Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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Now showing 1 - 5 of 5
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    Bryde’s whale (Balaenoptera edeni) occurrence and foraging behaviour along the east coast of Australia
    (Taylor and Francis Group, 2024-10-09) Pirotta V; Cagnazzi D; Dixon B; Millar S; Millar J; Pickering G; Butcher PA; Stockin KA; Peters KJ
    Despite their global occurrence in warm-temperate waters and their suspected non-migratory lifestyle, Bryde’s whales (Balaenoptera edeni spp.) are considered the least-known large baleen whale species. In Australian waters, information on their distribution, ecology and behaviour is scarce. This study documents Bryde’s whale occurrence and foraging behaviours along the Australian East Coast using opportunistic citizen science sightings via drone aerial photography, vessel and land-based observations. We observed foraging in both shallow (seafloor visible, beach and breaking waves present) and deep waters. We observed a range of foraging behaviours including lunge feeding (exhibited by individual whales and in pairs), sub-surface and surface skim feeding (shallow waters only) and described multispecies associations. We describe a potentially novel feeding behaviour in shallow waters, where Bryde’s whales are feeding directly within or behind the surf break (shallow water surf feeding). We quantify the presence of mother-calf pairs in Australian waters, highlighting the use of these waters for potential calving. This study provides insights into Bryde’s whale occurrence and foraging behaviour in both shallow and deep waters of eastern Australia.
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    Introduced alien, range extension or just visiting? Combining citizen science observations and expert knowledge to classify range dynamics of marine fishes
    (1/07/2021) Middleton I; Aguirre JD; Trnski T; Francis M; Duffy C; Liggins L
    Aim: Despite the unprecedented rate of species redistribution during the Anthropocene, there are few monitoring programmes at the appropriate spatial and temporal scale to detect distributional change of marine species and to infer climate- versus human-mediated drivers of change. Here, we present an approach that combines citizen science with expert knowledge to classify out-of-range occurrences for marine fishes as potential range extensions or human-mediated dispersal events. Innovation: Our stepwise approach includes decision trees, scoring and matrices to classify citizen science observations of species occurrences and to provide a measure of confidence and validation using expert knowledge. Our method draws on peer-reviewed literature, knowledge of the species (e.g. contributing to its detectability, and potential to raft with, or foul, man-made structures or debris) and information obtained from citizen science observations (e.g. life stage, number of individuals). Using a case study of suspected out-of-range marine fishes in Aotearoa New Zealand, we demonstrate our approach to defining species’ ranges, assigning confidence to these definitions and considering the species detectability to overcome the data deficiencies that currently hinder monitoring the range dynamics of these species. Our classification of citizen science observations revealed that six of ten species had out-of-range occurrences; one of these was classified as an extralimital vagrant, four species had potentially extended their ranges and one species occurrence was likely due to human-mediated dispersal. Conclusion: The case study of marine fishes in New Zealand validates our approach combining citizen science observations with expert knowledge to infer species range dynamics in real time. Our stepwise approach helps to identify data deficiencies important in informing scientific inferences and management actions and can be refined to suit other data sources, taxonomic groups, geographic settings or extended with new steps and existing tools.
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    Using citizen data to understand earthquake impacts: Aotearoa New Zealand’s earthquake Felt Reports
    (Massey University, 2021-12) Goded T; Tan ML; Becker JS; Horspool N; Canessa S; Huso R; Jonathan H; Johnston D
    Aotearoa New Zealand's national seismic network, GeoNet, administers Felt Reports, including the Felt RAPID and Felt Detailed databases, which are being collected at present. NZ has a long tradition of using earthquake Felt Reports provided by the public to analyse the damage caused by moderate to large earthquakes. From traditional paper-based Felt Reports to current online reports (using the GeoNet website or a mobile app), researchers have been using such data to obtain a geographical distribution of the damage caused by an earthquake and to assess what actions people take during shaking. Felt Reports include questions on people's reactions, indoor and outdoor effects of earthquake shaking, building damage, and tsunami evacuation. The database of long online Felt Reports (Felt Classic between 2004 and 2016 and Felt Detailed from 2016 to the present) comprises over 930,000 reports from more than 30,000 earthquakes. Current research being carried out using this data includes: 1) updating of the NZ Ground Motion to Intensity Conversion Equation and Intensity Prediction Equation, 2) understanding human behaviour for earthquakes and related hazards such as tsunami, 3) developing a predictive model of human behaviour in earthquakes to estimate injuries and fatalities, and 4) improving public education. This paper summarises the history of NZ earthquake Felt Reports as well as the research currently being carried out using this data. Finally, we discuss how citizen science helps in the understanding of earthquake impacts and contributes to the aim of improving Aotearoa New Zealand's resilience to future events.
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    “Saving Precious Seconds”—A Novel Approach to Implementing a Low-Cost Earthquake Early Warning System with Node-Level Detection and Alert Generation
    (MDPI (Basel, Switzerland), 8/03/2022) Prasanna R; Chandrakumar C; Nandana R; Holden C; Punchihewa A; Becker JS; Jeong S; Liyanage N; Ravishan D; Sampath R; Tan ML
    This paper presents findings from ongoing research that explores the ability to use Micro-Electromechanical Systems (MEMS)-based technologies and various digital communication protocols for earthquake early warning (EEW). The paper proposes a step-by-step guide to developing a unique EEW network architecture driven by a Software-Defined Wide Area Network (SD-WAN)-based hole-punching technology consisting of MEMS-based, low-cost accelerometers hosted by the general public. In contrast with most centralised cloud-based approaches, a node-level decentralised data-processing is used to generate warnings with the support of a modified Propagation of Local Undamped Motion (PLUM)-based EEW algorithm. With several hypothetical earthquake scenarios, experiments were conducted to evaluate the system latencies of the proposed decentralised EEW architecture and its performance was compared with traditional centralised EEW architecture. The results from sixty simulations show that the SD-WAN-based hole-punching architecture supported by the Transmission Control Protocol (TCP) creates the optimum alerting conditions. Furthermore, the results provide clear evidence to show that the decentralised EEW system architecture can outperform the centralised EEW architecture and can save valuable seconds when generating EEW, leading to a longer warning time for the end-user. This paper contributes to the EEW literature by proposing a novel EEW network architecture.
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    Citizen science initiatives in high-impact weather and disaster risk reduction
    (Massey University, 20/12/2021) Vinnell LJ; Becker JS; Scolobig A; Johnston DM; Tan ML; McLaren L
    High-impact weather events cause considerable social and economic harm, with these effects likely to increase as climate change drives extremes and population growth leads to commensurate growth in exposure. As part of the World Meteorological Organization’s World Weather Research Programme, the 10-year High-Impact Weather (HIWeather) Project facilitates global cooperation and collaboration to improve weather prediction, forecasting, and warning. As part of this, the HIWeather Citizen Science Project identifies and promotes activities which involve citizens in the warning value chain, from “sensors” where they passively provide data, through to “collaborators” where they are involved in designing, running, interpreting, and applying the research. As well as benefitting global efforts to reduce societal impacts of weather and other natural hazards, citizen science also encourages hazard awareness and scientific literacy and interest. This editorial introduces the HIWeather Citizen Science Project special issue, summarizing the three papers in this issue in the broader context of high-impact weather and citizen science.