Identifying marine Important Bird Areas using at-sea survey data

Smith, Melanie A.; Free, Christopher M.; Kirchhoff, Matthew J.; Drew, Gary S.; Warnock, Nils; Stenhouse, Iain J.

doi:10.1016/j.biocon.2014.02.039

Cited by 23 publications

(27 citation statements)

References 45 publications

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“…Although seabird sampling methodology is relatively standardized, data can be collected using either aircraft or ships and continuous or discrete transects (Tasker et al, 1984). Additionally, the number and duration of studies is much smaller as compared to terrestrial locations, such that it is difficult to use any one survey effort to determine hotspot/coldspot locations and combining data requires standardizing across sampling discrepancies (Smith et al, 2014). The second issue is that seabird populations tend to have patchy aggregations with extremely skewed distributions (Beauchamp, 2011).…”

Section: Introductionmentioning

confidence: 99%

“…Ongoing research efforts have focused on compiling all available seabird data in the OCS into the Atlantic Seabird Compendium (O'Connell et al, 2009), allowing an unprecedented opportunity to examine species' uses of the marine environment. Detailed spatio-temporal models of the occurrence and abundance of birds and other highly mobile species in the offshore marine environment are challenging (Smith et al, 2014). Our purpose here is not to create such a complicated model, but instead to develop a general framework that can be applied with a minimum of input data to provide a first-order estimate of retrospective and prospective statistical power to guide interpretation of past data collection efforts and planning of future surveys.…”

Section: Introductionmentioning

confidence: 99%

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Statistical guidelines for assessing marine avian hotspots and coldspots: A case study on wind energy development in the U.S. Atlantic Ocean

Zipkin

Kinlan

Sussman

et al. 2015

Biological Conservation

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a b s t r a c t Keywords:Marine spatial planning Model selection Power analysis Seabirds Sampling design Wind energy development Estimating patterns of habitat use is challenging for marine avian species because seabirds tend to aggregate in large groups and it can be difficult to locate both individuals and groups in vast marine environments. We developed an approach to estimate the statistical power of discrete survey events to identify species-specific hotspots and coldspots of long-term seabird abundance in marine environments. We illustrate our approach using historical seabird data from survey transects in the U.S. Atlantic Ocean Outer Continental Shelf (OCS), an area that has been divided into "lease blocks" for proposed offshore wind energy development. For our power analysis, we examined whether discrete lease blocks within the region could be defined as hotspots (3× mean abundance in the OCS) or coldspots (1/3×) for individual species within a given season. For each of 74 species/season combinations, we determined which of eight candidate statistical distributions (ranging in their degree of skewedness) best fit the count data. We then used the selected distribution and estimates of regional prevalence to calculate and map statistical power to detect hotspots and coldspots, and estimate the p-value from Monte Carlo significance tests that specific lease blocks are in fact hotspots or coldspots relative to regional average abundance. The power to detect species-specific hotspots was higher than that of coldspots for most species because species-specific prevalence was relatively low (mean: 0.111; SD: 0.110). The number of surveys required for adequate power (N 0.6) was large for most species (tens to hundreds) using this hotspot definition. Regulators may need to accept higher proportional effect sizes, combine species into groups, and/or broaden the spatial scale by combining lease blocks in order to determine optimal placement of wind farms. Our power analysis approach provides a general framework for both retrospective analyses and future avian survey design and is applicable to a broad range of research and conservation problems.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Statistical guidelines for assessing marine avian hotspots and coldspots: A case study on wind energy development in the U.S. Atlantic Ocean

Zipkin

Kinlan

Sussman

et al. 2015

Biological Conservation

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“…At-sea surveys are an established approach to inform marine spatial planning at regional (Smith et al 2014), national (Kober et al 2012) and international (Lambert et al 2017) scales. The best method to use is dependent on the species of interest, the area to be covered, accessibility and the amount of resources available.…”

Section: Introductionmentioning

confidence: 99%

Assessing the effectiveness of foraging radius models for seabird distributions using biotelemetry and survey data

et al. 2019

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Relatively simple foraging radius models have the potential to generate predictive distributions for a large number of species rapidly, thus providing a cost-effective alternative to large-scale surveys or complex modelling approaches. Their effectiveness, however, remains largely untested. Here we compare foraging radius distribution models for all breeding seabirds in Ireland, to distributions of empirical data collected from tracking studies and aerial surveys. At the local/colony level, we compared foraging radius distributions to GPS tracking data from seabirds with short (Atlantic puffin Fratercula arctica, and razorbill Alca torda) and long (Manx shearwater Puffinus puffinus, and European storm-petrel Hydrobates pelagicus) foraging ranges. At the regional/national level, we compared foraging radius distributions to extensive aerial surveys conducted over a two-year period. Foraging radius distributions were significantly positively correlated with tracking data for all species except Manx shearwater. Correlations between foraging radius distributions and aerial survey data were also significant, but generally weaker than those for tracking data. Correlations between foraging radius distributions and aerial survey data were benchmarked against generalised additive models (GAMs) of the aerial survey data that included a range of environmental covariates. While GAM distributions had slightly higher correlations with aerial survey data, the results highlight that the foraging radius approach can be a useful and pragmatic approach for assessing breeding distributions for many seabird species. The approach is likely to have acceptable utility in complex, temporally variable ecosystems and when logistic and financial resources are limited.

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“…Mixing of these currents occurs north of SLI and facilitates prey availability for piscivores (murres), planktivores (auklets), and omnivores (fulmars; Piatt and Springer 2003). All cholera-impacted species from this event occupy coastal waters surrounding SLI, which have been designated Globally Important Bird Areas of the United States (Smith et al 2014).…”

mentioning

confidence: 99%