Population demography and the evolution of helping behaviors.

Limited dispersal may favor the evolution of helping behaviors between relatives as it increases their relatedness, and it may inhibit such evolution as it increases local competition between these relatives. Here, we explore one way out of this dilemma: if the helping behavior allows groups to expand in size, then the kin-competition pressure opposing its evolution can be greatly reduced. We explore the effects of two kinds of stochasticity allowing for such deme expansion. First, we study the evolution of helping under environmental stochasticity that may induce complete patch extinction. Helping evolves if it results in a decrease in the probability of extinction or if it enhances the rate of patch recolonization through propagules formed by fission of nonextinct groups. This mode of dispersal is indeed commonly found in social species. Second, we consider the evolution of helping in the presence of demographic stochasticity. When fecundity is below its value maximizing deme size (undersaturation), helping evolves, but under stringent conditions unless positive density dependence (Allee effect) interferes with demographic stochasticity. When fecundity is above its value maximizing deme size (oversaturation), helping may also evolve, but only if it reduces negative density-dependent competition.

Analyse des risques d'extinction des populations naturelles

A review of extinction risk analysis and viability methods is presented. The importance of environmental, demographic and genetic uncertainties, as well as the role of catastrophes are successively considered, and different approaches aiming at the integration of these risk factors in predictive population dynamic models are discussed.

Using information from telephone panel surveys to predict reasons for refusal

One of the key problems in conducting surveys is convincing people to participate.¦However, it is often difficult or impossible to determine why people refuse. Panel surveys¦provide information from previous waves that can offer valuable clues as to why people¦refuse to participate. If we are able to anticipate the reasons for refusal, then we¦may be able to take appropriate measures to encourage potential respondents to participate¦in the survey. For example, special training could be provided for interviewers¦on how to convince potential participants to participate.¦This study examines different influences, as determined from the previous wave,¦on refusal reasons that were given by the respondents in the subsequent wave of the¦telephone Swiss Household Panel. These influences include socio-demography, social¦inclusion, answer quality, and interviewer assessment of question understanding and¦of future participation. Generally, coefficients are similar across reasons, and¦between-respondents effects rather than within-respondents effects are significant.¦While 'No interest' reasons are easier to predict, the other reasons are more situational. Survey-specific issues are able to distinguish¦different reasons to some extent.