Sampling Vegetation Attributes - Natural Resources Conservation ...

More documents

Recommendations

Info

STUDY DESIGN AND ANALYSIS developed by Brown et al. (1993), is available as freeware from the following Internet ftp (file transfer protocol) site: odin.mda.uth.tmc.edu. Documentation is included with the program. The program calculates sample sizes needed for all of the types of significance testing but does not calculate those required for estimating a single population average, total, or proportion. PC-SIZE: CONSULTANT is a shareware program that will calculate sample sizes for estimating an average (but not a proportion) and for all the types of significance tests. It was developed in 1990 by Gerard E. Dallal, who also developed the commercial program DESIGN discussed above. PC-SIZE: CONSULTANT appears to contain all of the algorithms included in DESIGN but at a fraction of the cost (the author asks for a fee of $15.00 if the user finds the program to be useful). The program is available via the World Wide Web at the following address: http://www.coast.net/SimTel/SimTel/ Once at the homepage, change to the directory msdos/statstic/ and download the file st-size.zip. Unzip the file using the shareware program PKUNZIP. Executable files and documentation are included. Alternatively, tables can be used to calculate sample size. For detecting change in averages, proportions, or totals between two time periods, the tables found in Cohen (1988) are highly recommended. 10. Graphical Display of Data The use of graphs, both to initially explore the quality of the monitoring data collected and to display the results of the data analysis, is important to designing and implementing monitoring studies. See Technical Reference, Measuring & Monitoring Plant Populations, for descriptions of these graphs, along with examples. a Graphs to Examine Study Data Prior to Analysis The best of these graphs plot each data point. These graphs can help determine whether the data meet the assumptions of parametric statistics, or whether the data set contains outliers (data with values much lower or much higher than most of the rest of the data—as might occur if one made a mistake in measuring or recording). Normal probability plots and box plots are two of the most useful types for this purpose. Graphs can also assist in determining appropriate quadrat size. For more information, see Technical Reference, Measuring & Monitoring Plant Populations. b Graphs to Display the Results of Data Analysis Rather than displaying each data point, these graphs display summary statistics (i.e., averages, totals, or proportions). When these summary statistics are graphed, error bars must be used to display the precision of estimates. Because it is the true parameter (average, median, total, or proportion) that is of interest, confidence intervals should be used as error bars. Types of graphs include: • Bar charts with confidence intervals. • Graphs of summary statistics plotted as points, with error bars. • Box plots with “notches” for error bars. 21
22 STUDY DESIGN AND ANALYSIS C. Other Important Considerations 1. <strong>Sampling</strong> All Species Although the key species concept is important in analyzing and evaluating management actions, other species should also be considered for sampling. Whenever possible, all species should be sampled, especially on the initial sampling. It is also important to record sampling data by individual species rather than by genera, form class, or other grouping. These data can be lumped later during the analysis if appropriate. Both of these approaches will provide greater flexibility in data analysis if objectives or key species change in the future. 2. Plant Species Identification The plant species must be properly identified in order for the data to be useful in grazing allotment, wildlife habitat area, herd management area, watershed area, or other designated management area evaluations. In some cases, it may be helpful to include pressed plant specimens, photographs, or other aids used for species identification in the study file. If data are collected prior to positive species identification, examiners should collect plant specimens for later verification. 3. Training The purpose of training is to provide resource specialists with the necessary skills for implementing studies and collecting reliable, unbiased, and consistent data. Examiners should understand data collection, documentation, analysis, interpretation, and evaluation procedures, including the need for uniformity, accuracy, and reliable monitoring data. Training should occur in the field by qualified personnel to ensure that examiners are familiar with the equipment and supplies and that detailed procedural instructions are thoroughly demonstrated and understood. As a follow-up to the training, data collected should be examined early in the study effort to ensure that the data are properly collected and recorded. Periodic review and/or recalibration during the field season may be necessary for maintaining consistency among examiners because of progressive phenological changes. Review and recalibration during each field season are especially important where data collection methods require estimates rather than direct measurements.
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 and 8: I. PREFACE PREFACE The intent of th
Page 9 and 10: 2 INTRODUCTION values when individu
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: 4 3.5 3 2.5 20 5 STUDY DESIGN AND A
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
Page 59 and 60: 52 METHODS—Dry Weight Rank After
Page 62 and 63: D. Daubenmire Method METHODS—Daub
Page 64 and 65: METHODS—Daubenmire b Ten Cover Cl
Page 66: Page of Daubenmire Study Number Dat
Page 70 and 71: 50 cm Six Cover Class Frame 20 cm R
Page 72 and 73: METHODS—Line Intercept b Pilot St
Page 74 and 75: METHODS—Line Intercept Hanley, Th
Page 77 and 78: 70 METHODS—Step Point F. Step-Poi
Page 79 and 80:
72 METHODS—Step Point the boot an
Page 81 and 82:
74 METHODS—Step Point measures AN
Page 85 and 86:
78 METHODS—Point Intercept G. Poi
Page 87 and 88:
80 METHODS—Point Intercept 8. Sam
Page 89 and 90:
82 METHODS—Point Intercept b Tran
Page 91 and 92:
METHODS—Point Intercept Examples
Page 93 and 94:
86 METHODS—Cover Board H. Cover B
Page 95 and 96:
88 METHODS—Cover Board g Study Do
Page 98:
Page of Cover Board Method Profile
Page 101 and 102:
94 METHODS—Density I. Density Met
Page 103 and 104:
96 METHODS—Density (often very mu
Page 105 and 106:
98 METHODS—Density able to make s
Page 107:
Page of Density Study Number Date E
Page 110 and 111:
• Herbage Yield Tables for Trees
Page 112 and 113:
METHODS—Double Weight Sampling (4
Page 114 and 115:
METHODS—Double Weight Sampling d
Page 116:
Page of Production Study Number Dat
Page 119 and 120:
112 METHODS—Harvest K. Harvest Me
Page 121 and 122:
114 METHODS—Harvest 7. Taking Pho
Page 123 and 124:
116 METHODS—Comparative Yield L.
Page 125 and 126:
118 METHODS—Comparative Yield (1)
Page 127 and 128:
120 METHODS—Comparative Yield Tab
Page 130 and 131:
M. Visual Obstruction Method - Robe
Page 132 and 133:
METHODS—Visual Obstruction—Robe
Page 134:
Sampling Interval Study Location 1
Page 137 and 138:
130 METHODS—Other N. Other Method
Page 139 and 140:
132 GLOSSARY browse: (1) the part o
Page 141 and 142:
134 GLOSSARY grazable woodland: for
Page 143 and 144:
136 GLOSSARY sample: a set of sampl
Page 145 and 146:
138 GLOSSARY
Page 147 and 148:
140 REFERENCES Crocker, R.L. and N.
Page 149 and 150:
142 REFERENCES Hironaka, M. 1985. F
Page 151 and 152:
144 REFERENCES Nie, Norman H., C. H
Page 153 and 154:
146 REFERENCES Society for Range Ma
Page 155 and 156:
148 REFERENCES Whitman, W.C. and E.
Page 157:
Location 150 APPENDIX A Study Locat
Page 160 and 161:
APPENDIX B APPENDIX B—STUDY AND P
Page 162 and 163:
APPENDIX B 3. Label 3 A placard on
Page 164 and 165:
APPENDIX C Photo Identification Lab
Page 167 and 168:
160 APPENDIX C
Page 169 and 170:
162 APPENDIX D The formula for usin
Page 171:
Form Approved OMB No. 0704-0188 Pub
show all

Sampling Vegetation Attributes - Natural Resources Conservation ...

Create successful ePaper yourself

Delete template?

Save as template?