; (B) improve the understanding of wildland fire through wildland fire research that can be applied by wildland fire management agencies; (C) develop technologies and other tools to understand, monitor, and predict wildland fire, including— (i) models to predict fire potential and the spread and behavior of wildland fire and smoke; (ii) models to predict how vegetation will respond to changes in the environment and wildland fire; (iii) the integration of technologies to predict the spread and behavior of wildland fire and smoke in as near-real-time as possible; and (iv) other innovations to be integrated into operational decision support systems relating to wildland fire; (D) develop technologies and other tools to safely support land treatments to reduce the severity of wildland fire; (E) leverage predictive capabilities to reduce the impact of smoke on communities and wildland firefighters; (F) improve the understanding of post-fire risk to the landscape, including flash flooding potential and watershed impacts; (G) test and operate models to support land management decision-making, including through— (i) operating models to support management of wildland fire and vegetation; (ii) the demonstration of integration technologies to support management of wildland fire in as near-real-time as possible; and (iii) the incorporation of decision science and social science that examines the perception and adoption of information related to wildland fire risk; (H) develop a career pathway training program with respect to carrying out wildland fire research; (I) develop data management protocols to allow for full and open exchange of data pursuant to the principles of findability, accessibility, interoperability, and reusability (commonly referred to as the FAIR principles ) and archive and access that data