File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

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

TitleSpatio-temporal divergence in the responses of Finland's boreal forests to climate variables
Authors
KeywordsBoreal forests
Climate variables
Monthly difference
Partial least squares (PLS) regression
Plant phenology index (PPI)
Issue Date2020
Citation
International Journal of Applied Earth Observation and Geoinformation, 2020, v. 92, article no. 102186 How to Cite?
AbstractSpring 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.
Persistent Identifierhttp://hdl.handle.net/10722/349504
ISSN
2023 Impact Factor: 7.6
2023 SCImago Journal Rankings: 2.108

 

DC FieldValueLanguage
dc.contributor.authorHou, Meiting-
dc.contributor.authorVenäläinen, Ari K.-
dc.contributor.authorWang, Linping-
dc.contributor.authorPirinen, Pentti-
dc.contributor.authorGao, Yao-
dc.contributor.authorJin, Shaofei-
dc.contributor.authorZhu, Yuxiang-
dc.contributor.authorQin, Fuying-
dc.contributor.authorHu, Yonghong-
dc.date.accessioned2024-10-17T06:58:58Z-
dc.date.available2024-10-17T06:58:58Z-
dc.date.issued2020-
dc.identifier.citationInternational Journal of Applied Earth Observation and Geoinformation, 2020, v. 92, article no. 102186-
dc.identifier.issn1569-8432-
dc.identifier.urihttp://hdl.handle.net/10722/349504-
dc.description.abstractSpring 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.-
dc.languageeng-
dc.relation.ispartofInternational Journal of Applied Earth Observation and Geoinformation-
dc.subjectBoreal forests-
dc.subjectClimate variables-
dc.subjectMonthly difference-
dc.subjectPartial least squares (PLS) regression-
dc.subjectPlant phenology index (PPI)-
dc.titleSpatio-temporal divergence in the responses of Finland's boreal forests to climate variables-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.jag.2020.102186-
dc.identifier.scopuseid_2-s2.0-85098289574-
dc.identifier.volume92-
dc.identifier.spagearticle no. 102186-
dc.identifier.epagearticle no. 102186-
dc.identifier.eissn1872-826X-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats