EXPLORING BIOPHYSICAL AND MANAGEMENT CHALLENGES OF SMALL-SCALE SHRIMP FARM CLUSTERS IN INDONESIA USING FINE-SCALE GEOSPATIAL INFORMATION AND ANALYSIS
This study presents model applications of fine-scale geospatial information and analysis to explore bio-physical and management challenges of small-holders shrimp farm clusters in Suppa Sub-Districts, Pinrang District, South Sulawesi Province, Indonesia.
WorldView-2 multispectral satellite imagery with a spatial resolution of 2 m was used to create pond units layout (Figure 1A). To demonstrate the application of geospatial information and analysis, selected soil and water quality variables were obtained from Research Institute for Coastal Aquaculture (RICA) of which GIS-based spatial analysis such as image-vector conversion, interpolation and geospatial statistical models were applied.
The results generally indicated that geospatial information and analysis is an effective and efficient way to discover detailed technical constraints relating to biophysical characteristics and to assess the effective implementation and dissemination of aquaculture better management practices (BMPs). This study discovered aquaculture management constraints due to ineffective water exchange in some pond units as directly known from ineffective canal networks and from their correlations to spatio-temporal characteristics of salinity and dissolved oxygen values (DO). These pond units were also characterized by soil C/N ratio values > 10 which is an indication of slow in decomposition process of organic matter. The presence of Acid Sulfate Soils (ASSs) in most pond unit areas was also identified as indicated by pHF-pHFOX > 3 and mean SPOS value of 0.88%. The ratio of nitrogen and phosphorous (N/P ratio) of pond bottom soils < 4 indicated that N would be a limiting factor of pond productivity (Figure 1B). One of the more significant findings to emerge from this study is that the fine-scale geospatial analysis can be applied to monitor and evaluate spatial distribution of BMPs implementations and be compared with biophysical characteristics of the respective pond units. It is somewhat surprising that most BMPs implementations in this study area have not or just partially taken into account the spatial variability of the biophysical characteristics.
The empirical findings in this study provide a new understanding of the effective applications of fine-scale geospatial information and analysis on farm-level management. Its applications can help sustain the operation and productivity of small-scale shrimp aquaculture in the study area and other locations in Indonesia.