Outline Report Framework

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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. Allnutt, UC Berkeley/Rebioma, USA
Alison Cameron, Max Planck Society, Germany
Claire Kremen, UC Berkeley/Rebioma, USA
Rija Rajaonson, Wildlife Conservation Society/Rebioma, Madagascar
Andry Jean Marc Rakotomanjaka/Rebioma, Madagascar
Andriamandimbisoa Razafimpahanana, Wildlife Conservation Society/Rebioma, Madagascar
37
10
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