Climate readiness of recovery plans for threatened Australian species

The rapidly changing climate is posing growing threats for all species, but particularly for those already considered threatened. We reviewed 100 recovery plans for Australian terrestrial threatened species (50 fauna and 50 flora plans) written from 1997 to 2017. We recorded the number of plans that acknowledged climate change as a threat and of these how many proposed specific actions to ameliorate the threat. We classified these actions along a continuum from passive or incremental to active or interventionist. Overall, just under 60% of the sampled recovery plans listed climate change as a current or potential threat to the threatened taxa, and the likelihood of this acknowledgment increased over time. A far smaller proportion of the plans, however, identified specific actions associated with ameliorating climate risk (22%) and even fewer (9%) recommended any interventionist action in response to a climate-change-associated threat. Our results point to a disconnect between the knowledge generated on climate-change-related risk and potential adaptation strategies and the extent to which this knowledge has been incorporated into an important instrument of conservation action.     

Estimating Potential Climate Change Effects on the Upper Neuse Watershed Water Balance Using the SWAT Model

Climate change poses water resource challenges for many already water stressed watersheds throughout the world. One such watershed is the Upper Neuse Watershed in North Carolina, which serves as a water source for the large and growing Research Triangle Park region. The aim of this study was to quantify possible changes in the watershed’s water balance due to climate change. To do this, we used the Soil and Water Assessment Tool (SWAT) model forced with different climate scenarios for baseline, mid‐century, and end‐century time periods using five different downscaled General Circulation Models. Before running these scenarios, the SWAT model was calibrated and validated using daily streamflow records within the watershed. The study results suggest that, even under a mitigation scenario, precipitation will increase by 7.7% from the baseline to mid‐century time period and by 9.8% between the baseline and end‐century time period. Over the same periods, evapotranspiration (ET) would decrease by 5.5 and 7.6%, water yield would increase by 25.1% and 33.2%, and soil water would increase by 1.4% and 1.9%. Perhaps most importantly, the model results show, under a high emission scenario, large seasonal differences with ET estimated to decrease by up to 42% and water yield to increase by up to 157% in late summer and fall. Planning for the wetter predicted future and corresponding seasonal changes will be critical for mitigating the impacts of climate change on water resources.     

Traditional agriculture in transition: examining the impacts of agricultural modernization on smallholder farming in Ghana under the new Green Revolution

Following the renewed effort at achieving a new green revolution for Africa, emphasis has been placed on modernizing smallholder agriculture through the deployment of improved inputs especially mechanized technologies. In Ghana, the government has in the last decade emphasized the provision of subsidized mechanized ploughing services to farmers alongside a rapidly growing private sector tractor service market. While mechanized technology adoption rates have increased rapidly, the deployment of these technologies has been without critical analysis of the impacts on production patterns and local agrarian systems. This paper examines the distributional impacts of agriculture mechanization on cropping patterns and farm sizes of smallholder farmers in northern Ghana using Geographic Information Systems (GIS) techniques, and semi-structured interviews with smallholder farmers (n=60). Specifically, comparative analysis of the field sizes and cropping patterns of participant farmers prior to and after the adoption of mechanized technologies was conducted. In-depth interviews were used to contextualize the experiences of smallholder farmers toward understanding how mechanization may be impacting traditional agriculture. Our findings reveal a mechanization paradox in which farm sizes are expanding, while cropping patterns are shifting away from traditional staple crops (pearl millet and sorghum bicolor) to market-oriented crops (maize, rice and groundnuts). This transition we argue, has adverse implications on the cultural dimension of food security, the organization of social life, and climate change adaptation. We recommend a retooling of the current agricultural policy focus to ensure context sensitivity for a more robust battle against food insecurity.     

Fast,cheap, and imperfect? US public opinion about solar geoengineering

ABSTRACT

Solar geoengineering, which seeks to cool the planet by reflecting a small fraction of sunlight back into space, has drawn the attention of scientists and policymakers as climate change remains unabated. Unlike mitigation, solar geoengineering could quickly and cheaply lower global temperatures. It is also imperfect. Its environmental impacts remain unpredictable, and its low cost and immediate effects may result in ‘moral hazard,’ potentially crowding out costly mitigation efforts. There is little understanding about how the public will respond to such tradeoffs. To address this, a 1000-subject nationally representative poll focused on solar geoengineering was conducted as part of the Cooperative Congressional Election Study (CCES) of the US electorate in October–November 2016. The importance that individuals place on solar geoengineering’s speed and cost predicts their support for it, but there is little to no relationship between their concerns about its shortcomings and support for its research and use. Acquiescence bias appears to be an important factor for attitudes around solar geoengineering and moral hazard.     

Climate policy support under political consensus: exploring the varying effect of partisanship and party cues

By creating attitudinal rifts among partisan voters, political polarization is expected to negatively affect chances of effectively mitigating climate change. While such expectations generally have found support, less attention has been paid to the opposite claim that political consensus should eliminate the partisan dimension in climate change politics. This study tests this claim by studying how party identification, and party cues specifically, affects public policy attitudes in a context defined by political consensus. Using data from a large online access panel in Sweden, party identification and party cues are shown to matter for policy attitudes even in a consensus context. This effect is not limited to certain issues but is found across a wide range of policies, and the effect of party cues, for a given issue, varies across parties. The implications of this study and areas for future work are discussed.     

淮河支流污染物综合降解系数动态测算

确定河流污染物综合降解系数动态变化规律对提高水环境容量测算精度和水环境管理具有重要意义。通过现场模拟法,采用一维稳态模型测算了淮河支流洪河五沟营-塔桥乡河段COD、氨氮和总磷在枯水期、平水期和丰水期的综合降解系数,COD、氨氮和总磷降解系数在各水期的关系为枯水期平水期丰水期,提出了建议值并利用实测浓度对计算结果进行了检验,结果表明,不同水期综合降解系数吻合情况较好。     

The effects of the Fukushima disaster on nuclear energy debates and policies: a two-step comparative examination

Under what conditions do critical events trigger large-scale public discussion and mobilisation, and can these lead to policy change? In a comparative study of nuclear energy policy after the Japanese Fukushima disaster in March 2011, a theory-development approach is adopted, mobilising data collected from national news agencies’ newswires, public surveys, legislation and parliamentary databases, and newspaper editorials in 12 established democracies between March 2011 and March 2013. The analysis suggests two main hypotheses that can guide future research: critical events are more likely to trigger policy change when intense (contentious) mobilisation from policy challengers aligns with the views of the general public, and is backed by major political allies; and critical events are more likely to trigger intense (contentious) mobilisation when policy challengers articulate their opposition around pre-existing policy debates on the issue and resort to pre-existing organisational and mobilisation resources.     

Eco-Environmental Degradation in the Source Region of the Yellow River, Northeast Qinghai-Xizang Plateau

The Yellow River is the second longest river in China and the cradle of the Chinese civilization. The source region of the Yellow River is the most important water holding area for the Yellow River, about 49.2% of the whole runoff comes from this region. However, for the special location, it is a region with most fragile eco-environment in China as well. Eco-environmental degradation in the source region of the Yellow River has been a very serious ecological and socially economic problem. According to census data, historical documents and climatic information, during the last half century, especially the last 30 years, great changes have taken place in the eco-environment of this region. Such changes are mainly manifested in the temporal-spatial changes of water environment, deglaciation, permafrost reduction, vegetation degeneracy and desertification extent, which led to land capacity decreasing and river disconnecting. At present, desertification of the region is showing an accelerating tendency. This paper analyzes the present status of eco-environment degradation in this region supported by GIS and RS, as well as field investigation and indoor analysis, based on knowledge, multi-source data is gathered and the classification is worked out, deals with their natural and anthropogenic causes, and points out that in the last half century the desertification and environmental degradation of this region are mainly attributed to human activities under the background of regional climate changes. To halt further degradation of the environment of this region, great efforts should be made to use land resources rationally, develop advantages animal agriculture and protect the natural grassland.     

Using fuzzy set theory to address the uncertainty of susceptibility to drought

This paper presents the technical aspects of a new methodology for assessing the susceptibility of society to drought. The methodology consists of a combination of inference modelling and fuzzy logic applications. Four steps are followed: (1) model input variables are selected—these variables reflect the main factors influencing susceptibility in a social group, population or region, (2) fuzzification—the uncertainties of the input variables are made explicit by representing them as ‘fuzzy membership functions’, (3) inference modelling—the input variables are used to construct a model made up of linguistic rules, and (4) defuzzification—results from the model in linguistic form are translated into numerical form, also through the use of fuzzy membership functions. The disadvantages and advantages of this methodology became apparent when it was applied to the assessment of susceptibility from three disciplinary perspectives: Disadvantages include the difficulty in validating results and the subjectivity involved with specifying fuzzy membership functions and the rules of the inference model. Advantages of the methodology are its transparency, because all model assumptions have to be made explicit in the form of inference rules; its flexibility, in that informal and expert knowledge can be incorporated through ‘fuzzy membership functions’ and through the rules in the inference model; and its versatility, since numerical data can be converted to linguistic statements and vice versa through the procedures of ‘fuzzification’ and ‘defuzzification’.     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability