Elevationally biased avian predation as a contributor to the spatial distribution of geometrid moth outbreaks in sub‐arctic mountain birch forest

1. Population dynamics and interactions that vary over a species' range are of particular importance in the context of latitudinal clines in biological diversity. Winter moth (Operophtera brumata) and autumnal moth (Epirrita autumnata) are two species of eruptive geometrids that vary widely in outbreak tendency over their range, which generally increases from south to north and with elevation. 2. The predation pressure on geometrid larvae and pupae over an elevational gradient was tested. The effects of background larval density and bird occupancy of monitoring nest boxes on predation rates were also tested. Predation on larvae was tested through exclusion treatments at 20 replicate stations over four elevations at one site, while pupae were set out to measure predation at two elevations at three sites. 3. Larval densities were reduced by bird predation at three lower elevations, but not at the highest elevation, and predation rates were 1.9 times higher at the lowest elevation than at the highest elevation. The rate of predation on larvae was not related to background larval density or nest box occupancy, although there were more eggs and chicks at the lowest elevation. There were no consistent differences in predation on pupae by elevation. 4. These results suggest that elevational variation in avian predation pressure on larvae may help to drive elevational differences in outbreak tendency, and that birds may play a more important role in geometrid population dynamics than the focus on invertebrate and soil predators of previous work would suggest.     

Nutrients are assimilated efficiently by Lymantria dispar caterpillars from the mature leaves of trees in the Salicaceae

The efficient aquisition of nutrients from leaves by insect herbivores increases their nutrient assimilation rates and overall fitness. Caterpillars of the gypsy moth (Lymantria dispar L.) have high protein assimilation efficiencies (PAE) from the immature leaves of trees such as red oak (Quercus rubra) and sugar maple (Acer saccharum) (71–81%) but significantly lower PAE from their mature leaves (45–52%). By contrast to this pattern, both PAE and carbohydrate assimilation efficiencies (CAE) remain high for L. dispar larvae on the mature leaves of poplar (Populus alba × Populus tremula) grown in greenhouse conditions. The present study tests two alternative hypotheses: (i) outdoor environmental stresses cause decreased nutrient assimilation efficiencies from mature poplar leaves and (ii) nutrients in the mature leaves of trees in the poplar family (Salicaceae) remain readily available for L. dispar larvae. When poplar trees are grown in ambient outdoor conditions, PAE and CAE remain high (approximately 75% and 78%, respectively) in L. dispar larvae, in contrast to the first hypothesis. When larvae feed on the mature leaves of species in the Salicaceae [aspen (Populus tremuloides), cottonwood (Populus deltoides), willow (Salix nigra) and poplar], PAE and CAE also remain high (68–76% and 72–92%, respectively), consistent with the second hypothesis. Larval growth rates are strongly associated with protein assimilation rates, and more strongly associated with protein assimilation rates than with carbohydrate assimilation rates. It is concluded that tree species in the Salicaceae are relatively high‐quality host plants for L. dispar larvae, in part, because nutrients in their mature leaves remain readily available.     

On the use of partial area under the ROC curve for comparison of two diagnostic tests

Evaluation of diagnostic performance is typically based on the receiver operating characteristic (ROC) curve and the area under the curve (AUC) as its summary index. The partial area under the curve (pAUC) is an alternative index focusing on the range of practical/clinical relevance. One of the problems preventing more frequent use of the pAUC is the perceived loss of efficiency in cases of noncrossing ROC curves. In this paper, we investigated statistical properties of comparisons of two correlated pAUCs. We demonstrated that outside of the classic model there are practically reasonable ROC types for which comparisons of noncrossing concave curves would be more powerful when based on a part of the curve rather than the entire curve. We argue that this phenomenon stems in part from the exclusion of noninformative parts of the ROC curves that resemble straight‐lines. We conducted extensive simulation studies in families of binormal, straight‐line, and bigamma ROC curves. We demonstrated that comparison of pAUCs is statistically more powerful than comparison of full AUCs when ROC curves are close to a “straight line”. For less flat binormal ROC curves an increase in the integration range often leads to a disproportional increase in pAUCs’ difference, thereby contributing to an increase in statistical power. Thus, efficiency of differences in pAUCs of noncrossing ROC curves depends on the shape of the curves, and for families of ROC curves that are nearly straight‐line shaped, such as bigamma ROC curves, there are multiple practical scenarios in which comparisons of pAUCs are preferable.