A coupled ice-ocean ecosystem model for 1-D and 3-D applications in the Bering and Chukchi Seas

Primary production in the Bering and Chukchi Seas is strongly influenced by the annual cycle of sea ice. Here pelagic and sea ice algal ecosystems coexist and interact with each other. Ecosystem modeling of sea ice associated phytoplankton blooms has been understudied compared to open water ecosystem model applications. This study introduces a general coupled ice-ocean ecosystem model with equations and parameters for 1-D and 3-D applications that is based on 1-D coupled ice-ocean ecosystem model development in the landfast ice in the Chukchi Sea and marginal ice zone of Bering Sea. The biological model includes both pelagic and sea ice algal habitats with 10 compartments： three phytoplankton （pelagic diatom, flagellates and ice algae： D, F, and Ai） , three zooplankton （copepods, large zooplankton, and microzooplankton ： ZS, ZL, ZP） , three nutrients （ nitrate ＋ nitrite, ammonium, silicon ： NO3 , NH4, Si） and detritus （Det）. The coupling of the biological models with physical ocean models is straightforward with just the addition of the advection and diffusion terms to the ecosystem model. The coupling with a multi-category sea ice model requires the same calculation of the sea ice ecosystem model in each ice thickness category and the redistribution between categories caused by both dynamic and thermodynamic forcing as in the physical model. Phytoplankton and ice algal self-shading effect is the sole feedback from the ecosystem model to the physical model.     

Wetlands in China: Feature, value and protection

The estimated total area of wetland in China is more than 25.9 million hectares including about 11.9 million hectares of marshes and bogs, 9.1 million hectares of lake and about 2.2 million hectares of coastal salt marshes and mudflats. The area of wetland is equivalent to 2.7% of the land surface. China also has 2.7 million hectares of shallow sea water (less 5m in depth at low tide). Marshes and bogs are equivalent 1.3% of the land surface. Only three provinces (regions)—Qinghai, Xizang (Tibet) and Heilongjiang — have a larger total area of marsh and bog. According to the structure, type and development of wetland in different river basins, wetland can be classified nine main regions. The experiments indicate that the coefficient of the marsh to regulate flood is similar to that of lakes. Wetlands occupy 17.8% of the Sanjiang Plain area, the annual carbon contribution is 0.78 × 10⁴t. Carbon released from marsh soil return into atmosphere is 3.95 × 10⁶t/a. At present there is a sharp contradiction between population growth and natural resources shortage, causing wetland to be exerted with huge pressures and serious threats. Foundation item: Under the auspices of the Key B Item of the Chinese Academy of Sciences (KZ951-B1-201-02). Biography: LU Xian-guo (1957 —), male, a native of Changchun City, Jilin Provice, professor. His research interests include wetland process and environmental effect.     

浙江省萧山北部地区农业地质环境调查成果

萧山北部地区农业地质环境调查从氮磷钾的合理配比和微量元素合理施用方面为农业生产科学施肥提供了科学的依据 ;从制定农田耕作层的保护措施 ,控制化肥施用 ,实行平衡施施肥 ,降低农田灌溉水的污染 ,充分发挥肥效等方面 ,提出了保护土地资源、实施“沃土计划” ;根据农业地质的基础资料进行了农业环境保护区划 ,将本区划分为沿江陆域岸线保护带、萧山南沙大堤保护带和农业环境保护区 ;并提出要加强钱塘江海堤建设 ,防治地质灾害的发生     

京津冀地区农业生产效率的时空格局及收敛性研究

将京津冀地区146个典型县域划分为京津近郊农业区（I）、冀东北农业区（II）、冀中平原农业区（III）、太行山农业区（IV）、坝上农业区（V）五大农业区,测算了2000—2015年京津冀及五大农业区的农业生产效率,检验了京津冀及五大农业区农业生产效率的收敛性,揭示了京津冀地区农业生产效率的收敛机理。研究结果表明,京津冀地区农业生产效率变化趋势总体较为平稳,五大农业区农业生产效率由大到小依次为：V>II>IV>I>III,Malmquist指数呈显著波动趋势,技术进步对对农业生产效率提升的作用显著;在农业资源禀赋、地理区位等内源性因素与经济发展环境、技术进步与农业政策支持等外源性因素的共同作用下,京津冀地区优化重组农业生产要素,提升了农业生产效率,并通过要素流动与要素替代作用,缩小了不同农业区内部的农业生产效率差距,使不同经济发展水平的各农业区农业生产效率收敛于不同稳态水平;最后,从现代农业生产经营体系、财政转移支付机制、农业规模经营等角度提出了京津冀地区农业协同发展的具体路径。     

黄河下游沿岸农业景观中蜘蛛对非农生境的响应（英文）

Non-crop habitats have been suggested to impact local biodiversity significantly in agricultural landscapes. However, there have been few studies of the effects of less-focused non-crop habitats(orchard, wetland, pit and ditch) on variation of spider abundance. In this study, spiders in 30 woodlands were captured using pitfall traps in Fengqiu County, China, and the effects of local and landscape variations at different scales(50 m, 100 m, 200 m, 350 m and 500 m) on spider abundance were analysed. The most important variation that influenced spider abundance at the 500 m scale was the less-focused non-crop habitat(LNH) cover, and 10% was an appropriate proportion of LNH cover to sustain high level of spider diversity in the investigated landscape. Non-metric multidimensional scaling analyses revealed that there were significant differences in the spider composition among the high, medium and low LNH coverage. Based on indicator species analysis, different spider species were associated with landscapes with different levels of LNH cover. Lycosidae, which accounted for 48% of the total specimens, preferred woodland habitats neighbouring areas with high LNH cover. Compared with woodland habitats, LNH provided more diverse food sources and habitat to sustain more spider species in the study area. Furthermore, linear elements composed of vegetation, such as pits and ditches, may prevent agricultural intensification by enhancing landscape connectivity and providing habitats for different spiders. Our findings may provide a theoretical basis for biodiversity conservation in agro-ecosystems and top-down control of pests.     

国土空间规划中水源涵养功能生态保护红线备选区的识别

水源涵养功能重要性是生态保护红线划分工作中重要的评价指标之一。通过对以往生态系统水源涵养功能区划分的指标及其区域导向的系统梳理,在进一步明晰国土空间规划中水源涵养功能生态保护红线区域指向的基础上,按照国土空间规划关于“三区三线”自下而上试划的要求,探讨了水源涵养重要性生态保护红线划分及其评价的改进方法。选取中国典型喀斯特区域六盘水市作为研究案例区,分别用环保部2015版与2017版《生态保护红线划定技术指南》中的模型法、NPP法以及本研究提出的改进方法,对六盘水市水源涵养功能生态保护红线进行了试划。对比三种方法的划定结果可以看出,改进方法因评价数据精度的提高减少了《生态保护红线划定技术指南》方法的区域损失,提高了区域判别的精准性,可望为国土空间规划中生态保护红线的划定提供科学依据。     

近20a来巢湖流域生态服务价值空间分异机制的地理探测

生态系统服务功能是生态系统和生态过程形成和维持的自然环境条件及作用。基于1995—2017年遥感分类数据,对研究区按3 km×3 km幅度网格化2019个样方,利用空间统计和缓冲区等方法进行巢湖流域生态服务价值时空演变特征分析,应用地理探测器工具揭示生态服务价值空间分异的主导因子及因子交互作用机制,并提出生态服务价值空间优化策略。结果表明：① 巢湖流域生态服务价值量由1995年的303.17亿元分别下降为2005年300.95亿元和2017年287.70亿元,近20a来减少约5.11%,年均下降率0.23%,其中合肥市区、巢湖南部和东部地区降速明显;② 生态服务价值等级空间转移分析表明,巢湖流域低级别生态服务价值区域在扩展,中等及高级别区域在缩小。以巢湖为核心的缓冲区分析表明,20a来缓冲区核心环带内生态服务价值量下降18.55%,巢湖流域水环境保护核心区的生态系统功能变化值得关注;③ 地理探测分析表明,人为影响综合指数是生态服务价值空间分异的主导因子;地形、气象因素是重要影响因子;人为影响指数因子、自然因子及社会经济因子的交互协同增强效应共同影响了流域生态服务价值在空间上的分异效果。研究结果在一定程度上可为巢湖流域生态系统调控与优化提供理论依据。     

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。     

Simulating runoff generation and its spatial correlation with environmental factors in Sancha River Basin: The southern source of the Wujiang River

Journal of Geographical Sciences - Runoff generation is an important part of water retention service, and also plays an important role on soil and water retention. Under the background of the...