Journal of Threatened Taxa |
www.threatenedtaxa.org | 26 July 2020 | 12(10): 16377–16379
ISSN 0974-7907 (Online) | ISSN
0974-7893 (Print)
doi: https://doi.org/10.11609/jott.6225.12.10.16377-16379
#6225 | Received 26 May 2020 |
Finally accepted 15 July 2020
Tracing heavy metals in urban ecosystems through the
study of bat guano - a preliminary study from Kerala, India
Jithin Johnson 1 & Moncey
Vincent 2
1,2 Department of Zoology, Sacred
Heart College (Autonomous), Pandit Karuppan Road, Thevara, Kerala 682013, India.
1 jithinjohnson94@gmail.com
(corresponding author), 2 moncey.vincent@gmail.com
Editor: Paul Racey,
University of Exeter, UK. Date of publication: 26 July 2020
(online & print)
Citation: Johnson, J. & M. Vincent (2020). Tracing heavy metals in urban
ecosystems through the study of bat guano - a preliminary study from Kerala,
India. Journal of Threatened
Taxa 12(10): 16377–16379. https://doi.org/10.11609/jott.6225.12.10.16377-16379
Copyright: © Johnson &
Vincent 2020. Creative Commons Attribution 4.0 International License. JoTT allows
unrestricted use, reproduction, and distribution of this article in any medium
by providing adequate credit to the author(s) and the source of publication.
Funding: None.
Competing interests: The authors declare no
competing interests.
Acknowledgements: We thank the
principal S.H. College, Thevara for providing the
necessary laboratory facilities. We also
thank Dr. Anu Gopinath
& Ms. Greeshma, KUFOS, Mr. Jaison, CSIR-CECRI and
Dr. Adarsh & the Director, SAIF-STIC, CUSAT, for
the help rendered in the analysis of the samples. We are also indebted to Mr. Tijo K. Joy, Mr. Sreehari Raman
and Dr. A. Madhavan (Retd.), Bharata Mata College, Thrikkakara for identifying the bat species.
Heavy metal pollution has greatly increased the mobilisation of metals
in the air, water, and soil. Metals such
as arsenic, cadmium, chromium, copper, mercury, manganese, nickel, lead, and
tin are toxic at elevated levels and
some even at low concentrations. As
these elements do not decay with time, their emission to the environment is a
serious problem. Bio-indicator organisms
like small mammals, particularly bats allow detection of biological responses
and provide a tool in assessing the state of ecosystem health (Clark 1981). Insectivorous bats are considered to be the
best bio-indicators as they are exposed to contaminants more directly through
invertebrates that may consume soil (Ma & Talmage 2001). Being the only flying mammal, bats are
sensitive to a wide range of environmental stresses to which they respond in
predictable ways (Zukal et al. 2015) and
thus, are important keystone species in the ecosystem, having enormous
potential as biodiversity, ecological, and environmental indicators (Jones et
al. 2009). Their widespread distribution
and proximity to humans make them susceptible to contamination through
anthropogenic activities. The potential
of bats as bio-indicators of pollution is two-fold: Firstly, exposure to
contaminants, including heavy metals, contributes to the decrease in bat populations. Secondly, levels of the contaminants in bat
guano serve as an indicator of the prevalent pollution levels in the
surrounding environment. This study aims
to evaluate the pollution levels in two different environments using bats as
indicator organisms and it is hypothesized that urban areas would reveal
comparatively greater amounts of contaminants than rural areas.
Sampling was carried out in different sites from Ernakulam (Mangalavanam Bird Sanctuary and Tripunithura)
and Thrissur (Irinjalakuda) districts of Kerala. Fresh (whenever possible) and few-days-old
guano deposits of bats like Pteropus medius Temminck, 1825, Megaderma spasma (Linnaeus,
1758) and Taphozous melanopogon
Temminck, 1841 were collected by placing
nets fitted onto PVC frame of size 0.8 × 0.8 m on the floor of the bat’s
roosting site and left undisturbed for 4–6 days to allow for sufficient guano
deposition. For sample digestion, a
mixture of concentrated nitric acid and perchloric acid (5:1 ratio) was added
to 0.5g of dry guano in a Borosil glass beaker; the
beaker kept in a heating mantle at 90oC for 1–2 h or until digestion
was complete. After cooling, the sample
was diluted to 20ml using distilled water, the contents filtered and
transferred to clean Borosil glass vials and then
stored at room temperature prior to analysis.
Analysis of the metals was done using the Inductively Coupled Plasma
Atomic Emission Spectroscopy (ICP-AES) facility at the Kerala University of
Fisheries and Ocean Studies, Panangad. Mercury (Hg)
analysis was performed using direct Hg analyser at the Sophisticated Test and
Instrumentation Centre, Cochin University of Science and Technology
(CUSAT). Elemental compositions of dry
homogenised samples were determined by X-ray fluorescence (XRF) analyser at the
CSIR-Central Electrochemical Research Institute, Karaikudi.
Statistical analyses was done using the software package PAST v 3.18 and graphs
were made using MS Excel.
It has been known that the composition of elements in bat guano normally
equals that in the undigested portion of the ingested food, and as such may
provide some clues to the location of contaminants in the environment (Martin
1992). Factors such as the bats’ diet,
roosting location, foraging habitat, and metabolism may significantly influence
accumulation. It seems likely,
therefore, that heavy metal exposure pathways differ between frugivorous and
insectivorous bat species.
Contamination in fruit bats is likely to be through atmospheric
pollution, contact with contaminated foliage whilst searching for and eating
food, which may be later ingested directly while grooming. Insectivorous bat species become contaminated
mainly through bio-accumulation through the food-chain, i.e., from
water/soil/sediments/plants or other sources to insects and finally to the bats
themselves. The additional routes of
exposure to heavy metals may include contact with skin and inhalation (Allinson et al. 2006).
Usually, upon oral ingestion, about 5–10% of the metal gets absorbed and
about 99.5% of total ingested metal is excreted through faeces/guano thus
leaving only 0.5% to be deposited in various body tissues (Klaassen
1976). Table 1 represents the general
composition of elements detected by the XRF analyser in the bat guano used for
the study.
Guano analysis indicated the presence of heavy metals such as mercury
(Hg) and various other metals in varying concentrations. The concentration of metals like lead,
cadmium and zinc, however, were below detection limits. Figure 1 represents the concentration of Hg
obtained from the direct Hg analyser and Table 2
represent the concentrations of the metals (Chromium, Copper, Manganese and
Nickel) obtained using the ICP-AES analyser.
In our study, the concentration of
mercury varied between the bats from the urban areas of Ernakulam and the rural
areas of Irinjalakuda (Thrissur), with higher
contamination levels in the Ernakulam District.
The composition of guano also
varied between the insectivorous and frugivorous bats and this was indicated by
the presence of the elements Aluminium (Al) and Titanium (Ti)
in insectivorous bat guano. It was also
noted that the levels of Copper (Cu),
Chromium (Cr), Manganese (Mn), and Nickel (Ni) were significantly different
between the insectivores from Ernakulam and those from Irinjalakuda. This may be probably due to the elevated
pollution levels in Ernakulam. Further studies are needed to determine if these values are
representative of the bat colonies from Kerala, to pinpoint the sources of
contamination, and to determine if these levels of contamination adversely
affect bats.
Variability in the levels of metals found in bat bodies is influenced by
their background environmental levels, which in turn reflects the amounts
accumulated. Metals may interfere with
the normal functioning of the immune system, cause physiological and
histological distress and thus, increase the prevalence of parasites or
wildlife infectious diseases (Hernout et al.
2016). Environmental pollution and
contamination, in turn, can cause population declines in bats. Assessments of these contaminants thus, help
us to understand the levels that would harm humans.
As far as we are aware, there are no other time-trend data for heavy
metals in bats in Kerala, and so it is impossible to assess whether the trend
in the studied bats is typical for other bat species. Ecotoxicological data are essential for risk
assessment and decision-making in bat conservation. Data from this study provides information on
baseline levels of interest to monitor status and trends in the heavy metal
residue in the bats of the study areas, and therefore, they represent a tool to
evaluate potential wildlife, ecological, and human health exposure. Such an evaluation of the contaminant load
through guano analysis sheds light on the potential use of guano as a simple,
relatively inexpensive and non-invasive bio-indicator tool to assess the
prevalent pollution levels and thus, the environmental quality. The relationship between levels of heavy metals
in bat guano, prey analysis, and the various components of the environment in
which the insects develop, should also prove to be a fruitful area for future
research.
Table 1. Elemental composition of guano from different bats.
Element |
Avg. mass (%) (n=4) |
|||
T. melanopogon |
M. spasma |
P. medius (1) |
P. medius (2) |
|
Aluminium (Al) |
4.6105 |
5.5846 |
BDL |
BDL |
Calcium (Ca) |
10.7272 |
17.0122 |
21.221 |
21.1739 |
Copper (Cu) |
BDL |
0.4237 |
1.3149 |
0.1164 |
Iron (Fe) |
42.8869 |
15.2537 |
4.1669 |
6.8953 |
Potassium (K) |
BDL |
3.1887 |
35.3471 |
36.4112 |
Molybdenum (Mo) |
0.0001 |
0.0002 |
0.0003 |
0.0002 |
Oxygen (O) |
34.7198 |
39.3272 |
27.7743 |
27.3338 |
Silicon (Si) |
6.7776 |
16.8635 |
8.335 |
7.2244 |
Titanium (Ti) |
0.278 |
1.1079 |
BDL |
BDL |
Zinc (Zn) |
BDL |
1.2382 |
1.8369 |
0.5562 |
BDL →Below detection limit ≈ 0 |
||||
(1)→ Irinjalakuda, Thrissur; (2) → Ernakulam |
Table 2. Comparison of metal concentrations (mg/kg wet weight) in the
guano of insectivorous bats from Ernakulam and Thrissur (mean ± standard
deviation [n=12]).
Metals |
Cr |
Cu |
Mn |
Ni |
Ernakulam |
79.69 ± 35.56 |
3973.68 ± 418.38 |
820.12 ± 464.26 |
60.03 ± 22.23 |
Thrissur |
24.93 ± 10.56 |
2869.22 ± 503.13 |
76.92 ± 38.62 |
24.61 ± 16.68 |
p-value |
0.016 |
0.057 |
0.016 |
0.033 |
p-values were calculated at 95% confidence using Mann-Whitney U test |
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