Preface: integrating historical ecology and ecological modeling

Abstract

There is increasing consensus that not only the present structure and functioning of ecosystems, but also their response to environmental stressors and management practices is partly a legacy of the system’s history (Rhemtulla and Mladenoff 2007). Similarly, there is little dispute that in order to assess the future trajectories of ecosystems, models of some sort need to be employed (e.g., Shugart 1998). Thus, there is a clear interface between the scientific attempts to elucidate the past of ecosystems (historical ecology) and the attempts to project their future dynamics (ecological modeling). However, to date this interface has received relatively little attention in scientific research (cf. Anderson et al. 2006). On the one hand, historical ecological research usually aims at uncovering past ecosystem dynamics and their drivers, using and combining a large variety of historical data sources (Egan and Howell 2001). A comprehensive understanding of anthropogenic impacts on ecosystems is not only crucial for the accurate interpretation of current ecosystem states, but it also forms the baseline for predictions of their future development, and for more informed ecosystem management (Burgi and Gimmi 2007). Historical ecologists therefore tend to emphasize the importance of their research for other fields such as ecosystem modeling, but they preferably place such statements in the outlook sections of their papers, often without a clear concept of how such integration should be achieved. On the other hand, many modeling studies that project the future state and fate of ecosystems are using baseline assumptions regarding current ecosystem states that are not much more than guesswork because they lack a historical consideration. A case in point is the assumption in studies of the future carbon cycle, a topic of eminent scientific, practical and political relevance, that current ecosystem carbon storage is in equilibrium with an assumed constant past climate and a constant past management (e.g., Wolf et al. 2012, and many others). Under most conditions, however, both assumptions are highly questionable, and are acceptable only because reliable and accessible data on past conditions are often absent. Indeed, the quest of modeling studies for appropriate historical data to set up more realistic ‘‘spin-up’’ runs of the models is often futile, as historical data are hardly ever collected and made available with the target variables of modeling studies in mind, unless a close collaboration is sought between modelers and historical ecologists (cf. Gimmi et al. 2009). Still, modelers tend to view historical ecology mainly as a source of ‘useful’ data while they underestimate the U. Gimmi (&) Research Unit Landscape Dynamics, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903 Birmensdorf, Switzerland e-mail: urs.gimmi@wsl.ch