1. The local climate in forest understories can deviate substantially from ambient conditions. Moreover, forest microclimates are often characterized by cyclic changes driven by management activities such as clear-cutting and subsequent planting. To understand how and why understory plant communities change, both ambient climate change and temporal variation in forest structure has to be considered. 2. We used inventories from 11436 productive forest sites in Sweden repeated every 10th year 1993 - 2017 to examine how variation in forest structure influences changes in the average value of minimum and maximum temperature preferences of all species in a community, i.e. community temperature indices (CTI). We then evaluated to what extent these changes were driven by local extinctions and colonizations, respectively, and to what extent the difference in CTI value between two inventories were related to changes in forest density and in macroclimate. Lastly, we tested whether effects on CTI change by these two drivers were modified by topography, soil moisture and tree species composition. 3. CTI values of the understory plant communities increased after clear-cutting, and decreased during periods when the forest grew denser. During the period immediately after clear-cutting, changes were predominately driven by colonizations of species with a preference for higher temperatures. During the forest regeneration phase, both colonization by species preferring lower temperatures and local extinctions of species preferring higher temperatures increased. The change in understory CTI over 10-year periods was explained more by changes in forest density, than by changes in macroclimate. Soil moisture, topography and forest tree species composition modified to some extent the effects of changes in forest density and in macroclimate on understory CTI values. 4. Synthesis. Via stand manipulation, forest management impacts the effects of regional climate on understory plant communities. This implies that forest management by creating denser stands locally even can counterbalance the effects of regional changes in climate by creating denser stands locally. Consequently, interpretations of changes in the mean temperature preference of species in forest understory communities should take forest management regimes into account. 

The data consist of 11436 plots inventoried for the National Inventory of Forests in Sweden between 1993-2017. The dataset has plot ID, year of inventory, basal area, basal area difference between inventories, proportion of spruce and pine, region, elevation, soil moisture index, relative elevation, northerness of slope, macroclimate temperature change (10 years), Community Temperature Indices of maximum and minimum temperatures of the understory communities (CTImax and CTImin).

CTI values were calculated from presence/absence data of understory plants that were inventoried in a 100 m2 circular plot. Forest structures such as basal area and forest tree composition were measured from a larger circular plot of 300 m2 with the same centre. CTI were calculated as an average value of species-specific temperature preferences for all species present in the inventory for maximum and minimum temperatures, respectively.

Elevation, Slope and Aspect were retrieved from a 50 meter resolution Digital Elevation Model of Sweden (the Swedish mapping, cadastral and land registration authority, www.lantmateriet.se).

Relative Elevation was calculated from the Digital Elevation Model. We calculated relative elevation as the difference between the elevation of the plot and the minimum elevation in a 500 meter radius. We log-transformed relative elevation, as cold air pooling has a negative logarithmic relationship with relative elevation.

Soil moisture index was extracted a 10 meter resolution map from the Swedish Environmental Protection Agency (http://www.naturvardsverket.se/Sa-mar-miljon/Kartor/Nationella-Marktackedata-NMD/).

Macroclimate temperatures were extracted from TerraClimate (Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A., & Hegewisch, K. C. (2018). TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015. Scientific Data, 5, 1–12. https://doi.org/10.1038/sdata.2017.191)

References for NFI data collection:

Fridman, J. (2016). The Swedish National Forest Inventory. Swedish University of Agricultural Sciences. https://www.slu.se/en/Collaborative-Centres-and-Projects/the-swedish-national-forest-inventory/about-us/how-we-work/

Fridman, J., Holm, S., Nilsson, M., Nilsson, P., Ringvall, A. H., & Ståhl, G. (2014). Adapting National Forest Inventories to changing requirements - The case of the Swedish National Forest Inventory at the turn of the 20th century. Silva Fennica, 48(3), 1–29. https://doi.org/10.14214/sf.1095