A recent body of research has begun to study how diversity within microbial communities, such as bacteria and fungi, can affect ecosystem processes. Since microbes are easily overlooked by students there are a few initial points that are worthy of emphasis to students. 1) Microbes are incredibly diverse with estimates ranging from thousands to millions of microbial “species”* per gram of soil! 2) Microbes, especially bacteria, contain most of the nitrogen and phosphorous, and approximately half of the carbon stored in living organisms. 3) Microbes are responsible for the bulk of decomposition and perform essential steps in the carbon, nitrogen, sulfur and phosphorous cycles. 4) Our limited knowledge of microbes, especially in the environment, is due to methodological hurdles.
This graph is from McGrady-Steed et al. 1997 in the journal Nature. In this paper the researchers asked the question, what is the effect of diversity on ecosystem predictability? (Emphasize to students that one of the goals of science and ecology is to build predictive models off of empirical research and data). The researchers defined predictability as low or reduced variability in an ecosystem process. Specifically in this set of experiments the scientists manipulated the diversity of aquatic microbial communities and then measured rates of ecosystem respiration. The x-axis in the above graph has realized species richness (# of different microbial species) as the independent variable. The y-axis in this case is actually a measure of variability. Notice that the y-axis is the standard deviation of carbon dioxide flux.** The negative correlation indicates that as microbial species richness increases the variability in carbon dioxide production decreases. What is important to emphasize is that as variation decreases, predictability increases — or put another way — as diversity increases the predictability of an ecosystem process increases.
*There is currently no agreed upon definition of a microbial species. Ask students why the commonly taught Biological Species Concept might not work as a unit of taxonomy for microbes.
**It may be worthwhile to draw a simple graph on the board and show students how error bars briefly work. For example. one bar with a small error bar and a second with a large error bar. Indicate to the students what this means about the populations that were measured. (For a brief summary: http://en.wikipedia.org/wiki/Error_bar).
1. What might be some of the challenges to studying microbes (especially in the environment)?
2. What are some of the recent technological and methodological advancements that have enhanced the study of microbial communities (e.g. Polymerase Chain Reaction, sequencing)?
3. Why is being able to predict ecosystem processes important? How can robust predictive models help us manage events of disturbance, extreme weather, and climate change?
4. How is human and public health dependent on microbial communities?
5. Thought question: if microbial communities contain large amounts of carbon how could they be involved in climate change processes (in both positive and negative ways)? Below: helpful graphic of carbon cycle. Emphasize to students that much of the respiration (production of CO2 indicated by blue up-arrows) is due to microbial processes. Notice that rates of photosynthesis and respiration are nearly equal.
Note: this post will work well with Crutsinger et al. 2008 and the post, “Genetic Diversity and Invasion.”
This graph is taken from Stachowicz et al. 1999 from the journal Nature. In this study the researchers asked the question, what is the effect of species diversity on the success of an invasive species? In this particular experiment the researchers used marine invertebrates communities to test the hypothesis that increased native species richness decreases the abundance of an invasive. Experimental communities were composed of 0-4 native species cultured on tiles. The invasive tunicate (Botrylloides diegensis) was then introduced into each of the experimental communities and its success was measured. The top graph (a) has community species richness (# of species) on the x-axis as the independent variable. The y-axis is invaders surviving as a percent as the dependent variable. The negative correlation shows that as species richness increases the percent of surviving tunicates decreases. This relationship suggests that communities that have greater species richness can slow or deter rates of invasion by exotic species more so than communities that are devoid of diversity. Graph (b) offers a hypothesized mechanisms for the observed pattern in graph (a). Graph (b) has the same independent variable, by the dependent variable in this case shows the amount of unoccupied space. The pattern in graph (b) shows that as richness increases that amount of available space (i.e. for invaders) decreases.
1. Why might biologists, managers, politicians, and citizens be worried about invasive species?
2. What are some local invasive species in your environment? What efforts are happening locally to manage these invasive species?
3. These patterns have been observed now in multiple systems (e.g. marine, plant, terrestrial.) How does observing similar patterns across systems and taxa support the general conclusion that higher levels of diversity can protect a community from invasion? Why is it good for science to test theories across multiple systems?
4. What are other examples of invasive species in marine or estuarine systems? What are some of the mechanisms by which these invasive species enter these new systems?