Ninth International Conference on Permafrost ... - IARC Research

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Modeling and Monitoring Ecosystem Performance of Boreal Forests in theYukon River BasinBruce K. WylieASRC Research and Technology Solutions, contractor to U.S. Geological Survey (USGS)Earth Resources Observation and Science (EROS) CenterLi ZhangSAIC, contractor to USGS EROSNorman BlissASRC Research and Technology Solutions, contractor to U.S. Geological Survey (USGS)Earth Resources Observation and Science (EROS) CenterLei JiASRC Research and Technology Solutions, contractor to U.S. Geological Survey (USGS)Earth Resources Observation and Science (EROS) CenterLarry TieszenU.S. Geological Survey, Earth Resources Observation and Science Center, Sioux Falls, South DakotaW.M. JollyU.S. Department of Agriculture Forest Service, Fire Sciences Laboratory, Missoula, MontanaIntroductionWe emphasize the ability to quantify ecosystem processes,not simply changes in land cover, across the entire period ofthe remote sensing archive (Wylie et al., in press). The methodbuilds upon remotely sensed measurements of vegetationgreenness for each growing season. However, a time seriesof greenness often reflects annual climate variations intemperature and precipitation. Our method seeks to removethe influence of climate so that changes in underlyingecological conditions are identified and quantified. Wedefine an “expected ecosystem performance” to representthe greenness response expected in a particular year giventhat year’s climate. We distinguish “performance anomalies”as cases where the ecosystem response is significantlydifferent from the expected ecosystem performance.Performance anomaly maps and anomaly trends providevaluable information on the ecosystem for land managersand policy makers at 1-km resolution. The results offer aprototype to assess the entire Yukon River Basin, a taskslated for completion with our Canadian counterparts for theentire archival period (1984 to current) at 1 km and at 250 m(2000 to current).MethodsA regression tree model was developed to predict growingseason Normalized Difference Vegetation Index (NDVI),or expected ecosystem performance, from nearly 14,000random pixels, which represents a range of annual climaticconditions and numerous site conditions. We used 1-kmAdvanced Very High Resolution Radiometer NDVI 7-daycomposites integrated from April through the first weekof October as a proxy for ecosystem performance. Usingspatial climatic data and site potential information, annualmaps of expected growing season NDVI from 1996 to 2004were constructed from this model.Site potential is the historical performance related toelevation, slope, aspect, soils, and other factors. Dry yearshave lower expected ecosystem performance, and wetyears have higher expected ecosystem performance. Areasthat do not perform within a normal range determined bythe regression tree model’s expected error were identifiedas ecosystem performance anomalies. These anomalies areareas that responded to climatic conditions differently fromareas with similar expected ecosystem performance.The anomalies were validated using Composite BurnIndex data from selected fires and Landsat spectral indicesacross a burned-to-unburned gradient. Linear time seriestrends in the performance anomaly were mapped based onthe significance and sign (positive or negative) of the slope.ResultsExpected ecosystem performanceRegression tree models predicted expected performancefrom site potential, climate data, and land cover (R 2 = 0.84)and showed little bias. Withheld test locations had similarmean standard error of regression values as those of themodel development dataset. Regression tree committeemodels were used, wherein each regression tree modelpossessed five different regression trees, each trying toimprove predictions made by the previous regression treemodel. This resulted in over 500 different piecewise multipleregressions being employed.Ecosystem performance anomalySignificant ecosystem performance anomalies weredetermined at 90% confidence intervals of the expectedecosystem performance model. Underperforming anomaliescorrelated with recent fires. Composite burn index (Eptinget al. 2005) from selected fires validated the ecosystemperformance results. Landsat spectral indices were also353
Ni n t h In t e r n at i o n a l Co n f e r e n c e o n Pe r m a f r o s tused to validate performance anomalies across a burnedto-unburnedgradient. We investigated trends in postfireperformance anomalies and found that ecosystemperformance in burned areas showed varying rates ofrecovery when compared to climatically-predicted expectedecosystem performance. This indicates that this approachidentifies and quantifies post-fire vegetation succession,although ground validation of vegetation and surface coverare needed for further interpretation.Areas with significant consistent performanceanomalies over multiple years are likely boreal forestsunder environmental stress. Frequency and trend maps ofperformance anomalies emphasize areas which perhapsexperience degrading permafrost, marked by dryness, insectinfestations, or disease.Areas with burn dates prior to the beginning of the studyoften exhibited positive trends during the study.ConclusionsOur approach uses climate data to account for interannualvariations in ecosystem performance. The ecosystemperformance anomalies reflect ecological changes that arecaused by factors other than climate or site potential. Theunderperforming areas documented in this study werestrongly associated with burn disturbances. Based on climate,portions of the study reveal that boreal forest performance isdeclining, and the trend appears more severe with time.AcknowledgmentsThe authors would like to thank Barry Baker of the NatureConservancy for providing domain cluster data (Saxon et al.2005) used to help map boreal forest site potential. Fundingwas provided by the USGS Earth Surface Dynamics andLand Remote Sensing programs, with work performedunder USGS contract numbers 08HQCN0007 (B.K. Wylie),03CRCN0001 (L. Zhang), and 08HQCN0007 (N. Bliss andL. Ji).ReferencesEpting, J., Verbyla, D. & Sorbel, B. 2005. Evaluation ofremotely sensed indices for assessing burn severity ininterior Alaska using Landsat TM and ETM+. RemoteSensing of Environment 96: 328-339.Saxon, E., Baker, B., Hargrove, W., Hoffman, F. & Zganjar,C. 2005. Mapping environments at risk under differentglobal climate change scenarios. Ecological Letters8: 53-60.Wylie, B.K., Zhang, L., Bliss, N., Ji, L., Tieszen, L. & Jolly,M. In press. Integrating modeling and remote sensingto identify ecosystem performance anomalies inthe boreal forest, Yukon River Basin, Alaska. Int. J.Digital Earth.354
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ContentsPreface ...................
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Mapping and Modeling the Distributi
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Satellite Observations of Frozen Gr
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xiiIce Wedge Thermal Regime in Nort
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xivPermafrost Response to Dynamics
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xvi
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NICOP SponsorsUniversitiesUniversit
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Deep Permafrost Studies at the Lupi
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Effect of Fire on Pond Dynamics in
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Cryological Status of Russian Soils
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Acoustical Surveys of Methane Plume
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Permafrost Delineation Near Fairban
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Preparatory Work for a Permanent Ge
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A Provisional Soil Map of the Trans
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Martian Permafrost Depths from Orbi
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Time Series Analyses of Active Micr
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Impact of Permafrost Degradation on
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DC Resistivity Soundings Across a P
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Modeling Thermal and Moisture Regim
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A Provisional Permafrost Map of the
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Alpine Permafrost Distribution at M
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Cryogenic Formations of the Caucasu
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Modeling Potential Climatic Change
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A Hypothesis: A Condition of Growth
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Modeled Continual Surface Water Sto
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Freeze/Thaw Properties of Tundra So
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Discontinuous Permafrost Distributi
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Thermal Regime Within an Arctic Was
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Seasonal and Interannual Variabilit
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Twelve-Year Thaw Progression Data f
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Continued Permafrost Warming in Nor
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Landsliding Following Forest Fire o
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A Permafrost Model Incorporating Dy
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Seasonal Sources of Soil Respiratio
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Greenland Permafrost Temperature Si
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The Importance of Snow Cover Evolut
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The Account of Long-Term Air Temper
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The Combined Isotopic Analysis of L
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Adaptating and Managing Nunavik’s
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Human Experience of Cryospheric Cha
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HiRISE Observations of Fractured Mo
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A Soil Freeze-Thaw Model Through th
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Mapping and Modeling the Distributi
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First Results of Ground Surface Tem
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Historical Changes in the Seasonall
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Rock Glaciers in the Kåfjord Area,
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Snowpack Evolution on Permafrost, N
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Climate Change in Permafrost Region
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Maximizing Construction Season in a
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Pleistocene Sand-Wedge, Composite-W
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