A trait-based model ensemble approach to design rice plant types for future climate.

Crop models are powerful tools to support breeding because of their capability to explore genotype × environment×management interactions that can help design promising plant types under climate change. However, relationships between plant traits and model parameters are often model specific and not necessarily direct, depending on how models formulate plant morphological and physiological features. This hinders model application in plant breeding. We developed a novel trait-based multi-model ensemble approach to improve the design of rice plant types for future climate projections. We conducted multi-model simulations targeting enhanced productivity, and aggregated results into model-ensemble sets of phenotypic traits as defined by breeders rather than by model parameters. This allowed to overcome the limitations due to ambiguities in trait-parameter mapping from single modelling approaches. Breeders' knowledge and perspective were integrated to provide clear mapping from designed plant types to breeding traits. Nine crop models from the AgMIP-Rice Project and sensitivity analysis techniques were used to explore trait responses under different climate and management scenarios at four sites. The method demonstrated the potential of yield improvement that ranged from 15.8% to 41.5% compared to the current cultivars under mid-century climate projections. These results highlight the primary role of phenological traits to improve crop adaptation to climate change, as well as traits involved with canopy development and structure. The variability of plant types derived with different models supported model ensembles to handle related uncertainty. Nevertheless, the models agreed in capturing the effect of the heterogeneity in climate conditions across sites on key traits, highlighting the need for context-specific breeding programmes to improve crop adaptation to climate change. Although further improvement is needed for crop models to fully support breeding programmes, a trait-based ensemble approach represents a major step towards the integration of crop modelling and breeding to address climate change challenges and develop adaptation options.

Temperature increase reduces global yields of major crops in four independent estimates.

Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population.

Importance of genetic parameters and uncertainty of MANIHOT, a new mechanistic cassava simulation model.

We identified the most sensitive genotype-specific parameters (GSPs) and their contribution to the uncertainty of the MANIHOT simulation model. We applied a global sensitivity and uncertainty analysis (GSUA) of the GSPs to the simulation outputs for the cassava development, growth, and yield in contrasting environments. We compared enhanced Sampling for Uniformity, a qualitative screening method new to crop simulation modeling, and Sobol, a quantitative, variance-based method. About 80% of the GSPs contributed to most of the variation in maximum leaf area index (LAI), yield, and aboveground biomass at harvest. Relative importance of the GSPs varied between warm and cool temperatures but did not differ between rainfed and no water limitation conditions. Interactions between GSPs explained 20% of the variance in simulated outputs. Overall, the most important GSPs were individual node weight, radiation use efficiency, and maximum individual leaf area. Base temperature for leaf development was more important for cool compared to warm temperatures. Parameter uncertainty had a substantial impact on model predictions in MANIHOT simulations, with the uncertainty 2-5 times larger for warm compared to cool temperatures. Identification of important GSPs provides an objective way to determine the processes of a simulation model that are critical versus those that have little relevance.

Global wheat production with 1.5 and 2.0°C above pre-industrial warming.

Efforts to limit global warming to below 2°C in relation to the pre-industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0°C warming above the pre-industrial period) on global wheat production and local yield variability. A multi-crop and multi-climate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by -2.3% to 7.0% under the 1.5°C scenario and -2.4% to 10.5% under the 2.0°C scenario, compared to a baseline of 1980-2010, when considering changes in local temperature, rainfall, and global atmospheric CO2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter-annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer-India, which supplies more than 14% of global wheat. The projected global impact of warming <2°C on wheat production is therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade.

Ester Formation via Symbiotic Activation Utilizing Trichloroacetimidate Electrophiles.

Trichloroacetimidates are useful reagents for the synthesis of esters under mild conditions that do not require an exogenous promoter. These conditions avoid the undesired decomposition of substrates with sensitive functional groups that are often observed with the use of strong Lewis or Brønsted acids. With heating, these reactions have been extended to benzyl esters without electron-donating groups. These inexpensive and convenient methods should find application in the formation of esters in complex substrates.

Multimodel ensembles improve predictions of crop-environment-management interactions.

A recent innovation in assessment of climate change impact on agricultural production has been to use crop multimodel ensembles (MMEs). These studies usually find large variability between individual models but that the ensemble mean (e-mean) and median (e-median) often seem to predict quite well. However, few studies have specifically been concerned with the predictive quality of those ensemble predictors. We ask what is the predictive quality of e-mean and e-median, and how does that depend on the ensemble characteristics. Our empirical results are based on five MME studies applied to wheat, using different data sets but the same 25 crop models. We show that the ensemble predictors have quite high skill and are better than most and sometimes all individual models for most groups of environments and most response variables. Mean squared error of e-mean decreases monotonically with the size of the ensemble if models are added at random, but has a minimum at usually 2-6 models if best-fit models are added first. Our theoretical results describe the ensemble using four parameters: average bias, model effect variance, environment effect variance, and interaction variance. We show analytically that mean squared error of prediction (MSEP) of e-mean will always be smaller than MSEP averaged over models and will be less than MSEP of the best model if squared bias is less than the interaction variance. If models are added to the ensemble at random, MSEP of e-mean will decrease as the inverse of ensemble size, with a minimum equal to squared bias plus interaction variance. This minimum value is not necessarily small, and so it is important to evaluate the predictive quality of e-mean for each target population of environments. These results provide new information on the advantages of ensemble predictors, but also show their limitations.

Improving the use of crop models for risk assessment and climate change adaptation.

Crop models are used for an increasingly broad range of applications, with a commensurate proliferation of methods. Careful framing of research questions and development of targeted and appropriate methods are therefore increasingly important. In conjunction with the other authors in this special issue, we have developed a set of criteria for use of crop models in assessments of impacts, adaptation and risk. Our analysis drew on the other papers in this special issue, and on our experience in the UK Climate Change Risk Assessment 2017 and the MACSUR, AgMIP and ISIMIP projects. The criteria were used to assess how improvements could be made to the framing of climate change risks, and to outline the good practice and new developments that are needed to improve risk assessment. Key areas of good practice include: i. the development, running and documentation of crop models, with attention given to issues of spatial scale and complexity; ii. the methods used to form crop-climate ensembles, which can be based on model skill and/or spread; iii. the methods used to assess adaptation, which need broadening to account for technological development and to reflect the full range options available. The analysis highlights the limitations of focussing only on projections of future impacts and adaptation options using pre-determined time slices. Whilst this long-standing approach may remain an essential component of risk assessments, we identify three further key components: 1.Working with stakeholders to identify the timing of risks. What are the key vulnerabilities of food systems and what does crop-climate modelling tell us about when those systems are at risk?2.Use of multiple methods that critically assess the use of climate model output and avoid any presumption that analyses should begin and end with gridded output.3.Increasing transparency and inter-comparability in risk assessments. Whilst studies frequently produce ranges that quantify uncertainty, the assumptions underlying these ranges are not always clear. We suggest that the contingency of results upon assumptions is made explicit via a common uncertainty reporting format; and/or that studies are assessed against a set of criteria, such as those presented in this paper.

Alkylation of Sulfonamides with Trichloroacetimidates under Thermal Conditions.

An intermolecular alkylation of sulfonamides with trichloroacetimidates is reported. This transformation does not require an exogenous acid, base, or transition metal catalyst; instead the addition occurs in refluxing toluene without additives. The sulfonamide alkylation partner appears to be only limited by sterics, with unsubstituted sulfonamides providing better yields than more encumbered N-alkyl sulfonamides. The trichloroacetimidate alkylating agent must be a stable cation precursor for the substitution reaction to proceed under these conditions.

Multimodel ensembles of wheat growth: many models are better than one.

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.

Brønsted acid catalyzed monoalkylation of anilines with trichloroacetimidates.

Trichloroacetimidates are useful alkylating agents for aromatic amines, requiring only a catalytic amount of a Brønsted acid to facilitate the reaction. Monoalkylation predominates under these conditions. Electron-poor anilines provide superior yields, with electron-rich anilines sometimes showing competitive Friedel-Crafts alkylation. A single flask protocol with formation of the imidate in situ is demonstrated, providing a convenient method for the direct substitution of alcohols with anilines. Reaction with a chiral imidate favors a mechanism that proceeds through a carbocation intermediate.

Synthesis and initial evaluation of quinoline-based inhibitors of the SH2-containing inositol 5'-phosphatase (SHIP).

Recently, inhibition of the SH2-containing inositol 5'-phosphatase 1 (SHIP1) has become an attractive strategy for facilitating engraftment of MHC-I mismatched bone marrow grafts, increasing the number of adult stem cells in vivo, and inducing mobilization of hematopoietic stem cells. Utilizing high-throughput screening, two quinoline small molecules (NSC13480 and NSC305787) that inhibit SHIP1 enzymatic activity were discovered. New syntheses of these inhibitors have been developed which verified the relative stereochemistry of these structures. Utilizing this synthetic route, some analogs of these quinolines have been prepared and tested for their ability to inhibit SHIP. These structure activity studies determined that an amine tethered to the quinoline core is required for SHIP inhibition. SHIP inhibition may explain the antitumor effects of similar quinoline amino alcohols and provides an impetus for further synthetic studies in this class of compounds.

The Neutrophilic Dermatoses, or the Cutaneous Expressions of Neutrophilic Inflammation.

Acute febrile neutrophilic dermatosis, or Sweet syndrome, has been described in 1964 and is now considered as a prototypical condition of the group of the neutrophilic dermatoses. Since this time, many clinical conditions have been included in this group and a clinical-pathological classification in 3 subgroups has been proposed. Neutrophilic infiltrates can localize in all internal organs. This defines the neutrophilic disease, which induces difficult diagnostic and therapeutic problems. Autoinflammation is the main pathophysiological mechanism of the neutrophilic dermatoses. There is a special link between myeloid malignancies (leukemia and myelodysplasia) and the neutrophilic dermatoses.

Silver lining to a climate crisis in multiple prospects for alleviating crop waterlogging under future climates.

Extreme weather events threaten food security, yet global assessments of impacts caused by crop waterlogging are rare. Here we first develop a paradigm that distils common stress patterns across environments, genotypes and climate horizons. Second, we embed improved process-based understanding into a farming systems model to discern changes in global crop waterlogging under future climates. Third, we develop avenues for adapting cropping systems to waterlogging contextualised by environment. We find that yield penalties caused by waterlogging increase from 3-11% historically to 10-20% by 2080, with penalties reflecting a trade-off between the duration of waterlogging and the timing of waterlogging relative to crop stage. We document greater potential for waterlogging-tolerant genotypes in environments with longer temperate growing seasons (e.g., UK, France, Russia, China), compared with environments with higher annualised ratios of evapotranspiration to precipitation (e.g., Australia). Under future climates, altering sowing time and adoption of waterlogging-tolerant genotypes reduces yield penalties by 18%, while earlier sowing of winter genotypes alleviates waterlogging by 8%. We highlight the serendipitous outcome wherein waterlogging stress patterns under present conditions are likely to be similar to those in the future, suggesting that adaptations for future climates could be designed using stress patterns realised today.

Congenital erosive and vesicular dermatosis: a new case and review of the literature.

Congenital erosive and vesicular dermatosis is a rare syndrome first described by Cohen et al in 1985. Most of the 18 cases published have been reported in premature newborns. Affected babies typically present with erosions and vesicles that tend to heal shortly after birth with reticulated scaring. We report an additional case, followed up for 5 years, in which we excluded a pathogenic mutation in the TP63 gene.

Giant basal cell carcinoma with regional lymph node and distant lung metastasis.

The prevalence of metastatic basal cell carcinoma (MBCC) varies between 0.0028% and 0.55% of all cases. In total, more than 300 MBCC have been reported in the literature. We report the case of a 72 year old lady, who presented in September 2009 with a 10-year history of a progressively growing, giant, facial basal cell carcinoma (BCC). Clinical and imaging evaluations identified large local invasion with bone and meningeal involvement. Treatment consisted of an extensive surgery including left eye exenteration and meningeal resection followed by radiotherapy. A solitary lung metastasis was identified five months after the primary tumor resection. As the lesion remained solitary but had increased in size five months later, the patient finally accepted a surgical resection. A right upper-lobe pneumonectomy was performed and pathologic examination confirmed the metastasis as a MBCC.

Atypical presentation of adult T-cell leukaemia/lymphoma due to HTLV-1: prurigo nodularis lasting twelve years followed by an acute micropapular eruption.

Prurigo nodularis is a pruritic dermatosis of unknown origin. Human T-cell lymphotropic virus type 1 (HTLV-1) causes adult T-cell leukaemia/lymphoma. HTLV-1 is not considered to be a cause of prurigo nodularis. A 52-year-old black man, from the French West Indies, who had had prurigo nodularis for 12 years, presented with a distinct micropapular eruption with the typical pathological picture of epidermotropic T-cell lymphoma. Based on HTLV-1-positive serology and monoclonal integration of HTLV-1 we diagnosed smouldering adult T-cell leukaemia/lymphoma. Re-examination of previous skin biopsies revealed that the disease had been evolving for 12 years. Treatment with alpha-interferon, 3 x 106 units three times a week, associated with zidovudine, 1 g daily, resulted in complete remission within 4 months. When investigating a prurigo nodularis, we therefore recommend: (i) performing HTLV-1 serology if the patient comes from an endemic area; (ii) if positive, performing CD25 staining and looking for a HTLV-1 clonal integration; and (iii) if positive, using a treatment targeting HTLV-1.

BLIGHTSIM: A New Potato Late Blight Model Simulating the Response of Phytophthora infestans to Diurnal Temperature and Humidity Fluctuations in Relation to Climate Change.

Temperature response curves under diurnal oscillating temperatures differ from those under constant conditions for all stages of the Phytophthora infestans infection cycle on potatoes. We developed a mechanistic model (BLIGHTSIM) with an hourly time step to simulate late blight under fluctuating environmental conditions and predict late blight epidemics in potato fields. BLIGHTSIM is a modified susceptible (S), latent (L), infectious (I) and removed (R) compartmental model with hourly temperature and relative humidity as driving variables. The model was calibrated with growth chamber data covering one infection cycle and validated with field data from Ecuador. The model provided a good fit to all data sets evaluated. There was a significant interaction between average temperature and amplitude in their effects on the area under the disease progress curve (AUDPC) as predicted from growth chamber data on a single infection cycle. BLIGHTSIM can be incorporated in a potato growth model to study effects of diurnal temperature range on late blight impact under climate change scenarios.

The neutrophilic dermatoses.

The neutrophilic dermatoses (ND) may present with pustules, plaques, ulcerations, and general malaise. They are secondary to the invasion of the skin by normal polymorphonuclear leukocytes in the absence of infection. ND are often associated with particular systemic diseases. The management of affected patients is reviewed, with a focus on nursing care.