flexsdm: An r package for supporting a comprehensive and flexible species distribution modelling workflow

Autores
Velazco, Santiago José Elías; Rose, Miranda Brooke; de Andrade, André Felipe Alves; Minoli, Ignacio; Franklin, Janet
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Species distribution models (SDM) are widely used in diverse research areas because of their simple data requirements and application versatility. However, SDM outcomes are sensitive to data input and methodological choices. Such sensitivity and diverse applications mean that flexibility is necessary to create SDMs with tailored protocols for a given set of data and model use. We introduce the r package flexsdm for supporting flexible species distribution modelling workflows. flexsdm functions and their arguments serve as building blocks to construct a specific modelling protocol for user's needs. The main flexsdm features are modelling flexibility, integration with other modelling tools, simplicity of the objects returned and function speed. As an illustration, we used flexsdm to define a complete workflow for California red fir Abies magnifica. This package provides modelling flexibility by incorporating comprehensive tools structured in three steps: (a) The Pre-modelling functions that prepare input, for example, sampling bias correction, sampling pseudo-absences and background points, data partitioning, and reducing collinearity in predictors. (b) The Modelling functions allow fitting and evaluating different modelling approaches, including individual algorithms, tuned models, ensembles of small models and ensemble models. (c) The Post-modelling functions include tools related to models' predictions, interpolation and overprediction correction. Because flexsdm comprises a large part of the SDM process, from outlier detection to overprediction correction, flexsdm users can delineate partial or complete workflows based on the combination functions to meet specific modelling needs.
Fil: Velazco, Santiago José Elías. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina. University of California; Estados Unidos. Universidade Federal da Integração Latino-Americana; Brasil
Fil: Rose, Miranda Brooke. University of California; Estados Unidos
Fil: de Andrade, André Felipe Alves. Universidade Federal de Goiás; Brasil
Fil: Minoli, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina
Fil: Franklin, Janet. University of California; Estados Unidos
Materia
ECOINFORMATICS
ECOLOGICAL NICHE MODELLING
ENSEMBLE MODELLING
MODEL FIT FOR PURPOSE
MODEL TUNING
SPATIAL ECOLOGY
SPATIALLY STRUCTURED VALIDATION
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/215195
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/215195
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling flexsdm: An r package for supporting a comprehensive and flexible species distribution modelling workflowVelazco, Santiago José ElíasRose, Miranda Brookede Andrade, André Felipe AlvesMinoli, IgnacioFranklin, JanetECOINFORMATICSECOLOGICAL NICHE MODELLINGENSEMBLE MODELLINGMODEL FIT FOR PURPOSEMODEL TUNINGSPATIAL ECOLOGYSPATIALLY STRUCTURED VALIDATIONhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Species distribution models (SDM) are widely used in diverse research areas because of their simple data requirements and application versatility. However, SDM outcomes are sensitive to data input and methodological choices. Such sensitivity and diverse applications mean that flexibility is necessary to create SDMs with tailored protocols for a given set of data and model use. We introduce the r package flexsdm for supporting flexible species distribution modelling workflows. flexsdm functions and their arguments serve as building blocks to construct a specific modelling protocol for user's needs. The main flexsdm features are modelling flexibility, integration with other modelling tools, simplicity of the objects returned and function speed. As an illustration, we used flexsdm to define a complete workflow for California red fir Abies magnifica. This package provides modelling flexibility by incorporating comprehensive tools structured in three steps: (a) The Pre-modelling functions that prepare input, for example, sampling bias correction, sampling pseudo-absences and background points, data partitioning, and reducing collinearity in predictors. (b) The Modelling functions allow fitting and evaluating different modelling approaches, including individual algorithms, tuned models, ensembles of small models and ensemble models. (c) The Post-modelling functions include tools related to models' predictions, interpolation and overprediction correction. Because flexsdm comprises a large part of the SDM process, from outlier detection to overprediction correction, flexsdm users can delineate partial or complete workflows based on the combination functions to meet specific modelling needs.Fil: Velazco, Santiago José Elías. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina. University of California; Estados Unidos. Universidade Federal da Integração Latino-Americana; BrasilFil: Rose, Miranda Brooke. University of California; Estados UnidosFil: de Andrade, André Felipe Alves. Universidade Federal de Goiás; BrasilFil: Minoli, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Franklin, Janet. University of California; Estados UnidosBritish Ecological Society2022-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/215195Velazco, Santiago José Elías; Rose, Miranda Brooke; de Andrade, André Felipe Alves; Minoli, Ignacio; Franklin, Janet; flexsdm: An r package for supporting a comprehensive and flexible species distribution modelling workflow; British Ecological Society; Methods in Ecology and Evolution; 13; 8; 8-2022; 1661-16692041-210XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.13874info:eu-repo/semantics/altIdentifier/doi/10.1111/2041-210X.13874info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:39:38Zoai:ri.conicet.gov.ar:11336/215195instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:39:38.41CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv flexsdm: An r package for supporting a comprehensive and flexible species distribution modelling workflow
title flexsdm: An r package for supporting a comprehensive and flexible species distribution modelling workflow
spellingShingle flexsdm: An r package for supporting a comprehensive and flexible species distribution modelling workflow
Velazco, Santiago José Elías
ECOINFORMATICS
ECOLOGICAL NICHE MODELLING
ENSEMBLE MODELLING
MODEL FIT FOR PURPOSE
MODEL TUNING
SPATIAL ECOLOGY
SPATIALLY STRUCTURED VALIDATION
title_short flexsdm: An r package for supporting a comprehensive and flexible species distribution modelling workflow
title_full flexsdm: An r package for supporting a comprehensive and flexible species distribution modelling workflow
title_fullStr flexsdm: An r package for supporting a comprehensive and flexible species distribution modelling workflow
title_full_unstemmed flexsdm: An r package for supporting a comprehensive and flexible species distribution modelling workflow
title_sort flexsdm: An r package for supporting a comprehensive and flexible species distribution modelling workflow
dc.creator.none.fl_str_mv Velazco, Santiago José Elías
Rose, Miranda Brooke
de Andrade, André Felipe Alves
Minoli, Ignacio
Franklin, Janet
author Velazco, Santiago José Elías
author_facet Velazco, Santiago José Elías
Rose, Miranda Brooke
de Andrade, André Felipe Alves
Minoli, Ignacio
Franklin, Janet
author_role author
author2 Rose, Miranda Brooke
de Andrade, André Felipe Alves
Minoli, Ignacio
Franklin, Janet
author2_role author
author
author
author
dc.subject.none.fl_str_mv ECOINFORMATICS
ECOLOGICAL NICHE MODELLING
ENSEMBLE MODELLING
MODEL FIT FOR PURPOSE
MODEL TUNING
SPATIAL ECOLOGY
SPATIALLY STRUCTURED VALIDATION
topic ECOINFORMATICS
ECOLOGICAL NICHE MODELLING
ENSEMBLE MODELLING
MODEL FIT FOR PURPOSE
MODEL TUNING
SPATIAL ECOLOGY
SPATIALLY STRUCTURED VALIDATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Species distribution models (SDM) are widely used in diverse research areas because of their simple data requirements and application versatility. However, SDM outcomes are sensitive to data input and methodological choices. Such sensitivity and diverse applications mean that flexibility is necessary to create SDMs with tailored protocols for a given set of data and model use. We introduce the r package flexsdm for supporting flexible species distribution modelling workflows. flexsdm functions and their arguments serve as building blocks to construct a specific modelling protocol for user's needs. The main flexsdm features are modelling flexibility, integration with other modelling tools, simplicity of the objects returned and function speed. As an illustration, we used flexsdm to define a complete workflow for California red fir Abies magnifica. This package provides modelling flexibility by incorporating comprehensive tools structured in three steps: (a) The Pre-modelling functions that prepare input, for example, sampling bias correction, sampling pseudo-absences and background points, data partitioning, and reducing collinearity in predictors. (b) The Modelling functions allow fitting and evaluating different modelling approaches, including individual algorithms, tuned models, ensembles of small models and ensemble models. (c) The Post-modelling functions include tools related to models' predictions, interpolation and overprediction correction. Because flexsdm comprises a large part of the SDM process, from outlier detection to overprediction correction, flexsdm users can delineate partial or complete workflows based on the combination functions to meet specific modelling needs.
Fil: Velazco, Santiago José Elías. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina. University of California; Estados Unidos. Universidade Federal da Integração Latino-Americana; Brasil
Fil: Rose, Miranda Brooke. University of California; Estados Unidos
Fil: de Andrade, André Felipe Alves. Universidade Federal de Goiás; Brasil
Fil: Minoli, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina
Fil: Franklin, Janet. University of California; Estados Unidos
description Species distribution models (SDM) are widely used in diverse research areas because of their simple data requirements and application versatility. However, SDM outcomes are sensitive to data input and methodological choices. Such sensitivity and diverse applications mean that flexibility is necessary to create SDMs with tailored protocols for a given set of data and model use. We introduce the r package flexsdm for supporting flexible species distribution modelling workflows. flexsdm functions and their arguments serve as building blocks to construct a specific modelling protocol for user's needs. The main flexsdm features are modelling flexibility, integration with other modelling tools, simplicity of the objects returned and function speed. As an illustration, we used flexsdm to define a complete workflow for California red fir Abies magnifica. This package provides modelling flexibility by incorporating comprehensive tools structured in three steps: (a) The Pre-modelling functions that prepare input, for example, sampling bias correction, sampling pseudo-absences and background points, data partitioning, and reducing collinearity in predictors. (b) The Modelling functions allow fitting and evaluating different modelling approaches, including individual algorithms, tuned models, ensembles of small models and ensemble models. (c) The Post-modelling functions include tools related to models' predictions, interpolation and overprediction correction. Because flexsdm comprises a large part of the SDM process, from outlier detection to overprediction correction, flexsdm users can delineate partial or complete workflows based on the combination functions to meet specific modelling needs.
publishDate 2022
dc.date.none.fl_str_mv 2022-08
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/215195
Velazco, Santiago José Elías; Rose, Miranda Brooke; de Andrade, André Felipe Alves; Minoli, Ignacio; Franklin, Janet; flexsdm: An r package for supporting a comprehensive and flexible species distribution modelling workflow; British Ecological Society; Methods in Ecology and Evolution; 13; 8; 8-2022; 1661-1669
2041-210X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/215195
identifier_str_mv Velazco, Santiago José Elías; Rose, Miranda Brooke; de Andrade, André Felipe Alves; Minoli, Ignacio; Franklin, Janet; flexsdm: An r package for supporting a comprehensive and flexible species distribution modelling workflow; British Ecological Society; Methods in Ecology and Evolution; 13; 8; 8-2022; 1661-1669
2041-210X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.13874
info:eu-repo/semantics/altIdentifier/doi/10.1111/2041-210X.13874
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv British Ecological Society
publisher.none.fl_str_mv British Ecological Society
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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