MODELING THE CURRENT AND FUTURE DISTRIBUTIONS OF JUNIPERUS VIRGINIANA ACROSS THE CONTINENTAL UNITED STATES Rashmi P. Mohanty and Michael L. Treglia Department of Biological Science, University of Tulsa, Tulsa, OK 74104-9700 Introduction Model Evaluation We evaluated the current model using a threshold-independent metric, the Area Under the Receiver Operating Curve (AUC), which ranges 0.5-1 (higher is better). We defined areas suitable for J. virginina if they had probabilities equal to or greater than the minimum value for actual presence locations. Based on this result, we also calculated a threshold dependent metric of model fit, the True Skill Statistic (TSS), which ranges -1 to 1 (1 indicates perfect fit). Eastern Redcedar (Juniperus virginiana; Fig. 1) is native to North America, but rapidly encroaching on grassland ecosystems [1]. This poses a threat to associated biodiversity and degrades grazing lands. Furthermore, pollen of many Juniperus species is a potent allergen, and expanding ranges pose human health concerns. We are developing species distribution models (SDMs [2]) to identify areas that currently have suitable climate and soil characteristics, and may become suitable for J. virginiana by 2050. Results of this work may help identify areas most susceptible to woody encroachment of J. virginiana, allowing for early detection of, and response to future range expansions. Fig. 2. Examples of data sources used in development of distribution models for J. virginiana. Modeling Approach We used a machine learning method, Random Forests [5], to develop distribution models based on available locality records, soil data, and the current climate data. This algorithm normally requires verifiable absence data to accurately discern suitable and non-suitable areas. In lieu of long-term, verifiable absence data, we used pseudo-absences, sampled randomly from our study area, with the same spatial biases as the occurrence data. To avoid biases from a specific sets of pseudo-absences, we ran the model 10 times with different sets of pseudo-absences and averaged the results. We eliminated correlated climate and soil variables to allow a more clear interpretation of variables that may influence the distribution of J. virginiana, and we confirmed the correlations in the current climate data were consistent in future scenarios. After developing the model using current climate data, we used it to project suitable habitat for J. virginiana under future climate scenarios. Fig. 4. Receiver Operating Curve for the current distribution model of J. virginiana in the continental U.S. Results Fig. 1. Eastern Redcedar (Juniperus virginiana) (photograph taken by Dr. Estelle Levetin along the highway in Oklahoma). The projections of our model to future climate scenarios indicate the suitable area for J. virginiana will expand progressively with increasing carbon emissions (Fig. 3). The total amount of suitable area may increase from approximately 2.3 million km2 to as much as 3.5 million km2. Our model for the current distribution of J. virginiana fit the data well (AUC = 0.98; TSS = 0.6; Fig. 4). A Data Sources We developed the species distribution models using publically available data from various sources as follows. Distribution Records for J. virginiana (Fig. 2): From the Global Biodiversity Information Facility (GBIF); USGS-BISON Database; and the Missouri Botanical Garden herbarium; we used records ranging 1940-2010. Environmental Data: Climate: From WorldClim Global Climate Data – Monthly Min. & Max. Temperature and Precipitation (~5km Resolution) [3]. Current Climate: 50 Year Avg (1950-2000). Future Climate: Projected Avg for (2041-2060). High and Low Carbon Emissions Scenarios (RCP 26 & RCP 85) from the CNRM-CM5 Model. Soil: From the Land-Atmosphere Interaction Research Group at Beijing Normal University [4], derived from USDA-NRCS STATSGO Data (~5km Resolution). We used weighted averages for seven metrics of soil composition across 8 horizons (0 - 2.3m) Discussion Encroachment of Juniper spp. into grassland habitats is a widely recognized problem in the U.S. Our distribution models for J. virginiana are preliminary, but suggest this issue will be exacerbated by climate change. Next steps of this research will involve model validation, development of models for other Juniper species, and evaluation of potential loss of grassland area in our study region. B C References: Adams, R. P. 2014. Junipers of the World : The genus Juniperus, 4th ed. Trafford Publishing: Liberty Drive, Bloomington, Indiana. Franklin J. 2009. Mapping Species Distributions: Spatial Inference and Prediction. Cambridge University Press: Cambridge, UK. Hijmans, R. J.,et al. 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25:1965-1978. Shangguan, W., et al. 2014. A global soil data set for earth system modeling. Journal of Advances in Modeling Earth Systems 6:249-263. Breiman, L. 2001. Random forests. Machine learning, 45(1), 5-32. Acknowledgements: Computing for this project was performed at the High Performance Computing Center at Oklahoma State University. This work was supported by the Oklahoma NSF-EPSCoR program, award number IIA-1301789. Fig. 3. Modeled suitable area for J. virginiana in the continental U.S., based on soil and current climate characteristics (A), and projected climate scenarios with high (B) and low (C) carbon emissions scenarios.