Predicting occurrence of juvenile shark habitat to improve conservation planning

Fishing and habitat degradation have increased the extinction risk of sharks, and conservation strategies recognize that survival of juveniles is critical for the effective management of shark populations. Despite the rapid expansion of marine protected areas (MPAs) globally, the paucity of shark‐monitoring data on large scales (100s–1000s km) means that the effectiveness of MPAs in halting shark declines remains unclear. Using data collected by baited remote underwater video systems (BRUVS) in northwestern Australia, we developed generalized linear models to elucidate the ecological drivers of habitat suitability for juvenile sharks. We assessed occurrence patterns at the order and species levels. We included all juvenile sharks sampled and the 3 most abundant species sampled separately (grey reef [Carcharhinus amblyrhynchos], sandbar [Carcharhinus plumbeus], and whitetip reef sharks [Triaenodon obesus]). We predicted the occurrence of juvenile sharks across 490,515 km² of coastal waters and quantified the representation of highly suitable habitats within MPAs. Our species‐level models had higher accuracy (? ≥ 0.69) and deviance explained (≥48%) than our order‐level model (? = 0.36 and deviance explained of 10%). Maps of predicted occurrence revealed different species‐specific patterns of highly suitable habitat. These differences likely reflect different physiological or resource requirements between individual species and validate concerns over the utility of conservation targets based on aggregate species groups as opposed to a species‐focused approach. Highly suitable habitats were poorly represented in MPAs with the most restrictions on extractive activities. This spatial mismatch possibly indicates a lack of explicit conservation targets and information on species distribution during the planning process. Non‐extractive BRUVS provided a useful platform for building the suitability models across large scales to assist conservation planning across multiple maritime jurisdictions, and our approach provides a simple for method for testing the effectiveness of MPAs.     

Fe(Ⅲ)-TAML/过氧化物体系催化降解双酚类化合物及其定量结构活性相关性

双酚类化合物（BPs）,如双酚A（BPA）,由于具有内分泌干扰性,而被广泛关注。本研究测定了8种常见的双酚类化合物,在四酰胺基六甲基苯基环铁（Fe(Ⅲ)-TAML）/过氧化物（即过氧化氢（H₂O₂）和过一硫酸盐（PMS））体系作用下的降解动力学,并通过拟一级动力学方程拟合得到pH10条件下拟一级反应速率常数（K_obs）。利用多元线性回归方法（MLR）探究了K_obs与BPs理论参数之间的相关性,建立了双酚类化合物的定量结构活性相关性（QSAR）模型,并验证了模型对选取的3种测试集具有良好的预测性能。根据模型发现在Fe(Ⅲ)-TAML/PMS体系中,K_obs与最高占据分子轨道能（E_HOMO）呈高度正相关性。而在Fe(Ⅲ)-TAML/H₂O₂体系中,K_obs与偶极矩（μ）呈负相关。这项工作可以为高价铁配合物通过非自由基途径有效降解有机污染物的机理提供新的思路,有助于拓宽均相催化剂在环境修复中的应用。     

General prevention and risk minimization in LCA A combined approach

Methods for life cycle assessment of products (LCA) are most often based on the general prevention principle, as opposed to the risk minimization principle. Here, the desirability and feasibility of a combined approach are discussed, along with the conditions for elaboration in the framework of LCA methodology, and the consequences for LCA practice. A combined approach provides a separate assessment of above and below threshold pollution, offering the possibility to combat above threshold impacts with priority. Spatial differentiation in fate, exposure, and effect modelling is identified to play a central role in the implementation. The collection of region-specific data turns out to be the most elaborate requirement for the implementation in both methodology and practice. A methodological framework for the construction of characterization factors is provided. Along with spatial differentiation of existing parameters, two newly introduced spatial parameters play a key role: the sensitivity factor and the threshold factor. The practicability of the proposed procedure is illustrated by an example of its application. Providing a reasonable data availability, the development of separate LCA characterization factors for the respective assessment of pollution levels above and below environmental threshold values seems to be a feasible task that may add to LCA credibility.     

Impact of Climate Change on Fish Population Dynamics in the Baltic Sea: A Dynamical Downscaling Investigation

Understanding how climate change, exploitation and eutrophication will affect populations and ecosystems of the Baltic Sea can be facilitated with models which realistically combine these forcings into common frameworks. Here, we evaluate sensitivity of fish recruitment and population dynamics to past and future environmental forcings provided by three ocean-biogeochemical models of the Baltic Sea. Modeled temperature explained nearly as much variability in reproductive success of sprat (Sprattus sprattus; Clupeidae) as measured temperatures during 1973-2005, and both the spawner biomass and the temperature have influenced recruitment for at least 50 years. The three Baltic Sea models estimate relatively similar developments (increases) in biomass and fishery yield during twenty-first century climate change (ca. 28 % range among models). However, this uncertainty is exceeded by the one associated with the fish population model, and by the source of global climate data used by regional models. Knowledge of processes and biases could reduce these uncertainties.     

Impacts of interannual climate variability on past and future forest composition

Numerous analyses of the possible impacts of future climatic changes on tree species composition have been published for both lowland and high-elevation forests. Most of these studies were based on the application of forest "gap" models, and the vast majority of them considered only changes in the average of climatic parameters over time. In this study, we use a unique data set on reconstructed past climatic variations to analyse forest dynamics simulated by the forest gap model ForClim. This analysis forms the basis for a systematic exploration of the ecological effects of changing means vs. changing variability of climate on central European forests. A reconstruction of historical climate covering the last 470 years in the Swiss lowlands (ClimIndex) is extrapolated to a transect across the alpine (cold) treeline and used to simulate the influence of climate variations on the time scale of decades on forest biomass and tree species composition at both sites. While the simulation at the low-elevation site shows little sensitivity to climate variations, the results from upper subalpine forests suggest that two major dieback events would have occurred at elevations above the current but below the climatic tree line, induced by clusters of exceptionally cold summers. The results are in agreement with available dendrochronological data and with documentary evidence on massive negative impacts on flora and fauna at high elevations during these periods. We conclude that ForClim is capable of capturing the effects on tree population dynamics of climate variability at these sites as reconstructed from the ClimIndex record. A factorial design is used to address the sensitivity of ForClim to changes of the long-term averages vs. changes of the variability of monthly temperature and precipitation data. To this end, the simulated tree species composition of near-natural forests is examined along a climate gradient in Europe. The results indicate that there are three types of forest response: (1) little sensitivity to both kinds of change, (2) strong sensitivity to changes in the means, but little sensitivity to changing variability, and (3) strong sensitivity to changing variability at least in parts of the examined climate space. Half of the cases investigated fall under the third category, suggesting that emphasis should be placed on also assessing the sensitivity of ecosystems to future changes in climate variability rather than on changes of average values alone. Electronic Publication     

Source and Delivery of Nutrients to Receiving Waters in the Northeastern and Mid‐Atlantic Regions of the United States1

Moore, Richard B., Craig M. Johnston, Richard A. Smith, and Bryan Milstead, 2011. Source and Delivery of Nutrients to Receiving Waters in the Northeastern and Mid‐Atlantic Regions of the United States. Journal of the American Water Resources Association (JAWRA) 47(5):965‐990. DOI: 10.1111/j.1752‐1688.2011.00582.x Abstract: This study investigates nutrient sources and transport to receiving waters, in order to provide spatially detailed information to aid water‐resources managers concerned with eutrophication and nutrient management strategies. SPAtially Referenced Regressions On Watershed attributes (SPARROW) nutrient models were developed for the Northeastern and Mid‐Atlantic (NE US) regions of the United States to represent source conditions for the year 2002. The model developed to examine the source and delivery of nitrogen to the estuaries of nine large rivers along the NE US Seaboard indicated that agricultural sources contribute the largest percentage (37%) of the total nitrogen load delivered to the estuaries. Point sources account for 28% while atmospheric deposition accounts for 20%. A second SPARROW model was used to examine the sources and delivery of phosphorus to lakes and reservoirs throughout the NE US. The greatest attenuation of phosphorus occurred in lakes that were large relative to the size of their watershed. Model results show that, within the NE US, aquatic decay of nutrients is quite limited on an annual basis and that we especially cannot rely on natural attenuation to remove nutrients within the larger rivers nor within lakes with large watersheds relative to the size of the lake.     

健康风险评估方法在中国重金属污染中的应用及暴露评估模型的研究进展

经济的快速发展导致中国环境质量日趋恶化.随着健康意识的增强,人们越来越重视污染物暴露人群的健康风险评估.与其他污染物相比,重金属污染区域广,重金属暴露人群多且集中.为了研究重金属暴露条件下人群的健康风险,USEPA 模型、统计模型、地理信息系统、可给性研究的方法已被中国不同学者应用.暴露评估模型作为污染物暴露人群健康风险评估的主要环节,国外的研究已经比较成熟,但相关研究在中国还处于空白阶段.对中国近年来在城市表层土壤（灰尘）、矿区土壤、膳食、地下水和饮用水、大气颗粒物进行重金属风险评估中应用的健康风险评估方法,进行了归纳和评述,并对欧美常用暴露评估模型：环境暴露评估模型、膳食暴露评估模型进行了介绍.中国健康风险评估工作起步晚,在评估的各环节均存在很大缺陷.随着新技术的发展以及人群对环境健康风险认识的深化,健康风险评估将成为中国热门研究领域之一.污染的环境行为、剂量一效应关系、模型、风险信息等方面,将是未来中国健康风险评估研究的重点.     

Multistate models for monitoring individual trees in permanent observation plots

This interdisciplinary research on forest ecosystems begins with some characteristics of ecosystems which are the basis for the derivation of statistical models for the development and vitality of trees. Several ecological problems which could be solved by longitudinal studies are mentioned. Statistical methods for the evaluation of the crowns of spruce trees (Picea abies Karst) in three permanent observation plots in Switzerland are described. In particular, the time-dependent proportional odds model and a transitional model are used. Through application of these multistate models the data give information on the dependence of an ordered categorical response variable on covariates characterizing the ecosystem. The response variable is observed through infrared aerial photographs. This monitoring system gives insight into the dynamic behaviour of the forest ecosystem. The need for more eco-systematically motivated statistical research using longitudinal studies is identified.