Drought is expected to increase in frequency and severity due to global warming, and its impacts on vegetation are typically extensively evaluated with climatic drought indices, such as multi-scalar Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the covariation between the SPEIs of various time scales and the anomalies of the normalized difference vegetation index (NDVI), from which the vegetation type-related optimal time scales were retrieved. The results indicated that the optimal time scales of needle-leaved forest, broadleaf forest and shrubland were between 10 and 12 months, which were considerably longer than the grassland, meadow and cultivated vegetation ones (2 to 4 months). When the optimal vegetation type-related time scales were used, the SPEI could better reflect the vegetation’s responses to water conditions, with the correlation coefficients between SPEIs and NDVI anomalies increased by 5.88% to 28.4%. We investigated the spatio-temporal characteristics of drought and quantified the different responses of vegetation growth to drought during the growing season (April–October). The results revealed that the frequency of drought has increased in the 21st century with the drying trend occurring in most of China. These results are useful for ecological assessments and adapting management steps to mitigate the impact of drought on vegetation. They are helpful to employ water resources more efficiently and reduce potential damage to human health caused by water shortages.

In recent decades, the area and proportion of planted forests have increased; thus, understanding the responses of planted and natural forests to drought are crucial because it forms the basis for forest risk assessments and management strategies. In this study, we combined the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI), meteorological aridity indices, and standardized precipitation evapotranspiration indices (SPEI) to identify the drought responses of planted and natural forests. In particular, we used the EVI standard anomaly (ESA) as a physiological drought indicator and analyzed the applicability of SPEIs at time scales of 1–30 months, thereby determining the optimal time scale for the SPEI (SPEI_opt), i.e., the SPEI that best represents the drought responses of forests in Yunnan. Next, we employed the optimal SPEI and the ESA as indices to statistically analyze the response characteristics of planted and natural forests under different drought intensities. The results indicated the following: (1) The SPEI in June and a time scale of five months (i.e., SPEI_Jun,5) comprise the optimal meteorological aridity indicator for forests in Yunnan Province, which had the strongest correlation with the EVI standard anomaly (ESA_Jun). (2) All forest types were affected by drought in Yunnan, but their responses varied according to the forest type, elevation, and drought intensity. In general, natural forests are more vulnerable and sensitive to drought than planted forests, especially natural coniferous forests at low (0–2000 m) and moderate (2000–4000 m) altitudes, and natural mixed forest at low altitudes (0–2000 m). (3) The remote sensing-based ESA (ESA_Jun) is sensitive to the intensity of water stress, which makes it a good indicator for drought monitoring. In addition, the forests’ inventory survey revealed that 8.05% of forests were affected by drought; thus, we used this as a guide to estimate an approximate threshold to map forest responses to drought across the region. Below this approximate threshold (i.e., ESA_Jun < −3.85), severe drought-induced effects on forests may occur. Given that natural forests are more vulnerable and sensitive to drought than the planted forests, natural forests need more careful management, especially in the context of projected increases in extreme drought events in the future.

We have integrated the observational capability of satellite remote sensing with plot-scale tree-ring data to upscale the evaluation of forest responses to drought. Satellite data, such as the normalized difference vegetation index (NDVI), can provide a spatially continuous measure with limited temporal coverage, while tree-ring width index (RWI) provides an accurate assessment with a much longer time series at local scales. Here, we explored the relationship between RWI and NDVI of three dominant species in the Southwestern United States (SWUS) and predicted RWI spatial distribution from 2001 to 2017 based on Moderate Resolution Imaging Spectroradiometer (MODIS) 1-km resolution NDVI data with stringent quality control. We detected the optimum time windows (around June–August) during which the RWI and NDVI were most closely correlated for each species, when the canopy growth had the greatest effect on growth of tree trunks. Then, using our upscaling algorithm of NDVI-based RWI, we were able to detect the significant impact of droughts in 2002 and in 2011–2014, which supported the validity of this algorithm in quantifying forest response to drought on a large scale.

Global climate change is leading to an increase in the frequency, intensity, and duration of drought events, which can affect the functioning of forest ecosystems. Because human activities such as afforestation and forest attributes such as canopy height may exhibit considerable spatial differences, such differences may alter the recovery paths of drought-impacted forests. To accurately assess how climate affects forest recovery, a quantitative evaluation on the effects of forest attributes and their possible interaction with the intensity of water stress is required. Here, forest recovery following extreme drought events was analyzed for Yunnan Province, southwest China. The variation in the recovery of forests with different water availability and canopy heights was quantitatively assessed at the regional scale by using canopy height data based on light detection and ranging (LiDAR) measurements, enhanced vegetation index data, and standardized precipitation evapotranspiration index (SPEI) data. Our results indicated that forest recovery was affected by water availability and canopy height. Based on the enhanced vegetation index measures, shorter trees were more likely to recover than taller ones after drought. Further analyses demonstrated that the effect of canopy height on recovery rates after drought also depends on water availability—the effect of canopy height on recovery diminished as water availability increased after drought. Additional analyses revealed that when the water availability exceeded a threshold (SPEI > 0.85), no significant difference in the recovery was found between short and tall trees (p > 0.05). In the context of global climate change, future climate scenarios of RCP2.6 and RCP8.5 showed more frequent water stress in Yunnan by the end of the 21st century. In summary, our results indicated that canopy height casts an important influence on forest recovery and tall trees have greater vulnerability and risk to dieback and mortality from drought. These results may have broad implications for policies and practices of forest management.

Revealing forest drought response characteristics and the potential impact factors is quite an important scientific issue against the background of global climate change, which is the foundation to reliably evaluate and predict the effects of future drought. Due to the high spatial heterogeneity of forest properties such as biomass, forest age, and height, and the distinct differences in drought stress in terms of frequency, intensity, and duration, current studies still contain many uncertainties. In this research, we used the forests in Yunnan Province in Southwest China as an example and aimed to reveal the potential impacts of forest properties (i.e., stock volume) on drought response characteristics. Specifically, we divided the forest into five groups of stock volume density values and then analyzed their drought response differences. To depict forest response to drought intensity, the standardized precipitation evapotranspiration index (SPEI) was chosen as the explanatory variable, and the change in remote sensing-based enhanced vegetation index (deficit of MODIS-EVI, dEVI) was chosen as the response variable of drought stress. Given that the SPEI has different time scales, we first analyzed the statistical dependency of SPEIs with different time scales (1 to 36 months) to the response variable (i.e., dEVI). The optimal time scale of SPEI (SPEI_opt) to interpret the maximum variation of dEVI (R-square) was then chosen to build the ultimate statistical models for the five groups of stock volume density. The main findings were as follows: (1) the impacts of drought showed hysteresis and cumulative effects, and the length of the hysteresis increased with stock volume densities; (2) forests with high stock volume densities required more soil water and were therefore more sensitive to the changes in water deficit; (3) compared with the optimal time scale of SPEI (SPEI_opt), the SPEI with the commonly used time scale (e.g., 1, 6, and 12 months) could not well reflect the impacts of drought on forests and the simulation error of dEVI increased with stock volume densities; and (4) forests with higher stock volume densities were likely to experience a greater risk of degradation following higher atmospheric concentrations of greenhouse gases (Representative Concentration Pathway (RCP) 8.5). As a result, both the time scale of the meteorological drought index and the spatial difference in forest stock volumes should be considered when evaluating forest drought responses at regional and global scales.

Under the background of global change, the internal relationship between forests' age and forests' carbon cycling is very important to study the position and function of forests in the global carbon cycle.Thus, the study employed field observations to inversely estimate the parameter of maximum light-use efficiency(ε max) of forests in different stand ages, generated a national map of forests' NPP on forests age.We found the ε max has decreased with the increased of forest ages that is consistent with other studies, and compared with the fixed ε max , the NPP of forests was calculated on forests age are more reliable and stable.The results shows a significant heterogeneity of forests' NPP_age, and the average NPP of the evergreen broadleaf forest, the deciduous broadleaf forest, evergreen needleleaf forest and deciduous needleleaf forests is about 377.34, 293.99,273.63 and 306.36 gC/m 2 •yr.On the national level, the forests' NPP_age was 303.45 C/m 2 •yr in China. In the future, the forests' age needs to be taken into account in the Estimation of the net primary productivity.