Significant public funds are spent on projects designed to improve environmental quality. Design and implementation of these initiatives is contingent on knowledge generated from environmental research. Funding agencies have many demands for research dollars while having limited research budgets. A prioritisation process is required for efficient and effective allocation of research funds. A review of research prioritisation literature suggests that ad hoc approaches are often used for ex ante analyses examining the value of environmental research (e.g., Delphi techniques, information gaps from literature reviews). This paper characterises environmental research prioritisation in the form of an economic decision problem, formulated using expected value of information concepts. An implicitly Bayesian modelling approach is developed with research priorities being made based on estimates of expected value of partial perfect information (EVPPI). Considerations and challenges associated with empirical implementation of EVPPI are discussed and a hypothetical example is provided to illustrate use of this approach in informing environmental research funding decisions.