Survival and population growth of a long‐lived threatened snake species,Drymarchon couperi(Eastern Indigo Snake)

Abstract

Demographic data provide a basis for understanding the life history and ecology of species, factors which are vital for informing conservation efforts; however, little is known regarding the population ecology of most snake species, including the threatened Eastern Indigo Snake (Drymarchon couperi). We used 11 years (1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)) of capture-mark-recapture (CMR) and 2.5 years (2003)(2004)(2005) of radiotelemetry data from southeastern Georgia, USA, in a CMR modeling framework to estimate apparent survival, capture and transition probabilities, and evaluate factors influencing these parameters. The model-averaged estimate of overall apparent annual survival probability was 0.700 (±0.030 SE) and is comparable to that obtained from known fate analysis (radiotelemetry) at the same site. Body size positively influenced survival, regardless of sex. Capture probability differed seasonally by sex, suggesting lower capture probability for females in fall and males in winter. There was no evidence for effect of precipitation or site-specific differences in survival. Model averaged estimate of annual adult survival estimated using multistate CMR models was 0.738 ± 0.030 and 0.515 ± 0.189 for subadults. We estimated population growth rate (k) and elasticity (proportional sensitivity) of k to vital rates using a stage-structured matrix population model. Population growth rate ranged from 0.96 to 1.03 depending on the value of the probability of transitioning from subadult to adult stage. The k was proportionally most sensitive to changes in adult survival rate, followed by subadult survival. Our results suggest that protecting adult snakes and their habitats would result in the highest likelihood of long-term population stability and growth.

Integrating growth and capture–mark–recapture models reveals size‐dependent survival in an elusive species

“…One solution to obtain survival estimates when capture probabilities are low is to assume constant survival rates (Pollock et al 1990). Obtaining precise yearly or population-specific survival estimates is even more challenging for elusive species, because increasing the number of parameters to be estimated from sparse data leads to greater uncertainty for each parameter (Pollock et al 1990); this can inhibit researchers' ability to estimate annual variation in survival (Hyslop et al 2012). Obtaining precise yearly or population-specific survival estimates is even more challenging for elusive species, because increasing the number of parameters to be estimated from sparse data leads to greater uncertainty for each parameter (Pollock et al 1990); this can inhibit researchers' ability to estimate annual variation in survival (Hyslop et al 2012).…”

“…Survival often varies over time and among populations, however (Brown and Weatherhead 1999, Gaillard and Yoccoz 2003, Miller et al 2011, and it is important to quantify this variation to understand natural population dynamics (Rees and Ellner 2009). Obtaining precise yearly or population-specific survival estimates is even more challenging for elusive species, because increasing the number of parameters to be estimated from sparse data leads to greater uncertainty for each parameter (Pollock et al 1990); this can inhibit researchers' ability to estimate annual variation in survival (Hyslop et al 2012).…”

Variation in vital‐rate sensitivity between populations of Texas horned lizards

“…Although the inclusion of 0 in hatchling survival distributions depressed the effects of all other parameters, a hatchling survival rate of 0 or a uniform distribution of rates among years are plausible assumptions. Highly variable survival rates of hatchlings have been documented in lizards (Heulin et al 1997;Tinkle et al 1993;Zuniga-Vega et al 2007) and other reptiles (Hyslop et al 2012;Perez-Heydrich et al 2012). For example, hatchling survival of Scleroporus graciosus can vary annually from 0.12 to 0.59 (Tinkle et al 1993).…”

Long‐term population dynamics reveal that survival and recruitment of tropical boobies improve after a hurricane

“…These vital rates often covary and make different contributions to λ in such a way that a change of the same magnitude in survival or reproduction may have different implications for population viability Doak 2004, Tuljapurkar et al 2009). For instance, in a variety of long-lived iteroparous species with delayed maturity, including numerous reptiles, birds, and mammals, fluctuations in adult survival probabilities have a greater relative influence on λ than shifts in juvenile survival or reproduction (Heppell 1998, Heppell et al 2000, Saether and Bakke 2000, Hyslop et al 2012).…”