Summary1. 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.

Identifying the factors that control population dynamics in migratory animals has been constrained by our inability to track individuals throughout the annual cycle. Using stable carbon isotopes, we show that the reproductive success of a long-distance migratory bird is influenced by the quality of habitat located thousands of kilometres away on tropical wintering grounds. For male American redstarts (Setophaga ruticilla), winter habitat quality influenced arrival date on the breeding grounds, which in turn affected key variables associated with reproduction, including the number of young fledged. Based on a winterhabitat model, females occupying high-quality winter habitat were predicted to produce more than two additional young and to fledge offspring up to a month earlier compared with females wintering in poorquality habitat. Differences of this magnitude are highly important considering redstarts are single brooded, lay clutches of only three to five eggs and spend only two-and-a-half months on the breeding grounds. Results from this study indicate the importance of understanding how periods of the annual cycle interact for migratory animals. Continued loss of tropical wintering habitat could have negative effects on migratory populations in the following breeding season, minimizing density-dependent effects on the breeding grounds and leading to further population declines. If conservation efforts are to be successful, strategies must incorporate measures to protect all the habitats used during the entire annual cycle of migratory animals.

BackgroundMigratory animals comprise a significant portion of biodiversity worldwide with annual investment for their conservation exceeding several billion dollars. Designing effective conservation plans presents enormous challenges. Migratory species are influenced by multiple events across land and sea–regions that are often separated by thousands of kilometres and span international borders. To date, conservation strategies for migratory species fail to take into account how migratory animals are spatially connected between different periods of the annual cycle (i.e. migratory connectivity) bringing into question the utility and efficiency of current conservation efforts.Methodology/Principal FindingsHere, we report the first framework for determining an optimal conservation strategy for a migratory species. Employing a decision theoretic approach using dynamic optimization, we address the problem of how to allocate resources for habitat conservation for a Neotropical-Nearctic migratory bird, the American redstart Setophaga ruticilla, whose winter habitat is under threat. Our first conservation strategy used the acquisition of winter habitat based on land cost, relative bird density, and the rate of habitat loss to maximize the abundance of birds on the wintering grounds. Our second strategy maximized bird abundance across the entire range of the species by adding the constraint of maintaining a minimum percentage of birds within each breeding region in North America using information on migratory connectivity as estimated from stable-hydrogen isotopes in feathers. We show that failure to take into account migratory connectivity may doom some regional populations to extinction, whereas including information on migratory connectivity results in the protection of the species across its entire range.Conclusions/SignificanceWe demonstrate that conservation strategies for migratory animals depend critically upon two factors: knowledge of migratory connectivity and the correct statement of the conservation problem. Our framework can be used to identify efficient conservation strategies for migratory taxa worldwide, including insects, birds, mammals, and marine organisms.

Summary1. Threats to migratory animals can occur at multiple periods of the annual cycle that are separated by thousands of kilometres and span international borders. Populations of the iconic monarch butterfly (Danaus plexippus) of eastern North America have declined over the last 21 years. Three hypotheses have been posed to explain the decline: habitat loss on the overwintering grounds in Mexico, habitat loss on the breeding grounds in the United States and Canada, and extreme weather events. 2. Our objectives were to assess population viability, determine which life stage, season and geographical region are contributing the most to population dynamics and test the three hypotheses that explain the observed population decline. 3. We developed a spatially structured, stochastic and density-dependent periodic projection matrix model that integrates patterns of migratory connectivity and demographic vital rates across the annual cycle. We used perturbation analysis to determine the sensitivity of population abundance to changes in vital rate among life stages, seasons and geographical regions. Next, we compared the singular effects of each threat to the full model where all factors operate concurrently. Finally, we generated predictions to assess the risk of host plant loss as a result of genetically modified crops on current and future monarch butterfly population size and extinction probability. 4. Our year-round population model predicted population declines of 14% and a quasiextinction probability (<1000 individuals) >5% within a century. Monarch abundance was more than four times more sensitive to perturbations of vital rates on the breeding grounds than on the wintering grounds. Simulations that considered only forest loss or climate change in Mexico predicted higher population sizes compared to milkweed declines on the breeding grounds. Our model predictions also suggest that mitigating the negative effects of genetically modified crops results in higher population size and lower extinction risk. 5. Recent population declines stem from reduction in milkweed host plants in the United States that arise from increasing adoption of genetically modified crops and land-use change, not from climate change or degradation of forest habitats in Mexico. Therefore, reducing the negative effects of host plant loss on the breeding grounds is the top conservation priority to slow or halt future population declines of monarch butterflies in North America.

ABSTRACT. We describe a new collaborative network, the Motus Wildlife Tracking System (Motus; https://motus.org), which is an international network of researchers using coordinated automated radio-telemetry arrays to study movements of small flying organisms including birds, bats, and insects, at local, regional, and hemispheric scales. Radio-telemetry has been a cornerstone of tracking studies for over 50 years, and because of current limitations of geographic positioning systems (GPS) and satellite transmitters, has remained the primary means to track movements of small animals with high temporal and spatial precision. Automated receivers, along with recent miniaturization and digital coding of tags, have further improved the utility of radio-telemetry by allowing many individuals to be tracked continuously and simultaneously across broad landscapes. Motus is novel among automated arrays in that collaborators employ a single radio frequency across receiving stations over a broad geographic scale, allowing individuals to be detected at sites maintained by others. Motus also coordinates, disseminates, and archives detections and associated metadata in a central repository. Combined with the ability to track many individuals simultaneously, Motus has expanded the scope and spatial scale of research questions that can be addressed using radio-telemetry from local to regional and even hemispheric scales. Since its inception in 2012, more than 9000 individuals of over 87 species of birds, bats, and insects have been tracked, resulting in more than 250 million detections. This rich and comprehensive dataset includes detections of individuals during all phases of the annual cycle (breeding, migration, and nonbreeding), and at a variety of spatial scales, resulting in novel insights into the movement behavior of small flying animals. The value of the Motus network will grow as spatial coverage of stations and number of partners and collaborators increases. With continued expansion and support, Motus can provide a framework for global collaboration, and a coordinated approach to solving some of the most complex problems in movement biology and ecology.Le Système de suivi de la faune Motus : un réseau de recherche collaboratif visant à mieux comprendre le déplacement des animaux RÉSUMÉ. Le Système de suivi de la faune Motus (Motus; https://motus.org), un nouveau réseau collaboratif de chercheurs internationaux, repose sur un ensemble coordonné de stations automatisées de radiotélémétrie pour étudier le déplacement de petits organismes volant, comme les oiseaux, les chauves-souris et les insectes, aux échelles locales et régionales, et à celle de l'hémisphère. Pierre angulaire pour les études de suivi depuis plus de 50 ans, la radiotélémétrie est encore le principal moyen de suivre le déplacement de petits animaux avec une grande précision temporelle et spatiale, en raison des limites que présentent les émetteurs basés sur le système de positionnement géographique (GPS) ou satellite. Des stations réceptrices automatisées,...

Abstract. The term 'carryover effect' originally arose from repeated measures clinical experiments.However, the term has more recently been applied to ecological and evolutionary studies, often in migratory systems, which has led to an emphasis on non-lethal effects across seasons. In this article, we suggest that ecological carryover effects can also occur between life-history stages, developmental stages, physiological states, or social situations, and each will be associated with a discrete time-scale. Therefore, we propose the working definition: In an ecological context, carryover effects occur in any situation in which an individual's previous history and experience explains their current performance in a given situation. This concept of carryover effects provides an explicit but highly flexible context for examining the mechanisms that drive non-lethal interactions between distinct periods of an organism's lifetime, and unites the currently disparate fields investigating these effects in ecological systems. Greater communication among research fields and identifying mechanisms of carryover effects at different time scales will ultimately lead to a better understanding of the factors influencing variation in individual fitness.Key words: carry over effect; delayed effect; latent effect; life-history trade-off; maternal effect; reproductive trade-off.

Insect migration may involve movements over multiple breeding generations at continental scales, resulting in formidable challenges to their conservation and management. Using distribution models generated from citizen scientist occurrence data and stable-carbon and -hydrogen isotope measurements, we tracked multi-generational colonization of the breeding grounds of monarch butterflies (Danaus plexippus) in eastern North America. We found that monarch breeding occurrence was best modelled with geographical and climatic variables resulting in an annual breeding distribution of greater than 12 million km 2 that encompassed 99% occurrence probability. Combining occurrence models with stable isotope measurements to estimate natal origin, we show that butterflies which overwintered in Mexico came from a wide breeding distribution, including southern portions of the range. There was a clear northward progression of monarchs over successive generations from May until August when reproductive butterflies began to change direction and moved south. Fifth-generation individuals breeding in Texas in the late summer/autumn tended to originate from northern breeding areas rather than regions further south. Although the Midwest was the most productive area during the breeding season, monarchs that re-colonized the Midwest were produced largely in Texas, suggesting that conserving breeding habitat in the Midwest alone is insufficient to ensure long-term persistence of the monarch butterfly population in eastern North America.

Determining the factors that influence migratory population abundance has been constrained by the inability to connect events in different periods of the annual cycle. Carry-over effects are events that occur in one season but influence individual success the following season and recent empirical evidence suggests that they may play an important role in migratory population dynamics. Using a long distance migratory shorebird as an example, I incorporate carry-over effects and changes in the relative amount of habitat quality into a density-dependent equilibrium population model. The model uses the example where the quality of habitat on the wintering grounds (nonbreeding season) influences breeding output the following summer (breeding season). Carry-over effects, however, may be manifested in a number of other ways that could influence population dynamics. In the simulations, population declines occur when habitat is lost on the wintering grounds. However, results show that carry-over effects can magnify these declines when a disproportionate amount of high quality habitat is lost the previous winter. Simulations also show that carry-over effects can have a relative, positive impact on population size when the majority of habitat that is lost in the previous season is low quality. In this case, the carry-over interacts with density-dependence the following season producing an additive and positive effect, buffering the population from severe declines. To predict changes in population size of migratory animals, it will be important to determine (i) which demographic factors in which season produce strong carry-over effects and, (ii) not just the amount, but the relative quality of habitat that is lost. If carry-over effects are significant, they could potentially mitigate 'seasonal compensation effects' from density-dependence, leading to exacerbated population declines.