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Boakye, E. A., Mvolo, C. S., and Stewart, J. (2023). “Systematic review: Climate and non-climate factors influencing wood density in the boreal zone,” BioResources 18(4), 8757-8770.

Abstract

Wood density is a crucial factor in determining the quality of wood in boreal ecosystems within the Northern Hemisphere. Climate variables play a significant role in shaping wood density, posing challenges for forest managers and stakeholders in the wood industry to adapt amidst climate change. However, our current understanding of these effects remains incomplete. This systematic literature review explores the multifaceted influences on wood density in the boreal zone, encompassing both climate-related and non-climatic factors. The findings demonstrate that warmer temperatures can cause both increases and decreases in wood density, primarily due to their impact on tracheid lignification and cell wall thickening. Nonetheless, the outcome depends on various factors, including species type, age, soil conditions, presence of pests and diseases, fire, windstorms, and silviculture practices. The quantification of complex relationships between these factors and wood density has been insufficient in existing literature. Understanding the impacts of both climate and non-climate factors on wood density is essential for fostering a sustainable wood industry, while effectively mitigating adverse effects and maximizing benefits. Forest managers can leverage this knowledge to optimize wood production strategies, ensuring long-term ecological resilience amidst the increasingly variable climate challenges.


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Systematic Review: Climate and Non-Climate Factors Influencing Wood Density in the Boreal Zone

Emmanuel A. Boakye,a,* Cyriac S. Mvolo,b and Jim Stewart b

Wood density is a crucial factor in determining the quality of wood in boreal ecosystems within the Northern Hemisphere. Climate variables play a significant role in shaping wood density, posing challenges for forest managers and stakeholders in the wood industry to adapt amidst climate change. However, our current understanding of these effects remains incomplete. This systematic literature review explores the multifaceted influences on wood density in the boreal zone, encompassing both climate-related and non-climatic factors. The findings demonstrate that warmer temperatures can cause both increases and decreases in wood density, primarily due to their impact on tracheid lignification and cell wall thickening. Nonetheless, the outcome depends on various factors, including species type, age, soil conditions, presence of pests and diseases, fire, windstorms, and silviculture practices. The quantification of complex relationships between these factors and wood density has been insufficient in existing literature. Understanding the impacts of both climate and non-climate factors on wood density is essential for fostering a sustainable wood industry, while effectively mitigating adverse effects and maximizing benefits. Forest managers can leverage this knowledge to optimize wood production strategies, ensuring long-term ecological resilience amidst the increasingly variable climate challenges.

DOI: 10.15376/biores.18.4.Boakye

Keywords: Wood density; Wood formation; Tree growth; Climate change; Non-climate factors; Boreal zone

Contact information: a: Département des Sciences Biologiques, Université du Québec à Montréal, Montréal Québec, H2X 3Y7, Canada; b: Natural Resources Canada, Canadian Forest Service, Canadian Wood Fibre Centre, Edmonton, AB T6H-3S5, Canada;

* Corresponding author: emmanuelamoah.boakye@uqat.ca; eaaboakye@yahoo.com

INTRODUCTION

The Boreal Zone (BZ) forms a ring around the North Pole and lies immediately south of the Arctic Circle, encircling the Northern Hemisphere (Brandt 2009; Gauthier et al. 2015). This region experiences long, cold winters and short, warm summers. It includes parts of Canada, USA, Norway, Sweden, Finland, Russia, and China (Gauthier et al. 2015). The BZ is renowned for its abundant biodiversity, with its forests providing habitats for diverse fauna. The region includes not only forested areas but also other types of woodland and treeless regions, such as alpine regions on mountains, heathlands in maritime regions, grasslands in drier areas, and wetlands (Brandt 2009; Gauthier et al. 2015). The tree species composition of the BZ forests varies depending on the specific location within the zone. In general, coniferous trees make up approximately 70% to 80% of the tree population (Brandt 2009; Gauthier et al. 2015).

The Boreal Zone covers 17% of the earth’s land surface and is crucial for the Earth’s ecosystem, as it holds more than 30% of all carbon present in terrestrial biomes (Kasischke 2000; Bradshaw et al. 2009). The BZ stores a total of approximately 1095 Pg of carbon, with most of it residing in the soils, peatlands, and forests (Bradshaw and Warkentin, 2015). Additionally, the BZ is essential to the global timber products market, with approximately 33% of lumber and 25% of paper exports originating from the boreal forest (Brecka et al. 2018). However, the region is currently facing threats from climate change, which may impact the health of the forest and the quality of wood production (Camarero and Gutiérrez 2017).

Climate change has a profound impact on wood production in boreal ecosystems. Rising temperatures have led to increased precipitation and longer growing seasons (Price et al. 2013), resulting in earlier primary growth such as shooting, leafing, and flowering, as well as enhanced secondary growth such as earlier xylem cell production and differentiation (Rossi et al. 2007; Lasserre et al. 2009; Zhai et al. 2012; Hember et al. 2017; Boakye et al. 2021). However, the benefits of climate change can be eroded due to the increased risk of disturbances such as pests, diseases, and extreme weather events (D’Orangeville et al. 2018; Venäläinen et al. 2020; Boakye et al. 2022, 2023). Furthermore, warmer temperatures have caused drought stress, leading to decreased tree growth and mortality (Hogg et al. 2008; Nabais et al. 2018; Venäläinen et al. 2020). As the pace of climate change accelerates, it is imperative for forest managers to adapt their management strategies to sustain wood production.

Wood quality attributes (WQA) refer to the characteristics of wood that influence its suitability for a particular end use. These attributes are primarily determined by cambium activity, also known as xylogenesis (Mvolo et al. 2019; Zhang et al. 2020). Of the various WQA, wood density is critical, since it affects the wood’s strength, durability, and workability (Rathgeber et al. 2006; Romagnoli et al. 2014) in addition to its weight, which can have broad applications. Moreover, wood density is closely linked to the amount of water that wood can absorb, which in turn affects its resistance to insect damage and decay (Huang et al. 2003). Therefore, comprehending the impacts of climate change on wood density is essential for mitigating any adverse effects on wood quality, which is a key factor in the success of the wood industry.

Wood density is influenced by several factors beyond just climate (Watt et al. 2008). These factors include the species of the tree, which is related to its genetics (Rozenberg and Cahalan 1997), the tree’s age (Gryc et al. 2011), the growing conditions of the soil (Wieruszewski and Mydlarz 2021), the topography of the area (Rossi et al. 2015), inter-tree competition (Pretzsch and Rais 2016), disturbances from pests (Brecka et al. 2018; Camarero, 2022), windstorms (Sanginés de Cárcer et al. 2021), wildfires (McCullough et al. 1998), and management practices (Peng and Stewart 2013). For instance, the density of a tree’s wood can vary widely depending on its genetic traits. This is because the genetic makeup of a tree influences the size, shape, and chemical composition of its wood cells, which affects the density of the wood (Peltola et al. 2009; Soro et al. 2022).

The growing conditions of the tree, such as soil fertility, water availability, and sunlight exposure, also have a significant impact on its wood density (Giroud et al. 2017; Bouslimi et al. 2022). Trees that grow in warmer locations with more sunlight and water generally produce denser wood. Conversely, trees that grow in cooler climates with less sunlight and water tend to produce less dense wood (Camarero and Gutiérrez 2017). Additionally, the fertility and moisture levels of the soil are also important factors in wood density. Wood density is influenced by changes in soil fertility, which can affect tree growth rates, ultimately impacting the accumulation and tightening of wood fibers (Cao et al. 2008).

In recent years, significant progress has been made in comprehending the influence of both climate change and non-climatic factors on the boreal zone. Nonetheless, most of the reviews in this field have been primarily centered around the effects of climate change on forest health, ecosystem functioning, forestry adaptation practices, and the overall carbon balance of the forest (Gauthier et al. 2015; Brecka et al. 2018; Triviño et al. 2022), with less attention given to wood quality (Zhang et al. 2020). There has not been a comprehensive synthesis of the impact of both climate and non-climatic factors on wood density and its effects on the production of quality wood. The objectives of this review are to integrate existing research on the impact of climate and non-climatic factors on wood density and to assess the implications of these findings for the future impacts of climate change. The apparent focus on conifers in this review is a reflection of the predominance of coniferous species over deciduous ones in the BZ forests and in the studies reported in the literature.

COMPILATION OF REVIEW STRATEGY

Systematic searches of peer-reviewed publications were conducted in three electronic databases (Scopus, ScienceDirect, and Google Scholar) from 1985 to 2023 to ensure the accessibility and inclusion of all relevant publications related to climate change and wood density in the boreal zone. The searches consisted of two steps. Firstly, to generate the most comprehensive list of relevant studies possible, specific keywords were used: (“climate change”) AND (“disturbance” OR “biotic” OR “abiotic”) AND (“management”) AND (“wood quality” OR “wood density”) AND (“Boreal zone” OR “Boreal forest” OR “Taiga” OR “Conifer” OR “Deciduous”). These keywords were selected based on their relevance to the research topic. The second search was similar to the first, but specific terms for climate change and wood quality were used to minimize the number of articles excluded and to ensure a thorough investigation of the available literature.

After the removal of duplicates, 66,900 studies were identified, of which 66,600 were excluded based on titles and abstracts. Further assessment excluded 219 studies due to a lack of relevant wood quality and climate assessments, leaving a final selection of 81 studies. In the following sections, the findings based on reviewing of both climate and non-climate factors and their effect on wood density, as well as the implications of these findings to management are discussed. Moreover, the importance of understanding the effects of climate on wood density and the need for further research are emphasized.

FINDINGS

Climate and Wood Density

Climate exerts a significant influence on the characteristics of wood density, including cell count, size, and cell wall thickness (Wang et al. 2002; Rossi et al. 2008; Lenz et al. 2010; Sattler et al. 2016; Sun et al. 2016). Maximum wood density displays a strong correlation with warm seasonal temperatures in various tree species, such as Picea mariana (Mill.) B.S.P. (black spruce), Picea glauca (Moench) Voss (white spruce), Pinus banksiana Lamb. (jack pine) (Kilpeläinen et al. 2003; Düthorn et al. 2015), Pseudotsuga menziesii (Mirbel) Franco (Douglas fir) (Filipescu et al. 2014), and Larix sibirica Ledeb. (Siberian larch) (Chen et al. 2012). Both earlywood density and latewood density of black spruce are positively correlated with summer temperature (Wang et al. 2002). Warmer conditions enhance the lignification of tracheids and thickening of cell walls, resulting in higher wood density (Gindl et al. 2001). Conversely, elevated temperatures and water deficits during summers may cause a decrease in jack pine wood density in eastern Canada due to reduced photosynthesis (Savva et al. 2010). Moreover, Camarero and Gutiérrez (2017) reported a reduction in maximum wood density during colder weather in the late growing season, attributable to decreased lignification and thickening rates of latewood tracheids. Nevertheless, the impact of climate on wood density is complex and species-dependent, with varying responses observed (Franceschini et al. 2013; Ramage et al. 2017; Harvey et al. 2020).

Species and Wood Density

Wood density differs substantially among tree species, which can be attributed to the influence of tree genetics on growth patterns, as demonstrated by various studies (Zhang et al. 2003; Lenz et al. 2010; Peltola et al. 2009; Soro et al. 2022), including investigations conducted on jack pine and white spruce in Eastern Canada (Savva et al. 2010). Throughout their growth, trees exhibit a wide range of densities due to variations in the compaction and thickness of cell walls, as well as the presence of air-filled vessels (Huang et al. 2003; Van Leeuwen et al. 2011). Interestingly, these variations in wood density are observed across both broad-leaved and coniferous species. Giroud et al. (2017) ranked the dominant boreal tree species in terms of average wood density, revealing the following descending order: Betula papyrifera Marshall (white birch) (575 kg/m3), black spruce (481 kg/m3), jack pine (469 kg/m3), Populus tremuloides Michx. (trembling aspen) (459 kg/m3), white spruce (431 kg/m3), and Abies balsamea (L.) P. Mill. (Balsam fir) (403 kg/m3).

Tree Aging and Wood Density

The variation in wood density follows a radial pattern, which is typically indicated by the number of annual rings counted from the pith outward. This measurement is referred to as the cambial age of the ring (Plomion et al. 2001; Mvolo et al. 2022). These radial trends assist in classifying wood into two categories: juvenile wood and mature wood zones. Juvenile wood generally forms within the first 15 to 20 years, while mature wood forms later (Zobel and Sprague 1998; Plomion et al. 2001).

While not all of these species are native to the boreal region, some boreal species such as Eastern hemlock (Tsuga canadensis (L.) Carrière), eastern larch (Larix laricina (Du Roi) K. Koch), as well as temperate species such as western larch (Larix occidentalis Nutt.), southern hard pines (subgenus Pinus, the diploxylon) including longleaf (Pinus palustris Mill.), and slash (Pinus elliottii Engelm.) pine, juvenile wood exhibits lower density than mature wood (Schimleck et al. 2022) due to its larger lumens, thinner cell walls, and lower lignification (Zobel and Sprague 1998; Plomion et al. 2001; Mansfield et al. 2009).

As a tree grows and ages, its wood fibers become more compressed and tightly packed within a given volume, and the cell walls thicken, resulting in higher density in mature wood (Park et al. 2009; Sillett et al. 2010; Mvolo et al. 2022). However, exceptions to this phenomenon exist due to species-specific genetic and anatomical characteristics, as well as site-specific environmental factors that influence tree growth. For example, in the case of white spruce (Mvolo et al. 2022) and jack pine (Park et al. 2009; Savva et al. 2010), juvenile wood tends to have higher density than mature wood. Koubaa et al. (2005) and Alteyrac et al. (2006) investigated the radial variation in wood density with cambial age and found that in black spruce, wood density is high near the pith but decreases significantly with increasing cambial age up to 10 years of tree growth. Schimleck et al. (2022) observed a similar trend in various tree species, including jack pine, red pine, the western hard pines, western hemlock, the genera Pseudotsuga, Picea, and Abies. In these species, wood density is initially high at the pith, decreases during the first few years, and then increases as cambial age continues to advance.

A few species such as Atlantic white cedar (Chamaecyparis thyoides (L.) BSP), bald cypress (Taxodium distichum (L.) Rich.), and eastern red cedar (Juniperus virginiana L.) exhibit a general decrease of wood density with the aging of the tree (Schimleck et al. 2022).

Overall, the juvenile wood zone exhibits significant variability. Rings closer to the pith can display both very high and very low density. However, they generally have wider ring widths due to their proximity to the living crown during xylogenesis. Consequently, these wider rings during the first 1 to 3 years have minimal impact on bulk wood density, particularly considering the long lifetime of trees in the BZ.

Soil and Wood Density

Nitrogen, phosphorus, and potassium are essential for tree growth and development. Increasing temperatures in the northern boreal forest are accelerating chemical reactions that release these nutrients, thus increasing the growth of trees and microbial populations. However, increasing soil nutrient addition has been linked to decreased wood density in Norway spruce (Cao et al. 2008). Increasing nutrient availability leads to increased tree growth rates, which results in less dense wood. Furthermore, higher temperatures in the southern boreal forest are increasing evaporation of soil moisture, making the soil more prone to droughts. The consequence of this is increased stress, stunted growth, and decreased wood density of tree species (Nearing et al. 2004; Giroud et al. 2017; Pugnaire et al. 2019; Bouslimi et al. 2022). Additionally, topographical variation causes individual trees to differ in wood density, as terrain slope, aspect, and altitude all modify the availability of light, moisture, and nutrients for growth (Rossi et al. 2015).

Pests and Disease and Wood Density

Pests can have varying effects on wood bulk density due to their distinct feeding habits and behaviors. For example, insects such as beetles tunnel into wood to lay their eggs and larvae, weakening the structure and reducing wood density. Termites, on the other hand, feed on wood’s cellulose and lignin, leading to a deterioration in density (McCullough et al. 1998; Brecka et al. 2018). Wood borers also cause physical damage by chewing on the surface, further reducing density. In live trees, pests damage the tree by consuming sapwood and heartwood, resulting in a decrease in density. In dead trees, pests consume softer wood, such as sapwood, which reduces density. Additionally, dead wood is more prone to decay, further lowering wood density (Jacobs and Work 2012).

Infectious diseases can significantly impact wood density, leading to slower growth, structural damage, and premature death. Fungal infections can cause trees to allocate more resources to defense mechanisms, reducing the available resources for growth and resulting in lower wood density (Brecka et al. 2008). Fungal root rot can reduce a tree’s ability to absorb water and nutrients, resulting in slower growth and lower wood density (Koricheva et al. 2006). For instance, brown rot decay in eastern white cedar (Thuja occidentalis L.) selectively removes structural carbohydrate components, leading to an increase in the lignin/carbohydrate ratio as decay progresses. This process causes more significant density changes in earlywood compared to latewood tracheids (Bouslimi et al. 2014). However, the brown-rot effect on decreasing wood density is less pronounced than that of its counterpart, white-root fungus, especially in spruce trees (Reinprecht et al. 2007).

Windstorm and Wood Density

Changes in wood density occur due to the formation of reaction wood in response to wind disturbance. This specialized wood, namely compression wood and tension wood, helps trees adapt and maintain their structural integrity (Sanginés de Cárcer et al. 2021). Compression wood is predominantly found in conifers, whereas tension wood is predominantly found in broadleaf trees. This distinction arises from the varying structural needs and growth patterns exhibited by these two types of trees (Schweingruber et al. 2018). Compression wood develops on the lower side of branches or leaning stems, becoming denser and stiffer than normal wood. It contains higher lignin content, smaller cell lumens, and thicker cell walls. This wood provides support against compressive stress caused by wind and gravity. On the other hand, tension wood forms on the upper side, exhibiting less density but greater flexibility. It has higher cellulose content, larger cell lumens, and thinner cell walls. Tension wood absorbs and dissipates tensile forces induced by wind, preventing breakage (Sanginés de Cárcer et al. 2021; Potterf et al. 2022). The changes in wood density associated with compression wood and tension wood enable trees to balance the effects of wind disturbance. Compression wood supports the compressed side, while tension wood counters tensile stress on the opposite side. This adaptive mechanism helps trees withstand wind-induced stresses and ensures their growth and survival in varying environmental conditions (Potterf et al. 2022).

Wildfire and Wood Density

Wildfires significantly impact wood density by causing physical changes in its structure (Bravo 2010). A study analyzed post-fire scars on North American conifers to understand the effects of fire on wood density (Arbellay et al. 2014). The findings revealed that Douglas fir (Pseudotsuga menziesii), western larch (Larix occidentalis), and ponderosa pine (Pinus ponderosa) species experienced the strongest impact on wood density within the first year after fire injury. Tracheid density increased by 21% to 53% for these species, while Douglas fir and western larch also exhibited a rise in ray density by 19% to 36%. The increased density of tracheids is linked to ethylene synthesis, which occurs as a response to fire-induced injuries and interferes with auxins flow during tracheid formation. On the other hand, ponderosa pine generally did not display an increase in ray tissue (radial parenchyma) after fire injury. Changes in ray density vary not only among species of different genera but also among species within the same genus.

Silviculture Practices and Wood Density

Silvicultural practices, such as thinning and spacing, have a direct impact on wood density by regulating the growth conditions of trees (Mörling 2002). Thinning improves the wood density of individual trees by promoting their growth rate through decreased competition (Zhai et al. 2012; Diao et al. 2022). However, despite the initial increase, thinning has been observed to decrease wood density in Quebec black spruce stands (Vincent et al. 2011) and jack pine stands in New Brunswick, Canada (Schneider et al. 2008). Excessive thinning diminishes the wood density of Norway spruce as it accelerates growth rates, resulting in a shorter duration for tracheid lignification (Cao et al. 2008).

Although low-intensity spacing, characterized by widely spaced trees, is advocated for reducing establishment costs and accelerating the diameter growth of individual trees, a study by Zhang et al. (2021) observed that such low spacing intensity actually reduces wood density in black spruce. However, Mvolo et al. (2022) found that except for extreme spacing, increasing the spacing intensity had no effect on wood density in white spruce. Silvicultural effects on wood density in lodgepole pine were relatively small and mostly masked by random variation at the tree level (Peng and Stewart 2013). These findings suggest that the impact of spacing on wood density is variable and dependent on the tree species. Silvicultural practices can have both positive and negative impacts on wood density, which are influenced by management objectives, tree species, and local environmental conditions.

Implications to Wood Industry

The enhancement of wood density can be achieved through various management implications, considering both climate-related and non-climatic factors. It is crucial to select suitable tree species based on local climate and soil conditions to achieve higher wood density. Additionally, silvicultural practices, such as thinning and spacing management, play a key role in optimizing wood density by ensuring trees have sufficient resources and reduced competition. Furthermore, genetic selection of tree varieties with higher wood density traits can provide advantages for future generations. By managing forests with different age classes, it becomes possible to optimize wood density variation, utilizing juvenile wood with lower density for specific applications and mature wood with higher density for others.

Adapting management strategies to climate change impacts involves altering rotations, adjusting planting times, and considering resilient species. Furthermore, the adoption of proper harvesting techniques plays a crucial role in preventing tree damage and mitigating factors that reduce wood density, thereby preserving structural integrity. Continuous monitoring of forest health and wood quality is vital for identifying emerging issues and adapting practices accordingly. Additionally, investing in research and technology to understand wood density relationships with climate and other factors facilitates informed decision-making for sustainable wood quality improvement. By implementing these implications, wood density can be enhanced, leading to valuable and sustainable timber resources.

Summary of Future Directions

Understanding the complex relationship between climate and non-climate factors is crucial for comprehending the impact of climate change on wood density in boreal ecosystems. Wood density serves as a significant indicator of forest health and productivity, making it necessary to unravel the multiple influencing factors. Climate change directly affects wood density through temperature and precipitation pattern alterations. Tree genetics, aging, soil condition, pest and disease infestations, windstorms, wildfires, and silvicultural practices also substantially shape wood density. By delving into the intricate interactions between these factors, researchers and policymakers can formulate effective strategies to mitigate climate change’s adverse effects on boreal ecosystems. Identifying genetic traits that enhance wood density resilience, implementing sustainable silvicultural practices, and developing resilient forest management approaches can help maintain healthy and productive forests amidst changing climate conditions. Ultimately, a comprehensive understanding of both climate and non-climate drivers of wood density will inform policies and practices, fostering the long-term sustainability of boreal ecosystems in a changing climate.

REFERENCES CITED

Alteyrac, J., Cloutier, A., and Zhang S. Y. (2006). “Characterization of juvenile wood to mature wood transition age in black spruce (Picea mariana (Mill) B.S.P) at different stand densities and sampling heights,” Wood Science and Technology 40(2), 124-138. DOI: 10.1007/s00226-005-0047-4

Arbellay, E., Stoffel, M., Sutherland, E. K., Smith, K. T., and Falk, D. A. (2014). “Changes in tracheid and ray traits in fire scars of North American conifers and their ecophysiological implications,” Annals of Botany 114(2), 223-232. DOI: 10.1093/aob/mcu112

Boakye, E.A., Bergeron, Y., Drobyshev, I., Beekharry, A., Voyer, D., Achim, A., Huang, J.G., Grondind, P., Bédard, S., Havreljukd, F., Gennarettib, F., and Girardin, M.P. (2023). “Recent decline in sugar maple (Acer saccharum Marsh.) growth extends to the northern parts of its distribution range in eastern Canada,” Forest Ecology and Management 545, article 121304. DOI: 10.1016/j.foreco.2023.121304

Boakye, E.A., Houle, D., Bergeron, Y., Girardin, M.P., and Drobyshev, I. (2022). “Insect defoliation modulates influence of climate on the growth of tree species in the boreal mixed forests of eastern Canada,” Ecology and Evolution 12, 3. DOI: 10.1002/ece3.8656

Boakye, E. A., Bergeron, Y., Girardin, M. P., and Drobyshev, I. (2021). “Contrasting growth response of jack pine and trembling aspen to climate warming in Quebec mixed woods forests of eastern Canada since the early twentieth century,” Journal of Geophysical Research: Biogeosciences 126(5), article e2020JG005873. DOI: 10.1029/2020JG005873

Bouslimi, B., Koubaa, A., and Bergeron, Y. (2022). “Regional, site, and tree variations of wood density and growth in Thuja occidentalis L. in the Quebec Forest,” Forests 13(12), article 1984. DOI: 10.3390/f13121984

Bouslimi, B., Koubaa, A., and Bergeron, Y. (2014). “Effects of biodegradation by brown-rot decay on selected wood properties in eastern white cedar (Thuja occidentalis L.),” International Biodeterioration and Biodegradation 87, 87-98. DOI: 10.1016/j.ibiod.2013.11.006

Bradshaw, C. J., and Warkentin, I. G. (2015). “Global estimates of boreal forest carbon stocks and flux,” Global and Planetary Change 128, 24-30. DOI: 10.1016/j.gloplacha.2015.02.004

Bradshaw, C. J., Warkentin, I. G., and Sodhi, N. S. (2009). “Urgent preservation of boreal carbon stocks and biodiversity,” Trends in Ecology and Evolution 24(10), 541-548. DOI: 10.1016/j.tree.2009.03.019

Bravo, S. (2010). “Anatomical changes induced by fire-damaged cambium in two native tree species of the Chaco region, Argentina,” IAWA journal 31(3), 283-292. DOI: 10.1163/22941932-90000023

Brecka, A. F., Shahi, C., and Chen, H. Y. (2018). “Climate change impacts on boreal forest timber supply,” Forest Policy and Economics 92, 11-21. DOI: 10.1016/j.forpol.2018.03.010

Brandt, J. P. (2009). “The extent of the North American boreal zone,” Environmental Reviews 17, 101-161. DOI: 10.1139/A09-004

Camarero, J. J. (2022). “Wood density as a proxy of drought-induced forest dieback in silver fir,” Dendrochronologia, article 126027. DOI: 10.1016/j.dendro.2022.126027

Camarero, J. J., and Gutiérrez, E. (2017). “Wood density of silver fir reflects drought and cold stress across climatic and biogeographic gradients,” Dendrochronologia 45, 101-112. DOI: 10.1016/j.dendro.2017.07.005

Cao, T., Valsta, L., Härkönen, S., Saranpää, P., and Mäkelä, A. (2008). “Effects of thinning and fertilization on wood properties and economic returns for Norway spruce,” Forest Ecology and Management 256(6), 1280-1289. DOI: 10.1016/j.foreco.2008.06.025

Chen, F., Yuan, Y. J., Wei, W. S., Fan, Z. A., Zhang, T. W., Shang, H. M., Zhang, R.-B., Yu, S.-L., Ji, C.-R., and Qin, L. (2012). “Climatic response of ring width and maximum latewood density of Larix sibirica in the Altay Mountains, reveals recent warming trends,” Annals of Forest Science 69(6), 723-733. DOI: 10.1007/s13595-012-0187-2

Diao, S., Sun, H., Forrester, D. I., Soares, A. A., Protásio, T. P., and Jiang, J. (2022). “Variation in growth, wood density, and stem taper along the stem in self-thinning stands of Sassafras tzumu,” Frontiers in Plant Science 13, article 853968. DOI: 10.3389/fpls.2022.853968

D’Orangeville, L., Houle, D., Duchesne, L., Phillips, R. P., Bergeron, Y., and Kneeshaw, D. (2018). “Beneficial effects of climate warming on boreal tree growth may be transitory,” Nature Communications 9(1), 3213. DOI: 10.1038/s41467-018-05705-4

Düthorn, E., Schneider, L., Günther, B., Gläser, S., and Esper, J. (2016). “Ecological and climatological signals in tree-ring width and density chronologies along a latitudinal boreal transect,” Scandinavian Journal of Forest Research 31(8), 750-757. DOI: 10.1080/02827581.2016.1181201

Filipescu, C. N., Lowell, E. C., Koppenaal, R., and Mitchell, A. K. (2014). “Modeling regional and climatic variation of wood density and ring width in intensively managed Douglas-fir,” Canadian Journal of Forest Research 44(3), 220-229. DOI: 10.1139/cjfr-2013-027

Franceschini, T., Bontemps, J. D., Perez, V., and Leban, J. M. (2013). “Divergence in latewood density response of Norway spruce to temperature is not resolved by enlarged sets of climatic predictors and their non-linearities,” Agricultural and Forest Meteorology 180, 132-141. DOI: 10.1016/j.agrformet.2013.05.011

Gauthier, S., Bernier, P., Kuuluvainen, T., Shvidenko, A. Z., and Schepaschenko, D. G. (2015). “Boreal forest health and global change,” Science 349(6250), 819-822. DOI: 10.1126/science.aaa90

Gindl, W., Grabner, M., and Wimmer, R. (2001). “Effects of altitude on tracheid differentiation and lignification of Norway spruce,” Canadian Journal of Botany 79(7), 815-821. DOI: 10.1139/b01-060

Giroud, G., Bégin, J., Defo, M., and Ung, C. H. (2017). “Regional variation in wood density and modulus of elasticity of Quebec’s main boreal tree species,” Forest Ecology and Management 400, 289-299. DOI: 10.1016/j.foreco.2017.06.019

Gryc, V., Vavrčík, H., and Horn, K. (2011). “Density of juvenile and mature wood of selected coniferous species,” Journal of Forest Science 57(3), 123-130. DOI: 10.17221/18/2010-JFS

Harvey, J. E., Smiljanić, M., Scharnweber, T., Buras, A., Cedro, A., Cruz‐García, R., …, and Wilmking, M. (2020). “Tree growth influenced by warming winter climate and summer moisture availability in northern temperate forests,” Global Change Biology 26(4), 2505-2518. DOI: 10.1111/gcb.14966

Hember, R. A., Kurz, W. A., and Coops, N. C. (2017). “Increasing net ecosystem biomass production of Canada’s boreal and temperate forests despite decline in dry climates,” Global Biogeochemical Cycles 31, 134-158. DOI: 10.1002/2016GB005459

Hogg, E. H., Brandt, J. P., and Michaelian, M. (2008). “Impacts of a regional drought on the productivity, dieback, and biomass of western Canadian aspen forests,” Canadian Journal of Forest Research 38, 1373-1384. DOI: 10.1139/X08-001

Huang, C. L., Lindström, H., Nakada, R., and Ralston, J. (2003). “Cell wall structure and wood properties determined by acoustics—A selective review,” Holz als Roh-und Werkstoff 61, 321-335. DOI: 10.1007/s00107-003-0398-1

Jacobs, J. M., and Work, T. T. (2012). “Linking deadwood-associated beetles and fungi with wood decomposition rates in managed black spruce forests,” Canadian Journal of Forest Research 42(8), 1477-1490. DOI: 10.1139/x2012-075

Kasischke, E. S. (2000). “Boreal ecosystems in the global carbon cycle,” in: Fire, Climate Change, and Carbon Cycling in the Boreal Forest, E. S. Kasischke, and B. J. Stocks (eds.), Ecological Studies, Vol. 138. Springer, New York, NY. DOI: 10.1007/978-0-387-21629-4_2

Kilpeläinen, A., Peltola, H., Ryyppö, A., Sauvala, K., Laitinen, K., and Kellomäki, S. (2003). “Wood properties of Scots pines (Pinus sylvestris) grown at elevated temperature and carbon dioxide concentration,” Tree Physiology 23(13), 889-897. DOI: 10.1093/treephys/23.13.889

Koubaa, A., Isabel, N., Zhang, S. Y., and Beaulieu, J. (2005). “Transition from juvenile to mature wood in black spruce (Picea mariana (Mill) B.S.P),” Wood Fiber Science 37(3), 445-455.

Koricheva, J., Vehviläinen, H., Riihimäki, J., Ruohomäki, K., Kaitaniemi, P., and Ranta, H. (2006). “Diversification of tree stands as a means to manage pests and diseases in boreal forests: myth or reality?,” Canadian Journal of Forest Research 36(2), 324-336. DOI: 10.1139/x05-172

Lasserre, J. P., Mason, E. G., Watt, M. S., and Moore, J. R. (2009). “Influence of initial planting spacing and genotype on microfibril angle, wood density, fibre properties and modulus of elasticity in Pinus radiata D. Don core wood,” Forest Ecology and Management 258(9), 1924-1931. DOI: 10.1016/j.foreco.2009.07.028

Lenz, P., Cloutier, A., MacKay, J., and Beaulieu, J. (2010). “Genetic control of wood properties in Picea glauca—an analysis of trends with cambial age,” Canadian Journal of Forest Research 40(4), 703-715. DOI: 10.1139/X10-014

Mansfield, S. D., Parish, R., Di Lucca, C. M., Goudie, J., Kang, K.-Y., and Ott, P. (2009). “Revisiting the transition between juvenile and mature wood: a comparison of fibre length, microfibril angle and relative wood density in lodgepole pine,” Holzforschung 63(4), 449-456. DOI: 10.1515/HF.2009.069

McCullough, D. G., Werner, R. A., and Neumann, D. (1998). “Fire and insects in northern and boreal forest ecosystems of North America,” Annual Review of Entomology 43(1), 107-127. DOI: 10.1146/annurev.ento.43.1.107

Mvolo, C. S., Goudiaby, V., Koubaa, A., and Stewart, J. D. (2022). “Influence of four spacings between trees and four samplings heights on selected wood quality attributes of white spruce (Picea glauca (Moench) Voss),” Forests 13(11), article 1807. DOI: 10.3390/f13111807

Mvolo, C. S., Koubaa, A., Beaulieu, J., Cloutier, A., Defo, M., and Yemele, M. C. (2019). “Phenotypic correlations among growth and selected wood properties in white spruce (Picea glauca (Moench) Voss),” Forests 10(7), article 589. DOI: 10.3390/f10070589

Mörling, T. (2002). “Evaluation of annual ring width and ring density development following fertilisation and thinning of Scots pine,” Annals of Forest Science 59(1), 29-40. DOI: 10.1051/forest:2001003

Nabais, C., Hansen, J. K., David-Schwartz, R., Klisz, M., Lopez, R., and Rozenberg, P. (2018). “The effect of climate on wood density: What provenance trials tell us?,” Forest Ecology and Management 408, 148-156. DOI: 10.1016/j.foreco.2017.10.040

Nearing, M. A., Pruski, F. F., and O’neal, M. R. (2004). “Expected climate change impacts on soil erosion rates: a review,” Journal of Soil and Water Conservation 59(1), 43-50.

Park, Y. I. D., Koubaa, A., Brais, S., and Mazerolle, M. J. (2009). “Effects of cambial age and stem height on wood density and growth of jack pine grown in boreal stands,” Wood and Fiber Science 41(4), 346-358.

Peltola, H., Gort, J., Pulkkinen, P., Zubizarreta Gerendiain, A., Karppinen, J., and Ikonen, V. P. (2009). “Differences in growth and wood density traits in Scots pine (Pinus sylvestris L.) genetic entries grown at different spacing and sites,” Silva Fennica 43(3), 339-354.

Peng, M., and Stewart, J. D. (2013). “Development, validation, and application of a model of intra- and inter-tree variability of wood density for lodgepole pine in western Canada,” Canadian Journal of Forest Research 43, 1172-1180. DOI: 10.1139/cjfr-2013-0208

Plomion, C., Leprovost, G., and Stokes, A. (2001). “Wood formation in trees,” Plant Physiology 127(4), 1513-1523. DOI: 10.1104/pp.010816

Potterf, M., Eyvindson, K., Blattert, C., Burgas, D., Burner, R., Stephan, J. G., and Mönkkönen, M. (2022). “Interpreting wind damage risk–How multifunctional forest management impacts standing timber at risk of wind felling,” European Journal of Forest Research 141(2), 347-361. DOI: 10.1007/s10342-022-01442-y

Pretzsch, H., and Rais, A. (2016). “Wood quality in complex forests versus even-aged monocultures: Review and perspectives,” Wood Science and Technology 50, 845-880. DOI: 10.1007/s00226-016-0827-z

Price, D. T., Alfaro, R. I., Brown, K. J., Flannigan, M. D., Fleming, R. A., Hogg, E. H., Girardin, M. P., Lakusta, T., Johnston, M., McKenney, D. W, et al. (2013). “Anticipating the consequences of climate change for Canada’s boreal forest ecosystems,” Environmental Reviews 21(4), 322-365. DOI: 10.1139/er-2013-0042

Pugnaire, F. I., Morillo, J. A., Peñuelas, J., Reich, P. B., Bardgett, R. D., Gaxiola, A., Wardle, D. A., and Van Der Putten, W. H. (2019). “Climate change effects on plant-soil feedbacks and consequences for biodiversity and functioning of terrestrial ecosystems,” Science Advances 5(11), article eaaz1834. DOI: 10.1126/sciadv.aaz1834

Ramage, M. H., Burridge, H., Busse-Wicher, M., Fereday, G., Reynolds, T., Shah, D. U., Wu, G., Yu, L., Fleming, P., Densley-Tingley, D., et al. (2017). “The wood from the trees: The use of timber in construction,” Renewable and Sustainable Energy Reviews 68, 333-359. DOI: 10.1016/j.rser.2016.09.107

Rathgeber, C. B., Decoux, V., and Leban, J. M. (2006). “Linking intra-tree-ring wood density variations and tracheid anatomical characteristics in Douglas fir (Pseudotsuga menziesii (Mirb.) Franco),” Annals of Forest Science 63(7), 699-706. DOI: 10.1051/forest:2006050

Reinprecht, L., Novotná, H., and Štefka, V. (2007). “Density profiles of spruce wood changed by brown-rot and white-rot fungi,” Wood Research 52(4), 17-28.

Romagnoli, M., Cavalli, D., and Spina, S. (2014). “Wood quality of chestnut: Relationship between ring width, specific gravity, and physical and mechanical properties,” BioResources 9(1), 1132-1147. DOI: 10.15376/biores.9.1.1132-1147

Rossi, S., Cairo, E., Krause, C., and Deslauriers, A. (2015). “Growth and basic wood properties of black spruce along an alti-latitudinal gradient in Quebec, Canada,” Annals of Forest Science 72, 77-87. DOI: 10.1007/s13595-014-0399-8

Rossi, S., Deslauriers, A., Griçar, J., Seo, J.-W., Rathgeber, C.B., Anfodillo, T., Morin, H., Levanic, T., Oven, P., and Jalkanen, R. (2008). “Critical temperatures for xylogenesis in conifers of cold climates,” Global Ecology and Biogeography 17, 696-707. DOI: 10.1111/j.1466-8238.2008.00417.x

Rossi, S., Deslauriers, A., Anfodillo, T., and Carraro, V. (2007). “Evidence of threshold temperatures for xylogenesis in conifers at high altitudes,” Oecologia 152, 1-12. DOI: 10.1007/s00442-006-0625-7

Rozenberg, P., and Cahalan, C. H. (1997). “Spruce and wood quality: Genetic aspects (A review),” Silvae Genetica 46(5), 270-279.

Sattler, D. F., and Stewart, J. D. (2016). “Climate, location, and growth relationships with wood stiffness at the site, tree, and ring levels in white spruce (Picea glauca) in the Boreal Plains ecozone,” Canadian Journal of Forest Research 46(10), 1235-1245. DOI: 10.1139/cjfr-2015-0480

Sanginés de Cárcer, P., Mederski, P. S., Magagnotti, N., Spinelli, R., Engler, B., Seidl, R., Eriksson, A., Eggers, J., Bont, L. G., and Schweier, J. (2021). “The management response to wind disturbances in European forests,” Current Forestry Reports 7, 167-180. DOI: 10.1007/s40725-021-00144-9

Savva, Y., Koubaa, A., Tremblay, F. (2010). “Effects of radial growth, tree age, climate, and seed origin on wood density of diverse jack pine populations,” Trees 24, 53-65. DOI: 10.1007/s00468-009-0378-0

Schimleck, L. R., Dahlen, J., and Auty, D. (2022). “Radial patterns of specific gravity variation in North American conifers,” Canadian Journal of Forest Research 52(6), 889-900. DOI: 10.1139/cjfr-2021-0338

Schneider, R., Zhang, S. Y., Swift, D. E., Begin, J., and Lussier, J. M. (2008). “Predicting selected wood properties of jack pine following commercial thinning,” Canadian Journal of Forest Research 38(7), 2030-2043. DOI: 10.1139/X08-03

Schweingruber, F. H., Börner, A., Schweingruber, F. H., and Börner, A. (2018). “Anatomical adaptations to temporarily changed environmental conditions,” The Plant Stem: A Microscopic Aspect 141-168. DOI: 10.1007/978-3-319-73524-5_10

Sillett, S. C., Van Pelt, R., Koch, G. W., Ambrose, A. R., Carroll, A. L., Antoine, M. E., and Mifsud, B. M. (2010). “Increasing wood production through old age in tall trees,” Forest Ecology and Management 259(5), 976-994. DOI: 10.1016/j.foreco.2009.12.003

Soro, A., Lenz, P., Hassegawa, M., Roussel, J. R., Bousquet, J., and Achim, A. (2022). “Genetic influence on components of wood density variation in white spruce,” Forestry 95(2), 153-165. DOI: 10.1093/forestry/cpab044

Sun, Y., Wang, L., and Yin, H. (2016). “Influence of climatic factors on tree-ring maximum latewood density of Picea schrenkiana in Xinjiang, China,” Frontiers of Earth Science 10, 126-134. DOI: 10.1007/s11707-015-0507-6

Triviño, M., Morán‐Ordoñez, A., Eyvindson, K., Blattert, C., Burgas, D., Repo, A., …, and Mönkkönen, M. (2022). “Future supply of boreal forest ecosystem services is driven by management rather than by climate change,” Global Change Biology. DOI: 10.1111/gcb.16566

Van Leeuwen, M., Hilker, T., Coops, N. C., Frazer, G., Wulder, M. A., Newnham, G. J., and Culvenor, D. S. (2011). “Assessment of standing wood and fiber quality using ground and airborne laser scanning: A review,” Forest Ecology and Management 261(9), 1467-1478.

Venäläinen, A., Lehtonen, I., Laapas, M., Ruosteenoja, K., Tikkanen, O. P., Viiri, H., Ikonen, V.-P., and Peltola, H. (2020). “Climate change induces multiple risks to boreal forests and forestry in Finland: A literature review,” Global Change Biology 26(8), 4178-4196. DOI: 10.1016/j.foreco.2011.01.032

Vincent, M., Krause, C., and Koubaa, A. (2011). “Variation in black spruce (Picea mariana (Mill.) BSP) wood quality after thinning,” Annals of Forest Science 68, 1115. DOI: 10.1007/s13595-011-0127-6

Wang, L., Payette, S., and Bégin, Y. (2002). “Relationships between anatomical and densitometric characteristics of black spruce and summer temperature at tree line in northern Quebec,” Canadian Journal of Forest Research 32(3), 477-486. DOI: 10.1139/x01-208

Watt, M. S., Clinton, P. W., Coker, G., Davis, M. R., Simcock, R., Parfitt, R. L., and Dando, J. (2008). “Modelling the influence of environment and stand characteristics on basic density and modulus of elasticity for young Pinus radiata and Cupressus lusitanica,” Forest Ecology and Management 255(3-4), 1023-1033. DOI: 10.1016/j.foreco.2007.09.086

Wieruszewski, M., and Mydlarz, K. (2021). “The influence of habitat conditions on the properties of pinewood,” Forests 12(10), article 1311. DOI: 10.3390/f12101311

Yang, K. C., and Hazenberg, G. (1994). “Impact of spacing on tracheid length, relative density, and growth rate of juvenile wood and mature wood in Picea mariana,” Canadian Journal of Forest Research 24(5), 996-1007. DOI: 10.1139/x94-130

Zhai, L., Bergeron, Y., Huang, J. G., and Berninger, F. (2012). “Variation in intra‐annual wood formation, and foliage and shoot development of three major Canadian boreal tree species,” American Journal of Botany 99(5), 827-837. DOI: 10.3732/ajb.1100235

Zhang, S. Y., Ren, H., and Jiang, Z. (2021). “Wood density and wood shrinkage in relation to initial spacing and tree growth in black spruce (Picea mariana),” Journal of Wood Science 67, 1-10. DOI: 10.1186/s10086-021-01965-9

Zhang, S., Belien, E., Ren, H., Rossi, S., and Huang, J. G. (2020). “Wood anatomy of boreal species in a warming world: A review,” iForest-Biogeosciences and Forestry 13(2), 130. DOI: 10.3832/ifor3230-013

Zhang, S. Y., Yu, Q., Chauret, G., and Koubaa, A. (2003). “Selection for both growth and wood properties in hybrid poplar clones,” Forest Science 49(6), 901-908. DOI: 10.1093/forestscience/49.6.901

Zobel, B. J., and Sprague, J. R. (1998). Juvenile Wood in Forest Trees, Springer Science and Business Media.

Article submitted: August 11, 2023; Peer review completed: September 16, 2023; Revised version received: September 27, 2023; Published: October 4, 2023.

DOI: 10.15376/biores.18.4.Boakye