100,563 research outputs found
Does Economic Optimisation Explain LAI and Leaf Trait Distributions Across an Amazon Soil Moisture Gradient?
No full textModel outputs presented in Flack-Prain, S., Meir, P., Malhi, Y., Smallman, T. L., & Williams, M. (2020).Does Economic Optimisation Explain LAI and Leaf Trait Distributions Across an Amazon Soil Moisture Gradient?. Global Change Biology
A preliminary analysis of factors affecting the rate and magnitude of secondary settlement of landfill waste
No full text
CARDAMOM Brazil C-cycle analysis (1x1 degree; monthly; 2001-2017)
No full textThis dataset contains a netCDF file reporting terrestrial C-cycle analysis of Brazil at 1 x 1 degree spatial and monthly temporal resolutions for 2001 to 2017. The analysis uses the CARDAMOM model-data fusion framework to retrieve information on Brazil's terrestrial C-cycle uncertainty uniquely for each location based on location and time specific observations and their uncertainties. The files contains pixel-level estimates of C storage (plant tissues and dead organic matter), C fluxes (photosynthesis, respiration, fire emissions), allocation of C to plant tissues and their residence times. All variables include uncertainty information reporting the 2.5 %, 25 %, 50 %, 75 % and 97.5% quantiles.The dataset contains a single netCDF file ("CARDAMOM_Brazil_1x1_2001_2017_v1.0.nc") which contains pixel-level outputs of the CARDAMOM model-data fusion system. The analysis resolution is 1 x 1 degree and monthly times step for a 17 year period between 2001 and 2017. The file includes estimates of ecosystem carbon stocks, fluxes and key traits. All estimates include uncertainty quantification derived from CARDAMOM at the 2.5 %, 25 %, 50 %, 75 % and 97.5% quantiles
CARDAMOM Brazil C-cycle multi-DALEC, multi-CMIP6 scenarios (1x1 degree; monthly; 2001-2017)
No full textDataset continues CARDAMOM output for the calibration of 5 DALEC C-cycle models (M1-5) across Brazil for a 17 year period (2001-2017) at a monthly time step and 1 x 1 degree spatial resolution. The calibration used Earth Observation derived estimates of leaf area, above ground woody biomass and databased soil carbon stocks. The calibrated models were then projected to 2100 using 4 climate change scenarios drawn from the UKESM submission to CMIP6. The dataset includes C-stocks, fluxes and ecosystem properties along with their associated parameteric uncertainties. Separate files exist for each model, calibration period and climate change scenario. The multi-model ensemble provides a quantification of the role of model structural uncertainty allowing partitioning of the relative importance of parametric, model structure and climate change scenario uncertainties. This dataset is associated with a paper intended for submission to Earth System Dynamics. Smallman et al., (in prep) Parameter uncertainty dominates forecast error across Brazil for much of the 21st Century.A brief description of differences between each DALEC model are outlined in the M1_M5_summary_description.txt file. The output files include MOHC indicating the scenario was drawn from the Meteorological Office Handley Centre (MOHC). The following scenarios are used SSP1-2.6 W/m2, SSP2-4.5 W/m2, SSP37.0 W/m2 and SSP5-8.5 W/m2. The file name structure is: [Model]_[DATATYPE]_MOHC_[SSPcode]_climate_change_[startyear]_[endyear].nc Specific files are provided per model, per scenario with files separately containing stocks, fluxes and ecosystem properties
ACM-GPP-ETv1
No full textSource code and example for the aggregated canopy model for gross primary productivity and evapotranspiration version 1 (ACM-GPP-ET v1). ACM-GPP-ETv1 is a model of intermediate complexity representing coupled daily plant carbon (photosynthesis or GPP) and water cycles (transpiration, soil evaporation and evaporation of canopy intercepted rainfall). ACM-GPP-ET represents the whole plant hydraulic pathway balancing available water supply and evaporative demand through ecophysiological principles.Software is composed of an input / output code (written in R) and an analysis code base of the simulation mode (written in Fortran). The software package include a example file "ACM_GPP_ET_single_site_test.r", an ./input directory and ./src. The example file deals with input and output of the analysis. The ./input directory contains input drivers for a single site example. The ./src directory contains two Fortran files. ./src/ACM_GPP_ET.f90 contains the main source code of the ACM-GPP-ET model while ./src/ACM_GPP_ET_R_interface.f90 handles in needed interface between the R component of the analysis system and the main Fortran model
Un grand atlas mondial du Sida : M. Smallman-Raynor, A. Cliff et P. Haggett, London International Atlas of Aids
No full textBesancenot Jean-Pierre. Un grand atlas mondial du Sida : M. Smallman-Raynor, A. Cliff et P. Haggett, London International Atlas of Aids. In: Annales de Géographie, t. 102, n°574, 1993. pp. 640-642
Un grand atlas mondial du Sida : M. Smallman-Raynor, A. Cliff et P. Haggett, London International Atlas of Aids
No full textBesancenot Jean-Pierre. Un grand atlas mondial du Sida : M. Smallman-Raynor, A. Cliff et P. Haggett, London International Atlas of Aids. In: Annales de Géographie, t. 102, n°574, 1993. pp. 640-642
The importance of physiological, structural and trait responses to drought stress in driving spatial and temporal variation in GPP across Amazon forests
No full textFolders contain experimental model runs outlined in Flack-Prain et al., 2019, whereby the (i) LAI, (ii) meteorology, (iii) rooting properties, (iv) soil, and (v) leaf photosynthetic capacity for each plot were alternated to that of all other plots.
Plots included in analysis are CAX04, CAX06, TAM05, TAM06, KEN01, KEN02, TAN05 (Tanguro).
File names are ordered PLOT1_PLOT2 where PLOT1 is focal plot, and PLOT2 is the plot of the alternated factor.
"_down" and "_up" are model runs under upper and lower LAI standard error.
file headers are as follows
Daily:
mod_ET(mm/d) Modelled evapotranspiration
mod_LE(MJ/m2/d) Modelled latent energy (latent heat flux)
mod_SoilE(mm/d) Modelled soil evaporation
mod_can_evap(mm/d) Modelled canopy evaporation (evaporated intercepted rainfall)
Soil_WP(MPa) Weighted soil water ptential
plant_resistance Plant resistance to waterflow
canopy_soil_resistance Canopy weighted soil+root hydraulic resistance to water flow
LSC(mmol/m2/s/Mpa) Leaf-soil conductance
sapflow(mm/d) Amount of water that moves through LSC continuum
mean-LAI(m2m-2) Mean Leaf Area Index
Flux:
Ra Autotrophic respiration
Af Carbon allocated to foliage
Aw Carbon alloacted to stem
Ar Carbon allocated to roots
Acr Carbon allocated to coarse roots
Lf Litterfall from foliage
Lw Litterfall from stem
Lr Litterfall from roots
Lcr Litterfall from coarse roots
Rh1 Heterotrophic respiration (litter)
Rh2 Heterotrophic respiration (soil)
D Decomposition
G Gross Primary Productivity
neesum Net Ecosystem Exchange
sumresp total_ET(mm/d)
resp_main Maintenance respiration
resp_growth Growth respiration
resp_l Leaf maintenance respiration
resp_s Stem maintenance respiration
resp_r Root maintenance respiration
resp_cr Coarse root maintenance respiration
resp_l_g Leaf growth respiration
resp_s_g Stem growth respiration
resp_r_g Root growth respiration
resp_cr_g Coarse root growth respiration
alloc_to_labile Carbon allocated to labile
Field data used in model calibration and validation can be accessed via Doughty et al., 2015.
Flack-Prain, S., Meir, P., Malhi, Y., Smallman, T. L., & Williams, M. The importance of physiological, structural and trait responses to drought stress in driving spatial and temporal variation in GPP across Amazon forests.
https://doi.org/10.5194/bg-2019-175
Doughty, C. E., Metcalfe, D. B., Girardin, C. A. J., Amézquita, F. F., Cabrera, D. G., Huasco, W. H., ... & Feldpausch, T. R. (2015). Drought impact on forest carbon dynamics and fluxes in Amazonia. Nature, 519(7541), 78.
doi:10.1038/nature1421
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