Boreal Tree Species Research Articles

Boreal tree species diversity increases with global warming but is reversed by extremes.

Tree species diversity is essential to sustaining stable forest ecosystem functioning. However, it remains unclear how boreal tree species diversity has changed in response to climate change and how it is associated with productivity and the temporal stability of boreal forest ecosystems. By combining 5,312 field observations and 55,560 Landsat images, here we develop a framework to estimate boreal tree species diversity (represented by the Shannon diversity index, H') for the years 2000, 2010 and 2020. We document an average increase in H' by 12% from 2000 to 2020 across the boreal forests. This increase accounts for 53% of all boreal forest areas and mainly occurs in the eastern forest-boreal transition region, the Okhotsk-Manchurian taiga and the Scandinavian-Russian taiga. Tree species diversity responds positively to increasing temperatures, but the relationship is weakened for higher temperature changes, and in areas of extreme warming (>0.065 °C yr-1), a negative impact on tree species diversity is found. We further show that the observed spatiotemporal increase in diversity is significantly associated with increased productivity and temporal stability of boreal forest biomass. Our results highlight climate-warming-driven increases in boreal tree species diversity that positively affect boreal ecosystem functioning but are countered in areas of extreme warming.

Band configurations and seasonality influence the predictions of common boreal tree species using UAS image data

Key messageData acquisition of remote sensing products is an essential component of modern forest inventories. The quality and properties of optical remote sensing data are further emphasised in tree species-specific inventories, where the discrimination of different tree species is based on differences in their spectral properties. Furthermore, phenology affects the spectral properties of both evergreen and deciduous trees through seasons. These confounding factors in both sensor configuration and timing of data acquisition can result in unexpectedly complicated situations if not taken into consideration. This paper examines how the timing of data acquisition and sensor properties influence the prediction of tree species proportions and volumes in a boreal forest area dominated by Norway spruce and Scots pine, with a smaller presence of deciduous trees.ContextThe effectiveness of remote sensing for vegetation mapping depends on the properties of the survey area, mapping objectives and sensor configuration.AimsThe objective of this study was to investigate the plot-level relationship between seasonality and different optical band configurations and prediction performance of common boreal tree species. The study was conducted on a 40-ha study area with a systematically sampled circular field plots.MethodsTree species proportions (0–1) and volumes (m3 ha−1) were predicted with repeated remote sensing data collections in three stages of the growing season: prior (spring), during (summer) and end (autumn). Sensor band configurations included conventional RGB and multispectral (MS). The importance of different wavelengths (red, green, blue, near-infrared and red-edge) and predictive performance of the different band configurations were analysed using zero–one-inflated beta regression and Gaussian process regression.ResultsPrediction errors of broadleaves were most affected by band configuration, MS data resulting in lower prediction errors in all seasons. The MS data exhibited slightly lower prediction errors with summer data acquisition compared to other seasons, whereas this period was found to be less suitable for RGB data.ConclusionThe MS data was found to be much less affected by seasonality than the RGB data. Spring was found to be the least optimal season to collect MS and RGB data for tree species-specific predictions.

Drivers of snag fall rates in Fennoscandian boreal forests

Abstract Persistence of standing dead trees (snags) is an important determinant for their role for biodiversity and dead wood associated carbon fluxes. How fast snags fall varies widely among species and regions and is further influenced by a variety of stand‐ and tree‐level factors. However, our understanding of this variation is fragmentary at best, partly due to lack of empirical data. Here, we took advantage of the accruing time series of snag observations in the Finnish, Norwegian and Swedish National Forest Inventories that have been followed in these programs since the mid‐1990s. We first harmonized observations from slightly different inventory protocols and then, using this harmonized dataset of ca. 43,000 observations that had a consistent 5‐year census interval, we modelled the probability of snags of the main boreal tree species Pinus sylvestris, Picea abies and Betula spp. falling, as a function of tree‐ and stand‐level variables, using Bayesian logistic regression modelling. The models were moderately good at predicting snags remaining standing or falling, with a correct classification rate ranging from 68% to 75% among species. In general, snag persistence increased with tree size and climatic wetness, and decreased with temperature sum, advancing stage of decay, site productivity and disturbance intensity (mainly harvesting). Synthesis and applications: The effect of harvesting demonstrates that an efficient avenue to increase the amount of snags in managed forests is protecting them during silvicultural operations. In the warmer future, negative relationship between snag persistence and temperature suggests decreasing the time snags remain standing and hence decreasing habitat availability for associated species. As decomposition rates generally increase after fall, decreasing snag persistence also implies substantially faster release of carbon from dead wood.

Factors limiting the potential range expansion of lodgepole pine in Interior Alaska.

Understanding the factors influencing species range limits is increasingly crucial in anticipating migrations due to human-caused climate change. In the boreal biome, ongoing climate change and the associated increases in the rate, size, and severity of disturbances may alter the distributions of boreal tree species. Notably, Interior Alaska lacks native pine, a biogeographical anomaly that carries implications for ecosystem structure and function. The current range of lodgepole pine (Pinus contorta var. latifolia) in the adjacent Yukon Territory may expand into Interior Alaska, particularly with human assistance. Evaluating the potential for pine expansion in Alaska requires testing constraints on range limits such as dispersal limitations, environmental tolerance limits, and positive or negative biotic interactions. In this study, we used field experiments with pine seeds and transplanted seedlings, complemented by model simulations, to assess the abiotic and biotic factors influencing lodgepole pine seedling establishment and growth after fire in Interior Alaska. We found that pine could successfully recruit, survive, grow, and reproduce across our broadly distributed network of experimental sites. Our results show that both mammalian herbivory and competition from native tree species are unlikely to constrain pine growth and that environmental conditions commonly found in Interior Alaska fall well within the tolerance limits for pine. If dispersal constraints are released, lodgepole pine could have a geographically expansive range in Alaska, and once established, its growth is sufficient to support pine-dominated stands. Given the impacts of lodgepole pine on ecosystem processes such as increases in timber production, carbon sequestration, landscape flammability, and reduced forage quality, natural or human-assisted migration of this species is likely to substantially alter responses of Alaskan forest ecosystems to climate change.

Future carbon sequestration potential in a widespread transcontinental boreal tree species: Standing genetic variation matters!

Climate change (CC) necessitates reforestation/afforestation programs to mitigate its impacts and maximize carbon sequestration. But comprehending how tree growth, a proxy for fitness and resilience, responds to CC is critical to maximize these programs' effectiveness. Variability in tree response to CC across populations can notably be influenced by the standing genetic variation encompassing both neutral and adaptive genetic diversity. Here, a framework is proposed to assess tree growth potential at the population scale while accounting for standing genetic variation. We applied this framework to black spruce (BS, Picea mariana [Mill] B.S.P.), with the objectives to (1) determine the key climate variables having impacted BS growth response from 1974 to 2019, (2) examine the relative roles of local adaptation and the phylogeographic structure in this response, and (3) project BS growth under two Shared Socioeconomic Pathways while taking standing genetic variation into account. We modeled growth using a machine learning algorithm trained with dendroecological and genetic data obtained from over 2600 trees (62 populations divided in three genetic clusters) in four 48-year-old common gardens, and simulated growth until year 2100 at the common garden locations. Our study revealed that high summer and autumn temperatures negatively impacted BS growth. As a consequence of warming, this species is projected to experience a decline in growth by the end of the century, suggesting maladaptation to anticipated CC and a potential threat to its carbon sequestration capacity. This being said, we observed a clear difference in response to CC within and among genetic clusters, with the western cluster being more impacted than the central and eastern clusters. Our results show that intraspecific genetic variation, notably associated with the phylogeographic structure, must be considered when estimating the response of widespread species to CC.

A study of annual tree-wise LiDAR intensity patterns of boreal species observed using a hyper-temporal laser scanning time series

This study introduces the annual tree-wise intensity patterns of three boreal tree species, silver birch (Betula pendula Roth.), Scots pine (Pinus sylvestris L.), and Norway spruce (P,icea abies H. Karst.), observed from a long-term hyper-temporal point cloud dataset collected with a permanent laser scanning (LiDAR) station. An annual LiDAR intensity pattern refers to the trend of variations of tree-wise calibrated LiDAR intensity values over the course of a year, primarily linked to species-specific phenological characteristics. Such pattern was discovered from hyper-temporal (76 observations between April 2020 and April 2021) high resolution (0.01 m 3D point spacing at 100 m distance) point cloud observations acquired using a single wavelength (1550 nm) static LiDAR system installed on a climate monitoring tower at the Hyytiälä forest research station in central Finland. A set of experiments was designed to explore the interactions among tree-wise calibrated LiDAR intensity, species, data quality, and observation dates. Thus, to provide practical suggestions for expectable accuracies of tree species classification using diverse types of LiDAR systems and data acquisition strategies. It was revealed that by combining high spatial resolution (up to 100,000 points/m2) with bi-weekly observations (two scans per week except winter period), the average tree species classification accuracy reaches 96.8% for the three boreal tree species in the study area, where the few misclassified cases are attributed to inaccurate individual tree segmentation. This suggests that the annual tree-wise LiDAR intensity patterns, which reflects the tree-wise phenological dynamics, are robust and species-specific. When the spatial resolution was reduced to 5 points/ m2, the average accuracy of species classification among the three studied species reached 85% when using bi-temporal data from spring and autumn. Our analysis further indicates that arranging data acquisition with a two-week variability in late autumn and late spring could yield higher accuracy in species classification. Furthermore, our study revealed the importance of subcanopy information for species classification, specifically in distinguishing different coniferous species. When limited to upper canopy data (as in simulated airborne LiDAR scenarios), achieving a tree species classification accuracy of over 80% required either high point density (e.g. 8000 points/m2) combined with bi-temporal collection in a year, or low point density (5 points/ m2) with a dense time series (e.g., 76 time points within a year), which showcased the possibility to compensate low spatial resolution with high temporal resolution, and vice versa, in capturing species-specific phenological characteristics of trees.

Simulations reveal variability in exposure to drier conditions during timing of budbreak for tree species of the mixedwood forests of Québec, Canada.

Due to climate change, the timing of budbreak is occurring earlier in temperate and boreal tree species. Since the warmer conditions also cause snow to melt earlier in the spring, the hypothesis that bud reactivation of tree species of the mixedwood forests of Québec would occur under drier conditions in the future and that species from the temperate forests with late budbreak would be most exposed to dry conditions was tested. The thermal-time bud phenology model was used to predict the timing of budbreak for early and late species using 300 and 500 growing degree-days as the threshold for the timing of budbreak. Climate data was obtained from four CMIP6 climate models from 1950-2100 for two socioeconomic pathways at two locations, one in the temperate forest and one in the boreal mixedwood forest. Using linear regressions, the anomaly, which results from the difference between the historical mean (1950-1980) and the yearly values in timing of budbreak was predicted by the anomaly in drought index (SPEI) per site, climate model, socioeconomic pathways, and species with early or late budbreak timing. Budbreak is expected to occur earlier in the future, whereas the temporal trends in SPEI remained weak during April and May. When paired with the anomalies in both timing of budbreak and drought index, analyses showed that budbreak could be expected to occur under drier conditions in the future. However, due to differences between climate models, it remains uncertain whether drought stress will begin earlier in the future.

Combination of Lidar Intensity and Texture Features Enable Accurate Prediction of Common Boreal Tree Species With Single Sensor UAS Data

Combination of Lidar Intensity and Texture Features Enable Accurate Prediction of Common Boreal Tree Species With Single Sensor UAS Data

UNSUPERVISED STATISTICAL APPROACH FOR TREE-LEVEL SEPARATION OF FOLIAGE AND NON-LEAF COMPONENTS FROM POINT CLOUDS

Abstract. Accurately classifying foliage and non-leaf components in point clouds is essential for remote sensing forest applications. Existing methods rely on radiometric attributes or local geometric features, often requiring time-consuming manual labelling. In this paper, we propose a statistical approach using flexible thresholds determined based on tree-level geometric features. Selected features (local anisotropy, curvature, linearity, first principal component, verticality, and sphericity) have shown robustness in earlier studies. Threshold values are identified as points of inflection in the fitted distributions for each tree. Our method requires only two parameters and was tested with manually labelled Terrestrial Laser Scanning (TLS) data and non-labeled data from an oblique and above canopy setup (Permanent LiDAR scanner setup). We tested two boreal tree species, Scots Pine, and silver birch, with 28 trees in total (14 trees for each species) using two data sources. Compared to two alternative methods (namely, fixed thresholding and CANUPO), our approach consistently outperforms in terms of recall. We achieved an average overall accuracy of 85%, recall of 88.5%, precision of 83%, and f1 score of 85%. Visually assessing oblique and above canopy results, our algorithm effectively captures tree structures. Our statistical approach provides an effective solution for foliage and non-leaf separation, with processing times of less than five minutes for individual tree point clouds containing up to 2 million points and no need for extensive manual labelling or parameter adjustments.

Predicting net growth rates in boreal forests using Landsat time series and permanent sample plot data

Abstract Increasing temperature and changes in water dynamics are bringing uncertainty regarding the future productivity of boreal forests, even in the absence of stand-replacing disturbances. There is accumulating evidence that water deficits caused by warmer summer temperatures are linked to decreases in the growth rate of boreal tree species in some regions. In this context, it is essential to provide forest professionals with a means of monitoring net forest growth rates in undisturbed areas and at the scale of a management unit in order to determine where and when changes in growth are taking place. This is challenging using conventional forest inventory approaches. In this study, we use Landsat time series and data from permanent sample plots (PSP) to develop spatially explicit estimates of annual net basal area growth at a 30-m spatial resolution for a forest management unit in Canada. An ordinary least square regression model was developed using data from 120 PSPs and validated on an independent set of 60 PSPs, with R2 values of 0.61 and 0.58, respectively. Applying the model over a 586 607-ha study area revealed considerable temporal and spatial variability in the predicted growth rates and their evolution through time. There was an overall decline in predicted growth rates over time, with this trend corroborated by the PSP data and attributed to the ageing demographics of the forests in the study area. This variability was related to forest development stage, species composition, and structural attributes derived from light detection and ranging (LiDAR). The information generated by the suggested approach can help to improve yield predictions, optimize rotation lengths, and allow for the identification of target areas where silvicultural interventions aimed at maintaining or enhancing growth could be conducted.

Plant–soil feedbacks among boreal forest species

Abstract Plant–microbial interactions in soils are considered to play a central role in regulating biodiversity in many global ecosystems. However, studies on plant–soil feedbacks (PSFs) and how these affect forest stand patterns in boreal regions are rare. We conducted a fully reciprocal PSF glasshouse experiment using four boreal tree species. Alnus glutinosa, Betula pendula, Picea abies and Pinus sylvestris seedlings were grown under controlled conditions in sterilised soil with or without soil inoculum collected under mature trees of each of the four species. Bacterial, fungal and oomycete communities in the rhizosphere were investigated using metabarcoding and correlated with differences in plant biomass. Alder grew best in conspecific soil, whereas birch grew equally well in all soil types. Pine and spruce grew best in heterospecific soil, particularly in soil from their successional predecessor. Ectomycorrhizal fungi (EMF) enhanced the growth of most seedlings, and Actinomycetota supported alder and birch growth and fungal plant pathogens hampered pine growth. Increased growth was linked to the ability of trees to recruit specific EMF and root‐associated fungi in heterospecific soils. Synthesis. This study experimentally examines the influence of root‐associated microbiota on the growth of boreal tree species. The observed plant–soil feedbacks mirror the successional patterns found in boreal forests, suggesting a possible contribution of soil microbiota to the successional progression. Species‐specific ectomycorrhizal fungi and a few bacteria rather than fungal plant pathogens or oomycetes seem to drive the feedbacks by promoting seedling growth in heterospecific soils.

Rapid migration of Mongolian oak into the southern Asian boreal forest.

The migration of trees induced by climatic warming has been observed at many alpine treelines and boreal-tundra ecotones, but the migration of temperate trees into southern boreal forest remains less well documented. We conducted a field investigation across an ecotone of temperate and boreal forests in northern Greater Khingan Mountains of northeast China. Our analysis demonstrates that Mongolian oak (Quercus mongolica), an important temperate tree species, has migrated rapidly into southern boreal forest in synchrony with significant climatic warming over the past century. The average rate of migration is estimated to be 12.0 ± 1.0 km decade-1 , being slightly slower than the movement of isotherms (14.7 ± 6.4 km decade-1 ). The migration rate of Mongolian oak is the highest observed among migratory temperate trees (average rate 4.0 ± 1.0 km decade-1 ) and significantly higher than the rates of tree migration at boreal-tundra ecotones (0.9 ± 0.4 km decade-1 ) and alpine treelines (0.004 ± 0.003 km decade-1 ). Compared with the coexisting dominant boreal tree species, Dahurian larch (Larix gmelinii), temperate Mongolian oak is observed to have significantly lower capacity for light acquisition, comparable water-use efficiency but stronger capacity to utilize nutrients especially the most limiting nutrient, nitrogen. In the context of climatic warming, and in addition to a high seed dispersal capacity and potential thermal niche differences, the advantage of nutrient utilization, reflected by foliar elementomes and stable nitrogen isotope ratios, is also likely a key mechanism for Mongolian oak to coexist with Dahurian larch and facilitate its migration toward boreal forest. These findings highlight a rapid deborealization of southern Asian boreal forest in response to climatic warming.

The Acadian Forest of New Brunswick in the 21st century: what shifting heat and water balance imply for future stand dynamics and management

Climate change is altering the dynamics of New Brunswick’s forests. To mitigate the effects of climate change, it is crucial to account for future uncertainties in climate projections and natural disturbance trajectories when designing forestry practices. This paper presents the projected changes in key climatic drivers for New Brunswick’s forests, examines the impacts of climate change on forest stand dynamics, and reviews adaptive silviculture tools for climate change adaptation. By 2071–2100, a projected 4–6 °C increase in mean annual temperature will lead to a 39%–77% rise in growing degree-days and a reduction in summer atmospheric water balance by 48–79 mm across New Brunswick. Foresters should anticipate a doubling of annual area burned, the northward migration of spruce budworm ( Choristoneura fumiferana (Clemens)), and the introduction of novel insects and diseases. Forest simulation models project a severe decline in boreal tree species abundance, including a 50% decline in balsam fir ( Abies balsamea (L.) Mill) and black spruce ( Picea mariana (Mill.) Britton et al.), offset by an increase in temperate species, notably red maple ( Acer rubrum L.; +200%) and American beech ( Fagus grandifolia Ehrh; +135%). Forests in the highlands and lowlands ecoregions, with 40%–50% and 15%–30% spruce and balsam fir composition, respectively, are particularly vulnerable. To limit climate change effects on forest values, foresters must prioritize climate resiliency in their management plans. Strategies should ensure the steady provision of forest goods and services under changing climatic conditions. Forest thinning enhances stand productivity and resilience, while shelterwood and two-age harvest balances timber production with diversity. Clearcutting, despite drawbacks, establishes younger, more vigorous forests with higher carbon sequestration potential. Assisted migration offers promise in helping threatened tree species adapt. Climate change will have a significant impact on New Brunswick’s forests, leading to changes in key climatic drivers, increased risks of disturbances, and a shift toward more temperate tree species. However, there are existing adaptation strategies available. It is crucial to consider future uncertainties when designing and evaluating forestry practices, as this is essential for mitigating the effects of climate change on forest values and ensuring the continued provision of forest goods and services over time.

Confounding effects of snow cover on remotely sensed vegetation indices of evergreen and deciduous trees: An experimental study.

Located at northern latitudes and subject to large seasonal temperature fluctuations, boreal forests are sensitive to the changing climate, with evidence for both increasing and decreasing productivity, depending upon conditions. Optical remote sensing of vegetation indices based on spectral reflectance offers a means of monitoring vegetation photosynthetic activity and provides a powerful tool for observing how boreal forests respond to changing environmental conditions. Reflectance-based remotely sensed optical signals at northern latitude or high-altitude regions are readily confounded by snow coverage, hampering applications of satellite-based vegetation indices in tracking vegetation productivity at large scales. Unraveling the effects of snow can be challenging from satellite data, particularly when validation data are lacking. In this study, we established an experimental system in Alberta, Canada including six boreal tree species, both evergreen and deciduous, to evaluate the confounding effects of snow on three vegetation indices: the normalized difference vegetation index (NDVI), the photochemical reflectance index (PRI), and the chlorophyll/carotenoid index (CCI), all used in tracking vegetation productivity for boreal forests. Our results revealed substantial impacts of snow on canopy reflectance and vegetation indices, expressed as increased albedo, decreased NDVI values and increased PRI and CCI values. These effects varied among species and functional groups (evergreen and deciduous) and different vegetation indices were affected differently, indicating contradictory, confounding effects of snow on these indices. In addition to snow effects, we evaluated the contribution of deciduous trees to vegetation indices in mixed stands of evergreen and deciduous species, which contribute to the observed relationship between greenness-based indices and ecosystem productivity of many evergreen-dominated forests that contain a deciduous component. Our results demonstrate confounding and interacting effects of snow and vegetation type on vegetation indices and illustrate the importance of explicitly considering snow effects in any global-scale photosynthesis monitoring efforts using remotely sensed vegetation indices.

Resurgence of warmth-demanding tree species and a common pending thermophilization in subalpine and northern boreal Sweden-an ecological signal of post-Little Ice Age climate improvement

Largely consistent with general predictions and earlier empirical studies, it appears that post-Little Ice Age climate warming has started to affect large-scale biogeographic patterns in northern Sweden. Long-term monitoring in subalpine and adjacent regions reveals sparse spread of broadleaved thermophilic tree species. Saplings of Quercus robur, Ulmus glabra, Acer platanoides, Alnus glutinosa and Betula pendula have responded to recent climate warming by jump-dispersal in the order of 50-300 km northwards and 500-800 m upwards, relative to their natural range limits. Consistent with treeline rise by boreal tree species, the thermophilies have reinvaded regions where they grew during the warmest phase of the Holocene, 9500-8000 years ago, but were subsequently extirpated by the Neoglacial cooling. Confined to the past 20 years or so, the unique observations of recent termophilies comply with background climate data, i.e. warming of all seasons. These results may contribute to more realistic vegetation models by stressing that the distributions of certain plant species are able to track climate warming without substantial migrational lag. Hitherto, vegetation and climate evolution appear to be well within the frames of natural dynamics during the postglacial era, although mechanisms may differ.

Sensitivity of Eurasian Rear-Edge Birch Populations to Regional Climate and Local Hydrological Conditions

South rear-edge populations of widely distributed temperate and boreal tree species such as birches (Betula pubescens and Betula pendula) are considered particularly vulnerable to climate warming, and at the same time, they constitute genetic reservoirs of drought-adapted ecotypes. Here, we compared radial growth patterns and responses to climate, river, or reservoir flows and a drought index of rear-edge (southernmost) populations (Toledo Mountains, central-southern Spain) with populations located in northern Spain of B. pubescens and B. pendula. Then, we performed a comparative analysis across Europe of B. pendula populations. The main climatic constraint of birch growth was a high summer water deficit, although the effect of local hydrological conditions was particularly important in rear-edge populations. We found declining growth trends in rear-edge stands dating from the early 21st century, related to decreasing water availability and increasing aridity. Our results also suggested distinct growth patterns and climate-growth associations of B. pendula across Europe that show how populations further south and in warmer locations were more sensitive to drought stress. Drought-induced growth decline can be exacerbated by local human land uses, leading to reduced river inflow, thus endangering birch populations at their southern distribution limit. Protection of threatened rear-edge birch populations requires adequate management of local water resources.

Seasonal, Monthly, Daily, and Diel Growth, and Water Status Dynamics of Balsam Fir in a Cold and Humid Boreal Environment

Despite new knowledge in recent years, our understanding of the phenology of wood formation for various species growing in different environments remains limited. To enhance our knowledge of the tree growth dynamics of boreal tree species, we investigated the average seasonal, monthly, daily, and diel patterns of tree growth and water status from 11 years of observations with the 15 min and 1.5 µm resolved stem radial size variation data of 12 balsam fir (Abies balsamea (L.) Mill.) trees growing in a cold and humid boreal environment. Growth only occurred above an air temperature threshold of 9–10 °C, and the maximal growth rate over the year (23–24 June) was synchronous with the maximal day length (20–21 June) and not with the maximal air temperature, which occurred on average about 2 weeks later (4–5 July). Tree growth was mostly restricted by air temperature and solar radiation under these cold and wet boreal conditions, but our results also highlight a turgor-driven growth mechanism. Diel dynamics reveal that tree growth is minimal during the day when the stem dehydrates, and higher past midnight when the stem is fully rehydrated. This pattern suggests that carbon assimilation through photosynthesis occurs primarily during the day, while energy production and carbon allocation to woody tissues occur primarily at night via cellular respiration. Overall, our results show that the temporal patterns of the growth and water status of balsam fir growing in cold and humid boreal environments are controlled by a set of environmental factors that influence various physiological processes and mechanisms, many of which still need to be documented.

Effect of soil warming on growth and physiology of aspen seedlings from Alberta, Canada

Boreal tree species are migrating northwards due to rising temperatures, and differences in heat tolerance can impact the range limits of boreal species. Soil warming may benefit tree growth by promoting root development, or harm growth by creating a high-stress environment, increasing root respiration rates. We assessed the impact of soil warming on the growth of 2-year-old trembling aspen seedlings from 10 families. These families originated from Peace River, in central Alberta, and Camrose, near the southern boreal fringe in Alberta, Canada. We correlated growth traits with climatic data from each region and analyzed the effect of soil warming on the gas exchange of seedlings from Camrose. Families from Peace River exhibited greater growth overall, regardless of warming treatment, while families from Camrose showed a positive growth response under soil warming. Camrose families exposed to soil warming showed greater total leaf area and total leaf biomass compared to those without warming. A Principal Component Analysis (PCA) showed that, regardless of region, some families displayed stronger positive responses and appeared better adapted to soil warming than others. The overall positive response of the Camrose families to soil warming suggests that they have the capacity to take advantage of warmer environmental conditions. Our results indicate regional growth differences in aspen families in Alberta and variation in performance between families within a region, indicating there is differential capacity within local populations to acclimate under rapid climate change.

Phenological assessment of transpiration: The stem-temp approach for determining start and end of season

Field-based assessment of transpiration phenology in boreal tree species is a significant challenge. Here we develop an objective approach that uses stem radius change and its correlation with sapwood temperature to determine the timing of phenological changes in transpiration in mixed evergreen species. We test the stem-temp approach using a five year stem-radius dataset from black spruce (Picea mariana) and jack pine (Pinus banksiana) trees in Saskatchewan (2016–2020). We further compare transpiration phenological transition dates from this approach with tower-based phenological assessment from green chromatic coordinate derived from phenocam images, eddy-covariance-derived evapotranspiration and carbon uptake, tower-based measurements of solar-induced chlorophyll fluorescence and snowmelt timing. The stem-temp approach identified the start and end of four key transpiration phenological phases: (i) the end of temperature-driven cycles indicating the start of biological activity, (ii) the onset of stem rehydration, (iii) the onset of transpiration, and (iv) the end of transpiration-driven cycles. The proposed method is thus useful for characterizing the timing of changes in transpiration phenology and provides information about distinct processes that cannot be assessed with canopy-level phenological measurements alone.

Phenotypic plasticity enables considerable acclimation to heat and drought in a cold-adapted boreal forest tree species

Increasing frequencies of severe heat waves and drought are expected to influence the composition and functioning of ecosystems globally. Our ability to predict and mitigate these impacts depends on our understanding of species- and age-specific responses to these stressors. To assess the adaptive capacity of balsam fir to climate change, a cold-adapted boreal tree species, we conducted a climate-controlled greenhouse experiment with four provenances originating from across the species biogeographic range, 12 temperature treatments ensuring a minimum of +11°C warming, and five drought treatment intensities. We found considerable acclimation to temperature and drought treatments across all provenances, with steady gains in biomass under temperatures well-beyond the “worst-case” (RCP 8.5) climate forcing scenario within the species natural range. Acclimation was supported by high phenotypic plasticity in root:shoot ratio (RSR) and photosynthesis, which were greatly increased with warming, but were not affected by drought. Our results suggest that regardless of the observed provenance variation, drought and heat are not limiting factors of the current-year balsam fir seedling growth, instead, these factors may be more impactful on later stages of regeneration or previously stressed individuals, thus highlighting the necessity of incorporating the factors of ontogeny and provenance origin in future research regarding plant and climate interactions.