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Multiscale Climatic, Topographic, and Biotic Controls of Tree Invasion in a Sub-Alpine Parkland Landscape, Jefferson Park, Oregon Cascades, USA Harold S.J. Zald, Oregon State University MTNCLIM 2010 | 06.09.2010 HJA | Blue River | OR .
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Multiscale Climatic, Topographic, and Biotic Controls of Tree Invasion in a Sub-Alpine Parkland Landscape, Jefferson Park, Oregon Cascades, USA Harold S.J. Zald, Oregon State University MTNCLIM 2010 | 06.09.2010 HJA | Blue River | OR
Why Study Tree Invasion in Mountain Ecotones? • Globally, treeline positions related to thermal conditions • Treeline movement a highly variable response to climate • across multiple climate regions, species, & land use histories • Treeline movement and meadow encroachment may influence: ecosystem productivity, carbon balance, energy budget, hydrological processes, species distributions, and biodiversity Harsch et al. (2009) Ecology Letters
Multiscale Drivers of Tree Invasion • Tree invasion fundamentally driven by regeneration processes • Not just climate! • Biophysical controls: topography, soils, disturbance, seed sources, facilitation, competition, etc. • Biophysical factors can control spatial patterns & sensitivity to climate Edaphic “Triple Treeline” Banff National Park, Canada Gentle Elevation Gradient Treeline Denali National Park, Alaska Multiple Gradient Subalpine Parkland Mount Hood, Oregon
Spatial Autocorrelation of Biophysical Controls • Traditionally, observations of treeline movement & • meadow invasion along transects with limited environmental gradients • Biophysical variables • spatially autocorrelated • Difficult to untangledrivers Modified from Brooke et al. 1970
0 50 100 m Applying New Technologies to Old Questions • Light Detection and Ranging (LiDAR) • Landscape characterization of fine-scale vegetation structure & topography • LiDAR can be used to sample across multiple biophysical gradients at scales compatible regeneration processes
Research Questions • How have climatic and • biophysical factors • controlled recent • rates & spatial patterns • of tree invasion? • Background: • PNW tree invasion driven by • snow depth and persistence, believed to determine growing season length • (Franklin et al. 1971, Woodward et al. 1995, Rochefort & Peterson 1996)
Study Area: Jefferson Park, OR • Mount Jefferson Wilderness • Willamette NF • Elevation: 1755-1840 m • ~130 ha • Tree islands of mountain hemlock & Pacific silver fir • Geomorphology: glacial & • neoglacial debris flows • No known fires • Unknown grazing history Jefferson Park HJA
LiDAR Derived Biophysical Variables Bio Overstory canopy Influences snow depth & persistence, seed sources Physical Topographic position, elevation, radiation Influence snow depth & persistence Landform (glacial v. debris flows) Disturbance, but also influences other biophysical variables
LiDAR Driven Sampling Sample along biophysical gradients believed to influence snow depth & persistence 100 x 100 m cluster Topography (5 Classes) Distance to overstory canopy (5 classes) Combine grids (5 x 5 = 25 classes) 100 x 100 m moving window (20 clusters) Stratified random sample (25 points per cluster)
LiDAR Driven Sampling Continued • Mapping of overstory canopy by species • (potential seed sources) • Spatial autocorrelation between explanatory variables accounted for • Landscape-level estimates of invasion possible
Field Data • Points located with sub-meter GPS • 2 m diameter plots • 390 on glacial landform • 109 on debris flows • Snow depth survey July 29- Aug 1, • 2008 • All trees < 8m tall tallied by species • & height (1620 trees) • 505 trees aged
Flow of Results • Spatial Patterns • Snow depth in relation to • biophysical controls • Tree abundance in relation to biophysical controls • Temporal Patterns • Tree invasion over time • Tree invasion and climate • Interactions of Climate & • Biophysical Controls
Mean: 0.67m 95%CI: 0.6-0.8m Glacial Landforms More snow in depressions, lower elevations, distance from overstory Nonlinear interactions between explanatory variables Mean: 0.2m 95% CI: 0.1-0.3m Debris Flows More snow with less radiation, lower elevation, distance More linear, reduced interactions, less variance described Results: Snow Depth & Biophysical Controls
Results: Multi-Scale Controls of Snow Landscape context is important • Larger landforms influence both overall snow depth and micro site controls of snow • Smoother surface • on debris flows • Greater wind • redistribution of snow on smoother debris flows
Results: Tree Abundance & Biophysical Controls • Mountain hemlock associated with microtopography and distance to overstory canopy • Silver fir strongly associated with distance to potential seed sources, followed by microtopography • Relationships between tree invasion and biophysical variables much stronger on glacial landforms • Glacial landforms Debris flow
Results: Temporal Patterns of Tree Invasion • Not just an increase in densities • 1950: 7.8% of meadow area with tree invasion • 2008: 34.7% of meadow area with tree invasion • Invasion dominated by Mountain hemlock, Pacific Silver Fir • restricted to under existing trees • Invasion rate • greater on • debris flows • (0.75% v. 0.57% Yr-1)
Results: Climate, Landforms, & Invasion Glacial Landforms Adj R2 = 0.2887 p ≤ 0.01 Debris Flows Adj R2 = -0.0356 p = 0.5 • Annual snowfall • most important, not temperature • On debris flows • tree invasion not associated with • annual snowfall • On debris flows, • positive association with spring snowfall!
Results: Climate, Microtopography, and Invasion • Only For Hemlock on Glacial • Landforms • Hemlock invasion largely in years with low snow on ridgetops & midslopes • During high snow years, less invasion overall & constrained to ridgetops
Conclusions • Snow and tree invasion associated with multi-scale landscape controls • Species matter • Landforms & topography alter both the spatial patterns of tree invasion & response to climate • Tree invasion on debris flow landforms • Scale & landscape context matter • Multiscale and context dependent responses pose problems for modeling future responses to climate at regional and global scales • Need for experimentation (future climate now)
Acknowledgements Funding provided by: USDA Forest Service, Pacific Northwest Research Station USDA Forest Service, Forest Inventory and Analysis Program The Native Plant Society of Oregon Hoener Memorial Fellowship, OSU Waring Travel Grant, OSU Thanks to field assistants: Dan Irvine Alex Gonsiewski