USE OF STAGE DATA TO CHARACTERIZE HYDROLOGIC CONDITIONS IN AN URBANIZING ENVIRONMENT1

ABSTRACT: This paper presents the results of a study on the use of continuous stage data to describe the relation between urban development and three aspects of hydrologic condition that are thought to influence stream ecosystems—overall stage variability, stream flashiness, and the duration of extreme‐stage conditions. This relation is examined using data from more than 70 watersheds in three contrasting environmental settings—the humid Northeast (the metropolitan Boston, Massachusetts, area); the very humid Southeast (the metropolitan Birmingham, Alabama, area); and the semiarid West (the metropolitan Salt Lake City, Utah, area). Results from the Birmingham and Boston studies provide evidence linking increased urbanization with stream flashiness. Fragmentation of developed land cover patches appears to ameliorate the effects of urbanization on overall variability and flashiness. There was less success in relating urbanization and streamflow conditions in the Salt Lake City study. A related investigation of six North Carolina sites with long term discharge and stage data indicated that hydrologic condition metrics developed using continuous stage data are comparable to flow based metrics, particularly for stream flashiness measures.     

Effect of Cross-Linking Waste Protein with Dialdehydes on Its Biodegradation Under Anaerobic Conditions

Most native polymers used in processing and application technologies are admittedly disposable from the environment in a biologic manner, but products possess low mechanical strength. One of the paths to increasing this attribute (if feasible) is their cross-linking, which may, however, affect their readiness to biodegradation. In the presented work this condition was observed on the example of waste protein (Hykol B) cross-linking by means of glutardialdehyde and glyoxal. Degree and course of cross-linking were determined through impedance spectroscopy. The objective of this work also was to obtain data for constructing a sensor capable of following the cross-linking course in real time, for potential industrial application of Hykol in continuous production. Impedance spectroscopy proved to be applicable even to this kind of material marked by considerable water content and exhibiting relatively high electric conductivity; so far it had been used only for materials of low conductivity. An aqueous environment inoculated with digested anaerobic sludge from a municipal wastewater treatment plant was selected for modeling anaerobic conditions. The relation was studied between cross-linking degree given by content of cross-linking agent (determined by impedance spectroscopy) and biodegradation degree under anaerobic conditions. It was confirmed that network density as given by quantity of added agent not only reduced breakdown degree but also slowed the course of the process. This fact is particularly obvious with cross-linking by means of glyoxal; network density is thus dependent on type of employed substance, which affect type and structure of created network. That not merely forms an obstacle during polymer swelling and dissolution but also prevents access of bacteria to source of metabolized organic carbon.     

ECONOMIC COSTS AND BENEFITS OF INSTREAM FLOW PROTECTION FOR ENDANGERED SPECIES IN AN INTERNATIONAL BASIN1

ABSTRACT: The U.S. Endangered Species Act (ESA) restricts federal agencies from carrying out actions that jeopardize the continued existence of any endangered species. The U.S. Supreme Court has emphasized that the language of the ESA and its amendments permits few exceptions to the requirement to give endangered species the highest priority. This paper estimates economic costs associated with one measure for increasing instream flows to meet critical habitat requirements of the endangered Rio Grande silvery minnow. Impacts are derived from an integrated regional model of the hydrology, economics, and institutions of the upper Rio Grande Basin in Colorado, New Mexico, Texas, and Mexico. One proposal for providing minimum streamflows to protect the silvery minnow from extinction would provide guaranteed year round streamflows of at least 50 cubic feet per second in the San Acacia reach of the upper Rio Grande. These added flows can be accomplished through reduced surface diversions by New Mexico water users in dry years when flows would otherwise be reduced below the critical level required by the minnow. Based on a 44‐year simulation of future inflows to the basin, we find that some agricultural users suffer damages, but New Mexico water users as a whole do not incur damages from a policy that reduces stream depletions sufficiently to provide habitat for the minnow. The same policy actually benefits downstream users, producing average annual benefits of over $200,000 per year for west Texas agriculture, and over $1 million for El Paso municipal and industrial water users, respectively. Economic impacts of instream flow deliveries for the minnow are highest in drought years.     

草地畜牧业雪灾脆弱性评价 --以内蒙古牧区为例

从综合减灾和区域可持续发展的角度，建立了雪灾脆弱性评价指标体系及评价模型，并从雪灾区域孕灾环境敏感性以及区域畜牧业承灾体对雪灾的适应性两方面，对内蒙古雪灾脆弱性进行了评价。研究结果表明：内蒙古牧区雪灾脆弱性存在若明显的地域差异，中西部牧区比东部牧区脆弱性大，北部牧区比南部牧区脆弱性大，并且近10年来脆弱性提高的旗县明显增多，草地季节性干旱、北方干旱化以及草场超载过牧、退化加剧是畜牧业雪灾脆弱性呈增加趋势的直接原因。     

A Conceptual Framework for Selecting and Analyzing Stressor Data to Study Species Richness at Large Spatial Scales

/ In this paper we develop a conceptual framework for selectingstressor data and analyzing their relationship to geographic patterns ofspecies richness at large spatial scales. Aspects of climate and topography,which are not stressors per se, have been most strongly linked withgeographic patterns of species richness at large spatial scales (e.g.,continental to global scales). The adverse impact of stressors (e.g., habitatloss, pollution) on species has been demonstrated primarily on much smallerspatial scales. To date, there has been a lack of conceptual developmenton how to use stressor data to study geographic patterns of speciesrichness at large spatial scales.The framework we developed includes four components: (1) clarification of theterms stress and stressor and categorization of factors affecting speciesrichness into three groups-anthropogenic stressors, natural stressors, andnatural covariates; (2) synthesis of the existing hypotheses for explaininggeographic patterns of species richness to identify the scales over whichstressors and natural covariates influence species richness and to providesupporting evidence for these relationships through review of previousstudies; (3) identification of three criteria for selection of stressor andcovariate data sets: (a) inclusion of data sets from each of the threecategories identified in item 1, (b) inclusion of data sets representingdifferent aspects of each category, and (c) to the extent possible, analysisof data quality; and (4) identification of two approaches for examiningscale-dependent relationships among stressors, covariates, and patterns ofspecies richness-scaling-up and regression-tree analyses.Based on this framework, we propose 10 data sets as a minimum data base forexamining the effects of stressors and covariates on species richness atlarge spatial scales. These data sets include land cover, roads, wetlands(numbers and loss), exotic species, livestock grazing, surface water pH,pesticide application, climate (and weather), topography, and streams.KEY WORDS: Anthropogenic impacts; Biodiversity; Environmental gradients;Geographic information systems; Hierarchy     

Denitrification Distributions in Four Valley and Ridge Riparian Ecosystems

/ Denitrification in riparian ecosystems can reduce the amount ofnitrogen transported from farm fields to streams. In this study, we examinedenitrification in four riparian ecosystems common to the Valley and Ridgephysiographic province in Pennsylvania, USA. The sites exhibit differentvegetation, are underlain by different rock types, and are downgradient offarm fields. Mean site denitrification rates ranging from 0.6 to 1.9 &mgr;gN/kg soil/day were measured using intact core incubation techniques. Thethree riparian sites covered with grass each exhibited greaterdenitrification rates than the wooded site. Denitrification rate wascorrelated with moisture content but not with nitrate-N or organic carboncontents. Denitrification rates were greatest near the soil surface and atpositions nearest the stream. Rates decreased uniformly with distance awayfrom the stream and also with depth in the soil for each site. While patternsof nitrate-N, moisture, and organic carbon content differ among the sites,their combined effects on denitrification support the observed, consistentdenitrification rate pattern.KEY WORDS: Denitrification; Riparian ecosystems     

生态条件和瘤胃菌丛密度与纤维分解的关系

在自行设计装配的人工模拟瘤胃发酵装置内，用90523-1瘤胃菌丛进行瘤胃体外发酵试验，结果表明纤维素的分解与瘤胃细菌的密度及其类群变化有着密切关系，都受生态环境条件的制约。在发酵温度40℃，搅拌速度为60～70r／min的条件下搅动20min／h，C／N为10：1的生态条件环境中的细菌密度和纤维素分解率都高于相同生态条件的其它梯度组。     

NATURAL EROSION RATES AND THEIR PREDICTION IN THE IDAHO BATHOLITH1

ABSTRACT: Natural rates of surface erosion on forested granitic soils in central Idaho were measured in 40 m² bordered erosion plots over a period of four years. In addition, we measured a variety of site variables, soil properties, and summer rainstorm intensities in order to relate erosion rates to site attributes. Median winter erosion rates are approximately twice summer period rates, however mean summer rates are nearly twice winter rates because of infrequent high erosion caused by summer rainstorms. Regression equation models and regression tree models were constructed to explore relationships between erosion and factors that control erosion rates. Ground cover is the single factor that has the greatest influence on erosion rates during both summer and winter periods. Rainstorm intensity (erosivity index) strongly influences summer erosion rates, even on soils with high ground cover percentages. Few summer storms were of sufficient duration and intensity to cause rilling on the plots, and the data set was too small to elucidate differences in rill vs. interrill erosion. The regression tree models are relatively less biased than the regression equations developed, and explained 70 and 84 percent of the variability in summer and winter erosion rates, respectively.