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This chapter considers a concept of niche that emphasizes multidimensional spaces of scenopoetic variables and provides a natural connection to the study of geographic distributions of species. It first explains the relations between environmental and geographic spaces before discussing the use of equations to link spatially explicit population growth patterns to variation in the ecological characteristics of species. It then describes the BAM diagram, a Venn diagram that displays the joint fulfillment in geographic space of three sets of conditions that together determine species distribution: biotic conditions, abiotic conditions, and movement of the species. The chapter also explores the spatial resolution of scenopoetic variables, estimation of the fundamental and existing fundamental niches, the biotically reduced niche, and caveats about reducing Grinnellian niches and the Eltonian Noise Hypothesis. Finally, it shows how distributional areas and ecological niches can be estimated.

This chapter proposes a formal and operational definition of a particular niche concept, introduces approaches for characterizing and measuring it, and uses it as a conceptual and terminological basis for describing and understanding much of the related practices of ecological niche modeling and species distribution modeling. It begins with a discussion of the themes that are most important in understanding niche concepts, focusing on three interrelated points: the meaning of “exist indefinitely”; what kinds of variables constitute the hypervolume; and the nature of feedback loops between a species and the variables composing the hypervolume. The chapter then considers the Grinnellian and Eltonian niches as well as the practicalities of estimating Grinnellian niches. It also considers two important interpretations of the niche concept, one of which is concerned with geographic and environmental spaces, and the other emphasizes the Eltonian niche.

This chapter introduces the species abundance distribution in a community or random sample. It describes statistical procedures that account for sampling variance in the estimated abundance of each species to fit species abundance distributions with Gamma or lognormal forms. Statistical properties are described for the three most commonly used nonparametric scalar measures of species diversity: species richness, Shannon information, and Simpson diversity. For each of these diversity measures we analyze the statistical accuracy of estimates of the actual diversity in a community that can be made from random samples. The chapter explains additive partitioning of species diversity into components attributable to subdivisions of the community in space and time. It concludes with examples of partitioning diversity into spatial and temporal components in highly diverse insect communities.

This chapter discusses the process of transforming a species’ primary occurrence data into a synthetic understanding of the geographic and ecological conditions under which the species occurs. The focus is on correlative models based on occurrence data, since such models can have quite broad applicability. The chapter first considers different types of occurrence data as well as factors that connect the suitability of a site to the existence of a data record documenting the species’ presence or absence at that site. It then examines variations in the geographic and ecological characteristics of species distributions and occurrences, along with sampling bias in geographic and environmental spaces. It also describes the characteristics of absence data before concluding with an assessment of issues of content and availability that affect occurrence data.

This chapter discusses the use of niche models to help address the “what” and “where” questions in conservation biology as well as climate change effects. It first reviews the conceptual aspects of the “what” and “where” questions in conservation planning, focusing on topics such as inferences about extinction risk, identification of regions for species reintroductions, conservation reserve network planning, and considerations of how climate change may affect species distributions. Each of these conservation applications is then examined with respect to the conceptual framework laid out for ecological niche modeling. The chapter concludes by offering practical recommendations regarding calibration and evaluation of niche models.

This chapter reveals that sampling plant diversity at multiple spatial scales may allow for a deeper understanding of relationships between species distributions and composition shifts relative to changing environmental gradients. Like single-scale techniques, different multi-scale techniques have various strengths and weaknesses, and some may be better suited than others for particular study goals and objectives. No single design will be the “end all, be all” for plant diversity sampling. All designs have advantages and disadvantages that must be carefully evaluated. An experimental approach is almost always warranted. Several examples provide a glimpse of the profound potential of multi-scale sampling for plant diversity.

This chapter reviews why standard methods for plant diversity studies have been slow to develop. It provides specific examples why plant diversity studies are inherently difficult due to issues of taxonomy, phonology, and species rarity. In addition, it shows that designing plant diversity studies also is hampered by plant-to-plant neighborhood scale variability, landscape-to-regional scale variability, and long-term changes in plant diversity brought about by immigration, particularly plant species invasions from other countries.

This chapter considers the practice of modeling ecological niches and estimating geographic distributions. It first introduces the general principles and definitions underlying ecological niche modeling and species distribution modeling, focusing on model calibration and evaluation, before discussing the principal steps to be followed in building niche models. The first task in building a niche model is to collate, process, error-check, and format the data that are necessary as input. Two types of data are required: primary occurrence data documenting known presences (and sometimes absences) of the species, and environmental predictors in the form of raster-format GIS layers summarizing scenopoetic variables that may (or may not) be involved in delineating the ecological requirements of the species. The next step is to use a modeling algorithm to characterize the species’ ecological niche as a function of the environmental variables, followed by model projection and evaluation and finally, model transferability.

This chapter focuses on the conceptual and applied aspects of environmental data in the context of building and interpreting ecological niche models. It first examines how different suites of environmental factors may affect species distributions across a range of spatial scales before discussing which and how many variables are needed for ecological niche modeling. It then reviews the diverse sources of environmental datasets that are of potential utility in ecological niche modeling and concludes by considering a number of challenges involved in designing and choosing environmental data for ecological niche modeling. These challenges include data preparation, data quality, spatial extent, resolution in space and time, types of environmental data, and ancillary data.

The distribution and dynamics of populations reflect the interplay between dispersal and demography with landscape structure. Understanding how landscape structure affects populations is essential to effective habitat management and species conservation, especially within landscapes undergoing habitat loss and fragmentation as a result of human land-use activities. This chapter thus begins with an overview of the effects of habitat loss and fragmentation on populations, followed by a discussion of species distribution modeling. Then, because population assessment figures so prominently in evaluating a species’ extinction risk to landscape change, the chapter considers the different classes of population models used to estimate population growth rates and population viability, including the use of metapopulation and spatially explicit simulation models.

This chapter examines the distribution of species and higher-level taxa among major geographic and habitat categories, using gymnotiform electric fishes as a case study. It proposes a simplified four-category classification of aquatic habitats, intended as a conceptual framework for understanding ecological distributions and describes the diversity and composition of their fish faunas. It highlights the role of habitat in constraining the distributions of individual species and higher taxa and the consequences this has for the formation of regional species assemblages.

Range expansions, biological invasions, and disease spread are all inherently spatial processes that involve the successful introduction or colonization, establishment, and dispersal of organisms (or their propagules) into new areas. Population spatial spread thus involves the interaction of both dispersal and demography with landscape structure. This chapter begins by exploring landscape effects on species’ range shifts and the extent to which species can shift their distributions in response to future land-use and climate-change scenarios. Next, the chapter evaluates the effect that landscape structure might have on invasive spread, including an overview of spatial models that are used to predict whether, when, and how fast an invasive species is likely to spread. The chapter concludes with a discussion of disease spread in a landscape context (landscape epidemiology), which involves the study of how pathogens, vectors, and hosts interact with environmental heterogeneity to influence the incidence and persistence of disease in an area.

This book deals with ecological niche modeling and species distribution modeling, two emerging fields that address the ecological, geographic, and evolutionary dimensions of geographic distributions of species. It provides a conceptual overview of the complex relationships between ecological niches and geographic distributions of species, both across space and (perhaps to a lesser degree) through time. The emphasis is on how that conceptual framework relates to ecological niche modeling and species distribution modeling, which the book argues are complementary and are most broadly applicable to diverse questions regarding the ecology and geography of biodiversity phenomena. Part I of the book introduces the conceptual framework for thinking about and discussing the distributional ecology of species, Part II is concerned with the data and tools that have been used in the early development of the field, and Part III focuses on real-world situations to which these tools have been applied.

This concluding chapter argues that Earth's climate is warming at a pace that may very well be unprecedented, and it is doing so from a higher baseline average temperature than that which was the starting point for the most recent episode of rapid warming, which signaled the end of the Pleistocene and the demise of most of its large mammals. That most recent warming episode also coincided with geographically widespread biome shifts. Perhaps more tellingly, current warming, still in its early stages, has already heralded similarly geographically widespread and taxonomically broad shifts in phenological dynamics, population dynamics, species distributions, and ecosystem carbon dynamics. Indeed, some have asserted that Earth may be on the threshold of the sixth major extinction event.

This chapter examines how biodiversity, the variety of life, is distributed across the globe and within local communities. It begins by considering some of the challenges associated with assessing biological diversity at different spatial scales. Then, three of the best-studied patterns in species richness are examined in detail—the species–area relationship, the distribution of species abundances, and the relationship between productivity and species richness. The chapter concludes with a detailed exploration of the most dramatic of Earth’s biodiversity patterns—the latitudinal diversity gradient. The above patterns constitute much of what community ecology seeks to explain about nature. Their study provides a foundation from which to explore mechanisms of species interactions, and to understand the processes that drive variation in species numbers and their distribution.

This chapter presents METE, a comprehensive, parsimonious, and testable theory of the distribution, abundance, and energetics of species across spatial scales. It develops the structure and predictions of the theory. These predictions include species abundance distributions, species–area relationships, distributions of metabolic rates across individuals, abundance–metabolic rate relationships, and spatial distribution patterns for individuals within species. Predictions all stem from prior knowledge of four ecological state variables – area, species richness, total abundance, and total metabolic rate – which are to ecology what pressure, volume, and temperature are to thermodynamics.

This book has described a comprehensive framework for thinking about the geography and ecology of species distributions, arguing that such a framework is critical to further progress in the field of ecological niches and distributions. To develop this framework, traditional concepts in ecology have been radically reworked. In this conclusion, some of the challenges for future work regarding ecological niche modeling are discussed, such as fully integrating the BAM diagram with central concepts of population biology and statistical theory; clarifying the notion of niche conservatism versus niche evolution as regards scenopoetic versus bionomic environmental dimensions; and improving the link between correlational and mechanistic approaches to estimating and understanding ecological niches. The book argues that careful conceptual thinking must be combined with detailed empirical exploration in order to address each of these challenges.

This chapter introduces mathematical and statistical modelling approaches in community ecology. 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 community ecology. The mathematical sections start with models of two interacting species in homogeneous space, including a model with competitive interactions, a resource–consumer model, and a predator–prey model. The competition model is expanded to heterogeneous space and to the case of many competing species. This model is used to analyse the consequences of habitat loss and fragmentation at the community level. To illustrate the interplay between models and data, the statistical section analyses data generated by the mathematical models, with emphasis on time-series data of two interacting species, point pattern analyses, and joint species distribution models.