Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years

The uncertainties of China's gross primary productivity (GPP) estimates by global data‐oriented products and ecosystem models justify a development of high‐resolution data‐oriented GPP dataset over China. We applied a machine learning algorithm developing a new GPP dataset for China with 0.1° spatial resolution and monthly temporal frequency based on eddy flux measurements from 40 sites in China and surrounding countries, most of which have not been explored in previous global GPP datasets. According to our estimates, mean annual GPP over China is 6.62 ± 0.23 PgC/year during 1982–2015 with a clear gradient from southeast to northwest. The trend of GPP estimated by this study (0.020 ± 0.002 PgC/year² from 1982 to 2015) is almost two times of that estimated by the previous global dataset. The GPP increment is widely spread with 60% area showing significant increasing trend (p < .05), except for Inner Mongolia. Most ecosystem models overestimated the GPP magnitudes but underestimated the temporal trend of GPP. The monsoon affected eastern China, in particular the area surrounding Qinling Mountain, seems having larger contribution to interannual variability (IAV) of China's GPP than the semiarid northwestern China and Tibetan Plateau. At country scale, temperature is the dominant climatic driver for IAV of GPP. The area where IAV of GPP dominated by temperature is about 42%, while precipitation and solar radiation dominate 31% and 27% respectively over semiarid area and cold‐wet area. Such spatial pattern was generally consistent with global GPP dataset, except over the Tibetan Plateau and northeastern forests, but not captured by most ecosystem models, highlighting future research needs to improve the modeling of ecosystem response to climate variations.     

Seasonal,interannual and decadal drivers of tree and grass productivity in an Australian tropical savanna

Tree–grass savannas are a widespread biome and are highly valued for their ecosystem services. There is a need to understand the long‐term dynamics and meteorological drivers of both tree and grass productivity separately in order to successfully manage savannas in the future. This study investigated the interannual variability (IAV) of tree and grass gross primary productivity (GPP) by combining a long‐term (15 year) eddy covariance flux record and model estimates of tree and grass GPP inferred from satellite remote sensing. On a seasonal basis, the primary drivers of tree and grass GPP were solar radiation in the wet season and soil moisture in the dry season. On an interannual basis, soil water availability had a positive effect on tree GPP and a negative effect on grass GPP. No linear trend in the tree–grass GPP ratio was observed over the 15‐year study period. However, the tree–grass GPP ratio was correlated with the modes of climate variability, namely the Southern Oscillation Index. This study has provided insight into the long‐term contributions of trees and grasses to savanna productivity, along with their respective meteorological determinants of IAV.     

Interannual variation of terrestrial carbon cycle: Issues and perspectives

With accumulation of carbon cycle observations and model developments over the past decades, exploring interannual variation (IAV) of terrestrial carbon cycle offers the opportunity to better understand climate–carbon cycle relationships. However, despite growing research interest, uncertainties remain on some fundamental issues, such as the contributions of different regions, constituent fluxes and climatic factors to carbon cycle IAV. Here we overviewed the literature on carbon cycle IAV about current understanding of these issues. Observations and models of the carbon cycle unanimously show the dominance of tropical land ecosystems to the signal of global carbon cycle IAV, where tropical semiarid ecosystems contribute as much as the combination of all other tropical ecosystems. Vegetation photosynthesis contributes more than ecosystem respiration to IAV of the global net land carbon flux, but large uncertainties remain on the contribution of fires and other disturbance fluxes. Climatic variations are the major drivers to the IAV of net land carbon flux. Although debate remains on whether the dominant driver is temperature or moisture variability, their interaction,that is, the dependence of carbon cycle sensitivity to temperature on moisture conditions, is emerging as key regulators of the carbon cycle IAV. On timescales from the interannual to the centennial, global carbon cycle variability will be increasingly contributed by northern land ecosystems and oceans. Therefore, both improving Earth system models (ESMs) with the progressive understanding on the fast processes manifested at interannual timescale and expanding carbon cycle observations at broader spatial and longer temporal scales are critical to better prediction on evolution of the carbon–climate system.     

Vegetation clumping modulates global photosynthesis through adjusting canopy light environment

The spatial dispersion of photoelements within a vegetation canopy, quantified by the clumping index (CI), directly regulates the within-canopy light environment and photosynthesis rate, but is not commonly implemented in terrestrial biosphere models to estimate the ecosystem carbon cycle. A few global CI products have been developed recently with remote sensing measurements, making it possible to examine the global impacts of CI. This study deployed CI in the radiative transfer scheme of the Community Land Model version 5 (CLM5) and used the revised CLM5 to quantitatively evaluate the extent to which CI can affect canopy absorbed radiation and gross primary production (GPP), and for the first time, considering the uncertainty and seasonal variation of CI with multiple remote sensing products. Compared to the results without considering the CI impact, the revised CLM5 estimated that sunlit canopy absorbed up to 9%–15% and 23%–34% less direct and diffuse radiation, respectively, while shaded canopy absorbed 3%–18% more diffuse radiation across different biome types. The CI impacts on canopy light conditions included changes in canopy light absorption, and sunlit–shaded leaf area fraction related to nitrogen distribution and thus the maximum rate of Rubisco carboxylase activity (V_cmax), which together decreased photosynthesis in sunlit canopy by 5.9–7.2 PgC year⁻¹ while enhanced photosynthesis by 6.9–8.2 PgC year⁻¹ in shaded canopy. With higher light use efficiency of shaded leaves, shaded canopy increased photosynthesis compensated and exceeded the lost photosynthesis in sunlit canopy, resulting in 1.0 ± 0.12 PgC year⁻¹ net increase in GPP. The uncertainty of GPP due to the different input CI datasets was much larger than that caused by CI seasonal variations, and was up to 50% of the magnitude of GPP interannual variations in the tropical regions. This study highlights the necessity of considering the impacts of CI and its uncertainty in terrestrial biosphere models.     

Latitudinal patterns of magnitude and interannual variability in net ecosystem exchange regulated by biological and environmental variables

Over the last two and half decades, strong evidence showed that the terrestrial ecosystems are acting as a net sink for atmospheric carbon. However the spatial and temporal patterns of variation in the sink are not well known. In this study, we examined latitudinal patterns of interannual variability (IAV) in net ecosystem exchange (NEE) of CO₂ based on 163 site-years of eddy covariance data, from 39 northern-hemisphere research sites located at latitudes ranging from ∼29°N to ∼64°N. We computed the standard deviation of annual NEE integrals at individual sites to represent absolute interannual variability (AIAV), and the corresponding coefficient of variation as a measure of relative interannual variability (RIAV). Our results showed decreased trends of annual NEE with increasing latitude for both deciduous broadleaf forests and evergreen needleleaf forests. Gross primary production (GPP) explained a significant proportion of the spatial variation of NEE across evergreen needleleaf forests, whereas, across deciduous broadleaf forests, it is ecosystem respiration (Re). In addition, AIAV in GPP and Re increased significantly with latitude in deciduous broadleaf forests, but AIAV in GPP decreased significantly with latitude in evergreen needleleaf forests. Furthermore, RIAV in NEE, GPP, and Re appeared to increase significantly with latitude in deciduous broadleaf forests, but not in evergreen needleleaf forests. Correlation analyses showed air temperature was the primary environmental factor that determined RIAV of NEE in deciduous broadleaf forest across the North American sites, and none of the chosen climatic factors could explain RIAV of NEE in evergreen needleleaf forests. Mean annual NEE significantly increased with latitude in grasslands. Precipitation was dominant environmental factor for the spatial variation of magnitude and IAV in GPP and Re in grasslands.     

毛竹林总初级生产力年际变化及其驱动因素——以安吉县为例

森林生态系统碳通量的年际变化及其驱动因素分析是了解森林碳收支动态变化以及预测未来气候变化对森林碳收支影响的重要理论基础,对评估森林应对气候变化的贡献具有重要意义。结合MODIS叶面积指数(LAI)和归一化植被指数(NDVI)产品、MERRA气象数据和通量塔观测数据,采用光能利用率模型模拟2004—2011年安吉县毛竹林生态系统总初级生产力(GPP)空间分布,并分析GPP年际变化及其驱动因素。结果表明:(1)小年毛竹林GPP稍高于大年GPP;(2)2004—2011年安吉县毛竹林年日均GPP呈下降趋势,东部、西部和整个安吉县毛竹林年日均GPP变化速率分别为-0.064、-0.033和-0.045g C m-2W-1,年均温度持续下降是主要驱动因素;(3)LAI年际变化是GPP年际变化的主要驱动因素,主要原因是毛竹林大小年交替规律引起了有效LAI年际间差异;(4)西部GPP年际变化幅度大于东部,环境和生物因素对GPP年际变化的作用方向决定了毛竹林GPP年际变化的幅度。     

Negative relationship between photosynthesis and late-stage canopy development and senescence over Tibetan Plateau

Canopy greening, which is associated with significant canopy structure changes, is the most notable signal of ecosystem changes in response to anthropogenic climate change. However, our knowledge of the changing pattern of canopy development and senescence, and its endogenous and climatic drivers is still limited. Here, we used the Normalized Difference Vegetation Index (NDVI) to quantify the changes in the speed of canopy development and senescence over the Tibetan Plateau (TP) during 2000–2018, and used a solar-induced chlorophyll fluorescence dataset as a proxy for photosynthesis, in combination with climate datasets to decipher the endogenous and climatic drivers of the interannual variation in canopy changes. We found that the canopy development during the early green-up stage (April–May) is accelerating at a rate of 0.45–0.8 × 10⁻³ month⁻¹ year⁻¹. However, this accelerating canopy development was largely offset by a decelerating canopy development during June and July (−0.61 to −0.51 × 10⁻³ month⁻¹ year⁻¹), leading to the peak NDVI over the TP increasing at a rate of only one fifth of that in northern temperate regions, and less than one tenth of that in the Arctic and boreal regions. During the green-down period, we observed a significant accelerating canopy senescence during October. Photosynthesis was found to be the dominant driver for canopy changes over the TP. Increasing photosynthesis stimulates canopy development during the early green-up stage. However, slower canopy development and accelerated senescence was found with larger photosynthesis in late growth stages. This negative relationship between photosynthesis and canopy development is probably linked to the source–sink balance of plants and shifts in the allocation regime. These results suggest a sink limitation for plant growth over the TP. The impact of canopy greening on the carbon cycle may be more complicated than the source-oriented paradigm used in current ecosystem models.     

The climate change mitigation effect of bioenergy from sustainably managed forests in Central Europe

We compare sustainably managed with unmanaged forests in terms of their contribution to climate change mitigation based on published data. For sustainably managed forests, accounting of carbon (C) storage based on ecosystem biomass and products as required by the United Nations Framework Convention on Climate Change is not sufficient to quantify their contribution to climate change mitigation. The ultimate value of biomass is its use for biomaterials and bioenergy. Taking Germany as an example, we show that the average removals of wood from managed forests are higher than stated by official reports, ranging between 56 and 86 mill. m³ year^?1 due to the unrecorded harvest of firewood. We find that removals from one hectare can substitute 0.87 m³ ha^?1 year^?1 of diesel, or 7.4 MWh ha^?1 year^?1, taking into account the unrecorded firewood, the use of fuel for harvesting and processing, and the efficiency of energy conversion. Energy substitution ranges between 1.9 and 2.2 t CO_{2 equiv.} ha^?1 year^?1 depending on the type of fossil fuel production. Including bioenergy and carbon storage, the total mitigation effect of managed forest ranges between 3.2 and 3.5 t CO_{2 equiv.} ha^?1 year^?1. This is more than previously reported because of the full accounting of bioenergy. Unmanaged nature conservation forests contribute via C storage only about 0.37 t CO_{2 equiv.}  ha^?1 year^?1 to climate change mitigation. There is no fossil fuel substitution. Therefore, taking forests out of management reduces climate change mitigation benefits substantially. There should be a mitigation cost for taking forest out of management in Central Europe. Since the energy sector is rewarded for the climate benefits of bioenergy, and not the forest sector, we propose that a CO₂ tax is used to award the contribution of forest management to fossil fuel substitution and climate change mitigation. This would stimulate the production of wood for products and energy substitution.     

Interannual NPP variation and trend of Picea schrenkiana forests under changing climate conditions in the Tianshan Mountains, Xinjiang, China

The interannual net primary production variation and trends of a Picea schrenkiana forest were investigated in the context of historical changes in climate and increased atmospheric CO₂ concentration at four sites in the Tianshan Mountain range, China. Historical changes in climate and atmospheric CO₂ concentration were used as Biome–BGC model drivers to evaluate the spatial patterns and temporal trends of net primary production (NPP). The temporal dynamics of NPP of P. schrenkiana forests were different in the western, middle and eastern sites of Tianshan, which showed substantial interannual variation. Climate changes would result in increased NPP at all study sites, but only the change in NPP in the western forest (3.186 gC m⁻² year⁻¹, P < 0.05) was statistically significant. Our study also showed a higher increase in the air temperature, precipitation and NPP during 1987–2000 than 1961–1986. Statistical analysis indicates that changes in NPP are positively correlated with annual precipitation (R = 0.77–0.92) but that NPP was less sensitive to changes in air temperature. According to the simulation, increases in atmospheric CO₂ increased NPP by improving the water use efficiency. The results of this study show that the Tianshan Mount boreal forest ecosystem is sensitive to historical changes in climate and increasing atmospheric CO₂. The relative impacts of these variations on NPP interact in complex ways and are spatially variable, depending on local conditions and climate gradients. W. Sang and H. Su contributed equally to this paper, arranged in alphabetical order by surnames.     

Climate change alters interannual variation of grassland aboveground productivity: evidence from a 22-year measurement series in the Inner Mongolian grassland

Climate change is known to influence interannual variation in grassland aboveground net primary productivity (ANPP), or seasonal biomass, but direct, long-term ground observations are rare. We present a 22-year (1982–2003) measurement series from the Inner Mongolia grassland, China, to examine the effect of climate change on interannual variations in ANPP and monthly aboveground biomass (MAB). ANPP exhibited no increase over 1982–2003 but there was an association with previous-year precipitation. MAB in May increased by 21.8% from 47.8 g m⁻² (averaged for 1982–1984) to 58.2 g m⁻² (2001–2003), whereas there was no significant variation in June, July and August, and a decrease of 29.7% in September. The MAB increase in May was correlated with increases in precipitation and temperature in the preceding months. These findings suggest that the effects of climate change on grassland production vary throughout the growing season, with warmer and wetter springs resulting in increased biomass early in the growing season, and drier falls causing a decrease in biomass late in the growing season.     

Tillage effects on carbon footprint and ecosystem services of climate regulation in a winter wheat–summer maize cropping system of the North China Plain

Inappropriate farm practices can increase greenhouse gases (GHGs) emissions and reduce soil organic carbon (SOC) sequestration, thereby increasing carbon footprints (CFs), jeopardizing ecosystem services, and affecting climate change. Therefore, the objectives of this study were to assess the effects of different tillage systems on CFs, GHGs emissions, and ecosystem service (ES) values of climate regulation and to identify climate-resilient tillage practices for a winter wheat (Triticum aestivum L.)-summer maize (Zea mays L.) cropping system in the North China Plain (NCP). The experiment was established in 2008 involving no-till with residue retention (NT), rotary tillage with residue incorporation (RT), sub-soiling with residue incorporation (ST), and plow tillage with residue incorporation (PT). The results showed that GHGs emissions from agricultural inputs were 6432.3–6527.3 kg CO₂-eq ha⁻¹ yr⁻¹ during the entire growing season, respectively. The GHGs emission from chemical fertilizers and irrigation accounted for >80% of that from agricultural inputs during the entire growing season. The GHGs emission from agricultural inputs were >2.3 times larger in winter wheat than that in the summer maize season. The CFs at yield-scale during the entire growing season were 0.431, 0.425, 0.427, and 0.427 without and 0.286, 0.364, 0.360, and 0.334 kg CO₂-eq kg⁻¹ yr⁻¹ with SOC sequestration under NT, RT, ST, and PT, respectively. Regardless of SOC sequestration, the CFs of winter wheat was larger than that of summer maize. Agricultural inputs and SOC change contributed mainly to the component of CFs of winter wheat and summer maize. The ES value of climate regulation under NT was ¥159.2, 515.6, and 478.1 ha⁻¹ yr⁻¹ higher than that under RT, ST, and PT during the entire growing season. Therefore, NT could be a preferred “Climate-resilient” technology for lowering CFs and enhancing ecosystem services of climate regulation for the winter wheat–summer maize system in the NCP.     

The effect of different anthropogenic disturbances on litterfall of a dominant pioneer rain forest tree in Gabon

Tropical rain forests worldwide are affected by anthropogenic disturbances, and secondary forests that develop afterwards are often dominated by pioneer tree species, but the consequences of different anthropogenic disturbances on nutrient cycling are poorly understood. Because most nutrient cycling in tropical rain forests occurs through litterfall and in the soil organic layer, we measured litterfall of a widespread and dominant pioneer tree, okoume (Aucoumea klaineana, Burseraceae) in Gabon, in one forest previously disturbed by logging and in another by agriculture. Litterfall of okoume trees, measured over 14 months, was 18.2 Mg ha⁻¹ year⁻¹ in the formerly logged forest, which was 72.6% greater than in the forest more recently disturbed by agriculture (10.6 Mg ha⁻¹ year⁻¹). Litter decomposition rates were more rapid in the formerly logged forest, and this may explain why litter thickness was 32% lower in the formerly logged forest, despite the greater litterfall within it. Our results highlight that two widespread anthropogenic disturbances in Gabonese rain forests have significantly different consequences on litterfall of a dominant tree and therefore are likely to have different effects on nutrient cycling and forest ecosystem function.     

基于碳-水-氮耦合过程改进模型的温带草地生态系统生产力模拟研究

基于碳-水-氮耦合过程改进模型的温带草地生态系统生产力模拟研究 预测气候变化背景下生态系统总初级生产力的响应是全球变化生态学研究领域的一项核心任务。然而,对模型研究领域来说,准确模拟干旱生态系统总初级生产力的年际变异仍然是一个巨大的挑战。土壤含水量和总初级生产力对土壤水敏感性的精确模拟,是预测干旱生态系统中总初级生产力年际变异的两个关键方面。为此,本研究以一个广泛应用的生态系统模型(Biome-BGC模型)为例,旨在改进温带草地生态系统的模型模拟效果。一方面,通过对蒸散模块、土壤水沿剖面的垂直分布和田间持水量计算的改进和调整,模型实现了对土壤水模拟的更新。另一方面,我们改进了影响水-氮关系的函数,从而调节了总初级生产力对土壤水的敏感性。研究结果表明,原有模型高估了土壤含水量,低估了总初级生产力敏感性的年际变异,从而导致模拟总初级生产力的年际变异低于观测值。例如,原模型严重低估了总初级生产力在干旱年份的减少。相比之下,改进后的模型准确地模拟了观测土壤水的季节和年际变化,特别是表层土壤水。通过优化影响氮矿化的参数,改进后的模型改善了总初级生产力对土壤水敏感性的模拟,使其更接近观测值。因此,改进后模型对总初级生产力年际变异的模拟得到了很大程度的提高。我们的结果表明,在对干旱生态系统总初级生产力年际变异进行模拟时,应优先考虑表层土壤水及其对氮有效性的影响。     

High within-stream replication is needed to predict litter fluxes in wet–dry tropical streams

1. Streams draining forested landscapes are fuelled by terrestrial plant litter, which can be transported downstream or retained and broken down locally. However, fluxes of plant litter in streams can vary at multiple spatio-temporal scales, affecting the availability of this key resource in heterotrophic stream food webs.
2. To explore this question we quantified several processes related to litter dynamics (i.e. litter inputs, storage, losses by transport and losses by breakdown) by sampling litter at multiple sites in three streams of the Brazilian Cerrado biome (which has a tropical wet–dry climate) for 2 years. We assessed the relative contribution of different spatial (among and within streams) and temporal scales (annual, seasonal and monthly) to total variability of these processes (hereafter fluxes).
3. Spatial and temporal variability of fluxes were both high, but spatial variation was 1.67-fold greater than temporal variation (61 versus 37%, respectively), especially at the within-stream scale (50% overall); an exception was litterfall, which varied less spatially than temporally (24 versus 76%). Temporal variation of litter storage (and hence availability to consumers) was mostly seasonal and due to differences in net transport.
4. Inputs and transport were higher in the wet than the dry season (wet versus dry season, 1.45 versus 0.92 and 1.43 versus 0.06 g litter m⁻² day⁻¹), while breakdown was similar between both seasons (0.88 versus 0.94 g litter m⁻² day⁻¹). Storage (i.e. accumulation) rate was positive and negative in the dry and wet season, respectively, indicating that litter was stored in the dry season and exported in the wet season. The transitional dry–wet season showed the highest inputs, breakdown and storage (3.21, 1.63 g litter m⁻² day⁻¹ and 145 g litter m⁻²), while the wet–dry season showed lower inputs (as in the dry season), higher transport (as in the wet season) and lower breakdown and storage than the other seasons (0.93, 0.65, 0.31 g litter m⁻² day⁻¹ and 24 g litter m⁻²).
5. Our results underscore the role of variation in biophysical drivers of litter fluxes within streams (e.g. pool–riffle configuration, substrate features, biological communities), and suggest that high within-stream replication is necessary to study litter fluxes at larger scales and over time. The seasonal patterns suggested potential changes in litter dynamics under future climate scenarios in the tropics, including increased storage due to reduced transport in a drier climate.

     

Effects of seasonal and interannual variations in leaf photosynthesis and canopy leaf area index on gross primary production of a cool-temperate deciduous broadleaf forest in Takayama, Japan

Revealing the seasonal and interannual variations in forest canopy photosynthesis is a critical issue in understanding the ecological mechanisms underlying the dynamics of carbon dioxide exchange between the atmosphere and deciduous forests. This study examined the effects of temporal variations of canopy leaf area index (LAI) and leaf photosynthetic capacity [the maximum velocity of carboxylation (V _cmax)] on gross primary production (GPP) of a cool-temperate deciduous broadleaf forest for 5 years in Takayama AsiaFlux site, central Japan. We made two estimations to examine the effects of canopy properties on GPP; one is to incorporate the in situ observation of V _cmax and LAI throughout the growing season, and another considers seasonality of LAI but constantly high V _cmax. The simulations indicated that variation in V _cmax and LAI, especially in the leaf expansion period, had remarkable effects on GPP, and if V _cmax was assumed constant GPP will be overestimated by 15%. Monthly examination of air temperature, radiation, LAI and GPP suggested that spring temperature could affect canopy phenology, and also that GPP in summer was determined mainly by incoming radiation. However, the consequences among these factors responsible for interannual changes of GPP are not straightforward since leaf expansion and senescence patterns and summer meteorological conditions influence GPP independently. This simulation based on in situ ecophysiological research suggests the importance of intensive consideration and understanding of the phenology of leaf photosynthetic capacity and LAI to analyze and predict carbon fixation in forest ecosystems.     

Divergent carbon cycle response of forest and grass‐dominated northern temperate ecosystems to record winter warming

Northern temperate ecosystems are experiencing warmer and more variable winters, trends that are expected to continue into the foreseeable future. Despite this, most studies have focused on climate change impacts during the growing season, particularly when comparing responses across different vegetation cover types. Here we examined how a perennial grassland and adjacent mixed forest ecosystem in New Hampshire, United States, responded to a period of highly variable winters from 2014 through 2017 that included the warmest winter on record to date. In the grassland, record‐breaking temperatures in the winter of 2015/2016 led to a February onset of plant growth and the ecosystem became a sustained carbon sink well before winter ended, taking up roughly 90 g/m² more carbon during the winter to spring transition than in other recorded years. The forest was an unusually large carbon source during the same period. While forest photosynthesis was restricted by leaf‐out phenology, warm winter temperatures caused large pulses of ecosystem respiration that released nearly 230 g C/m² from February through April, more than double the carbon losses during that period in cooler years. These findings suggest that, as winters continue to warm, increases in ecosystem respiration outside the growing season could outpace increases in carbon uptake during a longer growing season, particularly in forests that depend on leaf‐out timing to initiate carbon uptake. In ecosystems with a perennial leaf habit, warming winter temperatures are more likely to increase ecosystem carbon uptake through extension of the active growing season. Our results highlight the importance of understanding relationships among antecedent winter conditions and carbon exchange across land‐cover types to understand how landscape carbon exchange will change under projected climate warming.     

Primary production and climatic variability in the European sector of the Arctic Ocean prior to 2007: preliminary results

The primary production in the Greenland Sea, Fram Strait, Barents Sea, Kara Sea and adjacent Polar Ocean was investigated through the physically–biologically coupled, nested 3D SINMOD model with 4 km grid size for the years 1995–2007. The model had atmospheric forcing from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data. Three basic gross primary production (GPP) domains were distinguished: (i) an extensive domain dominated by Atlantic Water, (ii) an elongated domain roughly corresponding to the seasonal ice zone (SIZ) and (iii) a compact perennial ice zone (>100, between 100 and 30 and <30 g C m^?2 year^?1, respectively). The interannual coefficient of variation for GPP in domain (i) was <0.1, and increased northwards towards >0.6 in the northwesternmost and northeasternmost fringe of the SIZ. The primary production in the northern sector of the European Arctic Corridor (EAC) region prior to 2007 was characterised by limited interannual variability, on average 75.2 ± 10% and 24.0 ± 16% g C m^?2 year^?1 for the EAC region at 74–80 and >80°N, respectively. The main primary production anomalies were found early in the productive season and in sections of the SIZ, generally in regions with low GPP. There was no significant trend of increasing GPP in the 1995–2007 time interval.     

Importance of mangrove plantations for climate change mitigation in Bangladesh

Mangroves have been identified as blue carbon ecosystems that are natural carbon sinks. In Bangladesh, the establishment of mangrove plantations for coastal protection has occurred since the 1960s, but the plantations may also be a sustainable pathway to enhance carbon sequestration, which can help Bangladesh meet its greenhouse gas (GHG) emission reduction targets, contributing to climate change mitigation. As a part of its Nationally Determined Contribution (NDC) under the Paris Agreement 2016, Bangladesh is committed to limiting the GHG emissions through the expansion of mangrove plantations, but the level of carbon removal that could be achieved through the establishment of plantations has not yet been estimated. The mean ecosystem carbon stock of 5–42 years aged (average age: 25.5 years) mangrove plantations was 190.1 (±30.3) Mg C ha⁻¹, with ecosystem carbon stocks varying regionally. The biomass carbon stock was 60.3 (±5.6) Mg C ha⁻¹ and the soil carbon stock was 129.8 (±24.8) Mg C ha⁻¹ in the top 1 m of which 43.9 Mg C ha⁻¹ was added to the soil after plantation establishment. Plantations at age 5 to 42 years achieved 52% of the mean ecosystem carbon stock calculated for the reference site (Sundarbans natural mangroves). Since 1966, the 28,000 ha of established plantations to the east of the Sundarbans have accumulated approximately 76,607 Mg C year⁻¹ sequestration in biomass and 37,542 Mg C year⁻¹ sequestration in soils, totaling 114,149 Mg C year⁻¹. Continuation of the current plantation success rate would sequester an additional 664,850 Mg C by 2030, which is 4.4% of Bangladesh's 2030 GHG reduction target from all sectors described in its NDC, however, plantations for climate change mitigation would be most effective 20 years after establishment. Higher levels of investment in mangrove plantations and higher plantation establishment success could contribute up to 2,098,093 Mg C to blue carbon sequestration and climate change mitigation in Bangladesh by 2030.     

Impact of different ERA reanalysis data on GPP simulation

The performance of the terrestrial biosphere models (TBMs) is limited by the accuracy of climate forcing data. As the reanalysis products of the European Centre for Medium-Range Weather Forecasts (ECMWF), ERA-Interim and ERA5 data are widely used in the simulation of terrestrial carbon budgets and reveal their responses to climate change. However, the discrepancy between simulated carbon budgets driven by ERA-Interim and ERA5 on a global scale has not been evaluated. In this study, driven by ERA-Interim and ERA5, we conducted two simulations by a TBM, BEPS (Boreal Ecosystem Productivity Simulator), to investigate the differences of simulated Gross primary productivity (GPP) in temporal trends and spatial patterns and to identify the differences in climate factors resulted in the spreads of simulated GPPs. We found that by 2015, the relatively stable difference of simulated GPP by ERA-Interim and ERA5 was about 3.55 Pg C yr⁻¹. Since 2016, the differences of simulated GPP increased gradually and peaked in the last year of our simulation in 2018 at 13.16 Pg C yr⁻¹. This significant difference in GPP was due to the changes of GPP in the Amazon Basin, Congo Basin and South Asia, where tropical forests and tropical savannahs & grasslands were widely distributed. In these regions, the GPP of ERA5 in total was at least 3.0 Pg C yr⁻¹ lower than that of ERA-Interim after 2016. The difference of GPP in such regions was the main reason why ERA5 and ERA-Interim GPP showed different interannual variability. And less precipitation and higher temperature of ERA5 in tropical regions mainly results in the reduction of GPP compared with the results driven by ERA-Interim. Our results highlight challenges in using ERA5 and ERA-Interim to evaluate responses of ecosystem to climate change and provide implications for reducing the uncertainty of climate forcing data in simulating terrestrial carbon cycle.     

Small-scale variation in ecosystem CO2 fluxes in an alpine meadow depends on plant biomass and species richness

Characterizing the spatial variation in the CO₂ flux at both large and small scales is essential for precise estimation of an ecosystem’s CO₂ sink strength. However, little is known about small-scale CO₂ flux variations in an ecosystem. We explored these variations in a Kobresia meadow ecosystem on the Qinghai-Tibetan plateau in relation to spatial variability in species composition and biomass. We established 14 points and measured net ecosystem production (NEP), gross primary production (GPP), and ecosystem respiration (Re) in relation to vegetation biomass, species richness, and environmental variables at each point, using an automated chamber system during the 2005 growing season. Mean light-saturated NEP and GPP were 30.3 and 40.5 μmol CO₂ m⁻² s⁻¹ [coefficient of variation (CV), 42.7 and 29.4], respectively. Mean Re at 20°C soil temperature, Re₂₀, was −10.9 μmol CO₂ m⁻² s⁻¹ (CV, 27.3). Re₂₀ was positively correlated with vegetation biomass. GPP_max was positively correlated with species richness, but 2 of the 14 points were outliers. Vegetation biomass was the main determinant of spatial variation of Re, whereas species richness mainly affected that of GPP, probably reflecting the complexity of canopy structure and light partitioning in this small grassland patch.