Survival rates are known to vary over the course of an individual’s lifetime and among individuals within a population. Quantifying the natural variability in survival rates is crucial when scaling up to infer the dynamics of populations. Using ten years of mark–recapture data from two adjacent wetlands on the Florida Panhandle, we investigated individual and temporal variability in survival rates of Reticulated Flatwoods Salamanders (Ambystoma bishopi). Our objectives were to 1) provide the first estimates of survival for the species, 2) evaluate the relationship between body size and mortality risk, 3) quantify the degree of variability in survival rates across the study period, and 4) discern whether variability in survival or detection correlates with environmental conditions. To address these objectives, we constructed a modified Cormack-Jolly-Seber model that includes body size and year as covariates. Mean annual survival was estimated to be 0.72 and was strongly correlated with body size; survival rates of the smallest individuals in the study were 0.5 and those of the largest individuals were 0.85. Survival also varied considerably across years, but it did not correlate with temperature extremes or rainfall. Therefore, a key priority for future research should be to identify the ecological correlates of mortality risk in A. bishopi. Our results can be integrated into demographic projections for Reticulated Flatwoods Salamanders and will help managers to discern population viability, evaluate alternative management strategies (e.g., habitat restoration), or buffer the impacts of climate change. More broadly, our work highlights the need for more long-term studies that will garner accurate estimates of vital rates to aid ongoing recovery efforts for endangered and at-risk species.

SURVIVAL rates are known to vary over the course of an individual’s lifetime and among individuals within a population (Roff, 1992; Cooch, 2002; Ebenman and Persson, 2012). Mortality risk is intrinsically tied to environmental conditions and body size and can therefore show considerable variability through time and across a population (Laurie and Brown, 1990; Forsman, 1991; Sorci and Clobert, 1999; Kunz and Ekman, 2000; Church et al., 2022). For instance, in amphibians, regulating temperature and water balance is more challenging for smaller individuals, making them susceptible to prolonged periods of drought, temperature extremes, and food deprivation (Ash et al., 2003; Knapp et al., 2003; Rothermel and Semlitsch, 2006; Tilghman et al., 2012). In addition, body size can directly influence an individual’s vulnerability to gape-limited predators, such that smaller individuals experience higher mortality than larger individuals (Shine, 1991; Janzen, 1993; Forsman, 1996; Sorci and Clobert, 1999; Lind et al., 2008; Kishida et al., 2009).

Quantifying the natural variability in survival rates is crucial when scaling up to infer the dynamics of populations (Brooks et al., 2000; Rees and Ellner, 2009). Certain life histories can be extremely sensitive to changes in vital rates, and stochastic forces strongly impact population growth (Lande, 1993; Letcher and Horton, 2008; Van de Wolfshaar et al., 2008; Rees and Ellner, 2009; Xu et al., 2010). By treating survival as a fixed parameter, traditional demographic methods used to conduct population viability analyses may generate erroneous conclusions regarding population status and extinction risk (Ramula et al., 2009; Hegg et al., 2013). In the context of modern conservation efforts, assessments that neglect variation in mortality could lead to flawed management decisions, thereby reducing the effectiveness of conservation measures for at-risk species.

For studies with infrequent sampling events or low capture probabilities, however, discerning the relationship between survival and ecological covariates is often difficult to achieve (Wulfsohn and Tsiatis, 1997; Su and Wang, 2012; Langrock and King, 2013; Rose et al., 2018). Capture–recapture data sets are largely comprised of partial records, including individuals that were born prior to the start of the study, individuals that die after the study has ended, and instances that simply went unobserved (Lebreton et al., 1992; Pike et al., 2008; Royle, 2008; Papadatou et al., 2012; Rose et al., 2018). Historically, records such as these were often omitted from analyses (Bailey et al., 2004; Matechou et al., 2013), or it was necessary to assume survival rates were constant for models to be identifiable (Pollock et al., 1990). Methodological advances have allowed for the inclusion of more partial records in mark–recapture models (Pledger et al., 2003, 2010; Colchero and Clark, 2012; Su and Wang, 2012), but challenges remain (Letcher and Horton, 2008; Gilroy et al., 2012; Barbour et al., 2013; Ergon and Gardner, 2014). Notably, if ecological covariates impact both mortality risk and animal behavior, models may inadvertently conflate variation in survival with variation in detectability (Kellner and Swihart, 2014).

Amphibians exemplify the challenges associated with obtaining survival estimates from wild populations. Many amphibians are long lived, sometimes surviving for multiple decades in their terrestrial life stage (Duellman and Trueb, 1994; Petranka, 1998; Wells, 2019). Thus, there is a potential for significant variability in survival rates, which in turn has strong implications for population growth (Biek et al., 2002; Vonesh and De la Cruz, 2002; Harper et al., 2008; Terrell et al., 2023). Both survival and activity periods of amphibians are impacted by climatic factors (e.g., Brooks et al., 2019; Cayuela et al., 2020; Messerman et al., 2020; Sanchez et al., 2020), and a positive relationship between body size and vulnerability to abiotic conditions has been shown for a variety of species (Spotila, 1972; Maiorana, 1976; Duellman and Trueb, 1994; Cabrera-Guzmán et al., 2013; Yagi and Green, 2017; Messerman et al., 2020). However, the fossorial nature of many amphibians makes it hard to disentangle environmentally driven variation in survival from the environmental correlates of aboveground activity and detection (Pollock, 1982; Petranka, 1998; O’Donnell and Semlitsch, 2015; Burrow et al., 2021).

Using ten years of mark–recapture data from Eglin Air Force Base on the Florida Panhandle, we investigated individual and temporal variability in survival rates of Reticulated Flatwoods Salamanders (Ambystoma bishopi), a species endemic to the Southeastern United States. Reticulated Flatwoods Salamanders breed in ephemeral wetlands, a strategy that exhibits sporadic recruitment (Palis et al., 2006; Taylor et al., 2006; Brooks et al., 2020). Reticulated Flatwoods Salamanders are a federally listed endangered species, but recovery of the species is hampered by a lack of basic natural history information, including accurate survival estimates (USFWS, 2009, 2020). We constructed a modified Cormack-Jolly-Seber model that included body size and year as covariates. Our objectives were to 1) provide the first estimates of survival for Reticulated Flatwoods Salamanders, 2) evaluate the relationship between body size and survival, 3) quantify the degree of variability in survival and detection across the study period, and 4) discern whether variability in survival or detection correlates with environmental conditions. We predicted relatively high survival estimates, a positive association between survival and body size, and variability in survival and detection probabilities corresponding to extremes of temperature and precipitation. Our findings can be used to evaluate the long-term viability of Reticulated Flatwoods Salamander populations and help to inform ongoing recovery efforts.

Study site.—

Data were collected from a ten-year mark–recapture study of Reticulated Flatwoods Salamander populations on Eglin Air Force Base, Florida. Eglin is a large military installation (188,459 ha) primarily consisting of actively managed Longleaf Pine (Pinus palustris) dominated sandhills (approximately 145,000 ha) interspersed with treeless open test ranges, pine plantations, and mesic flatwoods. The landscape is punctuated by ephemeral wetlands which fill with late fall or early winter rains and typically remain inundated throughout the spring (Chandler et al., 2016, 2017). Wetlands in this region are typically characterized by open overstories dominated by Longleaf Pine, Slash Pine (Pinus elliottii), and Pond Cypress (Taxodium ascendens), with abundant herbaceous groundcover (including species of Aristida, Dicanthelium, and Eriocaulon). Long-term average temperatures for the region are 28°C in summer and 16°C in winter. Average precipitation is 166 cm annually.

Two Reticulated Flatwoods Salamander breeding wetlands have been completely encircled with drift fences and monitored since 2010 (see Erwin et al., 2016 and Brooks et al., 2019 for details). The dates that drift fences were operational changed through time in response to weather conditions and staff availability, but we generally attempted to open fences in time to capture the first movement of individuals in the fall (October–November). We typically ran fences into the spring only when metamorphosis was likely (identified through larval dipnet surveys conducted every spring) due to suitable hydrologic conditions. Upon capture of an individual salamander, we recorded the date and time of capture, and uniquely marked each individual using passive integrated transponder (PIT) tags (Biomark MiniHPT8 FDX-B) or visual implant elastomer (VIE; Northwest Marine Technologies, Inc.). We measured snout–vent length (SVL), total length, and mass of all animals captured at drift fences. By sampling repeatedly across years, we were able to generate a unique capture history for each marked individual. All field work was approved by the Virginia Tech Institutional Animal Care and Use Committee.

Statistical analysis.—

We fit a hierarchical Cormack-Jolly-Seber (CJS) model (Cormack, 1964; Jolly, 1965; Seber, 1965) to estimate annual survival and detection probabilities. We chose this approach because the CJS formulation can easily be modified to include continuous covariates and random effects while accounting for imperfect detection. We adopted a two-stage approach that first involves imputing values for unobserved body sizes, followed by a partial likelihood approach to estimate parameters of interest (Tsiatis et al., 1995; Su and Wang, 2012; Rose et al., 2018). Our formulation consists of a model for the partially observed state of each individual (the “process model”) and an observation model that accounts for imperfect detection, conditional on true state. Individual states, zi,t, describe whether individual i is alive and available for capture at time t. An individual’s state zi,t is modeled as
formula
where ϕ represents survival probability and zi,t−1 is the state of individual i in the previous time step. We modeled survival as a linear function of body size at time of capture using a logit link function:
formula
formula
formula
formula
formula
formula
where β is the slope for size-specific survival, μt is the intercept at time t, and X is a matrix of body sizes for every individual at each sampling period. Size measurements were standardized by subtracting the mean size of all captured individuals and dividing by the standard deviation, resulting in a transformed covariate with mean zero. Size estimates for unobserved individuals were interpolated using parameters estimated from the von Bertalanffy growth equation (von Bertalanffy, 1938; Brooks et al., 2020). Error (ε) was assumed to be normally distributed with mean zero and standard deviation σ2.
For each sampling occasion, an individual is either seen or not seen. Before an individual has entered the population, or after an individual has died, detection probability is zero. We used a non-informative prior on detection probability and compared scenarios with constant detection and scenarios where detection varied across years. Observed states for each individual (yi,t) are linked to true states in the process model with a Bernoulli function:
formula
formula
formula
formula
formula
formula
where p is the probability of detection given an individual is available for capture and ϵt is the random effect of year on detection probability.

To assess the environmental basis of variation in survival and detection, we estimated the correlation between parameter estimates and temperature and precipitation data obtained from the PRISM Climate Group (Oregon State University, https://prism.oregonstate.edu). We downloaded monthly precipitation and temperature data from PRISM at the highest resolution (800 m) for our study area covering the years 2010 to 2020. We then calculated mean temperatures and total precipitation for June through August of each year to characterize the severity of summers across the study and calculated the mean temperature and total precipitation for November through February of each year to characterize the severity of winters. We then determined to what degree annual survival and detection estimates were correlated with mean summer temperature, total summer precipitation, mean winter temperature, and total winter precipitation using Kendall’s τ statistic. All analyses were performed in R using the package R2WinBUGS (Sturtz et al., 2005; R Core Team, 2022). Results reported are posterior means and 95% credible intervals unless otherwise stated.

Between fall 2010 and spring 2020, 953 adult salamanders at two breeding wetlands on Eglin Air Force Base were marked and released. Of the 953 animals marked, 688 marked individuals were recaptured on at least one subsequent occasion. The longest recorded time between two capture events was ten years. In addition, 704 metamorphs were captured emerging from wetlands but were excluded from subsequent analyses to avoid bias introduced by unequal emigration rates. Over the entire study duration, only 59 individuals tagged as metamorphs were ever recaptured. The average snout–vent length (SVL) of marked individuals was 54 mm (range = 32–76 mm; Fig. 1). The sex of 77% of individuals could be identified. Of the animals that could not be sexed, 24% were identified as yearlings (based on color pattern). Females on average were larger than males (t = 13.4, df = 247, P < 0.001) and individuals of unknown sex (t = 13.4, df = 320, P < 0.001), and the average size of males was larger than individuals of unknown sex (t = 4.1, df = 272, P < 0.001; Table 1, Fig. 2). Sex ratios approximated 1:1 at the start of the study but fluctuated across years. In 2014–2015, there were almost three males for every female, but in subsequent years the population was female biased (Table 1).

Fig. 1.

Body size distributions for Reticulated Flatwoods Salamanders by year. Sizes are snout–vent length (SVL) in millimeters. Points represent the raw data points; the center lines show mean, 75%, and 95% confidence intervals; and the shaded region is an approximate density.

Fig. 1.

Body size distributions for Reticulated Flatwoods Salamanders by year. Sizes are snout–vent length (SVL) in millimeters. Points represent the raw data points; the center lines show mean, 75%, and 95% confidence intervals; and the shaded region is an approximate density.

Close modal
Fig. 2.

Body size distributions for males (M), females (F), and individuals of unknown sex (U). Sizes are snout–vent length (SVL) in millimeters. Points represent the raw data points; the center lines show mean, 75%, and 95% confidence intervals; and the shaded region is an approximate density. The average size of females was larger than males (t = 13.4, df = 247, P < 0.001) and individuals of unknown sex (t = 13.4, df = 320, P < 0.001), and the average size of males was larger than individuals of unknown sex (t = 4.1, df = 272, P < 0.001).

Fig. 2.

Body size distributions for males (M), females (F), and individuals of unknown sex (U). Sizes are snout–vent length (SVL) in millimeters. Points represent the raw data points; the center lines show mean, 75%, and 95% confidence intervals; and the shaded region is an approximate density. The average size of females was larger than males (t = 13.4, df = 247, P < 0.001) and individuals of unknown sex (t = 13.4, df = 320, P < 0.001), and the average size of males was larger than individuals of unknown sex (t = 4.1, df = 272, P < 0.001).

Close modal
Table 1.

Summary of Reticulated Flatwoods Salamander encounters at drift fences each year. Numbers are the number of unique individuals captured. Numbers in parentheses are the number of recaptures, i.e., animals that had been marked in previous years. Reported sizes are mean snout–vent length (SVL) in millimeters with associated standard deviations.

Summary of Reticulated Flatwoods Salamander encounters at drift fences each year. Numbers are the number of unique individuals captured. Numbers in parentheses are the number of recaptures, i.e., animals that had been marked in previous years. Reported sizes are mean snout–vent length (SVL) in millimeters with associated standard deviations.
Summary of Reticulated Flatwoods Salamander encounters at drift fences each year. Numbers are the number of unique individuals captured. Numbers in parentheses are the number of recaptures, i.e., animals that had been marked in previous years. Reported sizes are mean snout–vent length (SVL) in millimeters with associated standard deviations.

All parameters of the Cormack-Jolly-Seber model adequately converged; all potential scale reduction factors (PSRF) for individual parameters were <1.1. The multivariate PSRF for the full model was 1.06. Posterior P-values for survival and detection probabilities all approximated 0.5, indicating a good model fit. Owing to the model formulation, the parameters for survival and detection probabilities in the final year of the study were unidentifiable, and thus not reported here, nor used to calculate averages across years.

Estimated annual detection probabilities were 0.75 (CI: 0.66–0.82; Supplemental Fig. 1; see Data Accessibility). Thus, three years of monitoring on average would be required to achieve >95% detection probability for a given individual. However, two individuals went ten years between successive captures. The probability of detection varied across years. Detection was lowest in 2019 (mean = 0.61, CI: 0.45–0.76) and highest in 2015 (mean = 0.91, CI: 0.83–0.96). Annual variation in detection probability was not correlated with maximum summer temperatures (Kendall’s τ = 0.36, P = 0.14), minimum winter temperatures (Kendall’s τ = –0.36, P = 0.14), or total winter precipitation (Kendall’s τ = –0.14, P = 0.72). However, annual variation in detection rates was correlated with total summer precipitation, whereby detection probabilities of adults in the breeding season were higher in years with low amounts of rainfall in the previous summer (Kendall’s τ = −0.57, P = 0.03; Fig. 3).

Fig. 3.

Detection probability within each breading season as it relates to rainfall in the previous summer. Kendall’s tau was used to determine the strength of the correlation between the variables (Kendall’s τ = −0.57, P = 0.03). No other correlations were found between environmental conditions and parameters of interest.

Fig. 3.

Detection probability within each breading season as it relates to rainfall in the previous summer. Kendall’s tau was used to determine the strength of the correlation between the variables (Kendall’s τ = −0.57, P = 0.03). No other correlations were found between environmental conditions and parameters of interest.

Close modal

Mean survival of adult salamanders was 0.78 (CI: 0.61–0.89; Supplemental Fig. 1; see Data Accessibility). However, survival rates varied considerably among individuals and across years (Figs. 4, 5). Survival rates were positively correlated to body size in all but two years (Fig. 5; Supplemental Fig. 2; see Data Accessibility). Survival for the smallest individuals in our study (30 mm) averaged 0.56 (CI: 0.36–0.75), whereas survival of the largest individuals (80 mm) averaged 0.87 (CI: 0.75–0.94). Survival rates were not correlated with body size in 2015 where survival was uniformly high across individuals and in 2017 where survival was uniformly low across individuals (Fig. 5; Supplemental Fig. 2; see Data Accessibility). Survival was predicted to be highest in 2018 (mean = 0.95, CI: 0.84–0.99) and lowest in 2017 (mean = 0.46, CI: 0.37–0.55). Annual variation in survival was not correlated with maximum summer temperatures (Kendall’s τ = 0.00, P = 0.55) or minimum winter temperatures (Kendall’s τ = –0.14, P = 0.73). In addition, annual variation in survival rates was not correlated with total summer precipitation (Kendall’s τ = –0.07, P = 0.64) or total winter precipitation (Kendall’s τ = –0.07, P = 0.64).

Fig. 4.

Size-dependent survival estimates for Reticulated Flatwoods Salamanders averaged across years. Body size reflects snout–vent length (SVL) in mm. The shaded region indicates the 95% credible interval.

Fig. 4.

Size-dependent survival estimates for Reticulated Flatwoods Salamanders averaged across years. Body size reflects snout–vent length (SVL) in mm. The shaded region indicates the 95% credible interval.

Close modal
Fig. 5.

Size-dependent survival estimates for Reticulated Flatwoods Salamanders by year. Body size reflects snout–vent length (SVL) in mm. The shaded regions indicate the 95% credible intervals.

Fig. 5.

Size-dependent survival estimates for Reticulated Flatwoods Salamanders by year. Body size reflects snout–vent length (SVL) in mm. The shaded regions indicate the 95% credible intervals.

Close modal

Here we find evidence for a positive relationship between body size and survival in Reticulated Flatwoods Salamanders and considerable annual variability in adult mortality. Inferring survival rates from incomplete data has been a primary goal of many ecological studies (Pollock et al., 1989; Colchero and Clark, 2012; Gilroy et al., 2012; Gilbert et al., 2014). Conservation practitioners require accurate estimates of survival to parameterize demographic models and quantify extinction risk. Our results provide some insight into the imperiled status of Reticulated Flatwoods Salamanders, carry implications for the long-term viability of populations, and highlight future research directions that will aid ongoing recovery efforts.

The average survival rates estimated for Reticulated Flatwoods Salamanders were similar to those reported for congeners (e.g., Husting, 1965; Trenham et al., 2000; Gamble et al., 2009; Messerman et al., 2020) and align with population trends at the study sites (Brooks et al., 2023). These estimates suggest a mean life expectancy of 3–5 years and a maximum lifespan of 15 years. In support of this finding, a small percentage of individuals marked (as adults) in the first year of the study were recaptured ten years later. Unfortunately, the true age of individuals in this study was not known so the overall demographic structure can only be indirectly inferred. Nevertheless, the apparent longevity of flatwoods salamanders indicates that the terrestrial breeding population acts as a reservoir that is periodically supplemented via sporadic recruitment events (Husting, 1965; Whitford and Vinegar, 1966; Warner and Chesson, 1985; Dodd, 1993; Semlitsch and Bodie, 2003; Harper et al., 2008). In such species, interannual variation in survival has the potential to preclude multiple breeding attempts in a lifetime and may ultimately undermine population viability (Trenham et al., 2000; Griffiths et al., 2010). Improved, non-fatal aging methods offer exciting future avenues for studies that seek to answer such questions in long-lived amphibians (Sinsch, 2015).

The positive correlation we found between body size and survival is unsurprising given the ubiquity of this relationship in nature (Roff, 1992; Cooch, 2002; Ebenman and Persson, 2012). In several amphibians, size at metamorphosis has been shown to have long-term effects on future survival and reproductive success (Semlitsch et al., 1988; De Block and Stoks, 2005; Earl and Whiteman, 2015; Yagi and Green, 2017, 2018). A promising avenue for Reticulated Flatwoods Salamander conservation efforts, therefore, may lie in ensuring high quality habitat conditions for larval growth and development, including fire-maintained herbaceous vegetation, litter sources that provision high quality prey items, and extended wetland hydroperiods (Wilbur and Collins, 1973; Semlitsch et al., 1988; Alvarez and Nicieza, 2002; Altwegg and Reyer, 2003; Richter-Boix et al., 2011; Chandler et al., 2017; Jones et al., 2018; Burrow and Maerz, 2021). In addition, the use of larval headstarting may aid population recovery, when tailored to produce large individuals that have a higher probability of surviving their first summer and returning to breed (Newman, 1998; Griffiths and Pavajeau, 2008; Middleton and Green, 2015). A priority for future research efforts would be to understand the factors that impact size at metamorphosis in Reticulated Flatwoods Salamanders and to what extent larval conditions carry over to impact the terrestrial life stage (Ficetola and Bernardi, 2006; Richter-Boix et al., 2006; Cabrera-Guzmán et al., 2013; Earl and Semlitsch, 2013; Earl and Whiteman, 2015; Yagi and Green, 2018).

Given the strong link between ectothermic life histories and environmental conditions (Laurie and Brown, 1990; Forsman, 1991; Sorci and Clobert, 1999; Kunz and Ekman, 2000), temporal variability in survival rates is considered likely. Several salamander species have been shown to experience a negative energy budget at higher temperatures, resulting in elevated mortality during the hottest summer months (Bobka et al., 1981; Rothermel and Semlitsch, 2006; Homyack et al., 2010, 2011; Rohr and Palmer, 2013). Alternatively, survival of amphibians may be indirectly impacted by temperature through its effect on water balance or prey availability (Spotila, 1972; Maiorana, 1976; Ash et al., 2003; Knapp et al., 2003; Rothermel and Semlitsch, 2006; Tilghman et al., 2012; Messerman et al., 2020). Regardless of the mechanism, there is much concern regarding the impact of climate change on amphibian populations (Means et al., 1996; Blaustein et al., 2001, 2010; Corn, 2005; Lawler et al., 2010; Shoo et al., 2011; Foden et al., 2013; Yiming et al., 2013). However, we found no evidence for coarse metrics of temperature or precipitation being the drivers of variation in survival. Instead we find that detection probabilities, and therefore presumably periods of aboveground activity, are more strongly correlated with environmental conditions. This indicates that despite animals attempting to buffer variation in survival through behavioral means (time spent on the surface), differences in survival rates across years are still pronounced. A key research priority, therefore, is to uncover the proximate factors driving annual variability in survival.

Understanding how survival probabilities change over the course of an individual’s life is crucial when scaling up to infer the dynamics of a population. Variability in vital rates can strongly influence a population’s vulnerability to local extirpation (Letcher and Horton, 2008; Van de Wolfshaar et al., 2008; Xu et al., 2010). Conservation of pond-breeding amphibians has often neglected the terrestrial phase of the life history (Semlitsch, 2003; Burrow et al., 2021), but there is a growing body of literature demonstrating the sensitivity of amphibian populations to changes in adult survival rates (Vonesh and De la Cruz, 2002; Harper et al., 2008; Kissel et al., 2020; Terrell et al., 2023). Studies like the one presented here will provide a key component to demographic models that can be used to quantify the threat of extinction in at-risk species. Once the impact of variable survival on the long-term viability of populations has been established, management actions to either dampen or combat that variability can be implemented.

All data and code used to perform the analysis are available at https://github.com/geobro1992/AMBBIS-SURV. Supplemental material is available at https://www.ichthyologyandherpetology.org/h2020131. Unless an alternative copyright or statement noting that a figure is reprinted from a previous source is noted in a figure caption, the published images and illustrations in this article are licensed by the American Society of Ichthyologists and Herpetologists for use if the use includes a citation to the original source (American Society of Ichthyologists and Herpetologists, the DOI of the Ichthyology & Herpetology article, and any individual image credits listed in the figure caption) in accordance with the Creative Commons Attribution CC BY License.

We would like to thank the team of people who have made this research possible. Special mention should be given to Kelly Jones, Brandon Rincon, Steve Goodman, Vivian Porter, and the myriad seasonal technicians involved in data collection. We thank Dylan Childs, Leanna House, Yan Jiao, and Eleni Matechou for their guidance in developing the statistical analyses. We thank the Natural Resources Branch of Eglin Air Force Base (Jackson Guard), the U.S. Fish and Wildlife Service, the Department of Defense Legacy Resource Management Program, the Florida Fish and Wildlife Conservation Commission, the Aquatic Habitat Restoration and Enhancement Program, and the Department of Fish and Wildlife Conservation at Virginia Tech for funding and logistical support on this project. This research was approved by the Virginia Tech Institutional Animal Care and Use Committee, protocol 19-113.

Altwegg,
R.,
and
Reyer
H. U.
2003
.
Patterns of natural selection on size at metamorphosis in water frogs
.
Evolution
57
:
872
882
.
Alvarez,
D.,
and
Nicieza
A. G.
2002
.
Effects of temperature and food quality on anuran larval growth and metamorphosis
.
Functional Ecology
16
:
640
648
.
Ash,
A. N.,
Bruce
R. C.,
Castanet
J.,
and
Francillon-Vieillot
H.
2003
.
Population parameters of Plethodon metcalfi on a 10-year-old clearcut and in nearby forest in the southern Blue Ridge Mountains
.
Journal of Herpetology
37
:
445
453
.
Bailey,
L. L.,
Kendall
W. L.,
Church
D. R.,
and
Wilbur
H. M.
2004
.
Estimating survival and breeding probability for pond-breeding amphibians: a modified robust design
.
Ecology
85
:
2456
2466
.
Barbour,
A. B.,
Ponciano
J. M.,
and
Lorenzen
K.
2013
.
Apparent survival estimation from continuous mark–recapture/resighting data
.
Methods in Ecology and Evolution
4
:
846
853
.
Biek,
R.,
Funk
W. C.,
Maxell
B. A.,
and
Mills
L. S.
2002
.
What is missing in amphibian decline research: insights from ecological sensitivity analysis
.
Conservation Biology
16
:
728
734
.
Blaustein,
A. R.,
Belden
L. K.,
Olson
D. H.,
Green
D. M.,
Root
T. L.,
and
Kiesecker
J. M.
2001
.
Amphibian breeding and climate change
.
Conservation Biology
15
:
1804
1809
.
Blaustein,
A. R.,
Walls
S. C.,
Bancroft
B. A.,
Lawler
J. J.,
Searle
C. L.,
and
Gervasi
S. S.
2010
.
Direct and indirect effects of climate change on amphibian populations
.
Diversity
2
:
281
313
.
Bobka,
M. S.,
Jaeger
R. G.,
and
McNaught
D. C.
1981
.
Temperature dependent assimilation efficiencies of two species of terrestrial salamanders
.
Copeia
1981
:
417
421
.
Brooks,
G. C.,
Gorman
T. A.,
Jiao
Y.,
and
Haas
C. A.
2020
.
Reconciling larval and adult sampling methods to model growth across life-stages
.
PLoS ONE
15
:
e0237737
.
Brooks,
G. C.,
Smith
J. A.,
Gorman
T. A.,
and
Haas
C. A.
2019
.
Discerning the environmental drivers of annual migrations in an endangered amphibian
.
Copeia
107
:
270
276
.
Brooks,
G. C.,
Wendt
A.,
Haas
C. A.,
and
Roberts
J. H.
2023
.
Comparing estimates of census and effective population size in an endangered amphibian
.
Animal Conservation
26
:
839
850
.
Brooks,
S. P.,
Catchpole
E. A.,
and
Morgan
B. J.
2000
.
Bayesian animal survival estimation
.
Statistical Science
15
:
357
376
.
Burrow,
A. K.,
Crawford
B. A.,
and
Maerz
J. C.
2021
.
Ground cover and native ant predation influence survival of metamorphic amphibians in a Southeastern pine savanna undergoing restoration
.
Restoration Ecology
29
:
e13410
.
Burrow,
A. K.,
and
Maerz
J. C.
2021
.
Experimental confirmation of effects of leaf litter type and light on tadpole performance for two priority amphibians
.
Ecosphere
12
:
e03729
.
Cabrera-Guzmán,
E.,
Crossland
M. R.,
Brown
G. P.,
and
Shine
R.
2013
.
Larger body size at metamorphosis enhances survival, growth and performance of young Cane Toads (Rhinella marina)
.
PLoS ONE
8
:
e70121
.
Cayuela,
H.,
Griffiths
R. A.,
Zakaria
N.,
Arntzen
J. W.,
Priol
P.,
Léna
J. P.,
Besnard
A.,
and
Joly
P.
2020
.
Drivers of amphibian population dynamics and asynchrony at local and regional scales
.
Journal of Animal Ecology
89
:
1350
1364
.
Chandler,
H. C.,
McLaughlin
D. L.,
Gorman
T. A.,
McGuire
K. J.,
Feaga
J. B.,
and
Haas
C. A.
2017
.
Drying rates of ephemeral wetlands: implications for breeding amphibians
.
Wetlands
37
:
545
557
.
Chandler,
H. C.,
Rypel
A. L.,
Jiao
Y.,
Haas
C. A.,
and
Gorman
T. A.
2016
.
Hindcasting historical breeding conditions for an endangered salamander in ephemeral wetlands of the southeastern USA: implications of climate change
.
PLoS ONE
11
:
e0150169
.
Church,
D. R.,
Bailey
L. L.,
Wilbur
H. M.,
Green
J. H.,
and
Hiby
L.
2022
.
Salamander demography at isolated wetlands within mature and regenerating forests
.
Diversity
14
:
309
.
Colchero,
F.,
and
Clark
J. S.
2012
.
Bayesian inference on age‐specific survival for censored and truncated data
.
Journal of Animal Ecology
81
:
139
149
.
Cooch,
E. G.
2002
.
Fledging size and survival in snow geese: timing is everything (or is it?)
.
Journal of Applied Statistics
29
:
143
162
.
Cormack,
R. M.
1964
.
Estimates of survival from the sighting of marked animals
.
Biometrika
51
:
429
438
.
Corn,
P. S.
2005
.
Climate change and amphibians
.
Animal Biodiversity and Conservation
28
:
59
67
.
De Block,
M.,
and
Stoks
R.
2005
.
Fitness effects from egg to reproduction: bridging the life history transition
.
Ecology
86
:
185
197
.
Dodd,
C. K.,
Jr
.
1993
.
Cost of living in an unpredictable environment: the ecology of Striped Newts Notophthalmus perstriatus during a prolonged drought
.
Copeia
1993
:
605
614
.
Duellman,
W. E.,
and
Trueb
L.
1994
.
Biology of Amphibians
.
Johns Hopkins University Press
,
Baltimore, Maryland
.
Earl,
J. E.,
and
Semlitsch
R. D.
2013
.
Carry-over effects in amphibians: Are characteristics of the larval habitat needed to predict juvenile survival
?
Ecological Applications
23
:
1429
1442
.
Earl,
J. E.,
and
Whiteman
H. H.
2015
.
Are commonly used fitness predictors accurate? A meta-analysis of amphibian size and age at metamorphosis
.
Copeia
103
:
297
309
.
Ebenman,
B.,
and
Persson
L.
2012
.
Size-Structured Populations: Ecology and Evolution
.
Springer-Verlag
,
Berlin, Heidelberg
.
Ergon,
T.,
and
Gardner
B.
2014
.
Separating mortality and emigration: modelling space use, dispersal and survival with robust‐design spatial capture–recapture data
.
Methods in Ecology and Evolution
5
:
1327
1336
.
Erwin,
K. J.,
Chandler
H. C.,
Palis
J. G.,
Gorman
T. A.,
and
Haas
C. A.
2016
.
Herpetofaunal communities in ephemeral wetlands embedded within longleaf pine flatwoods of the Gulf Coast plain
.
Southeastern Naturalist
15
:
431
447
.
Ficetola,
G. F.,
and
De Bernardi
F.
2006
.
Trade-off between larval development rate and post-metamorphic traits in the frog Rana latastei
.
Evolutionary Ecology
20
:
143
158
.
Foden,
W. B.,
Butchart
S. H.,
Stuart
S. N.,
Vié
J. C.,
Akçakaya
H. R.,
Angulo
A.,
DeVantier
L. M.,
Gutsche
A.,
Turak
E.,
Cao
L.,
and
Donner
S. D.
2013
.
Identifying the world’s most climate change vulnerable species: a systematic trait-based assessment of all birds, amphibians and corals
.
PLoS ONE
8
:
e65427
.
Forsman,
A.
1991
.
Variation in sexual size dimorphism and maximum body size among adder populations: effects of prey size
.
Journal of Animal Ecology
60
:
253
267
.
Forsman,
A.
1996
.
Body size and net energy gain in gape-limited predators: a model
.
Journal of Herpetology
30
:
307
319
.
Gamble,
L. R.,
McGarigal
K.,
Sigourney
D. B.,
and
Timm
B. C.
2009
.
Survival and breeding frequency in Marbled Salamanders (Ambystoma opacum): implications for spatio-temporal population dynamics
.
Copeia
2009
:
394
407
.
Gilbert,
S. L.,
Lindberg
M. S.,
Hundertmark
K. J.,
and
Person
D. K.
2014
.
Dead before detection: addressing the effects of left truncation on survival estimation and ecological inference for neonates
.
Methods in Ecology and Evolution
5
:
992
1001
.
Gilroy,
J. J.,
Virzi
T.,
Boulton
R. L.,
and
Lockwood
J. L.
2012
.
A new approach to the “apparent survival” problem: estimating true survival rates from mark–recapture studies
.
Ecology
93
:
1509
1516
.
Griffiths,
R. A.,
and
Pavajeau
L.
2008
.
Captive breeding, reintroduction, and the conservation of amphibians
.
Conservation Biology
22
:
852
861
.
Griffiths,
R. A.,
Sewell
D.,
and
McCrea
R. S.
2010
.
Dynamics of a declining amphibian metapopulation: survival, dispersal and the impact of climate
.
Biological Conservation
143
:
485
491
.
Harper,
E. B.,
Rittenhouse
T. A.,
and
Semlitsch
R. D.
2008
.
Demographic consequences of terrestrial habitat loss for pool‐breeding amphibians: predicting extinction risks associated with inadequate size of buffer zones
.
Conservation Biology
22
:
1205
1215
.
Hegg,
D.,
MacKenzie
D. I.,
and
Jamieson
I. G.
2013
.
Use of Bayesian population viability analysis to assess multiple management decisions in the recovery programme for the endangered takahe Porphyrio hochstetteri
.
Oryx
47
:
144
.
Homyack,
J. A.,
Haas
C. A.,
and
Hopkins
W. A.
2010
.
Influence of temperature and body mass on standard metabolic rate of eastern red-backed salamanders (Plethodon cinereus)
.
Journal of Thermal Biology
35
:
143
146
.
Homyack,
J. A.,
Haas
C. A.,
and
Hopkins
W. A.
2011
.
Energetics of surface-active terrestrial salamanders in experimentally harvested forest
.
Journal of Wildlife Management
75
:
1267
1278
.
Husting,
E. L.
1965
.
Survival and breeding structure in a population of Ambystoma maculatum
.
Copeia
1965
:
352
362
.
Janzen,
F. J.
1993
.
An experimental analysis of natural selection on body size of hatchling turtles
.
Ecology
74
:
332
341
.
Jolly,
G. M.
1965
.
Explicit estimates from capture–recapture data with both death and immigration-stochastic model
.
Biometrika
52
:
225
247
.
Jones,
C. N.,
McLaughlin
D. L.,
Henson
K.,
Haas
C. A.,
and
Kaplan
D. A.
2018
.
From salamanders to greenhouse gasses: Does upland management affect wetland function
?
Frontiers in Ecology and the Environment
16
:
14
19
.
Kellner,
K. F.,
and
Swihart
R. K
.
2014
.
Accounting for imperfect detection in ecology: a quantitative review
.
PLoS ONE
9
:
e111436
.
Kishida,
O.,
Trussell
G. C.,
Nishimura
K.,
and
Ohgushi
T.
2009
.
Inducible defenses in prey intensify predator cannibalism
.
Ecology
90
:
3150
3158
.
Kissel,
A. M.,
Tenan
S.,
and
Muths
E.
2020
.
Density dependence and adult survival drive dynamics in two high elevation amphibian populations
.
Diversity
12
:
478
.
Knapp,
S. M.,
Haas
C. A.,
Harpole
D. N.,
and
Kirkpatrick
R. L.
2003
.
Initial effects of clearcutting and alternative silvicultural practices on terrestrial salamander abundance
.
Conservation Biology
17
:
752
762
.
Kunz,
C.,
and
Ekman
J.
2000
.
Genetic and environmental components of growth in nestling blue tits (Parus caeruleus)
.
Journal of Evolutionary Biology
13
:
199
212
.
Lande,
R.
1993
.
Risks of population extinction from demographic and environmental stochasticity and random catastrophes
.
The American Naturalist
142
:
911
927
.
Langrock,
R.,
and
King
R.
2013
.
Maximum likelihood estimation of mark–recapture–recovery models in the presence of continuous covariates
.
The Annals of Applied Statistics
7
:
1709
1732
.
Laurie,
W. A.,
and
Brown
D.
1990
.
Population biology of marine iguanas (Amblyrhynchus cristatus). II. Changes in annual survival rates and the effects of size, sex, age and fecundity in a population crash
.
Journal of Animal Ecology
59
:
529
544
.
Lawler,
J. J.,
Shafer
S. L.,
Bancroft
B. A.,
and
Blaustein
A. R.
2010
.
Projected climate impacts for the amphibians of the Western Hemisphere
.
Conservation Biology
24
:
38
50
.
Lebreton,
J.-D.,
Burnham
K. P.,
Clobert
J.,
and
Anderson
D. R.
1992
.
Modeling survival and testing biological hypotheses using marked animals: a unified approach with case studies
.
Ecological Monographs
62
:
67
118
.
Letcher,
B. H.,
and
Horton
G. E.
2008
.
Seasonal variation in size‐dependent survival of juvenile Atlantic salmon: performance of multistate capture–mark–recapture models
.
Canadian Journal of Fisheries and Aquatic Sciences
65
:
1649
1666
.
Lind,
M. I.,
Persbo
F.,
and
Johansson
F.
2008
.
Pool desiccation and developmental thresholds in the common frog, Rana temporaria
.
Proceedings of the Royal Society B: Biological Science
275
:
1073
1080
.
Maiorana,
V. C.
1976
.
Size and environmental predictability for salamanders
.
Evolution
30
:
599
613
.
Matechou,
E.,
Pledger
S.,
Efford
M.,
Morgan
B. J. T.,
Thomson
D. L.,
and
Gimenez
O.
2013
.
Estimating age-specific survival when age is unknown: open population capture–recapture models with age structure and heterogeneity
.
Methods in Ecology and Evolution
4
:
654
664
.
Means,
D. B.,
Palis
J. G.,
and
Baggett
M.
1996
.
Effects of slash pine silviculture on a Florida population of flatwoods salamander
.
Conservation Biology
10
:
426
437
.
Messerman,
A. F.,
Semlitsch
R. D.,
and
Leal
M.
2020
.
Estimating survival for elusive juvenile pond‐breeding salamanders
.
The Journal of Wildlife Management
84
:
562
575
.
Middleton,
J.,
and
Green
D. M.
2015
.
Adult age-structure variability in an amphibian in relation to population decline
.
Herpetologica
71
:
190
195
.
Newman,
R. A.
1998
.
Ecological constraints on amphibian metamorphosis: interactions of temperature and larval density with responses to changing food level
.
Oecologia
115
:
9
16
.
O’Donnell,
K. M.,
and
Semlitsch
R. D.
2015
.
Advancing terrestrial salamander population ecology: the central role of imperfect detection
.
Journal of Herpetology
49
:
533
540
.
Palis,
J. G.,
Aresco
M. J.,
and
Kilpatrick
S.
2006
.
Breeding biology of a Florida population of Ambystoma cingulatum (Flatwoods Salamander) during a drought
.
Southeastern Naturalist
5
:
1
8
.
Papadatou,
E.,
Pradel
R.,
Schaub
M.,
Dolch
D.,
Geiger
H.,
Ibañez
C.,
Kerth
G.,
Popa-Lisseanu
A.,
Schorcht
W.,
Teubner
J.,
and
Gimenez
O.
2012
.
Comparing survival among species with imperfect detection using multilevel analysis of mark–recapture data: a case study on bats
.
Ecography
35
:
153
161
.
Petranka,
J. W.
1998
.
Salamanders of the United States and Canada
.
Smithsonian Institution Press
,
Washington and London
.
Pike,
D. A.,
Pizzatto
L.,
Pike
B. A.,
and
Shine
R.
2008
.
Estimating survival rates of uncatchable animals: the myth of high juvenile mortality in reptiles
.
Ecology
89
:
607
611
.
Pledger,
S.,
Pollock
K. H.,
and
Norris
J. L.
2003
.
Open capture–recapture models with heterogeneity: I. Cormack-Jolly-Seber model
.
Biometrics
59
:
786
794
.
Pledger,
S.,
Pollock
K. H.,
and
Norris
J. L.
2010
.
Open capture–recapture models with heterogeneity: II. Jolly-Seber model
.
Biometrics
66
:
883
890
.
Pollock,
K. H.
1982
.
A capture–recapture design robust to unequal probability of capture
.
Journal of Wildlife Management
46
:
752
757
.
Pollock,
K. H.,
Nichols
J. D.,
Brownie
C.,
and
Hines
J. E.
1990
.
Statistical inference for capture–recapture experiments
.
Wildlife Monographs
107
:
3
97
.
Pollock,
K. H.,
Winterstein
S. R.,
Bunck
C. M.,
and
Curtis
P. D.
1989
.
Survival analysis in telemetry studies: the staggered entry design
.
The Journal of Wildlife Management
53
:
7
15
.
R Core Team
.
2022
.
R: a language and environment for statistical computing
.
R Foundation for Statistical Computing
,
Vienna, Austria
. https://www.R-project.org/
Ramula,
S.,
Rees
M.,
and
Buckley
Y. M.
2009
.
Integral projection models perform better for small demographic data sets than matrix population models: a case study of two perennial herbs
.
Journal of Applied Ecology
46
:
1048
1053
.
Rees,
M.,
and
Ellner
S. P.
2009
.
Integral projection models for populations in temporally varying environments
.
Ecological Monographs
79
:
575
594
.
Richter-Boix,
A.,
Llorente
G. A.,
and
Montori
A.
2006
.
Effects of phenotypic plasticity on post-metamorphic traits during pre-metamorphic stages in the anuran Pelodytes punctatus
.
Evolutionary Ecology Research
8
:
309
320
.
Richter-Boix,
A.,
Tejedo
M.,
and
Rezende
E. L.
2011
.
Evolution and plasticity of anuran larval development in response to desiccation. A comparative analysis
.
Ecology and Evolution
1
:
15
25
.
Roff,
D. A.
1992
.
The Evolution of Life Histories
.
Chapman and Hall
,
New York
.
Rohr,
J. R.,
and
Palmer
B. D.
2013
.
Climate change, multiple stressors, and the decline of ectotherms
.
Conservation Biology
27
:
741
751
.
Rose,
J. P.,
Wylie
G. D.,
Casazza
M. L.,
and
Halstead
B. J.
2018
.
Integrating growth and capture–mark–recapture models reveals size‐dependent survival in an elusive species
.
Ecosphere
9
:
e02384
.
Rothermel,
B. B.,
and
Semlitsch
R. D.
2006
.
Consequences of forest fragmentation for juvenile survival in spotted (Ambystoma maculatum) and marbled (Ambystoma opacum) salamanders
.
Canadian Journal of Zoology
84
:
797
807
.
Royle,
J. A.
2008
.
Modeling individual effects in the Cormack-Jolly-Seber model: a state–space formulation
.
Biometrics
64
:
364
370
.
Sanchez,
K.,
Grayson
K. L.,
Sutherland
C.,
Thompson
L. M.,
and
Hernandez-Pacheco
R.
2020
.
Environmental drivers of surface activity in a population of the eastern red-backed salamander (Plethodon cinereus)
.
Herpetological Conservation and Biology
15
:
642
651
.
Seber,
G. A. F.
1965
.
A note on the multiple-recapture census
.
Biometrika
52
:
249
259
.
Semlitsch,
R. D.
2003
.
Amphibian Conservation
.
Smithsonian Institution Press
,
Washington, D.C
.
Semlitsch,
R. D.,
and
Bodie
J. R.
2003
.
Biological criteria for buffer zones around wetlands and riparian habitats for amphibians and reptiles
.
Conservation Biology
17
:
1219
1228
.
Semlitsch,
R. D.,
Scott
D. E.,
and
Pechmann
J. H.
1988
.
Time and size at metamorphosis related to adult fitness in Ambystoma talpoideum
.
Ecology
69
:
184
192
.
Shine,
R.
1991
.
Why do larger snakes eat larger prey items
?
Functional Ecology
5
:
493
502
.
Shoo,
L. P.,
Olson
D. H.,
McMenamin
S. K.,
Murray
K. A.,
Van Sluys
M.,
Donnelly
M. A.,
Stratford
D.,
Terhivuo
J.,
Merino‐Viteri
A.,
Herbert
S. M.,
and
Bishop
P. J.
2011
.
Engineering a future for amphibians under climate change
.
Journal of Applied Ecology
48
:
487
492
.
Sinsch,
U.
2015
.
Skeletochronological assessment of demographic life-history traits in amphibians
.
The Herpetological Journal
25
:
5
13
.
Sorci,
G.,
and
Clobert
J.
1999
.
Natural selection on hatchling body size and mass in two environments in the common lizard (Lacerta vivipara)
.
Evolutionary Ecology Research
1
:
303
316
.
Spotila,
J. R.
1972
.
Role of temperature and water in the ecology of lungless salamanders
.
Ecological Monographs
42
:
95
124
.
Sturtz,
S.,
Ligges
U.,
and
Gelman
A.
2005
.
R2WinBUGS: a package for running WinBUGS from R
.
Journal of Statistical Software
12
:
1
16
.
Su,
Y.-R.,
and
Wang
J.-L.
2012
.
Modeling left-truncated and right-censored survival data with longitudinal covariates
.
The Annals of Statistics
40
:
1465
1488
.
Taylor,
B. E.,
Scott
D. E.,
and
Gibbons
J. W.
2006
.
Catastrophic reproductive failure, terrestrial survival, and persistence of the marbled salamander
.
Conservation Biology
20
:
792
801
.
Terrell,
V. C.,
Maerz
J. C.,
Engbrecht
N. J.,
Stiles
R. M.,
Crawford
B. A.,
and
Lannoo
M. J.
2023
.
Breeding population dynamics of threatened crawfish frogs inform targets for habitat management
.
Ichthyology & Herpetology
111
:
72
86
.
Tilghman,
J. M.,
Ramee
S. W.,
and
Marsh
D. M.
2012
.
Meta-analysis of the effects of canopy removal on terrestrial salamander populations in North America
.
Biological Conservation
152
:
1
9
.
Trenham,
P. C.,
Shaffer
H. B.,
Koenig
W. D.,
and
Stromberg
M. R.
2000
.
Life history and demographic variation in the California tiger salamander (Ambystoma californiense)
.
Copeia
2000
:
365
377
.
Tsiatis,
A. A.,
DeGruttola
V.,
and
Wulfsohn
M.
1995
.
Modeling the relationship of survival to longitudinal data measured with error: applications to survival and CD4 counts in patients with AIDS
.
Journal of the American Statistical Association
90
:
23
37
.
USFWS (United States Department of the Interior, Fish and Wildlife Service)
.
2009
.
Endangered and threatened wildlife and plants; Determination of endangered status for Reticulated Flatwoods Salamander; Designation of critical habitat for Frosted Flatwoods Salamander and Reticulated Flatwoods Salamander
.
Federal Register
74
:
6700
6774
.
USFWS (United States Department of the Interior, Fish and Wildlife Service).
2020
.
Species status assessment for the Reticulated Flatwoods Salamander (Ambystoma bishopi)
.
USFWS
,
Panama City, Florida
.
Van de Wolfshaar,
K. E.,
De Roos
A. M.,
and
Persson
L.
2008
.
Population feedback after successful invasion leads to ecological suicide in seasonal environments
.
Ecology
89
:
259
268
.
Von Bertalanffy,
L.
1938
.
A quantitative theory of organic growth (inquiries on growth laws. II)
.
Human Biology
10
:
181
213
.
Vonesh,
J. R.,
and
De la Cruz
O.
2002
.
Complex life cycles and density dependence: assessing the contribution of egg mortality to amphibian declines
.
Oecologia
133
:
325
333
.
Warner,
R. R.,
and
Chesson
P. L.
1985
.
Coexistence mediated by recruitment fluctuations: a field guide to the storage effect
.
The American Naturalist
125
:
769
787
.
Wells,
K. D.
2019
.
The Ecology and Behavior of Amphibians
.
University of Chicago Press
,
Chicago
.
Whitford,
W. G.,
and
Vinegar
A.
1966
.
Homing, survivorship, and overwintering of larvae in spotted salamanders, Ambystoma maculatum
.
Copeia
1966
:
517
519
.
Wilbur,
H. M.,
and
Collins
J. P.
1973
.
Ecological aspects of amphibian metamorphosis
.
Science
182
:
1305
1314
.
Wulfsohn,
M. S.,
and
Tsiatis
A. A.
1997
.
A joint model for survival and longitudinal data measured with error
.
Biometrics
53
:
330
339
.
Xu,
C. L.,
Letcher
B. H.,
and
Nislow
K. H.
2010
.
Size‐dependent survival of brook trout Salvelinus fontinalis in summer: effects of water temperature and stream flow
.
Journal of Fish Biology
76
:
2342
2369
.
Yagi,
K. T.,
and
Green
D. M.
2017
.
Performance and movement in relation to postmetamorphic body size in a pond-breeding amphibian
.
Journal of Herpetology
51
:
482
489
.
Yagi,
K. T.,
and
Green
D. M.
2018
.
Post-metamorphic carry-over effects in a complex life history: behavior and growth at two life stages in an amphibian, Anaxyrus fowleri
.
Copeia
106
:
77
85
.
Yiming,
L. I.,
Cohen
J. M.,
and
Rohr
J. R.
2013
.
Review and synthesis of the effects of climate change on amphibians
.
Integrative Zoology
8
:
145
161
.

Author notes

1

Virginia Tech, Department of Fish and Wildlife Conservation, 310 West Campus Drive, Blacksburg, Virginia 24060; Email: (GCB) [email protected]; and (CAH) [email protected]. Send correspondence to GCB.

2

Washington State Department of Natural Resources, Aquatic Resources Division, Olympia, Washington 98504; Email: [email protected].

Associate Editor: J. Kerby