Intro
They fit in the palm of your hand.
Every year, they fly from Mexico to Canada and back.
They are also listed as an endangered species in Canada.
You guessed it, it's the
monarch butterflies!
I've explored a dataset of over 700,000 monarch butterfly sightings
collected by citizens across North America. What started as curiosity
turned into a full analysis of migration corridors, phenology, and
understanding the limits of what volunteer-submitted data can tell us.
This is what I found.
An Endangered Species
The monarch butterfly was listed as
endangered under Canada's Species at Risk
Act in December 2023, a designation that reflects decades of population
decline driven by habitat loss, pesticide use, and climate change. The
eastern population, which migrates between Mexico and Canada, has lost an
estimated 80% of its numbers since the 1990s. The western population,
which overwinters along the California coast, has fared even worse,
declining by more than 95% since the 1980s.
Citizen-driven Efforts
The data used in this analysis was downloaded from the Global Biodiversity
Information Facility (GBIF), which aggregates occurrence records from
institutions and
citizen science platforms
around the world. The majority of records come from iNaturalist, a
platform where anyone can log a wildlife sighting using their phone. What
makes this dataset remarkable is that it exists entirely because ordinary
people (hikers, gardeners, teachers, kids) took a moment to photograph a
butterfly and record where they saw it. This is both the strength and the
limitation of the data. More eyes means more coverage, but it also means
the data reflects the number of citizens recording instead of actual
population measurements.
Data Analysis
Data Cleaning
The raw dataset contained 703,394 records spanning from the 1800s to 2025.
As visible in the chart below, data before 1980 is extremely sparse, so I
restricted the analysis to 1980 onwards. The spike in records around
1999-2001 also stood out. Digging into it, it turned out to be a bulk
submission from Monarch Watch, a dedicated monarch monitoring program
based out of the University of Kansas that has tracked the species since
the early 1990s. These records were aggregated annually and lacked day and
month information, making them unusable for phenological analysis.
After removing records with unrecoverable dates, missing coordinates,
duplicates, and pre-1980 observations, the dataset was reduced to 316,273
records. Given sparse coverage in the early years, the analysis was
further restricted to 2010 onwards, yielding a final dataset of 312,235
records, roughly 44% of the original.
Data Visualization
The maps below show monarch butterfly sightings across North America
colored by month. The full migration corridor is immediately visible, with
purple and blue dots clustering in Mexico during winter, greens push north
through spring, and reds and oranges spread across the US and Canada
through summer and fall. Comparing across periods, the density of
sightings increases noticeably over time, largely reflecting the increase
in participants and volunteers rather than the actual monarch population.
2010-2015
2016-2020
2021-2025
all years
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Each dot represents a sighting, colored by month of observation.
Colors follow the seasonal cycle, with cool purples and blues in
winter, greens in spring, warm oranges and reds through summer and
early fall.
The animation below shows the monthly migration pattern across the
full dataset. Watch the monarchs move north through spring and return
south in the fall.
Statistical Analysis
To better understand the migration pattern, I focused on the
Atlantic coast corridor and traced the path
monarchs take as they move north through Georgia, the Carolinas, Virginia,
and up through New England.
The table below shows the number of sightings per state per year. The
participation bias is immediately visible: records in every state jump
dramatically after 2017, reflecting an increase in citizen submissions
rather than monarch population changes.
| State |
2010 |
2011 |
2012 |
2013 |
2014 |
2015 |
2016 |
2017 |
2018 |
2019 |
2020 |
2021 |
2022 |
2023 |
2024 |
2025 |
| Connecticut |
3 |
7 |
6 |
1 |
21 |
7 |
43 |
75 |
92 |
225 |
220 |
362 |
338 |
213 |
325 |
493 |
| Delaware |
1 |
0 |
2 |
2 |
8 |
14 |
15 |
31 |
39 |
42 |
106 |
141 |
134 |
149 |
151 |
289 |
| Georgia |
8 |
27 |
17 |
13 |
25 |
5 |
17 |
43 |
59 |
126 |
199 |
253 |
387 |
286 |
236 |
633 |
| Maine |
4 |
1 |
35 |
18 |
36 |
10 |
48 |
151 |
112 |
352 |
202 |
347 |
506 |
208 |
484 |
714 |
| Maryland |
7 |
8 |
13 |
16 |
62 |
64 |
151 |
233 |
344 |
557 |
817 |
847 |
1034 |
571 |
627 |
1753 |
| Massachusetts |
2 |
9 |
25 |
18 |
50 |
54 |
70 |
198 |
300 |
760 |
529 |
928 |
915 |
667 |
937 |
1117 |
| New Jersey |
22 |
17 |
29 |
15 |
33 |
45 |
81 |
196 |
263 |
495 |
465 |
688 |
459 |
382 |
747 |
1526 |
| New York |
39 |
34 |
29 |
16 |
38 |
44 |
85 |
502 |
631 |
1378 |
1233 |
1649 |
1242 |
969 |
1336 |
2246 |
| North Carolina |
8 |
4 |
11 |
10 |
23 |
82 |
66 |
121 |
253 |
370 |
602 |
631 |
642 |
676 |
705 |
1683 |
| Rhode Island |
1 |
0 |
3 |
12 |
9 |
9 |
21 |
37 |
36 |
66 |
53 |
82 |
88 |
78 |
116 |
137 |
| South Carolina |
9 |
19 |
12 |
5 |
21 |
28 |
53 |
104 |
104 |
150 |
227 |
231 |
189 |
200 |
195 |
418 |
| Virginia |
15 |
13 |
40 |
13 |
41 |
62 |
126 |
220 |
409 |
585 |
1223 |
987 |
997 |
732 |
761 |
2074 |
Despite the uneven coverage, a clear pattern emerges when we look at
arrival dates. For each state, I calculated the 5th percentile sighting
date across years with at least 100 records, effectively when monarchs
first consistently show up. Only years with at least 5 valid years of data
were included.
The results tell a clean story. South Carolina sees its first consistent
sightings around March 30, Georgia around April 17, and the signal moves
steadily northward through Virginia in June, reaching Maine by early July.
The map below visualizes this progression along the corridor. This is the
spring northward migration captured in
citizen science data. While not perfect, it is remarkably coherent given
the limitations of the dataset.
Limitations of Citizen-driven Dataset
To investigate whether arrival dates are shifting, I fitted a
linear regression for each state using year
as the predictor, controlling for growth in citizen science participation.
After controlling for participation, no state showed a statistically
significant trend. Virginia shows the steepest slope at -51 days per
decade, but with a p-value of 0.15 and only 10 years of reliable data, the
signal-to-noise ratio is too low to confirm this as a biological pattern
rather than sampling noise.
This analysis establishes a baseline and a framework, and rerunning it in
2030 with nearly two decades of consistent citizen-driven data will be a
much stronger test of whether monarch arrival timing is responding to
climate change.
| State |
Slope (days/decade) |
P-Value |
| Virginia |
-51.41 |
0.1477 |
| Maryland |
-32.24 |
0.2200 |
| Georgia |
-28.97 |
0.5203 |
| North Carolina |
-26.74 |
0.3758 |
| New York |
-22.52 |
0.2861 |
| New Jersey |
-20.95 |
0.2122 |
| Connecticut |
-4.17 |
0.8957 |
| Delaware |
-3.73 |
0.9614 |
| Massachusetts |
0.43 |
0.9847 |
| Maine |
14.01 |
0.5101 |
| South Carolina |
72.98 |
0.2187 |
The Western Corridor
Unlike the eastern population, which follows a north-south corridor to
Mexico, western monarchs follow an
inland-coastal pattern. Sightings in Salt
Lake City peak in July, reflecting the summer inland breeding season. As
fall approaches, monarchs begin their journey westward to the California
coast. San Francisco sees its peak in October as the migration arrives,
while San Luis Obispo, one of the most famous overwintering sites in North
America, peaks in December as monarchs settle in for the winter.
This population has suffered a catastrophic decline. The western
overwintering population has dropped more than 95% since the 1980s, making
it at greater risk of extinction than the eastern population, and a
subject that warrants a dedicated analysis of its own.
Conclusions
This analysis set out to
explore what
citizen science data can tell us about monarch butterfly migration
patterns across North America. The Atlantic corridor analysis confirmed
what biologists expect: monarchs arrive progressively later as you move
north, from late March in South Carolina to early July in Maine. The fact
that this signal emerges clearly from noisy, volunteer-submitted data is
itself encouraging.
The western population tells a different story, following an
inland-coastal pattern rather than a north-south one, with inland breeding
in summer and coastal overwintering in winter.
Where the data falls short is in detecting change over time. The trend
analysis, even after accounting for growth in citizen science
participation, was inconclusive. With at most 10 years of reliable data
per state, the signal-to-noise ratio is simply too low to draw confident
conclusions about whether monarch arrival timing is shifting.
Next Steps
-
Incorporate climate covariates such as spring temperature anomalies to
separate biological signal from sampling noise
-
Extend the analysis as data matures: by 2030 there will be nearly 20
years of consistent coverage which should make trend detection more
reliable
-
Conduct a dedicated analysis of the western overwintering population,
whose 95% decline since the 1980s warrants closer examination
How You Can Help
The analyses in this post are only possible because thousands of
volunteers take the time to record and submit their sightings. If you
spot a monarch butterfly, consider logging it on
iNaturalist.
Every observation counts and directly contributes to the scientific
record.
If you are based in Canada,
Mission Monarch
is a citizen science program that tracks monarch and milkweed
distribution across the country. In the US,
Journey North
has been tracking monarch migration since the 1990s and welcomes new
observers.
You can also help by planting
native milkweed and nectar plants in your
garden, avoiding pesticide use, and supporting local conservation
organizations working to protect monarch habitat.
References
Data Sources
Monarch Status & Conservation
Migration & Biology
Citizen Science