Forest production efficiency (FPE) metric describes how efficiently the assimilated carbon is partitioned into plants organs (biomass production, BP) or-more generally-for the production of organic ...matter (net primary production, NPP). We present a global analysis of the relationship of FPE to stand-age and climate, based on a large compilation of data on gross primary production and either BP or NPP. FPE is important for both forest production and atmospheric carbon dioxide uptake. We find that FPE increases with absolute latitude, precipitation and (all else equal) with temperature. Earlier findings-FPE declining with age-are also supported by this analysis. However, the temperature effect is opposite to what would be expected based on the short-term physiological response of respiration rates to temperature, implying a top-down regulation of carbon loss, perhaps reflecting the higher carbon costs of nutrient acquisition in colder climates. Current ecosystem models do not reproduce this phenomenon. They consistently predict lower FPE in warmer climates, and are therefore likely to overestimate carbon losses in a warming climate.
This study tests the ability of five Dynamic Global Vegetation Models (DGVMs), forced with observed climatology and atmospheric CO₂, to model the contemporary global carbon cycle. The DGVMs are also ...coupled to a fast 'climate analogue model', based on the Hadley Centre General Circulation Model (GCM), and run into the future for four Special Report Emission Scenarios (SRES): A1FI, A2, B1, B2. Results show that all DGVMs are consistent with the contemporary global land carbon budget. Under the more extreme projections of future environmental change, the responses of the DGVMs diverge markedly. In particular, large uncertainties are associated with the response of tropical vegetation to drought and boreal ecosystems to elevated temperatures and changing soil moisture status. The DGVMs show more divergence in their response to regional changes in climate than to increases in atmospheric CO₂ content. All models simulate a release of land carbon in response to climate, when physiological effects of elevated atmospheric CO₂ on plant production are not considered, implying a positive terrestrial climate-carbon cycle feedback. All DGVMs simulate a reduction in global net primary production (NPP) and a decrease in soil residence time in the tropics and extra-tropics in response to future climate. When both counteracting effects of climate and atmospheric CO₂ on ecosystem function are considered, all the DGVMs simulate cumulative net land carbon uptake over the 21st century for the four SRES emission scenarios. However, for the most extreme A1FI emissions scenario, three out of five DGVMs simulate an annual net source of CO₂ from the land to the atmosphere in the final decades of the 21st century. For this scenario, cumulative land uptake differs by 494 Pg C among DGVMs over the 21st century. This uncertainty is equivalent to over 50 years of anthropogenic emissions at current levels.
Abstract
Fossil CO
2
emissions in 2021 grew an estimated 4.2% (3.5%–4.8%) to 36.2 billion metric tons compared with 2020, pushing global emissions back close to 2019 levels (36.7 Gt CO
2
).
Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in ...projections of future climate. The relative importance of changing climate, rising atmospheric CO
, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO
which shows almost twice the variability in cumulative land uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO
and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.
Sub-Saharan West Africa is a vulnerable region where a better quantification and understanding of the impact of climate change on crop yields is urgently needed. Here, we have applied the ...process-based crop model SARRA-H calibrated and validated over multi-year field trials and surveys at eight contrasting sites in terms of climate and agricultural practices in Senegal, Mali, Burkina Faso and Niger. The model gives a reasonable correlation with observed yields of sorghum and millet under a range of cultivars and traditional crop management practices. We applied the model to more than 7000 simulations of yields of sorghum and millet for 35 stations across West Africa and under very different future climate conditions. We took into account 35 possible climate scenarios by combining precipitation anomalies from −20% to 20% and temperature anomalies from +0 to +6 °C. We found that most of the 35 scenarios (31/35) showed a negative impact on yields, up to −41% for +6 °C − 20% rainfall. Moreover, the potential future climate impacts on yields are very different from those recorded in the recent past. This is because of the increasingly adverse role of higher temperatures in reducing crop yields, irrespective of rainfall changes. When warming exceeds +2 °C, negative impacts caused by temperature rise cannot be counteracted by any rainfall change. The probability of a yield reduction appears to be greater in the Sudanian region (southern Senegal, Mali, Burkina Faso, northern Togo and Benin), because of an exacerbated sensitivity to temperature changes compared to the Sahelian region (Niger, Mali, northern parts of Senegal and Burkina Faso), where crop yields are more sensitive to rainfall change. Finally, our simulations show that the photoperiod-sensitive traditional cultivars of millet and sorghum used by local farmers for centuries seem more resilient to future climate conditions than modern cultivars bred for their high yield potential (−28% versus −40% for the +4 °C − 20% scenario). Photoperiod-sensitive cultivars counteract the effect of temperature increase on shortening cultivar duration and thus would likely avoid the need to shift to cultivars with a greater thermal time requirement. However, given the large difference in mean yields of the modern versus traditional varieties, the modern varieties would still yield more under optimal fertility conditions in a warmer world, even if they are more affected by climate change.
Ecology Letters (2012)
Trees with sufficient nutrition are known to allocate carbon preferentially to aboveground plant parts. Our global study of 49 forests revealed an even more fundamental carbon ...allocation response to nutrient availability: forests with high‐nutrient availability use 58 ± 3% (mean ± SE; 17 forests) of their photosynthates for plant biomass production (BP), while forests with low‐nutrient availability only convert 42 ± 2% (mean ± SE; 19 forests) of annual photosynthates to biomass. This nutrient effect largely overshadows previously observed differences in carbon allocation patterns among climate zones, forest types and age classes. If forests with low‐nutrient availability use 16 ± 4% less of their photosynthates for plant growth, what are these used for? Current knowledge suggests that lower BP per unit photosynthesis in forests with low‐ versus forests with high‐nutrient availability reflects not merely an increase in plant respiration, but likely results from reduced carbon allocation to unaccounted components of net primary production, particularly root symbionts.