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- 15. Life on land
- 2. Zero hunger
- University of Oxford
Research data keyboard_double_arrow_right Dataset 2022Embargo end date: 30 Jan 2022Publisher:Dryad Authors:Barreaux, Antoine;
Barreaux, Antoine
Barreaux, Antoine in OpenAIREHigginson, Andrew;
Higginson, Andrew
Higginson, Andrew in OpenAIREBonsall, Michael;
English, Sinead;Bonsall, Michael
Bonsall, Michael in OpenAIREHere, we investigate how stochasticity and age-dependence in energy dynamics influence maternal allocation in iteroparous females. We develop a state-dependent model to calculate the optimal maternal allocation strategy with respect to maternal age and energy reserves, focusing on allocation in a single offspring at a time. We introduce stochasticity in energetic costs– in terms of the amount of energy required to forage successfully and individual differences in metabolism – and in feeding success. We systematically assess how allocation is influenced by age-dependence in energetic costs, feeding success, energy intake per successful feeding attempt, and environmentally-driven mortality. First, using stochastic dynamic programming, we calculate the optimal amount of reserves M that mothers allocate to each offspring depending on their own reserves R and age A. The optimal life history strategy is then the set of allocation decisions M(R, A) over the whole lifespan which maximizes the total reproductive success of distant descendants. Second, we simulated the life histories of 1000 mothers following the optimisation strategy and the reserves at the start of adulthood R1, the distribution of which was determined, the distribution of which was determined using an iterative procedure as described . For each individual, we calculated maternal allocation Mt, maternal reserves Rt, and relative allocation Mt⁄Rt at each time period t. The relative allocation helps us to understand how resources are partitioned between mother and offspring. Third, we consider how the optimal strategy varies when there is age-dependence in resource acquisition, energetic costs and survival. Specifically, we include varying scenarios with an age-dependent increase or a decrease with age in energetic costs (c_t), feeding success (q_t), energy intake per successful feeding attempt (y_t), and environmentally-driven extrinsic mortality rate (d_t) (Table 2). We consider the age-dependence of parameters one at a time or in pairs, altering the slope, intercept, or asymptote of the age-dependence (linear or asymptotic function). Our aim is to identify whether the observed reproductive senescence can arise from optimal maternal allocation. As such, we do not impose a decline in selection in later life as all offspring are equally valuable at all ages (for a given maternal allocation), and there are no mutations. For each scenario, we run the backward iteration process with these age-dependent functions, obtain the allocation strategy, and simulate the life history of 1000 individuals based on the novel strategy. We then fit quadratic and linear models to the reproduction of these 1000 individuals using the lme function, nlme package in R. For these models, the response variable is the maternal allocation Mt and explanatory variables are the time period t and t2 (for the quadratic fit only), with individual identity as a random term. We use likelihood ratio tests to compare linear and quadratic models using the anova function (package nlme) with the maximum-likelihood method. If the comparison is significant (p-value <0.05), we considered the quadratic model to have a better fit, otherwise the linear model is considered more parsimonious. We were particularly interested in identifying scenarios where the fit was quadratic with a negative quadratic term. For each scenario, the pseudo R2 conditional value (proportion of variance explained by the fixed and random terms, accounting for individual identity) is calculated to assess the goodness-of-fit of the lme model, on a scale from 0 to 1, using the “r.squared” function, package gabtool. All calculations and coding are done in R. Iteroparous parents face a trade-off between allocating current resources to reproduction versus maximizing survival to produce further offspring. Optimal allocation varies across age, and follows a hump-shaped pattern across diverse taxa, including mammals, birds and invertebrates. This non-linear allocation pattern lacks a general theoretical explanation, potentially because most studies focus on offspring number rather than quality and do not incorporate uncertainty or age-dependence in energy intake or costs. Here, we develop a life history model of maternal allocation in iteroparous animals. We identify the optimal allocation strategy in response to stochasticity when energetic costs, feeding success, energy intake, and environmentally-driven mortality risk are age-dependent. As a case study, we use tsetse, a viviparous insect that produces one offspring per reproductive attempt and relies on an uncertain food supply of vertebrate blood. Diverse scenarios generate a hump-shaped allocation: when energetic costs and energy intake increase with age; and also when energy intake decreases, and energetic costs increase or decrease. Feeding success and mortality risk have little influence on age-dependence in allocation. We conclude that ubiquitous evidence for age-dependence in these influential traits can explain the prevalence of non-linear maternal allocation across diverse taxonomic groups.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:NERC EDS Environmental Information Data Centre Authors:O’Gorman, E.J.;
O’Gorman, E.J.
O’Gorman, E.J. in OpenAIREWarner, E.;
Warner, E.
Warner, E. in OpenAIREMarteinsdóttir, B.;
Helmutsdóttir, V.F.; +2 AuthorsMarteinsdóttir, B.
Marteinsdóttir, B. in OpenAIREO’Gorman, E.J.;
O’Gorman, E.J.
O’Gorman, E.J. in OpenAIREWarner, E.;
Warner, E.
Warner, E. in OpenAIREMarteinsdóttir, B.;
Helmutsdóttir, V.F.;Marteinsdóttir, B.
Marteinsdóttir, B. in OpenAIREEhrlén, J.;
Ehrlén, J.
Ehrlén, J. in OpenAIRERobinson, S.I.;
Robinson, S.I.
Robinson, S.I. in OpenAIREHerbivory assessments were made at the plant community and species levels. We focused on three plant species with a widespread occurrence across the temperature gradient: cuckooflower (Cardamine pratensis, Linnaeus), common mouse-ear (Cerastium fontanum, Baumgerten), and marsh violet (Viola palustris, Linnaeus). For assessments of invertebrate herbivory at the species level, thirty individuals per species of C. pratensis, C. fontanum, and V. palustris were marked in each of ten plots, using a stratified random sampling method where individuals were randomly selected, but the full range of within-plot soil temperatures was represented. For assessments of invertebrate herbivory at the community level, five 50 × 50 cm quadrats were marked at random points in eight of the plots that best captured the full temperature gradient. The community-level herbivory assessment was conducted on 19th June. The number of damaged plants was recorded out of 100 random individuals, selected using a 10 × 10 grid within each 50 × 50 cm quadrat. For the species-level herbivory assessment, individual marked plants were surveyed for signs of invertebrate herbivory every two weeks from 30th May to 2nd July, generating three time-points per species. At each survey, all marked individuals for each species were assessed within a 48-hour period. Plants were recorded as damaged or not damaged by invertebrate herbivores at each time-point. Further details of how phenological stage of development, vegetation community composition, soil temperature, moisture, pH, nitrate, ammonium, and phosphate were recorded are provided in the supporting documentation. This is a dataset of environmental data, vegetation cover, and community- and species-level invertebrate herbivory, sampled at 14 experimental soil plots in the Hengill geothermal valley, Iceland, from May to July 2017. The plots span a temperature gradient of 5-35 °C on average over the sampling period, yet they occur within 1 km of each other and have similar soil moisture, pH, nitrate, ammonium, and phosphate.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors:Neubauer, David;
Neubauer, David
Neubauer, David in OpenAIREFerrachat, Sylvaine;
Siegenthaler-Le Drian, Colombe; Stoll, Jens; +18 AuthorsFerrachat, Sylvaine
Ferrachat, Sylvaine in OpenAIRENeubauer, David;
Neubauer, David
Neubauer, David in OpenAIREFerrachat, Sylvaine;
Siegenthaler-Le Drian, Colombe; Stoll, Jens; Folini, Doris Sylvia;Ferrachat, Sylvaine
Ferrachat, Sylvaine in OpenAIRETegen, Ina;
Tegen, Ina
Tegen, Ina in OpenAIREWieners, Karl-Hermann;
Wieners, Karl-Hermann
Wieners, Karl-Hermann in OpenAIREMauritsen, Thorsten;
Stemmler, Irene; Barthel, Stefan; Bey, Isabelle;Mauritsen, Thorsten
Mauritsen, Thorsten in OpenAIREDaskalakis, Nikos;
Heinold, Bernd;Daskalakis, Nikos
Daskalakis, Nikos in OpenAIREKokkola, Harri;
Kokkola, Harri
Kokkola, Harri in OpenAIREPartridge, Daniel;
Rast, Sebastian; Schmidt, Hauke;Partridge, Daniel
Partridge, Daniel in OpenAIRESchutgens, Nick;
Stanelle, Tanja;Schutgens, Nick
Schutgens, Nick in OpenAIREStier, Philip;
Stier, Philip
Stier, Philip in OpenAIREWatson-Parris, Duncan;
Watson-Parris, Duncan
Watson-Parris, Duncan in OpenAIRELohmann, Ulrike;
Lohmann, Ulrike
Lohmann, Ulrike in OpenAIREProject: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.AerChemMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MPI-ESM1.2-HAM climate model, released in 2017, includes the following components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the ETH Zurich, Switzerland; Max Planck Institut fur Meteorologie, Germany; Forschungszentrum Julich, Germany; University of Oxford, UK; Finnish Meteorological Institute, Finland; Leibniz Institute for Tropospheric Research, Germany; Center for Climate Systems Modeling (C2SM) at ETH Zurich, Switzerland (HAMMOZ-Consortium) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2013 United KingdomPublisher:Springer Science and Business Media LLC Funded by:UKRI | Designer Catalysts for Hi..., UKRI | Designer Catalysts for Hi...UKRI| Designer Catalysts for High Efficiency Biodiesel Production ,UKRI| Designer Catalysts for High Efficiency Biodiesel ProductionAuthors:Martinez Hernandez, E;
Martinez Hernandez, E
Martinez Hernandez, E in OpenAIRESADHUKHAN, J;
Campbell, GM;SADHUKHAN, J
SADHUKHAN, J in OpenAIREMartinez-Herrera, J;
Martinez-Herrera, J
Martinez-Herrera, J in OpenAIREDriven by the need to develop a wide variety of products with low environmental impact, biorefineries need to emerge as highly integrated facilities. This becomes effective when overall mass and energy integration through a centralised utility system design is undertaken. An approach combining process integration, energy and greenhouse gas (GHG) emission analyses is shown in this paper for Jatropha biorefinery design, primarily producing biodiesel using oil-based heterogeneously catalysed transesterification or green diesel using hydrotreatment. These processes are coupled with gasification of husk to produce syngas. Syngas is converted into end products, heat, power and methanol in the biodiesel case or hydrogen in the green diesel case. Anaerobic digestion of Jatropha by-products such as fruit shell, cake and/or glycerol has been considered to produce biogas for power generation. Combustion of fruit shell and cake is considered to provide heat. Heat recovery within biodiesel or green diesel production and the design of the utility (heat and power) system are also shown. The biorefinery systems wherein cake supplies heat for oil extraction and seed drying while fruit shells and glycerol provide power generation via anaerobic digestion into biogas achieve energy efficiency of 53 % in the biodiesel system and 57 % in the green diesel system. These values are based on high heating values (HHV) of Jatropha feedstocks, HHV of the corresponding products and excess power generated. Results showed that both systems exhibit an energy yield per unit of land of 83 GJ ha−1. The global warming potential from GHG emissions of the net energy produced (i.e. after covering energy requirements by the biorefinery systems) was 29 g CO2-eq MJ−1, before accounting credits from displacement of fossil-based energy by bioenergy exported from the biorefineries. Using a systematic integration approach for utilisation of whole Jatropha fruit, it is shown that global warming potential and fossil primary energy use can be reduced significantly if the integrated process schemes combined with optimised cultivation and process parameters are adopted in Jatropha-based biorefineries.
Biomass Conversion a... arrow_drop_down Biomass Conversion and BiorefineryArticle . 2013 . Peer-reviewedLicense: Springer TDMData sources: CrossrefBiomass Conversion and BiorefineryArticle . 2014 . Peer-reviewedData sources: Oxford University Research ArchiveUniversity of Surrey, Guildford: Surrey Scholarship Online.Article . 2014Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 40 citations 40 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
download 72download downloads 72 Powered bymore_vert Biomass Conversion a... arrow_drop_down Biomass Conversion and BiorefineryArticle . 2013 . Peer-reviewedLicense: Springer TDMData sources: CrossrefBiomass Conversion and BiorefineryArticle . 2014 . Peer-reviewedData sources: Oxford University Research ArchiveUniversity of Surrey, Guildford: Surrey Scholarship Online.Article . 2014Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors:Neubauer, David;
Neubauer, David
Neubauer, David in OpenAIREFerrachat, Sylvaine;
Siegenthaler-Le Drian, Colombe; Stoll, Jens; +18 AuthorsFerrachat, Sylvaine
Ferrachat, Sylvaine in OpenAIRENeubauer, David;
Neubauer, David
Neubauer, David in OpenAIREFerrachat, Sylvaine;
Siegenthaler-Le Drian, Colombe; Stoll, Jens; Folini, Doris Sylvia;Ferrachat, Sylvaine
Ferrachat, Sylvaine in OpenAIRETegen, Ina;
Tegen, Ina
Tegen, Ina in OpenAIREWieners, Karl-Hermann;
Wieners, Karl-Hermann
Wieners, Karl-Hermann in OpenAIREMauritsen, Thorsten;
Stemmler, Irene; Barthel, Stefan; Bey, Isabelle;Mauritsen, Thorsten
Mauritsen, Thorsten in OpenAIREDaskalakis, Nikos;
Heinold, Bernd;Daskalakis, Nikos
Daskalakis, Nikos in OpenAIREKokkola, Harri;
Kokkola, Harri
Kokkola, Harri in OpenAIREPartridge, Daniel;
Rast, Sebastian; Schmidt, Hauke;Partridge, Daniel
Partridge, Daniel in OpenAIRESchutgens, Nick;
Stanelle, Tanja;Schutgens, Nick
Schutgens, Nick in OpenAIREStier, Philip;
Stier, Philip
Stier, Philip in OpenAIREWatson-Parris, Duncan;
Watson-Parris, Duncan
Watson-Parris, Duncan in OpenAIRELohmann, Ulrike;
Lohmann, Ulrike
Lohmann, Ulrike in OpenAIREProject: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MPI-ESM1.2-HAM climate model, released in 2017, includes the following components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the ETH Zurich, Switzerland; Max Planck Institut fur Meteorologie, Germany; Forschungszentrum Julich, Germany; University of Oxford, UK; Finnish Meteorological Institute, Finland; Leibniz Institute for Tropospheric Research, Germany; Center for Climate Systems Modeling (C2SM) at ETH Zurich, Switzerland (HAMMOZ-Consortium) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2012 United KingdomPublisher:Wiley Frank Rosell; Ruairidh D. Campbell; Ruairidh D. Campbell; Ruairidh D. Campbell; David W. Macdonald;Pierre Nouvellet;
Chris Newman;Pierre Nouvellet
Pierre Nouvellet in OpenAIREpmid: 24501052
AbstractEcologists are increasingly aware of the importance of environmental variability in natural systems. Climate change is affecting both the mean and the variability in weather and, in particular, the effect of changes in variability is poorly understood. Organisms are subject to selection imposed by both the mean and the range of environmental variation experienced by their ancestors. Changes in the variability in a critical environmental factor may therefore have consequences for vital rates and population dynamics. Here, we examine ≥90‐year trends in different components of climate (precipitation mean and coefficient of variation (CV); temperature mean, seasonal amplitude and residual variance) and consider the effects of these components on survival and recruitment in a population of Eurasian beavers (n = 242) over 13 recent years. Within climatic data, no trends in precipitation were detected, but trends in all components of temperature were observed, with mean and residual variance increasing and seasonal amplitude decreasing over time. A higher survival rate was linked (in order of influence based on Akaike weights) to lower precipitation CV (kits, juveniles and dominant adults), lower residual variance of temperature (dominant adults) and lower mean precipitation (kits and juveniles). No significant effects were found on the survival of nondominant adults, although the sample size for this category was low. Greater recruitment was linked (in order of influence) to higher seasonal amplitude of temperature, lower mean precipitation, lower residual variance in temperature and higher precipitation CV. Both climate means and variance, thus proved significant to population dynamics; although, overall, components describing variance were more influential than those describing mean values. That environmental variation proves significant to a generalist, wide‐ranging species, at the slow end of the slow‐fast continuum of life histories, has broad implications for population regulation and the evolution of life histories.
Global Change Biolog... arrow_drop_down Global Change BiologyArticle . 2012 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 57 citations 57 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Global Change Biolog... arrow_drop_down Global Change BiologyArticle . 2012 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Embargo end date: 12 Jan 2023Publisher:Dryad Floess, Emily; Grieshop, Andrew; Puzzolo, Elisa; Pope, Daniel; Leach, Nicholas; Smith, Christopher J.; Gill-Wiehl, Annelise; Landesman, Katherine;Bailis, Robert;
Bailis, Robert
Bailis, Robert in OpenAIRENearly three billion people in low- and middle-income countries (LMICs) rely on polluting fuels, resulting in millions of avoidable deaths annually. Polluting fuels also emit short-lived climate forcers and greenhouse gases (GHGs). Liquefied petroleum gas (LPG) and grid-based electricity are scalable alternatives to polluting fuels but have raised climate and health concerns. Here, we compare emissions and climate impacts of a business-as-usual household cooking fuel trajectory to four large-scale transitions to gas and/or grid electricity in 77 LMICs. We account for upstream and end-use emissions from gas and electric cooking, assuming electrical grids evolve according to the 2022 World Energy Outlook’s “Stated Policies” Scenario. We input the emissions into a reduced-complexity climate model to estimate radiative forcing and temperature changes associated with each scenario. We find full transitions to LPG and/or electricity decrease emissions from both well-mixed GHG and short-lived climate forcers, resulting in a roughly 5 millikelvin global temperature reduction by 2040. Transitions to LPG and/or electricity also reduce annual emissions of PM2.5 by over 6 Mt (99%) by 2040, which would substantially lower health risks from Household Air Pollution. Primary input data was collected from the following sources: Baseline household fuel choices - WHO household energy database (https://www.nature.com/articles/s41467-021-26036-x) End-use emissions - US EPA lifecycle assessment of household fuels (https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=339679&Lab=NRMRL&simplesearch=0&showcriteria=2&sortby=pubDate&timstype=Published+Report&datebeginpublishedpresented) Upstream emissions - Argonne National Labs GREET Model (https://greet.es.anl.gov/index.php) Current and future population estimates - UNECA (http://data.un.org/Explorer.aspx?d=EDATA) Input data was processed by defining household fuel choice scenarios, estimating national household fuel consumption based on these scenarios, and applying fuel-specific emission factors to create country-specific emission pathways. These emission pathways were input into the FaIR model (https://zenodo.org/record/5513022#.Yt_jfHbMLb0) which generated additional data for each scenario including time series of pollution concentrations, radiative forcing, and temperature changes. All data is provided in CSV format. Nothing proprietary is required.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5061/dryad.jq2bvq8d9&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu1 citations 1 popularity Top 10% influence Average impulse Average Powered by BIP!
visibility 3visibility views 3 download downloads 2 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5061/dryad.jq2bvq8d9&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2010 United Kingdom, AustraliaPublisher:Wiley Authors: da Costa, Antonio Carlos Lola;Galbraith, David;
Almeida, Samuel; Portela, Bruno Takeshi Tanaka; +10 AuthorsGalbraith, David
Galbraith, David in OpenAIREda Costa, Antonio Carlos Lola;Galbraith, David;
Almeida, Samuel; Portela, Bruno Takeshi Tanaka; da Costa, Mauricio;Galbraith, David
Galbraith, David in OpenAIREde Athaydes Silva Junior, João;
Braga, Alan P.; de Gonçalves, Paulo H. L.; de Oliveira, Alex AR; Fisher, Rosie;de Athaydes Silva Junior, João
de Athaydes Silva Junior, João in OpenAIREPhillips, Oliver L.;
Metcalfe, Daniel B.;Phillips, Oliver L.
Phillips, Oliver L. in OpenAIRELevy, Peter;
Meir, Patrick;Levy, Peter
Levy, Peter in OpenAIREFeatured paper: See Editorial p553
Australian National ... arrow_drop_down Australian National University: ANU Digital CollectionsArticleFull-Text: http://hdl.handle.net/1885/79363Data sources: Bielefeld Academic Search Engine (BASE)New PhytologistArticle . 2010 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: CrossrefNatural Environment Research Council: NERC Open Research ArchiveArticle . 2010Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1111/j.1469-8137.2010.03309.x&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesbronze 287 citations 287 popularity Top 1% influence Top 1% impulse Top 1% Powered by BIP!
more_vert Australian National ... arrow_drop_down Australian National University: ANU Digital CollectionsArticleFull-Text: http://hdl.handle.net/1885/79363Data sources: Bielefeld Academic Search Engine (BASE)New PhytologistArticle . 2010 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: CrossrefNatural Environment Research Council: NERC Open Research ArchiveArticle . 2010Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1111/j.1469-8137.2010.03309.x&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2021 France, AustraliaPublisher:Cold Spring Harbor Laboratory Funded by:EC | T-FORCES, UKRI | The multi-year impacts of...EC| T-FORCES ,UKRI| The multi-year impacts of the 2015/2016 El Nino on the carbon cycle of tropical forestsAuthors: Lisa Patrick Bentley;Paul E. Santos-Andrade;
Paul E. Santos-Andrade
Paul E. Santos-Andrade in OpenAIRESami W. Rifai;
Sami W. Rifai; +20 AuthorsSami W. Rifai
Sami W. Rifai in OpenAIRELisa Patrick Bentley;Paul E. Santos-Andrade;
Paul E. Santos-Andrade
Paul E. Santos-Andrade in OpenAIRESami W. Rifai;
Sami W. Rifai; Sami W. Rifai;Sami W. Rifai
Sami W. Rifai in OpenAIRELucas A. Cernusak;
Lucas A. Cernusak
Lucas A. Cernusak in OpenAIRESean M. McMahon;
Sean M. McMahon
Sean M. McMahon in OpenAIRESusan G. Laurance;
Susan G. Laurance
Susan G. Laurance in OpenAIREMichael F. Hutchinson;
Michael F. Hutchinson
Michael F. Hutchinson in OpenAIREImma Oliveras;
Imma Oliveras
Imma Oliveras in OpenAIREOliver L. Phillips;
Oliver L. Phillips
Oliver L. Phillips in OpenAIREDavid Bauman;
David Bauman; David Bauman;David Bauman
David Bauman in OpenAIREMatt Bradford;
Hugo R. Ninantay-Rivera; Jimmy R. Chambi Paucar; Raymond Dempsey;Matt Bradford
Matt Bradford in OpenAIREClaire Fortunel;
Claire Fortunel
Claire Fortunel in OpenAIREBrandon E. McNellis;
Brandon E. McNellis
Brandon E. McNellis in OpenAIREYadvinder Malhi;
Yadvinder Malhi
Yadvinder Malhi in OpenAIREGuillaume Delhaye;
Guillaume Delhaye
Guillaume Delhaye in OpenAIREJesús Aguirre-Gutiérrez;
Jesús Aguirre-Gutiérrez;Jesús Aguirre-Gutiérrez
Jesús Aguirre-Gutiérrez in OpenAIREAbstractA better understanding of how climate affects growth in tree species is essential for improved predictions of forest dynamics under climate change. Long-term climate averages (mean climate) and short-term deviations from these averages (anomalies) both influence tree growth, but the rarity of long-term data integrating climatic gradients with tree censuses has so far limited our understanding of their respective role, especially in tropical systems. Here, we combined 49 years of growth data for 509 tree species across 23 tropical rainforest plots along a climatic gradient to examine how tree growth responds to both climate means and anomalies, and how species functional traits mediate these tree growth responses to climate. We showed that short-term, anomalous increases in atmospheric evaporative demand and solar radiation consistently reduced tree growth. Drier forests and fast-growing species were more sensitive to water stress anomalies. In addition, species traits related to water use and photosynthesis partly explained differences in growth sensitivity to both long-term and short-term climate variations. Our study demonstrates that both climate means and anomalies shape tree growth in tropical forests, and that species traits can be leveraged to understand these demographic responses to climate change, offering a promising way forward to forecast tropical forest dynamics under different climate trajectories.
James Cook Universit... arrow_drop_down James Cook University, Australia: ResearchOnline@JCUArticle . 2022Full-Text: https://doi.org/10.1111/gcb.15982Data sources: Bielefeld Academic Search Engine (BASE)CIRAD: HAL (Agricultural Research for Development)Article . 2022Full-Text: https://hal.inrae.fr/hal-03454584Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/2021.06.08.447571&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu23 citations 23 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert James Cook Universit... arrow_drop_down James Cook University, Australia: ResearchOnline@JCUArticle . 2022Full-Text: https://doi.org/10.1111/gcb.15982Data sources: Bielefeld Academic Search Engine (BASE)CIRAD: HAL (Agricultural Research for Development)Article . 2022Full-Text: https://hal.inrae.fr/hal-03454584Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1101/2021.06.08.447571&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2013 United KingdomPublisher:Proceedings of the National Academy of Sciences Funded by:EC | ECOCHANGEEC| ECOCHANGEAuthors: Macias-Fauria, M; Johnson, EA;Forests are expected to expand into alpine areas because of climate warming, causing land-cover change and fragmentation of alpine habitats. However, this expansion will only occur if the present upper treeline is limited by low-growing season temperatures that reduce plant growth. This temperature limitation has not been quantified at a landscape scale. Here, we show that temperature alone cannot realistically explain high-elevation tree cover over a >100-km 2 area in the Canadian Rockies and that geologic/geomorphic processes are fundamental to understanding the heterogeneous landscape distribution of trees. Furthermore, upslope tree advance in a warmer scenario will be severely limited by availability of sites with adequate geomorphic/topographic characteristics. Our results imply that landscape-to-regional scale projections of warming-induced, high-elevation forest advance into alpine areas should not be based solely on temperature-sensitive, site-specific upper-treeline studies but also on geomorphic processes that control tree occurrence at long (centuries/millennia) timescales.
Proceedings of the N... arrow_drop_down Proceedings of the National Academy of SciencesArticle . 2013 . Peer-reviewedData sources: CrossrefProceedings of the National Academy of SciencesArticle . 2013 . Peer-reviewedData sources: Oxford University Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1073/pnas.1221278110&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 111 citations 111 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
more_vert Proceedings of the N... arrow_drop_down Proceedings of the National Academy of SciencesArticle . 2013 . Peer-reviewedData sources: CrossrefProceedings of the National Academy of SciencesArticle . 2013 . Peer-reviewedData sources: Oxford University Research Archiveadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1073/pnas.1221278110&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu