Monthly microclimate models in a managed boreal forest landscape

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http://hdl.handle.net/10138/233778

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Greiser , C , Meineri , E , Luoto , M , Ehrlen , J & Hylander , K 2018 , ' Monthly microclimate models in a managed boreal forest landscape ' , Agricultural and Forest Meteorology , vol. 250-251 , pp. 147-158 . https://doi.org/10.1016/j.agrformet.2017.12.252

Title: Monthly microclimate models in a managed boreal forest landscape
Author: Greiser, Caroline; Meineri, Eric; Luoto, Miska; Ehrlen, Johan; Hylander, Kristoffer
Contributor organization: Department of Geosciences and Geography
BioGeoClimate Modelling Lab
Helsinki Institute of Sustainability Science (HELSUS)
Date: 2018-03-15
Language: eng
Number of pages: 12
Belongs to series: Agricultural and Forest Meteorology
ISSN: 0168-1923
DOI: https://doi.org/10.1016/j.agrformet.2017.12.252
URI: http://hdl.handle.net/10138/233778
Abstract: The majority of microclimate studies have been done in topographically complex landscapes to quantify and predict how near-ground temperatures vary as a function of terrain properties. However, in forests understory temperatures can be strongly influenced also by vegetation. We quantified the relative influence of vegetation features and physiography (topography and moisture-related variables) on understory temperatures in managed boreal forests in central Sweden. We used a multivariate regression approach to relate near-ground temperature of 203 loggers over the snow-free seasons in an area of ∼16,000 km2 to remotely sensed and on-site measured variables of forest structure and physiography. We produced climate grids of monthly minimum and maximum temperatures at 25m resolution by using only remotely sensed and mapped predictors. The quality and predictions of the models containing only remotely sensed predictors (MAP models) were compared with the models containing also on-site measured predictors (OS models). Our data suggest that during the warm season, where landscape microclimate variability is largest, canopy cover and basal area were the most important microclimatic drivers for both minimum and maximum temperatures, while physiographic drivers (mainly elevation) dominated maximum temperatures during autumn and early winter. The MAP models were able to reproduce findings from the OS models but tended to underestimate high and overestimate low temperatures. Including important microclimatic drivers, particularly soil moisture, that are yet lacking in a mapped form should improve the microclimate maps. Because of the dynamic nature of managed forests, continuous updates of mapped forest structure parameters are needed to accurately predict temperatures. Our results suggest that forest management (e.g. stand size, structure and composition) and conservation may play a key role in amplifying or impeding the effects of climate-forcing factors on near-ground temperature and may locally modify the impact of global warming.
Subject: 1172 Environmental sciences
Canopy cover
Cold air pooling
Climate change
Topoclimate
Climate variability
Forest management
SURFACE AIR TEMPERATURES
DOUGLAS-FIR FOREST
CLIMATE-CHANGE
SPECIES DISTRIBUTIONS
ENVIRONMENTAL-FACTORS
GLOBAL CHANGE
FINE-GRAIN
MICROREFUGIA
BIODIVERSITY
IMPACTS
Peer reviewed: Yes
Rights: cc_by_nc_nd
Usage restriction: openAccess
Self-archived version: publishedVersion


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