Composition of Larval, Juvenile, and Small Adult Fishes Relative to Changes in Environmental Conditions in Florida Bay

Habitat selection by top predators that are largely free from predation pressures is a function of prey availability and interspecific competition. Such competition can be minimized through niche dimensions: mechanism of resource partitioning based on prey choice and foraging tactic. This study compared habitat use patterns of 5 top predators (bottlenose dolphins, doublecrested cormorants, osprey, brown pelicans and terns) within Florida Bay with respect to each other, their prey and habitat variability. Foraging dolphins, osprey and pelicans exhibited similar habitat use patterns in shallow, turbid, productive waters with high proportions of mud and mudbank bottom types. These same habitat characteristics also described the distribution of their major prey items: mullet and catfish. Competition between these 3 predators is likely diluted by foraging tactic variation. Conversely, the habitat use patterns of cormorants showed strongest association with deeper water, with low chlorophyll a and turbidity levels, less mud and mudbank habitat, and greater proportions of hardbottom and seagrass bottoms. Those prey items of cormorants with less competition from other predators examined displayed the same habitat associations. Cormorants in Florida Bay may concentrate their foraging efforts on less competitive prey, occurring more frequently in habitats where these prey items dominate. Despite Florida Bay's limited bathymetric relief, habitat use patterns of top predators are significantly influenced by depth, and subsequently bottom type. Sighting rates of all predators, except non-foraging dolphins, peaked in shallow mudbank habitats. This pattern of strong habitat overlap among predators implies currently adequate resource availability and/or niche dimensions among interspecific competitors.KEY WORDS: Habitat use · Competition · Foraging tactics · Seabirds · Bottlenose dolphin · Habitat structure · Niche overlap · Nonmetric multidimensional scaling Resale or republication not permitted without written consent of the publisherMar Ecol Prog Ser 375: [289][290][291][292][293][294][295][296][297][298][299][300][301][302][303][304] 2009 and facilitate coexistence among interspecific competitors: the greater the number of niche dimensions, the greater potential for diffuse competition (Pianka 1974). May & MacArthur (1972) examined niche overlap between species as a function of environmental variability in an ecosystem with strong, constant competition for a resource. Pianka (1974) built upon this work to describe his 'niche overlap hypothesis', applicable when the supply of resources is variable. Pianka (1974) illustrated that interspecific niche overlap does not imply competition, but rather when resources are plentiful, organisms can share them without conflict (high niche overlap = reduced competition). Conversely, disparate niches between competitors indicates competition avoidance when resources are scarce (low niche overlap = increased competition).Comparative habitat use studies between seabird species ...

Section: Methodsmentioning

confidence: 98%

A kaleidoscope of mammal, bird and fish: habitat use patterns of top predators and their prey in Florida Bay

Torres¹

2009

“…Rakocinski et al 1992) and in unvegetated backwaters (McMicheal & Peters 1989). The distribution of juveniles of spotted seatrout was centered in the middle of the estuary in seagrass beds in Florida Bay (Thayer et al 1999) and in mid-estuary salt marshes in a northern Gulf of Mexico estuary (Rakocinski et al 1992). In Charlotte Harbor, the distribution of these juveniles was also centered in mid-estuary sites characterized by relatively large areas of discontinuous seagrass habitat.…”

Section: Individual Species Modelsmentioning

confidence: 99%

“…Seagrass beds are also considered to be the primary habitat for juveniles of spotted seatrout Cynoscion nebulosus (McMicheal & Peters 1989, Rooker et al 1998, Thayer et al 1999), although they can also be found in high abundance along marsh edges (e.g. Rakocinski et al 1992) and in unvegetated backwaters (McMicheal & Peters 1989).…”

Section: Individual Species Modelsmentioning

confidence: 99%

Using estuarine landscape structure to model distribution patterns in nekton communities and in juveniles of fishery species

Whaley¹,

Burd²,

Robertson³

2007

Spatial relationships between distribution patterns of many species and vegetated habitats over multiple scales have been used in terrestrial ecosystems to help identify and map important areas for conservation and management. This approach is not widely used in characterizing habitat use of nekton species in estuaries, but it has great potential because these systems contain fairly discrete vegetated habitat types, and the distribution of nekton species can be influenced by the spatial arrangement of habitat. We examined the spatial relationships between estuarine habitats and nekton species to help map estuarine nekton communities for use in conservation planning. Using a Geographic Information System (GIS), we measured area (m 2 ) and edge density (m km -2 ) of estuarine habitats over multiple scales in Charlotte Harbor, Florida (USA). We used redundancy analysis (RDA) to examine spatial patterns of nekton community composition, habitat, and local habitat characteristics. RDA revealed that spatial patterns in nekton community composition were most highly correlated with distance from the nearest pass to the Gulf of Mexico (r = -0.97) and with salinity (r = 0.94) and area of continuous seagrass habitat (r = 0.91). We used GIS maps of 2 variables (distance from the nearest pass and area of continuous seagrass habitat) to model spatial patterns in nekton community composition and the distribution of several juveniles of fishery species (red drum Sciaenops ocellatus, gray snapper Lutjanus griseus, lane snapper L. synagris, sand seatrout Cynoscion arenarius, and spotted seatrout C. nebulosus). The results suggest that incorporating measures of habitat area (over multiple scales) and spatial position into spatial models of nekton distribution is useful in conservation and management planning.

“…Common approaches taken to link eelgrass habitat with animal abundance have included field sampling for animals inside and outside of seagrass beds of varying size and/or density (Orth et al 1984, Heck et al 1995, Szedlmayer & Able 1996, Duffy & Baltz 1998, Scott-Denton 1999, Thayer et al 1999, comparative sampling of animal populations in different estuaries or embayments with differing amounts of eelgrass density or coverage (Heck & Orth 1980, Deegan et al 1997, Wyda et al 2002, eelgrass canopy removal in the field (Connolly 1994), and experimental studies completed in a laboratory setting (Heck & Thoman 1981, Graham et al 1998.…”

Section: Introductionmentioning

confidence: 99%

Experimental studies of predation by bluefish Pomatomus saltatrix in varying densities of seagrass and macroalgae

Harris

Buckley²,

Nixon³

et al. 2004

ABSTRACT:We conducted ecosystem level experiments to investigate predator-prey relationships in 3 habitat types; eelgrass Zostera marina, macroalgae, and bare sediment. Mesocosms containing marine sediments, coastal water, and varying densities of eelgrass (75 to 1000 shoots m -2 ) or macroalgae (50 to 1000 g wet weight m -2 ) were used to simulate conditions found in shallow coastal lagoons of Rhode Island, USA. We used bluefish Pomatomus saltatrix as predators in each experiment after appropriate acclimation in each habitat type. Prey fish were provided in equally weighted rations and included silversides Menidia menidia, tautog Tautoga onitis, cunner Tautogolabrus adspersus, and menhaden Brevoortia tyrranus. Eelgrass significantly increased the survivorship of silversides, tautog and cunner at very low shoot densities. Experiments using macroalgae did not result in significantly different survival rates between bare sand and macroalgae habitat for silversides or cunner, the 2 species tested for this vegetation type. With the decline of eelgrass and increase of macroalgal cover in shallow coastal areas of Rhode Island, this information increases our understanding of the relative value of eelgrass habitat to fish stocks and should provide added incentive to protect and conserve existing eelgrass beds.