Vascular plant‐mediated controls on atmospheric carbon assimilation and peat carbon decomposition under climate change

Climate change can alter peatland plant community composition by promoting the growth of vascular plants. How such vegetation change affects peatland carbon dynamics remains, however, unclear. In order to assess the effect of vegetation change on carbon uptake and release, we performed a vascular plant‐removal experiment in two Sphagnum‐dominated peatlands that represent contrasting stages of natural vegetation succession along a climatic gradient. Periodic measurements of net ecosystem CO₂ exchange revealed that vascular plants play a crucial role in assuring the potential for net carbon uptake, particularly with a warmer climate. The presence of vascular plants, however, also increased ecosystem respiration, and by using the seasonal variation of respired CO₂ radiocarbon (bomb‐¹⁴C) signature we demonstrate an enhanced heterotrophic decomposition of peat carbon due to rhizosphere priming. The observed rhizosphere priming of peat carbon decomposition was matched by more advanced humification of dissolved organic matter, which remained apparent beyond the plant growing season. Our results underline the relevance of rhizosphere priming in peatlands, especially when assessing the future carbon sink function of peatlands undergoing a shift in vegetation community composition in association with climate change.     

Climate change disequilibrium of boreal permafrost peatlands caused by local processes

Boreal forest and tundra are the biomes expected to experience the greatest warming during the course of the next century. The transient responses of boreal peatlands to climate change could be more complex than a simple large release of carbon and rapid migrations of vegetation and permafrost. Here we used alternative models to demonstrate that local processes typical of permafrost peatlands control carbon and vegetation dynamics in ways that strongly mediate effects of regional temperature gradients. Regional temperature affected stability and thaw rate. Thaw rate increased with mean annual temperature, and rates have accelerated within the last 50 yr. Local factors exerted a strong influence on stability, the levels of which were highest in three of the four temperature zones studied along the shaded south-southwest edges of collapse scars. The presence of Sphagnum fuscum cover increased stability. In all zones, survey points with S. fuscum showed more than twice the stability of points with feather moss, lichen, or no vegetation. In a direct model comparison between regional and local control, local factors were more important. Our results suggest that local processes mediate the effects of regional climate, and an accurate representation of ecosystem dynamics benefits from both local and regional processes.     

Long-term Perspectives on Lagged Ecosystem Responses to Climate Change: Permafrost in Boreal Peatlands and the Grassland/Woodland Boundary

Changes in climate could have far-reaching consequences for ecosystems sensitive to changes in temperature and precipitation, such as boreal permafrost peatlands and grassland/woodland boundaries. The long-term data from our studies in these ecosystems suggest that transient responses of permafrost and vegetation to climate change may be difficult to predict due to lags and positive feedbacks related to vegetation and disturbance. Boreal permafrost peatlands comprise an ecosystem with strong local controls on microclimate that influence the formation and thaw of permafrost. These local controls may preserve permafrost during the transient stages of climate warming, producing lagged responses. The prairie–forest border region of the northern Great Plains has experienced frequent change and has complex dynamics involving transitions in the grassland composition of prairie and in the degree of woodiness in bordering forests. Fire frequency interacts with fuel loading and tree recruitment in ways that affect the timing and direction of change. Lags and thresholds could lead to sudden large responses to future climate change that are not readily apparent from current vegetation. The creation of adequate models to characterize transient ecosystem changes will require an understanding of the linkages among processes operating at the scale of 10s of meters and over long time periods. Received 14 December 1999; accepted 7 July 2000.     

Climate change,woodpeckers, and forests: Current trends and future modeling needs

The structure and composition of forest ecosystems are expected to shift with climate‐induced changes in precipitation, temperature, fire, carbon mitigation strategies, and biological disturbance. These factors are likely to have biodiversity implications. However, climate‐driven forest ecosystem models used to predict changes to forest structure and composition are not coupled to models used to predict changes to biodiversity. We proposed integrating woodpecker response (biodiversity indicator) with forest ecosystem models. Woodpeckers are a good indicator species of forest ecosystem dynamics, because they are ecologically constrained by landscape‐scale forest components, such as composition, structure, disturbance regimes, and management activities. In addition, they are correlated with forest avifauna community diversity. In this study, we explore integrating woodpecker and forest ecosystem climate models. We review climate–woodpecker models and compare the predicted responses to observed climate‐induced changes. We identify inconsistencies between observed and predicted responses, explore the modeling causes, and identify the models pertinent to integration that address the inconsistencies. We found that predictions in the short term are not in agreement with observed trends for 7 of 15 evaluated species. Because niche constraints associated with woodpeckers are a result of complex interactions between climate, vegetation, and disturbance, we hypothesize that the lack of adequate representation of these processes in the current broad‐scale climate–woodpecker models results in model–data mismatch. As a first step toward improvement, we suggest a conceptual model of climate–woodpecker–forest modeling for integration. The integration model provides climate‐driven forest ecosystem modeling with a measure of biodiversity while retaining the feedback between climate and vegetation in woodpecker climate change modeling.     

Roles of Climate,Vegetation and Soil in Regulating the Spatial Variations in Ecosystem Carbon Dioxide Fluxes in the Northern Hemisphere

Climate, vegetation, and soil characteristics play important roles in regulating the spatial variation in carbon dioxide fluxes, but their relative influence is still uncertain. In this study, we compiled data from 241 eddy covariance flux sites in the Northern Hemisphere and used Classification and Regression Trees and Redundancy Analysis to assess how climate, vegetation, and soil affect the spatial variations in three carbon dioxide fluxes (annual gross primary production (AGPP), annual ecosystem respiration (ARE), and annual net ecosystem production (ANEP)). Our results showed that the spatial variations in AGPP, ARE, and ANEP were significantly related to the climate and vegetation factors (correlation coefficients, R = 0.22 to 0.69, P < 0.01) while they were not related to the soil factors (R = -0.11 to 0.14, P > 0.05) in the Northern Hemisphere. The climate and vegetation together explained 60 % and 58 % of the spatial variations in AGPP and ARE, respectively. Climate factors (mean annual temperature and precipitation) could account for 45 - 47 % of the spatial variations in AGPP and ARE, but the climate constraint on the vegetation index explained approximately 75 %. Our findings suggest that climate factors affect the spatial variations in AGPP and ARE mainly by regulating vegetation properties, while soil factors exert a minor effect. To more accurately assess global carbon balance and predict ecosystem responses to climate change, these discrepant roles of climate, vegetation, and soil are required to be fully considered in the future land surface models. Moreover, our results showed that climate and vegetation factors failed to capture the spatial variation in ANEP and suggest that to reveal the underlying mechanism for variation in ANEP, taking into account the effects of other factors (such as climate change and disturbances) is necessary.     

Robust dynamics of Amazon dieback to climate change with perturbed ecosystem model parameters

Climate change science is increasingly concerned with methods for managing and integrating sources of uncertainty from emission storylines, climate model projections, and ecosystem model parameterizations. In tropical ecosystems, regional climate projections and modeled ecosystem responses vary greatly, leading to a significant source of uncertainty in global biogeochemical accounting and possible future climate feedbacks. Here, we combine an ensemble of IPCC‐AR4 climate change projections for the Amazon Basin (eight general circulation models) with alternative ecosystem parameter sets for the dynamic global vegetation model, LPJmL. We evaluate LPJmL simulations of carbon stocks and fluxes against flux tower and aboveground biomass datasets for individual sites and the entire basin. Variability in LPJmL model sensitivity to future climate change is primarily related to light and water limitations through biochemical and water‐balance‐related parameters. Temperature‐dependent parameters related to plant respiration and photosynthesis appear to be less important than vegetation dynamics (and their parameters) for determining the magnitude of ecosystem response to climate change. Variance partitioning approaches reveal that relationships between uncertainty from ecosystem dynamics and climate projections are dependent on geographic location and the targeted ecosystem process. Parameter uncertainty from the LPJmL model does not affect the trajectory of ecosystem response for a given climate change scenario and the primary source of uncertainty for Amazon ‘dieback’ results from the uncertainty among climate projections. Our approach for describing uncertainty is applicable for informing and prioritizing policy options related to mitigation and adaptation where long‐term investments are required.     

Consistent centennial-scale change in European sub-Arctic peatland vegetation toward Sphagnum dominance—Implications for carbon sink capacity

Climate warming is leading to permafrost thaw in northern peatlands, and current predictions suggest that thawing will drive greater surface wetness and an increase in methane emissions. Hydrology largely drives peatland vegetation composition, which is a key element in peatland functioning and thus in carbon dynamics. These processes are expected to change. Peatland carbon accumulation is determined by the balance between plant production and peat decomposition. But both processes are expected to accelerate in northern peatlands due to warming, leading to uncertainty in future peatland carbon budgets. Here, we compile a dataset of vegetation changes and apparent carbon accumulation data reconstructed from 33 peat cores collected from 16 sub-arctic peatlands in Fennoscandia and European Russia. The data cover the past two millennia that has undergone prominent changes in climate and a notable increase in annual temperatures toward present times. We show a pattern where European sub-Arctic peatland microhabitats have undergone a habitat change where currently drier habitats dominated by Sphagnum mosses replaced wetter sedge-dominated vegetation and these new habitats have remained relatively stable over the recent decades. Our results suggest an alternative future pathway where sub-arctic peatlands may at least partly sustain dry vegetation and enhance the carbon sink capacity of northern peatlands.     

基于VAR模型的森林植被碳储量影响因素分析——以陕西省为例

森林作为陆地生态系统最大的碳库,对现在及未来的气候变化、碳平衡都具有重要影响。而对影响森林植被碳库的自然和非自然因素进行研究更是对增强森林的碳汇作用,继而改善生态环境状况意义重大。现有的森林动态模型虽然可以很好的模拟碳储量各影响因子之间的联系,但研究往往集中于小尺度从单一影响因素着手,且由于确定模型输入变量和参数的复杂性,使得这些模型在区域甚至更大尺度上的应用存在着一些困难。因此,运用VAR模型,以陕西省为例,构建森林植被碳储量与病虫害发生面积、木材产量、森林火灾面积、森林抚育面积、人工更新造林面积、降水和温度之间的动态关系,来验证该模型在省级尺度条件下的区域森林植被碳储量影响因素分析中的可行性。结果表明:各变量在5%的显著性水平下呈一阶单整序列并具有长期稳定的均衡关系,VAR模型也通过了平稳性检验满足运行的前提条件。通过脉冲响应和方差分解分析可知,森林病虫害、木材产量对陕西省森林植被碳储量呈现出很明显的负作用,并且贡献度很高,分别为5.61%和4.52%;森林抚育、人工更新造林对碳储量的影响存在一定的滞后期;火灾、温度和降水的冲击给碳储量带来的影响均不明显。模型较好的模拟了各影响因素对陕西省碳储量的影响,且具有一定的现实意义,因此,该模型可应用于省级尺度条件下的区域森林植被碳储量影响因素分析。     

中国陆地生态系统碳源/汇整合分析

国家尺度陆地生态系统碳收支及其循环过程的研究对于提升地球系统科学与全球变化科学的科技创新能力、提高我国参与应对全球气候变化国际行动和维护国家利益的话语权、保障国家生态安全和改进生态系统管理都具有重要意义。近年来,我国已经在气候变化与陆地生态系统碳循环领域开展了大量的研究工作,主要包括国家清查、生态系统模型模拟、大气反演等手段。然而,由于大尺度陆地生态系统碳源/汇的估算存在很大的不确定性,目前尚未形成国家尺度的陆地生态系统碳源/汇的整合分析。通过搜集已发表的关于中国陆地生态系统及其组分碳源/汇的59篇文献,整合国家清查、生态系统模型模拟、大气反演3种研究手段,分析中国陆地生态系统碳源/汇大小以及时间尺度上的动态变化。结果表明,在1960s-2010s期间中国陆地生态系统碳汇整体呈上升趋势,平均为（0.213±0.030）Pg C/a,其中森林、草地、农田和灌木生态系统碳汇分别为（0.101±0.023）Pg C/a、（0.032±0.007）Pg C/a、（0.043±0.010）Pg C/a和（0.028±0.010）Pg C/a。森林生态系统中的植被碳汇远大于土壤碳汇,然而这种格局在草地和农田生态系统却相反,而且1960s-2010s期间中国主要植被类型的生态系统碳汇总体上随时间呈增加趋势。融合多源数据（地面观测、激光雷达、卫星遥感等）、多尺度数据（样地尺度、站点尺度、区域尺度）以及多手段数据（联网观测、森林清查、模型模拟）,有助于全面准确地评估中国陆地生态系统碳源/汇及其对气候变化的响应。     

Biomass, Litter, and Soil Respiration Along a Precipitation Gradient in Southern Great Plains, USA

Knowledge of how ecosystem carbon (C) processes respond to variations in precipitation is crucial for assessing impacts of climate change on terrestrial ecosystems. In this study, we examined variations of shoot and root biomass, standing and surface litter, soil respiration, and soil C content along a natural precipitation gradient from 430 to 1200 mm in the southern Great Plains, USA. Our results show that shoot biomass and soil respiration increased linearly with mean annual precipitation (MAP), whereas root biomass and soil C content remained relatively constant along the precipitation gradient. Consequently, the root/shoot ratio linearly decreased with MAP. However, patterns of standing, surface, and total litter mass followed quadratic relationships with MAP along the gradient, likely resulting from counterbalance between litter production and decomposition. Those linear/quadratic equations describing variations of ecosystem C processes with precipitation could be useful for model development, parameterization, and validation at landscape and regional scales to improve predictions of C dynamics in grasslands in response to climate change. Our results indicated that precipitation is an important driver in shaping ecosystem functioning as reflected in vegetation production, litter mass, and soil respiration in grassland ecosystems.     

Holocene Carbon Accumulation of Fen Peatlands in Boreal Western Canada: A Complex Ecosystem Response to Climate Variation and Disturbance

Understanding the long-term ecological dynamics of northern peatlands is essential for assessment of the possible responses and feedbacks of these carbon-rich ecosystems to climate change and natural disturbance. I used high-resolution macrofossil and lithological analyses of a fen peatland in western Canada to infer the Holocene developmental history of the peatland, to document the temporal pattern of long-term peat accumulation, and to investigate ecosystems responses to climate changes in terms of species composition and carbon accumulation. The peatland has been dominated by sedges and brown mosses during its 10,000-year history, despite interruption by tephra deposition. Peat accumulation rates vary by more than an order of magnitude and decline from 5500 to 1300 cal BP, resulting in a convex depth–age curve, which contrasts with the carbon accumulation patterns documented for oceanic peatlands. The synthesis of regional data from continental western Canada indicates that fens tend to accumulate more carbon than bogs of the same ages. These data suggest that the carbon sink potential of northern peatlands has varied dramatically in the past, so estimates of the present and projected carbon sink strengths of these peatlands need to take this temporal variation into consideration. Widespread slowdown of peat accumulation over the last 4000 years may have resulted from climate cooling in northern latitudes after the Holocene insolation maximum. The findings indicate that long-term peatland dynamics are modified by many local and regional factors and that gradual environmental change may be capable of triggering abrupt shifts and jumps in ecosystem states.     

气候变化对森林土壤有机碳贮藏影响的研究进展

森林土壤有机碳库是全球碳循环的重要组成部分,其积累和分解的变化直接影响陆地生态系统的碳贮藏与全球的碳平衡.气候变化将影响植物光合作用及土壤有机碳的分解和转化过程,进而影响森林土壤有机碳贮量及土壤碳动态.温度、降水、大气CO2浓度等气候因子对森林土壤碳贮藏均具有重要影响.了解气候变化对森林土壤有机碳贮藏的影响有助于人们科学管理森林碳库以及进一步寻找缓解气候变化的可行途径.为此,本文综述了森林土壤有机碳贮量的分布以及升温、降水变化和大气CO2浓度升高对森林土壤有机碳贮藏影响的国内外研究进展,并提出了有关的研究展望.     

New coupled model used inversely for reconstructing past terrestrial carbon storage from pollen data: validation of model using modern data

The knowledge of potential impacts of climate change on terrestrial vegetation is crucial to understand long-term global carbon cycle development. Discrepancy in data has long existed between past carbon storage reconstructions since the Last Glacial Maximum by way of pollen, carbon isotopes, and general circulation model (GCM) analysis. This may be due to the fact that these methods do not synthetically take into account significant differences in climate distribution between modern and past conditions, as well as the effects of atmospheric CO₂ concentrations on vegetation. In this study, a new method to estimate past biospheric carbon stocks is reported, utilizing a new integrated ecosystem model (PCM) built on a physiological process vegetation model (BIOME4) coupled with a process-based biospheric carbon model (DEMETER). The PCM was constrained to fit pollen data to obtain realistic estimates. It was estimated that the probability distribution of climatic parameters, as simulated by BIOME4 in an inverse process, was compatible with pollen data while DEMETER successfully simulated carbon storage values with corresponding outputs of BIOME4. The carbon model was validated with present-day observations of vegetation biomes and soil carbon, and the inversion scheme was tested against 1491 surface pollen spectra sample sites procured in Africa and Eurasia. Results show that this method can successfully simulate biomes and related climates at most selected pollen sites, providing a coefficient of determination ( R ) of 0.83–0.97 between the observed and reconstructed climates, while also showing a consensus with an R -value of 0.90–0.96 between the simulated biome average terrestrial carbon variables and the available observations. The results demonstrate the reliability and feasibility of the climate reconstruction method and its potential efficiency in reconstructing past terrestrial carbon storage.     

Vascular plants promote ancient peatland carbon loss with climate warming

Northern peatlands have accumulated one third of the Earth's soil carbon stock since the last Ice Age. Rapid warming across northern biomes threatens to accelerate rates of peatland ecosystem respiration. Despite compensatory increases in net primary production, greater ecosystem respiration could signal the release of ancient, century‐ to millennia‐old carbon from the peatland organic matter stock. Warming has already been shown to promote ancient peatland carbon release, but, despite the key role of vegetation in carbon dynamics, little is known about how plants influence the source of peatland ecosystem respiration. Here, we address this issue using in situ ¹⁴C measurements of ecosystem respiration on an established peatland warming and vegetation manipulation experiment. Results show that warming of approximately 1 °C promotes respiration of ancient peatland carbon (up to 2100 years old) when dwarf‐shrubs or graminoids are present, an effect not observed when only bryophytes are present. We demonstrate that warming likely promotes ancient peatland carbon release via its control over organic inputs from vascular plants. Our findings suggest that dwarf‐shrubs and graminoids prime microbial decomposition of previously ‘locked‐up’ organic matter from potentially deep in the peat profile, facilitating liberation of ancient carbon as CO₂. Furthermore, such plant‐induced peat respiration could contribute up to 40% of ecosystem CO₂ emissions. If consistent across other subarctic and arctic ecosystems, this represents a considerable fraction of ecosystem respiration that is currently not acknowledged by global carbon cycle models. Ultimately, greater contribution of ancient carbon to ecosystem respiration may signal the loss of a previously stable peatland carbon pool, creating potential feedbacks to future climate change.     

西南喀斯特石漠化生态系统土壤有机碳分布特征及其影响因素

喀斯特石漠化已成为制约我国西南地区社会经济可持续发展最严重的生态地质环境问题,其恢复重建已成为我国社会经济建设中一项重要内容。土壤有机碳作为土壤质量评价的重要指标,可以综合反映土地生产力、环境健康功能,另一方面土壤有机碳也间接影响了陆地生物碳库,是陆地生态系统碳平衡的主要因子,它的转化和积累变化直接影响全球碳循环动态,已成为生态科学领域研究的热点之一。系统的总结了西南喀斯特石漠化地区不同土地覆被/土地利用、不同等级石漠化环境土壤有机碳的空间和季节分布特征。结合前人研究成果,进一步分析了影响喀斯特石漠化地区土壤有机碳分布的自然(气候、地形与土壤性质、植被等)和人为(土地覆被/土地利用变化、农业管理措施等)各因素,并提出增加喀斯特石漠化地区土壤有机碳含量的对策。研究结果为喀斯特石漠化退化生态系统恢复重建、石漠化地区土壤综合利用、增加碳截存应对全球碳循环减源增汇等提供了重要的科学参考。     

气候变暖对陆地植被-土壤生态系统的影响研究

由于自然因素及人类活动的长期影响,全球气候变化已经成为不容置疑的事实,并对陆地生态系统的植被及土壤产生了深远影响。陆地植被一土壤生态系统在全球气候变化中的反应与适应等过程已成为众多科学家所关注的问题。为更好地了解陆地植被一土壤生态系统对全球气候变化的响应机制,综述了气候变暖对植物的物候与生长、光合特征、生物量生产与分配,以及土壤呼吸等方面的影响,并对分析得到的结论进行了总结。分析指出,随着全球气候变暖,植物个体和群落特征以及土壤特性都会发生相应改变,高海拔地区的植被高度有增加趋势,而低海拔地区的植被可能出现矮化。然而,在以下方面还存有不确定性：（1）气候变暖导致的植被特征变化是否会减弱全球气候变化;（2）在较长时间尺度上气候变暖如何影响植物的物候和生长,特别是植物的体型;（3）高寒生态系统冬季土壤呼吸对气候变暖如何响应。     

The Impact of Fine-Scale Disturbances on the Predictability of Vegetation Dynamics and Carbon Flux

Predictions from forest ecosystem models are limited in part by large uncertainties in the current state of the land surface, as previous disturbances have important and lasting influences on ecosystem structure and fluxes that can be difficult to detect. Likewise, future disturbances also present a challenge to prediction as their dynamics are episodic and complex and occur across a range of spatial and temporal scales. While large extreme events such as tropical cyclones, fires, or pest outbreaks can produce dramatic consequences, small fine-scale disturbance events are typically much more common and may be as or even more important. This study focuses on the impacts of these smaller disturbance events on the predictability of vegetation dynamics and carbon flux. Using data on vegetation structure collected for the same domain at two different times, i.e. “repeat lidar data”, we test high-resolution model predictions of vegetation dynamics and carbon flux across a range of spatial scales at an important tropical forest site at La Selva Biological Station, Costa Rica. We found that predicted height change from a height-structured ecosystem model compared well to lidar measured height change at the domain scale (~150 ha), but that the model-data mismatch increased exponentially as the spatial scale of evaluation decreased below 20 ha. We demonstrate that such scale-dependent errors can be attributed to errors predicting the pattern of fine-scale forest disturbances. The results of this study illustrate the strong impact fine-scale forest disturbances have on forest dynamics, ultimately limiting the spatial resolution of accurate model predictions.     

Trend analysis of vegetation dynamics in Qinghai-Tibet Plateau using Hurst Exponent

As one of the most sensitive areas responding to global environmental change, especially global climate change, Qinghai-Tibet Plateau has been recognized as a hotspot for coupled studies on global terrestrial ecosystem change and global climate change. As an important component of terrestrial ecosystems, vegetation dynamic has become one of the key issues in global environmental change, and numerous case studies have been conducted on vegetation dynamic trend in different study periods. However, few are focused on the quantitative analysis of the consistency of vegetation dynamic trends after the study periods. In the study, taking Qinghai-Tibet Plateau as a case, vegetation dynamic trend during 1982-2003 were analyzed, with the application of the method of linear regression analysis. The results showed that, vegetation dynamics in Qinghai-Tibet Plateau experienced a significant increasing as a whole, with nearly 50% forest degradation in the study period. And among the 7 kinds of vegetation types, the change of forest was the most fluctuant with desert the least one. Furthermore, the consistency of vegetation dynamic trends after the study period, was quantified using Hurst Exponent and the method of R/S analysis. The results showed high consistency of future vegetation dynamic trends for the whole plateau, and inconsistent areas were mainly meadow and steppe distributed in the middle or east of the plateau. It was also convinced that, vegetation dynamic trends in the study area were significantly influenced by topography, especially the elevation.     

Integrating plant–soil interactions into global carbon cycle models

1.  Plant–soil interactions play a central role in the biogeochemical carbon (C), nitrogen (N) and hydrological cycles. In the context of global environmental change, they are important both in modulating the impact of climate change and in regulating the feedback of greenhouse gas emissions (CO₂, CH₄ and N₂O) to the climate system.
2.  Dynamic global vegetation models (DGVMs) represent the most advanced tools available to predict the impacts of global change on terrestrial ecosystem functions and to examine their feedbacks to climate change. The accurate representation of plant–soil interactions in these models is crucial to improving predictions of the effects of climate change on a global scale.
3.  In this paper, we describe the general structure of DGVMs that use plant functional types (PFTs) classifications as a means to integrate plant–soil interactions and illustrate how models have been developed to improve the simulation of: (a) soil carbon dynamics, (b) nitrogen cycling, (c) drought impacts and (d) vegetation dynamics. For each of these, we discuss some recent advances and identify knowledge gaps.
4.  We identify three ongoing challenges, requiring collaboration between the global modelling community and process ecologists. First, the need for a critical evaluation of the representation of plant–soil processes in global models; second, the need to supply and integrate knowledge into global models; third, the testing of global model simulations against large-scale multifactor experiments and data from observatory gradients.
5.   Synthesis . This paper reviews how plant–soil interactions are represented in DGVMs that use PFTs and illustrates some model developments. We also identify areas of ecological understanding and experimentation needed to reduce uncertainty in future carbon coupled climate change predictions.     

Contrasting ecosystem vegetation response in global drylands under drying and wetting conditions

Increasing aridity is one major consequence of ongoing global climate change and is expected to cause widespread changes in key ecosystem attributes, functions, and dynamics. This is especially the case in naturally vulnerable ecosystems, such as drylands. While we have an overall understanding of past aridity trends, the linkage between temporal dynamics in aridity and dryland ecosystem responses remain largely unknown. Here, we examined recent trends in aridity over the past two decades within global drylands as a basis for exploring the response of ecosystem state variables associated with land and atmosphere processes (e.g., vegetation cover, vegetation functioning, soil water availability, land cover, burned area, and vapor-pressure deficit) to these trends. We identified five clusters, characterizing spatiotemporal patterns in aridity between 2000 and 2020. Overall, we observe that 44.5% of all areas are getting dryer, 31.6% getting wetter, and 23.8% have no trends in aridity. Our results show strongest correlations between trends in ecosystem state variables and aridity in clusters with increasing aridity, which matches expectations of systemic acclimatization of the ecosystem to a reduction in water availability/water stress. Trends in vegetation (expressed by leaf area index [LAI]) are affected differently by potential driving factors (e.g., environmental, and climatic factors, soil properties, and population density) in areas experiencing water-related stress as compared to areas not exposed to water-related stress. Canopy height for example, has a positive impact on trends in LAI when the system is stressed but does not impact the trends in non-stressed systems. Conversely, opposite relationships were found for soil parameters such as root-zone water storage capacity and organic carbon density. How potential driving factors impact dryland vegetation differently depending on water-related stress (or no stress) is important, for example within management strategies to maintain and restore dryland vegetation.