On 13 September, 10:00 AM, Jacqueline Hoppenreijs will defend her PhD thesis. The thesis, titled Rooting for riparian vegetation – processes underlying community composition in boreal ecosystems, covers the roles of hydrology and geomorphology in dispersal and environmental filtering of riparian vegetation, and builds on four papers:

1. Pressures on Boreal Riparian Vegetation: A Literature Review https://doi.org/10.3389/fevo.2021.806130

2. Seed dispersal of riparian plants: mapping hydrochory across hydrology and geomorphology

3. Effects of dispersal and geomorphology on riparian seed banks and vegetation in a boreal stream https://doi.org/10.1111/jvs.13240

4. Riparian vegetation in a regulated and a free-flowing river: effects of stream size, order and tributaries

The full thesis can be downloaded from DiVA. The defence is open to the public, and it is possible to follow it on our campus and on Zoom. Please contact jacqueline.hoppenreijs@kau.se for more information. 

We (V. van ‘t Hoff & P. Cabral & F. O. Akinyemi, et al.) would like to bring to your attention an exciting session at the upcoming ESP Europe 2024 conference.

Conference SessionArtificial Intelligence and Ecosystem Services – Advancements in AI in the field of ecosystem services for transformative change
Date: 18-22 November 2024
Location: Wageningen, The Netherlands
Abstract Submission: Open from 15 May to 15 July 2024 (https://espconference.org/europe2024/home)

Hosted by: Felicia O. Akinyemi, Pedro Cabral, and Vince van ‘t HoffCo-hosts: Sara Alibakhshi, Bruna Almeida, Jan Haas, Ewa Orlikowska, Xi-Lillian Pang, Mieke Siebers, Guojie Wang Aim: This session explores the transformative potential of AI in understanding, monitoring, and managing ecosystem services (ES). It will highlight innovative AI solutions, such as satellite image analysis and natural language processing, which offer new ways to gather and analyze complex data. The session will cover various AI methodologies, including machine learning, deep learning, and GeoAI, and discuss their applications in assessing and modelling ES and ecosystem functions (EF).

For more information and to submit your abstract, please visit the ESP Europe 2024 website.

Why to attend?

1) This session is an excellent opportunity to stay at the forefront of advancements in AI and its applications in ecosystem services. I highly encourage you to attend and consider contributing your knowledge.


2) The communications presented at this session may be considered for inclusion in a synthesis paper or a review paper highlighting knowledge gaps in the use of AI for ecosystem services in both empirical and modelling contexts.

On 27 February, Gabriele Consoli will be giving a seminar to our department with the title Ecomorphological effects of experimental floods in an alpine river: insights from the long-term e-flow program on the Spöl River. His work centers on the ways in which large wood and flow management affect rivers and their ecological functioning. Having a background in ecology and geomorphology, he now works as a postdoc at the River Ecosystems research group at the University of Lausanne (Switzerland), where he combines abiotic, biotic and drone data to find out how flow affects the geomorphology and ecology of streams.

Read more about the River Ecosystems research group on their website and join us for the seminar on 27 February at 13:15 CET via  https://kau-se.zoom.us/j/65816884688

On February 20, Dr. Frank Jauker will be giving a talk about his work on agricultural landscapes and biodiversity promotion at the Justus Liebig University in Giessen, Germany. He will specifically present the GreenGrass project, where many societal stakeholders work together to improve grazing management, with the ultimate goal of making dairy production more sustainable.

Figure 1: View at one of the study sites in the GreenGrass project.

Attend the seminar via Zoom: https://kau-se.zoom.us/my/kaubiology, at 13:15 CET on February 20.

Description                                             

The Faculty of Health Science and Technology has an opening for one full-time post-doctoral research fellow in Biology at the Department of Environmental and Life Sciences in the field of quantitative aquatic ecology, with a focus on fish movement behaviour and machine learning techniques to predict how an eel will move in a river as a function of the surroundings.

The River Ecology and Management Research Group (RivEM), a research environment within the Department of Environmental and Life Sciences at Karlstad University, conducts both basic and applied research in and along rivers and lakes and their surrounding landscapes. The research group is interested in the sustainable use of natural resources in watersheds, working for solutions to environmental problems that benefit both society and nature. Areas of research addressed by RivEM include river connectivity and the effects of hydropower, aquatic- terrestrial interactions and habitats, winter ecology under global climate change, endangered species such as unionid mussels, conservation biology and social-ecological research relating to river regulation and recreational fishing (www.kau.se/biologyhttp://www.nrrv.se). Within many of these topics, research is conducted in collaboration with stakeholders from industry, administrative agencies, interest organizations and landowners. You will be employed as a post-doc in Biology and the employment is a temporary full-time position for two years, with a possible one-year-extension, and may include teaching or other academic duties in the Department.

Duties

Hydropower dams impact riverine connectivity, deteriorating life-cycle performance of many species as they obstruct the migration routes for organisms between areas used for feeding, reproduction and survival. To prevent further global declines in fish biodiversity, identifying and understanding key fish-environment interactions is crucial for successful conservation strategies. This is especially so for the European eel (Anguilla anguilla) whose population has declined 95% in the last 25 years and is currently categorized as critically threatened. The exact reasons for the decline in the eel population are not known, but a combination of effects from over-exploitation, new pathogens, climatic changes, and habitat degradation including fragmentation are believed to be the most probable causes. Adult seaward-migrating eels are more vulnerable to passage through hydropower installations than many other fish species due to their elongated body length. The need for mitigation and effective strategies for increasing survival of out-migrating eels in regulated rivers is thus obvious.

Concurrently, inferences of cost-effectiveness and relevance of mitigation and restoration efforts demand detailed knowledge of the specific processes that result in elevated migrating fish mortalities. In the case of eels and power plant-induced mortality, there is a very simple solution: prevent the eels from entering the turbines and restore river connectivity. This solution demands knowledge-based development of optimized solutions that should be rooted in in-depth knowledge about eel behaviour and ecology. However, at present there is a lack of detailed knowledge on how to create sustainable solutions to do this and at the same time prevent loss of hydropower electricity production. The reason being a lack of a fundamental understanding on how the eel behaves as a function of the hydrological environment.

Our project aims at developing a statistical framework that provides an understanding of how different key hydrological variables affect eel swimming behavior, and machine learning techniques to predict how an eel will move in a river as a function of the surroundings. The statistical model framework will be developed based on existing models for smolt behaviour, developed by members of the proposed project. This will provide a generic and general understanding of the correlation between hydrological variables and the swimming behavior of eels during downstream migration. This result will then be used in a machine learning model to predict eel downstream migratory routes. The results of this project are expected to help in the development of mitigation solutions for eels to strengthen the European eel population and consequently contribute to the restoration of the ecological dynamics of freshwater aquatic systems.

The successful candidate will work within RivEM, in close collaboration with experts from the Norwegian Institute for Nature Research (NINA) and Vattenfall R&D, with end-to-end data science projects which require leveraging state-of-the-art machine learning techniques, statistical methods, and other advanced analytics tools so as to deliver solutions for fish conservation. Through this role, you will have the opportunity to collaborate and develop your career together with experts within biology and other experienced data scientists in the project. In addition, silver eel telemetry studies in the field to study eel swimming behaviour and hydrodynamics can come into question. The applicant is expected to be active at the university and participate in the research environment.

Requirements

To be eligible for the position, applicants are required to hold a PhD (or to be completed before the decision about the employment is taken) in quantitative ecology, statistics, computational ecology, or related fields. The candidate must have completed the degree no more than three years before the last date for applications unless special grounds exist. Older PhD degrees can be taken into account when there are special reasons, such as leave due to sick leave, parental leave, clinical service, positions of trust within unions or other similar circumstances. Excellent oral and written communication skills in English are required.

To apply for this role, visit, https://kau.varbi.com/en/what:job/jobID:674172/

Felix Eissenhauer, a PhD student at the University of New Brunswick, will be giving a seminar entitled “Ecology of the American eel (Anguilla rostrata) in a large tidal and hydropower-regulated river” over Zoom  https://kau-se.zoom.us/j/65816884688 at 13:15 CET on December 5, 2023.

Felix’s work focuses on the ecology of the American eel in the Wolastoq River, a large tidal and hydropower-regulated river in Canada. He is studying how a hydropower dam affects the recruitment of eel elvers and using mark-recapture methods to assess their population size and demographics. Further, Felix uses acoustic telemetry to study the depth and thermal habitat use and the seasonal migration behaviour of yellow eels in the Wolastoq River.

You are welcome to join this seminar

Louis Addo, a doctoral student from the Department of Environmental and Life Science, biology, will give a 50 percent seminar on his doctoral research work. The opponent will be Paul Hart, Professor Emeritus, from the University of Leicester, UK. Date: November 16 at 13.15 CET. Location: 5F423  and Zoom: https://kau-se.zoom.us/s/65816884688. You are warmly welcome!

Stephen De Lisle (Associate Senior Lecturer)

Stephen’s research focuses on understanding the causes and consequences of natural selection, specifically in sexually reproducing populations. In this seminar, he will argue the following points: sexual dimorphism, or within species differences between the sexes, are a pervasive form of biodiversity, often with ecological importance. He will then present a series of experiments from salamanders and flies that test for a role of direct ecological causes of sexual dimorphism – that is, ecological character displacement between the sexes. He will then go on to explore the theoretical and realized consequences of sexual dimorphism for the assembly of ecological communities. 

Tuesday 31 October 2023, kl. 13.15 Room 5F322 (https://kau-se.zoom.us/j/3552606964). You are welcome!