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Wooded pastures serve as a traditional source of forage in Europe, where forest grazing is valued as an efficient tool for maintaining the diversity of semi-natural habitats. In a forest grazing setting with diverse diet composition, assessing the energy content of animal diets can be a difficult task because of its dependency on digestibility measures. In the present study, prediction equations of metabolizable energy (ME) were obtained performing stepwise regression with data (n = 297; 44 plant species) on nutritional attributes (Acid Detergent Fiber, lignin, silica, dry matter, crude protein, in vitro organic matter digestibility) from 20 representative stands of Atlantic dry heathlands and pedunculate oak woodlands. The results showed that the prediction accuracy of ME is reduced when the general model (R2 = 0.64) is applied, as opposed to the use of the specific prediction equations for each vegetation type (R2 = 0.61, 0.66, 0.71 for oak woodlands; R2 = 0.70 heather-gorse dominated heathlands, R2 = 0.41 continental heathlands). The general model tends to overestimate the ME concentrations in heaths with respect to the observed ME values obtained from IVOMD as a sole predictor, and this divergence could be corrected by applying the specific prediction equations obtained for each vegetation type. Although the use of prediction equations by season would improve accuracy in the case of a Winter scenario, using the general model as opposed to the prediction equations for Spring, Summer or Fall would represent a much smaller loss of accuracy.

sustainability

Estimating Energy Concentrations in Wooded Pastures of NW Spain Using Empirical Models That Relate Observed Metabolizable Energy to Measured Nutritional Attributes