Herpetological Review 52(1), 2021
and do not lead to habitat degradation, which may occur when
performing natural cover object or leaf litter surveys (e.g., Hyde
and Simons 2001; Hesed 2012). Additionally, coverboard arrays
serve to standardize both the number of cover objects and their
size and thus lead to a reduction in data collection variability
allowing increased robusticity when comparing across sites
within studies or comparing across studies (Moore 2009; Willson
and Gibson 2010; Fleming et al., unpubl.).
In spite of the widespread use of coverboards as a method
for censusing amphibian diversity (e.g., DeGraaf and Yamasaki
1992; Monti et al. 2000; Ryan et al. 2002; Mornealt et al. 2004)
and a large number of methodological studies relating to
coverboard effectiveness (e.g., Houze and Chandler 2002;
Marsh and Goicochea 2003; Moore 2005; Carlson and Szuch
2007), particularly with regards to P. cinereus, there is still little
consensus on a multitude of factors that may drive coverboard
use by salamanders. Variability in coverboard design and
protocols across studies has often made comparisons between
studies difficult (Hesed 2012). Recently, substantial work has been
performed to estimate potential confounding variables between
studies (e.g., wood type, board dimensions, sampling frequency).
For example, there are a large number of studies examining how
salamanders respond to different coverboard materials. Moore
(2005) examined if encounter rates were influenced by whether
coverboards were made of local wood in comparison with
other board materials. MacNeil and Williams (2013) compared
encounter rates for lightweight plastic coverboards designed
to retain moisture with traditional wood materials, while Grant
et al. (1992) compared encounter rates between wood and
tin coverboards. From this work, it is clear that factors such as
wood type play a role in establishing the microhabitat under the
coverboard, which affects the attractiveness of the coverboard to
salamanders (Carfioli et al. 2000).
It is critical when comparing salamander population
abundance either through time, as in multi-year studies, or
across locations, that detectability of salamanders is equal, and
if not equal, is sufficiently accounted for (Hyde and Simons 2001,
Williams et al. 2002). Potentially important sources of variation
are the impacts of ex situ board age (time since boards were cut)
and of in situ board weathering (time since boards were deployed
in an array) on salamander use. Once boards are placed in an
array, they start to integrate with their surrounding environment
forming microhabitats similar to that of natural cover objects.
However, older boards that have been weathered ex situ might
generate superior microhabitats than freshly cut boards that
have not weathered ex situ. Similarly, as boards weather in
situ, their microhabitat qualities may change over time, likely
becoming more similar to natural cover and potentially more
appealing to salamanders with age. While the need and effects
of relatively short (~2 month) establishment times are well
documented, the majority of studies have examined binary
comparisons of fresh and weathered boards, and even then, most
comparisons are made with short time differences between the
fresh and weathered boards (e.g., 1 year) relative to the total time
that coverboards are typically deployed (Grant et al. 1992; Monti
et al. 2000; Carlson and Szuch 2007; Grasser and Smith 2014).
Thus, potential additive or interactive effects of ex situ board age
and the longer-term board weathering process on multi-year
studies remains untested, especially because multi-year studies
cannot disentangle board weathering and weather condition
variables. If ex situ coverboard age and in situ weathering are
important parameters for salamander preference, not only
will comparability across previous studies be an issue, but also
comparisons within studies across multiple years (Grasser and
Smith 2014). Therefore, it is critical that we examine whether
salamanders have a preference for boards of either younger or
older ex situ age, and whether preference changes as boards
weather in situ (Brooks 1999; Hampton 2007; Grasser and Smith
To address this issue, we estimate the effects of coverboard
age by evaluating encounter probabilities using coverboard
arrays with different ex situ ages (0, 1, or 5 years) over the course
of three years. Although the boards that make up each array have
different ex situ ages, the arrays are all the same age. We assess
the following questions: 1) Do P. cinereus prefer boards that
were aged for longer periods ex situ in comparison with younger
boards given that they are more similar to natural cover objects?
2) Does in situ weathering of the boards during the study affect
P. cinereus preference? 3) Do larger P. cinereus frequent boards
that were aged for longer periods ex situ in higher proportions
than younger boards due to potential competition for resources?
4) Do boards that were aged for longer periods ex situ have a
higher proportion of adults or juveniles than younger boards?
These data will add to the growing understanding of salamander
coverboard preference and can be used to increase homogeneity
and standardization in study design, making coverboard
analyses more comparable both within multi-year studies and
MateriaLS and MetHodS
Field site and experimental set-up.—Our three study sites
were located in the Buffam Brook Community Forest on the
southeast side of Boyden Road in Palmer, Massachusetts (Site
1: 42.408944°N, 72.435056°W; Site 2: 42.408056°N, 72.435306°W;
Site 3: 42.407806°N, 72.434194°W). The forest canopy consists
of several species common to the region including Red Oak
(Quercus rubra), White Oak (Q. alba), Yellow Birch (Betula
alleghaniensis), Red Maple (Acer rubrum), White Ash (Fraxinus
americanus), Hemlock (Tsuga canadensis), and White Pine
(Pinus strobus) (Buffam Brook Community Forest Stewardship
Plan 2017). Common salamander species include Ambystoma
maculatum, Hemidactylium scutatum, and Notophthalmus
viridescens. However, P. cinereus dominates in the region.
Plethodon cinereus typically have a home range of 10–30 m2
(Muñoz et al. 2016; Sutherland et al. 2016; Hernández-Pacheco
et al. 2019) and spend the majority of their time underground
(Bailey et al. 2004). The range-wide eco-educational research
network SPARCnet (www.sparcnet.org) has developed
recommended coverboard sampling protocols for P. cinereus,
which we have adopted. SPARCnet has standardized wood type
(untreated solid pine), coverboard size (25 cm × 25 cm), and the
coverboard array design (50 boards total in a 5 × 10 array with
each board spaced 1 m apart) (Muñoz et al. 2016; Sutherland et
al. 2016; Hernández-Pacheco et al. 2019; Tedesco 2019). Each site
consisted of 50 coverboards arranged in a 5 × 10 array, with each
board separated by one meter (Fig. 1). Zero-year old boards were
purchased and newly cut in summer 2017. They were kept inside
and did not interact with the elements. Both one-year old boards
and five-year old boards were unused extra boards from previous
studies. They were left outside unused in small piles. They had
not been placed in a coverboard array and did not interact with
salamanders prior to our study. At each of the three sites, we
placed different ex situ board age cohorts (0, 1, and 5 years old)
Herpetological Review 52(1), 2021
in each array, with the organization of boards being determined
prior to placement with a random number generator. At site
one, 16 boards were zero-years old, 17 boards were one-year old,
and 17 boards were five-years old. At site two, the make-up was
17:16:17 for 0, 1, and 5-year old boards, respectively, and at site
three, it was 17:17:16. All boards were deployed on 20 August 2017
and sampling began on 15 October 2017. Natural cover objects
were removed from each site prior to boards being placed flush
with the ground.
Each coverboard was checked once approximately every two
weeks in the Fall of 2017 (Oct 15–Nov 24), Spring of 2018 (Apr 13–
Jul 23), and Spring (Apr 15–May 24) and Fall of 2019 (Oct 17–Nov
19) (Tables 1, A1; osf.io/46hrk). Personnel limitations meant it
was not possible to sample in the Fall of 2018. Prior to sampling,
the air temperature and soil temperature were recorded. During
sampling, P. cinereus found under boards were captured and
placed in a clear plastic bag (protocol following Moore 2009).
All P. cinereus were counted as presence-absence under each
board. Data collected included the specific board they were
captured under, their snout–vent length (SVL, measured twice
and averaged), total length (measured twice and averaged), their
sex (based on the presence or absence of testes, sensu Gillette
and Peterson 2001), color morph (striped versus lead-back), egg-
count, and the presence or absence of cirri. Further, P. cinereus
were considered juveniles if their SVL was < 35 mm and adults
if they were ≥ 35 mm (Sayler 1966). After data were collected, P.
cinereus were released adjacent to the board they were captured
Statistical analyses.—Generalized linear mixed-effects
models (GLMM) assuming a binomial error distribution were
used to assess how the dependent variable (presence of P. cinereus)
responded to both age-related effects and soil temperature.
Specifically, the unit of measurement is the coverboard, and the
binary dependent variable is the presence (y = 1) or absence (y =
0) of at least one salamander under each board on each sampling
occasion. The age-related effects that were incorporated into
models included ex situ board age (categorical predictor that
was constant across time: 0, 1, or 5 years old) and in situ board
weathering in the array (a continuous six-month ‘age’ variable
calculated as the deployment age plus 6 months per additional
sampling period, for example, the value was 0 for months 0–6,
0.5 for months 7–12, etc.). The aim of these two metrics was to
capture each board’s ex situ age relative to other boards but also
capture how boards being in the field over the multi-year study
impacted P. cinereus captures. Quadratic effects of temperature
have been previously found to affect salamander presence, with
P. cinereus preferring intermediate temperatures (Grasser and
taBLe 1. Salamander captures per season at each site totaling 427
captures over three years.
Site 1 Site 2 Site 3 Total
Fall 2017 11 24 5 40
Spring 2018 37 61 15 113
Spring 2019 31 50 23 104
Fall 2019 44 101 25 170
Fig. 1. Coverboard organization at all three sites set in arrays of 5 x 10 boards. Green signifies zero-year old boards, yellow-brown signi-
fies one-year old boards, brown signifies five-year old boards. Board location was set using a random number generator with 16 zero-
year old boards, 17 one-year old boards, and 17 five-year old boards at site 1, 17 zero-year old boards, 16 one-year old boards, and 17
five-year old boards at site 2, and 17 zero-year old boards, 17 one-year old boards, and 16 five-year old boards at site 3.
Herpetological Review 52(1), 2021
Smith 2014; Muñoz et al. 2016; Sutherland et al. 2016; Hernández-
Pacheco et al. 2019). Therefore, we included both temperature
and temperature squared (i.e., allowing for a quadratic effect) as
additional factors in our analyses. A preliminary analysis showed
no difference in encounter probability between seasons (Fall vs.
Spring), so season was omitted from the modeling.
Our final candidate model set included all combinations of
temperature (including the quadratic effect), age effects (ex situ
age and in situ weathering), and both additive and interactive site
effects that allowed the temperature and age effects to vary by
site (Table 2). Therefore, the full fixed effect model was: Presence
~ Site * (Age + Weathering + temperature + temperature2).
Because of the repeated sampling of boards across the season,
the unique board ID was included as a random effect in all
models. The ‘Age’ and ‘Weathering’ factors allow for testing of
which covariate best predicts P. cinereus presence, with the ‘Age’
factor assessing ex situ board age and ‘Weathering’ assessing in
situ board weathering from the starting point of the study. Model
selection was performed using AIC corrected for small sample
size (AICc, Burnham and Anderson 2002). For a given candidate
model set, AICc is a relative measure of the quality of the models,
where lowest AIC is considered the ‘best.’ Models were analyzed
in R v. 4. 0. 0. (R Core Team 2020) using lme4 (Bates et al. 2019).
Additionally, we sought to analyze whether either P. cinereus
SVL or the juvenile:adult ratio were correlated with ex situ board
age. Normality was assessed via a Shapiro-Wilk test (Shapiro and
Wilk 1965), which demonstrated non-normally distributed data
(K = 0.937, p < 0.001), and as such, we used a Kruskal-Wallis rank
sum test of P. cinereus SVL and ex situ board age using a = 0.05 to
determine significance. A Pearson’s c2 test of independence for
taBLe 2. Model selection table illustrating the top performing model (bolded) based on generalized linear mixed-effects models under a bino-
mial distribution. Age = board age when boards were first set. Weathering = incremental increases in board age since boards were set. Temp
= temperature. Temp2 = quadratic effect of temperature. Mod Lik = Model likelihood. Cum Wt = Cumulative model weight. Site-board ID was
included as a random effect.
Models K AICc △AICc Mod Lik Cum Wt
Age (ex situ) + temp + temp2 + Site 7 1926.81 0 0.45 0.45
Site + Age (ex situ) + Weathering (in situ) + temp + temp2 8 1927.77 0.96 0.28 0.73
Age (ex situ) * Site + temp + temp2 9 1927.85 1.04 0.27 1
Age (ex situ) + temp + temp2 6 1946.00 19.19 0 1
Age (ex situ) + Weathering (in situ) + temp + temp2 7 1946.93 20.12 0 1
temp + temp2 + Site 5 1949.49 22.68 0 1
Weathering (in situ) + temp + temp2 + Site 6 1950.45 23.64 0 1
Weathering (in situ) * Site + temp + temp2 7 1951.83 25.03 0 1
Site + Age (ex situ) + Weathering (in situ) + temp 7 1955.24 28.44 0 1
Site * Age (ex situ) + Weathering (in situ) + temp 9 1956.24 29.44 0 1
Site * Weathering (in situ) + Age (ex situ) + temp 8 1956.71 29.91 0 1
Age (ex situ) + temp + Site 6 1962.19 35.39 0 1
Age (ex situ) + Weathering (in situ) + Site 6 1962.62 35.82 0 1
Age (ex situ) * Site + temp 8 1963.18 36.37 0 1
Weathering (in situ) + Age (ex situ) * Site 8 1963.61 36.80 0 1
temp + temp2 4 1963.92 37.11 0 1
Age (ex situ) + Site 5 1963.94 37.14 0 1
Age (ex situ) + Weathering (in situ) * Site 7 1964.13 37.33 0 1
Weathering (in situ) + temp + temp2 5 1964.85 38.05 0 1
Age (ex situ) * Site 7 1964.92 38.11 0 1
(Age (ex situ) + Weathering (in situ)) * Site 9 1965.13 38.32 0 1
Age (ex situ) + Weathering (in situ) + temp 6 1974.04 47.23 0 1
Weathering (in situ) + temp + Site 5 1977.92 51.12 0 1
Weathering (in situ) * Site + temp 6 1979.39 52.58 0 1
Age (ex situ) + temp 5 1980.99 54.18 0 1
Age (ex situ) + Weathering (in situ) 5 1981.44 54.64 0 1
Age (ex situ) 4 1982.76 55.96 0 1
temp + Site 4 1984.87 58.07 0 1
Weathering (in situ) + Site 4 1985.30 58.50 0 1
Site 3 1986.62 59.82 0 1
Weathering (in situ) * Site 5 1986.81 60.00 0 1
Weathering (in situ) + temp 4 1992.04 65.24 0 1
temp 3 1998.99 72.18 0 1
Weathering (in situ) 3 1999.44 72.64 0 1
1 2 2000.76 73.96 0 1
Herpetological Review 52(1), 2021
two factor variables was used to evaluate whether a relationship
existed between the juvenile:adult ratio of captured P. cinereus
and ex situ board age.
Supplement al information is prov ided in th e following online
repository: osf.io/46hrk (Hedrick et al. 2021).
A total of 427 P. cinereus were captured during the study (Table
1), with no other salamander species using the coverboards. 110
P. cinereus were found under zero-year old boards, 82 under
one-year old boards, and 235 under five-year old boards across
all sites. Both site 1 and 3 had relatively few captures across the
study limiting statistical assessments at those sites (site 1, N =
123 captures; site 3, N = 68 captures). However, site 2 had 236
captures. Models that include all sites failed to converge in all
except the most-simple models, which did not allow testing of
the proposed hypotheses. This suggested that the sample sizes
were not sufficient to estimate many of the parameters (e.g., site
specific contrasts, interaction terms). Following this, the most
data poor site, site 3, was removed from the analysis and then
models were refit. In the new analysis incorporating data only
from site 1 and 2, almost all models converged, which suggested
that sites 1 and 2 had adequate sample sizes for the inference
objectives of testing whether ex situ age and in situ weathering
influenced whether salamanders used a board, accounting for
The best performing GLMM model, based on AICc,
incorporated ex situ board age, temperature, and the quadratic
effect of temperature, but not in situ weathering of the individual
boards during the study. The second-best performing model
incorporated in situ weathering and had a ‐AIC of 0.95 in
comparison with the top model (Table 2; Table A2; osf.io/46hrk).
However, this was considered to be a redundant effect following
Arnold (2010). Specifically, adding an additional parameter (e.g.,
in situ weathering) incurs a penalty of +2 AICs, but since the
model deviance is not also reduced, the additional parameter
does not incur a net reduction in AIC. As a result, the additional
parameter should not be interpreted as having an ecological
effect (Arnold 2010; Leroux 2019). As has been demonstrated
previously, after assessing the data in terms of the quadratic
temperature effect (βtemp: 0.20 ± 0.09, βtemp2: -0.44 ± 0.09), we
found an optimal detection temperature of approximately 15°C.
At site 1, at peak detection temperature (15.6°C), the probability
(and 95% confidence intervals) of detecting a salamander under
a zero, one, or five-year old board was 0.089 (0.058–0.128), 0.043
(0.023–0.068), and 0.163 (0.117–0.222), respectively. At site 2, at
peak detection temperature (15.6°C), the probability (and 95%
confidence intervals) of detecting a salamander under a zero,
one, or five-year old board was 0.154 (0.109–0.210), 0.139 (0.095–
0.187), and 0.265 (0.205–0.332), respectively (Fig. 2A, B). At both
sites, five-year old boards had substantially higher detection
probabilities than either zero- or one-year old boards.
When evaluating the effects of mean SVL and age ratio,
all three sites were pooled. Of 418 captures where SVL was
measured, the mean SVL under zero-year old boards was 33.56
± 7.10, 36.01 ± 5.95 under one-year old boards, and 34.45 ± 7.15
under five-year old boards. Plethodon cinereus SVL was not
statistically significantly correlated with ex situ board age (p =
0.071, df = 2). Of the P. cinereus captured, 187 P. cinereus were
juveniles and 231 were adults ( Table 3), and the age ratio was
also not statistically significantly related with ex situ board age
(c2 = 3.26, p = 0.196, df = 2).
Herpetological monitoring studies are typically multi-year
efforts, which often involve coverboards (e.g., DeGraff and
Yamasaki 2002; Hocking et al. 2013; Sutton et al. 2013). Numerous
studies have called for standardization of coverboard study
design to increase comparability between studies (Carfioli et al.
2000; Moore 2009). As such, understanding the effects of ex situ
board age and in situ board weathering is critical to being able to
interpret long-term data (Hesed 2012; Grasser and Smith 2014).
Fig. 2. (A) The predicted per-board per-visit detection probability
for the best performing model (Presence ~ Age + Temperature +
Temperature2 + Site) for Site 1 and (B) Site 2. Green (left) is the
relationship for zero-year old boards, yellow-brown (middle) is for
one-year old boards, and brown (right) is for five-year old boards.
Solid lines are expected values and shaded areas represent 95%
confidence intervals generated using the bootMer function in lme4
(Bates et al., 2019) (C) Boxplot with quartiles for board age versus
snout–vent length (SVL). Means with standard deviations are shown.
The results of a Kruskal-Wallis rank sum test showed no significant
difference in SVL across board ages.
Herpetological Review 52(1), 2021
We found that boards that were aged for 5 years ex situ integrated
faster than younger boards and are more attractive to P. cinereus
post-installation when controlling for array age. However, zero-
year old and one-year old boards were not different in their
attractiveness. Further, we did not find in situ weathering of
individual boards during the study to have a substantial effect
suggesting that board age at the time of installation rather than
in situ weathering per se impacts P. cinereus preference. This
suggests that P. cinereus preferred the microhabitats under the
five-year old boards in comparison with those under the zero-
and one-year old boards and that ex situ board age is a factor in
deciding the quality of the microhabitat under the boards.
Previous work has demonstrated that boards have an
“establishment period” lasting several months post-installation
after which salamander detectability is no longer influenced
(DeGraff and Yamasaki 1992; Monti et al. 2000; MacNeil and
Williams 2013). Carlson and Szuch (2007) and Monti et al. (2000)
found no significant differences between new and weathered
boards after the establishment period, although in the latter
study it appeared that new boards may have had a longer
integration time. The collective consensus here being that an
initial and relatively short establishment time is necessary
when deploying coverboards, after which the boards are
equally attractive to salamanders. Indeed, our results showing
no differences between zero-year and one-year old boards are
consistent with these comparisons. It is likely that P. cinereus see
zero-year old and one-year old boards both as “relatively new”
boards after accounting for the establishment period. However,
when comparing relatively young boards (0–1 years) with much
older boards (5+ years), we found a significant difference in
detectability (Fig. 2A). Grasser and Smith (2014) also found
more P. cinereus under older coverboards (6–7 years old) than
new coverboards initially, but that the difference between the
old and new boards decreased over the course of their study;
interestingly, our results show the opposite pattern in that we
observed no such in situ weathering effect.
Although ex situ board age affects P. cinereus presence, it
does not disproportionality influence the detection of P. cinereus
with different mean SVL or affect the age ratio of P. cinereus (Fig.
2B). Carlson and Szuch (2007) similarly did not find a difference
in P. cinereus mean SVL under old and new boards. However,
Carlson and Szuch (2007) did find a significant difference in
Desmognathus fuscus mean SVL across board ages, suggesting
that there may be species-specific responses to board age. Marsh
and Goicochea (2003) did find more P. cinereus juveniles under
natural cover objects than coverboards suggesting a preference
for the microhabitats formed under natural wood in comparison
with that under coverboards. Further, Moore (2009) found no
difference in age structure of P. cinereus for natural cover objects
and coverboards, in accordance with our results. Our study
design did not include natural cover objects and it is possible that
even the five-year old boards in our study do not mimic natural
cover objects. More work will need to be done to determine how
the ratio of P. cinereus juveniles and adults is affected by ex situ
board age and how that compares with the use of natural cover.
Given their minimal expense, lack of damage to habitat, and
the short time required for censusing a large area, coverboards
are a powerful method for monitoring herpetofauna. Increased
standardization is critical for ensuring comparability both within
and between long-term studies (Hesed 2012). Both ex situ board
age and in situ board weathering are factors that can potentially
impact inferences gleaned from long term studies. We found
that ex situ board age influences P. cinereus presence, whereas
in situ board weathering may not. Moreover, there appeared to
be no effect of ex situ board age on either P. cinereus mean SVL
or juvenile:adult ratios. Our results suggest that boards may have
non-linear integration times whereby the first several months
after installation allow some degree of integration (establishment
period), followed by periods where boards do not become
significantly more integrated (which we found between zero-
and one-year old boards), succeeded by additional increases
in board integration (between one and five years). Ultimately,
board age should be considered, recorded, and itself monitored
through time in order to account for potential biases that result
from the variation in detectability we describe.
Acknowledgments.––We thank J. Fleming, B. Padilla, A. Vander
Linden, G. Mutumi, and E. Grant for help with experimental design,
discussions, and fieldwork. We thank the Sutherland lab group for
very helpful comments on an earlier draft of this manuscript. We
thank the Kestrel Land Trust for help identifying the site and allowing
access to the land. Funding sources include NSF 1612211 (BPH). The
protocol was conducted under IACUC 2018-0021. Finally, we thank
two anonymous reviewers and Kristen Cecala (associate editor) and
Robert Hansen (editor) for helpful reviews, which have improved the
clarity of the paper.
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