Journal of Tropical Ecology (2008) 24:95–105. Copyright © 2008 Cambridge University Press
doi:10.1017/S0266467407004646 Printed in the United Kingdom
Sample size and appropriate design of fruit and seed traps
in tropical forests
Pablo R. Stevenson1 and Ivonne N. Vargas
CIEM, Departamento de Ciencias Biol´ogicas, Universidad de los Andes. Cr. 1a No. 18A-10. Bogot´a, Colombia
(Accepted 21 October 2007)
Abstract: Studies of seed dispersal and fruit production often use fruit traps. Different trap designs may give dissimilar
estimates; however, prior to this study there has been no tropical forest field comparison of trap designs. Likewise, there
are no recommendations about the number of traps required to assess ecological parameters, such as fruit production,
mass and number of seeds dispersed, and number of plant species producing fruits. We compared the effectiveness of
five trap designs in terms of fruit/seed bouncing out of traps, wind effects, area effects and seed removal by predators.
These studies took place in Colombia in two tropical rain forests and in laboratory conditions. We found that 300
traps (0.085 m2 each) were not enough to obtain stable estimates in two out of four parameters (number of species
and dispersed seeds). All estimates were highly variable when using fewer than 100 traps. All trap designs evaluated
(mesh on PVC frame, hanging mesh, basin and funnel traps) prevent seed removal by predators, in sharp contrast with
removal from the ground. Mesh traps were less affected by bouncing effects than plastic traps, and this factor was a
large source of bias among estimates from different traps. Since up to 68% of dry mass may bounce out, it is important
to consider adequate trap designs and to be careful when comparing studies using different methodologies. Small traps
received fewer seeds per area, however area affects were not evident when bouncing effects were controlled for. We
recommend the use of mesh traps on PVC frames, although hanging mesh traps are a good option in tropical forests
without strong winds.
´ fruit production, fruit traps, methodology, seed dispersal, trap design, Tinigua
Key words: Biased estimates, Caparu,
National Park
Resumen: Los estudios de dispersi´on de semillas y producci´on de frutos frecuentemente utilizan trampas. Diferentes
˜ de trampa pueden aportar estimativos distintos, pero esto no ha sido evaluado en bosques tropicales y tampoco
disenos
´
´
hay recomendaciones sobre el numero
de trampas requerido para cuantificar producci´on de frutos, biomasa y numero
´
˜
de semillas dispersadas, y numero
de especies de plantas representadas. Comparamos la efectividad de 5 disenos,
en
t´erminos de efectos de rebote, a´ rea de recolecci´on y remoci´on por viento y por animales. Estos estudios se hicieron en
´
Colombia en dos bosques humedos
tropicales y en condiciones de laboratorio. Trescientas trampas de 0.085 m2 no
´
fueron suficientes para conseguir estimativos estables en dos de los cuatro par´ametros evaluados (numero
de especies
y de semillas dispersadas). Encontramos que todos los estimativos son muy variables cuando se usan menos de 100
˜ de trampa (malla con estructura de PVC, malla colgante, plat´on y embudo) evitan de
trampas. Todos los disenos
manera similar la remoci´on por parte de animales, en contraste con la alta remoci´on en el suelo. Las trampas de malla
fueron menos afectadas por efectos de rebote que las trampas de pl´astico, y estas diferencias alteran substancialmente
los estimativos de producci´on. Ya que hasta un 68% de la masa seca puede rebotar, es importante considerar cuales
˜ de trampa y ser cuidadoso en el momento de comparar estudios que usan diferentes m´etodos.
son los mejores disenos
˜
Encontramos menos semillas por unidad de a´ rea en trampas pequenas,
pero el efecto de a´ rea de recolecci´on no fue
significativo al tener en cuenta los efectos de rebote. Recomendamos el uso de trampas de malla con estructura de
PVC para estudios en bosques tropicales, aunque las trampas de malla colgante son una buena opci´on en lugares sin
vientos fuertes.
1
Corresponding author. Email: [email protected]
96
INTRODUCTION
Traps have been used in both studies of seed dispersal
and fruit abundance (Chapman et al. 1994, Hamrick
& Godt 1996, Harms et al. 2000, Hubbell et al. 1999,
Jordano & Godoy 2002, Nathan & Muller-Landau 2000,
Parrado-Rosselli et al. 2006, Stevenson et al. 1998, 2005,
Terborgh 1983, Terborgh et al. 2002, Wright et al. 1999,
Zhang & Wang 1995). In spite of the wide use of traps in
important areas of tropical ecology, no published studies
compare the results provided by different trap designs in
tropical forests, even though it has been noted that trap
design affects results in other ecosystems (Chabrerie &
Alard 2005, Kollmann & Goetze 1998, Page et al. 2002).
Kollmann & Goetze (1998) found that the rate of seed
removal by predators and wind are important parameters
to consider when designing a seed trap. They also found
that trap height and area affect the quantity of seeds they
recovered for the species they monitored, mostly herbs,
bushes and small trees.
The potential bias inherent to each design makes it
difficult to compare the results between studies using
different traps. In addition, there has been no justification
for the number of traps used in past studies. Accordingly,
the first purpose of this study was to provide an estimate of
the number of traps necessary to estimate species richness
of seeds, fruit production and the mass and number of
seeds dispersed. The second purpose was to compare the
results among five of the common designs used to quantify
seed and fruit fall in terms of bouncing, wind effects, area
effects and seed removal by predators.
PABLO R. STEVENSON AND IVONNE N. VARGAS
PVC tubing that supports a net (Harms et al. 2000,
Muller-Landau et al. 2002, Wright et al. 1999). We
used a trap with a collection area of 0.64 m2 with a
polyester mesh bag, with holes of less than 1 mm,
which was supported by 4 PVC tubes at 0.8 m from
the ground (Figure 1a).
(3) Hanging mesh trap. A similar trap design consists of
a mesh or bag hanging from branches of plants in
the understorey (Stevenson 2002, Terborgh 1983),
and thus, the wind may flip the traps over. We
used polyester mesh bag with a collection area of
0.64 m2 . The corners of the trap were tied up with
string to branches of the surrounding vegetation at
an approximate height of 0.8 m (Figure 1b).
(4) Basin traps. This trap consisted of a basin 33 cm in
diameter with an area of 0.085 m2 . The basin was
supported with a plastic screw to a single PVC tube just
in the middle of the base (Figure 1c). Each basin had
a considerable number of holes 2 mm in diameter to
allow drainage. We placed a plastic bag full of leaf litter
inside the basin (about 5 cm thick), to help cushion
fruits landing in the trap.
(5) Funnel traps. These traps consisted of a plastic funnel,
22 cm in diameter, with a collection area of 0.038 m2
that was inserted into a PVC tube (8 cm diameter),
which was buried in the ground (Figure 1d). At the
funnel base a small polyester mesh bag was attached
to collect the fruits and seeds. The PVC tube had
several holes of 5 mm in diameter at the base for
drainage. Funnel traps have been recommended as
the best trap in open habitats in temperate zones
(Chabrerie & Alard 2005, Kollmann & Goetze 1998;
but see Page et al. 2002).
METHODS
Fruit and seed traps
Data collection and analyses
We compared and evaluated the effectiveness of five
different traps. The effective area of collection differed
among traps because of mechanical constraints (e.g. a
large basin standing by a single support would not be
stable).
Sample size. The data were obtained in three phases. In
the first phase, adequate sample size (number of traps) was
assessed from data collected in Tinigua National Park,
Colombia (2◦ 40 N; 74◦ 10 W) during the years 1990 and
1991. Tinigua National Park is situated in a tropical
lowland forest at an altitude of 350–400 m above sea
level with an annual precipitation of 2782 mm (Stevenson
2002).
To find out how many traps are necessary for a good
estimate of the number of species producing fruits, total
fruit production, and biomass and number of dispersed
seeds, we used information from 300 basin traps. The
traps were located randomly in 12 transects (each
c. 450 m length), scattered over an area of about 3 km2 .
All seeds, fruits, and fruit parts were collected twice a
month over 1 y, identified to species, and dried to constant
weight (Stevenson et al. 1998). Identification was based
(1) Delimited area on the ground. The simplest ‘trap’
design is a marked area on the ground where the
seeds or fruits are counted (Izhaki & Walton 1991).
This procedure may lead to biased results due to the
high potential for fruits and seeds to be removed by
frugivores, predators, wind or water (Gibson 2002,
Kollmann & Goetze 1998). We used a marked area of
1 m2 on the ground where leaf litter and seeds were
cleared.
(2) Mesh with PVC support. This commonly used trap
design in tropical rain forests consists of a frame of
Design of fruit and seed traps
97
Figure 1. Trap designs used in the study in Caparu´ Biological Station (Vaup´es, Colombia) and under laboratory conditions: mesh with PVC support
(a), hanging mesh (b), basin (c), and funnel (d). Basin traps were also used in Tinigua National Park to assess sampling effort.
on the fruit guide of the study site (Stevenson et al. 2000).
Additionally, all trees above each trap were identified
to assess the likelihood that a seed in the trap could
be classified as dispersed. This analysis was restricted to
species with fleshy fruits, excluding liana species, because
it was difficult to assess the presence of a parental liana
above the traps.
In order to assess the number of traps necessary to get
stable estimates of the ecological parameters, we used the
program EstimateS, version 7.5.0 (http://purl.oclc.org/
estimates) to graph the cumulative number of species as a
function of sample size. We also calculated the percentage
of precision (Norton-Griffiths 1975), which is a measure
of variation that decreases as sample size increases. This
coefficient was calculated as follows:
% precision = 95% confidence interval × 100/average
Then the percentage is proportional to the value for the
95% confidence interval of the parameter evaluated from
a set of traps, divided by its average in that sample (NRC
1981). To assess the variation in precision as a function
of sample size, we first calculated the percentage for a
set of 10 randomly chosen traps and this procedure was
replicated ten times for analyses of both fruit production
and dispersed seeds. This calculation provided an average
percentage of precision for 10 traps and the standard
error. Then, the same calculations were performed for
98
PABLO R. STEVENSON AND IVONNE N. VARGAS
Table 1. Characteristics of the species used in three different experimental trials: (a) bouncing effects,
(b) wind effects and (c) removal by predators.
Family
Species
Item
Dry weight (g)
N
a
a
a
a
a
a
b
b
b
b
b
c
Caricaceae
Fabaceae
Solanaceae
Fabaceae
Rosaceae
Rutaceae
Bromeliaceae
Bignoniaceae
Bignoniaceae
Fabaceae
Fabaceae
Malpighiaceae
Carica papaya L.
Ormosia amazonica Ducke
Physalis peruviana L.
Mucuna urens (L.) DC.
Malus pumila Mill.
Citrus reticulata Blanco
Tillandsia pastensis Andr´e
Adenocalymma purpurascens Rusby
Cydista aequinoctialis Miers
Machaerium floribundum Benth.
Pterocarpus sp.
Byrsonima japurensis A.Juss.
Myristicaceae
Virola duckei A.C.Sm.
c
Myristicaceae
Osteophloeum platyspermum Warb
0.002
0.2 ± 0.01
1.0 ± 0.1
5.6 ± 0.2
22.4 ± 3.7
26.3 ± 7.4
0.00091
0.07 ± 0.003
0.08 ± 0.002
0.21 ± 0.01
0.49 ± 0.05
0.9 ± 0.06
0.36 ± 0.03
5.01 ± 0.04
1.5 ± 0.18
3.5 ± 0.06
1.8 ± 0.03
10
10
10
10
10
10
c
Small, soft seed
Small, hard seed
Soft small fruit
Large, hard seed
Large, hard fruit
Large, soft fruit
Seed
Seed
Seed
Fruit
Fruit
Fruit
Seed
Fruit
Seed
Fruit
Seed
10
10
10
10
10
10
10
10
10
10
1 Based on the total weight of 77 seeds
20 traps, 30 traps, and so on until reaching the total of
300 traps. Minimum sampling effort is achieved when the
precision of the estimates does not improve as more traps
are added (i.e. when the slope of the curve approaches
zero). In order to find the number of traps required
to get stable estimates, we assessed deviations from
horizontality using traditional linear regression analyses
(testing for a slope < 0).
Bouncing and wind effects. The second phase was carried
out in a laboratory. We evaluated the bouncing and wind
effects for each of four different trap designs (mesh with
PVC support, hanging mesh, basin and funnel). We did
not test the ground trap because we assumed that the
bouncing effect would be negligible (i.e. the probability
that a seed will land in the square and bounce out of
the square is the same as the probability that a seed will
land outside and bounce in). To evaluate bouncing effects,
we used seeds or fruits of species with different weight and
consistency (Table 1). Throughout this paper we will refer
to each species only by generic name. Six bouncing trials
were conducted for each species. Each trial consisted in
dropping 10 seeds/fruits from 14 m above the traps and
we counted the number of seeds/fruits that bounced out
of the traps.
To evaluate wind effects we tested fruits and seeds
belonging to five species with wind-dispersed seeds, and
with different weights and shapes (Table 1). We measured
the wind effects for a wind speed of 20 km h−1 generated
R
fan, which is within the range
by a Falcon Super Deluxe
of highest values reported for the Colombian Amazon
in forested areas (http://www.ideam.gov.co/sectores/
aero/climat/index44.htm). Tests were conducted with
each of the four trap designs and each plant species
studied. We placed 10 seeds of each species in each trap
and turned the fan on. The fan was positioned horizontally
1 m from each trap. Six replicates were done for each test
and we counted the number of seeds that blew out of the
traps.
Area effects and seed removal by predators. The third phase
was carried out at the Mosiro Itajura Biological Station
(1◦ 05 S; 69◦ 31 W), Vaup´es, Colombia, formerly known
´ The biological station is situated in a tropical
as Caparu.
rain forest, at an altitude of 400 m asl with an annual
precipitation between 3000 and 4000 mm (Defler & Defler
1996). We monitored seed rain and removal effect by
predators from February to June 2005. We evaluated the
five trap designs to determine the extent of seed removal
by predators from traps in three species that produced
fruits during the study period (Table 1).
To assess the effect of trap area and seed removal by
predators, we used six parental trees of both Byrsonima
and Osteophloeum, and five Virola trees. All of the five trap
designs were tested under each parental tree. Two traps for
each design were placed under each tree and results were
averaged to be used as independent samples in further
analyses. Parental trees of each species were at least 30 m
apart. Traps were checked every 7 d and during each
visit we counted the number of seeds deposited in each
trap.
In order to assess an area effect for each trap design,
we compared the total number of seeds collected by trap
area. Furthermore, we made a second comparison using
a correction factor that takes into account the bouncing
effect inherent to each trap design. We included only data
Design of fruit and seed traps
from Byrsonima and Osteophloeum in this analysis, due to
the low seed representation under Virola trees for basin
and funnel traps.
To determine the seed removal by predators from traps,
we placed marked seeds into the traps used above. We
added a specific number of marked seeds to each trap,
simulating the natural seed rain of each tree species (10
seeds for Byrsonima, 3 for Osteophloeum and 4 for Virola).
Byrsonima and Osteophloeum seeds were marked with
water resistant ink, and Virola seeds were marked with
a thread inserted through the seed base with a needle. On
each weekly visit we counted the number of marked seeds
that were removed from the traps and in case of removal,
the seeds were replaced. A replicate group of traps – of
the same designs and quantities – were placed far away
from parental trees at a minimum distance of 50 m. The
replicates were used to assess differential removal between
traps under parental trees and traps away from parents.
Replicate traps were distributed at random and in similar
distribution to those under parental trees.
Statistical analyses
All the analyses were done with Statistix 8.0 (2003).
Bouncing data were log transformed (log(x+1)) and were
analysed with an ANOVA. A posteriori Tukey tests were
also performed. Differences among trap designs for wind
and removal by predators were analysed using Kruskal–
Wallis non-parametric tests.
RESULTS
Sample size
The cumulative number of species recorded as a function
of sample size did not reach a stabilization point for the
total number of traps used (Figure 2a). The percentage of
precision for fruit production and the mass of dispersed
seeds reached stabilization using 230 and 250 traps
respectively (Figure 2b–c). The percentage of precision
for number of seeds dispersed did not show a clear
stabilization point (Figure 2d). In most cases we observed
a rapid change in variation estimates with a small sample
size (c. 100 traps) and afterwards the variation changed
more gradually. The overall variation in the estimates of
fruit production was lower than for both quantifications of
seed dispersal, but in all cases there were large variations
among traps. For instance, the exclusion of a single trap
located under a howler monkey sleeping site changed
drastically the patterns of variation in the mass of
dispersed seeds (Figure 2c). The highest variation was
observed for the number of dispersed seeds (Figure 2d).
99
Bouncing and wind effects
We found highly significant differences for fruit and
seed bouncing between trap designs (F = 8.44, N = 24,
P = 0.002; Figure 3a). A posteriori comparisons showed
differences between two groups: Funnel and basin
traps vs. mesh traps with PVC support, with less
bouncing effects for the later. Hanging mesh traps
showed intermediate bouncing effects. We found highly
significant differences in bouncing among the species used
(F = 7.05, N = 24, P = 0.001, Figure 3b). A posteriori tests
showed differences between Citrus vs. Carica, Physalis,
Mucuna and Ormosia. There were also differences between
Malus with Carica and Physalis. The heaviest fruits, Citrus
and Malus, showed the greatest percentage of bouncing,
while Carica and Physalis bounced the least.
We found significant differences in fruit and seed
removal by wind among trap designs (H = 8.17, N = 20,
P = 0.042; Figure 4a), with the hanging mesh trap
showing the highest losses. We also found significant
differences in fruit/seed removal by wind among the
species (H = 8.73, P = 0.06; all N = 20; Figure 4b). In
all cases, we observed that small Tillandsia seeds had the
greatest removal and the heavy Machaerium samaras had
the lowest.
Area effects and seed removal by predators
We found significant differences in the number of
seeds according to area between trap designs in
Byrsonima (H = 10.3, P = 0.03, df = 4, N= 30); but not
in Osteophloeum (H = 5.69, P = 0.23, df = 4 N = 30).
However, the comparison taking into account the
bouncing effect rendered no significant differences
between trap designs with different area (Byrsonima:
H = 9.3, P = 0.052, N = 30; Osteophloeum: H = 5.8,
P = 0.21, df = 4, N= 30).
We did not find significant differences in the
mean numbers of seeds removed under parental trees
and far from parental trees (Byrsonima: H = 6.39,
N = 60, P = 0.84; Virola: H = 1.64, N = 50, P = 0.99;
Osteophloeum: H = 3.03, N = 60, P = 0.99). Thus, we
pooled data for traps located under and away from
parental trees for the remaining analyses, to assess
differences among trap designs. In all three species
studied, we found significant differences between trap
designs for seed removal by predators (Byrsonima:
H = 33.6, N = 60, P < 0.001; Virola: H = 41.5, N = 50,
P < 0.001; Osteophloeum: H = 51.8, N= 60, P < 0.001).
In all cases, a posteriori tests showed that seed removal
from the ground was significantly greater than other
traps (Figure 5), but we did not find differences in seed
removal among traps (P > 0.05). The mean proportion
100
PABLO R. STEVENSON AND IVONNE N. VARGAS
Figure 2. Analyses of the sample size (i.e. number of basin traps) necessary to estimate different ecological parameters in Tinigua National Park,
Colombia. Sample size required to get adequate estimates of species richness represented in fruit production (a). Percentage of precision in the
estimates of fruit production (b). Percentage of precision of mass of seeds dispersed as a function of cumulative sampling size (c). Percentage of
precision of number of dispersed seeds as a function of cumulative sampling size (d). The points represent averages from ten simulations and the
standard error (dotted lines or bars) associated with the mean. In the third panel filled points represent an analysis subtracting a single trap below a
howler monkey sleeping tree.
Design of fruit and seed traps
101
Figure 3. Number of seeds and fruits bouncing out of the traps under laboratory conditions. Comparing different trap designs (including data from all
plant species) (a) and comparing plant species (1. Carica, 2. Physalis, 3. Ormosia, 4. Mucuna, 5. Malus, 6. Citrus) (b). The box indicates the 25th and
75th percentiles from six replicates, the line inside the box is the median, the capped bars indicate the 10th and 90th percentiles, and the outlying
symbols are the extreme values.
of seeds removed from traps between each revision was
0.5% (SD = 0.5) for the three species, while the proportion
removed from the ground was 38.0% (SD = 19.1).
DISCUSSION
Sample size
Our sample size of 300 traps is above the average
for studies of fruit production and seed dispersal, e.g.
300 in Chapman et al. (1994), 120 in Jackson (1981),
40 in Silman (1996), 75 in Smythe (1970), 100 in
Terborgh (1983), 200 in Wright et al. (1999). However,
the parameters estimated in this study, in particular
species richness did not completely stabilize with such
large sampling effort and the relatively small basin traps.
Similarly, we did not reach stabilization in the percentage
of precision of the number of dispersed seeds, even though
the degree of variation may be underestimated since a
large number of small seeds might have been washed
away through the drainage holes. Our analyses indicate
that a large number of traps (>230) are necessary
to obtain stability in the variance estimates of fruit
production. All these results are mainly caused by the
clumped nature in the spatial patterns of both fruit
production and seed dispersal (Schupp et al. 2002), and
therefore, we recommend the use of more than 300
102
PABLO R. STEVENSON AND IVONNE N. VARGAS
Figure 4. Number of fruits or seeds blowing out of the traps under laboratory conditions. Comparing trap designs (including data from all plant
species) (a) and comparing plant species (1. Adenocalymma, 2. Cydista, 3. Machaerium, 4. Pterocarpus, 5. Tillandsia) (b). The box indicates the 25th
and 75th percentiles from six replicates, the line inside the box is the median, the capped bars indicate the 10th and 90th percentiles, and the
outlying symbols are the extreme values.
traps. However, when logistic problems might limit the
construction of a large number of traps, this number
should not be less than 100 traps.
Bouncing and wind effects
The results of the study showed astonishing differences in
bouncing effects among trap designs. Overall, 41.9% and
36.6% of the seeds falling into funnel and basin traps were
not retained. In terms of biomass (dry weight in g), this
turns out to be a 67.7% and 52.6% of loss, respectively
(Table 2). The percentage of number of seeds and biomass
lost in other trap designs was not as high, but still their
values considerably underestimate fruit production and
seed fall (Table 2). Thus, the funnel and basin traps
showed the highest bouncing effects, and this result was
expected for the funnel trap because the plastic material
had little cushioning for either fruits or seeds that fell into
them. It was surprising that the cushion in the basin trap
was not very effective at avoiding bouncing of large fruits
and seeds. The mesh traps, both the hanging and on PVC
frame, showed the smallest bouncing effect. In particular,
the concave shape of the mesh on PVC frame allowed
even heavy fruits to remain against the frame of the trap.
The bias was more pronounced for heavy seeds and fruits
than for light ones. Although the consistency of fruit and
seeds influenced bouncing probabilities, there were no
Design of fruit and seed traps
103
Figure 5. Number of seeds removed by predators from each trap design and for three different species studied in Caparu´ Biological Station. Byrsonima
(number of marked seeds placed in each trap N = 20) (a), Virola (N = 8) (b), and Osteophloeum (N = 6) (c). The box indicates the 25th and 75th
percentiles, the line inside the box is the median, the capped bars indicate the 10th and 90th percentiles, and the outlying symbols are the extreme
values.
differences between large fruits of different consistencies.
This indicates that there is a greater influence of weight
than consistency and since fruit productivity may depend
on a higher degree from large fruits, then the choice of a
particular fruit trap design is relevant to provide rigorous
estimates of fruit production.
104
PABLO R. STEVENSON AND IVONNE N. VARGAS
Table 2. Mean percentage of loss by bouncing and wind effects in terms of number of seeds or fruits lost and biomass (dry weight, g).
Bouncing effects
Trap
Mesh with PVC support
Hanging mesh
Basin
Funnel
Wind effects
Mean (% seeds/fruits loss)
Mean (% biomass loss)
Mean (% seeds loss)
Mean (% biomass loss)
11.8
21.1
36.7
41.9
29.1
38.3
52.7
67.8
2.67
26.0
24.3
10.3
0.02
16.7
2.71
1.34
The highest removal of seeds by wind from the hanging
trap (26% of seeds lost and 16% of biomass lost) was
due to trap instability (i.e. traps turned upside down).
This problem of flipping was avoided in the traps with
PVC frame (2.6% of seeds lost and 0.02% of biomass lost).
Nevertheless, in the wind experiments, the small Tillandsia
seeds were more frequently removed than the heavier
Machaerium seeds. Fruit production estimates were more
biased for the effects of bouncing than wind. For example,
for our study, on average, the percentage of loss from wind
effects was 19.2 for number of seeds/fruits lost, 5.2% for
biomass, and from bouncing effect was 27.8% for number
of seeds/fruits lost and 49.9% for biomass (Table 2).
Area effects and removal by predators
Contrary to the suggestion of Page et al. (2002), we found
no significant differences in the number of seeds per area
among traps, when the effect of bouncing was included.
Therefore, for the trap designs included in this study, the
effective collection area does not seem to have an influence
on the performance of the trap. However, it is possible
that very small or large traps should affect the seed rain
representation. An analysis determining the efficiency
of trap area in terms of number of species that can be
collected in each trap design remains to be done.
In all comparisons we found that the ground traps had
the greatest removal of marked seeds by predators and
this removal was significantly different from all the other
trap designs. Therefore, any estimates of fruit production
using marked areas on the ground may be strongly
biased, and the use of traps would help to reduce the
problem of predator removal, unless there is an additional
mechanism to prevent rodent removal (Au et al. 2006).
basin. The ground trap showed the greatest removal
by frugivores and predators. The hanging mesh traps
showed the highest removal rates by wind, though this
is not as problematic when estimating fruit production.
Therefore, according to the results of this study, the mesh
traps on PVC frame seem to be the most appropriate
design among the traps evaluated for studies of fruit
production and seed dispersal in tropical forests. At the
same time, this trap design would be preferred for longterm investigations because the PVC frame is strong
and resistant to degradation. However, an additional
consideration is that traps on PVC frame are the most
expensive and the most time-consuming to install. When
these economic and practical points are considered, the
hanging mesh trap is a good second choice for studies
of seed dispersal or frugivory, especially in forests where
wind speeds are not strong. Additional consideration
should be taken into account for specific sites (e.g. flooding
regimes, particular behaviours of predators, mechanical
damage by megafauna, etc.).
ACKNOWLEDGEMENTS
˜
We thank Marcela Quinones,
Jorge Ahumada, and Beatriz
Ram´ırez who collected trap data in the field. Nicole
Gibson and Daniel Cadena corrected the manuscript
and provided helpful comments. The study at Tinigua
National Park was made possible by the logistic support
from the Center of Ecological Investigations La Macarena
(CIEM). The study in Caparu´ was made possible by the
logistic help of Conservation International Colombia, and
we are grateful to Erwin Palacios. This study was funded
by Conservation International Colombia, Banco de La
´
Republica
and Universidad de Los Andes, Bogot´a.
Which is the most adequate trap design?
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