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fixed simd stacked bar plot

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knit_it.sh
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@ -1,2 +1 @@
Rscript -e 'library(rmarkdown); rmarkdown::render("./mapping_draft.Rmd", "html_document")' Rscript -e 'library(rmarkdown); rmarkdown::render("./mapping_draft.Rmd", "html_document")'
Rscript -e 'library(rmarkdown); rmarkdown::render("./mapping_draft.Rmd", "pdf_document")'

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mapping_draft.Rmd
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@ -8,7 +8,7 @@ affiliation: University of Birmingham
institute: University of Birmingham institute: University of Birmingham
e-mail: "[j.kidwell@bham.ac.uk](mailto:j.kidwell@bham.ac.uk)" e-mail: "[j.kidwell@bham.ac.uk](mailto:j.kidwell@bham.ac.uk)"
date: "`r Sys.Date()`" date: "`r Sys.Date()`"
bibliography: ~/Dropbox/bibtex/everything.bib bibliography: biblio.bib
linkcolor: black linkcolor: black
geometry: margin=1in geometry: margin=1in
# fontfamily: mathpazo # fontfamily: mathpazo
@ -324,6 +324,7 @@ admin_lev1_fortified <- join(admin_lev1_fortified,admin_lev1@data, by="id")
# TODO: fix issues with cut_interval / cut_number below. Current error: "'breaks' are not unique calls" # TODO: fix issues with cut_interval / cut_number below. Current error: "'breaks' are not unique calls"
# See here: https://stackoverflow.com/questions/16184947/cut-error-breaks-are-not-unique # See here: https://stackoverflow.com/questions/16184947/cut-error-breaks-are-not-unique
# Reference here: https://ggplot2.tidyverse.org/reference/cut_interval.html # Reference here: https://ggplot2.tidyverse.org/reference/cut_interval.html
# Reference re: size and scale for plots: http://sape.inf.usi.ch/quick-reference/ggplot2/size
ggplot() + ggplot() +
geom_polygon(aes(x = long, y = lat, group = group, geom_polygon(aes(x = long, y = lat, group = group,
@ -331,7 +332,7 @@ ggplot() +
data = admin_lev1_fortified, data = admin_lev1_fortified,
colour = 'black', colour = 'black',
alpha = .7, alpha = .7,
size = .3) + size = .005) +
viridis::scale_fill_viridis(discrete = TRUE) + viridis::scale_fill_viridis(discrete = TRUE) +
labs(x = NULL, y = NULL, fill = "Groups", labs(x = NULL, y = NULL, fill = "Groups",
title = "Figure 1", title = "Figure 1",
@ -340,13 +341,14 @@ ggplot() +
"Data: UK Data Service (OGL) & Jeremy H. Kidwell", "Data: UK Data Service (OGL) & Jeremy H. Kidwell",
"You may redistribute this graphic under the terms of the CC-by-SA 4.0 license.", "You may redistribute this graphic under the terms of the CC-by-SA 4.0 license.",
sep = "\n")) + sep = "\n")) +
guides(colour = guide_legend(reverse=T)) +
theme_void() + theme_void() +
theme(text = element_text(family = "Arial Narrow", size = 8), theme(text = element_text(family = "Arial Narrow", size = 9),
plot.title = element_text(size = 12, face = "bold"), plot.title = element_text(size = 12, face = "bold"),
plot.margin = unit(c(0, 0.25, 0.0, 0.25), "in"), plot.margin = unit(c(0, 0.25, 0.0, 0.25), "in"),
panel.border = element_rect(fill = NA, colour = "#cccccc"), panel.border = element_rect(fill = NA, colour = "#cccccc"),
legend.text = element_text(size = 8), legend.text = element_text(size = 9),
legend.position = c(0.9, 0.25)) legend.position = c(0.25, 0.85))
# TODO: shift to use of grobs: https://cran.r-project.org/web/packages/egg/vignettes/Ecosystem.html # TODO: shift to use of grobs: https://cran.r-project.org/web/packages/egg/vignettes/Ecosystem.html
# ggsave("figure1.pdf") # ggsave("figure1.pdf")
@ -361,7 +363,7 @@ ggplot() +
data = admin_lev1_fortified, data = admin_lev1_fortified,
colour = 'black', colour = 'black',
alpha = .7, alpha = .7,
size = .3) + size = .1) +
viridis::scale_fill_viridis(discrete = TRUE) + viridis::scale_fill_viridis(discrete = TRUE) +
labs(x = NULL, y = NULL, fill = "Groups", labs(x = NULL, y = NULL, fill = "Groups",
title = "Figure 2", title = "Figure 2",
@ -433,7 +435,19 @@ admin_gathered <- gather(data.frame(admin_lev1), key="group_type", value="number
# TODO: make custom legend labels, remove X axis label # TODO: make custom legend labels, remove X axis label
# Ambitious TODO: can we link Admin area titles to locations on adjacent map with lines # Ambitious TODO: can we link Admin area titles to locations on adjacent map with lines
ggplot(admin_gathered, aes(fill=group_type, y=number, x=name)) + geom_bar(position="dodge", stat="identity") + coord_flip() + labs(title = "Figure 4", subtitle="Comparison of Groups by Admin Region", fill = "Groups") ggplot(admin_gathered,
aes(fill=group_type, y=number, x=name)) +
geom_bar(position="dodge", stat="identity") +
coord_flip() +
labs(
title = "Figure 4",
subtitle ="Comparison of Groups by Admin Region",
fill = "Groups") +
theme(
legend.position="bottom",
legend.title = element_blank(),
axis.text.x = element_blank()) +
scale_color_manual(labels = c("DTAS", "ECS", "Permaculture", "Transition"))
``` ```
@ -529,7 +543,7 @@ A wide variety of historians and sociologists of religion have noted the regiona
So why provide this kind of data (i.e. at the level of individual churches) when more granular data (i.e. at the level of individuals persons) is available in the form of the census and related parallel publications such as the 2008 Scottish Environmental Attitudes survey? We believe that mapping places of worship provides a useful intermediate level of analysis and may complement our more atomised understanding of EA which has been assessed at the level of individual persons to date. Because representation within some administrative areas of Scotland, can lead to a small number of data points, we have kept analysis to a National level and have not provided more specific administrative-area level calculations. So why provide this kind of data (i.e. at the level of individual churches) when more granular data (i.e. at the level of individuals persons) is available in the form of the census and related parallel publications such as the 2008 Scottish Environmental Attitudes survey? We believe that mapping places of worship provides a useful intermediate level of analysis and may complement our more atomised understanding of EA which has been assessed at the level of individual persons to date. Because representation within some administrative areas of Scotland, can lead to a small number of data points, we have kept analysis to a National level and have not provided more specific administrative-area level calculations.
```{r create_ecs_denomination_table} ```{r create_ecs_denomination_table}
knitr::kable(ecs@data[["denomination"]], caption = 'ECS by denomination') knitr::kable(summary(ecs@data[["denomination"]]), caption = 'ECS by denomination')
# TODO: Add dataframe with overall church numbers for the UK from "ScottishChurches" dataset by JK # TODO: Add dataframe with overall church numbers for the UK from "ScottishChurches" dataset by JK
``` ```
@ -540,7 +554,7 @@ While Roman Catholic churches make up just over 10% of the church buildings in S
# Eco-Congregations, Urban, Rural and Remote # Eco-Congregations, Urban, Rural and Remote
```{r ur8fold} ```{r ur8fold, message=FALSE, warning=FALSE}
# read in relevant polygons for UR8fold scale # read in relevant polygons for UR8fold scale
if (file.exists("data/SG_UrbanRural_2016.shp") == FALSE) { if (file.exists("data/SG_UrbanRural_2016.shp") == FALSE) {
download.file("http://sedsh127.sedsh.gov.uk/Atom_data/ScotGov/ZippedShapefiles/SG_UrbanRural_2016.zip", download.file("http://sedsh127.sedsh.gov.uk/Atom_data/ScotGov/ZippedShapefiles/SG_UrbanRural_2016.zip",
@ -590,7 +604,15 @@ Of all the groups surveyed in this study, Eco-Congregation Scotland is the most
urbanrural_gathered <- gather(data.frame(urbanrural), key="group_type", value="number", ecs_count, transition_count, dtas_count, permaculture_count) urbanrural_gathered <- gather(data.frame(urbanrural), key="group_type", value="number", ecs_count, transition_count, dtas_count, permaculture_count)
# TODO: switch to stacked percentage plot, see here: https://www.r-graph-gallery.com/48-grouped-barplot-with-ggplot2/ # TODO: switch to stacked percentage plot, see here: https://www.r-graph-gallery.com/48-grouped-barplot-with-ggplot2/
ggplot(urbanrural_gathered, aes(fill=group_type, y=number, x=UR8FOLD)) + geom_bar(position="dodge", stat="identity") + coord_flip() + labs(title = "Figure 8", subtitle="Comparison of Groups by UrbanRural category", fill = "Groups")
ggplot(urbanrural_gathered,
aes(fill=group_type, y=number, x=UR8FOLD)) +
geom_bar(position="dodge", stat="identity") +
coord_flip() +
labs(
title = "Figure 8",
subtitle="Comparison of Groups by UrbanRural category",
fill = "Groups")
``` ```
```{r create_urbanrural_ecs_chart_choropleth, fig.width=4, fig.cap="Figure 9"} ```{r create_urbanrural_ecs_chart_choropleth, fig.width=4, fig.cap="Figure 9"}
@ -639,7 +661,7 @@ ggplot() +
```{r simd data, message=FALSE, warning=FALSE} ```{r simd data, message=FALSE, warning=FALSE}
# read in relevant polygons, Scottish Index of Multiple deprivation # read in relevant polygons, Scottish Index of Multiple deprivation
if (file.exists("data/c_dz_11.shp") == FALSE) { if (file.exists("data/simd2016_withgeog/c_dz_11.shp") == FALSE) {
download.file("http://simd.scot/2016/data/simd2016_withgeog.zip", download.file("http://simd.scot/2016/data/simd2016_withgeog.zip",
destfile = "data/simd2016_withgeog.zip") destfile = "data/simd2016_withgeog.zip")
unzip("data/simd2016_withgeog.zip", exdir = "data", junkpaths = TRUE) unzip("data/simd2016_withgeog.zip", exdir = "data", junkpaths = TRUE)
@ -696,15 +718,33 @@ allgroups_gathered <- gather(allgroups_simd, key = "simd_category", value = "ran
# Run plots # Run plots
# Faceted stacked bar plot # Faceted stacked bar plot
# See here: http://theduke.at/blog/science/beginners-guide-to-creating-grouped-and-stacked-bar-charts-in-r-with-ggplot2/
# Reference here: https://ggplot2.tidyverse.org/reference/geom_bar.html
ggplot(data=allgroups_gathered, aes(x=simd_category, y=rank)) + # Sort by SIMD ranks for bar stacking below
geom_bar(stat="identity") + allgroups_gathered <- allgroups_gathered[order(allgroups_gathered$simd_category, allgroups_gathered$rank),]
facet_grid(~group_type)
# Set manual x-axis labels
axisLabels.x <- c("Crime", "Education", "Employment","Geographic Access","Health","Housing","Income","Overall Rank")
# Plot
# TODO - tidy facet labels: http://www.cookbook-r.com/Graphs/Facets_(ggplot2)/
# TODO - add pointX, consider filtering out some of the simd_categories
ggplot(data=allgroups_gathered,
aes(x=simd_category, y=rank,
fill=cut_interval(allgroups_gathered$rank, n = 5))) +
geom_bar(stat="identity", position="fill") +
facet_grid(~group_type) +
theme(legend.position="none", axis.text.x = element_text(size=6, angle=90, hjust = 0.95, vjust = 0.2)) +
scale_x_discrete(labels=axisLabels.x) +
labs(x = NULL,
y = "SIMD Rank (in bins by quantile)",
fill = "Groups",
title = "Figure 10",
subtitle="Distribution of Groups across IMD Domains by Rank",
caption = paste("Jeremy H. Kidwell :: jeremykidwell.info",
"Data: UK Data Service (OGL) & Jeremy H. Kidwell",
"You may redistribute this graphic under the terms of the CC-by-SA 4.0 license.",
sep = "\n"))
# TODO modify fill = quantiles via cut_interval() or mutate ntile()
# cut_interval(x, n = NULL, length = NULL, ...)
# write.csv(simd_percents_only, "derivedData/simd_percents_only.csv", row.names=FALSE) # write.csv(simd_percents_only, "derivedData/simd_percents_only.csv", row.names=FALSE)
``` ```
@ -737,6 +777,12 @@ We can find divergence between transition communities and eco-congregation when
# Proximity to "Wilderness" # Proximity to "Wilderness"
Chasing down a curiosity, I decided to try and calculate whether proximity to "wilderness" or "scenic nature" or just trees might have some impact on generating more mobilised communities. I realised that there would be several problems with this kind of calculation up front, first being that "nature" is a deeply problematic construct, reviled by geographers and philosophers alike. With this in mind, I identified several different ways of reckoning wilderness, starting with the highly anachronistic "Scenic Land" designation from the 1970s. Then I pursued the more carefully calculated "core wild areas" generated by SNH just a few years ago. However, even the core wile areas concept has been criticised heavily, so I also expanded out my search to include all sites of special scientific interest and then went even wider to include the Scottish Forestry Service's "Native Woodland" and finally, the most generic possible measurement, any land identified as forested at the last Forest Inventory.
Proximity to these areas was the next concern, because many of these designations deliberately exclude human habitat, so it was necessary to measure the number of sites within proximity. There is a question which lies here regarding aesthetics, namely, what sort of proximity might generate an affective connection? From my own experience, I decided upon the distance represented by a short walk, i.e. a half-kilometre. However, with the more generic measurements, such as SSSI and forestation, this wouldn't do, as there are so many of these sites that a buffer of 500 meters encapsulates almost all of inhabited Scotland. So for these sites I also calculated a count within 50 metres.
So what did I discover? The results were inconclusive. First, it is important to note that on the whole, Eco-Congregations tend to be more urban than place of worship taken generally at a rate of nearly 3:1 (5.4% of Eco-Congregations lie in areas currently designated as "Very Remote Rural Areas" whereas nearly 15% of places of worship lie in these areas), so what I was testing for was whether this gap was smaller when specifying these various forms of "wild" remoteness. For our narrowest measurements, there were so few sites captured as to render measurement unreliable. There are, for obvious reasons, 0 sites located within any of SNG's core wild areas. Similarly, there are very few of our activist communities located within SSSI's (only 5 places of worship out of over 4k, 2 transition towns, (or 2%) and 7 community development trusts (3%)). However, expanding this out makes things a bit more interesting, within 50 metres of SSSI's in Scotland lie 3 Eco-Congregations (or just under 1%), which compares favourably with the 61 places of worship (or just 1.5%) far exceeding our ratio (1:1.5 vs. 1:3). This is the same with our more anachronistic measure of "scenic areas," there are 7 eco-congregations within these areas, and 175 places of worship, making for a ratio of nearly 1:2 (2.1% vs. 4.3%). Taking our final measure, of forested areas, this is hard to calculate, as only one Eco-Congregation lies within either native or generally forested land
# Appendix A # Appendix A
```{r pander_admin_table} ```{r pander_admin_table}
@ -753,8 +799,8 @@ write.csv(dtas, "derivedData/dtas.csv", row.names=FALSE)
write.csv(simd, "derivedData/simd.csv", row.names=FALSE) write.csv(simd, "derivedData/simd.csv", row.names=FALSE)
## Output mmd tables using pander ## Output mmd tables using pander
panderOptions("digits", 2) # panderOptions("digits", 2)
pander(as_data_frame(admin_lev1[,c(3,5,7,11,13)])) # pander(as_data_frame(admin_lev1[,c(3,5,7,11,13)]))
``` ```
# Appendix B # Appendix B
@ -770,6 +816,7 @@ pander(as_data_frame(admin_lev1[,c(3,5,7,11,13)]))
# urbanrural.shortened<-data.frame(urbanrural.shortened) # urbanrural.shortened<-data.frame(urbanrural.shortened)
# panderOptions("digits", 2) # panderOptions("digits", 2)
# pander(urbanrural.shortened) # pander(urbanrural.shortened)
```
# Citations # Citations

723
mapping_draft.html
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mapping_draft.md
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@ -1,14 +1,14 @@
--- ---
title: "Mapping Environmental Action in Scotland" title: "Mapping Environmental Action in Scotland"
abstract: abstract:
# thanks: "Replication files are available on the author's Github account (https://github.com/kidwellj/mapping_environmental_action). **Current version**: January 27, 2019 # thanks: "Replication files are available on the author's Github account (https://github.com/kidwellj/mapping_environmental_action). **Current version**: February 01, 2019
style: jeremy1 style: jeremy1
author: “[Jeremy H. Kidwell](http://jeremykidwell.info)” author: "[Jeremy H. Kidwell](http://jeremykidwell.info)"
affiliation: University of Birmingham affiliation: University of Birmingham
institute: University of Birmingham institute: University of Birmingham
e-mail: “[j.kidwell@bham.ac.uk](mailto:j.kidwell@bham.ac.uk)” e-mail: "[j.kidwell@bham.ac.uk](mailto:j.kidwell@bham.ac.uk)"
date: “2019-01-27” date: "2019-02-01"
bibliography: /Users/jeremy/Dropbox/bibtex/everything.bib bibliography: biblio.bib
linkcolor: black linkcolor: black
geometry: margin=1in geometry: margin=1in
# fontfamily: mathpazo # fontfamily: mathpazo
@ -20,6 +20,7 @@ output:
toc_depth: 2 toc_depth: 2
number_sections: true number_sections: true
fig_caption: true fig_caption: true
fig_retina: 1
pdf_document: pdf_document:
keep_tex: true keep_tex: true
number_sections: true number_sections: true
@ -56,7 +57,7 @@ For the sake of comparison, we also measured the geographical footprint of two o
# Technical Background # Technical Background
Analysis was conducted using QGIS 2.8 and R 3.5.2, and data-sets were generated in CSV format.[^15541313] To begin with, I assembled a data set consisting of x and y coordinates for each congregation in Scotland and collated this against a variety of other specific data. Coordinates were checked by matching UK postcodes of individual congregations against geo-referencing data in the Office for National Statistics postcode database. In certain instances a single "congregation" is actually a series of sites which have joined together under one administrative unit. In these cases, each site was treated as a separate data point if worship was held at that site at least once a month, but all joined sites shared a single unique identifier. As noted above, two other datasets were generated for the sake of comparative analysis.[^177171536] These included one similar Environmental Non-Governmental Organisation (ENGO) in Scotland (1) Transition Scotland (which includes Scotland Communities Climate Action Network);[^15541342] and another community-based NGO, Scottish Community Development Trusts.[^158261232] As this report will detail, these three overlap in certain instances both literally and in terms of their aims, but each also has a separate identity and footprint in Scotland. Finally, in order to normalise data, we utilised the PointX POI dataset which maintains a complete database of Places of Worship in Scotland.[^15541614] Analysis was conducted using QGIS 2.8 and R 3.5.1, and data-sets were generated in CSV format.[^15541313] To begin with, I assembled a data set consisting of x and y coordinates for each congregation in Scotland and collated this against a variety of other specific data. Coordinates were checked by matching UK postcodes of individual congregations against geo-referencing data in the Office for National Statistics postcode database. In certain instances a single "congregation" is actually a series of sites which have joined together under one administrative unit. In these cases, each site was treated as a separate data point if worship was held at that site at least once a month, but all joined sites shared a single unique identifier. As noted above, two other datasets were generated for the sake of comparative analysis.[^177171536] These included one similar Environmental Non-Governmental Organisation (ENGO) in Scotland (1) Transition Scotland (which includes Scotland Communities Climate Action Network);[^15541342] and another community-based NGO, Scottish Community Development Trusts.[^158261232] As this report will detail, these three overlap in certain instances both literally and in terms of their aims, but each also has a separate identity and footprint in Scotland. Finally, in order to normalise data, we utilised the PointX POI dataset which maintains a complete database of Places of Worship in Scotland.[^15541614]
# Background and History of Eco-Congregation Scotland # Background and History of Eco-Congregation Scotland
@ -77,9 +78,9 @@ Perhaps the first important question to ask of these groups is, where are they?
(*TODO: need to implement*) Though there are too few eco-congregations and transition groups for a numerically significant representation in any of the intermediate geographies, mapping the concentration of sites by agricultural parishes allows for a more granular visual and I include this for comparison sake. Note, for the sake of a more accurate visual communication, we have also marked out areas of Scotland that are uninhabited with hash marks on the map of agricultural parishes. (*TODO: this will be done in the final draft, once I get my image masking fixed!*).[^15571030] (*TODO: need to implement*) Though there are too few eco-congregations and transition groups for a numerically significant representation in any of the intermediate geographies, mapping the concentration of sites by agricultural parishes allows for a more granular visual and I include this for comparison sake. Note, for the sake of a more accurate visual communication, we have also marked out areas of Scotland that are uninhabited with hash marks on the map of agricultural parishes. (*TODO: this will be done in the final draft, once I get my image masking fixed!*).[^15571030]
![Figure 1](figures/plot_admin_ecs_choropleth-1.png)
![Figure 2](figures/plot_admin_ecs_normed_choropleth-1.png)![Figure 2](figures/plot_admin_ecs_normed_choropleth-2.png)
![][Figure2]
Given the way population and places of worship are unevenly distributed across Scotland it is important to represent data in terms of relative distribution. For this study, we attempted to "normalise" our data in two different ways, (1) as shown by Figure 2 above, by taking population figures from the 2011 census (see data sheet in Appendix A) and (2) by adjusting relative to the number of places of worship in each council region.[^15914204] The latter of these two can yield particularly unexpected results. Thus, of the 4048 "places of worship" in Scotland, the highest concentration is actually the region, with 435, second is 329 (). Rank of Council Areas by population and number of places of worship is also included in Appendix A. Given the way population and places of worship are unevenly distributed across Scotland it is important to represent data in terms of relative distribution. For this study, we attempted to "normalise" our data in two different ways, (1) as shown by Figure 2 above, by taking population figures from the 2011 census (see data sheet in Appendix A) and (2) by adjusting relative to the number of places of worship in each council region.[^15914204] The latter of these two can yield particularly unexpected results. Thus, of the 4048 "places of worship" in Scotland, the highest concentration is actually the region, with 435, second is 329 (). Rank of Council Areas by population and number of places of worship is also included in Appendix A.
@ -93,165 +94,122 @@ Whereas our initial measurements indicated a prominent lead for Edinburgh, by no
![](figures/create_admin_barplot-1.png)<!-- --> ![](figures/create_admin_barplot-1.png)<!-- -->
We can compare the representation in these various regions against our comparison groups to see how other community-based organisations cluster in Scottish administrative districts. Here there are some significant contrasts. Scottish Community Development trusts are most intensely concentrated in the Highlands and Argyll & Bute. But, this is consistent with all the other categories, Eco-Congregations, Places of Worship, and dtass are all over-represented in this area, varying only by the degree. Edinburgh is different, here we find that Eco-Congregations and Transition projects are over-represented, while dtass are under-represented. Finally, the highlands are another strong contrast, here we find a very strong over-representation by transition towns and dtass while the representation of Eco-Congregations is relatively close to the population share for that area. The two areas of greatest contrast for Eco-Congregations from the other groups are unsurprising, Edinburgh is the location of the ECS offices, while Stirling is the area in which ECS first began (see Appendix B for full data).
![][Figure3b] ![Figure 4](figures/create_choropleth_others-1.png)![Figure 4](figures/create_choropleth_others-2.png)![Figure 4](figures/create_choropleth_others-3.png)
[Figure 3c, map normalised by population; choropeth map with 6 gradients. with white represented by =/- 0.5; side-by-side with agricultural parishes map; uninhabited areas greyed out] We can compare the representation in these various regions against our comparison groups to see how other community-based organisations cluster in Scottish administrative districts. Here there are some significant contrasts. Scottish Community Development trusts are most intensely concentrated in the Highlands and Argyll & Bute. But, this is consistent with all the other categories, Eco-Congregations, Places of Worship, and dtas are all over-represented in this area, varying only by the degree. Edinburgh is different, here we find that Eco-Congregations and Transition projects are over-represented, while dtass are under-represented. Finally, the highlands are another strong contrast, here we find a very strong over-representation by transition towns and dtass while the representation of Eco-Congregations is relatively close to the population share for that area. The two areas of greatest contrast for Eco-Congregations from the other groups are unsurprising, Edinburgh is the location of the ECS offices, while Stirling is the area in which ECS first began (see Appendix B for full data).
[Figure 4, normalised by PointX data; also including agricultural parishes etc. as above] # Christian Denominations #
todo: plot as chlorogram: https://www.r-graph-gallery.com/331-basic-cartogram/ Eco-Congregation Scotland describes itself as an "ecumenical movement helping local groups of Christians link environmental issues to their faith, reduce their environmental impact and engage with their local community." There are several ties to the Church of Scotland, as the denomination provides office space to Eco-Congregation Scotland in the Church of Scotland complex at 121 George Street in Edinburgh and provides funding for one full-time member of staff. In spite of this, ECS has, from the start, attempted to emphasise its ecumenical aspirations and this is reflected in a wide variety of ways. The name "eco-congregation" is meant to be tradition neutral (in interviews, staff noted how they have sought to avoid names such as "eco-kirk" which would be the more obvious Presbyterian title, or "eco-community" or "eco-church" which might indicate allegiance towards another). Further, the group has a environmental chaplain on their staff whose position is funded by the United Reformed Church, and other members of staff are funded by the Scottish government, and as such, carry no formal affiliation with a religious institution. This diversity and ecumenicism is reflected in a membership which is, though dominated by the Church of Scotland, nevertheless, made up of a range of Christian traditions.
Though these are not numerically significant, it is important to note that some member congregations describe themselves as ecumenical communities, and others are hybrids reflecting the merging of two traditions. As this ecumenical/hybrid designation involves a small number of the overall total, for the sake of this research, these have been combined into a category called "ecumenical." Further, as research conducted by Church of Scotland statistician Fiona Tweedie has shown, in many Scottish communities with only one church, members of this church will specify their denominational affiliation in a variety of ways (Roman Catholic, Quaker, Methodist, etc.) even though the church and its minister are formally affiliated with the Church of Scotland.[^159142242] So, we should be careful not to assume that the various denominational affiliations of eco-congregations are indicative in an absolute way.
A wide variety of historians and sociologists of religion have noted the regional significance of different Christian denominations in Scotland so we sought to assess the relative distribution and concentration of eco-congregations by denomination. Finding comparative statistics is a complex task, made more complicated by several factors. First, most demographic data on religious belonging in Scotland comes in the form of the 2011 census and as such is far more atomised than this data-set which identifies groups at the level of "congregations" rather than individuals. Equating these two is also complex, as participation by members of congregations can be measured in a variety of ways, there are often a small number of active participants in each eco-congregation group, but may also be a large scale, but passive, support by the wider community.
So why provide this kind of data (i.e. at the level of individual churches) when more granular data (i.e. at the level of individuals persons) is available in the form of the census and related parallel publications such as the 2008 Scottish Environmental Attitudes survey? We believe that mapping places of worship provides a useful intermediate level of analysis and may complement our more atomised understanding of EA which has been assessed at the level of individual persons to date. Because representation within some administrative areas of Scotland, can lead to a small number of data points, we have kept analysis to a National level and have not provided more specific administrative-area level calculations.
Table: ECS by denomination
x
------------- ----
Baptist 4
C of S 254
C of S / URC 3
Cong 1
Ecu 5
FCS 1
Independent 2
Meth 4
Non. 1
Quaker 1
RC 15
SEC 41
Unitarian 1
URC 11
As one might expect, there is a strong representation of the Church of Scotland, almost 74% of eco-congregations, with this number remaining the same when we only count awarded sites. We can confirm, on the basis of this analysis that ECS has a disproportional representation by Church of Scotland churches. At the 2002 church census count, it only represented 40.20% of Scottish churches (1666 of 4144 total churches). Similarly, on the 2011 Scottish census, only 32.44% of persons claimed to be members of the Church of Scotland. We can adjust this representation to 60%, if one excludes the 2,445,204 persons (46% of the total on the census) who reported either "no religion" or adherence to a religious tradition not currently represented among the eco-congregation sites. There is a slight over-representation by the United Reformed church, though this seems considerably more dramatic when one takes into account the fact that this is a trebling or more of their overall share of Scottish churches. The URC makes up only sightly more than 1% of church buildings in Scotland and a tiny 0.04% of respondents to the 2011 census. The Scottish Episcopal church hovers right around a proportional representation within ECS. More concerning are the significant underrepresentation by Roman Catholic churches, Baptists, the Free Church of Scotland, and other independent churches.
While Roman Catholic churches make up just over 10% of the church buildings in Scotland, less than 5% of churches registered as eco-congregations are RC. Even more dramatic is the quartering of baptist churches, and the non-existent representation among the significant group of independent churches and small denominations. These make up nearly 25% of all Scottish churches (over a thousand) and yet only 4 have registered as eco-congregations. We provide several tentative advisories in response to these under-representations in the final section of this paper.
# Eco-Congregations, Urban, Rural and Remote
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## OGR data source with driver: ESRI Shapefile
## Source: "/Users/kidwellj/OneDrive - bham.ac.uk/writing/201708_mapping_environmental_action/data", layer: "SG_UrbanRural_2016"
## with 8 features
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```
Rather than bifurcate congregations into an urban/rural dichotomy, for this study we used the Scottish Government's six-point remoteness scale to categorise eco-congregations along a spectrum of highly populated to remote areas. This 8-fold scale (calculated biennially) offers a more nuanced measurement that combines measurements of remoteness and population along the following lines:
1. Large Urban Areas - Settlements of over 125,000 people.
2. Other Urban Areas - Settlements of 10,000 to 125,000 people.
3. Accessible Small Towns - Settlements of between 3,000 and 10,000 people, and within a 30 minute drive time of a Settlement of 10,000 or more.
4. Remote Small Towns - Settlements of between 3,000 and 10,000 people, and with a drive time between 30 and 60 minutes to a Settlement of 10,000 or more.
5. Very Remote Small Towns - Settlements of between 3,000 and 10,000 people, and with a drive time of over 60 minutes to a Settlement of 10,000 or more.
6. Accessible Rural Areas - Areas with a population of less than 3,000 people, and within a drive time of 30 minutes to a Settlement of 10,000 or more.
7. Remote Rural Areas - Areas with a population of less than 3,000 people, and with a drive time of between 30 and 60 minutes to a Settlement of 10,000 or more.
8. Very Remote Rural Areas - Areas with a population of less than 3,000 people, and with a drive time of over 60 minutes to a Settlement of 10,000 or more.
The key question which this analysis seeks to answer is whether ECS, or the other groups surveyed, are more concentrated in Urban or Rural areas, so as is the case below with our analysis of deprivation, we are concerned with the outer conditions, i.e. the urban areas (items 1-2) and remote areas (items 7-8).
Of all the groups surveyed in this study, Eco-Congregation Scotland is the most heavily concentrated in large urban areas (33.53%), exceeding by almost 50% the rate for all places of worship (22.96% in large urban areas). Transition is a much more modest 20% and development trusts a bit lower at 15%. It is interesting to note that the rate of ECS concentration in these large urban areas matches the level of overall population distribution (34.5%). On the other end of the scale, Eco-Congregation Scotland is the least concentrated in remote rural areas (with 3.93% on level 7 and 5.44% on level 8 on the urban-rural scale), though again, they correlate roughly to the general population distribution (3.2% and 2.9% respectively). Places of worship outpace both the population of Scotland and the footprint of Eco-Congregation Scotland, with 14.98% in very remote rural areas, but this is exceeded by transition at 16.47% and both by Scottish community development trusts at 32.14%. So while Eco-Congregation Scotland correlates roughly with Scottish population distribution across the urban-rural scale, it has a considerably more urban profile than either of the other two groups surveyed.
![](figures/create_ur_barplot-1.png)<!-- -->
![Figure 9](figures/create_urbanrural_ecs_chart_choropleth-1.png)
# Wealth, Employment, and Literacy
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## OGR data source with driver: ESRI Shapefile
## Source: "/Users/kidwellj/OneDrive - bham.ac.uk/writing/201708_mapping_environmental_action/data", layer: "sc_dz_11"
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![](figures/create_simd_barplot-1.png)<!-- -->
Another crucial point of assessment relates to the relation of Eco-Congregation communities to the Scottish Index of Multiple Deprivation. This instrument aggregates a large variety of factors which can lead to deprivation including crime rates, employment levels, access to services (implicating remoteness), and literacy. By assessing ECS, Transition, and dtas against the deprivation scale, we can assess whether eco-congregations fall within particular demographics and also whether the fully aggregated SIMD measurement provides a useful point of comparison for our purposes. The SIMD essentially divides Scotland into 6407 geographic zones and then ranks them based on their relative deprivation. This data set can be split into any number of groups, but for our purposes we have settled on Quintiles, splitting the SIMD data set at every 1302 entries. We then measured where each transition group, ECS, and dtas fell within these zones and calculated how they fell into these five quintiles, from more to least deprived.
The first, and most compelling finding is that, in general Eco-Congregation Scotland and Transition Scotland are both roughly the same and match the level of population distribution in the lowest quintile of the general SIMD measurement. 8% of transition groups and eco-congregation groups which have received awards and 9% of the population are located within this quintile. However, taken in relation to the distribution of places of worship in the lowest quintile, we find that eco-congregations are located at half the rate that places of worship are (15%) and dtass match this much more closely at 14%. Turning towards the top quintile, this pattern also holds, here both transition groups (21%) and eco-congregations (21% and 29% of awarded congregations) depart from the population distribution in this upper quintile (which is 10%). Again, general places of worship (at 11%) and DTASs (at 5%) take the opposite direction. We can say decisively that in communities which have been identified as good candidates for intervention to reduce deprivation, ECS and Transition are less likely, and they are over-represented at the areas which fall into the least deprived quintile.
We can find divergence between transition communities and eco-congregation when we split out SIMD domains. In the lowest quartile, measuring exclusively for the income domain, ECS is more represented (11%) - roughly the same as DTAS (12%), and transition is less (6%) represented. In general (as shown on the chart in Appendix D), these trends hold when representation of our groups are measured within other non-remoteness domains of the SIMD. Our basic conclusion is that transition towns are least likely to operate within the lowest quartile of SIMD and DTASs are most likely, with ECS somewhere in the middle. Given the general disparity against the presence of places of worship, it seems fair to suggest that this might be an area for improvement, perhaps even worth developing a special programme which might target areas in SIMD quartile 1 for eco-congregation outreach. This might be considered particularly in light of the starkest underrepresentation of ECS and transition within the SIMD domain of education, skills, and training.
# Proximity to "Wilderness"
Chasing down a curiosity, I decided to try and calculate whether proximity to "wilderness" or "scenic nature" or just trees might have some impact on generating more mobilised communities. I realised that there would be several problems with this kind of calculation up front, first being that "nature" is a deeply problematic construct, reviled by geographers and philosophers alike. With this in mind, I identified several different ways of reckoning wilderness, starting with the highly anachronistic "Scenic Land" designation from the 1970s. Then I pursued the more carefully calculated "core wild areas" generated by SNH just a few years ago. However, even the core wile areas concept has been criticised heavily, so I also expanded out my search to include all sites of special scientific interest and then went even wider to include the Scottish Forestry Service's "Native Woodland" and finally, the most generic possible measurement, any land identified as forested at the last Forest Inventory.
Proximity to these areas was the next concern, because many of these designations deliberately exclude human habitat, so it was necessary to measure the number of sites within proximity. There is a question which lies here regarding aesthetics, namely, what sort of proximity might generate an affective connection? From my own experience, I decided upon the distance represented by a short walk, i.e. a half-kilometre. However, with the more generic measurements, such as SSSI and forestation, this wouldn't do, as there are so many of these sites that a buffer of 500 meters encapsulates almost all of inhabited Scotland. So for these sites I also calculated a count within 50 metres.
So what did I discover? The results were inconclusive. First, it is important to note that on the whole, Eco-Congregations tend to be more urban than place of worship taken generally at a rate of nearly 3:1 (5.4% of Eco-Congregations lie in areas currently designated as "Very Remote Rural Areas" whereas nearly 15% of places of worship lie in these areas), so what I was testing for was whether this gap was smaller when specifying these various forms of "wild" remoteness. For our narrowest measurements, there were so few sites captured as to render measurement unreliable. There are, for obvious reasons, 0 sites located within any of SNG's core wild areas. Similarly, there are very few of our activist communities located within SSSI's (only 5 places of worship out of over 4k, 2 transition towns, (or 2%) and 7 community development trusts (3%)). However, expanding this out makes things a bit more interesting, within 50 metres of SSSI's in Scotland lie 3 Eco-Congregations (or just under 1%), which compares favourably with the 61 places of worship (or just 1.5%) far exceeding our ratio (1:1.5 vs. 1:3). This is the same with our more anachronistic measure of "scenic areas," there are 7 eco-congregations within these areas, and 175 places of worship, making for a ratio of nearly 1:2 (2.1% vs. 4.3%). Taking our final measure, of forested areas, this is hard to calculate, as only one Eco-Congregation lies within either native or generally forested land
# Appendix A # Appendix A
----------------------------------------------------------------
name ecs_count pow_count dtas_count
--------------------------- ----------- ----------- ------------
Fife 18 243 11
South Ayrshire 3 68 1 # Appendix B
Inverclyde 2 53 1 (JK note to self: same as above, but augmented with multipliers by which categories are different from one another)
Aberdeen City 15 96 1 # Appendix C - Data by Urban / Rural Classification
Highland 21 435 34
West Dunbartonshire 6 52 3
Moray 11 103 6
Orkney Islands 4 50 10
Aberdeenshire 19 244 15
East Renfrewshire 8 37 2
Clackmannanshire 3 30 1
East Ayrshire 4 68 6
North Lanarkshire 5 187 1
Dundee City 3 94 1
Argyll and Bute 18 172 24
Angus 12 106 0
Glasgow City 25 329 21
East Dunbartonshire 7 43 1
Shetland Islands 3 89 4
Scottish Borders 11 153 9
Comhairle nan Eilean Siar 0 114 9
Renfrewshire 6 84 5
North Ayrshire 7 96 3
East Lothian 8 71 2
Falkirk 8 83 0
West Lothian 11 70 7
Perth and Kinross 20 162 10
Dumfries and Galloway 7 189 15
Stirling 13 73 10
City of Edinburgh 48 233 7
Midlothian 1 45 4
South Lanarkshire 17 176 8
----------------------------------------------------------------
Table: Table continues below
--------------------
permaculture_count
--------------------
1
0
0
0
1
0
0
0
1
0
0
0
0
0
3
0
2
0
0
2
0
0
0
0
0
0
1
2
0
0
1
0
--------------------
# Citations # Citations
[^15541312]:This research was jointly funded by the AHRC/ESRC under project numnbers AH/K005456/1 and AH/P005063/1.
[^15541312]: This research was jointly funded by the AHRC/ESRC under project numnbers AH/K005456/1 and AH/P005063/1.
[^158261118]: This is not to say that there have been no collaborations before 2000, noteworthy in this respect is the WWF who helped to found the Alliance of Religion and Conservation (ARC) in 1985. [^158261118]: This is not to say that there have been no collaborations before 2000, noteworthy in this respect is the WWF who helped to found the Alliance of Religion and Conservation (ARC) in 1985.
[^159141043]: This suggestion should be qualified - RSPB would greatly exceed ECS both in terms of the number of individual subscribers and budget. The RSPB trustee's report for 2013-2014 suggests that their member base was 1,114,938 people across Britain with a net income of £127m - the latter of which exceeds the Church of Scotland. If we adjust this based on the Scottish share of the population of the United Kingdom as of the 2011 census (8.3%) this leaves us with an income of £9.93m. The British charity commission requires charities to self-report the number of volunteers and staff, and from their most recent statistics we learn that RSPB engaged with 17,600 volunteers and employed 2,110 members of staff. Again, adjusted for population, this leaves 1,460 volunteers in Scotland and 176 staff. However, if we measure environmental groups based on the number of sites they maintain, RSPB has only 40 reserves with varying levels of local community engagement. For comparison, as of Sep 14 2015, Friends of the Earth Scotland had only 10 local groups (concentrated mostly in large urban areas). Depending on how one measures "volunteerism," it may be possible that ECS has more engaged volunteers in Scotland as well - if each ECS group had only 4 "volunteers" then this would exceed RSPB. [^159141043]: This suggestion should be qualified - RSPB would greatly exceed ECS both in terms of the number of individual subscribers and budget. The RSPB trustee's report for 2013-2014 suggests that their member base was 1,114,938 people across Britain with a net income of £127m - the latter of which exceeds the Church of Scotland. If we adjust this based on the Scottish share of the population of the United Kingdom as of the 2011 census (8.3%) this leaves us with an income of £9.93m. The British charity commission requires charities to self-report the number of volunteers and staff, and from their most recent statistics we learn that RSPB engaged with 17,600 volunteers and employed 2,110 members of staff. Again, adjusted for population, this leaves 1,460 volunteers in Scotland and 176 staff. However, if we measure environmental groups based on the number of sites they maintain, RSPB has only 40 reserves with varying levels of local community engagement. For comparison, as of Sep 14 2015, Friends of the Earth Scotland had only 10 local groups (concentrated mostly in large urban areas). Depending on how one measures "volunteerism," it may be possible that ECS has more engaged volunteers in Scotland as well - if each ECS group had only 4 "volunteers" then this would exceed RSPB.
[^15541313]: Kidwell, Jeremy. (2016). Eco-Congregation Scotland, 2014-2016 [dataset]. University of Edinburgh. http://dx.doi.org/10.7488/ds/1357. [^15541313]: Kidwell, Jeremy. (2016). Eco-Congregation Scotland, 2014-2016. University of Edinburgh. http://dx.doi.org/10.7488/ds/1357.
[^15541342]:My dataset on transition towns will be made available later in 2016. Initial data was aquired from the Transition Scotland website http://www.transitionscotland.org/transition-in-scotland on December 10, 2014. We are currently in the process of collaboratively generating a more up-to-date dataset which will reflect their collaboration with SCCAN. [^15541342]:My dataset on transition towns will be made available later in 2016. Initial data was aquired from the Transition Scotland website http://www.transitionscotland.org/transition-in-scotland on December 10, 2014. We are currently in the process of collaboratively generating a more up-to-date dataset which will reflect their collaboration with SCCAN.
[^177171536]: For further detail on Dataset generation, see Kidwell, Forthcoming, 2018. [^177171536]: For further detail on Dataset generation, see Kidwell, Forthcoming, 2018.
[^158261232]:Data was acquired from the Development Trusts Association website, http://www.dtascot.org.uk, accessed on 20 July 2015. As above, we are currently in the process of active collaboration with volunteers from the DTAS to co-generate a new dataset. [^158261232]:Data was acquired from the Development Trusts Association website, http://www.dtascot.org.uk, accessed on 20 July 2015. As above, we are currently in the process of active collaboration with volunteers from the DTAS to co-generate a new dataset.
@ -261,3 +219,5 @@ Table: Table continues below
[^1554162]:From the Transition map key, "Green pins are 'official' groups [^1554162]:From the Transition map key, "Green pins are 'official' groups
Blue pins are active communities who are connected to the Scottish Transition network Yellow pins show interest in this area" Blue pins are active communities who are connected to the Scottish Transition network Yellow pins show interest in this area"
[^15571030]:This was calculated by calculating a 10m wide footprint for every postcode in Scotland, areas which are not within 10m of a postcode (as of May 2014) are counted as uninhabited. [^15571030]:This was calculated by calculating a 10m wide footprint for every postcode in Scotland, areas which are not within 10m of a postcode (as of May 2014) are counted as uninhabited.
[^159142242]: Fiona Tweedia, *Ecumenical Audit: Questionnaire Findings* (2014).
[^15914204]:See note above regarding the data used from the PointX POI database. Note, for our research,we filtered out religious groups not represented within the Eco-Congregation footprint. We discuss representation by tradition and religion further below.