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+ # A joint model for the estimation of species distributions and environmental characteristics from point-referenced data
+
+This repository contains the data, codes, and results for our paper. 
+
+Abstract:
+> Predicting and explaining species occurrence using environmental characteristics is essential for nature conservation and management, especially for rare species that are under threat from climate change, acidification and eutrophication. Species distribution models consider species occurrence as the dependent variable and environmental conditions as the independent variables. Suitable conditions are estimated based on a sample of species observations, where one assumes that the underlying environmental conditions are known. This is not always the case, as environmental variables at broad spatial scales are regularly extrapolated from point-referenced data. A two-stage approach is then used, where the missing environmental variables are predicted before a species distribution model is fitted. However, treating the predicted independent variables as accurate surveys of the environmental conditions at a specific point does not take into account prediction uncertainty or the fact that the species occurrence may inform us about their values. To address both issues, we present a joint hierarchical Bayesian model where models for the environmental variables, rather than a set of predicted values, are input to the species distribution model. All models are fitted together based only on point-referenced observations in the data set, which results in a correct propagation of uncertainty. This produces study area-wide maps for all variables and associations that differ from the two-stage approach.
+
+The codes compare the two-stage model and the joint model in identical interpretation and prediction problems.
+
+ ## Data curation
+
+The file **paper_data.Rmd** describes the curation and combination steps of the two primary data sets:
+ - The National Flora Monitoring Network - Environment and Nature Quality (LMF-M\&N) [link](https://www.rivm.nl/publicaties/ontwerp-landelijk-meetnet-flora-milieu-natuurkwaliteit-lmf-mn)
+ - Wageningen University \& Research abiotic factors [link](https://library.wur.nl/WebQuery/wurpubs/reports/367477)
+
+These data sets are not directly available to download by public but may be obtained for research from their respective authors. 
+
+These data sets are linked into additional spatial open data sets in the Netherlands: 
+- Provinces (Bestuurlijke Gebieden) [link](https://www.pdok.nl/geo-services/-/article/bestuurlijke-gebieden)
+- FGR regions (Fysisch Geografische Regio’s) [link](https://www.pdok.nl/introductie/-/article/fysisch-geografische-regio-s)
+- Landuse (Bestand Bodemgebruik) [link](https://www.pdok.nl/-/bestand-bodemgebruik-2015-van-cbs-nu-bij-pdok)
+- Soiltype (Grondsoorten) [link](http://www.geodesk.nl/Grondsoorten.htm)
+
+This results in the following files, which are required to run the experiments:
+- **data_paper/data_plots.csv** publishes a subset of the data used in our paper with the author's permission. 
+- **data_paper/data_grid.csv** contains the Netherlands grid for which predictions were made.
+- **data_paper/NL.shp** contains a shapefile for the land boundary of the Netherlands.
+
+## Codes
+
+The file **paper_codes.Rmd** contains the data set statistics, experiments, and visualization of the results.
+
+The experiments take a very long time to run, so we provide an alternative [LSF cluster](https://www.ibm.com/support/pages/what-lsf-cluster) implementation in the folder **lsf/**.
+See the file **lsf/run.sh** for submission of the jobs and combination of the results, where each job fits a species specific SDM to a given data set.
+
+The results from running the experiments are saved in the following files:
+- **data_paper/results.csv** contains the model parameters and predictions for the 50 species in the entire data set.
+- **data_paper/predictions_[province/fgr].csv** contains the model predictions for the 50 species in the validation data.
+- **data_paper/prevalences_[province/fgr].csv** contains posterior prevalences for the 50 species in the validation data.
+
+These files are sufficient to reproduce all of the tables and visualizations in the paper.
+
diff --git a/data_paper/FGR.ipynb b/data_paper/FGR.ipynb
diff --git a/data_paper/Fysisch_geografische_regios_ENGLISH.xlsx b/data_paper/Fysisch_geografische_regios_ENGLISH.xlsx
diff --git a/data_paper/LMF_Fysisch_geografische_regios_ENGLISH.xlsx b/data_paper/LMF_Fysisch_geografische_regios_ENGLISH.xlsx
diff --git a/data_paper/NL.dbf b/data_paper/NL.dbf
diff --git a/data_paper/NL.prj b/data_paper/NL.prj
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+PROJCS["RD_New",GEOGCS["GCS_Amersfoort",DATUM["D_Amersfoort",SPHEROID["Bessel_1841",6377397.155,299.1528128]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Double_Stereographic"],PARAMETER["False_Easting",155000.0],PARAMETER["False_Northing",463000.0],PARAMETER["Central_Meridian",5.38763888888889],PARAMETER["Scale_Factor",0.9999079],PARAMETER["Latitude_Of_Origin",52.1561605555556],UNIT["Meter",1.0]]
diff --git a/data_paper/NL.shp b/data_paper/NL.shp
diff --git a/data_paper/NL.shx b/data_paper/NL.shx
diff --git a/data_paper/chosen_species.csv b/data_paper/chosen_species.csv
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+"Nednaam","Wetnaam","n"
+"Gestreepte witbol","Holcus lanatus",4104
+"Zomereik","Quercus robur",3938
+"Grote brandnetel","Urtica dioica",3137
+"Pitrus","Juncus effusus",2284
+"Brede stekelvaren","Dryopteris dilatata",2080
+"Gewoon reukgras","Anthoxanthum odoratum",1882
+"Zachte berk","Betula pubescens",1844
+"Bochtige smele","Deschampsia flexuosa",1785
+"Ruwe berk","Betula pendula",1566
+"Engels raaigras","Lolium perenne",1434
+"Smalle stekelvaren","Dryopteris carthusiana",1297
+"Watermunt","Mentha aquatica",1199
+"Es","Fraxinus excelsior",1171
+"Gewone dophei","Erica tetralix",1015
+"Hulst","Ilex aquifolium",958
+"Jakobskruiskruid_Duinkruiskruid","Jacobaea vulgaris",955
+"Duizendblad","Achillea millefolium",915
+"Amerikaanse eik","Quercus rubra",702
+"Hazelaar","Corylus avellana",620
+"Gewone vogelkers","Prunus padus",580
+"Kruipwilg","Salix repens",528
+"Tweerijige zegge","Carex disticha",469
+"Veenpluis","Eriophorum angustifolium",432
+"Spaanse aak","Acer campestre",428
+"Zandstruisgras","Agrostis vinealis",387
+"Peen","Daucus carota",304
+"Kraaihei","Empetrum nigrum",302
+"Ruwe smele","Deschampsia cespitosa",288
+"Ratelpopulier","Populus tremula",238
+"Zoete kers","Prunus avium",209
+"Knolboterbloem","Ranunculus bulbosus",195
+"Kleine zonnedauw","Drosera intermedia",169
+"Bosanemoon","Anemone nemorosa",130
+"Muurpeper","Sedum acre",111
+"Wilde gagel","Myrica gale",105
+"Moeraswespenorchis","Epipactis palustris",102
+"Gevlekte orchis_Bosorchis","Dactylorhiza maculata",101
+"Brede wespenorchis_Duinwespenorchis","Epipactis helleborine",96
+"Dalkruid","Maianthemum bifolium",91
+"Witte klaverzuring","Oxalis acetosella",90
+"Parnassia","Parnassia palustris",87
+"Eenarig wollegras","Eriophorum vaginatum",81
+"Kleine ratelaar","Rhinanthus minor",77
+"Bosaardbei","Fragaria vesca",63
+"Tengere rus","Juncus tenuis",59
+"Kleine veenbes","Vaccinium oxycoccos",57
+"Bevertjes","Briza media",40
+"Gewoon kweldergras","Puccinellia maritima",37
+"Asperge_Liggende asperge","Asparagus officinalis",31
+"Slanke sleutelbloem","Primula elatior",24