{
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  "Title": "Detailed Development of Ecological Niche Models",
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  "Authors@R": "c(\nperson(\"Weverton C. F.\", \"Trindade\", email = \"wevertonf1993@gmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-2045-4555\")),\nperson(\"Luis F.\", \"Arias-Giraldo\", email = \"lfarias.giraldo@gmail.com\",\nrole = \"aut\", comment = c(ORCID = \"0000-0003-4861-8064\")),\nperson(\"Luis\", \"Osorio-Olvera\", email = \"luismurao@gmail.com\", role = \"aut\",\ncomment = c(ORCID = \"0000-0003-0701-5398\")),\nperson(\"A. Townsend\", \"Peterson\", email = \"town@ku.edu\", role = \"aut\",\ncomment = c(ORCID = \"0000-0003-0243-2379\")),\nperson(\"Marlon E.\", \"Cobos\", email = \"manubio13@gmail.com\", role = c(\"aut\"),\ncomment = c(ORCID = \"0000-0002-2611-1767\")))",
  "Maintainer": "Weverton C. F. Trindade <wevertonf1993@gmail.com>",
  "BugReports": "https://github.com/marlonecobos/kuenm2/issues",
  "Date": "2026-04-20",
  "Description": "A new set of tools to help with the development of\ndetailed ecological niche models using multiple algorithms.\nPre-modeling analyses and explorations can be done to prepare\ndata. Model calibration (model selection) can be done by\ncreating and testing models with several parameter\ncombinations. Handy options for producing final models with\ntransfers are included. Other tools to assess extrapolation\nrisks and variability in model transfers are also available.\nMethodological and theoretical basis for the methods\nimplemented here can be found in: Peterson et al. (2011)\n<https://www.degruyter.com/princetonup/view/title/506966>,\nRadosavljevic and Anderson (2014) <doi:10.1111/jbi.12227>,\nPeterson et al. (2018) <doi:10.1111/nyas.13873>, Cobos et al.\n(2019) <doi:10.7717/peerj.6281>, Alkishe et al. (2020)\n<doi:10.1016/j.pecon.2020.03.002>, Machado-Stredel et al.\n(2021) <doi:10.21425/F5FBG48814>, Arias-Giraldo and Cobos\n(2024) <doi:10.17161/bi.v18i.21742>, Cobos et al. (2024)\n<doi:10.17161/bi.v18i.21742>.",
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  "Language": "en-US",
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  "Repository": "https://marlonecobos.r-universe.dev",
  "Date/Publication": "2026-05-31 20:51:13 UTC",
  "RemoteUrl": "https://github.com/marlonecobos/kuenm2",
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  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-31 22:27:30 UTC",
    "User": "root"
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  "Author": "Weverton C. F. Trindade [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-2045-4555>),\nLuis F. Arias-Giraldo [aut] (ORCID:\n<https://orcid.org/0000-0003-4861-8064>),\nLuis Osorio-Olvera [aut] (ORCID:\n<https://orcid.org/0000-0003-0701-5398>),\nA. Townsend Peterson [aut] (ORCID:\n<https://orcid.org/0000-0003-0243-2379>),\nMarlon E. Cobos [aut] (ORCID: <https://orcid.org/0000-0002-2611-1767>)",
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    "all_response_curves",
    "binarize_changes",
    "bivariate_response",
    "calibration",
    "colors_for_changes",
    "detect_concave",
    "explore_calibration_hist",
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    "explore_partition_extrapolation",
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    "extract_var_from_formulas",
    "filter_decimal_precision",
    "fit_selected",
    "glm_mx",
    "glmnet_mx",
    "import_results",
    "independent_evaluation",
    "initial_cleaning",
    "move_2closest_cell",
    "organize_for_projection",
    "organize_future_worldclim",
    "partial_roc",
    "partition_response_curves",
    "perform_pca",
    "plot_calibration_hist",
    "plot_explore_partition",
    "plot_importance",
    "predict_selected",
    "predict.glmnet_mx",
    "prediction_changes",
    "prepare_data",
    "prepare_projection",
    "prepare_user_data",
    "project_selected",
    "projection_changes",
    "projection_mop",
    "projection_variability",
    "remove_cell_duplicates",
    "remove_corrdinates_00",
    "remove_duplicates",
    "remove_missing",
    "response_curve",
    "select_models",
    "single_mop",
    "sort_columns",
    "variable_importance"
  ],
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      "title": "Calibration Results (glm)",
      "object": "calib_results_glm",
      "class": [
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      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "calib_results_maxnet",
      "title": "Calibration Results (Maxnet)",
      "object": "calib_results_maxnet",
      "class": [
        "calibration_results"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
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      "title": "Spatial Blocks from ENMeval",
      "object": "enmeval_block",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
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      "object": "fitted_model_chelsa",
      "class": [
        "fitted_models"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
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      "title": "Fitted model with concave curves",
      "object": "fitted_model_concave",
      "class": [
        "fitted_models"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
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      "title": "Fitted model with glm algorithm",
      "object": "fitted_model_glm",
      "class": [
        "fitted_models"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
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      "title": "Fitted model with maxnet algorithm",
      "object": "fitted_model_maxnet",
      "class": [
        "fitted_models"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
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      "object": "flexsdm_block",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
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      "title": "Discrete palettes based on pals R package",
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      "class": [
        "list"
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      "fields": [],
      "table": false,
      "tojson": true
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      "title": "Independent Species Occurrence",
      "object": "new_occ",
      "class": [
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        "data.frame"
      ],
      "fields": [
        "species",
        "x",
        "y"
      ],
      "rows": 82,
      "table": true,
      "tojson": true
    },
    {
      "name": "occ_data",
      "title": "Species Occurrence",
      "object": "occ_data",
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      ],
      "fields": [
        "species",
        "x",
        "y"
      ],
      "rows": 51,
      "table": true,
      "tojson": true
    },
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      "title": "Species Occurrence with Erroneous Records",
      "object": "occ_data_noclean",
      "class": [
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      "fields": [
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        "x",
        "y"
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      "table": true,
      "tojson": true
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    {
      "name": "sp_swd",
      "title": "Prepared Data for maxnet models",
      "object": "sp_swd",
      "class": [
        "prepared_data"
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      "fields": [],
      "table": false,
      "tojson": false
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      "object": "sp_swd_glm",
      "class": [
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      "fields": [],
      "table": false,
      "tojson": false
    },
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      "title": "Prepared data with spatial blocks created with ENMeval",
      "object": "swd_spatial_block",
      "class": [
        "prepared_data"
      ],
      "fields": [],
      "table": false,
      "tojson": false
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    {
      "name": "user_data",
      "title": "User Custom Calibration Data",
      "object": "user_data",
      "class": [
        "data.frame"
      ],
      "fields": [
        "pr_bg",
        "bio_1",
        "bio_7",
        "bio_12",
        "bio_15",
        "SoilType"
      ],
      "rows": 527,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "kuenm2-package",
      "title": "kuenm2: Detailed Development of Ecological Niche Models",
      "topics": [
        "kuenm2-package",
        "kuenm2"
      ]
    },
    {
      "page": "advanced_cleaning",
      "title": "Advanced occurrence data cleaning",
      "topics": [
        "advanced_cleaning",
        "move_2closest_cell",
        "remove_cell_duplicates"
      ]
    },
    {
      "page": "bias",
      "title": "Example Bias File",
      "topics": [
        "bias"
      ]
    },
    {
      "page": "binarize_changes",
      "title": "Binarize changes based on the agreement among GCMs",
      "topics": [
        "binarize_changes"
      ]
    },
    {
      "page": "bivariate_response",
      "title": "Bivariate response plot for fitted models",
      "topics": [
        "bivariate_response"
      ]
    },
    {
      "page": "calib_results_glm",
      "title": "Calibration Results (glm)",
      "topics": [
        "calib_results_glm"
      ]
    },
    {
      "page": "calib_results_maxnet",
      "title": "Calibration Results (Maxnet)",
      "topics": [
        "calib_results_maxnet"
      ]
    },
    {
      "page": "calibration",
      "title": "Fitting and evaluation of models, and selection of the best ones",
      "topics": [
        "calibration"
      ]
    },
    {
      "page": "chelsa_current",
      "title": "SpatRaster Representing present-day Conditions (CHELSA)",
      "topics": [
        "chelsa_current"
      ]
    },
    {
      "page": "chelsa_lgm_ccsm4",
      "title": "SpatRaster Representing LGM Conditions (GCM: CCSM4)",
      "topics": [
        "chelsa_lgm_ccsm4"
      ]
    },
    {
      "page": "chelsa_lgm_cnrm_cm5",
      "title": "SpatRaster Representing LGM Conditions (GCM: CNRM-CM5)",
      "topics": [
        "chelsa_lgm_cnrm_cm5"
      ]
    },
    {
      "page": "chelsa_lgm_fgoals_g2",
      "title": "SpatRaster Representing LGM Conditions (GCM: FGOALS-g2)",
      "topics": [
        "chelsa_lgm_fgoals_g2"
      ]
    },
    {
      "page": "chelsa_lgm_ipsl",
      "title": "SpatRaster Representing LGM Conditions (GCM: IPSL-CM5A-LR)",
      "topics": [
        "chelsa_lgm_ipsl"
      ]
    },
    {
      "page": "chelsa_lgm_miroc",
      "title": "SpatRaster Representing LGM Conditions (GCM: MIROC-ESM)",
      "topics": [
        "chelsa_lgm_miroc"
      ]
    },
    {
      "page": "chelsa_lgm_mpi",
      "title": "SpatRaster Representing LGM Conditions (GCM: MPI-ESM-P)",
      "topics": [
        "chelsa_lgm_mpi"
      ]
    },
    {
      "page": "chelsa_lgm_mri",
      "title": "SpatRaster Representing LGM Conditions (GCM: MRI-CGCM3)",
      "topics": [
        "chelsa_lgm_mri"
      ]
    },
    {
      "page": "colors_for_changes",
      "title": "Set Colors for Change Maps",
      "topics": [
        "colors_for_changes"
      ]
    },
    {
      "page": "detect_concave",
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