minor corrections and updates to the paper

Author: RonaldVisser

paper/paper.Rmd

@@ -39,9 +39,9 @@ Dendrochronological analyses are often based on the comparison of tree-ring seri
 
 # Statement of need
 
-There are several packages available in R for dendrochronological research [@guiterman2020; @jevsenak2018; @campelo2012; @bunn2008; @shi2019; @vandermaaten-theunissen2015; @reynolds2021; @altman2014; @malevich2018; @rademacher; @campelo2019; @haneca2023; @alday2018]. An overview with links to these packages can be found online (<https://ronaldvisser.github.io/Dendro_R/>). Some packages are specifically creates to obtain measurements [@campelo2019; @shi2019], while others are written for crossdating [@reynolds2021]. There are also various for analysing tree-ring data [@alday2018; @alday2018; @altman2014; @bunn2008; @campelo2012; @guiterman2020]. These R-packages in dendrochronology all fill different needs, but the nice thing is that these are all interconnected in some way in depending on each other, or that they build further into different avenues. Apart from depending on dendrochronological packages, various packages from the Tidyverse [@wickham2019] are often also needed. The various relations can easily be visualised using a network, with the edges based on the dependency of two packages on each other, and and arrow indicating the direction of the dependency.
+There are several packages available in R for dendrochronological research [@guiterman2020; @jevsenak2018; @campelo2012; @bunn2008; @shi2019; @vandermaaten-theunissen2015; @reynolds2021; @altman2014; @malevich2018; @rademacher; @campelo2019; @haneca2023; @alday2018]. An overview with links to these packages can be found online (<https://ronaldvisser.github.io/Dendro_R/>). Some packages are specifically creates to obtain measurements [@campelo2019; @shi2019], while others are written for crossdating [@reynolds2021]. There are also various for analysing tree-ring data [@alday2018; @alday2018; @altman2014; @bunn2008; @campelo2012; @zang2015; @guiterman2020]. These R-packages in dendrochronology all fill different needs, but the nice thing is that these are all interconnected in some way in depending on each other, or that they build further into different avenues. Apart from depending on dendrochronological packages, various packages from the Tidyverse [@wickham2019] are often also needed. The various relations can easily be visualised using a network, with the edges based on the dependency of two packages on each other, and and arrow indicating the direction of the dependency. Some R-package for dendrochronology or tree-ring studies have no relation with others, but fill specific needs [@peters2018; @lara2018; @campelo2016; @aryal2020]. These are left out of the network (see Figure \@ref(fig:packages-network)).
 
-```{r, out.width="50%", fig.cap = "The interdependent relations between existing R-packages related to dendrochronology", echo=FALSE}
+```{r, packages-network, out.width="50%", fig.cap = "The interdependent relations between existing R-packages related to dendrochronology", echo=FALSE}
 g_dendro_packages <- igraph::graph( c("dplR", "dfoliatR", "tidyverse", "dfoliatR",
                      "dplR", "dendroTools", "tidyverse", "dendroTools",
                      "dplR", "detrendeR", "tidyverse", "dplR",
@@ -51,25 +51,25 @@ g_dendro_packages <- igraph::graph( c("dplR", "dfoliatR", "tidyverse", "dfoliatR
                      "dplR", "pointRes", "tidyverse", "pointRes",
                      "dplR", "RingdateR", "tidyverse", "RingdateR",
                      "dplR", "wiad", "tidyverse", "wiad",
-                     "dplR", "TRADER", "dplR", "xRing", "detrendeR", "xRing", "tidyverse","dendroSync", "tidyverse", "burnr"))
+                     "dplR", "TRADER", "dplR", "xRing", "detrendeR", "xRing", "tidyverse","dendroSync", "tidyverse", "burnr", "tidyverse", "treeclim"))
 plot(g_dendro_packages, edge.arrow.size=.1, vertex.color="deepskyblue", 
      vertex.size=15, vertex.label.color="darkslategrey", vertex.label.family="sans", vertex.font.size=5,
      vertex.label.cex=0.8, vertex.label.dist=2, vertex.shape="sphere")
 ```
 
-The network shows that nearly all packages depend on dplR [@bunn2008]. The newly created package dendroNetwork fits in this ecosystem of depending packages, since it depends on both dplR and the Tidyverse. In addition, it adds a whole new world by adding network analyses through igraph [@csardi2006] to the ecosystem of dendrochronological packages. The igraph library has close connections to the tidyverse, creating a full circle and filling a gap as shown in the networks below.
+The network shows that nearly all packages depend on dplR [@bunn2008]. The newly created package dendroNetwork fits in this ecosystem of depending packages, since it depends on both dplR and the Tidyverse. In addition, it adds a whole new world by adding network analyses through igraph [@csardi2006] to the ecosystem of dendrochronological packages. The igraph library has close connections to the tidyverse, creating a full circle and filling a gap as shown in the networks below (see Figure \@ref(fig:dendroNetwork-packages)).
 
-```{r, fig.show="hold", out.width="50%", fig.cap = "The interdependent relations between R-packages including dendroNetwork. On the left only the dependencies for dendroNetwork, on the right all dendrochronological R-packages, including dendroNetwork", echo=FALSE}
+```{r, dendroNetwork-packages, fig.show="hold", out.width="50%", fig.cap = "The interdependent relations between R-packages including dendroNetwork. On the left only the dependencies for dendroNetwork, on the right all dendrochronological R-packages, including dendroNetwork", echo=FALSE}
 g_dendroNetwork <- igraph::graph( c("dplR", "dendroNetwork", "tidyverse", "dendroNetwork", "igraph", "dendroNetwork", "igraph", "tidyverse", "tidyverse", "igraph"))
 plot(g_dendroNetwork, edge.arrow.size=.5, vertex.color="deepskyblue", vertex.shape="sphere", vertex.size=15,vertex.label.family="sans", vertex.label.color="darkslategrey", vertex.label.cex=0.8, vertex.label.dist=2)
 plot(g_dendroNetwork+g_dendro_packages, edge.arrow.size=.5, vertex.color="deepskyblue", vertex.size=15, vertex.label.family="sans", vertex.label.color="darkslategrey", vertex.label.cex=0.8, vertex.shape="sphere", vertex.label.dist=2)
 ```
 
 # Workflow using dendroNetwork
 
-The typical workflow when using the package consists of a number of successive steps. The result of each step is input for the next step.
+The typical workflow when using the package consists of a number of successive steps (see Figure \@ref(fig:workflow)). The result of each step is input for the next step.
 
-```{r, echo=FALSE, fig.width=4, fig.cap = "The typcial workflow when using dendroNetwork to visualise a network" }
+```{r, workflow, echo=FALSE, fig.width=4, fig.cap = "The typcial workflow when using dendroNetwork to visualise a network" }
 DiagrammeR::grViz("
 digraph {
   # graph attributes
@@ -125,9 +125,9 @@ g_hol_cpm <- clique_community_names(g_hol, k=3)
 hol_com_cpm_all <- find_all_cpm_com(g_hol)
 ```
 
-The next step is to visualize and explore the networks using Cytoscape or using R. Various functions are available to create visual styles for the communities in Cytoscape from R.
+The next step is to visualize and explore the networks using Cytoscape or using R (see Figure \@ref(fig:network-holrom)). Various functions are available to create visual styles for the communities in Cytoscape from R.
 
-```{r, fig.cap = "Network of the dendrochronological site chronologies in hol_rom"}
+```{r, network-holrom, fig.cap = "Network of the dendrochronological site chronologies in hol_rom", echo=FALSE}
 plot(g_hol, vertex.color="deepskyblue", vertex.size=15, vertex.frame.color="gray",
      vertex.label.color="darkslategrey", vertex.label.cex=0.8, vertex.label.dist=2)
 ```
@@ -139,9 +139,9 @@ The main advantage is that visualisation in Cytoscape is more easy, intuitive an
 3.  To visualize the styles for CPM with only k=3: `cyto_create_cpm_style(g_hol, k=3, com_k = g_hol_cpm)`
     -   This can be repeated for all possible clique sizes. To find the maximum clique size in a network, please use: `igraph::clique_num(g_hol)`.
     -   To automate this: `for (i in 3:igraph::clique_num(g_hol)) { cyto_create_cpm_style(g_hol, k=i, com_k = g_hol_cpm)}`.
-4.  To visualize the styles using the Girvan-Newman algorithm (GN): `cyto_create_gn_style(g_hol)` This would look something like this in Cytoscape:
+4.  To visualize the styles using the Girvan-Newman algorithm (GN): `cyto_create_gn_style(g_hol)` This would look something like this in Cytoscape (see Figure \@ref(fig:cytoscape-network)).
 
-```{r, echo=FALSE, fig.cap="The network of Roman sitechronologies with the Girvan-Newman communities visualized using Cytoscape.", out.width = "100%"}
+```{r, cytoscape-network, echo=FALSE, fig.cap="The network of Roman sitechronologies with the Girvan-Newman communities visualized using Cytoscape.", out.width = "75%"}
 knitr::include_graphics("g_hol_GN.png")
 ```
 

paper/paper.bib

@@ -342,3 +342,73 @@ @article{malevich2018
 	doi = {10.1016/j.dendro.2018.02.005},
 	url = {http://www.sciencedirect.com/science/article/pii/S1125786517301418}
 }
+
+@article{zang2015,
+	title = {treeclim: an R package for the numerical calibration of proxy-climate relationships},
+	author = {Zang, Christian and Biondi, Franco},
+	year = {2015},
+	date = {2015},
+	journal = {Ecography},
+	pages = {431--436},
+	volume = {38},
+	number = {4},
+	doi = {10.1111/ecog.01335},
+	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/ecog.01335},
+	note = {{\_}eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/ecog.01335},
+	langid = {en}
+}
+
+@article{peters2018,
+	title = {RAPTOR: Row and position tracheid organizer in R},
+	author = {Peters, Richard L. and Balanzategui, Daniel and Hurley, Alexander G. and von Arx, Georg and Prendin, Angela Luisa and Cuny, Henri E. and {Björklund}, Jesper and Frank, David C. and Fonti, Patrick},
+	year = {2018},
+	month = {02},
+	date = {2018-02-01},
+	journal = {Dendrochronologia},
+	pages = {10--16},
+	volume = {47},
+	doi = {10.1016/j.dendro.2017.10.003},
+	url = {https://www.sciencedirect.com/science/article/pii/S1125786517301236}
+}
+
+@article{lara2018,
+	title = {Multilevel analysis of dendroclimatic series with the R-package BIOdry},
+	author = {Lara, Wilson and Bogino, Stella and Bravo, Felipe},
+	year = {2018},
+	month = {05},
+	date = {2018-05-17},
+	journal = {PLOS ONE},
+	pages = {e0196923},
+	volume = {13},
+	number = {5},
+	doi = {10.1371/journal.pone.0196923},
+	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0196923},
+	note = {Publisher: Public Library of Science},
+	langid = {en}
+}
+
+@article{campelo2016,
+	title = {tracheideR{\textemdash}An R package to standardize tracheidograms},
+	author = {Campelo, Filipe and Nabais, Cristina and Carvalho, Ana and Vieira, Joana},
+	year = {2016},
+	month = {03},
+	date = {2016-03-01},
+	journal = {Dendrochronologia},
+	pages = {64--68},
+	volume = {37},
+	doi = {10.1016/j.dendro.2015.12.006},
+	url = {https://www.sciencedirect.com/science/article/pii/S1125786515000934}
+}
+
+@article{aryal2020,
+	title = {{\textquotedblleft}dendRoAnalyst{\textquotedblright}: A tool for processing and analysing dendrometer data},
+	author = {Aryal, Sugam and {Häusser}, Martin and {Grießinger}, Jussi and Fan, Zexin and {Bräuning}, Achim},
+	year = {2020},
+	month = {12},
+	date = {2020-12-01},
+	journal = {Dendrochronologia},
+	pages = {125772},
+	volume = {64},
+	doi = {10.1016/j.dendro.2020.125772},
+	url = {https://www.sciencedirect.com/science/article/pii/S1125786520301119}
+}