Simulating stand-level harvest prescriptions across landscapes: LANDIS PRO harvest module design

Forest landscape models (FLMs) are an important tool for assessing the long-term cumulative effects of harvest over large spatial extents. However, they have not been commonly used to guide forest management planning and on-the-ground operations. This is largely because FLMs track relatively simplistic vegetation information such as age cohort presence/absence, forest type, and biomass that are incompatible with tree density and size on which most harvest prescriptions are based. We describe and demonstrate the newly developed harvest module of the LANDIS PRO FLM, which tracks density, size, basal area, and stocking by species age cohorts for each site (cell). With this quantitative information, the module can simulate basal area controlled harvest, stocking-level controlled harvest, and group selection harvest. Through user-specified harvest year (frequency), stand ranking, and species and age preference, the new module can simulate a wide variety of harvest prescriptions such as thinning from above and below, shelterwood, clear-cutting, and group selection. We applied the LANDIS PRO harvest module to a large (17 000 km2) central hardwood forest landscape in Missouri. The simulated harvest prescriptions produced realistic stand-scale results when plotted on Gingrich stocking charts. The harvest module improves on previous versions by allowing partial treatment of individual age-classes within a cell and reporting results in metrics commonly used in stand-scale silviculture. It provides a closer link between landscape-scale simulation methods and stand-scale management.

Large-scale forest landscape model, design, validation, and application in management of oak decline

Forest landscape models (FLMs) have increasingly become important tools for exploring forest landscape changes by predicting forest vegetation dynamics over large spatial scales. However, two challenges confronting FLMs have persisted: how to simulate fine, site-scale processes while making large-scale (landscape and regional) simulation feasible, and how to fully take advantage of extensive U.S. Forest Service Inventory and Analysis (FIA) data to initialize and constraint model parameters. In this dissertation, first, a new FLM, LANDIS PRO was developed. In LANDIS PRO, forest succession and dynamics are simulated by incorporating species-, stand-, and landscape-scale processes by tracking number of trees by species age cohort. Because stand-scale resource competition is achieved by implementing rather than simulating the emergent properties of stand development, LANDIS PRO is computationally efficient, which makes large-scale simulation feasible. Since model parameters and simulation results are comparatively straightforward to forest inventory data, current intensive forest inventory data can be directly applied for model initialization and to constrain model parameters. Validation of FLMs is essential to ensure users’ confidence in model predictions and achieve reliable management decision making. To date, validation of FLMs has been limited due to lack of suitable data. However, recent advances in FLMs, together with increasingly available spatiotemporal data make FLM validation feasible. In this dissertation, second, I proposed a framework for validating forest landscape projections from LANDIS PRO using Forest Inventory Analysis (FIA) data. The proposed framework incorporated data assimilation techniques to constrain model parameters and the initial state of the landscape by verifying the initialized landscape and iteratively calibrating the model parameters. The model predictions were rigorously validated against independent FIA data at multiple scales, and the long-term natural successional pattern was also verified against empirical studies. Results showed model predictions were able to capture much of the variation overtime in species basal area and tree density at stand-, landtype- , and landscape-scales. Subsequent long-term predictions of natural succession patterns were consistent with expected changes in tree species density of oak-dominated forests in the absence of disturbance. Lastly, I used LANDIS PRO, a forest landscape model that includes stand-scale species density and basal area to evaluate the potential landscape-scale effects of alternative harvest methods (thinning, clearcutting and group selection) on oak decline mitigation. Projections indicated that forest harvesting can be effective in mitigating oak decline. Group selection and clearcutting were the most effective methods in the management of oak decline in the short-term (20 years) and mid-term (50 years), respectively. However, in the long-run (100 years), there was no significant difference predicted among the three methods.