WP4: Environmental models

Co-ordinator: University of Stirling (UoS)

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  1. The effluent outputs compared to the environment per unit production for cells in the species/ country matrix (Table.2)
  2. Models developed for quantitative investigation of environmental sustainability for the different systems/ countries that contributes to future ethical management standards (inc. comparison of environmental quality standards developed either as part of this project or from existing environment management initiatives).

Description of work and role of participants

T4.1 Review of environmental models and associated indicators. This task will review existing models used for the prediction of fate and impact of aquaculture on environmental goods and services used throughout the world (Southall et al, 2004), and indicators by which they are compared (mostly developed for intensive forms of aquaculture where inputs/outputs of feed and chemicals are well known, though some have been adapted for developing aquaculture systems in SE Asia – (Ferreira et al, 2006). Next the suitability of these models and how they might be adapted for the specified case study species and countries will be assessed. In addition, this task will review and assess potential for wider systems modelling e.g. “ecological footprint models” (Jeroen et al, 1999; Kautsky et al, 1997), which will provide inputs for “life cycle analysis” (WP3). Environmental impacts identified as particularly relevant to the case study species will be reviewed to enable development of environmental standards and predictive comparison as part of the index for these species.

T4.2 Develop appropriate environmental models. Based on outcomes of T4.1, appropriate predictive environmental models of fate and distribution of the major aquaculture wastes will be adapted or developed for use in the case study systems. Specifically, they will be used to assess environmental impact of waste nutrient inputs and chemical contamination (linked with WP6) and hence carrying capacity of the wider environment to support goods and services (Telfer and Robinson, 2003). They will finally be used to (1) compare the different farming systems in terms of environmental sustainability for input into the overall food chain sustainability index and (2) to help develop management criteria as part of the food chain practices feeding into action research (WP9).

T4.3 Parameterisation and verification. The new models, developed or adapted, will be parameterised and empirically verified for each case-study system. For parameterisation, production parameters e.g. growth and feed/fertilizer inputs will be recorded over a full year. Results will be used in the initial mass balance model components to estimate outputs of nutrient and chemicals from the systems into the external environment. These and subsequent spatial model components will then be verified through direct comparison between modelled and actual sensitivity of biological components and the environment under consideration towards the different stressors. This will rely on empirical data collected in WP4 (nutrients) and WP7 (chemical contaminants) and bio-monitoring studies on the effects of the contaminants over the course of the (same) full year. Dialogue outcomes (WP8) and data gathered in WP7 will be used both to verify and simplify the chemical contaminants models, in order to ease their inclusion into certification frameworks targeting data-poor farming systems, while reducing costs of conformity assessment. Since the model outputs for chemical contaminants will be indicative (i.e. rather than accurate concentration predictions), no exact validation is envisaged, but rather a ranked risk level assessment.

T 4.4 Incorporate wider field inputs. The predictive power of aquaculture waste impact models are liable to significant error issues if they do not take into account inputs of nutrients or contaminants from external sources e.g. local agriculture. This will be achieved through GIS land-use and catchment modelling, incorporating the predictive spatial models developed in T4.2 and verified in T4.3 (Corner et al, 2006).This task will allow additional estimates to be integrated into the models either numerically and/or spatially through use of a GIS framework (T4.5).

T4.5 Interpretation and integration. Quantitative and qualitative spatial models from T4.1 to T4.4, and WP7 (environmental risk from chemicals), will be integrated within a GIS framework with land-use data, and area sensitivity models (such as, biodiversity indicators, designated areas of importance (Hunter et al, 2007)). The GIS framework will be used to form the basis of a spatial environmental indicator system which can grade or assess and compare production systems using indicators of environmental quality (EQSs), potential risk and sensitivity. This indicator system will be tested by relevant stakeholders in WP9 (action Research) and adapted to improve its utility for enhancing “food values” in terms of environmental sustainability (WP8). The spatial data, which is in a transferable format, will also allow its transfer to other information databases (e.g. WorldFish, FAO see WP10). A training event on model application is included in WP 12.


D4.1 (month 12) Report on review of environmental models and relevant environmental indicators

D4.2 (month 24) Verified quantitative numerical and spatial models, and GIS integrated impact and land-use models developed and strategically archived with full meta-data.

D4.3 (month 24) Simplified predictive models incorporated into an environmental indicator tool to be tested by relevant stakeholders’ including MSMEs in WP9.

Photo © Loni Hensler