Dispersal, the movement of individuals away from their natal location to another location, is a basic driver of ecological and evolutionary processes. Direct measures of marine fish larval dispersal have shown that individual dispersal distances can vary over several orders of magnitude within a species. We currently do not know the causes of this variation. One plausible explanation for the cause of intraspecific variation in individual dispersal distances is dispersal plasticity. Dispersal plasticity, especially as an adaptive parental effect where parents can alter the dispersal phenotype of their offspring in response to an environmental cue, is widespread in terrestrial systems, but has yet to be described in marine fishes. In this study, we address a key, although often untested, condition for the evolution of dispersal plasticity as an adaptive parental effect: whether parents have information that would enable them to reliably predict the environmental conditions that their offspring will encounter. Using a wild population of orange anemonefish, Amphiprion percula, we investigate habitat quality predictability by testing for spatial autocorrelation in three habitat quality indicators: anemone size, female size, and egg clutch size. We found strong, positive spatial autocorrelation for all three habitat quality indicators from 50 to about 500 meters. This suggests that selection might favor parents that increase allocation to offspring that stay within 500 m if they are in good habitat and increase allocation to offspring that travel farther than this if they are in poor habitat. Results from this study lay solid foundations for further investigation of dispersal plasticity in A. percula and other marine fishes, providing testable hypotheses for probable causes of individual dispersal distance variation. Incorporating dispersal plasticity in our investigations of marine fish larval dispersal potentially could contribute to a greater understanding of marine fish metapopulation dynamics, and therefore fisheries recovery and reserve management.