Temporal and spatial variations in the parasitoid complex of the horse chestnut leafminer during its invasion of Europe

The enemy release hypothesis posits that the initial success of invasive species depends on the scarcity and poor adaptation of native natural enemies such as predators and parasitoids. As for parasitoids, invading hosts are first attacked at low rates by a species-poor complex of mainly generalist species. Over the years, however, parasitoid richness may increase either because the invading host continuously encounters new parasitoid species during its spread (geographic spread-hypothesis) or because local parasitoids need different periods of time to adapt to the novel host (adjustment-hypothesis). Both scenarios should result in a continuous increase of parasitoid richness over time. In this study, we reconstructed the development of the hymenopteran parasitoid complex of the invasive leafminer Cameraria ohridella (Lepidoptera, Gracillariidae). Our results show that the overall parasitism rate increases as a function of host residence time as well as geographic and climatic factors, altogether reflecting the historic spread of C. ohridella. The same variables also explain the individual parasitism rates of several species in the parasitoid complex, but fail to explain the abundance of others. Evidence supporting the “geographic spread-hypothesis” was found in the parasitism pattern of Cirrospilus talitzkii (Hymenoptera, Eulophidae), while that of Pediobius saulius, another eulophid, indicated an increase of parasitism rates by behavioral, phenological or biological adjustments. Compared to fully integrated host-parasitoid associations, however, parasitism rates of C. ohridella are still very low. In addition, the parasitoid complex lacks specialists, provided that the species determined are valid and not complexes of cryptic (and presumably more specialized) species. Probably, the adjustment of specialist parasitoids requires more than a few decades, particularly to invaders which establish in ecological niches free of native hosts, thus eliminating any possibility of recruitment of pre-adapted parasitoids

A Macroecological Analysis of SERA Derived Forest Heights and Implications for Forest Volume Remote Sensing

Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H100, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H100 and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 102–106 plants/hectare and heights 6–49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing physics is recommended as a more universal indicator of volume when using remote sensing than achieved using either maximum height or H100