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Anthropogenic climate change is expected to impact ecosystem structure, biodiversity and ecosystem services in Africa profoundly. We used the adaptive Dynamic Global Vegetation Model (aDGVM), which was originally developed and tested for Africa, to quantify sources of uncertainties in simulated African potential natural vegetation towards the end of the 21st century. We forced the aDGVM with regionally downscaled high‐resolution climate scenarios based on an ensemble of six general circulation models (GCMs) under two representative concentration pathways (RCPs 4.5 and 8.5). Our study assessed the direct effects of climate change and elevated CO2 on vegetation change and its plant‐physiological drivers. Total increase in carbon in aboveground biomass in Africa until the end of the century was between 18% to 43% (RCP4.5) and 37% to 61% (RCP8.5) and was associated with woody encroachment into grasslands and increased woody cover in savannas. When direct effects of CO2 on plants were omitted, woody encroachment was muted and carbon in aboveground vegetation changed between –8 to 11% (RCP 4.5) and –22 to –6% (RCP8.5). Simulated biome changes lacked consistent large‐scale geographical patterns of change across scenarios. In Ethiopia and the Sahara/Sahel transition zone, the biome changes forecast by the aDGVM were consistent across GCMs and RCPs. Direct effects from elevated CO2 were associated with substantial increases in water use efficiency, primarily driven by photosynthesis enhancement, which may relieve soil moisture limitations to plant productivity. At the ecosystem level, interactions between fire and woody plant demography further promoted woody encroachment. We conclude that substantial future biome changes due to climate and CO2 changes are likely across Africa. Because of the large uncertainties in future projections, adaptation strategies must be highly flexible. Focused research on CO2 effects, and improved model representations of these effects will be necessary to reduce these uncertainties.
In this study, we use simulations from seven global vegetation models to provide the first multi‐model estimate of fire impacts on global tree cover and the carbon cycle under current climate and anthropogenic land use conditions, averaged for the years 2001–2012. Fire globally reduces the tree covered area and vegetation carbon storage by 10%. Regionally, the effects are much stronger, up to 20% for certain latitudinal bands, and 17% in savanna regions. Global fire effects on total carbon storage and carbon turnover times are lower with the effect on gross primary productivity (GPP) close to 0. We find the strongest impacts of fire in savanna regions. Climatic conditions in regions with the highest burned area differ from regions with highest absolute fire impact, which are characterized by higher precipitation. Our estimates of fire‐induced vegetation change are lower than previous studies. We attribute these differences to different definitions of vegetation change and effects of anthropogenic land use, which were not considered in previous studies and decreases the impact of fire on tree cover. Accounting for fires significantly improves the spatial patterns of simulated tree cover, which demonstrates the need to represent fire in dynamic vegetation models. Based upon comparisons between models and observations, process understanding and representation in models, we assess a higher confidence in the fire impact on tree cover and vegetation carbon compared to GPP, total carbon storage and turnover times. We have higher confidence in the spatial patterns compared to the global totals of the simulated fire impact. As we used an ensemble of state‐of‐the‐art fire models, including effects of land use and the ensemble median or mean compares better to observational datasets than any individual model, we consider the here presented results to be the current best estimate of global fire effects on ecosystems.
The turnover time of terrestrial ecosystem carbon is an emergent ecosystem property that quantifies the strength of land surface on the global carbon cycle–climate feedback. However, observation- and modeling-based estimates of carbon turnover and its response to climate are still characterized by large uncertainties. In this study, by assessing the apparent whole ecosystem carbon turnover times (τ) as the ratio between carbon stocks and fluxes, we provide an update of this ecosystem level diagnostic and its associated uncertainties in high spatial resolution (0.083∘) using multiple, state-of-the-art, observation-based datasets of soil organic carbon stock (Csoil), vegetation biomass (Cveg) and gross primary productivity (GPP). Using this new ensemble of data, we estimated the global median τ to be 43+7−7 yr (median+difference to percentile 75−difference to percentile 25) when the full soil is considered, in contrast to limiting it to 1 m depth. Only considering the top 1 m of soil carbon in circumpolar regions (assuming maximum active layer depth is up to 1 m) yields a global median τ of 37+3−6 yr, which is longer than the previous estimates of 23+7−4 yr (Carvalhais et al., 2014). We show that the difference is mostly attributed to changes in global Csoil estimates. Csoil accounts for approximately 84 % of the total uncertainty in global τ estimates; GPP also contributes significantly (15 %), whereas Cveg contributes only marginally (less than 1 %) to the total uncertainty. The high uncertainty in Csoil is reflected in the large range across state-of-the-art data products, in which full-depth Csoil spans between 3362 and 4792 PgC. The uncertainty is especially high in circumpolar regions with an uncertainty of 50 % and a low spatial correlation between the different datasets (0.2<r<0.5) when compared to other regions (0.6<r<0.8). These uncertainties cast a shadow on current global estimates of τ in circumpolar regions, for which further geographical representativeness and clarification on variations in Csoil with soil depth are needed. Different GPP estimates contribute significantly to the uncertainties of τ mainly in semiarid and arid regions, whereas Cveg causes the uncertainties of τ in the subtropics and tropics. In spite of the large uncertainties, our findings reveal that the latitudinal gradients of τ are consistent across different datasets and soil depths. The current results show a strong ensemble agreement on the negative correlation between τ and temperature along latitude that is stronger in temperate zones (30–60∘ N) than in the subtropical and tropical zones (30∘ S–30∘ N). Additionally, while the strength of the τ–precipitation correlation was dependent on the Csoil data source, the latitudinal gradients also agree among different ensemble members. Overall, and despite the large variation in τ, we identified robust features in the spatial patterns of τ that emerge beyond the differences stemming from the data-driven estimates of Csoil, Cveg and GPP. These robust patterns, and associated uncertainties, can be used to infer τ–climate relationships and for constraining contemporaneous behavior of Earth system models (ESMs), which could contribute to uncertainty reductions in future projections of the carbon cycle–climate feedback. The dataset of τ is openly available at https://doi.org/10.17871/bgitau.201911 (Fan et al., 2019).
The turnover time of terrestrial carbon (τ) controls the global carbon cycle – climate feedback and, yet, is poorly simulated by the current Earth System Models (ESMs). In this study, by assessing apparent carbon turnover time as the ratio between carbon stocks and fluxes, we provide a new, updated ensemble of diagnostic terrestrial carbon turnover times and associated uncertainties on a global scale using multiple, state-of-the-art, observation-based datasets of soil organic carbon stock (Csoil), vegetation biomass (Cveg) and gross primary productivity (GPP). Using this new ensemble, we estimated the global average τ to be 42$% &' years when the full soil depth is considered, longer than the previous estimates of 23$) &* years. Only considering the top 1 m (assuming maximum active layer depth is up to 1 meter) of soil carbon in circumpolar regions yields a global τ of 35$) &' years. Csoil in circumpolar regions account for two thirds of the total uncertainty in global τ estimates, whereas Csoil in non-circumpolar contributes merely 9.38%. GPP (2.25%) and Cveg (0.05%) contribute even less to the total uncertainty. Therefore, the high uncertainty in Csoil is the main factor behind the uncertainty in global τ, as reflected in the larger range of full-depth Csoil (3152-4372 PgC). The uncertainty is especially high in circumpolar regions with a behaviour of ESMs which could contribute to uncertainty reductions in future projections of the carbon cycle - climate feedback. The dataset of the terrestrial turnover time ensemble (DOI: 10.17871/bgitau.201911) is openly available from the data portal: https://doi.org/10.17871/bgitau.201911 (Fan et al., 2019) uncertainty of 50% and the spatial correlations among different datasets are also low compared to other regions. Overall, we argue that current global datasets do not support robust estimates of τ globally, for which we need clarification on variations of Csoil with soil depth and stronger estimates of Csoil in circumpolar regions. Despite the large variation in both magnitude and spatial patterns of τ, we identified robust features in the spatial patterns of τ that emerge regardless of soil depth and differences in data sources of Csoil, Cveg and GPP. Our findings show that the latitudinal gradients of τ are consistent across different datasets and soil depth. Furthermore, there is a strong consensus on the negative correlation between τ and temperature along latitude that is stronger in temperate zones (30ºN-60ºN) than in subtropical and tropical zones (30ºS30ºN). The identified robust patterns can be used to infer the response of τ to climate and for constraining contemporaneous behaviour of ESMs which could contribute to uncertainty reductions in future projections of the carbon cycle - climate feedback. The dataset of the terrestrial turnover time ensemble (DOI:10.17871/bgitau.201911) is openly available from the data portal: https://doi.org/10.17871/bgitau.201911 (Fan et al., 2019).
Opportunities and challenges for paleoaltimetry in "small" orogens: insights from the European Alps
(2020)
Many stable isotope paleoaltimetry studies have focused on paleoelevation reconstructions of orogenic plateaus such as the Tibetan or Andean Plateaus. We address the opportunities and challenges of applying stable isotope paleoaltimetry to “smaller” orogens. We do this using a high‐resolution isotope tracking general circulation model (ECHAM5‐wiso) and explore the precipitation δ18O (δ18Op) signal of Cenozoic paleoclimate and topographic change in the European Alps. Results predict a maximum δ18Op change of 4–5‰ (relative to present day) during topographic development of the Alps. This signal of topographic change has the same magnitude as changes in δ18Op values resulting from Pliocene and Last Glacial Maximum global climatic change. Despite the similar magnitude of the isotopic signals resulting from topographic and paleoclimate changes, their spatial patterns across central Europe differ. Our results suggest that an integration of paleoclimate modeling, multiproxy approaches, and low‐elevation reference proxy records distal from an orogen improve topographic reconstructions.