We plan to use the Forest Vegetation Simulator (FVS), developed by the USFS over the previous couple of decades, in our ecological-economic model of a managed forest landscape. This week I’ve been thinking a lot about how best to link a representation of white-tailed deer browse with the FVS.
Two good examples I’ve found of the modelling of forest disturbance using FVS are the Fire and Fuels Extension (FFE) developed at the USFS Rocky Mountain Research Station in collaboration with other parties, and the Westwide Pine Beetle Model developed by the Forest Health Technology Enterprise Team (FHTET).
The Fire and Fuels Extension to the Forest Vegetation Simulator (FFE-FVS) links the existing FVS, models that represent fire and fire-effects, and fuel dynamics and crowning submodels. The overall model is currently calibrated for northern Idaho, western Montana, and northeastern Washington. More details on the FFE-FVS can be found here, where you can also download this video about the extension:
The Westwide Pine Beetle Model simulates impacts of mountain beetle (Dendroctonus ponderosae Hokpins), western pine beetle (D. brevicomis Leconte), and Ips species for which western pines are a host. The model simulates the movement of beetles between the forest stands in the landscape using the Parallel Processor Extension (PPE) to represent multiple forest stands in FVS.
We simulated management scenarios with and without thinning over 60 years, coupled with a mountain pine beetle outbreak (at 30 years) to examine how thinning might affect bark beetle impacts, potential fire behavior, and their interactions on a 16,000-ha landscape in northeastern Oregon. We employed the Forest Vegetation Simulator, along with sub-models including the Parallel Processing Extension, Fire and Fuels Extension, and Westwide Pine Beetle Model (WPBM). We also compared responses to treatment scenarios of two bark beetle-caused tree mortality susceptibility rating systems. As hypothesized, thinning treatments led to substantial reduction in potential wildfire severity over time. However, contrary to expectations, the WPBM predicted higher bark beetle-caused mortality from an outbreak in thinned versus unthinned scenarios. Likewise, susceptibility ratings were also higher for thinned stands. Thinning treatments favored retention of early seral species such as ponderosa pine, leading to increases in proportion and average diameter of host trees. Increased surface fuel loadings and incidence of potential crown fire behavior were predicted post-outbreak; however, these effects on potential wildfire behavior were minor relative to effects of thinning. We discuss apparent inconsistencies between simulation outputs and literature, and identify improvements needed in the modeling framework to better address bark beetle-wildfire interactions.
Whilst I’m still in the early stages of working out how our model will all fit together, it seems like an approach that takes a similar approach will be suitable for our purposes. We’ll need to develop a model that is able to represent the spatial distribution of the deer population across the landscape and that can specify the impact of those deer densities on the vegetation for given age-height classes (for each veg species). This model would likely then be linked with FVS via the the PPE. So concurrently over the next few months I’m going to be working on developing a model of deer density and browse impacts, coding this model into a structure that will link with FVS-PPE, and acquiring and developing data for model initialization.
Ager, A.A., McMahan, A., Hayes, J.L. and Smith, E.L. (2007) Modeling the effects of thinning on bark beetle impacts and wildfire potential in the Blue Mountains of eastern Oregon Landscape and Urban Planning 80:3 p.301-311