A conceptual framework for selecting environmental indicator sets

In recent years, environmental indicators have become a vital component of environmental impact assessments and “state of the environment” reporting. This has increased the influence of environmental indicators on environmental management and policy making at all scales of decision making. However, the scientific basis of the selection process of the indicators used in environmental reporting can be significantly improved. In many studies no formal selection criteria are mentioned and when selection criteria are used they are typically applied to indicators individually. Often, no formal criteria are applied regarding an indicator's analytical utility within the total constellation of a selected set of indicators. As a result, the indicator selection process is subject to more or less arbitrary decisions, and reports dealing with a similar subject matter or similar geographical entities may use widely different indicators and consequently paint different pictures of the environment. In this paper, a conceptual framework for environmental indicator selection is proposed that puts the indicator set at the heart of the selection process and not the individual indicators. To achieve this objective, the framework applies the concept of the causal network that focuses on the inter-relation of indicators. The concept of causal networks can facilitate the identification of the most relevant indicators for a specific domain, problem and location, leading to an indicator set that is at once transparent, efficient and powerful in its ability to assess the state of the environment.     

A genetically encoded indicator for monitoring intracellular chloride

Inhibitory drives in the nervous system are provided by synapses operating mostly through Cl⁻ ion channels. We describe a novel CFP-YFP-based fluorescence Cl⁻ indicator, Cl-sensor, characterized by a high sensitivity, which can be successfully used as a tool for monitoring intracellular Cl⁻ in various biological preparations. Neirofiziologiya/Neurophysiology, Vol. 39, Nos. 4/5, pp. 380–381, July–October, 2007.     

Importance of spatial autocorrelation in modeling bird distributions at a continental scale

Spatial autocorrelation in species' distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike's information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species' distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent.     

Biosensors for environmental monitoring

Increasing environmental legislation which controls the release and the levels of certain chemicals in the environment has created a need for reliable monitoring of these substances in air, soil and especially water. Conventional analytical techniques, although highly precise, suffer from the disadvantages of high cost, the need for trained personnel and the fact that they are mostly laboratory bound. Biosensors because of their specificity, fast response times, low cost, portability, ease of use and a continuous real time signal, can present distinct advantages in certain cases. Their biological base makes them ideal for toxicological measurements which are suited for health and safety applications. Over the last 3-4 years there has been an increase in the number of publications concerning biosensors for environmental monitoring, especially in the field of pesticide measurements.This paper reviews some of the more important developments over the past 3-4 years.     

Continuous monitoring of predator control operations at landscape scale

Summary   Exotic predators are considered pests to wildlife and agriculture, requiring predator-control programs. Effective monitoring of predator-control operations is essential to justify their considerable cost, but often impossible in practice. The difficulties are especially severe if the target species is small and wide-ranging, and the area to be protected is inaccessible and/or extensive. A convenient model predator of this type, the feral Ferret ( Mustela furo ), is subject to control on farmland in New Zealand. We monitored the distribution of Ferrets over 2400 ha in the central North Island, before and throughout a standard control operation by professional trappers. We used 24 units of a new automated monitoring device, the Scentinel, set in a grid at 1 per 100 ha. Over 11 weeks (11 February to 29 April 2005, 1718 trap nights), we recorded 1559 visits by small mammals, including 198 by Ferrets. By the end of the 4th week, Ferrets had been detected at 17 of 24 sites. Removal of Ferrets from the study area by contractors began during the 5th week, and was reflected in significant declines in the number of Ferret visits recorded per day ( P  = 0.008) and the number of sites visited ( P  = 0.021). Analysis of our extensive repeat-survey data by site-occupancy methods confirmed these trends in greater detail, while also allowing for variation in detectability.     

Biosensors for environmental monitoring.

In this article we will outline several biosensor applications which may fill existing technology gaps in the area of environmental monitoring. The requirements for these environmental biosensors, as well as difficulties in commercialization, are also addressed.     

Methodological approach for the assessment of environmental effects of agroforestry at the landscape scale

Silvoarable agroforestry, the deliberate combined use of trees and arable crops on the same area of land, has been proposed in order to improve the environmental performance of agricultural systems in Europe. Based on existing models and algorithms, we developed a method to predict the environmental effects of SAF at a farm and landscape scale. The method is comprised of an assessment of soil erosion, nitrogen leaching, carbon sequestration, and landscape diversity and allowed the comparison of the environmental performance of SAF with arable systems using these four indicators.The method was applied to three landscape test sites of 4 km × 4 km each in Spain, France, and The Netherlands, and compared different levels of agroforestry adoption on farmland of different potential productivity. Silvoarable agroforestry was predicted to reduce soil erosion by up to 70%, to reduce N leaching by 20–30%, to increase C sequestration over 60 years by up to 140 tonnes C ha⁻¹, and to increase landscape diversity up to four times. The method developed was executed with widely available landscape and farm structural data and can therefore be applied to other regions in order to obtain a broader assessment of the environmental performance of silvoarable agroforestry systems.     

The effects of environmental variation on bryophytes at a regional scale

The distribution of bryophytes in central Belgium was investigated using species grid‐mapping superimposed on a series of maps which included information on soil conditions and land use. Our objectives were to assess the influence of environmental variation on the bryoflora at a regional scale, to examine how bryophytes respond to environmental variation, and to assess the extent to which species ecological and life‐history traits determine the accuracy of the predictability of species occurrence in order to provide comprehensive lists of species based on environmental conditions. The first two axes of a correspondence analysis (CA) of the floristic data explained 14.6% of the total χ². CA1 was significantly correlated with loamy‐sandy soils on a sand layer (r=?0.74, p<0.001), forest cover (r=?0.80, p<0.001), loamy soils (r=0.79, p<0.001), and agricultural fields cover (r=0.61, p<0.001). CA2 had a low but significant correlation coefficient with pebbly soils cover (r=0.38, p<0.001). The probability of occurrence of 59% of the investigated species could be significantly predicted by logistic regression from the sets of environmental variables. About 55% of the species exhibited an increasing probability of occurrence with increasing forest cover and loamy‐sandy soils cover, 1% with agricultural fields and loamy soils cover, and 3% with pebbly soils cover. The predictability of species occurrence varied as a function of four life‐history traits (minimum spore size, life expectancy, type of gametophyte and papillose leaf cell walls) and three ecological traits (indicator values of light, temperature and soil acidity). The most predictable species, including a number of leafy liverworts, were characteristic for acidic, fresh and shaded conditions and displayed a strong preference for forest habitats. Taxa with limited predictability included epiphytes and mosses characteristic of pebbly soils due to the ability of these species to efficiently disperse and adapt to various ecological conditions. Species for which the distribution range could not successfully be predicted were either ubiquitous, characteristic for ephemeral habitats, or highly successful in a very common habitat.     

A continental scale evaluation of the role of limpet grazing on rocky shores

It is critical for our knowledge of biodiversity and ecosystem processes to understand how individual species contribute to ecosystem processes and how these contributions vary in space and time. We used a manipulative field experiment in five locations over 17° of latitude [from southern Portugal to the Isle of Man (British Isles)] to determine the relative response of rocky intertidal algal assemblages released from control by the grazing of limpets. Response ratios showed that when limpets were removed there was a trend of effects from north to south. In the north, grazing had a strong effect on algal assemblages, but removing grazers reduced spatial variability in assemblages. In the south, the effect of limpet grazing was far weaker and removal of grazers had a much reduced impact on spatial variability. Here we show a clear trophic control of an ecosystem in that grazing by limpets not only determines macroalgal abundance overall but also modifies ecosystem stability via variability in cover of algae.     

A low-cost, portable generic biotoxicity assay for environmental monitoring applications

Fish chromatophores have been shown to be promising biosensors for the detection of hostile agents in the environment. However, state-of-art methods for such applications are still based on extensive use of data/signal processing, in conjunction with need for a skilled human observer to carry out the detection. As a result, conventional methods are complex, costly and cumbersome rendering them useless for field applications requiring low-cost portable solutions capable of fast detection. A new technique is proposed based on the popular scheme of observing the aggregation response in chromatophores for detection of toxicity, and a solution using optical detection and electronic processing is outlined. This scheme has the advantage of being low in cost while providing simple, fast and reliable detection.     

Key predictors of soil organic matter vulnerability to mineralization differ with depth at a continental scale

Biogeochemistry - Soil organic matter (SOM) is the largest terrestrial pool of organic carbon, and potential carbon-climate feedbacks involving SOM decomposition could exacerbate anthropogenic...     

Quartz crystal microbalance immunosensors for environmental monitoring

This paper presents discussion of quartz crystal microbalance (QCM) immunosensors for environmental monitoring. Factors limiting the practical application of antibodies to analytical problems are also presented. Among several candidates for the QCM immunosensor device, selected QCM devices and oscillating circuits were tested thoroughly and developed to obtain highly stable and sensitive frequency signals. The biointerface of QCM immunosensor was designed and controlled to immobilize antibody on the QCM surface, to reduce non-specific binding and to suppress denaturation of immobilizing antibody by self-assembled monolayer technique and artificial phospholipid (2-methacryloyloxyethyl phosphorylcholine (MPC)) polymer. MPC polymer as a antibody-stabilizing reagent was added to reduce non-specific binding of the antigen solution and stabilize the immunologic activity of the antibody-immobilized QCM. In addition, it provides examples for detection and quantitation of environmental samples using QCM immunosensors. The analytical results for fly ash extracted samples of dioxins using the QCM immunosensor indicated a good relationship with GC/MS methods. The integrating protocols of the competitive immunoassay and signal-enhancing step are for detecting low molecular analytes with extremely low detection limits using an QCM immunosensor. Furthermore, its detect limitation was extended from 0.1 to 0.01 ng/ml by the signal-enhancing step when the anti-bisphenol-A antibody conjugated MPC polymeric nanoparticles was used. The QCM immunosensor method has demonstrated its effectiveness as an alternative screening method for environmental monitoring because these results were compared with results obtained through environmental monitoring methods such as ELISA and GC/MS.     

A quantitative indicator framework for stand level evaluation and monitoring of environmentally sustainable forest management

An indicator framework was designed as an operational science-based tool for the evaluation of the environmental aspects of sustainable forest management at stand level in Flanders (Belgium). The framework aims to assess the effects of forest management on forest composition, structure and functioning. It consists of seven principles and 19 criteria, to which 157 potential indicators, selected from literature, were assigned; 40 of these were considered as suitable by an expert panel, based on 10 operational selection criteria. All indicators were quantitative variables measurable in the field.After elaboration of a measurement protocol, the indicator framework was validated in 115 forest stands, distributed over the three main forest types of Flanders. The new indicator framework exhibited greater sensitivity to forest management practices and demonstrated better discriminating power than the method that is currently used by the Flemish forest administration to estimate the naturalness and environmental quality of a forest stand. Following a detailed cost calculation of each indicator and based on the sensitivity of each indicator to forest management practices, the indicator framework was further reduced to a final set of 29 indicators. This framework can also be applied in other regions, provided that local threshold values are defined to convert indicator values to indicator scores.The selection procedure and the possible contribution of this set to the forest management in Flanders are discussed.     

Tree-ring characterization of Araucaria columnaris Hook and its applicability as a lead indicator in environmental monitoring

Tree-rings have frequently been used for dating of trees and to determine annual growth increments and forest dynamics, but little is known in tropical conditions about their utilization for environmental monitoring. This paper presents the results of Araucaria columnaris tree-ring characterization by wood anatomy and X-ray densitometric analysis and the determination of Pb concentration. Core samples from twelve araucaria trees were extracted from two sites exposed to air pollution due to intense traffic of vehicles and industrial activities. The tree-rings distinctly presented radial variation in early-latewood thickness and density, and characteristics of juvenile and mature wood. Anatomical and X-ray densitometric analysis were useful to delimit the tree-ring boundaries and to date the tree-rings, as well as to prove the annual formation. The lead concentration in annual araucaria tree-rings, analyzed with graphite furnace atomic absorption spectrometry, indicated the seasonal presence of the heavy metal in the environment during the 30 years studied, although the Pb did not affect tree growth.     

F-IND: A framework to design fuzzy indices of environmental conditions

Multivariable indices of environmental conditions summarize the information provided by several biotic or abiotic variables into a single value of immediate interpretability. Thus they are important instruments for monitoring. Developing new indices that combine different variables is not a trivial task: variables may be qualitative, or measured in different units, and the relationship between primitive components and quality may be ambiguous. Fuzzy logic has been repeatedly proposed as an effective technique to cope with such problems; however, the variety of choices that exist at each stage of the development of fuzzy models may present a problem for the index designer. In this paper we present F-IND, a framework to create fuzzy indices by means of a simplified and intuitive procedure. It allows to capture the expert knowledge of the system under study (air, soil, water) to easily generate a multivariable index of environmental conditions. F-IND is implemented in Java, to achieve an optimal portability on any operating system.     

On-farm monitoring of economic and environmental performances of cropping systems: Results of a 2-year study at the field scale in northern Italy

Cropping systems in northern Italy are intensively managed, but an integrated environmental accounting of these systems has not been published yet. We conducted this study to evaluate cropping systems management in a study area in northern Italy using indicators. The study area is a regional agricultural Park, with cereal and livestock farms, cultivating mostly maize, rice, meadows, and winter cereals.To select the indicators, we identified for the study area the most relevant issues concerning the potential impact of agriculture on the environment: nutrient and pesticide management, use of fossil energy and soil management. Subsequently, we selected indicators from the literature, which could address these issues. We also added indicators describing the economic performance. The data were collected at the field level by periodic face-to-face interviews with seven farm managers over 2 years. Indicators were calculated for all crops cultivated in each field (n = 266).According to the methodology proposed, the best economic performance (gross margin) was obtained by rice, followed by maize, winter cereals, and forage crops. Nitrogen and phosphorus surpluses were high for maize (due to a large use of animal manures), and moderate for rice and permanent meadows (where mineral fertilisers are not usually applied). Maize used high fossil energy inputs; however, the output/input ratio (an indicator of the dependence of food and feed production on non-renewable energy) was elevated, due to high aboveground biomass production. The potential impact due to pesticide use (evaluated with indicators that consider the toxicity and the exposure to active ingredients) was relevant only for rice, moderate for maize and other cereals, and null for forages. Finally, soil management was evaluated for the 2-year crop succession on each field (n = 131): permanent meadows are excellent (due to continuous soil cover and large returns of organic carbon to soil), rice-based successions are unsatisfactory (due to low residues and manure application and continuous cropping), and maize successions are intermediate. This work shows that good quality data can be collected on-farm for economic and environmental accounting at field level. The indicators chosen for the analysis describe a range of issues in the study area, and make it possible to clearly separate and characterise different cropping systems. The procedure for their calculation is transparent and sound, and can be applied for ex-ante, ex-post, and monitoring procedures.