Effect of air pollution on biodiversity of coastal lichens

Extended Essay
Research Question: What effect has the development of Castle Peak Power
Station had on the percentage cover and biodiversity of coastal lichens in Lung Kwu
Tan, Hong Kong ?
Subject: Biology
Candidate Name: Anahita Sharma
Number: 003258-138
Exam Session: May 2012
Word Count: 3950

Abstract
This essay examines the impact of the 1981 commissioning of the coastal Castle
Peak Power Station on a 1980 established zone of normal lichen growth. The research
question is ‘What effect has the development of Castle Peak Power Station had on the
percentage cover and biodiversity of coastal lichens in Lung Kwu Tan, Hong Kong ?
Site A is a rocky outcrop 200 metres downwind, whereas Site B is 1.6 kilometres
upwind, from the power station; Site A is therefore significantly more exposed to by-
products produced as a result of the station’s activities. Any impact on coastal lichen
growth produced by the station would be suggested by differences between these sites,
thirty years later.
Lichens readily absorb pollutants that may damage the algae-fungi symbiosis. The
investigation was approached with three indicators of health within the lichen
community: population size, type of lichen, and biodiversity. The lichen was classified
in the field, the population size determined by percentage covers over randomly selected
quadrats, and the biodiversity a combination of the former dependent variables. The
scope was limited to coastal species found on granitic rock within the supra-littoral zone
(approximately 3.68 m above chart datum) between two independent sites under similar
abiotic conditions. Representative results could be achieved by selecting more sites
under uniform conditions. The research was also limited by a dearth of historical data
with which to compare.
The results supported the hypothesis: there was a greater Simpson’s biodiversity
level (4.48 compared to 3.45) and overall percentage cover of species at Site B. At site
B, four out of six species common to both sites were found to be more frequently found
and at a significantly (at a minimum confidence limit of 95%) higher percentage cover
than at Site A. This baseline study indeed prompts further investigation.
Word Count: 299
ii

Contents
1. Introduction
• ! 1.1 Hypotheses and Justification................................................................ p. 1
• 1.2 Lichen Biology..................................................................................... p. 3
• ! 1.3 Coastal Ecology and Site Significance................................................. p. 5
2. Methodology
• ! 2.1 Apparatus................................................................................................ p. 8
• ! 2.2 Methodology........................................................................................... p. 9
• 2.3 Spatial Site Observations........................................................................ p. 10
• 2.4 Abiotic Factors........................................................................................ p. 11
3. Treatment
• ! 3.1 Presence................................................................................................. p. 12
• 3.2 Transformation...................................................................................... p. 12
• 3.3 Statistical Significance: Independent samples t-test.............................. p. 14
• 3.4 Biodiversity............................................................................................ p. 16
• 3.5 Data Presentation................................................................................... p. 17
4. Discussion
• 4.1 Conclusion.............................................................................................. p. 18
• 4.2 Evaluation and further areas of study..................................................... p. 19
5. Works Cited................................................................................ p. 21
A. Appendix
• A1: Raw data........................................................................................................................... p. 22
• A2: Photographs of sites.......................................................................................................... p. 25
• A3: Quadrat size determination data........................................................................................ p. 26
• A4: Lichen species found......................................................................................................... p. 27
iii

Introduction
Research Question:
What effect has the development of Castle Peak Power Station had on the percentage cover and
biodiversity of coastal lichens in Lung Kwu Tan, Hong Kong ?
1.1 Hypotheses and Justification
Whilst making field observations, I considered whether the environmental impact of Hong Kong’s
largest coal-fired power stations (Castle Peak 1981) and its adjacent industrial establishments could be
biologically assessed.
Because the Castle Peak establishments are directly situated on the coast, coastal
lichens growing in the supra-littoral zone of the rocky shore were used as
‘bioindicators’. Lichens growing on substrate further inland would not have been
representative of the effect of Castle Peak.
Lichens are free and simple mechanisms for assessing the air pollution levels of a
potentially large source. I was interested and passionated about this subject because
air pollution is a relevant, daily point of conflict in Hong Kong. The CLP group
which partly owns the power stations, lists (gaseous) waste by-products of coal as
an energy source (fig. 1.1.1), many of which are known to affect lichens. In
addition, there have been few studies on lichens in Hong Kong; this investigation
builds upon S.L. Thrower’s work in 1979, when Hong Kong was mapped using
indicator lichen genera in terms of pollution zones.
fig. 1.1.1 waste by-products of coal energy source (source: CLP Group)
Lichens have been successfully used in other studies, for example, the works Hawksworth & Rose,
to assess air pollution and other factors. Fig 1.1.2 shows a covariation between lichen biodiversity and lung
cancer mortality. There is a strong case between air pollution and (human or ecological) health, because our
noses are not equipped to filter particles less than 10 micrometers (e.g. non-particulate gases including SO2
which causes both lung irritation in humans and chlorophyll damage in the photosynthetic component of
lichens).
fig. 1.1.2! map showing relationship
between lichen biodiversity and health:
lung cancer mortality
(higher the diversity value, lower the
mortality rate) (Purvis 101)
What effect has the development Castle Peak Power Station had on the percentage cover and biodiversity of coastal lichens in Lung Kwu Tan, Hong
Kong ? 1 Introduction
1
Anahita Sharma 003258-138

‘Bioindication’ is the use of an organism to obtain information on the quality of its environment (Purvis
76). Coastal lichens are good bioindicators because of their perennial, cumulative exposure to a moist
environment. Their metabolic rate increases under hydrated conditions, and the aqueous solubility of many
pollutants in means that these lichens can become ‘sinks’ for pollutants (e.g. SO2) even when metabolically
inactive (Nash 299). In addition, “where pollution levels are increasing lichen response is usually rapid, but
when these arez ameliorating... a time-lag does indeed occur.” (Hawksworth and Hill 135). As lichens solely
rely on atmospheric intake, growth is slow, and this means that if retrofitting to reduce emissions was
successful in 2005, the effect of the potentially higher air quality may not be entirely reflected through
present data collection. To rectify this, an idea is gleaned between comparisons of two sites.
From ‘Quantitative Approaches to Air Quality Studies’ (Will-Wolf 109), “species presence and cover
are the most important measures for lichen community data”.
My study followed: “Plan to collect samples both where air pollution is or is expected to be present and
where it is absent but all else is the same... If no historical records are available for the area being studied,
comparisons must be made with nearby comparable areas that are either presumed or known to be free
of air pollution”. The nature of this investigation means that some - fair - assumptions are made; this is
indeed a limitation of bioindication.
This baseline study examines differences between lichen coverage and biodiversity over the scope of
two sites. I hypothesize that species that would have survived would have disappeared from the substrate in
Site A. Site A is a displacement of 0.2 km from the stations, whereas Site B is 1.6 km away. (for Site and
Castle Peak photographs, refer to A1 (Appendix).
The uniformity of the substrate and abiotic conditions justified the choice of the rocky shore sites, which
primarily different in their situation with respects to the power stations.
This formed the hypotheses (height justified in 1.3):
H1 (Alternative Hypothesis): Site A has a lower lichen percentage cover at 3.68 ± 0.01 m above chart
datum and/or a lower biodiversity value than Site B.
H0 (Null Hypothesis): There is no significant difference in lichen percentage covers and/or biodiversity of
lichen between the rocky shore sites at 3.68 ± 0.01 m above chart datum.
This study records the percentage cover of all species found, because different species have different
pollution sensitivities. Sensitivity is influenced by ‘tolerance’ or ‘avoidance’. An example of ‘avoidance’ is
‘limited wettability’, which means the lichen decreases its porosity (Hawksworth and Hill 131).
Within lichens, a greater biodiversity suggests ecological health in that several species are able to
compete in the environment. Biodiversity is calculated by combining both the percentage cover and number
of species (species richness). A low biodiversity suggests a dominance of a few, possibly pollution-tolerant
species. The type of lichen (Section 1.2) is very significant, because, in general, “the more the lichen sticks
out from its substrate, the purer the air” (Thrower 5, 1979).
2

! Variables
fig 1.1.5: table showing variables used to test hypothesis
Dependent The location: rocky shore sites determined by the distance and predominant
wind direction from Castle Peak “a” Power Station.
Site A: 0.2 km downwind, Site B: 1.6 km upwind ± 0.05 km
The location: rocky shore sites determined by the distance and predominant
wind direction from Castle Peak “a” Power Station.
Site A: 0.2 km downwind, Site B: 1.6 km upwind ± 0.05 km
Controlled variables Independent Species and percentage cover per quadrat (± standard
deviation of species over 60 quadrats)
Controlled variables
Fixed Abiotic conditions such as rock type, shore height, aspect:
however, biological variation is appreciated and monitored.
Uncontrolled variables An uncontrolled variable that may have a significant effect on the dependent
variable is marine pollution - as lichens are also sensitive to marine effluents -
which may affect Site B differently from Site A. This is, if not controlled,
monitored.
An uncontrolled variable that may have a significant effect on the dependent
variable is marine pollution - as lichens are also sensitive to marine effluents -
which may affect Site B differently from Site A. This is, if not controlled,
monitored.
1.2 Lichen Biology
A lichen is “an association of a fungus and a photosynthetic symbiont resulting in a stable thallus
(body)” (Hawksworth and Hill 2). The algal complex is the photobiont (autotrophic/photosynthetic partner).
The mycobiont (fungi) has hyphae (cellular threads) adheres to hard, desiccated substrata, protecting the
photobiont against exposure and water loss and liberalizing minerals through the biochemical weathering of
substrate. This is mutualistic: for the mycobiont, lichenization is a form of heterotrophic nutrition; the
photobiont’s access to light increases (Nash 3).
Colonies organise themselves in degrees of increasing complexity: crustose, squamulose (scaly),
foliose (leafy) and fructicose (bushy). An accepted rule of thumb is the more complex the structure, the
greater its sensitivity to atmospheric pollutants. This reinforces the significance of not only the number,
but the type of lichen found at each site i.e. a large number of fructicose or foliose lichens would signify
good air quality.
fig 1.2.1 cross-section of lichen (Thrower 1979)
Crustose lichens (fig 1.1.1) are thin, granular, smooth or powdery crusts.
3
Algal cells caught in fungal
weft (mycelium).
Lower fungal cortex (coat)

fig 1.2.2 diagram of foliose structure (Dobson 26)
Squamulose or foliose lichens (fig 1.2.2) constitute flat ‘lobes’ or layers of tissue. Rhizines, “root-like
threads” (Thrower 1988), anchor the thallus.
fig 1.2.3 cross-section of fructicose lichen (Dobson 26)
Fructicose lichens are thread-like, stalk-like or bushy, with a central cylinder of hyphae (fig 1.2.3).
As lichens contain no vascular system, they have “developed efficient mechanisms for taking up water
and nutrients from atmospheric sources” (Nash 299). Because they lack a cuticle or stomata, aerosols are
absorbed over the thallus and there is little control over gas exchange. Once absorbed, the substance is
metabolised or bioaccumulated - this characteristic is normally advantageous on barren surfaces but in the
presence of polluted air, has become a threat to lichens (Thrower 4, 1988). They cannot regenerate existing
parts. Because lichens are poikilohydric - their “water status varies passively with surrounding
environmental conditions” (Nash 5) - their biomass directly varies with mean annual precipitations.
Recurring dehydration concentrates solutions to toxic levels which diffuse down to the photobiont layer in
the medulla, potentially rupturing the delicate symbiotic balance.
These substances irreversibly damage lichen metabolism via the photobiont as shown through
fumigation studies: “changes in respiration rates, increases in potassium efflux... chlorophyll
degradation” (Fields 175). They may inhibit photosynthetic fixation and the development of fruiting bodies
or spores for germination. The photobiont diverts energy to repair itself; the mycobiont which relies on it as a
source of nutrition is affected. Coastal lichens are additionally susceptible to marine oils, emulsifiers and
detergents.
4

1.3 Coastal Ecology and Site Significance
Coastal lichens are least affected by Hong Kong’s development and hill-fires and can effectively represent air
quality levels. This study focuses on lichens colonizing granitic outcrops or boulders in Lung Kwu Tan,
where I noticed there was a power station in close proximity to the shore.
fig 1.3.1! subdivisions of rocky shore profile
Rocky shores experience a steep environmental gradient (fig 1.3.1). Species that can “withstand extended
periods out of water” (Williams 2003) are distributed up shore in the splash or supra-littoral zone (Williams
2003). This presents advantages such as decreased interspecific competition and wave action.
After site visits it was notable that the lichens occur in a band higher up shore (approximately 3.00-4.00 m),
whereas the more frequently submerged parts of the shore were covered by cyanobacterial mats and
(seasonal) encrusting or erect algal species. Two fructicose species, Roccella sinensis and Ramalina litoralis,
occur almost exclusively in this habitat (Thrower 1988).
Lung Kwu Tan (Tuen Mun, Hong Kong)
A report by S.L. Thrower on the results of the ‘Clean Air and Lichens’ Project in 1979 that assessed lichen
growth in terms of pollution zones indicates that Lung Kwu Tan fell into a zone of ‘Normal Growth’ for
foliose and fructicose species. Such a categorization suggested a maximum of 50 micrograms per m3 of SO2
concentration; the upper annual average limit for the station is now 80 micrograms per m3 (Castle Peak
5
Supra-littoral
lichens

Power Station EPD Air Pollution Assessment). However, mean levels as low as 30 micrograms per m3 have
affected lichen species in the field (Hawksworth & Hill 131).
This baseline study explores whether the commission of the coal-fired Castle Peak Power stations - the
largest in Hong Kong at a gross capacity of 4108 MW (CLP) - and adjacent industrial activities in 1982 - had
any effect on lichen growth after Thrower’s report, by examining the difference in percentage cover and
biodiversity of two shores that are impacted very differently by such a development, but are otherwise
similar in terms of aspect, shore exposure, substrate and
other biotic and abiotic conditions.
fig.1.3.3! map from
‘Report on Clean Air and
Lichens
Fig 1.3.3 marks Thrower’s pollution zones in Hong
Kong in 1979; lichen deserts were associated with the
presence of power stations, industrial areas, or
desalting plants. As lichens grow at an average of
between 0.1 and 1 cm in radius annually (Jennings
132), prolonged exposure to high degrees of both
terrestrial and marine pollution would certainly affect the biodiversity of lichens on the shore, rate of new
growth, and their thallus size (the latter two affecting percentage cover).
fig 1.3.4 map of Sites
GPS Coordinates
Site A: N 22.378791 E 113.917893
Site B: N 22.391284 E 113.918024
The prevailing southern wind direction
indicates that effluents produced by
Castle Peak Power Station will not
directly affect Site B upwind, whereas
they will affect Site A, downwind.
This may not affect lichen growth or biodiversity if levels of of certain pollutants are not beyond a tolerable
limit. ‘Pollution’ encompasses a wide number of variables.
The combustion of fossil fuels results in the additional output of pollutants (fig 1.3.6), ultimately “[racing]
the energy cycles of nature” (fig 1.3.5) (Singer 105).
6
Lung Kwu Tan :
zone of normal growth for
fructicose and foliose
species in 1979

fig 1.3.5! the energy cycle of a power station
The proximity from the coal-fired power stations is associated
with impact. I hypothesize that this affects lichen abundance and
biodiversity in the supra-littoral zone on rocky shores in Lung
Kwu Tan.
The Power Station Environmental Impact Report rated the
intertidal habit of ‘Low’ ecological importance, of no
conservational interest. Lichens were not featured. The
introduction of low sulfur fuels and retrofits has purportedly
reduced NOx and SO2 emissions by 77% and 44% respectively, but these levels still affect lichen
communities (as aforementioned).
As lichen distribution is not affected on a short-term, daily basis, they can be used to study a long-term
impact. If the CLP initiatives to were effective, the lichen population abundance and diversity on Site B
should not significantly differ from Site A. Either was equally possible.
Word Count: 1580
7

2! Methodology
2.1 Apparatus
fig 2.1.1 table showing list of equipment needed
If uncertainties are not sourced, they are derived from the greatest unit of precision.
Apparatus/materials Quantity Purpose Uncertainty
Gridded Quadrat (0.5 m
by 0.5 m)*
1 To determine the percentage cover of a lichen
species within the area of the quadrat.
1 square represents
1% as the square is
divided 10 by 10.
Transect line (m) 1 To lay over the representative shore. ± 0.01 m
Magnifying glass 1 Aid lichen identification. -
Lichen books - Aid lichen identification. -
Metre ruler (m) 3 Determine tidal height (from chart datum) with
spirit levels and predicted tidal chart.
± 0.001 m
Spirit level 3 To avoid parallax error when measuring height. -
Predicted tide level chart
(Hong Kong Observatory)
1 To show tidal height at time of collection and
measure specific height
-
GPS-enabled device 1 Site location. Accuracy ± 10 yds
Camera 1 To record appearance of lichen if unidentified. -
Random numbers table 1 To ensure quadrat positions are randomly selected
from transect.
-
Ballantine Scale table 1 To ensure sites are of similar wave exposure
through this biological (zonation) scale.
-
*QUADRAT SIZE DETERMINATION
A gridded quadrat efficiently enables percentage cover calculation in the field. This size was reinforced by a
quick running means test on percentage cover. From fig 2.1.2, we can see that it is a suitable size as the curve
levels out and a 0.2500 m2 is representative of lichen communities.
fig 2.1.2! determination of quadrat size: graph
For data, refer to A2 (Appendix).
Kong ? 2 Methodology
8
0
25
50
75
100
0.0025 0.0625 0.2500
Percentage cover (%)
Quadrat Area (m2)

2.2 Methodology
SAMPLING
Random positions along the transect were selected from a random numbers table. A sample size of sixty
quadrats was representative, as it covered 50% of the zone along the quadrat.
TIDAL HEIGHT DETERMINATION
The tidal height is determined because, from prior research and site observations, coastal lichens are
distributed over the supra-littoral zone (i.e. at higher shore heights) and are rarely submerged.
fig 2.2.1! diagram showing how tidal height is measured
The spirit levels were
used to put three straight
rulers (fig 2.2.1) to
measure the height
difference from a pre-
determined tide level (fig
2.2.2).
fig 2.2.2! tidal chart (HKO)
ERROR ANALYSIS: The tidal chart
used was a prediction of the tide on the
day, so will have been inaccurate. I do not
think this caused significant error.
SPECIES IDENTIFICATION: To be ecologically sensitive, I visually identified lichens in the field with a
magnifying glass.
ERROR ANALYSIS: This choice to not chemically test lichen may have resulted in misidentification. To
minimize this, I researched the identified species’ habitat.
QUADRAT RULES
The quadrat was pressed against the vertical/horizontal/diagonal rock surface above and below the transect
line, with the bottom-left and top-left corner respectively touching the value on the line.
ERROR ANALYSIS: The substrate may not necessarily be flat where the quadrat is laid, and there may be
parallax error when counting.
9

fig 2.2.3! sketch of gridded quadrat on lichenous surface
Each square counted as 1% for an individual species. It was possible that
the coverage of species added up to more than 100% when more than one
was present within the same square.
LIMITATION: I rejected the possibility of measuring the thallus size of
each species due to impracticality. The limitation is that it is possible a
large thallus could be more relevant than, say, number of small thalli, and it
may not be fair to collectively consider them under ‘percentage cover’.
ERROR ANALYSIS: The method for percentage cover was not highly precise but provided an accurate
estimate. Sampling sixty quadrats increased the reliability of the data.
METHOD
1. Roughly estimate 3.700 m above chart datum by using the method shown in figures 2.2.1-2.
1. Lay a transect approximately 60.00 metres long.
3. Using the random numbers table, find positions for the 0.5 m by 0.5 m quadrat along the transect. If the
random number does not fall on a position where the quadrat can be laid against a rocky, granite substrate,
then move on to the next random number. If the position yields sampling possibilities on both sides of the
transect line, sample on both sides.
4. Identify any species seen in the quadrat and write it in the ‘Species’ column. Calculate the percentage
cover as shown by the method in fig 2.2.3. Place the quadrat both below and above the transect line.
5. Repeat steps 3-4 with the next position. If new species are identified, add them to the ‘Species’ column
and write in their percentage cover. Species should be subsequently marked as 0% if they are found not to
be present within the quadrat.
6. Repeat this method for 60 quadrats. 50% of the lichen population along the 60.00-metre transect at 3.700
m tidal height will have been sampled, increasing reliability.
2.3 Spatial Site Observations
- Site photographs can be found in A2 of the Appendix.
A village lies at the back of the bay whereas directly behind the beach. The
power stations lie to the left of the bay, at an approximately 1.6 kilometre
displacement away from Site B and 0.2 kilometre displacement from Site
A. They were seen from both Sites A and B. A white gas, possibly steam, was
seen; at Site A, there was a pungent odour, possibly liquid natural gas.
10
fig 2.3.1 satellite map

From fig 2.3.2, it is evident that pollutants generated
by the stations affect lichens at Site B to a far lesser
extent when compared to the
lichens at Site A.
From the Environmental
Impact Assessment of the
Emissions Control Project of
Castle Peak Power Station
(2006):
a) Effluents are discharged into coastal waters and the
site receives weekly traffic.
b) Lung Kwu Upper (Site B) is rated as a ‘Fair’ beach
whereas Lung Kwu Lower (Site A) is ‘poor’.
2.4 Abiotic Factors
Whether the rock is a xeric (dry), mesic (moist) or submesic habitat, light intensity, the sheltering of other
rocks and crevices also determine distribution across the tidal height. Whilst it is difficult to isolate Castle
Peak Power Station impact as the sole variable, we can monitor and attempt to control certain variables.
Tidal Height: a supra-littoral height of 3.700 m was found appropriate for lichen growth. Deviation from
this height was a half-metre below and above (quadrat method); Chu (1997) showed that in Hong Kong,
lichen cover and diversity increase with tidal height; the zone is characterized by the genera Blastenia,
Caloplaca, Buellia, Parmotrema, Ramalina and Roccella (all of these found in data collection).
Substrate: granite boulders were present in both sites; numerous species of lichens readily grow on this
substrate.
Shore Exposure: Chu showed that exposure influences the height and vertical width of the supralittoral
zone. Similarity was achieved through the use of the Ballantine Scale, which uses zonation patterns.
Aspect: A bearing of NW 340-350°; the direction the shores face is important in terms of wind and sunlight
exposure. Chu (1997) showed the effect of aspect relates to prevailing winds; lichen diversity and cover is
higher on south- or east-facing shores due to a milder climate.
Water Pollution: Oils, emulsifiers and marine effluents may affect coastal lichens. However, marine data
provided by the EPD for factors in the area seems to suggest that there are no significant variations over the
area (NM5 Zone) as per 2009 data which provides values for factors such as dissolved oxygen, suspended
solids, ammonia, nitrogen, phosphates; this makes Site A and B still comparable.
If the Power Station were to release marine pollutants, the would affect downwind Site A over Site B; the
hypothesis is still supported. Water samples were not taken as both sites occupied the same bay, in which
variations would almost certainly be affected by time rather than location; marine data was available.
Word Count: 960
Raw, including qualitative, data and lichen species found are in the Appendix (A1 and A4 respectively).
11
Lung Kwu Tan
(it can be seen that
the arrows are
pointing in a south-
westerly direction, at
Tuen Mun and Sha
Chau, and South East
at the Wetland Park)
fig 2.3.2 map with prevailing wind direction

3 Treatment
The raw data (quantitative and qualitative) are found in Section A1, and the species list in A4
of the Appendix.
3.1 Presence
This compares what species are present at both Site A and B, leading into the statistical signiﬁcance test. The
percentage of quadrats each species is found in at Site A or B is expressed in brackets, to aid comparison.
Worked example: % of quadrats D. actinostomus is found in at Site A
ﬁg 3.1.1 table showing species present at Site A and B
Species Site A Site B
B. handelii Present (8.3%) Not present (0.0%)
B. cif. subdisciformis Present (50.0%) Present (23.3%)
C. cinnabarina Present (20.0%) Present (58.3%)
D. actinostomus Present (26.7%) Present (83.3%)
D. picta Not present (0.0%) Present (1.7%)
P. incratassum Present (10.0%) Present (53.3%)
P. cocoes Present (8.3%) Present (13.3%)
R. litoralis Present (8.3%) Not present (0.0%)
R. sinensis Present (5.0%) Not present (0.0%)
Verrucaria Present (43.3%) Present (65.0%)
The species present at both sites are in bold.
3.2 Transformation
Percentage cover is a nominal variable, because it represents the nominal, dual variable of ‘presence’ and
‘non-presence’ within a quadrat, not a measurement variable, which could, for example, be the thallus
diameter. Nominal variables are summarized as proportions or percentages; the latter is the case here.
My data, therefore, do not conform to a normal distribution. They must be transformed before the t-test
which assumes a normal distribution.
I have chosen to use an Arc Sine transformation, which is used with percentage data obtained from a count;
percentage data has imposed limits (0 to 100). My data also conform to its conditions: the values lie,
heterogeneously, close to both limits. The arcsin transformation compresses data toward a centre.
Formula and Worked example:
! ! ! where x is the percentage cover; if x = 7:
Kong ? 3 Treatment
12

I will convert this value (in degrees) to radians to compress all the values to one end of the range (0):
ﬁg 3.2.1: Processed data table showing lichen species common to both Site A and B percentage covers
transformed to arcsin values (in radians) in all 60 quadrats
Species /
Type
Site Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)Percentage cover after arcsin transformation (radians / 2 s.f.)
Diploschistes
actinostomus
Crustose
Site A
0.41 0.0 0.10 0.0 0.40 0.0 0.0 0.35 0.0 0.0 0.0 0.0 0.0 0.0 0.45 0.0 0.23 0.0 0.0 0.0
Diploschistes
actinostomus
Crustose
Site A 0.0 0.40 0.49 0.27 0.20 0.0 0.34 0.0 0.20 0.0 0.0 0.0 0.00.
0
0.0 0.0 0.0 0.0 0.0 0.0 0.0Diploschistes
actinostomus
Crustose
Site A
0.31 0.0 0.0 0.0 0.0 0.0 0.27 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.20 0.0 0.0 0.34 0.0 0.0
Diploschistes
actinostomus
Crustose Site B
0.0 0.0 0.0 0.20 0.0 0.290.32 0.0 0.340.800.450.50 0.0 0.290.290.44 0.0 0.250.400.17
Diploschistes
actinostomus
Crustose Site B 0.94 0.35 0.45 0.610.290.320.49 0.0 0.440.670.340.290.410.350.611.140.340.270.200.20
Diploschistes
actinostomus
Crustose Site B
0.73 0.62 0.31 0.0 0.410.320.230.710.600.170.140.200.430.510.140.310.41 0.0 0.400.25
Parmotrema
incratassum
Foliose
Site A
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Parmotrema
incratassum
Foliose
Site A 0.0 0.20 0.0 0.20 0.14 0.0 0.10 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0Parmotrema
incratassum
Foliose
Site A
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.32 0.10 0.0 0.0 0.0 0.0 0.0
Parmotrema
incratassum
Foliose Site B
0.0 0.14 1.6 0.0 0.0 0.0 0.0 0.230.20 0.0 0.0 0.0 0.0 0.0 0.430.72 0.0 0.350.80 1.1
Parmotrema
incratassum
Foliose Site B 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.560.380.170.170.170.27 0.0 0.0 0.65 1.6
Parmotrema
incratassum
Foliose Site B
0.14 0.35 0.31 0.0 0.14 0.0 0.0 0.0 0.0 0.250.320.450.140.490.440.600.730.670.730.66
Verrucaria
Crustose
Site A
0.79 0.57 0.49 0.41 1.25 0.0 0.48 0.0 0.0 0.0 0.0 0.17 0.10 0.0 0.0 0.0 0.0 0.0 0.37 0.0
Verrucaria
Crustose
Site A 0.27 0.0 0.0 0.51 0.0 0.0 0.46 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.25 0.0 0.0 0.50Verrucaria
Crustose
Site A
0.61 1.6 0.0 0.34 0.46 0.49 0.00.
0
0.37 0.45 0.49 0.0 0.32 0.14 0.37 0.0 0.35 0.0 0.0 0.0 0.0
Verrucaria
Crustose
Site B
0.0 0.37 0.0 0.0 0.320.59 0.0 0.0 0.0 0.0 0.0 0.44 0.0 0.410.730.520.480.550.460.92
Verrucaria
Crustose
Site B 0.41 0.29 0.25 0.32 0.0 0.0 0.0 0.0 0.0 0.0 0.640.29 1.1 0.27 0.0 0.40 0.0 0.230.350.67
Verrucaria
Crustose
Site B
0.69 0.73 0 0.570.690.270.27 0.0 0.0 0.490.560.580.490.450.650.37 0.0 0.630.660.50
Caloplaca
cinnabarina
Crustose
Site A
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Caloplaca
cinnabarina
Crustose
Site A 0.65 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0Caloplaca
cinnabarina
Crustose
Site A
0.0 0.0 0.0 0.0 0.0 0.56 0.91 0.65 0.71 0.20 0.27 0.34 0.0 0.51 0.25 0.34 0.20 0.0 0.0 0.0
Caloplaca
cinnabarina
Crustose
Site B
0.31 0.0 0.10 0.0 0.10 0.0 0.14 0.0 0.380.460.340.550.290.140.17 0.0 0.290.440.450.62
Caloplaca
cinnabarina
Crustose
Site B 0.0 0.27 0.27 0.250.710.500.460.71 0.0 0.0 0.0 0.320.140.46 0.0 0.0 0.0 0.0 0.270.10
Caloplaca
cinnabarina
Crustose
Site B
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.10 0.0 0.0 0.0 0.170.200.140.350.29 0.0 0.0 0.310.10
Pyxine
cocoes
Foliose
Site A
0.0 0.0 0.10 0.0 0.0 0.0 0.25 0.17 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Pyxine
cocoes
Foliose
Site A 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.45 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0Pyxine
cocoes
Foliose
Site A
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Pyxine
cocoes
Foliose Site B
0.23 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Pyxine
cocoes
Foliose Site B 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.140.340.170.140.820.140.17 0.0 0.0 0.0 0.0
Pyxine
cocoes
Foliose Site B
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Buellia cif.
subdisciformis
Crustose
Site A
0.49 0.69 0.34 0.44 0.32 0.79 0.64 0.25 0.14 0.58 0.31 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Buellia cif.
subdisciformis
Crustose
Site A 1.5 0.92 0.66 1.3 1.6 1.4 1.3 0.10 0.61 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0Buellia cif.
subdisciformis
Crustose
Site A
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.37 0.69 0.73 0.20 0.20 0.10 0.23 0.20 0.20 0.27 0.0 0.0 0.0
Buellia cif.
subdisciformis
Crustose Site B
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.31 0.0 0.290.31 0.0 0.200.17 0.0
Buellia cif.
subdisciformis
Crustose Site B 0.14 0.89 0.0 0.0 0.100.46 0.0 0.0 0.77 0.0 0.0 0.0 0.0 0.59 0.0 0.0 0.20 0.0 0.0 0.0
Buellia cif.
subdisciformis
Crustose Site B
0.0 0.0 0.0 0.80 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.45 0.0
Kong ? 3 Treatment
13

3.3 Statistical significance: Independent Samples t-test
For species that were found in both Site A and B, a Student’s unpaired t-test is carried out to determine
whether the differences between the mean percentage cover of each population are statistically significant.
This test calculates a critical value (t) that is then compared to a ‘critical value’. If t is below the critical
value, there is no significant difference and the null hypothesis is supported. A t-test was used instead of the
Mann Whitney U test (which may also have been used) in the view that it is more rigorous.
The formula for the t-value is:
This test can only be carried out to compare a species that is present in both Site A and B.
Worked example: D. actinostomus at both Site A and B
1) Calculate the mean percentage cover of the species for each site.
The formula for the mean is:
Where is the mean, is the sum of the percentage covers, and the no. of samples (60).
This is the mean percentage cover. This is the value after transformations, but transforming it back it not
necessary. We are interested in only the final t value after inputting the transformed data.
Kong ? 3 Treatment
14

2) Calculate the standard deviation (s) of the percentage cover of the species for each site.
68% of the data falls within ±1 standard deviation of the mean; it represents the spread of the majority of the
data about the mean. The formula is:
The numerator is the sum of the difference of every value from the mean; this is squared to make it positive
and then divided by the (approximate) number of samples to get the average difference from the mean. It is
then square rooted to cancel out the former function.
The standard deviation is relatively large in comparison with the mean; this wide variation in the percentage
cover of a species over a transect is to be expected because of environmental discrepancies within a uniform
environment.
3) Substitute the above calculations into the formula for the t-value.
ﬁg 3.3.1 table showing t-values and means for species at both Site A and B
Species Site A: Mean Site B: Mean t
B. cif. subdisciformis 0.2928 0.0947 3.2
C. cinnabarina 0.0932 0.1817 2.3
D. actinostomus 0.1475 0.2426 7.0
P. incratassum 0.0177 0.2660 5.1
P. cocoes 0.0162 0.0358 1.1
Verrucaria 0.2067 0.3268 2.2
The site with the higher mean is in red, and the lower in blue, for this is relevant. The means presented are
still in their transformed states.
Kong ? 3 Treatment
15

The critical values (at 2 degrees of freedom) are 1.3 at a 90% confidence limit, 1.7 at 95%, 2.0 at 97.5%,
2.4 at 99%, 2.7 at 99.5%, 3.2 at 99.9% (“Upper Critical Values of the Student’s t-distribution”). The
confidence limit is the probability that the result is not due to ‘chance’ because the probability of exceeding
the critical value is low.
Therefore,
The population of B. cif. subdisciformis is greater at Site A than B at a confidence level of about 99.9%.
The population of C. cinnabarina is greater at Site B than A at a confidence level of 97.5-99%.
The population of D. actinostomus is significantly greater at Site B than A at a confidence level of over
99.9%.
The population of P. incratassum is greater at Site B than A at a confidence level of over 99.9%.
The population difference of P. cocoes is not statistically significant.
The population of Verrucaria is greater at Site B than A at a confidence level of 97.5-99%.
3.4 Biodiversity
The Simpson’s Biodiversity Index (D) is not entirely based on species richness - the number of different
organisms present - but also the proportion of each species in the area.
The formula is as follows:
Where N is the gross number of individuals and n the no. individuals within a species.
In order to represent the biodiversity of an entire site, I will add up all the percentage cover values of a
species. 1% represents 1 individual in this sense, in order to help our calculations. The absolute values do not
matter here, only the values of Site A and B in relation to each other.
Worked example:
Site B is shown to have a higher biodiversity value than Site A.
Kong ? 3 Treatment
16

3.5 Data Presentation
ﬁg 3.5.1 bar graph showing average percentage covers of lichen species common to Site A and B
(± standard deviation)
The error bars extended into the negative portion of the y-axis, but since the percentage cover cannot be a
negative value, this has been omitted. They were derived from the standard deviation; this showed how
lichen species greatly varied in their distribution over the transect. The bar chart shows that for ﬁve species
out of six, Site B has a greater mean percentage cover.
Kong ? 3 Treatment
17

4 Discussion
H1: Site A has a lower lichen percentage cover at 3.68 ± 0.01 m above chart datum and/or a lower
biodiversity value than Site B.
4.1! Conclusion
As this is firmly a baseline study, I cannot make causative conclusions from the results.
However, the results show value in further investigation. The quantitative data show that four out of
species common to both sides were statistically and significantly found more frequently and at
higher percentage covers at Site B. B. cif. subdisciformis is the exception.
Although Site A had a higher species richness at 9 different species to Site B’s 7 species, Site B
had a higher (Simpson’s) biodiversity value. This is attributed to the difference in percentage
covers: in 5 out of 9 species at Site A, 10.0% or less of the sampled quadrats contained the species.
In terms of form, the only fructicose (bushy) species - R. sinensis and R. litoralis were found at Site
A - but both of these were found in only 8.3% (5 out of 60) and 5.0% (3 out of 60) quadrats
respectively. They were dry and appeared discoloured as specimens, but their structure was
maintained well enough on the rocky substrate to permit identification. Foliose species were found
at both sites, which indicated, at least, a moderate air quality in general over both sites.
Thrower (1979) established indicator genera, which she categorized into Zones 1-6, 1 being most
polluted and 6 least. No lichens found fell into Zone 6. In Site A, a small sample of Ramalina,
which is in Zone 5, was found, but not to a significant extent. Pyxine, a Zone 2 lichen (most tolerant
of SO2) was found in both Sites A and B, but rarely or occasionally respectively. Parmotrema
indicates Zone 5; at Site B, it was in 53.3% of quadrats whilst only 10.0% at Site A; this is a clear
distinction. Dirinaria, a Zone 4 lichen, is not present at Site A and was only found in one quadrat at
Site B. The alga Protococcus which indicates Zone 1 (a lichen desert) was not found. Data were
unavailable for the other lichens. On the whole, the significantly greater population density of
lichens at Site B signifies a potential relationship (although abiotic differences are still a limitation).
Another factor to be considered is the lag time between the point of contact with the pollution and
when this affects the structure of the lichen.
Castle Peak Power Station’s environmental performance has improved:
- July, 1993: EPD suspects Castle Peak Power Station is partially to blame for spikes in sulphur dioxide and
nitrogen oxide levels, which are linked to respiratory disease and “reduced lung functions”. (Finlay SCMP)
- January, 1997: In 1996, all conventional burners were fit with low NOx burners to reduce NOx emissions by
50%. (Watkins SCMP)
- November, 1998: Coal imports are reduced. CLP is trying to buy coal with minimum sulphur content.
(Tang SCMP)
Kong ? 4 Discussion
18

- November, 2003: Greenpeace claims power generation is responsible for 64% of Hong Kong’s CO2
emissions; CLP Power supplies 80% of power. CLP claims that ‘fuel diversification’ has reduced CO2
emissions by 25% and levels of sulphur dioxide and NOx by 80%. (Gentle SCMP)
- March, 2011: Hong Kong is on the path to reaching or surpassing air pollution-cutting targets because of
retrofitting Castle Peak Power Station with emission control devices. (Cheung SCMP)
It is possible, therefore, that lichen growth may have regenerated or improved with
performance.
The qualitative data show that many species were found together, perhaps because they
coexist within the same niche. They will of course, affect each other’s percentage covers, because
they indirectly compete for the ideal substrate.
The qualitative data also showed few observable differences between Site A and B: both
consisted of large, granitic outcrops, the same type of sand, were exposed to the same exposure and
seawater, the only difference being their locations at opposite ends of a large bay. Their suitability
for comparison was reinstated during data collection.
Looking at Thrower’s results on air and lichens in 1979, Lung Kwu Tan fell under Pollution
zone number 6: Bushy lichens such as Usnea appear, which has an approximate SO2 concentration
of < 35 micrograms/m3.
My results for Site A, however, fall under Zone number 4 where the scaly crusts prevail and
Zone 5 for Site B where the leafy lichens begin to appear. This suggests that the introduction of a
pollution source had an effect on the type of growth.
Ultimately, Site A and B certainly showed significant differences in lichen abundance, which
supported the initial hypothesis and the value of further study to ascertain these differences, for
they cannot be isolated to the Power Station (although it presents a strong case). In future, it would
be necessary to quantitative differences between the sites in terms of pollutants rather than base the
study on a locational assumption.
4.2! Evaluation and extensions
There was certainly great variability in the percentage cover of a species over the transect as
indicated by the relatively very high standard deviations around every mean percentage cover. This
can only be explained by the changes in abiotic conditions: whilst the supra-littoral lichens share the
same band and generally homogeneous, terrestrial conditions, each species will have its own
realized niche within the potentiality of conditions along the transect. The transect was a straight
displacement across the shore and therefore across rocks that were exposed to slightly different
conditions: some were closer to shore, some were further away. To improve this, the transect could
be laid across a series of conditions that are perceivably uniform. As the quadrat positioning was
Kong ? 4 Discussion
19

randomized, I wonder if it would be more useful to use a belt transect along which one could
accurately track any variability in conditions.
One factor that was not directly measured was the individual thallus size. Thalli in crutose
lichens up to 25 cm across are approximately 500 years old (Thrower 1997). This was associated
with percentage cover but in many cases smaller thalli over an area generated similar percentages to
larger thalli over the same area. The age of the lichen is also relevant.
However, the results are replicable because of a standardized method. There were a few
systematic issues: the laying of the quadrat against the rock was occasionally on an uneven surface
and the counting was therefore affected by parallax error. At some random numbers, there was no
rock. Part of my method was the condition of there being the substrate before a measurement could
be taken, and although this cannot be truly changed, it introduces a selective bias. When the quadrat
fell upon a rocky surface containing a crevice, any lichens growing within the crevice could not be
counted. The figures may therefore not be an accurate representation of lichen population, though
one could argue that lichens growing within sheltered zones do not reflect the impact of pollution.
One great shortcoming of this study is the fact that sample size only consisted of two sites.
Comparing more than two sites over an even greater range of pollution would be preferable.
Possibilities for future studies could also include the biomonitoring of lichen growth over a larger
period of time: the use of photographic evidence has been shown to yield results. However, in
general, it is difficult to generalise given an inability to truly control living organisms and varying
environmental conditions.
There were also limitations to the sources of information: Thrower’s 1979 report was based
on a survey carried out by groups of high school students, and therefore the data is not necessarily
standardized nor accurate, nor was there specific information on species’ sensitivity. This research
makes presumptions on the relationship between lichens and pollution and relies on much
secondary data that may not definitely hold true in this context, although there is much evidence to
support that it does. The arbitrary scale constructed to categorize lichens into ‘Rare’, ‘Occasional’,
etc. categories introduced a bias. The lack of similar historical data against which I can compare
against is another shortcoming.
In conclusion, however, the hypothesis (H1) was supported by the data yielded by this
method, and there was certainly a significant difference between the communities two sites likely
affected by the industrial site, although it has improved its environmental performance in recent
years.
Word Count: 1345
Kong ? 4 Discussion
20

Acknowledgments
I would like to give due thanks to my Dad, who drove me out far and spent many long days in the humid and heat of
Hong Kong helping me collect the data. Only he would do that for me. And my supervisor, Mr Ferguson, as well as the
librarians Mrs Ow and Ms Wong.
Works Cited
"1.3.6.7.2. Upper Critical Values of the Student's-t Distribution." Web. 28 Aug. 2011. <http://itl.nist.gov/div898/handbook/eda/
section3/eda3672.htm>.
Bennett, Donald Peter., and David A. Humphries. Introduction to Field Biology. London: Edward Arnold, 1974. Print.
"Biodiversity Measures Explained." Raytheon Wildlife Habitat Committee - Wildlife Management. Web. 28 Aug. 2011. <http://
rewhc.org/biomeasures.shtml>.
Cadogan, Alan, and Gerry Best. Environment & Ecology. Glasgow: Nelson Blackie, 1993. Print.
Chapman, J. L., and Michael J. Reiss. Ecology: Principles and Applications. Cambridge: Cambridge UP, 1992. Print.
"CLP Hong Kong - Castle Peak Power Station." CLP Power Hong Kong - Powering Hong Kong Responsibly. 2010. Web. 24 Aug.
2011. <https://www.clp.com.hk/ouroperations/power/castlepeakpowerstation/Pages/castlepeakpowerstation.aspx>.
Dobson, Frank S. Lichens: an Illustrated Guide to the British and Irish Species. Slough: Richmond, 2005. Print.
Ellis, Christopher J. "Scotland's Lichen Diversity." Diss. Royal Botanic Garden Edinburgh, 2006. Web. 24 Aug. 2011.
<http://rbg-web2.rbge.org.uk/lichen/scottish%20lichen%20biodiversity/scotland's%20lichens.pdf>.
Environmental Protection Department. "Emissions Control Project at Castle Peak Power Station “B” Units ENVIRONMENTAL
IMPACT ASSESSMENT." EPD Environmental Impact Assessment. Government of Hong Kong, 2006. Web. 2 Oct. 2011. <http://
www.epd.gov.hk/eia/register/report/eiareport/eia_1232006/HTML/Main/Contents.htm>.
"European Guideline for Mapping Lichen Diversity as an Indicator of Environmental Stress." Web. <www.thebls.org.uk/content/
documents/eumap.pdf>.
Fung, Joanna Chu. Ecology of Supralittoral Lichens on Hong Kong Rocky Shores. Hong Kong: Hong Kong UP, 1997. Print.
Hawksworth, D. L., and David J. Hill. "1.2: Definining Lichen, 1.9: Air Pollution." The Lichen-forming Fungi. Glasgow: Blackie,
1984. Print.
Hawksworth, D. L., and Francis Rose. Lichens as Pollution Monitors. London: Edward Arnold, 1976. Print.
"Human Energy Production as a Process in the Biosphere by S. Fred Singer." The Biosphere. San Francisco: W. H. Freeman, 1970.
Print.
Jennings, Terry J. Collecting from Nature. Exeter: Wheaton, 1971. Print.
Lepp, Heino. "Pollution and Lichens." Australian National Botanic Gardens - Botanical Web Portal. 7 Mar. 2011. Web. 24 Aug.
2011. <http://www.anbg.gov.au/lichen/ecology-polution.html>.
Marine Department. "EPD Marine Report 2009 (English Version)." EPD. The Government of Hong Kong, 2009. Web. 2 Oct. 2011.
<http://www.epd.gov.hk/epd/english/environmentinhk/water/marine_quality/files/Marinereport2009Engv1.pdf>.
Nash, Thomas H., and Volkmar Wirth. "Physiological Responses of Lichens to Air Pollution Fumigations (Rebecca F. Fields)."
Lichens, Bryophytes, and Air Quality. Berlin: J. Cramer, 1988. Print.
Nash, Thomas H. Lichen Biology. Cambridge: Cambridge UP, 1996. Print.
Purvis, William. Lichens. Washington, DC: Smithsonian Institution, 2000. Print.
Sprent, Janet I. The Ecology of the Nitrogen Cycle. Cambridge [Cambridgeshire: Cambridge UP, 1987. 71. Print.
Thrower, S. L. Clean Air and Lichen Project. Hong Kong: Hong Kong UP, 1979. Print.
Thrower, S. L. Hong Kong Lichens. Hong Kong: Urban Council, 1988. Print.
Williams, Gray A., and Kevin J. Caley. Rocky Shores. Hong Kong: Department of Ecology & Biodiversity, The University of Hong
Kong, 2003. Print.
Kong ?
21

A1 Raw Data
For lichen identification sheet, refer to A4 (Appendix).
3.1 Quantitative Data
fig 3.1.1: Raw data table showing lichen species percentage cover at SITE A
Species / Type Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)Percentage cover (± 1%)
Diploschistes
actinostomus
Crustose
16 0 1 0 23 0 0 12 0 0 0 0 0 0 19 0 5 0 0 0Diploschistes
actinostomus
Crustose
0 15 22 7 4 0 11 0 4 0 0 0 0 0 0 0 0 0 0 0
Diploschistes
actinostomus
Crustose 9 0 0 0 0 0 7 0 0 0 0 0 0 0 4 0 0 11 0 0
Parmotrema
incratassum
Foliose
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Parmotrema
incratassum
Foliose
0 4 0 4 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
Parmotrema
incratassum
Foliose 0 0 0 0 0 0 0 0 0 0 0 0 0 10 1 0 0 0 0 0
Caloplaca
cinnabarina
Crustose
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Caloplaca
cinnabarina
Crustose
37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Caloplaca
cinnabarina
Crustose 0 0 0 0 0 28 62 37 42 4 7 11 0 24 6 11 4 0 0 0
Pyxine cocoes
Foliose
0 0 1 0 0 0 6 3 0 0 0 0 0 0 0 0 0 0 0 0Pyxine cocoes
Foliose 0 0 0 0 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0 0
Pyxine cocoes
Foliose
0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0
Verrucaria
Crustose
50 29 22 16 90 0 21 0 0 0 0 3 1 0 0 0 0 0 13 0Verrucaria
Crustose 7 0 0 24 0 0 20 0 0 0 0 0 0 0 0 0 6 0 0 23
Verrucaria
Crustose
33 100 0 11 20 22 0 13 19 22 0 10 2 13 0 12 0 0 0 0
Buellia cif.
subdisciformis
Crustose
22 41 11 18 10 50 36 6 2 30 9 0 0 0 0 0 0 0 0 0Buellia cif.
subdisciformis
Crustose
99 63 38 95 100 98 90 1 33 0 0 0 0 0 0 0 0 0 0 0
Buellia cif.
subdisciformis
Crustose 0 0 0 0 0 0 0 13 41 45 4 4 1 5 4 4 7 0 0 0
Blastenia handelii
Crustose
0 0 0 0 0 4 3 0 0 0 0 0 0 0 0 0 0 0 0 0Blastenia handelii
Crustose 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Blastenia handelii
Crustose
0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 82 0 0 0 0
Roccella sinensis
Fructicose
0 0 0 0 0 28 3 16 0 0 0 0 0 0 0 0 0 0 0 0Roccella sinensis
Fructicose 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Roccella sinensis
Fructicose
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Ramalina litoralis
Fructicose
0 0 0 0 0 0 0 0 0 0 0 0 9 8 0 0 0 0 0 0Ramalina litoralis
Fructicose 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Ramalina litoralis
Fructicose
0 0 0 0 0 0 2 2 1 0 0 0 0 0 0 0 0 0 0 0
fig 3.1.2: Raw data table showing lichen species percentage cover at SITE B
Species Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)Percentage cover (±1 %)
Diploschistes
actinostomus
Crustose
0 0 0 4 0 8 10 0 11 48 19 23 0 8 8 18 0 6 15 3Diploschistes
actinostomus
Crustose
65 12 19 33 8 10 22 0 18 39 11 8 16 12 33 83 11 7 4 4
Diploschistes
actinostomus
Crustose 45 34 9 0 16 10 5 42 32 3 2 4 17 24 2 9 16 0 15 6
Parmotrema
incratassum
Foliose
0 2 100 0 0 0 0 5 4 0 0 0 0 0 17 43 0 12 52 75Parmotrema
incratassum
Foliose
0 0 0 0 0 0 0 0 0 0 28 14 3 3 3 7 0 0 37 100
Parmotrema
incratassum
Foliose 2 12 9 0 2 0 0 0 0 6 10 19 2 22 18 32 44 39 44 38
Caloplaca
cinnabarina
Crustose
9 0 1 0 1 0 2 0 14 20 11 27 8 2 3 0 8 18 19 34Caloplaca
cinnabarina
Crustose
0 7 7 6 42 23 20 42 0 0 0 10 2 20 0 0 0 0 7 1
Caloplaca
cinnabarina
Crustose 0 0 0 0 0 0 0 1 0 0 0 3 4 2 12 8 0 0 9 1
Pyxine cocoes
Foliose
5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Pyxine cocoes
Foliose 0 0 0 0 0 0 0 0 0 2 11 3 2 53 2 3 0 0 0 0
Pyxine cocoes
Foliose
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Verrucaria
Crustose
0 13 0 0 10 31 0 0 0 0 0 18 0 16 44 25 21 27 20 63Verrucaria
Crustose 16 8 6 10 0 0 0 0 0 0 36 8 78 7 0 15 0 5 12 39
Verrucaria
Crustose
41 44 0 29 41 7 7 0 0 22 28 30 22 19 37 13 0 35 38 23
Buellia cif.
subdisciformis
Crustose
0 0 0 0 0 0 0 0 0 0 0 0 9 0 8 9 0 4 3 0Buellia cif.
subdisciformis
Crustose
2 60 0 0 1 20 0 0 49 0 0 0 0 31 0 0 4 0 0 0
Buellia cif.
subdisciformis
Crustose 0 0 0 51 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 0
Dirinaria picta
Squalumose
0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0Dirinaria picta
Squalumose 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Dirinaria picta
Squalumose
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Kong ? A Appendix
22

3.2 Qualitative Data
fig 3.2.1! Table showing qualitative data for Site A
GPS Coordinates N 22.37891 E 113.917893
General aspect of shore NW 350°
Changes over transect At one particular height, deep crevices and shaded areas as well as exposed
and sunny areas are covered.
Observed water traffic of time Occasional boats, freighters
Water appearance Grey-green colour
Ballantine scale rating 5 - Fairly sheltered
Very little wave action, appears to be directed away from sea, island across
breaks fetch
Geographical features Trees are densely growing directly behind Site.
Nearest beach is of white-yellow sand, but sand colour turns black and soft
at Site A (like at Site B)
Trees are behind the rocks.
No wind was felt at the time - seemed very sheltered as bay curves in and
protects side.
Urban features The Power Station is very close to the Site, which must be accessed through
a road leading to the station.
A lot of fisherman’s debris and litter lies by the water’s edge and within the
rocks.
Substrate features Very large, granite coastal boulders
Other Fructicose lichens are dry / discoloured although still identifiable
Lichens tend to grow with each other in specific niches, as is the case at Site
B.
Kong ? A Appendix
23

fig 3.2.2! Table showing qualitative data for Site B
GPS Coordinates N 22.391284 E 113.918024
General aspect of shore NW 340°
Changes over transect Deep crevices are seen; often rock occurs on both sides of transect.
Sometimes a lot of sea snails seen on rock / crabs and other motile
organisms; sometimes rock is entirely bare.
Observed water traffic of time Small, mainland freighters
Water appearance Grey-green
Ballantine scale rating 5 - Fairly sheltered
Weak swash; island across breaks fetch
Geographical features Sand is black and very soft
Urban features About 300 m away from a restaurant, and a basketball court, and 600 m
away from residencies. 1600 m away from power station. A dolphin lookout
is on the hillside behind the coastal cliff, but is not linked to site in any
apparent way.
There is much litter (broken bottles, plastics) dumped behind the rocks.
Substrate features Large, granite coastal boulders of same texture and appearance in Site A
Other Lichens tend to grow with each other in specific niches, as is the case at Site
A.
Kong ? A Appendix
24

Appendix
A2. Photographs of Sites
Site A
! ! ! ! ! ! ! View of power station
! ! ! ! ! ! ! from Site A
Site B
Power stations and adjacent
facilities (EPD Report)
Type to enter text
Kong ? A Appendix
25

A3. Data Recorded for Quadrat Size Determination (using Gridded Quadrat)
1 square in 0.5 m by 0.5 m grid = 0.052 = 0.0025 m2 % cover = 0.25(no. of squares) / Area
Area No. of squares containing lichen Percentage cover (%) (2 s.f.)
0.0025 1 100
0.0100 3 75
0.0225 4 44
0.0400 7 44
0.0625 11 44
0.0900 15 42
0.1225 21 43
0.1600 30 47
0.2025 39 48
0.25 46 46
Kong ? A Appendix
26

A4. Lichen Species found (Thrower 1988)
Blastenia handelii: (left) crustose;
whitish-grey irregular patches 4
cm across; thin black margin
(hypothallus).
Buellia cif. subdisciformis: (right)
crustose; irregular but smooth
grey patches 5 cm across with
black hypothallus; dark-grey spots seen in areoles (round,
‘cracked’ divisions) of thallus.
Caloplaca cinnabarina: (below) crustose; a deep orange makes
this easily identified; clear areoles; mainly small samples found
(2-4 cm across).
Diploschistes actinostomus: crustose; clear, grey colour spreading
to large sizes over rock (10 cm+ across); areoles; asocarps are
visible as round black spots sunk into the thallus.
Dirinaria picta: squalumose
(scaly); pale grey-green circular
patches with raised bumps; resistant to moderate levels of
pollution.
Parmotrema incratassum: (right) foliose (leafy); spreads out in
circular green-grey ‘lobes’; distinguishable; approximately 30 cm;
central part dead and recolonised by young thalli.
Pyxine cocoes: foliose; pale green-grey thallus; overlapping lobes; known to be pollution resistant;
confusable with D. picta.
Ramalina litoralis: fructicose (bushy); yellowish-grey, dry samples found; tangled tufts; easily
identifiable as one of two coastal, fructicose species.
Roccella sinensis: fructicose; tufted with grey branches to make it easily identifiable.
R. litoralis and R. sinensis are unique to the coastal habitat.
Verrucaria: crustose; black, ‘tar’ lichen; appears to be dark green when dry; common where
periodically under water but found at Site A and B in the splash zone; found as circular spots that
merge.
All of the above species are generally found on coastal rock. Most were in proximity to each other
and on land-facing rock; certain species were more frequently in shaded or sheltered areas whereas
others were more light-demanding.
Kong ? A Appendix
27

Effect of air pollution on biodiversity of coastal lichens

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Viewers also liked

Viewers also liked (8)

Similar to Effect of air pollution on biodiversity of coastal lichens

Similar to Effect of air pollution on biodiversity of coastal lichens (20)

More from Anahita Sharma

More from Anahita Sharma (20)

Recently uploaded

Recently uploaded (20)

Effect of air pollution on biodiversity of coastal lichens