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Space and time represent two of the many dimensions specifying the scale of evolutionary change. Scale adds yet another intimidating level in attempts to thoroughly understand evolution, and even more so when merged with the complications associated with mechanics, function, and structure. Fortunately, abstract short-cuts to model evolution can be used. One effective way is to build so-called fitness-generating functions that incorporate, implicitly, many of the complex mappings embedded in the structure matrix. Fitness-generating functions (also called G-functions) are one solution to the problem of scale. This chapter shows that if the interest is micro-evolution, a G-function should be constructed to model the fitness of different alleles. If the interest is macro-evolution, the G-function should be expanded to include suites of strategy sets. Evolutionary interest should be allowed to be a sliding scale where the assumptions and simplifications that are made to answer one question at one point are different from those at another.

Habitat may have a primary role in determining the distribution and abundance of species, yet ecologists have historically overlooked its importance. Models of habitat selection are briefly reviewed. A new conceptual and analytical model is presented that explains how dispersing organisms find and settle at a given location based upon habitat structural features providing cues for settlement. The model is based on a sequential process of dispersal, settlement, and establishment that can be described by probabilities. The spatial settlement pattern of juvenile individuals determines adult distribution and abundance. Evidence is provided that structural features of the habitat may be more effective cues than are food supply, conspecific density, or the absence of an antagonistic species. This is the habitat-cue hypothesis of species distribution and abundance. The hypothesis is intended to stimulate greater investigation into the role of physical structure and environmental cueing in habitat selection by all types of organism. The hypothesis also predicts that a species distribution in nature is determined by habitat more than any other factor.

This chapter describes terrestrial and underwater habitats for different otter species. Results of surveys of terrestrial habitat selection based on distribution of faeces (‘spraints’) should be treated with caution. The aquatic part of the habitat is restricted by depth as well as substrate and access to prey. Different habitats are used at various times of year, and in several species the sexes use different habitats; males preferring larger rivers or more exposed coasts. Small freshwater streams are used more intensively per unit area than larger rivers. Where several species of otter occur together, they show different selection of habitat. Sea otters have a dominating effect on ecosystems through their influence on numbers of sea urchins, which graze sea algae vegetations. For several otter species using marine habitats, the presence of freshwater sources (for cleansing fur) is essential; numbers of otter dens (‘holts’) and freshwater sources are correlated.

Movement is a fundamental process that enables individuals to find food or mates, locate suitable habitat, and colonize new areas. The effect of environmental heterogeneity on individual movement behavior is the finest scale at which organisms respond to landscape structure, and can be used to define different species’ perceptions of landscape structure. This chapter discusses different types and scales of movement, how patch structure is expected to influence movement, and various methods for tracking and analyzing animal movement. Because animal movements are typically bounded in space, the estimation of space utilization and home-range size is also considered in this chapter. The chapter concludes with a discussion of various approaches to measuring plant dispersal, which is likewise important for evaluating how movement (via propagules) translates into the redistribution or spread of populations across the landscape.

It has long been considered that abiotic factors are far more important than biotic variables in controlling the structure of desert communities. In recent years, this perception has changed because some prime examples of species interactions have come from experimental studies in desert ecosystems. Few will doubt that desert rodents present some of the best evidence for competition. Reviews also indicate that competition occurs among desert plants. This chapter focuses on some of the key competitive interactions and facilitation among desert organisms, drawn from several deserts. A great number of shrubs have been shown to have nurse plant effects on annual plants in particular, although other shrubs and geophytes may also benefit from this. Essentially, this means that the annual plants grow up under the shrub and benefit from a number of factors. The chapter also discusses indirect interactions, keystone species, priority effects and short-term apparent competition.

There are several reasons for conducting a habitat analysis and identifying the environmental (habitat) characteristics that a species associates with. (1) Knowledge of a species’ habitat requirements is crucial in restoring and managing habitat for the species. (2) Carrying capacity informs us about the potential (or lack thereof) for future population growth based on resource availability. Knowledge of a species’ habitat requirements allows us to interpret the importance of carrying capacity in a habitat-specific way. (3) The study of species interactions and the potential for species coexistence is supported by having knowledge of the habitat of each species under investigation. (4) Habitat preference and selection as eco-evolutionary processes continue to be widely studied by ecologists—interpretation of the results of such studies is best done with knowledge of the species–habitat associations. Such knowledge can also be useful in the design of preference and selection studies. (5) Knowledge of species–habitat associations can also be of great use in selecting the environmental variables to use in species distribution models. All five of these goals point to the great utility of conducting a habitat analysis as a supporting investigation or as a way to obtain knowledge to put to a practical purpose.

Anyone who is even slightly acquainted with plants or animals knows that different species inhabit different parts of the world, live in different habitats, and, in the case of animals, eat some imaginable kinds of food and not others. As with many other familiar facts, it may not occur to us to ask why the geographic and ecological ranges of species are limited, until we realize that species vary drastically in their geographic, ecological, and physiological amplitudes. The bracken fern (Pteridium aquilinum) is broadly distributed in temperate climates of every continent (except Antarctica), whereas the curly-grass fern (Schizaea pusilla) is limited to parts of eastern Canada and central New Jersey in the United States. The black-billed magpie (Pica pica) is a familiar bird from western Europe through eastern Asia and from Alaska to the Great Plains of North America, but the very similar yellow-billed magpie (Pica nuttalli) is restricted to central California. What accounts for the much narrower distribution of one than the other species? Related species often differ in the variety of habitats they occupy. The thistle Cirsium canescens is restricted to well-drained sandhills in the American prairie, whereas Cirsium arvense is a European species that has become a rampant weed in North America, growing in many types of soil. The endangered Kirtland’s warbler (Dendroica kirtlandii) nests only in stands of jack pine of a certain age, while its relatives, such as the yellow warbler (Dendroica aestiva), nest in many types of vegetation and have far broader geographic ranges as well. (Species with narrow and broad habitat associations are referred to as stenotopic and eurytopic, respectively.) Stenotopic species or populations frequently have a narrower tolerance of certain physical variables than do others. Most plants and animals from warm tropical environments cannot survive freezing temperatures, and Antarctic notothenioid fishes cannot tolerate temperatures above 6°C. In contrast, species that inhabit environments where the temperature varies widely often have broad temperature tolerance. In many such species, individuals are capable of biochemical and physiological alterations that acclimate them to pronounced changes in temperature.

This chapter describes beaver habitat selection and modification activities. It discusses their unusual ability to modify environments to suit their needs, including lodge and dam construction, location selection for these structures, and alteration of vegetation. Historically beavers have been described as a forest species. Whilst beavers may preferentially select wooded freshwater habitats, particularly in more northern landscapes, they are capable of successfully establishing in widely varying terrain, including mountainous, brackish, tundra, cultivated, and urban landscapes. Beavers occupy a wide range of freshwater bodies (ponds, streams, rivers, marshes, and lakes) but will also travel through brackish and saltwater bodies during dispersal. Beavers prefer still or slow-moving water with stable water levels of at least 0.6–1.0 m in depth, but they are highly adaptable and can modify many types of natural, cultivated, and artificial habitats. When preferred habitats are unavailable or already occupied by other beavers, they will select narrower watercourses and construct complex dam structures to create preferred/suitable habitats. In the process of engineering their habitat, beavers create trails and canals to access forage. They harvest saplings, shrubs, and trees, which they consume and use to fill their food caches for the northern winter.

This chapter introduces mathematical and statistical modelling approaches to study the ecology of movement. It starts with a conceptual section, continues with mathematical and statistical sections, and ends with a perspectives section. The conceptual section motivates the modelling approaches by providing the necessary background to movement ecology. The mathematical sections first introduce random walk and diffusion models in homogeneous space, and use these models to illustrate the relationship between the Lagrangian and the Eulerian viewpoints. The movement models are then expanded to heterogeneous space, and in particular to highly fragmented patch networks. To illustrate the interplay between models and data, the statistical section analyses data generated by the mathematical models, with emphasis on the analyses of tracking data and capture-mark-recapture data.

Following wild birds marked with radio tags is a technique that can be used to obtain data on movements, survival, and habitat selection. This chapter considers the choice of type of tag and attachment method most likely to achieve useful results without adverse effects on the bird. Techniques and equipment for tracking are described, and methods and software for recording and analysing tracking data are introduced. The relative merits of radio-tracking and other, less intensive, field methods are compared. Probable future developments in equipment and their implications for field studies are considered.

This chapter describes the key characteristics of “inSTREAM” and how it represents adaptive trade-off decisions, and provides the background needed to understand its design and complexity. The initial purpose of inSTREAM was to assess how alternative reservoir operation rules, which produce different patterns of flow and temperature in downstream waters, affect populations of sympatric trout species. It quickly became apparent that such a model would also be useful for a variety of management applications and for exploring more general ecological questions. InSTREAM has evolved into a family of models, each focused on specific salmonid communities and management problems. These models have also proved useful as virtual laboratories for exploring more general questions, of both management and theoretical importance, for which inclusion of adaptive trade-off behavior is probably critical. These questions have included how multiple stressors interact to affect populations; how opposing effects of increased turbidity—reduced feeding success and reduced predation risk—interact to affect populations; how habitat fragmentation affects population persistence and size structure; and how useful habitat selection models are for predicting population responses.

This chapter focuses on the relationship between the Normalized Difference Vegetation Index (NDVI) and wildlife management, exploring the potential of the NDVI in understanding the factors that influence habitat use and selection and the prediction of animal abundance. It studies the relationship between NDVI variability and life history traits, considering the role of the NDVI in the variability in animal body mass, survival, and recruitment. It also presents the use of NDVI in studying the patterns of animal movement.

This chapter begins by discussing the variety of habitats that are occupied by fish eggs and larvae; these habitats include the open ocean, coastal ocean, and estuaries. Also, the chapter discusses the stage-specificity of the area of occurrence of each stage (adults, eggs, larvae, juveniles) in the life history of fishes, pointing out the differences of demersal, pelagic, neustonic (associated with the very surface of the water), anadromous (fish that migrate from the ocean to fresh water to spawn), catadromus (fish that migrate from fresh water to the ocean to spawn), and estuarine or coastal fishes. The effect of human activity and pollution on water quality and fish habitats is discussed as well. This chapter also discusses conservation biology, marine protected areas, and fisheries management.

The phenomenon of diel vertical migration (DVM) of planktonic crustaceans, recognized by biologists for at least 2 centuries, is a special case of habitat selection behavior by pelagic animals, with their depth preference changing over a diel cycle in a way that prevents encounters with visually oriented predators (mostly fish). Migrating populations usually move toward cold, dark deep-water strata deprived of algal food when there is sufficient ambient light and move back to food-rich and warm surface waters after dusk. DVM has been recognized in pelagic representatives of all aquatic phyla of the animal kingdom and is considered the most massive diel biomass displacement on Earth. DVM can be observed in nearly all lentic freshwater and marine environments. As zooplankton occupy the central position in pelagic food webs, their massive migrations dramatically affect ecological functioning of offshore biota, particularly the efficiency of primary production utilization, energy flow, and biogeochemical pathways of essential nutrients such as carbon fluxes. The phenomenon of DVM is perhaps the most suitable for quantitative description and the major environmental factors underlying the fitness consequences of DVM, including vertical gradients of light intensity (predation risk), temperature related metabolic rates, food concentration (growth and fecundity), and others, are easy to monitor track in the field and to manipulate in laboratory systems. DVM, as inducible behavior, can be experimentally manipulated, both in the field and in the laboratory, which, in turn, makes it possible to design experiments convenient for testing specific hypotheses on various proximate and ultimate factors underlying this behavior. These characteristics make DVM suitable for investigating the evolution of animal behavior, its adaptive value, and ecosystem consequences. In the fondest memory of our friend Konrad Ciechomski with whom we made, years ago, our first steps into the world of plankton migrations.

Spatial resource gradients, processes of plant maturation, and grass-grazer interactions are among the biophysical factors that structure ungulate movement systems, irrespective of whether the animals are domesticated or wild. Not only do pastoralists move their herds in response to these constraints and opportunities, but also to achieve a variety of cultural, social, and economic goals. Density dependent theories of habitat selection provide only a partial explanation for land use systems that must balance the need to distribute livestock with respect to available resources with the restrictions of property rights and administrative boundaries. This chapter considers the social and economic constraints and incentives that influence livestock movements, using several case studies of contemporary domestic livestock systems (in the Sahel, Mongolia, and the Arctic). In so doing, it aims to develop an understanding of livestock mobility that recognises but does not exaggerate the biological processes that underpin this distinctive form of agricultural production.

Organisms can respond to environmental change by modifying their behavior to obtain an instant response, through short-term phenotypically plastic, often physiological, adjustments, and/or by adapting their life history through a more long-term evolutionary response. Behavioural and physiological responses, in fact, can occur at all these three temporal scales. Examples of behaviors so affected include congregation, dispersal, foraging, migration, or mating. Such responses have consequences at the population and community levels, and ultimately for the evolution of species. This chapter discusses insect examples of these kinds, with an emphasis on human-induced factors, such as (primarily) climate change, pollution, fragmentation, and urbanization.