diff --git a/index.html b/index.html index 9df95f8..7430aaa 100644 --- a/index.html +++ b/index.html @@ -74,7 +74,7 @@

ResultsSummaries of the results including maps of the projected future changes can be found online.

 @@ -98,13 +98,13 @@

Example ## Summary by country. points_bau_ffr |> - dplyr::mutate(flag_EN = if_else(fem_diff_t42 <= -0.5, 1, 0)) |> + dplyr::mutate(flag_EN = if_else(fem_diff_t35 <= -0.5, 1, 0)) |> dplyr::group_by(COUNTRY) |> dplyr::summarise(pop_start = sum(fem_t0), - pop_end = sum(fem_t42), - pop_change = round(((sum(fem_t42) - sum(fem_t0)) / sum(fem_t0)), 3), - change_lcl_95 = Hmisc::smean.cl.boot(fem_diff_t42)["Lower"], - change_ucl_95 = Hmisc::smean.cl.boot(fem_diff_t42)["Upper"], + pop_end = sum(fem_t35), + pop_change = round(((sum(fem_t35) - sum(fem_t0)) / sum(fem_t0)), 3), + change_lcl_95 = Hmisc::smean.cl.boot(fem_diff_t35)["Lower"], + change_ucl_95 = Hmisc::smean.cl.boot(fem_diff_t35)["Upper"], length_river = n(), length_endangered = sum((flag_EN))) |> dplyr::ungroup() |> @@ -116,15 +116,15 @@

Example#> # A tibble: 9 × 10 #> COUNTRY pop_start pop_end pop_change change_lcl_95 change_ucl_95 length_river #> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <int> -#> 1 Bolivia 222170 94300. -0.576 -0.584 -0.567 22217 -#> 2 Brazil 1905550 712133. -0.626 -0.629 -0.624 190555 -#> 3 Colombia 385520 199290. -0.483 -0.490 -0.477 38552 -#> 4 Ecuador 83020 18194. -0.781 -0.790 -0.771 8302 -#> 5 French … 32980 17147. -0.48 -0.503 -0.457 3298 -#> 6 Guyana 73720 55397. -0.249 -0.264 -0.234 7372 -#> 7 Peru 473630 149614. -0.684 -0.689 -0.679 47363 -#> 8 Suriname 57560 42552. -0.261 -0.279 -0.244 5756 -#> 9 Venezue… 300220 185219. -0.383 -0.390 -0.376 30022 +#> 1 Bolivia 222170 103830. -0.533 -0.498 -0.484 22217 +#> 2 Brazil 1905550 934926. -0.509 -0.475 -0.471 190555 +#> 3 Colombia 385520 204235. -0.47 -0.424 -0.412 38552 +#> 4 Ecuador 83020 25106. -0.698 -0.685 -0.667 8302 +#> 5 French … 32980 18580. -0.437 -0.404 -0.367 3298 +#> 6 Guyana 73720 52144. -0.293 -0.229 -0.203 7372 +#> 7 Peru 473630 173911. -0.633 -0.606 -0.597 47363 +#> 8 Suriname 57560 40255. -0.301 -0.240 -0.210 5756 +#> 9 Venezue… 300220 188560. -0.372 -0.316 -0.304 30022 #> # ℹ 3 more variables: length_endangered <dbl>, proportion_endangered <dbl>, #> # threat_status <chr>

Package developed and built using the following guides:

diff --git a/pkgdown.yml b/pkgdown.yml index 0914a96..5657a7b 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -4,7 +4,7 @@ pkgdown_sha: ~ articles: Interactive-map: Interactive-map.html testmap: testmap.html -last_built: 2024-08-07T21:37Z +last_built: 2024-08-07T23:50Z urls: reference: https://darrennorris.github.io/testmap/reference article: https://darrennorris.github.io/testmap/articles diff --git a/search.json b/search.json index d584077..867ad9c 100644 --- a/search.json +++ b/search.json @@ -1 +1 @@ -[{"path":"https://darrennorris.github.io/testmap/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"GNU General Public License","title":"GNU General Public License","text":"Version 3, 29 June 2007Copyright © 2007 Free Software Foundation, Inc.  Everyone permitted copy distribute verbatim copies license document, changing allowed.","code":""},{"path":"https://darrennorris.github.io/testmap/LICENSE.html","id":"preamble","dir":"","previous_headings":"","what":"Preamble","title":"GNU General Public License","text":"GNU General Public License free, copyleft license software kinds works. licenses software practical works designed take away freedom share change works. contrast, GNU General Public License intended guarantee freedom share change versions program–make sure remains free software users. , Free Software Foundation, use GNU General Public License software; applies also work released way authors. can apply programs, . speak free software, referring freedom, price. 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This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . Copyright (C) This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'. This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"https://darrennorris.github.io/testmap/articles/Interactive-map.html","id":"map","dir":"Articles","previous_headings":"","what":"Map","title":"Population change map","text":"Due number points, map can become slow respond zoom . Zoom level showing fewer points can pan around map find area interest. zoom check coloured points. find errors (e.g. points Podocnemis unifilis occur) please raise issue : https://github.com/darrennorris/testmap/issues . zoom see shaded points. points follow rivers produced remote sensing (Free-flowing Rivers, 2019: https://doi.org/10.1038/s41586-019-1111-9). facilitate online viewing mapped points subset intervals approximately 10 kilometers. points brown populations predicted decline 50% within 3 generations (35 years). Brown points therefore represent rivers species Endangered, following IUCN Red List population size reduction criteria - A3bd (https://www.iucnredlist.org//faqs). points represent rivers Podocnemis unifilis females likely nest likely accessible people boat.","code":""},{"path":"https://darrennorris.github.io/testmap/articles/Interactive-map.html","id":"methods","dir":"Articles","previous_headings":"","what":"Methods","title":"Population change map","text":"analysis developed : https://github.com/darrennorris/TACAR, methods used extension Norris et. al. 2019 includes: Stochastic population projections. Future impacts populations caused human acessibility (hunting) actions reduce river connectivity.","code":""},{"path":"https://darrennorris.github.io/testmap/articles/Interactive-map.html","id":"summaries","dir":"Articles","previous_headings":"","what":"Summaries","title":"Population change map","text":"summary map results presented . include summaries country major basin using full set points 1 kilometer intervals. date subpopulations identified due lack comprehensive genetic analysis. Summaries basin provided expected represent important management units predominantly aquatic species. implementation conservation actions regulated national levels summaries also provided country. Results include size extent future population changes. column “population change” difference number adult females 3 generations (35 years). consistent population size reduction criteria used IUCN Red List. column “River length Endangered”, proportion river length populations declined 50% , represents spatial extent future changes.","code":""},{"path":"https://darrennorris.github.io/testmap/articles/Interactive-map.html","id":"summary-by-country-","dir":"Articles","previous_headings":"Summaries","what":"Summary by country.","title":"Population change map","text":"Table 1. Population changes country.","code":""},{"path":"https://darrennorris.github.io/testmap/articles/Interactive-map.html","id":"summary-by-basin-","dir":"Articles","previous_headings":"Summaries","what":"Summary by basin.","title":"Population change map","text":"table “Amazon” includes Amazon Basin together Araguaia-Tocantins Basin Brazil. “Coastal North” covers Guianas includes Essequibo Basin. “Coastal South” includes part Maranhão State Brazil. Table 2. Population changes basin.","code":""},{"path":"https://darrennorris.github.io/testmap/articles/Interactive-map.html","id":"summary-by-major-basins-and-countries-","dir":"Articles","previous_headings":"Summaries","what":"Summary by major basins and countries.","title":"Population change map","text":"Table 3. Population changes country basin. table values can also presented graphically. enables clearer understanding patterns. Figure 1. Population changes across basins contries. grey bars figure show predicted population changes basin country combination. width bars proportional river length log scale. labels bar show river lengths thousands kilometers (e.g. “22.2” 22,200 kilometers). background shading follows gradient Near Threatened (“-0.2” 20% loss) Critically Endangered (“-0.8” 80% loss). Amazon Basin Brazil represents largest proportion rivers (51.1%). Considering spatial variation threats genetics, probably useful include Amazon Basin seperated major basins (Madeira, Negro, etc). summaries presented provide general overview enable assessment results, overall patterns change Amazon basin seperated .","code":""},{"path":"https://darrennorris.github.io/testmap/articles/Interactive-map.html","id":"next-steps","dir":"Articles","previous_headings":"","what":"Next steps","title":"Population change map","text":"Consult researchers check validate mapped results. Evaluate future impact conservation actions. Apply species.","code":""},{"path":"https://darrennorris.github.io/testmap/articles/testmap.html","id":"load-packages","dir":"Articles","previous_headings":"","what":"Load packages","title":"Getting started: make a map","text":"","code":"library(testmap) library(dplyr) library(sf) library(leaflet) library(leafem)"},{"path":"https://darrennorris.github.io/testmap/articles/testmap.html","id":"make-map","dir":"Articles","previous_headings":"","what":"Make map","title":"Getting started: make a map","text":"example shows map Podocnemis unifilis Endangered French Guiana. country chosen illustrative purposes relatively river points.","code":"## River points for specific country. points_bau4326 <- points_bau_ffr_map |> dplyr::filter(COUNTRY == \"French Guiana\") |> # country sf::st_as_sf(crs = 3395) |> sf::st_transform(4326) levels(points_bau4326$flag_50_35y) <- c(\"No\", \"Yes\") # colour palette leaf_pal <- colorFactor( palette = c(\"#7274C1\", \"#A3720E\"), domain = points_bau4326$flag_50_35y ) # interactive map. Options added to make panning smoother.... leaflet::leaflet(points_bau4326, options = leafletOptions(preferCanvas = TRUE)) |> # Basemap addTiles(options = tileOptions( updateWhenZooming = FALSE, # map won't update tiles until zoom is done updateWhenIdle = TRUE)) |> # Circles when zoom in. addCircles(color = ~leaf_pal(flag_50_35y), group = \"points_bau4326_low\" ) |> # Markers with cluster options for smoother panning. addCircleMarkers(color = ~leaf_pal(flag_50_35y), stroke = FALSE, fillOpacity = 0.4, clusterOptions = markerClusterOptions(), group = \"points_bau4326\" ) |> addLegend(\"bottomright\", pal = leaf_pal, title=\"Endangered\", values = ~flag_50_35y, group = \"en_legend\") |> groupOptions(\"points_bau4326\", zoomLevels = 1:6) |> groupOptions(\"points_bau4326_low\", zoomLevels = 7:15) |> addScaleBar() |> leafem::addMouseCoordinates()"},{"path":"https://darrennorris.github.io/testmap/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Darren Norris. Author, maintainer.","code":""},{"path":"https://darrennorris.github.io/testmap/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Norris D (2024). testmap: Population projection maps Yellow-spotted River Turtle. R package version 0.0.0.9000, https://darrennorris.github.io/testmap/, https://github.com/darrennorris/testmap.","code":"@Manual{, title = {testmap: Population projection maps for the Yellow-spotted River Turtle}, author = {Darren Norris}, year = {2024}, note = {R package version 0.0.0.9000, https://darrennorris.github.io/testmap/}, url = {https://github.com/darrennorris/testmap}, }"},{"path":"https://darrennorris.github.io/testmap/index.html","id":"testmap","dir":"","previous_headings":"","what":"Population projection maps for the Yellow-spotted River Turtle","title":"Population projection maps for the Yellow-spotted River Turtle","text":"goal testmap map future population changes Yellow-spotted river turtle (Podocnemis unifilis). predicted future changes female-, stochastic stage-based matrix population projection models, developed : https://github.com/darrennorris/TACAR","code":""},{"path":"https://darrennorris.github.io/testmap/index.html","id":"objectives","dir":"","previous_headings":"","what":"Objectives","title":"Population projection maps for the Yellow-spotted River Turtle","text":"maps used Provide updated assesment threatened species . Inform development implement improvements modelling process.","code":""},{"path":"https://darrennorris.github.io/testmap/index.html","id":"results","dir":"","previous_headings":"","what":"Results","title":"Population projection maps for the Yellow-spotted River Turtle","text":"Summaries results including maps projected future changes can found online. 3 generation. Predicted changes 42 years: https://darrennorris.github.io/testmap/articles/Interactive-map.html","code":""},{"path":"https://darrennorris.github.io/testmap/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Population projection maps for the Yellow-spotted River Turtle","text":"can download data check visualise using R. testmap submitted CRAN data files large package therefore pass “cran” checks. need install testmap like :","code":"install.packages(\"remotes\") remotes::install_github(\"darrennorris/testmap\")"},{"path":"https://darrennorris.github.io/testmap/index.html","id":"example","dir":"","previous_headings":"","what":"Example","title":"Population projection maps for the Yellow-spotted River Turtle","text":"example shows summary future changes Podocnemis unifilis populations different countries. Another example showing Podocnemis unifilis Endangered : https://darrennorris.github.io/testmap/articles/testmap.html Package developed built using following guides: Fan Wang: https://fanwangecon.github.io/PkgTestR/articles/ffv_pkgdown_github.html Emil Hvitfeldt: https://emilhvitfeldt.com/post/2018-09-02-usethis-workflow--package-development/ Saskia O: https://www.marinedatascience.co/blog/2020/01/09/checklist--r-package-re-submissions--cran/","code":"library(testmap) library(dplyr) ## Summary by country. points_bau_ffr |> dplyr::mutate(flag_EN = if_else(fem_diff_t42 <= -0.5, 1, 0)) |> dplyr::group_by(COUNTRY) |> dplyr::summarise(pop_start = sum(fem_t0), pop_end = sum(fem_t42), pop_change = round(((sum(fem_t42) - sum(fem_t0)) / sum(fem_t0)), 3), change_lcl_95 = Hmisc::smean.cl.boot(fem_diff_t42)[\"Lower\"], change_ucl_95 = Hmisc::smean.cl.boot(fem_diff_t42)[\"Upper\"], length_river = n(), length_endangered = sum((flag_EN))) |> dplyr::ungroup() |> dplyr::mutate(proportion_endangered = round((length_endangered / length_river), 2)) |> dplyr::mutate(threat_status = case_when(pop_change <= -0.8 ~ \"Critically Endangered\", pop_change <= -0.5 ~ \"Endangered\", pop_change <= -0.3 ~ \"Vulnerable\", pop_change <= -0.2 ~ \"Near Threatened\")) #> # A tibble: 9 × 10 #> COUNTRY pop_start pop_end pop_change change_lcl_95 change_ucl_95 length_river #> #> 1 Bolivia 222170 94300. -0.576 -0.584 -0.567 22217 #> 2 Brazil 1905550 712133. -0.626 -0.629 -0.624 190555 #> 3 Colombia 385520 199290. -0.483 -0.490 -0.477 38552 #> 4 Ecuador 83020 18194. -0.781 -0.790 -0.771 8302 #> 5 French … 32980 17147. -0.48 -0.503 -0.457 3298 #> 6 Guyana 73720 55397. -0.249 -0.264 -0.234 7372 #> 7 Peru 473630 149614. -0.684 -0.689 -0.679 47363 #> 8 Suriname 57560 42552. -0.261 -0.279 -0.244 5756 #> 9 Venezue… 300220 185219. -0.383 -0.390 -0.376 30022 #> # ℹ 3 more variables: length_endangered , proportion_endangered , #> # threat_status "},{"path":"https://darrennorris.github.io/testmap/reference/points_bau.html","id":null,"dir":"Reference","previous_headings":"","what":"Points along rivers. — points_bau","title":"Points along rivers. — points_bau","text":"points show projected population changes along rivers. Projections generated TACAR (https://github.com/darrennorris/TACAR). population projections updated extended version published Norris et. al. 2019 (https://doi.org/10.1016/j.biocon.2019.02.022). location South America. coord. ref WGS 84 (EPSG:3395).","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Points along rivers. — points_bau","text":"","code":"points_bau"},{"path":"https://darrennorris.github.io/testmap/reference/points_bau.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Points along rivers. — points_bau","text":"points_bau dataframe 215849 points 13 fields, including: BASIN_N Name major basin. subbasn Name subbasn. geometry sf geometry.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Points along rivers. — points_bau","text":"https://github.com/darrennorris/TACAR","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Points along rivers. — points_bau","text":"lot points along rivers.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Points along rivers. — points_bau","text":"Norris, D., et. al. (2019). Prospects freshwater turtle population recovery catalyzed pan-Amazonian community-based management. Biological Conservation, 233, https://doi.org/10.1016/j.biocon.2019.02.022.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Points along rivers. — points_bau","text":"","code":"if (FALSE) { # \\dontrun{ # convert to sf object sf_points_bau <- sf::st_as_sf(points_bau, crs = 3395) } # }"},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr.html","id":null,"dir":"Reference","previous_headings":"","what":"Points along Free-flowing rivers. — points_bau_ffr","title":"Points along Free-flowing rivers. — points_bau_ffr","text":"points show projected population changes along rivers. Projections generated TACAR (https://github.com/darrennorris/TACAR). population projections updated extended version published Norris et. al. 2019 (https://doi.org/10.1016/j.biocon.2019.02.022). location South America. coord. ref WGS 84 (EPSG:3395).","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Points along Free-flowing rivers. — points_bau_ffr","text":"","code":"points_bau_ffr"},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Points along Free-flowing rivers. — points_bau_ffr","text":"points_bau_ffr dataframe 353437 points 15 fields, including: BASIN_NAME Name major basin. subbasn Name subbasn. geom sf geometry column.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Points along Free-flowing rivers. — points_bau_ffr","text":"https://github.com/darrennorris/TACAR","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Points along Free-flowing rivers. — points_bau_ffr","text":"lot points along rivers.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Points along Free-flowing rivers. — points_bau_ffr","text":"Norris, D., et. al. (2019). Prospects freshwater turtle population recovery catalyzed pan-Amazonian community-based management. Biological Conservation, 233, https://doi.org/10.1016/j.biocon.2019.02.022. Grill, G., Lehner, B., Thieme, M. et al. (2019) Mapping world’s free-flowing rivers. Nature 569, 215–221, https://doi.org/10.1038/s41586-019-1111-9.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Points along Free-flowing rivers. — points_bau_ffr","text":"","code":"if (FALSE) { # \\dontrun{ # convert to sf object sf_points_bau_ffr <- sf::st_as_sf(points_bau_ffr, crs = 3395) } # }"},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr_map.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","title":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","text":"points show projected population changes along rivers. Projections generated TACAR (https://github.com/darrennorris/TACAR). population projections updated extended version published Norris et. al. 2019 (https://doi.org/10.1016/j.biocon.2019.02.022). location South America. coord. ref WGS 84 (EPSG:3395).","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr_map.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","text":"","code":"points_bau_ffr_map"},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr_map.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","text":"points_bau_ffr_map dataframe 35344 points 15 fields, including: BASIN_NAME Name major basin. subbasn Name subbasn. geom sf geometry column.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr_map.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","text":"https://github.com/darrennorris/TACAR","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr_map.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","text":"10% subset, includes one ten rows points_bau_ffr.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr_map.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","text":"Norris, D., et. al. (2019). Prospects freshwater turtle population recovery catalyzed pan-Amazonian community-based management. Biological Conservation, 233, https://doi.org/10.1016/j.biocon.2019.02.022. Grill, G., Lehner, B., Thieme, M. et al. (2019) Mapping world’s free-flowing rivers. Nature 569, 215–221, https://doi.org/10.1038/s41586-019-1111-9.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr_map.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","text":"","code":"if (FALSE) { # \\dontrun{ # convert to sf object sf_points_bau_ffr_map <- sf::st_as_sf(points_bau_ffr_map, crs = 3395) } # }"}] +[{"path":"https://darrennorris.github.io/testmap/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"GNU General Public License","title":"GNU General Public License","text":"Version 3, 29 June 2007Copyright © 2007 Free Software Foundation, Inc.  Everyone permitted copy distribute verbatim copies license document, changing allowed.","code":""},{"path":"https://darrennorris.github.io/testmap/LICENSE.html","id":"preamble","dir":"","previous_headings":"","what":"Preamble","title":"GNU General Public License","text":"GNU General Public License free, copyleft license software kinds works. licenses software practical works designed take away freedom share change works. contrast, GNU General Public License intended guarantee freedom share change versions program–make sure remains free software users. , Free Software Foundation, use GNU General Public License software; applies also work released way authors. can apply programs, . speak free software, referring freedom, price. 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Also add information contact electronic paper mail. program terminal interaction, make output short notice like starts interactive mode: hypothetical commands show w show c show appropriate parts General Public License. course, program’s commands might different; GUI interface, use “box”. also get employer (work programmer) school, , sign “copyright disclaimer” program, necessary. information , apply follow GNU GPL, see . GNU General Public License permit incorporating program proprietary programs. program subroutine library, may consider useful permit linking proprietary applications library. want , use GNU Lesser General Public License instead License. first, please read .","code":" Copyright (C) This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . Copyright (C) This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'. This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"https://darrennorris.github.io/testmap/articles/Interactive-map.html","id":"map","dir":"Articles","previous_headings":"","what":"Map","title":"Population change map","text":"Due number points, map can become slow respond zoom . Zoom level showing fewer points can pan around map find area interest. zoom check coloured points. find errors (e.g. points Podocnemis unifilis occur) please raise issue : https://github.com/darrennorris/testmap/issues . zoom see shaded points. points follow rivers produced remote sensing (Free-flowing Rivers, 2019: https://doi.org/10.1038/s41586-019-1111-9). facilitate online viewing mapped points subset intervals approximately 10 kilometers. points brown populations predicted decline 50% within 3 generations (35 years). Brown points therefore represent rivers species Endangered, following IUCN Red List population size reduction criteria - A3bd (https://www.iucnredlist.org//faqs). points represent rivers Podocnemis unifilis females likely nest likely accessible people boat.","code":""},{"path":"https://darrennorris.github.io/testmap/articles/Interactive-map.html","id":"methods","dir":"Articles","previous_headings":"","what":"Methods","title":"Population change map","text":"analysis developed : https://github.com/darrennorris/TACAR, methods used extension Norris et. al. 2019 includes: Stochastic population projections. Future impacts populations caused human acessibility (hunting) actions reduce river connectivity.","code":""},{"path":"https://darrennorris.github.io/testmap/articles/Interactive-map.html","id":"summaries","dir":"Articles","previous_headings":"","what":"Summaries","title":"Population change map","text":"summary map results presented . include summaries country major basin using full set points 1 kilometer intervals. date subpopulations identified due lack comprehensive genetic analysis. Summaries basin provided expected represent important management units predominantly aquatic species. implementation conservation actions regulated national levels summaries also provided country. Results include size extent future population changes. column “population change” difference number adult females 3 generations (35 years). consistent population size reduction criteria used IUCN Red List. column “River length Endangered”, proportion river length populations declined 50% , represents spatial extent future changes.","code":""},{"path":"https://darrennorris.github.io/testmap/articles/Interactive-map.html","id":"summary-by-country-","dir":"Articles","previous_headings":"Summaries","what":"Summary by country.","title":"Population change map","text":"Table 1. Population changes country.","code":""},{"path":"https://darrennorris.github.io/testmap/articles/Interactive-map.html","id":"summary-by-basin-","dir":"Articles","previous_headings":"Summaries","what":"Summary by basin.","title":"Population change map","text":"table “Amazon” includes Amazon Basin together Araguaia-Tocantins Basin Brazil. “Coastal North” covers Guianas includes Essequibo Basin. “Coastal South” includes part Maranhão State Brazil. Table 2. Population changes basin.","code":""},{"path":"https://darrennorris.github.io/testmap/articles/Interactive-map.html","id":"summary-by-major-basins-and-countries-","dir":"Articles","previous_headings":"Summaries","what":"Summary by major basins and countries.","title":"Population change map","text":"Table 3. Population changes country basin. table values can also presented graphically. enables clearer understanding patterns. Figure 1. Population changes across basins contries. grey bars figure show predicted population changes basin country combination. width bars proportional river length log scale. labels bar show river lengths thousands kilometers (e.g. “22.2” 22,200 kilometers). background shading follows gradient Near Threatened (“-0.2” 20% loss) Critically Endangered (“-0.8” 80% loss). Amazon Basin Brazil represents largest proportion rivers (51.1%). Considering spatial variation threats genetics, probably useful include Amazon Basin seperated major basins (Madeira, Negro, etc). summaries presented provide general overview enable assessment results, overall patterns change Amazon basin seperated .","code":""},{"path":"https://darrennorris.github.io/testmap/articles/Interactive-map.html","id":"next-steps","dir":"Articles","previous_headings":"","what":"Next steps","title":"Population change map","text":"Consult researchers check validate mapped results. Evaluate future impact conservation actions. Apply species.","code":""},{"path":"https://darrennorris.github.io/testmap/articles/testmap.html","id":"load-packages","dir":"Articles","previous_headings":"","what":"Load packages","title":"Getting started: make a map","text":"","code":"library(testmap) library(dplyr) library(sf) library(leaflet) library(leafem)"},{"path":"https://darrennorris.github.io/testmap/articles/testmap.html","id":"make-map","dir":"Articles","previous_headings":"","what":"Make map","title":"Getting started: make a map","text":"example shows map Podocnemis unifilis Endangered French Guiana. country chosen illustrative purposes relatively river points.","code":"## River points for specific country. points_bau4326 <- points_bau_ffr_map |> dplyr::filter(COUNTRY == \"French Guiana\") |> # country sf::st_as_sf(crs = 3395) |> sf::st_transform(4326) levels(points_bau4326$flag_50_35y) <- c(\"No\", \"Yes\") # colour palette leaf_pal <- colorFactor( palette = c(\"#7274C1\", \"#A3720E\"), domain = points_bau4326$flag_50_35y ) # interactive map. Options added to make panning smoother.... leaflet::leaflet(points_bau4326, options = leafletOptions(preferCanvas = TRUE)) |> # Basemap addTiles(options = tileOptions( updateWhenZooming = FALSE, # map won't update tiles until zoom is done updateWhenIdle = TRUE)) |> # Circles when zoom in. addCircles(color = ~leaf_pal(flag_50_35y), group = \"points_bau4326_low\" ) |> # Markers with cluster options for smoother panning. addCircleMarkers(color = ~leaf_pal(flag_50_35y), stroke = FALSE, fillOpacity = 0.4, clusterOptions = markerClusterOptions(), group = \"points_bau4326\" ) |> addLegend(\"bottomright\", pal = leaf_pal, title=\"Endangered\", values = ~flag_50_35y, group = \"en_legend\") |> groupOptions(\"points_bau4326\", zoomLevels = 1:6) |> groupOptions(\"points_bau4326_low\", zoomLevels = 7:15) |> addScaleBar() |> leafem::addMouseCoordinates()"},{"path":"https://darrennorris.github.io/testmap/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Darren Norris. Author, maintainer.","code":""},{"path":"https://darrennorris.github.io/testmap/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Norris D (2024). testmap: Population projection maps Yellow-spotted River Turtle. R package version 0.0.0.9000, https://darrennorris.github.io/testmap/, https://github.com/darrennorris/testmap.","code":"@Manual{, title = {testmap: Population projection maps for the Yellow-spotted River Turtle}, author = {Darren Norris}, year = {2024}, note = {R package version 0.0.0.9000, https://darrennorris.github.io/testmap/}, url = {https://github.com/darrennorris/testmap}, }"},{"path":"https://darrennorris.github.io/testmap/index.html","id":"testmap","dir":"","previous_headings":"","what":"Population projection maps for the Yellow-spotted River Turtle","title":"Population projection maps for the Yellow-spotted River Turtle","text":"goal testmap map future population changes Yellow-spotted river turtle (Podocnemis unifilis). predicted future changes female-, stochastic stage-based matrix population projection models, developed : https://github.com/darrennorris/TACAR","code":""},{"path":"https://darrennorris.github.io/testmap/index.html","id":"objectives","dir":"","previous_headings":"","what":"Objectives","title":"Population projection maps for the Yellow-spotted River Turtle","text":"maps used Provide updated assesment threatened species . Inform development implement improvements modelling process.","code":""},{"path":"https://darrennorris.github.io/testmap/index.html","id":"results","dir":"","previous_headings":"","what":"Results","title":"Population projection maps for the Yellow-spotted River Turtle","text":"Summaries results including maps projected future changes can found online. 3 generation. Predicted changes 35 years: https://darrennorris.github.io/testmap/articles/Interactive-map.html","code":""},{"path":"https://darrennorris.github.io/testmap/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Population projection maps for the Yellow-spotted River Turtle","text":"can download data check visualise using R. testmap submitted CRAN data files large package therefore pass “cran” checks. need install testmap like :","code":"install.packages(\"remotes\") remotes::install_github(\"darrennorris/testmap\")"},{"path":"https://darrennorris.github.io/testmap/index.html","id":"example","dir":"","previous_headings":"","what":"Example","title":"Population projection maps for the Yellow-spotted River Turtle","text":"example shows summary future changes Podocnemis unifilis populations different countries. Another example showing Podocnemis unifilis Endangered : https://darrennorris.github.io/testmap/articles/testmap.html Package developed built using following guides: Fan Wang: https://fanwangecon.github.io/PkgTestR/articles/ffv_pkgdown_github.html Emil Hvitfeldt: https://emilhvitfeldt.com/post/2018-09-02-usethis-workflow--package-development/ Saskia O: https://www.marinedatascience.co/blog/2020/01/09/checklist--r-package-re-submissions--cran/","code":"library(testmap) library(dplyr) ## Summary by country. points_bau_ffr |> dplyr::mutate(flag_EN = if_else(fem_diff_t35 <= -0.5, 1, 0)) |> dplyr::group_by(COUNTRY) |> dplyr::summarise(pop_start = sum(fem_t0), pop_end = sum(fem_t35), pop_change = round(((sum(fem_t35) - sum(fem_t0)) / sum(fem_t0)), 3), change_lcl_95 = Hmisc::smean.cl.boot(fem_diff_t35)[\"Lower\"], change_ucl_95 = Hmisc::smean.cl.boot(fem_diff_t35)[\"Upper\"], length_river = n(), length_endangered = sum((flag_EN))) |> dplyr::ungroup() |> dplyr::mutate(proportion_endangered = round((length_endangered / length_river), 2)) |> dplyr::mutate(threat_status = case_when(pop_change <= -0.8 ~ \"Critically Endangered\", pop_change <= -0.5 ~ \"Endangered\", pop_change <= -0.3 ~ \"Vulnerable\", pop_change <= -0.2 ~ \"Near Threatened\")) #> # A tibble: 9 × 10 #> COUNTRY pop_start pop_end pop_change change_lcl_95 change_ucl_95 length_river #> #> 1 Bolivia 222170 103830. -0.533 -0.498 -0.484 22217 #> 2 Brazil 1905550 934926. -0.509 -0.475 -0.471 190555 #> 3 Colombia 385520 204235. -0.47 -0.424 -0.412 38552 #> 4 Ecuador 83020 25106. -0.698 -0.685 -0.667 8302 #> 5 French … 32980 18580. -0.437 -0.404 -0.367 3298 #> 6 Guyana 73720 52144. -0.293 -0.229 -0.203 7372 #> 7 Peru 473630 173911. -0.633 -0.606 -0.597 47363 #> 8 Suriname 57560 40255. -0.301 -0.240 -0.210 5756 #> 9 Venezue… 300220 188560. -0.372 -0.316 -0.304 30022 #> # ℹ 3 more variables: length_endangered , proportion_endangered , #> # threat_status "},{"path":"https://darrennorris.github.io/testmap/reference/points_bau.html","id":null,"dir":"Reference","previous_headings":"","what":"Points along rivers. — points_bau","title":"Points along rivers. — points_bau","text":"points show projected population changes along rivers. Projections generated TACAR (https://github.com/darrennorris/TACAR). population projections updated extended version published Norris et. al. 2019 (https://doi.org/10.1016/j.biocon.2019.02.022). location South America. coord. ref WGS 84 (EPSG:3395).","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Points along rivers. — points_bau","text":"","code":"points_bau"},{"path":"https://darrennorris.github.io/testmap/reference/points_bau.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Points along rivers. — points_bau","text":"points_bau dataframe 215849 points 13 fields, including: BASIN_N Name major basin. subbasn Name subbasn. geometry sf geometry.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Points along rivers. — points_bau","text":"https://github.com/darrennorris/TACAR","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Points along rivers. — points_bau","text":"lot points along rivers.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Points along rivers. — points_bau","text":"Norris, D., et. al. (2019). Prospects freshwater turtle population recovery catalyzed pan-Amazonian community-based management. Biological Conservation, 233, https://doi.org/10.1016/j.biocon.2019.02.022.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Points along rivers. — points_bau","text":"","code":"if (FALSE) { # \\dontrun{ # convert to sf object sf_points_bau <- sf::st_as_sf(points_bau, crs = 3395) } # }"},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr.html","id":null,"dir":"Reference","previous_headings":"","what":"Points along Free-flowing rivers. — points_bau_ffr","title":"Points along Free-flowing rivers. — points_bau_ffr","text":"points show projected population changes along rivers. Projections generated TACAR (https://github.com/darrennorris/TACAR). population projections updated extended version published Norris et. al. 2019 (https://doi.org/10.1016/j.biocon.2019.02.022). location South America. coord. ref WGS 84 (EPSG:3395).","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Points along Free-flowing rivers. — points_bau_ffr","text":"","code":"points_bau_ffr"},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Points along Free-flowing rivers. — points_bau_ffr","text":"points_bau_ffr dataframe 353437 points 15 fields, including: BASIN_NAME Name major basin. subbasn Name subbasn. geom sf geometry column.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Points along Free-flowing rivers. — points_bau_ffr","text":"https://github.com/darrennorris/TACAR","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Points along Free-flowing rivers. — points_bau_ffr","text":"lot points along rivers.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Points along Free-flowing rivers. — points_bau_ffr","text":"Norris, D., et. al. (2019). Prospects freshwater turtle population recovery catalyzed pan-Amazonian community-based management. Biological Conservation, 233, https://doi.org/10.1016/j.biocon.2019.02.022. Grill, G., Lehner, B., Thieme, M. et al. (2019) Mapping world’s free-flowing rivers. Nature 569, 215–221, https://doi.org/10.1038/s41586-019-1111-9.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Points along Free-flowing rivers. — points_bau_ffr","text":"","code":"if (FALSE) { # \\dontrun{ # convert to sf object sf_points_bau_ffr <- sf::st_as_sf(points_bau_ffr, crs = 3395) } # }"},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr_map.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","title":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","text":"points show projected population changes along rivers. Projections generated TACAR (https://github.com/darrennorris/TACAR). population projections updated extended version published Norris et. al. 2019 (https://doi.org/10.1016/j.biocon.2019.02.022). location South America. coord. ref WGS 84 (EPSG:3395).","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr_map.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","text":"","code":"points_bau_ffr_map"},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr_map.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","text":"points_bau_ffr_map dataframe 35344 points 15 fields, including: BASIN_NAME Name major basin. subbasn Name subbasn. geom sf geometry column.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr_map.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","text":"https://github.com/darrennorris/TACAR","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr_map.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","text":"10% subset, includes one ten rows points_bau_ffr.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr_map.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","text":"Norris, D., et. al. (2019). Prospects freshwater turtle population recovery catalyzed pan-Amazonian community-based management. Biological Conservation, 233, https://doi.org/10.1016/j.biocon.2019.02.022. Grill, G., Lehner, B., Thieme, M. et al. (2019) Mapping world’s free-flowing rivers. Nature 569, 215–221, https://doi.org/10.1038/s41586-019-1111-9.","code":""},{"path":"https://darrennorris.github.io/testmap/reference/points_bau_ffr_map.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Subset of points along Free-flowing rivers. — points_bau_ffr_map","text":"","code":"if (FALSE) { # \\dontrun{ # convert to sf object sf_points_bau_ffr_map <- sf::st_as_sf(points_bau_ffr_map, crs = 3395) } # }"}]