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Source data for 'Comparable biophysical and biogeochemical feedbacks on warming from tropical moist forest degradation'. Please note that the file discription is included in the file name. '_sd' refer tostandard deviation.Thesource data for Extended Data Fig3 is the same as Fig1 and the Extended Data Fig5is the same as Fig4. Python code for the article can be found at:https://github.com/zhu3210/Tropical-forest-degradation

We describe a new coordination activity and initial results for a global synthesis of eddy covariance CH4 flux measurements.

Photosynthetic phenology has large effects on the land-atmosphere carbon exchange. Due to limited experimental assessments, a comprehensive understanding of the variations of photosynthetic phenology under future climate and its associated controlling factors is still missing, despite its high sensitivities to climate. Here, we develop an approach that uses cities as natural laboratories, since plants in urban areas are often exposed to higher temperatures and carbon dioxide (CO₂) concentrations, which reflect expected future environmental conditions. Using more than 880 urban-rural gradients across the Northern Hemisphere (≥30° N), combined with concurrent satellite retrievals of Sun-induced chlorophyll fluorescence (SIF) and atmospheric CO₂, we investigated the combined impacts of elevated CO₂ and temperature on photosynthetic phenology at the large scale. The results showed that, under urban conditions of elevated CO2 and temperature, vegetation photosynthetic activity began earlier (−5.6 ± 0.7 d), peaked earlier (−4.9 ± 0.9 d) and ended later (4.6 ± 0.8 d) than in neighbouring rural areas, with a striking two- to fourfold higher climate sensitivity than greenness phenology. The earlier start and peak of season were sensitive to both the enhancements of CO₂ and temperature, whereas the delayed end of season was mainly attributed to CO₂ enrichments. We used these sensitivities to project phenology shifts under four Representative Concentration Pathway climate scenarios, predicting that vegetation will have prolonged photosynthetic seasons in the coming two decades. This observation-driven study indicates that realistic urban environments, together with SIF observations, provide a promising method for studying vegetation physiology under future climate change.

Additional file 1. The contribution of LULUCF to the countries' climate pledges made in Paris and, more specifically, the expected contribution of forests to meet EU 2030 the climate targets, including an analysis of forest-based bioenergy.

Light-use efficiency (LUE), which quantifies the plants' efficiency in utilizing solar radiation for photosynthetic carbon fixation, is an important factor for gross primary production estimation. Here we use satellite-based solar-induced chlorophyll fluorescence as a proxy for photosynthetically active radiation absorbed by chlorophyll (APARchl) and derive an estimation of the fraction of APARchl (fPARchl) from four remotely sensed vegetation indicators. By comparing maximum LUE estimated at different scales from 127 eddy flux sites, we found that the maximum daily LUE based on PAR absorption by canopy chlorophyll (εchlmax), unlike other expressions of LUE, tends to converge across biome types. The photosynthetic seasonality in tropical forests can also be tracked by the change of fPARchl, suggesting the corresponding (εchlmax) to have less seasonal variation. This spatio-temporal convergence of LUE derived from fPARchl can be used to build simple but robust gross primary production models and to better constrain process-based models.

Following a land cover and land management change (LCMC), local surface temperature responds to both a change in available energy and a change in the way energy is redistributed by various non-radiative mechanisms. However, the extent to which non-radiative mechanisms contribute to the local direct temperature response for different types of LCMC across the world remains uncertain. Here, we combine extensive records of remote sensing and in situ observation to show that non-radiative mechanisms dominate the local response in most regions for eight of nine common LCMC perturbations. We find that forest cover gains lead to an annual cooling in all regions south of the upper conterminous United States, northern Europe, and Siberia—reinforcing the attractiveness of re-/afforestation as a local mitigation and adaptation measure in these regions. Our results affirm the importance of accounting for non-radiative mechanisms when evaluating local land-based mitigation or adaptation policies.

In this study we present an assessment of the impact of future climate change on total fire probability, burned area, and carbon (C) emissions from fires in Europe. The analysis was performed with the Community Land Model (CLM) extended with a prognostic treatment of fires that was specifically refined and optimized for application over Europe. Simulations over the 21st 27 century are forced by 5 different high resolution Regional Climate Models (RCMs) under the Special Report on Emissions Scenarios (SRES) A1B emission scenario. Both original and bias corrected meteorological forcings is used. Results show that the simulated C emissions o 30 ver the present period are improved by using bias corrected meteorological forcing, with a reduction of the inter-model variability. In the course of the 21st century burned area and C emissions from fires are shown to increase in Europe, in particular in the Mediterranean basins, in the Balkan regions and in Eastern Europe. However, the projected increase is lower than in other studies that did not fully account for the effect of climate on ecosystem functioning. We demonstrate that the lower sensitivity of burned area and C emissions to climate change is related to the predicted reduction of the net primary productivity (NPP), which is identified as the most important determinant of fire activity in the Mediterranean region after anthropogenic interaction. This behavior, consistent with the intermediate fire-productivity hypothesis, limits the sensitivity of future burned area and C emissions from fires on climate change, providing more conservative estimates of future fire patterns, and demonstrates the importance of coupling fire simulation with a climate driven ecosystem productivity model., JRC.H.7-Climate Risk Management