Estimating restorable wetland water storage at landscape scales

Globally, hydrologic modifications such as ditching and subsurface drainage have significantly reduced wetland water storage capacity (i.e., volume of surface water a wetland can retain) and consequent wetland functions. While wetland area has been well documented across many landscapes and used to guide restoration efforts, few studies have directly quantified the associated wetland storage capacity. Here, we present a novel raster‐based approach to quantify both contemporary and potential (i.e., restorable) storage capacities of individual depressional basins across landscapes. We demonstrate the utility of this method by applying it to the Delmarva Peninsula, a region punctuated by both depressional wetlands and drainage ditches. Across the entire peninsula, we estimated that restoration (i.e., plugging ditches) could increase storage capacity by 80%. Focusing on an individual watershed, we found that over 59% of restorable storage capacity occurs within 20 m of the drainage network, and that 93% occurs within 1 m elevation of the drainage network. Our demonstration highlights widespread ditching in this landscape, spatial patterns of both contemporary and potential storage capacities, and clear opportunities for hydrologic restoration. In Delmarva and more broadly, our novel approach can inform targeted landscape‐scale conservation and restoration efforts to optimize hydrologically mediated wetland functions.     

Landscape metrics as predictors of hydrologic connectivity between Coastal Plain forested wetlands and streams

Geographically isolated wetlands, those entirely surrounded by uplands, provide numerous landscape‐scale ecological functions, many of which are dependent on the degree to which they are hydrologically connected to nearby waters. There is a growing need for field‐validated, landscape‐scale approaches for classifying wetlands on the basis of their expected degree of hydrologic connectivity with stream networks. This study quantified seasonal variability in surface hydrologic connectivity (SHC) patterns between forested Delmarva bay wetland complexes and perennial/intermittent streams at 23 sites over a full‐water year (2014–2015). Field data were used to develop metrics to predict SHC using hypothesized landscape drivers of connectivity duration and timing. Connection duration was most strongly related to the number and area of wetlands within wetland complexes as well as the channel width of the temporary stream connecting the wetland complex to a perennial/intermittent stream. Timing of SHC onset was related to the topographic wetness index and drainage density within the catchment. Stepwise regression modelling found that landscape metrics could be used to predict SHC duration as a function of wetland complex catchment area, wetland area, wetland number, and soil available water storage (adj‐R² = 0.74, p < .0001). Results may be applicable to assessments of forested depressional wetlands elsewhere in the U.S. Mid‐Atlantic and Southeastern Coastal Plain, where climate, landscapes, and hydrological inputs and losses are expected to be similar to the study area.     

ArcGIS与SAS地统计分析方法应用于美国县区人口加权月温度估算的比较(英文)

气温变化对人群健康有重要的影响。通过对美国县区人口加权的月平均温度的准确估计可以用于气温与人群健康行为以及疾病的关联关系研究,如基于以县区为单位的抽样或者报告数据。针对气温的估计,多数学者都采用ArcGIS软件,很少使用SAS这一统计软件。本文比较了两种地统计模型的性能,并在同一个CITGO平台上采用ArcGIS9.3和SAS9.2工具软件估算全美48个州县区月平均温度。来自全美5435个气温监测站点2007年1-12月的平均温度和站点的海拔高度被用于估算县区人口中心点的温度,其中海拔数据是作为协变量。通过调整决定系数R2、均方误差、均方根误差和处理时间等指标来比较模型的效能。在ArcGIS中独立验证预测准确性在11个月中都达到90%以上,SAS中12个月均达到90%以上。与ArcGIS协同克里格相比,SAS协同克里格插值能获得更高的准确性和较低的偏差。两个软件包对于县区水平的气温估计值呈现正相关(调整R2在0.95-0.99之间);通过引入海拔高度作为协变量,使准确性和精确性都得以改善。两种方法对于美国县区层面的气温估计都是可靠的,但ArcGIS在空间数据前期处理和处理时间上的优势,尤其在涉及多年或者多个州的项目中是软件选择上的重要考虑。     

MPA design using sliding windows: Case study designating a research area

Coastal managers presently rely on a limited set of decision support tools for designing marine protected areas (MPAs) or subzones. A new approach, defining potential sizes and shapes of MPA boundaries early in the design process, is presented in a case study. A sliding window of the same dimensions as potential boundary configurations was regularly shifted throughout the study area and used to quantify variables representing preferred biophysical and socioeconomic characteristics. The technique offers advantages in spatially restricted areas, areas where habitat connectivity is critical, and situations wherein providing stakeholders with an up-front understanding of potential boundaries is required.     

The Multiscale TROPIcal CatchmentS critical zone observatory M-TROPICS dataset II: Land use,hydrology and sediment production monitoring in Houay Pano,northern Lao PDR

Mountain regions of the humid tropics are characterized by steep slopes and heavy rains. These regions are thus prone to both high surface runoff and soil erosion. In Southeast Asia, uplands are also subject to rapid land-use change, predominantly as a result of increased population pressure and market forces. Since 1998, the Houay Pano site, located in northern Lao PDR (19.85°N 102.17°E) within the Mekong basin, aims at assessing the long-term impact of the conversion of traditional slash-and-burn cultivation systems to commercial perennial monocultures such as teak tree plantations, on the catchment hydrological response and sediment yield. The instrumented site monitors hydro-meteorological and soil loss parameters at both microplot (1 m²) and small catchment (0.6 km²) scales. The monitored catchment is part of the network of critical zone observatories named Multiscale TROPIcal CatchmentS (M-TROPICS). The data shared by M-TROPICS in Houay Pano are (1) rainfall, (2) air temperature, air relative humidity, wind speed, and global radiation, (3) catchment land use, (4) stream water level, suspended particulate matter, bed particulate matter and stones, (5) soil surface features, and (6) soil surface runoff and soil detachment. The dataset has already been used to interpret suspended particulate matter and bed particulate matter sources and dynamics, to assess the impact of land-use change on catchment hydrology, soil erosion, and sediment yields, to understand bacteria fate and weed seed transport across the catchment, and to build catchment-scale models focused on hydrology and water quality issues. The dataset may be further used to, for example, assess the role of headwater catchments in large tropical river basin hydrology, support the interpretation of new variables measured in the catchment (e.g., contaminants other than faecal bacteria), and assess the relative impacts of both climate and land-use change on the catchment.     

Hydro-acoustic remote sensing of benthic biological communities on the shallow South East Australian continental shelf

Information regarding the composition and extent of benthic habitats on the South East Australian continental shelf is limited. In this habitat mapping study, multibeam echosounder (MBES) data are integrated with precisely geo-referenced video ground-truth data to quantify benthic biotic communities at Cape Nelson, Victoria, Australia. Using an automated decision tree classification approach, 5 representative biotic groups defined from video analysis were related to hydro-acoustically derived variables in the Cape Nelson survey area. Using a combination of multibeam bathymetry, backscatter and derivative products produced highest overall accuracy (87%) and kappa statistic (0.83). This study demonstrates that decision tree classifiers are capable of integrating variable data types for mapping distributions of benthic biological assemblages, which are important in maintaining biodiversity and other system services in the marine environment.