Within-stand Interactions of Forest Structure and Microclimate Variability in an Old-Growth, Mixed-Conifer Forest Siyan Ma Co-authors: Malcolm North, Jiquan.

Slides:

Advertisements

Similar presentations

Brief Overview & Summary THE TEAKETTLE EXPERIMENT:

Advertisements

Community and landscape ecology of forest interiors at Merry Lea Aradhana J. Roberts and Jonathon Schramm Goshen College Abstract Introduction Materials.

SPATIAL HETEROGENEITY SUB-GROUP UPDATE THURSDAY 23 RD JANUARY 2014 YVETTE DICKINSON.

Overstory and understory vegetation management to meet fire resilience and wildlife habitat objectives Eric Knapp, Becky Estes, and Carl Skinner U.S. Forest.

Examining fire spread patterns across a managed forest-land mosaic in northern Wisconsin, USA using a modeling approach Jacob LaCroix, Daolan Zheng, Soung-Ryoul.

SENSITIVITY ANALYSIS of the FOREST VEGETATION SIMULATOR Southern Variant (FVS-Sn) Nathan D. Herring Dr. Philip J. Radtke Virginia Tech Department of Forestry.

The Effects of Site and Soil on Fertilizer Response of Coastal Douglas-fir K.M. Littke, R.B. Harrison, and D.G. Briggs University of Washington Coast Fertilization.

THE IMPACT OF LODGEPOLE PINE SIZE ON HEAT-FORMED TREE WELLS Created by Philip Neumann Winter Ecology, Spring ‘08 Mountain Research Station – University.

Chap 19. Horticultural Geography 1.Climate 2.Climatic Regions Tropical and Subtropical Dry Climate (Arid, Semi-Arid) Temperature Zone 4.Distribution of.

Soil CO 2 Efflux from a Subalpine Catchment Diego A. Riveros-Iregui 1, Brian L. McGlynn 1, Vincent J. Pacific 1, Howard E. Epstein 2, Daniel L. Welsch,

Carbon flux at the scale up field of GLBRC. The Eddy Covariance cluster towers Terenzio Zenone 1 Jiquan Chen 1 Burkhard Wilske 1 and Mike Deal 1 Kevin.

Estimating forest structure in wetlands using multitemporal SAR by Philip A. Townsend Neal Simpson ES 5053 Final Project.

Simulated harvesting scenarios in old-growth mixed southern beech (Nothofagus) forest determine composition and structure Jenny Hurst 1,3, Glenn Stewart.

Down-scaling climate data for microclimate models and forecasts Securing the Conservation of biodiversity across Administrative Levels and spatial, temporal.

Effects of Experimental Burning and Thinning on Soil Respiration and Belowground Characteristics Soung-Ryoul Ryu 1, Amy Concilio 1, Jiquan Chen 1, Deborah.

Urban-to-rural gradients % change from noisy to quiet sites % song overlap with traffic noise R 2 = 0.4 p = More abundant in.

How to tell the president the facts Haiganoush K. Preisler Pacific Southwest Research Station USDA Forest Service, Albany, CA 6 August, 2003 JSM – San.

“Near term response of surface soil nitrogen cycling and pools to forest clearing and burning” Heather E. Erickson Recent soils research from the Teakettle.

Impact of Sea Surface Temperature and Soil Moisture on Seasonal Rainfall Prediction over the Sahel Wassila M. Thiaw and Kingtse C. Mo Climate Prediction.

 Vegetation Density and Snow Accumulation Evan Esfahani Winter Ecology 2014 Mountain Research Station.

 Discuss silvicultural principles related to restoration/fuels treatments  Compare conditions from the 1900 Cheesman Lake reconstruction to current.

 Tropical montane cloud forests (TMCF) are unique ecosystems characterized by a highly variable weather conditions including strong.

Comparing Pre-settlement, Pre-treatment and Post-treatment Stand Structure at Lonetree Restoration Site: Incorporating GIS into Restoration By Christine.

Effects of Burning and Thinning Treatments on Sunfleck Duration and Below- canopy Reference Evapotranspiration in an Old-growth Mixed Conifer Forest Siyan.

Strategic sampling of microclimate, soil moisture and sapflux for improving ecohydrological model estimates in the California Sierra Kyongho Son and Christina.

Drivers of Global Wildfires — Statistical analyses Master Thesis Seminar, 2010 Hongxiao Jin Supervisor: Dr. Veiko Lehsten Division of Physical Geography.

Estimating wood growth across the Hubbard Brook valley: an analysis linking imaging spectroscopy and ecosystem model PnET Zaixing Zhou, Scott Ollinger,

ASSESSMENT OF ALBEDO CHANGES AND THEIR DRIVING FACTORS OVER THE QINGHAI-TIBETAN PLATEAU B. Zhang, L. Lei, Hao Zhang, L. Zhang and Z. Zen WE4.T Geology.

CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 1 The CSIRO Canopy Lidar Initiative, its ECHIDNA® and an EVI David LB Jupp 1, Darius Culvenor 2, Jenny.

Fire climate interactions on the American Pacific Coast ACRE workshop Meteoswiss, June Valérie Trouet A.H. Taylor, A.M. Carleton, C.N. Skinner.

__________. Introduction Importance – Wildlife Habitat – Nutrient Cycling – Long-Term Carbon Storage – Key Indicator for Biodiversity Minimum Stocking.

Effects of Experimental Burning and Thinning on Soil Respiration and Belowground Characteristics Soung-Ryoul Ryu 1, Amy Concilio 1, Jiquan Chen 1, Deborah.

Part I: Representation of the Effects of Sub- grid Scale Topography and Landuse on the Simulation of Surface Climate and Hydrology Part II: The Effects.

The climate and climate variability of the wind power resource in the Great Lakes region of the United States Sharon Zhong 1 *, Xiuping Li 1, Xindi Bian.

Methane Emission from Natural Wetlands in Northern Mid and High Latitudes since 1980s Xiaofeng Xu 1, Hanqin Tian 1, Vivienne Payne 2, Janusz Eluszkiewicz.

PARTITIONING ET INTO E AND T USING CHAMBERS C. A. Garcia, D. I. Stannard, B. J. Andraski, M.J. Johnson.

ELECTRICAL RESISTIVITY SOUNDING TO STUDY WATER CONTENT DISTRIBUTION IN HETEROGENEOUS SOILS 1 University of Maryland, College Park MD; 2 BA/ANRI/EMSL, USDA-ARS,

Climate Sensitivity of Thinleaf Alder Growth in Interior Alaska: Implications for N-Fixation Inputs to River Floodplains Dana Nossov 1,2, Roger Ruess 1,

Eric A. Graham UCLA Department of Ecology and Evolutionary Biology Ecological Applications of CENS Technologies at the James Reserve Summer interns: Caitlin.

Geographic Template Environmental variables exhibit non- random patterns Patterns of spatial variation comprise the geographic template, forms the foundation.

Using Lidar to Identify and Measure Forest Gaps on the William B. Bankhead National Forest, Alabama Jeffrey Stephens 1, Dr. Luben Dimov 1, Dr. Wubishet.

Vegetation Module Seth Bigelow, Michael Papaik, Malcolm North USFS Pacific Southwest Research Station.

Cases Studies: Importance of Scales in Ecological Investigations EEES 6760, University of Toledo January 28, 2009.

Flow prediction accuracy given DEM resolution  Model accuracy for snow-rain transition watersheds was more sensitive to DEM resolution than for snow-dominated.

The Effects of Spatial Patterns on Canopy Cover Estimated by FVS (Forest Vegetation Simulator) A Thesis Defense by Treg Christopher Committee Members:

Biotic and Abiotic Drivers of Seedling Survival in a Hurricane-Impacted Forest Liza S. Comita Columbia University.

Influences of Changing Disturbance Regimes on Forest Structure in Southern Appalachian Landscapes: John Waldron Charles Lafon, David Cairns, Robert Coulson,

Multiscale Climatic, Topographic, and Biotic Controls of Tree Invasion in a Sub-Alpine Parkland Landscape, Jefferson Park, Oregon Cascades, USA Harold.

Controls on Catchment-Scale Patterns of Phosphorous in Soil, Streambed Sediment, and Stream Water Marcel van der Perk, et al… Journal of Environmental.

Ecosystem Water Use: A Concept Linking Water and Carbon Fluxes Jiquan Chen Landscape Ecology & Ecosystem Science (LEES) Lab University of Toledo Feb. 21,

Uncertainty analysis of carbon turnover time and sequestration potential in terrestrial ecosystems of the Conterminous USA Xuhui Zhou 1, Tao Zhou 1, Yiqi.

1 Xiaoyan Jiang, Guo-Yue Niu and Zong-Liang Yang The Jackson School of Geosciences The University of Texas at Austin 03/20/2007 Feedback between the atmosphere,

Mapping the Thermal Climate of the HJ Andrews Experimental Forest, Oregon Jonathan Smith Spatial Climate Analysis Service Oregon State University Corvallis,

TREE WELLS: COMPARISON OF CONIFEROUS AND DECIDUOUS TREES Magali Weissgerber, Winter Ecology, Spring 2015, CU Mountain research Station.

Black Cohosh Presence and Abundance Relative to Environmental Gradients Nicole Hupp- Regis University, Denver, Colorado Dr. Luben Dimov- Alabama A & M.

Van R. Kane University of Washington

Predicting species distributions for New England invasives

Results and discussion

Jili Qu Department of Environmental and Architectural College

Figure 1. Spatial distribution of pinyon-juniper and ponderosa pine forests is shown for the southwestern United States. Red dots indicate location of.

Species Diversity Comparison North and South Slopes

NASA Satellite Images for 2007

Species distribution modeling ideas

STEM Fair Graphs.

Hydrology of Walnut Gulch, Arizona

Average Distribution of Incoming Solar Radiation

1 GFDL-NOAA, 2 Princeton University, 3 BSC, 4 Cerfacs, 5 UCAR

Korea Ocean Research & Development Institute, Ansan, Republic of Korea

Investigating land-climate interactions across land cover types

by Sarah J. K. Frey, Adam S. Hadley, Sherri L

Presentation transcript:

Within-stand Interactions of Forest Structure and Microclimate Variability in an Old-Growth, Mixed-Conifer Forest Siyan Ma Co-authors: Malcolm North, Jiquan Chen, Stephen Mather, Martin Jurgensen, and Brian Oakley

A Heterogeneous, Old-Growth, Mixed-Conifer Forest CECO – C eanothus shrub (13.4%) CC – Closed Canopy (67.7%) OC – Open Canopy (4.7%)

Changes in Forest Structure before disturbancesAfter disturbances

Canopy cover Canopy cover influences within-stand microclimate variability.

Objectives examine heterogeneous forest and canopy structure in multiple demonstrating scales quantify spatial variability of microclimatic variables explore spatial distributions of microclimatic variables using empirical models

Teakettle Experimental Forest iriiri i = 1, 2, 3,…100 m Stem Map Microclimate Stations Hemispheric photos u PAR T a RH T sf T s15 M s G CR10 datalogger

Microclimate Variables Daily means of each microclimate station Seasonal variability Spatial variability ?

Spatial variability in a whole year Spatial variability - Coefficient of Variation (CV, %) Spatial variability – seasonal patterns

Histograms of CV Different ranges of CV indicate spatial variability of each variable. Most of variables have similar CV range. G has the greatest CV range.

iriiri i = 1, 2, 3,…100 m Forest Structure in different demonstrating scales

Forest structure is “Heterogeneous” within the area < 25 m radius. N = 18

Tree density, dbh, and basal area may determine canopy cover in Zeniths. Open canopy Average Closed canopy

The relationship between canopy cover and forest structure CanopyCover = TD TD BA DBH DBH DBH DBH DBH DBH 15 using stepwise regression.

From Stem Map to Canopy Map

Table Linear regression models for predicting microclimatic variables from topographic and forest- structure factors (EL – elevation, AS – aspect, and CC -canopy cover), using photosynthetically active radiation (PAR) and soil surface temperature (T sf ) in May and August, and soil moisture (M s ) in June, 1999 and July, 2000 as examples.

Within-stand Spatial Distribution

Conclusions Microclimate spatial variability can be measured using CV. CVs have seasonal patterns. Most of variables have similar spatial variability except soil heat flux (G). Forest structure is “Heterogeneous” within the area < 25 m radius. Spatial canopy distribution is related to forest structure. Microclimate spatial distribution is predicable using the relationship between microclimatic variables and canopy distribution, topographic factors, and other microclimatic variables.

Acknowledgements Nathan Williamson Rhonda Roberts Eric Huber Teakettle mapping Technicians (1999 ~ 2002) The University of Toledo USDA FS Pacific Southwest Research Station USDA FS Southern Research Station Michigan Technological University

Thanks for coming. Questions ?