Political commitment to CO<Subscript>2</Subscript> capture and storage: evidence from government RD&;D budgets

For CO₂ capture and storage (CCS) to succeed as a mitigation strategy, political commitment is one of several prerequisites. This article offers an appraisal of political commitment to a CCS strategy among high-income countries in Europe and North America: Which governments are committed, and what particular interests and concerns do they seek to accommodate by supporting CCS? In order to answer these questions, new data are reported on government CCS research, development and demonstration (RD&;D) budgets. RD&;D budgets divided by GDP is used as an indicator of political commitment, and explanations are sought for cross-national differences. The analysis shows that fossil fuels reserves and extraction within a country has a very strong bearing on funding levels. Likely explanations include the potential for combining CCS with enhanced resource recovery. All large economies (population >50 million) have a funding program. The smaller states that provide funding (Norway, Canada, the Netherlands) have the highest funding levels relative to GDP. These findings suggest that high-income petroleum producing countries are likely to be leaders in promoting CCS and a favorable regulatory environment. The fact that all large, high-income countries in the two regions now display some interest in CCS further improves its political outlook.     

Climate change, water availability and future cereal production in China

Climate scenarios from a regional climate model are used to drive crop and water simulation models underpinned by the IPCC A2 and B2 socio-economic development pathways to explore water availability for agriculture in China in the 2020s and 2040s. Various measures of water availability are examined at river basin and provincial scale in relation to agricultural and non-agricultural water demand and current and planned expansions to the area under irrigation. The objectives are to understand the influences of different drivers on future water availability to support China's food production. Hydrological simulations produce moderate to large increases in total water availability in response to increases in future precipitation. Total water demand increases nationally and in most basins, but with a decreasing share for agriculture due primarily to competition from industrial, domestic and municipal sectors. Crop simulations exhibit moderate to large increases in irrigation water demand which is found to be highly sensitive to the characteristics of daily precipitation in the climate scenarios. The impacts of climate change on water availability for agriculture are small compared to the role of socio-economic development.The study identifies significant spatial differences in impacts at the river basin and provincial level. In broad terms water availability for agriculture declines in southern China and remains stable in northern China. The combined impacts of climate change and socio-economic development produce decreases in future irrigation areas, especially the area of irrigated paddy rice. Overall, the results suggest that there will be insufficient water for agriculture in China in the coming decades, due primarily to increases in water demand for non-agricultural uses, which will have significant implications for adaptation strategies and policies for agricultural production and water management.     

Review of greenhouse gas emissions from crop production systems and fertilizer management effects

Fertilizer nitrogen (N) use is expanding globally to satisfy food, fiber, and fuel demands of a growing world population. Fertilizer consumers are being asked to improve N use efficiency through better management in their fields, to protect water resources and to minimize greenhouse gas (GHG) emissions, while sustaining soil resources and providing a healthy economy. A review of the available science on the effects of N source, rate, timing, and placement, in combination with other cropping and tillage practices, on GHG emissions was conducted. Implementation of intensive crop management practices, using principles of ecological intensification to enhance efficient and effective nutrient uptake while achieving high yields, was identified as a principal way to achieve reductions in GHG emissions while meeting production demands. Many studies identified through the review involved measurements of GHG emissions over several weeks to a few months, which greatly limit the ability to accurately determine system-level management effects on net global warming potential. The current science indicates: (1) appropriate fertilizer N use helps increase biomass production necessary to help restore and maintain soil organic carbon (SOC) levels; (2) best management practices (BMPs) for fertilizer N play a large role in minimizing residual soil nitrate, which helps lower the risk of increased nitrous oxide (N₂O) emissions; (3) tillage practices that reduce soil disturbance and maintain crop residue on the soil surface can increase SOC levels, but usually only if crop productivity is maintained or increased; (4) differences among fertilizer N sources in N₂O emissions depend on site- and weather-specific conditions; and (5) intensive crop management systems do not necessarily increase GHG emissions per unit of crop or food production; they can help spare natural areas from conversion to cropland and allow conversion of selected lands to forests for GHG mitigation, while supplying the world's need for food, fiber, and biofuel. Transfer of the information to fertilizer dealers, crop advisers, farmers, and agricultural and environmental authorities should lead to increased implementation of fertilizer BMPs, and help to reduce confusion over the role of fertilizer N on cropping system emissions of GHGs. Gaps in scientific understanding were identified and will require the collaborative attention of agronomists, soil scientists, ecologists, and environmental authorities in serving the immediate and long-term interests of the human population.     

A methodological proposal for the evaluation of farmer’s adaptation to climate variability, mainly due to drought in watersheds in Central America

The current study shows the process and the results of a methodology proposed to contribute with the issue of how to evaluate the adaptation to climate variability and future climate change. The proposed methodology consists of a standard to evaluate farmer’s adaptation to climate variability, mainly due to drought in watersheds in Central America; and was created with contributions from experts and professionals around this region. The phases for this process were: (1) literature review about the topic, (2) development of a preliminary standard, (3) expert interviews for the evaluation of this preliminary standard, (4) construction of a standard to evaluate the issue of adaptation to climate variability emphasizing drought through contributions from experts and their preliminary evaluations, (5) applicability test of this standard for the evaluation of climate variability under real conditions and (6) application of this standard through a case study in the Aguas Calientes river sub-watershed in Nicaragua, which permanently undergoes drought problems and climate variability. This standard has five main principles that go from the general, considering regional and national policies and institutionalism, to the specifics at the level of watersheds. In addition to those principles, the standard contains ten criteria, 26 indicators and 51 verifiers distributed among the main five principles. In the process for testing this standard in the Aguas Calientes river watershed in Nicaragua, the score for the general applicability to this standard was middle-level (score of 3 in a scale of 1 to 5), although, for the main principles of this standard, the score was four (high).     

Economic impacts of climatic variability and subsidies on European agriculture and observed adaptation strategies

In order to assess agricultural adaptation to climate impacts, new methodologies are needed. The translog distance function allows assessing interactions between different factors, and hence the influence of management on climate impacts. The Farm Accountancy Data Network provides extensive data on farm characteristics of farms throughout the EU15 (i.e. the 15 member states of the European Union before the extension in 2004). These data on farm inputs and outputs from 1990−2003 are coupled with climate data. As climate change is not the only change affecting European agriculture, we also include effects of subsidies and other changes on inputs and outputs of farms throughout Europe. We distinguish several regions and empirically assess (1) climate impacts on farm inputs and outputs in different regions and (2) interactions between inputs and other factors that contribute to the adaptation to these impacts. Changes in production can partly be related to climatic variability and change, but also subsidies and other developments (e.g. technology, markets) are important. Results show that impacts differ per region, and that ‘actual impacts’ cannot be explicitly separated into ‘potential impacts’ and ‘adaptive capacity’ as often proposed for vulnerability assessment. Farmers adapt their practices to prevailing conditions and continuously adapt to changing conditions. Therefore, ‘potential impacts’ will not be observed in practice, leaving it as a mainly theoretical concept. Factors that contribute to the adaptation also differ per region. In some regions more fertilizers or more irrigation can mitigate impacts, while in other regions this amplifies impacts. To project impacts of future climate change on agriculture, current farm management strategies and their influence on current production should be considered. This clearly asks for improved integration of biophysical and economic models.     

An overdue alignment of risk and resilience? A conceptual contribution to community resilience

A systematic review of literature on community resilience measurement published between 2005 and 2014 revealed that the profound lack of clarity on risk and resilience is one of the main reasons why confusion about terms such as adaptive capacity, resilience, and vulnerability persists, despite the effort spared to operationalise these concepts. Resilience is measured in isolation in some cases, where a shock is perceived to arise external to the system of interest. Problematically, this contradicts the way in which the climate change and disaster communities perceive risk as manifesting itself endogenously as a function of exposure, hazard, and vulnerability. The common conceptualisation of resilience as predominantly positive is problematic as well when, in reality, many undesirable properties of a system are resilient. Consequently, this paper presents an integrative framework that highlights the interactions between risk drivers and coping, adaptive, and transformative capacities, providing an improved conceptual basis for resilience measurement.     

Mitigating flood risk and enhancing community resilience to natural disasters: plan quality matters

In response to increasingly frequent and severe flooding events, tracking the explanatory elements of integrative planning effort can provide useful assessment of initiatives that foster improved community disaster resiliency. In this research, we address the effect of local hazard mitigation plan quality on mitigating disaster risk with an emphasis on the relationship between plan quality and community resilience. Using content analysis and principles of plan quality metrics, we evaluate local hazard mitigation plans to determine how well they support disaster risk reduction. Analytically, these metrics and relevant controls were incorporated into both a log-linear two-stage least squares model and a quantile regression model to explain flood loss at the county level for the US Mississippi River Basin. Findings suggest that better plan quality and high levels of community resilience result in reducing disaster losses.     

Modeling the influence of precipitation and nitrogen deposition on forest understory fuel connectivity in Sierra Nevada mixed-conifer forest

Climate change models for California's Sierra Nevada predict greater inter-annual variability in precipitation over the next 50 years. These increases in precipitation variability coupled with increases in nitrogen deposition from fossil fuel consumption are likely to result in increased productivity levels and significant increases in forest understory fuel loads. Higher understory plant biomass contributes to fuel connectivity and may increase future fire size and severity in the Sierra Nevada. The objective of this research was to develop and test a model to determine how changing precipitation and nitrogen deposition levels affect shrub and herb biomass production, and to determine how often prescribed fire would be needed to counter increasing fuel loads. Model outputs indicate that under an increasing precipitation scenario significant increases in shrub and herb biomass occur that can be counteracted by decreasing the fire return interval to 10 years. Under a scenario with greater inter-annual variability in precipitation and increased nitrogen deposition, implementing fire treatments at an interval equivalent to the historical range of 15–30 years maintains understory vegetation fuel loads at levels comparable to the control.     

A concept model to estimate the potential distribution of the Asiatic citrus psyllid (Diaphorina citri Kuwayama) in Australia under climate change—A means for assessing biosecurity risk

Increasing global temperatures as a result of climate change are widely considered inevitable for Australia. Despite this, the specific effects of climate change on Australian agriculture are little studied and the effects on agricultural pests and diseases are virtually unknown. In this paper we consider the impact of climate change on the Asiatic citrus psyllid (Diaphorina citri Kuwayama [Hemiptera: Psyllidae]); one of two known vectors of huanglongbing (citrus greening); a debilitating disease which is caused in Asia by a phloem-limited bacterium ‘Candidatus Liberibacter asiaticus’ (α-Proteobacteria). D. citri does not occur in Australia, but if introduced would pose a major threat to the viability of the Australian citrus industry and to native Citrus species. This paper presents an approach developed to understand how climate change may influence the behaviour, distribution and breeding potential of D. citri. Here we developed and describe an initial dynamic point model of D. citri biology in relation to its citrus host and applied it to a scenario of increasing temperatures, as indicators of climate change, on a continental scale. A comparison between model outputs for the three time frames considered (1990, 2030 and 2070) confirms that increasing temperatures projected under climate change will affect the timing and duration of new citrus growth (flush) necessary for psyllid development throughout Australia. Flushing will start progressively earlier as the temperature increases and be of shorter duration. There will also be a gradual southward expansion of shorter durations of the occurrence of flush. Increasing temperatures will impact on D. citri both directly through alteration of its temperature dependant development cycle and indirectly through the impact on the host flushing cycle. For the whole of Australia, a comparison between model outputs for the three scenarios considered indicates the seasonality of D. citri development will change to match changes in citrus flush initiation. Results indicate that the risk of establishment by D. citri is projected to decrease under increasing temperatures, mainly due to shortened intervals when it can feed on new leaf flushes of the host. However, the spatially heterogeneous results also suggest that regions located on the southern coastline of Australia could become more suitable for D. citri than projected under current temperatures. These results confirm the value of a linked host-pest approach as based on D. citri climatic requirements alone the model would have accounted only for shorter development periods and predicted an increased risk of potential distribution.