New approach for using remotely sensed chlorophyll a to identify seabird hotspots

Suryan, Robert M.; Santora, Jarrod A.; Sydeman, William J.

doi:10.3354/meps09597

Cited by 77 publications

(85 citation statements)

References 36 publications

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“…In this study we examined this relationship further and found that despite the observed shifts in penguin foraging distribution between years, the foraging ranges of penguins in 2008 and 2011 consistently occurred in waters with higher Chl-a content, turbidity, SST and lower salinity than their non-foraging ranges. The presence of penguins in productive waters is in line with several studies that found that seabirds forage in areas of elevated levels of primary productivity (Weimerskirch et al, 2004;Ainley et al, 2005;Suryan et al, 2012). Areas with high Chl-a content are associated with sustained primary productivity and are therefore more likely to attract and aggregate planktivores that in turn provide predictable food sources for planktivorous fish and their predators (Grimes and Finucane, 1991;Ressler et al, 2005;Scales et al, 2014).…”

Section: Environmental Differences Between the Foraging Range And Nonsupporting

confidence: 59%

“…We think that high Chl-a biomass was probably the key determinant of penguin distribution, as Chl-a rich areas are known to aggregate prey and act as important drivers of foraging effort (Weimerskirch et al, 2004;Ainley et al, 2005;Suryan et al, 2012). Within the foraging range, the core-range of penguins occurred in stable waters with lower productivity and lower turbidity than the near-river home-range.…”

Section: Discussionmentioning

confidence: 99%

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Selective foraging within estuarine plume fronts by an inshore resident seabird

et al. 2015

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The distribution of predators relative to specific abiotic and biotic factors within estuarine plume fronts is largely unexplored due to the lack of fine-scale temporal and spatial oceanographic data. Defining preferred foraging conditions of seabirds in these areas is critical to identifying important foraging habitats. Here, we use data obtained from Ships of Opportunity to improve the way we quantify oceanographic conditions at scales that match marine animal foraging activities within these areas. Using biologgers and data from a Ship of Opportunity, we assessed the fine-scale habitat utilization of the Little Penguin (Eudyptula minor) within an estuarine plume in Victoria, Australia. We assessed how environmental conditions within the home-range (transit and foraging) and core-range (subset area of intensive foraging within the home-range) of this inshore seabird differed to environmental conditions in the accessible, but non-utilized range (i.e., non-foraging range). Penguin foraging ranges occurred in waters with higher Chl-a, turbidity, temperature and lower salinity than non-foraging ranges. High Chl-a biomass was the most important explanatory variable of penguin distribution. Environmental conditions between the core-range and less used home-range also differed. Waters in the core-range were less productive, less turbid and less dynamic. We suggest penguins are foraging in these core-ranges due to the productive yet stable environmental conditions that likely offer a higher degree of prey predictability than the fluctuating conditions in the wider home-range. Furthermore, penguins may spend a greater proportion of their time in core-ranges as these waters have relatively low turbidity and may improve the ability of penguins to detect and capture their prey. Our results highlight the ability of a small-ranging, visual predator to selectively forage in waters with favorable conditions at fine-scales as a potential means to improve foraging efficiency.

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Section: Environmental Differences Between the Foraging Range And Nonsupporting

confidence: 59%

Section: Discussionmentioning

confidence: 99%

Selective foraging within estuarine plume fronts by an inshore resident seabird

et al. 2015

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“…We explored the relationships between common loon distribution and abundance and multiple spatially explicit environmental covariates including latitude, longitude, closest distance to coast, water depth, sediment median grain size, bottom roughness and multiple metrics of remotely sensed chlorophyll a (chl a). Several of these environmental covariates relate to the distribution and abundance of other species of marine birds (Louzao et al 2009, Tremblay et al 2009, Suryan et al 2012, Watson et al 2013, which allowed us to determine whether these covariates relate to spatial patterns of common loons using marine waters in the Northwest Atlantic.…”

Section: Introductionmentioning

confidence: 99%

Spatially explicit model of wintering common loons: conservation implications

Winiarski¹,

Miller²,

Paton³

et al. 2013

Mar. Ecol. Prog. Ser.

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Common loons Gavia immer are a conservation concern in New England due to a variety of anthropogenic factors, yet little is known about biotic and abiotic environmental factors determining their wintering distribution and abundance in nearshore and offshore waters. The primary objective of this study was to develop a spatially explicit abundance model of wintering common loons in the maritime waters of southern New England (USA) that could inform decisions about offshore development. Aerial line-transect surveys were conducted throughout a 3800 km 2 study area off the coast of Rhode Island during the winters of 2010-2011 and 2011-2012. A density surface model (DSM) approach was used to account for imperfect detection and incorporate spatially explicit environmental covariates. Common loon densities were greatest in waters < 35 m deep, with high chl a surface concentrations (> 2 mg m −3). The DSM predicted 5047 (95% CI = 3993−6379) common loons in the study area during winter, which suggests this region provides key habitat for this species in eastern North America. This study highlights important areas for common loons in the region, suggests key biotic (primary productivity as measured by long-term chl a surface concentrations) and abiotic covariates (water depth) driving the spatial distribution and abundance of common loons in southern New England, and identifies sites that should be considered for protection from offshore development, including offshore wind facilities.

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“…Resource distribution in relation to animal behavior is often estimated from satellite-derived chlorophyll-a (e.g., Guinet et al, 2001;Bradshaw et al, 2004;Suryan et al, 2012), but depth data are lacking. These data also become increasingly scarce and unreliable in polar regions due to cloud cover (Sumner et al, 2003), and are often spatially mismatched with animal behavior due to error inherent in animal location estimates (Ekstrom, 2004;Costa et al, 2010b).…”

Section: Discussionmentioning

confidence: 99%

Foraging strategy switch of a top marine predator according to seasonal resource differences

et al. 2015

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The spatio-temporal variability in marine resources influences the foraging behavior and success of top marine predators. However, little is known about the links between these animals and ocean productivity, specifically, how plankton density influences their foraging behavior. Southern elephant seals (Mirounga leonina) have two annual at-sea foraging trips: a 2 month post-breeding foraging trip (Nov-Jan) that coincides with elevated summer productivity; and an 8 month post-molting foraging trip (Feb-Oct) over winter, when productivity is low. Physical parameters are often used to describe seal habitat, whereas information about important biological parameters is lacking. We used electronic tags deployed on elephant seals during both trips to determine their movement and foraging behavior. The tags also recorded light, which measured the bio-optical properties of the water column, the bulk of which is presumably influenced by phytoplankton. We investigated the relationship between plankton density and seal foraging behavior; comparing trends between summer and winter trips. We found a positive relationship between plankton density and foraging behavior, which did not vary seasonally. We propose that profitable concentrations of seal prey are more likely to coincide with planktonic aggregations, but we also acknowledge that trophic dynamics may shift in response to seasonal trends in productivity. Seal prey (mid-trophic level) and plankton (lower-trophic level) are expected to overlap in space and time during summer trips when peak phytoplankton blooms occur. In contrast, aggregated patches of lower trophic levels are likely to be more dispersed during winter trips when plankton density is considerably lower and heterogeneous. These results show that southern elephant seals are able to exploit prey resources in different ways throughout the year as demonstrated by the variation observed between seal foraging behavior and trophic dynamics.

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New approach for using remotely sensed chlorophyll a to identify seabird hotspots

Cited by 77 publications

References 36 publications

Selective foraging within estuarine plume fronts by an inshore resident seabird

Selective foraging within estuarine plume fronts by an inshore resident seabird

Spatially explicit model of wintering common loons: conservation implications

Foraging strategy switch of a top marine predator according to seasonal resource differences

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