Abstract
For preserving biodiversity of European-Mediterranean forest ecosystems in current and future scenarios of global change by means of sustainable forest management it is necessary to determine how environment and forest characteristics correlate with biodiversity. For this purpose, neural networks were used to model forest bird species richness as a function of environment and forest structure and composition at the 1x1 km scale in Catalonia (NE Spain). Univariate and multivariate models respectively allowed exploring individual variable response and obtaining a parsimonious (ecologically meaningful) and accurate neural network. Forest area (with a canopy cover above 5%), mean forest canopy cover, mean annual temperature and summer precipitation were the best predictors of forest bird species richness. The resultant multivariate network had a good generalization capacity that failed however in the locations with highest species richness. Additionally, those forests with different degrees of canopy closure that were more mature and presented a more diverse tree species composition were also associated with higher bird species richness. This allowed us to provide management guidelines for forest planning in order to promote avian diversity in this European-Mediterranean region.
Highlights
The need for a sustainable forest management that considers productive aspects and the integrity of forest ecosystems and other non-wood values is widely recognized (Lindenmayer et al, 2000; Palahí et al, 2004)
This study aimed at modelling the relationships between forest bird species richness and environmental variables at 1 × 1 km in Catalonia (NE Spain) by means of Artificial Neural Networks (ANNs) in order to provide management guidelines for forest planning and biodiversity conservation in the current and future context of global change
From the 3038 UTM cells surveyed in the Atlas, we considered for study 2923 UTM cells that were completely inside Catalonia (Fig. 1), and for which the Spanish Forest Map (SFM) data were entirely available and updated
Summary
The need for a sustainable forest management that considers productive aspects and the integrity of forest ecosystems and other non-wood values is widely recognized (Lindenmayer et al, 2000; Palahí et al, 2004). Determining quantitative responses of forest biodiversity to environmental factors occurring in forest systems may be essential for the development of appropriate and well-founded forest management in Mediterranean Europe (Scarascia-Mugnozza et al, 2000). This would help to better understand how forest management can contribute to the mitigation of global change impacts. The huge growth and development of landscape ecology methods and approaches in the last two decades (Turner, 2005) may significantly contribute to the understanding of the relationships between species and forest beyond the stand scale at which most of the forestry practices are commonly planned. Valuable biodiversity databases have been created which can be of great interest for the assessment, management and conservation of forest ecosystems at broader scales than the stand and at the regional level (Fearer et al, 2007)
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