Forest Gross Primary Production Research Articles

Mutual inhibition effects of elevated CO2 and climate change on global forest GPP

The impact of CO2 fertilization on enhancing global forest gross primary productivity (GPP) is acknowledged, but its interaction with climate factors—air temperature (Tem), precipitation (Pre), vapor pressure deficit (VPD), and radiation (Rad)—remains unclear. In this study, global forest GPP trends from 1982 to 2018 were examined using BEPS, NIRv, FLUXCOM, and revised EC-LUE datasets, with interannual trends of 5.618 (p < 0.01), 5.831 (p < 0.01), 0.227, and 6.566 g C m−2 yr−1 (p < 0.01), respectively. Elevated CO2 was identified as the primary driver of GPP trends, with the dominant area ranging from 51.11% to 90.37% across different GPP datasets. In the NIRv and revised EC-LUE datasets, the positive impact of CO2 on GPP showed a decrease of 0.222 g C m−2 yr−1, while the negative impact of Rad increased by 0.007 g C m−2 yr−1. An inhibitory relationship was found between the actual effects of elevated CO2 and climate change on GPP in most forest types. At lower latitudes, Tem primarily constrained CO2 fertilization, while at higher latitudes, VPD emerged as the key limiting factor. This was mainly attributed to the potential trade-off or competition between elevated CO2 and climate change in influencing GPP, with strategic resource allocation varying across different forest ecosystems. This study highlights the significant inhibitory effects of elevated CO2 and climate change on global forest GPP, providing insights into the dynamic responses of forest ecosystems to changing environments.

Elevated atmospheric CO2 concentration and vegetation structural changes contributed to gross primary productivity increase more than climate and forest cover changes in subtropical forests of China

Abstract. The subtropical forests of China play a pivotal role in the global carbon cycle and in regulating the global climate. Quantifying the individual and combined effects of forest cover change (FCC), vegetation structural change (e.g. leaf area index (LAI)), CO2 fertilisation, and climate change (CC) on the annual gross primary productivity (GPP) dynamics of different subtropical forest types are essential for mitigating carbon emissions and predicting future climate changes, but these impacts remain unclear. In this study, we used a processed-based model to comprehensively investigate the impacts of these factors on GPP variations with a series of model experiments in China's subtropical forests from 2001 to 2018. Simulated GPP showed a significant increasing trend (20.67 gCm-2yr-1, p&lt;0.001) under the interaction effects of FCC, LAI change, rising CO2, and CC. The CO2 fertilisation (6.84 gCm-2yr-1, p&lt;0.001) and LAI change (3.79 gCm-2yr-1, p=0.004) were the two dominant drivers of total subtropical forest GPP increase, followed by the effects of FCC (0.52 gCm-2yr-1, p&lt;0.001) and CC (0.92 gCm-2yr-1, p=0.080). We observed different responses to drivers depending on forest types. The evergreen broad-leaved forests showed the maximum carbon sequestration rate due to the positive effects of all drivers. Both the FCC (0.19 gCm-2yr-1, p&lt;0.05) and CC (1.22 gCm-2yr-1, p&lt;0.05) significantly decreased evergreen needle-leaved forest GPP, while their negative effects were almost offset by the positive impact of LAI changes. Our results indicated that LAI outweighed FCC in promoting GPP, which is an essential driver that needs to be accounted for in studies and ecological and management programmes. Overall, our study offers a novel perspective on different drivers of subtropical forest GPP changes and provides valuable information for policy makers to better manage subtropical forests to mitigate climate change risks.

Spatiotemporal variation and response of gross primary productivity to climate factors in forests in Qiannan state from 2000 to 2020

Accurate estimation of terrestrial gross primary productivity (GPP) is essential for quantifying the carbon exchange between the atmosphere and biosphere. Light use efficiency (LUE) models are widely used to estimate GPP at different spatial scales. However, difficulties in properly determining the maximum LUE (LUEmax) and downregulation of LUEmax into actual LUE result in uncertainties in the LUE-estimated GPP. The recently developed P model, a new LUE model, captures the adaptability of vegetation to the environment and simplifies parameterization. Site-level studies have proven the superior performance of the P model over LUE models. As a representative karst region with significant changes in forest cover in Southwest China, Qiannan is useful for exploring the spatiotemporal variation in forest GPP and its response to climate change for formulating forest management policies to address climate changes, e.g., global warming. Based on remote sensing and meteorological data, this study estimated the forest ecosystem GPP in Qiannan from 2000–2020 via the P model. This study explored the spatiotemporal changes in GPP in the study region over the past 20 years, used the Hurst index to predict future development trends from a time series perspective, and used partial correlation analysis to analyse the spatiotemporal GPP changes over the past 20 years in response to three factors: temperature, precipitation, and vapor pressure deficit (VPD). Our results showed that (1) the total amount of GPP and average GPP in Qiannan over the past 21 years (2000–2020) were 1.9 × 104 ± 2.0 × 103 MgC ha−1 year−1 and 1238.9 ± 107.9 gC m−2 year−1, respectively. The forest GPP generally increased at a rate of 6.1 gC m−2 year−1 from 2000 to 2020 in Qiannan, and this increase mainly occurred in the nongrowing season. (2) From 2000 to 2020, the forest GPP in Qiannan was higher in the southeast and lower in the northwest, indicating significant spatial heterogeneity. In the future, more than 70% of regional forest GPP will experience a weak increase in nonsustainability. (3) In Qiannan, forest GPP was positively correlated with both temperature and precipitation, with partial correlation coefficients of 0.10 and 0.11, respectively. However, the positive response of GPP to precipitation was approximately 70.47%, while that to temperature was 64.05%. Precipitation had a stronger restrictive effect on GPP than did temperature in this region, and GPP exhibited a negative correlation with VPD. The results showed that an increase in VPD inhibits GPP to some extent. Under rapid global change, the P model GPP provides new GPP data for global ecology studies, and the comparison of various stress factors allows for improvement of the GPP model in the future. The results of this study will aid in understanding the dynamic processes of terrestrial carbon. These findings are helpful for estimating and predicting the carbon budget of forest ecosystems in karst regions, clarifying the regional carbon absorption capacity, clarifying the main factors limiting vegetation growth in these regions, promoting sustainable regional forestry development and serving the “dual carbon goal.” This work has important guiding significance for policy formulation to mitigate climate change.

Solar radiation variation weakened the boost of gross primary production by vegetation restoration in China’s most forestry engineering areas during 2001–2020

Over the past decades, ecological restoration initiatives in China have made great progress in restoring degraded forests and increasing vegetation coverage, yet the carbon sequestration effects of these initiatives in the context of climate change are not clear. In this study, we assessed the effects of vegetation restoration on gross primary production (GPP) in China’s forestry engineering areas, where large-scale vegetation restoration programmes were launched, during 2001–2020 by disentangling the respective roles of land cover change (LCC), CO2 fertilization, and climate changes using a two-leaf light use efficiency model. We found that LCC attributed by the vegetation restoration dominantly accelerated the increase of GPP in seven out of the eight areas, and CO2 fertilization played a near-equivalent role in all areas. By contrast, the changes in different climate factors contributed to GPP variations diversely. The solar radiation variation greatly inhibited the vegetation GPP over time in seven out of these areas, and the changes in air temperature and vapor pressure deficit regulated GPP inter-annual variations without clear trends in all areas. This study advances our understanding of the contribution of China’s afforestation on its forest GPP in a changing climate, which may help to better manage forests to tackle the challenge of the climate crisis in the future.

The Divergent Resistance and Resilience of Forest and Grassland Ecosystems to Extreme Summer Drought in Carbon Sequestration

It is projected that extreme drought events will become more frequent and more severe across many regions of the globe by the end of the 21st century. Despite the substantial efforts that have been made to explore the impacts of droughts on terrestrial ecosystems, our understanding of the response of diverse ecosystems, including resistance and resilience, remains unclear. A total of 16 site years of eddy covariance-based carbon flux data were used to reveal the different responses of forest and grassland ecosystems to two extreme summer droughts. We found that the carbon fluxes of the forest, namely gross primary productivity (GPP), ecosystem respiration (Re), and the net ecosystem carbon exchange (NEE), exhibited distinct seasonal patterns with a single peak. However, GPP and NEE of grassland showed multiple peaks owing to hay harvesting throughout one year. Meanwhile, all climate factors jointly affected the seasonal dynamics in the NEE of the forest, whereas solar radiation only dominated the variability in the NEE of grassland. Moreover, the optimal response relationship was quadratic between the vapor pressure deficit (VPD) and the NEE, with the thresholds being 5.46 and 5.84 for forest and grassland, respectively. Owing to the large increase in VPD during the droughts of 2003 and 2018, the carbon sequestration of forest and grassland reduced sharply and even altered from carbon sink to carbon source. Compared with grassland, forest GPP showed stronger resistance with weaker resilience to droughts. However, larger resilience appeared for both forest and grassland NEE relative to their resistance. All analyses reflect the different adaptive strategies among plant functional types, which is crucial to evaluate ecosystem carbon sequestration to overcome future climate change.

Temporal upscaling of MODIS instantaneous FAPAR improves forest gross primary productivity (GPP) simulation

Gross primary productivity (GPP) is a measure of carbon uptake by terrestrial ecosystems for carbon neutrality and serves as a key indicator for the Sustainable Development Goals. The instantaneous Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is applied in GPP estimation by light use efficiency (LUE) models. However, an obvious time scale mismatch exists between instantaneous FAPAR and daily accumulated GPP. In the study, we explored the potential of temporal upscaling instantaneous FAPAR in improving GPP simulation. The absorbed photosynthetically active radiation (APAR) derived from instantaneous and upscaled FAPARs were first compared. GPPs were estimated from instantaneous and upscaled FAPAR by MOD17 LUE model using default and optimized parameters. The optimized GPP was finally compared with three GPP products: GLASS, MOD17A2H and MYD17A2H GPP. The APARs and GPPs were evaluated with the Eddy Covariance (EC) GPP at 78 forest sites from the Fluxnet community. Results showed that when compared with EC GPP, the upscaled FAPAR-derived APAR held a higher R2 (0.26–0.73) than that from instantaneous FAPARs. The upscaled FAPAR-based GPPs by MOD17 LUE model with default or optimized parameters had a larger R2 and smaller RMSE reducing uncertainties by 6.82–7.8% (maximum value: 27.9–49%). The optimized upscaled FAPAR-derived GPP was far superior to the GPP products with larger R2 (0.69–0.85) and smaller RMSE (12.8–14.6 g C/m2/8d). It is concluded that temporal upscaling of MODIS instantaneous FAPAR can well improve the estimation of forest GPP and the parameters of MOD17 LUE model should be further optimized. Our study is an effort toward reducing the uncertainties from FAPAR in the GPP estimation for better assessing the achievement of carbon neutrality and Sustainable Development Goals.

Tree-ring δ13C of Pinus koraiensis is a better tracer of gross primary productivity than tree-ring width index in an old-growth temperate forest

Tree-ring carbon (C) isotope composition (δ13C) varies depending on photosynthetic capacity and stomatal conductance, and it is therefore intrinsically associated with vegetation productivity. Still, very little is known about the relationship between tree-ring δ13C values and forest gross primary productivity (GPP). Here, we investigated relationships between tree-ring δ13C, tree-ring width index (RWI) and ecosystem-level GPP in a Korean pine (Pinus koraiensis)-dominated old-growth temperate forest in northeastern China. Specifically, we generated chronologies of RWI and δ13C from early-wood (δ13CEW) and late-wood (δ13CLW) of Korean pines, and we built a 17-year continuous ecosystem-level GPP series using eddy covariance measurements, in which a GPP model was used for gap filling. RWI showed vague relationships with tree-ring δ13C and whole-forest GPP, and it was insensitive to interannual variations in climate at the study site. By contrast, both δ13CEW and δ13CLW showed significant relationships with climate variables and GPP. This suggests that isotopic signals of photosynthetic C uptake were imprinted on the formation of tree rings and that tree-ring δ13C of Korean pine is a better proxy for forest GPP than RWI. In addition, tree-ring δ13C of Korean pines was positively correlated with GPP, with an especially close relationship between δ13CEW and GPP of the current year. This implies that photosynthetic activity, rather than stomatal conductance, was the main driver of tree-ring δ13C signals of Korean pine and it was mainly influenced by the climate conditions of the current year, probably because of a limited use of previously fixed C during early-wood formation. Our findings demonstrate the great potential of tree-ring δ13C for reconstructing GPP timeseries at the centennial scale for forest ecosystems, and they could help to constrain parameters in terrestrial C cycle models to improve predictions of C fluxes.

The impacts of ambient ozone pollution on China's wheat yield and forest production from 2010 to 2021

Near-surface ozone causes damages on both crop and forest but their long-term spatiotemporal changes in China have been insufficiently explored, preventing comprehensive policy making with food security and climate targets. Moreover, limitation exists in the current metrics for long-term regional ozone risk assessment, AOT40 (the accumulated hourly ozone over a threshold of 40 ppbv) and PODY (phytotoxic ozone dose over a threshold of Y nmol ozone m−2 PLA s−1), with ignorance of meteorological influence for the former and complicated data collection and calculation procedures for the latter. Here, we developed a new metric for ozone-induced risk on winter wheat, O3MET, which can be easily derived based on ozone concentrations and meteorological variables, and is suitable for long-term assessment of ozone-induced wheat loss at the regional scale. Combining with existing metric for forest (O3RH), we comprehensively quantified the ozone damages on winter wheat yield and forest gross primary production (GPP) for mainland China during 2010–2021, the period with fast growth of ozone level across the country. The annual average losses of wheat yield and forest GPP were estimated at 26.5 Mt and 552.6 TgC, accounting for 17% and 4% of the total yield and GPP without ozone impact, respectively. Heavy dual ozone-induced damages on both wheat and forest were presented in East and South China. The ozone-induced wheat yield loss and forest GPP loss were estimated to increase at a rate of 1.8 Mt/yr and 13.9 TgC/yr for the entire country, respectively, driven mainly by the enhanced ambient ozone level within the research period. Besides ecological impact, the ozone pollution in the developed eastern China resulted in serious health burden as well, thus effective actions on ozone pollution alleviation in the region is crucial for reducing its ecological and health risks simultaneously.

A critical review of methods, principles and progress for estimating the gross primary productivity of terrestrial ecosystems

The gross primary productivity (GPP) of terrestrial ecosystems reflects the total amount of organic carbon assimilated by vegetation through photosynthesis per given unit of time and area, which represents the largest carbon flux in carbon budget and plays a fundamental part in the carbon cycle. However, challenges such as determining how to select appropriate methods to improve GPP estimation accuracy at the regional/global scale remain. Therefore, it is of great importance to comprehensively review the research progress on the methods for estimating the GPP of terrestrial ecosystems and to summarize their flaws, merits and application fields. In this study, we reviewed studies of GPP estimation at different spatiotemporal scales, and systematically reviewed the principles, formulas, representative methods (Ground observations, Model simulations, SIF based GPP, and NIRv based GPP) at different scales and models (Statistical/Ecological process/Machine learning/Light use efficiency models), as well as the advantages and limitations of each research method/models. A comprehensive comparison of GPP research methods was performed. We expect that this work will provide some straightforward references for researchers to further understand and to choose appropriate models for assessing forest ecosystem GPP according to the research objectives and area. Thus, critical and effective GPP estimation methods can be established for the terrestrial carbon cycle, carbon neutralization accounting and local carbon emission reduction policy formulation and implementation.

Land Surface Greening and CO2 Fertilization More than Offset the Gross Carbon Sequestration Decline Caused by Land Cover Change and the Enhanced Vapour Pressure Deficit in Europe

Satellite observations have revealed strong land surface “greening” (i.e., increases in vegetation greenness or leaf area index (LAI)) in the Northern Hemisphere over the past few decades. European terrestrial ecosystems are a greening hotspot, but how they respond to land surface greening, climate change, CO2 fertilization, land use and land cover change (LULCC) and other factors is unclear. Here, we assessed how these interacting factors might be combined to alter terrestrial gross primary production (GPP) throughout Europe during the period of 2001 to 2016 using a process-based Farquhar GPP model (i.e., FGM). We found a more productive European terrestrial ecosystem and most of the GPP enhancement in Europe was explained by increases in LAI (62%) and atmospheric CO2 concentration (29%). Spatially, the spatial signature of the LAI and GPP trends both suggested widespread (72–73% of the vegetated area) greening phenomena across Europe, among which 23.7% and 13.3% were statistically significant (p &lt; 0.05). The interannual trend of GPP estimated by the FGM (0.55% yr−1) was reasonable compared with other GPP products (0.47% yr−1 to 0.92% yr−1) and the observed LAI increasing rate (0.62% yr−1). FGM factorial simulations suggested that land surface greening (+35.5 Pg C yr−2, p &lt; 0.01), CO2 fertilization (+16.9 Pg C yr−2, p &lt; 0.01), temperature warming (+3.7 Pg C yr−2, p &lt; 0.05), and enhanced downwards solar radiation (+1.2 Pg C yr−2, p &gt; 0.05) contributed to the GPP enhancement, while the enhanced vapour pressure deficit (−5.6 Tg C yr−2, p &lt; 0.01) had significant negative impacts on GPP, especially in 2006 and 2012, when extreme droughts struck south-eastern Europe. Meanwhile, approximately 1.8% of the total area of Europe experienced LULCC from 2001 to 2016 and LULCC exerted a small but significant (−1.3 Tg C yr−2, p &lt; 0.01) impact on GPP due to decreases in the total number of vegetated pixels (−159 pixels yr−1). Although the LULCC effect was negative, the largest increase occurred in forested land (+0.9% of total area). In addition, the increasing trends for the annual mean LAI (0.01 m2 m−2 yr−1, p &lt; 0.001) and total GPP (22.2 Tg C yr−2, p &lt; 0.001) of forests were more significant and higher than those of other vegetation types, suggesting that European forests may continue to play important roles in combating climate change in the future with long-lasting carbon storage potential. These results provide the first systematic quantitative analysis of the driving force of enhanced gross carbon assimilation by European ecosystems by considering variations in leaf physiological traits with environmental adaptations.

Estimating local-scale forest GPP in Northern Europe using Sentinel-2: Model comparisons with LUE, APAR, the plant phenology index, and a light response function

Northern forest ecosystems make up an important part of the global carbon cycle. Hence, monitoring local-scale gross primary production (GPP) of northern forest is essential for understanding climatic change impacts on terrestrial carbon sequestration and for assessing and planning management practices. Here we evaluate and compare four methods for estimating GPP using Sentinel-2 data in order to improve current available GPP estimates: four empirical regression models based on either the 2-band Enhanced Vegetation Index (EVI2) or the plant phenology index (PPI), an asymptotic light response function (LRF) model, and a light-use efficiency (LUE) model using the MOD17 algorithm. These approaches were based on remote sensing vegetation indices, air temperature (Tair), vapor pressure deficit (VPD), and photosynthetically active radiation (PAR). The models were parametrized and evaluated using in-situ data from eleven forest sites in North Europe, covering two common forest types, evergreen needleleaf forest and deciduous broadleaf forest. Most of the models gave good agreement with eddy covariance-derived GPP. The VI-based regression models performed well in evergreen needleleaf forest (R2 = 0.69–0.78, RMSE = 1.97–2.28 g C m−2 d−1, and NRMSE = 9–11.0%, eight sites), whereas the LRF and MOD17 performed slightly worse (R2 = 0.65 and 0.57, RMSE = 2.49 and 2.72 g C m−2 d−1, NRMSE = 12 and 13.0%, respectively). In deciduous broadleaf forest all models, except the LRF, showed close agreements with the observed GPP (R2 = 0.75–0.80, RMSE = 2.23–2.46 g C m−2 d−1, NRMSE = 11–12%, three sites). For the LRF model, R2 = 0.57, RMSE = 3.21 g C m−2 d−1, NRMSE = 16%. The results highlighted the necessity of improved models in evergreen needleleaf forest where the LUE approach gave poorer results., The simplest regression model using only PPI performed well beside more complex models, suggesting PPI to be a process indicator directly linked with GPP. All models were able to capture the seasonal dynamics of GPP well, but underestimation of the growing season peaks were a common issue. The LRF was the only model tending to overestimate GPP. Estimation of interannual variability in cumulative GPP was less accurate than the single-year models and will need further development. In general, all models performed well on local scale and demonstrated their feasibility for upscaling GPP in northern forest ecosystems using Sentinel-2 data.

Nonlinear imprints of forest coverage on the relationships between gross primary production (GPP) and landscape patterns

Land use and land cover change (LUCC) has yielded significant impacts on ecosystem structure and functions. Gross primary production (GPP), the largest flux in the terrestrial carbon cycle, has been drastically changed by various LUCC activities. However, the indirect impacts of LUCC on GPP (i.e., local environment changes induced by LUCC), particularly those related to landscape dynamics, remain unclear. Here, we explored the relationships between GPP and landscape metrics of forest ecosystems in China along a forest coverage gradient from 2001 to 2019, using an up-to-date GPP dataset derived from Solar-Induced Chlorophyll Fluorescence and a widely used landcover product MCD12Q1. Results showed that forest landscape features (e.g., core area index, CAI) synchronized with GPP spatially as shown by the distribution of their hot/cold spots on correlations. Furthermore, two nonlinear change patterns of GPP and landscape metrics along forest coverage gradient were found. One is a hump-shaped pattern, which indicated that GPP and some landscape features (e.g., annual median GPP, annual change rate of forest composition) peaked in medium (about 70–80%) forest-cover regions. Another is a super-linear curve, revealing the rapid and accelerated growth of some landscape features (e.g., annual median CAI) in high forest-cover regions. Finally, forest coverage affected the sensitivity of GPP to landscape features in a nonlinear fashion, characterized as an inverted ‘hook’ curve peaking in intermediate (around 70%) forest-coverage regions. Our study proposed the optimal landscape regulation hypothesis to explain the nonlinear pattern: forest GPP is most responsive to the landscape pattern regulation at intermediate to low levels of disturbance, implying that forest coverage has various impacts on landscape features; together they affect GPP nonlinearly. Regulating the forest landscape composition and configuration can enhance the performance of forest ecosystems in addition to managing forest coverage. Thus, we recommend the adoption of suitable region-specific forest management practices to improve GPP and other ecosystem services of forest ecosystems via manipulating landscape composition and configuration.

Photosynthetic and hydraulic traits influence forest resistance and resilience to drought stress across different biomes

Drought events lead to depressions in gross primary productivity (GPP) of forest ecosystems. Photosynthetic and hydraulic traits are important factors governing GPP variation. However, how these functional traits affect GPP responses to drought has not been well understood. We quantified the capacity of GPP to withstand changes during droughts (GPP_resistance) and its post-drought responses (GPP_resilience) using eddy covariance data from the FLUXNET2015 dataset, and investigated how functional traits of dominant tree species that comprised >80% of the biomass (or composition) influenced GPP_resistance or GPP_resilience. Light-saturated photosynthetic rate of dominant tree species was negatively related to GPP_resistance, and was positively correlated with GPP_resilience. Forests dominated by species with higher hydraulic safety margins (HSM), smaller vessel diameter (Vdia) and lower sensitivity of canopy stomatal conductance per unit land area (Gs) to droughts had a higher GPP_resistance, while those dominated by species with lower HSM, larger Vdia and higher sensitivity of Gs to droughts exhibited a higher GPP_resilience. Differences in functional traits of forests located in diverse climate regions led to distinct GPP sensitivities to droughts. Forests located in humid regions had a higher GPP_resilience while those in arid regions exhibited a higher GPP_resistance. Forest GPP_resistance was negatively related to drought intensity, and GPP_resilience was negatively related to drought duration. Our findings highlight the significant role of functional traits in governing forest resistance and resilience to droughts. Overall, forests dominated by species with higher hydraulic safety were more resistant to droughts, while forests containing species with higher photosynthetic and hydraulic efficiency recovered better from drought stress.

Remotely Monitoring Vegetation Productivity in Two Contrasting Subtropical Forest Ecosystems Using Solar-Induced Chlorophyll Fluorescence

Subtropical forests can sequester a larger amount of atmospheric carbon dioxide (CO2) relative to other terrestrial ecosystems through photosynthetic activity and act as an important role in mitigating global climate warming. Compared with the model-based gross primary production (GPP) products, satellite-derived solar-induced fluorescence (SIF) opens a new window for quantification. Here, we used the remotely sensed SIF retrievals, two satellite-driven GPP products including MODIS (GPPMOD) and BESS (GPPBESS), and tower-based GPP measurements at two contrasting subtropical forests to provide a systematic analysis. Our results revealed that GPP and the associated environmental factors exhibited distinct seasonal patterns. However, the peak GPP values had large differences, with stronger GPP in the evergreen needleleaf forest site (8.76 ± 0.71 g C m−2 d−1) than that in the evergreen broadleaf forest site (5.71 ± 0.31 g C m−2 d−1). The satellite-derived SIF retrievals showed great potential in quantifying the variability in GPP, especially for the evergreen needleleaf forest with r reaching up to 0.909 (p &lt; 0.01). GPPMOD and GPPBESS showed distinctly different performances for the two subtropical forests, whereas the GPP estimates by exclusive use of satellite-based SIF data promised well to the tower-based GPP observations. Multi-year evaluation again confirmed the good performance of the SIF-based GPP estimates. These findings will provide an alternative framework for quantifying the magnitude of forest GPP and advance our understanding of the carbon sequestration capacity of subtropical forest ecosystems.

Land cover change instead of solar radiation change dominates the forest GPP increase during the recent phase of the Shelterbelt Program for Pearl River

China has implemented a series of large-scale afforestation projects to improve its ecological environment in recent decades. Meanwhile, the climate conditions in China have changed substantially. However, whether afforestation or climate change dominates vegetation gross primary production (GPP) in different stages of such afforestation projects is not clear. Here, taking the region of the Shelterbelt Program for Pearl River (SPPR) as the study area, we conducted six scenario simulations using the two-leaf light use efficiency (TL-LUE) model to decouple the effects of land cover change (LCC) and climate factors, i.e., solar radiation (Rad), vapor pressure deficit (VPD), and air temperature (Ta), on forest GPP, and disentangled the impact of various factors on forest GPP in Phase II (2001–2010) and Phase III (2011–2018). We found that industrialization and urbanization slightly changed the total forest area, partly offsetting the ecological benefits of the afforestation project in Phase II, and forest GPP increased slowly. As a result, Rad became the dominant factor of forest GPP increase (the cumulative contribution of 25.68 TgC in 10 years, accounting for 33.51%). In contrast, in Phase III, due to the further expansion of the afforestation area and the natural growth of earlier planted forests, the forest GPP increased rapidly, as did the contribution of LCC. Finally, LCC replaced Rad to become the primary contributor (the cumulative contribution of 114.42 TgC in 8 years, accounting for 60.51%) to the forest GPP increase. During the whole study period, Ta contributed insignificantly to the variation in forest GPP, while to some extent VPD decreased the forest GPP (−12.90% and −4.11% of the contributions in the two phases, respectively). The results suggest that the emergence of ecological benefits of afforestation projects requires a certain time length and forestation scale. Our study provides a basis for formulating effective land use policies.

A Study on Sensitivities of Tropical Forest GPP Responding to the Characteristics of Drought—A Case Study in Xishuangbanna, China

Droughts that occur in tropical forests (TF) are expected to significantly impact the gross primary production (GPP) and the capacity of carbon sinks. Therefore, it is crucial to evaluate and analyze the sensitivities of TF-GPP to the characteristics of drought events for understanding global climate change. In this study, the standardized precipitation index (SPI) was used to define the drought intensity. Then, the spatially explicit individual-based dynamic global vegetation model (SEIB-DGVM) was utilized to simulate the dynamic process of GPP corresponding to multi-gradient drought scenarios—rain and dry seasons × 12 level durations × 4 level intensities. The results showed that drought events in the dry season have a significantly greater impact on TF-GPP than drought events in the rainy season, especially short-duration drought events. Furthermore, the impact of drought events in the rainy season is mainly manifested in long-duration droughts. Due to abundant rainfall in the rainy season, only extreme drought events caused a significant reduction in GPP, while the lack of water in the dry season caused significant impacts due to light drought. Effective precipitation and soil moisture stock in the rainy season are the most important support for the tropical forest dry season to resist extreme drought events in the study area. Further water deficit may render the tropical forest ecosystem more sensitive to drought events.

Examination of aboveground attributes to predict belowground biomass of young trees

Just as the aboveground tree organs represent the interface between trees and the atmosphere, roots act as the interface between trees and the soil. In this function, roots take-up water and nutrients, facilitate interactions with soil microflora, anchor trees, and also contribute to the gross primary production of forests. However, in comparison to aboveground plant organs, the biomass of roots is much more difficult to study. In this study, we analyzed 19 European datasets on above- and belowground biomass of juvenile trees of 14 species to identify generalizable estimators of root biomass based on tree sapling dimensions (e.g. height, diameter, aboveground biomass). Such estimations are essential growth and sequestration modelling. In addition, the intention was to study the effect of sapling dimension and light availability on biomass allocation to roots. All aboveground variables were significant predictors for root biomass. But, among aboveground predictors of root biomass plant height performed poorest. When comparing conifer and broadleaf species, the latter tended to have a higher root biomass at a given dimension. Also, with increasing size, the share of belowground biomass tended to increase for the sapling dimensions considered. In most species, there was a trend of increasing relative belowground biomass with increasing light availability. Finally, the height to diameter ratio (H/D) was negatively correlated to relative belowground biomass. This indicates that trees with a high H/D are not only more unstable owing to the unfavorable bending stress resistance, but also because they are comparatively less well anchored in the ground. Thus, single tree stability may be improved through increasing light availability to increase the share of belowground biomass.

Nitrogen deposition shows no consistent negative nor positive effect on the response of forest productivity to drought across European FLUXNET forest sites

Atmospheric reactive nitrogen (N) deposition is an important driver of carbon (C) sequestration in forest ecosystems. Previous studies have focused on N-C interactions in various ecosystems; however, relatively little is known about the impact of N deposition on ecosystem C cycling during climate extremes such as droughts. With the occurrence and severity of droughts likely to be exacerbated by climate change, N deposition—drought interactions remain one of the key uncertainties in process-based models to date. This study aims to contribute to the understanding of N deposition-drought dynamics on gross primary production (GPP) in European forest ecosystems. To do so, different soil water availability indicators (Standardized Precipitation Evapotranspiration Index (SPEI), soil volumetric water) and GPP measurements from European FLUXNET forest sites were used to quantify the response of forest GPP to drought. The computed drought responses of the forest GPP to drought were linked to modelled N deposition estimates for varying edaphic, physiological, and climatic conditions. Our result showed a differential response of forest ecosystems to the drought indicators. Although all FLUXNET forest sites showed a coherent dependence of GPP on N deposition, no consistent or significant N deposition effect on the response of forest GPP to drought could be isolated. The mean response of forest GPP to drought could be predicted for forests with Pinus trees as dominant species (R 2 = 0.85, RMSE = 8.1). After extracting the influence of the most prominent parameters (mean annual temperature and precipitation, forest age), however, the variability remained too large to significantly substantiate hypothesized N deposition effects. These results suggest that, while N deposition clearly affects forest productivity, N deposition is not a major nor consistent driver of forest productivity responses to drought in European forest ecosystems.

Environmental Effects on Normalized Gross Primary Productivity in Beech and Norway Spruce Forests

The strong effects of climate change are expected to negatively impact the long-term resilience and function of forest ecosystems, which could lead to changes in forest carbon balance and productivity. However, these forest responses may vary with local conditions and forest types. Accordingly, this study was carried out to determine gross primary productivity (GPP) sensitivity to changes in environmental parameters. Central European beech (at Štítná) and spruce species (at Bílý Kr̆íz̆ and Rájec), growing under contrasting climatic conditions, were studied. The comparative analyses of GPP were based on a five-year-long dataset of eddy covariance fluxes during the main growing season (2012–2016). Results of forest GPP responses with changes in environmental factors from a traditional Stepwise multiple linear regression model (SMLR) were used and compared with Random forest (RF) analyses. To demonstrate how actual GPP trends compare to potential GPP (GPPpot) courses expected under near-optimal environmental conditions, we computed normalized GPP (GPPnorm) with values between 0 and 1 as the ratio of the estimated daily sum of GPP to GPPpot. The study confirmed the well-known effect of total intensity of the photosynthetically active radiation and its diffuse fraction on GPPnorm across all the forest types. However, the study also showed the secondary effects of other environmental variables on forest productivity depending on the species and local climatic conditions. The reduction in forest productivity at the beech forest in Štítná was presumed to be mainly induced by edaphic drought (anisohydric behaviour). In contrast, reduced forest productivity at the spruce forest sites was presumably induced by both meteorological and hydrological drought events, especially at the moderately dry climate in Rájec. Overall, our analyses call for more studies on forest productivity across different forest types and contrasting climatic conditions, as this productivity is strongly dependent on species type and site-specific environmental conditions.

Ecosystem Productivity and Evapotranspiration Are Tightly Coupled in Loblolly Pine (Pinus taeda L.) Plantations along the Coastal Plain of the Southeastern U.S.

Forest water use efficiency (WUE), the ratio of gross primary productivity (GPP) to evapotranspiration (ET), is an important variable to understand the coupling between water and carbon cycles, and to assess resource use, ecosystem resilience, and commodity production. Here, we determined WUE for managed loblolly pine plantations over the course of a rotation on the coastal plain of North Carolina in the eastern U.S. We found that the forest annual GPP, ET, and WUE increased until age ten, which stabilized thereafter. WUE varied annually (2–44%), being higher at young plantation (YP, 3.12 ± 1.20 g C kg−1 H2O d−1) compared to a mature plantation (MP, 2.92 ± 0.45 g C kg−1 H2O d−1), with no distinct seasonal patterns. Stand age was strongly correlated with ET (R2 = 0.71) and GPP (R2 = 0.64). ET and GPP were tightly coupled (R2 = 0.86). Radiation and air temperature significantly affected GPP and ET (R2 = 0.71 − R2 = 0.82) at a monthly scale, but not WUE. Drought affected WUE (R2 = 0.35) more than ET (R2 = 0.25) or GPP (R2 = 0.07). A drought enhanced GPP in MP (19%) and YP (11%), but reduced ET 7% and 19% in MP and YP, respectively, resulting in a higher WUE (27–32%). Minor seasonal and interannual variation in forest WUE of MP (age &gt; 10) suggested that forest functioning became stable as stands matured. We conclude that carbon and water cycles in loblolly pine plantations are tightly coupled, with different characteristics in different ages and hydrologic regimes. A stable WUE suggests that the pine ecosystem productivity can be readily predicted from ET and vice versa. The tradeoffs between water and carbon cycling should be recognized in forest management to achieve multiple ecosystem services (i.e., water supply and carbon sequestration).