Spatio-temporal divergence in the responses of Finland's boreal forests to climate variables

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http://hdl.handle.net/10138/318555

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Hou , M , Venalainen , A K , Wang , L , Pirinen , P , Gao , Y , Jin , S , Zhu , Y , Qin , F & Hu , Y 2020 , ' Spatio-temporal divergence in the responses of Finland's boreal forests to climate variables ' , International Journal of Applied Earth Observation and Geoinformation , vol. 92 , 102186 . https://doi.org/10.1016/j.jag.2020.102186

Title: Spatio-temporal divergence in the responses of Finland's boreal forests to climate variables
Author: Hou, Meiting; Venalainen, Ari K.; Wang, Linping; Pirinen, Pentti; Gao, Yao; Jin, Shaofei; Zhu, Yuxiang; Qin, Fuying; Hu, Yonghong
Contributor: University of Helsinki, Department of Agricultural Sciences
University of Helsinki, Helsinki Institute of Sustainability Science (profit unit at BY-TDK)
Date: 2020-10
Language: eng
Number of pages: 9
Belongs to series: International Journal of Applied Earth Observation and Geoinformation
ISSN: 1569-8432
URI: http://hdl.handle.net/10138/318555
Abstract: Spring greening in boreal forest ecosystems has been widely linked to increasing temperature, but few studies have attempted to unravel the relative effects of climate variables such as maximum temperature (TMX), minimum temperature (TMN), mean temperature (TMP), precipitation (PRE) and radiation (RAD) on vegetation growth at different stages of growing season. However, clarifying these effects is fundamental to better understand the relationship between vegetation and climate change. This study investigated spatio-temporal divergence in the responses of Finland's boreal forests to climate variables using the plant phenology index (PPI) calculated based on the latest Collection V006 MODIS BRDF-corrected surface reflectance products (MCD43C4) from 2002 to 2018, and identified the dominant climate variables controlling vegetation change during the growing season (May-September) on a monthly basis. Partial least squares (PLS) regression was used to quantify the response of PPI to climate variables and distinguish the separate impacts of different variables. The study results show the dominant effects of temperature on the PPI in May and June, with TMX, TMN and TMP being the most important explanatory variables for the variation of PPI depending on the location, respectively. Meanwhile, drought had an unexpectedly positive impact on vegetation in few areas. More than 50 % of the variation of PPI could be explained by climate variables for 68.5 % of the entire forest area in May and 87.7 % in June, respectively. During July to September, the PPI variance explained by climate and corresponding spatial extent rapidly decreased. Nevertheless, the RAD was found be the most important explanatory variable to July PPI in some areas. In contrast, the PPI in August and September was insensitive to climate in almost all of the regions studied. Our study gives useful insights on quantifying and identifying the relative importance of climate variables to boreal forest, which can be used to predict the possible response of forest under future warming.
Subject: Monthly difference
Plant phenology index (PPI)
Partial least squares (PLS) regression
Boreal forests
Climate variables
PARTIAL LEAST-SQUARES
VEGETATION GROWTH
NORTH-AMERICA
CONTRASTING RESPONSE
CANOPY REFLECTANCE
PLANT PHENOLOGY
PRODUCTIVITY
TEMPERATURE
DROUGHT
MODIS
11831 Plant biology
4112 Forestry
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