The influence of varying degress of spore aggregation on the coexistence of the mosses Splachnum ampullacuem and S. luteum: a simulation study

Abstract

Splachnum ampullaceum and S. luteum are mosses that grow on the droppings of large mammals and coexist throughout much of boreal North America. Field and laboratory data were incorporated into two simulation models to examine the influences of patchiness and the intraspecific aggregation of spores in promoting the coexistence of these mosses. Coexistence within a single peatland in a ‘local dynamics’ model and coexistence over three adjacent peatlands in a ‘regional dynamics’ model was examined. In both models, the spore production from droppings was determined by using Ricker-type equations that were modified by removing the intraspecific competition coefficient since the mean reproductive output of spores from a dropping appears to be independent of the recruitment of spores to that dropping and by assuming that the reproductive output from a dropping is a function of the relative proportion of spores of different species that were distributed on that dropping when it was fresh. Two types of simulation experiments using these models were performed: in one set the fixed number of droppings per peatland was varied, in a second set the mean number of droppings and the magnitude of year-to-year fluctuations about this mean was varied. In both models the mosses persisted longer as the number of droppings/peatland was increased, regardless of whether the number of droppings/peatland was held constant or fluctuated randomly. Also, in both models the two mosses coexisted for a longer time as the degree of intraspecific aggregation of spores increased. There was little difference between times to extinction in the regional dynamics model, either with or without dispersal of spores between adjacent peatlands, and the local dynamics model in which the number of droppings either equaled or fluctuated within the same range of values as the total number of droppings in the regional dynamics model.