In the context of global change, a better understanding of the dynamics of wood degradation, and how they relate to tree attributes and climatic conditions, is necessary to improve broad-scale assessments of the contributions of deadwood to various ecological processes and ultimately for the development of adaptive post-disturbance management strategies.
This post is a summary of the scientific article "Broad-scale wood dynamics in the face of climate change: a meta-analysis" by Catherine Chagnon, Guillaume Moreau, Christine-Bombardier-Cauffope, Julie Barrette, Filip Havreljuk and Alexis Achim, published in GCB Bioenergy, Volume 14, Issue 9, p 941-958 (https://onlinelibrary.wiley.com/doi/10.1111/gcbb.12951), and has been approved by the corresponding author.
A harmonized classification system for visual criteria of deadwood of both standing dead and downed wood debris
A harmonized three-class system was created to describe the state of decomposition of both downed and standing woody debris (Fig 1) to simplify data collected within the meta-analysis. This classification is then useful for its use to facilitate comparison with future studies.
Both climatic conditions and tree-level variables are important indicators of time since death (TSD) of woody debris
Using climatic conditions and tree-level variables obtained using a meta-analysis, linear regression models showed that TSD was best explained using interactions between decay class and the following four variables:
Maximum summer temperature; higher temperatures decreased TSD
Total annual precipitation; greater precipitation increased TSD
Wood density; greater wood density increased TSD
Tree phylogeny; TSD was 4.4 years higher in softwoods compared to hardwoods
The above four variables accounted for 84% of the variance between observations, which were classified into three main clusters using a PCA-analysis. A decay-class transition rate model was included to account for mean residence time of 75% of the trees being 'out of the system' and classified beyond DC #3 (Fig. 2).
Projected warming is likely to accelerate wood decomposition and decrease residence time in the decay stages
Using baseline climate data across Europe, mean TSD of deadwood in the first decay class was, on average, ~10 years. Lower values were observed around the Mediterranean and higher values in the Alps, Scotland and southwestern coast of Norway (Fig. 3). Future climate projections show that mean TSD could decrease from 10 years to 6 and 4 years by 2100, according to SSP2-4.5 and SSP5-8.5 scenarios, respectively (Fig. 3).
A shorter residence time will change deadwood dynamics, thereby impacting diversity and salvage logging practices
Saproxylic biodiversity may be altered due a reduced availability of deadwood of different decomposition stages over time, reducing the amount of available of habitat. This is likely to worsen with rising temperatures. Shorter residence times of deadwood suggests a reduced "shelf life" of dead trees that are used as value-added products. This is especially true for hardwoods in warmer regions where salvage harvesting needs to occur in a shorter period after a disturbance. Climate change and faster decaying wood is likely to affect the carbon footprint, sequestration rate, timing and quantity emissions related to the decomposition of dead trees.
Methodology (expand to read)
A literature review was performed for articles documenting time since death (TSD) and coarse woody debris (CWD). Based on five criteria, studies were compiled into a meta-analysis and the impact of 1) tree-level variables and 2) site-level climatic variables on TSD was tested. An integrated decay-class system was constructed to describe decomposition of both downed and standing woody debris and used to compile and classify TSD from all studies. A mixed-effect meta-regression was used to test the influence of variables on TSD and a cluster analysis was used to summarize woody debris dynamics. A stage-based matrix was used to describe each cluster's deadwood stages distribution over time. Lastly, projected changes in mean TSD were calculated using two future climate scenarios.
A copy of this blog post is available as an Extension Note in PDF format, available in English and French.
Corresponding author of article: Catherine Chagnon, M.Sc.
Summary and design by Amy Wotherspoon, PhD.