Abstract
Many different factors,such as species traits,socio-economic factors,geographical and environmental factors,can lead to specimen collection preference.This study aims to determine whether grassland specimen collection in China is preferred by species traits(i.e.,plant height,flowering and fruiting period),environmental range(i.e.,the temperature and precipitation range)and geographical range(i.e.,distribution range and altitudinal range).Ordinary least squares models and phylogenetic generalized linear mixed models were used to analyze the relationships between specimen number and the explanatory variables.Random Forest models were then used to find the most parsimonious multivariate model.The results showed that interannual variation in specimen number between 1900 and 2020 was considerable.Specimen number of these species in southeast China was notably lower than that in northwest China.Environmental range and geographical range of species had significant positive cor-relations with specimen number.In addition,there were relatively weak but significant associations between specimen number and species trait(i.e.,plant height and flowering and fruiting period).Random Forest models indicated that distribution range was the most important variable,followed by flowering and fruiting period,and altitudinal range.These findings suggest that future floristic surveys should pay more attention to species with small geographical range,narrow environmental range,short plant height,and short flowering and fruiting period.The correction of specimen collection preference will also make the results of species distribution model,species evolution and other works based on specimen data more accurate.
基金项目
Natural Science Foundation of Inner Mongolia,China(2023JQ01)
National Key R&D Program of China(2019YFA0607103)
Central Government Guides Local Science and Technology Development Fund Projects(2022ZY0224)
Open Project Program of Ministry of Education Key Laboratory of Ecology and Resources Use of the Mongolian Plateau,Hohhot,In(KF2023003)
Major Science and Technology Project of Inner Mongolia Autonomous Region(2021ZD0011)
国家科技期刊平台
NSTL
万方数据