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Forests both take up CO₂ and enhance absorption of solar radiation, with contrasting effects on global temperature. Based on a 9-year study in the forests' dry timberline, we show that substantial carbon sequestration (cooling effect) is maintained in the large dry transition zone (precipitation from 200 to 600 millimeters) by shifts in peak photosynthetic activities from summer to early spring, and this is counteracted by longwave radiation (L) suppression (warming effect), doubling the forestation shortwave (S) albedo effect. Several decades of carbon accumulation are required to balance the twofold S + L effect. Desertification over the past several decades, however, contributed negative forcing at Earth's surface equivalent to approximately 20% of the global anthropogenic CO₂ effect over the same period, moderating warming trends.

Afforestation is an important approach to mitigate global warming. Its complex interactions with the climate system, however, makes it controversial. Afforestation is expected to be effective in the tropics where biogeochemical and biogeophysical effects act in concert; however, its potential in the large semi-arid regions remains insufficiently explored. Here, we use a Global Climate Model to provide a process-based demonstration that implementing measured characteristics of a successful semi-arid afforestation system (2000 ha, ~300 mm mean annual precipitation) over large areas (~200 million ha) of similar precipitation levels in the Sahel and North Australia leads to the weakening and shifting of regional low-level jets, enhancing moisture penetration and precipitation (+0.8 ± 0.1 mm d −1 over the Sahel and +0.4 ± 0.1 mm d −1 over North Australia), influencing areas larger than the original afforestation. These effects are associated with increasing root depth and surface roughness and with decreasing albedo. This results in enhanced evapotranspiration, surface cooling and the modification of the latitudinal temperature gradient. It is estimated that the carbon sequestration potential of such large-scale semi-arid afforestation can be on the order of ~10% of the global carbon sink of the land biosphere and would overwhelm any biogeophysical warming effects within ~6 years.

Predicted climate change over land indicates decreasing precipitation in many regions and increased flooding in others. Globally, over 60% of land precipitation is consumed by evapotranspiration (ET); the remainder, available as runoff, recharge, and for consumption, is termed water yield (WY). Using a global dataset, we show that ET from ecosystems reaches a ‘saturation’ limit of about 480 ± 210 mm yr⁻¹ across climates and biomes, well below the energy-based limit predicted by the Budyko equation. This inflexibility in ET increases the sensitivity of WY to precipitation variability, implying enhanced vulnerability to flooding in wet regions and an accelerated approach to the limits of ecosystem and societal sustainability in dry regions. Both effects are also supported by model-based projections. WY thus provides a more sensitive and integrative indicator of climate impacts on terrestrial water resources and associated risks for ecosystems and society. The study shows that evapotranspiration from ecosystems saturates at about 480 mm per year, making water yield—the water available after evapotranspiration—highly sensitive to precipitation changes, amplifying climate impacts on land water resources.

Forestation actions are a major tool for both climate-change mitigation and biodiversity conservation. We address two weaknesses in this approach: the little attention given to the negative effects of reduced albedo associated with forestation in many regions, and ignoring the potential of drylands that account for 40% of the global potential land area for forestation. We propose an approach to identify suitable land for forestation and quantify its ‘net equivalent carbon stock change’ over 80 years of forest lifetime (NESC), accounting for both carbon sequestration and albedo changes. We combined remote-sensing tools with data-based estimates of surface parameters and with published climate matrices, to identify suitable land for forestation actions. We then calculated the cumulative (over 80 years) ‘net sequestration potential’ (ΔSP), the ‘emission equivalent of shortwave radiation forcing’ (EESF) due to changes in surface albedo, and, in turn, the combined NESC = ΔSP−EESF, of planting forests with >40% tree-cover. Demonstrating our approach in a large climatically diverse state (Queensland), we identified 14.5 million hectares of potential forestation land in its semi-arid land and show that accounting for the EESF, reduces the climatic benefits of the ΔSP by almost 50%. Nevertheless, it results in a total NESC of 0.72 Gt C accumulated by the end of the century, and 80 years of forestation cycle. This estimated NESC is equivalent to 15% of the projected carbon emissions for the same period in Queensland, for a scenario of no change in emission rates during that period. Our approach extends restoration efforts by identifying new land for forestation and carbon sequestration but also demonstrates the importance of quantifying the climatic value of forestation in drylands.

Remote sensing (RS) for vegetation monitoring can involve mixed pixels with contributions from vegetation and background surfaces, causing biases in signals and their interpretations, especially in low-density forests. In a case study in the semi-arid Yatir forest in Israel, we observed a mismatch between satellite (Landsat 8 surface product) and tower-based (Skye sensor) multispectral data and contrasting seasonal cycles in near-infrared (NIR) reflectance. We tested the hypothesis that this mismatch was due to the different fractional contributions of the various surface components and their unique reflectance. Employing an unmanned aerial vehicle (UAV), we obtained high-resolution multispectral images over selected forest plots and estimated the fraction, reflectance, and seasonal cycle of the three main surface components (canopy, shade, and sunlit soil). We determined that the Landsat 8 data were dominated by soil signals (70%), while the tower-based data were dominated by canopy signals (95%). We then developed a procedure to resolve the canopy (i.e., tree foliage) normalized difference vegetation index (NDVI) from the mixed satellite data. The retrieved and corrected canopy-only data resolved the original mismatch and indicated that the spatial variations in Landsat 8 NDVI were due to differences in stand density, while the canopy-only NDVI was spatially uniform, providing confidence in the local flux tower measurements.

The carbon sink intensity of the biosphere depends on the balance between gross primary productivity (GPP) of forest canopies and ecosystem respiration. GPP, however, cannot be directly measured and estimates are not well constrained. A new approach relying on canopy transpiration flux measured as sap flow, and water‐use efficiency inferred from carbon isotope analysis (GPPSF) has been proposed, but not tested against eddy covariance‐based estimates (GPPEC). Here we take advantage of parallel measurements using the two approaches at a semi‐arid pine forest site to compare the GPPSF and GPPEC estimates on diurnal to annual timescales. GPPSF captured the seasonal dynamics of GPPEC (GPPSF = 0.99 × GPPEC, r² = 0.78, RMSE = 0.82, n = 457 d) with good agreement at the annual timescale (653 vs 670 g C m⁻² yr⁻¹). Both methods showed that GPP ranged between 1 and 8 g C m⁻² d⁻¹, and the GPPSF/GPPEC ratio was between 0.5 and 2.0 during 82% of the days. Carbon uptake dynamics at the individual tree scale conformed with leaf scale rates of net assimilation. GPPSF can produce robust estimations of tree‐ and canopy‐scale rates of CO₂ uptake, providing constraints and greatly extending current GPPEC estimations.

Climate-related benefits of afforestation depend on the balance of the often-contrasting effects of biogeochemical (carbon sequestration) and biogeophysical (radiation balance) effects. These effects are known to vary at the continental scale (e.g., from boreal to tropical regions). Here, we show in a four-year study that the biogeochemical vs. biogeophysical balance in paired forested and non-forested ecosystems across short distances (approximately 200 Km) and steep aridity gradient (aridity index 0.64 to 0.18) can change dramatically. The required time for the forestation cooling effects via carbon sequestration, to surpass warming effects associated with the forests’ reduced albedo and suppressed longwave radiation, decreased from 213 years in the driest sites to 73 years in the intermediate and 43 years in the wettest sites. Climate-related benefits of forestation, previously considered at large-spatial scales, should be considered at high-spatial resolutions in climate-change mitigation programs aimed at taking advantage of the vast non-forested dry regions.

Climate change can impose large offsets between the seasonal cycle of photosynthesis and that in solar radiation and temperature which drive it. Ecophysiological adjustments to such offsets in forests growing under hot and dry conditions are critical for maintaining carbon uptake and survival. Here, we investigate the adjustments that underlie the unusually short and intense early spring productive season, under suboptimal radiation and temperature conditions in a semi-arid pine forest. We used eddy covariance flux, meteorological, and close-range sensing measurements, together with leaf chlorophyll content over four years in a semi-arid pine forest to identify the canopy-scale ecophysiological adjustments to the short active season, and long seasonal drought. The results reveal a range of processes that intricately converge to support the early spring peak (March) in photosynthetic activity, including peaks in light use efficiency, leaf chlorophyll content, increase in the absorption of solar radiation, and high leaf scattering properties (indicating optimizing leaf orientation). These canopy-scale adjustments exploit the tradeoffs between the yet increasing temperature and solar radiation, but the concurrently rapidly diminishing soil moisture. In contrast, during the long dry stressful period with rapidly declining photosynthesis under high and potentially damaging solar radiation, physiological photoprotection was conferred by strongly relaxing the early spring adjustments. The results provide evidence for canopy-scale ecophysiological adjustments, detectable by spectral measurements, that support the survival and productivity of a pine forest under the hot and dry conditions, which may apply to large areas in the Mediterranean and other regions in the next few decades due to the current warming and drying trends.

Short-term, intense heat waves (hamsins) are common in the eastern Mediterranean region and provide an opportunity to study the resilience of forests to such events that are predicted to increase in frequency and intensity. * The response of a 50-yr-old Aleppo pine (Pinus halepensis) forest to hamsin events lasting 1–7 d was studied using 10 yr of eddy covariance and sap flow measurements. * The highest frequency of heat waves was c. four per month, coinciding with the peak productivity period (March–April). During these events, net ecosystem carbon exchange (NEE) and canopy conductance (gc) decreased by c. 60%, but evapotranspiration (ET) showed little change. Fast recovery was also observed with fluxes reaching pre-stress values within a day following the event. NEE and gc showed a strong response to vapor pressure deficit that weakened as soil moisture decreased, while sap flow was primarily responding to changes in soil moisture. On an annual scale, heat waves reduced NEE and gross primary productivity by c. 15% and 4%, respectively. * Forest resilience to short-term extreme events such as heat waves is probably a key to its survival and must be accounted for to better predict the increasing impact on productivity and survival of such events in future climates.

Aim: The controls of gross radiation use efficiency (RUE), the ratio between gross primary productivity (GPP) and the radiation intercepted by terrestrial vegetation, and its spatial and temporal variation are not yet fully understood. Our objectives were to analyse and synthesize the spatial variability of GPP and the spatial and temporal variability of RUE and its climatic controls for a wide range of vegetation types. Location: A global range of sites from tundra to rain forest. Methods: We analysed a global dataset on photosynthetic uptake and climatic variables from 35 eddy covariance (EC) flux sites spanning between 100 and 2200 mm mean annual rainfall and between -13 and 26°C mean annual temperature.RUE was calculated from the data provided by EC flux sites and remote sensing (MODIS). Results: Rainfall and actual evapotranspiration (AET) positively influenced the spatial variation of annual GPP, whereas temperature only influenced the GPP of forests. Annual and maximum RUE were also positively controlled primarily by annual rainfall. The main control parameters of the growth season variation of gross RUE varied for each ecosystem type. Overall, the ratio between actual and potential evapotranspiration and a surrogate for the energy balance explained a greater proportion of the seasonal variation of RUE than the vapour pressure deficit (VPD), AET and precipitation. Temperature was important for determining the intra-annual variability of the RUE at the coldest energy-limited sites. Main conclusions: Our analysis supports the idea that the annual functioning of vegetation that is adapted to its local environment is more constrained by water availability than by temperature. The spatial variability of annual and maximum RUE can be largely explained by annual precipitation, more than by vegetation type. The intra-annual variation of RUE was mainly linked to the energy balance and water availability along the climatic gradient. Furthermore, we showed that intra-annual variation of gross RUE is only weakly influenced by VPD and temperature, contrary to what is frequently assumed. Our results provide a better understanding of the spatial and temporal controls of the RUE and thus could lead to a better estimation of ecosystem carbon fixation and better modelling.