2017: Birding by the Numbers

With 2017 nearly complete, I thought it might be interesting to take a look at my birding stats for this past year. I’m positive that 2017 was my best year of birding so far; however, there’s no better way to back up claims like that than by looking at the data itself!

I submit all my checklists to eBird, a fantastic citizen science website for submitting bird observations. It is a great two-way service that allows birders to submit their data for researchers while allowing the birder to curate their checklists and access data submitted by other birders. eBird allows each user to download their data anytime they want, and so that is what I am analyzing here.

The data I am analyzing is up-to-date as of December 30, 2017 at 4:46 PM. I don’t foresee myself getting many new life birds on December 31; if I do, I will run these analyses again and update this post! All analyses were run using scripts I wrote in R, which are available here if you are interested in viewing them or running them on your own data!

Let’s dive in.

Effort

The main metric I wanted to take a look at for tracking effort was the number of checklists I submitted. 2017 sticks out right away simply by looking at the number of checklists submitted by year:

yearlyNumChecklists

Note that I have two categorizations of “checklist type”. This is based off of eBird’s definition of “complete checklist”. As a quick summary, a complete checklist is a checklist where I am reporting ALL birds at a location and I am providing counts (or at least count estimates) of all the species in the checklist. In general, complete checklists are more valuable to eBird as they have more complete data. You can read more about that here!

At the beginning of 2017, eBird issued a challenge to submit a “checklist a day”. They later specified that the challenge was to only submit 365 total complete checklists in a year and not actually a checklist every day. As you can see from the graph above, I did, indeed, submit at least 365 complete checklists for 2017 (410 to be exact). Here’s how my checklist accumulation looked over the year:

monthlyCumulativeChecklists

Basically, the goal was for the orange line (complete checklists) to be above the black line (“checklist-a-day” target) by the end of the year, which it is! What surprised me was how consistently I actually stayed above my target; only a few times throughout the year did I come close to falling below.

So I’ve looked at how much I’ve birded in 2017, but another interesting variable is where I’ve birded. One would assume that more places birded implies a greater birding effort. The birding community seems to pay attention to locations at the county level, and so total counties birded is the variable I explored here:

yearlyNumCounties

I’ll note that of the 28 counties I birded in 2017, 27 of them are Ontario counties while the remaining county is Ingham County in Michigan (when I attended American Ornithology 2017).

Out of curiosity, I wanted to see numbers on my Top 10 counties for 2017:

topTenCounties

It’s evident from this graph where my two homes are: Sarnia, in Lambton County, and Guelph, in Wellington County. What I find kind of funny is that I spend, by far, more time in Wellington county, but I still have less bird species there than Lambton. I attribute this to the fact that if I am in Wellington county, there is a good chance that I am also in school, which takes up a fair bit of time. Mind you, Lambton County is objectively a better county to bird in (based on species count), but the fact that I am in school when I am in Wellington County is a good explanation to this anomaly, if you could call it that.

So, it’s clear that I at least put in my best effort for birding this year, but did it translate into a good year species-wise?

Total Year Birds

An easy metric to look at right off the hop is the number of species I managed to observe in 2017 versus previous years:

yearlyNumSpecies

Again, it’s evident that 2017 was my best year of birding based on number of species observed. Since I started seriously birding in 2015, I’ve made it a yearly goal to at least beat the total species count from the previous year, a goal I’ve consistently achieved since 2014 (before I even started seriously birding).

Let’s take a look at the accumulation of all 211 bird species I observed in 2017:

cumulativeSpecies

What I like about this plot is how you can see where the two major migration times are: spring migration from April to mid-May, and fall migration from mid-August to November. This is evident in the major “jumps” that you see in the cumulative species.

At this point, we have both the effort data and yearly species totals data to back up my claim of 2017 being my best birding year so far. Let’s look at one more area of data related to bird species.

Life List Additions

One of the main goals of any birder is to add new birds to their life list; that is, observe a species in the wild that they’ve never observed before. Birding is very much like real-life Pokemon: gotta catch them all! But don’t actually catch them. Just observe from a distance, and maybe snap a photo or two.

Investigating life list addition data actually has some caveats with it. I’m not going to get into those caveats in this blog post — that will be a post for sometime in early 2018. For now, let’s look at life list additions over the years since 2009:

cumulativeLifeSpecies

You can clearly see from this plot when I actually started birding more seriously. Data from 2009 – 2014 were simply historic observations I added to eBird based off of photos I had taken in the past, hence the very slow increase. On March 1, 2015, I observed my first Red-bellied Woodpecker. I consider this observation to be my “spark bird”, or the bird that sparked my interest in birding. I spent the summer of 2015 trying to photograph all the birds I can find (mostly just backyard and other “easily accessible” birds). In September 2015, I started at the University of Guelph and almost immediately joined the Wildlife Club where I met many other birders around my age. As you can see from the graph, I started seriously birding then and haven’t looked back since!

spark bird
My first observation of a Red-bellied Woodpecker – the bird that started it all.

Let’s take a look at how many life bird additions I had this year compared to previous years:

yearlyLifeSpecies

Despite the effort I put in and the number of species I observed in 2017, I actually saw less life birds this year than I did in 2016. It’s close, but still less. This is going to be the premise behind a future blog post discussing why yearly life bird additions may not actually be a great metric to track. For now, I will happily accept the 65 new bird species that have made it onto my life list!

Closing Remarks

Based on the data above, I think it’s safe to call 2017 my best year of birding so far. I clearly put in far more effort than previous years, and I believe it paid off in the number of species I was able to see this year.

I only thought of doing this blog post pretty recently, and so I didn’t have much time to actually code the scripts. Ideally, I’d like to make a post like this from now on at the end of the year. I’d call the above analyses fairly basic, so hopefully I’ll be able to provide some more interesting analyses for 2018’s post!

Thank you for reading, and I hope you have a great start to 2018!

 

Advertisements

4 thoughts on “2017: Birding by the Numbers

Add yours

  1. Wow, that’s really, really cool! And thanks for uploading the code you used. Thought I’d add a couple of my interesting charts:

    You can see where I started using eBird regularly in 2009, and two international birding trips in 2015 and 2017:
    https://imgur.com/Of52cpi

    One Texas county managed to sneak in to my top 10 for the year:
    https://imgur.com/LFtgSpw

    You can very clearly see that I was unemployed January/February and had a major birding vacation in October:
    https://imgur.com/hdm90XS
    https://imgur.com/G5kjWus

    2016 was definitely my best eBirding year:
    https://imgur.com/nFbOuLU

    Reuven

    Liked by 1 person

    1. Glad you were able to use the scripts, and get some interesting results from it!

      I have to admit, though I put a link to the scripts for people to use, I actually naively didn’t expect people to use them. So, I apologize for any of code being crappy! I rushed the code to get it done, and will be cleaning it up later!

      Like

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

Create a free website or blog at WordPress.com.

Up ↑

%d bloggers like this: