Soil organic carbon (SOC) content supports several ecosystem services. Quantifying SOC requires: (i) accurate C estimates of forest components, and (ii) soil estimates. However, SOC is difficult to measure, so predictive models are needed. Our objective was to model SOC stocks within 30 cm depth in Patagonian forests based on climatic, topographic and vegetation productivity measures from satellite images, including Dynamic Habitat Indices and Land Surface Temperature derived from Landsat-8. We used data from 1320 stands of different forest types in Patagonia, and random forest regression to map SOC. The model captured SOC variability well (R² = 0.60, RMSE = 22.1%), considering the huge latitudinal extension (36.4° to 55.1° SL) and the great diversity of forest types. Mean SOC was 134.4 ton C ha⁻¹ ± 25.2, totaling 404.2 million ton C across Patagonia. Overall, SOC values were highest in valleys of the Andes mountains and in southern Tierra del Fuego, ranging from 53.5 to 277.8 ton C ha⁻¹ for the whole Patagonia region. Soil organic carbon is a metric relevant to many applications, connecting major issues such as forest management, conservation, and livestock production, and having spatially explicit estimates of SOC enables managers to fulfil the international agreements that Argentina has joined.

Background: It is necessary to determine the implications for managing forest stands using variable retention harvesting for maintaining carbon and for calculating the effects of different harvesting practices on above- and below-ground carbon balance in forest ecosystems. In this context, forest carbon management has gained more attention among managers and policy-makers during recent years. The aim of this study was to determine carbon pool dynamics in different forest ecosystem components after variable retention harvesting (VRH) to characterize the ecological stability and quantify the recovery rate through the years-after-harvesting (YAH). Methods: Carbon pool compartmentalization of 14 different components was determined in 60 harvested and primary unmanaged forests during the first 18 YAH in Tierra del Fuego (Argentina). We compared them using uni- and multi-variate methods, relativizing the outputs with primary unmanaged forests. Results: We determined the effectiveness to retain carbon components in post-harvested stands under different retention strategies (aggregated vs. dispersed). The balance among carbon pool components changed between managed and unmanaged stands across the YAH, and was directly related to the impact magnitude. Aggregated retention improved the ecological stability of the harvested areas, where the below-ground components were more stable than the above-ground components. The recovery rate was directly related to the post-harvesting natural dynamics of the stands. The studied period was not enough to fully recover the C levels of primary unmanaged forests, but VRH showed advantages to increase the C pools in the managed stands. Conclusions: Promoting VRH can improve sustainable forestry at the landscape level and in the long term, generating positive synergies with biodiversity and the provision of ecosystem services. This study provides important new insights into forest carbon management, in particular to setting standards in carbon projects and sets the groundwork for analysing the economics of the mentioned harvesting systems.

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.