Publications and presentations associated with the
ATB project.
Publications:
- Fernandez-Gonzalez,
N., Huber, J.A., Vallino, J.J. (2016) Microbial communities are well
adapted to disturbances in energy input. mSystems 1 (5), 15 pp., doi: 10.1128/mSystems.00117-16.
This paper shows that microbial
communities can exhibit strong internal dynamics that may be more
important in shaping community succession than external drivers.
Dynamic “unstable” communities may be important for ecosystem
functional stability, with organisms of the rare biosphere playing
an important role incommunity restructuring.
This review paper places
Lotka's original ideas on
ecosystem organization and function within the formalized MEP concept.
- Chapman, E.J., Childers, D.L. and Vallino, J.J. (2016) How
The Second
Law of Thermodynamics has informed ecosystem ecology through its
history. BioScience
66 (1),
27-39, doi: 10.1093/biosci/biv166.
This manuscript reviews and compares the maximum entropy production
principle to the maximum power princple.
- Algar, C.K. and Vallino, J.J. (2014) Predicting microbial
nitrate reduction pathways in coastal sediments. Aquat.Microb.Ecol. 71 (3):
223-238, doi:10.3354/ame01678
This paper uses MEP to
predict
metabolic switching between denitrification, dissimilatory nitrate
reduction to ammonium (DNRA) and anammox during anaerobic nitrate
reduction.
- Vallino, J.J., Algar, C.K., Fernandez Gonzalez, N., Huber,
J.A.. (2014) Use of receding horizon optimal control to solve
MaxEP-based biogeochemistry problems. In Beyond the Second Law: Entropy
Production and Non-Equilibrium Systems, Dewar, R.C.,
Lineweaver, C., Niven, R. and Regenauer-Lieb, K., (eds),
Springer, pp 337-359, doi: 10.1007/978-3-642-40154-1_18.
(draft version)
This paper demonstrates
the use of receding horizon optimal control
to solve MEP-based problems and accurately simulates experimental data
from Exp 1 of the ATB project, which
are presented elsewhere on this web site (see
ATB Exp 1).
- Vallino,J.J. (2011) Differences and implications in
biogeochemistry from maximizing entropy production locally versus
globally. Earth Syst.
Dynam. 2,
69-85, doi: 10.5194/esd-2-69-2011
This paper uses a model
two-compartment system to examine how entropy production changes if
maximized within each compartment (locally) versus across both
compartments (globally). Results indicate that maximizing
entropy production globally is greater than the sum of entropy
production obtained from local maximization. These results
indicate that systems that coordinate function over space can out
compete those that function without cooperation in terms of energy
dissipation.
- Vallino, J.J. (2010) Ecosystem biogeochemistry considered
as a distributed metabolic network ordered by maximum entropy
production. Phil. Trans.
R. Soc. B, 365,
1417-1427, doi:10.1098/rstb.2009.0272
This paper presents an MEP-based
approach to modeling
microbial biogeochemistry using an optimal control algorithm. Since maximizing entropy
production instantaneously
will not lead to the synthesis of living biomass (i.e., biological
structure), entropy
production is maximized over intervals of time. By “investing” in the
synthesis
of biological catalyst, a system can ultimately generate more entropy
over a
finite time than a system that maximizes entropy production
instantaneously,
such as fire.
Presentations:
- Use of
methanotrophic microcosms, tag sequencing and thermodynamic metabolic
models to examine structure-function relationships.
ASLO Ocean Sciences Meeting, Salt Lake City, Utah, Feb 2012. (pdf, 2.4
MB)
- Use of
receding horizon optimal control to solve MEP-based
biogeochemistry problems. Australian National
University,
Canberra, Australia, Sep 2011. (pdf, 2.5 MB)
- How do
living systems differ from fire? Microbial biogeochemistry and the
maximum entropy production principle. UMass
Lowell, Oct 2010. (pdf, 6 MB).
- Differences
and implications of maximizing entropy production locally versus
globally. Max Planck Institute for Biogeochemistry, Jena,
Germany, May 2010. (pdf, 1.1 MB)