Version 1
: Received: 9 May 2023 / Approved: 9 May 2023 / Online: 9 May 2023 (08:46:10 CEST)
Version 2
: Received: 20 June 2023 / Approved: 21 June 2023 / Online: 21 June 2023 (12:56:03 CEST)
Portillo-Quintero, C.; Hernandez-Stefanoni, J.L.; Dupuy, J.M. Forest Clearing Dynamics and Its Relation to Remotely Sensed Carbon Density and Plant Species Diversity in the Puuc Biocultural State Reserve, Mexico. Remote Sens.2023, 15, 3445.
Portillo-Quintero, C.; Hernandez-Stefanoni, J.L.; Dupuy, J.M. Forest Clearing Dynamics and Its Relation to Remotely Sensed Carbon Density and Plant Species Diversity in the Puuc Biocultural State Reserve, Mexico. Remote Sens. 2023, 15, 3445.
Portillo-Quintero, C.; Hernandez-Stefanoni, J.L.; Dupuy, J.M. Forest Clearing Dynamics and Its Relation to Remotely Sensed Carbon Density and Plant Species Diversity in the Puuc Biocultural State Reserve, Mexico. Remote Sens.2023, 15, 3445.
Portillo-Quintero, C.; Hernandez-Stefanoni, J.L.; Dupuy, J.M. Forest Clearing Dynamics and Its Relation to Remotely Sensed Carbon Density and Plant Species Diversity in the Puuc Biocultural State Reserve, Mexico. Remote Sens. 2023, 15, 3445.
Abstract
In the Neotropics, the integration of remotely sensed products to understand socioecological processes at local scales is limited by the physical difficulties and financial costs of collecting field data to train and validate these models. In this study, we used carbon density and tree species richness models generated from ALOS-2 PALSAR 2 imagery and national scale forest inventory data and compared these products to a Landsat-based continuous change detection product for the 2000-2021 period. This was performed to evaluate forest clearing dynamics in and around the Puuc Biocultural State Reserve (PBSR) in Mexico. The estimated error-adjusted area of detected annual forest clearings from the year 2000 until the year 2021 was 230,511 ha in total (+19,979 ha). The analysis of annual forest clearing frequency and area suggests that although forest clearing was significantly more intensive outside of the PBSR than within the PBSR during the entire 2000-2021 period, there is no evidence suggesting that the frequency and magnitude of forest clearing has changed over the years after the creation of the PBSR in 2011. The emerging hotspot analysis shows, however, that forest clearing spatiotemporal clustering (hotspots) during the 2012-2021 period was less widespread and mostly confined to areas outside the PBSR. In addition, the analysis shows forest clearing clustering is on a downward trend within the PBSR. After comparing forest clearing events to carbon density and tree species richness models, our data also suggests that land owners within the PBSR might be practicing longer barbecho (fallow) periods in contrast to land owners outside the PBSR allowing forests to attain higher carbon density and tree species richness and hence better soil nutrient recovery after land abandonment. In conclusion, our results show that the PBSR effectively acts as stabilizing forest management scheme that minimizes the impact of productive activities by lowering the frequency of forest clearing events and preserving late secondary forests. We recommend the continuation of efforts for providing alternative optimal field data collection strategies and modeling techniques to spatially predict key tropical forest attributes. The combination of these models with continuous change detection datasets will allow to reveal underlying ecological processes and generate information better adapted to forest governance scales.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.