Journal cover Journal topic
Biogeosciences An interactive open-access journal of the European Geosciences Union
Journal topic
Discussion papers
https://doi.org/10.5194/bg-2019-403
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-2019-403
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 15 Oct 2019

Submitted as: research article | 15 Oct 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Biogeosciences (BG).

Ecosystem physio-phenology revealed using circular statistics

Daniel E. Pabon-Moreno1, Talie Musavi1, Mirco Migliavacca1, Markus Reichstein1,2, Christine Römermann2,3, and Miguel D. Mahecha1,2 Daniel E. Pabon-Moreno et al.
  • 1Max Planck Institute for Biogeochemistry, Hans–Knoell–Str. 10, 07745 Jena, Germany
  • 2German Centre for Integrative Biodiversity Research (iDiv), Deutscher Platz 5e, 04103 Leipzig, Germany
  • 3Friedrich Schiller University, Institute of Ecology and Evolution, Philosophenweg 16, 07743 Jena, Germany

Abstract. Quantifying responses of vegetation phenology to climate variability is a key prerequisite to predict shifts in how ecosystem dynamics due to climate change. So far, many studies have focused on responses of classical phenological events (e.g. budburst or flowering) to climatic variability for individual species. Comparatively little is known on physio-phenological events such as the timing of the maximum gross primary production (DOYGPPmax). However, understanding this type of physio-phenological phenomena is an essential element in predicting the response of the terrestrial carbon cycle to climate variability. In this study, we aim to understand how DOYGPPmax depends on climate drivers across 52 eddy-covariance (EC) sites in the FLUXNET network for different regions of the world. Most phenological studies rely on linear methods that cannot be generalized across both hemispheres and therefore do not allow for deriving general rules that can be applied for future predictions. Here we explore a new class of circular-linear (here called circular) regression approach that may show a path ahead. Circular regression allows relating circular variables (in our case phenological events) to linear predictor variables (e.g. climate conditions). As a proof of concept, we compare the performance of linear and circular regression to recover original coefficients of a predefined circular model on artificial and EC data. We then quantify the sensitivity of DOYGPPmax to air temperature, short-wave incoming radiation, precipitation and vapor pressure deficit using circular regressions. Finally, we evaluate the predictive power of the regression models for different vegetation types. Our results show that the DOYGPPmax of each FLUXNET site has a unique signature of climatic sensitivities. Overall radiation and temperature are the most relevant controlling factors of DOYGPPmax across sites. The circular approach gives us new insights at the site level. In a Mediterranean shrub-land, for instance, we find that the two growing seasons are controlled by different climatic factors. Although the sensitivity of the DOYGPPmax to the climate drivers is very site specific, it is possible to extrapolate the circular regression model across vegetation types. From a methodological point of view, our results reveal that circular regression is a robust alternative to conventional phenological analytic frameworks. In particular global analyses can benefit, where phase shifts play a role or double peaked growing seasons may occur.

Daniel E. Pabon-Moreno et al.
Interactive discussion
Status: open (until 06 Dec 2019)
Status: open (until 06 Dec 2019)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement
Daniel E. Pabon-Moreno et al.
Daniel E. Pabon-Moreno et al.
Viewed  
Total article views: 341 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
258 82 1 341 18 0 7
  • HTML: 258
  • PDF: 82
  • XML: 1
  • Total: 341
  • Supplement: 18
  • BibTeX: 0
  • EndNote: 7
Views and downloads (calculated since 15 Oct 2019)
Cumulative views and downloads (calculated since 15 Oct 2019)
Viewed (geographical distribution)  
Total article views: 265 (including HTML, PDF, and XML) Thereof 264 with geography defined and 1 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited  
Saved  
No saved metrics found.
Discussed  
No discussed metrics found.
Latest update: 22 Nov 2019
Publications Copernicus
Download
Citation