UPstream Regional LiDAR Model for Extent of Trout (UPRLIMET) model training and prediction data

We present a novel model development and evaluation framework, wherein we compare 26 models to predict upper distribution limits of trout in streams in Oregon using observational data collected in 2017. The models used machine learning, logistic regression, and a sophisticated nested spatial cross-v...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Jonathan D. Burnett (19659601) (author)
مؤلفون آخرون:	Brooke E. Penaluna (13049421) (author), Kelly Christiansen (2904431) (author), Ivan Arismendi (785959) (author), Sherri L. Johnson (8106482) (author), Kitty Griswold (19659604) (author), Brett Holycross (7244327) (author), Sonja H. Kolstoe (19659607) (author), William R. Hirsch (19659610) (author)
منشور في:	2025
الموضوعات:	Environmental sciences environment UPRLIMET Ecology, Ecosystems, & Environment Hydrology, watersheds, sedimentation Landscape ecology upper extent of fish inlandWaters end of fish Fish occurrence geoscientificInformation Wildlife (or Fauna) electrofishing biota
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UPstream Regional LiDAR Model for Extent of Trout (UPRLIMET) model training and prediction data

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