Characteristics, drivers and feedbacks of global greening
- Long-term satellite records reveal a significant global greening of vegetated areas since the 1980s, which recent data suggest has continued past 2010.
- Pronounced greening is observed in China and India due to afforestation and agricultural intensification.
- Global vegetation models suggest that CO2 fertilization is the main driver of global vegetation greening.
- Warming is the major cause of greening in boreal and Arctic biomes, but has negative effects on greening in the tropics.
- Greening was found to mitigate global warming through enhanced land carbon uptake and evaporative cooling, but might also lead to decreased albedo that could potentially cause local warming.
- Greening enhances transpiration, a process that reduces soil moisture and runoff locally, but can either amplify or reduce runoff and soil moisture regionally through altering the pattern of precipitation.
Regional trendsIn the high northern latitudes (>50°N), AVHRR and Landsat records indicate a widespread increase in vegetation greenness since the 1980s8,12,25 (Fig. 2a–d). Regions with the greatest greening trend include northern Alaska and Canada, the low-Arctic parts of eastern Canada and Siberia, and regions of Scandinavia12,25,26. Dendrochronological data and photographic evidence further corroborate these findings27,28,29,30. In general, the LAI over high northern latitudes will continue to increase by the end of this century31, based on the results of an ensemble of ESMs (Fig. 2e–h). However, although only 3% of the high latitudes show browning during 1982–2014 (ref.25), there is a growing proportion of Arctic areas exhibiting a browning trend32. Such trends first emerged in boreal forests, where a multitude of disturbances (for example, fires, harvesting and insect defoliation) prevail9,33,34,35,36,37. The North American boreal forests in particular exhibit browning areas nearly 20 times larger than the Eurasian boreal forests, showing heterogeneous regional greenness change38.
Seasonal changes of greennessIn the northern temperate and high latitudes, greenness often shows distinctive seasonal patterns within a calendar year (Fig. 3). Several metrics of land-surface phenology have been developed to depict the seasonal cycle of greenness47, including the widely used start of the growing season (SOS) and end of the growing season (EOS)48. Although phenology dates can vary depending on the greenness product or algorithm used49,50,51, significant trends towards both earlier SOS (2–8 days decade−1) and later EOS (1–6 days decade−1) and, thus, longer lengths of the growing season (LOS) (2–10 days decade−1), have been observed in most Northern Hemisphere regions during the past four decades7,8,25,52,53,54 (Fig. 3a–c). These trends are corroborated by ground-based observation data in spring and autumn55,56,57. The increase in LOS is driven mainly by an advanced SOS in Eurasia (53–81% of LOS lengthening is due to SOS advance) and delayed EOS in North America (57–96% of LOS lengthening is due to EOS delay), with the more rapid total LOS increase seen in Eurasia25,58,59,60.
Drivers of greening
CO2 fertilizationAs CO2 is the substrate for photosynthesis, rising atmospheric CO2 concentration can enhance photosynthesis66 by accelerating the rate of carboxylation; this process is known as the ‘CO2 fertilization effect’. In addition, increased CO2 concentrations can also enhance vegetation greenness by partially closing leaf stomata, leading to enhanced water-use efficiency67, which should relax water limitation to plant growth, particularly over semi-arid regions45,68,69. Analysis of the ‘Trends and drivers of the regional-scale sources and sinks of carbon dioxide’ (TRENDY) ensemble of dynamic global vegetation models (DGVMs)70 suggests that rising CO2 is the dominant driver of vegetation greening, accounting for nearly 70% of global LAI trend since the 1980s11 (Fig. 4). Statistical modelling also supports the important role of rising atmospheric CO2 concentration in driving vegetation greening71,72. Free-air CO2 enrichment (FACE) experiments show that elevating the CO2 concentration by ~200 ppm above the ambient conditions significantly enhances vegetation productivity73 and increases leaf area74. Different plant species vary largely in the magnitude of LAI enhancement75, with the larger effect on forest stands having lower LAI at the ambient conditions76. In DGVMs, elevated CO2 increases vegetation productivity more in tropical ecosystems than in temperate and boreal ecosystems11,77,78 (Fig. 4b). However, the strength of the CO2 fertilization effect can be limited by extreme weather events79,80 and nutrient and water availability73,81,82. Indeed, nitrogen and phosphorus have been shown to regulate the global pattern of CO2 fertilization effects83. Since nutrient processes were under-represented in the ESMs used in the IPCC Fifth Assessment Report (AR5), the predictions of continued greening trends through 2100 (ref.31) (Figs 2e–h,5) might overestimate the CO2 fertilization effects.
Climate changeAlthough rising atmospheric CO2 concentration is the main driver of global greening, climate change, such as anthropogenic warming and regional trends in precipitation, is a dominant driver of greenness changes over 28% of the global vegetated area11. The global contribution of climate change to increasing greenness is only 8% (Fig. 4a), however, because impacts of climate change on vegetation greenness vary between regions11. For example, warming could reduce vegetation growth in the tropics84, where ambient temperature is close to vegetation optimal temperature85, but warming significantly increases vegetation greenness in the boreal and Arctic regions86 by enhancing metabolism87 and extending the growing season59,88,89. DGVM simulations show that the positive effects of climate change, primarily from warmer temperature14, dominate the greening trend over more than 55% of the northern high latitudes (Fig. 4b) and in the Tibetan Plateau11. However, this positive impact of anthropogenic warming on greenness appears to have weakened during the past four decades90,91, when the correlation coefficient between temperature and greenness decreased by more than 50%90,91, suggesting a possible saturation of future greening in response to warmer temperature. In water-limited ecosystems, changes in precipitation — reflecting either decadal climate variability or trends from anthropogenic climate change — were suggested as the main driving factor of greening and browning45,92. Precipitation-driven greening is most evident in the African Sahel93,94 and semi-arid ecosystems of southern Africa and Australia45,95 (Fig. 4c). Both empirical models and DGVMs indicate that ‘the greening Sahel’, one of the early examples of vegetation greening detected by satellite measurements93,94, was primarily driven by increases in precipitation after a severe drought in the early 1980s96,97,98. This causal relationship between precipitation and greenness changes was further supported through analyses of recent microwave satellite measurements and long-term field surveys99,100.
Land-use changeLike climate change, land-use change exerts a considerable but highly spatially variable influence on greenness changes11,13 (Fig. 4). Specifically, deforestation dominates the tropics101,102, while afforestation increases forest area over temperate regions, particularly in China, where the forest area has increased by more than 20% since the 1980s103. The TRENDY ensemble of DGVMs70 indicates that greenness changes over 19% of the northern temperate vegetation (25–50°N) are primarily driven by land-use change11 (Fig. 4c). However, this might be an underestimate since critical land-use processes104,105 are under-represented or missing in the current generation of DGVMs. For example, forest-age dynamics are not represented in most DGVMs, even though one-third of the global forests are younger than 20 years old106, implying that forest regrowth might contribute to global greening in the future. In addition, agricultural intensification with multiple cropping, irrigation and fertilizer usage must contribute considerably to vegetation greening, which is exemplified by the dominance of other unmodelled factors over agricultural lands of India, China and Eastern Europe (Fig. 4c).
Nitrogen depositionAnthropogenic changes in the amount, rate and distribution of nitrogen deposition can impact greening patterns, since insufficient nitrogen availability can stunt plant growth107,108,109, potentially slowing greening or causing browning, but excess nitrogen can enhance plant growth in nitrogen-limited systems109. However, the few DGVMs that include the nitrogen cycle do not indicate that nitrogen deposition plays a dominant driving role on the greening at either the global or regional scales (Fig. 4). Modelling studies differ on the contribution of increasing nitrogen deposition to the global LAI increase11 (9 ± 12%), largely due to the incomplete representation of nitrogen-related processes110. A growing number of DGVMs are currently incorporating nitrogen processes111, though, and future research priorities include better measurement and representation of processes such as plant nitrogen uptake and allocation110.
Impact of greening on the carbon cycle
Biogeophysical impacts of greening
The hydrologic cycleVegetation greening modulates water cycling. Land water losses to the atmosphere occur through ET, which includes transpiration (60–90% of the total land ET134,135,136) and evaporation. Greening increases water losses through an extended area of leaves performing transpiration137. A larger foliage area reduces the bare ground surface from which soil evaporation occurs, but increases the re-evaporation of rainfall intercepted by leaves138, so that greening can cause the net evaporation to either increase or decrease. Various remote-sensing-based ET estimates consistently point to a significant increase in global terrestrial ET over the past four decades, suggesting an intensified water exchange between the land and the atmosphere concurrent with the greening trend139. More than half of the global ET increase since the 1980s has been attributed to vegetation greening138,139 (Fig. 7). By controlling the changes in ET, vegetation greening also alters the water distribution between regions and water pools (for example, water in soil, rivers and the atmosphere). Assuming that precipitation does not change in response to vegetation greening, a greening-induced ET increase will reduce soil moisture and runoff, which can intensify droughts at the catchment scale140,141. In China’s Loess Plateau for instance, where intensive afforestation is associated with a pronounced local greening, the river discharge has indeed decreased by a rate of 0.25 km3 year−2 over the past six decades142. However, when using ESMs that consider both the greening-induced ET increase and consequent changes in precipitation, simulations forced only with satellite-observed LAI trends do not generate dramatic changes in soil moisture or runoff at continental or global scales143,144. This is because greening-induced ET enhancement increases atmospheric water vapour content, which, in turn, promotes downwind precipitation145,146. The enhanced precipitation over transpiring regions is particularly evident in moist forests147 like the Amazon or Congo, which are ‘closed’ atmospheric systems where 80% of the rainfall originates from upwind ET145. Such an efficient atmospheric water recycling mitigates water loss from the soil, sustains inland vegetation and maintains mesic and humid ecosystems. In addition to intensifying water cycling at the annual scale, vegetation greening also induces seasonal hydrologic changes. There is emerging evidence that spring-greening-enhanced ET leads to a reduction in soil moisture content, which carries over into the following summer and likely suppresses vegetation growth and increases the risk of heatwaves148,149. The greening-induced water loss through ET is recycled as land precipitation in subsequent months, benefitting some remote regions through modulating large-scale atmospheric circulation patterns, despite often being insufficient to compensate for evaporative water loss locally149. Proposed climate-mitigation strategies, such as afforestation, therefore need to fully consider coupling between vegetation and other components of the Earth system.
Land-surface air temperaturesGreening impacts the exchange of energy between the land and the atmosphere, which ultimately leads to modifications in surface air temperature150. Greening increases ET, which cools the surface through evaporative cooling19,150, but greener canopies have a lower albedo than bare ground and absorb more sunlight, which can result in a larger sensible heat flux. This enhanced sensible heat warms the land surface, an effect called albedo warming151. The net effect of greening on surface air temperature in many cases can be viewed as the balance between evaporative cooling and albedo warming152,153, which was estimated globally to be −0.9 W m−2 from evaporative cooling and +0.1 W m−2 from albedo warming19 (Fig. 7c). Greening can also trigger a series of changes through atmospheric circulation that indirectly affect the surface temperature154. For example, the additionally transpired water enhances atmospheric water vapour content, which results in more longwave solar radiation entrapment and re-emission in the atmosphere, but reduces the amount of shortwave solar radiation reaching the Earth’s surface through increased cloud formation19,155,156 (Fig. 7). When all the aforementioned impacts of vegetation greening on near-surface air temperature were simulated in coupled ESMs driven by the satellite-based greening since the 1980s, the results suggested a net cooling trend by 12% ± 3% of the concurrent observed warming rate19. In warm regions such as the tropics and subtropics, evaporative cooling effects are generally larger than albedo warming effects, leading to a net cooling effect when vegetation greenness increases19,157,158. However, the net effect of greening on surface air temperature over the Northern Hemisphere extratropical regions is still subject to debate. Studies based on idealized afforestation and/or deforestation experiments1,159 or comparisons of the energy budget differences between paired forest and short vegetation sites132,153 suggested that the albedo warming effect plays a dominant role. These studies, though, assumed complete land cover changes, whereas greening can be gradual. By integrating satellite observations with ESMs, several studies provided an alternative approach that more realistically simulated the effects of vegetation greenness changes and isolated the signal of climate response to greening. These studies found that greening slowed down warming through evaporative cooling in Arctic and boreal regions19, the Tibetan Plateau160 and temperate regions like East Asia161. Nonetheless, current state-of-the-art modelling efforts are still inconclusive, as some processes are not yet well represented in ESMs, such as snow masking by greener canopies during cold seasons162,163,164 and the partitioning of transpiration and evaporation that is sensitive to vegetation greenness change136. Since most ESMs underestimate the ratio of transpiration to ET136, evaporative cooling by greening could have been underestimated19,133.
Bonan, G. B., Pollard, D. & Thompson, S. L. Effects of boreal forest vegetation on global climate. Nature 359, 716–718 (1992).
Haberl, H. et al. Quantifying and mapping the human appropriation of net primary production in earth’s terrestrial ecosystems. Proc. Natl Acad. Sci. USA 104, 12942–12947 (2007).
Griscom, B. W. et al. Natural climate solutions. Proc. Natl Acad. Sci. USA 114, 11645–11650 (2017).
Bastin, J.-F. et al. The global tree restoration potential. Science 365, 76–79 (2019).
Tucker, C. J., Fung, I. Y., Keeling, C. D. & Gammon, R. H. Relationship between atmospheric CO2 variations and a satellite-derived vegetation index. Nature 319, 195–199 (1986).
Fung, I. Y., Tucker, C. J. & Prentice, K. C. Application of advanced very high resolution radiometer vegetation index to study atmosphere-biosphere exchange of CO2. J. Geophys. Res. Atmos. 92, 2999–3015 (1987).
Myneni, R. B., Keeling, C. D., Tucker, C. J., Asrar, G. & Nemani, R. R. Increased plant growth in the northern high latitudes from 1981 to 1991. Nature 386, 698–702 (1997). The first study to reveal large-scale vegetation greening over the Northern Hemisphere.
Zhou, L. et al. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. J. Geophys. Res. Atmos. 106, 20069–20083 (2001).
Goetz, S. J., Bunn, A. G., Fiske, G. J. & Houghton, R. A. Satellite-observed photosynthetic trends across boreal North America associated with climate and fire disturbance. Proc. Natl Acad. Sci. USA 102, 13521–13525 (2005).
Xu, L. et al. Temperature and vegetation seasonality diminishment over northern lands. Nat. Clim. Change 3, 581–586 (2013).
Zhu, Z. et al. Greening of the Earth and its drivers. Nat. Clim. Change 6, 791–795 (2016). A detailed attribution study of global leaf area index change during the past three decades with ensemble dynamic global vegetation models.
Ju, J. & Masek, J. G. The vegetation greenness trend in Canada and US Alaska from 1984–2012 Landsat data. Remote. Sens. Environ. 176, 1–16 (2016).
Chen, C. et al. China and India lead in greening of the world through land-use management. Nat. Sustain. 2, 122–129 (2019). Demonstrates the pattern of global greening since 2000 with the latest MODIS C6 collection data.
Lucht, W. et al. Climatic control of the high-latitude vegetation greening trend and Pinatubo effect. Science. 296, 1687–1689 (2002).
Arneth, A. et al. IPCC special report on climate change and land. Intergovernmental Panel on Climate Change (IPCC) https://www.ipcc.ch/report/srccl/ (2019) (accessed October 2019).
Abram, N. et al. IPCC special report on the ocean and cryosphere in a changing climate. Intergovernmental Panel on Climate Change (IPCC) https://www.ipcc.ch/srocc/home/ (accessed October 2019).
Eyring, V. et al. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model. Dev. 9, 1937–1958 (2016).
Swann, A. L. S., Fung, I. Y. & Chiang, J. C. H. Mid-latitude afforestation shifts general circulation and tropical precipitation. Proc. Natl Acad. Sci. USA 109, 712–716 (2012).
Zeng, Z. et al. Climate mitigation from vegetation biophysical feedbacks during the past three decades. Nat. Clim. Change 7, 432–436 (2017). A quantification of the climatic impacts of vegetation greening through modulating land-atmosphere energy and water exchanges, with an Earth system model forced by satellite-observed LAI change during the past three decades.
de Jong, R., Verbesselt, J., Schaepman, M. E. & De Bruin, S. Trend changes in global greening and browning: contribution of short-term trends to longer-term change. Glob. Change Biol. 18, 642–655 (2012).
Tian, F. et al. Evaluating temporal consistency of long-term global NDVI datasets for trend analysis. Remote. Sens. Environ. 163, 326–340 (2015).
Zhang, Y., Song, C., Band, L. E., Sun, G. & Li, J. Reanalysis of global terrestrial vegetation trends from MODIS products: Browning or greening? Remote. Sens. Environ. 191, 145–155 (2017).
Liu, Y., Liu, R. & Chen, J. M. Retrospective retrieval of long-term consistent global leaf area index (1981–2011) from combined AVHRR and MODIS data. J. Geophys. Res. Biogeosciences 117, G04003 (2012).
Lyapustin, A. et al. Scientific impact of MODIS C5 calibration degradation and C6+ improvements. Atmos. Meas. Tech. 7, 4353–4365 (2014).
Park, T. et al. Changes in growing season duration and productivity of northern vegetation inferred from long-term remote sensing data. Environ. Res. Lett. 11, 084001 (2016).
Beck, P. S. A. & Goetz, S. J. Satellite observations of high northern latitude vegetation productivity changes between 1982 and 2008: ecological variability and regional differences. Environ. Res. Lett. 6, 045501 (2011).
Sturm, M., Racine, C. & Tape, K. Climate change: increasing shrub abundance in the Arctic. Nature 411, 546–547 (2001).
Frost, G. V. & Epstein, H. E. Tall shrub and tree expansion in Siberian tundra ecotones since the 1960s. Glob. Change Biol. 20, 1264–1277 (2014).
Myers-Smith, I. H. et al. Climate sensitivity of shrub growth across the tundra biome. Nat. Clim. Change 5, 887–891 (2015).
Myers-Smith, I. H. et al. Shrub expansion in tundra ecosystems: dynamics, impacts and research priorities. Environ. Res. Lett. 6, 045509 (2011).
Mahowald, N. et al. Projections of leaf area index in earth system models. Earth Syst. Dyn. 7, 211–229 (2016).
Bhatt, U. et al. Recent declines in warming and vegetation greening trends over pan-Arctic tundra. Remote. Sens. 5, 4229–4254 (2013).
Verbyla, D. The greening and browning of Alaska based on 1982–2003 satellite data. Glob. Ecol. Biogeogr. 17, 547–555 (2008).
Senf, C., Pflugmacher, D., Wulder, M. A. & Hostert, P. Characterizing spectral–temporal patterns of defoliator and bark beetle disturbances using Landsat time series. Remote. Sens. Environ. 170, 166–177 (2015).
Bjerke, J. W. et al. Understanding the drivers of extensive plant damage in boreal and Arctic ecosystems: Insights from field surveys in the aftermath of damage. Sci. Total. Environ. 599, 1965–1976 (2017).
White, J. C., Wulder, M. A., Hermosilla, T., Coops, N. C. & Hobart, G. W. A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series. Remote. Sens. Environ. 194, 303–321 (2017).
Sulla-Menashe, D., Woodcock, C. E. & Friedl, M. A. Canadian boreal forest greening and browning trends: an analysis of biogeographic patterns and the relative roles of disturbance versus climate drivers. Environ. Res. Lett. 13, 014007 (2018).
Bi, J., Xu, L., Samanta, A., Zhu, Z. & Myneni, R. Divergent Arctic-boreal vegetation changes between North America and Eurasia over the past 30 years. Remote. Sens. 5, 2093–2112 (2013).
Feng, X. et al. Revegetation in China’s Loess Plateau is approaching sustainable water resource limits. Nat. Clim. Change. 6, 1019–1022 (2016).
Zhou, L. et al. Widespread decline of Congo rainforest greenness in the past decade. Nature 509, 86–90 (2014).
Goswami, S., Gamon, J., Vargas, S. & Tweedie, C. Relationships of NDVI, biomass, and leaf area index (LAI) for six key plant species in Barrow, Alaska. PeerJ PrePrints 3, e913v1 (2015).
Samanta, A. et al. Amazon forests did not green-up during the 2005 drought. Geophys. Res. Lett. 37, L05401 (2010).
Saleska, S. R., Didan, K., Huete, A. R. & Da Rocha, H. R. Amazon forests green-up during 2005 drought. Science 318, 612 (2007).
Asner, G. P. & Alencar, A. Drought impacts on the Amazon forest: the remote sensing perspective. New Phytol. 187, 569–578 (2010).
Fensholt, R. et al. Greenness in semi-arid areas across the globe 1981–2007—an Earth Observing Satellite based analysis of trends and drivers. Remote. Sens. Environ. 121, 144–158 (2012).
Ahlström, A. et al. The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink. Science 348, 895–899 (2015).
Buitenwerf, R., Rose, L. & Higgins, S. I. Three decades of multi-dimensional change in global leaf phenology. Nat. Clim. Change 5, 364–368 (2015).
Piao, S. et al. Plant phenology and global climate change: current progresses and challenges. Glob. Change Biol. 25, 1922–1940 (2019).
White, M. A. et al. Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982–2006. Glob. Change Biol. 15, 2335–2359 (2009).
Schwartz, M. D. & Hanes, J. M. Intercomparing multiple measures of the onset of spring in eastern North America. Int. J. Climatol. 30, 1614–1626 (2010).
Richardson, A. D., Hufkens, K., Milliman, T. & Frolking, S. Intercomparison of phenological transition dates derived from the PhenoCam Dataset V1.0 and MODIS satellite remote sensing. Sci. Rep. 8, 5679 (2018).
Jeong, S.-J., Ho, C.-H., Gim, H.-J. & Brown, M. E. Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982–2008. Glob. Change Biol. 17, 2385–2399 (2011).
Keenan et al. Net carbon uptake has increased through warming-induced changes in temperate forest phenology. Nat. Clim. Change 4, 598–604 (2014).
Garonna, I., de Jong, R. & Schaepman, M. E. Variability and evolution of global land surface phenology over the past three decades (1982–2012). Glob. Change Biol. 22, 1456–1468 (2016).
Menzel, A. et al. European phenological response to climate change matches the warming pattern. Glob. Change Biol. 12, 1969–1976 (2006).
Cleland, E. E., Chuine, I., Menzel, A., Mooney, H. A. & Schwartz, M. D. Shifting plant phenology in response to global change. Trends Ecol. Evol. 22, 357–365 (2007).
Gill, A. L. et al. Changes in autumn senescence in northern hemisphere deciduous trees: a meta-analysis of autumn phenology studies. Ann. Bot. 116, 875–888 (2015).
Barichivich, J. et al. Large-scale variations in the vegetation growing season and annual cycle of atmospheric CO2 at high northern latitudes from 1950 to 2011. Glob. Change Biol. 19, 3167–3183 (2013).
Piao, S., Friedlingstein, P., Ciais, P., Viovy, N. & Demarty, J. Growing season extension and its impact on terrestrial carbon cycle in the Northern Hemisphere over the past 2 decades. Glob. Biogeochem. Cycles 21, GB3018 (2007).
Julien, Y. & Sobrino, J. A. Global land surface phenology trends from GIMMS database. Int. J. Remote. Sens. 30, 3495–3513 (2009).
Park, T. et al. Changes in timing of seasonal peak photosynthetic activity in northern ecosystems. Glob. Change Biol. 25, 2382–2395 (2019).
Gonsamo, A., Chen, J. M. & Ooi, Y. W. Peak season plant activity shift towards spring is reflected by increasing carbon uptake by extratropical ecosystems. Glob. Change Biol. 24, 2117–2128 (2018).
Bhatt, U. S. et al. Changing seasonality of panarctic tundra vegetation in relationship to climatic variables. Environ. Res. Lett. 12, 055003 (2017).
Epstein, H. et al. Tundra greenness. In Arctic Report Card 2018. National Oceanic and Atmospheric Administration (NOAA), 46–52 (2018).
Huang, M. et al. Velocity of change in vegetation productivity over northern high latitudes. Nat. Ecol. Evol. 1, 1649–1654 (2017).
Farquhar, G. D. & Sharkey, T. D. Stomatal conductance and photosynthesis. Annu. Rev. Plant. Physiol. 33, 317–345 (1982).
Keenan, T. F. et al. Increase in forest water-use efficiency as atmospheric carbon dioxide concentrations rise. Nature 499, 324–327 (2013).
Donohue, R. J., Roderick, M. L., McVicar, T. R. & Farquhar, G. D. Impact of CO2 fertilization on maximum foliage cover across the globe’s warm, arid environments. Geophys. Res. Lett. 40, 3031–3035 (2013).
Ukkola, A. M., Prentice, I. C., Keenan, T. F., van Dijk, A. I. J. M., Viney, N. R., Myneni, R. B. & Bi, J. Reduced streamflow in water-stressed climates consistent with CO2 effects on vegetation. Nat. Clim. Change 6, 75–78 (2015).
Sitch, S. et al. Recent trends and drivers of regional sources and sinks of carbon dioxide. Biogeosciences 12, 653–679 (2015).
Ahlbeck, J. R. Comment on “Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981–1999” by L. Zhou et al. J. Geophys. Res. Atmos. 107, ACH–9 (2002).
Los, S. O. Analysis of trends in fused AVHRR and MODIS NDVI data for 1982–2006: Indication for a CO2 fertilization effect in global vegetation. Glob. Biogeochem. Cycles 27, 318–330 (2013).
Norby, R. J., Warren, J. M., Iversen, C. M., Medlyn, B. E. & McMurtrie, R. E. CO2 enhancement of forest productivity constrained by limited nitrogen availability. Proc. Natl Acad. Sci.USA 107, 19368–19373 (2010).
Dubey, S. K., Tripathi, S. K. & Pranuthi, G. Effect of elevated CO2 on wheat crop: Mechanism and impact. Crit. Rev. Environ. Sci. Technol. 45, 2283–2304 (2015).
Ainsworth, E. A. & Long, S. P. What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. New Phytol. 165, 351–372 (2005).
Norby, R. J. & Zak, D. R. Ecological lessons from free-air CO2 enrichment (FACE) experiments. Annu. Rev. Ecol. Evol. Syst. 42, 181–203 (2011).
Hickler, T. et al. CO2 fertilization in temperate FACE experiments not representative of boreal and tropical forests. Glob. Change Biol. 14, 1531–1542 (2008).
Schimel, D., Stephens, B. B. & Fisher, J. B. Effect of increasing CO2 on the terrestrial carbon cycle. Proc. Natl Acad. Sci. USA 112, 436–441 (2015).
Obermeier, W. A. et al. Reduced CO2 fertilization effect in temperate C3 grasslands under more extreme weather conditions. Nat. Clim. Change 7, 137–141 (2017).
Gray, S. B. et al. Intensifying drought eliminates the expected benefits of elevated carbon dioxide for soybean. Nat. Plants 2, 16132 (2016).
Reich, P. B. & Hobbie, S. E. Decade-long soil nitrogen constraint on the CO2 fertilization of plant biomass. Nat. Clim. Change 3, 278–282 (2013).
Reich, P. B., Hobbie, S. E. & Lee, T. D. Plant growth enhancement by elevated CO2 eliminated by joint water and nitrogen limitation. Nat. Geosci. 7, 920–924 (2014).
Terrer, C. et al. Nitrogen and phosphorus constrain the CO2 fertilization of global plant biomass. Nat. Clim. Change 9, 684–689 (2019).
Corlett, R. T. Impacts of warming on tropical lowland rainforests. Trends Ecol. Evol. 26, 606–613 (2011).
Huang, M. et al. Air temperature optima of vegetation productivity across global biomes. Nat. Ecol. Evol. 3, 772–779 (2019).
Keenan, T. F. & Riley, W. J. Greening of the land surface in the world’s cold regions consistent with recent warming. Nat. Clim. Change 8, 825–828 (2018).
Braswell, B. H., Schimel, D. S., Linder, E. & Moore, B. III The response of global terrestrial ecosystems to interannual temperature variability. Science 278, 870–873 (1997).
Linderholm, H. W. Growing season changes in the last century. Agric. For. Meteorol. 137, 1–14 (2006).
Richardson, A. D. et al. Influence of spring and autumn phenological transitions on forest ecosystem productivity. Philos. Trans. R. Soc. Lond. 365, 3227–3246 (2010).
Piao, S. et al. Evidence for a weakening relationship between interannual temperature variability and northern vegetation activity. Nat. Commun. 5, 5018 (2014). Discusses the weakening temperature impacts on northern vegetation greenness since the 1980s.
Vickers, H. et al. Changes in greening in the high Arctic: insights from a 30 year AVHRR max NDVI dataset for Svalbard. Environ. Res. Lett. 11, 105004 (2016).
Nemani, R. R. et al. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science 300, 1560–1563 (2003).
Eklundh, L. & Olsson, L. Vegetation index trends for the African Sahel 1982–1999. Geophys. Res. Lett. 30, 1430 (2003).
Anyamba, A. & Tucker, C. J. Analysis of Sahelian vegetation dynamics using NOAA-AVHRR NDVI data from 1981–2003. J. Arid. Environ. 63, 596–614 (2005).
Donohue, R. J., McVicar, T. R. & Roderick, M. L. Climate-related trends in Australian vegetation cover as inferred from satellite observations, 1981–2006. Glob. Change Biol. 15, 1025–1039 (2009).
Herrmann, S. M., Anyamba, A. & Tucker, C. J. Recent trends in vegetation dynamics in the African Sahel and their relationship to climate. Glob. Environ. Change 15, 394–404 (2005).
Hickler, T. et al. Precipitation controls Sahel greening trend. Geophys. Res. Lett. 32, L21415 (2005).
Huber, S., Fensholt, R. & Rasmussen, K. Water availability as the driver of vegetation dynamics in the African Sahel from 1982 to 2007. Glob. Planet. Change 76, 186–195 (2011).
Dardel, C. et al. Re-greening Sahel: 30 years of remote sensing data and field observations (Mali, Niger). Remote. Sens. Environ. 140, 350–364 (2014).
Brandt, M. et al. Changes in rainfall distribution promote woody foliage production in the Sahel. Commun. Biol. 2, 133 (2019).
Brandt, M. et al. Human population growth offsets climate-driven increase in woody vegetation in sub-Saharan Africa. Nat. Ecol. Evol. 1, 0081 (2017).
Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A. & Hansen, M. C. Classifying drivers of global forest loss. Science 361, 1108–1111 (2018).
Eighth National Forest Resource Inventory Report (2009–2013) (State Forestry Administration of the People’s Republic of China, 2014).
Luyssaert, S. et al. Land management and land-cover change have impacts of similar magnitude on surface temperature. Nat. Clim. Change 4, 389–393 (2014).
Song, X.-P. et al. Global land change from 1982 to 2016. Nature 560, 639–643 (2018).
Poulter, B. et al. The global forest age dataset and its uncertainties (GFADv1.1). NASA National Aeronautics and Space Administration, PANGAEA https://doi.org/10.1594/PANGAEA.897392 (2019).
Reich, P. B. et al. Nitrogen limitation constrains sustainability of ecosystem response to CO2. Nature 440, 922–925 (2006).
Penuelas, J. et al. Human-induced nitrogen–phosphorus imbalances alter natural and managed ecosystems across the globe. Nat. Commun. 4, 2934 (2013).
Greaver, T. L. et al. Key ecological responses to nitrogen are altered by climate change. Nat. Clim. Change 6, 836–843 (2016).
Zaehle, S. et al. Evaluation of 11 terrestrial carbon–nitrogen cycle models against observations from two temperate Free-Air CO2 Enrichment studies. New Phytol. 202, 803–822 (2014).
Le Quéré, C. et al. Global carbon budget 2018. Earth Syst. Sci. Data 10, 2141–2194 (2018).
Chen, J. M. et al. Vegetation structural change since 1981 significantly enhanced the terrestrial carbon sink. Nat. Commun. 10, 4259 (2019).
van Dijk, A. I. J. M., Dolman, A. J. & Schulze, E.-D. Radiation, temperature, and leaf area explain ecosystem carbon fluxes in boreal and temperate European forests. Glob. Biogeochem. Cycles 19, GB2029 (2005).
Zhang, Y., Joiner, J., Alemohammad, S. H., Zhou, S. & Gentine, P. A global spatially contiguous solar-induced fluorescence (CSIF) dataset using neural networks. Biogeosciences 15, 5779–5800 (2018).
Cheng, L. et al. Recent increases in terrestrial carbon uptake at little cost to the water cycle. Nat. Commun. 8, 110 (2017).
Winkler, A. J., Myneni, R. B., Alexandrov, G. A. & Brovkin, V. Earth system models underestimate carbon fixation by plants in the high latitudes. Nat. Commun. 10, 885 (2019).
Shevliakova, E. et al. Historical warming reduced due to enhanced land carbon uptake. Proc. Natl Acad. Sci. USA 110, 16730–16735 (2013).
Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).
Liu, Y. Y. et al. Recent reversal in loss of global terrestrial biomass. Nat. Clim. Change 5, 470–474 (2015).
Keenan, T. F. et al. Recent pause in the growth rate of atmospheric CO2 due to enhanced terrestrial carbon uptake. Nat. Commun. 7, 13428 (2016).
Piao, S. et al. Lower land-use emissions responsible for increased net land carbon sink during the slow warming period. Nat. Geosci. 11, 739–743 (2018).
Kondo, M. et al. Plant regrowth as a driver of recent enhancement of terrestrial CO2 uptake. Geophys. Res. Lett. 45, 4820–4830 (2018).
Pugh, T. A. M. et al. Role of forest regrowth in global carbon sink dynamics. Proc. Natl Acad. Sci. USA 116, 4382–4387 (2019).
Naudts, K. et al. Europe’s forest management did not mitigate climate warming. Science 351, 597–600 (2016).
Keeling, C. D., Chin, J. F. S. & Whorf, T. P. Increased activity of northern vegetation inferred from atmospheric CO2 measurements. Nature 382, 146–149 (1996).
Graven, H. D. et al. Enhanced seasonal exchange of CO2 by northern ecosystems since 1960. Science 341, 1085–1089 (2013).
Piao, S. et al. On the causes of trends in the seasonal amplitude of atmospheric CO2. Glob. Change Biol. 24, 608–616 (2018).
Forkel, M. et al. Enhanced seasonal CO2 exchange caused by amplified plant productivity in northern ecosystems. Science 351, 696–699 (2016). Presents the linkage between increasing photosynthesis of northern vegetation and the enlarging seasonal CO 2 amplitude.
Piao, S. et al. Weakening temperature control on the interannual variations of spring carbon uptake across northern lands. Nat. Clim. Change 7, 359–363 (2017).
Barichivich, J., Briffa, K. R., Osborn, T. J., Melvin, T. M. & Caesar, J. Thermal growing season and timing of biospheric carbon uptake across the Northern Hemisphere. Glob. Biogeochem. Cycles 26, GB4015 (2012).
Piao, S. et al. Net carbon dioxide losses of northern ecosystems in response to autumn warming. Nature 451, 49–52 (2008).
Alkama, R. & Cescatti, A. Biophysical climate impacts of recent changes in global forest cover. Science 351, 600–604 (2016). Presents evidence for feedbacks of forest cover change to land-surface temperature and its regional disparities.
Arora, V. K. & Montenegro, A. Small temperature benefits provided by realistic afforestation efforts. Nat. Geosci. 4, 514–518 (2011).
Jasechko, S. et al. Terrestrial water fluxes dominated by transpiration. Nature 496, 347–350 (2013).
Good, S. P., Noone, D. & Bowen, G. Hydrologic connectivity constrains partitioning of global terrestrial water fluxes. Science 349, 175–177 (2015).
Lian, X. et al. Partitioning global land evapotranspiration using CMIP5 models constrained by observations. Nat. Clim. Change 8, 640–646 (2018).
Bernacchi, C. J. & VanLoocke, A. Terrestrial ecosystems in a changing environment: a dominant role for water. Annu. Rev. Plant. Biol. 66, 599–622 (2015).
Zhang, Y. et al. Multi-decadal trends in global terrestrial evapotranspiration and its components. Sci. Rep. 6, 19124 (2016).
Zeng, Z., Peng, L. & Piao, S. Response of terrestrial evapotranspiration to Earth’s greening. Curr. Opin. Environ. Sustain. 33, 9–25 (2018).
Bosch, J. M. & Hewlett, J. D. A review of catchment experiments to determine the effect of vegetation changes on water yield and evapotranspiration. J. Hydrol. 55, 3–23 (1982).
Evaristo, J. & McDonnell, J. J. Global analysis of streamflow response to forest management. Nature 570, 455–461 (2019).
Wang, S. et al. Reduced sediment transport in the Yellow River due to anthropogenic changes. Nat. Geosci. 9, 38–41 (2016).
Li, Y. et al. Divergent hydrological response to large-scale afforestation and vegetation greening in China. Sci. Adv. 4, eaar4182 (2018).
Zeng, Z. et al. Impact of Earth greening on the terrestrial water cycle. J. Clim. 31, 2633–2650 (2018).
van der Ent, R. J., Savenije, H. H. G., Schaefli, B. & Steele-Dunne, S. C. Origin and fate of atmospheric moisture over continents. Water Resour. Res. 46, W09525 (2010). Discusses the importance of land evapotranspiration to sustain downwind precipitation.
Teuling, A. J. et al. Observational evidence for cloud cover enhancement over western European forests. Nat. Commun. 8, 14065 (2017).
Spracklen, D. V., Arnold, S. R. & Taylor, C. M. Observations of increased tropical rainfall preceded by air passage over forests. Nature 489, 282–285 (2012).
Buermann, W. et al. Widespread seasonal compensation effects of spring warming on northern plant productivity. Nature 562, 110–114 (2018).
Lian, X. et al. Summer soil drying exacerbated by earlier spring greening of northern vegetation. Sci. Adv. (in the press) https://doi.org/10.1126/sciadv.aax0255.
Bonan, G. B. Forests, climate, and public policy: A 500-year interdisciplinary odyssey. Annu. Rev. Ecol. Evol. Syst. 47, 97–121 (2016).
Davin, E. L. & de Noblet-Ducoudré, N. Climatic impact of global-scale deforestation: Radiative versus nonradiative processes. J. Clim. 23, 97–112 (2010).
Bonan, G. B. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444–1449 (2008).
Lee, X. et al. Observed increase in local cooling effect of deforestation at higher latitudes. Nature 479, 384–387 (2011).
Winckler, J., Lejeune, Q., Reick, C. H. & Pongratz, J. Nonlocal effects dominate the global mean surface temperature response to the biogeophysical effects of deforestation. Geophys. Res. Lett. 46, 745–755 (2019).
Green, J. K. et al. Regionally strong feedbacks between the atmosphere and terrestrial biosphere. Nat. Geosci. 10, 410–414 (2017).
Devaraju, N., de Noblet-Ducoudré, N., Quesada, B. & Bala, G. Quantifying the relative importance of direct and indirect biophysical effects of deforestation on surface temperature and teleconnections. J. Clim. 31, 3811–3829 (2018).
Bateni, S. M. & Entekhabi, D. Relative efficiency of land surface energy balance components. Water Resour. Res. 48, 4510 (2012).
Forzieri, G., Alkama, R., Miralles, D. G. & Cescatti, A. Satellites reveal contrasting responses of regional climate to the widespread greening of Earth. Science 356, 1180–1184 (2017).
Betts, R. A. Offset of the potential carbon sink from boreal forestation by decreases in surface albedo. Nature 408, 187–190 (2000).
Shen, M. et al. Evaporative cooling over the Tibetan Plateau induced by vegetation growth. Proc. Natl Acad. Sci. USA 112, 9299–9304 (2015).
Jeong, S., Ho, C., Kim, K. & Jeong, J. Reduction of spring warming over East Asia associated with vegetation feedback. Geophys. Res. Lett. 36, L18705 (2009).
Essery, R. Large-scale simulations of snow albedo masking by forests. Geophys. Res. Lett. 40, 5521–5525 (2013).
Thackeray, C. W., Fletcher, C. G. & Derksen, C. The influence of canopy snow parameterizations on snow albedo feedback in boreal forest regions. J. Geophys. Res. Atmos. 119, 9810–9821 (2014).
Wang, L. et al. Investigating the spread in surface albedo for snow-covered forests in CMIP5 models. J. Geophys. Res. Atmos. 121, 1104–1119 (2016).
National Academies of Sciences, Engineering, and Medicine. Thriving on our changing planet: A decadal strategy for Earth observation from space (National Academies Press, 2018) https://doi.org/10.17226/24938.
Metcalfe, D. B. et al. Patchy field sampling biases understanding of climate change impacts across the Arctic. Nat. Ecol. Evol. 2, 1443–1448 (2018).
Schimel, D. et al. Observing terrestrial ecosystems and the carbon cycle from space. Glob. Change Biol. 21, 1762–1776 (2015).
Park, D. S. et al. Herbarium specimens reveal substantial and unexpected variation in phenological sensitivity across the eastern United States. Philos. Trans. R. Soc. Lond. B Biol. Sci. 374, 20170394 (2018).
Reichstein, M. et al. Deep learning and process understanding for data-driven Earth system science. Nature 566, 195–204 (2019).
Allen, C. D. et al. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For. Ecol. Manage. 259, 660–684 (2010).
Sturrock, R. N. et al. Climate change and forest diseases. Plant. Pathol. 60, 133–149 (2011).
Raynolds, M. K. & Walker, D. A. Increased wetness confounds Landsat-derived NDVI trends in the central Alaska North Slope region, 1985–2011. Environ. Res. Lett. 11, 085004 (2016).
Matasci, G. et al. Three decades of forest structural dynamics over Canada’s forested ecosystems using Landsat time-series and lidar plots. Remote. Sens. Environ. 216, 697–714 (2018).
Mitchard, E. T. A. The tropical forest carbon cycle and climate change. Nature 559, 527–534 (2018).
Esau, I., Miles, V. V., Davy, R., Miles, M. W. & Kurchatova, A. Trends in normalized difference vegetation index (NDVI) associated with urban development in northern West Siberia. Atmos. Chem. Phys. 16, 9563–9577 (2016).
Knyazikhin, Y. et al. Hyperspectral remote sensing of foliar nitrogen content. Proc. Natl Acad. Sci. USA 110, E185–E192 (2013).
Tucker, C. J. Red and photographic infrared linear combinations for monitoring vegetation. Remote. Sens. Environ. 8, 127–150 (1979).
Bannari, A., Morin, D., Bonn, F. & Huete, A. R. A review of vegetation indices. Remote. Sens. Rev. 13, 95–120 (1995).
Myneni, R. B., Hall, F. G., Sellers, P. J. & Marshak, A. L. The interpretation of spectral vegetation indexes. IEEE Trans. Geosci. Remote. Sens. 33, 481–486 (1995).
Xue, J. & Su, B. Significant remote sensing vegetation indices: A review of developments and applications. J. Sens. 2017, 1353691 (2017).
Ganguly, S. et al. Generating vegetation leaf area index Earth system data record from multiple sensors. Part 2: Implementation, analysis and validation. Remote. Sens. Environ. 112, 4318–4332 (2008).
Zhu, Z. et al. Global data sets of vegetation leaf area index (LAI) 3g and fraction of photosynthetically active radiation (FPAR) 3g derived from global inventory modeling and mapping studies (GIMMS) normalized difference vegetation index (NDVI3g) for the period 1981 to 2011. Remote. Sens. 5, 927–948 (2013).
Pinzon, J. & Tucker, C. A non-stationary 1981–2012 AVHRR NDVI3g time series. Remote. Sens. 6, 6929–6960 (2014). Discusses complexities and challenges in detecting greenness change with the longest available NDVI dataset (AVHRR NDVI) since the 1980s.
Knyazikhin, Y., Martonchik, J. V., Myneni, R. B., Diner, D. J. & Running, S. W. Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from MODIS and MISR data. J. Geophys. Res. Atmos. 103, 32257–32275 (1998).
Chen, J. M. & Black, T. A. Defining leaf area index for non-flat leaves. Plant. Cell Environ. 15, 421–429 (1992).
Asrar, G. Q., Fuchs, M., Kanemasu, E. T. & Hatfield, J. L. Estimating absorbed photosynthetic radiation and leaf area index from spectral reflectance in wheat 1. Agron. J. 76, 300–306 (1984).
Cohen, W. B., Maiersperger, T. K., Gower, S. T. & Turner, D. P. An improved strategy for regression of biophysical variables and Landsat ETM+ data. Remote. Sens. Environ. 84, 561–571 (2003).
Baret, F. et al. GEOV1: LAI and FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part1: Principles of development and production. Remote. Sens. Environ. 137, 299–309 (2013).
Claverie, M., Matthews, J., Vermote, E. & Justice, C. A 30+ year AVHRR LAI and FAPAR climate data record: Algorithm description and validation. Remote. Sens. 8, 263 (2016).
Ross, J. K. & Marshak, A. L. Calculation of canopy bidirectional reflectance using the Monte Carlo method. Remote. Sens. Environ. 24, 213–225 (1988).
Yang, B. et al. Estimation of leaf area index and its sunlit portion from DSCOVR EPIC data: Theoretical basis. Remote. Sens. Environ. 198, 69–84 (2017).
Xiao, Z. et al. Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. IEEE Trans. Geosci. Remote. Sens. 54, 5301–5318 (2016).
Myneni, R., Knyazikhin, Y. & Park, T. MOD15A2H MODIS/terra leaf area index/FPAR 8-day L4 global 500 m SIN grid V006. NASA EOSDIS L. Process. DAAC (2015).
Tucker, C. J. et al. An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. Int. J. Remote. Sens. 26, 4485–4498 (2005).
Huete, A. et al. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote. Sens. Environ. 83, 195–213 (2002).
Maisongrande, P., Duchemin, B. & Dedieu, G. VEGETATION/SPOT: an operational mission for the Earth monitoring; presentation of new standard products. Int. J. Remote. Sens. 25, 9–14 (2004).
Badgley, G., Field, C. B. & Berry, J. A. Canopy near-infrared reflectance and terrestrial photosynthesis. Sci. Adv. 3, e1602244 (2017).
Smith, W. K. et al. Large divergence of satellite and Earth system model estimates of global terrestrial CO2 fertilization. Nat. Clim. Change 6, 306–310 (2016).