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While policies for responding climate change impacts need the support and cooperation from the public who may be affected by the policies, understanding the general public’s opinion is important and can help form feasible action plans. In this paper we take advantage of a temperature event that took place during primary data collection to explore how this affects public opinion about helping farmers adapt to climate change. We find that the public is surprisingly supportive of government involvement in farmer adaptation, and that the warm spell has a brief positive effect on support. For several years until 2011, there was a trend of declining belief in the existence and seriousness of climate change. In 2012, belief in climate change bounced back and meanwhile for several months in that year the monthly average temperatures were record highs. While it is reasonable to hypothesize that contemporaneous weather may influence the public’s attitudes about addressing climate change issues, it is unclear how temperature affects public attitudes. There are gaps in existing research about the determinants of public attitudes towards climate change. How public attitudes towards adaptation policy, especially with respect to a government’s intervention aimed at improving prospects for a particular industry sector, is influenced under unusual weather events, are rarely discussed. Until very recently, researchers have not explored how public opinion is influenced by climate change phenomenon per se, especially periods abnormally warm temperature. Prior articles discuss the effect of temperature with certain limitations, including perception of temperature rather than actual temperature, general temperature rather than deviations from normal status, and either short run or relatively long run average temperature to represent the temperature when the survey was taken rather than the temperature of the day when the respondent answered the survey. Another missing issue among climate change surveys is the public’s opinion on adaptation policies, although many have discussed ideas surrounding that of mitigation policies. As Palutikof, Agnew and Hoar indicated in their work, “…none of these studies addressed people’s responses and adaptations.” How the general public thinks about adaptation strategies and policies is seldom considered. Similar to studies about public opinion, we found little research regarding how willingness to pay (WTP) for adaptation policies or strategies is influenced by specific climate change phenomenon. None of the research considered the WTP for an adaptation policy in reference to a particular industry or addressed the effect of abnormal warm temperature. Since agriculture is likely to be one of the most affected industries under climate change, with potentially serious global food availability issues if climate change outpaces the rate of adaptation, understanding public support for government involvement in adaptation and the public’s WTP to fund such efforts can inform policy dialogue about these critical questions. Therefore, we focus on adaptation in agriculture to explore public opinion toward government involvement in helping the sector adapt as well as the WTP for an adaptation policy. We use the data based on a random sample general population poll in Michigan, secondary sources, and an unseasonal fruit-crop damaging warm spell that occurred during the survey period to assess the effects of this short-term phenomenon on public attitudes and the WTP. Temperatures during the two-week warm spell went as high as 40° F above normal Considered as a natural experiment, this unexpected warm spell provided variation of daily temperature deviation and variation of the exposure of this abnormal temperature when respondents were surveyed. Thus, in addition to the daily temperature deviation, as well as its accumulation for a short period (3 days, a week, etc.), several time period index variables are used to explore how the level of the respondents’ exposure to the warm spell would affect the attitudes and WTP. The basic set up is before-within-after warm spell, and we test several variations of time modeling approaches to explore the duration of the effect. Demographic variables and political ideology are used to control selection bias. While it is unable to control in our data set, we consider the effect due to media coverage of the warm spell as an indirect effect and part of the priming mechanism. We constructed four questions to understand how attitudes about government adaptation assistance vary across levels of government (state or national) and crop types (corn-soybeans or fruits-vegetables) since climate change is an issue which has national and worldwide impacts but agricultural production techniques are more localized. In addition to the questions about government assistance, the instrument also included single-bounded dichotomous choice questions to evaluate the WTP for government-sponsored adaptation programs. Given the contentious nature of climate change, it was surprising to find that around two thirds of the respondents showed a tendency to support the idea of the governments’ role helping farmers of either corn/soybeans or fruit/vegetables adjust their cropping systems. This could be due to the warm spell or the fact that we focus on agriculture, where the public may more easily connect changes in weather with the need to adapt than might be the case with other sectors. Results from the basic models confirm several of our hypotheses. Abnormally warm temperature deviation does affect the public attitude toward government’s role on adaptation significantly. So does the variables of sub-periods or exposure of warm spell. However, the WTP is only affected significantly by these time period index variables while the temperature deviation is not significant. In other words, there appears to be a kind of tipping point beyond which further increases in deviation do not make much difference. From the preliminary results, we found that, the public attitudes about whether government should be involved in the adaptation are quite sensitive to short run temperature anomalies. The warm spell effect boosted the support, but it did not last long and quickly dropped back to the pre-event level or lower level merely on the second week of the warm spell. In addition, temperature anomalies may lead to more polarized public attitudes. We also found that the support is higher while the question specified the agriculture industry than in the general question without mentioning specific industry. The importance of local agriculture production had certain but more muted influence than our a priori expectations. Our research focuses on the agriculture industry, adaptation policies, as well as the WTP. The three key dimensions distinguish this paper from prior work. Our research further identifies the effect of the unusual warm spell event by various means. This paper shows how the warm spell event influenced the public attitudes toward climate change adaptation policy regarding two government levels and two crop types and the WTP for government-sponsored adaptation programs. The effects of daily or cumulated temperature deviation as well as the level of exposure to the warm spell will be discussed.

This study seeks assess how the uncertainties associated with the un- derlying biophysical processes in uence the optimal profile of land use over the next century, in light of potential irreversibility in these deci- sions. Our analysis is based on a dynamic stochastic model of global land use, and employs 3 modeling scenarios constructed using global crop simulation and climate models. The results of the deterministic model show that climate impacts appear to have mixed effects on yields - higher temperatures hurt food production but this effect is partially offset by greater CO2 fertilization effect. Declining food crop yields result in rela- tively small expansion of cropland and accumulated GHG emissions from land use change. We then contrast this optimal path to that obtained when the uncertainty is not ignored, thereby demonstrating significance of factoring uncertainty in the optimization stage.

The intensity of agricultural production affects both nutrient and greenhouse gas emissions. Environmental policy designed to reduce one type of pollution may have complementary effects on the other type. This paper explores this issue in the Lake Rotorua catchment in New Zealand using an agro-environmental economic model, NManager. The Regional Council is planning to implement a nutrient trading scheme (NTS) to reduce nutrient discharges to the lake, especially from non-point sources such as farmland, while at the same time the NZ government is planning the agricultural sector into the GHG emissions trading scheme (ETS). We model the abatement costs, potential level of total cost savings; and environmental impacts of agricultural production under three policy scenarios: the inclusion of agricultural in (1) the nutrient trading market only; (2) the NZ GHG emissions trading scheme (ETS) only; and (3) both the nutrient trading market and the NZ ETS concurrently. We find both analytically and numerically that (i) the total level of GHG mitigation is higher when there exist both the NTS and NZ ETS compared to when there is only a NZ ETS; (ii) the permit price of nutrient discharges is inversely related to the permit price of GHG emissions; and (iii) the total economic profit loss from pollution abatement is lower when GHG emissions and nutrient discharges are managed concurrently compared to the sum of the economic profit loss from regulating GHG emissions and nutrient discharges separately.

Recent statistical studies suggest yields for major U.S. food crops will dramatically decrease under climate change due to the rise of extreme temperatures over the growing season. However, these results do not account for changes in the crop mix, therefore overestimating potential damages to the sector. In this study we seek to determine how the crop mix and growing regions would shift in response to climate change. The paper develops a dynamic multinomial discrete choice framework to model adaptation to climate change through crop choice. A major innovation of this study is the construction of a very large high-resolution data set for the econometric analysis and the computational procedure developed to obtain estimates. We combine data on crop cover (USDA Cropland Data Layer (CDL), 30*30 meter resolution) and climate variables (PRISM, 4*4 km resolution) for the study region, matched with crop prices and production costs at regional level. The data set provides billions of spatial units from which we sample for the spatial analysis. The main advantage of such an extensive and detailed data set is the careful consideration of the spatial heterogeneity within counties. The generality of our empirical framework allows prediction of crop choices at field level under various climate change scenarios. The preliminary empirical results show that both market state variables (yields, prices, and costs) and crop state variables (related to crop rotations) are important predictors of farmers' crop choice at field level.

Payment-for-Ecosystem-Services (PES) programs are gaining appeal as flexible approaches to inducing the voluntary provision of ecosystem services (ES). Farmers, who manage agricultural ecosystems, provide important nonmarket ecosystem services to the public by their choice of production inputs and management practices. Although there exist various PES programs in the United States and Europe, we are aware of none that was designed based on a comprehensive understanding of the underlying supply and demand of ecosystem services. Taking advantage of unique, coupled datasets of stated preferences, this paper combines a supply-side cost function of farmers’ willingness to adopt practices that provide increased ES with a demand-side social benefit function of residents’ willingness to pay (WTP) for these ES. The result is an empirically based, welfare-maximizing price and quantity of ES that can inform the design of future PES programs.

We summarize existing theoretical claims linking poverty to rates of deforestation and then examine this linkage empirically for Costa Rica during the 20th century using an econometric approach that addresses the irreversibilities in deforestation. Our da FAO Document Repository: http://www.fao.org/3/a-ae401t.pdf