Estimating and analyzing savannah phenology with a lagged time series model
Boke-Olén, Niklas LU ; Lehsten, Veiko LU ; Ardö, Jonas LU
; Beringer, Jason
; Eklundh, Lars
LU
; Holst, Thomas
LU
; Veenendaal, Elmar
and Tagesson, Torbern
LU
(2016)
In PLoS ONE
11(4).
- Abstract
Savannah regions are predicted to undergo changes in precipitation patterns according to current climate change projections. This change will affect leaf phenology, which controls net primary productivity. It is of importance to study this since savannahs play an important role in the global carbon cycle due to their areal coverage and can have an effect on the food security in regions that depend on subsistence farming. In this study we investigate how soil moisture, mean annual precipitation, and day length control savannah phenology by developing a lagged time series model. The model uses climate data for 15 flux tower sites across four continents, and normalized difference vegetation index from satellite to optimize a statistical... (More)
Savannah regions are predicted to undergo changes in precipitation patterns according to current climate change projections. This change will affect leaf phenology, which controls net primary productivity. It is of importance to study this since savannahs play an important role in the global carbon cycle due to their areal coverage and can have an effect on the food security in regions that depend on subsistence farming. In this study we investigate how soil moisture, mean annual precipitation, and day length control savannah phenology by developing a lagged time series model. The model uses climate data for 15 flux tower sites across four continents, and normalized difference vegetation index from satellite to optimize a statistical phenological model. We show that all three variables can be used to estimate savannah phenology on a global scale. However, it was not possible to create a simplified savannah model that works equally well for all sites on the global scale without inclusion of more site specific parameters. The simplified model showed no bias towards tree cover or between continents and resulted in a cross-validated r2 of 0.6 and root mean squared error of 0.1. We therefore expect similar average results when applying the model to other savannah areas and further expect that it could be used to estimate the productivity of savannah regions.
(Less)
- author
- Boke-Olén, Niklas
LU
; Lehsten, Veiko
LU
; Ardö, Jonas
LU
; Beringer, Jason
; Eklundh, Lars
LU
; Holst, Thomas
LU
; Veenendaal, Elmar
and Tagesson, Torbern
LU
- organization
- publishing date
- 2016-04-01
- type
- Contribution to journal
- publication status
- published
- subject
- in
- PLoS ONE
- volume
- 11
- issue
- 4
- article number
- e0154615
- publisher
- Public Library of Science (PLoS)
- external identifiers
-
- scopus:84967239992
- wos:000375212600050
- pmid:27128678
- ISSN
- 1932-6203
- DOI
- 10.1371/journal.pone.0154615
- project
- Global Savannah Phenology: Integrating Earth Observation, Ecosystem Modeling, and PhenoCams
- language
- English
- LU publication?
- yes
- id
- b4a9221a-850e-4f01-8769-80b6d6465541
- date added to LUP
- 2016-05-25 09:06:41
- date last changed
- 2024-05-31 07:54:46
@article{b4a9221a-850e-4f01-8769-80b6d6465541,
abstract = {{<p>Savannah regions are predicted to undergo changes in precipitation patterns according to current climate change projections. This change will affect leaf phenology, which controls net primary productivity. It is of importance to study this since savannahs play an important role in the global carbon cycle due to their areal coverage and can have an effect on the food security in regions that depend on subsistence farming. In this study we investigate how soil moisture, mean annual precipitation, and day length control savannah phenology by developing a lagged time series model. The model uses climate data for 15 flux tower sites across four continents, and normalized difference vegetation index from satellite to optimize a statistical phenological model. We show that all three variables can be used to estimate savannah phenology on a global scale. However, it was not possible to create a simplified savannah model that works equally well for all sites on the global scale without inclusion of more site specific parameters. The simplified model showed no bias towards tree cover or between continents and resulted in a cross-validated r<sup>2</sup> of 0.6 and root mean squared error of 0.1. We therefore expect similar average results when applying the model to other savannah areas and further expect that it could be used to estimate the productivity of savannah regions.</p>}},
author = {{Boke-Olén, Niklas and Lehsten, Veiko and Ardö, Jonas and Beringer, Jason and Eklundh, Lars and Holst, Thomas and Veenendaal, Elmar and Tagesson, Torbern}},
issn = {{1932-6203}},
language = {{eng}},
month = {{04}},
number = {{4}},
publisher = {{Public Library of Science (PLoS)}},
series = {{PLoS ONE}},
title = {{Estimating and analyzing savannah phenology with a lagged time series model}},
url = {{http://dx.doi.org/10.1371/journal.pone.0154615}},
doi = {{10.1371/journal.pone.0154615}},
volume = {{11}},
year = {{2016}},
}