Caracteres morfométricos como indicadores de calidad de sitio de Tara spinosa (Leguminosae, Caesalpinioideae) en Cajamarca, Perú.

• Autores: Villena-Velásquez, J.J., Chávarry, P.M., Seminario, J.F., Sovero, G.M.
• Formato: artículo
• Fecha de Publicación: 2022
• Institución: Universidad Nacional de Cajamarca
• Repositorio: UNC-Institucional
• Lenguaje: español
• OAI Identifier: oai:repositorio.unc.edu.pe:20.500.14074/9545
• Enlace del recurso: http://hdl.handle.net/20.500.14074/9545; https://doi.org/10.30550/j.lil/2022.59.1/2022.04.01
• Nivel de acceso: acceso abierto
• Materia: Cajamarca; forest site; morphology; tara; taya; https://purl.org/pe-repo/ocde/ford#4.01.02

Tara spinosa (Molina) Britton & Rose [= Caesalpinia spinosa (Molina) Kuntze] (Fabaceae) is an economically important species for Peru and particularly for the department of Cajamarca. It presents adaptive plasticity to altitudinal gradients (0 to 3000 m asl) and soil types. However, there are no studies regarding its site quality, which are important to understand both its ecological and management requirements. The objective of this research was to evaluate the expression of morphometric characters as indicators of site quality of Tara spinosa, for this purpose, samples were collected from 15 localities of the department of Cajamarca, Peru. The height of 15 randomly selected trees was measured and 50 dried fruits were collected from the plant, their length, width and weight were also measured. Around each tree evaluated, a soil sample was taken from the A horizon, 17 physicochemical factors were analyzed in the laboratory. The average climatic data were obtained from the Peruvian National Meteorological and Hydrological Service database. The analysis of variance indicated that there are statistical differences among the materials and the Scott-Knott test determined the best materials. Pearson's linear correlation analysis (p < 0.05) between 21 variables (17 soil and four biometric) identified the degree of association between edaphic and plant variables. Ten linear regression models were found to explain fruit length and weight. It is concluded that these two traits are good indicators of the site quality of Tara spinosa.