Physical geology as a discipline is evolving into earth system science. What does that mean?

We can start with a simple metaphor. If you want to understand how a motor or clock works you take it apart, study the parts and their character, then note the arrangement of the parts, and then put it back together. You change one part and then see how it affects performance and thereby understand the system better. As a graduate student I was amazed to find with my old and rusty VW fastback that there were all sorts of pieces that it didn't seem to need. Other pieces were critical.

Natural science is similar. Focusing on and studying one part is a reductionist approach. Studying one mineral in a rock would be an example. Putting parts together to understand the operations of the larger system is an integrationist approach. Both are necessary in natural science, but often you start with a reductionist approach and move on to integration of the components you understand. With new tools and driving questions geoscience is embarking on more of an integrationist approach. If you want to understand what happens inside the earth's crust it turns out that not only are the rocks important, but the fluids that move through them, and the life that lives in them. Fluid dynamics, biology and geology begin to merge into earth science. Here are some of the large system bits we now are integrating:

• atmosphere.
• hydrosphere.
• biosphere.
• cryosphere.
• lithosphere.

Why would one want to learn about the earth?

Specific earth science knowledge is useful.

• in resource management, especially in the discovery, extraction and waste disposal aspects, all of which include environmental and sustainability considerations. These resources include groundwater, fossil fuels, soils, metallic ores and building stone material such as gravel and cement, resources that are core to modern society.
• as a career and in professional practice ( e.g., geologists, environmental scientists, civil engineers, planners, lawyers).
  • American Geological Institute video on geoscience careers.
• in personal endeavors (e.g. avoiding hazards, future problems when purchasing property).
• in civil issues and having an informed citizenry (e.g. voting and being involved in all sorts of issues with a geologic component such as waste disposal, water resources, and climate change). This aspect is addressed more in our Environmental Geology (GEOL 1010) course.
• In geohazard risk assessment (earthquakes, landslides, floods, volcanic eruptions and much much more) -Indian Ocean tsunami example. Image to right is of USGS scientists collecting volcanic gases at Mt. Hood in Oregon. Changes in such gases can signal an eruption. Image source: https://volcanoes.usgs.gov/volcanoes/mount_hood/mount_hood_monitoring_98.html .

Such knowledge helps develop useful mental skills:

• will provide experience in and tools for understanding complex problems and systems.
• ecology, economics and psychology are other good examples of disciplines focused on understanding complex problems and systems.
• geoscience is multidisciplinary by nature.

Aesthetic appreciation of the world around you:

• most intangible, but most valued by some.
• this course should literally change what you see as you travel through this world and life. Landscapes and rocks contain the stories of their formation within themselves if you learn how to read them.
• Loren Eisley: Nebraska author who explored the intersection of geology and literary art. More info.

Below is a list of some of the components that people often include.

• generation of models, ideas, hypotheses, explanations.
• data gathering, observations, measurements.
• data analysis.
• testing, comparison, experimentation
• repeatability
• publication and peer review.
• modeling.

The next question might be as to how they fit together.

The following is from Hempel (a historian of science):

" If we try to imagine how a mind of superhuman power and reach, but normal so far as logical processes of thought are concerned, .... would use the scientific method, the process would be as follows: First all facts would be observed and recorded, without selection or a priori guess as the their relative importance. Secondly, the observed and recorded facts would be analyzed, compared, and classified, without hypothesis or postulates other than those necessarily involved in the logic of thought. Third, from this analysis of the facts generalizations would be inductively drawn as to the relations, classificatory or causal, between them. Fourth, further research would be deductive as well as inductive, employing inferences from previously established generalizations. "

This can be distilled to the four following stages:

• "observation and recording of all facts,
• analysis and classification of these facts,
• inductive derivation of generalizations from them,
• further testing of the generalizations."

Induction: generalizations from specific cases, that can be applied elsewhere.

• exemplars: an explanation and the data it explains, training modules for the initiates. This is a focus of what you learn in a typical college course.
• metaphysics: e.g. historical continuity of basic physical laws.
• language: e.g. statistics for psychology.
• values: e.g. honesty.

Note that there can be significant overlap, shared exemplars, metaphysics, language and values between different scientific disciplines.

How can we understand complexity?

• To understand a complex system an initial requirement is to understand how the parts work in isolation. This is classic reductionist science.For example, in order to understand river behavior, you have to understand the physics of how water can move a particle. Isolating and simplifying a system in a lab beaker is perhaps an iconic image for reductionistic science. However, when the parts are combined they show new types of behavior only possible through the combination, a phenomena known as emergent properties - new behavior/properties emerges from the combination of parts. So while reductionist science is a necessary foundation, other tools are needed for understanding complex science.
• Conceptually we can use system diagrams (boxes and arrows to start with). Think of the water cycle as an example. We will also work with the rock cycle in this course. Feedback loops are an especially crucial type of behavior to understand.
• Certain concepts such as feedback loops, chaos and initial conditions sensitivity, strange attractors and fuzzy logic are also useful in understanding complexity. These terms may not make much sense at this point, but need to be developed as the course goes on.
• Computer models can be used to keep track of all the parts, interactions, and large amounts of dat, and to do the repetitive and tedious math required. A remarkable example are global climate models.

This is image of the lower part of the Niobrara River in Nebraska. It is a good example of a braided river system. Think of the myriad of factors that contribute to why this river has the pattern and behavior it does. Precipitation patterns, vegetation, the amount and type of sediment, the slope, river ice in the winter, groundwater interaction, and much more. It is a good example of a complex system.

Chaos - what is it?

• complex behavior from simple systems (e.g. sand slips on a sand pile).
• long term unpredictability of precise system configuration versus predictability of long term behavior patterns .
• related concepts are strange attractors, self organization, fractals and scale invariance (some of the jargon). We will be learning about some of these in this course.

Basically, one sees a mountain side. Often insights come from asking questions. How did this mountain form and is being shaped at present. What features are exposed in the mountain side, and how did they form. Here are some more specific thoughts that might come to mind when viewing this image with some training in geology:

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