Treesearch

Correlative species distribution models (SDMs) are essential tools in conservation biology, global change assessment and reserve prioritization, linking species occurrences with environmental conditions. These models often rely on coarse-scale spatial and temporal predictors, overlooking fine-scale environmental conditions experienced by organisms. Additionally, SDMs commonly use short-term occurrence data to make long-term predictions, which can reduce reliability.We hypothesized that long-term and finer temporal resolution data would provide more accurate predictions by capturing...

The U.S. Department of Agriculture (USDA), Forest Service, Forest Inventory and Analysis (FIA) program provides this resource update yearly as an overview of forest resources in Washington. These estimates are derived from field data collected across a systematic network of fixed-radius forest monitoring plots located on both public and private land. New updates are provided annually as a subset of plots within the State are remeasured. Each year, field crews visit and measure a subset of all FIA plots across the entire State (the size of the subset varies by State and year). Combining all...

The U.S. Department of Agriculture (USDA), Forest Service, Forest Inventory and Analysis (FIA) program provides this resource update yearly as an overview of forest resources in Oregon. These estimates are derived from field data collected across a systematic network of fixed-radius forest monitoring plots located on both public and private land. New updates are provided annually as a subset of plots within the State are remeasured. Each year, field crews visit and measure a subset of all FIA plots across the entire State (the size of the subset varies by State and year). Combining all the...

The U.S. Department of Agriculture (USDA), Forest Service, Forest Inventory and Analysis (FIA) program provides this resource update yearly as an overview of forest resources in California. These estimates are derived from field data collected across a systematic network of fixed-radius forest monitoring plots located on both public and private land. New updates are provided annually as a subset of plots within the State are remeasured. Each year, field crews visit and measure a subset of all FIA plots across the entire State (the size of the subset varies by State and year). Combining all...

The U.S. Department of Agriculture (USDA), Forest Service, Forest Inventory and Analysis (FIA) program provides this resource update yearly as an overview of forest resources in Oregon. These estimates are derived from field data collected across a systematic network of fixed-radius forest monitoring plots located on both public and private land. New updates are provided annually as a subset of plots within the State are remeasured. Each year, field crews visit and measure a subset of all FIA plots across the entire State (the size of the subset varies by State and year). Combining all the...

The U.S. Department of Agriculture (USDA), Forest Service, Forest Inventory and Analysis (FIA) program provides this resource update yearly as an overview of forest resources in Washington. These estimates are derived from field data collected across a systematic network of fixed-radius forest monitoring plots located on both public and private land. New updates are provided annually as a subset of plots within the State are remeasured. Each year, field crews visit and measure a subset of all FIA plots across the entire State (the size of the subset varies by State and year). Combining all...

The U.S. Department of Agriculture (USDA), Forest Service, Forest Inventory and Analysis (FIA) program provides this resource update yearly as an overview of forest resources in coastal Alaska. These estimates are derived from field data collected across a systematic network of fixed-radius forest monitoring plots located on both public and private land. New updates are provided annually as a subset of plots within the State are remeasured. Each year, field crews visit and measure a subset of all FIA plots across the entire State (the size of the subset varies by State and year). Combining...

The U.S. Department of Agriculture (USDA), Forest Service, Forest Inventory and Analysis (FIA) program provides this resource update yearly as an overview of forest resources in coastal Alaska. These estimates are derived from field data collected across a systematic network of fixed-radius forest monitoring plots located on both public and private land. New updates are provided annually as a subset of plots within the State are remeasured. Each year, field crews visit and measure a subset of all FIA plots across the entire State (the size of the subset varies by State and year). Combining...

Computer vision models show great promise for assisting researchers with rapid processing of ecological data from many sources, including images from camera traps. Access to user-friendly workflows offering collaborative features, remote and local access, and data control will enable greater adoption of computer vision models and accelerate the time between data collection and analysis for many conservation and research programs. We present Njobvu-AI, a no-code tool for multiuser image labeling, model training, image classification, and review. Using this tool, we demonstrate training and...

Ecological community data are used to infer levels of environmental stressors; for example, epiphytic lichen communities can be used to estimate levels of air pollutants. If stressors are so severe that the community of interest disappears altogether, then “empty” plots are recorded. The problem compounds when multiple environmental stressors strongly influence the community. We explore this problem using simulated data and a case study of epiphytic lichens in the Sierra Nevada mountains of the United States. This area experiences relatively high amounts of nitrogen (N) deposition that can...