Application of indicator kriging to the complementary use of bioindicators at three trophic levels

Saponaria officinalis L. and Achillea millefolium L. as possible indicators of trace elements pollution caused by mining and metallurgical activities in Bor, Serbia

This study evaluates bioaccumulation and translocation potentials of trace elements (TEs) by Saponaria officinalis L. (soapwort) and Achillea millefolium L. (yarrow) in order to select and optimize phytoremediation methods for the polluted environment of the city of Bor, Serbia. According to the enrichment factor for soil (i.e., 57.9-128.8 for Cd and As), pollution index (i.e., 6.6-84.7 for Cu), pollution load index (2.9-98.8), individual potential risk factors (11.5-5163), and potential ecological risk index values (260-6379), urban and rural soils from the city of Bor were classified as very contaminated with the investigated TEs. The results from all the indices and statistical analysis showed significant ecological risks of Cu, As, and Cd at the investigated sites and urge the need for remediation. The enrichment factor of the plants for As (566.3) and Cd (306.2) indicated a high enrichment level of the herb organs at all the sites. Since there are small differences in metal accumulation index values between the herbs and their parts (root, shoot), soapwort and yarrow can be considered as potential bioindicators. Based on the biological concentration and translocation factors, soapwort can be recommended as a suitable herb for phytoextraction purposes of Pb, As, and Cd polluted areas. Yarrow shows good characteristics for phytoextraction of Cu, Pb, and As from the contaminated soil. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) results indicate their similar origin from atmospheric deposition. Therefore, these herbs can be utilized as a bioindicator and phytoremediator in polluted areas influenced by metallurgical activities to detect possible levels of TEs.

Metal concentrations in Hydrocynus vittatus (Castelnau 1861) populations from a premier conservation area: Relationships with environmental concentrations

Metals are known to have deleterious effects on aquatic ecosystems, so monitoring the bioaccumulation of these pollutants is important for the assessment of potential impacts. The aim of the study was therefore to determine the degree to which aquatic biota in selected rivers of the world renowned Kruger National Park (KNP) are exposed to metals entering from the catchments outside the KNP and to determine how these metal levels reflect what is occurring within the environment. Many of these rivers have never previously been assessed and those which have, have not been assessed within the past two decades. Tigerfish (Hydrocynus vittatus) is an economically important apex predator and was selected as the bioindicator for this study. Fish were sampled from the KNP sections of the Luvuvhu, Letaba and Olifants Rivers during the high and low flow periods from 2009 to 2011. The analysis of various metals from the aforementioned systems revealed spatial and temporal related variation in metal level patterns of the chosen bioindicator, with concentrations in fish from the Olifants River>Letaba River>Luvuvhu River and 2009>2010>2011. Although there were differences between rivers, metal concentrations were comparable and indicate that all of the studied KNP rivers, even those considered to be in a natural state are affected to some degree by anthropogenic activities. However, concentrations found during this study were much lower than previous studies in the area, as well as contaminated sites across the world, but were higher than concentrations in fish from contaminated sites in the Vaal River, South Africa. Bioaccumulated metals showed no correlation to metals in the water column, but some were correlated to sediment metal concentrations and the contamination and bioavailability of these metals within the sediments. This is of concern when managing the water resources of the conservation area since the contaminants enter the park from outside the borders and pose potential risks to the mandated conservation of aquatic biota within the KNP.

Evaluation of geostatistical estimators and their applicability to characterise the spatial patterns of recreational fishing catch rates

Western Australians are heavily engaged in recreational fishing activities with a participation rate of approximately 30%. An accurate estimation of the spatial distribution of recreational catch per unit effort (catch rates) is an integral component for monitoring fish population changes and to develop strategies for ecosystem-based marine management. Geostatistical techniques such as kriging can provide useful tools for characterising the spatial distributions of recreational catch rates. However, most recreational fishery data are highly skewed, zero-inflated and when expressed as ratios are impacted by the small number problem which can influence the estimates obtained from the traditional kriging. The applicability of ordinary, indicator and Poisson kriging to recreational catch rate data was evaluated for three aquatic species with different behaviours and distribution patterns. The prediction performance of each estimator was assessed based on cross-validation. For all three species, the accuracy plot of the indicator kriging (IK) showed a better agreement between expected and empirical proportions of catch rate data falling within probability intervals of increasing size, as measured by the goodness statistic. Also, indicator kriging was found to be better in predicting the latent catch rate for the three species compared to ordinary and Poisson kriging. For each species, the spatial maps from the three estimators displayed similar patterns but Poisson kriging produced smoother spatial distributions. We show that the IK estimator may be preferable for the spatial modelling of catch rate data exhibiting these characteristics, and has the best prediction performance regardless of the life history and distribution patterns of those three species.

Spatial modeling of factor analysis scores: the case of heavy metal biomonitoring in mainland Portugal

The use of mosses as biomonitors operates as an indicator of their concentration in the environment, becoming a methodology which provides a significant interpretation in terms of environmental quality. The different types of pollution are variables that can not be measured directly in the environment - latent variables. Therefore, we propose the use of factor analysis to estimate these variables in order to use them for spatial modelling. On the contrary, the main aim of the commonly used principal components analysis method is to explain the variability of observed variables and it does not permit to explicitly identify the different types of environmental contamination. We propose to model the concentration of each heavy metal as a linear combination of its main sources of pollution, similar to the case of multiple regression where these latent variables are identified as covariates, though these not being observed. Moreover, through the use of geostatistical methodologies, we suggest to obtain maps of predicted values for the different sources of pollution. With this, we summarize the information acquired from the concentration measurements of the various heavy metals, and make possible to easily determine the locations that suffer from a particular source of pollution.

Spatio-temporal patterns of Cu contamination in mosses using geostatistical estimation

Several recent studies have reported temporal trends in metal contamination in mosses, but such assessments did not evaluate uncertainty in temporal changes, therefore providing weak statistical support for time comparisons. Furthermore, levels of contaminants in the environment change in both space and time, requiring space-time modelling methods for map estimation. We propose an indicator of spatial and temporal variation based on space-time estimation by indicator kriging, where uncertainty at each location is estimated from the local distribution function, thereby calculating variability intervals for comparison between several biomonitoring dates. This approach was exemplified using copper concentrations in mosses from four Portuguese surveys (1992, 1997, 2002 and 2006). Using this approach, we identified a general decrease in copper contamination, but spatial patterns were not uniform, and from the uncertainty intervals, changes could not be considered significant in the majority of the study area.

Integration of biomonitoring and instrumental techniques to assess the air quality in an industrial area located in the coastal of central Asturias, Spain

Throughout the world, epidemiological studies were established to examine the relationship between air pollution and mortality rates and adverse respiratory health effects. However, despite the years of discussion the correlation between adverse health effects and atmospheric pollution remains controversial, partly because these studies are frequently restricted to small and well-monitored areas. Monitoring air pollution is complex due to the large spatial and temporal variations of pollution phenomena, the high costs of recording instruments, and the low sampling density of a purely instrumental approach. Therefore, together with the traditional instrumental monitoring, bioindication techniques allow for the mapping of pollution effects over wide areas with a high sampling density. In this study, instrumental and biomonitoring techniques were integrated to support an epidemiological study that will be developed in an industrial area located in Gijon in the coastal of central Asturias, Spain. Three main objectives were proposed to (i) analyze temporal patterns of PM₁₀ concentrations in order to apportion emissions sources, (ii) investigate spatial patterns of lichen conductivity to identify the impact of the studied industrial area in air quality, and (iii) establish relationships amongst lichen conductivity with some site-specific characteristics. Samples of the epiphytic lichen Parmelia sulcata were transplanted in a grid of 18 by 20 km with an industrial area in the center. Lichens were exposed for a 5-mo period starting in April 2010. After exposure, lichen samples were soaked in 18-MΩ water aimed at determination of water electrical conductivity and, consequently, lichen vitality and cell damage. A marked decreasing gradient of lichens conductivity relative to distance from the emitting sources was observed. Transplants from a sampling site proximal to the industrial area reached values 10-fold higher than levels far from it. This finding showed that lichens reacted physiologically in the polluted industrial area as evidenced by increased conductivity correlated to contamination level. The integration of temporal PM₁₀ measurements and analysis of wind direction corroborated the importance of this industrialized region for air quality measurements and identified the relevance of traffic for the urban area.