迁徙季节水鸟对滨海不同类型湿地的利用——以广西山口红树林自然保护区为例

为了解迁徙季节水鸟在不同滨海湿地中的结构组成和行为特征,于2010年3月、4月、9月、11月和2011年3月,在山口自然保护区及其周边地区对不同滨海湿地类型的水鸟展开调查。结果显示:迁徙季节天然湿地共记录到水鸟6目8科39种,人工湿地有6目9科50种。天然湿地比人工湿地的物种数少,整体数量上,春季人工湿地大于天然湿地,秋季则为天然湿地水鸟数量更多。鹬鸻类在不同滨海湿地类型中觅食行为比例差异显著,在天然湿地中觅食比例达到76.67%,而在人工湿地中则以休息和睡眠等非觅食行为为主。天然湿地是鹬鸻类的重要觅食地,而人工湿地则是鹭类和鹬鸻类的主要休息地。鹭类在两种滨海湿地类型中觅食个体的数量不随潮汐的涨落而相应增减。鹬鸻类随潮汐高度上升,在两种滨海湿地类型中觅食的个体数量减少。山口地区的滨海人工湿地是水鸟在高潮期间天然湿地良好的替代栖息地。     

胶洲湾5 种海藻中的多不饱和脂肪酸与有机氯农药共摄入风险的评估研究

海藻中含有丰富的多不饱和脂肪酸(PUFA),但同时也富集一定浓度的有机氯农药,食用海藻摄入多不饱和脂肪酸的同时也会摄入这类污染物,其共摄入风险分析评估是食品安全领域必须关注的科学问题。本文以胶州湾近岸采集的条斑紫菜、坛紫菜、海带、裙带菜、龙须菜等5种常见经济海藻为研究对象,分析了其脂肪酸和有机氯农药组成情况。结果表明,这5种海藻中脂肪酸以棕榈酸、油酸、亚油酸、花生四烯酸和二十碳五烯酸(DHA)为主,n-6和n-3 PUFA的比值远小于建议值4,均有较高的营养价值;5种海藻中六六六类农药主要残留的是γ-HCH,滴滴涕类农药中P,P’-DDD、P,P’-DDT残留量较高。对PUFAs中的有效成分二十碳五烯酸(EPA)+DHA与有机氯农药污染物共摄入时对人体的益害风险进行了评估,发现对于健康成人在达到EPA+DHA摄入要求下,食用这5种海藻带来的多不饱和脂肪酸与有机氯农药污染物共摄入引起非致癌或致癌的健康风险较低。     

海冰对北极海冰边缘区大洋光学观测的影响评估

Diffuse attenuation coefficient(DAC) of sea water is an important parameter in ocean thermodynamics and biology, reflecting the absorption capability of sea water in different layers. In the Arctic Ocean, however, sea ice affects the radiance/irradiance measurements of upper ocean, which results in obvious errors in the DAC calculation. To better understand the impacts of sea ice on the ocean optics observations, a series of in situ experiments were carried out in the summer of 2009 in the southern Beaufort Sea. Observational results show that the profiles of spectral diffuse attenuation coefficients of seawater near ice cover within upper surface of 50 m were not contaminated by the sea ice with a solar zenith angle of 55°, relative azimuth angle of 110°≤φ≤115° and horizontal distance between the sensors and ice edge of greater than 25 m. Based on geometric optics theory, the impact of ice cover could be avoided by adjusting the relative solar azimuth angle in a particular distance between the instrument and ice. Under an overcast sky, ice cover being 25 m away from sensors did not affect the profiles of spectral DACs within the upper 50 m either. Moreover, reliable spectral DACs of seawater could be obtained with sensors completely covered by sea ice.     

Fishers' perceptions,facilitating factors and challenges of community-based no-take zones in the Sian Ka’an Biosphere Reserve,Quintana Roo,Mexico

In response to fisheries decline in the Mexican Caribbean and continuing deterioration of the Mesoamerican Reef, conservation NGOs have begun to negotiate and collaboratively design a network of no-take zones (NTZs) with three fishing cooperatives in the Sian Ka’an Biosphere Reserve (SKBR), among other places along the coast of Quintana Roo. Spiny lobster (Panulirus argus) is the target of the main fishery within cooperative concessions. Fishers are uniquely positioned to enforce and monitor NTZs and evaluate their effectiveness. This study analyzes fishers' perceptions as indicators of social acceptance of NTZs, and identifies facilitating factors and challenges of the community-based process. Consistent with similar studies, responses of fishers (89 out of a population of 124) to a semi-structured interview showed that perceptions of NTZs largely reflect fishers' concerns and interests. A high proportion of fishers accurately identified main NTZ objectives of regulation, conservation and economic improvement, as well as NTZ locations. Further, fishers cared about ecosystem sustainability and, because NTZs would not significantly limit their main economic activity, endorsed the initiative while expecting additional benefits. Declining trends in lobster catch influenced a perceived need for NTZs. Major concerns were that illegal fishers would reap NTZ benefits and that economic impacts and benefits were uncertain. Most fishers found the decision-making process inclusive, were willing to take responsibility for enforcing NTZs and believed people leading the process were trustworthy. Differences in endorsement of NTZs among cooperatives points to the importance of understanding fishers’ incentives to collaborate, and the leadership and organizational dynamics which shape participatory processes. This analysis highlights challenges in advancing NTZs in complex ecological, socio-economic and regulatory contexts. It underscores the need for community-based processes that transcend understanding of conservation measures but also invests in sustainable, operative and trustful working relationships, as well as the urgency of interdisciplinary approaches in ensuring effective design and implementation of this relatively new fishery management tool.     

基于PSR 模型的厦门湾中华白海豚资源评价

中华白海豚(Sousa chinensis Osbeck,1765)为国家Ⅰ级重点野生保护动物,厦门湾作为其在中国的主要分布区之一,自20世纪80年代以来,海岸带开发活动和环境污染程度均不断加大,导致此海域中华白海豚的生存环境不断恶化,种群数量日趋减少,资源状况面临严重威胁。作者采用PSR(压力-状态-响应)模型框架,对厦门湾中华白海豚资源面临的主要环境压力、当前的资源状态以及采取的保护响应措施进行了一个较全面的评价,评价结果认为:围填海工程、船只交通、水下爆破作业和陆源排污等人类活动给厦门湾中华白海豚带来了生境缩小、身体伤害、环境污染和饵料短缺等严重影响,厦门市已采取的保护政策响应包括就地保护、迁地保护和公共管理等方面,目前种群资源数量稳定在80头左右并有潜力扩大。基于评价结果,作者提出了加强保护的建议和策略,可为厦门以外海区的中华白海豚保护工作提供参考。     

基于LAGFD-WAM海浪数值模式的海南万宁近海波浪能资源评估

利用1991—2010年的NCEP再分析风场驱动LAGFD-WAM海浪数值模式,通过数值后报方法,对海南万宁近海海域近20年的波浪场进行了逐时数值模拟,数值模拟结果和实测结果对比的一致性良好。在数值后报数据的基础上计算了万宁近海波浪能流密度和能流密度变异系数,并对其年内变化特点、区域分布特征和稳定性进行了分析。万宁近海年均波浪能流密度3—10 k W/m,属于波浪能资源可利用区和较丰富区。年内各月月均能流密度差别较大,12月波浪能资源最好,5月波浪能资源最差。秋季(9—11月)和冬季(12—2月)月均波浪能流密度分别为5—24 k W/m和6—29 k W/m,春季(3—5月)和夏季(6—8月)分别为3—7 k W/m和1—6 k W/m。地形对波浪能量的辐聚作用明显,受岬角、岛屿、海底陡坡等因素影响,大洲岛、白鞍岛周边、大花角附近及白鞍岛以北部分近岸区域形成波浪能富集区。除9月外,年内其他时段能流密度变异系数都在2.8以下,9月能流密度变异系数在3.0—5.9之间。     

基于城市内涝仿真模型的天津风暴潮灾害评估

基于城市内涝仿真模型,根据天津沿海地区的地形、地貌特征以及排水系统等对城市内涝仿真模型进行改进,在沿海边界和河口设置时变水位,使得模型拓展到既能模拟暴雨产生的内涝,也能模拟由于风暴潮侵袭造成的淹没情景。该模型对天津沿海地区历史上典型风暴潮个例以及10年、20年、50年、100年一遇重现期风暴潮产生的积水范围和积水深度进行了模拟,并对2012年8月3日台风达维 (1210) 造成的天津沿海风暴潮进行了业务试应用。将历史风暴潮个例模拟结果以及2012年8月3日的评估结果与实际灾情进行对比,结果显示模型具有较好的模拟能力,可应用于风暴潮灾害的评估和预估业务中,为相关部门和行业提供决策参考。     

Assessing integration of intensity,polarimetric scattering,interferometric coherence and spatial texture metrics in PALSAR-derived land cover classification

Synthetic aperture radar (SAR) is an important alternative to optical remote sensing due to its ability to acquire data regardless of weather conditions and day/night cycle. The Phased Array type L-band SAR (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) provided new opportunities for vegetation and land cover mapping. Most previous studies employing PALSAR investigated the use of one or two feature types (e.g. intensity, coherence); however, little effort has been devoted to assessing the simultaneous integration of multiple types of features. In this study, we bridged this gap by evaluating the potential of using numerous metrics expressing four feature types: intensity, polarimetric scattering, interferometric coherence and spatial texture. Our case study was conducted in Central New York State, USA using multitemporal PALSAR imagery from 2010. The land cover classification implemented an ensemble learning algorithm, namely random forest. Accuracies of each classified map produced from different combinations of features were assessed on a pixel-by-pixel basis using validation data obtained from a stratified random sample. Among the different combinations of feature types evaluated, intensity was the most indispensable because intensity was included in all of the highest accuracy scenarios. However, relative to using only intensity metrics, combining all four feature types increased overall accuracy by 7%. Producer’s and user’s accuracies of the four vegetation classes improved considerably for the best performing combination of features when compared to classifications using only a single feature type.     

Risk mitigation and the social cost of carbon

The social cost of carbon – i.e., the marginal present-value cost imposed by greenhouse gas emissions – is determined by a complex interaction between factual assumptions, modeling methods, and value judgments. Among the most crucial factors is society's willingness to tolerate potentially catastrophic environmental risks. To explore this issue, the present analysis employs a stochastic climate–economy model that accounts for uncertainties in baseline economic growth, baseline emissions, greenhouse gas mitigation costs, carbon cycling, climate sensitivity, and climate change damages. In this model, preferences are specified to reflect the high degree of risk aversion revealed by private investment decisions, signaled by the large observed gap between the average rates of return paid by safe and risky financial instruments. In contrast, most climate–economy models assume much lower risk aversion. Given high risk aversion, the analysis finds that investment in climate stabilization yields especially large net benefits by forestalling low-probability threats to long-run human well-being. Accordingly, the social cost of carbon attains the markedly high value of $25,700 per metric ton of carbon dioxide in a baseline scenario in which emissions are unregulated. This value falls to just $4 per ton as the stringency of control measures is successively increased. These results cast doubt on the idea that the social cost of carbon takes on a uniquely defined, objective value that is independent of policy decisions. This does not, however, rule out the use of carbon prices to achieve the benefits of climate stabilization using least-cost mitigation measures.     

The economic impact of extreme sea-level rise: Ice sheet vulnerability and the social cost of carbon dioxide

The possibility of extreme sea-level rise is one of the commonly cited reasons for concern about climate change. Major increases in sea level would likely be driven by the melting or collapse of major ice sheets. This possibility has implications for the social cost of carbon dioxide, which is a key policy value as well as a useful summary measure of damage caused by greenhouse gas emissions.This paper extends earlier work on the importance of low-probability, high-impact events for the social cost of carbon dioxide to incorporate the possibility of extreme sea-level rise.To estimate its impact, an integrated assessment model is used, which allows a probabilistic assessment of climate change damages based on the linkages between the economic and climate systems. In the model, the generic discontinuity damage is replaced with the possibility of large-scale damage from factors that are taken to be correlated with temperature rise and, crucially for this paper, explicit consideration of extreme sea-level rise.Estimates of the amount of increase in the social cost of carbon dioxide that can be expected from incorporating extreme sea-level rise show that the increase is significant, though not especially large in percentage terms.The paper contributes to the literature of how to represent uncertain climate impacts in integrated assessment models and the associated estimation of the social cost of carbon dioxide.