The human impact on life on Earth has increased sharply since the 1970s, driven by the demands of a growing population with rising average per capita income. Nature is currently supplying more materials than ever before, but this has come at the high cost of unprecedented global declines in the extent and integrity of ecosystems, distinctness of local ecological communities, abundance and number of wild species, and the number of local domesticated varieties. Such changes reduce vital benefits that people receive from nature and threaten the quality of life of future generations. Both the benefits of an expanding economy and the costs of reducing nature’s benefits are unequally distributed. The fabric of life on which we all depend—nature and its contributions to people—is unravelling rapidly. Despite the severity of the threats and lack of enough progress in tackling them to date, opportunities exist to change future trajectories through transformative action. Such action must begin immediately, however, and address the root economic, social, and technological causes of nature’s deterioration.

Large interannual variations in the measured growth rate of atmospheric carbon dioxide (CO 2 ) originate primarily from fluctuations in carbon uptake by land ecosystems 1-3 . It remains uncertain, however, to what extent temperature and water availability control the carbon balance of land ecosystems across spatial and temporal scales 3-14 . Here we use empirical models based on eddy covariance data 15 and process-based models 16,17 to investigate the effect of changes in temperature and water availability on gross primary productivity (GPP), terrestrial ecosystem respiration (TER) and net ecosystem exchange (NEE) at local and global scales. We find that water availability is the dominant driver of the local interannual variability in GPP and TER. To a lesser extent this is true also for NEE at the local scale, but when integrated globally, temporal NEE variability is mostly driven by temperature fluctuations. We suggest that this apparent paradox can be explained by two compensatory water effects. Temporal waterdriven GPP and TER variations compensate locally, dampening water-driven NEE variability. Spatial water availability anomalies also compensate, leaving a dominant temperature signal in the yearto-year fluctuations of the land carbon sink. These findings help to reconcile seemingly contradictory reports regarding the importance of temperature and water in controlling the interannual variability of the terrestrial carbon balance 3-6,9,11,12,14 . Our study indicates that spatial climate covariation drives the global carbon cycle response.Large interannual variations in recently measured atmospheric CO 2 growth rates originate primarily from fluctuations in carbon uptake by land ecosystems, rather than from the oceans or variations in anthropogenic emissions [1][2][3] . There is a general consensus that the tropical regions contribute the most to terrestrial carbon variability 1,8,18,19 . The observed positive correlation between mean tropical land temperature and CO 2 growth rate 3,5,6,12,13 implies smaller land carbon uptake and enhanced atmospheric CO 2 growth during warmer years, with a sensitivity of about 5 gigatonnes of carbon per year per K. There is a tight relationship between this sensitivity on interannual timescales and long-term changes in terrestrial carbon per degree of warming across multiple climate carbon-cycle models 6 . Despite this strong emergent relationship with mean tropical land temperature, several studies suggest that variations in water availability have an important 8,10,11,14 , even a dominant role 4,9 , in shaping the interannual variability (IAV) of the carbon balance of extensive semi-arid and sub-tropical systems. Furthermore, the recent doubling of the tropical carbon cycle sensitivity to interannual temperature variability has been linked to interactions with changing moisture regimes 13 . A full understanding of the processes governing the climatic controls of terrestrial carbon cycling on interannual timescales and across spatial scales is therefore still lacking. H...

There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange (R 2 < 0.5), ecosystem respiration (R 2 > 0.6), gross primary production (R 2 > 0.7), latent heat (R 2 > 0.7), sensible heat (R 2 > 0.7), and net radiation (R 2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well (R 2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted (R 2 < 0.5). Fluxes were better predicted at forested and temperate climate sites than at sites in extreme climates or less represented by training data (e.g., the tropics). The evaluated large ensemble of ML-based models will be the basis of new global flux products.Published by Copernicus Publications on behalf of the European Geosciences Union.