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Research on urban ecosystems rapidly expanded in the 1990s and is now a central topic in ecosystem science. In this paper, we argue that there are two critical challenges for ecosystem science that are rooted in urban ecosystems: (1) predicting or explaining the assembly and function of novel communities and ecosystems under altered environmental conditions and (2) refining understanding of humans as components of ecosystems in the context of integrated social-ecological systems. We assert that these challenges are also linchpins in the further development of sustainability science and argue that there is a strong need for a new initiative in urban systems science to address these challenges and catalyze the next wave of fundamental advances in ecosystem science, and more broadly in interdisciplinary and transdisciplinary science.

Urban areas are growing in size and importance; however, we are only beginning to understand how the process of urbanization influences ecosystem dynamics. In particular, there have been few assessments of how the land-use history and age of residential soils influence carbon (C) and nitrogen (N) pools and fluxes, especially at depth. In this study, we used 1-m soil cores to evaluate soil profile characteristics and C and N pools in 32 residential home lawns that differed by previous land use and age, but had similar soil types. These were compared to soils from eight forested reference sites. Residential soils had significantly higher C and N densities than nearby forested soils of similar types (6.95 vs. 5.44 kg C/m2 and 552 vs. 403 g N/m2, P

Our understanding of the dynamics of urban ecosystems can be enhanced by examining the multidimensional social characteristics of households. To this end, we investigated the relative significance of three social theories of household structure—population, lifestyle behavior, and social stratification—to the distribution of vegetation cover in Baltimore, Maryland, USA. Our ability to assess the relative significance of these theories depended on fine-scale social and biophysical data. We distinguished among vegetation in three areas hypothesized to be differentially linked to these social theories: riparian areas, private lands, and public rights-of-way (PROWs). Using a multimodel inferential approach, we found that variation of vegetation cover in riparian areas was not explained by any of the three theories and that lifestyle behavior was the best predictor of vegetation cover on private lands. Surprisingly, lifestyle behavior was also the best predictor of vegetation cover in PROWs. The inclusion of a quadratic term for housing age significantly improved the models. Based on these research results, we question the exclusive use of income and education as the standard variables to explain variations in vegetation cover in urban ecological systems. We further suggest that the management of urban vegetation can be improved by developing environmental marketing strategies that address the underlying household motivations for and participation in local land management.

As defined by Ascher, biocomplexity results from a “multiplicity of interconnected relationships and levels.” However, no integrative framework yet exists to facilitate the application of this concept to coupled human–natural systems. Indeed, the term “biocomplexity” is still used primarily as a creative and provocative metaphor. To help advance its utility, we present a framework that focuses on linkages among different disciplines that are often used in studies of coupled human–natural systems, including the ecological, physical, and socioeconomic sciences. The framework consists of three dimensions of complexity: spatial, organizational, and temporal. Spatial complexity increases as the focus changes from the type and number of the elements of spatial heterogeneity to an explicit configuration of the elements. Similarly, organizational complexity increases as the focus shifts from unconnected units to connectivity among functional units. Finally, temporal complexity increases as the current state of a system comes to rely more and more on past states, and therefore to reflect echoes, legacies, and evolving indirect effects of those states. This three-dimensional, conceptual volume of biocomplexity enables connections between models that derive from different disciplines to be drawn at an appropriate level of complexity for integration.

The ecosystem is a fundamental ecological concept that is not as simple as it first appears. We explore three key dimensions of the concept that make it both complex and broadly useful—its basic definition, its application via models to concrete or specific situations, and its metaphorical connotations as used in general communication within the domain of science and with the public at large. Clarity in identifying what the dimensions are and how they are related can help to maintain the rigor of the concept for specific scientific uses while also allowing enough flexibility for its use in the integration of scientific principles, as well as in public discourse. This analysis of the ecosystem as a multidimensional concept is likely to be generalizable to other important concepts in ecology.

We approach the benefits and burdens of interdisciplinary research (IDR) from the perspective that science involves both constructive and critical approaches. The constructive aspect generates concepts, theories, and data to understand the observable world, while criticism tests the internal consistency of understanding and its fit to the observable world (Pickett and others 1994). IDR is the linkage of phenomena, research approaches, and conceptual tools that had previously been pursued independently (Parker 1993). Such linkages produce new research questions, new approaches to problems, new theories, and new generalizations. Therefore, IDR emphasizes the constructive aspect of science.

Large, infrequent disturbances (LIDs) can have significant impacts yet seldom are included in management plans. Although this neglect may stem from relative unfamiliarity with a kind of event that rarely occurs in the experience or jurisdiction of individual managers, it may also reflect the assumption that LIDs are so large and powerful as to be beyond the ability of managers to affect. However, some LIDs can be affected by management, and for many of those that cannot be affected, the resilience or recovery of the system disrupted by the disturbance can be influenced to meet management goals. Such results can be achieved through advanced planning that allows for LIDs, whether caused by natural events, human activities, or a combination of the two. Management plans for LIDs may adopt a variety of goals, depending on the nature of the system and the nature of the anticipated disturbance regime. Managers can choose to influence (a) the system prior to the disturbance, (b) the disturbance itself, (c) the system after the disturbance, or (d) the recovery process. Prior to the disturbance, the system can be managed in ways that alter its vulnerability or change how it will respond to a disturbance. The disturbance can be managed through no action, preventive measures, or manipulations that can affect the intensity or frequency of the disturbance. Recovery efforts can focus on either managing the state of the system immediately after the disturbance or managing the ongoing process of recovery. This review of the management implications of LIDs suggests that management actions should be tailored to particular disturbance characteristics and management goals. Management actions should foster survival of residuals and spatial heterogeneity that promote the desired recovery pattern and process. Most importantly, however, management plans need to recognize LIDs and include the potential for such disturbances to occur.