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A phylogenetic approach identifies patterns of beta diversity and floristic subregions of the Qinghai-Tibet Plateau

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Plant Diversity 2024年第1期46卷 59-69页

作者： Haibin Yu Man Yang Zixin Lu Weitao Wang Fangyuan Yu Yonghua Zhang Xue Yin Hongjun Yu Junjie Hu David C.Deane Key Laboratory of Conservation and Application in Biodiversity of South China School of Life SciencesGuangzhou UniversityGuangzhou 510006China School of Ecology Sun Yat-Sen UniversityShenzhen 510275China School of Geography and remote sensing Guangzhou UniversityGuangzhou 510006China College of Life and Environmental Science Wenzhou UniversityWenzhou 325035China centre for Future Landscapes and Department of Environment and Genetics La Trobe UniversityBundooraVIC 3083Australia

Patterns of taxonomic and phylogenetic beta diversity and their relationships with environmental correlates can help reveal the origin and evolutionary history of regional *** Qinghai-Tibet Plateau(QTP)harbors an exceptionally diverse flora,however,a phylogenetic perspective has rarely been used to investigate its beta diversity and floristic *** this study,we used a phylogenetic approach to identify patterns of beta diversity and quantitatively delimit floristic regions on the Qinghai-Tibet *** also examined the relationships between multifaceted beta diversity,geographical distance,and climatic difference,and evaluated the relative importance of various factors(i.e.,climate,topography and history)in shaping patterns of beta diversity.Sørensen dissimilarity indices indicated that patterns of species turnover among sites dominated the *** also found that patterns of both taxonomic and phylogenetic beta diversity were significantly related to geographical distance and climatic *** environmental factors that contributed most to these patterns of beta diversity include annual precipitation,mean annual temperature,climatic gradients and climatic *** dendrograms of dissimilarity and non-metric multidimensional scaling ordination based on phylogenetic beta diversity data identified ten floristic subregions in the *** results suggest that the contemporary environment and historical climate changes have filtered species composition among sites and eventually determined beta diversity patterns of plants in the QTP.

关键词： Biogeographical regionalization Phylogenetic beta diversity Seed plants Sørensen dissimilarity Qinghai-Tibet Plateau

Improving model performance in mapping cropland soil organic matter using time-series remote sensing data

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Journal of Integrative Agriculture 2024年第8期23卷 2820-2841页

作者： Xianglin Zhang Jie Xue Songchao Chen Zhiqing Zhuo Zheng Wang Xueyao Chen Yi Xiao Zhou Shi Institute of Applied remote sensing and Information Technology College of Environmental and Resource SciencesZhejiang UniversityHangzhou 310058China Department of Land Management Zhejiang UniversityHangzhou 310058China ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang UniversityHangzhou 311215China Institute of Digital Agriculture Zhejiang Academy of Agricultural SciencesHangzhou 310021China Key Laboratory of Spectroscopy sensing Ministry of Agriculture and Rural AffairsHangzhou 310058China

Faced with increasing global soil degradation,spatially explicit data on cropland soil organic matter(SOM)provides crucial data for soil carbon pool accounting,cropland quality assessment and the formulation of effective management *** a spatial information prediction technique,digital soil mapping(DSM)has been widely used to spatially map soil information at different ***,the accuracy of digital SOM maps for cropland is typically lower than for other land cover types due to the inherent difficulty in precisely quantifying human *** overcome this limitation,this study systematically assessed a framework of“information extractionfeature selection-model averaging”for improving model performance in mapping cropland SOM using 462 cropland soil samples collected in Guangzhou,China in *** results showed that using the framework of dynamic information extraction,feature selection and model averaging could efficiently improve the accuracy of the final predictions(R^(2):0.48 to 0.53)without having obviously negative impacts on *** the dynamic information of the environment was an efficient way to generate covariates that are linearly and nonlinearly related to SOM,which improved the R^(2)of random forest from 0.44 to 0.48 and the R^(2)of extreme gradient boosting from 0.37to *** recursive feature selection(FRFS)is recommended when there are relatively few environmental covariates(500).The Granger-Ramanathan model averaging approach could improve the prediction accuracy and average *** the structures of initial prediction models are similar,increasing in the number of averaging models did not have significantly positive effects on the final *** the advantages of these selected strategies over information extraction,feature selection and model averaging have a great potential for high-accuracy soil mapping

关键词： cropland soil organic matter digital soil mapping machine learning feature selection model averaging

Retrieval of high spatial resolution mountainous land surface temperature considering topographic and adjacency effects

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Science China Earth Sciences 2024年

作者： Zhiwei HE Bohui TANG Zhaoliang LI Faculty of Land Resources Engineering Kunming University of Science and Technology Key Laboratory of Plateau remote sensing Department of Education of Yunnan Province State Key Lab of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of Sciences Key Laboratory of Agricultural remote sensing Ministry of Agriculture and Rural Affairs Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences

Land surface temperature(LST) is a key parameter reflecting the interaction between land and atmosphere. Currently,thermal infrared(TIR) quantitative remote sensing technology is the only means to obtain large-scale, high spatial resolution LST. Accurately retrieving high spatial resolution mountainous LST(MLST) plays an important role in the study of mountain climate change. The complex terrain and strong spatial heterogeneity in mountainous areas change the geometric relationship between the surface and satellite sensors, affecting the radiation received by the sensors, and rendering the assumption of planar parallelism invalid. In this study, considering the influence of complex terrain in mountainous areas on atmospheric downward radiation and the thermal radiation contribution of adjacent pixels, a mountainous TIR radiative transfer model based on the sky view factor was developed. Combining with the atmospheric radiative transfer model MODTRAN 5.2, a nonlinear generalized split-window algorithm suitable for high spatial resolution MLST retrieval was constructed and applied to Landsat-9 TIRS-2satellite TIR remote sensing data. The analysis results indicate that neglecting the topographic and adjacency effects would lead to significant discrepancies in LST retrieval, with simulated data showing LST differences of up to 2.5 K. Furthermore, due to the lack of measured MLST in the field, the MLST accuracy obtained by this retrieval method was indirectly validated using the currently recognized highest-accuracy forward 3D radiative transfer model DART. The MLST and emissivity were input into the DART model to simulate the brightness temperature at the top of the atmosphere(TOA) of Landsat-9 band 10, and compared with the brightness temperature at TOA of Landsat-9 band 10. The RMSE(Root Mean Square Error) for the two subregions was0.50 and 0.61 K, respectively, indicating that the method proposed can retrieve high-precision MLST.

关键词：

Cloud Top Pressure Retrieval Using Polarized and Oxygen A-band Measurements from GF5 and PARASOL Satellites

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Advances in Atmospheric Sciences 2024年第4期41卷 680-700页

作者： Lesi WEI Huazhe SHANG Jian XU Chong SHI Gegen TANA Kefu CHAO Shanhu BAO Liangfu CHEN Husi LETU State Key Laboratory of remote sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100101China national Space Science Center Chinese Academy of SciencesBeijing 101407China College of Physics and Electronic Information Inner Mongolia Normal UniversityHohhot 010022China College of Geographical Science Inner Mongolia Normal UniversityHohhot 010022China University of Chinese Academy of Sciences Beijing 100101China

Cloud top pressure(CTP)is one of the critical cloud properties that significantly affects the radiative effect of ***-angle polarized sensors can employ polarized bands(490 nm)or O_(2)A-bands(763 and 765 nm)to retrieve the ***,the CTP retrieved by the two methods shows inconsistent results in certain cases,and large uncertainties in low and thin cloud retrievals,which may lead to challenges in subsequent *** study proposes a synergistic algorithm that considers both O_(2)A-bands and polarized bands using a random forest(RF)*** CTP data are used as the true values and the polarized and non-polarized measurements are concatenated to train the RF model to determine ***,through analysis,we proposed that the polarized signal becomes saturated as the cloud optical thickness(COT)increases,necessitating a particular treatment for cases where COTremote sensing algorithm within the Cloud Application for remote sensing,Atmospheric Radiation,and Updating Energy(CARE)platform.

关键词： atmospheric remote sensing cloud top pressure multi-angle polarized O_(2)A-band GF-5/DPC PARASOL/POLDER-3

Development of a novel critical nitrogen concentration-cumulative transpiration curve for optimizing nitrogen management under varying irrigation conditions in winter wheat

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The Crop Journal 2024年第4期12卷 1242-1251页

作者： Tianyang Ye Yu Zhang Jingyan Xuan Xintian Wang Yang Li Junhao Xu Liujun Xiao Leilei Liu Liang Tang Weixing Cao Bing Liu Yan Zhu national Engineering and Technology Center for Information Agriculture Engineering Research Center of Smart AgricultureMinistry of EducationKey Laboratory for Crop System Analysis and Decision MakingMinistry of AgricultureJiangsu Key Laboratory for Information AgricultureJiangsu Collaborative Innovation Center for Modern Crop ProductionNanjing Agricultural UniversityNanjing 210095JiangsuChina Institute of remote sensing and Digital Agriculture Sichuan Academy of Agricultural SciencesChengdu 610066SichuanChina

Accurate nitrogen(N)nutrition diagnosis is essential for improving N use efficiency in crop *** widely used critical N(Nc)dilution curve traditionally depends solely on agronomic variables,neglecting crop water *** three-year field experiments with winter wheat,encompassing two irrigation levels(rainfed and irrigation at jointing and anthesis)and three N levels(0,180,and 270 kg ha1),this study aims to establish a novel approach for determining the Nc dilution curve based on crop cumulative transpiration(T),providing a comprehensive analysis of the interaction between N and water *** Nc curves derived from both crop dry matter(DM)and T demonstrated N concentration dilution under different conditions with different *** equation Nc=6.43T0.24 established a consistent relationship across varying irrigation *** test results indicated that the nitrogen nutrition index(NNI),calculated from this curve,effectively identifies and quantifies the two sources of N deficiency:insufficient N supply in the soil and insufficient soil water concentration leading to decreased N availability for root ***,the NNI calculated from the Nc-DM and Nc-T curves exhibited a strong negative correlation with accumulated N deficit(Nand)and a positive correlation with relative grain yield(RGY).The NNI derived from the Nc-T curve outperformed the NNI derived from the Nc-DM curve concerning its relationship with Nand and RGY,as indicated by larger R2 values and smaller *** novel Nc curve based on T serves as an effective diagnostic tool for assessing winter wheat N status,predicting grain yield,and optimizing N fertilizer management across varying irrigation *** findings would provide new insights and methods to improve the simulations of water-N interaction relationship in crop growth models.

关键词： Crop dry matter Crop cumulative transpiration Bayesian statistical model Critical nitrogen dilution curve Nitrogen nutrition index

Improved simulation of winter wheat yield in North China Plain by using PRYM-Wheat integrated dry matter distribution coefficient

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Journal of Integrative Agriculture 2024年第4期23卷 1381-1392页

作者： Xuan Li Shaowen Wang Yifan Chen Danwen Zhang Shanshan Yang Jingwen Wang Jiahua Zhang Yun Bai Sha Zhang Research Center for remote sensing and Digital Earth College of Computer Science and TechnologyQingdao UniversityQingdao266071China Center for Geospatial Information Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China School of Geographical Sciences Hebei Normal UniversityShijiazhuang 050024China

The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in ***,most remote sensing process models use the“biomass×harvest index(HI)”method to simulate regional-scale winter wheat ***,spatiotemporal differences in HI contribute to inaccuracies in yield simulation at the regional ***-series dry matter partition coefficients(Fr)can dynamically reflect the dry matter partition of winter *** this study,Fr equations were fitted for each organ of winter wheat using site-scale *** equations were then coupled into a process-based and remote sensingdriven crop yield model for wheat(PRYM-Wheat)to improve the regional simulation of winter wheat yield over the North China Plain(NCP).The improved PRYM-Wheat model integrated with the fitted Fr equations(PRYM-Wheat-Fr)was validated using data obtained from provincial yearbooks.A 3-year(2000-2002)averaged validation showed that PRYM-Wheat-Fr had a higher coefficient of determination(R^(2)=0.55)and lower root mean square error(RMSE=0.94 t ha^(-1))than PRYM-Wheat with a stable HI(abbreviated as PRYM-Wheat-HI),which had R^(2) and RMSE values of 0.30 and 1.62 t ha^(-1),*** PRYM-Wheat-Fr model also performed better than PRYM-Wheat-HI for simulating yield in verification years(2013-2015).In conclusion,the PRYM-Wheat-Fr model exhibited a better accuracy than the original PRYM-Wheat model,making it a useful tool for the simulation of regional winter wheat yield.

关键词： dry matter partition remote sensing model winter wheat yield North China Plain

Experimental study of population density using an optimized random forest model

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Journal of Geographical Sciences 2024年第8期34卷 1636-1656页

作者： LI Lingling LIU Jinsong LI Zhi WEN Peizhang LI Yancheng LIU Yi School of Geographical Sciences Hebei Normal UniversityShijiazhuang 050024China Hebei Technology Innovation Center for remote sensing Identification of Environmental Change Shijiazhuang 050024China Geocomputation and Planning Center of Hebei Normal University Shijiazhuang 050024China Hebei Key Laboratory of Environmental Change and Ecological Construction Shijiazhuang 050024China

Random forest model is the mainstream research method used to accurately describe the distribution law and impact mechanism of regional *** took Shijiazhuang as the research area,with comprehensive zoning based on endowments as the modeling unit,conducted stratified sampling on a hectare grid cell,and systematically carried out incremental selection experiments of population density impact factors,optimizing the population density random forest model throughout the process(zonal modeling,stratified sampling,factor selection,weighted output).The results are as follows:(1)Zonal modeling addresses the issue of confusion in population distribution laws caused by a single *** on a grid cell not only ensures the quality of training data by avoiding the modifiable areal unit problem(MAUP)but also attempts to mitigate the adverse effects of the ecological *** sampling ensures the stability of population density label values(target variable)in the training sample.(2)Zonal selection experiments on population density impact factors help identify suitable combinations of factors,leading to a significant improvement in the goodness of fit(R^(2))of the zonal models.(3)Weighted combination output of the population density prediction dataset substantially enhances the model's robustness.(4)The population density dataset exhibits multi-scale superposition *** a large scale,the population density in plains is higher than that in mountainous areas,while on a small scale,urban areas have higher density compared to rural *** optimization scheme for the population density random forest model that we propose offers a unified technical framework for uncovering local population distribution law and the impact mechanisms.

关键词： population density random forest model endowment zones stratified sampling factor selection weighted output

Spatio-Temporal Characteristics of Heavy Precipitation Forecasts from ECMWF in Eastern China

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Journal of Tropical Meteorology 2024年第1期30卷 29-41页

作者：徐同谭燕顾问 Shanghai Typhoon Institute and Key Laboratory of Numerical Modeling for Tropical Cyclone of China Meteorological AdministrationShanghai 200030 China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100080 China Shanghai Ecological Forecasting and remote sensing Center Shanghai 200030 China

This study examines the spatio-temporal characteristics of heavy precipitation forecasts in eastern China from the European centre for Medium-Range Weather Forecasts(ECMWF) using the time-domain version of the Method for Object-based Diagnostic Evaluation(MODE-TD). A total of 23 heavy rainfall cases occurring between 2018 and 2021 are selected for analysis. Using Typhoon “Rumbia” as a case study, the paper illustrates how the MODE-TD method assesses the overall simulation capability of models for the life history of precipitation systems. The results of multiple tests with different parameter configurations reveal that the model underestimates the number of objects’ forecasted precipitation tracks, particularly at smaller radii. Additionally, the analysis based on centroid offset and area ratio tests for different classified precipitation objects indicates that the model performs better in predicting large-area, fast-moving, and longlifespan precipitation objects. Conversely, it tends to have less accurate predictions for small-area, slow-moving, and shortlifespan precipitation objects. In terms of temporal characteristics, the model overestimates the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. In terms of temporal characteristics, the model tends to overestimate the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. Overall, the model provides more accurate predictions for the duration and dissipation of precipitation objects with large-area or long-lifespan(such as typhoon precipitation) while having large prediction errors for precipitation objects with small-area or short-lifespan. Furthermore, the model’s simulation results regarding the generation of precipitation objects show that it performs relati

关键词： MODE-TD ECMWF heavy precipitation Eastern China

Data error propagation in stacked bioclimatic envelope models

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Integrative Zoology 2024年第2期19卷 262-276页

作者： Xueyan LI Babak NAIMI Peng GONG Miguel B.ARAÚJO Guangdong Provincial Key Laboratory of remote sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and ApplicationGuangzhou Institute of GeographyGuangdong Academy of ScienceGuangzhouChina ‘Rui Nabeiro’Biodiversity Chair CHANGE-MED InstituteUniversity ofÉvoraÉvoraPortugal Department of Geography and Department of Earth Sciences University of Hong KongHong KongChina Department of Biogeography and Global Change National Museum of Natural SciencesCSICMadridSpain

Stacking is the process of overlaying inferred species potential distributions for multiple species based on outputs of bioclimatic envelope models(BEMs).The approach can be used to investigate patterns and processes of species *** data limitations on individual species distributions are inevitable,but how do they affect inferences of patterns and processes of species richness?We investigate the influence of different data sources on estimated species richness gradients in *** fitted BEMs using species distributions data for 334 bird species obtained from(1)global range maps,(2)regional checklists,(3)museum records and surveys,and(4)citizen science data using presence-only(Mahalanobis distance),presence-background(MAXENT),and presence–absence(GAM and BRT)*** species predictions were stacked to generate species richness ***,we show that different data sources and BEMs can generate spatially varying gradients of species *** environmental predictors that best explained species distributions also differed between data *** using citizen-based data had the highest accuracy,whereas those using range data had the lowest *** richness patterns estimated by GAM and BRT models were robust to data *** multiple data sets exist for the same region and taxa,we advise that explicit treatments of uncertainty,such as sensitivity analyses of the input data,should be conducted during the process of modeling.

关键词： richness patterns species distribution stacked bioclimatic envelope models uncertainty