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Supplemental methods and results

Collaborative research prioritization (CRP) studies have become increasingly popular during the last decade. By bringing together a diverse group of stakeholders, and using a democratic process to create a list of research priorities, these methods purport to identify research topics that will better meet the needs of science users. Here, we review 41 CRP studies in the fields of ecology, biodiversity conservation and environmental science that collectively identify 2031 research priorities. We demonstrate that climate change, ecosystem services and protected areas are common terms found in the research priorities of many CRP studies, and that identified research priorities have become less unique over time. In addition, we show that there is a considerable variation in the size and composition of the groups involved in CRP studies, and that at least one aspect of the identified research priorities (lexical diversity) is related to the size of the CRP group. Although some CRP studies have been highly cited, the evidence that CRP studies have directly motivated research is weak, perhaps because most CRP studies have not directly involved organizations that fund science. We suggest that the most important impact of CRP studies may lie in their ability to connect individuals across sectors and help to build diverse communities of practice around important issues at the science–policy interface.

Ecopath with Ecosim has been extensively used to examine ecosystem attributes and the effects of management actions. One of the main limitations in using Ecopath to credibly guide management decisions lies in the quality and quantity of the data used. Linear Inverse Modelling treats the problem of ecosystem characterization in a rigorous mathematical way in which the foodweb is described as a (linear) function of the flows and model parameters are (inversely) derived from observed data. In this study, our thesis is that Linear Inverse Modelling can be used as a complement to Ecopath applications to evaluate our confidence in typically reported ecosystem characterizations. Based on a simplified version of a previously published foodweb topology (Hossain et al., 2012), we demonstrate that there is considerable uncertainty associated with the predicted energy flows within the ecosystem of Hamilton Harbour, Lake Ontario, Canada. Uncertainty related to external flows (e.g. respiratory and detrital flows) appears to be much higher than for internal flows associated with predator-prey relationships. Our Linear Inverse Modelling analysis reinforces earlier findings that most of the trophic flows are concentrated within the first two trophic levels, while mass fluxes at the higher trophic levels are significantly lower. The intermediate ecotrophic efficiency for zooplankton suggests that planktivorous fishes do not fully capitalize upon the available food in the system. Our model estimates that a substantial amount of the detrital material is being recycled by the microbial community within the system. Taken together with the significant detrital pool directly supporting zooplankton and oligochaetes/chironomids, this prediction is consistent with recent empirical evidence that particulate organic matter from various allochthonous or autochthonous origins constitute important components of the energy transferred to higher trophic levels. Overall, our Linear Inverse Modelling analysis offers meaningful insights that should contribute towards the development of a reliable ecosystem model for Hamilton Harbour.