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Article

Mitigation Potential of Ecosystem-Based Forest Management under Climate Change: A Case Study in the Boreal-Temperate Forest Ecotone

by
Gabriel Landry
1,
Evelyne Thiffault
1,*,
Dominic Cyr
2,
Lucas Moreau
1,
Yan Boulanger
3 and
Caren Dymond
4
1
Research Centre on Renewable Materials, Department of Wood and Forest Sciences, Université Laval, Quebec City, QC G1V 0A6, Canada
2
Science and Technology Branch, Environment and Climate Change Canada, Gatineau, QC J8Y 3Z5, Canada
3
Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Center, Quebec City, QC G1V 4C7, Canada
4
Climate Change and Integrated Planning Branch, Ministry of Forests, Lands, Natural Resource Operations and Rural Development, Government of British Columbia, Victoria, BC V8W 9C2, Canada
*
Author to whom correspondence should be addressed.
Forests 2021, 12(12), 1667; https://0-doi-org.brum.beds.ac.uk/10.3390/f12121667
Submission received: 7 November 2021 / Revised: 24 November 2021 / Accepted: 26 November 2021 / Published: 30 November 2021
(This article belongs to the Special Issue Carbon Stock and Sequestration in Forest Ecosystems)
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Abstract

:
The forest sector can help reduce atmospheric CO2 through carbon (C) sequestration and storage and wood substitution of more polluting materials. However, climate change can have an impact on the C fluxes we are trying to leverage through forestry. We calculated the difference in CO2 eq. fluxes between ecosystem-based forest management and total forest conservation in the context of the temperate-boreal forest ecotone of Quebec (Canada), taking into account fluxes from forest ecosystems, wood product life cycle, and the substitution effect of wood products on markets. Over the 2020–2120 period, in the absence of climate change, ecosystem-based forest management and wood production caused average net annual emissions of 66.9 kilotonnes (kt) of CO2 eq. year−1 (relative to forest conservation), and 15.4 kt of CO2 eq. year−1 when assuming a 100% substitution effect of wood products. While management increased the ecosystem C sink, emissions from degradation of largely short-lived wood products caused the system to be a net source. Moreover, climate warming would decrease the capacity of ecosystems to sequester C and cause a shift towards more hardwood species. Our study highlights the need to adapt the industrial network towards an increased capacity of processing hardwoods into long-lived products and/or products with high substitution potential.

1. Introduction

According to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) [1], the influence of human activity on the climate system and the atmospheric concentrations of carbon dioxide (CO2) has never been greater. Forest ecosystems can be used to mitigate climate change through carbon sequestration and provision of wood products that can store carbon for long periods of time and can displace fossil-based products in markets [2]. Forest management strategies can be designed to help increase forest carbon stocks at the landscape level [3,4]. Moreover, mobilizing wood products that can store sequestered carbon for several decades and/or that can efficiently displace carbon-intensive products on markets could also be part of a mitigation portfolio [5,6].
However, very few studies have addressed the potential issue of climate change impacts on those carbon stocks and fluxes we are trying to leverage through management. Ecological processes in forests such as tree growth, species regeneration, organic matter decomposition and natural disturbance regimes are likely to be altered by the expected changes in climate regimes [7]. For instance, climate change is currently occurring at a rate that is believed to be faster than the longevity of trees and the ability of stands to adapt; as such, an imbalance is occurring between environmental conditions from seed establishment to maturity [8,9]. Furthermore, forests in North America are expected to experience climate-induced increases in mortality through more frequent drought conditions or through an increase in natural disturbances (e.g., fire, insect outbreaks) [10,11,12,13]. Moreover, changes in productivity can directly affect interspecific competition and succession pathways, leading to major changes in forest composition, structure and carbon dynamics [14]. In this context, ecosystems located at their range limits, such as northern temperate forests, might be particularly vulnerable to these climate-induced changes. Indeed, as temperatures rise, hardwood species are predicted to become more abundant in these ecosystems at the expense of softwoods [15,16,17]. All together, these climate-induced impacts on northern forest ecosystems can have the potential to significantly alter their capacity to act as carbon sinks [14,18]. In such a context, the transfer of carbon towards wood products can either improve or worsen the overall carbon balance of the forest sector, depending on the characteristics of the industrial wood processing network (e.g., the share of long-lived wood products that it can processes) and on market use of wood products (e.g., whether they are used to displace GHG-intensive products) [19].
Along with other jurisdictions around the world, the province of Quebec (Canada) is exploring the potential of its forest sector to contribute to climate change mitigation. Ecosystem-based forest management is at the heart of provincial regulations under the Quebec Sustainable Forest Territory Management Act (Loi sur l’aménagement durable du territoire forestier chapitre A.-18.1). This form of management is applied on all forest lands under public tenure (i.e., about 92% of the 905,800 km2 of Quebec forest lands) and aims to ensure the maintenance of biodiversity and the viability of ecosystems by reducing the gaps between managed and natural forests, while still providing a constant wood supply. For example, the protection and establishment of natural regeneration are promoted on harvested areas; planting is only used to supplement natural regeneration. The use of partial cutting (instead of clearcutting) is also promoted to increase the structural diversity of stands, and targets are set for the protection of overmature forests. That said, the context of climate change creates uncertainty about the ability of ecosystem-based forest management to prepare forests for these changes [20]. Consequently, it remains to be seen whether forest ecosystem-based forest management can provide mitigation of CO2 emissions in a changing climate.
This study aimed to evaluate the performance of ecosystem-based forest management and wood production to mitigate CO2 emissions under a changing climate. We used the Maskinongé region as a case study, which is located at the ecotone between the temperate and the boreal forest biomes in Quebec. We selected this region because it is projected to undergo rapid climate-induced alterations in forest composition and structure in the upcoming decades [21]. The specific objective was to evaluate the cumulative impacts of ecosystem-based forest management and wood production and expected changes in the climate regime on the following variables:
(i)
forest composition and productivity;
(ii)
carbon fluxes from forests and wood products; and
(iii)
their substitution effect in markets (i.e., the avoidance of GHG emissions resulting from the displacement of GHG-intensive products with wood products).
The mitigation potential of ecosystem-based forest management and its associated wood production was assessed by comparing such a management scenario with conservation (no harvesting). We used the spatially-explicit forest landscape model LANDIS-II and the Forest Carbon Succession extension, along with the Carbon Budget Model—Harvested Wood Products framework, to simulate forest and carbon dynamics.

2. Materials and Methods

2.1. Study Area

Maskinongé (Figure 1) is located in south central Quebec, Canada. With a total area of 2380 km2, it covers three bioclimatic domains [22] that can be associated with the Northern Hardwood forest region: the sugar maple-bitternut hickory domain, the eastern sugar maple-basswood domain and the eastern sugar maple-yellow birch domain. Maskinongé is located on the St. Lawrence Plain in the southern part of its territory and the Laurentian Plateau in its northern part. The soils of the southern part are composed of clay and organic deposits, while the St. Lawrence Plateau is characterized by various soil types due to the upwelling of the Champlain Sea [22]. The hills of the plateau also contain stony deposits of glacial till. The climate varies across the territory, with an average annual temperature of 5.1 °C, total precipitation of 1019.7 mm and 172.3 cm of snowfall in Louiseville in the south, and 4.2 °C, 1072.2 mm and 232.4 cm in St-Alexis-des-Monts in the north [23].
Forests under public tenure cover 44% (105,055 ha) of Maskinongé’s total territory while privately-owned forests occupy 33% (79,564 ha). Public forests are comprised of 53% mixed, 36% hardwood and 12% softwood stands. Most private forests are located in the southern part of the region, where the climate favors temperate hardwoods; private forests contain 51% hardwood, 40% mixed and 9% softwood stands [24].

2.2. Modelling

A combination of several models was used to simulate forest growth and dynamics for the case study area, and to compile carbon fluxes from ecosystems, products and markets (Figure 2).

2.2.1. LANDIS-II (Landscape, Disturbance and Succession)

Simulations were carried out using the LANDIS-II (Landscape, Disturbance and Succession) spatially-explicit forest landscape model. LANDIS-II is designed to simulate the spatial dynamics of ecosystems and the interaction of processes governing them [25]. It integrates different ecological processes such as natural disturbances, succession, seed dispersal and harvesting. Succession depends on species autecology (shade tolerance, longevity, seed dispersal, etc.), the type of disturbance (logging, fire, etc.) as well as on growth and regeneration which are functions of climate and soil characteristics (see Table S1 in Supplementary Materials) [26]. LANDIS-II is oriented towards long-term simulations (100 years or more) to predict potential changes in species composition, biomass, carbon stocks, natural disturbances, etc. [27] over areas ranging between 103 to 106 hectares (ha). Forest stands are represented and modelled by age and species cohort within a grid. In our simulations, the cell size was 6.25 ha, corresponding more or less to the average area of a forest stand. Each cell is assigned to a single land type where soil and climate conditions are assumed to be homogeneous. The entire study area is, therefore, stratified into land types defined according to the initial soil and climate conditions and in which growth and reproduction functions are unique. The initial stand composition and age structure were retrieved from the provincial ecoforestry maps and the age of the cohorts from Quebec’s permanent and temporary inventories as in Boulanger and Pascual Puigdevall [21]. Cells with fewer than 50% of forest cover were excluded from the simulations. In this work, simulations were carried out using annual time-steps over a 100-year horizon, i.e., from 2020 to 2120. Species included in the modelling were sorted into three categories, i.e., softwoods, intolerant hardwoods and tolerant hardwoods (Table 1).
LANDIS-II simulates processes at both the stand and landscape scales using a variety of extensions. Each extension is parameterized independently and focuses on a specific process. The following extensions were used in our simulations: Forest Carbon Succession v2.1 [28] Base Harvest v4.0 [27], Base Biological Disturbance Agent v4.0 [29] and Base Wind v.3.0 [30]. In addition, the forest gap model PICUS v1.5 [31] was used to determine the growth and establishment potential of tree species as in Tremblay, et al. [32].

2.2.2. Forest Carbon Succession

Forest Carbon Succession (ForCS) [14] is the extension that tracks the evolution of forest stands and carbon dynamics. This extension simulates growth, mortality and decomposition in order to simulate carbon stocks and fluxes in the different pools of the ecosystems. Growth, senescence and reproduction are based on methods established by Scheller and Mladenoff [33] for the Biomass Succession extension. Changes in cohort biomass occur over time as they regenerate, age or die. Stand growth considers the age of the cohort, its history, species relative to the physical environment, and changes in its biomass. Forest Carbon Succession allows monitoring of above- and below-ground carbon fluxes in stands, and the tracking of carbon in decaying dead organic matter and soil [14]. All data follow the definition of carbon pools used in the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3), which itself follows the guidelines of the United Nations Framework Convention on Climate Change [34]. Equations and parameters regulating carbon transfers among ecosystem pools and with the atmosphere as a function of time and types of disturbances are user-defined. For this project we used the default parameters from CBM-CFS3.

2.2.3. Dynamic Growth and Reproduction Inputs

LANDIS-II was paired with PICUS v1.5 to estimate growth and establishment parameters used in ForCS for each tree species as a function of climate change and soil characteristics. PICUS is a spatially-explicit forest gap model oriented for stem simulation in a stand on an annual scale [31]. It generates and simulates stem germination, establishment, growth and mortality in stands under different climate scenarios and soil characteristics [32,35]. PICUS is used to parameterize three climate-sensitive growth processes in ForCS: maximum annual net primary productivity (maxANPP), maximum aboveground biomass (maxAGB) and species establishment probabilities (SEP) [36]. The PICUS model parameters (Table S2 in Supplementary Materials) used in this study were validated in several previous studies [16,35,36,37]. Further details regarding the parameterization, calibration and validation of PICUS can be found in Taylor, et al. [37].

2.2.4. Harvesting

Tree cohort harvest was simulated using the Base Harvest extension v4.0 [27]. Stand were deemed eligible for harvesting based on their age and time elapsed since last harvest (details below). Partial and selection harvesting was simulated by harvesting entire cohorts, i.e., that 1/n cohorts were entirely removed to approximate the desired impacts of silvicultural treatments on remaining standing biomass, transfers to dead organic matter and exports to forest products.
Two forest management scenarios were used in the simulations, adapted from Boulanger, et al. [36]. First, we modelled a conservation scenario, in which no harvest operations are performed. This scenario was compared to an ecosystem-based forest management scenario; this scenario emulates the measures prescribed by the Sustainable Forest Territory Management Act that prevails on Quebec’s public forests. For the purposes of this project, it was assumed that these same practices are also applied on private lands.
The ecosystem-based forest management scenario simulates different prescriptions that have been parameterized in the Base Harvest Extension according to the current vegetation. These include:
-
Partial Cutting in hardwood stands: a removal of 50% of the canopy every 40 years. Area targeted: 1.875% of the productive territory is harvested under this prescription every year.
-
Partial Cutting in softwood stands: 50% removal of canopy cover every 30 years starting with stands that are at least 60 years old. Area targeted: 0.089% every year.
-
Selection cutting: 33% removal of canopy cover every 20 years. Area targeted: 3% every year.
-
Clearcutting: 100% removal of canopy cover of cohorts that are at least 11 years of age in stands that are at least 60 years old. Area targeted: 0.803% every year.
To keep the management implementation simple and flexible with regards to expected changes in forest composition under various climate conditions, we did not specifically target any particular species, contrary to the actual management practices. Additionally, no optimization of timber supply or assessment of annual allowable cut were performed a priori nor revised throughout the courses of simulations. The simulated total harvested volume might, therefore, be different from current sustainable forest management practices. The carbon stocks were manipulated following the harvest descriptions above, with the appropriate portion of the merchantable-sized stemwood leaving the ecosystem and the branches, tops, roots, and stumps being transferred to the dead organic matter pools and left to decay.

2.2.5. Natural Disturbances

Windthrows were simulated as a background disturbance with a 2500-year return interval using Base Wind [30] following the same parameters as in Boulanger and Pascual Puigdevall [21].
Spruce budworm outbreaks (Choristoneura fumiferana) were simulated using the Biological Disturbance Agent extension [29]. This extension integrates the mortality of stems following the event of an epidemic. The probability of epidemics is mainly based on the presence of vulnerable species within a cell and their abundance within a given radius (here set at 1 km). Host species are, in decreasing order of vulnerability, balsam fir, white spruce, red spruce and black spruce. All parameters were calibrated and validated using various sources from mixed forests [38]. Epidemics were parameterized to occur at the most severe levels [36], to last a maximum of 10 years and to occur every 32 years according to the regional cycles observed in the study area [39]. In ForCS, the total carbon impact of the epidemic was applied over one single time step, i.e., the impact was concentrated within one single year. Carbon stocks of killed trees are transferred to dead organic matter after the event of an outbreak.

2.2.6. Harvested Wood Products

Data on harvesting that were generated by Forest Carbon Succession were used as input for the Carbon Budget Model—Framework for Harvested Wood Products (CBM-FHWP) tool developed by the Canadian Forest Service [40]. This tool tracks the carbon associated with wood products according to their half-life, based on a decay function. The values used as half-life times for sawnwood, panels and pulp and paper were the default values provided by the IPCC, i.e., 35, 25 and 2 years respectively [41] The carbon stock of wood used as bio-heat was considered to be emitted in the same year of the harvest. The carbon footprint includes all products used both in Quebec and those exported outside of the province. The basket of wood products (Figure 3) processed from harvested wood was adapted for softwoods, intolerant hardwoods and tolerant hardwoods from the average basket for the province of Quebec used in Beauregard, et al. [42]. For modelling purposes, the wood product reservoirs before the start of the simulations (time 0) were assumed to be empty; only the products created during the simulations were considered. Wood products included in the basket were sawnwood, panels, pulp and paper and bioenergy used internally as process heat within sawmills. Contrary to other regions of the world (e.g., European countries), bioenergy currently occupies only a marginal role in the energy portfolio of Quebec, which is dominated by hydropower; while it might be expected to grow in the future, there is currently no significant amount of woody biomass dedicated to energy production outside of the forest sector [43]. There might, however, be firewood collection in the study area; as it is mainly part of informal markets and is therefore poorly documented, it was not included in wood product baskets.
The substitution effect was calculated using the difference between the GHG emissions associated with the life cycle of a material (including its production, use and end-of-life) and the life-cycle emissions associated with the use of a wood product performing the same functions on markets [44]. The substitution effect was calculated as a negative flux and was assumed to occur the same year of the harvest. This effect was calculated using factors based on specific assumptions for the Quebec wood industry and markets, as recommended by Seppälä, et al. [45]: for each tonne of carbon contained in sawnwood and panels, the emission of 0.91 and 0.77 tonne of carbon was assumed to be avoided on markets, respectively [42]. No substitution effect was assumed for process heat from bark and other residues used internally in sawmills, since the displacement of fossil fuels caused by this bio-heat is already factored in the substitution factor for sawnwood. Pulp and paper products were also assumed to not yield any substitution effect; this assumption is similar to the one made in other North American studies [3,4,46] and avoids any over-estimation of climate benefits of wood products.
A sensitivity analysis was also performed to test the effect of the basket of wood products and the substitution factors on carbon fluxes and mitigation potential. First, two alternative baskets were tested:
-
one assuming that 22% of all logs (all species combined) are sent to sawmills, resulting in an overall lower share of roundwood ending up as sawnwood products (11% of sawnwood, 77% of pulp and paper, <1% of panels and 12% of bioenergy; based on the values used for intolerant hardwood processing in Figure 3); and
-
one assuming that 88% of all logs (all species combined) are sent to sawmills, resulting in an overall higher share of roundwood ending up as sawnwood products (42% of sawnwood, 44% of pulp and paper, 2% of panels of 12% in bioenergy; based on the values used for softwood processing in Figure 3).
Second, two alternative sets of substitution factors were tested. One was based on the Canadian averages calculated by Smyth, et al. [47], which provide values of 0.54 and 0.45 tonne of C avoided per tonne of C in sawnwood and panels, respectively, which are lower than the averages for Quebec. We also tested the substitution effect using the value of 1.2 tonne of C avoided per tonne of C in wood products provided by Leskinen, et al. [48] based on a general average for all wood products calculated from a meta-analysis of the international literature; this value is significantly higher than the Canadian and Quebec averages.

2.2.7. Climate Scenarios

The climate scenarios of the 100-year simulation were based on three different global warming trajectories:
  • A baseline scenario without climate change, which is a projection of historical (1981–2010) climate conditions without any change over the 100 years of simulation, and
  • two warming scenarios of increased anthropogenic radiative forcing (RCP—Representative Concentration Pathways), i.e., RCP 4.5 and RCP 8.5 [49].
Of the two global warming trajectories, the RCP 4.5 scenario is more optimistic with a radiative forcing of 4.5 W/m2 by the end of the century. The RCP 8.5 scenario is more pessimistic with radiative forcing reaching 8.5 W/m2 in 2100. Climate data of the RCP scenarios come from CanESM2 (Canadian Earth System Model version 2) simulations [50], downloaded from the Climate Model Intercomparison Project Phase 5 (CMIP5) archives of the World Climate Research Program (WCRP) [51]. Temperature and precipitation data from CanESM2 were biased-corrected using data for the period from 1961 to 1990 and were downscaled to a 10 km resolution using the ANUSPLIN method [52].

2.2.8. Simulation Design

We ran simulations according to a factorial design under baseline, RCP 4.5 and RCP 8.5 climate scenarios in interaction with ecosystem-based forest management and conservation scenarios. For each combination of management and climate change scenario, we ran five replicates for 100 years starting in 2020 and using an annual time step. Except for scenarios involving the baseline climate in which climate-sensitive parameters did not change, we allowed dynamic growth and establishment parameters in the Forest Carbon Succession extension (SEP, maxANPP and maxAGB) to be updated in 2041 and 2071, while mean annual temperature, which influenced decay rates, were updated every 10 years (2031, 2041, 2051, etc.).

2.3. Carbon Fluxes and Mitigation Potential

All results regarding ForCS outputs as well as the carbon fluxes were compiled at the study area level. For all carbon fluxes, a positive value indicates an emission to the atmosphere (carbon source), while a negative value indicates a removal/sequestration from the atmosphere (carbon sink) or an emission avoidance. The difference between the sum of CO2 fluxes of the ecosystem-based forest management scenario and the sum of CO2 fluxes from forests in the conservation scenario was calculated for each climate scenario (baseline, RCP 4.5, RCP 8.5). This difference is hereafter referred to as the mitigation potential of ecosystem-based forest management; a positive value indicates that ecosystem-based forest management increases emissions relative to conservation, while a negative value indicates a reduction in emissions. The mitigation potential was first calculated considering the sum of fluxes from forest ecosystems and the degradation of wood products during their life cycle. We then also estimated the potential substitution effect that wood products generated by the ecosystem-based forest management scenario may have on markets [4,19].

3. Results

3.1. Species and Age Composition

We projected a decrease in aboveground biomass with the increase in radiative forcing (irrespective of management) (Figure 4a). Indeed, after 100 years of simulation, total aboveground biomass with the conservation scenario under RCP 8.5 had decreased by 33.9 tonnes·ha−1 (22.7%) relative to the reference climate, and by 35.67 tonnes·ha−1 (26.1%) under ecosystem-based forest management (which includes harvesting).
With respect to the influence of management, there was on average lower aboveground biomass under the ecosystem-based forest management scenario than under the conservation scenario. In addition, climate warming (from the baseline climate scenario to RCP 4.5 and RCP 8.5) amplified the negative effect of forest harvesting on aboveground biomass: differences of −6.44, −7.13 and −7.32 tonnes·ha−1 were simulated (corresponding to a loss of 8.6%, 10.6% and 12.7%) between the management and conservation scenarios after 100 years of simulation for the reference climate, RCP 4.5 and RCP 8.5, respectively.
Forest harvesting under ecosystem-based forest management allowed for a higher proportion of softwoods to be maintained, relative to conservation, at the end of the 100 years of simulation under the baseline climate (+4.16 tonnes·ha−1, corresponding to a gain of 7.4%) (Figure 4a). However, with increasing radiative forcing, this trend was reversed with a decrease of 9.16 tonnes·ha−1 (corresponding to a loss of 29.7%) under RCP 8.5. Overall, the increase in radiative forcing increased the proportions of tolerant hardwoods at the expense of softwoods regardless of management scenarios. That being said, increased warming decreased aboveground biomass more than logging. Nevertheless, the greatest decrease was observed when logging was simulated under RCP 8.5 climate (i.e., the most pessimistic climate scenario).
The first two decades of simulations (2020 to 2040) were characterized by a rapid increase in aboveground biomass, irrespective of management and climate scenario, due to the recruitment of young tree cohorts (0–20 years) (Figure 4b). Unsurprisingly, younger stands (<40 years) were more abundant in landscapes under ecosystem-based forest management than under conservation, while the inverse was true for older stands (>100 years). Overall, increased climate forcing did not appear to modify the age class distribution.

3.2. Forest Carbon Dynamics

Biomass production and turnover did not appear to be influenced by the management scenario (Figure 5). However, both net growth, net primary productivity (NPP) and heterotrophic respiration (Rh) were slightly higher under ecosystem-based forest management than conservation. For its part, increased radiative forcing increased variability in biomass turnover, which tended to be constant over the simulation period under the baseline climate projection but showed sharper variations under RCPs 4.5 and 8.5. Net primary productivity also showed stronger variations with increasing radiative forcing. Net ecosystem productivity (NEP), which is the result of the subtraction of Rh from NPP, and net biome productivity (NBP), which represents NPP minus the losses from anthropogenic and natural disturbances, were very similar between ecosystem-based forest management and conservation; while they were close to 0 for the baseline climate projection, they became more negative with under RCP 4.5 and 8.5. Sudden biomass losses in all scenarios around the years 2065 and 2095 correspond to insect outbreak events.
The evolution of forest carbon stocks in the study area according to management and climate (Figure 6) resulted from these various ecosystem processes. Climate warming reduced carbon stocks of both belowground and aboveground biomass. Ecosystem-based forest management also reduced carbon stocks of aboveground biomass (relative to conservation), whereas its effect was only marginal on belowground biomass stocks. Nevertheless, aboveground biomass stocks remained stable or slightly increased over time under both the baseline and RCP 4.5 climate projections. Under RCP 8.5, aboveground biomass stocks started to decrease slightly from the year 2070 under both conservation and forest management. For dead organic matter (which includes carbon in dead wood, litter, humus and mineral soil), different trends were obtained. Dead organic matter stocks were the highest under the RCP 8.5 climate scenario until around the 2040s; however, at the end of the 100-year simulation period, these stocks were lowest under this scenario. On the other hand, ecosystem-based forest management produced on average the highest amount of dead organic matter.

3.3. Harvesting and Transfer to Wood Products

Results showed that there was an overall decrease in the total amount of carbon transferred to wood products with climate warming (Figure 7). Specifically, while there was an increase in harvested tolerant hardwoods (mainly American beech; see Figure S1 in the Supplementary Materials), this did not compensate for the important decrease in the amount of harvested softwoods at the end of the 100-year simulation with increasing radiative forcing (Figure 7a). Around year 2080, cohorts from several species that were regenerated in 2020 reach the age of eligibility to harvest (60 to 80 years) causing the apparent sudden increase in transfer to wood products.
The variation in harvested species caused by radiative forcing scenarios was somewhat reflected in the product composition of the harvested wood basket (Figure 7b). Since hardwood species were assumed to generate a smaller proportion of sawn lumber than softwoods (Figure 3), the overall proportion of sawnwood decreased slightly with increasing climate forcing, going from 29% to 27% between the baseline and RCP 8.5, while the proportion of pulp and paper products increased from 58% to 60%.

3.4. Carbon Fluxes

Carbon fluxes were estimated for the conservation and ecosystem-based forest management scenarios (Table 2). Under the baseline climate, forest landscapes under both conservation and ecosystem-based forest management were a carbon sink, with the latter sequestering more than twice as much carbon than the former on an average yearly basis. However, under RCP 4.5 and 8.5, forest ecosystems under conservation became a carbon source, while landscapes under ecosystem management experienced a reduction of their sink under RCP 4.5 and became a source under RCP 8.5.
Carbon emissions from life cycle of wood products generated by ecosystem-based forest management were slightly lower under increased climate forcing relative to the baseline climate, due to the decrease in harvested biomass and transfer to wood products. However, under RCP 4.5, emissions from products were higher than the ecosystem carbon sink; under RCP 8.5, they represented close to 90% of total annual emissions to the atmosphere (i.e., addition of forest ecosystems + products). Emission savings associated with the use of wood products on markets as a substitution for more GHG-intensive materials on markets remained low compared with other carbon fluxes; under RCP 8.5, these savings compensated for only about 22% of emissions from forest ecosystems and products.
The mitigation potential of forest ecosystem-based forest management was estimated as the difference in carbon fluxes for this scenario relative to the conservation scenario. In the absence of climate change (i.e., baseline climate), the annual delta carbon flux of ecosystem-based forest management was 66.9 kt of CO2 eq. per year between 2020 and 2120, and of 15.4 kt of CO2 eq. year−1 when assuming the substitution effect; therefore, the Maskinongé forest sector was a net carbon source for most of the simulation period relative to conservation (Figure 8a). Nevertheless, the forest ecosystems themselves remained a net carbon sink, as they displayed higher net primary productivity under ecosystem-based forest management than conservation. However, wood products were a net source of emissions to the atmosphere, especially in years towards the end of the simulations. The increased positive fluxes from products were due to the build-up of the product reservoir over the years, which was assumed to be empty at the beginning of the simulation period. Moreover, a high proportion of harvested wood was transferred to pulp and paper products, which were assumed to have a half-life of 2 years (based on the IPCC default values) and were assumed to not yield any substitution effect on markets. This resulted in an important share of carbon stocks in wood products that was quickly emitted to the atmosphere following harvest (as opposed to being stored in long-lived wood products), without any displacement of GHG-intensive products.
Under RCP 4.5 and RCP 8.5, the net annual carbon sequestration from forest ecosystems under management decreased relative to conservation (Figure 8a). As a result, the mitigation potential of the system under ecosystem-based forest management was 86.6 and 108.8 kt of CO2 eq. year−1 for RCP 4.5 and 8.5 respectively; assuming a substitution effect for wood products, these values would be 40.9 and 65.0 kt of CO2 eq. year−1. Periods of time for which the system was a net source of carbon to the atmosphere relative to conservation became longer with increased radiative forcing. In terms of cumulative fluxes (Figure 8b), climate warming under RCP 4.5 caused almost a tripling of cumulative net emissions from ecosystem management relative to conservation at the end of the simulation period, while they were more than four times higher under RCP 8.5.
Unsurprisingly, a lower proportion of sawnwood and/or lower substitution factors for solid wood products on markets all reduced the mitigation potential of forest management (i.e., increased emissions relative to conservation) (Table 3). However, a higher proportion of sawnwood produced from harvested roundwood would allow the system to be a net carbon sink relative to conservation under the baseline and RCP 4.5 climate projections, unless low substitution factors are assumed (the latter turning the system into a net carbon source). Moreover, higher substitution factors needed to be coupled with a higher proportion of sawnwood for the system to yield mitigation benefits under RCP 4.5. Under RCP 8.5, only a combination of a higher proportion of sawnwood and higher substitution factors would be able to partially compensate carbon emissions from ecosystems, with net average emissions of 0.9 kt CO2 eq. year−1 relative to conservation.

4. Discussion

Our results suggest that the capacity of the forest sector to mitigate CO2 emissions in the boreal-temperate ecotone will be negatively affected by increasing anthropogenic climate forcing. Current ecosystem-based forest management practices have the potential to improve the carbon sink of forest ecosystems relative to conservation under the baseline climate scenario in these ecosystems. However, these practices could interact negatively with climate change, compounding its detrimental effects on forest carbon sequestration, mainly through altered ecosystem-level processes that will affect net primary productivity and net ecosystem exchanges. In addition, the forest ecosystem carbon sink cannot compensate for emissions associated with mostly short-lived wood products that are sourced from increasingly hardwood-dominated landscapes. However, a substantial increase in the proportion of long-lived wood products (such as sawnwood) that can be yielded from harvested roundwood and a significant improvement in the efficiency with which wood products displace more GHG-intensive products on markets can preserve or increase the mitigation potential of forest ecosystem-based forest management, even under climate change.

4.1. Ecosystem Processes

Climate change is projected to drive a substantial decrease in net primary productivity (NPP) in the case study region, which is representative of the transition zone between the temperate and the boreal forest biomes. Climate change is notably associated with the decline of the cold-tolerant species such as spruces and balsam fir, as has been shown in similar conditions by Boulanger, Taylor, Price, Cyr, McGarrigle, Rammer, Sainte-Marie, Beaudoin, Guindon and Mansuy [16] and elsewhere in northeastern North America [53]. Indeed, with increasing temperatures, the presence of softwood species tended to decrease significantly partly at the expanse of hardwoods, regardless of forest management scenarios. Conifer growth and regeneration capacities decline at higher temperatures, resulting in a decreased competitiveness with hardwoods in a changing climate [17,37]. On the other hand, although thermophilous hardwood species should be favored by climate-induced softwood decline, it is hypothesized that dispersal limitations as well as further climate constraints on growth and regeneration under severe radiative forcing could limit the ability of hardwood species to fully compensate for softwood aboveground biomass decrease. Such a “climate lag” in productivity has also been projected in temperate and mixed wood landscapes in the Acadian Forest of Atlantic Maritime [37], northeastern United States [54] and other regions at the transition between temperate and boreal biomes [16,21]. Nevertheless, it should be noted that small gap dynamics were not explicitly simulated because of the grid resolution (6.25 ha); therefore, the competitiveness of species with more intermediate shade tolerance (e.g., yellow birch) is probably underestimated, especially in relation to shade-tolerant species.
While a decline in NPP was driven by climate change, results suggest that harvesting can stimulate tree growth compared with total conservation. Studies in northern hardwoods and mixed stands such those found in Maskinongé suggest that selection and partial cutting can have a positive impact on stand growth rates relative to control (no harvest) conditions, which may explain the observed increased in NPP under ecosystem-based forest management relative to conservation [55,56,57]. This gain in NPP (and thus carbon sequestration) attributable to harvesting, however, is partially negated by a concurrent increase in dead organic matter input due to the significant non-merchantable proportion of the harvested biomass that remains to decompose in situ. Perhaps more importantly, those larger fluxes of dead organic matter associated with harvesting tend to decay faster with climate change due to the temperature increases. Consequently, emissions due to heterotrophic respiration remains relatively constant under increasingly severe climate forcing despite an associated decrease in productivity and dead organic matter inputs. It can be noted that the total annual carbon balance in a context of high global warming (RCP 8.5) appeared to be subject to greater variations, both positive and negative, due to higher variability of ecosystem fluxes. This suggests that climate alterations under RCP 8.5 may be too large and too rapid for forest ecosystem processes, as was also suggested by Zhu, et al. [58] for North American forests, and by Valade, et al. [19] for European forests.
In our simulations, growth and regeneration parameters were updated in 2041 and 2071 to account for the effects of climate change on the relative competitiveness of each species. Although updating those parameters at an annual time step would have smoothed out some of the artefacts that are visible in those years, e.g., transient drops in average NPP and net ecosystem productivity (NEP), that also allowed us to detect more easily differences between climate scenarios but also between management scenarios. The most notable difference is that the landscape-level drops in average NPP and NEP observed in those years are not as dramatic under the conservation scenario: the effects of climate change in terms of carbon dynamics can be less important in the absence of harvesting. Moreover, the ecosystems appeared to adjust slightly faster afterwards in the absence of harvesting. The realized age structures at the landscape level suggest that harvesting reduces the abundance of sexually mature cohorts of species that are better adapted to a warmer climate, such as thermophilous (tolerant) hardwoods, or favors the relative abundance of ill-adapted ones such as softwoods. In either case, harvesting does not appear to facilitate species replacement in newly available climatic niches for species at the leading edge of their distribution [21]. Similar results were found by Liang, et al. [54] who showed that while disturbances may contribute to species’ recruitment into new sites, they actually had a relatively small effect compared to the species’ competitive abilities for establishment and growth. This underlines the fact that under a changing climate, silvicultural and harvesting practices will need to evolve to help maintain desired species in landscapes or to adapt stand composition to emerging environmental conditions [59].

4.2. Consequences on Harvested Wood Products

Climate-induced decrease in NPP and aboveground biomass stocks is expected to affect the total amount of carbon transferred to harvested wood products, as also observed by Dymond, et al. [60] in northwestern Canada. For Maskinongé, softwoods appear to be particularly affected by this change, mirroring climate-induced decline in cold-tolerant species. Conversely, the proportion of hardwoods in the volume harvested and sent to mills and then to markets increase with warming, as also observed in McKenney, et al. [61].
Climate-induced changes in species composition can directly contribute to increase carbon emissions by changing the product basket that can be processed from harvested wood over time. Indeed, the way in which the basket of wood products evolves will have a considerable influence on the ability of the forest sector to fight climate change [19]. In the simulations, the significant emissions from wood products under increased climate forcing are due to the fact that, based on model inputs (based on average values of Quebec wood-processing industrial network), a smaller proportion of sawtimber is derived from hardwoods than softwoods, with a significant proportion of hardwoods going to pulp mills. The short lifespan of pulp and paper means that the carbon contained in these products is quickly released to the atmosphere. Conversely, sawnwood products store carbon for several decades and, therefore, cause fewer annual emissions to the atmosphere [62]. However, it should be noted that the inputs used to describe the basket of products over time are a simplistic generalization of a much more complex reality. It is likely that the pulp and paper sector will evolve over the next few decades in response to declining demand [63], for example towards cellulose-based materials or biofuels that have a longer lifespan and/or can substitute for GHG-intensive fossil-based products. Future modelling exercises could use a dynamic basket of wood products that evolves over time according to expected innovations in wood processing and manufacturing.

4.3. Impacts on Carbon Fluxes of the Forest System

Our study suggests that the ability of forest management and wood production to mitigate climate change will be greatly reduced because of global warming. Indeed, our results showed that strict conservation yield lower carbon sequestration in forests than under ecosystem-based forest management; however, the ability to maintain a carbon sink with ecosystem-based forest management would be most effective without climate warming, which is increasingly unlikely. With global warming, this gain between managed and conserved forests diminishes, possibly due to a climate-induced increase in natural mortality, especially for softwoods. However, we did not simulate wildfire considering the rather rare current and future occurrence of this disturbance in the study area [11]. Nevertheless, the projected carbon balance might be affected were wildfires to occur along the time horizon considered here. Moreover, compounding effects on wildfire risks of management practices are also possible, i.e., specific forestry practices might increase fire risk of forest landscapes [64]. While forest management should aim to limit the vulnerability of landscapes to natural disturbances [65], salvage harvesting of stands damaged by disturbances can contribute to maintaining wood supply and avoiding over-harvesting of the living stock [66] as long as ecological impacts are carefully managed [67].
Change in the supply chain value could partially offset climate-induced impacts on carbon emissions from mixed and hardwood forests, notably by producing more long-lived wood products and/or products with higher substitution potential on markets. As mentioned, under the current configuration of the wood industrial network, climate-induced increase in hardwood content triggers more short-lived products, i.e., pulp and paper. As it is assumed that pulp and paper products would not yield any substitution effect on the markets (i.e., pulp and paper products do not displace GHG-intensive products) a lever towards GHG emission mitigation is, therefore, not applied. In Quebec, the recovery of hardwood into lumber products is limited by the low quality of hardwood stems [68,69]. As a long-term measure, appropriate silvicultural efforts are needed to improve the quality of the stems. The capacity of the forest industrial network to convert hardwood species into long-lived products (for example in the form of panels or other composite materials) would need to be improved. These improvements are even more relevant in a context of global warming [70]. Indeed, with the potential for forest ecosystems to become net sources of carbon to the atmosphere and for species composition to change under climate change, it will be crucial to increase the yield of long-lived wood products and their penetration and use on markets as a replacement for GHG-intensive products [19]. More generally, given the importance of emissions from wood products relative to overall simulated carbon fluxes, improving the durability of wood products to extend their lifespan and/or increase the recycling and reuse of wood products at the end of their life should also be strongly considered.
However, the health and quality of hardwood species that are projected to be favored by climate change might be compromised by existing or emerging diseases. For instance, the detailed data for individual species (see Figure S1 in Supplementary Materials) show that the climate-induced increase in hardwoods is mainly due to an increased presence of American beech. Such an increase in American beech has been observed at the expense of maple and birch species across the northeastern USA and is thought to have been at least partially driven by climate change [71]. However, our modelling did not consider the impact of beech bark disease, which is prevalent in eastern North America and causes important mortality of American beech and greatly affect its wood quality. The aftermath of bark disease-induced mortality is often associated with the establishment of dense thickets of beech sprouts [72]. How these dynamics influence forest composition and carbon fluxes, and how they will evolve under a changing climate [73], would need to be integrated into future modelling efforts. Moreover, due to the combination of historical features of the industrial structure and the presence of beech bark disease [74], American beech does not currently occupy a significant part of the volumes that are sent to the mills. If the predictions that this species will increase in stands under a changing climate are confirmed, it will become important to adapt the processing capacities for this species, as well as that of other hardwood species that are predicted to become more abundant with warming [61].
In this study, we adopted the systems approach for mitigation potential that considers fluxes from forests and products. Based on assumptions related to the role of wood products on markets where they could displace more GHG-intensive products, we also estimated their potential substitution effect. The assumed substitution effect would create cumulative savings at year 2120 ranging from −4379 kt CO2 eq. under RCP 8.5 to −5152 kt CO2 eq. under a baseline climate. As a reference, cumulative carbon sequestration of forest ecosystems in 2120 was estimated at −7663 kt CO2 eq. and −13,369 kt CO2 eq. for RCP 8.5 and baseline climate, respectively. However, at a regional scale such as that used in this study, accounting for emission avoidance from wood substitution might be questionable, as it is unclear what is the exact role and effects of the wood products sourced from the Maskinongé region on overall material and energy markets. Moreover, this benefit only materializes if there is an actual substitution for another material or energy source, i.e., the harvested wood is used in applications for which the business-as-usual scenario would be the use of another (GHG-intensive) product [44]. This benefit might be difficult to verify or may not materialize at all [75,76,77,78]. Also, it is possible that the GHG effects of displacement by wood products on markets will evolve over time due to expected changes in industrial processes of other products, such as improvements of energy efficiency and reduction of GHG emissions in cement production: a reduction of the GHG footprint of displaced products would lead to a reduction of the displacement factor of wood products [79]. Refinement of practices for its accounting and reporting is, therefore, an essential step towards implementing climate change mitigation policies related to the forest sector [80].

5. Conclusions

This study has brought to light several results that contribute to the understanding of the role of forest management and wood production in the context of climate change, using a region located at the boreal-temperate forest ecotone as a case study. While managed forest ecosystems were globally a carbon sink, the combined effect of greater sequestration in the forest and substitution on markets was not enough to offset emissions from a basket of products that generated a high rate of short-lived products. Also, the mitigation potential of forest management is likely to be adversely affected by climate warming; this is especially due to the decrease of the forest ecosystem sink, and to an increase in the output of short-lived wood products sourced from the increasingly hardwood-dominated landscapes. While ecosystem-based forest management practices aim to maintain the long-term integrity of ecosystem processes, they may need to be adapted in response to the expected increase in hardwoods and the decline of softwoods in this temperate-boreal ecotone. Moreover, the industrial sector would also need to increase the share of long-lived wood products that can be sourced from species that are predicted to increase in abundance due to climate change. On the other hand, conservation can be considered as a relevant climate adaptation measure in the context of the transition zones such as that studied here. Moreover, increased conservation measures would also benefit biodiversity, notably in the context of already fragmented forest landscapes that have been subjected to substantial anthropogenic pressure over the years.

Supplementary Materials

The following are available online at https://0-www-mdpi-com.brum.beds.ac.uk/article/10.3390/f12121667/s1, Table S1: LANDIS-II input data for tree species simulated within the study area. Table S2: Select input parameters specific to PICUS for species simulated within the Makinongé study area. Figure S1: Evolution of species composition.

Author Contributions

Conceptualization, G.L. and E.T.; Formal analysis, G.L., D.C., L.M. and Y.B.; Funding acquisition, E.T.; Methodology, E.T., D.C. and C.D.; Project administration, E.T.; Writing—original draft, G.L.; Writing—review and editing, E.T., D.C., Y.B. and C.D. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by a Discovery grant to E. Thiffault from the Natural Science and Engineering Research Council of Canada [RGPIN-2018-05755] and a research contract from the Municipalité régionale de comté de Maskinongé to E. Thiffault.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data generated from simulations performed in this study are available at: https://figshare.com/articles/dataset/Landry_et_al_Mitigation_potential_of_ecosystem-based_forest_management/14869317 (accessed on 25 November 2021).

Acknowledgments

This article is adapted from the bachelor thesis of the first author G. Landry.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

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Forests 12 01667 g001 550
Figure 1. Location of the study area according to Quebec’s bioclimatic domains.
Figure 1. Location of the study area according to Quebec’s bioclimatic domains.
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Forests 12 01667 g002 550
Figure 2. Modelling framework used in this study.
Figure 2. Modelling framework used in this study.
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Forests 12 01667 g003 550
Figure 3. Parameters of the basket of wood products used for the distribution of harvested wood in the ecosystem-based forest management scenario. See Table 1 for the list of species. Bioenergy refers here to bio-heat used internally within sawmills.
Figure 3. Parameters of the basket of wood products used for the distribution of harvested wood in the ecosystem-based forest management scenario. See Table 1 for the list of species. Bioenergy refers here to bio-heat used internally within sawmills.
Forests 12 01667 g003
Forests 12 01667 g004a 550Forests 12 01667 g004b 550
Figure 4. Evolution of (a) forest composition and (b) age classes of Maskinongé forests, in oven-dry tonnes·ha−1 of aboveground biomass. Columns correspond to climate scenarios, and rows to management scenarios, i.e., conservation, and ecosystem-based forest management (EBFM). See Table 1 for list of species. Results are based on the average of five replicates.
Figure 4. Evolution of (a) forest composition and (b) age classes of Maskinongé forests, in oven-dry tonnes·ha−1 of aboveground biomass. Columns correspond to climate scenarios, and rows to management scenarios, i.e., conservation, and ecosystem-based forest management (EBFM). See Table 1 for list of species. Results are based on the average of five replicates.
Forests 12 01667 g004aForests 12 01667 g004b
Forests 12 01667 g005 550
Figure 5. Ecosystem carbon fluxes of Maskinongé forests. Columns correspond to climate scenarios. Results are based on the average of five replicates. DelBio: Annual change in biomass stocks. Turnover: Annual transfer of biomass to dead organic matter and soil pools before disturbances occur. NetGrowth: Change in biomass from growth alone. NPP: Net Primary Production (=NetGrowth + Turnover). Rh: Heterotrophic respiration. NEP: Net Ecosystem Productivity (=NPP − Rh). NBP: Net Biome Productivity (=NEP − losses due to disturbances).
Figure 5. Ecosystem carbon fluxes of Maskinongé forests. Columns correspond to climate scenarios. Results are based on the average of five replicates. DelBio: Annual change in biomass stocks. Turnover: Annual transfer of biomass to dead organic matter and soil pools before disturbances occur. NetGrowth: Change in biomass from growth alone. NPP: Net Primary Production (=NetGrowth + Turnover). Rh: Heterotrophic respiration. NEP: Net Ecosystem Productivity (=NPP − Rh). NBP: Net Biome Productivity (=NEP − losses due to disturbances).
Forests 12 01667 g005
Forests 12 01667 g006 550
Figure 6. Carbon stocks of Maskinongé forests. Columns correspond to climate scenarios, and rows to management scenarios, i.e., conservation and ecosystem-based forest management (EBFM). Dead organic matter includes dead wood, litter, humus and mineral soil. Results are based on the average of five replicates.
Figure 6. Carbon stocks of Maskinongé forests. Columns correspond to climate scenarios, and rows to management scenarios, i.e., conservation and ecosystem-based forest management (EBFM). Dead organic matter includes dead wood, litter, humus and mineral soil. Results are based on the average of five replicates.
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Forests 12 01667 g007 550
Figure 7. Average annual carbon transfer to wood products by (a) species groups and (b) product category. Columns correspond to climate scenarios, and rows to management scenarios, i.e., conservation, and ecosystem-based forest management. See Table 1 for list of species. Results are based on the average of five replicates.
Figure 7. Average annual carbon transfer to wood products by (a) species groups and (b) product category. Columns correspond to climate scenarios, and rows to management scenarios, i.e., conservation, and ecosystem-based forest management. See Table 1 for list of species. Results are based on the average of five replicates.
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Forests 12 01667 g008a 550Forests 12 01667 g008b 550
Figure 8. Mitigation potential of ecosystem-based forest management in Maskinongé compared to the conservation scenario presented on (a) an annual basis (in kt of CO2 eq. year−1) and (b) a cumulative basis (in kt of CO2 eq.). The dashed line considers the sum of fluxes from forest ecosystem and wood product degradation; the solid line additionally assumes fluxes from the substitution effect of wood products on markets. Positive values indicate that ecosystem-based forest management causes a net increase of emissions to the atmosphere relative to conservation, while negative values indicate a net decrease (mitigation). Results are based on the average of five replicates.
Figure 8. Mitigation potential of ecosystem-based forest management in Maskinongé compared to the conservation scenario presented on (a) an annual basis (in kt of CO2 eq. year−1) and (b) a cumulative basis (in kt of CO2 eq.). The dashed line considers the sum of fluxes from forest ecosystem and wood product degradation; the solid line additionally assumes fluxes from the substitution effect of wood products on markets. Positive values indicate that ecosystem-based forest management causes a net increase of emissions to the atmosphere relative to conservation, while negative values indicate a net decrease (mitigation). Results are based on the average of five replicates.
Forests 12 01667 g008aForests 12 01667 g008b
Table
Table 1. List of species used in the simulations of Maskinongé forests.
Table 1. List of species used in the simulations of Maskinongé forests.
SoftwoodsIntolerant HardwoodsTolerant Hardwoods
Balsam fir (Abies balsamea)Red maple (Acer rubrum)Sugar maple (Acer saccharum)
Tamarack (Larix laricina)White birch (Betula papyrifera)Yellow birch (Betula alleghaniensis)
White spruce (Picea glauca)Trembling aspen (Populus tremuloides)American beech (Fagus grandifolia)
Black spruce (Picea mariana) Red oak (Quercus rubra)
Red spruce (Picea rubens)
Jack pine (Pinus banksiana)
Red pine (Pinus resinosa)
White pine (Pinus strobus)
Eastern white Cedar (Thuja occidentalis)
Eastern hemlock (Tsuga canadensis)
Table
Table 2. Average annual carbon fluxes in kt CO2 eq. year−1 for the 2020–2120 period for conservation and ecosystem-based forest management in Maskinongé under three radiative forcing scenarios. Positive values indicate emissions to the atmosphere while negative values indicate a sequestration (removal) or emission avoidance.
Table 2. Average annual carbon fluxes in kt CO2 eq. year−1 for the 2020–2120 period for conservation and ecosystem-based forest management in Maskinongé under three radiative forcing scenarios. Positive values indicate emissions to the atmosphere while negative values indicate a sequestration (removal) or emission avoidance.
Carbon FluxesBaselineRCP 4.5RCP 8.5
ConservationForest ecosystems−97.434.399.3
Ecosystem-based forest managementForest ecosystems−231.1−68.222.7
Products200.6189.1185.5
Substitution−51.5−45.6−43.8
Table
Table 3. Average mitigation potential of ecosystem-based forest management in Maskinongé compared to the conservation scenario in kt CO2 eq. year−1 for the 2020–2120 period under different radiative forcing scenarios and assumptions related to wood products and their substitution effects. The potential is based on the difference in the sum of fluxes from forest ecosystems, degradation of wood products and their substitution effect on markets relative to conservation. Positive values indicate emissions to the atmosphere while negative values indicate a sequestration (removal) or emission avoidance.
Table 3. Average mitigation potential of ecosystem-based forest management in Maskinongé compared to the conservation scenario in kt CO2 eq. year−1 for the 2020–2120 period under different radiative forcing scenarios and assumptions related to wood products and their substitution effects. The potential is based on the difference in the sum of fluxes from forest ecosystems, degradation of wood products and their substitution effect on markets relative to conservation. Positive values indicate emissions to the atmosphere while negative values indicate a sequestration (removal) or emission avoidance.
Climate Projections
BaselineRCP 4.5RCP 8.5
Proportion of
Sawnwood →		LowerQuebec
average		HigherLowerQuebec
average		HigherLowerQuebec
average		Higher
Substitution
factors ↓
Lower80.936.343.797.959.526.5119.782.950.4
Quebec
average		73.215.4−26.990.840.9−1.9112.865.122.9
Higher67.1−1.3−51.485.126.1−24.6107.350.90.9
Note: The Quebec averages for the proportion of sawnwood and substitution factors were adapted from Beauregard, et al. [42]. The lower and higher proportions of sawnwood were calculated assuming that all harvested roundwood (irrespective of species) was processed according to the ‘intolerant hardwoods’ and ‘softwood’ baskets of wood products respectively, as illustrated in Figure 3. The lower and higher substitution factors were based on Smyth, et al. [47] and Leskinen, et al. [48], respectively.
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Landry, G.; Thiffault, E.; Cyr, D.; Moreau, L.; Boulanger, Y.; Dymond, C. Mitigation Potential of Ecosystem-Based Forest Management under Climate Change: A Case Study in the Boreal-Temperate Forest Ecotone. Forests 2021, 12, 1667. https://0-doi-org.brum.beds.ac.uk/10.3390/f12121667

AMA Style

Landry G, Thiffault E, Cyr D, Moreau L, Boulanger Y, Dymond C. Mitigation Potential of Ecosystem-Based Forest Management under Climate Change: A Case Study in the Boreal-Temperate Forest Ecotone. Forests. 2021; 12(12):1667. https://0-doi-org.brum.beds.ac.uk/10.3390/f12121667

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Landry, Gabriel, Evelyne Thiffault, Dominic Cyr, Lucas Moreau, Yan Boulanger, and Caren Dymond. 2021. "Mitigation Potential of Ecosystem-Based Forest Management under Climate Change: A Case Study in the Boreal-Temperate Forest Ecotone" Forests 12, no. 12: 1667. https://0-doi-org.brum.beds.ac.uk/10.3390/f12121667

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