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Keyword: data integration

Costs and benefits of multiple data sources in monitoring programs

Science Spotlights Posted on: September 04, 2019
Model development combining multiple data sources to leverage data source strengths and for improved parameter precision has increased, but with limited discussion on precision gain versus effort. Some data sources take more effort than others, thus knowing how much improvement is gained with these monitoring metrics is important for allocating samples on the landscape. Our framework allows research and monitoring programs to evaluate optimal use of limited funds when multiple data sources are available within the study design phase to meet study objectives.

Precision gain versus effort with joint models using detection/non‐detection and banding data

Publications Posted on: May 30, 2019
Capture-recapture techniques provide valuable information, but are often more cost-prohibitive at large spatial and temporal scales than less‐intensive sampling techniques. Model development combining multiple data sources to leverage data source strengths and for improved parameter precision has increased, but with limited discussion on precision gain versus effort.

When tree rings go global: Challenges and opportunities for retro- and prospective insight

Publications Posted on: December 04, 2018
The demand for large-scale and long-term information on tree growth is increasing rapidly as environmental change research strives to quantify and forecast the impacts of continued warming on forest ecosystems. This demand, combined with the now quasi-global availability of tree-ring observations, has inspired researchers to compile large tree-ring networks to address continental or even global-scale research questions.

Predicting plot basal area and tree density in mixed-conifer forest from lidar and Advanced Land Imager (ALI) data

Publications Posted on: September 10, 2007
Multispectral satellite imagery are appealing for their relatively low cost, and have demonstrated utility at the landscape level, but are typically limited at the stand level by coarse resolution and insensitivity to variation in vertical canopy structure. In contrast, lidar data are less affected by these difficulties, and provide high structural detail, but are less available due to their comparatively high cost.