From 0f2453786e63842b59475f781f5f09f19a1f40f1 Mon Sep 17 00:00:00 2001 From: Quarto GHA Workflow Runner Date: Tue, 21 Jan 2025 11:53:00 +0000 Subject: [PATCH] Built site for gh-pages --- .nojekyll | 2 +- plot_trait_evolution.html | 4 ++-- search.json | 4 ++-- sitemap.xml | 18 +++++++++--------- 4 files changed, 14 insertions(+), 14 deletions(-) diff --git a/.nojekyll b/.nojekyll index 64005ac..1d97d81 100644 --- a/.nojekyll +++ b/.nojekyll @@ -1 +1 @@ -489bf14f \ No newline at end of file +ba427688 \ No newline at end of file diff --git a/plot_trait_evolution.html b/plot_trait_evolution.html index 1a5327b..7815947 100644 --- a/plot_trait_evolution.html +++ b/plot_trait_evolution.html @@ -321,7 +321,7 @@

Plot trait ggplotly(p)
- +


@@ -366,7 +366,7 @@

Session Info

collate C.UTF-8 ctype C.UTF-8 tz UTC - date 2025-01-20 + date 2025-01-21 pandoc 3.1.3 @ /usr/bin/ (via rmarkdown) ─ Packages ─────────────────────────────────────────────────────────────────── diff --git a/search.json b/search.json index 0f198c9..cba665c 100644 --- a/search.json +++ b/search.json @@ -96,14 +96,14 @@ "href": "plot_trait_evolution.html", "title": "Evolutionary lottery of skull and beak morphology", "section": "", - "text": "Beak and skull shapes in birds of prey (“raptors”) are strongly coupled and largely controlled by size.\n\ngif provided by the awesome Jen Bright @MorphobeakGeek!\n\nIn this exercise we will use a github repo to collaboratively collate and simulate evolutionary trajectories for each participants’ species body size using a simple brownian motion evolutionary model. This assumes evolutionary steps to progress comletely at random. You could say:\n\n\n\nEach participant has created and contributed a file specifying the parameters required to simulate and plot their species evolutionary trajectory. We’ve collect all participants’ files in the master repo. Next we need to simulate species trajectories plot them up.\nParticipants will then get to see the skull and beak shape corresponding to their species relative body size!\n\n\n\n\nFirst we load the required packages and create some objects to compile data on trait evolution for each species.\n\nlibrary(dplyr)\nlibrary(ggplot2) #3.5.1\nlibrary(plotly) #4.10.4\nset.seed(1)\n\nt <- 0:100 # generate time vector\ndt <- NULL # generate object to compile time-series data\ncols <- NULL # generate object to compile trendline colours\n\n\n\n\n\nWe’ll use the parameters supplied in your scripts to generate brownian trait evolution trendline for each species.\n\n#getting the file names for everything except the template that has undefined values\nspp.files <- dir(\"params/\")[dir(\"params/\") != \"params_tmpl.R\"]\n\nfor(spp in spp.files){\n # source parameters for each species\n source(file.path(\"params\", spp))\n \n # generate trait evolution time-series and compile plotting data\n dt <- rbind(dt, data.frame(t, \n trait = c(0, rnorm(n = length(t) - 1, sd = sqrt(sig2)) |> cumsum()),\n species = species.name))\n cols <- c(cols, color)\n}\n\n\n\n\nUse the data generated to plot all species.\n\n# Specify the order of species based on the order of colors in cols to stop a mismatch in colours\ndt$species <- factor(dt$species, levels = unique(dt$species))\n\n# Create the ggplot object\np <- ggplot(data = dt, aes(x = t, y = trait, group = species, colour = species)) + \n geom_line() + \n scale_colour_manual(values = cols) \n\n# Plot the results\nggplotly(p)\n\n\n\n\n\n\n\n\n\n\n\nSkulls are organised from largest to smallest. The largest skulls are vulture-like, (e.g. no. 50, the Andean condor Vultur gryphus) and the smallest are falconet-like, (e.g. no. 1 Collared falconet Microhierax caerulescens)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nsessioninfo::session_info()\n\n─ Session info ───────────────────────────────────────────────────────────────\n setting value\n version R version 4.4.0 (2024-04-24)\n os Ubuntu 24.04.1 LTS\n system x86_64, linux-gnu\n ui X11\n language (EN)\n collate C.UTF-8\n ctype C.UTF-8\n tz UTC\n date 2025-01-20\n pandoc 3.1.3 @ /usr/bin/ (via rmarkdown)\n\n─ Packages ───────────────────────────────────────────────────────────────────\n package * version date (UTC) lib source\n cli 3.6.3 2024-06-21 [1] CRAN (R 4.4.0)\n colorspace 2.1-1 2024-07-26 [1] CRAN (R 4.4.0)\n crosstalk 1.2.1 2023-11-23 [1] CRAN (R 4.4.0)\n data.table 1.16.4 2024-12-06 [1] CRAN (R 4.4.0)\n digest 0.6.37 2024-08-19 [1] CRAN (R 4.4.0)\n dplyr * 1.1.4 2023-11-17 [1] any (@1.1.4)\n evaluate 1.0.3 2025-01-10 [1] CRAN (R 4.4.0)\n fastmap 1.2.0 2024-05-15 [1] CRAN (R 4.4.0)\n generics 0.1.3 2022-07-05 [1] CRAN (R 4.4.0)\n ggplot2 * 3.5.1 2024-04-23 [1] CRAN (R 4.4.0)\n glue 1.8.0 2024-09-30 [1] CRAN (R 4.4.0)\n gtable 0.3.6 2024-10-25 [1] CRAN (R 4.4.0)\n htmltools 0.5.8.1 2024-04-04 [1] CRAN (R 4.4.0)\n htmlwidgets 1.6.4 2023-12-06 [1] CRAN (R 4.4.0)\n httr 1.4.7 2023-08-15 [1] CRAN (R 4.4.0)\n jsonlite 1.8.9 2024-09-20 [1] CRAN (R 4.4.0)\n knitr 1.49 2024-11-08 [1] CRAN (R 4.4.0)\n labeling 0.4.3 2023-08-29 [1] CRAN (R 4.4.0)\n lazyeval 0.2.2 2019-03-15 [1] CRAN (R 4.4.0)\n lifecycle 1.0.4 2023-11-07 [1] CRAN (R 4.4.0)\n magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.4.0)\n munsell 0.5.1 2024-04-01 [1] CRAN (R 4.4.0)\n pillar 1.10.1 2025-01-07 [1] CRAN (R 4.4.0)\n pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.4.0)\n plotly * 4.10.4 2024-01-13 [1] CRAN (R 4.4.0)\n purrr 1.0.2 2023-08-10 [1] CRAN (R 4.4.0)\n R6 2.5.1 2021-08-19 [1] CRAN (R 4.4.0)\n rlang 1.1.5 2025-01-17 [1] CRAN (R 4.4.0)\n rmarkdown 2.29 2024-11-04 [1] CRAN (R 4.4.0)\n scales 1.3.0 2023-11-28 [1] CRAN (R 4.4.0)\n sessioninfo 1.2.2 2021-12-06 [1] any (@1.2.2)\n tibble 3.2.1 2023-03-20 [1] CRAN (R 4.4.0)\n tidyr 1.3.1 2024-01-24 [1] CRAN (R 4.4.0)\n tidyselect 1.2.1 2024-03-11 [1] CRAN (R 4.4.0)\n vctrs 0.6.5 2023-12-01 [1] CRAN (R 4.4.0)\n viridisLite 0.4.2 2023-05-02 [1] CRAN (R 4.4.0)\n withr 3.0.2 2024-10-28 [1] CRAN (R 4.4.0)\n xfun 0.50 2025-01-07 [1] CRAN (R 4.4.0)\n yaml 2.3.10 2024-07-26 [1] CRAN (R 4.4.0)\n\n [1] /home/runner/work/_temp/Library\n [2] /opt/R/4.4.0/lib/R/site-library\n [3] /opt/R/4.4.0/lib/R/library\n\n──────────────────────────────────────────────────────────────────────────────" + "text": "Beak and skull shapes in birds of prey (“raptors”) are strongly coupled and largely controlled by size.\n\ngif provided by the awesome Jen Bright @MorphobeakGeek!\n\nIn this exercise we will use a github repo to collaboratively collate and simulate evolutionary trajectories for each participants’ species body size using a simple brownian motion evolutionary model. This assumes evolutionary steps to progress comletely at random. You could say:\n\n\n\nEach participant has created and contributed a file specifying the parameters required to simulate and plot their species evolutionary trajectory. We’ve collect all participants’ files in the master repo. Next we need to simulate species trajectories plot them up.\nParticipants will then get to see the skull and beak shape corresponding to their species relative body size!\n\n\n\n\nFirst we load the required packages and create some objects to compile data on trait evolution for each species.\n\nlibrary(dplyr)\nlibrary(ggplot2) #3.5.1\nlibrary(plotly) #4.10.4\nset.seed(1)\n\nt <- 0:100 # generate time vector\ndt <- NULL # generate object to compile time-series data\ncols <- NULL # generate object to compile trendline colours\n\n\n\n\n\nWe’ll use the parameters supplied in your scripts to generate brownian trait evolution trendline for each species.\n\n#getting the file names for everything except the template that has undefined values\nspp.files <- dir(\"params/\")[dir(\"params/\") != \"params_tmpl.R\"]\n\nfor(spp in spp.files){\n # source parameters for each species\n source(file.path(\"params\", spp))\n \n # generate trait evolution time-series and compile plotting data\n dt <- rbind(dt, data.frame(t, \n trait = c(0, rnorm(n = length(t) - 1, sd = sqrt(sig2)) |> cumsum()),\n species = species.name))\n cols <- c(cols, color)\n}\n\n\n\n\nUse the data generated to plot all species.\n\n# Specify the order of species based on the order of colors in cols to stop a mismatch in colours\ndt$species <- factor(dt$species, levels = unique(dt$species))\n\n# Create the ggplot object\np <- ggplot(data = dt, aes(x = t, y = trait, group = species, colour = species)) + \n geom_line() + \n scale_colour_manual(values = cols) \n\n# Plot the results\nggplotly(p)\n\n\n\n\n\n\n\n\n\n\n\nSkulls are organised from largest to smallest. The largest skulls are vulture-like, (e.g. no. 50, the Andean condor Vultur gryphus) and the smallest are falconet-like, (e.g. no. 1 Collared falconet Microhierax caerulescens)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nsessioninfo::session_info()\n\n─ Session info ───────────────────────────────────────────────────────────────\n setting value\n version R version 4.4.0 (2024-04-24)\n os Ubuntu 24.04.1 LTS\n system x86_64, linux-gnu\n ui X11\n language (EN)\n collate C.UTF-8\n ctype C.UTF-8\n tz UTC\n date 2025-01-21\n pandoc 3.1.3 @ /usr/bin/ (via rmarkdown)\n\n─ Packages ───────────────────────────────────────────────────────────────────\n package * version date (UTC) lib source\n cli 3.6.3 2024-06-21 [1] CRAN (R 4.4.0)\n colorspace 2.1-1 2024-07-26 [1] CRAN (R 4.4.0)\n crosstalk 1.2.1 2023-11-23 [1] CRAN (R 4.4.0)\n data.table 1.16.4 2024-12-06 [1] CRAN (R 4.4.0)\n digest 0.6.37 2024-08-19 [1] CRAN (R 4.4.0)\n dplyr * 1.1.4 2023-11-17 [1] any (@1.1.4)\n evaluate 1.0.3 2025-01-10 [1] CRAN (R 4.4.0)\n fastmap 1.2.0 2024-05-15 [1] CRAN (R 4.4.0)\n generics 0.1.3 2022-07-05 [1] CRAN (R 4.4.0)\n ggplot2 * 3.5.1 2024-04-23 [1] CRAN (R 4.4.0)\n glue 1.8.0 2024-09-30 [1] CRAN (R 4.4.0)\n gtable 0.3.6 2024-10-25 [1] CRAN (R 4.4.0)\n htmltools 0.5.8.1 2024-04-04 [1] CRAN (R 4.4.0)\n htmlwidgets 1.6.4 2023-12-06 [1] CRAN (R 4.4.0)\n httr 1.4.7 2023-08-15 [1] CRAN (R 4.4.0)\n jsonlite 1.8.9 2024-09-20 [1] CRAN (R 4.4.0)\n knitr 1.49 2024-11-08 [1] CRAN (R 4.4.0)\n labeling 0.4.3 2023-08-29 [1] CRAN (R 4.4.0)\n lazyeval 0.2.2 2019-03-15 [1] CRAN (R 4.4.0)\n lifecycle 1.0.4 2023-11-07 [1] CRAN (R 4.4.0)\n magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.4.0)\n munsell 0.5.1 2024-04-01 [1] CRAN (R 4.4.0)\n pillar 1.10.1 2025-01-07 [1] CRAN (R 4.4.0)\n pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.4.0)\n plotly * 4.10.4 2024-01-13 [1] CRAN (R 4.4.0)\n purrr 1.0.2 2023-08-10 [1] CRAN (R 4.4.0)\n R6 2.5.1 2021-08-19 [1] CRAN (R 4.4.0)\n rlang 1.1.5 2025-01-17 [1] CRAN (R 4.4.0)\n rmarkdown 2.29 2024-11-04 [1] CRAN (R 4.4.0)\n scales 1.3.0 2023-11-28 [1] CRAN (R 4.4.0)\n sessioninfo 1.2.2 2021-12-06 [1] any (@1.2.2)\n tibble 3.2.1 2023-03-20 [1] CRAN (R 4.4.0)\n tidyr 1.3.1 2024-01-24 [1] CRAN (R 4.4.0)\n tidyselect 1.2.1 2024-03-11 [1] CRAN (R 4.4.0)\n vctrs 0.6.5 2023-12-01 [1] CRAN (R 4.4.0)\n viridisLite 0.4.2 2023-05-02 [1] CRAN (R 4.4.0)\n withr 3.0.2 2024-10-28 [1] CRAN (R 4.4.0)\n xfun 0.50 2025-01-07 [1] CRAN (R 4.4.0)\n yaml 2.3.10 2024-07-26 [1] CRAN (R 4.4.0)\n\n [1] /home/runner/work/_temp/Library\n [2] /opt/R/4.4.0/lib/R/site-library\n [3] /opt/R/4.4.0/lib/R/library\n\n──────────────────────────────────────────────────────────────────────────────" }, { "objectID": "plot_trait_evolution.html#skulls-find-the-skull-associated-with-your-species", "href": "plot_trait_evolution.html#skulls-find-the-skull-associated-with-your-species", "title": "Evolutionary lottery of skull and beak morphology", "section": "", - "text": "Skulls are organised from largest to smallest. The largest skulls are vulture-like, (e.g. no. 50, the Andean condor Vultur gryphus) and the smallest are falconet-like, (e.g. no. 1 Collared falconet Microhierax caerulescens)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nsessioninfo::session_info()\n\n─ Session info ───────────────────────────────────────────────────────────────\n setting value\n version R version 4.4.0 (2024-04-24)\n os Ubuntu 24.04.1 LTS\n system x86_64, linux-gnu\n ui X11\n language (EN)\n collate C.UTF-8\n ctype C.UTF-8\n tz UTC\n date 2025-01-20\n pandoc 3.1.3 @ /usr/bin/ (via rmarkdown)\n\n─ Packages ───────────────────────────────────────────────────────────────────\n package * version date (UTC) lib source\n cli 3.6.3 2024-06-21 [1] CRAN (R 4.4.0)\n colorspace 2.1-1 2024-07-26 [1] CRAN (R 4.4.0)\n crosstalk 1.2.1 2023-11-23 [1] CRAN (R 4.4.0)\n data.table 1.16.4 2024-12-06 [1] CRAN (R 4.4.0)\n digest 0.6.37 2024-08-19 [1] CRAN (R 4.4.0)\n dplyr * 1.1.4 2023-11-17 [1] any (@1.1.4)\n evaluate 1.0.3 2025-01-10 [1] CRAN (R 4.4.0)\n fastmap 1.2.0 2024-05-15 [1] CRAN (R 4.4.0)\n generics 0.1.3 2022-07-05 [1] CRAN (R 4.4.0)\n ggplot2 * 3.5.1 2024-04-23 [1] CRAN (R 4.4.0)\n glue 1.8.0 2024-09-30 [1] CRAN (R 4.4.0)\n gtable 0.3.6 2024-10-25 [1] CRAN (R 4.4.0)\n htmltools 0.5.8.1 2024-04-04 [1] CRAN (R 4.4.0)\n htmlwidgets 1.6.4 2023-12-06 [1] CRAN (R 4.4.0)\n httr 1.4.7 2023-08-15 [1] CRAN (R 4.4.0)\n jsonlite 1.8.9 2024-09-20 [1] CRAN (R 4.4.0)\n knitr 1.49 2024-11-08 [1] CRAN (R 4.4.0)\n labeling 0.4.3 2023-08-29 [1] CRAN (R 4.4.0)\n lazyeval 0.2.2 2019-03-15 [1] CRAN (R 4.4.0)\n lifecycle 1.0.4 2023-11-07 [1] CRAN (R 4.4.0)\n magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.4.0)\n munsell 0.5.1 2024-04-01 [1] CRAN (R 4.4.0)\n pillar 1.10.1 2025-01-07 [1] CRAN (R 4.4.0)\n pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.4.0)\n plotly * 4.10.4 2024-01-13 [1] CRAN (R 4.4.0)\n purrr 1.0.2 2023-08-10 [1] CRAN (R 4.4.0)\n R6 2.5.1 2021-08-19 [1] CRAN (R 4.4.0)\n rlang 1.1.5 2025-01-17 [1] CRAN (R 4.4.0)\n rmarkdown 2.29 2024-11-04 [1] CRAN (R 4.4.0)\n scales 1.3.0 2023-11-28 [1] CRAN (R 4.4.0)\n sessioninfo 1.2.2 2021-12-06 [1] any (@1.2.2)\n tibble 3.2.1 2023-03-20 [1] CRAN (R 4.4.0)\n tidyr 1.3.1 2024-01-24 [1] CRAN (R 4.4.0)\n tidyselect 1.2.1 2024-03-11 [1] CRAN (R 4.4.0)\n vctrs 0.6.5 2023-12-01 [1] CRAN (R 4.4.0)\n viridisLite 0.4.2 2023-05-02 [1] CRAN (R 4.4.0)\n withr 3.0.2 2024-10-28 [1] CRAN (R 4.4.0)\n xfun 0.50 2025-01-07 [1] CRAN (R 4.4.0)\n yaml 2.3.10 2024-07-26 [1] CRAN (R 4.4.0)\n\n [1] /home/runner/work/_temp/Library\n [2] /opt/R/4.4.0/lib/R/site-library\n [3] /opt/R/4.4.0/lib/R/library\n\n──────────────────────────────────────────────────────────────────────────────" + "text": "Skulls are organised from largest to smallest. The largest skulls are vulture-like, (e.g. no. 50, the Andean condor Vultur gryphus) and the smallest are falconet-like, (e.g. no. 1 Collared falconet Microhierax caerulescens)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nsessioninfo::session_info()\n\n─ Session info ───────────────────────────────────────────────────────────────\n setting value\n version R version 4.4.0 (2024-04-24)\n os Ubuntu 24.04.1 LTS\n system x86_64, linux-gnu\n ui X11\n language (EN)\n collate C.UTF-8\n ctype C.UTF-8\n tz UTC\n date 2025-01-21\n pandoc 3.1.3 @ /usr/bin/ (via rmarkdown)\n\n─ Packages ───────────────────────────────────────────────────────────────────\n package * version date (UTC) lib source\n cli 3.6.3 2024-06-21 [1] CRAN (R 4.4.0)\n colorspace 2.1-1 2024-07-26 [1] CRAN (R 4.4.0)\n crosstalk 1.2.1 2023-11-23 [1] CRAN (R 4.4.0)\n data.table 1.16.4 2024-12-06 [1] CRAN (R 4.4.0)\n digest 0.6.37 2024-08-19 [1] CRAN (R 4.4.0)\n dplyr * 1.1.4 2023-11-17 [1] any (@1.1.4)\n evaluate 1.0.3 2025-01-10 [1] CRAN (R 4.4.0)\n fastmap 1.2.0 2024-05-15 [1] CRAN (R 4.4.0)\n generics 0.1.3 2022-07-05 [1] CRAN (R 4.4.0)\n ggplot2 * 3.5.1 2024-04-23 [1] CRAN (R 4.4.0)\n glue 1.8.0 2024-09-30 [1] CRAN (R 4.4.0)\n gtable 0.3.6 2024-10-25 [1] CRAN (R 4.4.0)\n htmltools 0.5.8.1 2024-04-04 [1] CRAN (R 4.4.0)\n htmlwidgets 1.6.4 2023-12-06 [1] CRAN (R 4.4.0)\n httr 1.4.7 2023-08-15 [1] CRAN (R 4.4.0)\n jsonlite 1.8.9 2024-09-20 [1] CRAN (R 4.4.0)\n knitr 1.49 2024-11-08 [1] CRAN (R 4.4.0)\n labeling 0.4.3 2023-08-29 [1] CRAN (R 4.4.0)\n lazyeval 0.2.2 2019-03-15 [1] CRAN (R 4.4.0)\n lifecycle 1.0.4 2023-11-07 [1] CRAN (R 4.4.0)\n magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.4.0)\n munsell 0.5.1 2024-04-01 [1] CRAN (R 4.4.0)\n pillar 1.10.1 2025-01-07 [1] CRAN (R 4.4.0)\n pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.4.0)\n plotly * 4.10.4 2024-01-13 [1] CRAN (R 4.4.0)\n purrr 1.0.2 2023-08-10 [1] CRAN (R 4.4.0)\n R6 2.5.1 2021-08-19 [1] CRAN (R 4.4.0)\n rlang 1.1.5 2025-01-17 [1] CRAN (R 4.4.0)\n rmarkdown 2.29 2024-11-04 [1] CRAN (R 4.4.0)\n scales 1.3.0 2023-11-28 [1] CRAN (R 4.4.0)\n sessioninfo 1.2.2 2021-12-06 [1] any (@1.2.2)\n tibble 3.2.1 2023-03-20 [1] CRAN (R 4.4.0)\n tidyr 1.3.1 2024-01-24 [1] CRAN (R 4.4.0)\n tidyselect 1.2.1 2024-03-11 [1] CRAN (R 4.4.0)\n vctrs 0.6.5 2023-12-01 [1] CRAN (R 4.4.0)\n viridisLite 0.4.2 2023-05-02 [1] CRAN (R 4.4.0)\n withr 3.0.2 2024-10-28 [1] CRAN (R 4.4.0)\n xfun 0.50 2025-01-07 [1] CRAN (R 4.4.0)\n yaml 2.3.10 2024-07-26 [1] CRAN (R 4.4.0)\n\n [1] /home/runner/work/_temp/Library\n [2] /opt/R/4.4.0/lib/R/site-library\n [3] /opt/R/4.4.0/lib/R/library\n\n──────────────────────────────────────────────────────────────────────────────" }, { "objectID": "clone.html", diff --git a/sitemap.xml b/sitemap.xml index f6c7fce..ce44e4a 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -2,38 +2,38 @@ https://lmu-osc.github.io/Collaborative-RStudio-GitHub/fork.html - 2025-01-20T08:07:28.126Z + 2025-01-21T11:50:33.427Z https://lmu-osc.github.io/Collaborative-RStudio-GitHub/pull-request.html - 2025-01-20T08:07:28.135Z + 2025-01-21T11:50:33.436Z https://lmu-osc.github.io/Collaborative-RStudio-GitHub/merge.html - 2025-01-20T08:07:28.135Z + 2025-01-21T11:50:33.436Z https://lmu-osc.github.io/Collaborative-RStudio-GitHub/pull-upstream.html - 2025-01-20T08:07:28.135Z + 2025-01-21T11:50:33.436Z https://lmu-osc.github.io/Collaborative-RStudio-GitHub/index.html - 2025-01-20T08:07:28.134Z + 2025-01-21T11:50:33.436Z https://lmu-osc.github.io/Collaborative-RStudio-GitHub/plot_trait_evolution.html - 2025-01-20T08:07:28.135Z + 2025-01-21T11:50:33.436Z https://lmu-osc.github.io/Collaborative-RStudio-GitHub/clone.html - 2025-01-20T08:07:28.126Z + 2025-01-21T11:50:33.427Z https://lmu-osc.github.io/Collaborative-RStudio-GitHub/commit.html - 2025-01-20T08:07:28.126Z + 2025-01-21T11:50:33.427Z https://lmu-osc.github.io/Collaborative-RStudio-GitHub/push.html - 2025-01-20T08:07:28.135Z + 2025-01-21T11:50:33.436Z