# Simulating Forest Dynamics of Lowland Rainforests in Eastern Madagascar
## 4 Discussion  
In this study, we applied the forest model FORMIND to simulate the dynamics of Madagascar lowland rainforest in Reserve Naturelle Integrale de Betampona, and then validated FORMIND in the lowland rainforest of Zahamena National Park. Madagascar, known for its \(>\)80% endemicity, is a imperilously threatened global biodiversity hotspot [39]. With the diminishing forest resources, the need to effectively conserve the remaining ecosystems has been eclipsed by the lack of long term inventory datasets, and there are few studies devoted to how the remaining forests and forest fragments will survive under the anthropogenic threat and changing environmental conditions. Our model has the ability to evaluate and simulate scenarios involving changing climatic conditions [38] and has been applied to a number of other tropical forests worldwide for understanding how the structure and dynamics are altered in fragmented forests [18]. A general challenge of predictive forest modeling is to accurately simulate and subsequently forecast how forest stands will develop in the near and distant future in response to the many disturbances to which they can be subjected, including: fragmentation, fires, logging, pollution, the loss of pollinating and seed-dispersing animals, and the direct (leaf physiology) and indirect (climate) effects of increasing atmospheric CO\({}_{2}\)[40]. An important advantage of the application of individual-based models (IBMs) toward understanding the impact of such perturbations is that their framework allows the modeler to control the resolution at which they are studied, both spatially and temporally [13]. Shifting dynamics be studied on the scale of individual leaf-level changes up to  
Figure 5: (**a**) Gross primary productivity (GPP), respiration, net primary productivity (NPP), and biomass mortality through time for the Madagascar rainforest simulation (50 ha forest area); (**b**) The net ecosystem exchange (NEE) time series for the Madagascar rainforest simulation. The shading refers to points in time where the simulated forest is a carbon source (blue) and a carbon sink (red) through the 1000-year timespan. landscape scale, and IBMs like FORMIND have been extensively applied with field data from various tropical forests [11; 13; 18; 38; 41; 42; 43]. Our Madagascar FORMIND Model accurately simulated the structure of both BTP and ZNP forests, though a few features of each were not well captured by the forest simulation. For instance, as shown in Figures 4 and 5, simulated total aboveground biomass and stem counts per PFT matches our calculations from field data well in the case of Betampona, and is within the range seen across the 50 runs, for the case of Zahamena. However, in looking at the stems per diameter size class for each (Figures 4 and 5), it is clear that the model underestimates the number of smaller to medium trees as compared to both study site datasets. At both sites, the smallest size (10-20 cm DBH) was overestimated by the model. Thus, though FORMIND is accurately depicting the forest structure in general, the character of the forest appears slightly differently. In BTP and ZNP, there are fewer small trees and more mid-sized trees. Two notable sources of error that occurred with the development of our parameterization were: (i) so little is known about Madagascar tree species in general, that the placement of species in the proper plant functional type groups was very challenging; and (ii) the growth forms of trees in Madagascar forests are not consistent with other rainforests worldwide. With respect to the first issue, the dataset used to parameterize this forest model contains a number of tree species that are described only to the genus level at present. The maximum sizes and light requirements of many of these species are not definitively known, thus their group placement was an educated guess based on expert knowledge and field-based observations.