Title: Data to Support Fish Stock Assessment ('FSA') Package
Version: 0.4.1
Date: 2023-8-23
Description: The datasets to support the Fish Stock Assessment ('FSA') package.
URL: https://fishr-core-team.github.io/FSAdata/
BugReports: https://github.com/fishR-Core-Team/FSAdata/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
LazyData: true
Depends: R (≥ 3.0.0)
Suggests: dplyr, fishmethods, FSA, knitr, pkgdown, readxl, rmarkdown
Encoding: UTF-8
RoxygenNote: 7.2.3
NeedsCompilation: no
Packaged: 2023-08-24 14:31:02 UTC; derek
Author: Derek Ogle ORCID iD [aut, cre]
Maintainer: Derek Ogle <derekogle51@gmail.com>
Repository: CRAN
Date/Publication: 2023-08-24 15:00:02 UTC

Data to support the FSA package.

Description

This package contains data to support the FSA package.

Usage

FSAdataTopics

Format

An object of class character of length 16.

Details

This package contains additional data files that can be used for common fisheries stock assessment methods described in the FSA package and on the fishR website.

The help files for these datasets are embedded with topics that can be searched to find data files that can be analyzed with those topics. For example, use the following commands to find data files for the corresponding topics.

help.search("Length Expansion",package=c("FSAdata","FSA")) Expand subsampled lengths.
help.search("Length Conversion",package=c("FSAdata","FSA")) Convert between length types.
help.search("Age Comparison",package=c("FSAdata","FSA")) Ageing (error, precision, or comparison).
help.search("Age-Length Key",package=c("FSAdata","FSA")) Age-Length Key data.
help.search("Weight-Length",package=c("FSAdata","FSA")) Weight-length model data.
help.search("Length Frequency",package=c("FSAdata","FSA")) Length frequency data.
help.search("Size Structure",package=c("FSAdata","FSA")) Size structure data.
help.search("Abundance",package=c("FSAdata","FSA")) Data for abundance estimates.
help.search("Capture-Recapture",package=c("FSAdata","FSA")) Mark-recapture data.
help.search("Mark-Recapture",package=c("FSAdata","FSA")) Mark-recapture data.
help.search("Capture History",package=c("FSAdata","FSA")) Capture history mark-recapture (compare to summarized data) data.
help.search("Petersen",package=c("FSAdata","FSA")) Petersen mark-recapture (closed population, single sample).
help.search("Schnabel",package=c("FSAdata","FSA")) Schnabel mark-recapture (closed population, multiple samples).
help.search("Jolly-Seber",package=c("FSAdata","FSA")) Jolly-Seber mark-recapture (open population, multiple samples).
help.search("Depletion",package=c("FSAdata","FSA")) Depletion (Leslie, DeLury) methods for estimating abundance.
help.search("Removal",package=c("FSAdata","FSA")) Removal (K-pass) methods for estimating abundance.
help.search("Mortality",package=c("FSAdata","FSA")) Data for mortality estimation.
help.search("Catch curve",package=c("FSAdata","FSA")) Catch curve.
help.search("Growth",package=c("FSAdata","FSA")) Growth model data.
help.search("Recruitment",package=c("FSAdata","FSA")) Stock-recruitment and recruitment time-series data.
help.search("Maturity",package=c("FSAdata","FSA")) Maturity data.

Additional fisheries-related data sets are in the FSA and fishmethods packages.

Internal functions used in FSAdata.

Description

Internal functions used in FSAdata.

Usage

.onAttach(lib, pkg, ...)

Ages and lengths of Araucanian Herring from Chilean waters.

Description

Ages and lengths of Araucanian Herring (Strangomera bentincki) from Chilean waters.

Format

A data frame with the following 2 variables:

age

Age in years.

len

Total length (to nearest 0.5 cm).

Topic(s)

Source

From figure 9 of Cubillos, L.A., D.F. Arcosa, D.A. Bucareya, M.T. Canalesa. 2001. Seasonal growth of small pelagic fish off Talcahuano, Chile (37S, 73W): A consequence of their reproductive strategy to seasonal upwelling? Aquatic Living Resources, 14:115-124. CSV file

Examples

data(AHerringChile)
str(AHerringChile)
head(AHerringChile)
plot(len~age,data=AHerringChile)

Characteristics of a sample of West African rivers.

Description

Characteristics of a sample of West African rivers.

Format

A data frame of 39 observations on the following 6 variables:

river

name of the river.

richness

fish species richness.

surface

surface area in km^2.

disch

mean annual discharge in \frac{m^3}{s}.

vegdiv

terrestrial vegetation diversity (Shannon's diversity index of vegetation in drainage).

forperc

percentage of drainage area covered by lowland rain forest.

Topic(s)

Source

From Table 1 in Hugueny, B. 1989. West African rivers as biogeographic islands: species richness of fish communities. Oecologia 79:236-243. CSV file

Examples

data(AfricanRivers)
str(AfricanRivers)
head(AfricanRivers)

Ages of Lake Huron Alewife assigned from otoliths and scales.

Description

Ages of Alewife (Alosa pseudoharengus) assessed from otoliths and scales.

Format

A data frame of 104 observations on the following 2 variables:

otoliths

Age assigned from examination of otoliths

scales

Age assigned from examination of scales

Topic(s)

Source

From Table 1A of Hoenig, J.M., M.J. Morgan, and C.A. Brown. 1995. Analysing differences between two age determination methods by tests of symmetry. Canadian Journal of Fisheries And Aquatic Systems, 52:364-368. Originally from O'Gorman, R., D.H. Barwick, and C.A. Bowen. 1987. Discrepancies between ages determined from scales and otoliths for alewives from the Great Lakes. pp. 203-210 In. Summerfelt, R.C. and G.E. Hall (Eds.) Age and Growth of Fish. Iowa State University Press, Ames, IA. CSV file

Examples

data(AlewifeLH)
str(AlewifeLH)
head(AlewifeLH)
plot(scales~otoliths,data=AlewifeLH)
xtabs(~otoliths+scales,data=AlewifeLH)

Ages and lengths of Anchoveta from Chilean waters.

Description

Ages (in months) and lengths of Anchoveta (Engraulis ringens) from central Chilean waters.

Format

A data frame with 207 observations of the following 3 variables:

age.mon

Age in months.

tl.cm

Total length (cm).

cohort

Year-class.

Topic(s)

Source

Directly from the authors of Cubillos, L.A., D.F. Arcosa, D.A. Bucareya, M.T. Canalesa. 2001. Seasonal growth of small pelagic fish off Talcahuano, Chile (37S, 73W): A consequence of their reproductive strategy to seasonal upwelling? Aquatic Living Resources 14:115-124. Data were in Figure 9. CSV file

Examples

data(AnchovetaChile)
str(AnchovetaChile)
head(AnchovetaChile)
AnchovetaChile$age <- AnchovetaChile$age.mon/12
plot(tl.cm~age,data=AnchovetaChile)

Fish information from samples collected from Big Hill Reservoir, KS, 2014.

Description

Fish information from samples collected from Big Hill Reservoir, KS, in May, 2014.

Format

A data frame with 266 observations on the following 6 variables.

UID

Unique sample identification number (see BGHRsample)

fishID

Unique fish identification number

specCode

Numeric code for each species (116=“Smallmouth Bass”, 118=“Largemouth Bass”, and 122=“Bluegill”)

length

Total length (mm)

weight

Weight (g)

count

Number of fish sampled of that species and length

Topic(s)

Note

Used in the Introductory Fisheries Analyses with R book.

Source

Obtained directly from Ben Neely. CSV file

See Also

See BGHRfish for individual fish collected in these samples.

Examples

data(BGHRfish)
str(BGHRfish)
head(BGHRfish)

Information for each electrofishing sample from Big Hill Reservoir, KS, 2014.

Description

Information for each electrofishing sample from Big Hill Reservoir, KS, in May, 2014.

Format

A data frame with 20 observations on the following 4 variables.

UID

Unique sample identification number

date

Data sample was collected

loc

Location code for where the sample was collected

effort

Effort (minutes) expended for the sample

Topic(s)

Note

Used in the Introductory Fisheries Analyses with R book.

Source

Obtained directly from Ben Neely. CSV file

See Also

See BGHRfish for individual fish collected in these samples.

Examples

data(BGHRsample)
str(BGHRsample)
head(BGHRsample)

Stock and recruitment data for Barndoor Skate from Georges Bank, 1966-2007.

Description

Stock and recruitment data for Barndoor Skate (Dipturus laevis) from Georges Bank for three seasons.

Format

A data frame with 31 observations on the following 4 variables.

spawners

a numeric vector giving CPUE of spawning fish

recruits

a numeric vector containing the CPUE of recruits

year

a numeric vector containing the year of the survey (recruits have been properly lagged (3 years) to match with spawners)

season

a factor containing the season of capture (fall, spring, winter)

Topic(s)

Note

Only years within each season where more than one spawner and more than one recruit were captured were recorded. The authors noted that the Beverton-Holt model could NOT be fit to the winter data.

Source

Estimated (using digitize) from figures 4-6 in Gedamke, T., J.M. Hoenig, W.D. DuPaul, and J.A. Musick. 2009. Stock-recruitment dynamics and the maximum population growth rate of the barndoor skate on Georges Bank. North American Journal of Fisheries Management 29:512-526. CSV file

Examples

data(BSkateGB)
str(BSkateGB)
head(BSkateGB)
op <- par(mfrow=c(3,2),pch=19)
plot(recruits~year,data=BSkateGB,subset=season=="fall",type="b",main="fall")
plot(recruits~spawners,data=BSkateGB,subset=season=="fall",main="fall")
plot(recruits~year,data=BSkateGB,subset=season=="spring",type="b",main="spring")
plot(recruits~spawners,data=BSkateGB,subset=season=="spring",main="spring")
plot(recruits~year,data=BSkateGB,subset=season=="winter",type="b",main="winter")
plot(recruits~spawners,data=BSkateGB,subset=season=="winter",main="winter")
par(op)

Catch-at-age for Suwanee and Largemouth Bass.

Description

Catch-at-age for Suwanee (Micropterus notius) and Largemouth Bass (Micropterus salmoides) collected from several lakes in Florida, 2001-2002.

Format

A data frame with 39 observations on the following 5 variables.

species

Species of bass (Suwanee and Largemouth)

loc

Location (SantaFe, Wacissa, Withlacoochee, Ochlockonee)

year

Year (2001, 2002)

num

Number of fish captured

age

Age of fish at capture

Topic(s)

Source

From Figure 2 of Bonvechio, T.F., M.S. Allen, and R.L. Cailteux. 2005. Relative Abundance, Growth, and Mortality of Suwannee Bass in Four Florida Rivers. North American Journal of Fisheries Management 25:275-283. CSV file

Examples

data(BassFL)
str(BassFL)
head(BassFL)
op <- par(mfrow=c(3,2),mar=c(3,3,2,1),mgp=c(1.75,0.5,0),tcl=-0.2,pch=19)
plot(log(num)~age,data=BassFL,subset=(loc=="SantaFe" & year==2001 & species=="Suwanee"),
  ylim=c(0,max(log(num))),main="Suwanee, Santa Fe")
points(log(num)~age,data=BassFL,subset=(loc=="SantaFe" & year==2002 & species=="Suwanee"),col="red")
legend("topright",legend=c("2001","2002"),col=c("black","red"),pch=19)
plot(log(num)~age,data=BassFL,subset=loc=="Wacissa" & year==2002 & species=="Suwanee",
 ylim=c(0,max(log(num))),main="Suwanee, Wacissa")
plot(log(num)~age,data=BassFL,subset=loc=="Withlacoochee" & year==2002 & species=="Suwanee",
 ylim=c(0,max(log(num))),main="Suwanee, Withlacoochee")
plot(log(num)~age,data=BassFL,subset=(loc=="SantaFe" & year==2001 & species=="Largemouth"),
 ylim=c(0,max(log(num))),main="Largemouth, Santa Fe")
points(log(num)~age,data=BassFL,subset=(loc=="SantaFe" & year==2002 & species=="Largemouth"),
 col="red")
legend("topright",legend=c("2001","2002"),col=c("black","red"),pch=19)
plot(log(num)~age,data=BassFL,subset=loc=="Ochlockonee" & year==2001 & species=="Largemouth",
 ylim=c(0,max(log(num))),main="Largemouth, Ochlockonee")
points(log(num)~age,data=BassFL,subset=(loc=="Ochlockonee" & year==2002 & species=="Largemouth"),
 col="red")
legend("topright",legend=c("2001","2002"),col=c("black","red"),pch=19)
par(op)

Biological data for Black Drum from Virginia waters of the Atlantic Ocean, 2001.

Description

Biological data (lengths, weights, ages (from otoliths), and sex) for Black Drum (Pogonias cromis) from Virginia waters of the Atlantic Ocean, 2001.

Format

A data frame with 141 observations on the following 9 variables.

year

Year of capture (all 2001)

agid

Unique identification number

spname

Species name (all “Black Drum”)

month

Month of capture

day

Day of capture

weight

Weight (lbs) – most are missing

tl

Total length (mm)

sex

Sex (female, male, and unknown)

otoage

Age (yrs; from otoliths)

Topic(s)

Note

Used in the Introductory Fisheries Analyses with R book.

Source

Obtained directly from the Virginia Marine Resources Commission via Hank Liao. CSV file

Examples

data(BlackDrum2001)
str(BlackDrum2001)
head(BlackDrum2001)
plot(tl~otoage,data=BlackDrum2001)

Stock and recruitment data for Lake Huron Bloaters, 1981-1996.

Description

Egg deposition and relative abundance of age-3 Lake Huron Bloaters (Coregonus hoyi) by year, 1981-1996.

Format

A data frame of 16 observations on the following 3 variables:

year

Year of data (1981-1996)

eggs

Millions of eggs deposited

age3

Relative abundance of age-3 fish

Topic(s)

Source

From (approximately) Figure 7 of Schaeffer, J.S. 2004. Population dynamics of bloaters Coregonus hoyi in Lake Huron, 1980-1998. Ann Zool Fennici. 41:271-279. CSV file

Examples

data(BloaterLH)
str(BloaterLH)
head(BloaterLH)
op <- par(mfrow=c(1,2),pch=19)
plot(eggs~year,data=BloaterLH,type="l")
plot(eggs~age3,data=BloaterLH)
par(op)

Ages and lengths of Blue Catfish.

Description

Ages and total lengths of Blue Catfish (Ictalurus furcatus) collected form the Wilson Reservoir on the Tennessee River, AL.

Format

A data frame with 119 observations on the following 2 variables.

age

Age (from otoliths)

tl

Total length (mm)

Topic(s)

Source

From (approximately) Figure 2 of Maceina, M.J. 2007. Use of piecewise nonlinear models to estimate variable size-related mortality rates. North American Journal of Fisheries Management 27:971-977. CSV file

Examples

data(BlueCatfish)
str(BlueCatfish)
head(BlueCatfish)
plot(tl~age,data=BlueCatfish)

Catch and effort data for male Blue Crabs.

Description

Catch and effort data for a population of male Blue Crabs (Callinectes sapidus) for a 12-week period.

Format

A data frame with 12 observations on the following 2 variables.

catch

A numeric vector of pounds of Blue Crab caught.

effort

A numeric vector of lines used per day to catch Blue Crab.

Topic(s)

Source

From Fischler, K.J. 1965. The use of catch-effort, catch-sampling, and tagging data to estimate a population of blue crabs. Transactions of the American Fisheries Society 94:287-310. CSV file

Examples

data(BlueCrab)
str(BlueCrab)
BlueCrab

Ages of Bluefish assigned from otoliths by two readers.

Description

Ages assigned to Bluefish (Pomatomus saltatrix) otoliths by two readers.

Format

A data frame with 445 observations on the following 2 variables.

r1

Ages assigned by the first reader

r2

Ages assigned by the second reader

Topic(s)

Source

From Figure 2 in Chapter 3 (Bluefish) of the VMRC Final Report on Finfish Ageing, 2003 by the Center for Quantitative Fisheries Ecology at Old Dominion University. CSV file

Examples

data(BluefishAge)
str(BluefishAge)
head(BluefishAge)
plot(r1~r2,data=BluefishAge)

Length-at-marking and recapture and time-at-large of Bluegill.

Description

Length-at-marking and recapture and time-at-large for Bluegill (Lepomis macrochirus) originally captured in Spring 2010 from Inch Lake, Wisconsin.

Format

A data frame with 61 observations on the following 5 variables:

tag

Unique Floy tag number.

lenMark

length (mm) at tagging.

lenRecap

Length (mm) at recapture.

deltaLen

Change in length (mm).

deltaTime

Time-at-large (yrs).

Topic(s)

Source

These unpublished data are from Derek H. Ogle, Northland College. Do not use for other than educational purposes without permission from the source. CSV file

Examples

data(BluegillIL)
str(BluegillIL)
head(BluegillIL)
plot((lenRecap-lenMark)~deltaTime,data=BluegillIL)

Lengths and weights for Bluegill from Lake Mary, MN.

Description

Lengths (standard, fork, and total) and weights for Bluegill (Lepomis macrochirus) collected from Lake Mary, Minnesota.

Format

A data frame with 100 observations on the following 5 variables:

sernum

Unique serial number

sl

Standard length (mm)

fl

Fork length (mm)

tl

Total length (mm)

wght

Weight (g)

Topic(s)

Source

CSV file

See Also

lakemary in alr3 for a different sample of Bluegill from Lake Mary that has length and age.

Examples

data(BluegillLM)
str(BluegillLM)
head(BluegillLM)
op <- par(mfrow=c(3,2),pch=19)
plot(wght~sl,data=BluegillLM)
plot(wght~fl,data=BluegillLM)
plot(wght~tl,data=BluegillLM)
plot(tl~fl,data=BluegillLM)
plot(tl~sl,data=BluegillLM)
plot(fl~sl,data=BluegillLM)
par(op)

Subampled lengths of Bluntnose Minnows from Inch Lake, WI.

Description

Total lengths for a subsample from 144 Bluntnose Minnows (Pimephales notatus) from Inch Lake, WI in May, 2007.

Format

A data frame of 25 observations on the following 3 variables:

netID

a netID factor (all 41)

species

species name (all Bluntnose)

tl

total length (inches to nearest 0.1)

Topic(s)

Source

Derek H. Ogle, personal collection. CSV file

See Also

InchLake1, InchLake2.

Examples

data(BluntnoseIL1)
str(BluntnoseIL1)
head(BluntnoseIL1)

Ages and lengths of Australian Bonito.

Description

Ages and lengths of Australian Bonito (Sarda australis).

Format

A data frame with the following 3 variables:

sex

Sex (Female, Juvenile, Male).

age

Age in decimal years.

fl

Total length (to nearest 0.1 cm).

Topic(s)

Source

From figure 3 of Stewart, J., W. Robbins, K. Rowling, A. Hegarty, and A. Gould. 2013. A multifaceted approach to modelling growth of the Australian bonito, Sarda australis (Family Scombridae), with some observations on its reproductive biology. Marine and Freshwater Research 64:671-678. CSV file

Examples

data(Bonito)
str(Bonito)
head(Bonito)
plot(fl~age,data=Bonito)

Stock and recruitment data for Brook Trout from Ball Creek, NC, 1991-2004.

Description

Stock and recruitment data for Brook Trout (Salvelinus fontinalis) from Ball Creek, NC, 1991-2004.

Format

A data frame with 10 observations on the following 2 variables.

adult

a numeric vector giving autumn adult density (number per square meter)

yoy

a numeric vector giving autumn YOY density (number per square meter) in following year

Topic(s)

Note

The authors fit a linear model to the stock-recruit relationship.

Source

From (approximately) Figure 5 in Grossman, G.D., R.E. Ratajczak, C.M. Wagner, and J.T. Petty. 2010. Dynamics and regulation of the southern brook trout (Salvelinus fontinalis) population in an Appalachian stream. Freshwater Biology 55:1494-1508. CSV file

Examples

data(BrookTroutNC)
str(BrookTroutNC)
head(BrookTroutNC)
plot(adult~yoy,data=BrookTroutNC)

Catches in removal events for Brook Trout in the Nashwaak Experimental Watersheds Project.

Description

Catches in removal events for Brook Trout (Salvelinus fontinalis) in two streams in the the Nashwaak Experimental Watersheds Project on multiple dates.

Format

A data frame of 16 observations on the following 7 variables:

stream

Stream (UNM=Upper Narrows Mountain Brook and Hay=Hyaden Brook).

section

Section of stream. See source.

date

Data of collections.

first

Catch on the first removal pass.

second

Catch on the second removal pass.

third

Catch on the third removal pass.

fourth

Catch on the fourth removal pass.

Topic(s)

Source

From Table 1 in Schnute, J. 1983. A new approach to estimating populations by the removal method. Canadian Journal of Fisheries and Aquatic Sciences, 40:2153-2169. CSV file

See Also

See BrookTroutNEWP1 for these data AND the results from Schnute (1983).

Examples

data(BrookTroutNEWP)

## extract data for one stream, section, and date (e.g., 3rd row)
BrookTroutNEWP[3,]

Catches in removal events for Brook Trout in the Nashwaak Experimental Watersheds Project.

Description

Catches in removal events for Brook Trout (Salvelinus fontinalis) in two streams in the the Nashwaak Experimental Watersheds Project on multiple dates. Includes results from Schnute (1983).

Format

A data frame of 16 observations on the following 7 variables:

sample

A unique identified for the sample.

stream

Stream (UNM=Upper Narrows Mountain Brook and Hay=Hyaden Brook).

section

Section of stream. See source.

date

Data of collections.

first

Catch on the first removal pass.

second

Catch on the second removal pass.

third

Catch on the third removal pass.

fourth

Catch on the fourth removal pass.

Moran.N

Schnute (1983) estimate of N using the Moran (1951) method.

Moran.NLCI

Schnute (1983) estimate of N 95% LCI using the Moran (1951) method.

Moran.NUCI

Schnute (1983) estimate of N 95% UCI using the Moran (1951) method.

Moran.p

Schnute (1983) estimate of p using the Moran (1951) method.

Moran.LH

Schnute (1983) negative log likelihood using the Moran (1951) method.

Schnute.N

Schnute (1983) estimate of N.

Schnute.NLCI

Schnute (1983) estimate of N 95% LCI.

Schnute.NUCI

Schnute (1983) estimate of N 95% UCI.

Schnute.p1

Schnute (1983) estimate of p1.

Schnute.p

Schnute (1983) estimate of p.

Schnute.LH

Schnute (1983) negative log-likelihood.

ChiSq

Schnute (1983) chi-square from likelihood ratio comparison of Moran and Schnute methods.

Topic(s)

Source

From Tables 1-3 in Schnute, J. 1983. A new approach to estimating populations by the removal method. Canadian Journal of Fisheries and Aquatic Sciences, 40:2153-2169. CSV file

See Also

See BrookTroutNEWP for only the data (note the results from Schnute (1983)).

Examples

data(BrookTroutNEWP1)

## extract data for one stream, section, and date (e.g., 3rd row)
BrookTroutNEWP1[3,]

Summarized single mark-recapture data for Brook Trout across many years.

Description

The number of Brook Trout (Salvelinus fontinalis) marked, captured, and recaptured for several years on Meach Lake in central Ontario.

Format

A data frame with 7 observations on the following 5 variables.

year

Year of the collection

mark

Total number of fish marked on the marking run

catch

Total number of fish caught on the recapture run

recap

Total number of previously marked fish in the recapture run

correction

Number of age-1 fish to be added to final estimated based on mark-recapture to correct for gear selectivity of age-1 fish

Topic(s)

Source

From Table 1 of Curry, R.A., C. Brady, and G.E. Morgan. 2003. Effects of Recreational Fishing on the Population Dynamics of Lake-Dwelling Brook Trout. North American Journal of Fisheries Management 23:35-47. CSV file

Examples

data(BrookTroutOnt)
str(BrookTroutOnt)
head(BrookTroutOnt)

Single census mark-recapture data with lengths for Brown Trout from Valley Creek, MN.

Description

Single census mark-recapture data for Brown Trout (Salmo trutta) from Valley Creek, MN captured in April, 1988. Length of trout was recorded so that abundance estimated can be made by length categories.

Format

A data frame with 1014 observations on the following 3 variables.

len

A numeric vector of total length measurements (cm)

sample

A factor variable representing the sample in which the fish was captured. The marking run is labelled with first and the recapture run is labelled with second

recap

A factor variable representing whether the fish was a “recap”ture in the second sample (YES) or not (NO)

Topic(s)

Source

Obtained directly from Tom Kwak, North Carolina Cooperate Unit at North Carolina State University and part of the data published in Kwak, T.J. and T.F. Waters. 1997. Trout production dynamics and water quality in Minnesota streams. Transactions of the American Fisheries Society, 126:35-48. CSV file

Examples

data(BrownTroutVC1)
str(BrownTroutVC1)
head(BrownTroutVC1)
hist(BrownTroutVC1$len,main="")

Lengths and weights for Bull Trout from two Rocky Mountain lakes and two eras.

Description

Lengths and weights of Bull Trout (Salvelinus confluentis) from two Rocky Mountain lakes in Alberta, CAN and two eras.

Format

A data frame with 137 observations on the following 3 variables:

fl

Fork length (mm)

mass

Wet mass (g)

era

Era of collection (1977-79 and 2001)

Topic(s)

Note

The historical (1977-1980) era samples were from before restrictive sportfishing regulatory regimes were implemented (in the 1990s) that led to changes in abundance and population structure of bull trout.

Source

From (approximately) Figure 2 of Parker, B.R., D.W. Schindler, F.M. Wilhelm, and D.B. Donald. 2007. Bull trout population responses to reductions in angler effort and retention limits. North American Journal of Fisheries Management 27:848-859. CSV file

Examples

data(BullTroutRML1)
str(BullTroutRML1)
head(BullTroutRML1)
op <- par(mfrow=c(1,2),pch=19)
plot(mass~fl,data=BullTroutRML1,subset=era=="1977-79",main="1977-79")
plot(mass~fl,data=BullTroutRML1,subset=era=="2001",main="2001")
par(op)

Ages and lengths of Bull Trout from two Rocky Mountain lakes at two times.

Description

Assigned ages (from otoliths) and fork lengths of Bull Trout (Salvelinus confluentis) from two Rocky Mountain lakes in Alberta, CAN before and after a regulation change.

Format

A data frame with 96 observations on the following 4 variables:

age

Age (from otoliths).

fl

Fork length (mm).

lake

Lake (Harrison and Osprey).

era

Era of collection (1977-80 and 1997-01). See details.

Topic(s)

Note

The historical (1977-1980) era samples were from before restrictive sportfishing regulatory regimes were implemented (in the 1990s) that led to changes in abundance and population structure of bull trout.

Source

From (approximately) Figure 2 of Parker, B.R., D.W. Schindler, F.M. Wilhelm, and D.B. Donald. 2007. Bull trout population responses to reductions in angler effort and retention limits. North American Journal of Fisheries Management 27:848-859. CSV file

Examples

data(BullTroutRML2)
str(BullTroutRML2)
head(BullTroutRML2)
op <- par(mfrow=c(2,2),pch=19)
plot(fl~age,data=BullTroutRML2,subset=lake=="Harrison" & era=="1977-80",main="Harrison, 1977-80")
plot(fl~age,data=BullTroutRML2,subset=lake=="Harrison" & era=="1997-01",main="Harrison, 1997-2001")
plot(fl~age,data=BullTroutRML2,subset=lake=="Osprey" & era=="1977-80",main="Osprey, 1977-80")
plot(fl~age,data=BullTroutRML2,subset=lake=="Osprey" & era=="1997-01",main="Osprey, 1997-2001")
par(op)

Catch-at-age for Bull Trout in Trestle Creek, ID.

Description

Catch-at-age (actually carcasses-at-age) for Bull Trout (Salvelinus confluentis) in Trestle Creek, ID.

Format

A data frame with 6 observations on the following 2 variables.

age

A numeric vector of assigned ages (from otoliths).

carcasses

A numeric vector of number of carcasses found in and along Trestle Creek.

Topic(s)

Source

From (approximately) Figure 4a in Downs, C.C., D. Horan, E. Morgan-Harris, and R. Jakubowski. 2006. Spawning demographics and juvenile dispersal of an adfluvial bull trout population in Trestle Creek, Idaho. North American Journal of Fisheries Management 26:190-200. CSV file

Examples

data(BullTroutTC)
str(BullTroutTC)
head(BullTroutTC)
plot(log(carcasses)~age,data=BullTroutTC)

Catch-at-age of Channel Catfish from two sections of the Platte River, NB.

Description

Catch-at-age of Channel Catfish (Ictalurs puncatatus) from two sections of the Platte River, NB, in 2007 and 2008.

Format

A data frame of 26 observations on the following 3 variables:

age

Age (years) assigned from pectoral spines

catch

Number of captured fish with baited hoopnets and electrofishing

loc

Location of collection (Central and Lower)

Topic(s)

Note

Used in the Introductory Fisheries Analyses with R book.

Source

From (approximately) Figure 3-14 in Barada, T.J. 2009. Catfish population dynamics in the Platte River, Nebraska. Master's thesis, University of Nebraska, Lincoln, NE. CSV file

Examples

data(CCatfishNB)
str(CCatfishNB)
head(CCatfishNB)
op <- par(mfrow=c(1,2),pch=19)
plot(log(catch)~age,data=CCatfishNB,subset=loc=="Central",main="Central")
plot(log(catch)~age,data=CCatfishNB,subset=loc=="Lower",main="Lower")
par(op)

Ages, lengths, and maturity for female Cabezon from Oregon.

Description

Ages, lengths, and maturity for female Cabezon (Scorpaenichthys marmoratus) from Newport and Depoe Bay, Oregon.

Format

A data frame with 525 observations on the following 5 variables.

date

Date fish was collected

length

Total length (cm)

age

Otolith age

maturity

Maturity state (Immature or Mature)

stage

Stage of maturity (1:Immature, 2:Maturing, 3:Mature, 4:Fertilized, 5:Ripe, 6:Spent, 7:Resting)

Topic(s)

Source

Actual data obtained directly (from Bob Hanna) from Hannah, R.W, M.T.O. Blume, and J.E. Thompson. 2009. Length and age at maturity of female yelloweye rockfish (Sebastes rubberimus) and cabezon (Scorpaenichthys marmoratus) from Oregon waters based on histological evaluation of maturity. Oregon Department of Fish and Wildlife, Information Reports 2009-04. [Was (is?) from http://www.dfw.state.or.us/mrp/publications/docs/Info200904_YlwEyeRF_Maturity.pdf.] CSV file

Examples

data(Cabezon)
str(Cabezon)
head(Cabezon)
op <- par(mfrow=c(2,2),pch=19)
plot(length~age,data=Cabezon,ylab="Total Length (cm)",xlab="Age")
hist(Cabezon$length,xlab="Total Length (cm)",main="")
tbl1 <- xtabs(~age+maturity,data=Cabezon)
(ptbl1 <- prop.table(tbl1,margin=1))
plot(ptbl1[,2]~as.numeric(row.names(ptbl1)),type="l",xlab="Age",ylab="Proportion Mature")
tbl2 <- xtabs(~length+maturity,data=Cabezon)
(ptbl2 <- prop.table(tbl2,margin=1))
plot(ptbl2[,2]~as.numeric(row.names(ptbl2)),type="l",xlab="Length",ylab="Proportion Mature")
par(op)

Instantaneous growth rates for two calcified ageing structures.

Description

Instantaneous growth rates (percent change per day) for body growth and two calcified ageing structures from age 1-4 female Northern Pike (Esox lucius) from Wickett Lake, Ontario.

Format

A data frame with 12 observations on the following 4 variables.

day

A numeric vector of days since the beginning of the study.

body

A numeric vector of instantaneous growth rates (percent change per day) for body growth.

cleithrum

A numeric vector of instantaneous growth rates (percent change per day) for cleithra.

scale

A numeric vector of instantaneous growth rates (percent change per day) for scales.

Topic(s)

Source

From Figure 8 of Casselman, J.M. 1990. Growth and relative size of calcified structures of fish. Transactions of the American Fisheries Society. 119:673-688. CSV file

Examples

data(Casselman1990)

# recreation of Casselman's (199) Figure 8.
p <- c(19,17,15); clr <- c("black","red","blue"); l <- 1
with(Casselman1990,
     matplot(day,cbind(body,cleithrum,scale),type="b",lwd=2,pch=p,col=clr,lty=l,
             ylab="Instantaneous Growth Rate",xaxt="n",xlab="")
)
axis(1,at=c(0,31,60,91,121,152,182,213,243,274,304,335,365),tick=TRUE,labels=FALSE)
axis(1,at=c(15,46,76,107,137,168,198,229,260,291,321,352),tick=FALSE,
     labels=c("Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"))
legend("topleft",legend=c("Body","Cleithrum","Scale"),pch=p,col=clr,lty=l,lwd=2)

Stock and recruitment data for Klamath River Chinook Salmon, 1979-2000.

Description

Stock and recruitment data for Klamath River Chinook Salmon (Oncorhynchus tshawytscha), 1979-2000 brood years.

Format

A data frame with 27 observations on the following 3 variables.

brood.year

a numeric vector of brood years

spawners

a numeric vector giving number of spawning fish

recruits

a numeric vector containing the number of recruits

Topic(s)

Source

From Pacific Fishery Management Council 2006 report. CSV file

Examples

data(ChinookKR)
str(ChinookKR)
head(ChinookKR)
op <- par(mfrow=c(1,2),pch=19)
plot(recruits~brood.year,data=ChinookKR,type="l")
plot(recruits~spawners,data=ChinookKR)
par(op)

Lengths, weights, and sex of Cisco from Trout Lake, WI.

Description

Lengths, weights, and sex for Cisco (Coregonus artedii) from Trout Lake, WI, 1981-2006. Fish were collected with a variety of gears.

Format

A data frame of 8594 observations on the following 8 variables:

lakeid

Lake name (all TR=Trout Lake)

year4

Year of capture

sampledate

Date of capture

gearid

Capture gear type

spname

Species name (all CISCO)

length

Total length (nearest mm) at capture

weight

Weight (nearest 0.1 or 1 g) at capture

sex

Sex (F=Female, I=Immature, M=Male)

Topic(s)

Source

Obtained from query to North Temperate Lakes LTER data portal at the University of Wisconsin Center for Limnology. CSV file

Examples

data(CiscoTL)
str(CiscoTL)
head(CiscoTL)
op <- par(mfrow=c(2,2),pch=19)
plot(weight~length,data=CiscoTL,subset=sex=="F",main="Female")
plot(weight~length,data=CiscoTL,subset=sex=="M",main="Male")
plot(weight~length,data=CiscoTL,subset=sex=="I",main="Immature")
par(op)

Stock and recruitment data for Crappies from four reservoirs in Arkansas and Mississippi, USA.

Description

Stock and recruitment data for Crappies from four reservoirs in Arkansas and Mississippi, USA.

Format

A data frame of 78 observations on the following 3 variables:

reservoir

Reservoir (Atkins, Nimrod, Okatibbee, Ross.Barnett)

stock

Number of age-1+ fish per hectare

recruits

Number of age-0 fish per hectare

Topic(s)

Source

From (approximately) Figure 2 of Allen, M.S. and L.E. Miranda. 1998. An age-structured model for erratic crappie fisheries. Ecological Modeling 107:289-303. CSV file

Examples

data(CrappieARMS)
str(CrappieARMS)
head(CrappieARMS)
op <- par(mfrow=c(2,2),mar=c(3,3,2,1),mgp=c(1.75,0.5,0),tcl=-0.2,pch=19)
plot(recruits~stock,data=CrappieARMS,subset=(reservoir=="Atkins"),main="Atkins")
plot(recruits~stock,data=CrappieARMS,subset=(reservoir=="Nimrod"),main="Nimrod")
plot(recruits~stock,data=CrappieARMS,subset=(reservoir=="Okatibbee"),main="Okatibbee")
plot(recruits~stock,data=CrappieARMS,subset=(reservoir=="Ross.Barnett"),main="Ross Barnett")
par(op)

Ages (subsample) and lengths (all fish) for Creek Chub.

Description

Ages (subsample) and lengths (all fish) for Creek Chub (Semotilus atromaculatus).

Format

A data frame with 218 observations on the following 2 variables.

len

Total length (mm)

age

Assigned ages (yrs; from scales)

Details

As many as 10 fish per 10 mm length interval were sampled for age assignment with scales.

Topic(s)

Note

Used in the Introductory Fisheries Analyses with R book.

Source

Recreated (random digits were added to construct mm lengths from the cm length bins) from information in Box 15.2 of Quist, M.C., Pegg, M.A., and DeVries, D.R. 2012. Age and growth. In Zale, A.V., Parrish, D.L., and Sutton, T.M., editors. Fisheries Techniques, Third Edition, chapter 15, pages 677-731. American Fisheries Society, Bethesda, MD. CSV file

Examples

data(CreekChub)
str(CreekChub)
head(CreekChub)
xtabs(~age,data=CreekChub)
plot(len~age,data=CreekChub)

Results of a large number of creel surveys in Minnestoa lakes.

Description

The species targeted, number of fish harvested, and number of individuals harvesting that number of that species of fish from a large number of surveys on Minnesota Lakes, 1980-1996.

Format

A data frame of 14550 observations on the following 2 variables:

species

species of fish that was targeted.

harvest

number of fish of that species harvested by one angler.

Topic(s)

Source

From tables in Cook, M.F., T.J. Goeman, P.J. Radomski, J.A. Younk, and P.C. Jacobson. 2001. Creel limits in Minnesota: A proposal for change. Fisheries 26:19-26. CSV file

Examples

data(CreelMN)
str(CreelMN)
head(CreelMN)
levels(CreelMN$species)

## ONLY RUN IN INTERACTIVE MODE
## Not run: 
  require(FSA)
  wae <- filterD(CreelMN,species=="WAE")
  ( waetbl <- table(wae$harvest) )
  ( waeptbl <- prop.table(waetbl)*100 )
  ( waercum <- rcumsum(waeptbl) )
  op <- par(mfrow=c(1,2),mar=c(3.5,3.5,0.5,0.5),mgp=c(2,0.5,0))
  barplot(waeptbl,xlab="Number of Walleye Harvested",ylab="Percentage of Individuals")
  barplot(waercum,xlab="Minimum Number of Walleye Harvested",ylab="Percentage of Individuals")
  par(op)       
  ( ttlwae <- sum(wae$harvest) )                 
  wae$svd5 <- wae$harvest-5             # Used to determine the number of fish                
  xtabs(~svd5,data=wae)                 #   saved if limit was reduced to 5.
  ( svd5 <- sum(wae$svd5[wae$svd5>0]) ) #   Only sum positive numbers (i.e., saved)
  round(svd5/ttlwae*100,1)              # Show as a percentage

  wae$svd1 <- wae$harvest-1             # same but if reduced to 1 bag.
  xtabs(~svd1,data=wae)
  ( svd1 <- sum(wae$svd1[wae$svd1>0]) )
  round(svd1/ttlwae*100,1)

## End(Not run)

Ages of Atlantic Croaker assigned from otoliths by two readers.

Description

Otolith age of Atlantic croaker (Micropogonias undulatus) from two readers.

Format

A data frame of 317 observations on the following 2 variables:

reader1

Age assigned by the first reader

reader2

Age assigned by the second reader

Topic(s)

Source

From Figure 2 in Chapter 1 (Atlantic Croaker) of the VMRC Final Report on Finfish Ageing, 1999 by the Center for Quantitative Fisheries Ecology at Old Dominion University. CSV file

Examples

data(Croaker1)
str(Croaker1)
head(Croaker1)
plot(reader2~reader1,data=Croaker1)
xtabs(~reader1+reader2,data=Croaker1)

Ages, lengths, and sexes of Atlantic Croaker by sex.

Description

Assigned ages (by otoliths), total lengths, and sexes of Atlantic Croaker (Micropogonias undulatus).

Format

A data frame of 318 observations on the following 3 variables:

age

Otolith age-at-capture (years).

tl

Total length (nearest mm) at capture.

sex

Sex of the fish (M=male and F=female).

Topic(s)

Source

From Figure 4 in Chapter 1 (Atlantic Croaker) of the VMRC Final Report on Finfish Ageing, 1999 by the Center for Quantitative Fisheries Ecology at Old Dominion University. CSV file

Examples

data(Croaker2)
str(Croaker2)
head(Croaker2)
op <- par(mfrow=c(1,2),pch=19)
plot(tl~age,data=Croaker2,subset=sex=="F",main="Female")
plot(tl~age,data=Croaker2,subset=sex=="M",main="Male")
par(op)

Capture histories (9 samples) of Cutthroat Trout from Auke Lake.

Description

Summarized (“RMark” format) capture histories of Cutthroat Trout (Oncorhynchus clarki) in Auke Lake, Alaska, from samples taken in 1998-2006.

Format

A data frame with 47 observations on the following 2 variables.

ch

Unique capture history (as a character string)

freq

Frequency of fish with that capture history

Topic(s)

Source

Entered from Appendix A.3 of Harding, R.D., C.L. Hoover, and R.P. Marshall. 2010. Abundance of Cutthroat Trout in Auke Lake, Southeast Alaska, in 2005 and 2006. Alaska Department of Fish and Game Fisheries Data Series No. 10-82. Accessed from http://www.sf.adfg.state.ak.us/FedAidPDFs/FDS10-82.pdf. CSV file

See Also

See CutthroatAL for the same data in “individual” fish format (i.e., the data in this file were converted using capHistConvert from FSA). See mrOpen from FSA for an example analysis.

Examples

data(CutthroatALf)
str(CutthroatALf)
head(CutthroatALf)

Catch and effort data for Fantail Darter.

Description

Catch and effort data for Fantail Darter (Etheostoma flabellare) from seven removal events conducted by Mahon (1980).

Format

A data frame with 7 observations on the following 2 variables.

catch

Catch of Fantail Darter.

effort

Constant electrofishing effort.

Details

Catch (number of fish) was recorded. Effort was a constant amount of electrofishing for each sampling event and is, thus, entered as a constant value of 1.

These data are used in many publications because the stream section was rotenoned following the removal surveys to determine a known population size of 1151 individuals.

Topic(s)

Source

From Mahon, R. 1980. Accuracy of catch-effort methods for estimating fish density and biomass in streams. Environmental Biology of Fishes. 4:343-363. CSV file

Examples

data(DarterMahon)
str(DarterMahon)
head(DarterMahon)

Ages and lengths of Channel Darters from two locations.

Description

Assigned ages (from otoliths), total length, and collection location of Channel Darter (Percina copelandi).

Format

A data frame of 54 observations on the following 3 variables:

age

Otolith age-at-capture (years).

tl

Total length (nearest 0.1 mm) at capture.

river

Location of capture (Salmon or Trent Rivers).

Topic(s)

Note

The original author used a linear model to describe the relationship between length and age.

Source

From Figure 2 of Reid, S.M. Age estimates and length distributions of Ontario channel darter (Percina copelandi) populations. Journal of Freshwater Ecology 19:441-444. CSV file

Examples

data(DarterOnt)
str(DarterOnt)
head(DarterOnt)
op <- par(mfrow=c(1,2),pch=19)
plot(tl~age,data=DarterOnt,subset=river=="Salmon",main="Salmon R.")
plot(tl~age,data=DarterOnt,subset=river=="Trent",main="Trent R.")
par(op)

Catches in removal events of Cutthroat Trout and Coho Salmon in Little Stawamus Creek (British Columbia, Canada) in 1997.

Description

Catches of Coho Salmon (Oncorhynchus kisutch) and Cutthroat Trout (Oncorhynchus clarki) in consecutive removal events at various locations in Little Stawamus Creek (British Columbia, Canada) in 1997.

Format

A data frame of 26 observations on the following 10 variables:

reach

Reach number of sampling location.

habitat

Habitat type of sampling location – pool, riffle, or run.

strata

Stratum number of sampling location.

area

Area (m^2) of sampling location.

coho1

Coho Salmon removed on the first pass.

coho2

Coho Salmon removed on the second pass.

coho3

Coho Salmon removed on the third pass.

cutt1

Cutthroat Trout removed on the first pass.

cutt2

Cutthroat Trout removed on the second pass.

cutt3

Cutthroat Trout removed on the third pass.

Topic(s)

Source

From Appendix 2a and 2b in Decker, A.S., J.M. Bratty, S.C. Riley, and J. Korman. 1999. Estimating standing stock of juvenile coho salmon (Oncorhynchus kisutch) and cutthroat trout (Oncorhynchus clarki) in a small stream: a comparison of sampling designs. Canadian Technical Report of Fisheries and Aquatic Sciences 2282. 24 pp. CSV file

Examples

data(Deckeretal1999)
str(Deckeretal1999)
head(Deckeretal1999)

## extract data for one sampling location (e.g., 3rd row)
Deckeretal1999[3,]

Ages, lengths, and sexes of European Perch.

Description

Assigned ages, measured fork lengths, and observed sexes for European Perch (Perca fluviatilis) from Lake Tjuekemeer (The Netherlands).

Format

A data frame of 69 observations on the following 3 variables:

fl

Fork lengths (cm).

age

Assigned ages.

sex

Sex (female, male).

Topic(s)

Source

From (approximately) Figure 2 in Mooij, W.M., J.M. Van Rooij, and S. Wijnhoven. 1999. Analysis and comparison of fish growth from small samples of length-at-age data: Detection of sexual dimorphism in Eurasian perch as an example. Transactions of the American Fisheries Society, 128:483-490. CSV file

Examples

data(EuroPerchTJ)
str(EuroPerchTJ)
head(EuroPerchTJ)
op <- par(mfrow=c(1,2),pch=19)
plot(fl~age,data=EuroPerchTJ,subset=sex=="female",main="Female")
plot(fl~age,data=EuroPerchTJ,subset=sex=="male",main="Male")
par(op)

Catch-at-age of Flathead Catfish from three southeastern rivers.

Description

Numbers of Flathead Catfish (Pylodictis olivaris) captured by electrofishing in three rivers – Coosa River, AL; Ocmulgee River, GA; and Satilla River, GA.

Format

A data frame of 39 observations on the following 3 variables:

river

Location of collection (Coosa, Ocmulgee, and Satilla)

age

Age (years) assigned from otolith

abundance

Number of captured fish with boat electrofishing

Topic(s)

Source

From (approximately) Figure 3 in Sakaris, P.C., E.R. Irwin, J.C. Jolley, and D. Harrison. 2006.Comparison of Native and Introduced Flathead Catfish Populations in Alabama and Georgia: Growth, Mortality, and Management. North American Journal of Fisheries Management 26:867-874. CSV file

Examples

data(FHCatfish)
str(FHCatfish)
head(FHCatfish)
op <- par(mfrow=c(2,2),pch=19)
plot(log(abundance)~age,data=FHCatfish,subset=river=="Coosa",main="Coosa")
plot(log(abundance)~age,data=FHCatfish,subset=river=="Ocmulgee",main="Ocmulgee")
plot(log(abundance)~age,data=FHCatfish,subset=river=="Satilla",main="Satilla")
par(op)

Catch-at-age of Flathead Catfish from three Atlantic rivers.

Description

Catch-at-age of Flathead Catfish (Pylodictis olivaris) from three populations of Atlantic rivers – Lumber River, Northeast Cape Fear River (NCF), and Neuse River.

Format

A data frame of 44 observations on the following 3 variables:

river

Collection river (Lumber, NCF, and Neuse).

age

Age (yrs) assessed by otolith.

number

Number of captured fish.

Topic(s)

Source

From (approximately) Figure 2 in Kwak, T.J., W.E. Pine III, and D.S. Waters. 2006. Age, growth, and mortality of introduced flathead catfish in Atlantic rivers and a review of other populations. North American Journal of Fisheries Management 26:73-87. CSV file

Examples

data(FHCatfishATL)
str(FHCatfishATL)
head(FHCatfishATL)
op <- par(mfrow=c(2,2),pch=19)
plot(log(number)~age,data=FHCatfishATL,subset=river=="Lumber",main="Lumber")
plot(log(number)~age,data=FHCatfishATL,subset=river=="NCF",main="NCF")
plot(log(number)~age,data=FHCatfishATL,subset=river=="Neuse",main="Neuse")
par(op)

Ages and lengths of Lake Erie Freshwater Drum.

Description

Assigned ages (from scales) and measured total lengths for each of 1577 Freshwater Drum (Aplodinotus grunniens) from Lake Erie.

Format

A data frame with 1577 observations on the following 2 variables.

age

Assigned ages (from scales).

tl

Measured total lengths (mm).

Topic(s)

Source

Simulated from Table 3 of Bur, M.T. 1984. Growth, reproduction, mortality, distribution, and biomass of freshwater drum in Lake Erie. Journal of Great Lakes Research. 10:48-58. CSV file

See Also

FWDrumLE2.

Examples

data(FWDrumLE1)
str(FWDrumLE1)
head(FWDrumLE1)
plot(tl~age,data=FWDrumLE1)

Ages (subsample) and lengths (all fish) for Freshwater Drum from Lake Erie.

Description

A total of 253 fish dispersed proportionately over 10-mm total length intervals from the FWDrumLE1 data frame was obtained for age assignment. The remaining fish in the file were only measured for length (i.e., the ages were deleted). This data file can be used to demonstrate the use of age-length keys.

Format

A data frame with 1577 observations on the following 2 variables.

age

Assigned ages (from scales).

tl

Measured total lengths (mm).

Topic(s)

Source

CSV file

See Also

FWDrumLE1.

Examples

data(FWDrumLE2)
str(FWDrumLE2)
head(FWDrumLE2)
## Extract the aged sample
FWD.aged <- subset(FWDrumLE2,!is.na(age))
str(FWD.aged)
## Extract the length sample
FWD.length <- subset(FWDrumLE2,is.na(age))
str(FWD.length)

Species accumulation data for fish of the Western Ghats of India.

Description

Species accumulation data for fish of the Western Ghats of India derived from nine random samples of publications.

Format

A data frame with 350 observations on the following 2 variables.

unit

a manuscript that was reviewed.

cumspec

cumulative number of species described in the reviewed manuscripts.

Topic(s)

Source

From (approximately) Figure 1 in Dahanukar, N., R. Raut, and A. Bhat. 2004. Distribution, endemism and threat status of freshwater fishes in the Western Ghats of India. Journal of Biogeography 31:123-126. CSV file

Examples

data(Ghats)
str(Ghats)
head(Ghats)
plot(cumspec~unit,data=Ghats)

Catches in removal events of Coho Salmon and Dolly Varden Char at various locations near the Greens Creek (AK) Mine site.

Description

Catches in removal events of Coho Salmon (Oncorhynchus kisutch) and Dolly Varden Char (Salvelinus malma) at various locations near the Greens Creek (AK) Mine site.

Format

A data frame of 66 observations on the following 8 variables:

location

Sampling location.

year

Sampling year.

species

Species (Coho.Salmon or Dolly.Varden).

set1

Catch on the first removal pass.

set2

Catch on the second removal pass.

set3

Catch on the third removal pass.

min.FL

Minimum observed fork length.

max.FL

Maximum observed fork length.

Details

Reaches were isolated by natural features, such as shallow riffles. The sample reaches were saturated with 6.35 mm (0.25 in) minnow traps baited with whirl packs containing disinfected salmon eggs.The traps were deployed for 1.5 h and then retrieved where each fish was transferred into a plastic bucket, and the trap was re-baited ans re-set for another 1.5 h soak. In between trapping events, fish were processed – measured and recorded FL to the nearest 1 mm, weight to the nearest 0.1 g, and species identified. Captured fish were retained during the sample period and returned alive after all three passes were complete.

Topic(s)

Source

From Appendix C1 of Kanouse, K.M. and B.P. Brewster. 2012. Aquatic Biomonitoring at Greens Creek Mine, 2012. Alaska Department of Fish and Game Technical Report No. 12-11. CSV file

Examples

data(GreensCreekMine)
str(GreensCreekMine)
head(GreensCreekMine)

## extract data for one location, year, and species (e.g., 3rd row)
GreensCreekMine[3,]

Stock and recruitment data for Hake, 1982-1996.

Description

Stock and recruitment data for Hake (Merluccius merluccius), 1982-1996.

Format

A data frame with 15 observations on the following 3 variables.

year

a numeric vector of years 1982-1996

recruits

a numeric vector of the number of recruits in millions

spawn.biomass

a numeric vector of spawning biomass in thousand tonnes

Topic(s)

Source

Cadima, E. 2003. Fish Stock Assessment Manual, FAO Fisheries Department. 131 pp. CSV file

Examples

data(Hake)
str(Hake)
head(Hake)
op <- par(mfrow=c(1,2),pch=19)
plot(recruits~year,data=Hake,type="l")
plot(recruits~spawn.biomass,data=Hake)
par(op)

Stock and recruitment data for Pacific Halibut, 1929-1991.

Description

Pacific Halibut (Hippoglossus stenolepis) stock, recruitment, landings, and fishing mortality by year, 1929-1991.

Format

A data frame of 63 observations on the following 5 variables:

year

Year of data

ssb

Spawning stock biomass (tonnes)

rec

Recruits (thousands)

land

Landings (in millions of pounds)

fmort

Fishing related mortality

Topic(s)

Source

From Anonymous. 1989. International Pacific Halibut Commission. Annual Report 1989.; Myhre, Gordon, Peltonen, Stpierre, Skud, and Walden. International Pacific halibut Commission. Technical Report No. 14.; Pers. Comm. with Pat Sullivan. Obtained from Ransom Myers old online database. CSV file

Examples

data(HalibutPAC)
str(HalibutPAC)
head(HalibutPAC)
op <- par(mfrow=c(1,2),pch=19)
plot(rec~year,data=HalibutPAC,type="l")
plot(rec~ssb,data=HalibutPAC)
par(op)

Lengths for Walleye, Yellow Perch, Black Crappie, and Black Bullheads from Lake Herman, SD.

Description

Total lengths of Walleye (Sander vitreus), Yellow Perch (Perca flavescens), Black Crappie (Pomoxis nigromaculatus), and Black Bullheads (Ameiurus melas) for four years in Lake Herman, SD.

Format

A data frame of 5931 observations on the following 3 variables:

tl

Total lengths (cm).

spec

Species codes (wae=walleye, yep=yellow perch, bkc=black crappie, and bbh=black bullhead).

yr

Capture years.

Details

Lake Herman was sampled on June 20-22, 2005 with four overnight gillnet sets and 10 overnight trapnet sets. The trapnets were constructed with 19-mm (0.75 in) bar-mesh netting, 0.9 m high x 1.5 m wide (3 ft high x 5 ft wide) frames and 18.3 m (60 ft) long leads. The gillnets were 45.7 m long x 1.8 m deep (150 ft long x 6 ft deep) with one 7.6 m (25 ft) panel each of 13, 19, 25, 32, 38 and 51-mm (0.5, 0.75, 1, 1.25, 1.5, and 2 in) bar-mesh monofilament netting.

Topic(s)

Source

From a South Dakota Fish and Game report. CSV file

Examples

data(Herman)
str(Herman)
head(Herman)
op <- par(mfrow=c(2,2),pch=19)
### Four (of 16 possible) examples
with(subset(Herman,spec=="bbh" & yr==2003),hist(tl,main="Black Bullhead, 2003"))
with(subset(Herman,spec=="bkc" & yr==2001),hist(tl,main="Black Crappie, 2001"))
with(subset(Herman,spec=="yep" & yr==2003),hist(tl,main="Yellow Perch, 2003"))
with(subset(Herman,spec=="wae" & yr==1999),hist(tl,main="Walleye, 1999"))
par(op)

Stock and recruitment data for Blackwater Estuary Herring, 1962-1997.

Description

Stock and recruitment data for Blackwater Estuary Herring (Clupea harengus), 1962-1997 spawning years.

Format

A data frame with 36 observations on the following 3 variables.

spawning.year

a numeric vector of spawning years

ssb

a numeric vector giving biomass of spawning fish

recruits

a numeric vector containing the number of recruits

Topic(s)

Source

From Fox, C.J. 2001. Recent trends in stock-recruitment of Blackwater herring (Clupea harengus L.) in relation to larval production. ICES Journal of Marine Science, 58:750-762. CSV file

Examples

data(HerringBWE)
str(HerringBWE)
head(HerringBWE)
op <- par(mfrow=c(1,2))
plot(recruits~spawning.year,data=HerringBWE,type="l")
plot(recruits~ssb,data=HerringBWE)
par(op)

Stock and recruitment data for Icelandic summer spawning Herring, 1946-1996.

Description

Icelandic summer spawning Herring (Clupeaformis harengus) stock, recruitment, landings, and fishing mortality by year, 1946-1996.

Format

A data frame of 51 observations on the following 6 variables:

year

Year of data

ssb

Spawning stock biomass (tonnes)

rec

Recruits – i.e., 1-year olds (thousands)

land

Landings (in millions of pounds)

fmort

Fishing related mortality

Topic(s)

Source

From the Report of the Atlanto-Scandian Herring and Capelin Working Group. ICES Doc. C.M. 1995. Assess: 9.; Anon. 1986. Report of the herring assessment working group for the area south of 62 degrees N. ICES Doc. C.M. 1986. Assess: 19.; Anon. 1991. Report of the Atlanto-Scandian Herring and Capelin Working Group. ICES Doc. C.M. 1991. Assess: 17.; State of marine stocks and environmental conditions in Icelandic waters 1989 Fishing prospects 1990, August 1990. Hafranns\'oknastofnun Fj\"olrit NR. 19. Marine Research Institute, Iceland. Mon Jun 20, 1988.; Report of the Northern Pelagic and Blue Whiting Fisheries Working Group. ICES Doc. C.M. 1997. Assess:14. Obtained from Ransom Myers old online database. CSV file

Examples

data(HerringISS)
str(HerringISS)
head(HerringISS)
op <- par(mfrow=c(1,2))
plot(rec~year,data=HerringISS,type="l")
plot(rec~ssb,data=HerringISS)
par(op)

Capture histories (2 sample) of Humpback Whitefish.

Description

Capture histories for Humpback Whitefish (Coregonus pidschian) greater than 360 mm in the Chatanika River, AK in 2012.

Format

A data frame with 1920 observations on the following 4 variables:

sectMrun

Section where the fish was captured on the marking run

Mrun

Indicator variable for the marking run (1=captured)

Rrun

Indicator variable for the recapture run (1=captured)

sectRrun

Section where the fish was captured on the recapture run

Topic(s)

Source

From Table 10 in Gryska, A.D. 2014. Stock assessment of humpback whitefish in the Chatanika River, 2012. Alaska Department of Fish and Game, Fishery Data Series No. 14-12, Anchorage. CSV file

Examples

data(HumpbackWFCR)
str(HumpbackWFCR)
head(HumpbackWFCR)

Lengths for all fish captured in Inch Lake, WI, in two years

Description

Total lengths of all fish captured in Inch Lake, WI in May, 2007 and May, 2008.

Format

A data frame of 4894 observations on the following 5 variables:

netID

A unique identifier for the sampling event

netType

gear used (angling, seine, miniWDNR fyke net, miniNC fyke net, regular fyke net)

year

year of capture

species

species name

length

total length (inches to nearest 0.1)

Topic(s)

Source

Derek H. Ogle, personal collection. CSV file

See Also

See InchLake2 for a subsample that include weights.

Examples

data(InchLake1)
str(InchLake1)
head(InchLake1)

## Isolate just Bluegills
bg.il <- subset(InchLake1,species=="Bluegill")

## Isolate just largemouth bass from 2007
lmb7.il <- subset(InchLake1,species=="Largemouth Bass" & year==2007)

## Isolate all fish captured in seines
seine.il <- subset(InchLake1,netType=="seine")

Lengths and weights for fish captured in Inch Lake

Description

Total lengths and weights for a subsample of fish captured in Inch Lake, WI in May, 2007 and May, 2008.

Format

A data frame of 516 observations on the following 6 variables:

netID

A unique identifier for the sampling event

fishID

A unique identifier for the individual fish

species

Species name

length

Total length (inches to nearest 0.1)

weight

Wet weight (grams to nearest 0.1)

year

Year of capture

Topic(s)

Source

Derek H. Ogle, personal collection. CSV file

See Also

See InchLake1 for the entire sample, but without weights.

Examples

data(InchLake2)
str(InchLake2)
head(InchLake2)

## Isolate just Bluegills
bg.il <- subset(InchLake2,species=="Bluegill")

## Isolate just largemouth bass from 2007
lmb7.il <- subset(InchLake2,species=="Largemouth Bass" & year==2007)

Catch and effort data for South Indian Ocean Jobfish.

Description

Catch and effort data for Jobfish (Pristipomoides filamentosus) from the South Indian Ocean.

Format

A data frame with 13 observations on the following 2 variables.

catch

Catches (kg).

effort

Effort (man-hours).

Topic(s)

Source

From Table 2 of Grandcourt, E.M. 2003. The effect of intensive line fishing on the virgin biomass of a tropical deepwater snapper, the crimson jobfish (Pristipomoides filamentosus). Fisheries Bulletin, 101:305-311. CSV file

Examples

data(JobfishSIO)
str(JobfishSIO)
head(JobfishSIO)

Catches in removal events of Brown and Rainbow Trout at various locations.

Description

Catches of Brown (Salmo trutta) and Rainbow Trout (Oncorhynchus mykiss) in consecutive removal events at various locations.

Format

A data frame of 40 observations on the following 10 variables:

species

Species of trout (brown or rainbow).

site

Site in the watershed. See source.

age0

Logical is TRUE if age-0 and FALSE if age is >0.

first

Catch on the first removal pass.

second

Catch on the second removal pass.

third

Catch on the third removal pass.

pop.cs

Population estimate by Carle-Strub method.

pop.sch

Population estimate by Schnute method.

q.cons

Logical is TRUE if catchability was constant.

rejected

Logical is TRUE if Schnute method rejected the population estimate because the standard error was too large.

Topic(s)

Source

From Table 1 in Jones, M.L. and J.D. Stockwell. 1995. A rapid assessment procedure for enumeration of salmonine populations in streams. North American Journal of Fisheries Management, 15:551-562. CSV file

Examples

data(JonesStockwell)
str(JonesStockwell)
head(JonesStockwell)

## extract data for one species, age, and site (e.g., 3rd row)
JonesStockwell[3,]

Ages and lengths of male Jonubi.

Description

Assigned ages and measured fork lengths for male Jonubi (Chalcalburnus mossulensis) from the Karasu River (Turkey).

Format

A data frame with 410 observations on the following 2 variables:

fl

Fork lengths (cm).

age

Assigned ages (years).

Topic(s)

Source

Simulated from table 2 of Yildirim, A., H.U. Haluloulu, M. Turkmen, and O. Erdouan. 2003. Age and growth characteristics of Chalcalburnus mossulensis (Heckel, 1843) living in Karasu River (Erzurum-Turkey). Turkish Journal of Veterinary and Animal Science 27:1091-1096. CSV file

See Also

Jonubi2.

Examples

data(Jonubi1)
str(Jonubi1)
head(Jonubi1)
plot(fl~age,data=Jonubi1)

Ages (subsample) and lengths (all fish) of Jonubi.

Description

Ages (subsample) and lengths (all fish) for Jonubi (Chalcalburnus mossulensis).

Format

A data frame with 410 observations on the following 2 variables.

fl

Fork length (cm) measurements

age

Assigned ages (years)

Details

A total of 50 fish dispersed proportionately over 1-cm fork length intervals from the Jonubi1 data frame was obtained for age assignment. The remaining fish in the file were only measured for length (i.e., the ages were deleted). This data file can be used to demonstrate the use of age-length keys.

Topic(s)

Source

CSV file

See Also

Jonubi1.

Examples

data(Jonubi2)
str(Jonubi2)
head(Jonubi2)
plot(fl~age,data=Jonubi2)

Stock and recruitment data for Red King Crab in Alaska, 1960-2004.

Description

Stock and recruitment data for Red King Crab (Paralithodes camtschaticus) from the northern Gulf of Alaska around Kodiak Island by brood year, 1960-2004.

Format

A data frame of 44 observations on the following 3 variables:

year

Brood year (1960-2004)

recruits

abundance (thousands) of male recruits (>=125 mm and <145 mm)

adults

abundance (thousands) legal (>=145 mm carapace length) males

Topic(s)

Source

From table 1 in Bechtol W.R. and G.H. Kruse. 2009. Analysis of a stock-recruit relationship for Red King Crab off Kodiak Island Alaska. Marine and Coastal Fisheries: Dynamics Management and Ecosystem Science 1:29-44. CSV file

Examples

data(KingCrabAK)
str(KingCrabAK)
head(KingCrabAK)
op <- par(mfrow=c(1,2),pch=19)
plot(recruits~year,data=KingCrabAK,type="l")
plot(recruits~adults,data=KingCrabAK)
par(op)

Ages and lengths of Longjaw Cisco from two locations in Lake Michigan.

Description

Assigned age (by scales) and total length of Longjaw Cisco (Leucichthys alpenae) captured at two locations in Lake Michigan.

Format

A data frame with 378 observations on the following 3 variables.

age

Assigned age (by scales).

tl

Measured total length (mm).

loc

Capture location (NE=northeast and S=south).

Topic(s)

Source

Simulated from age-length data provided in tables 2 and 3 of Jobes, F.W. 1946. The age, growth, and distribution of the longjaw cisco, Leucichthys alpenae Koelz, in Lake Michigan. Transactions of the American Fisheries Society 76:215-247. CSV file

Examples

data(LJCisco)
str(LJCisco)
head(LJCisco)
op <- par(mfrow=c(1,2))
plot(tl~age,data=LJCisco,subset=loc=="NE",main="northeast")
plot(tl~age,data=LJCisco,subset=loc=="S",main="south")
par(op)

Lengths for Largemouth Bass from Boomer Lake, OK.

Description

Length measurements of Largemouth Bass (Micropterus salmoides) from Boomer Lake, Oklahoma, in 1974.

Format

A data frame of 447 observations on the following 1 variable:

tl

measured total length (cm)

Topic(s)

Source

From McNew, R.W. and R.C. Summerfelt. 1978. Evaluation of a maximum-likelihood estimator for analysis of length-frequency distributions. Transactions of the American Fisheries Society 107:730-736. Data was simulated (uniform distribution of values within length bin) from summarized length frequencies in http://fishbase.org/. CSV file

Examples

data(LMBassBL)
str(LMBassBL)
head(LMBassBL)
hist(LMBassBL$tl,main="")

Lengths for Largemouth Bass from Lake Carl Blackwell, OK.

Description

Lengthsfor Largemouth Bass (Micropterus salmoides) from Lake Carl Blackwell, Oklahoma, in 1973.

Format

A data frame of 289 observations on the following variable:

tl

Measured total length (cm).

Topic(s)

Source

From McNew, R.W. and R.C. Summerfelt. 1978. Evaluation of a maximum-likelihood estimator for analysis of length-frequency distributions. Transactions of the American Fisheries Society 107:730-736. Data was simulated (uniform distribution of values within length bin) from summarized length frequencies in http://fishbase.org/. CSV file

Examples

data(LMBassLCB)
str(LMBassLCB)
head(LMBassLCB)
hist(LMBassLCB$tl,main="")

Biological data for Lake Trout from the Arctic LTER (AK).

Description

Biological data (lengths, weight, age, and sex) of Lake Trout (Salvelinus namaycush) sampled from Lake NE12 of the Arctic Long Term Ecological Research location.

Format

A data frame of 86 observations on the following 6 variables:

id

A unique identification number.

tl

Total Length (nearest mm) at capture.

fl

Fork Length (nearest mm) at capture.

sl

Standard Length (nearest mm) at capture.

w

Weight (nearest g) at capture.

otorad

Total otolith radius (mm) at capture.

age

Age (completed growing seasons) at capture.

sex

Sex of the fish (F=female and M=male).

Details

Lake trout were removed from Lake NE12 in the summers of 1986, 1988, and 1989 using five-panel experimental gill nets (mesh size of 0.75, 1, 1.5, 2, and 2.5 inches). Lengths, weights, and sex were recorded from the fish while otoliths, and if possible, stomachs and gonads were removed for future analysis. A check was performed on several otoliths by an independent colleague and prevents introduction of bias due to familiarity with the samples.The original file was “cleaned” in the following ways:

  1. Only Lake Trout were kept in the data file.

  2. All unknown sex fish were removed.

  3. Fish with missing data (length, weight,age, or sex) were removed.

  4. Decimals were removed from the ages.

  5. The unique IDs for fish from 1989 were changed to start at 500.

  6. The weight of fish number 509 was changed from 100 to 1100.

Topic(s)

Source

Obtained from the Arctic LTER site. CSV file

Examples

data(LakeTroutALTER)
str(LakeTroutALTER)
head(LakeTroutALTER)
op <- par(mfrow=c(2,2),pch=19)
## Four (of many possible) examples
hist(LakeTroutALTER$tl,main="")
plot(w~tl,data=LakeTroutALTER)
plot(tl~fl,data=LakeTroutALTER)
plot(tl~age,data=LakeTroutALTER)
par(op)

Length and egg deposition of Lake Superior Lake Trout.

Description

Length and egg deposition of Lake Superior Lake Trout (Salvelinus namaycush).

Format

A data frame of 101 observations on the following 2 variables:

tl

Total length (mm) of an individual fish.

eggs

Estimated number of eggs.

Topic(s)

Source

From (approximately) Figure 2 of Schram, S.T. 1993. Fecundity and egg deposition of a wild Lake Superior Lake Trout stock. Wisconsin Department of Natural Resources, Fisheries Management Report no. 149. CSV file

Examples

data(LakeTroutEggs)
str(LakeTroutEggs)
head(LakeTroutEggs)
plot(eggs~tl,data=LakeTroutEggs)

Stock and recruitment data for Lake Trout from Gull Island Shoal, Lake Superior, 1964-1991.

Description

Lake trout (Salvelinus namaycush) stock and recruitment by year at Gull Island Shoal, Lake Superior, 1964-1991.

Format

A data frame of 28 observations on the following 3 variables:

year

Year of data

stock

Mean CPE of adult female Lake Trout per 1000 m of gillnet captured in fall spawning surveys

recruits

Recruits (number of age-0 fish per ha) captured the following fall in bottom trawls

Topic(s)

Source

From Schram, S.T., J.H. Selgeby, C.R. Bronte, and B.L. Swanson. 1995. Population recovery and natural recruitment of Lake Trout at Gull Island Shoal, Lake Superior, 1964-1992. Journal of Great Lakes Research. 21(supp.1):225-232. Obtained from Ransom Myers old online database. CSV file

Examples

data(LakeTroutGIS)
str(LakeTroutGIS)
head(LakeTroutGIS)
op <- par(mfrow=c(1,2))
plot(recruits~year,data=LakeTroutGIS,type="l")
plot(recruits~stock,data=LakeTroutGIS)
par(op)

Stock and recruitment data for Lake Trout in Lake Superior, 1971-1991.

Description

Stock and recruitment data for the 1971-1991 year-classes of Lake Trout (Salvelinus namaycush) in Michigan waters of Lake Superior.

Format

A data frame of 105 observations on the following 5 variables:

year

Year of data

recruits

Recuit index – geometric mean number of age-7 fish/km/net-night

wild

Wild fish spawning stock index – geometric mean number of wild age-8 and older fish/km/net-night

stocked

Stocked fish spawning stock index – geometric mean number of stocked age-8 and older fish/km/net-night

area

Lake Superior management unit

Topic(s)

Source

From (approximately) figures in Richards, J.M., M.J. Hansen, C.R. Bronte, and S.P. Sitar. 2004. Recruitment dynamics of the 1971-1991 year-classes of Lake Trout in Michigan waters of Lake Superior. North American Journal of Fisheries Management 24:475-489. CSV file

Examples

data(LakeTroutMI)
LakeTroutMI$stock <- LakeTroutMI$wild+LakeTroutMI$stocked
str(LakeTroutMI)
head(LakeTroutMI)
op <- par(mfrow=c(3,2),pch=19)
plot(recruits~year,data=LakeTroutMI,subset=area=="MI3",type="l",ylim=c(0,max(recruits,na.rm=TRUE)))
lines(recruits~year,data=LakeTroutMI,subset=area=="MI4",col="blue")
lines(recruits~year,data=LakeTroutMI,subset=area=="MI5",col="green")
lines(recruits~year,data=LakeTroutMI,subset=area=="MI6",col="red")
lines(recruits~year,data=LakeTroutMI,subset=area=="MI7",col="yellow")
plot(recruits~stock,data=LakeTroutMI,subset=area=="MI3",main="MI3")
plot(recruits~stock,data=LakeTroutMI,subset=area=="MI4",col="blue",main="MI4")
plot(recruits~stock,data=LakeTroutMI,subset=area=="MI5",col="green",main="MI5")
plot(recruits~stock,data=LakeTroutMI,subset=area=="MI6",col="red",main="MI6")
plot(recruits~stock,data=LakeTroutMI,subset=area=="MI7",col="yellow",main="MI7")
par(op)

Stock and recruitment data for Greater Lizardfish, 1955-1964.

Description

Greater Lizardfish (Saurida tumbil) stock and recruitment by year, 1955-1964.

Format

A data frame of 10 observations on the following 6 variables:

year

Year of data

stock

Spawning stock (in ten thousands)

recruits

Recruits (in hundred thousands)

Topic(s)

Source

Visually estimated from Figure 7.12 (p. 267) of Hilborn, R. and C.J. Walters. 1992. Quantitative Fisheries Stock Assessment: Choice, Dynamics, and Uncertainty. Chapman and Hall, New York. 570 p. CSV file

Examples

data(Lizardfish)
str(Lizardfish)
head(Lizardfish)
op <- par(mfrow=c(1,2))
plot(recruits~year,data=Lizardfish,type="l")
plot(recruits~stock,data=Lizardfish)
par(op)

Catch and effort data for Hawaiian Islands Slipper Lobster.

Description

Catches of Slipper Lobster (Scyllarides squammosus) in three categories from the vicinity of Laysan Bank, Hawaiian Islands on 34 consecutive days in 1986.

Format

A data frame with 34 observations on the following 6 variables.

day

Day of the catch

legal

Number of legal lobsters caught.

sublegal

Number of sub-legal lobsters caught.

berried

Number of egg-bearing lobsters caught.

total

Total number of lobsters caught.

effort

Total daily effort expended.

Details

Catch (numbers) of lobster in three categories - legal (tail weight greater than 85g), sublegal (tail weight less than 85g), and berried (egg-bearing females). Sublegal and berried lobsters were returned to the water.

The vessel fished between 11 June and 14 July 1986 in the vicinity of Laysan Island and its associated bank. The daily operations of the vessel involved deploying and hauling 1,125 Fathom Plus lobster traps set in strings spaced at 30 m intervals.They were fished in 7 strings of about 160 traps each and baited with Pacific Mackerel, Scomber japonicus. Strings were soaked overnight and retrieved the following day; therefore, the standard unit of effort is the trap-haul.

Topic(s)

Source

From Table 1 of Clarke, R.P., and S.S. Yoshimoto. 1990. Application of the Leslie model to commercial catch and effort of the slipper lobster, Scyllarides squammosus, fishery in the northwestern hawaiian islands. Marine Fisheries Review 52(2):1-7. CSV file

Examples

data(LobsterHI)
str(LobsterHI)
head(LobsterHI)

Catch and effort data for Prince Edward Island Lobster.

Description

Catch and effort data for Lobster from 33 days in 1944 from the Tignish area of Prince Edward Island.

Format

A data frame with 34 observations on the following 3 variables.

day

Day of the catch. Day 1 is 2-May-1944.

catch

Catch of Lobster in 1000s of pounds.

effort

Total daily effort expended in 1000s of traps.

Details

Catch (1000s of pounds) and effort (1000s of traps) of Lobster from 33 days in 1944 from the Tignish area of Prince Edward Island. The data start on 2-May. These data are from DeLury (1947) who used the data after 22-May (i.e., day 16) to illustrate his depletion method. The data were also used in Example 7.1 of Seber (2002). DeLury (1947) noted that the weight of Lobster did not change appreciably over time so that the poundage caught is a reasonable surrogate for numbers caught.

Topic(s)

Source

From Table 1 of DeLury, D.B. 1947. On the estimation of biological populations. Biometrics 3:145-167. CSV file

Examples

data(LobsterPEI)
str(LobsterPEI)
head(LobsterPEI)

Catch-at-age for Gulf Menhaden, 1964-2004.

Description

Estimated catch-at-age for Gulf Menhaden (Brevoortia patronus), 1964-2004 from the reduction fishery in the U.S. Gulf of Mexico.

Format

A data frame with 41 observations on the following 7 variables.

year

Year of capture.

age0

Estimated catch (millions) of age-0 fish.

age1

Estimated catch (millions) of age-1 fish.

age2

Estimated catch (millions) of age-2 fish.

age3

Estimated catch (millions) of age-3 fish.

age4

Estimated catch (millions) of age-4 fish.

age5

Estimated catch (millions) of age-5 fish.

age6

Estimated catch (millions) of age-6 fish.

Topic(s)

Source

From Table 2 in Vaughan, D.S., K.W. Shertzer, and J.W. Smith. 2007. Gulf menhaden (Brevoortia patronus) in the U.S. Gulf of Mexico: Fishery characteristics and biological reference points for management. Fisheries Research 83:263-275. CSV file

Examples

data(Menhaden1)
str(Menhaden1)
head(Menhaden1)
ages <- 0:6
# Extract one year, delete year column (the -1), and transpose to be a vector
ct <- t(Menhaden1[Menhaden1$year==1974,-1])
plot(ct~ages,pch=16,type="b",xlab="Age",ylab="Est. Catch (Millions)",main="year==1974")

Ages of Morwong assigned from otoliths by Reader A at two times.

Description

Ages assigned at two different times by Reader A to the otoliths of Jackass Morwong (Nemadactylus macropterus).

Format

A data frame with 217 paired observations on the following 2 variables.

first

Ages assigned on the first reading

second

Ages assigned on the second reading

Topic(s)

Source

From Table 5 of Restall, J.E., and K. Krusic-Golub. 2004. Development of jackass morwong age-length keys for 2000-2002. Final report to Australian Fisheries Management Authority. 13 pp. Primary Industries Research Victoria, Queenscliff. CSV file

Examples

data(Morwong1)
str(Morwong1)
head(Morwong1)
plot(second~first,data=Morwong1)
xtabs(~first+second,data=Morwong1)

Ages of Morwong assigned from otoliths by Reader B at two times.

Description

Ages assigned at two different times by Reader B to the otoliths of Jackass Morwong (Nemadactylus macropterus).

Format

A data frame with 136 observations on the following 2 variables.

first

Ages assigned on the first reading

second

Ages assigned on the second reading

Topic(s)

Source

From Table 6 of Restall, J.E., and K. Krusic-Golub. 2004. Development of jackass morwong age-length keys for 2000-2002. Final report to Australian Fisheries Management Authority. 13 pp. Primary Industries Research Victoria, Queenscliff. CSV file

Examples

data(Morwong2)
str(Morwong2)
head(Morwong2)
plot(second~first,data=Morwong2)
xtabs(~first+second,data=Morwong2)

Ages of Morwong assigned from otoliths by two readers.

Description

Ages assigned by two different readers to the otoliths of Jackass Morwong (Nemadactylus macropterus).

Format

A data frame with 58 paired observations on the following 2 variables.

readerA

Ages assigned by Reader A

readerB

Ages assigned by Reader B

Topic(s)

Source

From Table 7 of Restall, J.E., and K. Krusic-Golub. 2004. Development of jackass morwong age-length keys for 2000-2002. Final report to Australian Fisheries Management Authority. 13 pp. Primary Industries Research Victoria, Queenscliff. CSV file

Examples

data(Morwong3)
str(Morwong3)
head(Morwong3)
plot(readerB~readerA,data=Morwong3)
with(Morwong3,table(readerA,readerB))

Ages and lengths of Morwong.

Description

Assigned ages (from otoliths) and fork lengths of Jackass Morwong (Nemadactylus macropterus) from the Eastern portion of the Southern and Eastern Scalefish and Shark Fishery (SESSF) in 2000.

Format

A data frame with 392 observations on the following 2 variables:

fl

Measured fork lengths (cm).

age

Assigned ages (from otoliths).

Topic(s)

Source

Ffrom appendix 1 of of Restall, J.E., and K. Krusic-Golub. 2004. Development of jackass morwong age-length keys for 2000-2002. Final report to Australian Fisheries Management Authority. 13 pp. Primary Industries Research Victoria, Queenscliff. CSV file

See Also

Morwong4a.

Examples

data(Morwong4)
str(Morwong4)
head(Morwong4)
plot(fl~age,data=Morwong4)

Ages (subsample) and lengths (all fish) for Morwong from Morwong4.

Description

A total of 104 fish dispersed proportionately over 1-cm fork length intervals from the Morwong4 data frame was obtained for age assignment. The remaining fish in the file were only measured for length (i.e., the ages were deleted). This data file can be used to demonstrate the use of age-length keys.

Format

A data frame with 392 observations on the following 2 variables.

fl

Fork lengths (cm)

age

Assigned ages

Topic(s)

Source

CSV file

See Also

Morwong4.

Examples

data(Morwong4a)
str(Morwong4a)
head(Morwong4a)

## extract aged sample
m4a.aged <- subset(Morwong4a,!is.na(age))
str(m4a.aged)

## extract length sample
m4a.length <- subset(Morwong4a,is.na(age))
str(m4a.length)

Ages and lengths of Eastern Mosquitofish from ten locations from southern France to southern Spain.

Description

Ages and lengths of Eastern Mosquitofish (Gambusia holbrooki) from ten locations from southern France to southern Spain.

Format

A data frame with the following 8 variables:

site

Site (as a name) of capture.

sitenum

Site (as a number) of capture.

day

Day of capture.

month

Month of capture.

year

Year of capture.

sl

Standard length (to nearest 0.01 cm).

age

Age in integer years.

age2

Age in decimal years.

Topic(s)

Source

From figure 3 of Carmona-Catot, G., A.F.G.N. Santos, P.A. Tedesco, and E. Garcia-Berthou. 2014. Quantifying seasonality along a latitudinal gradient: From stream temperature to growth of invasive mosquitofish. Ecosphere 5:134. CSV file

Examples

data(Mosquitofish)
str(Mosquitofish)
head(Mosquitofish)
plot(sl~age2,data=Mosquitofish)

Ages of Red Mullet assigned from whole and broken-burnt otoliths.

Description

Ages assigned to whole and broken-burnt otoliths of Red Mullet (Mullus barbatus ponticus) sampled from the Black Sea (Samsun, Turkey).

Format

A data frame with 51 paired observations on the following 2 variables.

whole

Ages assigned from whole otoliths

bb

Ages assigned from broken/burnt otoliths

Topic(s)

Source

From Figure 3 of Polat, N., D. Bostanci, S. Yilmaz. 2005. Differences between whole otolith and broken-burnt otolith ages of red mullet (Mullus barbatus ponticus Essipov, 1927) sampled from the Black Sea (Samsun, Turkey). Turkish Journal of Veterinary and Animal Science 29:429-433. CSV file

Examples

data(MulletBS)
str(MulletBS)
head(MulletBS)
plot(whole~bb,data=MulletBS)
xtabs(~bb+whole,data=MulletBS)

Ages of Muskellunge assigned from scales and cleithra.

Description

Ages of St. Lawrence River, ONT, Muskellunge (Esox masquinongy) assessed from scales and cleithra.

Format

A data frame of 43 observations on the following 2 variables:

ageC

Age assigned from examinaton of cleithrum

ageS

Age assigned from examination of scales

Topic(s)

Source

From Figure 3 in Casselman,J.M. 1983. Age and growth assessment of fish from their calcified structures - techniques and tools. In E.D. Prince and L.M. Pulos, editors, Proceedings of the international workshop on age determination of oceanic pelagic fishes: Tunas, billfishes, and sharks, volume NOAA Technical Report, NMFS 8:1-17. CSV file

Examples

data(MuskieSLR)
str(MuskieSLR)
head(MuskieSLR)
plot(ageS~ageC,data=MuskieSLR)
xtabs(~ageC+ageS,data=MuskieSLR)

Summarized mark-recapture data for Muskellunge from many Wisconsin Lakes, 2006.

Description

The number of Muskellunge (Esox masquinongy) from a variety of lakes in Wisconsin, 2006.

Format

A data frame with 40 observations on the following 7 variables.

county

County of the collection

lake

Lake of the collection

sex

Sex of the Muskellunge (male, female, unknown, total)

mark

Total number of fish marked on the marking run

catch

Total number of fish caught on the recapture run

recap

Total number of previously marked fish in the recapture run

Topic(s)

Source

Wisconsin Department of Natural Resources. CSV file

Examples

data(MuskieWI06MR)
str(MuskieWI06MR)
head(MuskieWI06MR)

Stock and recruitment data for Alaskan Pink Salmon, 1960-1990.

Description

Harvest, escapement, and return of northern Southeast Alaska Pink Salmon (Oncorhynchus gorbuscha), 1960-1991, and average sea surface temperature between June and November off Sitka, Alaska, 1960-1990.

Format

A data frame of 34 rows on the following 5 variables:

year

Year of data

harvest

Harvest (thousands of fish)

escapement

Escapement (thousands of fish)

return

Returns (thousands of fish) as sum of harvest and escapement from two years later (lagging is for proper brood year correspondence)

SST

Average sea surface temperature (C) between June and November off Sitka, AK from one year latter (lagging is for matching when the salmon are actually in the ocean)

Topic(s)

Source

From Table 3.1 in Quinn, T.J. and R.B. Deriso. 1999. Quantitative Fish Dynamics. Oxford University Press, New York, New York. CSV file

Examples

data(PSalmonAK)
str(PSalmonAK)
head(PSalmonAK)
op <- par(mfrow=c(1,2))
plot(return~year,data=PSalmonAK)
plot(return~escapement,data=PSalmonAK)
par(op)

Lengths and weights for Pallid Sturgeon from four locations in the Missouri River.

Description

Lengths (standard, fork, and total) and weights for Pallid Sturgion (Scaphirhynchus albus) collected at four locations in the Missouri River drainage.

Format

A data frame with 30 observations on the following 7 variables:

date

Date of collection

sl

Standard length (mm)

fl

Fork length (mm)

tl

Total length (mm)

w

Weight (g)

status

Living status of fish at time of collection (Frozen, Live, Dead).

loc

Location of fish collection (NB=Nebraska, SD=South Dakota, ND=North Dakota, MT=Montana)

Topic(s)

Source

From Table 1 in Keenlyne, K.D. and S.J. Maxwell. 1993. Length conversions and length-weight relations for pallid sturgeon. North American Journal of Fisheries Management 13:395-397. CSV file

Examples

data(Pallid)
str(Pallid)
head(Pallid)
op <- par(mfrow=c(2,2),pch=19)
## four (of many possible) examples
plot(w~tl,data=Pallid,subset=loc=="NB",main="Nebraska")
plot(w~tl,data=Pallid,subset=loc=="SD",main="South Dakota")
plot(w~tl,data=Pallid,subset=loc=="ND",main="North Dakota")
plot(w~tl,data=Pallid,subset=loc=="MT",main="Montana")
par(op)

Catch and effort for three Snapper species in a depletion experiment.

Description

Catch and effort for three Snapper species (Pristipomoides zonatus, Pristipomoides auricilla, and Etelis carbunculUs) in a depletion experiment around Pathfinder Reef in the Mariana Archipelago.

Format

A data frame with 13 observations on the following 5 variables.

date

Date (1984)

effort

Fishing effort (line-hours of a bottom hand-line)

Pzonatus

Catch of Pristipomoides zonatus

Pauricilla

Catch of Pristipomoides auricilla

Ecarbunculus

Catch of Etelis carbunculUs

Topic(s)

Source

From Table 3 of Polovina, J.J. 1985. A variable catchability version of the Leslie model with application to an intensive fishing experiment on a multispecies stock. Fishery Bulletin 84:423-428. CSV file

Examples

data(Pathfinder)
str(Pathfinder)
head(Pathfinder)

Capture histories (2 samples) of Northern Pike from Harding Lake.

Description

Capture histories for Northern Pike (Esox lucius) captured from Harding Lake, 1990.

Format

A data frame with 481 observations on the following 3 variables.

fish

a numeric vector of unique fish identification numbers

first

a numeric vector of indicator variables for the first sample (1=captured)

second

a numeric vector of indicator variables for the second sample (1=captured)

Topic(s)

Note

Only Northern Pike >449 mm were considered here.

Source

Capture histories simulated from summarized data in table 2 and text of Burkholder, A. 1991. Abundance and composition of northern pike, Harding Lake, 1990. Fishery Data Series 91-9, Alaska Department of Fish and Game. [Was (is?) from http://www.sf.adfg.state.ak.us/FedAidpdfs/Fds91-09.pdf.] CSV file

Examples

data(PikeHL)
str(PikeHL)
head(PikeHL)

Catch and effort data for Northern Pike from Island Lake, NB.

Description

Catch and effort data for nine removal events of Northern Pike (Esox lucius) from Island Lake, NB.

Format

A data frame with 9 observations on the following 3 variables:

date

Capture date.

nets

Number of fyke nets fished on that date.

catch

Number of captured and removed pike.

Topic(s)

Source

From Table 1 of Peterson, J., M. Taylor, and A. Hanson. 1980. Leslie population estimate for a large lake. Transactions of the American Fisheries Society, 109:329-331. CSV file

Examples

data(PikeIL)
str(PikeIL)
head(PikeIL)

Capture histories (4 samples) of a subset of Northern Pike from Buckthorn Marsh.

Description

Capture histories (4 samples), in capture-by-date format, of a subset of Northern Pike from Buckthorn Marsh.

Format

A data frame with 69 observations on the following 2 variables.

sample

Name of the sample taken

id

Unique fish identification numbers

Details

Each line consists of the date and unique fish identification number over four samples of northern pike (Esox lucius) in Buckthorn Marsh. This file contains the capture histories for only those pike captured from April 1-4.

Topic(s)

Source

Simulated from summary data in Table C-1 of New York Power Authority. 2004. Use of Buckhorn Marsh and Grand Island tributaries by Northern Pike for spawning and as a nursery. Technical report, New York Power Authority, January 2004. Niagara Power Project (FERC No. 2216). CSV file

Examples

data(PikeNYPartial2)
str(PikeNYPartial2)
head(PikeNYPartial2)

Stock and recruitment data for Northern Pike from Lake Windermere, 1944-1981.

Description

Stock and recruitment data for Northern Pike (Esox lucius) from Lake Windermere, 1944-1981.

Format

A data frame of 75 observations on the following two variables:

year

Year

stock

Female biomass (kg)

recruits

Number at age-2

basin

Basin of Windermere (North or South)

tdd14

Temperature degree-days over 14C

Topic(s)

Note

Stock values were originally reported in 1000s of kgs and recruits were originally recorded in tens of numbers. Thus, plots look very discrete.

Source

From table 3 in Kipling, C. 1983. Changes in the population of pike (Esox lucius) in Windermere from 1944 to 1981. Journal of Animal Ecology 52:989-999. CSV file

Examples

data(PikeWindermere)
str(PikeWindermere)
head(PikeWindermere)
op <- par(mfrow=c(2,2),pch=19)
plot(recruits~year,data=PikeWindermere,subset=basin=="North",main="North")
plot(recruits~stock,data=PikeWindermere,subset=basin=="North",main="North")
plot(recruits~year,data=PikeWindermere,subset=basin=="South",main="South")
plot(recruits~stock,data=PikeWindermere,subset=basin=="South",main="South")
par(op)

Biological data for Pygmy Whitefish from Dina Lake #1 (British Columbia), 2000 and 2001.

Description

Biological information for Pygmy Whitefish (Prosopium coulterii) from Dina Lake #1 (British Columbia), 2000 and 2001.

Format

A data frame with 690 observations on the following 13 variables.

year

Year of capture (2000, 2001)

month

Month of capture

week

Week within a month of capture

net_no

Unique net identification number

fish_no

Unique fish identification number

fl

Fork length (cm)

tl

Total length (cm)

wt

Weight (g)

sex

Sex code (F=Female, M=Male, Imm=immature)

mat

Maturity code (Imm=immature, MG=maturing, MT=mature)

scale_age

Scale age (in years)

oto_age

Otolith age (in years)

USE

Should the individual be used for analyses.

Topic(s)

Note

The tl and USE variables were added or teaching purposes only. The tl was created from fl using a known fl-tl relationship and a small random error.

Source

2000 data from Appendix 9 of J. D. McPhail and R. J. Zemlak. October 2001. Pygmy Whitefish studies on Dina Lake #1, 2000. Peace/Williston Fish and Wildlife Compensation Program, Report No. 245. 36pp plus appendices.

2001 data from Appendix 14 of Zemlak, R.J. and J.D. McPhail. 2003. Pygmy Whitefish studies on Dina Lake #1, 2001. Peace/Williston Fish and Wildlife Compensation Program Report No. 279. 35pp plus appendices. [Was (is?) from http://a100.gov.bc.ca/appsdata/acat/documents/r39503/pwfwcp_report_no_279_1383686631923_d6d1b25e3156cee45e442c5b3f756a6a7b4bb7ad7753efb1c51dc23ac997a9a6.pdf.] CSV file

Examples

data(PygmyWFBC)
str(PygmyWFBC)
head(PygmyWFBC)

Recruitment time-series for Rainbow Smelt in Lake Erie, 1977-1996.

Description

Rainbow Smelt (Osmerus mordax) recruitment time series for Lake Erie, 1977-1996.

Format

A data frame of 20 observations on the following 2 variables:

year

Year of data.

recruits

Number of recruits (per hour).

Topic(s)

Note

Zeros were changed to 0.1 in 1984, 1987, 1991, and 1994.

Source

From Ontario Ministry of Natural Resources, Fish and Wildlife Branch, 1997. Lake Erie fisheries report 1996. Lake Erie Committee Meeting, Great Lakes Fishery Commission, Ann Arbor, Michigan. pp 26. Obtained from Ransom Myers old online database. CSV file

Examples

data(RBSmeltErie)
str(RBSmeltErie)
head(RBSmeltErie)
plot(recruits~year,data=RBSmeltErie,type="l")

Lengths for Rainbow Smelt from Lake Michigan, 1977.

Description

Rainbow Smelt (Osmerus mordax) fork lengths from near Grand Haven, Lake Michigan, 1977.

Format

A data frame of 3293 observations on the following 1 variable:

fl

Fork length (mm)

Topic(s)

Source

From Brandt, S.B., J.J. Magnuson, and L.B. Crowder. 1980. Thermal habitat partitioning by fishes in Lake Michigan. Canadian Journal of Fisheries and Aquatic Sciences. 37:1557-1564. Data was simulated (uniform distribution of values within length bin) from summarized length frequencies in http://fishbase.org/. CSV file

Examples

data(RBSmeltLM)
str(RBSmeltLM)
head(RBSmeltLM)
hist(RBSmeltLM$fl,main="")

Length-at-marking and recapture and time-at-large of Rainbow Trout.

Description

Length-at-marking and recapture and time-at-large for Rainbow Trout (Oncorhynchus mykiss) from the Kenai River, Alaska.

Format

A data frame with 102 observations on the following 3 variables:

Lr

Length (mm) at recapture.

Lm

Length (mm) at marking.

dt

Time-at-large (yrs).

Topic(s)

Source

From Table 4.10 in Quinn, T.J. and R.B. Deriso. 1999. Quantitative Fish Dynamics. Oxford University Press. 560 pages. This table is a 1/3rd subsample of the actual data presented in Baker, T.T., R. Lafferty, and T.J. Quinn II. 1991. A general growth model for mark-recapture data. Fisheries Research 11:257-281. CSV file

Examples

data(RBTroutKenai)
str(RBTroutKenai)
head(RBTroutKenai)
plot((Lr-Lm)~dt,data=RBTroutKenai)

Capture histories (2 sample) of Rainbow Trout.

Description

Capture histories for Rainbow Trout (Oncorhynchus mykiss) in Upper Niagara Springs pond.

Format

A data frame with 173 observations on the following 2 variables:

first

Indicator variable for the first sample (1=captured)

second

Indicator variable for the second sample (1=captured)

Topic(s)

Source

Simulated from Table 10 in of Warren, C.D., K.A. Frank, and F.E. Partridge. 2004. Federal Aid in Fish Restoration - 2000 job performance report. Idaho Department of Fish and Game. CSV file

Examples

data(RBTroutUNSP)
str(RBTroutUNSP)
head(RBTroutUNSP)

Ages and lengths of Round Whitefish.

Description

Ages and total lengths of Round Whitefish (Prosopium cylindraceum) collected from the Apostles Islands, Lake Superior.

Format

A data frame with 995 observations on the following 2 variables.

tl

Total length (in).

age

Age (from scales).

Topic(s)

Source

From Table 3 (a random tenths digit was added to the TL) in Bailey, M.M. 1963. Age, growth, and maturity of Round Whitefish of the Apostle Islands and Isle Royale Regions, Lake Superior. Fishery Bulletin, 63:63-75. CSV file

Examples

data(RWhitefishAI)
str(RWhitefishAI)
head(RWhitefishAI)
plot(tl~age,data=RWhitefishAI)

Ages and lengths of Round Whitefish.

Description

Ages and total lengths of Round Whitefish (Prosopium cylindraceum) collected from Isle Royale, Lake Superior.

Format

A data frame with 103 observations on the following 2 variables.

tl

Total length (in).

age

Age (from scales).

Topic(s)

Source

From Table 4 (a random tenths digit was added to the TL) in Bailey, M.M. 1963. Age, growth, and maturity of round whitefish of the Apostle Islands and Isle Royale Regions, Lake Superior. Fishery Bulletin, 63:63-75. CSV file

Examples

data(RWhitefishIR)
str(RWhitefishIR)
head(RWhitefishIR)
plot(tl~age,data=RWhitefishIR)

Ages and lengths for Red Drum from the Atlantic Coast.

Description

Assigned ages (from otoliths) and fork lengths of Red Drum (Sciaenops ocellatus) from various areas of the Atlantic Coast, 1981-1988.

Format

A data frame with 393 observations on the following 2 variables.

age

Age (from otoliths to the nearest years but recorded at half-years)

fl

Fork length (mm)

Topic(s)

Source

From (approximately) Figure 27 in Vaughan, D.S. and T.E. Helser. 1990. Status of the red drum stock of the Atlantic Coast: Stock assessment report for 1989. NOAA Technical Memorandum, NMFS-SEFC-263. CSV file

Examples

data(RedDrum)
str(RedDrum)
head(RedDrum)
plot(fl~age,data=RedDrum)

Summarized multiple mark-recapture data for Tan Riffleshell.

Description

Summarized multiple mark-recapture data for Tan Riffleshell.

Format

A data frame with 6 observations on the following 4 variables.

t

Sample number

caught

Total number of fish caught in the sample

recaps

Number of previously marked fish in the sample

retmarks

Number of marked fish returned to the population

Details

The number of mussels caught in multiple samples of Tan Riffleshell (Epioblasma florentina walkeri) from Indian Creek, Virginia. The caught fish were examined for previous marks, marked (if previously unmarked), and then returned to the population.

Topic(s)

Source

From Table 1-2 of Rogers, S.O. 1999. Population biology of the Tan Riffleshell (Epioblasma florentina walkeri) and the effects of substratum and light on juvenile mussel propagation. Virginia Tech M.S. Thesis. CSV file

Examples

data(Riffleshell)
str(Riffleshell)
head(Riffleshell)

Catch-at-age of Cayuga Lake Rock Bass.

Description

Catch-at-age for Cayuga Lake Rock Bass (Amploplites rupestris) from a single season.

Format

A data frame of 6 observations on the following 2 variables:

age

Assigned age.

catch

Number in catch.

Topic(s)

Source

D.S. Robson and D.G. Chapman. 1961. Catch curves and mortality rates. Transactions of the American Fisheries Society 90:181-189. CSV file

Examples

data(RockBassCL)
str(RockBassCL)
RockBassCL
plot(log(catch)~age,data=RockBassCL)

Ages and lengths of Lake Ontario Rock Bass.

Description

Assigned ages (from scales) and measured total lengths for each of 1288 Rock Bass (Ambloplites rupestris) from Lake Ontario.

Format

A data frame with 1288 observations on the following 2 variables:

age

Assigned ages (from scales).

tl

Measured total lengths (mm).

Topic(s)

Source

Simulated from Table 1 of Wolfert, D.R. 1980. Age and growth of Rock Bass in Eastern Lake Ontario. New York Fish and Game Journal 27:88:90. CSV file

See Also

RockBassLO2.

Examples

data(RockBassLO1)
str(RockBassLO1)
head(RockBassLO1)
plot(tl~age,data=RockBassLO1)

Ages (subsample) and lengths (all fish) for Rock Bass from Lake Ontario.

Description

Ages (subsample) and lengths (all fish) for Rock Bass from Lake Ontario.

Format

A data frame with 1288 observations on the following 2 variables:

age

Assigned ages (from scales)

tl

Measured total lengths (mm)

Details

As many as 10 fish per 10-mm total length intervals from the RockBassLO1 data.frame was obtained for age assignment. The remaining fish in the file were only measure for length (i.e., the ages were deleted). This data file can be used to demonstrate the use of age-length keys.

Topic(s)

Source

CSV file

See Also

RockBassLO1.

Examples

data(RockBassLO2)
str(RockBassLO2)
head(RockBassLO2)

## extract aged sample
rb.aged <- subset(RockBassLO2,!is.na(age))

## extract length sample
rb.length <- subset(RockBassLO2,is.na(age))

Biological data for Ruffe captured from the St. Louis River in 1992.

Description

Biological data for Ruffe (Gymnocephalus cernuus) captured in the St. Louis River, Lake Superior in 1992.

Format

A data frame of 738 observations on the following 11 variables:

fish.id

A unique fish identification number (across all years, most of which are not shown in this file

month

Month (numeric) of capture

day

Day of capture

year

Year of capture

indiv

A unique fish identification number within the year

location

Grid location of capture

length

Total length (mm)

weight

Weight (g)

sex

Sex factor (female, male, or unknown)

maturity

Maturity stage factor (developing, immature, mature, nearly.ripe, nearly.spent, recovering, ripe, running, spent, unknown, or yoy)

age

Age (yrs) from scales

Topic(s)

Source

personal collection by the United States Geological Survey, Lake Superior Biological Station, Ashland, WI. CSV file

Examples

data(RuffeSLRH92)
str(RuffeSLRH92)
head(RuffeSLRH92)
op <- par(mfrow=c(2,2),pch=19)
hist(RuffeSLRH92$length,main="")
hist(RuffeSLRH92$age,main="")
plot(weight~length,data=RuffeSLRH92)
plot(length~age,data=RuffeSLRH92)
par(op)
xtabs(~age,data=RuffeSLRH92)
xtabs(~sex,data=RuffeSLRH92)
tmp <- c("yoy","immature","developing","mature","nearly.ripe","ripe",
         "running","nearly.spent","spent","recovering","unknown")
RuffeSLRH92$maturity <- ordered(RuffeSLRH92$maturity,levels=tmp)
xtabs(~maturity,data=RuffeSLRH92)
xtabs(~maturity+month+sex,data=RuffeSLRH92)

Lengths of Ruffe captured from the St. Louis River in July, 1989.

Description

Total length for Ruffe (Gymnocephalus cernuus) captured in July, 1989 (cycle 6) in the St. Louis River, Lake Superior.

Format

A data frame of 236 observations on the following 1 variable:

tl

Total length (mm).

Topic(s)

Source

personal collection by the United States Geological Survey, Lake Superior Biological Station, Ashland, WI. CSV file

Examples

data(RuffeTL89)
str(RuffeTL89)
head(RuffeTL89)
hist(RuffeTL89$tl,main="")

Stock and recruitment data for Sea Lamprey in the Great Lakes, 1997-2007.

Description

Stock and recruitment data for Sea Lamprey (Petromyzon marinus) in the Great Lakes, 1997-2007 from 37 streams.

Format

A data frame of 76 observations on the following two variables:

stock

Female spawners per 100 square meters.

recruits

Yearlngs per 100 square meters.

Topic(s)

Source

From (approximately) Figures 2a and 2b in Dawson, H.A. and M.L. Jones. 2009. Factors affecting recruiting dynamics of Great Lakes sea lamprey (Petromyzon marinus) populations. Journal of Great Lakes Research 35:353-360. CSV file

Examples

data(SLampreyGL)
str(SLampreyGL)
head(SLampreyGL)
plot(recruits~stock,data=SLampreyGL)

Catches in removal events of salmon parr.

Description

Catches in removal events of salmon parr from the Afon Dulas at Pentre, 19Jun79.

Format

A data frame with 5 observations on the following 2 variables:

catch

Removal event.

caught

Number of fish captured and removed.

Topic(s)

Source

From Table 2 in Cowx, I.G. 1983. Review of the methods for estimating fish population size from survey removal data. Fisheries Management 14:67-82. CSV file

See Also

TroutADP

Examples

data(SalmonADP)
str(SalmonADP)
SalmonADP

Catches in removal events of Cutthroate Trout and Steelhead of various sizes in two reaches of McGarvey Creek (CA).

Description

Catches in removal events of Cutthroate Trout (Oncorhynchus clarki) and Steelhead (Oncorhynchus mykiss) of various sizes in two reaches of McGarvey Creek (CA).

Format

A data frame of 5 observations on the following 5 variables:

reach

Sampling location.

group

Size or species caught (fry=both age-0 Cutthroat Trout and Steelhead, Steelhead=age-1+ Steelhead, or Cutthroat=age-1+ Cutthroat Trout).

pass1

Catch on the first removal pass.

pass2

Catch on the second removal pass.

pass3

Catch on the third removal pass.

Details

Sampling was conducted using a Smith Root model 15-D POW electrofisher. Block nets were placed at upstream and downstream reach boundaries. Efforts were made to keep the effort consistent between passes. Fixed electrofisher settings were used to maintain capture probabilities during sampling. Index reaches were rested for at least 90 minutes between passes to allow recovery time for fish not captured.Fish were measured (fork length in mm) and weighed to the nearest 0.1 gm. Scales were collected from below the dorsal fin on both left and right sides of selected fish. After data were recorded for each pass, fish were placed in a loating live car until all sampling was completed. Fish were then released throughout the reach.

Topic(s)

Source

From Table 2 of Voight, H. 1999. Assessment of juvenile salmonid populations in two index reaches of McGarvey Creek, a tributary to the lower Klamath River. First Year of Investigations - 1998. [Was (is?) from http://www.krisweb.com/biblio/klamath_yuroktfp_voight_1999_7.pdf.] CSV file

Examples

data(SalmonidsMCCA)
str(SalmonidsMCCA)
head(SalmonidsMCCA)

## extract data for one reach and group (e.g., 3rd row)
SalmonidsMCCA[3,]

Ages and lengths of two year-classes of Sardine from Chilean waters.

Description

Ages (in months) and total lengths of two year-classes of Sardine (Strangomera bentincki) from central Chilean waters.

Format

A data frame with 196 observations of the following 3 variables:

age.mon

Age in months.

tl.cm

Total length (cm).

cohort

Year-class.

Topic(s)

Source

Directly from the authors of Cubillos, L.A., D.F. Arcosa, D.A. Bucareya, M.T. Canalesa. 2001. Seasonal growth of small pelagic fish off Talcahuano, Chile (37S, 73W): a consequence of their reproductive strategy to seasonal upwelling? Aquatic Living Resources, 14:115-124. Data were in Figure 9. CSV file

Examples

data(SardineChile)
str(SardineChile)
head(SardineChile)
SardineChile$age <- SardineChile$age.mon/12
plot(tl.cm~age,data=SardineChile)

Ages and lengths of larval Lake Tanganyika Sardine.

Description

Ages (days) and total lengths of larval Lake Tanganyika Sardine (Limnothrissa miodon) from Lake Kariba.

Format

A data frame with 75 observations on the following 2 variables.

days

Age in days (determine from otoliths).

tl

Total length (mm within 0.1).

Topic(s)

Source

From (approximately) Figure 3 of Mtsambiwa, M.Z. 1992. Fitting a von Bertalanffy growth model to length at age data for larval Limnothrissa miodon from Lake Kariba. Paper presented at the Symposium on biology, stock assessment, and exploitation of small pelagic fish species in the African Great Lakes region. [Was (is?) from http://www.fao.org/docrep/005/v2648e/V2648E06.htm.] CSV file

Examples

data(SardineLK)
str(SardineLK)
head(SardineLK)
plot(tl~days,data=SardineLK)

Stock and recruitment data for Pacific Sardines, 1935-1990.

Description

Pacific Sardine (Sardinops sagax) stock and recruitment by year, 1935-1990.

Format

A data frame of 34 observations on the following 3 variables:

year

Year of data

ssb

Spawning stock biomass – millions of fish

recruits

Recruitment index – millions of fish

Topic(s)

Source

From Jacobson, L.D. and A.D. MacCall. 1995. Stock-recruitment models for Pacific Sardine (Sardinops sagax). Canadian Journal of Fisheries and Aquatic Sciences 52:566-577. CSV file

Examples

data(SardinesPacific)
str(SardinesPacific)
head(SardinesPacific)
op <- par(mfrow=c(1,2),pch=19)
plot(recruits~year,data=SardinesPacific,type="l")
plot(recruits~ssb,data=SardinesPacific)
par(op)

Biological data for Slimy Sculpin from the Arctic LTER (AK).

Description

Biological data (length, weight, and age) for Slimy Sculpin (Cottus cognatus) sampled from Lake S-6 of the Arctic Long Term Ecological Research location.

Format

A data frame of 117 observations on the following 3 variables:

w

Weight (nearest 0.1 g) at capture

tl

Total length (nearest mm) at capture

age

Age (completed growing seasons from otoliths) at capture

Details

Slimy Sculpin were captured from Lake S-6 during the summers of 1988 and 1989. Sculpins were captured using canning jars with acetate funnels inserted in them (similar in design to some minnow traps). The sculpin traps were set by raft and placed on the bottom of the lake in a specific habitat (inshore, rocky, rock-mud interface, and mud bottom). (Roughly) every three days the traps were retrieved and the sculpins, if any, were removed.The ages of the fish were determined by counting the rings in their otoliths.

Topic(s)

Source

Obtained from the Arctic LTER site. CSV file

Examples

data(SculpinALTER)
str(SculpinALTER)
head(SculpinALTER)
op <- par(mfrow=c(2,2),pch=19)
hist(SculpinALTER$tl,main="")
hist(SculpinALTER$age,main="")
plot(w~tl,data=SculpinALTER)
plot(tl~age,data=SculpinALTER)
par(op)

Ages of American Shad assigned from scales by three readers at two times.

Description

Ages of American Shad (Alosa sapidissima) assigned from scales by three readers at two times.

Format

A data frame with 53 observations on the following 8 variables.

fishID

A unique fish identification number

trueAge

The true age of the fish

agerA1

Ages assigned by reader A at time 1

agerA2

Ages assigned by reader A at time 2

agerB1

Ages assigned by reader B at time 1

agerB2

Ages assigned by reader B at time 2

agerC1

Ages assigned by reader C at time 1

agerC2

Ages assigned by reader C at time 2

Details

The true ages for fish in their sample were known because the Shad had been marked prior to being stocked. Additionally, 13 biologists twice (independently) estimated the age from scales for each fish. The known age of the fish (trueAge) and the age estimates from three of the 13 biologists are available in this data.frame. The estimated age variables are labeled with ager, a letter for the three biologists (A, B, or C) and a number for which time the scale was interpreted (1 or 2). Some biologists chose not to assign an age to some scales and, thus, those data are missing (shown as NA values).

Topic(s)

Note

Used in the Introductory Fisheries Analyses with R book.

Source

From McBride, R.S., Hendricks, M.L., and Olney, J.E. 2005. Testing the validity of Cating's (1953) method for age determination of American Shad using scales. Fisheries, 30:10-18. Obtained directly from Rich McBride. CSV file

Examples

data(ShadCR)
str(ShadCR)
head(ShadCR)
op <- par(mfrow=c(2,2),pch=19)
plot(agerA1~agerA2,data=ShadCR)
plot(agerB1~agerB2,data=ShadCR)
plot(agerC1~agerC2,data=ShadCR)
plot(agerA1~agerB1,data=ShadCR)
par(op)

Catch and effort data for Deepwater Caridean Shrimp.

Description

Catch and effort data for Deepwater Caridean Shrimp (Heterocarpus laevigatus) from 15 days in 1984 from near Alamagan Islan in the Marian Archipelago (near Guam).

Format

A data frame with 15 observations on the following 4 variables.

day

Day of the catch. Day 9 is 9-Jan-1984.

standard

Catch (kg) of of Shrimp in the standard traps.

pyramid

Catch (kg) of of Shrimp in the pyramid traps.

effort

Total effort (trap-nights) for the standard traps.

Details

Catch (kg) and effort (trap-nights) of Deepwater Caridean Shrimp (Heterocarpus laevigatus) from 15 days in 1984 from near Alamagan Islan in the Marian Archipelago (near Guam). The data start on 9-Jan-1984. Catches were recorded separately for standard traps and in pyramid traps.

The original authors estimated populations size using the Leslie method with the cumulative catch from the combined catch in the standard and pyramid traps, but with a CPE computed from just the catch in standard traps.

Topic(s)

Source

From Table 1 of Ralson, S. 1986. An intensive fishing experiment for the Caridean Shrimp, Heterocarpus laevigatus, at Alamagn Island in the Mariana Archipelago. Fishery Bulletin 84:927-934. CSV file

Examples

data(ShrimpGuam)
str(ShrimpGuam)
head(ShrimpGuam)

## Computations by the original authors
# CPE for just the standard traps
ShrimpGuam$CPE <- ShrimpGuam$standard/ShrimpGuam$effort
# Total catch in both traps
ShrimpGuam$total <- ShrimpGuam$standard+ShrimpGuam$pyramid
# Cumulative catch in both traps (with the Ricker modification)
ShrimpGuam$cumCatch <- cumsum(ShrimpGuam$total)-ShrimpGuam$total/2

Catches in removal events of trout at various locations.

Description

Catches of various species in consecutive removal events at various locations.

Format

A data frame of 58 observations on the following 7 variables:

species

Species of fish.

stream

Stream name.

first

Catch on the first removal pass.

second

Catch on the second removal pass.

third

Catch on the third removal pass.

fourth

Catch on the fourth removal pass.

pop.cs

Population estimate by Carle-Strub method.

Topic(s)

Source

From Appendix in Simonson, T.D. and J. Lyons. 1995. Comparison of catch per effort and removal procedures for sampling stream fish assemblages. North American Journal of Fisheries Management 15:419-427. CSV file

Examples

data(SimonsonLyons)
str(SimonsonLyons)
head(SimonsonLyons)

## extract data for one species and stream (e.g., 3rd row)
SimonsonLyons[3,]

Ages (subsample) and lengths (all fish) for male and female Siscowet Lake Trout captured at four locations in Michigan waters of Lake Superior.

Description

Ages (subsample) and lengths (all fish) for male and female Siscowet Lake Trout captured at four locations in Michigan waters of Lake Superior.

Format

A data frame with 780 observations on the following 8 variables.

locID

Locations (Blind Sucker,Deer Park,Grand Marais,Little Lake Harbor)

pnldep

Depth of gillnet panel in which the fish was captured

mesh

Gillnet stretch mesh measure

fishID

Unique fish identification code

sex

Sex (F and M)

age

Assigned ages (yrs; from otoliths)

len

Total length (mm)

wgt

Weight (g)

Topic(s)

Note

Used in the Introductory Fisheries Analyses with R book.

Source

Obtained directly from the U.S. Fish and Wildlife Service via Michael Seider. CSV file

Examples

data(SiscowetMI2004)
str(SiscowetMI2004)
head(SiscowetMI2004)
xtabs(~age+locID,data=SiscowetMI2004)
op <- par(mfrow=c(2,2),pch=19)
plot(len~age,data=SiscowetMI2004,subset=locID=="Blind Sucker",main="Blind Sucker")
plot(len~age,data=SiscowetMI2004,subset=locID=="Grand Marais",main="Grand Marais")
plot(len~age,data=SiscowetMI2004,subset=locID=="Little Lake Harbor",main="Little Lake Harbor")
par(op)

Lengths for Snapper from Australia.

Description

Lengths of Australian Snapper (Chrysophrys auratus) taken by trawl.

Format

A data frame of 256 observations on the following 1 variable:

len

Length in inches

Topic(s)

Source

Simulated from length frequency summaries found in data(cassie) of the mixdist package. Data originally from Cassie, R.M. 1954. Some uses of probability paper in the analysis of size frequency distributions. Australian Journal of Marine and Freshwater Research. 5:513-522. CSV file

Examples

data(Snapper)
str(Snapper)
head(Snapper)
hist(Snapper$len,main="")

Age (subsample) and length (all fish) of Snapper from two survey locations.

Description

A large sample (not random or proportional) of Snapper (Pagrus auratus) were aged from otoliths, with the remainder of the fish just measured for length. Note that age-20 is actually age 19+.

Format

A data frame of 18421 observations on the following 3 variables:

len

Measured lengths (cm)

age

Ages assigned from examination of otoliths

survey

Survey location (KAH8810 or KAH0012)

Topic(s)

Note

The unaged fish were simulated from Table 5 assuming that the total number of fish was large enough that at least one fish was observed in each cell where a proportion was listed.

Source

Recreated from Tables 2, 3, and 5 in Davies, N.M. and C. Walsh. 2002. Snapper age and length samples from Kaharoa research trawl surveys KAH8810 and KAH0012 of the Hauraki Gulf. Final Research Report for Ministry of Fisheries Research Project SNA2000/01. National Institute of Water and Atmospheric Research. [Was (is?) from http://fs.fish.govt.nz/Page.aspx?pk=113&dk=22516.] CSV file

Examples

data(SnapperHG1)
str(SnapperHG1)
head(SnapperHG1)

## Extract one of the sample surveys
sn1 <- subset(SnapperHG1,survey=="KAH8810")

## Extract the aged sample
sn1.aged <- subset(sn1,!is.na(age))
str(sn1.aged)

## Extract the length sample
sn1.length <- subset(sn1,is.na(age))
str(sn1.length)

Ages (subsample) and lengths (all fish) for Snapper.

Description

A large sample (approximately fixed sample size per length interval) of Snapper (Pagrus auratus) were aged, with the remainder of the fish just measured for length. Note that age-16 is actually age 16+ and length 60 is for 60-64 cm and 65 is for 65+ cm.

Format

A data frame of 6724 observations on the following 2 variables:

len

Measured lengths (cm)

age

Ages assigned

Topic(s)

Source

Recreated from summarized results in Table 8.3 of Quinn, T. J. and R. B. Deriso. 1999. Quantitative Fish Dynamics. Oxford University Press, New York, NY. 542 p. CSV file

See Also

See the same data in summarized format as alkdata in fishmethods.

Examples

data(SnapperHG2)
str(SnapperHG2)
head(SnapperHG2)

## Extract the aged sample
sn2.aged <- subset(SnapperHG2,!is.na(age))
str(sn2.aged)

## Extract the length sample
sn2.length <- subset(SnapperHG2,is.na(age))
str(sn2.length)

Stock and recruitment data for Sockeye Salmon from Karluk Lake, AK, 1921-1948.

Description

Sockeye Salmon (Oncorhynchus nerka) stock and recruitment in Karluk Lake, AK, by year, 1921-1948.

Format

A data frame of 28 observations on the following 3 variables:

year

Year of data.

stock

Upstream escapement.

recruits

Recruits.

Topic(s)

Source

From Gulland, J.A. 1983. Fish stock assessment: A manual of basic methods. John Wiley and Sons, New York, NY. 223 p. CSV file

Examples

data(SockeyeKL)
str(SockeyeKL)
head(SockeyeKL)
op <- par(mfrow=c(1,2),pch=19)
plot(recruits~year,data=SockeyeKL,type="b")
plot(recruits~stock,data=SockeyeKL)
par(op)

Stock and recruitment data for Skeena River Sockeye Salmon, 1940-1967.

Description

Stock and recruitment data for Skeena River Sockeye Salmon (Oncorhynchus nerka), 1940-1967.

Format

A data frame with 28 observations on the following 3 variables.

year

a numeric vector of years

spawners

a numeric vector giving number of spawning fish (in thousands)

recruits

a numeric vector containing the recruitment (thousands)

Topic(s)

Note

The dataset is usually analysed without case 12 because a rockslide occurred that year.

Source

Carroll, R. J. and Ruppert, D. 1988. Transformation and Weighting in Regression. Chapman and Hall, New York. 140 pp. CSV file

Examples

data(SockeyeSR)
str(SockeyeSR)
head(SockeyeSR)
SockeyeSR1 <- SockeyeSR[-12,]
op <- par(mfrow=c(1,2),pch=19)
plot(recruits~year,data=SockeyeSR1,type="b")
plot(recruits~spawners,data=SockeyeSR1)
par(op)

Ages (subsample) and lengths (all fish) for Spot.

Description

As many as 10 fish per 1-inch total length intervals from the SpotVA1 data frame in FSA were obtained for age assignment. The remaining fish in the file were only measured for length (i.e., the ages were deleted). This data file can be used to demonstrate the use of age-length keys.

Format

A data frame of 403 observations on the following 2 variables:

tl

Measured total lengths (in inches)

age

Ages assigned from examination of otoliths

Topic(s)

Source

From Table 1 in Chapter 8 (Spot) of the VMRC Final Report on Finfish Ageing, 2002 by the Center for Quantitative Fisheries Ecology at Old Dominion University. CSV file

See Also

SpotVA1 in FSA.

Examples

data(SpotVA2)
str(SpotVA2)
head(SpotVA2)

## Extract the aged sample
spot.aged <- subset(SpotVA2,!is.na(age))
str(spot.aged)

## Extract the length sample
spot.length <- subset(SpotVA2,is.na(age))
str(spot.length)

Ages and lengths of Spotted Sucker.

Description

Ages and total lengths of Spotted Sucker (Minytrema melanops) collected from the Apalachicola River, Florida.

Format

A data frame with 96 observations on the following 2 variables.

tl

Total length (mm).

age

Age (from scales).

Topic(s)

Source

From Box 5.4 in Iseley, J.J. and T.B. Grabowski. 2007. Age and Growth in Guy, C.S. and M.L. Brown, editors. Analysis and Interpretation of Freshwater Fisheries Data. American Fisheries Society. Likely originally from Grabowski, T.B., S.P. Young, J.J. Isely, and P.C. Ely. Age, growth, and reproductive biology of three catostomids from the Apalachicola River, Florida. Journal of Fish and Wildlife Management 3:223-237. CSV file

Examples

data(SpottedSucker1)
str(SpottedSucker1)
head(SpottedSucker1)
plot(tl~age,data=SpottedSucker1)

Ages of Striped Bass assigned from scales and otoliths.

Description

Ages of Striped Bass (Morone saxatilis) assessed from heat-pressed scales and cracked-and-burnt otoliths.

Format

A data frame of 343 observations on the following 2 variables:

ageO

Age assigned from examinaton of otoliths

ageS

Age assigned from examination of scales

Topic(s)

Source

From Figure 6 in Chapter 10 (Striped Bass) of the VMRC Final Report on Finfish Ageing, 2000 by the Center for Quantitative Fisheries Ecology at Old Dominion University. CSV file

Examples

data(StripedBass1)
str(StripedBass1)
head(StripedBass1)
plot(ageS~ageO,data=StripedBass1)
xtabs(~ageO+ageS,data=StripedBass1)

Ages and lengths of Atlantic Ocean Striped Bass.

Description

Assigned ages (from otoliths) and measured total lengths for each of 1201 Striped Bass (Morone saxatilis) from the Atlantic Ocean.

Format

A data frame of 1201 observations on the following 2 variables:

age

Assigned ages (from scales).

tl

Measured total lengths (in inches).

Topic(s)

Source

From Table 1 in Chapter 10 (Striped Bass) of the VMRC Final Report on Finfish Ageing, 2003 by the Center for Quantitative Fisheries Ecology at Old Dominion University. CSV file

See Also

StripedBass3.

Examples

data(StripedBass2)
str(StripedBass2)
head(StripedBass2)
plot(tl~age,data=StripedBass2)

Ages (subsample) and lengths (all fish) for Striped Bass.

Description

As many as 10 fish per 1-inch total length intervals from the StripedBass2 data frame were obtained for age assignment. The remaining fish in the file were only measured for length (i.e., the ages were deleted). This data file can be used to demonstrate the use of age-length keys.

Format

A data frame of 1201 observations on the following 2 variables:

tl

Measured total lengths (in inches).

age

Ages assigned from examination of otoliths.

Topic(s)

Source

CSV file

See Also

StripedBass2.

Examples

data(StripedBass3)
str(StripedBass3)
head(StripedBass3)

## Extract the aged sample
sb.aged <- subset(StripedBass3,!is.na(age))
str(sb.aged)

## Extract the length sample
sb.length <- subset(StripedBass3,is.na(age))
str(sb.length)

Ages of Striped Bass assigned from scales by two readers.

Description

Ages assigned by two different readers to the scales of Striped Bass (Morone saxatilis).

Format

A data frame of 1202 observations on the following 2 variables:

reader1

Ages assigned by the first reader

reader2

Ages assigned by the second reader

Topic(s)

Source

From Figure 3 in Chapter 10 (Striped Bass) of the VMRC Final Report on Finfish Ageing, 2003 by the Center for Quantitative Fisheries Ecology at Old Dominion University. CSV file

See Also

StripedBass5 and StripedBass6.

Examples

data(StripedBass4)
str(StripedBass4)
head(StripedBass4)
plot(reader2~reader1,data=StripedBass4)
xtabs(~reader1+reader2,data=StripedBass4)

Ages of Striped Bass assigned from otoliths by two readers.

Description

Ages assigned by two different readers to the otoliths of Striped Bass (Morone saxatilis).

Format

A data frame of 458 observations on the following 2 variables:

reader1

Ages assigned by the first reader

reader2

Ages assigned by the second reader

Topic(s)

Source

From Figure 5 in Chapter 10 (Striped Bass) of the VMRC Final Report on Finfish Ageing, 2003 by the Center for Quantitative Fisheries Ecology at Old Dominion University. CSV file

See Also

StripedBass4 and StripedBass6.

Examples

data(StripedBass5)
str(StripedBass5)
head(StripedBass5)
plot(reader2~reader1,data=StripedBass5)
xtabs(~reader1+reader2,data=StripedBass5)

Ages of Striped Bass assigned from scales and otoliths.

Description

Ages assigned to the scales and otoliths of Striped Bass (Morone saxatilis).

Format

A data frame of 451 observations on the following 2 variables:

scale

Ages assigned to scales

otolith

Ages assigned to otoliths

Topic(s)

Source

From Figure 6 in Chapter 10 (Striped Bass) of the VMRC Final Report on Finfish Ageing, 2003 by the Center for Quantitative Fisheries Ecology at Old Dominion University. CSV file

See Also

StripedBass4 and StripedBass5.

Examples

data(StripedBass6)
str(StripedBass6)
head(StripedBass6)
plot(scale~otolith,data=StripedBass6)
xtabs(~otolith+scale,data=StripedBass6)

Summarized multiple mark-recapture data for Lake Sturgeon.

Description

The number of Lake Sturgeon (Acipenser fulvescens) caught in multiple samples from Black Lake, MI in 1997. The caught fish were examined for previous marks, marked (if previously unmarked), and then returned to the population.

Format

A data frame with 6 observations on the following 4 variables:

t

Sample number

caught

Total number of fish caught in the sample

recaptures

Number of previously marked fish in the sample

retmarks

Number of marked fish (previously and newly marked) returned to the population

Topic(s)

Source

From Table 1 in Baker, E.A. and D.J. Borgeson. 1999. Lake sturgeon abundance and harvest in Black Lake, Michigan, 1975-1999. North American Journal of Fisheries Management 19:1080-1088. CSV file

Examples

data(SturgeonBL)
str(SturgeonBL)
head(SturgeonBL)

Capture years and ages for Lake Sturgeon from Goulais Bay, Lake Superior, Ont.

Description

Pratt et al. (2014) recorded the capture years and ages for Lake Sturgeon captured in multiple gillnet sets in Goulais Bay, Lake Superior (Ontario) in July 2010-2012.

Format

A data frame with 436 observations on the following 2 variables.

year

Year of capture

age

Age (yrs; from pectoral fin ray)

Topic(s)

Note

Used in the Introductory Fisheries Analyses with R book.

Source

From Pratt, T.C., Gardner, W.M., Pearce, J., Greenwood, S., and Chong, S.C. 2014. Identification of a robust Lake Sturgeon (Acipenser fulvescens Rafinesque, 1917) population in Goulais Bay, Lake Superior. Journal of Applied Ichthyology 30:1328-1334. Obtained directly from Tom Pratt. CSV file

Examples

data(SturgeonGB)
str(SturgeonGB)
head(SturgeonGB)
plot(age~year,data=SturgeonGB)

Summarized multiple mark-recapture data for Redear Sunfish.

Description

The number of Redear Sunfish (Lepomis microlophus) caught in multiple samples from Gordy Lake, IN. The caught fish were examined for previous marks, marked (if previously unmarked), and then returned to the population.

Format

A data frame with 6 observations on the following 4 variables:

t

Sample number

caught

Total number of fish caught in the sample

recaps

Number of previously marked fish in the sample

retmarks

Number of marked fish returned to the population

Topic(s)

Source

Originally from Gerking, S.D. 1953. Vital statistics of the fish population of Gordy Lake, Indiana. Transactions of the American Fisheries Society. 82:48-67. But also found in Table 2.4 of Krebs, C.J. 1999. Ecological Methodology. Addison-Welsey Educational Publishing, second edition and Table 4.4 of Ricker, W.E. 1975. Computation and interpretation of biological statistics of fish populations. Technical Report Bulletin 191, Bulletin of the Fisheries Research Board of Canada. CSV file

Examples

data(SunfishIN)
str(SunfishIN)
SunfishIN

Catch-at-age for Bluegill and Redear Sunfish in Florida.

Description

The percent frequency of of Bluegill (Lepomis macrochirus) and Redear Sunfish (Lepomis microlophus) caught in Lake Panasoffkee, FL.

Format

A data frame with 12 observations on the following 3 variables:

species

Species of sunfish (bluegill or redear)

age

Age (yrs from otoliths)

perc.freq

Percent frequency of fish collected in 1998

Topic(s)

Source

From (approximately) Figure 2 in Crawford, S. and M.S. Allen. 2006. Fishing and natural mortality of Bluegills and Redear Sunfish at Lake Panasoffkee, Florida: Implications for size limits. North American Journal of Fisheries Management 26:42-51. Note that I added a percentage for age-1 fish (the difference in percentages from Fig. 2). CSV file

Examples

data(SunfishLP)
str(SunfishLP)
head(SunfishLP)
plot(log(perc.freq)~age,data=SunfishLP)

Stock and recruitment data for Exmouth Gulf Tiger Prawn, 1970-83.

Description

Stock and recruitment data for Exmouth Gulf Tiger Prawn (Panaeus esculentus), 1970-1983.

Format

A data frame with 14 observations on the following 5 variables.

year

a numeric vector of years

stock

a numeric vector giving the index of spawning stock fish

recruits

a numeric vector containing the index of recruits

cycloneJan

a numeric vector containing the relative rainfal in January as an index of cyclonic activity

cycloneFeb

a numeric vector containing the relative rainfal in February as an index of cyclonic activity

Topic(s)

Source

From table 9.1 in Haddon, M. 2000. Modeling and Quantitative Methods in Fisheries, CRC Press. Originally from Penn, J. W., and Caputi, N. 1986. Spawning stock-recruitment relationships and environmental influences on the Tiger Prawn (Penaeus esculentus) fishery in Exmouth Gulf, Western Australia. Australian Journal of Marine and Freshwater Research 37:491-505. CSV file

Examples

data(TPrawnsEG)
str(TPrawnsEG)
head(TPrawnsEG)
op <- par(mfrow=c(1,2),pch=19)
plot(recruits~year,data=TPrawnsEG,type="l")
plot(recruits~stock,data=TPrawnsEG)
par(op)

Catches in removal events of trout.

Description

Catches of trout on five successive removal events from the Afon Dulas at Pentre, 19Jun79.

Format

A data frame with 5 observations on the following 2 variables:

catch

Removal event.

caught

Number of fish captured and removed.

Topic(s)

Source

From Table 1 in Cowx, I.G. 1983. Review of the methods for estimating fish population size from survey removal data. Fisheries Management 14:67-82. CSV file

See Also

SalmonADP

Examples

data(TroutADP)
str(TroutADP)
TroutADP

Ages and lengths of migratory Brown and Rainbow Trout.

Description

Total lengths (inches) and ages (from scales) of Brown Trout (Salmo trutta) and Rainbow Trout (Oncorhynchus mykiss) migrating upstream on the Bois Brule River, WI in 1978 and 1979.

Format

A data frame with 851 observations on the following 3 variables:

tl

Measured total length (inches).

age

Assigned age (from scales).

species

Species (Brown and Rainbow).

Topic(s)

Source

From tables 18 and 19 of Scholl, D.K., P.J. Peeters, and S.T. Schram. 1984. Migratory brown trout and rainbow trout populations of the Brule River, Wisconsin. Wisconsin Department of Natural Resources, Fish Management Report No. 123. CSV file

Examples

data(TroutBR)
str(TroutBR)
head(TroutBR)
op <- par(mfrow=c(1,2),pch=19)
plot(tl~age,data=TroutBR,subset=species=="Brown",main="Brown Trout")
plot(tl~age,data=TroutBR,subset=species=="Rainbow",main="Rainbow Trout")
par(op)

Ages, lengths, and sexes of Troutperch.

Description

The assigned ages (by scales), total lengths (mm), and sexes of Troutperch (Percopsis omsicomaycus) captured in southeastern Lake Michigan.

Format

A data frame with 431 observations on the following 3 variables:

age

Assigned ages (by scales).

tl

Measured total length (mm).

sex

Sex (f=female and m=male).

Topic(s)

Source

Simulated from the age-length data provided in Table 1 of House, R., and L. Wells. 1973. Age, growth, spawning season, and fecundity of the trout-perch (Percopsis omsicomaycus) in southeastern Lake Michigan. Journal of the Fisheries Research Board of Canada 30:1221-1225. CSV file

Examples

data(TroutperchLM1)
str(TroutperchLM1)
head(TroutperchLM1)
op <- par(mfrow=c(1,2),pch=19)
plot(tl~age,data=TroutperchLM1,subset=sex=="f",main="female")
plot(tl~age,data=TroutperchLM1,subset=sex=="m",main="male")
par(op)

Lengths for Troutperch from Lake Michigan, 1977.

Description

Troutperch (Percopsis omiscomaycus) fork lengths from near Grand Haven, Lake Michigan, 1977.

Format

A data frame of 3385 observations on the following 1 variable:

fl

fork length (mm)

Topic(s)

Source

From Brandt, S.B., J.J. Magnuson, and L.B. Crowder. 1980. Thermal habitat partitioning by fishes in Lake Michigan. Canadian Journal of Fisheries and Aquatic Sciences. 37:1557-1564. Data was simulated (uniform distribution of values within length bin) from summarized length frequencies in http://fishbase.org/. CSV file

Examples

data(TroutperchLM2)
str(TroutperchLM2)
head(TroutperchLM2)
hist(TroutperchLM2$fl,main="")

Subsampled lengths of Troutperch from Lake Michigan, 1977.

Description

Troutperch (Percopsis omiscomaycus) fork lengths from a subsample of fish captured near Grand Haven, Lake Michigan, 1977.

Format

A data frame of 300 observations on the following 1 variable:

fl

Fork length (mm)

Details

A random subsample of the lengths in the TroutperchLM2 data frame.

Topic(s)

Source

CSV file

See Also

TroutperchLM2.

Examples

data(TroutperchLM3)
str(TroutperchLM3)
head(TroutperchLM3)

Stock and recruitment data for Vendace from Lake Puulavesi, 1982-1996.

Description

Vendace (Coregonus albula) recruitment by year in Lake Puulavesi, 1982-1996.

Format

A data frame of 15 observations on the following 3 variables:

year

Year of data

stock

Spawning stock index – autumn biomass (kg/ha) of age-1+ fish

recruits

Recuit index – density (indivs/ha) of age-0+ fish in first autumn

Topic(s)

Source

From (approximately) Figure 1 and 2 of Marjomaki, T.J. 2004. Analysis of the spawning stock-recruitment relationship of vendace (Coregonus albula (L.)) with evaluation of alternative models, additional variables, biases and errors. Ecology of Freshwater Fish 13:46-60. CSV file

Examples

data(VendaceLP)
str(VendaceLP)
head(VendaceLP)
op <- par(mfrow=c(1,2),pch=19)
plot(recruits~year,data=VendaceLP,type="l")
plot(recruits~stock,data=VendaceLP)
par(op)

Stock and recruitment data for Vendace from Lake Pyhajarvi.

Description

Vendace (Coregonus albula) recruitment in Lake Pyhajarvi.

Format

A data frame of 9 observations on the following 2 variables:

fecundity

Total fecundity (10^9 eggs) of spawning stock

recruits

Number of recruits (10^6 fish) in Autumn after hatching

Topic(s)

Note

Original authors fit an exponential curve to the fecundity-recruits relationship.

Source

From (approximately) Figure 6 in Helminen, H. and J. Sarvala. 1994. Population regulation of vendance (Coregonus albula) in Lake Pyhajarvi, southwest Finland. Journal of Fish Biology 45:387-400. CSV file

Examples

data(VendaceLP2)
str(VendaceLP2)
head(VendaceLP2)
plot(recruits~fecundity,data=VendaceLP2)

Stock and recruitment data for White Shrimp off the coast of Georgia (USA), 1979-2000.

Description

White Shrimp (Litopenaeus setiferus) stock and recruitment data from off the coast of Georgia (USA), 1979-2000.

Format

A data frame with 22 observations on the following 3 variables:

year

Year of data

stock

Spawning stock index – CPUE in June assessment surveys

recruits

Recuit index – commercial landings in pounds from Aug-Jan

yrconf

A code of confidence for whether or not the stock value is known to come from the year shown (see the note)

Topic(s)

Note

No graph was shown for stock values vs. year so some stock values had to be haphazardly paired with recruit values – especially for stock values between 2.5 and 3.0.

Source

From (approximately) Figures 2 and 3 of Belcher, C.N., and C.A. Jennings. 2004. Evaluation of stock-recruitment curves for white shrimp in Georgia. North American Journal of Fisheries Management 24:654-661. CSV file

Examples

data(WShrimpGA)
str(WShrimpGA)
head(WShrimpGA)
op <- par(mfrow=c(1,2),pch=19)
plot(recruits~year,data=WShrimpGA,type="b")
plot(recruits~stock,data=WShrimpGA)
par(op)

Consumption of prey by Walleye.

Description

Consumption of prey by Walleye (Sander vitreus) at different prey densities.

Format

A data frame of 23 observations on the following 2 variables:

PreyDensity

Density of prey (mg per g per day).

FoodConsump

Food consumption by predator (mg per cubic meter)

Topic(s)

Source

From Figure 3 in Madenjian, C.P., and S.R. Carpenter. 1991. Individual-based model for growth of young-of-the-year walleye: A piece of the recruitment puzzle. Ecological Applications 1:268-279. Data were originally from Swenson, W. A. 1977. Food consumptions of walleye (Stizostedion vitreum vitreum) and sauger (S. canadense) in relation to food availability and physical conditions in Lake of the Woods, Minnesota, Shagawa Lake, and western Lake Superior. Journal of the Fisheries Research Board of Canada 34:1643-1654. CSV file

Examples

data(WalleyeConsumption)
str(WalleyeConsumption)
head(WalleyeConsumption)
plot(FoodConsump~PreyDensity,data=WalleyeConsumption,pch=16)

Stock and recruitment data for Walleye from Escanaba Lake, WI, 1958-1992.

Description

Abundance of age-0 and age-5 and older Walleye (Sander vitreus), abundance of adult Yellow Perch (Perca flavescens), and coefficient of variation of May temperatures for Escanaba Lake, WI, 1958-1992.

Format

A data frame of 39 observations on the following 5 variables:

yrclass

Year-class of the data

age0

Abundance of age-0 Walleye (recruits)

age5

Abundance of age-5 and older Walleye (stock)

maycv

Coefficient of variation of May temperatures in birth year

yep

Abundance of adult (larger than 152.4 mm) Yellow Perch

Topic(s)

Source

Hansen, M. J., M. A. Bozek, J. R. Newby, S. P. Newman, and M. D. Staggs. 1998. Factors affecting recruitment of walleyes in Escanaba Lake, Wisconsin, 1958-1995. North American Journal of Fisheries Management 18:764-774. CSV file

Examples

data(WalleyeEL)
str(WalleyeEL)
head(WalleyeEL)
op <- par(mfrow=c(1,2),pch=19)
plot(age0~yrclass,data=WalleyeEL,type="l")
plot(age0~age5,data=WalleyeEL)
par(op)

Recruitment time-series for Walleye in Lake Erie, 1959-1972.

Description

Walleye (Sander vitreus) recruitment time-series for Lake Erie, 1959-1972.

Format

A data frame of 14 observations on the following 6 variables:

year

Year of data.

recruits

Number of recruits (per 1000 ft of net).

Topic(s)

Source

From Wolfert, D. R. 1981. The commercial fishery for walleyes in New York waters of Lake Erie, 1959-1978. North American Journal of Fisheries Management 1: 112-126. Obtained from Ransom Myers old online database. CSV file

Examples

data(WalleyeErie)
str(WalleyeErie)
head(WalleyeErie)
plot(recruits~year,data=WalleyeErie,type="l")

Biological data for Walleye from Lake Erie, 2003-2014.

Description

Walleye (Sander vitreus) biological data (length, weight, sex, maturity, and age) from several locations in Lake Erie, October-November of 2003-2014.

Format

A data frame of 33734 observations on the following 10 variables:

setID

Unique gear (multifilament gill net kegged 6 ft below surface) set identification number.

loc

Regional location (1=Toledo to Huron, 2=Huron to Fairport Harbor, 3=Fairport Harbor to Conneaut).

grid

2.5-minute sampling grid location.

year

Year of data.

tl

Total length (mm).

w

Weight (g). There are several missing values.

sex

Sex (female, male).

mat

Maturity (immature, mature).

age

Age (yrs) from otoliths.

Topic(s)

Source

These unpublished data are from the Ohio Department of Natural Resources, Division of Wildlife (via Christopher Vandergoot). Do not use for other than educational purposes without permission from the source. CSV file

Examples

data(WalleyeErie2)
str(WalleyeErie2)
head(WalleyeErie2)
xtabs(~year+loc+sex,data=WalleyeErie2)

Catch-at-age for Walleye from eight Kansas reservoirs.

Description

Catch-at-age for Walleye (Sander vitreus) from eight Kansas reservoirs during 1991-1999.

Format

A data frame with 66 observations on the following 3 variables.

reservoir

Reservoir (Cedar.Bluff, Cheney, Glen.Elder, Kirwin, Lovewell, Marion, Webster, Wilson)

age

Age of fish at capture

catch

Number of fish captured

Topic(s)

Note

The authors used all age-2 and older Walleye to construct the catch curves.

Source

From Figure 2 of Quist, M.C., J.L. Stephen, C.S. Guy, and R.D. Schultz. 2004. Age structure and mortality of Walleyes in Kansas reservoirs: Use of mortality caps to establish realistic management objectives. North American Journal of Fisheries Management 24:990-1002. CSV file

Examples

data(WalleyeKS)
str(WalleyeKS)
head(WalleyeKS)
op <- par(mfrow=c(2,2),mar=c(3,3,2,1),mgp=c(1.75,0.5,0),tcl=-0.2,pch=19)
plot(log(catch)~age,data=WalleyeKS,subset=(reservoir=="Cedar.Bluff"),main="Cedar Bluff")
plot(log(catch)~age,data=WalleyeKS,subset=(reservoir=="Cheney"),main="Cheney")
plot(log(catch)~age,data=WalleyeKS,subset=(reservoir=="Glen.Elder"),main="Glen Elder")
plot(log(catch)~age,data=WalleyeKS,subset=(reservoir=="Kirwin"),main="Kirwin")
plot(log(catch)~age,data=WalleyeKS,subset=(reservoir=="Lovewell"),main="Lovewell")
plot(log(catch)~age,data=WalleyeKS,subset=(reservoir=="Marion"),main="Marion")
plot(log(catch)~age,data=WalleyeKS,subset=(reservoir=="Webster"),main="Webster")
plot(log(catch)~age,data=WalleyeKS,subset=(reservoir=="Wilson"),main="Wilson")
par(op)

Back-calculated lengths-at-age for Walleye from Lake Mille Lacs, 2000-2011.

Description

Back-calculated lengths-at-age for Walleye (Sander vitreus) from Lake Mille Lacs. Walleye were captured by Minnesota Department of Natural Resources personnel in fishery-independent gillnets (five multifilament nylon mesh panels with each panel measuring 15.2 m wide and 1.8 m high; bar-measure mesh sizes of the panels were 19.1, 25.4, 31.7, 38.1, and 50.8 mm) set in the fall (mid September to early October) from 2000 to 2011.

Format

A data frame of 14583 observations on the following 9 variables:

ID

A unique fish identification number.

Year

Year of data.

Sex

Sex (female, male).

Est.Age

Estimated (from otoliths) age (yrs) at capture.

TL

Total length (mm).

Scale.Rad

Total scale radius (mm) at capture.

Dist.Ann

Scale radius (mm) to annulus given in BC.Age.

BC.Age

Annulus or previous age.

BC.Len

Back-calculated length at BC.Age. Lengths were back-calculated using the Scale-Proportional Hypothesis method.

Topic(s)

Source

These unpublished data are from the Minnesota Department of Natural Resources, Section of Fisheries (via Melissa Treml). Do not use for other than educational purposes without permission from the source. CSV file

Examples

data(WalleyeML)
str(WalleyeML)
head(WalleyeML)
xtabs(~Year+Est.Age+Sex,data=WalleyeML)

Catch-at-age for Walleye.

Description

Catch-at-age for Walleye (Sander vitreus) collected from four lakes in Northern Minnesota, USA.

Format

A data frame with 52 observations on the following 3 variables.

lake

A factor vector of collection lake (Crooked, Fourmile, Island, Tom)

age

A numeric vector of assigned ages (from dorsal spines)

number

A numeric vector of number of fish

Topic(s)

Source

From various tables in Borkholder, B.D., A.J. Edwards, and C. Olson. 2007. Spring adult and fall juvenile walleye population surveys within the 1854 ceded territory of Minnesota, 2006. Fond du Lac Division of Resource Management, Technical Report 41. CSV file

Examples

data(WalleyeMN06a)
str(WalleyeMN06a)
head(WalleyeMN06a)
op <- par(mfrow=c(2,2),pch=19)
plot(log(number)~age,data=WalleyeMN06a,subset=lake=="Crooked")
plot(log(number)~age,data=WalleyeMN06a,subset=lake=="Fourmile")
plot(log(number)~age,data=WalleyeMN06a,subset=lake=="Island")
plot(log(number)~age,data=WalleyeMN06a,subset=lake=="Tom")
par(op)

Summarized multiple mark-recapture data for Walleye from four lakes in Northern Minnesota.

Description

Summary results of capture histories (number captured, number of recaptured fish, and number of unmarked fish that were marked) for Walleye (Sander vitreus) collected from four lakes in Northern Minnesota, USA.

Format

A data frame with 20 observations on the following 5 variables.

lake

Studied lake (Crooked, Fourmile, Island, Tom)

date

Capture date

catch

Total fish captured in each sample

recap

Marked fish captured in each sample

retMark

Marked fish returned to the population

Topic(s)

Source

From appendix 2 in Borkholder, B.D., A.J. Edwards, and C. Olson. 2007. Spring adult and fall juvenile walleye popluation surveys within the 1854 ceded territory of Minnesota, 2006. Fond du Lac Division of Resource Management, Technical Report 41. CSV file

Examples

data(WalleyeMN06b)
str(WalleyeMN06b)
head(WalleyeMN06b)

Summarized multiple mark-recapture data for YOY walleye.

Description

The numbers of young-of-year walleye (Sander vitreus) that were captured, found to have previous marks (i.e., recaptured), and were newly marked on several sampling occasions in 1959, 1960, 1961, and 1962 in Pike Lake, Wisconsin.

Format

A data frame with 33 observations on the following 5 variables:

year

Sampling year

t

Sampling occasion within each year

caught

Number of walleye captured

recaptures

Number of marked walleyes captured

newmarks

Number of unmarked walleyes that were captured, marked, and returned to the population

Topic(s)

Source

From table 3 of Mraz, D. 1968. Recruitment, growth, exploitation, and management of walleyes in a southeastern Wisconsin lake. Wisconsin Department of Natural Resources Technical Bulletin 40. 38 pages. CSV file

Examples

data(WalleyePL)
str(WalleyePL)
WalleyePL
subset(WalleyePL,year==1960)

Ages of Walleye assigned from otoliths, scales, and spines.

Description

Age of Pymatuning Sanctuary (PA) Walleye (Sander vitreus) assessed from three calcified structures – sectioned otoliths, sectioned dorsal spines, and scale impressions.

Format

A data frame with 61 observations on the following 4 variables:

otolith

Age (years) assigned from broken, ground, and polished otolith sections

spine

Age (years) assigned from dorsal spine sections

scale

Age (years) assigned from scale impressions

sex

Sex of fish (female and male)

Topic(s)

Note

Relationships between otoliths and spines and otoliths and scales are exact according to Figure 2. Relationship between spines and scales is approximate as Figure 2 did not show this exact relationship.

Source

From Figure 2 in Kocovsky, P.M., and R.M. Carline. 2000. A comparison of methods for estimating ages of unexploited walleyes. North American Journal of Fisheries Management 20:1044-1048. CSV file

Examples

data(WalleyePS)
str(WalleyePS)
head(WalleyePS)
op <- par(mfrow=c(3,2),pch=19)
plot(scale~otolith,data=WalleyePS,subset=sex=="female",main="Female")
plot(scale~otolith,data=WalleyePS,subset=sex=="male",main="Male")
plot(scale~spine,data=WalleyePS,subset=sex=="female",main="Female")
plot(scale~spine,data=WalleyePS,subset=sex=="male",main="Male")
plot(spine~otolith,data=WalleyePS,subset=sex=="female",main="Female")
plot(spine~otolith,data=WalleyePS,subset=sex=="male",main="Male")
par(op)

Growth increment data for Red Lakes Walleye.

Description

Growth increment data for Red Lakes Walleye (Sander vitreus) in one-fish-per-line format.

Format

A data frame with 1543 observations on the following 13 variables.

fish

A fish identification number. Unique within a year but not across years.

yearcap

Year the fish was captured.

ce

A factor denoting capture gear (C=commercial and E=experimental nets).

agecap

Age of fish at capture.

lencap

Length of fish at capture.

inc1

Scale measurement to first annulus.

inc2

Scale measurement between first and second annulus.

inc3

Scale measurement between second and third annulus.

inc4

Scale measurement between third and fourth annulus.

inc5

Scale measurement between fourth and fifth annulus.

inc6

Scale measurement between fifth and sixth annulus.

inc7

Scale measurement between sixth and seventh annulus.

radcap

Scale radius at time of capture

Topic(s)

Note

Data is in one-fish-per-line format.

Source

Cyterski, M.J. and G.R. Spangler. 1996. A tool for age determination. North American Journal of Fisheries Management 16:403-412. CSV file

Examples

data(WalleyeRL)
str(WalleyeRL)
head(WalleyeRL)

Catches-at-age for male and female Walleye from Lake Winnebago, WI, 2010.

Description

Catches-at-age for male and female Walleye from Lake Winnebago, WI, 2010.

Format

A data frame with 18 observations on the following 3 variables.

age

Age (yrs; from pectoral fin ray)

numF

Number of captured females

numM

Number of captured males

Details

Koenigs et al. (2015) captured adult Walleye from Lake Winnebago during spawning assessments in 2010. The sex was recorded and ages were estimated from sectioned otoliths for each fish. Koenigs et al. (2015) fit separate catch curves to female and male Walleye.

Topic(s)

Note

Used in the Introductory Fisheries Analyses with R book.

Source

From Koenigs, R.P., Bruch, R.M., Stelzer, R.S., and Kamke, K.K. 2015. Validation of otolith ages for Walleye (Sander vitreus) in the Winnebago System. Fisheries Research, 167:13-21. Obtained directly from Ryan Koenigs. CSV file

Examples

data(WalleyeWad)
str(WalleyeWad)
head(WalleyeWad)
plot(numF~age,data=WalleyeWad)
points(numM~age,data=WalleyeWad,pch=19)

Annual catches of yearling Walleye in bottom trawls from Lake Winnebago, WI, 1986-2010.

Description

Annual catches of yearling Walleye (Sander vitreus) in bottom trawls from Lake Winnebago, WI, 1986-2010.

Format

A data frame with 35 observations on the following 4 variables.

tows

Number of trawl tows (i.e., effort)

year

Year of capture

yearlings

Number of yearling Walleye captured

yrclass

Year-class of the captured yearlings (capture year minus 1)

Details

The catch of yearling Walleye and number of trawl tows by year are in this data.frame. The CPE is catch divided by number of tows. Koenigs et al. (2015) rescaled the CPE values to have a mean of 0 and a standard deviation of 1.

Topic(s)

Note

Used in the Introductory Fisheries Analyses with R book.

Source

From Koenigs, R.P., Bruch, R.M., Stelzer, R.S., and Kamke, K.K. 2015. Validation of otolith ages for Walleye (Sander vitreus) in the Winnebago System. Fisheries Research, 167:13-21. Obtained directly from Ryan Koenigs. CSV file

Examples

data(WalleyeWyrlng)
str(WalleyeWyrlng)
head(WalleyeWyrlng)
plot(yearlings~yrclass,data=WalleyeWyrlng)

Catch-at-age for White Grunt.

Description

Catch-at-age for White Grunt (Haemulon plumierii) collected from the central coast of Brazil.

Format

A data frame with 25 observations on the following 2 variables.

age

A numeric vector of assigned ages (from otoliths).

catch

A numeric vector of number of fish.

Topic(s)

Source

From Figure 7 of Araujo, J.N. and A.S. Martins. 2007. Age, growth and mortality of white grunt (Haemulon plumierii) from the central coast of Brazil. Scientia Marina 71:793-800. CSV file

Examples

data(WhiteGrunt1)
str(WhiteGrunt1)
head(WhiteGrunt1)
plot(log(catch)~age,data=WhiteGrunt1)

Ages, lengths, and sexes of White Grunt.

Description

Ages, lengths, and sexes of White Grunt (Haemulon plumierii) collected from the central coast of Brazil

Format

A data frame with 465 observations on the following 3 variables.

age

Age (from otoliths to the nearest 0.1 years)

tl

Total length (mm)

sex

Sex (male and female)

Topic(s)

Source

From (approximately) Figure 6 of Araujo, J.N. and A.S. Martins. 2007. Age, growth and mortality of white grunt (Haemulon plumierii) from the central coast of Brazil. Scientia Marina 71:793-800. CSV file

Examples

data(WhiteGrunt2)
str(WhiteGrunt2)
head(WhiteGrunt2)
op <- par(mfrow=c(1,2),pch=19)
plot(tl~age,data=WhiteGrunt2,subset=sex=="female",main="Female")
plot(tl~age,data=WhiteGrunt2,subset=sex=="male",main="Male")
par(op)

Catch-at-age of Great Slave Lake Whitefish (commercial) by area.

Description

Age composition of commercial Whitefish (Coregonus clupeaformis) catches for five areas of Great Slave Lake.

Format

A data frame with 16 observations on the following 6 variables:

age

Assigned ages.

area.IE

Catches for area IE.

area.II

Catches for area II.

area.IV

Catches for area IV.

area.V

Catches for area V.

area.IW

Catches for area IW.

Topic(s)

Note

All data are from summer samples except for Area.IW which is a winter sample

Source

From Table 19 of Mosenko, R.W., and G. Low. 1980. Data from the commercial fishery for lake whitefish Coregonus clupeaformis (Mitchill), on Great Slave Lake, Northwest Territories, 1979. Canadian Data Report of Fisheries And Aquatic Sciences, No. 194. CSV file

Examples

data(WhitefishGSL)
str(WhitefishGSL)
head(WhitefishGSL)
op <- par(mfrow=c(3,2),pch=19)
plot(log(area.IE)~age,data=WhitefishGSL)
plot(log(area.II)~age,data=WhitefishGSL)
plot(log(area.IV)~age,data=WhitefishGSL)
plot(log(area.V)~age,data=WhitefishGSL)
plot(log(area.IW)~age,data=WhitefishGSL)
par(op)

# can be reshaped to 'long' format with
## Not run: 
library(reshape)
WhitefishGSL1 <- melt(WhitefishGSL,id.vars="age")
names(WhitefishGSL1) <- c("age","area","number")

## End(Not run)

Landings and value of Lake Superior Lake Whitefish.

Description

Landings and value of Lake Whitefish Coregonus clupeaformis in Lake Superior by state from 1971-2001.

Format

A data frame with 12 observations on the following 4 variables:

year

Year of catch.

state

State of catch (MI, MN, or WI).

catch

Catch in lbs.

value

Value of catch in dollars.

Topic(s)

Source

Results from a query in 2006 to the NMFS Great Lakes Commercial Fishery Landings database. CSV file

Examples

data(WhitefishLS)
str(WhitefishLS)
head(WhitefishLS)

Ages of Lake Whitefish from four lakes assigned from scales and fin-rays.

Description

Ages of Lake Whitefish (Coregonus clupeaformis) from four lakes as determined by scales and fin-rays.

Format

A data frame with 859 observations on the following 3 variables:

fin

Ages assigned from fin-ray sections

scale

Ages assigned from scales

lake

Lake from which the fish was captured (L122, L226, Huron, or Dezadeash)

Topic(s)

Source

From (approximately) Figure 1 of Mills, K.H., and R.J. Beamish. 1980. Comparison of fin-ray and scale age determinations for lake whitefish (Coregonus clupeaformis) and their implications for estimates of growth and annual survival. Canadian Journal of Fisheries and Aquatic Sciences 37:534-544. CSV file

Examples

data(WhitefishMB)
str(WhitefishMB)
head(WhitefishMB)
op <- par(mfrow=c(2,2),pch=19)
plot(scale~fin,data=WhitefishMB,subset=lake=="L122",main="Lake L122")
plot(scale~fin,data=WhitefishMB,subset=lake=="L226",main="Lake L226")
plot(scale~fin,data=WhitefishMB,subset=lake=="Huron",main="Huron")
plot(scale~fin,data=WhitefishMB,subset=lake=="Dezadeash",main="Dezadeash")
par(op)

Stock and recruitment data for Lake Whitefish in Thunder Bay, Lake Superior, 1975-1988.

Description

Lake Whitefish (Coregonus clupeaformis) stock, recruitment, landings, and fishing mortality by year, 1975-1988.

Format

A data frame of 14 observations on the following 5 variables:

year

Year of data

ssb

Spawning stock biomass (in tonnes)

rec

Recruits (in thousands)

land

Landings (in tonnes)

fmort

Fishing related mortality (natural mortality was assumed to be 0.3)

Topic(s)

Source

From Petzold, M. 1995. An historical analysis of the Lake Whitefish fisheries of Thunder Bay (Zone 1) and Whitefish Bay (Zone 34), Lake Superior. Ontario Min. of Nat. Res. unpubl. manuscript. Obtained from Ransom Myers old online database. CSV file

Examples

data(WhitefishTB)
str(WhitefishTB)
head(WhitefishTB)
op <- par(mfrow=c(1,2),pch=19)
plot(rec~year,data=WhitefishTB,type="b")
plot(rec~ssb,data=WhitefishTB)
par(op)

Ages, lengths, and maturity for Yelloweye Rockfish.

Description

Ages, lengths, and maturity for female Yelloweye Rockfish (Sebastes rubberimus) from Oregon.

Format

A data frame with 159 observations on the following 5 variables.

date

Date fish was collected

length

Total length (cm)

age

Otolith age

maturity

Maturity state (Immature or Mature)

stage

Stage of maturity (1:Immature, 2:Maturing, 3:Mature, 4:Fertilized, 5:Ripe, 6:Spent, 7:Resting)

Topic(s)

Source

Obtained directly (from Bob Hannah). Data were used in Hannah, R.W, M.T.O. Blume, and J.E. Thompson. 2009. Length and age at maturity of female yelloweye rockfish (Sebastes rubberimus) and cabezon (Scorpaenichthys marmoratus) from Oregon waters based on histological evaluation of maturity. Oregon Department of Fish and Wildlife, Information Reports 2009-04. [Was (is?) from http://www.dfw.state.or.us/mrp/publications/docs/Info200904_YlwEyeRF_Maturity.pdf] CSV file

Examples

data(YERockfish)
str(YERockfish)
head(YERockfish)
op <- par(mfrow=c(2,2),pch=19)
plot(length~age,data=YERockfish,ylab="Total Length (cm)",xlab="Age")
hist(YERockfish$length,xlab="Total Length (cm)",main="")
tbl1 <- with(YERockfish,table(age,maturity))
(ptbl1 <- prop.table(tbl1,margin=1))
plot(ptbl1[,2]~as.numeric(row.names(ptbl1)),type="l",xlab="Age",ylab="Proportion Mature")
tbl2 <- with(YERockfish,table(length,maturity))
(ptbl2 <- prop.table(tbl2,margin=1))
plot(ptbl2[,2]~as.numeric(row.names(ptbl2)),type="l",xlab="Age",ylab="Proportion Mature")
par(op)

Catch-at-age for Yellow Perch from Chequamegon Bay, Lake Superior.

Description

Catch-at-age for Yellow Perch (Perca flavescens) from Chequamegon Bay, Lake Superior, 1973-1988.

Format

A data frame with 39 observations on the following 5 variables.

age

Age in that capture year (1973-1988).

year73

Number of fish at each age in capture year 1973.

year74

Number of fish at each age in capture year 1974.

year75

Number of fish at each age in capture year 1975.

year76

Number of fish at each age in capture year 1976.

year77

Number of fish at each age in capture year 1977.

year78

Number of fish at each age in capture year 1978.

year79

Number of fish at each age in capture year 1979.

year80

Number of fish at each age in capture year 1980.

year81

Number of fish at each age in capture year 1981.

year82

Number of fish at each age in capture year 1982.

year83

Number of fish at each age in capture year 1983.

year84

Number of fish at each age in capture year 1984.

year85

Number of fish at each age in capture year 1985.

year86

Number of fish at each age in capture year 1986.

year87

Number of fish at each age in capture year 1987.

year88

Number of fish at each age in capture year 1988.

Topic(s)

Source

From Table 1 in Bronte, C.R., J.H. Selgeby, D.V.Swedberg. 1993. Dynamics of a yellow perch population in Western Lake Superior. North American Journal of Fisheries Management 13:511-523. CSV file

Examples

data(YPerchCB1)
str(YPerchCB1)
head(YPerchCB1)
max.n <- max(YPerchCB1[,-1])  # maximum catch
op <- par(mfrow=c(4,4),mar=c(3.5,3.5,1,1),mgp=c(2,0.75,0))
plot(log(year73)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1973")
plot(log(year74)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1974")
plot(log(year75)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1975")
plot(log(year76)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1976")
plot(log(year77)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1977")
plot(log(year78)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1978")
plot(log(year79)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1979")
plot(log(year80)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1980")
plot(log(year81)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1981")
plot(log(year82)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1982")
plot(log(year83)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1983")
plot(log(year84)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1984")
plot(log(year85)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1985")
plot(log(year86)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1986")
plot(log(year87)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1987")
plot(log(year88)~age,data=YPerchCB1,ylim=c(0,log(max.n)),main="1988")
par(op)
op <- par(mfrow=c(1,2),mar=c(3.5,3.5,1,1),mgp=c(2,0.75,0))

## plot for 1973 and 1982 year-classes (be very careful)
# get 1973 year-class as diagonal for ages 0-9 and years 1973-1982
yc73 <- diag(as.matrix(YPerchCB1[,2:11]))
plot(log(yc73)~YPerchCB1$age,main="1973 Year-Class")
yc82 <- diag(as.matrix(YPerchCB1[1:7,11:17]))
plot(log(yc82)~YPerchCB1$age[1:7],main="1982 Year-Class")

Stock and recruitment data for Yellow Perch in Chequamegon Bay, 1975-1986.

Description

Yellow Perch (Perca flavescens) stock-recruitment by year-class in Chequamegon Bay, 1975-1986.

Format

A data frame with 12 observations on the following 2 variables:

yrclass

Year-class (see below)

stock

Estimated numbers of mature females caught the year prior to the origin of the 1975-1986 year classes

recruits

Catches of age-2 fish (when the year-class is formed)

Topic(s)

Source

From (approximately) Figure 7 in Bronte et al. 1993. Dynamics of a yellow perch population in Western Lake Superior. North American Journal of Fisheries Management. 13:511-523. CSV file

Examples

data(YPerchCB2)
str(YPerchCB2)
head(YPerchCB2)
op <- par(mfrow=c(1,2),pch=19)
plot(recruits~yrclass,data=YPerchCB2,type="b")
plot(recruits~stock,data=YPerchCB2)
par(op)

Recruitment time-series for Yellow Perch in Green Bay, 1978-1992.

Description

Yellow Perch (Perca flavescens) recruitment time-series for Green Bay, 1978-1992.

Format

A data frame with 15 observations on the following 2 variables:

year

Year of data.

recruits

Number of recruits (thousands per hour).

Topic(s)

Source

From Walters, C., and A. Punt. 1994. Placing odds on sustainable catch virtual population analysis and survey data. Canadian Journal of Fisheries and Aquatic Sciences, 51:946-958. Obtained from Ransom Myers old online database. CSV file

Examples

data(YPerchGB)
str(YPerchGB)
head(YPerchGB)
plot(recruits~year,data=YPerchGB)

Lengths and weights of Yellow Perch from Grafton Lake (ME) by year.

Description

Yellow Perch (Perca flavescens) fork lengths and weights separated by year.

Format

A data frame with 100 observations on the following 3 variables:

fl

Fork Length (nearest mm) at capture

w

Weight (nearest 0.1 g) at capture

year

Year of capture (1994 or 2000)

Topic(s)

Source

From (approximately) Figure 3 in Brylinsky, M. 2001. An evaluation of changes in the yellow perch (Perca flavescens) population of Grafton Lake, Kejimkujik National Park, after dam removal. Technical Report Publication No. 59, Acadia Centre for Estuarine Research. CSV file

Examples

data(YPerchGL)
str(YPerchGL)
head(YPerchGL)
op <- par(mfrow=c(1,2),pch=19)
plot(w~fl,data=YPerchGL,subset=year==1994,main="1994")
plot(w~fl,data=YPerchGL,subset=year==2000,main="2000")
par(op)

Recruitment time-series for Yellow Perch in Red Lakes, MN, 1942-1960.

Description

Yellow Perch (Perca flavescens) recruitment time-series for Red Lakes, MN, 1942-1960.

Format

a data.frame with:

year

Year of data.

recruits

CPUE of recruits (relative to a mean).

Topic(s)

Source

From Smith, L.L. Jr. 1977. Walleye (Stizostedion vitreum) and yellow perch (Perca flavescens) populations and fisheries of the Red Lakes, Minnesota, 1930-75. J. Fish. Res. Board Can. 34: 1774-1783. Obtained from Ransom Myers old online database. CSV file

Examples

data(YPerchRL)
str(YPerchRL)
head(YPerchRL)
plot(recruits~year,data=YPerchRL)

Stock and recruitment data for Yellow Perch from South Bay, Lake Huron, 1950-1983.

Description

Yellow Perch (Perca flavescens) stock and recruitment by year in South Bay, Lake Huron, 1950-1983.

Format

A data frame with 15 observations on the following 3 variables:

year

Year of data

stock

Spawning stock (number per set)

recruits

Recruits (number per set)

Topic(s)

Source

From Henderson, B.A. 1985. Factors affecting growth and recruitment of yellow perch, Perca flavescens Mitchill, in South Bay, Lake Huron. Journal of Fisheries Biology 26:449-458. Obtained from Ransom Myers old online database. CSV file

Examples

data(YPerchSB)
str(YPerchSB)
head(YPerchSB)
op <- par(mfrow=c(1,2),pch=19)
plot(recruits~year,data=YPerchSB,type="b")
plot(recruits~stock,data=YPerchSB)
par(op)

Lengths for Yellow Perch from two locations in Saginaw Bay, Lake Michigan.

Description

Length measurements for Yellow Perch (Perca flavescens) from two locations – inner and outer bay – in Saginaw Bay, Lake Michigan.

Format

A data frame with 2074 observations on the following 2 variables:

tl

Measured total length (cm).

loc

Location of capture (inner or outer).

Topic(s)

Source

Simulated (uniform distribution of values within length bin) from summarized length frequencies in Figure 2 (top) in Diana, J.S. and R. Salz. 1990. Energy storage, growth, and maturation of yellow perch from different locations in Saginaw Bay, Michigan. Transactions of the American Fisheries Society 119:976-984. CSV file

Examples

data(YPerchSB1)
str(YPerchSB1)
head(YPerchSB1)
op <- par(mfrow=c(1,2),pch=19)
with(subset(YPerchSB1,loc=="inner"),hist(tl,main="Inner"))
with(subset(YPerchSB1,loc=="outer"),hist(tl,main="Outer"))
par(op)

Lengths and weights for Yellow Perch from Trout Lake, WI.

Description

Lengths and weights for Yellow Perch (Perca flavescens) from Trout Lake, WI, 1981-2006. Fish were collected with a variety of gears.

Format

A data frame with 7238 observations on the following 7 variables:

lakeid

Lake name (all TR=Trout Lake)

year4

Year of capture

sampledate

Date of capture

gearid

Capture gear type – beach seine (BSEINE), crayfish trap (CRAYTR), electrofishing (ELFISH), fyke net (FYKNET), trammel net (TRAMML), vertical gillnets of different mesh sizes (VBN0XX), and different types of fyke nets (FYKNED and FYKNEL)

spname

Species name (all YELLOWPERCH)

length

Total Length (nearest mm) at capture

weight

Weight (nearest 0.1 or 1 g) at capture

Topic(s)

Source

From a query to the North Temperate Lakes Long Term Ecological Research, Fish Lengths and Weights Database. CSV file

Examples

data(YPerchTL)
str(YPerchTL)
head(YPerchTL)
plot(weight~length,data=YPerchTL)

Ages of Yellowtail Flounder assigned from scales and otoliths.

Description

Ages of commercially caught Georges Bank Yellowtail Flounder (Limanda ferruginea) as determined by scales, whole otoliths, or otolith cross-sections.

Format

A data frame with 27 paired observations on the following 3 variables.

scale

Ages assigned from scales

whole

Ages assigned from whole otoliths

cross

Ages assigned from cross-sections of otoliths

Topic(s)

Source

From tables in Annex 3 of Walsh, S.J. and J. Burnett. 2002. The Canada-United States yellowtail flounder age reading workshop: 28-30 November 2000, St. John's, Newfoundland. North Atlantic Fisheries Organization. Scientific Council Studies 35:1-59. CSV file

Examples

data(YTFlounder)
str(YTFlounder)
head(YTFlounder)
op <- par(mfrow=c(2,2),pch=19)
plot(scale~whole,data=YTFlounder)
plot(scale~cross,data=YTFlounder)
plot(whole~cross,data=YTFlounder)
par(op)