A Model Approach for Estimating Colony Size, Trends, and Habitat Associations of Burrow-Nesting Seabirds

Pearson, Scott F.; Hodum, Peter; Good, Thomas P.; Schrimpf, Michael B.; Knapp, Shannon M.

doi:10.1525/cond.2013.110207

Cited by 21 publications

(18 citation statements)

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“…We then related the estimated nest density at each recorder to the three habitat features to establish a predictive relationship between the level of each habitat feature and nest density (Pearson et al 2013). Because we had only a small dataset to train this model (n = 21 recorder locations with estimated nest density), we used a powerful machine-learning algorithm based on ensembles of regression trees (Random Forest) to predict nest density for each combination of habitat features that existed along the coast of Corvo (Cutler et al 2007;Hochachka et al 2007;Olden et al 2008).…”

Section: Extrapolation Of Breeding Population Sizementioning

confidence: 99%

“…In addition, several seabird species nest in burrows or cavities, and are active in breeding colonies only during the hours of darkness. For these nocturnal burrow-nesting seabirds visual assessments of population size are not possible, and robust estimates of population size are usually based on marking a large number of birds (Sanz-Aguilar et al 2010;Sutherland and Dann 2012) or estimates of burrow occupancy (Pearson et al 2013). On many islands the marking of seabirds or inspection of burrows is logistically not feasible, because birds nest on inaccessible cliffs.…”

Section: Introductionmentioning

confidence: 99%

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Estimating population size of a nocturnal burrow-nesting seabird using acoustic monitoring and habitat mapping

Oppel¹,

Hervías²,

Oliveira³

et al. 2014

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Estimating population size of a nocturnal burrow-nesting seabird using acoustic monitoring and habitat mapping. Nature Conservation 7: 1-13. doi: 10.3897/natureconservation.7.6890 Abstract Population size assessments for nocturnal burrow-nesting seabirds are logistically challenging because these species are active in colonies only during darkness and often nest on remote islands where manual inspections of breeding burrows are not feasible. Many seabird species are highly vocal, and recent technological innovations now make it possible to record and quantify vocal activity in seabird colonies. Here we test the hypothesis that remotely recorded vocal activity in Cory's shearwater (Calonectris borealis) breeding colonies in the North Atlantic increases with nest density, and combined this relationship with cliff habitat mapping to estimate the population size of Cory's shearwaters on the island of Corvo (Azores). We deployed acoustic recording devices in 9 Cory's shearwater colonies of known size to establish a relationship between vocal activity and local nest density (slope = 1.07, R 2 = 0.86, p < 0.001). We used this relationship to predict the nest density in various cliff habitat types and produced a habitat map of breeding cliffs to extrapolate nest density around the island of Corvo. The mean predicted nest density on Corvo ranged from 6.6 (2.1-16.2) to 27.8 (19.5-36.4) nests/ha. Extrapolation of habitat-specific nest densities across the cliff area of Corvo resulted in an estimate of 6326 Cory's shearwater nests (95% confidence interval: 524). This population size estimate is similar to previous assessments, but is too imprecise to detect moderate changes in population size over time. While estimating absolute population size from acoustic recordings may not be sufficiently precise, the strong positive relationship that we found between local nest density and recorded calling rate indicates that passive acoustic monitoring may be useful to document relative changes in seabird populations over time. RESEARCH ARTICLE Launched to accelerate biodiversity conservation A peer-reviewed open-access journalSteffen Oppel et al. / Nature Conservation 7: 1-13 (2014) 2

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Section: Extrapolation Of Breeding Population Sizementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimating population size of a nocturnal burrow-nesting seabird using acoustic monitoring and habitat mapping

Oppel¹,

Hervías²,

Oliveira³

et al. 2014

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“…soil depth, aspect, etc. ), as has been done in studies with a single detection method (Pearson et al , Oppel et al ). This may be important to yield reliable predictions at larger scales that include a variety of environments.…”

Section: Discussionmentioning

confidence: 87%

Estimating the abundance of burrow‐nesting species through the statistical analysis of combined playback and visual surveys

Bonnet‐Lebrun

Calabrese

Rocamora

et al. 2016

Journal of Avian Biology

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The conservation of elusive species relies on our ability to obtain unbiased estimates of their abundance trends. Many species live or breed in cavities, making it easy to define the search units (the cavity) yet hard to ascertain their occupancy. One such example is that of certain colonial seabirds like petrels and shearwaters, which occupy burrows to breed. In order to increase the chances of detection for these types of species, their sampling can be done using two independent methods to check for cavity occupancy: visual inspection, and acoustic response to a playback call. This double‐detection process allows us to estimate the probability of burrow occupancy by accounting for the probability of detection associated with each method. Here we provide a statistical framework to estimate the occupancy and population size of burrow‐dwelling species. We show how to implement the method using both maximum likelihood and Bayesian approaches, and test its precision and bias using simulated datasets. We subsequently illustrate how to extend the method to situations where two different species may occupy the burrows, and apply it to a dataset on wedge‐tailed shearwaters Puffinus pacificus and tropical shearwaters P. bailloni on Aride Island, Seychelles. The simulations showed that the single‐species model performed well in terms of error and bias except when detection probabilities and occupancies were very low. The two‐species model applied to shearwaters showed that detection probabilities were highly heterogeneous. The population sizes of wedge‐tailed and tropical shearwaters were estimated at 13 716 (95% CI: 12 909–15 874) and 25 550 (23 667–28 777) pairs respectively. The advantages of formulating the call‐playback sampling method statistically is that it provides a framework to calculate uncertainty in the estimates and model assumptions. This method is applicable to a variety of cavity‐dwelling species where two methods can be used to detect cavity occupancy.

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“…Two colonies containing several hundred pairs of double‐crested cormorants thrived on Protection Island for many years, and a small pelagic cormorant colony existed there for several years, but eagle disturbances frequently caused colony residents to flee their nests; by 2007 all three colonies were vacant and have remained so (J. L. Hayward, unpublished data). Rhinoceros auklets ( Cerorhinca monocerata ) remain abundant breeders on Protection Island (Pearson, Hodum, Good, Schrimpf, & Knapp, ), although in 2001 they comprised the most common remains beneath an active bald eagle nest on the island (Hayward et al, ). Our informal observations suggest that auklets are preyed upon mostly during predawn hours when auklets leave their nest burrows to forage.…”

Section: Discussionmentioning

confidence: 99%

Predator–prey dynamics of bald eagles and glaucous‐winged gulls at Protection Island, Washington, USA

Henson

Desharnais

Funasaki

et al. 2019

Ecology and Evolution

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Bald eagle ( Haliaeetus leucocephalus ) populations in North America rebounded in the latter part of the twentieth century, the result of tightened protection and outlawing of pesticides such as DDT. An unintended consequence of recovery may be a negative impact on seabirds. During the 1980s, few bald eagles disturbed a large glaucous‐winged gull ( Larus glaucescens ) colony on Protection Island, Washington, USA, in the Salish Sea. Breeding gull numbers in this colony rose nearly 50% during the 1980s and early 1990s. Beginning in the 1990s, a dramatic increase in bald eagle activity ensued within the colony, after which began a significant decline in gull numbers. To examine whether trends in the gull colony could be explained by eagle activity, we fit a Lotka–Volterra‐type predator–prey model to gull nest count data and Washington State eagle territory data collected in most years between 1980 and 2016. Both species were assumed to grow logistically in the absence of the other. The model fits the data with generalized R 2 = 0.82, supporting the hypothesis that gull dynamics were due largely to eagle population dynamics. Point estimates of the model parameters indicated approach to stable coexistence. Within the 95% confidence intervals for the parameters, however, 11.0% of bootstrapped parameter vectors predicted gull colony extinction. Our results suggest that the effects of bald eagle activity on the dynamics of a large gull colony were explained by a predator–prey relationship that included the possibility of coexistence but also the possibility of gull colony extinction. This study serves as a cautionary exploration of the future, not only for gulls on Protection Island, but for other seabirds in the Salish Sea. Managers should monitor numbers of nests in seabird colonies as well as eagle activity within colonies to document trends that may lead to colony extinction.

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A Model Approach for Estimating Colony Size, Trends, and Habitat Associations of Burrow-Nesting Seabirds

Cited by 21 publications

References 203 publications

Estimating population size of a nocturnal burrow-nesting seabird using acoustic monitoring and habitat mapping

Estimating population size of a nocturnal burrow-nesting seabird using acoustic monitoring and habitat mapping

Estimating the abundance of burrow‐nesting species through the statistical analysis of combined playback and visual surveys

Predator–prey dynamics of bald eagles and glaucous‐winged gulls at Protection Island, Washington, USA

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