Affiliation:
1. Sapienza University of Rome
2. University of Michigan
3. Smithsonian Tropical Research Institute
Abstract
Abstract
Context
Secondary forests are frequently re-cleared before they can recover to pre-disturbance conditions. The identification of factors associated with passive regeneration persistence success would help planning cost-efficient forest restoration.
Objectives
In this paper we investigated the role that the landscape context of naturally regenerated forest patches plays for their chances to mature and persist in time in central Panama. Maturation and persistence of secondary forests are concepts often undervalued representing, however, essential requisites for an effective and long-term restoration of the ecosystem processes.
Methods
A unique data set of land-cover maps of central Panama was used to identify the forest patches that naturally recovered and persisted between 1990 and 2020. We developed a Random Forest Classification (RFC) calibration method to identify areas with higher likelihood of forest persistence success.
Results
The RFC model discriminated between areas that naturally recovered and persisted in time and areas that did not persisted with an error rate of 2%. By tuning, we obtained a precision of 0.94 (94%) in the validation test. Based on the model, we developed a prediction map of central Panama areas with higher probability (≥ 90%) of secondary forests persistence success within the next 20 years.
Conclusions
Tracking simple landscape and socio-economic metrics allowed for a deeper understanding of the underlying mechanisms of secondary forest persistence in central Panama. Through the development of RFC calibration method, this study maximized the reliability of the patches identified as suitable to persistence success, representing a basis for management decisions and future investigations for a successful, long-term forest-landscape restoration.
Publisher
Research Square Platform LLC