Research alignment in the U.S. national park system: Impact of transformative science policy on the supply and demand for scientific knowledge for protected area management.

The US National Park System encompasses 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 in the 2000's, the mission scope has since expanded to promote overarching science-based objectives. Yet despite this paradigm shift instituting "science for parks, parks for science", there is scant research exploring the impact of the National Park Science Policy on the provision of knowledge. We address this gap by developing a spatiotemporal framework for evaluating research alignment, here operationalized via quantifiable measures of supply and demand for scientific knowledge. Specifically, we apply a machine learning algorithm (Latent Dirichlet analysis) to a comprehensive park-specific text corpus (combining official needs statements -i.e. demand- and scientific research metadata -i.e. supply-) to define a joint topic space, which thereby facilitates quantifying the direction and degree of alignment at multiple levels. Results indicate an overall robust degree of research 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 misalignment in mandated research domains. 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.

Impacts of Fire on Butterfly Genetic Diversity and Connectivity.

How do novel fire regimes and a long history of fire suppression influence species genetic diversity? Genetic diversity provides the raw materials for sustaining viable populations and for allowing adaptation to novel environmental challenges, and at present, few studies address the genetic responses of animals to fire management. Here we study the genetic responses of 2 butterfly species to a landscape gradient of fire timing and severity in Yosemite National Park using a large set of genome-wide single nucleotide polymorphisms (SNPs). Butterflies are important bio-indicators of invertebrate diversity and play important roles in both bottom-up and top-down ecosystem processes, and typically increase in abundance following wildfires, due to an increase in abundance of flowering plants. However, it is not clear how genetic diversity and genetic connectivity of butterflies respond to landscape change following fire, and whether fire management has positive or negative effects. We found evidence to suggest that fire increases genetic diversity and reduces isolation in 2 butterfly species, but that aspects of the fire regime (severity, extent, timing, and frequency) differ in importance depending on the ecology of the specific species. This research is the first study to address fire management impacts on genetic diversity in invertebrates, and the results will allow fire managers to predict that fire reintroduction in protected areas will generally benefit butterfly populations.