Outline Report Framework
Transcription
Outline Report Framework
FINAL VERSION June 2009 TABLE OF CONTENTS 1 Introduction................................................................................................................................... 4 1.1 Background ........................................................................................................................... 4 1.2 Durban Vision ....................................................................................................................... 6 1.2.1 History, outline of work and summary of progress to date........................................... 6 1.2.2 SAPM............................................................................................................................ 6 1.2.3 Timeline ........................................................................................................................ 7 1.3 Principles and methods of systematic conservation planning............................................... 9 1.3.1 Compile data for the planning region ......................................................................... 10 1.3.2 Identify conservation targets and goals....................................................................... 11 1.3.3 Review existing conservation areas ............................................................................ 12 1.3.4 Select new conservation areas..................................................................................... 12 2 SAPM analysis 2004, 2006......................................................................................................... 14 2.1 Introduction......................................................................................................................... 14 2.2 SAPM analysis 2004........................................................................................................... 14 2.2.1 Data ............................................................................................................................. 14 2.2.2 Methods....................................................................................................................... 16 2.2.3 Results......................................................................................................................... 16 2.2.3.1 Arrêté Mines-Forêt 2004......................................................................................... 16 2.3 SAPM analysis 2006........................................................................................................... 19 2.3.1 Data ............................................................................................................................. 19 2.3.2 Methods....................................................................................................................... 19 2.3.3 Results......................................................................................................................... 21 2.3.3.1 Arrêté Mines-Forêt 2006......................................................................................... 21 2.3.3.2 Gap analysis 2006 ................................................................................................... 22 3 Multi-taxonomic analysis 2008................................................................................................... 24 4 Priority Synthesis 2008 ............................................................................................................... 24 4.1 Introduction......................................................................................................................... 24 4.2 Data ..................................................................................................................................... 24 4.2.1 Species and habitat distribution data........................................................................... 24 4.2.2 SAPM parks data ........................................................................................................ 24 4.2.3 Conservation priority data........................................................................................... 25 4.2.4 Mining areas................................................................................................................ 25 4.3 Methods............................................................................................................................... 27 4.4 Results................................................................................................................................. 30 4.4.1 Marxan results............................................................................................................. 30 4.4.2 Arrêté Mines-Forêt 2008............................................................................................. 30 4.4.3 2008 Gap analysis of SAPM areas.............................................................................. 32 5 Discussion ................................................................................................................................... 34 5.1 Methodological comparisons .............................................................................................. 34 5.2 Implementation ................................................................................................................... 34 6 Recommendations....................................................................................................................... 36 7 Acknowledgements..................................................................................................................... 37 8 “Durban Vision Group” participating organizations .................................................................. 37 9 Authors and contributors............................................................................................................. 37 10 References............................................................................................................................... 38 2 LIST OF TABLES AND FIGURES Figure 1 - Evolution of new SAPM protected areas, by year ................................................................... 8 Figure 2 - Map for the "Arrêté mines-forêt" 2004 .................................................................................. 18 Figure 3 - Map for the "Arrêté Mines-Forêt" 2006................................................................................. 23 Figure 4 - Inputs into the 2008 Multi-taxonomic analysis...................................................................... 26 Figure 5 - Maps for the "Arrêté Mines-Forêt" 2008 ............................................................................... 31 Figure 6 - Final map of SAPM parks and protected areas, 2008/2009................................................... 33 Table 1 - Park area by date of establishment, and percent of Madagascar covered ................................. 7 Table 2 - Scenarios developed for Marxan. ............................................................................................ 28 3 1 Introduction 1.1 Background Madagascar is widely known for exceptional rates of both diversity and endemism in many taxonomic groups, as well as a low percentage of remaining native forest cover and high levels of threat (Goodman & Benstead 2005; Harper et al. 2007; Kremen et al. 2008). As such, the island is nearly universally recognized as a global biodiversity priority (Brooks et al. 2006; Myers et al. 2000; Rodrigues et al. 2004). At sub-island scales, however, complex and often non-concordant patterns of micro-endemism among taxa (Goodman & Benstead 2005; Kremen et al. 2003; Raherilalao & Goodman 2005; Schatz 2000; Schatz et al. 2000, Kremen et al. 2008) make the task of efficiently and effectively allocating land to conservation uses especially relevant and challenging (Cowling et al. 1999; Grenyer et al. 2006 ; Prendergast et al. 1993). Historically, Madagascar has demonstrated a strong and growing commitment to conservation. The first protected areas were created in 1927 (Nicoll & Langrand 1989) and their numbers have steadily increased since then. In 1989 conservation in Madagascar was significantly advanced with the initiation of the 15-year National Environmental Action Plan. This first phase of the implementation of this plan created the Association National pour la Gestion des Aires Protégées (ANGAP) to manage the network of protected areas. By 1990, Madagascar had 30 protected areas, in the following designations: 11 Strict Nature Reserves (IUCN Category I), two National Parks (IUCN Category II), and 17 Special Reserves (IUCN Category IV). By 1997, Madagascar had 46 protected areas, designated as Strict Nature Reserves (IUCN Category I), National Parks (IUCN Category II), or Special Reserves (IUCN Category IV). In 2002, just prior to the announcement of the “Durban Vision” (see below), 1.8 million ha., approximately 3.1% of the land surface area, was protected in some form of statutory reserve (Rasoavahiny et al. 2008; Razafimpahanana et al. 2008)1. In 2004, Madagascar passed the Protected Area Act to establish the legal framework for the management of the network by ANGAP, another significant milestone. At the Vth IUCN World Parks Congress (WPC) in Durban, South Africa, in 2003, Madagascar President Marc Ravalomanana made a significant addition to this historic commitment to conservation by announcing a plan to triple protected area coverage to 10% of the land area. This represented an increase of over 4 million ha. to achieve a total target of 6 million ha. This commitment, hereafter referred to as the “Durban Vision”, presented a unique and unprecedented opportunity for conservation in this global biodiversity hotpot. It also raised many new questions and challenges. Where are the best places to put new parks? What biodiversity data can be used to answer this question? What methods and tools are available to support this process? Fortunately, significant new data sources and planning tools existed to help answer these questions and achieve this ambitious goal. First, the Durban Vision’s “Prioritization Group” (see below for additional history on this group) and the Reseau de la Biodiversité de Madagascar (REBIOMA) joined forces to compile georeferenced locality data and refined “extent of occurrence” (rEOO) distribution polygons for a wide variety of vertebrate and non-vertebrate taxonomic groups across Madagascar, thereby leveraging results from decades of scientific research to better understand the distribution of the Malagasy biota. Second, advances in theory and methods for conservation planning have resulted in widely available tools like Maxent, Marxan and Zonation to inform priority setting and guide the selection of new protected areas. 1 The figures presented here are calculated directly from GIS shapefiles, and differ slightly from previous calculations. Razafimpahanana et al. 2008, for example, show 1.7 million ha. of parks in 2002. 4 In the nearly five years since the announcement of the Durban Vision, tremendous progress has been made in the identification and mapping of new biodiversity priority areas, a key step towards creating a new Madagascar Protected Area System (Système des Aires Protégées de Madagascar: SAPM). The Prioritization Group of the commission SAPM, a continuation of the early Durban Vision Prioritization Group, has carried out the bulk of this work, in several distinct stages. At each stage, new protected areas were identified and established progressing steadily towards the total area necessary to meet the Durban Vision commitment. Results of this identification and mapping work have also been instrumental in national-level decisions relating to the management of lands for mining and forestry. No detailed documentation or dissemination of the totality of this important work exists, however, lessening its utility and hindering its widespread adoption. For example, national level priority setting analyses have not always been directly incorporated at regional or “corridor” levels, as the island-wide results have not generally been in a format useful at local scales. Some components of this work have been described in various documents (e.g. Razafimpahanana et al. 2008, Rasoavahiny et al. 2008, Borrini-Feyerabend & Dudley 2005) but there is also a need for documentation of the entire process. With this report we attempt to rectify this situation by putting the results of this important work directly into the hands of decision makers. First, we document, in as much detail as possible, the decisions that have gone into each stage of the Durban Vision/SAPM priority setting exercises to date. Second, we present a companion “conservation atlas” for the Durban Vision. This atlas is available in digital CD and online version (http://atlas.rebioma.net), and presents detailed maps from several years of priority setting in a variety of common formats. For additional information on the maps themselves, see documentation accompanying the maps on the CD. 5 1.2 1.2.1 Durban Vision History, outline of work and summary of progress to date Implementation of the Durban Vision began soon after President Ravalomanana’s announcement at the World Parks Congress in 2003 (Norris 2006). First, in early 2004, a “Durban Vision Group” (DVG) steering committee was established under the leadership of the DGEEF (Department of the Environment, Water and Forests, now called the Department of Environment, Forests, or DGEF) to direct the implementation of the Durban Vision. The DVG integrated members from over a dozen national and international organizations, including staff from government ministries and nongovernmental organizations (see below for complete list). The DVG was divided into four core technical groups responsible for different aspects of the Durban Vision mission: 1) Sustainable Financing (“Financement Durable”), 2) Legal Framework (“Cadre Juridique”), 3) Categorization and Governance (“Catégories et Types de Gouvernances”), and 4) Prioritization (“Priorisation”). This document focuses on documenting the tasks of this last technical group. Prioritization Committee: The Prioritization Committee (hereafter: Prioritization Group) was responsible for defining the criteria for setting priorities and identifying terrestrial, marine and freshwater conservation priority sites. Members of the Prioritization Group were drawn from government agencies, NGO’s, and universities. Principal tasks of the group included: • • • To study and compile information on the distribution of Malagasy biodiversity To propose tools and methodologies for supporting the selection and identification of protected areas to relevant authorities To analyze and enumerate the contribution of existing and proposed protected areas and priority sites on the conservation of Malagasy biodiversity Details of how the group carried out these tasks included: • • • Collecting all available distribution data on plants, lemurs, birds, amphibians, reptiles, fish, other mammals and also of certain insects such as ants and butterflies Validating and organizing data with cooperation from national and international taxonomic and conservation experts Conducting analyses of these data with conservation planning software such as Marxan for the purpose of identifying priority conservation areas The Prioritization Group produced initial priority setting products in mid to late 2004. Subsequent priority setting analyses were conducted in 2006 and 2008, and these contributed both to interministerial “suspensions” (“arrêtés”), as well to new and potential protected area maps. A timeline for this work including details on each of these analyses is provided below. 1.2.2 SAPM In early 2005, the “Durban Vision Group” steering committee received technical assistance from IUCN to help develop management options and governance approaches in the new protected areas (BorriniFeyerabend & Dudley 2005). As a result of this mission, the steering committee decided to broaden its focus from what had originally been called “Sites de Conservation” to an expanded range of protected 6 area conservation categories and governance types corresponding to IUCN categories I-VI. This change meant that new protected areas established under the Durban Vision could be managed according to a range of management types including, for example governance by decentralized governments (regions, communes), the private sector, local communities, civil society and shared governance between the State and multiple actors (Rasoavahiny et al. 2008). At the same time, the Durban Vision group changed its name to “Commission Système des Aires Protégées de Madagascar”, or “Commission SAPM” (Madagascar Protected Area System Committee), under the direction of the Ministry of the Environment (DGEEF). This change in name is actually quite important, as it recognizes and formalizes the Commission SAPM as the instrument within the ministry for implementing what had formerly been simply called the “Durban Vision”. 1.2.3 Timeline At the time of the Durban Vision announcement in September 2003, protected areas covered approximately 1.8 million ha, or just over 3% of Madagascar (Table 1, Figure 1). In years following, this figure has more than doubled, with the establishment of more than 25,000 km2 of additional parks through 2007. Establishment of new parks has occurred incrementally, with a significant announcement of new areas occurring roughly once per year since 2005. The parks cited below are not all of the same type or status, and include parks with full decreed status under ANGAP, as well as parks which, at the time of writing, are on a likely track to become fully decreed SAPM protected areas in the near future. Although area in excess of the Durban Vision target has now been identified (9.4%), only a small fraction of this has actually been fully decreed as new protected areas. Year pre 2003 20052 2006 2007 20084 Additions Additions Total Total Additions ZPT (ha) NAP (ha) additions (ha) area (ha) AP (ha) ----1,757,486 -945,288 -945,288 2,702,774 -1,090,297 -1,090,297 3,793,071 554,771 -554,771 4,347,842 26,0343 -383,511 822,742 1,206,253 5,554,095 Total % of land surface 3.0 4.6 6.4 7.3 9.4 Table 1 - Park area by date of establishment, and percent of Madagascar covered Abbreviations are as follows: AP: Decreed protected area, ZPT: Zones protected by temporary decree; NAP: New protected area awaiting temporary decree. 2 The numbers for 2005-2007 come directly from calculations in GIS and may differ slightly from the official DSAP numbers. In addition, in certain cases, marine areas are included (e.g. Masoala). 3 This area (Sahamalaza) received decreed protected status in 2007. Because this was included as a ZPT in 2006, these 26,034 hectares are not included in the “Total Additions” column for 2007 4 Figures calculated in GIS in April, 2009. The official government numbers for 2008 are not yet available 7 Figure 1 - Evolution of new SAPM protected areas, by year 8 1.3 Principles and methods of systematic conservation planning Much has been written in recent years about the importance of employing systematic, quantitative methods when designing or making additions to protected area networks (Araújo & Williams 2000; Margules & Pressey 2000; Sarkar et al. 2006). In this section we review and synthesize key concepts of systematic conservation planning. We also discuss the topic in the context of protected area expansion under the Durban Vision. The overall aim of conservation planning is to design reserve systems that maximize the representation and persistence of species. Put in another way, it is important both to ensure that as many species and ecosystems are included in the reserve network in the first place (representation), and that the size and configuration of protected areas favors the long-term survival of species and ecosystems into the future (persistence). Systematic conservation planning helps meet these objectives in two ways: One, this methodology provides a structured, step-wise set of procedures to guide decision makers through the process of reserve selection; and, two, systematic methods typically employ quantitative tools such as computer algorithms and software programs to assist identification and mapping of priority areas and to design representative, viable sets of reserves. In the past, reserves have generally been selected opportunistically. Surveys in a wide variety of regions show that the majority of reserves occur in areas where there are few competing economic uses, e.g. “lands nobody wanted” (Pressey 1994). Such traditional, ad-hoc approaches to selecting conservation areas are considered inadequate, for two related reasons. First, such reserve networks often do not adequately represent target species and/or habitats. As a result, globally, many threatened species currently have inadequate protection. In fact, one recent global analysis of 11,633 vertebrate species found that 12% of all species and 21% of threatened species have no protection whatsoever, and many others have far less of their habitats protected than is advisable to ensure their survival (Rodrigues et al. 2004). Second, existing reserve networks are often “inefficient” in the sense that their “cost” (e.g. surface area, economic cost, social cost) is often considerably higher than necessary to meet conservation objectives (Stewart & Possingham). Systematic conservation planning aims to produce reserve systems that most efficiently meet the goals for representation and persistence (Margules & Pressey 2000). As noted, systematic conservation planning involves a structured, step-wise approach to reserve design. The actual approach taken in any given application, however, will vary according to local conditions and preferences. Nevertheless, several key steps are common to many systematic planning approaches (Cowling & Pressey 2003; Groves et al. 2002; Margules & Pressey 2000; Shafer 1999). Implementation of the reserve system and subsequent management of the reserves on the ground are sometimes topics of discussion in systematic conservation planning literature. These topics are generally outside of the scope of this paper, however, as we are focusing on the biodiversity assessment stage, and not the implementation of the Durban Vision. Naturally, implementation and management are key to successful conservation of Madagascar’s biodiversity (Knight et al. 2008; Knight et al. 2006). In a later section, we do briefly discuss the implementation of systematic conservation planning (the results of an analytical process) within the overall SAPM process. 9 1.3.1 Compile data for the planning region This step comprises basic data collection, organization and management, and like others, is iterative: as new data become available, they should be synthesized and incorporated to the extent possible. The first task is to search for, review and collect existing data. In most parts of the world, there have been considerable, though often scattered, survey and mapping efforts. The challenge here is both to discover these data and, to obtain permission to use them. Although digital, geographically referenced data are preferred, in some cases, data are only available in paper/analog format and must first be digitized and/or georeferenced. This review of existing data sources should target two general types of data. The first are geographic biodiversity data. Here the goal is to collect distribution data for as many biotic (e.g. species, vegetation types, habitats) and environmental parameters (e.g. elevation, climatic variables) as possible, in whatever forms available. Sources may include: range maps, museum locality data, modeled distributions of species or vegetation and remotely sensed data. This step may also include assessments of rarity, threat, endemicity and other conservation values. Without further supplementation this data can provide a “biodiversity benchmark” – a conservation solution optimized for maximum conservation impact, but not incorporating cost. Further desirable data to compile are socieconomic data, including data on resource ownership (e.g. land tenure, political boundaries, existing parks, plans and zonations), resource and indigenous concessions (e.g. mining, forestry), infrastructure (e.g. roads, dams), and population and other census data. This second class of data allows consideration of the relative costs of conservation, through exploration of the trade-off between biodiversity protection, financial costs and different conservation solutions. Additional actions can include the following: • Identify stakeholder groups and other participants in the planning process. Many consider this to be a first, separate step in the planning process, and much has been written on this topic (Pressey & Bottrill 2008). • Identify data gaps, and begin new surveys as necessary and possible. This involves a careful assessment of what data exist in terms of what data are needed to adequately complete the conservation plan, in light of timelines and budget constraints. • Review, assess, and document data quality • Design and build metadata and data management system, including databases, a system for data documentation (metadata) and data storage. • Identify and acquire necessary computer software and hardware to assist with all of the above tasks. Under the Durban Vision, this process has been iterative: Data have been collected and refined at key steps in the analysis. Initial work focused on polygon-based distribution maps, with a focus on threatened vertebrate species, as these had previously been mapped under the CAMP (CBSG 2002), and IUCN species assessments (GMA, GAA, etc.), and had already been used by members of the group to map priorities in the Ala Atsinana (Eastern Humid Forest) Ecoregion Vision (Erdmann et al. 2005). In subsequent years, MBG (Schatz et al. 2000) and REBIOMA (Kremen et al. 2008) conducted analyses that incorporated significant numbers of plants and invertebrates. Additional details on data are found in subsequent sections. 10 1.3.2 Identify conservation targets and goals The core goals of systematic conservation planning are the representation and persistence of biodiversity. Achieving these goals – or at least assessing whether a given conservation plan adequately addresses them – generally requires setting quantitative conservation targets for the following: • Amount of each species total distribution to include in protected areas, expressed in terms of areas or occurrences • Proportion of each habitat to include in protected areas • Minimum size, fragmentation and connectivity of conservation areas The first step is to select the full set of species and habitat types that are to be the focus of the conservation plan. It is generally impossible to include all species, especially as the majority of species have yet to be described or mapped in any way. Thus, a representative set of species is generally chosen. In other cases, species distributions are ignored, and the focus is only on habitats or environmental domains as “surrogates” for the distribution of species. Much has been written on the topic of surrogacy in the context of conservation planning and priority setting (Ferrier 2002; Wiens et al. 2008). Setting targets is not easy, and there is an inherent degree of subjectivity involved, given that species distributions are generally only poorly known, and the area needed for their long-term persistence can at best only be estimated (Burgman et al. 2001; Margules & Pressey 2000; Pressey et al. 2003). One general approach is to increase the proportional target amount for species and habitats with restricted distributions (e.g. endemic species and habitats). This results in widespread species having lower target percentages (e.g. 10%), and highly restricted range species having high target percentages (e.g. 100%) (Rodrigues et al. 2004). An alternative approach to setting targets is to estimate an acceptable extinction risk for individual, or all target species. Conservation areas may then be selected so as not to cross this threshold, or that minimize this overall extinction risk. Generally speaking this is the approach of the Zonation software tool (Moilanen 2007). The Durban Vision process has considered targets in a variety of ways during different stages of the analysis. Most Marxan based analyses have used the target setting method of Rodriques et al. (2004a). The Zonation analyses, in contrast, have not set species-based targets, but rather used species weights. The difference between targets and weights is subtle but important. Targets are fixed and usually the resulting solutions which would achieve all the individual species targets exceed the total area available for conservation (in this case 6 million hectares). The species weights in Zonation emulate the process that most target setters have to follow when they systematically erode their targets and re-run the prioritization until they reduce the area selected to the total area available for conservation. With weights, instead of deciding on a fixed area to be protected per species the experts have to decide on relative protection levels, for example that one species should always have twice as much protection as another within the total area available for conservation. A common goal when using either targets or weights is to try to minimize extinction risks for the most threatened species See below for additional details on individual analyses. 11 1.3.3 Review existing conservation areas The aim of this step is to assess the degree to which existing protected areas are already meeting the conservation goals elaborated in the previous step. This process, often referred to as “gap analysis”, provides a clear understanding of what work remains to be done to meet conservation goals. Accomplishing this step requires only well-defined maps of the protected areas, the species and habitat distributions of interest and the stated targets for each (e.g. the information obtained in the previous step). “Gaps” are expressed in terms of targets met or not met for every species and habitat. Numerous “gap analyses” have been conducted by the priority setting group under the Durban Vision process in an attempt to highlight species and habitats that are missing or under-represented from various configurations of parks and priority areas. Ideally a gap analysis should be conducted every time a new protected area is decided upon and added to a network, as it can then inform the subsequent iteration of prioritization analysis to identify the next most important area to add to the network. 1.3.4 Select new conservation areas Generally speaking, new reserves should be selected to meet conservation targets in a way that complements the protection offered by existing reserves (principle of complementarity). This is one way of ensuring a more efficient reserve network (Justus & Sarkar 2002; Kirkpatrick 1983). The selection of new conservation areas is the core step in developing a systematic conservation plan. The purpose of this step is to map a set (or sets) of areas that meet conservation targets. The final output may be a simple “binary” map showing areas that are either designated as “in” or “out” of the reserve solution. More often, especially at interim stages of the process, the output is a map that ranks areas according to their relative importance in meeting conservation targets. This step is usually implemented with the help of software tools and mathematical area- selection algorithms. In recent years, reserve selection software and algorithms have increased in power and sophistication and now are widely and increasingly used in conservation planning. Reasons for this include: • Algorithms enable the rapid analysis of very large data sets, including potentially thousands of targets and hundreds of thousands of planning units; analyses that are virtually impossible to do “by hand” or other traditional means • The quantitative nature of computer based reserve design can ensure that conservation targets are achieved in the plan, or that those that targets that are not achievable are clearly listed in the outputs. • Computer-based analyses can be repeated, as the rules and procedures are explicit and easy to document, thus lending a degree of transparency to what has traditionally been a very subjective process • In addition, repeated analyses can identify alternative sets of land areas that meet the defined targets The use of software and algorithms does not exclude expert opinion; in fact input from experts is generally solicited at various points during this stage of the process. Expert advice is utilized in setting options for running the algorithms, and, in evaluating the results produced by algorithms. In this sense, the algorithm produced maps serve as “guides” providing decision support to the overall reserve selection process – a “basis of negotiation” (Margules & Pressey). 12 As noted, one output of the area selection process may be a map showing the relative value of areas towards meeting conservation goals. This brings up the concept of “irreplaceability” (Ferrier et al. 2000). In essence, irreplacebility defines how “replaceable” a given area is, that is, how important an area is in terms of the species it contains and the targets that have been set. The more irreplaceable an area is, the more critical it is to meeting one or more conservation targets. An example of a highly irreplaceable area would be one that contains several endemic species that are found nowhere else. Clearly, not all the specified targets can be met unless this area is included in the conservation plan’s solution set. Producing maps of irreplaceability can thus help to determine the final set of reserves or conservation areas. The most irreplaceable areas are those that have the highest priority for inclusion in the reserve system as they are essential to meet the specified conservation targets. Areas with medium irreplaceability are more “flexible” – some, but not all of these areas will be needed to meet conservation targets; such areas provide opportunities for negotiation. The priority setting group has assisted the selection of new priority areas with numerous analyses using Marxan, Zonation and related tools at key steps in the process. See below for details on these efforts. 13 2 SAPM analysis 2004, 2006 2.1 Introduction Since 2004, the Prioritization Group has made significant progress towards defining conservation priority areas across Madagascar. In addition to producing priority area maps that helped define new protected areas, in both 2004 and 2006 the products of this analysis also served as the basis for interministerial “suspensions” (or “arrêtés”) between the Ministry of Energy and Mines and the Ministry of Environment, Waters and Forests, temporarily suspending logging and mining activities in the mapped priority areas. In this section we focus on the two iterations of this analysis that led to the suspensions of 2004, 2006. The analysis for renegotiating the 2008 suspension is covered in a later section. 2.2 SAPM analysis 2004 A tremendous amount of work on biodiversity and priority setting had already been conducted in Madagascar prior to 2004. To review and consolidate this existing work, shortly after the Durban Vision announcement, the Priority Setting group set about collecting the results of all national-level biodiversity priority-setting exercises conducted over the previous 10 years. The result was a map of the 36 “most prioritized areas” in Madagascar. This map was a synthesis of the following national-level priority-setting analyses: • Atelier de priorisation 1995 (PRISMA) • Sites ZICOMA (Birdlife) • Priorisation sur les familles endémiques des plantes 2000 (MBG) • Plan GRap (ANGAP) • Zonage 2001 (DGEF) • Atelier sur la couverture complète de la biodiversité 2001 (CI) 2.2.1 Data Below, we briefly describe each of these data products that served as inputs to the 2004 priority setting process. Atelier de priorisation 1995 (PRISMA) The PRISMA conservation priority workshop was held in 1995. The aim of the workshop was to map and list conservation priority sites across Madagascar. Participants reviewed the following criteria when assessing the conservation priority of different areas: Biological importance (species diversity, endemism), anthropomorphic threat or pressure (population density, charcoal production), conservation priority (necessity, local cooperation, regional development plan), research priority (inventory, longterm study). The result of the workshop included a list and maps of about 75 conservation priority sites in the north, east, west, south and south-west Madagascar based on the opinions of the expert participants. Sites included areas with existing protection, as well as new areas without formal protected status. Readers are referred to Conservation International-Madagascar for more information. 14 Sites ZICOMA (BirdLife) In 1997, BirdLife International initiated the Project ZICOMA to identify Zones of Importance for the Conservation of the Birds (ZICOs). These sites meet the Important Bird Area (IBA) international criteria, developed by BirdLife International (ZICOMA 1999). The IBA criteria are divided into four categories based on individual species vulnerability and/or whether the area hosts significant congregations of birds. By definition, IBAs are sites that support: 1. Species of conservation concern (e.g. IUCN threatened species) 2. Range-restricted species 3. Species that are vulnerable because their populations are concentrated in one general habitat type or biome 4. Species, or groups of similar species (such as waterfowl or shorebirds), that are vulnerable because they occur at high densities Eighty-four ZICO sites were selected from a total set of 101 sites visited over two years, representing the most important sites for bird conservation in Madagascar. Interested readers are referred to BirdLife International for additional information (ZICOMA 1999). Priorisation sur les familles endémiques des plantes 2000 (MBG) In 2000, MBG drew attention to the eight families of vascular plants endemic to Madagascar and the Comoros, describing the ca. 100 species in these families the “most endemic of the endemics”, and calling their conservation a high priority (Schatz et al. 2000). To identify which species in the endemic families are most threatened, and should therefore be the focus of protection and conservation monitoring, it was first necessary to review, and revise where appropriate, the existing taxonomic framework for each family. The risk of extinction of each species was then assessed according to the criteria established for assigning the IUCN Red List Categories. Natural history (herbarium) collections from the basis for both revised taxonomic frameworks and the first level of extinction risk analysis. Using GIS, species distributions were mapped based upon geo-referenced primary occurrence data, which permits the determination of the number of “sub-populations”, their area of occupancy and extent of occurrence, and presence/absence in protected areas. Field studies to determine ecological and population characteristics then targeted those species occurring exclusively outside of the protected areas or known only from historical collections and/or an extremely limited distribution. For the three families for which revised taxonomic frameworks and assessments of extinction risk have been completed, 18 of the 29 species assessed are classified as “threatened”. A GAP analysis revealed that 7 of the species are not included in the existing protected areas network. Based upon distributions of all ca. 100 species in the endemic families, five areas emerged as critical for their conservation, and these areas were used directly as inputs into the priority setting. PlanGrap (ANGAP) PlanGrap was an analysis of existing and potential protected areas to ensure adequate representation of biomes and ecosystems across Madagascar. The approach was based on an analysis of biogeography and bioclimate in relation to the location of existing protected areas. To prepare PlanGrap, a series of workshops were organized to bring together scientists and experts from partner organizations to examine scientific evidence and identify areas to protect to ensure the representation of the natural heritage. PlanGrap also defined strategies and management priorities in all areas of intervention such as conservation, research, development, ecotourism and environmental education. Interested readers are referred to ANGAP for additional information and documentation. 15 Zonage 2001 (DGEF) Readers should consult with the Department General d’Eaux et Forets (or MEFT) for additional details on this input to the priority setting analysis, as no details were available at the time of writing. Atelier sur la couverture complète de la biodiversité 2001 (CI) The aim of this workshop was to help define the conservation priorities outside protected areas across Madagascar, and to prioritize forests and wetlands that should be targeted in the near future for inclusion in the network of protected areas. Approximately 25 national and international conservation and taxonomic experts were invited to the workshop to identify the unprotected sites that contained species found nowhere else or found only outside protected areas. Specialists were drawn from across major taxonomic specialties, including mammalogy, botany and invertebrate taxonomy. The result was a map that identified top priority sites across all taxa by overlaying each individual taxon map, and according a score to each site following the number of taxa for which it was a priority. Interested readers are referred to Conservation International-Madagascar for additional information on this workshop and results. 2.2.2 Methods The group compiled these maps and used GIS overlay in order to identify areas of significant concordance across priority-setting schemes, according to the following rule: If an area was prioritized at least 3 times by the above six priority setting analyses, then it was included. The result is a map of 36 priority areas, with a total area of 4.8 million ha. Taken together, these areas, which included protected areas existing at that time, potentially protect a significant level of Madagascar’s biodiversity. When the group compared this result to the distribution of threatened vertebrates, however, gaps in protection were evident. In an initial attempt to remedy these gaps, the group incorporated results from a Marxan analysis of all lemur species that was conducted around the same time (June 2004). This Marxan analysis identified areas to meet representation targets for lemurs. Targets were set on a sliding scale depending on the total range size of the species in question (cf Rodrigues et al. 2004). The smallest target was at least 10% for the largest ranging species. For species with restricted ranges (less than 2000 km2), targets were as much as 100%. This result (Marxan “Best” solution) was added as a seventh layer to the existing map of priorities described above. 2.2.3 Results In October 2004, the group combined these 36 priority areas plus the Marxan lemur analysis to produce the 2004 priority area map (Figure 2 - Map for the "Arrêté mines-forêt" 2004). This map shows existing protected areas in blue (“Aires protégées actuelles (AP)”: 17,619.27 km2), areas reserved for conservation in red (“zones réservés pour sites de conservation (SC)”: 76,770.8 km2) and remaining natural forest in green (“habitat en dehors des AP and SC”). The red priority areas came exclusively from the analysis described above. 2.2.3.1 Arrêté Mines-Forêt 2004 The priority area map (Figure 2 - Map for the "Arrêté mines-forêt" 2004) also served as the basis for an interministerial “arrêté” specifying allowable land uses in the mapped areas. Specifically, between 16 2004 and 2006 no additional mining or logging permits could be issued in the red priority areas (“Zones réservées pour sites de conservation”), which total 7.677 million ha, pending review and potential creation of new protected areas. 17 Figure 2 - Map for the "Arrêté mines-forêt" 2004 18 2.3 SAPM analysis 2006 Following the 2004 analysis, in 2005, the Ministry of Environment, Water, and Forests established and granted temporary protected status to nearly one million hectares of new protected areas, including, for example, Makira, Ankeniheny-Zahamena, Anjozorobe and Daraina. Delineation of exact boundaries for each area was the responsibility of each area’s “promoteur”, or co-manager, according to guidelines provided by the ministry. For example, the boundaries of Daraina were provided by Fanamby. In some cases, initial boundaries that were provided in 2004-05 continue to be refined up through the present day. With temporary status provided by the 2004 “arrêté” set to expire in October, 2006, in mid-2006, the Priority Setting Group updated their analysis of priority areas to serve as a basis for a new suspension. This time, however, the group decided to leverage the power of several newly-available software based planning tools, conservation datasets, and conservation analyses available in Madagascar, in order to produce the new priority map. 2.3.1 Data The red areas (“sites potentielles”) on the 2006 map were created by combining, in whole or in part, the results of four independent conservation priority analyses: 1) Marxan analysis of threatened vertebrates (similar to the above analysis for lemurs, but now expanded to include many other vertebrate species, 2) APAPC-MBG analysis of plant conservation priorities, 3) Zonation analysis of ants and butterflies, 4) Key Biodiversity Areas. The combination process is described below in “Methods”. The following data were included in the above analyses: • APAPC-MBG. 264 plant species; • KBA’s: A composite map including some threatened vertebrate species distributions, some APAPC’s, many ZICO areas (see description above), some RAMSAR wetland sites, all AZE sites (see full description below); • Marxan threatened vertebrate species: 63 mammals (GMA), 31 birds (BirdLife), 51 amphibians (GAA), 50 reptiles (CBSG), 53 fish (CBSG); • Zonation invertebrates: 198 endemic butterflies (Lees, Cameron and Kremen), 89 endemic ants (Fisher and Cameron) 2.3.2 Methods In this section we describe each of the individual analyses that contributed to the 2006 result. Each analysis was conducted independently by different research teams or organizations. The Prioritization Group assessed and compiled the results for combination into a single priority map. APAPC-MBG Aires Prioritaires pour la Conservation des Plantes à Madagascar de Missouri Botanical Garden (APAPC-MBG). This analysis used 10% of the Malagasy flora representing a wide range of life forms, taxonomic groups and ecoregions (1200 species) to identify priority sites for plant research and conservation. The resulting 80 priority areas cover a total area of around 3 million ha, distributed in natural vegetation around different regions of Madagascar. 19 KBAs: Key Biodiversity areas In 2004, the Center for Biodiversity Conservation, Conservation International Madagascar, began the delineation of Key Biodiversity Areas for Madagascar (Eken et al. 2004). The delineation is based in part on the distribution of IUCN red listed species from global assessments including: Global Mammal Assessment (GMA), Global Amphibian Assessment (GAA) and Global Marine Species Assessment (GMSA). The final boundaries are based in whole or in part on the distribution of 532 threatened species covering 8 taxa, on remaining forest cover, and on existing park boundaries. In total, 164 KBAs have been identified in Madagascar. KBAs also include all of the AZE (Alliance for Zero Extinction) sites. Marxan analysis of threatened vertebrates The Prioritization Group used Marxan to identify a minimum set of areas to meet areal targets for threatened vertebrate species (species groups listed above). Targets were set according to the range size of each individual species so that species with smaller ranges (less than 2,000 km2) had higher targets (up to 100%) and species with larger range sizes had smaller targets (circa 10%). One species (Whitebreasted mesite, Mesitornis variegata) was divided into four populations based on expert input. Marxan was run on a 2.5 km2 square planning units grid. The group forced both existing and temporary status protected areas into the solution, so that they immediately contributed to species targets; regions outside of these areas selected by MARXAN would be considered as new priorities for protection. The Marxan “Best” solution was selected for individual runs of the analysis on each taxonomic group (mammals, birds, reptiles, amphibians, fish). These five results were intersected to produce a priority layer for all groups. To reduce areas in direct conflict with mining interests, the group used the “Best” Marxan results for individual taxonomic groups (mammals, birds, etc.) to identify cells in which only one taxonomic group overlapped with the mining grid cell. Such priority cells were removed from the prioritization result. If more than one group overlapped, then it was kept in the result. Zonation prioritization of modeled ant and butterfly distributions The distributions of 194 butterfly and 73 ant species with more than 6 independent sampling localities were modeled using Maximum Entropy (MAXENT) software for species distribution modeling (Phillips et al. 2006). Georeferenced species occurrence data from museum collections and recent field surveys were used, in conjunction with climate (www.worldclim.org) and forest cover (Harper et al. 2007) variables to model potentially suitable habitat for each species under current climate conditions and forest cover. The modeling methods were the same as those for Kremen et al. 2008 except that the species data and environmental data were further refined and cleaned for the 2008 analysis. The resulting species distribution models were then used as inputs for the Zonation conservation planning algorithm (http://www.helsinki.fi/bioscience/consplan/software/Zonation/index.html). Since very few butterflies and no ants have been red listed, and very little was known about the relative vulnerabilities of the species all species were given equal weights. Although there was an option to force the inclusion of specific areas, such as existing protected areas (using a mask or cost surface) in the result this option was not used and Zonation was allowed to freely prioritize across the landscape. The Zonation algorithm was run once for ants and once for butterflies and, the highest priority 5% of the landscape was selected for inclusion in the composite map. 20 The above results were combined according to the following three steps: 1) The two Zonation results were thresholded at the top 5% for Madagascar and then added together. This grid was then added to the Marxan “Best” result for vertebrates. 2) Next, the group added the MBG areas to the solution (so all are included) and made some fine boundary adjustments where the grids from Marxan showed a rougher edge than the MBG polygons. 3) Where the above result overlapped with KBAs, the KBA boundaries were used to refine grid boundaries produced by Marxan (and Zonation?). Note, however, that not all KBAs are included in the final prioritization map. 2.3.3 Results Some differences between this map and the 2004 result are immediately obvious (Figure 3). For one, the area in blue (“aire protégée actuelle et zone de protection temporaire”: 37931.15 km2) has expanded significantly, and now includes large areas denoted as temporary protected areas (“zone de protection temporaire”: 20356.29 km2), as well as existing protected areas “aire protégée actuelle”. These areas are highly likely to be granted full protected status under SAPM, and have been carried forward in subsequent analyses as such. As before, the process of legal gazetting and physical delimitation of these is the responsibility of the “promoteurs” or the co-managers of each area. In addition, large areas in green, potential zones for sustainable forestry (“zones potentiel de gestion forestière durable”: 24,626.25 km2) are also evident. These areas, though not recommended to be strictly protected under SAPM, are nonetheless significant as potential sustainable managed forest areas. Finally, the areas in red, potential protected areas (“sites potentiel pour les aires protégées”: 41,553.62 km2) are much reduced between 2004 and 2006. This is largely because they are now devoted either to blue or green areas, as noted above. The selection of these green areas was done by negotiation within the Ministry in charge of Environment, the DVRN (Promotion of Natural Resources Department- for forestry areas), and the DSAP (Madagascar Protected Areas System Department), although the boundaries were then drawn by priority setting group, represented by REBIOMA (WCS) and Jariala (USAID). Overall it should be noted that the red “potential” areas have come largely from the analysis of priority areas described in this section, whereas it is largely the “promoteurs” who have selected new blue areas to move forward as new parks. Generally, but not always, these have been drawn from within the set of red areas. 2.3.3.1 Arrêté Mines-Forêt 2006 The result of the above analysis and selection of priority areas also served as the basis for a new interministerial “arrêté” specifying allowable land uses in the mapped areas. No new forest or mining permits can be issued in the “blue” (new and existing: 3.79 million ha), “green” (KoloAla: 2.47 million ha), and “red” (site potentiel pour les nouvelle aires protégées”: 3.99 million ha) areas. These restrictions remained in effect for 24 months, until October, 2008. 21 2.3.3.2 Gap analysis 2006 As a first step in any conservation planning exercise, it is useful to ask how well the current set of protected areas is doing in terms of biodiversity conservation. Results of a gap analysis performed prior to the Convention on Biological Diversity in 2006 showed that the conservation value of the full set of existing and proposed protected areas (blue areas in Figure 3), while significant and improving, still left a number of threatened vertebrate species unprotected or without adequate protection: 14 of the close to 200 terrestrial vertebrate species analyzed were not included at all in existing or proposed protected areas – this number climbs over 40 when freshwater fish were included. Examples of the terrestrial vertebrates not included at all in the 2006 set of parks include two birds: Subdesert mesite (Monias benschi) and Long-tailed ground roller (Uratelornis chimaera), both IUCN vulnerable species. 22 Figure 3 - Map for the "Arrêté Mines-Forêt" 2006 23 3 Multi-taxonomic analysis 2008 For details on this analysis, readers are referred to the original Kremen et al. (2008) publication for additional details. In addition, we have provided a summary report (“SciencePaperForDCA_JULY08.pdf”) which is included on the Digital Conservation Atlas CD. 4 Priority Synthesis 2008 4.1 Introduction Following the 2004 and 2006 priority-setting analyses, several issues came forward concurrently to motivate the group to perform a new priority-setting analysis for 2008. The first, most pressing issue was the expiration of the 2006 Arrêté Mines-Forêt, in October, 2008. Second was the publication of the multi-taxonomic analysis (Kremen et al. 2008), and the availability of 800 species distributions not previously at the group’s disposal. Finally, 2008 saw the addition of what are likely to be the last major additions to the Madagascar protected area system. These factors together presented the group with an opportunity to conduct a major final priority-setting analysis, using vast new data sources, in order to look for gaps in what is likely to be the final SAPM areas, while simultaneously negotiating mining trade-offs for a renewal of the two-year “arrêté”. In following sections, we provide details of what was done. 4.2 Data Input data were of four main types: species and habitat distributions, parks data, conservation priorities and mining areas (Figure 4 - Inputs into the 2008 Multi-taxonomic analysis). 4.2.1 Species and habitat distribution data Species data consisted of presence/absence data from three main sources. 1) Refined expert derived extent of occurrence polygons for threatened vertebrates. These data are the same as the vertebrate distributions used in 2006, with a handful of alterations to species names and distributions. Two hundred and fifty species were included. 2) Missouri Botanical Garden threatened plants. Here, MBG produced maps from locality data for 264 threatened plant species. The software program “DOMAIN” was used to model species distributions, and these were then thresholded to produce presence/absence maps. 3) Modeled species distributions. Species models from the Zonation multi-taxonomic analysis (Kremen et al. 2008) were also included for Ants, butterflies, plants from the tribe Coleaee, the family palms, and additional plants from the Missouri Botanical Garden APAPC dataset. While the Kremen et al. 2008 analysis utilized the continuous range of model values it was necessary to convert the models into binary (presence/absence) distributions, so were thresholded at the 40% probability level. Kew Botanical Gardens provided data on major habitat types. In 2007, Kew released a map of vegetation/habitat types across Madagascar. The Prioritization Group selected the 10 classes that were more or less natural vegetation types, and included them in the analysis. 4.2.2 SAPM parks data Parks data were included for the latest SAPM park boundaries as of October, 2008, including several new parks added since 2006. Parks of four types were considered: APs (Protected Areas or "Aires 24 Protégées"), NAPs (New Protected Areas, or “Nouvelle Aires Protégées”), ZPTs (Temporary Protection Zones, or “Zones de Protection Temporaire”) and SPs (Potential Sites, or “Sites Potentielles”). 4.2.3 Conservation priority data The third main data types were conservation priorities. These data included the APAPCs and portions of the KBAs (both described in detail in previous sections). Note that the full KBA polygons were not used in the 2008 this analysis because KBAs themselves consist of some combination of IBAs (also known as Zicoma sites), AZE sites, APAPCs, RAMSAR areas, park boundaries and indeterminate threatened species distributions. Because of poorly documented overlap between the inputs to the KBA’s we preferred to include only IBAs, AZEs, and RAMSAR sites to represent the KBAs. Unfortunately, RAMSAR polygons (as noted above) and AZE sites could not be found prior to conducting the analysis, so these were not included. 4.2.4 Mining areas Mining data were provided by the Ministry of Mines and consisted of a shapefile of mining concession boundaries. The Prioritization Group considered only areas with the following classification in the analysis: • • • • Exploitation License (“Permis d’Exploitation”) Reserved License for Small Mining developers ("Permis Réservés aux petits Exploitants”) Research License (“Permis de Recherche”) Exclusive Authorization to Reserve Perimeter (“Autorisations Exclusives de Réservation de Périmètre”) In order to assess biodiversity trade-offs with mining areas, these mining areas were excluded from some parts of the priority area selection process, as detailed below. 25 Figure 4 - Inputs into the 2008 Multi-taxonomic analysis 26 4.3 Methods Two main kinds of analysis were conducted to serve two related purposes: 1) the renewal and negotiation of the inter-ministerial “arrêté”, and 2) to review the existing proposed SAPM and suggest new areas for protection. The first type of the analyses was gap/representation analysis of species. Species and habitat distributions (described above) were compared to the latest SAPM maps from October, 2008 in order to assess gaps in representation. The second was a series of Marxan analyses using different species groups under different scenarios of protection/priority (Figure 4, Table 2). The overall aim of this “super-analysis” was to see if any distinct areas consistently mapped as priorities outside of currently accepted SAPM and priority areas. 27 Scenario E. APNAP-ZPTSP, APAPCIBA-KBA F. APNAP-ZPT (MINES) G. AP-NAPZPT, APAPCIBA-KBA (MINES) H. AP-NAPZPT-SP, APAPC-IBAKBA (MINES) A. FREE CHOICE B. APNAPZPT C. APNAP-ZPTSP D. APNAP-ZPT, APAPCIBA-KBA 1. Threatened terrestrial vertebrates 1A 1B 1C 1D 1E 1F 1G 1H 2. Threatened terrestrial vertebrates and freshwater fish 2A 2B 2C 2D 2E 2F 2G 2H 3. Vertebrates, threatened plants, Kew habitat types 3A 3B 3C 3D 3E 3F 3G 3H 4. Vertebrates, threatened plants, Kew habitat types, Zonation species 4A 4B 4C 4D 4E 4F 4G 4H Species Group Table 2 - Scenarios developed for Marxan. AP = protected areas, NAP = new protected areas, ZPT = temporary protected zones, SP = potential sites, APAPC = MBG priority plant areas, IBA = important bird areas, KBA = CI key biodiversity areas. As shown in Table 2, there were four species groups. Groups were organized additively, so that the largest group (1140 species) contains all of the smaller groups. The first group consists of threatened terrestrial vertebrates. The second group is the same, but also includes threatened freshwater fish. The third group adds MBG plants and Kew habitats to the threatened vertebrates. The fourth and final group includes Zonation plant and invertebrate species plus all species from the previous groups. See additional details in “Data”, above. Each of these species groups was subjected to Marxan analysis to map areas to meet quantitative representation targets for each species. The Marxan analyses were constrained in six different scenarios, however, to test the adequacy of existing park and priority area configurations at meeting quantitative representation targets for species. There are 32 runs of the analysis in total (8 scenarios x 4 species groups). Marxan parameters were relatively consistent across species groups and scenarios. Key details are as follows. All species were mapped to a consistent, square 1km2 grid (presence/absence) that also served as the planning units. Cost per planning unit was calculated as the inverse of total forest found in each unit, such that cost was low in planning units with a lot of forest, and high otherwise. This was not weighted in any way: cost is simply the inverse of the total amount of forest per planning unit, scaled from 0 to 1. A boundary-length penalty of .0001 was used to attempt to increase the “compactness” of the solutions. Each scenario was run 10 times, with 1 billion iterations. In order to run Marxan with such a large number of species and habitats (1150), we first had to exclude species that already had their targets met under existing levels of protection. Species targets were set using a logarithmic curve that gives high targets to species with low range size and vice-versa (Rodrigues et al. 2004). The parameters for this were: Threshold for 100% target: 200 km2, threshold for 10% target: 10,000 km2. Maximum target size for any one species: 30,000 km2. The MBG threatened plants had slightly different target parameters, as follows: Threshold for 100% target: 250 km2, threshold for 10% target: 2,500 km2. 29 4.4 Results 4.4.1 Marxan results After a visual and qualitative evaluation of the 32 available results from the above analysis, members of the priority setting group decided that two of the scenarios warranted additional analysis and attention in the “arrêté”. These were: 4A (free choice) and 4D. The interest in scenarios from species group 4 (all species) was that it was the most comprehensive. From there, the group felt that both scenario A and D provided useful information: A (free choice) because it shows what areas are priorities regardless of existing protected or priority status, and D, because it shows what areas are priorities outside of existing protected areas, likely future protected areas, and existing well-established priority areas (APAPC, KBA, IBA). After careful consideration of these two results, in the end, the group selected scenario 4D for inclusion in the “arrêté” (Figure 5), as described in additional detail below. 4.4.2 Arrêté Mines-Forêt 2008 The Interministériel Arrêté of 2008 (Figure 5) was initially based on the SAPM 2008 priority maps. All the “blue” (existing protected) areas from 2006 were maintained, and supplemented with new “blue” areas with “promoteurs”. Existing 2006 “red” (conservation priority) areas were removed for reanalysis, as described below. The result was classified into three types as described below: • Blue areas: Existing terrestrial protected areas, protected areas with temporary protected status and new protected areas with NGO or civic support (“promoters”) including financing. Closed to new mining permits. Hectares = 6.4 million (exceeding the six million ha target), but includes overlaps with mining exploration or activity (14 percent in mining5). • Red areas: areas identified as most important additional protected areas by the comprehensive Marxan analysis (see above), that also overlapped with selected sites from KBAs, APAPC, priority KoloAla (sustainable forestry management), and promoters (no financing) on the ground. Closed to new mining permits. If some blue areas remain or become active mining sites, then selected red areas could be used as trade-offs for these sites. Similarly, some of the blue areas may be reduced during boundary delineation, triggering selection of areas from the red zone. Hectares = 1.8 million (13 percent in mining). • Green areas: Potential sites for protection identified by the comprehensive Marxan analysis that did not overlap with other priority schemes plus potential KoloAla sites. Subject to special conditions prior to permitting for mining (e.g. environmental impact assessment and other measures). These special conditions can take into account, for example, known sites for rare and endemic species. Hectares = 4.7 million (10 percent in mining). 5 Mining here includes both research, exploration and exploitation licenses. Some licenses may be inactive. 30 Figure 5 - Maps for the "Arrêté Mines-Forêt" 2008 Although much work remains to translate this result into a final set of terrestrial protected areas on the ground, this result effectively protects (albeit temporarily in some cases) virtually all of Madagascar’s large remaining forest blocks until final determinations and refinements can be made according to the Durban Vision. 4.4.3 2008 Gap analysis of SAPM areas As in 2006, the group conducted extensive gap analysis of the new parks and priority areas to see how well they covered species of interest. As expected, overall, the results are an improvement over 2006, if for nothing else simply because the 2008 areas cover more territory. Nevertheless, there are still several species that do not yet receive any protection in the 2008 SAPM map (4 Threatened Amphibians and 25 Freshwater Fish), and many others that are likely “under-represented”, having less than 5% of their range protected. More than anything, this is due to the fact that the current set of protected areas has not been designed from the top down to meet minimum species targets, but rather has developed from the bottom up by “promoteurs” or co-managers who have nominated particular areas for inclusion. There are of course significant social advantages for a bottom up approach to conservation that may lead to greater sustainability. 32 Figure 6 - Final map of SAPM parks and protected areas, 2008/2009 33 5 Discussion 5.1 Methodological comparisons Between 2003 and 2008 the priority-setting group employed an evolutionary, adaptive approach to setting and analyzing conservation priorities. As documented here, methods have ranged from straightforward GIS overlay to relatively sophisticated optimization analyses using numeric targets, quantitative models of species distributions, the latest priority-setting methods and consideration of the conservation requirements of literally thousands of species at high resolution. It is important to clearly distinguish between two different types of inputs into the various stages of the priority setting process, described above (2004, 2006 and 2008). The first are priority-setting products, that is to say, products of various priority-setting workshops and analyses. These have been produced by a wide range of methods, by various parties, for a wide variety of reasons, and include disparate data sources, both quantitative and expert-derived. Examples of priority setting products are many, and include PRISMA, PlanGRAP, Zicoma sites, AZEs, KBAs (see previous sections). In most cases, these products are not directly comparable with each other, as each has been produced with its own set of procedures and assumptions, often using different data sets and methods to map areas as conservation priorities. In addition, most of these products are not inherently or directly quantitative – generally speaking, the areas selected as priorities were not chosen to meet a particular target. This makes interpriority comparison difficult. To the extent possible, in previous sections of this paper we have tried to document how each of these products was produced. In some cases, readers may have to contact the originating institutions for full details. The second main type of input discussed here are the results of two quantitative priority-setting methods: Marxan and Zonation. These two approaches have been employed at several key steps in the process (especially 2006 and 2008) to understand and quantify how well existing SAPM areas meet numeric species targets, and to identify and map new conservation areas that would meet remaining targets most efficiently. In the end, for pragmatic and political reasons, these two main types of priority setting products have been used in conjunction with a bottom-up driven area selection process in order to map and understand relative conservation priority across Madagascar. There are clear benefits to this consensusbuilding approach, which from many perspectives has been quite successful in Madagascar. From a pure conservation planning point of view, however, this is not the ideal or recommended way to establish conservation priorities, for two reasons. First, some targets may not be met at all, and second, some redundancy may exist in the system (some species or habitats protected at a greater level than their original target) leading to less “efficiency”. 5.2 Implementation Implementation is perhaps the central challenge of conservation planning (Knight et al. 2008; Knight et al. 2006). Although an important aspect of implementation concerns how a given park is physically implemented on the ground (e.g. issues of management, land-use, fencing, enforcement, monitoring), in this section we discuss another, more abstract aspect of implementation: The incorporation of a conservation plan within policy, or in our specific case, the translation of a set of mapped priority areas into a set of implementable parks. 34 An important finding of this exercise has been that the final areas to be included as new parks under the Madagascar Protected Areas System (e.g. the medium blue "temporary status" areas in the second category in Figure 6) have only indirectly been identified through the analysis described in this document. While, in many cases, these areas have been drawn from a larger set of priority areas identified through the priority-setting process, whether or not a specific area has been granted full or temporary status (Figure 1, post 2003) has largely been driven by the presence of a “promoteur” willing to commit to long-term co-management of the area. For many reasons, this is a necessary and pragmatic approach: these areas are vast and funds are short; given the huge commitment involved in establishing and managing a large protected area network, it is critical to work with the support of co-managers. The “promoteurs” are dedicated partners who know these areas well, and have a presence on the ground as well as access to donors who can carry these projects forward. 35 6 Recommendations It is our sincere hope that by documenting and making available the wealth of conservation data and priority-setting products now available in Madagascar we have helped to make this information more readily available to future decision-making processes. In this section we provide several specific recommendations for how these data may potentially be used to support ongoing terrestrial planning at both the national and regional scale, as well as marine planning activities that are just getting underway in 2008. We also highlight several new types of analyses that can also support these activities. • • • • New SAPM protected areas established under the Durban Vision will be subject to many types of management. This includes strict protection, but also may involve areas of resource extraction and other “mixed-use areas” (i.e. IUCN categories I-VI). To date, however, priority areas and new parks have generally been mapped at the national level, at a relatively coarse scale. Zonation and Marxan map products can be useful in determining the IUCN categories to assign to different protected areas. Areas that show a high overlap of Marxan “Best” solutions, for example, would generally be areas of high conservation value, and thus appropriate for stricter protection categories. The Zonation solution actually ranks all areas in terms of conservation value, and is therefore even easier to interpret. Higher ranked areas within a given protected area are most appropriate for strict protection. Areas that are lower ranked, or have less overlap with Marxan “Best” solutions would be more appropriate for extractive use or other types of less strict management. The examples above provide a quick overview of how planners and decision-makers could use the existing national-level Marxan and Zonation products to inform conservation zoning within regions. But one could also use either of these programs to map and measure new conservation priorities within a region or even a single protected area. The approach would be similar to that employed at the national level. The key difference would likely be in the choice of targets, as well as the choice and scale of distribution and cost data. A new version of Marxan known as “Marxan with Zones” has recently been released. Unlike the original versions of Marxan that consider only one measure of cost and generally a binary view of “protection/no protection”, Marxan with Zones specifically supports multiple costs and meeting targets under different management types. This could be particularly useful for “zoning” types of analysis as described in the previous example. While the Atlas currently has a terrestrial focus, many of the methods can be applied to the marine realm as well. In fact, the program Marxan was originally designed to support Marine planning, and has been widely applied in that context. Likewise, the Zonation program has potential use for marine planning and has recently been used in this context in New Zealand (Leathwick et al. 2008). Efforts are currently underway to use the tools and techniques for marine conservation at several scales in Madagascar’s territorial waters and in the wider West Indian Ocean region through 2009 and into 2010. 36 7 Acknowledgements The authors would like to acknowledge input and assistance from many individuals and institutions that made this work possible, including all of the institutions named below. We also thank individual researchers and taxonomic specialists who have generously contributed knowledge, data and time in workshops and related activities throughout the prioritization and validation process. We would also like to acknowledge organizations listed below many of whom have donated significant staff time to the Durban Vision process done during all stages of prioritization. Finally, we thank the MacArthur Foundation for their sole support of the REBIOMA project during the period 2004-2009. 8 “Durban Vision Group” participating organizations BirdLife International Madagascar (BIMP/ASITY Madagascar) California Academy of Sciences (CAS) Conservation International (CI) Durrell Wildlife Conservation Trust (Durrell) Kew Botanical Gardens (Kew) Madagascar National Parks (ex-ANGAP) Madagasikara Voakajy (MAVOA) Ministère chargé de l'Environnement (MEF) Missouri Botanical Garden (MBG) Office National pour l'Environnement (ONE), Réseau de la Biodiversité de Madagascar (REBIOMA) Service d’Appui à la Gestion de l’Environnement (SAGE), The Peregrine Fund (TPF) University of Antananarivo: - Department of Animal Biology (DBA), - Department of Ecology and Plant Biology (DBEV), - Department of Agronomy, Department of Forestry (ESSA-Forêt) US Agency for International Development (USAID) Wildlife Conservation Society (WCS) World Wildlife Fund (WWF) 9 Authors and contributors Thomas F. 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