Contrasting water-use strategies to climate warming in white birch and larch in a boreal permafrost region

The effects of rising atmospheric CO2 concentrations (Ca) with climate warming on intrinsic water-use efficiency and radial growth in boreal forests are still poorly understood. We measured tree-ring cellulose δ13C, δ18O, and tree-ring width in Larix dahurica (larch) and Betula platyphylla (white birch), and analyzed their relationships with climate variables in a boreal permafrost region of northeast China over past 68 years covering a pre-warming period (1951-1984; base period) and a warm period (1985-2018; warm period). We found that white birch but not larch significantly increased their radial growth over the warm period. The increased intrinsic water-use efficiency in both species was mainly driven by elevated Ca but not climate warming. White birch but not larch showed significantly positive correlations between tree-ring δ13C, δ18O and summer maximum temperature as well as vapor pressure deficit in the warm period, suggesting a strong stomatal response in the broad-leaved birch to temperature changes. The climate warming-induced radial growth enhancement in white birch is primarily associated with a conservative water-use strategy. In contrast, larch exhibits a profligate water-use strategy. It implies an advantage for white birch over larch in the warming permafrost regions.

Assembly and annotation of the black spruce genome provide insights on spruce phylogeny and evolution of stress response

Black spruce (Picea mariana [Mill.] B.S.P.) is a dominant conifer species in the North American boreal forest that plays important ecological and economic roles. Here, we present the first genome assembly of P. mariana with a reconstructed genome size of 18.3 Gbp and NG50 scaffold length of 36.0 kbp. A total of 66,332 protein-coding sequences were predicted in silico and annotated based on sequence homology. We analyzed the evolutionary relationships between P. mariana and 5 other spruces for which complete nuclear and organelle genome sequences were available. The phylogenetic tree estimated from mitochondrial genome sequences agrees with biogeography; specifically, P. mariana was strongly supported as a sister lineage to P. glauca and 3 other taxa found in western North America, followed by the European Picea abies. We obtained mixed topologies with weaker statistical support in phylogenetic trees estimated from nuclear and chloroplast genome sequences, indicative of ancient reticulate evolution affecting these 2 genomes. Clustering of protein-coding sequences from the 6 Picea taxa and 2 Pinus species resulted in 34,776 orthogroups, 560 of which appeared to be specific to P. mariana. Analysis of these specific orthogroups and dN/dS analysis of positive selection signatures for 497 single-copy orthogroups identified gene functions mostly related to plant development and stress response. The P. mariana genome assembly and annotation provides a valuable resource for forest genetics research and applications in this broadly distributed species, especially in relation to climate adaptation.

Linkage between growth phenology and climate-growth responses along landscape gradients in boreal forests

Boreal forests represent an important carbon sink and, therefore, significantly contribute to climate change mitigation. Tree-ring width series of boreal species reflect climate variation at the moment of tree-ring formation but also lagged climatic effects from dormancy preceding tree-ring formation and antecedent growing seasons. However, little is known about how the growth sensitivity to climate in specific intra-annual periods varies across the landscape. Here, we assessed growth responses to climate variation during the 45 months preceding the tree-ring formation for nine boreal stands of Picea glauca and Picea mariana distributed along the gradients of elevation and slope aspect. We combined process-based modeling of wood formation and remote sensing data to determine growth phenology at each site. Next, we classified intra-annual seasons with significant climate-growth correlations based on the timing of dormancy and growth periods. Both the phenology and the climate-growth relationships systematically shifted with elevation and, to a lower extent, also with slope orientation at the treeline. The mean duration of the growing season varied between 100 days at treelines above 900 m and 160 days at lowlands below 500 m. The growth at treelines was stimulated by temperature in the summer of the tree-ring formation year and two years before tree-ring formation. The period of significant climate-growth correlations during the current summer did not exceed three months in agreement with the local duration of the growing season. The growth of trees in lower elevations was instead stimulated by high temperature during the dormancy periods but restricted by high temperature in antecedent summer seasons. In conclusion, our study highlights the linkage between the timing of climate-growth sensitivity and growth phenology, primarily determined by proximity to the treeline. Consequently, accounting for landscape gradients in growth phenology is crucial for upscaling the climatic limits of boreal stands' growth as climate change progresses.

Applying space-for-time substitution to infer the growth response to climate may lead to overestimation of tree maladaptation: Evidence from the North American White Spruce Network

Under climate change circumstances, increasing studies have reported the temporal instability of tree growth responses to climate, which poses a major challenge to linearly extrapolating past climate and future growth dynamics using tree-ring data. Space-for-time substitution (SFTS) is a potential solution to this problem that is widely used in the dendrochronology field to project past or future temporal growth response trajectories from contemporary spatial patterns. However, the projected accuracy of the SFTS in the climate effects on tree growth remains uncertain. Here, we empirically test the SFTS method by comparing the effect of spatial and temporal climate variations on climate responses of white spruce (Picea glauca), which has a transcontinental range in North America. We first applied a response surface regression model to capture the variations in growth responses along the spatial climate gradients. The results showed that the relationships between growth and June temperature varied along spatial climate gradients in a predictable way. And their relationships varied mainly along with local temperate condition. Then, the projected correlation coefficients between growth and climate using SFTS were compared against the observed. We found that the growth response changes caused by spatial versus temporal climate variations showed opposite trends. Moreover, the projected correlation coefficients using the SFTS were significantly lower than the observed. This finding suggests that applying the SFTS to project the growth response of white spruce might lead to an overestimation of the degree of tree maladaptation in future climate scenarios. And the overestimation is likely to get weaker from Alaska and Yukon Territory in the west to Quebec in the east. Although this is only a case study of the SFTS method for projecting tree growth response, our findings suggest that direct application of the SFTS method may not be applicable to all regions and all tree species.

Bridging implementation gaps to connect large ecological datasets and complex models

Merging robust statistical methods with complex simulation models is a frontier for improving ecological inference and forecasting. However, bringing these tools together is not always straightforward. Matching data with model output, determining starting conditions, and addressing high dimensionality are some of the complexities that arise when attempting to incorporate ecological field data with mechanistic models directly using sophisticated statistical methods. To illustrate these complexities and pragmatic paths forward, we present an analysis using tree-ring basal area reconstructions in Denali National Park (DNPP) to constrain successional trajectories of two spruce species (Picea mariana and Picea glauca) simulated by a forest gap model, University of Virginia Forest Model Enhanced-UVAFME. Through this process, we provide preliminary ecological inference about the long-term competitive dynamics between slow-growing P. mariana and relatively faster-growing P. glauca. Incorporating tree-ring data into UVAFME allowed us to estimate a bias correction for stand age with improved parameter estimates. We found that higher parameter values for P. mariana minimum growth under stress and P. glauca maximum growth rate were key to improving simulations of coexistence, agreeing with recent research that faster-growing P. glauca may outcompete P. mariana under climate change scenarios. The implementation challenges we highlight are a crucial part of the conversation for how to bring models together with data to improve ecological inference and forecasting.

Fine Root Growth of Black Spruce Trees and Understory Plants in a Permafrost Forest Along a North-Facing Slope in Interior Alaska

Permafrost forests play an important role in the global carbon budget due to the huge amounts of carbon stored below ground in these ecosystems. Although fine roots are considered to be a major pathway of belowground carbon flux, separate contributions of overstory trees and understory shrubs to fine root dynamics in these forests have not been specifically characterized in relation to permafrost conditions, such as active layer thickness. In this study, we investigated fine root growth and morphology of trees and understory shrubs using ingrowth cores with two types of moss substrates (feather- and Sphagnum mosses) in permafrost black spruce (Picea mariana) stands along a north-facing slope in Interior Alaska, where active layer thickness varied substantially. Aboveground biomass, litterfall production rate, and fine root mass were also examined. Results showed that aboveground biomass, fine root mass, and fine root growth of black spruce trees tended to decrease downslope, whereas those of understory Ericaceae shrubs increased. Belowground allocation (e.g., ratio of fine root growth/leaf litter production) increased downslope in both of black spruce and understory plants. These results suggested that, at a lower slope, belowground resource availability was lower than at upper slope, but higher light availability under open canopy seemed to benefit the growth of the understory shrubs. On the other hand, understory shrubs were more responsive to the moss substrates than black spruce, in which Sphagnum moss substrates increased fine root growth of the shrubs as compared with feather moss substrates, whereas the effect was unclear for black spruce. This is probably due to higher moisture contents in Sphagnum moss substrates, which benefited the growth of small diameter (high specific root length) fine roots of understory shrubs. Hence, the contribution of understory shrubs to fine root growth was greater at lower slope than at upper slope, or in Sphagnum than in feather-moss substrates in our study site. Taken together, our data show that fine roots of Ericaceae shrubs are a key component in belowground carbon flux at permafrost black spruce forests with shallow active layer and/or with Sphagnum dominated forest floor.