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Visual or Ocular Cover Estimates in Plots


contributed by Karen Colson and Jason Karl

Description and Uses

When collecting cover data in plots, Visual or Ocular Cover Estimates are a common approach. Visual plant cover estimates are very subjective but are often used because they are more rapid than other cover methods. Species and their covers are estimated visually as a percent of the area inside a plot. The cover can be defined as an independent percent or placed in a cover class. When using cover classes the observer puts the individual species in a pre-defined cover class, or percentage range, making estimating cover faster since the observer doesn’t need to decide if it is a few percentages more or less. Plots can be used to estimate canopy, foliar, or ground cover, however they don't work well for basal cover. Plot sizes vary, ranging from very small quadrats to belt transects, depending on the monitoring objectives and sample design. A variety of cover class systems have been developed and may vary by plot size or the amount of cover classes used.

The Daubenmire Method is commonly used. With this method canopy cover, frequency, and composition by canopy cover can be evaluated. It consists of systematically placing a 20- x 50-cm quadrat frame along a transect line, estimating the canopy coverage of each individual species within the quadrat, and placing each species in one of six cover classes (or ten classes when narrower and more numerous classes are preferred).

Advantages and Limitations

Visual or Ocular Cover Estimates in Plots are widely used because they are relatively simple and rapid to use. This method works better than other methods, such as point or line intercept, for locating and recording rare species or species with cover values less than 3%, since other methods might not capture species with such low cover values. However, visually estimating cover can be very subjective, increasing observer bias. Some techniques can decrease the amount of error, such as frames equiped with a known number of grids. Another limitation is that there can be large changes in canopy cover of herbaceous species between years because of climatic conditions, with no relationship to the effects of management. This annual variation can be a source of error in the results when using this method.

Manuals

Technical and Application References

  • Braun-Blanquet, J. 1965. Plant sociology: the study of plant communities. London: Hafner.
  • Daubenmire, R.F. 1959. A canopy-coverage method. Northwest Science 33: 43-64.
  • Dethier, M.N; Graham, E.S.; Cohen, S.; Tear, L.M. 1993. Visual versus random-point percent cover estimations: “objective” is not always better. Marine Ecology Progress Series 96: 93-100.
  • Hanley, T.A. 1978. A comparison of the line-interception and quadrat estimation methods of determining shrub canopy coverage. Journal of Range Management. 31:60-62
  • Jensen, M.E.; Hann, W.; Keane, R.E.; Caratti, J.; Bourgeron, P.S. 1994. ECODATA–A multire-source database and analysis system for ecosystem description and analysis. In Jensen, M.E.; Bourgeron, P.S.; eds. Eastside forest ecosystem health assessment, volume II: Ecosystem management: principles and applications. General Technical Report GTR-PNW-318. Portland, OR: U.S. Department of Agriculture, Forest Service: 203-216.

Similar Approaches

There are three main techniques for measuring cover: Ocular or Visual Estimates, Line-Point Intercept, or Line Intercept.

Line-Point Intercept is considered to be the least biased of all three. It is a rapid and accurate method for quantifying soil cover, which in addition to vegetation, includes cover by litter, rocks and biological soil crusts. Another similar method to line-point intercept is Step Point, which is more rapid because no tape is required, but also more subjective.

Line Intercept is separated into two main methods: Canopy Gap Intercept, which measures the proportion of a line covered by large gaps between plant canopies and is an important indicator of the potential for wind erosion and weed invasion and Basal Gap Intercept, which measures the proportion of the line covered by large gaps between plant bases and is important as an indicator of runoff and water erosion.

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