Keywords
biogeochemical model, synthesis, data assimilation, aquatic systems
Start Date
1-7-2012 12:00 AM
Abstract
Quantitative assessments of aquatic ecosystem dynamics and servicesare required to guide decision support activities and assess how socioeconomicscenarios of human development impact our aquatic environment. However, weare poorly equipped to predict across a broad range of scales the physical,biogeochemical and ecological interactions that control carbon and nutrient fluxpathways, despite a plethora of models and model approaches that have emerged.Our models have languished due to ambiguities and lack of agreement in modelconceptualisations, a focus on point-scale rather than system-scale validation, anda general inability to deal with uncertainty, particularly in spatially-resolved interdisciplinarymodels. Further, the site-specific and highly disciplinary nature of manymodel applications limits synthesis and transferability of knowledge between sites.Here we outline a blueprint for an integrative approach to address these barriers byfacilitating: i) the integration of inter-disciplinary modelling approaches, ii) reducinguncertainty through a multi-scale validation approach and managed assimilation ofenvironmental sensing data, and iii) cross-domain synthesis.
Blueprint for a unifying framework for synthesis of aquatic ecodynamics
Quantitative assessments of aquatic ecosystem dynamics and servicesare required to guide decision support activities and assess how socioeconomicscenarios of human development impact our aquatic environment. However, weare poorly equipped to predict across a broad range of scales the physical,biogeochemical and ecological interactions that control carbon and nutrient fluxpathways, despite a plethora of models and model approaches that have emerged.Our models have languished due to ambiguities and lack of agreement in modelconceptualisations, a focus on point-scale rather than system-scale validation, anda general inability to deal with uncertainty, particularly in spatially-resolved interdisciplinarymodels. Further, the site-specific and highly disciplinary nature of manymodel applications limits synthesis and transferability of knowledge between sites.Here we outline a blueprint for an integrative approach to address these barriers byfacilitating: i) the integration of inter-disciplinary modelling approaches, ii) reducinguncertainty through a multi-scale validation approach and managed assimilation ofenvironmental sensing data, and iii) cross-domain synthesis.
