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piney_point.Rmd
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---
title: "Piney Point Data and Analysis"
author: "[Dr. Marcus Beck](mailto:[email protected]) $\\bullet$ [\\@fawda123](https://twitter.com/fawda123) $\\bullet$ [#TampaBayOpensci](https://twitter.com/hashtag/TampaBayOpenSci?src=hashtag_click)"
institute: "Tampa Bay Estuary Program"
date: "6/15/2021"
output:
xaringan::moon_reader:
nature:
highlightLines: true
countIncrementalSlides: false
ratio: '16:9'
lib_dir: libs
css: styles.css
includes:
after_body: insert-logo-tbep.html
---
```{r, message = F, echo = F, warning = F}
library(knitr)
library(tidyverse)
library(lubridate)
library(extrafont)
library(xaringanExtra)
library(sf)
use_panelset()
source(file = "https://raw.githubusercontent.com/EvaMaeRey/little_flipbooks_library/master/xaringan_reveal_parenthetical.R")
loadfonts(device = 'win', quiet = T)
fml <- 'Lato Light'
# global knitr options
opts_chunk$set(message = FALSE, dev.args = list(family = fml), dpi = 300, dev = 'png', echo = F, warning = F, fig.align = 'center', out.width = '100%')
```
class: left, top
.center[
# Goals for today
]
* Understand the available data
* Understand how to access the available data
* Analyses to date
* Develop analysis goals and plan of attack
* Meeting notes [here](https://docs.google.com/document/d/1gWFnNe5kPj5rLmgmrLbVlt2UsxfE4pX1v6Gfdh8HbZc/edit)
---
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.center[
# Data in hand
]
* All raw data from partners are here (spreadsheet, GoogleDrive): https://bit.ly/3wtC5gz
* All compiled/formatted data are here (.RData, GitHub): https://github.com/tbep-tech/piney-point/tree/main/data)
---
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.center[
# Data in hand
]
* __Water quality__: 17 parameters
* __Phytoplankton__: qualitative, quantitative
* __Seagrass, macroalgae__: Freq. occurrence by species, groups
* __Contaminants__: mostly metals
* __Baseline__: water quality and seagrass
* __Spatial__: monitoring stations by type
---
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.center[
# Data in hand
]
* All data pulled from GoogleDrive and synthesized using [this](https://github.com/tbep-tech/piney-point/blob/main/R/dat_proc.R) R script
* Compile by source (e.g., DEP, Manatee Co., etc.)
* Standardize names, units, etc.
* Organize in tidy format for ease of analysis
* Each time data are updated, several automated [tests](https://github.com/tbep-tech/piney-point/tree/main/tests/testthat) are run to check accuracy, e.g.,
* Are the units, names correct?
* Are the station names matching between files?
* Are their duplicates, missing values?
---
class: left, top
.center[
# Getting the data
]
* All files are in .RData binary formats, access in R (I can make csv if needed)
* Files follow a loose naming convention, e.g.,
* `rswqdat`: response water quality data
* `bswqdat`: baseline water quality data
* `rstrndat`: response SAV, macroalgae transect data
* `rsphydat`: response phytoplankton data
* `rstrnpts`: response transect spatial data (points)
---
class: left, top
.center[
# Getting the data
]
* All files are "tidy" and able to join by station, source and/or date
```{r, echo = T}
load(url('https://tbep-tech.github.io/piney-point/data/rswqdat.RData'))
rswqdat
```
---
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.center[
# Analyses to date
]
* Some preliminary stuff: [https://github.com/tbep-tech/piney-point-analysis](https://github.com/tbep-tech/piney-point-analysis)
* [Interpolation example](https://tbep-tech.github.io/piney-point-analysis/chlinterp): chlorophyll response
* [Trends synthesis](https://tbep-tech.github.io/piney-point-analysis/trends): poor attempt at broad analysis
* [Seasonal analysis](https://tbep-tech.github.io/piney-point-analysis/seasonal): deviation from baseline relative to hydrology
* The data folder in this repo is synced daily with the source data on the Piney Point dashboard repo
* Open for GitHub Pull Requests
---
class: left, top
.center[
# Analysis goals
]
* We know there was an initial water column algal response
* We need to show other responses, the nutrients did not go away:
* Nutrient recycling between parts of the bay
* Broad vs local changes
* Deviation from baseline
* Link to modelling data
* Immediate concern is documenting impacts, but long-term plan is publication