Correcting for non-response bias in contingent valuation surveys concerning environmental non-market goods: an empirical investigation using an online panel

Data collection for economic valuation by using Internet surveys and pre-recruited Internet panels can be associated with severe disadvantages. Problems concerning sample coverage and sample representativeness can be expected. Representation errors may occur since people can choose whether to be part of an Internet panel and subsequently whether they wish to participate in the survey, thereby introducing two elements of potential self-selection. These elements may be correlated with preferences, thus making the respondents a non-random and non-representative sample, ultimately biasing results. This paper analyses a sample used for an Internet contingent valuation method survey eliciting preferences for improvements in water quality of a river. We find that some variables that affect the survey participation decision also affect willingness-to-pay, consequently biasing our welfare estimates. We show how adjusting willingness-to-pay for this bias can be accomplished by using a grouped data model incorporating a correlation parameter to account for selection.     

Inter-observer variation in habitat survey data: investigating the consequences for professional practice

Environmental assessments and land-use planning require reliable information on the botanical composition and distribution of habitats. There have been numerous academic studies of inter-observer variation in species-inventory and habitat mapping, but studies addressing the prevalence of inter-observer variation and consequences of poor quality data in professional practice are lacking. This paper addresses these questions via a questionnaire survey of environmental professionals, using the standard Phase 1 and National Vegetation Classification (NVC) survey methods in the United Kingdom. The survey revealed that misidentification of habitat types within survey reports was relatively common (approximating to 20% of all reports seen by respondents over the previous five years). Approximately 40% of respondents who had encountered erroneous reports stated that these had led to inaccurate initial site ecological assessments. Additional field surveys and discussions with surveyors were commonly used to resolve these issues, but for Phase 1 and NVC 26% and 34% of respondents, respectively, had encountered one or more cases where errors resulted in negative consequences for clients commissioning surveys (in terms of extra costs and project delays). Net loss of biodiversity arising from inaccurate reports was reported in at least one instance by 32% and 38% of respondents for Phase 1 and NVC surveys, respectively – results that may contribute to the attrition of natural capital within the UK. The study highlights the need to extend studies of inter-observer variation to consider impacts on environmental assessments and decision-making in professional practice. The potential benefits of introducing an accreditation scheme (favoured by the majority of respondents to the questionnaire) are discussed.     

化学氧化法处理资源回收后的J-酸和吐氏酸染料中间体废液

萘系磺酸染料中间体Ｊ－酸和吐氏酸废母液经有用资源的回收后,尚须进行最终出水的达标处理．通过吐氏酸和Ｊ－酸废母液萃余液的后处理试验,确定了盐回收－混凝沉淀－化学氧化的达标处理工艺方案,并确定了相应的工艺参数．其中化学氧化采用Ｆｅｎｔｏｎ试剂（以双氧水作氧化剂,绿矾为催化剂）,在经济合理的投量范围内经２—４ｈ反应,萃余液ＣＯＤＣｒ去除率达８０％以上,最终出水ＣＯＤｃｒ在２００ｍｇ／Ｌ以下,满足有关工业废水排放标准．     

大气中痕量挥发性有机物分析方法研究

利用自行研制的累积式大气采样装置、大气痕量有机物二步冷冻浓缩进样系统和气相色谱/质谱(GC/MS)联用技术对大气中的痕量挥发性有机物进行分析(CCS-GC/MS),并对分析方法进行了评估.结果表明,CCS-GC/MS系统将单纯GC/MS分析大气中痕量挥发性有机物检测下限体积分数值从10^-6量级扩展到10^-12,39种目标化合物平均响应因子为2.9×10^-12A^-1,1000cm³进样量最低检出限体积分数值为7×10^-12～40×10^-12;流出峰保留时间定性分析相对平均偏差<2.5s,对目标化合物定性分析准确率达到100%;0～400×10^-9浓度范围内外标定量曲线r²平均值大于0.99;回收率为88%～111%,平均值100.8%±5.6%;精密度误差2%～14%,平均6.6%.     

“精密度偏性分析”是环境监测质量保证的重要手段

“精密度偏性分析”是环境监测质量保证的重要手段。通过它可以了解其方法的误差和检出限是否达到要求,同时也了解实验室和操作人员对该方法的适应性。     

How decisions about fitting species distribution models affect conservation outcomes

Species distribution models (SDMs) are increasingly used in conservation and land-use planning as inputs to describe biodiversity patterns. These models can be built in different ways, and decisions about data preparation, selection of predictor variables, model fitting, and evaluation all alter the resulting predictions. Commonly, the true distribution of species is unknown and independent data to verify which SDM variant to choose are lacking. Such model uncertainty is of concern to planners. We analyzed how 11 routine decisions about model complexity, predictors, bias treatment, and setting thresholds for predicted values altered conservation priority patterns across 25 species. Models were created with MaxEnt and run through Zonation to determine the priority rank of sites. Although all SDM variants performed well (area under the curve >0.7), they produced spatially different predictions for species and different conservation priority solutions. Priorities were most strongly altered by decisions to not address bias or to apply binary thresholds to predicted values; on average 40% and 35%, respectively, of all grid cells received an opposite priority ranking. Forcing high model complexity altered conservation solutions less than forcing simplicity (14% and 24% of cells with opposite rank values, respectively). Use of fewer species records to build models or choosing alternative bias treatments had intermediate effects (25% and 23%, respectively). Depending on modeling choices, priority areas overlapped as little as 10–20% with the baseline solution, affecting top and bottom priorities differently. Our results demonstrate the extent of model-based uncertainty and quantify the relative impacts of SDM building decisions. When it is uncertain what the best SDM approach and conservation plan is, solving uncertainty or considering alterative options is most important for those decisions that change plans the most.     

Assessment of Alternative Methods for Statistically Downscaling Daily GCM Precipitation Outputs to Simulate Regional Streamflow

This study applied three statistical downscaling methods: (1) bias correction and spatial disaggregation at daily time scale (BCSD_daily); (2) a modified version of BCSD which reverses the order of spatial disaggregation and bias correction (SDBC), and (3) the bias correction and stochastic analog method (BCSA) to downscale general circulation model daily precipitation outputs to the subbasin scale for west‐central Florida. Each downscaled climate input dataset was then used in an integrated hydrologic model to examine differences in ability to simulate retrospective streamflow characteristics. Results showed the BCSD_daily method consistently underestimated mean streamflow because the highly spatially correlated small precipitation events produced by this method resulted in overestimation of evapotranspiration. Highly spatially correlated large precipitation events produced by the SDBC method resulted in overestimation of the standard deviation of wet season daily streamflow and the magnitude/frequency of high streamflow events. BCSA showed better performance than the other methods in reproducing spatiotemporal statistics of daily precipitation and streamflow. This study demonstrated differences in statistical downscaling techniques propagate into significant differences in streamflow predictions, and underscores the need to carefully select a downscaling method that reproduces precipitation characteristics important for the hydrologic system under consideration.     

Use of opportunistic sightings and expert knowledge to predict and compare Whooping Crane stopover habitat

Predicting a species’ distribution can be helpful for evaluating management actions such as critical habitat designations under the U.S. Endangered Species Act or habitat acquisition and rehabilitation. Whooping Cranes (Grus americana) are one of the rarest birds in the world, and conservation and management of habitat is required to ensure their survival. We developed a species distribution model (SDM) that could be used to inform habitat management actions for Whooping Cranes within the state of Nebraska (U.S.A.). We collated 407 opportunistic Whooping Crane group records reported from 1988 to 2012. Most records of Whooping Cranes were contributed by the public; therefore, developing an SDM that accounted for sampling bias was essential because observations at some migration stopover locations may be under represented. An auxiliary data set, required to explore the influence of sampling bias, was derived with expert elicitation. Using our SDM, we compared an intensively managed area in the Central Platte River Valley with the Niobrara National Scenic River in northern Nebraska. Our results suggest, during the peak of migration, Whooping Crane abundance was 262.2 (90% CI 40.2?3144.2) times higher per unit area in the Central Platte River Valley relative to the Niobrara National Scenic River. Although we compared only 2 areas, our model could be used to evaluate any region within the state of Nebraska. Furthermore, our expert‐informed modeling approach could be applied to opportunistic presence‐only data when sampling bias is a concern and expert knowledge is available.     

Myths and assumptions about human-wildlife conflict and coexistence

Recent extinctions often resulted from humans retaliating against wildlife that threatened people's interests or were perceived to threaten current or future interests. Today's subfield of human-wildlife conflict and coexistence (HWCC) grew out of an original anthropocentric concern with such real or perceived threats and then, starting in the mid-1990s, with protecting valued species from people. Recent work in ethics and law has shifted priorities toward coexistence between people and wild animals. To spur scientific progress and more effective practice, we examined 4 widespread assumptions about HWCC that need to be tested rigorously: scientists are neutral and objective about HWCC; current participatory, consensus-based decisions provide just and fair means to overcome challenges in HWCC; wildlife threats to human interests are getting worse; and wildlife damage to human interests is additive to other sources of damage. The first 2 assumptions are clearly testable, but if they are entangled can become a wicked problem and may need debunking as myths if they cannot be disentangled. Some assumptions have seldom or never been tested and those that have been tested appear dubious, yet the use of the assumptions continues in the practice and scholarship of HWCC. We call for tests of assumptions and debunking of myths in the scholarship of HWCC. Adherence to the principles of scientific integrity and application of standards of evidence can help advance our call. We also call for practitioners and interest groups to improve the constitutive process prior to decision making about wildlife. We predict these steps will hasten scientific progress toward evidence-based interventions and improve the fairness, ethics, and legality of coexistence strategies.     

旅游者环境质量感知的时空偏差

环境质量评价研究多为客观、专业化评价,较少从常人角度测量居民或游客对环境质量的评价或感知。而常人的评价可能影响其环境行为,进而促进环境保护。通过调查北京、上海、海南三地游客对居住地、旅游目的地、全国三个空间尺度以及当前、未来两个时间尺度的环境质量感知,分析旅游者环境质量感知的时空偏差。研究发现：（1）受访旅游者当前环境质量感知与全国相比存在乐观偏差,即“空间乐观”;与旅游目的地相比却是悲观倾向,即认为居住地环境质量不如旅游目的地;未来环境质量感知存在明显的乐观倾向,即“时间乐观”。（2）各省市旅游者对当前环境质量感知存在差异,与客观环境质量评价（EQI值）对比,安徽等8个省份的旅游者相对乐观,北京等7个省市旅游者则相对悲观;各省市旅游者未来环境质量感知的乐观偏差程度也存在差异。