Phenotypic Divergence During the Invasion of \u3cem\u3ePhyla Canescens\u3c/em\u3e in Australia and France: Evidence for Selection-Driven Evolution

Rapid adaptive evolution has been advocated as a mechanism that promotes invasion. Demonstrating adaptive evolution in invasive species requires rigorous analysis of phenotypic shifts driven by selection. Here, we document selection-driven evolution of Phyla canescens, an Argentine weed, in two invaded regions (Australia and France). Invasive populations possessed similar or higher diversity than native populations, and displayed mixed lineages from different sources, suggesting that genetic bottlenecks in both countries might have been alleviated by multiple introductions. Compared to native populations, Australian populations displayed more investment in sexual reproduction, whereas French populations possessed enhanced vegetative reproduction and growth. We partitioned evolutionary forces (selection vs. stochastic events) using two independent methods. Results of both analyses suggest that the pattern of molecular and phenotypic variability among regions was consistent with selection-driven evolution, rather than stochastic events. Our findings indicate that selection has shaped the evolution of P. canescens in two different invaded regions

Differential Influence of Clonal Integration on Morphological and Growth Responses to Light in Two Invasive Herbs

Background and aims: In contrast to seeds, high sensitivity of vegetative fragments to unfavourable environments may limit the expansion of clonal invasive plants. However, clonal integration promotes the establishment of propagules in less suitable habitats and may facilitate the expansion of clonal invaders into intact native communities. Here, we examine the influence of clonal integration on the morphology and growth of ramets in two invasive plants, Alternanthera philoxeroides and Phyla canescens, under varying light conditions. Methods: In a greenhouse experiment, branches, connected ramets and severed ramets of the same mother plant were exposed under full sun and 85 % shade and their morphological and growth responses were assessed. Key results: The influence of clonal integration on the light reaction norm (connection6light interaction) of daughter ramets was species-specific. For A. philoxeroides, clonal integration evened out the light response (total biomass, leaf mass per area, and stem number, diameter and length) displayed in severed ramets, but these connection6light interactions were largely absent for P. canescens. Nevertheless, for both species, clonal integration overwhelmed light effect in promoting the growth of juvenile ramets during early development. Also, vertical growth, as an apparent shade acclimation response, was more prevalent in severed ramets than in connected ramets. Finally, unrooted branches displayed smaller organ size and slower growth than connected ramets, but the pattern of light reaction was similar, suggesting mothe

Uncertain species distribution: From interpolation to extrapolation

Species distribution models (SDMs) are considered to exemplify Pattern rather than Process based models of a species' response to its environment. Hence when used to map species distribution, the purpose of SDMs can be viewed as interpolation, since species response is measured at a few sites in the study region, and the aim is to interpolate species response at intermediate sites. Increasingly, however, SDMs are also being used to also extrapolate species-environment relationships beyond the limits of the study region as represented by the training data. \ud \ud Regardless of whether SDMs are to be used for interpolation or extrapolation, the debate over how to implement SDMs focusses on evaluating the quality of the SDM, both ecologically and mathematically. This paper proposes a framework that includes useful tools previously employed to address uncertainty in habitat modelling. Together with existing frameworks for addressing uncertainty more generally when modelling, we then outline how these existing tools help inform development of a broader framework for addressing uncertainty, specifically when building habitat models. As discussed earlier we focus on extrapolation rather than interpolation, where the emphasis on predictive performance is diluted by the concerns for robustness and ecological relevance. We are cognisant of the dangers of excessively propagating uncertainty. Thus, although the framework provides a smorgasbord of approaches, it is intended that the exact menu selected for a particular application, is small in size and targets the most important sources of uncertainty. We conclude with some guidance on a strategic approach to identifying these important sources of uncertainty. Whilst various aspects of uncertainty in SDMs have previously been addressed, either as the main aim of a study or as a necessary element of constructing SDMs, this is the first paper to provide a more holistic view

Sellers’ Revisited: A Big Data Reassessment of Historical Outbreaks of Bluetongue and African Horse Sickness due to the Long-Distance Wind Dispersion of Culicoides Midges

The possibility that outbreaks of bluetongue (BT) and African horse sickness (AHS) might occur via long-distance wind dispersion (LDWD) of their insect vector (Culicoides spp.) was proposed by R. F. Sellers in a series of papers published between 1977 and 1991. These investigated the role of LDWD by means of visual examination of the wind direction of synoptic weather charts. Based on the hypothesis that simple wind direction analysis, which does not allow for wind speed, might have led to spurious conclusions, we reanalyzed six of the outbreak scenarios described in Sellers’ papers. For this reanalysis, we used a custom-built Big Data application (“TAPPAS”) which couples a user-friendly web-interface with an established atmospheric dispersal model (“HYSPLIT”), thus enabling more sophisticated modeling than was possible when Sellers undertook his analyzes. For the two AHS outbreaks, there was strong support from our reanalysis of the role of LDWD for that in Spain (1966), and to a lesser degree, for the outbreak in Cyprus (1960). However, for the BT outbreaks, the reassessments were more complex, and for one of these (western Turkey, 1977) we could discount LDWD as the means of direct introduction of the virus. By contrast, while the outbreak in Cyprus (1977) showed LDWD was a possible means of introduction, there is an apparent inconsistency in that the outbreaks were localized while the dispersion events covered much of the island. For Portugal (1956), LDWD from Morocco on the dates suggested by Sellers is very unlikely to have been the pathway for introduction, and for the detection of serotype 2 in Florida (1982), LDWD from Cuba would require an assumption of a lengthy survival time of the midges in the air column. Except for western Turkey, the BT reanalyses show the limitation of LDWD modeling when used by itself, and indicates the need to integrate susceptible host population distribution (and other covariate) data into the modeling process. A further refinement, which will become increasingly important to assess LDWD, will be the use of virus and vector genome sequence data collected from potential source and the incursion sites