Measured and modeled interactive effects of potassium deficiency and water deficit on gross primary productivity and light‐use efficiency in Eucalyptus grandis plantations

Global climate change is expected to increase the length of drought periods in many tropical regions. Although large amounts of potassium (K) are applied in tropical crops and planted forests, little is known about the interaction between K nutrition and water deficit on the physiological mechanisms governing plant growth. A process‐based model (MAESPA) parameterized in a split‐plot experiment in Brazil was used to gain insight into the combined effects of K deficiency and water deficit on absorbed radiation (aPAR), gross primary productivity (GPP), and light‐use efficiency for carbon assimilation and stem biomass production (LUE_C and LUE_s) in Eucalyptus grandis plantations. The main‐plot factor was the water supply (undisturbed rainfall vs. 37% of throughfall excluded) and the subplot factor was the K supply (with or without 0.45 mol K m^?2 K addition). Mean GPP was 28% lower without K addition over the first 3 years after planting whether throughfall was partly excluded or not. K deficiency reduced aPAR by 20% and LUE_C by 10% over the whole period of growth. With K addition, throughfall exclusion decreased GPP by 25%, resulting from a 21% decrease in LUE_C at the end of the study period. The effect of the combination of K deficiency and water deficit was less severe than the sum of the effects of K deficiency and water deficit individually, leading to a reduction in stem biomass production, gross primary productivity and LUE similar to K deficiency on its own. The modeling approach showed that K nutrition and water deficit influenced absorbed radiation essentially through changes in leaf area index and tree height. The changes in gross primary productivity and light‐use efficiency were, however, driven by a more complex set of tree parameters, especially those controlling water uptake by roots and leaf photosynthetic capacities.     

Impacts of tropospheric ozone and climate change on net primary productivity and net carbon exchange of China's forest ecosystems

Aim We investigated how ozone pollution and climate change/variability have interactively affected net primary productivity (NPP) and net carbon exchange (NCE) across China's forest ecosystem in the past half century. Location Continental China. Methods Using the dynamic land ecosystem model (DLEM) in conjunction with 10‐km‐resolution gridded historical data sets (tropospheric O₃ concentrations, climate variability/change, and other environmental factors such as land‐cover/land‐use change (LCLUC), increasing CO₂ and nitrogen deposition), we conducted nine simulation experiments to: (1) investigate the temporo‐spatial patterns of NPP and NCE in China's forest ecosystems from 1961–2005; and (2) quantify the effects of tropospheric O₃ pollution alone or in combination with climate variability and other environmental stresses on forests' NPP and NCE. Results China's forests acted as a carbon sink during 1961–2005 as a result of the combined effects of O₃, climate, CO₂, nitrogen deposition and LCLUC. However, simulated results indicated that elevated O₃ caused a 7.7% decrease in national carbon storage, with O₃‐induced reductions in NCE (Pg C year^?1) ranging from 0.4–43.1% among different forest types. Sensitivity experiments showed that climate change was the dominant factor in controlling changes in temporo‐spatial patterns of annual NPP. The combined negative effects of O₃ pollution and climate change on NPP and NCE could be largely offset by the positive fertilization effects of nitrogen deposition and CO₂. Main conclusions In the future, tropospheric O₃ should be taken into account in order to fully understand the variations of carbon sequestration capacity of forests and assess the vulnerability of forest ecosystems to climate change and air pollution. Reducing air pollution in China is likely to increase the resilience of forests to climate change. This paper offers the first estimate of how prevention of air pollution can help to increase forest productivity and carbon sequestration in China's forested ecosystems.     

利用CASA模型模拟西南喀斯特植被净第一性生产力

基于SPOT NDVI遥感数据并结合数字高程模型、气象数据和植被参数,利用实测植被生产力计算和修正最大光能利用率,通过改进CASA过程模型,本文估算了中国西南喀斯特地区1999—2003年的植被净第一性生产力（NPP）。结果表明：1）改进后的CASA模型模拟的植被NPP与实测值相关性显著,可较好用于西南喀斯特植被的NPP估算;2）西南8省市区1999—2000年喀斯特和非喀斯特植被的NPP有轻度增加,但空间变化不显著,2001年低值区范围增加,2002年NPP高值区的范围明显扩大,随后在2003年又降低,但仍高于2001年;3）5年间西南喀斯特地区年NPP的变化范围是381.7—439.9 gC m-2 yr-1,平均值为402.34 gC m-2 yr-1,逐年NPP波动中呈现总体增长趋势,平均增加值为9.93 gC m-2 yr-1,5年总增加量为11TgC,但非喀斯特地区的年NPP平均值和增加值都大于喀斯特地区;4）5年间喀斯特地区的热带森林、亚热带森林、灌丛和草地的逐年NPP均小于非喀斯特地区,温带森林和农业植被则相反;这6种典型植被年NPP均呈增加趋势,热带森林的增加值最大,草地最小,非喀斯特地区植被NPP的增长趋势相似,但每种植被的年NPP增加值均大于喀斯特地区。西南喀斯特地区植被NPP的时空变化与气温、降水和太阳辐射的变化有关,而喀斯特植被NPP低于非喀斯特地区,则主要由喀斯特地区水分匮缺、土壤贫瘠等恶劣条件而抑制植物生长造成的。     

Interactions between CO2 enhancement and N addition on net primary productivity and water‐use efficiency in a mesocosm with multiple subtropical tree species

Carbon dioxide (CO₂) enhancement (eCO₂) and N addition (aN) have been shown to increase net primary production (NPP) and to affect water‐use efficiency (WUE) for many temperate ecosystems, but few studies have been made on subtropical tree species. This study compared the responses of NPP and WUE from a mesocosm composing five subtropical tree species to eCO₂ (700 ppm), aN (10 g N m^?2 yr^?1) and eCO₂ × aN using open‐top chambers. Our results showed that mean annual ecosystem NPP did not changed significantly under eCO₂, increased by 56% under aN and 64% under eCO₂ × aN. Ecosystem WUE increased by 14%, 55%, and 61% under eCO₂, aN and eCO₂ × aN, respectively. We found that the observed responses of ecosystem WUE were largely driven by the responses of ecosystem NPP. Statistical analysis showed that there was no significant interactions between eCO₂ and aN on ecosystem NPP (P = 0.731) or WUE (P = 0.442). Our results showed that increasing N deposition was likely to have much stronger effects on ecosystem NPP and WUE than increasing CO₂ concentration for the subtropical forests. However, different tree species responded quite differently. aN significantly increased annual NPP of the fast‐growing species (Schima superba). Nitrogen‐fixing species (Ormosia pinnata) grew significantly faster only under eCO₂ × aN. eCO₂ had no effects on annual NPP of those two species but significantly increased annual NPP of other two species (Castanopsis hystrix and Acmena acuminatissima). Differential responses of the NPP among different tree species to eCO₂ and aN will likely have significant implications on the species composition of subtropical forests under future global change.     

基于耦合模型的干旱区植被净初级生产力估算

净初级生产力是陆地生态系统物质与能量运转研究的基础, 在干旱区生态环境演变及其与气候相互作用和影响方面极为敏感,是揭示干旱区生态环境特征的重要指标.本研究基于RS和GIS技术,利用地面气象数据、涡度相关数据、Landsat 8数据和MODIS数据,通过SEBAL模型和光能利用率模型的耦合,估算了新疆玛纳斯河流域植被净初级生产力(NPP),分析了其空间格局及与高程和坡度的关系.结果表明: SEBAL模型与光能利用率模型的耦合对玛纳斯河流域山地-绿洲-荒漠生态系统植被NPP的模拟效果较合理,能较好地反映植被净初级生产力的实际情况;2013年,玛纳斯河流域植被NPP总量为7066.72 Tg C·a^-1,平均值为278.06 g C·m^-2·a^-1,总体分布趋势是自南向北先增加后减少再增加最后减少,随着地貌和土地利用类型的变化呈现明显的分布规律,且其月变化比较明显,7—8月达到最大值,占总量NPP的52.2%;植被净初级生产力随海拔和坡度的增加整体呈下降趋势,但随海拔增加植被NPP出现3次波动.这些波动主要由地表植被覆盖类型和环境因素所引起.     

Carbon dynamics,net primary productivity and human‐appropriated net primary productivity across a forest–cocoa farm landscape in West Africa

Terrestrial net primary productivity (NPP) is an important metric of ecosystem functioning; however, there are little empirical data on the NPP of human‐modified ecosystems, particularly smallholder, perennial crops like cocoa (Theobroma cacao), which are extensive across the tropics. Human‐appropriated NPP (HANPP) is a measure of the proportion of a natural system's NPP that has either been reduced through land‐use change or harvested directly and, previously, has been calculated to estimate the scale of the human impact on the biosphere. Additionally, human modification can create shifts in NPP allocation and decomposition, with concomitant impacts on the carbon cycle. This study presents the results of 3 years of intensive monitoring of forest and smallholder cocoa farms across disturbance, management intensity, distance from forest and farm age gradients. We measured among the highest reported NPP values in tropical forest, 17.57 ± 2.1 and 17.7 ± 1.6 Mg C ha^?1 year^?1 for intact and logged forest, respectively; however, the average NPP of cocoa farms was still higher, 18.8 ± 2.5 Mg C ha^?1 year^?1, which we found was driven by cocoa pod production. We found a dramatic shift in litterfall residence times, where cocoa leaves decomposed more slowly than forest leaves and shade tree litterfall decomposed considerably faster, indicating significant changes in rates of nutrient cycling. The average HANPP value for all cocoa farms was 2.1 ± 1.1 Mg C ha^?1 year^?1; however, depending on the density of shade trees, it ranged from ?4.6 to 5.2 Mg C ha^?1 year^?1. Therefore, rather than being related to cocoa yield, HANPP was reduced by maintaining higher shade levels. Across our monitored farms, 18.9% of farm NPP was harvested (i.e., whole cocoa pods) and only 1.1% (i.e., cocoa beans) was removed from the system, suggesting that the scale of HANPP in smallholder cocoa agroforestry systems is relatively small.     

安徽省植被净初级生产力估算——基于改进的CASA模型

定量估算植被净初级生产力(NPP)对预测陆地碳循环趋势具有重要意义,目前广泛应用于NPP估算的CASA模型其精度仍有待提高。在已有CASA模型优化的基础上,考虑最大光能利用率(LUE_max)的动态变化来改进CASA模型,对改进前后的模拟结果进行比较,并利用改进后的模型估算2001—2020年安徽省植被NPP。结论如下：(1)改进的CASA模型可应用于研究区的植被NPP估算,NPP模拟值与实测值之间的相关性达到显著水平(R²=0.736,P<0.01)。(2)改进后模拟的安徽省植被NPP在空间表达上能够呈现更多细节,时间上较改进前在生长季NPP值更高,非生长季值更低,拉大了NPP的年内变化。(3)2001—2020年安徽省植被NPP整体呈波动上升趋势,多年平均值为547.61 gC m^-2 a^-1,年均增长量达2.18 gC m^-2 a^-1,2016—2020年间NPP增长最快。年内NPP具有明显的季节差异,表现为夏季>秋季>春季>冬...     

Effects of climate warming on net primary productivity in China during 1961–2010

The response of ecosystems to different magnitudes of climate warming and corresponding precipitation changes during the last few decades may provide an important reference for predicting the magnitude and trajectory of net primary productivity (NPP) in the future. In this study, a process‐based ecosystem model, Carbon Exchange between Vegetation, Soil and Atmosphere (CEVSA), was used to investigate the response of NPP to warming at both national and subregional scales during 1961–2010. The results suggest that a 1.3°C increase in temperature stimulated the positive changing trend in NPP at national scale during the past 50 years. Regardless of the magnitude of temperature increase, warming enhanced the increase in NPP; however, the positive trend of NPP decreased when warming exceeded 2°C. The largest increase in NPP was found in regions where temperature increased by 1–2°C, and this rate of increase also contributed the most to the total increase in NPP in China's terrestrial ecosystems. Decreasing precipitation depressed the positive trend in NPP that was stimulated by warming. In northern China, warming depressed the increasing trend of NPP and warming that was accompanied by decreasing precipitation led to negative changing trends in NPP in large parts of northern China, especially when warming exceeded 2°C. However, warming stimulated the increase in NPP until warming was greater than 2°C, and decreased precipitation helped to increase the NPP in southern China.     

Comparing global models of terrestrial net primary productivity (NPP): analysis of differences in light absorption and light-use efficiency

Twelve global net primary productivity (NPP) models were compared: BIOME3, CASA, CARAIB, FBM, GLO-PEM, HYBRID, KGBM, PLAI, SDBM, SIB2, SILVAN and TURC. These models all use solar radiation as an input, and compute either absorbed solar radiation directly, or the amount of leaves used to absorb solar radiation, represented by the leaf area index (LAI). For all models, we obtained or estimated photosynthetically active radiation absorbed by the canopy (APAR). We then computed the light use efficiency for NPP (LUE) on an annual basis as the ratio of NPP to APAR. We analysed the relative importance for NPP of APAR and LUE. The analyses consider the global values of these factors, their spatial patterns represented by latitudinal variations, and the overall grid cell by grid cell variability. Spatial variability in NPP within a model proved to be determined by APAR, and differences among models by LUE. There was a compensation between APAR and LUE, so that global NPP values fell within the range of ‘generally accepted values’. Overall, APAR was lower for satellite driven models than for the other models. Most computed values of LUE were within the range of published values, except for one model.     

A critical element of the light‐induced quaternary structural changes in YtvA‐LOV

YtvA, a photosensory LOV (light‐oxygen‐voltage) protein from Bacillus subtilis, exists as a dimer that previously appeared to undergo surprisingly small structural changes after light illumination compared with other light‐sensing proteins. However, we now report that light induces significant structural perturbations in a series of YtvA‐LOV domain derivatives in which the Jα helix has been truncated or replaced. Results from native gel analysis showed significant mobility changes in these derivatives after light illumination; YtvA‐LOV without the Jα helix dimerized in the dark state but existed as a monomer in the light state. The absence of the Jα helix also affected the dark regeneration kinetics and the stability of the flavin mononucleotide (FMN) binding to its binding site. Our results demonstrate an alternative way of photo‐induced signal propagation that leads to a bigger functional response through dimer/monomer conversions of the YtvA‐LOV than the local disruption of Jα helix in the As‐LOV domain.     

Net primary productivity and rain‐use efficiency as affected by warming,altered precipitation,and clipping in a mixed‐grass prairie

Grassland productivity in response to climate change and land use is a global concern. In order to explore the effects of climate change and land use on net primary productivity (NPP), NPP partitioning [f_BNPP, defined as the fraction of belowground NPP (BNPP) to NPP], and rain‐use efficiency (RUE) of NPP, we conducted a field experiment with warming (+3 °C), altered precipitation (double and half), and annual clipping in a mixed‐grass prairie in Oklahoma, USA since July, 2009. Across the years, warming significantly increased BNPP, f_BNPP, and RUE_BNPP by an average of 11.6%, 2.8%, and 6.6%, respectively. This indicates that BNPP was more sensitive to warming than aboveground NPP (ANPP) since warming did not change ANPP and RUE_ANPP much. Double precipitation stimulated ANPP, BNPP, and NPP but suppressed RUE_ANPP, RUE_BNPP, and RUE_NPP while half precipitation decreased ANPP, BNPP, and NPP but increased RUE_ANPP, RUE_BNPP, and RUE_NPP. Clipping interacted with altered precipitation in impacting RUE_ANPP, RUE_BNPP, and RUE_NPP, suggesting land use could confound the effects of precipitation changes on ecosystem processes. Soil moisture was found to be a main factor in regulating variation in ANPP, BNPP, and NPP while soil temperature was the dominant factor influencing f_BNPP. These findings suggest that BNPP is critical point to future research. Additionally, results from single‐factor manipulative experiments should be treated with caution due to the non‐additive interactive effects of warming with altered precipitation and land use (clipping).     

Satellite estimates of productivity and light use efficiency in United States agriculture, 1982–98

Remote sensing of net primary production (NPP) is a critical tool for assessing spatial and temporal patterns of carbon exchange between the atmosphere and biosphere. However, satellite estimates suffer from a lack of large‐scale field data needed for validation, as well as the need to parameterize plant light‐use efficiencies (LUEs). In this study, we estimated cropland NPP with the Carnegie‐Ames‐Stanford‐Approach (CASA), a biogeochemical model driven by satellite observations, and then compared these results with field estimates based on harvest data from United States Department of Agriculture National Agriculture Statistics Service (NASS) county statistics. Observed interannual variations in NPP over a 17‐year period were well modelled by CASA, with exceptions mainly due to occasional difficulties in estimating NPP from harvest yields. The role of environmental stressors in agriculture was investigated by running CASA with and without temperature and moisture down‐regulators, which are used in the model to simulate climate impacts on plant LUE. In most cases, correlations with NASS data were highest with modelled stresses, while the opposite was true for irrigated and temperature resistant crops. Analysis of the spatial variability in computed LUE revealed significantly higher values for corn than for other crops, suggesting a simple parameterization of LUE for future studies based on the fraction of area with corn. Absolute values of LUE were much lower than those reported in field trials, due to uncommonly high yields in most field trials, as well as overestimates of absorbed radiation in CASA attributed to bias from temporal compositing of satellite data. Total NPP for US croplands, excluding Alaska and Hawaii, was estimated as 0.62 Pg C year^?1, representing ～20% of total US NPP, and exhibited a positive trend of 3.7 Tg C year^?2. These results have several implications for large‐scale carbon cycle research that are discussed, and are especially relevant for studies of the role of agriculture in the global carbon balance.     

2001-2010年疏勒河流域植被净初级生产力时空变化及其与气候因子的关系

通过改进的光能利用率CASA模型估算2001-2010年间疏勒河流域陆地生态系统的净第一性生产力（NPP）,采用线性趋势分析、变异系数和Hurst指数等方法,分析了NPP的时空变化特征及其与气候因子的相关性。结果表明：①疏勒河流域NPP的空间分布具有明显差异,空间上呈现西北低、东南高的趋势,且具有较明显的经向"条带"分布特征,2001-2010年,NPP平均值为102.26 gC m^-2 a^-1。②2001-2010年,疏勒河流域NPP总体呈增长趋势,年际波动较大,NPP明显增加的区域占总面积25.15%,明显减小的区域约占11.93%。③Hurst指数分析显示,疏勒河流域NPP变化的同向特征强于反向特征,其中持续改善地区占总面积的78.3%,21.7%的区域将由改善转为退化。④在年尺度上,降水是植被NPP变化的主要影响因素,NPP与降水呈弱的正相关关系,与温度相关性不显著;在月尺度上,温度是NPP变化的主要控制因子。疏勒河流域NPP对气候因子不存在明显的时滞和累积效应。     

Modeling the interannual variation and response to climate change scenarios in gross and net primary productivity of Pinus elliottii forest in subtropical China

In this study, the BIOME-BGC model, a biogeochemical model, was used and validated to estimate GPP (Gross Primary Productivity) and NPP (Net Primary Productivity) of Pinus elliottii forest in red soil hilly region and their responses to inter-annual climate variability during the period of 1993–2004 and climate change scenarios in the future. Results showed that the average total GPP and NPP were 1941 g C m^?2a^?1 and 695 g C m^?2a^?1, and GPP and NPP showed an increasing trend during the study period. The precipitation was the key factor controlling the GPP and NPP variation. Scenario analysis showed that doubled CO₂ concentration would not benefit for GPP and NPP with less than 1.5% decrease. When CO₂ concentration fixed, GPP responded positively to precipitation change only, and temperature increase by 1.5°C with precipitation increase, while NPP responded positively to precipitation change only. When CO₂ concentration was doubled and climate was changed, GPP and NPP responded positively to precipitation change, and GPP also responded positively to temperature increase by 1.5°C with precipitation change.     

Controls of primary productivity and nutrient cycling in a temperate grassland with year‐round production

Abstract Net primary production (NPP) and nutrient dynamics of grasslands are regulated by different biotic and abiotic factors, which may differentially affect functional plant groups. Most studies have dealt with grasslands that have extremely low or zero production over a significant period of the year. Here we explore the relative importance of a few environmental factors as controls of aerial and below‐ground plant biomass production and nutrient dynamics in a grassland that is active throughout the year. We investigate their effect on the response of three main plant functional groups (warm‐ and cool‐season graminoids and forbs). We conducted a factorial experiment in a continuously grazed site in the Flooding Pampa grassland (Argentina). Factors were seasons (summer, autumn, winter and spring), and environmental agents (mowing, shade, addition of phosphorus [P] and nitrogen [N]). N addition had the largest and most extended impact: it tripled aerial NPP in spring and summer but had no effect on below‐ground biomass. This positive effect was accompanied by higher N acquisition and higher soil N availability. Mowing increased aerial NPP in winter, increased root biomass in the first 10 cm during autumn and winter and promoted N and P uptake by plants. Shading did not affect aerial NPP, but stimulated N and P uptake by plants. P addition had no effect on aerial NPP, but increased shallow root biomass and its N content in spring, and tripled P accumulation in plant biomass. The three plant functional groups differentially accounted for these ecosystem‐level responses. Graminoids explained the greater biomass production of N‐fertilized plots and mowing tended to promote forbs. These results suggest that the environmental controls of aerial NPP in this grassland vary among seasons, differentially impact the major floristic groups, and affect the energy and nutrient transfer to herbivores.     

毛乌素沙地海流兔河流域植被净初级生产力估算

采用CASA(Carnegie-Ames-Stanford Approach)模型,结合TERRA MODIS卫星数据和气象数据,对毛乌素沙地海流兔河流域2015年各月的植被净初级生产力(NPP)进行估算,并对植被NPP月平均值的时空分布规律及其与气象因子和地下水位埋深的关系进行了分析.结果表明:毛乌素沙地海流兔河流域2015年植被NPP总量为2.88×1011 g,生长季(4月份至10月份)的植被NPP总量达2.81×1011 g,占全年植被NPP总量的97.57%.随着时间推移,植被NPP月平均值和归一化差分植被指数(NDVI)月平均值呈"缓慢增加—急剧增加—急剧下降"的变化趋势.植被NPP月平均值季节变化明显,春季、夏季、秋季和冬季植被NPP月平均值之和分别为20.55、69.39、20.46和0.48 g·m-2.从空间分布上看,中部河谷和滩地的植被NPP月平均值总体上高于东南部、西部和西北部等沙丘荒漠区.月平均气温对植被NPP月平均值变化的影响最大,其次为平均实际日蒸散发量和地表月太阳辐射.植被NPP月平均值随着地下水位埋深的增加而减小,最大值出现在地下水位埋深1~2 m之间.上述研究结果显示:采用CASA模型可以较好地估算毛乌素沙地海流兔河流域植被NPP值,月平均气温和地下水位埋深对该流域植被NPP值的影响较大.     

近30年来黄河三角洲植被净初级生产力时空特征及主要影响因素

我国拥有丰富的海岸带蓝色碳汇,准确把握海岸带蓝碳生态系统净初级生产力(NPP)状况,辨识不同人为干扰下蓝碳生态系统NPP的时空分布特征具有重要意义。以黄河三角洲为研究区,以近30a(1987年、1995年、2005年、2016—2017年)为时间尺度,通过遥感手段和现场调查,对黄河三角洲NPP时空变化特征及其主要影响因素进行研究。结果显示:(1)近30年来研究区NPP均值和总量呈现先下降又略微增长的特征,2016—2017年度NPP平均值为294.38g C m~(-2)a~(-1),总量为710.05Gg C/a,表现出显著的季节差异。(2)研究区NPP在各行政区、保护区和地表覆盖类型中均表现出了明显的空间分异性;2016—2017年度NPP分区结果显示,不同分区面积由大到小依次为中生产力区(49.5%)、低生产力区(38.3%)和高生产力区(12.1%)。(3)研究区NPP的时空分异性是地表覆盖类型和植被生长状况共同影响的结果,海陆交互作用、开发利用活动和近年来的生态建设是NPP时空变化的主要影响因素。(4)湿地植被和农田是研究区碳汇的主要贡献者,20世纪90年代以来二者NPP均值逐渐上升,在2016—2016年度分别达570.28g C m~(-2)a~(-1)和335.92g C m~(-2)a~(-1);近30年来,湿地植被NPP总量逐渐减少,农田NPP总量则逐渐增加。湿地植被是海岸带蓝碳的典型载体,农田作为位于滨海地区、由湿地植被转化而来、本身具有较高固碳能力和潜力的碳汇类型,可作为海岸带蓝碳的重要补充。     

2001-2010年内蒙古植被净初级生产力的时空格局及其与气候的关系

利用MODIS NDVI数据、气象数据和植被分类数据,基于改进的光能利用率模型CASA模型对2001-2010年内蒙古不同植被类型净初级生产力(NPP)进行估算,并分析其时空分布特征及对气候因子的响应.结果表明:(1)10年间内蒙古植被年NPP的平均值为340.0 gCm-2a-1,且空间分布呈明显的经度地带性,由西向东的变化速率为每10度增加200.5 gCm-2a-1;(2)不同植被类型NPP有较大差异,森林、草地、农田和荒漠植被的NPP平均值分别为521.9、270.3、405.7和85.3 gCm-2a-1;(3)10年间内蒙古植被NPP总量的平均值为322.7 TgCa-1,波动范围为276.8-354.4 TgCa-1.从NPP年际变化的空间分布来看,阿拉善沙漠、毛乌素沙地西部、河套平原以北地区、浑善达克沙地东西缘和呼伦贝尔平原西北部植被的NPP呈极显著上升,而内蒙古中部的草地植被NPP呈极显著下降;(4)不同植被类型NPP对气候因子的敏感性有较大差异.森林植被NPP主要受温度的限制,而农田、草地和荒漠植被NPP主要受降水量控制.     

1982-2020年安徽省净生态系统生产力时空格局变化及其成因

净生态系统生产力（NEP）是定量描述陆地生态系统与大气之间碳交换的重要指标。明确区域尺度NEP的时空格局及主导因子,有助于增强对区域碳循环变化机制的认知。基于BEPS （Boreal Ecosystem Productivity Simulator）模型模拟结果,评估了安徽省1982-2020年NEP时空格局,分析了安徽省NEP对主要环境植被因子的敏感性,并借助通径分析和贡献率分析探究了影响安徽省NEP时空变化的驱动因子。结果表明：（1）1982-2020年,安徽省多年年均NEP为651.14 gC/m²,线性趋势变化率为1.10 gC m^-2 a^-1,总体呈显著增加趋势（P<0.01）。在空间上,NEP表现为"南北部较高、中部较低"的分布,显著增加（P<0.05）的区域占52.77%,主要分布在北部和南部,显著减小（P<0.05）的区域占7.11%,主要分布在西部和东南部。NEP重心有显著的北移趋势（P<0.01）。（2） NEP对大气CO₂浓度变化最为敏感,对降水变化最不敏感。时间上,NEP对叶面积指数（LAI）（P<0.01）、CO₂（P<0.01）和饱和水汽压差（VPD）（P<0.05）的敏感性变化显著增强,对总辐射的敏感性变化显著减弱（P<0.01）,对气温和降水的敏感性变化不显著（P>0.05）。空间上,NEP对各因子的敏感性有地区差异性。（3）所选环境植被因子综合解释了NEP 79%的时空变化。LAI与CO₂是安徽省NEP时空变化的主导因子,为正贡献,气候因子为次主导因子,为负贡献。空间上,LAI为主导因子的地区主要分布在安徽省北部、中西部的大部分地区,占49.65%,CO₂为主导因子的地区主要分布在安徽省西北部与东南部的大部分地区,占44.54%。     

Atmospheric CO2 mole fraction affects stand‐scale carbon use efficiency of sunflower by stimulating respiration in light

Plant carbon‐use‐efficiency (CUE), a key parameter in carbon cycle and plant growth models, quantifies the fraction of fixed carbon that is converted into net primary production rather than respired. CUE has not been directly measured, partly because of the difficulty of measuring respiration in light. Here, we explore if CUE is affected by atmospheric CO₂. Sunflower stands were grown at low (200 μmol mol^?1) or high CO₂ (1000 μmol mol^?1) in controlled environment mesocosms. CUE of stands was measured by dynamic stand‐scale ¹³C labelling and partitioning of photosynthesis and respiration. At the same plant age, growth at high CO₂ (compared with low CO₂) led to 91% higher rates of apparent photosynthesis, 97% higher respiration in the dark, yet 143% higher respiration in light. Thus, CUE was significantly lower at high (0.65) than at low CO₂ (0.71). Compartmental analysis of isotopic tracer kinetics demonstrated a greater commitment of carbon reserves in stand‐scale respiratory metabolism at high CO₂. Two main processes contributed to the reduction of CUE at high CO₂: a reduced inhibition of leaf respiration by light and a diminished leaf mass ratio. This work highlights the relevance of measuring respiration in light and assessment of the CUE response to environment conditions.