|Sampling Sufficiency||2014/10/21 16:26|
|Sampling Sufficiency||2014/10/21 16:26|
Frequency is the percentage of possible plots within a sampled area occupied by a target species. It is insensitive to the size or number of individual plants. The vegetation attributes monitored with frequency methods include frequency, basal cover and general cover categories (including litter), and reproduction of key species (if seedling data are collected). Frequency is a very useful monitoring method but does not express species composition, only species presence. With this method you don't make species counts-you are only concerned with whether the target species is present or absent within each quadrat. Frequency is an index that integrates species’ density and spatial patterns.
There are three methods of collectiong frequency data and all three consist of observing quadrats along transects, with quadrats systematically located at specified intervals along each transect. These include pace, quadrat and nested frequency. The only differences in these techniques are the size and configuration of the quadrat frames and the layout of the transect.
This is important however because one of the greatest disadvantages of assessing vegetation with frequency is that it is completely depended on quadrat size. In response to this shortcoming, the Nested Frequency technique was developed. Unlike the other two frequency methods, the Nested Frequency method allows observers to collect data on two or more different sized plots at one time. With this method several different sized plots are placed inside each other from smallest to largest. Each time the quadrat frame is placed on the ground, the observer determines the smallest size plot each species occurs in and records the plot number for that quadrat on the a data sheet. Another difference in methods is that with Nested and Quadrat Frequency the transect is measured while with Pace Frequency the line is paced.
Frequency methods in general are applicable to a wide variety of vegetation types and for species of any growth form (grasses, forbs, and shrubs). It is particulary useful for monitoring rhizomatous grass species (since observers don't have to define a counting unit) and invasive species.
The Nested Frequency method is useful for sampling communities in which many species are being monitored because the use of one size plot is usually not adequate to collect frequency data on all the important species within a community. In other words, a plot size appropriate for one species may not be appropriate for another species. For measuring a single species it may be more efficient to use a single quadrat size designed specifically for the denisty and distribution of that species. However, a nested frequency design used for a single target species can be useful when dealing with a species that changes in frequency dramatically from year to year (i.e., annuals or short-lived perennials). Nested plots are also useful for measuring populations by stage class (i.e., seedlings vs adults). It is also a great approach when performing a pilot study to determine plot size.
There are a lot of advantages to frequency sampling. It is objective, repeatable, and simple to perform, mainly because there are only a minimum number of decisions the observer must make, such as identifying species and determining whether or not species are rooted within the quadrats. In addition, if the target species is easy to recognize, this method can be very rapid.
To determine change, the frequency of a species must generally be at least 20% and no greater than 80% and frequency comparisons must be made with quadrats of the same size and shape since frequency is highly influenced by quadrat size and shape. With Nested Frequency the influence of quadrat size in lessened with the use of the nested plot configuration which improves the chance of selecting a proper size plot for frequency sampling because frequency data can be collected in different-sized quadrats with the use of the nested frame. When a plant of a particular species occurs within a plot, it also occurs in all of the successively larger plots and therefore frequency of occurrence for various size plots can be analyzed even though frequency is recorded for only one size plot, eliminating problems with comparing frequency data from different plot sizes.
Frequency is also highly sensitive to changes resulting from seedling establishment (i.e., seedlings present one year may not be persistent the following year). This can be a problem if data is collected only every few years. To lessen the influence of seedling variation in the data, seedlings can be recorded separately. Similarly, frequency is also very sensitive to changes in pattern of distribution in the sampled area.
This method can be used on any species growth form and particularly useful on rhizomatous grasses since the observer doesn't have to define the counting unit (unlike the density measurements). In addition, unlike cover measurements which can change significantly throughout the growing season as plants grow and develop, frequency measurements are less affected by seasonal environmental factors, allowing for a longer sampling window.
Minimal training is usually required with this method since the observer is mainly focused on recording whether or not the target species occurs in the plot. However, the observer does have to be aware of boundary plants (i.e. when a species occurs partly in and partly out of the plot). Therefore it is important to establish boundary rules and apply them consistently between individual observers.
The disadvantage of this method however is that since frequency is a measure that is sensitive to spatial distribution and population density, it can be difficult to determine if changes are the result of spatial arrangement, density or both.
vegetation change. Northwest Science 60:279-286.
Quadrat and Pace Frequency methods can also be used.
It is recommended that if time and money are availabe, that frequency should not be the only data collected since additional information on ground cover, plant cover, and other vegetation data would contribute to a better understanding of overall community changes.
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