Postglacial development of a marl and peat complex on the Precambrian Shield of northwestern Ontario

This paper presents the first paleolimnological study of the postglacial development of a marl and peat complex on the Canadian Precambrian Shield. Ring Lake (48° 46 N, 85° 51 W), situated within the carbonate glacial drift area of northwestern Ontario, originated about 9000 BP in a basin exposed by the retreating waters of proglacial Lake Superior. The development of Ring Lake was interpreted from pollen and diatom analysis of one sediment core from the littoral zone and another core from near the lake centre.The sequence of postglacial vegetation development parallels published accounts of forest history in northern Ontario. The predominant diatom throughout the littoral core was the alkaliphilous Cymbella diluviana. The central core was dominated by circumneutral and alkaliphilous species of Achnanthes Navicula, Fragilaria, and Cymbella, except in recent samples where acidophilous species of Anomoeoneis were common.Diatom-inferred (DI) pH shows that the early lake was alkaline because of drainage from base-rich tills. The presence of marl in the littoral core indicates deposition of calcareous materials until the site dried out during the Hypsithermal period. There is evidence that beaver activity around 5000 BP caused a temporary change in lake hydrology. A decline in DI pH over much of the postglacial reflects gradual exhaustion of carbonates in the drainage area. An increase in acidophilous diatoms in samples representing the past 3500 y is consistent with gradual acidification of the system and development of a littoral peatland in a cooler neoglacial climate.     

Effects of subsurface soil characteristics on wetland–groundwater interaction in the coastal plain of the Chesapeake Bay watershed

Ecosystem services provided by depressional wetlands on the coastal plain of the Chesapeake Bay watershed (CBW) have been widely recognized and studied. However, wetland–groundwater interactions remain largely unknown in the CBW. The objective of this study was to examine the vertical interactions of depressional wetlands and groundwater with respect to different subsurface soil characteristics. This study examined two depressional wetlands with a low‐permeability and high‐permeability soil layer on the coastal plain of the CBW. The surface water level (SWL) and groundwater level (GWL) were monitored over 1 year from a well and piezometer at each site, respectively, and those data were used to examine the impacts of subsurface soil characteristics on wetland–groundwater interactions. A large difference between the SWL and GWL was observed at the wetland with a low‐permeability soil layer, although there was strong similarity between the SWL and GWL at the wetland with a high‐permeability soil layer. Our observations also identified a strong vertical hydraulic gradient between the SWL and GWL at the wetland with a high‐permeability soil layer relative to one with a low‐permeability soil layer. The hydroperiod (i.e., the total time of surface water inundation or saturation) of the wetland with a low‐permeability soil layer appeared to rely on groundwater less than the wetland with a high‐permeability soil layer. The findings showed that vertical wetland–groundwater interactions varied with subsurface soil characteristics on the coastal plain of the CBW. Therefore, subsurface soil characteristics should be carefully considered to anticipate the hydrologic behavior of wetlands in this region.     

Deep neural network for complex open-water wetland mapping using high-resolution WorldView-3 and airborne LiDAR data

Wetland inventory maps are essential information for the conservation and management of natural wetland areas. The classification framework is crucial for successful mapping of complex wetlands, including the model selection, input variables and training procedures. In this context, deep neural network (DNN) is a powerful technique for remote sensing image classification, but this model application for wetland mapping has not been discussed in the previous literature, especially using commercial WorldView-3 data. This study developed a new framework for wetland mapping using DNN algorithm and WorldView-3 image in the Millrace Flats Wildlife Management Area, Iowa, USA. The study area has several wetlands with a variety of shapes and sizes, and the minimum mapping unit was defined as 20 m² (0.002 ha). A set of potential variables was derived from WorldView-3 and auxiliary LiDAR data, and a feature selection procedure using principal components analysis (PCA) was used to identify the most important variables for wetland classification. Furthermore, traditional machine learning methods (support vector machine, random forest and k-nearest neighbor) were also implemented for the comparison of results. In general, the results show that DNN achieved satisfactory results in the study area (overall accuracy = 93.33 %), and we observed a high spatial overlap between reference and classified wetland polygons (Jaccard index ∼0.8). Our results confirm that PCA-based feature selection was effective in the optimization of DNN performance, and vegetation and textural indices were the most informative variables. In addition, the comparison of results indicated that DNN classification achieved relatively similar accuracies to other methods. The total classification errors vary from 0.104 to 0.111 among the methods, and the overlapped areas between reference and classified polygons range between 87.93 and 93.33 %. Finally, the findings of this study have three main implications. First, the integration of DNN model and WorldView-3 image is useful for wetland mapping at 1.2-m, but DNN results did not outperform other methods in this study area. Second, the feature selection was important for model performance, and the combination of most relevant input parameters contributes to the success of all tested models. Third, the spatial resolution of WorldView-3 is appropriate to preserve the shape and extent of small wetlands, while the application of medium resolution image (30-m) has a negative impact on the accurate delineation of these areas. Since commercial satellite data are becoming more affordable for remote sensing users, this study provides a framework that can be utilized to integrate very high-resolution imagery and deep learning in the classification of complex wetland areas.     

A geostatistical model for estimating edge effects and cumulative human disturbance in wetlands and coastal waters

ABSTRACT

The modification of landscapes for agriculture, residential housing, and other human uses has the potential to alter ecosystem function, reduce native biodiversity, and to diminish the capacity of natural systems to provide essential goods and services. Resultantly, methods aimed at quantifying disturbance intensity at the intersection of anthropogenic and natural lands are important to applied aspects of landscape planning and natural resource management, as well as theoretical facets of spatial ecology. Tools to appraise human disturbance in wetlands and coastal waters are especially needed because the topographic settings of surface waters make them particularly susceptible to pollutant accumulation, hydrologic alteration, and other influences from the surrounding landscape. Assuming a water resources focus, we developed a novel geostatistical method to quantify and visualize edge effects and cumulative human disturbance for all wetlands and coastal waters in the State of Florida (USA). Model validation revealed that estimated disturbance intensity was strongly correlated to species richness, levels of heavy metal contamination, and persistent organic pollutant concentration. The presented modeling framework offers a flexible means to assess human disturbance across spatial scales and could be readily applied to prioritize conservation land acquisition and to anticipate future impacts from the proposed development.     

Short-term effects of changes in water management on the limnological characteristics and zooplankton of a eutrophic Mediterranean coastal lagoon (NE Iberian Peninsula)

The Ter Vell (NE Iberian Peninsula) is a eutrophic coastal lagoon which has been flooded by the excess irrigation water and the agricultural runoff during the last decades. Between 1999 and 2003, restoration measures were applied to improve its water quality. At the same time, but independently, agricultural water management drastically reduced the freshwater inflow. The short-term effects of these management actions on the limnological characteristics of the lagoon were analysed by comparing two hydrological cycles, one before (1999/2000) and the other one after (2002/2003) the actions. The two cycles are illustrative of opposite situations in the hydrological functioning of coastal wetlands. In the first, the lagoon was exorheic, with prolonged flooding periods and a low residence time; in the second, it had a more endorheic character, with scarce water inputs and prolonged periods of confinement. Consequently, nitrogen inputs diminished and organic load and salinity increased as the internal loading and the accumulation effects became more relevant. These effects were actually caused by the drastic reduction in the freshwater inflow which prevented, in turn, the success of the restoration measures. The zooplankton community of the Ter Vell lagoon was not significantly altered by the hydrological change, at least in the short-term, and rotifers and cladocerans, mainly those species indicative of eutrophy, dominated the community.     

黄河下游河滨湿地不同草本植物群落物种多样性研究

暖温带河滨湿地植被以草本植物群落为主。以黄河下游河滨湿地的河漫滩和背河洼地的15个草本植物群落为调查对象,研究河滨湿地不同草本植物群落的组成及多样性。结果表明,15个草本植物群落中共有31科73属94种植物,包括2科蕨类植物门植物和29科被子植物门植物,其中,禾本科植物最多(12属17种);丰富度最高的是狗尾草(Setaria viridis)群落;15个草本植物群落的Shannon-wiener指数介于0.22～2.07之间,人工群落荷花(Nelumbo nucifera)的Shannon-wiener指数最低,仅0.22,而另一人工群落水稻(Oryza sativa)的Shan-non-wiener指数却最大,达到2.07;典型湿地植物群落的Pielou均匀度指数较高,如扁秆藨草(Scirpus planiculmis)、芦苇(Phragmites australis)、水烛(Typha angustifolia)群落的Pielou均匀度指数都大于0.6;Simpson多样性指数最高的是荷花群落,而最低的是水稻群落;15个群落中,多样性指数、丰富度、均匀度指数和优势度指数在各群落间存在显著的差异;河滨湿地自然草本植物群落的Shannon-wiener指数、物种丰富度、Pielou均匀度指数均高于人工草本植物群落,而Simpson多样性指数则是前者低于后者,但人工草本植物群落与自然草本植物群落间4个多样性指数的差异并不明显。     

北京市杨镇一中人工湿地设计及污水处理效果

针对北京市农村地区居民居住相对分散、生活污水集中处理难度大的状况,在北京市杨镇一中,建立了经济且简便易行的用于处理污水的人工湿地。该人工湿地由地埋式一体化预处理、多级复合式人工湿地系统、景观湿地系统三部分组成。通过单元实验,对人工湿地的填料结构、植物选择、布水设计、水位调节、湿地防堵系统设计、预处理系统设计进行了创新,研究了1d、2d和3d水力停留时间对污水中有机物处理效应的影响,并开展了人工湿地基质堵塞实验、冬季保温措施研究以及人工湿地脱氮除磷效果研究。结果表明,比较而言,1d和3d的水力停留时间不利于有机物的去除,2d的水力停留时间有利于有机物的去除;人工湿地0～10m的水平距离内,0～5cm、30～35cm、60～65cm深度的基质的堵塞差异显著(n=10,p<0.05),从水平上看,在0m、2m、4m处基质的堵塞最为明显,因此,在更换人工湿地基质时,只需更换0～4m内的基质;棚膜+蒲席覆盖系统去除污水中总氮的效果要优于结冰盖系统,更适宜于北方使用;预处理系统、人工湿地系统、景观湿地系统三部分共同处理污水,优势互补,能使处理后的出水符合北京市水污染排放标准一级B限值。     

安庆沿江退耕还湖18年的湿地土壤生物化学性质研究

以安庆沿江农田不同退耕还湖方式——低坝高网式水产养殖和湿地自然恢复区的湿地土壤为研究对象,并以邻近的水田和旱地土壤作为参照,研究退耕还湖后湿地土壤生物化学性质变化.结果表明,退耕还湖18a(1991～2009年)后,在湿地自然恢复区,湿地土壤(深度为0～30 cm)微生物量碳含量、土壤磷酸酶活性和过氧化氢酶活性增大,土壤脲酶活性和蔗糖酶活性减小;由水田退耕18a的湿地亚表层土壤(深度为15～30 cm)脲酶活性和表层土壤(深度为0～15 cm)过氧化氢酶活性与由旱地退耕18a的湿地无明显差异,由水田退耕18a的湿地表层土壤脲酶活性和亚表层土壤过氧化氢酶活性、表层和亚表层土壤微生物量碳含量、蔗糖酶活性和磷酸酶活性都明显高于由旱地退耕18a的湿地.退耕还湖18a后,进行低坝高网式水产养殖的湿地土壤微生物量碳含量、土壤脲酶活性、蔗糖酶活性和磷酸酶活性减小,而过氧化氢酶活性增大;由水田退耕18a的湿地表层和亚表层土壤微生物量碳含量与由旱地退耕18a的湿地无明显差异,由水田退耕18a的湿地表层和亚表层土壤脲酶活性、表层土壤蔗糖酶活性和亚表层土壤磷酸酶活性明显高于由旱地退耕18a的湿地,而其亚表层土壤蔗糖酶、表层土壤磷酸酶、表层和亚表层土壤过氧化氢酶活性均显著低于由旱地退耕18a的湿地.天然湿地土壤微生物量碳含量、土壤脲酶活性、蔗糖酶活性和磷酸酶活性明显低于已退耕还湖的湿地和参照农田土壤.退耕还湖后,湿地的不同利用方式及其历史利用方式影响湿地土壤生物化学性质;湿地土壤有机质等养分含量和水文条件变化是导致湿地土壤生物化学性质变化的主要原因.     

In-stream wetlands and their significance for channel filling and the catchment sediment budget, Jugiong Creek, New South Wales

Evidence is presented here of recent and extensive infilling of the incised channel network of the Jugiong Creek catchment, SE Australia. The present channel network resulted from widespread stream and gully incision in the period between 1880 and 1920. Our survey shows that gully floors have been colonised extensively by emergent macrophyte vegetation since before 1944, forming continuous, dense, in-stream wetlands, which now cover 25% of the channel network in the 2175 km² catchment and have so far trapped almost 2,000,000 t of nutrient-enriched, fine sediments. This mass of sediments represents the equivalent of 4.7 years of annual sediment production across the catchment and in some tributaries, more than 20 years of annual yield is stored within in-stream wetlands.Previous work on the late Quaternary stratigraphy of the region has shown that there were repeated phases of channel incision in the past following which the channels quickly stabilised by natural means and then filled with fine-grained sediment to the point of channel extinction, creating unchannelled swampy valley floors. The current formation and spread of in-stream wetlands is interpreted to be the onset of the next infill phase but it is not known whether present conditions will allow complete channel filling and reformation of the pre-existing swampy valley floors. Nevertheless, further spread of in-stream wetlands is likely to increase the sediment trapping capacity and further reduce the discharge of sediments and nutrients into the Murrumbidgee River. The in-stream wetlands may provide a significant capacity to buffer erosion from gullied catchments of considerable size (up to 300 km²) as an adjunct to current riparian management options. They may also assist the recovery of sediment-impacted channels downstream.     

湿地功能评价研究进展

湿地功能评价是湿地研究的核心内容之一，也是开展湿地管理工作的重要工具。美国湿地功能评价的代表性方法有生境评估规程、湿地评价技术和水文地貌评价法等。欧盟于1990年以来开发的湿地功能评价技术吸收了美国水文地貌评价法的部分做法，但更适应欧洲湿地的具体情况。有关国际机构主要从理论上对湿地功能评价方法进行了研究。我国湿地功能评价研究还很薄弱，不能适应快速发展的湿地管理需要，急需加强这方面工作。