A robust approach for iterative contaminant source location and release history recovery

Contamination source identification is a crucial step in environmental remediation. The exact contaminant source locations and release histories are often unknown due to lack of records and therefore must be identified through inversion. Coupled source location and release history identification is a complex nonlinear optimization problem. Existing strategies for contaminant source identification have important practical limitations. In many studies, analytical solutions for point sources are used; the problem is often formulated and solved via nonlinear optimization; and model uncertainty is seldom considered. In practice, model uncertainty can be significant because of the uncertainty in model structure and parameters, and the error in numerical solutions. An inaccurate model can lead to erroneous inversion of contaminant sources. In this work, a constrained robust least squares (CRLS) estimator is combined with a branch-and-bound global optimization solver for iteratively identifying source release histories and source locations. CRLS is used for source release history recovery and the global optimization solver is used for location search. CRLS is a robust estimator that was developed to incorporate directly a modeler's prior knowledge of model uncertainty and measurement error. The robustness of CRLS is essential for systems that are ill-conditioned. Because of this decoupling, the total solution time can be reduced significantly. Our numerical experiments show that the combination of CRLS with the global optimization solver achieved better performance than the combination of a non-robust estimator, i.e., the nonnegative least squares (NNLS) method, with the same solver.     

Modelling forest management within a global vegetation model—Part 2: Model validation from a tree to a continental scale

The construction of a new forest management module (FMM) within the ORCHIDEE global vegetation model (GVM) allows a realistic simulation of biomass changes during the life cycle of a forest, which makes many biomass datasets suitable as validation data for the coupled ORCHIDEE-FM GVM. This study uses three datasets to validate ORCHIDEE-FM at different temporal and spatial scales: permanent monitoring plots, yield tables, and the French national inventory data. The last dataset has sufficient geospatial coverage to allow a novel type of validation: inventory plots can be used to produce continuous maps that can be compared to continuous simulations for regional trends in standing volumes and volume increments. ORCHIDEE-FM performs better than simple statistical models for stand-level variables, which include tree density, basal area, standing volume, average circumference and height, when management intensity and initial conditions are known: model efficiency is improved by an average of 0.11, and its average bias does not exceed 25%. The performance of the model is less satisfying for tree-level variables, including extreme circumferences, tree circumference distribution and competition indices, or when management and initial conditions are unknown. At the regional level, when climate forcing is accurate for precipitation, ORCHIDEE-FM is able to reproduce most productivity patterns in France, such as the local lows of needleleaves in the Parisian basin and of broadleaves in south-central France. The simulation of water stress effects on biomass in the Mediterranean region, however, remains problematic, as does the simulation of the wood increment for coniferous trees. These pitfalls pertain to the general ORCHIDEE model rather than to the FMM. Overall, with an average bias seldom exceeding 40%, the performance of ORCHIDEE-FM is deemed reliable to use it as a new modelling tool in the study of the effects of interactions between forest management and climate on biomass stocks of forests across a range of scales from plot to country.     

Global Urban Growth and the Geography of Water Availability,Quality, and Delivery

Globally, urban growth will add 1.5 billion people to cities by 2030, making the difficult task of urban water provisions even more challenging. In this article, we develop a conceptual framework of urban water provision as composed of three axes: water availability, water quality, and water delivery. For each axis, we calculate quantitative proxy measures for all cities with more than 50,000 residents, and then briefly discuss the strategies cities are using in response if they are deficient on one of the axes. We show that 523 million people are in cities where water availability may be an issue, 890 million people are in cities where water quality may be an issue, and 1.3 billion people are in cities where water delivery may be an issue. Tapping into groundwater is a widespread response, regardless of the management challenge, with many cities unsustainably using this resource. The strategies used by cities deficient on the water delivery axis are different than for cities deficient on the water quantity or water quality axis, as lack of financial resources pushes cities toward a different and potentially less effective set of strategies.     

Quantifying progress toward a conservation assessment for all plants

The Global Strategy for Plant Conservation (GSPC) set an ambitious target to achieve a conservation assessment for all known plant species by 2020. We consolidated digitally available plant conservation assessments and reconciled their scientific names and assessment status to predefined standards to provide a quantitative measure of progress toward this target. The 241,919 plant conservation assessments generated represent 111,824 accepted land plant species (vascular plants and bryophytes, not algae). At least 73,081 and up to 90,321 species have been assessed at the global scale, representing 21–26% of known plant species. Of these plant species, at least 27,148 and up to 32,542 are threatened. Eighty plant families, including some of the largest, such as Asteraceae, Orchidaceae, and Rubiaceae, are underassessed and should be the focus of assessment effort if the GSPC target is to be met by 2020. Our data set is accessible online (ThreatSearch) and is a baseline that can be used to directly support other GSPC targets and plant conservation action. Although around one‐quarter of a million plant assessments have been compiled, the majority of plants are still unassessed. The challenge now is to build on this progress and redouble efforts to document conservation status of unassessed plants to better inform conservation decisions and conserve the most threatened species.     

城市生活垃圾处理方式生命周期评价的比较研究

生命周期评价理论与方法作为一种量化环境影响的工具,在诸多领域中得到了广泛的应用。在垃圾处理领域,生命周期评价最早在20世纪90年代得到应用。生命周期评价与城市生活垃圾处理的有效结合,将促进城市生活垃圾的减量化、资源化、无害化目标的实现。总结了生命周期评价理论与方法在城市生活垃圾处理中的应用现状。对国内不同城市生活垃圾处理方式环境影响因子进行比较分析,诸如全球变暖潜力、酸化潜力和富营养化潜力等因子。针对其目标范围定义、数据收集、评价方法的选择、结果解释及工艺改进等方面指出了目前研究的局限性和不足。并对未来城市生活垃圾处理生命周期评价的发展方向进行展望。     

模拟增温效应对西藏苔草繁殖生态的影响

通过采用国际冻原计划模拟增温对植物影响的方法,从繁殖生态学角度研究了西藏苔草（Carex thibetica Franch）种群的物候期、分蘖数、生物量和种群繁殖对增温的响应。结果表明：暖棚内气温、土壤表层温度分别了1.17℃和1.50℃;物候期提前或延迟,生长期延长;增温可以提高西藏苔草的生殖产量,但不提高其种子发芽率;增温可提高西藏苔草分蘖数和生物量;西藏苔草繁殖对策趋于营养繁殖。     

气候变暖背景下森林土壤碳循环研究进展

由人类活动引起的温室效应以及由此造成的气候变暖对森林牛态系统的影响已引起人们的普遍关注.森林土壤碳循环作为全球碳循环的重要组成部分,是决定未来陆地牛物嘲表现为碳源/碳汇的关键环节,揭示这一作用对于准确理解全球变化背景下陆地生态系统碳循环过程具有重要的指导意义.本文主要通过论述影响土壤碳循环过程的5个方面(土壤呼吸、土壤微生物、土壤酶活性、凋落物输入与分解、土壤碳库),综述了近10 a来全球气候变暖对土壤碳循环过程的影响.近年来,尽管已开展了大量有关土壤碳循环对气候变暖的响应及反馈机制的研究,并取得了一定的成果,但研究结果仍然存在很大的不确定性.整合各种密切关联的全球变化现象,完善研究方法和实验手段,加强根际微生态系统碳循环过程与机理研究将是下一步研究的方向和重点.参70     

Role of predator switching in an eco-epidemiological model with disease in the prey

In the present paper we propose a modification of a basic eco-epidemiological model by incorporating predator switching among susceptible and infected prey population. A local and global study of the basic model is performed around the disease-free boundary equilibrium and the interior equilibrium to estimate important parameter thresholds that control disease eradication and species coexistence. Next we analyze the switching model from the same perspective in order to elucidate the role of switching on disease dynamics. Numerical simulations are carried out to justify analytical results.     

Database-driven models of the world's Large Marine Ecosystems

We present a new methodology for database-driven ecosystem model generation and apply the methodology to the world's 66 currently defined Large Marine Ecosystems. The method relies on a large number of spatial and temporal databases, including FishBase, SeaLifeBase, as well as several other databases developed notably as part of the Sea Around Us project. The models are formulated using the freely available Ecopath with Ecosim (EwE) modeling approach and software. We tune the models by fitting to available time series data, but recognize that the models represent only a first-generation of database-driven ecosystem models. We use the models to obtain a first estimate of fish biomass in the world's LMEs. The biggest hurdles at present to further model development and validation are insufficient time series trend information, and data on spatial fishing effort.