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Commensal relationships between wild plants and their dispersers play a key ecological and evolutionary role in community structure and function. While non-human dispersers are often considered critical to plant recruitment, human dispersers have received much less attention, especially when it comes to non-domesticated plants. Australia, as a continent historically characterized by economies reliant on non-domesticated plants, is thus a key system for exploring the ecological role of people as seed dispersers in the absence of agriculture. Here, we utilize a controlled observation research design, employing ecological surveys and ethnographic observations to examine how seed dispersal and landscape burning by Martu Aboriginal people affects the distribution of three preferred plants and one (edible, but non-preferred) control species. Using an information theoretic approach, we find that the three preferred plants show evidence of human dispersal, with the strongest evidence supporting anthropogenic dispersal for the wild bush tomato, Solanum diversiflorum. Human dispersal of wild plants has received limited attention. Here, the authors combine ecological surveys and ethnographic observations to examine how Martu Aboriginal people's seed dispersal and landscape burning impact plant distribution. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) tools, notably ChatGPT, are increasingly recognised for their transformative potential in higher education. This study employs a detailed case study approach complemented by a survey, delving into ChatGPT's impact on pedagogical practices, student engagement, and academic performance. It involved 74 undergraduate and postgraduate students enrolled in data analytics courses in Australia. The quantitative analysis highlights ChatGPT's role in providing personalised and on-demand support, which is highly valued among users for its flexibility and responsiveness, meeting a critical demand in educational settings. Notably, the study identifies a medium effect size ( η 2 = 0.173 ) in perceived benefits, indicating that ChatGPT accounts for approximately 17.3% of the variance in improved academic outcomes. However, challenges such as ChatGPT's limited understanding of complex queries and the lack of human interactions are primary concerns, with a medium effect size ( η 2 = 0.289 ) suggesting significant areas for improvement. Furthermore, statistical analyses reveal a clear relationship between the frequency of ChatGPT usage and the perception of its benefits, underscoring the transformative potential for users who have integrated it into their academic practices. Despite these challenges, the differential impact on users versus non-users highlights the potential for ChatGPT to foster more engaging and effective educational practices. The findings advocate for targeted strategies to epitomise ChatGPT's integration into educational settings, emphasising the need for ongoing research and the development of comprehensive guidelines to navigate its complexities and maximise its educational benefits. [ABSTRACT FROM AUTHOR]

The transformation of cities into smarter and more efficient environments relies on proactive and timely detection and maintenance of city-wide infrastructure, including roadside infrastructure such as road signs and the cleaning of illegally dumped rubbish. Currently, these maintenance tasks rely predominantly on citizen reports or on-site checks by council staff. However, this approach has been shown to be time-consuming and highly costly, resulting in significant delays that negatively impact communities. This paper presents AIoT-CitySense, an AI and IoT-driven city-scale sensing framework, developed and piloted in collaboration with a local government in Australia. AIoT-CitySense has been designed to address the unique requirements of roadside infrastructure maintenance within the local government municipality. A tailored solution of AIoT-CitySense has been deployed on existing waste service trucks that cover a road network of approximately 100 kms in the municipality. Our analysis shows that proactive detection for roadside infrastructure maintenance using our solution reached an impressive 85%, surpassing the timeframes associated with manual reporting processes. AIoT-CitySense can potentially transform various domains, such as efficient detection of potholes and precise line marking for pedestrians. This paper exemplifies the power of leveraging city-wide data using AI and IoT technologies to drive tangible changes and improve the quality of city life. [ABSTRACT FROM AUTHOR]