Comparing marine distribution maps for seabirds during the breeding season derived from different survey and analysis methods

Abstract

Understanding how seabirds use the marine environment is key for marine spatial planning, and maps of their marine distributions derived from transect-based surveys and from tracking of individual bird’s movements are increasingly available for the same geographic areas. Although the value of integrating these different datasets is well recognised, few studies have undertaken quantitative comparisons of the resulting distributions. Here we take advantage of four existing distribution maps and conduct a quantitative comparison for four seabird species (black-legged kittiwake Rissa tridactyla; European shag Phalacrocorax aristotelis; common guillemot Uria aalge; and razorbill Alca torda). We quantify the amount of overlap and agreement in the location of high use areas identified from either tracking or transect samples and use Bhattacharyya’s Affinity to quantify levels of similarity in the general distribution patterns. Despite multiple differences in the properties of the datasets, there was a far greater degree of overlap than would be expected by chance, except when adopting the most constrained definition of high use. Distance to the nearest conspecific colony appeared to be an important driver of the degree of similarity. Agreed areas of highest use tended to occur close to colonies and, with increasing distance from colonies, similarity between datasets declined and/or there was similarity in respect of their being relatively low usage. Interpreting reasons for agreement between data sources in some areas and not others was limited by an inability to control for the multiple potential sources of differences from both the sampling and modelling processes of the underlying datasets. Nevertheless, our quantitative comparative approach provides a valuable tool to quantify the degree to which an area’s importance is corroborated across multiple datasets, and therefore confidence that an important area has been correctly identified. This can help prioritise where the implementation of conservation measures should be targeted and identify where greatest scrutiny is required of the potential adverse environmental effects of any planned anthropogenic activities.

Linking foraging and breeding strategies in tropical seabirds

“…The BA statistic was calculated using rasters representing the 50% utilisation distribution. This allowed a reasonable size of area over which to calculate the similarity index (because the area of overlap reduces markedly with higher UDs), while excluding areas of very low usage which are of less interest and may otherwise complicate the interpretation of the calculation (Sansom et al 2018). Because the BA index is calculated between pairs of foraging trips made by one individual or between pairs of foraging trips made by different individuals within the population, the BA index across all pairwise comparisons were averaged for a given dataset.…”

A framework for mapping the distribution of seabirds by integrating tracking, demography and phenology

“…albatrosses, at-sea threats, conservation, distributions, longline fisheries, megafauna, petrels, seabird density estimating presence-absence and densities of animals at sea have been through ship-based surveys and electronic devices attached to individual animals (Eguchi, Gerrodette, Pitman, Seminoff, & Dutton, 2007;Tremblay et al, 2009). Ship-based surveys can provide a good overview of the space use of a species representing all life-history stages combined; however, they are often restricted to the surveyed area and cannot adequately describe the at-sea distribution of seabirds from a particular breeding location because the observed individuals are of unknown provenance (Mott & Clarke, 2018;Sansom, Wilson, Caldow, & Bolton, 2018). Tracking data have therefore proved vital in complementing traditional surveys and overcoming several of these limitations, improving our knowledge of how animals interact with their environment and facilitating a better understanding of the spatio-temporal distribution of seabirds and overlap with marine threats (Hays et al, 2016;Oppel et al, 2018;Sequeira et al, 2018).…”

Staying close to home: Ecological constraints on space use and range fidelity in a mountain ungulate

“…Range fidelity has been proposed to confer ecological benefits because increased familiarity with an area is predicted to enhance acquisition of nutritional resources and reduce predation risk (Greenwood, 1980 ; Schaefer et al., 2000 ), though predictable prey behavior may increase predation risk in some settings (Bowyer et al., 1999 ). Quantitative assessment of range fidelity by statistically comparing similarity of utilization distributions, using methods such as Bhattacharyya's affinity (BA) estimator, offers an informative means for characterizing the ecological underpinnings of range fidelity and has been used in a diversity of systems (Caillaud et al., 2014 ; Clapp & Beck, 2015 ; Hartman et al., 2015 ; Kochanny et al., 2009 ; Naveda‐Rodríguez et al., 2018 ; Robert et al., 2012 ; Sansom et al., 2018 ; Watson et al., 2014 ). Our findings indicate that at a broadscale mountain goats exhibit a high degree of range fidelity such that in nearly all cases (i.e., 99%, n = 138) individuals had overlapping seasonal home ranges from one year to the next, a finding comparable to earlier, less detailed study of the species (Keim, 2004 ; Schoen & Kirchoff, 1982 ; Swenson, 1985 ).…”