About
LDSim (Landscape Disturbance-Succession Simulator) is a disturbance and succession model used to understand and predict changes in forest ecosystems over time. It is a process-based model that incorporates information about forest disturbances (such as fire, windthrow, and insect outbreaks) and the subsequent recovery and succession of the forest.
The model was developed by Dr. Kevin McGarigal and his colleagues at the University of Massachusetts Amherst and is based on the premise that natural disturbances and succession processes are important drivers of forest ecosystem dynamics. The model uses a spatially-explicit approach, meaning that it simulates forest changes at multiple scales of spatial resolution (for example, from the site to the Subbasin scale) to meet different management needs and use cases.
LDSim modeling begins with an assessment of the historical range of variability (HRV) in the forest ecosystem, which is the range of natural variation in ecosystem structure and function that has occurred over a long period of time. This provides a baseline for evaluating the degree to which current forest conditions have deviated from historical patterns. The model then simulates the occurrence of various disturbances, such as fire, and predicts the subsequent recovery and succession of the forest over time.
LDSim modeling can be used to assess the effects of different management interventions, such as prescribed burning or thinning, on forest ecosystem dynamics. It can also be used to evaluate the potential impacts of future disturbances, such as changes in climate or land use.
Overall, LDSim disturbance and succession modeling is a powerful tool for understanding and predicting changes in forest ecosystems over time and guiding management and conservation efforts to maintain or restore more natural conditions.
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LDSim BPU
LDSim's BPU data layer categorizes site productivity into biophysical classes, mapping historical tree biomass and ecological departures for regional analysis.
Direct Access
Get hands-on access to this dataset using interactive notebooks. Choose between the Google Colab notebook for quick exploration in your browser or access the hosted Jupyter Notebooks via Binder or GitHub for more advanced workflows.
Direct access to the Google Collab notebook
Open and explore instantly
Click the button to the left to launch an interactive notebook directly in your browser. This pre-configured Colab notebook provides a quick and easy way to explore, visualize, and analyze the data—no setup required.
GitHub hosted Jupyter Notebooks
Flexible access for advanced workflows
Access the full collection of Jupyter Notebooks hosted on GitHub. These notebooks can be used on your local machine or via cloud platforms like Binder or Google Colaboratory, providing flexibility for more advanced customizations.