Climate-driven increases in global terrestrial net primary production from 1982 to 1999

Leaf N:P ratio does not predict productivity trends across natural terrestrial ecosystems

Nitrogen (N) and phosphorus (P) are crucial nutrients for regulating plant growth. The classic growth rate hypothesis (GRH) proposes that fast-growing organisms have lower N:P ratios, and it is promising to predict net primary productivity (NPP) using the leaf N:P ratio at the community level (N:P_Com ). However, whether leaf N:P ratio can predict NPP in natural ecosystems on a large scale remains nebulous. Here, we systematically calculated leaf N:P_Com (community biomass-weighted mean and species-arithmetic mean) using the consistently measured data of 2,192 plant species-site combinations and productivity (biomass-based aboveground NPP and flux-based NPP) in 66 natural ecosystems in China. Unexpectedly, leaf N:P_Com hardly predicted productivity in natural ecosystems due to their weak correlation, although significantly negative or positive relationships across different ecosystems were observed. The ambiguous relationship between leaf N:P and species dominance reflected a luxury consumption of N and P in turnover and structure in natural communities, unlike what GRH suggests. Climate, soil, and leaf nutrients (rather than N:P) influenced productivity, which highlighted the importance of external environment and nutrient constrains. Our findings pose a major challenge for leaf N:P_Com as a direct parameter in productivity models and further question the direct application of classic hypotheses in short-term experiments or model species to long-term and complex natural ecosystems.

Vegetation Responses to Climate Change and Anthropogenic Activity in China, 1982 to 2018

Climate change and human activities significantly affect vegetation growth in terrestrial ecosystems. Here, data reconstruction was performed to obtain a time series of the normalized difference vegetation index (NDVI) for China (1982−2018) based on Savitzky−Golay filtered GIMMS NDVI3g and MOD13A2 datasets. Combining surface temperature and precipitation observations from more than 2000 meteorological stations in China, Theil−Sen trend analysis, Mann−Kendall significance tests, Pearson correlation analysis, and residual trend analysis were used to quantitatively analyze the long-term trends of vegetation changes and their sources of uncertainty. Significant spatial and temporal heterogeneity was observed in vegetation changes in the study area. From 1982 to 2018, the vegetation showed a gradually increasing trend, at a rate of 0.5%·10 a−1, significantly improving (37.15%, p < 0.05) more than the significant degradation (7.46%, p < 0.05). Broadleaf (0.66) and coniferous forests (0.62) had higher NDVI, and farmland had the fastest rate of increase (1.02%/10 a−1). Temperature significantly affected the vegetation growth in spring (R > 0; p < 0.05); however, the increase in summer temperatures significantly inhibited (R < 0; p < 0.05) the growth in North China (RNDVI-tem = −0.379) and the Qinghai−Tibetan Plateau (RNDVI-tem = −0.051). Climate change has highly promoted the growth of vegetation in the plain region of the Changjiang (Yangtze) River (3.24%), Northwest China (1.07%). Affected by human activities only, 49.89% of the vegetation showed an increasing trend, of which 22.91% increased significantly (p < 0.05) and 9.97% decreased significantly (p < 0.05). Emergency mitigation actions are required in Northeast China, Xinjiang, Northwest China, and the Qinghai−Tibetan Plateau. Therefore, monitoring vegetation changes is important for ecological environment construction and promoting regional ecological protection.

Spatiotemporal changes in net primary productivity before and after the development of unused land in the hilly areas of Hebei, China

Net primary productivity (NPP) plays an important role in the carbon cycle of an ecosystem. To explore the impact of unused land development on NPP, this study adopted an improved Carnegie Ames Stanford Approach (CASA) model to analyze the changes in NPP before and after the development of unused land in Tang County, Hebei Province, in 2000, 2007, and 2018. The results showed that, due to the changes in land use types from unused land, forestland, arable land with high NPP values to urban and rural residential land, traffic land with low NPP values, and the changes in precipitation and temperature, the NPP in the study area showed an overall trend of decreasing first and then rising from 2000 to 2018. Before the development of unused land in 2000, the total NPP was 38.45×10¹⁰ g C. After the development in 2007 and 2018, the total NPP was 36.44×10¹⁰ g C and 41.05×10¹⁰ g C, respectively. The NPP of each land type in 2018 was arable land (1046.18 g C m^-2) > forestland (464.42 g C m^-2) > unused land (356.34 g C m^-2) > grassland (343.77 g C m^-2) > waters (182.56 g C m^-2) > urban and rural settlements (120.86 g C m^-2) > traffic land (120.70 g C m^-2). The distribution of NPP was generally high in the north and low in the south before and after development. NPP was mainly concentrated in the interval of 300 g C m^-2 yr^-1–400 g C m^-2 yr^-1, and the range of NPP change was mostly within 100 g C m^-2. The influence of elevation, temperature and precipitation on the spatial distribution of NPP was significant. Elevation and precipitation were positively correlated with NPP, while temperature was negatively correlated with NPP. The increase in NPP mainly originated from the conversion of unused land to forestland and arable land. The loss of NPP was mainly due to the conversion from forestland with high vegetation productivity to a land use type with low vegetation productivity, such as the conversion from forestland to urban and rural residential land. The results can provide references for making reasonable land planning decisions and ecological environment construction.

Estimation of Terrestrial Net Primary Productivity in the Yellow River Basin of China Using Light Use Efficiency Model

The net primary productivity (NPP) of vegetation is an essential factor of ecosystem functions, including the biological geochemical carbon cycle, which is often impacted by climate change and human activities. It plays a significant role in comprehending the nature of carbon balance in an ecosystem and demonstrates the global and regional carbon cycle dynamics. The present study used an upgraded CASA model to calculate the NPP in the Yellow River Basin (YRB), China. The model’s simulation ability was improved by changing the model parameters. Further, the CASA model was validated by comparing with MODIS-NPP and in situ observed NPP, wherein the accuracy of the CASA model estimation was found satisfactory to estimate NPP changes in the study area. The simulated results of the improved CASA model showed that the mean annual NPP value of vegetation in the YRB was 283.4 gC m–2 a–1 from 2001 to 2020, with a declining trend in spatial distribution from south to north. In contrast, the NPP appeared as an increasing trend in the YRB temporally from 212 gC m–2 a–1 in 2001 to 342 gC m–2 a–1 in 2020, with a mean annual growth rate of 4.6 gC m–2 a–1. The total NPP in the YRB increased by 40,088.3 GgC between 2001 and 2020, from 226.06 TgC to 266.15 TgC. This rise can be attributed to the increase in forests. The average grassland area has reduced by 4651 km2 during the last two decades, significantly impacting the total NPP of grasslands. Although the increase in NPP in wetlands was minimal, accounting for 815.53 GgC, the highest change percentage of 79.78%, could be observed among the six vegetation types due to the anthropogenic influences and climate change. The conditions favorable for vegetation growth and a sustained environment were enhanced by the increased precipitation and temperature and the reinforced ecological protection by the government.

Widespread decline in winds promoted the growth of vegetation

Vegetation dynamics are sensitive to climate change. Wind is an important climate factor that can affect carbon fluxes by altering carbon uptake and emission rates; however, the impact of wind has not been fully considered in previous studies; therefore, exploring the characteristics of vegetation responses to wind speed is crucial to sustainable natural resource utilization and ecological restoration. In this study, the global leaf area index (LAI) from 1984 to 2013 was used to investigate the vegetation spatial heterogeneities, change processes, and relative contributions of climate change. The differences in vegetation responses to climate factors, such as precipitation (PRE), temperature (TEM), and wind speed (WD), were compared by considering the effects of wind. The results revealed that (1) the global vegetation (86.24%) exhibited a greening trend, among which evergreen broad-leaved forests (0.0052 a^-1) changed the most. (2) The wind speed explained 31.54% of the vegetation variations, which is higher than the contribution of other factors. (3) Reduction of wind speed had a positive impact on vegetation changes. The contribution of climate to vegetation growth increased by 8.14% when considering the effects wind speed, particularly in India and South America. Wind speed effects were essential for enhancing the vegetation dynamics assessment and improving the prediction accuracy of the model.

Revisiting the cumulative effects of drought on global gross primary productivity based on new long-term series data (1982-2018)

Drought has broad and deep impacts on vegetation. Studies on the effects of drought on vegetation have been conducted over years. Recently, the cumulative effect of drought is recognized as another key factor affecting plant growth. However, global-scale studies on this phenomenon are still lacking. Thus, based on new satellite based gross primary productivity (GPP) and multi-temporal scale Standardized Precipitation Evapotranspiration Index data sets, we explored the cumulative effect duration (CED) of drought on global vegetation GPP and analyzed its variability across elevations and climatic zones. The main findings were as follows: (1) The cumulative effect of drought on GPP was widespread, with an average CED of 4.89 months. (2) CED of drought on GPP varied among vegetation types. Specifically, grasslands showed the longest duration, with an average value of 5.28 months, followed by shrublands (5.09 months), wetlands (5.03 months), croplands (4.85 months), savannas (4.58 months), and forestlands (4.57 months). (3) CED of drought on GPP changes with climate conditions. It decreased with the decrease of precipitation in the driest month (P_dry ) and mean annual precipitation in tropical and arid climate zones, respectively. In both temperate and cold climate zones, CED of drought on GPP was shorter in areas with dry winter than that in areas with dry summer. It increased with the decrease of mean annual air temperature in tropical climate zones and decreased with the increase of summer temperature in temperate and cold climatic zones. (4) With increasing elevation, CED of drought on GPP showed a pattern of increasing (0-3000 m), then decreasing (3000-5000 m), and increasing again (>5000 m). Our findings highlight the heterogeneity of CED of drought on GPP, owing to differences in vegetation types, long-term hydrothermal conditions, elevation, etc. The results could deepen our understanding of the effects of drought on global vegetation.

Three Decades of Gross Primary Production (GPP) in China: Variations, Trends, Attributions, and Prediction Inferred from Multiple Datasets and Time Series Modeling

The accurate estimation of gross primary production (GPP) is crucial to understanding plant carbon sequestration and grasping the quality of the ecological environment. Nevertheless, due to the inconsistencies of current GPP products, the variations, trends and short-term predictions of GPP have not been sufficiently well studied. In this study, we explore the spatiotemporal variability and trends of GPP and its associated climatic and anthropogenic factors in China from 1982 to 2015, mainly based on the optimum light use efficiency (LUEopt) product. We also employ an autoregressive integrated moving average (ARIMA) model to forecast the monthly GPP for a one-year lead time. The results show that GPP experienced an upward trend of 2.268 g C/m2 per year during the studied period, that is, an increasing rate of 3.9% per decade since 1982. However, these trend changes revealed distinct heterogeneity across space and time. The positive trends were mainly distributed in the Yellow River and Huaihe River out of the nine major river basins in China. We found that the dynamics of GPP were concurrently affected by climate factors and human activities. While air temperature and leaf area index (LAI) played dominant roles at a national level, the effects of precipitation, downward shortwave radiation (SRAD), carbon dioxide (CO2) and aerosol optical depth (AOD) exhibited discrepancies in terms of degree and scope. The ARIMA model achieved satisfactory prediction performance in most areas, though the accuracy was influenced by both data values and data quality. The model can potentially be generalized for other biophysical parameters with distinct seasonality. Our findings are further verified and corroborated by four widely used GPP products, demonstrating a good consistency of GPP trends and prediction. Our analysis provides a robust framework for characterizing long-term GPP dynamics that shed light on the improved assessment of the environmental quality of terrestrial ecosystems.

Surface Reflectance–Derived Spectral Indices for Drought Detection: Application to the Guadalupe Valley Basin, Baja California, Mexico

Evaluating how meteorological drought affects areas covered by natural ecosystems is challenging due to the lack of ground-based climate data, historical records, and weather station observation with limited coverage. This research tests how the surface reflectance–derived indices (SRDI) may solve this problem by assessing the condition and vegetation dynamics. We use long–term, monthly surface reflectance data (26 hydrological years, 1992/93–2017/18) from Landsat 5 TM, 7 ETM+, and 8 OLI/TIRS satellites and calculated the following five SRDI: Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), Vegetation Health Index (VHI), Normalized Difference Water Index (NDWI), and Modified Soil Adjusted Vegetation Index (MSAVI). The SRDI allows us to detect, classify, and quantify the area affected by drought in the Guadalupe Valley Basin (GVB) via correlations with the Reconnaissance Drought Index (RDI) and the Standardized Precipitation Index (SPI) (weather station-based data). For particular SRDI–RDI and SRDI–SPI combinations, we find positive seasonal correlations during April–May (IS2) and for annual (AN) values (MSAVI IS2–RDI AN, R = 0.90; NDWI IS2–SPI AN, R = 0.89; VHI AN–RDI AN, R = 0.86). The drought–affected GVB area accounted for >87% during 2001/02, 2006/07, 2013/14, and 2017/18. MSAVI and NDWI are the best meteorological drought indicators in this region, and their application minimizes the dependence on the availability of climatic data series.

Spatiotemporal Dynamics of Terrestrial Vegetation and Its Driver Analysis over Southwest China from 1982 to 2015

Global environmental changes have been dramatic recently, exerting substantial effects on the structures and functions of terrestrial ecosystems, especially for the ecologically-fragile karst regions. Southwest China is one of the largest karst continuum belts around the world, which also contributes about 1/3 of terrestrial carbon sequestration to China. Therefore, a deep understanding of the long-term changes of vegetation across Southwest China over the past decades is critical. Relying on the long time series of Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies normalized difference vegetation index (GIMMS NDVI3g) data set, this study examined the spatial and temporal patterns of vegetation conditions in Southwest China from 1982 to 2015, as well as their response to the environmental factors including temperature, precipitation and downward shortwave radiation. Multi-year mean NDVI showed that except the northwestern region, the NDVI of Southwest China was large, ranging from 0.5 to 0.8. Meanwhile, nearly 43.7% of the area experienced significant improvements in NDVI, whereas only 3.47% of the area exhibited significant decreases in NDVI. Interestingly, the NDVI in karst area increased more quickly with 1.035 × 10−3/a in comparison with that in the non-karst area with about 0.929 × 10−3/a. Further analysis revealed that temperature is the dominant environmental factor controlling the interannual changes in NDVI, accounting for 48.19% of the area, followed by radiation (3.71%) and precipitation (3.09%), respectively.

Identifying the Impacts of Climate Change and Human Activities on Vegetation Cover Changes: A Case Study of the Yangtze River Basin, China

The normalized difference vegetation index (NDVI) is a useful indicator to characterize vegetation development and land use which can effectively monitor changes in ecological environments. As an important area for ecological balance and safety in China, understanding the dynamic changes in land cover and vegetation of the Yangtze River Basin would be crucial in developing effective policies and strategies to protect its natural environment while promoting sustainable growth. Based on MODIS-NDVI data and meteorological data from 2000 to 2019, the temporal and spatial distribution of vegetation coverage in the Yangtze River Basin during the past 20 years were characterized, and the impacts of human activities and climate change were quantitatively evaluated. We drew the following research conclusions: (1) From 2000 to 2019, the vegetation cover of the Yangtze River Basin presented a fluctuating inter-annual growth trend. Except for the Taihu Lake sub-basin, the vegetation cover in other sub-basins showed an upward trend. (2) The vegetation cover exhibited a spatial distribution pattern of “high in the middle and low in the east and west”, with the multi-year average value of NDVI being 0.5153. (3) Areas with improved vegetation cover were significantly larger than the areas with degraded foliage. The central region has stronger overall trend of change than the east, and the east is stronger than the west. These vegetation cover changes are largely related to anthropogenic activities. (4) Vegetation cover changes due to precipitation and temperature exhibited significant spatial heterogeneity. While both temperature and precipitation influenced vegetation cover, the temperature was the leading climate factor in the area. (5) Anthropogenic and climate factors jointly promoted the change of vegetation cover in the Yangtze River Basin. Human activities contributed 79.29%, while climate change contributed 20.71%. This study could be used in subsequent studies analyzing the influencing factors affecting long-term vegetation cover in large-scale watersheds.

The Impact of Human Activities on Net Primary Productivity in a Grassland Open-Pit Mine: The Case Study of the Shengli Mining Area in Inner Mongolia, China

In grassland open-pit mining areas, net primary productivity (NPP) is mainly affected by climate conditions and human activities. The identification and assessment of the influence of human activities on NPP is important for mining production and the implementation of ecological restoration. In this study, we explored the influence of human activities on the NPP in the Shengli mining area in Inner Mongolia, China by using the Carnegie–Ames–Stanford Approach (CASA) model and the Chikugo model, in which a calibration method was applied. An analysis of four representative years showed that the proportion of NPP induced by human activities reached 56.2%, that the percentage of pixels with an inhibitory effect on NPP was 99% in 2011 with the highest intensity of mining activity, and that these two values decreased to 11.9% and 69% in 2020, respectively, with the steady implementation of ecological restoration. Moreover, from the analysis of global and local spatial correlation, mining activities and ecological restoration aggravated and weakened the aggregation of NPP induced by human activities, respectively.

Climatic and Topographical Effects on the Spatiotemporal Variations of Vegetation in Hexi Corridor, Northwestern China

Oases, as complex geographical landscapes, are strongly influenced by both natural variation and human activities. However, they have degenerated because of unplanned land use and water resource development. The research of oasis changes has mostly discussed single components, but multiple components, especially spatial changes to oasis vegetation, need further strengthening. Land use and NDVI were extracted based on Landsat 5/8 and Mod13A3, respectively, and a transfer matrix was constructed to analyze changes of land use in the Hexi Corridor during 2000–2020. The significant changes in the area of each land use were also quantified. Combined with regional temperature and precipitation, interpolated from meteorological data, the correlations between regional temperature, precipitation, and vegetation coverage were calculated, especially in the quantized areas with significant associations. The results showed that the area of bare land or desert decreased, while the areas of agricultural and residential land increased. The normalized difference NDVI of the studied oases increased at the rate of 0.021 per decade, which was positively related to precipitation (p < 0.05), rather than temperature; of which, farmland and planted grass land were 55.65% and 33.79% in the significantly increased area. In the area of significant positive relation between NDVI and precipitation, the ratio of grassland, farmland, and forest was 79.21%, 12.82%, and 4.06%, respectively. Additionally, changes in oasis vegetation were determined primarily by agricultural activities, which reflected a combination of natural and anthropic influences.

Rainfall pulse regime drives biomass and community composition in biological soil crusts

Future climates will alter the frequency and size of rain events in drylands, potentially affecting soil microbes that generate carbon feedbacks to climate, but field tests are rare. Topsoils in drylands are commonly colonized by biological soil crusts (biocrusts), photosynthesis-based communities that provide services ranging from soil fertilization to stabilization against erosion. We quantified responses of biocrust microbial communities to twelve years of altered rainfall regimes, with 60 mm of additional rain per year delivered either as small (5 mm) weekly rains or large (20 mm) monthly rains during the summer monsoon season. Rain addition promoted microbial diversity, suppressed the dominant cyanobacterium, Microcoleus vaginatus, and enhanced nitrogen-fixing taxa, but did not consistently increase microbial biomass. The addition of many small rain events increased microbial biomass, whereas few, large events did not. These results alter the physiological paradigm that biocrusts are most limited by the amount of rainfall and instead predict that regimes enriched in small rain events will boost cyanobacterial biocrusts and enhance their beneficial services to drylands. This article is protected by copyright. All rights reserved.

Beneficial effects of warming on temperate tree carbon storage depend on precipitation and mycorrhizal types

Despite evidence from multiple observation data sets and numerical model simulations that interactions between biotic and abiotic factors control tree carbon (C) storage in the Northern Hemisphere, it remains unclear whether the effect of one factor will be altered by other factors. Here, we used forest inventory data consisting of more than 500,000 trees from 1910 plots to explore the relative importance of these drivers of plant C storage in northeast China. We found that tree C storage was significantly positively associated with mean annual temperature (MAT). After controlling for the role of mean annual precipitation (MAP), directionality in the tree C storage-MAT relationship reversed, indicating that the direction of MAT affecting tree C storage depends on MAP. Accounting for the effects of tree-fungal symbioses on plant resistance to drought and warming, we found that warming increased AM tree C storage even after controlling the role of MAP, but decreased EcM tree C storage after controlling the role of MAP. Our analysis also shows that species richness, especially the relative richness of AM tree species, had a significantly positive relationship with all types of tree C storage. Our findings have implications for improving temperate forest C sink and afforestation strategies: the increasing richness of AM trees has the potential to enhance the tree C sink and reduce the sensitivity of warming-induced tree growth benefits to changes in precipitation.

Seasonal Variation of Vegetation and Its Spatiotemporal Response to Climatic Factors in the Qilian Mountains, China

The purpose of this study is to reveal the seasonal difference in vegetation variation and its seasonal response to climate factors in the Qilian Mountains (QM) under the background of global warming. Based on the MOD13 A2 normalized difference vegetation index (NDVI) data and meteorological data, this study analyzed the spatiotemporal dynamics and stability of vegetation in different seasons by using the mean value method, trend analysis and stability analysis method, and discussed their seasonal responses to climatic factors based on the correlation analysis method. The results show that the vegetation cover in the QM experienced a significant upward trend in the past 21 years, but there were obvious spatial differences in vegetation change in different seasons. The growth rate of vegetation in summer was the fastest, and summer vegetation provided the most significant contribution to the growing season vegetation. The order of vegetation stability in the QM among the seasons was growing season > summer > spring > autumn. The vegetation change was obviously affected by temperature in spring, while it was mainly controlled by precipitation in the growing season and summer. The response of vegetation to climatic factors was not significant in autumn. Our results can provide important data support for ecological protection in the QM and socioeconomic development in the Hexi Corridor.

Phenology-based seasonal terrestrial vegetation growth response to climate variability with consideration of cumulative effect and biological carryover

Vegetation growth is influenced not only by climate variability but also by its past states. However, the differences in the degree of the climate variability and past states affecting vegetation growth over seasons are still poorly understood, particularly given the cumulative climate effects. Relying on the Normalized Difference Vegetation Index (NDVI) data from 1982 to 2014, the vegetation growing season was decomposed into three periods (sub-seasons) - green-up (GSgp), maturity (GSmp), and senescence (GSsp) - following a phenology-based definition. A distributed lag model was then utilized to analyze the time-lag effect of vegetation growth response to climatic factors including precipitation, temperature, and solar radiation during each sub-season. On this basis, the relative importance of climatic factors and vegetation growth carryover (VGC) effect on vegetation growth was quantified at the phenology-based seasonal scale. Results showed that the longest peak lag of precipitation, temperature, and solar radiation occurred in the GSmp, GSsp, and GSgp, with 1.27 (1.13 SD), 0.89 (1.02 SD), and 0.80 (1.04 SD) months, respectively. The influence of climate variability was strongest in the GSgp, and diminished over the season, while the opposite for the VGC effect. The relative influence of each climatic factor also varied between sub-seasons. Vegetation in more than 58% of areas was more affected by temperature in the GSgp, and the proportion decreased to 34.00% and 31.78% in the GSmp and GSsp, respectively. Precipitation and solar radiation acted as the dominant climatic factors in only 28.80% and 20.88% of vegetation areas in the GSgp, but they increased to 35.21%, 32.61% in the GSmp, and 38.20%, 30.02% in the GSsp, respectively. The increased regions influenced by precipitation were mainly in dry areas especially for the boreal and cool temperate climate zones, while increased regions influenced by solar radiation were primarily located in moist areas of mid-high latitudes of the Northern Hemisphere. By introducing the cumulative climate effect, our findings highlight seasonal patterns of vegetation growth affected by climate variability and the VGC effect. The results provide a more comprehensive perspective on climate-vegetation interactions, which may help us to accurately forecast future vegetation growth under accelerating global warming.

Compound hydroclimatic extremes in a semi-arid grassland: Drought, deluge, and the carbon cycle

Climate change is predicted to increase the frequency and intensity of extreme events including droughts and large precipitation events or "deluges." While many studies have focused on the ecological impacts of individual events (e.g., a heat wave), there is growing recognition that when extreme events co-occur as compound extremes, (e.g., a heatwave during a drought), the additive effects on ecosystems are often greater than either extreme alone. In this study, we assessed a unique type of extreme-a contrasting compound extreme-where the extremes may have offsetting, rather than additive ecological effects, by examining how a deluge during a drought impacts productivity and carbon cycling in a semi-arid grassland. The experiment consisted of four treatments: a control (average precipitation), an extreme drought (<5th percentile), an extreme drought interrupted by a single deluge (>95th percentile), or an extreme drought interrupted by the equivalent amount of precipitation added in several smaller events. We highlight three key results. First, extreme drought resulted in early senescence, reduced carbon uptake, and a decline in net primary productivity relative to the control treatment. Second, the deluge imposed during extreme drought stimulated carbon fluxes and plant growth well above the levels of both the control and the drought treatment with several additional smaller rainfall events, emphasizing the importance of precipitation amount, event size, and timing. Third, while the deluge's positive effects on carbon fluxes and plant growth persisted for 1 month, the deluge did not completely offset the negative effects of extreme drought on end-of-season productivity. Thus, in the case of these contrasting hydroclimatic extremes, a deluge during a drought can stimulate temporally dynamic ecosystem processes (e.g., net ecosystem exchange) while only partially compensating for reductions in ecosystem functions over longer time scales (e.g., aboveground net primary productivity).

Change Trend and Restoration Potential of Vegetation Net Primary Productivity in China over the Past 20 Years

As an important vegetation parameter and ecological index, vegetation net primary productivity (NPP) can intuitively reflect changes in the ecological environment and the level of the carbon budget. However, the change trend of NPP and its recovery potential in China over the past 20 years remain unclear. Here, we used trend analysis, multiple regression analysis and residual analysis methods to analyse the change trend in the NPP of China’s terrestrial ecosystems from 2000 to 2019, as well as the climax background, restoration status and restoration potential of the NPP of forest, grassland and desert ecosystems. The results showed that (1) the change in vegetation NPP in China from 2000 to 2019 showed a continuous upward trend, with a change slope of 2.39 gC/m2/a2, and the area with a positive slope of change accounted for 68.10% of the country’s land area. The contribution rates of meteorological conditions and human activities to vegetation NPP changes were 85.41% and 14.59%, respectively. (2) The results obtained by the regression analysis method of meteorological conditions based on nature reserves could reflect the zonal climax vegetation status to a large extent, and the obtained values had a smooth transition within each ecogeographical division and between each ecogeographical division, which truly reflected the law of gradual change in climate, vegetation and natural conditions. The annual total NPP of the climax background vegetation in China’s forest, grassland and desert ecosystems was approximately 2.76 ± 0.28 PgC, and the annual total NPP of the three ecosystems was 1.90 ± 0.2 PgC, 0.80 ± 0.07 PgC and 0.009 ± 0.0005 PgC, respectively. (3) The annual total vegetation NPP of the restoration status of China’s forest, grassland and desert ecosystems was 2.24 PgC, and the annual total vegetation NPP of the three was 1.54 PgC, 0.65 PgC and 0.007 PgC, respectively. Benefiting from the effective implementation of climate warming and humidification and ecological engineering, the agro-pastoral zone, the Loess Plateau, the eastern Sichuan Basin and the Greater Khingan Range had the most significant increases in the past 20 years. (4) The annual total vegetation NPP of China’s forest, grassland and desert ecosystem restoration potential was approximately 0.52 ± 0.28 PgC, which accounted for approximately 19.05% of the annual total NPP of the climax background vegetation. The annual total vegetation NPP of forest, grassland and desert ecosystems restoration status was 0.36 ± 0.2 PgC, 0.16 ± 0.07 PgC and 0.002 ± 0.0005 PgC, respectively; the restoration potential accounted for 18.80%, 9.67% and 23.95% of the climax background vegetation NPP, respectively. The deployment of ecological projects should fully consider the restrictive climate conditions for decision makers and ecological scholars, and the benefits and costs of the projects should be considered comprehensively.

Assessment of Climate Change and Human Activities on Vegetation Development in Northeast China

Vegetation in Northeast China (NEC) has faced dual challenges posed by climate change and human activities. However, the factors dominating vegetation development and their contribution remain unclear. In this study, we conducted a comprehensive evaluation of the response of vegetation in different land cover types, climate regions, and time scales to water availability from 1990 to 2018 based on the relationship between normalized difference vegetation index (NDVI) and the standardized precipitation evapotranspiration index (SPEI). The effects of human activities and climate change on vegetation development were quantitatively evaluated using the residual analysis method. We found that the area percentage with positive correlation between NDVI and SPEI increased with time scales. NDVI of grass, sparse vegetation, rain-fed crop, and built-up land as well as sub-humid and semi-arid areas (drylands) correlated positively with SPEI, and the correlations increased with time scales. The negatively correlated area was concentrated in humid areas or areas covered by forests and shrubs. Vegetation water surplus in humid areas weakens with warming, and vegetation water constraints in drylands enhance. Moreover, potential evapotranspiration had an overall negative effect on vegetation, and precipitation was a controlling factor for vegetation development in semi-arid areas. A total of 53% of the total area in NEC showed a trend of improvement, which is mainly attributed to human activities (93%), especially through the implementation of ecological restoration projects in NEC. The relative role of human activities and climate change in vegetation degradation areas were 56% and 44%, respectively. Our findings highlight that the government should more explicitly consider the spatiotemporal heterogeneity of the influence of human activities and water availability on vegetation under changing climate and improve the resilience of regional water resources. The relative proportions and roles map of climate change and human activities in vegetation change areas provide a basis for government to formulate local-based management policies.

Global evidence on the asymmetric response of gross primary productivity to interannual precipitation changes

Understanding gross primary productivity (GPP) response to precipitation (PPT) changes is essential for predicting land carbon uptake under increasing PPT variability and extremes. Previous studies found that ecosystem GPP may have an asymmetric response to PPT changes, leading to the inconsistency of GPP gains in wet years compared to GPP declines in dry years. However, it is unclear how the asymmetric responses vary among vegetation types and under different PPT variabilities. This study evaluated the global patterns of asymmetries of GPP response to different PPT changes using two state-of-science global GPP datasets. The result shows that under mild PPT changes (|ΔPPT| ≤ 25%), grasslands, savannas, shrublands, and tundra show positive asymmetric responses (i.e., larger GPP gains in wet years than GPP losses in dry years), while other vegetation types show negative asymmetric responses (i.e., larger GPP losses in dry years than GPP gains in wet years). Conversely, all vegetation types show negative GPP asymmetric responses to moderate (25% < |ΔPPT| ≤ 50%) and extreme (|ΔPPT| > 50%) PPT changes. Thus, we propose a new non-linear asymmetric GPP-PPT model that incorporates three modes with regards to vegetation types. Meanwhile, we found that the spatial patterns of asymmetry were mainly driven by PPT amount and variability. Stronger and negative asymmetries were found in areas with smaller PPT amount and variability, while positive asymmetries were found in areas with higher PPT variability. These findings promote our understanding of carbon dynamics under increased PPT variability and extremes and provide new insights for land models to better predict future carbon uptake and its feedback to climate change.

Data-Driven Artificial Intelligence Model of Meteorological Elements Influence on Vegetation Coverage in North China

Based on remote sensing data of vegetation coverage, observation data of basic meteorological elements, and support vector machine (SVM) method, this study develops an analysis model of meteorological elements influence on vegetation coverage (MEVC). The variations for the vegetation coverage changes are identified utilizing five meteorological elements (temperature, precipitation, relative humidity, sunshine hour, and ground temperature) in the SVM model. The performance of the SVM model is also evaluated on simulating vegetation coverage anomaly change by comparing with statistical model multiple linear regression (MLR) and partial least squares (PLS)-based models. The symbol agreement rates (SAR) of simulations produced by MLR, PLS, and SVM models are 55%, 57%, and 66%, respectively. The SVM model shows obviously better performance than PLS and MLR models in simulating meteorological elements-related interannual variation of vegetation coverage in North China. Therefore, the introduction of the intelligent analysis method in term of SVM in model development has certain advantages in studying the internal impact of meteorological elements on regional vegetation coverage. It can also be further applied to predict the future vegetation anomaly change.

Exploring Ecosystem Functioning in Spain with Gross and Net Primary Production Time Series

The main objective of this study is to analyze the spatial and temporal variability of gross and net primary production (GPP and NPP) in Peninsular Spain across 15 years (2004–2018) and determine the relationship of those carbon fluxes with precipitation and air temperature. A time series study of daily GPP, NPP, mean air temperature, and monthly standardized precipitation index (SPI) at 1 km spatial resolution is conducted to analyze the ecosystem status and adaptation to changing environmental conditions. Spatial variability is analyzed for vegetation and specific forest types. Temporal dynamics are examined from a multiresolution analysis based on the wavelet transform (MRA-WT). The Mann–Kendall nonparametric test and the Theil–Sen slope are applied to quantify the magnitude and direction of trends (increasing or decreasing) within the time series. The use of MRA-WT to extract the annual component from daily series increased the number of statistically significant pixels. At pixel level, larger significant GPP and NPP negative changes (p-value < 0.1) are observed, especially in southeastern Spain, eastern Mediterranean coastland, and central Spain. At annual temporal scale, forests and irrigated crops are estimated to have twice the GPP of rainfed crops, shrublands, grasslands, and sparse vegetation. Within forest types, deciduous broadleaved trees exhibited the greatest annual NPP, followed by evergreen broadleaved and evergreen needle-leaved tree species. Carbon fluxes trends were correlated with precipitation. The temporal analysis based on daily TS demonstrated an increase of accuracy in the trend estimates since more significant pixels were obtained as compared to annual resolution studies (72% as to only 17%).

Representation of Leaf-to-Canopy Radiative Transfer Processes Improves Simulation of Far-Red Solar-Induced Chlorophyll Fluorescence in the Community Land Model Version 5

Recent advances in satellite observations of solar-induced chlorophyll fluorescence (SIF) provide a new opportunity to constrain the simulation of terrestrial gross primary productivity (GPP). Accurate representation of the processes driving SIF emission and its radiative transfer to remote sensing sensors is an essential prerequisite for data assimilation. Recently, SIF simulations have been incorporated into several land surface models, but the scaling of SIF from leaf-level to canopy-level is usually not well-represented. Here, we incorporate the simulation of far-red SIF observed at nadir into the Community Land Model version 5 (CLM5). Leaf-level fluorescence yield was simulated by a parametric simplification of the Soil Canopy-Observation of Photosynthesis and Energy fluxes model (SCOPE). And an efficient and accurate method based on escape probability is developed to scale SIF from leaf-level to top-of-canopy while taking clumping and the radiative transfer processes into account. SIF simulated by CLM5 and SCOPE agreed well at sites except one in needleleaf forest (R ² > 0.91, root-mean-square error <0.19 W⋅m^-2⋅sr^-1⋅μm^-1), and captured the day-to-day variation of tower-measured SIF at temperate forest sites (R ² > 0.68). At the global scale, simulated SIF generally captured the spatial and seasonal patterns of satellite-observed SIF. Factors including the fluorescence emission model, clumping, bidirectional effect, and leaf optical properties had considerable impacts on SIF simulation, and the discrepancies between simulate d and observed SIF varied with plant functional type. By improving the representation of radiative transfer for SIF simulation, our model allows better comparisons between simulated and observed SIF toward constraining GPP simulations.

Assessment of the importance of increasing temperature and decreasing soil moisture on global ecosystem productivity using solar-induced chlorophyll fluorescence

The accurate assessment of the global gross primary productivity (GPP) of vegetation is the key to estimating the global carbon cycle. Temperature (Ts) and soil moisture (SM) are essential for vegetation growth. It is acknowledged that the global Ts has shown an increasing trend, yet SM has shown a decreasing trend. However, the importance of SM and Ts changes on the productivity of global ecosystems remains unclear, as SM and Ts are strongly coupled through soil-atmosphere interactions. Using solar-induced chlorophyll fluorescence (SIF) as a proxy for GPP and by decoupling SM and Ts changes, our investigation shows Ts plays a more important role in SIF in 60% of the vegetation areas. Overall, increased Ts promotes SIF by mitigating the resistance from SM's reduction. However, the importance of SM and Ts varies, given different vegetation types. The results show that in the humid zone, the variation of Ts plays a more important role in SIF, but in the arid and semi-arid zones, the variation of SM plays a more important role; in the semi-humid zone, the disparity in the importance of SM and Ts is difficult to unravel. In addition, our results suggest that SIF is very sensitive to aridity gradients in arid and semi-arid ecosystems. By decoupling the intertwined SM-Ts impact on SIF, our study provides essential evidence that benefits future investigation on the factors the influence ecosystem productivity at regional or global scales.

Limitations of soil moisture and formation rate on vegetation growth in karst areas

Vegetation changes in karst areas are controlled by the soil formation rate (SFR) and soil moisture (SM). However, little is known about their thresholds and global control patterns. To this end, based on high-precision climate and vegetation data for 2000-2014, using Pearson correlation analysis, the Hurst index, and change-point analysis, the thresholds of the SFR and SM in vegetation growth in karst areas were identified. Furthermore, a spatial map (0.125° × 0.125°) of the global karst ecosystem with a static/dynamic limitation zone was established. We found that the net primary productivity (NPP) in 70% of the global climate zones exhibited a dual restriction relationship with the SM and SFR. The limitations of the SFR and SM in vegetation growth were most obvious in subpolar and semi-arid climates. In addition, their ecological thresholds were 25.2 t km^-2 yr^-1 and 0.28 m³ m^-3, respectively. The static limitation of the SFR on the NPP in karst areas accounted for 28.37%, and the influence of the SM enhanced this limit (21.79%). The limitation of the SFR on vegetation was mainly concentrated in Boreal forests (17%), and the limitation of the SM was mainly concentrated in tropical savannas (12%). The NPP and the Normalized Difference Vegetation Index (NDVI) were the most sensitive to changes in the SM and SFR. Moreover, the analysis based on 14 ecologically limitation karst areas further revealed that the reduction in these factors may cause the tropical rain forest to experience degradation. It can be seen that the SM enhanced the limiting effect of the SFR on vegetation in karst areas. In short, this interpretation of karst vegetation limitations provides a deeper understanding of and approach to ecosystem evolution and vegetation restoration in these regions.

Effects of forest growth in different vegetation communities on forest catchment water balance

Forest ecosystems are critical for adjusting the dynamic balance of the hydrological cycle. This balance is affected by vegetation community types, phenology, and forest density. Previous long-term catchment-scale model studies have focused on changes in forest areas while ignoring the above factors. Since the 1980s, climate change caused by increases in atmospheric CO₂ levels has enhanced forest growth. Moreover, amendments to forest management policies, including intermediate cuttings caused by economic factors, have yielded unprecedented changes in forest ecosystems. In this study, we designed a methodology and created a credible model using the Soil and Water Assessment Tool (SWAT) that can precisely reflect water balance variations caused by different ecosystem situations during long-term changes in forest density. We focused on the Yamato River catchment in Western Japan, which includes three planted forests and one primeval forest, each markedly different with respect to vegetation community composition and management policy. In the process, we examined the ratio of coniferous vegetation and broad-leaved vegetation in different forest areas, used remote sensing methods to quantify the maximum and minimum leaf area index (LAI) of each forest region over 40 years, and calibrated the model by comparing the LAI growth curve, evapotranspiration, and streamflow with observed data. Moreover, we separated the decadal canopy evaporation, transpiration, and soil evaporation from the SWAT output results. We found that (1) forest evapotranspiration has increased in recent decades because of the above reasons; (2) in young or well-managed forests, the forest water balance may have changed significantly with forest growth. For long-term studies, it is necessary to distinguish the growth characteristics of different forests during different periods, and a detailed definition of a mixed forest is required. The forest parameters and growth characteristics are critical for understanding forest ecosystems and cannot be ignored at catchment-scale.

Analysis of Effects of Recent Changes in Hydrothermal Conditions on Vegetation in Central Asia

Understanding the relationship of hydrothermal conditions to vegetation changes is conducive to revealing the feedback mechanism connecting climate variations and vegetation. Based on the methods of Theil–Sen median analysis, and the Mann–Kendall trend test, this research investigated the spatiotemporal vegetation dynamics in Central Asia using the Normalized Difference Vegetation Index (NDVI) and grid climate data from 1982 to 2015. Further, the contributions of hydrothermal conditions to vegetation changes were quantified using a boosted regression tree model (BRT). The results demonstrated that the spatiotemporal characteristics of vegetation dynamics exhibited significant differences in different seasons, and most pixels showed increasing trends in the growing season and spring. Boosted regression tree analysis indicated that the contributions of hydrothermal conditions to vegetation dynamics exhibited temporal and spatial heterogeneity. During the annual, growing season, and summer examination periods, the contribution value of the increase in warming conditions (temperature or potential evapotranspiration) to vegetation degradation in the region due to the hydrothermal tradeoff effect (water) was 49.92%, 44.10%, and 44.95%, respectively. Moreover, the increase in warming conditions promoted vegetation growth, with a contribution value of 59.73% in spring. The contribution value of the increase in wetting conditions (precipitation or soil moisture) to vegetation growth was 48.46% in northern Central Asia, but the contribution value of the increase in warming conditions to vegetation degradation was 59.49% in Ustyurt Upland and the Aral Sea basin in autumn. However, the increase in warming conditions facilitated irrigation vegetation growth, with a contribution value of 59.86% in winter. The increasing potential evapotranspiration was the main factor affecting vegetation degradation in the Kyzylkum Desert and Karakum Desert during the annual, growing season, and autumn examination periods. Precipitation and soil moisture played decisive roles in vegetation dynamics in northern Central Asia during the growing season, summer, and autumn. This research provides reference information for ecological restoration in Central Asia.

Warming weakens the night-time barrier to global fire

Night-time provides a critical window for slowing or extinguishing fires owing to the lower temperature and the lower vapour pressure deficit (VPD). However, fire danger is most often assessed based on daytime conditions^1,2, capturing what promotes fire spread rather than what impedes fire. Although it is well appreciated that changing daytime weather conditions are exacerbating fire, potential changes in night-time conditions-and their associated role as fire reducers-are less understood. Here we show that night-time fire intensity has increased, which is linked to hotter and drier nights. Our findings are based on global satellite observations of daytime and night-time fire detections and corresponding hourly climate data, from which we determine landcover-specific thresholds of VPD (VPD_t), below which fire detections are very rare (less than 95 per cent modelled chance). Globally, daily minimum VPD increased by 25 per cent from 1979 to 2020. Across burnable lands, the annual number of flammable night-time hours-when VPD exceeds VPD_t-increased by 110 hours, allowing five additional nights when flammability never ceases. Across nearly one-fifth of burnable lands, flammable nights increased by at least one week across this period. Globally, night fires have become 7.2 per cent more intense from 2003 to 2020, measured via a satellite record. These results reinforce the lack of night-time relief that wildfire suppression teams have experienced in recent years. We expect that continued night-time warming owing to anthropogenic climate change will promote more intense, longer-lasting and larger fires.

Can Artificial Intelligence Help in the Study of Vegetative Growth Patterns from Herbarium Collections? An Evaluation of the Tropical Flora of the French Guiana Forest

A better knowledge of tree vegetative growth phenology and its relationship to environmental variables is crucial to understanding forest growth dynamics and how climate change may affect it. Less studied than reproductive structures, vegetative growth phenology focuses primarily on the analysis of growing shoots, from buds to leaf fall. In temperate regions, low winter temperatures impose a cessation of vegetative growth shoots and lead to a well-known annual growth cycle pattern for most species. The humid tropics, on the other hand, have less seasonality and contain many more tree species, leading to a diversity of patterns that is still poorly known and understood. The work in this study aims to advance knowledge in this area, focusing specifically on herbarium scans, as herbariums offer the promise of tracking phenology over long periods of time. However, such a study requires a large number of shoots to be able to draw statistically relevant conclusions. We propose to investigate the extent to which the use of deep learning can help detect and type-classify these relatively rare vegetative structures in herbarium collections. Our results demonstrate the relevance of using herbarium data in vegetative phenology research as well as the potential of deep learning approaches for growing shoot detection.

Legislative and functional aspects of different metrics used for ozone risk assessment to forests

Surface ozone (O₃) is a threat to forests by decreasing photosynthesis and, consequently, influencing the strength of land carbon sink. However, due to the lack of continuous surface O₃ measurements, observational-based assessments of O₃ impacts on forests are largely missing at hemispheric to global scales. Currently, some metrics are used for regulatory purposes by governments or national agencies to protect forests against the negative impacts of ozone: in particular, both Europe and United States (US) makes use of two different exposure-based metrics, i.e. AOT40 and W126, respectively. However, because of some limitations in these metrics, a new standard is under consideration by the European Union (EU) to replace the current exposure metric. We analyse here the different air quality standards set or proposed for use in Europe and in the US to protect forests from O₃ and to evaluate their spatial and temporal consistency while assessing their effectiveness in protecting northern-hemisphere forests. Then, we compare their results with the information obtained from a complex land surface model (ORCHIDEE). We find that present O₃ uptake decreases gross primary production (GPP) in 37.7% of the NH forested area of northern hemisphere with a mean loss of 2.4% year^-1. We show how the proposed US (W126) and the currently used European (AOT40) air quality standards substantially overestimate the extension of potential vulnerable regions, predicting that 46% and 61% of the Northern Hemisphere (NH) forested area are at risk of O₃ pollution. Conversely, the new proposed European standard (POD1) identifies lower extension of vulnerability regions (39.6%).

Quantitatively Assessing the Impact of Driving Factors on Vegetation Cover Change in China’s 32 Major Cities

After 2000, China’s vegetation underwent great changes associated with climate change and urbanization. Although many studies have been conducted to quantify the contributions of climate and human activities to vegetation, few studies have quantitatively examined the comprehensive contributions of climate, urbanization, and CO2 to vegetation in China’s 32 major cities. In this study, using Global Land Surface Satellite (GLASS) fractional vegetation cover (FVC) between 2001 and 2018, we investigated the trend of FVC in China’s 32 major cities and quantified the effects of CO2, urbanization, and climate by using generalized linear models (GLMs). We found the following: (1) From 2001 to 2018, the FVC in China generally illustrated an increasing trend, although it decreased in 23 and 21 cities in the core area and expansion area, respectively. (2) Night light data showed that the urban expansion increased to varying degrees, with an average increasing ratio of approximately 168%. The artificial surface area increased significantly, mainly from cropland, forest, grassland, and tundra. (3) Climate factors and CO2 were the major factors that affected FVC change. The average contributions of climate factors, CO2, and urbanization were 40.6%, 39.2%, and 10.6%, respectively. This study enriched the understanding of vegetation cover change and its influencing factors, helped to explain the complex biophysical mechanism between vegetation and environment, and guided sustainable urban development.

Spatiotemporal dynamics of vegetation in China from 1981 to 2100 from the perspective of hydrothermal factor analysis

The increased growth of vegetation has the potential to slow global climate warming. Therefore, analyzing and predicting the response assessment of Chinese vegetation to climate change is of great significance to studies of global warming. In this paper, we examine the spatiotemporal dynamics of vegetation leaf area index (LAI) values in China from 1981 to 2017 and their correlations with meteorological (hydrothermal) factors based on trend analysis and correlation analysis. We further construct an LAI prediction model based on hydrothermal conditions. The climate data obtained under different scenarios in the CMIP5 and CMIP6 climate models were used to predict the dynamic change trend of vegetation LAI from 2021 to 2100. The results show that most areas of China (72.82%) showed an improving trend in vegetation LAI from 1981 to 2017, during which the annual average LAI value increased at a rate of 0.0029 year-1. Vegetation LAI in China was significantly correlated with climatic factors (temperature, precipitation, and evapotranspiration), and the LAI prediction model constructed based on hydrothermal conditions had a high accuracy (Pearson's Cor value is 0.9729). From 2021 to 2100, approximately 2/3 of China's vegetation LAI area showed an improvement trend, and the impact of climate change on vegetation LAI predictions under the high emission scenario was greater than that under the low emission scenario. This research can provide a basis for studies on the climatic drivers of vegetation change and the global vegetation dynamic model.

Foliar sieve elements: Nexus of the leaf

In this review, a central position of foliar sieve elements in linking leaf structure and function is explored. Results from studies involving plants grown under, and acclimated to, different growth regimes are used to identify significant, linear relationships between features of minor vein sieve elements and those of 1) leaf photosynthetic capacity that drives sugar synthesis, 2) overall leaf structure that serves as the platform for sugar production, 3) phloem components that facilitate the loading of sugars (companion & phloem parenchyma cells), and 4) the tracheary elements that import water to support photosynthesis (and stomatal opening) as well as mass flow of sugars out of the leaf. Despite comprising only a small fraction of physical space within the leaf, sieve elements represent a hub through which multiple functions of the leaf intersect. As the conduits for export of energy-rich carbohydrates, essential mineral nutrients, and information carriers, sieve elements play a central role in fueling and orchestrating development and function of the plant as well as, by extension, of natural and human communities that depend on plants as producers and partners in the global carbon cycle.

Heat and drought impact on carbon exchange in an age-sequence of temperate pine forests

BACKGROUND

Most North American temperate forests are plantation or regrowth forests, which are actively managed. These forests are in different stages of their growth cycles and their ability to sequester atmospheric carbon is affected by extreme weather events. In this study, the impact of heat and drought events on carbon sequestration in an age-sequence (80, 45, and 17 years as of 2019) of eastern white pine (Pinus strobus L.) forests in southern Ontario, Canada was examined using eddy covariance flux measurements from 2003 to 2019.

RESULTS

Over the 17-year study period, the mean annual values of net ecosystem productivity (NEP) were 180 ± 96, 538 ± 177 and 64 ± 165 g C m^-2 yr^-1 in the 80-, 45- and 17-year-old stands, respectively, with the highest annual carbon sequestration rate observed in the 45-year-old stand. We found that air temperature (Ta) was the dominant control on NEP in all three different-aged stands and drought, which was a limiting factor for both gross ecosystem productivity (GEP) and ecosystems respiration (RE), had a smaller impact on NEP. However, the simultaneous occurrence of heat and drought events during the early growing seasons or over the consecutive years had a significant negative impact on annual NEP in all three forests. We observed a similar trend of NEP decline in all three stands over three consecutive years that experienced extreme weather events, with 2016 being a hot and dry, 2017 being a dry, and 2018 being a hot year. The youngest stand became a net source of carbon for all three of these years and the oldest stand became a small source of carbon for the first time in 2018 since observations started in 2003. However, in 2019, all three stands reverted to annual net carbon sinks.

CONCLUSIONS

Our study results indicate that the timing, frequency and concurrent or consecutive occurrence of extreme weather events may have significant implications for carbon sequestration in temperate conifer forests in Eastern North America. This study is one of few globally available to provide long-term observational data on carbon exchanges in different-aged temperate plantation forests. It highlights interannual variability in carbon fluxes and enhances our understanding of the responses of these forest ecosystems to extreme weather events. Study results will help in developing climate resilient and sustainable forestry practices to offset atmospheric greenhouse gas emissions and improving simulation of carbon exchange processes in terrestrial ecosystem models.

Decoupling Relationship between Urbanization and Carbon Sequestration in the Pearl River Delta from 2000 to 2020

Rapid urbanization has a significant impact on the ecological environment. Net primary productivity (NPP) can effectively reflect the growth of urban vegetation and the carbon sequestration capacity of an ecosystem. Taking the rapidly growing Pearl River Delta (PRD) as our study area, the relative contributions of human activities and climate change to NPP were analyzed using an improved two-step method based on residual trend analysis. The decoupling index was used to compare the coordinated development of socioeconomic factors and the NPP in different time periods. This study lays the foundation for formulating comprehensive and reasonable urban low-carbon development measures. The results showed that (1) NPP decreased significantly before 2010, but by 2019, NPP in most regions of the PRD showed a slight increase. The NPP of new urban land was better than that of original urban land. (2) The negative contribution of climatic factors to NPP was clearer than that of human activities, and human activities contributed positively to NPP outside urban land. (3) The decoupling status of socioeconomic factors and NPP is improving, and the degree of decoupling in 2010–2019 was higher than that in 2000–2010. In conclusion, as the first forest urban agglomeration in China, the PRD has shown a good implementation of carbon sequestration policies, which can provide a reference for the coordinated development of urbanization and carbon sequestration.

Grassland Phenology Response to Climate Conditions in Biobio, Chile from 2001 to 2020

Plant phenology is affected by climate conditions and therefore provides a sensitive indicator to changes in climate. Studying the evolution and change in plant phenology aids in a better understanding of and predicting changes in ecosystems. Vegetation Indices (VIs) have been recognized for their utility in indicating vegetation activity. Understanding climatic variables and their relationship to VI support the knowledge base of how ecosystems are changing under a new climatic scenario. This study evaluates grassland growth phenology in the Biobio, Chile, biweekly with Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series. Four growth parameters for the six agro-climatic regions were analyzed from 2001 to 2020: start and end of the season, time and value of maximum NDVI. For this purpose, the NDVI time series were smoothed using Savitzky–Golay filtering. In addition, by using monthly gridded database climate data, we studied correlations between phenology markers and rainfall, maximum temperature and minimum temperature. The results show that both the start and end of the growing season did not significantly change; however, all agro-climatic regions grow faster and more vigorously. Thus, climatic conditions in Biobio have become more conducive to grassland growth over the 2001–2020 period.

Complex effects of moisture conditions and temperature enhanced vegetation growth in the Arid/humid transition zone in Northern China

Ecosystems in the arid/humid transition zone (AHTZ) of northern China are highly sensitive to climate change and human activities. Accurately assessing the impact of climate change on these ecosystems is important for effectively reducing the risks faced by them under future climate change. In this study, the leaf area index during the selected growing season (LAI_GS) was used as an indicator for vegetation activity. After comparison different potential indicators, the growing season temperature (T_GS) was used to indicate temperature, and the growing season aridity index (AI_GS), which considers the regional water budget, was used to indicate moisture rather than precipitation, which is used more commonly. Correlation analysis and residual trends were used to study the influence of climatic and non-climatic factors on vegetation activity in the AHTZ from 1982 to 2016. The results for regions where LAI_GS increased significantly (0.037/10 yr, 53.58% of the study area), the regions where LAI_GS dominated by non-climatic factors (18.40%) was larger than areas dominated by climatic factors (9.61%). However, most (25.57%) of the regions in the selected study area were mainly driven by both climatic and non-climatic factors. In about half (49.73%) of the climate-affected regions, significant changes in LAI_GS were driven jointly by T_GS and AI_GS. These regions were mainly in the northern and western Loess Plateau. The regions where changes were driven mainly by AI_GS, and those where changes were driven mainly by T_GS, each accounted for nearly a quarter of climate-affected regions (24.87% and 25.40%, respectively). The former regions were on the western Songliao Plain, the northern North China Plain, and the northern Loess Plateau, and the latter regions were in the northern Greater Khingan Mountains, on the southern North China Plain, in the western mountains of North China, and on the southern Loess Plateau.

Vegetation Dynamics Due to Urbanization in the Coastal Cities along the Maritime Silk Road

Substantial research indicates the effects of urbanization on vegetation cover; however, a view of this scenario from a regional scale is absent. Nowadays, coastal cities have become the new engine for the development of countries in coastal areas. To capture the effects of rapid urbanization on vegetation dynamics, 35 coastal cities along the Maritime Silk Road (MSR) were selected to study the related research using quantitative tools. We calculated spatiotemporal trends of vegetation dynamics along an urban development intensity (UDI) gradient using the MODIS-enhanced vegetation index (EVI) during the period of 2000–2015. We found a significant reduction (p < 0.05) in the EVI in the core area against that in the rural area (ΔEVI) of 14 cities and an insignificant change in vegetation in the peri-urban areas or urban outskirts. EVI decreased significantly along the UDI gradients in 12 coastal cities with a linear pattern and in seven coastal cities with a concave pattern; only Bangkok exhibited a convex pattern. The nonlinear pattern between the EVI and UDI reflected the fact that vegetation dynamics were affected by complicated factors, including climate change and human interventions, over a long period of time. In conclusion, our work provided a scientific reference for the sustainable development of coastal cities along the MSR; further work is necessary to explore the mechanic details of the positive and negative influences of urban factors and related policies on vegetation conditions.

Declining Growth Response of Siberian Spruce to Climate Variability on the Taiga–Tundra Border in the Putorana Mountains (Northwest Siberia)

Global warming is most pronounced at high latitudes where temperatures increase twice as fast as the global average. Boreal forest growth is generally limited by low temperatures, so elevated temperature is supposed to enhance biomass production and carbon sequestration. A large amount of evidence has recently shown inconsistent responses of tree growth derived from annual tree rings to increasing temperature. We studied Siberian spruce growth in the remote and isolated Putorana Mts, Western Siberia in populations at its natural distribution limit. Tree ring cores were sampled along vertical transect in 100, 200 and 350 m a.s.l. as the aim was to identify the tree growth rate at different altitudes. Detailed sampling site descriptions served to identify possible factors controlling the growth rate in extremely heterogeneous environments. Monthly climate data for the period 1900–2020 were extracted from the gridded CRU database. Tree ring chronologies confirmed long-lasting limited growth, and despite high year-to-year ring width variability, synchronous growth at vertical study sites dominantly controlled by climate. The positive tree ring growth response to summer temperature was significant for most of the 20th century but dramatically changed in recent decades, when unusually warm summers were reported. There was no, or even a negative growth rate correlation with precipitation, which indicates a sufficient water supply at the study sites. Elevated temperature in this region with a continental climate might turn the study localities to water-limited areas with many negative consequences on tree growth and related ecosystem services.

Assessment of ozone risk to Central European forests: Time series indicates perennial exceedance of ozone critical levels

In this study, the stomatal ozone (O₃) fluxes were investigated at five low-elevation forest sites in Western Germany (Rhineland Palatinate) over the time period 1998-2019. The Phytotoxic Ozone Dose with an hourly threshold of uptake (Y), to represent the detoxification capacity of trees (POD1 in mmol m^-2 per leaf area, with Y = 1 nmol O₃ m^-2 s^-1), and the number of exceedances of the O₃ critical level of 5.2 mmol O₃ m^-2 per leaf area for European beech and 9.2 mmol O₃ m^-2 per leaf area for Norway spruce were calculated by using the DO₃SE model. A Principal Component Analysis revealed strong correlations between daily O₃ concentrations, daytime O₃ (for hours with global radiation exceeding 50 W m^-2), POD1, global radiation, vapor pressure deficit and air temperature. Moreover, a significant correlation was obtained between POD1 and soil water content (SWC) at all sites (r = 0.51-0.74). The Random Forests Analysis confirmed that the SWC is the most important predictor of stomatal O₃ fluxes. The soil water supply is very important for POD1 estimation, because drought decreases stomatal conductance, leading to a reduction of transpiration, as well as to lower O₃ uptake through stomata. Between 1998 and 2019, the drier and warmer climate induced a soil drought (on average, SWC - 0.15 % per year) leading to lower stomatal O₃ uptake by forests (- 0.36 mmol O₃ m^-2 per year). Hence, during growing seasons with sufficient water supply and often lower O₃ levels compared to hot and dry periods, forests are at higher O₃ risk than during hot and dry periods when the drought stress is more significant than O₃ stress despite relatively higher O₃ levels. Irrespective of these differences in O₃ uptake between relatively cool and humid as compared to relatively hot and dry years in the study region, the Critical Level for O₃ was exceeded in late spring/early summer (May/June) during all 22 years. Risk assessment for the protection of European forests, which is urgently needed due to the forests current critical state after several successive years of drought and exceedance of the O₃ critical level in large areas of Europe, should therefore become flux-based to account for the inter-twined effects of drought and O₃ on the physiology and health of forest trees in the region. For stomatal O₃ fluxes estimation, a better soil water and leaf parameterization is needed e.g., by taking into account both O₃- and drought-induced effects.

Climate change scenarios of increased CO2 and temperature affect a coral reef peracarid (Crustacea) community

The effects of applying scenarios of increasing CO₂ and temperature, using a mesocosm experiment, on the structure of a macrofaunal coral reef peracarid community were investigated for the first time. Samples were taken from artificial substrate units (ASUs), colonized by macrofauna from the coral reef subtidal zone of Serrambi beach (Brazil). In the laboratory, the ASUs were exposed to a Control (Ctrl) treatment and three climate change Scenarios (Sc) (increase of T° of 0.6, 2, and 3 °C, and pH drop of 0.1, 0.3, and 0.7 units for Sc I, II and III respectively), and were collected after 15 and 29 days of exposure. Our results showed that the effect of different temperature and acidity levels under experimental climate change scenarios significantly impacted density, diversity and community structure. Major differences were observed when applying Sc II and III. Peracarida also showed a reduction in specimen number when comparing both exposure times. Overall, Amphipoda, Tanaidacea and Isopoda communities all displayed a reduction in the number of individuals for both scenarios and exposure time factors, while Cumacea responded negatively in all scenarios, suggesting that these individuals were more sensitive to the experimental conditions. Dissimilarities were greatest between the Ctrl and Sc III, particularly after 29 days. Two species, Elasmopus longipropodus (Amphipoda) and Chondrochelia dubia (Tanaidacea), greatly contributed to these dissimilarities. This study demonstrates that even an intermediate level of increasing ocean temperature and acidification will negatively impact the structure of the Peracarida macrofaunal community on coral reefs. Also demonstrates that different species of Peracarida exhibit divergent response patterns, highlighting the specific responses of these taxa to the impacts of environmental stressors. These outcomes highlight the importance of studying the effects of climate change on benthic peracarids, especially because they incubate their eggs. This characteristic can reduce migration potential and thereby reduces the individual's ability to disperse in response to a changing environment.

Interannual variability of vegetation sensitivity to climate in China

Many studies have assessed the relative sensitivity of ecosystems to climate change, and even optimized climate states from long-term averages to infer short-term changes, but how ecosystem sensitivity and its relationships with climate variability vary over time remains elusive. By combining the vegetation sensitivity index (VSI) and a 15 year moving window, we analyzed interannual variability in spatiotemporal patterns of vegetation sensitivity to short-term climate variability and its correlations with climatic factors in China over the past three decades (1982-2015). We demonstrated that vegetation sensitivity shows high spatial heterogeneity, and varies with vegetation type and climate region. Generally, vegetation in the southwest and mountainous regions was more sensitive, especially coniferous forests and isolated shrubland patches. Comparatively, vegetation in dry regions was less sensitive to climate variability than in wetter climates. Due to frequent climate variability in the early 1990s, a large increase in the VSI was detected in 1996. Significant increases in the interannual variability of vegetation sensitivity were observed in greater than 23.7% of vegetated areas and decreases in only 4.2%. Solar radiation was the dominant climate driver of vegetation sensitivity, followed by temperature and precipitation. However, climate controls are not invariable across a range of climatic conditions, such as precipitation exerted an increasing influence on changes of vegetation sensitivity. Quantitative analyses of ecosystem sensitivity to climate variability such as ours are vital to identify which regions and vegetation are most vulnerable to future climate variability.

Projected Changes in Terrestrial Vegetation and Carbon Fluxes under 1.5 °C and 2.0 °C Global Warming

The terrestrial ecosystem plays a vital role in regulating the exchange of carbon between land and atmosphere. This study investigates how terrestrial vegetation coverage and carbon fluxes change in a world stabilizing at 1.5 °C and 2 °C warmer than pre-industrial level. Model results derived from 20 Earth System Models (ESMs) under low, middle, and high greenhouse emission scenarios from CMIP5 and CMIP6 are employed to supply the projected results. Although the ESMs show a large spread of uncertainties, the ensemble means of global LAI are projected to increase by 0.04 ± 0.02 and 0.08 ± 0.04 in the 1.5 and 2.0 °C warming worlds, respectively. Vegetation density is projected to decrease only in the Brazilian Highlands due to the decrease of precipitation there. The high latitudes in Eurasia are projected to have stronger increase of LAI in the 2.0 °C warming world compared to that in 1.5 °C warming level caused by the increase of tree coverage. The largest zonal LAI is projected around 70° N while the largest zonal NPP is projected around 60° N and equator. The zonally inhomogeneous increase of vegetation density and productivity relates to the zonally inhomogeneous increase of temperature, which in turn could amplify the latitudinal gradient of temperature with additional warming. Most of the ESMs show uniform increases of global averaged NPP by 10.68 ± 8.60 and 15.42 ± 10.90 PgC year−1 under 1.5 °C and 2.0 °C warming levels, respectively, except in some sparse vegetation areas. The ensemble averaged NEE is projected to increase by 3.80 ± 7.72 and 4.83 ± 10.13 PgC year−1 in the two warming worlds. The terrestrial ecosystem over most of the world could be a stronger carbon sink than at present. However, some dry areas in Amazon and Central Africa may convert to carbon sources in a world with additional 0.5 °C warming. The start of the growing season in the northern high latitudes is projected to advance by less than one month earlier. Five out of 10 CMIP6 ESMs, which use the Land Use Harmonization Project (LUH2) dataset or a prescribed potential vegetation distribution to constrain the future change of vegetation types, do not reduce the model uncertainties in projected LAI and terrestrial carbon fluxes. This may suggest the challenge in optimizing the carbon fluxes modeling in the future.

Different increase rate in body mass of two marten species due to climate warming potentially reinforces interspecific competition

Many species show spatial variation in body size, often associated with climatic patterns. Studying species with contrasting geographical patterns related to climate might help elucidate the role of different drivers. We analysed changes in the body mass of two sympatric medium-sized carnivores—pine marten (Martes martes) and stone marten (Martes foina)—across Europe over 59 years. The body mass of pine marten increased with decreasing latitude, whereas stone marten body mass varied in a more complex pattern across its geographic range. Over time, the average body mass of pine martens increased by 255 g (24%), while stone marten by 86 g (6%). The greatest increase of body mass along both martens’ geographic range was observed in central and southern Europe, where both species occur in sympatry. The body mass increase slowed down over time, especially in allopatric regions. The average pine/stone marten body mass ratio increased from 0.87 in 1960 to 0.99 in 2019, potentially strengthening the competition between them. Thus, a differential response in body size to several drivers over time might have led to an adaptive advantage for pine martens. This highlights the importance of considering different responses among interacting species when studying animal adaptation to climate change.

Elevated growth and biomass along temperate forest edges

Fragmentation transforms the environment along forest edges. The prevailing narrative, driven by research in tropical systems, suggests that edge environments increase tree mortality and structural degradation resulting in net decreases in ecosystem productivity. We show that, in contrast to tropical systems, temperate forest edges exhibit increased forest growth and biomass with no change in total mortality relative to the forest interior. We analyze >48,000 forest inventory plots across the north-eastern US using a quasi-experimental matching design. At forest edges adjacent to anthropogenic land covers, we report increases of 36.3% and 24.1% in forest growth and biomass, respectively. Inclusion of edge impacts increases estimates of forest productivity by up to 23% in agriculture-dominated areas, 15% in the metropolitan coast, and +2% in the least-fragmented regions. We also quantify forest fragmentation globally, at 30-m resolution, showing that temperate forests contain 52% more edge forest area than tropical forests. Our analyses upend the conventional wisdom of forest edges as less productive than intact forest and call for a reassessment of the conservation value of forest fragments.