A5017566740- Species Distribution and Climate Change
- Wildlife Ecology and Conservation
- Data Analysis with R
- Physiological and biochemical adaptations
- scientometrics and bibliometrics research
- Metabolomics and Mass Spectrometry Studies
- Advanced Text Analysis Techniques
- Academic Writing and Publishing
- Recycled Aggregate Concrete Performance
- Ecology and Vegetation Dynamics Studies
- Primate Behavior and Ecology
- Meta-analysis and systematic reviews
- Zoonotic diseases and public health
- Environmental DNA in Biodiversity Studies
- Scientific Computing and Data Management
- Municipal Solid Waste Management
UNSW Sydney
2021-2024
Ecosystem Sciences
2022-2023
Environmental Earth Sciences
2022
Abstract Background Taxonomic bias is a known issue within the field of biology, causing scientific knowledge to be unevenly distributed across species. However, systematic quantification research interest that community has allocated individual species remains big data problem. Scalable approaches are needed integrate biodiversity sets and bibliometric methods large numbers The outputs these analyses important for identifying understudied directing future fill gaps. Findings In this study,...
Machine (especially deep) learning algorithms are changing the way wildlife imagery is processed. They dramatically speed up time to detect, count, and classify animals their behaviours. Yet, we currently have very few systematic literature surveys on its use in imagery. Through a survey (a ‘rapid’ review) bibliometric mapping, explored across: 1) species (vertebrates), 2) image types (e.g., camera traps, or drones), 3) study locations, 4) alternative machine algorithms, 5) outcomes...
In a growing digital landscape, enhancing the discoverability and resonance of scientific articles is essential. Here, we offer 10 recommendations to amplify studies in search engines databases. Particularly, argue that strategic use placement key terms title, abstract keyword sections can boost indexing appeal. By surveying 230 journals ecology evolutionary biology, found current author guidelines may unintentionally limit article findability. Our survey 5323 revealed authors frequently...
Abstract In a growing digital landscape, enhancing the discoverability and resonance of scientific articles is essential. Here, we offer ten recommendations to amplify studies in databases. Particularly, argue that strategic use placement key terms title, abstract, keyword sections can boost indexing appeal. By surveying 237 journals ecology evolutionary biology, found current author guidelines may unintentionally limit article discoverability. Our survey 5842 revealed authors frequently...
Taxonomic bias is a known issue within the field of biology, causing scientific knowledge to be unevenly distributed across species. However, systematic quantification research interest that community has allocated individual species remains big data problem. Scalable approaches are needed integrate biodiversity datasets and bibliometric methods large numbers The outputs these analyses important for identifying understudied directing future fill gaps.In this study, we used h-index quantity...
1. Machine (especially deep) learning algorithms are changing the way wildlife imagery is processed. They dramatically speed up time to detect, count classify animals and their behaviours. Yet, we currently lack a systematic literature survey on its use in imagery.2. Through (a ‘rapid’ review) bibliometric mapping, explored across: 1) species (vertebrates), 2) image types (e.g., camera traps, or drones), 3) study locations, 4) alternative machine algorithms, 5) outcomes recognition,...