Nutrition, Microbiomes, and Colony Health with the Carl Hayden Lab Team (404)

WEBVTT

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Hey, this is Bob and this is Chris from Hive

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Noon.

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We're from Dayton, Ohio, and this

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welcome to beekeeping today.

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Welcome to Beekeeping Today podcast presented by Better

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Bee, your

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source for beekeeping news, information, and entertainment.

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I'm Jeff.

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And I'm Becky Masterman.

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Today's episode is brought to you by the Bee Nutrition superheroes at Global Patties.

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com and give your bees the nutrition they deserve.

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Hey, a quick shout out to Betterbee and all of our sponsors

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whose support allows us to bring you this podcast each week without resorting to a fee-based subscription.

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You can find it all at www.

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beekeepingtoday.

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com.

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Thank you, Bob and Chris, for that great opening from the North American Honey Bee Expo.

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You know, Becky, I used to live near Dayton, Ohio.

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I used to live in Huber Heights.

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Huber

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Heights, Ohio.

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That's a great name for a town.

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It

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it

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was

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a great place to grow up.

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You know, it's not too far from the right

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Patterson Air Force Base and I remember

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no, I'm dating myself here, but you know, that was before they restricted sonic booms.

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And the jet fighters from uh

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Wright-Patterson would fly over in the sonic booms all the time was

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uh I guess that's why I like

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thunderstorms so much.

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That's great.

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Well thank you, Mark Rifris.

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No, I want to know when they restricted sonic booms.

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I

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you know, that's a good question.

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Maybe we should look it up.

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You know, if you find that out, I'll give you a hive tool.

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Oh, that's exciting.

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Wait, do I get the hive

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tools?

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Okay, this is fair.

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This is great.

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Okay, let's move on to beekeeping.

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Beekeeping.

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Thank you, Bob and Chris.

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Appreciate it.

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Becky, it's I can't believe it's September.

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This year is just flying

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by.

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Yes,

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except there's

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there's plenty to do, right?

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Oh my god.

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We just have less time to do it.

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That is the truth.

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That is the truth.

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I still need to paint some equipment, so

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do you think I'm behind this year?

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Well, at least it's assembled.

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It's assembled.

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Yes, yes.

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But I do have some unpainted equipment out there that I need to

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um exchange with painted equipment so I can not feel super guilty

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exposing them to a Minnesota winter.

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The fall is the time when I have the greatest angst over my bees

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because

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all

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of the

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things I put off

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All of the things I neglected.

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All of the things I know I should have done but didn't do because I chose

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to do something else

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show up

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because you know the

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row is too big

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or the colony is weak

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Or

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and I'm saying every anytime, you know, bees die naturally, but every time there's a weak colony I said, I should have done something better.

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Fall

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is hard that way.

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It seems like you're about to write a poem called The Guilty Beekeeper.

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A woeful

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poem.

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What a great book that would be.

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It would be a

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book of poems.

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sad, morose poems.

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Nobody's buying that book.

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Yeah, no, it

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it's it's always that's the

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uh the tricky part of the year for a lot of beekeepers

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is that they're running out of time.

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as far as the nights are starting to get cooler, if they need to get feed on the bees, they only have a certain amount of time

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when you're looking at Varroa control, although I think it's always appropriate

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if you've got a problem

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the efficacy is going to change based upon how long the bees have to

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really raise those winter bees without mite pressure.

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So

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it is it's a it's a tough, tough time of year.

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And so hopefully

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All of our listeners are ahead of the game instead of behind

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s

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in getting their bees

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ready for winter, regardless of the kind of winter they get to g go through.

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Do as we say and as our guests say, don't do as we do.

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Well I'm good with Varroa control

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and feeding.

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I'm on that.

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I just have unpainted equipment, Jeff.

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That's all I'm worried about right now.

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That's on me, and I have to pay more for it if it

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if it

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I guess if I

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if it goes through too much wear and tear.

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So

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yeah.

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The bees are fine.

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The late Kim Flottum

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used to have all sorts of equipment unpainted and that's just the way it was.

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So there you go.

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Then I'm in good company

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if I

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if I don't get paint on it.

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Although I I have the paint purchased.

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It's a beautiful lilac

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color, so

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very excited about that.

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You'll be ready for the spring

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We have

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for our Hive IQ

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tool today, we have a question from Burton

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Scripture.

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Now, the Hive IQ question is a giveaway we have for our sponsor, Hive IQ.

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They've given us a quantity of hive

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tools, bright and shiny, with uh hive

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IQ on it and beekeeping today.

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And for those listeners who send us a question and we are able to answer it online

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,

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We will send that listener a brand new hive tool.

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So we have one for Bri

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Burton.

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Did I say Brian before?

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You know you said Burton.

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Are we allowed to say that

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this is a name I recognize?

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Well you know so many people and you've met so many in your

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in your meetings.

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Yeah.

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Just a few.

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I recognize this name

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What is Bert

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looking for as far as a question and an answer?

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He wrote us um

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a nice short question.

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It says, what is the proper

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or

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best way to prepare plastic frames and foundation before

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placing in the hive for the bees to use.

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So

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I wonder if Bert's thinking about next spring already.

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Do you think he's like

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all set for twenty

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twenty six and he's looking forward to twenty twenty seven?

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Right now.

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That's true.

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That would be a disaster.

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Don't do that, Bert.

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That's a good question.

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So

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Jeff, what do you what do you

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advise as

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as far as doing any prep work for plastic frames and foundation?

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If it's brand new, it should be

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waxed

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and I don't do anything extra

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and I use

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it.

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I

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I do not use plastic frames, so I don't have any direct experience with that, but I do use a good amount of plastic foundation

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That

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said, I know some people

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like

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to reuse their plastic foundation because they don't want to throw it out and put it in a landfill or

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whatever, and they scrub it clean, pressure wash it, and then what do you do with it?

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How do you prep it?

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And for that, the best approach is to apply

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a fresh coat of real

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beeswax

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using a roller or a uh

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brush.

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And then

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the more wax on there the

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the

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crater and the quicker the bees accept it.

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So are you saying hot wax then with the brush?

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Yes, hot wax.

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You melt the wax

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Carefully, double boiler.

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Like double boilers?

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Double boiler.

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You don't have any

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no fires.

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No flare-ups, please.

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And then you brush it on or roller it on.

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Onto the frame, onto the foundation.

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So this smells good.

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This smells good.

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It's a fun job that

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smelling activity.

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You can tell I've actually

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I really have never put any extra wax on foundation.

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And I've also never pressure

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washed a frame

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or a foundation

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in order to put it back in the colony.

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So

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so I'm glad you understand.

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If I could admit

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something

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is that I don't reuse foundation.

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I punch it out and I throw it away.

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I feel guilty, but that's just time

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consuming for me to pressure wash it and reuse it and melt wax and put it back on.

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And it's also, yeah, it's just time consuming.

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I just don't have the time to do that.

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Yeah, and it's hard, even I mean, even I th

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I bet some people are scraping that wax off and rendering

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it

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and I just worry about pesticides when you get to that level.

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If you're going to replace the foundation and it's been drawn out

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and

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and

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used for the last five, six years, then I'm just worried what's in that wax.

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So

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let's not judge.

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Let's not judge each other.

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How's that?

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So that we don't get judged.

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I don't want to be judged.

00:08:36.459 --> 00:08:39.899
I will say though, talking about applying wax to a foun a plastic foundation

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this last summer

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when we spoke at the North uh North Dakota Beekeepers meeting or the tri-states

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meeting and I stopped in at

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Premier

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Bee

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products

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And that's a short that we've produced.

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To see how they pre-wax

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thousands of sheets of foundation every day.

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was amazing.

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The machine that spits them through and it sprays them, it cools them.

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It just it's an amazing process.

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It's

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it's

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not a bunch of people with paintbrushes and rollers of

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hot

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wax.

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And I know that

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I know that a lot of places when you're ordering

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that wax foundation, you can order double wax or triple wax even, right?

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So

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And typically they say that the more wax on the foundation

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the quicker the bees accept it.

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So that's something to keep in mind.

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I just make my bees work harder and just give 'em one layer or so.

00:09:28.620 --> 00:09:29.100
Well you

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you also live in an area where you have great nectar flows.

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Yeah, yeah, they

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usually don't have a problem.

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Yeah, that's really great.

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Hey, today's guest, this last summer I was

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went to the COLOSS

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meeting in Pullman, Washington, and I met Dr.

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Vanessa

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Corby

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Harris and her team, Mark

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Carroll and Kirk Anderson.

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They were there representing the USDA-ARS Carl Hayden Bee Research Center.

00:09:54.220 --> 00:09:55.580
Fantastic people.

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They agreed to be on the show and talk to us about what they're doing in the lab.

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I'm really looking forward to talking to 'em.

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I love a USDA

00:10:03.020 --> 00:10:05.580
bee researcher, so this should be a lot of fun.

00:10:05.580 --> 00:10:08.700
Well we'll hear from them as soon as we get back from this short word

00:10:08.860 --> 00:10:10.140
from our sponsors.

00:10:11.100 --> 00:10:14.220
For more than 45 years, BetterBee

00:10:14.380 --> 00:10:22.700
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00:11:00.180 --> 00:11:01.700
Hey everybody, welcome back.

00:11:01.700 --> 00:11:04.340
Sitting around this great big virtual beekeeping today

00:11:04.580 --> 00:11:05.780
podcast table.

00:11:05.780 --> 00:11:06.740
We have Dr.

00:11:06.740 --> 00:11:07.380
Vanessa

00:11:07.620 --> 00:11:09.620
Corby Harris.

00:11:09.240 --> 00:11:09.640
Dr.

00:11:09.640 --> 00:11:10.440
Kirk Anderson

00:11:10.600 --> 00:11:11.080
and Dr.

00:11:11.080 --> 00:11:13.320
Mark Carroll, all from the Carl Hayden

00:11:13.480 --> 00:11:15.080
honey bee Research Lab

00:11:15.240 --> 00:11:17.320
in Tucson, Arizona.

00:11:17.160 --> 00:11:18.920
Send some of the warmth this way.

00:11:18.920 --> 00:11:20.600
I'm glad you're here.

00:11:21.640 --> 00:11:22.920
Thank you.

00:11:23.160 --> 00:11:23.960
Welcome.

00:11:23.960 --> 00:11:27.320
This is so exciting to have the three of you here.

00:11:27.000 --> 00:11:28.520
It's going to be a great hour.

00:11:28.520 --> 00:11:34.040
Please introduce yourself and uh tell us a little bit about yourself and how you got interested in bees.

00:11:34.040 --> 00:11:37.560
And then then we'll pass the virtual mic around to everybody else.

00:11:37.420 --> 00:11:43.819
Okay, yeah, so Vanessa Corby-Harris, I'm a research insect physiologist

00:11:43.980 --> 00:11:45.259
is my, I guess

00:11:45.880 --> 00:11:48.280
formal title at the USDA-ARS lab

00:11:48.440 --> 00:11:49.800
here in Tucson.

00:11:49.800 --> 00:11:51.160
So yeah, I guess

00:11:51.320 --> 00:11:56.360
as my title sort of suggests, I have a background in insect physiology.

00:11:56.360 --> 00:11:56.680
So

00:11:56.800 --> 00:11:58.080
I got my PhD

00:11:58.240 --> 00:12:00.000
at the University of Georgia

00:12:00.240 --> 00:12:02.080
and that was in genetics

00:12:02.240 --> 00:12:04.640
and then I came to Arizona

00:12:04.820 --> 00:12:05.460
to do

00:12:05.780 --> 00:12:06.100
a

00:12:06.420 --> 00:12:08.180
postdoc fellowship

00:12:08.340 --> 00:12:09.780
working on mosquitoes

00:12:09.940 --> 00:12:10.740
actually.

00:12:10.740 --> 00:12:14.180
So we were working on mosquitoes and trying to make them

00:12:14.640 --> 00:12:16.240
less friendly to malaria

00:12:16.560 --> 00:12:18.480
using different genetic approaches.

00:12:18.480 --> 00:12:20.800
So that's where I got a lot of my

00:12:21.040 --> 00:12:24.080
true hardcore physiology training.

00:12:24.040 --> 00:12:29.959
And so that was uh a postdoc that was ending, gosh, I can't even remember how long ago.

00:12:29.959 --> 00:12:30.440
I guess

00:12:30.600 --> 00:12:33.000
20, that was 2010.

00:12:33.000 --> 00:12:33.320
So

00:12:33.560 --> 00:12:34.920
I was sort of

00:12:35.500 --> 00:12:43.819
In the insect world, and Kirk and I, we were postdocs together at this in this fellowship program at the University of Arizona.

00:12:44.000 --> 00:12:46.480
And I was sort of looking for my next step

00:12:46.639 --> 00:12:48.720
and Kirk said, hey, come

00:12:48.959 --> 00:12:50.480
come work with us on bees.

00:12:50.560 --> 00:12:54.639
And so that's that was actually how I got started in bees.

00:12:54.639 --> 00:12:57.120
I was actually a postdoc with Kirk for

00:12:57.440 --> 00:12:58.240
gosh, forty

00:12:58.480 --> 00:12:59.840
was it three or four or five?

00:12:59.840 --> 00:13:00.240
I don't know.

00:13:00.240 --> 00:13:01.440
It was a long time.

00:13:01.440 --> 00:13:03.920
That's how I got my start with bees.

00:13:03.920 --> 00:13:09.040
And it turned out that a lot of the skills that I had learned

00:13:09.240 --> 00:13:09.400
with

00:13:09.640 --> 00:13:12.680
regards to insect physiology and

00:13:13.000 --> 00:13:14.600
insect nutrition

00:13:14.920 --> 00:13:19.880
was very applicable to a lot of the questions that they were studying here.

00:13:19.880 --> 00:13:22.040
And so that was my entree into bees

00:13:22.200 --> 00:13:22.440
and

00:13:22.660 --> 00:13:28.020
So yeah, I started that in, I guess that was actually 2011 that I started at the B

00:13:28.260 --> 00:13:28.980
lab.

00:13:28.980 --> 00:13:33.220
Since 2015, I've been a scientist here with my own lab.

00:13:33.060 --> 00:13:34.580
Yeah, I've been here for a while

00:13:34.740 --> 00:13:35.460
too, got

00:13:35.620 --> 00:13:36.500
my PhD at

00:13:36.660 --> 00:13:39.540
Arizona State, then came to the U of A

00:13:39.860 --> 00:13:40.180
as

00:13:40.740 --> 00:13:42.660
Vanessa mentioned, and

00:13:43.240 --> 00:13:46.440
I was working on ants, so I'm really uh a social

00:13:46.760 --> 00:13:47.640
insect

00:13:47.960 --> 00:13:49.000
ecologist.

00:13:49.000 --> 00:13:52.920
I've done a lot of landscape work on both ants and uh

00:13:54.040 --> 00:13:59.320
and honey bees, long enough to know how horrifying landscape work can be, right?

00:13:59.880 --> 00:14:04.600
Oh let's go out in the world and do these things and then see what happens, right?

00:14:04.600 --> 00:14:05.160
But uh

00:14:05.320 --> 00:14:07.640
it's very difficult at at any rate.

00:14:07.640 --> 00:14:07.959
So

00:14:08.240 --> 00:14:12.640
Uh ironically, the ecology I work on is invisible.

00:14:12.640 --> 00:14:14.880
So I work on the honey bee microbiome

00:14:15.120 --> 00:14:18.320
and largely studying health and disease here

00:14:18.740 --> 00:14:18.900
So

00:14:19.060 --> 00:14:23.620
really it's just uh, you know, bacteria shared among niches and

00:14:23.860 --> 00:14:25.300
developmental states

00:14:25.460 --> 00:14:28.500
and queens and larvae and workers

00:14:28.660 --> 00:14:28.980
and

00:14:29.240 --> 00:14:29.400
how

00:14:29.560 --> 00:14:33.720
that influences their survival and their disease susceptibility.

00:14:33.720 --> 00:14:36.120
So I've studied, you know, the queen microbiome

00:14:36.360 --> 00:14:37.880
in extensively.

00:14:37.880 --> 00:14:39.160
This work only studies

00:14:39.480 --> 00:14:40.360
really started,

00:14:40.520 --> 00:14:43.960
Vanessa was in on the beginning of this work.

00:14:43.339 --> 00:14:45.420
and did just meticulous work.

00:14:45.420 --> 00:14:48.779
This is when I got to learn what a meticulous researcher of

00:14:48.940 --> 00:14:49.420
Vanessa

00:14:49.660 --> 00:14:49.819
is

00:14:49.980 --> 00:14:50.300
and

00:14:50.459 --> 00:14:52.540
really strives for perfection and

00:14:52.779 --> 00:14:54.220
just fantastic work.

00:14:54.220 --> 00:14:55.420
But the uh yeah, we

00:14:55.579 --> 00:14:57.660
moved into a number of different

00:14:58.000 --> 00:15:02.720
areas, plant compounds that affect, you know, host microbial health.

00:15:02.720 --> 00:15:02.880
Um

00:15:03.360 --> 00:15:04.240
Vanessa, we

00:15:04.399 --> 00:15:06.639
looked at short chain fatty acids and Vanessa

00:15:06.800 --> 00:15:07.839
's become like the

00:15:08.380 --> 00:15:08.940
the uh

00:15:09.260 --> 00:15:11.660
main component of fatty acid research

00:15:11.820 --> 00:15:12.060
uh

00:15:12.380 --> 00:15:13.500
tell you a lot more

00:15:13.740 --> 00:15:16.380
and all sorts of different fats

00:15:17.120 --> 00:15:19.040
I'm not sure how to say it correctly.

00:15:19.040 --> 00:15:20.560
I guess you can tell us later.

00:15:20.560 --> 00:15:23.920
Yeah, we've worked out a lot of different things from diet to

00:15:24.160 --> 00:15:25.279
to disease

00:15:25.519 --> 00:15:25.839
and

00:15:26.440 --> 00:15:27.080
And now

00:15:27.240 --> 00:15:27.320
I

00:15:27.480 --> 00:15:27.560
'm

00:15:27.720 --> 00:15:28.440
with Mark

00:15:28.600 --> 00:15:29.080
we're

00:15:29.240 --> 00:15:32.200
I'm working on the Varroa mite

00:15:32.360 --> 00:15:32.520
because

00:15:32.680 --> 00:15:34.840
it seems to be a problem in beekeeping.

00:15:34.840 --> 00:15:36.600
I don't know if you've heard about it

00:15:36.640 --> 00:15:36.800
But

00:15:40.080 --> 00:15:41.440
everyone's afraid of trophy

00:15:41.840 --> 00:15:42.080
laps

00:15:42.240 --> 00:15:44.400
now coming in, which it probably

00:15:44.720 --> 00:15:47.920
will, given the tight ship that's being run

00:15:48.320 --> 00:15:49.680
country to country.

00:15:49.680 --> 00:15:50.640
But yeah,

00:15:50.800 --> 00:15:52.320
I think that kind of

00:15:52.480 --> 00:15:54.960
is good for an introduction.

00:15:54.960 --> 00:15:55.760
Mark?

00:15:55.760 --> 00:15:56.800
If I can go ahead, um

00:15:56.960 --> 00:15:58.320
yeah, I'm Mark Carroll.

00:15:58.320 --> 00:16:00.240
I'm a research entomologist

00:16:00.480 --> 00:16:01.120
here.

00:16:00.959 --> 00:16:02.080
at uh Carl Hayden

00:16:02.240 --> 00:16:02.560
Bee.

00:16:02.560 --> 00:16:03.519
Research Center.

00:16:03.519 --> 00:16:08.880
Originally I came out of Mae Berenbaum's lab, uh, University of Illinois for my PhD

00:16:09.440 --> 00:16:11.279
and uh made my way to

00:16:11.900 --> 00:16:13.180
CMAVE, which is a U

00:16:13.420 --> 00:16:17.100
a USDA facility out in Gainesville, Florida, and they

00:16:17.340 --> 00:16:19.100
had some exciting adventures.

00:16:19.100 --> 00:16:19.500
Um we

00:16:19.660 --> 00:16:20.700
looked at plant uh

00:16:20.940 --> 00:16:22.380
plant compounds

00:16:22.820 --> 00:16:27.460
Now compounds that induce plant defenses, things found in caterpillar

00:16:27.620 --> 00:16:28.660
spit and so forth

00:16:28.820 --> 00:16:30.260
that turn on the full

00:16:30.839 --> 00:16:31.959
The full range.

00:16:31.959 --> 00:16:33.160
And uh when I was there

00:16:33.319 --> 00:16:38.680
we did find inceptins, which is one of the main ways that beans of all kinds

00:16:38.920 --> 00:16:39.240
detect

00:16:39.399 --> 00:16:39.560
or

00:16:39.720 --> 00:16:42.199
under attack and respond to things

00:16:42.520 --> 00:16:45.000
I did, however, this was at the height uh

00:16:45.160 --> 00:16:46.760
around 2008

00:16:47.080 --> 00:16:51.960
of all the problems that we were having with bees in the great expansion.

00:16:51.600 --> 00:16:51.839
And

00:16:52.000 --> 00:16:55.759
like so many other people, I was given an opportunity to jump into bees.

00:16:55.759 --> 00:16:56.560
Peter Teel

00:16:56.720 --> 00:17:00.639
memorably said to me, he goes, Mark, do you want to go out there and learn

00:17:00.800 --> 00:17:00.959
you know

00:17:01.120 --> 00:17:02.319
work on bees and grow it?

00:17:02.319 --> 00:17:03.120
And I said, Um

00:17:03.360 --> 00:17:05.360
it's it's a fascinating uh field

00:17:05.520 --> 00:17:06.240
and he goes

00:17:06.260 --> 00:17:08.579
go out and get stung and do something, you know.

00:17:08.579 --> 00:17:09.299
And that was

00:17:09.539 --> 00:17:10.740
that was pretty much uh

00:17:10.900 --> 00:17:12.100
my introduction.

00:17:12.100 --> 00:17:15.939
I was just down the road from Jamie Ellis, so I had some great help with

00:17:16.179 --> 00:17:18.020
collaboration with them and Jerry

00:17:18.179 --> 00:17:20.179
Hayes and some of the other folks

00:17:20.140 --> 00:17:21.260
to get me going.

00:17:21.260 --> 00:17:28.540
And then I came over here to Carl Hayden, mainly to work on nutritional ecology, looking at nutritional effects, uh

00:17:28.700 --> 00:17:31.260
seasonal effects, effects the diet.

00:17:31.060 --> 00:17:31.220
with

00:17:31.380 --> 00:17:32.260
a little bit of a chemical

00:17:32.420 --> 00:17:32.900
ecology

00:17:33.140 --> 00:17:33.540
spin

00:17:33.780 --> 00:17:35.300
and chemistry.

00:17:35.300 --> 00:17:39.300
And it's been many things since then, but I've kind of gotten back

00:17:39.260 --> 00:17:40.780
to my roots uh lately.

00:17:40.780 --> 00:17:46.299
We're still doing chemical ecology looking at things like seasonal effects, uh overwintering.

00:17:46.299 --> 00:17:47.340
These are big problems.

00:17:47.340 --> 00:17:48.860
I don't think I have to sell that hop

00:17:49.020 --> 00:17:50.620
that one too hard.

00:17:50.620 --> 00:17:50.860
But

00:17:51.100 --> 00:17:54.380
some of the other big questions that I'm interested in are

00:17:54.540 --> 00:17:57.340
how colonies manage to coordinate together

00:17:57.660 --> 00:17:57.980
to

00:17:58.220 --> 00:18:03.740
work against stress, and by stress I mean pesticides, pathogens, mites

00:18:03.940 --> 00:18:07.700
poor nutrition, the whole nine yards, the big peas that they talk about.

00:18:07.700 --> 00:18:08.340
And also

00:18:08.580 --> 00:18:08.899
how

00:18:09.139 --> 00:18:09.779
how things

00:18:09.940 --> 00:18:11.700
uh can come apart and fail.

00:18:11.700 --> 00:18:14.179
And is there anything that we can do in particular

00:18:14.340 --> 00:18:17.539
to nudge them in a direction, give them support

00:18:17.560 --> 00:18:25.720
I'll come back to that, I think, a little later with this uh β-ocimene, which is kind of on the frontier of looking at how we might be able to improve uh

00:18:25.880 --> 00:18:28.120
brood rearing at times when

00:18:28.279 --> 00:18:28.440
the

00:18:28.600 --> 00:18:28.919
colony

00:18:29.159 --> 00:18:30.440
is actually under

00:18:30.600 --> 00:18:31.559
nutritional stress

00:18:31.720 --> 00:18:32.679
during dearth.

00:18:32.679 --> 00:18:34.279
It's kind of a fascinating topic

00:18:34.440 --> 00:18:38.519
and it's the work of many other people working with me as well.

00:18:38.540 --> 00:18:40.860
Well, we're gonna need three more hours.

00:18:40.860 --> 00:18:43.500
So everybody clear your schedules.

00:18:43.500 --> 00:18:44.860
This is gonna be a multi-part

00:18:45.020 --> 00:18:45.500
segment.

00:18:45.500 --> 00:18:45.580
Or

00:18:45.820 --> 00:18:46.220
multi-part

00:18:46.700 --> 00:18:47.420
episode.

00:18:48.060 --> 00:18:48.300
Oh

00:18:48.460 --> 00:18:48.620
well

00:18:48.780 --> 00:18:49.580
this is fantastic

00:18:49.740 --> 00:18:50.300
and this

00:18:50.460 --> 00:18:52.300
I'm not even sure where to start.

00:18:52.300 --> 00:18:53.260
Me too.

00:18:53.260 --> 00:18:53.660
Yeah, it

00:18:53.820 --> 00:18:54.460
it's it's

00:18:54.620 --> 00:18:55.580
I mean I'm I'm looking

00:18:55.740 --> 00:18:57.900
uh actually I see Kirk's table in the background

00:18:58.060 --> 00:18:58.140
is

00:18:58.380 --> 00:19:00.140
all these rocks and it just made me think of

00:19:00.300 --> 00:19:00.540
all

00:19:00.860 --> 00:19:02.460
there's so many things to choose from.

00:19:02.460 --> 00:19:03.900
Where do you start?

00:19:04.419 --> 00:19:05.780
Well I have guitars.

00:19:05.780 --> 00:19:09.059
I have guitars at home, but I can't bring 'em to work.

00:19:10.660 --> 00:19:10.900
Uh

00:19:11.059 --> 00:19:12.020
the pleasure of working

00:19:12.179 --> 00:19:12.820
from home.

00:19:13.480 --> 00:19:15.799
You just haven't set up the right experiment, Kirk.

00:19:15.799 --> 00:19:16.039
If you

00:19:16.200 --> 00:19:19.720
actually set up the right experiment, you'd have guitars at work.

00:19:20.039 --> 00:19:21.000
That is correct.

00:19:21.000 --> 00:19:23.400
Well they have an acoustic room in the basement.

00:19:23.400 --> 00:19:25.720
It's completely soundproof.

00:19:25.440 --> 00:19:25.519
W

00:19:25.919 --> 00:19:27.600
nobody really knows why it's there.

00:19:27.600 --> 00:19:29.360
We have our suspicions.

00:19:29.840 --> 00:19:30.159
But

00:19:30.880 --> 00:19:31.039
they

00:19:31.200 --> 00:19:33.840
can't hear you scream in space, is that what you're saying?

00:19:33.840 --> 00:19:34.080
Yeah.

00:19:37.120 --> 00:19:38.960
Okay, on another topic.

00:19:38.960 --> 00:19:39.760
What's the

00:19:39.860 --> 00:19:43.860
The big project, what are you most excited about that you're working on right now?

00:19:43.940 --> 00:19:45.779
I mean, I guess the problem is

00:19:45.940 --> 00:19:47.139
you could kind of get

00:19:47.380 --> 00:19:49.059
from our description of what we do

00:19:49.220 --> 00:19:52.019
is we're excited about everything, unfortunately.

00:19:52.019 --> 00:19:52.340
So

00:19:52.400 --> 00:19:52.720
So

00:19:52.880 --> 00:19:53.680
really it's a

00:19:53.840 --> 00:19:54.560
it's a ex

00:19:54.800 --> 00:19:58.080
it's an exercise in restraint in many ways

00:19:58.400 --> 00:19:58.720
because

00:19:59.040 --> 00:20:02.800
we have to focus on the things that we think are most important.

00:20:02.820 --> 00:20:03.140
So

00:20:03.380 --> 00:20:03.940
my my

00:20:04.260 --> 00:20:04.580
love

00:20:04.740 --> 00:20:08.340
is insect nutrition and insect physiology.

00:20:08.340 --> 00:20:10.020
So I'll start out with that.

00:20:10.020 --> 00:20:12.260
So I think that nutrition is

00:20:12.740 --> 00:20:14.580
one of the few things

00:20:14.740 --> 00:20:15.060
that

00:20:16.080 --> 00:20:16.640
I guess

00:20:16.880 --> 00:20:18.480
we can do something about.

00:20:18.480 --> 00:20:18.640
So

00:20:18.880 --> 00:20:20.559
bee nutrition.

00:20:20.559 --> 00:20:22.960
The topics that I look at are

00:20:23.120 --> 00:20:25.440
number one, what do bees need?

00:20:25.519 --> 00:20:27.039
What nutrients do they need?

00:20:27.039 --> 00:20:29.120
Number two, how do those needs change

00:20:29.360 --> 00:20:37.039
depending on different factors like where they're located, the time of year, different stressors that they're coming into contact with?

00:20:37.039 --> 00:20:39.200
It could be anything from pesticide

00:20:39.340 --> 00:20:39.500
to

00:20:39.820 --> 00:20:42.539
mites, disease, things like that.

00:20:42.539 --> 00:20:43.660
And the third one is

00:20:43.820 --> 00:20:49.580
once you have an idea of what they need and how those needs change due to those certain factors.

00:20:49.620 --> 00:20:51.140
How do you give those

00:20:51.300 --> 00:20:53.220
those things that are missing

00:20:53.540 --> 00:20:55.060
back to the bees?

00:20:55.060 --> 00:20:55.700
And so

00:20:56.020 --> 00:21:01.780
the two main ways that you can do that is number one by giving them access to

00:21:02.260 --> 00:21:04.580
uh you know, a diverse type of forage

00:21:04.900 --> 00:21:08.100
where they can get many different types of nectars

00:21:08.340 --> 00:21:09.620
and polls.

00:21:09.620 --> 00:21:10.980
That's always the best

00:21:11.300 --> 00:21:12.420
thing, right?

00:21:12.420 --> 00:21:13.860
Because it's natural.

00:21:13.860 --> 00:21:17.460
And bees are really good at collecting that stuff from plants.

00:21:17.860 --> 00:21:24.580
And then the second way though, because a lot of times stuff is not available on the landscape either due to

00:21:25.320 --> 00:21:27.240
Things like bad weather

00:21:27.480 --> 00:21:33.240
or the way that agriculture is nowadays, where we have monocropping systems, that would be

00:21:33.400 --> 00:21:33.640
we

00:21:33.880 --> 00:21:36.920
we can give it back to them using diets.

00:21:36.900 --> 00:21:37.140
So

00:21:37.380 --> 00:21:38.420
supplements.

00:21:38.420 --> 00:21:41.620
The reason why I think that is so important

00:21:42.500 --> 00:21:47.460
is just basically the reality of the system now that we're working with.

00:21:47.460 --> 00:21:47.780
So

00:21:48.260 --> 00:21:50.340
There's a lot of stuff that we have no control

00:21:50.500 --> 00:21:50.980
over.

00:21:50.980 --> 00:21:53.700
Obviously, we don't have any control over weather.

00:21:53.700 --> 00:22:00.419
I don't think that I personally am going to be changing the way that modern agriculture is nowadays.

00:22:00.940 --> 00:22:04.460
And so, you know, we're left with those things that we can control

00:22:04.940 --> 00:22:05.260
and

00:22:05.580 --> 00:22:11.659
things like, you know, can we provide them different types of diets that are improved?

00:22:11.440 --> 00:22:13.039
compared to what we have now.

00:22:13.039 --> 00:22:15.600
I don't want to develop an entirely new diet.

00:22:15.600 --> 00:22:19.039
I think there's a lot of stuff on the market that is a good starting place

00:22:19.500 --> 00:22:20.299
But essentially

00:22:20.539 --> 00:22:26.299
can we add little components to that might kind of give them a nudge in a positive direction?

00:22:26.380 --> 00:22:29.580
The way that you evaluate whether bees are well

00:22:29.740 --> 00:22:34.059
fed is going to be different than uh how a beekeeper would do it.

00:22:34.500 --> 00:22:34.740
So

00:22:34.899 --> 00:22:35.220
how do

00:22:35.460 --> 00:22:39.220
how did you connect your research to the beekeepers?

00:22:39.220 --> 00:22:39.539
Because

00:22:39.700 --> 00:22:43.860
I think it's hard for especially for newer beekeepers to say, oh, this colony.

00:22:43.779 --> 00:22:44.019
has a

00:22:44.179 --> 00:22:45.779
has a nutrition deficit.

00:22:45.779 --> 00:22:47.620
Could you expand on that a little bit?

00:22:47.620 --> 00:22:48.260
Yeah, yeah.

00:22:48.260 --> 00:22:50.580
Thanks for giving me that opportunity.

00:22:50.580 --> 00:22:50.899
So

00:22:51.380 --> 00:22:53.620
essentially it's really hard to tell

00:22:53.779 --> 00:22:55.940
just based on the adults.

00:22:55.720 --> 00:22:55.880
what

00:22:56.360 --> 00:22:59.320
you know the adults they kind of all look the same

00:22:59.640 --> 00:22:59.880
so

00:23:00.040 --> 00:23:01.480
so it's not the adults

00:23:01.720 --> 00:23:04.920
you have to open up the hive to essentially see

00:23:05.240 --> 00:23:06.760
you know what's going on

00:23:06.880 --> 00:23:12.880
So it's gonna be things like the boot area is smaller than it should be at that particular time of year.

00:23:12.880 --> 00:23:13.760
I think that

00:23:14.160 --> 00:23:14.720
you know

00:23:14.960 --> 00:23:21.040
We have to learn from each other in terms of what would be typical for a colony at that particular location

00:23:21.200 --> 00:23:22.720
at that time of year.

00:23:22.720 --> 00:23:25.040
So, you know, that's going to be different.

00:23:24.940 --> 00:23:30.139
depending on location, but things like do they have brood, do they have all the stages of

00:23:30.380 --> 00:23:33.580
open and sealed brood, those sorts of things?

00:23:33.580 --> 00:23:38.139
Do they have stores at times of year where they should have stores

00:23:38.740 --> 00:23:42.820
Especially going into winter, you want to have plenty of pollen

00:23:43.140 --> 00:23:43.460
and

00:23:43.780 --> 00:23:45.299
nectar in the hive

00:23:45.620 --> 00:23:46.340
so that they're

00:23:46.820 --> 00:23:49.059
set up for success going in.

00:23:49.340 --> 00:23:53.820
And I mean I guess the one thing you can tell from the adults is just look at the hive entrance.

00:23:53.820 --> 00:23:57.500
Are they bringing anything in when they should be bringing things in?

00:23:57.500 --> 00:23:59.260
Those are important.

00:23:59.260 --> 00:23:59.900
Now

00:24:00.780 --> 00:24:04.860
We do measure those things in our in our studies.

00:24:04.860 --> 00:24:11.580
However, a lot of my earlier work, especially you know, when we bring up topics like physiology.

00:24:11.760 --> 00:24:16.240
That's kind of a really weird term for folks that are not familiar with it.

00:24:16.240 --> 00:24:19.200
And I just use it very casually, but

00:24:19.520 --> 00:24:21.760
but the reason why is because

00:24:22.880 --> 00:24:25.840
Every bee has their own way

00:24:26.160 --> 00:24:26.480
of

00:24:26.720 --> 00:24:29.280
dealing with what's coming into their bodies

00:24:29.440 --> 00:24:33.040
and how they're going to give that back to their hives.

00:24:33.120 --> 00:24:34.160
And essentially

00:24:34.320 --> 00:24:40.800
how they manage that input and output ratio, that's going to end up manifesting in things like brood

00:24:41.040 --> 00:24:46.080
Okay, it's gonna end up manifesting in the amount of nutrient storage that there have.

00:24:46.080 --> 00:24:48.080
So for example, the nurse

00:24:48.240 --> 00:24:48.720
fees

00:24:49.120 --> 00:24:52.560
The young nest bees, they're the ones that

00:24:52.720 --> 00:24:54.880
eat you know most of the pollen

00:24:55.120 --> 00:24:56.720
coming into the colony

00:24:56.860 --> 00:25:03.740
Now, if the queen is laying a bunch of eggs and they're rearing a bunch of brood, it might be normal to not see that much pollen

00:25:03.899 --> 00:25:04.539
stored

00:25:04.400 --> 00:25:07.120
but you're going to see a lot of brood, okay?

00:25:07.120 --> 00:25:09.360
And it's going to be of all different life stages

00:25:09.520 --> 00:25:14.480
because those nurse bees turn that pollen, they metabolize it.

00:25:14.679 --> 00:25:15.000
And

00:25:15.159 --> 00:25:17.080
they make it into brood food.

00:25:17.080 --> 00:25:27.080
Now, as foragers, they get older, they're, you know, they start out as nurse bees and then they work their way up in age and they turn into foragers.

00:25:27.019 --> 00:25:28.220
Bees that are

00:25:28.460 --> 00:25:29.899
malnourished

00:25:30.220 --> 00:25:30.539
in

00:25:32.460 --> 00:25:35.820
their younger lives, they're obviously not going to be doing so well

00:25:35.980 --> 00:25:37.899
later on in their lives.

00:25:37.919 --> 00:25:38.240
So

00:25:38.559 --> 00:25:41.120
that might turn out to be things like

00:25:41.280 --> 00:25:46.320
you're not they're not foraging for the same amount of resources as you would expect.

00:25:46.320 --> 00:25:48.480
So they're not collecting the stuff that they might

00:25:48.640 --> 00:25:50.880
that they should at that time of year

00:25:50.760 --> 00:25:53.720
And all of this basically comes back to the

00:25:53.960 --> 00:25:56.520
how the individual managed that

00:25:56.679 --> 00:26:00.039
the nutrients coming in and the nutrients going out.

00:26:00.120 --> 00:26:00.440
And

00:26:00.680 --> 00:26:06.920
that individual has to, I mean, when we say manage those things, that individual has to make

00:26:07.080 --> 00:26:09.240
a lot of choices in the hive

00:26:09.340 --> 00:26:11.179
You know, are they feeding brood?

00:26:11.179 --> 00:26:12.620
Are they supporting the queen?

00:26:12.620 --> 00:26:13.500
Things like that.

00:26:13.500 --> 00:26:16.539
So, but to answer your question briefly

00:26:20.100 --> 00:26:20.419
That

00:26:20.659 --> 00:26:22.500
input to output ratio

00:26:22.659 --> 00:26:26.899
and how those bees individually deal with those nutrients

00:26:27.040 --> 00:26:32.800
Whether or not that is successful is going to come out in things like brood and food stores.

00:26:32.800 --> 00:26:33.920
And that's what the beekeeper

00:26:34.160 --> 00:26:34.800
can see

00:26:34.740 --> 00:26:38.660
You're using a series of like biomarkers, aren't you, to m

00:26:38.820 --> 00:26:40.340
make measurements.

00:26:40.340 --> 00:26:42.100
Could you briefly

00:26:42.420 --> 00:26:43.060
share

00:26:43.380 --> 00:26:43.700
that

00:26:44.020 --> 00:26:44.740
information?

00:26:45.060 --> 00:26:46.660
Yeah, absolutely.

00:26:46.620 --> 00:26:46.940
So

00:26:47.100 --> 00:26:51.340
one of the biomarkers that we use a lot these days is fat

00:26:51.580 --> 00:26:53.020
body content.

00:26:53.180 --> 00:26:59.340
That's another term that we use that maybe not everybody knows about, but uh the fat body is essentially

00:26:59.500 --> 00:27:01.260
it does a lot of stuff in insects.

00:27:01.900 --> 00:27:02.220
It

00:27:02.460 --> 00:27:03.100
stores

00:27:03.340 --> 00:27:11.500
nutrients, so it stores protein that the individual consumes, it stores lipids or fats that the individual consumes.

00:27:11.620 --> 00:27:12.660
It's also

00:27:12.980 --> 00:27:15.620
a really key tissue for how that

00:27:15.780 --> 00:27:21.380
uh the physiology, sorry to use that term again, the physiology of the bee.

00:27:21.380 --> 00:27:26.100
So it produces things like antimicrobial peptides that might help

00:27:26.320 --> 00:27:26.480
the

00:27:26.640 --> 00:27:29.920
the bee to fight infection, things like that.

00:27:29.920 --> 00:27:30.240
So

00:27:30.480 --> 00:27:35.120
when we're looking at the fat body, we take that individual bee

00:27:35.780 --> 00:27:36.100
And

00:27:36.740 --> 00:27:37.060
we

00:27:37.380 --> 00:27:40.740
unfortunately have to collect them from the colony

00:27:40.980 --> 00:27:41.300
and

00:27:41.620 --> 00:27:43.220
we dissect them

00:27:43.760 --> 00:27:44.080
and

00:27:44.399 --> 00:27:45.919
we can measure the

00:27:46.240 --> 00:27:47.360
amount of

00:27:47.600 --> 00:27:47.840
say

00:27:48.000 --> 00:27:50.799
lipids and proteins in those bees.

00:27:50.799 --> 00:27:51.120
That

00:27:51.279 --> 00:27:55.200
is a good measure of, that's a good biomarker

00:27:55.360 --> 00:27:57.760
for how healthy the bees are.

00:27:57.620 --> 00:28:07.220
And the reason why that is, based on the individual but also the colony, is because it turns out that it's those proteins that are stored.

00:28:07.580 --> 00:28:11.980
That are recycled back to make things like brood food.

00:28:11.980 --> 00:28:13.660
It's those lipids

00:28:13.980 --> 00:28:14.299
that

00:28:14.460 --> 00:28:19.900
the bee needs to have energy to do all the things it needs to do in the colony.

00:28:19.960 --> 00:28:26.600
So that's one of those biomarkers that does a really good job of linking these kind of abstract topics

00:28:26.920 --> 00:28:31.080
in insect physiology to how a colony might look.

00:28:31.040 --> 00:28:32.080
Well, that's really good.

00:28:32.080 --> 00:28:32.480
The fat

00:28:32.640 --> 00:28:34.560
body has received a lot of press in the last eight

00:28:34.800 --> 00:28:36.240
last ten years, I would suppose.

00:28:36.560 --> 00:28:39.040
Maybe I don't know the exact number, but it's

00:28:39.100 --> 00:28:42.620
I know when I started in beekeeping, you talk about fat bodies, you're talking about beekeeper

00:28:42.780 --> 00:28:43.980
Bob, but you're not

00:28:44.299 --> 00:28:44.460
fat

00:28:44.620 --> 00:28:51.340
bodies now and beekeeping means something completely different, and that's really fascinating to hear how it's being used as a biomarker.

00:28:51.260 --> 00:28:52.700
So let's take a quick break.

00:28:52.700 --> 00:28:54.940
We're right at the time and we'll hear from our sponsors.

00:28:55.020 --> 00:28:59.580
We'll come back and we'll hear from Kirk.

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Welcome back, everybody.

00:30:31.460 --> 00:30:39.380
Kirk, we're gonna we're gonna throw that same question, not about biomarkers as much, but but as far as what research are you

00:30:39.620 --> 00:30:41.940
doing right now that's exciting

00:30:42.100 --> 00:30:43.060
and you're

00:30:43.300 --> 00:30:43.620
really

00:30:44.300 --> 00:30:45.820
looking forward to

00:30:46.140 --> 00:30:48.860
seeing how it can change beekeeping.

00:30:49.100 --> 00:30:49.820
This is really

00:30:49.980 --> 00:30:50.140
oh

00:30:50.460 --> 00:30:53.020
well I'm gonna I'm gonna return to the marker-based uh

00:30:53.180 --> 00:30:54.460
physiology of

00:30:54.740 --> 00:30:54.900
Oh

00:30:55.060 --> 00:30:56.180
fantastic.

00:30:56.180 --> 00:30:56.260
But

00:30:56.420 --> 00:30:56.980
Vanessa

00:30:57.140 --> 00:30:58.260
was talking about uh

00:30:58.580 --> 00:30:59.140
That's great.

00:30:59.140 --> 00:31:00.020
So I'm reminded

00:31:00.180 --> 00:31:03.380
of a study we did in two thousand fourteen and fifteen

00:31:03.540 --> 00:31:03.860
and uh

00:31:04.020 --> 00:31:04.340
Vanessa

00:31:04.740 --> 00:31:06.500
was involved in this as well.

00:31:06.500 --> 00:31:07.540
So we went up

00:31:07.960 --> 00:31:19.480
And I've been reviewing this information because of what Mark and I are doing right now, where we went and collected a bunch of landscape level, you know, longitudinal data.

00:31:19.440 --> 00:31:22.799
that included Varroa and Virus and all this other

00:31:23.039 --> 00:31:24.559
scobbledygook.

00:31:24.559 --> 00:31:25.200
But this

00:31:25.360 --> 00:31:26.880
this particular example

00:31:27.039 --> 00:31:30.000
I complained about landscape ecology.

00:31:29.940 --> 00:31:33.779
But this particular example had a really stark result

00:31:34.899 --> 00:31:35.940
where we put some

00:31:36.100 --> 00:31:40.820
we put a whole bunch of colonies and canola and sunflowers.

00:31:40.740 --> 00:31:43.460
Which are wonderful plants, don't get me wrong.

00:31:43.460 --> 00:31:46.340
And then a whole bunch of colonies, uh other colonies

00:31:46.500 --> 00:31:53.620
went into just what's called the CRP land, which has these, you know, nice flowers and wonderful nutrition for

00:31:53.860 --> 00:31:55.220
for honey bees.

00:31:55.220 --> 00:31:56.419
And then we did uh

00:31:56.740 --> 00:31:58.899
we did collect a bunch of marker

00:31:59.139 --> 00:31:59.860
response

00:32:00.500 --> 00:32:03.139
over the course of four months

00:32:03.160 --> 00:32:05.320
or not four months, over the course of a year

00:32:05.640 --> 00:32:08.040
at four separate times uh during that year.

00:32:08.040 --> 00:32:11.080
So it was a longitudinal study as well.

00:32:11.080 --> 00:32:11.400
So

00:32:11.660 --> 00:32:13.900
And we've looked at it through overwintering, so

00:32:14.060 --> 00:32:14.140
that

00:32:14.460 --> 00:32:15.100
very important

00:32:15.420 --> 00:32:15.740
time

00:32:15.900 --> 00:32:17.980
when when bees die off.

00:32:17.980 --> 00:32:18.300
So

00:32:18.940 --> 00:32:19.100
uh

00:32:19.420 --> 00:32:21.180
bees are constantly

00:32:21.340 --> 00:32:22.700
challenged by

00:32:23.320 --> 00:32:25.000
Pathogens and viruses

00:32:25.240 --> 00:32:25.400
uh

00:32:25.560 --> 00:32:26.680
all the time.

00:32:26.680 --> 00:32:27.560
And so there's just

00:32:27.720 --> 00:32:28.120
viruses

00:32:28.360 --> 00:32:34.760
that are consistently in their colony, and if you don't get good nutrition, you're simply gonna succumb

00:32:35.220 --> 00:32:36.260
to these things.

00:32:36.260 --> 00:32:37.620
The same is true of I think

00:32:37.780 --> 00:32:39.220
most all organisms.

00:32:39.220 --> 00:32:42.260
If you don't get good nutrition, you're gonna succumb to things.

00:32:42.260 --> 00:32:45.380
And then the extent to which you're exposed to

00:32:45.540 --> 00:32:48.740
not only the pathogens that are in your hive

00:32:48.840 --> 00:32:57.880
But then the stuff that they spray on plants, for instance, maybe canola and sunflowers, are gonna make that much more difficult to respond from

00:32:58.039 --> 00:33:01.400
because some of the same systems in your body that respond

00:33:01.640 --> 00:33:01.960
uh

00:33:02.340 --> 00:33:02.500
to

00:33:02.660 --> 00:33:06.500
those poisons are the ones that respond to the pathogens as well s

00:33:06.820 --> 00:33:11.620
and which is something I'm learning and reading a lot about right now.

00:33:11.640 --> 00:33:14.280
There's some of these same systems within the bee

00:33:14.920 --> 00:33:15.160
are

00:33:15.320 --> 00:33:22.200
shut down by virus, and those are the systems that would respond to the poisoning uh of the pesticides.

00:33:22.200 --> 00:33:23.080
Right.

00:33:23.019 --> 00:33:23.340
Although

00:33:23.500 --> 00:33:23.580
I

00:33:23.740 --> 00:33:23.899
know

00:33:24.059 --> 00:33:24.299
no

00:33:24.460 --> 00:33:26.940
by no means an expert on that kind of thing.

00:33:26.940 --> 00:33:29.899
But yeah, we looked at these these two groups of bees

00:33:30.059 --> 00:33:31.100
that went into canola

00:33:31.260 --> 00:33:33.899
and sunflowers and bees that went into CRP land.

00:33:34.340 --> 00:33:34.419
with

00:33:34.580 --> 00:33:38.100
the really wonderful flowers and it was like night and day.

00:33:38.100 --> 00:33:41.299
The colonies that came out of the CRP

00:33:41.460 --> 00:33:41.539
land

00:33:41.700 --> 00:33:44.580
were just beautiful, just flowing over with bees.

00:33:44.580 --> 00:33:46.740
You looked at them and you gasped

00:33:46.740 --> 00:33:48.980
You know, like the angels had come down

00:33:49.140 --> 00:33:53.140
and then you look at the other colonies and they were really bad.

00:33:53.140 --> 00:33:53.300
And

00:33:53.460 --> 00:33:54.100
none of 'em.

00:33:54.100 --> 00:33:54.340
So

00:33:54.500 --> 00:33:54.820
they come

00:33:55.060 --> 00:33:56.500
they come out of the situation

00:33:56.740 --> 00:33:58.900
overwintering, and then they go into

00:33:59.140 --> 00:33:59.780
almonds

00:34:00.020 --> 00:34:01.460
generally.

00:34:00.840 --> 00:34:01.160
So

00:34:01.400 --> 00:34:08.679
really none of the bees that were in the canola and sunflower graded well for almonds, and all of those that were in the CRP

00:34:08.840 --> 00:34:09.080
land

00:34:09.320 --> 00:34:09.480
uh

00:34:09.720 --> 00:34:11.480
graded well for almonds.

00:34:11.480 --> 00:34:11.720
So

00:34:11.960 --> 00:34:14.120
The nutritional state, as Vanessa

00:34:14.280 --> 00:34:16.920
was talking about, was overwhelmingly good

00:34:17.160 --> 00:34:20.440
in those bees that had access to that good forage.

00:34:20.440 --> 00:34:21.320
The oxidative

00:34:21.480 --> 00:34:22.920
stress response.

00:34:22.659 --> 00:34:26.500
And this is relative to the canola and sunflowers, of course, Rick,

00:34:26.659 --> 00:34:27.780
was overwhelmingly

00:34:28.020 --> 00:34:33.379
significantly better than the bees that were in sunflowers and canola

00:34:33.659 --> 00:34:35.659
And so was the immune response.

00:34:35.659 --> 00:34:36.139
The immune

00:34:36.300 --> 00:34:37.100
response.

00:34:37.100 --> 00:34:39.980
So they all kind of followed the nutrition, right?

00:34:39.980 --> 00:34:41.980
Underlying the importance uh

00:34:42.139 --> 00:34:44.620
of nutrition on the landscape.

00:34:44.639 --> 00:34:44.960
Yeah, and

00:34:45.119 --> 00:34:46.000
it was very stark.

00:34:46.079 --> 00:34:46.960
It's really the

00:34:47.200 --> 00:34:48.480
most overwhelming result

00:34:48.639 --> 00:34:48.879
I've

00:34:49.039 --> 00:34:50.079
ever seen.

00:34:50.079 --> 00:34:51.919
Of course I work on the microbiota

00:34:52.079 --> 00:34:54.240
where we get all sorts of funny looking results

00:34:54.399 --> 00:34:56.319
and often we're not really sure

00:34:56.480 --> 00:34:58.000
what they mean at all.

00:34:58.079 --> 00:34:59.039
But this one

00:34:59.340 --> 00:35:01.420
This one was quite evident.

00:35:01.420 --> 00:35:01.980
All right.

00:35:01.980 --> 00:35:02.300
So

00:35:02.540 --> 00:35:06.380
anyway, lately I've been working with Mark on a uh kind of a Varroa

00:35:06.860 --> 00:35:07.500
virus

00:35:08.280 --> 00:35:09.400
watermelon

00:35:09.720 --> 00:35:10.680
question

00:35:10.920 --> 00:35:11.080
w

00:35:11.320 --> 00:35:14.280
where we followed these bees that went into watermelons.

00:35:14.280 --> 00:35:16.120
Mark went and collected all these and

00:35:16.260 --> 00:35:20.180
We were doing an entirely different experiment, but then it

00:35:20.420 --> 00:35:26.340
it kind of became apparent that we should try to investigate this group of information.

00:35:26.320 --> 00:35:26.480
about

00:35:26.640 --> 00:35:30.320
what was happening because we have big collapses the past couple of years

00:35:30.560 --> 00:35:33.520
and this particular population collapsed as well.

00:35:33.520 --> 00:35:35.120
So we decided, well

00:35:35.540 --> 00:35:40.820
We're gonna try to look at it with these markers to see what happened and we found that uh

00:35:40.980 --> 00:35:41.060
real

00:35:41.380 --> 00:35:44.820
I'm just putting this together, but we found that it collapsed.

00:35:44.820 --> 00:35:46.900
I don't know if you guys have heard about amitraz

00:35:47.140 --> 00:35:47.860
resistance

00:35:48.180 --> 00:35:48.820
probably

00:35:49.040 --> 00:35:51.280
So it turned out all the

00:35:51.440 --> 00:35:52.320
the Varroa

00:35:52.480 --> 00:35:54.080
was really high going into

00:35:54.320 --> 00:35:58.800
overwintering, and all of those Varroa were resistant to amitraz

00:35:59.540 --> 00:36:00.500
And the beekeeper

00:36:00.740 --> 00:36:01.860
used amitraz

00:36:02.180 --> 00:36:02.980
towels,

00:36:03.300 --> 00:36:04.900
so they didn't have any effect.

00:36:04.900 --> 00:36:09.940
And these bees were also in watermelons where they where they sprayed neonicotinoids

00:36:10.240 --> 00:36:10.720
and uh

00:36:10.960 --> 00:36:11.440
apparently

00:36:11.600 --> 00:36:14.080
two different kinds of fungicides, but

00:36:14.240 --> 00:36:19.360
we don't really know which ones they were using because we didn't run a chemical analysis.

00:36:19.360 --> 00:36:21.760
But all of the markers I just talked about

00:36:22.000 --> 00:36:24.080
were incredibly low

00:36:24.140 --> 00:36:27.339
in these bees going into overwinter, right.

00:36:27.339 --> 00:36:28.539
So they'd been uh

00:36:28.779 --> 00:36:29.579
what I would say

00:36:29.740 --> 00:36:33.099
exposed to the agricultural nightmare.

00:36:32.840 --> 00:36:34.360
at the very least, right?

00:36:34.360 --> 00:36:39.400
And when that happens, then you lack this ability to fight off the viruses.

00:36:39.400 --> 00:36:39.560
So

00:36:39.720 --> 00:36:41.800
the virus loads went high.

00:36:41.559 --> 00:36:42.359
The Varroa

00:36:42.520 --> 00:36:44.839
helped spread all the viruses, the deform

00:36:45.000 --> 00:36:49.559
wheat virus, and then they also have the exacerbation of

00:36:49.720 --> 00:36:55.000
whatever pesticides they're using in watermelon, which although watermelon is considered one of the

00:36:55.140 --> 00:37:00.579
the not the dirty dozen, I guess, but uh one of the cleanest, they say.

00:37:00.740 --> 00:37:02.180
I'm not really sure uh

00:37:02.500 --> 00:37:03.779
what that means.

00:37:03.779 --> 00:37:05.460
So they do this uh

00:37:06.040 --> 00:37:06.840
What do they call it?

00:37:06.920 --> 00:37:12.280
Markimagation, where they pump the chemicals in the water to irrigate it, right?

00:37:12.280 --> 00:37:15.160
With the and so the bees will collect that water

00:37:15.320 --> 00:37:15.640
too

00:37:15.800 --> 00:37:19.160
when it's hot out and so that it's just a direct

00:37:19.540 --> 00:37:22.340
A direct way of uh poisoning the bees.

00:37:22.580 --> 00:37:23.300
Would you call that

00:37:23.460 --> 00:37:24.420
chemigation?

00:37:24.580 --> 00:37:25.460
Yeah, I think that's what it's

00:37:25.780 --> 00:37:26.660
Yeah, that's the

00:37:26.900 --> 00:37:28.420
technical term for it.

00:37:28.420 --> 00:37:28.500
I

00:37:28.660 --> 00:37:29.860
never heard of that term before.

00:37:30.100 --> 00:37:30.180
Like

00:37:30.340 --> 00:37:30.660
irrigation

00:37:30.820 --> 00:37:31.300
chemigation

00:37:31.840 --> 00:37:36.720
Sorry I didn't talk about microbes, but I'm finishing a giant thing on microbes

00:37:36.880 --> 00:37:40.000
and people just get lost when I talk about microbes anyway.

00:37:40.000 --> 00:37:40.080
So

00:37:40.480 --> 00:37:42.800
I thought I'd talk about some of the stuff that

00:37:43.420 --> 00:37:48.940
that's that's more in line with the rest of what's happening, I think, in the big bee world.

00:37:48.940 --> 00:37:49.500
The bees are

00:37:49.660 --> 00:37:53.340
the beekeepers are not concerned about the microbes.

00:37:53.340 --> 00:37:55.260
They think they might want to get some

00:37:55.799 --> 00:37:58.359
probiotics that are gonna work.

00:37:58.359 --> 00:38:00.520
But we did a paper on that and we found that

00:38:00.920 --> 00:38:03.240
the probiotics really aren't doing anything.

00:38:03.240 --> 00:38:05.799
At least the ones that are popular on the market.

00:38:06.540 --> 00:38:06.940
Yeah, they

00:38:07.180 --> 00:38:08.220
they can't even be found.

00:38:08.220 --> 00:38:08.940
That's a whole nother

00:38:09.100 --> 00:38:09.740
podcast.

00:38:10.300 --> 00:38:13.500
The microbiome work I think for that needs to be a video

00:38:13.660 --> 00:38:16.220
cast so that you can show the pretty pictures of

00:38:16.380 --> 00:38:17.180
your data

00:38:17.340 --> 00:38:18.860
because those data are

00:38:19.180 --> 00:38:19.500
Are

00:38:19.660 --> 00:38:19.740
they

00:38:20.060 --> 00:38:20.859
beautiful

00:38:21.099 --> 00:38:21.420
and

00:38:21.579 --> 00:38:22.140
and um

00:38:22.460 --> 00:38:24.540
maybe artwork at the same time.

00:38:24.700 --> 00:38:26.859
Yeah, they're shocking, that's for sure

00:38:27.160 --> 00:38:27.320
So

00:38:27.560 --> 00:38:28.440
g sorry Mark I

00:38:28.600 --> 00:38:29.480
took too long.

00:38:29.480 --> 00:38:31.160
I was just gonna say it's amazing because

00:38:31.320 --> 00:38:34.280
I feel like uh you know beekeepers are dealing with uh

00:38:34.460 --> 00:38:36.860
The horses of the apocalypse at all times.

00:38:36.860 --> 00:38:39.820
You know, it's it's land, sea and air, depending on uh

00:38:40.140 --> 00:38:40.540
what's

00:38:40.700 --> 00:38:41.900
what's getting at them.

00:38:41.900 --> 00:38:44.700
That was a Queen's study that we picked up right in the middle

00:38:44.860 --> 00:38:46.780
when everything kinda came apart

00:38:46.760 --> 00:38:47.320
for this.

00:38:47.320 --> 00:38:49.000
And he was doing many things right.

00:38:49.000 --> 00:38:52.760
It just happens sometimes, uh, under the wrong conditions.

00:38:52.760 --> 00:38:55.160
I gotta admit the thing that gets me up in the morning

00:38:55.320 --> 00:38:56.120
and probably

00:38:56.640 --> 00:38:57.440
the thing that links a

00:38:57.599 --> 00:39:00.400
fair amount of the things I'm looking at is trying to figure out

00:39:00.559 --> 00:39:01.520
we have all these things.

00:39:01.520 --> 00:39:01.599
We

00:39:01.839 --> 00:39:03.200
you know I'm an ecologist.

00:39:03.200 --> 00:39:03.359
Um

00:39:03.520 --> 00:39:04.000
I would say

00:39:04.160 --> 00:39:04.799
Kirk, you know

00:39:04.960 --> 00:39:05.279
Vanessa

00:39:05.599 --> 00:39:06.240
to a certain extent

00:39:06.400 --> 00:39:07.920
are ecologists too.

00:39:07.920 --> 00:39:09.520
That means we're kind of economist

00:39:09.680 --> 00:39:11.359
of life.

00:39:10.640 --> 00:39:15.839
And we're looking at inputs, outputs, we're looking at what it actually produces

00:39:16.319 --> 00:39:20.640
and under what conditions and so forth like that, stressors, those

00:39:21.120 --> 00:39:24.560
horses of the apocalypse that are uh coming down on it.

00:39:24.560 --> 00:39:24.640
I

00:39:24.800 --> 00:39:25.040
thought

00:39:25.200 --> 00:39:25.280
one

00:39:25.440 --> 00:39:28.640
of the things that kind of uh woke me up about this was

00:39:28.880 --> 00:39:31.040
long before you kill bees

00:39:31.359 --> 00:39:33.760
You're gonna mess up how they operate

00:39:34.079 --> 00:39:35.200
for critical things.

00:39:35.200 --> 00:39:37.839
And when I say critical, it's not feels

00:39:38.000 --> 00:39:38.880
or stuff like that.

00:39:38.880 --> 00:39:42.240
It's things like brood rearing and taking care of your queen

00:39:42.520 --> 00:39:46.040
Making sure that there's a good balance as far as nutrition.

00:39:46.280 --> 00:39:48.119
You see that go out of the window with no

00:39:48.280 --> 00:39:48.760
SEMA

00:39:48.920 --> 00:39:50.359
when things are out of whack

00:39:50.599 --> 00:39:51.160
there.

00:39:50.960 --> 00:39:53.920
And the thing that's amazing about this is that

00:39:54.160 --> 00:39:57.680
this is being done by young adult bees.

00:39:57.680 --> 00:40:03.920
All these decisions that are being made for the colony are these young adult bees, they don't have much experience

00:40:04.080 --> 00:40:05.760
in their lives.

00:40:05.160 --> 00:40:08.520
And yet they're going to have to interpret whatever is coming in

00:40:08.680 --> 00:40:11.160
and hopefully make some good choices.

00:40:11.160 --> 00:40:15.240
And those choices, you know, a lot of the things we look at, you know, when their

00:40:15.640 --> 00:40:18.200
times are good, we go, those are what we want

00:40:18.160 --> 00:40:22.000
Some of the things are when things are bad, you know, not rearing brood, eating

00:40:22.160 --> 00:40:29.040
cannibalizing brood, maybe getting rid of your queen, those may be good at certain times, the beekeepers may not like those.

00:40:29.180 --> 00:40:29.500
And

00:40:29.820 --> 00:40:31.740
the one appreciation above all

00:40:31.900 --> 00:40:33.500
is that this is a long game.

00:40:33.500 --> 00:40:35.020
You know, we're we're talking

00:40:35.260 --> 00:40:35.579
I s

00:40:35.740 --> 00:40:39.740
I started out with nutrition here and I was thinking, okay, let's look at nutrition um

00:40:40.060 --> 00:40:41.740
about a month or two before they go into

00:40:41.900 --> 00:40:42.780
almonds

00:40:42.640 --> 00:40:44.559
And then that got pushed back to

00:40:44.799 --> 00:40:48.960
let's look at nutrition in the early fall before they close up.

00:40:48.960 --> 00:40:50.960
We're having indications from coloss

00:40:51.359 --> 00:40:52.160
of all things

00:40:52.319 --> 00:40:52.640
that we

00:40:52.799 --> 00:40:56.400
gotta maybe even think further back as far as impacts

00:40:56.320 --> 00:40:57.040
on things.

00:40:57.040 --> 00:40:59.520
And that's what makes it so complex.

00:40:59.520 --> 00:41:04.720
But I will say that uh a lot of what I do is uh and that's why I look at pheromones.

00:41:04.740 --> 00:41:06.180
Because what we're really trying to do is

00:41:06.340 --> 00:41:06.980
pheromones

00:41:07.140 --> 00:41:08.660
are a big part of how

00:41:08.900 --> 00:41:10.980
those bees, those young bees, uh

00:41:11.220 --> 00:41:16.340
interpret what's going on and hopefully make the right decisions for their colony.

00:41:16.140 --> 00:41:21.180
whether or not to rear brood, whether or not to rear new queen or get rid of their queen in that case.

00:41:21.180 --> 00:41:26.059
And of course these feed into major issues of what we want to do.

00:41:25.960 --> 00:41:28.360
It's okay if they do those things when

00:41:28.520 --> 00:41:31.960
they're kind of doing them in the right way, aligned with beekeepers.

00:41:31.960 --> 00:41:33.320
But I mean, for example, with brew

00:41:33.480 --> 00:41:36.520
bring, how many times have people had something in a holding yard

00:41:36.680 --> 00:41:37.000
or

00:41:37.240 --> 00:41:37.320
right

00:41:37.480 --> 00:41:39.400
before the season and they're feeding pollen

00:41:39.560 --> 00:41:40.360
patty there.

00:41:40.360 --> 00:41:43.720
And those bees are getting fat, but they're not doing squat as far as brood

00:41:43.880 --> 00:41:44.280
bearing.

00:41:44.280 --> 00:41:46.760
They're just kind of holding back on it.

00:41:46.640 --> 00:41:50.480
Or you get a queen that's perfectly good just knocked off and you're wondering

00:41:50.640 --> 00:41:50.960
why did

00:41:51.279 --> 00:41:52.000
why'd they go

00:41:52.160 --> 00:41:53.839
why'd they knock her off?

00:41:53.839 --> 00:41:56.400
So that's why I look at the these pheromones

00:41:56.720 --> 00:42:00.799
and probably the best way to think of it, particularly with the brood pheromones, is

00:42:00.859 --> 00:42:03.500
They had some French researchers, Mason

00:42:03.660 --> 00:42:08.619
Ace, uh, Cedric Aloo, some of those folks, came out with the bright and brilliant idea

00:42:08.859 --> 00:42:09.180
that

00:42:09.520 --> 00:42:10.240
Everything ha

00:42:10.400 --> 00:42:11.520
everything in the colonies

00:42:11.760 --> 00:42:14.240
far as workers and larva and stuff

00:42:14.480 --> 00:42:15.440
have a little say

00:42:15.680 --> 00:42:16.320
in how

00:42:16.480 --> 00:42:18.160
in nudging these

00:42:18.400 --> 00:42:22.960
workers as they go from in their lives from being nest bees to foragers.

00:42:23.040 --> 00:42:23.200
how

00:42:23.440 --> 00:42:29.040
fast that goes, how much effort they're going to put in, they're kind of getting influenced by these pheromones.

00:42:29.040 --> 00:42:30.080
And β-ocimene

00:42:30.240 --> 00:42:31.440
is one of those pheromones.

00:42:31.440 --> 00:42:32.800
It's made by a lot of

00:42:32.960 --> 00:42:33.440
β-ocimene

00:42:33.680 --> 00:42:35.760
is made in large amounts by eggs

00:42:36.020 --> 00:42:36.900
in very young

00:42:37.060 --> 00:42:37.940
larva.

00:42:37.940 --> 00:42:38.339
And it

00:42:38.500 --> 00:42:40.339
also doubles up as a

00:42:40.660 --> 00:42:40.820
let

00:42:40.980 --> 00:42:41.300
's mean

00:42:41.460 --> 00:42:41.619
also

00:42:41.780 --> 00:42:42.820
doubles up it's a

00:42:42.980 --> 00:42:43.300
um

00:42:43.640 --> 00:42:48.359
Essentially, it's a starvation signal and a feeding signal to workers.

00:42:48.359 --> 00:42:50.680
It's like a baby bird chirping, trying to get

00:42:51.000 --> 00:42:52.839
attention and trying to be fed.

00:42:53.539 --> 00:42:59.619
We have researchers that showed that uh older larvae put out a lot of that and they get fed more if if they

00:42:59.859 --> 00:43:01.859
if they're putting that out.

00:43:01.859 --> 00:43:02.180
So

00:43:02.840 --> 00:43:04.360
There's a lot of ideas there.

00:43:04.360 --> 00:43:08.520
I'm still interested in improving the bottom line of

00:43:08.680 --> 00:43:11.000
of what we're doing here, but pro

00:43:11.240 --> 00:43:12.680
possibly on the margin.

00:43:12.680 --> 00:43:14.920
I think the latest thing that we have

00:43:15.140 --> 00:43:17.299
With that is looking at β-ocimene

00:43:17.779 --> 00:43:19.140
and looking at the fact that

00:43:19.299 --> 00:43:22.500
something that we picked up with and we were kind of shocked.

00:43:22.500 --> 00:43:26.339
It's not something that we can see or smell very easily.

00:43:26.240 --> 00:43:27.280
But, you know, you

00:43:27.440 --> 00:43:29.360
if you happen to have a GC-MS

00:43:29.600 --> 00:43:29.760
or

00:43:30.000 --> 00:43:32.000
some other instruments just lying around which

00:43:32.480 --> 00:43:33.760
Tell everybody what that is.

00:43:34.480 --> 00:43:36.960
Mark, you have to tell everybody, not everybody here.

00:43:36.960 --> 00:43:37.760
Yeah.

00:43:37.920 --> 00:43:39.760
Just just pull it out of the garage and use it.

00:43:39.760 --> 00:43:40.480
You know, um with

00:43:40.720 --> 00:43:40.880
with

00:43:41.039 --> 00:43:41.279
that

00:43:42.340 --> 00:43:44.500
Well we noticed that we kept on getting things where

00:43:44.820 --> 00:43:46.100
wait I'm not kidding Mark.

00:43:46.100 --> 00:43:46.980
Oh no, no, I know.

00:43:47.220 --> 00:43:47.620
gas chromatography-mass spectrometry.

00:43:47.700 --> 00:43:48.500
So yeah, I'll explain

00:43:48.660 --> 00:43:48.980
whether that

00:43:49.140 --> 00:43:50.660
that's just a thing that measures uh

00:43:50.820 --> 00:43:52.820
odoriferous compounds.

00:43:52.440 --> 00:43:53.800
You put it through it separates them

00:43:53.960 --> 00:43:55.880
out, you get peaks, and you can say, Ah

00:43:56.440 --> 00:43:56.520
the

00:43:56.760 --> 00:43:59.480
the peaks are that big and I'm getting that much of it.

00:43:59.480 --> 00:44:00.920
It's another one of those instruments

00:44:01.140 --> 00:44:02.740
We talk about like everybody has one.

00:44:04.660 --> 00:44:06.500
Now I think you have one in your garage.

00:44:08.020 --> 00:44:08.260
That's

00:44:08.819 --> 00:44:09.460
a fair one there.

00:44:12.420 --> 00:44:12.980
It might have.

00:44:13.060 --> 00:44:15.060
Yeah, you got a cool 150,000.

00:44:15.060 --> 00:44:15.220
It's

00:44:15.380 --> 00:44:16.260
it's right there.

00:44:16.260 --> 00:44:16.500
Um

00:44:16.740 --> 00:44:17.300
but we were

00:44:17.460 --> 00:44:18.980
we were surprised and shocked.

00:44:18.980 --> 00:44:19.700
You get these just

00:44:20.020 --> 00:44:20.260
so

00:44:20.420 --> 00:44:22.500
stories that occur in bees.

00:44:21.900 --> 00:44:23.900
And a lot of these things with pheromones

00:44:24.140 --> 00:44:26.059
and with other stories like queen pheromones

00:44:26.220 --> 00:44:28.859
and stuff, those were made when times are good.

00:44:28.859 --> 00:44:29.819
You know, they looked at

00:44:29.980 --> 00:44:31.740
they measured queen pheromones, Winston

00:44:31.900 --> 00:44:33.099
and those folks.

00:44:32.859 --> 00:44:35.660
They figured that out when things were going well

00:44:35.900 --> 00:44:37.579
and when they were gone.

00:44:37.579 --> 00:44:38.140
Same with uh

00:44:38.380 --> 00:44:39.099
β-ocimene.

00:44:39.099 --> 00:44:42.380
It's given off a lot by these eggs and young young brood

00:44:42.619 --> 00:44:45.260
when things are healthy and when there's lots of food

00:44:45.260 --> 00:44:47.420
And we were looking at things and we noticed in the mill

00:44:47.660 --> 00:44:47.900
summer

00:44:48.060 --> 00:44:49.660
dearth when we have no forage

00:44:49.820 --> 00:44:52.300
whatsoever, they weren't giving off β-ocimene

00:44:52.540 --> 00:44:53.180
at all

00:44:53.220 --> 00:44:53.380
So

00:44:53.539 --> 00:44:55.380
we're thinking, okay, it's uh

00:44:55.700 --> 00:45:01.299
it's a bit of a starvation signal, a little bit of a baby bird chirping uh signal for older larvae.

00:45:01.299 --> 00:45:03.299
What does it do for younger larvae?

00:45:03.160 --> 00:45:09.640
And you gotta realize that younger larva, we're looking at the pivot point with brood productivity there.

00:45:09.640 --> 00:45:11.480
Because younger larvae.

00:45:11.480 --> 00:45:11.560
.

00:45:11.559 --> 00:45:16.520
When bees need to restrict the population, what they do is eat eggs and young larva.

00:45:16.520 --> 00:45:18.440
They don't eat older larva, they eat

00:45:18.599 --> 00:45:20.039
eggs and young larvae.

00:45:20.200 --> 00:45:21.400
That's a pretty definitive

00:45:21.559 --> 00:45:22.839
you're not going to get brood care

00:45:23.160 --> 00:45:26.359
kind of uh story there if you're gonna be eating.

00:45:25.980 --> 00:45:26.220
Uh

00:45:26.380 --> 00:45:26.700
so

00:45:27.180 --> 00:45:27.260
I

00:45:27.500 --> 00:45:28.060
you know, our

00:45:28.220 --> 00:45:30.540
very simple thing that we looked and we're just looking at

00:45:30.700 --> 00:45:31.500
if you supplement

00:45:31.660 --> 00:45:34.460
it in, do you get more brood rearing at these times

00:45:34.620 --> 00:45:35.100
when you

00:45:35.260 --> 00:45:40.460
You have bees, you've been feeding them lots of pollen patty, they're holding back because there's no nectar coming in.

00:45:40.460 --> 00:45:41.660
And sure enough, they

00:45:41.900 --> 00:45:43.820
in this in these cases it does.

00:45:44.060 --> 00:45:44.380
They do

00:45:44.540 --> 00:45:44.940
rear

00:45:45.180 --> 00:45:47.500
more brood through that page.

00:45:47.440 --> 00:45:50.480
You could certainly come up with situations in your mind where

00:45:50.640 --> 00:45:58.960
maybe sometime of year when you're in a forage-free area where you're feeding the daylights out of your bees with supplemental feed, you wanna you wanna push them through it.

00:45:59.020 --> 00:46:01.660
But you know, we got a long way to go to look at that.

00:46:01.980 --> 00:46:06.859
It's going to depend on nutrition again, and we know that's gonna vary place to place.

00:46:06.960 --> 00:46:11.360
Is it connected to the amount of brood food that you're going to actually visualize in a cell?

00:46:11.360 --> 00:46:15.840
There's some of it in there, but it's mainly going to be you're mainly going to find it with egg laying

00:46:16.000 --> 00:46:16.640
queens, uh

00:46:16.800 --> 00:46:21.680
eggs themselves, and then the very young larva that you have there.

00:46:21.059 --> 00:46:26.180
Uh the older larvae give off smaller amounts, but they'll give it off in burst when they're they're being ignored.

00:46:26.180 --> 00:46:26.339
You

00:46:26.500 --> 00:46:27.859
if you ever see 'em when they

00:46:28.020 --> 00:46:28.500
some of the

00:46:28.660 --> 00:46:30.180
older larvae corkscrew

00:46:30.339 --> 00:46:32.099
out and fall out of the

00:46:32.620 --> 00:46:36.060
They um need to be fed a few hundred times during the fifth

00:46:36.220 --> 00:46:37.180
instar.

00:46:37.180 --> 00:46:40.620
But if you have a lot of the β-ocimene, will you have a lot of brood

00:46:40.780 --> 00:46:41.580
food?

00:46:41.460 --> 00:46:42.100
Like if you're re

00:46:42.340 --> 00:46:46.180
you're seeing high levels, does do you see high levels of brood food?

00:46:46.180 --> 00:46:47.780
That's an excellent question.

00:46:47.780 --> 00:46:52.340
That's kind of the thing that we catch on, is that they provision more brood

00:46:52.500 --> 00:46:53.140
food.

00:46:53.760 --> 00:46:58.960
You think of your young larvae, they're just basically they're not fed little piecemeals like a baby bird.

00:46:58.960 --> 00:47:00.080
What happens is the larva

00:47:00.320 --> 00:47:02.160
the workers come in there.

00:47:01.700 --> 00:47:01.859
And

00:47:02.020 --> 00:47:04.980
you just kind of take some of those hypopharyngeal glands, those lar

00:47:05.140 --> 00:47:05.220
the

00:47:05.380 --> 00:47:06.740
brood food that Vanessa

00:47:06.980 --> 00:47:10.820
was talking about, that she measures, and they spit that up into the cell.

00:47:10.820 --> 00:47:11.060
And you

00:47:11.300 --> 00:47:14.420
there's your little larva sitting on this puddle of food

00:47:14.200 --> 00:47:17.000
It's really one of the more bizarre things about bees.

00:47:17.000 --> 00:47:18.119
And that's what they're gonna

00:47:18.440 --> 00:47:19.960
that's what they're gonna get.

00:47:19.960 --> 00:47:25.720
If they don't you know, if they don't have good glands, they're not gonna make much food, they can't rear much larvae

00:47:25.680 --> 00:47:26.720
It's not gonna be good.

00:47:26.720 --> 00:47:29.760
If they don't get that, then they're gonna starve in a few hours.

00:47:29.760 --> 00:47:30.800
And that will be that.

00:47:30.800 --> 00:47:31.600
And it'll be can

00:47:32.000 --> 00:47:35.040
they'll be recycled, I guess, back into the

00:47:35.440 --> 00:47:36.560
Food is short and

00:47:36.800 --> 00:47:40.160
yeah, it's it's gotta be kept within the colony.

00:47:40.160 --> 00:47:44.720
And it seems like different genetics might have a different

00:47:45.240 --> 00:47:45.720
threshold

00:47:45.880 --> 00:47:48.200
for cannibalizing the young.

00:47:48.200 --> 00:47:48.680
Like like

00:47:48.840 --> 00:47:53.240
I think about Carniolans and they're not afraid to cannibalize eggs

00:47:53.440 --> 00:47:53.599
if

00:47:53.760 --> 00:47:55.280
the season changes.

00:47:55.359 --> 00:47:57.119
I think unmistakably um

00:47:57.280 --> 00:47:57.920
you have

00:47:58.240 --> 00:48:01.839
you think about the Italian strains that we've selected for.

00:48:01.839 --> 00:48:04.720
We select for productivity, brood productivity like

00:48:04.880 --> 00:48:05.040
out

00:48:05.200 --> 00:48:06.000
of the gate

00:48:05.960 --> 00:48:07.640
And then we have other ones like you know

00:48:07.800 --> 00:48:08.920
Russians and

00:48:09.080 --> 00:48:09.400
and

00:48:09.560 --> 00:48:12.120
Caucasians that hold back a little bit.

00:48:12.120 --> 00:48:13.800
This is a lot of the big differences

00:48:14.040 --> 00:48:17.080
between different subspecies and uh queen

00:48:17.240 --> 00:48:19.080
stocks that we have out there

00:48:19.059 --> 00:48:22.980
There's undoubtedly different thresholds for what they're willing to put up with

00:48:23.140 --> 00:48:28.339
and how those workers interpret the forage and nutritional environment.

00:48:28.220 --> 00:48:29.500
Yeah, we do have uh

00:48:29.740 --> 00:48:32.700
I should say that just because they're making less brood

00:48:33.020 --> 00:48:34.539
doesn't mean they're they're poor.

00:48:34.539 --> 00:48:38.779
I would have to tip my hat to uh William Meikle, who is here

00:48:38.940 --> 00:48:40.940
and just recently retired

00:48:40.880 --> 00:48:46.560
And he did some work where he was looking at Russians and Italians and the Russians make less brood, but the

00:48:46.720 --> 00:48:49.440
but the workers they produce are longer lived

00:48:49.600 --> 00:48:51.600
by quite a l quite a bit.

00:48:51.640 --> 00:48:54.920
So it's a quality versus quantity thing in that case.

00:48:54.920 --> 00:48:56.760
Well Becky, when you started this and said

00:48:57.240 --> 00:48:59.319
next three hours, I I think you're

00:48:59.980 --> 00:49:00.540
So accurate.

00:49:00.780 --> 00:49:02.300
Oh I was dead serious.

00:49:05.100 --> 00:49:10.220
Make sure you invite them back now so they can commit on air and then if they don't come back, it's they're all gonna

00:49:10.380 --> 00:49:10.380
be.

00:49:14.400 --> 00:49:14.480
And

00:49:14.720 --> 00:49:14.880
say

00:49:15.039 --> 00:49:15.839
if you want to have

00:49:16.000 --> 00:49:19.760
introductions to Vanessa, Kirk, and Mark, listen to this episode.

00:49:19.760 --> 00:49:20.720
We're going to continue the

00:49:20.880 --> 00:49:23.279
discussion on this next episode.

00:49:23.279 --> 00:49:25.680
There's so much information here.

00:49:25.640 --> 00:49:28.839
I think we're only just looking at the tip of the iceberg.

00:49:28.839 --> 00:49:30.119
I wanted to ask you before we

00:49:30.359 --> 00:49:32.279
just quick answers on these, because

00:49:32.440 --> 00:49:33.880
I met you all at COLOSS

00:49:34.200 --> 00:49:35.559
in Pullman.

00:49:35.260 --> 00:49:42.140
Was there anything about what you heard from researchers around the world at that meeting that surprised you?

00:49:42.380 --> 00:49:42.460
Was

00:49:42.620 --> 00:49:43.900
there something there that was

00:49:44.059 --> 00:49:45.339
Kind of stood out.

00:49:45.339 --> 00:49:48.299
I can say it didn't surprise me, but it stood out.

00:49:48.299 --> 00:49:49.339
Yeah, no, that's great.

00:49:49.339 --> 00:49:49.900
That's fair.

00:49:49.900 --> 00:49:50.460
Yeah.

00:49:50.460 --> 00:49:56.220
It's always great when people are doing their independent research and you converge on the same answer.

00:49:56.480 --> 00:49:56.880
And I

00:49:57.200 --> 00:49:58.400
think what was really

00:49:58.560 --> 00:50:00.240
coming up a lot is how

00:50:00.560 --> 00:50:01.200
just because

00:50:01.360 --> 00:50:08.240
you have a certain species of plant that makes a certain type of nectar or pollen, it's not a static thing.

00:50:08.240 --> 00:50:09.200
It's not like

00:50:09.559 --> 00:50:10.760
you know, you measure it once

00:50:10.920 --> 00:50:13.240
and that's the nutrition of that plant.

00:50:13.240 --> 00:50:17.480
It really depends on the environment that the plant is in

00:50:17.880 --> 00:50:18.200
and

00:50:18.359 --> 00:50:20.920
how, you know, there can be variation

00:50:21.079 --> 00:50:23.799
in that, in those nutrients.

00:50:23.520 --> 00:50:26.079
That makes sense when you say it, but we don't think that.

00:50:26.079 --> 00:50:27.280
No, no.

00:50:27.280 --> 00:50:30.240
I mean, to me it's just crazy, but but it doesn't

00:50:30.400 --> 00:50:32.320
you know but but maybe it's not crazy

00:50:32.480 --> 00:50:34.400
because that plant is a living thing

00:50:34.560 --> 00:50:35.520
too.

00:50:35.340 --> 00:50:35.740
Right.

00:50:35.740 --> 00:50:37.660
And it's got to balance its

00:50:37.900 --> 00:50:38.700
needs.

00:50:38.700 --> 00:50:43.420
It's all about, I think a lot of it can be boiled down to trade-offs.

00:50:43.760 --> 00:50:44.079
So

00:50:44.640 --> 00:50:48.320
a plant has to put its energy into growth, so

00:50:48.560 --> 00:50:48.800
be its

00:50:48.960 --> 00:50:50.880
leaves and how tall it gets, or

00:50:51.119 --> 00:50:52.480
reproduction, its

00:50:52.880 --> 00:50:54.880
pollen and nectar.

00:50:54.880 --> 00:50:55.200
And

00:50:56.099 --> 00:51:00.500
It's kind of I'm very simp I'm simplifying this a lot, but it's kind of a choice.

00:51:00.500 --> 00:51:03.460
How are you gonna budget those nutrients

00:51:03.720 --> 00:51:04.039
And

00:51:04.359 --> 00:51:13.160
if it's not to the pollen and the nectar, and they don't actually have to be budgeted the same, you know, you might have really good nectar, but not great pollen.

00:51:13.320 --> 00:51:14.760
All of it's a balance.

00:51:14.760 --> 00:51:20.600
And so that's all affected by the different aspects of the environment that the plant is experiencing.

00:51:20.600 --> 00:51:21.960
It's interesting because even with

00:51:22.120 --> 00:51:22.760
just with that,

00:51:23.000 --> 00:51:25.880
I was just reading an older text while Frank Pellet.

00:51:25.660 --> 00:51:26.780
American honey plants

00:51:26.940 --> 00:51:28.380
and basswood, I think

00:51:28.540 --> 00:51:32.300
it was it two to three great crops every five years or something like that.

00:51:32.300 --> 00:51:32.620
So

00:51:32.940 --> 00:51:33.660
so we've like

00:51:33.820 --> 00:51:34.940
known it, but not

00:51:35.240 --> 00:51:35.560
known

00:51:35.720 --> 00:51:36.040
it.

00:51:37.000 --> 00:51:37.160
So

00:51:37.320 --> 00:51:39.880
it takes scientists like you all to like

00:51:40.040 --> 00:51:40.440
help us

00:51:40.600 --> 00:51:41.800
help us get there.

00:51:41.800 --> 00:51:42.280
Yeah.

00:51:42.280 --> 00:51:43.000
Yeah.

00:51:43.240 --> 00:51:44.600
Yeah, absolutely.

00:51:44.600 --> 00:51:46.120
I think it's really important

00:51:46.280 --> 00:51:48.280
that beekeepers understand

00:51:48.600 --> 00:51:50.280
the work that you're doing.

00:51:50.280 --> 00:51:52.440
It's it's it's honestly so revolutionary

00:51:52.600 --> 00:51:53.160
because right

00:51:53.320 --> 00:51:54.200
we used to

00:51:54.440 --> 00:51:56.520
measure the health of the colony by maybe

00:51:56.680 --> 00:51:56.920
the

00:51:57.079 --> 00:51:58.839
the amount of honey it puts up.

00:51:58.839 --> 00:51:59.720
But you're going

00:51:59.880 --> 00:52:01.079
into the organism

00:52:01.560 --> 00:52:01.880
and

00:52:02.320 --> 00:52:03.600
understanding what

00:52:04.240 --> 00:52:05.200
the actual

00:52:05.440 --> 00:52:09.200
health of the bee is and then connecting that to the health of the colony

00:52:09.440 --> 00:52:11.760
and helping us to interpret

00:52:11.859 --> 00:52:13.700
colony health, colony death, all of that.

00:52:13.700 --> 00:52:15.859
But but the work that you're doing inside the bee

00:52:16.020 --> 00:52:16.099
is

00:52:16.260 --> 00:52:17.380
is so critical.

00:52:17.380 --> 00:52:19.300
Can you each just comment on that?

00:52:19.300 --> 00:52:19.460
And

00:52:19.700 --> 00:52:22.579
'cause it's it's not like we've been able to do this

00:52:22.740 --> 00:52:23.859
for years and years.

00:52:23.859 --> 00:52:25.700
This is this is kind of a newer

00:52:26.220 --> 00:52:26.619
newer

00:52:26.859 --> 00:52:27.819
field for

00:52:28.140 --> 00:52:29.420
science and for

00:52:29.579 --> 00:52:30.859
livestock, isn't it?

00:52:30.859 --> 00:52:31.900
Or for honey bees?

00:52:32.220 --> 00:52:36.380
Deep in that gut there's a lining of microbes.

00:52:36.240 --> 00:52:40.320
There's also a lining of microbes throughout the entire colony.

00:52:40.320 --> 00:52:44.400
There's microbes on the honey, not that many.

00:52:44.440 --> 00:52:46.280
Because that's an age of the honey.

00:52:46.280 --> 00:52:46.680
But there are

00:52:46.839 --> 00:52:49.000
microbes on the bee bread.

00:52:49.320 --> 00:52:49.560
Also

00:52:49.960 --> 00:52:51.800
not that many, right?

00:52:51.800 --> 00:52:55.480
There's microbes on the cuticle of the worker bee.

00:52:55.359 --> 00:52:55.520
and

00:52:55.680 --> 00:52:57.520
microbes all over its face

00:52:57.760 --> 00:52:58.079
and

00:52:58.240 --> 00:53:01.440
microbes on the queen's face and mouth parts.

00:53:01.440 --> 00:53:01.520
And

00:53:01.760 --> 00:53:04.079
microbes everywhere in that colony.

00:53:04.079 --> 00:53:05.119
And one of the

00:53:05.280 --> 00:53:05.440
uh

00:53:05.599 --> 00:53:07.760
so this is a very new field

00:53:07.920 --> 00:53:08.720
and what you

00:53:08.960 --> 00:53:10.160
as you mentioned.

00:53:10.140 --> 00:53:12.460
And what happens with a new field is

00:53:12.619 --> 00:53:13.099
is uh

00:53:13.260 --> 00:53:14.539
well the process of science

00:53:14.700 --> 00:53:14.779
is

00:53:15.020 --> 00:53:15.579
edit

00:53:15.819 --> 00:53:16.779
and refine

00:53:16.940 --> 00:53:19.500
and edit and refine, right?

00:53:19.559 --> 00:53:24.119
It seems to be the process of society in general, but it's also the process

00:53:24.359 --> 00:53:25.640
of science.

00:53:25.640 --> 00:53:25.960
And

00:53:26.680 --> 00:53:28.920
so what is happening is we're in a big

00:53:29.079 --> 00:53:29.400
uh

00:53:29.740 --> 00:53:29.980
I f

00:53:30.140 --> 00:53:32.220
I feel like I'm in a big refine

00:53:32.460 --> 00:53:33.340
moment, right?

00:53:33.340 --> 00:53:34.460
Or big edit.

00:53:34.460 --> 00:53:35.020
Well yeah,

00:53:35.820 --> 00:53:36.300
produce

00:53:36.860 --> 00:53:37.340
produce

00:53:37.580 --> 00:53:38.300
produce has

00:53:38.460 --> 00:53:39.740
gotta be in there somewhere.

00:53:39.740 --> 00:53:42.140
Produce, edit, refine, right?

00:53:41.859 --> 00:53:45.300
It's the thesis, the antithesis, and the synthesis.

00:53:45.300 --> 00:53:47.540
So I guess there's gotta be three of them, right?

00:53:47.540 --> 00:53:47.700
So

00:53:47.859 --> 00:53:52.020
I'm just making up words here that other people have said better than me, but

00:53:52.080 --> 00:53:56.000
Yeah, I'm in a process of like, well, a lot of garbage has spun

00:53:56.160 --> 00:53:57.600
forth out of the microbial

00:53:57.760 --> 00:53:58.400
world.

00:53:58.400 --> 00:53:59.600
A whole lot of it.

00:53:59.600 --> 00:54:03.200
And it's it's it's fueling a lot of speculation about

00:54:03.540 --> 00:54:06.580
making probiotics and it's it's creating well that

00:54:06.740 --> 00:54:11.940
this, you know, false hope is the same as hope, but that's where, you know, this is where things come from.

00:54:11.940 --> 00:54:12.260
So

00:54:12.460 --> 00:54:12.700
It's

00:54:12.860 --> 00:54:19.100
uh but you know, it should narrow out and then through the editing process maybe we will find something that works.

00:54:19.100 --> 00:54:24.380
But right now it's it's about shedding all of the garbage off of the field.

00:54:23.900 --> 00:54:27.339
So there's an incredible amount of garbage in the microbial

00:54:27.500 --> 00:54:28.220
field now.

00:54:28.220 --> 00:54:28.859
It's uh

00:54:29.099 --> 00:54:29.500
I'm

00:54:29.740 --> 00:54:33.099
writing a paper about that presently, but uh

00:54:33.700 --> 00:54:35.540
And it's due to a lot of

00:54:35.860 --> 00:54:37.700
lot of different things, primarily

00:54:37.940 --> 00:54:38.900
misunderstanding

00:54:39.220 --> 00:54:41.060
how to do the analysis.

00:54:41.060 --> 00:54:41.780
And it's a

00:54:41.940 --> 00:54:42.740
it's a cut and

00:54:42.900 --> 00:54:43.540
paste

00:54:43.940 --> 00:54:47.380
thing now where you can send your samples away to a lab and you get them

00:54:47.540 --> 00:54:53.700
back and then you can choose little default parameters about how to analyze them and you go click click click click

00:54:53.859 --> 00:54:55.940
and then it spits out a thing.

00:54:55.400 --> 00:54:58.760
And then you look up those microbes and learn something about them

00:54:58.920 --> 00:55:00.039
and write it down.

00:55:00.039 --> 00:55:00.920
And it's like a

00:55:01.079 --> 00:55:04.920
it's like a plug and play or, you know, cut and paste.

00:55:04.760 --> 00:55:05.160
And is

00:55:05.320 --> 00:55:06.440
these people haven't really

00:55:06.600 --> 00:55:10.760
and maybe it's the nature of a lot of things now, but perhaps they haven't earned the

00:55:11.160 --> 00:55:11.800
the right

00:55:12.040 --> 00:55:14.040
to look at that data.

00:55:14.460 --> 00:55:14.940
And it

00:55:15.500 --> 00:55:15.740
it may

00:55:17.980 --> 00:55:21.180
it may be true of a lot of things, but you go through

00:55:21.340 --> 00:55:25.180
there's a lot of loops you go through to try to learn that stuff.

00:55:24.960 --> 00:55:26.240
Don't don't put that on.

00:55:26.240 --> 00:55:26.880
That's horrible

00:55:27.040 --> 00:55:28.000
thing you say.

00:55:28.880 --> 00:55:31.600
I don't want to discourage anybody, but

00:55:31.760 --> 00:55:32.000
uh

00:55:32.160 --> 00:55:32.880
yeah.

00:55:32.880 --> 00:55:35.680
I mean if I can just jump in here, I think

00:55:35.940 --> 00:55:40.260
I think you're just talking about one very small layer of the onion.

00:55:40.260 --> 00:55:40.820
So we're just

00:55:40.980 --> 00:55:44.980
we're just peeling back all these different layers of the onion.

00:55:45.020 --> 00:55:45.579
Right?

00:55:45.579 --> 00:55:45.900
And

00:55:46.060 --> 00:55:51.740
you get to go into a new layer of onion when you develop new methods and techniques.

00:55:51.740 --> 00:55:52.380
Right?

00:55:52.380 --> 00:55:56.940
And that helps you understand a very specific layer of the onion.

00:55:56.840 --> 00:55:57.240
Right?

00:55:57.240 --> 00:56:00.280
And then there's going to be a new layer and a new layer.

00:56:00.280 --> 00:56:05.000
All of that needs to come together to help us understand

00:56:05.160 --> 00:56:08.040
how not only the colony functions.

00:56:08.120 --> 00:56:11.160
the individual functions, but then even

00:56:11.480 --> 00:56:15.320
within the individual, you know, how that all functions.

00:56:15.320 --> 00:56:15.640
So

00:56:15.880 --> 00:56:19.240
so all of these layers, it is revolutionary

00:56:19.560 --> 00:56:19.880
because

00:56:20.420 --> 00:56:20.660
We

00:56:20.980 --> 00:56:21.300
have

00:56:21.460 --> 00:56:24.340
all these new things to measure and understand.

00:56:24.340 --> 00:56:26.420
However, you can't get

00:56:26.660 --> 00:56:28.820
you can't get like distracted

00:56:29.140 --> 00:56:31.700
by all the onion layers, right?

00:56:32.040 --> 00:56:33.080
And you have to

00:56:33.240 --> 00:56:36.280
I mean it's really easy to get distracted, right?

00:56:36.280 --> 00:56:38.600
And just really get in, you know.

00:56:38.680 --> 00:56:40.760
Was I getting distracted?

00:56:41.480 --> 00:56:43.720
No, no.

00:56:43.720 --> 00:56:45.000
Absolutely not

00:56:45.420 --> 00:56:45.660
But

00:56:45.900 --> 00:56:50.620
you really have to, you know, working for the ARS, I can only speak to that

00:56:50.780 --> 00:56:51.100
really

00:56:51.500 --> 00:56:52.940
with bees, our

00:56:53.180 --> 00:56:54.620
job is slightly different

00:56:54.860 --> 00:56:55.180
because

00:56:55.300 --> 00:56:57.540
Our job is to help agriculture.

00:56:57.540 --> 00:57:08.980
And so you have to always be focusing on the layers and the aspects of the layers that eventually are going to make colonies happier, colonies healthier, and help crop pollination.

00:57:08.380 --> 00:57:12.140
So there's a lot of stuff out there, but you really have to focus.

00:57:12.300 --> 00:57:15.180
Vanessa, I don't like onions, but I like your medicine

00:57:15.580 --> 00:57:15.660
right

00:57:15.900 --> 00:57:16.140
there.

00:57:18.480 --> 00:57:20.480
It's it's you know, when I was

00:57:20.640 --> 00:57:25.280
I will say when I was young, when I was young and started into this, you know, and

00:57:25.520 --> 00:57:27.040
always seemed to be that uh

00:57:27.200 --> 00:57:27.920
my friends at

00:57:28.400 --> 00:57:28.960
bees uh

00:57:29.120 --> 00:57:29.760
needed

00:57:29.740 --> 00:57:29.980
help

00:57:30.140 --> 00:57:32.140
about the time that they were harvesting honey

00:57:32.300 --> 00:57:32.780
and you

00:57:33.020 --> 00:57:34.620
you probably could guess why.

00:57:34.620 --> 00:57:37.020
The one thing about it was you know back then

00:57:37.180 --> 00:57:40.460
looked at it and you see the wealth of it was in the honey in the

00:57:40.559 --> 00:57:42.880
the frames and stuff like that and you're missing the it

00:57:43.039 --> 00:57:43.200
it's

00:57:43.359 --> 00:57:44.640
misses the whole point.

00:57:44.640 --> 00:57:46.640
It's having healthy colonies that

00:57:46.799 --> 00:57:50.000
where the true wealth of uh beekeeping is.

00:57:49.840 --> 00:57:52.480
If you can do that, the rest of it follows uh

00:57:52.640 --> 00:57:58.720
through, especially in this time when everything's coming at these colonies and destroying them.

00:57:58.559 --> 00:58:04.640
Yeah, I think if people even tried to work in a particular part of the field, they can't ignore these other parts.

00:58:04.640 --> 00:58:06.160
You know, folks who work on

00:58:06.359 --> 00:58:08.760
Pathogens have to think about what pesticides

00:58:08.920 --> 00:58:11.800
exposures are going to alter things there.

00:58:11.800 --> 00:58:13.320
The nutrition parts, uh

00:58:13.480 --> 00:58:15.720
looking at forage and nutrition.

00:58:15.559 --> 00:58:18.039
Well, what if you get exposed to something um

00:58:18.200 --> 00:58:23.559
like a strong pesticide when your colony is weak and is going to get taken out by it

00:58:23.540 --> 00:58:23.700
It

00:58:23.860 --> 00:58:24.340
just kind of

00:58:24.500 --> 00:58:26.260
can't put down all the parts and it

00:58:26.420 --> 00:58:28.420
that's why we always seem to inevitably

00:58:28.580 --> 00:58:31.540
end up working on several different things at once

00:58:31.180 --> 00:58:32.140
But it makes for Lance

00:58:32.380 --> 00:58:33.420
collaboration.

00:58:33.420 --> 00:58:41.660
And that's one of the reasons why the honey bees is one of the what the most studied insect in the world, so it's so fascinating on so many different levels, so many different

00:58:41.900 --> 00:58:43.180
peels of the onion.

00:58:43.180 --> 00:58:44.860
To beat that metaphor again

00:58:45.140 --> 00:58:46.339
Well, I will have to say

00:58:46.500 --> 00:58:49.380
this has been a total pleasure, worth the wait.

00:58:49.380 --> 00:58:52.579
I enjoyed talking with you all and I look forward to having you back.

00:58:52.579 --> 00:58:53.380
I would I

00:58:53.539 --> 00:58:56.900
I'd almost like to say let's do this on a semi-annual basis.

00:58:56.900 --> 00:58:59.859
Every six months we'll just uh kind of circle back.

00:58:59.840 --> 00:59:01.520
And I will break that cycle.

00:59:01.520 --> 00:59:01.680
Uh

00:59:01.840 --> 00:59:02.480
I will

00:59:02.880 --> 00:59:03.280
we're w

00:59:03.440 --> 00:59:05.120
uh just a little sneak peek.

00:59:05.120 --> 00:59:07.680
I will be in Tucson in November for other events.

00:59:07.680 --> 00:59:09.440
We're we're gonna try to get into

00:59:09.600 --> 00:59:10.000
the B

00:59:10.240 --> 00:59:10.400
lab

00:59:10.640 --> 00:59:10.720
for

00:59:10.880 --> 00:59:13.360
a visit and uh a field report

00:59:13.200 --> 00:59:14.560
So I'm looking forward to that.

00:59:14.560 --> 00:59:14.720
But

00:59:14.880 --> 00:59:21.520
beside that, maybe next spring we can have you back and we can talk about future research and some of the things that you're looking forward to.

00:59:21.760 --> 00:59:23.200
I think that would be exciting.

00:59:23.440 --> 00:59:24.560
Absolutely.

00:59:24.380 --> 00:59:24.700
Thank you.

00:59:24.860 --> 00:59:26.940
Yeah, we can talk about bee research all day.

00:59:26.940 --> 00:59:27.180
So

00:59:27.580 --> 00:59:27.740
the

00:59:27.900 --> 00:59:30.460
three-hour talk, it's coming up right now.

00:59:31.580 --> 00:59:34.380
Well thank you so much and we look forward to having you back.

00:59:34.380 --> 00:59:34.700
Thank you.

00:59:35.580 --> 00:59:35.900
Thank you.

00:59:36.380 --> 00:59:36.780
Take care.

00:59:37.100 --> 00:59:39.260
Thank you.

00:59:39.700 --> 00:59:42.180
I don't know how many times I can say this during an episode

00:59:42.340 --> 00:59:47.300
and I'm sure there's folks out there who are counting it, but I really enjoyed having them on the show.

00:59:47.300 --> 00:59:49.300
I knew when I met them in June

00:59:49.540 --> 00:59:51.300
that they would be fun to have on the

00:59:51.540 --> 00:59:52.340
podcasting

00:59:53.040 --> 00:59:55.040
They met all expectations.

00:59:55.040 --> 00:59:56.000
Oh, you were so

00:59:56.160 --> 00:59:57.280
you were so right.

00:59:57.280 --> 01:00:00.320
That was just a jam-packed conversation.

01:00:00.320 --> 01:00:06.320
There was so much information, so many layers that we still could peel back.

01:00:06.040 --> 01:00:07.560
and explore.

01:00:07.560 --> 01:00:10.920
It's just a new road that research is taking.

01:00:10.920 --> 01:00:11.240
I

01:00:11.400 --> 01:00:12.600
I think for last

01:00:12.840 --> 01:00:14.040
early last year, I r

01:00:14.280 --> 01:00:17.400
oh for February, because it was blood related, I

01:00:17.740 --> 01:00:17.820
r

01:00:18.140 --> 01:00:19.100
really, which is not

01:00:19.260 --> 01:00:21.660
called blood, it's insect hemolymph.

01:00:21.660 --> 01:00:24.300
But I wrote an article for Bee Culture

01:00:24.860 --> 01:00:25.180
about

01:00:25.740 --> 01:00:27.420
biomarkers in Hemolymph

01:00:27.580 --> 01:00:34.860
and how many different avenues there are now to actually measure the health of bees through biomarkers, which

01:00:35.180 --> 01:00:35.500
really

01:00:35.740 --> 01:00:39.180
gives a researcher so many more tools

01:00:39.220 --> 01:00:39.460
to

01:00:39.779 --> 01:00:40.660
analyze

01:00:40.980 --> 01:00:43.140
colonies and colony health.

01:00:43.140 --> 01:00:43.380
So

01:00:43.619 --> 01:00:48.819
to talk to three people who are kind of doing some work around there, it's it's

01:00:48.980 --> 01:00:49.299
that was

01:00:49.460 --> 01:00:50.420
exciting.

01:00:50.240 --> 01:00:52.560
They're right in the mix of all the excitement

01:00:52.720 --> 01:00:54.720
and they're connected around the world.

01:00:54.720 --> 01:00:56.080
I'm looking forward to having them back.

01:00:56.080 --> 01:00:57.680
I'm looking forward to talking to them hopefully

01:00:57.840 --> 01:01:00.400
in November and then again next spring

01:01:00.400 --> 01:01:01.040
we can

01:01:01.200 --> 01:01:03.360
take a deeper dive into something.

01:01:03.360 --> 01:01:05.040
I'm sure we'll find something.

01:01:05.040 --> 01:01:06.480
I'd love these USDA

01:01:06.640 --> 01:01:07.360
researchers.

01:01:07.360 --> 01:01:09.040
We've got Jay Evans.

01:01:09.040 --> 01:01:09.280
We

01:01:09.440 --> 01:01:11.520
just talked to Vince and these three

01:01:11.680 --> 01:01:12.000
areas.

01:01:12.240 --> 01:01:12.560
Vanessa

01:01:12.720 --> 01:01:13.920
Kirk and Mark, yeah.

01:01:13.920 --> 01:01:14.880
There you go.

01:01:15.000 --> 01:01:15.240
And

01:01:15.480 --> 01:01:19.080
that about wraps it up for this episode of Beekeeping Today.

01:01:19.080 --> 01:01:22.440
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01:01:30.160 --> 01:01:31.680
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01:01:31.680 --> 01:01:37.920
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01:01:37.920 --> 01:01:43.040
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01:01:43.040 --> 01:01:44.960
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01:01:45.240 --> 01:01:49.160
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01:01:49.320 --> 01:01:52.360
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01:01:52.360 --> 01:01:56.280
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01:01:56.280 --> 01:01:59.880
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01:02:00.320 --> 01:02:00.640
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01:02:00.640 --> 01:02:02.000
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01:02:02.000 --> 01:02:03.920
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