Incorporating landscape pattern features in a spatial harvest model

The primary objective of this research is to solve area-based harvest scheduling problems which not only specify the timing and location of harvesting activities, but also predict the changes in landscape structure in terms of remnant patchiness. Remnant patches are considered to be ecologically important in maintaining biodiversity on the landscape. Based on existing knowledge and experience of spatially-constrained harvest scheduling and landscape pattern models, I developed the Landscape Harvesting Scheduling model (LHS) to meet the requirements of this research. LHS has four objectives related to timber harvesting: 1) opening size, 2) timber flow, 3) road construction cost, and 4) maximum disturbance rate (denoted by percentage of total planning area). It also has three objectives related to landscape pattern: 1) remnant patch size, 2) patch shape, and 3) inter-patch distance. Each objective is represented as an individual objective. All objectives are evaluated by penalty costs. A simulation annealing algorithm was used to randomly generate solutions and converge on those with minimum total penalty costs. A number of model runs were made under different management scenarios to: 1) determine the effects of adjacency constraints (opening size, green-up period) on timber production and landscape structure, 2) determine the effects of the remnant patch constraints on the changes in landscape structure, and 3) compare the simulation results to those from the harvest simulation model, ATLAS - A Tactical Landscape Analysis System. The simulation results show that the Relaxed Adjacency (RA) rule causes less timber reduction than the Strict Adjacency (SA) rule, and that timber reduction caused by exclusion period constraints can be offset by larger opening size limit constraints. The results also show that existing spatially-constrained harvest models cause forest landscapes to lose large remnant patches after about 60% of the total planning area is cut. It is concluded that without the remnant patch constraints, either changing the spatial constraint formulation or reducing the maximum harvest rate are not effective measures for achieving the objective of retaining large patches on the landscape. The simulation results under scenarios with and without the remnant patch (RP) objectives show that the RP constraints can control the dynamic changes in remnant patches on the forest landscape. The effects of reducing cutting rate on the landscape structure were significant only after the RP constraints were applied. The remnant patch constraints can also affect the total edge length at a lower cutting rate. Applying the RP constraints did not cause significant timber reduction (from 0.5 - 2.4%) compared to the scenarios without the RP constraints. The simulation results under different priorities show that setting timber harvest as the top priority caused higher average periodic timber yield at the cost of high variation in periodic road construction cost, especially high investment in the first period. Setting even periodic road cost as the top priority resulted in relatively even road cost distribution among the planning periods, but this also caused a small reduction and some variation in periodic timber harvest. Setting opening size objectives as the top priority reduced both timber harvest, and initial road construction cost compared to scenarios with timber as top priority. The advantages under opening size scenarios are relatively larger remnant patches, and relatively less variation in periodic edge length. Comparison with the ATLAS model showed the harvest schedule generated by ATLAS had a lower timber harvest (about 5.4% reduction from the timber target), and higher initial road construction cost. However, it took much less computation effort to run ATLAS. The model developed in this study can solve operational planning problems with multiple objectives, including landscape structure. Its advantage over existing models is that it incorporates landscape structure simultaneously with other forest operational issues, such as timber harvest, and road construction. Its disadvantage is that it needs a longer time to run than other harvest scheduling models. Further studies are required in this research field. The important issues suggested for future study are: incorporating landscape heterogeneity in the model, linking landscape pattern with population dynamics of specific wildlife species, and allowing multiple rotation scheduling.Forestry, Faculty ofGraduat