Conceptual Modeling for Adaptive Environmental Assessment and Management in the Barycz Valley, Lower Silesia, Poland
Abstract
:Introduction
Adaptive Management Framework with Conceptual Modeling
- a)
- An open, participatory and recursive process both for policy formulation and indicators selection is used instead of top-down control.
- b)
- Systems analysis including many feedbacks between sectors is performed, instead of narrow technical analysis.
- c)
- Conceptual, qualitative modeling is used instead of formal, quantitative modeling.
Agreeing on Issues and Objectives
Mapping Assumptions
- a)
- Identifying Variables and Interrelationships. Here conceptual modeling is used to map the underlying assumptions about the linkages and causality in the system. We have used the qualitative system dynamics methodology with causal loop diagrams as mapping tool.
- b)
- Assessing Major Uncertainties and Unknowns. Disagreements reveal gaps in understanding. Uncertainties are pondered to the point when they can be clearly stated as hypotheses.
Choosing Indicators
- a)
- Identifying Key Variables. Using the conceptual model developed in 2a, most important (key) variables are selected by considering the number of interactions and/or delays as well as employing a conservative rule that each feedback loop should be represented in the set of indicators by one of its variables.
- b)
- Deriving Indicators for Each Variable. Each key variable should be represented by at least one indicator. Often multiple indicators are needed to capture the range of values and qualities associated with a variable.
- c)
- Scoring Indicators with Three Sets of Criteria. The scoring process must be streamlined and simple enough to be easily understood and relatively rapid to accomplish. Criteria should also help one examine what makes an indicator useful and convincing. To meet these goals a set of three criteria was employed: importance (work group’s perspective), compellingness (stakeholders’ perspective) and measurability.
- d)
- Selecting a Final Set of Sustainability Indicators (based on cumulative scoring).
Defining Policies
Implementation
Monitoring and Evaluation
Project in the Barycz Valley
General Setting
Project Execution
- a)
- Differences (and agreements) in opinions were articulated much more precisely.
- b)
- Gaps in understanding were discovered more efficiently.
Regional Sustainability Model
Sustainability Indicators
Conclusions
Key Variables | Indicators |
---|---|
Environmental Quality | Biodiversity – number of species |
Water quality | |
Percentage of viable habitat (green area) | |
Environmentally Friendly Farms (EFF) | Ratio EFF/Total (Number) |
Ratio EFF/Total (Area) | |
Conversion rate | |
Revenues from Agri-Environmental Programs | Percentage of maximum subsidy |
Percentage of minimum yearly income | |
Green Local Product (GLP) Production | Sales revenues as percent of total sales per firm |
Number of people employed | |
Number of firms | |
Profits from GLP | Total amount earned in region |
Average profitability from GLP per firm | |
Profits from Environmentally Friendly Crops | Total amount earned in region |
Average profitability from env. friendly crops per farm | |
Profits from Green Tourism (GT) | Total amount earned from GT in region |
Average profitability from GT per firm | |
Organizational Support for Environmentally Friendly Farms | Hours of work on projects |
Perceived support by farmers | |
Brand Attractiveness | Brand awareness and acceptation |
Support for Green Local Products | Hours of work on projects |
Perceived support by green local producers | |
Social Support for Environmental Standards | Percentage of population that supports environmental standards |
Acknowledgments
Appendix 1 – Feedback Loops in Regional Sustainability Model
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Magnuszewski, P.; Sendzimir, J.; Kronenberg, J. Conceptual Modeling for Adaptive Environmental Assessment and Management in the Barycz Valley, Lower Silesia, Poland. Int. J. Environ. Res. Public Health 2005, 2, 194-203. https://doi.org/10.3390/ijerph2005020001
Magnuszewski P, Sendzimir J, Kronenberg J. Conceptual Modeling for Adaptive Environmental Assessment and Management in the Barycz Valley, Lower Silesia, Poland. International Journal of Environmental Research and Public Health. 2005; 2(2):194-203. https://doi.org/10.3390/ijerph2005020001
Chicago/Turabian StyleMagnuszewski, Piotr, Jan Sendzimir, and Jakub Kronenberg. 2005. "Conceptual Modeling for Adaptive Environmental Assessment and Management in the Barycz Valley, Lower Silesia, Poland" International Journal of Environmental Research and Public Health 2, no. 2: 194-203. https://doi.org/10.3390/ijerph2005020001