01878nas a2200133   4500008004100000245006700041210006600108300001400174490000700188520146200195100002001657700002001677856004701697       2005                        eng d00aEstimating postnatal dispersal: tracking the unseen dispersers0 aEstimating postnatal dispersal tracking the unseen dispersers  a1185-11900 v863 aPostnatal dispersal, defined as dispersal from the natal patch soon after reaching maturity, is common in a variety of insect species. Postnatal dispersal may increase connections among subpopulations and, thus, significantly affect local population dynamics in metapopulation and source-sink contexts. Yet most mark-recapture studies,of insects miss the postnatal dispersal phase because it comes soon after eclosion. Cephaloleia fenestrata (Chrysomelidae) is a specialist herbivore of the rolled leaves of Pleiostachya pruinosa (Marantaceae, common name "prayer plant"). Some P. pruinosa patches were flooded prior to the onset of this study, extirpating the majority of C. fenestrata in the flood zone and providing a natural experiment and an opportunity to observe recolonization dynamics. We built a spatially explicit population projection matrix model to simulate spatial population dynamics of C. fenestrata. The model was a poor fit to the empirical data. Adding postnatal dispersal to the model resulted in a much better model fit. This study suggests that 81% of C. fenestrata disperse from the natal site soon after eclosion. Model simulations indicated that postnatal dispersal increases the mean population size in the flood zone more than six-fold and the standard deviation more than three-fold. Herein we present an implicit method of estimating postnatal dispersal when marking animals before the postnatal dispersal phase is problematic.1 aJohnson, D., M.1 aHorvitz, C., C.  uhttps://cephaloleia.myspecies.info/node/2202357nas a2200121   4500008004100000245008900041210006900130300001400199490000700213520194800220100002002168856004702188       2005                        eng d00aMetapopulation models: An empirical test of model assumptions and evaluation methods0 aMetapopulation models An empirical test of model assumptions and  a3088-30980 v863 aPatch occupancy models provide a simple phenomenological approach to evaluating ecological questions on a metapopulation scale. In this study, I use and modify a patch occupancy model to evaluate the effects of synchronous extinctions correlated with flooding and patch-size-dependent migration on the regional dynamics of a neotropical beetle, Cephaloleia fenestrata. Various methods have been used to evaluate patch occupancy models. Previous authors most commonly have evaluated patch occupancy models by logistic regression of incidence functions. Likelihoods produced from regression methods, however, neglect autocorrelation in spatial occupancy patterns even though spatial autocorrelation is common in ecological data. In this study, I used a Monte Carlo method of model evaluation, which accounts for spatial autocorrelation. Results suggest that patches undergo synchronous extinctions correlated with flooding and this affects regional dynamics of C. fenestrata. Immigration probability positively correlated with patch size, and emigration probability negatively correlated with patch size, also affecting C. fenestrata regional dynamics. The patch occupancy pattern was positively spatially autocorrelated at only two of the sites, but was nearly significant at another. The logistic regression method was a reasonable alternative to the Monte Carlo method for model evaluation. Other model evaluation methods (fits to model development data, proportion of occupied patches, and turnover rates) were inconsistent (at best) quantitative measures of a model’s fit to independent data. When used to select among competing models, however, the fits to model development data were reasonably good indicators of fits to independent data. Given the increased complexity involved in using the Monte Carlo method, the simpler logistic regression method may be a preferable alternative, especially when spatial autocorrelation is minimal.1 aJohnson, D., M.  uhttps://cephaloleia.myspecies.info/node/23