Supplement 1. Data files, Limdep executable file, and Matlab executable files.

File List
All files at once
AllFiles.zip
Data files
NegBinMallardData.txt

BBSLand.csv

betasFIXEDC.csv

betasFIXEDP.csv

NegBinBeta.csv

NegBinCovBeta.csv

ObsCounts.csv
Limdep executable
file
NegBinMallardRegression.lim
Matlab executable files
BBSmax.m

CalculateMuClump.m

CalculateXprime.m

CalculateXrSTAR.m

CalculateXrUniform.m

FindBeta0.m

FindRestStar.m

WriteBBSmaxOut.m

DescriptionAllFiles.zip
- Contains all of the following files zipped together.
NegBinMallardData.txt
- Contains input data for the negative binomial regression results reported
in the paper.  Used as input to the Limdep file NegBinMallardRegression.lim.
The file is comma delimited and
contains 53 columns and 2714 rows.  The columns correspond to the variables
listed below, and each row corresponds to an observation, i.e., a unique route
stop-year combination.

-- TABLE: Please see in attached file. --

To make sure the file was downloaded properly,
compare the column sums to the following figures:

-- TABLE: Please see in attached file. --

BBSLand.csv - Contains
the amount of each land use type near all BBS route-stops in the Central Valley
of California.

The file is comma delimited and
contains 10 columns and 819 rows.  The columns correspond to the variables
listed below, and each row corresponds to an individual route-stop in the
Central Valley of California.

-- TABLE: Please see in attached file. --

To make sure the file was downloaded properly,
compare the column sums to the following figures:

-- TABLE: Please see in attached file. --

betasFIXEDC.csv
- Contains 500 draws from the multivariate normal sampling distribution of beta,
including only the most important land use variables (orchards, orchards^2,
wetlands, wetlands^2, rice, rice^2, and wetlands*rice), as estimated using the
data in NegBinMallardData.txt and the Limdep file NegBinMallardRegression.lim. 
The results presented in the paper can be reproduced using this file.
betasFIXEDP.csv
- Contains 500 draws from the multivariate normal sampling distribution of beta,
including all land use variables, as estimated using the data in NegBinMallardData.txt
and the Limdep file NegBinMallardRegression.lim.  The results presented
in the paper can be reproduced using this file.
NegBinBeta.csv -
Contains the estimated values for beta that result from using the data in NegBinMallardData.txt
and the Limdep file NegBinMallardRegression.lim.
NegBinCovBeta.csv
- Contains the estimated variance-covariance matrix for the sampling distribution
of beta that results from using the data in NegBinMallardData.txt and the Limdep
file NegBinMallardRegression.lim.
ObsCounts.csv -
Contains the observed counts of mallards at all BBS route-stops in the Central
Valley of California between 1997-2001.
NegBinMallardRegression.lim
- The Limdep file used to execute the negative binomial count regression model.
BBSmax.m - The main
Matlab file used to execute the optimization model and comparison scenarios.
All remaining *.m files
are subroutines of BBSmax.m.

Instructions
To reproduce the results
presented in the paper, follow these steps:
1.  Save all files in a single
directory.

2.  In the "NegBinMallardRegression.lim,"
"BBSmax.m," and "WriteBBSmaxOut.m" files, replace all occurrences of [directory]
with the name of the directory in which you saved the files.

3.  Execute the "NegBinMallardRegression.lim"
file using Limdep version 7.0.  Note: This step is only needed if you
want to verify the regression results reported in the paper, or to try alternative
versions of the regression model.

4.  Execute the "BBSmax.m"
file using Matlab version 6.5.  This will produce the following output
file:

BBSmaxOut.txt
- will contain the main results from the model.  The summary results,
which are reported in the paper in Table 4, are at the top of the file. 
Secondary results are given in four columns below the summary results. 
The four columns contain: (1) "rs," the route-stop number, (2) "conag," the
amount of land that could be converted from agriculture to wetlands at the
route-stop, (2) "rSTAR," the optimal amount of restoration to undertake at
the route stop, and (4) "muSTAR," the average number of mallards expected
to be counted at the route stop if the optimal amount of restoration is completed
there.