| 1. |
- Anderegg, William R L, et al.
(författare)
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A climate risk analysis of Earth's forests in the 21st century
- 2022
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Ingår i: Science (New York, N.Y.). - : American Association for the Advancement of Science (AAAS). - 1095-9203 .- 0036-8075. ; 377:6610, s. 1099-1103
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Tidskriftsartikel (refereegranskat)abstract
- Earth's forests harbor extensive biodiversity and are currently a major carbon sink. Forest conservation and restoration can help mitigate climate change; however, climate change could fundamentally imperil forests in many regions and undermine their ability to provide such mitigation. The extent of climate risks facing forests has not been synthesized globally nor have different approaches to quantifying forest climate risks been systematically compared. We combine outputs from multiple mechanistic and empirical approaches to modeling carbon, biodiversity, and disturbance risks to conduct a synthetic climate risk analysis for Earth's forests in the 21st century. Despite large uncertainty in most regions we find that some forests are consistently at higher risk, including southern boreal forests and those in western North America and parts of the Amazon.
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| 2. |
- Barredo, José I., et al.
(författare)
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Mapping and assessment of forest ecosystems and their services : Applications and guidance for decision making in the framework of MAES
- 2015
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The aim of this report is to illustrate by means of a series of case studies the implementation of mapping and assessment of forest ecosystem services in different contexts and geographical levels. Methodological aspects, data issues, approaches, limitations, gaps and further steps for improvement are analysed for providing good practices and decision making guidance. The EU initiative on Mappingand Assessment of Ecosystems and their Services (MAES), with the support of all Member States, contributes to improve the knowledge on ecosystem services. MAES is one of the building-block initiatives supporting the EU Biodiversity Strategy to 2020.
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| 3. |
- Beer, Christian, et al.
(författare)
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Harmonized European Long-Term Climate Data for Assessing the Effect of Changing Temporal Variability on Land-Atmosphere CO2 Fluxes
- 2014
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Ingår i: Journal of Climate. - 0894-8755 .- 1520-0442. ; 27:13, s. 4815-4834
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Tidskriftsartikel (refereegranskat)abstract
- Temporal variability of meteorological variables and extreme weather events is projected to increase in many regions of the world during the next century. Artificial experiments using process-oriented terrestrial ecosystem models make it possible to isolate effects of temporal variability from effects of gradual climate change on terrestrial ecosystem functions and the system state. Such factorial experiments require two long-term climate datasets: 1) a control dataset that represents observed and projected climate and 2) a dataset with the same long-term mean as the control dataset but with altered short-term variability. Using a bias correction method, various climate datasets spanning different periods are harmonized and then combined with the control dataset with consistent time series for Europe during 1901-2100. Then, parameters of a distribution transformation function are estimated for individual meteorological variables to derive the second climate dataset, which has similar long-term means but reduced temporal variability. The transformation conserves the number of rainy days within a month and the shape of the daily meteorological data distributions, which is important to ensure that, for example, drought duration does not modify the suitability of localized vegetation type to precipitation regimes. The median absolute difference between daily data of both datasets is 5% to 20%. On average, decadal extreme values are reduced by 2% to 35%. Driving a terrestrial ecosystem model with both climate datasets shows a general higher gross primary production under reduced temporal climate variability. This effect of climate variability on productivity demonstrates the potential of the climate datasets for studying various effects of temporal variability on ecosystem state and functions over large domains.
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| 4. |
- Beer, Christian, et al.
(författare)
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Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate
- 2010
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 1095-9203 .- 0036-8075. ; 329:5993, s. 834-838
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Tidskriftsartikel (refereegranskat)abstract
- Terrestrial gross primary production (GPP) is the largest global CO2 flux driving several ecosystem functions. We provide an observation-based estimate of this flux at 123 +/- 8 petagrams of carbon per year (Pg C year(-1)) using eddy covariance flux data and various diagnostic models. Tropical forests and savannahs account for 60%. GPP over 40% of the vegetated land is associated with precipitation. State-of-the-art process-oriented biosphere models used for climate predictions exhibit a large between-model variation of GPP's latitudinal patterns and show higher spatial correlations between GPP and precipitation, suggesting the existence of missing processes or feedback mechanisms which attenuate the vegetation response to climate. Our estimates of spatially distributed GPP and its covariation with climate can help improve coupled climate-carbon cycle process models.
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| 5. |
- Besnard, Simon, et al.
(författare)
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Quantifying the effect of forest age in annual net forest carbon balance
- 2018
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Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 13:12
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Tidskriftsartikel (refereegranskat)abstract
- Forests dominate carbon (C) exchanges between the terrestrial biosphere and the atmosphere on land. In the long term, the net carbon flux between forests and the atmosphere has been significantly impacted by changes in forest cover area and structure due to ecological disturbances and management activities. Current empirical approaches for estimating net ecosystem productivity (NEP) rarely consider forest age as a predictor, which represents variation in physiological processes that can respond differently to environmental drivers, and regrowth following disturbance. Here, we conduct an observational synthesis to empirically determine to what extent climate, soil properties, nitrogen deposition, forest age and management influence the spatial and interannual variability of forest NEP across 126 forest eddy-covariance flux sites worldwide. The empirical models explained up to 62% and 71% of spatio-temporal and across-site variability of annual NEP, respectively. An investigation of model structures revealed that forest age was a dominant factor of NEP spatio-temporal variability in both space and time at the global scale as compared to abiotic factors, such as nutrient availability, soil characteristics and climate. These findings emphasize the importance of forest age in quantifying spatio-temporal variation in NEP using empirical approaches.
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| 6. |
- Carvalhais, Nuno, et al.
(författare)
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Global covariation of carbon turnover times with climate in terrestrial ecosystems
- 2014
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 514:7521, s. 213-
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Tidskriftsartikel (refereegranskat)abstract
- The response of the terrestrial carbon cycle to climate change is among the largest uncertainties affecting future climate change projections(1,2). The feedback between the terrestrial carbon cycle and climate is partly determined by changes in the turnover time of carbon in land ecosystems, which in turn is an ecosystem property that emerges from the interplay between climate, soil and vegetation type(3-6). Here we present a global, spatially explicit and observation-based assessment of whole-ecosystem carbon turnover times that combines new estimates of vegetation and soil organic carbon stocks and fluxes. We find that the overall mean global carbon turnover time is 23(4)(+7) years (95 per cent confidence interval). Onaverage, carbon resides in the vegetation and soil near the Equator for a shorter time than at latitudes north of 75 degrees north (mean turnover times of 15 and 255 years, respectively). We identify a clear dependence of the turnover time on temperature, as expected from our present understanding of temperature controls on ecosystem dynamics. Surprisingly, our analysis also reveals a similarly strong association between turnover time and precipitation. Moreover, we find that the ecosystem carbon turnover times simulated by state-of-the-art coupled climate/carbon-cycle models vary widely and that numerical simulations, on average, tend to underestimate the global carbon turnover time by 36 per cent. The models show stronger spatial relationships with temperature than do observation-based estimates, but generally do not reproduce the strong relationships with precipitation and predict faster carbon turnover in many semiarid regions. Our findings suggest that future climate/carbon-cycle feedbacks may depend more strongly on changes in the hydrological cycle than is expected at present and is considered in Earth system models.
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| 7. |
- Erb, Karl-Heinz, et al.
(författare)
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Unexpectedly large impact of forest management and grazing on global vegetation biomass
- 2018
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 553:7686, s. 73-76
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Tidskriftsartikel (refereegranskat)abstract
- Carbon stocks in vegetation have a key role in the climate system(1-4). However, the magnitude, patterns and uncertainties of carbon stocks and the effect of land use on the stocks remain poorly quantified. Here we show, using state-of-the-art datasets, that vegetation currently stores around 450 petagrams of carbon. In the hypothetical absence of land use, potential vegetation would store around 916 petagrams of carbon, under current climate conditions. This difference highlights the massive effect of land use on biomass stocks. Deforestation and other land-cover changes are responsible for 53-58% of the difference between current and potential biomass stocks. Land management effects (the biomass stock changes induced by land use within the same land cover) contribute 42-47%, but have been underestimated in the literature. Therefore, avoiding deforestation is necessary but not sufficient for mitigation of climate change. Our results imply that trade-offs exist between conserving carbon stocks on managed land and raising the contribution of biomass to raw material and energy supply for the mitigation of climate change. Efforts to raise biomass stocks are currently verifiable only in temperate forests, where their potential is limited. By contrast, large uncertainties hinder verification in the tropical forest, where the largest potential is located, pointing to challenges for the upcoming stocktaking exercises under the Paris agreement.
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| 8. |
- Li, Wei, et al.
(författare)
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Land-use and land-cover change carbon emissions between 1901 and 2012 constrained by biomass observations
- 2017
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Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 14:22, s. 5053-5067
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Tidskriftsartikel (refereegranskat)abstract
- The use of dynamic global vegetation models (DGVMs) to estimate CO2 emissions from land-use and land-cover change (LULCC) offers a new window to account for spatial and temporal details of emissions and for ecosystem processes affected by LULCC. One drawback of LULCC emissions from DGVMs, however, is lack of observation constraint. Here, we propose a new method of using satellite-and inventory-based biomass observations to constrain historical cumulative LULCC emissions (E-LUC(c)) from an ensemble of nine DGVMs based on emerging relationships between simulated vegetation biomass and E-LUC(c). This method is applicable on the global and regional scale. The original DGVM estimates of E-LUC(c) range from 94 to 273 PgC during 1901-2012. After constraining by current biomass observations, we derive a best estimate of 155 +/- 50 PgC (1 sigma Gaussian error). The constrained LULCC emissions are higher than prior DGVM values in tropical regions but significantly lower in North America. Our emergent constraint approach independently verifies the median model estimate by biomass observations, giving support to the use of this estimate in carbon budget assessments. The uncertainty in the constrained Ec LUC is still relatively large because of the uncertainty in the biomass observations, and thus reduced uncertainty in addition to increased accuracy in biomass observations in the future will help improve the constraint. This constraint method can also be applied to evaluate the impact of land-based mitigation activities.
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| 9. |
- Luo, Yiqi, et al.
(författare)
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Toward more realistic projections of soil carbon dynamics by Earth system models
- 2016
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Ingår i: Global Biogeochemical Cycles. - 0886-6236. ; 30:1, s. 40-56
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Tidskriftsartikel (refereegranskat)abstract
- Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.
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| 10. |
- Migliavacca, Mirco, et al.
(författare)
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Semiempirical modeling of abiotic and biotic factors controlling ecosystem respiration across eddy covariance sites
- 2011
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Ingår i: Global Change Biology. - : Wiley. - 1354-1013. ; 17:1, s. 390-409
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Tidskriftsartikel (refereegranskat)abstract
- In this study we examined ecosystem respiration (R-ECO) data from 104 sites belonging to FLUXNET, the global network of eddy covariance flux measurements. The goal was to identify the main factors involved in the variability of R-ECO: temporally and between sites as affected by climate, vegetation structure and plant functional type (PFT) (evergreen needleleaf, grasslands, etc.). We demonstrated that a model using only climate drivers as predictors of R-ECO failed to describe part of the temporal variability in the data and that the dependency on gross primary production (GPP) needed to be included as an additional driver of R-ECO. The maximum seasonal leaf area index (LAI(MAX)) had an additional effect that explained the spatial variability of reference respiration (the respiration at reference temperature T-ref=15 degrees C, without stimulation introduced by photosynthetic activity and without water limitations), with a statistically significant linear relationship (r2=0.52, P < 0.001, n=104) even within each PFT. Besides LAI(MAX), we found that reference respiration may be explained partially by total soil carbon content (SoilC). For undisturbed temperate and boreal forests a negative control of total nitrogen deposition (N-depo) on reference respiration was also identified. We developed a new semiempirical model incorporating abiotic factors (climate), recent productivity (daily GPP), general site productivity and canopy structure (LAI(MAX)) which performed well in predicting the spatio-temporal variability of R-ECO, explaining > 70% of the variance for most vegetation types. Exceptions include tropical and Mediterranean broadleaf forests and deciduous broadleaf forests. Part of the variability in respiration that could not be described by our model may be attributed to a series of factors, including phenology in deciduous broadleaf forests and management practices in grasslands and croplands.
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