Sustainable Aquaculture Development Planning Through GIS Modeling: An Experience From Timor-Leste

Transcription

1 Sustainable Aquaculture Development Planning Through GIS Modeling: An Experience From Timor-Leste Shwu Jiau Teoh 1, Raimundo Mau 2, Julio da Cruz 2, Jharendu Pant 1 & Michael Phillips 1 1 WorldFish, Penang, Malaysia 2 National Directorate of Fisheries and Aquaculture (NDFA), Ministry of Agriculture and Fisheries (MAF), Timor-Leste - World Aquaculture Adelaide

2 Outline Background The Process Results Conclusions & Recommendations

3 Background Timor-Leste (also know as East Timor) is a new country, achieved independence on 20 May 2002 Widespread poverty and malnutrition: About 40% of the population living below US$0.55/day; Malnutrition among children under 5 years estimated at: Underweight: 45% Stunted: 54% (WFP, 2010) Aquaculture has been identified by the Government of Timor-Leste as one of the options for livelihood diversification

4 Background Per capita annual fish consumption: Timor-Leste: 6.1kg (RFLP/FAO, 2011) Global: 18.9kg (FAO, 2011) Current annual fish supply in Timor-Leste: Capture fisheries: 3,200t (FAO, 2007) Aquaculture: 46t (NDFA, 2010) To reach closer to global average, Timor-Leste needs a fish supply of 30,000t by 2030

5 Background Government of Timor-Leste developed National Aquaculture Development Strategy ( ): Supported by WorldFish Funded by RFLP/FAO and CTSP Key targets of the Aquaculture Strategy: Annual fish supply: 30,000t by 2030 (12,000t to come from aquaculture) Average per capita fish consumption: 15kg/capita/year by 2020 The Strategy emphasizes the development of aquaculture in agro-ecological niches area with favorable resource-base and social-economic contexts centre/wf_3602.pdf

6 The Process The process involved aquaculture suitability mapping of area taking a set of biophysical and socio-economic factors into account A simplified Geographical Information Systems (GIS) modeling using multi-criteria evaluation (MCE) was used for delineating recommendation domains for freshwater aquaculture across Timor-Leste

7 The Process 1 2 Identifying influencing factors (criteria) Weighing the factors Consultation with stakeholders Facilitator, stakeholder & expert inputs 3 4 Mapping indicators for factors Applying suitability rating to indicator maps GIS/Mapping tasks GIS technical expertise & software required 5 Mapping the suitability sub-models (MCE) 6 Mapping overall suitability model (MCE)

8 1 Identifying Influencing Factors/criteria Consultation meeting with national experts organized: National Directorate of Fisheries and Aquaculture (NDFA) National Directorate of Agriculture National Directorate of Forestry Agricultural Land use GIS (ALGIS) The experts were asked to list down factors (major determinants) for freshwater aquaculture development The discussions were guided by asking a few key questions: Which area(s) have high potential for aquaculture development in Timor-Leste? Why are these sites considered suitable?

9 2 Weighing the Factors (based on their relative importance) The determinants for freshwater aquaculture development are: biophysical & socio-economic All factors were grouped to construct sub-models Each factor was weighed based on its relative importance in every single sub-model Each sub-models was then weighed in another round to produce the overall model Boxes: Green: biophysical factors Orange: socio-economic factors

10 Socio-economic Biophysical 3 Mapping Indicators for Factors Required input data layers for creating the indicator maps acquired from various sources Factor Group Indicators Data sources (suitability sub-model) Biophysical (proxy function) Water (water supply for pond) Irrigated rice field (supplemental water supply from irrigation system) Natural lakes (natural conditions for aquaculture) Slope steepness (ease of pond construction) ALGIS ALGIS ALGIS CIAT-CSI SRTM v4.1 Inputs & Experiences Number of fish farmers (experiences with aquaculture) Access to hatcheries (access to seed) Access to different feeds (access to feed) NDFA,ALGIS NDFA,ALGIS ALGIS Market & Accessibility Population densities (local demand) Access to markets (market to sell fish) Proximity to road network (infrastructure) Coastal/Inland sucos (access to sea fish) ALGIS NDFA,ALGIS ALGIS ALGIS

11 3 Mapping Indicators for Factors Indicator maps were generated from data layers collected Water supply (Proximity to rivers & streams) River Network DEM Near Proximity to rivers & streams (unitless) Far Create proximity cost distance surface to rivers / streams by take into consideration the slope Terrain (Slope steepness) DEM Gentle Slope steepness (percent) Steep

12 4 Applying Suitability Rating to Indicator Maps Each indicator map was standardized to a common measurement scale of suitability rating ranging from 0 to 255 (0 = not suitable for aquaculture; 255 highly suitable for aquaculture) Need expert knowledge for applying the suitability rating Water supply (Proximity to rivers & streams) Apply suitability rating 0: Least Terrain (Slope steepness) 255: Most suitable

13 5 Mapping the Suitability Sub-models (MCE) Water supply (proximity to rivers & streams) Supplemental water supply (location of rice field) 45% + Combined indicator maps using Weighted Linear Combination (WLC) 15% Natural lakes (location of lakes) + = Least Terrain (slope steepness) 15% + Biophysical Sub-model Most suitable 25% Biophysical Inputs & Experiences Market & Accessibility

14 6 Mapping Overall Suitability Model (MCE) Sub-Models Biophysical Inputs & Experiences Market & Accessibility % 35% 20% Overall Model = Least Reclassify Most suitable Least suitable Moderately suitable Suitable Most suitable

15 Results: Harnessing Freshwater Fish Production Potential 1 ha : 3 tons productions Focal districts: * Bobonaro * Ermera * Baucau Least suitable Moderately suitable Suitable Most suitable Increase aquaculture production to 12,000t by 2030

16 Drilling Down to Identify Limitations Biophysical least-most suitable Sub-Models (fuzzy) Least Inputs & Experiences fuzz_suitbiophy Most limiting factors Most suitable Market & Accessibility fuzz_suitbiophy least-most suitable Overall Suitability Most limiting factor 1: Least suitable 2: Moderately suitable 3: Suitable 4: Most suitable Knowing the limitations helps determine what interventions are needed

17 Conclusions & Recommendations GIS is a useful decision support tool : Comprehensive database/map layers generated showing spatial distribution of area potential for aquaculture development in Timor-Leste GOs/NGOs prioritizing aquaculture development interventions in high potential areas In Sucu ida, Produto ida (one village one product) program, the government is promoting aquaculture in nine sub-districts of 3 high aquaculture potential districts

18 Conclusions & Recommendations Quality of suitability maps largely depends on the accuracy & quality of available data (spatial & temporal availability) Further refinement of the maps can be done using updated databases over time Weightage given to each of the factors depends on judicious decision made by local experts/stakeholder hence, a thorough discussion on each of the factors is vital

19 Acknowledgements

20 Thank You