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

Abstract

The identification of geographic areas where the densities of animals are highest across their annual cycles is a crucial step in conservation planning. In marine environments, however, it can be particularly difficult to map the distribution of species, and the methods used are usually biased towards adults, neglecting the distribution of other life‐history stages even though they can represent a substantial proportion of the total population. Here we develop a methodological framework for estimating population‐level density distributions of seabirds, integrating tracking data across the main life‐history stages (adult breeders and non‐breeders, juveniles and immatures). We incorporate demographic information (adult and juvenile/immature survival, breeding frequency and success, age at first breeding) and phenological data (average timing of breeding and migration) to weight distribution maps according to the proportion of the population represented by each life‐history stage. We demonstrate the utility of this framework by applying it to 22 species of albatrosses and petrels that are of conservation concern due to interactions with fisheries. Because juveniles, immatures and non‐breeding adults account for 47%–81% of all individuals of the populations analysed, ignoring the distributions of birds in these stages leads to biased estimates of overlap with threats, and may misdirect management and conservation efforts. Population‐level distribution maps using only adult distributions underestimated exposure to longline fishing effort by 18%–42%, compared with overlap scores based on data from all life‐history stages. Synthesis and applications. Our framework synthesizes and improves on previous approaches to estimate seabird densities at sea, is applicable for data‐poor situations, and provides a standard and repeatable method that can be easily updated as new tracking and demographic data become available. We provide scripts in the R language and a Shiny app to facilitate future applications of our approach. We recommend that where sufficient tracking data are available, this framework be used to assess overlap of seabirds with at‐sea threats such as overharvesting, fisheries bycatch, shipping, offshore industry and pollutants. Based on such an analysis, conservation interventions could be directed towards areas where they have the greatest impact on populations.

Environmental drivers of movement in a threatened seabird: insights from a mechanistic model and implications for conservation

“…Moreover, due to their focus on underlying processes, mechanistic frameworks offer promising applications for predicting how individuals may be exposed to and respond to changes in their environment (Bocedi, Zurell, Reineking, & Travis, 2014; Evans et al, 2019; Leroux et al, 2013). It is also important that scientists continue tracking individuals across life‐history stages to understand variation in the drivers of habitat use among and within species, and any consequences for susceptibility of each age class to different threats (Carneiro et al, 2020; Clay et al, 2019; Hazen et al, 2012). In the context of mitigating fisheries bycatch in seabirds, the development of exciting new bio‐logging tools (e.g.…”

“…Thirteen juveniles tracked from Kerguelen and Crozet Islands (southern Indian Ocean) travelled similar distances away from their natal sites as migrating adults, but settled in separate areas (de Grissac et al, 2016). Such results underline that juveniles may face differential mortality pressures, particularly relating to incidental mortality (bycatch) in demersal and pelagic longline fisheries, which represents the greatest at‐sea threat to many seabirds (Carneiro et al, 2020; Clay et al, 2019; Dias et al, 2019). Nonetheless, the environmental drivers of movements of juvenile white‐chinned petrels and their overlap with fisheries have not been quantified.…”

“…Such results underline that juveniles may face differential mortality pressures, particularly relating to incidental mortality (bycatch) in demersal and pelagic longline fisheries, which represents the greatest at-sea threat to many seabirds (Carneiro et al, 2020;Clay et al, 2019;Dias et al, 2019). Nonetheless, the environmental drivers of K E Y W O R D S fisheries bycatch mitigation, juvenile, mechanistic movement model, ontogeny, seabirds, tracking movements of juvenile white-chinned petrels and their overlap with fisheries have not been quantified.…”

Winter fidelity, movements, and energy expenditure of Midcontinent Greater White-fronted Geese

“…Here we showed that rich location and behavior data can provide unprecedented complementary understanding of animal decision-making. Insights from these data can be particularly revealing for migratory birds that are only observed in a region for a portion of each annual cycle [ 16 ], in addition to non-migratory bird movements and behaviors among discrete habitat patches, center places (e.g., roosts) or breeding areas (e.g., leks). We anticipate that as tracking devices become increasingly miniaturized, the utility and diversity of these data to answer common questions in ecology and conservation will only increase [ 14 ].…”

Evaluating the effectiveness of a large multi‐use MPA in protecting Key Biodiversity Areas for marine predators

“…Improved knowledge of the spatiotemporal distribution of top predators during all major life history stages is crucial for a holistic understanding of population‐level habitat use and overlap with threats (Carneiro et al, in press; Clay et al, ; Reisinger et al, ). For the species breeding at South Georgia, many have been tracked throughout key life history stages.…”