Influence of divergent sampling intensity across plant growth forms on estimating elevational richness patterns and their driversOA
Numerous studies have demonstrated that sampling intensity can significantly influence the detection of richness patterns and the assessment of the importance of driving factors.However,existing research has primarily focused on comparing the influence of sampling intensity across different locations or community types,with less attention paid to its influence across growth forms.Through field surveys on Baima Snow Mountain and bootstrap resampling analyses,we quantified the influence of sampling intensity on plant elevational richness patterns across growth forms(trees,shrubs,and herbs).Our results revealed that with increasing sampling intensity,the error in assessing elevational richness patterns decreased rapidly then stabilized for all growth forms.A similar trend was observed in the estimation of climatic drivers.However,significant variations emerged across different growth forms.The suitable sampling intensity was higher for trees and shrubs than for herbaceous plants.Furthermore,estimation errors for tree richness patterns declined significantly faster with increasing sampling intensity than those for shrubs and herbs.Similarly,the relationship between sampling intensity and error in estimating richness-climate relationships showed significant differences across growth forms.However,these differences were subject to the climate drivers selected.These findings demonstrate that growth-form differences must be considered in elevation-richness surveys.However,our meta-analysis revealed that no current study accounted for this factor in their protocols.Our findings provide empirical evidence for developing growth form-specific sampling protocols,offering practical solutions to improve the accuracy of mountain richness studies and enhance cross-study comparability in elevational gradient research.
Hongrui Ling;Jianqiang Yang;Yannan He;Pengwan Zhang;Jiangci nongbu;Sina laoding;Zhenyu Fan;Aoxiang Chang;Hang Sun;Shuang Zhang;Zihan Jiang
State Key Laboratory of Plant Diversity and Specialty Crops&Yunnan Key Laboratory of Plant Diversity and Biogeography,Kunming Institute of Botany,Chinese Academy of Sciences,Kunming 650201,China Plant Cell Laboratory,College of Life Sciences,Yunnan Normal University,Kunming 650000,ChinaQuzonggong Management Office of Deqin Branch of Yunnan Baima Snow Mountain National Nature Reserve Management and Protection Bureau,Deqin 674499,ChinaQuzonggong Management Office of Deqin Branch of Yunnan Baima Snow Mountain National Nature Reserve Management and Protection Bureau,Deqin 674499,ChinaQuzonggong Management Office of Deqin Branch of Yunnan Baima Snow Mountain National Nature Reserve Management and Protection Bureau,Deqin 674499,ChinaQuzonggong Management Office of Deqin Branch of Yunnan Baima Snow Mountain National Nature Reserve Management and Protection Bureau,Deqin 674499,ChinaQuzonggong Management Office of Deqin Branch of Yunnan Baima Snow Mountain National Nature Reserve Management and Protection Bureau,Deqin 674499,ChinaSchool of Life Science and Aericulture Forestry,Oiqihar University,Oiaihar 161006,ChinaSchool of Life Science and Aericulture Forestry,Oiqihar University,Oiaihar 161006,ChinaState Key Laboratory of Plant Diversity and Specialty Crops&Yunnan Key Laboratory of Plant Diversity and Biogeography,Kunming Institute of Botany,Chinese Academy of Sciences,Kunming 650201,ChinaState Key Laboratory of Urban and Regional Ecology,Research Center for Eco-Environmental Sciences,Chinese Academy of Sciences,Beijing 100085,ChinaState Key Laboratory of Plant Diversity and Specialty Crops&Yunnan Key Laboratory of Plant Diversity and Biogeography,Kunming Institute of Botany,Chinese Academy of Sciences,Kunming 650201,China
农业科技
Sampling intensityMulti-growth formsBootstrap samplingBaima Snow MountainRichness-climate relationships
《Plant Diversity》 2026 (2)
P.330-339,10
funded by Chinese Academy of Sciences Hundred Talents Program,Category BNational Postdoctoral ProgramsYunnan Provincial General Project Fund(202401CF070060)the Key R&D Program of Yunnan Province(202403AC100028)National Natural Science Foundation Regional Project(32360395)。
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