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Abstract ContextThe > 25,000 km²Flint Hills ecoregion in eastern Kansas and northeastern Oklahoma, USA, is an economically and ecologically important area encompassing the largest remaining tallgrass prairie ecosystem in North America. Prescribed fires are used routinely to control invasive woody species and improve forage production for the beef-cattle industry. However, burning releases harmful pollutants that, at times, contribute to air quality problems for communities across a multi-state area. ObjectivesEstablish a modeling framework for synthesizing long-term ecological data in support of Flint Hills tallgrass prairie management goals for identifying how much, where, and when rangeland burning can be conducted to maximize ecological and economic benefits while minimizing regional air quality impacts. MethodsWe used EPA’s VELMA ecohydrology model to synthesize long-term experimental data at the 35 km²Konza Prairie Biological Station (KPBS) describing the effects of climate, fire, grazing, topography, and soil moisture and nutrient dynamics on tallgrass prairie productivity and fuel loads; and to spatially extrapolate that synthesis to estimate grassland productivity and fuel loads across the nearly 1000 times larger Flint Hills ecoregion to support prescribed burning smoke trajectory modeling using the State of Kansas implementation of the U.S. Forest Service BlueSky framework. ResultsVELMA provided a performance-tested synthesis of KPBS data from field observations and experiments, thereby establishing a tool for regionally simulating the combined effects of climate, fire, grazing, topography, soil moisture, and nutrients on tallgrass prairie productivity and fuel loads. VELMA’s extrapolation of that synthesis allowed difficult-to-quantify fuel loads to be mapped across the Flint Hills to support environmental decision making, such as forecasting when, where, and how prescribed burning will have the least impact on downwind population centers. ConclusionsOur regional spatial and temporal extrapolation of VELMA’s KPBS data synthesis posits that the effects of integrated ecohydrological processes operate similarly across tallgrass prairie spatial scales. Based on multi-scale performance tests of the VELMA-BlueSky toolset, our multi-institution team is confident that it can assist stakeholders and decision makers in realistically exploring tallgrass prairie management options for balancing air quality, tallgrass prairie sustainability, and associated economic benefits for the Flint Hills ecoregion and downwind communities. 

Abstract Local adaptation is a fundamental phenomenon in evolutionary biology, with relevance to formation of ecotypes, and ultimately new species, and application to restoration and species’ response to climate change. Reciprocal transplant gardens, a common garden in which ecotypes are planted among home and away habitats, are the gold standard to detect local adaptation in populations.This review focuses on reciprocal transplant gardens to detect local adaptation, especially in grassland species beginning with early seminal studies of grass ecotypes. Fast forward more than half a century, reciprocal gardens have moved into the genomic era, in which the genetic underpinnings of ecotypic variation can now be uncovered. Opportunities to combine genomic and reciprocal garden approaches offer great potential to shed light on genetic and environmental control of phenotypic variation. Our decadal study of adaptation in a dominant grass across the precipitation gradient of the US Great Plains combined genomic approaches and realistic community settings to shed light on controls over phenotype.Common gardens are not without limitations and challenges. A survey of recent studies indicated the modal study uses a tree species, three source sites and one growing site, focuses on one species growing in a monoculture, lasts 3 years, and does not use other experimental manipulations and rarely employs population genetic tools. Reciprocal transplant gardens are even more uncommon, accounting for only 39% of the studies in the literature survey with the rest occurring at a single common site. Reciprocal transplant gardens offer powerful windows into local adaptation when (a) placed across wide environmental gradients to encompass the species’ range; (b) conducted across timespans adequate for detecting responses; (c) employing selection studies among competing ecotypes in community settings and (d) combined with measurements of form and function which ultimately determine success in home and away environments.Synthesis. Reciprocal transplant gardens have been one of the foundations in evolutionary biology for the study of adaptation for the last century, and even longer in Europe. Moving forward, reciprocal gardens of foundational non‐model species, combined with genomic analyses and incorporation of biotic factors, have the potential to further revolutionize evolutionary biology. These field experiments will help to predict and model response to climate change and inform restoration practices.