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Aquatic Plant Management
No full textWhile aquatic plants are an integral component of freshwater ecosystems, invasive aquatic plants can cause severe environmental and socioeconomic impacts. Managing aquatic plants is highly complex for a range of reasons. Tools developed for terrestrial weed management are frequently unsuitable for freshwater environments. Also, unfamiliarity with the effective control of invasive aquatic plants often leads to a haphazard approach, lacking clear management goals, or tools are chosen based on hearsay or personal preferences. As a result, the management of aquatic plants is often inefficient, and at worst, causes significant environmental damage to sensitive aquatic environments.
The management of aquatic plants is highly situation-dependent, and control tools should be selected based on management goals, the scale of the problem, the stage of the invasion process, the availability of funds, social acceptability, the growth form of the target species, and the specific settings of the aquatic environment (e.g., bathymetry, water movement, water physicochemical parameters, and human use). There is a wide variety of available control tools that fit into five categories: (1) surveillance and prevention, (2) physical control that uses various machinery and manual techniques, (3) chemical control with herbicides, (4) biological control, and (5) habitat modification and restoration activities. None of these control tools is inherently better than others, as all have benefits and limitations in terms of direct and indirect costs, control efficacy, and situation-specific suitability. It is important to intelligently choose and integrate tools for situation-specific management goals.
This chapter provides an overview of the ecology of aquatic plants, discusses the benefits and limitations of various control tools, and lastly discusses how to apply these tools for the effective management of aquatic plants
Negative variance components in linear mixed models: applications in plant breeding programs
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Macadamia Crop Forecasting 2023 - 2025
No full textThe ‘Macadamia Crop Forecasting’ project delivered –
• a climate-adjusted macadamia crop forecast for the 2023, 2024 and 2025 seasons, and
• longer-term forecasts (out to 10 years) for the expected production of the Australian macadamia industry.
This information is important to inform processors and producers, and to assist in decision-making regarding industry logistics, export contracts, and future industry expansion. Each year, targeted data were successfully sourced and analysed to create the annual and long-term crop forecasts. The Australian Macadamia Society (AMS) collated historical production on a regional basis. The relevant meteorological variables were obtained from the Australian Bureau of Meteorology, and other important data (including price history and satellite imagery) were collated. Production patterns were fitted by cross-matching actual production for each region against tree numbers. These models form the basis of the expected production for the long-term forecasts. Adjustments for climate and other proven effects were then made for each year’s final forecast in February. These forecasts were developed using both ‘more traditional’ statistical models along with some of the more promising machine-learning algorithms. In parallel, an industry-wide survey of flower ratings was collated by the Macadamia Benchmarking Project team, to identify any potential problems. The results and crop forecasts were drawn together in a full report that was forwarded to Hort Innovation and AMS each year. This report constitutes the key outcome of this project. The project’s Reference Group, including key AMS and industry personnel, met annually.
Whilst past results have been quite acceptable, in the future forecasting accuracy could well be improved by adopting some of the more-promising developing methodologies
Eight novel diagnostic markers differentiate lineages of the highly invasive myrtle rust pathogen Austropuccinia psidii
Full text linkAustropuccinia psidii is the causal agent of myrtle rust in over 480 species within the family Myrtaceae. Lineages of A. psidii are structured by their hosts in the native range, and some have success in infecting newly encountered hosts. For example, the pandemic biotype has spread beyond South America, and proliferation of other lineages is an additional risk to biodiversity and industries. Efforts to manage A. psidii incursions, including lineage differentiation, relies on variable microsatellite markers. Testing these markers is time-consuming, complex, and requires reference material that is not always readily available. We designed a novel diagnostic approach targeting eight selectively chosen loci including the fungal mating-type HD (homeodomain) transcription factor locus. The HD locus (bW1/2-HD1 and bE1/2-HD2) is highly polymorphic, facilitating clear biological predictions about its inheritance from founding populations. To be considered as potentially derived from the same lineage, all four HD alleles must be identical. If all four HD alleles are identical six additional markers can further differentiate lineage identity. Our lineage diagnostics relies on PCR amplification of eight loci in different genotypes of A. psidii followed by amplicon sequencing using Oxford Nanopore Technologies (ONT) and comparative analysis. The lineage-specific assay was validated on four isolates with existing genomes, uncharacterized isolates, and directly from infected leaf material. We reconstructed alleles from amplicons and confirmed their sequence identity relative to their reference. Genealogies of alleles confirmed the variations at the loci among lineages/isolates. Our study establishes a robust diagnostic tool for differentiating known lineages of A. psidii based on biological predictions and available nucleotide sequences. This tool is suited to detecting the origin of new pathogen incursions
Extended grain filling has potential to improve yield in grain sorghum
No full textYield increase in sorghum has been achieved primarily by increasing grain number. Scope exists to increase yield by increasing grain size, however this has been limited by the negative correlation between grain size and grain number. Extending the duration of the grain filling period has potential to enable increased grain size without the trade-off with grain number. This study explored grain filling duration (GFD) in a diverse panel of 904 sorghum genotypes in three environments across two years. Significant variation in GFD observed, ranging from 400 to 680 degree-days, included entries with significantly longer GFD than current commercial hybrids. Longer GFD was shown to result in larger grain size. Additionally, only low associations between GFD and grain number per panicle, flowering time or plant height were observed, indicating that GFD could be manipulated without adverse penalty to these traits. A simulation study to estimate the benefit of an increased GFD across Australian sorghum growing environments over 60 years revealed positive impacts on yield when GFD was increased by either 10% or 20% in environments with low and mild post anthesis water stress but not in environments with sustained terminal water stress. However, maintaining overall crop duration by shortening time to flowering while extending GFD led to neutral or negative effects on yield. These results reveal opportunities to exploit GFD for improved genetic gains for yield in sorghum especially in environments or seasons where water does not become more limiting post anthesis
Climate-Induced Range Shift and Risk Assessment of Emerging Weeds in Queensland, Australia
No full textAnticipation and identification of new invasive alien species likely to establish, spread and be impactful in a landscape, especially in response to climate change, are consistently a top priority of natural resource managers. Using available global bioclimatic variables limiting plant distributions, we employed maximum entropy (MaxEnt) as a correlative species distribution model to predict the current and future (2041–2060 and 2061–2080) distribution for 54 emerging weed species of different growth forms for the State of Queensland, Australia. Overall, the model predictive performance was excellent, with area under the curve (AUC) and the true skill statistic (TSS) averaging 0.90 and 0.67, respectively. Based on distribution records, the emerging weed species sorted out along environmental (climatic) space—with trees and succulents, each at the two ends of the continuum, while grasses, herbs and shrubs were distributed between the two extremes. Temperature seasonality and minimum temperature of the coldest month were the main driver variables that accounted for differences in climatic preference among the focal species and/or plant growth forms. Range shifts were predicted for many species in response to climate change; overall, habitat range increase will occur more often than range contraction and especially more so in trees compared to all other plant growth forms. Range stability was least in succulent weeds. In general, under climate change, the majority of the invasion hotspot area was projected to remain geographically stable (76.95%). Far northern Queensland (especially the Gulf of Carpentaria and Cape York Peninsula areas) and the coastal communities along the eastern seaboards of the State are the hotspots for emerging invasive alien species to establish and expand/contract in response to climate change. Based on observed and potential ranges, as well as species response to climate change, we derived an index of risk and hence statewide prioritisation watch list for management and policy of the emerging weeds of Queensland
High prevalence of low-concentration antimicrobial residues in commercial fish: A public health concern in Bangladesh
No full textAntibiotics are widely used in commercial fish farms in Bangladesh for therapeutic and prophylactic purpose, raising concerns about antimicrobial resistance (AMR) and environmental contamination. This study used Thin Layer Chromatography to detect antimicrobial residues in four commercially available fish species- Tilapia (Oreochromis aureus), Stinging catfish (Heteropneustes fossilis), Climbing perch (Anabas testudineus), and Pabda (Ompok pabda)—with 100 samples per species. Ultra High-Performance Liquid Chromatography quantified residues in a subset of 25 samples per species. The prevalence of Ciprofloxacin, Oxytetracycline, and Chlortetracycline residues varied significantly among fish species, with the highest prevalence observed for Ciprofloxacin in Tilapia (42%), Oxytetracycline in Pabda (41%), and Chlortetracycline in Tilapia (49%). Additionally, the prevalence of Levofloxacin and Chlortetracycline differed by sampling location, with the highest levels found in Jhawtala market, 27.5% for Levofloxacin and 53.8% for Chlortetracycline. Furthermore, residue concentrations were highest for Enrofloxacin in Climbing perch (69.32 µg/Kg) and Oxytetracycline in Pabda (88.73 µg/Kg). The highest Hazard Quotient (HQ) was for Enrofloxacin in Climbing perch (0.480), followed by Pabda (0.460), Stinging catfish (0.420), and Tilapia (0.387). While the HQ values were below 1.0, indicating no immediate toxicological risk, residues raise public health concerns due to the chance of potential AMR development. Further research is needed on antimicrobial bioaccumulation, indirect exposure sources, environmental contamination, and antimicrobial resistance in aquaculture and wild fish
Large-scale and long-term wildlife research and monitoring using camera traps: a continental synthesis
No full textCamera traps are widely used in wildlife research and monitoring, so it is imperative to understand their strengths, limitations, and potential for increasing impact. We investigated a decade of use of wildlife cameras (2012–2022) with a case study on Australian terrestrial vertebrates using a multifaceted approach. We (i) synthesised information from a literature review; (ii) conducted an online questionnaire of 132 professionals; (iii) hosted an in-person workshop of 28 leading experts representing academia, non-governmental organisations (NGOs), and government; and (iv) mapped camera trap usage based on all sources. We predicted that the last decade would have shown: (i) exponentially increasing sampling effort, a continuation of camera usage trends up to 2012; (ii) analytics to have shifted from naive presence/absence and capture rates towards hierarchical modelling that accounts for imperfect detection, thereby improving the quality of outputs and inferences on occupancy, abundance, and density; and (iii) broader research scales in terms of multi-species, multi-site and multi-year studies. However, the results showed that the sampling effort has reached a plateau, with publication rates increasing only modestly. Users reported reaching a saturation point in terms of images that could be processed by humans and time for complex analyses and academic writing. There were strong taxonomic and geographic biases towards medium–large mammals (>500 g) in forests along Australia's southeastern coastlines, reflecting proximity to major cities. Regarding analytical choices, bias-prone indices still accounted for ~50% of outputs and this was consistent across user groups. Multi-species, multi-site and multiple-year studies were rare, largely driven by hesitancy around collaboration and data sharing. There is no widely used repository for wildlife camera images and the Atlas of Living Australia (ALA) is the dominant repository for sharing tabular occurrence records. However, the ALA is presence-only and thus is unsuitable for creating detection histories with absences, inhibiting hierarchical modelling. Workshop discussions identified a pressing need for collaboration to enhance the efficiency, quality and scale of research and management outcomes, leading to the proposal of a Wildlife Observatory of Australia (WildObs). To encourage data standards and sharing, WildObs should (i) promote a metadata collection app; (ii) create a tagged image repository to facilitate artificial intelligence/machine learning (AI/ML) computer vision research in this space; (iii) address the image identification bottleneck via the use of AI/ML-powered image-processing platforms; (iv) create data commons for detection histories that are suitable for hierarchical modelling; and (v) provide capacity building and tools for hierarchical modelling. Our review highlights that while Australia's investments in monitoring biodiversity with cameras position it to be a global leader in this context, realising that potential requires a paradigm shift towards best practices for collecting, curating, sharing and analysing ‘Big Data’. Our findings and framework have broad applicability outside Australia to enhance camera usage to meet conservation and management objectives ranging from local to global scales. This review articulates a country/continental observatory approach that is also suitable for international collaborative wildlife research networks
Yield and Fruit Weight of Six Strawberry Cultivars over Two Seasons in Subtropical Queensland, Australia
No full textResearch was conducted to examine the marketable yield and fruit weight of six strawberry cultivars (Fragaria × ananassa Duch. ‘Festival’, ‘Fortuna’, ‘Brilliance’, ‘Red Rhapsody’, ‘Sundrench’ and ‘Suzie’) over two years in subtropical Queensland, Australia. In the first year, the transplants were planted on 30 March, while in the second year, they were planted on 22 April. The average daily minimum temperature was 3 °C higher than the long-term average for the area from 1965 to 1990, while the average daily maximum temperature was 1 °C higher. Temperatures and solar radiation were similar in the two years of the study. In contrast, it was wetter in the second year (478 mm) than in the first year (332 mm). Average yield was lower in the second year (142 ± 10 g/plant) than in the first year (330 ± 9 g/plant) (p < 0.001), possibly due to a later planting. Higher rainfall in the second year may have also contributed to a higher incidence of rain damage and fruit rots. Yield was lower in ‘Sundrench’ (176 g/plant) than in the other cultivars (235 to 252 g/plant) (p = 0.003). Fruit weight was lower in the second year (18.2 g) than in the first year (23.8 g) (p < 0.001), and lower in ‘Festival’ and ‘Fortuna’ (18.2 and 19.4 g), intermediate in ‘Brilliance’, ‘Red Rhapsody’ and ‘Sundrench’ (21.0, 21.3 and 21.8 g) and higher in ‘Suzie’ (24.3 g) (p < 0.001). These results demonstrate that yield and fruit size vary in cultivars in Queensland. ‘Suzie’ had the largest fruit, favoring marketing. The low productivity of ‘Sundrench’ suggests that this cultivar is not commercially viable in Queensland. Yields are expected to decline in the future under global warming, in the absence of better-adapted cultivars and other mitigating strategies. Further evaluations of cultivars in Queensland are required under different growing practices, including earlier times of planting, higher plant densities, light shade and protected cropping