Geo 599 – Concepts in Ecosystem Informatics
Module 1- Disturbance propagation in stream networks in space and time
J.A. Jones.
Part 1 of 4.
1. Key concepts.
A) a list of 5 to 10 key terms/concepts that we (faculty and students) should all know, from your disciplines (and be prepared to define them)
1-Disturbance, succession, disturbance history of a site
Disturbance – deviation from succession; physical or biological sudden change
Succession – predictable sequence of (plant) species and (vegetation) structure in time
Disturbance history of a site:
- multiple disturbances
- multiple types
- order is important (Harvard Forest)
2-Laws of thermodynamics, pressure gradients, heat/energy transfer, latent heat
Laws of thermodynamics:
- conservation of matter and energy
- entropy (declining free energy)
-
Pressure gradients – produce motion of air, water
Solar energy
Heat/energy transfer
- conduction
- convection
- radiation
Energy transfer through changes of state
- latent heat
- heat of vaporization (endothermic)
- heat of condensation (exothermic)
Energy to do work
- potential
- kinetic
- Coriolis forces
3-Climate, seasonality, atmospheric and ocean circulation
Laws of thermodynamics + changes of state of water + motion of air and water
= atmospheric circulation AND ocean conveyor belt AND climate
+ rotation, orbit, tilt of Earth and orbital variations
= seasons, glacial cycles
4-Hydrologic cycle, roles of vegetation
hydro cycle = movement of water through
- atmosphere
- biosphere
- geosphere
processes in hydrologic cycle that are tied to vegetation
- interception
- throughfall, stemflow
- evaporation
- transpiration
- soil moisture
5-Networks: small world, branching hierarchical v. patchworks: adjacency, linear distances
networks
- arcs, nodes
- branching hierarchical
- small world
- in space, in time (evolution)
patchworks
- patch size
- patch spacing
- amount of edge
6-Scale, grain, extent, scaling laws, self-similarity, fractals, power law
Scale = grain and extent
Scaling laws
- self-similarity
- power law
- fractals
7-Spatial transfers of water, sediment, wood in landscapes; Landform evolution
Water storage and routing
- soil moisture, water in veg and atmosphere
- floods, flood routing
sediment and wood storage and routing
- sediment on hillslopes
- wood on hillslopes
- sediment in streams
- wood in streams
8-Causality, experiments, observational studies, causal inference
Causality
- cause
- effect
- attribute
Experiment
- control
- treatment
- replicate
- temporal stability, causal transience
- unit homogeneity
9-Empirical models: Statistical significance, type 1 and type 2 errors, statistical power
Model fit to data
- goodness of fit
- types of error (fail to reject the null, fail to accept the alternative)
- selection of functional form, overfitting
Statistical power
10-Simulation and optimization models: discriminating among multiple solutions (JCA papers; Revelle, Church)
Simulation model: equations, variables
Optimization model: objective function equation, constraint equations, variables
Integer vs. continuous optimization (networks vs. patchworks)
Selecting among feasible solutions: solution algorithms; heuristics
Geo 599 – Concepts in Ecosystem Informatics
Module 1- Disturbance propagation in stream networks in space and time
J.A. Jones.
Pre-test
1. What are the laws of thermodynamics and what sorts of equations do they permit us to write about physical entities?
2. Name several forms of energy or energy transfer and give an example of each that involves water.
3. Earth is an open system with respect to ______, but a closed system with respect to ______(name some form(s) of energy/matter). Sketch an open system and a closed system.
4. How do various forms of energy and heat exchanges give rise to atmospheric and ocean circulation?
5. Draw the hydrologic cycle. List the components that are linked to vegetation.
6. Draw a branching hierarchical network and a small world network. How do they differ in form and function?
7. How do statistical methods help one to discriminate among alternative empirical models?
8. How does optimization help one to discriminate among alternative mathematical models for a given process?