Forest Productivity Decline Caused by Successional Paludification of Boreal Soils

Abstract

Long-term forest productivity decline in boreal forests has been extensively studied in the last decades, yet its causes are still unclear. Soil conditions associated with soil organic matter accumulation are thought to be responsible for site productivity decline. The objectives of this study were to determine if paludification of boreal soils resulted in reduced forest productivity, and to identify changes in the physical and chemical properties of soils associated with reduction in productivity. We used a chronosequence of 23 black spruce stands ranging in postfire age from 50 to 2350 years and calculated three different stand productivity indices, including site index. We assessed changes in forest productivity with time using two complementary approaches: (1) by comparing productivity among the chronosequence stands and (2) by comparing the productivity of successive cohorts of trees within the same stands to determine the influence of time independently of other site factors. Charcoal stratigraphy indicates that the forest stands differ in their fire history and originated either from high- or low-severity soil burns. Both chronosequence and cohort approaches demonstrate declines in black spruce productivity of 50-80% with increased paludification, particularly during the first centuries after fire. Paludification alters bryophyte abundance and succession, increases soil moisture, reduces soil temperature and nutrient availability, and alters the vertical distribution of roots. Low-severity soil burns significantly accelerate rates of paludification and productivity decline compared with high-severity fires and ultimately reduce nutrient content in black spruce needles. The two combined approaches indicate that paludification can be driven by forest succession only, independently of site factors such as position on slope. This successional paludification contrasts with edaphic paludification, where topography and drainage primarily control the extent and rate of paludification. At the landscape scale, the fire regime (frequency and severity) controls paludification and forest productivity through its effect on soil organic layers. Implications for global carbon budgets and sustainable forestry are discussed.

Influence of Fuel Load Dynamics on Carbon Emission by Wildfires in the Clay Belt Boreal Landscape

“…The poor drainage conditions induced by the presence of an impermeable clay substrate, flat topography, historical low fire activity, and cold climate facilitated the accumulation of thick layers of organic soil, a process often described as paludification [45,46]. In parts of the region, peat mosses accumulate on initially mesic soils, independently of topography or drainage, and are related to forest succession [34]. Therefore, in the prolonged absence of fire, these forests tend to convert into less productive spruce-Sphagnum opened forests regardless of the initial species composition [34,[47][48][49][50].…”

“…In parts of the region, peat mosses accumulate on initially mesic soils, independently of topography or drainage, and are related to forest succession [34]. Therefore, in the prolonged absence of fire, these forests tend to convert into less productive spruce-Sphagnum opened forests regardless of the initial species composition [34,[47][48][49][50]. Burned area and residual organic layers (i.e., layers that are not consumed by fire) jointly control forest structure and composition [51].…”

“…on mesic sites [48,[51][52][53]. In contrast, thick residual organic layers favor black spruce self-replacement [53,54] and accelerate the process of paludification [34,51].…”

“…Black spruce forests were separated into black spruce forests originating from severe fire (BS-S) and black spruce forests originating from non-severe fire (BS-NS), since fire severity influences tree and duff load dynamics in BS forests [34]. Successional stages were determined with TSF.…”

“…Successional stages were determined with TSF. We used information (tree basal area, organic layer depth, TSF) that was already available for 37 sites to calculate tree and duff loads [34,48,51]. We visited these sites to complete the inventory with information on DWD, shrubs, and herbs.…”