Ocean observatory data are useful for regional habitat modeling of species with different vertical habitat preferences

We examined habitat associations of 122 adult black sea bass Centropristis striata at a temperate reef off the coast of New Jersey, USA. The study site, located within the Historic Area Remediation Site, encompassed 46.1 km 2 and included areas of rocky bottom and highly variable bathymetry. Factors influencing dispersal and habitat use were determined from acoustic telemetry data collected between May and December 2003 from a grid of 72 moored receivers. About 2.7 times as many black sea bass used the site in summer as in fall. Fish were associated with relatively shallow, complex habitats characterized by previously placed, coarse-grain material that may have provided food, shelter, or both. Deep areas (> 27.5 m) with coarse-grain material were rarely used. Dispersal of black sea bass was not a pulse event, but rather a steady movement of individuals away from the site as inshore bottom water temperatures declined between late September and mid-December. Both temperature and photoperiod may serve as cues to the initiation of offshore movements of fish to wintering grounds near the edge of the shelf. Some black sea bass resided at the reef for periods of up to 6 mo encompassing the spawning period; as such, these habitats may be important to the continued production of the stock. In the mid-Atlantic Bight, surveys to estimate the relative abundance of this species during their inshore residency period should be conducted in July-August in structurally complex habitats and in waters < 28 m deep.

Section: Introductionmentioning

confidence: 99%

Habitat associations and dispersal of black sea bass from a mid-Atlantic Bight reef

Fabrizio¹,

Manderson²,

Pessutti³

2013

“…Link et al 2002, Nye et al 2009), while our study emphasized finescale variations in space and time. Further de velopment of our approach can provide techniques for developing dynamic models that describe essential fish habitat for ecologically and economically important species (Manderson et al 2011) and provide tactical advice for habitat conservation and other important management issues such as by-catch reduction and adaptive management (Kar & Matsuda 2006). The maps and response curves in Figs.…”

Section: Future Directionsmentioning

confidence: 99%

“…However, characteristics of ocean habitats are strongly defined by the pelagic environment for both bottom-dwelling and pelagic species (Manderson et al 2011). Many species spend at least part of their life cycle in the water column -often during the most sensitive early stages, when they suffer the highest mortality rates (Houde 2009) -and/or have prey that rely on water column characteristics (Yamashita et al 2001).…”

Section: Introductionmentioning

confidence: 99%

Improving habitat models by incorporating pelagic measurements from coastal ocean observatories

Palamara

Manderson

Kohut

et al. 2012

Self Cite

As in all temperate coastal seas, habitats in the Mid-Atlantic Bight are spatially and temporally dynamic. Understanding how species respond to the dynamics of their environment is important for developing effective management strategies. In this study, we used canonical correspondence analysis (CCA) to determine habitat variables most important in explaining variation in fish and invertebrate communities sampled with bottom trawls. We also quantified the relative explanatory power of seabed habitat features, pelagic features measured in situ and pelagic features measured remotely, all of which can be used to explain species variability. Pelagic habitat features, most notably surface and bottom temperature and stratification, explained 76% of the community variation observed, compared with 40.9% explained by seabed features, mainly depth. Remotely sensed pelagic characteristics explained 46.9% of the variation that was accounted for and were redundant for features measured in situ; this suggests that remotely sensed features are representative of features measured in situ including certain subsurface features. Cross-shelf and seasonal variation in environmental variables were the major predictors of species distributions and accounted for 71.3% of the total explained community variation. We described the seasonal dynamics of important habitat gradients and the responses of species with different habitat requirements and geographic range distributions to those gradients. We argue that consideration of dynamic pelagic features in addition to slowly changing features is important. Dynamic approaches are necessary for effective management and ocean observing systems can be used to develop dynamic space-based management strategies.KEY WORDS: Habitat characteristics · Pelagic · Remote sensing · Spatial fisheries management · Canonical correspondence analysis · CCA · Mid-Atlantic Bight Resale or republication not permitted without written consent of the publisherMar Ecol Prog Ser 447: [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] 2012 frequent and dramatic changes in the environment. In the short term the animals move to optimal habitats in new areas rather than remaining in the same location and adapting to new environmental conditions (Nye et al. 2009, Lucey & Nye 2010. They use a variety of habitats at different times in their life cycles and at different times of year. To develop effective spaceand time-based conservation strategies, it is important to un derstand how animal populations respond to changing habitat components like temperature (Yamashita et al. 2001), circulation (Bakun 2010) and primary pro duction (Yamashita et al. 2001).There is a tendency to concentrate on seabed characteristics when describing habitats selected by marine species. However, characteristics of ocean habitats are strongly defined by the pelagic environment for both bottom-dwelling and pelagic species (Manderson et al. 2011). Many species spend at least part of their life cycle in the water column -oft...

“…This information is available over a number of time intervals and across expansive seafloor landscapes. Combining visual observations with oceanographic model output or other broad-scale data may greatly contribute to the emerging body of research into regional and global predictive habitat modeling for cold-water corals, many of which remain among the most enigmatic organisms in the deep ocean (Davies & Guinotte 2011, Manderson et al 2011.…”

Section: Introductionmentioning

confidence: 99%

Environmental factors that influence the distribution, size, and biotic relationships of the Christmas tree coral Antipathes dendrochristos in the Southern California Bight

Huff¹,

Yoklavich²,

Love³

et al. 2013

The Christmas tree coral Antipathes dendrochristos is a recently discovered black coral species that represents a habitat associated with numerous sensitive taxa in the Southern California Bight. We evaluated whether broad-scale oceanographic features influence coral density and size by selecting from among generalized additive models (for density) and generalized linear models (for size) that represented competing hypotheses. We constructed models to predict coral density and size using depth, seafloor slope, surface primary productivity, bottom currents, ocean temperature, salinity, and dissolved oxygen as candidate covariates. Specifically, we evaluated hypothesized links between pelagic production and benthic coral utilization and between bottom currents and larval coral dispersal. Our analysis revealed that high surface primary productivity in combination with depth and January currents are important predictors of Christmas tree coral density. Higher coral density coincided with greater chlorophyll persistence and optimal depths near 400 m. Surface productivity increasingly was associated with Christmas tree corals at shallower depths. Our results supported the hypothesis that ocean currents affect coral density via larval dispersal mechanisms. The selected coral size models responded to similar covariates, corroborating coral density results. Fish and invertebrate ordinations indicated that Christmas tree corals were widely distributed across environmental gradients and that Christmas tree corals cooccurred with several demersal fish and invertebrates. Several predicted coral hotspots remain unprotected from fishing, particularly in areas adjacent to highly populated portions of the Southern California Bight. These regions should be targeted by future studies to confirm the presence of Christmas tree coral communities and to evaluate their vulnerability.