Dexi-Dairy indicator handbook - Sustainability tree and selected indicators for assessing European specialised dairy farms

The MilKey project aims at assessing the environmental, economic, and social sustainability of European dairy production systems, and at identifying ‘win-win’ farming practices for sustainable and greenhouse gas (GHG) optimised milk production. In this context, a holistic model was developed to evaluate the sustainability of specialised dairy farms and was entitled DEXi-Dairy. This model has the potential of aiding the identification of GHG and nitrogen (N) emission mitigation options and assessing their effects across multiple sustainability aspects. DEXi-Dairy covers the three sustainability pillars, i.e., environmental, economic, and social. Based on the ‘DEX’ multi-criteria methodology, the model is detailed under the form of a tree structure represented by four main hierarchical layers, i.e., branches, principles, criteria, and indicators. DEXi-Dairy was built following a participatory and interdisciplinary approach by MilKey project partners. It was then tested on three case study farms from Ireland, France, and Germany, respectively, using data from 2020. The DEXi-Dairy indicator handbook describes the sustainability tree and selected indicators to assess dairy production systems over a production year. Overall, this document can be used as a basis to replicate and expand the sustainability assessment framework developed as part of the MilKey project.acceptedVersio

The Value of Urban Farming in Oslo, Norway: Community Gardens, Aquaponics and Vertical Farming

Urban agriculture is increasingly recognized as an important sustainable pathway for climate change adaptation and mitigation, for building more resilient cities, and for citizens’ health. Urban agriculture systems appear in many forms – both commercial and non-commercial. The value of the services derived from urban agriculture, e.g., enhanced food security, air quality, water regulation, and high level of biodiversity, is often difficult to quantify to inform policymakers and the general public in their decision making. We perform a contingent valuation survey of four different types of urban agriculture Where the citizens of Oslo are asked about their attitudes and willingness to pay non-commercial (urban community gardens and urban gardens for work training, education and kindergartens) and for commercial (i.e. aquaponics and vertical production) forms of urban agriculture. Results show that the citizens of Oslo are willing to increase their tax payments to contribute to further development of urban farming in Oslo

Development of a Novel Framework for the Assessment and Improvement of Climate Adaptation and Mitigation Actions in Europe

The greenhouse gases (GHG) emissions in the European Union (EU) are mainly caused by human activity from five sectors—power, industry, transport, buildings, and agriculture. To tackle all these challenges, the EU actions and policies have been encouraging initiatives focusing on a holistic approach but these initiatives are not enough coordinated and connected to reach the much needed impact. To strengthen the important role of regions in climate actions, and stimulate wide stakeholders’ engagement including citizens, a conceptual framework for enabling rapid and far-reaching climate actions through multi-sectoral regional adaptation pathways is hereby developed. The target audience for this framework is composed by regional policy makers, developers and fellow scientists. The scale of the framework emphasizes the regional function as an important meeting point and delivery arena for European and national climate strategies and objectives both at urban and rural level. The framework is based on transformative and no-regret measures, prioritizing the Key Community Systems (KCS) that most urgently need to be protected from climate impacts and risks.publishedVersio

An Assessment of the Site-Specific Nutrient Management (SSNM) Strategy for Irrigated Rice in Asia

The site-specific nutrient management (SSNM) strategy provides guidelines for effective nitrogen, phosphorus and potassium management to help farmers make better decisions on fertilizer input and output levels in rice (Oryza sativa) production. The SSNM fertilizer recommendations are based on the yield goal approach, which has been frequently cited in empirical studies. This study evaluates the assumptions underlying the SSNM strategy for rice in the top rice-producing countries around the world, including India, Indonesia, the Philippines, Thailand, and Vietnam. Using a generalized quadratic production function, I explore whether major nutrients are substitutes as inputs and if there are complementarities between inorganic fertilizer and soil organic matter (SOM). The results suggest the relationships among major nutrients vary across sites—some inputs are complements, some are substitutes, and some are independent. The SOM also significantly affects the nitrogen fertilizer uptake. I conclude by suggesting that the SSNM strategy can be made to be more adaptive to farmer’s fields if these relationships are accounted for in the fertilizer recommendation algorithm

AN ASSESSMENT OF THE SITE-SPECIFIC NUTRIENT MANAGEMENT (SSNM) FOR IRRIGATED RICE IN ASIA

Site-specific nutrient management (SSNM) provides guidelines for effective nitrogen, phosphorus and potassium management to help farmers make better decisions on fertilizer input and output levels in rice production. I evaluated the assumptions underlying the SSNM strategy for rice in the top rice producing countries in the world: India, Indonesia, Philippines, Thailand and Vietnam. Using a generalized quadratic production function, I explored whether major nutrients are substitutes as inputs, and if there are complementarities between inorganic fertilizer and soil organic matter (SOM). I also used non-nested hypothesis framework to contrast the quadratic model against the linear von Liebig model. Results showed that the relationships among major nutrients vary across sites – some inputs are complements, some are substitutes, and some are independent. In addition, I found that the SOM significantly affects the economic returns to nitrogen fertilizer inputs. Accounting for these relationships in the fertilizer recommendation algorithm can make the SSNM strategy more adaptive to farmer’s fields. In areas where soils have limiting organic matter content, fertilizer subsidy or distribution might not be appropriate means to support rice production. Increased rice productivity can be achieved through integrated soil fertility management and adoption of soil conservation technologies

The Origins, Implications, and Consequences of Yield-Based Nitrogen Fertilizer Management

We examine the origins, implications, and consequences of yield-based N fertilizer management. Yield-based algorithms have dominated N fertilizer management of corn (Zea mays) in the United States for almost 50 yr, and similar algorithms have been used all over the world to make fertilizer recommendations for other crops. Beginning in the mid-1990s, empirical research started to show that yield-based rules-of-thumb in general are not a useful guide to fertilizer management. Yet yield-based methods continue to be widely used, and are part of the principal algorithms of nearly all current “decision tool” software being sold to farmers for N management. We present details of the theoretical and empirical origins of yield-based management algorithms, which were introduced by George Stanford (1966, 1973) as a way to make N fertilizer management less reliant on data. We show that Stanford’s derivation of his “1.2 Rule” was based on very little data, questionable data omissions, and negligible and faulty statistical analysis. We argue that, nonetheless, researchers, outreach personnel, and private-sector crop management consultants were obliged to give some kind of N management guidance to farmers. Since data generation is costly, it is understandable that a broad, “ball park” rule-of-thumb was developed, loosely based on agronomic principles. We conclude by suggesting that technology changes now allow for exciting new possibilities in data-intensive fertilizer management research, which may lead to more efficient N management possibilities in the near future.publishedVersio

An Empirical Investigation of the Stanford’s “1.2 Rule” for Nitrogen Fertilizer Recommendation

We evaluate an old and widely accepted rule of thumb for fertilizer management in corn production: apply 1.2 pounds of nitrogen fertilizer per bushel of corn expected. This “1.2 Rule” has dominated fertilizer management recommendations for almost fifty years, and similar algorithms have been used all over the world to make fertilizer recommendations for other crops. Here we show that the 1.2 Rule only makes economic sense if the production satisfies two restrictions: (1) to be of the von Liebig functional form, i.e. the function has a “kink” and a “plateau,” and (2) the kinks of the von Liebig response curves for different growing conditions lie on a ray out of the origin with slope 1.2. Non-linear estimation techniques and non-nested hypothesis framework are used to test if the 1.2 Rule satisfies these restrictions. We conclude that there exists little scientific justification of the 1.2 Rule, and that its long-term and widespread use basically resulted from its long-term and widespread use

Testing the Validity of Stanford's 1.2 Rule for N Fertilizer Recommendation

We evaluate an old and widely accepted rule of thumb for fertilizer management in corn production: apply 1.2 pounds of nitrogen fertilizer per bushel of corn expected. This “1.2 Rule” has dominated fertilizer management recommendations for almost fifty years, and similar algorithms have been used all over the world to make fertilizer recommendations for other crops. Here we show that the 1.2 Rule only makes economic sense if the production satisfies two restrictions: (1) to be of the von Liebig functional form, i.e. the function has a “kink” and a “plateau,” and (2) the kinks of the von Liebig response curves for different growing conditions lie on a ray out of the origin with slope 1.2. Non-linear estimation techniques and non-nested hypothesis framework are used to test if the 1.2 Rule satisfies these restrictions. We conclude that there exists little scientific justification of the 1.2 Rule, and that its long-term and widespread use basically resulted from its long-term and widespread use

Impacts of Site-Specific Nutrient Management in Irrigated Rice Farms in the Red River Delta, Northern Vietnam

This study estimates the impact of the adoption of SSNM practices on rice production of smallholder farmers in Vietnam using cross-section household data (n = 371) gathered from the provinces of Ha Nam and Ha Tay in the Red River Delta. Specifically, it investigates the economic impact of SSNM, focusing on SSNM-induced changes in the yield, profit, nitrogen use and pesticide use of farmers. The instrumental variables (IV) approach is used to achieve this objective because it deals with endogeneity and self-selection bias present in the study. SSNM improves the paddy yield of farmers by 0.6 tons per hectare and profit by $150 per hectare. It has no statistically significant effect on the amount of pesticide and nitrogen use of farmers. The higher profits for adopters versus non-adopters of SSNM arise from increased grain yield rather from reducing fertilizer costs and pesticide costs. Results of the impact analysis identified several directions that can be pursued to improve further the adoption of SSNM