Research alignment in the U.S. National Park Service : Impact of transformative science policy on the supply of scientific knowledge for protected area management

The US National Park System includes 63 national parks encompassing diverse environmental and tourism management regimes, together governed by the 1916 Organic Act and its dual mandate of conservation and provision of public enjoyment. However, with the introduction of transformative science policy mandates concentrated around the year 2000 (e.g., National Parks Omnibus Management Act; Natural Resources Challenge), the mission scope has since expanded to promote overarching science-based objectives, thereby fostering knowledge generation critical to park management, as well as promoting the “pristine” territory for “wild science” – as protected areas represent valuable counterfactuals to anthropogenic biomes. To this end, individual US national parks formally explicate itemized “need statements” representing targeted calls for science-based problem solving. Yet despite the paradigm shift instituting “science for parks, parks for science”, there is scant research exploring the impact of science policy on research alignment (i.e., supply-demand) in national parks. We address this gap by leveraging the clearly delineated and well-ordered attributes of the US national parks to develop a spatiotemporal framework for evaluating knowledge alignment, here operationalized via quantifiable measures of supply and demand for scientific knowledge. More specifically, we apply a machine learning algorithm (Latent Dirichlet analysis) to a comprehensive park-specific text corpus (combining official needs statements and scientific research metadata) in order to define a joint topic space, which thereby facilitates quantifying the direction and degree of knowledge alignment at both the parks and systems levels. Additionally, we grouped topics into two categories — normative (overarching) and non-normative (idiosyncratic) — to facilitate assessing their differential response to the transformative science policy characterized as addressing normative issues such as air quality and wilderness. Results indicate an overall robust degree of knowledge alignment, with misaligned topics tending to be over-researched (as opposed to over-demanded), which may be favorable to many parks, but is inefficient from the park system perspective. Results further indicate that the transformative science policy exacerbated the over-supply of research in normative knowledge domains, manifesting in higher levels of misalignment. In light of these results, we argue for improved decision support mechanisms to achieve more timely alignment of research efforts towards distinctive park needs, thereby fostering convergent knowledge co-production and leveraging the full value of national parks as living laboratories