Snorkelling and trampling in shallow-water fringing reefs: risk assessment and proposed management strategy

Shallow reefs (reef flats <1.5 m) in the northern Red Sea are impacted by growing tourism that includes swimmers, snorkellers and reef walkers but have largely been neglected in past studies. We selected a fringing reef along the lagoon of Dahab (Sinai, Egypt) as a model for a management strategy. Point-intercept line transects were used to determine substrate composition, coral community and condition, and the coral damage index (CDI) was applied. Approximately 84% of the coral colonies showed signs of damage such as breakage, partial mortality or algal overgrowth, especially affecting the most frequent coral genus Acropora. Questionnaires were used to determine the visitors' socio-economic background and personal attitudes regarding snorkelling, SCUBA-diving and interest in visiting a prospective snorkelling trail. Experiencing nature (97%) was by far the strongest motivation, and interest in further education about reef ecology and skill training was high. Less experienced snorkellers and divers--the target group for further education and skill training--were those most prepared to financially support such a trail. We therefore recommend a guided underwater snorkelling trail and restricting recreational use to a less sensitive 'ecotourism zone' while protecting the shallow reef flat. Artificial structures can complete the trail and offer the opportunity to snorkel over deeper areas at unfavourable tide or wind conditions. This approach provides a strategy for the management and conservation of shallow-water reefs, which are facing increasing human impact here and elsewhere.     

Characterization of biological responses under different environmental conditions: A hierarchical modeling approach

A natural river system is organized as a nested hierarchy of interconnected habitats with specific environmental conditions to which the biological community has adapted. Due to this hierarchical structure, identifying the role of different stressors on the biological community is a formidable task. Efforts trying to link stressors to biological integrity have always been bound to the geographic scale of the selected study area, leading to scale-specific results. In this research, an attempt is made to lift this limitation and develop a hierarchical, scale-sensitive methodology that can identify the significant environmental stressors to the biological community at different scales. Sites with similar background environmental conditions are clustered using self-organizing maps (SOM). This is used to identify stressors which affect the biological community throughout the area of study - called environmental gradients or large-scale stressors. Subsequently, these clusters of similar observations (sampling sites) are progressively sub-divided using environmental variables with a significant but localized effect on the biological community - called small-scale stressors. A parent group of sites is split only when the resulting sub-groups have significantly different biological responses. At the end of this recursive sites decomposition procedure, the original set of observations is organized as a tree of environmentally homogeneous groups of observations characterized by unique biological responses to multiple stressors with different geographic extents. The developed hierarchical analysis methodology has been validated using a large-size dataset of environmental observations from the State of Ohio. Our results show that habitat degradation and increased nutrient loading are the large-scale stressors with a widespread impact in Ohio. Other stressors, such as heavy metals, pH or nitrate concentrations have significant albeit localized effects on biological integrity.     

Establishing IUCN Red List Criteria for Threatened Ecosystems

Abstract: The potential for conservation of individual species has been greatly advanced by the International Union for Conservation of Nature's (IUCN) development of objective, repeatable, and transparent criteria for assessing extinction risk that explicitly separate risk assessment from priority setting. At the IV World Conservation Congress in 2008, the process began to develop and implement comparable global standards for ecosystems. A working group established by the IUCN has begun formulating a system of quantitative categories and criteria, analogous to those used for species, for assigning levels of threat to ecosystems at local, regional, and global levels. A final system will require definitions of ecosystems; quantification of ecosystem status; identification of the stages of degradation and loss of ecosystems; proxy measures of risk (criteria); classification thresholds for these criteria; and standardized methods for performing assessments. The system will need to reflect the degree and rate of change in an ecosystem's extent, composition, structure, and function, and have its conceptual roots in ecological theory and empirical research. On the basis of these requirements and the hypothesis that ecosystem risk is a function of the risk of its component species, we propose a set of four criteria: recent declines in distribution or ecological function, historical total loss in distribution or ecological function, small distribution combined with decline, or very small distribution. Most work has focused on terrestrial ecosystems, but comparable thresholds and criteria for freshwater and marine ecosystems are also needed. These are the first steps in an international consultation process that will lead to a unified proposal to be presented at the next World Conservation Congress in 2012.     

论开展主要环境质量指标浓度考核

针对现行环境质量考核体系中存在问题,选取主要的环境质量考核指标,提出逐步推行浓度值考核设想,并对比分析该考核办法与现行比例考核办法的优劣。     

Translating habitat class to land cover to map area of habitat of terrestrial vertebrates

Area of habitat (AOH) is defined as the “habitat available to a species, that is, habitat within its range” and is calculated by subtracting areas of unsuitable land cover and elevation from the range. The International Union for the Conservation of Nature (IUCN) Habitats Classification Scheme provides information on species habitat associations, and typically unvalidated expert opinion is used to match habitat to land-cover classes, which generates a source of uncertainty in AOH maps. We developed a data-driven method to translate IUCN habitat classes to land cover based on point locality data for 6986 species of terrestrial mammals, birds, amphibians, and reptiles. We extracted the land-cover class at each point locality and matched it to the IUCN habitat class or classes assigned to each species occurring there. Then, we modeled each land-cover class as a function of IUCN habitat with (SSG, using) logistic regression models. The resulting odds ratios were used to assess the strength of the association between each habitat and land-cover class. We then compared the performance of our data-driven model with those from a published translation table based on expert knowledge. We calculated the association between habitat classes and land-cover classes as a continuous variable, but to map AOH as binary presence or absence, it was necessary to apply a threshold of association. This threshold can be chosen by the user according to the required balance between omission and commission errors. Some habitats (e.g., forest and desert) were assigned to land-cover classes with more confidence than others (e.g., wetlands and artificial). The data-driven translation model and expert knowledge performed equally well, but the model provided greater standardization, objectivity, and repeatability. Furthermore, our approach allowed greater flexibility in the use of the results and uncertainty to be quantified. Our model can be modified for regional examinations and different taxonomic groups.     

北京市紫外线指数的观测研究

1999年5月—2001年10月在北京观象台对紫外线指数(UVI)进行了长期观测,结果表明:UVI季节差异明显,春、夏、秋、冬季的最大值分别为7 85,9 87,4 92,2 99;正午时的平均值分别为3 52,5 31,2 17,1 24。在UVI高峰时段(10:00—15:00),秋、冬季的UVI基本在0～2范围,对人体危害不大;而0～2,3～4,5～6,大于7的各级UVI的平均累积日照时间春季分别为159,87,47,2min,夏季分别为75,99,93,29min,春、夏季紫外线辐射对人体危害较大。另外,UVI的累积分布显示,春、秋、冬季的UVI多数集中在各季节平均值以下,而夏季正午前后的UVI多分布在其季节平均值以上。      

不同环境条件下偶氮染料酸性大红GR的生物降解性能

为了考察不同环境条件下偶氮染料酸性大红GR生物降解性能,采用已驯化的混合菌群作为接种液进行偶氮染料酸性大红GR脱色试验。结果表明,微氧条件下(静置敞口培养),偶氮染料酸性大红GR脱色效果最佳,染料脱色主要发生在菌体的对数生长期。混合菌群对pH、温度适应范围较广,pH为3.32~9.18,温度在20℃~37℃范围内均可以获得较好脱色效果,脱色率均在80%以上。微氧条件下酸性大红GR降解历程表明,偶氮基整个共轭系统被破坏,生成了一种新的结构,使原有的某些精细结构在二阶导数光谱中得以表现,由此探讨其生物降解机理。     

Fenton试剂处理酸性玫瑰红B的研究

采用Fenton试剂处理酸性玫瑰红B染料废水,考察了FeSO4投加量、H2O2投加量、pH值和反应时间对处理效果的影响,研究了原水的氧化还原电位和TOC的变化规律,评价了它的可生化性。结果表明,最佳pH值为3,FeSO4的适宜投加量为8mmol/L,H2O2最佳投加量为50mmol/L,此时COD去除率和脱色率分别为77.1%和92.8%,处理后该染料废水的可生化性大大提高。     

榆林地区植被时空分异特征及其影响因素研究

植被作为反映陆地生态系统和气候的重要指标,对研究全球或区域生态环境变化具有重要作用。以地处黄土高原生态脆弱区的榆林市为研究区,基于地理探测器模型,选取坡向、坡度、气温、降水和土壤类型5类自然因子,土地利用类型、人口密度和GDP 3类人文因子,分析榆林地区植被空间分异特征及其驱动力,并揭示了促进植被生长影响因子的最适宜特征。结果表明,（1）研究区2000—2018年植被覆盖趋向改善,NDVI呈现增加趋势,增速为0.11/10a,2008年以后植被增长较为明显;NDVI在2018年中高等级（0.6—0.8）面积比2000年中高等级面积明显增加;中高等级集中于榆林市东部黄土丘陵区,中低等级（0.2—0.4）集中于榆林市西北部的风沙区,植被覆盖呈现东部高西北低的空间分布特征。（2）人口密度和气温因子较好地解释植被NDVI空间分异性,是影响NDVI空间分异性的主要因子,GDP、土地利用类型和坡度是次级影响因子,其他因子对NDVI空间分异存在间接影响;坡向、降水和土壤类型因子与其他自然、人文因素对植被空间分布影响存在显著性差异。（3）自然、人文因子对榆林市NDVI的影响存在交互作用,因子之间的交互...     

Scaling range sizes to threats for robust predictions of risks to biodiversity

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range‐size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red‐list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale‐sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1–1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer‐scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid‐measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape‐scale threats to species and ecosystems.