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Starr County

So how did my simple projection work out?

Remember this? I divided the counties up by how much their voter rolls had grown or shrunk since 2012, then used the 2016 turnout levels and 2018 results to project final numbers for the Presidential election in 2020. Now that we have those numbers, how did my little toy do? Let’s take a look.

A couple of things to acknowledge first. The most up to date voter registration numbers show that the group of counties that looked to have lost voters since 2012 have actually gained them, at least in the aggregate. Second, the actual turnout we got so far exceeded past numbers that we literally couldn’t have nailed this, at least not at a quantitative level. So with that in mind, let’s move forward.

We start with the counties that had seen growth of at least 10K voters on their rolls since 2012. There were 33 of these. Here are the numbers I had in my initial review, updated to include what happened this year.


Romney  3,270,387   Obama    2,792,800
Romney      53.9%   Obama        46.1%
Romney +  477,587

Trump   3,288,107   Clinton  3,394,436
Trump       49.2%   Clinton      50.8%
Trump  -  106,329

Cruz    3,022,932   Beto     3,585,385
Cruz        45.7%   Beto         54.3%
Cruz   -  562,453

Trump   4,119,402   Biden    4,579,144
Trump       47.4%   Biden        52.6%
Trump  -  459,742

Year  Total voters   Total votes   Turnout
==========================================
2012    10,442,191     6,157,687     59.0%
2016    11,760,590     7,029,306     59.8%
2018    12,403,704     6,662,143     53.7%
2020    13,296,048     8,765,774     65.9%

When I did the original post, there were 12,930,451 registered voters in these 33 counties. As you can see, and will see for the other groups, that increased between August and November, by quite a bit. As you can see, Trump did considerably worse than he had in 2016 with these counties, but better than Ted Cruz did in 2018. That says it all about why this race wasn’t as close as the Beto-Cruz race in 2018. My projection had assumed 2016-level turnout, but we obviously got more than that. Here’s what I had projected originally, and what we would have gotten if the 2020 results had been like the 2018 results from a partisan perspective:


Trump   3,533,711   Biden    4,198,699
Trump  -  664,988

Trump   3,975,236   Biden    4,723,310
Trump  -  748,074

Fair to say we missed the mark. We’ll see how much of a difference that would have made later. Now let’s look at the biggest group of counties, the 148 counties that gained some number of voters, from one to 9,999. Again, here are my projections, with the updated voter registration number:


Romney  1,117,383   Obama      415,647
Romney      72.9%   Obama        27.1%
Romney +  701,736

Trump   1,209,121   Clinton    393,004
Trump       75.5%   Clinton      24.5%
Trump  +  816,117

Cruz    1,075,232   Beto       381,010
Cruz        73.8%                26.2%
Cruz   +  694,222

Trump   1,496,148   Biden      501,234
Trump       74.0%   Biden        26.0%
Trump  +  994,914

Year  Total voters   Total votes   Turnout
==========================================
2012     2,686,872     1,551,613     57.7%
2016     2,829,110     1,653,858     58.5%
2018     2,884,466     1,466,446     50.8%
2020     3,112,474     2,022,490     65.0%

As discussed, there’s a whole lot of strong red counties in here – of the 148 counties in this group, Beto carried ten of them. They had 2,929,965 voters as of August. What had been my projection, and how’d it go here?


Trump   1,264,954   Biden      449,076
Trump  +  815,878

Trump   1,496,148   Biden      501,234
Trump  +  994,914

The margin is wider due to the higher turnout, but Biden actually did a little better by percentage than Clinton did, and was right in line with Beto. This is obviously an area of great need for improvement going forward, but the projection was more or less right on target, at least from a partisan performance perspective. But as you can see, even with the more optimistic projection for Biden, he’s already in the hole. Like I said, this is an area of urgent need for improvement going forward.

Now on to the last group, the 73 counties that had lost voters from 2012, at least going by the August numbers. As you can see, that turned out not to be fully true:


Romney     182,073   Obama      99,677
Romney       64.6%   Obama       35.4%
Romney +    82,396

Trump      187,819   Clinton    90,428
Trump        67.5%   Clinton     32.5%
Trump  +    97,391

Cruz       162,389   Beto       79,237
Cruz         67.2%   Beto        32.8%
Cruz   +    83,152

Trump      226,104   Biden     105,490
Trump        68.2%   Biden       31.8%
Trump  +   120,514

Year  Total voters   Total votes   Turnout
==========================================
2012       517,163       284,551     55.0%
2016       511,387       286,062     55.9%
2018       505,087       243,066     48.1%
2020       546,997       335,110     61.2%

As you can see, that decline in registrations has reversed, quite dramatically. I didn’t check each individual county – it seems likely that some of them are still at a net negative – but overall they are no longer in decline. Good for them. As you can also see, Biden performed a little worse than Clinton and Beto, but close enough for these purposes. Let’s compare the projection to the reality:


Trump      187,587   Biden      91,561
Trump +     96,026

Trump      226,104   Biden     105,490
Trump  +   120,514

Put the best-case scenario from the first group with what we got in the last two, and we could have had this:


Trump    5,697,488   Biden   5,330,034
Trump       51.67%   Biden      48.33%

Which is pretty close to what I had projected originally, just with a lot more voters now. The actual final result is 52.18% to 46.39%, so I’d say my method came closer to the real result than most of the polls did. Clearly, I missed my calling.

All this was done as an exercise in frivolity – as I said at the time, I made all kinds of assumptions in making this projection, and the main one about turnout level was way wrong. The point of this, I think, is to show that while Dems have indeed improved greatly in performance in the biggest counties, they haven’t done as well everywhere else, and while the marginal difference from Obama 2012 to Clinton 2016 and Biden 2020 isn’t much, the overall direction is wrong (even as Biden improved somewhat on the middle group over Clinton), and we’re going to have a real problem making further progress if we can’t figure out a way to improve our performance in these smaller counties. There is room to grow in the big and growing counties – these include some fast-growing and very red places like Montgomery and Comal, for instance – but we’re going to reach diminishing marginal growth soon, if we’re not already there. We need to step it up everywhere else. I’ll be returning to this theme as we go forward. Let me know what you think.

A first response to the Latino voting (and polling) question

For your consideration:

It’s very much not my intent to pin blame on anyone. As I noted in my post about how voting went in these Latino counties, which includes a lot of RGV counties as well as Bexar and El Paso, I’m just showing what happened. I think Jolt has done a lot of good work, a lot of hard and necessary work, and I salute them for it.

I can’t address the specifics of the numbers cited in those tweets – I don’t have his data, and the public data is quite limited right now. I do have some limited Harris County canvass data, courtesy of Greg Wythe, so I thought I’d bring that in here to continue the discussion. Here’s what I can say about how voting went in the five predominantly Latino State Rep districts in Harris County:


Dist   Trump  Clinton  Trump%  Clinton%  Margin
===============================================
140    6,119   21,009   21.8%     75.0%  14,890
143    8,746   23,873   26.0%     70.9%  15,127
144   10,555   15,885   38.3%     57.6%   5,330
145   10,102   23,534   28.7%     66.8%  13,432
148   14,815   31,004   30.3%     63.4%  16,279

      50,337  115,305   30.4%     69.6%  64,968

Dist   Trump    Biden  Trump%    Biden%  Margin
===============================================
140   10,175   22,651   30.3%     67.4%  12,476
143   13,105   25,109   33.5%     64.1%  12,004
144   14,415   17,174   44.5%     53.0%   2,759
145   15,198   28,200   34.1%     63.4%  13,102
148   20,207   40,821   32.2%     65.0%  20,614

      73,100  133,955   35.3%     64.7%  60,855

The first table is 2016, the second is 2020. Please note that while the percentages for each candidate is their actual percentage for all voters in the district, the totals at the bottom are just the two-candidate values. I apologize for mixing apples and oranges. We should note that while these five districts are the five predominantly Latino districts in Houston, there is some variance. HDs 140 and 143 have the largest Latino population totals by percentage, while the others have a significant minority of Anglo residents. HD144 includes the Pasadena area, while HDs 145 and 148 include parts of the Heights and surrounding neighborhoods. HD148 is probably the least Latino of the five, and is currently represented by Anna Eastman, who won the special election to serve the remainder of Jessica Farrar’s term, though she was defeated in the primary by Penny Shaw.

As you can see, Trump improved on his 2016 performance in all five districts. Biden got more votes than Clinton in all five districts, but had a lower percentage in all but HD148. The reason both Trump and Biden could see an increase in percentage in HD148 is because the third-party share of the vote was so high in 2016 – it was over six percent that year, but looks to be less than three percent this year. Overall, Trump lost these five districts by about four thousand fewer votes than he did in 2016, with about 20K more votes cast.

This is not an eye-popping change like what we saw in some RGV counties was, but it’s still a decline. I don’t know how much of that is from Latinos voting for Trump, and how much is from Anglo voters in these districts turning out for Trump. Jolt’s mission is to turn out Latino voters, and in the aggregate that’s going to be good for Democrats even if there are some rough spots, and even if it’s not quite as good as we might have expected. My approach is not as granular as it could be, so we shouldn’t draw broad conclusions from it. There are plenty of Latino precincts elsewhere in Harris County – HDs 137 and 138 will have quite a few – so there’s much more to be said. This is the data I have right now. Make of it what you will.

So what happened in the Latino counties?

Let’s go to the data:


County       Trump  Clinton    Trump    Biden
=============================================
Bexar      240,333  319,550  303,871  440,823
Cameron     29,472   59,402   48,834   63,732
Dimmit         974    2,173    1,384    2,264
El Paso     55,512  147,843   81,235  168,801
Frio         1,856    2,444    2,812    2,421
Hidalgo     48,642  118,809   89,925  127,391
Jim Hogg       430    1,635      831    1,197
Jim Wells    5,420    6,694    7,077    5,094
Maverick     2,816   10,397    6,881    8,324
Nueces      50,766   49,198   64,467   60,749
Presidio       652    1,458      721    1,463
Starr        2,224    9,289    8,224    9,099
Webb        12,947   42,307   18,985   32,442
Willacy      1,547    3,422    2,437    3,097
Zapata       1,029    2,063    2,032    1,820
Zavala         694    2,636    1,490    2,864

Total      453,643  779,320  641,116  931,555

County      Trump% Clinton%   Trump%  Biden%
============================================
Bexar        42.9%    57.1%    40.8%   59.2%
Cameron      33.2%    66.8%    43.4%   56.6%
Dimmit       31.0%    69.0%    37.9%   62.1%
El Paso      27.3%    72.7%    32.5%   67.5%
Frio         43.2%    56.8%    53.7%   46.3%
Hidalgo      29.0%    71.0%    41.4%   58.6%
Jim Hogg     20.8%    79.2%    41.0%   59.0%
Jim Wells    44.7%    55.3%    58.1%   41.9%
Maverick     21.3%    78.7%    45.3%   54.7%
Nueces       50.8%    49.2%    51.5%   48.5%
Presidio     30.9%    69.1%    33.0%   67.0%
Starr        19.3%    81.7%    47.5%   52.5%
Webb         23.4%    76.6%    36.9%   63.1%
Willacy      31.1%    68.9%    44.0%   56.0%
Zapata       33.3%    66.7%    52.8%   47.2%
Zavala       20.8%    79.2%    34.2%   65.8%

Total        36.8%    63.2%    40.8%   59.2%

Webb County totals are early voting only – they have taken their sweet time getting those results. I have no prescriptions to offer, and even if I did, I’d be the wrong person to listen to for them. I’m just reporting what happened. As others have observed, in some counties Biden met or exceeded Hillary Clinton’s numbers from 2016, but Trump greatly increased his numbers from that election. You may recall that in the last NYT/Siena poll, Nate Cohn observed that higher turnout, at least beyond a certain point, didn’t actually benefit Biden, because sufficiently high Latino turnout wasn’t in his favor. Starr County was a particularly shocking example of that, but we see that in some larger counties like Hidalgo and Cameron, and to a lesser extent El Paso as well. In some counties – Maverick, Jim Hogg, Jim Wells, Willacy – it appears some Clinton voters may have switched to Trump, or not voted while non-participants from 2016 came in. Bexar County was the only clear improvement for Biden. If you had to pick only one county for that, Bexar would be the one, but there’s only so much it can do.

You can look at this two ways. Hillary Clinton netted 346K votes, while Biden netted 290K. That’s not all that much, but there’s the ground we could have gained given the higher turnout as well as the ground we lost. If Biden had performed at exactly the same level as Clinton, he’d have netted 415K votes. Adjust the final score to account for that, and Biden would have lost by four and a half points, instead of almost six. Wouldn’t have mattered in this case, but it wouldn’t have taken much. Plus, you know, better to make your task easier rather than harder.

Like I said, I have no solutions to offer. Plenty of smart people have plenty of ideas, and quite a few of them were raising issues before the election. Might be a good idea to listen to them. All I’m saying is that whatever happened here, it wasn’t what we wanted. If we want to avoid a repeat, we better get to work.

A very simple projection of the November vote

In my earlier post about the current state of voter registrations, I noted that you could see the county-by-county totals in the contest details for the Senate runoff. What that also means is that if you have current (till now, anyway) voter registration totals, you can do a comparison across the counties of where voter registration totals have gone up the most, and how the vote has shifted in recent elections. In doing so, you can come up with a simple way to project what the 2020 vote might look like.

So, naturally, I did that. Let me walk you through the steps.

First, I used the 2020 runoff results data to get current registration totals per county. I put that into a spreadsheet with county-by-county results from the 2012 and 2016 Presidential elections and the 2018 Senate election to calculate total voter registration changes from each year to 2020. I then sorted by net change since 2012, and grouped the 254 counties into three buckets: Counties that had a net increase of at least 10,000 voters since 2012, counties that had a net increase of less than 10,000 voters since 2012, and counties that have lost voters since 2012. From there, I looked at the top race for each year.

First, here are the 2012 big gain counties. There were 33 of these counties, with a net gain of +2,488,260 registered voters as of July 2020.


Romney  3,270,387   Obama    2,792,800
Romney      53.9%   Obama        46.1%
Romney +  477,587

Trump   3,288,107   Clinton  3,394,436
Trump       49.2%   Clinton      50.8%
Trump  -  106,329

Cruz    3,022,932   Beto     3,585,385
Cruz        45.7%   Beto         54.3%
Cruz   -  562,453

Year  Total voters   Total votes   Turnout
==========================================
2012    10,442,191     6,157,687     59.0%
2016    11,760,590     7,029,306     59.8%
2018    12,403,704     6,662,143     53.7%
2020    12,930,451     

The shift in voting behavior here is obvious. Hillary Clinton did much better in the larger, growing counties in 2016 than Barack Obama had done in 2012, and Beto O’Rourke turbo-charged that pattern. I have made this point before, but it really bears repeating: In these growing counties, Ted Cruz did literally a million votes worse than Mitt Romney did. And please note, these aren’t just the big urban counties – there are only seven such counties, after all – nor are they all Democratic. This list contains such heavily Republican places as Montgomery, Comal, Parker, Smith, Lubbock, Ector, Midland, Randall, Ellis, Rockwall, and Kaufman. The thing to keep in mind is that while Beto still lost by a lot in those counties, he lost by less in them than Hillary Clinton did, and a lot less than Obama did. Beto uniformly received more votes in those counties than Clinton did, and Cruz received fewer than Trump and Romney.

Here’s where we do the projection part. Let’s assume that in 2020 these counties have 59.8% turnout at 2018 partisan percentages, which is to say Biden wins the two-party vote 54.3% to 45.7% for Trump. At 59.8% turnout there would be 7,732,410 voters, which gives us this result:


Trump   3,533,711   Biden    4,198,699
Trump  -  664,988

In other words, Biden gains 100K votes over what Beto did in 2018. If you’re now thinking “but Beto lost by 200K”, hold that thought.

Now let’s look at the 2012 small gain counties, the ones that gained anywhere from eight voters to 9,635 voters from 2012. There are a lot of these, 148 counties in all, but because their gains were modest the total change is +243,093 RVs in 2020. Here’s how those election results looked:


Romney  1,117,383   Obama      415,647
Romney      72.9%   Obama        27.1%
Romney +  701,736

Trump   1,209,121   Clinton    393,004
Trump       75.5%   Clinton      24.5%
Trump  +  816,117

Cruz    1,075,232   Beto       381,010
Cruz        73.8%                26.2%
Cruz   +  694,222

Year  Total voters   Total votes   Turnout
==========================================
2012     2,686,872     1,551,613     57.7%
2016     2,829,110     1,653,858     58.5%
2018     2,884,466     1,466,446     50.8%
2020     2,929,965     

Obviously, very red. Beto carried a grand total of ten of these 148 counties: Starr, Willacy, Reeves, Jim Wells, Zapata, Val Verde, Kleberg, La Salle, Dimmit, and Jim Hogg. This is a lot of rural turf, and as we can see Trump did better here than Romney did, both in terms of percentage and net margin. Ted Cruz was a tiny bit behind Romney on margin, but did slightly better in percentage. The overall decline in turnout held Cruz back.

Once again, we project. Assume 58.5% turnout at 2018 partisan percentages. That gives us 1,714,030 voters for the following result:


Trump   1,264,954   Biden      449,076
Trump  +  815,878

Trump winds up with the same margin as he did in 2016, as the 2018 partisan mix helps Biden not fall farther behind. Trump is now in the lead by about 150K votes.

Finally, the counties that have had a net loss of registered voters since 2012. There were 73 such counties, and a net -17,793 RVs in 2020.


Romney     182,073   Obama      99,677
Romney       64.6%   Obama       35.4%
Romney +    82,396

Trump      187,819   Clinton    90,428
Trump        67.5%   Clinton     32.5%
Trump +     97,391

Cruz       162,389   Beto       79,237
Cruz         67.2%   Beto        32.8%
Cruz +      83,152

Year  Total voters   Total votes   Turnout
==========================================
2012       517,163       284,551     55.0%
2016       511,387       286,062     55.9%
2018       505,087       243,066     48.1%
2020       499,370    

Again, mostly rural and again pretty red. The counties that Beto won were Culberson, Presidio, Jefferson (easily the biggest county in this group; Beto was just over 50% here, as Clinton had been, while Obama was just under 50%), Zavala, Duval, Brooks, and Frio.

Assume 55.9% turnout at 2018 partisan percentages, and for 277,148 voters we get:


Trump      187,587   Biden      91,561
Trump +     96,026

Again, basically what Trump did in 2016. Add it all up, and the result is:


Trump    5,012,802   Biden    4,770,351
Trump       51.24%   Biden       48.76%

That’s actually quite close to the Economist projection for Texas. If you’re now thinking “wait, you walked me through all these numbers to tell me that Trump’s gonna win Texas, why did we bother?”, let me remind you of the assumptions we made in making this projection:

1. Turnout levels would be equal to the 2016 election, while the partisan splits would be the same as 2018. There’s no reason why turnout can’t be higher in 2020 than it was in 2016, and there’s also no reason why the Democratic growth in those top 33 counties can’t continue apace.

2. Implicit in all this is that turnout in each individual county within their given bucket is the same. That’s obviously not how it works in real life, and it’s why GOTV efforts are so critical. If you recall my post about Harris County’s plans to make voting easier this November, County Clerk Chris Hollins suggests we could see up to 1.7 million votes cast here. That’s 360K more voters than there were in 2016, and 500K more than in 2018. It’s over 70% turnout in Harris County at current registration numbers. Had Beto had that level of turnout, at the same partisan percentages, he’d have netted an additional 85K votes in Harris. Obviously, other counties can and will try to boost turnout as well, and Republicans are going to vote in higher numbers, too. My point is, the potential is there for a lot more votes, in particular a lot more Democratic votes, to be cast.

Remember, this is all intended as a very simple projection of the vote. Lots of things that I haven’t taken into account can affect what happens. All this should give you some confidence in the polling results for Texas, and it should remind you of where the work needs to be done, and what the path to victory is.

A very early glimmer of some possibly good news

We may be finally bending the curve, thanks to people finally taking seriously the need to wear face masks in public.

Three weeks after Gov. Greg Abbott required Texans to wear masks, epidemiologists and disease modelers say they are cautiously optimistic that the mandate is helping the state turn a corner in its efforts to contain an outbreak that has killed more than 4,500 Texans.

Throughout the summer, Texas’ coronavirus outbreak became grimmer by the day and by almost every metric: case counts, hospitalizations, deaths. But in the past week or so, Abbott and some of the state’s public health officials began to see hope in the daily case counts as they appeared to stabilize.

A growing body of evidence points to widespread mask-wearing as an effective strategy for containing the virus, and one North Texas researcher’s statistical analysis published this week argued that local mask orders in the region reduced viral transmission enough to avoid a lockdown. The governor, who has faced blistering criticism for his handling of the pandemic from members of his own political party, immediately seized upon those findings in defense of his statewide order.

“A community lock down is not needed as long as masks & other distancing strategies are used,” Abbott wrote Monday on Twitter, citing the analysis by Rajesh Nandy, a professor of biostatistics and epidemiology at the University of North Texas Health Science Center.

But public health experts warn that more restrictive lockdowns may still be appropriate in the state’s hardest-hit regions, as the disease continues to infect about 10 times as many people each day compared with two months ago, ravaging some parts of the state more severely than others.

State data now appears to show new daily infections leveling off, albeit at nearly record highs. There were around 9,100 daily new cases of the virus on average over the past week. The state recorded its largest number of daily new cases July 15, at 10,791. On Thursday, that number was 9,507.

“The downside is even though we are approaching another plateau, we are at a much higher level than in May,” Nandy said.

Yes, it would be good news if the case rate stops going up. But it won’t truly be good news until the number of infections starts to go down, and then continues to go down. You know, like it has in New York and Europe and Asia and other places with generally functional governments. It’s when we get the virus down to levels at or below where we were when we first shut down back in March that we can truly contemplate things like safely sending kids back to school and reopening the economy. You’d think this would be something that would be better understood by the elected officials who have been so resistant to taking basic measures to fight COVID-19 – poll data consistently shows that the public understands this, even if they’re not always great about doing it in the absence of leadership – but clearly for some people, these things have to be learned the hard way. And as they are learning this, the hospitals are still at capacity, and could get overwhelmed at any time.

The irony there is that it may take another broad, mostly national shutdown to get to the point we want to get to. That won’t happen under this President, and if it’s still a necessary thing under the next one, then my god have we effed this up beyond all comprehension. In the meantime:

Now Starr County is at a dangerous “tipping point,” reporting an alarming number of new cases each day, data show. Starr County Memorial Hospital — the county’s only hospital — is overflowing with COVID-19 patients.

The county has been forced to form what is being compared to a so-called “death panel.” A county health board – which governs Starr Memorial – is set to authorize critical care guidelines Thursday that will help medical workers determine ways to allocate scarce medical resources on patients with the best chance to survive.

A committee will deem which COVID-19 patients are likely to die and send them home with family, Jose Vasquez, the county health authority, said during a news conference Tuesday.

“The situation is desperate,” Vasquez said. “We cannot continue functioning in the Starr County Memorial Hospital nor in our county in the way that things are going. The numbers are staggering.”

That’s the same Starr County that was once lauded for its low infection rate and ability to keep the virus under control. That was back when local officials had the authority to make and enforce shelter-in-place orders, before Greg Abbott took that authority away. Starr County now plans to issue a new shelter in place order, though of course they won’t be able to enforce it. Greg Abbott could let them enforce it, and he could let other local governments that want to take a step back in an effort to get their numbers down do so, but that’s not something he has any interest in doing. And so here we are.

The Muscovy ducks of Pearland

The things you learn.

The bird sanctuary city of Pearland is encouraging residents to take matters into their own hands to address the growing problem of Muscovy ducks that have reportedly taken residence in the city.

Known for their red, warty-spotted faces and black, white, and brown plumage, Muscovy ducks are often considered a “problem duck.” Feral populations of Muscovy ducks are known to be aggressive and can cause property damage, transmit disease and create problems through competition with native species, according to the U.S. Fish and Wildlife Service.

According to the city of Pearland, the ducks have been spotted throughout the city, often frequenting the neighborhoods of West Oaks and Westwood Village. In response to the growing population, the city has advised residents they can lawfully shoot or dispose of the animals themselves.

“The general public has the legal authority to address the ducks—including Muscovy duck nests, eggs, and hybrids—on their property, without the requirement of a permit,” the city stated in a Nov. 1 release.

Residents are allowed to shoot and kill the ducks on their own property if: they are allowed permission by their respective homeowner’s association or landowner; if they are located outside of city limits; and if they use a nontoxic shot or nontoxic bullets, according to the release. The discharge of a firearm is “generally illegal” inside city limits.

If a resident destroys a duck within the city’s legal parameters, they must dispose of the animal through burial or incineration. Residents are not allowed to keep, consume, sell, offer to sell the duck or release the duck in another location.

Instead of shooting, residents can capture and transport the animals to Hidalgo, Starr, or Zapata County. A 2010 law deemed Muscovies an invasive species in the U.S. with the exception of these counties, where they are considered native and can be released, according to the Texas Wildlife Rehabilitation Coalition (TWRC.)

Turns out Muscovy ducks have been a problem for a few years now, and not just in Texas. And now it’s pitting neighbor against neighbor, as some just want to be kind to their web-footed friends while others…do not. I literally had no idea about any of this. Thanks to Mary Flood for flagging this.