November 1988

Southeastern Forest Experiment Station

P.O. Box 2880

Asheville, North Carolina 28802
Estimating Cone And Seed Production

And Monitoring Pest Damage

in Southern Pine Seed Orchards

Carl W. Fatzinger

Research Entomologist

Southeastern Forest Experiment Station

Olustee, Florida 32072

H. David Muse

Department of Mathematical and Computer Science

University of North Alabama

Florence, Alabama 35632

Thomas Miller

Research Plant Pathologist

Southeastern Forest Experiment Station

PO. Box 70

Olustee, Florida 32072

Helen T. Bhattacharyya

Assistant Director

Biostatistics, Glaxo Incorporated

Research Triangle Park, North Carolina 27709
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

The use of trade, firm, or corporation names in this Paper

is,for the information and convenience of the reader. Such

'usedoes not constitute official endorsement or approval by

the U.S.Department of Agriculture of any product or service

to the exclusion of others that may be suitable.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

The computer program is available on request with the

understanding that the U.S. Department of Agriculture cannot

assure its accuracy, completeness, reliability, or suitability

for any other purpose than that reported. The recipient may

not assert any proprietary rights thereto nor represent it to

anyone as other than a Government-produced computer program.
Contents

Orchard Sampling Procedures ...............

Selection of Sample Trees ...............

Selection of Sample Strobili. .............

Periodic Observations on Sample Clusters. .......

Field Data Forms. ...................

Cone Collection and Seed Analyses ...........

Optional Sampling Methods ...............

Computer Programs, Statistical and Analytical Methods

Datasets. .......................

Operation of the Programs ...............

Literature Cited. ....................

Appendix I. Hypothetical Example of Sampling Procedures

and User-Friendly Programs

Page

1

2

2

;

z

Southeast-Quadrant Sampling ..............

Operation of Computer Programs. ............

Appendix II. Field Data Forms

Initial Data Forms. ..................

Follow-Up Data Forms. .................

Seed Data Forms ....................

Appendix III. Guide for the Operation of Five Computer

Programs for Producing Random Numbers,

Field Data, Orchard Productivity

Estimates, and Seed Analyses

1 0

11

Random Numbers (Program A). ..............

Field Data Forms (Program B). .............

Orchard Productivity (Program C). ...........

Damage Estimates (Program D). .............

27

27

28

29

Seed Analyses (Program E) . . . . . . . . . . . . . . . 30

. . . 111
Abstract Field sampling procedures and computer programs are described

for monitoring seed production and pest damage in southern pine

seed orchards. The system estimates total orchard yields of

female strobili and seeds, quantifies pest damage, determines

times of year when losses occur, and produces life tables for

female strobili. An example is included to illustrate the

sampling procedures and the operation of user-friendly computer

programs.

Keywords: Cone and seed insects, cone and seed diseases,

sampling, seed orchard production, survey,

iv
Estimating Cone and Seed Production

and Monitoring Pest Damage

in Southern Pine Seed Orchards

Managers of southern pine seed orchards need periodic estimates

of the number and condition of the first- and second-year crops

of cones concurrently present on southern pines. Female

strobili are subject to damage by insects, diseases, and other

factors throughout the period of some 20 months required for

development from flowers to mature cones.

A sampling method was developed to provide periodic estimates

of pest damage and strobilus productivity in southern

orchards. Because of the wide variation in strobilus

production and mortality between orchards, clones, and years,

the sampling system was designed for individual seed orchards

(Fatzinger 1984). This paper describes the field sampling

procedures and computer programs developed from 198.2 to 1986 by

the Integrated Forest Pest Management Cooperative (U.S.

Department of Agriculture, Forest Service, and the University

of Florida). The objectives were to estimate orchard yields of

female strobili and seeds, to quantify pest damage, to

determine the times of year when losses occur, and to develop

life tables for female strobili. An example of a hypothetical

orchard is included to illustrate the sampling procedures and

the operation of user-friendly computer programs that have been

developed (Appendix I). Copies of the computer programs and

analyses for the hypothetical seed orchard can be obtained from

the Project Manager, Integrated Forest Pest Management

Cooperative, Department of Forestry, University of Florida,

Gainesville, FL 32611.

Orchard Sampling The sampling system includes four steps: (1) selecting sample

Procedures trees within an orchard, (2) sampling female strobili in

different portions of the crowns of sample trees, (3) making

periodic observations, and (4) collecting seed samples

(Appendix I, fig. 1). For each step, we have developed a basic

method, which will be described first. Other available

options, such as random selection of sample trees, and

whole-crown sampling, are discussed in later sections of this

Paper.
Selection of

Sample Trees

Selection of

Sample Strobili

The basic method calls for selection of 42 sample trees per

orchard. Fourteen sample clones are chosen, with the

probability of selection proportional to the relative strobilus

production (size) of each clone within the orchard (Appendix

1). When records of strobilus production are not available,

the number of ramets per clone is used as the criterion of

size. Clones are selected with replacement; i.e., selection of

a clone more than once is permitted. When this occurs, the

total number of sample trees remains the same, but the number

of clones sampled is decreased by one. Ramets are considered

to be primary sampling units, and three are randomly selected

as sample trees within each sample clone.

Clusters of female strobili are used as secondary sampling

units because they are more convenient to count than individual

strobili on sample trees. All clusters of first-year female

strobili are counted on each sample tree when the system is

installed. The counts should be made as accurately as possible

because they serve as a basis for estimating orchard

productivity and for determining total losses of strobili. The

accuracy of these total-tree counts is improved by dividing the

crowns into four directional quadrants. Plastic flagging

placed at midcrown height on the north, south, east, and west

sides of the trees serves this purpose.

The initial counts should be made shortly after the female

flowers have emerged through the bud scales (stage 3 to stage 4

of development, Bramlett and O'Gwynn 1980) when they are easily

distinguished from vegetative buds. If desired, a separate

sample can be made of the second-year strobili present on the

same sample trees, but only first-year strobili should be

counted on the ssme trees during subsequent years.

A lo-percent random sample of the flower clusters in the

southeast-crown quadrant is selected for subsequent

observations. Each of the sample clusters is identified by

consecutively numbered tags attached to the branch immediately

below the cluster. First-year strobili should not bear the

ssme tag numbers as the second-year strobili.

In practice, we make an initial count of the total number of

clusters in each of the four quadrants and total these for the

tree count. We then begin recounting clusters from the top of

the southeast quadrant and tag those clusters whose count

corresponds with the numbers in a table of random numbers

produced by computer program A, which is described later.

It may be necessary to include a few extra randomly selected

clusters to assure a representative spread of sample clusters

from the top to the bottom of the crown. A lo-percent sample

of the clusters on young trees bearing few strobili could

result in samples too small for reliable use in estimating

yields. Therefore, a minimum of 10 clusters is tagged or all

of the clusters are tagged when there are less than 10 clusters

present in a quadrant.
Periodic

Observations on

Sample Clusters

Two types of observations are taken on the sample clusters.

The first type, referred to as a "general sample," is taken

three times a year on all sample trees to estimate the numbers

and conditions of female strobili present in sample clones and

in the entire orchard. The times of these observations and the

corresponding stages of development of first- and second-year

female strobili are: (1) late winter (first-year flowers and

early second-year conelets), (2) late spring (early first-year

conelets and second-year green cones), and (3) fall (late

first-year conelets and second-year mature cones). The second

type of observation, referred to as an "intensive subsample,"

is made to meet local needs. One of the three sample ramets in

each sample clone is randomly selected and observed at monthly,

or more frequent, intervals during periods when major losses

are typically known to occur (Fatzinger and others 1980). The

intensive subsamples are taken to record pest damage before the

affected strobili die and fall from the trees. The data also

provide interim summaries of the proportions of strobili killed

or injured by different pests on the subsample of 14 trees.

When estimates of clonal and orchard productivity are desired,

the general sampling procedure can be substituted for some or

all of the intensive subsamples.

Field Data Forms Records of first- and second-year strobili are kept on separate

data forms. The "initial data sheets" are used only when the

female strobili are tagged at the beginning of sampling

(Appendix II). Data forms for subsequent observations on the

tagged clusters are generated by the program, which is

described in detail in a later section of this paper. The

program lists each sample cluster and updates the form with the

numbers of strobili remaining per cluster and the conditions

and causes of damage observed during the previous observation

period. This feature facilitates the use of strobilus clusters

as observational units for determining causes of damage to

strobili. The program also identifies inconsistencies in the

numbers of strobili recorded for individual clusters during

previous observations.

Sample trees are numbered consecutively from 1 to 42,

regardless of their clonal identity, and are identified

individually by these sample tree numbers. The clonal

information, seed source data, numbers of initial flower

clusters present, and other identification listed on the

initial data forms are stored in a computer file for use when

needed. The orchard name, tree species, sample tree number,

date of previous sampling, and year of flowering are printed on

the subsequent field data sheets for reference, so this

information need not be entered a second time.

Cone Collection A sample of six apparently healthy cones is collected from each

and Seed Analysis sample tree at cone harvest. The 252 sample cones (42 sample

trees x 6 cones per tree) are selected from the tagged clusters

in the southeast-crown quadrant by randomly marking six

clusters on the field data forms. One healthy cone is selected

as a sample from each of the six marked sample clusters or from

the nearest tagged or untagged cluster if no healthy cones

remain in a selected cluster. Each sample cone is placed in an

3
individual paper bag labeled with the orchard name, tree

number, and cluster tag number. The cones are stored until

their scales begin to open in a room with sufficient

ventilation to prevent mold formation. The cone scales of

slash and loblolly pines can then be opened further by drying

the cones in kilns or forced-air ovens for 24 hours at 49 'C

(120 OF).

Most of the seeds are extracted by forcibly tapping the dried

cones until seeds no longer fall from them. The remaining

seeds must be removed from the cones by dissection to increase

the accuracy of estimates of seed quality. This can be

accomplished by the procedures described by Bramlett and others

(1977) l All seeds extracted from each cone are placed in a

paper envelope for radiography. Radiographs can be interpreted

by criteria described by DeBarr (lg‘j'o), Ebel and others (1975).

and Bramlett and others (1977). The radiografihed seeds are

germinated following the procedures described by Fatzinger and

others (1980). Seed data are recorded on the standardized form

illustrated in Appendix II and used to estimate the average

number of seeds per cone, the proportion of seeds damaged,

causes of damage, and the proportion of seeds viable at

harvest.

Optional Sampling Random selection of sample trees. Simple random selection of

Methods sample trees is appropriate when clonal identities of trees

cannot be determined, such as in seedling seed orchards. In

that case, the 42 sample trees are selected at random (fig.

1). The intensive subsample is taken on a random selection of

14 sample trees.

Whole-crown sampling. The sampling system and its programs can

be used with data collected from sample clusters located

throughout the whole crown. Initial numbers of clusters present

in different quadrants of the crowns of sample trees must be

counted and recorded separately. If desired, separate records

of the numbers of clusters found specifically in the upper and

lower height levels of the southeast- and southwest-crown

quadrants also may be maintained.

Computer programs for analysis of whole-crown samples were

retained in the system for estimating damage of pests that may

be nonuniformly distributed among crown quadrants. The

whole-crown sampling procedure requires different types of

initial data forms than those used for the southeast-crown

quadrant sampling procedure (Appendix II).

General sample data only. The inclusion of intensive subsample

data in the sampling system is optional and need be taken only

when detailed information on the causes of strobilus mortality

is desired.
Datasets

Computer Programs, Five computer programs utilizing procedures in the Statistical

Statistical and Analysis System (SAS Institute 1985a, lq85b) were

Analytical Methoda developed for the seed orchard sampling system. One program

produces random number tables for use in selecting random

samples of strobilus clusters in tree crowns. A second program

provides field data sheets updated with information on the

numbers and conditions of sample strobili observed during the

previous sample. Two other programs are used to summarize the

field data and to compute periodic estimates of orchard

productivity and pest damage. The fifth program summarizes

information on seed quality and quantity on a clonal basis. An

example of the use of these programs and a guide for their use

are given in Appendixes I and III. All programs are currently

operated under an IBM interactive system Time-Sharing Option

(TSO) at the Northeast Regional Data Center (NERDC) of the

University of Florida. They can be installed on other

computers supporting SAS and TSO.

A set of data consists of all observations taken during one

general sample, one intensive subsample, or a seed analysis for

one crop of cones. At least six datasets are accumulated over

the period of strobilus development from flowers to mature

cones. The first general sample recorded on the initial data

form is referred to as the "Initial Dataset"; subsequent

observations on the same strobilus clusters are referred to as

"Follow-Up Datasets."

Naming dataaets. Each dataset is given a qualified name in the

format required by NERDC, which consists of alpha-numeric

fields separated by decimal points: for example:

'UF.A#######.FX86Ol.GEN86'

The qualified name begins and ends with a single quotation mark

and can consist of up to 17 fields. Each field must begin with

an alphabetic character and end with a period. A field can

contain up to 8 alpha-numeric characters. In the above example

of the format for a qualified name, the first field, UF, is a

prefix required by NERDC. The second field, A#######, is the

user's account number with the first numeral replaced by its

alphabetic equivalent; e.g., 1 = A, 2 = B, . . ., 9 = I. The

third field, EX8601, identifies the dataset. The first two

characters identify the orchard (EX = example), and the last

four characters identify the year (86 = 1986) and month (01 =

January) during which the sample was taken. The last field,

GEN86, identifies the type of sample taken (GEN = general

sample) and the year of flowering (86) for the strobili

sampled. Other abbreviations used for the type of sample are

INIT for an initial dataset, INT. for intensive subsample data,

and SEED for seed samples, for example:

'uF.A#######.EX8601.INIT86'

'uF.A#######.EX86Ol.INT86'

'UF.A#######.EX86Ol.GEN86'

'UF,A#######.EX8601.SEED87'
The dataset for the initial observation ('UF.A#######.

EX8601.INIT86') was obtained by taking a general sample, and

the abbreviation "INIT" is used instead of "GEN" to identify

the sample as the first one taken.

Operation of the The programs are written to be self-explanatory and user

Programs friendly. An operator is guided by messages or "prompts"

displayed on a terminal screen. Each program consists of a

control list and a control program. The control list (CLIST)

provides prompts for the input of information necessary to

initialize the control programs, Once initialized, the control

programs run automatically to analyze data and to print forms

or random number tables. The control lists are individually

called up for execution by one of the following commands:

EXEC 'UF.A#######.RANDOM.CLIST'

EXEC 'UF.A#######.FORMS.CLIST'

EXEC 'UF.A#######.YIELD.CLIST'

JXEC 'UF.A#######.DAMGINT.CLIST'

EXEC 'UF.A#######.SEED.CLIST'

Examples of the "prompts" for the five programs are given in

Appendix III. If a mistake is made while typing a response to

a "prompt," it can be corrected before it is entered into the

computer by backspacing and typing over the mistake with the

correct information. Once a mistake has been entered into the

computer with the "return" key, the program must be terminated

and begun over. The program can be terminated by striking the

"break" key, and typing END,N.

Random numbers (Program A). This program is used to generate

up to 43 tables of random numbers for selecting a lo-percent

random sample of clusters. The tables are titled with

different numbers representing the total numbers of clusters

within a quadrant from which a sample is to be drawn. Each

table contains 30 sets of random numbers, and the length of

each set is equal to the number of clusters to be included in

the lo-percent sample. A set of random numbers in a table is

used only once. The table with the next highest number of

total clusters is used when the total cluster count falls

between two of the tables.

The program is divided into three subprograms, which produce

random numbers for different sizes of strobilus crops on sample

trees. The first subprogram produces 8 tables (3 pages per

table) of random numbers for trees with 11 to 25 clusters

per-crown quadrant in steps of 2 clusters; i.e., 11 clusters,

13 clusters, etc.: the second subprogram produces 14 tables (3

pages per table) for trees with 25 to $35 clusters in steps of 5

clusters, and the third produces 21 tables (1 page per table)

for trees with 95 to 200 clusters per quadrant in steps of 5.

Since one of the subprograms usually provides a sufficient span

of numbers for a given orchard, it is not necessary to print

all 43 tables.

Field data forms (Program B). The "data forms" program is run

after the initial or follow-up datasets are on file. The

6
program produces 42 sets of forms for a general sample and 14

sets for an intensive subsample. The forms are printed on 9.5-

by 11-inch continuous form paper and are updated with

information on the numbers and conditions of strobili remaining

in each of the initial sample clusters. In addition,

inconsistencies in counts of strobili remaining in individual

clusters from one sampling period to the next are marked with

an asterisk.

Orchard productivity (Program C). Program C summarizes the

field data and provides estimates of the numbers of sound and

damaged strobili present in sample clones and the entire

orchard after each sampling. A "Clone Dataset" must be on file

when using the PPS (probability proportional to size) sampling

method. It is a list of all clones present in the orchard and

includes measures of the size (numbers of ramets per clone or

records of previous yields) for each clone, An example of a

"Clone Dataset" named 'UF.A#######.EX.CLONE86' is given in

Appendix I. When a simple random sample has been taken,

program C requires only the total number of trees present in an

orchard. The program output includes the following:

Orchard size and sample tree data:

(1) Numbers of ramets per clone in orchard.

(2) Numbers of total and sample clusters.

(3) Initial numbers of strobili in sample clusters.

(4) Current numbers of total and sound strobili

sampled.

Estimates for sample clones:

(1) Initial mean numbers of strobili per tree.

(2) Current mean numbers of total and sound

strobili per tree and per sample clone.

Estimates for entire orchard:

(1) Initial number of strobili.

(2) Current numbers of total and sound strobili.

(3) Variance, standard deviation, coefficient of

variation, upper and lower limits for

95-percent confidence limits of the estimates.

(4) Percent sound strobili.

_

Orchard productivity is estimated as follows. First, for each

sample ramet, the average initial number of strobili, the

current average number of strobili, and the current average

number of healthy (sound) strobili are estimated on a

per-cluster basis. Second, these results, together with the

initial total cluster count for the sample ramet, are used to

estimate the average initial total strobilus count, the current

total strobilus count, and the current total sound strobilus

count for each sample ramet. Third, estimates for the

individual sample ramet are averaged within each sample clone,

and these averages are multiplied by the number of ramets

within the clone to estimate the corresponding clonal totalf;.

7
Fourth, each estimated clonal total is divided by the

associated clonal PPS sampling fraction to estimate the orchard

total. Therefore, orchard totals for initial strobilus count,

current strobilus count, and current sound strobilus count are

estimated from corresponding values for sample clones.

Associated standard errors are computed for the estimates

pertaining to total strobilus count and total sound strobilus

count.

Damage estimates (Program D). Program D can be run on either

the general sample data (42 sample trees) or the intensive

subsample data (14 sample trees). Summaries containing the

information shown below can be obtained for each cause of

damage and for all causes combined:

(1) Initial number of strobili.

(2) Number and percent of strobili lost since start

of sampling (by date and clone).

(3) Number of strobili at time of last sample.

(4) Number and percent of strobili lost or injured

since last sample.

(5) Strobilus mortality curves.

The purpose of the damage estimates program is to track

specific factors causing damaged and missing strobili by clone

over time. To this end, rates of damage and destruction of

strobili are summarized for each clone-cause combination by

sample period. Changes occurring in any sample period are

carried across subsequent sample periods to facilitate

cumulative analyses over time. Analyses for individual sample

periods are based on the number of strobili available from the

previous sample period. Cumulative percentages are based on

initial strobilus counts. Output includes both counts and

percentages reflecting current and cumulative changes, by

sample period, for each clone-cause combination.

Seed analyses (Program E). This program summarizes the

quantity and quality of seeds extracted from the 252 sample

cones collected at harvest. The seed-data analysis provides

estimates for each sample clone and for all sample clones

combined. Each set of analyses includes summary statistics per

cone and per clone. Pooled summaries give percentages of: (1)

germination, (2) full seeds, (3) empty seeds, (4) seed bug

damage, (5) fungus damage, (6) seedworm damage, (7) unknown

damage, and (8) processing damage. Values provided include:

(1) Total number of cones examined, seeds extracted

and seeds germinated.

(2) Mean numbers of total seeds per cone, germinated

seeds per cone, percent of seed germinated, and

standard deviations.

(3) Numbers and percentages of seeds classified as

full, empty, and damaged by seed bugs, seedworms,

fungi, or unknown factors.
Literature Cited

Bramlett, D.L.; Belcher, E.W., Jr.; DeBarr, G.L. [and others].

1977 l Cone analysis of southern pines: a guidebook. Gen.

Tech. Rep. SE-13. Asheville, NC: U.S. Department of

Agriculture, Forest Service, Southeastern Forest

Experiment Station, and Atlanta, GA: Southeastern Area,

State and Private Forestry. 28 pp.

Bramlett, David L.; O'Gwynn, Claude H. 1980. Recognizing

developmental stages in southern pine flowers: the key to

controlled pollination. Gen. Tech. Rep. SE-18.

Asheville, NC: U.S. Department of Agriculture, Forest

Service, Southeastern Forest Experiment Station. 14 pp.

DeBarr, G.L. 1970. Characteristics and radiographic detection

of seedbug damage to slash pine seed. Florida

Entomologist. 53:109-117.

Ebel, Bernard H.; Flavell, Thomas H.; Drake, Loyd E. [and

others]. 1975. Seed and cone insects of southern pines.

Gen. Tech. Rep. SE-8. Asheville, NC: U.S. Department of

Agriculture, Forest Service, Southeastern Forest

Experiment Station, and Atlanta, GA: Southeastern Area,

State and Private Forestry. 40 pp.

Fatzinger, C.W. 1984. Monitoring pest-caused losses of cones

and seed in southern pine seed orchards. In: Yates, Harry

0 III, camp. and ed, Proceedings, cone and seed insects

woiking party conference, Working Party S2.O7-01, IUFRO;

1983 July 31-August 6; Athens, GA. Asheville, NC: U.S.

Department of Agriculture, Forest Service, Southeastern

Forest Experiment Station. pp. 122-127.

Fatzinger, Carl W.; Hertel, Gerard D.; Merkel, Edward P. [and

others]. 1980. Identification and sequential occurrence

of mortality factors affecting seed yields of southern

pine seed orchards. Res. Pap. ~~-216. Asheville, NC:

U.S. Department of Agriculture, Forest Service,

Southeastern Forest Experiment Station. 43 pp.

SAS Institute Inc. 1985a. SAS@ user's guide: basics. 5th

ed. Cary, NC: SAS Institute Inc. 1290 pp.

SAS Institute Inc. 1985b. SAS@ user's guide: statistics. 5th

ed. Cary, NC: SAS Institute Inc. 956 pp.

9
Apbdix I

Hypothetical Example of Sampling Procedures and User-Friendly

Computer Programs

A hypothetical seed orchard illustrates the sampling procedure

and operation of the computer programs. The orchard contains

860 trees of 30 clones with 2 to 98 ramets per clone (table

1). The example demonstrates the use of program A for

generating tables of random numbers and programs C, D, and E

for analyzing data simulated for two general samples, two

intensive subsamples, and a seed sample. A complete listing of

the programs and printouts of the results of analyses for this

example can be obtained from the Project Manager, Integrated

Forest Pest Management Cooperative, Department of Forestry,

University of Florida, Gainesville, FL 32611. Other examples

of analyses of data collected in soythern pine seed orchards

were given by Fatzinger and others.

Southeast Quadrant Selection of sample trees. Fourteen sample clones were

Sampling selected with the probability of selection proportional to

their relative sizes in the hypothetical orchard. Size was

based on the number of ramets per clone (table 1). The size

variable was then accumulated and the range of the accumulated

sizes was listed for each of the ranked clones. Fourteen

three-digit numbers less than or equal to the sum of the size

variables (= 860) were selected from a table of random

numbers. The first 14 random numbers selected were 823, 463,

719, 375, 155, 295, 783, 500, 653, 416, 300, 600, 571, and

028. Clones selected for sampling were those whose size range

included one or more of these 14 numbers. In the example,

clone number 9 was selected twice, resulting in a total of 13

sample clones for the orchard with 6 sample ramets in clone 9.

Selection of sample strobili. Random number tables were

generated with program A to facilitate the selection of sample

clusters in the southeast-crown quadrants of sample trees

(table 2). The control list of program A was initiated under

TSO with the command:

EXEC 'UF.A#######.RANDOM.CLIST'

The program responded with the "prompt":

ENTER CODE FOR TOTAL NUMBER OF CLUSTERS

IN THE SOUTHEAST QUADRANT

IF LESS THAN 25 THEN ENTER A

IF 25 ~0 95 THEN ENTER B

IF MORE THAN 95 THEN ENTER C

'Fatzinger, Carl W.; Muse, H. David; Miller, Thomas [and

others]. Survey and pest monitoring system for southern pine

seed orchards. Southern Journal of Applied Forestry [in

preparation].

10
The numbers of simulated clusters in the southeast-crown

quadrants of the sample trees in the hypothetical orchard

ranged from 20 to 98. Program A was therefore run three times

to enter each of the responses (A, B, and C) to produce random

number tables encompassing from 20 to 98 clusters per quadrant,

Field data forms and dataset names. Examples of filled-in

field data forms are illustrated in figures 1 through 4. The _

following fully qualified dataset names were assigned to the

simulated datasets:

'UF.A#######.EX8602.INIT86' = first general sample (initial

dataset) taken at beginning of

sampling (Feb. 1986)

'UF.A#######.EX8603.INT86' = first intensive subsample

(Mar. 1986)

'UF.A#######.EX8604.INT86' = second intensive subsample

(Apr. 1986)

'UF.A#######.EX8606.GEN86' = second and last general sample

(June 1986)

'UF.A#######.EX.SEED86' = seed collected for analysis

(Sep. 1987)

Operation of Clone dataset. A "clone dataset" washconstructed, named

Computer Programs 'UF.A#######.EX.CLONE86', and placed on file (table 3). Data

were entered into the clone dataset in list format with at

least one space between variables. The first variable (EX) is

the two-letter code used to identify the orchard. The second

variable is the clone identification number (1 to 30 in the

example). The third and fourth variables in each line of data

represent the relative sizes of clones within the orchard. The

third variable is the number of ramets present in the clone,

and the fourth variable is a measure of previous strobilus

production (numbers of flowers or mature cones) of the clone.

Only one of these last two variables is required but, if one is

not used, it must be represented in the dataset by a zero or a

decimal point.

Yield and damage estimates. Programs C and D provided

estimates of orchard productivity and pest damage using the

data for the first general sample. The operation of these

programs is illustrated by the following lists of 'prompts'

generated by the control lists. Responses to the "prompts"

are underlined and contained within brackets in each of the

examples.

11
Program C was initiated with the command:

EXEC 'UF.A#######.YIELD.CLIST'

The user-friendly "prompts" generated by program C were:

ENTER THE PINE SPECIES FOR WHICH ANALYSIS IS DESIRED.

USE ONE WORD [SLASH]

ENTER THE FULLY QUALIFIED DATASET NAME FOR INITIAL DATA

['UF.A#######.EX8602.INIT86']

IS THERE A FOLLOW-UP DATASET TO BE ANALYZED?

IF YES ENTER Y

IF NO ENTER N [NJ

ENTER SIZE MEASURE TO BE USED IN DEVELOPING ESTIMATES

IF MEASURE IS PREVIOUS YIELD THEN ENTER PY

IF MEASURE IS NUMBER OF RAMETS PER CLONE THEN ENTER NR

OTHERWISE ENTER SR [NR]

ENTER THE FULLY QUALIFIED DATASET NAME FOR CLONE DATA

['UF.A#######.EX.CLONE86']

ENTER 2 DIGIT FLOWER YEAR FOR WHICH YIELDS ARE TO BE

ESTIMATED [86]

ENTER 2 CHARACTER ORCHARD CODE USED IN DATA [EX]

ENTER COMPANY TITLE. USE UP TO THREE WORDS WITH A HYPHEN

BETWEEN WORDS [HYPOTHETICAL-ORCHARD-EXAMPLE]

ENTER LOCATION OF CROWN SAMPLED

IF WHOLE CROWN THEN ENTER WC

IF SE QUADRANT THAN ENTER SE [SE]

ENTER TYPE ANALYSIS DESIRED. CHOICES ARE:

YIELDL, YIELDM, AND YIELDS. FOR A STANDARD ANALYSIS

ENTER YIELDS [YIELDS]

Program D was executed to estimate damage caused by specific

pests and other factors observed during the initial sampling:

EXEC 'UF.A#######.DAMGINT.CLIST'

The program "prompts" were:

ENTER PINE SPECIES FOR WHICH ANALYSIS IS DESIRED.

USE ONE WORD [SLASH]

ENTER THE FULLY QUALIFIED DATASET NAME FOR INITIAL DATA

['UF.A#######.EX8602.INIT86']

ENTER THE NUMBER OF FOLLOW-UP DATASETS TO BE USED IN

THIS ANALYSIS. MINIMUM NUMBER IS 0 AND MAXIMUM NUMBER

IS 12 [O]
ENTER 2 DIGIT FLOWER YEAR FOR WHICH ANALYSIS IS DESIRED

I361

ENTER 2 CHARACTER ORCHARD CODE USED IN DATA [EX]

ENTER COMPANY TITLE. USE UP TO THREE WORDS WITH A

HYPHEN BETWEEN WORDS [HYPOTHETICAL-ORCHARD-EXAMPLE]

ENTER LOCATION OF CROWN SAMPLED

IF WHOLE CROWN THEN ENTER WC

IF SE QUADRANT THAN ENTER SE [SE]

Program D also was used to estimate pest damage for the two

intensive subsamples simulated for March and April. Responses

to the control list were identical to those listed above for

the initial sample with the exception of the response to the

third "prompt. (( This response was changed from [0] to [l] for

the first intensive subsample and to [2] for the second

subsample. The control list program then requested names for

the follow-up datasets; i.e., 'UF.A#######.EX8603.INT86' for

the March observation, and 'UF.A#######.EX8604.INT86' for the

April observation.

A fifth analysis was run for the general sample of data

simulated for the June observation. Program C was again run to

produce estimates of orchard productivity using dataset

'UF.A#######.EX8606.GEN86' as a follow-up dataset.

Simulated data for a seed extraction were the last data

analyzed for the example. Program E was used for these

analyses as follows:

EXEC 'UF.A#######.SEED.CLIST'

The program responded with the following "prompts":

ENTER THE FULLY QUALIFIED DATASET NAME FOR SEED DATA

['UF.A#######.EX.SEED86']

ENTER THE FULLY QUALIFIED DATASET NAME FOR INITIAL DATA

['UF.A#######.EX8602.INIT86']

ENTER THE 2 CHARACTER ORCHARD CODE USED IN THE DATA [EX]

ENTER THE COMPANY TITLE. USE UP TO THREE WORDS WITH

A HYPHEN BETWEEN WORDS [HYPOTHETICAL-ORCHARD-EXAMPLE]

ENTER 2 DIGIT FLOWER YEAR FOR WHICH ANALYSIS IS DESIRED

C871

ENTER SPECIES FOR WHICH ANALYSIS IS DESIRED [SLASH]

13
Table 1. --Example of procedure used for selecting sample clones from a

hypothetical 30 clone seed orchard with probability proportional to size

Size Accumulated Size Random Clones

(No. ramets) Clone size range numbers selected

(No. ramets) (No. ramets)

26 98 l- g8 28 26

3 194 99-194 155 3

;i 1 5 272 273-334 195-272 295, 300

60 7' 335-394 375 7'

58

4" ?;:

395-452 416

43 463 t

;fl 30 17 531 565

g;;:

532-565 500 30

27 28 592 566-592 571 28

26 29 618 593-618 600 29

25 10 643 619-643

2 4 5 667 644-667 653 5

20 1 1 687 668-687

19 1 4 706 688-706

19 2 ;zz 719 2

1 7 1 2

16 2318 ::i

1 2 1 3 786 775-786 783 13

12 2 0 798

1 2 19 810

; 27 21 819 828 820-828 823

8 22 836 829-836

2 1

8 24 844 837-844

fi 25 1 850 854 845-850 851-854

4 16 858

2 8 860

1 4
Table 2.-- Example of a random number table generated with Program A for

selection of sample clusters in the southeast-crown quadrant of sample

tree number 4 in the example

RANDOM NUMBERS FOR A TOTAL OF 50 CLUSTERS

SET 1 1 6 lg 24 33 37 38 41 46 49

SET 2 4 10 13 16 22 26 27 38 41 44

SET 3 1 2 4 14 26 27 28 29 43 46

SET 4 3 6 7 14 25 27 34 40 43 44

SET 5 4 6 14 18 25 30 33 34 41 46

SET 6 3 7 14 18 21 22 23 25 34 4g

SET 7 3 12 20 22 23 29 31 33 40 48

SET 8 1 11 14 23 26 27 31 36 38 46

SET 9 2 12 16 23 29 33 36 43 48 49

SET 10 6 11 12 21 22 25 26 28 31 43

.

.

.

SET 30 7 16 23 24 30 33 37 4 1 42 46

15
Table 3. --Example of the clone dataset ('UF.A#######.EX.CLONE86') used

for the hypothetical orchard in this Paper

Ex

EX

Ex

Ex

Ex

EX

EX

'EX

Ex

E X

EX

Ex

EX

Ex

EX

Ex

Ex

EX

E x

EX

EX

Ex

EX

Ex

Ex

Ex

EX

EX

E x

EX

1 1

1 2

l3

1 4

1 5

1 6

1 7

1 8

19

2 0

2 1

22

4;

2 5

2 6

2 7

2 8

29

3 0

1 7

1 2

:'8

3::

1 6

1 2

1 2

9

8

1 6

8

4

9 8

9

2 7

2 6

3 6

6

$3

2 4

5 8

6 0

6;

2 5

2 0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1 6
STANDARD PROCEDURE OPTIONS

1 SELECT SAMPLE TREES 1

14 SAMPLE CLONES (PPS) x

3 SAMPLE RAMETS / CLONE =

42 SAMPLE TREES

I I

I I

1 SELECT SAMPLE AREA OF CROWN 1

I

MAKE INITIAL COUNTS OF FEMALE STROBILUS CLUSTERS IN TOTAL-CROWN

AREA AND TAG 10 % SAMPLE OF CLUSTERS IN EACH SAMPLE QUADRANT

1 SELECT FREQUENCY OF OBSERVATIONS 1

COLLECT SEED SAMPLES (6 MATURE CONES / SAMPLE TREE)

Figure 1. --Schematic of sampling procedure identifying several options

available in the system: (1) methods for selection of sample trees with the

selection proportional to size (PPS) or simple random sampling (SRS)

techniques, (2) whole-crown and southeast-crown quadrant methods for sampling

tree crowns, and (3) modification in frequency of sampling.

17
1 8
General Sample Data

(IFPM Coop.)

Orchard = IFPM Coop. example

Previous date =

Observations marked by l

contain one or more mistakes

Species = Slash

Sample tree = 8

Flower year = 88

I

ta

-22

Yr s

001

002

003

004

005

006

007

008

009

010

Current condition lition

Cl

Date

mo d

Previous cof

2

s Cl Cl

co

2

5

3 Pl

3 Pl

2 Pl

5

4

5 Pl

3

2

E

2

8

.-8

iii g WC’

01 8

01 8

01 8

01 8

01 8

01 8

01 8

01 8

01 8

01 8

CIM CIM CIM

2 0 fo2

El3 5 5

Ex

Ex

EX

EX

EX

EX 55

4 4

6 4 PC’/ Ao/

EX

EX

EX 3 0 A03

Ex 2 2

Figure 3.-- Example of the follow-up data forms generated by program B for the

second observation period in the hypothetical seed orchard.

19
EXA/VlPdE Sheet of

1 12 13 14 151 6 17 16 19 110 11112113 14~15~16~17~18~19~20 21122123124125 2 6 2712 29 30131132 33 34135(36137(38139

i!

-b

I'Jc

I

I

I

I

I

I

I

I

I

I

I

I

I

I

Seed analysis

X-ray interpretation

]2 ] 314 ] 5] 6 ]7 ]8 ]9 ]10]11]12]13]14]15]16]17]18]19]20~21]22]23]24]25]26]27]28~29]~]31]32~~~~~35]~~37~38~39

Figure 4. --Example of the data form for seed analyses used to record results

of seed extraction, radiographic analyses, and germination tests.
Appendix II

Field Data Forms

Initial Data Forms The two types of initial data forms are illustrated in, and can

be copied directly from, this Appendix (figs. 5 and 6). All

data entries must be right-justified within the columns.

Information used to identify the orchard, the sample tree, the

type and size of sample, and the observation date (~01s. l-33

and 67-70) is entered only once in the first row of each

initial data form (figs. 2 and 7). Changes in the information

listed in columns 19 to 33 of the form for whole-crown sampling

(fig. 7) or columns 28-33 of the form for southeast-crown

quadrant sampling (fig. 2) are made only once in the row where

the change occurs, The information listed in columns 1 to 33

and 67 to 70, however, must be duplicated by the keypunch

operator for each row of data OP the form that follows the

entry before it is filed as a dataset.

Different types of information are entered in columns 18 to 26

of the initial forms for the southeast-crown quadrant and

whole-crown sampling procedures. The quadrant and height level

sampled, the type of sample (general or intensive subsample),

and the total number of clusters present in the quadrant are

listed in columns 19 to 26 of the form for whole-crown

samples. Columns 18 to 26 of the form for southeast-crown

quadrant samples are used ta record the numbers of total

clusters outside and inside the southeast quadrant, and the

type of sample taken.

Columns 1 through 17 and 27 through 80 of both forms are

identical. A two-digit code used to identify the species of

pine sampled is entered in columns 5 and 6:

Slash pine 0 1

Loblolly pine 02

Longleaf pine 03

Shortleaf pine 04

Virginia pine 05

Sand pine 06

Columns 9 to lb (clone number) and columns 35 to 37 (cluster

number) must contain zeros instead of blanks in unused spaces.

The cluster numbers (tag numbers) and numbers of female

strobili present in the sample clusters are recorded in columns

35 to 40.

Columns 42 through 64 are used to record observations on the

survival of strobili and causes of damage within the sample

clusters. The number of undamaged (sound) strobili is recorded

in columns 42 to 44, and the causes of injury and numbers of

injured or missing strobili are recorded under the five columns

headed "CIM," Single letter or number codes for the causes of

injuries are listed on the left side of the data sheet and are

recorded under the columns headed "C." The numbers of strobili

21
Follow-Up Data

Forms

Seed Data Forms

injured but still present in the cluster are recorded under the

"I" columns, and the numbers of strobili missing from the

sample clusters are recorded under the "M" columns. For

example, a “CIM” entry might be "P24" indicating that within

one sample cluster' two strobili were injured by thrips and

four strobili were killed by thrips. If more than 9 strobili

within a sample cluster are affected by the same factor, the

information can be recorded in more than one "CIM" column by

repeating the cause code letter; e.g., 'P21 ~81” indicates that

within the same cluster, 10 strobili (P2- + ~8 ) were injured

by thrips and 2 (P-1 + P-1) were killed by thrips. The last

two digits of the year during which a sample was taken are

entered in columns 67 to 68 and the two-digit number for the

month of sampling is entered in columns 69 and 70.

Follow-up data forms are produced by program B for each

observation after an initial dataset is on file (fig. 3). One

set of forms is produced for each sample tree to be included in

the next sample. These forms are headed with information

identifying the orchard, year of flowering, sample tree number,

and date of the most recent sample. Only the date of the

current observation and the number and conditions of strobili

in each sample cluster need to be entered on these forms. The

date needs to be entered only once, in the first row of each

data form, but must be duplicated by the keypunch operator for

each row of data following the entry before it is filed as a

dataset. Three-digit codes must be used for entries in the

"CIM" columns. For example, an entry for two strobili missing

with the cause of death unknown should be entered on the form

as "A02" rather than "A2." Likewise, an entry for two strobili

injured by thrips should be entered as "A20" rather than "A2."

Information identifying the source of a seed sample is listed

in columns 1 to 15, and the results of radiographic analyses

and germination tests are recorded in columns 17 to 37 (fig.

8). Information in columns 1 to 9 needs to be entered only

once, in the first row of each data form, but must be

duplicated for each row of data following the entry before it

is filed as a dataset. Changes in this information are made

only once in the row where the change occurs.

22
L 1

23
m

I ‘0I

24
25
Sheet of

1 12 13 415 6 17 16 19 IlOll 12113114 15116117 1 6 19120121122 23124125126 272 2 9 30131 3 2 3 3 34136 36137(36139

Seed analysis

X-ray interpretation

1 12 13 14 151 6 17 16 19 ~10~11~12~13~14~15~16~17~16~19~20~21~22~23~24~25~26~27~~6~29~30~31~32~33~34~35~36~37~38~39

Figure 8. --Seed data form used to record results of seed extraction,

radiographic analyses, and germination tests (for example of data

entries, see fig. 4).

2 6
Appendix III

Guide for the Operation of Five Computer Programs for Producing

Random Numbers, Field Data Forms, Orchard Productivity Estimates,

Damage Estimates, and Seed Analyses

Random Numbers

(Program A)

The control list is executed by the following command:

EXEC 'UF.A#######.RANDOM.CLIST'

Once executed, the "prompts" request information on the total

numbers of strobilus clusters expected in the sampled

quadrant:

ENTER CODE FOR TOTAL NUMBER OF CLUSTERS

IN THE SOUTHEAST QUADRANT

IF LESS THAN 25 THEN ENTER A

IF 25 TO 95 THEN ENTER B

IF MORE THAN 95 THEN ENTER C

Field Data Forms The program is executed with:

(Program B)

EXEC 'UF.A#######.FORMS.CLIST'

The following "prompts" are displayed requesting specific

information on the orchard for which the field data forms are

required:

ENTER TYPE OF SAMPLE FORM DESIRED

IF GENERAL SAMPLE FORM THEN ENTER GEN

IF INTENSIVE SAMPLE FORM THEN ENTER INT

ENTER LOCATION OF CROWN TO BE SAMPLED

IF WHOLE CROWN THEN ENTER WC

IF SE QUADRANT THEN ENTER SE

ENTER TWO DIGIT FLOWER YEAR

ENTER TWO CHARACTER ORCHARD CODE TO BE USED IN DATA

ENTER COMPANY TITLE. USE UP TO THREE WORDS WITH

A HYPHEN BETWEEN WORDS

ENTER CODE TO INDICATE THE NUMBER OF INITIAL AND

FOLLOW-UP DATASETS

IF 1 INITIAL FILE AND 0 FOLLOW-UP FILES THEN

ENTER 1

IF 1 INITIAL FILE AND 1 FOLLOW--UP FILE THEN ENTER

IF f INITIAL FILES AND 1 FOLLOW-UP FILE FOR ONLY

ONE OF THE INITIAL FILES THEN ENTER 3

IF 2 INITIAL FILES AND A FOLLOW-UP FILE FOR EACH

INITIAL FILE THEN ENTER 4

Depending on the numbers entered, the following

"prompts" will appear. Numbers to the left of

statements refer to the numbers entered in the above

step.

2 7
Orchard

Productivity

(Program C)

1.2 ENTER FULLY QUALIFIED DATASET NAME FOR THE INITIAL

FILE

3 ENTER FULLY QUALIFIED DATASET NAME FOR THE INITIAL

FILE WITH NO CORRESPONDING FOLLOW-UP FILE

3 ENTER FULLY QUALIFIED DATASET NAME FOR REMAINING

INITIAL FILE

4 ENTER FULLY QUALIFIED DATASET NAME FOR FIRST INITIAL

FILE

4 ENTER FULLY QUALIFIED DATASET NAME FOR SECOND

INITIAL FILE

2,394 ENTER CODE TO INDICATE MOST RECENT GENERAL AND/OR

INTENSIVE SAMPLES

IF A GENERAL SAMPLE AND NO INTENSIVE SAMPLE THEN

ENTER 1

IF NO GENERAL SAMPLE AND AN INTENSIVE SAMPLE THEN

ENTER 2

IF A GENERAL SAMPLE AND AN INTENSIVE SAMPLE THEN

ENTER 3

Numbers in parentheses to the left of the statements

refer to the code numbers entered in the previous

step.

(1.3) ENTER THE FULLY QUALIFIED DATASET NAME OF MOST

RECENT GENERAL SAMPLE

(2,3) ENTER THE FULLY QUALIFIED DATASET NAME OF MOST

RECENT INTENSIVE SAMPLE

The orchard productivity or "yield" program is

initiated by the command:

EXEC 'UF.A#######.YIELD.CLIST'

The control list program responds with the following

"prompts":

ENTER THE PINE SPECIES FOR WHICH ANALYSIS IS

DESIRED. USE ONE WORD (e.g., SLASH)

ENTER THE FULLY QUALIFIED DATASET NAME FOR INITIAL

DATA

IS THERE A FOLLOW-UP DATASET TO BE ANALYZED?

IF YES ENTER Y

IF NO ENTER N

If a Y is entered the program responds with:

2 8
ENTER THE FULLY QUALIFIED DATASET NAME FOR

FOLLOW-UP DATA

ENTER SIZE MEASURE TO BE USED IN DEVELOPING ESTIMATES

IF MEASURE IS PREVIOUS YIELD THEN ENTER PY

IF MEASURE IS NUMBER OF RAMETS PER CLONE THEN

ENTER NR OTHERWISE ENTER SR

If SR is entered the program responds with:

ENTER NUMBER OF TREES IN ORCHARD

ENTER THE FULLY QUALIFIED DATASET NAME FOR CLONE

DATA

ENTER 2 DIGIT FLOWER YEAR FOR WHICH YIELDS ARE TO BE

ESTIMATED

ENTER 2 CHARACTER ORCHARD CODE USED IN DATA

ENTER COMPANY TITLE. USE UP TO THREE WORDS WITH A

HYPHEN BETWEEN WORDS

ENTER LOCATION OF CROWN SAMPLED

IF WHOLE CROWN THEN ENTER WC

IF SE QUADRANT THAN ENTER SE

ENTER TYPE ANALYSIS DESIRED. CHOICES ARE:

YIELDL, YIELDM, AND YIELDS. FOR A STANDARD

ANALYSIS ENTER YIELDS

The program will produce three types of yield analyses. The

L, M, and S suffixes to the word YIELD represent long, medium,

and short analyses, respectively. The short analysis program

(YIELDS) is the one generally selected and provides all

estimates of strobilus productivity and survival. The medium

analysis program (YIELDM) provides lists of factors used in

estimating clonal and orchard yields in addition to the output

of the YIELDS program. The long analysis program (YIELDL) is

used to analyze data from four directional crown quadrants and

two height levels.

Damage Estimates The damage estimate program is executed with:

Program (D)

EXEC 'UF.A#######.DAMGINT.CLIST'

The program responds with the following "prompts":

ENTER PINE SPECIES FOR WHICH ANALYSIS IS DESIRED.

USE ONE WORD (e.g. "LOBLOLLY")

ENTER THE FULLY QUALIFIED DATASET NAME FOR INITIAL

DATA

ENTER THE NUMBER OF FOLLOW-UP DATASETS TO BE USED IN

THIS ANALYSIS. MINIMUM NUMBER IS 0 AND MAXIMUM

NUMBER IS 12

2 9
Depending on the number entered in the above step, the

program will step through a sequence of "prompts" to

allow entry of dataset names for each follow-up dataset

as follows:

ENTER THE FULLY QUALIFIED DATASET NAME FOR THE

FIRST FOLLOW-UP DATASET

ENTER THE FULLY QUALIFIED DATASET NAME FOR THE

NUMBER 2 FOLLOW-UP DATASET

ENTER THE FULLY QUALIFIED DATASET NAME FOR THE

NUMBER 3 FOLLOW-UP DATASET

ENTER THE FULLY QUALIFIED DATASET NAME FOR THE

NUMBER 12 FOLLOW-UP DATASET

The program then continues:

ENTER 2 DIGIT FLOWER YEAR FOR WHICH ANALYSIS IS

DESIRED

ENTER 2 CHARACTER ORCHARD CODE USED IN DATA

ENTER COMPANY TITLE. USE UP TO THREE WORDS WITH A

HYPHEN BETWEEN WORDS

ENTER LOCATION OF CROWN SAMPLED

IF WHOLE CROWN THEN ENTER WC

IF SE QUADRANT THAN ENTER SE

Seed Analyses

(Program E)

This program is executed by entering:

EXEC 'UF.A#######.SEED.CLIST'

The program then responds:

ENTER THE FULLY QUALIFIED DATASET NAME FOR SEED

DATA

ENTER THE FULLY QUALIFIED DATASET NAME FOR INITIAL

DATA

ENTER THE 2 CHARACTER ORCHARD CODE USED IN THE DATA

ENTER THE COMPANY TITLE. USE UP TO THREE WORDS WITH

A HYPHEN BETWEEN WORDS

ENTER 2 DIGIT FLOWER YEAR FOR WHICH ANALYSIS IS

DESIRED

ENTER SPECIES FOR WHICH ANALYSIS IS DESIRED

3 0
I---

---------d--_------------

Fatzinger, Carl W.; Muse. H. David; Miller, Thomas; I

I \

Bhattacharyya. Helen T. 1988. Estimating cone and seed I

production and monitoring pest damage in southern pine seed

/

orchards. Res. Pap. SE-271. Asheville, N.C.: U.S. I

Department of Agriculture, Forest Service, Southeastern I

I

Forest Experiment Station. 30 PP.

Field sampling procedures and computer programs are described

for monitoring seed production and pest damage in southern pine [

I

I

seed orchards. The system estimates total orchard yields of I

female strobili and seeds, quantifies pest damage, determines

times of year when losses occur, and produces life tables for

female strobili. An example is included to illustrate the

sampling procedures and the operation of user-friendly computer

programs.

I1

1 Keywords: Cone and seed insects, cone and seed diseases, I

, sampling, seed orchard production, survey. I

Fatzinger, Carl W.; Muse, H. David; Miller, Thomas;

Bhattacharyya. Helen T. lg88. Estimating cone and seed

production and monitoring pest damage in southern pine seed

orchards. Res. Pap. SE-271. Asheville, N.C.: U.S.

Department of Agriculture, Forest Service. Southeastern

Forest Experiment Station. 30 PP.

Field sampling procedures and computer programs are described

for monitoring seed production and pest damage in southern pine

seed orchards. The system estimates total orchard yields of

female strobili and seeds, quantifies pest damage. determines

times of year when losses occur, and produces life tables for

female strobili. An example is included to illustrate the

sampling procedures and the operation of user-friendly computer

programs.

Keywords: Cone and seed insects, cone and seed diseases,

sampling, seed orchard production, survey.

‘1

I

I