This document summarizes a final workshop on analyzing decision networks in coastal ecosystems. (1) The workshop objectives were to contextualize global climate change knowledge into local decision making, investigate land use changes from paddy to shrimp farming in coastal Bangladesh, and develop an ecosystem health framework using multi-criteria analysis. (2) Case studies from three districts examined land use trends over time and suitability for crops under climate change. (3) A conceptual framework was presented for assessing sustainable ecosystem services using drivers, pressures, state of ecosystem, and impacts. Criteria and indicators were developed to calculate an ecosystem health index.

1. Final Workshop
on
Whole Decision Network Analysis in Coastal Ecosystem (WD-NACE)
Modelling Interacting Impacts of Processes and
Decisions on Ecosystem Dynamics
Presented by
Dr Ahmadul Hassan
Director, R&D and Training Division, CEGIS
ahassan@cegisbd.com
Date: 27 September, 2012
London, UK

2. Objectives
1. Contextualize knowledge on global climate
change into local decision making
2. To investigate the spatial and temporal
dimensions in land use changes from paddy
to shrimp farming in the coastal areas of
Bangladesh.
3. To develop a framework for estimating the
ecosystem health index using Multi Criteria
Analysis (MCA).
2

3. Study Area
Three districts:
–Satkhira
–Khulna
–Bagerhat
Area :1,201,319 ha
Population: 5.74 million
Area of Sundarbans:
- 577,000 ha
3

4. Objective 1: Contextualize knowledge on global
climate change into local decision making
4

5. Application of Global Knowledge for
Local Decision Making
Downscaling • NAPA
Global
into local • BCCSAP
Models and
context • SNC
Tools
• Plans and
policies
• Generate
funds 5

6. Observed Trends in Maximum Temperatures
6

7. Observed Trend in sea level rise
Hiron Point, Passur River
(Source: BIWTA)
2.10
y = 0.005x + 1.739
2.00
R² = 0.324
1.90
1.80
1.70
W
m
n
e
a
v
L
r
t
i
l
1.60
1.50
7
9
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5
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6
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0
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0
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2
Year
7

8. Downscaling of Climatic Parameters for
Bangladesh
 IPCC Used 23 GCMs for forecasting global climate
 Based on the method described in MGICC 8 best
suited GCMs for Bangladesh has been selected
1. CGCM 3.1 (T47) 5. GFDL-CM 2.0 2.1
2. CCSM 3.0 6. INM CM-3.0
7. MIROC 3.2 (medres)
3. CSIRO-Mk3.0
and
4. GFDL-CM 2.0 8. UKMO-HadCM3. 8

9. Climate Change Scenario
(Bangladesh)
Annual average changes
Temperature Precipitation
Emission (Change in °C) (% change)
Scenario
2030s 2050s 2030s 2050s
A2 0. 73 1.32 4.9 8.1
B1 0.78 1.62 6.3 8.4
** Ensemble average of eight GCM results [CGCM 3.1, CCSM 3.0, CSIRO-Mk3.0, GFDL-CM 2.0 and 2.1, INM CM-
3.0, MIROC 3.2 (medres) and UKMO-HadCM3]
***Assessment done by CEGIS
9

10. Changes in Annual Temperature and Precipitation
10

11. Sea Level Rise
• Sea level rise will increase about 27 cm by
2050 and 80 cm by 2080 in coast of the Bay of
Bengal
11

12. Objective 2: To investigate the spatial
and temporal dimensions in land use
changes from paddy to shrimp farming
in the coastal areas of Bangladesh.
12

13. Major Cropping Pattern
Crops Reason for selection
Shrimp Shrimp Economic and Physical
Aman Shrimp Environment and Economic
(Monsoon rice)
Aman Boro Environment and Food security
(Winter rice)
13

14. Landuse (2011)
Boro (winter rice) Aman (monsooon rice)
Districts Area Production Area Production
(Mt) (Mt)
Khulna 50,025 212,552 82,835 213,979
Bagerhat 47,385 187,960 70,580 148,370
Satkhira 73,985 291,713 87,080 235,876
Total 171,395 692,225 240,495 598,225
14

15. Changes in Boro (winter rice) cultivated Area from1992-2009
• Due tohigher salinity, Boro production decreases
• Boro area started to reduce from 1990
• Now people are shifting from shrimp to rice production
• Shrimp area reduced in 2009 and Boro area increased in
2009
15

16. Changes in Bagda (salt water shrimp) cultivated Area from1992-2009
• Shrimp cultivation started increasing in 1990 &
increased upto 2005
• Salinity increased because of shrimp culture
16

17. Change in Boro and Bagda Area over time
 In 2005, Boro area reduces where Bagda area shows slightly
increasing trend.
 Area under Boro cultivation in 2009 increase significantly from that
of 2005 17

18. Trend in Boro and Bagda Area Changes
 Boro and Bagda area in Satkhira districts changes slowly
than that of Khulna district
 Boro and Bagda area in Bagerhat districts changes firstly
than the other two districts. 18

19. Reasons Behind Changes
Fallow Boro For more economic return
Changes in physical factors
Shrimp Boro - Conversion of saline areas
to fresh water
19

20. Suitability – Boro
20

21. Suitability – Bagda
Scenarios Highly Suitable (S1) Suitable (S2) Moderately Suitable (S3) Not Suitable (S4)
Base 0 25 35 40
32 cm SLR 1 37 42 20
88 cm SLR 9 29 29 33
Suitability for 32 cm SLR Suitability for 88 cm SLR
Figure 9.3.4 Bagda - Suitability under different SLR scanrios
21

22. Objective 3: To develop a framework for estimating
the ecosystem health index using Multi Criteria
Analysis (MCA).
Externalities Land use
Changes
- Demographic
pressure Livelihood
-Climate change
- Ecosystem
Dynamics
22

23. Changing pattern in distribution of Sundri
and Gewa from 1992 to 04-05
23

24. Changing pattern in distribution of Goran
and Gewa from 1992 to 2004-05
24

25. Salinity condition in coastal area (2005 and 2050)
25

26. Tree Species Distribution in Sundarbans
26

27. Conceptual Framework for Sustainable Ecosystem Services of
Sundarbans Mangrove Forest
Drivers Pressures State of the Ecosystem
1. Demographic Land use change
–Population pressure Salinity intrusion Forest Habitat
–Livelihood • Canopy area, species
Low dry season water flow
2. Market dominance
Overexploitation of forest
–Commodity price
3. Climate change resources
Diversity
–Freshwater flow Sedimentation in river channels
•Terrestrial and aquatic
–Sea level rise Drainage congestion
4. Policies Industrial pollution Environment
–Forest policy, land use policy •Hydrological condition
–Law enforcement
Responses Impacts
• Declaration of Sundarbans as Reserve Forest,
Ecologically Critical Area (ECA) Productivity
•Restriction on timber and fish harvesting •Timber, fish, honey
•Afforestation in the deforested land in the forest as well as in
newly developed islands
•Establishing fish sanctuary Services
•Livelihood support,
•Established 3 wildlife sanctuary
•Disease and pest control tourism
•Alternative livelihoods development programme for forest 27
dependent people

28. Mangrove Ecosystem Health Index: Computational
Framework
Pressures State
Land use change •Enabling forest habitat
Salinity intrusion •Required Hydrological
Low dry season water condition
Ecosystem
•Conservation of
flow Health
biological diversity Index
Overexploitation of
forest resources
Sedimentation in river Impact (On goods and
services)
channels
Drainage congestion •Sustainable forest
productions
Industrial pollution •Enhancement of socio-
economic benefits 28

29. Criteria and Indicators for MCA
Sl No Criteria Sub Criteria Indicators Type
1. Enabling Forest canopy % of forest area B
forest habitat under high density
forest canopy
Species Area of Sundri B
dominance coverage (%)
Area of goran C
coverage (%)
Forest No. of Deer Poaching C
Management offense per year
2. Required Upstream Annual flow of Gorai B
Hydrological freshwater river (million m3/ yr)
condition flow 29

30. Criteria and Indicators for MCA (Cont…)
Sl No. Criteria Sub Criteria Indicator Type
3. Conservation Species density No. of Sundari tree/ B
of biological ha
diversity No. of Gewa tree /ha B
4. Sustainable Timber resource Annual timber B
forest (Sunduri, Bine, harvest (cubic meter/
productions Keora, Gewa) yr)
Fuel wood resource Annual fuelwood B
(Goran, Hetal, harvest (ton / yr)
Kakra and others)
Fish (Dry and White Annual fish harvest B
fish) (ton / yr)
Honey Annual honey B
collection (ton /yr)
Golpata Annual golpata B
harvest (ton / yr) 30

31. Criteria and Indicators for MCA (Cont…)
Sl No. Criteria Sub Criteria Indicator Type
5. Enhancement Forest % of forest C
of socio- dependant dependant
economic livelihood livelihood (0-5 km
benefits Impact zone)
Tourism No. of visitors per B
year
Shrimp % of area covered by C
farming shrimp farms in
three districts
31

32. Values of Indicators and Score of MCA
Criteria Sub Criteria Indicators Value Score Value Score
Enabling forest Forest canopy % of forest area under high
53 15 24 6
habitat density forest canopy
Species dominance Area of Sundri coverage (%) 29% 8 36% 15
Area of goran coverage (%) 8% 14 17% 5
Forest Management No. of Deer Poaching offense per
22 16 26 13
year
Required Hydro- Upstream freshwater
Annual flow of Gorai river
meteorological flow 45,658 15 29,314 9
(million m3/ yr)
condition
Conservation of Species density No. of Sundari tree per ha
biological 106 5 205 14
diversity
Sustainable Timber resource (Sunduri, Annual timber harvest (cubic
3,220 8 5502 12
forest Bine, Keora, Gewa) meter/ yr)
productions Fuel wood resource
Annual fuelwood harvest (ton/
(Goran, Hetal, Kakra and 32,194 16 14,192 5
yr)
others)
Fish (Dry and white fish) Annual fish harvest (ton/ yr) 3,298 7 2,217 4
Honey Annual honey collection (ton/yr) 87 4 103 5
Golpata Annual golpata harvest (ton/ yr) 21,409 8 25,547 10
Enhancement of Forest dependant % of forest dependant livelihood
18 7.5 18
socio-economic livelihood (0-5 km Impact zone)
benefits Tourism No. of visitors per year 71,202 8 119,256 16
Shrimp farming % of area covered by shrimp
8 18 18 10
farms in three districts

33. Score of MCA
Scores
Criteria Previous yrs Ref Yrs
(1983-2004) (2005-12)
Enabling forest habitat 13 10
Required Hydrological condition 15 9
Conservation of biological
diversity 15 14
Sustainable forest productions 9 7
Enhancement of socio-economic
benefits 5 15
Overall Score 57 55
33

34. Conclusion
 Global knowledge on climate change was
incorporated in national strategies, policies and
plans like NAPA, SNC
 Landuse changes is driven by both economic
and environmental factors
 Dependency on Sundarbans for livelihood of the
buffer area population is still higher
 Alternate livelihood options is needed to reduce
the dependency on Sundarbans
 Detail historical data is required to understand
the dynamics of Sundarbans ecosystem 34

35. Thank you
35