The energetic and survival costs of growth in free-ranging chipmunks

The growth/survival trade-off is a fundamental aspect of life-history evolution that is often explained by the direct energetic requirement for growth that cannot be allocated into maintenance. However, there is currently no empirical consensus on whether fast-growing individuals have higher resting metabolic rates at thermoneutrality (RMRt) than slow growers. Moreover, the link between growth rate and daily energy expenditure (DEE) has never been tested in a wild endotherm. We assessed the energetic and survival costs of growth in juvenile eastern chipmunks (Tamias striatus) during a year of low food abundance by quantifying post-emergent growth rate (n = 88), RMRt (n = 66), DEE (n = 20), and overwinter survival. Both RMRt and DEE were significantly and positively related to growth rate. The effect size was stronger for DEE than RMRt, suggesting that the energy cost of growth in wild animals is more likely to be related to the maintenance of a higher foraging rate (included in DEE) than to tissue accretion (included in RMRt). Fast growers were significantly less likely to survive the following winter compared to slow growers. Juveniles with high or low RMRt were less likely to survive winter than juveniles with intermediate RMRt. In contrast, DEE was unrelated to survival. In addition, botfly parasitism simultaneously decreased growth rate and survival, suggesting that the energetic budget of juveniles was restricted by the simultaneous costs of growth and parasitism. Although the biology of the species (seed-storing hibernator) and the context of our study (constraining environmental conditions) were ideally combined to reveal a direct relationship between current use of energy and future availability, it remains unclear whether the energetic cost of growth was directly responsible for reduced survival.

Survival misperception, time inconsistency, and implications for life-cycle saving and welfare

Some empirical studies firmly reveal that people tend to form overly pessimistic survival expectations for relatively less distant ages and overly optimistic survival expectations for relatively more distant ages. We incorporate this observation into a life-cycle continuous time overlapping-generations model of consumption/saving with a general form for a subjective survival function. Resulting time-inconsistent optimal control problem has been analytically solved. At the micro level, time inconsistency leads to higher consumption at young and old ages, but this alone fails to improve lifetime well-being since micro-level decisions made with a lack of information about true mortality are suboptimal. In general equilibrium, however, such time inconsistent behavior with survival misperception is conducive to aggregate capital accumulation and greater equilibrium bequest income. The latter effects can produce substantial welfare gains. We also note that empirically observed old age optimistic bias is an important phenomenon, as it helps to avoid unrealistic very old-age debt accumulation within a life-cycle model. In addition, if for a given level of optimistic bias we increase early-life pessimism, this would result in slower capital accumulation, lower bequest income, and thus be detrimental to welfare. Since recent literature reports that young-age survival pessimism has grown over time, it raises some concerns.

Death or survival from invasive pneumococcal disease in Scotland: associations with serogroups and multilocus sequence types

We describe associations between death from invasive pneumococcal disease (IPD) and particular serogroups and sequence types (STs) determined by multilocus sequence typing (MLST) using data from Scotland. All IPD episodes where blood or cerebrospinal fluid (CSF) culture isolates were referred to the Scottish Haemophilus, Legionella, Meningococcal and Pneumococcal Reference Laboratory (SHLMPRL) from January 1992 to February 2007 were matched to death certification records by the General Register Office for Scotland. This represented 5959 patients. The median number of IPD cases in Scotland each year was 292. Deaths, from any cause, within 30 days of pneumococcal culture from blood or CSF were considered to have IPD as a contributing factor. Eight hundred and thirty-three patients died within 30 days of culture of Streptococcus pneumoniae from blood or CSF [13.95 %; 95 % confidence interval (13.10, 14.80)]. The highest death rates were in patients over the age of 75. Serotyping data exist for all years but MLST data were only available from 2001 onward. The risk ratio of dying from infection due to particular serogroups or STs compared to dying from IPD due to all other serogroups or STs was calculated. Fisher’s exact test with Bonferroni adjustment for multiple testing was used. Age adjustment was accomplished using the Cochran–Mantel–Haenszel test and 95 % confidence intervals were reported. Serogroups 3, 11 and 16 have increased probability of causing fatal IPD in Scotland while serogroup 1 IPD has a reduced probability of causing death. None of the 20 most common STs were significantly associated with death within 30 days of pneumococcal culture, after age adjustment. We conclude that there is a stronger association between a fatal outcome and pneumococcal capsular serogroup than there is between a fatal outcome and ST.

Climate change, multiple paternity and offspring survival in lizards

Recent work suggests that rising spring temperatures over recent decades have eliminated many lizard populations, and threaten many more worldwide. However, because ambient temperatures constrain activity times in ectotherms, warming conditions (as expected under global climate change scenarios) can increase the duration of seasonal opportunities for courtship and mating. Thus, in species where polyandry results in enhanced offspring viability, a warming climate may not necessarily impair long-term survival. Our nine-year study of a sand lizard (Lacerta agilis) population near the northern range limit in Sweden revealed consistently higher incidence of multiple paternity of clutches in warmer years, and higher viability of offspring from multiply-sired clutches (presumably reflecting the advantages of more intense sperm competition). Any trend to warmer spring temperatures likely will benefit offspring viability in this system, by increasing a female's opportunities to mate with additional males.

Survival analysis of time-to-event data in respiratory health research studies

This article provides a review of techniques for the analysis of survival data arising from respiratory health studies. Popular techniques such as the Kaplan–Meier survival plot and the Cox proportional hazards model are presented and illustrated using data from a lung cancer study. Advanced issues are also discussed, including parametric proportional hazards models, accelerated failure time models, time-varying explanatory variables, simultaneous analysis of multiple types of outcome events and the restricted mean survival time, a novel measure of the effect of treatment.

Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry

Using the prediction of cancer outcome as a model, we have tested the hypothesis that through analysing routinely collected digital data contained in an electronic administrative record (EAR), using machine-learning techniques, we could enhance conventional methods in predicting clinical outcomes.

Modelling grouped survival times in toxicological studies using generalized additive models

A method for combining a proportional-hazards survival time model with a bioassay model where the log-hazard function is modelled as a linear or smoothing spline function of log-concentration combined with a smoothing spline function of time is described. The combined model is fitted to mortality numbers, resulting from survival times that are grouped due to a common set of observation times, using Generalized Additive Models (GAMs). The GAM fits mortalities as conditional binomials using an approximation to the log of the integral of the hazard function and is implemented using freely-available, general software for fitting GAMs. Extensions of the GAM are described to allow random effects to be fitted and to allow for time-varying concentrations by replacing time with a calibrated cumulative exposure variable with calibration parameter estimated using profile likelihood. The models are demonstrated using data from a studies of a marine and a, previously published, freshwater taxa. The marine study involved two replicate bioassays of the effect of zinc exposure on survival of an Antarctic amphipod, Orchomenella pinguides. The other example modelled survival of the daphnid, Daphnia magna, exposed to potassium dichromate and was fitted by both the GAM and the process-based DEBtox model. The GAM fitted with a cubic regression spline in time gave a 61 % improvement in fit to the daphnid data compared to DEBtox due to a non-monotonic hazard function. A simulation study using each of these hazard functions as operating models demonstrated that the GAM is overall more accurate in recovering lethal concentration values across the range of forms of the underlying hazard function compared to DEBtox and standard multiple endpoint probit analyses.