Different Approaches of Forest Type Classifications for Argentina Based on Functional Forests and Canopy Cover Composition by Tree Species

Autores
Martínez Pastur, Guillermo José; Loto, Dante; Rodríguez‑Souilla, Julián; Silveira, Eduarda M.O.; Cellini, Juan Manuel; Peri, Pablo Luis
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Modern forestry systems rely on typologies of forest types (FTs). In Argentina, several proposals have been developed, but they lack unified criteria. The objective was to compare different approaches, specifically focusing on (i) phenoclusters (functional forests based on vegetation phenology variations and climate variables) and (ii) forest canopy cover composition by tree species. We conducted comparative uni-variate analyses using data from national forest inventories, forest models (biodiversity, carbon, structure), and regional climate. We assessed the performance of phenoclusters in differentiating the variability of native forests (proxy: forest structure), biodiversity (proxy: indicator species), and environmental factors (proxies: soil carbon stock, elevation, climate). Additionally, we proposed a simple FT classification methodology based on species composition, considering the basal area of tree species. Finally, we compared the performance of both proposals. Our findings showed that classifications based on forest canopy cover composition are feasible to implement in regions dominated by mono-specific forests. However, phenoclusters allowed for the increased complexity of categories at the landscape level. Conversely, in regions where multi-specific stands prevailed, classifications based on forest canopy cover composition proved ineffective; however, phenoclusters facilitated a reduction in complexity at the landscape level. These results offer a pathway to harmonize national FT classifications by employing criteria and indicators to achieve sustainable forest management and conservation initiatives.
EEA Santa Cruz
Fil: Martínez Pastur, Guillermo José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina.
Fil: Loto, Dante. Universidad Nacional de Santiago del Estero. Instituto de Silvicultura y Manejo de Bosques; Argentina.
Fil: Loto, Dante. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fil: Rodríguez‑Souilla, Julián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina.
Fil: Silveira, Eduarda M.O. University of Wisconsin. Department of Forest and Wildlife Ecology. SILVIS Lab.; Estados Unidos.
Fil: Cellini, Juan Manuel. Universidad Nacional de la Plata. Facultad de Ciencias Naturales y Museo. Laboratorio de Investigaciones en Maderas; Argentina.
Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA), Estación Experimental Agropecuaria Santa Cruz; Argentina.
Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.
Fuente
Resources 13 (5) : 62. (April 2024)
Materia
Primary Forests
Forest Resources
Sustainable Land Management
Forest Management
Phenology
Biodiversity
Carbon
Bosques Primarios
Recursos Forestales
Gestión Sostenible de la Tierra
Ordenación Forestal
Fenología
Biodiversidad
Carbono
Argentina
Phenoclusters
Forest Structure and Function
Climate Variables
Forest Canopy Cover Composition
Tree Species
Fenoclusters
Estructura Funcional Forestal
Variables Climáticas
Composición de la Cubierta del Dosel Forestal
Especies de Arboles
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/17676
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oai_identifier_str oai:localhost:20.500.12123/17676
network_acronym_str INTADig
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network_name_str INTA Digital (INTA)
spelling Different Approaches of Forest Type Classifications for Argentina Based on Functional Forests and Canopy Cover Composition by Tree SpeciesMartínez Pastur, Guillermo JoséLoto, DanteRodríguez‑Souilla, JuliánSilveira, Eduarda M.O.Cellini, Juan ManuelPeri, Pablo LuisPrimary ForestsForest ResourcesSustainable Land ManagementForest ManagementPhenologyBiodiversityCarbonBosques PrimariosRecursos ForestalesGestión Sostenible de la TierraOrdenación ForestalFenologíaBiodiversidadCarbonoArgentinaPhenoclustersForest Structure and FunctionClimate VariablesForest Canopy Cover CompositionTree SpeciesFenoclustersEstructura Funcional ForestalVariables ClimáticasComposición de la Cubierta del Dosel ForestalEspecies de ArbolesModern forestry systems rely on typologies of forest types (FTs). In Argentina, several proposals have been developed, but they lack unified criteria. The objective was to compare different approaches, specifically focusing on (i) phenoclusters (functional forests based on vegetation phenology variations and climate variables) and (ii) forest canopy cover composition by tree species. We conducted comparative uni-variate analyses using data from national forest inventories, forest models (biodiversity, carbon, structure), and regional climate. We assessed the performance of phenoclusters in differentiating the variability of native forests (proxy: forest structure), biodiversity (proxy: indicator species), and environmental factors (proxies: soil carbon stock, elevation, climate). Additionally, we proposed a simple FT classification methodology based on species composition, considering the basal area of tree species. Finally, we compared the performance of both proposals. Our findings showed that classifications based on forest canopy cover composition are feasible to implement in regions dominated by mono-specific forests. However, phenoclusters allowed for the increased complexity of categories at the landscape level. Conversely, in regions where multi-specific stands prevailed, classifications based on forest canopy cover composition proved ineffective; however, phenoclusters facilitated a reduction in complexity at the landscape level. These results offer a pathway to harmonize national FT classifications by employing criteria and indicators to achieve sustainable forest management and conservation initiatives.EEA Santa CruzFil: Martínez Pastur, Guillermo José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina.Fil: Loto, Dante. Universidad Nacional de Santiago del Estero. Instituto de Silvicultura y Manejo de Bosques; Argentina.Fil: Loto, Dante. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Rodríguez‑Souilla, Julián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina.Fil: Silveira, Eduarda M.O. University of Wisconsin. Department of Forest and Wildlife Ecology. SILVIS Lab.; Estados Unidos.Fil: Cellini, Juan Manuel. Universidad Nacional de la Plata. Facultad de Ciencias Naturales y Museo. Laboratorio de Investigaciones en Maderas; Argentina.Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA), Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.MDPI2024-05-09T09:43:54Z2024-05-09T09:43:54Z2024-04-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/17676https://www.mdpi.com/2079-9276/13/5/62Martínez Pastur G.; Loto D.; Rodríguez-Souilla J.; Silveira E.M.O.; Cellini J.M.; Peri P.L. (2024) Different approaches of forest type classifications for Argentina based on functional forests and canopy cover composition by tree species. Resources 13: 62. https://doi.org/10.3390/resources130500622079-9276 (electronic)https://doi.org/10.3390/resources13050062Resources 13 (5) : 62. (April 2024)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-09-29T13:46:31Zoai:localhost:20.500.12123/17676instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-29 13:46:32.022INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Different Approaches of Forest Type Classifications for Argentina Based on Functional Forests and Canopy Cover Composition by Tree Species
title Different Approaches of Forest Type Classifications for Argentina Based on Functional Forests and Canopy Cover Composition by Tree Species
spellingShingle Different Approaches of Forest Type Classifications for Argentina Based on Functional Forests and Canopy Cover Composition by Tree Species
Martínez Pastur, Guillermo José
Primary Forests
Forest Resources
Sustainable Land Management
Forest Management
Phenology
Biodiversity
Carbon
Bosques Primarios
Recursos Forestales
Gestión Sostenible de la Tierra
Ordenación Forestal
Fenología
Biodiversidad
Carbono
Argentina
Phenoclusters
Forest Structure and Function
Climate Variables
Forest Canopy Cover Composition
Tree Species
Fenoclusters
Estructura Funcional Forestal
Variables Climáticas
Composición de la Cubierta del Dosel Forestal
Especies de Arboles
title_short Different Approaches of Forest Type Classifications for Argentina Based on Functional Forests and Canopy Cover Composition by Tree Species
title_full Different Approaches of Forest Type Classifications for Argentina Based on Functional Forests and Canopy Cover Composition by Tree Species
title_fullStr Different Approaches of Forest Type Classifications for Argentina Based on Functional Forests and Canopy Cover Composition by Tree Species
title_full_unstemmed Different Approaches of Forest Type Classifications for Argentina Based on Functional Forests and Canopy Cover Composition by Tree Species
title_sort Different Approaches of Forest Type Classifications for Argentina Based on Functional Forests and Canopy Cover Composition by Tree Species
dc.creator.none.fl_str_mv Martínez Pastur, Guillermo José
Loto, Dante
Rodríguez‑Souilla, Julián
Silveira, Eduarda M.O.
Cellini, Juan Manuel
Peri, Pablo Luis
author Martínez Pastur, Guillermo José
author_facet Martínez Pastur, Guillermo José
Loto, Dante
Rodríguez‑Souilla, Julián
Silveira, Eduarda M.O.
Cellini, Juan Manuel
Peri, Pablo Luis
author_role author
author2 Loto, Dante
Rodríguez‑Souilla, Julián
Silveira, Eduarda M.O.
Cellini, Juan Manuel
Peri, Pablo Luis
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Primary Forests
Forest Resources
Sustainable Land Management
Forest Management
Phenology
Biodiversity
Carbon
Bosques Primarios
Recursos Forestales
Gestión Sostenible de la Tierra
Ordenación Forestal
Fenología
Biodiversidad
Carbono
Argentina
Phenoclusters
Forest Structure and Function
Climate Variables
Forest Canopy Cover Composition
Tree Species
Fenoclusters
Estructura Funcional Forestal
Variables Climáticas
Composición de la Cubierta del Dosel Forestal
Especies de Arboles
topic Primary Forests
Forest Resources
Sustainable Land Management
Forest Management
Phenology
Biodiversity
Carbon
Bosques Primarios
Recursos Forestales
Gestión Sostenible de la Tierra
Ordenación Forestal
Fenología
Biodiversidad
Carbono
Argentina
Phenoclusters
Forest Structure and Function
Climate Variables
Forest Canopy Cover Composition
Tree Species
Fenoclusters
Estructura Funcional Forestal
Variables Climáticas
Composición de la Cubierta del Dosel Forestal
Especies de Arboles
dc.description.none.fl_txt_mv Modern forestry systems rely on typologies of forest types (FTs). In Argentina, several proposals have been developed, but they lack unified criteria. The objective was to compare different approaches, specifically focusing on (i) phenoclusters (functional forests based on vegetation phenology variations and climate variables) and (ii) forest canopy cover composition by tree species. We conducted comparative uni-variate analyses using data from national forest inventories, forest models (biodiversity, carbon, structure), and regional climate. We assessed the performance of phenoclusters in differentiating the variability of native forests (proxy: forest structure), biodiversity (proxy: indicator species), and environmental factors (proxies: soil carbon stock, elevation, climate). Additionally, we proposed a simple FT classification methodology based on species composition, considering the basal area of tree species. Finally, we compared the performance of both proposals. Our findings showed that classifications based on forest canopy cover composition are feasible to implement in regions dominated by mono-specific forests. However, phenoclusters allowed for the increased complexity of categories at the landscape level. Conversely, in regions where multi-specific stands prevailed, classifications based on forest canopy cover composition proved ineffective; however, phenoclusters facilitated a reduction in complexity at the landscape level. These results offer a pathway to harmonize national FT classifications by employing criteria and indicators to achieve sustainable forest management and conservation initiatives.
EEA Santa Cruz
Fil: Martínez Pastur, Guillermo José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina.
Fil: Loto, Dante. Universidad Nacional de Santiago del Estero. Instituto de Silvicultura y Manejo de Bosques; Argentina.
Fil: Loto, Dante. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fil: Rodríguez‑Souilla, Julián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina.
Fil: Silveira, Eduarda M.O. University of Wisconsin. Department of Forest and Wildlife Ecology. SILVIS Lab.; Estados Unidos.
Fil: Cellini, Juan Manuel. Universidad Nacional de la Plata. Facultad de Ciencias Naturales y Museo. Laboratorio de Investigaciones en Maderas; Argentina.
Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA), Estación Experimental Agropecuaria Santa Cruz; Argentina.
Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.
description Modern forestry systems rely on typologies of forest types (FTs). In Argentina, several proposals have been developed, but they lack unified criteria. The objective was to compare different approaches, specifically focusing on (i) phenoclusters (functional forests based on vegetation phenology variations and climate variables) and (ii) forest canopy cover composition by tree species. We conducted comparative uni-variate analyses using data from national forest inventories, forest models (biodiversity, carbon, structure), and regional climate. We assessed the performance of phenoclusters in differentiating the variability of native forests (proxy: forest structure), biodiversity (proxy: indicator species), and environmental factors (proxies: soil carbon stock, elevation, climate). Additionally, we proposed a simple FT classification methodology based on species composition, considering the basal area of tree species. Finally, we compared the performance of both proposals. Our findings showed that classifications based on forest canopy cover composition are feasible to implement in regions dominated by mono-specific forests. However, phenoclusters allowed for the increased complexity of categories at the landscape level. Conversely, in regions where multi-specific stands prevailed, classifications based on forest canopy cover composition proved ineffective; however, phenoclusters facilitated a reduction in complexity at the landscape level. These results offer a pathway to harmonize national FT classifications by employing criteria and indicators to achieve sustainable forest management and conservation initiatives.
publishDate 2024
dc.date.none.fl_str_mv 2024-05-09T09:43:54Z
2024-05-09T09:43:54Z
2024-04-24
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/20.500.12123/17676
https://www.mdpi.com/2079-9276/13/5/62
Martínez Pastur G.; Loto D.; Rodríguez-Souilla J.; Silveira E.M.O.; Cellini J.M.; Peri P.L. (2024) Different approaches of forest type classifications for Argentina based on functional forests and canopy cover composition by tree species. Resources 13: 62. https://doi.org/10.3390/resources13050062
2079-9276 (electronic)
https://doi.org/10.3390/resources13050062
url http://hdl.handle.net/20.500.12123/17676
https://www.mdpi.com/2079-9276/13/5/62
https://doi.org/10.3390/resources13050062
identifier_str_mv Martínez Pastur G.; Loto D.; Rodríguez-Souilla J.; Silveira E.M.O.; Cellini J.M.; Peri P.L. (2024) Different approaches of forest type classifications for Argentina based on functional forests and canopy cover composition by tree species. Resources 13: 62. https://doi.org/10.3390/resources13050062
2079-9276 (electronic)
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv Resources 13 (5) : 62. (April 2024)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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