Significant gaps exist in our knowledge of the impact of leaf aging on canopy signal variability, which limits our understanding of vegetation status based on remotely sensed data. To understand the effects of leaf aging at the leaf and canopy scales, a combination of field, remote-sensing and physical modeling techniques was adopted to assess the canopy spectral signals of evergreen Cunninghamia forests. We observed an approximately 10% increase in Near-Infrared (NIR) reflectance for new leaves and a 35% increase in NIR transmittance for mature leaves from May to October. When variations in leaf optical properties (LOPs) of only mature leaves, or both new and mature leaves were considered, the Geometric Optical and Radiative Transfer (GORT) model-simulated canopy reflectance trajectory was more consistent with Landsat observations (R² increased from 0.37 to 0.82~0.89 for NIR reflectance, and from 0.35 to 0.67~0.88 for EVI2, with a small RMSE (0.01 to 0.02)). This study highlights the importance of leaf age on leaf spectral signatures, and provides evidence of age-dependent LOPs that have important impacts on canopy reflectance in the NIR band and EVI2, which are used to monitor canopy dynamics and productivity, with important implications for RS and forest ecosystem ecology.

The value of leaf photosynthetic capacity (V_cmax) varies with time and space, but state-of-the-art terrestrial biosphere models rarely include such V_cmax variability, hindering the accuracy of carbon cycle estimations on a large scale. In particular, while the European terrestrial ecosystem is particularly sensitive to climate change, current estimates of gross primary production (GPP) in Europe are subject to significant uncertainties (2.5 to 8.7 Pg C yr⁻¹). This study applied a process-based Farquhar GPP model (FGM) to improve GPP estimation by introducing a spatially and temporally explicit V_cmax derived from the satellite-based leaf chlorophyll content (LCC) on two scales: across multiple eddy covariance tower sites and on the regional scale. Across the 19 EuroFLUX sites selected for independent model validation based on 9 plant functional types (PFTs), relative to the biome-specific V_cmax, the inclusion of the LCC-derived V_cmax improved the model estimates of GPP, with the coefficient of determination (R²) increased by 23% and the root mean square error (RMSE) decreased by 25%. V_cmax values are typically parameterized with PFT-specific V_cmax calibrated from flux tower observations or empirical V_cmax based on the TRY database (which includes 723 data points derived from V_cmax field measurements). On the regional scale, compared with GPP, using the LCC-derived V_cmax, the conventional method of fixing V_cmax using the calibrated V_cmax or TRY-based V_cmax overestimated the annual GPP of Europe by 0.5 to 2.9 Pg C yr⁻¹ or 5 to 31% and overestimated the interannually increasing GPP trend by 0.007 to 0.01 Pg C yr⁻² or 14 to 20%, respectively. The spatial pattern and interannual change trend of the European GPP estimated by the improved FGM showed general consistency with the existing studies, while our estimates indicated that the European terrestrial ecosystem (including part of Russia) had higher carbon assimilation potential (9.4 Pg C yr⁻¹). Our study highlighted the urgent need to develop spatially and temporally consistent V_cmax products with a high accuracy so as to reduce uncertainties in global carbon modeling and improve our understanding of how terrestrial ecosystems respond to climate change.

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 < 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 < 0.01), CO₂ fertilization (+16.9 Pg C yr⁻², p < 0.01), temperature warming (+3.7 Pg C yr⁻², p < 0.05), and enhanced downwards solar radiation (+1.2 Pg C yr⁻², p > 0.05) contributed to the GPP enhancement, while the enhanced vapour pressure deficit (−5.6 Tg C yr⁻², p < 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 < 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 < 0.001) and total GPP (22.2 Tg C yr⁻², p < 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.

Since the implementation of the Grain-for-Green Program (GGP), vegetation across the Loess Plateau (LP) has substantially recovered. However, whether the associated increase in ecosystem carbon gain was accompanied by a proportional increase in water consumption and whether groundwater storage changed synchronously remain unclear. This study integrated multi-source remote sensing products, GLDAS-Noah land-surface assimilation data, GRACE/GRACE-FO satellite gravimetry, irrigation water-use data, provincial water-use statistics, and coal-resource information to examine long-term changes in gross primary productivity (GPP), evapotranspiration (ET), water-use efficiency (WUE), soil moisture (SM), and groundwater storage anomaly (GWSA) during 2002–2023. GPP increased significantly by 10.67 g C m⁻² yr⁻¹ ($p<0.01$), whereas ET increased more modestly by 1.97 mm yr⁻¹ ($p<0.05$). The relative growth rate of GPP (1.66%) was approximately 3.5 times that of ET (0.47%), and WUE increased by 0.018 g C m⁻² mm⁻¹ yr⁻¹ ($p<0.01$). In the XGBoost–SHAP models for 2004–2019, LAI showed the strongest model-based association with GPP and WUE, whereas ET was associated more broadly with LAI, air temperature, and precipitation. SM declined during 2002–2015 but showed an increasing tendency during 2016–2023, particularly in the middle and deep layers. The long-term GWSA slopes derived from CSR and JPL were −8.707 and −9.505 mm yr⁻¹, respectively, and the averaged CSR–JPL GWSA series showed a Sen’s slope of −9.131 mm yr⁻¹. GWSA declined during 2002–2020 and showed only a short-term, nonsignificant increase during 2020–2023 (4.110 mm yr⁻¹, $p>0.05$). These contrasting trajectories indicate that increases in surface carbon uptake and improvements in soil-water conditions were not accompanied by synchronous regional groundwater recovery. Overall, the ecological-restoration period was accompanied by increased carbon gain and WUE without a proportional increase in regional ET, while groundwater storage followed a distinct trajectory. These findings provide regional-scale evidence and a quantitative basis for coordinating sustainable water-resource management with ecological-restoration optimization on the LP.