Sampling Vegetation Attributes - Natural Resources Conservation ...

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II. INTRODUCTION INTRODUCTION Identifying the appropriate sampling technique first requires the identification of the proper vegetation characteristic or attribute to measure. To do this the examiner must consider objectives, life form (grass, forb, shrub, or tree), distribution patterns of individuals of a species, distribution patterns between species (community mosaic pattern), efficiency of data collection from an economic standpoint, and accuracy and precision of the data. Permittees, lessees, other rangeland users, and interested publics should be consulted and encouraged to participate in the collection and analysis of monitoring data. Those individuals or groups interested in helping to collect data should be trained in the technique used in the specific management unit. This document deals with the collection of vegetation data. The interpretation of that data will be addressed in other documents. This document does not address interpreting vegetation data for adjusting livestock numbers or making other management decisions. A. Terms and Concepts The following terms require an expanded discussion beyond the scope of the Glossary of Terms: 1. Inventory Inventory is the systematic acquisition and analysis of information needed to describe, characterize, or quantify vegetation. As might be expected, data for many different vegetation attributes can be collected. Inventories can be used not only for mapping and describing ecological sites, but also for determining ecological status, assessing the distribution and abundance of species, and establishing baseline data for monitoring studies. 2. Population A population (used here in the statistical, not the biological, sense) is a complete collection of objects (usually called units) about which one wishes to make statistical inferences. Population units can be individual plants, points, plots, quadrats, or transects. 3. Sampling Unit A sampling unit is one of a set of objects in a sample that is drawn to make inferences about a population of those same objects. A collection of sampling units is a sample. Sampling units can be individual plants, points, plots, quadrats, or transects. 4. Sample A sample is a set of units selected from a population used to estimate something about the population (statisticians call this making inference about the population). In order to properly make inferences about the population, the units must be selected using some random procedure (see Technical Reference, Measuring & Monitoring Plant Populations). The units selected are called sampling units. 5. Sampling Sampling is a means by which inferences about a plant community can be made based on information from an examination of a small proportion of that community. The most complete way to determine the characteristics of a population is to conduct a complete enumeration or census. In a census, each individual unit in the population is sampled to provide the data for the aggregate. This process is both time-consuming and costly. It may also result in inaccurate 1
2 INTRODUCTION values when individual sampling units are difficult to identify. Therefore, the best way to collect vegetation data is to sample a small subset of the population. If the population is uniform, sampling can be conducted anywhere in the population. However, most vegetation populations are not uniform. It is important that data be collected so that the sample represents the entire population. Sample design is an important consideration in collecting representative data. (See Section III.) 6. Shrub Characterization Shrub characterization is addressed here since it is not covered in most of the techniques in this technical reference. Shrub characterization is the collection of data on the shrub and tree component of a vegetation community. Attributes that could be important for shrub characterization are height, volume, foliage density, crown diameter, form class, age class, and total number of plants by species (density). Another important feature of shrub characterization is the collection of data on a vertical as well as a horizontal plane. Canopy layering is also important. The occurrence of individual species and the extent of canopy cover of each species is recorded in layers. The number of layers chosen should represent the herbaceous layer, the shrub layer, and the tree layer, though additional layers can be added if needed. 7. Trend Trend refers to the direction of change. Vegetation data are collected at different points in time on the same site and the results are then compared to detect a change. Trend is described as moving “towards meeting objectives,” “away from meeting objectives,” “not apparent,” or “static.” Trend data are important in determining the effectiveness of on-the-ground management actions. Trend data indicate whether the rangeland is moving towards or away from specific objectives. The trend of a rangeland area may be judged by noting changes in vegetation attributes such as species composition, density, cover, production, and frequency. Trend data, along with actual use, authorized use, estimated use, utilization, climate, and other relevant data, are considered in evaluating activity plans. 8. Vegetation Attributes Vegetation attributes are quantitative features or characteristics of vegetation that describe how many, how much, or what kind of plant species are present. The most commonly used attributes are: Frequency Production Cover Structure Density Species Composition B. Techniques Not Addressed The following are not included in this document: • Riparian Monitoring • Monitoring Using Aerial Photography • Special Status Plant Monitoring • Weight Estimate and Ocular Reconnaissance Methods • Soil Vegetation Inventory Method • Community Structure Analysis Method • Photo Plot Method
Page 1 and 2: SAMPLING VEGETATION ATTRIBUTES INTE
Page 3 and 4: TABLE OF CONTENTS SAMPLING VEGETATI
Page 5 and 6: TABLE OF CONTENTS TABLE OF CONTENTS
Page 7: I. PREFACE PREFACE The intent of th
Page 11 and 12: 4 INTRODUCTION represent the “pul
Page 13 and 14: 6 INTRODUCTION G. Coordination Moni
Page 15 and 16: 8 STUDY DESIGN AND ANALYSIS A. Plan
Page 17 and 18: 10 STUDY DESIGN AND ANALYSIS Macrop
Page 19 and 20: 12 STUDY DESIGN AND ANALYSIS Becaus
Page 21 and 22: 14 STUDY DESIGN AND ANALYSIS d From
Page 23 and 24: 16 STUDY DESIGN AND ANALYSIS b Cove
Page 25 and 26: 18 STUDY DESIGN AND ANALYSIS sideoa
Page 27 and 28: 4 3.5 3 2.5 20 5 STUDY DESIGN AND A
Page 29 and 30: 22 STUDY DESIGN AND ANALYSIS C. Oth
Page 31 and 32: 24 ATTRIBUTES Frequency is the numb
Page 33 and 34: 26 ATTRIBUTES 2. Advantages and Lim
Page 35 and 36: 28 ATTRIBUTES b Standing crop and p
Page 37 and 38: 30 ATTRIBUTES
Page 39 and 40: 32 METHODS—Photographs c Angle ir
Page 41 and 42: METHODS—Photographs Hinge Rod sta
Page 43 and 44: METHODS—Photographs angle iron st
Page 45 and 46: 38 METHODS—Frequency • One tran
Page 47 and 48: 40 METHODS—Frequency transected,
Page 49 and 50: 42 METHODS—Frequency (3) Total fr
Page 51: Page of Frequency 44 Study Number D
Page 55 and 56: METHODS—Frequency The frame is ma
Page 57 and 58: 50 METHODS—Dry Weight Rank C. Dry
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52 METHODS—Dry Weight Rank After
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D. Daubenmire Method METHODS—Daub
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METHODS—Daubenmire b Ten Cover Cl
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Page of Daubenmire Study Number Dat
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50 cm Six Cover Class Frame 20 cm R
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METHODS—Line Intercept b Pilot St
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METHODS—Line Intercept Hanley, Th
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70 METHODS—Step Point F. Step-Poi
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72 METHODS—Step Point the boot an
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74 METHODS—Step Point measures AN
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78 METHODS—Point Intercept G. Poi
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80 METHODS—Point Intercept 8. Sam
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82 METHODS—Point Intercept b Tran
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METHODS—Point Intercept Examples
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86 METHODS—Cover Board H. Cover B
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88 METHODS—Cover Board g Study Do
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Page of Cover Board Method Profile
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94 METHODS—Density I. Density Met
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96 METHODS—Density (often very mu
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98 METHODS—Density able to make s
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Page of Density Study Number Date E
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• Herbage Yield Tables for Trees
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METHODS—Double Weight Sampling (4
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METHODS—Double Weight Sampling d
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Page of Production Study Number Dat
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112 METHODS—Harvest K. Harvest Me
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114 METHODS—Harvest 7. Taking Pho
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116 METHODS—Comparative Yield L.
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118 METHODS—Comparative Yield (1)
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120 METHODS—Comparative Yield Tab
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M. Visual Obstruction Method - Robe
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METHODS—Visual Obstruction—Robe
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Sampling Interval Study Location 1
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130 METHODS—Other N. Other Method
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132 GLOSSARY browse: (1) the part o
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134 GLOSSARY grazable woodland: for
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136 GLOSSARY sample: a set of sampl
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138 GLOSSARY
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140 REFERENCES Crocker, R.L. and N.
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142 REFERENCES Hironaka, M. 1985. F
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144 REFERENCES Nie, Norman H., C. H
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146 REFERENCES Society for Range Ma
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148 REFERENCES Whitman, W.C. and E.
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Location 150 APPENDIX A Study Locat
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APPENDIX B APPENDIX B—STUDY AND P
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APPENDIX B 3. Label 3 A placard on
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APPENDIX C Photo Identification Lab
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160 APPENDIX C
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162 APPENDIX D The formula for usin
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Form Approved OMB No. 0704-0188 Pub
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