DOI: 10.5061/dryad.pvmcvdntm
title: Redesigning Modern Portfolio Theory to Improve Spatial Recovery Planning for Oregon Coast (OC) Coho Salmon

description: Oregon Coast (OC) coho salmon (Oncorhynchus kisutch) are a federally
 listed threatened species under the Endangered Species Act. It is integral
 to conserve this species due to their ecological importance in nutrient
 cycling and cultural significance to Indigenous peoples. The combination
 of their threatened status and significance creates a sense of urgency for
 conservation organizations, like the Wild Salmon Center, to efficiently
 allocate their budgets. In this project we redesigned Modern Portfolio
 Theory (MPT) to optimize habitat restoration spending. MPT is
 traditionally used in finance to inform portfolio managers what the risks
 and returns are of investing in different portfolios of assets. In our
 redesigned application, the 21 populations of OC coho salmon are treated
 as assets, with the increase of salmon abundance and variance directly
 relating to the amount of money allocated to conserve each population.
 More specifically, we applied our new approach to mitigating barriers that
 inhibit salmon from traveling back to their natal streams. To do this, we
 gathered and collected data on fish passage barriers, average project
 costs to remove barriers, and estimated how removing barriers would affect
 the abundance of coho salmon. We analyzed portfolios under multiple
 budgets and scenarios that prioritize conservation spending in watersheds
 important to Indigenous peoples. This endogenous application is the first
 of its kind in the conservation field and can be applied to a multitude of
 species or restoration actions beyond OC coho salmon and barrier
 mitigation. 
description: Adult Coho Salmon Spawner data: This dataset was
 given to us by our client, the Wild Salmon Center, but was sourced through
 the Oregon Adult Salmonid Inventory & Sampling Project run by the
 Oregon Department of Fish & Widlife (ODFW).  
 National Hydrography Reaches: All files were given to us by our
 client the Wild Salmon Center. Each file were given and downloaded as .shp
 files for each individual population in the OC coho Salmon Evolutionary
 Significant Unit (ESU). These files were created specifically for the Wild
 Salmon Center and NOAA by Terrainworks using USGS' National
 Hydrography Dataset. Many variables are outputs of different climate
 models ran by Terrainworks using the variables within USGS' orginal
 hydrography dataset. These .shp files were used to better understand
 stream habitat within the ESU. Population Boundaries:
 All files were given to us by our client the Wild Salmon Center as a .shp
 file with all populations included. Each individual population was then
 exported to its own .shp file. All population boundaries were used to clip
 the reach data and barrier data in ArcGIS Pro to only look at ESU specific
 attributes. Oregon Fish Passage Barriers: This
 dataset was sourced from ODFW's Fish Barrier Data basin. The barrer
 data for the state of Oregon was downloaded as a layer package. For our
 project, the layer package was clipped by each individual population
 boundary .shp files. This allowed us to isolate the barriers that are
 within the ESU. Cost Data: The cost data was
 collected by downloading a .xlsx file from the Oregon Watershed
 Restoration Inventory and it managed by the the Oregon Watershed
 Enhancement Board. The inventory contains information on self reported
 restoration projects that have taken place in Oregon from 1995 - 2022. The
 file was then filtered by project type. All project types that involved
 bridges, culverts, dams, waterfalls, tide gates, fords, and cascades were
 used in our analysis. Each project type was given its own tab in the .xlsx
 file to calculate an average cost for each barrier type. The average cost
 was then applied to our barrier data where each barrier type received
 it's estimated cost to mitgate. This data informed our R model to
 estimate the impacts of barrier mitgation on adult salmon population
 returns.   
description: # Redesigning Modern Portfolio Theory to Improve Spatial Recovery Planning
 for Oregon Coast (OC) Coho Salmon
 [https://doi.org/10.5061/dryad.pvmcvdntm](https://doi.org/10.5061/dryad.pvmcvdntm) In this project, we redesigned Modern Portfolio Theory as an endogenous framework. To do this, we developed a model, based on the Beverton-Holt population model, in R to calculate the impact of conservation investment on OC Coho Salmon spawner abundance in the Pacific Northwest. Our model considered barrier impact data and cost data to estimate how many fish would return to the population for every dollar spent on conservation projects, given a budget constraint, and aggregated those results to the ESU level. This resulted in the total ESU fish abundance and total ESU variance calculated for each population, which was visualized along an efficiency frontier. This frontier can inform conservation managers how to allocate funds to maximize salmon returns for a given level of variance. The code for our model can be found in our GitHub repository.  To replicate our GIS analysis, refer to the GIS_readme.docx file, which outlines the steps to implement our barrier analysis using ModelBuilder in ArcGIS Pro. ## Files * Adult OC Coho Abundance * OC Coho Abundance.xlsx * Reaches * reach_alsea.shp * reach_coos.shp * reach_Coquille.shp * reach_Necanicum.shp * reach_nehl.shp * reach_NorthUmpqua.shp * reach_Salmon.shp * reach_siletz.shp * reach_Siu1.shp * reach_Siu3.shp * reach_Siu4.shp * reach_SouthUmpqua * reach_Umpqua * reach_Wilson * reach_Yaquina * reach_siul.gdb * reach_siul.shp * Population Boundaries * SAP_Watersheds.shp * alesa_population.shp * beaver_population.shp * coos_population.shp * coquille_population.shp * floras_population.shp * lower_ump_population.shp * mid_ump_population.shp * necanicum_population.shp * nehalem_population.shp * nestucca_population.shp * north_ump_population.shp * salmon_population.shp * siletz_population.shp * siltcoos_population.shp * siuslaw_population.shp * sixes_population.shp * south_ump_population.shp * tenmile_population.shp * tillamook_population.shp * yaquina_population.shp * Oregon Fish Passage Barriers * ofpbds_pt.lpk * Cost * cost_data.xlsx ### **Adult OC Coho Abundance** ###### Sharing/Access information Data was derived from the following sources: * This dataset was given to us by our client, the Wild Salmon Center, but was sourced through the Oregon Adult Salmonid Inventory & Sampling Project run by the Oregon Department of Fish & Wildlife (ODFW). * Oregon Department of Fish and Wildlife (ODFW). 2019. *Oregon Adult Salmonid Inventory & Sampling Project (OASIS)*. ODFW, Salem, Oregon, USA. [online] URL: [https://odfw-oasis.forestry.oregonstate.edu/coho-salmon-data](https://odfw-oasis.forestry.oregonstate.edu/coho-salmon-data) ###### Data Specific Information: OC Coho Abundance.xlsx * Rows: 31 * Columns: 22 * Variable List: * year: year of salmon return from 1994 - 2019 * alsea: salmon returner abundance for the population Alsea * beaver: salmon returner abundance for the population Alsea * coos: salmon returner abundance for the population Coos * coquille: salmon returner abundance for the population Coquille * floras: salmon returner abundance for the population Floras * Lower Umpqua: salmon returner abundance for the population Lower Umpqua * Middle Umpqua: salmon returner abundance for the population Middle Umpqua * Necanicum: salmon returner abundance for the population Necanicum * Nehalem: salmon returner abundance for the population Nehalem * Salmon: salmon returner abundance for the population Salmon * Siletz: salmon returner abundance for the population Siletz * Siltcoos: salmon returner abundance for the population Siltcoos * Siuslaw: salmon returner abundance for the population Siuslaw * Sixes: salmon returner abundance for the population Alsea * South Umpqua: salmon returner abundance for the population South Umpqua * Tahkenitch: salmon returner abundance for the population Alsea * Tenmile: salmon returner abundance for the population Tenmile * Tillamook: salmon returner abundance for the population Tillamook * Yaquina: salmon returner abundance for the population Yaquina ###### Code/Software This is data was used for the bulk of our analysis that can be found in the link to our GitHub repository.  Instrument or software needed to interpret the data: RStudio or Microsoft Excel ### **Reaches** ###### Sharing/Access information Links to other publicly accessible locations of the data: * [https://terrainworks.com/about-terrainworks](https://terrainworks.com/about-terrainworks) Data was derived from the following sources: * All files were given to us by our client, the Wild Salmon Center. This dataset was also created for the Wild Salmon Center by Terrainworks with added variables using the USGS National Hydrography Dataset for each individual shapefile.  * U.S. Geological Survey (2019) National Hydrography Dataset (ver. USGS National Hydrography Dataset Best Resolution (NHD) for Hydrologic Unit (HU) 8, accessed March 1, 2023 at URL [https://www.usgs.gov/national-hydrography/access-national-hydrography-products](https://www.usgs.gov/national-hydrography/access-national-hydrography-products) * All files that are denoted under 'Reach Data' all are publicly available to download from the above link. * Master Attribute table that can be applied to all .shp files can be found here: [https://www.netmaptools.org/Pages/NetMapHelp/master_attribute_list.htm?mw=MzQ2&st=MQ==&sct=MA==&ms=AAAAAAA= ](https://www.netmaptools.org/Pages/NetMapHelp/master_attribute_list.htm?mw=MzQ2&st=MQ==&sct=MA==&ms=AAAAAAA=) ###### Data Specific Information: Not all 74 variables (columns) listed in files were used. More detailed metadata describing all collumns can be found in the 'Sharing/Access Information' section above. The project only used two variables `ID: Stream` and `IDSTRM_ORDER: Stream Order (Strahler)`for files described below: reach_Alsea.shp * Rows: 77,803 reach_coos.shp * Rows: 64,674 reach_Coquille.shp * Rows: 130,970 reach_Necanicum.shp * Rows: 16,760 reach_nehl.shp * Rows: 106,913 reach_NorthUmpqua.shp * Rows: 100,234 reach_Salmon.shp * Rows: 5,846 ###### Data - Specific Information: reach_siletz.shp * Rows: 29,427 reach_siltcoos.shp * Rows: 29,437 reach_siltcoos.shp * Rows: 16,760 reach_SouthUmpqua.shp * Rows: 167,119 reach_Umpqua.shp * Rows: 169,416 reach_Wilson.shp * Rows: 169,416 reach_Yaquina.shp * Rows: 23,779 reach_siul.gdb * Rows: 77,880 ###### ***Code/Software*** This is data was used to generate our barrier_data output in ArcGIS Pro's Modelbuilder and exported as .csv files. The .csv files were used simultaneously with the abundance data in our model in RStudio. All code to run analysis are located in our GitHub repository. Instrument or software needed to interpret the data: ArcGIS Pro 3.3 or earlier verisons ### Population Boundaries ###### Sharing/Access information Data was derived from the following sources: * This dataset was given to us by our client, the Wild Salmon Center.   * Wild Salmon Center, Strategic Action Plan - OC Coho Salmon Watershed. Coast Coho Partnership, Downloaded September 2023.  ###### Data Specific Information: The listed shape files share the same characteristics as further described below: * SAP_Watersheds.shp * alsea_populations.shp * beaver_population.shp * coos_population.shp * coquille_population.shp * floras_population.shp * lower_ump_population.shp * mid_ump_population.shp * necanicum_population.shp * nehalem_population.shp * nestucca_population.shp * north_ump_population.shp * salmon_population.shp * siletz_population.shp * siltcoos_population.shp * siuslaw_population.shp * sixes_population.shp * south_ump_population.shp * tenmile_population.shp * tillamook_population.shp * yaquina_population.shp ##### Descritpion: Columns: 7 * Variables: * FID: field for all populations, default is 0.  * Shape: Type of data * MIDLEVEL_G: Location in the ESU  * Mid - Coast * Mid - South Coast * Umpqua * North Coast * Lakes * POPULATION: Population Name  * Shape_Leng: Shape Length of population border (M) * Shape_Area: Shape Area of population (M) * sharpes: Unknown ###### Code/Software This is data was used to generate our barrier_data output in ArcGIS Pro's Modelbuilder by using the population outlines to clip the barrier data to each population. The .csv files were used simultaneously with the abundance data in our model in RStudio. In addition, the polygons were used to generate visualizations using ArcGIS Pro. The .csv files were used simultaneously with the abundance data in our model in RStudio. All code to run analysis are located in our GitHub repository. Instrument or software needed to interpret the data: ArcGIS Pro 3.3 or earlier versions. ### **Oregon Fish Passage Barriers** ###### Sharing/Access information Links to other publicly accessible locations of the data: * Data Basin - Oregon Fish Passage Barriers uploaded by Conservation Biology Institute * [https://databasin.org/datasets/668516a57c0c4accb2d478716013f189/](https://databasin.org/datasets/668516a57c0c4accb2d478716013f189/) * Detailed Metadata can be found in the 'Attributes Tab' Data was derived from the following sources: * This dataset was given to us by our client, the Wild Salmon Center, but was sourced through ODFW's Fish Barrier Data collected through their Natural Resources Information Management Program.  * Oregon Department of Fish and Wildlife. (2024). Oregon Fish Passage Barrier Prioritization Database. Retrieved from [https://nrimp.dfw.state.or.us/nrimp/default.aspx?pn=fishbarrierdata](https://nrimp.dfw.state.or.us/nrimp/default.aspx?pn=fishbarrierdata) ###### Data Specific Information: ofpdbds_pt.lpk * Rows: 40,118 * Columns: 72 * Variables: * For this project, all 72 variables were not used. Provided are the variables that were relevant to the project. More detailed metadata can be found in the 'Sharing/Access Information' section above. * fpbFtrTy: The type of fish passage barrier  * fpbFPasSta: Passability status for each barrier  * Unknown * Blocked * Partial  * Passable * UnkAnad, this variable is treated as 'Unknown' ###### Code/Software This is data was used to generate our barrier_data output in ArcGIS Pro's Modelbuilder by mapping the location of each fish passage barrier to a specific population and exported as .csv files. The .csv files were used simultaneously with the abundance data in our model in RStudio. In addition, the polygons were used to generate visualizations using ArcGIS Pro. The .csv files were used simultaneously with the abundance data in our model in RStudio. All code to run analysis are located in our GitHub repository. Instrument or software needed to interpret the data: ArcGIS Pro 3.3 or earlier versions. ### **Cost** ###### Sharing/Access information Data was derived from the following sources: * This dataset was downloaded from the Oregon Watershed Restoration Inventory managed by the Oregon Watershed Enhancement Board (OWEB). The OWEB has tabular data of the inventory which was downloaded as an excel file.  * Oregon Explorer (2022). Enhancing Watersheds in Oregon Database. [OWRI Excel Spreadsheet]. Retrieved from [https://oregonexplorer.info/content/enhancing-watersheds-oregon?topic=56&ptopic=38#TheOWRIDatabaseandGISdata](https://oregonexplorer.info/content/enhancing-watersheds-oregon?topic=56&ptopic=38#TheOWRIDatabaseandGISdata) * Detailed Metadata can be found when 'OWRI Data Dictionary' is downloaded from the above link. ###### Data - Specific Information: cost_data.xlsx * Rows: 19,743 * Columns: 75 * Tabs: 15 * Variables:  * Provided are the variables that were relevant to the project. More detailed metadata can be found in the 'Sharing/Access Information' section above. * ProjectID: Unique identifier, database record number auto-generated by SQL Server * ProjName: Project name * TotalCash: Total cash cost of project ($) * StartYear: Project start year (1995 - 2022) * CompleteYear: Project completation year (1995 - 2022) * drvdProjDesc: Brief description of project activities –this is not completed by the respondent.  It is populated after data entry and QA/QC as time permits.