓3

696.8 (2.5%)

1,303.9 (4.7%)

4,490.3 (16.2%)

↓↓1, =2, ↓↓3

↓↓1, ↑2, ↓↓3

=1, ↑↑2, ↓↓3

0 (0%)

2.7 (0%)

1,621.5 (15.4%)

↓↓1, ↓2, ↓↓3

↓↓1, ↓2, ↓↓3

↓1, ↑↑2, ↓↓3

3,280.8 (26.1%)

322.3 (2.6%)

0 (0%)

↑↑1, ↑↑2, ↓↓3

↓↓1, ↑2, ↓↓3

↓↓1, ↓2, ↓↓3

0 (0%)

1,751.1 (12.7%)

9,106.8 (65.9%)

↓↓1, ↓2, ↓↓3

↓1, ↑↑2, ↓↓3

↑↑1, ↑↑2, ↑3

21,747.6 (20.7%)

3,856.5 (3.7%)

10,151.7 (9.7%)

↑1, ↑↑2, ↓3

↓↓1, ↓↓2, ↓↓3

↓↓1, =2, ↓↓3

8,669.3 (30.0%)

356.0 (1.2%)

1,187.8 (4.1%)

↑↑1, ↑↑2, ↑↑3

↓↓1, ↓2, ↓↓3

↓↓1, ↑2, ↓↓3

254.8 (1.7%)

2,105.0 (13.9%)

0 (0%)

↓↓1, =2, ↓↓3

↓1, ↑↑2, ↓↓3

↓↓1, ↓2, ↓↓3

7,005.2 (10.9%)

13,040.5 (20.3%)

10,230.4 (15.9%)

↓↓1, ↑2, ↓↓3

↑1, ↑↑2, ↓↓3

↓1, ↑↑2, ↓↓3

0 (0%)

14,819.3 (15.6%)

9,762.3 (10.3%)

↓↓1, ↓↓2, ↓↓3

↓1, ↑↑2, ↓↓3

↓↓1, ↑2, ↓↓3

0 (0%)

733.5 (2.7%)

6,357.5 (23.3%)

↓↓1, ↓2, ↓↓3

↓↓1, =2, ↓↓3

↑↑1, ↓↓2, ↓↓3

8,114.9 (71.6%)

0 (0%)

3,040.4 (26.8%)

↑↑1, ↑↑2, ↑↑3

↓↓1, ↓2, ↓↓3

↑↑1, ↑↑2, ↓↓3

370.9 (13.8%)

0 (0%)

0 (0%)

↓1, ↑↑2, ↓↓3

↓↓1, ↓2, ↓↓3

↓↓1, ↓2, ↓↓3

Uneven representation of biogeographical regions in Bolivia’s protected areas and indigenous territories

Northwestern Chaco

97,096.8

Northeastern Chaco

4,109.2

Total

16,506.4 (17%)

8,669.9 (8.9%)

26,216.1 (27.0%)

698.6 (17%)

15.5 (0.4%)

3,780.5 (92.0%)

1,087,418.5 184,861.1 61,749.7 438,310.0 (15.6%)

representation targets calculated under the three criteria, showing the importance of the SPA and, especially, the IT (the latter as OEABCM), in the total representation of Bolivia’s biogeographical regions.

If we analyze from the larger to the smaller scales, we see that the Tropical-Andean Region is under-represented by our criterium that at least two of the three targets be coincident (target 1 and 2, and even target 3 which shows this regions is slightly underrepresented).

The Brasilian-Paranaense is slightly underrepresented by criteria 1 and 3, and underrepresented by criterium 2. Some provinces within the Tropical Andean Region were the cause for its underrepresentation. We see that the xerophytic Puna stands out, as it is underrepresented by our three criteria; the Bolivian-Tucumano is underrepresented by two criteria (1 and 3) and slightly underrepresented by criterium 2. For the xerophytic Puna, three out of its four of sectors are poorly represented, except the Southwestern Lípez. Unlike most of the underrepresented sectors (which are mainly Puna, i.e., roughly beneath 4100-4,200 m), the Southwestern Lípez is essentially a high Andean portion of the province (above 4,200-4,300 m). This means that true Puna plant communities are practically outside the national system. For the Bolivian-Tucuman, the Prepuna is completely absent (all three criteria show it) and, although not as strongly (because criteria 1 and 3 show under-representation, criterium 2 does not), two of the three remaining sectors appear also with poor representation (only Bermejo is not

29,567.4 (30.5%)

301.0 (0.3%)

7,830.8 (8.1%)

↑↑1, ↑↑2, ↑3

↓↓1, ↓↓2, ↓↓3

↓↓1, =2, ↓↓3

3,315.3 (80.7%)

0 (0%)

0 (0%)

↑↑1, ↑↑2, ↓↓3

↓↓1, ↓2, ↓↓3

↓↓1, ↓2, ↓↓3

169,762.9 (7.8%)

85,189.8 (19.5%)

212,561.8

under-represented because of the existence of an already old park there, Tariquía).

In the case of the Brasilian-Paranaense Region, its Beni province is the reason for its under-representation. Two out of three of Beni’s sectors are very poorly represented.

Moreover, although the Western Chiquitania is not underrepresented, one of its sectors is: the Chiquitano transitional to Amazonia.

Finally, albeit Amazonia as a region and as the provinces is well represented, one sector is not (high Madeira), which means that in some cases the good representation of a given biogeographic category is given by an over-representation of some of its sectors in detriment of other sectors.

The subnational protected areas help counteract the deficiencies existent in the NPA, especially at the level of biogeographical provinces, but somehow also at the level of sectors (except for the high Madeira sector, which remains poorly represented).

However, it is the IT which helps counteract the national deficiencies particularly at the sector level (save for Eastern Beni, which has good representation in the SPA). The value of IT as real conservation units, at least in the high Andes, is dubious. People do no necessarily get identified with conservation planning, but with development strategies instead. Different types of Puna, dry valleys, and the Prepuna remain scarcely protected despite the fact that studies in these regions are showing that they are much more diverse and apparently present more endemism than previously thought (F.S. Zenteno, pers. obs.).

151

D. M. Larrea-Alcázar, R. P. López, F. S. Zenteno-Ruíz, I. Lafuente & Y. Fernández

Figure 2. Protected areas and indigenous territories officially recognized in Bolivia. The map shows also the biogeographical classification proposed by Navarro & Ferreira (2009): Region: I. Amazonian, II. Tropical Andean, III. Brasilian-Paranaense, IV. Chaco. Province: 1.

Southwestern Amazonia (Acre-Madre de Dios), 2. Central-southern Amazonia (MadeiraTapajós), 3. Western Cerrado, 4. Beni, 5. Pantanal, 6. Northern Chaco, 7. Yungas PeruvianBolivian, 8. Mesophytic Puna, 9. Xerophytic Puna, 10. Bolivian-Tucumano Sectors: 1a. Acre and Madre de Dios, 1b. Heath and Bajo Madidi, 1c. Pre-Andean from Northern Bolivia and Southern Peru, 2a. High Madeira, 2b. Guaporé, 3a. Chiquitania transitional to Amazonia, 3b.

Central Chiquitania, 3c. Chiquitania transitional to Chaco, 3d. Santa Cruz Chiquitania, 4a.

Western Beni, 4b. Eastern Beni, 4c. Northern Beni, 5a. Northwestern Pantanal (Curiche Grande Basin), 5b. Southern Pantanal (Corumbá-Miranda), 6a. Northwestern Chaco, 6b. Northeastern Chaco, 7a. Beni High Basin, 7b. Ichilo High Basin, 8a. Southern Mesophytic, 9a. SajamaDesaguadero, 9b. Uyuni Salar, 9c. Potosí, 9d. Southwestern Lípez, 10a. Piraí-Río Grande, 10b.

Pilcomayo-High Parapetí, 10c. San Juan del Oro Prepuna, 10d. Bermejo.

152

Uneven representation of biogeographical regions in Bolivia’s protected areas and indigenous territories

The conservation status of the biogeographical units analyzed seek to contribute to a better understanding of Bolivia’s biodiversity. Among the biogeographical provinces of the lowlands (but including the Yungas), the Beni Cerrado (Brasilian-Paranaense Region), and the Acre and Madre de Dios (Amazonian Region) stand out as those that have experienced the least degree of conversion of their natural ecosystems (Quintanilla & Larrea-Alcázar 2015). These provinces are important also because of their high species richness (Meneses et al. 2014 for Poaceae, Moraes et al.

2014 for palms, Larrea-Alcázar & Quintanilla 2015). Nevertheless, the advancement in the floristic knowledge of these provinces and their sectors is slow (Jörgensen et al. 2014) and the efforts to achieve that goal are still sparse (Fernández et al. 2015). Implementing a research agenda in areas with important information gaps is priority.

Although not strictly comparable, the analysis based on Ibisch et al. (2003) and Navarro (2011)’s maps show some common points. This is important if we want to evaluate the possible changes that may have occurred in more than one decade. In 2006, López & Zambrana-Torrelio (L-Z for brevity) reached several conclusions which we compare with our findings in the present article. They found that xeric regions were under-represented and humid regions were over-represented.

We can say that this has not changed. L-Z also concluded that the Prepuna, the dry Puna, the humid Puna, and the Beni Cerrado ecoregions were absent from the NSPA (National System of Protected Areas). The Prepuna is still absent, and the dry Puna (which roughly corresponds to Navarro’s Sajama-Desaguadero sector) is highly under-represented. According to our analysis regarding the humid Puna, its equivalent in Navarro’s map (mesophytic Puna Province) should not be considered clearly under-represented (it depends on the goal used), but Navarro’s mesophytic

Puna extends beyond Ibisch’s humid Puna, and covers parts of what some Bolivian biogeographers consider another ecoregion, the Yungas Paramo. Thus, the humid Puna s.s. is still not represented today in the NSPA. Ibisch’s Beni Cerrado ecoregion (corresponding to Northern Beni) is now highly under-represented, as is the Eastern Beni (which in part corresponds to Ibisch et al’s Moxos Plains, an ecoregion recognized

by L-Z as markedly under-represented). In L-Z, the semi-humid Puna was also poorly represented, and continues to be so (Potosí Sector). Finally, the dry interandean valleys had a very low representation. They can be analogued to the Piraí-Río Grande and Pilcomayo-Alto Parapetí sectors within the Bolivian-Tucuman Province. Based on our criterium that the coincidence of two of the three goals indicate a tendency, they can still be considered under-represented today.

Therefore, the analysis at a national level show that very little changes have been produced in more than ten years.

Conclusion Our results show differences in the representation targets depending on which ways were used. This support the hypothesis that the conservation targets based on representation areas are based on political consensus and may underestimate the recommendations that conservation science can make (e.g., Locke 2014). We suggest cautiousness in the use and interpretation of the 17% target recommended by the Aichi targets of the CDB. For example, the Amazonian Region showed different results in NPA for the three criteria of calculation of representation targets. On the other hand, the results also highlight the potential importance of the SPA and the IT in the vegetation representation in Bolivia, the latter two being examples of “other efficient conservation measures based on areas” (OEABCM); 153

D. M. Larrea-Alcázar, R. P. López, F. S. Zenteno-Ruíz, I. Lafuente & Y. Fernández

however, we also suggest cautiousness on the role of IT in the highlands.

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Challenges and Opportunities for the Bolivian Biodiversity Observation

Acknowledgements This study was partially done within the course “Conservation and Management of Natural Areas” of the career of Biology of the UMSA (Universidad Mayor de San Andrés).

P. Casilla helped with part of the preliminary analysis. Two anonymous reviewers provided valuable input. ACEAA thanks the Amazon Conservation Association (ACA) for financial support. The authors declare no conflict of interest.

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Artículo recibido en: 11 de junio de 2016.

Manejado por: Andrea Premoli.

Aceptado en: 27 de septiembre de 2016.

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