As I transitioned from academia to a government agency, I noticed some similarities between the two. In both places I have worked with an incredible lab/team that are always willing to help figure out why some R code isn’t working or review a paper. Also, in both places I have been constantly learning new things and testing my skills. On the other hand, I have noticed many differences between my experience as a graduate student at the University of Florida and as a fellow with the Marine Reserves Program at the Oregon Department of Fish and Wildlife (ODFW).

One major difference between the two places is how I speak about my research. As a student I was allowed to be an advocate. I could speak about wanting to expand protected areas and conserve all species to my heart’s content. It was practically expected of me to have these strong opinions about conservation and discuss them openly. Working for a state agency, the expectation is exactly the opposite. I now must be impartial in my word choice both in person and in writing. Though I work for the Marine Reserves Program, I am not an advocate for marine reserves. I am simply studying how the marine reserves may have impacted communities and presenting these results in a straightforward manner. If I take a strong position on marine reserves, the public may lose trust in my ability to conduct unbiased research. If the public loses this trust, they are less likely to support the agency and follow agency regulations. This trust is crucial, but also fragile.

Another difference between academia and government is the type of research being conducted. In academia, the focus is more on what is interesting and would advance the field. In government, the focus is on achieving the mandate. Therefore, our research options are limited and must be strictly applied research rather than theoretical. We also must be transparent about our research and where funds are going since we are a largely tax-funded agency. This is another important component of building that trust.

Government agencies typically work on projects with larger scale timeframes than what graduate students are involved in. While long-term monitoring projects are typically considered boring and unpublishable in academia, these types of data are the bread and butter of ODFW reports. We are constantly monitoring fish stocks, commercial fishing pressure, license sales, oceanographic conditions, etc. Most of these data are written up in annual reports and used to inform management. While long-term monitoring is generally not considered “sexy” research, it is extremely useful to have these historical datasets to understand how things have changed over time. I am using many of these historical datasets in my current work looking at how marine reserves may have impacted factors like recreational anglers’ Catch Per Unit Effort (CPUE), commercial fishing employment, and coastal communities’ socioeconomic conditions.

Lastly, one of the best changes I experienced when going from academia to government was an increased focus on having a work-life balance. In graduate school I was applauded for staying in the lab late and working on weekends. In my current position, I am expected to only be working 40-hour weeks and taking weekends off. We spend time in our weekly meetings discussing general life announcements that aren’t marine reserves related in the slightest. We even share good places to hike, mountain bike, snowshoe, camp, etc. because we know we will all have time to do these fun hobbies.

These are some of the major differences I observed in my life going from academia to government. These are solely based on my personal experience and are likely not applicable to everyone that made this transition.

We’ve almost made it! The year 2020 is just about to end and 2021 is right around the corner. Though many issues that were highlighted in 2020 won’t be going away in 2021 and need to continue to be addressed, there are some things to look forward to. Just this month, healthcare workers started receiving the first round of the COVID-19 vaccine. As more and more people get vaccinated, we will hopefully see the end of strict quarantine measures in the near future. Maybe we will even be able to spend the 2021 holidays with family without a mask in sight! 2021 will also bring a new administration with climate change as a top priority, which will likely influence ocean policies and management. So, while 2020 was an important year and we should not forget what we learned in it, here’s to hoping that 2021 doesn’t throw us any detrimental curveballs.

Now that you’re up to date on some of what’s happening in the USA, let me update you on what I’ve been working on. In my last blog post I outlined how I’m using the Oregon Department of Fish and Wildlife’s (ODFW) daily angling license sale data to determine if marine reserves have influenced recreational fishing. Since people are no longer able to fish in the marine reserve sites, we might expect this to result in fewer licenses purchased in towns near the reserves post implementation. This might also be observed by an increase in licenses purchased in towns further from the reserves.

However, whether or not people decide to go fishing is just one aspect of measuring a potential reserve effect on recreational fishing communities. For those that do decide to go fishing, how much they catch and over what time period is another crucial component. This metric is referred to as Catch Per Unit Effort (CPUE). For our analysis, we calculate CPUE by dividing the total number of fish caught by the number of anglers aboard the vessel and by the number of hours fished. This creates a standardized metric whereby we can compare fishing trips with varying numbers of anglers and hours fished. Specifically, we can compare CPUE reported at docks near marine reserves pre- and post-marine reserve implementation. We might expect that marine reserve site closures could increase effort, thereby decreasing CPUE, by forcing anglers to spend more time traveling further to avoid the reserves. On the other hand, we might expect site closures to increase catch, thereby increasing CPUE, due to spillover effects whereby a greater abundance of fish inside the reserves leads to a greater abundance of fish outside the reserves.

Lucky for me, ODFW has been collecting the information I need to calculate CPUE through the Ocean Recreational Boat Survey (ORBS).  This is an annual survey of Oregon’s marine recreational fishery that estimates both catch and effort at the top 10-11 ocean access points. This survey was first developed in 1979, but the original focus was on generating accurate salmon estimates in a timely manner. The ORBS survey has since expanded and provides valuable data on stock abundance and health for many species, which is used for management purposes.

By looking at both daily angling license sales as well as CPUE on charter boats, we should be able to uncover any potential marine reserve effects on the recreational fishing community. Of course, there are many covariates to take into account that could influence CPUE, such as catch regulations and environmental variables. I won’t dive into this right now, but maybe another blog post detailing the difficulties of finding downloadable historical buoy data without huge gaps is in order. Signing off for now, happy New Year!

Amid the chaotic nature of this summer with COVID-19, protests, wildfires, and an upcoming election, I have managed to seamlessly transition into my second year as a Natural Resource Policy Fellow with the Oregon Department of Fish and Wildlife (ODFW). Over the next year, I will continue to evaluate the impacts of marine reserves on coastal communities, communities of interest (e.g. commercial fishers), and ocean users (e.g. tourists).

Over the last year working on this mandate I have discovered that there are no perfect data sources to answer this question. Data often have errors associated with insufficient sampling in small communities, issues with changes in methodology, or are simply not available for the years or communities of interest. However, we can’t let these issues stop us. Therefore, we are gathering and analyzing relevant data from as many sources as possible while documenting the limitations of the data.

One source of data we have used are ODFW’s one- through seven-day fishing and shellfishing license sales. Implementing marine reserves closes off any extractive activities within that area. Therefore, we might expect that daily fishing and shellfishing license sales in communities located near marine reserves would decrease following reserve implementation. However, we also need to control for the historical trend in license sales on the coast. If license sales are decreasing in towns located near reserves, but also decreasing across the entire coast, then this reduction may be caused by something other than the reserves, such as a change in culture.

License sales are just one example of the data we are using to analyze marine reserve impacts. While we don’t always have perfect data to work with, using the best data available from multiple sources should be sufficient to understand if and how marine reserves have impacted communities.

While I had hoped that this summer would be full of trips to sunny, salty, sea lion filled Newport to mentor ODFW’s Summer Scholars, unfortunately everyone is still working remotely. Though I have heard from my Newport-based coworkers that this pandemic is not stopping the hordes of tourists from flocking to the coast for celebrations such as the recent 4^th of July.

One of the main projects that I’ve been working on this summer while stuck in Bend (there are worse places to be stuck!) is understanding if marine reserves have influenced socioeconomic conditions in communities located near them. To investigate this, I first had to gather information on the socioeconomic conditions of coastal communities over time. I used the Census Bureau’s American Community Survey 5-year estimates from 2010 to 2018. While accessing data prior to 2010 would be ideal, the first 5-year estimate summary tables were only released in 2010, so we work with what we got.

After collecting all of these data, the exploratory analyses began, as did the true test of what I can remember from those statistics courses long ago and how far my R coding skills can take me. These exploratory analyses include tests and visualizations such as correlation plots, non-metric multidimensional scaling plots, bubble plots, vector analyses, principal component analyses, PERMANOVAs, the list goes on. When working with complicated multivariate data, I have learned that exploration is key to understanding what is really shaping your data.

I have also been trying to figure out what my control and treatment communities should be. With this first approach, I am considering treatment communities as those that are located <15km from a marine reserve. Control communities are therefore all coastal communities located >15km from a marine reserve. Since the marine reserves were phased in over time, I have three separate treatment groups. The 2012 group includes communities located near Redfish Rocks Marine Reserve and Otter Rock Marine Reserve, the 2014 group near Cape Perpetua Marine Reserve and Cascade Head Marine Reserve, and the 2016 group near Cape Falcon Marine Reserve. While this approach is a good first step, I will likely need to consider if other groupings or controls would be more appropriate. One method I am currently researching is creating a synthetic control by weighting non-treatment communities based on socioeconomic similarities to treatment communities prior to marine reserve implementation. But I won’t get too into the weeds with that statistical discussion here for everyone’s sake!

As I’ve been working with these census data, I’ve been thinking about the unfortunate timing of the decennial census this year. The Census Bureau conducts a survey every ten years with the goal to obtain a comprehensive snapshot of households in the United States. Unfortunately, the census this year coincided with a massive pandemic leading to significant economic loss and unemployment and the consequences that follow that loss. When future researchers use the decennial census to look at change over time, they are going to see data from 2020 that is not representative of the previous ten years, which will likely impact their analyses. I’m assuming that this data issue will lead to many footnotes in future papers. Luckily I will only be using data through 2019 (once it is made available) since the 2020 data will not be made available until after the marine reserve synthesis report is due.