Systemic Management describes a different form of management of ecosystems and the biosphere that goes beyond conventional management techniques. It intends to account for and minimize human abnormality, and thus shift society toward sustainability. In its attempt at this goal, the book begins with an introduction of systemic management based around nine tenets, which include accounting for complexity, avoiding abnormality, being goal oriented and realizing that control over non-humans is impossible, among others. From this base, Fowler discusses how patterns among species, basically graphs of macroecological variables plotted against proportions of species, can be used to detect abnormality. Using examples from the eastern Bering Sea, Fowler shows how these patterns charting human abnormality against other species can help to answer management questions and set goals. The book then goes on to discuss why conventional management (and recent advances in ecosystem management in particular) does not work. It then contrasts these shortcomings with a more in-depth overview of why systemic management works. The final chapter focuses on the disproportionate impact of humanity on the biosphere and the need to shift management approaches.

In writing this book for scientists and practitioners, Fowler does a commendable job in showing how empirical patterns can be used as a diagnostic tool. Repeatedly, examples provide a means to demonstrate how basic operational-level managerial questions, like setting limits on fishing catch or harvesting quotas on flora/fauna, can be addressed using patterns, what Fowler sees as the Monte Carlo simulations run in the natural world. Another strong suit of the book is the critique of the shortcomings in conventional management. This provides a wonderful assessment of many current management practices and their inherent problems. Ultimately, the shortcomings of conventional management and the frequent human abnormalities discerned through patterns highlight the challenges of achieving any semblance of sustainability given current human population levels and resource usage.

In spite of these strong points, three serious shortfalls in the book temper my enthusiasm for a positive recommendation. These emerge early on in discussions of the differences between conventional and systemic management in the opening pages. Fowler takes the position that in moving the input of stakeholders from processing data to defining the management questions, as displayed in Figure 1.1, politics is mitigated. On p. 214, Fowler revisits this point and states that ‘people will learn that the effects of politics largely disappear other than as starting points for asking the right questions’. This misunderstands governance and the policy process, which demonstrates that governance is not a linear process but one that is reiterative with multiple feedback loops as more data are gathered. On the whole, Fowler fails to understand political decision-making. Second, this position privileges the role of science as unbiased and apolitical. It does this at the expense of indigenous knowledge and at the expense of values beyond the realm of science. Some of the ‘solutions’ based on patterns result in contentious, value-laden conclusions which stem, in part, from the specific types of questions that are being asked. To pretend that politics and subjectivity are removed by scientific methodology is myopic. Nor does it account for cases where scientific studies result in conflicting results or unclear outcomes. Again, political decision-making is not removed from the process, as many critiques on adaptive management have likewise concluded. Finally, while using patterns comparing humans with other species to assess the resultant abnormalities provides a beneficial marker for humanity's place in the biosphere, it also neglects to account for human exceptionalism. I do not use this phrase to place humanity beyond the pale. I commiserate with many of the Fowlers's positions. However, it is problematic to rely on humans’ outlier position on a species distribution curve when so many features of the human species are already several standard deviations removed from other species, including intelligence, language and communication capabilities, technological advances and so on. With this background, is outlier status so unexpected? I do not mean to negate the role of patterns or to discount the abnormality of the human species entirely; however, it begs the question as to how far the use of patterns can go in supplying management answers, particularly when the answers (population reduction, reduced resource usage, minimal energy usage) are so politically contentious.

In summary, I applaud Fowler's efforts to respond to the shortcomings of conventional management and I agree with the need to return the human species to the analysis of the biosphere. I only regret that the role of governance is misunderstood.