Evaluation of the robustness of predictive yield models based on catchment characteristics using GIS for reservoir fisheries in Sri Lanka

Abstract

Land‐use patterns in the catchment areas of Sri Lankan reservoirs, which were quantified using Geographical Information Systems (GIS), were used to develop quantitative models for yield prediction. The validity of these models was evaluated through the application to five reservoirs that were not used in the development of the models, and by comparing with the actual fish yield data of these reservoirs collected by an independent body. The robustness of the predictive models developed was tested by principal component analysis (PCA) on limnological characteristics, land‐use patterns of the catchments and fish yields. The predicted fish yields in five Sri Lankan reservoirs, using the empirical models based on the ratios of forest cover and/or shrub cover to reservoir capacity or reservoir area were in close agreement with the observed fish yields. The scores of PCA ordination of productivity‐related limnological parameters and those of land‐use patterns were linearly related to fish yields. The relationship between the PCA scores of limnological characteristics and land‐use types had the appropriate algebraic form, which substantiates the influence of the limnological factors and land‐use types on reservoir fish yields. It is suggested that the relatively high predictive power of the models developed on the basis of GIS methodologies can be used for more accurate assessment of reservoir fisheries. The study supports the importance and the need for an integrated management strategy for the whole watershed to enhance fish yields.

Influence of hydrology on water quality and trophic state of irrigation reservoirs in Sri Lanka

“…These findings indicate that nutrient enrichment and trophic state are negatively influenced by RRLF . It is also well known that allochthonous nutrient enrichment into streams and reservoirs is influenced by land‐use patterns in stream/reservoir catchment areas (Amarasinghe, De Silva, & Nissanka, ; Borre, Barker, & Duker, ; Lenat & Crawford, ; Roth, Allan, & Erickson, ). Because this aspect was beyond the scope of the present study, only the possible influences of hydrological regimes on the water quality in the study irrigation reservoirs were investigated.…”

The use of GIS for the integration of traditional and scientific knowledge in supporting artisanal fisheries management in southern Brazil

“…Ranging from pioneer studies in fishery and aquaculture management (Meaden and Kapetsky, 1991) to recent applications in fisheries evaluation and planning (Amarasinghe et al, 2002;Isaak and Hurbert, 1997), the application of geographic information technologies has gradually increased in the fisheries management context (Close and Hall, 2006;Meaden, 2000). Anuchiracheeva et al (2003) showed that GIS was an important decision support tool to systematize, analyze, and display local knowledge in fisheries management at the community level in Thailand.…”

Food potential of continental aquatic ecosystems in China

“…It can be foreseen that the assessment of fishery productivity based on GIS should be a new hotspot in future fishery researches [17,18] .…”