This paper aims to identify the spatial and temporal distribution of net aerial primary production (NAPP) of oats and sorghum in silvopastoral systems (SPS) and in a treeless situation (TLS), in Southern Cordoba, Argentina. The silvopastoral systems are composed of three woody cultures (Pinus elliottii, Eucalyptus viminalis and Quercus robur), and two grass species (Avena sativa and Sorghum sudanense). NAPP of Avena sativa and Sorghum sudanense were lower in the silvopastoral systems than in the treeless situation. However, there were also differences in terms of NAPP according to the tree species, and these differences were related to the intensity of competition between trees and grasses. Pinus elliottii and Quercus robur were less competitive than Eucalyptus viminalis, which might be associated with their morphophysiological differences, their differential growth rate and their differences in terms of phenology. Finally, facilitation effects between trees and grasses were also identified under certain conditions.

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In Prosopis caldenia forests, currently, the main activity is cattle rearing. Almost all research focuses on the herbaceous component, losing sight of the value of the forest resource and the implications of its management on the forage resource. The objective of this work is to evaluate forage availability based on forest cover, apply a model of diameter classes that allows predicting the evolution of forest mass and establish the relationship between the evolution of forest cover and forage availability. For this, forage availability was measured under and outside the projection of woody canopies, in two covers: open (10-15 m 2 ha -1 ) and closed (25-30 m 2 ha -1 ). Afterwards, through a model of diameter classes, it was sought to predict how the parameters of forest mass would evolve. The results of the herbaceous component showed that, up to 15 m 2 ha -1 of basal area (BA), there is no significant decrease in forage availability (approximately 2,700 kg ha -1 ). Regarding the forestry component, in a projected period of 10 years, 6.68 m 3 ha -1 would be obtained, representing 9.61 % of total standing volume. The relationship between canopy coverage and BA showed increase of 3.18 % per BA unit (R 2 = 0.96). This would allow projecting their participation by diameter class to propose improvement cuts that allow conducting these systems at coverage levels that do not significantly affect forage yield.

& Key message To be useful for silvicultural and forest management practices, the models of Site Index (SI) should be based on accessible predictor variables. In this study, we used spatially explicit data obtained from digital elevation models and climate data to develop SI prediction models with high local precision. & Context Predicting tree growth and yield is a key component to sustainable forest management and depends on accurate measures of site quality. & Aims The aim of this study was to develop both empirical models to predict site index (SI) from biophysical variables and a dynamic model of top height growth for plantations of Pinus elliottii Engelm. in Córdoba, Argentina. & Methods Site productivity described by SI was related to environmental characteristics, including topographic and climatic variables. Separate models were created from only topographic data and the combination of topographic and climate data. & Results Although SI can be adequately predicted through both types of models, the best results were obtained when combining topographic and climate variables (R 2 = 0.83, RMSE% = 7.02%, for the best-fitting model). The key factors affecting site productivity were the landscape position and the mean precipitation of the last 5 years before the reference age, both related to the amount of plant-available water in the soils. Furthermore, the top height growth models developed are fairly accurate, considering the proportion of variance explained (R 2 = 98%) and the precision of the estimates (RMSE % < 8%). & Conclusion The models developed here are likely to have considerable application in forestry, since they are based on accessible predictor variables, which make them useful for silvicultural and forest management practices, particularly for nonforest areas and for the young or uneven-aged stands.

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