---
title: 'Read Me'
author: 'Florian Muthreich'
date: '2020/02/04'
output: pdf_document
---

# Reproducability
The file 'packages.R' is a list of essential packages that are needed to run the analysis and figures in this manuscript.
This manuscript is also enabled for the package 'renv' which enables a sandboxed, version controlled library of all packages used during writing and analysis.
The 'renv.lock' file can be used to initiate the library after 'renv' is installed by calling 'renv::restore()'.

# Detailed Methods and Materials

## Pollen Counts
```{r DALcounts, echo=FALSE, results='asis'}
count_grains = function(core){
  counts = core %>%
    subset(type == "pollen" & species == "Pinus") %>% 
    group_by(type, depth, treatment) %>%
    summarise(count=n())
  return(counts)
}
count_grains = function(core){
  counts = core %>%
    subset(type == "pollen") %>% 
    group_by(treatment, depth, species) %>%
    summarise(count=n())
  return(counts)
}
kable(count_grains(DAL), booktabs = T, format = "latex",
      caption = "Pinus pollen grain count in Dalmutladdo core.")
#      digits = 1, format.args = list(scientific = F),
#      col.names = c("")) %>% 
#  add_header_above()
```

```{r TSKcounts, echo=FALSE, results='asis'}
kable(count_grains(TSK), booktabs = T, format = "latex",
      caption = "Pinus pollen grain count in Tiefer See core.")
```

```{r MFMcounts, echo=FALSE, results='asis'}
kable(count_grains(MFM), booktabs = T, format = "latex",
      caption = "Pinus pollen grain count in Meerfelder Maar core.")
```


## Mean spectra

```{r}
mean_plotsSM = readRDS(here("data","output","mean_plots.rds"))
mean_plots = readRDS(here("data","output","mean_plots_whole.rds"))
```

```{r echo = FALSE, message=FALSE, warning=FALSE, out.width = "100%", fig.cap="DAL SPT"}
mean_plotsSM[[1]]
```

```{r echo = FALSE, message=FALSE, warning=FALSE, out.width = "100%", fig.cap="DAL acet"}
mean_plotsSM[[2]]
```

```{r echo = FALSE, message=FALSE, warning=FALSE, out.width = "100%", fig.cap="TSK SPT"}
mean_plotsSM[[3]]
```

```{r echo = FALSE, message=FALSE, warning=FALSE, out.width = "100%", fig.cap="TSK acet"}
mean_plotsSM[[4]]
```

```{r echo = FALSE, message=FALSE, warning=FALSE, out.width = "100%", fig.cap="MFM SPT"}
mean_plotsSM[[5]]
```

```{r echo = FALSE, message=FALSE, warning=FALSE, out.width = "100%", fig.cap="MFM acet"}
mean_plotsSM[[6]]
```

\newpage

```{r echo = FALSE, message=FALSE, warning=FALSE, out.width = "100%", fig.cap="DAL SPT"}
blank_mean_plots = readRDS(here("data","output","blank_mean_plots.rds"))
blank_mean_plots[[1]]
```

```{r echo = FALSE, message=FALSE, warning=FALSE, out.width = "100%", fig.cap="DAL acet"}
blank_mean_plots[[2]]
```

```{r echo = FALSE, message=FALSE, warning=FALSE, out.width = "100%", fig.cap="TSK SPT"}
blank_mean_plots[[3]]
```

```{r echo = FALSE, message=FALSE, warning=FALSE, out.width = "100%", fig.cap="TSK acet"}
blank_mean_plots[[4]]
```

```{r echo = FALSE, message=FALSE, warning=FALSE, out.width = "100%", fig.cap="MFM SPT"}
blank_mean_plots[[5]]
```

```{r echo = FALSE, message=FALSE, warning=FALSE, out.width = "100%", fig.cap="MFM acet"}
blank_mean_plots[[6]]
```

## SPT extraction

Pollen extraction:

1. add 1 cube to vial (~1cm^-3^)
2. wash with water -> dissolve sediment vortex
3. centrifuge 3min 3000rpm
4. decant; save decant
5. add 3 ml 1.43 SPT solution
6. vortex
7. centrifuge 3min 3000rpm
8. decant supernatant into new vial
9. repeat 5-7; decant into same vial
10. wash with water; save decant for checking
11. wash with water; save decant x2
12. wash residue with water; save in vial

#Lab-Notes
##Samples 2020-02-13
Vial  Sample         Pinus  Betula  Salix  Spores
5*    A4-DL 138-140  +++    +              +++
4     D4-DL 161-163  ++     +              +++
4*    A5-UR  64- 66  ++     +       1      +++

1. add 1 cube to vial (~1cm^-3^)
2. wash with water -> dissolve sediment vortex
3. centrifuge 3min 3000rpm
4. decant; save decant
5. add 3 ml 1.43 SPT solution
6. vortex
7. centrifuge 3min 3000rpm
8. decant supernatant into new vial
9. repeat 5-7; decant into same vial
10. wash with water; save decant for checking
11. wash with water; save decant x2
12. wash residue with water; save in vial

2nd Run
Vial  Sample
2*    A4-DL 188-190
3*    A5-UR  72- 74
5     D4-DL 182-184
6     A4-DL 130-132
7*    A4-DL 163-165

3rd Run
Vial  Sample
4     A4-DL 175-177
5     D4-DL 149-151
6     A4-DL 145-147
7*    D4-DL 138-140

##Samples 2020-02-19
Vial  Samples
1     TSK15-K6 42.0-42.8
2*    TSK15-K6 17.5-18.2
3*    TSK15-K6 38.7-39.2
4*    TSK15-K6  9.8-10.5
4     TSK15-K6 26.0-26.8
5     TSK15-K6  0.0- 1.5
5*    TSK15-K6 14.0-14.5
6     TSK15-K6 34.0-35.0
7     TSK15-K6 29.5-31.0
8     TSK15-K6 21.5-22.2

##Samples 2020-05-04
Urio Zuazzrocchi
Vial  Samples
1     UQC-20
2     UQC-70
2*    UQC-150
3*    UQC-268
4     UQC-365
5*    UQC-468
6     UQC-588
7     UQC-667
8     UQC-767
8*    UQC-882

Notes: after first waterwash vial 5-8 spilled in the centrifuge

##Samples 2020-05-05
Sa Curcurica
Vial  Samples
1     SCUR-12
2     SCUR-120
2*    SCUR-232
3*    SCUR-328
4     SCUR-430
5*    SCUR-526
6     SCUR-664
7     SCUR-728
8     SCUR-824
8*    SCUR-944

##Samples 2020-05-06
Lago del Sangiatto
Vial  Samples
1     SNG-32
2     SNG-72
2*    SNG-128
3*    SNG-176
4     SNG-224
5*    SNG-264
6     SNG-308
7     SNG-328
8     SNG-360
8*    SNG-390

##Samples 2020-05-07
Dalmutladdo
Vial  Samples
1     DL-20
2     DL-40
2*    DL-60
3*    DL-90
4     DL-100
5*    DL-110
6     DL-120
7     DL-130
8     DL-140
8*    DL-150



Meeting with Boris
higher microscope
tradeoff more time less image
BSi region showing up on the spectra
36x 1 px = 1 µm
testing of objective

#Plan for Ås Lab work

dependant on results from Boris tests

Status after last update that binding medium is working:
- much better picture than on ZnSe slides
- only measured empty sample
- normal objectiv works, no switching objectives needed
- if comparison to modern material, needs to be measured on new setup as well, cant use old data
Problems:
- Pollen density on slides
- unknownd layer over pollen; BSi? (maybe more washing, switching to store in alcohol instead of water?)

Possible set ups:
1. Measure one core. Multiple samples (5+), multiple species (3+) -> 15 samples
2. measure multiple cores (5+), reduced number of samples (<3) and red species (1; only Pinus) -> 15 samples

RQ for both setups:
Description of method for FTIR analysis of single grain fossil pollen

specific to 1: 
RQ1 Taxonomic differences between fossil pollen
RQ2 change in pollen chem with age (finer scale 100s of years)

specific to 2:
RQ1 chem differences of same species between cores (assuming P. sylvestris everwhere)
RQ2 change in pollen with age (broader scale 1000s of years)

#Ås Labwork

2020-05-11
Bergen PS7_02
all sideways pollen
polar pollen left 2x2

INN_PS3_01
sideways pollen: all
polar pollen: 1x1 and 1x2

INN_PS19_01
sideways_pollen: 1x1, 1x3
polar pollen: 1x1,1x2

DAL_20_01
all Pinus
Alnus (6)
BetCor (8)

DAL_20_02
all Pinus
Alnus (1)
BetCor (7)

BGO_PS08
sideways: 25 grains
polar: 25 grains

DAL_90_01
all Pinus (8)
blanks (6)

DAL_90_02
all Pinus (9)
blanks (6)

DAL_90_03
all Pinus (19)
blanks (6)

DAL_130_01
all Pinus (12)
blanks (6)

DAL_130_02
all Pinus (27)
blanks (6)

DAL_60_01
Pinus 1x1 to 6x4 (47)
blanks (6)

DAL_110_01
Pinus (11)
blanks (6)

DAL_110_02
Pinus (21)
blanks (6)

DAL_150_03-09
Pinus (7)

Cor_ave 14B1 skip 1x2 quadrant

DAL_08_01
Pinus (7)
blanks (4)

DAL_08_02
Pinus (2)
blanks (4)

DAL_08_03
Pinus (2)

DAL_40_01
Pinus 1x1 to 2x6 (37)
blanks (5)

DAL_08_04-15
Pinus (12)

DAL_140_01_17
Pinus (17)

# Notes
extracted fossil pollen from sediment.
ca 5 common taxa: Alnus, Picea, Pinus,

## Cores
Dalmuttlado:
- pine
- holocene

Younger Dryas [@brauerHighResolutionSediment1999]:
- 12 samples laminated sediment
- from  11400 to 13120
- min 500 grains
- pollen conc highest in 11000-11600 and 12700-12900
- Pinus betula most common (ca 150 grains counted)
- salix (ca 25 counted)
- quercus throughout in low conc (<1%)
- graminoids/cyperaceae/artemisia common

Tiefer See [@theuerkaufEffectsChangesLand2015]:
- 1870-2010
- laminated sediments
- Pinus pollen

Research Questions:
1. chemical variation between taxa in the same cores.
2. chemical variation between taxa between cores 
3. chemical variation of pollen with depths/age

## Labwork Report

did µFTIR on fresh and fossil pollen using Hyperion-FPA

This is very sample dependent.
organic rich cores are problematic (requires a better extraction protocol), pollen density is another.
Dalmutladdo was a very good core for this: low in organic and relatively rich in pollen.
BSi increased with depth, highest in oldest samples (extracted blanks).
Still, some depth were more time intensive (130/150), low amount of pollen .
I managed about 2-3 core samples per day, the fresh samples can be done in a fraction of the time, all done within 1 half day.

9 depth from Dalmutladdo core. targeted and extracted Pinus pollen (Table \@ref(tab:pollencounts), Table \@ref(tab:fresh))

possibilities for Alnus and Betula, even though scattering visible in spectra 

```{r pollencounts, echo=FALSE}
dalmutladdo = data.frame(ID = c("DAL_08","DAL_20","DAL_40","DAL_60","DAL_90", "DAL_110","DAL_130","DAL_140","DAL_150"),
                         pinus_pollen = c(23,49,37,47,36,32,39,17,7),
                         alnus_pollen = c(0,7,0,0,0,0,0,0,0),
                         betula_pollen = c(0,15,0,0,0,0,0,0,0))
knitr::kable(dalmutladdo, format="latex", booktabs=TRUE,
             caption = "Pollen counts")
```

```{r fresh, echo=FALSE}
fresh_pollen = data.frame(ID = c("BGO_PS7", "BGO_PS8", "INN_PS13", "INN_PS19A","NMBU_Pin_syl_14E1", "NMBU_Pin_syl_14H1", "NMBU_Aln_glu_14E1", "NMBU_Aln_glu_14J1", "NMBU_Aln_inc_14B1", "NMBU_Aln_inc_14G1", "NMBU_Bet_pub_14A1", "NMBU_Bet_pub_14B1", "NMBU_Cor_ave_14B1", "NMBU_Cor_ave_14C1"),
                          extracted = c(109,55,51,24,0,0,0,0,0,0,0,0,0,0))
knitr::kable(fresh_pollen, format="latex", booktabs=TRUE,
             caption = "Fresh pollen counts")
```

9 fossil samples from 1 core

2 trees of Pinus at each location

Research questions we could answer with this set:

- Differences between fresh and fossil/near fossil grains of Pinus
- chemical changes in Pinus pollen with age/depth
(- chemical differences between Pinus/Alnus/Betula)

extensions to this set:
- add more samples from Dalmuttladdo highest and lowest depth (maybe labwork)
- add cores (e.g. MFM, Tiefer See or Italian cores), Festi core was quite organic rich
- add more grains from already measured samples (to hit min 25 or 50)