Kimberly D. Robinson, Nah Eun Kim, and Bryan C. Pijanowski

Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN 47906

The Great Lakes Social-Ecological System

Socioeconomic DriversFigure 1. Socio-ecological system framework modified from Grove, Hinson, and Northrop (2003).

The Great Lakes region of the U.S. is composed of both natural and human systems, whose functions are intricately woven together to create one complex socio-ecological system (Figure 1). Changes in the structure or function of specific system components (or processes) within the natural system can have profound impacts on other natural system components (or processes), as well as on the structure and function of the region’s social system, and vice versa. Changes in one part of a socio-ecological system are often felt within other parts of the system. As such it is important to consider the linkages between system components (i.e., natural and social) when making land use planning and natural resource management decisions.

When making land use planning and natural resource management decisions, one of the underlying goals should always be to maintain (or restore, if necessary) the integrity of the ecosystem (i.e., the ecological integrity). The term ecological integrity is used to refer to a socio-ecological system that balance natural system processes with those of the social system without compromising the structure, function, or self-organizing way in which the two systems interact (Francis and Reiger, 1995). Within the Great Lakes states, measures of ecological integrity can be used to assess to what extent the socio-ecological system within the region has the ability to 1) self-regulate itself and adjust to disturbances without compromising its structure or function,

2) support healthy biotic and abiotic communities (both terrestrial and aquatic), and 3) support the integral role humans (or their impacts) play within the system. One such way to measure the ecological integrity of a region is through the use of tipping points or thresholds.

What is a tipping point and why are they important?

The vast majority of watersheds within the Great Lakes states are dominated by human activities and are often categorized as complex adaptive systems. Complex adaptive systems being able to change over space and time, have the potential to exist in numerous different stable states (or regimes) in which the linkages and feedbacks from both social and natural processes remain fairly stable and predictable. However, rapid changes in these systems caused by natural events or human disturbances can alter both the structure and function of the systems. Changes to a system’s structure and functions often leads to the complex adaptive system shifting from one stable state regime to another.

The point at which the system can move away from one stable state toward another is called a tipping point (or threshold). As stated by Cairns in 2004, the term tipping point refers to the point in which “the forces that create stability are overcome by the forces that create instability… [and the] system tips over into disequilibrium.” Eventually, over time, a socio-ecological system will reach a new equilibrium (i.e., stable state) in terms of both structure and function, but the ecological integrity is often severely degraded and may not be able to adequately support the natural and/or social systems relying on it. The crossing of socio-ecological tipping points may come about as a result of 1) a series of small changes to the socio-ecological system, or 2) a large abrupt change to system properties, phenomenon, drivers of change, or feedback loops (Groffman et al., 2006).

To help illustrate the tipping point concept, Lewontin (1969), and later Walker and Salt (2006), portrayed tipping points and stable states (i.e., regimes) using a ball-in-basin model (Figure 2). In this model, the basins represent ecosystem regimes, while the ball

Tipping Point ConceptFigure 2. Tipping point concept as represented by the ball-basin model (adapted from Walker and Salt, 2006 and Lewontin, 1969)

corresponds to the current state of the ecosystem. As the ball moves up the edges of one basin and toward the second basin, the ecosystem is approaching and ecological tipping point. When the ball reaches the tipping point between the two basins, it has an equal propensity to move into either basin. Likewise, as an ecosystem reaches a tipping point, it can either remain in its current regime or shift to a different regime changing both the ecosystem’s structure and function. However, once a tipping point has been crossed, the system will automatically begin to rearrange itself into the new regime. If tipping points are cross and result in unfavorable changes, transitioning from the new equilibrium state back to the old equilibrium state may be difficult if not impossible. Forcing a complex adaptive system to revert back to an old equilibrium state, if even possible, often requires considerable amounts of energy (and potentially monetary resources if humans engage in system restoration efforts).

Some tipping points may be identifiable, but it is much easier to see where tipping points are once they have been crossed. Early detection (i.e., identifying tipping points before they have been crossed) is often difficult, if not impossible (Robinson, 2013).

Past Research

Since the 1960’s, concerted efforts to counteract or alleviate human induced stresses within the Great Lakes region have been a priority for many government organizations and scientific researchers (Kim, 2012). By 1997, Booth and Jackson (and later Yang et al., 2010) proposed that even with very low levels of urbanization within a watershed, water quality degradation and negative impacts to aquatic communities can already be seen. They stated that when 10% (Booth and Jackson, 1997) or 8-15% (Yang et al., 2010) a watershed’s land area becomes impermeable surface area (most often associated with urban land uses) the watershed reaches (or crosses) a possible ecological tipping point (or threshold). When a watershed exceeds this percentage of impervious surface area, “negative effects to the system” are evident, as macro-invertebrate populations significantly decline (Booth and Jackson, 1997; Yang et al., 2010).

The National Non-point Education of Municipal Officials (NEMO) network has promoted Booth and Jackson’s potential tipping point for years. Over 30 states and hundreds of watershed planning groups and local governments have adopted Booth and Jackson’s potential

tipping point and now require consideration of the 10% impervious surface area threshold when writing master plans (Kim, 2012). However, as pointed out by Kim (2012), the 10% impervious surface area ‘rule’ does not hold true for all locations, as considerations need to be made based on the percentage of other land use/covers present within a watershed, the configuration of those land uses/covers in the watershed, and the variation in local geomorphological effects on stream ecosystem health.

Current Research

Keeping in mind that broad sweeping tipping points may not be accurate for all locations or watersheds, researchers from throughout the Great Lakes region are working to identify potential water quality tipping points based on regional watershed similarities and differences. These researchers are have been tasked with 1) developing land use/cover indicators for the Great Lakes region and 2) studying the relationship of measured indicator changes to current ecosystem structure and function. Great Lakes Environmental Indicator (GLEI) project scientists have also developed a list of 14 ecological indicators linked to responses of amphibians, diatom algae, fish, birds, micro-invertebrates, and wetland vegetation to human induced stressors. By studying the relationship between land use/cover indicators and changes within the ecosystem, a handful of potential tipping points within the Great Lakes region’s socio-ecological system have be identified.

Preliminary research results from one study being conducted by researchers at Purdue University and the University of Michigan have identified possible tipping points associated with impacts of riparian zone agriculture and urban lands on water quality. Kim (2012) studied changes in the variety of species and abundance of EPT taxa (i.e., macro invertebrates such as stoneflies, mayflies, and caddisflies) in response to varying percentages of urban and agricultural lands within Great Lakes region catchment buffer zones (i.e., 150m buffers surrounding rivers and streams). Here, the term catchment is used to refer to all land that drains into a specific river or stream. Results from her study show significant differences in EPT taxa populations within catchments when 15-20% of the buffer zone land along rivers and streams are composed of urban and agricultural lands. When 30% of the entire catchment is composed of urban and agricultural lands, EPT taxa in the states of Illinois, Michigan, and Wisconsin seem to reach a tipping point.

Additional tipping points research, conducted by Wiley and Riseng (unpublished) from the University of Michigan, predicts that when the percentage of land within a watershed is composed of urban uses, that particular watershed is heading down a “slippery slope” toward an ecological tipping point. By the time the watershed reaches 22-23% urbanized the quality of water in its rivers and streams have become impaired. Slightly higher percentages in the amount of agricultural lands are needed to reach impairment than urbanized land. According to Wiley and Riseng, river and stream impairment is reached when approximately 33% of the watershed is composed of agricultural lands. Although these identified potential tipping points results are only preliminary, the urban and agricultural land use cut-off percentages values proposed by Kim (2012) and Wiley and Risen (unpublished) closely mimic those identified by the U.S. EPA and other researchers working throughout the Great Lakes region.

Using the potential tipping points identified by both Kim (2012) and Wiley and Riseng (unpublished), Robinson (2013) identified which of the 150 HUC8 watersheds (identified by the U.S. Geological Survey) (Figure 3) compromising the U.S. portion of the Great Lakes drainage basin are predicted to become impaired by the year 2060. Future land use/cover predictions for each HUC8 watershed were developed by Tayebbi et al., (2012) using the Land Transformation Model (LTM), originally developed by Purdue University.

By the year 2060, Robinson’s (2013) research study results predict that by the year 2060, 25 watersheds within the Great Lakes drainage basin will experience 23% or more of their land area being composed of urban land uses, indicating that these watersheds are expected to reach (or exceed) ecological tipping points identified by Wiley and Riseng (unpublished). Furthermore, by the same year (i.e., 2060), another 58 watersheds are predicted have the majority (i.e., great than 50%) of their land area devoted to urban and agricultural uses. Such statistics lead to troubling conclusions about the future ability of Great Lakes region watersheds to maintain socio-ecological system stability and integrity. If these predictions hold true, the vast majority of watersheds may lose their ability to maintain their current ecosystem structure and functions needed to preserve both surface and ground water quality and support societal needs and processes.

HUC 8 watersheds in the Great Lakes
Figure 3. Location of the 150 HUC8 watersheds falling within the Great Lakes drainage basin

Use of tipping points for land use planning and natural resource management

Historically the management of Great Lakes water resources (both surface and ground water) within the U.S. has been reactionary in nature (i.e., water quality management/protection policies were put in place following the identification existent threats to human health or aquatic communities) (Huber, 1989). More recently, however, governmental entities and local watershed restoration/conservation groups have begun to recognize the importance of preemptive management (i.e., managing before problems arise) when it comes to managing natural resources and ecosystems. Monitoring the current status of ecosystem components (i.e., water quality) and directing management efforts based on potential tipping points, may help to maintain or restore favorable ecosystem characteristics while avoiding unfavorable changes in ecosystem status, structure, and function.

As with overall water resource management within the Great Lakes region, current uses of tipping points for ecosystem management today are often retrospective in nature (Kim, 2012). Changes to ecosystems are recognized and studied only after tipping points have been crossed. This retrospective can be associated with the current lack of knowledge about and identification of tipping points within the Great Lakes socio-ecological system. Never the less, some potential tipping points have been identified.

Despite the overall lack of abundance of identified tipping points, land use planners and natural resource managers can still work to avoid unfavorable changes (associated with reaching and exceeding tipping points) within socio-ecological systems by engaging in adaptive management efforts. Adaptive management allows for the adjustment of planning/management decisions and implementation strategies based on observable environmental (Gunderson, 1999) and societal impacts. Engaging in adaptive management will ensure that decisions are being made with the recognition that outcomes from these decisions may result in a number of different acceptable outcomes, each allowing for the socio-ecological system to adapt to the changes in a way in which its ecological integrity remains uncompromised.

In addition, by responding to unfavorable changes resulting from planning/management decision, land use planners and natural resource managers will have the ability to avoid socio-ecological tipping points without having to necessarily know exactly where the tipping points are at. Indeed, if tipping points are known, planning and management decisions can be made with the tipping points in mind. It should be noted though that the exact value of the tipping points may vary slightly due to regional or watershed characteristics. Thus, when making decisions based on a specific tipping point, it is important to remember that there may be a tipping point range (without exact tipping point falling within a range of possible values) instead of an exact tipping point threshold value.

Literature Cited

Booth, D.B. and C.R. Jackson. 1997. Urbanization of aquatic systems: Degradation thresholds, stormwater detection, and the limits of mitigation. Journal of the American Water Resource Association 33(5): pg. 1077-1190.

Cairns, Jr., John. 2004. Ecological tipping points: A major challenge for experimental sciences. Asian Journal of Experimental Sciences 18 (1 & 2): pg. 1-16.

Francis, G.R. and H.A. Regier. 1995. Barriers and bridges to the restoration of the Great Lakes Basin ecosystem. Chapter 6 in L.H. Gunderson, C.S. Holling, and S.S. Light (eds). Barriers and bridges to the renewal of ecosystems and institutions. Columbia University Press, New York, New York.

Groffman, P.M., J.S. Baron, T. Blett, A.J. Gold, I. Goodman, L.H. Gunderson, B.M. Levinson, M.A. Palmer, H.W. Paerl, G.D. Peterson, N.L. Poff, D.W. Rejeski, J.F. Reynolds, M.G. Turner, K.C. Weathers, and J. Wiens. 2006. Ecological thresholds: The key to successful environmental management or an important concept with no practical application? Ecosystems 9: pg. 1-13.

Grove, J.M., K.E. Hinson, and R.J. Northrop. 2003. A social ecological approach to understanding urban ecosystems and landscapes. In A.R. Berkowitz, C.H. Nilon, and

K.S. Hollweg (eds). Understanding Urban Ecosystems: A new frontier for science and education. Springer-Verlag, New York, New York.

Gunderson, L. 1999. Resilience, flexibility, and adaptive management: Antidotes for spurious certitude? Conservation Ecology 3(1): pg. 7-18.

Huber, C.V. 1989. A concerted effort for water quality. Journal of the Water Pollution Control Federation 61: pg. 310-315.

Kim, N.E. 2012. Ecosystem tipping points in the Laurentian Great Lakes. Purdue University, West Lafayette, IN.

Lewontin, R.C. 1969. The meaning of stability. Brookhaven Symp. Biological Journal of the Linnean Society 22: pg. 13-24.

Robinson, K.D. 2013. Deciding the Future: Informing the Development of a Decision Support System for Water Resource Management by Great Lakes Region Land Use Planners. Purdue University, West Lafayette, IN.

Tayyebi, A., B.K. Pekin, B.C. Pijanowski, J.D. Plourde, J.S. Doucette, and D. Braun. 2012. Hierarchical modeling of urban growth across the conterminous USA: developing meso-scale quantity drivers for the Land Transformation Model. Journal of Land Use Science: pg. 1-21.

Walker, B. and D. Salt. 2006. Resilience thinking: Sustaining ecosystems and people in a changing world. Island Press, Washington D.C.

Yang, G., Bowling, L.C., Pijanowski, B., and Niyogi. D. 2010. Hydroclimatic response of watersheds to urban intensity: an observational and modeling-based analysis for the White River Basin, Indiana. Journal of Hydrometeorology 11: pg.122-138.

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