@article{maudlin_mcneal_dinon-aldridge_davis_boyles_atkins_2020, title={Website Usability Differences between Males and Females: An Eye-Tracking Evaluation of a Climate Decision Support System}, volume={12}, ISSN={["1948-8335"]}, DOI={10.1175/WCAS-D-18-0127.1}, abstractNote={ABSTRACT}, number={1}, journal={WEATHER CLIMATE AND SOCIETY}, author={Maudlin, Lindsay C. and McNeal, Karen S. and Dinon-Aldridge, Heather and Davis, Corey and Boyles, Ryan and Atkins, Rachel M.}, year={2020}, month={Jan}, pages={183–192} }
 @article{duan_sun_mcnulty_caldwell_cohen_sun_aldridge_zhou_zhang_zhang_2017, title={Future shift of the relative roles of precipitation and temperature in controlling annual runoff in the conterminous United States}, volume={21}, number={11}, journal={Hydrology and Earth System Sciences}, author={Duan, K. and Sun, G. and McNulty, S. G. and Caldwell, P. V. and Cohen, E. C. and Sun, S. L. and Aldridge, H. D. and Zhou, D. C. and Zhang, L. X. and Zhang, Y.}, year={2017}, pages={5517–5529} }
 @article{thomas_brooks_jersild_ward_wynne_albaugh_dinon-aldridge_burkhart_domec_fox_et al._2017, title={Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments}, volume={14}, ISSN={["1726-4189"]}, DOI={10.5194/bg-14-3525-2017}, abstractNote={Abstract. Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6  ×  105 km2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.
                    }, number={14}, journal={BIOGEOSCIENCES}, author={Thomas, R. Quinn and Brooks, Evan B. and Jersild, Annika L. and Ward, Eric J. and Wynne, Randolph H. and Albaugh, Timothy J. and Dinon-Aldridge, Heather and Burkhart, Harold E. and Domec, Jean-Christophe and Fox, Thomas R. and et al.}, year={2017}, month={Jul}, pages={3525–3547} }
 @article{duan_sun_sun_caldwell_cohen_mcnulty_aldridge_zhang_2016, title={Divergence of ecosystem services in US National Forests and Grasslands under a changing climate}, volume={6}, ISSN={["2045-2322"]}, DOI={10.1038/srep24441}, abstractNote={Abstract}, journal={SCIENTIFIC REPORTS}, author={Duan, Kai and Sun, Ge and Sun, Shanlei and Caldwell, Peter V. and Cohen, Erika C. and McNulty, Steven G. and Aldridge, Heather D. and Zhang, Yang}, year={2016}, month={Apr} }
 @article{templeton_shane perkins_aldridge_bridges_lassiter_2014, title={Usefulness and uses of climate forecasts for agricultural extension in South Carolina, USA}, volume={14}, ISSN={["1436-378X"]}, DOI={10.1007/s10113-013-0522-7}, number={2}, journal={REGIONAL ENVIRONMENTAL CHANGE}, author={Templeton, Scott R. and Shane Perkins, M. and Aldridge, Heather Dinon and Bridges, William C., Jr. and Lassiter, Bridget Robinson}, year={2014}, month={Apr}, pages={645–655} }