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The National Evolutionary Synthesis Center (NESCent), in Durham, North Carolina, was established in December 2004 to foster synthetic, collaborative, cross-disciplinary studies in evolutionary biology. The center sponsors scientific catalysis meetings to stimulate new approaches to research and working groups for in-depth investigations of particular topics. NESCent also offers faculty sabbaticals and postdoctoral fellowships, as well as education and outreach opportunities.
We outline a general scheme for migration that applies across taxa, incorporates the several varieties of migration, and includes all levels of biological organization, from genes to populations. The scheme links the environment, pathways, traits, and genes, and highlights the selective forces that shape and maintain migratory adaptation. We endorse an individual-based behavioral definition of migration that allows an objective distinction between migration and other forms of movement. We recognize migration as an adaptation to resources that fluctuate spatiotemporally either seasonally or less predictably, and note that it is often preemptive. Migration plays a central role in the spatial dynamics of mobile populations, and is largely distinct in both form and function from the within-population mixing arising from postnatal dispersal and from the interpatch movements characteristic of metapopulations. We call for more interaction between biologists studying different taxa and different forms of movement, and between behaviorists and population ecologists.
Migratory animals show a suite of adaptations to cope with their journeys. These include not only morphological features for efficient locomotion and storage of energy but also behavioral adjustments to exploit winds and currents or to avoid drift caused by moving fluids. Migration strategies across locomotory modes can be analyzed in the context of optimality models, using some general principles concerning migration range and selection criteria. Comparisons of model predictions with natural behavior help researchers understand the selection pressures that underlie migration strategies. We give examples of typical migration speeds and distances for animals using different locomotion models. Successful migration also requires accurate orientation and/or navigation between distant areas for reproduction and survival. Animals can use a suite of different compasses, which may be cross-calibrated or integrated for direction finding, depending on the geographical and ecological situation, and may be used with an endogenous clock for time compensation.
Migration is a widespread and ancient phenomenon commonly involving a seasonal response to predictable changes in the environment. Such changes include the four seasons at the higher latitudes and wet–dry seasons in the tropics. In general, migrations are movements to breeding grounds followed by a postbreeding return to areas for nonreproductive activities. We focus on these seasonal migrations and summarize processes by which diverse organisms prepare and adjust to different phases of the migration life history stage, such as preparation, onset (actual traveling), and termination. This framework enables investigations of physiological and behavioral mechanisms involved in each phase, as well as studies of how environmental signals control this diverse and successful process across the taxa.
New technologies are improving scientists' understanding of the links between sources and destinations of subpopulations of migrants within populations as a whole (metapopulations). Such links and the importance of environmental patchiness are illustrated by migrations of two major pests, the red-billed quelea (Quelea quelea) and the desert locust (Schistocerca gregaria). The spatiotemporal distribution of rainfall determines where and when Quelea can breed, as shown for Quelea populations in southern Africa. Numbers and distributions of swarms of desert locusts in four different regions of their huge invasion area (29,000,000 km2) were analyzed as local populations of a metapopulation. Lagged cross-correlations of seasonally adjusted monthly data demonstrate links between the local populations, which vary in significance according to the pairings of regions analyzed and the lengths of the lags, illustrating the strength of the connectivity between them. Understanding such relationships is essential for predictions concerning future climate change scenarios.
Because areas suitable for growth and reproduction are often ephemeral, a primary selective force in the evolution of migratory behavior in insects is the need to colonize new habitats. However, both migration itself and flight capability reduce present reproductive success. Thus the long-term fitness benefit of migration, the colonization of new habitats, is balanced by a short-term reduction in fitness, the result being that variation for migratory ability is preserved in a population. Migration is but one component of a wide suite of functionally connected traits that together form a migratory syndrome. Genetic variation is found in all components of the migratory syndrome, and selection for migration results in a change in the frequency of expression of these components, which can be analyzed and predicted using the mathematics of quantitative genetics. We illustrate this evolutionary interplay with the example of the evolution of wing dimorphism in the sand cricket.
One of the characteristics of avian migration is its variability within and among species. Variation in migratory behavior, and in physiological and morphological adaptations to migration, is to a large extent due to genetic differences. Comparative studies suggest that migratory behavior has rapidly and independently evolved in different lineages. One reason behind the high potential for de novo evolution of migratory behavior in sedentary populations seems to be the ubiquity of genetic variation for migratory traits in nonmigratory individuals. In resident lineages, a high degree of hidden genetic variation for migratory traits can be maintained because a migratory threshold determines whether migratory behavior is expressed. Genetic correlations among migratory traits and with other traits of the annual cycle are likely to play a major role in determining the rate and direction of evolutionary change.
What kinds of workplace are current life sciences students, and other students in science and engineering, willing to work in? What kinds of salaries do they expect to earn upon graduation? How well do the salary expectations of life sciences students match the reality of the job market? Do white and minority life sciences students have similar work preferences and salary expectations? This article examines these issues by analyzing data from a national study of college students in science and engineering fields, conducted by the author. Students expressed a willingness to work in a variety of institutional settings upon graduation, and their salary expectations were comparable to what employers are paying new graduates. However, the study also found racial and gender differences in workplace preferences and salary expectations.
Although many scientists recommend adaptive management for large forest tracts, there is little evidence that its use has been effective at this scale. One exception is the 10-million-hectare Northwest Forest Plan, which explicitly included adaptive management in its design. Evidence from 10 years' implementation of the plan suggests that formalizing adaptive steps and committing to monitoring worked better than allocating land to adaptive management areas. Clearly, some of the problems in implementing any new strategy should have been expected and probably would have been avoided if the plan had called for even more focused feedback. But decisions made after monitoring results were analyzed have led to new management priorities, including new approaches to adaptive management. These decisions suggest that one adaptive management loop has been completed. A continued commitment to learning about and adapting practices and institutions will most likely be needed to improve performance in the future.