Modeling the kinneret ecosystem

Abstract

Modeling of the Lake Kinneret ecosystem and its various components has developed greatly since the first effort in 1980. Modeling studies have included a range of approaches, some of which have focused on the entire ecosystem, while others only on certain components. The modeling approaches that have been applied to the Lake Kinneret ecosystem range from statistical approaches, data mining, and machine-learning techniques to flux models, bioenergetics, nutrient– phytoplankton–zooplankton (N–P–Z)-type models, and complete ecosystem models. Models have been used to enhance our understanding of key limnological and food-web processes. The models, however, have also been used as a means for providing resource managers with improved management tools. This has included, in some cases, integrating model output and a quantified water quality (WQ) system as the basis for establishing the relationships between management measures and water quality. Thus, highlighting the role of ecosystem modeling as a critical management tool. The use of models, especially complex ecosystem models, requires constant updating and ongoing development along with a wide range of information and data. In most cases, the available information and data do not satisfy model needs thereby introducing model uncertainty. In order to improve model reliability, and, as a result, its applicability, it is important to increase the overlap between routine monitoring and model data requirements.