Plant community traits can explain variation in productivity of selective logging forests after different restoration times
The emerging concept of plant community traits offers a promising tool for explaining the variations in forest productivity. We measured the leaf thickness (LT), leaf area (LA), specific leaf area (SLA), and leaf dry matter content (LDMC) of 234 plant species from seven adjacent Korean pine and broa...
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| Autores principales: | , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/50b7429290cd42ebbf841274bc387459 |
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| Sumario: | The emerging concept of plant community traits offers a promising tool for explaining the variations in forest productivity. We measured the leaf thickness (LT), leaf area (LA), specific leaf area (SLA), and leaf dry matter content (LDMC) of 234 plant species from seven adjacent Korean pine and broad-leaved mixed forests in Northeast China, which varied in restoration time after selective logging (6, 14, 25, 36, 45, 55, and 100 years). Four leaf traits varied significantly at the species, plant functional group, and community scales. At the community level, LA, SLA, and LDMC followed a significant quadratic trend along the chronological sequence of restoration after selective logging, whereas LT showed no significant variation with time. Interestingly, plant community traits (LT, LA, and SLA) were significantly positively correlated with aboveground net primary productivity (ANPP). Furthermore, plant community traits, restoration time, species diversity, and soil nutrients could jointly explain 78% of the ANPP variation. These findings highlight that the variation in community traits of leaves may play an important role in determining the spatial variation of ANPP in temperate broadleaf-conifer mixed forests. These findings further demonstrate the close linkages between plant community traits and productivity and offer a theoretical basis for incorporating these community traits into future ecological models. |
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