荒漠生态质量科学框架:概念、指标、监测及评估（英文）

荒漠生态系统是地球上最大的陆地生态系统,全球四分之一的人口生活在这一区域。清晰地定义荒漠生态系统生态质量,制定反映生态质量优劣的关键监测指标,集成"星–空–地"一体化监测技术、构建综合评价模型可为干旱区生态质量监测、促进区域可持续发展提供技术支撑。荒漠生态质量是指一定时空范围内荒漠生态系统要素、结构和功能的综合特征。该研究通过集成卫星、无人机和地面传感器网络的"星–空–地"一体化监测技术,在区域和站点两个尺度上对荒漠生态系统的生态要素、生物多样性和生态功能进行连续监测,通过标准化生态质量指标数值、厘定其阈值范围,构造判断矩阵建立生态质量综合评价模型,评价荒漠生态系统质量状况。本论文阐明了构建荒漠生态质量动态综合监测技术规范与评价方法的概念框架,为实现我国荒漠生态系统生态质量综合监测、科学诊断和定量评估提供理论基础。     

The Scientific Conceptual Framework for Ecological Quality of the Dryland Ecosystem: Concepts,Indicators, Monitoring and Assessment

The dryland ecosystem is the dominant component of the global terrestrial ecosystem since arid regions occupy 45% of the earth’s land area and feed 38% of the world's population. The stability and sustainable development of the dryland ecosystem are critical for achieving the millennium development goal (MDG) in the arid and semiarid areas. However, there is still no scientific guideline for measuring and conserving the health and productivity of dryland ecosystems. Therefore, the purpose of this study is to develop the scientific conceptual framework of defining, monitoring and evaluating the ecological quality of dryland ecosystems. The ecological quality of dryland ecosystems is represented by a system of comprehensive indicators that are each extracted from the ecological elements, and structural and functional indices of the ecosystem. These indicators can be monitored by integrating satellites and unmanned aerial vehicles with ground-based sensor networks at the scale of either observational sites or regional scales. Finally, the ecological quality can be evaluated by evaluation models based on the normalized index values and their thresholds. This paper presents a conceptual framework for monitoring and evaluating the ecological quality of drylands, which provides a way of advancing the monitoring, diagnosis, and evaluation of the ecological quality of the dryland ecosystems.     

渤、黄海生态环境模拟的参数敏感度空间差异分析

随着海洋生态系统模型的发展,生态变量增多,众多生物过程参数量值的确定成为制约生态环境模拟的瓶颈问题,生态系统结构区域性要求模型中的生态参数具有区域差异。为探究不同海区的关键参数及参数敏感度的空间差异,本研究在渤、黄海建立了ROMS-CoSiNE物理–生物耦合的高分辨率生态系统模型,并对13种生态参数的敏感度空间分布进行分析。结果表明:南黄海中部与渤海及近岸海域的敏感度差异较大。渤海敏感度最大的参数为决定光合速率的浮游植物P-I曲线初始斜率,其次为浮游动物捕食半饱和常数和浮游动物最大捕食率。而南黄海中部敏感度最大的参数为浮游动物最大捕食率,其次为浮游植物死亡率和浮游植物P-I曲线初始斜率。结合敏感度分布及浮游植物生物量收支得出,渤海水体透明度较南黄海偏低、浮游植物生长光限制较强,是引起浮游植物P-I曲线初始斜率敏感度在渤海高于黄海的主要原因。浮游动物最大捕食率及浮游植物死亡率的敏感度空间差异,受渤、黄海浮游植物生物量差异的影响,与生态系统中的高度非线性特征有关。     

基于多源遥感数据的区域生态系统服务价值年际动态监测 ——以中原城市群为例

通过对多源遥感数据在生态系统服务价值（ESV）遥感模型中的尺度效应分析,选择满足最佳空间分辨率和长时间序列的遥感数据,对中原城市群区域2001~2013年的ESV实现了逐年逐像元水平的动态监测。结果表明：该区应用于遥感模型输入数据的最适空间分辨率为30~1 000 m,相对于30 m尺度,其他尺度估算结果的相对偏差均小于0.4%;结合年际动态监测的需求,选择了MODIS数据产品（空间分辨率500 m,时间尺度1 a）作为遥感模型的最佳数据源;研究区ESV总值在研究期内整体上呈显著增长趋势,增速约为8.6亿元/a,但在持续增长过程中经历了3次波动,且表现得越来越剧烈;在空间上,研究区ESV多年均值呈现出明显的不均衡性,表现为从西南向东部递减的趋势。研究表明此方法简单易行,初步实现了区域ESV年际动态监测遥感模型的准业务化运行。     

生态系统服务弹性敏感性系数的合理性与决策属性探讨

在经济学弹性基本概念的基础之上,采用数学推导的方式重点探讨3种生态系统服务弹性敏感性评价模型的合理性与决策属性。研究结果表明：① Kreuter敏感性系数大小始终为0~1;在极限形式下,生态系统服务价值变率函数与Kreuter敏感性系数具有相同的数学表达式与值域;所以这两种敏感性评价模型把1作为是否敏感的评价标准并不合适。生态系统服务交叉敏感性系数不符合一般意义上的“交叉敏感性”的概念,并且其计算公式不符合弹性的基本定义。② 弹性敏感性计算方式适用于随机变量间的研究,不适用于具有确定性关系的变量;生态系统服务框架下的3种弹性敏感性系数均建立在具有确定性关系的生态系统服务价值计算公式的基础之上,导致其敏感性计算结果缺乏深层次的决策属性。     

海洋生态系统净生产力研究进展

海洋生态系统净生产力 （net ecosystem production,NEP） 表示总初级生产力 （gross primary production,GPP） 和呼吸作用 （respiration,R） 过程之间的差异,它对碳收支平衡、海洋生态系统营养状态乃至气候变化等研究具有十分重要的指示意义。影响海洋 NEP 的因素有细菌、浮游生物、温度、太阳辐射、海冰融化、水团迁移、富营养有机质排放以及海水酸化等。目前计算 NEP 的方法可分为实验培养测定及数据模型计算两种。溶解氧培养法及同位素标记法等是经典的培养测定方法,但存在误差较大且重现性较差等问题。数据模型计算即借助养分质量平衡、响应面模型、O2/Ar 示踪等方法,通过将现场实测数据和生物地球化学模型结合,进行高时间分辨率的连续性观测,这也是目前测算 NEP 的主流应用手段。然而,相较于发达国家,我国在 NEP 的研究设备、技术、测定方法等方面仍存在一定差距。今后的研究重点将是建立 NEP 指标与表征海洋环境、气候变化之间的耦合关系以及 NEP 测定方法的改进,这将有助于深入理解和探索全球变化背景下海洋生态系统响应机制及变化趋势。     

Ecosystem health assessment of Honghu Lake Wetland of China using artificial neural network approach

Honghu Lake, located in the southeast of Hubei Province, China, has suffered a severe disturbance during the past few decades. To restore the ecosystem, the Honghu Lake Wetland Protection and Restoration Demonstration Project (HLWPRDP) has been implemented since 2004. A back propagation (BP) artificial neural network (ANN) approach was applied to evaluatinig the ecosystem health of the Honghu Lake wetland. And the effectiveness of the HLWPRDP was also assessed by comparing the ecosystem health before and after the project. Particularly, 12 ecosystem health indices were used as evaluation parameters to establish a set of three-layer BP ANNs. The output is one layer of ecosystem health index. After training and testing the BP ANNs, an optimal model of BP ANNs was selected to assess the ecosystem health of the Honghu Lake wetland. The result indicates that four stages can be identified based on the change of the ecosystem health from 1990 to 2008 and the ecosystem health index ranges from morbidity before the implementation of HLWPRDP (in 2002) to middle health after the implementation of the HLWPRDP (in 2005). It demonstrates that the HLWPRDP is effective and the BP ANN could be used as a tool for the assessment of ecosystem health.     

基于参数空间分布的海洋生态系统模拟

在模拟大尺度海洋生态系统时,由于子区域的生态系统有着各自的特征,导致参数值在空间上存在差异,因此参数在整个研究区域取常数的做法必须改进.基于此,使用气候模式FOAM的气侯态背景场驱动一个简单的三维海洋生态系统模型,并引入参数的空间分布,在全球尺度上通过伴随方法同化SeaWiFS叶绿素资料.引入参数空间分布后,同化结果得到很大改进:浮游植物表层生物量(氮)的平均差从0.155 3减小至0.060 6 mmol·m-3,下降了60.9%,有效地降低了模拟值与观测值在空间上的差异;浮游植物表层生物量平均值也从0.103 1上升至0.125 2 mmol·m-3,更接近SeaWiFS观测.实验结果表明通过引入参数的空间分布来改进海洋生态系统的模拟是可行的.     

Climate change and coral reef bleaching: An ecological assessment of long-term impacts,recovery trends and future outlook

Since the early 1980s, episodes of coral reef bleaching and mortality, due primarily to climate-induced ocean warming, have occurred almost annually in one or more of the world's tropical or subtropical seas. Bleaching is episodic, with the most severe events typically accompanying coupled ocean–atmosphere phenomena, such as the El Niño-Southern Oscillation (ENSO), which result in sustained regional elevations of ocean temperature. Using this extended dataset (25+ years), we review the short- and long-term ecological impacts of coral bleaching on reef ecosystems, and quantitatively synthesize recovery data worldwide. Bleaching episodes have resulted in catastrophic loss of coral cover in some locations, and have changed coral community structure in many others, with a potentially critical influence on the maintenance of biodiversity in the marine tropics. Bleaching has also set the stage for other declines in reef health, such as increases in coral diseases, the breakdown of reef framework by bioeroders, and the loss of critical habitat for associated reef fishes and other biota. Secondary ecological effects, such as the concentration of predators on remnant surviving coral populations, have also accelerated the pace of decline in some areas. Although bleaching severity and recovery have been variable across all spatial scales, some reefs have experienced relatively rapid recovery from severe bleaching impacts. There has been a significant overall recovery of coral cover in the Indian Ocean, where many reefs were devastated by a single large bleaching event in 1998. In contrast, coral cover on western Atlantic reefs has generally continued to decline in response to multiple smaller bleaching events and a diverse set of chronic secondary stressors. No clear trends are apparent in the eastern Pacific, the central-southern-western Pacific or the Arabian Gulf, where some reefs are recovering and others are not. The majority of survivors and new recruits on regenerating and recovering coral reefs have originated from broadcast spawning taxa with a potential for asexual growth, relatively long distance dispersal, successful settlement, rapid growth and a capacity for framework construction. Whether or not affected reefs can continue to function as before will depend on: (1) how much coral cover is lost, and which species are locally extirpated; (2) the ability of remnant and recovering coral communities to adapt or acclimatize to higher temperatures and other climatic factors such as reductions in aragonite saturation state; (3) the changing balance between reef accumulation and bioerosion; and (4) our ability to maintain ecosystem resilience by restoring healthy levels of herbivory, macroalgal cover, and coral recruitment. Bleaching disturbances are likely to become a chronic stress in many reef areas in the coming decades, and coral communities, if they cannot recover quickly enough, are likely to be reduced to their most hardy or adaptable constituents. Some degraded reefs may already be approaching this ecological asymptote, although to date there have not been any global extinctions of individual coral species as a result of bleaching events. Since human populations inhabiting tropical coastal areas derive great value from coral reefs, the degradation of these ecosystems as a result of coral bleaching and its associated impacts is of considerable societal, as well as biological concern. Coral reef conservation strategies now recognize climate change as a principal threat, and are engaged in efforts to allocate conservation activity according to geographic-, taxonomic-, and habitat-specific priorities to maximize coral reef survival. Efforts to forecast and monitor bleaching, involving both remote sensed observations and coupled ocean–atmosphere climate models, are also underway. In addition to these efforts, attempts to minimize and mitigate bleaching impacts on reefs are immediately required. If significant reductions in greenhouse gas emissions can be achieved within the next two to three decades, maximizing coral survivorship during this time may be critical to ensuring healthy reefs can recover in the long term.