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.     

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.     

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     

Long-Term Changes in the Fauna of Diurnal Lepidopterans (Lepidoptera,Diurna) in the Northern Taiga Subzone of the Western Russian Plain

In the diurnal lepidopteran fauna of the northern taiga subzone in the western Russian Plain, the species inhabiting primary biotopic complexes typical of this subzone currently account for slightly more than 60% of the total species richness and abundance. A large part of the fauna is represented by the species of more southern origin, whose expansion to the northern taiga was caused by anthropogenic transformation of landscapes between the 12th and 20th centuries and recent climate warming.     

水质监测频率与极端气候对高原湖泊入湖河流氮磷通量估算的影响

河流是流域氮磷营养盐的主要输出途径之一,准确掌握其通量变化和驱动因素对流域营养盐管理具有重要意义.本研究以滇池主要入湖河流宝象河为例,基于周水质观测数据和逐日水量数据,构建了河流氮磷通量LOADSET模型.估算了宝象河不同时间尺度（日、季、年）TN和TP的通量,评估了4种低频水质采样和极端气候指数对河流氮磷通量计算的影响.结果表明：①2018年宝象河的TN和TP年通量分别为270.49 t和11.19 t,存在显著的年内差异,夏季是通量最高的季节,分别占TN和TP年通量的40.78%和41.96%.②基于LOADEST模型的低频水质采样的氮磷估算结果与高频采样差异较小,宝象河TN、TP通量估算受采样频率影响较小.③宝象河的TN和TP通量变化受连续5日最大降水量、平均最低气温、平均最高气温、最低气温、最低气温极大值、最高气温极小值和平均温差7种极端气候指数的显著影响.     

基于遥感尾气监测的柴油车气态污染物排放因子计算方法研究

采用遥感尾气测试系统实测了柴油车在实际道路工况下的CO、HC和NO排放特征,修正了排放因子的计算方法,并与车载排放测试系统（PEMS）实测结果进行了验证,获得了实测车辆的CO、HC和NO排放因子.测试结果显示,在各种遥感监测的工况下柴油车尾气中均含有较高浓度的氧气,未考虑氧气影响的燃烧方程反演获得的各污染物体积浓度计算值与PEMS实测值的偏差较大,且氧气浓度越大,偏差越大.经过氧气修正的燃烧方程反演计算的尾气浓度与PEMS实测值吻合度大幅提升,适用于实际工况下遥感检测车辆尾气的反演计算.修正算法得到CO、HC和NO的排放因子离散性较小,精确度较高,可以为量化柴油车尾气排放贡献提供科学依据.     

喜凉作物生长期对全球变暖停滞响应的时空差异——以中国绿洲为例

基于中国绿洲喜凉作物（chimonophilous crop）分布区39个站点1960~2016年逐日平均气温资料,运用线性趋势法、反距离加权插值（IDW）、Morlet小波、Mann-Kendall检验等方法,研究中国绿洲喜凉作物气候生长期的时空变化对变暖停滞的响应.结果表明：①变暖停滞期,中国绿洲喜凉作物气候生长期起、止日及生长期日数以-0.2d/10a、0.33d/10a、0.53d/10a的趋势变化,较1960~2016年起始日提前趋势减缓1.01d/10a,终止日推迟减缓1.28d/10a,生长期日数延长减缓2.3d/10a,对变暖停滞有响应.②中国绿洲喜凉作物气候生长期起始日对变暖停滞响应的站点有44%,终止日和生长期日数均为49%,主要分布在南疆、柴达木盆地和河西绿洲,其中河西绿洲对变暖停滞响应最明显,南疆次之,柴达木最小,而北疆绿洲不存在滞缓现象,显然空间差异明显.③M-K检验显示,中国绿洲喜凉作物气候生长期起、止日及生长期日数分别在2001年、1990年和1997年发生突变,起始日晚于变暖停滞起始年份,终止日和生长期日数早于变暖停滞起始年,且分绿洲生长期日数突变年与变暖停滞起始年相接近.④Morlet小波得出变暖停滞期其变化稳定存在2.4~4.3a的震荡周期,表明未来几年中国绿洲喜凉作物气候生长期仍持续延长.