The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake

Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple‐use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders’ willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders’ decisions to engage in management. To test the utility of our best‐supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost‐effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost‐effective for prioritizing management when social data collection costs were low (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost‐efficient and effective manner.     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.     

The role of digital data entry in participatory environmental monitoring

Many argue that monitoring conducted exclusively by scientists is insufficient to address ongoing environmental challenges. One solution entails the use of mobile digital devices in participatory monitoring (PM) programs. But how digital data entry affects programs with varying levels of stakeholder participation, from nonscientists collecting field data to nonscientists administering every step of a monitoring program, remains unclear. We reviewed the successes, in terms of management interventions and sustainability, of 107 monitoring programs described in the literature (hereafter programs) and compared these with case studies from our PM experiences in Australia, Canada, Ethiopia, Ghana, Greenland, and Vietnam (hereafter cases). Our literature review showed that participatory programs were less likely to use digital devices, and 2 of our 3 more participatory cases were also slow to adopt digital data entry. Programs that were participatory and used digital devices were more likely to report management actions, which was consistent with cases in Ethiopia, Greenland, and Australia. Programs engaging volunteers were more frequently reported as ongoing, but those involving digital data entry were less often sustained when data collectors were volunteers. For the Vietnamese and Canadian cases, sustainability was undermined by a mismatch in stakeholder objectives. In the Ghanaian case, complex field protocols diminished monitoring sustainability. Innovative technologies attract interest, but the foundation of effective participatory adaptive monitoring depends more on collaboratively defined questions, objectives, conceptual models, and monitoring approaches. When this foundation is built through effective partnerships, digital data entry can enable the collection of more data of higher quality. Without this foundation, or when implemented ineffectively or unnecessarily, digital data entry can be an additional expense that distracts from core monitoring objectives and undermines project sustainability. The appropriate role of digital data entry in PM likely depends more on the context in which it is used and less on the technology itself.     

Resembling a Viper: Implications of Mimicry for Conservation of the Endangered Smooth Snake

The phenomenon of Batesian mimicry, where a palatable animal gains protection against predation by resembling an unpalatable model, has been a core interest of evolutionary biologists for 150 years. An extensive range of studies has focused on revealing mechanistic aspects of mimicry (shared education and generalization of predators) and the evolutionary dynamics of mimicry systems (co‐operation vs. conflict) and revealed that protective mimicry is widespread and is important for individual fitness. However, according to our knowledge, there are no case studies where mimicry theories have been applied to conservation of mimetic species. Theoretically, mimicry affects, for example, frequency dependency of predator avoidance learning and human induced mortality. We examined the case of the protected, endangered, nonvenomous smooth snake (Coronella austriaca) that mimics the nonprotected venomous adder (Vipera berus), both of which occur in the Åland archipelago, Finland. To quantify the added predation risk on smooth snakes caused by the rarity of vipers, we calculated risk estimates from experimental data. Resemblance of vipers enhances survival of smooth snakes against bird predation because many predators avoid touching venomous vipers. Mimetic resemblance is however disadvantageous against human predators, who kill venomous vipers and accidentally kill endangered, protected smooth snakes. We found that the effective population size of the adders in Åland is very low relative to its smooth snake mimic (28.93 and 41.35, respectively).Because Batesian mimicry is advantageous for the mimic only if model species exist in sufficiently high numbers, it is likely that the conservation program for smooth snakes will fail if adders continue to be destroyed. Understanding the population consequences of mimetic species may be crucial to the success of endangered species conservation. We suggest that when a Batesian mimic requires protection, conservation planners should not ignore the model species (or co‐mimic in Mullerian mimicry rings) even if it is not itself endangered. Implications of mimicry for Conservation of the endangered smooth snake     

重金属阳离子荧光传感器合成及光谱性研究

通过亚胺缩合的反应制备出阳离子荧光传感器（Cation Fluorescent Sensors,CFSs）,并对其结构、光谱性能检测、荧光量子产率等进行了详细的研究.通过荧光化学传感器产生的荧光光谱一直是高效的分析方法,因此合成了新的基于席夫碱的荧光化学传感器,并研究了对各种金属离子的结合特性.在CH3CN溶液中测试了阳离子荧光传感器时不同阳离子的选择性响应,发现对Cu2＋有较好的选择性,可用于Cu2＋的检测.该类阳离子荧光传感器是基于2,2-联噻吩-5-乙醛的荧光发射基团和邻氨基苯甲醚为识别基团的一类阳离子荧光传感器.     

CO2浓度增加对作物影响的研究动态

大气CO2浓度不断增加将以两种方式影响作物的代谢、生长发育和产量的形成：一是通过温室效应“加热”气候,改变降水类型,进而影响作物;二是浓度变化本身对作物生理过程的影响。介绍了国内外近年来在与CO2浓度有关的作物生理实验方面取得的进展及其主要结果。     

中国旅游业CO_2排放区域差异的空间分析

在旅游业节能减排形势严峻的背景下,深入研究中国旅游业CO_2排放问题,制定科学的区域节能减排政策已刻不容缓。本文首先运用"自下而上"法,估算了1993-2012年中国整体旅游业、旅游业各分部门、大陆各省区(不含西藏)旅游业CO_2排放量。在此基础上,对全国及三大地带旅游业CO_2排放的总体特征进行分析;利用Theil指数法分析了中国旅游业CO_2排放强度的区域差异、区域内差异和区域间差异;运用AreView软件对中国旅游业CO_2排放强度的省际差异进行直观图示。分析结果显示:1993-2012年,中国旅游业CO_2排放量从1 480.868×10~4t升至6 274.129×10~4t;全国及三大地带旅游业CO_2排放强度整体上呈现出先显著下降、再缓慢梯度下降的趋势;中国旅游业CO_2排放强度空间分布不均匀,东部地区旅游业CO_2排放强度低于中部和西部地区;中国旅游业CO_2排放强度的区域总体差异、区域间差异和区域内差异整体呈逐渐缩小的趋势,区域间差异对总体差异的贡献率为94%-98%,区域间差异占主导地位;中国旅游业CO_2排放强度省际差异明显,属于旅游业CO_2排放强度弱显著区的省区基本位于东部沿海地区,河北、湖南、河南、广西、甘肃和新疆等省区频繁出现在旅游业CO_2排放强度强显著区之列,因此上述省区应是中国旅游业CO_2未来节能减排的区域重点。据此提出差别化的CO_2减排对策:东部地区应通过技术改进和调整产业结构、能源消费结构来降低CO_2排放强度,并以此带动中部和西部地区旅游业节能减排;中部和西部地区应加强与东部地区合作,将提高能源使用率、降低CO_2排放强度作为旅游业减排工作的重点。     

不同类型填料的三维电极/Fenton试剂法处理苯酚废水

采用不同类型填料对三维电极/Fenton试剂法处理苯酚模拟废水进行研究.结果表明.不同类型活性炭填料对苯酚去除率有很大影响,粒炭不适合做粒子电极,采用5.0 mm柱炭处理效果较好;采用石英砂与活性炭混合填料的处理效果比单一活性炭填料好,但苯酚去除率提高不明显;电解槽反应器中按比例投加涂膜活性炭和活性炭混合填料能明显提高苯酚去除率;当涂膜活性炭与活性炭体积比为1,2时,苯酚去除率最高,达96.8%.     

双水相气浮浮选光度法处理环境水样中痕量土霉素残留物

建立了一种新型分离方法--双水相气浮浮选光度法,使其处理环境水样中痕量土霉紊(OTC)残留物,研究了其工作原理,并用高效液相色谱法对该方法的可靠性进行了验证.利用自制的双水相气浮浮选装置,选择四氢呋喃作亲水有机溶剂、质量分数为10%的NaCl溶液作分相剂,NaOH溶液调节pH,将Cu2+与OTC形成的疏水配合物浮选至有机相,实现OTC与水样分离.浮选完毕后,经紫外-可见分光光度法分析,线性回归方程为A=1.532×105c+0.1230(其中:A为有机相的吸光度;c为水样的OTC摩尔浓度,mol/L),相关系数为0.9998,该方法的线性范围为4.8×10-7～7.3×10-5 mol/L,OTC加标回收率为99.5%～100.1%.     

负载型TiO2薄膜光催化剂降解亚甲基蓝

采用溶胶-凝胶法制备了玻璃负载的TiO2薄膜光催化剂,研究了该催化剂对亚甲基蓝溶液的光催化降解,考察了反应时间、水样的初始浓度、溶液的pH等对光催化降解效果的影响。