Nitrogenous and Phosphorus Soil Contents in Tierra del Fuego Forests: Relationships with Soil Organic Carbon, Climate, Vegetation and Landscape Metrics

Author:

Martínez Pastur Guillermo1ORCID,Aravena Acuña Marie-Claire1ORCID,Chaves Jimena E.1ORCID,Cellini Juan M.2ORCID,Silveira Eduarda M. O.3ORCID,Rodriguez-Souilla Julián1ORCID,von Müller Axel4,La Manna Ludmila5,Lencinas María V.1ORCID,Peri Pablo L.6ORCID

Affiliation:

1. Laboratorio de Recursos Agroforestales, Centro Austral de Investigaciones Científicas (CADIC), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Ushuaia 9410, Argentina

2. Laboratorio de Investigaciones en Maderas (LIMAD), Universidad Nacional de la Plata, La Plata 1900, Argentina

3. SILVIS Lab, Department of Forest and Wildlife Ecology, University of Wisconsin, Madison, WI 53715, USA

4. Estación Experimental Agroforestal Esquel, Instituto Nacional de Tecnología Agropecuaria (INTA), Esquel 9200, Argentina

5. Centro de Estudios Ambientales Integrados (CEAI), Universidad Nacional de la Patagonia San Juan Bosco, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Esquel 9200, Argentina

6. Instituto Nacional de Tecnología Agropecuaria (INTA), Universidad Nacional de la Patagonia Austral, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Río Gallegos 9400, Argentina

Abstract

Soil nitrogen (SN) and soil phosphorus (SP) contents support several ecosystem services and define the forest type distribution at local scale in Southern Patagonia. The quantification of nutrients during forest surveys requires soil samplings and estimations that are costly and difficult to measure. For this, predictive models of soil nutrients are needed. The objective of this study was to quantify SN and SP contents (30 cm depth) using different modelling approaches based on climatic, topographic and vegetation variables. We used data from 728 stands of different forest types for linear regression models to map SN and SP. The fitted models captured the variability of forest types well (R²-adj. 92–98% for SN and 70–87% for SP). The means were 9.3 ton ha−1 for SN and 124.3 kg ha−1 for SP. Overall, SN values were higher in the deciduous forests than those in the mixed evergreen, while SP was the highest in the Nothofagus pumilio forests. SN and SP are relevant metrics for many applications, connecting major issues, such as forest management and conservation. With these models, the quantification of SN and SP stocks across forests of different protection status (National Law 26,331/07) and national/provincial reserve networks is possible, contributing to the determination of nutrient contents at landscape level.

Publisher

MDPI AG

Subject

Nature and Landscape Conservation,Ecology,Global and Planetary Change

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