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http://www.dpi.nsw.gov.au/agriculture/pests-weeds/vertebrate-pests/general/monitoring-techniques
How to do the count
•­ Select sites to be monitored (use 4 km2 sampling
sites and separate sites by a minimum of 5 km).
Sampling site – use the same sampling plots for each
count.
•­ randomly position 100 plots (10 × 2 m) within the
site, but ensure there is no overlap of plots.
Timing – count dung once every month.
•­ use two pegs (numbered so that plots are easily
recognised) spaced 10 m apart to mark out the
centre line of the plot.
•­ record the number and location of all plots on a
map and use a gpS.
•­ clear each plot of all dung.
•­ return to the plots in 1 month and use
small-diameter rope to extend a line the length of
the plot between the two pegs.
•­ count and record the number of feral pig dung
pellets 1 m either side of the centre line.
•­ clear the plot of all dung after completion of the
count.
•­ repeat the count every month.
•­ use the average number of dung pellets per plot
as the index and plot on a graph to keep track of
changes.
•­ the presence/absence of feral pig dung can be
used to show the frequency of occurrence of feral
pig presence within plots.
26
Standards
Monitoring techniques for Vertebrate pests – feral pigs, Bruce Mitchell & Suzanne Balogh
Animal welfare considerations
Impact on target animals – nil
Impact on non-target animals – nil
Health and safety considerations
feral pigs may carry diseases such as leptospirosis,
Q fever, brucellosis, sparganosis and tuberculosis,
which can all affect humans. wear gloves when
handling dung and routinely wash your hands and
other skin surfaces that may have had contact with
dung.
Training required
identification of dung
spotlight counts
night-time counting using spotlights has been used
to survey feral pigs and examine their nocturnal
activity (hone and pedersen 1980; hone 1983;
choquenot et al. 1990; choquenot et al. 1993; cahill
et al. 2003). this is mainly because of the ease with
which spotlighting is carried out and the fact that
it can cover large areas in a short amount of time.
Spotlighting can sample different vegetation types
and compare them under similar conditions within a
site (e.g. season, time, weather). feral pigs are most
active at dusk and during the night (Saunders and Kay
1991).
Simple indexes of abundance can be produced from
these counts, such as the number of animals observed
per kilometre travelled. however, indexes created
from spotlighting counts have bias caused by the use
of different observers and differences in visibility, or
‘sightability’, which changes with vegetation density
and animal behaviour (twigg et al. 1998; wilson and
delahy 2001; Saunders and Mcleod 2004). feral pigs
lack a well-reflecting layer in the retina of the eye,
and as a result do not have distinctive eye-shine,
thus further reducing sightability (focardi et al.
2001). other sources of potential variation include
seasonal variation in animal behaviour, and the use
of roads that are often used as transects, resulting in
potentially uneven survey of vegetation types. (weber
et al. 1991; thompson et al. 1998). this monitoring
method is unsuitable in heavy rain or other extreme
conditions, as these affect the activity and sightability
of feral pigs.
Because of these shortcomings, spotlighting has not
been extensively used in australia for monitoring feral
pigs. despite this, it may still be a practical method of
indexing feral pig abundance if the country is open
and the sampling effort is high (choquenot et al.
1990).
density estimates from spotlight counts can be made
by using methods similar to those described for aerial
surveys. for example, the distance sampling method,
where the distance to the animal is used to correct
for visibility bias (Buckland et al. 1993; thompson
et al. 1998). Key assumptions of distance sampling
for unbiased estimates are that every target animal
on the transect is detected with certainty; individuals
are detected in their initial location and do not move
before detection by the observer, or they move in a
random direction away from the observer (evasion),
and bias is towards underestimation. alternatively,
movement may be towards the observer (attraction),
and bias is towards overestimation. individuals are
not recorded twice and distance measurements
and angles of movement are accurate (Buckland
et al. 1993; rudran et al. 1996). Buckland et al. (1993)
suggested that a sample size greater than 60 sightings
is needed for accurate density estimation.
problems that arise from these assumptions can lead
to inaccuracies in the density estimates obtained
by distance sampling. detection of all animals on a
transect may not be achievable, although double
sampling, using two independent observers, may
alleviate the problem. Most spotlight counts of feral
pigs occur on roads or trails and have associated
problems (as discussed above). there is also an
increased chance of double counting, because
roads are rarely straight, and visual estimates of
perpendicular distance are prone to error (heydon
et al. 2000; ruette et al. 2003; Saunders and Mcleod
2004). heydon et al. (2000) suggested that hand-held
laser range finders could overcome the latter
difficulty.
Before the start of a spotlight count, standardise the
technique to be used.
Monitoring feral pig abundance
27
Figure 18: Spotlighting for feral pigs which are most active at
dusk and during the night. Pigs have no distinctive eyeshine.
(photo Glen Saunders)
the route being taken, including the length of the
transect, should be established and plotted on a
map. ensure the transect passes through areas that
represent all vegetation types in the area, and that the
route is traversable in all weather conditions. inspect
the area during daylight, before planning the transect.
Mark transects with reflectors so that future surveys
can follow the same path. once set out, this transect
may be used for all further surveys, so that valid
comparisons to prior surveys can be made .
Surveys need to be conducted at least quarterly to
account for seasonal differences in abundance of
animals; however, the use of more frequent surveys
could provide even greater information. if the
monitoring is being done to check on pest control
success, the surveys need to be done prior to the
control and then approximately 1 week post-control.
regardless of frequency, a survey needs to be made
up of counts repeated on 3 or 4 consecutive nights.
where possible, repeat counts until they give a similar
index – this will achieve a consistent level of precision,
with standard error of counts within 10% of the mean
(Saunders et al. 1995). Similar weather conditions for
all counts are required; avoid nights of heavy rain.
Starting at the same time for each survey is important.
the spotlight count needs to coincide with the period
of highest activity of the target species. generally, a
start time of at least half an hour after sunset will be
adequate to survey pigs.
28
Monitoring techniques for Vertebrate pests – feral pigs, Bruce Mitchell & Suzanne Balogh
the length of the transect depends on the size of
the area being surveyed. indexes of abundance
are calculated as animals per kilometre; therefore
a transect should be a minimum of 1 km, but the
longer the transect the more accurate the estimate.
Somewhere between 10 and 30 km would be ideal.
Materials required
Vehicle – 4wd with an enclosed cabin and a fixed
roof-mounted spotlight (passenger side). the
observer sits within the cabin and operates the
spotlight by a swivel handle or uses a hand-held
spotlight.
People – one driver; one or more observers
Spotlight – hand-held: 100 w, 12V, or roof-mounted
Spotlight count sheet and clipboard
How to do the count
•­ Start approximately half an hour after sunset from
an established start point.
•­ one person drives and another person counts
animals.
•­ drive at a constant slow speed (5 to 10 km/h).
•­ observer scans a 180° arc ahead of the vehicle
with the spotlight and counts animals seen within
100 m on either side.
•­ when an animal is seen, stop the vehicle to
enable an accurate identification, and record
it on a standardised spotlight count sheet (see
example in table 1).
Table 1: Spotlight counting – example of a count sheet using encounter rate
Date:
Site:
Start time:
Start odometer:
Observer:
Vehicle:
Finish time:
Finish odometer:
Driver:
Speed:
Position: roof-mounted
sitting hand-held
Spotlight power: V
W
Page:
Temperature: cold cool mild warm hot
Wind: nil light medium strong
Cloud: nil 20% 40% 60% 80% 100%
Moon visibility: 0 1/4 1/2 3/4 full
Last rain: > week ago this week yesterday today now
Surface condition: dry wet slushy dew frost
Transect section Pig
Other
Rabbit
Fox, dog, cat
Stock
of
Direction:
Vegetation type and condition
comments:
Monitoring feral pig abundance
29
•­ repeat the count on three or more consecutive
nights of similar weather.
•­ on subsequent counts start at the same time as
the first count, use the same route, distance and
direction and the same vehicle, speed, spotlight
and people.
•­ when the survey is finished, determine the
average of the counts and divide by the length of
the transect to get a simple index of abundance
or animals per kilometre.
Variations on technique:
Two people counting – use two hand-held spotlights of
the same power: each observer counts on one side of
the vehicle in a 90° arc ahead of the vehicle.
Tape recording – use a tape recorder rather than a
count sheet to record what was seen. transcribe
the data at a later date, or use a laptop computer to
record data. forms can be made using programs such
as Microsoft Visual Basic or Microsoft access.
Standards
Route – use the same transect and travel in the same
direction for each count.
Time – use the same start time for each count at least
half an hour after sunset.
Rate of travel – 5 to 10 km h–1 (constant speed)
Spotlight power – 100w, 12V
Observer – use the same observer(s) for each count.
Vehicle – use the same vehicle for each count.
30
Monitoring techniques for Vertebrate pests – feral pigs, Bruce Mitchell & Suzanne Balogh
Animal welfare considerations
Impact on target animals – nil
Impact on non-target animals – nil
Health and safety considerations
the driver and observer should be familiar with
the track in daylight conditions, having driven it
before starting the survey to demonstrate that it
is readily navigable. ensure that the spotlight is
well maintained, with leads connected securely
to the battery terminals and insulated from other
components. always disconnect the spotlight from
the power source before changing the globe or
making repairs. Switch the spotlight off when not
surveying. do not leave the spotlight switched
on face-down on the seat or other heat-sensitive
material. do not run the spotlight for long periods
without the motor running. all occupants should
carry drinking water, a torch and sufficient clothing
for warmth in the event of the vehicle becoming
stranded. avoid shining the spotlight beam into
other people’s eyes. check previous rainfall and
surface conditions before the survey. the driver and
observer must not be fatigued at the time they do the
spotlight survey. the observer should wear adequate
clothing during cold weather. drive at correct speed
and continually watch the surface ahead on the
track. remove dangerous overhanging tree branches
and obstructions before starting the survey. record
observations when the vehicle is stationary.
Training required
4wd training
instruction in setting up and using spotlight
equipment.
Worked example
to evaluate the success of a feral pig control
operation. the transect length is 32 km.
feral pigs seen pre-control:
1st count – 9, 2nd count – 15, 3rd count – 12
total = 36
average = 36 ÷ 3 = 12
number of feral pigs per km = 12 ÷ 32 = 0.38 feral pigs km–1
feral pigs seen post-control:
1st count – 1, 2nd count – 0, 3rd count – 2
total = 3
average = 3 ÷ 3 = 1
•­ each time a feral pig is encountered, stop the
vehicle and calculate the perpendicular distance
from the transect line with a laser range finder;
or, calculate the radial distance from the observer
to the feral pig, as well as the sighting angle
between the line of sight to the feral pig and the
transect line, at the moment of detection.
•­ density estimates are computed using computer
software such as diStance (laake et al. 1993).
•­ for an extensive review of distance sampling see
Buckland et al. (1993).
number of feral pigs per km = 1 ÷ 32 = 0.03 feral pigs km–1
Standards
the percentage reduction in feral pig numbers is
estimated from these figures:
as outlined on page 30.
0.03 × 100 = 7.89
0.38
Animal welfare considerations
100 – 7.89 = 92.11% reduction
Distance Sampling
Materials required in addition to those outlined on
page 28 include:
Range finder – hand-held device that determines the
distance between the animal and observer
compass, gpS or angle board
computer software for density estimates
distance sampling count data sheet see table 2.
How to do the count
Impact on target animals – nil
Impact on non-target animals – nil
Health and safety considerations
as outlined on page 30.
Training required
4wd training
instruction in setting up and using spotlight
equipment.
Measurement of distances and angles
computer software
Variations on techniques outlined on pages 27 and 28:
•­ transects should be as straight as possible; if
possible avoid major roads.
Monitoring feral pig abundance
31
Table 2: Spotlight counting – example of a count sheet using distance sampling
Date:
Site:
Start time:
Start odometer:
Observer:
Vehicle:
Finish time:
Finish odometer:
Driver:
Speed:
Spotlight power: V
W
Page:
Position: roof-mounted
sitting hand-held
Temperature: cold cool mild warm hot
Wind: nil light medium strong
Cloud: nil 20% 40% 60% 80% 100%
Moon visibility: 0 1/4 1/2 3/4 full
Last rain: > week ago this week yesterday today now
Surface condition: dry wet slushy dew frost
Species
Number
Range
Bearing
Habitat
P – pig, K – kangaroo, C – cat, R – rabbit, W – wallaroo, F – fox, D – dingo/dog
32
of
Monitoring techniques for Vertebrate pests – feral pigs, Bruce Mitchell & Suzanne Balogh
Waypoint
Easting
Direction:
Northing
Time
G A A T A C T A A C C C T G T G A
C T T A T G A T T GGG A C A C T
Dna sampling
Sampling the dna of animals may help overcome
some of the limitations of traditional monitoring
techniques, by providing accurate identification of
samples to the species and individual level (piggott
and taylor 2003). dna collection can be invasive,
using blood and tissue samples; or non-invasive, by
collecting faecal and hair samples. Samples for the
non-invasive testing are much simpler to collect, as
the feral pig does not need to be handled. this type
of sampling can be used for population, home range
estimation, sex ratio and immigration or emigration of
the population.
the development of methods of extraction of the
dna contained in faeces and hair offers the most
appealing opportunities for more precise population
estimates, through the derivation of genetic profiles
of individual animals (Kohn and wayne 1997; piggott
and taylor 2003). for example, coyote (Canis latrans)
abundance has been estimated using large samples
of coyote scats (651) collected from roads; these scats
were positively identified from diagnostic sections
of mitochondrial dna (Kohn et al. 1999). the scats
were genotyped to determine individual animals,
and the cumulative number of unique microsatellites
was expressed as a proportion of the number of
scats sampled. the flattening-out, or asymptote, of
this curve was determined as an estimate of local
population size. the capture–recapture models
can be used with this type of data. a population of
endangered wolverines (Gulo gulo) in norway was
monitored, using scats as a source of dna, to estimate
population size, sex ratio, immigration rate and
reproductive contribution from immigrants (flagstad
et al. 2004). Scats that were successfully analysed were
treated as one trapping event, and the number of
Figure 19: Example of DNA sequence (diagram courtesy of
AGAL)
times that each individual was trapped was recorded
using capture–recapture model. hair sampling has
proved useful to estimate population size for studies
of grizzly bears (Ursus arctos) in north america (Mowat
and Strobeck 2000; poole et al. 2001). Bear dna was
captured by removing hair at bait sites surrounded
by a single strand of barbed wire . Microsatellite
profiling of the root portion of the hair was then used
to identify individuals. Subsequent sampling provided
recaptures. other types of monitoring tools that
can be used in conjunction with dna profiling are
catch per unit effort (romain-Bondi et al. 2004) and
presence or absence studies.
there are various problems associated with dna
sampling. one of the main limitations is the high cost
of extraction of dna from scats and hair, owing to the
low quantity and quality of dna typically recovered
from these types of sample (harrison et al. 2002;
davison et al. 2002; piggott and taylor 2003).
fresh samples are required, and must be stored
correctly to preserve the sample, as dna degrades
over time. (foran et al. 1997; Kohn et al. 1999;
piggott and taylor 2003). piggot and taylor (2003)
investigated faecal preservation and dna extraction
methods for mammals found in australia, and
developed a protocol that was found to be optimal for
five different species. this method involved air-drying
the fresh scats in paper bags (ideal for field collection),
followed by a surface wash to collect cells for the dna
extraction process. there is an inherent error rate in
the process of dna amplification using polymerase
chain reaction (pcr), which may lead to misleading
Monitoring feral pig abundance
33
results, such as population overestimation (wilson
and delahy 2001; piggott 2004). Scats less than a
week old will give the most accurate results, and this
needs to be taken into consideration when planning
a monitoring program. these methods, when used
for population estimation, rely on assumptions such
as defecation rates being equal among sexes and
age classes and independent of social class. they
also rely on the non-violation of capture–recapture
assumptions (Kohn et al. 1999; Mowat and Strobeck
2000).
in spite of these problems, dna sampling is an
effective and efficient way of monitoring a species
such as the feral pig that is difficult to observe,
exists at low densities and/or has large home
ranges (piggott and taylor 2003). collecting scats
is a relatively easy way to obtain dna samples,
with the additional benefit of dietary information.
hair samples should be easy to obtain using bait
stations surrounded by a strand of barbed wire at
an appropriate height of 25 cm. this technique has
been used successfully for monitoring bear and
badger (Meles meles) populations (woods et al.
1999; Mowat and Strobeck 2000; poole et al. 2001;
romain-Bondi et al. 2004; frantz et al. 2004). this is a
variation of the scent stations used for canids, where
instead of footprints, hair is left to indicate visitation.
the advantage of this technique over traditional
scent stations is that the dna sampling can give a
population estimation.
track counts
footprints, or tracks of animals, are often among the
few indications that some species are present in an
area, and counting the density of these tracks may be
useful for monitoring purposes. track counts are used
predominantly for elusive animals or those found
in low densities. there is an assumed relationship
between the number of tracks and the actual
abundance of the target species, but there have been
few validations against known populations (fleming
et al. 2001; wilson and delahy 2001). nevertheless,
track counts are considered to produce reliable
indexes of abundance that can be used to detect
changes in animal populations (Bider 1968; catling
and Burt 1994; allen et al. 1996; engeman et al. 2001;
wilson and delahy 2001).
counting tracks is passive and animal behaviour is not
altered by detection. it involves the use of either track
stations or sand plots, strips of sand raked across a
road at set intervals, (catling and Burt 1994; engeman
et al. 2001) or road counts where the road is used as
a transect and the number of sets of tracks on it are
counted (corbett 1995; Mahon et al. 1998). however,
unlike canids, that use roads for movement and
territorial marking (triggs 1996; corbett 2001), feral
pigs show little preference for using roads (Saunders
et al. 1993). instead, track counts for feral pigs have
been used around dams in Queensland in areas where
feral pigs need water under dry climatic conditions
(Mitchell 2003; lapidge et al. 2003).
problems associated with using footprints to monitor
populations include the effects of weather, season
and humans. Strong rain and wind can reduce the
clarity of (or remove) footprints, making accurate
identification difficult or impossible. the actions of
34
Monitoring techniques for Vertebrate pests – feral pigs, Bruce Mitchell & Suzanne Balogh
humans in walking or driving over plots can likewise
affect counts. there is variability in the detectability
of footprints along a given transect due to soil
type, colour, dampness and dappled shadows. this
can be accounted for by correcting for the relative
detectability of sign (fleming et al. 1996).
More specifically, the use of roads and watering
points as sampling units creates bias due to
unrepresentative sampling of the study area
(anderson 2001; McKelvey and pearson 2001), and
the relationship between track counts and animal
density is usually unknown. these indexes measure
changes in feral pig activity, which may or may not
relate to actual abundance. in many cases activity is
likely to change seasonally or annually, independently
of density (Mcilroy 1989; Mcilroy 1993). Similarly, the
detectability of footprints may vary due to hot, dry
and dusty conditions or cold, damp conditions and
compacted soil. therefore, its necessary to exercise
caution in relying solely on track counts to measure
changes in abundance until these techniques can
be validated against known populations. Stratified
sampling across the survey area may overcome
some bias, but it would also significantly increase
the time and cost of monitoring. furthermore, even
though they may be simple to conduct, passive index
surveys require large sample sizes to provide accurate
estimates of low-density populations (allen et al.
1996; fleming et al. 2001; wilson and delahy 2001).
the scale of the survey must match the likely home
range size of the target species. if this is not achieved,
the survey will measure the activity of the few animals
within the survey area; therefore, track counts are not
suitable for small-scale surveys (Sargeant et al. 2003).
Figure 20: Sand plots made on used access ways. Check
weather forecasts prior to setting up (photo Peter Fleming)
to account for the variation in detectability of
footprints, and to make more valid comparisons
between sites, a measure of ‘imprintability’ should
be taken (fleming et al. 1996). at every track station,
the observer takes 10 paces across the tracking
substrate and scores the resulting imprints on a
scale of 0–3 (Van dyke et al. 1986), where 0 = no
print visible; 1 = print barely visible; 2 = complete
outline of print and some detail of the sole visible;
3 = complete outline of print and all details of the sole
visible. the resulting point value for each location
will vary between 0 and 30, and allows the allocation
of a score for the location. a score of 0 – 5 = poor
imprintability (1); 6 – 15 = fair (2); 16 – 25 = good (3);
and 26 – 30 = excellent (4). any track stations that
score (1) should be excluded from the index. these are
arbitrary cut-off points and may need to be expanded
on a site-by-site basis; (1) may need to include scores
of 1–10.
Materials required
Vehicle – either utility or with a trailer to transport
sand.
Sand, shovel and rake/broom/drag – where possible,
use local sand from washouts and road gutters to
avoid importing weeds and novel smells that may
influence the response of feral pigs.
Monitoring feral pig abundance
35
count sheet
Map and gpS
Track diagrams – suggested text: triggs, B. (1996)
Tracks, Scats and Other Traces: a Field Guide to
Australian mammals. oxford university press, South
Melbourne.
How to do the count
•­ Select sites to be monitored, use roads with low,
or no, usage. at least 26 usable track stations are
required.
•­ Set routes and mark out the transects on a map
and gpS-record them so that future surveys can
easily follow the same paths. once set out, this
transect may be used for all further surveys so
that valid comparisons to prior surveys can be
made.
•­ when establishing track stations, avoid situating
them under overhanging foliage where dripping
dew can affect the clarity of footprints.
•­ create track station by putting down a thin layer
of sand approximately 1 m wide and 1 to 3 cm
deep, covering the road from one side to the
other. rake or sweep sand or soil smooth. if track
stations are established around dams, the size of
each station should be 5 × 1 m.
•­ create a unique name for each station and mark
the station’s position on a gpS.
•­ create track stations every 1 km for the length of
the transect. around dams, use 10 stations per
dam.
36
Monitoring techniques for Vertebrate pests – feral pigs, Bruce Mitchell & Suzanne Balogh
• count and record all sets of feral pig tracks, and
tracks of other species, the following morning.
•­ determine the imprintability value, and then
sweep the track station clean of footprints.
•­ repeat count for at least three consecutive
mornings or more than 78 station nights required.
•­ convert to indexes via the percentage of station
nights with tracks (catling index) (see example in
table 3). remember to remove track stations that
have an imprintability score of 1.
Standards
Route – use the same transects/dams for each count.
Sampling time – always conduct survey at the
same time (i.e. season) and during similar weather
conditions (i.e. not during heavy rain).
Animal welfare considerations
Impact on animals – there may be some aversion
or attraction to transects if the area is not naturally
sandy.
Health and safety considerations
the driver must be licensed, and undergo 4wd
training. drive appropriately for the conditions on
and off-road at all times. when establishing and
maintaining track stations, wear sturdy boots and
gloves to minimise the risk of foot injuries and
splinters, and be careful of back strain. Maintain
awareness of oncoming traffic when inspecting track
stations.
Training required
Worked example
identification of tracks
feral pig control was being planned in southern
Queensland, and the abundance of these animals
needed to be monitored immediately before and after
the operation to gauge the outcome. there were eight
dams within the study area and no other sources of
water. ten track stations were established at each dam
and monitored for 4 consecutive days.
use of gpS
4wd
from the track count data it was assumed that there
had been a 60% reduction in feral pig abundance.
Table 3: Tracking counts: use of the Catling Index
No. of track
statioNs
No. of statioN
Nights
No. of statioNs with
No. of operable
impriNtability score of 1 statioN Nights
No. of statioNs with
feral pig tracks
catliNg iNdex value
80 (pre-baiting)
320
0
320
132
80 (post-baiting)
320
12
308
51
= 132 ÷ 320 × 100
= 41.25
= 51 ÷ 308 × 100
= 16.56
Monitoring feral pig abundance
37
38
Monitoring techniques for Vertebrate pests – feral pigs, Bruce Mitchell & Suzanne Balogh
Monitor fer aL pig iMpac ts
this section discusses the methods that can be
used to monitor the impacts caused by feral pigs. a
summary of these and a comparison between the
methods of monitoring feral pig abundance are
provided in a table 5.
the quantification of feral pig damage is often
difficult and costly, requiring a lot of time and
scientific expertise (caley 1993b; choquenot et al.
1996); however, there are a number of qualitative
techniques that can be used to monitor the impact of
feral pigs. these methods include monitoring feral pig
sign in crops or pastures, lamb predation assessments,
the mapping of damage and measuring abundance. a
major problem with attempting to monitor feral pig
impact is that the damage varies both in space and
time (hone 1995). as a result, the development of
simple and economical indexes of feral pig impact
may be difficult (choquenot et al. 1996).
economic cost monitoring
it is difficult to accurately estimate the agricultural
costs attributable to feral pigs in australia on a
national, state or regional level (Bomford and hart
2002). conservative estimates of the annual cost
impact of feral pigs have been put at a monetary value
of $107 million (Mcleod 2004). however, this value
is based on limited information extrapolated from
sources such as government agency estimates and
landholder surveys, and it has been acknowledged
that there are many gaps in the knowledge (Bomford
and hart 2002; Mcleod 2004). individual landholders
can therefore play an important role in filling these
gaps, by calculating and monitoring all the costs
attributable to feral pigs (Mitchell and dorney 2002).
these costs include control expenditure, and others
such as shooting or trapping; checking, moving
and sheltering ewes during lambing; lamb losses
(see table 4); and infrastructure installation and
maintenance (e.g. fencing). these costs could be
recorded as part of the economic management of a
property, and hence there is little extra expense to
the landholder. the inference that is made from cost
monitoring is that a decline in costs is associated with
a decline in feral pig damage and abundance (Mitchell
and Kanowski 2003).
Monitoring feral pig impacts
39
Table 4: Economic cost of monitoring: example of a sheet used to calculate costs
activity
Shooting
Trapping
Exclusion fence maintenance
labour
……h @ $ h–1
material
cost $
Vehicle @ $ km–1
Ammunition
Firearm maintenance
Vehicle @ $ km–1
Trap maintenance
Ammunition
Firearm maintenance
Posts
Wire
Ewe/lamb protection
Lamb losses
Ewe scanning @ $ ewe–1
Crop damage
Re-sowing crops
sign counts
feral pigs leave abundant sign of damage that
indicates the presence or absence from an area.
feral pig sign can include rooting, wallows, dung,
footprints, travel pads, plant damage and tree rubs.
the frequency of occurrence of sign may be used to
monitor feral pig abundance and damage. there are
two main approaches to sign counts: simple scoring
and presence or absence systems.
Simple counts of feral pig sign can be used to score
feral pig damage, or as indicators of feral pig activity.
examples of scoring feral pig damage include a
4-point activity scale used in rainforests in north
Queensland, where 0 = no sign, 1 = low (1– signs
per transect), 2 = moderate (4 0 signs); and 3 = high
(more than 10 signs) (pavlov et al. 1992; laurance
40
Monitoring techniques for Vertebrate pests – feral pigs, Bruce Mitchell & Suzanne Balogh
and harrington 1997). Scales based on percentage
area of rooting within quadrats have also been used
(Bowman and Mcdonough 1991; Mitchell and Mayer
1997; cahill et al. 2003). using presence or absence
of feral pig sign simplifies these counts further and
reduces the time required to sample each site (hone
1988b). although simple score systems are used
primarily to monitor feral pig damage, they have
been used as indexes of feral pig abundance, with the
assumption that there is a relationship between the
amount of sign and feral pig abundance (hone 1988c;
Mitchell and dorney 2002). these counts have used
permanently established activity plots to record the
presence or absence of sign, with the frequency of
occurrence used as the index. for digging transects
using recent pig diggings as an index, see Mitchell
(2002).
the advantages of simple score methods are
simplicity and speed, but these methods are limited
by subjectivity, low precision and the frequent use of
roads and trails, as well as their associated problems
of unrepresentative sampling as transects. random
selection of sampling sites can alleviate some of these
problems (hone 1988c).
Materials required
count sheet
gpS
2 × 30 m tape measures
pegs or reflectors to mark transect sections
How to do the count
Simple score:
•­ determine the average score for each transect
and use these results to calculate the mean score
and variance for the survey area.
•­ if the variance exceeds 20% of the mean, more
transects are required.
•­ repeat the count each season.
activity plot:
• Select sites to be monitored, use 4 km2 sampling
sites and separate sites by a minimum of 5 km.
•­ randomly position 100 plots (10 × 2 m) within the
site, but ensure there is no overlap of plots.
•­ use two pegs, numbered so that plots are easily
recognised, spaced 10 m apart to mark out the
centre line of the plot.
•­ Select sites to be monitored.
•­ record the number and location of all plots on a
map and use a gpS.
•­ randomly select the locations of 1 km transects
within the site.
•­ use a small-diameter rope to mark the length of
the plot, extended between the two pegs.
•­ record locations on a map via gpS.
•­ count and record the presence or absence of feral
pig sign 1 m either side of the centre line.
•­ use numbered pegs or reflectors to mark out each
transect into 50 m sections.
•­ lay a tape measure or rope between the markers,
record the frequency and assign a score or
presence or absence of feral pig sign 1 m either
side of the tape in every 50 m section.
•­ use the frequency of occurrence of feral pig
presence within plots as the index. an alternative
to this is to record the frequency of occurrence
of each type of sign including rooting, wallow,
tracks, dung, travel pad, plant damage, rubs and
actual sightings. average these for each site to
gain the index (Mitchell and dorney 2002).
•­ repeat the count each season.
Monitoring feral pig impacts
41
Standards
Figure 21: Feral pigs will attack lambs leaving few remains
(photo Peter Fleming)
Sampling site – use the same site for each survey.
Sampling time – use the same seasonal conditions for
each survey.
Animal welfare considerations
Impact on target animals – nil
Impact on non-target animals – nil
Health and safety considerations
Suitable footwear and sun protection
Materials required
count sheet
How to do the count
Training required
• determine if lamb kills are due to feral pigs.
identification of feral pig sign
•­ calculate the proportion of ewes with lost lambs
by using either udder scores or ultrasound.
Monitoring lamb predation by feral pigs
•­ ultrasound is the most effective method to
determine how many lambs will be born. Scan for
dry, singles, twins and triplets.
feral pigs can reduce lamb production by preying
upon newborn lambs (plant et al. 1978; pavlov et al.
1981; pavlov and hone 1982; choquenot et al. 1997).
choquenot et al. (1997) measured the predation
rate of lambs by feral pigs, and found a curvilinear
relationship between the density of feral pigs and
reduction in lamb yield. this can be explained by
the unequal susceptibility of all lambs to predation,
mainly due to differences in fitness, with feral pigs
rarely chasing lambs for more than 20 seconds
(pavlov and hone 1982). furthermore, not all feral
pigs will attack and eat lambs (choquenot et al. 1996).
therefore, there is an upper limit to the proportion
of lambs that will be lost to feral pig predation. as a
result, monitoring feral pig predation will give little
more than the presence or absence of feral pigs.
the first step in monitoring lamb predation is to
determine the cause of lamb death (see figure 22).
42
the characteristics of feral pig kills are that few
remains are found, apart from the skin and some
bones. the proportion of ewes that lose lambs can be
recorded and compared with that in previous lambing
seasons.
Monitoring techniques for Vertebrate pests – feral pigs, Bruce Mitchell & Suzanne Balogh
•­ udder scores (dun 1963; choquenot et al. 1996)
can help in calculating the proportion of ewes
that have lost lambs.
•­ for udder scoring examine the udder of each ewe
and score as:
•­ dry – no evidence of impending or recent
lactation or pregnancy
•­ pregnant – impending lactation, as indicated
by obvious pregnancy and/or production of
colostrum
•­ wet – currently lactating; udder firm, full,
warm and clean
•­ lost lamb – recently ceased lactating; udder
hard, cold and dirty.
Standards
Health and safety considerations
Site – count and compare lamb predation from the
same paddocks.
nil
Training required
Animal welfare considerations
identification of lamb predation
Impact on target animals – nil
udder scoring
Impact on non-target animals – nil
have adult sheep
been attacked or
severely injured?
No
have lamb
carcasses been eaten
or mutilated?
probably not killed
by predator
No
yes
has the carcass
been entirely eaten
except for skin and
some bones?
No
has the attack
been confined to the
orifices?
No
has lamb breathed?
No
probably born dead
yes
has lamb walked?
No
probably born dead
or very weak
No
probably born dead
or very weak
yes
any signs of
bleeding?
yes
have fat reserves
been used?
yes
probably starved
No
is milk present in
intestine?
yes
yes
yes
yes
probably dingoes
or dogs
probably feral pigs
probably birds
of prey
probably healthy
when killed –foxes or
dogs likely cause
No
probably starved
Figure 22: A decision tree for determining the cause of lamb death (source WA Department of Agriculture 2001)
Monitoring feral pig impacts
43
high
medium
low
absent
Monitoring crop damage
crop damage can be visually estimated by walking
through the crop and locating areas where feral pigs
have been active. this is most often in areas close
to refugia (caley 1999). the area of damage can be
estimated by pacing its dimensions and assigning a
visual damage rating, an estimate of the percentage
reduction in the number of standing plants, and
hence harvestable plants (caley 1993b). the overall
estimate of damage to the crop is calculated as
the sum of the products of the area damaged by
the proportion of plants knocked down by feral
pigs. for example, in a 100 ha crop of corn in the
northern territory, it was estimated that 7 ha had
been completely destroyed by feral pigs and the
yield from the remaining crop was 300 tonnes (caley
1993b). the available crop was therefore 93 ha and
the yield was 3.2 tonnes ha–1 (300/93). from this it was
assumed that feral pigs destroyed 22.4 tonnes of grain
(7 ha × 3.2 tonnes ha-1). See Mitchell and dorney (2002)
for examples of a technique to calculate crop damage.
Monitoring vulnerable species:
fauna and flora
feral pigs have been implicated in the decline of many
animal and plant species in australia, but further
studies are required to review the level of impact
on these and other nationally listed threatened
species and ecological communities (department of
environment and heritage 2003). despite reports of
feral pigs destroying nests and eating eggs and chicks
of some ground-nesting birds such as cassowaries
(Casuarius casuarius), brush-turkeys (Alectura lathama)
and scrubfowl (Megapodius reinwardt) (hopkins and
graham 1985; crome and Moore 1990; Mitchell 1993),
44
Monitoring techniques for Vertebrate pests – feral pigs, Bruce Mitchell & Suzanne Balogh
Figure 23: Feral pig density (source NSW DPI)
issues such as types of prey actually eaten, rates of
predation, the density, status of prey, and whether
or not predation is density dependent need to be
addressed (choquenot et al. 1996). Similarly, the
impact of competition for food with native animals
needs to be evaluated.
Mapping feral pig damage and density
Mapping the distribution of feral pig problems
and their population density over a given area
such as an individual property or region, facilitates
the development of feral pig management plans
(choquenot et al. 1996). regular updating of
these maps allows for the modification of existing
management plans. these maps can be as simple
as hand-drawn property charts or more detailed
and accurate topographic maps generated with
giS software. the choice of map type will depend
largely on the scale of the area involved, the cost
and availability of the technique, and the extent
of the feral pig problem (choquenot et al. 1996).
these maps may include the locations of poison
baiting trails, areas of feral pig damage and refuge
habitat of feral pigs to indicate gaps in the coverage
of control programs; and they may include refugia
habitat and the preferred habitat of endangered
species. these maps can be used as part of the overall
property, local or regional management plan and to
assess progress over time. at a larger scale, the nSw
department of primary industries has surveyed nSw
rural lands protection Boards and nSw national parks
and wildlife rangers to develop State-wide maps of
pest species distribution and abundance (west and
Saunders 2003).
it is important to make new maps with each new
assessment. in this way new maps can be compared
with the previous map to evaluate the current
management.
information to include on maps is:
•­ a scale and north (magnetic/grid)
•­ name and location of property
•­ size of property
•­ property boundaries, permanent fences, gates,
and roads
•­ topographic features such as watercourses, hill
contours, rock outcrops
•­ refugia habitat: vegetation other than pasture
and crop such as woodland or riverine
•­ lambing paddocks
•­ feral pig abundance estimates using spotlight
indexes
•­ areas of feral pig damage with a scale of damage
such as number of lambs lost
•­ type of agricultural or other activities on this and
adjoining properties
• watering and wallowing points
• other feral pig sign.
Monitoring feral pig impacts
45
46
Monitoring techniques for Vertebrate pests – feral pigs, Bruce Mitchell & Suzanne Balogh
suMMary of fer aL pig
Monitoring techniques
the various feral pig abundance and impact monitoring techniques discussed in this manual, and their
advantages and disadvantages, are listed in table 5. table 6 compares the different monitoring techniques.
Table 5. Advantages and disadvantages of the monitoring techniques discussed in this manual
moNitoriNg techNique
advaNtages
disadvaNtages
Aerial survey
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Catch per unit effort
can survey large spatial areas
can sample more than one species at the same time
can be incorporated into control program
removes feral pigs
Capture–recapture
• accurate estimate of abundance
• other information may be collected at the same time
(e.g. home range)
Radio-telemetry
• other information may be collected at the same time
(e.g. home range)
GPS and satellite telemetry
• improved ability to monitor animals in rugged and remote
terrain
• reductions in travel and field work time
• no need to handle feral pigs
• can be incorporated into control program
• inexpensive
• can be used in difficult terrain
• sampling schedule flexible
• quick and simple
• inexpensive
Bait-take
Dung counts
Spotlight count
DNA sampling
Track counts
•
•
•
•
•
•
target animal doesn’t need to be sighted
improved accuracy of scat counts
density estimates possible
can monitor several different species at the same time
quick and simple
target animal doesn’t need to be sighted
expensive
reliable correction factors are not always available
expensive
labour intensive
time-consuming
trap-shy animals undetected
expensive
labour intensive
time-consuming
trap-shy animals undetected
expensive
labour intensive
time-consuming
expensive
accuracy of fixes can be variable
• bait-shy animals undetected
• time-consuming
• inappropriate for monitoring short-term changes
• counts can be highly variable between observers
• sightability can be affected by height of pasture, vegetation
or habitat type
• unreliable method in wet and windy conditions
• difficult to compare counts between variable weather
conditions
• expensive
• correct storage important
• time-consuming
• unreliable method in wet and windy conditions
• unknown relationship to density
• road-based sampling = non-representative coverage of area
• potential for interference
(e.g. trampling from vehicles or humans)
Summary of feral pig Monitoring techniques
47
moNitoriNg techNique
advaNtages
disadvaNtages
Sign
•
•
•
•
•
•
• inappropriate for monitoring short-term changes
Lamb predation
Vulnerable flora and fauna
species
Cost monitoring
inexpensive
can be used in difficult terrain
sampling schedule flexible
can indicate the successfulness of control measures
simple
vulnerable species may be easier to monitor than feral pigs
• inexpensive
• can be incorporated into existing economical management
• unreliable indexes
• difficulties in determining whether abundance is related to
feral pig density
• assumed relationship with feral pig abundance
• costs increase each year: need to account for inflation
Table 6. Feral pig monitoring techniques ranking table
48
labour
start-up cost
specialised
equipmeNt
Moderate
humaNeNess
oh&s risk
High
expertise aNd
traiNiNg
Moderate
Aerial surveys
High
High
Moderate
Catch per unit effort
High
Moderate
Moderate
Moderate
Low
Moderate
Capture–recapture
High
Moderate
Moderate
Moderate
Low
Moderate
Radio- telemetry
High
High
High
High
Moderate
Low
Satellite & GPS telemetry
Low
High
Low
High
Moderate
Low
Index-removal-index
High
Moderate
Moderate
Moderate
Moderate
Moderate
Bait-take
Moderate
Low
Low
Low
Moderate
Low
Dung counts
High
Low
Low
Low
High
Low
Distance sampling
High
Moderate
Moderate
Moderate
High
Low
DNA sampling
Moderate
High
Low
High
High
Low
Track counts
High
Moderate
Low
Low
High
Low
Monitoring techniques for Vertebrate pests – feral pigs, Bruce Mitchell & Suzanne Balogh
gLossary
Angle board
Panel trap
a large protractor used to aid is estimating angles.
a trap that is usually built on site and has rigid panel sides
that lock together.
Bait-station night
the number of bait stations multiplied by the number of
nights of baiting.
Canid
Member of the canidae family of carnivorous animals.
includes wolves, jackals, foxes, coyotes, domestic dogs and
dingoes.
Catling Index
Petersen estimate
a method of estimating population abundance on the
basis of the ratio of marked to unmarked individuals
within a population. it assumes that the population is
closed to immigration and emigration and assumes that
population size is related to the number of marked and
released animals in the same way that the total caught at a
subsequent time is related to the number recaptured.
the percentage of station nights with animal tracks.
Polymerase chain reaction (PCR)
Dispersal
a powerful method of amplifying specific dna segments
that exploits certain features of dna replication.
Movement of an animal from its place of birth to another
area where it reproduces. this process is important
to population dynamics, because dispersal is when
immigration and emigration occur.
Index of abundance
a relative measure of the abundance of a species
(for example, catch per unit effort).
Leslie technique
a method of estimating population, based on the principle
that the catch rate is proportional to the population size.
Microsatellite
repeated stretches of short sequences of dna used as
genetic markers to track inheritance in families. they
are short sequences of nucleotides (e.g. atgc) that are
repeated over and over again in tandem.
Mitochondrial DNA
the genetic material of the mitochondria, the organelles that
generate energy for the cell. Mitochondrial dna is passed
down from the mother to all her children, males and females.
Octal
Presence/absence study
an approach to determining diversity in an ecosystem by
determining what species are present in the ecosystem.
Quadrat
an ecological sampling unit that consists of a square frame
of known area. the quadrat is used for quantifying the
number or percentage cover of a given species within a
given area.
Silo trap
a roll of mesh staked in a rough circle with an entrance to
form a trap.
Transect
a straight line placed on the ground along which ecological
measurements are taken. a fixed transect is one that is set
out for use in all further surveys so that valid comparisons
with prior surveys can be made.
Trap night
the number of traps placed out multiplied by the number
of nights of trapping.
a measure of cloud cover. a completely covered sky is
scored as 8 out of 8 octals.
glossary
49
50
Monitoring techniques for Vertebrate pests – feral pigs, Bruce Mitchell & Suzanne Balogh
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