Mixed forests are increasingly recognized for their resilience to climate change and enhanced ecosystem services (ESs) provision, making them a focal point for sustainable forest management strategies. This study examines the trade-offs in ESs provision between pure and different proportions of mixed stands of Scots pine (Pinus sylvestris L.) and Maritime pine (Pinus pinaster Ait.) in the Northern Iberian Range, Spain. Using the SIMANFOR simulation platform, we evaluated various silvicultural scenarios developed to obtain different ESs such as carbon sequestration, timber and mushroom yields. Our findings reveal that ESs provision varies depending on the forest type (pure or mixed) and the mixture proportion, following different trends on each ES. The initial species proportions and their maintenance were less critical than the management approach itself, which significantly influenced ESs outcomes. Focusing solely on individual ESs can lead to trade-offs, as highlighted by our study on silviculture focused on large saw timber yields. However, adopting a balanced approach that considers multiple ESs can mitigate these trade-offs. Our findings underscore the effectiveness of this approach in maximizing yields of mushrooms, sequestered carbon, and small saw timber. This research provides valuable insights for forest managers aiming to balance productivity and sustainability in ESs provision, providing strategies to maximize compatible ESs effectively.

Aim of study: Despite its potential in the wood industry, Pyrenean oak (Quercus pyrenaica Willd.) has suffered from traditional use as firewood and the lack of profitable management guidelines, leading to the deterioration of its stands. This study explores the effects of different silvicultural scenarios on transforming regular coppice stands into irregular high forests and managing irregular stands sustainably. Area of study: Castile and Leon (Spain), where Pyrenean oak stands are widespread and play a critical ecological and potential economic role. Material and methods: Data were collected from pure coppice Pyrenean oak stands across the Castile and Leon region. Silvicultural scenarios were simulated using the SIMANFOR forest management simulator, incorporating various thinning intensities and periodicities to evaluate forest development and timber production. Main results: Intensive silviculture resulted in higher timber production. However, selective and continuous thinning based on Pro Silva guidelines effectively promoted the establishment and maintenance of high irregular forests, offering a sustainable alternative. Research highlights: While numerical predictions may involve some bias, observed trends under different management guidelines allow them to be ranked according to management objectives. Skilled managers are essential to adapt thinning periodicity and intensity to the local conditions, considering the heterogeneity of the stands.

Understanding tree mortality is crucial to understand forest dynamics and is essential for growth models and simulators. Although factors such as competition, drought, and pathogens drive mortality, their underlying mechanisms remain difficult to model. While substantial attention has focused on selecting appropriate algorithms and covariates, evaluating individual tree mortality models also requires careful selection of performance criteria. This study compares seven different metrics to assess their impact on model evaluation and selection. Results show that candidate models exhibited varying performances across metrics and that the choice of metric significantly influences the selection of the best model. When no confusion matrix was available, the area under the precision-recall curve (AUCPR) emerged as a more reliable alternative to the area under the ROC curve (AUC), offering a more informative assessment for imbalanced datasets. When a confusion matrix was available, Cohen’s Kappa coefficient (K) and Matthews correlation coefficient (MCC) outperformed accuracy-based metrics, providing a fairer evaluation of both live and dead tree classifications. These findings emphasize the importance of choosing appropriate evaluation standards to enhance mortality model assessment and ensure reliable predictions in forestry applications.