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Vascular epiphyte populations with higher leaf nutrient concentrations showed weaker resilience to an extreme drought in a montane cloud forest.

T HuWen-Yao LiuH D WenLiang SongT T ZhangQ ChenS Liu
Published in: Plant biology (Stuttgart, Germany) (2022)
Leaf stoichiometry can characterize plant ecological strategies and correlate with plant responses to climate change. The role of vascular epiphytes in the ecosystem processes of tropical and subtropical forest ecosystems cannot be ignored. Vascular epiphytes are very vulnerable to climate change, however, the relationship between the response of epiphytes to climate change and leaf stoichiometry is not well understood. We present data for 19 vascular epiphyte species that were collected during four consecutive censuses (in 2005, 2010, 2015, and 2020) over 15 years in a subtropical montane cloud forest. We assessed the relationships between the population dynamics and leaf stoichiometry of these vascular epiphytes. Experiencing an extreme drought, 14 of the 19 epiphyte species showed an obvious decrease in the number of individuals, and all species showed negative growth in the number of populations. Subsequently, the total number of individuals gradually recovered, increasing from 7,195 in 2010 to 10,121 in 2015, then to 13,667 in 2020. The increase in the number of vascular epiphyte individuals from 2010 to 2015 was significantly negatively correlated with leaf nitrogen and phosphorus concentration, and was significantly positively correlated with the leaf carbon-nitrogen ratio. Vascular epiphyte populations with higher leaf nutrient concentrations exhibited weaker resilience to the extreme drought, which demonstrated that a resource-conservative strategy was advantageous for the recovery of epiphyte populations. Our findings suggest that ecological stoichiometry can be a useful framework for forecasting the dynamics of vascular epiphyte populations in response to climate change.
Keyphrases
  • climate change
  • human health
  • genetic diversity
  • risk assessment
  • electronic health record
  • artificial intelligence