Regime Shifts and Leading Indicators

1. Regime Shifts and Leading Indicators Michael Pace University of Virginia

2. Outline • Human accelerated environmental change • Regime shifts • Theory of leading indicators • An experiment to test indicator theory • Microbial communities and regime shifts

4. Humans Global climate change Loss of biodiversity Land-use changes Stratospheric ozone depletion Invasions of Exotic Species Toxification of the Biosphere From Likens 1998 Environmental change caused by multiple and interacting human activities.

5. Regime Shifts • Massive reorganizations of ecosystems that occur abruptly and led to an alternate state • May be driven external causes or internal processes • Shifts may be difficult or impossible to reverse • Feedbacks that control ecosystem processes are different after a regime shifts • Example: switch during eutrophication from limitation by external nutrient loading to internal nutrient recycling

6. Regime Shift Second Regime Resilience First Regime

7. Anderson et al. TREE in press

8. ENSO – Example of Regime Shift

10. El Nino Forecast

11. Shallow Lakes • Shift from clear water, vegetation-dominated condition • To turbid, algal-dominated state • These shift are triggered by several switches

12. Algae + + grazers Turbidity Nutrients fish resuspended sediments - - Vegetation waves

13. Zebra Mussels – Dreissena polymorpha

16. Zebra Mussel Dynamics 1991-2002

18. Hudson River Zebra Mussel Invasion

20. Effects on Hudson Ecosystem • Direct consumption – plankton • Change in light transmission - plants • Fouling – native bivalves • Competition – other filter feeders • Propagation through food web – fish • Creation of structure – benthic animals

21. Problem • Regime shifts are difficult to predict • Ideally manage to avoid “going over the cliff” • Are there leading indicators that would warn of shifts prior to initiation?

22. Possible Leading Indicators of Regime Shifts From Theory • Increase in variance of time series • Variance shifts to lower frequencies (“red shift”) • Recovery rate from small perturbations increases (“critical slowing down”) Known from physics, models of ocean thermohaline circulation, economics, climate studies, and ecological models

24. Carpenter et al. 2008 Ecology Letters

28. Conclusions from Model • Signals of regime can be detected well in advance if the driver of the regime shift (e.g. fish harvest) changes more slowly than key ecological variables (e.g. phytoplankton production, zooplankton biomass) • However regime shifts can occur after the driver has already passed the critical point (i.e. ecosystem is already committed to going over the cliff when indicators go off)

29. Paul Peter

30. Continuous Observation Methods Nighttime: Daytime:

33. Can Microbial Communities Drive Regime Shifts? • Perhaps rapid response and diversity of microbes results simply in community shifts to groups adapted to the new conditions • However competitive interactions, metabolic capacity, genetic composition or other phenomena might drive regime shifts that are determined by relative abilities with profound consequences for ecosystem structure and function

35. Initial Model • Adapted modeling framework of Fellows et al. • Start with simple two group model of phytoplankton based on relative ability to compete for N and P (e.g. cyanobacteria vs. greens)

37. Status • Elaborating model to build an approach to an experimental • Idea would be to fertilize a lake varying N:P ratio through time • Continuously monitor changes in phytoplankton (and others) • Measure leading indicators

38. The hypoxic zone of the Gulf of Mexico has approximately doubled in size per unit nitrogen input. This partially reflects the accumulation of organic carbon in sediments that supports increased oxygen demand Turner et al. 2008 EST

39. Perspective • Not all environmental change is abrupt (many transitions are gradual) • Not all regime shifts will have leading indicators • Continuous measurement systems provide opportunity to detect systems in transition (whether slow or fast) • How do we manage to avoid transitions • Defining indicators • Ability to detect “signals” of change • Proactive means to stay away from “the edge” and/or avoid “slow progressive” changes • What microbial capacities and processes will drive regime shifts particularly in relation to climate change?