Consequences of variation in predator attack for the evolution of the selfish herd

There is a strong body of evidence that patterns of collective behaviour in grouping animals are governed by interactions between small numbers of individuals within the group. These findings contrast with study of the ‘selfish herd’, where increasingly complex individual-level movement rules have been proposed to explain the rapid increase in aggregation observed when prey groups are startled by or detect a predator. While individuals using simple rules take into account the position of only a few neighbours, those using complex rules incorporate multiple neighbours, and their relative distance, to determine their movement direction. Here, we simulate the evolution of selfish herd behaviour to assess the conditions under which simple and complex movement rules might evolve, explicitly testing predictions arising from previous work. We find that complex rules outperform simple ones under a range of predator attack strategies, but that simple rules can fix in populations particularly when they are already in the majority, suggesting strong positive frequency dependence in rule success. In addition, we explore whether a movement rule derived from studies of collective behaviour (where individuals use the position of seven neighbours to determine movement direction) performs as successfully as more complex rules, finding again positive frequency dependence in rule success, and a particular role for predator attack strategy (from within or outside the group)

Technology adoption from hybrid corn to beta blockers

In his classic 1957 study of hybrid corn, Griliches emphasized the importance of economic incentives and profitability in the adoption of new technology, and this focus has been continued in the economics literature. But there is a distinct literature with roots in sociology emphasizing the structure of organizations, informal networks, and ““change agents.”” We return to a forty-year-old debate between Griliches and the sociologists by considering state-level factors associated with the adoption of a variety of technological innovations: hybrid corn and tractors in the first half of the 20th century, computers in the 1990s, and the treatment of heart attacks during the last decade. First, we find that some states consistently adopted new effective technology, whether hybrid corn, tractors, or effective treatments for heart attacks such as Beta Blockers. Second, the adoption of these new highly effective technologies was closely associated with social capital and state-level 1928 high school graduation rates, but not per capita income, density, or (in the case of Beta Blockers) expenditures on heart attack patients. Economic models are useful in identifying why some regions are more likely to adopt early, but sociological barriers -- perhaps related to a lack of social capital or informational networks -- can potentially explain why other regions lag far behind.

Technology Adoption From Hybrid Corn to Beta Blockers

In his classic 1957 study of hybrid corn, Griliches emphasized the importance of economic incentives and profitability in the adoption of new technology, and this focus has been continued in the economics literature. But there is a distinct literature with roots in sociology emphasizing the structure of organizations, informal networks, and "change agents." We return to a forty-year-old debate between Griliches and the sociologists by considering state-level factors associated with the adoption of a variety of technological innovations: hybrid corn and tractors in the first half of the 20th century, computers in the 1990s, and the treatment of heart attacks during the last decade. First, we find that some states consistently adopted new effective technology, whether hybrid corn, tractors, or effective treatments for heart attacks such as Beta Blockers. Second, the adoption of these new highly effective technologies was closely associated with social capital and state-level 1928 high school graduation rates, but not per capita income, density, or (in the case of Beta Blockers) expenditures on heart attack patients. Economic models are useful in identifying why some regions are more likely to adopt early, but sociological barriers -- perhaps related to a lack of social capital or informational networks -- can potentially explain why other regions lag far behind.