Biology subjects

Ryan Baldini

Publications and source records attributed to Ryan Baldini.

5 recordsLinked to original sources

bioRxiv2015

Harsh environments and "fast" human life histories: What does the theory say?

AO_SCPLOWBSTRACTC_SCPLOWA common belief among human life history researchers is that \"harsher\" environments - i.e., those with higher mortality rates and resource stress - select for \"fast\" life histories, i.e. earlier reproduction and faster senescence. I show that these \"harsh environments, fast life histories\" - or HEFLH - hypotheses are poorly supported by evolutionary theory. First, I use a simple model to show that effects of environmental harshness on life history evolution are incredibly diverse. In particular, small changes in basic but poorly understood variables - e.g., whether and how population density affects vital rates - can cause selection to favor very different life histories. Furthermore, I show that almost all life history theory used to justify HEFLH hypotheses is misapplied in the first place. The reason is that HEFLH hypotheses usually treat plastic responses to heterogeneous environmental conditions within a population, whereas the theory used to justify such hypotheses treat genetic responses to environmental changes across an entire population. Counter-intuitively, the predictions of the former do not generally apply to the latter: the optimal response to a harsh environment within a large heterogeneous environment is not necessarily the optimal strategy of a population uniformly inhabiting the same harsh environment. I discuss these theoretical results in light of the current state of empirical research.

Evolutionary Biology↗

bioRxiv2014

How cultural transmission facilitates a long juvenile learning period

The evolution of the long, slow human life history is a major challenge to evolutionary biologists. A compelling theory states that our late age at maturity allows us to acquire the many skills needed to survive in the economically intensive human foraging niche. Cultural transmission may be a crucial part of this process, by exposing learners to a wealth of information and skills that they would otherwise not likely discover. I use mathematical models to show that whether cultural transmission allows a later age at maturity depends on the details of selection and population regulation. In particular, cultural transmission appears to readily allow a later age at maturity under density-dependent fertility, but may not under density-dependent mortality or density-independent population growth. I close with a discussion of possibilities for future theoretical and empirical research.

Evolutionary Biology↗

bioRxiv2014

Estimating the evolution of human life history traits in age-structured populations

I propose a method that estimates the selection response of all vital rates in an age-structured population. I assume that vital rates are determined by the additive genetic contributions of many loci. The method uses all relatedness information in the sample to inform its estimates of genetic parameters, via an MCMC Bayesian framework. One can use the results to estimate the selection response of any life history trait that is a function of the vital rates, including the age at first reproduction, total lifetime fertility, survival to adulthood, and others. This method closely ties the empirical analysis of life history evolution to dynamically complete models of natural selection, and therefore enjoys some theoretical advantages over other methods. I demonstrate the method on a simulated model of evolution with two age classes. Finally I discuss how the method can be extended to more complicated cases.

Evolutionary Biology↗

bioRxiv2013

Revisiting the effect of population size on cumulative cultural evolution

Henrich (2004) argued that larger populations can better maintain complex technologies because they contain more highly skilled people whom others can imitate. His original model, however, did not distinguish the effects of population size from population density or network size; a learners social network included the entire population. Does population size remain important when populations are subdivided and networks are realistically small? I use a mathematical model to show that population size has little effect on equilibrium levels of mean skill under a wide range of conditions. The effects of network size and transmission error rate usually overshadow that of population size. Population size can, however, affect the rate at which a population approaches equilibrium, by increasing the rate at which innovations arise. This effect is small unless innovation is very rare. Whether population size predicts technological complexity in the real world, then, depends on whether technological evolution is innovation-limited and short of equilibrium. The effect of population \"connectedness,\" via migration or trade, is similar. I discuss the results of this analysis in light of the current empirical debate.

Evolutionary Biology↗

bioRxiv2013

The importance of population growth and regulation in human life history evolution

Explaining the evolution of human life history characteristics remains an outstanding problem to evolutionary anthropologists. Progress is hindered by common misunderstandings of how selection works in age-structured populations. I review two important results of life history theory related to demography. First, different life history strategies evolve under density-independent and density-dependent population growth. Second, and more poorly appreciated, different kinds of density-dependence also select for different life history strategies; assuming zero population growth alone is insufficient to determine the optimal strategy. I show that these facts are more than methodological niceties by reanalyzing the model by Kaplan et al. (2000) and showing that the results depend strongly on the form of population regulation assumed. This analysis suggests that progress in human life history theory requires better understanding of the demography of our ancestors. I close with a discussion of empirical implications.

Evolutionary Biology↗