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2011 SOUTHEASTERN NATURALIST 10(2):245–250
No Difference in Short-term Temporal Distribution of
Trapping Effort on Hoop-net Capture Efficiency for
Donald J. Brown1,*, Ivana Mali1, and Michael R.J. Forstner1
Abstract We investigated the influence of trapping duration on freshwater turtle captures
using baited hoop-nets. We trapped 9 ponds in the Lower Rio Grande Valley and 6 ponds
in the Lost Pines ecoregion areas of Texas in the summer of 2010 using high-intensity,
short-duration trapping (40 traps/1 day) and low-intensity, longer-duration trapping (10
traps/4 days). We found that the number of captures was not different between sampling
schemes. However, the mean capture rate was twice as high after the first day of lowintensity
trapping. This study showed that researchers seeking to maximize captures
per-unit-effort (CPUE) should focus on the least time-intensive, labor-intensive, and
expensive way to complete the trapping effort, rather than short-term temporal distribution
of trapping effort.
Estimation of demographic components (e.g., population size and survivorship)
is fundamental to many population-monitoring programs (Buckland et al.
2000, Campbell et al. 2002). Capture-recapture methods are widely used and are
often the most accurate means for estimating demographic components (Amstrup
et al. 2005). These methods rely on capturing and marking individuals, and
then recapturing the individuals during later sampling periods. Because of time,
money, and personnel constraints, researchers often seek to maximize capture
efficiency (Gamble 2006) through determining when, where, and how to best
sample a population to optimize captures per-unit-effort (CPUE), while minimizing
biases that skew estimates (Thompson 2004).
Many techniques have been developed for sampling aquatic turtle populations
(Lagler 1943, Vogt 1980). Hoop-nets remain one of the most common turtle-trapping
devices used today (Davis 1982, Thomas et al. 2008). They are logistically
superior to most other passive trapping devices (i.e., basking traps, fyke nets, and
trammels) because they are lightweight, easily portable in large numbers, require
only one worker, and provide easily quantifiable results. Several factors can
influence hoop-net capture rates and affect sex- and size-specific capture probabilities,
including trap size, trap placement, and type of bait (Cagle and Chaney
1950, Thomas et al. 2008). In addition, capture rates may change with trapping
effort and duration.
The purpose of this study was to investigate the influence of trapping duration
on turtle capture rates using baited hoop-nets. It is usually less expensive
1Department of Biology, Texas State University-San Marcos, 601 University Drive, San
Marcos, TX 78666. *Corresponding author - email@example.com.
246 Southeastern Naturalist Vol. 10, No. 2
and time-consuming to conduct high-intensity trapping for short periods of time,
as opposed to low-intensity trapping for longer time periods. However, this may
result in fewer captures from a given population if highly variable abiotic conditions
(e.g., temperature or precipitation) affect activity patterns and thus captures
(Cagle 1950, Crawford et al. 1983), if the water body is large and turtles utilize
different areas on different days (Bodie and Semlitsch 2000, Brown and Brooks
1993), or if captures increase as turtles become accustomed to presence of the
traps (Vogt 1980). Alternately, high-intensity trapping may increase captures by
increasing the concentration of bait scent in the water, or both trapping schemes
may produce comparable CPUE results.
We conducted this study in two ecoregions of Texas, the Lower Rio Grande
Valley (LRGV), and the Lost Pines. We trapped freshwater ponds in Cameron,
Hidalgo, and Willacy counties in the LRGV, and Bastrop County in the Lost
Pines. Ponds in the LRGV were typically bordered by reeds, primarily Typha
spp. (cattails) and Arundo donax L. (Giant Cane). Ponds in the Lost Pines were
typically surrounded by Pinus taeda L. (Loblolly Pine), Juniperus virginiana L.
(Eastern Red Cedar), and Quercus stellata Wangenh (Post Oak) trees. Pond area
ranged from 0.08 ha to 8.2 ha (mean = 2.01 ha) across all sites.
Two freshwater turtle species are found in the LRGV that were not captured in
this study, Kinosternon flavescens (Agassiz) (Yellow Mud Turtle) and Chelydra
serpentina (L.) (Eastern Snapping Turtle). Based on our extensive freshwater turtle
work in the LRGV since 2008, densities seem to be low for both species (Dickerson
et al. 2009). In addition to turtles, we routinely captured Nerodia rhombifer
(Hallowell) (Diamond-backed Watersnake) and Siren intermedia texana Goin (Rio
Grande Lesser Siren) in LRGV ponds. Two of the LRGV ponds also contained Alligator
mississippiensis (Daudin) (American Alligator) during this study.
Two freshwater turtle species are found in the Lost Pines that were not captured
in this study, the Yellow Mud Turtle and Pseudemys texana Baur (Texas Cooter).
We did not capture other aquatic reptile fauna in the Lost Pines during this study,
but have observed large numbers of Nerodia erythrogaster transversa (Hallowell)
(Blotched Watersnake) and several Agkistrodon piscivorus leucostoma (Troost)
(Western Cottonmouth) at the same ponds during other investigations.
All ponds sampled contained fish populations. We captured Lepomis megalotis
(Rafinesque) (Longear Sunfish) and Ictalurus punctatus (Rafinesque) (Channel
Catfish) in hoop-nets in the Lost Pines. We did not specifically identify fish species
in the LRGV captured during this project. We know that one pond had been
previously stocked with Micropterus salmoides (Lacepède) (Largemouth Bass),
and these were occasionally seen in traps. At several of the sites in the LRGV, we
observed Cichlasoma cyanoguttatum (Baird and Girard) (Rio Grande Cichlid)
alongside abundant introduced Oreochromis aureus (Steindachner) (Blue Tilapia),
Hypostomus spp. (suckermouth catfish), and Cyprinus carpio L. (Common
Carp) in past years. Among notable native fishes, we captured several Awaous
banana (Valenciennes) (River Goby) at one of the LRGV sites in 2008 and 2009.
2011 D.J. Brown, I. Mali, and M.R.J. Forstner 247
The majority of ponds were located on preserves or state parks. One pond in the
LRGV was located on a private ranch stocked with cattle.
We trapped 9 and 6 ponds in the LRGV and Lost Pines, respectively. Trapping
sites were chosen based on access and security from trap-theft. We conducted
short-term, high-intensity trapping by placing 40 hoop-nets in each pond for 1
day (23–25 hours). We conducted longer-term, low-intensity trapping by placing
10 hoop-nets in each pond for 4 days (94–97 hours). Ponds were randomized for
initial trap intensity, and were re-trapped with opposite intensity after a 33- to
55-day cool-down period. The goal of performing both sampling schemes at each
pond was to mitigate the influence of inherent population-size differences on
We spaced traps evenly along the edges of ponds, tying them to reeds or
other vegetation at 5- to 15-m (40 traps/1day) or 20- to 60-m (10 traps/4 days)
intervals. We marked individual trap locations with a portable GPS unit (Map60,
Garmin Ltd., Olathe, KS) to ensure that the same area was trapped during the
second trapping event at each site. We performed this study between 10 May and
13 July 2010.
We used 76.2-cm-diameter single-opening, single-throated, widemouth hoopnets
with a 2.54-cm mesh size and four hoops per net (Memphis Net and Twine
County, Memphis, TN). Traps were kept taut using wooden posts connected to the
first and last hoop. Two stretcher posts were used for each trap, located lateral to
the mouth opening. We baited all traps with sardines in non-consumable containers
containing holes for scent escape. Fresh bait was used for high-intensity trapping,
and bait was refreshed every 2 days for low-intensity trapping. We placed flotation
devices between the two middle hoops to prevent drowning and to keep traps parallel
with the water’s surface. We inspected traps for holes and damage daily.
We measured carapace length and width, plastron length and width, and body
depth of captured individuals to the nearest 1.0 mm using tree calipers (Haglof,
Madison, MS). Turtles were weighed to the nearest 10 g using spring scales
(Pesola, Baar, Switzerland), and individually marked by notching the carapace
using a rotary tool (Dremel, Racine, WI). We determined sex using secondary
sexual characteristics (Conant and Collins 1998, Gibbons and Lovich 1990).
We used a paired randomization test with 10,000 iterations to determine if
total number of captures differed by sampling-duration scheme (i.e., 40 traps/1
day or 10 traps/4 days), using pond as the sampling unit. The P-value obtained
was the proportion of trials resulting in a capture difference between duration
schemes as great or greater than the one obtained (Sokal and Rohlf 1995). We
then re-performed the test using only Trachemys scripta elegans (Wied-Neuwied)
(Red-eared Slider) captures, which represented 79.5% of total captures.
We removed captures for individuals captured more than once within a sampling
period (n = 1). We treated recaptures between sampling periods as new individuals
(n = 2). We conducted the statistical analyses using R 2.7.2 (The R Foundation
for Statistical Computing, Vienna, Austria).
248 Southeastern Naturalist Vol. 10, No. 2
We captured 65 turtles while conducting high-intensity trapping and 62 turtles
conducting low-intensity trapping (Table 1). In the LRGV, we captured 78 Redeared
Sliders and 19 Apalone spinifera emoryi (Agassiz) (Texas Spiny Softshell).
In the Lost Pines, we captured 23 Red-eared Sliders and 7 Eastern Snapping Turtles.
Number of captures between the two trapping schemes was not different for
the complete data set (P = 0.437), or when only Red-eared Sliders were included
(P = 0.429). For low-intensity trapping, we obtained 50% of total captures on the
first day of trapping, 14.5% on day 2, 22.6% on day 3, and 12.9% on the fourth
day of trapping.
We found that short-term high-intensity trapping yielded similar total captures
to longer-term low-intensity trapping (Table 1). Therefore, at least for Red-eared
Sliders, when the goal is to maximize CPUE, the least time-intensive, laborintensive,
and expensive way to complete the trapping effort should be primary
considerations, rather than temporal distribution of trapping effort. This study
also showed that total effort matters. We captured 52.3% more turtles in the 40
traps/1 day sampling scheme than in the first day of the 10 traps/4 days sampling
scheme. However, from the perspective of capture-rates, 10 traps/1 day was more
effective than 40 traps/1 day, with mean capture-rates of 0.21 and 0.11 turtles per
trap day, respectively.
Table 1. Number and captures per-unit-effort (CPUE) of freshwater turtles captured in baited hoop
nets using short-term, high-intensity trapping and longer-term, low-intensity trapping at 9 ponds
in the Lower Rio Grande Valley (LRGV) and 6 ponds in the Lost Pines areas of Texas. Ponds were
trapped with both sampling schemes to mitigate the influence of inherent population size differences
Study area 40 traps/1day total 10 traps/4 days total Day 1 Day 2 Day 3 Day 4
LRGV 0 6 0 1 4 1
LRGV 1 3 2 0 0 1
LRGV 6 6 0 1 3 2
LRGV 8 18 16 1 0 1
LRGV 2 3 1 1 1 0
LRGV 2 5 0 3 1 1
LRGV 1 3 2 0 1 0
LRGV 13 7 4 0 3 0
LRGV 13 0 0 0 0 0
Lost Pines 2 4 3 0 0 1
Lost Pines 6 1 1 0 0 0
Lost Pines 1 1 1 0 0 0
Lost Pines 3 4 1 2 0 1
Lost Pines 3 1 0 0 1 0
Lost Pines 4 0 0 0 0 0
Sum 65 62 31 9 14 8
CPUE 0.108 0.103 0.207 0.06 0.093 0.053
2011 D.J. Brown, I. Mali, and M.R.J. Forstner 249
Besides maximizing CPUE, these results have important implications for
study repetitions and long-term monitoring of freshwater turtle populations.
First, it is probably more important to focus on repeating observations within the
same general time-frame (e.g., season, month, or week) than to focus on equal
temporal distribution of sampling effort. Activity patterns and captures have
been shown to vary substantially by season (Brown and Brooks 1993, Ream
and Ream 1966, Thomas et al. 1999). Secondly, capture rate might not be an
appropriate metric for assessing change if total effort is not repeated. This topic
warrants further study, as it is not always tenable to exactly repeat trapping effort
every year in long-term monitoring programs. Based on this study, the mean
capture rate was similar between sampling schemes when 50% of the effort was
completed in the low-intensity trapping (mean capture rate = 0.13 turtles per trap
day). Therefore, when using capture rate as a proxy for abundance differences,
we recommend that trapping effort does not vary by more than 50% due to the
risk of concluding artificial abundance differences among sites or years.
Finally, we found that capturing no turtles in one sampling period did not mean
that the habitat wasn’t suitable. For 3 of the ponds, we captured turtles in only
1 sampling period. In one of these ponds, a 5.3-ha oxbow lake in the LRGV, we
captured no turtles during the 4-day low-intensity trapping event, but captured 13
during the high-intensity event. Given that this water body is located in a highly
urbanized area, we speculate that most of the turtles were present in the pond during
the low-intensity trapping, but were simply not near enough to the traps to be
attracted by the scent. This result is contrary to our expectation that longer-term
trapping would be a more efficient trapping scheme in larger water bodies, and may
indicate a bait-scent-concentration effect. However, because we captured 42 turtles
during both sampling schemes in the 6 largest ponds (1.5−8.2 ha), it is not apparent
that increasing bait scent in larger water bodies attracts more turtles.
We thank J.R. Dixon, J. Tokarz, J. Barnett, M. Lindsay, and M. Vandewege for assistance
in checking traps. We are indebted to M. Pons, Jr. and the Nature Conservancy
of Texas for allowing us to reside at Southmost Preserve and use the preserve for this
study. Thanks to the Boy Scouts of America, Texas Parks and Wildlife Department, and
private agencies and landowners for allowing us to trap turtles on their properties. Individuals
and funding were through the Texas Parks and Wildlife Department (Permit No.
SPR-0102-191). This research was approved by the Texas State University-San Marcos
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