Protected area planning to conserve biodiversity in an uncertain future

Protected areas are a key instrument for conservation. Despite this, they are vulnerable to risks associated with weak governance, land-use intensification, and climate change. We used a novel hierarchical optimization approach to identify priority areas for expanding the global protected area system that explicitly accounted for such risks while maximizing protection of all known terrestrial vertebrate species. To incorporate risk categories, we built on the minimum set problem, where the objective is to reach species distribution protection targets while accounting for 1 constraint, such as land cost or area. We expanded this approach to include multiple objectives accounting for risk in the problem formulation by treating each risk layer as a separate objective in the problem formulation. Reducing exposure to these risks required expanding the area of the global protected area system by 1.6% while still meeting conservation targets. Incorporating risks from weak governance drove the greatest changes in spatial priorities for protection, and incorporating risks from climate change required the largest increase (2.52%) in global protected area. Conserving wide-ranging species required countries with relatively strong governance to protect more land when they bordered nations with comparatively weak governance. Our results underscore the need for cross-jurisdictional coordination and demonstrate how risk can be efficiently incorporated into conservation planning. Planeación de las áreas protegidas para conservar la biodiversidad en un futuro incierto     

Starch-Based Materials Encapsulating Anthocyanins: A Review

Journal of Polymers and the Environment - Anthocyanins (ACNs) are natural pigments broadly used in the food industry due to their color, antioxidant, and antimicrobial properties, however, these...     

Assessing conservation status with extensive but low-resolution data: Application of frequentist and Bayesian models to endangered Athabasca River rainbow trout

Use of extensive but low-resolution abundance data is common in the assessment of species at-risk status based on quantitative decline criteria under International Union for Conservation of Nature (IUCN) and national endangered species legislation. Such data can be problematic for 3 reasons. First, statistical power to reject the null hypothesis of no change is often low because of small sample size and high sampling uncertainty leading to a high frequency of type II errors. Second, range-wide assessments composed of multiple site-specific observations do not effectively weight site-specific trends into global trends. Third, uncertainty in site-specific temporal trends and relative abundance are not propagated at the appropriate spatial scale. A common result is the propensity to underestimate the magnitude of declines and therefore fail to identify the appropriate at-risk status for a species. We used 3 statistical approaches, from simple to more complex, to estimate temporal decline rates for a designatable unit (DU) of rainbow trout in the Athabasca River watershed in western Canada. This DU is considered a native species for purposes of listing because of its genetic composition characterized as >0.95 indigenous origin in the face of continuing introgressive hybridization with introduced populations in the watershed. Analysis of abundance trends from 57 time series with a fixed-effects model identified 33 sites with negative trends, but only 2 were statistically significant. By contrast, a hierarchical linear mixed model weighted by site-specific abundance provided a DU-wide decline estimate of 16.4% per year and a 3-generation decline of 93.2%. A hierarchical Bayesian mixed model yielded a similar 3-generation decline trend of 91.3% and the posterior distribution showed that the estimate had a >99% probability of exceeding thresholds for an endangered listing. We conclude that the Bayesian approach was the most useful because it provided a probabilistic statement of threshold exceedance in support of an at-risk status recommendation.     

Methods for selenium removal from contaminated waters: a review

Environmental Chemistry Letters - Worldwide contamination of waters by metals, metalloids, and organometallic pollutants is a major health issue. In particular, the occurrence of the selenium...     

我国4个大城市空气PM_(2.5)、PM_(10)污染及其化学组成

报告了 1 995～ 1 996年在中国的广州、武汉、兰州、重庆 4大城市 8个采样点 PM2 .5 、PM2 .5～ 1 0 和 PM1 0 的监测结果。结果表明 ,1 995年 PM2 .5 年均值浓度为 57～ 1 60 μg/m3,比美国 1 997年颁布的标准值 (1 5μg/m3)高 2 .8～ 9.7倍。PM1 0 年日均值为 95～ 2 73μg/m3。除武汉市 1个对照点外 ,其余 7个监测点的 PM1 0 均超过我国空气质量二极标准 (1 0 0μg/m3)2 8%～ 1 73 % ,比美国标准 (50μg/m3)超过更多 ,说明污染是相当严重的。用 XRF分析了 PM2 .5 、PM2 .5～ 1 0 中 4 2种化学元素 ,结果表明 ,燃煤、燃油和其它工业污染的元素 As、Pb、Se、Zn、Cu、Cl、Br、S在这些颗粒物中有明显富集 ,特别是在PM2 .5 中的富集倍数达数十倍至数万倍 ,对人体健康有很大危害