In a meta-analysis published by myself and co-authors, we report differences in the life history risk factors for estrogen receptor negative (ER−) and estrogen receptor positive (ER+) breast cancers. Our meta-analysis did not find the association of ER− breast cancer risk with fast life history characteristics that Hidaka and Boddy suggest in their response to our article. There are a number of possible explanations for the differences between their conclusions and the conclusions we drew from our meta-analysis, including limitations of our meta-analysis and methodological challenges in measuring and categorizing estrogen receptor status. These challenges, along with the association of ER+ breast cancer with slow life history characteristics, may make it challenging to find a clear signal of ER− breast cancer with fast life history characteristics, even if that relationship does exist. The contradictory results regarding breast cancer risk and life history characteristics illustrate a more general challenge in evolutionary medicine: often different sub-theories in evolutionary biology make contradictory predictions about disease risk. In this case, life history models predict that breast cancer risk should increase with faster life history characteristics, while the evolutionary mismatch hypothesis predicts that breast cancer risk should increase with delayed reproduction. Whether life history tradeoffs contribute to ER− breast cancer is still an open question, but current models and several lines of evidence suggest that it is a possibility.
Experiments have made important contributions to our understanding of human behavior, including behavior relevant for understanding social-ecological systems. When there is a conflict between individual and group interests in social-ecological systems, social dilemmas occur. From the many types of social-dilemma formulations that are used to study collective action, common-pool resource and public-good dilemmas are most relevant for social-ecological systems. Experimental studies of both common-pool resource and public-good dilemmas have shown that many predictions based on the conventional theory of collective action, which assumes rational, self-interested behavior, do not hold. More cooperation occurs than predicted (Ledyard 1995), “cheap talk” increases cooperation (Ostrom 2006), and participants are willing to invest in sanctioning free riders (Yamagishi 1986, Ostrom et al. 1992, Fehr and Gächter 2000, Chaudhuri 2011). Experiments have also demonstrated a diversity of motivations, which affect individual decisions about cooperation and sanctioning (see Fehr and Fischbacher 2002 and Sobel 2005 for reviews, and Bowles 2008 for policy implications).
The structure and dynamics of ecosystems can affect the information available to resource users on the state of the common resource and the actions of other resource users. We present results from laboratory experiments that showed that the availability of information about the actions of other participants affected the level of cooperation. Since most participants in commons dilemmas can be classified as conditional cooperators, not having full information about the actions of others may affect their decisions. When participants had more information about others, there was a more rapid reduction of the resource in the first round of the experiment. When communication was allowed, limiting the information available made it harder to develop effective institutional arrangements. When communication was not allowed, there was a more rapid decline of performance in groups where information was limited. In sum, the results suggest that making information available to others can have an important impact on the conditional cooperation and the effectiveness of communication.
Cancer therapy selects for cancer cells resistant to treatment, a process that is fundamentally evolutionary. To what extent, however, is the evolutionary perspective employed in research on therapeutic resistance and relapse? We analyzed 6,228 papers on therapeutic resistance and/or relapse in cancers and found that the use of evolution terms in abstracts has remained at about 1% since the 1980s. However, detailed coding of 22 recent papers revealed a higher proportion of papers using evolutionary methods or evolutionary theory, although this number is still less than 10%. Despite the fact that relapse and therapeutic resistance is essentially an evolutionary process, it appears that this framework has not permeated research. This represents an unrealized opportunity for advances in research on therapeutic resistance.