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The authors determine the effectiveness of the Rainfall Index Annual Forage Program (RIAFP) in offsetting yield risk of winter annual forage growers. The authors also evaluate the effectiveness in reducing risk of potential alternative weather indices.

The RIAFP is designed to compensate forage producers when yield losses occur. Prior research found weak correlation between the rainfall index and actual winter annual forage yields. The authors use long-term small-plot variety trials of rye, ryegrass, wheat, triticale and oats with rainfall recorded on site and measure the correlation of the index with actual rainfall and actual yields. The alternative indices include frequency of precipitation events and of days with temperature below freezing.

The correlation between actual rainfall and the current RMA index was strongly positive as in previous research. Correlations between forage yields and monthly intervals of the current RMA index were mostly statistically insignificant, and many had an unexpected sign. All indices had some correlations that were inconsistent across time intervals and forage variety. The inconsistent signs suggest a nonlinear relationship with weather and forage yield, indicating that rainfall can be too much or too little. The number of days below freezing has the most potential of the three measures examined.

Producers should view the winter forage RIAFP as a risk-increasing income-transfer farm program. A product to reduce the risk for forage producers may need to use a crop growth simulation model or another approach that can capture the nonlinearity.

Considerably more data were considered than in past research. Past research did not consider alternative weather indices. The program should be continued if its goal is to serve as disguised income transfer, but it should be discontinued if its goal is to reduce risk.

The purpose of this paper is to evaluate the Dual Use (DU) Option – a crop insurance policy created by the 2018 Farm Bill – relative to other policies available to dual-purpose annual forage producers. The new policy combines existing rainfall-based policies for annual forage crops and multi-peril policies for grain, allowing coverage for multiple crop uses on the same acres during the same growing season.

The paper uses a simulation model to examine crop insurance choices for a typical Texas dual-purpose wheat farm. The certainty equivalent (CE) of wealth is used to rank choices within and between three insurance plans and to analyze the effects of those choices over a range of producer risk aversion levels and for three cases of yield expectations.

The DU Option is more preferred as risk aversion increases, but it is not universally preferred. Therefore, while the policy can be a viable risk management tool, certain restrictions may be limiting its effectiveness.

The findings of this paper can help explain farm-level decision making related to dual-purpose annual forage crop insurance program choices.

This paper contributes to the literature by documenting a new crop insurance program made available in the 2018 Farm Bill and provides insights into producers' possible choices by evaluating extensive scenarios.

The purpose of this paper is to empirically examine the financial outcomes from forage production and RI-PRF insurance interval for two locations in Nebraska. Both locations provide historical forage production and precipitation data, allowing the authors to examine the relation between RI-PRF net income and forage production.

The authors focus on evaluating the producer net income and risk (measured as variance of net income) by examining the relation between farm precipitation and production and comparing multiple insurance intervals to no insurance. Each insurance interval will likely have a different relation (basis risk) between observed production and return from insurance and, therefore, a different impact on the variance of net incomes. The impact on variance of net incomes identifies the risk-reducing aspects of RI-PRF insurance intervals. The authors then rank each scenario into four mutually exclusive zones that describe the risk-reducing effectiveness and whether the subsidy is working correctly.

The authors found both risk increasing and decreasing insurance intervals exist at both locations. One insurance scenario (low in BBR) provided the highest net income while increasing risk, suggesting a profit maximizing opportunity. RI-PRF reduces net income risk with intervals insuring during high expected precipitation (growing season); while net income risk increases with intervals insuring low expected precipitation (non-growing season, winter months). The farmer would want to insure during the high expected precipitation months, which coincides with the growing season, since RI-PRF lowers the net income risk. For the government, removing net income risk increasing intervals improves the allocation of government resources.

In this paper, the authors modeled the relation between RI-PRF interval selection using the historical forage production data at two locations in Nebraska. The use of historical forage production data allowed the authors to precisely identify the risk-reducing effectiveness of RI-PRF interval selection.

The purpose of this paper is to examine factors affecting the use of forage index insurance. Forage is a difficult crop to insure, and index insurance may be well suited for forage insurance and has been implemented in several countries, including Canada, the USA and France. Despite being a promising risk management tool, forage index insurance participation rates in Canada, and other countries are low relative to crop insurance participation rates for grain and oilseed producers.

A survey was conducted with 87 beef and cattle producers from Alberta and Saskatchewan, Canada. A probit regression model was used, and a number of variables were included to examine the use of forage index insurance.

In total, 6 of 11 variables in the model are found to be statistically significant in explaining forage producers’ use of forage index insurance. Results suggest that producers who maintain lower feed reserves are more likely to purchase forage index insurance. Also, producers with higher levels of knowledge of crop insurance and a more positive attitude toward forage insurance are more likely to use forage index insurance. Furthermore, producers are more likely to use forage index insurance if they perceive drought and weather risk as being of greater importance, and if they are younger. The importance of the variable forage index insurance premium price was statistically insignificant. This could be due to the effect of subsidization, reducing the importance of price for the decision to purchase. Similarly, the use of other subsidized risk management policies, including a whole-farm margin policy (e.g. the government program and AgriStability), did not reduce forage index insurance use. A possible explanation for this is that the subsidization of the policies may make it profitable to purchase both, despite the overlapping coverage.

These results may be useful for policy makers interested in increasing forage index insurance participation rates, as forage index insurance participation rates have historically been low relative to grain and oilseed producers.

This study is believed to be one of the first studies regarding the use of forage index insurance by forage producers. Producers can be exposed to catastrophic risks such as drought or other extreme weather events, and forage index insurance may be an effective means to manage these risks. Index insurance determines payments using an index that is correlated to producers’ actual yields. A downside of this method is basis risk, which is the mismatch between the insured index and the producer’s actual yield. Research has focused on basis risk and developing improved methods to reduce basis risk. However, less research has investigated the other important factors that may contribute to forage index insurance use. Producers may have a different risk management environment regarding forage production compared to other farm activities, and these differences have largely not been examined.

The purpose of this paper is to discuss some of the implications of policies, practices and new “non‐equilibrium” management approaches in mobile grassland management.

The author takes an actor‐oriented perspective on the narrative of land‐use practices, notional sustainable stocking rates and the problematic of state policy interventions in local context. The paper is based on two years in the field on a bilateral aid‐funded grassland management project at Xing'an League, Inner Mongolia and follow‐up among selected informants.

The constitution of grasslands “degradation” is in fact contested by resource users. Most grassland scientists, Party and Government officials in China have tended to associate ethnic “minority” mobile pastoralists with destructive cultural practices that, they argue, have led to ecological decline on the steppes. This argument is integral to the “degradation narrative” that underpins the discourse on grassland science. The conventional bio‐ecology emphasis on species dominance (growth‐form), in fact says little about the extent of anthropogenic impacts on above‐ground biomass and whether these factors have been the cause of degradation. The paper suggests that greater consideration is given to specific changes in human activity, climatic and plant productivity over time and space, based on endogenous, flexible seasonal estimates.

Although presenting challenges to conventional grassland science based on endogenous experiences and herder practices, it may have specific geopolitical limits to more general scaling‐up in different contexts.

The paper discusses new modalities of non‐equilibrium grassland management, inverting normative top‐down approaches to controlling environmental degradation, livestock distribution and stocking rates.

The paper suggests rethinking the use of customary practices, vernacular knowledge and the social organisation of herders in the design of sustainable grassland management.

The paper may be valuable to practitioners, rural development planners, funders and researchers interested in the use of integrated, cross‐disciplinary, new ecological knowledge in grassland management.

Case studies from many countries indicate that even when rainfall is high drought can still occur. Droughts have been recorded in Bangladesh, where the rainfall is 2,300mm per year, and in Luang Prabang, Laos, where the annual rainfall is 3,200mm. Similarly, the highest Standardized Precipitation Index (SPI) value of 2.78 indicates a possibility of floods in Cambodia. Identification of a threshold SPI value is necessary to pinpoint impending drought. Since SPI values reflect only the rainfall situation and not the existing water availability in reservoirs and canal systems, such a detailed impact-assessment study should also compare the duration of a negative SPI value with that of reduction in the available water from various sources, including groundwater, reservoirs, and canal irrigation systems. So drought occurs not only because of lack of rainfall but also because of bad practices of water usage and water management.

Natural resource management decisions are complicated by multiple property rights, management objectives, and stakeholders with varying degrees of influence over the decision making process. Underlying institutional factors will give certain stakeholders a greater level of influence over the policy outcome. How a stakeholder uses their influence can greatly effect the decision making process. We utilized the Legal Institutional Analysis Model to account for stakeholdersʼ political power in the decision making process. We then extended the use of this model by integrating concepts from decision analysis and public choice economics into a single, comprehensive approach called Disparate Stakeholder Management. We demonstrate this new approach in this report through a case study concerning elk and bison management in the Southern Greater Yellowstone Area.

The purpose of this paper is to present the application of an adaptive bacterial foraging (BF) algorithm for the design optimization of an energy efficient induction motor.

The induction motor design problem is formulated as a mixed integer nonlinear optimization problem. A set of nine independent variables is selected, and to make the machine feasible and practically acceptable, six constraints are imposed on the design. Two different objective functions are considered, namely, the annual active material cost, and the sum of the annual active material cost, annual cost of the active power loss of the motor and annual energy cost required to supply such power loss. A new adaptive BF algorithm is used for solving the optimization problem. A generic penalty function method, which does not require any penalty coefficient, is employed for constraint handling.

The adaptive BF algorithm is validated for two sample motors and benchmarked with the genetic algorithm, particle swarm optimization, simple BF algorithm, and conventional design methods. The results show that the proposed algorithm outperforms the other methods in both the solution quality and convergence rate. The annual cost of the induction motor is remarkably reduced when designed on the basis of minimizing its annual total cost, instead of minimizing its material cost only.

To the best of the knowledge, none of the existing work has applied the BF algorithms for electrical machine design problems. Therefore, the solution to this problem constitutes the main contribution of the paper. According to the huge number of induction motors operating all over the world, the BF techniques used in their design, on minimum annual cost basis, will lead to a tremendous saving in global energy consumption.

The purpose of this paper is to show how the promotion of integrated forage/ruminant‐livestock industries forms a key plank in efforts to improve rural household livelihoods in Western China.

The paper critiques how this industry development has proceeded in the case of Qingyang prefecture in Gansu. The way in which the industry policy has manifested from central to local levels of government is outlined along with how the industry policy relates to other measures intended to improve household livelihoods.

The outcomes of this forage‐livestock industry policy do not always match the intention, and the paper examines the various disconnects that arise between government agencies, government and households and households and the market. The foremost challenge for policy makers is in connecting households and markets.

Identifying the impacts of policy and institutional settings associated with forage‐livestock systems is crucial if improvements are to be made and as these systems become more widespread in Western China.

From the perspectives of the probable replacement of the national calamity funds by multi-peril grassland insurance, the purpose of this paper is to estimate demand for grassland production insurance.

A discrete stochastic programming model with a three-year planning horizon was used to run simulations for farms raising suckler cows primarily with grasslands. In this model, the annual area insured and some production decisions are optimized under grasland yield uncertainty, with possible ex post production-system adjustments. The effects of insurance loading cost (14 levels), insurance coverage level (three levels), risk aversion (two levels) and stock levels (forage and animal stocks vary according to grassland yields and to farm management of the previous years) were analyzed.

The results show that grassland insurance could be used as a flexible risk management tool, when farm becomes vulnerable to fodder shortfall. According to previous years’ grassland yields and to the subsequent states of hay stock and animal liveweight, the area insured could vary between nearly the none and full. Farmers with low-average stocking rate and important hay storage capacity have less incentive to buy grassland insurance. The author also demonstrates that for a given loading cost, more insurance is purchased at a coverage level of 70 percent of average yield than at higher coverage levels. The cost of self-insurance increases for important and rare losses while multi-peril grassland insurance premium decreases. Higher levels of risk aversion also raise the quantity of insurance subscribed. Eventually, insurance price is a key factor. Almost no insurance is bought for loading costs greater than 1.1 under low-risk aversion and for loading costs greater than 1.3 under moderate risk aversion.

The willingness to pay for insurance could have been overestimated for different reasons. First, basis risks have not been introduced in the simulation framework. Although the Forage Production Index performed quite well, basis risks are high enough to trigger inappropriate indemnifications in some cases. Consequences of these risks should be estimated in further research. Second, other self-insurance options and public emergency measures such as subsidized loan or reduction in social security contributions should also be considered to assess and reduce farmers vulnerability to risks.

The launching of the multi-peril grassland insurance is likely to be successful thanks to the 65 percent of public subsidies on insurance premiuml. However, considering that the loading cost is likely to be high and that demand for grassland production insurance is rather low, multi-peril grassland production insurance may struggle to continue unsubsidized.

This paper provides a framework that enables to estimate demand for grassland production insurance factoring in substitution with self-insurance and taking into account successive risks.