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.

文件清单
一次性获取全部文件：AllFiles.zip
## 数据文件
NegBinMallardData.txt、BBSLand.csv、betasFIXEDC.csv、betasFIXEDP.csv、NegBinBeta.csv、NegBinCovBeta.csv、ObsCounts.csv
## Limdep可执行脚本文件
NegBinMallardRegression.lim
## Matlab脚本文件
BBSmax.m、CalculateMuClump.m、CalculateXprime.m、CalculateXrSTAR.m、CalculateXrUniform.m、FindBeta0.m、FindRestStar.m、WriteBBSmaxOut.m

## 文件说明
AllFiles.zip：将下述所有文件打包压缩所得。
NegBinMallardData.txt：为本论文报告的负二项回归（negative binomial regression）结果提供输入数据，作为Limdep文件NegBinMallardRegression.lim的输入。该文件为逗号分隔格式，包含53列与2714行数据，列对应下述变量，每一行代表一组观测值，即唯一的调查路线-站点-年份组合。—— 表格：详见附件文件。—— 若需验证文件是否下载完整，请将列总和与下述数值比对：—— 表格：详见附件文件。
BBSLand.csv：包含美国加利福尼亚州中央谷地所有BBS调查路线站点周边各类土地利用类型的占比数据。该文件为逗号分隔值（CSV）格式，包含10列与819行数据，列对应下述变量，每一行代表加州中央谷地区的单个路线站点。—— 表格：详见附件文件。—— 若需验证文件是否下载完整，请将列总和与下述数值比对：—— 表格：详见附件文件。
betasFIXEDC.csv：包含从β的多元正态抽样分布中抽取的500个样本，仅纳入核心土地利用变量（果园、果园平方、湿地、湿地平方、水稻田、水稻田平方以及湿地与水稻田的交互项），该分布基于NegBinMallardData.txt数据与NegBinMallardRegression.lim文件估算得到。利用本文件可复现论文中报告的结果。
betasFIXEDP.csv：包含从β的多元正态抽样分布中抽取的500个样本，纳入全部土地利用变量，该分布基于NegBinMallardData.txt数据与NegBinMallardRegression.lim文件估算得到。利用本文件可复现论文中报告的结果。
NegBinBeta.csv：包含基于NegBinMallardData.txt数据与NegBinMallardRegression.lim文件运行负二项回归得到的β估计值。
NegBinCovBeta.csv：包含基于NegBinMallardData.txt数据与NegBinMallardRegression.lim文件运行负二项回归得到的β抽样分布估计方差-协方差矩阵。
ObsCounts.csv：包含1997年至2001年间加州中央谷地所有BBS调查路线站点观测到的绿头鸭（mallards）数量。
NegBinMallardRegression.lim：用于执行负二项计数回归模型的Limdep脚本文件。
BBSmax.m：用于执行优化模型与对比情景的核心Matlab脚本文件，其余后缀为.m的文件均为BBSmax.m的子例程。

## 复现步骤
若需复现论文中报告的结果，请遵循以下步骤：
1. 将所有文件保存至同一目录下。
2. 在"NegBinMallardRegression.lim""BBSmax.m"与"WriteBBSmaxOut.m"文件中，将所有出现的[directory]替换为你保存文件的目录名称。
3. 使用Limdep 7.0版本运行"NegBinMallardRegression.lim"文件。注意：仅当你需要验证论文中报告的回归结果，或尝试修改回归模型版本时，才需要执行本步骤。
4. 使用Matlab 6.5版本运行"BBSmax.m"文件，将生成以下输出文件：
BBSmaxOut.txt：包含模型的主要结果。论文中表4报告的汇总结果位于文件顶部，汇总结果下方有四列辅助结果：
(1) "rs"：路线-站点编号；
(2) "conag"：该路线-站点可从农业用地转换为湿地的土地面积；
(3) "rSTAR"：该站点最优的生态修复规模；
(4) "muSTAR"：若在该站点完成最优规模的生态修复后，预期观测到的绿头鸭平均数量。