FWS Endangered Species Data Analysis

Posted on Aug 1, 2022

The skills the authors demonstrated here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.


The earth is currently experiencing its 6th mass extinction. There are over 1,300 endangered animals today. During the past five, ninety-nine percent of all species that have ever lived have gone extinct. (Cho) Now, the loss of species is estimated at 100 to 1,000 times faster than the background rate of extinction and future predictions are even higher. (De Vos et al. , Lamkin et al.) This crisis can be linked to climate change, land use change, invasive species introduction, pollution, and resource exploitation. (Bleau)


The Endangered Species Act (ESA) was passed in 1973 to prevent the further loss of species. The ESA is administered by two agencies, the Fish and Wildlife Service (FWS) and the National Oceanic and Atmospheric Administration (NOAA). The FWS manages land and freshwater species while NOAA is responsible for marine species. (“Summary of the Endangered Species Act.”) Unfortunately, ESA protections and regulations have been weakened due to industrial and economic pressures. (Bleau)


Why Does This Matter?

The natural world is made up of intricate ecological systems that include organisms, the physical environment and the interactions between them. Ecosystems benefit humanity through provisioning, regulating, supporting and cultural services. These services support biodiversity and impact the global economy through: food, timber, biomass fuels, pharmaceuticals and natural fibers. (Daily) Although it is difficult to accurately put a cost on species loss, the global value of ecosystem services was estimated to average between $125 -145 trillion per year in 2011 according to Costanza et al. Humanity’s wellbeing is dependent on the functioning of ecosystems and the survival of countless species. (Daily)


 "Extinction, at its current rate, will ensure that financial markets will collapse, which will happen shortly before extinction of the human race, if no urgent action is taken,"

- Dr. Jill Atkins and Barry Atkins

Data Science Project


For this project, I will be focusing on the Fish and Wildlife Service's protection of terrestrial and freshwater species. My objective is to highlight the need for additional FWS funding and greater ESA protections. My target audience includes policy makers and the industries affected by this problem.

Here is a link to the GitHub repository.

Data Sourcing

I obtained data from the Fish and Wildlife Service (FWS) through their data explorer and public reports. This includes the FWS species (including species managed by FWS under the ESA) and recovery plan datasets as well as datasets compiled from the endangered and threatened species expenditure reports from 2017 and 2018. These reports included total spending for ESA protections by the FWS, Other Federal Organizations, States, and combined total funding for each species population. 

Data Analysis

Using the FWS Species dataset, I decided to look at the distribution of species by taxonomic group. The dataset included 10,316 rows of species across twenty species groups. Looking at figure 1.0, it is unclear what the total counts are for the least groups. Because the spread among species groups is so uneven, I decided to remove the Flowering Plants group outlier in figure 1.1 and look at just the last five groups in figure 1.2 below.



Figure 1.3 shows the distribution of species by status code. The majority of species in this initial dataset are not protected by the ESA (only endangered and threatened statuses qualify).  Table 1.0 includes the corresponding status codes for reference.



Figure 1.4 includes a bar chart of the species distribution by location. Domestic species accounted for 84.8 percent of the dataset while foreign made up 8.4 percent and the remainder included foreign and domestic species. Using the FWS Recovery Plan dataset, figure 1.5 shows the spread of listed species with recovery plans based on the eight FWS domestic regions. Figure 1.6 illustrates the number of recovery actions combined for each taxonomic group.



How do the top funded compare to the least funded?

The FWS Endangered and Threatened Species Expenditures Report from fiscal year 2017 and 2018 separates each listing by ESA regulations. Each expense entry can be identified as a species, subspecies, distinct population segment (DPS) or evolutionarily significant unit (ESU). The data does not include expenditures for unlisted species, litigation, salaries, operational costs or land acquisitions. According to the FWS, reporting includes "reasonably identifiable expenditures for the conservation of listed species."

The 2017 report includes 1,685  of the 1,772 domestically listed species at the time of reporting. The 2018 report includes 1,719  of the 1,912 domestically listed species at the time of reporting. For the 2017 data, figure 2.0 shows the distribution of combined funding for each taxonomic group. Based on the figure, there is a disproportionate amount of funding for the Fishes Group. It also appears that there is no funding for the lower five groups (Crustaceans, Conifers and Cycads, Ferns and Allies, Arachnids, and Lichens).



How does the budget compare from year-to-year?

Of the fifteen species groups included in the expenditures reports, the top five most-funded groups receive 95 percent of the total funding for that year. This combined to 1.14 billion dollars or 95.46 percent of total funding in 2017 and 1.2 billion dollars or 95.91 percent in 2018.

Figure 2.1 takes a closer look at these top five groups, with 2017 data represented in blue and 2018 data in orange. The top five groups are the same across these fiscal years with the Fishes Group receiving over 65 percent of the total funding (65.8 percent in 2017 and 66.44 percent in 2018).  Although Figure 1.0 showed that the Flowering Plants Group had the highest number of imperiled species, the group takes fifth place both years, accumulating 2.99 percent of funding in 2017  which decreased to 2.47 percent in 2018.




The least-funded groups also appear to be the same during those years. Because of the disparity in funding between groups, funding was not shown on the bar chart. Total funding for these five groups can be seen in figure 2.2, which appears in millions of dollars in contrast to figure 2.0 and 2.1. In 2017, the total funding sum of the least 5 species groups was 5.36 million dollars or 0.45 percent. The Crustaceans Group received 0.28 percent of total funding and the Lichens Group made up only 0.008 percent. Funding for these groups decreased in 2018 to 4.27 million dollars or 0.34 percent.  Crustaceans made up 0.26 percent of total funding and Lichens decreased to 0.003 percent.


Do the top funded have anything in common?

Now that we've seen the combined groups, what about the individual populations? Figure 2.3 and 2.5 show the top fifteen species populations for their respective years. But the fifteen only account for eight species in 2017 and seven species in 2018. Figures 2.4 and 2.6 show the counts of duplicate species listed in the top-funded entries. In figure 2.4, the Chinook Salmon is listed six times, with the Steelhead listed three times. Of the eight species, all but one are in the Fishes Group. The Chinook Salmon is also listed six times in 2018 and the Steelhead listed is four times. Again, all but one population are part of the Fishes Group.



What Agencies provide the most funding for ESA Species?

The FWS Expenditures data separates the funding for each species population into four columns: FWS funding, Other Federal funding (including all other federal agencies), State funding, and the Total funding for that year. Figure 3.0 displays the relationship between two of the funding columns for 2018: Other Federal and Total Funding. There is a clear linear relationship between these two columns. This was expected since the Total Funding combines the other three columns. But looking at figure 3.1, the same expected relationship is unclear. Figure 3.1 shows the relationship between FWS Funding and Total Funding for that same year.

The FWS is one of two administering agencies for the ESA and is in charge of protections for terrestrial and freshwater species. And yet, in the most recent public expenditures report the largest funding contribution to endangered and threatened species comes from outside the FWS.



Key Takeaways

  • There was not a meaningful change in ESA funding from year to year
  • The distribution of funding for ESA protections is extremely uneven
  • The Fishes Group receives over 65% of all funding and the least 5 groups receive less than 1% combined - if this is an appropriate allocation of resources, how are other species groups expected to recover without appropriate funding?
  • 93.33 percent of the 15 top-funded species populations are in the Fishes Group.
  • The majority of funding for ESA species comes from Other Federal Organizations, not the FWS - one of the main administering agencies

Future ideas

During my analysis, I wanted to merge the recovery plan and expenditures data frames to compare the number of recovery actions with funding. Unfortunately, after performing the join, there was not enough data for a meaningful analysis. In the future, I would like to investigate this further and see what error could be causing this.

I would also like to expand the scope of the project to include more expenditures reports and look for trends in the data over time. Additionally, I would like to work with the FWS Data Explorer Petition dataset that includes species petitioned for listing as well as the petition date. This data would require excessive cleaning because the formatting of the document has changed over time.



Bleau, Katie. “Biodiversity on the Brink: The Consequences of a Weakened Endangered Species Act.” Yale Environment Review, 23 Jan. 2020, https://environment-review.yale.edu/biodiversity-brink-consequences-weakened-endangered-species-act.
Cho, Renee. “Why Endangered Species Matter.” State of the Planet, 3 Apr. 2019, https://news.climate.columbia.edu/2019/03/26/endangered-species-matter/#:~:text=%E2%80%9CEven%20if%20it's%20not%20a,that%20ecosystem%20to%20stop%20working.%E2%80%9D.
Costanza, Robert, et al. “Changes in the Global Value of Ecosystem Services.” Global Environmental Change, vol. 26, May 2014, pp. 152–158., https://doi.org/10.1016/j.gloenvcha.2014.04.002.
Daily, Gretchen C. "Introduction: what are ecosystem services." Nature’s services: Societal dependence on natural ecosystems 1.1 (1997).
“Data Services.” ECOS, https://ecos.fws.gov/ecp/services.
De Vos, Jurriaan M., et al. “Estimating the Normal Background Rate of Species Extinction.” Conservation Biology, vol. 29, no. 2, 26 Aug. 2014, pp. 452–462., https://doi.org/10.1111/cobi.12380.
Lamkin, Megan, and Arnold I. Miller. “On the Challenge of Comparing Contemporary and Deep-Time Biological-Extinction Rates.” BioScience, vol. 66, no. 9, 17 Aug. 2016, pp. 785–789., https://doi.org/10.1093/biosci/biw088.
Lien, Aaron M., et al. “Opportunities and Barriers for Endangered Species Conservation Using Payments for Ecosystem Services.” Biological Conservation, vol. 232, Apr. 2019, pp. 74–82., https://doi.org/10.1016/j.biocon.2019.01.017.
“Summary of the Endangered Species Act.” EPA, Environmental Protection Agency, 28
Sept. 2021, https://www.epa.gov/laws-regulations/summary-endangered-species-act.
U.S. Fish & Wildlife Service Federal and State Endangered and Threatened Species Expenditures FY 2017. https://www.fws.gov/sites/default/files/documents/endangered-species-expenditures-report-fiscal-year-2017.pdf.
U.S. Fish & Wildlife Service Federal and State Endangered and Threatened Species Expenditures FY 2018. https://www.fws.gov/sites/default/files/documents/endangered-species-expenditures-report-fiscal-year-2018.pdf.
“Why Species Extinction Matters to Business.” Investec, https://www.investec.com/en_za/focus/beyond-wealth/to-bee-or-not-to-bee-species-extinction.html.


About Author

Sarah Adams

I have a background in Sustainability and Natural Resources Management and have experience working in conservation research with government and non-government organizations. I am currently a student at the NYC Data Science Academy and am interested in gaining...
View all posts by Sarah Adams >

Related Articles

Leave a Comment

No comments found.

View Posts by Categories

Our Recent Popular Posts

View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay gbm Get Hired ggplot2 googleVis Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI