Natural regeneration has been proposed as a cost-effective forest restoration approach for both small and large-scale initiatives. However, attributes for assessing the success of forest restoration through natural regeneration may vary among them in spatial patterns depending on the scale of analysis and on environmental gradients. The authors analysed the spatial patterns of recovery completeness (i.e. how similar attributes in restored forests are to the same attributes in reference forests) in response to environmental factors in a Mediterranean forest landscape of Central Chile. They evaluated (1) forest recovery completeness using basal area (BA), quadratic mean diameter (QMD), adult species density (ASD), adult species richness (ASR), and seedling species richness (SSR); (2) the spatial congruence of recovery completeness estimated by each of these indicators; and (3) the environmental factors potentially shaping these spatial patterns. We used field measurements and geospatial information sources to quantify and predict indicator responses by fitting boosted regression tree models.
To assess the spatial congruence of predictions we overlaid high-level recovery completeness values for all indicators. The results suggest that low spatial congruence among forest recovery indicators may hinder the monitoring of restoration at large scales. The implications of such divergence in defining restoration success can be enormous given the current global challenge of forest restoration. Although the authors' research was tested in a threatened region of global importance, the results may have wider significance for restoration planning providing cautionary notes and recommendations for the appropriate use of forest recovery indicators when monitoring large-scale restoration projects.
Full Reference:
Altamirano, A., Miranda, A., Meli, P., Dehennin, J., Muys, B., Prado, M. & Rey-Benayas, J. M. 2019. Spatial congruence among indicators of recovery completeness in a Mediterranean forest landscape: Implications for planning large-scale restoration. Ecological Indicators, 102, 752-759. DOI: https://doi.org/10.1016/j.ecolind.2019.03.046