Monitoring, Modeling, and Projecting Global Dynamics in Alpine Treeline Ecotones under Climate Change - Student: Chenyang Wei

CHANGING CLIMATIC CONDITIONS OVER LAST CENTURY HAVE SIGNIFICANTLY AFFECTED GLOBAL BIOLOGICAL SYSTEMS ESPECIALLY IN HIGH-ELEVATION AREAS. AS A SENSITIVE MONITOR OF THE RECENT CLIMATE CHANGE TREELINES ARE EXPECTED TO BE DRIVEN UPSLOPE IN ALPINE REGIONS WORLDWIDE. THE SHIFT OF TREELINE HAS NEGATIVE IMPACTS ON ALPINE DIVERSITY AND HIGH-ALTITUDE ECOSYSTEM FUNCTION. MOREOVER THESE EFFECTS ARE VERY LIKELY TO CONTINUE TO INCREASE AS THE GLOBAL CLIMATE SYSTEM CONTINUES TO CHANGE IN THE FUTURE. WHILE A NUMBER OF STUDIES HAVE BEEN PERFORMED ON ALPINE TREELINES MOST WERE CARRIED OUT AT LOCAL TO REGIONAL SCALES AND ONLY A FEW EXPLICITLY TRACKED SHIFTS OVER TIME. THERE ARE CRITICALLY IMPORTANT QUESTIONS ABOUT THE SPATIOTEMPORAL DYNAMICS OF GLOBAL ALPINE TREELINES AND ITS CLIMATIC DRIVERS OVER THE PAST FEW DECADES. ACCORDINGLY THE OVERALL OBJECTIVES OF THIS STUDY ARE: 1) TO QUANTIFY THE SPATIOTEMPORAL DYNAMICS OF POSITION AND PRODUCTIVITY IN GLOBAL ALPINE TREELINE ECOTONES (ATES) OVER THE PAST FEW DECADES 2) TO DETERMINE THE MOST IMPORTANT ENVIRONMENTAL FACTORS ASSOCIATED WITH SHIFTING ALPINE TREELINES WORLDWIDE AND 3) TO PREDICT FUTURE VARIATION OF GLOBAL ALPINE TREELINES UNDER DIFFERENT SCENARIOS OF CLIMATE CHANGE. IN THIS STUDY WE PROPOSE TO ASSEMBLE HIGH RESOLUTION (30M) SATELLITE-DERIVED DATA ON VEGETATION DYNAMICS FOR THE WORLD'S MOUNTAIN RANGES TO STUDY THE SPATIOTEMPORAL VARIATION OF VEGETATIVE ACTIVITY NEAR GLOBAL ALTITUDINAL TREELINES FROM 1984 TO THE PRESENT. WE WILL USE THOSE PATTERNS IN COMBINATION WITH CLIMATIC VARIABILITY TO INFER THE IMPACT OF CLIMATE AND TOPOGRAPHIC FEATURES ASSOCIATED WITH ANY OBSERVED TREELINE DYNAMICS. FINALLY WE WILL USE MODELS FITTED OVER THE PAST FEW DECADES WITH CLIMATIC FACTORS FROM AN ENSEMBLE OF CMIP5 CLIMATE MODELS TO PROJECT THE SPATIOTEMPORAL DYNAMICS OF GLOBAL ALPINE TREELINE VEGETATION FROM THE PRESENT TO THE YEAR 2100. THE UNDERSTANDING OF GLOBAL TREELINE DYNAMICS UNDER CLIMATE CHANGE DURING THE RECENT DECADES WILL BE GREATLY ADVANCED THROUGH APPLYING NOVEL STATISTICAL THEORY TO THE ANALYSIS OF LARGE GRIDDED ENVIRONMENTAL DATASETS. THE PROPOSED RESEARCH WILL FILL KEY GAPS IN UNDERSTANDING HOW CLIMATE HAS AFFECTED TREELINE POSITION AND WILL USE HIERARCHICAL BAYESIAN STATISTICAL MODELS TO LINK PREDICTIONS OF HIGH-RESOLUTION VEGETATION DYNAMICS WITH A VARIETY OF CLIMATE SCENARIOS; THIS HAS NOT BEEN ACCOMPLISHED TO DATE AND REPRESENTS A SIGNIFICANT CHALLENGE FOR EARTH SYSTEM MODELING AND ECOLOGICAL FORECASTING RELATED TO CLIMATE CHANGE. THE CONCEPTS AND METHODOLOGIES WILL BE BROADLY APPLICABLE AND TRANSFERABLE TO UNDERSTANDING AND PREDICTING VEGETATION RESPONSES AND ASSOCIATED ECOLOGICAL EFFECTS IN OTHER SYSTEMS ELSEWHERE IN THE WORLD. PROJECT DATA AND MODEL PREDICTIONS WILL BE MADE FREELY AVAILABLE THROUGH AN INTERACTIVE WEB INTERFACE WITH PAST AND PREDICTED ALPINE TREELINE DYNAMICS WORLDWIDE