4.2 Article

Predictive habitat modelling of reef fishes with contrasting trophic ecologies

Journal

MARINE ECOLOGY PROGRESS SERIES
Volume 474, Issue -, Pages 201-216

Publisher

INTER-RESEARCH
DOI: 10.3354/meps10099

Keywords

Spatial predictive modelling; Habitat mapping; Generalised additive model; GAM; Multi-species; Abundance; GIS; Azores

Funding

  1. European Marie Curie Research Training Network FREESUBNET [MRTN-CT-2006-036186]
  2. Portuguese Foundation for Science and Technology (FCT) [SFRH/BD/66117/2009]
  3. project CLIPE [FCT-Praxis XXI/3/3.2/EMG/1957/95]
  4. project MARE [LIFE B4-3200/98-509]
  5. project MARE-FISH [FCT-POCTI/BSE/41207/2001]
  6. project OGAMP [INTERREGIIIb/MAC/4.2/A2 2001]
  7. project MARMAC [INTERREGIIIb-03/MAC/4.2/A1 2004]
  8. Projecto Estrategio LA9 [PEst-OE/EEI/LA0009/2011]
  9. FCT/MCE

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The success of marine spatial management and, in particular, the zonation of marine protected areas (MPAs), largely depends on the good understanding of species' distribution and habitat preferences. Yet, detailed knowledge of fish abundance is often reduced to a few sampled locations and a reliable prediction of this information across broader geographical areas is of major relevance. Generalised additive models (GAMs) were used to describe species-environment relationships and identify environmental parameters that determine the abundance or presence-absence of 11 reef fishes with contrasting life histories in shallow habitats of the Azores islands, Northeast Atlantic. Predictive models were mapped and visualised in a geographic information system (GIS) and areas with potential single or multi-species habitat hotspots were identified. Schooling, pelagic species typically required presence-absence models, whereas abundance models performed well for benthic species. Depth and distance to sediment significantly described the distribution for nearly all species, whereas the influence of exposure to swell or currents and slope of the seafloor depended on their trophic ecology. Potential presence of single species was widespread across the study area but much reduced for multiple species. There were no habitats shared by high abundances of all species in a given trophic group, and areas shared by minimal abundances were smaller than expected. Potential habitat hotspots should be considered as priority sites for conservation, but were only partially included in the existing MPA network. These findings highlight the potential of this methodology to support scientifically sound conservation planning, including but not restricted to fragmented and constrained habitats, such as those of oceanic archipelagos.

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