Anomalous wet summers and rising atmospheric CO2 concentrations increase the CO2 sink in a poorly drained forest on permafrost.

At the northern high latitudes, rapid warming, associated changes in the hydrological cycle, and rising atmospheric CO2 concentrations, [CO2], are observed at present. Under rapid environmental changes, it is important to understand the current and future trajectories of the CO2 budget in high-latitude ecosystems. In this study, we present the importance of anomalous wet conditions and rising [CO2] on the long-term CO2 budget based on two decades (2003-2022) of quasicontinuous measurements of CO2 flux at a poorly drained black spruce forest on permafrost peat in interior Alaska. The long-term CO2 budget for the black spruce forest was a small sink of -53 ± 63 g C m-2 y-1. The CO2 sink increased from 49 g C m-2 y-1 for the first decade to 58 g C m-2 y-1 for the second decade. The increased CO2 sink was attributed to an 11.3% increase in gross primary productivity (GPP) among which 9% increase in GPP was explained by a recent increase in precipitation. Furthermore, a 3% increase in GPP in response to a 37-ppm increase in [CO2] was estimated from the data-model fusion. Our study shows that understanding the coupling between hydrological and carbon cycles and the CO2 fertilization effect is important for understanding the current and future carbon budgets of high-latitude ecosystems in permafrost regions.

CO2 fertilization of terrestrial photosynthesis inferred from site to global scales.

SignificanceThe magnitude of the CO2 fertilization effect on terrestrial photosynthesis is uncertain because it is not directly observed and is subject to confounding effects of climatic variability. We apply three well-established eco-evolutionary optimality theories of gas exchange and photosynthesis, constraining the main processes of CO2 fertilization using measurable variables. Using this framework, we provide robust observationally inferred evidence that a strong CO2 fertilization effect is detectable in globally distributed eddy covariance networks. Applying our method to upscale photosynthesis globally, we find that the magnitude of the CO2 fertilization effect is comparable to its in situ counterpart but highlight the potential for substantial underestimation of this effect in tropical forests for many reflectance-based satellite photosynthesis products.

Optimality principles explaining divergent responses of alpine vegetation to environmental change.

Recent increases in vegetation greenness over much of the world reflect increasing CO2 globally and warming in cold areas. However, the strength of the response to both CO2 and warming in those areas appears to be declining for unclear reasons, contributing to large uncertainties in predicting how vegetation will respond to future global changes. Here, we investigated the changes of satellite-observed peak season absorbed photosynthetically active radiation (Fmax ) on the Tibetan Plateau between 1982 and 2016. Although climate trends are similar across the Plateau, we identified robust divergent responses (a greening of 0.31 ± 0.14% year-1 in drier regions and a browning of 0.12 ± 0.08% year-1 in wetter regions). Using an eco-evolutionary optimality (EEO) concept of plant acclimation/adaptation, we propose a parsimonious modelling framework that quantitatively explains these changes in terms of water and energy limitations. Our model captured the variations in Fmax with a correlation coefficient (r) of .76 and a root mean squared error of .12 and predicted the divergent trends of greening (0.32 ± 0.19% year-1 ) and browning (0.07 ± 0.06% year-1 ). We also predicted the observed reduced sensitivities of Fmax to precipitation and temperature. The model allows us to explain these changes: Enhanced growing season cumulative radiation has opposite effects on water use and energy uptake. Increased precipitation has an overwhelmingly positive effect in drier regions, whereas warming reduces Fmax in wetter regions by increasing the cost of building and maintaining leaf area. Rising CO2 stimulates vegetation growth by enhancing water-use efficiency, but its effect on photosynthesis saturates. The large decrease in the sensitivity of vegetation to climate reflects a shift from water to energy limitation. Our study demonstrates the potential of EEO approaches to reveal the mechanisms underlying recent trends in vegetation greenness and provides further insight into the response of alpine ecosystems to ongoing climate change.

Greening drylands despite warming consistent with carbon dioxide fertilization effect.

The rising atmospheric CO2 concentration leads to a CO2 fertilization effect on plants-that is, increased photosynthetic uptake of CO2 by leaves and enhanced water-use efficiency (WUE). Yet, the resulting net impact of CO2 fertilization on plant growth and soil moisture (SM) savings at large scale is poorly understood. Drylands provide a natural experimental setting to detect the CO2 fertilization effect on plant growth since foliage amount, plant water-use and photosynthesis are all tightly coupled in water-limited ecosystems. A long-term change in the response of leaf area index (LAI, a measure of foliage amount) to changes in SM is likely to stem from changing water demand of primary productivity in water-limited ecosystems and is a proxy for changes in WUE. Using 34-year satellite observations of LAI and SM over tropical and subtropical drylands, we identify that a 1% increment in SM leads to 0.15% (±0.008, 95% confidence interval) and 0.51% (±0.01, 95% confidence interval) increments in LAI during 1982-1998 and 1999-2015, respectively. The increasing response of LAI to SM has contributed 7.2% (±3.0%, 95% confidence interval) to total dryland greening during 1999-2015 compared to 1982-1998. The increasing response of LAI to SM is consistent with the CO2 fertilization effect on WUE in water-limited ecosystems, indicating that a given amount of SM has sustained greater amounts of photosynthetic foliage over time. The LAI responses to changes in SM from seven dynamic global vegetation models are not always consistent with observations, highlighting the need for improved process knowledge of terrestrial ecosystem responses to rising atmospheric CO2 concentration.

Tree rings provide no evidence of a CO2 fertilization effect in old-growth subalpine forests of western Canada.

Atmospheric CO2 concentrations are now 1.7 times higher than the preindustrial values. Although photosynthetic rates are hypothesized to increase in response to rising atmospheric CO2 concentrations, results from in situ experiments are inconsistent in supporting a CO2 fertilization effect of tree growth. Tree-ring data provide a historical record of tree-level productivity that can be used to evaluate long-term responses of tree growth. We use tree-ring data from old-growth, subalpine forests of western Canada that have not had a stand-replacing disturbance for hundreds of years to determine if growth has increased over 19th and 20th centuries. Our sample consisted of 5,858 trees belonging to five species distributed over two sites in the coastal zone and two in the continental climate of the interior. We calculated annual increments in tree basal area, adjusted these increments for tree size and age, and tested whether there was a detectable temporal trend in tree growth over the 19th and 20th centuries. We found a similar pattern in 20th century growth trends among all species at all sites. Growth during the 19th century was mostly stable or increasing, with the exception of one of the coastal sites, where tree growth was slightly decreasing; whereas growth during the 20th century consistently decreased. The unexpected decrease in growth during the 20th century indicates that there was no CO2 fertilization effect on photosynthesis. We compared the growth trends from our four sites to the trends simulated by seven Earth System Models, and saw that most of the models did not predict these growth declines. Overall, our results indicate that these old-growth forests are unlikely to increase their carbon storage capacity in response to rising atmospheric CO2 , and thus are unlikely to contribute substantially to offsetting future carbon emissions.

On the causes of trends in the seasonal amplitude of atmospheric CO2.

No consensus has yet been reached on the major factors driving the observed increase in the seasonal amplitude of atmospheric CO2 in the northern latitudes. In this study, we used atmospheric CO2 records from 26 northern hemisphere stations with a temporal coverage longer than 15 years, and an atmospheric transport model prescribed with net biome productivity (NBP) from an ensemble of nine terrestrial ecosystem models, to attribute change in the seasonal amplitude of atmospheric CO2 . We found significant (p < .05) increases in seasonal peak-to-trough CO2 amplitude (AMPP-T ) at nine stations, and in trough-to-peak amplitude (AMPT-P ) at eight stations over the last three decades. Most of the stations that recorded increasing amplitudes are in Arctic and boreal regions (>50°N), consistent with previous observations that the amplitude increased faster at Barrow (Arctic) than at Mauna Loa (subtropics). The multi-model ensemble mean (MMEM) shows that the response of ecosystem carbon cycling to rising CO2 concentration (eCO2 ) and climate change are dominant drivers of the increase in AMPP-T and AMPT-P in the high latitudes. At the Barrow station, the observed increase of AMPP-T and AMPT-P over the last 33 years is explained by eCO2 (39% and 42%) almost equally than by climate change (32% and 35%). The increased carbon losses during the months with a net carbon release in response to eCO2 are associated with higher ecosystem respiration due to the increase in carbon storage caused by eCO2 during carbon uptake period. Air-sea CO2 fluxes (10% for AMPP-T and 11% for AMPT-P ) and the impacts of land-use change (marginally significant 3% for AMPP-T and 4% for AMPT-P ) also contributed to the CO2 measured at Barrow, highlighting the role of these factors in regulating seasonal changes in the global carbon cycle.

Detection and attribution of vegetation greening trend in China over the last 30 years.

The reliable detection and attribution of changes in vegetation growth is a prerequisite for the development of strategies for the sustainable management of ecosystems. This is an extraordinary challenge. To our knowledge, this study is the first to comprehensively detect and attribute a greening trend in China over the last three decades. We use three different satellite-derived Leaf Area Index (LAI) datasets for detection as well as five different process-based ecosystem models for attribution. Rising atmospheric CO2 concentration and nitrogen deposition are identified as the most likely causes of the greening trend in China, explaining 85% and 41% of the average growing-season LAI trend (LAIGS) estimated by satellite datasets (average trend of 0.0070 yr(-1), ranging from 0.0035 yr(-1) to 0.0127 yr(-1)), respectively. The contribution of nitrogen deposition is more clearly seen in southern China than in the north of the country. Models disagree about the contribution of climate change alone to the trend in LAIGS at the country scale (one model shows a significant increasing trend, whereas two others show significant decreasing trends). However, the models generally agree on the negative impacts of climate change in north China and Inner Mongolia and the positive impact in the Qinghai-Xizang plateau. Provincial forest area change tends to be significantly correlated with the trend of LAIGS (P < 0.05), and marginally significantly (P = 0.07) correlated with the residual of LAIGS trend, calculated as the trend observed by satellite minus that estimated by models through considering the effects of climate change, rising CO2 concentration and nitrogen deposition, across different provinces. This result highlights the important role of China's afforestation program in explaining the spatial patterns of trend in vegetation growth.

Projected decline in the strength of vegetation carbon sequestration under climate change in India.

Tropical vegetation plays a critical role in terrestrial carbon budget and supply many ecological functions such as carbon sequestration. In recent decades, India has witnessed an increase in net primary productivity (NPP), an important measure of carbon sequestration. However, uncertainties persist regarding the sustainability of these land carbon sinks in the face of climate change. The enhanced NPP is driven by the strong CO2 fertilization effect (CFE), but the temporal patterns of this feedback remain unclear. Using the carbon flux data from the Earth System Models (ESMs), an increasing trend in NPP was observed, with projections of NPP to 2.00 ± 0.12 PgCyr-1 (25 % increase) during 2021-2049, 2.36 ± 0.12 PgCyr-1 (18 % increase) during 2050-2079, and 2.67 ± 0.07 PgCyr-1 (13 % increase) during 2080-2099 in Indian vegetation under SSP585 scenario. This suggests a significant decline in the NPP growth rate. To understand the feedback mechanisms driving NPP, the relative effects of CFE and warming were analyzed. Comparing simulations from the biogeochemically coupled model (BGC) with the fully coupled model, the BGC model projected a 74.7 % increase in NPP, significantly higher than the 55.9 % increase projected by the fully coupled model by the end of the century. This indicates that the consistent increase in NPP was associated with CO2 fertilization. More importantly, results reveal that the decrease in the NPP growth rate was due to the declining contribution of CFE at a rate of -0.62 % per 100 ppm CO2 increase. This decline could be attributed to factors such as nutrient limitations and high temperatures. Additionally, significant shifts in the strength of carbon sinks in offsetting the CO2 emissions were identified, decreasing at a rate of -1.15 % per decade. This decline in the strength of vegetation carbon sequestration may increase the societal dependence on mitigation measures to address climate change.

Declining tree growth rates despite increasing water-use efficiency under elevated CO2 reveals a possible global overestimation of CO2 fertilization effect.

Though rising atmospheric CO2 concentrations (Ca) harm the environment and society, they may also raise photosynthetic rates and enhance intrinsic water-use efficiency (iWUE). Numerous short-term studies have investigated tree growth under elevated CO2 (eCO2) conditions, but no long-duration study has investigated eCO2 impacts on tree growth and iWUE under natural conditions. Utilizing a new dendrochronological experimental design in a heavily-touristed nature preserve in Southwest China (Jiuzhaigou National Nature Reserve), we compared tree growth (e.g., basal area increment) and iWUE in two biophysically and environmentally similar valleys with contrasting anthropogenic activities. Trees in the control valley with ambient CO2 benefited from increasing Ca, possibly due to the CO2 fertilization effect and optimal environmental conditions. However, trees in the treatment valley with intensive tourism experienced comparatively higher localized eCO2 and growth rate declines. While iWUE increased (1959-2017) in the control (25.3%) and treatment sites (47.8%), declining tree growth rates in the treatment site was likely because comparatively extreme CO2 exposure levels encouraged stomatal closures. As the first long-term study investigating eCO2 impacts on tree growth and iWUE under natural conditions, we demonstrate that increased forest iWUE is unlikely to overcome negative drought stress and rising temperature impacts. Thus, forest potential for mitigating eCO2 and global climate change is likely overestimated, particularly under dry temperate conditions.

Water Deficit Modulates the CO2 Fertilization Effect on Plant Gas Exchange and Leaf-Level Water Use Efficiency: A Meta-Analysis.

Elevated atmospheric CO2 concentrations ([eCO2]) and soil water deficits significantly influence gas exchange in plant leaves, affecting the carbon-water cycle in terrestrial ecosystems. However, it remains unclear how the soil water deficit modulates the plant CO2 fertilization effect, especially for gas exchange and leaf-level water use efficiency (WUE). Here, we synthesized a comprehensive dataset including 554 observations from 54 individual studies and quantified the responses for leaf gas exchange induced by e[CO2] under water deficit. Moreover, we investigated the contribution of plant net photosynthesis rate (P n ) and transpiration rates (T r) toward WUE in water deficit conditions and e[CO2] using graphical vector analysis (GVA). In summary, e[CO2] significantly increased P n and WUE by 11.9 and 29.3% under well-watered conditions, respectively, whereas the interaction of water deficit and e[CO2] slightly decreased P n by 8.3%. Plants grown under light in an open environment were stimulated to a greater degree compared with plants grown under a lamp in a closed environment. Meanwhile, water deficit reduced P n by 40.5 and 37.8%, while increasing WUE by 24.5 and 21.5% under ambient CO2 concentration (a[CO2]) and e[CO2], respectively. The e[CO2]-induced stimulation of WUE was attributed to the common effect of P n and T r, whereas a water deficit induced increase in WUE was linked to the decrease in T r. These results suggested that water deficit lowered the stimulation of e[CO2] induced in plants. Therefore, fumigation conditions that closely mimic field conditions and multi-factorial experiments such as water availability are needed to predict the response of plants to future climate change.

Evaluating and comparing remote sensing terrestrial GPP models for their response to climate variability and CO2 trends.

Remote sensing (RS)-based models play an important role in estimating and monitoring terrestrial ecosystem gross primary productivity (GPP). Several RS-based GPP models have been developed using different criteria, yet the sensitivities to environmental factors vary among models; thus, a comparison of model sensitivity is necessary for analyzing and interpreting results and for choosing suitable models. In this study, we globally evaluated and compared the sensitivities of 14 RS-based models (2 process-, 4 vegetation-index-, 5 light-use-efficiency, and 3 machine-learning-based models) and benchmarked them against GPP responses to climatic factors measured at flux sites and to elevated CO2 concentrations measured at free-air CO2 enrichment experiment sites. The results demonstrated that the models with relatively high sensitivity to increasing atmospheric CO2 concentrations showed a higher increasing GPP trend. The fundamental difference in the CO2 effect in the models' algorithm either considers the effect of CO2 through changes in greenness indices (nine models) or introduces the influences on photosynthesis (three models). The overall effects of temperature and radiation, in terms of both magnitude and sign, vary among the models, while the models respond relatively consistently to variations in precipitation. Spatially, larger differences among model sensitivity to climatic factors occur in the tropics; at high latitudes, models have a consistent and obvious positive response to variations in temperature and radiation, and precipitation significantly enhances the GPP in mid-latitudes. Compared with the results calculated by flux-site measurements, the model performance differed substantially among different sites. However, the sensitivities of most models are basically within the confidence interval of the flux-site results. In general, the comparison revealed that models differed substantially in the effect of environmental regulations, particularly CO2 fertilization and water stress, on GPP, and none of the models performed consistently better across the different ecosystems and under the various external conditions.

The optimal atmospheric CO2 concentration for the growth of winter wheat (Triticum aestivum).

This study examined the optimal atmospheric CO2 concentration of the CO2 fertilization effect on the growth of winter wheat with growth chambers where the CO2 concentration was controlled at 400, 600, 800, 1000, and 1200 ppm respectively. I found that initial increase in atmospheric CO2 concentration dramatically enhanced winter wheat growth through the CO2 fertilization effect. However, this CO2 fertilization effect was substantially compromised with further increase in CO2 concentration, demonstrating an optimal CO2 concentration of 889.6, 909.4, and 894.2 ppm for aboveground, belowground, and total biomass, respectively, and 967.8 ppm for leaf photosynthesis. Also, high CO2 concentrations exceeding the optima not only reduced leaf stomatal density, length and conductance, but also changed the spatial distribution pattern of stomata on leaves. In addition, high CO2 concentration also decreased the maximum carboxylation rate (Vc(max)) and the maximum electron transport rate (J(max)) of leaf photosynthesis. However, the high CO2 concentration had little effect on leaf length and plant height. The optimal CO2 fertilization effect found in this study can be used as an indicator in selecting and breeding new wheat strains in adapting to future high atmospheric CO2 concentrations and climate change.