Temperature-induced Multi-species Cohort Effects in Sympatric Snakes
Richard B. King
Department of Biological Sciences and Institute for the Study of the
Environment, Sustainability, and Energy, Northern Illinois University,
DeKalb, IL 60115,
rbking@niu.edu
Short Title: Temperature-induced Multi-species Cohort Effects
Abstract
In reptiles, reproductive maturity is often determined by size rather
than age. Consequently, growth early in life may influence population
dynamics through effects on generation time and survival to
reproduction. Because reproductive phenology and pre- and post-natal
growth are temperature-dependent, environmental conditions may induce
multi-species cohort effects on body size in sympatric reptiles. I
present evidence of this using ten years of neonatal size data for three
sympatric viviparous snakes, Dekay’s Brownsnakes (Storeria
dekayi ), Red-bellied Snakes (S. occipitomaculata ) and Common
Gartersnakes (Thamnophis sirtalis ). End-of-season neonatal size
varied in parallel across species such that snout-vent length was
36-61% greater and mass was 65-223% greater in years when gestating
females could achieve higher April-May (vs. June-July or
August-September) operative temperatures. Thus, temperature had a larger
impact during follicular enlargement and ovulation than during gestation
or post-natal growth. Multi-species cohort effects like these may affect
population dynamics and increase with climate change.
Key Words: Gestation; Ovulation; Neonatal Size; Parturition;Storeria ; Thamnophis
Introduction
For many reptiles, more rapid growth results in earlier maturity (Gibson
& Hamilton 1984; Frazer, Green, and Gibbons 1993; Ford & Seigel 1994;
Bronikowski & Arnold 1999). This means that growth early in life can
influence population dynamics through effects on generation time and
survival to reproduction (Cole 1956; Gibbons et al. 1981; Oli & Dobson
2003). Rapid neonatal growth can produce a “silver-spoon effect” in
which individuals that grow quickly early in life also experience higher
growth rates later in life (Madsen & Shine 2000; Baron et al. 2010; Le
Henanff, Meylan & Lourdais 2013). Pre-natal events can also influence
post-natal growth (Wapstra et al. 2010; While et al. 2009). For example,
in Meadow Vipers (Vipera ursinii ursinii ), earlier parturition is
associated with greater offspring mass and body condition and faster
post-natal growth (Baron et al. 2010). Environmental temperature can
influence both the timing of parturtition (Blanchard & Blanchard 1940;
Cadby et al. 2010; Wapstra et al. 2010) and the rate of post-natal
growth (Arnold & Peterson 1989; Peterson, Gibson & Dorcas 1993; Adolph
& Porter 1996), potentially inducing cohort effects with long-term
impacts on population dynamics (Lindstrom & Kokko 2002; Beckerman et
al. 2003; Wittmer, Powell & King 2007). If environmental temperature
has similar effects on multiple sympatric species, multi-species cohort
effects may result.
Here, I provide evidence that pre-natal thermal conditions have parallel
effects on end-of-season neonatal size in wild populations of three
sympatric viviparous snakes, the Red-bellied Snake (Storeria
occipitomaculata ), Dekay’s Brownsnake (S. dekayi ), and the
Common Gartersnake (Thamnophis sirtalis ). All three are colubrid
snakes in the subfamily Natriciniae (Pyron, Burbrink & Weins 2013), are
widely distributed and locally abundant across eastern (and western,T. sirtalis ) North American (Powell, Conant & Collins 2016), and
have similar reproductive phenology. Mating mostly occurs in spring,
followed by follicular enlargement and ovulation (Noble 1937). At my
study site in Illinois, enlarged follicles are first detectable by
palpation in April and May. Gestation spans several months and
parturition, as indicated by the appearance of neonates and post-partum
females, commences in late July or early August. Neonates lack yolk
reserves at birth (Mack et al. 2017) but begin feeding soon after
parturition and grow rapidly until cold weather brings about the
cessation of above ground activity (late September – mid-October). Body
size differs markedly among species, with S. occipitomaculataranging from 67-284 mm snout-vent length (SVL) and 0.4-15.8 g, S.
dekayi ranging from 76-378 mm SVL and 0.4-32.4 g, and T.
sirtalis ranging from 115-780 mm SVL and 0.9-277.6 g at my study site.
Diet also differs among species with S. occipitomaculataconsuming almost exclusively slugs, S. dekayi consuming slugs,
snails, and earthworms, and T. sirtalis consuming earthworms,
amphibians, rodents, and birds (Virgin & King 2019; personal
observation).
Methods
I conducted a capture-mark-recapture study of S. occipitomaculata,
S. dekayi , and T. sirtalis at Potawatomi Woods Forest Preserve
in northern DeKalb County, Illinois (42.4051 N, -88.8635 W) between
April 2009 and October 2018. Fieldwork was focused in a wet sedge meadow
and adjacent old field (approximately 5 ha; Fig. 1). To facilitate snake
detection, I placed 33-41 artificial cover objects (used rubber conveyor
belt measuring ca. 60 x 90 x 1 cm) 15-20 m apart in an irregular grid. I
checked artificial cover objects approximately weekly and captured
snakes by hand. I classified snakes by species and sex and measured
snout-vent length (SVL) using a cloth tape and mass using an electronic
balance (Fitch 1987). Snakes were individually marked by clipping
ventral scales (using 3.5-x magnification) and released where captured,
usually within 10 minutes.
I identified neonates (animals captured prior to their first
hibernation) as a distinct age class by plotting SVL against day of year
(DOY) separately for each year and species (an example is shown in Fig.
2). For each species, I used analysis of covariance with neonatal SVL or
neonatal mass as dependent variable, year as factor, DOY as covariate,
and including the year-by-DOY interaction, to generate equations
relating SVL and mass to DOY. Prior to analysis, I transformed SVL and
mass by adding 1 and computing natural logarithms to linearize
relationships and homogenize variances (analyses of untransformed data
yielded virtually identical results). To compare year-to-year variation
in neonatal growth, I computed the expected SVL and mass on October 1,
the approximate end of the active season, for each year and species
combination.
To identify possible temperature-related causes of year-to-year
variation in end-of-season SVL and mass, I estimated operative body
temperatures using the hindcaster feature of NicheMapR (microclimate
model with gridMET USA meteorological grids and ectotherm model,
http://bioforecasts.science.unimelb.edu.au/app_direct/ectotherm_usa/;
Kearney & Porter 2017, 2020; Kearney 2020). Operative temperatures were
estimated separately for three periods corresponding to follicular
enlargement and ovulation (April-May), gestation (June-July), and
post-natal growth (August-September). For April-May and June-July, I set
animal mass to the mean mass of gravid females at my study site
(S. occipitomaculata = 9.7 g, S. dekayi = 17.5 g, T.
sirtalis = 76.8 g); for August-September, I set animal mass to the mean
mass of neonates at my study site (S. occipitomaculata = 1.0 g,S. dekayi = 1.5 g, T. sirtalis = 3.5 g; see Appendix 1 for
other model settings). For each species, year, and period, I computed
the number of hours that body temperature exceeded 25 °C, the
temperature at which natricinae digestive rate, crawling speed, oxygen
consumption, and tongue flick rate reach ca. 50% of their maxima and
above which oxygen consumption increases rapidly from baseline
(Stevenson, Peterson & Tsuji 1985). I used analysis of covariance with
species as a factor to test whether end-of-season SVL or mass covaried
with hours >25 °C in April-May, June-July, or
August-September. I first tested for a significant factor-by-covariate
interaction to determine if the slope of the relationship between
end-of-season SVL or mass and hours >25 °C differed among
species. When no such interaction was detected (Results), main effects
were tested in follow-up analyses of covariance with the
factor-by-covariate interaction omitted. I generated estimates of effect
size (partial η2; the proportion of variation in
end-of-season SVL or mass explained by hours >25 °C after
removing variation attributable to species; Richardson 2011) to assess
the magnitude of each period’s influence. For comparison, I computed
mean April-May, June-July, and August-September air temperatures from
daily temperature data downloaded from
https://prism.oregonstate.edu/. IBM SPSS Statistics Version 26 was
used for analysis with α = 0.05.
Results
Neonate captures numbered 10 to 64 per year for S.
occipitomaculata (total n = 269 after excluding 2009 and 2010 due to
small sample size), 10 to 106 per year for S. dekayi (total n =
437 after excluding 2012 due to small sample size), and 21 to 193 per
year for T. sirtalis (total n = 988). Analysis of covariance
revealed that in each species the relationship between SVL and DOY
differed in slope among years as indicated by a significant year-by-DOY
interaction (S. occipitomaculata: F 7,253 = 7.27,P < 0.001); S. dekayi :F 8,418 = 4.65, P < 0.001;T. sirtalis : F 9,962 = 7.15, P< 0.001; Appendix 2). Similarly, the relationship between mass
and DOY differed in slope among years (S. occipitomaculata:
F 7,251 = 5.23, P < 0.001); S.
dekayi : F 8,419 = 5.67, P <
0.001; T. sirtalis : F 9,965 = 6.45,P < 0.001; Appendix 2). End-of-season SVL and mass
varied in parallel among species (SVL: intraclass correlation = 0.73,
95% confidence limits = 0.37, 0.94; mass: intraclass correlation =
0.53, 95% confidence limits = 0.02, 0.89; Zar 2010, pp 411-414), was
greatest in 2010 and 2016, and was least in 2009 and 2017 (Table 1, Fig.
3.A).
Depending on species, body temperature was predicted to exceed 25 °C for
an average of 250.5-268.4 hr in April-May (range = 183-253), 651.6 –
669.4 hr in June-July (range = 543-753), and 485.3-503.8 hr in
August-September (range = 427-540; Table 1). Tests for a difference in
slope among species in the relationship between end-of-season SVL and
mass to hours >25 °C were consistently non-significant
(April-May – SVL: F2,21 -= 1.249, P = 0.304, mass:
F2,21 = 1.457, P = 0.255; June-July – SVL:
F2,21 -= 1.482, P = 0.250, mass: F2,21 =
3.087, P = 0.067; August-September – SVL: F2,21 -=
0.015, P = 0.985, mass: F2,21 = 0.021, P = 0.979). In
subsequent analyses with the factor-by-covariate interaction omitted,
species had consistently significant effects on end-of-season SVL and
mass (F2,23 = 51.969 – 85.889, P < 0.001),
April-May hours >25 °C had significant effects on
end-of-season SVL and mass (SVL: F1,23 = 15.053, P =
0.001; mass: F1,23 = 12.795, P = 0.002; Fig. 3.B),
June-July hours >25 °C had a no significant effect on
end-of-season SVL but did have a significant effect on mass (SVL:
F1,23 = 2.245, P = 0.148; mass: F1,23 =
5.875, P = 0.24), and August-September hours >25 °C had no
significant effect on end-of-season SVL or mass (SVL:
F1,23 = 1.654, P = 0.210; mass: F1,23 =
2.104, P = 0.160). Estimated effect sizes indicated that April-May hours
>25 °C had the largest effect on end-of-season SVL and mass
(SVL: partial η2 = 0.40; mass: partial
η2 = 0.36), June-July hours >25 had small
to medium effects (SVL: partial η2 = 0.09; mass:
partial η2 = 0.24), and August-September hours
>25 had only small effects (SVL: partial
η2 = 0.07; mass: partial η2 = 0.08).
Similar results were obtained using thresholds of 10 C and 20 C except
that August-September hours >20 C had a significant effect
on end-of-season SVL and mass (SVL: F1,23 = 4.909, P =
0.037, partial η2 = 0.18; mass: F1,23= 5.339, P = 0.030, partial η2 = 0.19). The duration
of time that body temperature was predicted to exceed 25 °C was
positively, but imperfectly, correlated with mean air temperature
(April-May: r2 = 0.66, 0.73, and 0.79 for S.
occipitomaculata , S. dekayi , and T. sirtalis ,
respectively; June-July: r2 = 0.97, 0.98, and 0.98:
August-September: r2 = 0.66, 0.70, and 0.70; all P
< 0.05).
Discussion
Sympatric S. dekayi , S. occipitomaculata , and T.
sirtalis showed parallel patterns of variation in neonatal size across
10 years such that end-of-season SVL was 36-61% greater and
end-of-season mass was 65-223% greater in years with maximal size
relative to years with minimal size. Furthermore, end-of-season SVL and
mass were associated with the amount of time that gravid females could
achieve April-May body temperatures >25 °C. This result
suggests that the rate follicular enlargement and timing of ovulation
had especially large impacts on neonate size. Variation in the amount of
time that females could achieve June-July body temperatures
>25 °C (gestation and parturition) or the amount of time
that neonates could maintain August-September temperatures
>25 °C (post-natal growth) had less impact. Of these three
periods, the amount of time that snakes could achieve body temperatures
>25 °C was least for April-May (averaging ca. 260 hr vs.
660 hr in June-July and 490 hr in August-September) and had the largest
among-year coefficient of variation (23-27% depending on species vs.
9-11% in June-July and 8-9% in August-September). Behavioral
thermoregulation may allow gestating females to achieve their preferred
body temperatures more easily in June-July when ambient temperatures are
high than in April-May when ambient temperatures are lower (Peterson
1987; Huey et al. 1989). Possibly, the small size of neonates limits
their thermoregulatory ability during August-September (Bittner, King &
Kerfin 2002). Alternatively, the thermal dependence of physiological
processes in neonates may differ from that of adults as suggested by the
significant association of end-of-season SVL and mass with
August-September hours >20 °C but not >25 °C.
Experimental manipulations of environmental temperatures in semi-natural
enclosures could provide more rigorous tests of thermal effects on
neonatal size (Blouin-Demers, Kissner & Weatherhead 2000; Lourdais et
al. 2004; Le Henaff et al. 2013). For example, in a multi-year study ofT. sirtalis maintained in outdoor enclosures, Blanchard &
Blanchard (1940) found that parturition dates were accelerated 4.5 days
per °F increase in mean May-July temperature (= 8.1 days per °C). Given
that April-July temperatures differed by 3.3 °C among years at my study
site (https://prism.oregonstate.edu/), their results suggest that
parturition dates might vary ca. 25 days among years, shortening or
extending the time available for post-natal growth accordingly.
Unfortunately, accurate estimates of the timing of ovulation and
parturition are difficult to obtain and are likely to vary among
individuals in the field.
Cohort effects at my study site were of sufficient magnitude to
accelerate attainment of reproductive maturity in at least some
individuals during warm years. For example, in 2010, the end-of-season
SVL of S. dekayi neonates (185.5 mm) exceeded the minimum SVL of
reproductively mature males (175 mm based on presence of sperm in
cloacal smears, personal observation) and at least some neonatal males
exceeded 175 mm in 2010, 2014, 2016, and 2018. Accelerated maturation
promotes population growth by reducing the likelihood of mortality
before reproductive maturity and by shorting generation time (Cole 1956;
Gibbons et al. 1981; Oli & Dobson 2003). In addition, the larger size
attained by neonates in warm years may result in increased survival
(Jayne & Bennett 1990) independent of age at reproductive maturity.
Consequently, the cohort effects described here may generate temporal
variation in population abundance, density, and size structure much like
patterns of geographic variation attributed to differences in activity
season (Adolph & Porter 1996). Given the degree of dietary overlap
among snake species at my study site, especially between S.
dekayi and S. occipitomaculata (Virgin & King 2019), temporal
variation in abundance and density may affect competitive interactions
among snake species and have top-down and bottom-up effects on their
prey and predators. Additional data on the degree to which cohort
effects persist beyond the neonatal life stage and the extent to which
reproductive maturity is size vs. age dependent (Bronikowski & Arnold
1999) would aid in evaluating their impact on population dynamics.
Cohort effects like those observed here are not unusual, having been
documented in a wide range of plant and animal taxa (Lindstrom & Kokko
2002 and citations therein). What is unusual, although not unexpected,
is the occurrence of parallel cohort effects across multiple sympatric
species. Because of their physiological dependence on environmental
temperature (Huey 1982), ectothermic vertebrates are likely candidates
for exhibiting multi-species cohort effects but similar patterns are
anticipated in other taxa as a consequence of different shared
environmental drivers (e.g., water availability in plants, Streng,
Glitzenstein & Harcombe 1989; beech masting in rodents, Wittmer et al.
2007; fire in grassland birds, Powell 2006). Although analyses of cohort
effects on single-species population dynamics have been fruitful
(Lindstrom & Kokko 2002; Becherman et al. 2003; Wittmer et al. 2007; Le
Galliard, Marquis, and Massot 2010), multi-species cohort effects, with
their potential impacts on competitive and predator-prey interactions,
warrant further study (Huss et al. 2013). The more frequent occurrence
of extreme weather events (IPCC 2014) may result in even larger cohort
effects than those observed here (Lourdais et al. 2004; Cadby at al.
2010). Equally interesting are situations where weather or other
environmental drivers have contrasting effects on sympatric species due
to differing ecological traits (e.g., Ma et al. 2018). For example, a
hot year might have negative effects on diurnal or open-habitat species,
but positive effects on nocturnal or shade-dwelling species, as has been
suggested in the context of climate change (Huey et al. 2012; Paaijmans
et al. 2013). The fact that cohort effects can arise from pre-natal or
pre-ovulatory environmental conditions has the potential to magnify the
impact of climate change on demography and life history.
Acknowledgements
I thank M. Blackowicz, P. Larson, S. Melton, A. Moore, T. O’Brien, L.
Raimondi, K. Skar, A. Stedman, B. Tendick-Matesanz, and E. Virgin for
assistance in the field and the DeKalb County Forest Preserve District
for access to the field site. I thank R. Huey for comments on the
manuscript and M. Kearney for advice on NicheMapR implementation. This
work was conducted with approval of the Northern Illinois University
Institutional Animal Care and Use Committee (LA08-381) under permits
from the Illinois Department of Natural Resources (NH09.0584-NH17.0584,
HRP18.0584).
Data and Code Accessibility
Data and R code will be archived at Dryad.
Literature Cited
Adolph, S.C. & Porter, W.P. (1996). Growth, seasonality, and lizard
life histories: age and size at maturity. Oikos 77 ,
267-278.
Arnold, S.J. & Peterson, C.R. (1989). A test for temperature effects on
the ontogeny of shape in the Garter Snake Thamnophis sirtalis .Physiol Zool. 62 , 1316-1333.
Baron, J.P., Le Galliard, J. F., Tully, T. & Ferriere, F. (2010).
Cohort variation in offspring growth and survival: prenatal and
postnatal factors in a late-maturing viviparous snake. J Anim
Ecol. 79 , 640-649.
Beckerman, A.P., Benton, T.G., Lapsley, C.T. & Koesters, N. (2003).
Talkin’ ‘bout my generation: environmental variability and cohort
effects. Am Nat. 162 , 754-767.
Bittner T.D., King, R.B. & Kerfin, J.M. (2002). Effects of body size
and melanism on the thermal biology of garter snakes (Thamnophis
sirtalis ). Copeia 2002 , 477-484.
Blanchard, F.N. & F. C. Blanchard. (1940). Factors determining time of
birth in the garter snake Thamnophis sirtalis sirtalis(Linnaeus). Papers from the Michigan Academy of Science, Arts and
Letters 26, 161-176.
Blouin-Demers, G., Kissner, K.J. & Weatherhead, P.J. (2000). Plasticity
in preferred body temperature in young snakes in response to temperature
during development. Copeia 2000 , 841-845.
Bronikowski, A.M. & Arnold, S.J. (1999). The evolutionary ecology of
life history variation in the garter snake Thamnophis elegans .Ecology 80 , 2314-2325.
Cadby, C.D., While, G.M., Hobday, A.J., Uller, T. & Wapstra, E. (2010).
Multi-scale approach to understanding climate effects on offspring size
at birth and date of birth in a reptile. Integr Zool. 5 ,
164-175.
Cole, L.C. (1954). The population consequences of life-history
phenomena. Q Rev Biol. 29 , 103-137.
Fitch, H.S. (1987). Collecting and life-history techniques. InSnakes: ecology and evolutionary biology : 43-164. Seigel, R.A.,
Collins, J.T. & Novak, S.S. (Eds). New York: Macmillan Publishing
Company.
Ford, N.B. & Seigel, R.A. (1994). An experimental study of trade-offs
between age and size at maturity: effects of energy availability.Funct Ecol. 8 , 91-96.
Frazer, N.B., Greene, J.L. & Gibbons, J.W. (1993). Temporal variation
in growth rate and age at maturity of male painted turtles,Chrysemys picta . Am Midl Nat. 130 , 314-324.
Gibbons, J.W., Semlitsch, R.D., Greene J.L. & Schubauer, J.P. (1981).
Variation in age and size at maturity of the slider turtle
(Pseudemys scripta ). Am Nat. 117 , 841-845.
Gibson, C.W.D. & Hamilton, J. (1984). Population processes in a large
herbivorous reptile: the giant tortoise of Aldabra Atoll.Oecologia 61 , 230-240.
Huey, R.B. (1982). Temperature, physiology, and the ecology of reptiles.
In Biology of the Reptilia, Vol. 12, Physiology (C) : 25-91. Gans,
C. & Pough, H.F. (Eds.). London: Academic Press.
Huey R.B., Kearney, K.R., Krockenberger, A., Holtum, J.A.M, Jess, M. &
Williams, S.E. (2012). Predicting organismal vulnerability to climate
warming: roles of behaviour, physiology and adaptation. Philos
Trans R Soc Lond B Biol Sci. 367 , 1665–1679.
Huey, R.B., Peterson, C.R., Arnold, S.J. & Porter, W.P. (1989). Hot
rocks and not-so-hot rocks: retreat-site selection by garter snakes and
its thermal consequences. Ecology 70 , 931-944.
Huss, M., de Roos, A.M., Van Leeuwen, A., Casini, M. & Gardmark, A.
(2013). Cohort dynamics give rise to alternative stable community
states. Am Nat. 169 , 673-683.
[IPCC] Intergovernmental Panel on Climate Change. (2014). Climate
change 2014: synthesis report. Contribution of Working Groups I, II and
III to the Fifth Assessment Report of the Intergovernmental Panel on
Climate Change [Core Writing Team, Pachauri, R.K. & Meyer, L.A.
editors]. Geneva: IPCC. https://www.ipcc.ch/report/ar5/syr/.
Jayne, B.C. & Bennett, A.F. (1990). Selection on locomotor performance
capacity in a natural population of garter snakes. Evolution44 , 1204-1229.
Kearney, M R. (2020). How will snow alter exposure of organisms to cold
stress under climate warming? Glob Ecol Biogeogr. 29 ,
1246–1256.
Kearney, M.R. & Porter, W.P. (2017). NicheMapR—An R package for
biophysical modelling: the microclimate model. Ecography40 , 664–674.
Kearney, M.R. & Porter, W.P. (2020). NicheMapR – an R package for
biophysical modelling: the ectotherm and Dynamic Energy Budget models.Ecography 43 , 85-96.
Le Galliard, J.F., Marquis, O. & Massot, M.. (2010). Cohort variation,
climate effects and population dynamics in a short-lived lizard. J
Anim Ecol. 79 , 1296-1307.
Le Henanff, M., Meylan, S. & Lourdais, O. (2013). The sooner the
better: reproductive phenology drives ontogenetic trajectories in a
temperate squamate (Podarcis muralis ). Biol J Linn Soc
Lond. 108 , 384-395.
Lindstrom, J. & Kokko, H. (2002). Cohort effects and population
dynamics. Ecol Lett. 5 , 338-344.
Lourdais, O., Shine, R., Bonnet, X., Guillon, M. & Naulleau, G. (2004).
Climate affects embryonic development in a viviparous snake,Vipera aspis . Oikos 104 , 551-560.
Ma, B.-J.S., Li, S-R., Hao, X Bi, J.-H. & Du, W.-G. (2018). The
vulnerability of developing embryos to simulated climate warming differs
between sympatric desesrt lizards. J Exp Zool A Ecol Integr
Physiol. 329 , 252-261.
Mack, E.W., Beck, J.L., Stanford, K.M. & King, R.B. (2017). Maternal
investment and delayed feeding in neonatal Lake Erie watersnakes: a
life-history strategy. J Zool. 301 , 150-156.
Madsen, T. & Shine, R. (2000). Silver spoons and snake body sizes: prey
availability early in life influences long-term growth rates of
free-ranging pythons. J Anim Ecol. 69 , 952-958.
Noble, G.K. (1937). The sense organs involved in the courtship ofStoreria , Thamnophis and other species. Bull Am Mus
Nat Hist. 73 , 673−725.
Oli, M.K. & Dobson, F.S. (2003). The relative importance of
life-history variables to population growth rate in mammals: Cole’s
prediction revisited. Am Nat. 161 , 422-440.
Paaijmans, K.P., Heinig, R.L., Seliga, R.A., Glanford, J.I., Blanford,
S., Murdock, C.C. & Thomas, M.B.. (2013). Temperature variation makes
ectotherms more sensitive to climate change. Glob Chang Biol.19 , 2373-2380.
Peterson, C.R. (1987). Daily variation in the body temperatures of
free-ranging garter snakes. Ecology 68 , 160-169.
Peterson, C.R., Gibson, A.R. & Dorcas, M.E. (1993). Snake thermal
ecology: the causes and consequences of body-temperature variation. InSnakes: ecology and evolutionary biology : 241-314. Seigel, R.A.,
Collins, J.T. & Novak, S.S. (Eds). New York: Macmillan Publishing
Company.
Powell, F.L.A. (2006). Effects of prescribed burns and bison (Bos
bison ) grazing on breeding bird abundances in tallgrass prairie.Auk 123 , 183-197.
Powell, R., Conant, R. & Collins, J.T. (2016). Peterson field
guide to reptiles and amphibians of eastern and central North America,
4th edition. Boston: Houghton Mifflin Harcourt
Publishing.
Pyron, R.A., Burbrink, F.T. & Weins, J. (2013). A phylogeny and revised
classification of squamata, including 4161 species of lizards and
snakes. BMC Evol Biol. 13 , 93 (2013).
https://doi.org/10.1186/1471-2148-13-93
Richardson, J.T.E. (2011). Eta squared and partial eta squared as
measures of effect size in educational research. Educ Res Rev.6 , 135-147.
Stevenson, R.D., Peterson, C.R. & Tsuji, J.S. (1985). The thermal
dependence of locomotion, tongue flicking, digestion, and oxygen
consumption in the wandering garter snake. Physiol Zool.58 , 46-57.
Streng, D.R., Glitzenstein, J.S. & Harcombe, P.A. (1986). Woody
seedling dynamics in an East Texas floodplain forest. Ecol
Monogr. 59 , 177-204.
Virgin, E.E. & King, R.B. (2019). What does the snake eat? Breadth,
overlap, and non-native prey in the diet of three sympatric natricine
snakes. Herpetol Conserv Biol. 14 , 132-142.
Wapstra, E., Uller, T., While, M., Olsson, M. & Shine, R. (2010).
Giving offspring a head start in life: field and experimental evidence
for selection on maternal basking behavior in lizards. J Evol
Biol. 23 , 651-657.
While, G.M., Uller, T., McEvoy, J. & Wapstra, E. (2009). Long-lasting
effects of among- but not within-litter timing of birth in a viviparous
lizard. Evol Ecol Res. 11 , 1259-1270.
Wittmer, H.U., Powell, R.A. & King, C.M. (2007). Understanding
contributions of cohort effects to growth rates of fluctuating
populations. J Anim Ecol. 76 , 946-956.
Zar, J.H. (2010). Biostatistical analysis, 5thedition . Upper Saddle River: Prentice Hall.
Table 1. Number of hours that body temperatures are expected to exceed
25 °C in April-May, June-July, and August-September and end-of-season
SVL and mass of neonatal S. occipitomaculata, S. dekayi ,
and T. sirtalis at Potawatomi Woods Forest Preserve, DeKalb
County, Illinois in 2009-2018. Small sample size precluded computing
end-of-season snout-vent length and mass for S. dekayi in 2012
and S. occipitomaculata in 2009 and 2010. Values shown for SVL
and mass are back-transforms from the regression of ln(SVL+1) and
ln(mass+1) on DOY (Appendix 2) for DOY = 274.