Responding to stakeholder's demands for climate information: from research to applications in Florida

Previous research shows that Florida's climate and agricultural production are influenced by the El Niño-Southern Oscillation, suggesting that farmers and ranchers might use new methods of climate forecasting to modify management, increase profits and reduce economic risks. The purposes of this paper are to describe the framework used by a Florida Consortium (FC) of researchers to assess the potential use of climate forecasts in agricultural decision-making and to summarize what was learned in the research process. The framework includes components for generation, communication and use of climate information as well as an implementation and evaluation component. Results showed that winter months are affected most by ENSO phase (higher rainfall and lower temperatures in El Niño years and the opposite during La Niña years). Yields of most crops were significantly associated with ENSO phase as were prices of some commodities. Through various mechanisms of interacting with farmers, ranchers, and extension faculty, we learned that interest in climate forecasts varied widely from highly optimistic to skeptical, and that these clients had good ideas of how to vary management if they have good forecasts. Case studies aimed at understanding potential value and risks associated with use of climate forecasts were conducted for winter fresh market tomato, cow-calf operations, and peanut production. Analytical results, confirmed by interactions with clients, showed significant value in using climate forecasts to alter specific decisions. Risks of using climate information varied among commodities, with considerable risk found in tomato due to the strong link between production and price. Perhaps the most important lesson learned was the importance of engaging trusted advisors in research and outreach efforts. A major output of the project was the close cooperation established between the FC and the Florida Cooperative Extension Service. Prospects for sustaining a climate information program in Florida are high due to joint research and extension initiatives.     

Land allocation conditioned on El Niño-Southern Oscillation phases in the Pampas of Argentina

The El Niño-Southern Oscillation (ENSO) contributes to the vulnerability of crop production to climate variability in the Pampas region of Argentina. Predictability of regional climate anomalies associated with ENSO may provide opportunities to tailor decisions to expected climate, either to mitigate expected adverse conditions or to take advantage of favorable conditions. Model analysis was used to explore the potential for tailoring land allocation among crops to ENSO phases at the farm scale in two sub-regions of the Pampas. The model identifies as a function of risk preferences and initial wealth the crop mix that maximizes expected utility of wealth at the end of a 1-year decision period based on current costs and prices, and crop yields simulated for each year of historical weather. The model reproduced recent land allocation patterns at the district scale under moderate risk aversion, and predicted increasing diversification with increasing risk aversion. Differences in land allocation among ENSO phases were consistent with known climate response to ENSO, and crop response to water availability. Tailoring land allocation to ENSO phase increased mean net farm income between US$5 and $15 ha⁻¹ year⁻¹ relative to optimizing the crop mixture for all years, depending on location, risk aversion and initial wealth. The relationship between potential value of ENSO information and risk aversion was not monotonic, and differed between locations. Crop mix and information value also varied with crop prices and initial soil moisture. There are potential financial benefits of applying this approach to tailoring decisions to ENSO phases.     

Agent-based social simulation: a method for assessing the impact of seasonal climate forecast applications among smallholder farmers

Seasonal climate forecasts provide probabilistic information on future climate on timescales of two to three months. Where this information is not presently used it is difficult to evaluate the impact it might have. In order to justify disseminating the information to marginal groups it is important that the potential impact of the forecast is explored so that the negative and positive effects are at least partially appreciated before use of the information is widely promoted. We use an agent-based social simulation model, based on empirical evidence from field work in Lesotho, to assess the impact of using seasonal forecasts among smallholder farmers. The impact of using the forecast depends on the agents' initial household characteristics, what options they choose in responding to the forecast and the trust they place in the forecast (which in turn depends on their ability to learn and to follow their neighbours). Interaction of climate, crop productivity and social factors determines how much household-agents benefit or lose, evaluated in terms of crop yields and likelihood of exhausting food storage. Adoption of the forecast has the potential to decrease starvation among marginal household-agents but poor forecasts may do more harm than good. This work suggests that if forecasts are not correct more than 60–70% of the time, then they are unlikely to benefit poor farmers. Poor forecasts, or forecasts that fail badly, when they do fail, lead to longer adoption timescales for forecast use. Further investigation into the impact of the forecast at the village level is encouraged before dissemination is actively pursued without appreciating potential impacts.     

Using hierarchical systems aggregation to model the value of information in agricultural systems: An application for climate forecast information

The process of interdisciplinary research in aggregating sub-system models to model larger systems is disucussed and applied to valuing midwestern (USA) crop climate forecasts. Elements of climate forecast information schemes and characteristics of users and their environment which give rise to or restrict climate forecast information value in corn and soybean production are identified. Methods of varying these elements are applied to determine their effect on the value of climate forecast schemes.     

Maize ethanol feedstock production and net energy value as affected by climate variability and crop management practices

Ethanol from various plant resources, especially maize, is increasingly being used as a substitute for fossil fuels. The production potential of ethanol from maize varies with weather and climatic conditions and crop management practices. The merits and prospects of ethanol production have been evaluated based on its impact on greenhouse gas emissions, economic viability and national energy security. The net energy value (NEV), i.e. the output energy after all non-renewable energy inputs have been accounted for, is a measure of energy gain. At the same time, the NEV can be an indicator for the long-term sustainability of bio-ethanol production, regardless of other conditions e.g. climate change scenarios, global trade restrictions, or local variability in natural resources such as water availability. Crop management practices directly affect the NEV of ethanol. Moreover, both crop management practices and climate variability affect the NEV through the grain yield. The objective of this study was to assess the impact of crop management practices and climate variability on grain yield of maize for ethanol production and ethanol NEV for conditions that represent the southeastern USA. Maize grain yield was simulated with the dynamic crop growth model CSM–CERES–Maize and ethanol NEV was calculated using the simulated yield levels and crop management practices. The simulations were conducted for conditions representing Mitchell County, Georgia, USA, using weather data from 1939 to 2006 and local soil profile information. The impact of irrigation, nitrogen fertilizer, planting date and El Niño Southern Oscillation (ENSO) phases were determined for the maize cultivars DeKalb DKC 61-72 (RR2), Pioneer 31D58 and Pioneer 31G98. Crop management practices and ENSO phase had a significant impact on ethanol feedstock production and NEV. The NEV of ethanol produced from irrigated maize was more than two times higher and varied less than the NEV of ethanol from rainfed maize. NEV of ethanol produced from maize grown during La Niña years was significantly higher than maize grown during El Niño years, both under rainfed and irrigated conditions. This study showed the importance of crop management practices and climate variability on ethanol feedstock productivity and long-term energy sustainability as assessed by the NEV. We discuss methods of implementing the findings of this study in practical farming e.g. through market mechanisms and governmental initiatives.     

Analyzing the effects of risk and uncertainty on optimal tillage and nitrogen fertilizer intensity for field crops in Germany

This study provides a risk analysis of long-term field experiments in Germany (Bavaria) on various field crops (potato, wheat and corn), grown in rotation, under a variety of different tillage and nitrogen management systems. The field experiment provided yield and input data for the analysis, and was combined with market data relevant to the case-study region. The emphasis of the analysis is on the interaction between risk and tillage and nitrogen strategies. Over the whole rotation (corn-wheat-potato-wheat), conventional tillage combined with conventional nitrogen rates is optimal, both for risk-neutral and risk-averse farmers. Although less intensive management practices involve lower risk, the decrease in risk premium is not sufficient to alter the ranking of strategies, even for farmers with higher levels of risk aversion. Reducing nitrogen rates would be costly to farmers, especially under reduced or shallow tillage. Decoupled farm subsidies within the expected utility model show that even for a scenario with no subsidies our conclusions do not change.     

Gains from crop diversification in the Sudan Gezira scheme

Land allocation in Gezira irrigation scheme (the Gezira) has, for the most part, been based on the political judgement of the government rather than economic criteria. This paper determined optimum crop combinations for the Gezira using the mean-variance (M-V) model. This large-scale gravity-irrigated project which was started for export cotton cultivation on 27,372 feddan (11,496 ha) in 1927 has now expanded to over two million feddan, and has a multi crop production system. Sources of production uncertainty include government control of prices, often announced after planting, and crop area in favor of cotton. Diversification was analyzed under various levels of risk using, in contrast to what is in the reviewed literature, both cross sectional and time series farm level data. The cross-sectional data comprised of net farm returns of 100 farmers for the 1987/1988 season, and the time series data were average net farm returns from the same area from 1971 to 1988. Cropping decisions in the Gezira are mostly based on cross-sectional data from a sample of tenants in the preceding season. This paper estimated variance and covariance parameters of observed net margins of both sets of data and found significant differences in the results. The certainty equivalence results used to evaluate crop diversification showed that current policies of controlling crop acreage lead to inefficient land use; and that farmers diversify into wheat and groundnuts out of cotton when cross-section data were used; and from groundnuts to cotton and wheat when time series data were used.     

Irrigation management: An information system approach

An information system is under development to enable both farmers and extension officers to investigate the dynamics of irrigation decision making in an uncertain environment. The system is designed to provide a simulation of an individual farm unit with each enterprise within the farm being represented by an individual enterprise module. The system can, therefore, be tailored to the requirements of the particular user. Details of the system and its development and use in the New Zealand context are described.     

Demand management of groundwater with monsoon forecasting

This paper presents an operational approach to setting prices for groundwater in accordance with the interannual variability of monsoon rainfall and the dynamic cost of groundwater use to society. The pricing system is designed for the state of Tamil Nadu, India, where groundwater is largely unregulated and the electricity for pumping is heavily subsidized. Depletion of aquifers during the primary growing season causes environmental damage and drying of wells. The proposed price-setting system estimates the marginal social cost of groundwater use based on the current state of aquifer storage and the forecast of the coming monsoon. Prices are set prior to onset of the monsoon so farmers can plan crop rotations according to the expectation of seasonal rainfall as reflected in the pricing signal. During years that forecasts accurately characterize the probability distribution of monsoon outcomes the market signal encourages economically efficient use of the resource. When monsoons differ from the expected outcome farmers are cushioned by ancillary effects of the pricing system.     

Policies to support economic and environmental goals at farm and regional scales: Outcomes for rice farmers in Southern India depend on their resource endowment

Improving water use and nitrogen efficiencies is of overall importance to society at large - to conserve scarce water resources and prevent environmental pollution. Efficient cultivation practices for rice which had no yield penalty were not adopted by farmers because of the open access to water free of charge. Well-chosen combinations of policy measures are thus needed to stimulate adoption of new cultivation practices. We developed a multi-objective linear programming (MGLP) model to explore the impact of: (i) modified rice cultivation including water-saving irrigation on farm profit; (ii) water pricing and water quota government policies on adoption of modified rice cultivation by farmers; (iii) a combination of (i) and (ii) to achieve the objectives of both farmers and society at large, and (iv) to study the trade-offs between income, water and nitrogen use. The analysis was carried out on four rice-based farm types for the state of Tamil Nadu, South India. Model results showed that observed farm profit of all four farm types could be increased using current practices simply by optimizing land use for specific crops. Adoption of modified rice cultivation further increased farm profit. Water-saving practices were selected only when water pricing was introduced. Farm profits were reduced even at low water prices but were compensated by farmers through adoption of modified rice cultivation. The combination of policies that stimulate adoption of modified rice cultivation was effective in achieving both increased farm income and water savings. The required water prices differed across farm types and seasons and impacted poor resource-endowed farmers the most. Providing water quotas could protect the poor resource-endowed farmers. The model helped to identify the optimal water price and water quota for each farm type to achieve both the objectives of farmers and society at large. Opportunities for reducing water use and avoiding environmental pollution at acceptable profits are available for all farm types, but need to be tailored to the farmers’ resource endowments.     

Operational forecasting of South African sugarcane production: Part 2 – System evaluation

The performance of a model-based crop forecasting system is assessed in this paper. The operational error associated with a forecast originates from two independent sources. First, the system error reflects the system’s ability to match yields simulated from historic data to actual yields. The system error is due to factors such as model and data inaccuracies, incorrect aggregation assumptions and the system’s inability to reflect all the compelling factors, like pest and diseases, climatic disasters and suboptimal crop management. Second, the climate error reflects inaccuracies of the operational yield forecasts associated with the assumed future climate. The purpose of the study was to assess the performance of a system to forecast sugarcane yields by quantifying the accuracy of (1) estimates based on complete sets of actual weather data and (2) operational system forecasts with incomplete sets of actual weather data. Estimates and forecasts were compared to actual yields recorded from 1980 to 2004. Industry production data from 1980 to 2002, corrected for various time trends, were used to calculate the system error for mills and the industry. The skill of estimation was calculated by comparing the size of the system error with the observed seasonal variation. On an industry scale, estimates captured 57% of inter-annual variability. Production at most mills was also simulated well, with some exceptions in irrigated areas. Operational forecasts issued between January and April for the industry between 1998 and 2004 had an average forecast error of 4.0%, which is 2.2% lower than the equivalent mill committee forecasts. The study provides ample evidence that industry stakeholders could use information from this system to enhance their management of sugarcane production.     

Perceived environmental uncertainty in Dutch dairy farming: The effect of external farm context on strategic choice

This paper explores the way in which dairy farmers perceive their environment (PE), i.e., the external context of their farm, and the uncertainty (PEU) this poses to them. The environment is defined using the STEP concept (society, technology, economy and politics) and Porter’s five forces model. The relationship between the perception of the external farm environment and the strategy farmers choose for their farm is quantified to gain insight into the effect of the external farm environment on decision-making. Data from a survey of 103 Dutch dairy farmers was analyzed using regression analysis. The results indicate that environmental uncertainty is not related to complexity or dynamism, but to the illiberality (i.e., intolerance, hostility) of the external farm environment. The institutional environment is considered especially illiberal, thus causing high uncertainty. Farmers with high PEU are more likely to choose a diversification strategy, while low perceived uncertainty results in a process-control strategy for the farm. A growth strategy is not affected by perceived environmental uncertainty. The PE and PEU approach is new in agricultural research and shows that the farmer’s view on the external environment is a key issue for decision-making on farms The significant relationship between the perceived uncertainty caused by the external farm environment and farm strategies shows that to get a good understanding of the farm, farming system boundaries should be expanded to incorporate the effect of the external farm environment on decision making. Reduction of uncertainty will enhance decision-making because instead of farming within an uncertain context, risk management practices can be used.     

Realizing the potential benefits of climate prediction to agriculture: issues,approaches, challenges

Advances in our ability to predict climate fluctuations months in advance suggest opportunity to improve management of climatic risk in agriculture, but only if particular conditions are in place. This paper outlines prerequisites to beneficial forecast use; highlights key issues, approaches and challenges related to each; and suggests an evolutionary strategy. The first prerequisite is that forecast information must address a need that is both real and perceived. Second, benefit arises only through viable decision options that are sensitive to forecast information. Third, benefit depends on prediction of the components of climate variability that are relevant to viable decisions. Fourth, appropriate forecast use requires effective communication of relevant information. Finally, sustained use requires institutional commitment and favorable policies. It is useful to consider three phases of effort: an exploratory phase to gain understanding and assess potential, a pilot phase characterized by co-learning between researchers and target decision makers, and an operational phase focusing on engaging and equipping relevant institutions. Although examples of use and potential use, and advances in institutional support, are cause for optimism, use of climate prediction by agriculture s still too new to support strong generalizations about its value.     

Quantitative analysis and forecasting of monthly prices of lumber and flooring products

Four time series of monthly prices of oak and softwood lumber and flooring are analysed using the autoregressive integrated moving average technique. The principles of the method are exposed and one model is estimated for each time series. The steps in model formulation, estimation and diagnostic checking are described in detail for the series of oak lumber prices. All series are stationary after a first order differencing. The behaviour of monthly prices of softwood products is well described by pure autoregressive models while the oak product prices require full autoregressive integrated moving average models. The models obtained generate one-month forecasts which are significantly more accurate than those obtained from a no-change extrapolarive model, except in the case of softwood flooring prices for which the behaviour is close to a random walk. Six-month forecasts are computed for each series with corresponding confidence intervals. An adaptive forecasting procedure is used to revise multiple-month forecasts after the errors on the first month forecast have been observed.     

A seasonal model of contracts between a monopsonistic processor and smallholder pepper producers in Costa Rica

We model the contractual arrangements between smallholder pepper (Piper nigrum L.) producers and a single processor in Costa Rica. Producers in the El Roble settlement sell their pepper to only one processing firm, which exerts its monopsonistic bargaining power by setting the purchase price of fresh pepper. It also sets quality norms that result in the rejection of considerable amounts of the pepper produced by individual farmers. Because the firm is not able to produce its own raw pepper and requires a sufficiently stable flow of the fresh product to be processed into high quality white pepper, it usually relies on contracts with individual smallholders. Nevertheless, the latter considered collective marketing and took the initiative to propose a group contract with the firm. Such a contract increases the producers’ bargaining power vis-à-vis the processing firm and reduces rejection rates as more care is taken when transporting the pepper to be processed. Although a group contract causes the firm to lose part of its monopsonistic rents, it also reduces transaction costs as only one contract must be negotiated instead of many. Both the firm and the producers benefit, yet from the very beginning of the association, the producers breached the group contract. We have used a mixed integer linear model which, given a set of constraints, maximises the weighted sum of the expected incomes of the firm and producers. We modelled the contract chosen by the firm and the producers according to the conditions included, such as minimum income requirements and risk considerations of both processor and farmers. We calibrated the model with data from pepper producers and the firm in El Roble. The results show that at different fresh pepper prices, the contract preferred changes with the bargaining power attributed to the firm and smallholders. However, in general, it can be concluded that fresh pepper prices high enough to cover the costs, for the farmers, of a group contract lead to lower rejection rates, and thus to more pepper of an acceptable quality, increasing the incomes of both the processor and the farmers. This is also of interest in agricultural policy-making.     

Stochastic efficiency analysis of deficit irrigation with standard risk aversion

The main objective of this research was to develop an expected utility optimisation model to economically evaluate deficit irrigation within a multi-crop setting while taking into account the increasing production risk of deficit irrigation. The dynamic problem of optimising water use between multiple crops within a whole-farm setting when intraseasonal water supply may be limited was approximated by the inclusion of multiple irrigation schedules into the optimisation model. The SAPWAT model (South African Plant WATer) was further developed to quantify crop yield variability of deficit irrigation while taking the non-uniformity of irrigation applications into account. Stochastic budgeting procedures were used to generate appropriately correlated matrixes of gross margins necessary to incorporate risk into the water use optimisation model. Special care was taken to represent risk aversion consistently between the alternatives through the use of a new procedure to standardise values of absolute risk aversion. The model was applied to study the impact of increasing levels of risk aversion on the profitability of deficit irrigation under limited water supply conditions. The main conclusion from the analyses was that although deficit irrigation was stochastically more efficient than full irrigation under limited water supply conditions, irrigation farmers would not willingly choose to conserve water through deficit irrigation and would be expected to be compensated to do so. Deficit irrigation would not save water if the water that was saved through deficit irrigation were used to plant larger areas to increase the overall profitability of the strategy. Standard risk aversion was used to explain the simultaneous increasing and decreasing relationship between the utility weighted premiums and increasing levels of absolute risk aversion and was shown to be more consistent than when constant absolute risk aversion was assumed.     

Heterogeneity in farmers’ production decisions and its impact on soil nutrient use: Results and implications from northern Nigeria

Sustainable use (in terms of nutrients) of soil resources by farmers in Sub-Saharan Africa is constrained by institutions and markets. This paper explores the case of northern Nigeria, by using a combination of multi-attribute utility theory and bio-economic modelling. This approach allowed us to identify heterogeneity in production strategies and to quantify its effect on the use of soil nutrient resources.We find that farmers with larger land holdings place more emphasis on gross margins in their utility function, while those with larger holdings of fertile fadama fields place more emphasis on sustainability. Risk aversion, operationalised through variance minimization, appears an important attribute in the utility function of many farm households that are more dependent on agriculture for their overall income.A regression analysis shows that differences in production strategies significantly affect nutrient balances, but also shows that such effects are heterogeneous across locations. We find more favourable nutrient balances for some of the more market-oriented farm households who place more emphasis on sustainability. In farm plans of the most risk-averse households, the production of cereals for subsistence consumption dominates and leads to negative soil nutrient balances, especially for potassium.Farmers who place a large importance on gross margins are likely to benefit most from policies aimed at enhancing profitability through improving functioning of markets. The large group of risk-averse farmers will have the largest immediate gain in utility from policies and technologies aimed at reducing production risk in high-value crops. Additional policies aimed at creating a stronger market-oriented production by the least-endowed farm households could play a role in reducing intensity of soil fertility mining. Under these conditions, the efficient cropping pattern shifts partially from cereal cropping to high-value crops, associated with higher input use.The main results are similar to those in other studies, although some of the nutrient balances are less negative. The results do appear to be sensitive to the type of cropping activities included in the analysis, and additional methodological research is required. Extensions of the used method should further account for temporal and spatial differences in soil fertility, leading to differences in nutrient uptake and production, as well as potential temporal heterogeneity in production strategies.     

Modelling the effect of household composition on the welfare of limited-resource farmers in Coastal Cañete,Peru

Family composition and its changes over time are believed to have a major impact on the welfare and sustainability of small-scale, limited resource farm households. In order to understand and test the effects of household composition on overall farm household well-being, a simulation model was developed based on information from 60 small farms from the Coastal Cañete Valley, Peru. The model accounts dynamically for the birth, age and death of household members and for crop, livestock, and economic activities. A representative farm with ten scenarios representing the range of household composition was simulated. Results in 10, 20 and 40-year runs showed that family composition has a large influence on economic stress. Families with fewer members were economically better off after 10, 20, and even 40 years. With more young or very old members, the expenses and consumption requirements exceeded the benefits from the additional labor, and debt was greater and of longer duration. Changing prices and yields across their observed ranged of variability influenced simulated financial position, but not the ranking of results among household composition scenarios.     

农机推广培训工作中存在的问题及解决措施

农机推广培训是农机工作的重要环节,但目前依然存在农机购置补贴政策实施滞后、农机产品供货不及时、农机购置补贴范围不宽、农机培训内容单一以及部分农机具定价偏高、适用性不强等问题,为此,提出牢固树立为农民服务的意识、合理分配农机化投入资金、建设高素质农机科技队伍、简化办事程序等工作措施,以促进农机推广培训工作的有效开展。     

考虑多种气候指数的淮河流域气象干旱预测

干旱是一种形成机制复杂的自然灾害,其对人类社会造成的严重危害促使干旱预测技术的发展。为提高淮河流域的干旱预报水平,通过标准化降水蒸散发指数(SPEI)监测干旱状态,利用Regular vine(R-vine)Copula模型建立多维变量联合分布,将厄尔尼诺-南方涛动(ENSO)、中部型ENSO(ENSO Modoki)、北大西洋涛动(NAO)、印度洋偶极子(IOD)和北极涛动(AO)作为预报因子以提高基于SPEI的干旱等级转移的预报精度。分析结果表明R-vine Copula在评价气候指数对转移概率的影响上表现良好,且多维指数较单维指数更能提升预报精度,这与区域气象干旱同时受多种气候因子调节的事实相一致。为多维气候指数影响下干旱转移行为的研究提供了新的认识。