A triage framework for managing novel,hybrid, and designed marine ecosystems

The novel ecosystem (NE) concept has been discussed in terrestrial restoration ecology over the last 15 years but has not yet found much traction in the marine context. Against a background of unprecedented environmental change, managers of natural marine resources have portfolios full of altered systems for which restoration to a previous historical baseline may be impractical for ecological, social, or financial reasons. In these cases, the NE concept is useful for weighing options and emphasizes the risk of doing nothing by forcing questions regarding the value of novelty and how it can best be managed in the marine realm. Here, we explore how the concept fits marine ecosystems. We propose a scheme regarding how the NE concept could be used as a triage framework for use in marine environments within the context of a decision framework that explicitly considers changed ecosystems and whether restoration is the best or only option. We propose a conceptual diagram to show where marine NEs fit in the continuum of unaltered to shifted marine ecosystems. Overall, we suggest that the NE concept is of interest to marine ecologists and resource managers because it introduces a new vocabulary for considering marine systems that have been changed through human actions but have not shifted to an alternate stable state. Although it remains to be seen whether the concept of marine NEs leads to better conservation and restoration decisions, we posit that the concept may help inform management decisions in an era of unprecedented global marine change.     

Application of a Probabilistic Risk Assessment Methodology to a Lead Smelter Site

Exposure of children to lead in the environment was assessed at the Murray Smelter Superfund site using both a deterministic risk assessment approach, the Integrated Exposure Uptake Biokinetic (IEUBK) model, and a probabilistic approach, the Integrated Stochastic Exposure (ISE) model. When site-specific data on lead in environmental media were input as point estimates into the IEUBK model, unacceptable risks were predicted for children living within five of eight study zones. The predicted soil cleanup goal was 550?ppm. Concentration and exposure data were then input into the ISE model as probability distribution functions and a one-dimensional Monte Carlo analysis (ID MCA) was run to predict the expected distribution of exposures and blood lead values. Uncertainty surrounding these predictions was examined in a two-dimensional Monte Carlo analysis (2-D MCA). The ISE model predicted risks that were in the same rank order as those predicted by the IEUBK model, although the probability estimates of exceeding a blood lead level of 10?µg/dl (referred to as the P10) from the ISE model were uniformly lower than those predicted by the IEUBK model. The 2-D MCA allowed evaluation of the confidence around each P10 level, and identified the main sources of both uncertainty and variability in exposure estimates. The ISE model suggested cleanup goals ranging from 1300 to 1500 ppm might be protective at this site.     

Obtaining Critical Values for Simultaneous Confidence Intervals and Multiple Testing

There are many situations where it is desired to make simultaneous tests or give simultaneous confidence intervals for linear combinations (contrasts) of population or treatment means. Somerville (1997, 1999) developed algorithms for calculating the critical values for a large class of simultaneous tests and simultaneous confidence intervals. Fortran 90 and SAS‐IML batch programs and interactive programs were developed. These programs calculate the critical values for 15 different simultaneous confidence interval procedures (and the corresponding simultaneous tests) and for arbitrary procedures where the user specifies a combination of one and two sided contrasts. The programs can also be used to obtain the constants for “step‐down” testing of multiple hypotheses. This paper gives examples of the use of the algorithms and programs and illustrates their versatility and generality. The designs need not be balanced, multiple covariates may be present and there may be many missing values. The use of multiple regression and dummy variables to obtain the required variance covariance matrix is illustrated. Under weak normality assumptions the methods are “exact” and make the use of approximate methods or “simulation” unnecessary.     

Implications of future climate and atmospheric CO2 content for regional biogeochemistry,biogeography and ecosystem services across East Africa

We model future changes in land biogeochemistry and biogeography across East Africa. East Africa is one of few tropical regions where general circulation model (GCM) future climate projections exhibit a robust response of strong future warming and general annual‐mean rainfall increases. Eighteen future climate projections from nine GCMs participating in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment were used as input to the LPJ dynamic global vegetation model (DGVM), which predicted vegetation patterns and carbon storage in agreement with satellite observations and forest inventory data under the present‐day climate. All simulations showed future increases in tropical woody vegetation over the region at the expense of grasslands. Regional increases in net primary productivity (NPP) (18–36%) and total carbon storage (3–13%) by 2080–2099 compared with the present‐day were common to all simulations. Despite decreases in soil carbon after 2050, seven out of nine simulations continued to show an annual net land carbon sink in the final decades of the 21st century because vegetation biomass continued to increase. The seasonal cycles of rainfall and soil moisture show future increases in wet season rainfall across the GCMs with generally little change in dry season rainfall. Based on the simulated present‐day climate and its future trends, the GCMs can be grouped into four broad categories. Overall, our model results suggest that East Africa, a populous and economically poor region, is likely to experience some ecosystem service benefits through increased precipitation, river runoff and fresh water availability. Resulting enhancements in NPP may lead to improved crop yields in some areas. Our results stand in partial contradiction to other studies that suggest possible negative consequences for agriculture, biodiversity and other ecosystem services caused by temperature increases.     

Ecosystem services and management options as blanket indicators of ecosystem health

A pragmatic and integrative approach to evaluation of the environment combines ecosystem sciences, health sciences, and social sciences. Each has a crucial role to play: the ecosystem sciences provide information on the complex dynamics of ecosystems as they are influenced by stress and disturbance; the health sciences provide a methodology for systematic diagnosis of pathology, taxonomy of ills, and models for preventive as well as rehabilitative modes; the social sciences bring to the fore the importance of human values which are part and parcel of any health evaluation. The complexity of stress-response systems precludes anything approximating a complete understanding of mechanisms underpinning ecosystem transformations. However, the loss of ecosystem services and management options appears to be a general phenomenon that permits an overall evaluation of ecosystem health in both aquatic and terrestrial systems. Such blanket indicators take into account both the impairment of ecosystem function and societal values. This is illustrated by the history of ecosystem transformation in the Laurentian Lower Great Lakes and in the overharvested forest ecosystems of Eastern Canada. In both cases, cultural stress resulted in losses in highly valued ecosystem services and management options. These losses have been partially compensated for by new technologies that have permitted commercial use of the remaining lower quality resources. This process itself, however, may be pathological, reinforcing a degradation sequence rather than serving to restore ecosystem health.     

内蒙古羊草草原群落主要植物的热值动态

对内蒙古羊草草原主要植物种群的干重热值动态研究表明,热值随植物种类,植物部位,取样时植物所处物候期及气候条件的不同而变化,羊草草原主要植物种群地上部分热值的变动范围在15703－18141J／g之间,其中灌木小叶锦鸡儿（Caragang microphylla)的热值最高,禾草类植物的热值多数较高,而大多数杂类草的热值相对较低,主要植物种群地下部分热值的分布范围为15051－16410J/g。其中根茎型草地下部分热值较高。不同种类植物地下部分热值差异并不与地上部分一致,根茎型禾草地上、地下部分热值差异较小,而须根型植物差异较在,不同种群的植物地上部分热值随植物候期的不同而波动,其变化规律是与植物种群本身的生物学特性相联系的,不同植物种群热值的年际小 规律有所不同,羊草（Leymus chinensis)、大针茅（Stipa grandis)和洽草（Koeloria cristata)的年际热值波动相关显著。但与生长季降水量和生长季累积日照时数之间无明显相关性,在某种程度上,植物热值的 种内变化反映了植物生长状况的差异。     

Design for Recycling

As design for recycling becomes more broadly applied in material and product design, analytical tools to quantify the environmental implications of design choices will become a necessity. Currently, few systematic methods exist to measure and direct the metallurgical alloy design process to create alloys that are most able to be produced from scrap. This is due, in part, to the difficulty in evaluating such a context‐dependent property as recyclability of an alloy, which will depend on the types of scraps available to producers, the compositional characteristics of those scraps, their yield, and the alloy specification itself. This article explores the use of a chance‐constrained based optimization model, similar to models used in operational planning in secondary production today, to (1) characterize the challenge of developing recycling‐friendly alloys due to the contextual sensitivity of recycling, (2) demonstrate how such models can be used to evaluate the potential scrap usage of alloys, and (3) explore the value of sensitivity analysis information to proactively identify effective alloy modifications that can drive increased potential scrap use. These objectives are demonstrated through two cases that involve the production of a broad range of alloys utilizing representative scraps from three classes of industrial end uses.     

Assessing the suitable habitat for reintroduction of brown trout (Salmo trutta forma fario) in a lowland river: A modeling approach

Huge efforts have been made during the past decades to improve the water quality and to restore the physical habitat of rivers and streams in western Europe. This has led to an improvement in biological water quality and an increase in fish stocks in many countries. However, several rheophilic fish species such as brown trout are still categorized as vulnerable in lowland streams in Flanders (Belgium). In order to support cost‐efficient restoration programs, habitat suitability modeling can be used. In this study, we developed an ensemble of habitat suitability models using metaheuristic algorithms to explore the importance of a large number of environmental variables, including chemical, physical, and hydromorphological characteristics to determine the suitable habitat for reintroduction of brown trout in the Zwalm River basin (Flanders, Belgium), which is included in the Habitats Directive. Mean stream velocity, water temperature, hiding opportunities, and presence of pools or riffles were identified as the most important variables determining the habitat suitability. Brown trout mainly preferred streams with a relatively high mean reach stream velocity (0.2–1 m/s), a low water temperature (7–15°C), and the presence of pools. The ensemble of models indicated that most of the tributaries and headwaters were suitable for the species. Synthesis and applications. Our results indicate that this modeling approach can be used to support river management, not only for brown trout but also for other species in similar geographical regions. Specifically for the Zwalm River basin, future restoration of the physical habitat, removal of the remaining migration barriers and the development of suitable spawning grounds could promote the successful restoration of brown trout.