From 9d7655a9216c0dc1c44ee08bd7945a22bba848ac Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?V=C3=ADctor=20Julio=20Rinc=C3=B3n-Parra?= <108538775+vicjulrin@users.noreply.github.com> Date: Wed, 9 Oct 2024 16:59:55 -0400 Subject: [PATCH] Update link readme yml --- pipelines/GeneticIndicator_VJRP/AA.json | 110 ------------ pipelines/GeneticIndicator_VJRP/bb.json | 221 ------------------------ pipelines/New folder/AA.json | 197 --------------------- pipelines/qq.json | 65 ------- scripts/Pops_from_DispDist/README.Rmd | 8 +- scripts/Pops_from_DispDist/README.md | 16 +- 6 files changed, 12 insertions(+), 605 deletions(-) delete mode 100644 pipelines/GeneticIndicator_VJRP/AA.json delete mode 100644 pipelines/GeneticIndicator_VJRP/bb.json delete mode 100644 pipelines/New folder/AA.json delete mode 100644 pipelines/qq.json diff --git a/pipelines/GeneticIndicator_VJRP/AA.json b/pipelines/GeneticIndicator_VJRP/AA.json deleted file mode 100644 index fc3138a4..00000000 --- a/pipelines/GeneticIndicator_VJRP/AA.json +++ /dev/null @@ -1,110 +0,0 @@ -{ - "nodes": [ - { - "id": "16", - "type": "io", - "position": { - "x": 1100.1309386300816, - "y": 8.12555073849029 - }, - "data": { - "descriptionFile": "Pops_from_distance>Pops_from_distance.yml" - } - }, - { - "id": "17", - "type": "output", - "position": { - "x": 1600.987838167659, - "y": 50.719932855958234 - }, - "data": { - "label": "Output" - } - }, - { - "id": "24", - "type": "io", - "position": { - "x": 389.5333251953125, - "y": 279 - }, - "data": { - "descriptionFile": "Pops_from_DispDist2>Pops_from_DispDist.yml" - } - }, - { - "id": "28", - "type": "io", - "position": { - "x": 620.5333251953125, - "y": 166 - }, - "data": { - "descriptionFile": "getPopCountry.json" - } - }, - { - "id": "29", - "type": "output", - "position": { - "x": 1051.5333251953125, - "y": 169 - }, - "data": { - "label": "Output" - } - } - ], - "edges": [ - { - "source": "16", - "sourceHandle": "plot_hypothesis", - "target": "17", - "targetHandle": null, - "id": "reactflow__edge-16plot_hypothesis-17" - }, - { - "source": "28", - "sourceHandle": "GBIF_from_polygon>GBIF_from_polygon.yml@10|vector_presence", - "target": "29", - "targetHandle": null, - "id": "reactflow__edge-28GBIF_from_polygon>GBIF_from_polygon.yml@10|vector_presence-29" - } - ], - "inputs": { - "getPopCountry.json@28|GBIF_from_polygon>GBIF_from_polygon.yml@10|country": { - "description": "Optional string, country to retrieve the occurrences from. Leave blank to ignore administrative boundaries.", - "label": "country", - "weight": 0, - "type": "text", - "example": "Colombia" - }, - "getPopCountry.json@28|GBIF_from_polygon>GBIF_from_polygon.yml@10|vector_polygon": { - "description": "Text string with the complete path location for the spatial file containing the study area boundaries. Accepted file types include shapefile (.shp), raster (.tif/GeoTIFF), GeoJSON (.json) or GeoPackage (.gpkg).", - "label": "vector_polygon", - "weight": 1, - "type": "application/geo+json", - "example": [ - "/scripts/GBIF_from_polygon/input/sp_map.GeoJSON" - ] - }, - "getPopCountry.json@28|GBIF_from_polygon>GBIF_from_polygon.yml@10|species": { - "description": "Scientific name of the species", - "label": "species names", - "weight": 2, - "type": "text[]", - "example": [ - "Myrmecophaga tridactyla" - ] - } - }, - "outputs": { - "getPopCountry.json@28|GBIF_from_polygon>GBIF_from_polygon.yml@10|vector_presence": { - "description": "Text string with the complete path location for the spatial file to the study area's raster image (TIFF format) with the chosen projected coordinate system. Use this file for spatial operations and when biological data coordinates are projected to a particular coordinate system.", - "label": "vector_presence", - "weight": 0, - "type": "application/geo+json" - } - } -} \ No newline at end of file diff --git a/pipelines/GeneticIndicator_VJRP/bb.json b/pipelines/GeneticIndicator_VJRP/bb.json deleted file mode 100644 index d7235cce..00000000 --- a/pipelines/GeneticIndicator_VJRP/bb.json +++ /dev/null @@ -1,221 +0,0 @@ -{ - "nodes": [ - { - "id": "5", - "type": "io", - "position": { - "x": 306.5333251953125, - "y": 254 - }, - "data": { - "descriptionFile": "SHS_pipeline.json" - } - }, - { - "id": "6", - "type": "output", - "position": { - "x": 836.5333251953125, - "y": 288 - }, - "data": { - "label": "Output" - } - }, - { - "id": "7", - "type": "constant", - "position": { - "x": -41.4666748046875, - "y": 258 - }, - "dragHandle": ".dragHandle", - "data": { - "type": "text", - "value": "EPSG:3116" - } - } - ], - "edges": [ - { - "source": "5", - "sourceHandle": "SHI>habitatChange_GFW.yml@67|img_shs_map", - "target": "6", - "targetHandle": null, - "id": "reactflow__edge-5SHI>habitatChange_GFW.yml@67|img_shs_map-6" - }, - { - "source": "7", - "sourceHandle": null, - "target": "5", - "targetHandle": "pipeline@78", - "id": "reactflow__edge-7-5pipeline@78" - } - ], - "inputs": { - "SHS_pipeline.json@5|data>getAreaOfHabitat.yml@80|country_code": { - "description": "Name of the country for the analysis. Check the available countries and regions here: https://www.naturalearthdata.com/downloads/10m-cultural-vectors/", - "label": "country", - "weight": 0, - "type": "text", - "example": "Colombia" - }, - "SHS_pipeline.json@5|pipeline@77": { - "description": "Source of the expert range map for the species. The options are:\nMap of Life (MOL), International union for conservation of nature (IUCN) and range maps from the Ministère de l’Environnement du Québec (QC).\n", - "label": "source of expert range map", - "weight": 1, - "type": "options", - "options": [ - "MOL", - "IUCN", - "QC" - ], - "example": "IUCN" - }, - "SHS_pipeline.json@5|pipeline@76": { - "description": "Scientific name of the species. Multiple species names can be specified, separated with a comma.", - "label": "species", - "weight": 2, - "type": "text[]", - "example": [ - "Myrmecophaga tridactyla" - ] - }, - "SHS_pipeline.json@5|data>getAreaOfHabitat.yml@80|r_range_map": { - "description": "Raster with expected area for the species if choosing option \"Raster\"", - "label": "range map (raster)", - "weight": 3, - "type": "image/tiff;application=geotiff[]", - "example": [ - null - ] - }, - "SHS_pipeline.json@5|data>getAreaOfHabitat.yml@80|study_area": { - "description": "Path to the study area file if you choosing option \"User defined\" for study area option. This file should be a polygon with a .gpkg extension or .shp (in this case do not foget to add the projection file to the folder). ", - "label": "study area", - "weight": 4, - "type": "application/geopackage+sqlite3", - "example": null - }, - "SHS_pipeline.json@5|data>getAreaOfHabitat.yml@80|study_area_opt": { - "description": "Choose the source for the study area either if it should be at a country level and downloaded according to the 'country_code', at region level according to 'region' or a user defined polygon with the borders of the study area.", - "label": "study area option", - "weight": 5, - "type": "options", - "options": [ - "Country", - "Region in Country", - "User defined" - ], - "example": "Country" - }, - "SHS_pipeline.json@5|data>getAreaOfHabitat.yml@80|buff_size": { - "description": "Size of the buffer around the study area. If it is not defined it will be estimated as half of the total width of the study area.", - "label": "buffer for study area", - "weight": 6, - "type": "int", - "example": 0 - }, - "SHS_pipeline.json@5|data>getAreaOfHabitat.yml@80|elev_buffer": { - "description": "Elevation buffer in meters to add (or substract) to the reported species elevation range. Default is zero. Positive values will increase the range in that value in meters and negative values will reduce the range in that value.", - "label": "elevation buffer", - "weight": 7, - "type": "int" - }, - "SHS_pipeline.json@5|data>getAreaOfHabitat.yml@80|elevation_filter": { - "description": "If 'yes' an elevation filter using IUCN information is applied, if 'no' the range map is taken as the area of habitat.", - "label": "filter by elevation", - "weight": 8, - "type": "options", - "options": [ - "Yes", - "No" - ], - "example": "Yes" - }, - "SHS_pipeline.json@5|SHI>habitatChange_GFW.yml@67|max_forest": { - "description": "Maximum tree cover percentage required for each species, based on suitable habitat of the species. Acts as a filter for the Global Forest Watch Data. If not available, use Map of Life Values (e.g. [https://mol.org/species/range/Saguinus_oedipus])", - "label": "max forest", - "weight": 9, - "type": "int[]", - "example": [ - 100 - ] - }, - "SHS_pipeline.json@5|data>getAreaOfHabitat.yml@80|range_map_type": { - "description": "Select type of range map according to the type of the source file: 1) polygon, 2) raster, 3) an intersection between the raster and polygon files.", - "label": "type of range map", - "weight": 10, - "type": "options", - "options": [ - "Polygon", - "Raster", - "Both" - ], - "example": "Polygon" - }, - "SHS_pipeline.json@5|SHI>habitatChange_GFW.yml@67|t_0": { - "description": "Year where the analysis should start. Starts in 2000, check the time interval available for the Global Forest Watch data at https://stac.geobon.org/collections/gfw-lossyear.", - "label": "initial time", - "weight": 11, - "type": "int", - "example": 2000 - }, - "SHS_pipeline.json@5|SHI>habitatChange_GFW.yml@67|time_step": { - "description": "Temporal resolution for analysis given in number of years. To get values for the end year, time step should fit evenly into the given analysis range.", - "label": "time step", - "weight": 12, - "type": "int", - "example": 10 - }, - "SHS_pipeline.json@5|SHI>habitatChange_GFW.yml@67|t_n": { - "description": "Year where the analysis should end (it should be later than Initial time). It should be inside the time interval for the Global Forest Watch data at https://stac.geobon.org/collections/gfw-lossyear.", - "label": "final time", - "weight": 13, - "type": "int", - "example": 2020 - }, - "SHS_pipeline.json@5|SHI>habitatChange_GFW.yml@67|min_forest": { - "description": "Minimum tree cover percentage required for each species, based on suitable habitat of the species. Acts as a filter for the Global Forest Watch Data. If not available, use Map of Life Values (e.g. [https://mol.org/species/range/Saguinus_oedipus])", - "label": "min forest", - "weight": 14, - "type": "int[]", - "example": [ - 50 - ] - }, - "SHS_pipeline.json@5|data>getAreaOfHabitat.yml@80|region": { - "description": "For cases when a more specific administrative boundary (than the country level) is required, a region name can be used. Check the available countries and regions here: https://www.naturalearthdata.com/downloads/10m-cultural-vectors/", - "label": "region", - "weight": 15, - "type": "text" - }, - "SHS_pipeline.json@5|pipeline@79": { - "description": "Spatial resolution (in meters) for the output of the analysis.", - "label": "output spatial resolution", - "weight": 16, - "type": "int", - "example": 1000 - } - }, - "outputs": { - "SHS_pipeline.json@5|SHI>habitatChange_GFW.yml@67|img_shs_map": { - "description": "Figure showing a map with changes in the habitat for the time range for each species.", - "label": "SHS map", - "weight": 0, - "type": "image/png[]" - } - }, - "metadata": { - "name": "Hello World pipeline", - "description": "This very simple pipeline shows how to connect a single script to a single output.\nThe input of the script is left blank, thus becoming a pipeline input.", - "author": [ - { - "name": "Jean-Michel Lord", - "identifier": "https://orcid.org/0009-0007-3826-1125" - } - ], - "license": "MIT", - "external_link": "https://github.com/GEO-BON/biab-2.0" - } -} \ No newline at end of file diff --git a/pipelines/New folder/AA.json b/pipelines/New folder/AA.json deleted file mode 100644 index 81f94799..00000000 --- a/pipelines/New folder/AA.json +++ /dev/null @@ -1,197 +0,0 @@ -{ - "nodes": [ - { - "id": "34", - "type": "io", - "position": { - "x": 618.5333251953125, - "y": -62 - }, - "data": { - "descriptionFile": "SHI_pipeline.json" - } - }, - { - "id": "35", - "type": "output", - "position": { - "x": 1178.5333251953125, - "y": -59 - }, - "data": { - "label": "Output" - } - } - ], - "edges": [ - { - "source": "34", - "sourceHandle": "SHI>habitatChange_GFW.yml@96|df_shs", - "target": "35", - "targetHandle": null, - "id": "reactflow__edge-34SHI>habitatChange_GFW.yml@96|df_shs-35" - } - ], - "inputs": { - "SHI_pipeline.json@34|pipeline@78": { - "description": "Reference system for the area of interest. It can be 1) the Spatial Reference System Identifier (SRID), 2) the authority name (e.g. EPSG) with the SRID or 3) the description of the spatial reference system details (e.g. [https://spatialreference.org/]). If just the SRID is given and the software can not find the reference system try options 2 or 3.", - "label": "spatial reference system", - "weight": 0, - "type": "text", - "example": "EPSG:3116" - }, - "SHI_pipeline.json@34|data>getAreaOfHabitat.yml@80|country_code": { - "description": "Name of the country for the analysis. Check the available countries and regions here: https://www.naturalearthdata.com/downloads/10m-cultural-vectors/", - "label": "country", - "weight": 1, - "type": "text", - "example": "Colombia" - }, - "SHI_pipeline.json@34|pipeline@77": { - "description": "Source of the expert range map for the species. The options are:\nMap of Life (MOL), International union for conservation of nature (IUCN) and range maps from the Ministère de l’Environnement du Québec (QC).\n", - "label": "source of expert range map", - "weight": 2, - "type": "options", - "options": [ - "MOL", - "IUCN", - "QC" - ], - "example": "IUCN" - }, - "SHI_pipeline.json@34|pipeline@76": { - "description": "Scientific name of the species. Multiple species names can be specified, separated with a comma.", - "label": "species", - "weight": 3, - "type": "text[]", - "example": [ - "Myrmecophaga tridactyla", - "Ateles fusciceps" - ] - }, - "SHI_pipeline.json@34|data>getAreaOfHabitat.yml@80|r_range_map": { - "description": "Raster with expected area for the species if choosing option \"Raster\"", - "label": "range map (raster)", - "weight": 4, - "type": "image/tiff;application=geotiff[]", - "example": [ - null - ] - }, - "SHI_pipeline.json@34|SHI>habitatChange_GFW.yml@96|t_0": { - "description": "Year where the analysis should start. Starts in 2000, check the time interval available for the Global Forest Watch data at https://stac.geobon.org/collections/gfw-lossyear.", - "label": "initial time", - "weight": 5, - "type": "int", - "example": 2000 - }, - "SHI_pipeline.json@34|data>getAreaOfHabitat.yml@80|study_area": { - "description": "Path to the study area file if you choosing option \"User defined\" for study area option. This file should be a polygon with a .gpkg extension or .shp (in this case do not foget to add the projection file to the folder). ", - "label": "study area", - "weight": 6, - "type": "application/geopackage+sqlite3", - "example": null - }, - "SHI_pipeline.json@34|data>getAreaOfHabitat.yml@80|study_area_opt": { - "description": "Choose the source for the study area either if it should be at a country level and downloaded according to the 'country_code', at region level according to 'region' or a user defined polygon with the borders of the study area.", - "label": "study area option", - "weight": 7, - "type": "options", - "options": [ - "Country", - "Region in Country", - "User defined" - ], - "example": "Country" - }, - "SHI_pipeline.json@34|SHI>habitatChange_GFW.yml@96|t_n": { - "description": "Year where the analysis should end (it should be later than Initial time). It should be inside the time interval for the Global Forest Watch data at https://stac.geobon.org/collections/gfw-lossyear.", - "label": "final time", - "weight": 8, - "type": "int", - "example": 2020 - }, - "SHI_pipeline.json@34|data>getAreaOfHabitat.yml@80|buff_size": { - "description": "Size of the buffer around the study area. If it is not defined it will be estimated as half of the total width of the study area.", - "label": "buffer for study area", - "weight": 9, - "type": "int", - "example": 0 - }, - "SHI_pipeline.json@34|SHI>habitatChange_GFW.yml@96|max_forest": { - "description": "Maximum tree cover percentage required for each species, based on suitable habitat of the species. Acts as a filter for the Global Forest Watch Data. If not available, use Map of Life Values (e.g. [https://mol.org/species/range/Myrmecophaga-tridactyla]). For multiple species, input in the same order as input in species and separate with a comma.", - "label": "max forest", - "weight": 10, - "type": "int[]", - "example": [ - 100 - ] - }, - "SHI_pipeline.json@34|data>getAreaOfHabitat.yml@80|elev_buffer": { - "description": "Elevation buffer in meters to add (or substract) to the reported species elevation range. Default is zero. Positive values will increase the range in that value in meters and negative values will reduce the range in that value.", - "label": "elevation buffer", - "weight": 11, - "type": "int" - }, - "SHI_pipeline.json@34|data>getAreaOfHabitat.yml@80|elevation_filter": { - "description": "If 'yes' an elevation filter using IUCN information is applied, if 'no' the range map is taken as the area of habitat.", - "label": "filter by elevation", - "weight": 12, - "type": "options", - "options": [ - "Yes", - "No" - ], - "example": "Yes" - }, - "SHI_pipeline.json@34|SHI>habitatChange_GFW.yml@96|time_step": { - "description": "Temporal resolution for analysis given in number of years. To get values for the end year, time step should fit evenly into the given analysis range.", - "label": "time step", - "weight": 13, - "type": "int", - "example": 10 - }, - "SHI_pipeline.json@34|data>getAreaOfHabitat.yml@80|range_map_type": { - "description": "Select type of range map according to the type of the source file: 1) polygon, 2) raster, 3) an intersection between the raster and polygon files.", - "label": "type of range map", - "weight": 14, - "type": "options", - "options": [ - "Polygon", - "Raster", - "Both" - ], - "example": "Polygon" - }, - "SHI_pipeline.json@34|SHI>habitatChange_GFW.yml@96|min_forest": { - "description": "Minimum tree cover percentage required for each species, based on suitable habitat of the species. Acts as a filter for the Global Forest Watch Data. If not available, use Map of Life Values (e.g. [https://mol.org/species/range/Myrmecophaga-tridactyla]). For multiple species, input in the same order as input in species and separate with a comma.", - "label": "min forest", - "weight": 15, - "type": "int[]", - "example": [ - 0 - ] - }, - "SHI_pipeline.json@34|data>getAreaOfHabitat.yml@80|region": { - "description": "For cases when a more specific administrative boundary (than the country level) is required, a region name can be used. Check the available countries and regions here: https://www.naturalearthdata.com/downloads/10m-cultural-vectors/", - "label": "region", - "weight": 16, - "type": "text" - }, - "SHI_pipeline.json@34|pipeline@79": { - "description": "Spatial resolution (in meters) for the output of the analysis.", - "label": "output spatial resolution", - "weight": 17, - "type": "int", - "example": 1000 - } - }, - "outputs": { - "SHI_pipeline.json@34|SHI>habitatChange_GFW.yml@96|df_shs": { - "description": "A TSV (Tab Separated Values) file containing Area Score, Connectivity Score and SHS by time step for each species. Percentage of change, 100% being equal to the reference year.", - "label": "SHS table", - "weight": 0, - "type": "text/tab-separated-values[]" - } - } -} \ No newline at end of file diff --git a/pipelines/qq.json b/pipelines/qq.json deleted file mode 100644 index a63c148b..00000000 --- a/pipelines/qq.json +++ /dev/null @@ -1,65 +0,0 @@ -{ - "nodes": [ - { - "id": "0", - "type": "io", - "position": { - "x": 345.5333251953125, - "y": 234.3333282470703 - }, - "data": { - "descriptionFile": "Pops_from_DispDist>Pops_from_DispDist.yml" - } - }, - { - "id": "1", - "type": "output", - "position": { - "x": 882.5333251953125, - "y": 234.3333282470703 - }, - "data": { - "label": "Output" - } - } - ], - "edges": [ - { - "source": "0", - "sourceHandle": "distance_map", - "target": "1", - "targetHandle": null, - "id": "reactflow__edge-0distance_map-1" - } - ], - "inputs": { - "Pops_from_DispDist>Pops_from_DispDist.yml@0|grid_map": { - "description": "Map used as the study area for estimating population polygon hypotheses (e.g., study area, species distribution model).", - "label": "grid_map", - "type": "image/tiff;application=geotiff", - "example": "/scripts/Pops_from_DispDist/input/raster_study_area_path.tif", - "weight": 0 - }, - "Pops_from_DispDist>Pops_from_DispDist.yml@0|occ_points": { - "description": "Occurrence points of the species within the study area, used to calculate the distance map.", - "label": "occ_points", - "type": "application/geo+json", - "example": "/scripts/Pops_from_DispDist/input/vector_presence_path.GeoJSON", - "weight": 1 - }, - "Pops_from_DispDist>Pops_from_DispDist.yml@0|DispersalDistance_m": { - "description": "Maximum known dispersal distance of the species in meters. If available, it is added as an additional hypothesis for defining population polygons; otherwise, hypotheses are estimated based on quantiles from the distance map values.", - "label": "DispersalDistance_m", - "type": "int", - "weight": 2 - } - }, - "outputs": { - "Pops_from_DispDist>Pops_from_DispDist.yml@0|distance_map": { - "description": "Map showing the calculated distances from occurrence points within the study area.", - "label": "distance_map", - "type": "image/tiff;application=geotiff", - "weight": 0 - } - } -} \ No newline at end of file diff --git a/scripts/Pops_from_DispDist/README.Rmd b/scripts/Pops_from_DispDist/README.Rmd index f8ba07de..2898531d 100644 --- a/scripts/Pops_from_DispDist/README.Rmd +++ b/scripts/Pops_from_DispDist/README.Rmd @@ -121,10 +121,10 @@ data_hypothesis<- read.csv(file.path(file.path(dirname(this.path::this.path()), knitr::kable(data_hypothesis) ``` -### Estimate discrete populations hypotesis +### Estimate discrete populations hypothesis For each dispersal threshold `data_hypothesis`, the script generates hypotheses about potential discrete population areas. A cutoff is created around all cells whose distance to the occurrence point is less than or equal to the threshold. These areas are converted into polygons, which are then grouped based on geographic proximity to identify potential discrete populations. Each polygon generated from the threshold is assigned an identifier, classifying it as part of a distinct population. ```{r, eval=F, echo=T, results='hide', warning= F, message = F} -### Estimate discrete populations hypotesis #### +### Estimate discrete populations hypothesis #### list_hypothesis<- pbapply::pblapply(seq_along(list_thresholds), function(i){ threshold <- list_thresholds[i] # @@ -168,7 +168,7 @@ table_hypothesis<- read.csv(file.path(file.path(dirname(this.path::this.path()), knitr::kable(table_hypothesis) ``` -### Plot discrete populations hypotesis +### Plot discrete populations hypothesis Graphs `plot_results` are generated to illustrate how the discrete populations are distributed within the study area based on the different distance thresholds. Each graph displays the polygons corresponding to the populations, distinguished by a color scale. The titles of the graphs indicate the distance threshold applied to each hypothesis. ```{r, eval=F, echo=T, results='hide', warning= F, message = F} @@ -182,7 +182,7 @@ coltab(list_hypothesis_tifcol[[i]]) <- data.frame(values= seq(discrete_vals), co } list_hypothesis_tifcol<- list_hypothesis_tifcol %>% setNames(names(list_hypothesis_tif)) -### Plot discrete populations hypotesis #### +### Plot discrete populations hypothesis #### plot_results<- pbapply::pblapply(list_hypothesis_sf, function(x) { ggplot()+geom_sf(data= x, aes(fill= pop_name))+theme_void()+ scale_fill_manual(values = cols_vals) + diff --git a/scripts/Pops_from_DispDist/README.md b/scripts/Pops_from_DispDist/README.md index ca6e9424..9f2745bd 100644 --- a/scripts/Pops_from_DispDist/README.md +++ b/scripts/Pops_from_DispDist/README.md @@ -13,7 +13,8 @@ output: Population Polygons Using Dispersal Thresholds from Distance Maps ================ -This `box script` estimates discrete population polygons using dispersal + +This `box` estimates discrete population polygons using dispersal thresholds based on distance maps generated from species occurrence points within a predefined grid map, such as a study area or species distribution model. It calculates a distance map from the occurrence @@ -40,13 +41,12 @@ threshold hypotheses derived from distance maps. - [Estimate Distance Density Map](#estimate-distance-density-map) - [Estimate Distance tresholds](#estimate-distance-tresholds) - [Estimate discrete populations - hypotesis](#estimate-discrete-populations-hypotesis) + hypothesis](#estimate-discrete-populations-hypothesis) - [Summary table](#summary-table) - [Plot discrete populations - hypotesis](#plot-discrete-populations-hypotesis) + hypothesis](#plot-discrete-populations-hypothesis) - [Export results](#export-results) - ## inputs - ***`grid_map`***: Map used as the study area for estimating population @@ -208,7 +208,7 @@ print(data_hypothesis) | 90% | 9 | 276875 | | 100% | 10 | 507923 | -### Estimate discrete populations hypotesis +### Estimate discrete populations hypothesis For each dispersal threshold `data_hypothesis`, the script generates hypotheses about potential discrete population areas. A cutoff is @@ -220,7 +220,7 @@ threshold is assigned an identifier, classifying it as part of a distinct population. ``` r -### Estimate discrete populations hypotesis #### +### Estimate discrete populations hypothesis #### list_hypothesis<- pbapply::pblapply(seq_along(list_thresholds), function(i){ threshold <- list_thresholds[i] # @@ -276,7 +276,7 @@ print(table_hypothesis) | 9 | 276875 | 1 | | 10 | 507923 | 1 | -### Plot discrete populations hypotesis +### Plot discrete populations hypothesis Graphs `plot_results` are generated to illustrate how the discrete populations are distributed within the study area based on the different @@ -295,7 +295,7 @@ coltab(list_hypothesis_tifcol[[i]]) <- data.frame(values= seq(discrete_vals), co } list_hypothesis_tifcol<- list_hypothesis_tifcol %>% setNames(names(list_hypothesis_tif)) -### Plot discrete populations hypotesis #### +### Plot discrete populations hypothesis #### plot_results<- pbapply::pblapply(list_hypothesis_sf, function(x) { ggplot()+geom_sf(data= x, aes(fill= pop_name))+theme_void()+ scale_fill_manual(values = cols_vals) +