Cell states

Algal cells exhibit a range of physiological activity in response to forcing environmental factors, but these behaviors are clustered around mechanism that work together. For example, although the cell may exhibit a full range from 0 to Pmax for photosynthetic output, that output is not independent of cellular composition, temperature and oxygen. Under realistic combinations of environmental parameters, these cells exhibit suites of physiological activitis that we are calling "states".

Cells and colonies may progress from one state to another state in response to internal build up of metabolites (for example, having taken up plenty of nitrate) or in response to shifts in the environement forcing factors (for example, if the cells are moved by currents to higher or lower light).

It might be possible to model the physiological state of individual cells or colonies in the water column. This approach has been attemped in Lagrangian particle models. We have constructed similar models to examine photoinhibition in Waldo Lake. The problem with these models is that they are at a fundamentally different scale than we are measuring in lake. It is possible to study a limited number of states (eight to ten) that may occur in the course of a typical day as both the physical conditions and internal biological parameters change. For example there may be a totally mixing of the water in a shallow lake over night and then as the sun comes up the surface water warms and then depending on whether there is wind mixing, several general trajectories of these cells as they go through normal progressions could be described.

Purpose of the work

Identification of these cell states and potential trajectories through predictable progressions of physical conditions allows us to address three aspects of the ecology and managment of shallow lakes.

1. We how to understand the importance of physiological regulation in determining these states. Cells/colonies can't be assumed to be at an optimal state (ala Shuter) all of the time, but need time and the right conditions to grow into those states. In addition, this line of research may help us understand why cell regulation may not be able to achieve certain state transitions, there may be some internal interference. This work is moving from an optimization paradigm to a limited-adaptation hypothesis.
2. In our preliminary examination of these trajectories, there are certain states that are dead ends and have been implicated in crashes. We will be looking at the pen-ultimate states for these dead ends and asking if there are possible conditions or management strategies that could push the cells away from potentially crashing. This approach is consistent with my belief that many lake systems will never be restored to les than eutrophic status, and our challenge will be to manage dense algal populations. The previous advice was to avoid noxious cyanobacterial blooms we should manage the system to avoid blooms. That option doesn't seem viable and we need new ways to address the management of blooms and learn to live with high density algae.
3. Examining states and physical conditions may allow us to find smaller scale ecosystem interventions that can be used right at the point of transition. For example, it may be that multiple, flexible small-scale installations can be used to replace the large scale projects. For example, it might be that about a hundred several-hectare wetlands pumping projects could control the algal growth in a large, shallow lake. This might be in combination with longer term efforts to reduce P loading. The state trajectories will allow us to have specific physiological indicators to track and use those to adjust local interventions.