Towards generalised reference condition models for environmental assessment: a case study on rivers in Atlantic Canada

Evaluation of the ecological status of river sites in Canada is supported by building models using the reference condition approach. However, geography, data scarcity and inter-operability constraints have frustrated attempts to monitor national-scale status and trends. This issue is particularly true in Atlantic Canada, where no ecological assessment system is currently available. Here, we present a reference condition model based on the River Invertebrate Prediction and Classification System approach with regional-scale applicability. To achieve this, we used biological monitoring data collected from wadeable streams across Atlantic Canada together with freely available, nationally consistent geographic information system (GIS) environmental data layers. For the first time, we demonstrated that it is possible to use data generated from different studies, even when collected using different sampling methods, to generate a robust predictive model. This model was successfully generated and tested using GIS-based rather than local habitat variables and showed improved performance when compared to a null model. In addition, ecological quality ratio data derived from the model responded to observed stressors in a test dataset. Implications for future large-scale implementation of river biomonitoring using a standardised approach with global application are presented.     

Coupling GIS and mulitvariate approaches to reference site selection for wadeable stream monitoring

Geographic Information System (GIS) was used to identify potential reference sites for wadeable stream monitoring, and multivariate analyses were applied to test whether invertebrate communities reflected a priori spatial and stream type classifications. We identified potential reference sites in segments with unmodified vegetation cover adjacent to the stream and in >85% of the upstream catchment. We then used various landcover, amenity and environmental impact databases to eliminate sites that had potential anthropogenic influences upstream and that fell into a range of access classes. Each site identified by this process was coded by four dominant stream classes and seven zones, and 119 candidate sites were randomly selected for follow-up assessment. This process yielded 16 sites conforming to reference site criteria using a conditional-probabilistic design, and these were augmented by an additional 14 existing or special interest reference sites. Non-metric multidimensional scaling (NMS) analysis of percent abundance invertebrate data indicated significant differences in community composition among some of the zones and stream classes identified a priori providing qualified support for this framework in reference site selection. NMS analysis of a range standardised condition and diversity metrics derived from the invertebrate data indicated a core set of 26 closely related sites, and four outliers that were considered atypical of reference site conditions and subsequently dropped from the network. Use of GIS linked to stream typology, available spatial databases and aerial photography greatly enhanced the objectivity and efficiency of reference site selection. The multi-metric ordination approach reduced variability among stream types and bias associated with non-random site selection, and provided an effective way to identify representative reference sites.     

A Bird Community Index of Biotic Integrity for the Mid-Atlantic Highlands

We report on the development and preliminary application of a songbird community-based index of biotic integrity. The bird community index (BCI) sorts bird species found at sample sites into a series of values representing the proportional species richness of 20 behavioral and physiological response guilds. Relative proportions of specialist and generalist guilds are used to assign a composite score to each site. Scores from multiple sites indicate the overall biotic integrity of the study area. The BCI is intended to function as a landscape-scale indicator of biotic integrity, integrating conditions across large sample sites containing diverse ecological resources and intensities of human use. We developed the BCI with data from a 1994 pilot study in central Pennsylvania, then applied our preliminary index in 1995 and 1996 to independent samples of sites across the Mid-Atlantic Highlands Assessment area (MAHA). The 1995 and 1996 sample sites were selected using the probability-based sampling design of the Environmental Monitoring and Assessment Program (EMAP), and therefore represent the total land area in MAHA. Our preliminary assessment indicates that MAHA exhibits six categories of biotic integrity, and that more than 40% of the land area supports the two highest biotic integrity categories. Pending BCI refinement and incorporation of landscape and vegetation explanatory variables, the BCI will be included in a suite of indicators designed to provide an assessment of overall ecological condition in MAHA.     

Selection of MSW landfill site for Konya, Turkey using GIS and multi-criteria evaluation

Landfill is a common solution for the final disposal of municipal solid waste (MSW) in Turkey. Landfill siting is an extremely difficult task to accomplish because the site selection process depends on different factors and regulations. To ensure that an appropriate site is chosen, a systematic process should be developed and followed. Unsuccessful landfill siting is typically the result of strong public opposition. In this study, candidate sites for an appropriate landfill area in Cumra County of Konya City are determined by using the integration of geographic information systems (GIS) and multi-criteria evaluation (MCE). ArcGIS 9.0 software and its extensions were used as the GIS tool since it is able to perform suitability analysis using MCE analysis. To identify appropriate landfill areas in the Cumra district, eight input map layers including proximity to municipal and local wells and irrigational canals, distance from transportation routes and rails, distance from archaeological sites, distance from urban areas, land use/land cover, and land slope are used in constraint mapping. A final map was generated which identifies regions showing suitability for the location of the landfill site. According to the map, 6.8% of the study area is most suitable, 15.7% is suitable, 10.4% is moderately suitable, 25.8% is poorly suitable, and 41.3% is unsuitable. At the end of the analyses, three candidate sites are determined. The selection of the final MSW landfill site, however, requires further field research.     

Spatial analysis and land use regression of VOCs and NO2 in Dallas, Texas during two seasons

Passive air sampling for nitrogen dioxide (NO(2)) and select volatile organic compounds (VOCs) was conducted at 24 fire stations and a compliance monitoring site in Dallas, Texas, USA during summer 2006 and winter 2008. This ambient air monitoring network was established to assess intra-urban gradients of air pollutants to evaluate the impact of traffic and urban emissions on air quality. Ambient air monitoring and GIS data from spatially representative fire station sites were collected to assess spatial variability. Pairwise comparisons were conducted on the ambient data from the selected sites based on city section. These weeklong samples yielded NO(2) and benzene levels that were generally higher during the winter than the summer. With respect to the location within the city, the central section of Dallas was generally higher for NO(2) and benzene than north and south. Land use regression (LUR) results revealed spatial gradients in NO(2) and selected VOCs in the central and some northern areas. The process used to select spatially representative sites for air sampling and the results of analyses of coarse- and fine-scale spatial variability of air pollutants on a seasonal basis provide insights to guide future ambient air exposure studies in assessing intra-urban gradients and traffic impacts.     

Prediction of stream fish assemblages from land use characteristics: implications for cost-effective design of monitoring programmes

Increasing human impact on stream ecosystems has resulted in a growing need for tools helping managers to develop conservations strategies, and environmental monitoring is crucial for this development. This paper describes the development of models predicting the presence of fish assemblages in lowland streams using solely cost-effective GIS-derived land use variables. Three hundred thirty-five stream sites were separated into two groups based on size. Within each group, fish abundance data and cluster analysis were used to determine the composition of fish assemblages. The occurrence of assemblages was predicted using a dataset containing land use variables at three spatial scales (50 m riparian corridor, 500 m riparian corridor and the entire catchment) supplemented by a dataset on in-stream variables. The overall classification success varied between 66.1–81.1% and was only marginally better when using in-stream variables than when applying only GIS variables. Also, the prediction power of a model combining GIS and in-stream variables was only slightly better than prediction based solely on GIS variables. The possibility of obtaining precise predictions without using costly in-stream variables offers great potential in the design of monitoring programmes as the distribution of monitoring sites along a gradient in ecological quality can be done at a low cost.     

Selecting objectively defined reference sites for stream bioassessment programs

Our study develops and demonstrates an objective method for selecting reference sites for the assessment of ecological condition in freshwater ecosystems. The method uses widely available GIS data to group potential sites based on their natural environments. It then establishes the degree and types of human activities each site is exposed to prior to scoring the sites in each group by the relative amount of human activity present. Finally, the sites in each group with the least amount of human activity are categorized as reference sites, with the boundary between reference and test sites defined to maximize the distinctiveness of the two categories with respect to human activity. Application of this technique for the purpose of identifying headwater reference basins in rural areas of southwestern Ontario resulted in the classification of basins into six natural groups based on the dominant texture of the surface geology. Development of a human activity gradient indicated that basins varied according to the amount of exposure to agricultural activities with most basins having at least moderate exposure. Establishment of the reference test boundary indicated that the selected reference basins exhibited substantively lower extents of agricultural activity than test sites for most groups. Because this method uses only widely available GIS data, it enables rapid and cost-effective identification of candidate reference sites, even for large, remote, and understudied regions.     

The SSC cycle: a PDCA approach to address site-specific characteristics in a continuous shallow water quality monitoring project

In any water quality-monitoring project there are several critical success factors that must be adequately addressed in order to ensure the implementation and realization of the monitoring objectives. Site selection is one of these critical success factors. The monitoring sites must be selected to comply with the monitoring and data quality objectives. In the real world, ideal monitoring setting conditions are difficult to achieve, and compromises must be made in order to locate the monitoring stations that best represent the environment to be monitored. Site-specific characteristics are all the environmental, logistical and management factors particular to the monitoring site, that could influence the fulfilment of the monitoring and data quality objectives. Therefore, during the site selection process, it is essential to properly consider and evaluate these site-specific characteristics. The SSC cycle was developed with this goal in mind, to assist the monitoring team to systematically address site-specific characteristics. The cycle is a methodology to organize the site-specific characteristics in different categories, and to ensure a comprehensive overview of these characteristics throughout the project life cycle.     

Addressing statistical and operational challenges in designing large-scale stream condition surveys

Implementing a statistically valid and practical monitoring design for large-scale stream condition monitoring and assessment programs can be difficult due to factors including the likely existence of a diversity of ecosystem types such as ephemeral streams over the sampling domain; limited resources to undertake detailed monitoring surveys and address knowledge gaps; and operational constraints on effective sampling at monitoring sites. In statistical speak, these issues translate to defining appropriate target populations and sampling units; designing appropriate spatial and temporal sample site selection methods; selection and use of appropriate indicators; and setting effect sizes with limited ecological and statistical information about the indicators of interest. We identify the statistical and operational challenges in designing large-scale stream condition surveys and discuss general approaches for addressing them. The ultimate aim in drawing attention to these challenges is to ensure operational practicality in carrying out future monitoring programs and that the resulting inferences about stream condition are statistically valid and relevant.     

Geospatial strategy for sustainable management of municipal solid waste for growing urban environment

This paper presents the implementation of a Geospatial approach for improving the Municipal Solid Waste (MSW) disposal suitability site assessment in growing urban environment. The increasing trend of population growth and the absolute amounts of waste disposed of worldwide have increased substantially reflecting changes in consumption patterns, consequently worldwide. MSW is now a bigger problem than ever. Despite an increase in alternative techniques for disposing of waste, land-filling remains the primary means. In this context, the pressures and requirements placed on decision makers dealing with land-filling by government and society have increased, as they now have to make decisions taking into considerations environmental safety and economic practicality. The waste disposed by the municipal corporation in the Bhagalpur City (India) is thought to be different from the landfill waste where clearly scientific criterion for locating suitable disposal sites does not seem to exist. The location of disposal sites of Bhagalpur City represents the unconsciousness about the environmental and public health hazards arising from disposing of waste in improper location. Concerning about urban environment and health aspects of people, a good method of waste management and appropriate technologies needed for urban area of Bhagalpur city to improve this trend using Multi Criteria Geographical Information System and Remote Sensing for selection of suitable disposal sites. The purpose of GIS was to perform process to part restricted to highly suitable land followed by using chosen criteria. GIS modeling with overlay operation has been used to find the suitability site for MSW.     

Evaluating macroinvertebrate biological metrics for ecological assessment of streams in northern Portugal

A procedure to select the most relevant metrics for assessing the ecological condition of the Douro basin (north Portugal) was developed based upon a set of 184 benthic community metrics. They were grouped into 16 biological categories selected from literature using data collected over 2 years from 54 sites along 31 rivers covering the whole perceived range of human disturbance. Multivariate analyses were carried out to identify the main trends in the macroinvertebrate data, to select reference versus impaired sites, to avoid multicolinearity between metrics, and to identify those that were clearly independent from natural stream typology. Structural metrics, adaptation metrics, and tolerance measures most effectively responded across a range of human influence. We find these attributes to be ecologically sound for monitoring Portugal’s lotic ecosystems and providing information relevant to the Water Framework Directive, which asserts that the definition of water quality depends on its “ecological status”, independent of the actual or potential uses of those waters.     

基于Landsat ETM+等影像的无锡市十年陆地生态环境遥感评价

遥感和GIS技术的发展为研究区域生态环境变化提供了有效手段,以无锡市2004-2013年的ETM＋等遥感影像和GDEM高程数据为数据源,运用遥感和GIS方法提取生态因子信息并进行陆地生态状况遥感评价。结果表明,无锡市近十年陆地生态环境整体趋好。     

Sampling state and process variables on coral reefs

Contemporary coral reefs are forced to survive through and recover from disturbances at a variety of spatial and temporal scales. Understanding disturbances in the context of ecological processes may lead to accurate predictive models of population trajectories. Most coral-reef studies and monitoring programs examine state variables, which include the percentage coverage of major benthic organisms, but few studies examine the key ecological processes that drive the state variables. Here we outline a sampling strategy that captures both state and process variables, at a spatial scale of tens of kilometers. Specifically, we are interested in (1) examining spatial and temporal patterns in coral population size-frequency distributions, (2) determining major population processes, including rates of recruitment and mortality, and (3) examining relationships between processes and state variables. Our effective sampling units are randomly selected 75 × 25 m stations, spaced approximately 250?C500 m apart, representing a 10³ m spatial scale. Stations are nested within sites, spaced approximately 2 km apart, representing a 10⁴ m spatial scale. Three randomly selected 16 m² quadrats placed in each station and marked for relocation are used to assess processes across time, while random belt-transects, re-randomized at each sampling event, are used to sample state variables. Both quadrats and belt-transects are effectively sub-samples from which we will derive estimates of means for each station at each sampling event. This nested sampling strategy allows us to determine critical stages in populations, examine population performance, and compare processes through disturbance events and across regions.     

Desertification Evaluated Using an Integrated Environmental Assessment Model

Desertification has been defined as land degradation in arid, semi-arid and dry sub-humid areas resulting from various factors, including climatic variations and human activities (United Nations, 1992). A technique for identifying and assessing areas at risk fordesertification in the arid, semi-arid, and subhumid regionsof the United States was developed by the Desert Research Institute and the U.S. Environmental Protection Agency (EPA), using selected environmental indicators integrated into a Geographic Information System (GIS). Five indicators were selected: potential erosion, grazing pressure, climatic stress (expressed as a function of changesin the Palmer Drought Severity Index [PDSI]), change invegetation greenness (derived from the Normalized DifferenceVegetation Index [NDVI]), and weedy invasives as a percentof total plant cover. The data were integrated over aregional geographic setting using a GIS, which facilitateddata display, development and exploration of data relationships, including manipulation and simulation testing. By combining all five data layers, landscapes having a varying risk for land degradation were identified, providing a tool which could be used to improve landmanagement efficiency.     

Designing a Spatially Balanced, Randomized Site Selection Process for Regional Stream Surveys: The EMAP Mid-Atlantic Pilot Study

In 1993, the U.S. Environmental Protection Agency (EPA), as part of the Environmental Monitoring and Assessment Program (EMAP), initiated a sample survey of streams in the mid-Atlantic. A major objective of the survey was to quantify ecological condition in wadeable streams across the region. To accomplish this goal, we selected 615 stream sites using a randomized sampling design with some restrictions. The design utilized the digitized stream network taken from 1:100,000-scale USGS topographic maps as the sample frame. Using a GIS, first- through third-order (wadeable) stream segments in the sample frame were randomly laid out in a line and sampled at fixed intervals after a random start. We used a variable probability approach so that roughly equal numbers of first-, second-, and third-order stream sites would appear in the sample. The sample design allows inference from the sample data to the status of the entire 230,400 km of wadeable stream length in the mid-Atlantic study area. Of this mapped stream length, 10% was not in the target population because no stream channel existed (4%), the stream channel was dry (5%), or the stream was not wadeable (1%). We were unable to collect field data from another 10% of the mapped stream length due to lack of access (mostly landowner denials). Thus, the field data we collected at 509 sites allows inference to the ecological condition for 184,600 km of the mapped stream length in the region.     

Environmental quality assessment combining sediment metal levels, biomarkers and macrobenthic communities: application to the óbidos coastal lagoon (Portugal)

Macroinvertebrate benthic communities are one of the key biological components considered for the assessment of benthic integrity in the context of the Water Framework Directive (WFD). However, under moderate contamination scenarios, the assessment of macrobenthic alterations at community level alone could be insufficient to discriminate the environmental quality of coastal and transitional waters. Keeping this in view, sediment quality of moderately contaminated sites in a coastal lagoon (óbidos lagoon, Portugal) was assessed by the combination of sediment metal levels, Carcinus maenas biomarkers (accumulated metals and oxidative stress responses) and macrobenthic communities. Two sites were selected in confined inner branches (BS and BB) and a third one in the middle lagoon (ML). The site BB presented slightly higher levels of metals in sediment but biological variables calculated for macrobenthic data were not significantly different between sites. The biotic index M-AMBI that is being applied to assess environmental quality of transitional waters in the scope of the WFD pointed either to high (site ML) or good quality status (BS and BB) in the selected sites. However, crabs from BB site presented significantly higher levels of Ni in hepatopancreas than those from ML and macrobenthic community structure was significantly different between BB and ML. Additionally, spatial differences were obtained for oxidative stress parameters suggesting that BB site presented stressors for crabs (higher GST and lower GSH_t at BB site). Factor analysis (PCA) integrating sediment contamination, biomarkers in crabs and macrobenthic data also distinguished BB site as the most environmentally disturbed. On the other hand, at ML site, some macrobenthic variables (equitability and polychaetes’ diversity) were found to be enhanced by current environmental conditions, suggesting the existence of a better sediment quality. Current results pointed to the usefulness of integrating macrobenthic community alterations with responses at organism level (bioaccumulation and biochemical endpoints) in order to increase the accuracy of environmental quality assessment in lagoon systems. Moreover, the application of different statistical methods was also found to be recommendable.     

Solid waste disposal site selection with GIS and AHP methodology: a case study in Senirkent�CUluborlu (Isparta) Basin, Turkey

The appropriate site selection for waste disposal is one of the major problems in waste management. Also, many environmental, economical, and political considerations must be adhered to. In this study, landfill site selection is performed using the Geographic Information System (GIS), the Analytical Hierarchy Process (AHP), and the remote sensing methods for the Senirkent?CUluborlu Basin. The basin is located in the E?irdir Lake catchment area, which is one of the most important fresh water in Turkey. So, waste management must be regulated in the basin. For this aim, ten different criteria (lithology, surface water, aquifer, groundwater depth, land use, lineaments, aspect, elevation, slope, and distance to roads) are examined in relation to landfill site selection. Each criterion was identified and weighted using AHP. Then, each criterion is mapped using the GIS technique, and a suitability map is prepared by overlay analyses. The results indicate that 96.3% of the area in the basin is unsuitable; 1.6%, moderately suitable; and 2.1%, most suitable. Finally, suitable regions in the basin are determined for solid waste landfill disposal and checked in the field. The selected and investigated regions are considered to be suitable for the landfill.     

Delineation of Environmental Units by Multivariate Techniques in the Duero River Watershed,Michoacán,Mexico

Environmental or hydrological landscape units can integrate various environmental characteristics to support proper management of natural resources. To delineate these units, quantitative methods such as ordination, clustering, and classification of abiotic factor information are used. In the present work, environmental units were delineated in the Duero River watershed of Michoacán, Mexico. This will enhance understanding of the hydrologic landscape, which is a fundamental to natural resource management. A digital elevation model was used to generate sub-basins. Climatic data were obtained from 16 meteorological stations. Sixty-nine soil and 150 water samples were collected and analyzed in the laboratory. Geostatistical methods for spatial prediction of the environmental variables were used. Mean data for each sub-basin were obtained from the environmental variable grids, generating an abiotic factor data matrix. A multivariate analysis was conducted. Exponential, linear, spherical, and Gaussian models were fit to an empirical variogram. Spatial prediction of the environmental data was done via universal and ordinary kriging. Based on principal component analysis, abiotic factors evaporation, total nitrogen, soil pH, and sodium absorption ratio of water were selected for cluster analysis. Five environmental units were delineated in the Duero watershed. One environmental unit (number 4) provided greater than 50 % of the payment for ecosystem services. The general trend is an increase of urban area. The urban surface in 1983 and 2014 was 1724 and 4750 ha, respectively, an increase of 275 %. Environmental unit 1 showed the greatest urban area growth (1336 ha) during the latter period.