Environmental water managers must make best use of scarce environmental water allocations, and adaptive management is one means of improving the outcomes from a given volume of environmental water. We developed statistical models designed to inform adaptive management of the threatened Australian grayling (Prototroctes maraena) in the Thomson River, Victoria Australia. More specifically, the models assessed the importance of spring flows for facilitating recruitment of this diadromous species. However, grayling young of year are relatively rare and difficult to sample, which may limit the inferential power of statistical models. Therefore, we simultaneously applied the same statistical model to young of year of a more abundant diadromous species (tupong - Pseudaphritis urvilli), which is expected to respond to flow similarly to grayling. The grayling models were highly uncertain, providing no strong evidence of responses. Conversely, tupong responded strongly to spring flows, demonstrating the importance of such flows for recruitment. Our results suggest two, potentially complementary, approaches to adaptive management of Australian grayling. First, we could investigate whether refined monitoring approaches may improve sampling efficiency of young of year of this species. This may allow better direct elucidation of effects of spring flows on grayling recruitment. Second, we could further investigate the use of tupong as an indicator species, making the assumption that responses seen in this species are equivalent to unobserved, but real, responses in Australian grayling. The models developed in this paper are the type that can be used in an adaptive management cycle. They can be used to make predictions of environmental response to different management decisions; implementation of one or more management scenarios in conjunction with continued monitoring, allows adaptive learning. This could potentially allow managers to fine tune these flow events to maximize ecological response for the water delivered.