警惕生态旅游中的"生态破坏"

生态旅游是当今世界旅游业的一个热点，受到人们的普遍关注。但是由于人们对生态旅游的认识存在偏差，以及盲目地追求经济效益，使生态旅游演变成了破坏生态的旅游。本文讨论了生态旅游的内涵，提出了目前生态旅游中存在的问题，并提出了实现生态旅游可持续发展的若干建议。     

Air Quality Management in Izmir Region of Turkey as Required by Clean Air Plans

Future (24 h later) daily ground level SO₂ concentration in Istanbul was modeled and predicted using a new and powerful technique, Artificial Neural Networks (ANN) in the case of meteorological parameters as input variables. Results show that the trend of SO₂ from higher values in winter to lower values in spring and summer, and again to higher values towards winter can be correctly represented by the neural networks. The model better predicted the lower SO₂ values in spring and summer seasons when compared to higher values in winter season because of the pattern distribution in training data sets. Beside the amount of the database, the more the variation of the values of the parameters in their own ranges, the more the network learns the database. As a result of this study, considerably successful results were obtained when considering the complex and nonlineer structure of the atmosphere, which is the source of the database.     

Ecological Impact Assessment in Data-Poor Systems: A Case Study on Metapopulation Persistence

Legislation on the protection of biodiversity (e.g., European Union Habitat and Bird Directives) increasingly requires ecological impact assessment of human activities. However, knowledge and understanding of relevant ecological processes and species responses to different types of impact are often incomplete. In this paper we demonstrate with a case study how impact assessment can be carried out for situations where data are scarce but some expert knowledge is available. The case study involves two amphibian species, the great crested newt (Triturus cristatus) and the natterjack toad (Bufo calamita) in the nature reserve the Meinweg in the Netherlands, for which plans are being developed to reopen an old railway track called the Iron Rhine. We assess the effects of this railway track and its proposed alternatives (scenarios) on the metapopulation extinction time and the occupancy times of the patches for both species using a discrete-time stochastic metapopulation model. We quantify the model parameters using expert knowledge and extrapolated data. Because of our uncertainty about these parameter values, we perform a Monte Carlo uncertainty analysis. This yields an estimate of the probability distribution of the model predictions and insight into the contribution of each distinguished source of uncertainty to this probability distribution. We show that with a simple metapopulation model and an extensive uncertainty analysis it is possible to detect the least harmful scenario. The ranking of the different scenarios is consistent. Thus, uncertainty analysis can enhance the role of ecological impact assessment in decision making by making explicit to what extent incomplete knowledge affects predictions.     

Prioritizing Abandoned Coal Mine Reclamation Projects Within the Contiguous United States Using Geographic Information System Extrapolation

Coal mine reclamation projects are very expensive and require coordination of local and federal agencies to identify resources for the most economic way of reclaiming mined land. Location of resources for mine reclamation is a spatial problem. This article presents a methodology that allows the combination of spatial data on resources for the coal mine reclamation and uses GIS analysis to develop a priority list of potential mine reclamation sites within contiguous United States using the method of extrapolation. The extrapolation method in this study was based on the Bark Camp reclamation project. The mine reclamation project at Bark Camp, Pennsylvania, USA, provided an example of the beneficial use of fly ash and dredged material to reclaim 402,600 sq mi of a mine abandoned in the 1980s. Railroads provided transportation of dredged material and fly ash to the site. Therefore, four spatial elements contributed to the reclamation project at Bark Camp: dredged material, abandoned mines, fly ash sources, and railroads. Using spatial distribution of these data in the contiguous United States, it was possible to utilize GIS analysis to prioritize areas where reclamation projects similar to Bark Camp are feasible. GIS analysis identified unique occurrences of all four spatial elements used in the Bark Camp case for each 1 km of the United States territory within 20, 40, 60, 80, and 100 km radii from abandoned mines. The results showed the number of abandoned mines for each state and identified their locations. The federal or state governments can use these results in mine reclamation planning.     

Spatial Modeling of Harvest Constraints on Wood Supply Versus Wildlife Habitat Objectives

We studied the effects of spatial and temporal timber harvesting constraints on competing objectives of sustaining wildlife habitat supply and meeting timber harvest objectives in a boreal mixedwood forest. A hierarchical modeling approach was taken, where strategic and tactical level models were used to project blocking and scheduling of harvest blocks. Harvest block size and proximity, together with short- and long-term temporal constraints, were adjusted in a factorial manner to allow creation of response–surface models. A new measure of the habitat mosaic was defined to describe the emergent pattern of habitat across the landscape. These models, together with multiple linear regression, were used to provide insight on convergence or divergence between spatial objectives. For example, green-up delay (defined as time required before a harvest block adjacent to a previously logged block can be scheduled for harvest) had an adverse effect on the amount of annual harvest area that could be allocated and blocked spatially, and habitat supply responded in an opposite direction to that of wood supply, where caribou, moose wintering, and marten habitat supply increased when harvest blocks were further apart, maximum block size smaller, and both a green-up delay and mesoscale stratification were applied. Although there was no solution space free of conflicts, the analysis suggests that application of the mesoscale stratification, together with a diversity of harvest block sizes and a between-harvest block proximity of 250 m, will perform relatively well with respect to wood supply objectives, and at the same time create a less fragmented landscape that better reflects natural forest patterns.     

The US Clean Water Act and habitat replacement: evaluation of mitigation sites in Orange County,California, USA

Both permit requirements and ecological assessments have been used to evaluate mitigation success. This analysis combines these two approaches to evaluate mitigation required under Section 404 of the United States Clean Water Act (CWA) and Section 10 of the Rivers and Harbors Act, which allow developers to provide compensatory mitigation for unavoidable impacts to wetlands. This study reviewed permit files and conducted field assessments of mitigation sites to evaluate the effectiveness of mitigation required by the US Army Corps of Engineers for all permits issued in Orange County, California from 1979 through 1993. The 535 permit actions approved during this period allowed 157 ha of impacts. Mitigation was required on 70 of these actions, with 152 ha of enhanced, restored, and created habitat required for 136 ha of impacts. In 15 permit actions, no mitigation project was constructed, but in only two cases was the originally permitted project built; the two cases resulted in an unmitigated loss of 1.6 ha. Of the remaining 55 sites, 55% were successful at meeting the permit conditions while 11% failed to do so. Based on a qualitative assessment of habitat quality, only 16% of the sites could be considered successful and 26% were considered failures. Thus, of the 126 ha of habitat lost due to the 55 projects, only 26 ha of mitigation was considered successful. The low success rate was not due to poor enforcement, although nearly half of the projects did not comply with all permit conditions. Mitigation success could best be improved by requiring mitigation plans to have performance standards based on habitat functions.     

Determining Ecological Equivalence in Service-to-Service Scaling of Salt Marsh Restoration

The amount of ecological restoration required to mitigate or compensate for environmental injury or habitat loss is often based on the goal of achieving ecological equivalence. However, few tools are available for estimating the extent of restoration required to achieve habitat services equivalent to those that were lost. This paper describes habitat equivalency analysis (HEA), a habitat-based “service-to-service” approach for determining the amount of restoration needed to compensate for natural resource losses, and examines issues in its application in the case of salt marsh restoration. The scientific literature indicates that although structural attributes such as vegetation may recover within a few years, there is often a significant lag in the development of ecological processes such as nutrient cycling that are necessary for a fully functioning salt marsh. Moreover, natural variation can make recovery trajectories difficult to define and predict for many habitat services. HEA is an excellent tool for scaling restoration actions because it reflects this ecological variability and complexity. At the same time, practitioners must recognize that conclusions about the amount of restoration needed to provide ecological services equivalent to those that are lost will depend critically on the ecological data and assumptions that are used in the HEA calculation.     

Fuzzy decision analysis for integrated environmental vulnerability assessment of the mid-Atlantic Region

A fuzzy decision analysis method for integrating ecological indicators was developed. This was a combination of a fuzzy ranking method and the analytic hierarchy process (AHP). The method was capable of ranking ecosystems in terms of environmental conditions and suggesting cumulative impacts across a large region. Using data on land cover, population, roads, streams, air pollution, and topography of the Mid-Atlantic region, we were able to point out areas that were in relatively poor condition and/or vulnerable to future deterioration. The method offered an easy and comprehensive way to combine the strengths of fuzzy set theory and the AHP for ecological assessment. Furthermore, the suggested method can serve as a building block for the evaluation of environmental policies.     

Applying Ecological Risk Principles to Watershed Assessment and Management

Considerable progress in addressing point source (end of pipe) pollution problems has been made, but it is now recognized that further substantial environmental improvements depend on controlling nonpoint source pollution. A watershed approach is being used more frequently to address these problems because traditional regulatory approaches do not focus on nonpoint sources. The watershed approach is organized around the guiding principles of partnerships, geographic focus, and management based on sound science and data. This helps to focus efforts on the highest priority problems within hydrologically-defined geographic areas. Ecological risk assessment is a process to collect, organize, analyze, and present scientific information to improve decision making. The U.S. Environmental Protection Agency (EPA) sponsored three watershed assessments and found that integrating the watershed approach with ecological risk assessment increases the use of environmental monitoring and assessment data in decision making. This paper describes the basics of the watershed approach, the ecological risk assessment process, and how these two frameworks can be integrated. The three major principles of watershed ecological risk assessment found to be most useful for increasing the use of science in decision making are (1) using assessment endpoints and conceptual models, (2) holding regular interactions between scientists and managers, and (3) developing a focus for multiple stressor analysis. Examples are provided illustrating how these principles were implemented in these assessments.     

APPLICATION OF THE SNOWMELT RUNOFF MODEL USING MULTIPLE-PARAMETER LANDSCAPE ZONES ON THE TOWANDA CREEK BASIN,PENNSYLVANIA1

ABSTRACT: The Snowmelt Runoff Model (SRM) is designed to compute daily stream discharge using satellite snow cover data for a basin divided into elevation zones. For the Towanda Creek basin, a Pennsylvania watershed with relatively little relief, analysis of snow cover images revealed that both elevation and land use affected snow accumulation and melt on the landscape. The distribution of slope and aspect on the watershed was also considered; however, these landscape features were not well correlated with the available snow cover data. SRM streamflow predictions for 1990, 1993 and 1994 snowmelt seasons for the Towanda Creek basin using a combination of elevation and land use zones yielded more precise streamflow estimates than the use of standard elevation zones alone. The use of multiple-parameter zones worked best in non-rain-on-snow conditions such as in 1990 and 1994 seasons where melt was primarily driven by differences in solar radiation. For seasons with major rain-on-snow events such as 1993, only modest improvements were shown since melt was dominated by rainfall energy inputs, condensation and sensible heat convection. Availability of GIS coverages containing satellite snow cover data and other landscape attributes should permit similar reformulation of multiple-parameter watershed zones and improved SRM streamflow predictions on other basins.