scholarly journals Early unpredictability predicts increased adolescent externalizing behaviors and substance use: A life history perspective

2015 ◽  
Vol 28 (4pt2) ◽  
pp. 1505-1516 ◽  
Author(s):  
Jenalee R. Doom ◽  
Adrienne A. Vanzomeren-Dohm ◽  
Jeffry A. Simpson

AbstractAccording to evolutionary life history models, environmental harshness and unpredictability can both promote a fast life history strategy characterized by increased risk taking and enacting short-term, opportunistic behaviors. The current longitudinal study tests whether environmental unpredictability during childhood has stronger effects on risky behavior during adolescence than harshness, and whether there may be an early “sensitive period” during which unpredictability has particularly strong and unique effects on these outcomes. Using data from the Minnesota Longitudinal Study of Risk and Adaptation, prospective assessments of environmental unpredictability (changes in residence, cohabitation, and parental occupation) and harshness (mean socioeconomic status) from birth into adolescence were used to predict self-reported externalizing behaviors and substance use at age 16 (N = 220). Exposure to greater early unpredictability (between ages 0 and 5) predicted more externalizing behaviors as well as more alcohol and marijuana use at age 16, controlling for harshness and later unpredictability (between ages 6 and 16). Harshness predicted adolescent substance use, and later unpredictability predicted adolescent externalizing behaviors at the trend level. Early unpredictability and harshness also interacted, such that the highest levels of risk taking occurred in individuals who experienced more early unpredictability and lived in harsher environments. Age 16 externalizing behaviors, but not substance use, mediated the association between early unpredictability and externalizing/criminal behaviors at age 23. We discuss how exposure to early environmental unpredictability may alter biological and social–cognitive functioning from a life history perspective.

2014 ◽  
Vol 12 (5) ◽  
pp. 147470491401200 ◽  
Author(s):  
George B. Richardson ◽  
Ching-Chen Chen ◽  
Chia-Liang Dai ◽  
Patrick H. Hardesty ◽  
Christopher M. Swoboda

2016 ◽  
Vol 46 (2) ◽  
pp. 102-121 ◽  
Author(s):  
George B. Richardson ◽  
Chia-Liang Dai ◽  
Ching-Chen Chen ◽  
Joseph L. Nedelec ◽  
Christopher M. Swoboda ◽  
...  

The Condor ◽  
2006 ◽  
Vol 108 (3) ◽  
pp. 530-546 ◽  
Author(s):  
Joshua T. Ackerman ◽  
John M. Eadie ◽  
Thomas G. Moore

AbstractLife-history theory predicts that longer-lived, less fecund species should take fewer risks when exposed to predation than shorter-lived, more fecund species. We tested this prediction for seven species of dabbling ducks (Anas) by measuring the approach behavior (behavior of ducks when approaching potential landing sites) of 1099 duck flocks during 37 hunting trials and 491 flocks during 13 trials conducted immediately after the 1999–2000 waterfowl hunting season in California, USA. We also experimentally manipulated the attractiveness of the study site by using two decoy treatments: (1) traditional, stationary decoys only, and (2) traditional decoys in conjunction with a mechanical spinning-wing decoy. Approach behavior of ducks was strongly correlated with their life history. Minimum approach distance was negatively correlated with reproductive output during each decoy treatment and trial type. Similarly, the proportion of flocks taking risk (approaching landing sites to within 45 m) was positively correlated with reproductive output. We found similar patterns of approach behavior in relation to other life-history parameters (i.e., adult female body mass and annual adult female survival rate). Thus, species characterized by a slower life-history strategy (e.g., Northern Pintail [A. acuta]) were more risk-averse than species with a faster life-history strategy (e.g., Cinnamon Teal [A. cyanoptera]). Furthermore, although we were able to reduce risk-averseness using the spinning-wing decoy, we were unable to override the influence of life history on risk-taking behavior. Alternative explanations did not account for the observed correlation between approach behavior and life-history parameters. These results suggest that life history influences the risk-taking behavior of dabbling ducks and provide an explanation for the differential vulnerability of waterfowl to harvest.


2020 ◽  
Author(s):  
Rebecca Sear

Interest in incorporating life history research from evolutionary biology into the human sciences has grown rapidly in recent years. Two core features of this research have the potential to prove valuable in strengthening theoretical frameworks in the health and social sciences: the idea that these is a fundamental trade-off between reproduction and health; and that environmental influences are important in determining individual life histories. For example, the idea that mortality risk in the environment shifts individuals along a ‘fast-slow continuum’ of ‘life history strategy’ is now popular in the evolutionary human sciences. In biology, ‘fast’ life history strategists prioritise reproduction over health so that individuals grow quickly, reproduce early and often, and suffer a rapid deterioration in health and relatively early death; ‘slow’ strategists start reproducing later, have fewer offspring, and die at an older age. Evolutionary human scientists tend to assume that, along with these life history outcomes, several behavioural traits, such as parenting, mating and risk-taking behaviour and, in the most expansive version, a whole suite of psychological and personality traits also cluster together into ‘fast’ and ‘slow’ life histories. Here, I review the different approaches to life history strategies from evolutionary anthropologists, developmental psychologists and evolutionary psychologists, in order to assess the theoretical and empirical evidence for human ‘life history strategies’. While there is precedent in biology for the argument that some behavioural traits, notably risk-taking behaviour, may be linked in predictable ways with life history outcomes, there is relatively little theoretical or empirical justification for including a very wide range of behavioural traits in a ‘life history strategy’. Given the diversity and lack of consistency in this human life history literature, I then make recommendations for improving its usefulness: 1) greater clarity over terminology, so that a distinction is made between life history outcomes such as age at maturity, first birth and death, and behavioural traits which may be associated with life history outcomes but are not life history traits themselves; 2) more empirical data on linkages between life history traits, behavioural traits and the environment, including the underlying mechanisms which generate these linkages; 3) more empirical work on life history strategies in a much broader range of populations than has so far been studied. Such a research programme on human life history has the potential to produce valuable insights for the health and social sciences, not least because of its interest in environmental influences on health, reproduction and behaviour.


Nematology ◽  
2017 ◽  
Vol 19 (3) ◽  
pp. 263-270 ◽  
Author(s):  
Robin A.J. Taylor ◽  
Sun-Jeong Park ◽  
Parwinder S. Grewal

In the first longitudinal study of nematode spatial distribution with sufficiently large samples to estimate Taylor’s power law (TPL), we concluded that TPL is sensitive to life history strategy. We also observed that the value of TPL slope b was generally higher for more widespread and abundant taxa. We deduce that removal of empty samples increases b and discuss the results in relation to known causes of bias in estimating TPL. Only one cause might explain an increase in b with removal of empty quadrats: the underestimation of variance. Although bias cannot be ruled out in rare taxa, the consistency of the pattern with very abundant genera suggests a different explanation. TPL appears sensitive to the number of samples in a survey that do not contain the taxon of interest. We conclude that TPL measures the space between individuals as well as the density-dependence of the numerical distribution of abundance.


2021 ◽  
Vol 15 (1) ◽  
pp. 27-41
Author(s):  
Curtis S. Dunkel ◽  
Jonathan J. Hammersley ◽  
Micheal L. Waters ◽  
Dimitri van der Linden ◽  
Laureon A. Merrie ◽  
...  

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