On Wed, 27 Apr 2016, Rich Shepard wrote:
I've looked for the source of the problem but have not seen it. A hint as
to why the figures are not displayed when the multicol package is used will
be much appreciated.
Brief example attached (with separate figure so you can include it more
easily).
Rich
#LyX 2.1 created this file. For more info see http://www.lyx.org/
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\begin_body
\begin_layout Title
Regulatory Science: Mathematical vs.
Statistical Models
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Copyright
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textcopyright
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2016 Applied Ecosystem Services, Inc.
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\begin_layout Subtitle
Environmental Decision Making Under Conditions of Uncertainty
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\begin_layout Author
Richard B.
Shepard, PhD
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Applied Ecosystem Services, Inc.
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\begin_layout Date
April 24, 2016
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\begin_layout Abstract
Natural resource companies do not object to environmental regulations that
are consistent and support predictability.
Consistency and predictability are critical for decision making under condition
s of uncertainty.
Natural ecosystems are inherently variable across a broad range of temporal
and spatial scales; climate change, drought, and societal desires for sustainab
ility make people more aware of this variability.
The science used for development and enforcement of environmental regulations
has not kept pace with developments in ecological theory and the analytical
tools capable of describing, characterizing, classifying, and predicting
natural ecosystems as well as distinguishing natural variability from anthropog
enic changes.
\end_layout
\begin_layout Abstract
Because natural resource industries (agriculture, energy, mining) provide
the base for all economic and societal activities it is critical that environme
ntal statutes and regulations be regularly updated to use the most technically
sound and legally defensible scientific knowledge and tools.
\end_layout
\begin_layout Abstract
Mathematical models were the tools of choice when environmental statutes
and regulations were introduced, perhaps because they were successfully
applied to static components of the built environment such as buildings
and bridges.
While their limitations for highly variable natural ecosystems were accepted
then, there is now no benefit to not replacing them with statistical models.
\end_layout
\begin_layout Abstract
This paper describes limitations in policy and regulatory decision-making
based on mathematical models and explains how the appropriate statistical
models avoid the subjectivity and rigidity of the former.
Changing the basis of determining and justifying policy and environmental
regulations is consistent with the concepts of regulatory science applied
to human health.
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begin{multicols}{2}
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\begin_layout Part*
Introduction
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\begin_layout Standard
Natural resource companies do not object to environmental regulations that
are consistent and predictable.
Consistency and predictability are critical for decision making under condition
s of uncertainty.
Natural ecosystems are inherently variable across a broad range of temporal
and spatial scales; climate change, drought, and societal desires for sustainab
ility make people more aware of this variability.
The science used for development and enforcement of environmental regulations
has not kept pace with developments in ecological theory and analytical
tools capable of describing, characterizing, classifying, and predicting
natural ecosystems and distinguishing natural variability from anthropogenic
changes.
\end_layout
\begin_layout Subsection*
Pit Lake Hydrodynamic and Water Quality Model (PITLAKQ)
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PITLAKQ couples the models CE-QUAL-W2 and PHREEQC and adds new functionality
to account for the pit lake requirements.
It includes the most important processes in pit lakes.
For example, several sources of acidity such as erosion or release from
submerged sediments and spatially distributed groundwater inflow help to
better represent pit lake conditions.
Furthermore, PITLAKQ can account for the effects of water treatment on
water quality.
The two-dimensional model setup with one vertical and one horizontal dimension
allows having sinks and sources with defined spatial locations.
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PITLAKQ models hydrodynamics, transport, heat exchange, wind impact, ice
cover, tributary inflow, atmospheric exchanges of O
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2
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and CO
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2
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, precipitation, evaporation, groundwater exchange, groundwater flow and
transport, erosion (both mass transport and water quality impacts), algae
and nutrients, chemical lake reactions, mineral precipitation, sediment
release, deliberate treatment (on defined spatial and temporal schedules),
alkalinity of sinks and sources, coupling of all processes, and user process
additions and modifications (Figure
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reference "fig: PITLAKQ"
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).
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The physical and chemical processes modeled by PITLAKQ.
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\begin_layout Part*
Conclusions
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Policies and regulations can be supported by demonstrably best available
science by taking advantage of current knowledge in environmental data
analytical methods and our understanding of ecological theory applicable
to all natural ecosystems.
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bibfiles "/home/rshepard/documents/jabrefdb"
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