Distribution of PERIOD-immunoreactive neurons and temporal change of the immunoreactivity under long-day and short-day conditions in the larval brain of the flesh fly Sarcophaga similis

The flesh fly Sarcophaga similis show a clear photoperiodic response; they develop into adults under long days, whereas they arrest their development at the pupal stage under short days. Although the involvement of a circadian clock in photoperiodic time measurement is suggested in this species, the anatomical location of the clock neurons responsible for the time measurement has been unknown. We detected two PERIOD-immunoreactive cell clusters in the larval brain; one cluster was located at the dorsoanterior region and the other at the medial region. We further investigated their temporal changes in PERIOD-immunoreactivity and compared their patterns under different photoperiods.     

Mechanical performance of endodontic restorations with prefabricated posts: sensitivity analysis of parameters with a 3D finite element model

Many studies have investigated the effect of different parameters of the endodontically restored tooth on its final strength, using in vitro tests and model simulations. However, the differences in the experimental set-up or modelling conditions and the limited number of parameters studied in each case prevent us from obtaining clear conclusions about the relative importance of each parameter. In this study, a validated 3D biomechanical model of the restored tooth was used for an exhaustive sensitivity analysis. The individual influence of 20 different parameters on the mechanical performance of an endodontic restoration with prefabricated posts was studied. The results bring up the remarkable importance of the loading angle on the final restoration strength. Flexural loads are more critical than compressive or tensile loads. Young's modulus of the post and its length and diameter are the most influential parameters for strength, whereas other parameters such as ferrule geometry or core and crown characteristics are less significant.     

Climate oscillations and species interactions: large‐scale congruence but regional differences in the phylogeographic structures of an alpine plant and its monophagous insect

Aim To predict the fate of alpine interactions involving specialized species, using a monophagous beetle and its host plant as a case study. Location The Alps. Methods We investigated genetic structuring of the herbivorous beetle Oreina gloriosa and its specific host‐plant Peucedanum ostruthium. We used genome fingerprinting (in the insect and the plant) and sequence data (in the insect) to compare the distribution of the main gene pools in the two associated species and to estimate divergence time in the insect, a proxy for the temporal origin of the interaction. We quantified the similarity in spatial genetic structures by performing a Procrustes analysis, a tool from shape theory. Finally, we simulated recolonization of an empty space analogous to the deglaciated Alps just after ice retreat by two lineages from two species showing unbalanced dependence, to examine how timing of the recolonization process, as well as dispersal capacities of associated species, could explain the observed pattern. Results Contrasting with expectations based on their asymmetrical dependence, patterns in the beetle and plant were congruent at a large scale. Exceptions occurred at a regional scale in areas of admixture, matching known suture zones in Alpine plants. Simulations using a lattice‐based model suggested these empirical patterns arose during or soon after recolonization, long after the estimated origin of the interaction c. 0.5 million years ago. Main conclusions Species‐specific interactions are scarce in alpine habitats because glacial cycles have limited the opportunities for co‐evolution. Their fate, however, remains uncertain under climate change. Here we show that whereas most dispersal routes are paralleled at a large scale, regional incongruence implies that the destinies of the species might differ under changing climate. This may be a consequence of the host dependence of the beetle, which locally limits the establishment of dispersing insects.     

Sinks and sources of methylmercury in a boreal catchment

A simple, catchment-scale, cascade model was used toassess the importance of sinks and sources ofmethylmercury (MeHg) in a boreal catchment thatcontains a forested upland, a lowland peatland and asmall lake. The three compartment model was run usingrealistic flow rates and atmospheric loading of MeHg,and the model was constrained by observedconcentrations of MeHg in each compartment. Assumingno internal sinks and sources of MeHg, modelledcatchment yields showed reasonable agreement withfield observation, but the predicted internal MeHgconcentrations in each compartment were implausible. Only when sources and sinks of MeHg are added to thethree compartments do MeHg-pool concentrations fallinto the range of those measured in the field. Tomaintain both catchment-scale and compartment-scalecontinuity, the upland and peatland were net sourcesof MeHg (0.0007 and 0.1065 mg ha^-1 d^-1respectively), and the lake a net sink (-0.2215 mgha^-1 d^-1). These source/sink rates are 1.73,259 and -539 times the input of MeHg via wetprecipitation input for the modelled ice-free season. Sensitivity analysis revealed that the volume ofrunoff delivered to the peatland by the upland area,peatland size and porewater MeHg concentration in thepeatland are important controls on catchment MeHgyield, and that contemporary atmospheric deposition ofMeHg is insignificant compared to the sources of MeHgwithin the catchment.     

Modelling minirhizotron observations to test experimental procedures

In order to help design experiments with minirhizotrons or interpret data from such experiments, a modelling approach is a valuable tool to complement empirical approaches. The general principle of this modelling approach is to calculate and to study the part of a theoretical root system that is intersected by passes through a virtual minirhizotron tube (modelled here as a cylinder). Various outputs can be calculated from this part of the root system, and related to the surrounding root system which is perfectly known, since it has been simulated and stored in a data structure. Therefore, the method involves two levels of modelling that are presented and discussed: the root system architecture of a crop, and the observations that can be achieved with minirhizotron tubes. Illustrations of the method are presented to study the effect of several factors on the rooting depth curves, and to show how images may be calculated to mimic what can actually be viewed from inside the tube. These first results show that the maximum rooting depth curves, as virtually observed in the minirhizotron tube, present large variations and strongly underestimate the maximum rooting depth of the modelled root system (up to 60 cm in average). The underestimation is still more critical when the radius of the tube is lower than 3 cm, and when the tube is close to the vertical (angle lower than 0.2 rad). The use of the 0.9 quantile instead of the average value, for each of the observation dates, leads to a better estimation of the maximum rooting depth.     

Characterizing and predicting species distributions across environments and scales: Argentine ant occurrences in the eye of the beholder

Aim Species distribution models (SDMs) or, more specifically, ecological niche models (ENMs) are a useful and rapidly proliferating tool in ecology and global change biology. ENMs attempt to capture associations between a species and its environment and are often used to draw biological inferences, to predict potential occurrences in unoccupied regions and to forecast future distributions under environmental change. The accuracy of ENMs, however, hinges critically on the quality of occurrence data. ENMs often use haphazardly collected data rather than data collected across the full spectrum of existing environmental conditions. Moreover, it remains unclear how processes affecting ENM predictions operate at different spatial scales. The scale (i.e. grain size) of analysis may be dictated more by the sampling regime than by biologically meaningful processes. The aim of our study is to jointly quantify how issues relating to region and scale affect ENM predictions using an economically important and ecologically damaging invasive species, the Argentine ant (Linepithema humile). Location California, USA. Methods We analysed the relationship between sampling sufficiency, regional differences in environmental parameter space and cell size of analysis and resampling environmental layers using two independently collected sets of presence/absence data. Differences in variable importance were determined using model averaging and logistic regression. Model accuracy was measured with area under the curve (AUC) and Cohen's kappa. Results We first demonstrate that insufficient sampling of environmental parameter space can cause large errors in predicted distributions and biological interpretation. Models performed best when they were parametrized with data that sufficiently sampled environmental parameter space. Second, we show that altering the spatial grain of analysis changes the relative importance of different environmental variables. These changes apparently result from how environmental constraints and the sampling distributions of environmental variables change with spatial grain. Conclusions These findings have clear relevance for biological inference. Taken together, our results illustrate potentially general limitations for ENMs, especially when such models are used to predict species occurrences in novel environments. We offer basic methodological and conceptual guidelines for appropriate sampling and scale matching.