Wild boar hair (Sus scrofa) as a non-invasive indicator of mercury pollution
Introduction
Rapid technological development and a consequent increase in the human impact on the environment have created a compelling need for the development of various pollution monitoring procedures. Both biological and non-biological techniques are available. Although biological methods have many potential advantages and are an important complement to chemical and physical methods, the choice of the proper indicative bio-derived material may be complicated and can be controversial.
Wild mammals are known to be convenient indicators of heavy metal pollution (Chyla, 1998, Chyla et al., 2000). By accumulating chemicals over many trophic levels, they provide an early warning of adverse toxic effects in whole ecosystems. They are relatively long-lived, integrating effects of environmental stress over a long period of time. Moreover, by sharing some physiological characteristics with human organisms, they may reflect the mechanisms by which pollution influences human health (Furness, 1993). To avoid the problems resulting from terminal sampling, which is required to obtain internal body organs for analysis, there is an increasing interest in the development of non-invasive methods in environmental monitoring (Fossi and Leonzio, 1994).
Although many authors have reported that human hair is a good non-invasive indicator of environmental pollution, there is very little reported work on the use of wild animal hair data for this purpose (Burger et al., 1994). The most controversial parts of the hair analysis process seem to be the various stages of sample preparation, especially washing procedures (Bencze, 1990).
Considering the origin of trace elements in hair, two main sources have to be distinguished: endogenous quantities of metals are those incorporated into the hair proteins during the short period of hair formation from the diet, while endogenous trace elements in the hair structure are assumed to be metabolically inert, irreversible or at least quite firm (Karz, 1988). Exogenous quantities are those attached by direct environmental contact after hair formation (Leotsinides and Kondakis, 1990).
Mercury occurs in the environment in several forms, each with a quite different biological impact. It accumulates in different animal tissues and organs, causing contamination along the food chain (Burger et al., 1994). The main anthropogenic sources of this element in the environment are coal combustion, municipal waste incineration, smelting of non-ferrous metals, the paper industry and agriculture.
Investigating the usefulness of wild boar (Sus scrofa) hair as a non-invasive indicator of mercury pollution, it was expected that the content of this element in hair could be affected by different factors, both biological (intrinsic) and behavioural (extrinsic), such as: age, gender, hair colour or habitat, which, if not taken into account, might drastically change the interpretation of data.
The aim of the present work was to investigate the multiplicity of different factor, that might significantly influence the nutritional status of the organisms and hair elemental composition. Metal distribution along hair was determined. The influence of physiological, ecological and environmental factors (age, gender, season, habitat and dietary status of sampled animals) was estimated and taken into account. The analysis of hair samples systematically taken from a living individual from a local Zoological Garden was performed to observe the seasonal changes in the content of metals in the wild boar hair.
Section snippets
Hair samples
Wild boar (S. scrofa) hair was collected in two hunting seasons (1998/1999 and 1999/2000) by local hunters. Samples were collected according to specially prepared instructions. The pinch of front dorsal hair cut nearest to the skin was cut into 2–3 mm parts by means of stainless-steel surgical scissors and homogenised carefully before washing. Additionally, the gender and age of animals were estimated.
Samples were obtained from four differently polluted regions of Poland: 17 individuals from
Results
The percentage content of mercury in wild boar hair (n=5) after different washing methods is presented in Fig. 1.
Additionally a high positive correlation between washed and unwashed hair from animals living in differently polluted regions (Fig. 2) was found. The correlation coefficient estimated between washed and unwashed wild boar hair is given by r=0.98.
The mercury content in wild boar hair in relation to habitat is presented in Fig. 3. In the present studies significantly increased levels
Washing procedures
In the present study, de-ionised water was found to be satisfactorily effective in the removal of exogenous mercury deposited on the hair surface. As a strong non-ionic detergent, Triton X-100 could remove the remaining mercury from laboratory vessels, increasing metal content in the analysed samples.
Moreover, irrespective of the washing agent, mercury was removed from analysed hair only to a small extent, which would suggest its endogenous origin in hair (Karz, 1988). This was confirmed by a
Conclusions
As a contaminant-monitoring tissue, hair has many potential advantages:
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It is a specimen easy to collect and analyse. De-ionised water appears to be a sufficient washing agent to remove external mercury contamination from the hair surface.
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Mercury concentration in wild boar hair is positively correlated with its internal body organ content and reflects heavy metal pollution in the surrounding environment.
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The highest mercury content was found in young individuals between 1 and 2 years of age. A
Acknowledgements
This study is a part of the PhD project entitled “Wild boar fur as non-destructive indicators of environmental pollution” performed and defended at the Wroclaw University of Technology in Poland. First of all, I am grateful to everyone who helped me with sample collection. I also thank Prof. I. Trzepierczynska, Prof. W. Żyrnicki, Dr. A. Chyla and Prof. K. Sawicka-Kapusta for consultation and professional advice as well as Lucy and Marek Szablewski for the language check up. Finally, I thank to
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