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Rangeland Inventory, Monitoring, and Evaluation:
Vegetation Attributes

Introduction | General Principles | Sampling Concepts | Vegetation Attributes
Rangeland Evaluation | Management Applications | Chapter Outline

Sample Variance

The sample variance (s²) is a measure of dispersal that reflects the spread of data around the sample mean. The sample variance is calculated as

Allocation of Sample Units - Sampling Designs

Decisions relating to the arrangement of sample units within the site have a large influence on sample precision, sample efficiency, and statistical models used to analyze the data. These decisions are an important component of designing the inventory or monitoring program before the data is actually collected.

Angle of Points

With most techniques involving point sampling to estimate cover, points are placed vertically to the ground. However, some studies indicate that points inclined at about a 45° angle provide more accurate data for the cover of narrow-leaved species, particularly grasses.

References and Further Reading

Bonham, C.D. Measurements of terrestrial vegetation. John Wiley Sons, New York, NY. p 111-115.

Example to Calculate Carrying Capacity by Matching Forage Supply and Animal Demand

Problem

A 4,000 ha ranch in the black grama (Bouteloua eriopoda) semi-desert ranges of south-eastern Arizona produces 300 kg/ha/year of key forage species in an average year. Because range condition across the ranch is currently fair, allowable use is set at 30% with the objective of improving range condition.

Dry Matter Content

Biomass is usually determined on a dry matter basis, which is the weight of plant material after the moisture within the plant material has been extracted. Moisture content varies among species and during the year, according to the stage of growth, growth form (herbaceous, woody, succulent), soil moisture levels, and atmospheric humidity. Standardizing weights on a dry matter basis facilitates comparisons of biomass among sites and over time by eliminating these other confounding factors.