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Data from: Drivers of snag fall rates in Fennoscandian boreal forests

Cite this dataset

Aakala, Tuomas; Storaunet, Ken Olaf; Jonsson, Bengt Gunnar; Korhonen, Kari T. (2024). Data from: Drivers of snag fall rates in Fennoscandian boreal forests [Dataset]. Dryad. https://doi.org/10.5061/dryad.37pvmcvtt

Abstract

Persistence of standing dead trees (snags) is an important determinant for their role for biodiversity and dead wood associated carbon fluxes. How fast snags fall varies widely among species and regions and is further influenced by a variety of stand- and tree-level factors. However, our understanding of this variation is fragmentary at best, partly due to lack of empirical data. Here, we took advantage of the accruing time series of snag observations in the Finnish, Norwegian, and Swedish National Forest Inventories that have been followed in these programs since the mid-1990s. We first harmonized observations from slightly different inventory protocols and then, using this harmonized dataset of ca. 43 000 observations that had a consistent 5-year census interval, we modeled the probability of snags of the main boreal tree species Pinus sylvestris, Picea abies, and Betula spp. falling, as a function of tree- and stand-level variables, using Bayesian logistic regression modeling. The models were moderately good at predicting snags remaining standing or falling, with a correct classification rate ranging from 68% to 75% among species. In general, snag persistence increased with tree size and climatic wetness, and decreased with temperature sum, advancing stage of decay, site productivity, and disturbance intensity (mainly harvesting).

Synthesis and applications. The effect of harvesting demonstrates that an efficient avenue to increase the amount of snags in managed forests is protecting them during silvicultural operations. In the warmer future, negative relationship between snag persistence and temperature suggests decreasing the time snags remain standing and hence decreasing habitat availability for associated species. As decomposition rates generally increase after fall, decreasing snag persistence also implies substantially faster release of carbon from dead wood.

README: Data from: Drivers of snag fall rates in Fennoscandian boreal forests

https://doi.org/10.5061/dryad.37pvmcvtt

Data used for fitting the models in Aakala et al. (2024). Drivers of snag fall rates in Fennoscandian boreal forests to be published in Journal of Applied Ecology.

Description of the data and file structure

The tab-separated text file contains variables used in modeling the probability of standing dead trees to remain standing over the 5-year remeasurement interval. The variables (with full descriptions in the main article):

survival = binary response variable, whether the standing dead tree survived as standing (1), or fell (0).

dbh = Diameter at 1.3 m height, in cm.

gdd0 = Growing degree days, with a threshold value of 0 °C. Originally obtained from the Envirem data set (Title, P.O. and Bemmels, J.B., 2018. ENVIREM: an expanded set of bioclimatic and topographic variables increases flexibility and improves performance of ecological niche modeling. Ecography 41:291-307).

moisture_index = Climatic moisture index, originally obtained from the Envirem data set (Title and Bemmels 2018). The index is described in: Willmott, C. & Feddema, J. (1992). A More Rational Climatic Moisture Index. The Professional Geographer, 44, 84-88.

basal_area = Stand basal area (m2/ha).

decay_class = Decay class.

site_type = Site type.

disturbance_intensity = Categorical variable describing the intensity of disturbance (natural or logging).

species = Tree species identity, one of psy (Pinus sylvestris), pab (Picea abies), or bet (Betula spp.)

plot_id = Plot identification.

tree_id = Tree identification.

Funding

Kone Foundation