Understanding the Long-Term Impact of Bamboos on Secondary Forests: A Case for Bamboo Management in Southern Brazil

As secondary forests become more common around the world, it is essential to understand successional pathways to ensure their proper forest management. Despite optimism about secondary forests in terms of landscape restoration, the influence of invasive species on their development has been poorly explored. Here, forest plots in the Araucaria Forest, Southern Brazil, are used to compare forest dynamics over a 14-year period between unmanaged bamboo forest development (control) and the removal of bamboo. Six control plots (15 × 15 m) were monitored for all adult trees since 2007 alongside six adjacent removal plots; after the initial measurement of the control in 2007, all plots were measured bi-annually from 2010 to 2020. Comparisons were based on tree species diversity, composition, and structure parameters. Removal plots show a trend towards developing a forest composition with more secondary and late successional species while the control plots demonstrate succession restricted to the pioneer trees that regenerated immediately after bamboo die-off (2005–2006). Without the presence of bamboos, removal plots are mirroring the well-known successional pathway typical of the Araucaria Forest. Conversely, bamboos are effectively arresting successional development in the control, resulting in lower levels of diversity and less complex forest structure. For the first time, this study presents a direct analysis of the influence of bamboos on forest succession, providing evidence on which practices to manage bamboo forests can be developed so these secondary forests can fulfill their ecological and economic potential.

Landscape-level interactions of prefire vegetation, burn severity, and postfire vegetation over a 16-year period in interior Alaska

Landsat imagery was used to study the relationship between a remotely sensed burn severity index and prefire vegetation and the postfire vegetation response related to burn severity within a 1986 burn in interior Alaska. Vegetation was classified prior to the fire and 16 years after the fire, and a chronosequence of remotely sensed vegetation index values was analyzed as a surrogate of vegetation recovery. Remotely sensed burn severity varied by vegetation class, with needle-leaf forest classes experiencing higher burn severity than broadleaf forest or broadleaf shrubland classes. Burn severity varied by cover within needle-leaf classes. Elevation also had an influence on burn severity, presumably as a result of there being less fuel above the treeline. Several large broadleaf areas at the fire perimeter appeared to act as fire breaks. A remotely sensed vegetation index peaked 8–14 years after the fire, and increase in the vegetation index was highest within the highest burn severity class. Self-replacement appeared to be the dominant successional pathway, with prefire needle-leaf forest classes mostly succeeding to needle-leaf woodland and with prefire broadleaf forest mostly succeeding to broadleaf shrubland. Because the remotely sensed indices were based on reflected solar radiation, they are likely indicative of surface properties, such as canopy destruction and surface charring, rather than subsurface properties, such as postfire depth of organic soil.