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Carbon allocation plays a key role in ecosystem dynamics and plant adaptation to changing environmental conditions.
Hence, proper description of this process in vegetation models is crucial for the simulations of the impact of climate change on carbon cycling in forests. Here we review how carbon allocation modelling is currently implemented in 31...
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... This might be due to the increased transpiration caused by earlier vegetation greening as a result of spring warming, leading to a significant soil moisture deficit in summer [55][56][57]. In such cases, plants tend to invest more carbon into their root systems during the late greening stage to acquire water and nutrients, thus increasing the carbon cost per unit of leaf area, which is unfavorable for canopy growth in the region [58][59][60][61]. Therefore, we believe that the accelerated development of the spring vegetation canopy consumes additional resources needed to maintain subsequent growth [30], intensifying water stress on the vegetation, resulting in a decrease in net photosynthetic rate and a shift in carbon allocation from leaves to stems [62], and thereby negatively affecting grassland VLAI. ...
Studying climate change’s impact on vegetation canopy growth and senescence is significant for understanding and predicting vegetation dynamics. However, there is a lack of adequate research on canopy changes across the lifecycles of different vegetation types. Using GLASS LAI (leaf area index) data (2001–2020), we investigated canopy development (April–June), maturity (July–August), and senescence (September–October) rates in Northeast China, focusing on their responses to preseason climatic factors. We identified that early stages saw canopy development acceleration, with over 71% of areas experiencing such acceleration in April and May. As the vegetation grew, the accelerating canopy development slowed down, and the canopy reached its maturation earlier. By analyzing the partial correlation between canopy growth and preseason climatic factors, it was identified that changes in canopy growth were most significantly affected by preseason air temperature. A positive correlation was observed in the early stages, which shifted to a negative correlation during canopy maturation and senescence. Notably, the transition timing varied among different vegetation types, with grasslands (June) occurring earlier than forests (July) and farmlands (August). Additionally, grassland canopy growth showed a stronger response to precipitation than forests and farmlands, with a lagged effect of 2.50 months. Our findings improve understanding of vegetation canopy growth across different stages, holding significant importance for ecological environmental monitoring, land-use planning, and sustainable development.
... These approaches have expanded into a variety of sectors [4,15,16]. Agriculture, forestry, and other land use (AFOLUs) models focus on better resource management (e.g., suitability analysis [17], nutrient loading [5], and crop yield projections [18]) and forestry, allocation, and zoning [19], timber [20], watershed analysis [4], and harvest planning [21]. ...
We conduct a literature review on integrated land use modelling to guide policy on sustainable food provisioning. Modelling approaches are discussed in the spatial, temporal, and human dimensions, as well as environmental and socio-economic considerations. Many studies have focused on model development over their application to specific policy objectives, often relying on top-down approaches. While ecosystem services are a frequent focus, indicators for their assessment are inconsistently quantified. Socio-economic considerations are coarse in scale compared to biophysical ones, limiting their use in nuanced policy development. Recommendations are made such as standardising data collection and sharing to streamline modelling processes and collaboration. Comprehensive ecosystem services frameworks would benefit from a more uniform classification of values. More bottom-up modelling, connected with top-down models, could account for the heterogeneity between smaller units of analysis such as the landscape, farms, or people. This could reveal further insights into the local contexts and decision-making responses essential for effective land use policy. These advancements would help to design policies that address the complexities of sustainable food provisioning. By connecting local and global perspectives, future models can support more resilient and adaptive food systems, ensuring sustainability in the face of environmental and socio-economic challenges.
... As key components of forest carbon dynamics, simulating NSC variations in different organs should be integrated into the framework of carbon allocation modelling. However, current carbon allocation models are often oversimplified and lack organspecific NSC simulations (Merganičová et al., 2019). Reviewing the current state of carbon allocation modelling, we highlight the knowledge gaps in NSC (and general carbon allocation) modelling and summarize potential approaches to fill these gaps. ...
... (De Kauwe et al., 2014;Poorter et al., 2012). Apart from the fixed carbon allocation ratios, current carbon allocation models have other shortcomings, such as (1) a deficiency in accounting for the direct sensitivity of carbon allocation to environmental conditions (Merganičová et al., 2019); (2) ignorance of the impacts of disturbances on carbon allocation such as the influences from drought, wind damage, insects, ice storms, and pathogens (Seidl et al., 2011(Seidl et al., , 2017; (3) failure to represent certain carbon pools in reproductive and storage organs that are used for defence and repair (Merganičová et al., 2019) and particularly carbon pools for mycorrhiza (Vargas, 2009) and root exudates; (4) coarse temporal resolution so that the models are not efficient to compute seasonal changes in carbon allocation (Merganičová et al., 2019); (5) a lack of high-quality observational data to calibrate and validate carbon allocation in different carbon pools (Hartmann & Trumbore, 2016). ...
... (De Kauwe et al., 2014;Poorter et al., 2012). Apart from the fixed carbon allocation ratios, current carbon allocation models have other shortcomings, such as (1) a deficiency in accounting for the direct sensitivity of carbon allocation to environmental conditions (Merganičová et al., 2019); (2) ignorance of the impacts of disturbances on carbon allocation such as the influences from drought, wind damage, insects, ice storms, and pathogens (Seidl et al., 2011(Seidl et al., , 2017; (3) failure to represent certain carbon pools in reproductive and storage organs that are used for defence and repair (Merganičová et al., 2019) and particularly carbon pools for mycorrhiza (Vargas, 2009) and root exudates; (4) coarse temporal resolution so that the models are not efficient to compute seasonal changes in carbon allocation (Merganičová et al., 2019); (5) a lack of high-quality observational data to calibrate and validate carbon allocation in different carbon pools (Hartmann & Trumbore, 2016). ...
Plant phenology is crucial for understanding plant growth and climate feedback. It affects canopy structure, surface albedo, and carbon and water fluxes. While the influence of environmental factors on phenology is well‐documented, the role of plant intrinsic factors, particularly internal physiological processes and their interaction with external conditions, has received less attention.
Non‐structural carbohydrates (NSC), which include sugars and starch essential for growth, metabolism and osmotic regulation, serve as indicators of carbon availability in plants. NSC levels reflect the carbon balance between photosynthesis (source activity) and the demands of growth and respiration (sink activity), making them key physiological traits that potentially influence phenology during critical periods such as spring leaf‐out and autumn leaf senescence. However, the connections between NSC concentrations in various organs and phenological events are poorly understood.
This review synthesizes current research on the relationship between leaf phenology and NSC dynamics. We qualitatively delineate seasonal NSC variations in deciduous and evergreen trees and propose testable hypotheses about how NSC may interact with phenological stages such as bud break and leaf senescence. We also discuss how seasonal variations in NSC levels, align with existing conceptual models of carbon allocation.
Accurate characterization and simulation of NSC dynamics are crucial and should be incorporated into carbon allocation models. By comparing and reviewing the development of carbon allocation models, we highlight the shortcomings in current methodologies and recommend directions to address these gaps in future research.
Understanding the relationship between NSC, source–sink relationships, and leaf phenology poses challenges due to the difficulty of characterizing NSC dynamics with high temporal resolution. We advocate for a multi‐scale approach that combines various methods, which include deepening our mechanistic understanding through manipulative experiments, integrating carbon sink and source data from multiple observational networks with carbon allocation models to better characterize the NSC dynamics, and quantifying the spatial pattern and temporal trends of the NSC‐phenology relationship using remote sensing and modelling. This will enhance our comprehension of how NSC dynamics impact leaf phenology across different scales and environments.
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... Recently, the development of remote sensing technology provides the possibility of using remotely sensed vegetation index data to analyze the dynamics of carbon allocation in vegetation (Chen et al. 2019;Park, Jeong, and Peñuelas 2020;Piao et al. 2020). Specifically, carbon allocation processes of vegetation regulate leaf growth, and plants will invest more carbon to leaves when their growth is not limited (Friedlingstein et al. 1999;Merganičová et al. 2019;Hartmann et al. 2020). When more carbon is allocated to leaves during the leaf green-up period, the photosynthetic rate of the vegetation increases, and the vegetation greening characterized by increasing leaf area index (LAI) will increase Meng, Hong et al. 2023). ...
Using MODIS leaf area index and meteorological data from 2000 to 2020, this study analyzed the variations in carbon allocation to leaves (Cleaf) of marsh during the leaf green-up period and their response to climate change across the TP based on partial correlation and linear regression analysis methods. The regionally averaged Cleaf of marsh showed an increasing trend during the leaf green-up period from 2000 to 2020. Diurnal warming has asymmetric effects on Cleaf of marsh during different stages of the leaf green-up period. During the early leaf green-up period, warming preseason daytime temperature significantly reduced Cleaf in the southwestern region, while warming preseason daytime and night-time temperatures increased Cleaf in the central region. During the late leaf green-up period, preseason temperatures exerted significantly positive and negative effects on Cleaf in the southwestern and central regions, respectively. During the early leaf green-up period, preseason precipitation increases significantly enhanced Cleaf in the southwestern region, but decreased Cleaf in the central region. This study highlights the distinct impacts of climatic change on Cleaf during different stages of the leaf green-up period and indicates that the asymmetric effects of diurnal warming should be considered in simulations of marsh carbon allocation in the future.
... Our R h estimate could be overestimated by artifacts of root exclusion method due to increased soil water content in trenched plots . The estimated contribution of R root was higher during cooler months, whereas that of R canopy was higher during warmer months (Figure 2b), suggesting seasonal variations in carbon allocation to aboveground and belowground biomass that could be incorporated into future model versions (Merganičová et al., 2019;Renchon et al., 2024). ...
... Alternative formulations for estimating temperature sensitivity from observations, such as the sigmoidal approach used for R eco , should be tested for component respiration. Temperature sensitivity and fluxes in CABLE-POP could be improved by specifying seasonal dynamics of leaf area and fine root biomass in relation to confounding drivers such as soil water content (Merganičová et al., 2019;Piñeiro et al., 2020;Renchon et al., 2024). ...
Ecosystem respiration (Reco) arises from interacting autotrophic and heterotrophic processes constrained by distinct drivers. Here, we evaluated up‐scaling of observed components of Reco in a mature eucalypt forest in southeast Australia and assessed whether a land surface model adequately represented all the fluxes and their seasonal temperature responses. We measured respiration from soil (Rsoil), heterotrophic soil microbes (Rh), roots (Rroot), and stems (Rstem) in 2018–2019. Reco and its components were simulated using the CABLE–POP (Community Atmosphere‐Biosphere Land Exchange–Population Orders Physiology) land surface model, constrained by eddy covariance and chamber measurements and enabled with a newly implemented Dual Arrhenius and Michaelis‐Menten (DAMM) module for soil organic matter decomposition. Eddy‐covariance based Reco (Reco.eddy, 1,439 g C m⁻² y⁻¹) was slightly higher than the sum of the respiration components (Reco.sum, 1,295 g C m⁻² y⁻¹) and simulated Reco (1,297 g C m⁻² y⁻¹). The largest mean contribution to Reco was from Rsoil (64%) across seasons. The measured contributions of Rh (49%), Rroot (15%), and Rstem (22%) to Reco.sum were very close to model outputs of 46%, 11%, and 22%, respectively. The modeled Rh was highly correlated with measured Rh (R² = 0.66, RMSE = 0.61), empirically validating the DAMM module. The apparent temperature sensitivities (Q10) of Reco were 2.22 for Reco.sum, 2.15 for Reco.eddy, and 1.57 for CABLE‐POP. This research demonstrated that bottom‐up respiration component measurements can be successfully scaled to eddy covariance‐based Reco and help to better constrain the magnitude of individual respiration components as well as their temperature sensitivities in land surface models.
... Tree growth is an integrative measure that results from carbon, water and light 598 uptake, whereas CASTANEA is calibrated using CO 2 fluxes , (Dufrêne et al., 599 2005). Moreover, the modeling of carbon allocation, which plays a decisive role 600 in simulating wood growth, can still be improved : is :: a :::::::::: potential ::::::: source ::: of ::::: error 601 (Davi et al., 2009;Merganičová et al., 2019). Additionally, the climate was 602 parameterized at the site scale ::::: using :: a :: 8 :::: km ::::::::::: resolution ::::: data ::: set : instead of the 603 stand scale, although climatic variables such as precipitation could vary between 604 stands due to local topography. ...
... A forest of different age groups integrates young, middle-aged, and mature trees, leading to vertical stratification that augments ecosystem complexity and stability. This stratification fosters gradients in biomass (both deadwood and living aboveground biomass), diverse carbon allocation methods (Merganičová et al., 2019), and ecological niches for flora and fauna, thereby enhancing biodiversity and the capacity to adaptively respond to environmental disturbances Lafond et al., 2014;Pardos et al., 2021). ...
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, bio-physical, 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.
... The phenological and allocation schemes are all described extensively in Collalti et al. [22,23,39] and Merganičová et al. [39]. The 3D-CMCC-FEM accounts for the 'age-effect' in several ways. ...
... The phenological and allocation schemes are all described extensively in Collalti et al. [22,23,39] and Merganičová et al. [39]. The 3D-CMCC-FEM accounts for the 'age-effect' in several ways. ...
Carbon assimilation and wood production are influenced by environmental conditions and endogenous factors, such as species auto-ecology, age, and hierarchical position within the forest structure. Disentangling the intricate relationships between those factors is more pressing than ever due to climate change's pressure. We employed the 3D-CMCC-FEM model to simulate undisturbed forests of different ages under four climate change (plus one no climate change) Representative Concentration Pathways (RCP) scenarios from five Earth system models. In this context, carbon stocks and increment were simulated via total carbon woody stocks and mean annual increment, which depends mainly on climate trends. We find greater differences among different age cohorts under the same scenario than among different climate scenarios under the same age class. Increasing temperature and changes in precipitation patterns led to a decline in above-ground biomass in spruce stands, especially in the older age classes. On the contrary, the results show that beech forests will maintain and even increase C-storage rates under most RCP scenarios. Scots pine forests show an intermediate behavior with a stable stock capacity over time and in different scenarios but with decreasing mean volume annual increment. These results confirm current observations worldwide that indicate a stronger climate-related decline in conifers forests than in broadleaves.
... Another source of uncertainty is the oversimplified allocation parametrization in the IBIS model, which assumes constant allocations of carbon among plant tissues (Merganičová et al., 2019). However, in reality, plants may alter their allocation strategies under the influence of climate changes (Collalti et al., 2020;Xu et al., 2012), and during different periods. ...
Many land surface models (LSMs) assume a steady‐state assumption (SS) for forest growth, leading to an overestimation of biomass in young forests. Parameters inversion under SS will potentially result in biased carbon fluxes and stocks in a transient simulation. Incorporating age‐dependent biomass into LSMs can simulate real disequilibrium states, enabling the model to simulate forest growth from planting to its current age, and improving the biased post‐calibration parameters. In this study, we developed a stepwise optimization framework that first calibrates “fast” light‐controlled CO2 fluxes (gross primary productivity, GPP), then leaf area index (LAI), and finally “slow” growth‐controlled biomass using the Global LAnd Surface Satellite (GLASS) GPP and LAI products, and age‐dependent biomass curves for the 25 forests. To reduce the computation time, we used a machine learning‐based model to surrogate the complex integrated biosphere simulator LSM during calibration. Our calibrated model led to an error reduction in GPP, LAI, and biomass by 28.5%, 35.3% and 74.6%, respectively. When compared with net biome productivity (NBP) using no‐age‐calibrated parameters, our age‐calibrated parameters increased NBP by an average of 50 gC m⁻² yr⁻¹ across all forests, especially in the boreal needleleaf evergreen forests, the NBP increased by 118 gC m⁻² yr⁻¹ on average, increasing the estimate of the carbon sink in young forests. Our work highlights the importance of including forest age in LSMs, and provides a novel framework for better calibrating LSMs using constraints from multiple satellite products at a global scale.
... This differential response may arise from biological constraints associated with the climate variability hypothesis, or possibly by a direct impact of temperature itself, as 3.5°C of warming may have differential impacts at basal home temperatures of 18 vs 27.5°C (Drake et al., 2017b). Our understanding of the patterns and controls over allocation are less advanced than our understanding of physiological acclimation of photosynthesis and respiration to climate warming but merits further study (Mergani cov a et al., 2019;Ceballos-N uñez et al., 2020). ...
Contemporary climate change will push many tree species into conditions that are outside their current climate envelopes. Using the Eucalyptus genus as a model, we addressed whether species with narrower geographical distributions show constrained ability to cope with warming relative to species with wider distributions, and whether this ability differs among species from tropical and temperate climates.
We grew seedlings of widely and narrowly distributed Eucalyptus species from temperate and tropical Australia in a glasshouse under two temperature regimes: the summer temperature at seed origin and +3.5°C. We measured physical traits and leaf‐level gas exchange to assess warming influences on growth rates, allocation patterns, and physiological acclimation capacity.
Warming generally stimulated growth, such that higher relative growth rates early in development placed seedlings on a trajectory of greater mass accumulation. The growth enhancement under warming was larger among widely than narrowly distributed species and among temperate rather than tropical provenances. The differential growth enhancement was primarily attributable to leaf area production and adjustments of specific leaf area.
Our results suggest that tree species, including those with climate envelopes that will be exceeded by contemporary climate warming, possess capacity to physiologically acclimate but may have varying ability to adjust morphology.
