Department of Primary Industries

Tick fever or cattle fever (babesiosis) is economically the most important arthropod-borne disease of cattle worldwide with vast areas of Australia, Africa, South and Central America and the United States continuously under threat. Tick fever was the first disease for which transmission by an arthropod to a mammal was implicated at the turn of the twentieth century and is the first disease to be eradicated from a continent (North America). This review describes the biology of Babesia spp. in the host and the tick, the scale of the problem to the cattle industry, the various components of control programmes, epidemiology, pathogenesis, immunity, vaccination and future research. The emphasis is on Babesia bovis and Babesia bigemina.

Abstract In this paper we examine the levels and trends in agricultural output and productivity in 93 developed and developing countries that account for a major portion of the world population and agricultural output. We make use of data drawn from the Food and Agriculture Organization of the United Nations and our study covers the period 1980–2000. Due to the nonavailability of reliable input price data, the study uses data envelopment analysis (DEA) to derive Malmquist productivity indices. The study examines trends in agricultural productivity over the period. Issues of catch‐up and convergence, or in some cases possible divergence, in productivity in agriculture are examined within a global framework. The paper also derives the shadow prices and value shares that are implicit in the DEA‐based Malmquist productivity indices, and examines the plausibility of their levels and trends over the study period.

Better understanding of root system structure and function is critical to crop improvement in water-limited environments. The aims of this study were to examine root system characteristics of two wheat genotypes contrasting in tolerance to water limitation and to assess the functional implications on adaptation to water-limited environments of any differences found. The drought tolerant barley variety, Mackay, was also included to allow inter-species comparison. Single plants were grown in large, soil-filled root-observation chambers. Root growth was monitored by digital imaging and water extraction was measured. Root architecture differed markedly among the genotypes. The drought-tolerant wheat (cv. SeriM82) had a compact root system, while roots of barley cv. Mackay occupied the largest soil volume. Relative to the standard wheat variety (Hartog), SeriM82 had a more uniform rooting pattern and greater root length at depth. Despite the more compact root architecture of SeriM82, total water extracted did not differ between wheat genotypes. To quantify the value of these adaptive traits, a simulation analysis was conducted with the cropping system model APSIM, for a wide range of environments in southern Queensland, Australia. The analysis indicated a mean relative yield benefit of 14.5% in water-deficit seasons. Each additional millimetre of water extracted during grain filling generated an extra 55 kg ha–1 of grain yield. The functional implications of root traits on temporal patterns and total amount of water capture, and their importance in crop adaptation to specific water-limited environments, are discussed.

Bats have been identified as a natural reservoir for an increasing number of emerging zoonotic viruses, including henipaviruses and variants of rabies viruses. Recently, we and another group independently identified several horseshoe bat species (genus Rhinolophus) as the reservoir host for a large number of viruses that have a close genetic relationship with the coronavirus associated with severe acute respiratory syndrome (SARS). Our current research focused on the identification of the reservoir species for the progenitor virus of the SARS coronaviruses responsible for outbreaks during 2002-2003 and 2003-2004. In addition to SARS-like coronaviruses, many other novel bat coronaviruses, which belong to groups 1 and 2 of the 3 existing coronavirus groups, have been detected by PCR. The discovery of bat SARS-like coronaviruses and the great genetic diversity of coronaviruses in bats have shed new light on the origin and transmission of SARS coronaviruses.

Genera of Phytopathogenic Fungi (GOPHY) is introduced as a new series of publications in order to provide a stable platform for the taxonomy of phytopathogenic fungi. This first paper focuses on 21 genera of phytopathogenic fungi: Bipolaris , Boeremia , Calonectria , Ceratocystis , Cladosporium , Colletotrichum , Coniella , Curvularia , Monilinia , Neofabraea , Neofusicoccum , Pilidium , Pleiochaeta , Plenodomus , Protostegia , Pseudopyricularia , Puccinia , Saccharata , Thyrostroma , Venturia and Wilsonomyces . For each genus, a morphological description and information about its pathology, distribution, hosts and disease symptoms are provided. In addition, this information is linked to primary and secondary DNA barcodes of the presently accepted species, and relevant literature. Moreover, several novelties are introduced, i.e. new genera, species and combinations, and neo-, lecto- and epitypes designated to provide a stable taxonomy. This first paper includes one new genus, 26 new species, ten new combinations, and four typifications of older names.

Novel species of microfungi described in the present study include the following from South Africa: Cercosporella dolichandrae from Dolichandra unguiscati, Seiridium podocarpi from Podocarpus latifolius, Pseudocercospora parapseudarthriae from Pseudarthria hookeri, Neodevriesia coryneliae from Corynelia uberata on leaves of Afrocarpus falcatus, Ramichloridium eucleae from Euclea undulata and Stachybotrys aloeticola from Aloe sp. (South Africa), as novel member of the Stachybotriaceae fam. nov. Several species were also described from Zambia, and these include Chaetomella zambiensis on unknown Fabaceae, Schizoparme pseudogranati from Terminalia stuhlmannii, Diaporthe isoberliniae from Isoberlinia angolensis, Peyronellaea combreti from Combretum mossambiciensis, Zasmidium rothmanniae and Phaeococcomyces rothmanniae from Rothmannia engleriana, Diaporthe vangueriae from Vangueria infausta and Diaporthe parapterocarpi from Pterocarpus brenanii. Novel species from the Netherlands include: Stagonospora trichophoricola, Keissleriella trichophoricola and Dinemasporium trichophoricola from Trichophorum cespitosum, Phaeosphaeria poae, Keissleriella poagena, Phaeosphaeria poagena, Parastagonospora poagena and Pyrenochaetopsis poae from Poa sp., Septoriella oudemansii from Phragmites australis and Dendryphion europaeum from Hedera helix (Germany) and Heracleum sphondylium (the Netherlands). Novel species from Australia include: Anungitea eucalyptorum from Eucalyptus leaf litter, Beltraniopsis neolitseae and Acrodontium neolitseae from Neolitsea australiensis, Beltraniella endiandrae from Endiandra introrsa, Phaeophleospora parsoniae from Parsonia straminea, Penicillifer martinii from Cynodon dactylon, Ochroconis macrozamiae from Macrozamia leaf litter, Triposporium cycadicola, Circinotrichum cycadis, Cladosporium cycadicola and Acrocalymma cycadis from Cycas spp. Furthermore, Vermiculariopsiella dichapetali is described from Dichapetalum rhodesicum (Botswana), Ophiognomonia acadiensis from Picea rubens (Canada), Setophoma vernoniae from Vernonia polyanthes and Penicillium restingae from soil (Brazil), Pseudolachnella guaviyunis from Myrcianthes pungens (Uruguay) and Pseudocercospora neriicola from Nerium oleander (Italy). Novelties from Spain include: Dendryphiella eucalyptorum from Eucalyptus globulus, Conioscypha minutispora from dead wood, Diplogelasinospora moalensis and Pseudoneurospora canariensis from soil and Inocybe lanatopurpurea from reforested woodland of Pinus spp. Novelties from France include: Kellermania triseptata from Agave angustifolia, Zetiasplozna acaciae from Acacia melanoxylon, Pyrenochaeta pinicola from Pinus sp. and Pseudonectria rusci from Ruscus aculeatus. New species from China include: Dematiocladium celtidicola from Celtis bungeana, Beltrania pseudorhombica, Chaetopsina beijingensis and Toxicocladosporium pini from Pinus spp. and Setophaeosphaeria badalingensis from Hemerocallis fulva. Novel genera of Ascomycetes include Alfaria from Cyperus esculentus (Spain), Rinaldiella from a contaminated human lesion (Georgia), Hyalocladosporiella from Tectona grandis (Brazil), Pseudoacremonium from Saccharum spontaneum and Melnikomyces from leaf litter (Vietnam), Annellosympodiella from Juniperus procera (Ethiopia), Neoceratosperma from Eucalyptus leaves (Thailand), Ramopenidiella from Cycas calcicola (Australia), Cephalotrichiella from air in the Netherlands, Neocamarosporium from Mesembryanthemum sp. and Acervuloseptoria from Ziziphus mucronata (South Africa) and Setophaeosphaeria from Hemerocallis fulva (China). Several novel combinations are also introduced, namely for Phaeosphaeria setosa as Setophaeosphaeria setosa, Phoma heteroderae as Peyronellaea heteroderae and Phyllosticta maydis as Peyronellaea maydis. Morphological and culture characteristics along with ITS DNA barcodes are provided for all taxa.

Novel species of fungi described in this study include those from various countries as follows: Australia : Apiognomonia lasiopetali on Lasiopetalum sp., Blastacervulus eucalyptorum on Eucalyptus adesmophloia , Bullanockia australis (incl. Bullanockia gen. nov.) on Kingia australis , Caliciopsis eucalypti on Eucalyptus marginata , Celerioriella petrophiles on Petrophile teretifolia , Coleophoma xanthosiae on Xanthosia rotundifolia , Coniothyrium hakeae on Hakea sp., Diatrypella banksiae on Banksia formosa , Disculoides corymbiae on Corymbia calophylla , Elsinoë eelemani on Melaleuca alternifolia , Elsinoë eucalyptigena on Eucalyptus kingsmillii , Elsinoë preissianae on Eucalyptus preissiana , Eucasphaeria rustici on Eucalyptus creta , Hyweljonesia queenslandica (incl. Hyweljonesia gen. nov.) on the cocoon of an unidentified microlepidoptera, Mycodiella eucalypti (incl. Mycodiella gen. nov.) on Eucalyptus diversicolor , Myrtapenidiella sporadicae on Eucalyptus sporadica , Neocrinula xanthorrhoeae (incl. Neocrinula gen. nov.) on Xanthorrhoea sp., Ophiocordyceps nooreniae on dead ant, Phaeosphaeriopsis agavacearum on Agave sp., Phlogicylindrium mokarei on Eucalyptus sp., Phyllosticta acaciigena on Acacia suaveolens , Pleurophoma acaciae on Acacia glaucoptera , Pyrenochaeta hakeae on Hakea sp., Readeriella lehmannii on Eucalyptus lehmannii , Saccharata banksiae on Banksia grandis , Saccharata daviesiae on Daviesia pachyphylla , Saccharata eucalyptorum on Eucalyptus bigalerita , Saccharata hakeae on Hakea baxteri , Saccharata hakeicola on Hakea victoria , Saccharata lambertiae on Lambertia ericifolia , Saccharata petrophiles on Petrophile sp., Saccharata petrophilicola on Petrophile fastigiata , Sphaerellopsis hakeae on Hakea sp., and Teichospora kingiae on Kingia australis . Brazil : Adautomilanezia caesalpiniae (incl. Adautomilanezia gen. nov.) on Caesalpina echinata , Arthrophiala arthrospora (incl. Arthrophiala gen. nov.) on Sagittaria montevidensis , Diaporthe caatingaensis (endophyte from Tacinga inamoena ), Geastrum ishikawae on sandy soil, Geastrum pusillipilosum on soil, Gymnopus pygmaeus on dead leaves and sticks, Inonotus hymenonitens on decayed angiosperm trunk, Pyricularia urashimae on Urochloa brizantha , and Synnemellisia aurantia on Passiflora edulis . Chile : Tubulicrinis australis on Lophosoria quadripinnata . France : Cercophora squamulosa from submerged wood, and Scedosporium cereisporum from fluids of a wastewater treatment plant. Hawaii : Beltraniella acaciae , Dactylaria acaciae , Rhexodenticula acaciae , Rubikia evansii and Torula acaciae (all on Acacia koa ). India : Lepidoderma echinosporum on dead semi-woody stems, and Rhodocybe rubrobrunnea from soil. Iran : Talaromyces kabodanensis from hypersaline soil. La Réunion : Neocordana musarum from leaves of Musa sp. Malaysia : Anungitea eucalyptigena on Eucalyptus grandis × pellita , Camptomeriphila leucaenae (incl. Camptomeriphila gen. nov.) on Leucaena leucocephala , Castanediella communis on Eucalyptus pellita , Eucalyptostroma eucalypti (incl. Eucalyptostroma gen. nov.) on Eucalyptus pellita , Melanconiella syzygii on Syzygium sp., Mycophilomyces periconiae (incl. Mycophilomyces gen. nov.) as hyperparasite on Periconia on leaves of Albizia falcataria , Synnemadiella eucalypti (incl. Synnemadiella gen. nov.) on Eucalyptus pellita , and Teichospora nephelii on Nephelium lappaceum . Mexico : Aspergillus bicephalus from soil. New Zealand : Aplosporella sophorae on Sophora microphylla , Libertasomyces platani on Platanus sp., Neothyronectria sophorae (incl. Neothyronectria gen. nov.) on Sophora microphylla , Parastagonospora phoenicicola on Phoenix canariensis , Phaeoacremonium pseudopanacis on Pseudopanax crassifolius , Phlyctema phoenicis on Phoenix canariensis , and Pseudoascochyta novae-zelandiae on Cordyline australis . Panama : Chalara panamensis from needle litter of Pinus cf. caribaea . South Africa : Exophiala eucalypti on leaves of Eucalyptus sp., Fantasmomyces hyalinus (incl. Fantasmomyces gen. nov.) on Acacia exuvialis , Paracladophialophora carceris (incl. Paracladophialophora gen. nov.) on Aloe sp., and Umthunziomyces hagahagensis (incl. Umthunziomyces gen. nov.) on Mimusops caffra . Spain : Clavaria griseobrunnea on bare ground in Pteridium aquilinum field, Cyathus ibericus on small fallen branches of Pinus halepensis , Gyroporus pseudolacteus in humus of Pinus pinaster , and Pseudoascochyta pratensis (incl. Pseudoascochyta gen. nov.) fromsoil. Thailand : Neoascochyta adenii on Adenium obesum , and Ochroconis capsici on Capsicum annuum . UK : Fusicolla melogrammae from dead stromata of Melogramma campylosporum on bark of Carpinus betulus . Uruguay : Myrmecridium pulvericola from house dust. USA : Neoscolecobasidium agapanthi (incl. Neoscolecobasidium gen. nov.) on Agapanthus sp., Polyscytalum purgamentum on leaf litter, Pseudopithomyces diversisporus from human

and allied fusarioid genera (www.fusarium.org).

Development of resistance in major grain insect pest species to the key fumigant phosphine (hydrogen phosphide) across the globe has put the viability and sustainability of phosphine in jeopardy. The resistance problem has been aggravated over the past two decades, due mostly to the lack of suitable alternatives matching the major attributes of phosphine, including its low price, ease of application, proven effectiveness against a broad pest spectrum, compatibility with most storage conditions, and international acceptance as a residue-free treatment. In this review, we critically analyze the published literature in the area of phosphine resistance with special emphasis on the methods available for detection of resistance, the genetic basis of resistance development, key management strategies, and research gaps that need to be addressed.

Abstract Epigenetic variation is likely to contribute to the phenotypic plasticity and adaptative capacity of plant species, and may be especially important for long‐lived organisms with complex life cycles, including forest trees. Diverse environmental stresses and hybridization/polyploidization events can create reversible heritable epigenetic marks that can be transmitted to subsequent generations as a form of molecular “memory”. Epigenetic changes might also contribute to the ability of plants to colonize or persist in variable environments. In this review, we provide an overview of recent data on epigenetic mechanisms involved in developmental processes and responses to environmental cues in plant, with a focus on forest tree species. We consider the possible role of forest tree epigenetics as a new source of adaptive traits in plant breeding, biotechnology, and ecosystem conservation under rapid climate change.

Abstract Enteric methane ( CH 4 ) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH 4 is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH 4 production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH 4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH 4 production (g/day per cow), yield [g/kg dry matter intake ( DMI )], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross‐validate their performance; and (4) assess the trade‐off between availability of on‐farm inputs and CH 4 prediction accuracy. The intercontinental database covered Europe ( EU ), the United States ( US ), and Australia ( AU ). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error ( RMSPE ) as a percentage of mean observed value of 16.6%, 14.7%, and 19.8% for intercontinental, EU , and United States regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH 4 production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH 4 emission conversion factors for specific regions are required to improve CH 4 production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary neutral detergent fiber ( NDF ) concentration, improve the prediction. For enteric CH 4 yield and intensity prediction, information on milk yield and composition is required for better estimation.

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships for Parthenium hysterophorus L. (Asteraceae) with four modeling methods run with multiple scenarios of (i) sources of occurrences and geographically isolated background ranges for absences, (ii) approaches to drawing background (absence) points, and (iii) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved using a global dataset for model training, rather than restricting data input to the species' native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e., into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g., boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post hoc test conducted on a new Parthenium dataset from Nepal validated excellent predictive performance of our 'best' model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for parthenium. However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed.

Genotype-environment interactions (GEI) limit genetic gain for complex traits such as tolerance to drought. Characterization of the crop environment is an important step in understanding GEI. A modelling approach is proposed here to characterize broadly (large geographic area, long-term period) and locally (field experiment) drought-related environmental stresses, which enables breeders to analyse their experimental trials with regard to the broad population of environments that they target. Water-deficit patterns experienced by wheat crops were determined for drought-prone north-eastern Australia, using the APSIM crop model to account for the interactions of crops with their environment (e.g. feedback of plant growth on water depletion). Simulations based on more than 100 years of historical climate data were conducted for representative locations, soils, and management systems, for a check cultivar, Hartog. The three main environment types identified differed in their patterns of simulated water stress around flowering and during grain-filling. Over the entire region, the terminal drought-stress pattern was most common (50% of production environments) followed by a flowering stress (24%), although the frequencies of occurrence of the three types varied greatly across regions, years, and management. This environment classification was applied to 16 trials relevant to late stages testing of a breeding programme. The incorporation of the independently-determined environment types in a statistical analysis assisted interpretation of the GEI for yield among the 18 representative genotypes by reducing the relative effect of GEI compared with genotypic variance, and helped to identify opportunities to improve breeding and germplasm-testing strategies for this region.

Climate change in Australia is expected to influence crop growing conditions through direct increases in elevated carbon dioxide (CO2) and average temperature, and through increases in the variability of climate, with potential to increase the occurrence of abiotic stresses such as heat, drought, waterlogging, and salinity. Associated effects of climate change and higher CO2 concentrations include impacts on the water-use efficiency of dryland and irrigated crop production, and potential effects on biosecurity, production, and quality of product via impacts on endemic and introduced pests and diseases, and tolerance to these challenges. Direct adaptation to these changes can occur through changes in crop, farm, and value-chain management and via economically driven, geographic shifts where different production systems operate. Within specific crops, a longer term adaptation is the breeding of new varieties that have an improved performance in ‘future’ growing conditions compared with existing varieties. In crops, breeding is an appropriate adaptation response where it complements management changes, or when the required management changes are too expensive or impractical. Breeding requires the assessment of genetic diversity for adaptation, and the selection and recombining of genetic resources into new varieties for production systems for projected future climate and atmospheric conditions. As in the past, an essential priority entering into a ‘climate-changed’ era will be breeding for resistance or tolerance to the effects of existing and new pests and diseases. Hence, research on the potential incidence and intensity of biotic stresses, and the opportunities for breeding solutions, is essential to prioritise investment, as the consequences could be catastrophic. The values of breeding activities to adapt to the five major abiotic effects of climate change (heat, drought, waterlogging, salinity, and elevated CO2) are more difficult to rank, and vary with species and production area, with impacts on both yield and quality of product. Although there is a high likelihood of future increases in atmospheric CO2 concentrations and temperatures across Australia, there is uncertainty about the direction and magnitude of rainfall change, particularly in the northern farming regions. Consequently, the clearest opportunities for ‘in-situ’ genetic gains for abiotic stresses are in developing better adaptation to higher temperatures (e.g. control of phenological stage durations, and tolerance to stress) and, for C3 species, in exploiting the (relatively small) fertilisation effects of elevated CO2. For most cultivated plant species, it remains to be demonstrated how much genetic variation exists for these traits and what value can be delivered via commercial varieties. Biotechnology-based breeding technologies (marker-assisted breeding and genetic modification) will be essential to accelerate genetic gain, but their application requires additional investment in the understanding, genetic characterisation, and phenotyping of complex adaptive traits for climate-change conditions.

) is responsible for damage to 'Lady Finger' (AAB, Pome subgroup) and other less widely grown cultivars such as 'Ducasse' (Pisang Awak, ABB). Subtropical Race 4 (STR4) also affects these cultivars as well as Cavendish cultivars (AAA) in southern Queensland and northern New South Wales where cold temperature predisposition is involved. Tropical Race 4 (TR4) has led to the demise of the Cavendish industry in the Northern Territory, and its presence was confirmed in a North Queensland plantation in 2015, which warranted destruction of all banana plants on the property; as of this writing (April 2019), TR4 has spread to two adjacent properties. This review, which was commissioned by Biosecurity Queensland in response to the 2015 TR4 outbreak, considers the key epidemiological factors associated with the onset of a Fusarium wilt epidemic. Resistance to TR4, which is mediated by events following entry by the pathogen into the xylem, is not present in any commercially acceptable banana cultivar. Also, there is no effective chemical agent that can be used to manage the disease. Besides prevention, very early recognition and rapid containment of a disease outbreak are necessary to prevent epidemic development. A good understanding of the key factors responsible for disease development is required when devising practical protocols for the destruction of infected plants, treatment of surrounding infested soil, and reduction of inoculum in plant residues and soil.

BACKGROUND: Water availability is a major limiting factor for wheat (Triticum aestivum L.) production in rain-fed agricultural systems worldwide. Root system architecture has important functional implications for the timing and extent of soil water extraction, yet selection for root architectural traits in breeding programs has been limited by a lack of suitable phenotyping methods. The aim of this research was to develop low-cost high-throughput phenotyping methods to facilitate selection for desirable root architectural traits. Here, we report two methods, one using clear pots and the other using growth pouches, to assess the angle and the number of seminal roots in wheat seedlings- two proxy traits associated with the root architecture of mature wheat plants. RESULTS: Both methods revealed genetic variation for seminal root angle and number in the panel of 24 wheat cultivars. The clear pot method provided higher heritability and higher genetic correlations across experiments compared to the growth pouch method. In addition, the clear pot method was more efficient - requiring less time, space, and labour compared to the growth pouch method. Therefore the clear pot method was considered the most suitable for large-scale and high-throughput screening of seedling root characteristics in crop improvement programs. CONCLUSIONS: The clear-pot method could be easily integrated in breeding programs targeting drought tolerance to rapidly enrich breeding populations with desirable alleles. For instance, selection for narrow root angle and high number of seminal roots could lead to deeper root systems with higher branching at depth. Such root characteristics are highly desirable in wheat to cope with anticipated future climate conditions, particularly where crops rely heavily on stored soil moisture at depth, including some Australian, Indian, South American, and African cropping regions.

Wastewater surveillance for pathogens using reverse transcription-polymerase chain reaction (RT-PCR) is an effective and resource-efficient tool for gathering community-level public health information, including the incidence of coronavirus disease-19 (COVID-19). Surveillance of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in wastewater can potentially provide an early warning signal of COVID-19 infections in a community. The capacity of the world's environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is increasing rapidly. However, there are no standardized protocols or harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can cause false-positive and false-negative errors in the surveillance of SARS-CoV-2 RNA in wastewater, culminating in recommended strategies that can be implemented to identify and mitigate some of these errors. Recommendations include stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, PCR inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly when the incidence of SARS-CoV-2 in wastewater is low. Corrective and confirmatory actions must be in place for inconclusive results or results diverging from current trends (e.g., initial onset or reemergence of COVID-19 in a community). It is also prudent to perform interlaboratory comparisons to ensure results' reliability and interpretability for prospective and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization and detection for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance continues to be demonstrated during this global crisis. In the future, wastewater should also play an important role in the surveillance of a range of other communicable diseases.

Strigolactones are a group of plant compounds of diverse but related chemical structures. They have similar bioactivity across a broad range of plant species, act to optimize plant growth and development, and promote soil microbe interactions. Carlactone, a common precursor to strigolactones, is produced by conserved enzymes found in a number of diverse species. Versions of the MORE AXILLARY GROWTH1 (MAX1) cytochrome P450 from rice and Arabidopsis thaliana make specific subsets of strigolactones from carlactone. However, the diversity of natural strigolactones suggests that additional enzymes are involved and remain to be discovered. Here, we use an innovative method that has revealed a missing enzyme involved in strigolactone metabolism. By using a transcriptomics approach involving a range of treatments that modify strigolactone biosynthesis gene expression coupled with reverse genetics, we identified LATERAL BRANCHING OXIDOREDUCTASE (LBO), a gene encoding an oxidoreductase-like enzyme of the 2-oxoglutarate and Fe(II)-dependent dioxygenase superfamily. Arabidopsis lbo mutants exhibited increased shoot branching, but the lbo mutation did not enhance the max mutant phenotype. Grafting indicated that LBO is required for a graft-transmissible signal that, in turn, requires a product of MAX1. Mutant lbo backgrounds showed reduced responses to carlactone, the substrate of MAX1, and methyl carlactonoate (MeCLA), a product downstream of MAX1. Furthermore, lbo mutants contained increased amounts of these compounds, and the LBO protein specifically converts MeCLA to an unidentified strigolactone-like compound. Thus, LBO function may be important in the later steps of strigolactone biosynthesis to inhibit shoot branching in Arabidopsis and other seed plants.

Information on the geographic variation in soil has traditionally been presented in polygon (choropleth) maps at coarse scales. Now scientists, planners, managers and politicians want quantitative information on the variation and functioning of soil at finer resolutions; they want it to plan better land use for agriculture, water supply and the mitigation of climate change land degradation and desertification. The GlobalSoilMap project aims to produce a grid of soil attributes at a fine spatial resolution (approximately 100 m), and at six depths, for the purpose. This paper describes the three-dimensional spatial modelling used to produce the Australian soil grid, which consists of Australia-wide soil attribute maps. The modelling combines historical soil data plus estimates derived from visible and infrared soil spectra. Together they provide a good coverage of data across Australia. The soil attributes so far include sand, silt and clay contents, bulk density, available water capacity, organic carbon, pH, effective cation exchange capacity, total phosphorus and total nitrogen. The data on these attributes were harmonised to six depth layers, namely 0–0.05 m, 0.05–0.15 m, 0.15–0.30 m, 0.30–0.60 m, 0.60–1.00 m and 1.00–2.00 m, and the resulting values were incorporated simultaneously in the models. The modelling itself combined the bootstrap, a decision tree with piecewise regression on environmental variables and geostatistical modelling of residuals. At each layer, values of the soil attributes were predicted at the nodes of a 3 arcsecond (approximately 90 m) grid and mapped together with their uncertainties. The assessment statistics for each attribute mapped show that the models explained between 30% and 70% of their total variation. The outcomes are illustrated with maps of sand, silt and clay contents and their uncertainties. The Australian three-dimensional soil maps fill a significant gap in the availability of quantitative soil information in Australia.

Focusing on woody vegetation in Queensland, Australia, the study aimed to establish whether the relationship between Advanced Land Observing Satellite (ALOS) Phased Array L-band SAR (PALSAR) HH and HV backscattering coefficients and above ground biomass (AGB) was consistent within and between structural formations (forests, woodlands and open woodlands, including scrub). Across these formations, 2781 plot-based measurements (from 1139 sites) of tree diameters by species were collated, from which AGB was estimated using generic allometric equations. For Queensland, PALSAR fine beam dual (FBD) 50 m strip data for 2007 were provided through the Japanese Space Exploration Agency's (JAXA) Kyoto and Carbon (K&C) Initiative, with up to 3 acquisitions available for each Reference System for Planning (RSP) paths. When individual strips acquired over Queensland were combined, `banding' was evident within the resulting mosaics, with this attributed to enhanced L-band backscatter following rainfall events in some areas. Reference to Advanced Microwave Scanning Radiometer-EOS (AMSR-E) data indicated that strips with enhanced L-band backscatter corresponded to areas with increased effective vegetation water content (kg m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> ) and, to a lesser extent, soil moisture (g cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> ). Regardless of moisture conditions, L-band HV topographically normalized backscattering intensities backscatter (σ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> ) increased asymptotically with AGB, with the saturation level being greatest for forests and least for open woodlands. However, under conditions of relative maximum surface moisture, L-band HV and HH σ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> was enhanced by as much as 2.5 and 4.0 dB respectively, particularly for forests of lower AGB, with this resulting in an overall reduction in dynamic range. The saturation level also reduced at L-band HH for forests and woodlands but remained similar for open woodlands. Differences in the rate of increase in both L-band HH and HV σ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> with AGB were observed between forests and the woodland categories (for both relatively wet and dry conditions) with these attributed, in part, to differences in the size class distribution and stem density between non-remnant (secondary) forests and remnant woodlands of lower AGB. The study concludes that PALSAR data acquired when surface moisture and rainfall are minimal allow better estimation of the AGB of woody vegetation and that retrieval algorithms ideally need to consider differences in surface moisture conditions and vegetation structure.