Relative contributions of biotic and abiotic factors to the spatial variation of litter stock in a mature subtropical forest

Aims Dead plant material(i.e.litter)is the major source of soil organic matter and thus plays a fundamental role in regulating soil carbon cycling in global forest ecosystems.The storage of litter is jointly determined by its production from plants and decomposition in a given environment.However,only few studies have explored the relative importance of en-vironmental(i.e.abiotic)and plant(i.e.biotic)factors in driving the spa-tial variation of litter mass.The objective of this study is to quantify the relative contributions of biotic and abiotic factors in affecting the spatial variation of aboveground litter stock in a mature subtropical forest.Methods The aboveground litter mass was sampled in 187 grids of a 20-hm forest dynamics plot in a subtropical broad-leave forest in eastern China.The contributions of environmental variables,topographical and species variables on litter stocks were quantified by the boosted regression tree analysis.Important Findings The mean aboveground litter stock was 367.5 g m^(−2) in the Tiantong dynamics forest plot across all the 187 grids.The litter stock ranged from 109.2 to 831.3 g m^(−2) and showed a large spatial variation with the coefficient of variance as 40.8%.The boosted regression tree analysis showed that slope elevation and soil moisture were the most influential variables on the spatial variation of litter stock.The relatively influence of abiotic factors(environmental and topographical factors)was 71.4%,which is larger than biotic factors(28.6%).Overall,these findings sug-gest that abiotic factors play a more important role than plants in driving the spatial variation of aboveground litter stock in the subtropical forest.Given that the global carbon-cycle models have been aiming to refine from the hundred kilometers to sub-kilometer scale,this study highlights the urgency of a better understanding of the spatial variation of litter stock on the fine scale.

A traceability analysis system for model evaluation on land carbon dynamics: design and applications

Background:An increasing number of ecological processes have been incorporated into Earth system models.However,model evaluations usually lag behind the fast development of models,leading to a pervasive simulation uncertainty in key ecological processes,especially the terrestrial carbon(C)cycle.Traceability analysis provides a theoretical basis for tracking and quantifying the structural uncertainty of simulated C storage in models.Thus,a new tool of model evaluation based on the traceability analysis is urgently needed to efficiently diagnose the sources of inter-model variations on the terrestrial C cycle in Earth system models.Methods:A new cloud-based model evaluation platform,i.e.,the online traceability analysis system for model evaluation(TraceME v1.0),was established.The TraceME was applied to analyze the uncertainties of seven models from the Coupled Model Intercomparison Project(CMIP6).Results:The TraceME can effectively diagnose the key sources of different land C dynamics among CMIIP6 models.For example,the analyses based on TraceME showed that the estimation of global land C storage varied about 2.4 folds across the seven CMIP6 models.Among all models,IPSL-CM6A-LR simulated the lowest land C storage,which mainly resulted from its shortest baseline C residence time.Over the historical period of 1850–2014,gross primary productivity and baseline C residence time were the major uncertainty contributors to the inter-model variation in ecosystem C storage in most land grid cells.Conclusion:TraceME can facilitate model evaluation by identifying sources of model uncertainty and provides a new tool for the next generation of model evaluation.

Disentangling land model uncertainty via Matrix-based Ensemble Model Inter-comparison Platform(MEMIP)

Background:Large uncertainty in modeling land carbon(C)uptake heavily impedes the accurate prediction of the global C budget.Identifying the uncertainty sources among models is crucial for model improvement yet has been difficult due to multiple feedbacks within Earth System Models(ESMs).Here we present a Matrix-based Ensemble Model Inter-comparison Platform(MEMIP)under a unified model traceability framework to evaluate multiple soil organic carbon(SOC)models.Using the MEMIP,we analyzed how the vertically resolved soil biogeochemistry structure influences SOC prediction in two soil organic matter(SOM)models.By comparing the model outputs from the C-only and CN modes,the SOC differences contributed by individual processes and N feedback between vegetation and soil were explicitly disentangled.Results:Results showed that the multi-layer models with a vertically resolved structure predicted significantly higher SOC than the single layer models over the historical simulation(1900–2000).The SOC difference between the multi-layer models was remarkably higher than between the single-layer models.Traceability analysis indicated that over 80%of the SOC increase in the multi-layer models was contributed by the incorporation of depth-related processes,while SOC differences were similarly contributed by the processes and N feedback between models with the same soil depth representation.Conclusions:The output suggested that feedback is a non-negligible contributor to the inter-model difference of SOC prediction,especially between models with similar process representation.Further analysis with TRENDY v7 and more extensive MEMIP outputs illustrated the potential important role of multi-layer structure to enlarge the current ensemble spread and the necessity of more detail model decomposition to fully disentangle inter-model differences.We stressed the importance of analyzing ensemble outputs from the fundamental model structures,and holding a holistic view in understanding the ensemble uncertainty.

Evapotranspiration partitioning using an optimality-based ecohydrological model in a semiarid shrubland

Partitioning of evapotranspiration(ET)into biological component transpiration(T)and non-biological component evaporation(E)is crucial in understanding the impact of environmental change on ecosystems and water resources.However,direct measurement of transpiration is still challenging.In this paper,an optimality-based ecohydrological model named Vegetation Optimality Model(VOM)is applied for ET partitioning.The results show that VOM model can reasonably simulate ET and ET components in a semiarid shrubland.Overall,the ratio of transpiration to evapotranspiration is 49%for the whole period.Evaporation and plant transpiration mainly occur in monsoon following the precipitation events.Evaporation responds immediately to precipitation events,while transpiration shows a lagged response of several days to those events.Different years demonstrate different patterns of T/ET ratio dynamic in monsoon.Some of the years show a low T/ET ratio at the beginning of monsoon and slowly increased T/ET ratio.Other years show a high level of T/ET ratio for the whole monsoon.We find out that spring precipitation,especially the size of the precipitation,has a significant influence on the T/ET ratio in monsoon.

Climate warming restructures seasonal dynamics of grassland soil microbial communities

Soil microbial community's responses to climate warming alter the global carbon cycle.In temperate ecosystems,soil microbial communities function along seasonal cycles.However,little is known about how the responses of soil microbial communities to warming vary when the season changes.In this study,we investigated the seasonal dynamics of soil bacterial community under experimental warming in a temperate tall‐grass prairie ecosystem.Our results showed that warming significantly(p=0.001)shifted community structure,such that the differences of microbial communities between warming and control plots increased nonlinearly(R^(2)=0.578,p=0.021)from spring to winter.Also,warming significantly(p<0.050)increased microbial network complexity and robustness,especially during the colder seasons,despite large variations in network size and complexity in different seasons.In addition,the relative importance of stochastic processes in shaping the microbial community decreased by warming in fall and winter but not in spring and summer.Our study indicates that climate warming restructures the seasonal dynamics of soil microbial community in a temperate ecosystem.Such seasonality of microbial responses to warming may enlarge over time and could have significant impacts on the terrestrial carbon cycle.

Country-level land carbon sink and its causing components by the middle of the twenty-first century

Background:Countries have long been making efforts by reducing greenhouse-gas emissions to mitigate climate change.In the agreements of the United Nations Framework Convention on Climate Change,involved countries have committed to reduction targets.However,carbon(C)sink and its involving processes by natural ecosystems remain difficult to quantify.Methods:Using a transient traceability framework,we estimated country-level land C sink and its causing components by 2050 simulated by 12 Earth System Models involved in the Coupled Model Intercomparison Project Phase 5(CMIP5)under RCP8.5.Results:The top 20 countries with highest C sink have the potential to sequester 62 Pg C in total,among which,Russia,Canada,USA,China,and Brazil sequester the most.This C sink consists of four components:productiondriven change,turnover-driven change,change in instantaneous C storage potential,and interaction between production-driven change and turnover-driven change.The four components account for 49.5%,28.1%,14.5%,and 7.9%of the land C sink,respectively.Conclusion:The model-based estimates highlight that land C sink potentially offsets a substantial proportion of greenhouse-gas emissions,especially for countries where net primary production(NPP)likely increases substantially and inherent residence time elongates.

Dynamic carbon-nitrogen coupling under global change

Carbon-nitrogen coupling is a fundamental principle in ecosystem ecology.However,how the coupling responds to global change has not yet been examined.Through a comprehensive and systematic literature review,we assessed how the dynamics of carbon processes change with increasing nitrogen input and how nitrogen processes change with increasing carbon input under global change.Our review shows that nitrogen input to the ecosystem mostly stimulates plant primary productivity but inconsistently decreases microbial activities or increases soil carbon sequestration,with nitrogen leaching and nitrogenous gas emission rapidly increasing.Nitrogen fixation increases and nitrogen leaching decreases to improve soil nitrogen availability and support plant growth and ecosystem carbon sequestration under elevated CO_(2)and temperature or along ecosystem succession.We conclude that soil nitrogen cycle processes continually adjust to change in response to either overload under nitrogen addition or deficiency under CO_(2)enrichment and ecosystem succession to couple with carbon cycling.Indeed,processes of both carbon and nitrogen cycles continually adjust under global change,leading to dynamic coupling in carbon and nitrogen cycles.The dynamic coupling framework reconciles previous debates on the“uncoupling”or“decoupling”of ecosystem carbon and nitrogen cycles under global change.Ecosystem models failing to simulate these dynamic adjustments cannot simulate carbonnitrogen coupling nor predict ecosystem carbon sequestration well.

植物碳、氮、磷在不同火烧强度下的分配策略

森林野火是影响北方针叶林演替过程中养分分配规律的重要因素。然而,植物叶片和细根之间的碳(C)、氮(N)、磷(P)分配策略在不同强度森林野火后的研究尚不充分。本研究旨在探讨不同野火强度下叶片和细根间C、N、P的分配策略。运用化学计量学理论和异速生长方程,选取中国东北大兴安岭地区的4个不同火烧强度(未火烧、低、中、高)恢复10年后的火烧迹地为研究样地,比较不同火烧强度下各物种叶片和细根的C、N、P含量。研究结果表明,与未受到火烧的样地相比,轻度火烧迹地的植物叶片和细根C浓度增加,重度火烧迹地植物叶片N浓度最高,但是细根N浓度最低。N:P比值的平均值大于16的结果表示植物养分利用策略在高火烧强度下趋于P限制。更重要的是,随着火烧严重程度的增加,细根与叶片间的C、N、P分配规律出现由异速生长向等速生长的转变,即随着火烧强度的增加,元素分配表现为对叶片的分配多于细根。这些结果表明,植物叶片和细根之间的元素分配策略在受到不同强度的野火干扰以后发生了失衡。本研究加深了我们对火后森林生态系统演替过程中植物与土壤养分动态的认识。

草地生态系统碳氮库对增温响应的整合分析

陆地生态系统碳氮耦合过程有可能改变全球碳循环对气候变化的敏感性。然而,碳氮的交互作用对陆地生态系统碳固存的贡献仍不明确。本研究采用Meta分析的方法量化了野外增温条件下草地碳氮储量的变化,并且进一步评估了3个主要的碳氮耦合过程(生态系统氮总量的变化,氮在植被和土壤之间的重新分配,植被与土壤碳氮比的变化)对草地碳固存的相对贡献。增温使得土壤、凋落物和植被的碳氮比增加,并导致约2%的氮从土壤转移到植被和凋落物中。增温提高了植被和凋落物的碳储量(111.2 g·m^(−2)),而降低了土壤的碳储量(30.0 g·m^(−2)),由此可见,增温提高了整个草地生态系统的碳储量。碳氮比的变化是温度升高条件下草地碳储量增加的主要贡献者,氮的重新分配次之。相反,氮总量的减少则降低了生态系统的碳储量。这些结果表明,温度升高对草地生态系统碳氮储量的变化及其耦合过程具有显著的影响,建议生态模型考虑碳氮循环的交互作用,以便更准确地预测未来陆地碳储量的变化。

增温对高寒草甸生态系统碳氮循环耦合关系的影响

陆地生态系统碳吸收受土壤氮素可用性的调节。然而,全球变化背景下的不同生态系统组分的碳氮比及其所反映的碳氮循环耦合关系尚不十分清楚。本文运用数据同化的方法,将一个高寒草甸增温试验的14组数据同化到草地生态系统模型中,从而评估了增温如何影响陆地生态系统的碳氮循环耦合关系。研究结果表明,增温提高了土壤氮素的有效性,降低了土壤活性碳库的碳氮比,导致植物对土壤氮的吸收增加。但是由于植物叶片吸收的碳比吸收的氮增加更多,使得叶片中碳氮比增加,而根部的碳输入增加则低于氮的增加,导致根部的碳氮比减少。同时,增温降低了凋落物碳氮比,可能是在土壤高氮有效性的条件下,凋落物氮的固定得到增强;而且增温加速了凋落物的分解。同时增温还增加了慢速土壤有机质的碳氮比,使得该土壤碳库的碳固存潜力增大。由于大多数模型在不同的环境中通常使用相对固定的碳氮比,本研究所发现的气候变暖条件下碳氮比的差异变化可为模型参数化提供一个有效的参考,有利于模型对未来气候变化背景下生态系统碳氮耦合关系响应的预测。