A Priori Typology-Based Prediction of Benthic Macroinvertebrate Fauna for Ecological Classification of Rivers

We evaluated a simple bioassessment method based on a priori river typology to predict benthic macroinvertebrate fauna in riffle sites of rivers in the absence of human influence. Our approach predicted taxon lists specific to four river types differing in catchment area with a method analogous to the site-specific RIVPACS-type models. The reference sites grouped in accordance with their type in NMS ordination, indicating that the typology efficiently accounted for natural variation in macroinvertebrate assemblages. Compared with a null model, typology greatly increased the precision of prediction and sensitivity to detect human impairment and strengthened the correlation of the ratio of observed-to-expected number of predicted taxa (O/E) with the measured stressor variables. The performance of the typology-based approach was equal to that of a RIVPACS-type predictive model that we developed. Exclusion of rarest taxa with low occurrence probabilities improved the performance of both approaches by all criteria. With an increasing inclusion threshold of occurrence probability, especially the predictive model sensitivity first increased but then decreased. Many common taxa with intermediate type-specific occurrence probabilities were consistently missing from impacted sites, a result suggesting that these taxa may be especially important in detecting human disturbances. We conclude that if a typology-based approach such as that suggested by the European Union’s Water Framework Directive is required, the O/E ratio of type-specific taxa can be a useful metric for assessment of the status of riffle macroinvertebrate communities. Successful application of the approach, however, requires biologically meaningful river types with a sufficient pool of reference sites for each type.     

Integrating drivers influencing the detection of plant pests carried in the international cut flower trade

This paper analyses the cut flower market as an example of an invasion pathway along which species of non-indigenous plant pests can travel to reach new areas. The paper examines the probability of pest detection by assessing information on pest detection and detection effort associated with the import of cut flowers. We test the link between the probability of plant pest arrivals, as a precursor to potential invasion, and volume of traded flowers using count data regression models. The analysis is applied to the UK import of specific genera of cut flowers from Kenya between 1996 and 2004.There is a link between pest detection and the Genus of cut flower imported. Hence, pest detection efforts should focus on identifying and targeting those imported plants with a high risk of carrying pest species. For most of the plants studied, efforts allocated to inspection have a significant influence on the probability of pest detection. However, by better targeting inspection efforts, it is shown that plant inspection effort could be reduced without increasing the risk of pest entry. Similarly, for most of the plants analysed, an increase in volume traded will not necessarily lead to an increase in the number of pests entering the UK. For some species, such as Carthamus and Veronica, the volume of flowers traded has a significant and positive impact on the likelihood of pest detection. We conclude that analysis at the rank of plant Genus is important both to understand the effectiveness of plant pest detection efforts and consequently to manage the risk of introduction of non-indigenous species.     

Models,Assumptions, and Stakeholders: Planning for Water Supply Variability in the Colorado River Basin1

Abstract: Declining reservoir storage has raised the specter of the first water shortage on the Lower Colorado River since the completion of Glen Canyon and Hoover Dams. This focusing event spurred modeling efforts to frame alternatives for managing the reservoir system during prolonged droughts. This paper addresses the management challenges that arise when using modeling tools to manage water scarcity under variable hydroclimatology, shifting use patterns, and institutional complexity. Assumptions specified in modeling simulations are an integral feature of public processes. The policymaking and management implications of assumptions are examined by analyzing four interacting sources of physical and institutional uncertainty: inflow (runoff), depletion (water use), operating rules, and initial reservoir conditions. A review of planning documents and model reports generated during two recent processes to plan for surplus and shortage in the Colorado River demonstrates that modeling tools become useful to stakeholders by clarifying the impacts of modeling assumptions at several temporal and spatial scales. A high reservoir storage‐to‐runoff ratio elevates the importance of assumptions regarding initial reservoir conditions over the three‐year outlook used to assess the likelihood of reaching surplus and shortage triggers. An ensemble of initial condition predictions can provide more robust initial conditions estimates. This paper concludes that water managers require model outputs that encompass a full range of future potential outcomes, including best and worst cases. Further research into methods of representing and communicating about hydrologic and institutional uncertainty in model outputs will help water managers and other stakeholders to assess tradeoffs when planning for water supply variability.     

Food web assessments in the Baltic Sea: Models bridging the gap between indicators and policy needs

Ecosystem-based management requires understanding of food webs. Consequently, assessment of food web status is mandatory according to the European Union’s Marine Strategy Framework Directive (MSFD) for EU Member States. However, how to best monitor and assess food webs in practise has proven a challenging question. Here, we review and assess the current status of food web indicators and food web models, and discuss whether the models can help addressing current shortcomings of indicator-based food web assessments, using the Baltic Sea as an example region. We show that although the MSFD food web assessment was designed to use food web indicators alone, they are currently poorly fit for the purpose, because they lack interconnectivity of trophic guilds. We then argue that the multiple food web models published for this region have a high potential to provide additional coherence to the definition of good environmental status, the evaluation of uncertainties, and estimates for unsampled indicator values, but we also identify current limitations that stand in the way of more formal implementation of this approach. We close with a discussion of which current models have the best capacity for this purpose in the Baltic Sea, and of the way forward towards the combination of measurable indicators and modelling approaches in food web assessments. Supplementary InformationThe online version contains supplementary material available at 10.1007/s13280-021-01692-x.     

土地市场发展的经济驱动机制:理论与实证分析

探讨中国土地市场发展的经济驱动机制对于促进土地市场的有序发展意义重大。本文提出了一个土地市场发展的经济驱动机制框架,然后以此为基础从理论上分析我国土地市场发展的经济驱动因素,并结合计量经济模型的构建进行相应的实证检验。结果表明,无论是土地一级市场还是土地二级市场,影响土地供求的因素都是中国土地市场发展的驱动要素,而土地市场环境和制度政策则会对土地市场的发展起到抑制或加速作用。因此,对于今后中国土地市场的有序发展,宜从提高土地一级市场市场化程度、优化产业结构、提升城镇化质量等方面展开。     

江汉平原湿地农业技术体系探讨

以十多年来江汉平原农业地理和涝渍地开发研究实践为基础,综合国内外湿地研究新成果,首次提出了建立中国南方湿地农业技术体系的构想。针对本地区涝渍灾害严重和生态脆弱化突出的实际,重点探讨了湿地农业关键技术和建立湿地农业开发模式的问题,湿地农业的关键技术主要有涝渍地农业小区综合整治开发规划与实施;涝渍地排水改良技术;涝渍地土壤肥力特征及改良技术;适生生物资源的发现、引进与鉴定;主要作物抗涝渍的机理及抗渍高产栽培;涝渍地作物病虫草害的发生规律及综合防治技术;涝渍地生态环境异化评价与生态恢复技术。基于江汉平原实际,今后湿地农业必须在国土整治与水资源合理分配、调控技术、选择与培育湿地特色产业和恢复优美环境与确保食物安全等方面进行重点攻关研究。     

溃坝后果严重程度评价模型研究

为了建立溃坝严重程度综合评价的定量模型,依据现行法规,采用建立数学模型的方法,分别分析并提出了决定大坝溃决后果严重性的3个主要影响因子(生命损失、经济损失和社会环境影响)的严重程度系数及其对数非线性和对数线性评价模型,构造了溃坝后果严重程度的综合评价模型.依据该模型,定量分析了5座水库大坝溃坝的严重性,给出了判别严重程度的定量指标.     

核电站核事故核素污染评估模式

利用修正了的高斯模式探讨核电站核素污染事故中的核素扩散。分析了边界条件,气象条件和核素衰变规律对核素扩散污染的影响,并进一步讨论了核素的污染范围,距源距离及核素的沉积量,可作为确定应急安全的理论依据。     

Modeling Animal Habitats Based on Cover Types: A Critical Review

The simplest type of model describing animal habitats is a “cover-type model,” in which a species is assumed to be present in certain vegetation types and absent in others. Ecologists and managers use these models to predict animal distributions for gap analysis and conservation planning. Critics, however, have suggested that the models are overly simplistic and inaccurate. We reviewed the use of cover-type models including assessing their error rates, diagnosing the problems with these models, and determining how they should best be used by managers. To determine models’ accuracy rates, we conducted a meta-analysis of 35 studies in which cover-type models were tested against data on animal occurrences. Models had a mean accuracy rate of 0.71 ± 0.18 (SD). Rates of commission error averaged 0.20 ± 0.16, and omission errors averaged 0.09 ± 0.11. A review of the effects of errors in conservation planning suggests that the observed error rates were high enough to call into question any management decisions based on these models. Reasons for the high error rates of cover-type models include the fallibility of expert opinion, the fact that the models oversimplify how animals actually use habitats, and the dynamic nature of animal populations. Given the high rate of errors in cover-type models, any conclusions based on them should be taken with extreme caution. We suggest that these models are best used as coarse filters to identify locations for further study in the field.     

塔里木河下游植被覆盖变化遥感定量分析

在RS与GIS技术支持下,采用空间模型分析法,以2 a为一研究时段,定量分析塔里木河下游输水后植被覆盖变化。结果表明:输水11 a来,Ⅳ级低覆盖植被、Ⅴ级裸地及沙地仍是研究区主要地类。与2000年相比,2010年Ⅰ级极高覆盖植被、Ⅱ级高覆盖植被、Ⅲ级中覆盖植被、Ⅳ级低覆盖植被均呈现逐级增加的趋势,分别增加了986.76、 681.84、 1 091.88、 8 641.89 hm²;Ⅴ级裸地、沙地减少了11 420.37 hm²。整个研究时段,Ⅲ级与Ⅳ级间、Ⅳ级与Ⅴ级间的转化为研究区主要转化类型。随着输水次数和年输水量的稳步增加,研究区植被覆盖类型将向覆盖度、面积稳步增长的平衡态发展,而随着输水量的减少,植被覆盖又转向类型变化频繁的非平衡态。植被覆盖度的增减变化客观反映了输水状况(输水量、输水持续时间),持续、稳定的输水是植被覆盖(覆盖度、面积)稳步增长的前提。