WL Open C 27 Feb 2013 Identification

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Organisms were taken out of the scint vial and washed through a 250  µm mesh sieve; then transferred to a petri dish with a small amount of water.  The organisms were sorted into organismal groups and then counted individually in each group; while counting a tally was made of the number per group. Upon completion, the organisms were transferred back into the vial and store in 70% EtOH.

*Oligochaete fragments were found in sample, but not included in final data.

Organism Number
Chaoborus 2
Chironominae 11
Tanypodinae 0
Ceratopogonidae 1

WL Open B 27 Feb 2013 Identification

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Organisms were taken out of the scint vial and washed through a 250  µm mesh sieve; then transferred to a petri dish with a small amount of water.  The organisms were sorted into organismal groups and then counted individually in each group; while counting a tally was made of the number per group. Upon completion, the organisms were transferred back into the vial and store in 70% EtOH.

*Oligochaete fragments were found in sample, but not included in final data.

Organism Number
Chaoborus 1
Chironominae 16
Tanypodinae 2
Ceratopogonidae 0

WL Open A 27 Feb 2013 Bug ID

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Organisms were taken out of the scint vial and washed through a 250  µm mesh sieve; then transferred to a petri dish with a small amount of water.  The organisms were sorted into organismal groups and then counted individually in each group; while counting a tally was made of the number per group. Upon completion, the organisms were transferred back into the vial and store in 70% EtOH.

*Oligochaete fragments were found in sample, but not included in final data.

Organism Number
Chaoborus 3
Chironominae 17
Tanypodinae 0
Ceratopogonidae 2

Generate a table of mean bug density and percent of total density of each taxon for Carly’s poster

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Macroinvertebrate abundance data and analysis for WL and LPP

Metadata

Collected by: Kenneth Fortino, Leanna Tacik, and Carly Martin

Collected on:

  • Wilkes Lake – 20 Feb 2013
  • Lancer Park Pond – 20 March 2013

Affiliation: Longwood University

Location:

  • Wilkes Lake – Samples were collected to the E of the island approximately equidistant from the N and S shore of the lake and about 20 m from the S shore.
  • Lancer Park Pond – Samples were collected in the approximate middle of the lake and in the SW corner of the pond about 1 m from the S shore

Description:

Three replicate samples were collected with an Ekman dredge and then washed through a 250μm mesh in the field and preserved in 70% ethanol.

Back in the lab the CPOM was removed from the samples by washing through a 1 mm sieve. Macroinvertebrates retained with this coarse fraction were removed from the CPOM by picking in a basin without magnification.

The macroinvertebrates collected in the fine fraction were removed from the fine sediment under a dissecting scope.

Insects were identified to family (ceratopogonidae), subfamily (chironomidae) or genus (chaoborus).

Oligochatetes were not identified or quantified and occurred mostly as fragments

Created: 17 April 2013

Modified:

18 April 2013 – added LPP data to bug dataset – KF

23 April 2013 – created data table of mean macroinvertebrate densities and the percent contribution of each taxa to the total density – KF

Variables:

  • lake = the name of the lake
    • WL = Wilkes Lake
    • LPP = Lance Park Pond
  • samp = the type of sample
    • open = away from the shore
    • lit = littoral, near shore

  • repl = the replicate

  • depth = the water depth where the sample was collected (m)

  • cerat.count = the number of Ceratopogonidae collected from a single Ekman

  • tany.count = the number of Tanypodinae collected from a single Ekman

  • chiro.count = the number of Chironominae collected from a single Ekman

  • chaob.count = the number of Chaoborus collected from a single Ekman

  • cerat = the density of Ceratopogonidae in n m-2

  • tany = the density of Tanypodinae in n m-2

  • chiro = the the density of Chironominae in n m-2

  • chaob = the density of Chaoborus in n m-2

  • bugs = the total macroinvertebrate density (omitting oligochaetes) in n m-2

R Code


# Generate Variables for data.frame

lake <- c(rep("WL", 6), rep("LPP", 6))
samp <- rep(c(rep("open", 3), rep("lit", 3)), 2)
repl <- rep(c("A", "B", "C"), 4)
depth <- c(rep(2.0, 3), rep(1.9, 3), rep(1.0, 3), rep(1.1, 3))
cerat.count <- c(0, 0, 5, 4, 7, 6, 0, 1, 0, 2, 0, 2)
tany.count <- c(25, 14, 23, 81, 29, 117, 5, 3, 1, 29, 20, 47)
chiro.count <- c(6, 5, 2, 0, 5, 0, 14, 4, 5, 5, 6, 41)
chaob.count <- c(5, 8, 15, 11, 16, 14, 0, 0, 0, 0, 0, 0)
# convert from count per ekman (n / 0.0225 m^2^) to densty (n / m^2^)
cerat <- cerat.count / 0.0225
tany <- tany.count / 0.0225
chiro <- chiro.count / 0.0225
chaob <- chaob.count / 0.0225
bugs <- cerat + tany + chiro + chaob
# create data.frame of macroinvertebrates for spring samples
WL.LPP.bugs.sp13 <- data.frame(lake, samp, repl, depth, cerat.count, tany.count, chiro.count, chaob.count, cerat, tany, chiro, chaob, bugs, stringsAsFactors = F)

# save data table

write.table(WL.LPP.bugs.sp13, file = "./data/WL_LPP_bugs_sp13.txt", row.names = F, quote = F)

Output


   lake samp repl depth cerat.count tany.count chiro.count chaob.count
1    WL open    A   2.0           0         25           6           5
2    WL open    B   2.0           0         14           5           8
3    WL open    C   2.0           5         23           2          15
4    WL  lit    A   1.9           4         81           0          11
5    WL  lit    B   1.9           7         29           5          16
6    WL  lit    C   1.9           6        117           0          14
7   LPP open    A   1.0           0          5          14           0
8   LPP open    B   1.0           1          3           4           0
9   LPP open    C   1.0           0          1           5           0
10  LPP  lit    A   1.1           2         29           5           0
11  LPP  lit    B   1.1           0         20           6           0
12  LPP  lit    C   1.1           2         47          41           0
       cerat       tany      chiro    chaob      bugs
1    0.00000 1111.11111  266.66667 222.2222 1600.0000
2    0.00000  622.22222  222.22222 355.5556 1200.0000
3  222.22222 1022.22222   88.88889 666.6667 2000.0000
4  177.77778 3600.00000    0.00000 488.8889 4266.6667
5  311.11111 1288.88889  222.22222 711.1111 2533.3333
6  266.66667 5200.00000    0.00000 622.2222 6088.8889
7    0.00000  222.22222  622.22222   0.0000  844.4444
8   44.44444  133.33333  177.77778   0.0000  355.5556
9    0.00000   44.44444  222.22222   0.0000  266.6667
10  88.88889 1288.88889  222.22222   0.0000 1600.0000
11   0.00000  888.88889  266.66667   0.0000 1155.5556
12  88.88889 2088.88889 1822.22222   0.0000 4000.0000
>

Analysis

Macroinvertebrate Presentation Table for Carly’s Poster

The following code is to generate a table of the mean density of the different macroinvertebrate taxa in each of the lakes and sampled locations.

Metadata

  • lake = the name of the lake (as above)
  • samp = the location of the sample (as above)
  • tany.mean = the mean density of tanypodinae (num m^-2)
  • tany.sd = the standard deviation of tany.mean
  • cerat.mean = the mean density of ceratopogonidae (num m^-2)
  • cerat.sd = the standard deviation of cerat.mean
  • chiro.mean = the mean density of chironiminae (num m^-2)
  • chiro.sd = the standard deviation of chiro.mean
  • chaob.mean = the mean density of chaoborus (num m^-2)
  • chaob.sd = the standard deviation of chaob.mean
  • bugs.mean = the mean density of all the collected and enumerated macroinvertebrates (excludes oligocheates) (num m^-2)
  • bugs.sd = the standard deviation of bugs.mean
  • tany.perc = the percentage of the total macroinvertebrate density (bugs.mean) that is made up of tanypodinae
  • cerat.perc = the percentage of the total macroinvertebrate density (bugs.mean) that is made up of ceratopogonidae
  • chiro.perc = the percentage of the total macroinvertebrate density (bugs.mean) that is made up of chironominae
  • chaob.perc = the percentage of the total macroinvertebrate density (bugs.mean) that is made up of chaoborus

# Calculate Mean Density and SD for each taxon in each sampling location and lake
## Wilkes Lake
## tany
tapply(WL.LPP.bugs.sp13$tany[WL.LPP.bugs.sp13$lake == "WL"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "WL"], mean)
tapply(WL.LPP.bugs.sp13$tany[WL.LPP.bugs.sp13$lake == "WL"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "WL"], sd)
# cerat
tapply(WL.LPP.bugs.sp13$cerat[WL.LPP.bugs.sp13$lake == "WL"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "WL"], mean)
tapply(WL.LPP.bugs.sp13$cerat[WL.LPP.bugs.sp13$lake == "WL"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "WL"], sd)
# chiro
tapply(WL.LPP.bugs.sp13$chiro[WL.LPP.bugs.sp13$lake == "WL"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "WL"], mean)
tapply(WL.LPP.bugs.sp13$chiro[WL.LPP.bugs.sp13$lake == "WL"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "WL"], sd)
# chaob
tapply(WL.LPP.bugs.sp13$chaob[WL.LPP.bugs.sp13$lake == "WL"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "WL"], mean)
tapply(WL.LPP.bugs.sp13$chaob[WL.LPP.bugs.sp13$lake == "WL"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "WL"], sd)
# bugs
tapply(WL.LPP.bugs.sp13$bugs[WL.LPP.bugs.sp13$lake == "WL"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "WL"], mean)
tapply(WL.LPP.bugs.sp13$bugs[WL.LPP.bugs.sp13$lake == "WL"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "WL"], sd)
## Lancer Park Pond
## tany
tapply(WL.LPP.bugs.sp13$tany[WL.LPP.bugs.sp13$lake == "LPP"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "LPP"], mean)
tapply(WL.LPP.bugs.sp13$tany[WL.LPP.bugs.sp13$lake == "LPP"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "LPP"], sd)
# cerat
tapply(WL.LPP.bugs.sp13$cerat[WL.LPP.bugs.sp13$lake == "LPP"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "LPP"], mean)
tapply(WL.LPP.bugs.sp13$cerat[WL.LPP.bugs.sp13$lake == "LPP"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "LPP"], sd)
# chiro
tapply(WL.LPP.bugs.sp13$chiro[WL.LPP.bugs.sp13$lake == "LPP"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "LPP"], mean)
tapply(WL.LPP.bugs.sp13$chiro[WL.LPP.bugs.sp13$lake == "LPP"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "LPP"], sd)
# chaob
tapply(WL.LPP.bugs.sp13$chaob[WL.LPP.bugs.sp13$lake == "LPP"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "LPP"], mean)
tapply(WL.LPP.bugs.sp13$chaob[WL.LPP.bugs.sp13$lake == "LPP"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "LPP"], sd)
# bugs
tapply(WL.LPP.bugs.sp13$bugs[WL.LPP.bugs.sp13$lake == "LPP"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "LPP"], mean)
tapply(WL.LPP.bugs.sp13$bugs[WL.LPP.bugs.sp13$lake == "LPP"], WL.LPP.bugs.sp13$samp[WL.LPP.bugs.sp13$lake == "LPP"], sd)

## Generate data.frame

lake <- c("WL", "WL", "LPP", "LPP")
samp <- c("open", "lit", "open", "lit")
tany.mean <- c(919, 3363, 133, 1422)
tany.sd <- c(260, 1966, 89, 611)
cerat.mean <- c(74, 252, 15, 59)
cerat.sd <- c(128, 68, 26, 51)
chiro.mean <- c(193, 74, 341, 770)
chiro.sd <- c(92, 128, 245, 911)
chaob.mean <- c(415, 607, 0, 0)
chaob.sd <- c(228, 112, NA, NA)
bugs.mean <- c(1600, 4296, 489, 2251)
bugs.sd <- c(400, 1778, 311, 1530)
tany.perc <- (tany.mean / bugs.mean) * 100
cerat.perc <- (cerat.mean / bugs.mean) * 100
chiro.perc <- (chiro.mean / bugs.mean) * 100
chaob.perc <- (chaob.mean / bugs.mean) * 100

# Create data frame
WL.LPP.meanBugs.sp13 <- data.frame(lake, samp, tany.mean, tany.sd, cerat.mean, cerat.sd, chiro.mean, chiro.sd, chaob.mean, chaob.sd, bugs.mean, bugs.sd, tany.perc, cerat.perc, chiro.perc, chaob.perc)

# Create output table
write.table(WL.LPP.meanBugs.sp13, file = "./data/WL_LPP_meanBugs_sp13.txt", row.names = F, quote = F)

Output


> WL.LPP.meanBugs.sp13
  lake samp tany.mean tany.sd cerat.mean cerat.sd chiro.mean chiro.sd
1   WL open       919     260         74      128        193       92
2   WL  lit      3363    1966        252       68         74      128
3  LPP open       133      89         15       26        341      245
4  LPP  lit      1422     611         59       51        770      911
  chaob.mean chaob.sd bugs.mean bugs.sd tany.perc cerat.perc chiro.perc
1        415      228      1600     400  57.43750   4.625000  12.062500
2        607      112      4296    1778  78.28212   5.865922   1.722533
3          0       NA       489     311  27.19836   3.067485  69.734151
4          0       NA      2251    1530  63.17192   2.621057  34.207019
  chaob.perc
1   25.93750
2   14.12942
3    0.00000
4    0.00000

Macroinvertebrate Data from LPP added to WL data

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Macroinvertebrate abundance data and analysis for WL and LPP

Metadata

Collected by: Kenneth Fortino, Leanna Tacik, and Carly Martin

Collected on:

  • Wilkes Lake – 20 Feb 2013
  • Lancer Park Pond – 20 March 2013

Affiliation: Longwood University

Location:

  • Wilkes Lake – Samples were collected to the E of the island approximately equidistant from the N and S shore of the lake and about 20 m from the S shore.
  • Lancer Park Pond – Samples were collected in the approximate middle of the lake and in the SW corner of the pond about 1 m from the S shore

Description:

Three replicate samples were collected with an Ekman dredge and then washed through a 250μm mesh in the field and preserved in 70% ethanol.

Back in the lab the CPOM was removed from the samples by washing through a 1 mm sieve. Macroinvertebrates retained with this coarse fraction were removed from the CPOM by picking in a basin without magnification.

The macroinvertebrates collected in the fine fraction were removed from the fine sediment under a dissecting scope.

Insects were identified to family (ceratopogonidae), subfamily (chironomidae) or genus (chaoborus).

Oligochatetes were not identified or quantified and occurred mostly as fragments

Created: 17 April 2013

Modified:

18 April 2013 – added LPP data to bug dataset – KF

Variables:

  • lake = the name of the lake
    • WL = Wilkes Lake
    • LPP = Lance Park Pond
  • samp = the type of sample
    • open = away from the shore
    • lit = littoral, near shore

  • repl = the replicate

  • depth = the water depth where the sample was collected (m)

  • cerat.count = the number of Ceratopogonidae collected from a single Ekman

  • tany.count = the number of Tanypodinae collected from a single Ekman

  • chiro.count = the number of Chironominae collected from a single Ekman

  • chaob.count = the number of Chaoborus collected from a single Ekman

  • cerat = the density of Ceratopogonidae in n m-2

  • tany = the density of Tanypodinae in n m-2

  • chiro = the the density of Chironominae in n m-2

  • chaob = the density of Chaoborus in n m-2

  • bugs = the total macroinvertebrate density (omitting oligochaetes) in n m-2

R Code


# Generate Variables for data.frame

lake <- c(rep("WL", 6), rep("LPP", 6))
samp <- rep(c(rep("open", 3), rep("lit", 3)), 2)
repl <- rep(c("A", "B", "C"), 4)
depth <- c(rep(2.0, 3), rep(1.9, 3), rep(1.0, 3), rep(1.1, 3))
cerat.count <- c(0, 0, 5, 4, 7, 6, 0, 1, 0, 2, 0, 2)
tany.count <- c(25, 14, 23, 81, 29, 117, 5, 3, 1, 29, 20, 47)
chiro.count <- c(6, 5, 2, 0, 5, 0, 14, 4, 5, 5, 6, 41)
chaob.count <- c(5, 8, 15, 11, 16, 14, 0, 0, 0, 0, 0, 0)
# convert from count per ekman (n / 0.0225 m^2^) to densty (n / m^2^)
cerat <- cerat.count / 0.0225
tany <- tany.count / 0.0225
chiro <- chiro.count / 0.0225
chaob <- chaob.count / 0.0225
bugs <- cerat + tany + chiro + chaob
# create data.frame of macroinvertebrates for spring samples
WL.LPP.bugs.sp13 <- data.frame(lake, samp, repl, depth, cerat.count, tany.count, chiro.count, chaob.count, cerat, tany, chiro, chaob, bugs, stringsAsFactors = F)

# save data table

write.table(WL.LPP.bugs.sp13, file = "./data/WL_LPP_bugs_sp13.txt", row.names = F, quote = F)

Output


   lake samp repl depth cerat.count tany.count chiro.count chaob.count
1    WL open    A   2.0           0         25           6           5
2    WL open    B   2.0           0         14           5           8
3    WL open    C   2.0           5         23           2          15
4    WL  lit    A   1.9           4         81           0          11
5    WL  lit    B   1.9           7         29           5          16
6    WL  lit    C   1.9           6        117           0          14
7   LPP open    A   1.0           0          5          14           0
8   LPP open    B   1.0           1          3           4           0
9   LPP open    C   1.0           0          1           5           0
10  LPP  lit    A   1.1           2         29           5           0
11  LPP  lit    B   1.1           0         20           6           0
12  LPP  lit    C   1.1           2         47          41           0
       cerat       tany      chiro    chaob      bugs
1    0.00000 1111.11111  266.66667 222.2222 1600.0000
2    0.00000  622.22222  222.22222 355.5556 1200.0000
3  222.22222 1022.22222   88.88889 666.6667 2000.0000
4  177.77778 3600.00000    0.00000 488.8889 4266.6667
5  311.11111 1288.88889  222.22222 711.1111 2533.3333
6  266.66667 5200.00000    0.00000 622.2222 6088.8889
7    0.00000  222.22222  622.22222   0.0000  844.4444
8   44.44444  133.33333  177.77778   0.0000  355.5556
9    0.00000   44.44444  222.22222   0.0000  266.6667
10  88.88889 1288.88889  222.22222   0.0000 1600.0000
11   0.00000  888.88889  266.66667   0.0000 1155.5556
12  88.88889 2088.88889 1822.22222   0.0000 4000.0000
>

Macroinvertebrate Data for WL, Spring 2013

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Macroinvertebrate abundance data and analysis for WL and LPP

Metadata

Collected by: Kenneth Fortino, Leanna Tacik, and Carly Martin

Collected on:

  • Wilkes Lake – 20 Feb 2013
  • Lancer Park Pond – 20 March 2013

Affiliation: Longwood University

Location:

  • Wilkes Lake – Samples were collected to the E of the island approximately equidistant from the N and S shore of the lake and about 20 m from the S shore.
  • Lancer Park Pond – Samples were collected in the approximate middle of the lake and in the SW corner of the pond about 1 m from the S shore

Description:

Three replicate samples were collected with an Ekman dredge and then washed through a 250μm mesh in the field and preserved in 70% ethanol.

Back in the lab the CPOM was removed from the samples by washing through a 1 mm sieve. Macroinvertebrates retained with this coarse fraction were removed from the CPOM by picking in a basin without magnification.

The macroinvertebrates collected in the fine fraction were removed from the fine sediment under a dissecting scope.

Insects were identified to family (ceratopogonidae), subfamily (chironomidae) or genus (chaoborus).

Oligochatetes were not identified or quantified and occurred mostly as fragments

Created: 17 April 2013

Modified: 17 April 2013

Variables:

  • lake = the name of the lake
    • WL = Wilkes Lake
    • LPP = Lance Park Pond
  • samp = the type of sample
    • open = away from the shore
    • lit = littoral, near shore

  • repl = the replicate

  • depth = the water depth where the sample was collected (m)

  • cerat.count = the number of Ceratopogonidae collected from a single Ekman

  • tany.count = the number of Tanypodinae collected from a single Ekman

  • chiro.count = the number of Chironominae collected from a single Ekman

  • chaob.count = the number of Chaoborus collected from a single Ekman

  • cerat = the density of Ceratopogonidae in n m-2

  • tany = the density of Tanypodinae in n m-2

  • chiro = the the density of Chironominae in n m-2

  • chaob = the density of Chaoborus in n m-2

  • bugs = the total macroinvertebrate density (omitting oligochaetes) in n m-2

R Code


# Generate Variables for data.frame

lake <- c(rep("WL", 6), rep("LPP", 6))
samp <- rep(c(rep("open", 3), rep("lit", 3)), 2)
repl <- rep(c("A", "B", "C"), 4)
depth <- c(rep(2.0, 3), rep(1.9, 3), rep(1.0, 3), rep(1.1, 3))
cerat.count <- c(0, 0, 5, 4, 7, 6, NA, NA, NA, NA, NA, NA)
tany.count <- c(25, 14, 23, 81, 29, 117, NA, NA, NA, NA, NA, NA)
chiro.count <- c(6, 5, 2, 0, 5, 0, NA, NA, NA, NA, NA, NA)
chaob.count <- c(5, 8, 15, 11, 16, 14, NA, NA, NA, NA, NA, NA)
# convert from count per ekman (n / 0.0225 m^2^) to densty (n / m^2^)
cerat <- cerat.count / 0.0225
tany <- tany.count / 0.0225
chiro <- chiro.count / 0.0225
chaob <- chaob.count / 0.0225
bugs <- cerat + tany + chiro + chaob
# create data.frame of macroinvertebrates for spring samples
WL.LPP.bugs.sp13 <- data.frame(lake, samp, repl, depth, cerat.count, tany.count, chiro.count, chaob.count, cerat, tany, chiro, chaob, bugs, stringsAsFactors = F)

# save data table

write.table(WL.LPP.bugs.sp13, file = "./data/WL_LPP_bugs_sp13.txt", row.names = F, quote = F)

Output


   lake samp repl depth cerat.count tany.count chiro.count chaob.count    cerat
1    WL open    A   2.0           0         25           6           5   0.0000
2    WL open    B   2.0           0         14           5           8   0.0000
3    WL open    C   2.0           5         23           2          15 222.2222
4    WL  lit    A   1.9           4         81           0          11 177.7778
5    WL  lit    B   1.9           7         29           5          16 311.1111
6    WL  lit    C   1.9           6        117           0          14 266.6667
7   LPP open    A   1.0          NA         NA          NA          NA       NA
8   LPP open    B   1.0          NA         NA          NA          NA       NA
9   LPP open    C   1.0          NA         NA          NA          NA       NA
10  LPP  lit    A   1.1          NA         NA          NA          NA       NA
11  LPP  lit    B   1.1          NA         NA          NA          NA       NA
12  LPP  lit    C   1.1          NA         NA          NA          NA       NA
        tany     chiro    chaob     bugs
1  1111.1111 266.66667 222.2222 1600.000
2   622.2222 222.22222 355.5556 1200.000
3  1022.2222  88.88889 666.6667 2000.000
4  3600.0000   0.00000 488.8889 4266.667
5  1288.8889 222.22222 711.1111 2533.333
6  5200.0000   0.00000 622.2222 6088.889
7         NA        NA       NA       NA
8         NA        NA       NA       NA
9         NA        NA       NA       NA
10        NA        NA       NA       NA
11        NA        NA       NA       NA
12        NA        NA       NA       NA

OM data analysis for WL and LPP Spring 2013

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CPOM Mass Data and Analysis for WL and LPP

Metadata

Collected by: Kenneth Fortino, Leanna Tacik, and Carly Martin

Collected on:

  • Wilkes Lake – 20 Feb 2013
  • Lancer Park Pond – 20 March 2013

Affiliation: Longwood University

Location:

  • Wilkes Lake – Samples were collected to the E of the island approximately equidistant from the N and S shore of the lake and about 20 m from the S shore.
  • Lancer Park Pond – Samples were collected in the approximate middle of the lake and in the SW corner of the pond about 1 m from the S shore

Description:

Three replicate samples were collected with an Ekman dredge and then washed through a 250μm mesh in the field and preserved in 70% ethanol.

Back in the lab the preserved samples were washed through a 1 mm sieve. For WL the material retained by the sieve was dried in a pre-weighed weigh boat at 50o C for at least 48h before massing. For LPP the material retained by the sieve was collected in a pre-weighed paper lunch bag and dried for at least 48 h before massing.

Created: 12 April 2013

Modified: 12 April 2013

Variables:

  • lake = the name of the lake
    • WL = Wilkes Lake
    • LPP = Lance Park Pond
  • samp = the type of sample
    • open = away from the shore
    • lit = littoral, near shore

  • repl = the replicate

  • depth = the water depth where the sample was collected (m)

  • cruc.num = the name of the crucible

  • cruc.mass = the mass of the empty crucible (g)

  • cruc.sed = the mass of the crucuble and the dry sediment (g)

  • cruc.ash = the mass of the crucible and ashed (550o C for 4h) sediment (g)

  • sed = the mass of the dry sediment in crucible (g)

  • ash = the mass of the ashed sediment in crucible (g)

  • OM = the mass of the organic matter in crucible (g)

  • perc.OM = the percent organic matter in the sediment

  • boat.bag.num = the name of the pre-weighed weighboat or paper pag

  • boat.bag.mass = the mass of the empty weighboat or paper bag (g)

  • boat.bag.CPOM = the mass of the weighboat + the dried CPOM (g)

  • CPOM.ekman = the mass of the dry CPOM (g / 0.0225 m2)

  • CPOM = the mass of the dry CPOM (g / m2)

R Code


# Import LOI data to add CPOM data

WL.LPP.LOI.sp13 <- read.delim("./data/WL_LPP_LOI_sp13.txt", header = T, sep = " ", stringsAsFactors = F)

# Create variable for CPOM
# note these data replace the data in WL_CPOM_20Feb2013.md

boat.bag.num <- c(27, 72, 57, 28, 53, 66, 4, 5, 6, 1, 2, 3)
boat.bag.mass <- c(1.6925, 1.8084, 1.7482, 1.9434, 1.8294, 1.8443, 7.1048, 7.0473, 7.1103, 7.0334, 6.9891, 7.1693)
boat.bag.CPOM <- c(1.8544, 2.204, 2.0725, 2.4342, 2.4063, 2.5529, 12.3407, 9.0054, 8.4776, 36.5694, 12.7007, 23.0556)
CPOM.ekman <- boat.bag.CPOM - boat.bag.mass
# convert from g / 0.0225 m^2^ to g / m^2^
CPOM <- CPOM.ekman / 0.0225
# Create data.frame of all OM data from WL LPP spring 2013 sampling

WL.LPP.OM.sp13 <- data.frame(WL.LPP.LOI.sp13, boat.bag.num, boat.bag.mass, boat.bag.CPOM, CPOM.ekman, CPOM)

# Save data table

write.table(WL.LPP.OM.sp13, file = "./data/WL_LPP_OM_sp13.txt", row.names = F, quote = F)

Data


> WL.LPP.OM.sp13
   lake samp repl depth cruc.num cruc.mass cruc.sed cruc.ash    sed    ash
1    WL open    A   2.0        1   13.1339  16.1084  16.0627 2.9745 2.9288
2    WL open    B   2.0        2   12.6351  16.9807  16.7785 4.3456 4.1434
3    WL open    C   2.0        3   13.0659  14.1274  14.0378 1.0615 0.9719
4    WL  lit    A   1.9        4   12.2410  13.4951  13.3678 1.2541 1.1268
5    WL  lit    B   1.9        5   12.9951  14.9187  14.7305 1.9236 1.7354
6    WL  lit    C   1.9        6   11.9876  13.2359  13.1089 1.2483 1.1213
7   LPP open    A   1.0        7   12.1973  13.1231  13.0049 0.9258 0.8076
8   LPP open    B   1.0        8   12.5987  14.3463  14.1463 1.7476 1.5476
9   LPP open    C   1.0        9   11.6665  13.0951  12.9363 1.4286 1.2698
10  LPP  lit    A   1.1       10   12.9349  13.5505  13.4565 0.6156 0.5216
11  LPP  lit    B   1.1       11   11.8880  12.7876  12.6797 0.8996 0.7917
12  LPP  lit    C   1.1       12   11.7819  12.1739  12.1200 0.3920 0.3381
     perc.OM boat.bag.num boat.bag.mass boat.bag.CPOM CPOM.ekman        CPOM
1   1.536393           27        1.6925        1.8544     0.1619    7.195556
2   4.652982           72        1.8084        2.2040     0.3956   17.582222
3   8.440886           57        1.7482        2.0725     0.3243   14.413333
4  10.150706           28        1.9434        2.4342     0.4908   21.813333
5   9.783739           53        1.8294        2.4063     0.5769   25.640000
6  10.173836           66        1.8443        2.5529     0.7086   31.493333
7  12.767336            4        7.1048       12.3407     5.2359  232.706667
8  11.444266            5        7.0473        9.0054     1.9581   87.026667
9  11.115778            6        7.1103        8.4776     1.3673   60.768889
10 15.269656            1        7.0334       36.5694    29.5360 1312.711111
11 11.994220            2        6.9891       12.7007     5.7116  253.848889
12 13.750000            3        7.1693       23.0556    15.8863  706.057778
>

Analysis

Relationship between CPOM, lake, and sample location

Due to non-homogeneity in the variance the CPOM mass was ln transformed


# SD in CPOM across samp
tapply((WL.LPP.OM.sp13$CPOM), WL.LPP.OM.sp13$samp, sd)
     lit     open 
522.8097  85.5926 

tapply(log(WL.LPP.OM.sp13$CPOM), WL.LPP.OM.sp13$samp, sd)
     lit     open 
1.815811 1.302288

# SD in CPOM across lake
tapply(WL.LPP.OM.sp13$CPOM, WL.LPP.OM.sp13$lake, sd)
       LPP         WL 
485.471298   8.574693

tapply(log(WL.LPP.OM.sp13$CPOM), WL.LPP.OM.sp13$lake, sd)
      LPP        WL 
1.1783661 0.5225174

After transformation the CPOM mass was significantly greater in LPP and in the littoral samples and there was no interaction between the factors.


# 2-way ANOVA of CPOM mass ln transformed by lake * sample location

anova(lm(log(CPOM) ~ as.factor(lake) * as.factor(samp), data = WL.LPP.OM.sp13))

> anova(lm(log(CPOM) ~ as.factor(lake) * as.factor(samp), data = WL.LPP.OM.sp13))
Analysis of Variance Table

Response: log(CPOM)
                                Df  Sum Sq Mean Sq F value    Pr(>F)    
as.factor(lake)                  1 21.3718 21.3718 59.9653 5.516e-05 ***
as.factor(samp)                  1  4.7140  4.7140 13.2266  0.006619 ** 
as.factor(lake):as.factor(samp)  1  0.7427  0.7427  2.0838  0.186865    
Residuals                        8  2.8512  0.3564                      

jpeg("./output/plots/CPOM_by_lake_samp_sp13.jpg")
par(las = 1)
plot(log(CPOM) ~ as.factor(samp), data = WL.LPP.OM.sp13, subset = lake == "WL", ylim=c(0, 7), col = "green")
plot(log(CPOM) ~ as.factor(samp), data = WL.LPP.OM.sp13, subset = lake == "LPP", add = T, col = "brown")
legend(0.5, 1.5, c("WL", "LPP"), pch=16, col=c("green", "brown"))
dev.off()
pdf("./output/plots/CPOM_by_lake_samp_sp13.pdf")
plot(log(CPOM) ~ as.factor(samp), data = WL.LPP.OM.sp13, subset = lake == "WL", ylim=c(0, 7), col = "green")
plot(log(CPOM) ~ as.factor(samp), data = WL.LPP.OM.sp13, subset = lake == "LPP", add = T, col = "brown")
legend(0.5, 1.5, c("WL", "LPP"), pch=16, col=c("green", "brown"))
dev.off()
ln CPOM mass by lake and sample location, Spring 2013

ln CPOM mass by lake and sample location, Spring 2013

Identification of LPP Open A 20 March 2013

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Though this sample was taken at LPP, the process of identification remains the same. Organisms were taken out of the scint vial and washed through a 250  µm mesh sieve; then transferred to a petri dish with a small amount of water.  The organisms were sorted into organismal groups and then counted individually in each group; while counting a tally was made of the number per group. Upon completion, the organisms were transferred back into the vial and store in 70% EtOH.

*Oligochaete fragments were found in sample, but not included in final data.

Organism Number
Chaoborus 0
Chironominae 14
Tanypodinae 5
Ceratopogonidae 0

WL Open/Shallow A 20 Feb 2013

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Organisms were taken out of the scint vial and washed through a 250  µm mesh sieve; then transferred to a petri dish with a small amount of water.  The organisms were sorted into organismal groups and then counted individually in each group; while counting a tally was made of the number per group. Upon completion, the organisms were transferred back into the vial and store in 70% EtOH.

*Oligochaete fragments were found in sample, but not included in final data.

Organism Number
Chaoborus 0
Chironominae 6
Tanypodinae 25
Ceratopogonidae 0

WL Open/ Shallow B 20 Feb 2013

Leave a reply

Organisms were taken out of the scint vial and washed through a 250  µm mesh sieve; then transferred to a petri dish with a small amount of water.  The organisms were sorted into organismal groups and then counted individually in each group; while counting a tally was made of the number per group. Upon completion, the organisms were transferred back into the vial and store in 70% EtOH.

*Oligochaete fragments were found in sample, but not included in final data.

Organism Number
Chaoborus 0
Chironominae 5
Tanypodinae 14
Ceratopogonidae 0