PREDICTING ACTIVITY OF THE GOLDEN SUN MOTH (SYNEMON PLANA) USING
DAILY WEATHER VARIABLES
by Kelsey Jane Tucker
(School of Biological Sciences, Monash University Clayton campus)
Introduction
The Golden Sun Moth (Synemon plana) is a winged invertebrate insect listed as critically
endangered, under the Environment Protection and Biodiversity Conservation Act 1999 (EPBC Act).
Herein referred to as the GSM, the moth belongs to the order Lepidoptera and generally occurs in
grasslands, consisting of either native Australian or exotic species. GSMs spend two to three years
underground pupating among grass roots, and emerge during summer, surviving as an adult for one to
four days. During late October to early January, males fly approximately one metre above ground,
searching for a female to mate with. Females have bright orange hind wings and display on the
ground in inter-tussock spaces (see Figure 1). Given certain practical considerations, GSM surveys
involve spotting flying males. The ‘Significant Impact Guidelines for the Critically Endangered
Golden Sun Moth (Synemon plana)’ specify that surveys for GSM should occur when skies are clear
or relatively cloudless, wind conditions are relatively still, with the temperature reaching 20°C by 10:
00 hrs. There should also be at least two days since rain. Such specific guidelines limit the number of
days suitable for surveying.
Figure 1. Example of female Golden Sun Moth (photo by Fabian Douglas)
No published studies currently indicate that emergence patterns can be predicted by daily
weather patterns. The aim of this study was to determine if there are any trends between
meteorological data (maximum wind speed, maximum air temperature, amount of rainfall in the last
48 hours and cloud type) on a daily basis, and the activity of the GSM. A number of factors are
described relating to GSMs: it was determined that temperature is not a strong predictor of GSM
flying activity, even though GSMs were active when daily maxima were between 26-32°C, however
rainfall accumulated in the 48 hours prior to surveying was a statistically significant variable.
Methods
Surveying for GSMs
Data was collected from 40 sites in western Melbourne within a defined time frame during
2011-2013, and within a 30 km proximity to Melbourne Airport, Avalon Airport or Laverton Royal
Australian Air Force (RAAF). Site habitat where the surveys occurred was dominated by exotic or
native grassland. Surveys were conducted between 10:00 – 15:00 hours. Data collection occurred over
two flight periods; November 2011 to January 2012, and November 2012 to January 2013. Hourly
meteorological data was supplied from the Bureau of Meteorology for the weather stations located at
Melbourne Airport, Avalon Airport and Laverton RAAF.
The guidelines referred to in the Introduction outline that transects should be run 50 m apart
initially, and then the distance between transects decreased on following surveys if no moths are
found. Surveys can be undertaken by either walking or driving at less than 10 km/h, and this guideline
was strictly adhered to. Data was collected by multiple ecological consultancies, with no standardised
sampling method used.
Statistical analysis
Data was entered into the standard Microsoft Excel 2010 computer program and analysed
using R Studio; free, open-source software compatible with Windows, Mac and Linux (R Studio Inc).
Although GSM abundance data was provided by consultants, sampling details of the survey method
were not supplied. Consequently, for the purposes of this report the information has been simplified to
binomial data: i.e. whether GSMs were active or not on the sampling day. If moths were not found on
site, this could either be because weather conditions were unfavourable or GSMs did not inhabit the
site. Sites where no moths were found were excluded from analysis, so as to not introduce
confounding variables.
Boxplots were used to test for equal variances between days on which GSMs were active or
not active. Welch’s t-test was used to determine if the mean maximum air temperature between 10:00
to 18:00 hours was significantly different for when GSMs were active or inactive. The Wilcoxon rank
sum test was used to test if mean maximum wind speeds between 10:00 to 18:00 hours were
significantly different when GSMs were either active or inactive. This test was also applied to data
concerning rainfall accumulated in the 48 hours prior to 0:00 hours of the sampling day. A KruskalWallis test was applied to cloud type (clear, broken, scattered or broken) to assess if GSM activity
was significantly different depending on cloud type. A P value of 0.05 or below was considered
statistically significant.
Results
There was no significant difference in maximum air temperature on the days which GSMs
were active or inactive (Figure 2, P > 0.05). Likewise, there was no significant difference in
maximum wind speed (Figure 3, P > 0.05), although the maximum wind speed during days where
GSMs were active may have been relatively lower. The rainfall accumulated in the 48 hours prior to
surveying was significantly higher, when GSMs were active compared to inactive (Figure 4, P <
0.05). Correlative trends between meteorological variables and GSM activity are shown in Table 1:
30
25
20
Maximum air temperature (°C)
surprisingly, cloud type was demonstrated not to be an important factor.
N
Y
Activity
Figure 2. Maximum air temperature during the 8-hour survey periods (10am -6pm), spanning
November 2011 to January 2012, and November 2012 to January 2013
50
40
30
20
Maximum wind speed (km/h)
N
Y
Activity
Figure 3. Maximum wind speed during the 8-hour survey periods (10 am – 6 pm), spanning
100
80
60
40
20
0
Rainfall last 48 hours (mm)
November 2011 to January 2012, and November 2012 to January 2013
N
Y
Activity
Figure 4. Rainfall levels during the last 48 hours prior to the day of GSM surveying, spanning the
period November 2011 to January 2012, and November 2012 to January 2013
Table 1. Results of the statistical tests for trends between meteorological variables and GSM activity
Meteorological variable
Moth
activity
(Yes or
No)
Mean (± standard error) of
meteorological variable
Maximum air temperature (°C)
Yes
27.85 ± 0.58
No
28.24 ± 0.61
Yes
29.69 ± 1.24
No
30.02 ± 1.42
Yes
2.53 ± 2.23
No
0.97 ± 0.57
Yes
N/A
No
N/A
Maximum wind speed (km/h)
Rainfall last 48 hours (mm)
Cloud type
(clear/scattered/broken/overcast)
Test
statistic
P-value
t = 0.4613
0.646
W = 985.5
0.729
W = 1244.5
0.046
χ2 = 0.9898
0.804
Discussion and Recommendations
Recommendations
From the data in this study, it is concluded that temperature is not a strong predictor of GSM
flying, with similar temperature ranges observed for when GSMs were either active or inactive. GSMs
were found to be active during days when temperature maxima were between 26-32°C, information
which can be used for optimised future surveys.
The maximum wind speed during the survey period also cannot be used to predict GSM
activity. Although it appears that GSMs are active within a relatively narrow range of wind speeds
(approximately 25-31 km/h), the mean maximum wind speeds for the assessed survey periods were
not significantly different for active versus inactive GSMs. This suggests that maximum wind speed
on the surveying day is not a good predictor of GSM activity. This is despite how the Biodiversity
Precinct Planning Kit (Department of Environment and Primary Industries) states that surveying can
occur on moderately windy days, which implies protocol modification is required and informing the
Victorian State Government of the results of this study.
Cloud type was also not a good predictor of GSM activity. Therefore it can be concluded that
surveying can be undertaken when skies are either clear, have some cloud (scattered or broken) or are
overcast. By contrast, GSM activity was higher when it had rained 48 hours prior to surveying. This is
contradictory to the survey guidelines in ‘Significant Impact Guidelines for the Critically Endangered
Golden Sun Moth (Synemon plana)’. Seasonal rain during summer triggers the emergence of adult
Christmas beetles (Anoplognathus), another Australian flying insect, have a similar pattern of
pupating underground for two years and emerging during summer. Rainfall is thought to soften the
soil and allow Christmas beetles to dig into the surface. Perhaps this could also explain why GSMs
are more likely to emerge after rainfall.
Study limitations
The distance from survey sites to the nearest weather station was highly variable, with some
weather stations up to 30 km away from survey sites. This may have influenced the accuracy of the
recorded data, at least to a certain extent. In addition, binomial analysis was used to analyse the raw
data, which means that certain variables have not been assessed. For the purposes of this study, such
detail is perhaps less important since the primary interest of ecological consultants is to record if
GSMs are present or not, as opposed the abundance of the moth species.
Conclusions
The following was determined as a result of this survey study:

daily temperature is not a strong predictor of GSM flying

maximum wind speed is not a strong predictor of GSM flying

cloud type is not a strong predictor of GSM flying

GSM activity was higher when it had rained 48 hours prior to surveying
References
‘Biodiversity Precinct Planning Kit’ Department of Sustainability and the Environment, State
of
Victoria,
accessed
via
http://www.dse.vic.gov.au/__data/assets/pdf_file/0004/102298/BiodiversityPlanningKit.pdf
on
17/10/2013
‘Christmas
beetles
arrive
on
cue’
CSIRO
Factsheet,
accessed
via
http://www.csiro.au/Outcomes/Food-and-Agriculture/ChristmasBeetles.aspx on 16/10/13
‘Background Paper to EPBC Act Policy Statement 3.12 – Nationally Threatened Species and
Ecological Communities: Significant Impact Guidelines for the Critically Endangered Golden Sun
Moth (Synemon plana)’ Australian Government Department of the Environment, Water, Heritage and
the Arts (2009)
Acknowledgements
I wish to thank Alan Brennan (Brett Lane and Associates), Annabelle Stewart (Brett Lane and
Associates), Theodoros Papakonstantinou (Monash University), Elizabeth Ebert (Bureau of
Meteorology), and Christopher Johnstone (Monash University) for assistance in the preparation of this
report. To the best of my knowledge, there are no intentional errors or inaccuracies present herein.
Kelsey Jane Tucker
Melbourne, 17th October 2013