Browsing by Author "Downie, Eleanor"

The study of forest fragmentation, the break-up of forests into smaller patches, has become increasingly important due to increases in human-induced deforestation. Currently, approximately 12 million ha of forest are lost per year and 32% of this loss is tropical. There is substantial evidence showing that edge effects can alter the structure and functioning of remaining tropical forests, even hundreds of meters from the forest edge. However, implementing empirical experiments to understand the effects of fragmentation on forest structural metrics is logistically and scientifically challenging and limited to smaller areas. The use of forest models may help overcome these limitations, as they are able to quickly reproduce long-term ecological processes, as well as simulate a broad range of boundary forcings, such as biogeographical variability. This study evaluates the capability of a state-of-the-art forest dynamic model in reproducing the three-dimensional vertical distribution of plants in Amazonian forests affected by fragmentation. To achieve this, we optimized parameters driving plant demography and mortality, as well as their response to edge effects. FORMIND is an individual and process-based gap model suited for species rich vegetation communities, with the option of a fragmentation module. We modified processes and parameters in FORMIND to mimic the dynamics observed in a long-term (40 years-old) forest fragmentation experiment in the Brazilian Amazon. Forest structural metrics extracted from the FORMIND model output were compared with those obtained from terrestrial laser scans of the Amazonian Forest fragments. The resulting simulations demonstrated that, after 40 years of edge effects, the model in its original state was not capable of reproducing comparable results to those observed using the terrestrial LiDAR system. However, the addition of a new parameter capable of adjusting tree mortality at varying edge distances and inclusion of understory vegetation, drastically improved the model’s ability to replicate the three-dimensional distribution of plant material in the forest fragments. Total Plant Area Index (PAI), and PAI at varying height intervals (PAI 0-10m, PAI 10-20m, PAI 20-30m), amongst other metrics, showed consistent responses from edge effects, thus resulting in an adequate vertical plant distribution. Results demonstrate that, with the implementation of new parameters, forest models such as FORMIND have strong potential to study the mechanisms and the impact of environmental changes on forests. Models can also expand the possibilities of in-situ studies, which are limited in time and space, when calibrated carefully with suitable in-situ data, here delivered by terrestrial LiDAR.