Cover Photos: © Anisa Prawi (Conservaon Internaonal)sp13.conservation.org/global/indonesia/media/Documents/Blue_Carbon... · Overlay of high resoluoon pre-2006 image and the mangrove

58 B l u e C a r b o n S c i e n c e & P o l i c y : w i t h a P a r t i c u l a r R e f e r e n c e t o K a i m a n a , W e s t P a p u a

59B l u e C a r b o n S c i e n c e & P o l i c y : w i t h a P a r t i c u l a r R e f e r e n c e t o K a i m a n a , W e s t P a p u a

Cover Photos: © Anisa Pratiwi (Conservation International)


Blue Carbon Science & Policy:with a Particular Reference to Kaimana, West Papua

Author:Barakalla & Rony Megawanto


AcknowledgementMinistry of Environment and Forestry, Republic of IndonesiaMinistry of Marine Affairs and Fisheries, Republic of IndonesiaMinistry of National Development Planning (Bappenas), Republic of IndonesiaCoordinating Ministry of Marritime Affairs, Republic of IndonesiaGovernment of Kaimana Regency, West Papua Balai Besar Konservasi Sumber Daya Alam Papua BaratUniversity of Papua (UNIPA) Institute of Marine Research and ObservationCenter for International Forestry Research (CIFOR) MacArthur FoundationConservation International

The Analysis was supported by Sigit Deni Sasmito and Jennifer Howard.This research was funded by MacArthur Foundation.A special thank you goes to Victor Nikijuluw and Jennifer Howard for the extensive review and comments.Valuable inputs and review also provided by Ketut Sarjana Putra, Daniel Murdiyarso and Emily Pidgeon.Our sincere gratitude to Kaimana government, Conservation International Kaimana Team, University of Papua team members, Institute of Marine Research and Observation.

Editors;

Chief Editors;Barakalla (Conservation International)Rony Megawanto (Conservation International).

Members;Ketut Sarjana Putra (Conservation International), Victor Nikijuluw (Conservation International), Iman Santoso (Conservation International), Emily Pidgeon (Conservation International), Jennifer Howard (Conservation International), Sigit Deni Sasmito (CIFOR / Charles Darwin University),Regina Nikijuluw (Conservation International), Dwiki Dewantoro (Conservation International), Anastasia Ramalo Sijabat (Conservation International), Ines Ayostina (Conservation International).

Contributors;Frida Sidik (Institute of Marine Research and Observation – Ministry of Marine and Fisheries), Nuryani Widagti (Institute of Marine Research and Observation – Ministry of Marine and Fisheries), Rina Jowei (University of Papua), Wolfram Y Mofu (University of Papua), Herry Kopalit (University of Papua), Hendri (University of Papua), Victor Simbiak (University of Papua), Alfredo Wanma (University of Papua), Ping Machmud (Conservation International), Irwan Pasambo (Conservation International), Sefrianto T Saleda (Conservation International), Annisa Pertiwi (Conservation International), Dortheus Rumere (Conservation International), Fini Lovita (Conservation International).

© Conservation International Indonesia, 2017

www.conservation.org

Reference for Citation;Barakalla & Megawanto.R, (2017) Blue Carbon Science and Policy : with particular reference to Kaimana, West Papua.


TABLE OF CONTENTS

Acknowledgement ................................................................................................................................. 2Table of Contents ................................................................................................................................... 3Figure list ................................................................................................................................................ 4Table list ................................................................................................................................................. 5Acronyms and Definitions ...................................................................................................................... 6Unit list ................................................................................................................................................... 10Keywords ................................................................................................................................................ 11Foreword National Development Agency .............................................................................................. 12Foreword Kaimana Regent ..................................................................................................................... 13Preface Conservation International Indonesia Vice President ............................................................... 141. Introduction ...................................................................................................................................... 15

1.1 What is Blue Carbon? .................................................................................................................. 151.2 Why is measuring Blue Carbon important? ................................................................................ 151.3 The International Blue Carbon Initiative ..................................................................................... 161.4 Conservation International Blue Carbon work in Kaimana ......................................................... 17

2. Blue Carbon Field Procedure .............................................................................................................. 182.1 Kaimana Regency Background .................................................................................................... 182.2 Mangrove in Kaimana ................................................................................................................. 222.3 Mangrove Crab and Blue Carbon in Arguni Bay, Kaimana ........................................................... 242.4 Consideration for Carbon Measurement in Mangrove Ecosystem ............................................. 252.5 Blue Carbon Assessments in Kaimana ......................................................................................... 26

3. Blue Carbon related Policies and Regulations in Indonesia ................................................................ 433.1 National target for NDC .............................................................................................................. 433.2 Blue Carbon Ecosystem Contribution ......................................................................................... 453.3 Mangrove Management ............................................................................................................. 47

References ............................................................................................................................................... 52


FIGURE LIST

Figure 1. Annual mean carbon sequestration rates for blue carbon habitats per unit area compared to terrestrial forest habitats .................................................................................................... 15Figure 2. Mean carbon storage aboveground and belowground in coastal ecosystems versus terrestrial forest ...................................................................................................................... 16Figure 3. Trends in vegetation “greenness” over a 15-year time span ................................................... 22Figure 4. Vegetation changes for Arguni Bay and Kaimana City ............................................................. 23Figure 5. Overlay of high resolutioon pre-2006 image and the mangrove change validation points located near a type of awuatic farming ................................................................................... 23Figure 6. CI working with Fishing and Living (MDPI) on sustainable fisheries program focusing mud crabs as primary commodity ................................................................................................... 24Figure 7. The cycle of tides and the ‘Rule of Twelfths’ ........................................................................... 25Figure 8. Sample site locations in Arguni Bay, West Papua .................................................................... 29Figure 9. Carbon stocks ground biomass across the different geographic regions of Arguni Bay, West Papua ............................................................................................................................. 30Figure 10. Soil bulk density with depth across regions of Arguni Bay, West Papua ................................. 30Figure 11. Relationship between soil C concentration and soil organic matter of a subset of calibration samples from Arguni Bay, West Papua .................................................................. 31Figure 12. Changes in soil C with depth across the different geographic regions of Arguni Bay, West Papua ............................................................................................................................. 31Figure 13. Changes in C density with depth across geographic regions of Arguni Bay ............................ 32Figure 14. Soil C stocks across regions of Arguni Bay, West Papua .......................................................... 32Figure 15. Map of sampling location in Buruway, Kaimana City and Etna ............................................... 34Figure 16. Schematic of original standardized plot layout for mangrove C-stock sampling ..................... 34Figure 17. Standing dead tree status illustration ..................................................................................... 35Figure 18. Field assessment of C stocks in the Kaimana mangrove ecosystems ...................................... 36Figure 19. The description of transect measurement and size for woody debris sampling ..................... 37Figure 20. Mangroves stand and canopy condition in study sites ............................................................ 37Figure 21. The mean of vegetation C stocks including aboveground biomass, belowground biomass and woody debris throughout assessed sites ......................................................................... 40Figure 22. The mean of top 100 cm soil C stocks across assessed sites ................................................... 40Figure 23. Soil properties across assessed sites ....................................................................................... 41Figure 24. Field documentation of sampled mangrove soils in Buruway, Etna, and Kaimana City .......... 42


TABLE LIST

Table 1. Estimates of carbon released by land-use change in coastal ecosystems globally and associated economic impacts .................................................................................................. 17Table 2. Mangrove extent and deforestation (2006-2016) in Kaimana ................................................. 17Table 3. Kaimana regency population density ....................................................................................... 18Table 4. Kaimana tribe population ......................................................................................................... 18Table 5. Crops plantation in Kaimana .................................................................................................... 20Table 6. Livestock in Kaimana ................................................................................................................ 20Table 7. Destructive fishing activities in Kaimana .................................................................................. 21Table 8. Carbon stock analysis for the Kaimana Regency ...................................................................... 26Table 9. Carbon stock analysis for project subsites ............................................................................... 27Table 10. Site gps coordinates and geographic region within Arguni Bay, West Papua ........................... 28Table 11. Basal area of mangrove stands across regions of Arguni Bay, West Papua .............................. 29Table 12. Basal area and relative dominance of mangrove species across Arguni Bay, West Papua ....... 29Table 13. Carbon stocks pool across regions of Arguni Bay ..................................................................... 32Table 14. Summary of data and sample collection for mangrove C-stock assessment ............................ 35Table 15. List of species composition and vegetation type throughout all sites in Kaimana Regency, West Papua .............................................................................................................................. 38Table 16. Important value index (Iv) of mangrove tree species across sampling sites in Kaimana Regency, West Papua ................................................................................................. 39Table 17. The summary of forest structure, site condition and organic soil depth ................................. 40Table 18. Projected BAU and greenhouse gas emission reduction from each sector category ............... 44


ACRONYMS AND DEFINITIONS

AAFOLU Agriculture, Forestry and Other Land UseArcView ArcGIS Software that is used within the approach for spatial analysis needsATM (Indonesian) Ayo Tanam Mangrove MMAF program for Mangrove

BB BiomassBAU Business As UsualBappenas National Planning Agency (Indonesia)BD Bulk densityBetatas (native Papuan) PotatoBIG (Indonesian) Badan Informasi Geospasial Geospatial Information AgencyBMKG (Indonesian) Badan Meteorologi, Klimatologi dan Geofisika Meteorology, Climatology and Geophysics AgencyBwN Building with Nature

CC CarbonCaCO3 Calcium carbonateCDM Clean Development MechanismCGIAR Consultative Group on International Agricultural ResearchCHN analyzer Elemental analyzer of mainly carbon, hydrogen and nitrogenCI Confidence IntervalCI Conservation InternationalCIFOR Center for International Forestry ResearchCO2 Carbon DioxideCOP Conference of the PartiesCorg Organic Carbon

DD DiameterDAS (Indonesian) Daerah Aliran Sungai WatershedD30 Mainstem diameter at 30 cm heightDbase Mainstem basal diameterDBD Dry Bulk Densitydbh Diameter at Breast HeightDEM Digital Elevation MapsDIC Dissolved Inorganic CarbonDmax Mainstem maximum diameter of sampled treesDtop Mainstem top diameter

Eeq EquivalentESRI Environmental Systems Research Institute

FFAO Food and Agriculture OrganizationsFIP Fisheries Improvement Project


GGHG Greenhouse GasGIS Geographic Information SystemGPS Global Positioning System

HH HydrogenH2O2 Hydrogen peroxideHCl Hydrogen chlorideHmax Maximum HeightHGU (Indonesian) Hak Guna Usaha The right to use a land / concession by National law

IID Identity Document, IdentifierIMRO Institute of Marine Research and Observation (BROL KKP)INCAS Indonesian national Carbon Accounting SystemIOC Intergovernmental Oceanographic CommissionIPB (Indonesian) Institute Pertanian Bogor Bogor Agriculture InstituteIPCC Intergovernmental Panel on Climate ChangeIUCN International Union for Conservation of NatureIv Important Value Index

KKampung (Indonesian) VillageKKMTN (Indonesian) Kelompok Kerja Mangrove Tingkat Nasional National Mangrove Working GroupKKP Agency for Research and Development of Marine and Fisheries (Baltitbang KP), Indonesia

LLAPAN (Indonesian) Lembaga Penerbangan dan Antariksa Nasional National Institute of Aeronautics and SpaceLIPI (Indonesian) Lembaga Ilmu Pengetahuan Indonesia Indonesian Institute of Scienceln Natural LogarithmLOI Loss on Ignition

MMFF Mangrove for the FutureMH SET marker horizonMoEF Ministry of Environment and Forestry (Indonesia)MMAF Ministry of Marine Affairs and Fisheries (Indonesia)MPA Marine Protected Areas

Nn Number of subsamplesN NitrogenN2 DinitrogenN2O Nitrous oxideNASA National Aeronautics and Space AdministrationND No DataNDC Nationally Determined ContributionNDVI Normalized Difference Vegetation Index


OO OxygenOM Organic Matter

PPDPT (Indonesian) Pengembangan Desa Pesisir Tangguh Coastal Development Programρ Wood densityPALSAR Phased Array L band Synthetic Aperture RadarPpt Part Per ThousandsPVC Polyvinyl chloride

RR2 Coefficient of determinationRAN GRK (Indonesian) Rencana Aksi Nasional Gas Rumah Kaca National Action Plan GHGREDD Reducing Emissions from Deforestation and Forest DegradationRHL (Indonesian) Rehabilitasi Hutan dan Lahan Forest and Land RehabilitationRp Rupiah (Indonesian currency)RTRW (Indonesian) Rencana tata Ruang Wilayah Regional Spatial Plan

SSD Standard DeviationSET Surface Elevation TableSNPEM (Indonesian) Strategi Nasional Pengelolaan Ekosistem Mangrove National Strategy for Mangrove Ecosystem ManagementSOM Soil Organic MatterSp (biological term) Species

TTambaks Aquaculture as a threat to mangrove ecosystem.T TempertureT1 Initial AssessmentT2 Subsequent Assessmentsth Tree Height

UUNEP United Nations Environment ProgrammeUNESCO United Nations Educational Scientific and Cultural OrganizationUNFCCC United Nations Framework Convention on Climate ChangeUNIPA University of PapuaUSD United States dollarUSGS US Geological Survey

VVCS Verified Carbon Standard


UNIT LIST

atmos AtmosphereºC Degree Celsiuscm Centimetercm3 Cubic centimeterh Hourha Hectareg GramGtCO2e Giga ton Carbon dioxide equivalentkg KilogramL Literm Meterm2 Square meter m3 Cubic meter Mg Megagrammg Milligrammm milimetermin MinutemL Millilitermol Mole% Percentπ Mathematical constant, the ratio of a circle’s circumference to its diameter, approximately equal to 3.14159$ Dollarσ Standard deviationt Metric ton


KEYWORDS

Active Remote Sensing – A remote-sensing system, such as radar, that produces electromagnetic radiation and measures its reflection back from a surface.

Activity Data – Geographical data showing the types of land coverage and use in a given area.

Allochthonous Carbon – Carbon produced in one location and deposited in another. In the context of blue carbon systems, this type of carbon results from the hydrodynamic environment in which they are found where sediments and associated carbon is transported from neighboring ecosystems (offshore and terrestrial).

Allometric Equations – Allometric equations establish quantitative relationships between key characteristics that are easy to measure (i.e., stem height/diameter) and other properties that are often more difficult to assess (i.e., biomass).

Autochthonous Carbon – Carbon produced and deposited in the same location. In the context of blue carbon systems, this type of carbon results from vegetation uptake of CO2 from the ocean and/or atmosphere that gets converted for use by plant tissue and decomposes into the surrounding soil.

Blue Carbon – The carbon stored in mangroves, tidal salt marshes, and seagrass meadows within the soil, the living biomass above ground (leaves, branches, stems), the living biomass below ground (roots), an the non-living biomass (litter and dead wood).

Carbon Inventory – A carbon inventory is an accounting of carbon gains and losses emitted to or removed from the atmosphere/ocean over a period of time. Policy makers use inventories to establish a baseline for tracking emission trends, developing mitigation strategies and policies, and assessing progress

Carbon Pool – Carbon pools refer to carbon reservoirs such as soil, vegetation, water, and the atmosphere that absorb and release carbon. Together carbon pools make up a carbon stock.

Carbon Stock – A carbon stock is the total amount of organic carbon stored in a blue carbon ecosystem of a known size. A carbon stock is the sum of one or more carbon pools. Emission Factors – A term used to describe changes in the carbon content of a pre-defined area due to change in land coverage and use (i.e., conversion from mangroves to shrimp ponds) or changes within a land use type (i.e., nutrient enrichment of seagrass).

Gain-loss Method – This method estimates the difference in carbon stocks based on emissions factors for specific activities (e.g., plantings, drainage, rewetting, deforestation) derived from the scientific literature and country activity data and results in Tier 1 and 2 estimates.

Inorganic Soil Carbon – The term soil inorganic carbon refers to the carbon component of carbonates (i.e., calcium carbonate) and can be found in coastal soils in the form of shellsand/or pieces of coral.

IPCC Tiers – The IPCC has identified three tiers of detail in carbon inventories that reflect the degrees of certainty or accuracy of a carbon stock inventory (assessment).

Tier 1 – Tier 1 assessments have the least accuracy and certainty and are based on simplified assumptions and published IPCC default values for activity data and emissions factors. Tier 1 assessments may have a large error range of +/- 50% for aboveground pools and +/- 90% for the variable soil carbon pools.Tier 2 – Tier 2 assessments include some country or site-specific data and hence have increased accuracy and resolution. For example, a country may know the mean carbon stock for different ecosystem types within the country.


Tier 3 – Tier 3 assessments require highly specific data of the carbon stocks in each component ecosystem or land use area, and repeated measurements of key carbon stocks through time to provide estimates of change or flux of carbon into or out of the area. Estimates of carbon flux can be provided through direct field measurements or by modeling.

Kaimana – A regency in West Papua, wchich holds 76,000 Ha of mangrove ecosystem. And where the blue carbon project is conducted as well as the fisheries improvement project.

Mangrove – A mangrove is a tree, shrub, palm or ground fern, generally exceeding one half meter in height that normally grows above mean sea level in the intertidal zone of marine coastal environments and estuarine margins. A mangrove is also the tidal habitat comprising such trees and shrubs.

Passive Remote Sensing – A remote-sensing system, such as an aerial photography imaging system, that only detects energy naturally reflected or emitted by an object.

Resolution – In remote sensing resolution of an image is an indication of its potential detail, where the smaller the pixel the higher the detail. In other words, 250 meters resolution data could identify any earthly feature that is 250 meters by 250 meters (useful for mapping ecosystem extent). Higher resolution data, such as 30 meters can be used to monitor in more detail (useful for identifying encroachment by aquaculture).

Soil Organic Carbon – The term soil organic carbon refers to the carbon component of the soil organic matter. The amount of soil organic carbon depends on soil texture, climate, vegetation and historical and current land use/management.

Soil Organic Matter – The term soil organic matter is used to describe the organic constituents in the soil (undecyed tissues from dead plants and animals, products produced as these decompose and the soil microbial biomass).

Stratification – A technique used to divide large heterogeneous sites (which require manysamples to account for variation) into smaller more homogeneous areas (where fewer samplesare needed) and is also useful when field conditions, logistical issues, and resource limitationsprevent dense sampling regimes


FOREWORDDirector of Marine Affairs and Fisheries of Indonesian National Development Planning Agency

I’m very grateful for the publication of this study report. In addition to comprehensive data, it offers a district-level approach that provides a greater insight into the natural wealth of our country. Unlike other smaller scope studies, this report is the first developed by our partner to examine the full extent of district-level potentials.

Mangrove is an ecosystem with many beneficial functions and services, one of which is climate change mitigation and adaptation. Indonesia has the largest mangrove population in the world – nearly a quarter of the world’s mangroves. For this reason, our mangroves play a major role in mitigating global warming and sequestering carbon as one of the global warming contributors.

Blue carbon is a term coined to describe the ecosystem services offered by mangroves. Other blue carbon contributors include seagrass meadows and tidal marshes. Recognizing the importance of blue carbon in climate change mitigation and adaptation, 50 countries are committed to the initiative under the Paris Agreement, and follow-through at both global and national levels has become a priority.

In terms of national program plans and directions, blue carbon is central to climate change mitigation and adaptation efforts. Furthermore, the fact that almost 60% of Indonesia’s population lives in and depends their livelihoods on coastal areas, which are home to mangrove ecosystem, places blue carbon as a key aspect in promoting coastal community welfare in Indonesia. The government will monitor and support the aligning of mangrove-related programs and blue carbon initiatives, which will then be translated into grassroot-level programs.

Going forward, we are envisioning a link and alignment between blue carbon and the Nationally Determined Contribution (NDC) as well as the Sustainable Development Goals (SDGs). Under the NDC, blue carbon contributes to potential carbon storage that supports efforts to achieve reduced greenhouse gas emissions, in which a 17.2% target is set for the forestry sector to secure potential carbon deposits in blue carbon ecosystems. Under the SDGs, blue carbon is included as SDG 13 for climate change and SDG 14 for ocean health.

I congratulate and thank Conservation International Indonesia for publishing this book, Blue Carbon Science & Policy : with a Particular Reference to Kaimana, West Papua. This report will serve as our collective source and reference for blue carbon approach, both in terms of science and research as well as policy and regulation.

Ir. R . Anang Noegroho Setyo Moeljono, M.E.MDirector of Marine Affairs and FisheriesNational Development Planning Agency


FOREWORDHead of Kaimana District

Global warming has long been a hot-button issue both nationally and globally. Indonesia has also made various efforts to mitigate and adapt to global warming. One that is starting to gain prominence is Blue Carbon.

Kaimana District covers more than 70 thousand hectares of mangrove forests with tremendous potential natural resources, which we, the locals, try very hard to protect. To conserve the environment, the Papuans maintain their own local wisdoms, such as sasi and hak ulayat, which are passed down for generations from the ancestors. Today, those local wisdoms are being reinforced with the support from Conservation International. On the other hand, the local government has also been trying to formulate local regulations that encourage environmental conservation, including for mangroves and the surrounding waters, to ensure sustainable and equitable distribution of welfare for Kaimana people.

National and local policies need to work in synergy to help Indonesia achieve its national commitment under the Paris Agreement, and also improve public welfare. For this purpose, Kaimana District is ready to become a National Blue Carbon Field Laboratory to support Indonesia’s national ambition. Since 70% of the people of Kaimana live in coastal areas, they heartily agree that mangroves need to be protected as an important source of livelihoods.

This document represents initiatives and collaborations of different stakeholders since 2014 to explore potentials of mangroves in Kaimana, West Papua. We hope this document can positively contribute to sustainable national management of Blue Carbon. Kaimana District is more than ready to become a model for other regions in Indonesia in the management of Blue Carbon, which offers enormous benefits to the local, national, and global communities.

Drs. Mathias MairumaHead of Kaimana District, West Papua


First of all, we’d like to thank all contributors who have been involved and supported the writing of this book, Blue Carbon Science & Policy : with a Particular Reference to Kaimana, West Papua. As part of the Blue Carbon program initiative undertaken by Conservation International (CI) Indonesia, this book provides an overview of blue carbon

ecosystems (particularly mangroves), CI Indonesia programs in Kaimana, and blue carbon-related policies.

Since launching the initiative in 2014, as a scientific organization, CI has always been relying on scientific data when formulating policy recommendations and program plans. Under this program, mangrove conservation is part of a three-pronged integrated approach: natural resources conservation, improved governance and policy support, and alternative community economic empowerment; to creating model blue carbon ecosystem management in Indonesia.

This study is the first to base its research on regional jurisdiction and has managed to provide an overview of comprehensive carbon stock accounting (that includes below- and above-ground carbon). The study was conducted in four locations to attempt to obtain a comprehensive description of district-level data. Further reading of this book will confirm the importance of mangroves for Indonesia, especially towards meeting the National Determined Contribution target set by the government in the forestry sector.

Besides lending significant benefits to conservation target, CI Indonesia has proven firsthand the economic benefits of mangrove conservation from mud crab farming. This serves as another valid proof for “mutualistic symbiosis between conservation and economy”, and an important consideration for policymakers at various levels when developing model mangrove management in Indonesia.

We sincerely hope this book can serve as a scientific reference for improved mangrove conservation management, and specifically as a reference for blue carbon ecosystem positioning in the Government of Indonesia’s national strategy for climate change mitigation and adaptation.

Ketut Sarjana PutraVice PresidentConservation International Indonesia

PREFACE Vice President Conservation International Indonesia


1.1 WHAT IS BLUE CARBON?The coastal ecosystems of mangroves, tidal marshes, and

seagrass meadows provide numerous benefits and services

that are essential for climate change adaptation along

coasts globally, including protection from storms and sea

level rise, prevention of shoreline erosion, regulation of

coastal water quality, provision of habitat for commercially

important fisheries and endangered marine species, and

food security for many coastal communities. Additionally,

these ecosystems sequester and store significant amounts

of coastal blue carbon from the atmosphere and ocean and

hence are now recognized for their role in mitigating climate

change.

Despite these benefits and services, coastal blue carbon

ecosystems are some of the most threatened ecosystems

on Earth, with an estimated 340,000 to 980,000 hectares

being destroyed each year. It is estimated that up to 67% and

at least 35% and 29% of the global coverage of mangroves

tidal marshes and seagrass meadows respectively have

been lost. If these trends continue at current rates, a

further 30–40% of tidal marshes and seagrasses and

nearly all unprotected mangroves could be lost in the next

100 years. When degraded or lost, these ecosystems can

become significant sources of the greenhouse gas carbon

dioxide.

Blue Carbon provides a new opportunity for motivating and

supporting coastal ecosystem conservation (restoration

and protection) globally, and hence for sustaining the

multiple benefits these ecosystems provide. Conservation

and restoration of these coastal ecosystems has been

increasingly addressed in international and national

climate change mitigation policy and finance mechanisms.

However, to date, countries have not incorporated coastal

blue carbon into their portfolio of climate change mitigation

or coastal management policies and actions.

1.2 WHY IS MEASURING BLUE CARBON IMPORTANT?The coastal ecosystems of mangroves, tidal marshes, and

seagrass meadows mitigate climate change by sequestering

carbon dioxide (CO2) from the atmosphere and oceans at

significantly higher rates, per unit area, than terrestrial

forests (Figure 1). The carbon deposits accumulated within

these systems are stored aboveground in the biomass of

plants (tree trunks, stems, and leaves), belowground in

the plant biomass (root systems and rhizomes), and in the

carbon-rich organic soils typical to these ecosystems.

Carbon is dominantly stored belowground in the soils of

coastal ecosystems (see Figure 2). Of the coastal blue carbon

stored within mangroves, tidal marshes, and seagrass

meadows, 50 – 99% is located in the soils belowground. This

rich soil carbon stores can be up to six

Figure 1. Annual mean carbon sequestration rates for blue carbon habitats per unit area compared to terrestrial forest habitats (error bars indicate standard error). The annual sequestration rate for a given ecosystem is the quantity of CO2 removed from the atmosphere and/or ocean and trapped in natural habi-

tats (Modified from McLeod et al. 2011)

[Tropical Forests – Boreal Forests – Temperate Forests Mangroves – Tidal Marshes – Seagrass Meadows]

1 INTRODUCTION

The following parts (1.1 untill 1.3) was taken from The Blue Carbon

Initiative website (http://thebluecarboninitiative.org/blue-carbon).


Recent studies estimate carbon storages in the top meter of

soil to be approximately 280 Mg C ha-1 for mangroves, 250

Mg C ha-1 for tidal marshes, and 140 Mg C ha-1 for seagrass

meadows, equivalent to 1,030 megagrams of carbon

dioxide equivalence per hectare (Mg CO2 ha-1) for estuarine

mangroves, 920 Mg CO2 ha-1 for tidal marshes, and 520 Mg

CO2 ha-1 for seagrass meadows. Adding the carbon in the

plants, the mean carbon storages are 1,494, 951, and 607

Mg CO2 eq ha-1 for mangroves, tidal marshes, and seagrass

meadows respectively.

There is, however, significant variation in the carbon stored

by coastal ecosystems with regional and local differences.

Some extreme examples of blue carbon storage include

the Micronesian mangrove forests on the island of Palau,

where carbon storage levels have been measured at 1,385

Mg C ha-1 (3.4 x the global average). North American tidal

marshes can hold up to 1,728 Mg C ha-1, well beyond the

global average. A recent global study on seagrass meadows

found that seagrasses located in the Mediterranean had the

highest average soil carbon measuring 372.4 Mg C ha-1 as

well as high carbon storage in plant biomass (7.29 Mg C ha-1).

Compared to other ecosystems, blue carbon ecosystems

release significant amounts of CO2 per unit area upon

conversion or degradation.

When coastal ecosystems are degraded, lost or converted to

other land uses, the large stores of blue carbon in the soils

are exposed and released as CO2 into the atmosphere and/

or ocean. Current rates of loss of these coastal ecosystems

may result in 0.15 – 1.02 billion tons of CO2 released

annually. Although the combined global area of mangroves,

tidal marshes, and seagrass meadows equates to only 2 –

Figure 2. Mean carbon storage aboveground and belowground in coastal ecosystems versus terrestrial forest (Fourqueran et al. 2012; Pan et al. 2011; Pendleton et al. 2012).

6% of the total area of tropical forest, degradation of these

ecosystems account for 3 – 19% carbon emissions from

global deforestation. Note that previous estimates of the

greenhouse gas impact of coastal ecosystem conversion

only accounted for lost sequestration and not the release of

carbon, and hence were significant underestimates. Recent

analysis suggests that the annual loss of the three blue

carbon ecosystems is resulting in emissions (0.45 Pg CO2 yr-1

– see Table 1) similar to the annual fossil fuel CO2 emissions

of the United Kingdom (the world’s 9th ranked country by

emissions).

1.3 THE INTERNATIONAL BLUE CARBON INITIATIVEThe International Blue Carbon Initiative is a coordinated,

global program focused on mitigating climate change

through the conservation and restoration of coastal and

marine ecosystems. Coastal ecosystems are some of the

most productive on Earth. They provide us with essential

ecosystem services, such as coastal protection from storms

and nursery grounds for fish. We also know that they provide

another integral service - sequestering and storing “blue”

carbon from the atmosphere and oceans and hence are an

essential piece of the solution to global climate change.

The Blue Carbon Initiative focuses on mangroves, salt

marshes, and seagrasses, which are found on every continent

except Antarctica. These coastal ecosystems cover between

13.8 and 15.2 million hectares (Mha), 2.2 and 40 Mha, and

17.7 and 60 Mha, respectively. Combined, these ecosystems

cover approximately 49 Mha.

• The Blue Carbon Initiative works to protect and restore

coastal ecosystems for their role in reducing impacts of

global climate change. To support this work, the Initiative


Table 1. Estimates of carbon released by land-use change in coastal ecosystems globally and associated economic impacts. Notes: 1 Pg = 1 billion metric tons. To obtain values per km2, multiply by 100. (Modified from Pendleton et al. 2012)

Inputs Results

Ecosystem Global extent(Mha)

Current conversion rate (% yr-1)

Near-surface C susceptible(top meter sediment+biomass, Mg

CO2 ha-1)

C emissions(Pg CO2 yr-1)

Mangroves 13,8 – 15,2 (14,5) 0,7 – 30 (1,9) 373 – 1492 (933) 0,09 – 0,45 (0,24)

Tidal Marsh 2,2 – 40 (5,1) 1,0 - 2,0 (1,5) 237 – 949 (593) 0,2 – 0,24 (0,06)

Seagrass Meadows 17,7 – 60 (30) 0,4 – 2,6 (1,5) 131 – 522 (326) 0,5 – 0,33 (0,15)

Total 33,7 – 115,2 (48,9) 0,15 – 1,02 (0,45)

is coordinating the International Blue Carbon Scientific

Working Group and International Blue Carbon Policy

Working Group, which provide guidance for needed

research, project implementation and policy priorities.

• Projects are being developed at sites globally to protect

and restore coastal ecosystems for their “blue” carbon

value. Learn more in the Field Work section.

• Research into the sequestration, storage and loss of

carbon from blue carbon systems is ongoing.

Field-based projects are critical to developing blue carbon

as an approach to conserve, restore and manage coastal

ecosystems. Strategically designed and implemented field

projects will demonstrate the viability of blue carbon,

facilitate the development of practical, science-based

methodologies and build local and national capacity to

protect and manage coastal ecosystems and their myriad

ecosystem services in blue carbon-rich countries.

The Blue Carbon Initiative partners, as well as many

other organizations around the world, are working on

conservation science, policy and management of blue

carbon ecosystems globally. Major objectives include

national-level accounting of carbon stocks and emissions

from blue carbon ecosystems, increased management

effectiveness of blue carbon ecosystems within protected

areas, and the development of blue carbon offsets for

tourism activities.

1.4 CONSERVATION INTERNATIONAL BLUE CARBON WORK IN KAIMANA

The overall goal of this project is to demonstrate the

viability of blue carbon financing for the Kaimana MPA

by developing the necessary project documents and

tools to access carbon-based funding for sustainable use

and conservation activities in the areas mangroves and

develop concrete lessons learned for future blue carbon

initiatives across Indonesia and globally. This project was

built on Conservation International’s (CI) established

marine and coastal conservation work in the mangrove-

rich areas of Kaimana, West Papua. It compliments on-

going efforts to provide a sustainable livelihoods program

based on mangrove related fisheries and integrate blue

carbon into policy and management decisions as a

potential long term sustainable funding source for marine

protected area (MPA) management.

CI’s Geospatial Applications team within the Moore Center

for Science generated a multi-date map of mangrove extent

and mangrove deforestation over three time periods for

our project sites in the Kaimana Regency, West Papua. The

product was based on classification of Landsat images from

ca. 2006, ca. 2010 and ca. 2016. During this period 2.47 %

of the area was consistently covered by mangroves (74,393

± 1,518 ha), and mangrove loss of only 0.0003 % of the

area (7.3 ± 0.3 ha), mostly due to urban expansion and

road development.

Table 2. Mangrove extent and deforestation (2006-2016) in Kaimana

Nonmangrove

Mangrove Mangrove change

Total User’saccuracy (%)

Mappedarea (ha)

Error adjusted area (ha)

95% CI of error ad-justed area (ha)

Nonmangrove

0.975283 0.000000 0.000000 0.975283 100.0% 2,995,564.7 2,997,083.6 2,997,083,6 + _ 1,518.2

Mangrove 0.000494 0.024221 0.000000 0.024715 98.0% 75,911.1 74,393.1 74,393.1 + _ 1,518.2

Mangrovechange

0.000000 0.000000 0.000002 0.000003 90.0% 8.1 7,3 7.3 + _ 0.3

Total 0.975777 0.024221 0.000002 1.000000 - 3,071,483.9 3,071,483.9 -

Producer’s accuracy

99.9% 100.0% 100.0% - 99.95%

Nasa Earth Observatory images created by Jesse Allen, using data provided by Chandra Giri, U.S. Geological Survey, acessed online htttp://earthobservatory.nasa.gov/IOTD/view.php?id=47427&src=ve


The number of people living in coastal villages average

of 470 inhabitants per village. The biggest coastal village

population is located in Kaimana’s Kampung Lobo region

with a population of 1005.

2.1.1 Tribes

Native tribes that inhabit coastal Kaimana consist of the

Koiwai tribe, Mariasi tribe and Baham tribe. The Koiwai tribe

occupies Adi Jaya and Namatota villages. The Mariasi tribe

are found from the Maimai village to Macan tutul bay which

includes villages such as; Lobo, Kamaka, and Lumira. The

Baham tribe lives in the Nusaulan village located adjacent

to Fakfak Regency.

New settlers currently coming to live in coastal villages in

Kaimana come from Jayapura, Merauke, Biak, Nabire, Raja

Ampat, and Sorong. And the ones coming from outside

Papua come from Maluku (Seram, Tual, Tanimbar, Kei, Dobo,

and Banda) Sulawesi (Bugis, Makassar, Toraja, Butin, Sangir),

Jawa, Lombok, and Flores.

2.1.2 Religion

The majority of locals in coastal Kaimana practice Islamic

and Christian Protestant religions. The existence of Islam

in this region is due to the Tidore and Ternate sultanate.

Table 4. Kaimana tribe population

Meanwhile Christianity was spread during the Netherlands

occupation in Indonesia through missionary activities. In this

area, Islam spread more in the coastal area while Christianity

is more inland.

2.1.3 Livelihoods

Livelihoods are heavily impacted by the availability of

natural resources, both land and sea. This means that the

top professions are gatherers, farmers, and fisherman.

This is largely due to tradition and that available land gets

passed down from generation to generation. Markets with

high selling point commodities, such as shark fins, sea

cucumber, sea snails, live grouper, and nutmeg, are also

are available. These markets are driven by buyers from the

larger cities (i.e. Fakfak, Kaimana, and Makassar).

Locals living in Adi Jaya and Namatota villages chose

to be fishermen since they live on an island. But due to

increased interaction with newcomers as well as adoption

of new technology, they have established an agriculture

and fisheries seasonal system to increase productivity.

In the high tide season they focus more on agricultural

activities and during low tide season they will do more

fisheries activities, and may act as a model for livelihood

diversification.

2 BLUE CARBON FIELD PROCEDURE

Table 3. Kaimana regency population density

District Population Area coverage (km2) Average village size Population per km2

Buruway 4,748 2,650 449 1.79

Arguni Bay 5,598 5,000 450 1.12

Kaimana 18,892 2,850 495 6.63

Etna Bay 6,485 8,000 485 0.81

(CII and UNIPA, 2006)

(CII and UNIPA, 2006)

Village Households Population Tribes Dominant religion

Adi Jaya 89 311 Koiwai Islam

Namatota 104 485 Koiwai Islam

Maimai 76 515 Mairasi Protestan

Kamaka 42 196 Mairasi Protestan

Lobo 248 1005 Mairasi Protestan

Nusaulan 58 307 Baham Islam

Total 617 2819

2.1 KAIMANA REGENCY BACKGROUND

The following part (2.1) was cited from a report by Paulus Boli (2007),

as a result of cooperation between Conservation International

Indonesia (CII) and Universitas Papua (UNIPA).


2.1.3.1 Agriculture

Before farming became popular, the people of Kaimana

survived largely from gleaning the forest and fields. And

while agriculture has taken off in the region, the practice of

gleaning is still a large source of food for many people. In

many instances, agriculture is used to meet dietary needs

for carbohydrates (i.e., sweet potatoes, and bananas)

while gleaning, hunting, and fishing supplies all other

requirements.

Being a heavily forested location, clearing of land must be

done prior to planting. This is usually carried out by a group,

clan, and/or family members. The location of the planting

area is based on specific criteria: (1) does it have a layer of

thick soil; (2) how far away is it from their home; and (3) is

it somewhat protected from pests such as boar and deer.

Clearing of agricultural land includes cutting down trees

and shrubs but good tree types for manufacturing housing

material and firewood are set aside. The leaves, branches

and other woody stems are left to dry for about a week and

then burned. The ash becomes an organic layer on top of the

soil surface that acts as a fertilizer. Land processing taking

about 3 to 4 weeks, after that the process of planting seeds

or young plants cultivated in a village nursery is started.

The most popular crops are taro, sweet potatoes (betatas),

cassava, corn, bananas, and vegetables. Short term crops

like sweet potatoes are planted around 4 to 6 months before

they can be harvested and must be planted every year.

Banana trees are planted only once and allowed to produce

for as long as the soil can sustain them.

When the soil looses capacity to grow enough food, the

farmer will move on and clear a new area of land. The used

patch of land is left to rest for about 5 years and then the

farmer may come back and re-establish the farm once the

soil has been restored, but by that time the land will usually

require clearing again. The communities in Kampung Maimai

work to not let the soil deplete by implementing crop

rotation using long-term crops that have high economical

value such as, nutmeg and cocoa. Farmers do not use any

artificial fertilizers or pesticides (boars are considered the

biggest pest).

Change of consumption patterns

The unfolding relationship between Kaimana and other areas

in Indonesia brought changes in the pattern of consumption.

Before, local communities main ingredients were sweet

potatoes and bananas, nowadays it has shifted to rice to

follow the majority of the population in the western part

of Indonesia. This change is largely due to a government

program to assist the poor by providing rice rations on a

monthly basis (at Rp. 1,000 per kg, approximately $0.08

USD). This program began to be implemented in 2000 and

continues to present day. Rice rations are made available to

Kaimana families in 30 kg rations every three months and

the average family will consume this in as little as 7-10 days.

After the rations are gone the family must travel to the city

and purchase rice at around Rp. 5,000 per kg. The residents

of villages that have more money will purchase rice, the

families in poorer villages will revert to eating other crops

namely sweet potatoes, banana and sago.

The forest is still full of various birds, reptiles and mammals;

including cockatoos, parrots, snakes, crocodiles, wild pigs,

deer and kangaroos. Locals typically utilize some of these

animal to meet their protein needs or sell them to earn

money. The animals most commonly hunted are deer, wild

boar, and some kinds of birds.

Plantation Crops

The most common types of plantation crops grown by

farmers and plantation companies in Kaimana are coconuts,

cocoa, nutmeg, and cloves. Nutmeg and coconut employ the

most people in Kaimana with cocoa mainly comes from a

single plantation on the island of Adi Jaya.

Coastal communities in Kaimana produce nutmeg as a main

source of household income. Therefore almost all villages

have nutmeg gardens. Local interest in planting nutmeg trees

is also high, based on the consideration that the selling price

of this commodity is quite high (Rp. 7,000 – 10,000 rupiah

per kg). In addition, demand for nutmeg is high enough that

the farmers never outstrip the demand. The interest of the

local population is also influenced by the relatively easy

handling of the nutmeg trees, ranging from planting and

caring for trees up to the harvesting and processing of the

fruit.

Coconut is the second most important plantation crop

after nutmeg. Coconut trees can be found along the beach

throughout Kaimana. Community interest in working with

this crop is mainly due to its low maintenance and coconut

trees are often used as a sign or evidence of land tenure of

a clan or family. The selling price of coconut ranges from Rp.

500 up to Rp.1000 per fruit. However, this crop is really only

feasible for villages near Kaimana city due to the high cost

of transportation. One way to make transporting of coconut

easier is to dry it but this is a difficult since the coconut

needs to be skinned first and separated from the shell, then


Table 5. Crops plantation in Kaimana

the fruit is smoked on the grill until dry. This process takes

2-3 days. Other plantation crops such as cloves, cashew nuts

and coffee are relatively limited.

2.1.3.2 Livestock

Livestock is not a large part of the economy for costal communities

in Kaimana. But of the farmers that do work livestock the main

types are cattle, pigs, goats, and chickens. Most communities

raise chickens, where the average number of chickens owned

by each households is about five. Pigs are not very popular due

to the prominence of the Islamic religion which does not allow

pork to be consumed. Cattle, pigs, and goats also come with the

added strain of providing them with food and finding breeders.

2.1.3.3 Forestry

The forests of Kaimana are largely pristine, both terrestrial and

mangroves. However, in 1999 a policy known as the Kopermas

scheme was put in place that recognized indigenous Papuans

as the rightful owners of their land. And through this scheme

they were allowed to log their forest as long as they applied

for a logging licence. However, often local communities were

exploited by logging companies who would buy the traditional

landowners’ forest rights at a very low price and sell the

timber to international buyers. This scheme was halted in

2009 and the rate of deforestation that occurred sporadically,

mainly in the coastal regions, has declined. Currently, forest

management is done by only a few logging companies and are

Government controlled. Meanwhile, the utilization of forest

products by the local communities are limited to meeting

basic needs such as wood for housing.

The main forest product in Kaimana is timber for housing

(pillars and boards) and other community needs such as

bridges or village piers. Wood processing is done using

community owned chain saws and logging is done mainly

in forests belonging to the community. The types of wood

utilized are kayu besi, matoa wood and linggua wood, and

other wood types (mangrove wood is not often harvested).

Most of the villages have an agreement prohibiting the selling

wood outside the village.

Other forest products include masohi bark, mainly by the

residents of Kampung Kamaka, Maimai and Lobo, for its oil

which is used in perfumes. Revenues earned from the sale of

this bark is quite high and most often sold in the larger cities in

Fakfak and Kaimana. Eaglewood (gaharu) is another product

that is highly sought after for its high retail value but it is very

rare.

A new pressure on forests, in addition to subsidized agricultural

expansion and logging for timber, has emerged in the form

of ‘biofuel’, including palm oil, sugar cane and jatropha

(nettlespurge). Ironically, policies that promote the production

and use of biofuels as an environmentally friendly alternative

to fossil fuels have the effect of increasing greenhouse gas

emissions by encouraging the conversion of natural forests,

either directly or indirectly, to energy producing crops.

2.1.3.4 Fisheries

Fishing is a major component of the local economy and is the

main protein source for many village communities. The type

of fishery implemented is largely related to the location of the

Table 6. Livestock in Kaimana

Crop type Hectarage Households

Coconut 790 1,295

Cocoa 534 740

Cloves 62,5 223

Nutmeg 1,649 1,467

Village Livestock type

Pigs Goats Chickens

Adi Jaya 0 30 178

Namatota 0 100 520

Maimai 0 2 380

Kamaka 0 0 210

Lobo 3 0 1240

Nusaulan 0 174 580


Table 7. Destructive fishing activities in Kaimana

Village Destructive activities

Bomb Cyanide Compressors

Adi Jaya Existed Existed 5 units

Namatota Existed Existed 3 units

Maimai Not existed Not existed 0

Kamaka Not existed Not existed 0

Lobo Not existed Not existed 0

Nusaulan Not existed Existed 0

village in relation to the market, higher value fish are caught in

the villages that are the farthest away to compensate for the

cost of transportation. Sea cucumber, lola and stone fisheries

are found along the intertidal area and are especially utilized

by villages that still practice the culture of sasi (a fisheries

management strategy based on traditional knowledge).

Lobster is mainly fished in the villages of Faur and Keaba.

Other types of catches include: grouper, snapper, shark and

bubara. Grouper, snapper and bubara are captured using

fishing line and nets. Fresh fish are usually sold to a holding

vessel that will visit various villages and transport the fish to

market. Fisherman can sell their fish in the market directly but

only if they live close to the city. Fishing seasons depend on

the weather and the height of the tide. When the sea is calm

fishing can be done for all species mentioned. But when the

tide is high and the seas are more rough fishermen will focus

on sharks for fins, meat, skin, and bone.

Fishing Technique

Fishing methods used in Kaimana vary, including

environmentally friendly methods as well as destructive

methods. Most local fisherman use fishing line and gill nets

to catch fish as well as sharks, they also charter boats for

pelagic fish, use diving equipment primarily to catch lola,

sea cucumber, lobster, batu laga snails and grouper, bombs

to catch reef fish and fish for bait, and potassium cyanide to

drug fish making them easier to catch.

Means of transport used to get to a fishing location include

rowboats to capture near-shore fish and long boats equipped

with an outboard engine for farther distances. For non-

indigenous fishermen, for example from Buton, Makassar and

Maluku, they usually use larger speed boats that are better

equipped giving them an unfair advantage over the locals.

As with other Papuan fishermen, fishermen in Kaimana

still lack the knowledge, skills, and technology to increase

their catch while decreasing fishing effort. Methods remain

very traditional and have not changed much over the

course of several generations. Training of local fishermen is

obtained through interacting with outside fishermen but this

knowledge is not often implemented. For example, methods

of using diving equipment to catch benthic dwelling fish has

been practiced by incoming fishermen from Madura and

South Sulawesi since the 1980s, and was only started to be

followed local communities in 2004.

Destructive fishing

Destructive fishing is seen in the use of bombs, cyanide

(poison), and scuba gear. However, local communities do not

use bombs, this is largely an activity brought in from outside

fisherman, specifically into Adi Jaya and Namatota villages.

The target is usually game fish that live in the reef area to

be sold in the market place and also fish for bait. In general

local fishermen are helpless to stop fish bombing because the

bombers often have fishing boats with larger engines than

the ones belong to the local fishermen and they often will

threaten local fishermen with the bombs if they do not back

away.


From previous work related to this project, trends in the

change of greenness over a fifteen-year time span (2000-

2014) was mapped for the entire Birds Head (Figure 3).

The analysis looked at both the deforestation (or loss of

vegetation) and revegetation. To summarize, red areas are

losing vegetation at a higher rate than the green areas, which

are also losing vegetation but at a slower rate. The black

areas are revegetated at a faster rate than the gray areas.

This ‘revegetation’ may mean two things: cleared forests may have been planted with rapidly-growing oil palm or

other plantations, or degraded forests may be revegetating

with native plants. Our experience indicates it is more likely

to be the former. White areas are where either no significant

change was detected, or where a series of cloud-free images

were not available.

Analysis of Arguni Bay and Kaimana City specifically (Figure

4) show that Kaimana is growing and deforestation (or

denuding of vegetation) is increasing along the periphery of

the town. The circle near the Arguni Bay shows areas that

seem to be revegetating.

Following this initial result, it was important that a more

detailed analysis of the Post-Deforestation Land Use (PDLU)

allocation for areas of mangrove deforestation. While

mangrove deforestation through 2016 is minimal in Kaimana

Regency, it is important to capture the main drivers, which

can be informed by assessing the PDLU allocation. The PDLU

allocation also has carbon implications as not all PDLUs impact

carbon storage similarly.

The area that shows most change is in a high populated area

in the Kaimana district. Sentinel 2 images and historical high

resolution imagery from ESRI ArcGIS online were used to

attempt to identify the land change. Features probably used

for a type of farming (i.e. shrimp farm) were identified in

pre-2006 images adjacent to change detected. Due to image

resolution and cloud cover it was difficult to determine the

driver of change; therefore, field validation is recommended.

Mangrove deforestation for the period ca.2006-ca.2010-

ca.2016 represented only a small proportion of the

initial mangrove area (0.01% of the mangrove present in

2006) in Kaimana Regency. Conversely, based on visual

interpretation of Landsat imagery of forest land in areas

adjacent to mangrove habitat, much deforestation has

occurred and continues with large scale deforestation that

Figure 3. Trends in vegetation “greenness” over a 15-year time span. Circled area is Kaimana. It is important to note that the map accounts for all vegetation types, not just mangroves.

2.2 MANGROVE IN KAIMANA

This part (2.2) was the result of Conservation International

collaboration with Dr. Faiz Rahman (2015) from the University of

Texas Pan America and Conservation International’s Moore Center.


Figure 5. Overlay of high resolutioon pre-2006 image and the mangrove change validation points (shown in red) located near a type of awuatic

farming

Figure 4. Vegetation changes for Arguni Bay and Kaimana City

has occurred in period 2010-2016 in an area North of Kaimana

Regency. Images show patterns characteristic of deforestation,

including logging roads and expansion perpendicular to this

main artery in an area of southern Kaimana Regency. While

no mangrove deforestation was detected in this area, the

prevalence of deforestation in the vicinity may impact the

integrity of the mangrove system or increase pressure on the

mangrove extent.

History has shown that at the national scale, the largest threats

to mangrove ecosystems are brackish water shrimp farm or

tambak development and, at a smaller scale, timber exploitation.

Although Polidoro et al. (2010) suggested that shrimp

aquaculture attributed to 38% of the loss of world’s mangroves,

the actual contribution is far higher in the South East Asia region,

particularly in Indonesia (Wolanski et al., 2000). Other threats

described by Duke et al. (2007), Lee et al. (2014), and McIvor

et al. (2012) include infrastructure development, sea level rise,

agriculture plantations, and natural disasters. Projecting the

future trends for mangrove degradation is challenging because

few data are available, especially regarding timber exploitation,

urban development, and plantations. Therefore, apart from

the estimates of losses to brackish water farming, the impacts

of other activities on mangroves are projected by using proxy

information. The following discussion describes the threats and

how they will shape the future of Indonesia’s mangroves.


2.3 MANGROVE CRAB AND BLUE CARBON IN ARGUNI BAY, KAIMANA

CI has partnered with a local NGO, Fishing and Living,

to assess the potential for a mangrove based fishery in

Arguni Bay and to design a Fisheries Improvement Project

(FIP) strategy. CI and Fishing and Living worked together

to gain support from the Fisheries Department to examine

management and zoning arrangements to ensure that the

strategy would be in full compliance with the existing MPA

management framework. Fishing and Living completed

their report after assessing the level of experience, local

knowledge and potential for developing the mangrove crab

fishery in Arguni Bay. They found that the communities

had a high level of capacity for mangrove crab fishing and

worked with CI to develop a FIP for mangrove mud crab.

Traditionally, women are the primary fishers for crab and

through the FIP about 40 women are being supported by the

Fisheries Department through the contributions of boats.

The crab that the women collect are going into a national

data collection effort known as iFish. Data collected includes

landing weight, size, and sex of each crab. This information

can be used to monitor the health of the fishery as well as

inform management. Groups of women fishers were trained

on national regulations for crab fishing, including minimum

size requirements, sex identification, and techniques for

determining if females are gravid or not (gravid females

must be returned to the mangrove).

However, sustainable fishing practices are only one part of

building a sustainable fishery and supply chain. To ensure

market availability for the crab, CI and Fishing and Living

created an ‘Sustainable Buyers Group’ in Bali consisting of

four restaurants (Pica, Locovore, Cuca, Kudeta) that have

agreed to source their crab from Arguni Bay. One of the

chefs presented his connection to this project at the Ubud

writers festival, which will hopefully increase awareness

and interest in this project. To date several shipments have

been delivered and each shipment shows improvements in

shipping methods. There is now one airline that has agreed

to transport the crab from Arguni Bay to Bali, and the future

plan is to develop a fisher’s co -op in Ambon that would

purchase the crab. Ambon is closer to Arguni Bay which

decreases shipping time (thus improving the chances that

the crab survives transportation) and increases profits for

the local communities.

Figure 6. CI working with Fishing and Living (MDPI) on sustainable fisheries program focusing mudcrabs as the primary commodity.


Figure 7. The cycle of tides and the ‘Rule of Twelfths’ that influence the optimal times to sample vegetation and soils in mangrove ecosystems.

Note: Hours 0 and 12 are the approximate high tides; hour 6 is the approximate low tide. A period of minimal change in water level

accurs for about 2 hours on either side of low tide, creating a sampling window of about 4 hours, begineeing at hour 4 and continuing

through hour 8. Sampling time periods in mangrove are sometimes longer at higher elevations.

2.4 CONSIDERATION FOR CARBON MEASUREMENT IN MANGROVE ECOSYSTEM

Mangroves have many unique features that must be

considered in project design. They often have extremely

high stem densities with abundant prop roots and/or

pneumatophores. Mangroves are frequently dissected by

tidal channels that are difficult to cross, especially at high

tides. These and a number of other hazards limit mobility

and create safety concerns.

Most mangroves are also subject to semidiurnal tidal

cycles and can only be sampled during low tides, limiting

both the timing and duration of the sampling, especially

for components on the forest floor. In the lowest elevation

mangroves, sampling may be limited to low tidal periods

of as little as 3–4 hours (Figure 7). This narrow window

necessitates an efficient sampling protocol.

The ‘Rule of Twelfths’ provides insight into the length of

time available to sample (Figure 7). The water level during

the tidal cycle changes in a predictably nonlinear pattern:

This following part (2.4) was cited from CIFOR working paper by J.

Boone Kauffman and Daniel C. Donato (2012) from the University

of Wisconsin and Oregon State University.


Table 8. Carbon stock analysis for the Kaimana Regency

each project site as well as estimates for the total mangrove

carbon stock for the Kaimana regency are presented in Table

8 and 9.

Determining the carbon stock for the Kaimana mangroves is

important as a means of understanding carbon ecosystem

services potentially available for future financing schemes,

and in helping Indonesia measure and meet greenhouse

gas reduction commitments. According to the Activity 1.1.

only 7.3 ha have been lost in the last ten years; if we take

the average carbon stock (above and below-ground) for

the Kaimana Regency of 723.6 Mg C ha-1 we estimate that

19,386 Mg of CO2 were released as a result of that loss.

Area (ha) Total carbon stock for all Kaimana (Mg C)

Annual sequestration (2.26 Mg C/thn)

(McLeod et al 2011)

Potential Emissions (Mg CO2)

(if 100% ofmangroves are lost)

Entire Kaimana region 74,393 54,091,909 168,128 198,517,305

2.5 BLUE CARBON ASSESSMENTS IN KAIMANAA carbon analysis had already been completed for Arguni

Bay (biomass, litter, and soil) in 2014. Collating carbon stocks

from above- and below-ground tree biomass and soils we

found the mean carbon stocks for all Arguni Bay to be 689

Mg C ha-1, similar to the mean carbon stocks for Indonesia

generally. Below-ground carbon accounted for the majority

(82%) of these stocks, reflecting the peat soils (>25% OM)

of the region. Working closely with CIFOR and UNIPA, the

methods used for sampling the carbon stock of Arguni Bay

were used to sample carbon stocks in Buruway and Etna Bay

as well as carbon stocks for the degraded mangrove areas

around Kaimana. Sample analysis was done in the same lab

and used the same methods for the Arguni Bay samples to

maintain data uniformity. Results for carbon stocks within


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Table 10. Site gps coordinates and geographic region within Arguni Bay, West Papua

2.5.1 Arguni Bay

2.5.1.1 Site descriptionArguni Bay is a large embayment connected to the Arafura

sea by an opening that is approximately 7 km wide. There

are five main rivers and numerous creek system flowing

into the bay, delivering sediments derived from the

steep topography that surround the bay. The mangrove

forests are predominantly fringing forest, no more than

a few hundred metres in depth from the low intertidal

to the highest intertidal mangroves. These forests were

dominated by tall (>30m) Rhizophora sp., Bruguiera sp. and Xylocarpus sp. with many areas of the mangrove

forests also providing habitat for mangrove associate

species such as Mangrove palm (Nypa Fruticans),

mangrove holly (Acanthus ilicifolius) and mangrove fern

(Acrostichum speciosum). Much of the intertidal zone

across Arguni Bay is characterised with an initial steep

bank stepping up from the bay to the lowest intertidal

zone followed by a gradual, inclination up to the highest

intertidal zone where the mangrove forest gradually

transitions into terrestrial rainforest. Many mangrove

forests across Arguni Bay were observed to have a thick

mat of leaf litter cover indicating a habitat that had

accreted above the highest intertidal zone and was no

longer experiencing regular tidal inundation. Across West

Papua most rain falls between January and April, the

‘northwest season’, with the least falling between May

and August, the ‘southest season’. Our sampling was

done in the northwest season in February, 2015.

2.5.1.2 ApproachTen sampling sites, distributed around Arguni Bay, were

chosen for field sampling. The ten sites were chosen to

reflect different habitats of the bay that are differentially

influenced by rivers, distance from marine influences and

vary in forest type. The sites were categorised into regions

based on location within the bay; sites 1 and 2 were in the

Western region (“West”) approximately 70km from the bay

entrance, sites 3 to 5 in the Northern region, about 80km

from the entrance to the bay, sites 6 and 9 in the Central

region (50 km from the entrance) and sites 7, 8 and 11 in

the Southern region of the bay, 40 km from the entrance

(Fig 8 and Table 10). At each site soil carbon was assessed

to 1 m using soil cores collected from the centre of up to

five 20m diameter plots distributed along a transect at

50m intervals. Cores were sampled at 5, 20, 35, 60 and 85

cm depths. A subsample of each core slice was dried and

combusted at 550 C to determine the soil organic matter as

% loss on ignition (LOI). In order to assess the %C in samples

approximately 100 samples were sent to the University

of Hawaii to assess %C. %N, del13C and del13N were also

assessed. Mangrove biomass was estimated from measures

of diameter at breast height (dbh) of trees which were

used to estimate total above- and below-ground C stocks

using allometric equations (Howard et al. 2014). Mangrove

associate biomass was calculated using allometric equations

for Nypa Palm and through mean dried weight per plant

for mangrove holly. Leaf litter C on the soil surface was

calculated through the collection of a subset of samples

from 50 cm2 and the calculation of litter C per gram of wet

litter sample. Carbon within pneumatophore biomass was

calculated through the collection of a random number of

pneumatophores to calculate mean C per pneumatophore

and counts of pneumatophores within a 50 cm2.

Site GPS coordinates Region

PT1 3°3’50.90”S 133°54’37.60”E West

PT2 3°7’25.36”S 133°53’16.97”E West

PT3 2°57’19.40”S 133°51’25.70”E North

PT4 2°54’45.45”S 133°48’33.86”E North

PT5 2°57’3.74”S 133°49’2.72”E North

PT6 3°7’6.30”S 133°48’2.90”E Central

PT7 3°12’57.10”S 133°41’22.40”E South

PT8 3°12’54.86”S 133°39’42.21”E South

PT9 3°6’59.40”S 133°39’29.40”E Central

PT11 3°10’40.43”S 133°42’52.95”E South

This following part (2.5.1) was the result of Conservation

International collaboration with Matthew Hayes and Catherine E.

Lovelock (2015) from the University of Queensland.


Figure 8. Sample site locations in Arguni Bay, West Papua

other species and Excoecaria agallocha the lowest (Table

12). Rhizophora sp. was found to be the dominant species

across Arguni Bay making up 40% of basal area in the

mangrove forests. There was no significant difference in

species basal area between regions (F 9,13 = 1.86, P =

0.15) indicating species basal area was not affected by

geographic distribution (Table 12).

2.5.1.3 Mangrove forest assesmentMangrove stand basal area (m2 ha-1) varied significantly

across regions of Arguni Bay (F 3,29 = 9.08, P < 0.001) with

the largest basal area coverage located in the Central region

and the lowest basal area coverage found in the North region

(Table 11). Mangrove species basal area varied significantly

across Arguni Bay (F 6,13 = 4.93, P < 0.001) with Rhizophora sp. found to have a much higher basal coverage than all

Region Stand basal area (m2 ha-1)

North 57.55

South 150.72

West 229.53

Center 421.09

Table 11. Basal area of mangrove stands across regions of Arguni Bay, West Papua

Mangrove Mean basal area (m2 ha-1)

Relative dominance

Rhizophora sp. 113.7 ± 31.9 40%

Heritiera littoralis 39.1 ± 15.5 14%

Soneratia sp. 21.9 ± na 8%

Xylocarpus sp. 22.4 ± 8.3 8%

Avicennia sp. 21.1 ± 6.6 8%

Bruguiera sp. 57.5 ± 30.2 2%

Excoecaria agallocha 5.5 ± na 2%

Table 12. Basal area and relative dominance of mangrove species across Arguni Bay, West Papua.


2.5.1.4 Vegetation carbon stocksAbove-ground carbon (C) stocks of trees varied significantly

across regions of Arguni Bay, with the largest C stocks found

in the Central region of the bay where the intertidal zone

was dominated by large Rhizophora species and lowest in

the North region where mangrove trees were sparse and the

intertidal zone was dominated by mangrove associate Nypa

palm (F 3,28 = 8.21, P < 0.001; Figure 9a). Carbon stocks for the

root component of the trees also varied significantly between

regions (F 3,28 = 8.05, P < 0.001; Figure 9b) and followed the

same pattern as observed for the above-ground component

where root C stocks were significantly higher in the Central

region and lowest in the North and West regions. Combining

C stocks for above-ground components (including litter fall and

pneumatophores with the mean tree above-ground biomass)

observed in Arguni Bay gives mean biomass C stocks of 101 Mg

C ha-1 for above-ground biomass and 22 Mg C ha-1 for below-

ground biomass. These estimates are comparable to the mean

values reported for Indonesia, where above- and below-ground

biomass averaged 171.3 ± 127.2 Mg C ha-1 and 20.5 ± 15.7 Mg

C ha-1 respectively (Alongi et al. 2015).

2.5.1.5 Soil Carbon StocksSoil carbon stocks are calculated from independent

measures of soil bulk density and carbon concentrations

integrated over a known depth of soil. Below we present

the variation in the underlying bulk density and C

concentrations that comprise carbon stocks in the soils

before presenting the estimated carbon stocks for the

region.

Soil bulk densitySoil bulk density (BD, g cm-3) was found to increase

significantly with depth across the bay (F 4, 143 = 39.18, P <

0.001) and with depth across the different regions of the bay

(F 12, 143 = 4.62, P < 0.001, Fig 10) where bulk density ranged

from as low as 0.26 in the surface soils to as high as 0.46

at a deeper depth of 100 cm. Bulk Density was significantly

higher in the Northern region within the top 30cm of the soil

depth profile than other regions (P < 0.05). At deeper soil

depths (> 50 cm) the Northern and Southern regions had

higher BD’s than either the West or Central regions.

Figure 9. Carbon stocks for above (a) and below (b) ground biomass across the different geographic regions of Arguni Bay, West Papua.

Figure 10. Soil bulk density with depth across of Arguni Bay


Soil carbon concentrationsSoil C stocks have been based on soilt organic matter

measured through loss on ignition (% LOI). In order to predict

C stocks based on soil organic matter a subset of samples

were sent to the University of Hawaii for analysis of soil C

concentrations using a CHN analyser. These samples were

then used to create a predictive model in order to establish

the relationship between LOI and %C for Arguni Bay. We

found a strong relationship between soil organic matter and

soil C concentration of our calibration samples (Figure 11)

indicating a 95% confidence in the predictive model used to

calculate soil C stocks for all the sediment samples collected

in Arguni Bay. This is a less variable relationship between

%C and that estimated by LOI than presented in Kauffman

et. al (2011) which may be due to lower variability in organic

matter contribution throughout the sediment profile and

across geographic distributions and also the very limited

contribution of carbonates in this system.

2.5.1.6 Changes in Carbon Stocks with DepthSoil C concentration differed significantly with depth across

Arguni Bay (F 6, 143 = 3.42, P < 0.001). Soil C concentrations

indicated that many of the soils are peats (>30% dry organic

mass; Joosten and Clarke 2002) with the exception of those

associated with Nypa palm in the northern region of the

bay. The rate of decline in %C with depth was much more

gradual through the soil profile in the Central region than

that observed for Southern and Western regions (P < 0.05),

where soil C concentration declined rapidly below a depth of

50 cm. Overall we found that C concentrations were higher

in the surface layer of soil (< 50 cm) across all regions, whilst

below 50 cm soil C was much more variable, increasing with

depth in the Western regions, declining in the Southern

and Western regions and remaining relatively stable in the

Northern region. Soil C also differed between regions (F 3,

143 = 112.61, P < 0.001; Figure 12) with soil C being lowest in the Northern region.

Figure 11. Showing the relationship between soil C concentration and soil organic matter of a subset of calibration samples from Arguni Bay, West Papua..

Figure 12. Changes in soil C with depth across the different geographic regions of Arguni Bay, West Papua


Carbon densityCarbon density (mg cm-3) is the product of soil bulk density

and carbon concentration. Across Arguni Bay, there was no

significant change in soil C density with depth across the

research area (F 4,143, = 2.02, P = 0.09) with a mean C density

of 0.06 across all sediment depth profiles. Across regions,

C density also remained relatively constant throughout

the soil depth profile with little change from the sediment

surface down to 100 cm depth. Soil C density was lower

across all depth profiles in the North region of the bay than

the South, West or Central regions although the difference

in C density with depth between regions was not significant

(F 12,143 = 1.07, P = 0.39, Figure 13).

Figure 13. Changes in C density with depth across geographic regions of Arguni Bay

Figure 14. Soil C stocks (Mg C ha-1) across regions of Arguni Bay, West Papua

Soil carbon stocksSoil carbon stocks to a depth of 1m varied significantly

across regions of Arguni Bay (F 3,33 = 16.29, P < 0.001) ranging

from as low as 375 ± 93 Mg C ha-1 in the Northern region of

the bay where the bay is shallower and the soil more silty,

up to as high as 641 ± 59 Mg C ha-1 in the Western region of

the bay where the soil was highly organic with visibly higher

organic material observed in the collected sediment samples

(Fig. 14 and Table 13). Mean soil C stocks were 568 Mg C ha-

1, comparable to those calculated for all of Indonesia where

soil C stocks to a depth of 1m have been estimated at 773.8

± 388.4 Mg C ha-1 (Alongi et al. 2015).

Table 13. Carbon stocks pool across regions of Arguni Bay

Bay Region West North Central South

Sediment

< 1m depth 642 376 628 628

Live trees

Above ground 104 31 202 63

Roots 23 7 43 14

Associate mangroves 2 1 1 1

Pneumatophores 0.03 0.14 0.03 0.03

Surface litter 0.02 0.01 0.03 0.01

Total C stocks 771.05 415.15 874.06 696.04

CO2e of the ecosystem 2829.75 1523.6 3207.8 2554.47


2.5.1.7 DiscussionCollating C stocks from above- and below-ground tree

biomass and soils we found the mean C stocks for all

of Arguni Bay is 689 Mg C ha-1. Below-ground C stocks

accounted for the majority (82%) of these stocks, reflecting

the peat soils (>25% OM) of the region that are likely the

result of a high rate of autochthonous production and slow

decomposition of organic matter.

The highest C stocks were located in the Central region

of Arguni Bay (874 Mg C ha-1) whilst the lowest C stocks

were observed in the Northern region (415 Mg C ha-1),

highlighting a significant variability in C stocks across

Arguni Bay. The relatively lower C stocks in the northern

region and low C concentrations within the soils are

likely related to abundance of Nypa which may have low

allocation of biomass to roots. Very low salinities in the

northern regions of Arguni Bay as a result of reduced tidal

influence and a high precipitation rate may limit mangrove

development (Krauss and Ball, 2013) and enhance rates

of decomposition (ref), but prior land-use change (e.g.

clearing of the woody vegetation) may also have occurred.

Additionally, high sediment input to the northern regions

of the bay from terrestrial sediment runoff in conjunction

with low autochthonous production would also significantly

reduce soil C stocks in the top m of soil in this system, but

could result in deep sediment deposits.

The pattern of C down-core indicated that in the south,

closest to the ocean, deposits within the soils are

consistently C rich (approximately 35% C) while those in

the west and centre decline in %C with depth. Variation

in C concentrations down core can be driven by a number

of factors such as: 1. Decomposition rate, which may be

variable across the bay as a result of salinity, nutrient

availability, elevation or hydrology, 2. Sea-level history and

changes in forest structure over time, such as a terrestrial

forest transitioning to a mangrove forest with increasing

sea levels; and 3. Sedimentation rates, whereby increased

sedimentation within the bay may lead to the shallowing

of the water column such that mangroves can establish

on newly exposed sediments and start to prograde in a

seaward direction

Above-ground C was considerably lower in the southern

region mangroves than similar mangrove forests in the

central region of Arguni Bay. This may be due to a lower

nutrient availability in the southern region of the bay

which has reduced riverine inputs, which can result in a

greater allocation to the root systems to increase nutrient

acquisition, which may lead to a lower stature forest

but high soil C stocks. Characterization of environmental

gradients in Arguni Bay (e.g. nutrients, salinity, tidal

influence) would assist in understanding the patterns in

vegetation and soil C observed.

2.5.2 Buruway, Etna Bay & Kaimana City2.5.2.1 Methodology Study sitesThe study was conducted in Kaimana Regency, West Papua

Province (Figure 15), represented the most remained

undisturbed mangrove forests in Indonesia. We established

a total of 20 transects, with 9 transects in Buruway District,

8 transects in Etna District and 3 transects in Kaimana City.

Undisturbed mangrove forests in Buruway are characterized

tall mangroves and moderate dense canopy cover.

Most of sampling sites are located in fringe and riverine

hydrogeomorphic settings. Kaimana City was the only

degraded site assessed for C-stocks in this project. A riverine

dominated mangrove forests have been cleared over past

few years ago and converted into other land uses such as

fishponds and settlements. In Kaimana City, we developed

two transects in fishponds, while an additional transect was

located in small-scale cleared mangroves. Field assessments

were conducted in two times, September and November

2016.

Sampling designWe assessed all mangrove ecosystem C stock compartments

including above-ground tree biomass, below-ground

root biomass, woody debris, and soil C. We adopted a

globally applied protocol for mangrove ecosystem C stocks

assessment by Kauffman and Donato (2012). The protocol

uses transect-based assessment lied perpendicular to the

coastline or tidal creek ecotones, with 6 of circular plots

replication therein (Fig. 16). In this project, we modified

the plot radius and transect length to become 10 m and

250 m respectively in order to accommodate the larger

tree diameters that dominated this forest type, and avoid

overestimation of forest structure and biomass carbon

(Hayes and Lovelock, 2015). All carbon pool assessments and

sample collections were conducted consistently throughout

all transects within the three study sites (see Table 14).


Figure 15. Map of sampling location in Buruway, Kaimana City and Etna

Figure 16. Schematic of original standardized plot layout for mangrove C-stock sampling adopted from Kauffman and Donato (2012).


Forest structure, above and below-ground biomass carbon

pools

We measured tree diameters at breast height (DBH) or at 130

cm above the forest floor or 30 cm above the highest prop

root for Rhizophora spp. throughout the entire sampling plot

(Kauffman and Donato, 2012). Tree DBHs were measured

inside three different plots following DBH classes, 40 x 250

m2 (A= 1 ha) square plot for big trees with DBH>50cm, 10m

radius circular plot for trees with DBH between 5–50cm, and

2m radius circular nested-plot for mangrove saplings and

seedlings with BDH<5 cm. Standing dead tree status was

documented following the available dead tree definition by

Kauffman and Donato (2012) (see Figure 17).

We estimated above-ground tree and below-ground root

biomass (kg) from tree DBH data by using general allometric

equations provided by Komiyama (2008). We multiplied

biomass (kg) by commonly used C content factors of 0.47 and

0.39 for above-ground trees and below-ground roots biomass,

respectively (Kauffman and Donato, 2012). The total biomass

C was divided by sampling area depending plot, sub-plot and

nested plot sizes in order to get biomass C stock (Mg C ha-1).

We described vegetation structures by their properties

including species relative frequency, basal area and tree

density following common procedures proposed by (Gross et

al., 2013). We calculated species relative frequency from the

number of trees and seedlings encountered for each species

relative to the total number of trees in the surveyed area.

We calculated stand basal area (m2 ha-1) by summing basal

area for all trees across the surveyed area and dividing by

the area. We estimated tree density (tree ha-1) by counting

tree quantities across the surveyed area and dividing by the

area.

Sampling site and replication strategy Field data measured and recorded in the field

• Buruway District (8 transects of undisturbed mangroves)

General site condition and descriptionGeographical coordinate and elevation

• Etna District (9 transects of undisturbed mangroves) Mangrove types (fringe or riverine mangroves)Transect direction

• Kaimana City (3 transects of degraded mangroves) Tree diameter (DBH)

• Total 20 transects Tree species name

Number of woody debris (for fine, small, medium and large classes)

Large class woody debris diameter (rotten and sound)

Soil and organic soil depth

Soil pH and salinity

Soil wet weight

Table 14. Summary of data and sample collection for mangrove C-stock assessment

Figure 17. Standing dead tree status illustration (1. Status 1 trees are recently dead and maintain many smaller branches and twigs; 2. Status 2 trees have lost small branches and twigs, and a portion of large branches; 3. Decay status 3 applies to standing ‘snags’, where most branches have

been lost and only the main stem remains. The main stem is often broken). Picture and definition are adopted from Kauffman and Donato (2012).

Woody debris carbon poolWe measured all downed dead woody debris including

stem, branch and prop root debris lying on the forest floor

using planar intercept technique (Kauffman and Donato,

2012). Two diagonal lines transect were established and

intersected in the midpoint of each circular plot. We

classified downed deadwood into four classes based on

their diameter (D) sizes: fine (D<0.6cm), small (0.6cm<D<2.5

cm), medium (2.5cm<D<7.5 cm), and large sound or rotten

class (D>7.5cm). The DBH for large sound and rotten woody

debris classes were measured and recorded, while all fine,

small and medium classes were only counted following

systematic measurement sections as described in Figure 19.

We adopted Murdiyarso et al. (2010) for quadratic mean

diameter (cm), specific gravity (g cm-3) and C content (%)

information of woody debris in the mangrove ecosystems.


Soil carbon poolWe collected soil samples from three-center point of circular

plot using a stainless steel Russian peat soil auger. A 5 cm

thick of soil samples were collected following consistent

depth interval mid-point horizons of 5–15, 15–30, 30–50,

50–100. Organic soil depths varied depending on mangrove

settings and degradation degrees. In total, we have collected

457 soil samples from all thee study sites. We also measured

other physical and chemical parameters of mangrove forest

soils, including pore water pH and salinity using portable YSI

EcoSense pH100 and EC300 (YSI, Xylem Inc. Ohio USA).

We processed all soil samples by drying them at 60o C

until constant weight was reached. Bulk density was then

determined for each sample by dividing the dried weight

with given soil auger volume. Samples are then grounded

using a mortar and pestle and passed through a 0.5

mm sieve to remove large roots and inorganic debris. A

carbonate removal treatment was conducted by using

acidification technique in order to quantify the portion of

inorganic carbon of the sample (Howard et al. 2014). A loss

on ignition (LOI) technique was used in order to quantify

the amount of soil organic matter (SOM) for all collected

soil samples. At the same time, about 150 subset samples

were analyzed for total organic carbon (%C) by using dry

combustion method. We corrected the final soil organic

carbon by subtracting SOM and %C with inorganic carbon

and organic carbon fractions. The acidification and dry

combustion analyses were performed at Soil Biotechnology

Lab, Bogor Agricultural University, while LOI analysis was

conducted in BPOL Soil laboratory, Perancak, Bali. Soil C

stock (MgC ha-1) is the final product of bulk density (g cm-

3) x C content (%) x total soil organic depth intervals (cm).

Other soil properties such as C density (mg C cm-3) were

determined in order to provide further specific information

of sediment characteristics.

Figure 18. Field assessment of C stocks in the Kaimana mangrove ecosystems: (a) DBH measurement, (b) soil sampling, (c) woody debris diameter measurement, and (d) pH and salinity measurement.


most diverse vegetation species with 30 species compare to

other two sites with only 16 and 12 species found in Etna

and Kaimana City, respectively. Though the total numbers

of recorded species among sites were different, the

species composition and dominance were relatively similar

across sites (Table 16). Rhizophora apiculata, Bruguiera gymnorrhiza, and Rhizophora mucronata were among

the most essential species—top three highest relative

density, frequency, and dominance—in Buruway and Etna

natural mangrove ecosystems. In contrast, we found high

domination of Rhizophora genus, and did not find any single

of Bruguiera spp. trees in degraded mangrove locations

of Kaimana City. Overall, we encountered more diverse

species composition—dominated by typically Southeast

Asian mangrove genera of Rhizophora and Bruguiera—in

natural undisturbed mangrove forests of Buruway and Etna

compare to the disturbed site in Kaimana City.

Statistical AnalysisThe variation of soil bulk density, %SOM, %C, and C density

for all locations and soil depths were analyzed using Two

Way-Analysis of Variance (ANOVA). We applied a Shapiro–

Wilk test of normality prior ANOVA analysis and a logarithmic

normal data transformation applied if the data were not

normally distributed. All statistical analyses were performed

using IBM SPSS Statistic Version 23 (IBM Corp, New York,

USA 2015).

2.5.2.2 ResultsForest structure and tree species characteristicsMangrove forest condition in Kaimana was generally

undisturbed, characterized by tall canopy, and dominated

by big trees, especially in Buruway and Etna assessment

sites (Figure 20). Table 15 summarizes encountered species

diversity in all three sites. We observed total of 37 different

species, with 22, 2 and 13 true mangrove trees, shrubs and

non-mangrove vegetation, respectively. Buruway site has the

Figure 20. Mangroves stand and canopy condition in study sites, Buruway (left), Kaimana City (center), and Etna (right)

Figure 19. The description of transect measurement and size for woody debris sampling


Table 15. List of species composition and vegetation type throughout all sites in Kaimana Regency, West Papua.

No Species name Vegetation type Buruway Etna Kaimana City1 Acrostichum aureum Shrub √2 Avicennia alba True species √ √ √3 Avicennia eucalyptifolia True species √4 Bruguiera cylindrica True species √5 Bruguiera gymnorrhiza True species √ √ √6 Bruguiera parviflora True species √ √7 Bruguiera sexangula True species √8 Calophyllum inophyllum Other species √9 Camptostemon schultzii True species √

10 Ceriops decandra True species √ √11 Ceriops tagal True species √ √ √12 Decaspermum fructicosum Other species √13 Deplancea tetraphylla Other species √14 Diospyros sp. Other species √ √15 Dolichandrone spathacea True species √16 Excoecaria agallocha True species √17 Finlaysonia maritima Shrub √18 Garcinia sp. Other species √19 Harpulia sp. Other species √20 Heritiera littoralis True species √ √ √21 Hibiscus tiliaceus Other species √22 Inocarpus fagiferus Other species √23 Intsia bijuga Other species √24 Lumnitzera littorea True species √25 Nypa fruticans True species √26 Osbornea oktodonta True species √27 Planconella sp. Other species √28 Pongamia pinnata Other species √29 Rapanea sp. Other species √30 Rhizophora apiculata True species √ √ √31 Rhizophora mucronata True species √ √ √32 Rhizophora stylosa True species √33 Schiphiphora hydrophyllacea True species √34 Sonneratia alba True species √ √ √35 Tristaniopsis sp. Other species √36 Xylocarpus granatum True species √ √ √37 Xylocarpus moluccensis True species √ √ √

Grand total 30 16 12

The summary of forest structure such as basal area, tree

density and mean tree diameter, and site characteristic such

as organic soil depth, porewater pH and salinity for each

assessed transect is described in Table 17.

Forest structure and study site characteristic were different

throughout site assessments. Etna site has mean basal area

coverage of 27.59±7.20 m2ha-1, which was slightly larger

than Buruway (23.88±6.28 m2ha-1), and significantly larger


Table 16. Important value index (Iv) of mangrove tree species across sampling sites in Kaimana Regency, West Papua.

Species name Relative density (%)

Relative frequency (%)

Relative dominance (%)

Iv

Rhizophora apiculata 35.57 35.57 48.80 119.95

Bruguiera gymnorrhiza 23.06 23.06 23.37 69.48

Rhizophora mucronata 9.62 9.62 12.09 31.33

Avicennia eucalyptifolia 4.87 4.87 0.65 10.40

Sonneratia alba 3.43 3.43 3.03 9.88

Xylocarpus moluccensis 3.56 3.56 2.58 9.69

Others 19.89 19.89 9.48 49.27

Grand total Buruway 100.00 100.00 100.00 300.00




Sonneratia alba 3.29 3.29 1.36 7.93

Ceriops tagal 2.36 2.36 0.93 5.65

Bruguiera parviflora 2.26 2.26 0.47 4.98

Others 2.67 2.67 1.08 6.42

Grand total Etna 100.00 100.00 100.00 300.00



Xylocarpus moluccensis 6.06 6.06 12.57 24.69

Schiphiphora hydrophyllacea 10.61 10.61 1.52 22.73

Sonneratia alba 6.06 6.06 4.22 16.34


Xylocarpus granatum 4.55 4.55 1.92 11.01

Grand total Kaimana City 100.00 100.00 100.00 300.00

C stocks was obtained in Etna with 674±116 MgC ha-1 and

Buruway as much as 637±201 MgC ha-1, while Kaimana City

degraded mangroves stored lower C stocks with 286±211

MgC ha-1, respectively (p<0.001). Overall, soil C pool

contributed the largest portion (58%) of total ecosystems C

stocks followed by total biomass and woody debris carbon

pools with 41% and 2%, respectively. There was no different

of total vegetation C throughout natural mangrove forest

sites of Buruway and Etna. However, we obtained more than

five times lower (p<0.001) of vegetation C stocks in Kaimana

City compare to natural mangrove sites. The ratio between

below-ground root and above-ground tree biomass carbon

was approximately 28% to 32% suggesting that more than

two-third biomass carbon were stored in above-ground

standing trees. The mean of C stocks stored in top 100 cm

below-ground soil was significantly different across sites, with

the highest soil C found in Etna (383±109 MgC ha-1) followed

by Buruway (345±148 MgC ha-1) and Kaimana City (239±213

MgC ha-1) (p<0.001).

than Kaimana City (2.67±1.48 m2ha-1). Similar trends were

also observed for stand density with 639±111, 590±119,

and 175±37 mean of trees per hectare in Etna, Buruway and

Kaimana City, respectively. We encountered more big trees

domination in Buruway than two other sampling sites—

described by mean DBH of 27.49±4.69 cm.

The mean of organic soil depth in natural undisturbed

mangroves was twice as deep compared to the degraded

site in Kaimana City. There was no significant difference of

porewater pH across sites, which ranged between 5.2 – 8.1.

The mean of salinity in Etna site was the highest (24.0±4.2

ppt) compare to Buruway and Kaimana City with only

14.3±5.2 and 16.0±9.0 ppt, respectively.

Ecosystem C StocksThe mean of C-stocks for all assessed pools such as above-

ground tree biomass and woody debris, and below-ground

root biomass and soil is presented in Figure 21 and 22,

respectively. At the ecosystem level, the highest mangrove


Transect name Basal area(m2 ha-1)

Tree density(pohon ha-1)

Mean DBH (cm)

Organic soil depth

organik (cm)

pH Salinity (ppt)

BF-1 16,44 414 33,42 97 7,7 17,0

BF-2 29,88 713 29,15 78 6,6 13,5

BF-3 12.97 494 28.52 153 7.2 10.5

BF-4 25.95 685 20.43 110 6.1 23.8

BR-1 21.36 661 25.6 115 8.1 8.0

BR-2 28.70 701 21.9 244 - -

BR-3 27.80 594 27.9 218 6.5 11.4

BR-4 27.91 456 33.0 233 6.8 15.7

Grand mean Buruway 23.88±6.28 590±119 27.49±4.69 156±66 7±0.7 14.3±5.2

EF-1 29.68 674 19.10 293 6.1 27.3

EF-2 32.11 701 17.90 190 5.2 15.1

EF-3 33.36 669 23.75 300 6.9 23.0

EF-4 21.73 565 18.55 192 6.6 26.4

EF-5 41.21 579 19.66 175 5.6 26.1

ER-1 24.28 594 19.04 260 6.5 28.6

ER-2 18.52 425 23.29 196 6.1 22.6

ER-3 21.14 788 20.67 254 - -

ER-4 26.27 752 13.06 186 6.1 22.9

Grand mean Etna 27.59±7.20 639±111 19.45±3.14 227±49 6.1±0.5 24.0±4.2

KK-1 4.09 207 18.38 102 6.7 11.0

KK-2 1.14 135 14.77 53 6.2 10.5

KK-3 2.79 183 7.88 85 6.9 26.4

Grand mean Kaimana City

2.67±1.48 175±37 13.68±5.33 80±25 6.6±0.4 16.0±9.0

p-value* 0.001 0.001 0.001 0.002 0.043 0.01

Table 17. The summary of forest structure, site condition and organic soil depth

*Note: p-value indicates significance different of forest structure and site characteristic among three assessed sites resulted from Analysis of Varians.

Figure 21. The mean of vegetation C stocks including above-ground bio-mass, below-ground biomass and woody debris throughout assessed sites.

Error bars denote standard deviation of C stocks for each C pool

Figure 22. The mean of top 100 cm soil C stocks across assessed sites. Error bars denote standard deviation of C stocks for each soil layer


Soil propertiesFigure 23 summaries soil property averages and variation

toward depth throughout assessed sites. Overall, we

observed significant different value across soil depth

only for bulk density while SOM and %C were differed

significantly toward three sampled locations.

We found that bulk density did not differ significantly

across assessed sites (p=0.066), but varied towards depth

with deeper soil layer has higher bulk density (p=0.001).

The lowest and largest bulk density were found in

Buruway with 0.44±0.04 and 0.70±0.03 g cm-3 at top 15

cm and 50-100 cm soil layers, respectively. There was no

statistical significant interaction between sampling sites

and soil depths toward bulk density variation (p=0.243).

We observed similar trend of SOM and %C, and obtained

significant different of SOM and %C values throughout

assessed sites. The greatest mean of %C was obtained

in Buruway with 8.59±0.39%, followed by Kaimana City

and Etna with 6.87±0.69% and 6.67±0.07%, respectively

(p<0.001). Moreover, we did not observed SOM and %C

significant variation toward depths. There was statistical

significant interaction between sampling sites and soil

depths on both SOM (p=0.001) and %C (p=0.009). We

obtained strong interaction between sampling sites and soil

depths on C density (p=0.001), however these properties

did not vary toward both factors.

Figure 23. Soil properties across assessed sites: (A) bulk density, (B) SOM, (C) %C, (D) C density. Error bars denote standard error of soil properties for each depth


DiscussionThis project has successfully conducted field C stock

assessments in three study sites in Kaimana mangrove

ecosystems, namely Buruway, Etna and Kaimana City.

Totaling C stocks from biomass, woody debris and soil

carbon we calculated the mean C stocks from all sites is

601±210 MgC ha-1. Similar with previous findings from

another site within Kaimana region (Hayes and Lovelock

2015), more than 58% of total ecosystem C stocks are

stored in organic-rich (SOM>25%) below-ground soils. Our

assessment findings are comparable with recent C stocks

quantification average from Indonesian natural mangrove

forests (Murdiyarso et al., 2015), suggesting that West

Papuan mangroves are among the most C-rich remaining

ecosystems in Indonesia.

The variation of ecosystem C stocks across three assessed

sites was high, with larger C stocks were found in Etna

and Buruway natural mangrove forests respectively

(674±116 and 637±201 MgC ha-1), while lowest C stocks

were located in degraded mangrove habitat of Kaimana

City with 286±211 MgC ha-1. These variations indicate that

the disturbance regimes affect lowering C storage capacity

significantly. The significant thickness of the organic soil

layer and high concentration of soil SOM are the major

factors for large amount of C stocks in Etna. Deep organic

soil layer also indicates that constant and rapid organic

matter have been accumulated in below-ground soil for

long periods (Breithaupt et al., 2012). We also obtained

exceptionally high values of SOM, particularly in Etna

where the mean of SOM was more than 60%—suggesting

that a major portion of soils are peat (McKee and Faulkner,

2000) (Fig. 24). These conditions are supported by natural

undisturbed mangrove forests with dense canopy coverage

and tall trees (>20 m height), that are potential for below-

ground soil C inputs. Our findings reflect that C stocks in

mangrove ecosystems are highly variation spatially due to

the changing vegetation structure and site characteristic

driven by ecosystem degradation.

We discovered significant lower of biomass C stock in

Kaimana City due to mangrove clearing activities occurred

in our assessment plots several years ago. In addition, the

numbers of vegetation species in these degraded mangroves

are significantly lower than natural forests control. Though

the baseline C stocks information must be obtained before

degradation occurred or from natural ecosystems at the

same site location, by using nearby sampling locations

as study control site, these findings imply that mangrove

clearing activities are directly lowering biomass C stocks

with may also prevent C accumulation into the system, and

reduce original species composition substantially.

Our findings on natural mangrove C stocks are comparable

with other studies in the West Papua region (Murdiyarso

et al., 2015; Aslan et al., 2016). West Papuan mangroves

are among the last remaining undisturbed ecosystems and

largest C density in Southeast Asia. However, emerging

ecosystem degradation drivers in this study region such as

aquaculture and settlement expansion could affect forest

structure, species composition and C storage capacity

substantially.

Figure 24. Field documentation of sampled mangrove soils in Buruway (left), Etna (center) and Kaimana City (right)


The government plays an important role in

mainstreaming blue carbon in Indonesia,

considering that it involves different government

institutions and various stakeholders. Integrated policies

and coordinated institutional arrangements will create

blue carbon governance that benefits the people and

contributes positively to the environment.

In global context, Indonesia supports the UNFCCC (United

Nations Framework Convention on Climate Change), not

only as part of its global responsibility, but also because

of a realization that as an archipelagic state, Indonesia

is particularly vulnerable to impacts of climate change.

Furthermore, Indonesia is also one of the top contributors

to carbon emissions from forest land use change, forest

fire, industry, transportation, etc. The government’s formal

support for the global treaty takes for as Law No. 6 of 1994 on

the Ratification of the United Nations Framework Convention

on Climate Change. This law confirms Indonesia’s active

participation alongside other members of international

community in preventing rising atmospheric concentrations

of greenhouse gases.

3.1 NATIONAL TARGET FOR NDCThe UNFCCC is an international treaty adopted in the

1992 Earth Summit in Rio de Janeiro, Brazil. It entered into

force in 1994 after a sufficient number of countries had

ratified it. In general, the UNFCCC’s objective is to stabilize

greenhouse gas concentrations in the atmosphere at

a level that would prevent dangerous anthropogenic

interference with the climate system.

The signatories to the UNFCCC meet in regular meetings

known as Conferences of the Parties (COP) to discuss

issues related to a global effort to address climate

change. The third session of the COP (COP3) in 1997 in

Kyoto, Japan adopted the Kyoto Protocol, to which the

parties agree to lower their greenhouse gas emissions

to 5% below the 1990 level in the period of 2008-2012.

However, compared to the emission levels that would

be expected by 2010 without the Kyoto Protocol, this

limitation represents a 29% cut.

The Kyoto Protocol is agreed based on the principle of

common but differentiated responsibilities, which means

that the world’s countries have a common responsibility

but at differentiated portions. In this case, developed

countries should take the lead in reducing greenhouse

gas emissions on the basis that they are historically

responsible for producing greenhouse gases since

the industrialization period. Meanwhile, developing

countries have no obligation to reduce their greenhouse

gas emissions and instead are entitled to support from

developed countries to lower their greenhouse gas

emissions voluntarily. Agreed mechanisms include

Joint Implementation, Emissions Trading, and Clean

Development Mechanism.

Developed countries are called Annex-1 countries,

while developing countries are non-Annex 1 countries.

Indonesia ratified the Kyoto Protocol under Law No.

17 of 2004 on the Ratification of the Kyoto Protocol to

The United Nations Framework Convention on Climate

Change. As a developing (non-Annex 1) country, Indonesia

has no-binding target for emission reduction based on

the Kyoto Protocol.

Further to the COP13 in Bali, which adopted the Bali

Action Plan, and the COP16 in Cancun, Mexico, the

Government of Indonesia has pledged to reduce

greenhouse gas emissions by 26% on its own efforts and

41% with international support against the business as

usual (BAU) scenario by 2020. The target is included in

the Presidential Regulation No. 61 of 2011 (Presidential

Regulation 61/2011) on the Action Plan for Greenhouse

Gas Emission reduction (Rencana Aksi Nasional Penurunan Emisi Gas Rumah Kaca/RAN GRK).

According to the Presidential Regulation 61/2011, RAN GRK

is a work plan for implementing activities that directly and

indirectly reduce greenhouse gas emissions consistent with

the national development targets. The core activities under

the greenhouse gas emission reduction target (26% & 41%)

are divided into five sectors (Appendix I), i.e. agriculture,

forestry and peatland, energy and transportation, industry,

and waste management. In addition to the core sectors,

the regulation proposes other supporting activities

(Appendix II) assigned to different ministries/institutions,

i.e. Meteorological, Climatological, and Geophysical Agency

(Badan Meteorologi, Klimatologi, dan Geofisika/BMKG);

Ministry of Environment; Ministry of Marine Affairs and

Fisheries; and cross-sector collaboration. No target of

emission reduction is set for the supporting activities.

3 BLUE CARBON RELATED POLICIES AND REGULATIONS IN INDONESIA


Blue carbon activities fall under the forestry and peatland

core sectors as ‘forest and land rehabilitation and forest

reclamation in priority watersheds’ action plan, with

activities/objectives that include rehabilitating 40,000

ha of mangrove forest/coastal forest. Blue carbon is

also included in other supporting activities (Appendix II)

undertaken by the Ministry of Marine Affairs and Fisheries

as two action plans: i) ocean carbon research in Indonesia

with 5 packages of ocean research; and ii) rehabilitation

of coastal ecosystems (mangroves, coastal vegetations,

seagrasses, coral reefs) in a 300,000 ha coastal area.

As the Kyoto Protocol soon expires, a new agreement

on the target of emission reduction called the Paris

Agreement was adopted in the COP21 in Paris, France in

2015. It aims to keep a global average temperature rise

well below 2°C above pre-industrial levels and to pursue

efforts to limit the temperature increase even further to

1.5°C above pre-industrial levels.

In contrast to the Kyoto Protocol, which obligates

no developing country to lower its greenhouse gas

emissions, the Paris Agreement mandates all countries

to make Nationally Determined Contributions (NDC).

Each reduction target should go beyond previously set

target for each period, and developing countries need

international support to increase such ambition.

Indonesia ratified the Paris Agreement under Law No.

16 of 2016 on the Ratification of the Paris Agreement to

the United Nations Framework Convention on Climate

Change. With this law, Indonesia is recorded as the 89th

country to have ratified the Paris Agreement. In addition,

Indonesia is one of the 95 countries that have submitted

their NDC to the UNFCCC Secretariat.

The NDC document states that post-2020, Indonesia

envisions a progression beyond its existing commitment

(26% on its own efforts and 41% with international

support). In the first period (first NDC), Indonesia’s NDC

target is to reduce emissions by 29% on its own efforts

(unconditional) and 41% with international support

(conditional) against the business as usual (BAU) scenario

by 2030. The BAU scenario is projected to be 2,869 GtCO2e

in 2030. Indonesia’s NDC commitment for subsequent

periods will be determined based on performance

assessment and should reflect improvement over the

next periods.

In terms of adaptation, Indonesia will facilitate smooth

transition towards implementation of NDC under the Paris

Agreement post-2020. The following pre-2020 policies and

actions will lay a strong foundation for adaptation actions

from 2020 onwards:

Pre-condition:

• Development of nationwide climate vulnerability index

data information system, built on the existing system

known as SIDIK (Sistem Informasi Data dan Informasi Kerentanan/ Vulnerability Index Data Information

System), which allows public access to the website at

http://ditjenppi.menlhk.go.id.

• Regulation of the Minister of Environment and Forestry

No. P.33/2016 on the Guidelines for the Development

of National Action Plan for Climate Change Adaptation

(Rencana Aksi Nasional Adaptasi Perubahan Iklim/RAN-

API), which allows local governments to formulate their

own sub-national adaptation action plan.

• Enhancement of existing RAN-API, which has been

formulated in 2014.

(Source: Indonesia’s First NDC Document 2016)

Table 18. Projected BAU and greenhouse gas emission reduction from each sector category

*Including fugitive **Including peat fireNotes: CM1 = Counter Measure 1 (unconditional mitigation scenario)CM2 = Counter Measure 2 (conditional mitigation scenario)


Environment and Socio-economic area:

• Law No. 37/2014 on Soil and Water Conservation, which

leads to sustainable agriculture and land use. The law

guides stakeholders in conserving lands and increasing

productivity towards conservation agricultural approach.

• Governmental Regulation No. 37/2012 on Watershed

Management, which leads to enhanced watershed

carrying capacity. The regulation provides guideline to

identify watersheds that need to be protected, restored,

and rehabilitated.

• Community-based forest management will enhance

community income and at the same time reduce

pressure on primary forests that leads to deforestation

and forest degradation.

• Enhance role of ProKlim (joint climate change adaptation

and mitigation) as a bottom-up approach in village-

level climate resilience program. ProKlim will enable

to account for its contribution to the achievement of

greenhouse gas emission reduction both pre- and post-

2020.

3.2 BLUE CARBON ECOSYSTEM CONTRIBUTIONThe NDC target is divided into five sectors, i.e. forestry

(17.2%), energy (11%), agriculture (0.32%), industry (0.10%),

and waste (0.38%). Blue carbon ecosystems, especially

mangroves, have the potential to contribute to achieving

the NDC target through the forestry sector. Meanwhile,

contributions from other blue carbon ecosystems, i.e.

seagrass meadows and tidal marshes, greenhouse gas

emission reduction are harder to account for since they are

not included in the five designated sectors.

Indonesia is a country with the largest mangrove ecosystems

in the world, covering an extensive area of more than 31

million hectares, containing 23% of the world’s mangroves.

Australia is the second largest, with an area of less than 1

million hectares, containing 7% of the world’s mangroves.

The world’s potential carbon stocks in blue carbon

ecosystems (mangroves, seagrass meadows, and tidal

marshes) are estimated at 1 billion tons (1015 gr C), of which

3.315 gr C is stored in Indonesia.

In climate change mitigation context, forest plays an

important role since the primary source of emissions in

Indonesia (63%) in 2005 was land use changes and forest and

land fires. In 2012, the top contributor to emissions (47.8%)

was the LUCF (Land-Use Change and Forestry) sector, which

includes peat fires.

The COP13 in Bali in 2007 adopted the Bali Action Plan. One

of its key points is to agree on an REDD (Reducing Emissions

from Deforestation and Forest Degradation) scheme, which

is a mechanism to reduce greenhouse gas emissions by

compensating the parties for preventing deforestation

and forest degradation. In the framework of REDD, the

Government of Indonesia submitted a Forest Reference

Emission Level (FREL) to the UNFCCC Secretariat in 2015,

which covers deforestation and forest degradation as well as

peat decomposition.

The FREL is set at 0.568 GtCO2e/year for Aboveground

Biomass carbon pool, with 1990-2012 as the reference

period. The deforestation rate for business as usual (BAU)

2013-2020 based on FREL-REDD baseline is at 0.920 million

ha/year for both unplanned and planned deforestation.

According to the baseline, the Indonesia’s NDC document

assumes deforestation rate for BAU 2021-2030 to be

0.820 million ha/year. The emission reduction target for

unconditional scenario (CM1) and conditional scenario

(CM2) is 0.325 million ha/year, respectively.

An MRV (Measurement, Reporting, and Verification)

system is needed to measure whether or not the emission

reduction target set in the NDC has been achieved. Such

status information is important not only for the government

but also for the relevant stakeholders and the public. With

this information, the parties can provide input and even

directly contribute to the efforts of reducing greenhouse gas

emissions. Therefore, the MRV system must be accurate, use

an internationally-recognized method, and produce reliable

results for both national and global communities.

The IPCC (Intergovernmental Panel on Climate Change) has

published a set of guidelines for methods of measuring

greenhouse gas emissions, such as IPCC 2003 Good Practice

Guidance for Land Use, Land Use Change and Forestry

(LULUCF) and IPCC 2006 Guidelines for National Greenhouse

Gas Inventories-Volume 4 Agriculture, Forestry and Other

Land Use (AFOLU). For blue carbon measurement, the IPCC

has issued IPCC 2013 Supplement to the 2006 IPPC Guidelines

for National Greenhouse Gas Inventories: Wetlands. The

term used in this document is not ‘blue carbon’ but ‘coastal

wetland’; however both refer to the same ecosystems, i.e.

mangroves, seagrass meadows, and tidal marshes.


To build the MRV system, the government has issued

Presidential Regulation No. 71 of 2011 (Presidential

Regulation 71/2011) on the Implementation of National

Greenhouse Gas Inventory. This Presidential Regulation

aims to provide regular information on the level, status, and

trend of in GHG emission change and absorption, including

national, provincial, and district/city carbon stocks. In

addition, it also mandates the provision of information

on GHG emission reduction from national climate change

mitigation.

In 2015, the Ministry of Environment and Forestry

developed a standard method to quantify estimated

greenhouse gas emissions from the forestry sector, known

as INCAS (Indonesian National Carbon Accounting System).

The INCAS was developed to support the MRV requirements

for greenhouse gas emissions from land-based sectors,

particularly the forestry sector.

The INCAS describes in detail the standard methods

developed to quantify net greenhouse gas (GHG) emissions

for the forestry sector in Indonesia. These standard methods

describe the approach and methods used for data collation,

data analysis, quality control (QC), quality assurance (QA),

modeling, and reporting. The standard methods include:

1. Standard Method – Initial Conditions: describes the

process for defining initial conditions that are used as

inputs for modeling GHG emissions and removals. This

includes aboveground biomass, belowground biomass,

litter, and dead wood for each biomass class.

2. Standard Method – Forest Growth and Turnover:

describes the process for defining the rate of growth,

turnover of aboveground and belowground biomass,

decomposition of dead wood for each component of

each biomass class to be used as inputs in modeling GHG

emissions and removals.

3. Standard Method – Forest Management Events and

Regimes: describes the process for defining forest

management events and regimes and their impact on

carbon stocks as inputs for modeling GHG emissions and

removals.

4. Standard Method – Regimes Spatial Allocation: elaborates

on how the existing spatial data is used consistently to

allocate the area of management regime for analysis and

to generate annual land area change statistics to be used

in INCAS modeling.

5. Standard Method – Peatland GHG Emissions: describes

the process for quantifying GHG emissions from

biological oxidation of drained peat, direct emissions

from drained organic soils and canal drainage, as well as

emissions from peat fire.

6. Standard Method – Modeling and Reporting: describes

the process used to bring together data from the

other INCAS standard method (1-5) and to model GHG

emissions and removals from deforestation, forest

degradation, conservation role, sustainable forest

management, and forest carbon stock enhancement in

Indonesia.

In addition, the standard methods used to monitor changes

in forest in Indonesia are described in detail in The Remote

Sensing Monitoring Program of Indonesia’s National Carbon

Accounting System: Methodology and Products, Version

1 (Program Pemantauan Sistem Penghitungan Karbon Nasional Indonesia dengan Penginderaan Jauh: Metodologi dan Hasil, Versi 1) (LAPAN, 2014).

Based on the description above, the INCAS does not

seem to include a standard method for quantifying carbon

stored in soils/sediments in mangrove ecosystems (below

the ground carbon). This is an opportunity to refine the

INCAS by incorporating blue carbon contributions into the

national accounting of greenhouse gas emissions.

The Intergovernmental Panel on Climate Change (IPCC)

has actually published a document describing the carbon

accounting standard methods for wetlands, titled: 2013

Supplement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories: Wetlands. Chapter IV of this

document specifically discusses coastal wetlands that

cover three coastal ecosystems, i.e. mangroves, seagrass

meadows, and tidal marshes. It means that substantively,

coastal wetlands are blue carbon ecosystems. The chapter

provides guidance on estimating GHG emissions associated

with specific activities on coastal wetlands (blue carbon

ecosystems) that may or may not result in a land use change.

The estimated greenhouse gas emissions include not only

biomass and dead organic matter (aboveground), but also

more importantly, soil carbon (belowground).


3.3 MANGROVE MANAGEMENTThere are two somewhat overlapping legal bases for mangrove

management, i.e. Law No. 41 of 1999 (Law 41/1999) on

Forestry and Law No. 27 of 2007 in conjunction with Law No.

1 of 2014 (Law 27/2007 jo. Law 1/2014) on the Management

of Coastal Areas and Small Islands.

Law 41/1999 states that forest is an integral unit of ecosystem

in the form of lands containing biological resources,

dominated by trees in their natural environment (Article

1 paragraph 2). By this definition, a mangrove ecosystem is

classified as a forest. Meanwhile, Law 27/2007 jo. Law 1/2014

state that coastal area is the transitional area between land

and sea ecosystem influenced by a change in the land and sea.

By this definition, a mangrove ecosystem is also classified as

a coastal area. Therefore, mangrove ecosystems are natural

resources subjected to two Laws, i.e. Law 41/1999 and Law

27/2007 jo. Law 1/2014.

For implementation, two ministries are responsible for

mangrove management based on both laws, i.e. Ministry

of Environment and Forestry (MoEF), under Law 41/1999

and Ministry of Marine Affairs and Fisheries (MMAF), under

Law 27/2007 jo. Law 1/2014. This overlapping authority is

the source of a potential management problem. Both can

deny responsibility or fight over responsibility. Some argue

that management by more than one entity equals to no

management, which is similar to the ‘common property’

concept that often interprets as ‘nobody’s property’.

An example of this problematic double authority is when the

MoEF launched a program called ‘Rantai Emas’ (Gold Chain)

in Demak District in 2013. The main activity of this program

was Forest and Land Rehabilitation (Rehabilitasi Hutan dan Lahan/RHL) of coastal areas/beaches through mangrove

planting. However, in 2012 the MMAF had undertaken

a similar program in Demark District called ‘Ayo Tanam Mangrove’/ATM (Let’s Plant Mangrove), followed by several

other mangrove planting activities from 2013 to 2016 under

programs such as Mangrove for the Future (MFF), Building

with Nature (BwN), and Coastal Development Program

(Pengembangan Desa Pesisir Tangguh/PDPT).

Fortunately, the problem did not last long and ended with

the MoEF and the MMAF’s agreeing to divide authority

according to the status of forest area. The MoEF now is

responsible for managing any mangrove ecosystems which

are part of a forest area, while the MMAF manages any

mangroves ecosystems outside a forest area. Law 41/1999

defines forest area as a government designated area that

is to be preserved as permanent forest. Currently, both

ministries are waiting for the government’s decision on

which mangroves are classified as forest areas and which

ones are not.

To avoid the negative impact of double authority, the

government has also issued Presidential Regulation No. 73

of 2012 (Presidential Regulation 73/2012) on the National

Strategy for Mangrove Ecosystem Management. Two

major considerations base the issuance of this Presidential

Regulation:

1. Mangrove ecosystems are invaluable coastal wetland

natural resources and life support system as well as

natural wealth. For this reason, they need to be protected,

conserved, and used sustainably for promoting public

welfare;

2. Coordination, integration, synchronization, and synergy

across sectors, agencies, and institutions are necessary to

sustainably manage mangrove ecosystems as an integral

part of integrated coastal and watershed management.

A National Coordinating Team for Mangrove Ecosystem

Management was established under Presidential Regulation

73/2012 and consists of Steering and Executive Committees.

The Head of the Steering Committee is the Coordinating

Minister for Economic Affairs, with members consisting of

the Minister of Home Affairs, Minister of Finance, Minister

of Environment, Minister of Public Works, and Minister

of National Development Planning/Head of (Bappenas).

Meanwhile, the Head of the Executive Committee is the

Minister of Forestry and the Alternate Head is the Minister

of Marine Affairs and Fisheries, with members consisting

of echelon 1 officials from various ministries, such as the

Coordinating Ministry for Economic Affairs, Coordinating

Ministry for People’s Welfare, Ministry of Forestry, Ministry

of Marine Affairs and Fisheries, LIPI (Indonesian Institute of

Science), Bappenas, Ministry of Public Works, Ministry of

Home Affairs, Geospatial Information Agency, and National

Land Agency.

Presidential Regulation 73/2012 has mandated two

important tasks to the National Coordinating Team for

Mangrove Ecosystem Management:

1. To formulate policies, strategies, programs, and

performance indicators for mangrove management.

2. To establish a National Mangrove Working Group

(Kelompok Kerja Mangrove Tingkat Nasional/KKMTN).


The first task was accomplished in 2017 through Regulation

of the Coordinating Minister for Economic Affairs No.

4 of 2017 (Coordinating Minister for Economic Affairs

Regulation 2/2017) on Policies, Strategies, Programs, and

Performance Indicators for Mangrove Management. As

stated in Presidential Regulation 73/2012 and Regulation of

the Coordinating Minister for Economic Affairs 4/2017, the

National Strategy for Mangrove Ecosystem Management

(Strategi Nasional Pengelolaan Ekosistem Mangrove/

SNPEM) aims to synergize policies and programs for

mangrove ecosystem management that deal with ecology,

social and economy, institutional capacity, and laws and

regulations to ensure functions and benefits of sustainable

mangrove ecosystems for public welfare. SNPEM is also said

to be a coordinated basis and guideline for the government,

local governments, businesses, and communities. The

policy direction of SNPEM in Regulation of the Coordinating

Minister for Economic Affairs 4/2017 is also guided by

Presidential Regulation 73/2012, as follows:

1. Control on mangrove ecosystem conversion and utilization

based on the principles of sustainability (no net lost).

2. Improvement of mangrove ecosystem function in

biodiversity conservation, coastline and coastal resources

conservation, and increase in resulting products as

sources of income for the country and the people.

3. Mangrove ecosystem management as an integral part of

integrated coastal and watershed management.

4. Strong political commitment and support from central

and local governments as well as other parties.

5. Vertical and horizontal coordination and cooperation

across agencies and relevant parties to ensure the

implementation of SNPEM policy.

6. Community-based mangrove ecosystem management

that takes into account ecological, economic, and

sociocultural values, and aims to create better community

livelihoods and supports sustainable development.

7. Local government capacity building for exercising authority

and performing obligation of mangrove ecosystem

management based on local conditions and aspirations.

8. Development of research, science and technology, and

information system needed for stronger sustainable

mangrove ecosystem management.

9. Mangrove ecosystem management through partnership

between central and local governments, businesses,

and communities with support from international

organizations and communities as an effort to

accomplish the global environmental commitment.

Regulation of the Coordinating Minister for Economic Affairs

4/2017 divides the missions, objectives, targets, strategies,

programs, performance indicators, and roles of the

parties into four important values, i.e. ecology, social and

economy, institutional capacity, and laws and regulations.

One of the key programs and activities in the ‘important

ecological value’ category is expediting the designation of

mangrove area status (legality), whether as a protected area

(conservation zone) or as a cultivated area (general use zone).

The regulation is targeting for 3.49 million hectares of good

mangrove cover by 2045, with incremental implementation

from 2017 to 2045.

Meanwhile, the second task mandated by Presidential

Regulation 73/2012 (to establish a National Mangrove

Working Group (KKMTN)) was completed through Decree

of the Minister of Forestry No. SK. 504/Menhut-V/2013 on

the Establishment of National Mangrove Working Group.

KKMTN is tasked with:

1. Helping the National Coordinating Team formulate

policies, national strategies, and programs for mangrove

ecosystem management.

2. Encouraging the formation of province- and district/

city-level Coordinating Teams for Mangrove Ecosystem

Management, implementation of programs and

activities according to SNPEM, capacity building and

public awareness raising of mangrove conservation,

development of sustainable mangrove management

demo sites, and preparation of baseline data for

mangroves in Indonesia.

3. Synergizing the implementation of mangrove

management programs across sectors, central and

local governments, and other stakeholders, as well as

monitoring and evaluation of mangrove ecosystem

management.

4. Performing other tasks as instructed by the Coordinating

Team for Mangrove Ecosystem Management.

Interestingly, under Decree of the Minister of Forestry

504/2013, the Head of KKMTN is appointed alternately every

two consecutive years from the Ministry of Forestry, Ministry

of Marine Affairs and Fisheries, Ministry of Home Affairs,

and Ministry of Environment (Note: since 2014, the Ministry

of Forestry has merged with the Ministry of Environment to

form the Ministry of Environment and Forestry, or MoEF).

In addition to the head, KKMTN membership consists of

Bappenas, Geospatial Information Agency (Badan Informasi

Geospasial/BIG), National Land Agency, Ministry of Public

Works, Indonesian National Police, Attorney General’s

Office, LIPI, HNSI, IPB, and mangrove specialists.


Some suggest amending Decree of the Minister of Forestry

504/2013 to accommodate changes of nomenclature in

many ministries’ organizational structure. Furthermore,

KKMTN needs to recruit other stakeholders directly

dealing with mangrove management as members. Another

important consideration for such amendment is Law No.

23 of 2014 (Law 23/2014) on Local Governments, which

revokes a district/city government’s authority to administer

government affairs in the forestry, marine affairs, energy and

mineral resources sectors.

Mangrove management programs have been carried out

by different parties, including central-local government

partnership and environmental agencies and organizations,

to support to government policies. Some of the mangrove

programs launched by the central government are as follows:

1. Coastal Rehabilitation by Local Communities Program

(Rehabilitasi Pantai Entaskan Masyarakat Setempat/Rantai EMAS) – Deputy of Environmental Damage

Control and Climate Change, MoEF

• Year: 2011 – 2014

• Location: 63 locations in 13 districts/cities, 10

provinces, i.e. North Sumatra, Banten, West Java,

Central Java, East Java, Bali, East Nusa Tenggara,

Southeast Sulawesi, Gorontalo, and West Kalimantan.

• Objective: Rehabilitate mangrove ecosystems and

alleviate poverty in coastal communities.

• Activity: Mangrove planting in degraded coastal areas

involving 25-50 members of community groups. Each

participating community member is rewarded an

incentive of Rp100,000 - Rp150,000 for 8 months.

• Result: In 2011, 550,000 mangroves were planted.

In 2012, 1,130,000 mangroves were planted.

In 2013, 790,000 mangroves were planted.

2. Let’s Plant Mangrove/(Ayo Tanam Mangrove/ATM) –

MMAF

• Year : Since 2009

• Location: All Indonesian coastal areas

• Objective: Restore coastal areas in the long term, raise

public awareness of the importance of mangrove

ecosystems, engage communities to improve the

quality of coastal areas, rehabilitate mangrove

ecosystems, and build community capacity.

• Activity: Mangrove planting involving community

groups and other relevant parties.

• Result: From 2009 to 2011, 420,000 mangroves were

planted in 7 villages in 4 provinces.

3. One Map Program – BIG

• Year: Since 2013, following Presidential Instruction

No. 10 of 2011 on the Suspension of Granting of New

Licenses and Improvement of Governance of Natural

Primary Forest and Peat Land.

• Location: Entire Indonesia

• Objective: BIG together with the MoEF, Ministry of

Agriculture, and National Land Agency generate a

map with one reference, one standard, one database,

and one geoportal, as well as renew the Moratorium

Map every 6 months.

• Activity: Formation of 12 national working groups for

thematic geospatial information.

• Result: Mangrove Mapping Book (Sumatra)

Salt Pond Mapping Book

Shallow Water Characteristic Mapping Book

(Gorontalo, South Sulawesi)

Local governments have also implemented mangrove

conservation programs, as follows:

1. Village Regulation No. 1 of 2015 on Mangrove

Management in Wedung Village, Wedung Sub-district,

Demak District, Central Java Province. The regulation

was issued to deal with a threat of massive mangrove

ecosystem degradation in Wedung Village as a

consequence of land clearing for tambaks and housing.

The most severe damage occurs in the estuary and along

the coastline. With the full support of LPPSP Semarang

NGO and under the Medium Grant Project (MGF) of

Mangroves for the Future (MFF) program, Wedung Village

Government issued the regulation upon the approvals of

Demak District Government and Central Java Provincial

Government in March 2015. The regulation provides

for various activities, including coastal rehabilitation,

milkfish aquaculture with silvo-fishery method, local

economic capacity building (home business upscaling),

as well as communication and learning, which involve all

community elements.

2. Local Regulation of Penajam District Government No. 24

of 2012 on Mangrove Forest Management. The regulation

was issued by the local government in response to the

poor conditions of watersheds and coasts in North

Penajam Paser as a consequence of environmentally

destructive land use practices. Designating Buluminung

Industrial Estate in the district’s regional spatial plan

(Rencana Tata Ruang Wilayah/RTRW) has been a

double-edged sword for the local government since the

industrial estate envelopes a 4,000 ha mangrove forest


that is in danger because of the estate. Nevertheless, the

local government guarantees 30% of the mangrove forest

will be preserved in accordance with the environmental

management law.

Meanwhile, some of the mangrove programs undertaken

by NGOs and private sector (CSR program) through public-

private partnership include: :

1. Mangroves for the Future (MFF) Program – IUCN and

UNDP

• Year: Initiated in 2006, implementation began in

2008

• Location: 32 small, medium, and large projects in 35

villages in 9 provinces, i.e. DKI Jakarta, West Java,

Banten, Central Java, DI Yogyakarta, East Java, North

Sulawesi, Gorontalo, and South Sulawesi.

• Objective: Initiated in 2006 (as a response to tsunami)

and implemented in 2008, the regional program is

a multiparty collaboration in coastal management,

especially in areas impacted by climate change and

disaster-prone areas (tsunami, flash flood, etc.),

involving the government, NGOs, community groups,

educational institutions, and private sector.

• Activity: Community group capacity building in the

process of climate change impact adaptation and

mitigation, community livelihood improvement

involving more than 30 women groups, or around

300 women in coastal areas.

• Result: More than 1,500,000 mangroves have been

planted in an area of more than 150 ha, more than 30

small businesses have been developed by community

groups using local wisdom and resources, several fish

cultivation pilot projects have been launched in West

Java, Central Java, and East Java.

2. Partnership for Resilience (PfR) – Wetlands International

Indonesia (WII)

• Year: Period I: 2011-2015, Period II: 2016-2021

• Location: 9 countries, including Indonesia (East Nusa

Tenggara and Banten Bay), Ethiopia, Guatemala,

India, Kenya, etc.

• Objective: Contribute to improved community

resilience through ecosystem management by

incorporating climate change adaptation (CCA) and

ecosystem management and restoration (EMR) into

Disaster Risk Reduction (DRR), and build community

capacity to cope with disaster impacts.

• Activity: Community and local partner capacity

building, collaboration with local governments,

environmental quality improvement through

mangrove planting and semi-permeable method

pilot project.

• Result: Community capacity building and mangrove

planting in more than 30 villages in 9 locations in 2

provinces have been carried out with more than

54,000 people as beneficiaries.

3. Coastal carbon corridor – Yayasan Gajah Sumatra

(YAGASU)

• Year: Initiated in 2001, actively implemented in 2003.

• Location: Medan, North Sumatra and Aceh, DI Aceh

• Objective: Improve environmental carrying capacity

and forest ecosystem conservation for the purposes

of climate change mitigation and adaptation,

biodiversity conservation, disaster risk reduction, and

as improved green livelihood.

• Activity: Increased carbon stocks through mangrove

ecosystems, public welfare improvement, carbon

research and economic valuations, research grants,

and conservation of certain animal species.

• Result: Carbon credit from mangrove ecosystems in

the eastern coast of North Sumatra has been prepared

for mitigating GHG emissions, environmental

education has been provided at public schools,

YAGASU research center has been built in Aceh, and

Mangrove Protected Area has been established in

Belawan Sicanang Village.

4. LESTARI – USAID

• Year: Began in 2015

• Location: 6 strategic locations in Aceh, Central

Kalimantan, and Papua

• Objective: Support the Government of Indonesia in

reducing GHG emissions and carry out biodiversity

conservation through carbon storages and mangrove

and forest ecosystems. Use landscape, integrated

forest, and peat land conservation approaches to low

emission development in degraded lands.

• Activity: Advocacy and institutional capacity for land

and forest use, conservation through collaborative

management, and private sector engagement.

• Result: MoU between LESTARI and Aceh Provincial

Government has been signed, two more MoUs

with Papua and Central Kalimantan Provincial

Governments are being prepared, forest patrol has

been carried out at national parks, cooperation

with BRG has been established to conduct rapid

hydrological assessment of Block C, sustainable

community livelihoods have been developed, signing

for Cyclop Natural Reserve has been completed


with the relevant parties, gender training has been

provided, and grant has been awarded to a project of

creating 5 videos related to fire and smoke in Central

Kalimantan.

5. Restoring Coastal Livelihood (RCL) – OXFAM

• Year: 2010 – 2015

• Location: 60 villages in the western coast of South

Sulawesi

• Objective: Increase ecological and economic resilience

of coastal communities through mangrove forest

restoration, develop saline soil farming, encourage

small business growth, and encourage female

participation in development.

• Activity: Establishment of 60 business groups, beach

schools, and mangrove forest area restoration.

• Result: 1,000 beneficiaries (mostly women) from

60 small businesses (some have been upscaled), 44

small business training, restoration of more than 300

ha of mangrove forests.

6. Mangrove planting program by PT Pertamina in

Indramayu District, West Java

• Year: 2010

• Location: Karangsong Village

• Objective: Conserve and rehabilitate coastal areas to

contribute to improved local economy.

• Activity: Mangrove planting involving community

groups and development of mangrove tourism site.

• Result: 15,000 mangroves have been planted followed

by replication by other parties, and mangrove tourism

site has been developed with direct contributions to

local economy.

7. Mangrove planting program by PT. Jawa Power in

Probolinggo District, East Java

• Year: Began in 2009

• Location: Randutatah Village

• Objective: Develop a coastal conservation area that

supports stronger community institutional capacity.

• Activity: Mangrove and sea pine cultivation and

planting, development of mangrove and sea pine

ecotourism site by engaging community groups.

• Result: In 2014 and 2015, 83,000 mangroves and

sea pines were planted, and mangrove and sea

pine ecotourism site has been developed with

direct management by the local government and

community.

Below are the mangrove management activities carried out

by community groups and individuals in many locations in

Indonesia:

11. Pancer Pindang Community Self-Supporting Group in

Indramayu District, West Java cultivates and plants

mangroves around Laut Cilik in Cangkring Village, Cantigi

Sub-district, runs home fish processing businesses using

fish from local fishermen, and develops home hydroponic

vegetable farming.

2. Sido Agung Tambak Farmer Group in Probolinggo District,

East Java cultivates and plants mangroves in tambaks,

rivers, and salt fields. The group also runs home fish

processing businesses using fish from local fishermen and

has started a unique initiative called Salt Bank, where salt

farmers set aside some of their profits to buy and plant

mangroves around the salt fields.

3. Paddakauang Environmentally Aware Group in Pohuwato

District, Gorontalo cultivates and plants mangroves and runs

reef fish aquaculture businesses. The group has managed

to restore mangrove ecosystems by adopting local wisdom

through continuous self-taught learning (autodidact). This

achievement has attracted Gorontalo State University

(UNG) to collaborate as partners in studies of mangrove

ecosystem in Pohuwato District. UNG and Paddakauang

have signed a Memorandum of Understanding (MoU) for

mangrove ecosystem rehabilitation and restoration.

4. Mukhlis from Sinar Pagi Farmer Group in Probolinggo

Municipality, East Java has been planting and growing

mangroves (using his own money and efforts) since 1987

and was once nominated for the province’s Kalpataru

Award. His wife processes mangrove seeds into flour

and uses it to make different kinds of snack with high-

economic value.


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