Variants of Myxococcus virescens Exhibiting Dispersed Growth. Growth and Production of Extracellular Enzymes and Slime

The growth of two strains of Myxococcus virescens exhibiting dispersed growth was followed in casamino acids (N III-C) media and casitone media. The changes in optical density, pH, pigmentation as well as the secretion of bacteriolytic and proteolytic enzymes, DNA and polysaccharides during growth were recorded. In both media the bacteria grew exponentially with a generation time of 4 (casitone) and 20 hours (N III-C) respectively. The maximal cell mass was about 4 times higher in casitone than in casamino acids media. The amounts of bacteriolytic enzymes produced by the two strains in N III-C medium were different but in casitone medium they were about equal and considerably higher. The maximal values of proteolytic enzymes were about the same in both media and always occurred later than the bacteriolytic maxima. Both activity peaks appeared before the phase of decline. The polysaccharide production reached a maximum during the stationary growth phase in both media. A higher value was reached during growth in casitone medium than in N III-C medium. During the phase of decline a second increase of polysaccharide in the medium appeared. No DNA could be detected in the cell-free solutions until the beginning of the phase of decline.     

Static species distribution models in dynamically changing systems: how good can predictions really be?

It is widely acknowledged that species respond to climate change by range shifts. Robust predictions of such changes in species’ distributions are pivotal for conservation planning and policy making, and are thus major challenges in ecological research. Statistical species distribution models (SDMs) have been widely applied in this context, though they remain subject to criticism as they implicitly assume equilibrium, and incorporate neither dispersal, demographic processes nor biotic interactions explicitly. In this study, the effects of transient dynamics and ecological properties and processes on the prediction accuracy of SDMs for climate change projections were tested. A spatially explicit multi‐species dynamic population model was built, incorporating species‐specific and interspecific ecological processes, environmental stochasticity and climate change. Species distributions were sampled in different scenarios, and SDMs were estimated by applying generalised linear models (GLMs) and boosted regression trees (BRTs). Resulting model performances were related to prevailing ecological processes and temporal dynamics. SDM performance varied for different range dynamics. Prediction accuracies decreased when abrupt range shifts occurred as species were outpaced by the rate of climate change, and increased again when a new equilibrium situation was realised. When ranges contracted, prediction accuracies increased as the absences were predicted well. Far‐dispersing species were faster in tracking climate change, and were predicted more accurately by SDMs than short‐dispersing species. BRTs mostly outperformed GLMs. The presence of a predator, and the inclusion of its incidence as an environmental predictor, made BRTs and GLMs perform similarly. Results are discussed in light of other studies dealing with effects of ecological traits and processes on SDM performance. Perspectives are given on further advancements of SDMs and for possible interfaces with more mechanistic approaches in order to improve predictions under environmental change.