Expert knowledge-based assessment of farming practices for different biotic indicators using fuzzy logic

Area of Science:

• Agricultural Science
• Ecology
• Environmental Science

Background:

• Assessing the impact of farming practices on biodiversity is crucial for sustainable agriculture.
• Existing methods may struggle with uncertain knowledge, such as expert judgment.

Purpose of the Study:

• To develop and present a modeling approach for the ex-ante assessment of farming practices concerning their risk to single-species biodiversity indicators.
• To evaluate the suitability of various farming practices for biodiversity conservation.

Main Methods:

• Utilized fuzzy-logic techniques to create a model tolerant to uncertain knowledge sources like expert judgment.
• Developed an Index of Suitability (IS) for five biotic indicators, calculated per farming practice.

Main Results:

• Modeled results demonstrate significant differences in farming practice suitability across various biotic indicators.
• Identified that farmers can select practices favoring biodiversity conservation.
• Highlighted that the approach can identify practices beneficial to multiple biotic indicators.

Conclusions:

• The fuzzy-logic modeling approach effectively assesses farming practices' risk to biodiversity indicators.
• The Index of Suitability (IS) aids in identifying farming practices that promote biodiversity conservation.
• The methodology supports informed decision-making for farmers seeking to enhance biodiversity on their land.