Forest production efficiency increases with growth temperature

Stand age diversity (and more than climate change) affects forests' resilience and stability, although unevenly

Stand age significantly influences the functioning of forest ecosystems by shaping structural and physiological plant traits, affecting water and carbon budgets. Forest age distribution is determined by the interplay of tree mortality and regeneration, influenced by both natural and anthropogenic disturbances. Unfortunately, human-driven alteration of tree age distribution presents an underexplored avenue for enhancing forest stability and resilience. In our study, we investigated how age impacts the stability and resilience of the forest carbon budget under both current and future climate conditions. We employed a state-of-the-science biogeochemical, biophysical, validated process-based model on historically managed forest stands, projecting their future as undisturbed systems, i.e., left at their natural evolution with no management interventions (i.e., forests are left to develop undisturbed). Such a model, forced by climate data from five Earth System Models under four representative climate scenarios and one baseline scenario to disentangle the effect of climate change, spanned several age classes as representative of the current European forests' context, for each stand. Our findings indicate that Net Primary Production (NPP) peaks in the young and middle-aged classes (16- to 50-year-old), aligning with longstanding ecological theories, regardless of the climate scenario. Under climate change, the beech forest exhibited an increase in NPP and maintained stability across all age classes, while resilience remained constant with rising atmospheric CO2 and temperatures. However, NPP declined under climate change scenarios for the Norway spruce and Scots pine sites. In these coniferous forests, stability and resilience were more influenced. These results underscore the necessity of accounting for age class diversity -lacking in most, if not all, the current Global Vegetation Models - for reliable and robust assessments of the impacts of climate change on future forests' stability and resilience capacity. We, therefore, advocate for customized management strategies that enhance the adaptability of forests to changing climatic conditions, taking into account the diverse responses of different species and age groups to climate.

Drought alters aboveground biomass production efficiency: Insights from two European beech forests

The fraction of photosynthetically assimilated carbon that trees allocate to long-lasting woody biomass pools (biomass production efficiency - BPE), is a key metric of the forest carbon balance. Its apparent simplicity belies the complex interplay between underlying processes of photosynthesis, respiration, litter and fruit production, and tree growth that respond differently to climate variability. Whereas the magnitude of BPE has been routinely quantified in ecological studies, its temporal dynamics and responses to extreme events such as drought remain less well understood. Here, we combine long-term records of aboveground carbon increment (ACI) obtained from tree rings with stand-level gross primary productivity (GPP) from eddy covariance (EC) records to empirically quantify aboveground BPE (= ACI/GPP) and its interannual variability in two European beech forests (Hainich, DE-Hai, Germany; Sorø, DK-Sor, Denmark). We found significant negative correlations between BPE and a daily-resolved drought index at both sites, indicating that woody growth is de-prioritized under water limitation. During identified extreme years, early-season drought reduced same-year BPE by 29 % (Hainich, 2011), 31 % (Sorø, 2006), and 14 % (Sorø, 2013). By contrast, the 2003 late-summer drought resulted in a 17 % reduction of post-drought year BPE at Hainich. Across the entire EC period, the daily-to-seasonal drought response of BPE resembled that of ACI, rather than that of GPP. This indicates that BPE follows sink dynamics more closely than source dynamics, which appear to be decoupled given the distinctive climate response patterns of GPP and ACI. Based on our observations, we caution against estimating the magnitude and variability of the carbon sink in European beech (and likely other temperate forests) based on carbon fluxes alone. We also encourage comparable studies at other long-term EC measurement sites from different ecosystems to further constrain the BPE response to rare climatic events.

Incorporating high-resolution climate, remote sensing and topographic data to map annual forest growth in central and eastern Europe

To enhance our understanding of forest carbon sequestration, climate change mitigation and drought impact on forest ecosystems, the availability of high-resolution annual forest growth maps based on tree-ring width (TRW) would provide a significant advancement to the field. Site-specific characteristics, which can be approximated by high-resolution Earth observation by satellites (EOS), emerge as crucial drivers of forest growth, influencing how climate translates into tree growth. EOS provides information on surface reflectance related to forest characteristics and thus can potentially improve the accuracy of forest growth models based on TRW. Through the modelling of TRW using EOS, climate and topography data, we showed that species-specific models can explain up to 52 % of model variance (Quercus petraea), while combining different species results in relatively poor model performance (R2 = 13 %). The integration of EOS into models based solely on climate and elevation data improved the explained variance by 6 % on average. Leveraging these insights, we successfully generated a map of annual TRW for the year 2021. We employed the area of applicability (AOA) approach to delineate the range in which our models are deemed valid. The calculated AOA for the established forest-type models was 73 % of the study region, indicating robust spatial applicability. Notably, unreliable predictions predominantly occurred in the climate margins of our dataset. In conclusion, our large-scale assessment underscores the efficacy of combining climate, EOS and topographic data to develop robust models for mapping annual TRW. This research not only fills a critical void in the current understanding of forest growth dynamics but also highlights the potential of integrated data sources for comprehensive ecosystem assessments.

Oligomeric HIV-1 Integrase Structures Reveal Functional Plasticity for Intasome Assembly and RNA Binding

Integrase (IN) performs dual essential roles during HIV-1 replication. During ingress, IN functions within an oligomeric "intasome" assembly to catalyze viral DNA integration into host chromatin. During late stages of infection, tetrameric IN binds viral RNA and orchestrates the condensation of ribonucleoprotein complexes into the capsid core. The molecular architectures of HIV-1 IN assemblies that mediate these distinct events remain unknown. Furthermore, the tetramer is an important antiviral target for allosteric IN inhibitors. Here, we determined cryo-EM structures of wildtype HIV-1 IN tetramers and intasome hexadecamers. Our structures unveil a remarkable plasticity that leverages IN C-terminal domains and abutting linkers to assemble functionally distinct oligomeric forms. Alteration of a newly recognized conserved interface revealed that both IN functions track with tetramerization in vitro and during HIV-1 infection. Collectively, our findings reveal how IN plasticity orchestrates its diverse molecular functions, suggest a working model for IN-viral RNA binding, and provide atomic blueprints for allosteric IN inhibitor development.

Transitional responses of tree growth to climate warming at the southernmost margin of high latitudinal permafrost distribution

The marked increase in temperature warming and permafrost degradation has raised apprehensions about the fate of forests of boreal forests in permafrost regions. However, the impact of climate on tree growth is not limited to direct effects but also involves complex interactions with permafrost. The degradation of permafrost poses a threat to forest growth that has received insufficient attention thus far, after analyzing the impact of permafrost degradation and climate on Dahurican larch (Larix gmelinii) growth from six forest sites with two maximum active layer thickness (ALT) classifications (more and less than tree root length) across the southern margin of the permafrost region. We found that accompanying the continued degradation of permafrost, tree growth was inhibited (slope = -0.67, p < 0.05) by the degradation of permafrost and the growth-climate relationship was shifted from positive to negative at maximum ALT less than tree root length sites. However, the growth rate of trees significantly accelerated (slope = 5.46, p < 0.05) at maximum ALT more than tree root length sites. Path analysis indicated that tree growth did not benefit from temperature warming and more stress could be caused by waterlogging due to permafrost degradation at maximum ALT less than tree root length sites, however, enhanced tree growth primarily by reducing the physical spatial constraints and root layer additional water source with permafrost degradation at maximum ALT more than tree root length sites. It also implies that the matchiness between tree root and maximum active layer depth is critical to the effect of permafrost degradation on tree growth. The transitional response to climate warming and the opposite trend of tree growth at two ALT classification sites suggest that future tree growth responds to the different stages of permafrost degradation differently. Our study provides a new insight on permafrost degradation impact on tree growth.

Reduced global plant respiration due to the acclimation of leaf dark respiration coupled with photosynthesis

Leaf dark respiration (Rd ) acclimates to environmental changes. However, the magnitude, controls and time scales of acclimation remain unclear and are inconsistently treated in ecosystem models. We hypothesized that Rd and Rubisco carboxylation capacity (Vcmax ) at 25°C (Rd,25 , Vcmax,25 ) are coordinated so that Rd,25 variations support Vcmax,25 at a level allowing full light use, with Vcmax,25 reflecting daytime conditions (for photosynthesis), and Rd,25 /Vcmax,25 reflecting night-time conditions (for starch degradation and sucrose export). We tested this hypothesis temporally using a 5-yr warming experiment, and spatially using an extensive field-measurement data set. We compared the results to three published alternatives: Rd,25 declines linearly with daily average prior temperature; Rd at average prior night temperatures tends towards a constant value; and Rd,25 /Vcmax,25 is constant. Our hypothesis accounted for more variation in observed Rd,25 over time (R2  = 0.74) and space (R2  = 0.68) than the alternatives. Night-time temperature dominated the seasonal time-course of Rd , with an apparent response time scale of c. 2 wk. Vcmax dominated the spatial patterns. Our acclimation hypothesis results in a smaller increase in global Rd in response to rising CO2 and warming than is projected by the two of three alternative hypotheses, and by current models.

Topography shapes the carbon allocation patterns of alpine forests

Topography plays a crucial role in determining the structure of alpine forests, as it restricts the availability of nutrients and water necessary for plant growth. Nevertheless, our information on how variations in forest carbon allocation patterns driven by fine-scale topography are influenced by broader-scale environmental contexts is limited. In the northern Tibetan Plateau, we combined field data from 89 forest plots with a high-resolution (1 m2) digital elevation model (DEM) and utilized a linear mixed-effects model to investigate how microtopography (characterized by slope, aspect, and topographic wetness index (TWI)) and broader-scale environmental context (characterized by elevation) and their interactions affect the carbon allocation patterns of alpine forest. Our results revealed that at low and high elevations with pronounced subsurface resource limitations, plants tend to allocate a higher proportion of carbon to the root system and have lower aboveground carbon stocks (ACS). Microtopographic heterogeneity significantly influenced the carbon allocation patterns of forest, with the intensity and direction of these effects varying across the environmental gradient. At low elevations, topographically wetter and northerly microhabitats had higher ACS and lower ratios of below- and aboveground carbon stocks (RBA); however, at high elevations, topographically drier and southerly microhabitats had higher ACS and lower RBA. TWI and aspect had the weakest effect on ACS and RBA in the mid-elevations. The relationship between slope and ACS and RBA was significantly positive but not evidently related to the broader-scale environmental gradient.

Dynamically optimizing stomatal conductance for maximum turgor-driven growth over diel and seasonal cycles

Stomata have recently been theorized to have evolved strategies that maximize turgor-driven growth over plants' lifetimes, finding support through steady-state solutions in which gas exchange, carbohydrate storage and growth have all reached equilibrium. However, plants do not operate near steady state as plant responses and environmental forcings vary diurnally and seasonally. It remains unclear how gas exchange, carbohydrate storage and growth should be dynamically coordinated for stomata to maximize growth. We simulated the gas exchange, carbohydrate storage and growth that dynamically maximize growth diurnally and annually. Additionally, we test whether the growth-optimization hypothesis explains nocturnal stomatal opening, particularly through diel changes in temperature, carbohydrate storage and demand. Year-long dynamic simulations captured realistic diurnal and seasonal patterns in gas exchange as well as realistic seasonal patterns in carbohydrate storage and growth, improving upon unrealistic carbohydrate responses in steady-state simulations. Diurnal patterns of carbohydrate storage and growth in day-long simulations were hindered by faulty modelling assumptions of cyclic carbohydrate storage over an individual day and synchronization of the expansive and hardening phases of growth, respectively. The growth-optimization hypothesis cannot currently explain nocturnal stomatal opening unless employing corrective 'fitness factors' or reframing the theory in a probabilistic manner, in which stomata adopt an inaccurate statistical 'memory' of night-time temperature. The growth-optimization hypothesis suggests that diurnal and seasonal patterns of stomatal conductance are driven by a dynamic carbon-use strategy that seeks to maintain homeostasis of carbohydrate reserves.

Plant Growth-Promoting Rhizobacteria Improve Rice Response to Climate Change Conditions

Rice is one of the most important crops in the world and is considered a strategic crop for food security. Furthermore, the excessive use of chemical fertilizers to obtain high yields causes environmental problems. A sustainable alternative includes taking advantage of beneficial bacteria that promote plant growth. Here, we investigate the effect of five bacterial biofertilizers from halophytes on growth, and we investigate photosynthetic efficiency in rice plants grown under saline conditions (0 and 85 mmol L^-1 NaCl) and future climate change scenarios, including increased CO₂ concentrations and temperature (400/700 ppm and 25/+4 °C, respectively). Biofertilizers 1-4 increased growth by 9-64% in plants grown with and without salt in both CO₂- temperature combinations, although there was no significant positive effect on the net photosynthetic rate of rice plants. In general, biofertilizer 1 was the most effective at 400 ppm CO₂ and at 700 ppm CO₂ +4 °C in the absence of salt. Inocula 1-5 also stimulated plant length at high CO₂ levels without salt. Finally, the positive effect of biofertilization was attenuated in the plants grown under the interaction between salt and high CO₂. This highlights the significance of studying biofertilization under stress interaction to establish the real potential of biofertilizers in the context of climate change conditions.

Do stomata optimize turgor-driven growth? A new framework for integrating stomata response with whole-plant hydraulics and carbon balance

Every existing optimal stomatal model uses photosynthetic carbon assimilation as a proxy for plant evolutionary fitness. However, assimilation and growth are often decoupled, making assimilation less ideal for representing fitness when optimizing stomatal conductance to water vapor and carbon dioxide. Instead, growth should be considered a closer proxy for fitness. We hypothesize stomata have evolved to maximize turgor-driven growth, instead of assimilation, over entire plants' lifetimes, improving their abilities to compete and reproduce. We develop a stomata model that dynamically maximizes whole-stem growth following principles from turgor-driven growth models. Stomata open to assimilate carbohydrates that supply growth and osmotically generate turgor, while stomata close to prevent losses of turgor and growth due to negative water potentials. In steady state, the growth optimization model captures realistic stomatal, growth, and carbohydrate responses to environmental cues, reconciles conflicting interpretations within existing stomatal optimization theories, and explains patterns of carbohydrate storage and xylem conductance observed during and after drought. Our growth optimization hypothesis introduces a new paradigm for stomatal optimization models, elevates the role of whole-plant carbon use and carbon storage in stomatal functioning, and has the potential to simultaneously predict gross productivity, net productivity, and plant mortality through a single, consistent modeling framework.

Simulating diverse forest management options in a changing climate on a Pinus nigra subsp. laricio plantation in Southern Italy

Mediterranean pine plantations provide several ecosystem services but are vulnerable to climate change. Forest management might play a strategic role in the adaptation of Mediterranean forests, but the joint effect of climate change and diverse management options have seldom been investigated together. Here, we simulated the development of a Laricio pine (Pinus nigra subsp. laricio) stand in the Bonis watershed (southern Italy) from its establishment in 1958 up to 2095 using a state-of-the-science process-based forest model. The model was run under three climate scenarios corresponding to increasing levels of atmospheric CO₂ concentration and warming, and six management options with different goals, including wood production and renaturalization. We analysed the effect of climate change on annual carbon fluxes (i.e., gross and net primary production) and stocks (i.e., basal area, standing and harvested carbon woody stocks) of the autotrophic compartment, as well as the impact of different management options compared to a no management baseline. Results show that higher temperatures (+3 to +5 °C) and lower precipitation (-20 % to -22 %) will trigger a decrease in net primary productivity in the second half of the century. Compared to no management, the other options had a moderate effect on carbon fluxes over the whole simulation (between -14 % and +11 %). While standing woody biomass was reduced by thinning interventions and the shelterwood system (between -5 % and -41 %), overall carbon stocks including the harvested wood were maximized (between +41 % and +56 %). Results highlight that management exerts greater effects on the carbon budget of Laricio pine plantations than climate change alone, and that climate change and management are largely independent (i.e., no strong interaction effects). Therefore, appropriate silvicultural strategies might enhance potential carbon stocks and improve forest conditions, with cascading positive effects on the provision of ecosystem services in Mediterranean pine plantations.

Individual and mutual effects of elevated carbon dioxide and temperature on salt and cadmium uptake and translocation by rice seedlings

Plant kingdoms are facing increasingly harsh environmental challenges marked by the coexposure of salinity and pollution in the pedosphere and elevated CO₂ and temperature in the atmosphere due to the rapid acceleration of industrialization and global climate change. In this study, we deployed a hydroponics-based experiment to explore the individual and mutual effects of different temperatures (low temperature, T1: 23°C; high temperature, T2: 27°C) and CO₂ concentrations (ambient CO₂: 360 ppm; medium CO₂: 450 ppm; high CO₂: 700 ppm) on the uptake and translocation of sodium chloride (NaCl, 0.0, 0.2, 0.6, and 1.1 g Na/L) and cadmium nitrate (Cd(NO₃)₂·4H₂O, 0.0, 0.2, 1.8, and 5.4 mg Cd/L) by rice seedlings. The results indicated that Cd and Na exposure significantly (P< 0.05) inhibited plant growth, but T2 and medium/high CO₂ alleviated the effects of Cd and Na on plant growth. Neither significant synergistic nor antagonistic effects of Cd and Na were observed, particularly not at T1 or high CO₂. At increasing temperatures, relative growth rates increased despite higher concentrations of Cd and Na in both rice roots and shoots. Similarly, higher CO₂ stimulated the growth rate but resulted in significantly lower concentrations of Na, while the Cd concentration was highest at medium CO₂. Coexposure experiments suggested that the concentration of Cd in roots slightly declined with additional Na and more at T2. Overall, our preliminary study suggested that global climate change may alter the distribution of mineral and toxic elements in rice plants as well as the tolerance of the plants.

Responses of spatial relationships between ecosystem services and the Sustainable Development Goals to urbanization

Ecosystem services (ES) are the important component supporting the United Nations Sustainable Development Goals (SDGs) realization. In recent decades, rapid urbanization has strongly affected the relationship between ES and SDGs, resulting in the decoupling of ES and SDGs. However, the key urbanization factors dominating the relationship between ES and SDGs are still unclear. In this study, a structural equation model was constructed to explore the impact path and its change of urbanization structure and scale factors on the relationship between ES and SDGs. The results showed that the economic urbanization structure indicator (Engel coefficient) under the influence of technology import significantly impacted the relationship between ES and SDGs in different periods. Under the influence of changes in urban and rural population, population urbanization structure indicator (labor force population proportion) had significant impact on the relationship between ES and economic SDGs, which was significantly stronger in the period of 2010-2015 than in the period of 2000-2005. Land urbanization scale indicators (construction land proportion, and protected natural area proportion) also significantly impacted the relationship between ES and SDGs. Especially for ecological SDGs, the negative impact of construction land on protected natural area increased significantly in the period of 2010-2015, which might further weaken the ES's contribution to SDGs. This study highlighted that along with the continuous transformation of China's society, the key impacts on the relationship between ES and SDGs resulted from the urbanization indicators of scale as well as structure, which provided an extensive support for the sustainable development and social transformation of developing countries and regions.

Strategic roadmap to assess forest vulnerability under air pollution and climate change

Although it is an integral part of global change, most of the research addressing the effects of climate change on forests have overlooked the role of environmental pollution. Similarly, most studies investigating the effects of air pollutants on forests have generally neglected the impacts of climate change. We review the current knowledge on combined air pollution and climate change effects on global forest ecosystems and identify several key research priorities as a roadmap for the future. Specifically, we recommend (1) the establishment of much denser array of monitoring sites, particularly in the South Hemisphere; (2) further integration of ground and satellite monitoring; (3) generation of flux-based standards and critical levels taking into account the sensitivity of dominant forest tree species; (4) long-term monitoring of N, S, P cycles and base cations deposition together at global scale; (5) intensification of experimental studies, addressing the combined effects of different abiotic factors on forests by assuring a better representation of taxonomic and functional diversity across the ~73,000 tree species on Earth; (6) more experimental focus on phenomics and genomics; (7) improved knowledge on key processes regulating the dynamics of radionuclides in forest systems; and (8) development of models integrating air pollution and climate change data from long-term monitoring programs.

Pinus tabulaeformis Forests Have Higher Carbon Sequestration Potential Than Larix principis-rupprechtii Forests in a Dryland Mountain Ecosystem, Northwest China

Carbon sinks in terrestrial ecosystems can be significantly increased by afforestation, which will slow global warming. However, it is still unclear how different plantations influence the carbon sink and how they respond to environmental factors, especially in drylands. In this study, eddy correlation method (EC) was used to measure carbon and water fluxes and environmental factors of two artificial forests (Larix principis-rupprechtii and Pinus tabulaeformis) in the dryland of Northwest China, and the responses of evapotranspiration (ET), net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RECO) to environmental factors were also assessed. Results showed that the L. principis-rupprechtii forest ecosystem had higher water use efficiency (WUE), light use efficiency (LUE), GPP, and RECO than the P. tabulaeformis forest ecosystem. However, the proportion of net ecosystem production (NEP) to GPP in the P. tabulaeformis forest ecosystem (62.89%) was higher than that in the L. principis-rupprechtii forest ecosystem (47.49%), indicating that the P. tabulaeformis forest ecosystem had the higher carbon sequestration efficiency. In addition, the CO2 and H2O fluxes in the L. principis-rupprechtii forest ecosystem were more sensitive to environmental factors, compared with the P. tabulaeformis forest ecosystem. Further, the RECO of the L. principis-rupprechtii forest ecosystem was more sensitive to temperature changes, which implies that the L. principis-rupprechtii forest ecosystem will release more CO2 than the P. tabulaeformis forest ecosystem with a warming climate. Therefore, the P. tabulaeformis forest ecosystem may have better carbon sequestration potential. These results are important for understanding the effects of climate change on the CO2 and H2O cycles in coniferous plantation ecosystems in drylands.

Linking landscape structure and vegetation productivity with nut consumption by the Cantabrian brown bear during hyperphagia

In bears, reproduction is dependent on the body reserves accumulated during hyperphagia. The Cantabrian brown bear mainly feeds on nuts during the hyperphagia period. Understanding how landscape heterogeneity and vegetation productivity in human-dominated landscapes influence the feeding habits of bears may therefore be important for disentangling species-habitat relationships of conservation interest. We determined the spatial patterns of nut consumption by brown bears during the hyperphagia period in relation to landscape structure, characteristics of fruit-producing patches and vegetation productivity. For this purpose, we constructed foraging models based on nut consumption data (obtained by scat analysis), by combining vegetation productivity data, topographical variables and landscape metrics to identify nut foraging patterns during this critical period for bears. The average wooded area of patches where scats were collected and where the nuts that the bears had consumed were produced was larger than that of the corresponding patches where nuts were not produced. For scats collected outside of nut-producing patches, the distance between the scats and the patches was greatest for chestnut-producing patches. Elevation, Gross Primary Production (GPP) and the Aggregation Index (AI) were good predictors of acorn consumption in the models. Good model fits were not obtained for data on chestnut consumption in bears. The findings confirm that brown bears feeding on nuts show a preference for relatively large, highly aggregated patches with a high degree of diversity in the landscape pattern, which may help the bears to remain undetected. The nut prediction model highlights areas of particular importance for brown bears during hyperphagia. The human presence associated with sweet chestnut forest stands or orchards may make bears feel more vulnerable when feeding.

Joint effects of climate, tree size, and year on annual tree growth derived from tree-ring records of ten globally distributed forests

Tree rings provide an invaluable long-term record for understanding how climate and other drivers shape tree growth and forest productivity. However, conventional tree-ring analysis methods were not designed to simultaneously test effects of climate, tree size, and other drivers on individual growth. This has limited the potential to test ecologically relevant hypotheses on tree growth sensitivity to environmental drivers and their interactions with tree size. Here, we develop and apply a new method to simultaneously model nonlinear effects of primary climate drivers, reconstructed tree diameter at breast height (DBH), and calendar year in generalized least squares models that account for the temporal autocorrelation inherent to each individual tree's growth. We analyze data from 3811 trees representing 40 species at 10 globally distributed sites, showing that precipitation, temperature, DBH, and calendar year have additively, and often interactively, influenced annual growth over the past 120 years. Growth responses were predominantly positive to precipitation (usually over ≥3-month seasonal windows) and negative to temperature (usually maximum temperature, over ≤3-month seasonal windows), with concave-down responses in 63% of relationships. Climate sensitivity commonly varied with DBH (45% of cases tested), with larger trees usually more sensitive. Trends in ring width at small DBH were linked to the light environment under which trees established, but basal area or biomass increments consistently reached maxima at intermediate DBH. Accounting for climate and DBH, growth rate declined over time for 92% of species in secondary or disturbed stands, whereas growth trends were mixed in older forests. These trends were largely attributable to stand dynamics as cohorts and stands age, which remain challenging to disentangle from global change drivers. By providing a parsimonious approach for characterizing multiple interacting drivers of tree growth, our method reveals a more complete picture of the factors influencing growth than has previously been possible.

Climate change impacts plant carbon balance, increasing mean future carbon use efficiency but decreasing total forest extent at dry range edges

Carbon use efficiency (CUE) represents how efficient a plant is at translating carbon gains through gross primary productivity (GPP) into net primary productivity (NPP) after respiratory costs (R_a ). CUE varies across space with climate and species composition, but how CUE will respond to climate change is largely unknown due to uncertainty in R_a at novel high temperatures. We use a plant physiological model validated against global CUE observations and LIDAR vegetation canopy height data and find that model-predicted decreases in CUE are diagnostic of transitions from forests to shrubland at dry range edges. Under future climate scenarios, we show mean growing season CUE increases in core forested areas, but forest extent decreases at dry range edges, with substantial uncertainty in absolute CUE due to uncertainty in R_a . Our results highlight that future forest resilience is nuanced and controlled by multiple competing mechanisms.

Global sensitivities of forest carbon changes to environmental conditions

The responses of forest carbon dynamics to fluctuations in environmental conditions at a global scale remain elusive. Despite the understanding that favourable environmental conditions promote forest growth, these responses have been challenging to observe across different ecosystems and climate gradients. Based on a global annual time series of aboveground biomass (AGB) estimated from radar satellites between 1992 and 2018, we present forest carbon changes and provide insights on their sensitivities to environmental conditions across scales. Our findings indicate differences in forest carbon changes across AGB classes, with regions with carbon stocks of 50-125 MgC ha^-1 depict the highest forest carbon gains and losses, while regions with 125-150 MgC ha^-1  have the lowest forest carbon gains and losses in absolute terms. Net forest carbon change estimates show that the arc-of-deforestation and the Congo Basin were the main hotspots of forest carbon loss, while a substantial part of European forest gained carbon during the last three decades. Furthermore, we observe that changes in forest carbon stocks were systematically positively correlated with changes in forest cover fraction. At the same time, it was not necessarily the case with other environmental variables, such as air temperature and water availability at the bivariate level. We also used a model attribution method to demonstrate that atmospheric conditions were the dominant control of forest carbon changes (56% of the total study area) followed by water-related (29% of the total study area) and vegetation (15% of the total study area) conditions. Regionally, we find evidence that carbon gains from long-term forest growth covary with long-term carbon sinks inferred from atmospheric inversions. Our results describe the contributions from the atmosphere, water-related and vegetation conditions to forest carbon changes and provide new insights into the underlying mechanisms of the coupling between forest growth and the global carbon cycle.

Integrating terrestrial laser scanning with functional-structural plant models to investigate ecological and evolutionary processes of forest communities

BACKGROUND

Woody plants (trees and shrubs) play an important role in terrestrial ecosystems, but their size and longevity make them difficult subjects for traditional experiments. In the last 20 years functional-structural plant models (FSPMs) have evolved: they consider the interplay between plant modular structure, the immediate environment and internal functioning. However, computational constraints and data deficiency have long been limiting factors in a broader application of FSPMs, particularly at the scale of forest communities. Recently, terrestrial laser scanning (TLS), has emerged as an invaluable tool for capturing the 3-D structure of forest communities, thus opening up exciting opportunities to explore and predict forest dynamics with FSPMs.

SCOPE

The potential synergies between TLS-derived data and FSPMs have yet to be fully explored. Here, we summarize recent developments in FSPM and TLS research, with a specific focus on woody plants. We then evaluate the emerging opportunities for applying FSPMs in an ecological and evolutionary context, in light of TLS-derived data, with particular consideration of the challenges posed by scaling up from individual trees to whole forests. Finally, we propose guidelines for incorporating TLS data into the FSPM workflow to encourage overlap of practice amongst researchers.

CONCLUSIONS

We conclude that TLS is a feasible tool to help shift FSPMs from an individual-level modelling technique to a community-level one. The ability to scan multiple trees, of multiple species, in a short amount of time, is paramount to gathering the detailed structural information required for parameterizing FSPMs for forest communities. Conventional techniques, such as repeated manual forest surveys, have their limitations in explaining the driving mechanisms behind observed patterns in 3-D forest structure and dynamics. Therefore, other techniques are valuable to explore how forests might respond to environmental change. A robust synthesis between TLS and FSPMs provides the opportunity to virtually explore the spatial and temporal dynamics of forest communities.

Unravelling resilience mechanisms in forests: role of non-structural carbohydrates in responding to extreme weather events

Extreme weather events are increasing in frequency and intensity due to global climate change. We hypothesized that tree carbon reserves are crucial for resilience of beech, buffering the source-sink imbalance due to late frosts and summer droughts, and that different components of non-structural carbohydrates (NSCs) play specific roles in coping with stressful situations. To assess the compound effects on mature trees of two extreme weather events, first a late frost in spring 2016 and then a drought in summer 2017, we monitored the phenology, radial growth and the dynamics of starch and soluble sugars in a Mediterranean beech forest. A growth reduction of 85% was observed after the spring late frost, yet not after the drought event. We observed a strong impact of late frost on starch, which also affected its dynamic at the beginning of the subsequent vegetative season. In 2017, the increase of soluble sugars, associated with starch hydrolysis, played a crucial role in coping with the severe summer drought. Non-structural carbohydrates helped to counteract the negative effects of both events, supporting plant survival and buffering source-sink imbalances under stressful conditions. Our findings indicate a strong trade-off between growth and NSC storage in trees. Overall, our results highlight the key role of NSCs on beech trees, response to extreme weather events, confirming the resilience of this species to highly stressful events. These insights are useful for assessing how forests may respond to the potential impacts of climate change on ecosystem processes in the Mediterranean area.

Global patterns of forest autotrophic carbon fluxes

Carbon (C) fixation, allocation, and metabolism by trees set the basis for energy and material flows in forest ecosystems and define their interactions with Earth's changing climate. However, while many studies have considered variation in productivity with latitude and climate, we lack a cohesive synthesis on how forest carbon fluxes vary globally with respect to climate and one another. Here, we draw upon 1,319 records from the Global Forest Carbon Database, representing all major forest types and the nine most significant autotrophic carbon fluxes, to comprehensively review how annual C cycling in mature, undisturbed forests varies with latitude and climate on a global scale. Across all flux variables analyzed, rates of C cycling decreased continuously with absolute latitude-a finding that confirms multiple previous studies and contradicts the idea that net primary productivity of temperate forests rivals that of tropical forests. C flux variables generally displayed similar trends across latitude and multiple climate variables, with no differences in allocation detected at this global scale. Temperature variables in general, and mean annual temperature or temperature seasonality in particular, were the best single predictors of C flux, explaining 19%-71% of variation in the C fluxes analyzed. The effects of temperature were modified by moisture availability, with C flux reduced under hot and dry conditions and sometimes under very high precipitation. Annual C fluxes increased with growing season length and were also influenced by growing season climate. These findings clarify how forest C flux varies with latitude and climate on a global scale. In an era when forests will play a critical yet uncertain role in shaping Earth's rapidly changing climate, our synthesis provides a foundation for understanding global patterns in forest C cycling.

Tackling unresolved questions in forest ecology: The past and future role of simulation models

Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio-temporal scales unreachable by most empirical investigations.We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.Using three widely applied but contrasting approaches - species distribution models, individual-based forest models, and dynamic global vegetation models - as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.

The three major axes of terrestrial ecosystem function

The leaf economics spectrum^1,2 and the global spectrum of plant forms and functions³ revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species². Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities⁴. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability^4,5. Here we derive a set of ecosystem functions⁶ from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems^7,8.

Model-Based Estimation of Amazonian Forests Recovery Time after Drought and Fire Events

In recent decades, droughts, deforestation and wildfires have become recurring phenomena that have heavily affected both human activities and natural ecosystems in Amazonia. The time needed for an ecosystem to recover from carbon losses is a crucial metric to evaluate disturbance impacts on forests. However, little is known about the impacts of these disturbances, alone and synergistically, on forest recovery time and the resulting spatiotemporal patterns at the regional scale. In this study, we combined the 3-PG forest growth model, remote sensing and field derived equations, to map the Amazonia-wide (3 km of spatial resolution) impact and recovery time of aboveground biomass (AGB) after drought, fire and a combination of logging and fire. Our results indicate that AGB decreases by 4%, 19% and 46% in forests affected by drought, fire and logging + fire, respectively, with an average AGB recovery time of 27 years for drought, 44 years for burned and 63 years for logged + burned areas and with maximum values reaching 184 years in areas of high fire intensity. Our findings provide two major insights in the spatial and temporal patterns of drought and wildfire in the Amazon: (1) the recovery time of the forests takes longer in the southeastern part of the basin, and, (2) as droughts and wildfires become more frequent—since the intervals between the disturbances are getting shorter than the rate of forest regeneration—the long lasting damage they cause potentially results in a permanent and increasing carbon losses from these fragile ecosystems.