Evidence of response of vegetation to environmental change on high-elevation sites in the Swiss Alps

Climate change has in the past led to shifts in vegetation patterns; in a future, warmer climate due to enhanced greenhouse-gas concentrations, vegetation is also likely to be highly responsive to such warming. Mountain regions are considered to be particularly sensitive to such changes. In this paper we present an approach to assess the impact of climate change on long-term vegetation plots at the high-elevation site of the Schynige Platte, 2000 m above sea level, in the Bernese Alps (Switzerland). Records of vegetation spanning the period from 1928 to today at two different sites, each with several plots, were considered. The observed change in the species composition was then related to changes in land use and climate. We used daily values of temperature, snow and precipitation from several high-elevation weather stations to conduct these analyses. The correlation between climate and vegetation patterns revealed that species that prefer low thermal conditions move out of the plots, i.e., their frequency of occurrence is negatively correlated with the average number of degree-days over the last six decades. On the other hand, species with higher thermal demands are seen to be invading the plots, i.e., their frequency of occurrence is positively correlated to the average number of degree-days. Nutrient changes – though independent from climate – also play an important role in the observed shifts in species. Received: 20 June 1999 · Accepted: 14 January 2000     

DETERMINING CRITICAL WATER QUALITY CONDITIONS FOR INORGANIC NITROGEN IN DRY,SEMI‐URBANIZED WATERSHEDS1

ABSTRACT: Traditional approaches to establishing critical water quality conditions, based on statistical analysis of low flow conditions and expressed as a recurrence interval for low flow conditions (e.g., 7Q10), may be inappropriate for drier watersheds. The use of 7Q10 as a standard design flow assumes year‐round flow, but in these watersheds, 7Q10 is zero or very small. In addition, the increasing use of multiple year dynamic water quality models at daily time steps can supercede the use of steady state approaches. Many of these watersheds are also under increasing urbanization pressure, which accentuates the flashiness of runoff and the episodic nature of critical water quality conditions. To illustrate, the conditions in the Santa Clara River, California, are considered. A statistical analysis indicates that higher inorganic nitrogen concentrations correlate strongly with low flow. However, peaks in concentrations can occur during the first storms, particularly where nonpoint source contribution is significant. Critical conditions can thus occur at different flow regimes depending on the relative magnitude of flow and pollutant contributions from various sources. The use of steady state models for these dry semi‐urbanized watersheds based on 7Q10 flows is thus unlikely to accurately simulate the potential for exceeding water quality objectives. Dynamic simulation of water quality is necessary, and as the recent intense storm event sampling data indicate, the models should be formulated to consider even smaller time steps. This places increasing demand on computational resources and datasets to accurately calibrate the models at this temporal resolution.     

Decreased acid deposition and the chemical recovery of Killarney,Ontario, lakes

Lakes in Killarney Park near Sudbury, Ontario, Canada, have shown dramatic water quality changes including general increases in pH and alkalinity, and decreases in SO4(2-), base cations and metals. While some lakes have recovered to pH > 6.0, many are still highly acidic despite decades of improvement. Very high historical S deposition related to emissions from the Sudbury metal smelters dominated the acidification process in this region. However, since the implementation of substantial S emission controls (90%) at the smelters, the Sudbury emissions are no longer the major source of S deposition in the Sudbury area. Wet deposition of SO4(2-) and SO4(2-) concentrations in lakewaters at Killarney now approach values in the Dorset, Ontario, area, about 200 km from Sudbury. This suggests that the S deposition to the Killarney area is now primarily from long-range transport, not from local sources. Studies of Killarney lakes are revealing the complex nature of the chemical recovery process. As lake acidity decreases, other changes including decreased Ca2+ concentrations, increased transparency, and altered thermal regimes may potentially affect some of these ecosystems. It is clear that continuing assessments of the recovery of Killarney lakes, within a multiple-stressor framework, are needed.     

酸沉降作用的降低和安大略省基拉尼湖泊的化学恢复

毗邻加拿大安大略省萨德伯里市的基拉尼公园中的湖泊都表现出明显的水质变化,其中包括pH值和碱度的普遍增加,SO2- 4、碱基阳离子和金属浓度的减少.经过数十年的改善,尽管一些湖泊的pH值已经大于6,但仍有许多湖泊的湖水酸度却一直很高.过去,萨德伯里金属冶炼厂排放引起的过高的硫沉降左右了这一地区的酸化过程.然而,自从冶炼厂的硫排放被严格控制之后(排放量降低了90%),萨德伯里地区的硫排放就不再是该地区最主要的硫沉降源了.目前,基拉尼地区的SO2- 4湿沉降和湖水中SO2- 4浓度已经十分接近约200km外的安大略省多赛特地区,这就表明基拉尼地区的硫沉降现在主要来自于长距离传输,而不是当地污染源.对基拉尼湖泊的研究揭示了化学恢复过程的复杂本质.一旦湖水的酸度降低,就会引起一系列的变化,包括Ca2+浓度的减少,透明度增加和热力学状态改变.这些变化可能会潜在地影响一些生态体系.因此很明显需要对基拉尼湖泊的恢复在多胁迫因子的框架内继续进行评价.     

MANAGING CRISIS: THE EFFECTIVENESS OF LOCAL DISTRICTS FOR CONTROL OF GROUND WATER MINING1

: This article examines the willingness and capacity of local districts to control ground water mining of the Ogallala Aquifer in the High Plains. The questions of willingness and capacity were approached through extensive field interviews and a survey of all district board members and managers. The analysis focuses on the policy alternatives board members and managers perceive and how they evaluate these alternatives. Methodologically, the study utilized factor analysis of responses rating the desirability of various policy alternatives to ascertain what alternatives were perceived by the sample. Then the sample's preferences for each of the identified factors were calculated. The results demonstrate that the sample of those who must regulate if ground water mining is to be controlled at the substate level are not oriented to regulatory policies and therefore lack the willingness to deal with ground water mining.     

Is being a leader a mixed blessing? A dual‐pathway model linking leadership role occupancy to well‐being

Recent leadership research has drawn greater attention to how the well‐being of leaders influences leadership behaviors, follower performance and well‐being, and overall leadership effectiveness. Yet little attention has been paid to the relationship between occupying leadership positions and job incumbents' well‐being. This research addresses this question by developing and testing a dual‐pathway model. Our model proposes that incumbency in leadership positions is positively related to high levels of both job demands and job control, whereas job demands and job control have offsetting effects on well‐being. Results based on a longitudinal sample revealed that employees who transitioned from nonleadership positions to leadership roles showed trajectories of increasing job demands and job control, whereas such trends were weaker among those who remained in nonleadership positions. Findings from three additional samples generally demonstrated that leadership role occupancy was indirectly related to various indices of psychological and physiological well‐being through job demands and job control. Because the signs of the indirect effects through job demands and job control differed in expected ways, the overall relationship between leadership role occupancy and the well‐being outcomes was generally small and nonsignificant. We discuss research and practical implications of our framework and findings for organizations, employees, and leaders.     

AgInput: An Agricultural Nutrient and Pesticide Source Model

Agriculture can be a major nonpoint source (NPS) of nutrient and pesticide contamination in the environment. Available databases do not provide accurate and dynamic data on fertilizer and pesticide application, which limits the ability of complex watershed models to simulate contaminant loads into impaired water bodies. A model for estimating agricultural nutrient and pesticide input for watershed modeling has been developed. Climate, soils, and major agricultural operations are considered within the model, so that it can be adapted to any watershed or subregion within a watershed. The timing of the agricultural operations is a function of the weather data, providing realistic results at daily, monthly, or annual application rates. The model also predicts irrigation demand and biomass production, which can be used to calibrate the model. Model output can be used in any watershed model that considers agricultural land uses. Two case studies were evaluated, using grape vineyards in the Napa River and strawberry production in Newport Bay as examples. The predicted time to maturity corresponded well with actual data. Irrigation and fertilizer needs were very sensitive to weather input. Although the model can generate weather from long-term averages, the simulated results are best when at least observed precipitation and temperature are provided, to capture extreme events. The model has data for 98 crops and 126 pesticides, based on the California Department of Pesticide Regulation database. The databases are easily modifiable by the user to adapt them to local conditions. The output from AgInput is much needed for watershed modeling and for development of total maximum daily loads (TMDLs), based on realistic targets of irrigation, nutrient, and pesticide inputs. The model is available for free download at .     

A new generic approach for estimating the concentrations of down-the-drain chemicals at catchment and national scale

A new generic approach for estimating chemical concentrations in rivers at catchment and national scales is presented. Domestic chemical loads in waste water are estimated using gridded population data. River flows are estimated by combining predicted runoff with topographically derived flow direction. Regional scale exposure is characterised by two summary statistics: PEC(works), the average concentration immediately downstream of emission points, and, PEC(area), the catchment-average chemical concentration. The method was applied to boron at national (England and Wales) and catchment (Aire-Calder) scales. Predicted concentrations were within 50% of measured mean values in the Aire-Calder catchment and in agreement with results from the GREAT-ER model. The concentration grids generated provide a picture of the spatial distribution of expected chemical concentrations at various scales, and can be used to identify areas of potentially high risk.