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      Major stopover regions and migratory bottlenecks for Nearctic-Neotropical landbirds within the Neotropics: a review

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          Summary

          Nearly 300 species of landbirds, whose populations total billions, migrate between the Neotropics and North America. Many migratory populations are in steep decline, and migration is often identified as the greatest source of annual mortality. Identifying birds’ needs on migration is therefore central to designing conservation actions for Nearctic-Neotropical migratory birds; yet migration through the Neotropics is a significant knowledge gap in our understanding of the full annual cycle. Here, we synthesise current knowledge of Neotropical stopover regions and migratory bottlenecks, focusing on long-distance, migratory landbirds that spend the boreal winter in South America. We make the important distinction between “true” stopover—involving multi-day refuelling stops—and rest-roost stops lasting < 24 hours, citing a growing number of studies that show individual landbirds making long stopovers in just a few strategic areas, to accumulate large energy reserves for long-distance flights. Based on an exhaustive literature search, we found few published stopover studies from the Neotropics, but combined with recent tracking studies, they describe prolonged stopovers for multiple species in the Orinoco grasslands (Llanos), the Sierra Nevada de Santa Marta (Colombia), and the Yucatan Peninsula. Bottlenecks for diurnal migrants are well described, with the narrowing Central American geography concentrating millions of migrating raptors at several points in SE Mexico, Costa Rica, Panama and the Darién. However, diurnally migrating aerial insectivores remain understudied, and determining stopover/roost sites for this steeply declining group is a priority. Despite advances in our knowledge of migration in the Neotropics, we conclude that major knowledge gaps persist. To identify stopover sites and habitats and the threats they face, we propose a targeted and collaborative research agenda at an expanded network of Neotropical sites, within the context of regional conservation planning strategies.

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          Carry-over effects as drivers of fitness differences in animals.

          1. Carry-over effects occur when processes in one season influence the success of an individual in the following season. This phenomenon has the potential to explain a large amount of variation in individual fitness, but so far has only been described in a limited number of species. This is largely due to difficulties associated with tracking individuals between periods of the annual cycle, but also because of a lack of research specifically designed to examine hypotheses related to carry-over effects. 2. We review the known mechanisms that drive carry-over effects, most notably macronutrient supply, and highlight the types of life histories and ecological situations where we would expect them to most often occur. We also identify a number of other potential mechanisms that require investigation, including micronutrients such as antioxidants. 3. We propose a series of experiments designed to estimate the relative contributions of extrinsic and intrinsic quality effects in the pre-breeding season, which in turn will allow an accurate estimation of the magnitude of carry-over effects. To date this has proven immensely difficult, and we hope that the experimental frameworks described here will stimulate new avenues of research vital to advancing our understanding of how carry-over effects can shape animal life histories. 4. We also explore the potential of state-dependent modelling as a tool for investigating carry-over effects, most notably for its ability to calculate optimal rates of acquisition of a multitude of resources over the course of the annual cycle, and also because it allows us to vary the strength of density-dependent relationships which can alter the magnitude of carry-over effects in either a synergistic or agonistic fashion. 5. In conclusion carry-over effects are likely to be far more widespread than currently indicated, and they are likely to be driven by a multitude of factors including both macro- and micronutrients. For this reason they could feasibly be responsible for a large amount of the observed variation in performance among individuals, and consequently warrant a wealth of new research designed specifically to decompose components of variation in fitness attributes related to processes across and within seasons. © 2010 The Authors. Journal compilation © 2010 British Ecological Society.
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            Variation in survivorship of a migratory songbird throughout its annual cycle

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              Migratory animals couple biodiversity and ecosystem functioning worldwide.

              Animal migrations span the globe, involving immense numbers of individuals from a wide range of taxa. Migrants transport nutrients, energy, and other organisms as they forage and are preyed upon throughout their journeys. These highly predictable, pulsed movements across large spatial scales render migration a potentially powerful yet underappreciated dimension of biodiversity that is intimately embedded within resident communities. We review examples from across the animal kingdom to distill fundamental processes by which migratory animals influence communities and ecosystems, demonstrating that they can uniquely alter energy flow, food-web topology and stability, trophic cascades, and the structure of metacommunities. Given the potential for migration to alter ecological networks worldwide, we suggest an integrative framework through which community dynamics and ecosystem functioning may explicitly consider animal migrations.
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                Author and article information

                Journal
                applab
                Bird Conservation International
                Bird Conservation International
                Cambridge University Press (CUP)
                0959-2709
                1474-0001
                March 2018
                October 30 2017
                March 2018
                : 28
                : 01
                : 1-26
                Article
                10.1017/S0959270917000296
                73c6c735-35c4-4fed-b16e-2c781c319822
                © 2018

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