Tackling current challenges in ecology: novel tools and technologies – applications to invasion science

Biological invasions are a critical driver of environmental change and biodiversity loss. With globalisation accelerating these changes, managing invasive alien species demands robust and dynamic detection and monitoring systems coupled with adaptive response strategies. This advanced course delves into the latest advancements and practical applications of tools and technologies: artificial intelligence, citizen science and iEcology, Remote Sensing and Earth Observation; Static, Hybrid and Dynamic modelling and Economic Tools. .Participants will engage in both theoretical and practical sessions, learning from leading researchers about innovative solutions and their applications across different spatial-temporal contexts.

 

Key Areas Covered:

1. Artificial Intelligence in Ecology:

Application of AI and deep learning models.

Enhancing detection of invasive alien species through computer vision.

2. Citizen Science and iEcology:

Leveraging public participation for data collection.

Improving data availability and quality through citizen science initiatives.

3. Remote Sensing and Earth Observation:

Using satellite imagery to detect, map, and monitor biological invasions.

Integrating remote sensing data for real-time monitoring.

Using UAVs to collect data.

4. Modelling Invasive Species Distributions:

Static, dynamic, and hybrid modelling approaches.

Predicting current and future distributions of invasive species.

5. Management of Invasive Species

Economic tools

This course is timely and novel, focusing on the intersection of cutting-edge technology and invasive species management. It addresses the pressing need for innovative and scalable solutions in a globalised world where biological invasions pose increasing threats to ecosystems, economies, and human health. The course aims to provide participants with the knowledge and practical skills needed to develop and implement effective management strategies, thereby contributing to ongoing and future projects in this critical field.

[Morning - Citizen Science and iEcology]

Course Introduction and Objectives

Lecture: The Role of Citizen Science and iEcology

Practical Session: Digital Data Collection Techniques

[Afternoon - Introduction and AI in Ecology]

Lecture: AI and Deep Learning for Ecological Applications

Practical Session Pre-processing data and implementing Computer Vision Models

[Morning - Remote Sensing and Earth Observation] 

Lecture: Down on earth and up in the sky – applications of satellite and UAV very-high resolution imagery for invasion mapping and surveying

Practical Session (PART I) – Aerophotogrammetry using UAV’s for remote sensing of plant invaded sites - field session 

[Afternoon - Remote Sensing and Earth Observation] 

Practical Session (PART I) – Aerophotogrammetry using UAV’s for remote sensing of plant invaded sites - room session 

[Morning – Habitat Distribution Models] 

Lecture: Introduction to Habitat Suitability Models

Practical Session: Introduction into spatial modelling of ecological niches and conflicts between invasive alien and rare species 

[Afternoon – Dynamic/hybrid modelling tools]

Lecture: The Stochastic Dynamic Methodology (StDM)

Practical Session: StDM modelling development and applications

[Morning - Economics of invasive species] 

Lectures

[Afternoon - Economics of invasive species] 

Practical Session 

4 days - 24 hours - Schedule: 10:00 - 13:00 & 14:00 - 17:00

Coordination

Joana Vicente | BIOPOLIS/ CIBIO-InBIO

Nicolas Quérou | CEE-M (Montpellier) 

Instructors

Pierre Courtois | CEE-M (Montpellier)

Renato Henriques | Institute of Earth Sciences – University of Minho

João Gonçalves | BIOPOLIS/ CIBIO-InBIO

Eva Pinto | BIOPOLIS/ CIBIO-InBIO

Ana Sofia Cardoso | BIOPOLIS/ CIBIO-InBIO

Cristina Lima | BIOPOLIS/ CIBIO-InBIO

Bruno Marcos | BIOPOLIS/ CIBIO-InBIO

Nuno Mouta | BIOPOLIS/ CIBIO-InBIO

The course will be open to a maximum number of 15 participants. 

75% of available student slots are reserved for BIODIV students.

 Priority will be given to:

• 1st year and other PhD students attending the BIODIV Doctoral Program;

• PhD students attending other courses;

• Other post-graduate students and researchers.

(A minimum number of participants is required for the course to take place)

Deadline: 2 May 2025

To apply fill the FORM

A copy of the form will be sent to the email address you provide as proof that you have successfully submitted your application. Results will be emailed to you within 8 working days of the application deadline.

80€ (students) | 120€ (other participants).

BIOPOLIS/ CIBIO members will have an additional discount of 20%. Participation is free of charge for BIODIV Students MBGE 1st year Students & CIBIO's TwinLabs 

(If applicable, payment will be made to Associação BIOPOLIS - VAT No. 516033727. Information on the payment amount and the payment deadline will be sent together with the results notification, and a proforma invoice may be issued in due time).

Registration fees do not include accommodation or meals. 

No ECTS credits are awarded for attending the course. Participants receive a certificate of attendance without quantitative evaluation.