I'd suggest reading prior discussions of the so-called "poor meat eater problem."
I see a few problems with this argument. (These are mostly not original ideas.)
- This argument would likely reflect badly on EA and/or animal advocacy if it became more common and more public. Unpopular arguments may be worth it if the benefits of arguing them outweigh the costs, but that seems unlikely here.
- If you believe farmed animal welfare is the cause area that warrants the highest priority, then you should be looking for the most cost-effective interventions within that cause area. There are interventions in this area that seem very cost-effective, such as corporate campaigns, and it seems unlikely that persuading EAs working in global poverty that their interventions are harmful, or pursuing human population control interventions instead, is anywhere near as cost-effective.
- This analysis looks at one potential flow-through effect of EA global poverty interventions, and does not consider any others that could potentially benefit animals:
- Good things can lead to more good things, e.g. Open Phil has recommended $80 million in effective grants towards farmed animal welfare, but they would not exist if GiveWell had not established their credibility in global poverty. (Open Phil started out as a GiveWell project called GiveWell Labs.)
- Solving human problems may free up resources for solving animal welfare problems.
- Increases in human population and/or consumption may lead to decreases in wild animal populations, which may reduce wild animal suffering.
- It's better if EAs working on global poverty and animal welfare are cooperative rather than antagonistic.
It would probably help (me, at least) if you were a bit more specific about what ethical system you're using.
Some of your post seems like it's using a harmed/not-harmed dichotomy (which doesn't seem like a very useful metric to me, but might be more compelling to others), while other parts seem to be going more for minimising-net-suffering / maximising-total-wellbeing kinds of metrics.