Integrating channel design and assessment methods based on sediment transport capacity in gravel bed streams

Natural channel design (NCD) and analytical channel design (ACD) are two competing approaches to stable channel design that share fundamental similarities in accounting for sediment transport processes with designs based on hybrid fluvial geomorphology and hydraulic engineering methods. In this paper, we highlight the linkage between ACD's capacity/supply ratio (CSR) and NCD's sediment capacity models (FLOWSED/POWERSED), illustrating how ACD and NCD have reached a point of convergent evolution within the stream restoration toolbox. We modified an existing CSR analytical spreadsheet tool which enabled us to predict relative channel stability using both conventional bed load transport equations and regional sediment regression curves. The stable channel design solutions based on measured data most closely matched the Parker (ACD) and/or Pagosa good/fair (NCD) relationships, which also showed the greatest CSR sensitivity in response to channel alterations. We found that CSR differences among the transport relationships became more extreme the further the design width deviated from the supply reach, suggesting that a stable upstream supply reach may serve as the best design analog. With this paper, we take a step toward resolving lingering controversy in the field of stream restoration, advancing the science and practice by reconciling key differences between ACD and NCD in the context of reach scale morphodynamics.     

Comparing Vapor Intrusion Mitigation System Performance for VOCs and Radon

This article summarizes a long‐term study of vapor intrusion mitigation system performance in a historic, unoccupied residential duplex with an extensive set of temporal variability observations. The experimental design included multiple cycles of subslab depressurization (SSD) system operation and shut‐off during a seven‐month period, followed by a year‐long period of continuous operation. Results showed that the system provided rapid pressure field extension and radon control as much as 100 days of operation before optimum volatile organic compound (VOC) mitigation was achieved. Greater variability in VOC concentrations than in radon concentrations was observed during the initial mitigation system cycling. Subslab VOC concentrations at numerous locations increased during this initial period of SSD operation, and indoor air VOC concentrations were more variable than radon. However, indoor air concentrations were considerably less variable (and lower) during the first year of continuous mitigation system operation. ©2015 Wiley Periodicals, Inc.     

A Critique of Estimating Future Costs Using Most Likely Value

ASTM E2137 (Standard Guide for Estimating Monetary Costs and Liability for Environmental Matters, or E2137) is the guidance for developing estimates of future environmental costs. E2137 provides a hierarchy of cost estimation approaches, and expresses an explicit preference for the use of probabilistic cost analysis to develop expected values for environmental costs. Dr. Ram and his colleagues have published an article (Remediation Journal, Autumn 2013) which rejects the use of EV analysis, arguing that while “good in principle” it has little practical value because it is nearly impossible to develop supportable probabilities. The E2137 principles and processes have been used for more than a decade in the context of addressing future environmental costs, yet their view of E2137 renders the standard meaningless. We conclude that the deficiency is not in the ASTM standard, and that when properly constructed, probabilistic analyses can be used to develop expected values with supportable probabilities. ©2015 Wiley Periodicals, Inc.     

Fertilization trajectory of the root crop Raphanus sativus across atmospheric pCO2 estimates of the next 300 years

Plant biomass is known to increase in response to elevated atmospheric CO₂ concentration (pCO₂); however, no experiments have quantified the trajectory of crop fertilization across the full range of pCO₂ levels estimated for the next 300 years. Here we quantify the above- and below-ground biomass response of Raphanus sativus (common radish) across eight pCO₂ levels ranging from 348 to 1791 ppmv. We observed a large net biomass increase of 58% above ground and 279% below ground. A large part of the net increase (38% of the above-ground and 53% of the below-ground) represented biomass fertilization at the high levels of pCO₂ (700–1791 ppmv) predicted if fossil fuel emissions continue unabated. The trajectory of below-ground fertilization in R. sativus greatly exceeded a trajectory based on extrapolation of previous experiments for plants grown at pCO₂ < 800 ppmv. Based on the experimental parameters used to grow these plants, we hypothesize that these experiments represent the maximum CO₂ fertilization that can be achieved for this plant growing under low light levels. If the below-ground biomass enhancement that we have quantified for R. sativus represents a generalized root-crop response that can be extrapolated to agricultural systems, below-ground fertilization under very high pCO₂ levels could dramatically augment crop production in some of the poorest nations of the world, provided that water resources are sufficient and sustainable.     

Effects of sampling error and temporal correlations in population growth on process variance estimators

Estimates of a population’s growth rate and process variance from time-series data are often used to calculate risk metrics such as the probability of quasi-extinction, but temporal correlations in the data from sampling error, intrinsic population factors, or environmental conditions can bias process variance estimators and detrimentally affect risk predictions. It has been claimed (McNamara and Harding, Ecol Lett 7:16–20, 2004) that estimates of the long-term variance that incorporate observed temporal correlations in population growth are unaffected by sampling error; however, no estimation procedures were proposed for time-series data. We develop a suite of such long-term variance estimators, and use simulated data with temporally autocorrelated population growth and sampling error to evaluate their performance. In some cases, we get nearly unbiased long-term variance estimates despite ignoring sampling error, but the utility of these estimators is questionable because of large estimation uncertainty and difficulties in estimating correlation structure in practice. Process variance estimators that ignored temporal correlations generally gave more precise estimates of the variability in population growth and of the probability of quasi-extinction. We also found that the estimation of probability of quasi-extinction was greatly improved when quasi-extinction thresholds were set relatively close to population levels. Because of precision concerns, we recommend using simple models for risk estimates despite potential biases, and limiting inference to quantifying relative risk; e.g., changes in risk over time for a single population or comparative risk among populations.     

Simulating dynamic and mixed-severity fire regimes: A process-based fire extension for LANDIS-II

Fire regimes result from reciprocal interactions between vegetation and fire that may be further affected by other disturbances, including climate, landform, and terrain. In this paper, we describe fire and fuel extensions for the forest landscape simulation model, LANDIS-II, that allow dynamic interactions among fire, vegetation, climate, and landscape structure, and incorporate realistic fire characteristics (shapes, distributions, and effects) that can vary within and between fire events. We demonstrate the capabilities of the new extensions using two case study examples with very different ecosystem characteristics: a boreal forest system from central Labrador, Canada, and a mixed conifer system from the Sierra Nevada Mountains (California, USA). In Labrador, comparison between the more complex dynamic fire extension and a classic fire simulator based on a simple fire size distribution showed little difference in terms of mean fire rotation and potential severity, but cumulative burn patterns created by the dynamic fire extension were more heterogeneous due to feedback between fuel types and fire behavior. Simulations in the Sierra Nevada indicated that burn patterns were responsive to topographic features, fuel types, and an extreme weather scenario, although the magnitude of responses depended on elevation. In both study areas, simulated fire size and resulting fire rotation intervals were moderately sensitive to parameters controlling the curvilinear response between fire spread and weather, as well as to the assumptions underlying the correlation between weather conditions and fire duration. Potential fire severity was more variable within the Sierra Nevada landscape and also was more sensitive to the correlation between weather conditions and fire duration. The fire modeling approach described here should be applicable to questions related to climate change and disturbance interactions, particularly within locations characterized by steep topography, where temporally or spatially dynamic vegetation significantly influences spread rates, where fire severity is variable, and where multiple disturbance types of varying severities are common.     

Water Transactions for Streamflow Restoration,Water Supply Reliability,and Rural Economic Vitality in the Western United States

Across the western United States, environmental water transaction programs (EWTPs) restore environmental flows by acquiring water rights and incentivizing changes in water management. These programs have evolved over several decades, expanding from relatively simple two‐party transactions to multiobjective deals that simultaneously benefit the environment and multiple water‐using sectors. Such programs now represent an important water management tool and provide an impetus for collaboration among stakeholders; yet, most evaluations of their effectiveness focus exclusively on environmental outcomes, without adequate attention to impacts on other water users or local economies. To understand how these programs affect stakeholders, a systematic, multiobjective evaluation framework is needed. To meet this need, we developed a suite of environmental and socioeconomic indicators that can guide the design and track the implementation of water transaction portfolios, and we applied them to existing EWTPs in Oregon and Nevada. Application of the indicators quantifies impacts and helps practitioners design water transaction portfolios that avoid unintended consequences and generate mutually beneficial outcomes among environmental, agricultural, and municipal interests.     

Uncertainty-based quantitative assessment of sustainability for higher education institutions

Evaluation of sustainability in various facets of life is gaining increasing importance. Traditionally, different multi-criteria decision-making methods have been used for sustainability assessment. “Sustainability” can be a qualitative concept, and as such several researchers have attempted fuzzy logic for the quantitative assessment of sustainability. This paper outlines a new evaluation model based on fuzzy multi-criteria decision-making. The model is tested for sustainability assessment of higher education institutions (HEIs). It is based on a driving force–pressure–state–exposure–effect–action (DPSEEA) framework and is called uncertainty-based DPSEEA-Sustainability index Model (uD-SiM). The uD-SiM is a causality-based model in which the sustainability index is an outcome of nonlinear impacts of sustainability indicators in different stages of DPSEEA. The percent contribution of driving forces on the sustainability index of HEI is investigated using sensitivity analysis. The study reveals that education in sustainability and global and local research trends are the major driving forces for achieving sustainability in HEI, followed by financial and economic growth rate, social equity, energy requirements rate, and institutional enhancement, in descending order. The results of uD-SiM were found to be more realistic and rational than our earlier proposed approach, D-SiM.     

近期和长远时段内北极生态系统结构受到的影响

生物在物种水平上对全球气候变暖和紫外线B(UV-B)辐射增强的反应受到其群落内其他物种以及生态系统内养分循环的调节,所有的这些反应将会导致生态系统结构的变化.根据高纬度地区坏境因子的可能变化而做的控制试验表明,由夏季变暖而引起苔原植被的变化要小于增加施肥而引起的变化,试验涉及的某些环境因子对北极生态系统的结构有非常强烈地影响,但是这些影响因地区而异,观测结果表明,处于最寒冷地区的植物群落和无脊椎动物群落对全球气候变暖和紫外线B辐射的增强反应最为强烈.尽管微生物量和养分储存量相对稳定,北极无脊椎动物群落还是很可能会对全球变暖产生迅速的反应.试验结果显示,加强紫外线B辐射会改变革兰氏阴性细菌和真菌的群落组成结构,但不会对植物群落的组成产生影响.由夏季气温升高而提高的植物生产力将会控制食物网的动态变化,以苔原植被和亚极地森林植物为基础的食物网中的营养流动会明显地影响到几种优势动物种群数量的周期性波动,在某些年分这些动物的种群数量会达到峰值.小型啮齿动物和食叶昆虫如秋毛虫种群数量的周期性变化则会影响苔原和森林苔原植物的组成结构和多样性,同时也会影响到一些专性捕食者和寄生虫的变化.在暖冬,雪表形成冰壳可能会减少旅鼠的植物食物来源,然而较深的雪也可以使它们免受雪地表面上捕食者对它们的捕食.在芬诺斯堪的亚地区,已有证据表明小型啮齿类动物群落结构和种群动态的显著变化会导致专门以小型啮齿类动物为食物的捕食者的数量减少.气候还可能改变昆虫在白桦森林生态系统中的作用,因为暖冬可以增加这些昆虫卵的成活率,并且扩大其分布范围.此外,在夏季困扰驯鹿的昆虫会由于夏季气候的变暖而扩大其分布范围、增加种群数量并且种群更为活跃;同时在另一方面也会对驯鹿不利,即那些昔日驯鹿/北美驯鹿的避难场所--冰川和未融的成片的雪--在这样温暖的夏季则可能会消失.