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Assessment Indices of Littoral Habitat Condition for Lakes in Maine and New England, USA.
Deeds, Jeremy; Amirbahman, Aria; Hugger, Kirsten; Kaufmann, Philip R; Matthews, Leslie J; Merrell, Kellie; Norton, Stephen A.
Afiliación
  • Deeds J; The Maine Department of Environmental Protection, Augusta, Maine 04333.
  • Amirbahman A; Department of Civil, Environmental and Sustainable Engineering, Santa Clara University, Santa Clara, California 95053.
  • Hugger K; The New Hampshire Department of Environmental Services, Concord, NH 03302.
  • Kaufmann PR; US Environmental Protection Agency, Office of Research and Development, Center for Public Health and Environmental Assessment, Pacific Ecological Systems Division, Corvallis, OR, and Department of Fisheries, Wildlife and Conservation Sciences, Oregon State University, Corvallis, Oregon 97331, USA.
  • Matthews LJ; The Vermont Department of Environmental Conservation, Montpelier, VT 05620.
  • Merrell K; The Vermont Department of Environmental Conservation, Montpelier, VT 05620.
  • Norton SA; School of Earth and Climate Sciences, University of Maine, Orono, Maine 04469.
Lake Reserv Manag ; 39(2): 141-155, 2023 Jul 10.
Article en En | MEDLINE | ID: mdl-37969555
ABSTRACT
Littoral habitat is critical for lake biota but is adversely affected by residential shoreland development through the loss and reduced structural complexity of lakeshore vegetation. There currently exists no assessment methodology for evaluating littoral habitat condition of individual lakes in northeastern US. We addressed this assessment need by creating multi-metric indices of littoral habitat condition that focus on lakeshore residential development as the primary stressor. We did this by using habitat metrics derived primarily from National Lake Assessment (NLA) Physical Habitat (PHAB) survey field observations to create Linear Discriminant Analysis (LDA) models that assign lakeshore stations into littoral habitat condition categories. Lake PHAB survey data were used from New England NLA surveys as well as state-level surveys completed in Maine, New Hampshire, and Vermont. Prediction success rates in New England models averaged 83%. The Maine LDA models, which used finer scale survey methods, had an average prediction success rate of 89%. We used 95% bootstrapped confidence intervals to make assessment designations of natural (meeting reference quality), diminished (not meeting reference quality), or intermediate (existing between natural and diminished) littoral habitat condition for each lake. Our results show that efficacious single-lake littoral habitat assessments may be completed within the framework of NLA PHAB methodology, but confidence in assessment results, and therefore better-informed management decisions, can be improved with finer-scale observation data.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Lake Reserv Manag Año: 2023 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Lake Reserv Manag Año: 2023 Tipo del documento: Article
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