Untangling Ecological Complexity: The Macroscopic Perspective. Brian A. Maurer. 251 pp. University of Chicago Press, 1999. $18.
Over the past two decades, scientists have become increasingly aware of global biodiversity loss. Plants and animals are disappearing from their native landscapes at 50 to 100 times their estimated natural rate. Ecologists are assessing whether biodiversity reduction is part of a natural cycle or the result of human activity. They also are trying to determine how many species an ecosystem can lose before its vital processes begin to falter and which species are the most critical for an ecosystem's maintenance.
Community ecology, which focuses on species associations in ecosystems, seeks to understand various mechanisms that cause communities to change. A large proportion of research in community ecology has attempted to analyze localized ecological communities through controlled experiments, which have yielded a wealth of valuable data regarding competition, predation and the ability of species to persist together. Various stochastic and deterministic modeling approaches have been incorporated when experiments cannot be done.
In Untangling Ecological Complexity, Brian A. Maurer suggests that the experimental approach cannot satisfactorily tackle large-scale mechanisms that influence species diversity on local scales. Maurer proposes that community ecologists adopt a much broader approach to understand diversity at biogeographic scales. Maurer states that climate change, invasions and evolutionary processes are complex and need to be analyzed macroscopically, suggesting that this perspective can lead to intriguing discoveries of patterns that appear to be very general. Sometimes these patterns can lead to elegant explanations and testable hypotheses with independent data sets. Although no two biological systems are alike, he writes, regularities (simplifications) in biological systems arise and remain stable through a statistical process of causality; relations between individual components may be small but when added together can determine the fate of the entire system.
In the book's 10 chapters, Maurer considers regularities and constraints that operate on large-scale and complex continental species assemblages. He emphasizes a species' community structure and population dynamics. There is much that pertains to birds and mammals for which there are sufficiently large databases; coverage of plant communities is lacking. Throughout the book Maurer demonstrates how empirical and theoretical statistical applications are useful to identify and measure processes such as nonrandom extinction and dispersal mechanisms in continental biotas. These patterns are maintained across large expanses and operate on evolutionary timescales that are longer than the careers of most researchers studying them. One of Maurer's own contributions to macroecology is emphasized in a chapter on how some communities can be observed using a hierarchical set of data transformations and how others behave as a chaotic system. Maurer also presents macroscopic perspective models that are compilations and extensions of various contributions and treatments generated by other ecologists. For example, he discusses J. Gurevitch's competition experiments, A. J. Lotka's community model, D. W. Davidson's control and rodent removal plots, R. H. MacArthur's ideas on body size, colonization and competition, and J. Diamond's ideas on resource use and species assemblages.
Maurer's book is provocative and stimulating and will serve as a guide for much further research in macroecology. He has filled in some of the missing pieces on the dynamics of how ecological systems can be linked to large-scale geographic studies. Bridging macro- and microecological studies is essential for understanding complex ecological questions. An understanding of processes and patterns at multiple scales is required if ecology plans to help society in a shrinking biosphere.—Nina L. Baghai, Geology/Environmental Science, Black Hills State University, Spearfish, South Dakota