Projecting grassland sensitivity to climate change from an ensemble of models

The grassland biome covers about one-quarter of the earth’s land area and contributes to the livelihoods of ca. 800 million people. Increased aridity and persistent droughts are projected in the twenty-first century for most of Africa, southern Europe and the Middle East, most of the Americas, Australia and South East Asia. A number of these regions have a large fraction of their land use covered by grasslands and rangelands. Grasslands are the ecosystems that respond most rapidly to precipitation variability. However, global projections of climate change impacts on grasslands are still lacking in the scientific literature. Within AgMIP, based on the C3MP protocol initially developed for crops, we have explored the sensitivity of temperate grasslands to climate change drivers with an ensemble of models. Site calibrated models are used to provide projections under probabilistic climate change scenarios, which are defined by a combination of air temperature, precipitation and atmospheric CO2 changes resulting in 99 runs for each model times site combination. This design provides a test of grassland production, GHG (N2O and CH4) emissions and soil carbon sensitivity to climate change drivers. This integrated approach has been tested for 12 grassland simulation models applied to 19 sites over three continents. We show here that a single polynomial emulator can be fitted with high significance to the results of all models and sites, when these are expressed as relative changes from the optimal combination of climate drivers. This polynomial emulator shows that elevated atmospheric CO2 expands the thermal and hydric range which allows for the development of temperate grasslands. Moreover, we calculate the climatic response surface of GHG emissions per unit grassland production and we show that this surface varies with elevated CO2. From these results we provide first estimates of the impacts of climate change on temperate grasslands based on a range of climate scenarios

Multimodel Evaluation of Nitrous Oxide Emissions From an Intensively Managed Grassland

Process‐based models are useful for assessing the impact of changing management practices and climate on yields and greenhouse gas (GHG) emissions from agricultural systems such as grasslands. They can be used to construct national GHG inventories using a Tier 3 approach. However, accurate simulations of nitrous oxide (N$_{2}$O) fluxes remain challenging. Models are limited by our understanding of soil‐plant‐microbe interactions and the impact of uncertainty in measured input parameters on simulated outputs. To improve model performance, thorough evaluations against in situ measurements are needed. Experimental data of N$_{2}$O emissions under two management practices (control with typical fertilization versus increased clover and no fertilization) were acquired in a Swiss field experiment. We conducted a multimodel evaluation with three commonly used biogeochemical models (DayCent in two variants, PaSim, APSIM in two variants) comparing four years of data. DayCent was the most accurate model for simulating N$_{2}$O fluxes on annual timescales, while APSIM was most accurate for daily N$_{2}$O fluxes. The multimodel ensemble average reduced the error in estimated annual fluxes by 41% compared to an estimate using the Intergovernmental Panel on Climate Change (IPCC)‐derived method for the Swiss agricultural GHG inventory (IPCC‐Swiss), but individual models were not systematically more accurate than IPCC‐Swiss. The model ensemble overestimated the N$_{2}$O mitigation effect of the clover‐based treatment (measured: 39–45%; ensemble: 52–57%) but was more accurate than IPCC‐Swiss (IPCC‐Swiss: 72–81%). These results suggest that multimodel ensembles are valuable for estimating the impact of climate and management on N$_{2}$O emissions

Global Research Alliance N2O chamber methodology guidelines : Summary of modeling approaches

Acknowledgements Funding for this publication was provided by the New Zealand Government to support the objectives of the Livestock Research Group of the Global Research Alliance on Agricultural Greenhouse Gases. Individual authors work contribute to the following projects for which support has been received: Climate smart use of Norwegian organic soils (MYR, 2017-2022) project funded by the Research Council of Norway (decision no. 281109); Scottish Government's Strategic Research Programme, SuperG (under EU Horizon 2020 programme); DEVIL (NE/M021327/1), Soils-R-GRREAT (NE/P019455/1) and the EU H2020 project under Grant Agreement 774378—Coordination of International Research Cooperation on Soil Carbon Sequestration in Agriculture (CIRCASA); to project J-001793, Science and Technology Branch, Agriculture and Agri-Food Canada; and New Zealand Ministry of Business, Innovation and Employment (MBIE) core funding. Thanks to Alasdair Noble and the anonymous reviewers for helpful comments on a draft of this paper and to Anne Austin for editing services.Peer reviewedPublisher PD

Evaluating the Potential of Legumes to Mitigate N2O Emissions From Permanent Grassland Using Process-Based Models

Funding Information: This modeling study was a joint effort of the Models4Pastures project within the framework of FACCE-JPI. Lutz Merbold and Kathrin Fuchs acknowledge funding received for the Swiss contribution to Models4Pastures (FACCE-JPI project, SNSF funded contract: 40FA40_154245/1) and for the Doc. Mobility fellowship (SNSF funded project: P1EZP2_172121). Lutz Merbold further acknowledges the support received for CGIAR Fund Council, Australia (ACIAR), Irish Aid, the European Union, the Netherlands, New Zealand, Switzerland, UK, USAID, and Thailand for funding to the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) as well as for the CGIAR Research Program on Livestock. The NZ contributors acknowledge funding from the New Zealand Government Ministry of Primary Industries to support the aims of the Livestock Research Group of the Global Research Alliance on Agricultural Greenhouse Gases and from AgResearch's Strategic Science Investment Fund (the Forages for Reduced Nitrate Leaching (FRNL) research program). The UK partners acknowledge funding by DEFRA and the RCUK projects: N-Circle (BB/N013484/1), UGRASS (NE/M016900/1), and GREENHOUSE (NE/K002589/1). R.M. Rees and C.F.E. Topp also received funding from the Scottish Government Strategic Research Programme. Lorenzo Brilli, Camilla Dibari, and Marco Bindi received funding from the Italian Ministry of Agricultural Food and Forestry Policies (MiPAAF). The FR partners acknowledge funding from CN-MIP project funded by the French National Research Agency (ANR-13-JFAC-0001) and from ADEME (no. 12-60-C0023). Open access funding enabled and organized by Projekt DEAL Funding Information: This modeling study was a joint effort of the Models4Pastures project within the framework of FACCE‐JPI. Lutz Merbold and Kathrin Fuchs acknowledge funding received for the Swiss contribution to Models4Pastures (FACCE‐JPI project, SNSF funded contract: 40FA40_154245/1) and for the Doc. Mobility fellowship (SNSF funded project: P1EZP2_172121). Lutz Merbold further acknowledges the support received for CGIAR Fund Council, Australia (ACIAR), Irish Aid, the European Union, the Netherlands, New Zealand, Switzerland, UK, USAID, and Thailand for funding to the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) as well as for the CGIAR Research Program on Livestock. The NZ contributors acknowledge funding from the New Zealand Government Ministry of Primary Industries to support the aims of the Livestock Research Group of the Global Research Alliance on Agricultural Greenhouse Gases and from AgResearch's Strategic Science Investment Fund (the Forages for Reduced Nitrate Leaching (FRNL) research program). The UK partners acknowledge funding by DEFRA and the RCUK projects: N‐Circle (BB/N013484/1), UGRASS (NE/M016900/1), and GREENHOUSE (NE/K002589/1). R.M. Rees and C.F.E. Topp also received funding from the Scottish Government Strategic Research Programme. Lorenzo Brilli, Camilla Dibari, and Marco Bindi received funding from the Italian Ministry of Agricultural Food and Forestry Policies (MiPAAF). The FR partners acknowledge funding from CN‐MIP project funded by the French National Research Agency (ANR‐13‐JFAC‐0001) and from ADEME (no. 12‐60‐C0023). Open access funding enabled and organized by Projekt DEAL Publisher Copyright: ©2020. The Authors. Open access funding enabled and organized by Projekt DEALPeer reviewedPublisher PD

How Modelers Model: the Overlooked Social and Human Dimensions in Model Intercomparison Studies

There is a growing realization that the complexity of model ensemble studies depends not only on the models used but also on the experience and approach used by modelers to calibrate and validate results, which remain a source of uncertainty. Here, we applied a multi-criteria decision-making method to investigate the rationale applied by modelers in a model ensemble study where 12 process-based different biogeochemical model types were compared across five successive calibration stages. The modelers shared a common level of agreement about the importance of the variables used to initialize their models for calibration. However, we found inconsistency among modelers when judging the importance of input variables across different calibration stages. The level of subjective weighting attributed by modelers to calibration data decreased sequentially as the extent and number of variables provided increased. In this context, the perceived importance attributed to variables such as the fertilization rate, irrigation regime, soil texture, pH, and initial levels of soil organic carbon and nitrogen stocks was statistically different when classified according to model types. The importance attributed to input variables such as experimental duration, gross primary production, and net ecosystem exchange varied significantly according to the length of the modeler’s experience. We argue that the gradual access to input data across the five calibration stages negatively influenced the consistency of the interpretations made by the modelers, with cognitive bias in “trial-and-error” calibration routines. Our study highlights that overlooking human and social attributes is critical in the outcomes of modeling and model intercomparison studies. While complexity of the processes captured in the model algorithms and parameterization is important, we contend that (1) the modeler’s assumptions on the extent to which parameters should be altered and (2) modeler perceptions of the importance of model parameters are just as critical in obtaining a quality model calibration as numerical or analytical details.info:eu-repo/semantics/acceptedVersio

Mental health needs and services in the West Bank, Palestine

Background Palestine is a low income country with scarce resources, which is seeking independence. This paper discusses the high levels of mental health need found amongst Palestinian people, and examines services, education and research in this area with particular attention paid to the West Bank. Methods CINAHL, PubMed, and Science Direct were used to search for materials. Results and conclusion Evidence from this review is that there is a necessity to increase the availability and quality of mental health care. Mental health policy and services in Palestine need development in order to better meet the needs of service users and professionals. It is essential to raise awareness of mental health and increase the integration of mental health services with other areas of health care. Civilians need their basic human needs met, including having freedom of movement and seeing an end to the occupation. There is a need to enhance the resilience and capacity of community mental health teams. There is a need to increase resources and offer more support, up-to-date training and supervision to mental health teams

The Consensus Coding Sequence (Ccds) Project: Identifying a Common Protein-Coding Gene Set for the Human and Mouse Genomes

Effective use of the human and mouse genomes requires reliable identification of genes and their products. Although multiple public resources provide annotation, different methods are used that can result in similar but not identical representation of genes, transcripts, and proteins. The collaborative consensus coding sequence (CCDS) project tracks identical protein annotations on the reference mouse and human genomes with a stable identifier (CCDS ID), and ensures that they are consistently represented on the NCBI, Ensembl, and UCSC Genome Browsers. Importantly, the project coordinates on manually reviewing inconsistent protein annotations between sites, as well as annotations for which new evidence suggests a revision is needed, to progressively converge on a complete protein-coding set for the human and mouse reference genomes, while maintaining a high standard of reliability and biological accuracy. To date, the project has identified 20,159 human and 17,707 mouse consensus coding regions from 17,052 human and 16,893 mouse genes. Three evaluation methods indicate that the entries in the CCDS set are highly likely to represent real proteins, more so than annotations from contributing groups not included in CCDS. The CCDS database thus centralizes the function of identifying well-supported, identically-annotated, protein-coding regions.National Human Genome Research Institute (U.S.) (Grant number 1U54HG004555-01)Wellcome Trust (London, England) (Grant number WT062023)Wellcome Trust (London, England) (Grant number WT077198

The use of biogeochemical models to evaluate mitigation of greenhouse gas emissions from managed grasslands

Simulation models quantify the impacts on carbon (C) and nitrogen (N) cycling in grasslandsystems caused by changes in management practices. To support agricultural policies, it is however important to contrast the responses of alternative models, which can differ greatly in their treatment of key processes and in their response to management. We applied eight biogeochemical models at five grassland sites (in France, New Zealand, Switzerland, United Kingdom and United States) to compare the sensitivity of modelled C and N fluxes to changes in the density of grazing animals (from 100% to 50% of the original livestock densities), also in combination with decreasing N fertilization levels (reduced to zero from the initial levels). Simulated multi-model median values indicated that input reduction would lead to an increase in the C sink strength (negative net ecosystem C exchange) in intensive grazing systems: −64 ± 74 g C m−2 yr−1 (animal density reduction) and −81 ± 74 g C m−2 yr−1(N and animal density reduction), against the baseline of −30.5 ± 69.5 g C m−2 yr−1 (LSU [livestock units] ≥ 0.76 ha−1 yr−1). Simulations also indicated a strong effect of N fertilizer reduction on N fluxes, e.g. N2O-N emissions decreased from 0.34 ± 0.22 (baseline) to 0.1 ± 0.05 g N m−2 yr−1 (no N fertilization). Simulated decline in grazing intensity had only limited impact on the N balance. The simulated pattern of enteric methane emissions was dominated by high model-to-model variability. The reduction in simulated offtake (animal intake + cut biomass) led to a doubling in net primary production per animal (increased by 11.6 ± 8.1 t C LSU−1 yr−1 across sites). The highest N2O-N intensities (N2O-N/offtake) were simulated at mown and extensively grazed arid sites. We show the possibility of using grassland models to determine sound mitigation practices while quantifying the uncertainties associated with the simulated outputs

Post-Franco Theatre

In the multiple realms and layers that comprise the contemporary Spanish theatrical landscape, “crisis” would seem to be the word that most often lingers in the air, as though it were a common mantra, ready to roll off the tongue of so many theatre professionals with such enormous ease, and even enthusiasm, that one is prompted to wonder whether it might indeed be a miracle that the contemporary technological revolution – coupled with perpetual quandaries concerning public and private funding for the arts – had not by now brought an end to the evolution of the oldest of live arts, or, at the very least, an end to drama as we know it