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Effects of surrounding land use and water depth on seagrass dynamics relative to a catastrophic algal bloom.
Breininger, David R; Breininger, Robert D; Hall, Carlton R.
Afiliación
  • Breininger DR; NASA Ecological Program, IMSS-300, Kennedy Space Center, FL, 32899, U.S.A.
  • Breininger RD; 150 W. University Boulevard, Biological Sciences, Florida Institute of Technology, Melbourne, FL, 32901, U.S.A.
  • Hall CR; NASA Ecological Program, IMSS-300, Kennedy Space Center, FL, 32899, U.S.A.
Conserv Biol ; 31(1): 67-75, 2017 02.
Article en En | MEDLINE | ID: mdl-27346673
Seagrasses are the foundation of many coastal ecosystems and are in global decline because of anthropogenic impacts. For the Indian River Lagoon (Florida, U.S.A.), we developed competing multistate statistical models to quantify how environmental factors (surrounding land use, water depth, and time [year]) influenced the variability of seagrass state dynamics from 2003 to 2014 while accounting for time-specific detection probabilities that quantified our ability to determine seagrass state at particular locations and times. We classified seagrass states (presence or absence) at 764 points with geographic information system maps for years when seagrass maps were available and with aerial photographs when seagrass maps were not available. We used 4 categories (all conservation, mostly conservation, mostly urban, urban) to describe surrounding land use within sections of lagoonal waters, usually demarcated by land features that constricted these waters. The best models predicted that surrounding land use, depth, and year would affect transition and detection probabilities. Sections of the lagoon bordered by urban areas had the least stable seagrass beds and lowest detection probabilities, especially after a catastrophic seagrass die-off linked to an algal bloom. Sections of the lagoon bordered by conservation lands had the most stable seagrass beds, which supports watershed conservation efforts. Our results show that a multistate approach can empirically estimate state-transition probabilities as functions of environmental factors while accounting for state-dependent differences in seagrass detection probabilities as part of the overall statistical inference procedure.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Conservación de los Recursos Naturales / Eutrofización Tipo de estudio: Prognostic_studies País/Región como asunto: America do norte Idioma: En Revista: Conserv Biol Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Conservación de los Recursos Naturales / Eutrofización Tipo de estudio: Prognostic_studies País/Región como asunto: America do norte Idioma: En Revista: Conserv Biol Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos