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- A framework for mapping the distribution of seabirds by integrating tracking, demography and phenologyPublication . Carneiro, Ana Paula B.; Pearmain, Elizabeth J.; Oppel, Steffen; Clay, Thomas A.; Phillips, Richard A.; Bonnet‐Lebrun, Anne‐Sophie; Wanless, Ross M.; Abraham, Edward; Richard, Yvan; Rice, Joel; Handley, Jonathan; Davies, Tammy E.; Dilley, Ben J.; Ryan, Peter G.; Small, Cleo; Arata, Javier; Arnould, John P. Y.; Bell, Elizabeth; Bugoni, Leandro; Letizia, Campioni; Catry, Paulo; Cleeland, Jaimie; Deppe, Lorna; Elliott, Graeme; Freeman, Amanda; Gonzalez-Solis, Jacob; Granadeiro, José Pedro; Grémillet, David; Landers, Todd J.; Makhado, Azwianewi; Nel, Deon; Nicholls, David G.; Rexer‐Huber, Kalinka; Robertson, Christopher J. R.; Sagar, Paul M.; Scofield, Paul; Stahl, Jean‐Claude; Stanworth, Andrew; Stevens, Kim L.; Trathan, Philip N.; Thompson, David R.; Torres, Leigh; Walker, Kath; Waugh, Susan M.; Weimerskirch, Henri; Dias, Maria P.1. 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. 2. Here we develop a methodological framework for estimating populationlevel 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. 3. 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 lifehistory stages. 4. 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.
- Methods to detect spatial biases in tracking studies caused by differential representativeness of individuals, populations and timePublication . Pujol, Virginia Morera; Catry, Paulo; Magalhães, Maria; Peron, Clara; Reyes‐González, José Manuel; Granadeiro, José P.; Militão, Teresa; Dias, Maria P.; Oro, Daniel; Dell'Omo, Giacomo; Müller, Martina; Paiva, Vitor H.; Metzger, Benjamin; Neves, V C; Navarro, Joan; Karris, Georgios; Xirouchakis, Stavros; Cecere, Jacopo G.; Zamora‐López, Antonio; Forero, Manuel G.; Ouni, Ridha; Romdhane, Mohamed Salah; De Felipe, Fernanda; Zajková, Zuzana; Cruz‐Flores, Marta; Grémillet, David; González‐Solís, Jacob; Ramos, RaülAim Over the last decades, the study of movement through tracking data has grown exceeding the expectations of movement ecologists. This has posed new challenges, specifically when using individual tracking data to infer higher-level distributions (e.g. population and species). Sources of variability such as individual site fidelity (ISF), environmental stochasticity over time, and space-use variability across species ranges must be considered, and their effects identified and corrected, to produce accurate estimates of spatial distribution using tracking data. Innovation We developed R functions to detect the effect of these sources of variability in the distribution of animal groups when inferred from individual tracking data. These procedures can be adapted for their use in most tracking datasets and tracking techniques. We demonstrated our procedures with simulated datasets and showed their applicability on a real-world dataset containing 1346 year-round migratory trips from 805 individuals of three closely related seabird species breeding in 34 colonies in the Mediterranean Sea and the Atlantic Ocean, spanning 10 years. We detected an effect of ISF in one of the colonies, but no effect of the environmental stochasticity on the distribution of birds for any of the species. We also identified among-colony variability in nonbreeding space use for one species, with significant effects of population size and longitude. Main conclusions This work provides a useful, much-needed tool for researchers using animal tracking data to model species distributions or establish conservation measures. This methodology may be applied in studies using individual tracking data to accurately infer the distribution of a population or species and support the delineation of important areas for conservation based on tracking data. This step, designed to precede any analysis, has become increasingly relevant with the proliferation of studies using large tracking datasets that has accompanied the globalization process in science driving collaborations and tracking data sharing initiatives.