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M. Julian Caley

Researcher at Queensland University of Technology

Publications -  94
Citations -  5921

M. Julian Caley is an academic researcher from Queensland University of Technology. The author has contributed to research in topics: Coral reef & Population. The author has an hindex of 34, co-authored 94 publications receiving 5047 citations. Previous affiliations of M. Julian Caley include James Cook University & Australian Research Council.

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The relationship between local and regional diversity

TL;DR: In this article, the authors investigate the relationship between local and regional species richness in a broad array of taxa from around the world to address five questions: 1) is the relationship among local and local species richness linear, or does local richness accumulate more slowly at pro- gressively higher regional diversities, suggesting local saturation of species diversity? Sec- ond, do these relationships vary with locality size? Third, do taxa and continents differ in the form of relationships between local on regional diversity? Fourth, do relationships between global diversity depart from that expected from a null
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Global Patterns and Predictions of Seafloor Biomass Using Random Forests

TL;DR: This biomass census and associated maps are vital components of mechanistic deep-sea food web models and global carbon cycling, and as such provide fundamental information that can be incorporated into evidence-based management.
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Key Questions in Marine Megafauna Movement Ecology

Graeme C. Hays, +46 more
TL;DR: This exercise assembled 40 experts to identify key questions in this field, focussing on marine megafauna, which include a broad range of birds, mammals, reptiles, and fish, and shows that the questions have broad applicability to other taxa, including terrestrial animals, flying insects, and swimming invertebrates.
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Outstanding Challenges in the Transferability of Ecological Models.

Katherine L. Yates, +54 more
TL;DR: Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions.
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Species richness on coral reefs and the pursuit of convergent global estimates

TL;DR: The uncertainties revealed here should guide future research toward achieving convergence in global species richness estimates for coral reefs and other ecosystems via adaptive learning protocols whereby such estimates can be tested and improved, and their uncertainties reduced, as new knowledge is acquired.