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SDG 6 | Understanding Grass Carp Spawning Behavior to Enhance Lake Management | Ryan Brown

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Manage episode 434471823 series 2817616
Innhold levert av Kevin Sofen & James Armour, Kevin Sofen, and James Armour. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Kevin Sofen & James Armour, Kevin Sofen, and James Armour eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

How can simulations combat sampling bias?

Thanks for joining us for another episode of highlighting change makers and their inspirational work towards the United Nations Sustainable Development Goals (SDGs).

In this episode:

  • Why is timing in spawning behavior important?

  • Using simulations to combat sampling bias and improve data accuracy in lake management

  • How does Wisconsin Water Week explore diverse topics and specializations in lake management?

Learn from ⁠Ryan Brown⁠ - a Field Research Data Manager at the University of Toledo.

Ryan talks about his research on invasive grass carp in Lake Erie, emphasizing the importance of timing in their spawning behavior. He explains how understanding spawning timing can help removal crews increase their efficiency in removing adult fish.

Ryan also discusses the use of simulations to combat sampling bias and improve data accuracy. He concludes by highlighting future research on grass carp and its potential benefits for lake management.

Click play now to soak up what he has to share!

To learn more and get involved with ongoing efforts in Wisconsin, visit the partner websites:

Let’s get SDG Talking!!

Do you have a good story or want to collaborate? Send us an email at sdgtalkspodcast@gmail.com and we will get back to you as soon as we can.

And don’t forget to check out our Virtual Roundtables on our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠

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135 episoder

Artwork
iconDel
 
Manage episode 434471823 series 2817616
Innhold levert av Kevin Sofen & James Armour, Kevin Sofen, and James Armour. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Kevin Sofen & James Armour, Kevin Sofen, and James Armour eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

How can simulations combat sampling bias?

Thanks for joining us for another episode of highlighting change makers and their inspirational work towards the United Nations Sustainable Development Goals (SDGs).

In this episode:

  • Why is timing in spawning behavior important?

  • Using simulations to combat sampling bias and improve data accuracy in lake management

  • How does Wisconsin Water Week explore diverse topics and specializations in lake management?

Learn from ⁠Ryan Brown⁠ - a Field Research Data Manager at the University of Toledo.

Ryan talks about his research on invasive grass carp in Lake Erie, emphasizing the importance of timing in their spawning behavior. He explains how understanding spawning timing can help removal crews increase their efficiency in removing adult fish.

Ryan also discusses the use of simulations to combat sampling bias and improve data accuracy. He concludes by highlighting future research on grass carp and its potential benefits for lake management.

Click play now to soak up what he has to share!

To learn more and get involved with ongoing efforts in Wisconsin, visit the partner websites:

Let’s get SDG Talking!!

Do you have a good story or want to collaborate? Send us an email at sdgtalkspodcast@gmail.com and we will get back to you as soon as we can.

And don’t forget to check out our Virtual Roundtables on our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠

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135 episoder

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