Seasonal connections between meteoric water and streamflow generation along a mountain headwater stream

In snowmelt-driven mountain watersheds, the hydrologic connectivity between meteoric waters and stream flow generation varies strongly with the season, reflecting variable connection to soil and groundwater storage within the watershed. This variable connectivity regulates how streamflow generation mechanisms transform the seasonal and elevational variation in oxygen and hydrogen isotopic composition (δ¹⁸O and δD) of meteoric precipitation. Thus, water isotopes in stream flow can signal immediate connectivity or more prolonged mixing, especially in high-relief mountainous catchments. We characterized δ¹⁸O and δD values in stream water along an elevational gradient in a mountain headwater catchment in southwestern Montana. Stream water isotopic compositions related most strongly to elevation between February and March, exhibiting higher δ¹⁸O and δD values with decreasing elevation. These elevational isotopic lapse rates likely reflect increased connection between stream flow and proximal snow-derived water sources heavily subject to elevational isotopic effects. These patterns disappeared during summer sampling, when consistently lower δ¹⁸O and δD values of stream water reflected contributions from snowmelt or colder rainfall, despite much higher δ¹⁸O and δD values expected in warmer seasonal rainfall. The consistently low isotopic values and absence of a trend with elevation during summer suggest lower connectivity between summer precipitation and stream flow generation as a consequence of drier soils and greater transpiration. As further evidence of intermittent seasonal connectivity between the stream and adjacent groundwaters, we observed a late-winter flush of nitrate into the stream at higher elevations, consistent with increased connection to accumulating mineralized nitrogen in riparian wetlands. This pattern was distinct from mid-summer patterns of nitrate loading at lower elevations that suggested heightened human recreational activity along the stream corridor. These observations provide insights linking stream flow generation and seasonal water storage in high elevation mountainous watersheds. Greater understanding of the connections between surface water, soil water and groundwater in these environments will help predict how the quality and quantity of mountain runoff will respond to changing climate and allow better informed water management decisions.     

基于多元统计分析的渔山列岛潮间带软体动物功能群和次级生产力比较

渔山列岛于2008年成为国家级海洋生态保护区,为了解渔山列岛保护区内潮间带软体动物次级生产力的时空变化。于1982年和2010年的3个季节(春、夏、冬)在渔山列岛进行潮间带软体动物调查,采用多元统计分析软体动物时空差异,以Brey经验公式计算分析软体动物次级生产力(P值,P/B值)。结果表明,年际间物种食性结构发生了明显的改变,1982年潮间带软体动物对次级生产力贡献率最大的物种有单齿螺(Monodonta labio)、锈凹螺(Chlorostoma rustica),占软体动物总次级生产力的42.88%,2010年潮间带软体动物对次级生产力贡献率最大的物种有覆瓦小蛇螺(Serpulorbis imbricata)、条纹隔贻贝(Septifer virgatus),占软体动物总次级生产力的75.96%。1982年,年均栖息密度为2758ind/m2,年均生物量为2100.26g/m2,年均次级生产力为240.04g/(m2·a),年均P/B值为0.63a–1;2010年,年均栖息密度为699ind/m2,年均生物量为1101.85g/m2,年均次级生产力为94.82g/(m2·a),年均P/B值为0.55a–1。多因素方差分析表明软体动物次级生产力年际间差异显著(F=5.761,P0.05),季节间和潮位间差异都不显著(F=0.135,P0.05;F=2.076,P0.05),P/B的值较低,表明该海域软体动物世代更替速度较慢,2010年的P/B值(0.55a–1)低于1982年的P/B值(0.63a–1),表明近30年来群落结构受到影响。     

基于ArcGIS Engine与ArcGIS Server的海域定级信息管理系统设计与开发

以Visual Studio 2012为平台,利用ArcGIS Engine强大的空间分析功能,以C#为开发语言结合第三方插件设计开发海域定级决策子系统,实现了不同用海方式海域的自动化定级,对海域定级基础数据、过程数据和结果数据进行综合管理,构建了一个具有一定实用价值的海域定级信息管理系统原型;此外,利用WebGIS将海域定级决策子系统分析生成的结果数据发布成服务,实现海域定级信息共享子系统。本研究为海域定级提供智能化平台,提高对海域定级及评估效率,有利于海洋可持续发展。     

A New Retracking Technique for Brown Peaky Altimetric Waveforms

A new Brown-Peaky (BP) retracker has been developed for peaky waveforms that usually appear within ～10 km to the coastline. The main feature of the BP is that it fits peaky waveforms using the Brown model without introducing a peak function. The retracking strategy first detects the peak location and width of a waveform using an adaptive peak detection method, and then estimates retracking parameters using a weighted least squares (WLS) estimator. The WLS assigns a downsized weight to corrupted waveform gates, but an equal weight to other normal waveform gates. The BP retracker has been applied to 4-year Jason-1 waveform (2002–2006) in two Australian coastal zones. The results retracked by BP, MLE4 and ALES retrackers have been validated against tide-gauge observations located at Burnie, Lorne and Broome. The comparison results show that three retrackers have similar performance over open oceans with the correlation coefficient (～0.7) and RMSE (～13 cm) between altimetric and tide-gauge sea levels for distance >7 km offshore. The main improvement of BP retracker occurs for distance ≤7 km to the coastline, where validation results indicate that data retracked by BP are more accurate (15–21 cm) than those by ALES (16–24 cm) and MLE4 (19–37 cm).     

A New Wavelet Method for Identification of Eddies and Assessment of Incidents on Islands of the Eastern Caribbean

Using two dimensional continuous wavelet transforms, a novel method for identification of mesoscale eddies is presented to facilitate extraction of characteristics for area, amplitude, type, and location from maps of sea level anomalies. In comparison with the previously established growing method for eddy identification, it is found that the wavelet method identifies more than twice the number of eddies and is particularly better at resolving small eddies down to the 0.25 degree resolution of the data. Such research into eddy identification and tracking is significant to the assessment of eddies with potential to impact on coastlines of small islands. The method is applied to the identification of eddies on tracks towards islands of the Eastern Caribbean over 23?years. Spatial and temporal variation in rate of occurrence and magnitude is established. For Barbados there is an average of 9 anticyclonic incidents a year with maximum amplitude of typically 0.22?m in the dry seasons and 0.16?m in the wet seasons. Seasonal variation is reversed for the other islands with twice the number of anticyclonic incidents having maximum amplitudes of about 0.20?m annually.     

强光照和黑暗条件下刺参体壁的基因表达差异

参对光照变化非常敏感，研究刺参对光照的分子响应非常重要。本研究应用RNA测序获取了刺参暴露于强光（“强光”）、正常光照（“对照”）和完全黑暗（“黑暗”）环境下体壁的基因表达谱情况，通过“对照”与“黑暗”，“对照”与“强光”和“黑暗”与“强光”的比较，在|log₂ ratio|≥1和FDR≤0.001的标准下分别发现了1161、113和1705个差异表达基因（DEGs）。基因本体分析表明，“cellular process”和“binding”在“生物过程”和“分子功能”类别中的DEGs富集最多，而“cell”和“cell part”在“细胞组分”类别中的DEGs富集最多。将DEGs与Kyoto Encyclopedia基因和基因组数据库上的于214、41和229条通路进行比对，发现了51、2和57条通路分别显著富集。本研究发现的光特异性DEGs可作为深入研究刺参对光照变化的生化适应机制的重要目标基因。     

新疆和田地区耕地面源污染生态风险评价

随着化肥、农膜等在农业生产中的过量投入，耕地面源污染的程度随之加重。文章选取塔里木河流域上游和田地区为研究区域，依据P-S-R框架理论，构建和田地区耕地面源污染生态风险评价指标体系，加入土壤理化数据，使用生态风险评价模型对和田地区1980 年及2016 年耕地面源污染状况进行生态风险评价，运用耕地生态风险模型、生态风险转移矩阵、Arcgis分析和田地区耕地面源污染时空分异状况。研究结论如下：和田地区1980 年耕地生态风险等级均为II级或III级，呈“中间高，两侧低”分布；2016 年耕地生态风险等级上升至IV级或V级，呈“倒W型”分布，各县耕地面源污染程度较1980 年均有较大幅度的上升，其中墨玉县和于田县在2016 年耕地生态风险等级达到最高的V级，而民丰县因自身生态环境的强脆弱性，同样需要提高关注。根据面源污染“从源头治理”的原则，应切实推进和田地区耕地生态环境保护与治理，提高政府重视程度，增强技术指导，开展试点工作，改善和田地区耕地面源污染现状。     

基于ROMS和4DVAR的沿轨与网格化SSH数据同化效果评价

Remote sensing products are significant in the data assimilation of an ocean model. Considering the resolution and space coverage of different remote sensing data, two types of sea surface height(SSH) product are employed in the assimilation, including the gridded products from AVISO and the original along-track observations used in the generation. To explore their impact on the assimilation results, an experiment focus on the South China Sea(SCS) is conducted based on the Regional Ocean Modeling System(ROMS) and the four-dimensional variational data assimilation(4 DVAR) technology. The comparison with EN4 data set and Argo profile indicates that, the along-track SSH assimilation result presents to be more accurate than the gridded SSH assimilation, because some noises may have been introduced in the merging process. Moreover, the mesoscale eddy detection capability of the assimilation results is analyzed by a vector geometry–based algorithm. It is verified that, the assimilation of the gridded SSH shows superiority in describing the eddy's characteristics, since the complete structure of the ocean surface has been reconstructed by the original data merging.     

Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification,visual interpretation and machine learning approaches

We evaluate three approaches to mapping vegetation using images collected by an unmanned aerial vehicle (UAV) to monitor rehabilitation activities in the Five Islands Nature Reserve, Wollongong (Australia). Between April 2017 and July 2018, four aerial surveys of Big Island were undertaken to map changes to island vegetation following helicopter herbicide sprays to eradicate weeds, including the creeper Coastal Morning Glory (Ipomoea cairica) and Kikuyu Grass (Cenchrus clandestinus). The spraying was followed by a large scale planting campaign to introduce native plants, such as tussocks of Spiny-headed Mat-rush (Lomandra longifolia). Three approaches to mapping vegetation were evaluated, including: (i) a pixel-based image classification algorithm applied to the composite spectral wavebands of the images collected, (ii) manual digitisation of vegetation directly from images based on visual interpretation, and (iii) the application of a machine learning algorithm, LeNet, based on a deep learning convolutional neural network (CNN) for detecting planted Lomandra tussocks. The uncertainty of each approach was assessed via comparison against an independently collected field dataset. Each of the vegetation mapping approaches had a comparable accuracy; for a selected weed management and planting area, the overall accuracies were 82 %, 91 % and 85 % respectively for the pixel based image classification, the visual interpretation / digitisation and the CNN machine learning algorithm. At the scale of the whole island, statistically significant differences in the performance of the three approaches to mapping Lomandra plants were detected via ANOVA. The manual digitisation took a longer time to perform than others. The three approaches resulted in markedly different vegetation maps characterised by different digital data formats, which offered fundamentally different types of information on vegetation character. We draw attention to the need to consider how different digital map products will be used for vegetation management (e.g. monitoring the health individual species or a broader profile of the community). Where individual plants are to be monitored over time, a feature-based approach that represents plants as vector points is appropriate. The CNN approach emerged as a promising technique in this regard as it leveraged spatial information from the UAV images within the architecture of the learning framework by enforcing a local connectivity pattern between neurons of adjacent layers to incorporate the spatial relationships between features that comprised the shape of the Lomandra tussocks detected.     

全球气候变化下南海诸岛保护优先区识别分析

全球变化下,珊瑚礁保护区是保护生物多样性、增强珊瑚礁对气候变暖抵抗力的有效方式,而维持珊瑚礁弹性是其核心内容。针对珊瑚礁最具有威胁性的热压力因子,基于南海1982—2009年卫星观测海表面温度（SST）数据和CMIP5加拿大地球系统模式CanESM2模型预估的2006—2100年南海SST数据构建热压力强度模型,从维持珊瑚礁弹性的角度识别IPCC RCP 4.5和RCP 8.5情景下南海诸岛保护优先区。结果表明：RCP 4.5和RCP 8.5情景下13%左右的南海诸岛珊瑚礁识别为保护优先区。根据热压力强度与珊瑚抵抗力及避难所关系,西沙群岛七连屿和晋卿岛近年观测与未来预估的热压力强度均比较低,在保障其服务功能的基础上建议实施完全保护;东沙群岛东沙环礁和中沙环礁排洪滩近年观测急性热压力强度较高但未来预估热压力强度较低,建议实施50%禁止利用保护;中沙群岛黄岩岛近年观测和未来预估的急性热压力强度均比较低,建议实施50%多用途保护。南沙群岛有14%左右的珊瑚礁识别为保护优先区,根据其热压力强度可实施30%~100%禁止利用保护或30%~50%多用途保护。RCP 4.5和RCP 8.5情景下的南海诸岛保护优先区及保护对策,可为维持珊瑚礁生态弹性及应对全球气候变化提供重要的参考价值。