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.     

SELECTING TREND TESTS FOR WATER QUALITY SERIES WITH SERIAL CORRELATION AND MISSING VALUES1

ABSTRACT: The use of nonparametric tests for monotonic trend has flourished in recent years to support routine water quality data analyses. The validity of an assumption of independent, identically distributed error terms is an important concern in selecting the appropriate nonparametric test, as is the presence of missing values. Decision rules are needed for choosing between alternative tests and for deciding whether and how to pre-process data before trend testing. Several data pre-processing procedures in conjunction with the Mann-Kendall tau and the Seasonal Kendall test (with and without serial correlation correction) are evaluated using synthetic time series with generated serial correlation and missing data. A composite test (pre-testing for serial correlation followed by one of two trend tests) is evaluated and was found to perform satisfactorily.     

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     

长江三峡柑桔的冻害和热害（二）

本文从柑桔冻害和热害的危害因子和指标等级划分的研究和选取入手,着重探讨了长江三峡地区(湖北境内)两害显著的时空变化特征、差异与关联性及对柑桔生产的影响;揭示了80年代以来冬暖春热的重大气候变化是使两害向“两极分化”的根本原因;讨论了三峡水利工程对两害时空格局的可能调整及减灾原理;最后提出了可能的对策。     

Vulnerability assessment of sea-level rise in Viti Levu, Fiji Islands

Fiji is expected to come under increasing pressure and risk from various threats resulting from climate change and sea-level rise (SLR). Fiji consists of 332 islands and thus has a predominant and large coastline. Viti Levu is the largest and most important of the islands, harboring Fiji’s capital city and most of the major towns concentrated around its coast. The objectives of this study were to evaluate the extent of possible sea-level rise using GIS, and to identify high-risk locations. Potential sea level rise was shown graphically as an output to determine where inundation or flooding would take place. This analysis allowed important areas facing risk to be highlighted for future action. Flooding/inundation can be classified into two kinds: ‘permanent inundation’, which is the result of sea-level rise with tide; and ‘temporary flooding’, also including occasional storm surge events. The inundated area was displayed under different projections and quantified. The results produced output maps showing the distribution of inundation/flooding around the island of Viti Levu as well as the extent of flooding. Six scenarios for sea-level rise were used (0.09, 0.18, 0.48, 0.50, 0.59, 0.88 m). Six scenarios for storm surge were used with return intervals of 1, 2, 5, 10, 25, 50 years. High risk and priority locations are identified as Fiji’s capital Suva, the major tourist center and arrival port of Nadi, and Fiji’s second city Lautoka. Future action, adaptation and response strategies in these identified locations must occur to reduce risk from climate change.     

近14年西北地区甲醛柱浓度的时空变化研究

基于臭氧监测仪（OMI）卫星反演数据,对2005~2018年西北4省区域大气甲醛柱浓度数据进行提取及分析,探讨其时空变化特征及影响因素.结果表明：在时间变化上,14a甲醛柱浓度整体呈先上升后下降的波动变化趋势,夏秋季显著高于冬春季,且冬季均值略高于春季.在空间分布上,甲醛柱浓度自西向东、自北向南逐渐升高,高值区集中于陕西和甘肃东南部及青海西南部;低值区集中于宁夏、青海和甘肃的西北部;稳定性呈现出东部分散、西部集聚、差异显著的分布格局.影响甲醛柱浓度变化的因素包括自然和人为因素,自然因素中,甲醛柱浓度受地形影响显著,与风向、气温均呈现显著正相关;人为因素中,甲醛柱浓度与人口密度、地区生产总值、工业废气排放量及建筑房屋竣工面积均表现出正相关关系,与工业废气排放量的相关度最高.大气中甲醛分子与气溶胶粒子二者间呈显著正相关关系,这进一步说明甲醛浓度受到了诸多因素的综合影响,但气溶胶粒子、气温及工业废气的排放是主导因素.     

祁连山七一冰川物质平衡的时空变化特征

基于2011-2016年七一冰川的野外观测资料,结合气象站数据及1975-2015年的遥感影像,分析了冰川末端变化、物质平衡时空变化特征及其对气候变化的敏感性,结果表明：1975年以来,七一冰川末端持续退缩235 m,平均退缩速率为5.9 m/a,冰川面积减少0.13 km²（4.5%）。2011-2016年,七一冰川的平均物质平衡为-476 mm w.e.,平均ELA为4941 m a.s.l.,物质平衡梯度为2.9 mm/m。从季节变化看,受风吹雪和冰面升华影响,11月至次年3月冰川呈负平衡;4月和9月物质平衡受降水控制,随海拔变化呈现降水效应;强消融期（6-8月）物质平衡随海拔升高线性增加;消融期末由9月初延后至9月底。敏感性分析结果表明,物质平衡对气温变化的敏感性为-178.7 mm w.e. °C^-1 a^-1,对降水变化的敏感性为+2.93 mm w.e. mm^-1 a^-1。即61 mm的降水增加才能弥补暖季气温升高1 °C引起的冰川净物质损失。     

气候变化和人类活动对伊逊河流域径流变化的影响

借助Mann-Kendall趋势检验和突变检验对气象水文序列进行一致性分析,划分基准期（1961—1979年）和影响期（① 1980—1989年、② 1990—1999年、③ 2000—2016年）,利用基准期校准的可变下渗容量（VIC）模型,采用步进式方法,探究气候变化和人类活动对伊逊河流域径流变化的波动影响过程。结果表明:研究区近56年年均气温显著升高,年降水量无明显变化趋势,流域年径流量下降趋势明显,季节尺度上流域非汛期降水量增加显著。气候变化和人类活动均会对径流产生显著影响且作用机理复杂,步进式方法对影响机理的研究较传统方法更能体现其变化过程;在降水丰沛的影响 ② 期,冬季降水量增加会显著增加流域径流量,而在降水略少的影响 ① 期和 ③ 期,蒸发量增加以及土壤含水量降低使得流域径流减少;人类活动耗水在影响 ① 期和 ③ 期引起流域径流减少并且影响作用逐渐增强,影响 ② 期由于城镇化和耕地扩张使得流域产流能力增强导致径流增加。深入研究气候变化和人类活动对径流的影响机制,可为流域水资源管理和规划提供理论依据。