Linking plant functional traits with ecosystem carbon fluxes in response to climate warming

Abstract

Rapid global warming significantly affects terrestrial carbon (C) cycling, altering climate feedbacks and amplifying uncertainty in ecosystem C balance projection under future climates. Although the direct impacts of warming on ecosystem C fluxes through changes in temperature and moisture are well studied, the indirect effects mediated by warming-induced shifts in plant communities remain poorly understood. A key challenge lies in quantifying these community-level changes under warming and linking them to ecosystem C cycling. Traditional frameworks based on broad functional groups or life forms often fail to capture species-specific responses to warming. In contrast, plant traits provide a mechanistic understanding of how plant species and communities respond to warming and regulate ecosystem C fluxes. This review highlights the potential of a trait-based framework to bridge this knowledge gap, unifying plant community responses to warming with their impacts on ecosystem C fluxes. By identifying key community-level traits and/or trait combinations, such a framework can improve predictions of ecosystem C cycling and improve model performance under future climate scenarios.

Graphical abstract

Keywords

plant traits / community traits / ecosystem carbon fluxes / climate warming

1 Introduction

Global surface temperatures have risen rapidly since the Industrial Revolution, with projections suggesting an increase of 1.5°C between 2030 and 2052, and up to 3°C by 2100 (Masson-Delmotte et al., 2022). This rapid warming significantly alters terrestrial carbon (C) cycling, which, in turn, affects climate feedbacks that may either amplify or mitigate future warming (Heimann and Reichstein, 2008; Fang et al., 2018). While understanding the impacts of warming on terrestrial ecosystem C cycling is critical, substantial uncertainties persist in modeling and predicting ecosystem C fluxes under future warming scenarios (Friedlingstein, 2015; Xia and Lu, 2020; Yuan et al., 2024). Much of this uncertainty stems from our limited knowledge of vegetation responses and their feedbacks to climate change.

Warming influences CO₂ fluxes not only by modifying environmental factors such as temperature and moisture, but also by altering plant communities, both of which are critical drivers of C cycling (Cahoon et al., 2012; Mekonnen et al., 2018). However, most studies focused primarily on environmental factors, usually neglecting vegetation dynamics (Ward et al., 2013), which introduces substantial biases in modeling C fluxes and predicting future climate trajectories.

Quantifying warming-induced changes in plant communities and linking these changes to ecosystem CO₂ fluxes remains a key challenge. Current approaches relying on plant functional groups often produce inconsistent results: the same functional group may respond differently across studies, and species within a group can exhibit divergent responses (Alatalo et al., 2020; Hu et al., 2021). In addition, some modeling studies have also found that plant functional type (PFT)-based parameterizations usually fail to capture the substantial variability in processes within the same PFT (Yang et al., 2021; Ren et al., 2025). Thus, the use of functional types in models predicting the C cycle under climate warming may introduce considerable uncertainty.

Plant traits, as measurable characteristics that reflect plants’ long-term responses and adaptations to environmental changes, offer a robust framework. Species with contrasting traits respond differently to climate change, driving shifts in community composition and structure (Wang et al., 2017; Xiao et al., 2021). These shifts, in turn, alter community-level traits, which directly drive ecosystem C cycling and feedback (Gross et al., 2017; Bjorkman et al., 2018). This trait-based approach offers two key advantages: (i) it reveals the mechanistic links between warming and plant community responses, and (ii) it provides quantitative metrics to assess vegetation dynamics and their impacts on CO₂ fluxes. This perspective therefore provides novel insights into how ecosystem structure and function respond to warming and reveals the underlying mechanisms involved.

2 Uncertainty in warming impacts on plant community

Long-term observations (Boutin et al., 2017; Myers-Smith et al., 2019), model simulations (Botkin et al., 2007), and manipulative experiments (Cowles et al., 2016; Zhu et al., 2020) consistently show that climate warming drives shifts in plant communities worldwide. However, the impact of these warming-induced shifts on ecosystem CO₂ fluxes remains poorly understood. A major challenge lies in quantifying these community changes and linking them to ecosystem C cycling.

Numerous studies have attempted to quantify plant community dynamics by categorizing plants into functional types or life forms. However, this simplified approach often fails to capture the complexity of plant responses, leading to inconsistent results. For example, in Arctic tundra ecosystems, warming has been shown to favor shrubs and herbaceous plants (Walker et al., 2006; Myers-Smith et al., 2019), but no significant changes have been observed in these groups in northern wetlands (Mäkiranta et al., 2018) and alpine meadows (Price and Waser, 2000) under similar warming conditions. Moreover, even within the same functional group or life form, individual species often respond differently to warming. For instance, warming has been found to reduce moss abundance in Arctic regions (Alatalo et al., 2020) and shrubs in peatlands (Weltzin et al., 2003), yet some species within these groups have increased while others decreased. In Arctic tundra grasslands, the overall increase in grasses is driven by a few species, while others remained unaffected by warming (Myers-Smith et al., 2019). A similar pattern emerges on the Qinghai-Xiazang Plateau, where warming decreases the abundance of forbs but has no effect on sedges, despite some species within both groups increasing (Hu et al., 2021).

3 Plant species trait as mechanistic predictors of community responses to warming

The divergent responses suggest that the current framework, based on broad functional categories, is inadequate for predicting and understanding how plant communities respond to climate warming. However, plant traits offer a more unified approach to understanding of species’ complex responses to warming, transcending the limitations of taxonomic classifications (e.g., functional type, life form, photosynthetic pathway). For example, in temperature-limited ecosystems, warming has been shown to enhance vegetation biomass and height, intensifying aboveground light competition (Hu et al., 2021). This shift confers a competitive advantage to taller species, resulting in the exclusion of shorter plants. Warming-induced soil drought can favor species with root traits conducive to efficient water acquisition, leading to an increase in grasses and a decline in sedges and forbs (Ganjurjav et al., 2016; Liu et al., 2018). However, some forb species, despite overall declines, have exhibited increased abundance due to traits such as underground storage organs, climbing growth habits, and parasitic strategies, which allow them to secure resources by extracting water and nutrients from neighboring plants (Li et al., 2021). Moreover, a range of leaf traits, including leaf size, leaf nutrient content and specific leaf area, can also influence plant community responses to warming (Bjorkman et al., 2020; Zhu et al., 2020). Species with distinct traits exhibit specific responses to warming, leading to shifts in plant community composition. Studies have shown that plant communities are shifting toward more thermophilic compositions under warming, a trend observed at regional (Boutin et al., 2017), national (Martin et al., 2019), and continental scales (Feeley et al., 2020).

These evidences suggest that plant species traits, as measurable characteristics reflecting plants’ long-term responses and adaptations to environmental changes, can offer a robust framework for elucidating how plant communities respond to warming and the underlying mechanisms. By linking observed patterns to these traits, researchers can gain deeper insights into vegetation responses across species, functional groups, and ecosystems. Identifying these thermophilic traits or trait combinations is crucial for understanding plant community responses to warming and predicting their future dynamics. However, current research remains limited, highlighting the need for further investigation in this area.

4 Community traits linking community shifts to ecosystem C fluxes

Growing evidence indicates that changes in plant community can significantly influence ecosystem C fluxes, often exceeding the effects of environmental factors (Cahoon et al., 2012; Ward et al., 2013 and 2015). However, substantial knowledge gaps remain in understanding how changes in plant communities influence the direction, magnitude, and climate sensitivity of ecosystem C fluxes, as well as the underlying mechanisms driving these processes. Extensive studies across diverse ecosystems and vegetation types have reported contrasting effects of warming-induced plant community shifts on ecosystem CO₂ fluxes. For instance, in US tallgrass and temperate prairies, changes in the C3/C4 ratio under warming significantly promoted soil CO₂ emissions (Xu et al., 2015) and reduced soil C storage (Pendall et al., 2011). Similarly, in the coastal wetlands of the Yellow River Delta, warming shifted the relative abundance of two dominant species, leading to decreased net ecosystem productivity (NEP) and ecosystem C sink (Sun et al., 2021). Conversely, in the alpine meadows of the Qinghai-Xizang Plateau, warming increased grasses and forbs while reducing sedges, leading to higher NEP (Peng et al., 2017). However, these studies often span various ecosystems, with various biotic and abiotic confounding effects. This heterogeneity makes it challenging to isolate the effects of plant community change and the underlying mechanisms (D’Orangeville et al., 2016; Kim et al., 2017; Xu et al., 2020).

Few warming experiments have explored how changes in plant community composition influence C fluxes through targeted removal of specific functional groups. An early warming experiment incorporating functional group manipulations revealed that while warming enhanced NEP in shrub-dominated communities, it reduced NEP when herbaceous plants were present. These contrasting responses were attributed to differences in photosynthetic rates, resource allocation, litter chemistry, and soil microbial communities among functional groups (Ward et al., 2013, 2015). Unlike plant manipulation experiments that randomly remove or combine plant functional types, warming-induced shifts in plant communities are usually directional. This key difference suggests that random species manipulation cannot properly reveal how warming-induced vegetation changes affect C cycling processes and its feedback to warming. Furthermore, as previously discussed, plant responses to warming can vary significantly both within and among functional groups, such as C3/C4 (Cowles et al., 2016), shrubs/herbs (Alatalo et al., 2020), or grasses/sedges/forbs (Ganjurjav et al., 2016). It is not feasible to determine which plant functional groups or life forms should be removed in a way that reflects the complexity of warming-induced changes. Moreover, the directional shifts in plant community are shaped by trait-based environmental filtering. Under this warming filtering condition, plant communities tend to retain species with more similar and converging traits. The loss of functional complementarity under warming can reduce the community's capacity to buffer environmental fluctuations, potentially leading to greater variability in ecosystem C fluxes (Chen et al., 2020; Wolf et al., 2021). Such processes and mechanisms are difficult to capture through experiments involving random species removal or manipulation.

Plant community traits, derived from individual species traits and weighted by community composition, provide a crucial link between plant community structure and ecosystem processes. Species with different traits respond differently to climate change, driving shifts in community composition and structure (Wang et al., 2017; Xiao et al., 2021). These shifts, in turn, alter community-level traits, offering an effective way to quantify vegetation dynamics and their impacts on ecosystem CO₂ fluxes (Gross et al., 2017; Bjorkman et al., 2018). Studies have shown that community-level traits such as chlorophyll content, specific leaf area, and stomatal conductance can effectively explain variations in ecosystem CO₂ flux (Wolz et al., 2017; Durán et al., 2019). Furthermore, research has demonstrated that ecosystem CO₂ fluxes respond hierarchically to global change, with plant height playing a significant role in mediating these responses (Liao et al., 2024; Quan et al., 2024). These findings not only clarify complex community processes but also establish direct links between plant traits and ecosystem function.

5 The trait-based framework

In the face of climate change, growing attention has been paid to understanding how warming-driven shifts in plant communities influence ecosystem C cycling and associated C-climate feedbacks. A key challenge lies in predicting and quantifying warming-induced vegetation changes and linking them to ecosystem C dynamics. The trait-based approach offers a promising path forward by integrating these processes into a unified framework (Fig. 1). This framework links individual-level traits (e.g., specific leaf area, plant height, and leaf nitrogen content) to community-level properties using metrics such as the community-weighted mean and functional diversity. By integrating these metrics, the framework captures both the dominant trait within a community and the range of functional strategies present, which together govern C uptake and release. At its core, the trait-based framework seeks to identify the key traits or trait combinations that mediate plant community responses to warming and regulate ecosystem CO₂ fluxes. These insights provide a theoretical basis for incorporating trait indicators into ecosystem models, thereby enhancing the accuracy of ecosystem C flux simulations and improving projections of ecosystem responses under future climate scenarios.

A recent study that combined a field warming experiment with a regional transect investigation on the high-elevation Qinghai-Xizang Plateau provided a trait-based perspective on how plant communities respond to warming and regulate ecosystem C fluxes in cold and high-altitude region. This study suggested that warming promoted plant growth and intensified aboveground competition for light, favoring taller species. Warming not only increased the height of plant species but also raised the proportion of taller species, collectively promoting the overall height of the plant community. These changes enhanced NEP, its temperature sensitivity and soil C storage (Quan et al., 2024). As a key trait in the cold and high-elevation biomes, plant height plays a central role in mediating both plant community composition and ecosystem C sequestration under warming (Fig. 2). This trait-based linkage of climate warming, plant community structure and traits, and ecosystem CO₂ fluxes, offers a novel perspective for predicting the direction, magnitude, and sensitivity of ecosystem C fluxes in a warming world.

However, despite the vast number of studies on climate warming, C fluxes and plant traits individually (Fig. 3), only about 4% to 10% of these publications involve cross-disciplinary research, and just 283 (0.03%) papers have explicitly used plant traits to understand the effects of global warming on C fluxes. Given the demonstrated effectiveness of plant traits in explaining how plants and communities respond to warming and regulate ecosystem C dynamics (He et al., 2019; Quan et al., 2024), such integrative research remains significantly underdeveloped. Nonetheless, it is worth affirming that over the past decade, an increasing number of studies have begun to employ plant traits as a bridge liking climate warming and C fluxes (Fig. 3). This suggests that trait-based approaches will become more prevalent in future investigations of global change impact of global warming on the C cycle.

6 Improving ecosystem models with community traits

Ecosystems models commonly classify vegetation into PFTs, such as C₃ and C₄ plants, to assign photosynthetic and water-use efficiency parameters based on flux data (Kowalczyk et al., 2006; Mauritsen et al., 2019; Danabasoglu et al., 2020). While this classification has facilitated global modeling of carbon and water fluxes, evidence from trait-based studies indicates that PFTs often fail to capture the full spectrum of trait diversity within plant communities. Specifically, they may underestimate average trait values or fail to reflect the broad variability observed in situ (Kattge et al., 2009; Van Bodegom et al., 2012). Hence, models need to use trait data to parameterize models instead of relying solely on PFTs.

And indeed, some processes in models are represented using plant traits, like the C and nitrogen (C:N) ratio, which could affect plant photosynthesis and respirations (Kowalczyk et al., 2006; Danabasoglu et al., 2020; Wang et al., 2021, 2022b). However, many models still rely on trait data from a limited number of species or use simple arithmetic means, which poorly represent the functional diversity and structure of entire plant communities. Hence, incorporating community-level traits information, such as community-weighted means and functional diversity, can improve the ecological realism and predictive accuracy of these models.

In addition, advances in trait-based research are paving the way for a new generation of ecosystem models that incorporate a broader range of vegetation traits (He et al., 2019). Increasingly, researchers recognize that incorporating more trait parameters is an effective measure to enhances model performance (Larson and Funk, 2016; Lu et al., 2017; Wang et al., 2022a). As trait databases continue to expand, future models will likely integrate more community-level traits, thereby improving the accuracy of carbon cycle simulations under changing climate conditions.

7 Conclusions

Climate warming profoundly affects plant communities and ecosystem C dynamics, presenting both a critical research challenge and policy concern. Plant traits offer a powerful, mechanistic framework for linking community composition changes to ecosystem C fluxes under warming, offering valuable insights into these intricate interactions. Future research should focus on integrating trait-based framework with long-term experimental observations and ecosystem modeling to improve predictions of C cycling across diverse ecosystems. Identifying key traits that govern plant responses to warming, particularly those influencing growth, competition, and resource acquisition, will enhance our ability to predict ecosystem productivity and carbon sequestration under future climate scenarios. Furthermore, incorporating community-level traits into ecological models, alongside traditional plant functional types, will improve the accuracy and sensitivity of C flux projections.

References

[1] Alatalo J M, Jägerbrand A K, Erfanian M B, Chen S, Sun S Q, Molau U (2020). Bryophyte cover and richness decline after 18 years of experimental warming in alpine Sweden.AoB Plants, 12: plaa061

[2] Bjorkman A D, García Criado M, Myers-Smith I H, Ravolainen V, Jónsdóttir I S, Westergaard K B, Lawler J P, Aronsson M, Bennett B, Gardfjell H, Heiðmarsson S, Stewart L, Normand S (2020). Status and trends in Arctic vegetation: evidence from experimental warming and long-term monitoring.Ambio, 49: 678–692

[3] Bjorkman A D, Myers-Smith I H, Elmendorf S C, Normand S, Rüger N, Beck P S A, Blach-Overgaard A, Blok D, Cornelissen J H C, Forbes B C, Georges D, Goetz S J, Guay K C, Henry G H R, HilleRisLambers, J, Hollister R D, Karger D N, Kattge J, Manning P, Prevéy J S, Rixen C, Schaepman-Strub G, Thomas H J D, Vellend M, Wilmking M, Wipf S, Carbognani M, Hermanutz L, Lévesque E, Molau U, Petraglia A, Soudzilovskaia N A, Spasojevic M J, Tomaselli M, Vowles T, Alatalo J M, Alexander H D, Anadon-Rosell A, Angers-Blondin S, Beest M te, Berner L, Björk R G, Buchwal A, Buras A, Christie K, Cooper E J, Dullinger S, Elberling B, Eskelinen A, Frei E R, Grau O, Grogan P, Hallinger M, Harper K A, Heijmans M M P D, Hudson J, Hülber K, Iturrate-Garcia M, Iversen C M, Jaroszynska F, Johnstone J F, Jørgensen R H, Kaarlejärvi E, Klady R, Kuleza S, Kulonen A, Lamarque L J, Lantz T, Little C J, Speed J D M, Michelsen A, Milbau A, Nabe-Nielsen J, Nielsen S S, Ninot J M, Oberbauer S F, Olofsson J, Onipchenko V G, Rumpf S B, Semenchuk P, Shetti R, Collier L S, Street L E, Suding K N, Tape K D, Trant A, Treier U A, Tremblay J. -P, Tremblay M, Venn S, Weijers S, Zamin T, Boulanger-Lapointe N, Gould W A, Hik D S, Hofgaard A, Jónsdóttir I S, Jorgenson J, Klein J, Magnusson B, Tweedie C, Wookey P A, Bahn M, Blonder B, van Bodegom P M, Bond-Lamberty B, Campetella G, Cerabolini B E L, Chapin F S, Cornwell W K, Craine J, Dainese M, de Vries F T, Díaz S, Enquist B J, Green W, Milla R, Niinemets Ü, Onoda Y, Ordoñez J C, Ozinga W A, Penuelas J, Poorter H, Poschlod P, Reich P B, Sandel B, Schamp B, Sheremetev S, Weiher E (2018). Plant functional trait change across a warming tundra biome. Nature, 562: 57-62

[4] Botkin D B, Saxe H, Araújo M B, Betts R, Bradshaw , R H W, Cedhagen T, Chesson P, Dawson T P, Etterson J R, Faith D P, Ferrier S, Guisan A, Hansen A S, Hilbert D W, Loehle C, Margules C, New M, Sobel M J, Stockwell D R B (2007). Forecasting the effects of global warming on biodiversity.Bioscience, 57: 227–236

[5] Boutin M, Corcket E, Alard D, Villar L, Jiménez J J, Blaix C, Lemaire C, Corriol G, Lamaze T, Pornon A (2017). Nitrogen deposition and climate change have increased vascular plant species richness and altered the composition of grazed subalpine grasslands.J Ecol, 105: 1199–1209

[6] Cahoon S M P, Sullivan P F, Shaver G R, Welker J M, Post E, Holyoak M (2012). Interactions among shrub cover and the soil microclimate may determine future Arctic carbon budgets.Ecol Lett, 15: 1415–1422

[7] Chen Y, Huang Y, Niklaus P A, Castro-Izaguirre N, Clark A T, Bruelheide H, Ma K, Schmid B (2020). Directed species loss reduces community productivity in a subtropical forest biodiversity experiment.Nat Ecol Evol, 4: 550–559

[8] Cowles J M, Wragg P D, Wright A J, Powers J S, Tilman D (2016). Shifting grassland plant community structure drives positive interactive effects of warming and diversity on aboveground net primary productivity.Glob Change Biol, 22: 741–749

[9] D’Orangeville L, Duchesne L, Houle D, Kneeshaw D, Côté B, Pederson N (2016). Northeastern North America as a potential refugium for boreal forests in a warming climate.Science, 352: 1452–1455

[10] Danabasoglu G, Lamarque J F, Bacmeister J, Bailey D A, DuVivier A K, Edwards J, Emmons L K, Fasullo J, Garcia R, Gettelman A, Hannay C, Holland M M, Large W G, Lauritzen P H, Lawrence D M, Lenaerts J T M, Lindsay K, Lipscomb W H, Mills M J, Neale R, Oleson K W, Otto-Bliesner B, Phillips A S, Sacks W, Tilmes S, van Kampenhout L, Vertenstein M, Bertini A, Dennis J, Deser C, Fischer C, Fox-Kemper B, Kay J E, Kinnison D, Kushner P J, Larson V E, Long M C, Mickelson S, Moore J K, Nienhouse E, Polvani L, Rasch P J, Strand W G (2020). The Community Earth System Model Version 2 (CESM2).J Adv Model Earth Syst, 12: e2019MS001916

[11] Durán S M, Martin R E, Díaz S, Maitner B S, Malhi Y, Salinas N, Shenkin A, Silman M R, Wieczynski D J, Asner G P, Bentley L P, Savage V M, Enquist B J (2019). Informing trait-based ecology by assessing remotely sensed functional diversity across a broad tropical temperature gradient.Sci Adv, 5: eaaw8114

[12] Fang J, Zhu J, Shi Y (2018). How will ecosystems respond to global warming? IB-CAS, 63 Available at Institute of Botany, Chinese Academy of Sciences website

[13] Feeley K J, Bravo-Avila C, Fadrique B, Perez T M, Zuleta D (2020). Climate-driven changes in the composition of New World plant communities.Nat Clim Chang, 10: 965–970

[14] Friedlingstein P (2015). Carbon cycle feedbacks and future climate change. Philos Trans- Royal Soc, Math Phys Eng Sci, 373: 20140421

[15] Ganjurjav H, Gao Q, Gornish E S, Schwartz M W, Liang Y, Cao X, Zhang W, Zhang Y, Li W, Wan Y, Li Y, Danjiu L, Guo H, Lin E (2016). Differential response of alpine steppe and alpine meadow to climate warming in the central Qinghai–Tibetan Plateau.Agric For Meteorol, 223: 233–240

[16] Gross N, Bagousse-Pinguet Y L, Liancourt P, Berdugo M, Gotelli N J, Maestre F T (2017). Functional trait diversity maximizes ecosystem multifunctionality.Nat Ecol Evol, 1: 1–9

[17] He N, Liu C, Piao S, Sack L, Xu L, Luo Y, He J, Han X, Zhou G, Zhou X, Lin Y, Yu Q, Liu S, Sun W, Niu S, Li S, Zhang J, Yu G (2019). Ecosystem traits linking functional traits to macroecology.Trends Ecol Evol, 34: 200–210

[18] Heimann M, Reichstein M (2008). Terrestrial ecosystem carbon dynamics and climate feedbacks.Nature, 451: 289–292

[19] Hu X, Zhou W, Li X, Niklas K J, Sun S (2021). Changes in community composition induced by experimental warming in an alpine meadow: beyond plant functional type.Front Ecol Evol, 9: 569422

[20] Kattge J, Knorr W, Raddatz T, Wirth C (2009). Quantifying photosynthetic capacity and its relationship to leaf nitrogen content for global-scale terrestrial biosphere models.Glob Change Biol, 15: 976–991

[21] Kim J S, Kug J S, Jeong S J, Huntzinger D N, Michalak A M, Schwalm C R, Wei Y, Schaefer K (2017). Reduced North American terrestrial primary productivity linked to anomalous Arctic warming.Nat Geosci, 10: 572–576

[22] Kowalczyk E, Wang Y, Law R, Davies H, Mcgregor J, Abramowitz G (2006). The CSIRO Atmosphere Biosphere Land Exchange (CABLE) model for use in climate models and as an offline model. CSIRO Marine and Atmospheric Research Paper 13, 42

[23] Larson J E, Funk J L (2016). Regeneration: an overlooked aspect of trait-based plant community assembly models.J Ecol, 104: 1284–1298

[24] Li C, Lai C, Peng F, Xue X, You Q, Liu F, Guo P, Liao J, Wang T, 2021 (2021). Dominant plant functional group determine the response of the temporal stability of plant community biomass to 9-year warming on the Qinghai–Tibetan Plateau.Front Plant Sci, 12: 704138

[25] Liao J, Quan Q, Ma F, Peng J, Niu S (2024). Plant height bridges hierarchical community responses to nitrogen enrichment.J Ecol, 112: 2069–2081

[26] Liu H, Mi Z, Lin L, Wang Y, Zhang Z, Zhang F, Wang H, Liu L, Zhu B, Cao G, Zhao X, Sanders N J (2018). Shifting plant species composition in response to climate change stabilizes grassland primary production.Proc Natl Acad Sci USA, 115: 4051–4056

[27] Lu X, Wang Y P, Wright I J, Reich P B, Shi Z, Dai Y (2017). Incorporation of plant traits in a land surface model helps explain the global biogeographical distribution of major forest functional types.Glob Ecol Biogeogr, 26: 304–317

[28] Mäkiranta P, Laiho R, Mehtätalo L, Straková P, Sormunen J, Minkkinen K, Penttilä T, Fritze H, Tuittila E S (2018). Responses of phenology and biomass production of boreal fens to climate warming under different water-table level regimes.Glob Change Biol, 24: 944–956

[29] Martin G, Devictor V, Motard E, Machon N, Porcher E (2019). Short-term climate-induced change in French plant communities.Biol Lett, 15: 2019028

[30] Masson-Delmotte V, Pörtner H O, Skea J, Zhai P, Roberts D, Shukla P R, Pirani A, Pidcock R, Chen Y, Lonnoy E, Moufouma-Okia W, Péan C, Connors S, Matthews J B R, Zhou X, Gomis M I, Maycock T, Tignor M, Waterfield T (2022). Global Warming of 1.5 C: IPCC special report on impacts of global warming of 1.5 C above pre-industrial levels in context of strengthening response to climate change, sustainable development, and efforts to eradicate poverty.

[31] Mauritsen T, Bader J, Becker T, Behrens J, Bittner M, Brokopf R, Brovkin V, Claussen M, Crueger T, Esch M, Fast I, Fiedler S, Fläschner D, Gayler V, Giorgetta M, Goll D S, Haak H, Hagemann S, Hedemann C, Hohenegger C, Ilyina T, Jahns T, Jimenéz-de-la-Cuesta D, Jungclaus J, Kleinen T, Kloster S, Kracher D, Kinne S, Kleberg D, Lasslop G, Kornblueh L, Marotzke J, Matei D, Meraner K, Mikolajewicz U, Modali K, Möbis B, Müller W A, Nabel J E M S, Nam C C W, Notz D, Nyawira S S, Paulsen H, Peters K, Pincus R, Pohlmann H, Pongratz J, Popp M, Raddatz T J, Rast S, Redler R, Reick C H, Rohrschneider T, Schemann V, Schmidt H, Schnur R, Schulzweida U, Six K D, Stein L, Stemmler I, Stevens B, Storch J S von, Tian F, Voigt A, Vrese P, Wieners K H, Wilkenskjeld S, Winkler A, Roeckner E (2019). Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2) and its response to increasing CO₂.J Adv Model Earth Syst, 11: 998–1038

[32] Mekonnen Z A, Riley W J, Grant R F (2018). 21st century tundra shrubification could enhance net carbon uptake of North America Arctic tundra under an RCP8.5 climate trajectory.Environ Res Lett, 13: 054029

[33] Myers-Smith I H, Grabowski M M, Thomas H J D, Angers-Blondin S, Daskalova G N, Bjorkman A D, Cunliffe A M, Assmann J J, Boyle J S, McLeod E, McLeod S, Joe R, Lennie P, Arey D, Gordon R R, Eckert C D (2019). Eighteen years of ecological monitoring reveals multiple lines of evidence for tundra vegetation change.Ecol Monogr, 89: e01351

[34] Pendall E, Osanai Y, Williams A L, Hovenden M J (2011). Soil carbon storage under simulated climate change is mediated by plant functional type.Glob Change Biol, 17: 505–514

[35] Peng F, Xue X, Xu M, You Q, Jian G, Ma S (2017). Warming-induced shift towards forbs and grasses and its relation to the carbon sequestration in an alpine meadow.Environ Res Lett, 12: 044010

[36] Price M V, Waser N M (2000). Responses of subalpine meadow vegetation to four years of experimental warming.Ecol Appl, 10: 811–823

[37] Quan Q, He N, Zhang R, Wang J, Luo Y, Ma F, Pan J, Wang R, Liu C, Zhang J, Wang Y, Song B, Li Z, Zhou Q, Yu G, Niu S (2024). Plant height as an indicator for alpine carbon sequestration and ecosystem response to warming.Nat Plants, 10: 890–900

[38] Ren Y, Wang H, Harrison S P, Prentice I C, Mengoli G, Zhao L, Reich P B, Yang K (2025). Incorporating the acclimation of photosynthesis and leaf respiration in the Noah-MP land surface model: model development and evaluation.J Adv Model Earth Syst, 17: e2024MS004599

[39] Sun B, Yan L, Jiang M, Li X, Han G, Xia J (2021). Reduced magnitude and shifted seasonality of CO₂ sink by experimental warming in a coastal wetland.Ecology, 102: e03236

[40] Van Bodegom P M, Douma J C, Witte J P M, Ordoñez J C, Bartholomeus R P, Aerts R (2012). Going beyond limitations of plant functional types when predicting global ecosystem–atmosphere fluxes: exploring the merits of traits-based approaches.Glob Ecol Biogeogr, 21: 625–636

[41] Walker M D, Wahren C H, Hollister R D, Henry G H R, Ahlquist L E, Alatalo J M, Bret-Harte M S, Calef M P, Callaghan T V, Carroll A B, Epstein H E, Jónsdóttir I S, Klein J A, Magnússon B, Molau U, Oberbauer S F, Rewa S P, Robinson C H, Shaver G R, Suding K N, Thompson C C, Tolvanen A, Totland Ø, Turner P L, Tweedie C E, Webber P J, Wookey P A (2006). Plant community responses to experimental warming across the tundra biome.Proc Natl Acad Sci USA, 103: 1342–1346

[42] Wang G, Gao Q, Yang Y, Hobbie S E, Reich P B, Zhou J (2022a). Soil enzymes as indicators of soil function: a step toward greater realism in microbial ecological modeling.Glob Change Biol, 28: 1935–1950

[43] Wang P, Limpens J, Mommer L, van Ruijven J, Nauta A L, Berendse F, Schaepman Strub G, Blok D, Maximov T C, Heijmans M M P D (2017). Above- and below-ground responses of four tundra plant functional types to deep soil heating and surface soil fertilization.J Ecol, 105: 947–957

[44] Wang S, Luo Y, Niu S (2022b). Reparameterization required after model structure changes from carbon only to carbon-nitrogen coupling.J Adv Model Earth Syst, 14: e2021MS002798

[45] Wang S, Quan Q, Meng C, Chen W, Luo Y, Niu S (2021). Experimental warming shifts coupling of carbon and nitrogen cycles in an alpine meadow.J Plant Ecol, 14: 541–554

[46] Ward S E, Orwin K H, Ostle N J, Briones M J I, Thomson B C, Griffiths R I, Oakley S, Quirk H, Bardgett R D (2015). Vegetation exerts a greater control on litter decomposition than climate warming in peatlands.Ecology, 96: 113–123

[47] Ward S E, Ostle N J, Oakley S, Quirk H, Henrys P A, Bardgett R D (2013). Warming effects on greenhouse gas fluxes in peatlands are modulated by vegetation composition.Ecol Lett, 16: 1285–1293

[48] Weltzin J F, Bridgham S D, Pastor J, Chen J, Harth C (2003). Potential effects of warming and drying on peatland plant community composition.Glob Change Biol, 9: 141–151

[49] Wolf A A, Funk J L, Selmants P C, Morozumi C N, Hernández D L, Pasari J R, Zavaleta E S (2021). Trait-based filtering mediates the effects of realistic biodiversity losses on ecosystem functioning.Proc Natl Acad Sci USA, 118: e2022757118

[50] Wolz K J, Wertin T M, Abordo M, Wang D, Leakey A D B (2017). Diversity in stomatal function is integral to modelling plant carbon and water fluxes.Nat Ecol Evol, 1: 1292–1298

[51] Xia J, Lu R L, Zhu C, Cui E Q, Du Y, Huang K, Sun B Y (2020). Response and adaptation of terrestrial ecosystem processes to climate warming.Acta Phytoecol Sin, 44: 494–514

[52] Xiao Y, Liu X, Zhang L, Song Z, Zhou S (2021). The allometry of plant height explains species loss under nitrogen addition. Ecol Lett

[53] Xu B, Arain M A, Black T A, Law B E, Pastorello G Z, Chu H (2020). Seasonal variability of forest sensitivity to heat and drought stresses: a synthesis based on carbon fluxes from North American forest ecosystems.Glob Change Biol, 26: 901–918

[54] Xu X, Shi Z, Li D, Zhou X, Sherry R A, Luo Y (2015). Plant community structure regulates responses of prairie soil respiration to decadal experimental warming.Glob Change Biol, 21: 3846–3853

[55] Yang H, Ciais P, Wang Y, Huang Y, Wigneron J P, Bastos A, Chave J, Chang J, E. Doughty C, Fan L, Goll D, Joetzjer E, Li W, Lucas R, Quegan S, Le Toan T, Yu K (2021). Variations of carbon allocation and turnover time across tropical forests.Glob Ecol Biogeogr, 30: 1271–1285

[56] Yuan W, Xia J, Song C, Wang Y P (2024). Simulating the land carbon sink: progresses and challenges of terrestrial ecosystem models.Agric For Meteorol, 358: 110264

[57] Zhu J, Zhang Y, Yang X, Chen N, Li S, Wang P, Jiang L (2020). Warming alters plant phylogenetic and functional community structure. J Ecol, 108

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