Fast‐tracking species at risk conservation: A framework for addressing recovery actions through multi‐agency collaboration

Abstract A major challenge in conservation biology is to prevent the loss of species and communities that are critical to biodiversity on Earth. One of the tools governing bodies have to ameliorate the loss of species is through Species at Risk legislation. The Canadian species at risk act ensures that a recovery strategy is implemented for species that are listed as endangered or at risk. However, enacting the recovery strategy hinges on independent participants that often operate at different scales (e.g. local, regional) and interests (management, academic, etc.) and potentially compete for projects and funding. Here we outline a conceptual framework for overcoming such challenges using the recovery strategy for the endangered queensnake ( Regina septemvittata ) as a case study. Our approach was to fold the recovery strategy under a single project. There were two parts to this approach. First, we formed a central coordination team that addressed knowledge gaps outlined by the recovery strategy and assigned research questions to either an ecological or genomics data stream depending on the type of data collection. The data streams were used to identify expertise required for data collection and analysis. Subsequently, participants were invited based on expertise and/or strong local presence of where queensnake historically is extant. The relationship among collaborators was guided by five key principles to ensure a respectful and effective communication and that training and data collections were standardized throughout the recovery project. Practical implication . Our work directly addresses previous concerns that approaches to recovery strategies often lack coordination among groups and negatively impact the manner in which critical data are collected. By developing a framework that seeks to harmonize the recovery efforts of queensnake in their Canadian range, we demonstrate how a complex network of multi‐jurisdictional and interdisciplinary groups can accelerate data collection to inform policy and management decision‐making. Our framework can easily be amended to species at risk in general by applying questions to data streams and coordinating collaboration through a central team.