Download Seasonality of a Diverse Beetle Assemblage Inhabiting Lowland

THE JOURNAL OF TROPICAL BIOLOGY AND CONSERVATION
BIOTROPICA 41(3): 328–337 2009
10.1111/j.1744-7429.2008.00477.x
Seasonality of a Diverse Beetle Assemblage Inhabiting Lowland Tropical
Rain Forest in Australia
Peter S. Grimbacher1,2,4 and Nigel E. Stork3
1 Department
of Resource Management and Geography, Melbourne School of Land and Environment, University of Melbourne, Melbourne,
Australia
2 School
of Marine and Tropical Biology, James Cook University, PO Box 6811, Cairns 4870, Queensland, Australia
3 Burnley
Campus, 500 Yarra Boulevard, Richmond, VIC 3121, Melbourne, Australia
ABSTRACT
One of the least understood aspects of insect diversity in tropical rain forests is the temporal structuring, or seasonality, of communities. We collected 29,986 beetles
of 1473 species over a 4-yr period (45 monthly samples), with the aim to document the temporal dynamics of a trophically diverse beetle assemblage from lowland
tropical rain forest at Cape Tribulation, Australia. Malaise and flight interception traps were used to sample adult beetles at five locations at both ground and canopy
levels. Beetles were caught throughout the year, but individual species were patchy in their temporal distribution, with the 124 more abundant species on average being
present only 56 percent of the time. Climatic variables (precipitation, temperature, and solar radiation) were poorly correlated with adult beetle abundance, possibly
because: (1) seasonality of total beetle abundance was slight; (2) the peak activity period (September–November) did not correspond to any climatic maxima or
minima; or (3) responses were nonlinear owing to the existence of thresholds or developmental time-lags. Our results do not concur with the majority of tropical insect
seasonality studies suggesting a wet season peak of insect activity, perhaps because there is no uniform pattern of insect seasonally for the humid tropics. Herbivores
showed low seasonality and individual species’ peaks were less temporally aggregated compared to nonherbivores. Canopy-caught and larger beetles (> 5 mm) showed
greater seasonality and peaked later in the year compared to smaller or ground-caught beetles. Thus seasonality of adult beetles varied according to the traits of feeding
ecology, body size, and habitat strata.
Key words: Coleoptera; feeding guild; phenology; spatiotemporal dynamics; temporal partitioning; time-series; vertical stratification; Wet Tropics.
WHY TROPICAL FORESTS ARE SO RICH IN SPECIES, particularly insects, has puzzled many for decades (Godfray et al. 1999). Tropical
insect assemblages are renowned for their spatial and temporal complexity and thus remain poorly understood both taxonomically and
ecologically (May 1997, Basset et al. 2003; but see Novotný et al.
2002a). In recent years considerable progress has been made to understand ‘the pieces of the diversity jigsaw puzzle’ (Kitching 2006,
Stork 2007a) through key studies of tropical insect host-specificity,
and beta-diversity (Novotný et al. 2002b, 2007; Dyer et al. 2007).
One of the less well-studied areas is the temporal dynamics of insects in tropical forests (Wolda 1988). Such studies documenting
intra- and interannual population dynamics of multi-species insect
assemblages are important because they provide a basic knowledge
baseline of the ecological processes operating within tropical rain
forests. They can also inform whether species are genuinely rare or
rare because they are only able to be sampled at particular times
of the year. This information is particularly important for those
monitoring faunal responses to environmental change, such as climate change. Furthermore, understanding the temporal dynamics
of insects is important because of the roles insects play in mediating
many ecological processes (Miller 1993, Godfray et al. 1999, Wall
& Moore 1999).
If there is low host specificity (Novotný et al. 2002b, but
see Dyer et al. 2007) and spatial turnover of tropical rain forest
insects (Novotný et al. 2007), other possible reasons to explain the
Received 6 March 2008; revision accepted 25 Augugst 2008.
author; e-mail: [email protected]
4 Corresponding
328
concentration of insect biodiversity in the tropics might need to
be considered. One such reason is the partitioning of resources
through time. Insects with similar ecological traits may coexist by
being abundant or active at different times of the day or year, thereby
avoiding competition (Wolda & Fisk 1981, Tylianakis et al. 2005),
although this idea has been little explored to date.
Problems in establishing and maintaining long-term (multiyear) sampling in the tropics and difficulties in sorting large numbers of often taxonomically intractable taxa have meant that there
have been few long-term studies into the temporal dynamics (often
referred to as seasonality) of multi-species assemblages of tropical
insects, with the Central American studies of Wolda (1978, 1988,
1989) being the exception. While short-term studies on a few,
concurrently studied species are useful, extrapolating conclusions
to other species with diverse life histories is problematic and thus
many assumptions about tropical insect seasonality exist (Wolda
1988).
In practice, there are few generalizations that can be made
about insect seasonality in the tropics and tropical insects can show
a wide array of seasonal patterns, even at the same site (Wolda
1988). Species can be aseasonal, occurring throughout the year, can
show one or more seasonal peaks, and those peaks can be short and
sharp or spaced over a broad period (Wolda 1988). In the highly
seasonal temperate forests there are a range of life-history strategies
to deal with the large differences in temperature and rainfall and
consequent availability of resources during the year. Some adult
insects enter a state of reproductive dormancy in the winter months
and sometimes during hot dry periods of the summer. Cues that
C 2008 The Author(s)
C 2008 by The Association for Tropical Biology and Conservation
Journal compilation Seasonality of Rain Forest Beetles
control the switching from one state to another or from one life
stage to the next are thought to include photoperiod, temperature,
and moisture (Wolda 1988, Tauber et al. 1998 but see Didham &
Springate 2003).
Despite the usually low intraannual variation in temperature
and photoperiod in the tropics, the climate of most tropical rain
forests is distinctly seasonal particularly with respect to precipitation (Leigh 2004). Consequently tropical insect assemblages have
shown strong seasonal patterns, more often associated with changes
in precipitation rather than temperature (Denlinger 1980, Wolda
1988, Frith & Frith 1990, Hill 1993). A majority of tropical
studies covering a wide range of insect groups support the classic view of tropical entomologists that insect activity and diversity
peak during the wettest part of the year (Owen & Chanter 1970,
Wolda 1978, Denlinger 1980, Smythe 1982, Frith & Frith 1985,
Hammond 1990, Hill 1993, Novotný & Basset 1998, DeVries &
Walla 2001) rather then the driest (Boinski & Fowler 1989, Basu
1997, Dibog et al. 1998). However, the cues for changes in activity and reproductive behavior can vary even among closely related
species (Jones & Rienks 1987), and can be relatively subtle. For
example, in the virtually aseasonal African equatorial rain forests of
the Democratic Republic of Congo, a change in soil temperature
of 0.9◦ C is believed to trigger the onset of reproductive dormancy
in the majority of ground beetle species (Carabidae) and hence the
driver of seasonal abundance patterns for these beetles (Paarmann
1976).
The paucity of long-term, multi-species assemblage studies
means that we have been unable to answer such basic questions as:
(1) For how long do insect species remain active? (2) When are they
most active? (3) Is the seasonality of insects correlated with climatic
seasonality? (4) Does the seasonality of insects vary according to
ecological traits such as feeding ecology, body size, and habitat
strata? Answering such questions is essential if we are to better
understand spatiotemporal dynamics of tropical insect communities
and predict impacts of climate change. For this reason we sampled
adult beetle species assemblages at monthly intervals over a 4-yr
period from a lowland rain forest in northeastern Australia, with a
view to answering the four questions above.
METHODS
STUDY SITE.—We conducted our study in tropical lowland rain
forest at the Australian Canopy Crane Research Facility (16◦ 17 S,
145◦ 29 E; 40 m asl), 3–4 km south-west of Cape Tribulation
Queensland, Australia (Stork 2007b). This site lies within the Daintree subregion of the Wet Tropics World Heritage Area, an area
recognized as being particularly species rich (Nix 1991). The rain
forest at the site is classified as complex mesophyll vine forest type
1a (Webb & Tracey 1981). There are 657 individual trees (> 10 cm
dbh) comprising 70 species in 32 families in the almost 1-ha area
below the canopy crane (Laidlaw et al. 2007). The site is flanked to
the west by coastal ranges rising to > 1300 m and by the Coral Sea
to the east. Extensive Quaternary alluvia underlie the area.
329
We used three different sources to present climate data for the
study site. Precipitation data were recorded from the Cape Tribulation weather station situated < 1 km from the site, for the duration of the study (March 2000–February 2004). Temperature was
recorded from equipment at the crane site. Solar radiation data
were sourced from satellite imagery (cloud reflectance) processed by
the Bureau of Meteorology from the Geostationary Meteorological Satellite GMS-5. For these data there were some missing data
points spanning all of 2002 and some months in 2001 and 2003.
We dealt with this missing data by modeling the day-to-day relationship of solar radiation between Cairns and Cape Tribulation for the
time period 1990–2006 where data existed (y = 0.817x + 3.592;
R2 = 0.71, P < 0.0001, N = 3295). The missing values for Cape
Tribulation were then predicted using the Cairns data for the time
period in question and the derived model.
The region is also subject to tropical storms and cyclones, the
most recent to directly affect the area being Cyclone Rona in 1999,
a Category 3 Cyclone with winds up to 190 kph that affected the
study site prior to the commencement of this study (Stork 2007b).
Damage to the structure of the forest included the felling of trees
and branches and a reduction in canopy height and cover. However,
recovery was very rapid and canopy closure was re-attained after
only a few years.
BEETLE SAMPLING PROTOCOL.—Beetles were chosen as suitable insect group to study because they are the most species-rich insect
order (Nielsen & Mound 2000) and because species from different
families encompass a wide range of feeding, body size, and lifehistory strategies (Lawrence & Britton 1991). Adult beetle flight
activity was measured using a combined Malaise and Flight Intercept Trap (FIT; see Stork & Grimbacher 2006). This style of trap
is very efficient at capturing winged beetles but is poor at sampling
flightless ones that are unlikely to crawl into collecting containers.
Malaise–flight interception traps measure the flight activity
of adult beetles. Therefore data obtained from such samples are
unable to inform us of the seasonality of nonactive adults or immature stages. By quantifying flight activity, we are measuring adult
beetles engaged in foraging for food and microhabitat resources,
searching for mates, avoiding predation and potentially dispersing
or migrating (Johnson 1966). Even though we cannot determine
the exact reason why beetles are flying, we believe that this type
of data validly describes the seasonal dynamics beetle assemblages
because most adult beetles are fairly long-lived. Unlike many fragile
insects, adult beetles are heavily sclerotized with robust mouthparts and well-developed digestive systems that predispose them for
extended longevity (Carey 2001). This longevity can range from
several weeks through to many years (Carey 2001) and means that
adult beetles must actively forage (including flying) to find food and
resources fairly regularly throughout their adult life span. Thus, we
believe that sampling flying adult beetles measures more than just
mate searching or migratory behavior. We also acknowledge that
measuring fluctuations in activity may not always reflect real variations in abundance. For example, this may occur when insects try
to compensate for adverse environmental conditions through extra
foraging activity.
330
Grimbacher and Stork
Five locations, each 40–60 m apart were selected for sampling,
within or near the circumference of the Australian Canopy Crane.
At each location one combined Malaise–FIT trap was located on
the ground and another was suspended in the canopy. Canopy
traps were hoisted 15–20 m up into the treecrowns on ropes and
pulleys. Equal sampling effort went into the canopy and the ground
because each stratum contains distinct species assemblages (Stork
& Grimbacher 2006).
Traps were run for 2 wk/mo from March 2000 to February
2004 as near as could be arranged given the remoteness of the
site and problems with inclement weather. Samples were missed
from July and October 2001, March 2002 and May 2003, while
two samples were obtained early and late in August 2000. This sampling strategy generated five replicate Canopy FIT, Canopy Malaise,
Ground FIT, and Ground Malaise samples, during all 45 sampling
periods. To simplify analyses and maximize statistical power, samples
from different trapping methods (Malaise and FIT), and replicate
traps at the five sites were pooled.
All beetles were mounted, labeled, and sorted first to family or
subfamily and then to morphospecies. Both authors were involved
in sorting all specimens to morphospecies to provide two taxonomic
opinions. We used morphospecies as surrogates for species because
there were so many species, many of which are undescribed (Stork
et al. 2008).
STATISTICAL ANALYSIS.—We tested if the temporal distribution
of beetles was clumped or random over the 4-yr sampling period with the Runs test. This nonparametric test determines
whether the sequence of values above and below the median
is random (no seasonality exists) or is aggregated (seasonality
exists; SPSS v. 13.0, 2004, Chicago, Illinois). For this analysis, the four missing values in the 4-yr time series were substituted with the means of adjacent values. Beetle abundance
was used because it was thought to best represent beetle activity. Note that total beetle abundance and total species richness
were strongly correlated over the 45 sampling periods (R2 = 0.74,
P < 0.0001). The Runs test was performed on total beetle abundance and the abundance of beetles grouped by feeding ecology,
body size, or whether they were caught from the canopy or the
ground. Feeding guilds were: predators, herbivores, xylophages,
fungivores and saprophages. Body size categories were < 2 mm,
2–5 mm, and > 5 mm. Feeding guild and body size data were
sourced from Grimbacher and Stork (2007).
The existence of temporal autocorrelation in the number of
beetle species and individuals caught was analyzed with the autocorrelation function described by the following equation:
n−k
rk =
(x i − x̄ )(x i+k − x̄ )
i=1
n
,
(x i − x̄ )
2
i=1
where x̄ is the average of the n observations. This procedure tests
the strength of the correlation of the data against itself for in-
creasing time-lags. The four missing values in the 4-yr time series
were substituted with the means of adjacent values. We explored
the relationship between climate and beetle abundance with linear
regression. We tested total beetle abundance and the abundance
of beetles grouped by feeding ecology, body size, or whether they
were caught from the canopy or the ground against three climatic
variables; total monthly precipitation, mean daily maximum temperature, and mean daily solar radiation. Mean daily maximum
temperature and mean daily minimum temperature were strongly
correlated (R2 = 0.67, P < 0.0001, N = 48) so we used the former.
Because these time-series data were both positively and negatively
temporally autocorrelated, depending on the monthly time lag (see
Results), before conducting regressions, the data were seasonally
adjusted by removing periodicity operating at a 12-mo cycle. In
this procedure the four missing values in the 4-yr time series were
substituted with the means of adjacent values and then the ‘seasonal
decomposition’ function in SPSS was used to model periodicity. The
residuals from this analysis (excluding substituted missing values)
were used in subsequent regression analyses.
Descriptive statistics were performed on the more abundant
species with ≥ 45 individuals. This cutoff was chosen as there were
45 sampling periods. Circular statistics (Batschelet 1981) were used
to quantify the period of greatest activity for individual species. For
the more abundant species, the peak within-year abundance period
was expressed as an algebraic vector: φ, whereby
φ = arctan (y/x ) if x > 0
or φ = 180◦ + arctan (y/x ) if x < 0;
and
x=
n̄ i cos φ i , y =
n̄ i sin φi ,
n̄ i is the mean monthly abundance (across the 4 yr) for month i and
φ is the midpoint of month i expressed as an angle (0–360◦ ). For
these calculations, monthly values were based on monthly means
from the 4-yr sampling period to account for the slightly unequal
monthly sampling across years (see above). Data were presented for
all species analyzed and grouped according to feeding ecology and
body size. To examine possible seasonal variation among species
sampled from the canopy or the ground, additional analyses were
conducted for species sampled separately from each stratum. In
this last analysis, the same species could appear in both groups
provided there were ≥ 45 individuals encountered separately from
each stratum. We also calculated the mean period of activity (mean
vector and 95% CIs of total beetle abundance) and compared beetles
grouped by the ecological traits listed above.
To quantify how long species were active within the study
period, we tallied the number of times species were detected among
the 45 temporal samples (for species with ≥ 45 individuals). Counts
were performed for the total number of samples, and for the number
of consecutive samples where a species was present.
Seasonality of Rain Forest Beetles
331
FIGURE 1. Total monthly precipitation (bars), mean daily minimum and maximum temperature (solid lines) and mean daily solar radiation (dashed line) for Cape
Tribulation for the study period March 2000–February 2004.
RESULTS
The climate of the site is distinctly seasonal (Fig. 1). Precipitation
data for the duration of the study (March 2000–February 2004),
showed that there is usually some rain throughout the year (Fig. 1).
However, most rain occurs in the ‘wet season’ of November–April,
although the onset, duration, and cessation of the wet season can
vary by several months. The 50-yr average (to 1995) annual precipitation at Cape Tribulation is 3926 mm (Hopkins et al. 1996). Mean
daily temperature records show distinct seasonality, with the mean
daily temperature fluctuating by as much as 5◦ C from the warmest to
the coldest months (Fig. 1). Mean daily solar radiation data for Cape
Tribulation also show considerable within-year variation in solar
radiation (Fig. 1). All three climatic variables (solar radiation, temperature, and precipitation) were temporally intercorrelated, with
FIGURE 2.
the yearly peak in precipitation preceded by a peak in temperature, which was itself preceded by an earlier peak in solar radiation
(Fig. 1). Linear regressions testing the intercorrelation of these three
variables at time lags of up to 5 mo showed that the strongest correlations between mean daily solar radiation and mean daily maximum
temperature was at a 1-mo time lag (R2 = 0.65, P < 0.0001,
N = 48) and for mean daily solar radiation and total monthly precipitation it was 3 mo (R2 = 0.36, P < 0.0001, N = 48). The
strongest correlation between mean daily maximum temperature
and total monthly precipitation was at a 1-mo time lag (R2 = 0.28,
P < 0.0001, N = 48).
A total of 29,986 beetles sorted to 1473 morphospecies and
77 families were collected over the 4-yr period. Beetles were caught
throughout this time and although they did show peaks and troughs
in activity each year (Fig. 2), the runs test on total beetle abundance
Total number of individuals (bars) and species (stars/ line) caught across the 45 sampling periods (March 2000–February 2004) using 10 Malaise/FIT
traps at Cape Tribulation, Australia.
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Grimbacher and Stork
TABLE 1. Abundance of beetle groups and results of the runs test (P-values), testing whether the abundance of beetles captured from 45 sampling periods during March
2000-February 2004 using10 FIT/ Malaise traps at Cape Tribulation, Australia was temporally aggregated. Pearson’s correlation coefficients, (r-values) are also
presented for comparisons among climatic variables and beetle abundance groups over the same time period. For the Runs test, values in bold are significant at
P < 0.05. Note that correlations have not been adjusted for multiple comparisons or temporal autocorrelation.
Beetle grouping
Total abundancea
Runs test (P-value)
Total monthly
precipitation (r-value)
Mean daily maximum
temperature (r-value)
Mean daily solar
radiation (r-value)
−0.26
−0.31∗
−0.37∗
0.27
0.09
0.12
0.33∗
0.40∗∗
0.45∗∗
−0.19
−0.20
0.06
−0.47∗∗
Saprophage
Fungivore
Predator
1493
5724
3002
0.0627
0.0003
< 0.0001
Herbivore
Xylophage
7445
6099
0.1892
0.0292
< 2 mm
2–5 mm
> 5 mm
10007
17045
2924
0.0022
0.0131
< 0.0001
−0.35∗
−0.34∗
−0.09
−0.03
−0.03
0.39∗∗
0.36∗
0.36∗
0.50∗∗∗
Canopy
Ground
All beetles
14473
15513
29986
0.0003
0.1892
0.1892
−0.27
−0.38∗
−0.37∗
0.20
−0.19
−0.00
0.55∗∗∗
0.21
0.42∗∗
0.27
−0.12
a Note that groups do not necessarily add up because not all beetle families could be allocated into feeding guilds and the body length of some species could not be
measured (see Grimbacher & Stork 2007).
∗ P < 0.05, ∗∗ P < 0.01, ∗∗∗ P < 0.001.
suggested no significant temporal aggregation (Table 1). However,
when the assemblage was divided into groups corresponding to feeding ecology, body size, and strata caught, most groupings showed
significant seasonality (Table 1). The exceptions were the herbivores
and ground-caught beetles, while the saprophages were marginally
significant. The autocorrelation function analysis showed temporal autocorrelation within the data operating at various timescales.
Neighboring temporal samples (1–2 mo) were positively autocorrelated, samples 5–7 mo apart were negatively autocorrelated,
while samples spaced 11–12 mo apart were positively autocorrelated (Fig. S1).
None of the correlations between beetle abundance residuals
and total monthly precipitation, mean daily maximum monthly
temperature, and mean daily monthly solar radiation were significant (results not presented). We suspected that this was because
the process of accounting for temporal autocorrelation may have
been overly conservative. Therefore we repeated the tests, correlating beetle abundance directly with the three climatic variables
(Table 1) without accounting for temporal autocorrelation. By
conducting these subsequent analyses we acknowledge the risk of
making type I statistical errors. However, we believe that this risk
should not prohibit exploring the existence of potential patterns
provided that the results are interpreted with caution (see Roback
& Askins 2005). From these subsequent analyses we found that
there was a fairly weak negative relationship between total beetle abundance and total monthly precipitation (Table 1; Fig. 3A),
no significant relationship with mean daily maximum temperature (Table 1; Fig. 3B), and a weak positive correlation with mean
daily solar radiation (Table 1; Fig. 3C). For the most part individual beetle groups followed these same trends however, there were
some subtle but interesting differences with the xylophages and
larger beetles (> 5 mm) deviating the most from the general trends
(Table 1).
There were 124 species (with ≥ 45 individuals) on which we
could conduct further analyses. These species account for 21,963 individuals (73% of the total abundance and 8% of the species). Analysis of species’ peak abundance period showed that the within-year
distribution was heavily skewed, with most species (60%) peaking
during September–November (Fig. 4A). By contrast, only 5 percent
of species peaked during February–April. Like the correlations with
climate, there were some intriguing differences among the different
beetle groups. Among feeding guilds, 84 percent of predator species
peaked in abundance during October and November, whereas the
distribution for herbivore species was more even, with species peaking throughout the year (Fig. 4B). These results corroborate the:
(1) tests for seasonality (Table 1), which showed that the abundance
of predators was significantly seasonal while that of herbivores was
not; and (2) larger confidence intervals for the herbivores, relative
to other feeding guilds (Fig. 5). Xylophages peaked several months
earlier than beetles with different feeding ecologies (Fig. 5) probably
because there was a group of xylophage species that peaked in July.
Larger beetle species (> 5 mm) only peaked in abundance during October–January, whereas smaller species peaked throughout
the year (Fig. 4C). The mean period of activity for larger beetles (>
5mm) was later than for smaller beetles (Fig. 5). More canopy caught
beetle species peaked in abundance during November, whereas the
peak in ground-caught beetle species was during October (Fig. 4D).
The overall mean period of activity for canopy-caught beetles was
significantly later than for the ground-caught beetles (Fig. 5). On
average, the most abundant species were present in 25 of the 45 samples (median = 25, SD = 7.7), but only ten consecutive samples
(median = 7.5, SD = 7.8; Fig. S2).
Seasonality of Rain Forest Beetles
FIGURE 3.
333
Plots of the total number of beetle individuals caught against:
(A) total monthly precipitation; (B) mean daily maximum temperature; and (C)
mean daily solar radiation.
DISCUSSION
The results from this study concur with those of other rain
forest insect studies that observed year-round insect activity
(Lowman 1982, Smythe 1982, Wolda 1988, Hammond 1990,
Novotný & Basset 1998, DeVries & Walla 2001, Novotný
et al. 2002a) although studies conducted in other Queensland
rain forests with more seasonal climates (Jones & Rienks 1987,
Frith & Frith 1990, Basset 1991, Hill 1993, Seymour & Jones
2000) have shown stronger within-year differences in abun-
FIGURE 4.
Species’ distribution (for species with ≥ 45 individuals) for the
peak monthly activity calculated as an algebraic vector for: (A) all species (N =
124); (B) species grouped by feeding guild (N = 99); (C) species grouped by
body size (N = 124); and (D) species caught from the canopy and the ground
(N = 82). Data are based on 4-yr monthly means. In (D) circular statistics were
performed on species with ≥ 45 individuals separately for each strata.
dance and species richness than those observed in this study.
Tests for seasonality of total beetle abundance suggested no significant seasonality existed despite strong climatic seasonality.
However, repeated peaks in adult beetle activity were evident in
each of the 4 yr when this study was conducted, a result that was
corroborated by the peak activity analyses and the autocorrelation
334
Grimbacher and Stork
FIGURE 5. Period of mean activity (and 95% CIs) for beetles grouped by feeding ecology, body size, and whether caught from the canopy or the ground. Note that
comparisons are only valid within these groups (color coded).
function analysis. Furthermore, individual adult beetle species were
not evenly distributed through time and were present for only 56
percent of the duration of the study, with only 22 percent of that
time being consecutive presence. This contrasts with studies conducted in climatically less seasonal rain forests that show that Lepidoptera (Novotný et al. 2002a, Hamer et al. 2005) are active for
longer periods of the year. Our result has important implications
for those targeting particular species, such as indicator species for
environmental monitoring, as it suggests that there is a high chance
of missing target species, with one sampling period, even if the target species are relatively common and several traps are in concurrent
use.
Surprisingly, climate was not strongly correlated with beetle
abundance patterns, in spite of clear seasonality among climatic
variables and a relaxation of statistical rigor among correlative tests.
There are several possible reasons to explain this result, the first
of which might be attributed to the low seasonality for the whole
beetle assemblage. Another reason may be because more species
were most active on, and either side of the month of October,
and this period does not correspond to the maxima or minima
of any of the climatic variables (see Fig. 1). We did not conduct
any correlations among beetle abundance and climatic variables
with time lags because interpreting such tests would have been
confounded by the intercorrelation of the climatic variables at times
lags of 1–3 mo. If the adult beetles are responding directly to climate,
our results suggest that it is not in a simple linear way and it may
not be due to any one particular variable. Insects are most likely
to display nonlinear or threshold-type responses (Tauber & Tauber
1976, Chown & Gaston 1999) and multiple climatic cues may
operate in synergies.
Both climatic and chemical cues have been suggested as possible
factors causing insect seasonality in the tropics (Wolda 1988, 1989;
Tauber et al. 1998; Didham & Springate 2003), and this remains
a controversial topic. Didham and Springate (2003) suggest that
many species may respond to biotic triggers such as leaf flush and
chemical cues associated with seasonal changes in plants, which in
themselves are a response to more direct climatic changes. Several
studies have shown that insect abundance peaks with leaf flush and
flowering (Lowman 1982, Basset 1991, Kato et al. 1995, Intachat
et al. 2001, Richards & Coley 2007). There is some circumstantial
evidence that the peak period of flowering in the northern lowlands
of the Wet Tropics (an area that includes our study site; Boulter
et al. 2006) corresponds with the peak beetle activity period in our
study. The peak period of flowering and fruiting of Normanbya
normanbyi, a common palm at our study site, is also at this time of
year (Inkrot et al. 2007). Thus the beetle activity peaks in our study
may be caused by the seasonality of biological resources although the
nature of our data precludes us from drawing any such conclusions.
Consideration of the whole life cycle of insects, including the
larval stages may be necessary to explain the insect seasonality patterns observed among the adults. Each of the beetle life-history
stages of egg, larvae, pupae, and adult need a minimum time to
complete development before proceeding to the next stage. Once
development proceeds to the next life-history stage it cannot be
reversed. For example, if a certain climatic (or chemical) threshold
is reached that triggers pupal emergence, the adults have to make
do with the environmental conditions even if they subsequently
become suboptimal (Tauber & Tauber 1976). This feature of lifehistory behavior may also explain the observed poor correlations
with climatic parameters. The environmental pressures on the larval
life-history stages could also be very important in explaining the seasonality patterns of the adults. For example resource constraints or
the abundance of predators may control larval abundance (Godfray
& Hassell 1987, Richards & Coley 2007), which would obviously
limit the number of insects emerging as adults.
We speculate that the larvae of the beetle species in this study
may show quite different seasonal patterns to those observed by the
adults (but see Basset 1991). Larvae may display their abundance
peak after the adults have mated and the females laid eggs. For
most species at Cape Tribulation this could be after the October
Seasonality of Rain Forest Beetles
peak in adult activity, during the wet season. Testing this hypothesis
will prove difficult given that a large proportion of the adult beetle
species in this assemblage are undescribed (Stork et al. 2008) and
that the larvae are even less well known.
Interestingly our results do not concur with the majority of
tropical insect seasonality studies suggesting that the wet season is
the peak time of activity and diversity of adult insects (Owen &
Chanter 1970, Wolda 1978, Denlinger 1980, Smythe 1982, Frith
& Frith 1985, Hammond 1990, Hill 1993, Novotný & Basset 1998,
DeVries & Walla 2001), although a small number of other studies
have observed reduced insect numbers in the wet season (Boinski
& Fowler 1989, Basu 1997, Dibog et al. 1998, Hill et al. 2003)
or a prewet season peak similar to our study (Buskirk & Buskirk
1976). This may be because the Cape Tribulation site has a very high
rainfall compared to other parts of the Australian Wet Tropics and
to many other tropical rain forest research sites around the world,
which typically receive 2500–3000 mm rainfall a year, although it is
comparable to La Selva research station in Costa Rica, el Choco and
the Amazon basin of Ecuador (Leigh 2004). Interestingly Janzen
(1973) and Richards and Windsor (2007) observed spatiotemporal
variation in the abundance of rain forest insects, with the more
moist (or shaded) sites having a peak in abundance during the dry
season, while the drier sites had peaks during the wet season. Thus
it is quite plausible that no uniform pattern of insect seasonally
exists for the humid tropics (Wolda 1988) owing to the large spatial
variability in precipitation regimes (Sombroek 2001, Leigh 2004).
A further argument against the existence of a uniform pattern is
that insects with varying ecologies may not show the same seasonal
patterns (see below).
Our results showed some subtle, yet important, differences in
the seasonal patterns of adult beetles grouped according to feeding
ecology, body size, and habitat strata that were not apparent when
the assemblage was only examined as a whole. This is a good example
of how analyses performed at high taxonomic levels can sometimes
mask contrasting responses within ecological groups or lower taxonomic levels (see Grimbacher et al. 2008). Interestingly seasonality
differences among ecological groups existed in spite of strong temporal correlation within and between all of these groups (results not
presented). Unlike the other feeding guilds, herbivores did not show
significant seasonality and there was a greater spread of herbivore
species activity peaks throughout the year. Although this cannot
be interpreted as definitive evidence of temporal partitioning, we
suggest that it warrants further investigation. Our results contrast
with those of Basset (1991) who found that herbivorous canopy
arthropods from Australian subtropical rain forest were much more
seasonal than nonherbivores. In contrast, the temporal distribution
of nonherbivorous species in the present study was much more
aggregated, which are not supportive of the existence of temporal partitioning (at least at the temporal scale investigated). Thus
with the exception of the herbivores, these results suggest that fairly
strong environmental pressures (biotic or abiotic) are structuring
the seasonality of this beetle assemblage.
Among body size groups, larger beetles were more seasonal and
their activity peaks were later than those of smaller beetles. These
differences may be caused by different adult emergence triggers. For
335
example, larger beetles such as scarabs remain as pupae until the
first significant rainfall event at the start of the wet season softens
the pupal case and surrounding soil, allowing the adult to emerge
(Lawrence & Britton 1991). Our results corroborate with Smythe
(1982), who found that larger insects showed more pronounced
seasonality than smaller insects. In our study, beetles caught from
the canopy were more seasonal than ground-caught beetles, a result that concurs with light trap caught insects from the Neotropics
(Smythe 1982, Wolda & Broadhead 1985). Canopy-caught beetles also peaked later in the year than ground-caught beetles. By
contrast ground-caught beetles did not show significant seasonality. We speculate that this might be because the microclimate near
the ground is buffered by the canopy and hence is less seasonal
(Walsh 1996). The similarity in seasonal patterns between larger
and canopy-caught beetles is likely to be due to the significant relationship between these two traits as canopy-caught beetles also tend
to be larger (Grimbacher & Stork 2007).
In summary, we are unable to definitively attribute our beetle
seasonal patterns to any particular cause given that our data simply
represent the activity of adult beetles. Our results suggest that environmental manipulations to test the influence of abiotic factors
such as precipitation, solar radiation, and day length are unlikely
to be of use in future in situ experiments because of the likely existence of threshold responses to climate and life-history time-lags.
In contrast, better progress may result from bottom-up approaches
with single species or guilds of species looking at complete life cycles
rather than just the adult life stages. Our results show that important differences in seasonality exist among adult beetles depending
on their feeding ecology, body size, and whether they live in the
canopy or near the ground.
ACKNOWLEDGMENTS
We thank the Australian Canopy Crane for use of the crane to
access the canopy and M. Cermak, B. Howlett, R. Rader, J. Hill, K.
Goodall, and Green Corps volunteers for help in servicing traps and
sorting and mounting of the beetles. Comments from W. Edwards,
R. Didham, T. Schowalter, M. Lowman, and several anonymous
referees improved earlier versions of this manuscript. This project
was supported by funding from the Rainforest Cooperative Research
Centre and from the Marine and Tropical Science Research Facility.
We also acknowledge the support of the John T Reid Charitable
Trusts, the Vincent Fairfax Family Foundation, and an anonymous
donor for generous funding for the operation of the Australian
Canopy Crane.
SUPPORTING INFORMATION
Additional Supporting Information may be found in the online
version of this article:
FIGURE S1. Plots of the autocorrelation function for the number
of beetle species and individuals captured during March 2000–
February 2004.
336
Grimbacher and Stork
FIGURE S2. Counts of the number of samples when the 124 most
abundant beetle species were present.
Please note: Wiley-Blackwell is not responsible for the content or
functionality of any supporting materials supplied by the authors.
Any queries (other than missing material) should be directed to the
corresponding author for the article.
LITERATURE CITED
BASSET, Y. 1991. The seasonality of arboreal arthropods foraging within an
Australian rainforest tree. Ecol. Entomol. 16: 265–278.
BASSET, Y., V. NOVOTNY, S. MILLER, AND R. L. KITCHING. 2003. Arthropods
of tropical forests: Spatio-temporal dynamics and resource use in the
canopy. Cambridge University Press, Cambridge, UK.
BASU, P. 1997. Seasonal and spatial patterns in ground foraging ants in a rain
forest in the western Ghats, India. Biotropica 29: 489–500.
BATSCHELET, E. 1981. Circular statistics in biology. Academic Press, London,
UK.
BOINSKI, S., AND N. L. FOWLER. 1989. Seasonal patterns in a tropical lowland
rainforest. Biotropica 21: 223–233.
BOULTER, S. L., R. L. KITCHING, AND B. G. HOWLETT. 2006. Family, visitors
and the weather—patterns of flowering in tropical rainforests of northern
Australia. J. Ecol. 94: 369–382.
BUSKIRK, R. E., AND W. H. BUSKIRK. 1976. Changes in arthropod abundance
in a highland Costa-Rican forest. Am. Midl. Nat. 95: 288–298.
CAREY, J. R. 2001. Insect biodemography. Annu. Rev. Entomol. 46: 79–110.
CHOWN, S. L., AND K. J. GASTON. 1999. Exploring links between physiology and
ecology at macro-scales: The role or respiratory metabolism in insects.
Biol. Rev. 74: 87–120.
DENLINGER, D. L. 1980. Seasonal and annual variation in insect abundance in
the Nairobi National Park, Kenya. Biotropica 12: 100–106.
DEVRIES, P. J., AND T. R. WALLA. 2001. Species diversity and community
structure in Neotropical fruit-feeding butterflies. Biol. J. Linn. Soc. 74:
1–15.
DIBOG, L., P. EGGLETON, AND F. FORZI. 1998. Seasonality of soil termites in
a humid tropical forest, Mbalmayo, southern Cameroon. J. Trop. Ecol.
14: 841–850.
DIDHAM, R. K., AND N. SPRINGATE. 2003. Determinants of temporal variation
in community structure. In Y. Basset, V. Novotny, S. E. Miller, and R. L.
Kitching (Eds.). Arthropods of tropical forests. Spatio-temporal dynamics and resource use in the canopy. pp. 28–39. Cambridge University
Press, Cambridge, UK.
DYER, L. A., M. S. SINGER, J. T. LILL, J. O. STIREMAN, G. L. GENTRY, R.
J. MARQUIS, R. E. RICKLEFS, H. F. GREENEY, D. L. WAGNER, H. C.
MORAIS, I. R. DINIZ, T. A. KURSAR, AND P. D. COLEY. 2007. Host
specificity of Lepidoptera in tropical and temperate forests. Nature 448:
696–700.
FRITH, C., AND D. FRITH. 1985. Seasonality of insect abundance in an Australian
upland tropical rainforest. Aust. J. Ecol. 10: 237–248.
FRITH, D., AND C. FRITH. 1990. Seasonality of litter invertebrate populations
in an Australian upland tropical rainforest. Biotropica 22: 181–190.
GODFRAY, H. C. J., AND M. P. HASSELL. 1987. Natural enemies may be a cause
of discrete generations in tropical insects. Nature 327: 144–147.
GODFRAY, H. C. J., O. T. LEWIS, AND J. MEMMOTT. 1999. Studying insect
diversity in the tropics. Philos. Trans. R. Soc. Lond. B 354: 1811–1824.
GRIMBACHER, P. S., AND N. E. STORK. 2007. Vertical stratification of feeding
guilds and body size in beetle assemblages from an Australian tropical
rainforest. Austral Ecology 32: 77–85.
GRIMBACHER, P. S., C. P. CATTERALL, AND R. L. KITCHING. 2008. Detecting the
effects of environmental change above the species level with beetles in a
fragmented tropical rainforest landscape. Ecol. Entomol. 33: 66–79.
HAMER, K. C., J. K. HILL, N. MUSTAFFA, S. BENDICK, T. N. SHERRATT, V.
K. CHEY, AND M. MARYATI. 2005. Temporal variation in abundance
and diversity of butterflies in Bornean rainforests: Opposite impacts of
logging recorded in different seasons. J. Trop. Ecol. 21: 417–425.
HAMMOND, P. M. 1990. Insect abundance and diversity in the Dumoga-Bone
National Park, N. Sulawesi, with special reference to the beetle fauna
of lowland rain forest in the Toraut region. In W. J. Knight, and J.
D. Holloway (Eds.). Insects and the rain forests of South East Asia
(Wallacea). pp. 197–254. Royal Entomological Society, London, UK.
HILL, C. J. 1993. The species composition and seasonality of an assemblage of tropical Australian dung beetles (Coleoptera: Scarabaeidae:
Scarabaeinae). Aust. Entomol. 20: 121–126.
HILL, J. K., K. C. HAMER, M. M. DAGWOOD, J. TANGAH, AND V. K. CHEY.
2003. Rainfall but not selective logging affect changes in abundance of
a tropical forest butterfly in Sabah, Borneo. J. Trop. Ecol. 19: 35–42.
HOPKINS, M. S., J. HEAD, J. E. ASH, R. K. HEWETT, AND A. W. GRAHAM. 1996.
Evidence of a Holocene and continuing recent expansion of lowland rain
forest in humid, tropical North Queensland. J. Biogeogr. 23: 737–745.
INKROT, D., D. SATTLER, C. GEYER, AND W. MORAWETZ. 2007. Flowering
and fruiting phenology of Normanbya normanbyi (W. Hill) L. H. Bailey
(Arecacea), a palm endemic to the lowland tropical rainforest of northeastern Australia. Austral. Ecol. 32: 21–28.
INTACHAT, J., J. D. HOLLOWAY, AND H. STAINES. 2001. Effects of weather and
phenology on the abundance and diversity of geometroid moths in a
natural Malaysian rain forest. J. Trop. Ecol. 17: 411–429.
JANZEN, D. H. 1973. Sweep samples of tropical foliage insects: Effects of seasons,
vegetation types, elevation, time of day, and insularity. Ecology 54: 687–
708.
JOHNSON, C. G. 1966. A functional system of adaptive dispersal by flight. Annu.
Rev. Entomol. 11: 233–260.
JONES, R. E., AND J. RIENKS. 1987. Reproductive seasonality in the tropical
genus Eurema (Lepidoptera: Pieridae). Biotropica 19: 7–16.
KATO, M., T. INOUE, A. A. HAMID, H. NAGAMITSU, M. B. MERDEK, A. R.
NONA, Y. ITINO, S. YAMANE, AND T. YUMOTO. 1995. Seasonality and
vertical structure of light attracted insect communities in a dipterocarp
forest in Sarawak. Res. Popul. Ecol. 37: 59–79.
KITCHING, R. L. 2006. Crafting the pieces of the diversity jigsaw puzzle. Science
313: 1055–1057.
LAIDLAW, M., R. L. KITCHING, K. GOODALL, A. SMALL, AND N. E. STORK.
2007. Temporal and spatial variation in an Australian tropical rainforest.
Austral. Ecol. 32: 10–20.
LAWRENCE, J. E., AND E. B. BRITTON. 1991. Coleoptera (Beetles). In I. D.
Naumann, P. B. Carne, J. E. Lawrence, E. S. Nielsen, J. P. Spredbery,
R. W. Taylor, M. J. Whitten, and M. J. Littlejohn (Eds.). The Insects of
Australia. pp. 543–683. Melbourne University Press, Carlton Victoria,
Australia.
LEIGH, E. G. J. 2004. How wet are the wet tropics. In E. C. Losos, and E. G.
J. Leigh (Eds.). Tropical forest diversity and dynamism. pp. 43–55. The
University of Chicago Press, Chicago, Illinois.
LOWMAN, M. D. 1982. Seasonal variation in insect abundance among three
Australian rain forests, with particular reference to phytophagous types.
Aust. J. Ecol. 7: 353–361.
MAY, R. M. 1997. The dimensions of life on earth. In P. H. Raven, and T.
Williams (Eds.). Nature and human society: The quest for a sustainable
world. pp. 30–45. National Academy Press, Washington, DC.
MILLER, J. C. 1993. Insect natural history, multi-species interactions and biodiversity in ecosystems. Biodivers. Conserv. 2: 233–241.
NIELSEN, E. S., AND L. A. MOUND. 2000. Global diversity of insects: The
problems of estimating numbers. In P. H. Raven (Ed.). Nature and
human society: The quest for a sustainable world. pp. 213–222. National
Academy Press, Washington, DC.
NIX, H. 1991. Biogeography: Pattern and process. In H. Nix, and M. Switzer
(Eds.). Rainforest animals. Atlas of vertebrates endemic to Australia’s
wet tropics. pp. 11–40. Australian National Parks and Wildlife Service,
Canberra, Australia.
Seasonality of Rain Forest Beetles
NOVOTNÝ, V., AND Y. BASSET. 1998. Seasonality of sap-sucking insects (Auchenorrhyncha, Hemiptera) feeding on Ficus (Moraceae) in a lowland rain
forest in New Guinea. Oecologia 115: 514–522.
NOVOTNÝ, V., S. MILLER, Y. BASSET, L. CIZEK, P. DROZD, K. DARROW, AND
J. LEPS. 2002a. Predictably simple: Assemblages of caterpillars (Lepidoptera) feeding on rainforest trees in Papua New Guinea. Proc. R. Soc.
Lond. B 269: 2337–2344.
NOVOTNÝ, V., Y. BASSET, S. E. MILLER, G. D. WEIBLEN, B. BREMER, L. CIZEK,
AND P. DROZD. 2002b. Low host specificity of herbivorous insects in a
tropical forest. Nature 416: 841–844.
NOVOTNY, V., S. E. MILLER, J. HULCR, R. A. I. DREW, Y. BASSET, M. JANDA, G.
P. SETLIFF, K. DARROW, A. J. A. STEWART, J. AUGA, B. ISUA, K. MOLEM,
M. MANUMBOR, E. TAMTIAI, M. MOGIA, AND G. D. WEIBLEN. 2007.
Low beta diversity of herbivorous insects in tropical forests. Nature 448:
692–U698.
OWEN, D. F., AND D. O. CHANTER. 1970. Species diversity and seasonal abundance in tropical Ichneumonidae. Oikos 21: 142–144.
PAARMANN, W. 1976. Jahreszeitliche Aktivität un Fortpflanzungsrhythmik von
Laufkäfern (Col., Carab.) im Kivugebiet (Ost-Zaire, Zentralafrika). Zoologisches Jb Syst 103: 311–354.
RICHARDS, L. A., AND P. D. COLEY. 2007. Seasonal and habitat differences affect
the impact of food and predation on herbivores: A comparison between
gaps and understory of a tropical forest. Oikos 116: 31–40.
RICHARDS, L. A., AND D. M. WINDSOR. 2007. Seasonal variation of arthropod
abundance in gaps and the understorey of a lowland moist forest in
Panama. J. Trop. Ecol. 23: 169–176.
ROBACK, P. J., AND R. A. ASKINS. 2005. Judicious use of multiple hypothesis
tests. Conserv. Biol. 19: 261–267.
SEYMOUR, J. E., AND R. E. JONES. 2000. Humidity-terminated diapause in the
tropical braconid parasitoid Microplitis demolitor. Ecol. Entomol. 25:
481–485.
SMYTHE, N. 1982. The seasonal abundance of night-flying insects in a Neotropical forest. In E. G. Leigh, A. S. Rand, and D. M. Windsor (Eds.). The
ecology of a tropical forest: Seasonal rhythms and long term changes.
pp. 309–318. Smithonian Institution Press, Washington, DC.
SOMBROEK, W. 2001. Spatial and temporal patterns of Amazon rainfall. Ambio
30: 388–396.
337
STORK, N. E. 2007a. Biodiversity—world of insects. Nature 448: 657–658.
STORK, N. E. 2007b. Australian tropical forest canopy crane: New tools for new
frontiers. Austral. Ecol. 32: 4–9.
STORK, N. E., AND P. S. GRIMBACHER. 2006. Beetle assemblages from an Australian tropical rainforest show that the canopy and the ground strata
contribute equally to biodiversity. Proc. R. Soc. Lond. B. 273: 1969–
1975.
STORK, N. E., P. S. GRIMBACHER, R. STOREY, R. G. OBERPRIELER, C. A. M.
REID, AND A. SLIPINSKI. 2008. What determines whether a species of
insect is described? Evidence from a study of tropical forest beetles. Insect
Conserv. Divers. 1: 114–119.
TAUBER, M. J., AND C. A. TAUBER. 1976. Insect seasonality: Diapause maintenance, termination, and postdiapause development. Annu. Rev. Entomol. 21: 81–107.
TAUBER, M. J., C. A. TAUBER, J. P. NYROP, AND M. G. VILLANI. 1998. Moisture,
a vital but neglected factor in the seasonal ecology of insects: Hypotheses
and tests of mechanisms. Environ. Entomol. 27.
TYLIANAKIS, J. M., A.-M. KLEIN, AND T. TSCHARNTKE. 2005. Spatiotemporal variation in the diversity of hymenoptera across a tropical habitat
gradient. Ecology 86: 3296–3302.
WALL, D. H., AND J. C. MOORE. 1999. Interactions underground—Soil biodiversity, mutualism, and ecosystem processes. Bioscience 49: 109–117.
WALSH, R. P. D. 1996. Microclimate and hydrology. In P. W. Richards (Ed.).
The tropical rain forest an ecological study. pp. 206–236. Cambridge
University Press, Cambridge, UK.
WEBB, L. J., AND J. TRACEY. 1981. Australia’s rainforests. Patterns and Change.
In A. Keast (Ed.). Ecological biogeography of Australia. pp. 607–694.
Junk, The Hague, The Netheralands.
WOLDA, H. 1978. Seasonal fluctuations in rainfall, food and abundance of
tropical insects. J. Anim. Ecol. 47: 369–381.
WOLDA, H. 1988. Insect seasonality: Why? Annu. Rev. Ecol. Syst. 19: 1–18.
WOLDA, H. 1989. Seasonal cues in tropical organisms. Rainfall? Not necessary!
Oecologia 80: 437–442.
WOLDA, H., AND E. BROADHEAD. 1985. Seasonality of Psocoptera in two tropical
forests in Panama. J. Anim. Ecol. 54: 519–530.
WOLDA, H., AND F. W. FISK. 1981. Seasonality of tropical insects. II. Blattaria
in Panama. J. Anim. Ecol. 50: 827–838.