Sunday, October 11, 2009

Adaptive Capacity of the Baltimore Socio-Ecological System: A Discussion Document for the Baltimore Ecosystem Study

Adaptive Capacity of the Baltimore Socio-Ecological System: A Discussion Document for the Baltimore Ecosystem Study

This essay lays out thoughts on guiding questions and conceptual approaches to guide research and synthesis in the third phase of the Baltimore Ecosystem Study (BES III). It is intended to help inform the planning meeting on Tuesday, October 20, 2009.

Urban systems are undergoing vast changes around the globe. Changes in economic and commercial strategies, human migration, land conversion, household structure, lifestyles, and global climate are among the most conspicuous kinds of change, to which urban systems must respond. These complex urban systems, spanning central cities, old suburbs, new suburban enclaves, edge city business centers, exurbs and the lands beyond, will adapt in part or whole, and to differing degrees. The principal question facing both researchers and managers of urban systems today must be, “Is this urban area capable of adapting to the suite of drastic biological, physical, and social changes it is now experiencing?”
As we envision Phase III of the Baltimore Ecosystem Study (BES), Long-Term Ecological Research (LTER) project, we can use a form of this question to organize our research, scholarship, education, and engagement with our host communities:

• What is the adaptive capacity of the Baltimore socio-ecological system?

Adaptive capacity of a socio-ecological system is its ability to experience perturbations, shocks, and novel inputs and still remain in a given domain of attraction. That domain has environmental, social, and economic dimensions, and hence relates to the idea of sustainability. Adaptive capacity is the ability to respond to alterations in a way that retains its overall structure and functional processes. Adaptive capacity is closely related to resilience, and reflects the ability of a system to adjust to changing conditions. It is an evolutionary concept that recognized that fixed stability is unlikely in biological and social systems, but that the components, interactions, and feedbacks can often alter in ways that maintain system identity and identifiable or desirable functions.

This overarching question requires attention to several, more specific questions:
1. How can the adaptive capacity of Baltimore be measured?
2. How has adaptive capacity changed in the past?
3. How might it change in the future?
4. How can education enhance the adaptive capacity of Baltimore?

These questions will engage and integrate work that emerges from a variety of disciplines, including soil science, biogeochemistry, atmospheric science, hydrology, community ecology, human demography, sociology, environmental economics, and education. Accomplishing our goal of understanding the adaptive capacity of Baltimore will also engage us in a dialog with citizen groups, community leaders, decision makers, and managers within and beyond government. Through this dialog, scenarios will be developed to help the citizens and leaders of the Baltimore region evaluate the adaptive capacity of their metropolitan home.

This new guiding question builds on the field and synthetic research platform developed through Phases I and II of BES. It will continue to require data organized around patterns and processes of watersheds, ecosystem biogeochemistry, physical and biological components, social dynamics, group identity, and institutional behaviors, among others. Yet it extends the scope of BES into new arenas. In particular, we employ several theoretical and modeling tools for the first time in our research strategy:
• Socio-economic theory of locational choice by households and firms;
• A version of the river continuum concept developed for urban watersheds;
• Meta-community theory to understand biodiversity in the urban mosaic.

Furthermore, we extend the spatial scope and temporal reach of our research. Although we have employed some sampling efforts that encompass both Baltimore City and Baltimore County, we have acquired extensive social and land cover data that cover Baltimore City and all of the five surrounding counties. A new partnership with the Maryland State Archives has yielded unprecedented access to historical records useful for understanding development of the current urban mosaic and its interaction with the countryside. To allow our future scenarios to be most relevant, we will focus not only on changing areas within the old city, such as conversion of old industrial lands to new residential development on the waterfront, and thinning row house neighborhoods near the core, but also on changing inner ring suburbs, and new residential and commercial development on the urban fringe in Carroll County and Harford County. Scenarios will be driven by a variety of social and ecological assumptions, to be informed by dialog with community and policy stakeholders. These assumptions can include different estimates of physical conditions such as sea level rise, storm surge, and heat stress, as well as contrasting assumptions about lifestyle, migration, economic investment, and spatially explicit policy options.

The Urban Meta-mosaic

An integrated spatial framework is required to address the adaptive capacity of the metropolis. The landscape perspective provides a useful way to conceive of urban ecosystems as complex systems, and to build the data bases to assess adaptive capacity. Landscape heterogeneity is a key feature of urban systems. The spatial heterogeneity of cities and suburbs is often referred to as urban fabric by designers and planners. Similarly, ecologists have employed a patch dynamic approach to understand this same spatial complexity. However, two insights from prior research and social-ecological synthesis in BES indicate that a conceptually layered approach to urban heterogeneity may be productive as we investigate adaptive capacity.

The urban mosaic is in reality a series of different landscapes, each generated or perceived by different actors in the urban ecosystem. For example, Don Outen of the Baltimore County Department of Environmental Protection and Resource Management alerted us to the existence of a “landscape of policy” which interacted with other landscapes, such as that defined by watersheds, or social identities, which we were already studying (Figure 1). This insight led us to postulate the other kinds of landscape that could organize our research. The different landscapes when composited illustrate that the city-suburban-exurban region is actually a complex land mosaic. This multilayered compilation can be called a meta-mosaic. Having a complete model of the meta-mosaic can help ensure that we assess the key factors contributing to or constraining the adaptive capacity of metropolitan Baltimore.

To organize the complicated topic of multiple landscapes, we group them into three categories. There are landscapes of 1) ecosystem process, 2) human choice, 3) and social outcome (Figure 2). Each kind of landscape can act as a constraint or enabler of structures and actions that are perceived as a different kind of landscape. In other words, there can be connections among different landscapes. In addition, local or regional landscapes can be connected to neighboring or distant landscapes. The point of this classification is not to put landscapes into distinct categories. Rather, it recognizes different processes that complex landscapes embody.

Landscapes of process

These landscapes are characterized by fluxes. The spatial patterns of biogeochemistry, with their recognition of “hot spots” and cool spots and gradients between them, or the topographic and infrastructural networks of water and sewage flow, are examples of landscapes of process. Spatial fluxes of human migration, and the movements of plants, and animals are also process landscapes.

Landscapes of Choice

We identified one of the landscapes of choice, that of policy, as the stimulus for the meta-mosaic approach. Policies are diverse in origin and effect. Zoning regulations, economic investment and disinvestment, and transportation strategies are examples of spatially explicit policy choices that generate landscapes. Other landscapes of choice include the landscapes defined by design, and by lifestyle. Lifestyle, an increasingly important features as economies shift from production to consumption bases, determines how households deploy their resources and influences decisions about purchasing, yard management, and transportation, for example.

Landscapes of Outcome

The interaction of process and choice yields outcomes that can be mapped and modeled as another kind of landscape. The biodiversity landscape of urban systems results from the interaction of the biophysical landscapes defined by topography, buildings, infrastructure, and flows, with policies about land and species management, and household preferences for lawn and garden species, for example.

Design landscapes generate outcomes in terms of the mix of built and green, the distribution of social groups, and the array of solar and wind exposures, for example. Landscapes of injustice result from formal regulations, informal norms, differential investment, and the locational choices of polluting firms or of households. Landscapes of safety and vulnerability result from different degrees of social cohesion, economic opportunity, and exposure to natural, artificial and hybrid hazards.

Landscapes of outcome can have an important temporal dimension. Some outcomes can be legacies of past conditions, as for example when neighborhood composition reflects past policies of lending or investment. Landscapes of inheritance can exist in situations where the amenities or structures now in place were established by prior occupants of different social class, identity, or status. Furthermore, the order in which decisions are made may have important implications for the structure of contemporary landscapes. Path dependence in landscape structure thus is a third temporal dimension of outcome in urban landscapes.

Interaction of Landscapes

All the individual landscapes can act as enablers or constraints of other phenomena and landscapes. Indeed, this is well recognized in planning theory and practice, where site evaluation combines different thematic maps. The fact that urban systems are often managed by distinct disciplines or professions, means, however, that the various urban landscapes may sometimes be treated as separate, isolated entities. The meta-mosaic that results from combining the landscapes, as well as their changes and interactions through time, can provide a convenient way to conceptualize the complexity of urban systems. Documenting the connections between landscapes, and understanding the nature and dynamics of the linkages among them is an important goal for the science of ecology and for design, planning, and management of urban ecosystems. It is important to recognize which landscapes reflect legacies, or which are inherited from prior occupants and their decisions. Similarly, present day landscapes may reflect path dependence. That is, the order of past events and decisions may be important to the present state of the landscape.

The interactions across the different landscapes evoke theories of control that represent different disciplines. In biophysical sciences hierarchical causation is relevant. From the social sciences concerns of structuration emerge. In geography, cross scale interactions appear as a theoretical motivation. A shared question across all these perspectives is “How do top down and bottom up causation interact in the urban meta-mosaic of linked landscapes?”

In order to address questions of control and causation between the different landscapes, we can employ the Integrated Science for Society and Environment (ISSE) model template developed by the LTER Network. This model template, which has sometimes been called a framework,shows potential linkages between the social and biophysical components of ecosystems. These are linked by ecosystem services, which reflect human values and economic interests, and by the inclusion of modes of change that range from pulsed events to gradual or continuous press events (Figure 3). In essence, the kinds of landscapes we have enumerated above are tools for highlighting and quantifying the interacting, spatially explicit elements of socio-ecological systems. These two model templates together provide a powerful way to organize empirical research, modeling efforts, education, and policy dialogs in urban systems.
A research strategy guided by this formulation of interacting landscapes and the ISSE requires these steps:

1. Identify the drivers, including human choices, that are key influences for each landscape type;
2. Include both external, that is global and larger regional, and local drivers;
3. Identify the consequences in each landscape of the biophysical drivers and human choices;
4. Identify the feedbacks between the different landscapes, paying attention to those that are lagged or indirect.

This strategy can be employed in contemporary time as well as retrospectively by employing historical information. It can also be projected into the future by addressing assumptions about emerging or possible landscape structure and drivers based on economic, social, climate, and other biophysical factors. Hence it is appropriate for scenario generation as well as historical and contemporary model building.

Choices and Constraints in Urban Mosaics

The landscapes that constitute a complex urban mosaic reflect human choices. The choices that individuals, households, communities, institutions, agencies, and various levels of government make, can of course have both intentional and unintentional effects. In either event, the linkage between choice and environment is what unifies different components of urban ecosystems. Hence, the adaptive capacity of Baltimore depends on a suite of decisions and their consequences, and the feedbacks to subsequent decisions. Such a cycle can be represented by the ISSE mentioned earlier.

To promote our research agenda, the role of human perceptions in the interaction between choices or decisions and environmental effects must be recognized. Three classes of effects or outcomes can be used: goods, services, and hazards. The Millennium Assessment provides an excellent outline of these outcomes. Goods include materials people derive from socio-ecological systems. Services
include processes in ecosystems that result in benefits, including material, aesthetic, and spiritual ones. Hazards are conditions or events that pose a threat to human wellbeing or survival. Hazards include such things as climatic stresses, severe storms, or earthquakes.

The features of the native ecosystem, the human choices, and their subsequent effects are the source of the adaptive capacity of the urban system. Choices reduce or enhance the services provided by the native biophysical environment, generate new services in the hybrid socio-ecological system, or constrain the capacity of the hybrid system to continue to adapt and provide crucial or desired services. We propose examining a subset of the possible drivers in order to focus our research, but also to respond to widely expressed social concerns about urban systems in general and about metropolitan Baltimore in particular.

New Focal Processes for BES III

To answer our principal questions requires us to quantify the adaptive capacity of Baltimore, and to examine its changes through time. Three major areas are of interest:

• Climate change and vulnerability;
• Land change and locational choices; and
• Status and regulation of biodiversity.

These factors are significant for a variety of reasons. First, they resonate with components of the
Figure 5. An outline of the main topics and their subtopics from the Baltimore City Sustainability Plan. (http://www.baltimorecity.gov/government/planning/sustainability/downloads/0509/051509_BCS-001SustainabilityReport.pdf)
sustainability plan adopted by Baltimore City and reflect concerns addressed by sustainability planning in Baltimore County and the State of Maryland. These factors are in common with urban accords about sustainability that many cities have adopted. Each has important ramifications for other components of the urban socio-ecological system. Climate change and vulnerability relate to economics of infrastructure loss, sea level rise, coastal and storm surge flooding, human health effects of heat waves and air quality, and environmental justice, among other effects. Land change reflects locational choices by households, institutions, and business firms, as well as government regulations and agency actions. Such choices reflect personal and household preferences, community activism, zoning rules and variances, and legal environmental regulation. In addition, land change follows or influences transportation policies. Land change and the spatial patterns of lifestyle or institutional culture it arrays across the metropolitan area are concomitant with different modes and intensities of resource management and use, along with waste generation and management. Land change in the Baltimore region includes shifting pockets of vacancy within the city, shifts in use of waterfront parcels, and greenfield conversion in some outlying counties. Biodiversity reflects the preferences and capacity to manage for tree canopy, horticultural planting and maintenance, interaction between exotic and native species, and management public or open access properties. Biodiversity influences quality of life, the potential for regulation of disease organisms, and the mitigation of microclimate. The spatial patterns of biota, lawn, vacant lots, and tree canopy throughout the metropolis can have feedbacks to crime, property values, and environmental inequities.

These three synthetic features of the conurbation – climate change and vulnerability, land change and locational choice, and biodiversity – will be subjected to scenario modeling. In consultation with stakeholders in communities and government, we will identify specific indicators of these three features to project into the future. The assumptions shaping alternative scenarios in each realm will also be derived from dialog with stakeholders. The involvement of stakeholders throughout the process of scenario development will increase the likelihood that the scenarios will be useful in the policy process and in education.
The three areas of focus for BES III are important for the theoretical motivation each invokes, and for the potential for integrating social and biophysical processes. These three areas also retain a connection with the data bases established in the first two phases of BES.

Climate change addresses models of sea level change, hydrology and flooding, storm severity, and urban heat islands. Hazard and vulnerability theories apply to this topic as well. Climate change will likely affect the structure and function of urban stream networks and the drainage and sanitary infrastructure with which they interact. Hence, we draw on an emerging theory of the “urban stream dis/continuum.” The mid- to fine-scale spatial heterogeneity that may interact with and modify these climatic effects is particularly important to parse out in an urban meta-mosaic.

Locational choice is relevant to theories of demography and migration. Furthermore, in a consumption based economy, locational choice requires an understanding of market segmentation and lifestyle. Environmental justice can be affected by locational choices and the procedural inclusion by which these choices are made.
Finally, urban design and planning theory are also relevant to locational choices. Again, hydrological and stream processes are relevant to locational choice, both as constraints that may change with climate or perception of hazard, and as outcomes of land change.

The status and regulation of biodiversity draw on the ecological theory of the metacommunity. This theory is hypothesized to be applicable in urban mosaics where biotic populations may be arrayed among isolated yet potentially interacting patches. Models of this theory address the degree of connectivity between population patches, the vagility of the biota themselves, or the transportive activities of people. Biodiversity in the metropolis also invokes theories of regional species richness, and ecosystem services, the ecology of infectious disease, and of psychological, behavioral, and educational effects on people. Soil differences are key to understanding community composition. Both aquatic and terrestrial biodiversity are related to watershed structure and function, and the recognition that urban riparian and watershed functions are modified by drainage infrastructure. Hence, biodiversity also relates to the urban stream dis/continuum concept. Certain aspects of biodiversity are addressed by models of community and individual preference and neighborhood cohesion.

The different landscape perspectives used in this research will promote cross-disciplinary synthesis. Ultimately, the scenarios will be a powerful synthetic tool, as implications of one realm for processes and structures represented on other landscapes will be drawn out. However, even before the full scenarios are developed, implications of one landscape, say in the biophysical realm, for another in the socio-economic realm can readily be determined. Finer scale statistical models are a tool to permit exploring the relationships between structures and processes residing in different of the urban landscapes we will quantify.

Data Requirements for Assessing Adaptive Capacity

Because adaptive capacity reflects human needs and perceptions, it is embodies values. This puts our analyses of ecosystem processes in the realm of ecosystem services, and invokes concerns of environmental justice. Adaptive capacity in a social context should enhance ecosystem services and reduce inequitable access to environmental services, amenities, and hazards. The ecological structures and processes, and the socio-economic patterns and processes that are required to assess adaptive capacity can be spatially represented as different landscapes. The landscapes can be related to one another using the interactions such as those suggested by the ISSE.