2,219 research outputs found
JULES-BE:Representation of bioenergy crops and harvesting in the Joint UK Land Environment Simulator vn5.1
We describe developments to the land surface model JULES, allowing for flexible user-prescribed harvest regimes of various perennial bioenergy crops or natural vegetation types. Our aim is to integrate the most useful aspects of dedicated bioenergy models into dynamic global vegetation models, in order that assessment of bioenergy options can benefit from state-of-the-art Earth system modelling. A new plant functional type (PFT) representing Miscanthus is also presented. The Miscanthus PFT fits well with growth parameters observed at a site in Lincolnshire, UK; however, global observed yields of Miscanthus are far more variable than is captured by the model, primarily owing to the model's lack of representation of crop age and establishment time. Global expansion of bioenergy crop areas under a 2 ?C emissions scenario and balanced greenhouse gas mitigation strategy from the IMAGE integrated assessment model (RCP2.6- SSP2) achieves a mean yield of 4.3 billion tonnes of dry matter per year over 2040-2099, around 30 % higher than the biomass availability projected by IMAGE. In addition to perennial grasses, JULES-BE can also be used to represent short-rotation coppicing, residue harvesting from cropland or forestry and rotation forestry
Robust Ecosystem Demography (RED version 1.0): a parsimonious approach to modelling vegetation dynamics in Earth system models
A significant proportion of the uncertainty in climate projections arises from uncertainty in the representation of land carbon uptake. Dynamic global vegetation models (DGVMs) vary in their representations of regrowth and competition for resources, which results in differing responses to changes in atmospheric CO2 and climate. More advanced cohort-based patch models are now becoming established in the latest DGVMs. These models typically attempt to simulate the size distribution of trees as a function of both tree size (mass or trunk diameter) and age (time since disturbance). This approach can capture the overall impact of stochastic disturbance events on the forest structure and biomass – but at the cost of increasing the number of parameters and ambiguity when updating the probability density function (pdf) in two dimensions. Here we present the Robust Ecosystem Demography (RED), in which the pdf is collapsed onto the single dimension of tree mass. RED is designed to retain the ability of more complex cohort DGVMs to represent forest demography, while also being parameter sparse and analytically solvable for the steady state. The population of each plant functional type (PFT) is partitioned into mass classes with a fixed baseline mortality along with an assumed power-law scaling of growth rate with mass. The analytical equilibrium solutions of RED allow the model to be calibrated against observed forest cover using a single parameter – the ratio of mortality to growth for a tree of a reference mass (μ0). We show that RED can thus be calibrated to the ESA LC_CCI (European Space Agency Land Cover Climate Change Initiative) coverage dataset for nine PFTs. Using net primary productivity and litter outputs from the UK Earth System Model (UKESM), we are able to diagnose the spatially varying disturbance rates consistent with this observed vegetation map. The analytical form for RED circumnavigates the need to spin up the numerical model, making it attractive for application in Earth system models (ESMs). This is especially so given that the model is also highly parameter sparse
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Increased importance of methane reduction for a 1.5 degree target
To understand the importance of methane on the levels of carbon emission reductions required to achieve temperature goals, a processed-based approach is necessary rather than reliance on the Transient Climate Response to Emissions. We show that plausible levels of methane (CH4) mitigation can make a substantial difference to the feasibility of achieving the Paris climate targets through increasing the allowable carbon emissions. This benefit is enhanced by the indirect effects of CH4 on ozone (O3). Here the differing effects of CH4 and CO2 on land carbon storage, including the effects of surface O3, lead to an additional increase in the allowable carbon emissions with CH4 mitigation. We find a simple robust relationship between the change in the 2100 CH4 concentration and the extra allowable cumulative carbon emissions between now and 2100 (0.27 ± 0.05 GtC per ppb CH4). This relationship is independent of modelled climate sensitivity and precise temperature target, although later mitigation of CH4 reduces its value and thus methane reduction effectiveness. Up to 12% of this increase in allowable emissions is due to the effect of surface ozone. We conclude early mitigation of CH4 emissions would significantly increase the feasibility of stabilising global warming below 1.5C, alongside having co-benefits for human and ecosystem health
Supramolecular interactions in clusters of polar and polarizable molecules
We present a model for molecular materials made up of polar and polarizable
molecular units. A simple two state model is adopted for each molecular site
and only classical intermolecular interactions are accounted for, neglecting
any intermolecular overlap. The complex and interesting physics driven by
interactions among polar and polarizable molecules becomes fairly transparent
in the adopted model. Collective effects are recognized in the large variation
of the molecular polarity with supramolecular interactions, and cooperative
behavior shows up with the appearance, in attractive lattices, of discontinuous
charge crossovers. The mean-field approximation proves fairly accurate in the
description of the gs properties of MM, including static linear and non-linear
optical susceptibilities, apart from the region in the close proximity of the
discontinuous charge crossover. Sizeable deviations from the excitonic
description are recognized both in the excitation spectrum and in linear and
non-linear optical responses. New and interesting phenomena are recognized near
the discontinuous charge crossover for non-centrosymmetric clusters, where the
primary photoexcitation event corresponds to a multielectron transfer.Comment: 14 pages, including 11 figure
Influence of ENSO and the NAO on terrestrial carbon uptake in the Texas-northern Mexico region
Climate extremes such as drought and heat waves can cause substantial reductions in terrestrial carbon uptake. Advancing projections of the carbon uptake response to future climate extremes depends on (1) identifying mechanistic links between the carbon cycle and atmospheric drivers, (2) detecting and attributing uptake changes, and (3) evaluating models of land response and atmospheric forcing. Here, we combine model simulations, remote sensing products, and ground observations to investigate the impact of climate variability on carbon uptake in the Texas‐northern Mexico region. Specifically, we (1) examine the relationship between drought, carbon uptake, and variability of El Niño–Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO) using the Joint UK Land‐Environment Simulator (JULES) biosphere simulations from 1950–2012, (2) quantify changes in carbon uptake during record drought conditions in 2011, and (3) evaluate JULES carbon uptake and soil moisture in 2011 using observations from remote sensing and a network of flux towers in the region. Long‐term simulations reveal systematic decreases in regional‐scale carbon uptake during negative phases of ENSO and NAO, including amplified reductions of gross primary production (GPP) (−0.42 ± 0.18 Pg C yr^(−1)) and net ecosystem production (NEP) (−0.14 ± 0.11 Pg C yr^(−1)) during strong La Niña years. The 2011 megadrought caused some of the largest declines of GPP (−0.50 Pg C yr^(−1)) and NEP (−0.23 Pg C yr^(−1)) in our simulations. In 2011, consistent declines were found in observations, including high correlation of GPP and surface soil moisture (r = 0.82 ± 0.23, p = 0.012) in remote sensing‐based products. These results suggest a large‐scale response of carbon uptake to ENSO and NAO, and highlight a need to improve model predictions of ENSO and NAO in order to improve predictions of future impacts on the carbon cycle and the associated feedbacks to climate change
Improved representation of plant functional types and physiology in the Joint UK Land Environment Simulator (JULES v4.2) using plant trait information
Dynamic global vegetation models are used to predict the response of vegetation to climate change. They are essential for planning ecosystem management, understanding carbon cycle–climate feedbacks, and evaluating the potential impacts of climate change on global ecosystems. JULES (the Joint UK Land Environment Simulator) represents terrestrial processes in the UK Hadley Centre family of models and in the first generation UK Earth System Model. Previously, JULES represented five plant functional types (PFTs): broadleaf trees, needle-leaf trees, C3 and C4 grasses, and shrubs. This study addresses three developments in JULES. First, trees and shrubs were split into deciduous and evergreen PFTs to better represent the range of leaf life spans and metabolic capacities that exists in nature. Second, we distinguished between temperate and tropical broadleaf evergreen trees. These first two changes result in a new set of nine PFTs: tropical and temperate broadleaf evergreen trees, broadleaf deciduous trees, needle-leaf evergreen and deciduous trees, C3 and C4 grasses, and evergreen and deciduous shrubs. Third, using data from the TRY database, we updated the relationship between leaf nitrogen and the maximum rate of carboxylation of Rubisco (Vcmax), and updated the leaf turnover and growth rates to include a trade-off between leaf life span and leaf mass per unit area.
Overall, the simulation of gross and net primary productivity (GPP and NPP, respectively) is improved with the nine PFTs when compared to FLUXNET sites, a global GPP data set based on FLUXNET, and MODIS NPP. Compared to the standard five PFTs, the new nine PFTs simulate a higher GPP and NPP, with the exception of C3 grasses in cold environments and C4 grasses that were previously over-productive. On a biome scale, GPP is improved for all eight biomes evaluated and NPP is improved for most biomes – the exceptions being the tropical forests, savannahs, and extratropical mixed forests where simulated NPP is too high. With the new PFTs, the global present-day GPP and NPP are 128 and 62 Pg C year−1, respectively. We conclude that the inclusion of trait-based data and the evergreen/deciduous distinction has substantially improved productivity fluxes in JULES, in particular the representation of GPP. These developments increase the realism of JULES, enabling higher confidence in simulations of vegetation dynamics and carbon storage
Defining and unpacking the core concepts of pharmacology education
Pharmacology education currently lacks a research-based consensus on which core concepts all graduates should know and understand, as well as a valid and reliable means to assess core conceptual learning. The Core Concepts in Pharmacology Expert Group (CC-PEG) from Australia and New Zealand recently identified a set of core concepts of pharmacology education as a first step toward developing a concept inventory—a valid and reliable tool to assess learner attainment of concepts. In the current study, CC-PEG used established methodologies to define each concept and then unpack its key components. Expert working groups of three to seven educators were formed to unpack concepts within specific conceptual groupings: what the body does to the drug (pharmacokinetics); what the drug does to the body (pharmacodynamics); and system integration and modification of drug–response. First, a one-sentence definition was developed for each core concept. Next, sub-concepts were established for each core concept. These twenty core concepts, along with their respective definitions and sub-concepts, can provide pharmacology educators with a resource to guide the development of new curricula and the evaluation of existing curricula. The unpacking and articulation of these core concepts will also inform the development of a pharmacology concept inventory. We anticipate that these resources will advance further collaboration across the international pharmacology education community to improve curricula, teaching, assessment, and learning.Marina Santiago, Elizabeth A. Davis, Tina Hinton, Thomas A. Angelo, Alison Shield, Anna-Marie Babey, Barbara Kemp-Harper, Gregg Maynard, Hesham S. Al-Sallami, Ian F. Musgrave, Lynette B. Fernandes, Suong N. T. Ngo, Arthur Christopoulos, Paul J. Whit
How can the First ISLSCP Field Experiment contribute to present-day efforts to evaluate water stress in JULESv5.0?
The First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), Kansas, US, 1987–1989, made important contributions to the understanding of energy and CO2 exchanges between the land surface and the atmosphere, which heavily influenced the development of numerical land-surface modelling. Now, 30 years on, we demonstrate how the wealth of data collected during FIFE and its subsequent in-depth analysis in the literature continue to be a valuable resource for the current generation of land-surface models. To illustrate, we use the FIFE dataset to evaluate the representation of water stress on tallgrass prairie vegetation in the Joint UK Land Environment Simulator (JULES) and highlight areas for future development. We show that, while JULES is able to simulate a decrease in net carbon assimilation and evapotranspiration during a dry spell, the shape of the diurnal cycle is not well captured. Evaluating the model parameters and results against this dataset provides a case study on the assumptions in calibrating “unstressed” vegetation parameters and thresholds for water stress. In particular, the responses to low water availability and high temperatures are calibrated separately. We also illustrate the effect of inherent uncertainties in key observables, such as leaf area index, soil moisture and soil properties. Given these valuable lessons, simulations for this site will be a key addition to a compilation of simulations covering a wide range of vegetation types and climate regimes, which will be used to improve the way that water stress is represented within JULES
Stomatal optimisation based on xylem hydraulics (SOX) improves land surface model simulation of vegetation responses to climate
This is the final version. Available on open access via the DOI in this record•Land surface models (LSMs) typically use empirical functions to represent vegetation responses to soil drought. These functions largely neglect recent advances in plant ecophysiology that link xylem hydraulic functioning with stomatal responses to climate. •We developed an analytical stomatal optimisation model based on xylem hydraulics (SOX) to predict plant responses to drought. Coupling SOX to the Joint UK Land Environment Simulator (JULES) LSM, we conducted a global evaluation of SOX against leaf- and ecosystem-level observations. •SOX simulates leaf stomatal conductance responses to climate for woody plants more accurately and parsimoniously than the existing JULES stomatal conductance model. An ecosystem-level evaluation at 70 eddy flux sites shows that SOX decreases the sensitivity of gross primary productivity (GPP) to soil moisture, which improves the model agreement with observations and increases the predicted annual GPP by 30% in relation to JULES. SOX decreases JULES root mean squared error in GPP by up to 45 % in evergreen tropical forests, and can simulate realistic patterns of canopy water potential and soil water dynamics at the studied sites. •SOX provides a parsimonious way to incorporate recent advances in plant hydraulics and optimality theory into LSMs, and an alternative to empirical stress factors.Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil)Natural Environment Research Council (NERC
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