Last month the climatologist Justin Maxwell from Indiana University gave an interesting talk at our department about drought-busting tropical cyclones. In his talk, and in conversations before and after with our physical geography crew, he had some interesting things to say about climate teleconnections involving mainly sea surface temperature and pressure patterns such as ENSO, NAO, etc. If teleconnections and the various acronyms are unfamiliar, check out the National Climatic Data Center’s teleconnections page: http://www.ncdc.noaa.gov/teleconnections/

I've thought, written, and talked a lot about the need to incorporate geographical and historical contingency--that is, idiosyncratic characteristics of place and history--in geosciences, in addition to (not instead of!) general or universal laws. I've also emphasized the fact that places and environmental systems have elements of uniqueness. This leads to the issue of how to measure or assess place similarity (or the similarity of different, e.g., landscapes, ecosystems, plant communities, soils, etc.). This is a way of thinking about this problem, dressed up with some formal mathematical symbolism. Though I'm personally pretty informal, I'm a big believer in formal statements in science, as it makes arguments at least partly independent of linguistic skills (or lack thereof). 

In fluid dynamics the Reynolds Number is the ratio of inertial to viscous forces, and is used to distinguish laminar from turbulent flow. Peter Haff (2007) applied this logic to develop a landscape Reynolds number, and also suggested how other generalized “Reynolds numbers” can be constructed as ratios of large-scale to small-scale diffusivities to measure the efficiencies of complex processes that affect the surface. As far as I know, there has been little follow-up of this suggestion, but the premise seems to me quite promising at an even more general level, to produce dimensionless indices reflecting the ratio of larger to smaller scale sets of processes or relationships. The attached file gives a couple of examples. 

Resistance of environmental systems is their capacity to withstand or absorb force or disturbance with minimal change. In many cases we can measure it based on, e.g., strength or absorptive capacity. Resilience is the ability of a system to recover after a disturbance or applied force to (or toward) its pre-disturbance condition—in many cases a function of dynamical stability. In my classes I illustrate the difference by comparing a steel bar and a rubber band. The steel bar has high resistance and low resilience—you have to apply a great deal of force to bend it, but once bent it stays bent. A rubber band has low resistance and high resilience—it is easily broken, but after any application of force short of the breaking point, it snaps back to its original state.

Some form of the diagram below is often used as a pedagogical tool, and to represent a theoretical framework, in fluvial geomorphology, hydrology, and river science. It is called a Lane Diagram, and originated in a publication by E.W. Lane in 1955:

The diagram shows that stream degradation (net erosion and incision) and aggradation (net deposition) responds to changes in the relationship between sediment supply (amount of sediment, Q_s, and typical sediment size, D₅₀) and sediment transport capacity (a function of discharge or flow, Q_w, and slope, S). The diagram is a very helpful metaphor in understanding the sediment supply vs. transport capacity relationship, and its effects on channel aggradation or degradation.

Yesterday I heard a very interesting river restoration workshop at the British Society for Geomorphology meeting. What I’m about to discuss was not the focus of the workshop, but it was triggered by thinking about geomorphology, hydrology, and river science in stream rehabilitation and restoration, which is a big business now.

The stream restoration problem is often portrayed as something like this:

That is, the stream is currently in some kind of degraded, suboptimal, unwanted state. The goal is to restore it to a “natural” or some more desired condition, often conceived as whatever the stream was like before the degradation commenced. There are a number of problems with this, one being that in many cases the pre-existing state is not known. Even if it is, since rivers—like other landforms and ecosystems—are dynamic and changeable, there is no particular scientific reason to believe that, in the absence of human-driven changes, the river would still be now as it was decades ago.

"In each human coupling, a thousand million sperm vie for a single egg. Multiply those odds by countless generations, against the odds of your ancestors being alive, meeting, siring this precise son; that exact daughter...until your mother loves a man ...and of that union, of the thousand million children competing for fertilization, it was you, only you...(it's) like turning air to gold... a thermodynamic miracle."

Those words, from Alan Moore’s “Watchmen,” indicate that despite the common features of all members of our species, the biological laws and relationships that apply to us all, each of us is unique in some way. I am reminded on this on the occasion of the birth of my first grandchild, Caroline Harper Phillips, yesterday.

Caroline Harper Phillips, age <1 day

I recently stumbled upon the OCBIL theory. In the words of Hopper (2009): “OCBIL theory aims to develop an integrated series of hypotheses explaining the evolution and ecology of, and best conservation practices for, biota on very old, climatically buffered, infertile landscapes (OCBILs). Conventional theory for ecology and evolu- tionary and conservation biology has developed primarily from data on species and communities from young, often disturbed, fertile landscapes (YODFELs), mainly in the Northern Hemisphere.” As a geomorphologist, and in particular a biogeomorphologist interested in coevolution of landscapes, biota, and soils, the OCBIL-YODFEL contrast is extremely interesting—mainly because it implies a key role for landscape age, stability, and geomorphic disturbance regimes in the development of ecosystems and evolution of biodiversity patterns.