Forest Inventory Midterm

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Author:
rice2am
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264779
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Forest Inventory Midterm
Updated:
2014-03-03 01:00:36
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Forest Inventory
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inventorying forests bro
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  1. Why is forest inventory important?
    • managing habitat
    • maximizing profits
    • carbon trading
    • buying and selling land
  2. Levels of measurement in forest inventory
    • individual tree
    • plot
    • stand
    • forest
  3. plot
    small group of trees that are measured
  4. stand
    a group of individual trees that are more or less homogeneous
  5. forest
    group of stands that cover an area of interest
  6. accuracy
    difference between a measured value and a true value
  7. bias
    difference between the average of repeated measurements or estimates and the true value
  8. precision
    the variation in repeated measurements or estimates
  9. biased imprecise
  10. biased, precise result
  11. unbiased, imprecise result
  12. unbiased, precise result
  13. why measure stem diameter?
    • useful for predicting things that are hard to measure directly such as biomass
    • may reflect monetary value of tree
    • some species require certain tree sizes for habitat
    • often reflects the competitive position of a tree
  14. DBH
    Diameter at 4.5 ft above ground
  15. often used for DBH of small trees
    tree calipers, usually two measurements are made at right angles and the average is taken
  16. take diameter under bark to determine
    amount of mulch that can be produced
  17. why is measuring tree height important?
    • length of the stem is important for estimating the tree's weight and how much wood it contains
    • combined with age it is used to determine site productivity
    • height can tell you whether the tree is dominant or not
    • variations in height help determine the stand's structure (important for wildlife)
  18. Why dominant trees important
    • dominant are healthier and more valuable
    • often chop down not-dominant ones to release dominant trees
  19. two types of height measured
    • total height
    • merchantable height
  20. merchantable height
    height to a diameter limit or to where the stem becomes unusable due to defects or branching
  21. sawtimber diameter limit
    10 inches
  22. pulpwood diameter limit
    4 inches
  23. a log is ___ feet
    16
  24. direct measurement method
    measuring poles
  25. clinometer gives heights based on d =
    66'
  26. laser hypsometer
    • combines a clinometer with a laser rangefinder
    • allows for d to be found quickly and accurately
    • all calculations performed for you
  27. if the ground is sloped...
    calculate a new value for d
  28. advantages of geometric method
    • don't need to measure the distance to the tree
    • slope of the ground does not matter
    • equipment cost is very low
    • accuracy is about the same as trigonometric method
  29. geometric method disadvantages
    • takes practice
    • carrying around a big stick is a pain
  30. stem volume
    • volume of wood in a tree's stem
    • given in board feet
  31. board feet
    1 foot x 1 foot x 1 inch
  32. ___ board feet in a cubic foot
    12
  33. stem volume importance
    controls the amount of product that can be made from a tree
  34. methods of stem volume measurement
    • immersing the step in water and measuring the volume that comes out
    • taking photographs of the stem and calculating the volume photogrammetrically
    • profiling the stem using laser beams
  35. sectional volume estimates
    • volume estimates of a tree stem by estimating the volume of section of the stem and adding up the measurements
    • typically applied to trees that have been chopped down
    • used to create equations for predicting volume based on diameter and height measurements
    • sometimes used for finding volume of logs
  36. Volume functions
    • allow you to estimate volume based on easily obtained measurements
    • developed using regression
  37. regression
    • creating an equation for predicting one set of data based on another
    • use higher order equations that incorporate powers of the predictor variable to follow curved line
  38. multiple regression
    multiple predictor variables can be used (DBH, height, and volume)
  39. Types of volume equations
    • regular
    • local
    • taper-based
    • merchantable volume equations
  40. regular volume equations
    • based on DBH and height
    • assumes the stem is a cylander
  41. local volume equations
    • based on only DBH
    • find the height and DBH of a number of tree in area
    • use regression to develop an equation for predicting height based on DBH
    • substitute this equation into the regular volume equation
  42. taper based volume equations
    • based on two diameter measurements and height
    • attempts to adjust volume based on how quickly the stem tapers
    • gives good results in highly varied stands
  43. merchantable volume equations
    • based on DBH, height, and the smallest diameter that is merchantable
    • tell you the amount of volume in sections of a stem that is above a certain diameter limit
  44. Estimating biomass important
    • estimating how much carbon dioxide the trees are storing
    • determining how much pulp can be made from a tree
    • determining how much heat the tree could produce when burned
    • assessing the value of a tree for pulp or firewood
  45. tree parts contain about __ percent carbon
    50
  46. obtaining direct biomass is difficult because
    leaves, branches, and roots are hard to measure
  47. below ground biomass is __times the above ground biomass
    0.25
  48. Important stand properties
    • age
    • basal area
    • stocking density
    • mean diameter
    • quadratic mean diameter
    • dominant height
    • site productivity capacity
    • volume and biomass per acre
    • growth
  49. ways to determine stand age
    • planting date
    • date of disturbance
    • tree cores
  50. basal area
    • cross sectional area per acre or hectare
    • add up the cross sectional areas and divide by plot size
  51. point sampling___large trees and ___small trees
    • oversamples
    • undersamples
  52. point sampling
    use a basal area factor lens
  53. borderline trees point sampling
    • calculate the limit associated with the tree
    • then measure the distance from the plot center to the tree
    • if the distance is less than the tree, include the tree
  54. stocking density
    number of trees per unit area
  55. quadratic mean diameter
    mean diameter weighted by basal area so more emphasis is placed on larger trees
  56. dominant height
    • height of the tallest trees in a stand
    • closely reflects how productive the stand will be
  57. predominant height
    measure and average heights of the n tallest trees in a plot (20-50 stems/acre) 1-3 trees in .5 acre plot
  58. top height method
    measure and average the heights of the n trees with the largest DBH in a plot
  59. site index
    • how productive a site is
    • height at a particular base age
  60. current annual increment
    how much the volume or biomass is increasing each year
  61. mean annual increment
    at what rate has the volume or biomass increased since the tree came into being
  62. fixed plot estimating average volume or biomass per tree in plot.
    • Usually measure this of 1/3 of trees
    • multiply this value by the number of tree/acre or hectare
  63. random sampling
    plots placed randomly throughout the forest
  64. systematic sampling
    often done in forestry, all plots in a grid
  65. cluster sampling
    • used by USFS for the Forest Inventory and Analysis program
    • specialized math needed
  66. stratified random sampling
    forest divided into stands and the number of plots established is proportional to the area of the stand
  67. probability proportional to size
    • variable correlated to the one you are interested in predicting is measure for all possible plot locations
    • plots place randomly, but the probability of a location being selection is proportional to the variable that was measure
    • increases accuracy
  68. most common statistics for a forest inventory
    • estimated means of the variable of interest
    • 95 percent confidence intervals for the means

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