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The difficulty of forecasting “normal” climate conditions is demonstrated in the context of bivariate normally distributed forecasts and observations. Deterministic and probabilistic skill scores for the normal category are less than for the outer category for all-but-perfect models. There are two important mathematical properties of the normal category in a three-category climatologically equiprobable forecast system that affect the scores for this category. First, the normal category can achieve the highest probability less frequently than the outer categories, and far less frequently in contexts of weak to moderate skill. Second, there are upper limits to the probability the normal category can reach. These mathematical constraints suggest that summary measures of skill may underestimate the predictability and forecast-skill of extreme events, and that subjective inputs to probabilistic forecasts may need to take greater account of limitations to the predictability of normal conditions. [ABSTRACT FROM AUTHOR]

Little has been documented about the benefits and impacts of the recent growth in climate services, despite a growing call to justify their value and stimulate investment. Regional Climate Outlook Forums (RCOFs), an integral part of the public and private enterprise of climate services, have been implemented over the last 20 years with the objectives of producing and disseminating seasonal climate forecasts to inform improved climate risk management and adaptation. In proposing guidance on how to measure the success of RCOFs, we offer three broad evaluative categories that are based on the primary stated goals of the RCOFs: 1) quality of the climate information used and developed at RCOFs; 2) legitimacy of RCOF processes focused on consensus forecasts, broad user engagement, and capacity building; and 3) usability of the climate information produced at RCOFs. Evaluating the quality of information relies largely on quantitative measures and statistical techniques that are standardized and transferrable, but assessing the RCOF processes and perceived usability of RCOF products will necessitate a combination of quantitative and qualitative social science methods that are sensitive to highly variable regional contexts. As RCOFs have taken up different formats and procedures to adapt to diverse institutional and political settings and varied technical and scientific capacities, objective evaluation methods adopted should align with the goals and intent of the evaluation and be performed in a participatory, coproduction manner where producers and users of climate services together design the evaluation metrics and processes. To fully capture the potential benefits of the RCOFs, it may be necessary to adjust or recalibrate the goals of these forums to better fit the evolving landscape of climate services development, needs, and provision. [ABSTRACT FROM AUTHOR]

Background: The fungus Aspergillus niger is an important industrial organism for citric acid fermentation; one of the most efficient biotechnological processes. Previously we introduced a dynamic model that captures this process in the industrially relevant batch fermentation setting, providing a more accurate predictive platform to guide targeted engineering. In this article we exploit this dynamic modelling framework, coupled with a robust genetic algorithm for the in silico evolution of A. niger organic acid production, to provide solutions to complex evolutionary goals involving a multiplicity of targets and beyond the reach of simple Boolean gene deletions. We base this work on the latest metabolic models of the parent citric acid producing strain ATCC1015 dedicated to organic acid production with the required exhaustive genomic coverage needed to perform exploratory in silico evolution. Results: With the use of our informed evolutionary framework, we demonstrate targeted changes that induce a complete switch of acid output from citric to numerous different commercially valuable target organic acids including succinic acid. We highlight the key changes in flux patterns that occur in each case, suggesting potentially valuable targets for engineering. We also show that optimum acid productivity is achieved through a balance of organic acid and biomass production, requiring finely tuned flux constraints that give a growth rate optimal for productivity. Conclusions: This study shows how a genome-scale metabolic model can be integrated with dynamic modelling and metaheuristic algorithms to provide solutions to complex metabolic engineering goals of industrial importance. This framework for in silico guided engineering, based on the dynamic batch growth relevant to industrial processes, offers considerable potential for future endeavours focused on the engineering of organisms to produce valuable products. [ABSTRACT FROM AUTHOR]

Background: Aspergillus niger fermentation has provided the chief source of industrial citric acid for over 50 years. Traditional strain development of this organism was achieved through random mutagenesis, but advances in genomics have enabled the development of genome-scale metabolic modelling that can be used to make predictive improvements in fermentation performance. The parent citric acid-producing strain of A. niger, ATCC 1015, has been described previously by a genome-scale metabolic model that encapsulates its response to ambient pH. Here, we report the development of a novel double optimisation modelling approach that generates time-dependent citric acid fermentation using dynamic flux balance analysis. Results: The output from this model shows a good match with empirical fermentation data. Our studies suggest that citric acid production commences upon a switch to phosphate-limited growth and this is validated by fitting to empirical data, which confirms the diauxic growth behaviour and the role of phosphate storage as polyphosphate. Conclusions: The calibrated time-course model reflects observed metabolic events and generates reliable in silico data for industrially relevant fermentative time series, and for the behaviour of engineered strains suggesting that our approach can be used as a powerful tool for predictive metabolic engineering. [ABSTRACT FROM AUTHOR]

The article discusses a study published within the issue which showed significant results that show that genes that introduce ferulic acid (FA) to arabinoxylans (AXs). Topics covered include uniqueness of FA side chains of AXs to commelinid monocots including grasses, different model species used in the study to approach the problem, and the role of BAHD01 gene in AX feruloylation.

Co‐occurring hazards present unparalleled challenges to development and disaster recovery. In this study, we investigate the relationship between anomalous heat in the aftermath of tropical cyclones in the eastern Caribbean between 1991 and 2020. We analyze the spatial patterns of anomalous heat index (HI) values for 53 tropical storms and hurricanes using a Lagrangian analysis framework. Furthermore, we analyze temporal patterns of 205 city‐storms pairings. The spatial patterns displayed distinct and statistically significant areas of anomalously warm conditions regardless of the storm intensity classification. Moreover, all 205 city‐storm events had positive HI anomalies following the storms' passage with a maximum of 5°C. The results show that HI anomalies can be high, have a time lag of days, and be observed in locations not directly impacted by the storm. The results have implications for tropical cyclones preparedness, including suggesting that preparedness include informing the public about heat impacts. Plain Language Summary: Two or more extreme events that are coincident in time or that occur in close succession present unparalleled challenges to development and disaster recovery. It is well known that tropical cyclones cause long‐lived damage from strong winds, storm surges, intense rain, and/or flooding. Equally, heat is a main concern for public health. However, heat in the aftermath of tropical cyclones has not been a focus.We analyze 53 tropical storms and hurricanes in the eastern Caribbean between 1991 and 2020 and 205 storm‐city events. The storms' heat index (HI) values are statistically significantly warmer during the storm than average in some regions, regardless of groupings of storms by their strength. The HI values before and after storms passed main cities in 14 Caribbean islands further show that in all 205 cases, warm HI anomalies follow the storms' passage, with values as high as 5°C (9 Fahrenheit). The results show that HI anomalies following tropical cyclones can be high, have maximums that occur several days after the storm's passage, and can be observed in locations that are not directly impacted by the storm. The results suggest tropical cyclone preparedness should include informing the public about heat risk. Key Points: Areas around tropical cyclones have heat index (HI) values significantly warmer than average, a result insensitive to storm strengthPositive HI anomalies occur after the cyclones passage in all storms; the maximum anomalies range from 0.3°C to 5.2°CAnomalous heat can be observed in areas 100s of kilometers away from the central location of the tropical storm [ABSTRACT FROM AUTHOR]

In 2008, the seasonal forecast issued at the Seasonal Climate Outlook Forum for West Africa (PRESAO) announced a high risk of above-normal rainfall for the July-September rainy season. With probabilities for above-normal rainfall of 0.45, this forecast indicated noteworthy increases in the risk of heavy rainfall. When this information reached the International Federation of Red Cross and Red Crescent Societies (IFRC) West and Central Africa Office, it led to significant changes in the organization's flood response operations. The IFRC regional office requested funds in advance of anticipated floods, prepositioned disaster relief items in strategic locations acrossWest Africa to benefit up to 9,500 families, updated its flood contingency plans, and alerted vulnerable communities and decision-makers across the region. This forecast-based preparedness resulted in a decrease in the number of lives, property, and livelihoods lost to floods, compared to just one year prior in 2007 when similar floods claimed above 300 lives in the region. This article demonstrates how a science-based early warning informed decisions and saved lives by triggering action in anticipation of forecast events. It analyses what it took to move decision-makers to action, based on seasonal climate information, and to overcome traditional barriers to the uptake of seasonal climate information in the region, providing evidence that these barriers can be overcome. While some institutional, communication and technical barriers were addressed in 2008, many challenges remain. Scientists and humanitarians need to build more common ground. [ABSTRACT FROM AUTHOR]

This article refers to the study of Mason and Weigel, where the generalized discrimination score D has been introduced. This score quantifies whether a set of observed outcomes can be correctly discriminated by the corresponding forecasts (i.e., it is a measure of the skill attribute of discrimination). Because of its generic definition, D can be adapted to essentially all relevant verification contexts, ranging from simple yes-no forecasts of binary outcomes to probabilistic forecasts of continuous variables. For most of these cases, Mason and Weigel have derived expressions for D, many of which have turned out to be equivalent to scores that are already known under different names. However, no guidance was provided on how to calculate D for ensemble forecasts. This gap is aggravated by the fact that there are currently very few measures of forecast quality that could be directly applied to ensemble forecasts without requiring that probabilities be derived from the ensemble members prior to verification. This study seeks to close this gap. A definition is proposed of how ensemble forecasts can be ranked; the ranks of the ensemble forecasts can then be used as a basis for attempting to discriminate between corresponding observations. Given this definition, formulations of D are derived that are directly applicable to ensemble forecasts. [ABSTRACT FROM AUTHOR]

This paper evaluates the quality of real-time seasonal probabilistic forecasts of the extreme 15%% tails of the climatological distribution of temperature and precipitation issued by the International Research Institute for Climate and Society (IRI) from 1998 through 2009. IRI's forecasts have been based largely on a two-tiered multimodel dynamical prediction system. Forecasts of the 15%% extremes have been consistent with the corresponding probabilistic forecasts for the standard tercile-based categories; however, nonclimatological forecasts for the extremes have been issued sparingly. Results indicate positive skill in terms of resolution and discrimination for the extremes forecasts, particularly in the tropics. Additionally, with the exception of some overconfidence for extreme above-normal precipitation and a strong cool bias for temperature, reliability analyses suggest generally good calibration. Skills for temperature are generally higher than those for precipitation, due both to correct forecasts of increased probabilities of extremely high (above the upper 15th percentile) temperatures associated with warming trends, and to better discrimination of interannual variability. However, above-normal temperature extremes were substantially underforecast, as noted also for the IRI's tercile forecasts. [ABSTRACT FROM AUTHOR]

This is the second of a two-part investigation of rainfall in southern Africa during the strong El Niño of 1997/98. In Part I it was shown that widespread drought in southern Africa, typical of past El Niño events occurring between 1950 and 2000, generally failed to materialize during the 1997/98 El Niño, most notably during January–March (JFM) 1998. Here output from three atmospheric general circulation models (AGCMs) forced with observed sea surface temperatures (SSTs) and seasonal forecasts from three coupled models are examined to see to what extent conditions in JFM 1998 could have potentially been anticipated. All three AGCMs generated widespread drought conditions across southern Africa, similar to those during past El Niño events, and did a generally poor job in generating the observed rainfall and atmospheric circulation anomaly patterns, particularly over the eastern and southern Indian Ocean. In contrast, two of the three coupled models showed a higher probability of wetter conditions in JFM 1998 than for past El Niño events, with an enhanced moisture flux from the Indian Ocean, as was observed. However, neither the AGCMs nor the coupled models generated anomalous stationary wave patterns consistent with observations over the South Atlantic and Pacific. The failure of any of the models to reproduce an enhanced Angola low (favoring rainfall) associated with an anomalous wave train in this region suggests that the coupled models that did indicate wetter conditions in JFM 1998 compared to previous El Niño episodes may have done so, at least partially, for the wrong reasons. The general inability of the climate models used in this study to generate key features of the seasonal climate over southern Africa in JFM 1998 suggests that internal atmospheric variability contributed to the observed rainfall and circulation patterns that year. With the caveat that current climate models may not properly respond to SST boundary forcing important to simulating southern Africa climate, this study finds that the JFM 1998 rainfall in southern Africa may have been largely unpredictable on seasonal time scales. [ABSTRACT FROM AUTHOR]

There are numerous reasons for calculating forecast verification scores, and considerable attention has been given to designing and analyzing the properties of scores that can be used for scientific purposes. Much less attention has been given to scores that may be useful for administrative reasons, such as communicating changes in forecast quality to bureaucrats and providing indications of forecast quality to the general public. The two-alternative forced choice (2AFC) test is proposed as a scoring procedure that is sufficiently generic to be usable on forecasts ranging from simple yes–no forecasts of dichotomous outcomes to forecasts of continuous variables, and can be used with deterministic or probabilistic forecasts without seriously reducing the more complex information when available. Although, as with any single verification score, the proposed test has limitations, it does have broad intuitive appeal in that the expected score of an unskilled set of forecasts (random guessing or perpetually identical forecasts) is 50%, and is interpretable as an indication of how often the forecasts are correct, even when the forecasts are expressed probabilistically and/or the observations are not discrete. [ABSTRACT FROM AUTHOR]

Following the onset of the strong El Niño of 1997–98 historical rainfall teleconnection patterns and dynamical model predictions both suggested an enhanced likelihood of drought for southern Africa, but widespread dry conditions failed to materialize. Results from a diagnostic study of NCEP–NCAR reanalysis data are reported here demonstrating how the large- and regional-scale atmospheric circulations during the 1997–98 El Niño differed from previous events. Emphasis is placed on the January–March 1998 season and comparisons with the strong 1982–83 El Niño, although composites of eight events occurring between 1950 and 2000 are also considered. In a companion paper, simulation runs from three atmospheric general circulation models (AGCMs), and forecasts from three fully coupled models are employed to investigate the extent to which the anomalous atmospheric circulation patterns during the 1997–98 El Niño may have been anticipated. Observational results indicate that the 1997–98 El Niño displayed significant differences from both the 1982–83 episode and the composite event. An unusually strong Angola low, exceptionally high sea surface temperatures (SSTs) in the western Indian and eastern tropical South Atlantic Oceans, and an enhanced northerly moisture flux from the continental interior and the western tropical Indian Ocean all appear to have contributed to more seasonal rainfall in 1997–98 over much of the southern Africa subcontinent than in past El Niño events. [ABSTRACT FROM AUTHOR]

Abstract: Complementing market-based policy instruments with conflict analysis approaches provides a wider understanding of market situations and allows to identify minimal requirements regarding needs, power and conflict dynamics. If these are not met, a market cannot be successfully introduced or a liberalization process implemented. Conflict analysis offers a language better suited to the concerns of people negatively affected by new markets. Applying this language helps to counterbalance the predominance of economic concepts. This fosters mutual understanding and enhances the prospect for successful implementation of market-based policies. We illustrate the potential of conflict analysis with examples from water privatization and labeling. [Copyright &y& Elsevier]

Probabilistic forecasts of variables measured on a categorical or ordinal scale, such as precipitation occurrence or temperatures exceeding a threshold, are typically verified by comparing the relative frequency with which the target event occurs given different levels of forecast confidence. The degree to which this conditional (on the forecast probability) relative frequency of an event corresponds with the actual forecast probabilities is known as reliability, or calibration. Forecast reliability for binary variables can be measured using the Murphy decomposition of the (half) Brier score, and can be presented graphically using reliability and attributes diagrams. For forecasts of variables on continuous scales, however, an alternative measure of reliability is required. The binned probability histogram and the reliability component of the continuous ranked probability score have been proposed as appropriate verification procedures in this context, but are subject to some limitations. A procedure is proposed that is applicable in the context of forecast ensembles and is an extension of the binned probability histogram. Individual ensemble members are treated as estimates of quantiles of the forecast distribution, and the conditional probability that the observed precipitation, for example, exceeds the amount forecast [the conditional exceedance probability (CEP)] is calculated. Generalized linear regression is used to estimate these conditional probabilities. A diagram showing the CEPs for ranked ensemble members is suggested as a useful method for indicating reliability when forecasts are on a continuous scale, and various statistical tests are suggested for quantifying the reliability. [ABSTRACT FROM AUTHOR]

Various spider species produce dragline silks with different mechanical properties. The primary structure of silk proteins is thought to contribute to the elasticity and strength of the fibres. Previously published work has demonstrated that the dragline silk of Euprosthenops sp. is stiffer then comparable silk of Nephila edulis, Araneus diadematus and Latrodectus mactans. Our studies of Euprosthenops dragline silk at the molecular level have revealed that nursery web spider fibroin has the highest polyalanine content among previously characterised silks and this is likely to contribute to the superior qualities of pisaurid dragline. [Copyright &y& Elsevier]

The Brier and ranked probability skill scores are widely used as skill metrics of probabilistic forecasts of weather and climate. As skill scores, they compare the extent to which a forecast strategy outperforms a (usually simpler) reference forecast strategy. The most widely used reference strategy is that of “climatology,” in which the climatological probability (or probabilities in the case of the ranked probability skill score) of the forecast variable is issued perpetually. The Brier and ranked probability skill scores are often considered harsh standards. It is shown that the scores are harsh because the expected value of these skill scores is less than 0 if nonclimatological forecast probabilities are issued. As a result, negative skill scores can often hide useful information content in the forecasts. An alternative formulation of the skill scores based on a reference strategy in which the outcome is independent of the forecast is equivalent to using randomly assigned probabilities but is not strictly proper. Nevertheless, positive values of the Brier skill score with random guessing as a strategy correspond to positive-sloping reliability curves, which is intuitively appealing because of the implication that the conditional probability of the forecast event increases as the forecast probability increases. [ABSTRACT FROM AUTHOR]

Craterostigma plantagineum is one of the few higher plants capable of surviving desiccation throughout its vegetative tissues. Water loss results in cell shrinkage and a commensurate folding of the cell wall indicating an unusual degree of wall flexibility. We show that wall extensibility undergoes a marked increase during dehydration and rehydration. Similar increases were observed in the activity of expansins in cell walls during these processes suggesting a role for these proteins in increasing wall flexibility. Three α-expansin cDNAs were cloned from dehydrating leaves and transcript levels for one correlated closely with the observed changes in expansin activity during the dehydration and rehydration of leaves. [Copyright &y& Elsevier]

The International Research Institute (IRI) for Climate Prediction seasonal forecast system is based largely on the predictions of ensembles of several atmospheric general circulation models (AGCMs) forced by two versions of an SST prediction—one consisting of persisted SST anomalies from the current observations and one of evolving SST anomalies as predicted by a set of dynamical and statistical SST prediction models. Recently, an objective multimodel ensembling procedure has replaced a more laborious and subjective weighting of the predictions of the several AGCMs. Here the skills of the multimodel predictions produced retrospectively over the first 4 years of IRI forecasts are examined and compared with the skills of the more subjectively derived forecasts actually issued. The multimodel ensemble predictions are generally found to be an acceptable replacement, although the precipitation forecasts do benefit from inclusion of empirical forecast tools. Planned pattern-level model output statistics (MOS) corrections for systematic biases in the AGCM forecasts may render them more sufficient in their own right. [ABSTRACT FROM AUTHOR]

Numerous models have been developed in recent years to provide predictions of the state of the El Niño–Southern Oscillation (ENSO) phenomenon. Predictions of the ENSO phenomenon are usually presented in deterministic form, but because of the inherent uncertainty involved probabilistic forecasts should be provided. In this paper, various statistical methods are used to calculate probabilities for monthly Niño-3.4 anomalies within predefined ranges, or categories. The statistical methods used are predictive discriminant analysis, canonical variate analysis, and various forms of generalized linear models. In addition, probabilistic forecasts are derived from a multiple regression model by using contingency tables and from the model's prediction intervals. By using identical sets of predictors and predictands, the methods are compared in terms of their performance over an independent retroactive forecast period, which includes the 1980s and 1990s. The models outperform persistence and damped persistence as reference forecast strategies at some times of the year. The models have greatest skill in predicting El Niño, although La Niña is predicted with greater skill at longer lead times and with greater reliability. The forecasts for the ENSO extremes are reasonably well calibrated, and so the forecast probabilities are reliable estimates of forecast uncertainty. All models are wrong, but some are useful. G. Box [ABSTRACT FROM AUTHOR]

The skill of global-scale sea surface temperature forecasts using a statistically based linear forecasting technique is investigated. Canonical variates are used to make monthly sea surface temperature anomaly forecasts using evolutionary and steady-state features of antecedent sea surface temperatures as predictors. Levels of forecast skill are investigated over several months' lead time by comparing the model performance with a simple forecast strategy involving the persistence of sea surface temperature anomalies. Forecast skill is investigated over an independent test period of 18 yr (1982/83–1999/2000), for which the model training period was updated after every 3 yr. Forecasts for the equatorial Pacific Ocean are a significant improvement over a strategy of random guessing, and outscore forecasts of persisted anomalies beyond lead times of about one season during the development stages of the El Niño–Southern Oscillation phenomenon, but only outscore forecasts of persisted anomalies beyond 6 months' lead time during its most intense phase. Model predictions of the tropical Indian Ocean outscore persistence during the second half of the boreal winter, that is, from about December or January, with maximum skill during the March–May spring season, but poor skill during the autumn months from September to November. Some loss in predictability of the equatorial Pacific and Indian Oceans is evident during the early and mid-1990s, but forecasts appear to have improved in the last few years. The tropical Atlantic Ocean forecast skill has generally been poor. There is little evidence of forecast skill over the midlatitudes in any of the oceans. However, during the spring months significant skill has been found over the Indian Ocean as far south as 20°S and over the southern North Atlantic as far north as 30°N, both of which outscore persistence beyond a lead time of less than about one season. [ABSTRACT FROM AUTHOR]

Reports cluster analysis used in climatology. Basis on the form of distance matrix in metric climatological field; Use of Euclidean distance for covariance matrix; Calculation for Euclidean and Mahalanodis distance from principal components.

Examines precipitation anomalies in many areas of the world that are associated with the El Nino-Southern Oscillation. Percentages of times that seasonal precipitation over land areas was above, near and below normal during the eight strongest El Nino and La Nina episodes; Calculation of the significance levels of the posterior probabilities.

Focuses on how theology or religion can help in dealing with ecological crisis. Crisis of interrelationship of organisms and environment; Principles and spirit in the development of relationships.

The relative operating characteristic (ROC) curve is a highly flexible method for representing the quality of dichotomous, categorical, continuous, and probabilistic forecasts. The method is based on ratios that measure the proportions of events and nonevents for which warnings were provided. These ratios provide estimates of the probabilities that an event will be forewarned and that an incorrect warning will be provided for a nonevent. Some guidelines for interpreting the ROC curve are provided. While the ROC curve is of direct interest to the user, the warning is provided in advance of the outcome and so there is additional value in knowing the probability of an event occurring contingent upon a warning being provided or not provided. An alternative method to the ROC curve is proposed that represents forecast quality when expressed in terms of probabilities of events occurring contingent upon the warnings provided. The ratios used provide estimates of the probability of an event occurring given the forecast that is issued. Some problems in constructing the curve in a manner that is directly analogous to that for the ROC curve are highlighted, and so an alternative approach is proposed. In the context of probabilistic forecasts, the ROC curve provides a means of identifying the forecast probability at which forecast value is optimized. In the context of continuous variables, the proposed relative operating levels curve indicates the exceedence threshold for defining an event at which forecast skill is optimized, and can enable the forecast user to estimate the probabilities of events other than that defined by the forecaster. [ABSTRACT FROM AUTHOR]

Focuses on the formation of the weather forecasting organization International Research Institute for Climate Prediction. Date formed; Goal of fostering the improvement, production and use global forecasts of seasonal to interannual climate variability; Forecasting tools developed for the purpose.

Presents information on a study which examined the long-term changes in the intensity of extreme rainfall events in South Africa. Data and methods; Significance of changes in the intensity of high rainfall events over South Africa; Summary.

Informs about the role that expansin, an extracellular protein, plays in the increasing of plant cell wall extensibility. Expansin inducing tissue expansion in vivo; Localized control of tissue expansion possibly sufficient to induce leaf formation; Suggestion of a role for biophysical forces in the regulation of plant development.

El Niño-Southern Oscillation (ENSO) is the dominant source of seasonal climate predictability. This study quantifies the historical impact of ENSO on seasonal precipitation through an update of the global ENSO teleconnection maps of Mason and Goddard. Many additional teleconnections are detected due to better handling of missing values and 20 years of additional, higher quality data. These global teleconnection maps are used as deterministic and probabilistic empirical seasonal forecasts in a verification study. The probabilistic empirical forecast model outperforms climatology in the tropics demonstrating the value of a forecast derived from the expected precipitation anomalies given the ENSO phase. Incorporating uncertainty due to SST prediction shows that teleconnection maps are skillful in predicting tropical precipitation up to a lead time of 4 months. The historical IRI seasonal forecasts generally outperform the empirical forecasts made with the teleconnection maps, demonstrating the additional value of state-of-the-art dynamical-based seasonal forecast systems. Additionally, the probabilistic empirical seasonal forecasts are proposed as reference forecasts for future skill assessments of real-time seasonal forecast systems. [ABSTRACT FROM AUTHOR]

SUMMARY: Triticum aestivum L. (bread wheat) is a crop relied upon by billions of people around the world, as a major source of both income and calories. Rising global temperatures, however, pose a genuine threat to the livelihood of these people, as wheat growth and yields are extremely vulnerable to damage by heat stress. Here we present the YoGI wheat landrace panel, comprising 342 accessions that show remarkable phenotypic and genetic diversity thanks to their adaptation to different climates. We quantified the abundance of 110 790 transcripts from the panel and used these data to conduct weighted co‐expression network analysis and to identify hub genes in modules associated with abiotic stress tolerance. We found that the expression of three hub genes, all heat‐shock proteins (HSPs), were significantly correlated with early thermotolerance in a validation panel of landraces. These hub genes belong to the same module, with one (TraesCS4D01G207500.1) being a candidate master‐regulator potentially controlling the expression of the other two hub genes, as well as a suite of other HSPs and heat‐stress transcription factors (HSFs). In this work, therefore, we identify three validated hub genes, the expression of which can serve as markers of thermotolerance during early development, and suggest that TraesCS4D01G207500.1 is a potential master regulator of HSP and HSF expression – presenting the YoGI landrace panel as an invaluable tool for breeders wishing to determine and introduce novel alleles into modern varieties, for the production of climate‐resilient crops. Significance Statement: Global wheat yields and crop growth are vulnerable to damage by heat stress, a threat that is likely to become more common globally in the coming years through climate change. Conducting weighted co‐expression network analysis on 337 diverse landrace accessions, we identified and validated TraesCS4D01G207500.1 as a hub gene that can be used as a marker of early thermotolerance, seemingly via the regulation of the expression of a suite of HSP and HSF genes. [ABSTRACT FROM AUTHOR]

Sudangrass, Sorghum sudanense (Piper) Stapf, is a vigorous forage crop that has also been used for biogas, paper, and electricity production. Due to the large biomass yields achieved by sudangrass and the large area of potential growth in Argentina seven sudangrass accessions from a collection of S. sudanense were analyzed to evaluate their potential as feedstocks for lignocellulosic bioethanol production, and to assess whether there is an association between the response to biotic and abiotic stresses and the composition of the biomass. The biomass composition was analyzed for major cell wall polymers, monosaccharides, and elemental composition. On average, 68% of stem lignocellulosic biomass was comprised of matrix polysaccharides and crystalline cellulose, representing a potential source of sugars for bioethanol production. Xylose was the predominant matrix polysaccharide monosaccharide comprising, on average, 45% of the total sugars, followed by arabinose, glucose, galactose, galacturonic acid, mannose, glucuronic acid, and fucose. Rhamnose was not detected in any of the biomasses analyzed. Silica was the most abundant element in sudangrass stem, followed by chloride, calcium, phosphorus and sulfur. We performed saccharification analyses after pretreatments. Alkaline pretreatment was more effective than water pretreatment. Sodium hydroxide pretreatment exposed different levels of recalcitrance among sudangrass accessions, whereas the water pretreatment did not. Phenological traits were also evaluated, showing significant variability among accessions. The comparison of major cell wall polymers and monosaccharide composition between tolerant and susceptible accessions to abiotic and biotic stresses suggests an association between the composition of the biomass and the response to stress. [ABSTRACT FROM AUTHOR]

During the austral summer 2015/16, severe flooding displaced over 170 000 people on the Paraguay River system in Paraguay, Argentina, and southern Brazil. These floods were driven by repeated heavy rainfall events in the lower Paraguay River basin. Alternating sequences of enhanced moisture inflow from the South American low-level jet and local convergence associated with baroclinic systems were conducive to mesoscale convective activity and enhanced precipitation. These circulation patterns were favored by cross-time-scale interactions of a very strong El Niño event, an unusually persistent Madden–Julian oscillation in phases 4 and 5, and the presence of a dipole SST anomaly in the central southern Atlantic Ocean. The simultaneous use of seasonal and subseasonal heavy rainfall predictions could have provided decision-makers with useful information about the start of these flooding events from two to four weeks in advance. Probabilistic seasonal forecasts available at the beginning of November successfully indicated heightened probability of heavy rainfall (90th percentile) over southern Paraguay and Brazil for December–February. Raw subseasonal forecasts of heavy rainfall exhibited limited skill at lead times beyond the first two predicted weeks, but a model output statistics approach involving principal component regression substantially improved the spatial distribution of skill for week 3 relative to other methods tested, including extended logistic regressions. A continuous monitoring of climate drivers impacting rainfall in the region, and the use of statistically corrected heavy precipitation seasonal and subseasonal forecasts, may help improve flood preparedness in this and other regions. [ABSTRACT FROM AUTHOR]

The article focuses on a study which examines mannitol biosynthesis in algae. Topics discussed include the occurrence of enzymes involved in mannitol biosynthesis across algal lineages and the evolution of the mannitol biosynthetic pathways and the distribution of mannitol biosynthetic genes in algae.

Sugarcane (Saccharum spp.) is a genetically complex crop with great potential for the second-generation (2 G) ethanol industry. Despite this, there is scarce knowledge of the variability of bagasse cell-wall components and its association with agronomic traits that could be used in the selection of cultivars with improved bagasse digestibility. In this work, the acid detergent fiber method was used to determine cellulose, hemicellulose, and acid detergent lignin (ADL) in a sugarcane progeny from crossing two commercial cultivars, and in two energy-cane biotypes. Additionally, acetyl bromide-soluble lignin was determined and compared with ADL values. Despite the crossed parents showing similar bagasse composition, transgressive inheritance observed in the progeny for all bagasse cell-wall components underlines the possibility of improving sugarcane for specific bioenergetic uses. Additionally, the low association between cell-wall and yield components found in this work, suggests that indirect selection of cell-wall components for 2 G ethanol industry through agronomic traits would have a limited impact on improving the biomass composition. [ABSTRACT FROM AUTHOR]

The aim of producing sustainable liquid biofuels and chemicals from lignocellulosic biomass remains high on the sustainability agenda, but is challenged by the costs of producing fermentable sugars from these materials. Sugars from plant biomass can be fermented to alcohols or even alkanes, creating a liquid fuel in which carbon released on combustion is balanced by its photosynthetic capture. Large amounts of sugar are present in the woody, nonfood parts of crops and could be used for fuel production without compromising global food security. However, the sugar in woody biomass is locked up in the complex and recalcitrant lignocellulosic plant cell wall, making it difficult and expensive to extract. In this paper,wereview what is known about the major polymeric components of woody plant biomass, with an emphasis on the molecular interactions that contribute to its recalcitrance to enzymatic digestion. In addition, we review the extensive research that has been carried out in order to understand and reduce lignocellulose recalcitrance and enable more cost-effective production of fuel from woody plant biomass. [ABSTRACT FROM AUTHOR]

Using volunteered geographic information (VGI) to supplement disaster risk management systems, including forecasting, risk assessment, and disaster recovery, is increasingly popular. This attention is driven by difficulties in detection and characterization of hazards, as well as the rise of VGI appropriate for characterizing specific forms of risk. Flash-flood historical records, especially those that are impact-based, are not comprehensive, leading to additional barriers for flash-flood research and applications. In this paper we develop a method for associating VGI flood reporting clusters against authoritative data. Using Hurricane Harvey as a case study, VGI reports are assimilated into a spatial analytic framework that derives spatial and temporal clustering parameters supported by associations between Waze's community-driven emergency operations center and authoritative reports. These parameters are then applied to find previously unreported likely flash flood-events. This study improves the understanding of the distribution of flash flooding during Hurricane Harvey and shows potential application to events in other areas where Waze data and reporting from official sources, such as the National Weather Service, are available. [ABSTRACT FROM AUTHOR]

Background: Citric acid is typically produced industrially by Aspergillus niger-mediated fermentation of a sucrose-based feedstock, such as molasses. The fungus Aspergillus niger has the potential to utilise lignocellulosic biomass, such as bagasse, for industrial-scale citric acid production, but realising this potential requires strain optimisation. Systems biology can accelerate strain engineering by systematic target identification, facilitated by methods for the integration of omics data into a high-quality metabolic model. In this work, we perform transcriptomic analysis to determine the temporal expression changes during fermentation of bagasse hydrolysate and develop an evolutionary algorithm to integrate the transcriptomic data with the available metabolic model to identify potential targets for strain engineering. Results: The novel integrated procedure matures our understanding of suboptimal citric acid production and reveals potential targets for strain engineering, including targets consistent with the literature such as the up-regulation of citrate export and pyruvate carboxylase as well as novel targets such as the down-regulation of inorganic diphosphatase. Conclusions: In this study, we demonstrate the production of citric acid from lignocellulosic hydrolysate and show how transcriptomic data across multiple timepoints can be coupled with evolutionary and metabolic modelling to identify potential targets for further engineering to maximise productivity from a chosen feedstock. The in silico strategies employed in this study can be applied to other biotechnological goals, assisting efforts to harness the potential of microorganisms for bio-based production of valuable chemicals. [ABSTRACT FROM AUTHOR]

Background: Shipworms are marine xylophagus bivalve molluscs, which can live on a diet solely of wood due to their ability to produce plant cell wall-degrading enzymes. Bacterial carbohydrate-active enzymes (CAZymes), synthesised by endosymbionts living in specialised shipworm cells called bacteriocytes and located in the animal's gills, play an important role in wood digestion in shipworms. However, the main site of lignocellulose digestion within these wood-boring molluscs, which contains both endogenous lignocellulolytic enzymes and prokaryotic enzymes, is the caecum, and the mechanism by which bacterial enzymes reach the distant caecum lumen has remained so far mysterious. Here, we provide a characterisation of the path through which bacterial CAZymes produced in the gills of the shipworm Lyrodus pedicellatus reach the distant caecum to contribute to the digestion of wood. Results: Through a combination of transcriptomics, proteomics, X-ray microtomography, electron microscopy studies and in vitro biochemical characterisation, we show that wood-digesting enzymes produced by symbiotic bacteria are localised not only in the gills, but also in the lumen of the food groove, a stream of mucus secreted by gill cells that carries food particles trapped by filter feeding to the mouth. Bacterial CAZymes are also present in the crystalline style and in the caecum of their shipworm host, suggesting a unique pathway by which enzymes involved in a symbiotic interaction are transported to their site of action. Finally, we characterise in vitro four new bacterial glycosyl hydrolases and a lytic polysaccharide monooxygenase identified in our transcriptomic and proteomic analyses as some of the major bacterial enzymes involved in this unusual biological system. Conclusion: Based on our data, we propose that bacteria and their enzymes are transported from the gills along the food groove to the shipworm's mouth and digestive tract, where they aid in wood digestion. [ABSTRACT FROM AUTHOR]

Highlights: [•] Industry interviews show mixed views on government support for waste recovery. [•] Expert focus groups consider “do nothing” to be an inappropriate policy approach. [•] Government procurement can stimulate demand for recovered biomaterials. [•] Targeting product purity can increase the supply of recovered biomaterials. [•] Existing independent recovery schemes cannot provide industry-wide solutions. [ABSTRACT FROM AUTHOR]