ORCID Profile
0000-0002-5505-3869
Current Organisation
University of Sydney
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Food Packaging, Preservation and Safety | Food Sciences | Horticultural Production not elsewhere classified
Publisher: IOP Publishing
Date: 04-2022
Abstract: Human activities both aggravate and alleviate streamflow drought. Here we show that aggravation is dominant in contrasting cases around the world analysed with a consistent methodology. Our 28 cases included different combinations of human-water interactions. We found that water abstraction aggravated all drought characteristics, with increases of 20%–305% in total time in drought found across the case studies, and increases in total deficit of up to almost 3000%. Water transfers reduced drought time and deficit by up to 97%. In cases with both abstraction and water transfers into the catchment or augmenting streamflow from groundwater, the water inputs could not compensate for the aggravation of droughts due to abstraction and only shift the effects in space or time. Reservoir releases for downstream water use alleviated droughts in the dry season, but also led to deficits in the wet season by changing flow seasonality. This led to minor changes in average drought duration (−26 to +38%) and moderate changes in average drought deficit (−86 to +369%). Land use showed a smaller impact on streamflow drought, also with both increases and decreases observed (−48 to +98%). Sewage return flows and pipe leakage possibly counteracted the effects of increased imperviousness in urban areas however, untangling the effects of land use change on streamflow drought is challenging. This synthesis of erse global cases highlights the complexity of the human influence on streamflow drought and the added value of empirical comparative studies. Results indicate both intended and unintended consequences of water management and infrastructure on downstream society and ecosystems.
Publisher: Elsevier BV
Date: 05-2012
Publisher: CSIRO Publishing
Date: 2017
DOI: 10.1071/ZO17081
Abstract: Habitat heterogeneity can have considerable effects on gene flow and migration across a region of parapatry. Describing habitat across a region of parapatry is important for the development of eco-evolutionary theory. Two subspecies of thick-billed grasswren (Amytornis modestus) share a region of parapatry between the South Australian salt lakes, Lake Eyre and Lake Torrens. While the two subspecies remain morphologically erged outside the region of parapatry, it is not known what factors within the region of parapatry may affect migration and gene flow. In this study, we test associations between habitat differences and subspecies distributions and discuss whether ecological barriers could play a role in mitigating gene flow between the subspecies. We compare dominant plant species (1) between the allopatric ranges of the subspecies and within their region of parapatry, and (2) in relation to presence or absence of grasswrens within their region of parapatry. We found that the dominant plant species differed between grasswren subspecies in their allopatric range and in their region of parapatry, and also differed in the region of parapatry at sites with or without grasswrens. Specifically, grasswrens were absent in vegetation that is typical of sand dunes. These findings are discussed in light of evidence for secondary contact and hybridisation between A. m. indulkanna and A. m. raglessi, and susceptibility to introgression.
Publisher: Elsevier BV
Date: 07-2023
Publisher: Elsevier BV
Date: 05-2021
Publisher: MDPI AG
Date: 18-02-2023
Abstract: Pendimethalin herbicide toxicity to rice plants and barnyard grass invasion have increasingly affected the productivity of direct-seeded rice (DSR) in the fields. Whether and how to promote DSR productivity and sustain weed management depend on the appropriate pre-emergence herbicide application rate to minimise its toxicity in the rice ecosystem. Pot experiments were conducted to determine the effects of pendimethalin rates (1.5, 1.75, 2.0 kg a.i. ha−1, two control treatments include the untreated control and the treated control with 1.5 kg a.i. ha−1 S-metolachlor) on barnyard grass (Echinochloa crus-galli (L.) Beaux) and their potential toxicity risk to photosynthetic performances of rice (Topaz and Sen pidao). All the pendimethalin treatments provided excellent control of barnyard grass. Among the treatments, 1.5, 1.75, 2.0 kg a.i. ha−1 pendimethalin and 1.5 kg a.i. ha−1 S-metolachlor (treated control) decreased leaf area of barnyard grass significantly by 38.9, 49.6, 49.6 and 46.2%, respectively, compared with the untreated control at 40 days after sowing (DAS). The above-ground biomass of barnyard grass significantly decreased by 40% (1.48 g plant−1) with 2.0 kg a.i. ha−1 pendimethalin and by 46.2% (1.33 g plant−1) when 1.5 kg a.i. ha−1S-metolachlor was applied at 40 DAS compared with the untreated pots. Higher pendimethalin rates increased toxicity in Topaz and Sen pidao varieties, and 2.0 kg a.i. ha−1 pendimethalin significantly reduced effective quantum yield (light-adapted) of photosystem (PS) II by 18% (0.58) and 19% (0.52), respectively, compared with the untreated control. Application of 2.0 kg a.i. ha−1 pendimethalin rate significantly decreased the maximum quantum yield (dark-adapted) of Sen pidao (0.66) compared with 1.5 kg a.i. ha−1 pendimethalin (0.68) including the untreated control. All pendimethalin treatments suppressed above-ground biomass at 55 DAS, but above-ground biomass of barnyard grass significantly decreased by 59.9% when 2.0 kg a.i. ha−1 pendimethalin was applied compared with the untreated control. Although application of 1.5 kg a.i. ha−1 pendimethalin rates reduced the effective quantum yield (light-adapted) of photosystem II of Sen pidao (0.55) by a small percentage (8%) than Topaz (0.65), it was non-toxic for both varieties compared with 2.0 kg a.i. ha−1 pendimethalin. Therefore, the use of 1.5 kg a.i. ha−1 pendimethalin can be used for effective weed management in the direct seeding of rice at an early growth stage.
Publisher: Elsevier BV
Date: 08-2021
Publisher: Wiley
Date: 26-11-2018
DOI: 10.1111/PBR.12660
Publisher: MDPI AG
Date: 14-03-2019
DOI: 10.3390/W11030533
Abstract: Wildfire can have significant impacts on hydrological processes in forested catchments, and a key area of concern is the impact upon water quality, particularly in catchments that supply drinking water. Wildfire effects runoff, erosion, and increases the influx of other pollutants into catchment waterways. Research suggests that suspended sediment and nutrient levels increase following wildfire. However, past studies on catchment water quality change have generally focused on the short term (1–3 years) effects of wildfire. For appropriate catchment management, it is important to know the long-term effect of wildfire on catchment water quality and the recovery process. In this study, a statistical analysis was performed to examine the effect of 2001/2002 Sydney wildfire on catchment water quality. This research is particularly important, since the catchments studied provide drinking water to Sydney. Linear mixed models were used in this study in an analysis of covariance (ANCOVA)-type change detection approach to assess the effect of wildfire. We used both burnt and unburnt catchments to aid the interpretation of the results and to help disentangle the effects of natural climate variation, as well as of the wildfire. The results of this study showed persistent long-term (10-year) effects of wildfire, including increases in total suspended sediment concentrations (64% higher than in unburnt catchments), total nitrogen concentrations (48% higher), and total phosphorus (40% higher).
Publisher: CSIRO Publishing
Date: 2015
DOI: 10.1071/SR13170
Abstract: Soil properties can be considerably modified as a result of wildfire. This study examined the impact of wildfire on total carbon and water repellency at two study sites, namely Cranebrook and Wentworth Falls, located 45 and 75 km west of Sydney, Australia, respectively. Within each study site, we measured soil properties at two depth intervals from five burn severity classes along 15 transects (10 s le points per transect). S les were taken 6, 12 and 36 months after wildfire. Soil total carbon was measured using LECO combustion analysis and potential soil water repellency was determined using water drop penetration time. Two-way analysis of variance (ANOVA) was used to analyse the results, with burn severity and time as factors. Burn severity had a significant effect on both soil total carbon and water repellency at both study sites, whereas time was only significant for soil carbon at Wentworth Falls. Soil total carbon and water repellency were variable through time due to local environmental variables, such as rainfall and temperature. The relationship between soil total carbon and water repellency was strong for Cranebrook in the surface soil (r = 0.62) and lower in the subsurface soil (r = 0.41), but weaker at Wentworth Falls, with values of r = 0.22 and r = 0.15 in the surface and subsurface soils respectively.
Publisher: MDPI AG
Date: 15-04-2019
DOI: 10.3390/W11040780
Abstract: Uncertainty about global change requires alternatives to quantify the availability of water resources and their dynamics. A methodology based on different satellite imagery and surface elevation models to estimate surface water volumes would be useful to monitor flood events and reservoir storages. In this study, reservoirs with associated digital terrain models (DTM) and continuously monitored volumes were selected. The inundated extent was based on a supervised classification using surface reflectance in Landsat 5 images. To estimate associated water volumes, the DTMs were s led at the perimeter of inundated areas and an inverse distance weighting interpolation was used to populate the water elevation inside the flooded polygons. The developed methodology (IDW) was compared against different published methodologies to estimate water volumes from digital elevation models, which assume either a flat water surface using the maximum elevation of inundated areas (Max), and a flat water surface using the median elevation of the perimeter of inundated areas (Median), or a tilted surface, where water elevations are based on an iterative focal maximum statistic with increasing window sizes (FwDET), and finally a tilted water surface obtained by replacing the focal maximum statistic from the FwDET methodology with a focal mean statistic (FwDET_mean). Volume estimates depend strongly on both water detection and the terrain model. The Max and the FwDET methodologies are highly affected by the water detection step, and the FwDET_mean methodology leads to lower volume estimates due to the iterative smoothing of elevations, which also tends to be computationally expensive for big areas. The Median and IDW methodologies outperform the rest of the methods, and IDW can be used for both reservoir and flood volume monitoring. Different sources of error can be observed, being systematic errors associated with the DTM acquisition time and the reported volumes, which for ex le fail to consider dynamic sedimentation processes taking place in reservoirs. Resolution effects account for a fraction of errors, being mainly caused by terrain curvature.
Publisher: Informa UK Limited
Date: 24-07-2020
Publisher: Springer Science and Business Media LLC
Date: 27-10-2020
Publisher: Elsevier BV
Date: 05-2015
Publisher: Elsevier BV
Date: 05-2020
Publisher: Springer Science and Business Media LLC
Date: 06-2019
Publisher: Springer Science and Business Media LLC
Date: 06-01-2017
Publisher: Springer Science and Business Media LLC
Date: 12-09-2014
Publisher: Oxford University Press (OUP)
Date: 02-06-2020
DOI: 10.1111/LAM.13302
Publisher: Elsevier BV
Date: 12-2015
Publisher: Springer Science and Business Media LLC
Date: 10-03-2022
DOI: 10.1007/S11069-022-05286-Y
Abstract: Recently, applications of agent-based model (ABM) have been used to understand the interaction between social and hydrological systems. These systems are dynamic and co-evolving, which can be captured through different decision-making entities in an ABM simulation. Therefore, this review aims to better understand the use of ABM for flood risk management and assessment (FRMA). The review comprises a systematic selection of literature using the PRISMA method, which is then assessed using an adapted version of the overview, design, and detail (ODD) protocol to better understand the ABM model development process for FRMA. The review finds that the use of the ODD protocol was only seen in 25% of the studies. The studies which did not explicitly use the ODD had a comprehensive description of the models, albeit done in a non-standardised way. Modellers continue to face the dilemma between parsimony and the breadth of the model as identified from the design component of the ODD. The hydrological component is mainly captured in the sub-model process of the ODD, however, improvements in the definition of the sub-model component may warrant a more comprehensive description of the processes and facilitate comparison across studies. The applications of ABM have shown promise to understand long term flood risks, test the efficacy of policies and better understand the factors that affect warning response during the flood evacuation process. ODD adopted for this review may consequently allow for the adoption and more coherent use of the protocol to document models in FRMA.
Publisher: Wiley
Date: 15-10-2014
DOI: 10.1002/MET.1429
Publisher: Elsevier BV
Date: 10-2016
Publisher: Informa UK Limited
Date: 04-08-2017
Publisher: Copernicus GmbH
Date: 07-11-2011
DOI: 10.5194/HESS-15-3343-2011
Abstract: Abstract. Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a statistical model to forecast streamflow up to 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine the probability of flow occurring in any of the systems. We then use the same regression framework in combination with a right-skewed distribution, the Box-Cox t distribution, to model the intensity (depth) of the non-zero streamflows. Time, seasonality and climate indices, describing the Pacific and Indian Ocean sea surface temperatures, are tested as covariates in the GAMLSS model to make probabilistic 6 and 12-month forecasts of the occurrence and intensity of streamflow. The output reveals that in the study region the occurrence and variability of flow is driven by sea surface temperatures and therefore forecasts can be made with some skill.
Publisher: Frontiers Media SA
Date: 02-12-2022
DOI: 10.3389/FCENG.2022.1039675
Abstract: There are hundreds of species of Agaves found globally in natural and anthropogenic systems. Agaves are used to produce fibres, alcoholic beverages like tequila, and in biofuel production. The objectives of this study were to assess the research available into Agave planting density and to use PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) to suggest an optimum planting density for the highest dry aboveground productivity. Background research into Agave planting densities found little data on the effect of planting density on biomass production, with most studies focusing on other independent variables affecting productivity. There were 13 data points included in the analysis. The meta-analysis suggested that the optimal planting density of Agave is approximately 2,600 plants ha −1 , which provides optimal dry aboveground biomass of 28.8 Mg ha −1 yr −1 . These findings provide a framework for further experimentation in Australian conditions using a Nelder design density experiment to ground-truth the meta-analysis.
Publisher: Elsevier BV
Date: 08-2022
Publisher: PeerJ
Date: 26-08-2019
DOI: 10.7717/PEERJ.7523
Abstract: Analysis of observational data to pinpoint impact of land cover change on local rainfall is difficult due to multiple environmental factors that cannot be strictly controlled. In this study we use a statistical approach to identify the relationship between removal of tree cover and rainfall with data from best available sources for two large areas in Australia. Gridded rainfall data between 1979 and 2015 was used for the areas, while large scale (exogenous) effects were represented by mean rainfall across a much larger area and climatic indicators, such as Southern Oscillation Index and Indian Ocean Dipole. Both generalised additive modelling and step trend tests were used for the analysis. For a region in south central Queensland, the reported change in tree clearing between 2002–2005 did not result in strong statistically significant precipitation changes. On the other hand, results from a bushfire affected region on the border of New South Wales and Victoria suggest significant changes in the rainfall due to changes in tree cover. This indicates the method works better when an abrupt change in the data can be clearly identified. The results from the step trend test also mainly identified a positive relationship between the tree cover and the rainfall at p 0.1 at the NSW/Victoria region. High rainfall variability and possible regrowth could have impacted the results in the Queensland region.
Publisher: Springer Science and Business Media LLC
Date: 30-10-2016
Publisher: Elsevier BV
Date: 09-2019
DOI: 10.1016/J.HAL.2018.10.005
Abstract: Photoautotrophs are capable of consuming high quantities of CO
Publisher: ASM Press
Date: 05-09-2017
Publisher: Elsevier BV
Date: 11-2014
Publisher: Springer Science and Business Media LLC
Date: 12-2016
Publisher: Wiley
Date: 02-11-2015
DOI: 10.1002/WAT2.1121
Abstract: Forecasts can be an important component of water cycle management and farm decision making, particularly where rainfall is uncertain. In Kenya, the use of informal or indigenous forecasting ( IF ) is known to be widespread, but farmers also use more formal seasonal forecasting ( SF ) to make decisions in relation to the water cycle. A review of literature indicates that local knowledge is adaptable and often mixes indigenous knowledge and external information. In most cases, IF focusses on more local features and relates more to practical farm activities. Based on extensive interviews and focus groups of farmers in two study areas in Kenya, a majority of farmers from each area used IF , even though SF was also used. There were few farmer characteristics that explained the difference in the use of IF and SF . However, there were differences between the two study areas in how farmers interpreted SF and whether they used a combination of SF and IF . Furthermore there were differences in the local IF indicators used by farmers to identify the onset of the rainy season. To improve the acceptance of SF and increase its use, the information provided in SF needs to be easily incorporated into farmers’ current working knowledge, which might also include IF . This means that SF tools should be developed using participatory approaches to ensure the engagement of local farmers. WIREs Water 2016, 3:127–140. doi: 10.1002/wat2.1121 This article is categorized under: Human Water Water as Imagined and Represented
Publisher: Wiley
Date: 15-01-2016
DOI: 10.1002/RRA.2993
Publisher: Springer Science and Business Media LLC
Date: 31-10-2016
Publisher: Elsevier BV
Date: 07-2015
DOI: 10.1016/J.CUB.2015.02.070
Abstract: While et al's quick guide to Egernia lizards, a group of social lizards from Austalasia.
Publisher: Elsevier BV
Date: 02-2016
Publisher: Springer Science and Business Media LLC
Date: 29-03-2021
DOI: 10.1007/S13753-021-00336-8
Abstract: Integrating local knowledge and scientific information can aid in co-developing locally relevant approaches for climate change adaptation and disaster risk reduction. Communities along the Mekong River have adapted to variability in temperature, rainfall, and flooding patterns over time. Rapid environmental change in the Mekong Basin presents a new set of challenges related to drought, altered seasonal rainfall, more frequent high-flow flood events, and water withdrawals for hydropower and irrigation. We present a multi-method approach to understand how local knowledge of the spatial and temporal patterns of floods, droughts, and rainfall can be integrated with scientific information along a flood-prone section of the lower Mekong River in Kratie Province, Cambodia. Participatory hazard mapping of community members’ knowledge of the movement of floodwaters through the landscape enabled interpretation of flood extent mapping using Synthetic Aperture Radar images from the Sentinel-1A satellite. Seasonal calendars of weather patterns and livelihood activities, together with local indicators of flooding, rainfall, and drought were compared with trends in 35 years of rainfall data, and highlighted “pressure points” at the beginning and end of the rainy season where agriculture may be particularly impacted by climate change. We discuss potential applications of our findings for adaptation and hazard planning.
Publisher: Elsevier BV
Date: 07-2020
Publisher: Wiley
Date: 09-2016
Publisher: Elsevier BV
Date: 05-2021
Publisher: American Society for Microbiology
Date: 07-11-2018
Abstract: Cryptococcosis results in hundreds of thousands of deaths annually, predominantly in sub-Saharan Africa. Cryptococcus is an encapsulated yeast, and during infection, cells have the capacity for substantial morphological changes, including capsule enlargement and shedding and variations in cell shape and size. In this study, we examined 70 Cryptococcus isolates causing meningitis in HIV/AIDS patients in Botswana in order to look for associations between phenotypic variation and clinical symptoms. Four variant phenotypes were seen across strains: giant cells of ≥15 µm, micro cells of ≤1 µm, shed extracellular capsule, and irregularly shaped cells. We found that “large” and “small” phenotypes were associated with differing disease symptoms, indicating that their production may be important during the disease process. Overall, our study indicates that Cryptococcus strains that can switch on cell types under different situations may be more able to sustain infection and resist the host response.
Publisher: American Society for Microbiology
Date: 10-03-2017
DOI: 10.1128/MICROBIOLSPEC.FUNK-0038-2016
Abstract: The ersity and abundance of zoosporic true fungi have been analyzed recently using fungal sequence libraries and advances in molecular methods, such as high-throughput sequencing. This review focuses on four evolutionary primitive true fungal phyla: the Aphelidea, Chytridiomycota, Neocallimastigomycota, and Rosellida (Cryptomycota), most species of which are not polycentric or mycelial (filamentous), rather they tend to be primarily monocentric (unicellular). Zoosporic fungi appear to be both abundant and erse in many aquatic habitats around the world, with abundance often exceeding other fungal phyla in these habitats, and numerous novel genetic sequences identified. Zoosporic fungi are able to survive extreme conditions, such as high and extremely low pH however, more work remains to be done. They appear to have important ecological roles as saprobes in decomposition of particulate organic substrates, pollen, plant litter, and dead animals as parasites of zooplankton and algae as parasites of vertebrate animals (such as frogs) and as symbionts in the digestive tracts of mammals. Some chytrids cause economically important diseases of plants and animals. They regulate sizes of phytoplankton populations. Further metagenomics surveys of aquatic ecosystems are expected to enlarge our knowledge of the ersity of true zoosporic fungi. Coupled with studies on their functional ecology, we are moving closer to unraveling the role of zoosporic fungi in carbon cycling and the impact of climate change on zoosporic fungal populations.
Publisher: Springer Science and Business Media LLC
Date: 31-03-2022
DOI: 10.1007/S00477-022-02204-3
Abstract: Hydrological extremes occupy a large spatial extent, with a temporal sequence, both of which can be influenced by a range of climatological and geographical phenomena. Understanding the key information in the spatial and temporal domain is essential to make accurate forecasts. The capabilities of deep learning methods can be applied in such instances due to their enhanced ability in learning complex relationships. Given its success in other domains, this study presents a framework that features a long short-term memory deep learning model for spatio temporal hydrological extreme forecasting in the South Pacific region. The data consists of satellite rainfall estimates and sea surface temperature (SST) anomalies. We use the satellite rainfall estimate to calculate the effective drought index (EDI), an indicator of hydrological extreme events. The framework is developed to forecast monthly EDI using three different approaches: (i) univariate (ii) multivariate with neighbouring spatial points (iii) multivariate with neighbouring spatial points and the eigenvector values of SST. Additionally, better identification of extreme wet events is noted with the inclusion of the eigenvector values of SST. By establishing the framework for the multivariate approach in two forms, it is evident that the model accuracy is contingent on understanding the dominant feature which influences precipitation regimes in the Pacific. The framework can be used to better understand linear and non-linear relationships within multi-dimensional data in other study regions, and provide long-term climate outlooks.
Publisher: MDPI AG
Date: 19-11-2019
DOI: 10.3390/W11112424
Abstract: Many lumped rainfall-runoff models are available but no single model can account for the uniqueness and variability of all catchments. While there has been progress in developing frameworks for optimal model selection, the process currently selects a range of model structures a priori rather than starting from the hydrological data and processes. In addition, studies on differential split s le tests (DSSTs) have focused on objective function definitions and calibration approaches. In this study, seven hydrological signatures and 12 catchment characteristics from 108 catchments around Australia were extracted for two 7-year time periods: (1) wet and (2) dry. The data was modelled using the GR4J, HBV and SIMHYD models using three objective functions to explore the relationship between model performance, catchment features and identified parameters. The hypothesis is that the hydrological signatures and catchment characteristics reflect catchment behaviour, and that certain signatures and characteristics are associated with better calibration performance. The results show that a greater percentage of catchments achieved a better calibration performance in the wet period compared to the dry period and that better calibration performance is associated with catchments that have greater cumulative flow and a steeper flow duration curve. The findings are consistent across the three models and three objective functions, suggesting that there is a bias in the studied models to wetter catchments. This study echoes the need to develop a conceptual model that can accommodate a wide variety of catchments and climates and provides a foundation to optimise and improve model selection in catchments based on their unique characteristics.
Publisher: Wiley
Date: 04-09-2017
DOI: 10.1111/WRE.12265
Publisher: Wiley
Date: 15-12-2020
DOI: 10.1002/HYP.13999
Publisher: Wiley
Date: 21-09-2015
DOI: 10.1002/WAT2.1118
Abstract: Farmer perceptions clearly influence the adoption of technology and adaptation to climate change, but may not be consistent with or captured by scientific measurements. There has been a significant research on how perceptions influence water resource management and adaptation to climate, but conclusions are unclear or contradictory. This research aimed to clarify what shapes perceptions and how this understanding can refine meteorological data collection and to make more relevant and useful tools for farmers to adapt to changes in the water cycle. A survey of 244 small‐scale maize farmers was conducted using a questionnaire and semi‐structured interviews in two districts in southern and western Kenya which differed in climate type and farming systems. Farmer perceptions of and adaptation to climate uncertainty were investigated and compared with meteorological data. Most farmers perceived changes in the patterns of rainfall and dry spells, including later onset of rains than in the past. They have already adjusted their management based on these perceptions, including later planting times. Despite this, analysis of meteorological data indicated no major trends in rainfall or dry spell patterns in the two regions. This research confirms that the perception that the water cycle is changing is based on a combination of climatic, economic, or social observations, and farmers are already changing their management to adapt to the perceived changes in climate. The article explores the reasons why these perceptions were inconsistent with the available meteorological data and suggests that research may improve the usefulness of meteorological data to farmers. WIREs Water 2016, 3:105–125. doi: 10.1002/wat2.1118 This article is categorized under: Human Water Water as Imagined and Represented
Publisher: Copernicus GmbH
Date: 26-03-2019
DOI: 10.5194/HESS-23-1725-2019
Abstract: Abstract. Quantifying the influence of human activities, such as reservoir building, water abstraction, and land use change, on hydrology is crucial for sustainable future water management, especially during drought. Model-based methods are very time-consuming to set up and require a good understanding of human processes and time series of water abstraction, land use change, and water infrastructure and management, which often are not available. Therefore, observation-based methods are being developed that give an indication of the direction and magnitude of the human influence on hydrological drought based on limited data. We suggest adding to those methods a “paired-catchment” approach, based on the classic hydrology approach that was developed in the 1920s for assessing the impact of land cover treatment on water quantity and quality. When applying the paired-catchment approach to long-term pre-existing human influences trying to detect an influence on extreme events such as droughts, a good catchment selection is crucial. The disturbed catchment needs to be paired with a catchment that is similar in all aspects except for the human activity under study, in that way isolating the effect of that specific activity. In this paper, we present a framework for selecting suitable paired catchments for the study of the human influence on hydrological drought. Essential elements in this framework are the availability of qualitative information on the human activity under study (type, timing, and magnitude), and the similarity of climate, geology, and other human influences between the catchments. We show the application of the framework on two contrasting case studies, one impacted by groundwater abstraction and one with a water transfer from another region. Applying the paired-catchment approach showed how the groundwater abstraction aggravated streamflow drought by more than 200 % for some metrics (total drought duration and total drought deficit) and the water transfer alleviated droughts with 25 % to 80 %, dependent on the metric. Benefits of the paired-catchment approach are that climate variability between pre- and post-disturbance periods does not have to be considered as the same time periods are used for analysis, and that it avoids assumptions considered when partly or fully relying on simulation modelling. Limitations of the approach are that finding a suitable catchment pair can be very challenging, often no pre-disturbance records are available to establish the natural difference between the catchments, and long time series of hydrological data are needed to robustly detect the effect of the human activities on hydrological drought. We suggest that the approach can be used for a first estimate of the human influence on hydrological drought, to steer c aigns to collect more data, and to complement and improve other existing methods (e.g. model-based or large-s le approaches).
Publisher: Elsevier BV
Date: 10-2013
Publisher: MDPI AG
Date: 18-01-2022
DOI: 10.3390/AGRICULTURE12020130
Abstract: Smallholder rice farmers need a multi-purpose model to forecast yield and manage limited resources such as fertiliser, irrigation water supply in-season, thus optimising inputs and increasing rice yield. Active sensing tools like Canopeo and GreenSeeker-NDVI have provided the opportunity to monitor crop health and development at different growth stages. In this study, we assessed the effectiveness of in-season estimation of rice yield in lowland fields of northwest Cambodia using weather data and vegetation cover information measured with (1) the mobile app-Canopeo, and (2) the conventional GreenSeeker hand-held device that measures the normalised difference vegetative index (NDVI). We collected data from a series of on-farm field experiments in the rice-growing regions in 2018 and 2019. Average temperature and cumulative rainfall were calculated at panicle initiation and pre-heading stages when the crop cover index was measured. A generalised additive model (GAM) was generated using log-transformed data for grain yield, with the combined predictors of canopy cover and weather data during panicle initiation and pre-heading stages. The pre-heading stage was the best stage for grain yield prediction with the Canopeo-derived vegetation index and weather data. Overall, the Canopeo index model explained 65% of the variability in rice yield and Canopeo index, average temperature and cumulative rainfall explained 5, 65 and 56% of the yield variability in rice yield, respectively, at the pre-heading stage. The model (Canopeo index and weather data) evaluation for the training set between the observed and the predicted yield indicated an R2 value of 0.53 and root mean square error (RMSE) was 0.116 kg ha−1 at the pre-heading stage. When the model was tested on a validation set, the R2 value was 0.51 (RMSE = 925.533 kg ha−1) between the observed and the predicted yield. The NDVI-weather model explained 62% of the variability in yield, NDVI, average temperature and cumulative rainfall explained 3, 62 and 54%, respectively, of the variability in yield for the training set. The NDVI-weather model evaluation for the training set showed a slightly lower fit with R2 value of 0.51 (RMSE = 0.119 kg ha−1) between the observed and the predicted yield at pre-heading stage. The accuracy performance of the model indicated an R2 value of 0.46 (RMSE = 979.283 kg ha−1) at the same growth stage for validation set. The vegetation-derived information from Canopeo index-weather data increasingly correlated with rice yield than NDVI-weather data. Therefore, the Canopeo index-weather model is a flexible and effective tool for the prediction of rice yield in smallholder fields and can potentially be used to identify and manage fertiliser and water supply to maximise productivity in rice production systems. Data availability from more field experiments are needed to test the model’s accuracy and improve its robustness.
Publisher: Elsevier BV
Date: 12-2020
Publisher: Wiley
Date: 06-2017
DOI: 10.1002/HYP.11219
Publisher: Elsevier BV
Date: 10-2014
Publisher: Elsevier BV
Date: 11-2014
Publisher: Elsevier BV
Date: 08-2015
Publisher: Elsevier BV
Date: 06-2019
Publisher: BMJ
Date: 08-2020
DOI: 10.1136/BMJGH-2020-002478
Abstract: Half the children under the age of 5 years in Papua New Guinea (PNG) are undernourished, more than double the global average with rural areas disproportionately affected. This study examines factors associated with stunting, wasting and underweight in cocoa growers’ children ( years) in the Autonomous Region of Bougainville (ARoB), using data from a comprehensive 2017 cross-sectional livelihoods survey. Sixteen independent predictors for stunting, wasting and underweight were selected based on the UNICEF Conceptual Framework of Determinants of Undernutrition. We used multilevel logistic mixed regression models to measure the association of the explanatory variables with stunting, wasting and underweight. At the household level, the adjusted OR (aOR) of stunting (aOR=1.71,95% CI 1.14 to 2.55) and underweight (aOR=2.11, 95% CI 1.16 to 3.82) increased significantly among children from households with unimproved toilet facilities. The aOR for underweight also increased among children from households without access to clean drinking water (aOR=1.97, 95% CI 1.19 to 3.29). Short maternal stature was significantly associated with child stunting, the odds increased as maternal height decreased (from 150 to cm, aOR=1.52, 95% CI 1.02 to 2.26) ( cm, aOR=2.37, 95% CI 1.29 to 4.35). At the in idual level, the odds of a child being underweight increased with birth order (second born, aOR=1.92, 95% CI 1.09 to 3.36 third born, aOR=6.77, 95% CI 2.00 to 22.82). Compared with children less than 6 months, children aged 6–23 months and 24–59 months had a higher odds of being stunted (aOR=3.27, 95% CI 1.57 to 6.78 and aOR=2.82, 95% CI 1.40 to 5.67) and underweight (aOR=4.83, 95% CI 1.36 to 17.24 and aOR=4.59, 95% CI 1.29 to 16.26). No variables were found to be significant for wasting. Interventions that simultaneously target key life stages for women and children and the underlying social and environmental determinants are required for sustained improvements to undernutrition.
Publisher: Informa UK Limited
Date: 03-02-2021
Publisher: Oxford University Press (OUP)
Date: 02-01-2017
Publisher: Cold Spring Harbor Laboratory
Date: 16-09-2018
DOI: 10.1101/418897
Abstract: Pathogenic species of Cryptococcus cause hundreds of thousands of deaths annually. Considerable phenotypic variation is exhibited during infection, including increased capsule size, capsule shedding, giant cells (≥ 15 μm) and micro cells (≤ 1 μm). We examined 70 clinical isolates of Cryptococcus neoformans and Cryptococcus tetragattii from HIV/AIDS patients in Botswana to determine if the capacity to produce morphological variants was associated with clinical parameters. Isolates were cultured under conditions designed to simulate in vivo stresses. Substantial variation was seen across morphological and clinical data. Giant cells were more common in C. tetragattii, while micro cells and shed capsule occurred in C. neoformans only. Phenotypic variables fell into two groups associated with differing symptoms. The production of “large” phenotypes (greater cell and capsule size and giant cells) was associated with higher CD4 count and was negatively correlated with intracranial pressure indicators, suggesting these are induced in early-stage infection. “Small” phenotypes (micro cells and shed capsule) were associated with lower CD4 counts, negatively correlated with meningeal inflammation indicators and positively correlated with intracranial pressure indicators, suggesting they are produced later during infection and may contribute to immune suppression and promote proliferation and dissemination. These trends persisted at the species level, indicating that they were not driven by association with particular Cryptococcus species. Isolates possessing giant cells, micro cells, and shed capsule were rare, but strikingly were associated with patient death (p=0.0165). Our data indicate that pleomorphism is an important driver in Cryptococcus infection. Cryptococcosis results in hundreds of thousands of deaths annually, predominantly in sub-Saharan Africa. Cryptococcus is an encapsulated yeast, and during infection cells have the capacity for substantial morphological changes, including capsule enlargement and shedding, and variations in cell shape and size. In this study we examined 70 Cryptococcus isolates causing meningitis in HIV/AIDS patients in Botswana in order to look for associations between phenotypic variation and clinical symptoms. Four variant phenotypes were seen across strains: giant cells ≥ 15 μm, micro cells ≤ 1 μm, shed extracellular capsule, and irregularly shaped cells. We found “large” and “small” phenotypes were associated with differing disease symptoms, indicating that their production may be important during the disease process. Overall, our study indicates that Cryptococcus strains that can switch on cell types under different situations may be more able to sustain infection and resist the host response.
Start Date: 2017
End Date: 2020
Funder: Australian Research Council
View Funded ActivityStart Date: 2014
End Date: 2019
Funder: Australian Centre for International Agricultural Research
View Funded ActivityStart Date: 2017
End Date: 2021
Funder: Australian Centre for International Agricultural Research
View Funded ActivityStart Date: 2017
End Date: 2019
Funder: Asia-Pacific Network for Global Change Research
View Funded ActivityStart Date: 2022
End Date: 2026
Funder: Grains Research and Development Corporation
View Funded ActivityStart Date: 02-2017
End Date: 02-2021
Amount: $2,259,000.00
Funder: Australian Research Council
View Funded Activity