S7 veg mon report final

SCIENTIFIC REPORT

KFCP Vegetation Monitoring

Rates of change for forest characteristics, and the influence of environmental conditions, in the KFCP study area Laura L. B. Graham, Tri Wahyu Susanto, Fransiscus Xaverius, Eben Eser, Didie, Andri Thomas Salahuddin, Abdi Mahyudi, and Grahame Applegate Kalimantan Forests and Climate Partnership

SCIENTIFIC REPORT

KFCP Vegetation Monitoring Rates of change for forest characteristics, and the influence of environmental conditions, in the KFCP study area Laura L. B. Graham, Tri Wahyu Susanto, Fransiscus Xaverius, Eben Eser, Didie, Andri Thomas Salahuddin, Abdi Mahyudi and Grahame Applegate Kalimantan Forests and Climate Partnership May 2014

ACKNOWLEDGEMENTS This report was prepared by Laura L. B. Graham, Tri Wahyu Susanto, Fransiscus Xaverius, Eben Eser, Didie, Andri Thomas Salahuddin, Abdi Mahyudi, and Grahame Applegate. We wish to thank all team members for their inputs into this paper, and particularly Laura Graham as lead writer. We also wish to thank Grahame Applegate for his technical guidance in the field, Fatkhurohman for his data support, Susan E. Page for her technical review, Rachael Diprose and Lis Nuhayati for their assistance in preparing this paper and other related papers, and the communications team (James Maiden and Nanda Aprilia) for their publishing assistance.

Copy editor: Lisa Robins Reviewer: Susan E. Page Layout and publication: James Maiden and Nanda Aprilia

This research was carried out in collaboration with the governments of Australia and Indonesia, but the analysis and findings presented in this paper represent the views of the authors and do not necessarily represent the views of those governments. Any errors are the authors’ own. The paper constitutes a technical scientific working paper and, as such, there is potential for future refinements to accommodate feedback and emerging evidence.

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EXECUTIVE SUMMARY Tropical peatlands and tropical peat swamp forests are among the most challenging and relevant ecosystems to monitor, as required by Reducing Emissions from Deforestation and forest Degradation (REDD+). The logistical difficulties associated with implementing monitoring systems in tropical peatland means that few studies have considered the effect of different environmental conditions and disturbance regimes on peatlands’ forests.

Unlike most other forest types, in peatlands the soil stores more carbon than the forest vegetation. Peat carbon stores are important, but are difficult to measure. The forest vegetation inputs carbon to the peat and is integral to the protection, maintenance and long-term stability of peatlands. Studies such as this are essential to: •

Understand peatland forest dynamics including biomass accumulation, rate of regeneration, and species diversity under different environmental settings;

•

Determine the appropriate actions to protect and preserve peatlands and their forests; and,

•

Support emissions estimation, including for Indonesia’s National Carbon Accounting System.

To address this need, the Kalimantan Forests and Climate Partnership started a Vegetation Monitoring Program. The program aimed to quantify the biomass, structure and species composition of tropical peat swamp forests under different environmental and disturbance conditions. To do this, 96 plots were established at eight locations covering different environmental conditions and disturbance histories. Five of these locations were situated adjacent to canals that formed part of the extensive Ex-Mega Rice Project canal system in Central Kalimantan, Indonesia. Trees within each plot were measured annually for the diameter at breast height, height and species of seedlings, saplings, poles and trees. The fire history, hydrology, peat depth and light intensity for each plot were also recorded. The program ran for four years to allow for analysis of change.

The results of the study showed the range of forest conditions and dynamics across the KFCP site—an area which cover parts of the heavily degraded Block A and the relatively intact Block E forest areas of the ExMega Rice Project—with forests ranging from relatively undegraded, to regenerating, to severly degraded.

The results also show the influence that environmental conditions and disturbance history have on these forest states. For example, occurance of a single fire event dramatically affects forest structure, with subsequent fires having a less marked effect. Furthermore, the forest regeneration and composition is limited in Block A due to the altered hydrology, and also the newly open-canopy.

The study identifies optimal water table depths for future canal blocking in Block A to promote forest regeneration. The study also indicated that, at least for vegetation, hydrology is less of a concern in Block E, which remains less impacted by drainage. The data show the importance of protecting deep peat areas, preventing fire in forested areas and the need for shade-cover for successful regeneration of most tree species.

The Vegetation Monitoring Program represents a first step in the work necessary to estimate changes in forest biomass, regeneration rates, biodiversity and emissions, especially with regard to altered environmental conditions. Future studies should aim to develop and maintain this level of monitoring, allowing long-term analyses of the rates of change and responses to implementation activities that are aimed at protection of forest and peat carbon stocks, as well as of biodiversity.

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CONTENTS ACKNOWLEDGEMENTS ............................................................................................................................. i EXECUTIVE SUMMARY ............................................................................................................................. ii CONTENTS .............................................................................................................................................. iii ABBREVIATIONS....................................................................................................................................... v LIST OF TABLES ....................................................................................................................................... vi LIST OF FIGURES..................................................................................................................................... vii 1

2

3

INTRODUCTION ............................................................................................................................... 1 1.1

Project background ................................................................................................................... 1

1.2

Aims and principles of monitoring in REDD+............................................................................... 3

1.3

Tropical peat swamp forest vegetation ...................................................................................... 3

1.4

Objectives ................................................................................................................................. 5

METHODS ........................................................................................................................................ 6 2.1

Study site .................................................................................................................................. 6

2.2

Plot locations ............................................................................................................................ 6

2.3

Plot design and layout ............................................................................................................... 8

2.4

Methods for measuring environmental conditions ..................................................................... 9

2.5

Analysis .................................................................................................................................. 11

RESULTS ........................................................................................................................................ 12 3.1

3.1.1

Seedling, sapling, pole and tree densities.................................................................................. 13

3.1.2

Basal area .................................................................................................................................. 15

3.1.3

Species number .......................................................................................................................... 17

3.2

5

The influence of environmental conditions on forest characteristics ......................................... 19

3.2.1

Fire history ................................................................................................................................. 19

3.2.2

Hydrology—average annual water table .................................................................................. 21

3.2.3

Peat depth ................................................................................................................................. 25

3.2.4

Light intensity ............................................................................................................................ 28

3.3 4

Forest characteristics across the KFCP area .............................................................................. 12

Changes in the forest characteristics over time ........................................................................ 33

DISCUSSION ................................................................................................................................... 41 4.1

Forest characteristics............................................................................................................... 41

4.2

Influence of environmental conditions on forest characteristics ............................................... 42

4.3

Changes in forest characteristics over time .............................................................................. 44

OVERALL DISCUSSION AND CONCLUSIONS...................................................................................... 45

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6

REFERENCES .................................................................................................................................. 46

7

APPENDIX ...................................................................................................................................... 48 7.1

Tree species list ....................................................................................................................... 48

7.2

Tree species list ....................................................................................................................... 57

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ABBREVIATIONS cm

centimetre

CO2

Carbon dioxide

DBH

Diameter at breast height

DFC

Distance from canal

EMRP

Ex-Mega Rice Project

FMP

Forest monitoring plot

FMTeam

Fire management team

GHG

Greenhouse gas

GIMP

GNU Image Manipulation Program

GIS

Geographic information system

GPS

Global positioning system

Gt

Gigatonnes

ha

Hectare

IAFCP

Indonesia-Australia Forest Carbon Partnership

INCAS

Indonesian National Carbon Accounting System

IPCC

Intergovernmental Panel on Climate Change

KFCP

Kalimantan Forests and Climate Partnership

km

Kilometre

m

Metre

MRV

Measurement, reporting and verification

Mt

Megatonne

PHM

Peat and hydrology monitoring

PHTeam

Peat and hydrology monitoring team

PSF

Peat swamp forest

REDD+

Reducing Emissions from Deforestation and forest Degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries.

REL

Reference emission level

TPSF

Tropical peat swamp forest

UNFCCC

United Nations Framework Convention on Climate Change

VA

Village agreement

VMTeam

Vegetation monitoring team

WTD

Water table depth

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LIST OF TABLES Table 2.1: FMP locations, codes and descriptions .............................................................................................. 6 Table 2.2: The nested plot sizes and plant measurements there-in ................................................................... 8 Table 3.1: The environmental conditions found at each location..................................................................... 12 Table 3.2: The annual minimum, average and maximum water table depth in 2011 as observed in the forest FMPs ................................................................................................................................................ 22 Table 3.3: Years in which each FMP location was measured, with explanation ............................................... 33 Table 7.1: Tree species presented for all locations, as per tree maturity ......................................................... 48 Table 7.2: Species dominance (top five most dominant species shown) with respect to location, distance from canal (where relevant) and tree maturity stage. .................................................................... 57

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LIST OF FIGURES Figure 1.1: Map of KFCP site................................................................................................................................ 2 Figure 2.1: Map depicting the locations of FMPs L1-L8 ...................................................................................... 7 Figure 2.2: Nested plot design ............................................................................................................................. 8 Figure 2.3: Arrangement of FMPs at each canal-associated location (L2, L3, L4, L5, L6), in relation to canal ... 9 Figure 2.4: The layout of FMPs associated with hydrology transect KF-21 (L1, L7, L8) ...................................... 9 Figure 2.5: Locations of light intensity recording within the nested FMP ........................................................ 10 Figure 3.1: Average densities of seedlings, saplings, poles and trees at each forest monitoring location and, where relevant (L2–L6), with regard to DFC .................................................................................. 14 Figure 3.2: Average basal area of saplings, poles and trees at each forest monitoring location and, where relevant (L2–L6), with regard to DFC ............................................................................................. 16 Figure 3.3: Cumulative number of species for seedlings, saplings, poles and trees at each forest monitoring location and, where relevant (L2–L6), with regard to DFC ............................................................ 18 Figure 3.4: The average density of seedlings, saplings, poles and trees, in relation to the total number of fire events for each FMP ...................................................................................................................... 20 Figure 3.5: The average basal area of all individuals in relation to the total number of fire events for each FMP ................................................................................................................................................ 21 Figure 3.6: The average total number species in relation to the total number of fire events for each FMP ... 21 Figure 3.7: The average density of seedlings, saplings, poles and trees, in relation to the average annual (2011) WTD for each FMP .............................................................................................................. 23 Figure 3.8: The average basal areas for saplings, poles and trees, in relation to the average annual (2011) WTD for each FMP ......................................................................................................................... 24 Figure 3.9: The average cumulative number of species for all individuals, in relation to the average annual (2011) WTD for each FMP .............................................................................................................. 24 Figure 3.10: Influence of peat depth on seedling, sapling, pole and tree densities per ha .............................. 26 Figure 3.11: Influence of peat depth on average basal area (m2 per ha) for all individuals ............................. 27 Figure 3.12: Influence of peat depth on cumulative species number for all individuals .................................. 27 Figure 3.13: Influence of light intensity, 1 m above ground, on seedling, sapling, pole and tree densities per ha ............................................................................................................................................. 29 Figure 3.14: Influence of light intensity, 1 m above ground, on average basal area (m2 per ha) for all individuals ...................................................................................................................................... 30 Figure 3.15: Influence of light intensity, 1 m above ground, on cumulative species number for all individuals 30 Figure 3.16: Influence of light intensity, at ground level, on seedling, sapling, pole and tree densities per ha31 Figure 3.17: Influence of light intensity, at ground level, on average basal area (m2 per ha) for all individuals 32 Figure 3.18: Influence of light intensity, at ground level, on cumulative species number for all individuals ... 32

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Figure 3.19: Change in individual density, basal area and cumulative species number over time for each tree maturity growth stage, for Locations 1, 7 and 8 ............................................................................ 35 Figure 3.20: Change in individual density, basal area and cumulative species number over time for each tree maturity growth stage, for Location 2 with regard to DFC ............................................................ 36 Figure 3.21: Change in individual density, basal area and cumulative species number over time for each tree maturity growth stage, for Location 3 with regard to DFC ............................................................ 37 Figure 3.22: Change in individual density, basal area and cumulative species number over time for each tree maturity growth stage, for Location 4 with regard to DFC ............................................................ 38 Figure 3.23: Change in individual density, basal area and cumulative species number over time for each tree maturity growth stage, for Location 5 with regard to DFC ............................................................ 39 Figure 3.24: Change in individual density, basal area and cumulative species number over time for each tree maturity growth stage, for Location 6 with regard to DFC ............................................................ 40

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1 INTRODUCTION 1.1 Project background Indonesia has taken a leading role among developing countries in exploring how to reduce greenhouse gas (GHG) emissions through REDD+ (Reducing Emissions from Deforestation and forest Degradation 1 ) initiatives. In mid-2009, Australia and Indonesia established the Kalimantan Forests and Climate Partnership (KFCP) and the Indonesia-Australia Forest Carbon Partnership (IAFCP) under a partnership between both governments, to undertake a REDD+ demonstration activity in peat swamp forest (PSF) in Central Kalimantan province, Indonesia.

The activities carried out by KFCP took place in an area of approximately 120 000 hectares (ha) of tropical peatlands. The southern section (approximately 50 000 ha) was located in the north-east corner of Block A and the northern section (approximately 70 000 ha) was located centrally within Block E of the Ex-Mega Rice Project (EMRP) in Central Kalimantan (Figure 1.1). Up until the implementation of the Mega Rice Project in 1995, the project area was covered by PSF, but is now bisected by a major canal, with the two sections of land differing in terms of level of disturbance and forest quality. Block E has one 12 kilometre (km) long canal running north–south that impacts upon its hydrology, and has been subjected to both concession logging (1980s–1998) and illegal logging resulting in numerous small hand-built canals that also drain the peat.

Relative to the extensive canal establishment that has occurred in Block A, however, large sections of the Block E forest remain relatively undisturbed. Block A is criss-crossed by a network of canals 6–10 metres (m) wide with two large 30 m wide canals dividing Block A from Block E. Almost all of Block A, apart from about 5 000 ha, has been either deforested or the forest has been very badly degraded. Fourteen community settlements are located in the KFCP area along the Kapuas River. These settlements form nine village administrative units (desa) 2 that are spread among two sub-districts (kecamatan) within the Kapuas district (kabupaten).

KFCP program activities since 2009 have included assistance to formulate Five-year Village Development Plans, opportunities for direct income-generating benefits from small-scale reforestation and rehabilitation activities, alternative livelihoods activities, an extensive peatland monitoring program (including fire management and monitoring), village-level capacity building, self-management and implementation activities under Village Agreements (VAs) between villages and the program, and educational activities.

To build a model for estimating GHG emissions from tropical peatlands, and, depending on the interventions implemented, to assess the effect of any physical interventions and social activities, KFCP required a core peatland monitoring unit to assess the changes in the local environment. This was essential for developing methodologies for calculate GHG emissions from tropical peat swamp forests (TPSF) where vast quantities of carbon are stored but where there are few developed practices for monitoring and calculating emissions from this ecosystem. To this end, KFCP established the Vegetation Monitoring team (VMTeam), the Fire Management Monitoring team (FMTeam), and the Peat and Hydrology Monitoring team (PHTeam).

1

... and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries.

2

During the monitoring study period (2010–mid-2013) there were only seven villages made up from 14 hamlets. In July 2013 two of the villages were jurisdictionally split into two, resulting in nine villages.

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Figure 1.1: Map of KFCP site

N.B. In July 2013 two of the ‘jurisdictional villages’ that bordered the KFCP study area, Katunjung and Tumbang Muroi, separated and became four villages, Tumbang Mangkutup and Katunjung, and Tumbang Muroi and Lapetan, respectively. As the activities described in this report occurred when the villages had not yet separated (2012), only seven villages are represented here.

Source: KFCP

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1.2 Aims and principles of monitoring in REDD+ REDD+ initiatives aim to reduce carbon emission levels by incentivising efforts to avoid actions which, had they continued as usual, would likely have contributed to the release of carbon into the atmosphere.

Methods to reduce emissions include implementing national and local policies and regulations, and establishing programs and projects for Measurement, Reporting and Verification (MRV), which is required to assess emissions. These can then be compared to a Reference Emission Level 3 (REL, a type of baseline) to determine if emissions reductions have been achieved.

The Intergovernmental Panel on Climate Change (IPCC) divides ecosystems into five carbon pools (the five areas where carbon is found within an ecosystem). The change of carbon in each of these pools can then be used to estimate emisions. These carbon pools are aboveground biomass (e.g. the biomass of trees, shrubs, etc.), belowground biomass (roots), dead wood, litter and soil (mineral and organic). The methods used for estimating the change in carbon stocks are determined by individual countries. For REDD+, the United Nations Framework Convention on Climate Change (UNFCCC) requires the use of remote sensing and ground data. Indonesia has developed the Indonesian National Carbon Accounting System (INCAS) to do this. 4

1.3 Tropical peat swamp forest vegetation Peatlands are formed when the rate of input of organic material exceeds the rate of decomposition under waterlogged, anaerobic conditions. This leads to the accumulation of partially-decomposed organic matter (i.e. peat) which, in the tropics, can sometimes reach a thickness in excess of 15 m (Page et al. 2011).

Tropical peatlands cover 0.3% of the Earth’s land area but, owing to the thickness of many deposits, they contain a large carbon store of 82–92 Gt (Page et al. 2011), equivalent to 3.5% of the global vegetation and soil carbon pool (Amthor et al. 1998) and 15–19% of the global peatland carbon store (Gorham 1991; Immirizi et al. 1992). Tropical peatlands are found in the Caribbean, South and Central America, Africa and mainland Asia, but the majority (56% by area) are in Southeast Asia, with 47% of the total area (206 950 km2) occurring in Indonesia alone (Page et al. 2011). Indonesia’s peatlands are found mainly in Sumatra, Kalimantan and West Papua, where they form extensive domes in coastal and sub-coastal lowland locations, and the vast majority are ombrotrophic (i.e. rainfed and thus very low in available plant nutrients). They contain a carbon store of 57 Gt, which comprises 74% of Indonesia’s total forest soil carbon pool (Page et al.

2011). In addition to carbon storage, they also provide a range of other environmental services: support floral and faunal biodiversity, including several habitat endemics (Posa et al. 2011); stabilise hydrological and nutrient cycling systems (Wösten et al. 2006, 2008); and provide a means of livelihood for local communities (Sjarkowi 2002).

In recent decades, PSF has been logged for timber, drained and converted to palm oil and pulpwood plantations, or used for other agricultural projects, such as the failed EMRP in Central Kalimantan (Muhamad and Rieley 2001; Furniss 2006; Potter and Lee 1998). Between 1985 and 2006 about 47% (121 000 km2) of Southeast Asia’s PSF became degraded or converted to agricultural use (Hooijer et al. 2010) and at 2014 only 4% of the PSFs in Sumatra and Kalimantan remain in a near-pristine condition, with 37% classified as degraded forest (i.e. impacted by logging), 24% deforested and/or burnt, and 32% under some form of 3

Establishing a REL requires estimating past emissions levels and developing estimates of emissions for the future. The country then estimates emissions for the current year, aiming for this level to be lower than the previous calculated years. The REL is therefore the aimed for, or achieved, lower emissions level.

4 For further information see Reducing emissions from deforestation and degradation in Indonesia. IFCA Consolidation report.

Ministry of Forestry of the Republic of Indonesia, IPCC (2000) Emissions Scenarios. In Nakicenovic, N. and R. Swart (eds). Cambridge University Press, UK.

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agricultural use (Miettinen and Liew 2010). In PSF the forest vegetation and the peat are strongly interdependent (Page et al. 1999) thus, when the forest is removed, peat accumulation ceases. Logging and drainage cause direct changes to forest structure and composition (van Eijk et al. 2009); they also enhance aerobic decomposition of the peat and increase the risk of wildfire. Fires combust both the biomass and also, where the peat is sufficiently de-watered, the surface peat to depths of 30–50 cm (Page et al. 2002; Ballhorn et al. 2009). Drainage increases the risk of dry season drought, while surface subsidence, a consequence of peat de-watering, biological oxidation and combustion, can increase the risk of semipermanent (wet season) or permanent flooding (Page et al. 2009). The greater the level and frequency of disturbance, the more likely that peat wastage, fire, drought and flooding will follow (Page et al. 2009).

The net result of tropical peatland degradation is that species-diverse PSF is replaced by a variety of less biodiverse secondary communities. Following low levels of disturbance, forest regrowth will occur, but following more severe and/or regular disturbance, the re-establishment of woody species is retarded, while at extreme levels of degradation (severity and frequency), woody vegetation is replaced by herbaceous vegetation like ferns (Page et al. 2009; Giesen 2004; van Eijk et al. 2009). In addition to a reduction in biodiversity, PSF degradation also leads to the loss of most, if not all, ecosystem services, including carbon storage and hydrological regulation (Page et al. 2009). For example, Hooijer et al. (2010) estimate that the CO2 emissions arising from peat oxidation in drained peatlands in Southeast Asia are in the range 355–874 Mt CO2 yr-1. At least one-third of these emissions is associated with degraded peatlands (i.e. deforested and drained land but with no current economic use). Additional emissions of a similar magnitude are associated with wildfires, with degraded peatlands, particularly in Indonesia, identified as the foremost source (Langner et al. 2007; Langner and Siegert 2009; Page et al. 2002; van der Werf et al. 2008). Total emissions from Indonesian peatlands (including those from peat oxidation and fire plus loss of biomass and debris) from 2000 to 2006 are estimated at 640 Mt CO2 yr-1, equivalent to 2.1% of current annual global fossil fuel emissions (Boer et al. 2010).

Unlike other forest ecosystems the main carbon stores of tropical peatlands are found in the peat, with a smaller percentage being stored aboveground in the forest biomass (Page et al. 2011). Consequently, peat rehabilitation and protection are the key objectives for REDD+ activities on tropical peatlands (Alexander et al. 2011; IAFCP 2009). Due to the inter-dependent relationship of peat and the aboveground TPSF, the forest must also be monitored and protected because: -

The forest contributes to the total carbon storage of the ecosystem (Page et al. 2011).

-

The root system of the forest, in addition to substantially contributing to soil organic matter and consequently to peat accumulation (Brady 1997), also theoretically holds the peat in place, reducing erosion and subsidence rates.

-

The forest protects and controls the hydrology of the ecosystem, supporting high water tables which reduce peat decomposition rates (Dommain et al. 2010).

-

The continual input of leaf litter from the forest canopy adds to the supply of organic material available for peat formation and increases the overall peat volume/carbon stocks (Page and Rieley 2005).

-

The forest contributes directly to the high biodiversity of tropical peatlands (and faunal and floral diversity are also criteria for REDD+ activities) (Posa et al. 2011).

In their natural condition, tropical peatlands are notoriously heterogeneous. At a local scale, different forest sub-types occur across individual peat domes in response to changing peat thickness, hydrology, nutrient availability and land use (Anderson 1964; Page et al. 1999; Miyamoto et al. 2003). In their natural state,

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tropical peatlands have high water tables, just above or below the peat surface for most of the year (Wรถsten et al. 2008). Once the peat is saturated, excess water flows radially across the surface of the peat dome into local waterways and the convex shape of the peat surface prevents flooding from adjacent riverine or marine systems (Rieley and Page 2005). When an intact peatland is disturbed, for example as a result of forest degradation or loss, drainage and/or fire, the effects include changes in the microclimate (higher temperatures, reduced humidity and altered light levels), lowering of surface water levels and increasing speed of water run-off, reduction or loss of the hummock-hollow topography, peat surface compaction and subsidence, and loss of plant nutrient stocks, both from the forest biomass and the uppermost peat layer (Page et al. 2009; Notohadiprawiro 1997; Rieley and Page 2005). All these factors can influence the regeneration and state of the subsequent forest.

1.4 Objectives The Vegetation Monitoring program was started with the aim of improving the estimation of carbon stocks and emissions from peatland in the KFCP area, and for developing and improving monitoring methods that can be applied elsewhere.

Main objectives: -

To determine the key forest characteristics (densities, basal areas and species numbers for seedlings, saplings, poles and trees) across the KFCP study site, with the purpose of describing the forest conditions across a range of environmental and disturbance histories.

-

To use these data to better describe changes in forest characteristics over time, and the influence of a range of environmental conditions on these forest characteristics.

-

To use these findings to discuss the overall contributions of the forest vegetation to the carbon biomass of the system, to assess how this is influenced by environmental conditions, and how this may change in response to REDD+ implemenation activities.

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2 METHODS 2.1 Study site See Section 1.1.

2.2 Plot locations A series of Forest Monitoring Plots (FMPs) were established at selected locations across the KFCP study site.

Eight locations were chosen as representative of the forest types within the study site, based on previous ecological and forestry studies conducted in the area 5 (described in Table 2.1, and presented in Figure 2.1).

Table 2.1: FMP locations, codes and descriptions

FMP Location Code L2 L3 L4 L5 L6 L7 L8 L1

FMP location Block A, compartment M1, running south from SP2 Block A, compartment C2, running south from upper E-W canal Block A, compartment B2, running south from upper E-W canal Block A, compartment C7, running south from upper E-W canal Block E, running west from canal SPU7, at position where KF21 meets SPU7 Block E, along western-third of KF21

Forest Description Burnt in 2009

Block E, along central-third of KF21

Forested, deep peat

Block E, along eastern-third of KF21

Disturbed forest, mid-depth peat

Disturbed, forested, deep peat compartment Disturbed, semi-forested, deep peat compartment Degraded, non-forested, shallowpeat compartment Forested, canal-disturbed, deep peat Forested, deep peat

5

BOS-Mawas KFCP Report Phase II, Wetlands KFCP Report on Land Cover Assessment, Master Plan KFCP Strategic Peatland Rehabilitation Plan.

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Figure 2.1: Map depicting the locations of FMPs L1-L8

Source: KFCP

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2.3 Plot design and layout Plots were based on a nested plot design (Table 2.2, Figure 2.2).

Table 2.2: The nested plot sizes and plant measurements there-in

Plant classification

Size description

Plot size

Tree

DBH > 20 cm

32 x 32 m

Pole

20 cm > DBH > 10 cm

16 x 16 m

Sapling

10 cm > DBH, height > 1.5 m

8x8m

Seedling

height < 1.5 m

2x2m

N.B. DBH = Diameter at breast height

Figure 2.2: Nested plot design

At each location associated with a canal (L2, L3, L4, L5, L6), three transects were established that ran perpendicular to the canal and parallel to the hydrology transects, and the route by which the LiDAR flight would take (facilitating increased data transfer) (Figure 2.3). Along each transect, four plots were established, at 50 m, 100 m, 400 m and 700 m from the canal, thus reaching near to the centre of each compartment.

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Figure 2.3: Arrangement of FMPs at each canal-associated location (L2, L3, L4, L5, L6), in relation to canal

Note: DFCâ&#x20AC;&#x201D;Distance from canal

Three locations were not associated with canals: L1, L7 and L8. These were positioned along the KF-21 hydrology transect, representing different sections of the relatively undisturbed, closed-canopy forest. For each of these locations 12 plots were established under a similar design to the canal-associated locations, but running parallel to the hydrology transect KF-21 (Figure 2.4).

Figure 2.4: The layout of FMPs associated with hydrology transect KF-21 (L1, L7, L8)

N.B. DFS - distance from start.

2.4 Methods for measuring environmental conditions The following methods were used to monitor the environmental conditions in the FMPs so as to facilitate exploration of the relationships between local environment and forest characteristics.

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Fire history: Data on the number of fire events that had occurred at each FMP were collated by KFCPâ&#x20AC;&#x2122;s geographic information system (GIS) specialist.

Hydrology, peat depth and subsidence: Using the data collected from the dip-wells and subsidence poles established by the KFCP Peat and Hydrology Monitoring team (PHMTeam), the maximum, minimum and average water table, and the peat depth for each year of forest measurement was obtained for each FMP. All FMPs were established in the vicinity of the PHM transects, and data from the nearest dip-well for each forest plot were used.

Light intensity: Light intensity was measured indirectly. The percentage canopy cover at each position was recorded as a proxy for light intensity. To achieve this, a digital camera was set-up on a flat surface (using a tripod with spirit-level) and photographs were taken, first at 1 m above the ground, then at ground level.

This was done for each height within each plot, with four replicate locations for each plot (Figure 2.5). Each location was GPS-recorded, in order to return to the same spot in future years. The photos taken were converted to percentage of black and white pixels using a basic photo analysis package, GIMP (GNU Image Manipulation Program) and the percentage of white pixels was used as a proxy of percentage of open canopy.

Figure 2.5: Locations of light intensity recording within the nested FMP

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2.5 Analysis Forest vegetation data from each FMP were used to calculate the individual densities per ha, basal area (m2 per ha) and species number per FMP for seedlings (excluding basal area), saplings, poles and trees. These data were used to calculate the average and standard deviation of the forest characteristics for each location (L1, L7 and L8; 12 replicate plots per location) or for location and distance from canal (L2, L3, L4, L5 and L6; 3 replicate plots per location). These results were then represented graphically for all locations, so as to describe forest characteristics across the KFCP area (Section 3.1).

For each individual FMP, a range of environmental conditions was recorded (see above). Light intensity and water table depth (WTD) are continuous data sets, while data on fire history (number of recorded fire events) is discrete. The continuous data were split into appropriate discrete ranges to facilitate data presentation in the form of bar charts. The FMPs (and the forest characteristics associated with that FMP) were then sorted based on their related environmental condition data into the appropriate environmental data/range. The average forest characteristic for each environmental range was then calculated and presented graphically (Section 3.2).

Forest vegetation data were collected annually for up to 4 years. The average and standard deviation forest characteristics for each tree maturity stage was calculated as described above with regard to Section 3.1.

This average and standard deviation was calculated for each location and with regard to distance from canal.

The data were then presented graphically for each year (Section 3.3).

Statistical analysis was not carried out on these data as the aim was to provide a qualitative description of the forest plots and to determine trends and relationships. A scientific article based on this work is intended to be published in the next year in a peer-reviewed journal, and this will provide a more rigorous data analysis.

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3 RESULTS 3.1 Forest characteristics across the KFCP area Using the data collected, the individual densities for all tree maturities, their total species numbers and basal areas were calculated for seedlings, saplings, poles and trees for each of the 8 locations and, where relevant, with respect to distance from canal (L2, L3, L4, L5 and L6). The results are presented in the following three sub-sections, 3.1.1–3.1.3. The data presented here were collected in 2010, at the start of KFCP’s vegetation monitoring program. Rates of change in all these variables during the 3.5 years of study are shown in Section 3.3. Many of the trends observed in the forest characteristics across the locations can be explained by the prevailing environmental conditions. These relationships are explored in more depth in Section 3.2, with a brief overview of the environmental conditions at each location presented below (Table 3.1). Note that the environmental data used in this report are mainly for 2011, based on availability of complete annual data sets (see Section 3.2 for further details).

Table 3.1: The environmental conditions found at each location Location

L2 L2 L2 L2 L3 L3 L3 L3 L4 L4 L4 L4 L5 L5 L5 L5 L6 L6 L6 L6 L1 L7 L8 a

Distance from canal (m) 50 100 400 700 50 100 400 700 50 100 400 700 50 100 400 700 50 100 400 700 N/A N/A N/A

Average no. of fire a events 6 5 4 4 1 1 1 0 1 1 0 0 3 3 2 2 0 0 0 0 0 0 0

Average water table b depth (cm) -23.41 -23.41 -23.41 -23.41 -61.31 -49.99 -42.29 -50.88 -52.06 -40.19 -40.16 -43.66 -41.81 -43.06 -23.41 -24.64 -79.65 -87.91 -55.47 -49.25 7.63 -32.76 -39.67

Peat depth c (m) 8.22 8.22 8.22 8.22 6.67 6.78 7.70 7.60 6.53 6.58 7.25 6.86 6.82 7.33 7.73 7.20 8.14 8.11 8.25 7.32 9.64 9.69 12.23

Average light intensity at 1 m d height (%) 100.00 99.69 96.38 74.19 64.21 14.29 29.36 11.00 70.47 67.20 9.37 9.19 97.25 100.00 53.13 59.31 11.13 8.45 7.54 7.16 9.36 7.31 7.40

Average light intensity at ground d level (%) 41.50 38.90 22.36 15.56 9.10 3.82 9.28 8.28 43.34 40.83 7.41 7.20 27.46 29.58 21.79 32.15 8.45 7.35 6.99 6.02 8.43 6.16 6.86

There was a unique number of fire events per forest monitoring plot, which was averaged across location and distance from canal

(L2–L6; n=3) and across location (L1, L7, L8; n=12). b

There was a unique water table depth average value per forest monitoring plot, calculated across approximately 12 measurements

through the year. These values were averaged across location and distance from canal (L2–L6; n=3) and across location (L1, L7, L8; n=12). Negative values indicate when the average water table depth was below the peat surface. c

Peat depth was measured at dipwells, and a single peat depth measurement was used for each location and distance from canal (n=1). d

Average light intensity was calculated per forest monitoring plot based on four light intensity points within the plots. These values

were averaged across location and distance from canal (L2–L6; n=3) and across location (L1, L7, L8; n=12).

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3.1.1 Seedling, sapling, pole and tree densities The results of the woody plant density counts highlight the large differences between the 8 locations and the differences in relation to distance from canal (Figure 3.1). Location 2 is potentially the most severely degraded location, being located adjacent to the large SP1 canal and burnt between 3–6 times. The vegetation here was dominated by seedlings, at 15 833 individuals/ha, with saplings only appearing at greater density at 700 m from the canal (156 individuals/ha) and with none present near the canal. There were no trees or poles. The main vegetation cover at this location was provided by ferns.

Locations 3 and 4 showed the greatest effect of distance from canal (DFC). At Location 3, while densities of woody indiividuals were high at 700 m from the canal (average 127 500, 18 854, 573 and 91 individuals/ha for seedlings, saplings, poles and trees, respectively) they were significantly lower with increasing proximity to the canal, i.e. at 400 m, 100 m and 50 m for all tree maturity stages (ranging from, on average, 0–20, 833, 260–7656, 0–13 and 7–29 individuals/ha for seedlings, saplings, poles and trees, respectively). The vegetation between 50–400 m from the canal had been burned at least once, while that at 700 m remained unburned. The densities of all growth stages found at 700 m were, in fact, comparable to those found in the relatively non-degraded Locations 7 and 8. Location 4 also showed the effect of DFC and of fire history. At this location there had been between 0–2 fires at distances 50 m and 100 m from the canal (with densities ranging from, on average, 27 500–30 000, 2865–4687, 130–234 and 10–20 individuals/ha for seedlings, saplings, poles and trees, respectively), but the vegetation between 400 m and 700 m remained unburned (with densities ranging from, on average, 54 167–101 667, 24 167–27 552, 586–599, 62–78 individuals/ha for seedlings, saplings, poles and trees, respectively). Locations 3 and 4 had similar hydrological conditions, therefore the higher densities of all growth stages at Location 4 highlight the key influence that fire has on forest growth and regeneration.

Location 5, similar to Location 2, had been burned 2–3 times, was situated on shallower peat and had been affected by hydrological disturbance. All these factors may have contributed to the overall low individual densities (ranging from, on average, 1667–25 833, 0–3021, 0–117 and 0 individuals/ha for seedlings, saplings, poles and trees, respectively) (see discussion in section 3.2). Interestingly, seedling density was higher at 50 m from the canal, suggesting favourable conditions for regeneration at this location.

Location 6 also shows an effect of proximity to the canal, but also has comparable individual densities to Locations 1, 7 and 8, all of which are in relatively less degraded forest (for Location 6 densities ranged from, on average, 18 333–68 333, 7031–23 177, 755–1042 and 17–108 individuals/ha for seedlings, saplings, poles and trees, respectively; for Location 1 average densities were 35 000, 20 339, 697 and 86; for Location 7 average densities were 52 500, 26 810, 1156 and 120; and for Location 8 average densities were 72 708, 53 529, 801 and 72 individuals/ha for seedlings, saplings, poles and trees, respectively). These three locations were all in areas where there was limited hydrological disturbance; Location 1 has slightly lower overall densities, while Location 8 has lower pole and tree densities and much higher sapling densities.

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Figure 3.1: Average densities of seedlings, saplings, poles and trees at each forest monitoring location and, where relevant (L2â&#x20AC;&#x201C;L6), with regard to DFC

a)

b)

c)

d)

e) Location

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3.1.2 Basal area Basal area is the measurement of the total area of a given section of land that is occupied by the crosssection of stems at breast height. It, therefore, only includes saplings, poles and trees in the measurement.

The plot biomass values are yet to be calculated because of the uncertainties associated with the wood density mathematical constant; consequently, the basal area data will be used as a proxy.

As would be expected, the basal area trends are similar to those seen for individual densities (Figure 3.2).

Locations 2 and 5 have low basal areas (0.2 m2 ha-1 at 700 m from the canal and 5.2 m2 ha-1 at 400 m from the canal, respectively). The basal area data also show an effect of DFC. Location 3 had a high basal area at 700 m from the canal (25.1 m2 ha-1); however, all distances closer to the canal had low basal areas. Similarly, Location 4 had a basal area of approximately 6 m2 ha-1 at both 50 m and 100 m from the canal, and then greater than 25 m2 ha-1 at 400 m and 700 m from the canal. The basal areas for Location 6 were also affected by distance from canal, with approximately 25 m2 ha-1 at 50 m and 100 m from the canal and 35 m2 ha-1 at 400 m and 700 m from the canal. Only Location 6 attained basal areas similar to those in Location 7 (39.1 m2 ha-1) and Location 8 (36.8 m2 ha-1).

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Figure 3.2: Average basal area of saplings, poles and trees at each forest monitoring location and, where relevant (L2â&#x20AC;&#x201C;L6), with regard to DFC

a)

b)

c)

d) Location

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3.1.3 Species number The total cumulative species number across all locations in 2010 was 104. Interestingly, all locations, except Locations 2 and 5, had cumulative species numbers of between 70 and 80 (Figure 3.3). However, the effect of DFC (and related fire histories and individual densities) was still clear, with Locations 3, 4 and 6 all attaining greater species numbers at 400 m and 700 m from the canal, as compared to 50 m and 100 m.

Saplings represented the most species-diverse tree maturity stage.

See the Appendix (Table 7.1) to review the species found at each location; this provides both scientific and local names for the individuals found at each location, according to DFC and tree maturity stage.

The five most dominant species were calculated for each tree maturity stage, at each location, and with regard to DFC (Table 7.2). For Locations 2 and 5, where total individual count and also species number count were very low, the dominant species are classic pioneers for TPSF (e.g. Cratoxylum arborescens, Combretocarpus rotundatus, Antidesma spp. and Syzygium spp.). At Location 3, near the canal, similar dominant species are observed; however, after 100 m from the canal, a greater mix of species and dominance is observed. At 700 m the typical low dominances of undisturbed TPSF are observed, with no species attaining more than 25% dominance apart from Diospyros areolata, which attained 46% dominance for the tree maturity growth stage. For Location 4, and for all subsequent species this low species dominance is repeated again, with a wide range of species, from 50â&#x20AC;&#x201C;700 m from the canal. Species such as Stemonurus scorpioldes, Baccaurea bracteata, Rapanea borneensis, Campnosperma coriaceum, Garcinia spp. and Lithocarpus spp. appeared more restricted to closed-forest locations. Additionally, Combretocarpus rotundatus was often found to be dominant as a tree, but not as a seedling or sapling in closed-forest locations (L3â&#x20AC;&#x201C;700 m, L06, L07 and L08) suggesting the end of its role in the forest succession. For nearly all locations there is a notable lack of consistency in species dominance from seedling, to sapling, to pole, to tree maturity stages. This trend is more notable for the locations in Block A than Block E.

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Figure 3.3: Cumulative number of species for seedlings, saplings, poles and trees at each forest monitoring location and, where relevant (L2â&#x20AC;&#x201C;L6), with regard to DFC

I88

a)

b)

c)

d)

e) Location

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3.2 The influence of environmental conditions on forest characteristics For each individual FMP, a range of environmental conditions was recorded. These included peat depth (2010), fire history, hydrology and light intensity (collected 2011–2013, data presented from 2011). The influence of each of these environmental conditions on the FMP’s forest characteristics are presented and discussed below (Sections 3.2.1—3.2.4).

The descriptions of average forest characteristics presented in the following sections are the most likely characteristic values to be found for each environmental condition range, and do not link to specific locations. The focus of this section is not to go into detail regarding the forest characteristics for each environmental condition and range, although this can be viewed in the figures, but to understand the general influence that the altered environmental conditions have on the forest characteristics.

3.2.1 Fire history KFCP collected and analysed fire history data, based on satellite records and ground-truthing, to create a GIS map showing the fire history across the whole area. Using this information, the fire history (the number of ‘burns’ or ‘fire events’ to have occurred) was established for each FMP. There was a distinct and consistent relationship between fire history and the forest characteristics.

Graphically represented for all individuals, with the average and standard deviation shown for the different growth stages, it can be seen that after one or more fire events that the density of individuals at all growth stages (Figure 3.4), the basal area (Figure 3.5) and the number of species (Figure 3.6) significantly decrease.

Note, there were a total of 6 FMPs where 5 or 6 burns had occurred, and in which there were no individuals.

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Figure 3.4: The average density of seedlings, saplings, poles and trees, in relation to the total number of fire events for each FMP

Average seedling density(individuals per ha)

120,000 100,000 80,000 60,000 40,000 20,000

Average sapling density(individuals per ha)

0 45,000 40,000 35,000 30,000 25,000 20,000 15,000 10,000 5,000 0

Average pole density(individuals per ha)

1,200 1,000 800 600 400 200 0 140

Average tree density (individuals per ha)

120 100 80 60 40 20 0

0

1

2

3

4

5

6

Number of years when fire event was detected

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Figure 3.5: The average basal area of all individuals in relation to the total number of fire events for each FMP 45.0

Average basal area (m^2 per ha)

40.0 35.0 30.0 25.0 20.0 15.0 10.0 5.0 0.0

1

0

2 3 4 Number of years when fire event was detected

5

6

Figure 3.6: The average total number species in relation to the total number of fire events for each FMP

Average cumulative number of species

60 50 40 30 20 10 0

0

1

2

3

4

5

6

Number of years when fire event was detected

3.2.2 Hydrologyâ&#x20AC;&#x201D;average annual water table Hydrology data (water surface level in relation to peat surface level i.e. WTD) were collected at least monthly by KFCPâ&#x20AC;&#x2122;s PHMTeam. FMPs were established in the vicinity of the peat and hydrology monitoring transects to facilitate data transfer. The hydrological data collected were used to calculate minimum, maximum and average annual WTDs for each FMP, and to investigate the role of hydrology in influencing forest characteristics. In the analysis and discussion below, data from 2011 were used; 2011 was a relatively wet year with a short dry season; however, the analysis was also carried out for 2012 (with a much longer and drier dry season), and the same trends were observed (not shown).

Due to the differing hydrological disturbances between Block E (with only one large canal) and Block A (numerous canals forming a drainage network) the two blocks had distinct hydrological regimes (i.e. it was not just the minimum, average and maximum WTD that influenced the vegetation, but the way that the water moved within the peat in terms of rates, flows, pressures and fluxes). Consequently, the two blocks had to be treated separately for the analysis. For the range of hydrological conditions across the two blocks see Table 3.2.

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Table 3.2: The annual minimum, average and maximum water table depth in 2011 as observed in the forest FMPs for Block E (northern KFCP area with a single canal) and Block A (southern KFCP area with many canals)

Block

Minimum water table depth (cm)

Average water table depth (cm)

Maximum water table depth (cm)

E

140.50 to 6.30

87.90 to 20.31

54.70 to 41.40

A

110.60 to 58.80

61.30 to 23.41

37.70 to 9.10

Once the FMPs had been separated according to their location in either Block A or Block E, two clear trends could be established regarding the influence of hydrology on forest characteristics. These trends were similar regardless of whether the minimum, average or maximum annual WTDs were being analysed and, therefore, only the analysis of the influence of the average annual WTD on forest characteristics is presented and discussed below.

In Block E, a much wider range of average WTDs was present (88 to +20 cm) compared to Block A (61 to 23 cm). However, the densities of trees at different growth stages in Block E were less strongly influenced by the WTD than in Block A (Figure 3.7). In Block E, saplings showed greater densities at 50 to 30 cm WTD, with lower densities observed at WTD extremes. Poles and seedlings also showed some indication of this trend, but less strongly. Trees had slightly greater densities in wetter conditions, peaking at 0 to +10 cm WTD. All tree maturity stages had low densities at average WTDs lower than 60 cm, except for poles. There was a much smaller range of WTDs across Block A, as compared to Block E; however, the response of all tree growth stages to WTD, as indicated by the density data, was more significant. All tree maturity stages showed greater densities at 60 to 40 cm WTD, with low densities at other WTDs. There were similar trends regarding the average basal areas for saplings, poles and trees in response to WTD in both Block E and Block A (Figure 3.8). In Block E, saplings and poles had greater basal areas at the middle WTD ranges (approx. 60 to 20 cm); however, trees, again, had greater basal areas under wetter conditions (0 to +10 cm WTD). All tree maturity stages had reduced basal areas at WTDs below -60 cm, although this was much more significant for trees compared to saplings and poles. In Block A, the trend remained very similar to that for individual densities, with all tree maturity stages showing greater basal areas in the 60 to 40 cm WTD range, with low basal areas at all other WTDs. The trend for the average cumulative number of species per WTD range differed little between seedlings, saplings, poles or trees for Block E and Block A and, consequently, pooled data for all stages of tree maturity are presented (Figure 3.9). In Block E, there was little effect of WTD on cumulative species number. At the lowest WTD, 70 to 90 cm, the species number did decline; however, from 60 to +30 cm there is little significant change in species number. In Block A, the trend was repeated, in that species number was low across the range of WTD 70 to 20 cm apart from the range between 60 to 40 cm, over which the average cumulative species number peaked.

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Figure 3.7: The average density of seedlings, saplings, poles and trees, in relation to the average annual (2011) WTD for each FMP Average seedling density (individuals per ha)

160,000 140,000 120,000 100,000 80,000 60,000 40,000 20,000 0

Average sapling density (individuals per ha)

60,000 50,000 40,000 30,000 20,000 10,000 0

Average pole density (individuals per ha)

1,600 1,400 1,200 1,000 800 600 400 200 0

Average tree density (individuals per ha)

250 200 150 100 50 0

-90--80

-80--70

-70--60

-60--50

-50--40

-40--30

-30--20

-10-0

0-10

10-20

20-30

Average water table depth (cm)

N.B. Dark blue窶認MPs located within Block E, pale blue窶認MPs within Block A. Source: KFCP Vegetation Monitoring Database and KFCP Peat and Hydrology Monitoring data (managed by Deltares)

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Average sapling basal area (m2 per ha)

Figure 3.8: The average basal areas for saplings, poles and trees, in relation to the average annual (2011) WTD for each FMP 30.0 25.0 20.0 15.0 10.0 5.0 0.0

Average pole basal area (m2 per ha)

25.0 20.0 15.0 10.0 5.0 0.0

Average tree basal area (m2 per ha)

14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0

-90--80

-80--70

-70--60

-60--50

-50--40

-40--30

-30--20

-10-0

0-10

10-20

20-30

Average water table depth (cm)

N.B. Dark blue窶認MPs located within Block E, pale blue窶認MPs within Block A. Source: KFCP Vegetation Monitoring Database and KFCP Peat and Hydrology Monitoring data (managed by Deltares)

Average cumulative no. species, all individuals

Figure 3.9: The average cumulative number of species for all individuals, in relation to the average annual (2011) WTD for each FMP 60 50 40 30 20 10 0

-90--80

-80--70

-70--60

-60--50

-50--40

-40--30

-30--20

-10-0

0-10

10-20

20-30

Average water level depth (cm)

N.B. Dark blue窶認MPs located within Block E, pale blue窶認MPs within Block A. Source: KFCP Vegetation Monitoring Database and KFCP Peat and Hydrology Monitoring data (managed by Deltares)

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3.2.3 Peat depth Peat depth was recorded at over 800 locations throughout the KFCP area. The closest peat depth value for each FMP was established through the application of GIS data. In 2010 the peat depths located nearest to the FMP plots ranged from 6.5 m to 12.5 m. Across this range of peat depths there is a consistent trend for all forest characteristics, namely that with increasing peat depth there were increasing densities of individuals (Figure 3.10), basal area values (Figure 3.11) and species numbers (Figure 3.12). These trends were consistent for seedlings and saplings for all forest characteristics. This trend was consistent for poles and trees across the transition from ‘shallower’ peat (6.5–8.5 m) to ‘deeper’ peat (9.25–10.25 m), while for the transition from ‘deeper’ to ‘deepest’ peat (11.75–12.75 m) this effect was lost or even reversed (see Figure 3.10 for tree densities). Neither the trends nor values were significantly different between different tree maturity stages for average basal area and total species numbers, and thus only the ‘all individuals’ graphs are shown here.

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Figure 3.10: Influence of peat depth on seedling, sapling, pole and tree densities per ha 160,000 Average seedling density (individuals per ha)

140,000 120,000 100,000 80,000 60,000 40,000 20,000 0 80,000 Average sapling density (individuals per ha)

70,000 60,000 50,000 40,000 30,000 20,000 10,000 0 1,600 Average pole density (individuals per ha)

1,400 1,200 1,000 800 600 400 200 0 180 160 Average tree density (individuals per ha)

140 120 100 80 60 40 20 0

Peat depth (m)

N.B. Blank spaces indicate there are no FMPs at that peat depth range.

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2

Figure 3.11: Influence of peat depth on average basal area (m per ha) for all individuals 50.0 45.0

Average basal area (m^2/ha)

40.0 35.0 30.0 25.0 20.0 15.0 10.0 5.0 0.0

Peat depth(m)

N.B. Blank spaces indicate there are no FMPs at that peat depth range.

Figure 3.12: Influence of peat depth on cumulative species number for all individuals

Average cumulative number of species

60 50 40 30 20 10 0

Peat depth (m)

N.B. Blank spaces indicate there are no FMPs at that peat depth range.

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3.2.4 Light intensity Light intensity was recorded through the proxy method of taking photos of the canopy at 1 m above the ground and at ground level. The photos were converted into black and white pixilated images and the percentage of white pixels (percentage open canopy) was used to indicate percentage light intensity. These data were collected annually by the VMTeam at the same time that the vegetation data in the FMPs was collected. The data were analysed to show growth stage densities, basal area and cumulative species numbers against the range of light intensities for both 1 m above the ground and at ground level.

The overall trend across all forest characteristics, and at both levels, is that at high light intensities there were fewer individuals and lower basal areas and species numbers. There were, however, some further details of note.

At 1 m above the ground surface, individual densities (Figure 3.13), basal area (Figure 3.14) and species number (Figure 3.15) were all highest between 5–20% light intensity, peaking at 5–10%, with a notable absence at 0–5% light. At higher light intensities, values for all of these forest characteristics reduced to zero, the exception to this being seedling densities, which peaked at 15–20%, and also showed some densities for 75–95% light intensity.

For ground level light intensity, the relationship was even simpler, with individual densities (Figure 3.16), basal area (Figure 3.17) and species number (Figure 3.18) all highest at between 5–10% light intensity with decreasing values at higher light intensities, reducing to zero by 35% average light intensity. Thus optimal/sufficient light conditions for all growth stages were observed where canopy closure was highest.

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Figure 3.13: Influence of light intensity, 1 m above ground, on seedling, sapling, pole and tree densities per ha

Average seedling density (individuals per ha)

120,000 100,000 80,000 60,000 40,000 20,000 0 50,000 Average sapling density (individuals per ha)

45,000 40,000 35,000 30,000 25,000 20,000 15,000 10,000 5,000 0 1,200

Average pole density (individuals per ha)

1,000 800 600 400 200 0 140

Average tree density (individuals per ha)

120 100 80 60 40 20 0

0-5

5-10

10-15

15-20

25-30

30-35

35-40

50-55

65-70

70-75

75-80

85-90

90-95 95-100

Average light intensity 1 m above ground, percent

N.B. Blank spaces indicate there are no FMPs at that light intensity range.

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2

Figure 3.14: Influence of light intensity, 1 m above ground, on average basal area (m per ha) for all individuals

Average basal area (m^2 per ha)

60 50 40 30 20 10 0

0-5

5-10

10-15

15-20

25-30

30-35

35-40

50-55

65-70

70-75

75-80

85-90

90-95

95-100

Average light intensity 1 m above ground, percent

N.B. Blank spaces indicate there are no FMPs at that light intensity range.

Figure 3.15: Influence of light intensity, 1 m above ground, on cumulative species number for all individuals

Average cumulative number of species

50 45 40 35 30 25 20 15 10 5 0

0-5

5-10

10-15

15-20

25-30

30-35

35-40

50-55

65-70

70-75

75-80

85-90

90-95

95-100

Average light intensity 1 m above ground, percent

N.B. Blank spaces indicate there are no FMPs at that light intensity range.

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Figure 3.16: Influence of light intensity, at ground level, on seedling, sapling, pole and tree densities per ha

Average seedling density (individuals per ha)

120,000 100,000 80,000 60,000 40,000 20,000 0 45,000 Average sapling density (individuals per ha)

40,000 35,000 30,000 25,000 20,000 15,000 10,000 5,000 0

Average pole density (individuals per ha)

1,200 1,000 800 600 400 200 0 140

Average tree density (individuals per ha)

120 100 80 60 40 20 0

0-5

5-10

10-15

15-20

20-25

25-30

30-35

35-40

40-45

45-50

50-55

55-60

60-65

>65

Average light intensity, at ground level, percent

N.B. Blank spaces indicate there are no FMPs at that light intensity range.

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2

Figure 3.17: Influence of light intensity, at ground level, on average basal area (m per ha) for all individuals 45.0

Average basal area (m^2/ha)

40.0 35.0 30.0 25.0 20.0 15.0 10.0 5.0 0.0

0-5

5-10

10-15

15-20

20-25

25-30

30-35

35-40

40-45

45-50

50-55

55-60

60-65

>65

Average light intensity, at ground level, percent

N.B. Blank spaces indicate there are no FMPs at that light intensity range.

Figure 3.18: Influence of light intensity, at ground level, on cumulative species number for all individuals

Average cumulative number of species

60 50 40 30 20 10 0

0-5

5-10

10-15

15-20

20-25

25-30

30-35

35-40

40-45

45-50

50-55

55-60

60-65

>65

Average light intensity, at ground level, percent

N.B. Blank spaces indicate there are no FMPs at that light intensity range.

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3.3 Changes in the forest characteristics over time The forest characteristics (individual densities, basal areas and cumulative species numbers for seedlings, saplings, poles and trees) were calculated for each location, and with regard to DFC, where relevant, for the 3.5 years of study (Table 3.3). These data were then represented graphically (Figures 3.19 to 3.24).

Table 3.3: Years in which each FMP location was measured, with explanation

Block

Adjacent to Location a canal?

2010

2011

2012

2013

A

Yes

All locations measured

All locations measured excluding L1 (L1 fell within jurisidictional area of village that ended VA with KFCP)

All locations measured excluding L1 and L2 (L1 and L2 fell within jurisidictional area of village that ended VA with KFCP)

Not measured (outside VA)

L2 L3 L4 L5 L6

E

No

Measured Measured Measured Not measured (KFCP vegetation monitoring program ended)

L1

Not measured (outside VA)

L7

Not measured (KFCP vegetation monitoring program ended)

L8

Not measured (KFCP vegetation monitoring program ended)

Note: VA â&#x20AC;&#x201C; Village Agreement; data had to be collected in agreement with villages

Two key points were observed. Firstly, variation within the FMPs for each location (and with DFC) was often greater than any change over time. Secondly, three to four years of study was a short period of time, from a forestry perspective, especially for monitoring the growth of poles and trees. These two points meant that while some changes over time were noted across the eight locations, they were neither strongly significant nor did they show clear trends of change. These data can however, be useful to suggest possible future trends in terms of changes in forest carbon biomass and rates of forest regeneration.

For L1, L7 and L8, there were no notable trends regarding changes in forest characteristics over the twoâ&#x20AC;&#x201C; three year monitoring period. This was also the case for Location 2.

For Location 3, at 50 and 100 m from the canal, there were also no notable changes over the four years of study. At 400 m from the canal, however, the basal area of poles increased. At 700 m the basal area and densities of poles also increased, while the densities of seedlings and saplings, and the basal area for saplings, decreased. Overall cumulative species number appeared to decline for seedlings at 700 m from the canal, while it increased for trees.

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At Location 4, at 50 and 100 m from the canal there were also no notable changes to forest characteristics during the four years of study, apart from a slight overall increase in sapling densities. At 400 m from the canal, seedling and sapling densities decreased during the study period, while tree densities increased, as did tree cumulative species number. Seedling and sapling densities also decreased at 700 m during the study period, but to a lesser extent than at 400 m from the canal. Tree densities and basal area increased at 700 m.

At Location 5, seedling densities decreased at 50 m from the canal, while cumulative species numbers increased for saplings, at 100, 400 and 700 m, and pole densities increased at 700 m. This location, however, had extremely low overall values for all forest caharcteristics, and a slight change in the annual data had a notable effect not only on rates of change but also on the variation in the data.

At Location 6, at 50 m from the canal, seedling and tree densities increased, as did pole and tree basal areas.

At 100 m from the canal, sapling densities decreased, while pole and tree densities increased. Sapling density also decreased at 400 and 700 m from the canal, as did seedling densities at 400 m. Basal areas of poles and trees, however, both increased at 400 and 700 m.

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Figure 3.19: Change in individual density, basal area and cumulative species number over time for each tree maturity growth stage, for Locations 1, 7 and 8 Seedlings

Saplings

180

60,000

150

50,000

80,000

120

1,000

40,000

90

30,000

40,000

60

500

20,000

30

10,000

0

0

2010

2011

2012

2013

Average basal area (m^2/ha)

Average density (Individuals/ha)

Trees

1,500

70,000

120,000

0

2010

2011

2012

2013

0

2010

2011

2012

2013

30.0

25.0

12.0

25.0

20.0

10.0

20.0

35 30 25 20 15 10 5 0

2010

2011

KFCP Vegetation Monitoring

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2013

2013

2010

2011

2012

2013

0.0

2010

2011

2012

2013

2011

2012

2013

2.0 2010

2011

2012

2013

0.0

74

60

30

72

50

25

70

40

20

68

30

15

66

20

10

64

10

5

62

2012

4.0

5.0

5.0

40

2011

6.0 10.0

10.0

0.0

2010

8.0

15.0

15.0

45

Cumulative species number

Poles

2010

2011

2012

2013

0

2010

2011

2012

2013

0

2010

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Figure 3.20: Change in individual density, basal area and cumulative species number over time for each tree maturity growth stage, for Location 2 with regard to DFC Saplings

30 25 20

600

15

400

15,000

10

200

0

2010

2011

2012

0

2013

1

35

800

30,000

Trees

40

1,000

5 2010

2011

2012

2013

0

1.2

0.5

1.0

0.4

0.8

2010

2011

2012

2013

2010

2011

2012

2013

0.3 0.5 0.2

0.4

0.1

0.2 0.0

0

1.0

0.6

7

Cumulative species number

Poles

1,200

45,000

Average basal area (m^2/ha)

Average density (Individuals/ha)

Seedlings

2010

2011

2012

2013

4

0.0

2010

2011

2012

2013

2

0.0

2010

2011

2012

2013

1

6 3

5 4

2

3 2

1

1

1 0

2010

2011

KFCP Vegetation Monitoring

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2013

0

2010

2011

2012

2013

0

2010

2011

2012

2013

0

2010

2011

2012

2013

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Figure 3.21: Change in individual density, basal area and cumulative species number over time for each tree maturity growth stage, for Location 3 with regard to DFC Seedlings

Saplings

Poles

Average density (Individuals/ha)

150,000

200,000

120,000

150,000

120

600

90

400

60

200

30

60,000

50,000

30,000

2010

2011

2012

0

2013

2010

2011

2012

2013

Average basal area (m^2/ha)

16.0

Cumulative species number

800

90,000

100,000

0

Trees

2010

2011

2012

2013

12.0

0

4.0

2010

2011

2012

2013

0.0

2010

2011

2012

2013

0.0

12

25

50

20

10

20

40

15

30

2010

2011

KFCP Vegetation Monitoring

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2013

0

2011

2012

2013

2010

2011

2012

2013

2.0

25

0

2010

3.0

60

10

2013

6.0

30

5

2012

6.0

4.0

20

2011

9.0

8.0

8.0

10

2010

10.0

12.0

0.0

0

8

15

6

10

4 5

2010

2011

2012

2013

0

2 2010

2011

2012

2013

0

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Figure 3.22: Change in individual density, basal area and cumulative species number over time for each tree maturity growth stage, for Location 4 with regard to DFC Seedlings

Saplings

Average density (Individuals/ha)

160,000

30,000

20,000

80,000

900

120

600

80

300

40

15,000 10,000

40,000

5,000 2010

2011

2012

0

2013

2010

2011

2012

Average basal area (m^2/ha)

0

2013

15.0

Cumulative species number

Trees

25,000

120,000

0

Poles

12.0

2010

2011

2012

2013

0

12.0

12.0

9.0

9.0

6.0

6.0

3.0

3.0

2010

2011

2012

2013

2010

2011

2012

2013

2012

2013

9.0 6.0 3.0 0.0

2010

2011

2012

2013

0.0

2010

2011

2012

2013

0.0

30

60

25

18

25

50

20

15

20

40

15

30

10

20

5

10

0

2010

2011

KFCP Vegetation Monitoring

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0

12

15

9

10

6

5

3

0 2010

2011

2012

2013

2010

2011

2012

2013

0

2010

2011

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Figure 3.23: Change in individual density, basal area and cumulative species number over time for each tree maturity growth stage, for Location 5 with regard to DFC Seedlings

Saplings

Average density (Individuals/ha)

75,000

Poles

Trees

300

5,000

20

4,000 50,000

15

200

3,000

10 2,000

25,000

100

5

1,000 0

2010

2011

2012

0

2013

2010

2011

2012

0

2013

2010

2011

2012

2013

12.0

Average basal area (m^2/ha)

9.0

Cumulative species number

2011

2012

2013

2010

2011

2012

2013

2012

2013

0.6 0.5

3.0

0.4

6.0

2.0

3.0

0.3 0.2

1.0

2010

2011

2012

2013

5

4

2010

0.7 4.0

0.0

0

0.0

0.1 2010

2011

2012

2013

0.0

2

2

1

1

4

3

3

2 2

1 0

1

2010

2011

KFCP Vegetation Monitoring

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2013

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2010

2011

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0

2010

2011

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0

2010

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Figure 3.24: Change in individual density, basal area and cumulative species number over time for each tree maturity growth stage, for Location 6 with regard to DFC

Average density (Individuals/ha)

Seedlings

Saplings

Poles

125,000

30,000

1,400

100,000

25,000

1,200

15,000 50,000

10,000

25,000 0

2011

2012

0

2013

Average basal area (m^2/ha)

800

120

600

80 40

200 2010

2011

2012

0

2013

25.0

Cumulative species number

160

400

5,000 2010

200

1,000

20,000

75,000

Trees

2010

2011

2012

2013

0

2010

2011

2012

2013

2010

2011

2012

2013

12.0

45.0

10.0

20.0

8.0

30.0

15.0

6.0 10.0

4.0

15.0

5.0 0.0

2.0 2010

2011

2012

2013

0.0

2010

2011

2012

2013

0.0

30

70

35

25

60

30

50

25

40

20

12

30

15

8

20

10

10

5

20 15 10 5 0

2010

2011

KFCP Vegetation Monitoring

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2010

2011

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0

20 16

4

2010

2011

2012

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0

2010

2011

2012

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4 DISCUSSION 4.1

Forest characteristics

The range of forest conditions at the macro and local scale (across the KFCP area and within a single location, respectively) are presented in Section 3.1. Each location was selected as it represented a different forest type and disturbance history and this is clearly reflected in the values for the densities of individuals and basal area. Individual densities and basal areas follow similar trends across the locations and with respect to DFC. Block E is much less disturbed, notably with regard to hydrology and fire history, as compared to Block A. It consequently houses forest with the greatest tree densities, basal areas and species diversity. Location 7 had the greatest overall values for densities and basal areas of poles and trees, indicating that it may be one of the best available datasets to date for relatively undisturbed tropical mixed peat swamp forests. This information will be of key importance to the Indonesian National Carbon Accounting System (INCAS), for programs such as REDD+, and as baseline data. The tree density values for each growth stage, basal areas and species numbers are comparable to those found in mixed PSF in the Sabangau peat dome, which is located to the west of and adjacent to the EMRP area (Graham 2013) and also to basal area data for mixed PSF, low pole and tall pole forest on the same peat dome (Page et al. 1999).

Location 8, located closer to the centre of the peat dome, has much higher densities of seedlings and saplings, but has lower densities of larger trees. This location may therefore be representative of low pole forest rather than mixed PSF, and has similarities with the low pole forest described by Page et al. (1999) on the Sabangau peat dome.

Unlike Locations 7 and 8, Locations 1 and 6 both represent semi-disturbed locations in Block E. The lower densities of individuals and basal areas in Location 1 most likely indicate previous logging at this location, which is only 1 km away from the river and therefore easily accessible. Location 6 is more comparable to Locations 3 and 4, having undergone hydrological modification due to its proximity to a canal. However, comparably, Location 6 has higher densities of individuals and basal areas at all growth stages than either Locations 3 or 4. This may be due to its more remote location, making access difficult, or that overall the location is â&#x20AC;&#x2DC;bufferedâ&#x20AC;&#x2122; and better able to cope with disturbance due to it being situated within the less disturbed Block E. There have also been no fires at this location.

The effect of repeat fires on individual densities, basal area and species number is highlighted by the data for Locations 3 and 4. At these locations there are high densities of individuals at all growth stages and basal areas, at 700m for Location 3, and 400 and 700m for Location 4, but much lower values at 50m and 100m where the plots have been burned regularly. Location 3 has burned slightly more frequently than Location 4, and has a more negative WTD, and this is reflected in comparably lower densities of individuals and basal areas. Locations 3 and 4 have notably high densities of all tree growth stages at the greatest distance away from the canal, at which point the data are comparable to those for Location 7, although the basal area values are lower. The lower basal area values may be due to selective logging of the larger trees (although these locations were not recorded as having been logged on the KFCPâ&#x20AC;&#x2122;s GIS database, field observations at these locations did indicate selective logging by the local communities). The more severe disruption of the

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hydrology at these locations may also have made the larger trees more unstable and at greater risk of uprooting as a result of peat subsidence.

Locations 2 and 5 both demonstrate the most extreme effects of anthropogenic disturbances within the KFCP area. Location 5 is situated close to human settlements and has been burned several times, in addition to experiencing hydrological disturbance through close proximity to the canal system, which results in frequent flooding during the wet season. Location 2, conversely, is on deep peat yet it is located adjacent to the largest canal within the KFCP area and has been burned the greatest number of times (ranging between 4–6 times, dependent on DFC). Location 5 (similar to Location 4) has high seedling densities near to the canal (at 50 and 100 m), indicative of forest regeneration, while there is no similar trend at these distances for Location 2, indicating the negative impact that repeated fire has on woody regrowth.

Total species number, similar to the tree density and basal area data, also showed an effect of DFC, but species numbers were lower; overall, nearer to the canal, and in the two most degraded locations, L2 and L5.

The cumulative species numbers for all other locations were comparable, and in fact higher than those obtained in other studies of TPSF in the area (Graham 2013) indicating a high overall floral biodiversity across the KFCP area, even in semi-degraded locations. Saplings represented the most species-diverse tree maturity stage, which raises the question of whether seedlings, that will be key to the ongoing regrowth of the forest in this area, will provide a sufficient diversity of tree species for sustainable forest regeneration.

Species dominance also showed another impact of disturbance from fires and canals. Locations 2 and 5, and Location 3 near the canal, all had low species numbers with high species dominance (i.e. these locations are dominated by the few pioneer tree species). Meanwhile, for L03–700 m and the remaining other locations, the more typical low-dominance—high-species number, commonly found in TPSF, was observed. More common late-successional species also began to dominate. One interesting point, however, was the difference in dominant species between the tree maturity stages, observed across nearly all the locations.

Those species most dominant for seedlings and saplings were rarely the most dominant at the pole and tree growth stages. This was especially notable in Locations 3 and 4, and less notable in Locations 1, 7 and 8.

These results suggest that throughout the KFCP area, and especially in Block A, that the forested areas are still progressing through post-disturbance successional stages, possibly even pre-dating the EMRP, with shifts in dominance from pioneer, to mid- to late-successional species. This is exemplified by the dominance of Combretocarpus rotundaus at the tree growth stage but its absence at the seedling or sapling stages.

4.2

Influence of environmental conditions on forest characteristics

Fire history showed a very strong influence on vegetation and, notably, there was little significant difference between the effect of a single fire event and two or more fires. Pre-fire densities, basal areas and species numbers for all tree growth stages were high, while all were reduced considerably following fire. Hoscilo (2009) also showed the influence of fire history, as well as fire severity and period of time for recovery postfire, on these forest characteristics.

The influence of hydrology—as indicated by the WTD on the forest characteristics—proved to be the most complex environmental condition to study. Initially the analysis showed little correlation or trend regarding the influence of hydrology on the FMPs. Upon further investigation, however, it was found that trends could be discerned, but only when data for Block A and Block E were considered separately. This was understandable given the very different hydrological regimes that exist across the two blocks. It also strengthens the observation, discussed in the above section, that Location 6 was able to maintain more favourable forest characteristic values than Locations 3 and 4 due to being ‘buffered’ by the overall lower

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disturbance and degradation of Block A, including less modification to the hydrology and no fire events, despite its proximity to a canal.

Block E had a much wider range of average WTDs yet, despite this, the vegetation appears to be less affected by the hydrology. Two logical, though weak, trends appeared in the data for Block E. For seedlings, saplings and poles, FMPs with both the lowest and highest WTDs appeared to be slightly less favourable to these growth stages than WTDs in the middle ranges. Meanwhile, trees preferred wetter conditions with higher WTDs. For all stages of tree maturity, but excluding poles, there does appear to be a cut-off point at which individual densities and basal areas were greatly reduced when WTD became very low. In Block A, for all forest characteristics and tree maturity stages, there was a similar trend. All seedlings, saplings, poles and trees showed their best performance in a small middle range of WTDs, while at slightly lower or higher WTDs than this, densities, basal areas and species numbers dropped to very low levels. These data highlight the more extreme hydrological conditions found in Block A, which appear to limit forest productivity and regeneration.

Peat depth was found to have a weak but consistent effect on forest characteristics. Generally, as peat became thicker (9.25–10.25 m, the shallowest peat in this study being 6.5–8.5 m), the values for density, basal area and species numbers also increased. For poles and trees on the deepest peat (11.75–12.75 m), however, this effect was lost or even reversed. This may indicate that, as observed on other peat domes, that towards the centre of the dome, the taller mixed swamp forest is replaced by low pole forest, which has a higher density of saplings and poles rather than trees (Page et al. 1999). The locations of the FMPs in this study did not, however, represent very shallow peat, found at the edge of this peat dome, along the Kapuas River. The reason for this was, for this peat dome, that numerous human settlements along the Kapuas River have led to the general degradation of the adjacent forest. Other studies have described intact riverine forest, found on the shallowest peat adjacent to rivers, to be the most diverse (Page et al. 1999). Therefore, caution should be applied to this observed trend regarding peat depth, as forest on the shallowest peat in the KFCP area has already been lost.

In addition to recording the peat depth across the KFCP area in 2010, KFCP also monitored peat subsidence rates throughout the study period (2010–2012). Subsidence analysis across the whole peat dome requires the development of complex models and point-by-point representation can badly misrepresent the trends.

Consequently, at the time of writing this report, the subsidence data were not yet available for use and it was not possible to explore its influence on forest characteristics. Subsidence rates, which can be in the range of 2–5 cm per year on tropical peatlands, are unlikely to have large effects on vegetation over a short period of time, but over longer periods of time they may be responsible for loss of rooting stability and tree fall.

At high light intensities, there were fewer individuals, lower basal areas and species numbers. This was to be expected since few tree species of TPSF are adapted to the higher light intensities that occur in degraded forest areas (Banjarbaru Forestry Research Unit and Graham 2014). Some seedlings were present at the higher light intensities indicating the presence of sun-loving pioneers and early succession/regeneration species. The reverse was also true; however, with a notable absence of any seedlings between 0–5% light intensity.

For seedlings on the forest floor, light intensity appeared to be optimal/sufficient at 5–10% light intensity.

Once seedlings become larger, i.e. greater than 1 m, a slightly wider range of light intensities was optimal, up to 20%. These results indicate that, for TPSF, most species are shade-tolerators that are excluded from degraded forest by the higher light intensity.

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Most of the environmental conditions described above do not operate independently. For example, light intensity is determined by both canopy closure and tree cover, which are determined by fire history, hydrology, etc. Equally, hydrology is affected by peat depth, and fire history is also linked with hydrology.

Thus, areas with low WTDs are at greatest risk of fire. This study merely aims to suggest some basic indicators of how the forest state might be predicted from, and affected by, prevailing environmental conditions and how this knowledge may be useful in helping to describe and understand forest states, regeneration and biodiversity, as will be required for REDD+.

4.3

Changes in forest characteristics over time

Overall, given the short study period (relatively, in terms of recording forest dynamics), there were few strong trends to observe across the locations. Indeed, L1, L2, L7 and L8 showed no significant change at all.

Locations 3, 4 and 6 did show some changes over time, with a greater rate of change observed further from the canal. This was somewhat surprising, as it might be expected that the more degraded areas would show more activity (continued degradation or beginnings of regeneration). As this was the case, it indicates towards a somewhat stable, although degraded system. There were indications that at these locations more mature forest was developing, with poles and trees becoming more dominant. The decline of seedlings might also be expected as the forest matures, but the reason for the decline in saplings is less clear. Only Location 5 showed signs of regeneration throughout; a positive sign for REDD+ MRV. The data should be treated carefully, however, as while the data values are still so few, small changes to them can create large but variable rates of change, as shown by the standard deviation at this location.

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5 OVERALL DISCUSSION AND CONCLUSIONS To achieve the MRV requirements associated with REDD+ (the degree of accuracy associated with the nation-wide monitoring of carbon volumes and emissions), in particular for Indonesia there is a requirement for the collection of forest inventory data from permanent FMPs. Tropical peatlands and TPSF are among the most relevant, and challenging, ecosystems in which to achieve this level of monitoring.

Due to the logistical challenges associated with monitoring peatlands, the forests remain under-studied, with few accurate studies of how forest characteristics are affected by different environmental conditions and disturbance regimes. Furthermore, the peatlands themselves store much more carbon than the aboveground forest, unlike many other REDD+ forest systems. These belowground carbon stores are extremely important but difficult to accurately quantify. The forest is understood to provide its own quota of carbon to the system, but also to be integral to the protection, maintenance and long-term stability of the peat. Consequently, studies such as this one are essential to facilitate better quantification of the forest biomass under different environmental settings and to understand the most appropriate implementation activities necessary to protect and preserve the forest and the peatlands, so as to better target disturbances, to provide accurate data to INCAS, and to monitor the changes in forest biomass and species diversity over time.

This study has provided important field data to describe and quantify TPSF carbon stocks under different conditions, and these data were, at the time of writing, being incorporated into INCAS. This study has also begun to explore and describe the influence that prevailing environmental conditions have on forest regeneration and diversity. Some of these findings and the data collected have begun to be incorporated into village land management plans and into implementation activity planning. This work shows the need for successful fire prevention in areas which still retain a good forest cover, highlights optimal WTDs for future canal blocking activities in Block A, while indicating, that for vegetation at least, hydrological disturbance is less of a concern in Block E. The data indicate the relative greater importance of deep peat for forest biomass and also highlight the need for shade-cover for successful regeneration of most tree species. The data also indicate the relatively high tree species diversity associated with the deeper peat of the central peat dome, compared to middle peat depths in the area. Note, as described above, this study has not been able to represent any intact riverine forest, normally found on the shallowest peat (pre-disturbance), which would also be likely to contribute high biomass and species diversity to the ecosystem. Finally the data provide a baseline for ongoing vegetation monitoring that will be necessary to accurately record changes in forest biomass, regeneration and biodiversity, while indicating some early trends during the first three to four years of this study.

Ideally this level of monitoring activity will continue to facilitate long-term analysis of the rates of change in forest characteristics and their responses to implementation activities.

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Restoration Ecology 19:683–689.

Amthor, J. S. and Huston, M. A. (eds.). 1998. Terrestrial ecosystem responses to global change: a research strategy. Oak Ridge National Laboratory, Oak Ridge, TN. (ORNL/TM-1998/27).

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Ballhorn, U., F. Siegert, M. Mason and S. Limin. 2009. Derivation of burn scar depths and estimation of carbon emissions with LIDAR in Indonesian peatlands. Proceedings of the National Academy of Sciences 106:21213–21218.

Banjarbaru Forestry Research Unit, FORDA and L.L.B. Graham. 2014. Tropical peat swamp forest silviculture in Central Kalimantan.

Scientific Report. Indonesia-Australia Forest Carbon Partnership (IAFCP), Jakarta, Indonesia.

Boer, R. et al. 2010. Reducing carbon emissions from Indonesia’s peatland: Multidisciplinary study. BAPPENAS, Jakarta, Indonesia.

Brady, M.A. 1997. Effects of vegetation changes on organic matter dynamics in three coastal peat deposits in Sumatra, Indonesia. In: Rieley, J.O. and S.E. Page (eds). Biodiversity and sustainability of tropical peatlands, pp.113-134.

Dommain, R., J. Couwenberg and H. Joosten. 2010. Hydrological regulation of domed peatlands in south-east Asia and consequences for conservation and restoration. Mires & Peat 6:1–17.

Furniss, C. 2006. Dossier: palm oil, seeds of destruction. Geographical 78:45–59.

Giesen, W. 2004. Causes of swamp forest degradation in Berbak National Park and recommendations for restoration. Water for Food and Ecosystems Programme Project on: Biodiversity & the EMRP Revised draft Euroconsult Mott MacDonald 45 ‘Promoting the river basin and ecosystem approach for sustainable management of SE Asian lowland peat swamp forests’. ARCADIS Euroconsult, Arnhem, The Netherlands.

Gorham, E. 1991. Northern peatlands: role in the carbon cycle and probable responses to climatic warming. Ecological Applications 1:182–195.

Graham, L.L.B. 2013. Restoration from within: An interdisciplinary methodology for tropical peat swamp forest restoration, Indonesia.

PhD thesis submitted to the University of Leicester. http://hdl.handle.net/2381/28192.

Hooijer, A., S. Page, J.G. Canadell, M. Silvius, J. Kwadijk, H. Wösten and J. Jauhiainen. 2010. Current and future CO2 emissions from drained peatlands in Southeast Asia. Biogeosciences 7:1505–1514.

Hoscilo, A. 2009. Fire regime, vegetation dynamics and land cover change in tropical peatland, Indonesia. PhD thesis, University of Leicester, UK. IAFCP. 2009. Kalimantan Forests and Climate Partnership (KFCP) design document. Indonesia-Australia Forest Carbon Partnership, (IAFCP), Jakarta, Indonesia.

Immirizi, C.P. and E. Maltby. 1992. The global status of peatlands and their role in the carbon cycle. Wetlands Ecosystems Research Group, Report 11. University of Exeter, Exeter, UK. Langner, A., J. Miettinen and F. Siegert. 2007. Land cover change 2002–2005 in Borneo and the role of fire derived from MODIS imagery. Global Change Biology 13: 2329–2340.

Langner, A. and F. Siegert. 2009. Spatiotemporal fire occurrence in Borneo over a period of 10 years. Global Change Biology 15 48– 62.

Miettinen, J. and S.C. Liew. 2010. Degradation and development of peatlands in Peninsular Malaysia and in the islands of Sumatra and Borneo since 1990. Land Degradation and Development 21:285–296.

Miyamoto, K., E. Suzuki, T. Kohyama, T. Seino, E. Mirmanto and H. Simbolin. 2003. Habitat differentiation among tree species with small-scale variation of humus depth and topography in a tropical heath forest of Central Kalimantan, Indonesia. Journal of Tropical Ecology 19:43–54.

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Muhamad, N. and J. Rieley. 2001. Management of tropical peatlands in Indonesia: mega-reclamation project in Central Kalimantan.

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Notohadiprawiro, T. 1997. Twenty-five years experience in peatland development for agriculture in Indonesia. In: Rieley, J.O. and S.E. Page, S. E. (eds). Biodiversity and sustainability of tropical peatlands. Pp.301-310 Page, S.E., A. Hoscilo, H. Wosten, J. Jauhiainen, H. Ritzema, K. Tansey, M. Silvius, L. Graham, H. Vasander, J. Rieley and S. Limin. 2009.

Ecological restoration of lowland tropical peatlands in Southeast Asia—Current knowledge and future research directions.

Ecosystems 12:888–905.

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7 APPENDIX 7.1 Tree species list Table 7.1: Tree species presented for all locations, as per tree maturity (S = seedling, S/P/T = Sapling, pole and/or tree) Note for all tables: DFC â&#x20AC;&#x201C; Distance from canal. Data pooled across three plots for each DFC. For L1, L7 and L8, DFC is not relevant so pooled across all twelve plots per location.

Scientific name Antidesma phanerophleum (Euphorbiaceae) Combretocarpus rotundatus (Anisophyllaceae) Cratoxylon arborescens (Hypericaceae) Diospyros sp. (Ebenaceae) Elaeocarpus Mastersii (Elaeocarpaceae) Ilex cymosa (Aquifoliaceae) Syzygiumsp. (Myrtaceae) Syzygiumsp.3 (Myrtaceae)

Location L03

Scientific name Aglaia rubignosa (Meliaceae)

Kajalaki

L03 L03

Alseodaphne coriacea (Lauraceae) Antidesma coriaceum (Euphorbiaceae)

Gemor Bua dawat

L03

Antidesma phanerophleum (Euphorbiaceae)

Matan undang

L03

Archidendronborneensis (Fabaceae (Leguminosae))

Kacang nyaring

L03

Ardisiapyrsocoma B.C.Stone (Myrsinaceae)

Kayu berang

S/P/T

S, S/P/T

L03

Baccaurea bracteata (Euphorbiaceae)

Rambai hutan

S/P/T

S, S/P/T

L03

Calophyllum hosei (Clusiaceae (Guttiferae))

Bintangor

L03

Campnosperma coriaceum (Anacardiaceae)

Tarantang

L03

Campnosperma squamatum (Anacardiaceae)

Teras nyating

L03

Clerodendron sp. (Verbenaceae)

Supang

L03

Combretocarpus rotundatus (Anisophyllaceae)

Tumih

S/P/T

L03

Cratoxylon arborescens (Hypericaceae)

Garunggang

S, S/P/T

L03

Daytyloclados stenostachys (Crypteroniaceae)

Martibu

L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03

Dialiumindum (Fabaceae (Leguminosae)) Diospyros cf.evena (Ebenaceae) Diospyros siamang (Ebenaceae) Diospyros sp. (Ebenaceae) Diospyros sp. (Ebenaceae) Elaeocarpus acmocarpus (Elaeocarpaceae) Elaeocarpus sp. (Elaeocarpaceae) Elaeocarpus sp. (Elaeocarpaceae) Fragraea racemosa (Loganiaceae) Garciniasp. (Clusiaceae (Guttiferae)) Garciniasp.4 (Clusiaceae (Guttiferae)) Gymnacranthera parquhariania (Myristicaceae) Horsfieldiacrassifolia (Myristicaceae) Ilex cymosa (Aquifoliaceae) Ilex hypoglauca (Aquifoliaceae) Ixora havilandii (Rubiaceae) Knema intermedia (Myristicaceae) Koompassia malaccensis (Fabaceae (Leguminosae)) Licania Splendens (Chrysobalanaceae) Lithocarpussp. (Fagaceae)

Teras bamban Gulung haduk Ehang Kayu arang Malam-malam Patanak daun besar Kasuhui Mangkinang daun besar Tabat barito/Tasang saluang Manggis hutan Mahalilis Mandarahan daun kecil Mandarahan daun besar Kambasira Kambasira sumpung Karanji Karandau merah Bangaris/Kempas Bintan Pampaning bitik

KFCP Vegetation Monitoring

Local name Matan undang Tumih Garunggang Kayu arang Mangkinang balawau Kambasira Jambu burung kecil Tampohot batang

50m DFC

Local name

50m DFC

100m DFC

Location L02 L02 L02 L02 L02 L02 L02 L02

400m

S/P/T

100m DFC

S/P/T

DFC S S/P/T S/P/T S S S S S, S/P/T

400m S/P/T

DFC S/P/T

S/P/T S, S/P/T

S, S/P/T

S, S/P/T

S, S/P/T

S/P/T

S, S/P/T

S/P/T S/P/T S/P/T

S S, S/P/T

S/P/T

S/P/T

S/P/T

S/P/T S/P/T S/P/T

S/P/T S/P/T

S/P/T

S/P/T S/P/T S/P/T

S/P/T

S/P/T S/P/T S, S/P/T S/P/T S

S, S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S, S/P/T S, S/P/T

S/P/T S/P/T

S/P/T S, S/P/T

Page 48

Location L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03 L03

Scientific name Litsea cf.fusca (Lauraceae) Litsea sp. (Lauraceae) Macaranga caladiifolia (Euphorbiaceae) Mesua sp. (Clusiaceae (Guttiferae)) Mezzetia parviflora (Annonaceae) Mezzetia umbellata (Annonaceae) Neoscortechinia kingii (Euphorbiaceae) Nephellium sp.1 (Sapindaceae) Palaquium cochlearifolium (Sapotaceae) Palaquium sp. (Sapotaceae) Sandoricum beccanarium (Meliaceae) Shoreabalangeran (Dipterocarpaceae) Shoreateysmanniana (Dipterocarpaceae) Stemonorus scorpiodes (Icacinaceae) Sterculia sp. (Sterculiaceae) Syzygiumsp. (Myrtaceae) Syzygiumsp.1 (Mytaceae) Syzygiumsp.3 (Myrtaceae) Syzygiumsp.4 (Myrtaceae) Tetractomia tetrandra (Rutaceae) Tetrameristaglabra (Tetrameristaceae) Timonius sp. (Rubiaceae) Tristaniopsis sp.1 (Myrtaceae) Tristaniopsis sp.2 (Myrtaceae) Unknown Unknown (Dipterocarpaceae) Unknown Unknown (Lauraceae) Unknown Unknown (Myrtaceae) Unknown Unknown (Myrtaceae) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Xanthophyllumdiscolour Chod. (Polygalaceae) Xylopia cf.malayana (Annonaceae) Xylopia fusca (Annonaceae)

Location L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04

Scientific name Aglaia rubignosa (Meliaceae) Alseodaphne coriacea (Lauraceae) Antidesma coriaceum (Euphorbiaceae) Antidesma phanerophleum (Euphorbiaceae) Archidendronborneensis (Fabaceae (Leguminosae)) Ardisiapyrsocoma B.C.Stone (Myrsinaceae) Baccaurea bracteata (Euphorbiaceae) Calophyllum hosei (Clusiaceae (Guttiferae)) Calophyllum soulasttri (Clusiaceae (Guttiferae)) Campnosperma coriaceum (Anacardiaceae) Campnosperma squamatum (Anacardiaceae) Clerodendron sp. (Verbenaceae) Combretocarpus rotundatus (Anisophyllaceae) Cratoxylon arborescens (Hypericaceae) Cyathocalyx biovulatus (Annonaceae) Daytyloclados stenostachys (Crypteroniaceae) Diospyros cf.evena (Ebenaceae) Diospyros sp. (Ebenaceae)

KFCP Vegetation Monitoring

Local name Tampang Madang litsea Mahang bitik Tabaras akar tinggi Pisang-pisang besar Kambalitan /Pisang-pisang kecil Pupuh palanduk Rambutan hutan Nyatu gagas Nyatu burung Papong Kahui Maranti bitik Tabaras tidak akar tinggi Pendu Jambu burung kecil Kayu lalas daun kecil Tampohot batang Tatumbu Rambangun Ponak Bua bintang Balawan punei Balawan merah Rasak Madang Jambu burung Jambu-jambu Bangkuang napu Kopi-kopi merah Latak manuk Lombok-lombok/sampel lombok Sampel C sampel during sampel jambu biji Udi-udi Kamuning Tagula /Jangkang hijau Jangkang kuning

50m DFC

400m S/P/T S/P/T S/P/T S/P/T

DFC S/P/T S/P/T S/P/T S/P/T

S/P/T

S

S/P/T

S/P/T S S/P/T S/P/T S, S/P/T S/P/T S, S/P/T

S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T

S/P/T S/P/T

S/P/T

Local name Kajalaki Gemor Bua dawat Matan undang Kacang nyaring Kayu berang Rambai hutan Bintangor Takal Tarantang Teras nyating Supang Tumih Garunggang Karandau biasa Martibu Gulung haduk Kayu arang

100m DFC

50m DFC

100m DFC S/P/T S/P/T S, S/P/T S/P/T

S, S/P/T S, S/P/T S, S/P/T

S S/P/T S/P/T S

S, S/P/T

400m S/P/T S/P/T S, S/P/T S, S/P/T

S S/P/T

S/P/T S/P/T S/P/T S/P/T

S/P/T

S/P/T S/P/T S, S/P/T S/P/T

S, S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S, S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T DFC S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T

Page 49

Location L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04 L04

Scientific name Diospyros sp. (Ebenaceae) Elaeocarpus acmocarpus (Elaeocarpaceae) Elaeocarpus sp. (Elaeocarpaceae) Elaeocarpus sp. (Elaeocarpaceae) Eugeniaspicata (Mytaceae) Garciniasp. (Clusiaceae (Guttiferae)) Garciniasp.1 (Clusiaceae (Guttiferae)) Garciniasp.4 (Clusiaceae (Guttiferae)) Gonystylus bancanus (Thymeleaeaceae) Gymnacranthera parquhariania (Myristicaceae) Horsfieldiacrassifolia (Myristicaceae) Ilex cymosa (Aquifoliaceae) Ixora havilandii (Rubiaceae) Knema intermedia (Myristicaceae) Koompassia malaccensis (Fabaceae (Leguminosae)) Licania Splendens (Chrysobalanaceae) Lithocarpussp. (Fagaceae) Litsea sp. (Lauraceae) Macaranga caladiifolia (Euphorbiaceae) Mesua sp. (Clusiaceae (Guttiferae)) Mezzetia parviflora (Annonaceae) Neoscortechinia kingii (Euphorbiaceae) Nephellium sp.1 (Sapindaceae) Palaquium cochlearifolium (Sapotaceae) Palaquium sp. (Sapotaceae) Palaquium sp. (Sapotaceae) Platea sp. (Icacinaceae) Rapanea borneensis (Myrsinaceae) Sandoricum beccanarium (Meliaceae) Shoreabalangeran (Dipterocarpaceae) Shoreateysmanniana (Dipterocarpaceae) Stemonorus scorpiodes (Icacinaceae) Sterculia sp. (Sterculiaceae) Syzygiumsp. (Myrtaceae) Syzygiumsp.1 (Mytaceae) Syzygiumsp.3 (Myrtaceae) Syzygiumsp.4 (Myrtaceae) Ternstromia magnifica (Theaceae) Tetractomia tetrandra (Rutaceae) Tetrameristaglabra (Tetrameristaceae) Timonius sp. (Rubiaceae) Tristaniopsis sp.1 (Myrtaceae) Tristaniopsis sp.2 (Myrtaceae) Unknown Unknown (Dipterocarpaceae) Unknown Unknown (Lauraceae) Unknown Unknown (Myrtaceae) Unknown Unknown (Myrtaceae) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Xanthophyllumdiscolour Chod. (Polygalaceae) Xylopia cf.malayana (Annonaceae) Xylopia fusca (Annonaceae)

KFCP Vegetation Monitoring

Local name Malam-malam Patanak daun besar Kasuhui Mangkinang daun besar Kayu lalas daun besar Manggis hutan Aci Mahalilis Ramin Mandarahan daun kecil Mandarahan daun besar Kambasira Karanji Karandau merah Bangaris/Kempas Bintan Pampaning bitik Madang litsea Mahang bitik Tabaras akar tinggi Pisang-pisang besar Pupuh palanduk Rambutan hutan Nyatu gagas Nyatu burung Nyatu undus Sampel mahung/Tambalik angin Marabungkan Papong Kahui Maranti bitik Tabaras tidak akar tinggi Pendu Jambu burung kecil Kayu lalas daun kecil Tampohot batang Tatumbu Tabunter daun besar Rambangun Ponak Bua bintang Balawan punei Balawan merah Rasak Madang Jambu burung Jambu-jambu Bangkuang napu Jambu Kajalaki puti Kayu Tulang/Kopi-kopi Kopi-kopi merah Prupuk keras sampel during Tatumbu merah Kamuning Tagula /Jangkang hijau Jangkang kuning

50m DFC S/P/T

100m DFC S, S/P/T S

S/P/T S, S/P/T S/P/T

S/P/T S/P/T

S/P/T S/P/T S/P/T S, S/P/T S/P/T

S/P/T S/P/T S/P/T

S/P/T S, S/P/T

S/P/T

S, S/P/T

400m S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T

S S/P/T S/P/T

S, S/P/T

S/P/T S/P/T

S S/P/T S/P/T

S/P/T S/P/T S/P/T

S, S/P/T

S/P/T

S/P/T S, S/P/T S/P/T S, S/P/T S/P/T S, S/P/T

S/P/T S

S S/P/T S/P/T S/P/T

S/P/T S, S/P/T S, S/P/T

S, S/P/T S S/P/T

S/P/T

S/P/T

S/P/T S, S/P/T S, S/P/T S, S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T

S/P/T

S/P/T S/P/T

S/P/T S/P/T

S, S/P/T

S/P/T S/P/T

S/P/T

S S/P/T S/P/T

S/P/T

S/P/T S/P/T S/P/T S S/P/T S/P/T

DFC S/P/T S/P/T S/P/T S/P/T S S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T S, S/P/T S S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S, S/P/T S, S/P/T S/P/T

S/P/T S/P/T S, S/P/T S/P/T S, S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T

S/P/T S/P/T

Page 50

Location L05 L05 L05 L05 L05 L05 L05

Scientific name Alseodaphne coriacea (Lauraceae) Antidesma coriaceum (Euphorbiaceae) Antidesma phanerophleum (Euphorbiaceae) Combretocarpus rotundatus (Anisophyllaceae) Cratoxylon arborescens (Hypericaceae) Litsea sp. (Lauraceae) Tetractomia tetrandra (Rutaceae)

Gemor Bua dawat Matan undang Tumih Garunggang Madang litsea Rambangun

Location L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06

Scientific name Adenanthera pavonina (Fabaceae (Leguminosae)) Alseodaphne sp. (Lauraceae) Antidesma coriaceum (Euphorbiaceae) Antidesma phanerophleum (Euphorbiaceae) Archidendronborneensis (Fabaceae (Leguminosae)) Baccaurea bracteata (Euphorbiaceae) Blomedendron tokbrai (Euphorbiaceae) Calophyllum hosei (Clusiaceae (Guttiferae)) Campnosperma coriaceum (Anacardiaceae) Campnosperma squamatum (Anacardiaceae) Clerodendron sp. (Verbenaceae) Combretocarpus rotundatus (Anisophyllaceae) Cratoxylon arborescens (Hypericaceae) Cyathocalyx biovulatus (Annonaceae) Dacrydium pectinateum (Podacarpaceae) Daytyloclados stenostachys (Crypteroniaceae) Dialiumindum (Fabaceae (Leguminosae)) Diospyros cf.evena (Ebenaceae) Diospyros siamang (Ebenaceae) Diospyros sp. (Ebenaceae) Diospyros sp. (Ebenaceae) Elaeocarpus acmocarpus (Elaeocarpaceae) Elaeocarpus sp. (Elaeocarpaceae) Elaeocarpus sp. (Elaeocarpaceae) Eugeniaspicata (Mytaceae) Garciniasp. (Clusiaceae (Guttiferae)) Garciniasp.1 (Clusiaceae (Guttiferae)) Garciniasp.4 (Clusiaceae (Guttiferae)) Gonystylus bancanus (Thymeleaeaceae) Gymnacranthera parquhariania (Myristicaceae) Horsfieldiacrassifolia (Myristicaceae) Ilex cymosa (Aquifoliaceae) Ilex hypoglauca (Aquifoliaceae) Ixora havilandii (Rubiaceae) Knema intermedia (Myristicaceae) Licania Splendens (Chrysobalanaceae) Lithocarpussp. (Fagaceae) Litsea sp. (Lauraceae) Mezzetia parviflora (Annonaceae) Mezzetia umbellata (Annonaceae) Neoscortechinia kingii (Euphorbiaceae) Nephellium sp.1 (Sapindaceae) Palaquium cochlearifolium (Sapotaceae) Palaquium pseodorostratum (Sapotaceae) Palaquium sp. (Sapotaceae) Parartocarpus venenosus (Moraceae) Platea sp. (Icacinaceae) Rapanea borneensis (Myrsinaceae) Shoreabalangeran (Dipterocarpaceae) Shoreasp. (Dipterocarpaceae)

Local name Tapanggang Madang marakuwung Bua dawat Matan undang Kacang nyaring Rambai hutan Kenari Bintangor Tarantang Teras nyating Supang Tumih Garunggang Karandau biasa Alau Martibu Teras bamban Gulung haduk Ehang Kayu arang Malam-malam Patanak daun besar Kasuhui Mangkinang daun besar Kayu lalas daun besar Manggis hutan Aci Mahalilis Ramin Mandarahan daun kecil Mandarahan daun besar Kambasira Kambasira sumpung Karanji Karandau merah Bintan Pampaning bitik Madang litsea Pisang-pisang besar Kambalitan /Pisang-pisang kecil Pupuh palanduk Rambutan hutan Nyatu gagas Nyato bawui Nyatu burung Tapakan Sampel mahung/Tambalik angin Marabungkan Kahui Maranti lampung

KFCP Vegetation Monitoring

Local name

100m DFC

50m DFC

400m

DFC S/P/T S

S S, S/P/T S/P/T

S/P/T S/P/T

S 50m DFC S, S/P/T S/P/T S, S/P/T S, S/P/T S S, S/P/T

S S/P/T

100m DFC

S, S/P/T S/P/T S S, S/P/T

400m S, S/P/T S/P/T S, S/P/T S/P/T S/P/T S, S/P/T

S/P/T

S, S/P/T S/P/T

S

S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T

S/P/T S, S/P/T S/P/T S, S/P/T S

S/P/T S/P/T S/P/T S, S/P/T

S/P/T

S/P/T S/P/T

S/P/T S/P/T S, S/P/T S/P/T S, S/P/T

S/P/T S/P/T S/P/T S S/P/T

S/P/T S/P/T S, S/P/T S, S/P/T

S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T

S/P/T

S/P/T S/P/T S/P/T

S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T

S, S/P/T S/P/T S, S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S, S/P/T S/P/T S/P/T

S/P/T

DFC S S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T

Page 51

Location L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 L06 Location L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01

Scientific name Shoreateysmanniana (Dipterocarpaceae) Stemonorus scorpiodes (Icacinaceae) Sterculia sp. (Sterculiaceae) Syzygiumsp. (Myrtaceae) Syzygiumsp.1 (Mytaceae) Syzygiumsp.3 (Myrtaceae) Syzygiumsp.4 (Myrtaceae) Ternstromia hosei (Theaceae) Ternstromia magnifica (Theaceae) Tetractomia tetrandra (Rutaceae) Tetrameristaglabra (Tetrameristaceae) Timonius sp. (Rubiaceae) Tristaniopsis sp. (Myrtaceae) Tristaniopsis sp.1 (Myrtaceae) Tristaniopsis sp.2 (Myrtaceae) Unknown Cek di lapangan (Unknown) Unknown Unknown (Dipterocarpaceae) Unknown Unknown (Lauraceae) Unknown Unknown (Myrtaceae) Unknown Unknown (Myrtaceae) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Xanthophyllumdiscolour Chod. (Polygalaceae) Xylopia cf.malayana (Annonaceae) Xylopia fusca (Annonaceae) Scientific name Aglaia rubignosa (Meliaceae) Alseodaphne coriacea (Lauraceae) Antidesma coriaceum (Euphorbiaceae) Antidesma phanerophleum (Euphorbiaceae) Archidendronborneensis (Fabaceae (Leguminosae)) Ardisiapyrsocoma B.C.Stone (Myrsinaceae) Baccaurea bracteata (Euphorbiaceae) Calophyllum hosei (Clusiaceae (Guttiferae)) Calophyllum sp. (Clusiaceae (Guttiferae)) Campnosperma coriaceum (Anacardiaceae) Campnosperma squamatum (Anacardiaceae)

Local name Maranti bitik Tabaras tidak akar tinggi Pendu Jambu burung kecil Kayu lalas daun kecil Tampohot batang Tatumbu Tabunter daun kecil Tabunter daun besar Rambangun Ponak Bua bintang Balawan Balawan punei Balawan merah Unknown cek di lapangan Rasak Madang Jambu burung Jambu-jambu Bangkuang napu Kayu Tulang/Kopi-kopi Sampel Manggis Kamuning Tagula /Jangkang hijau Jangkang kuning Local name Kajalaki Gemor Bua dawat Matan undang Kacang nyaring Kayu berang Rambai hutan Bintangor Kapurnaga kalakai Tarantang Teras nyating

L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01

Cnenolophon parvifolius (Linaceae) Combretocarpus rotundatus (Anisophyllaceae) Cratoxylon arborescens (Hypericaceae) Dacrydium pectinateum (Podacarpaceae) Daytyloclados stenostachys (Crypteroniaceae) Dialiumindum (Fabaceae (Leguminosae)) Diospyros cf.evena (Ebenaceae) Diospyros sp. (Ebenaceae) Diospyros sp. (Ebenaceae) Elaeocarpus sp. (Elaeocarpaceae) Garciniasp. (Clusiaceae (Guttiferae)) Garciniasp.1 (Clusiaceae (Guttiferae)) Garciniasp.2 (Clusiaceae (Guttiferae)) Garciniasp.4 (Clusiaceae (Guttiferae)) Gonystylus bancanus (Thymeleaeaceae) Horsfieldiacrassifolia (Myristicaceae) Ilex cymosa (Aquifoliaceae) Ilex hypoglauca (Aquifoliaceae) Ixora havilandii (Rubiaceae)

Kayu cahang/Bintan rambut merah Tumih Garunggang Alau Martibu Teras bamban Gulung haduk Kayu arang Malam-malam Kasuhui Manggis hutan Aci Gandis Mahalilis Ramin Mandarahan daun besar Kambasira Kambasira sumpung Karanji

KFCP Vegetation Monitoring

50m DFC

S/P/T S/P/T

100m DFC S/P/T S, S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T

S/P/T S/P/T

S/P/T S/P/T S/P/T S/P/T

S/P/T S/P/T S/P/T S, S/P/T

S/P/T S/P/T S/P/T S, S/P/T

400m S, S/P/T S, S/P/T S/P/T S/P/T S/P/T

S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T S, S/P/T S, S/P/T

S/P/T S/P/T S/P/T

S/P/T S/P/T S/P/T S/P/T

DFC S, S/P/T S, S/P/T S/P/T S/P/T S/P/T

S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T

Strata S, S/P/T S/P/T S, S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S, S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S, S/P/T S/P/T S, S/P/T

Page 52

Location L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 L01 Location L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07

Scientific name Knema intermedia (Myristicaceae) Licania Splendens (Chrysobalanaceae) Lithocarpussp. (Fagaceae) Litsea cf.fusca (Lauraceae) Litsea sp. (Lauraceae) Mezzetia parviflora (Annonaceae) Mezzetia umbellata (Annonaceae) Neoscortechinia kingii (Euphorbiaceae) Nephellium sp.1 (Sapindaceae) Palaquium cochlearifolium (Sapotaceae) Palaquium sp. (Sapotaceae) Parartocarpus venenosus (Moraceae) Platea sp. (Icacinaceae) Rapanea borneensis (Myrsinaceae) Shoreabalangeran (Dipterocarpaceae) Shoreateysmanniana (Dipterocarpaceae) Stemonorus scorpiodes (Icacinaceae) Sterculia sp. (Sterculiaceae) Syzygiumsp. (Myrtaceae) Syzygiumsp. (Myrtaceae) Syzygiumsp.1 (Mytaceae) Syzygiumsp.3 (Myrtaceae) Syzygiumsp.4 (Myrtaceae) Ternstromia hosei (Theaceae) Ternstromia magnifica (Theaceae) Tetractomia tetrandra (Rutaceae) Timonius sp. (Rubiaceae) Tristaniopsis sp. (Myrtaceae) Tristaniopsis sp.1 (Myrtaceae) Tristaniopsis sp.2 (Myrtaceae) Unknown Unknown (Dipterocarpaceae) Unknown Unknown (Dipterocarpaceae) Unknown Unknown (Myrtaceae) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Xylopia cf.malayana (Annonaceae) Xylopia fusca (Annonaceae) Scientific name Adenanthera pavonina (Fabaceae (Leguminosae)) Antidesma coriaceum (Euphorbiaceae) Antidesma phanerophleum (Euphorbiaceae) Archidendronborneensis (Fabaceae (Leguminosae)) Ardisiapyrsocoma B.C.Stone (Myrsinaceae) Baccaurea bracteata (Euphorbiaceae) Calophyllum hosei (Clusiaceae (Guttiferae)) Campnosperma coriaceum (Anacardiaceae) Campnosperma squamatum (Anacardiaceae) Clerodendron sp. (Verbenaceae) Combretocarpus rotundatus (Anisophyllaceae) Cratoxylon arborescens (Hypericaceae) Daytyloclados stenostachys (Crypteroniaceae) Dialiumindum (Fabaceae (Leguminosae)) Diospyros cf.evena (Ebenaceae) Diospyros sp. (Ebenaceae)

KFCP Vegetation Monitoring

Local name Karandau merah Bintan Pampaning bitik Tampang Madang litsea Pisang-pisang besar Kambalitan /Pisang-pisang kecil Pupuh palanduk Rambutan hutan Nyatu gagas Nyatu burung Tapakan Sampel mahung/Tambalik angin Marabungkan Kahui Maranti bitik Tabaras tidak akar tinggi Pendu Jambu burung kecil Tabati Himba Kayu lalas daun kecil Tampohot batang Tatumbu Tabunter daun kecil Tabunter daun besar Rambangun Bua bintang Balawan Balawan punei Balawan merah Rasak Rasak napu Jambu burung Kajalaki puti Kayu Tulang/Kopi-kopi Kopi-kopi merah Lombok-lombok/sampel lombok Prupuk keras Sampel Manggis Tatumbu merah Tagula /Jangkang hijau Jangkang kuning Local name Tapanggang Bua dawat Matan undang Kacang nyaring Kayu berang Rambai hutan Bintangor Tarantang Teras nyating Supang Tumih Garunggang Martibu Teras bamban Gulung haduk Malam-malam

Strata S, S/P/T S, S/P/T S, S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S S, S/P/T S, S/P/T S/P/T S, S/P/T S S, S/P/T S/P/T S/P/T S, S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S, S/P/T Strata S/P/T S, S/P/T S, S/P/T S S, S/P/T S, S/P/T S, S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T

Page 53

Location L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07 L07

Scientific name Diospyros sp. (Ebenaceae) Elaeocarpus acmocarpus (Elaeocarpaceae) Elaeocarpus Mastersii (Elaeocarpaceae) Elaeocarpus sp. (Elaeocarpaceae) Elaeocarpus sp. (Elaeocarpaceae) Eugeniaspicata (Mytaceae) Garciniasp. (Clusiaceae (Guttiferae)) Garciniasp.1 (Clusiaceae (Guttiferae)) Garciniasp.2 (Clusiaceae (Guttiferae)) Garciniasp.4 (Clusiaceae (Guttiferae)) Gonystylus bancanus (Thymeleaeaceae) Gymnacranthera parquhariania (Myristicaceae) Horsfieldiacrassifolia (Myristicaceae) Ilex cymosa (Aquifoliaceae) Ilex hypoglauca (Aquifoliaceae) Ixora havilandii (Rubiaceae) Knema intermedia (Myristicaceae) Licania Splendens (Chrysobalanaceae) Lithocarpussp. (Fagaceae) Litsea sp. (Lauraceae) Macaranga caladiifolia (Euphorbiaceae) Mesua sp. (Clusiaceae (Guttiferae)) Mezzetia parviflora (Annonaceae) Mezzetia umbellata (Annonaceae) Neoscortechinia kingii (Euphorbiaceae) Nephellium sp.1 (Sapindaceae) Palaquium cochlearifolium (Sapotaceae) Palaquium sp. (Sapotaceae) Parartocarpus venenosus (Moraceae) Platea sp. (Icacinaceae) Rapanea borneensis (Myrsinaceae) Shoreabalangeran (Dipterocarpaceae) Shoreasp. (Dipterocarpaceae) Shoreateysmanniana (Dipterocarpaceae) Stemonorus scorpiodes (Icacinaceae) Sterculia sp. (Sterculiaceae) Syzygiumsp. (Myrtaceae) Syzygiumsp. (Myrtaceae) Syzygiumsp.1 (Mytaceae) Syzygiumsp.3 (Myrtaceae) Syzygiumsp.4 (Myrtaceae) Ternstromia hosei (Theaceae) Ternstromia magnifica (Theaceae) Tetractomia tetrandra (Rutaceae) Tetrameristaglabra (Tetrameristaceae) Timonius sp. (Rubiaceae) Tristaniopsis sp. (Myrtaceae) Tristaniopsis sp.1 (Myrtaceae) Tristaniopsis sp.2 (Myrtaceae) Unknown Cek di lapangan (Unknown) Unknown Unknown (Dipterocarpaceae) Unknown Unknown (Lauraceae) Unknown Unknown (Myrtaceae) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown)

KFCP Vegetation Monitoring

Local name Kayu arang Patanak daun besar Mangkinang balawau Mangkinang daun besar Kasuhui Kayu lalas daun besar Manggis hutan Aci Gandis Mahalilis Ramin Mandarahan daun kecil Mandarahan daun besar Kambasira Kambasira sumpung Karanji Karandau merah Bintan Pampaning bitik Madang litsea Mahang bitik Tabaras akar tinggi Pisang-pisang besar Kambalitan /Pisang-pisang kecil Pupuh palanduk Rambutan hutan Nyatu gagas Nyatu burung Tapakan Sampel mahung/Tambalik angin Marabungkan Kahui Maranti lampung Maranti bitik Tabaras tidak akar tinggi Pendu Jambu burung kecil Tabati Himba Kayu lalas daun kecil Tampohot batang Tatumbu Tabunter daun kecil Tabunter daun besar Rambangun Ponak Bua bintang Balawan Balawan punei Balawan merah Unknown cek di lapangan Rasak Madang Jambu burung Tatumbu merah Kopi-kopi merah Lombok-lombok/sampel lombok Sampel Manggis Prupuk keras Kayu Tulang/Kopi-kopi

Strata S, S/P/T S S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S, S/P/T S, S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S, S/P/T S, S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T

Page 54

L07 Location L07 L07 Location L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08

Xanthophyllumdiscolour Chod. (Polygalaceae) Scientific name Xylopia cf.malayana (Annonaceae) Xylopia fusca (Annonaceae) Scientific name Aglaia rubignosa (Meliaceae) Antidesma coriaceum (Euphorbiaceae) Antidesma phanerophleum (Euphorbiaceae) Ardisiapyrsocoma B.C.Stone (Myrsinaceae) Baccaurea bracteata (Euphorbiaceae) Calophyllum hosei (Clusiaceae (Guttiferae)) Calophyllum sp. (Clusiaceae (Guttiferae)) Campnosperma coriaceum (Anacardiaceae) Campnosperma squamatum (Anacardiaceae) Clerodendron sp. (Verbenaceae) Combretocarpus rotundatus (Anisophyllaceae) Cratoxylon arborescens (Hypericaceae) Daytyloclados stenostachys (Crypteroniaceae) Dialiumindum (Fabaceae (Leguminosae)) Diospyros cf.evena (Ebenaceae) Diospyros sp. (Ebenaceae) Diospyros sp. (Ebenaceae) Elaeocarpus acmocarpus (Elaeocarpaceae) Elaeocarpus sp. (Elaeocarpaceae) Elaeocarpus sp. (Elaeocarpaceae) Eugeniaspicata (Mytaceae) Garciniasp. (Clusiaceae (Guttiferae)) Garciniasp.1 (Clusiaceae (Guttiferae)) Garciniasp.4 (Clusiaceae (Guttiferae)) Gonystylus bancanus (Thymeleaeaceae) Gymnacranthera parquhariania (Myristicaceae) Horsfieldiacrassifolia (Myristicaceae) Ilex cymosa (Aquifoliaceae) Ixora havilandii (Rubiaceae) Knema intermedia (Myristicaceae) Koompassia malaccensis (Fabaceae (Leguminosae)) Licania Splendens (Chrysobalanaceae) Lithocarpussp. (Fagaceae) Litsea sp. (Lauraceae) Macaranga caladiifolia (Euphorbiaceae) Mezzetia parviflora (Annonaceae) Mezzetia umbellata (Annonaceae) Neoscortechinia kingii (Euphorbiaceae) Nephellium sp.1 (Sapindaceae) Palaquium cochlearifolium (Sapotaceae) Palaquium sp. (Sapotaceae) Palaquium sp. (Sapotaceae) Parartocarpus venenosus (Moraceae) Platea sp. (Icacinaceae) Rapanea borneensis (Myrsinaceae) Shoreabalangeran (Dipterocarpaceae) Shoreateysmanniana (Dipterocarpaceae) Stemonorus scorpiodes (Icacinaceae) Sterculia sp. (Sterculiaceae) Syzygiumsp. (Myrtaceae) Syzygiumsp.1 (Mytaceae) Syzygiumsp.3 (Myrtaceae) Syzygiumsp.4 (Myrtaceae) Ternstromia hosei (Theaceae) Ternstromia magnifica (Theaceae)

KFCP Vegetation Monitoring

Kamuning Local name Tagula /Jangkang hijau Jangkang kuning Local name Kajalaki Bua dawat Matan undang Kayu berang Rambai hutan Bintangor Kapurnaga kalakai Tarantang Teras nyating Supang Tumih Garunggang Martibu Teras bamban Gulung haduk Malam-malam Kayu arang Patanak daun besar Mangkinang daun besar Kasuhui Kayu lalas daun besar Manggis hutan Aci Mahalilis Ramin Mandarahan daun kecil Mandarahan daun besar Kambasira Karanji Karandau merah Bangaris/Kempas Bintan Pampaning bitik Madang litsea Mahang bitik Pisang-pisang besar Kambalitan /Pisang-pisang kecil Pupuh palanduk Rambutan hutan Nyatu gagas Nyatu undus Nyatu burung Tapakan Sampel mahung/Tambalik angin Marabungkan Kahui Maranti bitik Tabaras tidak akar tinggi Pendu Jambu burung kecil Kayu lalas daun kecil Tampohot batang Tatumbu Tabunter daun kecil Tabunter daun besar

S/P/T Strata S, S/P/T S, S/P/T Strata S/P/T S, S/P/T S, S/P/T S, S/P/T S, S/P/T S, S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S, S/P/T S/P/T S S/P/T S/P/T S, S/P/T S/P/T S, S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S, S/P/T S/P/T S S/P/T S/P/T S, S/P/T

Page 55

L08 Location L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08 L08

Tetractomia tetrandra (Rutaceae) Scientific name Timonius sp. (Rubiaceae) Tristaniopsis sp. (Myrtaceae) Tristaniopsis sp.1 (Myrtaceae) Tristaniopsis sp.2 (Myrtaceae) Unknown tunggu info Herbarium (Unknown) Unknown Unknown (Dipterocarpaceae) Unknown Unknown (Lauraceae) Unknown Unknown (Myrtaceae) Unknown Unknown (Myrtaceae) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Unknown Unknown (Unknown) Xylopia cf.malayana (Annonaceae) Xylopia fusca (Annonaceae)

KFCP Vegetation Monitoring

Rambangun Local name Bua bintang Balawan Balawan punei Balawan merah Tunggu info Herbarium Rasak Madang Jambu burung Jambu-jambu Kajalaki puti Prupuk keras Sampel Manggis sampel jambu biji Kopi-kopi merah Lombok-lombok/sampel lombok Tatumbu merah Tagula /Jangkang hijau Jangkang kuning

S, S/P/T Strata S/P/T S/P/T S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S/P/T S/P/T S/P/T S, S/P/T S, S/P/T S, S/P/T

Page 56

7.2 Tree species list Table 7.2: Species dominance (top five most dominant species shown) with respect to location, distance from canal (where relevant) and tree maturity stage.

Note: Blank rows indicate no individuals present.

Location

Distance from canal

Tree maturity

L02

50 m

Seedling

L02

50 m

Sapling

L02

Ranking 1 Species

50 m

Pole

L02

50 m

Tree

L02

100 m

Seedling

L02

100 m

Sapling

L02

100 m

Pole

L02

100 m

Tree

L02

400 m

Seedling

L02

400 m

Sapling

L02

400 m

Pole

L02

400 m

Tree

L02

700 m

Seedling

L02

700 m

Sapling

L02

700 m

Pole

700 m

Tree

L02

KFCP Vegetation Monitoring

Ranking 2 %

Cratoxylum arborescens

100

- Diospyros sp.

- Elaeocarpus mastersii - Combretocarpus rotundatus - Syzygiumsp.3 - Cratoxylum arborescens

26

Species

Ranking 3 %

Ranking 4

Ranking 5

Species

%

Species

%

Species

%

Antidesma montanum

21

Syzygiumsp.3

16

- Syzygiumsp.

- Ilex cymosa

5

33

Page 57

Location

Distance from canal

Tree maturity

Ranking 1

Ranking 2

Ranking 3

Species

%

Species

%

Cratoxylum arborescens - Garciniasp.

- Gymnacranthera parquhariania - Cratoxylum arborescens

33

L03

50 m

Seedling

Shoreabalangeran

67

L03

50 m

Sapling

Antidesma coriaceum

40

L03

50 m

Pole

L03

50 m

Tree

Combretocarpus rotundatus

100

L03

100 m

Seedling

L03

100 m

Sapling

L03

100 m

Pole

L03

100 m

Tree

L03

400 m

Seedling

L03

400 m

Sapling

L03

400 m

L03

400 m

L03

44

Combretocarpus rotundatus

19

Combretocarpus rotundatus

75

Diospyros areolata

25

Ilex cymosa Baccaurea bracteata

48

Syzygiumsp.

Unknown unknown (Myrtaceae)

20

Pole

Stemonurus scorpioldes

100

Tree

Combretocarpus rotundatus

700 m

Seedling

L03

700 m

L03

700 m

L03

700 m

9

56

- Tristaniopsis sp.2 - Xylopia cf.malayana - Diospyros areolata - Shoreateysmanniana

11

Shoreabalangeran

24

Antidesma montanum

12

Sapling

Antidesma coriaceum

14

Tetractomia obovatum

10

Pole

Tetractomia obovatum

20

- Shoreateysmanniana - Garciniasp.

11

Tree

Diospyros areolata

46

Combretocarpus rotundatus

18

KFCP Vegetation Monitoring

Ranking 4 %

Species

Ranking 5 %

Species

%

13

- Koompassia malaccensis - Elaeocarpus acmocarpus

6

12

- Antidesma montanum - Antidesma coriaceum - Sandoricum beccarianum

4

Antidesma coriaceum

6

20

Shoreabalangeran

17

Species

- Unknown unknown (Lauraceae) Archidendronborneensis

Ixora havilandii Shoreabalangeran

- Diospyros areolata Archidendronborneensis - Unknown unknown (Myrtaceae) - Garciniasp.

- Mezzetia parviflora - Horsfieldiacrassifolia - Daytyloclados stenostachys

7.5

Stemonurus scorpioldes Antidesma coriaceum Lithocarpussp.

8 6.8

10 5.2

- Stemonurus scorpioldes - Lithocarpussp.

- Horsfieldiacrassifolia

Lithocarpussp.

5.0

7

7

Page 58

Location

Distance from canal

Tree maturity Species

Ranking 1 %

Species

Ranking 2 %

Seedling

Garciniasp.

18

Unknown unknown (Myrtaceae)

12

Ranking 3 Species - Palaquium cochleariifolium - Lithocarpussp.

- Clerodendrum sp.

- Ixora havilandii - Macaranga caladiifolia

Ranking 4 %

L04

50 m

L04

50 m

Sapling

Lithocarpussp.

20

Garciniasp.

13

Unknown unknown

9

L04

50 m

Pole

28

Shoreateysmanniana

22

Garciniasp.

17

L04

50 m

Tree

Lithocarpussp.

- Palaquium cochleariifolium - Unknown unknown - Shoreateysmanniana

8 8

Seedling

Antidesma montanum

42

Lithocarpussp.

17

100 m

Sapling

Lithocarpussp.

20

12

Cotylelobium lanceolatum

L04

100 m

Pole

Lithocarpussp.

30

L04

100 m

Tree

Combretocarpus rotundatus

50

Unknown unknown - Shoreateysmanniana - Xylopia fusca - Mezzetia parviflora - Palaquium cochleariifolium - Shoreabalangeran - Diospyros areolata

L04

400 m

Seedling

27

Lithocarpussp.

13

Syzygiumsp.

L04

400 m

Sapling

20

Tetrameristaglabra

11

Antidesma coriaceum

100 m

L04

KFCP Vegetation Monitoring

Shoreabalangeran Unknown unknown (Myrtaceae)

Ranking 5 %

Species

%

7

- Unknown unknown (Lauraceae) - Cotylelobium lanceolatum

5

Xanthophyllumdiscolour - Clerodendrum sp.

- Diospyros areolata - Tetractomia obovatum

6

Palaquium cochleariifolium

10

Shoreateysmanniana

4

9

Stemonurus scorpioldes - Unknown unknown (Lauraceae) - Xylopia fusca - Unknown unknown (Myrtaceae) - Garciniasp.1 - Horsfieldiacrassifolia - Palaquium cochleariifolium

6

33 - Cotylelobium lanceolatum - Elaeocarpus acmocarpus

L04

Species

- Garciniasp.

- Unknown unknown

6

20

17 12

- Unknown unknown (Lauraceae) - Antidesma coriaceum

6

9.3

Tetractomia obovatum

8.7

Page 59

Location

Distance from canal

Tree maturity

Ranking 1 Species - Garciniasp.

- Mezzetia parviflora - Palaquium cochleariifolium

Species

Ranking 3 %

Species

Ranking 4 %

Species

32

Combretocarpus rotundatus

26

Diospyros areolata

11

- Tetractomia obovatum - Stemonurus scorpioldes - Lithocarpussp - Shoreateysmanniana - Syzygiumsp - Daytyloclados stenostachys - Tetrameristaglabra - Horsfieldiacrassifolia - Palaquium cochleariifolium

17

Syzygiumsp.

15

Stemonurus scorpioldes

11

Macaranga caladiifolia

21

Tetractomia obovatum

7

Tetrameristaglabra

6.5

Tetractomia obovatum

16

Garciniasp.

11

Xylopia fusca

Combretocarpus rotundatus

33

Calophyllum soualattri Diospyros areolata

13

Garciniasp.

- Nephellium sp.1 - Xylopia cf.malayana - Garciniasp.1 - Calophyllum hosei - Syzygiumsp.1 - Unknown unknown (Lauraceae)

L04

400 m

Pole

L04

400 m

Tree

L04

700 m

Seedling

L04

700 m

Sapling

Unknown unknown (Lauraceae) Unknown unknown (Myrtaceae) Unknown unknown (Myrtaceae)

L04

700 m

Pole

L04

700 m

Tree

KFCP Vegetation Monitoring

Ranking 2 %

9

9

Ranking 5 %

Species

%

8

Antidesma montanum

6

6.0

Antidesma coriaceum

5.8

7

5

7 8

Page 60

Location

Distance from canal

Tree maturity

L05

50 m

Seedling

L05

50 m

Sapling

L05

50 m

Pole

L05

50 m

Tree

L05

100 m

Seedling

L05

100 m

Sapling

L05

100 m

Pole

L05

100 m

Tree

L05

400 m

Seedling

L05

400 m

Sapling

L05

400 m

Pole

L05

400 m

Tree

L05

700 m

Seedling

L05

700 m

Sapling

L05

700 m

Pole

L05

700 m

Tree

KFCP Vegetation Monitoring

Ranking 1 Species

%

Tetractomia obovatum

100

Antidesma montanum

100

Combretocarpus rotundatus Combretocarpus rotundatus Combretocarpus rotundatus Antidesma coriaceum Combretocarpus rotundatus Combretocarpus rotundatus

Ranking 2 Species

%

Cratoxylum arborescens

2

Litsea sp.

5

Ranking 3 Species

%

Alseodaphne coriacea

3

Ranking 4 Species

%

Ranking 5 Species

%

100 98 100 100 91 100

Page 61

Location

Distance from canal

Tree maturity

L06

50 m

Seedling

Antidesma coriaceum

23

Ixora havilandii

14

Ranking 3 Species - Adenanthera pavonina - Elaeocarpus acmocarpus - Neoscortechinia kingii

L06

50 m

Sapling

Baccaurea bracteata

25

13

Tetramerista glabra

11

Ilex cymosa

6

L06

50 m

Pole

Rapanea borneensis

62

16

Horsfieldia crassifolia

10

Elaeocarpus acmocarpus

6

- Mezzetia umbellata - Rapanea borneensis Unknown unknown (Lauraceae)

L06

50 m

Tree

Rapanea borneensis

60

Antidesma coriaceum Gymnacranthera parquhariania - Cratoxylum arbourescens - Litsea angulata

L06

100 m

Seedling

23

Baccaurea bracteata

21

Antidesma coriaceum

13

Ixora havilandii

8

100 m

Sapling

20

Garcinia sp.

9

Adenanthera pavonina - Rapanea borneensis - Baccaurea bracteata

15

L06

100 m

Pole

26

19

Shorea teysmanniana

16

Cratoxylum arborescens

10

L06

100 m

Tree

67

Rapanea borneensis - Shorea teysmanniana - Shorea smithiana

Syzygium sp.1 - Lithocarpus sp.

- Shorea balangeran

5

L06

Lithocarpus sp.

Unknown unknown (Myrtaceae) Unknown unknown (Lauraceae) Combretocarpus rotundatus

L06

400 m

Seedling

22

Adenanthera pavonina

12

Ixora havilandii

7

6

L06

400 m

Sapling

Unknown unknown (Myrtaceae) Unknown unknown (Myrtaceae)

- Calophyllum hosei - Tristaniopsis sp.1 - Ilex cymosa - Lithocarpus sp.

20

Tetractomia obovatum

17

Ixora havilandii

9

Antidesma coriaceum

3.6

L06

400 m

Pole

Rapanea borneensis

11

- Shorea teysmanniana - Xylopia fusca

10

L06

400 m

Tree

18

Shorea teysmanniana

15

Campnosperma coriaceum

12

L06

700 m

Seedling

Combretocarpus rotundatus Unknown unknown (Myrtaceae)

Lithocarpus sp.

- Garcinia sp.

- Unknown unknown (Myrtaceae) - Rapanea borneensis - Daytyloclados stenostachys - Diospyros areolata

18

13

Adenanthera pavonina

12

L06

700 m

Sapling

Tetractomia obovatum

18

Ixora havilandii Unknown unknown (Myrtaceae)

15

Ixora havilandii

5

L06

700 m

Pole

Garcinia sp.

12

- Rapanea borneensis - Xylopia fusca

KFCP Vegetation Monitoring

Ranking 1

Ranking 2

Species

%

Species

%

Ranking 4 %

Ranking 5

Species

%

9

Species

%

5 3

20

7

17

11

Palaquium cochleariifolium

4.3 8

Licania splendens - Antidesma montanum - Elaeocarpus sp.

9

Baccaurea bracteata - Syzygium sp.1 - Tristaniopsis sp.2 - Unknown unknown (Myrtaceae)

4

7

6

6

6 Lithocarpus sp.

3

6

Page 62

L06

700m

Location

Tree maturity

Tree

Daytyloclados stenostachys

15

Ranking 1

Combretocarpus rotundatus

12

- Palaquium cochleariifolium - Shorea balangeran - Shorea teysmanniana - Parartocarpus venenosus

Ranking 2

9

Ranking 3

Ranking 4

Ranking 5 Species - Diospyros evena - Syzygium sp.

- Ixora havilandii

Species

%

Species

%

Species

%

Species

%

21

Diospyros areolata

16

Stemonurus scorpioldes

12

Tetractomia obovatum

5

13

Tetractomia obovatum

8

5

Timonius sp.

4.0

Ilex cymosa

3.8

13 25

Litsea sp.

Diospyros areolata

8 21

Stemonurus scorpioldes Unknown unknown (Myrtaceae) Palaquium sp.

7 8

Shorea teysmanniana Shorea teysmanniana

6.1 6

Stemonurus scorpioldes Combretocarpus rotundatus

5.6 5

L01

Seedling

L01

Sapling

Unknown unknown Unknown unknown (Myrtaceae)

L01 L01

Pole Tree

Campnosperma coriaceum Campnosperma coriaceum

KFCP Vegetation Monitoring

% 4

Page 63

Location

Tree maturity

L07

Seedling

Ranking 1 Species Unknown unknown (Myrtaceae)

Ranking 2

Ranking 3

Ranking 4

L07

Sapling

Tetractomia obovatum

20

L07

Pole

19

L07

Tree

Palaquium cochleariifolium Combretocarpus rotundatus

Tetractomia obovatum Unknown unknown (Myrtaceae) Unknown unknown (Myrtaceae)

34

Campnosperma coriaceum

22

Shorea teysmanniana Daytyloclados stenostachys

Location

Tree maturity Species

%

%

Species

%

Species

%

Species

%

21

11

Palaquium cochleariifolium

6.0

Tetractomia obovatum

5.7

12

Palaquium cochleariifolium

5

Stemonurus scorpioldes Unknown unknown (Myrtaceae) - Syzygium sp.1 - Sterculia sp.

- Gonystylus bancanus - Shorea balangeran

4

Species

%

Species

%

Species

%

Species

%

21

15

Antidesma coriaceum

11

Stemonurus scorpioldes

10

Ixora havilandii

9

16

Ixora havilandii

7

6

Palaquium cochleariifolium

4

10

8

Antidesma coriaceum - Stemonurus scorpioldes - Rapanea borneensis

- Rapanea borneensis - Calophyllum hosei

5

Ranking 1

7

6

L08

Seedling

Ixora havilandii

23

Ranking 2 Species Unknown unknown (Myrtaceae)

L08

Sapling

Tetractomia obovatum

23

Ixora havilandii

12

Stemonurus scorpioldes Unknown unknown (Myrtaceae)

L08

Pole

Campnosperma coriaceum

22

Palaquium cochleariifolium

12

Syzygium sp.1

9

Calophyllum hosei

L08

Tree

Combretocarpus rotundatus

49

Campnosperma coriaceum

36

Calophyllum hosei

6

Daytyloclados stenostachys

KFCP Vegetation Monitoring

Ranking 5

%

Ranking 3

Ranking 4

Ranking 5

7.3

5

6.5

1

Page 64