Filters: Tags: vegetation modeling (X)4 results (38ms)
Applying Vulnerability Assessment Tools to Plan for Climate Adaptation: Case Studies in the North Pacific LCC - Final Report
The central objective of this project was to answer two questions: 1) how downscaled climate datasets, modeled vegetation changes, and information on estimated species sensitivities can be used to develop climate change adaptation strategies, and 2) how model results and datasets can be made more useful for informing the management of species and landscapes. To answer these questions, we identified enthusiastic partners working in two very different complex landscapes within the North Pacific Landscape Conservation Cooperative (NPLCC): 1) the British Columbia Park system, specifically the midcoast region, and 2) the National Wildlife Refuge system in the Willamette Valley, OR. The issues and concerns of each group...
This project gallery includes all project reports and associated assessment materials, including interactive and downloadable connectivity and climate datasets for the project " Creating Practitioner-driven, Science-based Plans for Connectivity Conservation in a Changing Climate: A Collaborative Assessment of Climate-Connectivity Needs in the Washington-British Columbia Transboundary Region".
The over-arching theme of this work is that soil data affect the performance and realism of vegetation models with particular focus on their ability to predict or explain disturbances such as fire or disease. We tested the sensitivity of the Excel version of the 3-PG model to soil properties and applied this information to understanding bark beetle attacks in drought-stressed forests. We tested the sensitivity of the MC2 model to soil depth with a particular focus on how soils affect the biogeochemistry and fire modules of the Dynamic Global Vegetation Model (DGVM). We found in these sensitivity analyses, soil depth, soil water storage capacity (ASW) and soil texture are among the most important soil factors to...
Multi-season satellite imagery (Landsat ETM+) from 1999-2001 were used in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform, aspect, etc.) to model natural and semi-natural vegetation. Landcover classes are drawn from NatureServe's Ecological System concept, with 109 of the 125 total classes mapped at the system level. For the majority of classes, a decision tree classifier was used to discriminate landcover types, while a minority of classes (e.g. urban classes, sand dunes, burn scars, etc.) were mapped using other techniques. Twenty mapping areas, each characterized by similar ecological and spectral characteristics, were modeled independently of one another. These mapping...