Merge pull request #41 from weecology/2023-cleanup

weecology · Aug 21, 2023 · 1e00ec1 · 1e00ec1
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diff --git a/content/lessons/R-empirical-dynamic-modeling/_index.md b/content/lessons/R-empirical-dynamic-modeling/_index.md
@@ -2,7 +2,7 @@
 title: "Empirical Dynamic Modeling in R"
 linkTitle: "R: Empirical Dynamic Modeling"
 type: book
-weight: 24
+weight: 26
 summary: R Tutorial on fitting and making forecasts using empirical dynamic modeling
 show_date: false
 editable: true

diff --git a/content/lessons/R-empirical-dynamic-modeling/material.md b/content/lessons/R-empirical-dynamic-modeling/material.md
@@ -0,0 +1,14 @@
+---
+title: "Data & Software"
+weight: 1
+type: book
+summary: Software installation requirements
+show_date: false
+editable: true
+---
+
+## Software installation requirements
+
+* `ggplot2` R package: `install.packages('ggplot2')`
+* `portalr` R package: `install.packages('portalr')`
+* `rEDM` R package: `install.packages('rEDM')`
diff --git a/content/lessons/R-forecasting-gams/_index.md b/content/lessons/R-forecasting-gams/_index.md
@@ -0,0 +1,19 @@
+---
+title: "Forecasting with GAMs in R"
+linkTitle: ""
+type: book
+weight: 19
+summary: "Using generalized additive models for making forecasts"
+show_date: false
+editable: true
+---
+
+{{% callout note %}}
+
+**Learning Objectives:**
+* First lesson objective
+* Second lesson objective
+
+{{% /callout %}}
+
+{{< list_children >}}
diff --git a/content/lessons/R-species-distribution-models/_index.md b/content/lessons/R-species-distribution-models/_index.md
@@ -2,7 +2,7 @@
 title: "Species Distribution Models in R"
 linkTitle: "R: Species Distribution Models"
 type: book
-weight: 20
+weight: 22
 summary: An R tutorial on using fitting simple species models and making forecasts based on these models
 show_date: false
 editable: true

diff --git a/content/lessons/R-time-series-GAMS/_index.md b/content/lessons/R-time-series-GAMS/_index.md
@@ -0,0 +1,19 @@
+---
+title: "Fitting time-series GAMS in R"
+linkTitle: ""
+type: book
+weight: 18
+summary: " "
+show_date: false
+editable: true
+---
+
+{{% callout note %}}
+
+**Learning Objectives:**
+* First lesson objective
+* Second lesson objective
+
+{{% /callout %}}
+
+{{< list_children >}}
diff --git a/content/lessons/R-time-series-decomposition/r_tutorial.md b/content/lessons/R-time-series-decomposition/r_tutorial.md
@@ -57,12 +57,7 @@ editable: true
 
 ### Written version of the lesson. It will vary from the videos, but the core info is the same.
 ### You may find it helpful to watch the videos without "in R" in their title as these are more informative videos with visuals that are not  present in the written document.
----
-title: "Decomposition"
-author: "Morgan Ernest"
-date: "September 20, 2018"
-output: html_document
----
+
 ## Inherent scales within a time series
 
 

diff --git a/content/lessons/R-time-series-modeling/r_tutorial.md b/content/lessons/R-time-series-modeling/r_tutorial.md
@@ -63,12 +63,12 @@ Modify the max orders, if needed, and rerun the model.
 
 ## White noise model - Simplest Time series
 
-## Data setup
+### Data setup
 
 Let's start by getting our environment ready to go by loading our rpackage and data.
 
 We're going to be using the rpackage forecast today. Forecast is the package developed by Rob Hyndeman as an aid to learning basic forecasting techniques in R. It makes some of the modeling approaches more user friendly.
----
+
 ```{r}
 library(forecast)
 ```
@@ -91,7 +91,7 @@ whitenoise = ts(rnorm(273,0.18))
 ```
 Reminder: set.seed is fixing that random draw so we all have the same numbers. rnorm() pulls random draws from a normal distribution. And we've asked it to pull 273 observations from a normal distribution with mean 0.18
 
-## Fit the white noise model
+### Fit the white noise model
 Now let's fit this white noise model (the equation above) to our data. We'll use the meanf function from the forecast package. It fits a model where you have a mean and assumes data are independent and identifcally distributed  (so no time series structure)
 
 ```{r}
@@ -175,7 +175,7 @@ Let's see how this model performs relative to the white noise model we plotted b
 plot(NDVI.ts)
 lines(fitted(MA2), col='blue')
 ```
-SO, just with the information about correlated errors at short time intervals, we are able to generate a plot that doesn't look ridiculuously different from the observed data.
+SO, just with the information about correlated errors at short time intervals, we are able to generate a plot that doesn't look ridiculously different from the observed data.
 
 The next step whenever we fit any model is to check how its fitting our data. Are there signals in our residuals that indicate something is amiss. With a time series model, we're often looking to see if we left any autocorrelation unaccounted for. 
 
@@ -213,7 +213,7 @@ There are differences between this fit and the non-seasonal ARIMA we fit above,
 ```{r}
 summary(season_MA2)
 ```
-JUst like before, we see the model structure at the top, and the cofficient values that it fit to the data for that model structure. sMA refers to that seasonal MA component that we added to this model.
+JUst like before, we see the model structure at the top, and the coefficient values that it fit to the data for that model structure. sMA refers to that seasonal MA component that we added to this model.
 
 And, let's check the residuals:
 ```{r}

diff --git a/content/lessons/ask-us-anything/_index.md b/content/lessons/ask-us-anything/_index.md
@@ -0,0 +1,19 @@
+---
+title: "Ask us anything"
+linkTitle: ""
+type: book
+weight: 20
+summary: "Ask us anything you've been wondering about forecasting and we'll talk about it"
+show_date: false
+editable: true
+---
+
+{{% callout note %}}
+
+**Learning Objectives:**
+* First lesson objective
+* Second lesson objective
+
+{{% /callout %}}
+
+{{< list_children >}}
diff --git a/content/lessons/ask-us-anything/discussion_questions.md b/content/lessons/ask-us-anything/discussion_questions.md
@@ -0,0 +1,10 @@
+---
+title: "Discussion Questions"
+weight: 2
+type: book
+summary: " "
+show_date: false
+editable: true
+---
+
+Bring any questions related to the course that you've been wanting to ask we'll talk about them.
diff --git a/content/lessons/ask-us-anything/instructor_notes.md b/content/lessons/ask-us-anything/instructor_notes.md
@@ -0,0 +1,10 @@
+---
+title: "Instructor Notes"
+weight: 4
+type: book
+summary: " "
+show_date: false
+editable: true
+---
+
+This material generates a lot of questions from students so we recommend setting aside one or more days for students to either submit questions in advance, or just bring them to class, and you answer/discuss them.
diff --git a/content/lessons/course-wrap-up/_index.md b/content/lessons/course-wrap-up/_index.md
@@ -2,7 +2,7 @@
 title: "Wrap up: Can we (and what should we) forecast in ecology?"
 linkTitle: "Course wrap up"
 type: book
-weight: 27
+weight: 29
 summary: "Synthetic discussion of how to use forecasting in ecology given the strengths, weakness, and approaches we've learned." 
 show_date: false
 editable: true

diff --git a/content/lessons/course-wrap-up/material.md b/content/lessons/course-wrap-up/material.md
@@ -9,4 +9,4 @@ editable: true
 
 ## Reading
 
-[Prediction, precaution, and policy under global change](https://doi.org/10.1126/science.1261824)
+[Prediction, precaution, and policy under global change](https://landscapepartnership.org/maps-data/climate-context/cc-resources/ClimateSciPDFs/Science-2015-Schindler-953-4.pdf/app-download-file/file/Science-2015-Schindler-953-4.pdf)
diff --git a/content/lessons/data-driven-forecasts/_index.md b/content/lessons/data-driven-forecasts/_index.md
@@ -2,7 +2,7 @@
 title: "Data-driven models for forecasting"
 linkTitle: "Data-driven models"
 type: book
-weight: 23
+weight: 25
 summary: A discussion of data-driven models, how they compare to process models, and how they can be used for forecasting, with a focu on Empirical Dynamic Modeling
 show_date: false
 editable: true

diff --git a/content/lessons/election-forecasts/_index.md b/content/lessons/election-forecasts/_index.md
@@ -2,7 +2,7 @@
 title: "Election forecasts"
 linkTitle: "Election forecasts"
 type: book
-weight: 22
+weight: 24
 summary: Discussion of modelling approaches and data challenges in election forecasting
 show_date: false
 editable: true

diff --git a/content/lessons/election-forecasts/material.md b/content/lessons/election-forecasts/material.md
@@ -7,6 +7,6 @@ show_date: false
 editable: true
 ---
 
-* Reading:[A User's Guide to FiveThirtyEight's 2016 Election Forecast](https://fivethirtyeight.com/features/a-users-guide-to-fivethirtyeights-2016-general-election-forecast/)
-* Reading:[Another model to forecast the house elections? Meet Mr. P](https://www.thecrosstab.com/2018/04/20/mrp-house/)
+* Reading: [A User's Guide to FiveThirtyEight's 2016 Election Forecast](https://fivethirtyeight.com/features/a-users-guide-to-fivethirtyeights-2016-general-election-forecast/)
+* Reading: [Another model to forecast the house elections? Meet Mr. P]()
 
diff --git a/content/lessons/ethics/_index.md b/content/lessons/ethics/_index.md
@@ -2,7 +2,7 @@
 title: "Ethics of Ecological Forecasting"
 linkTitle: "Forecasting Ethics"
 type: book
-weight: 26
+weight: 28
 summary: Discussion focused on ethical issues that can arise when we make predictions about the future
 show_date: false
 editable: true

diff --git a/content/lessons/hurricane-forecasts/_index.md b/content/lessons/hurricane-forecasts/_index.md
@@ -2,7 +2,7 @@
 title: "Hurricane Forecasts"
 linkTitle: "Hurricane Forecasts"
 type: book
-weight: 21
+weight: 23
 summary: Learn how the field of hurricane forecasting approaches data and model challenges
 show_date: false
 editable: true

diff --git a/content/lessons/hurricane-forecasts/instructor_notes.md b/content/lessons/hurricane-forecasts/instructor_notes.md
@@ -49,5 +49,3 @@ Finding a good and - most improtantly - accessible reading to introduce ecology
 
 > Do you think numerical weather prediction is a good model for ecological forecasting? What issues would we have in applying this approach? Can we overcome them?
   * Instructor note: push the students to think about applying something like this to their systems. What types of 'fundamental equations' would they need? What type of data? How intensively collected? How close are we to being able to do this in ecology?
-
-•
diff --git a/content/lessons/intro-to-forecasting/material.md b/content/lessons/intro-to-forecasting/material.md
@@ -13,5 +13,5 @@ editable: true
 
 ## Readings
 
-* [Ecological forecasting and data assimilation in a data‐rich era](https://pdfs.semanticscholar.org/9ddf/dd71c64715c6c474ac04f6505f3eb95d3e8b.pdf). **Only read through the end of the "Uses of Models for Ecological Forecasting" section.** We are reading the begining this paper because it provides a good background in ecological forecasting.
-* [Forecasting Principles & Process Chapter 1](https://www.otexts.org/fpp/1). **Skip section 1.5 on case studies.**
+* [Ecological forecasting and data assimilation in a data‐rich era](https://esajournals.onlinelibrary.wiley.com/doi/full/10.1890/09-1275.1). **Only read through the end of the "Uses of Models for Ecological Forecasting" section.** We are reading the beginning this paper because it provides a good background in ecological forecasting.
+* [Forecasting Principles & Process Chapter 1](https://otexts.com/fpp3/intro.html). **Skip section 1.5 on case studies. Watching videos is optional**
diff --git a/content/lessons/intro-to-gams/_index.md b/content/lessons/intro-to-gams/_index.md
@@ -0,0 +1,19 @@
+---
+title: "Introduction to Generalized Additive Models (GAMs)"
+linkTitle: "Intro to GAMS"
+type: book
+weight: 17
+summary: "An introduction to generalized additive models and how then can be used with time-series"
+show_date: false
+editable: true
+---
+
+{{% callout note %}}
+
+**Learning Objectives:**
+* First lesson objective
+* Second lesson objective
+
+{{% /callout %}}
+
+{{< list_children >}}
diff --git a/content/lessons/scenarios/_index.md b/content/lessons/scenarios/_index.md
@@ -2,7 +2,7 @@
 title: "Scenario based forecasting"
 linkTitle: "Forecasting scenarios"
 type: book
-weight: 25
+weight: 27
 summary: Discussion of scenario based approaches to forecasting, which explore general classes of future outcomes to facilitate decision making.
 show_date: false
 editable: true

diff --git a/content/lessons/scenarios/material.md b/content/lessons/scenarios/material.md
@@ -9,4 +9,4 @@ editable: true
 
 ## Reading
 
-[Why global scenarios need ecology](https://pdfs.semanticscholar.org/9c80/a836268cda3be37dce4b6c381601b5e1ce9e.pdf)
+[Why global scenarios need ecology](https://d1wqtxts1xzle7.cloudfront.net/43697691/Why_global_scenarios_need_ecology20160313-1679-1sayw8s-libre.pdf?1457918888=&response-content-disposition=inline%3B+filename%3DWhy_global_scenarios_need_ecology.pdf&Expires=1692630235&Signature=Bw3SbMDUGVEOnhJk1pdkUWXe6IlyNnMvMPTZASllRPaMjNu51X85gBEnTamr-I2e1GIJCxQ8eCFaATUEmBX9LyLqk27fN4RgkvsdBcdjyAP3vv9TFQT~WQpjAUcC3K9DsNpBqOhxMLKtWXD4o~oNqNtPOTbjoluttW7kyRjjPQImafRbGXNdZATKA4-c4ZKhXATf9GUBnW-jccez3tCiEB7zCIKqBRSg~IseT~VPSi8xHQwA7YJRvB9HTtsA~dvIojScly8RolCdgPjyjhD35MLA1MXyRz5hi7-aYRzd55SVi4DB44i3DwFlel8ePTWXAYwjCboz1c4zO2ZIEp6p8A__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA)
diff --git a/content/lessons/species-distribution-models/_index.md b/content/lessons/species-distribution-models/_index.md
@@ -2,7 +2,7 @@
 title: "Forecasting using species distribution models"
 linkTitle: "Species Distribution Models"
 type: book
-weight: 17
+weight: 21
 summary: How forecasts are made from species distribution modelings and the challenges associated with these forecasts
 show_date: false
 editable: true

diff --git a/content/lessons/species-distribution-models/material.md b/content/lessons/species-distribution-models/material.md
@@ -9,4 +9,4 @@ editable: true
 
 ## Reading
 
-[Species Distribution Models:Ecological Explanation and Prediction Across Space and Time](http://eurobasin.dtuaqua.dk/eurobasin/documents/Training%20ISM/Elith_and_Leathwick_2009.pdf)
+[Species Distribution Models: Ecological Explanation and Prediction Across Space and Time](https://web.archive.org/web/20170809005318id_/http://sysnevo.thu.edu.tw/lib/courses_lib_file/phylogeography_file/elith_leathwick_2009.pdf)