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Ren Zhi-An (任治安)*, Lu Wei (陆伟), Yang Jie (杨杰), Yi Wei (衣玮), Shen Xiao-Li (慎晓丽), Li Zheng-Cai (李 正才), Che Guang-Can (车广灿), Dong Xiao-Li (董晓莉), Sun Li-Ling (孙立玲), Zhou Fang (周放), Zhao Zhong-Xian (赵忠贤)*

We use powder neutron diffraction to study the spin and lattice structures of polycrystalline samples of nonsuperconducting PrFeAsO and superconducting PrFeAsO 0.85 F 0.15 and PrFeAsO 0.85 . We find that PrFeAsO exhibits an abrupt structural phase transitions at 153 K, followed by static long range antiferromagnetic order at 127 K.Both the structural distortion and magnetic order are identical to other rare-earth oxypnictides. Electron-doping the system with either Fluorine or oxygen deficiency 2 suppresses the structural distortion and static long range antiferromagnetic order, therefore placing these materials into the same class of FeAs-based superconductors.

Pollinating species are in decline globally, with land use an important driver. However, most of the evidence on which these claims are made is patchy, based on studies with low taxonomic and geographic representativeness. Here, we model the effect of land-use type and intensity on global pollinator biodiversity, using a local-scale database covering 303 studies, 12,170 sites, and 4502 pollinating species. Relative to a primary vegetation baseline, we show that low levels of intensity can have beneficial effects on pollinator biodiversity. Within most anthropogenic land-use types however, increasing intensity is associated with significant reductions, particularly in urban (43% richness and 62% abundance reduction compared to the least intensive urban sites), and pasture (75% abundance reduction) areas. We further show that on cropland, the strongly negative response to intensity is restricted to tropical areas, and that the direction and magnitude of response differs among taxonomic groups. Our findings confirm widespread effects of land-use intensity on pollinators, most significantly in the tropics, where land use is predicted to change rapidly.

Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control activities for sustaining elimination and preventing reintroduction of malaria. In China, however, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of climate change on four dominant malaria vectors (An. dirus, An. minimus, An. lesteri and An. sinensis) using species distribution models for two future decades: the 2030 s and the 2050 s. Simulation-based estimates suggest that the environmentally suitable area (ESA) for An. dirus and An. minimus would increase by an average of 49% and 16%, respectively, under all three scenarios for the 2030 s, but decrease by 11% and 16%, respectively in the 2050 s. By contrast, an increase of 36% and 11%, respectively, in ESA of An. lesteri and An. sinensis, was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios. in the 2050 s. In total, we predict a substantial net increase in the population exposed to the four dominant malaria vectors in the decades of the 2030 s and 2050 s, considering land use changes and urbanization simultaneously. Strategies to achieve and sustain malaria elimination in China will need to account for these potential changes in vector distributions and receptivity.

By investigating the F-doping effect in the SmFeAsO1−xFx, SmFeAsO1−xF0.20 and SmFeAsO0.90Fx systems as well as the oxygen vacancy effect in the SmFeAsO1−y superconductors, we obtained the following results: (a) the substitution range of F for oxygen in the SmFeAsO1−xFx system prepared by the ambient pressure method is 0≤x≤0.125; (b) F cannot substitute for oxygen in samples without oxygen vacancies; (c) the oxygen-deficient SmFeAsO1−y superconductor cannot be prepared by the ambient pressure method; and (d) F-doping and oxygen vacancies both lead to lattice shrinkage. Oxygen-deficient SmFeAsO0.85 and F-doped SmFeAsO0.85F0.15 prepared by the high pressure method have higher superconducting transition temperature compared to SmFeAsO0.85F0.15 prepared by the ambient pressure method.

Geographically weighted regression (GWR) is an important local method to explore spatial non-stationarity in data relationships. It has been repeatedly used to examine spatially varying relationships between epidemic diseases and predictors. Malaria, a serious parasitic disease around the world, shows spatial clustering in areas at risk. In this article, we used GWR to explore the local determinants of malaria incidences over a 7-year period in northern China, a typical midlatitude, high-risk malaria area. Normalized difference vegetation index (NDVI), land surface temperature (LST), temperature difference, elevation, water density index (WDI) and gross domestic product (GDP) were selected as predictors. Results showed that both positively and negatively local effects on malaria incidences appeared for all predictors except for WDI and GDP. The GWR model calibrations successfully depicted spatial variations in the effect sizes and levels of parameters, and also showed substantially improvements in terms of goodness of fits in contrast to the corresponding non-spatial ordinary least squares (OLS) model fits. For example, the diagnostic information of the OLS fit for the 7-year average case is R 2 5 0.243 and AICc 5 837.99, while significant improvement has been made by the GWR calibration with R 2 5 0.800 and AICc 5 618.54. K E Y W O R D Sgeographically weighted regression, local determinants examination, malaria incidence, remote sensing monitoring data, spatial analysis models 1 | I NTR OD U CTI ON

The evolution of floral traits in animal-pollinated plants involves the interaction between flowers as signal senders and pollinators as signal receivers. Flower colors are very diverse, effect pollinator attraction and flower foraging behavior, and are hypothesized to be shaped through pollinator-mediated selection. However, most of our current understanding of flower color evolution arises from variation between discrete color morphs and completed color shifts accompanying pollinator shifts, while evidence for pollinator-mediated selection on continuous variation in flower colors within populations is still scarce. In this review, we summarize experiments quantifying selection on continuous flower color variation in natural plant populations in the context of pollinator interactions. We found that evidence for significant pollinator-mediated selection is surprisingly limited among existing studies. We propose several possible explanations related to the complexity in the interaction between the colors of flowers and the sensory and cognitive abilities of pollinators as well as pollinator behavioral responses, on the one hand, and the distribution of variation in color phenotypes and fitness, on the other hand. We emphasize currently persisting weaknesses in experimental procedures, and provide some suggestions for how to improve methodology. In conclusion, we encourage future research to bring together plant and animal scientists to jointly forward our understanding of the mechanisms and circumstances of pollinator-mediated selection on flower color.