Treesearch

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 South Dakota. 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 t...

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 South Dakota. 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 t...

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 South Dakota. 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 t...

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 South Dakota. 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 t...

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 South Dakota. 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 t...

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 depl...

Planting a mixture of species during reforestation is of increasing interest, underlying a need to quantify the long-term effects of mixtures on stand development for a wide array of species. Here we report on ∼40 year response of three dual species mixture trials at a moderate quality site in Washington, USA where coast Douglas-fir (DF, Pseudotsuga menziesii var. menziesii) was grown at 3 m spacing in a 50:50 mix with either western hemlock (WH, Tsuga heterophylla), noble fir (NF, Abies procera) or western white pine (WWP, Pinus monticola). Stand metrics were compared for each trial between r...

Passive acoustic monitoring (PAM) has revolutionized wildlife monitoring by lowering barriers associated with data collection. Data from PAM can support adaptive management programs aimed at meeting multiple objectives in the face of uncertainty. Pairing PAM with acoustic classifiers capable of identifying sounds produced by wildlife can generate thousands of species detections across managed landscapes. However, such species detections represent both true- and false-positive detections, and human review is required to generate accurate detection data. Although collecting audio recordings is h...

With the development of cellulose nanofibril (CNF)-based adsorbents, the influence of particle size on adsorption capability has become increasingly recognized. In this study, endoglucanase FiberCare® was utilized to decrease fibril size of TEMPO-oxidized cellulose nanofibrils (TCNFs) without changing carboxyl groups content of the resulting TCNFs. Average fibril length decreased by 27.3% (from 508.7 nm to 369.4 nm) after enzymatic hydrolysis for 12 h and further decreased by 35.4% (to 328.2 nm) after 24 h. Meanwhile, the average fibril diameter decreased 20.2% (from 56.8±16.3 to 45.3±14.3) af...

Postharvest fruit losses can be 25–50 %. This study is to develop a microfibrillated cellulose (MFC)-based lowcost barrier coating technology to extend banana shelf life and decrease postharvest losses. The coating performance of MFC adding carboxymethyl cellulose (MFC/CMC) on banana was evaluated by monitoring banana peel appearance/color browning, weight loss, firmness, and total soluble solids (TSS) at the ambient condition. The results showed that MFC/CMC coating with the addition of a proper amount of CMC could effectively delay banana browning by 2 days and decrease weight loss over 30 %...