Rapid carbon stock appraisal

Rapid carbon stock appraisal

Kalahan, Nueva Vizcaya, Philippines

Grace B. Villamor, Nelson Pampolina, Reginald Forcadilla, Nonoy Bugtong, Jerome Alano, Delbert Rice, Tina Omas,

Reymar Castillo, Dennis Pulan

Rapid carbon stock appraisal Kalahan, Nueva Vizcaya, Philippines

Grace B. Villamor, Nelson Pampolina, Reginald Forcadilla, Nonoy Bugtong, Jerome Alano, Delbert Rice, Tina Omas, Reymar Castillo, Dennis Pulan

Working paper 106

LIMITED CIRCULATION Correct citation Villamor GB, Pampolina N, Forcadilla R, Bugtong N, Alano J, Rice D, Omas T, Castillo R, Pulan D. 2010. Rapid Carbon Stock Appraisal: Kalahan, Nueva Vizcaya, Philippines. Working paper 106. Bogor, Indonesia: World Agroforestry Centre (ICRAF) Southeast Asia Program. 87p Titles in the Working Paper series disseminate interim results on agroforestry research and practices to stimulate feedback from the scientific community. Other publication series from the World Agroforestry Centre include agroforestry perspectives, technical manuals and occasional papers. Published by the World Agroforestry Centre (ICRAF) Southeast Asia Program PO Box 161, Bogor 16001, West Java, Indonesia Tel: +62 251 8625415 Fax: +62 251 8625416 Email: [email protected] http://www.worldagroforestrycentre.org/sea © World Agroforestry Centre 2010 Working Paper 106 The views expressed in this publication are those of the author(s) and not necessarily those of the World Agroforestry Centre. Articles appearing in this publication may be quoted or reproduced without charge, provided the source is acknowledged. All images remain the sole property of their source and may not be used for any purpose without written permission of the source.

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About the authors

Grace Villamor Grace Villamor is currently a researcher at the Center for Development Research (ZEF) in Bonn, Germany, and a research fellow under the REDD ALERT project of the World Agroforestry Centre in Southeast Asia. Prior to that, she was involved in the Rewarding Upland Poor for Environmental Services they provide (RUPES phase 1) program in the Philippines where she was working together with the Kalahan Educational Foundation for developing rewards schemes for carbon sequestration and biodiversity conservation. Contact: [email protected] Nelson P. Pampolina Nelson P. Pampolina is an Associate Professor and Coordinator for Research Extension and Linkages in the College of Forestry and Natural Resources, University of the Philippines at Los Baños. Contact: [email protected] Reginald Forcadilla Reginald Forcadilla is a forester from the University of the Philippines at Los Baños. Contact: [email protected] Nonoy Bugtong Nonoy Bugtong is an Agroforester with the Kalahan Educational Foundation. Jerome Alano Jerome Alano is a GIS specialist at the ASEAN Biodiversity Centre. Contact: [email protected] Delbert Rice Delbert Rice is the Director for Research at the Kalahan Educational Foundation. Contact: [email protected]. Tina Omas Tina Omas is an Agroforester with the Kalahan Educational Foundation. Reymar Castillo Reymar Castillo is a Forester at the University of the Philippines at Los Baños. Contact: [email protected] Dennis Pulan Dennis Pulan is a Dendrologist at the University of the Philippines at Los Baños.

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Abstract A research method called Rapid Carbon Stock Appraisal (RaCSA) was conducted in Kalahan Forest Reserve (KFR), in Nueva Vizcaya Province, Northern Luzon, Philippines from August 2009 to January 2010. The aim of this activity was to support communities, such as the Ikalahan people, to establish basic data needed in negotiating with carbon markets in a cost-effective and time-efficient manner. The appraisal involved a combination of methods and activities (for example, plot-level carbon measurement, spatial analysis of land-use cover, focus group discussions, key informant interviews and a review of the literature).

There were several key results of the appraisal.

• Land-use types and farming practices. The majority of Ikalahan are swidden farmers practising traditional farming (for example, pang-omis, which involves integrating tree seedlings of species such as Alnus in the swidden farms). Five major land-use and land-cover types were identified and assessed, that is, agriculture, agroforest, grassland, reforestation and secondary forests.

• Plot-level carbon stocks. The estimated carbon stock of land-use systems in the KFR ranged 0.61–77.86 Mg/ha for aboveground carbon; and 21.8–67.4 Mg/ha for belowground. Total (above- and belowground) carbon stock was estimated to range 54.31–151.13 Mg/ha. These results are low compared to other carbon assessments conducted in the country.

• Land-use and land-cover changes. Land-use and land-cover changes within KFR between 1981 and 2001 were assessed. A decrease in forest, pine and agriculture occurred while there was an increase in old pine and reforestation (for example, mahogany). Carbon values from monitoring plots in 1994 and 2003 were used to extrapolate the land-cover types of the 1981 and 2001 maps, respectively. Based on the results, total carbon stock was approximately 375.8 Gg in 1994 and 452.1 Gg in 2003, that is, a 21% increase in 12 years.

• Carbon emissions. From the land-cover changes, we estimated that the KFR sequestered carbon annually at an average of 0.5 Gg and that 1.4 Gg of carbon was emitted each year over the period 1989 to 2001.

• The Kalahan Educational Foundation is the major stakeholder in the KFR. It has established its own rules and regulations related to natural resources development and has supported traditional farming practices and management strategies (for example, their ‘forest improvement technology’) to enhance the carbon stock within the KFR. Currently, the Foundation is exploring the Clean Development Mechanism market. Future options and their implications for the KFR are included in the paper.

Keywords

carbon stock assessment, farming practices, Ikalahan Ancestral Domain, land-use change

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Acknowledgements The RaCSA implementation was conducted by the Kalahan Educational Foundation in collaboration with the Forest Biological Sciences Department, College of Forestry and Natural Resources, University of the Philippines at Los Baños, Laguna, and the World Agroforestry Centre (ICRAF) Southeast Asia Program through the Trees in Multi-Use Landscapes in Southeast Asia project (funded by the German Federal Ministry for Economic Cooperation and Development (BMZ)) and the Rewards for, Use of, and Shared Investment in Pro-poor Environmental Services phase 2 program.

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Contents 1. Introduction ..................................................................................................................... 1

2. Land Tenure and Ownership ......................................................................................... 3

2.1 Carbon Stocks Assessment .......................................................................................... 3

3. Objectives of the study and expected outputs ............................................................... 5

3.1 Objectives: ................................................................................................................... 5

3.2 Expected Output: ......................................................................................................... 5

4. Methodology ..................................................................................................................... 7

4.1 Site Orientation and Reconnaissance Survey .............................................................. 7

4.2 Selection of Prospective Sites ..................................................................................... 7

4.3 Site Preparation and Establishment of Sampling Transect .......................................... 7

4.4 Sampling sites and major land uses ............................................................................. 8

4.5 Primary and Secondary Data Collection and Processing .......................................... 10

5. Results and Discussion .................................................................................................. 13

5.1 Farming and Livelihood Conditions .......................................................................... 13

5.2 Land Use Characteristics and Practices ..................................................................... 18

5.3 Plant Diversity and Composition .............................................................................. 21

5.4 Carbon Stocks ........................................................................................................... 23

5.5 Land Use Change Dynamics in KFR ........................................................................ 29

5.6 Carbon emissions by land use/cover change ............................................................. 35

5.7 Carbon Offset Options............................................................................................... 39

5.8 Scenario Building and Future options ....................................................................... 40

6. Conclusion and recommendation ................................................................................. 43

6.1 Conclusion ................................................................................................................. 43

6.2 Recommendation ....................................................................................................... 43

References .............................................................................................................................. 45

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List of Tables

Table 1. Major land-use types identified ................................................................................... 9

Table 2. Physical areas devoted to rice by production environment (in hectare), selected barangays, Sta. Fe, Nueva Vizcaya, 2000 ................................................................. 13

Table 3. Livelihoods of the people (percentage) ..................................................................... 14

Table 4. Summary of livelihoods’ assessment in the KFR ...................................................... 15

Table 5. Physical area devoted to fruits and vegetable production (in hectare), selected barangays, Sta. Fe, Nueva Vizcaya, 2000 ................................................................. 15

Table 6. Mean cropping, fallow periods and cycle lengths employed by selected farmers in the KFR ................................................................................................................. 17

Table 7. Characteristics of the different land uses and practices of local communities in the KEF mountain ecosystem ......................................................................................... 19

Table 8. Characteristics and activities of various key drivers of change in the Kalahan landscape ................................................................................................................... 20

Table 9. Percentage of trees with different diameter ranges from various land uses .............. 21

Table 10. Population density per plot in the canopy, intermediate and undergrowth layers in different land uses ................................................................................................. 22

Table 11. Plot-level aboveground biomass carbon stocks ....................................................... 23

Table 12. Mean aboveground carbon stocks in land uses sampled in the KFR ...................... 24

Table 13. Plot-level belowground biomass carbon-stock ........................................................ 24

Table 14. Mean belowground carbon stocks in land uses sampled in the KFR ...................... 25

Table 15. Soil carbon and carbon stock ................................................................................... 25

Table 16. Mean soil carbon-stock per land use ....................................................................... 26

Table 17. Plot-level mean carbon-stock of each land use ....................................................... 26

Table 18. Total carbon stock at plot-level in the KFR ............................................................ 26

Table 19. Land-cover classes in the KFR, 1989 ...................................................................... 29

Table 20. Land-cover classes in the KFR, 2001 ...................................................................... 30

Table 21. Land-cover changes between 1989 and 2001 (area in ha) ....................................... 32

Table 22. Mean biomass in 1994 and 2003 and the blocks and plots sampled ....................... 33

Table 23. Carbon densities based on biomass-monitoring plots in the KFR ........................... 33

Table 24. Plots with very high estimated carbon densities ...................................................... 35

Table 25. Land-cover types and carbon densities used ........................................................... 35

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Table 26. Mean carbon emissions from land-use changes, 1994–2003 .................................. 37

Table 27. Mean carbon emissions per year, 1994–2003 ......................................................... 38

Table 28. Future options and their implications for the KFR .................................................. 40

List of Figures

Figure 1. Location of Kalahan Forest Reserve .......................................................................... 4

Figure 2. Sampling sites where five major land uses were observed ........................................ 8

Figure 3. Nested plot design for sampling various carbon stocks ............................................. 9

Figure 4. Percentage of species’ composition in three structural layers in various land uses . 23

Figure 5. Total (above- and belowground) carbon stocks and their relative composition in the KFR (Upper panel: absolute values in Mg/ha. Lower panel: as percentage) ..... 27

Figure 6. Distribution of land-cover-derived carbon density in the KFR, based on a carbon-stock estimate (2009) ............................................................................................... 28

Figure 7. Land-cover classes in the KFR, 1989 ...................................................................... 29

Figure 8. Land-cover map of the KFR, 1989 .......................................................................... 30

Figure 9. Land-cover classes in the KFR, 2001 ...................................................................... 30

Figure 10. Land-cover map of the KFR, 2001 ........................................................................ 31

Figure 11. Overall land-cover change within the KFR............................................................ 31

Figure 12. Distribution of land-cover-derived carbon density in the KFR in 1989 (upper panel) and 2001 (lower panel) .............................................................................. 34

Figure 13. Target sites for CDM project (red dots) ................................................................. 39

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1. Introduction

The Ikalahans are the indigenous people of the province of Nueva Vizcaya, northeastern Philippines. They belong to the Kalanguya-Ikalahan tribe and inhabit the Ikalahan Ancestral Domain. They are largely swiddeners who plant sweet potato, ginger, gabi, cassava and vegetables and build terraces to grow upland rice.

Encompassing a total of 38 000 ha, the Ikalahan Ancestral Domain, of which the Kalahan Forest Reserve comprises 14 730 ha, lies in the Cordillera and Caraballo mountains and is overlooked by Mt Akbob (1658 m) in the northwest and Mt Talabing (1717 m) in the southwest (KEF 1993). Dividing the watershed between the two peaks and determining the water flow lies a ridge known as Bantay Lakay. Elevation varies 600–1717 m above sea level, with average annual rainfall recorded at over 4000 mm and temperatures ranging 8–24 ˚C (RUPES website1). The majority of the forests are secondary and for the most part tree species found in this entirely mountainous region are endemic dipterocarps. There are also areas where the coverage is predominantly pine or oak on the western and apex zones of the ridge respectively. The study covered approximately 10 000 ha, excluding the grasslands and sanctuary regions.

In 1973, the Kalahan Educational Foundation (KEF) was established by the Ikalahan tribal elders to protect their communities from possible eviction because the Government at that time was unable to defend their rights. The Foundation’s mission is to promote the education of the Ikalahan people and protect the environment of their ancestral domain. Among its aims is to provide sustainable, forest-based livelihoods, improved watersheds and biodiversity (KEF 1993). From its inception, KEF has been recognised as a community-based organization. It legally represents the Ikalahans in their community-based forest management agreement, in which they are the pioneers in the Philippines.

1 http://rupes.worldagroforestry.org/researchsite_kalahan/2

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2. Land tenure and ownership

The Indigenous Peoples’ Rights Act of 1997 (RA 8371) strengthens the rights of the Ikalahan to their ancestral land and led to the approval in 1999 of their ancestral domain claims that cover 58 000 ha.

Other laws such as the Wildlife Resources Conservation and Protection Act of 2001 (RA 9147) and the National Integrated Protected Areas System of 1992 (RA 7586) are legal mandates to establish and protect critical habitats and species.

Further, the Memorandum of Agreement No. 1 of 1973 is an agreement between the KEF and the Bureau of Forest Development that recognizes the rights of the Ikalahans to manage their ancestral land and ‘utilize the area to the exclusion of all other parties not already “subsisting” within the area at the time of signing’. The agreement specifically allocated 14 730 ha of land to be managed directly by the Ikalahan through the KEF for a period of 25 years, renewable for another 25 years.

2.1 Carbon-stock appraisal

The KEF is currently developing a 900 ha Clean Development Mechanism (CDM) project inside the ancestral domain. The results of a Rapid Carbon Stock Appraisal (RaCSA) were intended to provide essential baseline information for the negotiation of carbon credits with potential carbon buyers. The appraisal would also help provide experience and insight into reducing the transaction cost of such projects.

RaCSA is part of a ‘negotiation support toolbox’ for rapid appraisal of landscapes developed by the World Agroforestry Centre (ICRAF) Southeast Asia Program through the Trees in Multi-Use Landscapes in Southeast Asia project. The project had several aims.

1) Bridge the gaps between local, public/policy and scientific modellers’ knowledge.

2) Increase recognition and respect for these multiple knowledge systems.

3) Provide quantification of trade-offs between economic and environmental impacts at landscape scale.

4) Enable joint analysis of plausible scenarios based on available data and information.

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Figure 1. Location of Kalahan Forest Reserve.

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3. Objectives of the study and expected outputs

3.1 Objectives

1. To identify the different land-use practices at the site and the key drivers of change in the landscape.

2. To estimate the carbon stocks of the main land uses at plot and landscape levels.

3. To assess the opportunity to use or adjust policy frameworks to enhance or maintain the carbon stocks in the area.

4. To complete the modelling of land-use and carbon dynamics of the Kalahan using GIS and/or remote sensing.

3.2 Expected outputs

1. Carbon stock per land-cover and land-use assessed and calculated.

2. Land-use practices that enhance or maintain carbon stocks identified and documented.

3. Results from the carbon-stock appraisal used as the baseline for the CDM project (initial stage of development of the project design document).

4. Scenarios featuring different drivers of change in the landscape (using remote sensing) presented and assessed.

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4. Methodology

4.1 Site orientation and reconnaissance

The research team was oriented by community representatives regarding the purpose of the carbon-stock study and the coverage of the project site (Figure 1). Available maps (for example, topographic and vegetation) were useful in identifying the various land uses within the 48 000 ha ancestral domain. A three-dimensional model of the area was instrumental in gaining appreciation of the whole site and approximating logistics and costings prior to fieldwork (Figure 2). Reconnaissance was conducted in September 2009 to finalise the carbon-stock study sites.

4.2 Selection of sites

The major land uses in the study area were first identified using the vegetation maps and the results of the reconnaissance with farmers and through secondary data. The sites were selected by locating areas that had high conservation values in the context of the appraisal. This step involved identifying areas with one or more features such as a high richness of species; featured ‘flagship’ species; enjoyed a unique habitat; or were experiencing rapid resource or habitat degradation. These features were considered against the various land uses and local human populations. The secondary data available from the KEF were used as baseline information. Participatory mapping was conducted involving the community and other stakeholders, forming part of the capacity-building strategy of the project. A total of five land uses from fifteen barangays (smallest government unit in the Philippines) within the KEF were identified. All sites were classified as secondary forest, agroforest farm, agricultural area, grassland or reforestation (Table 1). The corresponding land uses were situated in two or more sites.

4.3 Site preparation and establishment of sampling transects

The sampling sites and transects were prepared by measuring and pegging 20 m x 100 m plots in the various land uses (Figure 3). Two sampling transects were established for each land use to estimate carbon stock above- and belowground. We used a metre tape to measure distance and GPS Garmin to locate the coordinates. Each sampling transect was demarcated to obtain the following.

• Tree species, with diameter at breast height of 5.0 cm and above within the whole transect.

• Plants in the intermediate layer, with diameter below 5.0 cm and height of above 1 m sampled in a 3 m x 3 m sub-plot within the transect plot.

• Undergrowth vegetation, with height below 1 m sampled within four smaller sub-plots measuring 1 m x 1 m each.

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• Necromass or litter fall, collected from one plot in the intermediate layer and four plots in the undergrowth, with each plot measuring 0.25 m x 0.25 m.

• Soil, sampled using a trowel (5 cm diameter and 30 cm length), at depths of 0–20 and 20–30 cm.

For each of the land-use samples, the team used a slightly modified protocol from the ASB Lecture Note 4b (Hairiah et al. 2001).

4.4 Sampling sites and major land uses

Figure 2. Sampling sites where five major land uses were observed.

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Table 1. Major land-use types identified

No. Identified land uses Subsets Barangay Plot Code 1. Secondary forest • Pine‐dominated

• Dipterocarp‐dominated • Myrtaceous oak‐

dominated

Sta. Rosa Baracbac Malico

S1T1 S4T1 S2T1

2. Agroforest • Tree‐crop/fruit‐crop Sta. Rosa Baracbac Bacneng

S1T2 S4T2 S5T1

3. Agriculture • Garden/vegetable • Swidden/fallow

Bacneng Tactac Atbu

S5T2 S6T2 S7T1

4. Grassland • Abandoned • Pasture • Pure grassland

Atbu Sta. Rosa Malico

S7T2 S2T4 S2T3

5. Reforestation • Old rehabilitated • Pine‐ and Alnus‐

dominated

Bacneng Imugan

S5T1 S8T3 S8T1

Figure 3. Nested plot design for sampling various carbon stocks.

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4.5 Primary and secondary data collection and processing

4.5.1 Taxonomic characterisation

All vascular plants within the established transect were identified using local names and were verified using morphological characteristics from the field and herbarium collection at the KEF and the University of the Philippines at Los Baños museum. The identity of plants was further verified from references. Unknown plants were kept for future verification and their codes were used in the computation of parameters. Sterile samples of known and unknown species were collected for herbarium purposes and were preserved at the KEF and the university. The taxonomic list was prepared showing local, scientific and family names and plant habitat.

4.5.2 Measurement of biometrics and biomass

The height and diameter of trees at breast height (DBH) in the canopy and intermediate layers within the transect plot were estimated in metres and measured with a diameter tape, respectively, for proper encoding in an MS Excel spreadsheet (Figure 4).

Plant density, or the number of individuals in each layer, and transect plots were counted using the formula:

Plant Density (N) = Density of each plant species Unit Area of Sampling Plot

The biomass of each plant in the canopy, intermediate and undergrowth layers, together with leaf litter, was computed using the following:

a. Allometric regression for aboveground biomass of all trees greater than 5.0 cm DBH using the equation prepared by Ketterings et al. (2001):

y = 0.11 p D 2.62

where y = aboveground tree biomass

p = average wood density equivalent to 0.9035 gram.cc-1 (Pulhin 2008)

D = tree DBH

b. Estimated belowground biomass in trees and intermediate layers was equivalent to 15% of the aboveground tree biomass as proposed by Delany (1999).

c. Destructive harvesting of randomly sampled above- and belowground biomass of undergrowth plants represented by mean values of 5–10 samples of either wildling indigenous tree and agroforestry species, agricultural crops, grass, shrubs, vines, ferns or palms.

d. Actual samplings of litter fall to represent necromass from all structural layers.

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e. Soil samples were placed in labelled plastic bags, air dried and taken to the Soils Laboratory of the Soil Science Department of the College of Agriculture, University of the Philippines at Los Baños for analysis. The method used for the analysis was the Walkey-Black method (PCARR 1981). The mean bulk density of the 2006 soil carbon calculation in the KFR was used (Appendix 2). The dry weight of the soil and the equivalent carbon stock was determined using the following formula:

Soil mass at specified depth (Mg) = Bulk density at specified depth (Mg/m3) x 10 000 m2 x depth (m)

Soil carbon at specified depth (Mg) = Soil mass at specified depth (Mg) x % organic carbon at specified depth/100

4.5.3 Carbon-stock estimations at plot and landscape levels

With the values of biomass computed from plants and litter fall obtained from five different land uses, the amount of carbon stock at plot and landscape levels was estimated. This was achieved by using the mean carbon value from plant tissues obtained by Dixon et al. (1993) from similar sites and ecosystem, together with the 45% generic carbon value commonly used in much of the literature as a carbon estimate for plant cells (Raven et al. 1999). On average, the percentage of carbon in agricultural farm and grassland ecosystems was 40% while in agroforest, reforestation and secondary forest it was 45%.

At the landscape level, the method used for estimation of carbon stock was extrapolation based on a land-cover map. Two ‘snapshots’ over time for each of the landscapes’ carbon stocks were made by re-attributing the land-cover map of the particular year with corresponding plot-level carbon stock. The output was a carbon-stock estimation based on aboveground biomass calculations from land cover in 1994 and 2003.

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5. Results and discussion

5.1 Farming and livelihoods’ conditions2

5.1.1 Land access

The average size of landholding per household was 3 ha, one-third of which was cultivated while the rest was forested. Water was the determining factor in whether or not to cultivate the land, especially for rice production (tables 2 and 5). Community access was allowed in production forests and prohibited in the watersheds and sanctuaries. Land tenure was based on the ancestral domain claim, which was approved in 1999.

Table 2. Physical areas devoted to rice by production environment (in hectare), selected barangays, Sta. Fe, Nueva Vizcaya, 2000

No. Barangay Irrigated Rainfed Upland Total 1. Bacneng 10 0 7 17 2. Baracbac 20 0 10 30 3. Imugan 15 0 2 17 4. Malico 0 0 10 10 5. Sta. Rosa 25 6 2 33 6. Unib 20 0 3 23

Total 90 6 34 130 Source: Department of Agriculture, Sta. Fe, Nueva Vizcaya

5.1.2 Livelihood options

The majority of the people in the study area were farmers (Table 3). They were indigenous swiddeners with camote (sweet potato) and upland rice as their staple crops. Off-farm activities consisted of forest-fruit processing and soft-broom production (from tiger grass). Others were employed as professionals in the local government offices, Kalahan Academy and the KEF.

A livelihoods’ assessment was conducted through the KEF’s involvement with the Non-Timber Forest Products Exchange Program3. Table 3 shows that more than 50% of farmers in Bacneng, Baracbac, Imugan and Unib were more engaged with off-farm activities compared to the other barangays. Table 4 shows the barangays that are most concentrated on broom making. Table 5 shows the areas devoted to fruit and vegetable production.

2 Most of the information provided in this section was taken from Villamor and Pindog (2008). 3 A regional non-governmental organization.

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Table 3. Livelihoods of the people (percentage)

Major Occupation

Barangays/Villages Imugan Malico Sta. Rosa Unib Bacneng Baracbac Tactac

Farmers 70 90 94 100 90 96 80 Professionals * 25 5 1 0 6 2 10 Business/ Traders

5 5 5 0 4 2 10

100 100 100 100 100 100 100 * For example, teachers, government bureaucrats, soldiers, health workers and police

Source: Stakeholder analysis conducted in 2009

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Table 4. Summary of livelihoods’ assessment in the KFR

Barangays

Bacneng Baracbac Imugan Unib Malico Sta. Rosa Number of households 250 115 149 40 67 57 Crafts population 70%: broom making 90%: broom making 29%: broom making;

23%: basket weaving 50%: broom making 15%: broom making 18%: broom making

Geographical accessibility (distance from town)

5 km 3 km 7 km ~15 km ~15 km ~20 km

Sources of income Broom making Swidden Farming

Broom making Swidden Farming

Supplier of tiger grass (as raw material) Broom making Farming




Market (current) Local traders Solano* Baguio

Local traders Solano

Local traders Consolidators




Craft products Brooms, baskets Brooms Brooms, baskets, quilts Brooms, baskets Brooms, baskets Brooms, baskets

* Neighbouring town or city

Source: Non‐timber forest product (NTFP) project 2009, unpublished

Table 5. Physical area devoted to fruits and vegetable production (in hectare), selected barangays, Sta. Fe, Nueva Vizcaya, 2000

Total Area

(ha)

Vegetables Root Crops

Permanent Crops Temporary Crops

Upland Lowland Mango Citrus Coffee Guava Other fruits

Papaya Banana

Bacneng 229.08 45.0 10.25 85.25 70.0 1.07 5.03 6.8 5.0 0.14 0.54 Baracbac 105.73 37.5 27.1 35.0 0.47 0.43 0.20 3.36 0.10 ‐ 1.17 Imugan 51.57 13.75 12.50 20.60 0.04 0.44 0.40 2.29 1.24 ‐ 0.31 Malico 37.51 17.75 7.0 11.50 0.13 0.06 0.20 0.67 0.08 ‐ 0.12 Sta. Rosa 25.40 11.00 1.50 12.00 0.09 0.05 0.16 0.50 ‐ 0.01 0.09 Unib 30.09 8.75 4.00 2.50 0.23 0.30 0.80 2.26 0.89 ‐ 0.36 Total

(‐) no data

Source: Department of Agriculture, Sta. Fe, 2000

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5.1.3 Farming practices

The Ikalahan are known for their indigenous knowledge practice systems that are environmentally sustainable. These include:

• Day-og and gengen are composting techniques on level and sloping land respectively.

• Balkah is a contour line of deep-rooted plants, which trap eroded topsoil at the belt line (Rice 2000).

• Pang-omis is a method of expediting the fallow. It was invented by one of the tribal elders after attending an ecology seminar. Farmers intercrop tree seedlings, for example, Alnus nepalensis, in their swidden farms along with sweet potato.

A study of the farming systems and fallow management of households within the KFR (Banaticla et al. 2008) indicated that families use a much smaller area of land (around 2.93 ha) than the limit imposed by the community (10 ha) for farming and other purposes. The inherent physical limitations in the amount of land suitable for farming, declining population densities (except in villages nearest to the urban centre) and current cropping and fallow cycles (Table 6) also indicated the tendency towards sedentarization of agriculture. Former swidden fields were under long fallow and these were further protected by direct interventions of the community through regulation of forest clearing and other forest protection and rehabilitation activities (Appendix 4).

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Table 6. Mean cropping, fallow periods and cycle lengths employed by selected farmers in the KFR

Res‐pondent

No. Age

Residence (barangay)

Time span reported (years)*

No. of swiddens opened through

time

No. of swiddens with more than one cropping cycle

Mean cropping period (years)

Mean fallow period (years)

Mean crop:fallow

ratio

Mean crop‐fallow cycle length

(years)

1. 59 Baracbac 1974–2008 (34) 9 1 7.00

(1–14) 15.13 (1–29)

0.46 22.13

2. 62 Baracbac 1960–2008 (48) 3 0 9.33

(3–16) 7.33

(0–22) 1.27 16.66

3. 70 Unib 1959–2008 (49) 5 2 13.17 (4–26)

17.00 (1–45)

0.77 30.17

4. 75 Baracbac 1951–2008 (57) 3 3 8.25

(3–16) 5.30

(1.5–14) 1.56 13.55

5. 48 Imugan 1978–2008 (30) 3 2 8.40

(1–13) 16.50

(16–17) 0.51 24.90

6. 60 Malico 1984–2008 (24) 2 0 8.50

(4–16) 8.50

(6–11) 1.00 17.00

7. 75 Unib 1950–2008 (58) 2 1 13.25 (4–39)

14.33 (5–23)

0.92 27.58

8. 70 Malico 1986–2008 (22) 4 0 3.50 (2–5)

16.50 (10–23)

0.21 20.00

9. 45 Unib 1985–2008 (23) 2 0 8.5

(3–14) 11.00 (2–20)

0.77 19.50

Mean 8.88 12.40 0.83 21.28

* An initial list of 20 respondents were chosen but was narrowed down to 9 because of the difficulty of obtaining complete histories from each respondent. All nine respondents, except one, were female, residents of the KFR from birth, had no formal education or reached only the primary level, married or widowed, with farming as primary occupation up to the time of interview Source: Banaticla et al. 2008

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5.2 Land-use characteristics and practices

The major land uses in the Kalahan mountain ecosystem were classified into five, based on the dominant vegetation and community activities, as shown in Table 1 and described below.

5.2.1 Agriculture

The agricultural areas were represented in barangays Bacneng, Tactac and Atbu. The agriculture at these sites was generally situated in an open condition located on relatively flat-to-sloping terrain. Structurally, the vegetation was more undergrowth with few trees and an intermediate layer on the perimeter of farms, represented by a mix of crops (camote, cassava, beans, rice, corn, taro, okra, ginger) planted in patches, grown using a combination of traditional swidden farming and non-traditional systems that used inputs to increase production.

5.2.2 Agroforest

This land use in barangays Sta. Rosa, Baracbac and Unib was dominated by a mixture of agricultural fruit crops (avocado, mango, guava, citrus, papaya) planted in-between forest trees (for example, mahogany, Gmelina, narra) and was, hence, classified as agroforest. The land use was basically situated on moderate slopes with a semi-open canopy created by fruit and large trees, with little intermediate growth but abundant undergrowth layers. Minimal practices were applied, such as brush-cutting to clear some land for favoured crops and no tilling of the soil.

5.2.3 Grassland

The grassland at two sites in barangay Malico and another area in barangay Atbu were usually abundantly stocked in open areas on moderate-to-steep terrain. The areas were dominated by Imperata cylindrica, with several species of ferns, shrubs and a few patches of small trees. The main land-use practice was pasturing, although other areas were already abandoned, inviting fires.

5.2.4 Reforestation

This land use was established about 10–15 years ago in barangay Imugan using either Alnus or Gmelina and in barangay Bacneng with Benguet pine combined with mahogany. Reforestation sites were situated on moderate-to-steep slopes with a semi-open canopy with little intermediate growth but abundant undergrowth layers. There was some intercropping of coffee in reforested areas planted with Alnus and agricultural farming adjacent to the Gmelina plots but pure planting of mixed trees in other areas.

- 19 -

5.2.5 Secondary forest

This land use was dominated by either dipterocarp pine or myrtaceous oak forest ecosystems. Areas in barangay Baracbac, Sta. Rosa and Malico that featured this type of land use were covered with large diameter trees ranging 20–70 cm DBH. The forests were located on middle-to-higher elevated land with semi-closed canopy and fewer understorey layers. The dipterocarp forest was dominated by palosapis (Anisoptera thurifera), white lauan (Shorea contorta), bagtikan (Parashorea malaanonan) and guijo (Shorea guiso). Non-dipterocarp species included Benguet pine (Pinus kesiya), Philippine oak (Lithocarpus ovalis), legume (Pterocarpus indicus) and myrtaceae (Syzygium sp.). There were no practices recorded for this land use.

Table 7. Characteristics of the different land uses and practices of local communities in the KEF mountain ecosystem

Land use Community (GPS reading)

Physical features Dominant species Land‐use practices

Agriculture Bacneng N16°11'57.6''; E 120°56'19.6'' Tactac N16°08'42.1'' E 120°56'32.4'' Atbu N16°08'26.4' E 120°56'345.0''

Generally in an open condition located on relatively flat‐to‐sloping terrain structurally showing more undergrowth and few trees and with an intermediate layer on the perimeter of farms

Mixed agricultural crops (camote, cassava, beans, rice, corn, taro, okra, ginger) planted in patches

Agricultural farming using combined traditional swidden farming and non‐traditional systems

Agroforest Sta Rosa N 16°10'50.7'' E120°51'36.0'' Baracbac N 16°11'08.2'' E120°55'32.6'' Unib N 16°09'26.2'' E120°55'32.6''

Largely situated on moderate slopes with a semi‐open canopy with little intermediate but abundant undergrowth layers

Fruit‐bearing (avocado, mango, guava, citrus, papaya) and tree (mahogany, Gmelina, narra) crops

Intercropping with mostly fruit‐bearing and tree crops

Grassland Malico 1 N16°08'118.2' E 120°56'58.3'' Malico 2 N 16°10'10.9' E 120°51'24.4'' Atbu N 16°10'27.9'' E 120°52'09.7''

Usually abundant in open areas along moderate‐to‐steep terrain. Structurally, undergrowth layer dominated with abundance of grasses with very few patches of small trees

Mostly Imperata cylindrica and Themed triandra but with some species of ferns, shrubs and other grasses

Commonly used as pasture though some areas were left abandoned making them prone to grassfire

Reforestation Bacneng N 16°08'56.7'' E 120°56'11.5'' Imugan1 N 16°09'18.6'' E 120°54'25.7''

On steep‐to‐very steep slopes with slightly open canopy with dominant trees and intermediate and undergrowth layers

Dominance of 10–15 year‐old plantation of either Alnus, Benguet pine or Gmelina

Intercropping of coffee in reforested areas planted with Alnus and agricultural farming adjacent to Gmelina areas

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Land use Community (GPS reading)

Physical features Dominant species Land‐use practices

Imugan2 N 16°09'08.0'' E 120°54'11.8''

but pure planting of mixed trees in other areas

Secondary forest Baracbac N 16°10'14.6'' E 120°51'55.4'' Sta Rosa N 16°10'37.4'' E 120°51'07.2'' Malico N 16°09'26.2' E 120°55'32.6''

Located on middle‐to‐higher elevated areas with a semi‐closed canopy and fewer understorey layers

Dominance of dipterocarps (palosapis, white lauan, guijo) and non‐dipterocarp (pine, Philippine oak, legume, Syzygium) trees

Absence of any land‐use practices within, except for tree planting in pine forest

5.2.6 Key drivers of change

The key players that could contribute to changes (either positive or negative) in the landscape were households, the KEF organization, local political leaders and conservationists (Table 8). ‘Households’ includes all family members residing in the ancestral domain. ‘The KEF’ refers to the foundation that manages the mountain ecosystem, together with key barangay leaders that oversee the political existence of the community. ‘Conservationists’ includes bird watchers, academics, researchers and ecotourists.

The changes that influence the landscape of the mountainous ecosystem were categorized as socio-economic and political, biophysical and chemical, anthropogenic, and indirectly natural. The implementation of laws related to the environment—such as those pertaining to clean air, solid waste management, chemical application, protected area management, bio-invasion and threatened species—falls under socioeconomic and political activities.

Table 8. Characteristics and activities of various key drivers of change in the Kalahan landscape

Stakeholders Composition Function Activities that drive change in landscape Households Members of the

family Provides basic family role

Intermarriage of local to foreigners Introduction of verified or unverified upland farming technologies

KEF Board and members

Manage mountain ecosystem

Implementation of KEF policies regarding the overall use and management of natural resources in the area (Appendix 4)

Local political leaders Barangay captains and youth leaders

Oversee the political needs of the community as legal owners of the ancestral domain

Making decisions with regards to political activities that affect or are related to land ownership, use of farm land and natural resources, entry of outsiders to the area, and implementation of environmental laws ( clean air, solid waste management, chemical application, protected area management, bio‐invasion, threatened species etc)

Conservationists Bird watchers, ecotourists, researchers, academics

Conduct conservation research

Frequency of visits to the different areas by conservationists; activities that could be against bio‐prospecting, solid waste management and other environmental laws

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5.3 Plant diversity and composition

The diversity and composition of plants—particularly those in the canopy, intermediate and undergrowth layers that capture carbon physiologically during photosynthetic activities—varied depending on location, plot and land use, as presented below and in Table 7 above. Table 9 shows the percentage of trees with various diameters. Figure 4 shows the proportion of species’ composition in three structural layers in various land uses. Table 10 presents the percentage of population density of plants in the different structural layers.

Table 9. Percentage of trees with different diameter ranges from various land uses

Type of land use

< 5 cm 5–30 cm > 30 cm

Agriculture 14.81 81.48 3.70

Agroforest 20.16 74.31 5.53

Grassland 43.24 51.35 5.41

Reforestation 44.70 48.84 6.46

Secondary forest 16.49 72.68 10.82

5.3.1 Agriculture

In agricultural areas, stocks of carbon were pooled in common cultivated crops like upland and hybrid rice (Oryza sativa), beans (Vigna sesquipedalis), corn (Zea mays), taro (Colocasia esculentum), luya (Zingiber officinale), saging (Musa sapientum) and okra (Abelmoschus esculentus). Although classified as agricultural, there were, however, trees with diameters ranging 5–30 cm, representing about 81.5% of all trees, such as mango (Mangifera indica), suha (Citrus maxima) and hamak. All other trees in this category that had less than 5 cm and greater than 30 cm comprised 14.8 and 3.7%, respectively.

5.3.2 Agroforest

Carbon stocks in plants in agroforestry systems were represented by fruit (Citrus sp., Psidium guajava, Mangifera indica) and tree crops (Ficus nota, Alnus nepalensis, Eriobotrya japonica, Leucaena lueocephala, Pinus kesiya and Ficus septica). Among these, the most dominant was Citrus sp. (29.51%), followed by Ficus nota (5.33%) and Alnus nepalensis (4.92 %). The diameters of trees varied: 20.2% were at less than 5 cm DBH; 74.3% had DBH of 5–30 cm; while only 5.5% were greater than 30 cm DBH.

5.3.3 Grassland

The grassland ecosystem was characterised as ‘purely grassland’ or ‘abandoned pastureland’. The former was dominated by Paspalum conjugatum, Crassocephallum crepidioides and a local grass named tab-an. The latter ecosystem had an abundance of Pennisetum alopecuroides, Oleandra pistillaris and Imperata cylindrica. Sparsely interspersed through

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the ecosystem were patches of trees (Ficus septica, Boehmeria densiflora, Ficus nota, Saurauia latibractea, Persea americana and Mangifera indica). There were also species of moss (Portulaca grandiflora), busikad (Cyperus kyllingia), kilob (Dicranopteris linearis), cogon (Cyperus kyllingia), landrina (Borreria ocymoides), pal-ot (Miscanthus sinensis), dilang baka (Elephantopus tomentosus), kawad-kawad (Polytrias amaura) and two unknown local plants (buyot and galakgak). The percentages of trees with respect to DBH was 43.2% (> 5 cm), 51.4% (5–30 cm) and 5.4% (> 50 cm).

5.3.4 Reforestation

In reforestation areas, the species used were Benguet pine (Pinus kesiya), citrus (Citrus sp.), coffee (Coffea arabica), Alnus (Alnus nepalensis), narra (Pterocarpus indicus), guava (Psidium guajava), mahogany (Swietenia macrophylla) and amuwag (Clethra sp.). The dominant species for the whole land use were coffee (Coffea arabica), amuwag (Clethra sp.) and Alnus (Alnus nepalensis), composing 21.45%, 13.30% and 11.18% of the total of observed tree species, respectively.

5.3.5 Secondary forest

In secondary forest, the dominant species were Benguet pine (Pinus kesiya), is-is (Ficus ulmofolia) and white lauan (Shorea contorta) with values of 15.54%, 13.47% and 12.44%, respectively. Large trees in the sampled plots of secondary forest—exemplified by Pinus kesiya, Shorea contorta and Anisoptera thurifera–had greater percentages of individuals with DBH of small (44.7%) and medium (48.8%) than those with large DBH, that is, greater than 50 cm (6.4%).

Table 10. Population density per plot in the canopy, intermediate and undergrowth layers in different land uses

Type of land use Trees Intermediate Undergrowth

Agriculture 24 279 1296

Agroforest 244 299 864

Grassland 39 286 1593

Reforestation 564 112 1075

Secondary forest 193 80 366

Note: Plot size for canopy, intermediate and undergrowth layers were 2000 m2, 9 m2 and 1 m2, respectively.

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Figure 4. Percentage of species’ composition in three structural layers in various land uses.

5.4 Carbon stocks

5.4.1 Aboveground

Aboveground carbon stock in land-use systems in the KFR were estimated to range 0.61–77.86 Mg/ha (Table 11). The highest value recorded was in the reforestation area, with 32% of trees contributing to total aboveground carbon stock (Figure 4).

Table 11. Plot-level aboveground biomass carbon stocks

Land use Sample plot

code

Tree Intermediate Understorey Total

Mg/ha Mg/ha Mg/ha Mg/ha

Agriculture

S5T2 10.042 0.207 0.025 10.274

S6T2 0.000 0.577 0.037 0.614

S7T1 0.754 0.663 0.014 1.430

Agroforest

S1T2 1.682 0.310 0.002 1.994

S3T1 30.588 0.093 0.073 30.753

S4T2 19.025 0.547 0.028 19.599

Grassland

S2T3 0.000 0.604 0.095 0.699

S2T4 9.807 0.575 0.031 10.412

S7T2 0.760 0.556 0.026 1.342

Reforestation

S5T1 77.479 0.324 0.055 77.857

S8T1 25.890 0.119 0.030 26.039

S8T3 62.293 0.149 0.037 62.479

Secondary forest

S1T1 37.054 0.409 0.038 37.502

S2T1 4.541 0.028 0.041 4.611

S4T1 44.652 0.035 0.037 44.723

81.0561.41

83.0661.39 57.28

17.45

21.25

14.91

6.40 12.52

1.5017.34

2.03

32.21 30.20

Agriculture Agroforest Grassland Reforestation Secondary forest

Undergrowth Intermediate Trees

- 24 -

Table 12. Mean aboveground carbon stocks in land uses sampled in the KFR

Land use Tree Intermediate Understorey Total

Mg/ha Mg/ha Mg/ha Mg/ha

Agriculture 3.599 0.482 0.025 4.106

Agroforest 17.098 17.098 0.034 34.230

Grassland 3.522 0.578 0.050 4.151

Reforestation 55.220 0.197 0.041 55.458

Secondary Forest 28.749 0.157 0.039 28.945

The mean aboveground carbon stock for each land use ranges 4.11–55.46 Mg/ha (Table 12). Land uses such as reforestation, agroforest and secondary forest have higher carbon content where trees are a higher proportion compared to other plant forms (Figure 4).

The carbon-stock values generated are far smaller compared to the values of similar land cover. Lasco and Pulhin (2003) recorded average carbon densities of 207.9 Mg/ha for secondary forest, 45.4 Mg/ha for agroforest, 12.1 Mg/ha for grassland and 59.0 Mg/ha for tree plantations. This observation could be attributed to the tree composition of the sampled plots. For example, large trees in the sampled plots of secondary forest—exemplified by Pinus kesiya, Shorea contorta and Anisoptera thurifera–had greater percentages of individuals with DBH of small (44.7%) and medium (48.8%) than those with large DBH, that is, greater than 50 cm (6.4%).

5.4.2 Belowground

Delany (1999) proposed belowground biomass of trees and intermediate layers equivalent to 15% of the aboveground tree biomass. The carbon content is presented in Table 13, while the mean land-use carbon stock is shown in Table 14.

Table 13. Plot-level belowground biomass carbon-stock

Land use Sample plot code

Stump & roots Mg/ha

Intermediate Mg/ha

Understorey Litter Mg/ha

Total Mg/ha

Agriculture S5T2 3.766 0.078 0.035 3.879 S6T2 0.000 0.216 0.035 0.251 S7T1 0.283 0.248 0.025 0.557

Agroforest S1T2 5.606 1.035 0.028 6.668 S3T1 10.196 0.031 0.040 10.266 S4T2 6.342 0.182 0.027 6.551

Grassland S2T3 0.000 0.201 0.049 0.250 S2T4 3.677 0.216 0.025 3.918 S7T2 0.285 0.209 0.030 0.523

Reforestation S5T1 25.826 0.108 0.017 25.951 S8T1 8.630 0.040 0.012 8.682 S8T3 20.764 0.050 0.016 20.830

Secondary forest S1T1 12.351 0.136 0.021 12.509 S2T1 1.514 0.009 0.032 1.555 S4T1 14.884 0.012 0.018 14.913

- 25 -

Table 14. Mean belowground carbon stocks in land uses sampled in the KFR

Land use Stump & roots Mg/ha

Intermediate Mg/ha

Understorey Mg/ha

Total Mg/ha

Agriculture 1.349 0.181 0.032 1.562

Agroforest 7.381 0.416 0.032 7.829

Grassland 1.321 0.208 0.034 1.564

Reforestation 18.407 0.066 0.015 18.488

Secondary Forest 9.583 0.052 0.024 9.659

5.4.3 Soil Carbon

The organic soil carbon of the various land uses is presented in Table 15. The estimated belowground carbon stocks are between 21.8 and 67.4 Mg/ha. Reforestation has the highest soil carbon stock in the area. In 2006, the soil carbon density values of grassland ranged from 35.36–47.22 Mg/ha (Pulhin et al. 2006). The current value (39.09 Mg/ha) of grassland falls in the middle of that range.

Table 15. Soil carbon and carbon stock

Sample plot code

Land uses OM% OC% Carbon stock Mg/ha

S6T2

Agriculture

4.74 2.76 49.87

S5T2 4.53 2.63 47.52

S7T1 3.15 1.83 33.07

S3T1

Agroforest

4.54 2.64 47.70

S4T2 4.00 2.33 42.10

S1T2 4.93 2.87 51.86

S2T4

Grassland

2.59 1.51 27.29

S2T3 4.52 2.63 47.52

S7T2 4.05 2.35 42.46

S5T1

Reforestation

4.82 2.8 50.60

S8T3 6.39 3.71 67.40

S8T1 5.80 3.37 60.90

S2T1

Secondary forest

3.56 2.07 48.79

S1T1 2.08 1.21 21.86

S4T1 3.37 1.96 35.42

The mean soil carbon of the KFR (Table 16) was lower compared to other studies conducted in Leyte and Tanay, Rizal, which were 52.70 Mg/ha and 55 Mg/ha, respectively (Lasco et al. 1999).

- 26 -

Table 16. Mean soil carbon-stock per land use

Land use Mean total Mg/ha

Agriculture 43.49

Agroforest 47.22

Grassland 39.09

Reforestation 59.63

Secondary Forest 35.36

Mean total 44.96

5.4.4 Total carbon stock

The estimated total (above- and belowground) carbon stock of different land-use systems in the KFR ranged 54.31–151.13 Mg/ha (Table 17). The results were low compared to assessments conducted in other areas of the country.

Table 17. Plot-level mean carbon-stock of each land use

Land use

Tree Mg/ha

Intermediate Mg/ha

Understorey Mg/ha

Litter Mg/ha

Soil & litter Mg/ha

Total Mg/ha

Agriculture 3.60 0.48 0.03 5.15 45.05 54.31

Agroforest 17.10 0.32 0.03 6.06 55.05 78.56

Grassland 3.52 0.58 0.05 10.06 40.65 54.87

Reforestation 55.22 0.20 0.04 17.67 78.00 151.13

Secondary forest 28.75 0.16 0.04 20.59 45.02 94.55

Table 18. Total carbon stock at plot-level in the KFR

Land use

Sample plot code

Aboveground Below‐ ground

Total Mg/ha Tree

Mg/ha Intermediate Mg/ha

Understorey Mg/ha

Litter Mg/ha

Soil & litter Mg/ha

Agriculture

S5T2 10.04 0.21 0.03 5.61 51.40 67.29

S6T2 0.00 0.58 0.04 3.01 50.12 53.74

S7T1 0.75 0.66 0.01 6.84 33.63 41.90

Agroforest

S1T2 1.68 0.31 0.00 0.55 58.53 61.07

S3T1 30.59 0.09 0.07 14.82 57.97 103.54

S4T2 19.03 0.55 0.03 2.82 48.65 71.07

Grassland

S2T3 0.00 0.60 0.10 6.59 47.77 55.06

S2T4 9.81 0.57 0.03 19.23 31.21 60.85

S7T2 0.76 0.56 0.03 4.37 42.98 48.70

Reforestation

S5T1 77.48 0.32 0.05 23.39 76.55 177.80

S8T1 25.89 0.12 0.03 18.17 69.58 113.79

S8T3 62.29 0.15 0.04 11.45 87.87 161.80

- 27 -

Land use

Sample plot code

Aboveground Below‐ ground

Total Mg/ha Tree

Mg/ha Intermediate Mg/ha

Understorey Mg/ha

Litter Mg/ha

Soil & litter Mg/ha

Secondary forest

S1T1 37.05 0.41 0.04 7.49 34.37 79.36

S2T1 4.54 0.03 0.04 30.15 50.34 85.11

S4T1 44.65 0.03 0.04 24.12 50.33 119.18

Figure 5. Total (above- and belowground) carbon stocks and their relative composition in the KFR

(Upper panel: absolute values in Mg/ha. Lower panel: as percentage).

C st

ock,

Mg/

ha

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

intermediate

understorey

tree

litter

Soil &litter

0

20

40

60

80

100

120

intermediate

understorey

tree

litter

soil&litter

C st

ock

com

posi

tion

(%)

- 28 -

Carbon stocks from soil and litter contribute about 50–80 percent of the total carbon (Figure 5). The reforestation area has the highest total carbon stock both from soil and tree components.

5.4.5 Landscape carbon-stock estimation

The estimated mean carbon stocks (Table 17) of the major land-use types was plotted in the land cover map of 20014 to view the distribution of carbon density (Figure 6).

Figure 6. Distribution of land-cover-derived carbon density in the KFR, based on a carbon-stock estimate (2009).

4 At the time of writing, the latest satellite image of this area awaits processing

- 29 -

5.5 Land-use change dynamics in the KFR

Landscape-level carbon-stocks were estimated from land-cover types. By integrating the changes in vegetation cover with carbon-stock measurements at plot level, changes in carbon stock in the landscape can be estimated. Land-cover maps of 1989 and 2001 that were processed by Ekadinata and Nugroho (in preparation) were used for this estimation. There were seven major land-cover classes identified.

1) Forest: characterised by more or less dense and extensive natural tree cover. 2) Secondary forest: re-grown woodland area. 3) Mahogany: areas dominated by Swietenia mahogany with ages of 10–30 years. 4) Pine:– areas dominated by Pinus kesiya (Benguet pine). 5) Agricultural land: areas with less trees and cultivated by sweet potato, ginger, potato,

banana and corn. 6) Rice fields: both irrigated and non-irrigated, cultivated with hybrid and native rice

varieties. 7) Fallow: areas that are left idle to regain soil productivity and planted with Alnus

nepalensis.

5.5.1 Land cover in 1989

About 39% (8500 ha) of the area was classified as agricultural land. Natural and secondary forest covered 20% (4300 ha) and 3% (670 ha) of the area, respectively (Table 19). About 27% (5800 ha) of the study area was covered by pine forest. Figure 8 shows the land cover map of 1989.

Table 19. Land-cover classes in the KFR, 1989

Classes Area (ha) %

Forest 4162.6 19 Secondary forest 670.9 3

Old pine 1513.3 7

Pine 4256.0 20

Mahogany 321.4 1

Agriculture 8473.9 39

Fallow 359.5 2

Rice field 976.4 4

Settlement 458.1 2

Grassland 28.1 0.1

Cloud 401.3 2

Shadow 172.7 1

Total 21794.0 100.0

Figure 7. Land-cover classes in the KFR, 1989.

FiguSourc

5.5.

AboAgriold p

Tabl

For

Sec

Old

Pine

Ma

Agr

Fall

Rice

Sett

Gra

Clo

Sha

Tot

ure 8. Land-coce: ICRAF

.2 Land cov

out 15.6 % (3iculture areapine increase

le 20. Land-co2001

Classes

est

ondary forest

pine

e

hogany

riculture

ow

e field

tlement

assland

ud

adow

al

over map of th

ver in 2001

3400 ha) of aa covered aroed 7% to 10%

over classes in

Area (ha)

3394.1

373.6

2125.1

3978.8

529.9

8154.8

340.9

1516.4

514.4

35.9

601.7

228.4

21 794.0

he KFR, 1989

1

area was clasound 8150 ha%. Figure 10

n the KFR,

) %

15.6

1.7

9.8

18.3

2.4

37.4

1.6

7.0

2.4

0.2

2.8

1.0

100.0

- 30 -

.

ssified as natua, a decrease 0 shows the la

Figure 9.

ural forest, afrom 39% toand-cover m

Land-cover cl

a 3.5% decreao 37% of the

map of 2001.

lasses in the K

ase from 198e total area, w

KFR, 2001.

89. while

- 31 -

Figure 10. Land-cover map of the KFR, 2001. Source: ICRAF

5.5.3 Land-cover change matrix

A land-cover change matrix is presented in Table 21. There was a considerable decrease of mature forest, secondary forest, pine forest and agriculture areas. On the other hand, there was an increase in old pine forest, mahogany plantation, rice field, grassland and settlement areas.

Figure 11. Overall land-cover change within the KFR.

Are

a (h

a)

Legend

2001 Land Cover

- 32 -

Table 21. Land-cover changes between 1989 and 2001 (area in ha)

2001

Land use Forest Secondary forest

Old pine Pine Mahogany Agriculture Fallow Rice field

Settle‐ment

Grassland

Cloud Shadow Total

1989

Forest 3145.23 308.88 8.64 209.43 20.7 187.11 1.62 9.27 271.71 4162.6

Secondary forest

370.08 126.63 6.03 47.52 0.81 37.71 0.09 1.8 52.56 27.63 670.9

Old pine 1134.9 28.8 257.4 5.94 61.02 0.9 1.17 10.53 12.6 1513.3

Pine 945.18 1897.2 87.57 784.44 74.61 279.45 17.37 8.91 107.64 53.64 4256.0

Mahogany 302.22 8.91 0.09 6.3 0.18 2.97 0.72 321.4

Agriculture 1362.42 90.18 6257.97 149.85 421.56 69.3 9.72 67.23 45.63 8473.9

Fallow 56.34 4.77 185.4 73.8 33.3 0.09 0.54 4.5 0.72 359.5

Rice field 166.77 317.97 5.13 432.45 9.18 2.07 14.76 28.08 976.4

Settlement 415.08 29.34 13.68 458.1

Grassland 10.8 7.38 6.75 1.71 0.18 0.18 0.63 0.45 28.1

Cloud 165.51 1.98 23.13 34.02 0.54 62.91 3.24 45.36 0.54 1.98 26.19 35.91 401.3

Shadow 83.34 1.53 21.87 15.75 1.17 15.48 10.44 0.09 13.68 9.36 172.7

Total 3394.1 373.6 2125.1 3978.8 529.9 8154.8 340.9 1516.4 514.4 35.9 601.7 228.4

Source: ICRAF

- 33 -

5.5.4 Carbon monitoring plots

KEF’s agroforestry program monitored plant biomass in 106 plots within the KFR between 1994 and 2003 (Figure 11). Table 22 shows the biomass generated.

Table 22. Mean biomass in 1994 and 2003 and the blocks and plots sampled

Land use No. of blocks

No. of plots

1994 Mean biomass (Mg/ha)

2003 Mean biomass (Mg/ha)

Agriculture 13 30 32.73 47.55 Forest 7 20 20.76 28.65 Secondary forest 3 8 39.89 56.71 Old pine 13 19 28.00 40.71 Pine 16 23 30.35 41.48 Rice field 4 5 17.14 23.73 Mahogany* 1 1 30.79 53.50 Total 57 106

*Only one mahogany plot appeared after the plot’s coordinates were intersected on the 1989 and 2001 land‐cover maps The carbon densities for 1994 and 2003 were obtained from these plots (Table 23). The total carbon budget estimated from the land cover was obtained from the total area of each land-cover type (excluding the areas under cloud and shadow). Figure 10 shows the land-cover density maps that indicate increases of carbon stock over the period 1994–2003. Table 23. Carbon densities based on biomass-monitoring plots in the KFR

Land use

1994

Carbon density (Mg/ha)

2003


Agriculture 14.73 21.40 Forest 9.34 12.89 Secondary forest 17.95 25.52 Old pine 13.66 19.87 Pine 14.81 19.91 Rice field 6.86 9.49 Mahogany 13.86 21.07

It was estimated that the total carbon stock was approximately 375.8 Gg5 in 1994 and 452.1 Gg in 2003 or a 21% increase in 9 years. This may be due to the increase of old pine and reforestation and the decrease of agricultural areas.

5 1 Gg (Gigagram) = 1000 Mg (Megagram)

- 34 -

Figure 12. Distribution of land-cover-derived carbon density in the KFR in 1989 (upper panel) and 2001 (lower panel).

It is also interesting to note that there were a few plots with much higher carbon densities than the average (Appendix 3), as shown in Table 24. From a statistical point of view, these are outliers that affect the average values. These plots were not used in the extrapolation. We suggest they should be validated on the ground.

Carbon (Mg/ha)

Carbon (Mg/ha)

- 35 -

Table 24. Plots with very high estimated carbon densities

No. Land use

1994 2003

Biomass (Kg/ha)

Biomass (Mg/ha)


Biomass (Kg/ha)

Biomass (Mg/ha)


1. Old pine 48336.30 193.35 87.01 59124.61 236.50 106.42

2. Pine 62915.89 251.66 113.25 72941.69 291.77 131.30

3. Forest 50376.52 201.51 90.68 62108.81 248.44 111.80

4. Forest 61598.65 246.39 110.88 72842.67 291.37 131.12

5. Forest 30341.68 121.37 54.62 38550.60 154.20 69.39

6. Agriculture 27768.31 111.07 49.98 39703.36 158.81 71.47

From these monitoring plots, one noticeable carbon value was observed in the agriculture category. In 2003, monitoring plots in agriculture areas had an average of 21.4 Mg/ha, which was more than that of forest and pines. This suggests that farmers planted more high-carbon trees outside the forest or it could be due to the sedentarisation of agriculture, which was noted by Banaticla et al. (2008) (see page 13).

5.6 Carbon emissions by land-use and land-cover change

Carbon emissions from land-use and land-cover changes between 1989 and 2001 were calculated using the derived carbon densities from this study (with addition from another study of land-cover types not sampled locally), as shown in Table 25.

Table 25. Land-cover types and carbon densities used

Land‐cover type from image classification

Mean carbon densities (aboveground) Mg/ha

Sources

Agricultural land 17.61 KEF monitoring plots*

Dipterocarp/mahogany 45.0 Recent data

Fallow (swidden‐fallow) 19.7 Recent data

Forest (mature) 28.9 Recent data

Grassland 4.1 Recent data

Pasture land 10.4 Recent data

Pine 17.53 KEF monitoring plots*

Old pine 16.76 KEF monitoring plots*

Rice field 8.17 KEF monitoring plots*

Secondary forest 21.74 KEF monitoring plots*

Settlement 4.1 ICRAF (Kalimantan data)

*Average of the 1994 and 2001 carbon densities (Appendix 3)

- 36 -

Based on our calculations (Table 26), the KFR sequestered an average of 0.30 Mg/ha of carbon less than what was emitted (average 0.82 Mg/ha) from its land-cover changes between 1989 and 2001. The carbon emission potential was 0.5 Mg/ha. Table 26 shows the estimated yearly average carbon emissions. From this, it is estimated that per year the KFR is emitting 1.4 Gg of carbon while sequestering 0.5 Gg.

- 37 -

Table 26. Mean carbon emissions from land-use changes, 1994–2003

Forest Secondary forest

Old Pine Pine Mahogany Agriculture Fallow Rice field Settlement Grass Total

Forest 0 0 0 0.177159 ‐0.00595 0.123002 0.009783 0.187419 0.001925 0.011016 0.504357 Secondary Forest 0 0 0 0.024403 ‐0.00645 0.009812 7.43E‐05 0.023411 7.27E‐05 0.001454 0.05278

Old Pine 0 0 0 0 ‐0.03732 ‐0.0052 ‐0.0008 0.024051 0.000523 0.00068 ‐0.01806

Pine 0 0 0.03209287 0 ‐0.1105 0.010798 ‐0.00753 0.119632 0.01068 0.005478 0.060653

Mahogany 0 0 0 0 0 0.011365 0.000104 0.010646 0 0.000338 0.022454

Agriculture 0 0 0 ‐0.01875 ‐0.11503 0 ‐0.01719 0.174666 0.041655 0.005843 0.071189

Fallow 0 0 0 0.005687 ‐0.00554 0.021267 0 0.017617 6.44E‐05 0.000387 0.039485

Rice field 0 0 0 ‐0.07139 0 ‐0.13175 ‐0.00271 0 0.001714 0.000387 ‐0.20375

Settlement 0 0 0 0 0 0 0 0 0 0 0

Grass 0 0 0 ‐0.00664 0 ‐0.00444 ‐0.00483 ‐0.00032 0 0 ‐0.01623

Total 0 0 0.03209287 0.110461 ‐0.28078 0.034866 ‐0.02311 0.557123 0.056634 0.025581 0.512875 Mg/ha emission

0.815232 Mg/ha emitted

0.302356 Mg/ha sequestered

- 38 -

Table 27. Mean carbon emissions per year, 1994–2003

Forest Secondary forest

Old Pine Pine Mahogany Agriculture Fallow Rice field Settlement Grass Total

Forest 0 0 0 0.014763 ‐0.0005 0.01025 0.000815 0.015618 0.00016 0.000918 0.04203 Secondary Forest 0 0 0 0.002034 ‐0.00054 0.000818 6.19E‐06 0.001951 6.06E‐06 0.000121 0.004398

Old Pine 0 0 0 0 ‐0.00311 ‐0.00043 ‐6.7E‐05 0.002004 4.36E‐05 5.66E‐05 ‐0.00151

Pine 0 0 0.00267441 0 ‐0.00921 0.0009 ‐0.00063 0.009969 0.00089 0.000457 0.005054

Mahogany 0 0 0 0 0 0.000947 8.71E‐06 0.000887 0 2.81E‐05 0.001871

Agriculture 0 0 0 ‐0.00156 ‐0.00959 0 ‐0.00143 0.014556 0.003471 0.000487 0.005932

Fallow 0 0 0 0.000474 ‐0.00046 0.001772 0 0.001468 5.37E‐06 3.22E‐05 0.00329

Rice field 0 0 0 ‐0.00595 0 ‐0.01098 ‐0.00023 0 0.000143 3.22E‐05 ‐0.01698

Settlement 0 0 0 0 0 0 0 0 0 0 0

Grass 0 0 0 ‐0.00055 0 ‐0.00037 ‐0.0004 ‐2.7E‐05 0 0 ‐0.00135

Total 0 0 0.00267441 0.009205 ‐0.0234 0.002905 ‐0.00193 0.046427 0.00472 0.002132 0.04274 Mg/ha emission

0.067936 Mg/ha emitted

0.025196 Mg/ha sequestered

- 39 -

5.7 Carbon-offset6 options

1) CDM Market: The KEF is negotiating a CDM project. Potential sites for this project are abandoned agricultural and grassland areas. A list of participants is being prepared together with their planting strategies for the proposed CDM sites (Figure 13).

Figure 13. Target sites for CDM project (red dots).

Plant species that local farmers preferred to plant (some already have planted) were tuai (Biscofia javanica), Alnus (Alnus nepalensis) and rain tree (Albizia saman). Among the proposed planting schemes were reforestation with mixed tree species. Others propose to implement nurse tree to integrate climax species (for example, Benguet pine and dipterocarps). However, a possible problem under this target market is meeting the CDM requirements of forest definition, baseline, leakage and additionality7. Thus, the voluntary carbon market is likely to be the best for the KFR owing to its increasing carbon stock.

2) Voluntary market: The data and information generated from this study will be used to find voluntary carbon markets. However, the baseline should be well established. The forest improvement technology developed by the KEF could potentially enhance the carbon stock of the standing forests (Appendix 5) at the same time as maintaining the

6 A reduction in carbon dioxide emission by a third party purchased by a heavy carbon dioxide producer as part of carbon emissions trading. 7 CDM projects must result in ‘reduction in emissions that are additional to any that would occur in the absence of the certified project activity’.

- 40 -

biodiversity within. The KEF is optimistic that this could be used as a management strategy to tap ‘reducing emissions from deforestation and degradation’ (REDD) markets.

5.8 Scenario building and future options

This section presents the results of Forest, Agroforest, Low-value Landscape Or Wasteland (FALLOW) model application in the KFR that was conducted by Suyamto et al. (2011)8 under the Rewarding Upland Poor for the Environmental Services they provide (RUPES) project (phase 1). The FALLOW model simulates landscape dynamics and the consequences of the application of different drivers in various scenarios.

5.8.1 Baseline

Using population growth (at a rate of 1.78%) as the driver, the model predicted that within the next three decades (2001–2030), the landscape would experience a decrease in forest area of about 85 ha/yr and an increase of agricultural/grassland area of about 85 ha/yr. Depletion of biodiversity, carbon stock and sediment-filtering capacity would occur at the rate of 0.4 species/yr, 53 Gg/yr and 117 Gg/yr, respectively. Secondary expenses of the people would increase at a relatively low rate of about PHP 110 per capita per year.

5.8.2 Future options

Three options were identified based on existing livelihoods (1 and 2) and alternative land-uses (3) within the KFR, with possible future implications.

Table 28. Future options and their implications for the KFR

Options Implications Option 1: Improve non‐timber forest products’ (NTFP) productivity and markets (by increasing productivity and price 2x, 6x and 10x from the baseline)

By increasing NTFP productivity and price up to 10x from the baseline, agricultural land expansion can only be reduced at an average of about 233 ha or 8% per year

Option 2: Provide better off‐farm jobs (increase incomes from off‐farms jobs 2x, 6x and 10x from the baseline)

• By increasing income from off‐farm jobs 2x from the baseline, agricultural land expansion could decrease at an average of 289 ha or 10% per year

• By increasing income 6x, agricultural land expansion could decrease at an average of 551 ha or 17% per year and forests could increase at an average of 229 ha or 2% per year

• By increasing income 10x, agricultural land expansion could decrease at an average of 1005 ha or 31% per year and forests could increase at an average of 834 ha or 8% per year

8 Detailed information on data inputs of the model and some assumptions can be found in this working paper.

- 41 -

Options Implications

Option 3: Promote tree‐based systems (for example, cacao and coffee) through extension, subsidy and market improvements

Among the tree‐based systems scenarios, coffee could be adopted at the fastest rate, followed by cacao and mahogany. This assumes that economically, smallholder tree‐based systems are more profitable than pasture and, biophysically, pasture can be converted into tree‐based systems. These efforts would replace grasslands with more valuable systems

Source: Suyanto et al. (2011) (draft working paper)

Appendix 6 shows the additionality from each scenario on biodiversity (that is, species numbers in four functional groups: pioneer, early succession, medium succession and late succession), carbon stocks, watershed functions (that is, sediment-filtering capacity) and people’s welfare (that is, non-food expenses per capita).

- 43 -

6. Conclusion and recommendations

6.1 Conclusion

The matrix below summarises the findings of the appraisal.

Value: • Major land‐use and land‐cover types—

agriculture, agroforest, grassland, secondary forest and reforestation—were assessed and their carbon stocks were calculated

• KFR has its own farming practices that enhance carbon stocks in the area, such as pang‐omis, in which Alnus species are integrated into swidden farming

Opportunity: • KEF has long‐term biomass monitoring plots

to support carbon‐offset trading and already has skills to monitor carbon stocks within KFR (to reduce transaction cost)

• KEF’s own farming practices and technology can be used as a strategy to explore voluntary markets

Trust:

• KEF’s rules and regulations on natural

resources control the cutting of trees inside KRF. It also initiates the active participation of each village in tree‐planting activities

Threat:

• Encroachment of outsiders owing to

intermarriages (concern over changing farming practices)

• Limited livelihoods’ options (certificate of ancestral domain title holders might seek to sell their land)

6.2 Recommendations

For the voluntary carbon market, further research is required to assess the potential of the KEF’s forest improvement technology for REDD.

More ground-truthing activities are need to validate the landscape-level carbon estimations.

Process the recent satellite image of the area and use it for analysis of land-use and land-cover changes and carbon dynamics.

- 45 -

References

Banaticla MRN, Palijon AM, Takeuchi K. 2008. Assessing local variation in shifting cultivation and fallow management among households in the Kalahan Forest Reserve, Northern Luzon, Philippines. Journal of Nature Studies 7(2):129–143.

Delany M. 1999. Field test of carbon monitoring methods for agroforestry in the Philippines, In: Field Test of Carbon Monitoring Methods in Forestry Projects. Forest Carbon Monitoring Program. Arlington, USA: Winrock International.

Dixon RK, Andrasko KJ, Sussman FG, Lavinson MA, Trexler MC, Vinzon TS. 1993. The forest sector carbon offset projects: near term opportunities to mitigate greenhouse gas emission. Water, Air and Soil Pollution 70:561–577.

Ekadinata A, Nugroho DK. In preparation. Geospatial data processing in Kalahan forest reserve, Philippines: World Agroforestry Centre (ICRAF) Southeast Asia Program.

Hairiah K, Sitompul SM, van Noordwijk M, Palm C. 2001. Methods for sampling carbon stocks above and below ground. ASB Lecture Note 4B. Nairobi: World Agroforestry Centre.

Hairiah K, Dewi S, Agus F, van Noordwijk M, Rahayu S. 2009. Measuring carbon stocks across land-use systems: a manual. Bogor, Indonesia: World Agroforestry Centre (ICRAF) Southeast Asia Program; Malang, Indonesia: Brawijaya University; Indonesian Centre for Agricultural Land Resources Research and Development.

[KEF] Kalahan Educational Foundation. 1993. Kalahan Educational Training Centre information leaflet. Imugan Santa Fe, Philippines: Kalahan Educational Foundation.

Ketterings QM, Coe R, van Noordwijk M, Ambagau Y, Palm C. 2001. Reducing uncertainty in the use of allometric biomass equations for predicting aboveground tree biomass in mixed secondary forests. Forest Ecology and Management 146:199–209.

Lasco RD, Pulhin FB. 2003. Philippine forest ecosystems and climate change: carbon stocks, rate of sequestration and Kyoto protocol. Annals of Tropical Research 25(2):37–51.

Lasco RD, Sales JS, Arnuevo MT, Guillermo IQ. 1999. Carbon dioxide absorption and sequestration in the PNOC-Leyte Geothermal Reservation. Final Report. Environmental Forestry Programme. Los Baños, Philippines: College of Forestry and Natural Resources, University of the Philippines at Los Baños.

[PCARR] Philippine Council for Agriculture and Resources Research. 1980. Standard methods of analysis for soil, plant, tissue, water and fertilizer. Los Baños, Philippines. Philippine Council for Agriculture and Resources Research.

Pulhin FB, Lasco RD, Gesvana DT. 2006. Rehabilitation of degraded lands through a carbon sink project: the case of Mirant Philippines. 2006 FORESPI Symposium on Forest Landscape Restoration and Rehabilitation: Poster. College Laguna, Philippines. 15p. www.agris.fao.org

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Pulhin F. 2008. Carbon storage assessment of the grassland areas of Ikalahans Ancestral Domain, Nueva Vizcaya, the Philippines. Working Paper 74. Bogor, Indonesia: World Agroforestry (ICRAF) Southeast Asia Program.

Raven PH, Evert RF, Eichhorn SE. 1999. Biology of Plants. 6th ed. New York: WH Freeman.

Rice D. 2000. The Ikalahan: towards sustainable forest use. ILEIA Newsletter (September). 21p.

Suyamto DA, van Noordwijk M, Lusiana B, Villamor GB, Ekadinata A, Nugroho DK. 2011. Prospecting peoples’ welfare and ecosystem services in Kalahan landscape (the Philippines) using the FALLOW model. Draft Working Paper. Bogor, Indonesia: World Agroforestry Centre (ICRAF) Southeast Asia Program.

Villamor GB, Pindog M. 2008. Participatory poverty and livelihood assessment report, Kalahan, Nueva Vizcaya, the Philippines. Bogor, Indonesia: World Agroforestry Centre (ICRAF) Southeast Asia Program.

- 47 -

Appendix 1: List of plant species and its biomass per land use

- 48 -

Appendix 1: Reforestation – list of plant species and biomass

No. Local name biomass Kg/m2 No. Local name biomass

Kg/m2 No. Local name biomass Kg/m2 No. Local name biomass

Kg/m2

1 Alagai 268.00 32 Alnus 301.62 63 Alnus 637.24 94 Amuwag 20.50

2 Alnus 6.04 33 Alnus 301.62 64 Alnus 648.34 95 Amuwag 20.50












14 Alnus 87.85 45 Alnus 421.90 76 Amuwag 14.49 107 Amuwag 27.85









23 Alnus 222.06 54 Alnus 493.93 85 Amuwag 19.20 116 Antipolo 9.70

24 Alnus 222.06 55 Alnus 532.60 86 Amuwag 20.50 117 Avocado 72.45








- 49 -



Kg/m2

125 Ayuhip 11.02 156 Benguet Pine 1227.20 187 Coffee 8.11 218 Coffee 8.11

126 Balanti 12.93 157 Benguet Pine 1260.54 188 Coffee 8.11 219 Coffee 8.11

127 Bauang 6.04 158 Benguet Pine 1346.31 189 Coffee 8.11 220 Coffee 8.11

128 Bauang 6.04 159 Benguet Pine 1435.57 190 Coffee 8.11 221 Coffee 8.11

129 Benguet Pine 105.11 160 Benguet Pine 1881.99 191 Coffee 8.11 222 Coffee 8.11

130 Benguet Pine 145.53 161 Bilwa 9.70 192 Coffee 8.11 223 Daguay 9.70

131 Benguet Pine 171.30 162 Bilwa 13.44 193 Coffee 8.11 224 Danglin 14.49

132 Benguet Pine 194.33 163 Bilwa 46.93 194 Coffee 8.11 225 Ginnabang 17.34

133 Benguet Pine 227.88 164 Bilwa 76.88 195 Coffee 8.11 226 Gmelina 58.84



136 Benguet Pine 337.73 167 Bilwa 202.41 198 Coffee 8.11 229 Guava 7.03

137 Benguet Pine 337.73 168 Bini 6.04 199 Coffee 8.11 230 Guava 36.63



140 Benguet Pine 461.56 171 Buta buta 9.70 202 Coffee 8.11 233 Guava 27.85



143 Benguet Pine 484.54 174 Buta buta 114.46 205 Coffee 8.11 236 hauili 87.85

144 Benguet Pine 557.68 175 Canthum 9.70 206 Coffee 8.11 237 Hili-hili 14.49

145 Benguet Pine 604.63 176 Coffee 6.04 207 Coffee 8.11 238 Ihit 291.28



148 Benguet Pine 723.43 179 Coffee 8.11 210 Coffee 8.11 241 Ipil-ipil 24.00

149 Benguet Pine 753.66 180 Coffee 8.11 211 Coffee 8.11 242 Kahoy dalaga 65.43



152 Benguet Pine 916.47 183 Coffee 8.11 214 Coffee 8.11 245 Kulatingan 6.04

153 Benguet Pine 951.40 184 Coffee 8.11 215 Coffee 8.11 246 Lablaban 25.50

154 Benguet Pine 987.15 185 Coffee 8.11 216 Coffee 8.11 247 Lablabang 105.11

155 Benguet Pine 1146.24 186 Coffee 8.11 217 Coffee 8.11 248 Lablabang 430.53

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Reforestation continues…



Kg/m2

249 Ladau 87.85 280 Mangga 6.04 311 Narra 670.91

250 Langka 27.85 281 Marang 81.47 312 Narra 882.33

251 Langka 69.59 282 Molave 20.50 313 Padpad 14.49

252 Langka 79.92 283 Molave 27.85 314 Padpad 79.92

253 Lapting 87.85 284 Mussaenda setosa 20.50 315 Padpad 284.50

254 Liwliw/Hauili 508.22 285 Narra 6.04 316 Padpad 461.56

255 Macaranga 6.04 286 Narra 6.04 317 Palai 11.48

256 Macaranga 6.04 287 Narra 6.04 318 Papaya 6.04

257 Macaranga 134.66 288 Narra 9.70 319 Papaya 12.43

258 Mahogany 14.49 289 Narra 16.74 320 Papaya 14.49




262 Manga 10.13 293 Narra 32.05 324 Pitikan 19.20

263 Manga 20.50 294 Narra 58.84 325 Piwi 20.50

264 Manga 24.00 295 Narra 61.42 326 Santol 36.63

265 Manga 34.75 296 Narra 78.39 327 Sapinit 14.49

266 Manga 62.74 297 Narra 96.24 328 Suha 6.69

267 Manga 87.85 298 Narra 134.66 329 Suha 258.38

268 Manga 281.15 299 Narra 168.85 330 Suha 723.43

269 Manga 291.28 300 Narra 168.85 331 Suha 816.44

270 Manga 330.30 301 Narra 213.50 332 Tibanglan 114.46

271 Manga 356.73 302 Narra 222.06 333 Tuwal 58.84

272 Manga 484.54 303 Narra 236.78 Total 73625.34

273 Manga 532.60 304 Narra 268.00

274 Manga 637.24 305 Narra 291.28

275 Manga 653.94 306 Narra 330.30

276 Manga 693.95 307 Narra 368.44

277 Manga 723.43 308 Narra 400.81

278 Manga 723.43 309 Narra 498.67

279 Manga 810.02 310 Narra 642.78

- 51 -

Secondary Forest



Kg/m2

1 Adawai 26.268954 32 Benguet Pine 110.6587 63 Hagahaka 32.937682 94 Palosapis 29.487379

2 Adawai 124.3082 33 Benguet Pine 154.60227 64 Halinghing 39.551651 95 Palosapis 35.68119

3 Alagasi 11.017251 34 Benguet Pine 168.84816 65 Hauili 7.3792394 96 Palosapis 52.674717

4 Alagasi 78.389935 35 Benguet Pine 194.33328 66 Hauili 29.487379 97 Palosapis 56.322386

5 Alagau 9.7046768 36 Benguet Pine 227.87747 67 Iilog 18.563665 98 Palosapis 75.384151

6 Alagau 24.003636 37 Benguet Pine 287.87751 68 Iilog 134.66232 99 Palosapis 145.53084

7 Alagau 38.560999 38 Benguet Pine 298.14853 69 Ilo-ilog 43.670247 100 Palosapis 145.53084

8 Alagau 105.10542 39 Benguet Pine 315.76216 70 Itangan 25.499865 101 Palosapis 168.84816

9 Alagau 168.84816 40 Benguet Pine 341.4751 71 Itangan 33.837194 102 Palosapis 168.84816

10 Alagau 1178.2167 41 Benguet Pine 372.39289 72 Kamiling 16.159476 103 Palosapis 202.41227

11 Amuwag 27.849561 42 Benguet Pine 409.16755 73 Kamiling 20.503207 104 Palosapis 337.72582

12 Amuwag 32.937682 43 Benguet Pine 753.664 74 Kolalabang 15.03348 105 Palosapis 396.67228

13 Amuwag 36.62586 44 Benguet Pine 875.6026 75 kubangbang liit 14.489144 106 Palosapis 637.24009

14 Amuwag 45.824393 45 Benguet Pine 979.93283 76 La huet 15.03348 107 Palosapis 951.4035

15 Amuwag 48.042718 46 Benguet Pine 1046.0322 77 Ladao 124.3082 108 Pangnan 13.957109

16 Antipolo 76.878003 47 Benguet Pine 1083.9073 78 Ladaw 20.503207 109 Pangnan 20.503207

17 Apitong 7.7398193 48 Benguet Pine 1194.4076 79 Litan 6.3601929 110 Pangnan 36.62586

18 Ayohip 17.335929 49 Benguet Pine 1320.2104 80 Loklohong 78.389935 111 Pangnan 58.838158

19 Ayohip 36.62586 50 Benguet Pine 1745.3628 81 Luglohong 18.563665 112 Pangnan 72.450359

20 Ayohip 210.6947 51 Benguet Pine 1776.3308 82 Molave 44.739342 113 Pangnan 87.845743

21 Balete 951.4035 52 Benguet Pine 2506.3025 83 Molave 252.09138 114 Pangnan 105.10542

22 Bangat 20.503207 53 Bini 64.07435 84 Pad pad 35.68119 115 Pangnan 194.33328

23 Bangat 52.674717 54 Bini 78.389935 85 Pad pad 61.42192 116 Pangnan 1463.0459

24 Benguet Pine 16.159476 55 Binukau 219.18247 86 Pad pad 73.908297 117 Pili nut 19.8435

25 Benguet Pine 27.052154 56 Bolalog 12.433748 87 Padpad 32.053038 118 Piwi(Is-is) 15.03348

26 Benguet Pine 28.253622 57 Buta buta 10.568326 88 Palosapis 7.0291869 119 Piwi(Is-is) 17.335929

27 Benguet Pine 28.661271 58 Buta buta 147.76709 89 Palosapis 7.0291869 120 Piwi(Is-is) 19.8435

28 Benguet Pine 34.751666 59 Dagwey 20.503207 90 Palosapis 8.1110429 121 Piwi(Is-is) 31.183169

29 Benguet Pine 39.054392 60 Guijo 58.838158 91 Palosapis 15.590223 122 Piwi(Is-is) 46.925489

30 Benguet Pine 46.925489 61 Guijo 76.878003 92 Palosapis 19.8435 123 Piwi(Is-is) 51.492081

31 Benguet Pine 84.620084 62 Guijo 284.50297 93 Palosapis 20.503207 124 Salingogon 7.3792394

- 52 -

Secondary Forest continues…



Kg/m2

125 Salingogon 11.477724 156 White Lauan 417.63058

126 Salingogon 637.24009 157 White Lauan 439.25684

127 Tabangawan 103.29329 158 White Lauan 693.95008

128 Tabangawan 124.3082 159 White Lauan 882.33399

129 Tibanglan 34.751666 160 White Lauan 1099.2901

130 Tiklad 27.849561 161 White Lauan 1194.4076

131 Tiklad 52.674717 162 White Lauan 1346.3061

132 Tiklad 64.07435 Total 38331.918

133 Tiklad 76.878003

134 Tiklag 36.62586

135 Uyok 28.661271

136 Uyok 57.571816

137 Uyok 261.56209

138 White Lauan 12.433748


















- 53 -

Agroforest No. Local name biomass


Kg/m2 No. Local name biomass Kg/m2

8 Adawai 11.95 8 Benguet pine 6.04 34 Citrus 6.04 65 Citrus 6.04



4 Alagai 9.29 11 Benguet pine 27.85 37 Citrus 6.04 68 Citrus 6.04

1 Alnus 9.70 12 Benguet pine 27.85 38 Citrus 6.04 69 Citrus 6.04

2 Alnus 20.50 13 Benguet pine 4757.32 39 Citrus 6.04 70 Citrus 6.04

3 Alnus 9.70 29 Bini 42.62 40 Citrus 6.04 71 Citrus 6.04

47 Alnus 124.31 46 Bini 112.55 41 Citrus 6.04 72 Citrus 6.04

50 Alnus 145.53 1 Binunga 6.04 42 Citrus 6.04 73 Citrus 6.04



64 Alnus 426.20 14 Citrus 1528.40 45 Citrus 6.04 76 Citrus 6.04




28 American kapok 723.43 18 Citrus 6.04 49 Citrus 6.04 80 Citrus 6.04

17 Atsuete 130.46 19 Citrus 6.04 50 Citrus 6.04 81 Citrus 6.04

28 Avocado 41.58 20 Citrus 6.04 51 Citrus 6.04 82 Citrus 6.04

20 Avocado 216.33 21 Citrus 6.04 52 Citrus 6.04 83 Citrus 26.27

2 Bakhi 6.69 22 Citrus 6.04 53 Citrus 6.04 84 Citrus 97.97

25 Balanti 36.63 23 Citrus 6.04 54 Citrus 6.04 85 Citrus 138.95

59 Balanti 227.88 24 Citrus 6.04 55 Citrus 6.04 86 Daguey 14.49

1 Bawang 6.04 25 Citrus 6.04 56 Citrus 6.04 87 Danglin 9.70

5 Bawang 9.29 26 Citrus 6.04 57 Citrus 6.04 88 Guava 13.44



55 Bawang 194.33 29 Citrus 6.04 60 Citrus 6.04 91 Guba-gubai 27.85

4 Benguet pine 58.84 30 Citrus 6.04 61 Citrus 6.04 92 Hanga 105.11

5 Benguet pine 87.85 31 Citrus 6.04 62 Citrus 6.04 93 Ihit 305.12

6 Benguet pine 105.11 32 Citrus 6.04 63 Citrus 6.04 94 Ipil-ipil 11.95

7 Benguet pine 105.11 33 Citrus 6.04 64 Citrus 6.04 95 Ipil-ipil 65.43

- 54 -

Agroforest continues…



Kg/m2

96 Ipil-ipil 271.25 127 Mahogany 9.70 158 Saging 2.52

97 Ipil-ipil 994.39 128 Mahogany 36.63 159 Santol 1023.70

98 Jacobina sp. 20.50 129 mahogany 105.11 160 Suha 41.58

99 Jual 268.00 130 Mahogany 583.48 161 Suha 124.31

100 Kahoy dalaga 36.63 131 Mangga 20.50 162 Suha 284.50

101 Kamilin 8.89 132 Mangga 6.04 163 Suha 396.67

102 Kangah 20.50 133 Mangga 9.70 164 Suha 1435.57

103 La hwe/ La huit 45.82 134 Mangga 57.57 165 Syzygium sp. (Hangan) 105.11

104 Lablabang 17.34 135 Mangga 79.92 166 Talanak 15.59

105 Lablabang 52.67 136 Mangga 145.53 167 Talanak 27.05

106 Lablabang 52.67 137 Mangga 699.79 168 Tibig 6.04

107 Lablabang 168.85 138 Mangga 916.47 169 Tibig 9.29

108 Ladau 20.50 139 Nangka 230.82 170 Tibig 15.59

109 Ladau 202.41 140 Nangka 281.15 171 Tibig 252.09

110 Ladau 356.73 141 Narra 156.92 172 Tuai 1936.24

111 Ladau 753.66 142 Ngak ngak 24.74 173 Tubang 1023.70

112 Ladaw 334.00 143 Nganga 51.49 Total 29890.57

113 Langka 128.39 144 Nganga 86.22

114 Lapting 19.84 145 Nganga 105.11

115 Litan 36.63 146 Ngatngat 21.86

116 Lithocarphus 6.04 147 Niog 1023.70

117 Liwliw 36.63 148 Oak (Lithocarphus) 36.63

118 Liwliw 57.57 149 Patat 46.93

119 Liwliw 72.45 150 Pitikan 24.74

120 Liwliw 159.27 151 Saging 2.52

121 Liwliw 168.85 152 Saging 2.52

122 Liwliw/Hauili 9.29 153 Saging 2.52

123 Lukban/Suha 17.34 154 Saging 2.52



126 Madlakat 46.93 157 Saging 2.52

- 55 -

Agriculture


Kg/m2

1 Saging 11.01 32 ipil ipil 58.84

2 Saging 11.01 33 Dita 951.40

3 Saging 12.53 34 Guava 1.60

4 Saging 12.53 35 Hamak 3.38

5 Saging 9.60 36 Adaway 9.70

6 Saging 11.01 37 Hamak 9.70

7 Saging 9.60 38 Hamak 9.70

8 Saging 9.60 39 Tual 9.70

9 Saging 11.01 40 Kamiling 14.49

10 Saging 11.01 41 Lablabang 20.50

11 Saging 12.53 42 Liwliw 20.50

12 Saging 12.53 43 Balanti 27.85

13 Saging 9.60 44 Pitikan 46.93

14 Saging 11.01 45 Idu-iduh 58.84

15 Saging 11.01 46 Bawang 145.53

16 Saging 12.53 Total 5399.5106

17 Saging 12.53

18 Saging 17.71

19 Saging 9.60

20 Saging 12.53

21 Saging 15.88

22 Manga 396.67

23 Manga 484.54

24 Manga 532.60

25 Manga 583.48

26 Manga 637.24

27 Suha 222.06

28 Suha 356.73

29 Suha 484.54

30 papaya 58.84

31 citrus 7.74

- 56 -

Grassland


Kg/m2

1 Ammowag 6.041014 32 Banana 8.2865541

2 Ammowag 6.041014 33 Banana 8.2865541

3 Ammowag 27.849561 34 Banana 9.5983291

4 Ammowag 46.925489 35 Banana 9.5983291

5 Benguet pine 72.450359 36 Banana 9.5983291

6 Kahoy dalaga 72.450359 37 Banana 11.012776

7 Ammowag 87.845743 38 Banana 11.012776









16 Bawang 6.041014 47 Banana 15.880582

17 Avocado 20.503207 48 Banana 15.880582

18 Avocado 20.503207 Total 5283.2753

19 Manga 20.503207

20 Manga 20.503207

21 Manga 20.503207

22 Banana 5.9672923

23 Banana 5.9672923

24 Banana 5.9672923

25 Banana 5.9672923

26 Banana 5.9672923

27 Banana 5.9672923

28 Banana 7.076534

29 Banana 7.076534

30 Banana 7.076534

31 Banana 8.2865541

- 57 -

Appendix 2: List of intermediate and undergrowth

- 58 -

A. Agriculture (S5T2)

Undergrowth Intermediate Species No. of individuals S5T2 Species No. of individuals

Alatin 7 3x3 Ayas-as 7

Bulak manok 178 Cogon 6

Busikad 51 Dilang baka 4

Dilang butiki 1 Gonoy 4

Euphorbia hirta 5 Kamot kabag 7

Habugan 7 Kamoteng baging 1

Kamot pusa 4 Kulapi 30

Kamote 7 Makahiya 15

Kulapi 19 Panibat 3

Kulitis 8 Sapinit 3

Leptochloa chinensis 20 Uoko 4

Ligad-ligad 10

Makahiya 25

Mutha 5

Panibat 71

Paragis 24

Paragis like 4

Putokan putokan 9

Sampalok sampalokan 5

Tagulinaw 3

Tuhod manok 45

- 59 -

Agriculture (S6T2)

Intermediate Undergrowth S6T2S5 Species N Species N

3x3 Bulak manok 25 Bulak manok 89

Cogon 15 Camote cordate 36

Dilang baka 1 Camote lobed 22

Kamoteng kahoy 10 /clump Cogon 5

Makahiya 1 Crassucephaum 10

Panibat 3 Cupphea sp. 2

Uoko 2 Cyperus iria 1

Digitaria sp. 5

Gabi 4

Guava 1

Kaliskis dalag 3

Kudzu 1

Ligad ligad 6

Luya 7

Makahiya 16

Okra 2

Panibat 24

Sampalokan 1

Susoloyeli sp. 5

Tabang 3

Tagulinaw liitan 1

Takip kuhol 14

Upland rice 18

- 60 -

Agriculture (S7T1)

Intermediate Undergrowth S7T1S3 Species N Local names N

3x3 Baka-baka 2 Baka baka 4

Bakhi 1 Bakhi 2

Coronitas 9 Bulak manok 66

Golon/cogon 68 Centrocema pubiscens 20

Hagonoi 4 Chistella dentata 8

Lokdo 13 Cogon 110

Runo 22 Cyperus iria 50

Suag kabayo 8 Dilang aso 5

Tambo 3 Galakpak 32

Uoko 8 Hakate 14

Higis manok 2

Kaitana 1

kandikandilaan 10

Kulapi 42

Panawal 73

Panibat 5

Pa-o 29

Paragis 2

Paspalum distichum 3

Pulat 8

Uoko 3

Walis-walisan 4

- 61 -

Agroforest (S1T2)

Intermediate Undergrowth S1T2S2 Species N Local name N

3x3 Alam-am (fern) 10 Alam-am 9

Bakhi 2 Alinaw 1

Cogon 150 Amuwag 9

Dilang baka 6 Baka baka 12

Guava 1 Bakhi 2

Runo 6 Cogon 52

Panawal 25 Galakgak 13

Sida/ Kulat 1 Hakati 4

Kalawag 3

Kulapi 56

Palat 3

Panawal 26

Paol 1

Wild berry 2

- 62 -

Agroforest (S3T1)


3x3 Acanthaceae 1 Arachis sp. 31

Alagau 6 Baluingia 2

Alam-am 9 Bogus 4

Avocado 1 Bulak manok 37

Ayusan 1 Busikad 10

Bagaluan 2 Carabao grass 35

Binunga 1 Christella dentata 6

Dama de noche 3 Compositae 3

Gnetum latifolium 1 Dilang aso 6

ground orchid 5 Dilang Baka 17

Kamiring 1 Fimbristylis 1

Katurog 6 Higis manok 2

Leei sp. 3 Hyptis 1

Marang 2 Kandilaan 2

Rattan 1 Kawad kawad 8

Rubus mollucanus 1 Kudzu 4

Salagong sibat 1 Kulitis 1

Spaglottis sp. 1 Ligad-ligad 2

Subiang 1 Lubi-lubi 2

Tiger grass 1 Mischanthus 1

Tuai 1 Mutha 5

Tulibos tilos 1 Pako 7

Wild Strawberry 2 Panawal 20

Zingiber sp. 1 Panibat 4

Rattan 2

Uoko 14

Zingiber 1

- 63 -

Agroforest (S4T2)

Intermediate Undergrowth Local name N Local name N

Achuete 2 Bulak manok 14

Ayas-as 3 Busikad 1

Hauili 1 Carabao grass 130

Hyptis sp. 13 Dilang butiki 6

Kamote kahoy 2 Hithit 12

Kandikandilaan 3 Ipil-pil 3

Kullio kulliot 2 Kamra kamra 13

Okra-okrahan 11 Kandikandilaan 14

Synedrella nodiflora 2 Kulapi 57

Tambo 2 Landrina 3

Yautia 4 Lokdo 4

Makahiya 12

Panibat 4

Rice 139

Sampasampalukan 1

Sitsit 43

Uoko 10

- 64 -

Grassland (S2T3)


3x3 Alam-am 9 Alam-am 7

Amorseko 60 Amorseko 1

Amuwag 9 Apgad 1

Bakhi 8 Bakhi 6

Buyot 1 Bigas bigasan 15

Cogon 25 Bulak manok 12

Dilang baka 17 Busikad 60

Giant bracken fern 5 Buyot 35

Kulapi 20 Cogon 54

Pakong alakdan 1 Cyperus iria 6

Panawal 2 Dilang baka 31

Paragis 14 Galakgak 28

Runo 17 Kamra kamra 9

Kawad kawad 19

Kilob 57

Kilob babae 7

Kollo kolliot 3

kulapi 19

Landrina 38

Leptocloa chinensis 2

Ligad-ligad 1

Lubi lubi 1

Lycopodium 7

Malatabako 1

Moss 112

Pal-ot 35

Pandan 7

Paspalidum flavidum 11


Tabang 4

Takip kuhol 11

Themeda triandra 9

Wild strawberry 4

- 65 -

Grassland (S2T4)

Intermediate Undergrowth S2T4S3 Species N Localname N

3x3 Bakhi 13 Ammowag 1

Cogon 8 Amorseko 37

Giant bracken fern 6 Apiit 2

Golon 5 Bagingay 28

Guava 2 Baka baka 22

Panawal 7 Bakhi 44

Baludgangan 22

Benguet pine 4

Bulak manok 17

Chrysopogon aciculatus 8

Cyperus iria 26

Elephantopus scaber 2

Galakgak 15

Golon 50

Kaibuan 91

Kaliskis ahas 62

Kamra-kamra 17

Kilob 41

Ligad-ligad 5

Lycopodium 21

Panawel 3

Panibat 3

Paspalidum distichum 34

Paspalum conjugatum 6

Takip kuhol 22

Themeda triandra 7

- 66 -

Grassland (S7T2)

Intermediate Undergrowth Local names N Local names N

Baka baka 2 A-apid 5

Hagonoy 3 Anwad 44

Kandi-kandilaan 5 Bulak manok 55

Kulapi 10 Camote 16

Lantana 3 Christella dentata 21

Pulat 4 Cyperus iria 11

Tab-an 3 Dioscorea flabelleflora 1

Talahib 12 Gatas-gatas 2

Uoko 15 Gattodan 3

Hagonoy 1

Hakati 90

Higis manok 2

Kamra-kamra 3

Kulapi 17


Patpati 10

Tab-an 50

Talong-talungan 1

Tambo 5

Uoko 39

Vernonia sp. 8

Wakal 6

- 67 -

Reforestation (S5T1)

Intermediate Undergrowth S5T1S2 Species No. of individuals Local name No. of individuals

3x3 Avocado 1 Alikbangon 5

Binunga 1 Avocado 5

Dilang butiki 8 Baging 2

Ipil ipil 1 Bulak manok 46

Kakauate 1 Calopogium 1

Kollo kolliot 2 Carabao grass 60

Mahogany 9 Cyperus sp. 9

Papaya 1 Dayang 53

Sapinit 11 Dilang baka 1

Talingpunay 5 pako 1

Uoko 5 Euphorbia hirta 4

grass 1

Kulapi 12

Kullo kuliot 11

Mahogany 4

Makahiya 2

Malvaceae 1

Panibat 1

Paragis 1

Silver fern 1

Tuhod manok 8

Tutumpak 4

Uoko 14

- 68 -


Intermediate Undergrowth S8T1S2 Species No. of individuals Localname No. of individuals

3x3 Amuwag 4 Akba grass 10

Buta buta 1 Bulak manok 21

Dilang baka 3 Carabao grass 106

Hagonoy 2 Mutha 9

Kahoy dalaga 1 Dilang baka 43

Kalulot 4 Kaliskis dulog 200

Bakhi 5 Kulapi 88

Wild strawberry 2 Kuliot 6

Lobi lobi 2

Makahiya 8

Myrtaceae 1

Padpad 2

Panawal 16

Sun flower 10

Tuhod manok 7

Uoko 13

Wedelia sp. 6

Wild strawberry 2

- 69 -


Intermediate Undergrowth S8T3S1 Species No. of individuals Species No. of individuals

3x3 Balbas pusa 1 Asak 8

Hagonoy 1 Balbas pusa 15

Kape 2 Baludgangan 20

Kulliot 5 Christella dentata 27

Lubi lubi 6 Dilang baka 6

Panawal 22 Hagonoy 8

Pneumatopteris levis 5 Hyptis sp. 23

Uoko 2 Kape 12

Kulapi 66

Langkuas 1

Lokdo 7

Malvaceae (Gummamela) 5

Panawal 20

Paspalidum flavidum 22

Rubus sp. 2

Uoko 21

Uyot 3

Wild strawberry 6

Secondary Forest (S1T1)


3x3 Alam-am 2 Alam-am 12 Cogon 12 Ayusan 3 Dilang baka/Baka baka 2 Baka baka 2 Kaibuan 30 Cogon 33 Panawal 6 Guava 1 Tagulinau 1 Kaibuan 95

kaliskis ahas 1

Kulapi 2

Pal-ot 2

Panawal 4

Pulat 1

Tagulinau 7

Tan-al 1

- 70 -



Alam-am 1 Alam-am 9

Iilog 2 Baka Baka 8

Kahoy dalaga 1 Bakhi 2

Lemon tree 2 Blechnum 4

Syzidium sp. 2 Cogon 63

Wild Strawberry 2 Galakgak 1

Kilob 12

Panawal 50

Runo 9

Sabung-sabung 1

Wild Strawberry 2



3x3 Alambrillong gubat 1 Ayas-as 1

Binukaw 1 Baka baka 2

Guijo 4 Bayabas 1

Ligas 3 Cogon 18

Mayapis 2 Hauili 1

Mutha 1 Kandikandilaan 1

Palosapis 1 Kasupangil 1

Pangnan 2 Kubamba 1

White lauan 2 Kulapi 1

Makahiya 10

Palosapis 1

Santol 1

Siver fern 1

Tutumbak 3

Uoko 1

- 71 -

Appendix 3: List of biomass monitoring plots

- 72 -

Appendix 3: KEF Monitoring plots per landuse

A. Agriculture

Block # Plot #

1994 2003

Biomass (Kg/ha)

Biomass (Mg/ha) C (Mg/ha)

Biomass (Kg/ha)


28 2 3078.40 12.31 5.54 1814.68 7.26 3.27 28 4 5497.46 21.99 9.90 9120.05 36.48 16.42 30 2 9388.91 37.56 16.90 13982.93 55.93 25.17 30 3 11129.47 44.52 20.03 15308.42 61.23 27.56 30 4 12172.38 48.69 21.91 17058.03 68.23 30.70 31 1 11429.49 45.72 20.57 14133.02 56.53 25.44 31 2 4460.36 17.84 8.03 5206.40 20.83 9.37 31 3 5710.47 22.84 10.28 9502.75 38.01 17.10 31 4 12639.93 50.56 22.75 18186.43 72.75 32.74 33 1 6069.49 24.28 10.93 7122.50 28.49 12.82 33 3 5456.07 21.82 9.82 8347.99 33.39 15.03 33 4 4662.13 18.65 8.39 7808.80 31.24 14.06 34 1 11013.75 44.05 19.82 15706.90 62.83 28.27 34 2 15035.80 60.14 27.06 20002.51 80.01 36.00 36 1 10294.75 41.18 18.53 15152.17 60.61 27.27 36 2 9899.49 39.60 17.82 15657.72 62.63 28.18 40 1 10965.71 43.86 19.74 14652.10 58.61 26.37 40 4 3209.10 12.84 5.78 5778.51 23.11 10.40 41 1 1699.00 6.80 3.06 3657.09 14.63 6.58 41 2 6133.84 24.54 11.04 8912.22 35.65 16.04 41 3 12957.73 51.83 23.32 19406.49 77.63 34.93 42 2 8291.43 33.17 14.92 15879.53 63.52 28.58 42 3 14015.91 56.06 25.23 20465.11 81.86 36.84 47 2 8960.75 35.84 16.13 12842.17 51.37 23.12 48 3 1228.06 4.91 2.21 3051.25 12.20 5.49 58 2 1922.93 7.69 3.46 3346.62 13.39 6.02 59 1 5926.25 23.71 10.67 6916.20 27.66 12.45 59 2 10033.32 40.13 18.06 13483.81 53.94 24.27 59 3 9458.03 37.83 17.02 13741.02 54.96 24.73 59 4 7608.13 30.43 13.69 10303.55 41.21 18.55

Average 8181.73 32.73 14.73 11887.32 47.55 21.40

- 73 -

Figure 1. Average C-densities in agriculture areas.

B. Rice field

Block # Plot #

1994 2003

Biomass (Kg/ha)


Biomass (Kg/ha)


14 1 3345.261 13.38 6.02 5224.299 20.90 9.40 14 2 5576.314 22.31 10.04 7630.863 30.52 13.74 24 4 5747.104 22.99 10.34 7353.663 29.41 13.24 26 1 4970.109 19.88 8.95 6658.986 26.64 11.99 45 3 1789.096 7.16 3.22 2788.914 11.16 5.02

Average 4285.58 17.14 7.71 5931.35 23.73 10.68

Figure 2. Average C-densities in rice fiels areas.

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

0 10 20 30 40

C ‐d

ensity (M

g/ha

)

Plot number

C (Mg/ha)

Linear (C (Mg/ha))

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

0 2 4 6

C de

nsities (M

g/ha

)

Plot number

C (Mg/ha)

Linear (C (Mg/ha))

- 74 -

C. Forest

Block # Plot #

1994 2003

Biomass (Kg/ha)


Biomass (Kg/ha)


1 2 11763.25 47.05 21.17386 14178.56 56.71 25.52142 1 3 16709.57 66.84 30.07723 20946.36 83.79 37.70344 1 4 2080.026 8.32 3.744048 2992.232 11.97 5.386017 4 1 674.2393 2.70 1.213631 1384.778 5.54 2.492601 4 2 1685.045 6.74 3.033081 2713.238 10.85 4.883829 4 4 1263.151 5.05 2.273673 2406.447 9.63 4.331604

20 1 3738.924 14.96 6.730064 5847.02 23.39 10.52464 20 2 3917.678 15.67 7.05182 6722.766 26.89 12.10098 24 1 4093.377 16.37 7.368079 5994.237 23.98 10.78963 24 2 4241.263 16.97 7.634274 6691.106 26.76 12.04399 24 3 5887.197 23.55 10.59695 6975.474 27.90 12.55585 52 1 4245.595 16.98 7.642072 5834.626 23.34 10.50233 52 2 4396.309 17.59 7.913356 5948.26 23.79 10.70687 52 3 10734.26 42.94 19.32166 15789.91 63.16 28.42184 56 1 552.0802 2.21 0.993744 1004.158 4.02 1.807484 56 2 6233.833 24.94 11.2209 8597.786 34.39 15.47601 56 3 6031.132 24.12 10.85604 7747.869 30.99 13.94616

Average 5190.996 20.76 9.343793 7163.225 28.65 12.89381

Figure 3. Average C-density in forest areas.

0

5

10

15

20

25

30

35

40

0 5 10 15 20

C de

nsity (M

g/ha

)

Plot number

C (Mg/ha)

Linear (C (Mg/ha))

- 75 -

D. Old Pine

Block # Plot #

1994 2003

Biomass (Kg/ha)


Biomass (Kg/ha)


15 1 3906.49 15.63 7.63 4580.40 18.32 8.94 28 3 2692.93 10.77 5.26 8116.41 32.47 15.84 29 3 8343.79 33.38 16.29 11253.64 45.01 21.97 34 3 8537.13 34.15 16.66 12404.76 49.62 24.21 34 4 7748.78 31.00 15.13 11602.79 46.41 22.65 35 1 6775.14 27.10 13.23 9062.74 36.25 17.69 35 2 12660.14 50.64 24.71 17332.27 69.33 33.83 37 1 14150.60 56.60 27.62 20214.78 80.86 39.46 39 3 10118.99 40.48 19.75 14759.74 59.04 28.81 39 4 10220.22 40.88 19.95 15065.34 60.26 29.41 40 2 9028.43 36.11 17.62 11047.04 44.19 21.56 40 3 3994.58 15.98 7.80 7953.81 31.82 15.53 48 2 1191.48 4.77 2.33 3068.35 12.27 5.99 55 1 594.87 2.38 1.16 1088.47 4.35 2.12 55 4 4594.43 18.38 8.97 6230.41 24.92 12.16 57 1 1882.36 7.53 3.67 3219.83 12.88 6.29 57 3 6257.61 25.03 12.21 10500.25 42.00 20.50 58 1 12141.11 48.56 23.70 15888.20 63.55 31.01 62 1 8139.27 32.56 15.89 9999.37 40.00 19.52

Average 6998.86 28.00 13.66 10178.35 40.71 19.87

Figure 4. Average C-density in old pine areas.

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

0 5 10 15 20

C de

nsity (M

g/ha

)

Plot no.

C (Mg/ha)

Linear (C (Mg/ha))

- 76 -

E. Pine dominated

Block # Plot #

1994 2003

Biomass (Kg/ha)


Biomass (Kg/ha)


14 3 4147.16 16.59 8.10 6311.48 25.25 12.32

15 2 3465.97 13.86 6.77 5520.39 22.08 10.78

15 3 2054.86 8.22 4.01 3367.21 13.47 6.57

15 4 1579.28 6.32 3.08 2775.82 11.10 5.42

26 2 4857.36 19.43 9.48 6519.10 26.08 12.73

26 3 4864.56 19.46 9.50 6519.10 26.08 12.73

28 1 2335.94 9.34 4.56 4430.88 17.72 8.65

29 1 8317.63 33.27 16.24 10976.87 43.91 21.43

29 2 10026.75 40.11 19.57 12742.78 50.97 24.87

30 1 10519.46 42.08 20.53 14651.07 58.60 28.60

35 3 16977.68 67.91 33.14 22044.44 88.18 43.03

35 4 9691.50 38.77 18.92 5755.52 23.02 11.23

39 1 17695.88 70.78 34.54 26378.33 105.51 51.49

39 2 16676.13 66.70 32.55 25499.69 102.00 49.78

45 2 5559.16 22.24 10.85 10183.62 40.73 19.88

47 1 11596.02 46.38 22.64 15792.35 63.17 30.83

48 1 953.22 3.81 1.86 748.76 3.00 1.46

55 3 2722.74 10.89 5.31 4663.60 18.65 9.10

57 2 3767.62 15.07 7.35 5844.26 23.38 11.41

58 3 1922.93 7.69 3.75 3346.62 13.39 6.53

60 1 11353.82 45.42 22.16 14813.59 59.25 28.92

60 2 15251.12 61.00 29.77 18125.65 72.50 35.38

62 2 8181.58 32.73 15.97 11474.69 45.90 22.40

Average 7587.75 30.35 14.81 10368.95 41.48 20.24

Figure 5. Average C-density in pine areas.

0.005.00

10.0015.0020.0025.0030.0035.0040.0045.0050.00

0 5 10 15 20 25

C de

nsities (M

g/ha

)

Plot No.

C (Mg/ha)

Linear (C (Mg/ha))

- 77 -

F. Secondary Forest

Block # Plot #

1994 2003

Biomass (Kg/ha)


Biomass (Kg/ha)


11 1 13875 55.50 24.97 16498.87 66.00 29.70 11 2 18330.01 73.32 32.99 23784.55 95.14 42.81 11 3 7928.554 31.71 14.27 11721.84 46.89 21.10 11 4 8704.358 34.82 15.67 15829.79 63.32 28.49 16 1 6674.291 26.70 12.01 9590.779 38.36 17.26 16 2 9276.825 37.11 16.70 12599.29 50.40 22.68 16 3 5680.229 22.72 10.22 8351.617 33.41 15.03 20 9319.37 37.28 16.77 15044.32 60.18 27.08

Average 9973.58 39.89 17.95244 14177.63 56.71 25.51974

Figure 6. Average C-density in secondary forest.

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

0 2 4 6 8 10

C de

nsity (M

g/ha

)

Plot number

C (Mg/ha)

Linear (C (Mg/ha))

- 78 -

Appendix 4: Rules and Regulations

- 79 -

Appendix Rules and regulations

Natural resources development program and

agro-forestry rules and regulations

I. SWIDDEN FARMING PERMIT A. Any person who wants to prepare a new farm clearing (uma) must get a permit from the

Agro-forestry Office. A fee of five (5.00) pesos shall be collected for the permit. B. Only residents of the Kalahan Reserve shall be granted a swidden farming permit. C. Any person who wants to cultivate land outside his/her own claim must obtain a written

permission from the claimant. This practice shall be discouraged. D. Whenever a newly cleared area is to be burned, the owner must maintain a fireline with a

width of 10 meters. This should be inspected first by a forest guard before the clearing is burned. Violation of this regulation shall be penalized for causing forest fires.

E. Clearing in reserved areas, parks, watersheds, sanctuaries, research sites shall not be allowed.

F. Forest guards neglecting their duties with regards to these policies shall be subjected to administrative sanctions.

G. Penalties 1. Anybody clearing or extending clearings in restricted areas shall be fined PhP500 and

will be required to repair the damage or shoulder the equivalent cost of said repair. 2. Anybody clearing without a permit shall be fined 250 pesos. Clearing any area other

than the inspected site is considered clearing without a permit.

II. TREE CUTTING PERMIT A. Any person who wants to cut any tree must first get a permit from the Agro-forestry

office. B. The permit shall identify the tree to be cut and the time frame within which the tree

should be cut and removed from the forest. C. A “minute” of the lumber needed shall be required from the applicants. This must be

approved by the Barangay Captain of the area where the tree is to be used. D. Tree cutting permits shall only be issued upon approval of the Agro-Forestry office and

upon payment of the corresponding permit fee as to the following purposes: E. Profit sharing from the permit fees to be collected shall be implemented based on a 40-

60% scheme between the barangay and the KEF respectively. F. No tree shall be cut without the proper mark of the Forester responsible for the Forest

Improvement Technology (FIT) activities under the Natural Resources Development Program. No permit shall be issued to cut any tree not so marked. This includes salvage trees or sanitation cutting. The mark will indicate the direction to fell. The foresters shall avoid issuing permits to be implemented during the rainy season when forest damage may be severe.

G. Penalties 1. First offense: any person violating these regulations shall be fined 400 pesos fore

every tree cut. Any lumber, slab or other products obtained will be confiscated.

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2. Second offense: Violators shall be fined 400 pesos and shall be denied a cutting permit in the future. Any lumber, slab, or other products obtained shall be confiscated.

III. CHAINSAW REGISTRATION AND OPERATIONS A. All chainsaws operating within the Kalahan Reserve must be registered annually with the

Agro-forestry Office. A copy of the registration will be furnished to the CENRO. A charge of 200 pesos registration will be paid by the owner/operator per year.

B. A maximum of 14 chainsaws shall only be allowed to operate within the Kalahan Reserve. Replacements or new chainsaws shall not be allowed.

C. The entry or operations of unregistered chainsaws in the Kalahan Reserve is absolutely forbidden.

D. A forest charge will be collected from the chainsaw owners/operators equivalent to 15% of the lumber price generated purposely for forest improvement.

E. No lumber shall be brought outside the Kalahan Reserve. Accepting orders, selling, or donating lumbers to any person, group, or institution outside the Reserve is prohibited.

F. PENALTIES: Any person found violating any of these regulations will be fined as follows: 1. First offense: Any person who accepts lumber orders to donate or sell to persons

outside of the Kalahan Reserve will be fined 500 pesos. 2. Second offense: Permanent cancellation of chainsaw registration. 3. Any chainsaw owner or operator who fails to pay the proper forest charges within 90

days shall be suspended from the operation of his chainsaw until his obligation is paid in full.

4. Operations of unregistered chainsaws shall be fined 500 pesos and an additional fine of 400 pesos for every tree cut.

5. Failure to renew chainsaw registration in 2 months after the expiration of its registration shall be a ground for cancellation of the permit to operate.

IV. FISHING A. Residents of the Kalahan Reserve are free to do fishing by traditional means but

chemicals and electricity shall not be allowed under any circumstances. Non-residents are strictly forbidden to fish within the Kalahan Reserve.

B. Penalties: Violators of this policy shall be fined as follows:

1. Use of illegal fishing methods will be fined 400 pesos per violator and all fishing supplies and/or equipment will be confiscated.

2. Non-residents who fish within the Kalahan Reserve shall be charged with illegal entry in addition to being punished for illegal fishing.

C. Use of “natural tuba” in halap may be allowed provided that the waterflow be returned immediately after fishing.

V. FOREST FIRES A. Limited prescribed burning in grazing lands may be allowed provided that the interested

party obtains a permit describing the specific area to be burned and the date and time of

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burning. Only a forester shall be allowed to issue this permit. A charge of five pesos will be paid.

Any fire which occurs which is not covered by a swidden permit or grazing land burning permit shall be considered as a forest fire.

B. Penalties 1. Any person who causes a forest fire shall pay the proper remuneration for all persons

involved in putting out the fire. 2. The guilty party must pay or repair all damages to houses, fruit trees, forest trees, etc. 3. The guilty party must reforest the burned area. 4. The guilty party must pay a fine of 500 pesos.

VI. QUARRYING A. Quarrying in the riverbeds shall be supervised by the Barangay concerned in cooperation

with the Agro-Forestry Office. B. Clearing stone from the road shall not be considered quarrying.

VII. ILLEGAL ENTRY A. Persons who are not bonafide residents of the Kalahan Reserve are not entitled to harvest

or utilize the natural resources within the Kalahan Reserve. B. Penalties: Any person violating this regulation shall be fined a minimum of 500 pesos or

a maximum of 5,000 pesos and any and all harvested forest products shall be confiscated. Said violation may also be reported to the DENR or PNP with a request that violators be prosecuted according to law.

VIII. SANCTUARIES AND WATERSHEDS A. The KEF has designated two Watershed-Sanctuaries within the Kalahan Reserve. All

plant and animal resources found therein are under protection. Hunting, catching animals and harvesting plants are prohibited. Gathering of limited samples for research purposes may be permitted subject to permission from the KEF and Barangay authorities.

B. Barangays are encouraged to identify additional watersheds within their jurisdiction. FIT may be practiced inside unless the watershed is also declared to be a sanctuary.

C. Penalties 1. Violations of this regulation shall be punished with a fine of at least 1,000 pesos but

not more than 10,000 pesos depending on the severity of the violation. Any and all products or resources obtained by the violator shall be confiscated.

2. Attempts to violate this regulation shall be considered as consummated violations.

IX. HUNTING A. Seasonal hunting is allowed outside the sanctuaries during the following periods:

Animals: July to August

Birds: November to December

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The night bird catching “Akik” has not regulation provided to cover this issue. A larger body should reconsider this to resolve issues.

B. Penalties Any person found violating this regulation shall be fined 500 pesos plus confiscation of harvest and hunting equipment.

X. LAND CLAIMS A. Each bonafide resident family may claim a maximum of ten (10) hectares of private land

within the Kalahan Reserve. Each claimant must make and implement a land use plan of which 25% shall be dedicated to environmental protection and register the same with the Agro-forestry Office. Each claimant shall be issued a copy his/her claim.

B. Any claimant who does not begin implementation of his/her land use plan within a period of five (5) years from its registration may have his/her claim reduced in size.

C. Sale, mortgage or transfer of possession of any land claim to other bonafide residents of the Kalahan Reserve shall require the approval of the Board of Trustees (BOT) through the NRDP Agro-forestry Office which shall maintain an up-to-date record of all such claims.

D. Sale, mortgage or transfer of possession of any land claim to any person who is not a bonafide resident of th4e Kalahan reserve shall not be allowed and the KEF will not recognize such transactions.

E. All surveys, including relocation and subdivision, shall be done by the Agro-forestry Office of the KEF. The Agro-forestry office shall charge the amount of 800 pesos for the first day and 600 pesos for each succeeding day needed for the resurvey to cover costs of labor in the field, equipment, transportation, materials and registration. Disputes over boundaries must be discussed first among the concerned claimants and referred to the Tribal Elders and Barangay officials. Failure of the accomplishment of the survey due to unclarified boundary disputes shall be charged against the claimant requesting resurvey.

XI. MISCELLANEOUS POLICIES A. Tree planting: All barangays covered by the Kalahan Reserve are encouraged to initiate

and actively participate to the regular tree planting activities in their respective barangays.

B. Banned Species: Cutting and or gathering of the banned or endangered plant or animal species inside the Kalahan Reserve is strictly prohibited.

C. Certification of lumber origin: A Certification of Lumber Origin may be issued by the Agro-Forestry Office to individuals who wish to move lumber from a house within the Reserve to some location outside of the Reserve provided that the lumber are originally sourced from within the Kalahan Reserve with proper permits.

D. Ban of chemical pesticides: In Keeping with the KEF policy of environmental cooperation in all undertakings that involve the natural resources, no chemical pesticides be used within the Reserve. It was understood that use of these will have adverse effects on the soil, biodiversity, and human health.

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The effects of thrown pesticides in the river, the guilty party is obliged to pay the damage on lives and properties.

E. Collection of fines and fees: All fines must be collected within three (3) months from the date they were promulgated. Fines not paid within three months shall be charged an interest of 3% per month. For the share of the barangays from all fines and fees, it shall be given every 12th month of the year.

F. Disposition of fines: Fines shall be shared by KEF and the Barangay concerned. The 75% shall go to the apprehending party and 25% shall be given to the other party. When an individual apprehends the violator, he/she shall receive 50% of the fine and the KEF and the concerned barangay shall be entitled to 25% each

G. Other actions: Violations may be referred to higher authorities for action if violators fail to comply.

H. Lumber price: P6.00 per board foot I. Orchid gathering moratorium: Moratorium on gathering orchids in all parts of the

Reserve shall be imposed on January 1, 2002. Training on orchid production shall also be conducted.

J. Effectivity: February 1, 2001.

Approved this day of December 5, 2000 at Imugan, Sta. Fe, Nueva Vizcaya.

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Appendix 5: Forest Improvement Technology (FIT)

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Appendix 5: Forest Improvement Technology (FIT) Source: Rice (2000)

The goal of FIT is to improve the forest, rather than simply improve the short-term income of the forest farmer. In the long run this will lead to more sustainable increases in income. Trees are cut continuously in small amounts rather than all together every thirty years. In this way the forest ecosystem can be maintained.

Each year the forest farmer makes a selection of trees to be cut. He checks the forest for crooked, damaged or crowded trees that need to be removed to improve the forest. When these have been removed, they are sawn into lumber. It may not be first-class wood but it can be used or sold. Simple equipment is used and the sawdust, tops and branches are left to rot because they restore fertility to the forest soil and help maintain biodiversity. The forest farmer does not separate the potential crop trees from the other trees because he knows that all trees have a role to play in the forest.

In natural forests there is a continuous process of rejuvenation. Trees die or are felled by storms. In this way the canopy is opened and, because the microclimate is not damaged, young seedlings get a chance to develop. FIT follows this natural process. Mature trees that have stopped growing are removed to create favourable conditions for forest rejuvenation. If this is done every year, the forest will continue to develop and improve. The removal of individual trees does not hurt the forest or its environment and provides first class lumber. If there are large open spaces, a forest pioneer species will be planted first. Agricultural crops are not planted between the trees because they would bother the other plants that need to grow to make a good forest. The population of one or two species of large or small plants can be increased by enrichment planting. This can be very favourable as long as the forest is not turned into a plantation.

As the forest grows, biodiversity will continue to improve and many species of insects, small animals, grasses and other plants will move in. This is good because all of these species help each other and the improved biodiversity will encourage the forest to grow faster and become healthier. The forest farmer will only cut a small amount of growth allowing the forest to improve each year.

The growth-rate presently expected in Philippine forests is about 4.5 cubic meters per hectare per year. Under proper management, using FIT, the forest can produce as much as 15 - 20 cubic meters per hectare per year. Such an analogue forest still retains the characteristics of a natural forest. It is not a plantation. It still has high bio-diversity and is an effective watershed with a high percolation rate. It will also provide a sanctuary for many kinds of wild orchids, animals, birds and insects.

If each forest farmer cares for 5 hectares of good forest, he may harvest up to 80 cubic meters of first class lumber every year without damaging the forest. That would provide him with higher cash income than many professionals and he would still have plenty of time to produce his own food on the farm. Once the forest has developed, it can be sustained indefinitely.

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Appendix 6: FALLOW Model results on biodiversity, carbon stocks and sediment filtering capacity

Appendix

x 6: PredictedKalahan

d time-average2001-2030 pe

ed relative adderdio under so

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ditionality on eome scenarios

ecosystem ser(in %).

rvices and commmunity welffare in

WORKING PAPERS IN THIS SERIES

2005 1. Agroforestry in the drylands of eastern Africa: a call to action 2. Biodiversity conservation through agroforestry: managing tree species diversity within a

network of community-based, nongovernmental, governmental and research organizations in western Kenya.

3. Invasion of prosopis juliflora and local livelihoods: Case study from the Lake Baringo area of Kenya

4. Leadership for change in farmers organizations: Training report: Ridar Hotel, Kampala, 29th March to 2nd April 2005.

5. Domestication des espèces agroforestières au Sahel : situation actuelle et perspectives 6. Relevé des données de biodiversité ligneuse: Manuel du projet biodiversité des parcs

agroforestiers au Sahel 7. Improved land management in the Lake Victoria Basin: TransVic Project’s draft report. 8. Livelihood capital, strategies and outcomes in the Taita hills of Kenya 9. Les espèces ligneuses et leurs usages: Les préférences des paysans dans le Cercle de

Ségou, au Mali 10. La biodiversité des espèces ligneuses: Diversité arborée et unités de gestion du terroir dans le

Cercle de Ségou, au Mali 2006 11. Bird diversity and land use on the slopes of Mt. Kilimanjaro and the adjacent plains, Tanzania 12. Water, women and local social organization in the Western Kenya Highlands 13. Highlights of ongoing research of the World Agroforestry Centre in Indonesia 14. Prospects of adoption of tree-based systems in a rural landscape and its likely impacts on

carbon stocks and farmers’ welfare: The FALLOW Model Application in Muara Sungkai, Lampung, Sumatra, in a ‘Clean Development Mechanism’ context

15. Equipping integrated natural resource managers for healthy Agroforestry landscapes. 17. Agro-biodiversity and CGIAR tree and forest science: approaches and examples from

Sumatra. 18. Improving land management in eastern and southern Africa: A review of policies. 19. Farm and household economic study of Kecamatan Nanggung, Kabupaten Bogor, Indonesia:

A socio-economic base line study of Agroforestry innovations and livelihood enhancement. 20. Lessons from eastern Africa’s unsustainable charcoal business. 21. Evolution of RELMA’s approaches to land management: Lessons from two decades of

research and development in eastern and southern Africa

22. Participatory watershed management: Lessons from RELMA’s work with farmers in eastern Africa.

23. Strengthening farmers’ organizations: The experience of RELMA and ULAMP. 24. Promoting rainwater harvesting in eastern and southern Africa. 25. The role of livestock in integrated land management. 26. Status of carbon sequestration projects in Africa: Potential benefits and challenges to scaling

up. Social and Environmental Trade-Offs in Tree Species Selection: A Methodology for Identifying Niche Incompatibilities in Agroforestry [Appears as AHI Working Paper no. 9]

28. Managing tradeoffs in agroforestry: From conflict to collaboration in natural resource management. [Appears as AHI Working Paper no. 10]

29. Essai d'analyse de la prise en compte des systemes agroforestiers pa les legislations forestieres au Sahel: Cas du Burkina Faso, du Mali, du Niger et du Senegal.

30. Etat de la recherche agroforestière au Rwanda etude bibliographique, période 1987-2003 2007 31. Science and technological innovations for improving soil fertility and management in Africa: A

report for NEPAD’s Science and Technology Forum. 32. Compensation and rewards for environmental services. 33. Latin American regional workshop report compensation. 34. Asia regional workshop on compensation ecosystem services. 35. Report of African regional workshop on compensation ecosystem services. 36. Exploring the inter-linkages among and between compensation and rewards for ecosystem

services CRES and human well-being 37. Criteria and indicators for environmental service compensation and reward mechanisms:

realistic, voluntary, conditional and pro-poor 38. The conditions for effective mechanisms of compensation and rewards for environmental

services. 39. Organization and governance for fostering Pro-Poor Compensation for Environmental

Services. 40. How important are different types of compensation and reward mechanisms shaping poverty

and ecosystem services across Africa, Asia & Latin America over the Next two decades? 41. Risk mitigation in contract farming: The case of poultry, cotton, woodfuel and cereals in East

Africa. 42. The RELMA savings and credit experiences: Sowing the seed of sustainability 43. Yatich J., Policy and institutional context for NRM in Kenya: Challenges and opportunities for

Landcare. 44. Nina-Nina Adoung Nasional di So! Field test of rapid land tenure assessment (RATA) in the

Batang Toru Watershed, North Sumatera. 45. Is Hutan Tanaman Rakyat a new paradigm in community based tree planting in Indonesia?

46. Socio-Economic aspects of brackish water aquaculture (Tambak) production in Nanggroe Aceh Darrusalam.

47. Farmer livelihoods in the humid forest and moist savannah zones of Cameroon. 48. Domestication, genre et vulnérabilité : Participation des femmes, des Jeunes et des catégories

les plus pauvres à la domestication des arbres agroforestiers au Cameroun. 49. Land tenure and management in the districts around Mt Elgon: An assessment presented to

the Mt Elgon ecosystem conservation programme. 50. The production and marketing of leaf meal from fodder shrubs in Tanga, Tanzania: A pro-poor

enterprise for improving livestock productivity. 51. Buyers Perspective on Environmental Services (ES) and Commoditization as an approach to

liberate ES markets in the Philippines. 52. Towards Towards community-driven conservation in southwest China: Reconciling state and

local perceptions. 53. Biofuels in China: An Analysis of the Opportunities and Challenges of Jatropha curcas in

Southwest China. 54. Jatropha curcas biodiesel production in Kenya: Economics and potential value chain

development for smallholder farmers 55. Livelihoods and Forest Resources in Aceh and Nias for a Sustainable Forest Resource

Management and Economic Progress 56. Agroforestry on the interface of Orangutan Conservation and Sustainable Livelihoods in

Batang Toru, North Sumatra. 57. Assessing Hydrological Situation of Kapuas Hulu Basin, Kapuas Hulu Regency, West

Kalimantan. 58. Assessing the Hydrological Situation of Talau Watershed, Belu Regency, East Nusa Tenggara. 59. Kajian Kondisi Hidrologis DAS Talau, Kabupaten Belu, Nusa Tenggara Timur. 60. Kajian Kondisi Hidrologis DAS Kapuas Hulu, Kabupaten Kapuas Hulu, Kalimantan Barat. 61. Lessons learned from community capacity building activities to support agroforest as

sustainable economic alternatives in Batang Toru orang utan habitat conservation program (Martini, Endri et al.)

62. Mainstreaming Climate Change in the Philippines. 63. A Conjoint Analysis of Farmer Preferences for Community Forestry Contracts in the Sumber

Jaya Watershed, Indonesia. 64. The highlands: a shared water tower in a changing climate and changing Asia 65. Eco-Certification: Can It Deliver Conservation and Development in the Tropics. 66. Designing ecological and biodiversity sampling strategies. Towards mainstreaming climate

change in grassland management. 67. Towards mainstreaming climate change in grassland management policies and practices on

the Tibetan Plateau 68. An Assessment of the Potential for Carbon Finance in Rangelands 69. ECA Trade-offs Among Ecosystem Services in the Lake Victoria Basin.

69. The last remnants of mega biodiversity in West Java and Banten: an in-depth exploration of RaTA (Rapid Land Tenure Assessment) in Mount Halimun-Salak National Park Indonesia

70. Le business plan d’une petite entreprise rurale de production et de commercialisation des plants des arbres locaux. Cas de quatre pépinières rurales au Cameroun.

71. Les unités de transformation des produits forestiers non ligneux alimentaires au Cameroun. Diagnostic technique et stratégie de développement Honoré Tabuna et Ingratia Kayitavu.

72. Les exportateurs camerounais de safou (Dacryodes edulis) sur le marché sous régional et international. Profil, fonctionnement et stratégies de développement.

73. Impact of the Southeast Asian Network for Agroforestry Education (SEANAFE) on agroforestry education capacity.

74. Setting landscape conservation targets and promoting them through compatible land use in the Philippines.

75. Review of methods for researching multistrata systems. 76. Study on economical viability of Jatropha curcas L. plantations in Northern Tanzania assessing

farmers’ prospects via cost-benefit analysis 77. Cooperation in Agroforestry between Ministry of Forestry of Indonesia and International Center

for Research in Agroforestry 78. "China's bioenergy future. an analysis through the Lens if Yunnan Province 79. Land tenure and agricultural productivity in Africa: A comparative analysis of the economics

literature and recent policy strategies and reforms Boundary organizations, objects and agents: linking knowledge with action in Agroforestry watersheds

81. Reducing emissions from deforestation and forest degradation (REDD) in Indonesia: options and challenges for fair and efficient payment distribution mechanisms

2009 82. Mainstreaming climate change into agricultural education: challenges and perspectives 83. Challenging conventional mindsets and disconnects in conservation: the emerging role of eco-

agriculture in Kenya’s landscape mosaics 84. Lesson learned RATA garut dan bengkunat: suatu upaya membedah kebijakan pelepasan

kawasan hutan dan redistribusi tanah bekas kawasan hutan 85. The emergence of forest land redistribution in Indonesia 86. Commercial opportunities for fruit in Malawi 87. Status of fruit production processing and marketing in Malawi 88. Fraud in tree science 89. Trees on farm: analysis of global extent and geographical patterns of agroforestry 90. The springs of Nyando: water, social organization and livelihoods in Western Kenya 91. Building capacity toward region-wide curriculum and teaching materials development in

agroforestry education in Southeast Asia 92. Overview of biomass energy technology in rural Yunnan (Chinese – English abstract) 93. A pro-growth pathway for reducing net GHG emissions in China

94. Analysis of local livelihoods from past to present in the central Kalimantan Ex-Mega Rice Project area

95. Constraints and options to enhancing production of high quality feeds in dairy production in Kenya, Uganda and Rwanda

2010 96. Agroforestry education in the Philippines: status report from the Southeast Asian Network for

Agroforestry Education (SEANAFE) 97. Economic viability of Jatropha curcas L. plantations in Northern Tanzania- assessing farmers’

prospects via cost-benefit analysis. 98. Hot spot of emission and confusion: land tenure insecurity, contested policies and competing

claims in the central Kalimantan Ex-Mega Rice Project area 99. Agroforestry competences and human resources needs in the Philippines 100. CES/COS/CIS

paradigms for compensation and rewards to enhance environmental Services 101. Case study approach to region-wide curriculum and teaching materials development in

agroforestry education in Southeast Asia 102. Stewardship agreement to reduce emissions from deforestation and degradation (REDD):

Lubuk Beringin’s Hutan Desa as the first village forest in Indonesia 103. Landscape dynamics over time and space from ecological perspective 104. A performance-based reward for environmental services: an action research case of

“RiverCare” in Way Besai sub-watersheds, Lampung, Indonesia 105. Smallholder voluntary carbon scheme: an experience from Nagari Paningahan, West Sumatra,

Indonesia

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