| Changes in impacts of climate extremes: human systems and ecosystems J Handmer, Y Honda, ZW Kundzewicz, N Arnell, G Benito, J Hatfield, ... Managing the risks of extreme events and disasters to advance climate change …, 2012 | 402 | 2012 |
| How much do disasters cost? A comparison of disaster cost estimates in Australia M Ladds, A Keating, J Handmer, L Magee International Journal of Disaster Risk Reduction 21, 419-429, 2017 | 78 | 2017 |
| Super machine learning: improving accuracy and reducing variance of behaviour classification from accelerometry MA Ladds, AP Thompson, JP Kadar, D J Slip, D P Hocking, R G Harcourt Animal Biotelemetry 5, 1-9, 2017 | 62 | 2017 |
| Updating the costs of disasters in Australia J Handmer, M Ladds, L Magee Australian Journal of Emergency Management, The 33 (2), 40-46, 2018 | 45 | 2018 |
| Seeing it all: evaluating supervised machine learning methods for the classification of diverse otariid behaviours MA Ladds, AP Thompson, DJ Slip, DP Hocking, RG Harcourt PloS one 11 (12), e0166898, 2016 | 43 | 2016 |
| Chew, shake, and tear: Prey processing in Australian sea lions (Neophoca cinerea) DP Hocking, MA Ladds, DJ Slip, EMG Fitzgerald, AR Evans Marine Mammal Science 33 (2), 541-557, 2017 | 31 | 2017 |
| Locating the intangible: Integrating a sense of place into cost estimations of natural disasters L Magee, J Handmer, T Neale, M Ladds Geoforum 77, 61-72, 2016 | 29 | 2016 |
| Acoustic accelerometry reveals diel activity patterns in premigratory Port Jackson sharks J Kadar, M Ladds, J Mourier, J Day, C Brown Ecology and Evolution 9 (16), 8933-8944, 2019 | 28 | 2019 |
| Proxies of energy expenditure for marine mammals: an experimental test of “the time trap” MA Ladds, DAS Rosen, DJ Slip, RG Harcourt Scientific reports 7 (1), 11815, 2017 | 28 | 2017 |
| Using accelerometers to develop time-energy budgets of wild fur seals from captive surrogates MA Ladds, M Salton, DP Hocking, RR McIntosh, AP Thompson, DJ Slip, ... PeerJ 6, e5814, 2018 | 24 | 2018 |
| Creating functional groups of marine fish from categorical traits MA Ladds, N Sibanda, R Arnold, MR Dunn PeerJ 6, e5795, 2018 | 20 | 2018 |
| Government liabilities for disaster risk in industrialized countries: a case study of Australia S Hochrainer-Stigler, A Keating, J Handmer, M Ladds Environmental Hazards 17 (5), 418-435, 2018 | 20 | 2018 |
| Swimming metabolic rates vary by sex and development stage, but not by species, in three species of Australian otariid seals MA Ladds, DJ Slip, RG Harcourt Journal of Comparative Physiology B 187, 503-516, 2017 | 17 | 2017 |
| Intrinsic and extrinsic influences on standard metabolic rates of three species of Australian otariid MA Ladds, DJ Slip, RG Harcourt Conservation physiology 5 (1), cow074, 2017 | 17 | 2017 |
| Assessment of machine learning models to identify Port Jackson shark behaviours using tri-axial accelerometers JP Kadar, MA Ladds, J Day, B Lyall, C Brown Sensors 20 (24), 7096, 2020 | 14 | 2020 |
| How functionally diverse are fish in the deep? A comparison of fish communities in deep and shallow‐water systems VG Carrington, Y Papa, CM Beese, J Hall, R Covain, P Horn, MA Ladds, ... Diversity and Distributions 27 (7), 1208-1223, 2021 | 11 | 2021 |
| Relationship between morphometrics and trophic levels in deep-sea fishes MA Ladds, MH Pinkerton, E Jones, LM Durante, MR Dunn Marine Ecology Progress Series 637, 225-235, 2020 | 9 | 2020 |
| J Slip, D., P Hocking, D., & G Harcourt, R.(2017). Super machine learning: Improving accuracy and reducing variance of behaviour classification from accelerometry MA Ladds, AP Thompson, JP Kadar Animal Biotelemetry 5 (8), 0 | 9 | |
| A benchmark for computational analysis of animal behavior, using animal-borne tags B Hoffman, M Cusimano, V Baglione, D Canestrari, D Chevallier, ... arXiv preprint arXiv:2305.10740, 2023 | 5 | 2023 |
| Diving deep into trouble: the role of foraging strategy and morphology in adapting to a changing environment M Ladds, D Rosen, C Gerlinsky, D Slip, R Harcourt Conservation physiology 8 (1), coaa111, 2020 | 5 | 2020 |
