13 Sep 2022
13 Sep 2022
Status: this preprint is currently under review for the journal BG.

Revisiting and attributing the global controls on terrestrial ecosystem functions of climate and plant traits at FLUXNET sites with causal networks

Haiyang Shi1,2,4,5, Geping Luo1,2,3,5, Olaf Hellwich6, Alishir Kurban1,2,3,5, Philippe De Maeyer1,2,4,5, and Tim Van de Voorde4,5 Haiyang Shi et al.
  • 1State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
  • 2College of Resources and Environment, University of the Chinese Academy of Sciences, 19 (A) Yuquan Road, Beijing, 100049, China
  • 3Research Centre for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi, China
  • 4Department of Geography, Ghent University, Ghent 9000, Belgium
  • 5Sino-Belgian Joint Laboratory of Geo-Information, Ghent, Belgium
  • 6Department of Computer Vision & Remote Sensing, Technische Universität Berlin, 10587 Berlin, Germany

Abstract. Using statistical methods that do not emphasize the systematic causality to attribute climate and plant traits to control ecosystem function may produce biased perceptions. We revisit this issue using a Bayesian network (BN) capable of quantifying causality. Based on expert knowledge and climate, vegetation, and ecosystem function data from the FLUXNET flux stations, we constructed a BN containing the causal relationship of 'climate-plant trait-ecosystem function'. Based on the sensitivity analysis function of the BN, we attributed the control of climate and plant traits to ecosystem function and compared the results with those based on Random forests and correlation analysis. The main conclusions of this study include: BN can be used for the quantification of causal relationships between complex ecosystems and climatic and environmental systems, and enables the analysis of indirect effects among variables. The control of ecosystem function by climate variables (especially mean temperature and mean vapor pressure deficit) may have been underestimated previously, and the mechanism of indirect effects of climate variables on ecosystem function through plant traits should be emphasized in future studies. Further inclusion of temporal information in BN holds promise for improving the analysis of lagged effects and interactions and feedback effects between variables.

Haiyang Shi et al.

Status: open (until 25 Oct 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Haiyang Shi et al.

Haiyang Shi et al.


Total article views: 184 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
132 47 5 184 1 1
  • HTML: 132
  • PDF: 47
  • XML: 5
  • Total: 184
  • BibTeX: 1
  • EndNote: 1
Views and downloads (calculated since 13 Sep 2022)
Cumulative views and downloads (calculated since 13 Sep 2022)

Viewed (geographical distribution)

Total article views: 173 (including HTML, PDF, and XML) Thereof 173 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 28 Sep 2022
Short summary
In studies of the relationship between ecosystem function and climate and plant traits, previous studies based on data-driven methods such as multiple regression and random forest may be inadequate for the representation of systematic causality due to limitations such as covariance among variables. Based on FLUXNET site data, we used a causal network to revisit the control of climate and vegetation traits on ecosystem function.