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Dairy farmers face increasing pressure to decrease environmental impact while remaining economically viable. Adaptation of farm management practices in response to seasonal climate forecasts may be one means of achieving these objectives. This paper describes the interactive and iterative process by which farmers, researchers, extension agents, regulatory agencies, and other stakeholders collaborated to create, calibrate, and validate the Dynamic North Florida Dairy Farm model (DyNoFlo), a whole-farm decision support system to decrease nitrogen leaching while maintaining profitability under variable climate conditions. Participatory modeling may enhance the creation of adoptable and adaptable user-friendly models that include environmental, economic and biophysical components. By providing farmers, policy makers, and other stakeholders with a more holistic view of current practices, common ground among them was more easily identified and collaboration was fostered. Farmer values included willingness to be good environmental stewards when they are profitable. The participatory research and development process enhanced understanding of and potential adaptation to seasonal climate variability conditioned to the El Niño Southern Oscillation (ENSO) phases in light of increasing environmental regulations and economic challenges. Adoption of the collaboratively-developed DyNoFlo is expected to be higher than usual because stakeholders feel greater ownership of the final product. [ABSTRACT FROM AUTHOR]

The article focuses on the increase in soybean production in Paraguay. According to the article, the increase in production makes the country as the fourth largest soybean exporter in the world. As stated, differences in mean precipitation among El Niño Southern Oscillation (ENSO) phases were investigated under the context of crop development phases. Influences of ENSO phases on mean precipitation during planting and blooming, blooming and seed podding and from young pods to physiological maturity were explored through tests of difference in the central tendency. Moreover, mean precipitation between seed podding and crop maturity was found to be significantly lower during La Niña years than during El Niño years in one of the locations studied.

Evidence of increasing nitrogen levels in the Suwannee River Basin in North Florida demands a collaborative effort to find creative ways to reduce N pollution. This study explores the perspectives, perceptions, and attitudes of dairy farmers regarding adoption of climate forecasts as a potential way to mitigate the problem. These farmers are heavily scrutinized because of their nitrogen emissions. By contrasting scientists' pre-conceived attitudes about the usefulness of ENSO-based forecasts with dairy farmers' perceptions, gathered in a participatory and consensual manner, valuable lessons were learned. A deeper understanding of the day to day realities of dairy farming systems help researchers pinpoint management adaptations that are not only useful, but feasible, in light of improved seasonal climate forecasts. Furthermore, dairy farmers' perceptions regarding the use of seasonal climate information to mitigate the nitrate problem are critical for designing future dairy systems. [ABSTRACT FROM AUTHOR]

Abstract: Dairies are challenged to comply with stricter environmental regulations and remain economically viable. This paper studies the potential use of ENSO-based climate forecasts to reduce N leaching without reducing profits on North Florida dairies. A model was created to perform the analyses, the Dynamic North Florida Dairy Farm Model (DyNoFlo). DyNoFlo is an integrated dynamic model that incorporates Markov-chain simulation of cow flows and crop model simulations for historical climatic years (El Niño, La Niña, and Neutral years). It also includes optimization of managerial options. It responds to dairy-specific environment (climate and soils) and management (livestock management, waste management, crop systems management). The DyNoFlo model was designed to be a tool for producers, regulatory agencies, and extension services in addition to a research tool. Analyzing a typical North Florida dairy farm, it was found that N leaching was highest during winter El Niño years. Sandy soils were substantially more prone to leach N, and perennial grasses were better to prevent N leaching. The typical farm could decrease N leaching up to 23% in an El Niño year and still maintain profit by adjusting protein in the diet, confinement time for milking cows, and combining perennial grasses and forages in pastures and sprayfields. Application of the DyNoFlo model to small, medium, and large dairy farms showed that they could decrease their N leaching by 9, 20, and 25%, respectively, without reducing profits by varying management strategies according to ENSO phases. [Copyright &y& Elsevier]