Despite that several studies have shown that data derived from species lists generated from distribution occurrence records in the Global Biodiversity Information Facility(GBIF)are not appropriate for those ecological...Despite that several studies have shown that data derived from species lists generated from distribution occurrence records in the Global Biodiversity Information Facility(GBIF)are not appropriate for those ecological and biogeographic studies that require high sampling completeness,because species lists derived from GBIF are generally very incomplete,Suissa et al.(2021)generated fern species lists based on data with GBIF for 100 km×100 km grid cells across the world,and used the data to determine fern diversity hotspots and species richness-climate relationships.We conduct an evaluation on the completeness of fern species lists derived from GBIF at the grid-cell scale and at a larger spatial scale,and determine whether fern data derived from GBIF are appropriate for studies on the relations of species composition and richness with climatic variables.We show that species sampling completeness of GBIF is low(<40%)for most of the grid cells examined,and such low sampling completeness can substantially bias the investigation of geographic and ecological patterns of species diversity and the identification of diversity hotspots.We conclude that fern species lists derived from GBIF are generally very incomplete across a wide range of spatial scales,and are not appropriate for studies that require data derived from species lists in high completeness.We present a map showing global patterns of fern species diversity based on complete or nearly complete regional fern species lists.展开更多
This paper reviews literature pertaining to the development of data science as a discipline,current issues with data bias and ethics,and the role that the discipline of information science may play in addressing these...This paper reviews literature pertaining to the development of data science as a discipline,current issues with data bias and ethics,and the role that the discipline of information science may play in addressing these concerns.Information science research and researchers have much to offer for data science,owing to their background as transdisciplinary scholars who apply human-centered and social-behavioral perspectives to issues within natural science disciplines.Information science researchers have already contributed to a humanistic approach to data ethics within the literature and an emphasis on data science within information schools all but ensures that this literature will continue to grow in coming decades.This review article serves as a reference for the history,current progress,and potential future directions of data ethics research within the corpus of information science literature.展开更多
As a huge,intense,and elevated atmospheric heat source(AHS) approaching the mid-troposphere in spring and summer,the Tibetan Plateau(TP) thermal forcing is perceived as an important factor contributing to the formatio...As a huge,intense,and elevated atmospheric heat source(AHS) approaching the mid-troposphere in spring and summer,the Tibetan Plateau(TP) thermal forcing is perceived as an important factor contributing to the formation and variation of the Asian summer monsoon.Despite numerous studies devoted to determine the strength and change of the thermal forcing of the TP on the basis of various data sources and methods,uncertainties remain in quantitative estimation of the AHS and will persist for the following reasons:(1) Routine meteorological stations cover only limited regions and show remarkable spatial inhomogeneity with most distributed in the central and eastern plateau.Moreover,all of these stations are situated at an altitude below 5000 m.Thus,the large area above that elevation is not included in the data.(2) Direct observations on heat fluxes do not exist at most stations,and the sensible heat flux(SHF) is calculated by the bulk formula,in which the drag coefficient for heat is often treated as an empirical constant without considering atmospheric stability and thermal roughness length.(3) Radiation flux derived by satellite remote sensing shows a large discrepancy in the algorithm in data inversion and complex terrain.(4) In reanalysis data,besides the rare observational records employed for data assimilation,model bias in physical processes induces visible errors in producing the diabatic heating fields.展开更多
文摘Despite that several studies have shown that data derived from species lists generated from distribution occurrence records in the Global Biodiversity Information Facility(GBIF)are not appropriate for those ecological and biogeographic studies that require high sampling completeness,because species lists derived from GBIF are generally very incomplete,Suissa et al.(2021)generated fern species lists based on data with GBIF for 100 km×100 km grid cells across the world,and used the data to determine fern diversity hotspots and species richness-climate relationships.We conduct an evaluation on the completeness of fern species lists derived from GBIF at the grid-cell scale and at a larger spatial scale,and determine whether fern data derived from GBIF are appropriate for studies on the relations of species composition and richness with climatic variables.We show that species sampling completeness of GBIF is low(<40%)for most of the grid cells examined,and such low sampling completeness can substantially bias the investigation of geographic and ecological patterns of species diversity and the identification of diversity hotspots.We conclude that fern species lists derived from GBIF are generally very incomplete across a wide range of spatial scales,and are not appropriate for studies that require data derived from species lists in high completeness.We present a map showing global patterns of fern species diversity based on complete or nearly complete regional fern species lists.
文摘This paper reviews literature pertaining to the development of data science as a discipline,current issues with data bias and ethics,and the role that the discipline of information science may play in addressing these concerns.Information science research and researchers have much to offer for data science,owing to their background as transdisciplinary scholars who apply human-centered and social-behavioral perspectives to issues within natural science disciplines.Information science researchers have already contributed to a humanistic approach to data ethics within the literature and an emphasis on data science within information schools all but ensures that this literature will continue to grow in coming decades.This review article serves as a reference for the history,current progress,and potential future directions of data ethics research within the corpus of information science literature.
基金supported by the the National Natural Science Foundation of China (Grants 91337216 and 41175070)and the Open Project of the Key Laboratory of Meteorological Disaster of Ministry of Education (Grant KLME1309)
文摘As a huge,intense,and elevated atmospheric heat source(AHS) approaching the mid-troposphere in spring and summer,the Tibetan Plateau(TP) thermal forcing is perceived as an important factor contributing to the formation and variation of the Asian summer monsoon.Despite numerous studies devoted to determine the strength and change of the thermal forcing of the TP on the basis of various data sources and methods,uncertainties remain in quantitative estimation of the AHS and will persist for the following reasons:(1) Routine meteorological stations cover only limited regions and show remarkable spatial inhomogeneity with most distributed in the central and eastern plateau.Moreover,all of these stations are situated at an altitude below 5000 m.Thus,the large area above that elevation is not included in the data.(2) Direct observations on heat fluxes do not exist at most stations,and the sensible heat flux(SHF) is calculated by the bulk formula,in which the drag coefficient for heat is often treated as an empirical constant without considering atmospheric stability and thermal roughness length.(3) Radiation flux derived by satellite remote sensing shows a large discrepancy in the algorithm in data inversion and complex terrain.(4) In reanalysis data,besides the rare observational records employed for data assimilation,model bias in physical processes induces visible errors in producing the diabatic heating fields.
