Modelling climate change impacts on maize yields under low nitrogen input conditions in sub-Saharan Africa.

Smallholder farmers in sub-Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low-input systems is currently lacking. We evaluated the impact of varying [CO2 ], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi-arid Rwanda, hot subhumid Ghana and hot semi-arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in-season soil water content from 2-year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2 ], temperature and rainfall. Without N fertilizer input, maize (a) benefited less from an increase in atmospheric [CO2 ]; (b) was less affected by higher temperature or decreasing rainfall; and (c) was more affected by increased rainfall because N leaching was more critical. The model intercomparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low-input systems. Climate change and N input interactions have strong implications for the design of robust adaptation approaches across SSA, because the impact of climate change in low input systems will be modified if farmers intensify maize production with balanced nutrient management.

Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments.

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some breadbasket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in an increase in vulnerable households and the poverty rate.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.

Biophysical and economic implications for agriculture of +1.5° and +2.0°C global warming using AgMIP Coordinated Global and Regional Assessments.

This study presents results of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Global and Regional Assessments (CGRA) of +1.5° and +2.0°C global warming above pre-industrial conditions. This first CGRA application provides multi-discipline, multi-scale, and multi-model perspectives to elucidate major challenges for the agricultural sector caused by direct biophysical impacts of climate changes as well as ramifications of associated mitigation strategies. Agriculture in both target climate stabilizations is characterized by differential impacts across regions and farming systems, with tropical maize Zea mays experiencing the largest losses, while soy Glycine max mostly benefits. The result is upward pressure on prices and area expansion for maize and wheat Triticum aestivum, while soy prices and area decline (results for rice Oryza sativa are mixed). An example global mitigation strategy encouraging bioenergy expansion is more disruptive to land use and crop prices than the climate change impacts alone, even in the +2.0°C scenario which has a larger climate signal and lower mitigation requirement than the +1.5°C scenario. Coordinated assessments reveal that direct biophysical and economic impacts can be substantially larger for regional farming systems than global production changes. Regional farmers can buffer negative effects or take advantage of new opportunities via mitigation incentives and farm management technologies. Primary uncertainties in the CGRA framework include the extent of CO2 benefits for diverse agricultural systems in crop models, as simulations without CO2 benefits show widespread production losses that raise prices and expand agricultural area.

Towards a new generation of agricultural system data, models and knowledge products: Information and communication technology.

Agricultural modeling has long suffered from fragmentation in model implementation. Many models are developed, there is much redundancy, models are often poorly coupled, model component re-use is rare, and it is frequently difficult to apply models to generate real solutions for the agricultural sector. To improve this situation, we argue that an open, self-sustained, and committed community is required to co-develop agricultural models and associated data and tools as a common resource. Such a community can benefit from recent developments in information and communications technology (ICT). We examine how such developments can be leveraged to design and implement the next generation of data, models, and decision support tools for agricultural production systems. Our objective is to assess relevant technologies for their maturity, expected development, and potential to benefit the agricultural modeling community. The technologies considered encompass methods for collaborative development and for involving stakeholders and users in development in a transdisciplinary manner. Our qualitative evaluation suggests that as an overall research challenge, the interoperability of data sources, modular granular open models, reference data sets for applications and specific user requirements analysis methodologies need to be addressed to allow agricultural modeling to enter in the big data era. This will enable much higher analytical capacities and the integrated use of new data sources. Overall agricultural systems modeling needs to rapidly adopt and absorb state-of-the-art data and ICT technologies with a focus on the needs of beneficiaries and on facilitating those who develop applications of their models. This adoption requires the widespread uptake of a set of best practices as standard operating procedures.

Brief history of agricultural systems modeling.

Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the "next generation" models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of this history and its lessons to ensure that we avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statistical models based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for the major advances in agricultural systems science that are needed for the next generation of models, databases, knowledge products and decision support systems. The lessons from history should be considered to help avoid roadblocks and pitfalls as the community develops this next generation of agricultural systems models.

Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science.

We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and need to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.

Medical Students' Perception of Psychotherapy and Predictors for Self-Utilization and Prospective Patient Referrals.

The study explored if willingness to seek psychotherapy or refer patients to therapy is predicted by either perception of its usefulness or stigma (public and self-stigma), and if there are any differences based on specific psychological disorders for this population. A cross-sectional study was conducted surveying medical students enrolled at a southeastern university during spring 2022. These medical students completed the Mental Help Seeking Attitudes Scale (MHSAS), revised Self-Stigma of Seeking Help Scale (SSOSH-7), Stigma Scale for Receiving Psychological Help (SSRPH), in addition to vignette-based items assessing the likelihood they would seek therapy treatment and refer a patient for therapy based on two specific psychological disorders. The survey was completed by 106 medical students out of 495 current students (21.4% response rate). The data reveal that the greater the public stigma endorsed, the less likely medical students would be willing to seek therapy for panic disorder; however, the greater the self-stigma, the less likely they would seek therapy for depression. This study found differences in willingness to utilize therapy based on stigma-related attitudes and specific disorders, but not for referring patients.

Mental Health Disclosure Questions on Medical Licensure Applications: Implications for Medical Students, Residents, and Physicians.

Medical trainees and physicians experience high rates of depression, anxiety, suicidal ideation, and burnout. The stigma surrounding mental health may deter help-seeking behaviors and increase informal treatment to maintain anonymity. Invasive health history questions on state medical licensure applications regarding mental health diagnoses and treatment likely increase stigma, reduce help-seeking, and consequently may motivate some applicants to report an inaccurate history to the state medical board. Research on physician mental health, suicide rates, and lack of help-seeking have led to recommendations for changes to licensure questions. In this article, the authors review the language of health history questions, disclosure requirements for applicants, and the potential consequences of disclosing mental health or substance abuse history on state medical licensure applications. They review recent changes to some states' health history questions, using the changes to Florida's licensure application in 2021 as an example, and explore the implications of these changes for reducing stigma and encouraging help-seeking. The authors recommend that state medical boards review and refine licensure applications' health history questions regarding mental health disclosure in ways that strategically address concerns related to stigma, bias, and unwarranted scrutiny. They call for research to examine the impact of such question changes on applicant response accuracy, help-seeking behaviors, and mental health outcomes and stigma. They also recommend that medical schools offer and promote access to mental health services, encourage faculty to normalize help-seeking behaviors, and provide students with information about state licensure processes. Reducing stigma, normalizing trainee and physician experiences, and promoting help-seeking are preliminary steps to promote a culture in academic medicine that prioritizes mental health. In turn, this will encourage trainees and physicians to care for themselves and cultivate physicians who are better equipped to heal and support their patients.

Indigenous Resilience in Australia: A Scoping Review Using a Reflective Decolonizing Collective Dialogue.

Contemporary definitions and understandings of resilience refer to an individual's positive adaptation to the experience of adversity. One of the challenges of this extant body of work is that the central concept of resilience is rarely questioned. Current understandings of these concepts, largely framed in Western understandings, are unquestioningly accepted, reframed for, yet not by, Indigenous peoples, and then are unchallenged when imposed on Indigenous peoples. A scoping review was conducted and reported in line with the PRISMA-ScR guidelines. The review involved the participation of local Aboriginal Research Cultural Advisory Groups who participated and approved the analysis of the findings and collaborated on the design and writing of the paper. Eight publications drew on Aboriginal constructs of resilience in examining the effectiveness of programs, processes, and practices to promote individual and/or collective resilience and well-being. Most studies emphasized the need for strategies to strengthen individual or community connection to culture to foster resilience. Six studies used culturally validated strength-based tools to measure resilience, while two relied on Western constructs. This review reveals both the distinctive colonial characteristics of adversity experienced by Aboriginal people and the range of coping strategies and protective resources that support the development of resilience within different Aboriginal communities in diverse research sites across Australia. Importantly, many studies confirm adversity is linked to the enduring legacies of colonization, continuous and cumulative transgenerational grief and loss, structural inequities, racism, and discrimination. These external factors of adversity are unique to Aboriginal populations, as are the protective factors that entail strengthening connection to culture (including language reclamation), community, ancestry and land (including management and economic development) which contribute to individual and collective resilience. These findings suggest that Aboriginal community resilience is strengthened through the collective experience of adversity, such as transgenerational grief and loss, and the resulting support structures and shared resources that are developed and maintained through cultural practices to strengthen the bonds and mutual reciprocity to participate in transformative strategies to address adversity. This review highlights that strategies such as building on community strengths, capacities, and resources is critical when strengthening resilience within Indigenous communities across Australia.

Influence of COVID-19 on the preventive health behaviours of indigenous peoples of Australia residing in New South Wales: a mixed-method study protocol.

INTRODUCTION: Chronic conditions impact indigenous peoples of Australia at a much higher rate than non-indigenous Australians. Attendance at the Medicare Benefits Scheme (MBS) supported indigenous health checks are crucial to improve prevention and management of chronic health conditions. However, in conjunction with lifestyle and environmental factors, attendance rates at primary healthcare services for screening and treatment have fallen in Australia during the COVID-19 pandemic. This study aims to explore the influence of the COVID-19 pandemic on preventive health behaviours of indigenous Australians and the associated barriers to, and enablers of, engagement with health services to formulate a targeted intervention strategy. METHODS AND ANALYSIS: A concurrent mixed-methods study (comprising quantitative and qualitative data collection methods) will be employed. Descriptive analysis of MBS data about the characteristics of indigenous peoples of Australia claiming health assessment services will be performed. Generalised estimating equation regression models will be used to examine the use of health assessment services over time. Qualitative interviews informed by indigenous research methods will be conducted. Interviews will investigate barriers to, and enablers of, engagement with health services. Thematic approach guided by the principles of indigenist praxis, storytelling and collaborative research will be used to analyse the interview data. The project commenced in July 2020 and will be completed by July 2022. ETHICS AND DISSEMINATION: The project received ethics approval from the Aboriginal Health and Medical Research Council of New South Wales and the University of New England Human Research Ethics Committee. Findings will be disseminated via peer-reviewed journal articles, conferences, government and relevant stakeholder reports, and infographics.

Climate impacts on global agriculture emerge earlier in new generation of climate and crop models.

Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project's Global Gridded Crop Model Intercomparison based on the Coupled Model Intercomparison Project Phase 5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new twenty-first-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to -6% (SSP126) and from +1% to -24% (SSP585)-explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO2 concentrations and expanded high-latitude gains. The 'emergence' of climate impacts consistently occurs earlier in the new projections-before 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.

Mythic dyes or mythic colour? New insight into the use of purple dyes on codices.

The traditional knowledge concerning the use of Tyrian purple in Late Antique and Medieval purple codices - those precious biblical texts written with noble metal inks on parchment dyed or painted with purple colourants - is here updated in view of new analytical evidence. Recent literature reports the analysis carried out on some purple codices, suggesting that Tyrian purple has not, if ever, been used in their making. A large number of purple codices has been considered in this work to elucidate the nature of the purple colour. Results have been discussed within the frame of previous information, thus covering a vast majority of the purple codices presently identified. In most of the instances the use of less expensive dyes such as folium or orchil is suggested. Moreover, analytical results from a non-invasive spectroscopic approach have been definitely confirmed by micro-invasive surface-enhanced Raman analysis performed on micro samples of purple parchment taken from two 6th century codices.

Test--retest reliability of a modified multiple point stimulation technique for motor unit number estimation.

OBJECTIVE: Multiple point stimulation (MPS) is a widely used technique to estimate the number of motor units in a muscle. Test-retest reliability must be high for the motor unit number estimates to be clinically useful. We hypothesized that the reliability of MPS can be improved by using a long stimulus pulse width (1ms), in addition to the standard 0.05ms pulse width. METHODS: Median nerve innervated thenar muscles were examined in 11 young subjects, 27+/-3 (mean +/-SD) years old and in 5 elderly subjects, 71+/-11 years old. The experimenter conducted the studies twice on each subject. RESULTS: Test-retest reliability, using the modified MPS technique, was substantially higher (Cronbach's alpha of 0.88) than using the standard method (Cronbach's alpha of 0.80) in the young subjects. In contrast, for the elderly subjects the test-retest reliability of MUNE was high for both the modified technique (Cronbach's alpha of 0.96) and the standard technique (Cronbach's alpha of 0.99). CONCLUSIONS: Test-retest reliability of MPS can be significantly improved by using a long stimulus pulse width and the standard stimulus pulse width in younger subjects. However, this is not necessary in elderly subjects. SIGNIFICANCE: The greater reliability of this modified MPS method should enhance its clinical utility.

Fuzzy Union to Assess Climate Suitability of Annual Ryegrass (Lolium multiflorum), Alfalfa (Medicago sativa) and Sorghum (Sorghum bicolor).

The Law of the Minimum is often implemented using t-norm or fuzzy intersection. We propose the use of t-conorm or fuzzy union for climate suitability assessment of a grass species using annual ryegrass (Lolium multiflorum Lam.) as an example and evaluate the performance for alfalfa (Medicago sativa L.) and sorghum (Sorghum bicolor L.). The ORF and ANDF models, which are fuzzy logic systems based on t-conorm and t-norm between temperature and moisture conditions, respectively, were developed to assess the quality of climate conditions for crops. The parameter values for both models were obtained from existing knowledge, e.g., the EcoCrop database. These models were then compared with the EcoCrop model, which is based on the t-norm. The ORF model explained greater variation (54%) in the yield of annual ryegrass at 84 site-years than the ANDF model (43%) and the EcoCrop model (5%). The climate suitability index of the ORF model had the greatest likelihood of occurrence of annual ryegrass compared to the other models. The ORF model also had similar results for alfalfa and sorghum. We emphasize that the fuzzy logic system for climate suitability assessment can be developed using knowledge rather than presence-only data, which can facilitate more complex approaches such as the incorporation of biotic interaction into species distribution modeling.

On the identification of folium and orchil on illuminated manuscripts.

The identification of the two purple dyes folium and orchil has rarely been reported in the analysis of painted artworks, especially when analysing illuminated manuscripts. This is not consistent with the fact that ancient literary sources suggested their use as substitutes for the more expensive Tyrian purple dye. By employing non-invasive spectroscopic techniques, the present work demonstrates that these dyes were actually widely used in the production of ancient manuscripts. By employing UV-visible diffuse reflectance spectrophotometry with optic fibres (FORS) and spectrofluorimetry, the abundant identification of both dyes on medieval manuscripts was performed by comparing the spectra recorded on ancient codices with those obtained on accurate replicas of dyed or painted parchment. Moreover, examples are also reported whereby the considered purple dyes were used in mixtures with other colourants. The overall information obtained here allowed us to define new boundaries for the time range in which orchil and folium dyes were used which is wider than previously thought, and to focus on their particular uses in the decoration of books.

Improving agricultural knowledge management: The AgTrials experience.

Background: Opportunities to use data and information to address challenges in international agricultural research and development are expanding rapidly. The use of agricultural trial and evaluation data has enormous potential to improve crops and management practices. However, for a number of reasons, this potential has yet to be realized. This paper reports on the experience of the AgTrials initiative, an effort to build an online database of agricultural trials applying principles of interoperability and open access. Methods: Our analysis evaluates what worked and what did not work in the development of the AgTrials information resource. We analyzed data on our users and their interaction with the platform. We also surveyed our users to gauge their perceptions of the utility of the online database. Results: The study revealed barriers to participation and impediments to interaction, opportunities for improving agricultural knowledge management and a large potential for the use of trial and evaluation data.  Conclusions: Technical and logistical mechanisms for developing interoperable online databases are well advanced.  More effort will be needed to advance organizational and institutional work for these types of databases to realize their potential.

Transcranial direct current stimulation of the primary motor cortex affects cortical drive to human musculature as assessed by intermuscular coherence.

Intermuscular coherence analysis can be used to assess the common drive to muscles. Coherence in the beta-frequency band (15-35 Hz) is thought to arise from common cortical sources. Intermuscular coherence analysis is a potentially attractive tool for the investigation of motor cortical excitability changes because it is non-invasive and can be done relatively quickly. We carried out this study to test the hypothesis that intermuscular coherence analysis was able to detect cortical excitability changes in healthy subjects following transcranial direct current stimulation (tDCS). tDCS has been shown to increase (anodal stimulation) or decrease (cathodal stimulation) the size of the muscle potential evoked by TMS. We found that anodal tDCS caused an increase in motor evoked potential (MEP) size that was paralleled by an increase in beta-band intermuscular coherence. Similarly, the reduction in MEP size produced by cathodal tDCS was paralleled by a reduction in beta-band intermuscular coherence, while sham stimulation did not result in any change in either MEP amplitude or beta-band intermuscular coherence. The similar pattern of change observed for MEP and intermuscular coherence may indicate similar mechanisms of action, although this cannot be assumed without further investigation. These changes do suggest that at least some of the action of tDCS is on cortical networks, and that combined tDCS and intermuscular coherence analysis may be useful in the diagnosis of pathologies affecting motor cortical excitability.