Literature DB >> 24128847

An imperative need for global change research in tropical forests.

Xuhui Zhou1, Yuling Fu, Lingyan Zhou, Bo Li, Yiqi Luo.   

Abstract

Tropical forests play a crucial role in regulating regional and global climate dynamics, and model projections suggest that rapid climate change may result in forest dieback or savannization. However, these predictions are largely based on results from leaf-level studies. How tropical forests respond and feedback to climate change is largely unknown at the ecosystem level. Several complementary approaches have been used to evaluate the effects of climate change on tropical forests, but the results are conflicting, largely due to confounding effects of multiple factors. Although altered precipitation and nitrogen deposition experiments have been conducted in tropical forests, large-scale warming and elevated carbon dioxide (CO2) manipulations are completely lacking, leaving many hypotheses and model predictions untested. Ecosystem-scale experiments to manipulate temperature and CO2 concentration individually or in combination are thus urgently needed to examine their main and interactive effects on tropical forests. Such experiments will provide indispensable data and help gain essential knowledge on biogeochemical, hydrological and biophysical responses and feedbacks of tropical forests to climate change. These datasets can also inform regional and global models for predicting future states of tropical forests and climate systems. The success of such large-scale experiments in natural tropical forests will require an international framework to coordinate collaboration so as to meet the challenges in cost, technological infrastructure and scientific endeavor.

Entities:  

Keywords:  carbon; climate change; elevated CO2; energy; tropical forests; warming; water

Mesh:

Year:  2013        PMID: 24128847     DOI: 10.1093/treephys/tpt064

Source DB:  PubMed          Journal:  Tree Physiol        ISSN: 0829-318X            Impact factor:   4.196


  3 in total

1.  Assessing scale-dependent effects on Forest biomass productivity based on machine learning.

Authors:  Jingyuan He; Chunyu Fan; Yan Geng; Chunyu Zhang; Xiuhai Zhao; Klaus von Gadow
Journal:  Ecol Evol       Date:  2022-07-13       Impact factor: 3.167

2.  What have we learned from global change manipulative experiments in China? A meta-analysis.

Authors:  Zheng Fu; Shuli Niu; Jeffrey S Dukes
Journal:  Sci Rep       Date:  2015-07-24       Impact factor: 4.379

3.  Large sensitivity in land carbon storage due to geographical and temporal variation in the thermal response of photosynthetic capacity.

Authors:  Lina M Mercado; Belinda E Medlyn; Chris Huntingford; Rebecca J Oliver; Douglas B Clark; Stephen Sitch; Przemyslaw Zelazowski; Jens Kattge; Anna B Harper; Peter M Cox
Journal:  New Phytol       Date:  2018-04-10       Impact factor: 10.151

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.