Point-Quarter Method
(scroll down for Figure 2.6b)

Figure 2.6a. In this diagram, the circles represent trees, the dashed line represents a transect, the solid lines represent N-S and E-W axes for visually dividing the forest into four sections (NE, SE, SW, and NW), the black circles represent sampled trees, and the dotted lines represent distances to those trees. Under the point-quarter method, sampling points are chosen along transects (in this figure the transect is running due north, though the transect may be oriented in other directions). The area around each sampling point is divided into four sections (NE, SE, SW, and NW) by visually dividing along the N-S and E-W axes. It's often helpful to use short lengths of pvc or meter sticks crossing at the sampling point to aid in this visualization.

Within each section (such as NE), the nearest tree is sampled. In this diagram, the sampled trees are shown in black. Measurements that can be taken include species of tree, diameter of tree, damage category to canopy of tree, etc. If tree density is to be calculated, distance from the sampling point to the tree should also be measured. (For methods to calculate density, click here.)

Though this method was originally designed for sampling forest trees, it can also work for sign left by animals, such as rodent burrows or scat (if burrows or scat are common enough).

Figure 2.6b. This diagram is the same in that as in Figure 2.6a except that it also shows the sampling interval between two sampling points. When using this method, it's important to choose a sampling interval that's large enough so that the same tree is not measure twice in order to avoid repeat sampling (repeat sampling is explained at the bottom of the section on unbiased representative samples.)

For forest trees, an interesting variation on this method is to measure both the nearest canopy tree and the nearest sub-canopy tree within each of the four sections. This approach allows comparison of the canopy and the understory and can be used to determine whether species composition of the forest may shift in the future. Here is a data sheet for doing just that.

Additional information on the point-quarter method can be found here.

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