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working_groups:cp:collection_of_publications [2021/12/20 10:37]
ameier
working_groups:cp:collection_of_publications [2021/12/22 11:53] (current)
ameier
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-==== Collection of Publications ====+==== Collection of Publications and access to non-open-access publications ====
  
  
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 If that fails, then try this hack [[.collection_of_publications:ups_doi_access_hack| UPC DOI access hack]] If that fails, then try this hack [[.collection_of_publications:ups_doi_access_hack| UPC DOI access hack]]
  
-A) If that fails, then open a new tab in your browser and paste this address  +  
-   https://doi-org.recursos.biblioteca.upc.edu/ +
-into the address bar WITHOUT hitting enter. Then+
  
-B) grab the tail of your DOI html address like "10.1111/gcb.14917" from+== Tables of Literature potentially useful to our work... == 
 +Feel free to create more sub-pages as you see fit. 
 +Please insert any additions alphabetically by sir name of the first author.
  
-   https://doi.org/10.1111/gcb.14917 +[[.collection_of_publications:carbon_cycle  | Carbon Cycle related publications ]]
-or directly from (restrictive) publisher site like this one +
-   https://onlinelibrary.wiley.com/doi/10.1111/gcb.14917+
  
-C) and paste it into the same new tab's address bar to obtain something like this (from our example): +[[.collection_of_publications:ecearth_inner_functioning  | EC-Earth inner functioning related publications ]]
-  https://doi-org.recursos.biblioteca.upc.edu/10.1111/gcb.14917 +
-and hit enter.  +
-If you are lucky your publication may be found and accessed that way as in this example.... +
  
 +[[.collection_of_publications:LPJGUESS_inner_functioning_and_applications  | LPJGUESS inner functioning and application related publications ]]
  
-  +[[.collection_of_publications:lai_publications  | LAI Leaf Area Index related publications ]]
  
-== Table of Literature potentially useful to our work... == +[[.collection_of_publications:lulcc_publications  | LULCC Land Use & Land Cover Change publications ]]
-Please insert any additions alphabetically by sir name of the first author.+
  
 ^ Author      ^ Title, Description, DOI, Document ^ ^ Author      ^ Title, Description, DOI, Document ^
-| Masayuki Kondo | State of the science in reconciling top-down and bottom-up approaches for terrestrial CO2 budget | 
-| 2019 | Their set of atmospheric inversions and bio-sphere models, showed a high level of agreement for global and hemispheric CO2 budgets in the 2000s as well as for the regions of North America and South-east Asia.  Differences in budget estimates are substantial for East Asia and South America. There is uncertainty in several regions as to whether these represent a carbon sink or source. Given these findings, caution should be taken when interpreting regional CO2 budgets.Those uncertainties continue to limit our ability to project the mitigation potential by the terrestrial biosphere. | 
-|  | https://doi.org/10.1111/gcb.14917 | 
-|  | {{ :working_groups:cp:kondo_-_status_of_reconciling_top-down_and_bottom-up_approaches_for_co2_-_2019.pdf |}} | 
-| Andreas Krause | Legacy Effects from Historical Environmental Changes Dominate Future Terrestrial Carbon Uptake | 
-| 2020 | They use LPJ‐GUESS to quantify legacy effects for the 21st century. LUH2 (historic) and bias-corrected IPSL‐CM5A‐LR climate mode (future) are employed to provide land use forcing. The combined legacy effects of historical (1850–2015) environmental changes result in a land carbon uptake of +126 Gt C over the future (2015–2099) period. This by far exceeds the impacts of future environmental changes (range −53 Gt C to +16 Gt C for three scenarios) and is comparable in magnitude to historical carbon losses (−154 Gt C). The response of the biosphere to historical environmental changes dominates future terrestrial carbon cycling at least until mid-century. | 
-|  | https://doi.org/10.1029/2020EF001674 | 
-|  | {{ :working_groups:cp:krause-legacy_effects_from_historical_environmental_changes_2020ef001674.pdf |}} | 
-| Andreas Krause |  Large uncertainty in carbon uptake potential of land-based climate-change mitigation efforts | 
-| 2018 | {{ :working_groups:cp:krause-large_uncertainty_in_carbon_uptake_potential_of_lmts-_2018.pdf |}} | 
-|  | https://doi.org/10.1111/gcb.14144 | 
 | Pete Smith | Which practices co-deliver food security, climate change mitigation and adaptation, and combat land degradation and desertification? | | Pete Smith | Which practices co-deliver food security, climate change mitigation and adaptation, and combat land degradation and desertification? |
 | 2019 |  | | 2019 |  |
 |  | https://doi.org/10.1111/gcb.14878 | |  | https://doi.org/10.1111/gcb.14878 |
 |  | {{ :working_groups:cp:smith_which_practices_co-deliver_food_security_climate_change_mitigation_and_adaptation-2019.pdf |}} | |  | {{ :working_groups:cp:smith_which_practices_co-deliver_food_security_climate_change_mitigation_and_adaptation-2019.pdf |}} |
-| Philip Vergragt et al  | Comparison of forest above-ground biomass from dynamic global vegetation models with spatially explicit remotely sensed observation-based estimates |  
-| 2011 | This paper investigates if and how carbon capture and storage (CCS) could help to avoid reinforcing fossil fuel lock-in. The outcome is that a large-scale BECCS development could be feasible under certain conditions, thus largely avoiding the risk of reinforced fossil fuel lock-in. //Keywords: Carbon capture and storage, Biomass, Fossil fuel// | 
-| | https://doi-org.recursos.biblioteca.upc.edu/10.1111/gcb.15117      |  
-| | {{ :working_groups:cp:vergragt-comparison_of_forest_above-ground_biomass_from_dgvms-1-s2.0-s0959378011000215-main.pdf |}} | 
-| Hui Yang | Comparison of forest above-ground biomass from dynamic global vegetation models with spatially explicit remotely sensed observation-based estimates | 
-| 2020 | Uses the GlobBiomass data set of forest above-ground biomass (AGB) density for the year 2010, obtained from multiple remote sensing and in situ observations at 100 m spatial resolution to evaluate AGB estimated by nine dynamic global vegetation models (DGVMs).Model estimates are 365 ± 66 Pg C compared to 275 (±13.5%) Pg C from GlobBiomass. The results suggest that TRENDY v6 DGVMs tend to underestimate biomass loss from anthropogenic disturbances.| 
-| | https://doi-org.recursos.biblioteca.upc.edu/10.1111/gcb.15117 |  
-| | {{ :working_groups:cp:yang_-_comparison_of_forest_above_ground_biomass-2020.pdf |}} | 
  
working_groups/cp/collection_of_publications.1639996664.txt.gz · Last modified: 2021/12/20 10:37 by ameier