Spatio-temporal Exploration of Paleo Fire Climate Patterns Using the Superposed Epoch Analysis (S.E.A.) Capstone Project Proposal, PSU MGIS Author: Wendy Gross, Advisor: Dr. Alan Taylor

Conclusions and Anticipated Results Proposal Outline Background Goals and Objectives Proposed Methodology Project Timeline Conclusions and Anticipated Results 1

Paleoclimatology and Paleoclimate Proxies the study of climate prior to the widespread availability of instrumental climate records Paleoclimate Proxies: natural recorders of the environment used to yield quantitative reconstructions of past climate tree-rings are used as a proxy to study precipitation and temperature Background Goals and Objectives Proposed Methodology Project Timeline Conclusions and Anticipated Results Increment Borer Wide ring indicating Wet Year Narrow Ring indicating Dry Year Bark Fire Scar Dry Years Pith (Seedling) Core Extracted from a tree via an Increment Borer 2

The Palmer Drought Severity Index (PDSI) Has Been Reconstructed from Tree-ring Data (for 0 A.D. to 2000 A.D.) Background Goals and Objectives Proposed Methodology Project Timeline Conclusions and Anticipated Results Each 2.5x2.5 degree grid cell has a time series of PDSI values associated with it Palmer Drought Severity Index Values for 1851 3 Extremely Dry PDSI Neutral PDSI Extremely Wet PDSI

Paleoenvironmental Proxies Fire Scars in the annual growth rings of trees are a paleoenvironmental proxy that allows us to determine when a fire event happened – called the fire event year Paleoclimate proxies can be linked to paleoenvironmental proxies to gain an understanding as to how climate effects ecosystem processes Linking PDSI drought data to fire event years to gain an understanding of how drought affects fire , Background Goals and Objectives Proposed Methodology Project Timeline Conclusions and Anticipated Results Fire-scarred cross section from a ponderosa pine (photo © P.M.Brown) Fire-scar data sites (NOAA/Paleo) 4

Superposed Epoch Analysis (S.E.A.) Basic Definition and Inputs S.E.A. is a statistical technique that can be used to analyze the relationship between : proxy-base climatic phenomena (for example drought), and environmental events such as Fire Event Years Inputs to the S.E.A technique: A time series, and the start and end dates over which the analysis is to take place For this project - a PDSI time series for one grid cell (2) A list of event dates that are within the start and end dates of the time series used as input For this project - Fire Event Years derived from fire scar sites 5

The Superposed Epoch Analysis “Window” (“Epoch”) Background Goals and Objectives Proposed Methodology Conclusions Anticipated Results ( not to scale ) Yr -4 (lag -4) Yr -3 (lag -3) Yr- 2 (lag -2) Yr -1 (lag -1) Event Year (Year Zero) Yr 1 (lag 1) Yr 2 (lag 2) S.E.A. “Window” 6

Computations (Averaging) Performed by the S.E.A. Yr 2 (lag 2) Yr 1 (lag 1) Yr -1 (lag -1) Yr- 2 (lag -2) Yr -3 (lag -3) Yr -4 (lag -4) Event Year (Year Zero) S.E.A. “Windows” Avg Avg Avg Avg Avg Avg Avg Results Yr 2 (lag 2) Yr 1 (lag 1) Yr -1 (lag -1) Yr- 2 (lag -2) Yr -3 (lag -3) Yr -4 (lag -4) Event Year (Year Zero) Legend: PDSI Values 7 Extremely Dry PDSI Neutral PDSI Extremely Wet PDSI

Goals and Objectives Goals - enhance the understanding of: Background Goals and Objectives Proposed Methodology Project Timeline Conclusions and Anticipated Results Goals - enhance the understanding of: spatio-temporal variability in fire and climate interaction the mechanisms that drive fire and climate interaction Objectives - develop a web-mapping tool that provides a spatially explicit representation of the S.E.A. technique results. This will: help researchers to spatially resolve the temporal patterns of fire and climate they are identifying in their analysis allow researchers to relate the spatial inference to the spatial footprint of different climatic mechanisms 8

Work to Date – Pilot Project “Verification of Concept” Background Goals and Objectives Proposed Methodology Project Timeline Conclusions and Anticipated Results Pilot Project Goal: Verify that through a spatial representation of the S.E.A. technique results, I can reproduce published findings Research questions had to do with the relationship of fire event years to drought and El Niño-Southern Oscillation One of the primary questions addressed : “Scientific research has found that in times prior to anthropogenic influence in the Southwestern United States, there were wet years prior to Major Southwestern Fire Event Years, and dry conditions during the actual Fire Event Years.” * * Barton Et al, 2001; Grissino-Mayer, 2000; Swetnam and Betancourt, 1989 9

Pilot Project – Southwest Study Area Depicting the PDSI Grid Cells and Fire Scar Sites Background Goals and Objectives Proposed Methodology Project Timeline Conclusions and Anticipated Results 10

Southwest Fire Event Years Selected Pilot Project Southwest Fire Event Years Selected Background Goals and Objectives Proposed Methodology Conclusions and Anticipated Results Background Goals and Objectives Proposed Methodology Project Timeline Conclusions and Anticipated Results 1850 A total of 17 years were selected. Selected years are shown with yellow markers, and have at least 10% of trees scared. 11

Pilot Project - S.E.A. Results for Lags before/during/after Major Fire Events that Occurred in the Southwest Year -2 Year -1 Year Zero Year 1 Year 2 Extremely Dry PDSI | Extremely Wet PDSI Neutral PDSI from -0.5 to +0.5 PDSI SEA Results for Grid Cell 104 of Southwest Study Area Southwest Study Area Grid Cell 104 12

Methodologies for Enhancing Scientific Discovery Background Goals and Objectives Proposed Methodology Conclusions and Anticipated Results Background Goals and Objectives Proposed Methodology Project Timeline Conclusions and Anticipated Results Scientific discovery can be promoted by automation of computations, as well as interactive and dynamic visualization, and exploration of analysis results* • software web-mapping software tool proposed will perform : (1) automation of computations of the S.E.A. technique for every grid cell of the gridded dataset used as input (2) creation of a full complement of interactive, and dynamic maps, in addition to graphs that depict the patterns realized for every lag • significance of the results will be provided through graphical visualization of the certainty levels * Symanzik, 2007, Rubel, 2010 13

Potential Geospatial Information Systems and Technologies (GIST) Background Goals and Objectives Proposed Methodology Conclusions and Anticipated Results Background Goals and Objectives Proposed Methodology Project Timeline Conclusions and Anticipated Results Web-mapping: ESRI’s ArcGIS geospatial web services (server-side) ESRI’s ArcGIS Javascript Interface (client-side) Automation of the S.E.A. computations and Geoprocessing: PostreSQL/PostGIS RDBMS (server-side) PHP programming language (server-side) User Interface and Graphs: ExtJS Javascript Library, Sencha.com (client-side) 14

Project Timeline Pilot Project/Verificaiton of Concept (Term Project, MGIS/GEOG 586, Geospatial Analysis, and beyond …) Winter/Spring, 2010 and Winter, 2011 Project Proposal and Presentation Winter/Spring, 2011 Research and prototype of GIST tools for development of web-mapping tools Spring/Summer, 2011 Define use cases for web-mapping tool, and research geo-visualization techniques Develop Software tool, and finish MGIS coursework Summer /Fall/Winter, 2011-2012 Create presentation for professional conference Spring/Summer/Fall, 2012 Present software tool at professional conference Possibilities: American Association of Geographers Conference NYC, Feb, 2012 Tree-Ring Society Conference University of Arizona, Sep, 2011 Association of Fire Ecologist Intl. Conference Portland, Oregon, Dec, 2012 Publish report on software tool Winter/Spring, 2012 Background Goals and Objectives Proposed Methodology Project Timeline Conclusions and Anticipated Results * Note: Dates will be adjusted, based on the conference that I present at, and the status of software development. 15

Summary, Conclusions and Anticipated Results A spatial representation of Superposed Epoch Analysis results will help paleo fire researchers to spatially resolve the temporal patterns they are seeing. This will enhance researchers’ understanding of : spatial variability in fire climate interaction the climate mechanisms that drive fire climate interaction The proposed web-mapping tool will facilitate this spatial representation of the S.E.A. results, as well as enhance visualization and exploration of the results through: the spatial representation of the S.E.A. results for all grid cells of gridded datasets via the automation of computations and creation of interactive and dynamic maps and graphs for every lag interfacing with the FHEvent Software tool for assessment and visualization of confidence intervals Background Goals and Objectives Proposed Methodology Project Timeline Conclusions and Anticipated Results 16

Acknowledgements I am most grateful for the guidance and support of my Advisor: Professor Alan Taylor, PSU 17

Spatio-temporal Exploration of Paleo Fire Climate Patterns Using the Superposed Epoch Analysis (S.E.A.) Questions ? 18