The potential impact of climate change on Taiwan's agriculture

This paper intends to estimate the potential impact of climate change on Taiwan's agricultural sector. Yield response regression models are used to investigate the climate change's impact on 60 crops. A price‐endogenous mathematical programming model is then used to simulate the welfare impacts of yield changes under various climate change scenarios. Results suggest that both warming and climate variations have a significant but non‐monotonic impact on crop yields. Society as a whole would not suffer from warming, but a precipitation increase may be devastating to farmers.     

Evidence of climate change impacts on crop comparative advantage and land use

Relative agricultural productivity shocks emerging from climate change will alter regional cropland use. Land allocations are sensitive to crop profits that in turn depend on yield effects induced by changes in climate and technology. We develop and apply an integrated framework to assess the impact of climate change on agricultural productivity and land use for the U.S. Northern Great Plains. Crop-specific yield–weather models reveal crop comparative advantage due to differential yield impacts of weather across the region's major crops, that is, alfalfa, wheat, soybeans, and maize. We define crop profits as a function of the weather-driven yields, which are then used to model land use allocation decisions. This ultimately allows us to simulate the impact of climate change under the RCP4.5 emissions scenario on land allocated to the region's major crops as well as to grass/pasture. Upon removing the trends effects in yields, climate change is projected to lower yields by 33–64% over 2031–2055 relative to 1981–2005, with soybean being the least and alfalfa the most affected crops. Yield projections applied to the land use model at present-day input costs and output prices reveals that Dakotas’ grass acreage will increase by up to 23%, displacing croplands. Wheat acreage is expected to increase by up to 54% in select southeastern counties of North Dakota and South Dakota, where maize/soy acreage had increased by up to 58% during 1995–2016.     

Carbon mitigation potential of the French forest sector under threat of combined physical and market impacts due to climate change

Objectives(1) To quantify the contribution of the French forest-wood product chain in terms of carbon sequestration and substitution when accounting for both the physical impacts (shifts in tree growth and mortality rates) and the market impacts (increased demand of harvested wood products (HWP)) of climate change (cc) and the subsequent forest managers adaptations; (2) To assess the uncertainty of the impacts on the above carbon balance and on forest allocation; and (3) To assess the role of managers’ expectations toward these future, uncertain but highly anticipated, impacts.MethodologyWe used a bio-economic model of the French Forest Sector (FFSM++) that is able to consider and integrate: (a) the effects of climate change over forest dynamics; (b) forest investment decisions (among groups of species) according to expected profitability; and (c) market effects in terms of regionalised supply, consumption and trade of HWP, depending on the forest resource stocks and international prices. By including both forest dynamics and forest products, we can evaluate the carbon balance taking the following elements into consideration: (a) carbon sequestered in live and dead biomass in the forest; (b) carbon sequestered in HWP; (c) carbon substituted when wood is used in place of fossil fuels or more energy-intensive materials; and (d) carbon released by forest operations.ResultsWhen the model is run at constant conditions for the next century, the average carbon potential of French forests is 66.2–125.3 Mt CO₂ y⁻¹, depending on whether we consider only inventoried wood resources, HWP pools and direct energy substitution, or if we also account for the carbon stored in tree branches and roots and if we consider the more indirect, but also largely more subjective, material substitution. These values correspond to 18.3% and 34.7%, respectively, of the French 2010 emissions (361 Mt CO₂). However, when we consider both the probable increment of coniferous mortality and changes in forest growth, plus the rise in HWP demand worldwide, the average sequestration rate of the French forest decreases by 6.6–5.8% to 61.8–118.0 Mt CO₂ y⁻¹. Running partial scenarios, we can assess the relative interplay of these two factors, where the price factor increases the HWP stock while decreasing the forest stocks (where the latter effect prevails), while the physical impact of climate change reduces both, but to a lesser extent. Considering short-sighted forest managers, whose behaviour is based uniquely on the observed conditions at the time decisions are made, we obtain a limited effect of the overall carbon balance but a relatively large impact on the area allocation of broadleaved vs. coniferous species.     

Climate and agricultural risk: measuring the effect of ENSO on U.S. crop insurance

Predictive models of climatic phenomena can aid in insurance program design and decision making. Extreme weather outcomes have been linked to the El Niño Southern Oscillation (ENSO), which globally impacts agricultural production. This study demonstrates that extreme ENSO events alter cotton yield distributions in the Southeastern United States. These impacts translate into economically meaningful effects on crop insurance premium rates. Commercial insurers can use publicly available information to determine if government‐set premium rates are mispriced, and in turn extract economic rents via the federally mandated Standard Reinsurance Agreement. By ceding underpriced policies in El Niño and La Niña years, we find that private insurance companies can reduce paid indemnities by 10–15% on average.     

Impacts of changing water inflow distributions on irrigation and farm income along the Drâa River in Morocco

Irrigation water is essential for agriculture in the arid Drâa River basin in Morocco but climate change leads to increasingly unreliable water supply in the area. This article analyzes impacts of changing water inflow distributions on irrigation and farm income extending a conjunctive river basin model toward a stochastic modeling approach. Regional climate scenarios are used to derive a maximum likelihood density estimate of current and future water supplies. Based on these distributions, Monte Carlo simulations are performed to obtain stochastic model results on surface and groundwater irrigation as well as economic indicators for six oases along the river. The probability of farmers to receive revenues below the subsistence level is around 2% under current conditions, but this is likely to rise to rates of 6% to 15% depending on the underlying climate change scenario. The composition of water sources for irrigation will shift to more groundwater use. The river basin model is able to represent complex spatial interactions between oases as well as a partial complementarity between groundwater and surface water irrigation due to salinity management effects. Interestingly, the value of groundwater is not necessarily increasing under future climatic conditions as salinity problems are aggravated with expanded groundwater use.