EFI-ESA Stats Seminar: Introduction to continuous-time movement modeling for animal tracking data

EFI-ESA Stats Seminar: Introduction to continuous-time movement modeling for animal tracking data

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Name: EFI-ESA Stats Seminar: Introduction to continuous-time movement modeling for animal tracking data
Start: 2025-09-08 12:00
End: 2025-09-08 13:00

Posted by sandra on August 20, 2025

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09/08/2025 12:00 PM - 1:00 PM

https://notredame.zoom.us/webinar/register/WN_uQcwMy7RSwWgwTH0G60QwA#/registration

Ecological Forecasting Initiative

Website: https://ecoforecast.org/

This Statistical Methods seminar by the Ecological Forecasting Initiative and the Ecological Society of America Statistical Ecology Section is hosting Dr. Christen Fleming from the University of Central Florida to talk about the continuous-time movement modeling {ctmm} R package

Increasing resource conservation through adoption of Integrated Pest Management 595 conservation practice systems

12/17/2025 12:00 PM - 12/17/2025 1:00 PM

Date: Wednesday, December 17, 2025
Time: 12:00 PM - 1:00 PM Central
What's New in the Revised FSC US "Forest Stewardship Standard"

12/17/2025 1:00 PM - 12/17/2025 2:00 PM

The webinar will be live on Wednesday, December 17 at 1:00 pm ET.

It will be recorded, and its recording will be accessible for a year following air date. Access will close after December 17, 2026.
EFI Statistical Method Seminar: Building Spatial Statistical Models in R using {spmodel}

01/12/2026 12:00 PM - 01/12/2026 1:00 PM

No additional details for this event.
Developing Safe and Inclusive Fieldwork Settings

01/13/2026 12:00 PM - 01/13/2026 1:00 PM

Date: Tuesday, January 13, 2026
Time: 11:00 AM - 12:15 PM Central
Deadline: AGU-ESA Special Collection: Ecological Forecasting in the Earth System

10/31/2026 All day

Submission deadline: Saturday, 31 October 2026

This special collection jointly hosted by the American Geophysical Union (AGU) and the Ecological Society of America (ESA) focuses on the emerging field of ecological forecasting, which involves predicting the future states of ecosystems. The issue welcomes contributions that use novel methodologies, interdisciplinary approaches, real-time data integration, and multi-forecast synthesis to enhance the accuracy, uncertainty representation, applicability, and equality of ecological forecasts.

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