| 1. |
- Anav, Alessandro, et al.
(författare)
-
Spatiotemporal patterns of terrestrial gross primary production : A review
- 2015
-
Ingår i: Reviews of geophysics. - 8755-1209 .- 1944-9208. ; 53:3, s. 785-818
-
Forskningsöversikt (refereegranskat)abstract
- Great advances have been made in the last decade in quantifying and understanding the spatiotemporal patterns of terrestrial gross primary production (GPP) with ground, atmospheric, and space observations. However, although global GPP estimates exist, each data set relies upon assumptions and none of the available data are based only on measurements. Consequently, there is no consensus on the global total GPP and large uncertainties exist in its benchmarking. The objective of this review is to assess how the different available data sets predict the spatiotemporal patterns of GPP, identify the differences among data sets, and highlight the main advantages/disadvantages of each data set. We compare GPP estimates for the historical period (1990-2009) from two observation-based data sets (Model Tree Ensemble and Moderate Resolution Imaging Spectroradiometer) to coupled carbon-climate models and terrestrial carbon cycle models from the Fifth Climate Model Intercomparison Project and TRENDY projects and to a new hybrid data set (CARBONES). Results show a large range in the mean global GPP estimates. The different data sets broadly agree on GPP seasonal cycle in terms of phasing, while there is still discrepancy on the amplitude. For interannual variability (IAV) and trends, there is a clear separation between the observation-based data that show little IAV and trend, while the process-based models have large GPP variability and significant trends. These results suggest that there is an urgent need to improve observation-based data sets and develop carbon cycle modeling with processes that are currently treated either very simplistically to correctly estimate present GPP and better quantify the future uptake of carbon dioxide by the world's vegetation.
|
|
| 2. |
- Krause, Andreas, et al.
(författare)
-
Large uncertainty in carbon uptake potential of land-based climate-change mitigation efforts
- 2018
-
Ingår i: Global Change Biology. - : Wiley. - 1354-1013. ; 24:7, s. 3025-3038
-
Tidskriftsartikel (refereegranskat)abstract
- Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land-based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land-based mitigation scenarios from two land-use models (IMAGE and MAgPIE) as input to four dynamic global vegetation models (DGVMs; LPJ-GUESS, ORCHIDEE, JULES, LPJmL). Each of the four combinations of land-use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage (BECCS) or avoided deforestation and afforestation (ADAFF). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVMs is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVMs achieves an equivalent or higher carbon uptake than achieved in the land-use models. The large differences in carbon uptake between the DGVMs and their discrepancy against the carbon uptake in IMAGE and MAgPIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land-use change. Differences between land-use models and DGVMs regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land-based mitigation scenario, and that negative emissions simulated by the DGVMs are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy.
|
|
| 3. |
|
|
| 4. |
- Murray-Tortarolo, Guillermo, et al.
(författare)
-
The dry season intensity as a key driver of NPP trends
- 2016
-
Ingår i: Geophysical Research Letters. - 1944-8007. ; 43:6, s. 2632-2639
-
Tidskriftsartikel (refereegranskat)abstract
- We analyze the impacts of changing dry season length and intensity on vegetation productivity and biomass. Our results show a wetness asymmetry in dry ecosystems, with dry seasons becoming drier and wet seasons becoming wetter, likely caused by climate change. The increasingly intense dry seasons were consistently correlated with a decreasing trend in net primary productivity (NPP) and biomass from different products and could potentially mean a reduction of 10–13% in NPP by 2100. We found that annual NPP in dry ecosystems is particularly sensitive to the intensity of the dry season, whereas an increase in precipitation during the wet season has a smaller effect. We conclude that changes in water availability over the dry season affect vegetation throughout the whole year, driving changes in regional NPP. Moreover, these results suggest that usage of seasonal water fluxes is necessary to improve our understanding of the link between water availability and the land carbon cycle.
|
|
