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Plant pathogens are increasingly considered as important agents in promoting plant coexistence, while plant symbionts like ectomycorrhizal fungi (EMF) can facilitate plant dominance by helping conspecific individuals to defend against plant pathogens. However, we know little about their relationships with plants at large scales. Here, using soil fungal data collected from 28 forest reserves across China, we explored the latitudinal diversity gradients of overall fungi and different fungal functional guilds, including putative plant pathogens, EMF, and saprotrophic fungi. We further linked the spatial patterns of alpha diversities of putative plant pathogens and EMF to the variation of plant species richness. We found that the relationships between latitude and alpha diversities of putative plant pathogens and EMF were region-dependent with sharp diversity shifts around the mid-latitude (~35°N), which differed from the unimodal diversity distributions of the overall and saprotrophic fungi. The variations in the diversities of putative plant pathogens and EMF were largely explained by the spatial regions (south vs. north/subtropical zone vs. temperate zone). Additionally, the alpha diversities of these two fungal guilds exhibited opposing trends across latitude. EMF could alter the relationship between diversities of putative plant pathogens and plants in the south/subtropical region, but not vice versa. We also found that the ratio of their alpha diversities (EMF to putative plant pathogens) was negatively related to plant species richness across the spatial regions (north to south), and explained ~10% of the variation of plant species richness. Overall, our findings suggest that plant-microbe interactions not only shape the local plant diversity but also may have non-negligible contributions to the large-scale patterns of plant diversity in forest ecosystems.

Aim: We examined the effects of space, climate, phylogeny and species traits on module composition in a cross-biomes plant–hummingbird network. Location: Brazil, except Amazonian region. Methods: We compiled 31 local binary plant–hummingbird networks, combining them into one cross-biomes metanetwork. We conducted a modularity analysis and tested the relationship between species’ module membership with traits, geographical location, climatic conditions and range sizes, employing random forest models. We fitted reduced models containing groups of related variables (climatic, spatial, phylogenetic, traits) and combinations of groups to partition the variance explained by these sets into unique and shared components. Results: The Brazilian cross-biomes network was composed of 479 plant and 42 hummingbird species, and showed significant modularity. The resulting six modules conformed well to vegetation domains. Only plant traits, not hummingbird traits, differed between modules, notably plants’ growth form, corolla length, flower shape and colour. Some modules included plant species with very restricted distributions, whereas others encompassed more widespread ones. Widespread hummingbirds were the most connected, both within and between modules, whereas widespread plants were the most connected between modules. Among traits, only nectar concentration had a weak effect on among-module connectivity. Main conclusions: Climate and spatial filters were the main determinants of module composition for hummingbirds and plants, potentially related to resource seasonality, especially for hummingbirds. Historical dispersal-linked contingency, or environmental variations not accounted for by the explanatory factors here evaluated, could also contribute to the spatial component. Phylogeny and morphological traits had no unique effects on the assignment of species to modules. Widespread species showed higher within- and/or among-module connectivity, indicating their key role connecting biomes, and, in the case of hummingbirds, communities within biomes. Our results indicate that biogeography and climate not only determine the variation of modularity in local plant–animal networks, as previously shown, but also affect the cross-biomes network structure.

Owing to its prominent π‐delocalization and stability, vinylene linkage holds great merits in the construction of covalent organic frameworks (COFs) with promising semiconducting properties. However, carbon‐carbon double bond formation reaction always exhibits relatively low reversibility, unfavorable for the formation of high crystalline frameworks through self‐error correction and assembling processes. In this work, we report a heteroatom‐tuned strategy to build up a series of two‐dimensional (2D) vinylene‐linked COFs by Knoevenagel condensation of an electron‐deficient methylthiazolyl‐based monomer with different triformyl substituted (hetero−)aromatic derivatives. The resulting COFs show high‐quality periodic mesoporous structures with high surface areas. Embedding heteroatoms into the backbones enables significantly improving their crystallinity, and finely tailoring their semiconducting structures. Upon visible light stimulation, one of the as‐prepared COFs with donor‐π‐acceptor structure could deliver a nearly seven‐fold increase in the catalytic activity of hydrogen generation as compared with the other two. Meanwhile, in combination with high crystallinity and the matched conduction band energy level, such kind of COFs can be able to selectively generate singlet oxygen and superoxide radicals in a high ratio of up to 30 : 1, allowing for catalyzing aerobic thioanisole oxidation in distinctly tunable activities through the substituent electronic effect of the substrates. [ABSTRACT FROM AUTHOR]

Aim: The Kunming‐Montreal Global Biodiversity Framework requires that evolutionary histories of species should be considered in conservation planning. The phylogenetic structure of species assemblages quantifies species evolutionary histories and increasingly becomes an endeavour for ecologists. Understanding the geographic patterns of phylogenetic structure of species assemblages and their drivers can provide a fundamental reference for conservation planning. Although several theoretical hypotheses based on the effects of contemporary environment, historical climate change and evolutionary niche conservatism had been widely discussed in previous studies, the relative contributions of these hypotheses on phylogenetic structure of angiosperms, especially herbaceous species, remain debated. Location: East Eurasia. Major Taxa Studied: Angiosperms. Methods: We compiled distributions of 43,023 angiosperm species in east Eurasia at spatial resolution (100 × 100 km2). Using this newly compiled database and a species‐level phylogeny, we estimated the phylogenetic structure patterns for species with different growth forms. We explored the relationships of these patterns with contemporary environment and historical climate change to test predictions of the tropical niche conservatism hypothesis (TCH) and to compare the contribution of different hypotheses using generalised linear models and hierarchical partitioning. Results: We found that phylogenetic structure of angiosperms displayed significant latitudinal gradients. Notably, phylogenetic structure patterns and their drivers differed between woody and herbaceous species. Actual evapotranspiration was the best predictor of phylogenetic structure patterns for all and herbaceous species, while the mean temperature of the coldest quarter was the best predictor for woody species. The effect of historical climate change on phylogenetic structure patterns was weak. Main Conclusions: Our results suggest that the TCH only explains the phylogenetic structure pattern of woody species, not herbaceous species. Moreover, contemporary climate influences the phylogenetic structure of angiosperms in east Eurasian by affecting herbaceous and woody species differently. [ABSTRACT FROM AUTHOR]

Landslides are one of the major disasters that exist worldwide, posing a serious threat to human life and property safety. Rapid and accurate detection and mapping of landslides are crucial for risk assessment and humanitarian assistance in affected areas. To achieve this goal, this study proposes a landslide recognition method based on machine learning (ML) and terrain feature fusion. Taking the Dawan River Basin in Detuo Township and Tianwan Yi Ethnic Township as the research area, firstly, landslide-related data were compiled, including a landslide inventory based on field surveys, satellite images, historical data, high-resolution remote sensing images, and terrain data. Then, different training datasets for landslide recognition are constructed, including full feature datasets that fusion terrain features and remote sensing features and datasets that only contain remote sensing features. At the same time, different ratios of landslide to non-landslide (or positive/negative, P/N) samples are set in the training data. Subsequently, five ML algorithms, including Extreme Gradient Boost (XGBoost), Adaptive Boost (AdaBoost), Light Gradient Boost (LightGBM), Random Forest (RF), and Convolutional Neural Network (CNN), were used to train each training dataset, and landslide recognition was performed on the validation area. Finally, accuracy (A), precision (P), recall (R), F1 score (F1), and intersection over union (IOU) were selected to evaluate the landslide recognition ability of different models. The research results indicate that selecting ML models suitable for the study area and the ratio of the P/N samples can improve the A, R, F1, and IOU of landslide identification results, resulting in more accurate and reasonable landslide identification results; Fusion terrain features can make the model recognize landslides more comprehensively and align better with the actual conditions. The best-performing model in the study is LightGBM. When the input data includes all features and the P/N sample ratio is optimal, the A, P, R, F1, and IOU of landslide recognition results for this model are 97.47%, 85.40%, 76.95%, 80.95%, and 71.28%, respectively. Compared to the landslide recognition results using only remote sensing features, this model shows improvements of 4.51%, 35.66%, 5.41%, 22.27%, and 29.16% in A, P, R, F1, and IOU, respectively. This study serves as a valuable reference for the precise and comprehensive identification of landslide areas. [ABSTRACT FROM AUTHOR]

Aim: Reproductive systems strongly influence plants' evolution and adaption, and the biogeographic pattern of its variation has intrigued biologists and ecologists. Here, to test the impacts of paleoglaciation on plants' reproductive system variation, we compared the geographical pattern and environmental drivers in the proportions of different reproductive systems in Primula in regions affected and unaffected by paleoglaciation. Location: Global. Time Period: Since the Last Glacial Maximum (LGM). Major Taxa Studied: Primula. Methods: Using data on reproductive systems and distributions of 604 Primula taxa around the world and 221 along the elevational gradient of the Himalayas, we demonstrated the global pattern and the elevational pattern in the proportions of homostylous taxa. We employed general linear models to establish the relationship between the proportion of homostylous taxa and environmental variables and hierarchical partitioning to assess the relative contributions of these variables in both regions affected and unaffected by paleoglaciation, respectively. Results: We found a higher proportion of homostylous taxa in regions glaciated during the LGM than those unglaciated, with different latitudinal patterns and climate drivers. The proportion of homostylous taxa showed varying trends across different regions: increasing with latitude and temperature anomaly in glaciated regions while concentrating at lower latitudes with higher winter temperatures in unglaciated regions. Additionally, homostylous taxa were more prevalent at lower elevations in the Himalayas. Main Conclusions: Our study provides the first quantitative evidence for the hypothesis that selfers are more prevailing in regions affected by paleoglaciation facilitated by recolonization via comparing the geographic pattern and drivers in regions affected and unaffected by paleoglaciation. Our findings also reveal the concentrated distribution of homostylous taxa in Primula at low latitudes, which may be the result of population shrinkage caused by heat stress, facing a more severe survival crisis under the circumstances of global warming and increasing human activities. [ABSTRACT FROM AUTHOR]

Mechanisms underlying large‐scale spatial patterns of species richness are one of the central issues in ecology. Although contemporary climate, evolutionary history, and historical climate change have been proposed as drivers of species richness patterns, variation in the relative importance of different factors remains a major challenge. Here, using newly compiled distribution data with a spatial resolution of 100 × 100 km for 43 023 angiosperms plant species in east Eurasia, we mapped species richness patterns for plants with different growth forms (i.e. woody versus herbaceous) and range sizes (i.e. wide‐ranged versus narrow‐ranged species), and compared the relative importance of the four hypotheses in explaining these patterns, i.e. freezing tolerance hypothesis, historical climate change hypothesis, Janzen's hypothesis (predicting that climate seasonality and topography determine species richness patterns), and diversification rate hypothesis. We found that species richness of all angiosperm plants presented a clear latitudinal gradient and was highest in southwestern China and Central Asian mountains. Notably, species richness patterns and their dominant drivers differed between species groups. Historical climate change was the dominant driver for richness patterns of all and herbaceous species. The freezing tolerance hypothesis dominated the drivers for all woody species, while Janzen's hypothesis dominated narrow‐ranged woody and herbaceous species. Our study suggests that different hypotheses contribute to large‐scale plant richness patterns via their effects on different plant groups. Our results did not support the diversification rate hypothesis, but demonstrated the high importance of historical climate change to plant diversity in east Eurasia, providing new perspectives on the mechanisms of plant diversity patterns in this continent. [ABSTRACT FROM AUTHOR]

Jinci spring is a famous karst spring in Shanxi Province, and its backflow is an ecological restoration goal of the Shanxi Provincial government. Composed of Nanlao spring, Shengmu spring, and Shanli spring, Jinci spring is exposed at the foot of Xuanweng mountain in the western mountains of Taiyuan, twenty-five kilometers away from the city center, and it is a concentrated discharge point for karst water in the Jinci spring area. Karst water in the spring area is mainly supplied by atmospheric precipitation infiltration and leakage from rivers and reservoirs. Karst water in the Jinci spring area is an important water source for people's life and industrial and agricultural production in Taiyuan City. In recent years, with the intensification of climate change, large-scale development of karst water, coal mining and other human activities, especially after the construction of the second reservoir of the Fenhe river, the karst hydrogeological conditions in the spring area have undergone fundamental changes, with the spring area expanding from 2,030 km2 to 2,713 km2, which has affected the evaluation, management and protection of karst water resources in the spring area. The original zoning of protected areas can no longer meet the needs of water resource management and protection. Therefore, it is urgent to re-zone the protected areas and formulate corresponding protection measures. In terms of the problems on water quality and quantity, there exist differences in the causes, regions, and protective measures, and thus LIANG Yongping et al. proposed the concepts of "water quantity vulnerability" and "water quality vulnerability", as well as a method of "first classifying, and then grading" for the zoning of karst aquifer protected areas.This study focuses on the hydrogeological conditions of special recharge, runoff, and discharge in the karst water system of North China, as well as the main influencing factors of the antifouling performance of karst aquifer systems. It combines European methods and "water vulnerability assessment" to evaluate the antifouling performance. Based on infiltration duration of karst water in the unsaturated zone, leakage of rivers and reservoirs, precipitation infiltration in different regions, and replacement of karst aquifer media structure with water abundance, this study selects four factors to evaluate the antifouling performance of karst aquifers in North China, including the thickness of unsaturated zone, the amount of infiltration recharge, the lithology of overlying strata, and the water abundance of karst aquifers. Taking the newly divided karst water system in the Jinci spring area as the evaluation object, this study aims to evaluate the vulnerability of karst water system in the spring area and to zone the protected areas.The results show as follows, (1) The protected areas are mainly distributed in Jinci park and its surrounding areas. (2) The first-class protected areas are mainly distributed in the main stream of the Fenhe river, the exposed areas of carbonate rocks in the front of western mountains of Taiyuan, and the leakage sections of carbonate rocks in Tunlanchuan, the Tianchi river and the Liulin river. (3) The second-class protected areas are mainly distributed in the north of the spring area and the north bank of the Fenhe river. (4) The quasi-protected areas are mainly distributed in the south bank of the Fenhe river and the Taiyuan basin in the southeast. The newly zoned protected areas for spring water quality can provide a basis for the rational protection and scientific utilization of karst water resources in the Jinci spring area [ABSTRACT FROM AUTHOR]

GaN HEMT devices are sensitive to the single event effect (SEE) caused by heavy ions, and their reliability affects the safe use of space equipment. In this work, a Ge ion (LET = 37 MeV·cm2/mg) and Bi ion (LET = 98 MeV·cm2/mg) were used to irradiate Cascode GaN power devices by heavy ion accelerator experimental device. The differences of SEE under three conditions: pre-applied electrical stress, different LET values, and gate voltages are studied, and the related damage mechanism is discussed. The experimental results show that the pre-application of electrical stress before radiation leads to an electron de-trapping effect, generating defects within the GaN device. These defects will assist in charge collection so that the drain leakage current of the device will be enhanced. The higher the LET value, the more electron–hole pairs are ionized. Therefore, the charge collected by the drain increases, and the burn-out voltage advances. In the off state, the more negative the gate voltage, the higher the drain voltage of the GaN HEMT device, and the more serious the back-channel effect. This study provides an important theoretical basis for the reliability of GaN power devices in radiation environments. [ABSTRACT FROM AUTHOR]