Identification of Responsible Cultivation Areas In West Kalimantan ...

Identification of Responsible Cultivation
Areas In West Kalimantan Indonesia
Phase II: Desk-based analysis
Authors: Hans Harmen Smit, Utrecht University, Dept. STS, Arif Budiman, WWF Indonesia
Coordinators: Fitrian Ardiansyah, WWF Indonesia; Laszlo Mathe, WWF International
Reviewers: Bart Dehue, Ecofys; Sebastian Meyer, Ecofys; Rodney Taylor, WWF International

Acknowledgment
The development of this report and the underlying analysis would not have been possible without the expertise and
input provided by the project partners and the support from sponsors. The following institutions contributed to this
report: Ecofys, WWF International and Conservation International. The work on this pilot report was made
possible through sponsorship by the Packard Foundation.
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Introduction
Background
Potential Responsible Cultivation Areas (RCA’s) were preselected in phase I for West
Kalimantan based on: the presence of conservation areas, carbon stocks, land use, legal status
and agricultural suitability for oil palm cultivation. Existing plantation concessions larger than
15.000 ha, in which at least 50% of the land was found suitable are considered potential
RCA’s. From this assessment it was found that 30 concessions (see figure 0.1) are potentially
suitable as RCA. The preselected concessions are further analyzed on compliance with the
RCA criteria in this report.
Figure 0.1: Concessions potentially suitable as RCA as identified in phase I
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Content
Introduction 1
Goal & process phase II 5
P1: Energy crop plantations maintain or increase High Conservation Values 7
P2: Establishment of energy crop plantations does not lead to significant reductions
in carbon stocks 31
P3: Establishment of energy crop plantations respects formal and customary land
rights 33
P4: Establishment of energy crop plantations does not cause unwanted displacement
effects 35
P5: The identified areas is agriculturally suitable for the target energy crop 36
Recommendation Phase II: Identified priority areas 37
References 39
Appendix 40
List of figures
Figure 0.1: Concessions potentially suitable as RCA as identified in phase I.................................................................................................................3
Figure 1.1.1: (International) Protection and Conservation Areas that are close or overlap with the 30 concessions...........................................9
Figure 1.1.2: Map representing orangutan distribution in West Kalimantan (source: UNEP, 2004).................................................................. 12
Figure 1.1.4: Map of important habitat for migration species, Important Bird Areas, and Endemic Bird Areas (source: Ministry of forestry,
2002; Birdlife International, 1998 and 2003) .................................................................................................................................................................... 13
Figure 1.2.1: Map of potential corridors between orangutan habitats.......................................................................................................................... 18
Table 1.3: The status of peat inside concessions. ............................................................................................................................................................... 22
Table 1.4.1. Concessions that have 100 m wide forest along the river and the total required buffer zone........................................................... 24
Table 1.4.2: Erosion classification based on USLE Methodology (source: HCV Consortium, 2008)................................................................ 25
Figure 1.4.2: Map indicating soil erosion risk in West Kalimantan Province............................................................................................................. 26
Table 1.4.3: Occurred fires in the 30 concessions in West Kalimantan during 2000 - 2007 .................................................................................. 28
Table 2.1: Above ground carbon Stock estimation in the 30 concessions ................................................................................................................... 32
Figure 3.1: Map of Land use (function) in West Kalimantan Province....................................................................................................................... 34
Table 6.1: Overview identified conflicts/risk for conflict with RCA principles ........................................................................................................ 37
Figure 6.1: Location concession 30 identified for further analysis in phase II ............................................................................................................ 38
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Goal & process phase II
Goal
The goal of phase II is to:
1. Refine the findings of phase I (pre-selected areas).
2. Identify remaining knowledge gaps that must be filled in through the field activities.
Process
Ideally the analysis in phase II should be based on regional information sources, however in
this pilot it was found that information sources with such a level of detail are not available (a
spatial resolution with a scale of 1:10,000 or higher would be ideal for application in
cultivated areas, and minimum scale of 1:50,000 is recommended. However, most of national
scale maps in Indonesia were presented in 1:100,000 and 1:250,000, see also Muliastra,
2009). Due to this limitation, no region specific recommendations can be made, and the phase
II analysis was done on a landscape level for all 30 concessions. As a result, phase II is
similar to phase I in the sense that both are done on the landscape level, and some data
sources used in phase I are also included in phase II. In phase I, priority areas were selected
based on the selection criterion that at least 50% of the concession is suitable based on this
rapid assessment. In phase II, a number of additional data sources are added to make a more
detailed analysis for each selected concession. In phase II the areas unsuitable as RCA within
the concessions are identified, and specific recommendations are made on the field data
needed to improve the limitations of the desk-based assessment.
For the selected areas, the following tasks are carried out:
• P1: Establishment of energy crop plantations maintain or increases High
Conservation Values: Desk-based HCV-Assessment of the preselected areas
according to step 1, 2 and 3 of the practical guidelines for HCV assessment as
proposed by HCV Consortium (2008). The desk-based assessment in the context of
P1 is especially relevant for the identification of HCV´s of type 1,2,3 and 4 (see
global HCV toolkit of Proforest (Jennings, 2003)).
• P2: Establishment of energy crop plantations does not lead to significant
reductions in carbon stocks: Verification and refinement of information on land
cover and presence of peat areas and wetlands through regional studies.
• P3: Establishment of energy crop plantations respects formal and customary
land rights: Special focus will be given the possibility of conflicting information
about land-use planning and actual land use. The formal ownership of the concessions
is verified based on governmental databases, non scientific literature (newspapers,
internet), and interviews.
• P4: Establishment of energy crop plantations does not cause unwanted
displacement effects: Verification and refinement of information on current land use
through regional experts.
• P5: The identified area is agriculturally suitable for the target energy crop.
Refinement of the desk-based information from phase I through fieldwork (e.g.
collection of more detailed soil and slope information) and consultation of experts.
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Based on the more detailed information collected in this phase, changes may be made to the
pre-selected areas that will actually be analyzed in depth in the field work in phase III. During
phase II it will also become clear what information gaps remain after the desk-based
assessment. This forms the basis for the field work to be performed in phase III.
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P1: Energy crop plantations maintain or increase High Conservation
Values
This section describes the results of the desk-based HCV assessment of the preselected areas.
For the HCV assessment, the HCV guidance documents developed by the HCV consortium
(2008) were used.
For each High Conservation Value it is described what the HCV entails, the information that
has been gathered on this HCV (including its sources), and the resulting findings in terms of
the (potential) presence of the HCV in the preselected area. After this, it is determined for
each HCV what information will need to be gathered or verified through field work in order
to conclude on the presence of the HCV.
HCV 1.1; Areas that Contain or Provide Biodiversity Support Function to
Protection or Conservation Areas
Protected areas or conservation areas are gazetted in order to maintain ecological functions
specifically, or preserve other characteristics (including biodiversity, water resource
protection), endangered species and its viable populations or a combination of them, see also
HCV Consortium, 2008). All protected areas and conservation areas were created with the
aim of protecting culture, ecological functions (e.g., water provision), biodiversity or a
combination of these, are considered HCV 1.1. Apart from the protection areas established by
the Government, areas that have important ecological functions as identified by esteemed
societal organizations such as IUCN, are also considered here.
The assessment should identify the presence of any gazetted protected areas and conservation
areas in West Kalimantan that may be impacted by potential operations in the preselected
areas.
Data Input
To assess the presence/impact on HCV 1.1 areas proximate to the concessions, the following
data on conservation and protected areas were used:
• Indonesian Conservation Areas (source: Ministry of Forestry, 2007). The data used is
the official data for Indonesia conservation areas produced by Central Government of
Indonesia. In addition to the boundaries of the protection areas indicated in this
dataset, an additional buffer of 1 km was considered (government regulations require
a 500m buffer zone, however it was found that the accuracy of the maps is biased,
therefore twice the buffer as recommended is considered, to avoid a faulty
interpretation in the field).
• Protected Forest and Forest status (source: Spatial Planning unit Provincial
Government West Kalimantan). This dataset provides the official boundaries for
Protected Areas/forests (in these areas important environmental functions are
identified, e.g. water provision and erosion protection).
• IUCN conservation areas categories I – IV (source: IUCN – UNEP). This dataset is
used to identify additional conservation areas. The IUCN conservation areas are used
because these are internationally recognized (endorsed by the Indonesian
Government: more detailed information on the definition of each category can be
found on www.unep-wcmc.org)..
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• RAMSAR Areas (source: The Ramsar Convention on Wetlands of International
Importance). This dataset is used to identify wetland areas internationally recognized
as conservation areas (endorsed by the Indonesian Government: detailed information
can be found on www.ramsar.org).
The 30 preselected concessions are overlaid with the boundaries of the identified conservation
areas described above. By applying GIS analysis, every concession that contains, or adjacent
to these areas is identified as potential HCV 1.1.
Findings
Based on the desktop analysis, it is concluded that HCV 1.1 is potentially present in 8 of 30
concessions; no 3, 14, 17, 19, 21, 22, 24, and 26. The concessions no 3, no 22, no 24, and no
26 are found to be adjacent to protection forest; one concession is close to Strict Nature
Reserve (no 14), and a portion of 3 concessions overlap with IUCN Category IV, concession
no 22 is adjacent to forest protection and overlap with IUCN Category IV. The results of the
analysis can be found in figure 1.1. and Appendix 1 table 1.1.
Required field data
Based on the desktop analysis, HCV 1.1 was found present in 8 of 30 concessions (partly
based on the precautionary principal). For these 8 concessions, the findings need verification
in the field, since occasionally the border of conservation and protected areas are not precisely
mapped (these are indicative maps), and the location of the area may in practice be located
100 – 200m from the mapped location.
In addition, if the company wants to develop any of these concessions, a comprehensive study
to assess the impact of the activities on the conservation and protected areas should be
conducted. The fact that an HCV is present does not automatically mean it cannot be used for
sustainable feedstock production.
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Figure 1.1.1: (International) Protection and Conservation Areas that are close or overlap with the 30 concessions
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HCV 1.2; Critically Endangered Species
Any species (potentially) present and listed as critically endangered by IUCN, Appendix 1 of
CITES or in Indonesia Government Regulation on Protected Species is a HCV 1.2.
Endangered species have a high risk of becoming extinct and therefore each individual is
considered important for regeneration of the species.
Other species will be a HCV 1.2 when identified as endangered by a consensus of influential
stakeholders. Three categories are described that are relevant to the above criteria are:
1. Species that have significance in the global conservation: presence of such species
would constitute as a High Conservation Value. The species are listed in the category
'Critically Endangered' on the IUCN Red List (http://www.redlist.org), or listed in
Appendix I of CITES. All these species are considered an HCV. In addition species
are considered that are listed in Indonesian regulation to be protected from extinction.
2. Undiscovered or enigmatic endangered species (HCV Consortium, 2008). Thus not
listed in the IUCN Red List.
3. Species threatened with local extinction (HCV Consortium, 2008).
Data Input
In the desktop analysis, identification will be made of critically endangered (sub) species that
occur in/near the 30 concessions and that may be affected by operational activities in the
future. This will be done through a landscape level analysis on distribution of critically
endangered species and their habitats that (potentially) are inside and/or surrounding the
concession (category 1).
To assess the presence of HCV 1.2 on a landscape level the following data-sources are used in
relation to the category 1 as mentioned above (for category 2 and 3 no desktop data is
available):
• IUCN Red list (source: http://www.iucnredlist.org/). In this list, an overview is given
of all the species identified as endangered in line with international consensus. The
species included in this list (the categories ‘Endangered’ and ‘Vulnerable’ are
considered in the analysis
• CITES Appendix (source: www.cites.org). CITES (the Convention on International
Trade in Endangered Species of Wild Fauna and Flora) is an international agreement
between governments on species that need protection from extinction. Its aim is to
ensure that international trade in specimens of wild animals and plants does not
threaten their survival. The species included in ‘Appendix I’ are considered an HCV.
• Appendix of Indonesian regulation (Peraturan Pemerintah, no 7 1999). In this
appendix a list of species is presented that require protection under Indonesian law.
The species included in this list are considered in the analysis.
• Orangutan distribution map (based on regular surveys by WCMC, source www.unepwcmc.org).
This data is used to assess the presence of orangutan habitats proximate to
the concessions.
• Orangutan Population and Habitat Viability Assessment (Singleton, 2004). This map
is a contribution of the IUCN/SSC Conservation Breeding Specialist Group. The
collected data of Borneo Orangutan is used to identify orangutan populations.
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• Important Bird Area (IBA) and Endemic Bird Area (EBA) (source: Birdlife
International, 1998 and 2003). These datasets are used to assess presence of bird
species (listed in IUCN Red List or CITES) in the concessions.
• Distribution of large mammals (Elephant, Banteng, Rhino) (source: Hearth of Borneo
(HOB), Rautner, 2005). This data is used to assess the presence of large mammal
species (listed in IUCN red list or CITES) to the concessions. These species are
considered flagship species.
By applying GIS analysis, the species distribution data listed above is overlaid preselected
concessions. For all the concessions that overlap with distribution of any species listed, it is
assumed that this area is HCV 1.2.
Findings
In West Kalimantan province only a few species as listed above are found to be present.
Based on the existing data it was found that; except for orangutan and important/endemic bird
areas, almost all important species were found inside conservation or protected forest areas.
Therefore most significant species for this analysis, in terms of distribution are orangutan and
several bird species. As a result of the analysis, 2 concessions (no 25 and no 28) were found
to contain/overlap with orangutan populations. In addition one concession (no 24) was
identified to be adjacent to an Endemic Bird Area (Bird life Area 157, Kalimantan). The
results of the HCV 1.2 analysis can be found in figure 1.2 and 1.4, and also in appendix 1
table 1.2.
Required field data
In the landscape level analysis on endangered species in the 30 concessions, the available data
is limited. All the data on the endangered species is mostly from the conservation areas.
However, outside these areas these species are also potentially present. The concessions are
quite far from conservation areas, and thus any species present is unlikely to be mapped. It is
therefore strongly recommended to verify the absence of endangered species in a field survey.
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Figure 1.1.2: Map representing orangutan distribution in West Kalimantan (source: UNEP, 2004)
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Figure 1.1.4: Map of important habitat for migration species, Important Bird Areas, and Endemic Bird Areas
(source: Ministry of forestry, 2002; Birdlife International, 1998 and 2003)
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HCV 1.3; Areas that Contain Habitat for Viable Populations of Endangered, Restricted
Range or Protected Species
HCV 1.3 aims to identify habitats that can sustain viable populations of protected,
endangered, or restricted range species. An area containing sufficient concentrations of such
species, is thus recognized as HCV 1.3. Habitat loss and fragmentation are among the most
common threats facing endangered species. Often habitat loss and fragmentation, combined
with the natural heterogeneity of landscapes, forces species to exist in multiple populations
inhabiting relatively isolated habitat patches (Acakaya, 1996).
The more land that is cleared, the more animal populations will be concentrated in an area too
small to sustain viable population. Whereas this will give a short term impression of a
landscape "teeming with wildlife", the long term prospects will be severely reduced numbers
and population viability and resources are rapidly depleted. The viability of a population can
be assessed based on knowledge of the number of individuals present in an assessment area,
or by drawing inference given the potential carrying capacity of available habitat in the
landscape of which the assessment area forms a part (HCV Consortium, 2008).
The assessment should identify the presence of habitats that could sustain viable populations
of protected, endangered, or restricted range species in, or near the concessions. To identify
the presence of HVC 1.3 the following tasks have been performed:
• Identify where different habitat types intersect within the concession.
• Decide if these give rise to concentrations of threatened endangered or endemic
species.
The species that need to be considered to assess the presence of HCV 1.3 include species that
are categorized as:
• Endangered or Vulnerable in accordance with IUCN’s Red list (see also HCV 1.2)
• Protected species by the Government of Indonesia under the Act No. 7 (see also HCV
1.2)
• CITES Appendix 1 and 2 (see also HCV 1.2)
• Endemic species (e.g. Important Bird Area (IBA), Endemic Bird Area (EBA), see
also HCV 1.2)
Data Input
To identify the presence of these species, the following datasets were used:
• Forest cover 2005 map (source: ministry of forestry). It is assumed that areas with
large intact forest cover contain a natural ecosystem (>20.000 ha) that can support
viable populations of the listed species.
• Distribution of Orangutan (source: WCMC 2004). (see also HCV 1.2)
• Orangutan Population and Habitat Viability Assessment (Singleton et al. (2004), see
also HCV 1.2).
• IBA and EBA (Birdlife International, 1998 and 2003). (see also HCV 1.2).
• Distribution of large Mammals ; Elephant, Banteng, Rhino (source: Rautner et al
(2005), see also HCV 1.2).
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To verify the presence of HCV 1.3, both the quality and the quantity of the species listed
above are assessed.
Findings
If there is no forest or natural ecosystem (an area where ecological processes
remain unperturbed, see also (HCV Consortium, 2008)) then HCV 1.3 is unlikely to be
present, since these conditions are assumed to be necessary to be able to sustain viable
populations. Based on analysis of the literature and spatial data, it is found that no habitat is
likely to be present inside the 30 concessions that can support a viable population of
endangered, restricted or protected species.
Required field data
For the desk-based analysis it can be concluded that HCV 1.3 is absent for all pre-selected
concessions. However, considering the uncertainties of the land cover data, and the
limitations of the distribution data (see also HCV 1.2) field verification is recommended on
the presence of natural ecosystems and endangered species.
HCV 1.4 Areas that Contain Habitat of Temporary Use by Species or
Congregations of Species
HCV 1.4 identifies key habitats temporarily used by a collection of individuals or species in a
landscape. In addition to key habitats, areas that harbor concentrations of migratory species or
important migration routes are considered here. Key habitats can also be a place of refuge
(refugium) for a species during the long dry season for drinking, floods or fires. All the
habitats identified as HCV 1.4 have the similar characteristic that if the habitat is lost then the
impact on the population of some particular species will be very significant, even though the
area itself might be relatively small. Examples of such temporary key habitats are:
• Places to breed or nest, e.g. caves or wetland habitats used by several bird, bat and
reptile species.
• Places along main migration routes (bird species transit in West Kalimantan in
migrating from the pole to areas on the other side of the equator)
• Local wildlife movement paths (corridors) where individuals can move between
different ecosystems in the search for food with seasonal availability (HCV
Consortium, 2008)
Data input
Areas that are considered to have an important function as a temporary habitat are: extensive
mangroves, freshwater swamp forest, peat swamp forest, riparian forest. To identify these
areas, the following data-sources were used:
• Land cover West Kalimantan, 2006 (WWF, 2009). This data is used to identify areas
with: mangroves, freshwater swamp forest and riparian forest
• IBA and EBA (source: Birdlife International, 1998 and 2003). This data is used to
identify important migration areas for bird species.
• West Kalimantan Peat Land Areas (source: Wetland International, 2002). This data is
used to identify peat swamp forest.
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Findings
Based on existing literature, the following important habitats were identified in West
Kalimantan: Gunung Palung NP, Betung Kerihun NP, Danau Sentarum NP, Bukit Baka –
Bukit Raya NP, Kendawang Wildlife Sanctuary, Gunung Nyiut Perinsen, Gunung Poteng,
littoral areas of Paloh swamp, and littoral areas of Kapuas swamp.
In the desktop analysis on HCV 1.4, using 2005 land cover of West Kalimantan data and the
literature data, found that there was no temporary habitat used by the species or congregations
of species within the concessions (HCV Consortium, 2008). In the desk-based analysis HCV
1.4 was found not present.
Required field data
Based on the desktop study, HCV 1.4 is considered absent in all concessions. The accuracy of
the data on migratory species is considered limited, and verification on the temporal presence
of such species is thus recommended by experts for the fieldwork (pers. comm. Yana
Suryadinata (TNC)).
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HCV 2.1 Large Natural Landscapes with Capacity to Maintain Natural
Ecological Processes and Dynamics
HCV 2.1 aims to protect the ecological functions within a natural landscape in which natural
ecosystem processes have the potential for a continued long-term future. The main objective
is to identify and protect core areas of the landscape that ensure natural ecological processes
can take place without negative influence of fragmentation and edge effects.
The definition of a landscape with a core area is; a forest block (or other natural landscape
mosaic) with an internal core larger than 20,000 ha surrounded by a natural vegetation buffer
of at least 3 km from the forest edge (HCV Consortium, 2008). Every concession that is
within, or is part of a landscape with such a core area is potentially a HCV 2.1. To verify this
both the condition and the size of the ecosystem the concessions has to be assessed. In
addition, the potential impact of the conversion on the large natural landscapes under HCV
2.1 has to be included in the analysis.
Data Input
To verify the proximity of core areas to the concessions, and the impact of potential
conversion of any MU on any large forest landscape, the following datasets were used:
• Land system classification for Indonesia, (source: RePPProT 1989). This data is used
to assess the type of landscape present based on: parent material, hydro climate,
landform, soil and vegetation
• Land cover West Kalimantan, 2006 (WWF, 2009). This dataset was used to identify
the presence of forest blocks (larger than 20.000 ha). This dataset is used in addition
to RePPProT, since up to date land cover data is required for a reliable analysis.
Findings
Based on the analysis done using RePPProT and the land cover data, it was found that HCV
2.1 is potentially present in one concession (nr. 25, see also figure 2.1). Although the size of
this concession is less than 20,000 ha (requirement to qualify as HCV 2.1), it forms a part of a
larger natural ecosystem in which the concession covers a potential corridor for orangutan.
Required field data
Because the land cover and land system data used in this analysis is not of sufficient quality,
it is possible that other concessions also contain HCV 2.1. Considering the precautionary
principle, it is recommended that the current land cover is verified in the field.
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Figure 1.2.1: Map of potential corridors between orangutan habitats
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HCV 2.2 Areas that Contain Two or More Contiguous Ecosystems
Areas supporting a diversity of ecosystems, in general support great numbers of species and
have high capacity to sustain them in the long term. The maintenance of ecosystem types,
especially those co-occurring within a single landscape, is a major goal of local conservation,
it guarantees the movement of species among ecosystems and the flow of materials and
energy in the face of environmental changes (like fluctuating food availability, extreme
weather and changing climate). HCV 2.2 aims to identify landscapes that contain multiple
ecosystem types, to protect their core areas and to maintain connectivity among these types
(HCV Consortium, 2008).
Data Input
Transition areas between ecosystems (ecotone area’s) often contain relatively high
biodiversity levels, especially the transition zone between swamp and non-swamp, or heath
forest and non-heath forest. (HCV Consortium, 2008). In mountainous areas these zones can
be distributed along different elevation gradients, for example those including transitions
between lowland forest to sub-montane and montane forest. Therefore, to be able to assess the
status of the ecotone regions, the boundaries between the relevant ecosystems proximate to
the concessions have to be identified. Data on land systems will be used to identify ecosystem
transition zones (ecotone regions), in addition land cover data will be used to verify whether
these areas are still intact. To verify the proximity to or the presence in the concessions of any
important ecotone areas, the following dataset was used:
• Land system map, (source: RePPProT 1989). This datasets were used to identify the
different ecosystems in the landscape as well as the ecotone regions.
• Forest cover 2006 map (source: WWF 2009). This dataset is use in addition to
RePPProT to assess the current status of the ecosystems present. For example when
the vegetation cover is lost, the ecotone areas no longer exist.
• West Kalimantan Peat land Areas (Wetlands International, 2002). This dataset was
used to identify the transition areas from peat to non-peat.
Findings
From the analysis it was found that none of the concessions contains areas considered as
ecotone, or an area where two intact ecosystems overlap. Almost all the land inside the
concession has lost forest cover. Even if areas with important ecosystems where present here
in the past, it can be assumed that these are lost.
Required field data
As mentioned previously, the findings from the land cover data have to be verified in the
field, since the accuracy of the classes ‘agricultural land’ or ‘open land’ (most prominent in
the concessions) is limited (pers. Com. Niels Wielaard, SarVision).
HCV 2.3 Areas that Contain Representative Populations of Most Naturally
Occurring Species
The Indonesian HCV Toolkit states that an area containing a minimum viable population
(MVP) of most naturally occurring species is an HCV 2.3. The long-term presence of a
species requires maintaining habitat of sufficient quality and extent for population viability.
To identify areas that contain representative populations of most naturally occurring species,
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HCV 2.3 employs several proxies. These include landscapes with populations of higher
predators of different taxa (e.g., tigers, leopards, and eagles) or a low density of far ranging
species (e.g., orangutans and elephants) that require large areas to persist (HCV Consortium,
2008).
To support minimum viable population, a larger forested landscape has to be considered. To
assess this, concessions that contain viable populations of potential umbrella species have to
be identified. Since these species may not always have been signaled, from a precautionary
principle areas containing large natural forests are dealt with with caution. Concessions that
contain sufficient extent of forest that would be large enough to support such populations are
therefore also identified. Since this is in line with the analysis related to HCV 2.1, those
related findings are also considered here.
Data Input
To assess the presence of species considered in HCV 2.3 the following datasets are used:
• Land cover West Kalimantan, 2006 (WWF, 2009). This dataset is used to identify
large forest areas in the proximity of the concessions that can provide a habitat for the
species considered under HCV 2.3 (see HCV 1.2).
• Distribution of orangutan (WCMC 2004). To identify overlap with umbrella species,
the identified species suitable for such an analysis (based on the distribution and data
available) is the orangutan. The orangutan distribution data was used to assess the
overlap of the habitat of this umbrella species with the concessions. (see HCV 1.2).
• Orangutan Population and Habitat Viability Assessment (Singleton, 2004). The
orangutan distribution data was used to in addition to the WCMC data ro assess the
overlap of umbrella species with the concessions. (see HCV 1.2).
To identify the HCV 2.3 presence from the data above, the overlap and proximity to the
(potential) habitats 30 concessions has been analyzed.
Findings
None of concessions were found to overlap with an umbrella species habitat. However, one
concession (nr. 25) was found to be between 2 orangutan habitats, and this area is likely to
form a corridor. Although this corridor area is not part of the main habitat, it is likely to be
important for the viability of the species, since this migration potential increases genetic
variability in both populations.
Required field data
Based on the desk-based analysis, HCV 2.3 is unlikely to be present the preselected areas.
Due to the potential corridor function of a part of concession 25, this concession, and its
function as a corridor should be examined in more detail. However, due to the uncertainty in
the land-cover data it is thus recommended that the land cover is verified in the field, and
confirm HCV 2.3 is indeed absent.
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HCV 3 Rare or Endangered Ecosystems
Ecosystems can be classified as rare or threatened due to natural factors that limit its
distribution (e.g. Karst forest is found only on limestone), as a result of land cover changes
and degradation caused by anthropogenic activity. HCV 3 aims to identify rare or endangered
ecosystems in a landscape. Ecosystems can be considered a plant and animal community,
including its physical environment, which together functions as an inseparable unit (HCV
Consortium, 2008). Different ecosystems harbor different communities, environmental
biophysics and patterns of interaction between all organisms. To preserve the variety of
environmental services, representative samples of ecosystem types should be maintained
(HCV Consortium, 2008). The types of ecosystem recommended to preserve include rare
forests such as freshwater swamp forests or peat swamp forests, but can also refer to
ecosystem types formerly widespread but declining rapidly (see also HCV Consortium,
2008).
To assess whether an ecosystem is rare or endangered, an analysis has to be made comparing
the current condition of bio-physiographic situation at the landscape level with the historical
condition and predict future trends. If one ecosystem was reduced with more than 50%
compared to the historical situation, or if it is likely to decrease with more than 75% in the
future as a result of forest conversion, the ecosystem can be classified as HCV 3 (see also
HCV Consortium, 2008). Although a large proportion of the natural land ecosystems in
Indonesia are forest ecosystems, other aquatic ecosystems such as lakes and open swamps or
marshlands should also be considered (HCV Consortium, 2008). In case a concession
contains a significant size of such rare or endangered ecosystem types, the area will be
considered under HCV 3. Furthermore, any rare or endangered ecosystem that is located
outside the management unit and likely to be negatively affected as a result of the conversion
of the area, will also result in the concession being identified as HCV 3. Therefore, for each
concession it has been assessed:
• What the extent and quality is of ecosystems found in the landscape where the
concessions are located.
• What ecosystem types are present within the concessions and whether these are rare,
threatened or endangered in the wider landscape.
• Whether any areas are present that are identified by an independent organization as
important for conservation.
Data input
To assess the presence of HCV 3 the following data was used:
• Forest cover 2006 (source: WWF, 2008). This dataset is used to identify large forest
area’s in the proximity of the concessions.
• Land system map, (source: RePPProt 1989). This dataset is used to assess the type of
forest present.
• Forest Class Zone (MoF, 2002), in this data the forest is classified based on the
system as proposed by the MoF in 2002). This dataset is used to assess the type of
forest present.
• Peat land Areas (Wetlands International, 2002). This dataset is used to identify
unique ecosystems.
21

• Asian Karst Data (source: School of Environment, The University of Auckland,
http://www.sges.auckland.ac.nz/research/karst.shtml) This dataset is developed by
Ford & Williams in 1989, the revision was published in 2007 was used here to
identify unique karst ecosystems.
Findings
Based on the analysis it was found that there are 4 concessions (nr’s 8, 17, 18, 22) that
potentially contain peat land. However, only one of these concessions (nr. 22) contains an
area of peat with a relatively large size compared to the whole concession (about 4,600 ha,
see also table: 1.3). According to the data analyzed, no other ecosystems that could qualify as
HCV 3 were found in the preselected areas.
Nr Name Soil Proportion Depth Hectares
5 PT. Kalimantan Bina Permai Hemists/Mineral 4 50-100 90
14 PT. Maiska Bhumi Semesta Hemists/Mineral 4 50-100 59
15 PT. Mestika Karunia Abadi Hemists/Fibrists 1 1/2 100-200 191
19 PTP. XIII Hemists/Mineral 4 50-100 4,579
Table 1.3: The status of peat inside concessions.
Required field data
Also in this case, the precautionary principle should be considered. Since the data available to
assess the presence of HCV 3 has considerable limitations (especially the data on peat and
land systems have a low resolution, 1:250.000), a field assessment on land cover is strongly
recommended, even though no significant areas containing HCV 3 were identified in the
desktop analysis.
22

HCV 4.1 Areas or Ecosystems Important for the Provision of Water and
Prevention of Floods for Downstream communities
Land use activities or forest use in a watershed often results in the degradation of land due to
disturbance in the water cycle. The main parties that feel consequences of this degradation are
downstream communities. Land cover water catchment areas consisting of forest in good
condition functions to regulate water downstream. If a forest area is found to play a role in the
production of clean water or to control flooding in downstream communities, then it qualifies
as HCV 4.1 (HCV Consortium, 2008).
There are several land- and forest ecosystems that have exceptional hydrological functions
that should be attended to. For example wetland and forest eco-systems, are included in HCV
4.1. In addition, there are several terrestrial ecosystems (for example cloud forest, ridge line
forest, riparian ecosystems, karst forest) that have an extremely important hydrological
function and require special attention.
Data input
To identify the potential presence of this HCV, the data below is collected and analyzed:
• Priority Water Catchment Areas (Source Ministry of Forestry 1999 – 2009). This data
is used to identify watersheds. Priority Areas are watersheds classified by priority for
conservation (the MoF defined criteria related to the status of the land in terms of
erosion and land cover, water quality, water use, the context in the land use plan, see
also HCV consortium, 2008).
• Land cover West Kalimantan, 2006 (WWF, 2009). This data is used to identify
riparian zones. Remaining forest cover along the river has to be identified, since such
areas can qualify as an HCV 4.1 if it is likely to affect the hydrological situation
watersheds.
• Asian Karst Data (source: School of Environment, The University of Auckland,
http://www.sges.auckland.ac.nz/research/karst.shtml) This dataset is developed by
Ford & Williams in 1989, (the revision was published in 2007) used here to identify
unique karst ecosystems.
Findings:
It was found that there are three high priority water catchments, and 5 low priority water
catchments in West Kalimantan (identified in 1994 – 1999). A follow up study indicated that
West Kalimantan has become critical in terms of water management and hence needs serious
and good management in water sector. The status of watershed present in 30 concessions can
be seen in table 1.4.1 (see also appendix 1 figure 1.4.1 and table 1.4.1).
No Name Forest Cover Class Total Required buffer
23
zone (ha)
1 PT. Inma Makmur Lestari Secondary Dry land Forest 123
4 PT. Selaras Mukti Lestari Secondary Dry land Forest 132
8 PT. Indoresins Putra Mandiri Secondary Dry land Forest 18
9 PT. Putra Indotropical Secondary Dry land Forest 13
11 PT. Mitra Austral Sejahtera Secondary Swamp Forest 7
12 PT. Prana Reksa Karya Secondary Dry land Forest 27

18 PTP. XIII Secondary Dry land Forest 17
20 PT. Bintara Tani Nusantara Secondary Dry land Forest 230
23 PT. Tanjung Berkah Mulia Secondary Dry land Forest 43
24 PT. Mustika Agung Sentosa Secondary Dry land Forest 26
27 PT. Borneo Khatulistiwa Sawit Secondary Dry land Forest 19
28 PT. Bangun Nusa Mandiri Secondary Dry land Forest 92
Table 1.4.1. Concessions that have 100 m wide forest along the river and the total required buffer zone
Areas in proximity to the river, the buffer-zones, are considered HCV 4.1 and should be
maintained. HCV 4.1 was found to be present in the concessions 1, 4, 8, 9, 11, 12, 18, 20, 23,
24, 27, 28 ((based on the minimum requirements in decree No. 128/Kpts/V/1997, see table
1.4.1). Although this does not mean these areas cannot be used for oil palm cultivation (since
the value only covers a relatively small portion of the land), in the development of the
plantation the watershed areas have to be managed (see appendix 1.4.1 and table 1.4.1 as well
as HCV Consortium, 2008).
Required field work
The identified areas considered as HCV 4.1 are relatively small, and thus do not make the
concessions unsuitable for potential conversion. However, in the management plan the
presence of the HCV 4.1 should be considered. Based on the uncertainty of the data used
(very course scale of the data), field verification is recommended to precisely map the
location of water sources and required buffer-­‐zones.
HCV 4.2 Areas Important for the Prevention of Erosion and Sedimentation
Erosion and sedimentation have significant ecological and economic consequences at the
landscape level. Surface erosion causes the loss of topsoil, which in turn decreases the
productivity of the land. Morpho-erosion like landslides or the creation of ravines reduces the
area of productive land, damages economic infrastructure and increases sediment loads.
Under natural conditions, the rate of soil erosion is approximately equal to the rate of soil
formation. In disturbed environments, accelerated erosion is extremely destructive and bears
high cost in time and money to control it. Among factors that affect erosion rates, those which
can be fully controlled by humans are land cover and soil conservation practices. Natural
forest land cover is much more effective than non-forest at reducing erosion levels, due in
large part to a closed canopy, complex understory and surface leaf litter protecting the soil
(HCV Consortium, 2008)).
To assess the erosion risk the HCV toolkit proposes to use an adjusted version of the USLE
(R x K x LS) in which the vegetation parameter C is excluded (see for a detailed explanation
of the method HCV consortium, 2008). Based on USLE methodology, the erosion factor is
categorized into 5 levels: Very Low, Low, Moderate, High, Very High (see also table 4.2.1).
24

25
Soil Loss (ton/ha/year)
Erosion Class 1 2 3 4 5
Soil Depth 480
Depth (>90 cm) Very low Low Medium High Very high
Middle (60-90 cm) Low Medium High Very high Very high
Thin (30-60 cm) Medium High Very high Very high Very high
Very Thin (

Figure 1.4.2: Map indicating soil erosion risk in West Kalimantan Province
26

HCV 4.3: Areas that Function as Natural Barriers to the Spread of Forest or
Ground Fire
Forest fires in Indonesia have become a serious problem, which until now has not been
resolved. Forest fires affect almost all parts of Indonesia, such as Central Kalimantan, West
Kalimantan, South Sumatra, Jambi, and Riau with intervals 1987, 1991, 1997/1998, and year
2006. Various types of natural forests like, intact peat swamp forests, swamp forests, pool
areas, and other wetlands that are still in good condition have physical attributes that mitigate
the risk of large-scale fire. Areas that can protect and prevent forest fires on a large scale are
considered areas containing HCV 4.3.
To identify HCV 4.3, the fire occurrences inside and around the concessions have been
checked. It is assumed that when an area is burned over repeatedly, HCV 4.3 is not present In
addition potential fire barriers have been identified, such as large forest areas and wetland
ecosystems inside or around the concession.
Data input
To assess the presence of HCV 4.3 in the 30 concessions, the following data sources are used:
• Land cover West Kalimantan, 2006 (WWF, 2009) The land cover data was used to
identify any large forest area, that potentially functions as a barrier for large scale fire
is present in or proximate to the concessions.
• Peat and wetland Areas (Wetland International, 2002). This dataset is used to identify
wetlands, since these have a high potential of functioning like a barrier.
• Forest Fire data (source: NOAA and MODIS Rapid Response). This data was used to
assess the occurrence of fire in or around the concessions. If the area burned severely
in the recent past, it can be assumed that no HCV 4.3 is present.
Findings
Based on the analysis no significant fire barriers such as large wetland forest, or large blocks
of primary forests were found inside the concessions. In addition, based on the historical data,
many fires were found to have occurred proximate, or in the concessions (see table 4.3).
Therefore it is concluded from the desktop study that HCV 4.3 is absent in all 30 concessions.
Required field data
Since no significant barriers were indicated, and both the resolution and the quality of the data
are of sufficient detail for the purpose of our analysis, no further verification data is required.
27

No. Name 2000 2002 2003 2004 2005 2006 2007
West Kalimantan 648 2,331 4,112 8,002 3,434 12,948 2,271
Inside 30 MUs 14 51 225 351 204 370 72
% from Province 2% 2% 5% 4% 6% 3% 3%
1 PT. Inma Makmur Lestari 1 10 18 16 27 5
2 PT. Global Kalimantan Makmur 4 18 12 21 38 5
3 PT. Malindo Persada Khatulisti 5 11 12 5 5
4 PT. Selaras Mukti Lestari 16 14 14 7
5 PT. Kalimantan Bina Permai 1 13 8 3 7 4
6 PT. Grand Utama Mandiri 3 3 1 4
7 PT. Pratama Prosentindo 5 5 2 1
8 PT. Indoresins Putra Mandiri 3 6 4 5
9 PT. Putra Indotropical 5 3 2 1 4
10 PTP. XIII 8
11 PT. Mitra Austral Sejahtera 1 11 7 5 7 8
12 PT. Prana Reksa Karya 5 1 6 3
13 PT. Maiska Bhumi Semesta 14 16 15 21 2
14 PT. Mestika Karunia Abadi 1 14 12 11 2 8
15 PT. Sime Indoagro 4 5 7 4 1
16 PT. Bumi Pratama Khatulistiwa 1 15 9 15 23 3
17 PT. Multi Prima Entakai 1 1 18 11 13 7 1
18 PTP. XIII 7 20 6 3
19 PT. Multi Jaya Perkasa 8 12 8 9 1
20 PT. Bintara Tani Nusantara 2 6 3 5 10 6 3
21 PT. Bintang Harapan Desa 1 3 2
22 PT. Sumatra Makmur Lestari 2 6 11 3 4 1
23 PT. Tanjung Berkah Mulia 3 12 19 9 20 2
24 PT. Arvena Sepakat 1 2 15 1 4 1
25 PT. Mustika Agung Sentosa 4 12 6 19 1
26 PT. SMART (Sinar Mas Group) 5 7 17 47 7
27 PT. Borneo Khatulistiwa Sawit 1 5 6 31 1 39 3
28 PT. Bangun Nusa Mandiri 14 1 28
29 No-Info yet 3
30 No-Info yet 6 22 16 51 7 23
Table 1.4.3: Occurred fires in the 30 concessions in West Kalimantan during 2000 - 2007
28

HCV 5: Natural Areas Critical for Meeting the Basic Needs of Local People
This HCV aims to identify the natural areas that have important functions as a source of
livelihood for local communities, both to meet the direct needs (subsistence/consumption) or
indirectly (commercial), namely by selling products (forest products or other natural
resources) to meet financial needs. Basic needs include: food, water, clothing, materials and
equipment for homes, fuel wood, medicines, and animal feedings.
A natural area is identified as HCV 5, if one or more community members use the area in
order to meet the basic needs, and no affordable alternative is present. The value is present
when 50% or more of a single basic need is met by the use of natural ecosystems (see also
(HCV Consortium, 2008). An important factor to take into account is the existence of market
access. Isolated communities may be largely dependent on forests or other natural
ecosystems. However, communities with good accessibility, market access and
communication networks will be more able to switch to other means to meet their basic
needs.
In addition, the use of the forests resources must be sustainable and not excessive. This means
that HCV 5 is not present in the application of traditional practices that damage or threaten
other HCV, such as excessive hunting of endangered species (HCV 1.2).
Data input
To assess the presence of HCV 5, the basic needs related to: food, water, clothing, materials
for the house and tools, firewood, medicine, and livestock originating from areas in the
concessions have to be identified.
Finding
No desk-based data on how local populations meet their basic needs was found.
Required field data
Information has to be gathered on where basic needs of the local communities are obtained
from and which alternatives may be available.
29

HCV 6: Areas Critical for Maintaining the Cultural Identity of Local
Communities
HCV 6 concerns areas that play an important role in the traditional cultural identity of local
communities and/or where a particular area is needed to fulfill their cultural needs. The
relationship between a community and an area can be rooted in ideas, concepts, norms,
values, activities, and activity patterns, as well as features of the environment/natural
resources/objects. Together, these features form the basis of a collective behavior of a
community and that define the relationship between a community and an area (HCV
Consortium, 2008).
Unique cultural identity is the identity emerging from a collective of individuals
(communities) who lived in a certain area, based on shared historical background and
common collective interpretation of the surrounding environment and resources. The
interaction between the community and the natural environment is unique and can't be
separated if it would disrupt the pattern of life or ecological balance that has been built (HCV
Consortium, 2008).
Thus an area may be designated HCV 6 if it provides values without which a local
community would suffer a drastic cultural change.
Data input
To be able to identify HCV 6, an inventory must be made of the areas in the concessions that
are critical to the maintenance of communities’ traditional cultural identity. In addition the
relevant cultural ties to natural areas in the concessions have to be identified, as well as the
types of community forest management that may lead to irreversible change in case this is not
continued.
Finding
The information and the data related to HCV 6 that is needed to perform the analysis could
not be found.
Required field data
Data on HCV 6 must be collected in specifically designed fieldwork. The information
required can be obtained through focus group discussions (FGD), Participatory Rural
Appraisal (PRA) or by directly interviewing the communities. It is recommended that this is
done for specific concessions on a site level.
30

P2: Establishment of energy crop plantations does not lead to
significant reductions in carbon stocks
As outlined in the methodology for RCA (Dehue, 2009), both the (dominant) land cover, and
the presence of high carbon soils, such as peat soils, have to be identified to assess whether or
not the carbon stocks in the concession will be significantly reduced in case of conversion to
energy crop plantation. The threshold value for the carbon payback time resulting from
emissions from land use change may not exceed 10 years.
Data input
To estimate of the above ground carbon stock in each concession, secondary data and
literature data will be used. This approach is in line with the IPCC guidelines in tier 2. In the
estimation of carbon stocks based on present biomass, the carbon content is estimated 50% of
the biomass (Gibbs, 2006). In line with the IPCC Tier 1 methodology, no significant change
in soil carbon is assumed in the conversion of grassland or forest to a perennial crop such as
oil palm (see also Vlek, 2005). For the consistency of the study, the same land cover data is
used as applied in phase I.
• Distribution wetlands (Wetlands International, 2002) Used to identify the wetlands.
• Carbon stocks (SEAMEO Biotrop): As a reference for carbon stock data for each
land cover category, a study from SEAMEO-Biotrop was used. In this study data
from several sources was collected and baselines were developed by SEAMEO-
Biotrop. For the 30 concessions identified as promising RCA’s, the carbon stocks
were assessed based on the stratification of the land cover. The study used a range for
carbon stocks by giving minimum (low estimation) and maximum (high estimation)
estimates (see also table 2.1).
Findings
Based on the desk-based analysis, it was found that the aboveground carbon stocks in the
concessions are significantly lower than the default value for an oil palm plantation (48
Mg/ha, based on Palm et al.1999. It can be concluded that the carbon stocks in the
concessions are relatively low, and thus can be considered in line with RCA principle 2 (see
also table 2.1). The main reason for the relatively low carbon stocks found in the concessions
is due to the fact that the preselected concessions have a no or very little forest cover.
Required field data
Considering the uncertainties in the data used, (mainly the land cover data and the wide
ranges for the carbon stocks for a given land cover type in the SEAMEO-Biotrop study), it is
recommended to assess the actual land cover in the field and to make an estimate of the above
ground carbon stocks of any forest re-growth patches in the preselected areas.
31

No Company Hectares C/Ha LE C/Ha HE
1 PT. Inma Makmur Lestari 21,470 5.7 11.7
2 PT. Global Kalimantan Makmur 27,367 4.4 8.4
3 PT. Malindo Persada Khatulisti 21,055 1.2 4.2
4 PT. Selaras Mukti Lestari 20,029 9.5 15.8
5 PT. Kalimantan Bina Permai 36,928 0.7 2.8
6 PT. Grand Utama Mandiri 17,387 0.5 2.3
7 PT. Pratama Prosentindo 20,086 1.0 3.0
8 PT. Indoresins Putra Mandiri 18,044 3.7 7.5
9 PT. Putra Indotropical 19,908 3.1 6.7
10 PTP. XIII 20,972 2.5 8.0
11 PT. Mitra Austral Sejahtera 26,567 0.6 2.7
12 PT. Prana Reksa Karya 21,819 1.9 4.3
13 PT. Maiska Bhumi Semesta 20,612 0.7 3.2
14 PT. Mestika Karunia Abadi 19,595 1.4 5.5
15 PT. Sime Indoagro 22,040 0.6 2.9
16 PT. Bumi Pratama Khatulistiwa 49,480 0.8 2.8
17 PT. Multi Prima Entakai 29,519 1.6 3.9
18 PTP. XIII 28,682 1.1 3.5
19 PT. Multi Jaya Perkasa 43,334 0.8 2.7
20 PT. Bintara Tani Nusantara 19,363 10.7 18.6
21 PT. Bintang Harapan Desa 16,786 0.5 2.3
22 PT. Sumatra Makmur Lestari 43,944 0.6 2.6
23 PT. Tanjung Berkah Mulia 19,317 2.0 4.6
24 PT. Arvena Sepakat 21,989 0.8 2.7
25 PT. Mustika Agung Sentosa 19,667 12.0 19.6
26 PT. SMART (Sinar Mas Group) 37,209 4.4 8.9
27 PT. Borneo Khatulistiwa Sawit 17,611 5.6 18.1
28 PT. Bangun Nusa Mandiri 25,903 10.8 31.4
29 No-Info yet 19,734 4.1 17.8
30 No-Info yet 21,078 2.1 9.2
Table 2.1: Above ground carbon Stock estimation in the 30 concessions
Note: Estimation carbon stock in each concession, which is:
C/Ha LE: Carbon Stock Low Estimation in Mg/hectare
C/Ha HE: Carbon Stock High Estimation in Mg/hectare
32

P3: Establishment of energy crop plantations respects formal and
customary land rights
Under principle 3, an energy crop plantation should respect formal and customary land rights,
with a special focus on conflicting information about land-use planning and actual land use.
To assess whether or not land rights can be respected, or that there is a high potential for
conflict, both the formal land right holder as well as the holders of customary land right was
identified. Recent conflicts between right holders are used as an indicator for risk for
conflicting/overlapping land rights. In addition, the land use plans are assessed on potential
conflict with energy crop production.
Data input
To assess the potential conflict on land (use) rights, the following datasets were analyzed in
this phase:
• Based on data available on permits issued (Plantation service, 2007), non-scientific
literature (internet, newspapers, RSPO database) and interviews, the formal
ownership of almost all the 30 concessions could be established.
• West Kalimantan Plantation Service (Plantation service, 2007). To assess the plans
for land use by the formal land right holders, the official status of the concessions
(active or non active) was verified.
Findings
The concession status and its owner were identified for most of the concessions (see
Appendix 3). Most are officially still inactive (there hasn’t been any activity during three
years to develop the plantation). For detailed information what the plan is of the local
government with this land, what the land-claims are within the concessions, and what
conflicts have occurred in recent history no literature data was found.
Required field data
To clarify the plans on land use by the government, interviews should be held with local
governments and the concession holders. To obtain better insight in the current situation
related to land claims and potential conflicts, a more detailed study on a concession level is
required, in which representative group and experts in the local communities are interviewed.
33

Figure 3.1: Map of Land use (function) in West Kalimantan Province
34

P4: Establishment of energy crop plantations does not cause
unwanted displacement effects
To assess whether the establishment of energy crop plantations does not cause unwanted
displacement effects in line with principle 4, it must be clarified what the current provisioning
services are. For this purpose, existing plantations and agricultural land used by local
communities are identified and mapped. In addition, for the unused land inquiries will be
made on why the land is not used or abandoned.
Data input
It is difficult to assess the land use by local communities with a desk-based analysis.
However, as a proxy an analysis was made based on the following input:
• Land cover West Kalimantan, 2006 (WWF, 2009). This dataset was used to assess
how much land is used for agriculture and settlements.
• Plantation concession (plantation service, 2007). This data is used to assess whether
the concession is active.
Findings
Based on the analysis, no land preparation for plantations seems to taken place yet in the
preselected areas. Based on remote sensing data the current land use by communities seems
relatively high, in some concessions some above 90% (see Appendix 3), indicating a potential
risk of displacing small scale local agriculture.
Required field data
In case communities use a large portion of the land, the potential displacement effects (and
the risk for conflicts) will be significant. It is however unlikely that the amount of land
indicated for agriculture by remote sensing is actually used in practice. The wide variety of
reflection patterns, associated with the shifting cultivation methods of the communities,
strongly limit the reliability of an assessment based on remote sensing data. For example; the
reflection pattern of “jungle rubber” in the field, is very similar to “re-growth”.
Considering the limitations of remote sensing, land use data has to be compared with the
conditions in the field. Thus to assess the potential displacement, a more detailed analysis of
the actual amount of land used in the concessions is needed.
35

P5: The identified areas is agriculturally suitable for the target
energy crop
To assess whether the concessions are agriculturally suitable for energy crop development in
line with principle 5, a reference is made to crop specific studies. In line with this
recommendation, an inventory of relevant studies is made.
In addition to the analysis on biophysical suitability, the access and proximity to
infrastructure was assessed, since this will strongly influence the economic viability of
developing a plantation in a specific area. To be able to support oil palm plantation
development access by road or river, and settlements (people, accommodation to support the
employers, electricity, etc) are crucial.
Data Input
To assess the biophysical suitability for oil palm cultivation in the concessions, and the
proximity to infrastructure, the following data sources were used:
• Biophysical suitability for oil palm in Kalimantan (Mantel 2007). The biophysical
suitability was assessed based on climate, topographic- (elevation, slope) and soil
properties (soil type, soil depth, drainage).
• Ministry of Public Works (2007/2008). To assess the access of the concessions the
distance from rivers, infrastructure and existing plantations was analyzed.
Findings
Based on the biophysical suitability analysis, all concessions were found to have sufficient
portion (minimum 5000 ha) of the land classified as suitable (see appendix 5 table 5.1). In the
assessment on access, two concessions were found to be to remote from rivers infrastructure
or existing plantations. Concession 23 is remote from main road, and does not have sufficient
access to other infrastructure (see Appendix 5 table 5.2). The development of a plantation in
this area is therefore not likely to be economically feasible. These concessions are therefore
not considered as RCA areas. The other concessions have sufficient access to infrastructure.
Required field work
Since the resolution of data produced by Mantel et al. (2007) (1:250000) is unsuitable for a
reliable biophysical suitability analysis on a site level, an on-site assessment of the
biophysical suitability is recommended. Specifically an analysis on the soil type and soil
depth should be included in the field activities as well as a visual inspection of the slopes of
the terrain.
On access to infrastructure, no further field assessment is required, since the data used is
considered to have been sufficiently verified by the Ministry of Public Works (2007/2008).
36

Recommendation Phase II: Identified priority areas
The analysis for phase II started with 30 preselected areas identified in phase I. Based on the
additional analysis of Phase II, a number areas have been removed as potential RCA since
conflicts with the RCA principles were identified. In addition, for a number of areas a risk for
conflict with RCA principles was identified. The latter areas may still be suitable as RCA.
However, these would need special attention to one or more of the RCA principles due to
potential issues in these areas The results of the analysis in phase II are summarized in table
6.1 below.
RCA Presence of HCV’s Presence of
Preselected area
nr.s unsuitable as
RCA
Preselected area
nr.s that need
special attention
due to risks
identified
No conflicts with
the RCA criteria
were found
25 (HCV 2.1, 2.3)
HCV 1.1: 3, 14, 22,
24, and 26 (also 17,
19, 21, but already
excluded based on P
3)
HCV, 1.2: 24, 28
HCV 3: 8, 18, 22
(also 17 but already
excluded
high carbon
stocks
Table 6.1: Overview identified conflicts/risk for conflict with RCA principles
For concessions 1, 2, 4, 6, 7, 8, 9, 10, 12, 13, 20, 27, 28, 29, 30, no conflicts with the RCA
criteria were found. These areas are recommended for a first focus in initiatives identifying
potential expansion areas for oil palm in West Kalimantan.
The phase III assessment will focus in detail on concessions 20, 29, 30. These concession
ware selected for further analysis since its location is proximate to the heart of Borneo, and
thus can potentially provide an option to divert planned operations in or close to heart of
Borneo to (see also figure 6.1).
37
Land right
issues
5, 11, 15,
16, 17, 18,
19, 21
(status
active)
1, 2, 4, 6, 7, 8, 9, 10, 12, 13, 20, 27, 28, 29, 30
Displacement
risk
Agricultural
suitability
23, remote
from main
road, but has
access to
river)

Figure 6.1: Location concession 30 identified for further analysis in phase II
The next chapter will describe the results of the fieldwork that was performed in concession
30. The designed field activities are based on information requirements identified desk-based
assessment in phase II, and aims to fill the identified information gaps (aspects on which no
desk-based information was available), as well as improve data quality (data that requires
verification on the ground).
38

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HCV Consortium, 2008. Toolkit for
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Values in Indonesia. Jakarta
Jennings., S., Judd, N., Nussbaum, R.,
Evans., J. 2003. The High Conservation
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Mantel, S., Wösten, H. and Verhagen, J.,
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Jakarta, Indonesia.
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Stephens, S. Utami Atmoko, M. Leighton,
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sequestration on degraded land in
Indonesia. Ecology and Development
Series No. 28. Center for Development
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Goettingen, Germany
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accessed oktober, 2009

Appendix 1
Table 1.1 Protected and Conservation Areas that are close or overlap with the 30
concessions
No Name Hectares Forest
40
(ha)
1 PT. Inma Makmur Lestari 21,470 1,474
2 PT. Global Kalimantan Makmur 27,367 1,389
Protected
Forest
3 PT. Malindo Persada Khatulistiwa 21,055 129 Adjacent
4 PT. Selaras Mukti Lestari 20,029 2,514
5 PT. Kalimantan Bina Permai 36,928
6 PT. Grand Utama Mandiri 17,387
7 PT. Pratama Prosentindo 20,086 132
8 PT. Indoresins Putra Mandiri 18,044 784
9 PT. Putra Indotropical 19,908 602
10 PTP. XIII 20,972
11 PT. Mitra Austral Sejahtera 26,567 65
12 PT. Prana Reksa Karya 21,819 411
13 PT. Maiska Bhumi Semesta 20,612
Conservation
Area
14 PT. Mestika Karunia Abadi 19,595 385 Adjacent
15 PT. Sime Indoagro 22,040
16 PT. Bumi Pratama Khatulistiwa 49,480 146
IUCN
17 PT. Multi Prima Entakai 29,519 416 Cat IV, 9 ha
18 PTP. XIII 28,682 154
19 PT. Multi Jaya Perkasa 43,334 149 Cat IV, 1717 ha
20 PT. Bintara Tani Nusantara 19,363 2,646
21 PT. Bintang Harapan Desa 16,786 Cat IV, 15 ha
22 PT. Sumatra Makmur Lestari 43,944 22 Adjacent Cat IV, 5067 ha
23 PT. Tanjung Berkah Mulia 19,317 421
24 PT. Arvena Sepakat 21,989 83 Adjacent
25 PT. Mustika Agung Sentosa 19,667 3,097
26 PT. SMART (Sinar Mas Group) 37,209 1,326 Adjacent
27 PT. Borneo Khatulistiwa Sawit 17,611 547
28 PT. Bangun Nusa Mandiri 25,903 1,987
29 No-Info yet 19,734
30 No-Info yet 21,078

Table 1.2: Important habitats that are close or overlap with the 30 concessions
No Name Hectares Forest (ha) Orang Utan Habitat Bird Life (EBA)
24 PT. Arvena Sepakat 21,989 83 Adjacent
25 PT. Mustika Agung Sentosa 19,667 3,097 75 ha
28 PT. Bangun Nusa Mandiri 25,903 1,987 5243 ha
Table 1.4.1.1 Watershed status inside the 30 concessions
No Name Hectares Watershed Condition
1 PT. Inma Makmur Lestari 21,470 Critical
2 PT. Global Kalimantan Makmur 27,367 Critical
3 PT. Malindo Persada Khatulisti 21,055 Not Critical
4 PT. Selaras Mukti Lestari 20,029 Not Critical
5 PT. Kalimantan Bina Permai 36,928 Critical
6 PT. Grand Utama Mandiri 17,387 Critical
7 PT. Pratama Prosentindo 20,086 Not Critical
8 PT. Indoresins Putra Mandiri 18,044 Not Critical
9 PT. Putra Indotropical 19,908 Not Critical
10 PTP. XIII 20,972 Critical
11 PT. Mitra Austral Sejahtera 26,567 Critical
12 PT. Prana Reksa Karya 21,819 Critical
13 PT. Maiska Bhumi Semesta 20,612 Not Critical
14 PT. Mestika Karunia Abadi 19,595 Not Critical
15 PT. Sime Indoagro 22,040 Critical
16 PT. Bumi Pratama Khatulistiwa 49,480 Critical
17 PT. Multi Prima Entakai 29,519 Critical
18 PTP. XIII 28,682 Critical
19 PT. Multi Jaya Perkasa 43,334 Critical
20 PT. Bintara Tani Nusantara 19,363 Critical
21 PT. Bintang Harapan Desa 16,786 Critical
22 PT. Sumatra Makmur Lestari 43,944 Critical
23 PT. Tanjung Berkah Mulia 19,317 Critical
24 PT. Arvena Sepakat 21,989 Critical
25 PT. Mustika Agung Sentosa 19,667 Critical
26 PT. SMART (Sinar Mas Group) 37,209 Not Critical
27 PT. Borneo Khatulistiwa Sawit 17,611 Not Critical
28 PT. Bangun Nusa Mandiri 25,903 Not Critical
29 No-Info yet 19,734 Critical
30 No-Info yet 21,078 Critical
41

Figure 1.4.1.2: Zones with critical watersheds (Kapuas and Sambas), the watersheds in a
zone classified as critical are considered Super Priority to be be managed by Government
42

Table 1.4.2: Estimated erosion levels inside the 30 concessions.
No . Name Area
(ha)
1 2
Erosion risk
3 4 5
1 PT. Inma Makmur Lestari 21,478 44% 9% 0% 0% 0%
2 PT. Global Kalimantan Makmur 27,389 75% 20% 4% 0% 0%
3 PT. Malindo Persada Khatulisti 21,077 13% 71% 14% 1% 0%
4 PT. Selaras Mukti Lestari 20,036 50% 40% 10% 0% 0%
5 PT. Kalimantan Bina Permai 36,937 94% 5% 0% 0% 0%
6 PT. Grand Utama Mandiri 17,394 84% 16% 0% 0% 0%
7 PT. Pratama Prosentindo 20,091 45% 35% 14% 6% 1%
8 PT. Indoresins Putra Mandiri 18,061 39% 48% 9% 3% 0%
9 PT. Putra Indotropical 19,927 44% 39% 14% 3% 0%
10 PTP. XIII 20,978 86% 14% 0% 0% 0%
11 PT. Mitra Austral Sejahtera 26,582 83% 16% 1% 0% 0%
12 PT. Prana Reksa Karya 21,840 28% 44% 18% 9% 1%
13 PT. Maiska Bhumi Semesta 20,627 27% 67% 4% 0% 0%
14 PT. Mestika Karunia Abadi 19,611 40% 51% 6% 2% 0%
15 PT. Sime Indoagro 22,048 84% 13% 3% 0% 0%
16 PT. Bumi Pratama Khatulistiwa 49,496 83% 15% 2% 0% 0%
17 PT. Multi Prima Entakai 29,522 83% 15% 2% 0% 0%
18 PTP. XIII 28,683 94% 5% 0% 0% 0%
19 PT. Multi Jaya Perkasa 43,353 73% 18% 6% 3% 0%
20 PT. Bintara Tani Nusantara 19,390 68% 30% 1% 0% 0%
21 PT. Bintang Harapan Desa 16,807 51% 47% 1% 0% 0%
22 PT. Sumatra Makmur Lestari 44,003 22% 53% 16% 8% 1%
23 PT. Tanjung Berkah Mulia 19,368 33% 41% 23% 3% 0%
24 PT. Arvena Sepakat 22,013 26% 40% 22% 10% 2%
25 PT. Mustika Agung Sentosa 19,694 46% 49% 5% 0% 0%
26 PT. SMART (Sinar Mas Group) 37,248 48% 33% 11% 7% 1%
27 PT. Borneo Khatulistiwa Sawit 17,623 82% 17% 1% 0% 0%
28 PT. Bangun Nusa Mandiri 25,915 77% 17% 5% 1% 0%
29 No-Info yet 19,744 97% 3% 0% 0% 0%
30 No-Info yet 21,082 74% 22% 3% 1% 0%
43

Table 1.4.3: Occurred fires in the 30 concessions in West Kalimantan between 2000 –
2007
No. Name 2000 2002 2003 2004 2005 2006 2007
West Kalimantan 648 2,331 4,112 8,002 3,434 12,948 2,271
Inside 30 MUs 14 51 225 351 204 370 72
% from Province 2% 2% 5% 4% 6% 3% 3%
1 PT. Inma Makmur Lestari 1 10 18 16 27 5
2 PT. Global Kalimantan Makmur 4 18 12 21 38 5
3 PT. Malindo Persada Khatulisti 5 11 12 5 5
4 PT. Selaras Mukti Lestari 16 14 14 7
5 PT. Kalimantan Bina Permai 1 13 8 3 7 4
6 PT. Grand Utama Mandiri 3 3 1 4
7 PT. Pratama Prosentindo 5 5 2 1
8 PT. Indoresins Putra Mandiri 3 6 4 5
9 PT. Putra Indotropical 5 3 2 1 4
10 PTP. XIII 8
11 PT. Mitra Austral Sejahtera 1 11 7 5 7 8
12 PT. Prana Reksa Karya 5 1 6 3
13 PT. Maiska Bhumi Semesta 14 16 15 21 2
14 PT. Mestika Karunia Abadi 1 14 12 11 2 8
15 PT. Sime Indoagro 4 5 7 4 1
16 PT. Bumi Pratama Khatulistiwa 1 15 9 15 23 3
17 PT. Multi Prima Entakai 1 1 18 11 13 7 1
18 PTP. XIII 7 20 6 3
19 PT. Multi Jaya Perkasa 8 12 8 9 1
20 PT. Bintara Tani Nusantara 2 6 3 5 10 6 3
21 PT. Bintang Harapan Desa 1 3 2
22 PT. Sumatra Makmur Lestari 2 6 11 3 4 1
23 PT. Tanjung Berkah Mulia 3 12 19 9 20 2
24 PT. Arvena Sepakat 1 2 15 1 4 1
25 PT. Mustika Agung Sentosa 4 12 6 19 1
26 PT. SMART (Sinar Mas Group) 5 7 17 47 7
27 PT. Borneo Khatulistiwa Sawit 1 5 6 31 1 39 3
28 PT. Bangun Nusa Mandiri 14 1 28
29 No-Info yet 3
30 No-Info yet 6 22 16 51 7 23
44

Appendix 3
Table 3.1: Formal ownership concessions and land use by communities
No Owner Status Action Ha Agriculture Settlement
1 Pinehill Ventures Limited Inactive No Land Clearing yet 21,470 19,350 48
2 Indonusa Inactive No Land Clearing yet 27,367 25,441 152
3 Global Natural Resources Inactive No Land Clearing yet 21,055 19,758 114
4 Un-identified Inactive No Land Clearing yet 20,029 17,458 55
5 Lyman Agro Active No Land Clearing yet 36,928 35,750 27
6 Un-identified Inactive No Land Clearing yet 17,387 17,334 41
7 Wilmar Inactive No Land Clearing yet 20,086 19,793 159
8 Wilmar Inactive No Land Clearing yet 18,044 17,063 74
9 Wilmar Inactive No Land Clearing yet 19,908 18,366 98
10 State owned company Inactive No Land Clearing yet 20,972 15,988 141
11 Sinergy Drive Active No Land Clearing yet 26,567 26,265 136
12 Un-identified Inactive No Land Clearing yet 21,819 20,970 315
13 Global Natural Resources Inactive No Land Clearing yet 20,612 20,183 107
14 Un-identified Inactive No Land Clearing yet 19,595 18,297 67
15 Sinergy Drive Active No Land Clearing yet 22,040 21,741 116
16 Wilmar Active No Land Clearing yet 49,480 48,360 303
17 MPE Group Active No Land Clearing yet 29,519 29,011 92
18 State owned company Active No Land Clearing yet 28,682 27,868 135
19 MJP Group Active No Land Clearing yet 43,334 42,680 330
20 Incasi Raya Inactive No Land Clearing yet 19,363 14,353 147
21 BHD Group Active No Land Clearing yet 16,786 16,785
22 Incasi Raya - Gunas Inactive No Land Clearing yet 43,944 43,583 221
23 Un-identified Inactive No Land Clearing yet 19,317 17,058 106
24 Incasi Raya Inactive No Land Clearing yet 21,989 21,840 64
25 Un-identified Inactive No Land Clearing yet 19,667 16,535 24
26 SMART Group Inactive No Land Clearing yet 37,209 32,561 379
27 Artha Inactive No Land Clearing yet 17,611 12,946 87
28 Un-identified Inactive No Land Clearing yet 25,903 15,889 147
29 Un-identified Inactive No-Info yet 19,734 13,977 49
30 Un-identified Inactive No-Info yet 21,078 8,105 60
45

Appendix 5
Table 5.1: The biophysical suitability in the 30 concessions according to the Low Input
and High Input base on ISRIC data.
Low Input High Input
No Hectares No Data Not Possible Constrained Possible Optimal Not Possible Possible Optimal
1 21,470 79 21,391 21,470
2 27,367 132 1,197 26,039 654 26,713
3 21,055 79 1,600 19,376 1,018 20,038
4 20,029 26 20,003 20,029
5 36,928 175 1,291 35,462 1,261 35,667
6 17,387 72 17,315 17,387
7 20,086 97 840 6 19,143 340 19,746
8 18,044 65 2,360 43 15,577 1,845 16,199
9 19,908 37 1 19,870 19,908
10 20,972 72 20,900 20,972
11 26,567 48 193 26,326 155 26,412
12 21,819 85 6,216 176 15,345 4,448 17,371
13 20,612 18 1,142 19,451 428 20,184
14 19,595 91 1,902 28 17,575 1,310 18,285
15 22,040 34 22,006 22,040
16 49,480 157 991 48,332 653 48,827
17 29,519 59 184 29,277 110 29,409
18 28,682 75 28,135 473 28,176 505
19 43,334 42 2,709 26 40,557 2,256 41,078
20 19,363 50 19,313 19,363
21 16,786 21 16,765 16,786
22 43,944 61 10,348 149 33,387 8,561 35,383
23 19,317 20 15 13 19,269 19 19,299
24 21,989 48 7,833 22 14,089 6,045 15,944
25 19,667 58 796 3 18,809 525 19,142
26 37,209 56 8,214 214 28,726 6,492 30,717
27 17,611 37 1,471 16,103 1,002 16,608
28 25,903 50 1,838 39 23,978 1,048 24,855
29 19,734 16 14 19,704 9 19,725
30 21,078 31 21,047 21,078
46

Table 5.2: Accessibility of the 30 concessions, based on existing infrastructure and
proximity to the nearest plantation.
Distance to road Distance to river Distance to nearest plantation
No Ha
0 - 5 5 - 20 20 - 40 > 40 0 - 5 5 - 20 20 - 40 > 40 0 - 5 km 5 - 10 km 10 - 30 km > 30 km
km km km km km km km km
1 21,470 7,868 13,602 21,470 1,986 19,484
2 27,367 10,201 17,166 27,367 847 26,520
3 21,055 11,041 10,014 10,176 10,879 8,236 3,755 9,064
4 20,029 10,966 9,063 2 20,027 2,963 17,067
5 36,928 8,381 23,168 5,379 3,419 7,797 22,382 3,330 6,460 15,983 14,485
6 17,387 13,313 4,073 38 17,160 188 6,106 10,127 1,153
7 20,086 14,144 5,942 755 19,331 5,328 13,091 1,667
8 18,044 2,539 15,505 18,044 1,836 15,455 753
9 19,908 92 19,816 19,908 7,605 7,045 5,258
10 20,972 14,954 6,017 1,976 18,996 9,821 1,410 9,741
11 26,567 9,068 17,499 22,497 4,070 3,499 23,068
12 21,819 11,323 10,497 12,683 9,137 824 20,995
13 20,612 6,740 13,872 6,045 14,567 2,161 18,451
14 19,595 13,276 6,319 19,246 349 19,595
15 22,040 8,533 13,507 4,403 17,637 22,040
16 49,480 20,750 28,730 5,240 21,880 22,360 16,205 21,287 11,988
17 29,519 10,335 19,184 3,251 25,945 324 11,396 6,137 11,986
18 28,682 11,874 16,808 14,981 13,701 14,824 2,665 11,193
19 43,334 22,622 20,712 10,121 30,103 3,111 11,240 30,862 1,233
20 19,363 16,390 2,973 1,210 18,153 14,997 4,366
21 16,786 12,620 4,165 6,819 9,967 11,457 38 5,291
22 43,944 29,210 14,734 11,173 32,771 11,038 21,477 11,429
23 19,317 19,317 17,446 1,872 305 19,013
24 21,989 21,989 8,152 13,838 9,678 5,966 6,346
25 19,667 11,878 7,788 8,513 11,154 19,667
26 37,209 24,511 12,698 2,590 34,619 8,482 26,119 2,608
27 17,611 12,152 5,458 1,652 15,959 8,949 2,515 6,147
28 25,903 13,100 12,803 1,567 24,325 12 10,982 1,148 13,773
29 19,734 1,981 17,753 10,130 9,604 3,941 15,543 250
30 21,078 5,120 15,959 5,043 16,035 8,308 8,769 4,002
47