| Input selection and optimisation for monthly rainfall forecasting in Queensland, Australia, using artificial neural networks J Abbot, J Marohasy Atmospheric Research 138, 166-178, 2014 | 220 | 2014 |
| Application of artificial neural networks to rainfall forecasting in Queensland, Australia J Abbot, J Marohasy Advances in Atmospheric Sciences 29, 717-730, 2012 | 207 | 2012 |
| The design and interpretation of host-specificity tests for weed biological control with particular reference to insect behaviour J Marohasy Biocontrol News and Information 19, 13N-20N, 1998 | 207 | 1998 |
| Host shifts in biological weed control: real problems, semantic difficulties or poor science? J Marohasy International Journal of Pest Management 42 (2), 71-75, 1996 | 85 | 1996 |
| A taxonomic revision of Cryptostegia R. Br.(Asclepiadaceae: Periplocoideae) J Marohasy, PI Forster Australian Systematic Botany 4 (3), 571-577, 1991 | 58 | 1991 |
| Skilful rainfall forecasts from artificial neural networks with long duration series and single-month optimization J Abbot, J Marohasy Atmospheric Research 197, 289-299, 2017 | 36 | 2017 |
| The gall midges (Diptera: Cecidomyiidae) of Acacia spp. (Mimosaceae) in Kenya RJ Gagne, J Marohasy Insecta Mundi, 77-124, 1993 | 35 | 1993 |
| Prospects for the biological control of prickly acacia, Acacia nilotica (L.) Willd. ex Del.(Mimosaceae) in Australia J Marohasy Plant Protection Quarterly 10, 24-24, 1995 | 34 | 1995 |
| The application of machine learning for evaluating anthropogenic versus natural climate change J Abbot, J Marohasy GeoResJ 14, 36-46, 2017 | 30 | 2017 |
| A leaf feeding moth,Euclasta whalleyi [Lep.: Pyralidae] for the biological control ofCryptostegia grandiflora [Asclepiadaceae] in Queensland, Australia RE McFadyen, JJ Marohasy Entomophaga 35, 431-435, 1990 | 27 | 1990 |
| Myth and the Murray: measuring the real state of the river environment J Marohasy | 25 | 2003 |
| Acceptability and suitability of seven plant species for the mealybug Phenacoccus parvus J Marohasy Entomologia experimentalis et applicata 84 (3), 239-246, 1997 | 23 | 1997 |
| A survey of fireweed (Senecio madagascariensis Poir) and its natural enemies in Madagascar with a view to biological control in Australia. JJ Marohasy Plant Protection Quarterly 4 (4), 139-145, 1989 | 22 | 1989 |
| Application of artificial neural networks to forecasting monthly rainfall one year in advance for locations within the Murray Darling basin, Australia J Abbot, J Marohasy International Journal of Sustainable Development and Planning 12 (8), 1282-1298, 2017 | 18 | 2017 |
| The potential benefits of using artificial intelligence for monthly rainfall forecasting for the Bowen Basin, Queensland, Australia J Abbot, J Marohasy Water Resources Management VII 171, 287, 2013 | 18 | 2013 |
| Importation Protocols and Risk Assessment of Weed Biological Control Agents in Australia: The Example of Carmenta nr Ithacae T Withers, R McFadyen, J Marohasy Nontarget effects of biological control, 195-214, 1999 | 16 | 1999 |
| Assessing the quality of eight different maximum temperature time series as inputs when using artificial neural networks to forecast monthly rainfall at Cape Otway, Australia J Marohasy, J Abbot Atmospheric Research 166, 141-149, 2015 | 14 | 2015 |
| Using lagged and forecast climate indices with artificial intelligence to predict monthly rainfall in the Brisbane Catchment, Queensland, Australia J Abbot, J Marohasy International Journal of Sustainable Development and Planning 10 (1), 29-41, 2015 | 14 | 2015 |
| Has the herbicide diuron caused mangrove dieback? A re-examination of the evidence J Abbot, J Marohasy Human and Ecological Risk Assessment: An International Journal 17 (5), 1077-1094, 2011 | 14 | 2011 |
| Biology and host specificity ofWeiseana barkeri (Col.: Chrysomelidae): A biological control agent forAcacia nilotica (mimosaceae) J Marohasy Entomophaga 39, 335-340, 1994 | 14 | 1994 |
