Accelerated rate of vegetation green-up related to warming at northern high latitudes

Weakened connection between spring leaf-out and autumn senescence in the Northern Hemisphere

Vegetation autumn phenology is critical in regulating the ecosystem carbon cycle and regional climate. However, the dominant drivers of autumn senescence and their temporal shifts under climate change remain poorly understood. Here, we conducted a multi-factor analysis considering both direct climatic controls and biological carryover effects from start-of-season (SOS) and seasonal peak vegetation activities on the end-of-season (EOS) to fill these knowledge gaps. Combining satellite and ground observations across the northern hemisphere, we found that carryover effects from early-to-peak vegetation activities exerted greater influence on EOS than the direct climatic controls on nearly half of the vegetated land. Unexpectedly, the carryover effects from SOS on EOS have significantly weakened over recent decades, accompanied by strengthened climatic controls. Such results indicate the weakened constraint of leaf longevity on senescence due to prolonged growing season in response to climate change. These findings underscore the important role of biological carryover effects in regulating vegetation autumn senescence under climate change, which should be incorporated into the formulation and enhancement of phenology modules utilized in land surface models.

Characteristics and drivers of vegetation productivity sensitivity to increasing CO2 at Northern Middle and High Latitudes

Understanding and accurately predicting how the sensitivity of terrestrial vegetation productivity to rising atmospheric CO2 concentration (β) is crucial for assessing carbon sink dynamics. However, the temporal characteristics and driving mechanisms of β remain uncertain. Here, observational and CMIP6 modeling evidence suggest a decreasing trend in β at the Northern Middle and High Latitudes during the historical period of 1982-2015 (-0.082 ± 0.005% 100 ppm-1 year-1). This decreasing trend is projected to persist until the end of the 21st century (-0.082 ± 0.005% 100 ppm-1 year-1 under SSP370 and -0.166 ± 0.006% 100 ppm-1 year-1 under SSP585). The declining β indicates a weakening capacity of vegetation to mitigate warming climates, posing challenges for achieving the temperature goals of the Paris Agreement. The rise in vapor pressure deficit (VPD), that triggers stomata closure and weakens photosynthesis, is considered as the dominated factor contributing to the historical and future decline in β, accounting for 62.3%-75.2% of the effect. Nutrient availability and water availability contribute 15.7%-21.4% and 8.5%-16.3%, respectively. These findings underscore the significant role of VPD in shaping terrestrial carbon sink dynamics, an aspect that is currently insufficiently considered in many climate and ecological models.

An emergent constraint on the thermal sensitivity of photosynthesis and greenness in the high latitude northern forests

Despite the general consensus that the warming over the high latitudes northern forests (HLNF) has led to enhanced photosynthetic activity and contributed to the greening trend, isolating the impact of temperature increase on photosynthesis and greenness has been difficult due to the concurring influence of the CO2 fertilization effect. Here, using an ensemble of simulations from biogeochemical models that have contributed to the Trends in Net Land Atmosphere Carbon Exchange project (TRENDY), we identify an emergent relationship between the simulation of the climate-driven temporal changes in both gross primary productivity (GPP) and greenness (Leaf Area Index, LAI) and the model's spatial sensitivity of these quantities to growing-season (GS) temperature. Combined with spatially-resolved observations of LAI and GPP, we estimate that GS-LAI and GS-GPP increase by 17.0 ± 2.4% and 24.0 ± 3.0% per degree of warming, respectively. The observationally-derived sensitivities of LAI and GPP to temperature are about 40% and 71% higher, respectively, than the mean of the ensemble of simulations from TRENDY, primarily due to the model underestimation of the sensitivity of light use efficiency to temperature. We estimate that the regional mean GS-GPP increased 28.2 ± 5.1% between 1983-1986 and 2013-2016, much larger than the 5.8 ± 1.4% increase from the CO2 fertilization effect implied by Wenzel et al. This suggests that warming, not CO2 fertilization, is primarily responsible for the observed dramatic changes in the HLNF biosphere over the last century.

Decoupling the effects of air temperature change on soil erosion in Northeast China

Changes in the air temperature tend to indirectly affect soil erosion by influencing rainfall, vegetation growth, economic development, and agricultural activities. In this study, the partial least squares-structural equation model (PLS-SEM) was used to decouple the impacts of temperature change on soil erosion in Northeast China from 2001 to 2019, and the indirect effect of temperature change on the pathways of natural and socioeconomic factors was analyzed. The results showed that temperature increase in Northeast China caused an increase in soil erosion by increasing rainfall and promoting economic development. Under the pathway of natural factors, in spring, the promoting effect on soil erosion under the influence of temperature change on rainfall was greater than the inhibiting effect on soil erosion under by the influence of temperature change on vegetation. In summer, the opposite effect was observed. Under the pathway of natural factors, over time, the promoting effect of temperature increase on soil erosion increased by 22.7%. Under the pathway of socioeconomic factors, temperature change not only aggravated soil erosion by promoting economic development, but also indirectly increased investments in agriculture and water conservation by improving the economy, thus inhibiting soil erosion to a certain extent. Over time, the contribution of temperature change to soil erosion through socioeconomic pathway was reduced by 44.4%. When the pathway of natural factors is compared with that of socioeconomics factors, temperature change imposed a more notable effect on the change in soil erosion through the socioeconomic pathway, indicating that human activities are the driving factors with a greater effect on soil erosion. Based on this, reasonable human intervention is an important means to alleviate soil erosion aggravation caused by rising temperatures.

Increased impact of the El Niño-Southern Oscillation on global vegetation under future warming environment

There are broad effects of vegetation changes on regional climate, carbon budget, the water cycle, and ecosystems' productivity. Therefore, further knowledge of the drivers of future vegetation changes is critical to mitigate the influences of global warming. The El Niño-Southern Oscillation (ENSO) is a major mode of interannual climate variability and is likely to affect vegetation on the global scale. Nonetheless, little is known about the causal impacts of ENSO on future vegetation cover with changes in land use and a warming environment. Here, we examined the connections between ENSO and vegetation using leaf area index (LAI) data over the period 2015-2100 from Coupled Modeling Intercomparison Project Phase 6. Our findings indicate that, compared with the historical period 1915-2000, the vegetated areas influenced by ENSO are projected to rise by approximately 55.2% and 20.7% during the twenty-first century of the scenarios SSP2-4.5 and SSP5-8.5, respectively. Though uncertainty for the causal link between ENSO and vegetation changes remains in several regions (i.e., parts of North America, southern Australia, and western Asia), ENSO signature on LAI variations is robust over northern Australia, Amazonia, and parts of Southeast Asia. These results indicate that the influences of ENSO on global vegetation may strengthen in the future.

Negative relationship between photosynthesis and late-stage canopy development and senescence over Tibetan Plateau

Canopy greening, which is associated with significant canopy structure changes, is the most notable signal of ecosystem changes in response to anthropogenic climate change. However, our knowledge of the changing pattern of canopy development and senescence, and its endogenous and climatic drivers is still limited. Here, we used the Normalized Difference Vegetation Index (NDVI) to quantify the changes in the speed of canopy development and senescence over the Tibetan Plateau (TP) during 2000-2018, and used a solar-induced chlorophyll fluorescence dataset as a proxy for photosynthesis, in combination with climate datasets to decipher the endogenous and climatic drivers of the interannual variation in canopy changes. We found that the canopy development during the early green-up stage (April-May) is accelerating at a rate of 0.45-0.8 × 10^-3  month^-1  year^-1 . However, this accelerating canopy development was largely offset by a decelerating canopy development during June and July (-0.61 to -0.51 × 10^-3  month^-1  year^-1 ), leading to the peak NDVI over the TP increasing at a rate of only one fifth of that in northern temperate regions, and less than one tenth of that in the Arctic and boreal regions. During the green-down period, we observed a significant accelerating canopy senescence during October. Photosynthesis was found to be the dominant driver for canopy changes over the TP. Increasing photosynthesis stimulates canopy development during the early green-up stage. However, slower canopy development and accelerated senescence was found with larger photosynthesis in late growth stages. This negative relationship between photosynthesis and canopy development is probably linked to the source-sink balance of plants and shifts in the allocation regime. These results suggest a sink limitation for plant growth over the TP. The impact of canopy greening on the carbon cycle may be more complicated than the source-oriented paradigm used in current ecosystem models.

Global methyl halide emissions from biomass burning during 2003-2021

Methyl halides (CH₃Cl, CH₃Br, and CH₃I) are ozone-depleting substances. Biomass burning (BB) is an important source of methyl halides. The temporal variations and global spatial distribution of BB methyl halide emissions are unclear. Thus, global methyl halide emissions from BB during 2003-2021 were estimated based on satellite data. A significant decreasing trend (p < 0.01) in global methyl halide emissions from BB was found between 2003 and 2021, with CH₃Cl emissions decreasing from 302 to 220 Gg yr^-1, CH₃Br emissions decreasing from 16.5 to 11.7 Gg yr^-1, and CH₃I emissions decreasing from 8.9 to 6.1 Gg yr^-1. From a latitudinal perspective, the northern high-latitude region (60-90° N) was the only latitude zone with significant increases in BB methyl halide emissions (p < 0.01). Based on an analysis of the drivers of BB methyl halide emissions, emissions from cropland, grassland, and shrubland fires were more correlated with the burned area, while BB emissions from forest fires were more correlated with the emissions per unit burned area. The non-BB emissions of CH₃Cl increased from 4749 Gg yr^-1 in 2003 to 4882 Gg yr^-1 in 2020, while those of CH₃Br decreased from 136 Gg yr^-1 in 2003 to 118 Gg yr^-1 in 2020 (global total CH₃I emissions are not available). The finding indicates that global CH₃Cl and CH₃Br emissions from sources besides BB increased and decreased during 2003-2020. Based on our findings, not only searching for unknown sources is important, but also re-evaluating known sources is necessary for addressing methyl halide emissions.

Revegetation affects the response of land surface phenology to climate in Loess Plateau, China

Land surface phenology (LSP), defined as the plant's growth rhythm retrieved from satellite sensing products, is proven to shift with climate change and affect the carbon cycles of terrestrial ecosystems. Global afforested area is largely increasing and consequently affecting local and global climate. However, how and to what extent revegetation affects LSP remains relatively unexplored. Here we investigated the difference in four LSPs (i.e., greenup, maturity, senescence, and dormancy) and the response of LSP to climate between restored and native vegetation on Loess Plateau, China, where a remarkable process of vegetation restoration happened during 1982-2015. Most study regions showed a longer growing season (LOS) over time, specifically, with a slight delay in greenup but a relatively large delay in senescence. We found that air temperature was the dominant factor affecting greenup and maturity, while precipitation mostly controlled the senescence and dormancy in the study area. Under similar climate conditions, the LSP of restored vegetation (i.e., restored forest and grassland) showed a significant difference (p < 0.05) from native ones during 1999-2015. Compared to the native forest, restored forest from cropland and grassland showed a delayed greenup date by 0.3 and 3.6 days (p < 0.05) and an advanced dormancy date of 6.6 and 9.0 days (p < 0.05), respectively. Furthermore, the restored vegetation became less sensitive to air temperature than native vegetation, while the restored forest was more sensitive to precipitation, and its growth was affected by the water limitation to a larger extent in the study area. Our study highlights the necessity of considering land use management and its effect on the LSP change to better understand the effect of afforestation on global climate and carbon cycles.

Spatio-temporal changes in the speed of canopy development and senescence in temperate China

China has been suggested to be the country with the largest vegetation greenness over the last four decades. In this study, we investigated the change in the speed of canopy development and senescence as well as its linkage with climate at monthly scale across temperate China, using satellite-derived Normalized Difference Vegetation Index (NDVI) data from 1982 to 2015. A significant increase in mean monthly NDVI occurred across all growing-season months except June and November, but this greening trend was mainly contributed by the faster speed of canopy development in April and the slower speed of canopy senescence in October. The average of V_NDVI (the difference in NDVI between 2 consecutive months) over temperate China is significantly increased only in April (7.75 × 10^-4  year^-1 , p < .05) and October (4.98 × 10^-4  year^-1 , p < .05). In contrast, V_NDVI in November is significantly decreased, indicating an increasing trend in the magnitude of leaf fall in the last month of the growing season due to both increase in season maximum greenness and slower canopy senescence in October. We also found clear seasonal differences in the correlations between V_NDVI and climatic factors, especially temperature. In April and October, the correlations between V_NDVI and temperature were generally positive, while they were negative in June. V_NDVI in spring (early growing season) and summer (middle growing season) was also positively correlated with precipitation in semiarid regions. Such seasonally distinct climatic controls on V_NDVI should be considered in modelling vegetation responses to climate change. Overall, our findings can help quantify the contribution of different climatic drivers on the shifts in canopy development and senescence and better elucidate the change in vegetation greenness under future climate change.

Climate Controls on the Spatial Variability of Vegetation Greenup Rate across Ecosystems in Northern Hemisphere

Variations in individual phenological events in response to global change have received considerable attentions. However, the development of phenological stages is relatively neglected, especially based on in situ observation data. In this study, the rate of vegetation greenup (Vgreenup) across the Northern Hemisphere was examined for different plant functional types (PFTs) by using eddy covariance flux data from 40 sites (417 site-years). Then, the controls of climatic variables on the spatial distribution of Vgreenup across PFTs were further investigated. The mean Vgreenup was 0.22 ± 0.11 g C m^-2 day^-2 across all sites, with the largest and lowest values observed in cropland and evergreen needle-leaf forest, respectively. A strong latitude dependence by Vgreenup was observed in both Europe and North America. The spatial variations of Vgreenup were jointly regulated by the duration of greenup (Dgreenup) and the amplitude of greenup (Agreenup). However, the predominant factor was Dgreenup in Europe, which changed to Agreenup in North America. Spring climatic factors exerted significant influences on the spatial distribution of Vgreenup across PFTs. Specifically, increasing temperature tended to shorten Dgreenup and promote Agreenup simultaneously, resulting in an acceleration of Vgreenup. Dryness had a depression effect on Vgreenup for the whole study area, as exhibited by a lower Vgreenup with increasing vapor pressure deficit or decreasing soil moisture. However, Vgreenup in North America was only significantly and positively correlated with temperature. Without the limitation of other climatic factors, the temperature sensitivity of Vgreenup was higher in North America (0.021 g C m^-2 day^-2 °C^-1) than in Europe (0.015 g C m^-2 day^-2 °C^-1). This study provides new cognitions for Vgreenup dynamics from in situ observations in complement to satellite observations, which can improve our understanding of terrestrial carbon cycles.

Vegetation Greenness Dynamics in the Western Greater Khingan Range of Northeast China Based on Dendrochronology

Understanding the vegetation greenness dynamics in the forest–steppe transition zone is essential for ecosystem management, and in order to study ecological changes in the region. This study provides a valuable record of the vegetation greenness dynamics in the western Greater Khingan Range over the past 193 years (1826–2018) based on tree-ring data represented by the normalized difference vegetation index (NDVI). The reconstructed vegetation greenness dynamics record contains a total of 32 years of high vegetation greenness and 37 years of low vegetation greenness, together occupying 35.8% of the entire reconstructed period (193 years). Climate (precipitation) is the main influence on the vegetation greenness dynamics at this site, but human activities have also had a significant impact over the last few decades. The magnitude, frequency, and duration of extreme changes in vegetation greenness dynamics have increased significantly, with progressively shorter intervals. Analyses targeting human behavior have shown that the density of livestock, agricultural land area, and total population have gradually increased, encroaching on forests and grasslands and reducing the inter-annual variability. After 2002, the government implemented projects to return farmland to its original ecosystems, and for the implementation of new land management practices (which are more ecologically related); as such, the vegetation conditions began to improve. These findings will help us to understand the relationship between climate change and inter- and intra- annual dynamics in northeastern China, and to better understand the impact of human activities on vegetation greenness dynamics.

Dynamics of Vegetation Greenness and Its Response to Climate Change in Xinjiang over the Past Two Decades

Climate change has proven to have a profound impact on the growth of vegetation from various points of view. Understanding how vegetation changes and its response to climatic shift is of vital importance for describing their mutual relationships and projecting future land–climate interactions. Arid areas are considered to be regions that respond most strongly to climate change. Xinjiang, as a typical dryland in China, has received great attention lately for its unique ecological environment. However, comprehensive studies examining vegetation change and its driving factors across Xinjiang are rare. Here, we used the remote sensing datasets (MOD13A2 and TerraClimate) and data of meteorological stations to investigate the trends in the dynamic change in the Normalized Difference Vegetation Index (NDVI) and its response to climate change from 2000 to 2019 across Xinjiang based on the Google Earth platform. We found that the increment rates of growth-season mean and maximum NDVI were 0.0011 per year and 0.0013 per year, respectively, by averaging all of the pixels from the region. The results also showed that, compared with other land use types, cropland had the fastest greening rate, which was mainly distributed among the northern Tianshan Mountains and Southern Junggar Basin and the northern margin of the Tarim Basin. The vegetation browning areas primarily spread over the Ili River Valley where most grasslands were distributed. Moreover, there was a trend of warming and wetting across Xinjiang over the past 20 years; this was determined by analyzing the climate data. Through correlation analysis, we found that the contribution of precipitation to NDVI (R2 = 0.48) was greater than that of temperature to NDVI (R2 = 0.42) throughout Xinjiang. The Standardized Precipitation and Evapotranspiration Index (SPEI) was also computed to better investigate the correlation between climate change and vegetation growth in arid areas. Our results could improve the local management of dryland ecosystems and provide insights into the complex interaction between vegetation and climate change.

Memories of Migrations Past: Sociality and Cognition in Dynamic, Seasonal Environments

Seasonal migrations are a widespread and broadly successful strategy for animals to exploit periodic and localized resources over large spatial scales. It remains an open and largely case-specific question whether long-distance migrations are resilient to environmental disruptions. High levels of mobility suggest an ability to shift ranges that can confer resilience. On the other hand, a conservative, hard-wired commitment to a risky behavior can be costly if conditions change. Mechanisms that contribute to migration include identification and responsiveness to resources, sociality, and cognitive processes such as spatial memory and learning. Our goal was to explore the extent to which these factors interact not only to maintain a migratory behavior but also to provide resilience against environmental changes. We develop a diffusion-advection model of animal movement in which an endogenous migratory behavior is modified by recent experiences via a memory process, and animals have a social swarming-like behavior over a range of spatial scales. We found that this relatively simple framework was able to adapt to a stable, seasonal resource dynamic under a broad range of parameter values. Furthermore, the model was able to acquire an adaptive migration behavior with time. However, the resilience of the process depended on all the parameters under consideration, with many complex trade-offs. For example, the spatial scale of sociality needed to be large enough to capture changes in the resource, but not so large that the acquired collective information was overly diluted. A long-term reference memory was important for hedging against a highly stochastic process, but a higher weighting of more recent memory was needed for adapting to directional changes in resource phenology. Our model provides a general and versatile framework for exploring the interaction of memory, movement, social and resource dynamics, even as environmental conditions globally are undergoing rapid change.

Declined trend in herbaceous plant green-up dates on the Qinghai-Tibetan Plateau caused by spring warming slowdown

There has been much debate on the temporal change trend and existence of a turning point in spring green-up date (GUD) of plants on the Qinghai-Tibetan Plateau (QTP). Most previous studies on the QTP used remote sensing data, which have large uncertainties. In this study, using a large amount of long-term ground observation data at 27 phenological stations across the QTP (1694 GUD records), we showed that on the whole, QTP herbaceous plant GUD insignificantly advanced during 1982-2017. Although the direction of the GUD trend did not change from 1982 to 2017, the magnitude of the advancing trend greatly weakened after 1999. According to our estimated results from 28 paired GUD time series, the overall GUD trend shifted from -2.70 days/decade during 1982-1999 to -0.56 days/decade during 2000-2017. This finding contrasts with the conclusions of previous satellite-based studies, which either reported a continuous significant advancement of GUD or a turning point in the mid-to-late 1990s. Through partial correlation analysis and partial least squares regression, we found that winter and spring air temperatures were the primary climatic factors that influenced the temporal change in GUD, and both had negative effects on GUD. The decreased GUD trend was mainly attributable to the warming slowdown in spring. On average, the spring warming rate decreased by 52.43% after 1999, whereas the winter warming rate displayed no obvious change. This study also found that the GUD of forbs showed stronger sensitivity to air temperature change than that of sedges and grasses. This indicates that forbs are more competitive in adaptation to climate warming, which might shift plant community structure and affect ecosystem service function. Moreover, the declined advancement in GUD implies that the spring phenologically driven increase in carbon uptake may have also slowed in the past two decades.

Toward a comprehensive understanding of global vegetation CO2 assimilation from space

Large-scale global analysis of the relationship between growing season solar-induced chlorophyll fluorescence (SIF) and gross primary productivity (GPP), indicated by the GPP/SIF ratio, varied greatly with higher values found in wet-and-cold climate regions and lower values found in hot-and-dry climate regions. Such pattern has been shown to be most influenced by the environmental factor of moisture availability.