A Concentric Analysis of the Impact of Urbanization on the Threatened European Tree Frog in an Agricultural Landscape

Abstract:  Pond-breeding amphibians are affected by site-specific factors and regional and landscape-scale patterns of land use. Recent anthropogenic landscape modifications (drainage, agriculture intensification, larger road networks, and increased traffic) affect species by reducing the suitable habitat area and fragmenting remaining populations. Using a robust concentric approach based on permutation tests, we evaluated the impact of recent landscape changes on the presence of the endangered European tree frog ( Hyla arborea ) in wetlands. We analyzed the frequency of 1 traffic and 14 land-use indices at 20 circular ranges (from 100-m up to 2-km radii) around 76 ponds identified in western Switzerland. Urban areas and road surfaces had a strong adverse effect on tree frog presence even at relatively great distances (from 100 m up to 1 km). When traffic measurements were considered instead of road surfaces, the effect increased, suggesting a negative impact due to a vehicle-induced effect. Altogether, our results indicate that urbanization and traffic must be taken into account when pond creation is an option in conservation management plans, as is the case for the European tree frog in western Switzerland. We conclude that our easy-to-use and robust concentric method of analysis can successfully assist managers in identifying potential sites for pond creation, where probability of the presence of tree frogs is maximized.     

1999年委内瑞拉阿维拉山北坡入海型泥石流

委内瑞拉阿维拉山呈东一西走向，北坡濒临加勒比海．１９９９年１２月１６日，阿维拉山北坡２０多条沟谷暴发泥石流，使沿海的城镇、村庄、港口、公路及各种设施遭到毁灭性破坏，造成数万人死亡，直接经济损失超过刀亿美元．泥石流发生在森林植被良好的山区，具低频率和群发性特征，规模大，直接入海．分析这次泥石流灾害，对我国的防灾减灾工作具有启示意义．     

Testing of the Storm Water Management Model Low Impact Development Modules

Stormwater infrastructure designers and operators rely heavily on the United States Environmental Protection Agency’s Storm Water Management Model (SWMM) to simulate stormwater and wastewater infrastructure performance. Since its inception in the late 1970s, improvements and extensions have been tested and evaluated rigorously to verify the accuracy of the model. As a continuation of this progress, the main objective of this study was to quantify how accurately SWMM simulates the hydrologic activity of low impact development (LID) storm control measures. Model performance was evaluated by quantitatively comparing empirical data to model results using a multievent, multiobjective calibration method. The calibration methodology utilized the PEST software, a Parameter ESTimation tool, to determine unmeasured hydrologic parameters for SWMM’s LID modules. The calibrated LID modules’ Nash–Sutcliffe efficiencies averaged 0.81; average percent bias (PBIAS) ?9%; average ratio of root mean square error to standard deviation of measured values 0.485; average index of agreement 0.94; and the average volume error, simulated vs. observed, was +9%. SWMM accurately predicted the timing of peak flows, but usually underestimated their magnitudes by 10%. The average volume reduction, measured outflow volume divided by inflow volume, was 48%. We had more difficulty in calibrating one study, an infiltration trench, which identified a significant limitation of the current version of the SWMM LID module; it cannot simulate lateral exfiltration of water out of the storage layers of a LID storm control measure. This limitation is especially severe for a deep LIDs, such as infiltration trenches. Nevertheless, SWMM satisfactorily simulated the hydrologic performance of eight of the nine LID practices.     

稻田土壤种子库研究进展

土壤种子库是指存在于土壤表面和土壤中全部存活种子的总和。稻田土壤种子库是地上杂草产生的根本来源。我国是一个水稻种植大国,目前关于稻田土壤种子库的研究还不够全面和深入。研究稻田土壤种子库对于防治稻田草害具有重要指导意义,同时也是种子库研究领域的一个重要补充。取样方法和取样时间是研究土壤种子库的关键所在。而萌发法是最常见的判定方法。关于稻田土壤种子库大小的结论相差很大,从103~105 m-2不等。稻田土壤种子库中的杂草主要有19科55种,一般的稻田可检出10科或20种左右。种子的垂直分布格局主要受耕作强度的影响。70%~80%甚至更多的杂草种子分布在0~10 cm。稻田土壤种子库由于萌发、捕食、衰老和种子散布等原因具有季节动态。轮作制度、耕作方式、不同施肥处理以及除草方式等对稻田土壤种子库有重要影响。连续多年的田间管理会使种子库的大小、分布和物种组成产生年际变化。目前,需要加强长期定位研究,扩大研究区域和研究内容,重点研究杂草种子的休眠萌发机制和种子命运研究,为杂草治理提供更准确的信息。     

Managing Uncertainty in Runoff Estimation with the U.S. Environmental Protection Agency National Stormwater Calculator

The U.S. Environmental Protection Agency National Stormwater Calculator (NSWC) simplifies the task of estimating runoff through a straightforward simulation process based on the EPA Stormwater Management Model. The NSWC accesses localized climate and soil hydrology data, and options to experiment with low‐impact development (LID) features for parcels up to 5 ha in size. We discuss how the NSWC treats the urban hydrologic cycle and focus on the estimation uncertainty in soil hydrology and its impact on runoff simulation by comparing field‐measured soil hydrologic data from 12 cities to corresponding NSWC estimates in three case studies. The default NSWC hydraulic conductivity is 10.1 mm/h, which underestimates conductivity measurements for New Orleans, Louisiana (95 ± 27 mm/h) and overestimates that for Omaha, Nebraska (3.0 ± 1.0 mm/h). Across all cities, the NSWC prediction, on average, underestimated hydraulic conductivity by 10.5 mm/h compared to corresponding measured values. In evaluating how LID interact with soil hydrology and runoff response, we found direct hydrologic interaction with pre‐existing soil shows high sensitivity in runoff prediction, whereas LID isolated from soils show less impact. Simulations with LID on higher permeability soils indicate that nearly all of pre‐LID runoff is treated; while features interacting with less‐permeable soils treat only 50%. We highlight the NSWC as a screening‐level tool for site runoff dynamics and its suitability in stormwater management.