2021/9/29

Blue Carbon and Ecosystem Services:
small-scale fisheries inmangroves and seagrasses
Busuanga Island, Philippines
T. E. Angela L. Quiros, Kenji Sudo and Masahiro Nakaoka
Akkeshi Marine Station, Hokkaido University
APBON
September 30, 2021
AngelaLQuiros@fsc.hokudai.ac.jp;
nakaoka@fsc.hokudai.ac.jp
1
Twitter: @SurfNSeagrass

Ecosystem Services

Copyright © 2020, Land Trust Alliance. All rights reserved.

21

2021/9/29

Mangroves

Spalding, Kainuma, Collins, 2010

Seagrass

Short, et al. 2011

Small-scale fisheries: 200 million people, 90% developing world

Allison & Ellis, 2001; Bene, Hersoug, Allison, 201042

2021/9/29

Capture fisheries and aquaculture provide
3.0 billion people with 20% of their average
per capita of animal protein (FAO, 2014)

5Questions• Can we assess differences incoastal communities’
vulnerability to the loss of blue
carbon habitat?
• How prevalent is theprovisioning service of blue
carbon habitat for coastal
communities?
• Can we use socio-ecological data
to improve management of blue
carbon ecosystems?
632021/9/29

Deltares, 2014

Short, et al. 2011

Philippines context• 78% of provinces and 56% of cities andmunicipalities along the coastline, making
up 60% of population• Fish gives 70% of total animal protein• Philippines has 16 seagrass species and42 mangrove species

42021/9/29

10115

2021/9/29

12BusuangaCoron• 14 barangays• 23 barangays• High mangrove, seagrass,(30% urban barangays)
coral cover, but low
biomass of target reef fish • High mangrove, seagrass,coral cover• Dugong, sea turtle• 87% of people in poverty • Tourism leading livelihood
source• High number ofrecreation, tourism areas • Problems: illegal mangrove
cutting• Problems: coral
harvesting, conflicting
knowledge on MPAs, needfor food livelihood &access to tourism
13

Source: Busuanga and Coron ECAN Resource Management Plans, 2017-2022

62021/9/29

Sensitivity

Adaptive Capacity

Actual & perceived threats“local societal importance”
of seagrass & mangroves“assets available”
to avoid impacts fromseagrass & mangrove loss

Seagrass ecosystem

Seagrass ecosystem

Seagrass ecosystem- % cover, coastal area, species- species, connectivity

Exposure

Mangrove ecosystem

Socio-economic- urbanism, tourismMangrove ecosystem

Mangrove ecosystem- coastal area, forest type

- connectivity, adjacent habitat

Socio-economic

Socio-economic- population density, fisheries
income, tourism income- other income, salaried
income, education

Fisheries

Fisheries- catch composition, catch rate

- alternative livelihoods,
fishing experience

Governance- knowledge, organizations

Social vulnerability
Risk

Data sources using multiple methods

Ecologicalsurveys &spatial
analysesLandingsurveys(n=601)

Key
informantinterviews

Householdsurveys(n=310)Participant
observation(120 days)(n=10)(n=10)
Indo-Pacific Seagrass
Network

Field collections between February 2019 - October 2020157

2021/9/29

16178

2021/9/29

18

Some communities specialize in seagrass fisheries,
others in mangrove fisheries, or both
Municipality

Barangay

Mangrovelandings

Mean CPUE(kg/hr) (SD)

Seagrass
landings

Mean CPUE(kg/hr) (SD)

Busuanga

Concepcion

n=19

1.58 (1.11)

n=117

1.37 (1.76)

SGNew Busuanga

n=0

n=32

0.83 (0.55)

SGQuezon

n=17

6.12 (3.70)

n=40.86 (0.32)

MGSalvacion

n=80.31 (0.21)

n=60

1.73 (1.62)

SGBoracn=92

2.02 (1.21)

n=0Brgy. 5n=100.78 (0.38)

n=49

0.93 (0.99)

SG

Decalachao

n=19

1.87 (1.91)

n=90.64 (0.15)

MGSan Jose

n=18

1.63 (1.11)

n=50

1.02 (1.31)

SGTurdan=150.97 (1.35)

n=21

1.17 (0.91)

SG/MG

n=198

2.24 (2.39)

n=342

1.23 (1.42)

CoronTotals

MG9

2021/9/29

Seagrass catch

Mangrove catch
clam

clam

crab

shrimp

SGMG

snail

snail
fish
Landingsurveys20

Spatial analyses• Limited analysis to 10 barangays within Busuanga Island• Exposure: UrbanismWeighted average distance, human population, with Coron Town
weighted heaviest (population 19,000) and Salvacion town
(population 4,000)• Coron had a weight of 0.84 (a/(a + b))
Salvacion had a weight of 0.16 (b/(a + b))

2110

2021/9/29

Spatial analyses• Sensitivity: Coastline covered by seagrass and mangroves
Remotely sensed data ground-truthed in the field or by expert
opinion• Mangrove Vegetation Index (MVI): Baloloy et al, 2020
Using a 100-m buffer distance (ArcGIS), calculated the length ofmangrove forest by total length of each barangay coastline• Landsat 8 linear spectral unmixing method for seagrass
Overlaid validated seagrass map on UNEP coral reef base layer (reefflat) to show the proportion of reef flat covered by seagrass in eachbarangay
2223

11

2021/9/29

Spatial analyses• Adaptive capacity: Habitat patchiness• Continuous grid of 500-m cells in the mangrove & seagrass layers• Focal statistics function (ArcGIS) to calculate the contiguous area of 3
cells with seagrass or mangroves, separately• Focal analysis score divided by number of 500-m cells within thatbarangay for a connectivity ratio• Focal analysis ratio <25% small, fragmented habitats
25-60% medium patchiness>60% contiguous
https://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/how-focal-statistics-works.htm

24

Spatial analyses• Adaptive capacity: Adjacent habitat• Same grid of 500-m cells in the mangrove & seagrass layers• Connectivity score between 0 and 2
Score = 0 : 1 habitat (seagrass, mangrove or coral)
Score = 1: 2 habitats (seagrass/mangrove, seagrass/coral or coral/mangrove)
Score = 2: 3 habitats present
Divide total cells in barangay grid by cumulative connectivity score
Low connectivity score <1; Medium score between 1 to 1.5;
High score > 1.5
https://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/how-focal-statistics-works.htm

25

12

2021/9/29

Seagrass
abundance byspecies,

Map created by Ayin Tamondong with superimposed data from the BlueCARES Ecology Group

Seagrass
abundance byspecies,
Mangroveforest type,Riverinebasin-fringing
Riverinefringing
Scrub-fringing

Map created by Ayin Tamondong with superimposed data from the BlueCARES Ecology Group13

2021/9/29

LH

Seagrass
abundance byspecies,
Mangroveforest type,
Proportion
seagrass &mangrove
landings codedby Catch Per
Unit Effort(CPUE) across 9
barangays
Busuanga
Island,Philippines% seagrasslandings% mangrove
landings% otherlandings

M
M

CPUE
Low (L) = < 1 kg/ hr
Medium (M) = >1 kg/ hr
High (H) = >2 kg/ hr

Riverinebasin-fringing
Riverinefringing

M

Scrub-fringing
MLM

L

M

M

M
M
HLL

Map created by Ayin Tamondong with superimposed data from the BlueCARES Ecology Group

Sensitivity

Exposure

Adaptive CapacityActual & perceived threats

Seagrass ecosystem
Mangrove ecosystem
Socio-economic

Social vulnerability
Risk14

2021/9/29

Exposure
Indicatorsfor fisheriessystems
Mamauag et al, 2013;
Jacinto et al, 2015;
Licuanan et al, 2015

*additional variable
created for this study

Criteria

Low, Medium, High

Seagrass
ecosystem

Perception tochanges in seagrasscoverLow exposure: widespread, dense
Medium exposure: patchy, decreasing
High exposure: sparse

Mangroveecosystem

Perception to
Low exposure: widespread, densechanges in mangrove Medium exposure: patchy, decreasing
coverHigh exposure: sparse

Socioeconomic

Urban gradient*

Low exposure: Weighted distance > 40 km
Medium exposure: Weighted distance 20-40km
High exposure: Weighted distance < 20 km

Tourism gradient*

Low exposure: low
Medium exposure: medium
High exposure: high30

Urban
barangays
havehigherExposure
3115

2021/9/29

Adaptive Capacity

Sensitivity

Exposure
Actual & perceived threats“local societal importance”
of seagrass & mangroves

Seagrass ecosystem

Seagrass ecosystem

Mangrove ecosystem

Mangrove ecosystem

Socio-economic
Socio-economic

Fisheries

Social vulnerability
Risk

What makes up a healthy seagrass bed?
•Methods• Seagrass habitat(Seagrass Watch,Indo-Pacific Seagrass
Network (IPSN))

Ecologicalsurveys

Sensitivity
IndicatorLowsensitivity(1-2 pts)

Mediumsensitivity(3-4 pts)Highsensitivity(5 pts)Seagrass %cover> 51%

21-50%<20%

2–4species
seagrass

Monospecificseagrass bed

Seagrass species > 5 species
numberseagrass

33

16

2021/9/29

Ecosystem

Sensitivity
Indicatorsfor fisheriessystems

SG

Mamauag et al, 2013;
Jacinto et al, 2015;
Licuanan et al, 2015

MG

Criteria

Low, Medium, High

Seagrass % coverLow sensitivity: seagrass % cover > 51%
Medium sensitivity: seagrass % cover 21-50%
High sensitivity: seagrass % cover <20%

Coastal area coveredby seagrasses

Low sensitivity: > ½ reef flat
Medium sensitivity: 1/8 to ½ reef flat
High sensitivity: < ½ reef flat

Seagrass species
numberLow sensitivity: > 5 species
Medium sensitivity: 2-4 species
High sensitivity: monoculture

Coastal area coveredby mangroves

Low sensitivity: > ½ coastline
Medium sensitivity: 1/8 to ½ coastline
High sensitivity: < ½ coastline

Kind of mangrove
forestLow sensitivity: riverine-basin-fringing
Medium sensitivity: riverine-fringing
High sensitivity: scrub-fringing*additional variable
created for this study

34

What makes up a less sensitive catch?
Methods• Fishery variables(Quiros et al, 2018,
Indo-Pacific Seagrass
Network (IPSN))

LandingsurveysSensitivity
Indicator

Low
Mediumsensitivity sensitivity(1-2 pts)(3-4 pts)Highsensitivity(5 pts)Dominant catchpelagics

mix of pelagic,
demersal

demersal,nearshore

Seagrass CPUE
(catch per uniteffort)> 8 kg /3 kg / fisher/fisher/ day day< 3 kg /fisher/ day35172021/9/29

Fisheries

Sensitivity
Indicatorsfor fisheriessystems

Socioeconomic

Mamauag et al, 2013;
Jacinto et al, 2015;
Licuanan et al, 2015

Criteria

Low, Medium, High

Dominant catchcomposition

Low sensitivity: pelagics
Medium sensitivity: mix of pelagic, demersal
High sensitivity: demersal, nearshore

Catch rate

Low sensitivity: > 8 kg / fisher/ dayMedium sensitivity: 3 kg / fisher/ dayHigh sensitivity: < 3 kg / fisher/ day

Population density

Low sensitivity: < 200 /km2
Medium sensitivity: 200-400 /km2
High sensitivity: > 500 / km2

Fisheries ecosystemdependency

Low sensitivity: < 25% full time fishers
Medium sensitivity: 25-50% full time fishers
High sensitivity: > 50% full time fishers

Tourism income

Low sensitivity: <7 % tourism workers
Medium sensitivity: 7-15% tourism workers
High sensitivity: >15% tourism workers*additional variable
created for this study

36

How reliant are households on seagrassresources?
Socio-economic• Non-fishing employment• Household reliance on seagrassHouseholdsurveys

Quiros et al, 2018

Sensitivity
IndicatorLowsensitivity(1-2 pts)

Mediumsensitivity(3-4 pts)Highsensitivity(5 pts)Humanpopulation
density< 200 /km2

200-400/km2> 500 / km2

Fisheries
income< 25% fulltime fishers

25-50% full > 50% full time
37
time fishers fishers

18

2021/9/29

Urban
barangays
havehigher
Sensitivity
38

Sensitivity

Adaptive Capacity

Actual & perceived threats“local societal importance”
of seagrass & mangroves“assets available”
to avoid impacts fromseagrass & mangrove loss

Seagrass ecosystem

Seagrass ecosystem

Seagrass ecosystem

Mangrove ecosystem

Mangrove ecosystem

Socio-economic

Socio-economic

Fisheries

Fisheries

Exposure

Mangrove ecosystem
Socio-economic

GovernanceSocial vulnerability
Risk192021/9/29

Criteria

Low, Medium, High

Seagrass species

Low adaptive capacity: Enhalus or no seagrass
Med adaptive capacity: Enhalus, Thalassia,
Cymodocea, Halodule
High adaptive capacity: Halophila, Halodule

Ecosystem
Adaptive
composition
CapacitySG
Seagrass habitat
Indicators
extentfor fisheries
Presence ofsystems
adjacent habitat
Mamauag et al, 2013;
Jacinto et al, 2015;
Licuanan et al, 2015(seagrass ormangroves orcorals)
MG

Mangrove habitat
extentLow adaptive capacity: Small, fragmented
Med adaptive capacity: Patchy, but large area
High adaptive capacity: Large, contiguous area
Low adaptive capacity: Absent
Med adaptive capacity: Presence of 1 adjacent
habitat in good condition
High adaptive capacity: Presence of 2 adjacent
habitats
Low adaptive capacity: Small, fragmented
Med adaptive capacity: Patchy, but large area
High adaptive capacity: Large, contiguous area*additional variable
created for this study

40AdaptiveSocioCapacity
economic
Indicatorsfor fisheriessystems
Fisheries

Criteria

Low, Medium, High

Fishers withother sources ofincome

Low adaptive capacity: < 40% fishers
Med adaptive capacity: 40-60% fishers
High adaptive capacity: > 60% fishers

Alternative
livelihoods tofishing

Low adaptive capacity: Only fishing
Med adaptive capacity: 1-2 other livelihoods
High adaptive capacity: > 3 other livelihoods

Mamauag et al, 2013;
Jacinto et al, 2015;
Licuanan et al, 2015

Fishingexperience

Low adaptive capacity: > 20 years
Med adaptive capacity: 5-10 or 10-20 years
High adaptive capacity: < 5 years*additional variable
created for this study

Households with Low adaptive capacity: < 10% salaried
Salaried income Med adaptive capacity: 10-15% salariedHigh adaptive capacity: > 15% salaried

4120

2021/9/29

Criteria
Adaptive
Governance Access toCapacity
knowledge,
information
Indicators
People’sfor fisheries
Organizations
systems
Education
Mamauag et al, 2013;
Jacinto et al, 2015;
Licuanan et al, 2015

*additional variable
created for this study

Low, Medium, HighLow adaptive capacity: No NGOs, 1 past NGO
Med adaptive capacity: 1 current NGOs
High adaptive capacity: 2 current NGOs
Low adaptive capacity: No presence, 1 PO
Med adaptive capacity: 2-5 POs
High adaptive capacity: > 5 Pos
Low adaptive capacity: > 60% less than 10 years
schooling (high school)
Med adaptive capacity: 20-40% or 40-60% lessthan 10 years schoolingHigh adaptive capacity: < 10 % with less than 10years schooling

42

Rural &Peri-urban
barangays
havehigher
AdaptiveCapacity4321

2021/9/29

Simple ranking of vulnerability scores
Categories Numberofvariables
3BlueCarbonfisheries
4Socioeconomic
2Seagrassecosystem

Minimum Maximum LOW MEDIUM HIGH
score
score
score score
score
315

3-7

8-11

12-15

420

4-9

10-15

16-20

210

2-4

5-7

8-10

Scores were usedto rank variables
using a point classinterval

44

Mamauag et al, 201345

22

2021/9/29

LH

Seagrass
abundance byspecies,
Mangroveforest type,
Proportion
seagrass &mangrove
landings coded
by Catch Per
Unit Effort(CPUE) across 9
barangays
BusuangaIsland,
Philippines% seagrasslandings% mangrove
landings% otherlandings

MMCPUELow (L) = < 1 kg/ hrMedium (M) = >1 kg/ hr
High (H) = >2 kg/ hr

Riverinebasin-fringing
Riverinefringing

M

Scrub-fringing
MLMLMMMMHLLMap created by Ayin Tamondong with superimposed data from the BlueCARES Ecology GroupConclusions• Vulnerability criteria can help address multiple SDGs at once (poverty,hunger), while tackling natural resource management issues• Policy prescriptions for Busuanga Island:
1) Improve access to education
2) Increase information and organization opportunities
3) Equitable fisheries management
4) Establish protected areas and limit tourism development in sensitivehabitat

4723

2021/9/29

Less vulnerable
communities
Low population density
Low fisheries
dependency
Good governance
Healthy blue carbon
habitatMany thanks toUniversity of the Philippines, Dilliman – Gay Go, Joy Jamilla, Mikko Garcia
C3 Philippines –Reynante Ramilo, Muammar Soniega, Helbert Garay
Local Governments of Busuanga and Coron,
Barangay officials of Concepcion, Salvacion, San Jose, Decalachao Barangay V, Tagumpay
Municipal Agricultural Officer of Busuanga and Coron
Palawan Council for Sustainable Development
Field assistants – Jun Esplana, Dodong Castano, Joey Ormido, Wilfred Salvacion,
Jing Abela, Edgar Villareal, Baby Jane Villalreal, Vincent Rodriguez, Vicky Hefty,Vincent Valera, Angel los Angeles, Rench Ramos, Mariel Quiros

AngelaLQuiros@fsc.hokudai.ac.jp;
nakaoka@fsc.hokudai.ac.jp“Kuya Jun”

Twitter: @SurfNSeagrass24