太阳辐射变化对亚热带人工常绿针叶林总初级生产力影响的模拟分析

太阳辐射是陆地生态系统碳水循环的能量来源。太阳辐射的变化对植被吸收大气CO₂具有重要影响。该文通过辐射观测数据建立散射辐射比例与晴空指数的关系, 结合生态过程模型(BEPS)和通量观测数据, 模拟分析了太阳辐射变化对千烟洲常绿针叶林总初级生产力(GPP)的影响。研究结果表明: 千烟洲森林生态系统的阴叶对年GPP总量的贡献达67%, 太阳辐射变化对阴叶光合作用的影响决定了冠层GPP的变化; 太阳辐射强度和分布的年际差异导致年GPP对太阳辐射变化的响应不同, 2003、2004和2005年太阳辐射分别变化-5.44%、-1.83%和6.26%, 可使千烟洲生态系统当年GPP总量达到最大值; 在季节上, 太阳辐射的增加会导致5-6月GPP上升, 7-9月GPP下降, 使年GPP变化程度降低; 在天尺度上, 晴空指数在0.43时, 太阳辐射变化对GPP的影响最小。     

散射辐射对中国东部典型人工林总初级生产力的影响

散射辐射是影响森林碳吸收的重要因子。然而,有关生态系统总初级生产力(GPP)对散射辐射响应机理的理解仍有限。该研究利用中国东部6个人工林生态系统2019–2020年观测的碳通量数据和气象数据,估算了散射辐射,区分了直接辐射和散射辐射条件;基于直角双曲线方程获取了不同辐射条件下生态系统光响应参数;量化了GPP对散射辐射和直接辐射变化的响应;采用偏相关方法分析了光照和环境因子对GPP日变化的贡献,旨在探究生长季散射辐射对人工林生态系统GPP的影响机理。研究表明:散射辐射增加可以有效促进冠层光合作用,初始量子效率(α)和光合有效辐射(PAR)为1 000μmol·m^–2·s^–1时的GPP (P₁₀₀₀)分别提高了47%–150%和2%–65%。与直接辐射条件相比,散射辐射条件下的PAR每增加1μmol·m^–2·s^–1,GPP增加0.86%–1.70%,森林植被类型和站点物候变化会影响这一过程,具有较低归一化植被指数(NDVI)的樟子松(Pinus sylvestris var. mo...     

Incident radiation and the allocation of nitrogen within Arctic plant canopies: implications for predicting gross primary productivity

Arctic vegetation is characterized by high spatial variability in plant functional type (PFT) composition and gross primary productivity (P). Despite this variability, the two main drivers of P in sub‐Arctic tundra are leaf area index (L_T) and total foliar nitrogen (N_T). L_T and N_T have been shown to be tightly coupled across PFTs in sub‐Arctic tundra vegetation, which simplifies up‐scaling by allowing quantification of the main drivers of P from remotely sensed L_T. Our objective was to test the L_T–N_T relationship across multiple Arctic latitudes and to assess L_T as a predictor of P for the pan‐Arctic. Including PFT‐specific parameters in models of L_T–N_T coupling provided only incremental improvements in model fit, but significant improvements were gained from including site‐specific parameters. The degree of curvature in the L_T–N_T relationship, controlled by a fitted canopy nitrogen extinction co‐efficient, was negatively related to average levels of diffuse radiation at a site. This is consistent with theoretical predictions of more uniform vertical canopy N distributions under diffuse light conditions. Higher latitude sites had higher average leaf N content by mass (N_M), and we show for the first time that L_T–N_T coupling is achieved across latitudes via canopy‐scale trade‐offs between N_M and leaf mass per unit leaf area (L_M). Site‐specific parameters provided small but significant improvements in models of P based on L_T and moss cover. Our results suggest that differences in L_T–N_T coupling between sites could be used to improve pan‐Arctic models of P and we provide unique evidence that prevailing radiation conditions can significantly affect N allocation over regional scales.     

Metabolic compensation constrains the temperature dependence of gross primary production

Gross primary production (GPP) is the largest flux in the carbon cycle, yet its response to global warming is highly uncertain. The temperature dependence of GPP is directly linked to photosynthetic physiology, but the response of GPP to warming over longer timescales could also be shaped by ecological and evolutionary processes that drive variation in community structure and functional trait distributions. Here, we show that selection on photosynthetic traits within and across taxa dampens the effects of temperature on GPP across a catchment of geothermally heated streams. Autotrophs from cold streams had higher photosynthetic rates and after accounting for differences in biomass among sites, biomass‐specific GPP was independent of temperature in spite of a 20 °C thermal gradient. Our results suggest that temperature compensation of photosynthetic rates constrains the long‐term temperature dependence of GPP, and highlights the importance of considering physiological, ecological and evolutionary mechanisms when predicting how ecosystem‐level processes respond to warming.     

A cross-biome comparison of daily light use efficiency for gross primary production

Vegetation light use efficiency is a key physiological parameter at the canopy scale, and at the daily time step is a component of remote sensing algorithms for scaling gross primary production (GPP) and net primary production (NPP) over regional to global domains. For the purposes of calibrating and validating the light use efficiency ( ε _g) algorithms, the components of ε _g– absorbed photosynthetically active radiation (APAR) and ecosystem GPP – must be measured in a variety of environments. Micrometeorological and mass flux measurements at eddy covariance flux towers can be used to estimate APAR and GPP, and the emerging network of flux tower sites offers the opportunity to investigate spatial and temporal patterns in ε _g at the daily time step. In this study, we examined the relationship of daily GPP to APAR, and relationships of ε _g to climatic variables, at four micrometeorological flux tower sites – an agricultural field, a tallgrass prairie, a deciduous forest, and a boreal forest. The relationship of GPP to APAR was close to linear at the tallgrass prairie site but more nearly hyperbolic at the other sites. The sites differed in the mean and range of daily ε _g, with higher values associated with the agricultural field than the boreal forest. ε_g decreased with increasing APAR at all sites, a function of mid‐day saturation of GPP and higher ε _g under overcast conditions. ε _g was generally not well correlated with vapor pressure deficit or maximum daily temperature. At the agricultural site, a ε _g decline towards the end of the growing season was associated with a decrease in foliar nitrogen concentration. At the tallgrass prairie site, a decline in ε _g in August was associated with soil drought. These results support inclusion of parameters for cloudiness and the phenological status of the vegetation, as well as use of biome‐specific parameterization, in operational ε _g algorithms.     

Site-level evaluation of satellite-based global terrestrial gross primary production and net primary production monitoring

Operational monitoring of global terrestrial gross primary production (GPP) and net primary production (NPP) is now underway using imagery from the satellite‐borne Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Evaluation of MODIS GPP and NPP products will require site‐level studies across a range of biomes, with close attention to numerous scaling issues that must be addressed to link ground measurements to the satellite‐based carbon flux estimates. Here, we report results of a study aimed at evaluating MODIS NPP/GPP products at six sites varying widely in climate, land use, and vegetation physiognomy. Comparisons were made for twenty‐five 1 km² cells at each site, with 8‐day averages for GPP and an annual value for NPP. The validation data layers were made with a combination of ground measurements, relatively high resolution satellite data (Landsat Enhanced Thematic Mapper Plus at ～30 m resolution), and process‐based modeling. There was strong seasonality in the MODIS GPP at all sites, and mean NPP ranged from 80 g C m^?2 yr^?1 at an arctic tundra site to 550 g C m^?2 yr^?1 at a temperate deciduous forest site. There was not a consistent over‐ or underprediction of NPP across sites relative to the validation estimates. The closest agreements in NPP and GPP were at the temperate deciduous forest, arctic tundra, and boreal forest sites. There was moderate underestimation in the MODIS products at the agricultural field site, and strong overestimation at the desert grassland and at the dry coniferous forest sites. Analyses of specific inputs to the MODIS NPP/GPP algorithm – notably the fraction of photosynthetically active radiation absorbed by the vegetation canopy, the maximum light use efficiency (LUE), and the climate data – revealed the causes of the over‐ and underestimates. Suggestions for algorithm improvement include selectively altering values for maximum LUE (based on observations at eddy covariance flux towers) and parameters regulating autotrophic respiration.     

Remote sensing estimation of gross primary productivity and its response to climate change in the upstream of Heihe River Basin

AimsQuantifying the gross primary productivity (GPP) of vegetation is of primary interest in studies of global carbon cycle. This study aims to optimize the MODIS GPP model for specific environments of a fragile waterhead ecosystem, by performing simulations of long-term (from 2001 to 2012) GPP with optimized MOD_17 model, and to analyze the response of GPP to the local climatic variations.Methods The original MODIS GPP products that underestimate GPP were validated against two years (2010-2011) of eddy covariance (EC) data at two sites (i.e. an alpine pasture site and a forest site, respectively) in the upstream of Heihe River Basin. Three comparative experiments were then conducted to analyze the effects of input parameters derived from three sources (i.e. meteorological, biome-specific, and fraction of absorbed photosynthetically active radiation (fPAR) parameters) on the model behavior. After refining the model-driven parameters, long-term GPPs of the study area were estimated using the optimized MOD_17 model, and the Least Absolute Deviation method was applied to analyze the partial correlations between interannual GPPs and climatic variables (temperature, precipitation and vapor pressure deficit (VPD)). Important findings The uncertainties in the original MODIS GPP products are attributable to biome-specific parameters, input data (e.g. meteorological and radiometry data) and vegetation maps. At the pasture site, the light use efficiency had the strongest impact on the GPP simulations. The refined fPAR calculated from the leaf area index (LAI) products of Global Land Surface Satellite (GLASS) greatly improved the GPP estimates, especially at the forest site. The GPPs from the optimized MOD_17 model well matched the EC data (R² = 0.90, root mean squared error (RMSE) = 1.114 g C·m^-2·d^-1 at the alpine pasture site; R² = 0.91, RMSE = 0.649 g C·m^-2·d^-1 at the forest site). The time series of GPPs displayed an up trend at an average rate of 9.58 g C·m^-2·a^-1 from 2001 to 2012. Examination of the partial correlations between interannual GPPs and climatic variables showed that the annual mean temperature and VPD generally had significant positive impacts on GPP, and the annual precipitation had a negative impact on GPP.     

Ecophysiological adaptability of four tree species in the southern subtropical evergreen broad-leaved forest to warming

Aims The subject of this study was to investigate warming effects on leaf stomatal traits, anatomical structure and photosynthetic traits of four common tree species in subtropical evergreen broad-leaved forest of southern China, and to compare their physiological adaptability to warming. Our study aims to provide a theoretical basis for better predicting the tree growth of native forests in a warming climate.Methods One-year-old seedlings of Syzygium rehderianum, Ormosia pinnata, Castanopsis hystrix and Schima superba were selected and exposed to two levels of temperature (ambient temperature and infrared heater warming). Leaf stomatal traits, anatomical structure and photosynthetic characteristics were measured to represent the abilities of stomatal regulation, leaf tissue regulation and nutrient maintenance, respectively.Important findings For Syzygium rehderianum, warming decreased its leaf sponge tissue thickness, photosynthetic nitrogen-use efficiency (PNUE) and photosynthetic phosphorous-use efficiency (PPUE). Seedling of O. pinnata exposed to warming showed increased stomatal conductance, photosynthetic rate, PNUE and PPUE, but decreased stomatal density, leaf thickness and palisade tissue thickness. For C. hystrix, warming decreased the stomata size, but did not affect its photosynthetic rate. Seedling of Schima superba exposed to warming showed lower stomata density, leaf palisade tissue thickness, photosynthetic rate, PNUE and PPUE, but higher stomata size. These results suggested that O. pinnata, Syzygium rehderianum and Schima superba could reduce their leaf thickness to acclimate to warming conditions. The abilities of stomatal regulation, nutrient maintenance, photosynthetic rate and PNUE varied among these tree species. Warming would be beneficial for the growth of O. pinnata due to increased photosynthetic rate, PNUE and PPUE, while not for Syzygium rehderianum and Schima superba, the two dominant tree species of native forests. This study indicated that, with projected climate change, O. pinnata may replace Syzygium rehderianum and Schima superba as a new dominant tree species in the subtropical evergreen broad-leaved forest for its stronger adaptability to warming.     

Temporal changes of vegetation water use efficiency and its influencing factors in Northern China

水分利用效率(WUE)既是衡量植被生长适应性的重要指标, 也是连接生态系统水碳循环的纽带。认识不同类型植被WUE的时间变化特征及驱动机制有助于增进对生态系统水碳循环过程的理解。已有研究表明, 在不同时间尺度下, WUE呈现不同的时间变化特征, 但现有研究多是集中在单一的时间尺度下开展的, 对不同植被类型在不同时间尺度下的动态变化及影响因子分析开展得较少。该研究选用中国北方地区9个定位观测台站的通量与气象数据, 分析了WUE的日内变化和季节变化特征, 并在0.5 h、1 d、8 d以及月尺度下, 分别分析了气温(T_a)、相对湿度(RH)、饱和水汽压差(VPD)以及光合有效辐射(PAR)等非生物因子对WUE的影响。同时, 该研究也分析了植被叶面积指数(LAI)和降水(P)对WUE的影响。研究发现: (1) WUE的日变化呈现不对称的“U”型特征, 日出时的WUE普遍高于日落时。荒漠地区WUE的季节变化呈“U”型, 而其他站点呈现单峰型。不同站点WUE的季节变化可以分为总初级生产力(GPP)主导型和蒸发散(ET)主导型, 并随着时间尺度的扩大, GPP或ET的主导作用逐渐增强。(2)在较短的时间尺度(0.5 h、1 d)上, T_a、RH、VPD和PAR是影响WUE变化的主要因子, 但随着时间尺度的扩大, T_a和RH成为影响WUE变化的主要因子, 并且与WUE的相关关系受GPP或ET对WUE主导作用的影响, 随着时间尺度增大, T_a和RH与WUE的线性关系更加显著。(3) WUE大体上随LAI的增加而增加, 但当LAI超过一定值时, 在长白山、海北和张掖站, WUE对LAI的敏感性降低。降水与WUE的关系在研究区域内并不显著。(4)不同植被类型的WUE由大到小依次为森林、农田、草地、湿地和荒漠。     

气候变化下中国不同植被区总初级生产力对干旱的响应

干旱变化具有明显的空间分异,不同植被类型对干旱的响应亦有差别。开展气候变化下不同植被覆盖类型对干旱响应的差异分析,厘清温升干旱化进程对植被的影响,对了解植被发展动态及预测未来格局有着非常重要的意义。基于1982—2017年的总初级生产力(GPP)数据和同时期东安格利亚大学气候研究中心(CRU)时间序列(TS)气候数据,分析了中国8个植被区GPP和干旱的变化趋势,通过对比标准化降水指数(SPI)和标准化降水蒸散指数(SPEI)的趋势差异识别了典型的温升干旱化区域,在此基础上研究气温上升如何影响GPP对干旱的响应,进一步讨论了不同植被类型对干旱的敏感性差异。结果表明：(1) 36年来8个植被区除青藏高原高寒植被区呈湿润化,其他植被区均呈现变干趋势;(2)气温上升大面积加剧了温带荒漠区和温带草原区的变干趋势;(3)亚热带常绿阔叶林区和热带季风雨林、雨林区的GPP受温度和干旱影响相当,青藏高原高寒植被区和针叶、落叶林混交林区的GPP受温度主导,其他植被区GPP均受干旱主导。     

Effects of global change on key processes of primary production in marine ecosystems

工业革命以来, 不断加剧的人类活动所引起的大气CO₂浓度增加、温度上升等全球变化问题, 正使得海洋生态系统面临着前所未有的压力。该文通过文献计量的方法分析了国内外的研究现状, 简要地回顾了全球变化对海洋生态系统影响研究的发展简史, 并聚焦海洋暖化、海洋酸化和富营养化与缺氧这三个核心研究方向, 重点阐述了它们对海洋生态系统初级生产的关键过程的影响, 总结了已取得的重要进展以及存在的主要问题, 最后提出前沿展望。     

Forest carbon use efficiency: is respiration a constant fraction of gross primary production?

Carbon‐use efficiency (CUE), the ratio of net primary production (NPP) to gross primary production (GPP), describes the capacity of forests to transfer carbon (C) from the atmosphere to terrestrial biomass. It is widely assumed in many landscape‐scale carbon‐cycling models that CUE for forests is a constant value of ∼0.5. To achieve a constant CUE, tree respiration must be a constant fraction of canopy photosynthesis. We conducted a literature survey to test the hypothesis that CUE is constant and universal among forest ecosystems. Of the 60 data points obtained from 26 papers published since 1975, more than half reported values of GPP that were not estimated independently from NPP; values of CUE calculated from independent estimates of GPP were greater than those calculated from estimates of GPP derived from NPP. The slope of the relationship between NPP and GPP for all forests was 0.53, but values of CUE varied from 0.23 to 0.83 for different forest types. CUE decreased with increasing age, and a substantial portion of the variation among forest types was caused by differences in stand age. When corrected for age the mean value of CUE was greatest for temperate deciduous forests and lowest for boreal forests. CUE also increased as the ratio of leaf mass‐to‐total mass increased. Contrary to the assumption of constancy, substantial variation in CUE has been reported in the literature. It may be inappropriate to assume that respiration is a constant fraction of GPP as adhering to this assumption may contribute to incorrect estimates of C cycles. A 20% error in current estimates of CUE used in landscape models (i.e. ranging from 0.4 to 0.6) could misrepresent an amount of C equal to total anthropogenic emissions of CO₂ when scaled to the terrestrial biosphere.     

Simulation on the light-response curves of electron transport rate of Quercus variabilis and Robinia pseudoacacia leaves in the Xiaolangdi area,China

为了比较直角双曲线模型、非直角双曲线模型与叶子飘模型的优缺点, 研究阴生叶和阳生叶电子传递速率的差异, 探讨环境/生物因素对电子传递速率等参数的影响, 该文采用LI-6400XT荧光测定系统对黄河小浪底栓皮栎(Quercus variabilis)、刺槐(Robinia pseudoacacia)叶片电子传递速率-光响应(J-I)曲线进行了测定, 利用直角双曲线模型、非直角双曲线模型和叶子飘模型对J-I曲线进行了拟合。结果表明, 3种模型对叶片J-I曲线拟合的决定系数(R ²)在0.96以上, 叶子飘模型的R ²最高(> 0.99)。直角双曲线模型和非直角双曲线模型无法模拟植物叶片光系统II动力学下调现象, 且不能得出饱和光强(I_sat); 直角双曲线模型对最大电子传递速率(J_max)的模拟明显大于实测值; 叶子飘模型能很好地模拟光系统II动力学下调现象, 得出的J_max和I_sat均最接近实测值。对阴生叶和阳生叶J-I曲线研究发现, 栓皮栎、刺槐阴生叶的J_max分别低于阳生叶25.0%和18.0%, 阳生叶的I_sat分别高于阴生叶26.0%和10.1%。栓皮栎和刺槐J_max与气温显著正相关; 刺槐I_sat与气温、土壤水分含量和净光合速率具有显著的正相关关系; 栓皮栎和刺槐J-I曲线初始斜率α均与净光合速率呈显著负相关关系。     

A simulation of the importance of length of growing season and canopy functional properties on the seasonal gross primary production of temperate alpine meadows

Background and Aims: Along snowmelt gradients, the canopies of temperate alpine meadowsdiffer strongly in their structural and biochemical properties.Here, a study is made of the effects of these canopy dissimilaritiescombined with the snow-induced changes in length of growingseason on seasonal gross primary production (GPP). Methods: Leaf area index (LAI) and community-aggregated values of leafangle and leaf nitrogen content were estimated for seven alpineplant canopies distributed along a marked snowmelt gradient,and these were used as input variables in a sun–shadecanopy bulk-photosynthesis model. The model was validated forplant communities of early and late snowmelt sites by measuringthe instantaneous CO₂ fluxes with a canopy closed-chamber technique.A sensitivity analysis was conducted to estimate the relativeimpact of canopy properties and environmental factors on thedaily and seasonal GPP. Key Results: Carbon uptake was primarily related to the LAI and total canopynitrogen content, but not to the leaf angle. For a given levelof photosynthetically active radiation, CO₂ assimilation washigher under overcast conditions. Sensitivity analysis revealedthat increase of the length of the growing season had a highereffect on the seasonal GPP than a similar increase of any otherfactor. It was also found that the observed greater nitrogencontent and larger LAI of canopies in late-snowmelt sites largelycompensated for the negative impact of the reduced growing season. Conclusions: The results emphasize the primary importance of snow-inducedchanges in length of growing season on carbon uptake in alpinetemperate meadows. It was also demonstrated how using leaf-traitvalues of the dominants is a useful approach for modelling ecosystemcarbon-cycle-related processes, particularly when continuousmeasurements of CO₂ fluxes are technically difficult. The studythus represents an important step in addressing the challengeof using a plant functional-trait approach for biogeochemicalmodelling.     

Calibration of Terra/MODIS gross primary production over an irrigated cropland on the North China Plain and an alpine meadow on the Tibetan Plateau

This paper evaluated the MODerate resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) product (MOD17) by using estimated GPP from eddy‐covariance flux measurements over an irrigated winter wheat and maize double‐cropping field on the North China Plain in 2003–2004, and an alpine meadow on the Tibetan Plateau in 2002–2003. The mean annual GPP from MOD17 accounted for 1/2–2/3 of the surface estimated mean annual GPP for the alpine meadow, but only about 1/5–1/3 for the cropland. This underestimation was partly attributed to low estimates of leaf area index by a MODIS product (MOD15) because it is used to calculate absorbed photosynthetically active radiation in the MOD17 algorithm. The main reason is that the parameter maximum light use efficiency (ε_max) in the MOD17 algorithm was underestimated for the two biomes, especially for the cropland. Contrasted to the default, ε_max was optimized using surface measurements. The optimized ε_max for winter wheat, maize and meadow was 1.18, 1.81 and 0.73 g C/MJ, respectively. By using the surface measurements and optimized ε_max , the MOD17 algorithm significantly improved the accuracy of GPP estimates. The optimum MOD17 algorithm explained about 82%, 68%, and 79% of GPP variance for winter wheat, maize, and meadow, respectively. These results suggest that it is necessary to adjust the MOD17 parameters for the estimation of cropland and meadow GPP, particularly over cropland.     

不同数据集的1982—2017年中国总初级生产力的时空动态

了解陆地生态系统总初级生产力(GPP)时空变化及其与气候因子的关系,可以为植被恢复及保护提供重要依据。基于气象数据和3套公开的GPP数据集(EC-LUE GPP、GLASS GPP和NIRv GPP),本研究系统分析了中国1982—2017年GPP的时空变化特征及其对气候变化的响应。结果表明: 3套GPP数据均表明,1982—2017年,中国年和季节的GPP呈逐年上升趋势,1998和2002年明显高于研究期间的平均水平,1989和1992年明显低于多年平均GPP。1982—2017年,中国大部分地区GPP呈显著上升趋势,3套GPP数据显著增加的区域分别占整个研究区的75.7%、73.0%和69.6%。年GPP与降水和温度均存在显著正相关关系,但空间异质性较强。其中GPP与温度呈正相关的区域主要分布在西北和华中地区,GPP与降水呈正相关的区域主要分布在华北地区。不同季节的GPP受气温、降水影响的区域存在明显的时空异质性。温度是春、秋和冬季GPP的限制因子,而夏季GPP主要受降水影响。     

1980—2013年中国陆地生态系统总初级生产力对干旱的响应特征

干旱事件通过影响陆地生态系统的组成、结构和功能显著改变整个陆地生态系统碳循环。陆地生态系统总初级生产力(GPP)是全球陆地碳通量中最大的组成部分,反映了陆地生态系统的生产力水平。本研究利用基于过程模型模拟的GPP数据(DLM GPP)、基于通量观测升尺度的GPP数据(FLUXCOM GPP)和标准化降水蒸散指数(SPEI),量化分析了1980—2013年中国陆地生态系统GPP和干旱的时空格局,讨论了不同时间尺度上GPP对干旱的响应特征。结果表明:1980—2013年,两种不同GPP数据在中国地区呈现的时间变化趋势的空间分布格局较为一致,上升趋势主要分布在西南地区,下降趋势主要分布在东北大部分地区;中国干旱面积的长期时间变化趋势略有下降,其中干旱化趋势主要位于秦岭淮河以南地区,而西北内陆地区则呈现明显的湿润化趋势;时间尺度上,GPP与SPEI年际变化格局基本吻合,1986、1997、2001和2011年等干旱年份的GPP显著降低;空间尺度上,北方大部分地区的GPP与SPEI呈正相关,南方大部分地区呈负相关,干旱对GPP的影响在半干旱地区表现更加明显; GPP对干旱的响应格局与选取干旱指数...     

Environmental controls on the light use efficiency of terrestrial gross primary production

Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf-level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy-level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C₃ species; however, additional assumptions are required to “scale up” from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed-effects model. The same model design was fitted to site-based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple “goodness of fit” comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies.     

常绿阔叶林林冠环境对栲幼苗建成的影响

植物幼苗建成阶段是决定种群自然更新的关键生活史阶段。研究林冠环境对常绿阔叶林优势种幼苗建成阶段的影响对该类森林的恢复和管理具有重要意义。2014-2016年, 该研究在重庆市缙云山国家级自然保护区的常绿阔叶林的不同林冠环境(大林窗: >150 m ², 中林窗: 100-150 m ², 小林窗: 50-100 m ², 对照: 林下)下进行栲(Castanopsis fargesii)种子野外播种实验, 并对栲幼苗命运和生长情况进行了3年的持续监测。结果表明: (1)栲幼苗出土时间从7月持续到12月, 出苗时间较长, 大林窗对幼苗出土具有延迟作用; (2)栲种子野外平均萌发率为(62.8 ± 2.0)%, 第3个生长季(2016年)末幼苗平均存活率为(65.1 ± 2.2)%, 枯萎是栲幼苗死亡的主要原因; (3)林冠环境对栲种子萌发率及第1个生长季(2014年)末的幼苗存活率无显著影响, 对第2个(2015年)和第3个生长季末的幼苗存活率具有显著影响; (4)林冠环境在第1个生长季对幼苗生长无明显影响, 但在第2个和第3个生长季具有显著影响, 大、中林窗中幼苗总生物量、株高、基径、根长和叶片数显著高于林下, 比叶面积显著低于林下; (5) 3个生长季内, 4类林冠条件下栲幼苗的叶质量比和茎质量比升高, 根质量比和根冠比降低, 并且从第2个生长季开始大林窗中栲幼苗的叶质量比显著高于林下, 根质量比和根冠比显著低于林下。栲幼苗早期的存活和生长依赖种子储存的能量, 受林冠条件影响较弱, 后期则依赖光合作用, 受林冠条件影响较强, 从整个幼苗建成过程看, 大、中林窗更有利于栲幼苗定居。     

Climate‐driven uncertainties in modeling terrestrial gross primary production: a site level to global‐scale analysis

We used a land surface model to quantify the causes and extents of biases in terrestrial gross primary production (GPP) due to the use of meteorological reanalysis datasets. We first calibrated the model using meteorology and eddy covariance data from 25 flux tower sites ranging from the tropics to the northern high latitudes and subsequently repeated the site simulations using two reanalysis datasets: NCEP/NCAR and CRUNCEP. The results show that at most sites, the reanalysis‐driven GPP bias was significantly positive with respect to the observed meteorology‐driven simulations. Notably, the absolute GPP bias was highest at the tropical evergreen tree sites, averaging up to ca. 0.45 kg C m^?2 yr^?1 across sites (ca. 15% of site level GPP). At the northern mid‐/high‐latitude broadleaf deciduous and the needleleaf evergreen tree sites, the corresponding annual GPP biases were up to 20%. For the nontree sites, average annual biases of up to ca. 20–30% were simulated within savanna, grassland, and shrubland vegetation types. At the tree sites, the biases in short‐wave radiation and humidity strongly influenced the GPP biases, while the nontree sites were more affected by biases in factors controlling water stress (precipitation, humidity, and air temperature). In this study, we also discuss the influence of seasonal patterns of meteorological biases on GPP. Finally, using model simulations for the global land surface, we discuss the potential impacts of site‐level reanalysis‐driven biases on the global estimates of GPP. In a broader context, our results can have important consequences on other terrestrial ecosystem fluxes (e.g., net primary production, net ecosystem production, energy/water fluxes) and reservoirs (e.g., soil carbon stocks). In a complementary study (Barman et al., 2013 ), we extend the present analysis for latent and sensible heat fluxes, thus consistently integrating the analysis of climate‐driven uncertainties in carbon, energy, and water fluxes using a single modeling framework.