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- Anav, Alessandro, et al.
(författare)
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Spatiotemporal patterns of terrestrial gross primary production : A review
- 2015
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Ingår i: Reviews of geophysics. - 8755-1209 .- 1944-9208. ; 53:3, s. 785-818
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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.
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| 2. |
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| 3. |
- Murray-Tortarolo, Guillermo, et al.
(författare)
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The dry season intensity as a key driver of NPP trends
- 2016
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Ingår i: Geophysical Research Letters. - 1944-8007. ; 43:6, s. 2632-2639
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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.
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| 4. |
- Piao, Shilong, et al.
(författare)
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Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends
- 2013
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Ingår i: Global Change Biology. - : Wiley. - 1354-1013. ; 19:7, s. 2117-2132
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Tidskriftsartikel (refereegranskat)abstract
- The purpose of this study was to evaluate 10 process-based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity (GPP) is compared with flux-tower-based estimates by Jung etal. [Journal of Geophysical Research 116 (2011) G00J07] (JU11). The net primary productivity (NPP) apparent sensitivity to climate variability and atmospheric CO2 trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO2 sensitivity of NPP is compared to the results from four Free-Air CO2 Enrichment (FACE) experiments. The simulated global net biome productivity (NBP) is compared with the residual land sink (RLS) of the global carbon budget from Friedlingstein etal. [Nature Geoscience 3 (2010) 811] (FR10). We found that models produce a higher GPP (133 +/- 15Pg Cyr-1) than JU11 (118 +/- 6Pg Cyr-1). In response to rising atmospheric CO2 concentration, modeled NPP increases on average by 16% (5-20%) per 100ppm, a slightly larger apparent sensitivity of NPP to CO2 than that measured at the FACE experiment locations (13% per 100ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 +/- 0.8Pg Cyr-1 is remarkably close to the mean value of RLS (2.1 +/- 1.2 Pg Cyr-1). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980-2009. Both model-to-model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is -3.0 +/- 1.5Pg Cyr-1 degrees C-1, within the uncertainty of what derived from RLS (-3.9 +/- 1.1Pg Cyr-1 degrees C-1). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO2 and climate, the agreement between modeled and observation-based GPP and NBP can be fortuitous. Carbon-nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO2 concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models.
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