An interdisciplinary study on indicators: A comparative review of quality-of-life,macroeconomic, environmental,welfare and sustainability indicators

It is generally recognised that indicator-based research forms a substantial part both of the everyday practice and of the current theoretical pursuits in an extensive set of different scientific fields that relate to the socio-economic and the environmental sphere. However, the lack of an endogenous indicator's theory hinders the enhancement of indicator's research into an autonomous scientific field and subdues the indicators study to the broader ecological, social, or economic context. Thus, scientists are often bounded to the study of indicators within their specialisation area, as evidenced by the very limited number of interdisciplinary studies on the use of indicators that have been published. Based on this deficiency of the current literature, the paper elaborates on the use of indicators in the socio-economic and the environmental area, focusing on fields in which indicators are essential to their practice. Namely, the paper reviews quality-of-life, macroeconomic, environmental, welfare and sustainability indicators in order to detect similarities and differences, pertain to their practice and to the theoretical frameworks in which indicators are utilised. The study concludes that quality-of-life, welfare and sustainability indicators are supported by weak theoretical foundations, as a result to the choice of the respective fields to exploit the possible benefits of an empirical interdisciplinary perspective, a fact that leads the use of indicators to methodological inconsistencies. In contrast, macroeconomic and environmental indicators are supported by a coherent theoretical body, which is reflected in their well-organised structure and leads to their sound practice. Last but not least, the study suggests that the way the aforementioned two fields utilise indicators can provide useful guidance to the formation of future objectives in the quality-of-life, welfare and sustainability indicators’ research. Specifically, their corresponding fields should moderate their interest on composite indicators and, instead, their future research should be focused, so much on the identification of their field's key indicators that play a crucial role to the interpretation of the complex phenomena studied, as on the identification of the relationships that link these key indicators together.     

Conservation efforts based on local ecological knowledge: The role of social variables in identifying environmental indicators

The incorporation of local ecological knowledge in monitoring processes has been one of the great challenges of conservation initiatives worldwide. Therefore, it is essential to use indicators as local evaluation tools of the conditions of a species in order to support conservation actions. Local populations observe the environment, climate change and the influence of these factors on the species they use. However, their observations and perceptions may vary depending on different social factors. We used as model two species of economic importance involved in sociobiodiversity product chains to evaluate the role of social variables in the identification of conservation indicators for this plants. The species studied were: Caryocar coriaceum Wittm. (locally known as pequi), and Himatanthus drasticus (Mart.) Plumel (locally known as janaguba). We also registered which indicators are perceived as the most important and what they are measuring. Our results show that the knowledge among collectors is homogeneous and that, generally, the social factors do not affect the knowledge on local indicators. Age and extraction time were factors that influenced the knowledge on climate indicators and population structure only for C. coriaceum. In the communities studied, collectors not only monitor the biological characteristics of the species, but also the environmental and climatic phenomena that are threatening the sustainability of the species. These results can help to improve our ability to manage information about natural resources, incorporating local ecological knowledge in the scientific process of evaluation and monitoring of biodiversity.     

On the equivalence of case-crossover and time series methods in environmental epidemiology

The case-crossover design was introduced in epidemiology 15 years ago as a method for studying the effects of a risk factor on a health event using only cases. The idea is to compare a case's exposure immediately prior to or during the case-defining event with that same person's exposure at otherwise similar "reference" times. An alternative approach to the analysis of daily exposure and case-only data is time series analysis. Here, log-linear regression models express the expected total number of events on each day as a function of the exposure level and potential confounding variables. In time series analyses of air pollution, smooth functions of time and weather are the main confounders. Time series and case-crossover methods are often viewed as competing methods. In this paper, we show that case-crossover using conditional logistic regression is a special case of time series analysis when there is a common exposure such as in air pollution studies. This equivalence provides computational convenience for case-crossover analyses and a better understanding of time series models. Time series log-linear regression accounts for overdispersion of the Poisson variance, while case-crossover analyses typically do not. This equivalence also permits model checking for case-crossover data using standard log-linear model diagnostics.     

Sampling efficiency of the pale grass blue butterfly Zizeeria maha (Lepidoptera: Lycaenidae): A versatile indicator species for environmental risk assessment in Japan

The pale grass blue butterfly, Zizeeria maha (Lepidoptera, Lycaenidae), has successfully been employed as an indicator species to evaluate acute biological changes in polluted human-living environments after the Fukushima nuclear accident. Here, we quantitatively examined the field sampling efficiency of the butterfly and its associated sexual sampling bias under different conditions, which may provide important information for environmental risk assessment. Sampling data were obtained in 2014 and 2015 from 87 localities across Japan. Across the localities, the mean capture rate was 17 individuals per hour per person, and males represented approximately 80% of the collected butterflies. No significant difference was detected in the capture rate under different weather conditions. Among the four habitats, the riverside showed a significantly higher capture rate than the city park. A shorter sampling time tended to yield a higher capture rate. Comparisons among prefectures and districts of collection localities revealed that the Kanto district had significantly higher percentages of collected males than 4 other districts. Fukushima prefecture also had high percentage, although not significant. A generalized linear mixed model indicated that the capture rate was significantly negatively affected by the agricultural village, the city park, the rainy weather, and latitude and positively by longitude. Together, the present study showed high sampling efficiency and versatility of this butterfly as an indicator for environmental risk assessment but simultaneously suggested preferable conditions for a field sampling design. This study also suggested a possibility that the Fukushima nuclear accident or other factors might have affected behavioral or population dynamics of the butterfly.     

On the statistical analysis of vegetation change: a wetland affected by water extraction and soil acidification

Abstract. A case study is presented on the statistical analysis and interpretation of vegetation change in a wetland subjected to water extraction and acidification, without precise information on the environmental changes. The vegetation is a Junco-Molinion grassland and the changes in vegetation are evaluated on the basis of relevés in 1977 and 1988 of 20 plots in a small nature reserve on moist oligotrophic, Pleistocene sands in the Netherlands. The changes are attributed to water extraction (since 1972) and soil acidification and the effect of the environmental changes on the vegetation is inferred from data on water depth and acidity collected in 1988. Many species typical of wetlands decreased in abundance, including rare species such as Parnassia palustris, Selinum carvifolia and Ophioglossum vulgatum. Some species increased, notably Anthoxanthum odoratum, Holcus lanatus and Plantago lanceolata. A significant decrease was found in the mean Ellenberg indicator values for moisture and acidity. The mean indicator value for nutrients did not change significantly. Multivariate analysis of the species data by Redundancy Analysis demonstrated the overall significance of the change in species composition between 1977 and 1988 (P < 0.01, Monte Carlo permutation). The spatial and temporal variation in the species data was displayed in ordination diagrams and interpreted in terms of water depth and pH. A simple model is developed to infer the change in water depth and pH from the relevé data and recent data on water depth and pH. Because the correlation between water depth and pH made a joint estimation of the changes useless, the change in pH was estimated for a series of likely changes in water depth. For the most likely change in water depth, significant acidification was inferred from the change in vegetation. The model is more generally applicable as a constrained calibration method.     

Ground level environmental protein concentrations in various ecuadorian environments: Potential uses of aerosolized protein for ecological research

Large quantities of free protein in the environment and other bioaerosols are ubiquitous throughout terrestrial ground level environments and may be integrative indicators of ecosystem status. Samples of ground level bioaerosols were collected from various ecosystems throughout Ecuador, including pristine humid tropical forest (pristine), highly altered secondary humid tropical forest (highly altered), secondary transitional very humid forest (regrowth transitional), and suburban dry montane deforested (suburban deforested). The results explored the sensitivity of localized aerosol protein concentrations to spatial and temporal variations within ecosystems, and their value for assessing environmental change. Ecosystem specific variations in environmental protein concentrations were observed: pristine 0.32 ± 0.09 μg/m³, highly altered 0.07 ± 0.05 μg/m³, regrowth transitional 0.17 ± 0.06 μg/m³, and suburban deforested 0.09 ± 0.04 μg/m³. Additionally, comparisons of intra-environmental differences in seasonal/daily weather (dry season 0.08 ± 0.03 μg/m³ and wet season 0.10 ± 0.04 μg/m³), environmental fragmentation (buffered 0.19 ± 0.06 μg/m³ and edge 0.15 ± 0.06 μg/m³), and sampling height (ground level 0.32 ± 0.09 μg/m³ and 10 m 0.24 ± 0.04 μg/m³) demonstrated the sensitivity of protein concentrations to environmental conditions. Local protein concentrations in altered environments correlated well with satellite-based spectral indices describing vegetation productivity: normalized difference vegetation index (NDVI) (r² = 0.801), net primary production (NPP) (r² = 0.827), leaf area index (LAI) (r² = 0.410). Moreover, protein concentrations distinguished the pristine site, which was not differentiated in spectral indices, potentially due to spectral saturation typical of highly vegetated environments. Bioaerosol concentrations represent an inexpensive method to increase understanding of environmental changes, especially in densely vegetated ecosystems with high canopies or in areas needing high spatial and temporal resolution. Further research to expand understanding of the applicability of bioaerosol concentrations for environmental monitoring is supported by this pilot study.     

Testing environmental Kuznets curve hypothesis: The role of renewable and non-renewable energy consumption and trade in OECD countries

This paper investigates the causal relationships between per capita CO₂ emissions, gross domestic product (GDP), renewable and non-renewable energy consumption, and international trade for a panel of 25 OECD countries over the period 1980–2010. Short-run Granger causality tests show the existence of bidirectional causality between: renewable energy consumption and imports, renewable and non-renewable energy consumption, non-renewable energy and trade (exports or imports); and unidirectional causality running from: exports to renewable energy, trade to CO₂ emissions, output to renewable energy. There are also long-run bidirectional causalities between all our considered variables. Our long-run fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) estimates show that the inverted U-shaped environmental Kuznets curve (EKC) hypothesis is verified for this sample of OECD countries. They also show that increasing non-renewable energy increases CO₂ emissions. Interestingly, increasing trade or renewable energy reduces CO₂ emissions. According to these results, more trade and more use of renewable energy are efficient strategies to combat global warming in these countries.     

Benchmarking the environmental performance of specialized milk production systems: selection of a set of indicators

Dairy production across the world contributes to environmental impacts such as eutrophication, acidification, loss of biodiversity, and use of resources, such as land, fossil energy and water. Benchmarking the environmental performance of farms can help to reduce these environmental impacts and improve resource use efficiency. Indicators to quantify and benchmark environmental performances are generally derived from a nutrient balance (NB) or a life cycle assessment (LCA). An NB is relatively easy to quantify, whereas an LCA provides more detailed insight into the type of losses and associated environmental impacts. In this study, we explored correlations between NB and LCA indicators, in order to identify an effective set of indicators that can be used as a proxy for benchmarking the environmental performance of dairy farms. We selected 55 specialised dairy farms from western European countries and determined their environmental performance based on eight commonly used NB and LCA indicators from cradle-to-farm gate. Indicators included N surplus, P surplus, land use, fossil energy use, global warming potential (GWP), acidification potential (AP), freshwater eutrophication potential (FEP) and marine eutrophication potential (MEP) for 2010. All indicators are expressed per kg of fat-and-protein-corrected milk. Pearson and Spearman Rho’s correlation analyses were performed to determine the correlations between the indicators. Subsequently, multiple regression and canonical correlation analyses were performed to select the set of indicators to be used as a proxy. Results show that the set of selected indicator, including N surplus, P surplus, energy use and land use, is strongly correlated with the eliminated set of indicators, including FEP (r = 0.95), MEP (r = 0.91), GWP (r = 0. 83) and AP (r = 0.79). The canonical correlation between the two sets is high as well (r = 0.97). Therefore, N surplus, P surplus, energy use and land use can be used as a proxy to benchmark the environmental performance of dairy farms, also representing GWP, AP, FEP and MEP. The set of selected indicators can be monitored and collected in a time and cost-effective way, and can be interpreted easily by decision makers. Other important environmental impacts, such as biodiversity and water use, however, should not be overlooked.     

Macroinvertebrate indicators of lake acidification: analysis of monitoring data from UK, Norway and Sweden

Although the acid sensitivity of many invertebrate species in lakes is well known, methods for assessment of lake acidification based on macroinvertebrate samples are less developed than for rivers. This article analyses a number of existing metrics developed for assessment of river acidification, and evaluates their performance for assessment of lake acidification. Moreover, new species-based indicators of lake acidification were developed and tested. The selected dataset contains 668 samples on littoral macroinvertebrates from 427 lakes with almost 60% of the samples from Sweden and the rest from UK and Norway. Flexible, non-parametric regression models were used for explorative analyses of the pressure–response relationships. The metrics have been assessed according to their response to pH, the degree of non-linearity of the response and the influence of humic compounds. Acid-sensitive metrics often showed a threshold in response to pH between 5.8 and 6.5. Highly acid-tolerant metrics were typically dominant across the whole pH range. Humic level had a positive effect for most acid-sensitive metrics. Generally, most metrics showed a more non-linear response pattern for the humic lakes than for clear lakes. The significant relationship between these macroinvertebrate metrics and acidification shows that there is a potential for developing further the assessment systems for ecological quality of lakes based on these metrics, although the metrics explained a low % of the variation (<30%). In order to improve the predictive power of the biotic metrics across the acidified part of Europe, further harmonization and standardisation of sampling effort and taxa identification are needed.     

Habitat ecological integrity and environmental impact assessment of anthropic activities: A GIS-based fuzzy logic model for sites of high biodiversity conservation interest

In literature, an effective method enabling the classification, based on a single indicator, of habitats that need a priority protection intervention has not been identified yet. Moreover, the excessive number of landscape metrics, used to quantify integrity of habitats, can cause confusion, often providing redundant and inconsistent results.The aim of this work is to develop a method for evaluating the ecological vulnerability of the habitats in sites of high biodiversity conservation interest. In the first phase, we selected and analyzed, by using principal component analysis (PCA) and fuzzy logic, the landscape metrics, in order to obtain the map of the intrinsic ecological vulnerability index. In the second step, the result of this intrinsic vulnerability was connected, through another fuzzy model, to anthropogenic impacts, obtaining the integrated ecological vulnerability index. We developed specific spatial indicators (landscape metrics), which can examine the mutual position and morphology of the habitats present, along with indicators of human pressure, related to the type and intensity of use of the anthropic territory, with reference to the habitat itself as well as to the areas immediately adjacent. The developed fuzzy models are innovative, compared to the current ecological studies, and examine landscape metrics as well as the impact of human activities.The case study is the “Val Basento-Ferrandina Scalo” Site of Community Importance, Ferrandina-SCI (Basilicata Region, Southern Italy). The results allowed us to build a rank of the habitats based on their intrinsic and integrated ecological vulnerability. Moreover, the results show that, in the Ferrandina-SCI, the most important source of concern is not human activities, but rather the inherent risk of ecological fragility caused by geographical and landscape features of the different patches of habitats themselves.This model aims to be a tool for decision support in sustainable landscape management. It is easy to use and to apply on other regions, although it should always be accompanied by a sensitivity analysis to reduce the subjectivity.     

Bird sensitivity to disturbance as an indicator of forest patch conditions: An issue in environmental assessments

An Environmental Assessment (EA) is one of the steps within the Environmental Impact Assessment process. Birds are often used in EA to help decision makers evaluate potential human impacts from proposed development activities. A “sensitivity to human disturbance” index, created by Parker III et al. (1996) for all Neotropical species, is commonly considered an ecological indicator. However, this parameter was created subjectively and, for most species, there have been no rigorous field test to validate its effectiveness as such. Therefore, in this study, we aim to: (1) evaluate if, at the local scale, birds from forest patches in a human-modified landscape (HML) may differ in sensitivity from Parker's sensitivity classification; (2) evaluate the effectiveness of the species richness value at each sensitivity level as an ecological indicator; (3) gather information on how often and in which manner Parker's classification has been used in EA. To do so, bird sampling was performed in eight forest patches in a HML over one year. Then, we created a local sensitivity to disturbance using information about threat, endemism, spatial distribution and relative abundance of all species in the study area. We found that 37% of the forest birds showed different local sensitivity levels when compared with Parker's classification. Our results show that only the richness of high-sensitivity species from our local classification fitted the ecological indicator assumptions helping the environmental conditions evaluation of the studied patches. We conclude that species richness of each Parker's bird sensitivity levels do not necessarily perform as an ecological indicator at the local scale, and particularly in HML. Nevertheless, Parker's Neotropical bird sensitivity classification was used in 50% of EA we reviewed. In these, 76% assumed that it was an accurate ecological indicator of the local forest conditions for birds. The lack of clear criteria used in Parker's classification allows diverse interpretations by ornithologists, and there is no agreement about the ecological meaning of each sensitivity level and what environmental conditions each level may indicate of. Therefore, the use of Parker's classification in EA may jeopardize accurate interpretations of proposed anthropogenic impacts. Furthermore, because a bird species’ sensitivity often varies between locations, we argue that Parker's generalized classification of bird sensitivity should not be used as an indicator of forest environmental conditions in EA throughout HMLs in Neotropics. Rather, local bird ecological indices should be explored, otherwise, erroneous predictions of the anthropogenic impacts will continue to be common.     

Evaluation of window flight traps for effectiveness at monitoring dead wood-associated beetles: the effect of ethanol lure under contrasting environmental conditions

1 Subsequent to the diversity of saproxylic beetles being proposed as a management tool in forestry, more explicit knowledge about the efficiency and selective properties of beetle sampling methods is needed.
2 We compared saproxylic beetle assemblages caught by alcohol-baited or unbaited window traps in different forest contexts. Considering that trap attractiveness depends on kairomone concentrations, we appraised whether the trap efficiency was influenced by trap environment (openness and local supply of fresh dead wood).
3 Saproxylic beetles were sampled using 48 cross-vane window flight traps, arranged in paired designs (alcohol-baited/unbaited), in eight ancient and eight recent gaps (open stands), and eight closed-canopy control stands in an upland beech forest in the French Pyrenees.
4 Baited traps were more efficient than unbaited traps in terms of abundance and richness in our deciduous forests. The ethanol lure did not have any repellent effect on the individual response of saproxylic taxa.
5 The influence of local environmental conditions on trap attractiveness was observed. Openness had a significant moderate effect on species richness. Trap attractiveness was slightly reduced in the alcohol-saturated environment of recent gaps probably due to a disruption by local fresh dead-wood concentrations of the kairomonal response of saproxylic beetles to baited traps ('alcohol disruption').
6 Because the ethanol lure enhanced the probability of species detection, it may be useful in early-warning surveillance, monitoring and control of wood borers, despite slight influences of local conditions on baited trap efficiency.     

Relative importance of factors controlling the success of Oxalis acetosella: an example of linear modelling in ecological research

An ecological hypothesis concerning the relative importance of factors governing the success of Oxalis acetosella on mesic upland forest sites in southern Finland was formulated and tested statistically by means of a multivariate linear model. The data consisted of a stratified random sample of 40 plots with biological measurements and associated observations on environmental variables. The covariance matrix between the incorporated variables was computed and the model parameters were estimated using the method of maximum likelihood provided by the computer programme LISREL V. The results supported the hypothesis based on previous observations and experiments: Oxalis acetosella benefits from a high nutrient level of the soil, but is decisively dependent on the shelter provided by the tree stand. When both spruce stands and well-lit pine stands on mesic and relatively rich forest sites were considered simultaneously, only a weak correlation was found between light availability and site fertility. Accordingly, the presumed value of Oxalis acetosella as an indicator of site fertility appears to be questionable. The adequacy of linear modelling in an ecological context is discussed. The kind of models applied in this study have only a limited application range in non-experimental ecological research. However, linear modelling may contribute to solving particular ecological problems in cases where short environmental gradients are considered so that nonlinearity is not a dominant feature.     

Pattern Detection in Intensive Care Monitoring Time Series with Autoregressive Models: Influence of the Model Order

The detection of patterns in monitoring data of vital signs is of great importance for adequate bedside decision support in critical care. Currently used alarm systems, which are based on fixed thresholds and independency assumptions, are not satisfactory in clinical practice. Time series techniques such as AR‐models consider autocorrelations within the series, which can be used for pattern recognition in the data. For practical applications in intensive care the data analysis has to be automated. An important issue is the suitable choice of the model order which is difficult to accomplish online. In a comparative case‐study we analyzed 34564 univariate time series of hemodynamic variables in critically ill patients by autoregressive models of different orders and compared the results of pattern detection. AR(2)‐models seem to be most suitable for the detection of clinically relevant patterns, thus affirming that treating the data as independent leads to false alarms. Moreover, using AR(2)‐models affords only short estimation periods. These findings for pattern detection in intensive care data are of medical importance as they justify a preselection of a model order, easing further automated statistical online analysis.     

Validation of the detection of Pseudo-nitzschia spp. using specific RNA probes tested in a microarray format: Calibration of signal based on variability of RNA content with environmental conditions

Harmful algal blooms (HAB) occur worldwide and cause health problems and economic damage to fisheries and tourism. Monitoring for toxic algae is therefore essential but is based primarily on light microscopy, which is time consuming and can be limited by insufficient morphological characters such that more time is needed to examine critical features with electron microscopy. Monitoring with molecular tools is done in only a few places world-wide. EU FP7 MIDTAL (Microarray Detection of Toxic Algae) used SSU and LSU rRNA genes as targets on microarrays to identify toxic species. In order to comply with current monitoring requirements to report cell numbers as the relevant threshold measurement to trigger closure of fisheries, it was necessary to calibrate our microarray to convert the hybridisation signal obtained to cell numbers. Calibration curves for two species of Pseudo-nitzschia for use with the MIDTAL microarray are presented to obtain cell numbers following hybridisation. It complements work presented by Barra et al. (2012b. Environ. Sci. Pollut. Res. doi: 10.1007/s11356-012-1330-1v) for two other Pseudo-nitzschia spp., Dittami and Edvardsen (2012a. J. Phycol. 48, 1050) for Pseudochatonella, Blanco et al. (2013. Harmful Algae 24, 80) for Heterosigma, McCoy et al. (2013. FEMS. doi: 10.1111/1574-6941.12277) for Prymnesium spp., Karlodinium veneficum, and cf. Chatonella spp. and Taylor et al. (2014. Harmful Algae, in press) for Alexandrium.