1. Introduction to Vegetation Inventory, Assessment, and Monitoring
The purpose of this section is to explore steps in designing and conducting vegetation monitoring projects. Specific concepts and tools will complete the story in subsequent sections of this course.
2. Sampling Principles
This unit focuses on the principles of sampling: why we sample, the relationship between population parameters and sample statistics, accuracy and precision, types of error and their causes, and using confidence intervals to make inferences about populations. Very simply, we sample so that we can gather accurate and precise information about populations, and to make inferences about populations with confidence.
3. Sampling Design
This module focuses on the elements of sampling design. Sampling design encompasses all of the practical components of a sampling endeavor: where to sample, what to sample, and how to sample!
4. Monitoring Implementation, Data Quality, and Best Practices
Data management is fundamental to any type of data gathering activity. It is a process that includes many steps, each of which provide opportunities to introduce non-sampling errors related to human error. This module focuses on the best management practices that can be used to reduce or eliminate potential errors associated with data management.
5. Indicators, Methods, Descriptors, and Covariates
This section explores the distinctions between indicators and methods, introduces the concepts of site descriptors and covariates that are used to help classify and interpret monitoring data.
This module focuses on plant density: what it is, how it is measured, and how density data are used by land managers to inform resource management decisions. Very simply, density is defined as the number of individuals per unit area, and reflects the closeness of individuals.
This module focuses on plant frequency: what it is, how it is measured, and how frequency data are used by land managers to inform resource management decisions. Very simply, frequency measurements record the presence of species in quadrats or plots placed repeatedly across a stand of vegetation. Frequency reflects the probability of finding a species at any location in the vegetated area.
This module focuses on cover: what it is, how it is measured, and how cover data are used by land managers to inform resource management decisions.
9. Vegetation Height and Structure
This module focuses on vegetation structure: what structure represents, how it is measured, and how information about vegetation structure is used to inform resource management decisions. Very simply, vegetation structure refers to the three-dimensional arrangement of plants and plant materials on a site or across a landscape. Vegetation structure is primarily influenced by plant cover on horizontal and vertical planes.
10. Biomass and Production
This module focuses on plant biomass: what it is, how it is measured, and how biomass data are used by land managers to inform resource management decisions.
This module focuses on plant utilization: what it is, how it is measured, and how utilization data are used by land managers to inform resource management decisions.
12. Composition, Diversity, Similarity
This module focuses on plant community diversity: how it is described, how it is measured, and how diversity is interpreted by land managers to inform management decisions.
13. Remote Sensing for Vegetation Monitoring and Assessment
Remote sensing techniques offer many opportunities to inform, supplement, and sometimes replace traditional field-based aproaches to vegetation assessment and monitoring. This module explores ways in which remote sensing can be used in monitoring and provides example applications.
14. Assessment and Monitoring Programs
This module explores some established rangeland assessment and monitoring programs, describes their protocols, and discusses how the collected data are used in management decision making.
7.1: Frequency Overview
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Introduction to Frequency
The easiest and most objective measurement in vegetation sampling is to simply declare if a plant is present or not. Frequency is the number of times a plant species is present in a given number of uniformly-sized quadrats that are placed repeatedly across a vegetation stand. If you examine a group of plots in an area and you find at least one individual of a plant species in 75% of the plots, then the frequency for that species is 75%. Consequently, frequency reflects the probability of finding a species at any location within an area of interest.
For example, assume we placed 300 quadrats across a mixed-grass prairie site in Badlands National Park, South Dakota, and found needle-leaf sedge (Carex filifolia) in 45 of the quadrats. Frequency is calculated as the percent of plots with the species present divided by the total number of plots in the sample, so the frequency of this species would be 15% (C. filifolia present in 45 quadrats ÷ 300 quadrats examined = 0.15 or 15%).
We can conclude that needle-leaf sedge occurs on the site but it is not common.
Frequency is most often used to compare plant communities and to detect changes in vegetation composition over time. In this way frequency can be used to assess vegetation trend.
Frequency Depends on Plot Size
Since frequency measures of the proportion of quadrats in which a plant species is present relative to all quadrats examined, it makes sense that larger quadrats will produce larger frequency estimates. Suppose you examined a plant community to determine the abundance of black-eyed Susan (Rudbeckia hirsuta) using 10 quadrats that are 25 cm2 in size (Figure 2a). If you found that black-eyed Susan occurred in 1 of the 10 plots you examined, then the frequency of this plant is 10%. Now, suppose you repeat these measurements in the exact same locations, but use a larger, 1 m2 quadrat (Figure 2b). The black-eyed Susan now occurs in 3 of the 10 plots, resulting in a frequency of 30%. Thus the frequency estimate is greater even though the population did not change. Plants are simply more likely to occur in larger plots.
Figure 2. A smaller size of quadrat for a particular plant species or community may show a lower frequency (a) than a larger size quadrat for the same plant species or community (b).
Advantages of Assessing Frequency
Frequency is widely used among land management agencies such as the US Forest Service, Bureau of Land Management, and US Park Service to monitor changes in vegetation communities. From a monitoring perspective, frequency is often the measurement of choice, because it is:
- Highly repeatable. No counting or measuring is involved – the only decision to be made is whether a species occurs or does not occur in a plot. Minimal training for observers is required because of the simplicity of measurements.
- Fast and easy to measure. Frequency measurements do not require sophisticated equipment or extensive training on protocol.
- Relatively stable, and not sensitive to seasonal changes. The amount of plant cover and biomass typically varies throughout the growing season.
- Not necessary to distinguish individuals. This is especially convenient for clonal plants, sod-forming grasses, or plants that reproduce by rhizomes, stolons, or runners.
- A reliable indicator of population change due to invasions. Frequency is highly sensitive to changes resulting from establishment of seedlings and new individuals, so it can be an early indicator of population change or invasion by new species in a community.
- Sensitive to changes in plant communities that result from changes in density, plant dispersion, or both (Figure 3). This sensitivity makes frequency extremely valuable for monitoring and documenting changes in populations and communities. Since it is not possible to determine whether frequency changes reflect changes in density or dispersion without additional data, this feature is also considered a disadvantage!
Limitations of Assessing Frequency
There are several shortcomings to using frequency that must be considered when designing monitoring protocols.
- Frequency is highly sensitive to the size and shape of the quadrat used. First, it can be difficult to determine the most appropriate size and shape of quadrat to estimate frequency. Second, for populations that are exhibiting a large amount of change, the size and shape may need to be adjusted, and this can create difficulties.
- Comparisons can only be made if the quadrat size and shape are consistent between sampling periods.
- The “ideal” size and shape of quadrat may be different for different species. We usually address this issue by using nested quadrats or nested plots in order to ensure that the most appropriate plot size is being used.
- Frequency estimates are very sensitive to variation in seedling establishment. The presence and establishment of seedlings may be episodic or sporadic over time, and large fluctuations in frequency estimates for a species could simply reflect measurements that either “captured” or “missed” emergence and establishment events. This limitation can be avoided if the presence of seedlings and mature plants are recorded separately.
- Estimating frequency requires excellent plant identification skills. Experienced observers are needed or many hours must be initially spent to ensure good identification of plants.
- It is difficult to “visualize” frequency. Unlike other commonly measured attributes like cover, density, and biomass, frequency values are not absolute because measurements are linked inextricably to quadrat size.
- When frequency changes, it may be due to changes in a species’ spatial distribution or density, or both. Changes in frequency may be difficult to interpret because frequency measurements alone do not provide sufficient information to determine the reason for the change (Figure 3).
Figure 3. Examples “a” and “b” show different spatial distributions of the same density of plants, resulting in a 33% frequency for the patchy distribution of “a” and 89% frequency for the homogeneous distribution of “b”. In examples “c” and “d”, the same spatial distribution with different densities (15 plants and 40 plants, respectively) result in a frequency of 44% for the lower density “c” and 22% for the higher density “d”. Examples “e” and “f” have different densities (30 plants and 15 plants, respectively) and different spatial distributions, but have the same frequency (11%). Thus frequency is affected by density and spatial distribution, but it does not tell us anything about either the density or spatial distribution of plants without additional information.
Three Cautionary Notes:
1. Comparisons over time can only be made when frequency was estimated using the same size and shape of quadrats each time sampling was conducted.
2. Report changes in frequency in absolute terms, not relative terms. For example, if frequency changes from 20% to 30%, report this as a 10% increase in frequency, not a 50% increase.
3. Use frequency to monitor changes or trends within individual species, but not to make comparisons between species, even if they were measured using the same size quadrat.
Ground Rules for Assessing Frequency
What Counts as “In”
As with density, it is critical to clearly specify the criteria that we use to determine whether a plant is present in the quadrat or plot. The criteria applied depends on species characteristics such a plant growth form. Therefore it is essential to define, document, and consistently apply criteria to count a plant as occurring in the plot. The following criteria may be applied:
The plant must be rooted inside the plot. This includes any portion of the plant base. For example, grasses with mat-like growth habits may be rooted both in and out of the plot, while a dicot like the dandelion may be clearly rooted only in the plot; both are counted (Figure 4a). Rooted frequency also includes stolons or runners that may have ramets rooted in the plot (Figure 4b). Be careful to clearly identify that the ramets are in fact rooted in the plot and not simply overhanging (unrooted ramets do not count). Rooted frequency is the standard approach to determining plant presence in the plot.
Canopy frequency is a special consideration usually applied to larger species, such as trees and some shrubs. A plant is counted as “in” the quadrat if any portion of canopy overhangs the plot. This follows a rule described by Bonham (1989), in which a plant is counted if any perennating bud occurs in the volume of space extending vertically above the plot boundaries (Figure 4c). Using this method is not recommended for all situations and is a special adaptation to account for dominant plant species that might otherwise be missed without using impractically large plots. It is important to clearly document the use of this approach, including which species it applies to, when canopy frequency is employed.
Figure 4. Decision rules are demonstrated with red plots: a) plants rooted in the plot, b) stolons or runners rooted in the plot [pointed out by the blue arrow], and c) canopy overhangs in the plot [the top plot has canopy “in”, but the lower plot does not, as shown with the vertical plot projections in red].
Note that frequency measurements always include rooted frequency, and the decision whether to count canopy frequency is case specific and considered as an optional addition to the criteria of counting species that are rooted in the plots.
Level of Identification
Ground rules are needed to determine the taxonomic level of identification, whether to separate some species by age-classes, and how to account for annual plants.
Taxonomic level: Decisions about taxonomic level of identification are guided primarily by management objectives. Plants are most often identified to the species level for frequency measurements, and this provides the most detailed data and complete picture of the plant community. When we are monitoring for threatened, endangered, or other species of concern, identification to the species level is usually a high priority.
Sometimes it is extremely difficult to identify plants to the species level. This is true for certain genera such as threeawns (Aristida spp.), especially without inflorescences, or in mixed plant communities that include cool- and warm-season plants that flower in different seasons. If the need to identify plants to species is not a high priority, we may decide to lump certain species together and identify to the genus level. If this is done, it is essential to clearly document which species are being grouped together.
Age-class: Since seedling presence can be highly variable within and between years, frequency estimates for relatively stable populations may fluctuate widely if we count any individual of a species, regardless of age-class or stage of development. Therefore we need to determine whether to tally individuals of different age-classes separately (e.g., seedling, non-reproductive, reproductive) for some species. Alternatively, we may decide to exclude seedlings of certain species.
Annual plants: Annual plants may be alive and growing for an entire growing season, or only a short period of time. Decisions need to be made about whether to count annual plants that are dead but standing and identifiable. Depending on the management objectives, the aim might be only to characterize the perennial plants, in which case annual plants would not be recorded. Obviously this would not apply in communities such as the California Annual Grassland, where annuals are a major component of the plant community.
Quadrat Size Matters!
Determining the quadrat size for frequency measurements is extremely important as quadrat size greatly influences the results. If the plot is too small, the probability of recording a plant species of interest is low, resulting in a low frequency estimate. If the quadrat is too large, the most common species may be found in all or nearly all quadrats, resulting in very high frequency estimates, sometimes 100%.
In other words, plant frequency is completely affected by the size of the quadrat. This effect of plot size is so profound that some ecologists do not recognize frequency as a true plant attribute. Rather, they consider frequency a joint characteristic of plant and quadrat. Thus, when assessing frequency, it is very important to select an appropriate plot size that adequately samples each plant of interest. This will occasionally requires that multiple plot sizes are used when the most important plants being monitored require different quadrat sizes. This problem is solved by using nested quadrats or plots, discussed in a subsequent lesson.
The appropriate quadrat size depends on the size and density of the plant:
•It is difficult to detect increase in plant frequency if it occurs in nearly all the plots. General rule: if the frequency is ≥ 90% for the species of interest, reduce the quadrat size.
•Likewise, it is difficult to record a decline in a species if the initial frequency of the plant is very low. General rule: if the frequency estimate for a species of interest is ≤ 10%, increase the plot size.
•The greatest sensitivity to change occurs when frequency values occur between 20% and 80%. Some research suggests that plot sizes should be selected to produce frequency estimates between 30% and 70% for most species.
•Choose a plot size that is appropriate for as many species as possible. Plot size should be 1 to 2 times as large as the average area of the most common species. If one plot size simply won’t be sufficient for monitoring objectives, use nested quadrats.
•Bonham (1989) presents a mathematical approach to determine appropriate size of plot using a logarithmic relationship between frequency and density.
Sample Size and Design
To detect changes in a meaningful time frame, the sample size and sampling design need to be determined in the context of the sampling objectives and characteristics of the vegetation stand. Most frequency estimates are based on 100-200 quadrats per vegetation stand, with 100 as an absolute minimum (in Ruyle et al 1991, Ch2). If the sampling objectives require being able to detect small differences, the required sample size may be as large as 500 or more.
Quadrats may be distributed systematically throughout the vegetation stand, or they may be arranged systematically along transects. If transects are used, 15-20 quadrats are usually placed at regular intervals along the transect, and the transect becomes the sampling unit. Quadrats need to be spaced so that successive quadrats do not measure in the same patch or clump of plants. When the goal is to compare frequency across ecological sites within a large area, stratification might also be advantageous.
How to Calculate Frequency
Frequency calculations are relatively straight-forward. Step 1: Collect the data. Count and record the number of individuals of each species in each plot. In the example below, 100 plots were examined (Figure 5).
Figure 5. Frequency for 15 species in the Blue Dome allotment was calculated using 100 plots in which species presence was recorded with a diagonal slash [ / ].
Step 2: Calculate frequency of each plant.
- In the example data sheet above, 100 plots were examined so the total number of plots in which a plant occurred equals the percent frequency. BOCU occurred in 35 of 100 quadrats, so the frequency of that species is 35%.
- Two important details:
1) The number of times a plant occurs in a plot are often called “hits.” In the example above, there was 1 hit of juniper (JUNIP, at the bottom of the list).
2) Plant names are often recorded with species codes, such as in the data sheet above. In most cases these are 4-letter codes with the first 2 letters of the genus and first 2 letters of the specific epithet, sometimes with a number at the end. Therefore, BOCU is Boutelouacurtipendula or sideoats grama. HYRI = Hymenoxys richardsonii or pingue rubberweed. To find the species codes (i.e., symbol) for a plant or the name of the plant associated with a code visit www.plants.usda.gov .