Abstract. Global forest assessments assist climate policy development, ecosystem science, and conservation planning, yet they rely on biomass and canopy data that do not explicitly represent the stand structural attributes derived from tree diameter measurements. This limits the ability to compare size-related structure and within-stand heterogeneity at large spatial scales. Here we present a global, spatially explicit dataset of stand-level tree diameter structure for forest cover in 2020 at 0.027° (~3 km) resolution, based on 1,203,524 georeferenced forest inventory plots comprising 54.6 million trees (≥10 cm DBH) integrated with more than 50 environmental and satellite-derived covariates into machine learning models. The dataset provides the first globally consistent maps of three complementary diameter-based metrics: arithmetic mean diameter (Dmean), quadratic mean diameter (Dqm), and the coefficient of variation of diameter (Dcv), representing average tree size, large-tree dominance, and within-stand size variability, respectively. Model performance of the ecozone-specific Random Forest framework ranged from R² = 0.41–0.82 (RMSE = 3.91–4.63 cm) for Dmean, R² = 0.43–0.83 (RMSE = 4.38–5.27 cm) for Dqm, and R² = 0.47–0.62 with (RMSE = 0.10–0.13) for Dcv across different forest ecozones. By jointly quantifying central tendency and variability in tree size, the dataset revealed spatial patterns of forest structural organization not captured by existing biomass or canopy-height products. It provides a consistent baseline for cross-biome comparison of forest structure, supporting parameterization and evaluation of vegetation and Earth system models, while offering an independent benchmark for remotely sensed structural proxies. Furthermore, it enables spatial assessment of stand structural attributes, including large-tree dominance and structural complexity, facilitating integration of diameter-based structure into global analyses of carbon dynamics and ecosystem functioning.

Species' traits and environmental conditions determine the abundance of tree species across the globe. The extent to which traits of dominant and rare tree species differ remains untested across a broad environmental range, limiting our understanding of how species traits and the environment shape forest functional composition. We use a global dataset of tree composition of >22,000 forest plots and 11 traits of 1663 tree species to ask how locally dominant and rare species differ in their trait values, and how these differences are driven by climatic gradients in temperature and water availability in forest biomes across the globe. We find three consistent trait differences between locally dominant and rare species across all biomes; dominant species are taller, have softer wood and higher loading on the multivariate stem strategy axis (related to narrow tracheids and thick bark). The difference between traits of dominant and rare species is more strongly driven by temperature compared to water availability, as temperature might affect a larger number of traits. Therefore, climate change driven global temperature rise may have a strong effect on trait differences between dominant and rare tree species and may lead to changes in species abundances and therefore strong community reassembly.

Unraveling the mechanisms underlying the maintenance of species diversity is a central pursuit in ecology. It has been hypothesized that ectomycorrhizal (EcM) in contrast to arbuscular mycorrhizal fungi can reduce tree species diversity in local communities, which remains to be tested at the global scale. To address this gap, we analyzed global forest inventory data and revealed that the relationship between tree species richness and EcM tree proportion varied along environmental gradients. Specifically, the relationship is more negative at low latitudes and in moist conditions but is unimodal at high latitudes and in arid conditions. The negative association of EcM tree proportion on species diversity at low latitudes and in humid conditions is likely due to more negative plant-soil microbial interactions in these regions. These findings extend our knowledge on the mechanisms shaping global patterns in plant species diversity from a belowground view.

AimTo determine the relationships between the functional trait composition of forest communities and environmental gradients across scales and biomes and the role of species relative abundances in these relationships.LocationGlobal.Time periodRecent.Major taxa studiedTrees.MethodsWe integrated species abundance records from worldwide forest inventories and associated functional traits (wood density, specific leaf area and seed mass) to obtain a data set of 99,953 to 149,285 plots (depending on the trait) spanning all forested continents. We computed community-weighted and unweighted means of trait values for each plot and related them to three broad environmental gradients and their interactions (energy availability, precipitation and soil properties) at two scales (global and biomes).ResultsOur models explained up to 60% of the variance in trait distribution. At global scale, the energy gradient had the strongest influence on traits. However, within-biome models revealed different relationships among biomes. Notably, the functional composition of tropical forests was more influenced by precipitation and soil properties than energy availability, whereas temperate forests showed the opposite pattern. Depending on the trait studied, response to gradients was more variable and proportionally weaker in boreal forests. Community unweighted means were better predicted than weighted means for almost all models.Main conclusionsWorldwide, trees require a large amount of energy (following latitude) to produce dense wood and seeds, while leaves with large surface to weight ratios are concentrated in temperate forests. However, patterns of functional composition within-biome differ from global patterns due to biome specificities such as the presence of conifers or unique combinations of climatic and soil properties. We recommend assessing the sensitivity of tree functional traits to environmental changes in their geographic context. Furthermore, at a given site, the distribution of tree functional traits appears to be driven more by species presence than species abundance.

AimEcological and anthropogenic factors shift the abundances of dominant and rare tree species within local forest communities, thus affecting species composition and ecosystem functioning. To inform forest and conservation management it is important to understand the drivers of dominance and rarity in local tree communities. We answer the following research questions: (1) What are the patterns of dominance and rarity in tree communities? (2) Which ecological and anthropogenic factors predict these patterns? And (3) what is the extinction risk of locally dominant and rare tree species?LocationGlobal.Time period1990-2017.Major taxa studiedTrees.MethodsWe used 1.2 million forest plots and quantified local tree dominance as the relative plot basal area of the single most dominant species and local rarity as the percentage of species that contribute together to the least 10% of plot basal area. We mapped global community dominance and rarity using machine learning models and evaluated the ecological and anthropogenic predictors with linear models. Extinction risk, for example threatened status, of geographically widespread dominant and rare species was evaluated.ResultsCommunity dominance and rarity show contrasting latitudinal trends, with boreal forests having high levels of dominance and tropical forests having high levels of rarity. Increasing annual precipitation reduces community dominance, probably because precipitation is related to an increase in tree density and richness. Additionally, stand age is positively related to community dominance, due to stem diameter increase of the most dominant species. Surprisingly, we find that locally dominant and rare species, which are geographically widespread in our data, have an equally high rate of elevated extinction due to declining populations through large-scale land degradation.Main conclusionsBy linking patterns and predictors of community dominance and rarity to extinction risk, our results suggest that also widespread species should be considered in large-scale management and conservation practices.

The density of wood is a key indicator of the carbon investment strategies of trees, impacting productivity and carbon storage. Despite its importance, the global variation in wood density and its environmental controls remain poorly understood, preventing accurate predictions of global forest carbon stocks. Here we analyse information from 1.1million forest inventory plots alongside wood density data from 10,703 tree species to create a spatially explicit understanding of the global wood density distribution and its drivers. Our findings reveal a pronounced latitudinal gradient, with wood in tropical forests being up to 30% denser than that in boreal forests. In both angiosperms and gymnosperms, hydrothermal conditions represented by annual mean temperature and soil moisture emerged as the primary factors influencing the variation in wood density globally. This indicates similar environmental filters and evolutionary adaptations among distinct plant groups, underscoring the essential role of abiotic factors in determining wood density in forest ecosystems. Additionally, our study highlights the prominent role of disturbance, such as human modification and fire risk, in influencing wood density at more local scales. Factoring in the spatial variation of wood density notably changes the estimates of forest carbon stocks, leading to differences of up to 21% within biomes. Therefore, our research contributes to a deeper understanding of terrestrial biomass distribution and how environmental changes and disturbances impact forest ecosystems.

The density of wood is a key indicator of trees’ carbon investment strategies, impacting productivity and carbon storage. Despite its importance, the global variation in wood density and its environmental controls remain poorly understood, preventing accurate predictions of global forest carbon stocks. Here, we analyze information from 1.1 million forest inventory plots alongside wood density data from 10,703 tree species to create a spatially-explicit understanding of the global wood density distribution and its drivers. Our findings reveal a pronounced latitudinal gradient, with wood in tropical dry forests being up to twice as dense as that in boreal forests. In both angiosperms and gymnosperms, temperature and water availability emerged as the primary factors influencing the variation in wood density globally. This indicates similar environmental filters and evolutionary adaptations among distinct plant groups, underscoring the essential role of abiotic factors in determining wood density in forest ecosystems. Additionally, our study highlights the prominent role of disturbance, such as human modification and fire risk, in influencing wood density at more local scales. Factoring in the spatial variation of wood density notably changes the estimates of forest carbon stocks, leading to differences of up to 21% within biomes. Therefore, our research contributes to a deeper understanding of terrestrial biomass distribution and how environmental changes and disturbances impact forest ecosystems.

Research highlights: At the turn of the 21st century, there were more forest territories found disturbed by both natural processes (climate change, wildfires, insect outbreaks, permafrost thawing, etc.) and anthropogenic interferences (air pollution, clearcuts, etc.). Seed collecting, then growing seedlings in forest nurseries, and then planting seedlings over lost forest areas are the forestry measures needed to restore the forest after disturbances. Goals were to construct bioclimatic models of ranges and seed mass of major Siberian conifers (Siberian pine (Pinus sibirica Du Tour), Siberian fir (Abies sibirica Ledeb.), Siberian spruce (Picea obovata Ledeb.), Siberian larches (Larix sibirica Ledeb., L. gmelini (Rupr) Rupr, and L. cajanderi Mayr.) and Pinus sylvestris L.) and predict their potential change in a warming climate by the mid-century. Methods: Multi-year seed mass data were derived from the literature, seed station data, and were collected in the field. Climate data (January and July data and annual precipitation) were derived from published Russian reference books and websites on climate. Bioclimatic indices (growing degree-days > 5 C, negative degree-days < 0 C, and annual moisture index) were calculated from January and July temperatures and annual precipitation for both contemporary and the 2050s (2040–2060) climates using the general circulation model INM-CM5-0 and two climate change scenarios, ssp126 and ssp585, from CMIP6. Our bioclimatic range models (envelope and MaxEnt models) and regression seed mass models for major conifers were built based on these bioclimatic indices. Additionally, their ranges were limited by the permafrost border, which divided the forest area into the permafrost-free zone, where five conifers are able to grow, and the permafrost zone, where only one conifer, Dahurian larch, is able to survive. Results: Under warmed climates, the ranges of all Siberian conifers would expand 1.5-fold due to the decrease in the permafrost zone, except Dahurian larch, which would lose 5–20% of its coverage due to permafrost retreat. Conifers shifting northward would be slower than predicted only by warmed climates because permafrost would thaw slower than climates would warm. Scots pine may expand by up to 60%, covering dryer lands in the south. Future climates were found to favor seed mass increase for major Siberian conifers and for heavier seed to shift northward. Our major conifers differ by the type of seed dispersal mode: zoochoric, animal (Siberian pine) and anemochoric, and wind-dispersed (other five trees). The seed masses of the five anemochoric conifers varied within the range of 1.5–15 g of 1000 seeds, which is about 40–50-fold less than that of zoochoric Siberian pine. Site climate explained about 28–65% of the seed mass variation for the five anemochoric trees and only 11% for Siberian pine (zoochoric tree). This finding needs additional research to explain the reasons. Conclusions: Warmed climates would favor the expansion of the ranges of major Siberian conifers and their seed mass to be heavier, which would support the high-quality seed production for forest well-being and its restoration in Siberia.

1. Biodiversity is an important component of natural ecosystems, with higher species richness often correlating with an increase in ecosystem productivity. Yet, this relationship varies substantially across environments, typically becoming less pronounced at high levels of species richness. However, species richness alone cannot reflect all important properties of a community, including community evenness, which may mediate the relationship between biodiversity and productivity. If the evenness of a community correlates negatively with richness across forests globally, then a greater number of species may not always increase overall diversity and productivity of the system. Theoretical work and local empirical studies have shown that the effect of evenness on ecosystem functioning may be especially strong at high richness levels, yet the consistency of this remains untested at a global scale.2. Here, we used a dataset of forests from across the globe, which includes composition, biomass accumulation and net primary productivity, to explore whether productivity correlates with community evenness and richness in a way that evenness appears to buffer the effect of richness. Specifically, we evaluated whether low levels of evenness in speciose communities correlate with the attenuation of the richness-productivity relationship.3. We found that tree species richness and evenness are negatively correlated across forests globally, with highly speciose forests typically comprising a few dominant and many rare species. Furthermore, we found that the correlation between diversity and productivity changes with evenness: at low richness, uneven communities are more productive, while at high richness, even communities are more productive.4. Synthesis. Collectively, these results demonstrate that evenness is an integral component of the relationship between biodiversity and productivity, and that the attenuating effect of richness on forest productivity might be partly explained by low evenness in speciose communities. Productivity generally increases with species richness, until reduced evenness limits the overall increases in community diversity. Our research suggests that evenness is a fundamental component of biodiversity-ecosystem function relationships, and is of critical importance for guiding conservation and sustainable ecosystem management decisions.

Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17–34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling.

Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4. Here, leveraging global tree databases5-7, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions.

Inter-annual and seasonal variations of energy, vapor water, and carbon fluxes and associated climate variables in a middle taiga pine (Pinus sylvestris) forest on sandy soils and in a northern taiga larch (Larix gmelinii) forest on permafrost in central Siberia were studied from eddy covariance measurements acquired during the growing seasons of 1998–2000 and 2004–2008, respectively. Both the pure Scots pine of 215-year-old and pure Gmelin larch of 105-year-old forests naturally regenerated after forest fires, differed by their tree stand characteristics, and grew in extremely contrasting environments with distinctive climatic and soil conditions. Net radiation was greater in the pine forest due to higher values in the summer months and a longer growing season. Sensible heat flux was the larger term in the radiation balance in both forests. The Bowen ratio stayed between 1 and 2 during the growing season and was as high as 8–10 in dry spring in both forests. In the dry summers, latent heat explained 70%–80% of the daily net ecosystem CO2 exchange (NEE) variation in both forests. The average NEE was significantly smaller in the larch ecosystem at −4 µmol m−2s−1 compared to −7 µmol m−2s−1 in the pine forest. NEP for the growing season was 83 in the larch forest on continuous permafrost and 228 g C m−2 in the pine forest on warm sandy soils. Water use efficiency was 5.8 mg CO2 g−1H2O in the larch forest and 11 mg CO2 g−1H2O in the pine forest and appeared to be consistent with that in boreal forests. As a result of the forest structure change from Gmelin larch to Scots pine due to the permafrost retreat in a warming climate, the boreal forest C-sink may be expected to increase. Thus, potential feedback to the climate system in these “hot spots” of forest-forming replacement species may promote C-uptake from the atmosphere. However, as many studies suggest, in the pace of transition from permafrost to non-permafrost, C-sink would turn into C-source in hot spots of permafrost retreat.

Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system 1 . Remote-sensing estimates to quantify carbon losses from global forests 2 – 5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced 6 and satellite-derived approaches 2 , 7 , 8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151–363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea 2 , 3 , 9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.

The South Siberian and North Mongolian Mountains have enormous forests potential; however, more and more territories of forests disturbed by cutting and fire appeared during the late twenty years. One more negative phenomenon has been observed in unique dark-needle forests across the South Siberian Mountains: massive dieback of dark-needled forests that was related to climate aridization by many researchers. Our goal was to study predicted climate change impacts on the montane vegetation (altitudinal vegetation belts, AVB) transformation in a changing climate across the South Siberian and North Mongolian Mountains (window 48°–58° N and 80°–120° E). We based on outputs of the general circulation model the of the Computing Mathematics Institute, RAS (INM-CM5-0) and recent climate change scenarios (IPCC 2022) at 2050: the moderate ssp126 and extreme ssp585. Predictions of climate anomalies at 2050 were July temperatures 2–5°С, January temperature 1–4°С and annual precipitation 50–125 mm. According to this climate change, potential AVB may undergo transformation as follows: tundra, subalpine and “podgolets” open forest (under bare uplands) would significantly shrink; montane taiga would shrink 1.7-fold from the moderate scenario and 2.3-fold from the extreme scenario. Dark-needled AVB would remain on the same areas at the expense of subalpine AVB. Potential forest space including forest-tundra and forest-steppe ecotones would change insignificantly: would not change under the moderate scenario and would 10% decrease under the extreme scenario. Forest-steppe AVB would twice increase at the expense of light-needled AVB. One third of forest-steppe would favor broad-leaved forest-steppe. Steppe and semidesert would extend.

Background. Since the mid-20th century, massive dieback of coniferous forests has been observed in the temperate and boreal zones across North America and Northern Eurasia. The first hypotheses explaining forest dieback were associated with industrial air pollution (acid rain). At the end of the century, new hypotheses emerged that supported critical climate-induced aridization to explain forest dieback. Many studies were based on the SPEI (Standardized Precipitation Evapotranspiration Index) drought index. Our goals were to investigate if the SPEI drought index was a suitable metric to reflect drought conditions in wet and moist dark-needled forests in the South Siberian Mountains (Mts) and if droughts trigger the dieback of those forests. Methods. We calculated the SPEI drought index, the annual moisture index AMI, potential evapotranspiration PET, and water balance dynamics for the period 1961–2019 for four transects in the South Siberian Mts. where decline/dieback of dark-needled Siberian pine and fir forests were identified in situ. Climate data from nine weather stations located at lower and upper elevations of each transect were used to calculate climatic index dynamics for the 1961–2019 period to identify dry and wet phases of the period. Results. Our findings showed that climatic moisture/dryness indices have rarely gone down to high risk levels during the last 60 years (1961–2019). AMI did not reach the critical limit, 2.25, characteristic of the lower border for the dark-needled taiga. SPEI values < −1.5 represent drought stress conditions for dark-needled conifers at the lower border, and these conditions occurred 3–4 times during the 60-year period. However, the annual water balance stayed positive in those years in wet and moist forests at mid-to-high elevations. Trees are known to survive occasional (1–2) dry years. We found that dark-needled conifer dieback often occurs in wet years with plentiful rain rather than in drought years. We found forest dieback was associated with the westerlies that bring atmospheric pollution from the west at 50–56 N latitudes, where the air masses cross populated regions that have widespread industrial complexes. Conclusions. We concluded that the observed decline of dark-needled conifers at middle-to-high elevations across the South Siberia’s Mts was conditioned by several plausible causes, among which air pollution seems to be more credible, rather than dry climatic conditions, as cited in recent literature. Results are essential for understanding these ecosystems and others as our planet changes. Other causes and mechanisms should be further investigated, which would necessitate creating infrastructure that supports multi-disciplinary, inter-agency teamwork of plant physiologists, foresters, chemists, etc.

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers. Examining drivers of the latitudinal biodiversity gradient in a global database of local tree species richness, the authors show that co-limitation by multiple environmental and anthropogenic factors causes steeper increases in richness with latitude in tropical versus temperate and boreal zones.

A critical review of contemporary publications searching for the causes of the decline/dieback of dark-needled forests in the boreal and temperate zones over Northern Eurasia with an emphasis on the southern Siberian mountains is presented. Three groups of factors were considered: primary abiotic factors that weaken the tree defense mechanism (climate aridization, total ozone column, ultraviolet radiation (UV-B), dimming), anthropogenic factors (air pollution), and secondary biotic factors (invasive insect pests and phytopatogens that inhabit weakened trees, which finally leads to their decline/dieback). As there is no irrefutable evidence of the fatal impact of one particular factor, a synergic effect of some of them is possible against a certain climatic background. Further investigations are necessary to find out causes for the dark-needled forest decline/dieback in Northern Eurasia.

Research highlights: We investigated bioclimatic relationships between Scots pine seed mass and seed zones/climatypes across its range in Russia using extensive published data to predict seed zones and seed mass distributions in a changing climate and to reveal ecological and genetic components in the seed mass variation using our 40-year common garden trial data. Introduction: seed productivity issues of the major Siberian conifers in Asian Russia become especially relevant nowadays in order to compensate for significant forest losses due to various disturbances during the 20th and current centuries. Our goals were to construct bioclimatic models that predict the seed mass of major Siberian conifers (Scots pine, one of the major Siberian conifers) in a warming climate during the current century. Methods: Multi-year seed mass data were derived from the literature and were collected during field work. Climate data (January and July data and annual precipitation) were derived from published reference books on climate and climatic websites. Our multiple regression bioclimatic models were constructed based on the climatic indices of growing degree days > 5 °C, negative degree days < 0 °C, and annual moisture index, which were calculated from January and July temperatures and annual precipitation for both contemporary and future climates. The future 2080 (2070–2100) January and July temperatures and annual precipitation anomalies were derived from the ensemble of twenty CMIP5 (the Coupled Model Intercomparison Project, Phase 5) global circulation models (GCMs) and two scenarios using a mild RCP (Representative Concentration Pathway) 2.6 scenario and an extreme RCP 8.5 scenario. Results: Site climate explained about 70% of the seed mass variation across the Scots pine range. Genetic components explained 30% of the seed mass variation, as per the results from our common garden experiment in south central Siberia. Seed mass varied within 3.5 g (min) and 10.5 g (max) with the mean 6.1 g (n = 1150) across Russia. Our bioclimatic seed mass model predicted that a July temperature elevated by 1 °C increased seed mass by 0.56 g, and a January temperature elevated by 5 °C increased seed mass by 0.43 g. The seed mass would increase from 1 g to 4 g in the moderate RCP 2.6 and the extreme RCP 8.5 climates, respectively. Predicted seed zones with heavier seed would shift northwards in a warming climate. However, the permafrost border would halt this shifting due to slower permafrost thawing; thus, our predicted potential for Scots pine seed zones and seed mass would not be realized in the permafrost zone in a warmed climate. Our common garden experiment in central Siberia showed that trees of northerly origins produced lighter seeds than local trees but heavier ones than the trees at the original site. Trees of southerly origins produced heavier seeds than local trees but lighter seeds than the trees at the original site. Conclusions: The findings from this study could serve as blueprints for predicting new landscapes with climatic optima for Pinus sylvestris to produce better quality seeds to adjust to a warming climate.