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

Guillermo J. Martínez Pastur (), Dante Loto, Julián Rodríguez-Souilla, Eduarda M. O. Silveira, Juan M. Cellini and Pablo L. Peri
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Guillermo J. Martínez Pastur: Centro Austral de Investigaciones Científicas (CADIC), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Houssay 200, Ushuaia 9410, Tierra del Fuego, Argentina
Dante Loto: Instituto de Silvicultura y Manejo de Bosques Nativos (INSIMA), Universidad Nacional de Santiago del Estero (UNSE), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Belgrano 1912, Santiago del Estero 4200, Santiago del Estero, Argentina
Julián Rodríguez-Souilla: Centro Austral de Investigaciones Científicas (CADIC), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Houssay 200, Ushuaia 9410, Tierra del Fuego, Argentina
Eduarda M. O. Silveira: SILVIS Lab, Department of Forest and Wildlife Ecology, University of Wisconsin, 1630 Linden Drive, Madison, WI 53706, USA
Juan M. Cellini: Laboratorio de Investigaciones en Maderas (LIMAD), Universidad Nacional de la Plata (UNLP), Diagonal 113 469, La Plata 1900, Buenos Aires, Argentina
Pablo L. Peri: Instituto Nacional de Tecnología Agropecuaria (INTA), Universidad Nacional de la Patagonia Austral (UNPA), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), cc 332, Río Gallegos 9400, Santa Cruz, Argentina

Resources, 2024, vol. 13, issue 5, 1-20

Abstract: 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.

Keywords: native forests; forest resources; phenoclusters; forest structure and function; sustainable forest management (search for similar items in EconPapers)
JEL-codes: Q1 Q2 Q3 Q4 Q5 (search for similar items in EconPapers)
Date: 2024
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