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Variables Affecting Tree Well Formation. http://www.steamboattoday.com/news/2008/jan/17/hidden_dangers/. Christopher White EBIO 4100 – Winter Ecology Spring 2012. Tree Well Formation.
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Variables Affecting Tree Well Formation http://www.steamboattoday.com/news/2008/jan/17/hidden_dangers/ Christopher White EBIO 4100 – Winter Ecology Spring 2012
Tree Well Formation • The tree wells that form at the bases of trees in the winter are a result of radiative balance within the tree. • As the tree absorbs short wave radiation from the sun, it then emits long wave radiation to preserve this radiative balance. • This long wave radiation melts the snow at the base of the tree, creating a depression in the surrounding snow. http://www.skimaven.com/post/single-chair-rides-and-powder-turns-at-vermonts-mad-river-glen/
Tree Wells, Who Cares? • These tree wells create lots of variation in snow depth within a region: - Can affect which animals, plants, and microbes are present - A dense forest can collectively alter the snowpack surrounding the trees • Recreational Accidents: - Many people die each year by falling into tree wells - Tree wells can be deceivingly large, and if a skier or a snowboarder falls into them, it can be an extremely dangerous situation For safety information: http://www.treewelldeepsnowsafety.com/index.php http://www.skiwhitewater.com/store/images/treewell.jpg
Question • What are the relationships between DBH, tree height, surrounding tree density, and tree species on the size of tree wells? Which are most important, and which have no significance?
Hypotheses • DBH: The wider the tree, the larger the well • Tree Height: The taller the tree, the larger the well • Surrounding Tree Density: The denser the transect, the smaller the wells • Species: The darker the bark, the larger the wells (proportional to size)
Previous Studies • Lot’s on tree well influence, not much on formation: • “The net effect of forest canopies is a snowpack with spatially heterogeneous depth and snow water equivalence (SWE)” • “In Northern Vermont, Hardy and Albert [1995] measured approximately one third less snow at the time of peak SWE beneath the canopy as found in the open. In the boreal forest, Pomeroy and Schmidt [1993] observed snow beneath jack pine canopy equal to 55% of the undisturbed snow, while in Alaska’s taiga, Sturm [1993] found snow depths at the tree trunks equal to approximately 20% of the undisturbed snow.”
Methods • Identify the tree species • Measure: • Tree Well Radius and Depth • DBH • Tree Height • Measure 25 m2 transect (5x5) – count trees to determine density http://media.lonelyplanet.com/lpi/15169/15169-3/681x454.jpg
DBH Significant Relationship!
Tree Height NO Significant Relationship!
Surrounding Tree Density Significant Relationship!
Tree Species Ratios (Volume/DBH): Lodgepole Pine: 1457.46 Subalpine Fir: 1235.65 Aspen: 184.62
Discussion • DBH: Significant Relationship (Confirms Hypothesis) – Why? - The wider the tree, the more surface area exposed to the sun, the more short wave radiation, the more long wave radiation emitted • Tree Height: Not Significant (Rejects Hypothesis) – Why? - Radiation received at the top of the tree does not have a large impact on radiation emission at the base of the tree. Other factors are inhibiting – tree bark heat transmission.
Discussion • Surrounding Tree Density: Significant relationship (Confirms Hypothesis) – Why? - Competition for light in dense areas of the forest limit the amount of short wave radiation exposure – as a result, tree wells are generally smaller • Tree Species - ????????
Tree Species Lodgepole Pine Aspen Subalpine Fir Due to lack of proper equipment (radiometer to actually measure longwave radiation coming from the tree), I’m going to make the assumption that Lodgepole Pine has the largest tree wells (proportional to DBH) due to its darker bark color in comparison with Subalpine Fir and Aspen. A darker bark color will absorb more solar energy, and as a result, the tree will emit more long wave energy, melting more snow and creating larger tree wells.
Sources of Error • First day of data collection followed precipitation event – may have filled tree wells • Assumed perfectly geometric shapes (when calculating volume of the tree well) • Tree selection wasn’t exactly “random” – looked for trees with prominent/measurable tree wells (lots were filled in with snow)
Future Experiments • Microbial respiration rates vs. tree well depth • Animal activity around tree wells • Use a radiometer to actually measure longwave emissions http://www.erdc.usace.army.mil/pls/erdcpub/docs/erdc/images/Measuring_spatial_variability_of_longwave_radiation.jpg
References • Hardy, J.P., 1998. Snow Ablation Modeling in a Mature Aspen Stand of the Boreal Forest. Hydrologic Processes 12, 1763- 1778 • Hardy, J.P., 2004. Solar Radiation Transmission Through Conifers Canopies. Agricultural and Forest Meterology 126. • Pomeroy, John. 2009. The Impact of Coniferous Forest Temperature on Incoming Longwave Radiation to Melting Snow. Hydrological Processes.