Abstract

IntroductionLeaf functional traits constitute a crucial component of plant functionality, providing insights into plants’ adaptability to the environment and their regulatory capacity in complex habitats. The response of leaf traits to environmental factors at the community level has garnered significant attention. Nevertheless, an examination of the environmental factors determining the spatial distribution of leaf traits in the karst region of southwest China remains absent.MethodsIn this study, we established a 25 ha plot within a karst forest and collected leaf samples from 144 woody species. We measured 14 leaf traits, including leaf area (LA), leaf thicknes (LT), specific leaf area (SLA), leaf length to width ratio (LW), leaf tissue density (LTD), leaf carbon concentration (LC), leaf nitrogen concentration (LN), and leaf phosphorus concentration (LP), leaf potassium concentration (LK), leaf calcium concentration (LCa), leaf magnesium Concentration (LMg), leaf carbon to nitrogen ratio (C/N), leaf carbon to phosphorus ratio (C/P), and leaf nitrogen to phosphorus ratio (N/P), to investigate the spatial distribution of community-level leaf traits and the response of the leaf trait community-weighted mean (CWM) to topographic, soil, and spatial factors.ResultsResults showed that the CWM of leaf traits display different spatial patterns, first, the highest CWM values for LT, LTD, C/N, and C/P at hilltops, second, the highest CWM values for LA, SLA, LW, LC, LN, LP, and LK at depressions, and third, the highest CWM values for LCa, LMg, and N/P at slopes. The correlation analysis showed that topographic factors were more correlated with leaf trait CWM than soil factors, with elevation and slope being the strongest correlations. RDA analysis showed that topographic factors explained higher percentage of leaf trait CWM than soil factors, with the highest percentage of 19.96% being explained by elevation among topographic factors. Variance Partitioning Analysis showed that the spatial distribution of leaf traits is predominantly influenced by the combined effects of topography and spatial factors (37%-47% explained), followed by purely spatial factors (24%-36% explained).DiscussionThe results could improve our understanding of community functional traits and their influencing factors in the karst region, which will contribute to a deeper understanding of the mechanisms that shape plant communities.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.