Using the Sustainability Monitoring and Assessment Routine (SMART) for the Systematic Analysis of Trade-Offs and Synergies between Sustainability Dimensions and Themes at Farm Level
Abstract
:1. Introduction
2. Materials and Methods
2.1. SMART-Farm Tool
2.1.1. Determining the Sustainability Performance
2.1.2. Indicator Selection
- Relevance: The indicator needs to have a logical or scientifically justifiable direct impact on at least one of the sub-themes, they may, however, be relevant for several sub-themes. This should not to be confused with the geographic/farm-type relevance-check of indicators in the course of the farm assessment mentioned above.
- Comprehensiveness: The indicator set should cover the most relevant aspects of the themes and is applicable to all farm types, regions and farming systems (conventional, integrated, organic, etc.).
- Interpretability: The indicators need to be interpretable and consequences for farm management need to be directly deducible for farmers, scientists and advisors.
- Data quality: The information gathered on the farm needs to enable the auditor to assess the indicator reliably.
- Efficiency: The time required for data collection needs to be minimized, therefore, SMART comprises indicators that are straightforward to determine for which data is globally accessible.
2.1.3. Determination of Indicator Weights
2.2. Application of the SMART-Farm Tool on Sample Farms
2.2.1. Procedure for Assessing Farms with the SMART-Farm Tool
2.2.2. Selection of Farms
2.3. Determination of Trade-Offs and Synergies
3. Results
3.1. Results of Sustainability Assessments in Different Countries and Farm Types
3.1.1. Governance Dimension
3.1.2. Environmental Dimension
3.1.3. Economic Dimension
3.1.4. Social Dimension
3.2. Trade-Offs and Synergies between Dimensions and Sub-Themes
4. Discussion and Conclusions
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
Abbreviations
SMART | Sustainability Monitoring and Assessment Routine |
SAFA | Sustainability Assessment of Food and Agriculture Systems |
MCA | Multi-Criteria Analysis |
References and Notes
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Scale | Description: This indicator has… |
---|---|
+3 | …a strong positive impact on the degree of goal achievement of the subtheme |
+2 | …a medium positive impact on the degree of goal achievement of the subtheme |
+1 | …a slight positive impact on the degree of goal achievement of the subtheme |
0 | …neither a positive nor a negative impact on the degree of goal achievement of the subtheme or is ambiguous |
−1 | …a slight negative impact on the degree of goal achievement of the subtheme |
−2 | …a medium negative impact on the degree of goal achievement of the subtheme |
−3 | …a strong negative impact on the degree of goal achievement of the subtheme |
Type of scale | Indicator Example |
---|---|
Yes/No | Is overtime compensated at this farm (in terms of time off or overtime pay)? (Indicator 437) |
Number | How many active substances of pesticides are used per year? (Indicator 377.1) |
Percentage | What proportion of the electricity consumed is derived from renewable resources? (Indicator 185) |
Rating Scale 1–5 | How many days of further education or training (per person) were taken during the last year (including farm manager and employees)? Further training: External person on the farm or participation in external, thematic events (excluding trade shows). Total number of days spent for further training during last year on average per person “1 ≤ 0.5 days per year/person 2 = 0.5–1 day per year/person, 3 = 1 day per year/person, 4 = 2 days per year/person, 5 ≥ 2 days per year/person” (Indicator 72) |
Country | Farm Size | Farming System | Crops | Livestock |
---|---|---|---|---|
Switzerland | 11.7 | Organic | Vegetables (greenhouse), grassland | no |
Switzerland | 52.1 | Conventional | Grassland, pasture, maize | Cattle |
Austria | 27.7 | Organic | Barley, wheat, rye, spelt, triticale, peas/oat, grassland, potatoes | Cattle, chicken |
Austria | 160.0 | Organic | Maize, tuberous vetchling, triticale, wheat, vetch | Cattle |
Germany | 172.7 | Conventional | Rapeseed, wheat, barley, maize, clover grass | Cattle |
Germany | 46.0 | Organic | Grassland, orchards | Cattle |
Kenya | 2.4 | Conventional | Bananas, avocados, mangos, french beans, spinach, tomatoes, kale, custard apple, pasture | Chicken, sheep, goats, cattle |
Kenya | 0.7 | Conventional | Tea, tree tomatoes, cabbage, carrots, chamomile, arabicum flowers, maize, napier grass, eucalyptus | Chicken, goats |
Ghana | 2.4 | Conventional | Maize, water melon, sweet potatoes, soybeans, rice, onion, millet, spinach | Chicken, Guinee fowls, sheep, goats |
Ghana | 4.6 | Conventional | Cocoa, plantain, pepper, cassava, maize, fallow, grassland | Chicken, sheep, goats |
Costa Rica | 275.7 | Conventional | Bananas | no |
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Schader, C.; Baumgart, L.; Landert, J.; Muller, A.; Ssebunya, B.; Blockeel, J.; Weisshaidinger, R.; Petrasek, R.; Mészáros, D.; Padel, S.; et al. Using the Sustainability Monitoring and Assessment Routine (SMART) for the Systematic Analysis of Trade-Offs and Synergies between Sustainability Dimensions and Themes at Farm Level. Sustainability 2016, 8, 274. https://doi.org/10.3390/su8030274
Schader C, Baumgart L, Landert J, Muller A, Ssebunya B, Blockeel J, Weisshaidinger R, Petrasek R, Mészáros D, Padel S, et al. Using the Sustainability Monitoring and Assessment Routine (SMART) for the Systematic Analysis of Trade-Offs and Synergies between Sustainability Dimensions and Themes at Farm Level. Sustainability. 2016; 8(3):274. https://doi.org/10.3390/su8030274
Chicago/Turabian StyleSchader, Christian, Lukas Baumgart, Jan Landert, Adrian Muller, Brian Ssebunya, Johan Blockeel, Rainer Weisshaidinger, Richard Petrasek, Dóra Mészáros, Susanne Padel, and et al. 2016. "Using the Sustainability Monitoring and Assessment Routine (SMART) for the Systematic Analysis of Trade-Offs and Synergies between Sustainability Dimensions and Themes at Farm Level" Sustainability 8, no. 3: 274. https://doi.org/10.3390/su8030274