Carbon Uptake Period Research Articles

Evolution and Mechanism Analysis of Terrestrial Ecosystems in China with Respect to Gross Primary Productivity

The gross primary productivity (GPP) of vegetation stores atmospheric carbon dioxide as organic compounds through photosynthesis. Its spatial heterogeneity is primarily influenced by the carbon uptake period (CUP) and maximum photosynthetic productivity (GPPmax). Grassland, cropland, and forest are crucial components of China’s terrestrial ecosystems and are strongly influenced by the seasonal climate. However, it remains unclear whether the evolutionary characteristics of GPP are attributable to physiology or phenology. In this study, terrestrial ecosystem models and remote sensing observations of multi-source GPP data were utilized to quantitatively analyze the spatio-temporal dynamics from 1982 to 2018. We found that GPP exhibited a significant upward trend in most areas of China’s terrestrial ecosystems over the past four decades. Over 60% of Chinese grassland and over 50% of its cropland and forest exhibited a positive growth trend. The average annual GPP growth rates were 0.23 to 3.16 g C m−2 year−1 for grassland, 0.40 to 7.32 g C m−2 year−1 for cropland, and 0.67 to 7.81 g C m−2 year−1 for forest. GPPmax also indicated that the overall growth rate was above 1 g C m−2 year−1 in most regions of China. The spatial trend pattern of GPPmax closely mirrored that of GPP, although local vegetation dynamics remain uncertain. The partial correlation analysis results indicated that GPPmax controlled the interannual GPP changes in most of the terrestrial ecosystems in China. This is particularly evident in grassland, where more than 99% of the interannual variation in GPP is controlled by GPPmax. In the context of rapid global change, our study provides an accurate assessment of the long-term dynamics of GPP and the factors that regulate interannual variability across China’s terrestrial ecosystems. This is helpful for estimating and predicting the carbon budget of China’s terrestrial ecosystems.

Better representation of vegetation phenology improves estimations of annual gross primary productivity

Carbon uptake by vegetation plays a vital role in the global carbon cycle. Annual gross primary productivity (AGPP) represents the total amount of carbon compounds produced by vegetation photosynthesis over a year and is a crucial metric for quantifying vegetation carbon uptake. Although some theories have been developed to explain the spatiotemporal variation in AGPP, they often overlook the seasonal differences in photosynthesis across vegetation phenological periods. This gap highlights the need for a more reasonable representation of vegetation phenology in AGPP modelling. Therefore, we developed a novel theoretical AGPP model that decomposes AGPP into detailed vegetation phenological periods (green-up, maturation, and senescence) and investigated the effects of climatic factors on the seasonal components of AGPP. Compared with existing models, our model considers the length of the multiple vegetation phenological periods, rather than just the length of the carbon uptake period. When evaluated against flux tower data, our model outperformed the comparative model, with a higher determination coefficient and lower root mean square error. The analysis also demonstrated that the developed model can reproduce spatial and temporal variations in satellite-based global AGPP. In addition, we identified distinct differences in the responses of AGPP's seasonal components to climatic factors: shortwave radiation predominantly affected the seasonal component of AGPP during senescence, air temperature during green-up, and vapor pressure deficit during maturation. Our study proposes a potential mechanism for AGPP estimation and highlights the importance of accurately representing vegetation phenology in AGPP modelling.

Impact of Fragmentation on Carbon Uptake in Subtropical Forest Landscapes in Zhejiang Province, China

Global changes cause widespread forest fragmentation, which, in turn, has given rise to many ecological problems; this is especially true if the forest carbon stock is profoundly impacted by fragmentation levels. However, the way in which forest carbon uptake changes with different fragmentation levels and the main pathway through which fragmentation affects forest carbon uptake are still unclear. Remote sensing data, vegetation photosynthesis models, and fragmentation models were employed to generate a time series GPP (gross primary productivity) dataset, as well as forest fragmentation levels for forest landscapes in Zhejiang province, China. We analyzed GPP variation with forest fragmentation levels and identified the relative importance of the phenology (carbon uptake period—CUP) and physiology (maximum daily GPP—GPPmax) control pathways of GPP under different fragmentation levels. The results showed that the normalized mean annual GPP data of highly fragmented forests during the period from 2000 to 2018 were significantly higher than those of other fragmentation levels, while there was almost no significant difference in the annual GPP trend of forest landscapes with all fragmentation levels. Moreover, the percentage area of the control variable, GPPmax, gradually increased with fragmentation levels; the mean GPPmax between 2000 and 2018 of high-level fragmentation was higher than that of other fragmentation levels. Our results demonstrate that the carbon uptake capacity per unit area was enhanced in highly fragmented forest areas, and the maximum photosynthetic capacity (physiology-based process) played an important role in controlling carbon uptake, especially in highly fragmented forest landscapes. Our study calls for a better and deeper understanding of the potential of forest carbon uptake, and it is necessary to explore the mechanism by which forest fragmentation changes the vegetation photosynthetic process.

Interannual Variation and Trend of Carbon Budget Observed for More Than Two Decades at Takayama in a Cool‐Temperate Deciduous Forest in Central Japan

AbstractLong‐term carbon dioxide (CO2) flux measurements between the atmosphere and the ecosystem have been made since 1993 at a cool‐temperate deciduous forest site (Takayama) in Japan influenced by the Asian Monsoon, constituting the longest data set among all the AsiaFlux sites. Interannual variations (IAVs) and trends in the annual carbon budget components and related environmental factors were examined. Annual net ecosystem production (NEP) (mean ± 1σ) during the period of eddy covariance measurements in 1999–2021 was 265 ± 86 gC m−2 yr−1, and its IAV was dependent more on gross primary production (GPP) than on ecosystem respiration. The annual NEP and GPP were correlated with the monthly mean NEP, GPP and leaf area index from June to September, as well as with the length of the net carbon uptake period. Significantly increasing and decreasing trends in the annual NEP and GPP were detected during 2004–2013 and 2013–2021, respectively. The increasing trends were mainly caused by the vegetation recovery from typhoon disturbances. On the other hand, although the cause of the decreasing trends was not clearly identified, recent extreme weather events and/or forest succession might be related to the trends. Significant positive correlations between the start and the end of the net carbon uptake period, and between the leaf expansion and leaf fall were found. These may be attributed to phenological characteristics and negative correlation between air temperature in spring and solar radiation in early fall associated with ENSO events that can also influence IAVs in annual NEP and GPP.

Estimating global annual gross primary production based on satellite-derived phenology and maximal carbon uptake capacity

The high uncertainty regarding global gross primary production (GPP) remains unresolved. This study explored the relationships between phenology, physiology, and annual GPP to provide viable alternatives for accurate estimation. A statistical model of integrated phenology and physiology (SMIPP) was developed using GPP data from 145 FLUXNET sites to estimate the annual GPP for various vegetation types. By employing the SMIPP model driven by satellite-derived datasets of the global carbon uptake period (CUP) and maximal carbon uptake capacity (GPPmax), the global annual GPP was estimated for the period from 2001 to 2018. The results demonstrated that the SMIPP model accurately predicted annual GPP, with relative root mean square error values ranging from 11.20 to 19.29% for forest types and 20.49–35.71% for non-forest types. However, wetlands, shrublands, and evergreen forests exhibited relatively low accuracies. The average, trend, and interannual variation of global GPP during 2001–2018 were 132.6 Pg C yr−1, 0.25 Pg C yr−2, and 1.57 Pg C yr−1, respectively. They were within the ranges estimated in other global GPP products. Sensitivity analysis revealed that GPPmax had comparable effects to CUP in high-latitude regions but significantly greater impacts at the global scale, with sensitivity coefficients of 0.85 ± 0.23 for GPPmax and 0.46 ± 0.28 for CUP. This study provides a simple and practical method for estimating global annual GPP and highlights the influence of GPPmax and CUP on global-scale annual GPP.

Dynamic regulation of water potential in Juniperus osteosperma mediates ecosystem carbon fluxes.

Some plants exhibit dynamic hydraulic regulation, in which the strictness of hydraulic regulation (i.e. iso/anisohydry) changes in response to environmental conditions. However, the environmental controls over iso/anisohydry and the implications of flexible hydraulic regulation for plant productivity remain unknown. In Juniperus osteosperma, a drought-resistant dryland conifer, we collected a 5-month growing season time series of in situ, high temporal-resolution plant water potential ( ) and stand gross primary productivity (GPP). We quantified the stringency of hydraulic regulation associated with environmental covariates and evaluated how predawn water potential contributes to empirically predicting carbon uptake. Juniperus osteosperma showed less stringent hydraulic regulation (more anisohydric) after monsoon precipitation pulses, when soil moisture and atmospheric demand were high, and corresponded with GPP pulses. Predawn water potential matched the timing of GPP fluxes and improved estimates of GPP more strongly than soil and/or atmospheric moisture, notably resolving GPP underestimation before vegetation green-up. Flexible hydraulic regulation appears to allow J. osteosperma to prolong soil water extraction and, therefore, the period of high carbon uptake following monsoon precipitation pulses. Water potential and its dynamic regulation may account for why process-based and empirical models commonly underestimate the magnitude and temporal variability of dryland GPP.

Phenological characteristics of net ecosystem carbon exchange of Stipa krylovii steppe in Inner Mongolia, China and its remote sensing monitoring.

To accurately monitor the phenology of net ecosystem carbon exchange (NEE) in grasslands with remote sensing, we analyzed the variations in NEE and its phenology in the Stipa krylovii steppe and discussed the remote sensing vegetation index thresholds for NEE phenology, with the observational data from the Inner Mongolia Xilinhot National Climate Observatory's eddy covariance system and meteorological gradient observation system during 2018-2021, as well as Sentinel-2 satellite data from January 1, 2018 to December 31, 2021. Results showed that, from 2018 to 2021, NEE exhibited seasonal variations, with carbon sequestration occurring from April to October and carbon emission in other months, resulting in an overall carbon sink. The average Julian days for the start date (SCUP) and the end date (ECUP) of carbon uptake period were the 95th and 259th days, respectively, with an average carbon uptake period lasting 165 days. Photosynthetically active radiation showed a negative correlation with daily NEE, contributing to carbon absorption of grasslands. The optimal threshold for capturing SCUP was a 10% threshold of the red-edge chlorophyll index, while the normalized difference vegetation index effectively reflected ECUP with a threshold of 75%. These findings would provide a basis for remote sensing monitoring of grassland carbon source-sink dynamics.

Synchronized slowdown of climate warming and carbon sink enhancement over deciduous broadleaf forests based on FLUXNET analysis

The temperate deciduous broadleaf forests (DBFs) are widely distributed in middle and high latitudes and play vital role in providing ecosystem services and mitigating human induced climate change, however, the responses of the carbon sink of DBFs to recent warming slowdown were not well known at regional scale. Here, we investigated the temporal pattern of carbon sink in DBFs and its drivers based on the eddy covariance carbon flux observations at 15 FLUXNET sites from 1997 to 2014. The annual mean net ecosystem production (NEP) was 272 ± 43 g C m−2 yr−1 during 1997–2005 and it increased to 445 ± 13 g C m−2 yr−1 during 2006–2014, as a result of boosted gross primary production (GPP) and weakened ecosystem respiration, respectively. We found slowdown in trends of temperature and carbon sink enhancement during 2006–2014. The NEP decreased at the rate of −11.9 g C m−2 yr−1 during the warming slowdown period (2006–2014, p < 0.05) compared to a prior strong increased trend during the warming period (1997–2005, 47.6 g C m−2 yr−1, p < 0.05). The mean annual temperature dominated the inter-annual variation of NEP (46.9 %), and it worked together with seasonal water availability to control the NEP changes. The slowdown of peak photosynthesis growth rate and carbon uptake period (CUP) extension may contribute to the NEP reversal during the later period. Our results demonstrated that the carbon uptake potential of temperate DBFs may highly depend on warming trends.

An Earlier Spring Phenology Reduces Vegetation Growth Rate during the Green-Up Period in Temperate Forests

Climatic warming advances the start of the growing season (SOS) and sequentially enhances the vegetation productivity of temperate forests by extending the carbon uptake period and/or increasing the growth rate. Recent research indicates that the vegetation growth rate is a main driver for the interannual changes in vegetation carbon uptake; however, the specific effects of an earlier SOS on vegetation growth rate and the underlying mechanisms are still unclear. Using 268 year-site PhenoCam observations in temperate forests, we found that an earlier SOS reduced the vegetation growth rate and mean air temperature during the green-up period (i.e., from the SOS to the peak of the growing period), but increased the accumulation of shortwave radiation during the green-up period. Interestingly, an earlier-SOS-induced reduction in the growth rate was weakened in the highly humid areas (aridity index ≥ 1) when compared with that in the humid areas (aridity index &lt; 1), suggesting that an earlier-SOS-induced reduction in the growth rate in temperate forests may intensify with the ongoing global warming and aridity in the future. The structural equation model analyses indicated that an earlier-SOS-induced decrease in the temperature and increase in shortwave radiation drove a low vegetation growth rate. Our findings highlight that the productivity of temperate forests may be overestimated if the negative effect of an earlier SOS on the vegetation growth rate is ignored.

Reducing errors on estimates of the carbon uptake period based on time series of atmospheric CO2

Abstract. High-quality, long-time-series measurements of atmospheric greenhouse gases show interannual variability in the measured seasonal cycles. These changes can be analyzed to better understand the carbon cycle and the impact of climate drivers. However, nearly all discrete measurement records contain gaps and have noise due to the influence of local fluxes or synoptic variability. To facilitate analysis, filtering and curve-fitting techniques are often applied to these time series. Previous studies have recognized that there is an inherent uncertainty associated with this curve fitting, and the choice of a given mathematical method might introduce biases. Since uncertainties are seldom propagated to the metrics under study, this can lead to misinterpretation of the signal. In this study, we use an ensemble-based approach to quantify the uncertainty of the derived seasonal cycle metrics. We apply it to CO2 dry-air mole fraction time series from flask measurements in the Northern Hemisphere. We use this ensemble-based approach to analyze the carbon uptake period (CUP: the time of the year when the CO2 uptake is greater than the CO2 release): its onset, termination and duration. Previous studies have diagnosed CUP based on the dates on which the detrended, zero-centered seasonal cycle curve switches from positive to negative (the downward zero-crossing date, DZCD) and vice versa (upward zero-crossing date, UZCD). However, the UZCD is sensitive to the skewness of the CO2 seasonal cycle during the net carbon release period. Hence, we develop an alternative method proposed by Barlow et al. (2015) to estimate the onset and termination of the CUP based on a threshold defined in terms of the first derivative of the CO2 seasonal cycle. Using the ensemble approach, we arrive at a tighter constraint to the threshold by considering the annual uncertainty; we call this the ensemble of first derivative (EFD) method. Further, using the EFD approach and an additional curve-fitting algorithm, we show that (a) the uncertainty of the studied metrics is smaller using the EFD method than when approximated using the timing of the zero-crossing date (ZCD), and (b) the onset and termination dates derived with the EFD method provide more robust results, irrespective of the curve-fitting method applied to the data.

On the temporal mismatch between in-situ and satellite-derived spring phenology of European beech forests

ABSTRACT Forest phenology plays a key role in the global terrestrial ecosystem influencing a range of ecosystem processes such as the annual carbon uptake period, and many food webs and changes in their timing and progression. The timing of the start of the phenology season has been successfully determined at a range of scales, from the individual tree by in situ observations to landscape and continental scales by using remotely sensed vegetation indices (VIs). The spatial resolution of satellites is much coarser than traditional methods, creating a gap between space-borne and actual field observations, which brings limitations to phenological research at the ecosystem level. Several unconsidered methodological and observational-related limitations may lead to misinterpretation of the timing of the satellite-derived signals. The aim of this study is therefore to clarify the meaning of a set of spring phenology metrics derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) time series in beech forests distributed across Europe with respect to PEP725 in situ observations, from 2003 to 2020. To this aim, we (i) tested the differences between remotely sensed and in situ start-of-season (SOS) metrics and (ii) quantified the influence of latitude, elevation, temperature, and precipitation on such differences. Results demonstrated that there is a clear temporal gradient among the different SOS metrics, all of them occurring prior to the in situ observations. Furthermore, latitude and temperatures proved to be the main factors guiding the differences between remotely sensed and in situ SOS metrics. Evidence from this study may help in recognizing the actual meaning of what we see by means of remotely sensed phenology metrics. In this perspective, field observations are crucial in understanding phenology events and provide a reference base. Satellite data, on the other hand, complement field observations by filling in gaps in spatial and temporal coverage, thus enhancing the overall understanding.

Joint control of alpine meadow productivity by plant phenology and photosynthetic capacity

Under global climate change, climate warming and changing precipitation patterns would greatly affect plant phenology and photosynthetic capacity and hence affect the gross primary productivity (GPP) of the sensitive alpine meadow. To deeply understand the variations in GPP, it is important to clarify the joint effects of plant phenology and photosynthetic capacity. In this study, 10-year continuous flux and microclimatic data and in situ phenology period observation data were used to explore the roles of growing season length (GSL) and the seasonal maximal capacity of carbon uptake (GPPmax) on annual cumulative gross primary productivity (GPPann). The results indicated that the temperature and water conditions, especially water conditions, dominated GSL and GPPmax and hence determined GPPann. Both GSL and GPPmax were dominated by annual precipitation, and the soil water content in August also showed a strong influence over them. GSL and GPPmax together could explain 87% of the variation in GPPann. Compared with GSL, GPPmax had stronger effects on the interannual variability (IAV) in GPPann. This study provides a new perspective on clarifying the proximate causes of IAV in GPPann. The IAV in GPPann of alpine ecosystems could be determined by these two key underlying processes, the length of the carbon uptake period and amplitude. These results are of critical importance for improving our ability to predict future changes in alpine meadow ecosystems.

Disentangling carbon uptake and allocation in the stems of a spruce forest

Although forests store significant amounts of carbon in tree stems, the extent to which stem growth depends on carbon assimilation and environmental factors is poorly understood. In this study, gross primary productivity (GPP) and net ecosystem productivity (NEP) are compared for the first time at daily resolution with stem carbon allocation (SCA) in a spruce forest. We found substantial differences in the seasonal patterns of all variables as a function of environmental conditions, leading to three important findings. First, carbon uptake was only marginally invested in wood growth during the first half of the growing season. This means that there were other priorities for carbon allocation than stem growth at this time of year. Second, our results show that SRI at the beginning of the stem growth period, which mainly involves cell division and expansion, is a process that requires less carbon than the process of xylem lignification and thickening that follows. And third, NEP was generally less sensitive to drought than SCA. This suggests that the carbon uptake balance is less sensitive to dry periods than growth, particularly because the carbon uptake period is much longer than the growth window. These results may change the way we perceive the effects of climate change on forests, as tree carbon dynamics are primarily explained by the seasonal timing of dry periods rather than the intensity of these events. • Novel daily-resolved stem carbon allocation data of spruce trees. • Carbon uptake and allocation are partially decoupled. • Drought limits stem growth of spruce before carbon uptake is affected. • Timing of extreme events determines the impact on the carbon balance of forests. • Spruce trees increasingly suffer under drought stress.

Does growing atmospheric CO2 explain increasing carbon sink in a boreal coniferous forest?

The terrestrial net ecosystem productivity (NEP) has increased during the past three decades, but the mechanisms responsible are still unclear. We analyzed 17 years (2001–2017) of eddy‐covariance measurements of NEP, evapotranspiration (ET) and light and water use efficiency from a boreal coniferous forest in Southern Finland for trends and inter‐annual variability (IAV). The forest was a mean annual carbon sink (252 [±42] gC m‐2 a‐1), and NEP increased at rate +6.4–7.0 gC m‐2 a‐1 (or ca. +2.5% a‐1) during the period. This was attributed to the increasing gross‐primary productivity GPP and occurred without detectable change in ET. The start of annual carbon uptake period was advanced by 0.7 d a‐1, and increase in GPP and NEP outside the main growing season contributed ca. one‐third and one‐fourth of the annual trend, respectively. Meteorological factors were responsible for the IAV of fluxes but did not explain the long‐term trends. The growing season GPP trend was strongest in ample light during the peak growing season. Using a multi‐layer ecosystem model, we showed that direct CO2 fertilization effect diminishes when moving from leaf to ecosystem, and only 30–40% of the observed ecosystem GPP increase could be attributed to CO2. The increasing trend in leaf‐area index (LAI), stimulated by forest thinning in 2002, was the main driver of the enhanced GPP and NEP of the mid‐rotation managed forest. It also compensated for the decrease of mean leaf stomatal conductance with increasing CO2 and LAI, explaining the apparent proportionality between observed GPP and CO2 trends. The results emphasize that attributing trends to their physical and physiological drivers is challenged by strong IAV, and uncertainty of LAI and species composition changes due to the dynamic flux footprint. The results enlighten the underlying mechanisms responsible for the increasing terrestrial carbon uptake in the boreal zone.

Comparing in situ spring phenology and satellite-derived start of season at rural and urban sites in Ireland

ABSTRACT The timing of spring phenology marks the start of the growing season and the beginning of the carbon-uptake period. In order to accurately calculate carbon budgets across different vegetation types, reliable start-of-season data over relatively large areas is necessary. However, in-situ phenological observation networks are generally restricted in their geographical extent and limited to a small number of species, typically dominant trees. Satellite remote sensing can provide spatially extensive phenological information but requires validation with in-situ observations. Here, we examined trends (1968–2016) in the timing of leaf-unfolding (LU) as well as growing-season-length (GSL), derived from in-situ observations, of a suite of deciduous trees, at three rural sites and one urban site in Ireland, all of which are within the International Phenological Gardens network. We compared in-situ trends with satellite derived phenometrics, including start of greening increase and GSL, based on two-band Enhanced Vegetation Index (EVI2) from a combined AVHRR and MODIS time-series over the time period 1982–2016. The aim of this study was to assess the effectiveness of satellite remote sensing in capturing LU and GSL as determined by in-situ observations from sites dominated by varying land cover types. The timing of LU (DOY 111) at the urban site was significantly (p < 0.000) later than all rural sites, apart from one (1982–2016). The significantly (p < 0.000) longer (2–5 weeks) GSL (217 days), at the urban site, was thus driven by delayed leaf fall (LF). Satellite derived Start of Season (SOS) was consistently earlier than LU across all sites (RMSE 25–52d; MBE −5 to −50 d) whereas EVI2-derived GSL was consistently longer than in situ data (RMSE 65–102d; MBE 45 to 96 d). Overall, the discrepancies reported here between the timing of in-situ spring phenology and satellite-derived phenometrics at these sites were possibly due to a combination of factors including differences in scale between the two methods, the small number of cloned trees being monitored, which does not appear to represent the broader landscape vegetation, the heterogeneity of the landscape and technical differences between the satellite sensors used to construct the EVI2 time-series. Addressing these issues is challenging but engaging citizen scientists to monitor local vegetation would increase the spatial coverage of the in-situ observation network while also incorporating a broader range of species some of which would undoubtedly represent native vegetation.

Functional traits predict tree‐level phenological strategies in a mesic Indian savanna

AbstractLeaf phenology influences terrestrial primary production by determining the period of carbon uptake. While dominant leaf habit (evergreen/deciduous) is predictable at large scales based on environmental factors, there is substantial variability in the timing of key events such as leaf flush and senescence at smaller site‐level scales. How much of this variability is explained by species functional traits related to a plant's carbon economy? We monitored leaf phenology for 113 individual trees of eleven dominant species in an Indian mesic savanna. Specifically, we related leaf functional traits and wood density to the (i) timing of leaf flush, leaf maturity, peak canopy, and senescence, (ii) duration of leaf deployment, (iii) duration from start of senescence to leaflessness, and (iv) time to attainment of peak mature canopy following leaf flush. We expected species that use resources conservatively (low specific leaf area (SLA), high leaf dry matter content, low leaf nitrogen, and high wood density) to senesce later and retain their leaves longer. For all species, leaflessness was most pronounced in early dry season and leaf flushing occurred in the late dry season. Species with high leaf carbon and dry matter content showed earlier leaf maturation, attained peak mature canopies sooner, and deployed leaves longer. Species with high SLA, leaf nitrogen, and low wood density showed earlier senescence but relationships were weak. In this savanna, phenology at fine scales was indeed associated with species functional traits relating to carbon investment, but these relationships were strong only when intra‐specific variation in phenology was low.

Autumn Warming Delays the Downregulation of Photosynthesis and Does Not Increase the Risk of Freezing Damage in Interior and Coastal Douglas-fir

During autumn, evergreen conifers utilize the decrease in daylength and temperature as environmental signals to trigger cold acclimation, a process that involves the downregulation of photosynthesis, upregulation of photoprotection, and development of cold hardiness. Global warming will delay the occurrence of autumn low temperatures while daylength remains unaffected. The impact of autumn warming on cold acclimation and the length of the carbon uptake period of species with ranges that encompass diverse climates, such as Douglas-fir (Pseudotsuga menziesii), remains unclear. Our study investigated intraspecific variation in the effects of autumn warming on photosynthetic activity, photosynthetic pigments, and freezing tolerance in two interior (var. glauca) and two coastal (var. menziesii) Douglas-fir provenances. Following growth under simulated summer conditions with long days (16 h photoperiod) and summer temperatures (22/13°C day/night), Douglas-fir seedlings were acclimated to simulated autumn conditions with short days (8 h photoperiod) and either low temperatures (cool autumn, CA; 4/−4°C day/night) or elevated temperatures (warm autumn, WA; 19/11°C day/night). Exposure to low temperatures in the CA treatment induced the downregulation of photosynthetic carbon assimilation and photosystem II efficiency, increased the size and de-epoxidation of the xanthophyll cycle pigment pool, and caused the development of sustained nonphotochemical quenching (NPQ). Seedlings in the WA treatment exhibited no downregulation of photosynthesis, no change in xanthophyll cycle pigment de-epoxidation, and no development of sustained NPQ. Albeit these changes, freezing tolerance was not impaired under WA conditions compared with CA conditions. Interior Douglas-fir seedlings developed greater freezing tolerance than coastal seedlings. Our findings suggest that autumn warming, i.e., short photoperiod alone, does not induce the downregulation of photosynthesis in Douglas-fir. Although autumn warming delays the downregulation of photosynthesis, the prolonged period of photosynthetic activity does not bear a trade-off of impaired freezing tolerance.

Increasing temperature shortened the carbon uptake period and decreased the cumulative net ecosystem productivity in a maize cropland in Northeast China

• Carbon uptake period (CUP) was mainly determined by the end date of CUP in autumn. • NEP max explained greater interannual variation in cumulative NEP than CUP. • Both start and end dates of CUP were advanced with increasing winter temperature. • NEP max decreased with increasing precipitation in summer and autumn. • CUP tended to shorten with increasing temperature, thus decreasing cumulative NEP. Phenology—mainly associated with climatic factors—is crucial for the accurate estimation of cumulative annual carbon exchange between terrestrial ecosystems and the atmosphere. However, the effects of changes in phenology on annual vegetation productivity and its regulatory mechanisms remain unclear, particularly in agricultural ecosystems. Therefore, in this study, we examined the associations among cumulative net ecosystem productivity (NEP), phenological metrics, and climatic factors based on long-term (2005–2014) eddy covariance flux and meteorological observations in a maize cropland in Northeast China. The results showed that carbon uptake period (CUP) was mainly determined by the end date of CUP (ECUP) in autumn. Cumulative NEP from May to September (NEP 5−9 ), a period generally corresponding to the growing season, significantly increased with NEP max (defined in this study as the 90th percentile of daily NEP during CUP) and CUP. NEP max explained greater interannual variation in NEP 5−9 than CUP. The start date of CUP (SCUP) and ECUP were both advanced with increasing winter temperature, but ECUP was more temperature-sensitive than SCUP. Thus, CUP tended to shorten with increasing temperature, ultimately decreasing cumulative NEP. In addition, NEP max decreased with increasing precipitation in summer and autumn. The Greenup and MidGreendown dates from the MODIS Global Vegetation Phenology (MCD12Q2) product generally captured the interannual variation in the carbon flux-based SCUP and ECUP, respectively, well. The results of this study would be of great significance for predicting the response of ecosystem productivity to plant phenology shifts in agricultural ecosystems in future climate change scenarios.

Patterns and trends of the dominant environmental controls of net biome productivity

Abstract. In the last decades terrestrial ecosystems have reabsorbed on average more than one-quarter of anthropogenic emissions (Le Quéré et al., 2018). However, this large carbon sink is modulated by climate and is therefore highly variable in time and space. The magnitude and temporal changes in the sensitivity of terrestrial CO2 fluxes to climate drivers are key factors to determine future atmospheric CO2 concentration and climate trajectories. In the literature, there is so far a strong focus on the climatic controls of daily and long-term variability, while less is known about the key drivers at a seasonal timescale and about their variation over time (Wohlfahrt et al., 2008). This latter temporal scale is relevant to assess which climatic drivers dominate the seasonality of the fluxes and to understand which factors limit the CO2 exchange during the course of the year. Here, we investigate the global sensitivity of net terrestrial CO2 fluxes, derived from atmospheric inversion, to three key climate drivers (i.e. global radiation and temperature from WFDEI and soil water content from ERA-Interim) from weekly to seasonal temporal scales, in order to explore the short-term interdependence between climate and the terrestrial carbon budget. We observed that the CO2 exchange is controlled by temperature during the carbon uptake period over most of the land surface (from 55 % to 52 % of the total surface), while radiation is the most widespread dominant climate driver during the carbon release period (from 64 % to 70 % of the total surface). As expected, soil water content plays a key role in arid regions of the Southern Hemisphere during both the carbon uptake and the carbon release period. Looking at the decadal trend of these sensitivities (1985–2016) we observed that the importance of radiation as a driver is increasing over time, while we observed a decrease in sensitivity to temperature in Eurasia. Overall, we show that flux temporal variation due to a specific driver has been dominated by the temporal changes in ecosystem sensitivity (i.e. the response of ecosystem to climate) rather than to the temporal variability of the climate driver itself over the last decades. Ultimately, this analysis shows that the ecosystem response to climate is significantly changing both in space and in time, with potential repercussion on the future terrestrial CO2 sink and therefore on the role that land may play in climate trajectories.

Spatial patterns and climate controls of seasonal variations in carbon fluxes in China's terrestrial ecosystems

Abstract Seasonal changes in CO2 exchange determine the strength and dynamics of the carbon budget in terrestrial ecosystems. Knowledge about seasonal and spatial variations in carbon fluxes (net ecosystem productivity (NEP), gross primary productivity (GPP), and ecosystem respiration (RE)) is thus essential to support accurate modeling of carbon flux dynamics. To the best of our knowledge, this study represents the first comprehensive evaluation of how carbon fluxes vary seasonally in different ecoregions in China. Using eddy covariance measurements from ChinaFLUX, we analyzed the spatial variations and climate controls of the phenological and physiological properties of NEP, GPP, and RE across China. Apart from the beginning and ending day of NEP (net carbon uptake), the phenological properties of the carbon fluxes varied significantly with latitude; however, there were no evident trends in the physiological properties of the carbon fluxes with latitude (apart from the annual values of GPP and RE, known as AGPP and ARE). The spatial variation in the physiological properties of GPP and RE was influenced by the precipitation patterns, while the spatial distribution of the phenological properties of GPP and RE was related to air temperature. Moreover, the spatial variation for the end of the growing season changed with the autumn mean soil temperatures. The factors that contributed to the spatial distribution in the annual NEP (ANEP) and annual GPP and RE (AGPP and ARE) were quite different. The mean daily GPP and RE were the main contributors to the spatial variations in AGPP and ARE, while the net carbon uptake period was the main contributor to the spatial variation in ANEP. In this study, we identified a series of ecological parameters and reference values for seasonal patterns that can be used to validate models that simulate changes in regional carbon fluxes.