Long-term trends and spatial variability in nitrate leaching from alpine catchment-lake ecosystems in the Tatra Mountains (Slovakia-Poland)

Relationships between catchment characteristics of 31 alpine lakes and observed trends in lake water concentrations of nitrate were evaluated in the Tatra Mountains. Nitrate concentrations increased from background levels <4 microeql(-1) in the 1930s to maxima (up to 55 microeql(-1)) in the 1980s, after which they declined to 4-44 microeql(-1) by the late 1990s. In-lake nitrate concentrations correlated negatively with parameters characterising catchment-weighted mean pools (CWM; kgm(-2)) of soil, i.e. with percent land cover with meadow and soil depth, and positively with grade of terrain, annual precipitation, and the highest elevation in the catchment. The CWM pool of soil and annual precipitation explained together 65% of the current spatial variability in nitrate concentrations. Denitrification and direct N deposition on surface area explained 14% of the variability. Increased atmospheric N deposition and declining net N retention in soils were responsible for long-term changes in nitrate concentrations. Long-term decline in %N retention in soils decreased along with the estimated decline in C:N ratios (from 21 to 18 on average during the last 70 years). An empirical model linking nitrate concentrations in different types of alpine Tatra Mountain lakes to four independent variables (CWM soil pool, annual precipitation, increased N deposition, and average trend in soil C:N ratios) explained 80% of the observed spatial and temporal nitrate variability over the period 1937-2000.     

Some political aspects of pollution control

In this paper some principles of optimal control theory are applied to an examination of the possible differences that political and economic decisions making may have in the area of pollution control. The main points are that (1) Pollution Control Boards (PCB's) may behave as though they place weights on control and benefit functions that differ from market determined weights, (2) divergencies between political and market weights impose welfar; losses, and (3) given that PCB's may be succeeded by another board the current PCB may adapt its behavior to counteract or enforce the expected future behavior of the new PCB.     

Application of nanoparticle tracking analysis for characterising the fate of engineered nanoparticles in sediment-water systems

Novel applications of nanotechnology may lead to the release of engineered nanoparticles (ENPs), which result in concerns over their potential environmental hazardous impact. It is essential for the research workers to be able to quantitatively characterise ENPs in the environment and subsequently to assist the risk assessment of the ENPs. This study hence explored the application of nanoparticle tracking system (NTA) to quantitatively describe the behaviour of the ENPs in natural sediment-water systems. The NTA allows the measurement of both particle number concentration (PNC) and particle size distribution (PSD) of the ENPs. The developed NTA method was applied to a range of gold and magnetite ENPs with a selection of surface properties. The results showed that the positively-charged ENPs interacted more strongly with the sediment than neutral and negatively-charged ENPs. It was also found that the citrate coated Au ENPs had a higher distribution percentage (53%) than 11-mercaptoundecanoic acid coated Au ENPs (20%) and citrate coated magnetite ENPs (21%). The principles of the electrostatic interactions between hard (and soft) acids and bases (HSAB) are used to explain such behaviours; the hard base coating (i.e. citrate ions) will interact more strongly with hard acid (i.e. magnetite) than soft acid (i.e. gold). The results indicate that NTA is a complementary method to existing approaches to characterise the fate and behaviour of ENPs in natural sediment.     

Estimating Floodwater Depths from Flood Inundation Maps and Topography

Information on flood inundation extent is important for understanding societal exposure, water storage volumes, flood wave attenuation, future flood hazard, and other variables. A number of organizations now provide flood inundation maps based on satellite remote sensing. These data products can efficiently and accurately provide the areal extent of a flood event, but do not provide floodwater depth, an important attribute for first responders and damage assessment. Here we present a new methodology and a GIS‐based tool, the Floodwater Depth Estimation Tool (FwDET), for estimating floodwater depth based solely on an inundation map and a digital elevation model (DEM). We compare the FwDET results against water depth maps derived from hydraulic simulation of two flood events, a large‐scale event for which we use medium resolution input layer (10 m) and a small‐scale event for which we use a high‐resolution (LiDAR; 1 m) input. Further testing is performed for two inundation maps with a number of challenging features that include a narrow valley, a large reservoir, and an urban setting. The results show FwDET can accurately calculate floodwater depth for diverse flooding scenarios but also leads to considerable bias in locations where the inundation extent does not align well with the DEM. In these locations, manual adjustment or higher spatial resolution input is required.     

Flood resilience: consolidating knowledge between and within critical infrastructure sectors

Flood resilience has been rising up the political, economic and social agendas. Taking an integrated systems approach, using the right design guidance and tools and ensuring that education is in place for all stakeholders are three themes which are intrinsically linked to delivering flood resilience. This paper reviews these themes across the academic research, policy landscape and practitioner approaches, drawing conclusions on the way forward to increase our societies resilience to floods. The term ‘flood resilience’ is being increasingly used, however, it remains to be clearly defined and implemented. The UK, USA and Australia are leading the way in considering what flood resilience really means, but our review has found few examples of action underpinned by an understanding of systems and complexity. This review investigates how performance objectives & indicators are currently interpreted in guidance documents. It provides an in-depth exploration of the methods, that although developed through European and US expertise, can be used for worldwide application. Our analysis highlights that resilience is often embedded in engineering education and frequently linked to risk. This may however, mask the importance of resilience and where it differs from risk. With £2.6 billion to be spent in the UK over the next 6 years on strengthening the country’s flood and coastal defences, this is the opportunity to rethink resilience from a systems approach, and embed that learning into education and professional development of engineers. Our conclusions indicate how consolidating flood resilience knowledge between and within critical infrastructure sectors is the way forward to deliver flood resilience engineering.     

A COST‐BENEFIT ANALYSIS OF WATER QUALITY PROTECTION IN THE CATAWBA BASIN1

ABSTRACT: The primary objective of this study was to perform a cost‐benefit analysis of maintaining the current level of water quality in the Catawba River basin. Economic benefits were estimated using a stated preference survey method designed to value respondents' willingness to pay for a management plan to protect water quality in the Catawba basin over time. From the surveys conducted with 1,085 area residents, we calculated an annual mean willingness to pay of $139 for the management plan, or more than $75.4 million for all taxpayers in the area. Over the five‐year time horizon in which respondents were asked to pay for the management plan, this resulted in a total economic benefit of $340.1 million. The Watershed Analysis Risk Management Framework model was used to estimate the amount of management activities needed to protect the current level of water quality in the basin over time. Based on the model results, the total cost of the management plan was calculated to be $244.8 million over a ten‐year period. The resulting cost‐benefit analysis indicated that the potential benefits of this management plan would outweigh the costs by more than $95 million.     

Identifying socioeconomic and biophysical factors driving forest loss in protected areas

Protected areas (PAs) are a commonly used strategy to confront forest conversion and biodiversity loss. Although determining drivers of forest loss is central to conservation success, understanding of them is limited by conventional modeling assumptions. We used random forest regression to evaluate potential drivers of deforestation in PAs in Mexico, while accounting for nonlinear relationships and higher order interactions underlying deforestation processes. Socioeconomic drivers (e.g., road density, human population density) and underlying biophysical conditions (e.g., precipitation, distance to water, elevation, slope) were stronger predictors of forest loss than PA characteristics, such as age, type, and management effectiveness. Within PA characteristics, variables reflecting collaborative and equitable management and PA size were the strongest predictors of forest loss, albeit with less explanatory power than socioeconomic and biophysical variables. In contrast to previously used methods, which typically have been based on the assumption of linear relationships, we found that the associations between most predictors and forest loss are nonlinear. Our results can inform decisions on the allocation of PA resources by strengthening management in PAs with the highest risk of deforestation and help preemptively protect key biodiversity areas that may be vulnerable to deforestation in the future.     

The Researcher's Notebook: Mission and scope

Order and simplification are the first steps toward the mastery of a subject—the actual enemy is the unknown.

相似文献   

Effects of site-selection bias on estimates of biodiversity change

Estimates of biodiversity change are essential for the management and conservation of ecosystems. Accurate estimates rely on selecting representative sites, but monitoring often focuses on sites of special interest. How such site-selection biases influence estimates of biodiversity change is largely unknown. Site-selection bias potentially occurs across four major sources of biodiversity data, decreasing in likelihood from citizen science, museums, national park monitoring, and academic research. We defined site-selection bias as a preference for sites that are either densely populated (i.e., abundance bias) or species rich (i.e., richness bias). We simulated biodiversity change in a virtual landscape and tracked the observed biodiversity at a sampled site. The site was selected either randomly or with a site-selection bias. We used a simple spatially resolved, individual-based model to predict the movement or dispersal of individuals in and out of the chosen sampling site. Site-selection bias exaggerated estimates of biodiversity loss in sites selected with a bias by on average 300–400% compared with randomly selected sites. Based on our simulations, site-selection bias resulted in positive trends being estimated as negative trends: richness increase was estimated as 0.1 in randomly selected sites, whereas sites selected with a bias showed a richness change of −0.1 to −0.2 on average. Thus, site-selection bias may falsely indicate decreases in biodiversity. We varied sampling design and characteristics of the species and found that site-selection biases were strongest in short time series, for small grains, organisms with low dispersal ability, large regional species pools, and strong spatial aggregation. Based on these findings, to minimize site-selection bias, we recommend use of systematic site-selection schemes; maximizing sampling area; calculating biodiversity measures cumulatively across plots; and use of biodiversity measures that are less sensitive to rare species, such as the effective number of species. Awareness of the potential impact of site-selection bias is needed for biodiversity monitoring, the design of new studies on biodiversity change, and the interpretation of existing data.