Program
Keynote Speakers
K1
Tallinn University of Technology, Estonia
Talk: Aquatic sensing using underwater robots: preparing for a deluge of environmental data.
K2
San Diego State University, USA
Talk: Mining and management of eco-acoustic data.
K3
Agricultural Research Service (ARS), United States Department of Agriculture (USDA), USA
Talk: Harnessing the power of big data in ecology by machine learning.
K4
University of Trento, Italy
Talk: A look beyond biogeographical theories: advances and challenges.
This page shows an overview of the conference themes, keynote talks, regular and special sessions.
NEW Oral presentations have been added to the sessions. The order of the talks within each session is still subject to changes.
In addition, you can find poster presentations and computer demonstrations below.
For an overview of the program schedule click here.
For the detailed program schedule click here.
Please find infos on the course on ‘Bayesian belief networks for integrated ecological modelling to assess communities and ecosystem services’ below. The course takes place on Saturday, September 29, 2018.
Theme 1: Ecological Monitoring and Data Management
Keynote Talks
K1 _ Aquatic sensing using underwater robots: preparing for a deluge of environmental data. (Maarja Kruusmaa, Estonia)
Information is everywhere. But in some places it is incredibly difficult to obtain. This talk tells a story of how to get information from water. The exploration begins by taking ideas from highly advanced biological systems to build human-purposed technologies, and presents new types of bio-inspired sensors that pick up signals from water never before perceived. It then investigates various ways of modelling, interpreting, classifying flow information to better understand what is going on in the aquatic realm, by exploiting the interactions occurring at the interface between a fluid and solid. To conclude, the talk illustrates several real-world research applications where flow information can be used to better understand, protect, control and explore within the underwater world.
Maarja Kruusmaa is one of Europe’s leaders in novel multi-sensor monitoring of ecosystems by novel robots. Her research interests are robotics, biorobotics, artificial muscles, electroactive polymers, underwater robotics, robot learning, flow sensing and experimental fluid dynamics. Maarja received her Ph.D. degree from Chalmers Univeristy of Technology, Gothenburg, Sweden and is now Professor at Tallinn University of Technology, Estland. More information can be found at: https://www.ttu.ee/institutes/centre-for-biorobotics/centre/people-7/
K2 _ Mining and management of eco-acoustic data. (Marie Roch, USA)
Long-term passive acoustic data sets can provide insights into many topic areas related to animals such as behavior, ecology, density, and communication. Acoustic data sets are becoming ubiquitous as the cost of acquisition, storage, and analysis hardware decreases coupled with an explosion of scientific data analysis products. Advances in algorithms to classify and localize sounds are permitting us to ask questions that would not have been possible only a short time ago.
In this talk, we will examine work from projects that discuss classification in the context of large data sets. We will also examine the management of acoustic recording metadata. Many of the processes that affect animal populations operate on multiple time scales (e.g., diel, lunar, decadal) or over large spatial areas. We present methods that can be used to retain and organize these metadata and place them in context with respect to other data such as lunar phase or climatic indicators.
Marie A. Roch is interested in pattern recognition, particularly as applied to categorization of audio signals. Her current work is in pattern recognition for bioacoustics, the study of sound production and perception in animals. She studies questions of identification, behavior, and communication through acoustics. Marie received her Ph.D. degree from The University of Iowa, USA, and is now Professor at San Diego State University, USA. She is associate editor of Ecological Informatics for Imaged Based Monitoring. More information can be found at: https://roch.sdsu.edu/
Regular Sessions
R1.1 _ Ecological monitoring by camera, thermal and acoustic images. (Session Chair: Marie Roch)
Camera traps, thermal infrared videos and soundscapes are non-invasive monitoring techniques of elusive animals without significantly sacrificing analytical accuracy. These methods reduce field hours for estimating demographic parameters, inventory species and migration patterns. Automatic classification systems of camera, thermal and acoustic images allow large datasets to be analyzed over short timescales, and yield valuable information for natural resource decision-making.
- Keeping the Human in the Loop: Towards Automatic Visual Monitoring in Biodiversity Research
Joachim Denzler, Christoph Käding and Clemens-Alexander Brust - Automating biological monitoring on the Northern Andes of South America: combining biology and machine learning for conservation
Juan M. Daza, Claudia Isaza, Carol Bedoya, Estefany Cano, Diana Duque, William Gomez and Camilo Sanchez-Giraldo - Understanding the relationship between soundscape and landscape features in a Tropical Andean environment
Camilo Sanchez-Giraldo, Estefany Cano, William E. Gomez, Diana C. Duque, Claudia Isaza, Carol Bedoya and Juan M. Daza - The Diversity of Heath Flowering Phenology – Revealing Fine Scale Patterns of Heterogeneity by High Resolution Drone Cameras
Carsten Neumann, Robert Behling, Sibylle Itzerott, Gabriele Weiss, Matthias Wichmann and Jörg Müller - Using automated species identification in passive acoustic recording to test the acoustic niche partition hypothesis in Neotropical frogs
Estefany Cano Rojas, Carol Bedoya, Juan Manuel Daza Rojas and Claudia Victoria Isaza Narvaez - Automated recognition of people and identification of animal species in camera trap images
Laura Hoebeke, Michiel Stock, Stijn Van Hoey, Jim Casaer and Bernard De Baets - A method for automatic creation of a vegetation map using high-resolution aerial photographs of unmanned aerial vehicles
Masatoshi Denda, Sayuri Yoshioka and Yoshiko Maeda - Complimenting long-term bird monitoring observations with acoustic sensors and camera traps: best of both worlds
Elizabeth Znidersic, Michael Towsey, David M. Watson, Kelly W. Roy, Sarah E. Darling, Anthony Truskinger and Paul Roe - Optimisation of video monitoring of fish for reef assessment and management
Stijn Bruneel, Amber Schoeters, Rafael Bermudez and Peter Goethals - Annotating Species Trait Images with Absolute Size Information Using Mobile Devices
Martin Hofmann, Marco Seeland and Patrick Mäder
Special Sessions
S1.1 _ Earth Observation for ecosystem analysis and decision making. (Session Chairs: Klaus Joehnk and Janet Anstee)
Earth observation data is acquired from satellites, airborne platforms, and in-situ measurements on land and in water. Combined with modelling tools this yields detailed insights into ecosystem functioning from small to large scales and allows for improved prediction algorithms, which then provides decision makers with reliable and up-to-date information.
In this special session we want to address the challenges and opportunities
of the use of Earth observation data in modelling and forecasting of ecosystem trends. This can be, but is not restricted to, water quality modelling, harmful algal blooms, biodiversity trends, ecosystem accounting, etc.
Keywords: earth observation, remote sensing, water quality, bio-optics
- Alpine forest biodiversity estimated from the space: testing the Spectral Variation Hypothesis comparing Landsat 8 and Sentinel 2 using a multi-temporal Rao Q
Michele Torresani, Duccio Rocchini, Marc Zebisch, Ruth Sonnenschein and Giustino Tonon - Gross Primary Production and spring onset linked by spatio-temporal data analysis
Emma Izquierdo-Verdiguier, Alvaro Moreno, Raul Zurita-Milla, Gustau Camps Valls and Steve Running - Monitoring the spread of invasive plant species in Germany – how many species can we possibly detect by remote sensing and what data do we need?
Sandra Skowronek, Stefanie Stenzel and Hannes Feilhauer - Spatial patterns of Leaf Mass per Area of wetland vegetation under water stress analyzed with imaging spectroscopy
Hannes Feilhauer, Thomas Schmid, Ulrike Faude, Salvador Sánchez-Carrillo and Santos Cirujano - A constrained depth-resolved artificial neural network model of marine phytoplankton primary production
Francesco Mattei and Michele Scardi - Exploring environmental variables through ecotope derived by remote sensing
Julien Radoux, Brieuc François, Thomas De Maet, Quentin Vandersteen and Pierre Defourny - Estimating Gross Primary Productivity in Crops with Satellite Data, Radiative Transfer Modeling and Machine Learning
Aleksandra Wolanin, Luis Guanter, Gustau Camps-Valls, Luis Gómez-Chova, Gonzalo Mateo García, Christiaan van der Tol and Yongguang Zhang - Estimating grasslands biomass- Potential and limitations of point cloud analysis
Thomas Möckel and Michael Wachendorf - Integration of near-surface and satellite observations for algal bloom detection
Janet Anstee, Klaus Joehnk, Phillip Ford, Tim Malthus, Elizabeth Botha, Marit van Oostende, Eric Lehmann, Xavier Ho and Stephen Gensemer - A neural network approach to infer the 3D chlorophyll-a field from remote sensing observations
Michela Sammartino, Salvatore Marullo, Rosalia Santoleri and Michele Scardi - Towards Understanding the Trends of Informal Harvesting of Sand Forest in Maputaland, South Africa
Ryan Nel, Kevin Mearns and Maarten Jordaan - Challenges and opportunities of Earth observation for the prediction of water quality in inland waters
Klaus Joehnk and Janet Anstee - Mapping of invasive plant species with Sentinel-1 and -2 data calibrated with UAV-based training data
Teja Kattenborn, Javier Lopatin, Michael Förster and Fabian Ewald Fassnacht - An interactive tool for real-time rendering of fuzzy remote sensing based vegetation maps
Adam Kania - tSNE dimensionality reduction for more eficient remote sensing based vegetation mapping
Adam Kania - Modelling tree species diversities of the Afromontane forest ecosystem with satellite remote sensing and macro-ecological data
Ralph Adewoye - Connectivity and Synchronisation of Lake Ecosystems in Space and Time – CONNECT
Stella A. Berger, Sabine Wollrab, J.N. Nejstgaard, H.-P. Grossart, G. Singer, F. Hölker, A. Jechow, J. Fischer, T. Ruhtz, P. Gege, T. Sachs, M. Labrenz, G. Lischeid, R. Röttgers and T. Schneider
S1.2 _ Analysis of ecoacoustic recordings: detection, segmentation and classification. (Session Chairs: Jérôme Sueur and Dan Stowell)
Ecoacoustics is a newly emerged discipline that aims at tackling ecological research questions through the lens of sound analysis. Ecoacoustics covers several questions in marine, freshwater and terrestrial environments dealing with biodiversity monitoring, population ecology, community ecology and landscape ecology. One of the key approaches of ecoacoustics consists in identifying sounds of ecological importance in environmental recordings that were collected in an unattended way by automatic recorders. This search task is made difficult by the occurrence of background noise due to human activities, the co-occurrence of several sounds of interest, the degradation of the sounds of interest related to their propagation in the environment, a high-degree of variability of the sounds of interest, a large amount of data, and a lack of reference archives. Solutions including computer processes are currently in development to try to get around these difficulties. This session will be the occasion to report and share new techniques involving signal analysis, machine learning, deep learning and high dimension statistics for advances in detection, segmentation, supervised and unsupervised classification of sound events.
Keywords: ecoacoustics, sound analysis, classification
- AUREAS: a tool for recognition of anuran vocalizations
William E. Gómez, Claudia V. Isaza, Sergio Gómez, Juan M. Daza and Carol Bedoya - Content description of very-long-duration recordings of the environment
Michael Towsey, Aniek Roelofs, Yvonne Phillips, Anthony Truskinger and Paul Roe - What male humpback whale song chorusing can and cannot tell us about their ecology: strengths and limitations of passive acoustic monitoring of a vocally active baleen whale
Anke Kügler and Marc Lammers - Improving acoustic monitoring of biodiversity using deep learning-based source separation algorithms
Mao-Ning Tuanmu, Tzu-Hao Lin, Joe Chun-Chia Huang, Yu Tsao and Chia-Yun Lee - Acoustic sensor networks and machine learning: scalable ecological data to advance vidence-based conservation
Matthew McKown and David Klein - Information retrieval from marine soundscape by using machine learning-based source separation
Tzu-Hao Lin, Tomonari Akamatsu, Yu Tsao and Katsunori Fujikura - A Novel Set of Acoustic Features for the Categorization of Stridulatory Sounds in Beetles
Carol Bedoya, Eckehard Brockerhoff, Michael Hayes, Richard Hofstetter, Daniel Miller and Ximena Nelson - Noise robust 2D bird localization via sound using microphone arrays
Daniel Gabriel, Ryosuke Kojima, Kotaro Hoshiba, Katsutoshi Itoyama, Kenji Nishida and Kazuhiro Nakadai - Fine-scale observations of spatiotemporal dynamics and vocalization type of birdsongs using microphone arrays and unsupervised feature mapping
Reiji Suzuki, Shinji Sumitani, Naoaki Chiba, Shiho Matsubayashi, Takaya Arita, Kazuhiro Nakadai and Hiroshi Okuno - Articulating citizen science, automatic classification and free web services for long-term acoustic monitoring: examples from bat monitoring schemes in France and UK
Yves Bas, Kevin Barre, Christian Kerbiriou, Jean-Francois Julien and Stuart Newson
S1.3 _ Computer vision in environmental sciences. (Session Chairs: Shinji Fukuda and Jeffrey Tuhtan)
Image-based methods are at the forefront of artificial intelligence applications. This special session provides a forum for researchers and professionals using image-based methods to study species, population, biodiversity and the abiotic environment.
The topics of this special session include:
-UAV imagery
-GIS/orthoimagery
-Video tracking/motion estimation
-Object recognition and classification
-High speed imaging
-Multispectral remote sensing
Keywords: image analysis, machine learning, artificial intelligence, classification/regression
- NAIRA a tool to automatic mammals genera identification in Camera Trapping Pictures
Claudia Victoria Isaza Narvaez, Luis Fernando Pulido and Angélica Diaz - Assessment of permanent grasslands in Latvia using spectral remote sensing techniques
Dainis Jakovels, Agris Brauns, Jevgenijs Filipovs, Juris Taskovs and Ruta Abaja - Exploiting Taxonomic Relations in Image-based Plant Species Classification
Marco Seeland, David Boho and Patrick Mäder - Computer vision applications using multispectral UAS imagery: comparing pixel and object-based methods for automatic classification of river landscapes
Jeffrey Tuhtan, Philipp Thumser and Christian Haas - Tracking swimming Lefua echigonia to assess the impact of crayfish introduction
Shinji Fukuda and Jeffrey Tuhtan - Trends in machine learning for plant species identification
Jana Wäldchen, Michael Rzanny, Marco Seeland and Patrick Mäder - Deep Learning for Cracking the Leaf Code
Dimitri Belousow, Georg Graser, Marco Seeland and Patrick Mäder
S1.4 _ Integrating data for analysis – how far are we? (Session Chairs: Corinna Gries, Margaret O'Brien, Kristin Vanderbilt and Colin Smith)
This session will discuss advances and tools for the second step of the data life cycle in ecological research. The first step being either field data collection and/or data discovery, the second step has been called the ‘janitorial’ step, but is mostly known as data cleaning, data harmonization, or data integration. It poses major data management challenges and is frequently a time consuming process with estimates of up to 80% of the data analysis. The reasons for this large proportion of effort range from those that cannot be addressed with technological solutions and are rooted in sampling methods to those that are related to data organization and semantics that may be addressed with developing technologies.
This session will explore the progress that is being made toward reducing the effort needed for pre-analysis data harmonization. Encouraged are: (1) reports on data integration projects spanning the range of employing and advancing semantics, ontology, linked data, specific tools, workflow systems, and standards developments, (2) considerations of an approach’s promise for a high return on the investment and/or whether it will it significantly improve documentation of data manipulations, (3) experiences and discussions focusing on comparing effectiveness in reducing time spent in data integration, (4) technological gaps and shortcomings.
Keywords: data synthesis, data integration, data harmonization
- Whip: Human and machine-readable specifications for data
Stijn Van Hoey and Peter Desmet - sPlot – the global vegetation-plot database
Francesco Maria Sabatini, Milan Chytrý, Jürgen Dengler, Florian Jansen, Borja Jiménez-Alfaro, Valério D. Pillar, Helge Bruelheide and Splot Consortium - Integration and dissemination of aquatic biodiversity and ecosystem services data for case studies focusing on ecosystem-based management
Aaike De Wever, Astrid Schmidt-Kloiber, Juan Arévalo Torres, Declan Dunne, Ana Luisa Barbosa, Koen Martens and Alejandro Iglesias Campos - The Netherlands Biodiversity Data Services and the R package nbaR: Automated workflows for biodiversity data analysis
Hannes Hettling, Maarten Schermer, Rutger Vos and Daphne Duin - Integrating data and analysis: On bridging data publishers and computational environments
Markus Stocker, Uwe Schindler and Robert Huber - Development of a reef fish community evaluation system for the Galapagos islands
Peter Goethals, Heleen Raat, Stijn Bruneel, Rafael Bermudez and Marie Anne Eurie Forio - Harmonizing long-tail ecological data sets for synthesis
Corinna Gries, Margaret O’Brien and Colin Smith - BBN models as trade-off tools for ecosystem services
Peter Goethals and Marie Anne Eurie Forio - Leveraging Cloud Computing and IoT to Improve Research Solutions for Ecological Modelling
Fabiana Santana
S1.5 _ The German Federation for Biological Data (GFBio) - from data acquisition to analysis. (Session Chairs: Michael Diepenbroek, Birgitta König-Ries and Anton Güntsch)
The German Federation for Biological Data (GFBio) aims to set up a sustainable, service oriented, national data infrastructure facilitating data sharing and stimulating data intensive science in the fields of biological and environmental research. GFBio follows a holistic approach including technical, organizational, cultural, and policy aspects. The development of the infrastructure is essentially based on the collective experience and expertise of leading researchers from multiple disciplines as well as on a network of complementary and professional data facilities in the biological and environmental sciences communities, including PANGAEA, major German natural history collection data repositories, and selected facilities from the molecular biology research community. GFBio is projected for three
phases setting out the way from development to management of services.
Keywords: data aquisition, data archiving, data discovery, terminologies, data integration, data visualization, data analysis
- The Development Of A Data Recommender System For Improving the Discovery Of Environmental And Biological Scientific Datasets
Anusuriya Devaraju, Uwe Schindler, Michael Diepenbroek, Robert Huber, Jens Klump and Markus Stocker - The EDIT Platform for Cybertaxonomy – an integrated software environment for biodiversity research data management
Anton Güntsch, Andreas Müller, Patrick Plitzner, Tilo Henning, Norbert Kilian, David Fichtmüller, Maren Gleisberg, Naouel Karam, Claudia Müller-Birn and Walter G. Berendsohn - Publishing and analysing biodiversity data rapidly, repeatably and FAIR-ly for agile policy relevant results
Quentin Groom, Sonia Vanderhoeven, Lien Reyserhove, Damiano Oldoni, Tim Adriaens and Peter Desmet - A flexible Diversity Workbench tool to publish biodiversity data from SQL database networks through platforms like GFBio
Markus Weiss, Tanja Weibulat, Stefan Seifert, Juan Carlos Monje, Marcel Ruff, Dieter Neubacher, Wolfgang Reichert and Dagmar Triebel - Managing and publishing fungal community barcoding data by use of the process-oriented schema MOD-CO and a GFBio data publication pipeline
Janno Harjes, Dagmar Triebel, Tanja Weibulat, Anton Link and Gerhard Rambold - Unfolding existing Data Publication Practice in Research Data Workflows in the Biological and Environmental Sciences – First Results from a Survey
Felicitas Löffler, Tina Astor and Claudia Müller-Birn
S1.6 _ Semantics for biodiversity and ecosystem research. (Session Chairs: Alsayed Algergawy, Clement Jonquet, Naouel Karam, Friederike Klan, Nikos Minadakis, Alessandro Oggioni and Ilaria Rosati)
Biodiversity research aims at comprehending the totality and variability of organisms, their morphology, genetics, life history, habitats and geographical ranges; including the network of interactions with the abiotic and biotic components. Ecosystem research puts its focus on how natural systems and their valuable resources can be protected and thus is tightly coupled to biodiversity. Both domains are outstanding not only with respect to their societal relevance, but also from a data science point of view. They deal with heterogeneous and distributed data resources generated from a large number of disciplines which need to be integrated to advance scientific knowledge in these areas. The presence of such a myriad of data resources makes integrative biodiversity and ecosystem research increasingly important, but at the same time very challenging. It is severely strangled by the way data and information are made available and handled today. Semantic Web techniques have shown their potential to enhance data interoperability, discovery and integration by providing common formats to achieve a formalized conceptual environment, but have not been widely applied to address open data management issues in the biodiversity domain as well as in ecosystem research.
This session aims at bringing together computer scientists, biologists and ecologists working on Semantic Web approaches in biodiversity and ecosystem research, including related areas such as agro-ecology. After the successful of a number of initiatives of the organizers, such as the “Thesauri & Semantics in the Ecological Domain”, “Ontology & Semantic Web for Web for Research” and “Semantics for Biodiversity” workshops, the goal of the session is to keep up the positive momentum and attempt to define a common strategy for advancing semantic web approaches in these domains. The goal is to present new ideas and early on experiences related to the design of high quality biodiversity and ecosystem information systems based on Semantic Web techniques and to foster the exchange on these topics between disciplines.
We welcome topics related to the development and application of semantic technologies to support research in the biodiversity and ecosystem domain and related areas. These include, but are not limited to the following areas:
· Applications of Semantic Web technologies for biodiversity
· Semantic data integration
· Development and design of domain specific ontologies
· Ontology-based applications
· Semantic annotation of biodiversity data
· Semantic approaches for the discovery of biodiversity data and research data services
· Semantic support for scientific workflows
· Data provenance and reproducibility
· Data lifecycle management
· Knowledge extraction and text mining
· Ontology learning
· Standards for biodiversity Data
· Linked Open biodiversity Data
· Ontology development for biodiversity
· Semantic representation of biodiversity and ecosystem data
· Interoperability of biodiversity and earth observation data
Keywords: semantic web, biodiversity data, ecosystem data, integrative research, semantic annotation, semantic data integration, semantic data interoperability, ontology based applications
- Extending the Environment Ontology with Text-mined Habitat Mentions
Riza Batista-Navarro, Marie-Angelique Laporte, Michael Regan, William Ulate and Claus Weiland - A Semantic Big Biodiversity Data Integration Tool
Taysir Soliman, Alsayed Algergawy, Birgitta König-Ries, Majid Askar and Marwa Abdelreheim - LakeBase Semantic Service
Jan Martin Keil - Towards an Interactive Approach for Ontology Recommendation and Reuse
Marwa Abdelreheim, Friederike Klan and Taysir Soliman - How to Search for Biological Data? A Comparison of User Interfaces in a Semantic Search
Felicitas Löffler, Friederike Klan and Birgitta Koenig-Ries - Towards a harmonization of distributed trait datasets
Florian D. Schneider, Malte Jochum, Gaetane Le Provost, Andreas Ostrowski, Caterina Penone and Nadja K. Simons - Visualizing the research ecosystem of ecosystem research via Wikidata
Daniel Mietchen, Finn Årup Nielsen and Egon Willighagen - Towards Interoperability for Observed Parameters: Position Statement of an Emerging Working Group
Barbara Magagna, Markus Stocker and Michael Diepenbroek - Extracting granular information on habitats and reproductive conditions of Dipterocarps through pattern-based literature analysis
Roselyn Gabud and Riza Theresa Batista-Navarro - Towards Semantic Data Management in LifeWatch Italy: the Phytoplankton Study Case
Nicola Fiore, Caterina Bergami, Carla Carrubba, Alessandro Oggioni, Ilaria Rosati, Elena Stanca and Paolo Tagliolato - Provenance-based Semantic Approach for the Reproducibility of Scientific Experiments
Sheeba Samuel and Birgitta König-Ries - Extraction of terms highly associated with named rivers
Juan Rojas-Garcia, Riza Batista-Navarro and Pamela Faber
Theme 2: Ecological Data Synthesis by Machine Learning and Hybrid Modelling
Keynote Talk
K3 _ Harnessing the power of big data in ecology by machine learning. (Debra P. C. Peters, USA)
My talk will be about a Trans-Disciplinary Data-Model Integration (TDMI) approach that focuses on spatio-temporal modeling and cross-scale interactions, and employs interactive machine learning strategies. Applied to ecological problems, my approach integrates knowledge and data on: (1) biological processes, (2) spatial heterogeneity in the land surface template, and (3) variability in environmental drivers using data and knowledge drawn from multiple lines of evidence (i.e., observations, experimental manipulations, analytical and numerical models, products from imagery, conceptual model reasoning, theory). I will apply this approach to a suite of increasingly complex ecologically-relevant problems, and will show how the framework can be linked with a Data Science Integration System (DSIS) to allow more complex questions to be addressed in the future.
Debra P. C. Peters does research in Systems Biology, Ecology and Bioinformatics. Her expertise is amongst others in Ecosystem Functioning, Conservation Biology, Natural Resource Management, as well as Big Data, Simulation Modeling and Machine Learning. Debra received her Ph.D. degree from Colorado State University, USA. She currently works as a Research Scientist at the Agricultural Research Service (ARS), United States Department of Agriculture (USDA), Las Cruces, USA. More information can be found at: https://www.researchgate.net/profile/Debra_Peters
Regular Sessions
R2.1 _ Understanding species distribution, population dynamics and phenology by machine learning. (Session Chairs: Antonino Staiano, Alberto Lanzoni and Friedrich Recknagel)
Inferential modelling by machine learning techniques allows efficient and user-friendly analysis and synthesis of highly complex ecological data. Methods like random forest, quantile regression forest, Maxent, GARP have been successfully applied for species distribution modelling of extensive spatial data resulting in species response curves that describe a species’ response to a given habitat condition, and illustrate specific habitat requirements for the species. Non-supervised artificial neural networks, regression trees and canonical correspondence analyses allow to ordinate and classify complex ecological data. Applications of support vector machines, supervised artificial neural networks and evolutionary algorithms to large spatial and temporal data allow to predict population dynamics and reveal phenology.
This session welcomes papers on all aspects of inferential modelling of ecological data by means of novel machine learning techniques.
- Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data
Patrick Schratz, Jannes Muenchow, Jakob Richter, Eugenia Iturritxa and Alexander Brenning - Statistically reinforced machine learning for nonlinear interactions of factors and hierarchically nested spatial patterns
Masahiro Ryo and Matthias Rillig - Reconstruction and recognition of spatial patterns from sparse data in the problem of biological invasion
Natalia Petrovskaya - Modeling Green Peach Aphid populations exposed to elicitors inducing plant resistance on peach
Alberto Lanzoni, Francesco Camastra, Angelo Ciaramella, Antonino Staiano and Giovanni Burgio - Testing the strengths of relationships between otter populations, fish and macroinvertebrate communities as well as habitat conditions across three Korean rivers by inferential modelling based on the hybrid evolutionary algorithm HEA
Sungwon Hong, Friedrich Recknagel, Tae-Soo Chon and Gea-Jae Joo - Community and Population Abundance Patterns in Benthic Macroinvertebrates in Streams Unraveled by Species Abundance Distribution and Machine Learning
Tae-Soo Chon, Kyu-Suk Kwak, Yong-Hyuck Jang, Jaehan Choi and Joo-Baek Leem - Modelling urban bird breeding sites with a random forest classifier using indicators of spatial heterogeneity in plant communities derived from earth observation data
Thilo Wellmann, Angela Lausch, Sebastian Scheuer and Dagmar Haase - Maxent modelling of spiked pepper (Piper aduncum L.) in Mindanao, Philippines
Rowena Japitana and Damasa Macandog - A machine learning approach to the assessment of the vulnerability of Posidonia oceanica meadows
Elena Catucci and Michele Scardi - Supervised learning methods to predict species interactions based on traits and phylogeny
Michiel Stock and Bernard De Baets - Overall and site-specific response of the macroinvertebrate community of the Swan Coastal Plain Wetlands (West Australia) to water quality gradients revealed by GF and HEA
Jawairia Sultana, Friedrich Recknagel, Jennifer A. Davis and Bruce C. Chessman - Causal relationships of Cylindrospermopsis dynamics with water temperature and N/P-ratios: a meta-analysis across lakes with different climate based on inferential modelling by HEA
Friedrich Recknagel, Tamar Zohary, Ilia Ostrovsky, Jacqueline Rücker, Philip Orr, Christina Castello Branco, Brigitte Nixdorf and Ricardo Tezini - Remote Sensing based Estimation of Forest Biophysical Variables using Machine Learning Algorithm
Ritika Srinet, Subrata Nandy and N. R. Patel - A mixed model approach to modelling global habitat suitability and invasion risk of the American bullfrog
Desiree Andersen and Yikweon Jang - Dynamics of four cyanobacteria in the Nakdong River, South Korea over 24 years (1993-2016) patternized by an artificial neural network
Hyo Gyeom Kim, Sungwon Hong, Dong-Kyun Kim and Gea-Jae Joo - Integrating context-based recommendation with deep CNN image classification for on-site plant species identification
Hans Christian Wittich, David Boho and Patrick Mäder
Special Sessions
S2.2 _ Why Bayesian? Integrating environmental modelling with Bayesian inference techniques. (Session Chairs: George Arhonditsis, Alex Neumann and Yuko Shimoda)
The credibility of the scientific methodology of environmental models and their adequacy to form the basis of public policy decisions have been frequently challenged. The current challenges make compelling the development of more realistic modeling platforms (i) to elucidate causal mechanisms, complex interrelationships, direct and indirect ecological paths; (ii) to examine the interactions among the various stressors (e.g., climate change, urbanization/land‐use changes, alternative management practices, invasion of exotic organisms); and (iii) to assess their potential consequences on ecosystem functioning. The proposed session aims to provide insights into the current state of the field, and also highlight the major challenges and future directions of research. Special emphasis will be placed on studies that address topics, such as novel uncertainty analysis techniques, Bayesian inference methods (including Bayesian networks), development of new model formulations and proper representation of biotic functional types, emerging techniques of data assimilation and model optimization, effective integration of physics with biology, and strategies to improve the contribution of complex models to ecological theories. The proposed session encourages contributions from both mathematical and statistical ecosystem modelers.
Keywords: bayesian inference, uncertainty analysis, environmental management, policy analysis
- Predicting Ecological Responses to Climate Variability with a Dynamic Bayesian Network Model
Neda Trifonova, Mandy Karnauskas and Chris Kelble - Uncertainty assessment of scenarios on climate and land use changes for the Millbrook catchment – reservoir system simulated by the model ensemble SWAT-SALMO
Hanh Hong Nguyen, Friedrich Recknagel and Wayne Meyer - What is a Prior and How to Find One
Song Qian - Uncertainty Analysis by Bayesian Inference
George Arhonditsis - Beyond Allopatric Speciation: Testing for Genetic Homogeneity in Duttaphrynus melanostictus in Relation to Human-induced Dispersal
Siti N. Othman, Yi-Huey Chen, Desiree Andersen, Ming-Feng Chuang, Yikweon Jang and Amaël Borzée - Integrating Hierarchical Bayes with Limnological Modelling
Yuko Shimoda and George Arhonditsis - Predicting the spatial and temporal dynamics of hypoxia in Hamilton Harbour, Ontario, Canada: A Bayesian modelling framework
Dong-Kyun Kim and George Arhonditsis - Overview of Bayesian inference techniques for conceptual semi-empirical watershed models (SPARROW, GREEN)
Alex Neumann, Dong-Kyun Kim, Feifei Dong and George Arhonditsis - Application of BBN-models to link aquatic invertebrate traits to environmental river conditions in the Guayas basin (Ecuador)
Marie Anne Eurie Forio, Wout Van Echelpoel, Niels De Troyer, Arne De Knock, Luis Dominguez and Peter Goethals - Modeling a Species Identification Process as a Bayesian Inference Problem
Oliver Bley and Patrick Mäder - Evaluating explanations of land-cover change in the Iberian agricultural revolution using approximate Bayesian computation
Andrew Lane
S2.3 _ Quantifying the functions in terrestrial ecosystems: from concepts to data driven methods. (Session Chairs: Talie Musavi, Miguel Mahecha, Xuanlong Ma and Mirco Migliavacca)
One argument for nature conservation efforts is preserving e.g. ecosystem services such as carbon sequestration potential, water and nutrient retention, among many others. To quantify such processes, we not only need a clear conceptual understanding of ecosystem functioning
but also novel ways to quantify them and understand controlling factors at various spatial and temporal scales.
In this session we invite contributions on conceptual advances to define and identify “Ecosystem Functioning”. We also aim to discuss latest developments in observing ecosystem functions from in-situ data or with proximal or remote sensing from the site level to the global scale. Innovative advances on nonlinear statistical methods, model-data integration, or inversion studies that help us to constrain ecosystem functioning or to retrieve functional properties of the ecosystems (e.g.
radiation use efficiency, nitrogen use efficiency, water use efficiency and so forth) – even if in early stages of development are also encouraged to participate as we strive for a broad session. The goal of our session is to provide a stage for those interested in understanding the ecosystem functioning combining diverse data streams or analytic frameworks.
Keywords: ecosystem function, ecosystem processes, model, in-situ data, remote sensing
- Sensitivity of potential gross primary productivity to climate drivers
Daniel E. Pabon-Moreno, Talie Musavi, Mirco Migliavacca and Miguel D. Mahecha - What controls global fire activity? Evaluating emergent responses in satellite observations and ecosystem models using machine learning
Matthias Forkel, Sandy Harrison, Niels Andela, Gitta Lasslop, Margreet van Marle, Wouter Dorigo, Matthew Forrest, Stijn Hantson, Angelika Heil, Fang Li, Stephane Mangeon, Joe Melton, Chao Yue and Almut Arneth - Insight into hydrochemistry: a multi-catchment comparison using Horizontal Visibility Graphs
Eva Klotzbücher, Holger Lange, Sebastian Sippel, Michael Hauhs and Britta Aufgebauer - Nutrient induced changes in Sun-Induced Fluorescence emission in a Mediterranean grassland
David Martini, Javier Pacheco-Labrador, Oscar Perez-Priego, Christiaan van der Tol, Tarek El-Madany, Tommaso Julitta, Micol Rossini, Anatoly Gitelson, Markus Reichstein and Mirco Migliavacca - Analyzing the time variant causality in ecological time series: a time-frequency approach
Maha Shadaydeh, Yanira Guanche Garcia, Miguel Mahecha, Markus Reichstein and Joachim Denzler - Early indicators of high impact of an invasive ecosystem engineer on ecosystem functioning from leaf to landscape scale
André Große-Stoltenberg, Christine Hellmann, Jan Thiele, Christiane Werner and Jens Oldeland - Representativeness-Based Sampling Network Design for the Arctic
Forrest M. Hoffman, Jitendra Kumar, William W. Hargrove, Martijn Pallandt and Mathias Goeckede
S2.4 _ Deep learning for environmental science and ecology. (Session Chairs: Christian Requena-Mesa, Basil Kraft, Markus Reichstein, Joachim Denzler and Marco Körner)
Deep learning is an extremely active research area in machine learning and pattern recognition communities. It has gained huge success in areas such as speech recognition, computer vision, or natural language processing. Applications in geosciences and ecology, like extracting knowledge from big-data, short-term forecasting or anomaly detection are promising, in particular since deep-learning can deal very well with space-time structures.
In this session, we invite contributions on the use of deep learning in ecology and environmental science in a series of talks lasting up to half a day (3-4 hours –1 keynote and 11-15 talks). We aim to discuss the latest developments in deep learning for insight into and prediction of ecological systems. We welcome contributions covering all aspects of ecology and environmental science, including biodiversity, climate impact, ecosystem and organismal ecology, biogeography etc.
Keywords: deep learning, machine learning, big-data, environmental science, biodiversity, organismal ecology, community ecology, ecosystem ecology
- Extracting trait data from digitized herbarium specimens using deep convolutional networks
Sohaib Younis, Marco Schmidt, Claus Weiland, Stefan Dressler, Susanne Tautenhahn, Jens Kattge, Robert Hoehndorf, Bernhard Seeger and Thomas Hickler - Habitat-Net: Habitat interpretation using deep neural nets
Anand Vashishtha, Jesse F. Abrams, Azlan Mohamed, Andreas Wilting and Anirban Mukhopadhyay - Structured observations for automated plant identification
Michael Rzanny, Jana Wäldchen, Alice Deggelmann, David Boho, Marco Seeland and Patrick Mäder - Evaluating State-of-the-art Object Detection Methods for Plant Organ Detection
Minqian Chen, Marco Seeland and Patrick Mäder - Deep Learning Approach for Mapping Arctic Vegetation using Multi-Sensor Remote Sensing Fusion
Jitendra Kumar, Zachary L. Langford and Forrest M. Hoffman - Identification and Segmentation of Whale Call Events Using Convolutional Neural Networks
Carlos de Obaldia and Udo Zölzer
Theme 3: Applications, Innovations and Communication of Eco-informatics
Keynote Talk
K4 _ A look beyond biogeographical theories: advances and challenges. (Duccio Rocchini, Italy)
Biogeographical theories on species distributions and the spatial variation of biodiversity in space and time represent a long lasting theme in ecology. The development of new modelling techniques based on spatial science and remote sensing allow nowadays to test them in a theoretical (virtual) and an empirical domain.
In this talk I will retrace the progress in ecological informatics applied to biogeography, focusing on exciting advances and major challenges.
Duccio Rocchini is Professor in Biology and Ecology at the University of Trento, Italy. He received his Ph.D. degree from the University of Siena, Italy. His main research interests are related to species distribution modelling, spatial and computational ecology and ecological remote sensing. Over the years, he promoted the use of remote sensing for the study of biodiversity change in space and time, publishing more than 120 ISI papers on this theme. He is currently Associate Editor of Ecological Informatics, being responsible for the “GIS, Remote Sensing and Biogeography” theme. More information can be found at: https://www4.unitn.it/People/en/Web/Persona/PER0196062#INFO
Special Sessions
S3.2 _ Citizen science meets informatics: Data science challenges in ecological research with public participation. (Session Chairs: Friederike Klan and Jana Wäldchen)
During the last decade, Citizen Science, i.e. the involvement of laymen in scientific research, has gained great attention, both from the public and within the scientific community. Particularly the life sciences benefit from this development as citizen scientists contribute environmental observations of high resolution, analyze large amounts of ecological data or raise entirely new research questions. In doing so, they help to tackle pressing societal challenges such as loss of biodiversity and climate change.
In addition to the issue of how to engage and empower volunteers, data science aspects are major challenges in Citizen Science projects. This includes the following questions
1.How to make sure that data collected by citizen scientists are useful and relevant for addressing scientific questions?
2.How can data collected by citizen scientists be found, accessed, interpreted and used by others?
3.How to integrate and analyze data collected by the public with other data sources?
4.How to assess and improve the quality and reliability of Citizen Science data?
5.How to increase the credibility of data collected by volunteers and how to acknowledge citizen contributions?
6.How to enable citizen scientists to gain insights from data?
While some of these topics are specific to Citizen Science, they often share challenging aspects of data-intensive science in general (e.g. How to make data findable, accessible, interoperable and re-usable?). However, despite first cross-disciplinary and Citizen Science specific initiatives such as FORCE11 and the FAIR Data Principles [1], the Cost Action “Citizen Science to promote creativity, scientific literacy, and innovation throughout Europe” [2] or first ideas on a EU Citizen Science Gateway for Biodiversity Data [3] where basic data science challenges are jointly discussed and best practices are collected, Citizen Science practitioners often address these core questions in an ad-hoc manner and individually in the context of specific projects.
We believe that the Citizen Science community would greatly benefit from an intensified scholarly exchange on data science topics related to Citizen Science across projects and disciplines. Thus, the objective of this special session is to bring together practitioners in Citizen Science projects as well as “traditional” scientists to discuss basic data science challenges arising in Citizen Science projects, to share best practices and lessons learned as well as to identify next steps towards a regular exchange on these topics and to initiate joint efforts on systematically addressing these challenges.
Keywords: citizen science, data science, data management
- Support of Forest Inventory Data Collection by Citizen Scientists
Christian Thiel, Friederike Klan, Carsten Pathe, Christiane Schmullius and Jussi Baade - Beyond Data and Quality – Unleashing the Value of Citizen Contributions
Friederike Klan - Citizen science and science-policy interface: Towards sustainable forest managements
Ryo Kohsaka, Shuichiro Kajima and Yuta Uchiyama - Crowdsourcing participatory millet variety selection in Hoima Uganda for climate change adaptation through Triadic Comparisons of Technologies
Tobias Recha, Gloria Otieno and Carlo Fadda - Wikimedia projects as citizen science platforms
Daniel Mietchen - Mobile app and platform development in citizen science
Ulrike Sturm - Planktonid – Combining in situ imaging, deep learning and citizen science for global plankton research
Rainer Kiko, Svenja Christiansen, Simon-Martin Schröder, Reinhard Koch and Lars Stemmann - sMon – Trend analysis of German biodiversity data
Aletta Bonn, David Eichenberg, Helge Bruelheide, Florian Jansen and Marten Winter - Flora Capture – An Adaptive Digital Herbarium Using Mobile Devices
David Boho, Michael Rzanny, Jana Wäldchen and Patrick Mäder
S3.3 _ Operationalizing essential biodiversity variables: aspects of data integration, production and dissemination. (Session Chairs: Néstor Fernández, W. Daniel Kissling, Robert Guralnick and Alex Hardisty)
The Group on Earth Observations – Biodiversity Observation Network (GEO BON) has the impetus to develop conceptual and technical approaches to the production of Essential Biodiversity Variables (EBVs). However, the ecological scientific community as well as those who are responsible for acquiring, curating, publishing, processing and using heterogeneous biodiversity and ecological data must invest into supporting a systematic production and use of EBVs. Such information products should be applicable to any geographic area, covering time-period(s) of interest for detecting biodiversity change at policy-relevant time scales, with data that is held in any or multiple repositories, and produced by appropriately skilled persons anywhere in the world. Within constraints of specific data types, EBV information products should be harmonised and comparable at various scales from local to global and across time, such that they can be used to monitor and measure biodiversity change.
By showcasing what has been done so far, and guided by principles of global coordination of biodiversity monitoring, this session intends to foster scientific and technical exchange and build communities of practice to support production, delivery, use and sustainability of Essential Biodiversity Variables (EBVs) data products. This session specifically aims to:
• Showcase the role and need for informatics to develop and support of the production and delivery of Essential Biodiversity Variables (EBVs) information products at scales from local to global;
• Showcase approaches for utilising and sustaining EBV information products and their adherence to FAIR (Findable, Accessible, Interoperable, Re-usable) principles.
• Provide recommendations for the production and dissemination of biodiversity observations under the EBV framework
Keywords: biodiversity monitoring, data interoperability, global change, global observation systems, GEO BON, research infrastructures
- 10 outcomes to improve informatics interoperability in cyber / e-Infrastructures for biodiversity and ecological sciences through the Essential Biodiversity Variables (EBV) use case
Alex Hardisty - Towards an EBV Analyzer based on VAT
Christian Beilschmidt, Johannes Drönner, Néstor Fernández, Christian Langer, Michael Mattig and Bernhard Seeger - Minimum Information Standards for Essential Biodiversity Variables
Néstor Fernández, Robert Guralnick and W. Daniel Kissling - Towards structured biodiversity data
Henrique Pereira - Developing and implementing a general standard for inventory data
Robert Guralnick, Ramona Walls and Walter Jetz
S3.5 _ Plant traits and biogeochemical cycles. (Session Chairs: Jens Kattge, Susanne Tautenhahn, Michael Bahn, Han Wang and Oskar Franklin)
Plant traits extend the range of earth observations to the level of individual organisms, providing a link to ecosystem function and modeling in the context of rapid global changes. However, overcoming the differences in temporal and spatial scales between plant trait data and biogeochemical cycles remains a challenge.
This session will address the role of plant species, biodiversity and adaptation / acclimation / optimality and their connection to the biogeochemical cycles of water, carbon, nitrogen and phosphorus.
We welcome conceptual, observational, experimental and modeling approaches, and studies from the local to the global scale, including e.g. remote sensing observations and novel concepts and tools for the acquisition, management, analysis and synthesis of trait data.
Keywords: plant traits, biogeochemical cycles, functional biogeography, ecosystem modelling, plant adaptation / acclimation / optimality
- Biophysical modelling of risks and feedbacks from forest fires: the role of plant traits
Philip Zylstra - Variability in community productivity: mediation by vegetation traits
Wayne Polley and Brian Wilsey - Inconstant exponents of scaling leaf nitrogen to phosphorus
Di Tian, Zhengbing Yan and Jingyun Fang - How do nitrogen and phosphorus supply affect elemental stoichiometry in plant leaves? Using experimental manipulations of Arabidopsis thaliana
Zhengbing Yan, Wenxuan Han, Di Tian and Jingyun Fang - The TRY Database System
Gerhard Boensich, Jens Kattge and Christian Wirth - SCOPE model inversion for Sentinel-3 data retrieval
Egor Prikaziuk and Christiaan Van der Tol - Plant functional groups for carbon and nitrogen cycle modelling and diversity estimation in boreal forest ecosystems
Larisa Khanina, Maxim Bobrovsky, Vadim Smirnov and Nataliya Lukina - A general framework for global mapping of plant traits with operational satellites and climatological data
Alvaro Moreno Martinez, Gustau Camps Valls, Jens Kattge, Nuno Carvalhais, Markus Reichstein, Emma Izquierdo, Daniel Heestermans Svendsen and Steven W Running - Potentials and challenges of remote sensing functional trait diversity by integrating high-resolution spaceborne multispectral and radar measurements
Xuanlong Ma, Miguel Mahecha, Mirco Migliavacca, Talie Musavi, Fons van der Plas, Ronny Richter, Sophia Ratcliffe, Raquel Benavides, Daniel Pabon, Timo Domisch, Leena Finér, Jens Kattge, Markus Reichstein and Christian Wirth - How are spectrally relevant plant traits distributed across plant functional gradients?
Teja Kattenborn and Sebastian Schmidtlein - Remote sensing for the observation of senescence in Conference pear trees
Laura Paladini, Stephaniie Delalieux, Laurent Tits and Ben Somers - Towards the Automatic Extraction of Plant Traits from Textual Descriptions
Onatkut Dagtekin, William Ulate and Riza Batista-Navarro - Phenological diversity is linked to the diversity of functional traits in alpine grasslands
Gianluca Filippa, Edoardo Cremonese, Marta Galvagno, Mirco Migliavacca, Christine Römermann, Solveig Franziska Bucher and Talie Musavi - Spatiotemporal trends of carbon residence time across global forests: linking plant traits, soil properties, and climate change
Kailiang Yu, William Anderegg and Tom Crowther
S3.6 _ Efficient data and workflow management for reaching Sustainable Development Goals (SDGs) targets associated to biodiversity and ecosystems. (Session Chairs: Jan Bumberger, Jitendra Gaikwad and Aidin Niamir)
The Sustainable Development Goals (SDGs) are a collection of 17 global goals, including zero hunger, good health and well-being, climate action, clean water and sanitation, affordable and clean energy, that has been agreed by international communities to be hopefully achieved by 2030. Monitoring progress towards these goals require a reliable data and information which are accessible and reproducible over time and space. Earth Observation (EO) products can potentially address such a need for trusted sources of data to monitor the trends of environmental conditions (i.e. essential variables), and also inform models to predict progress (i.e. indicators) towards policy targets over variety of scenarios. However, efficient management of big earth observation datasets and reproducible modeling workflows remains a challenge.
In this session we want to bring together experts representing broad range of experience in applications related to SDGs with a special focus on biodiversity and ecosystem services. We invite contributions presenting challenges, solutions, cases studies, and best practices dealing with big data and modeling workflows management. We intend to discuss on the list (not excluding) of following topics:
– Efficient data management approaches along the chain of information from field data to derived indicators taking into account the uncertainties
– Standardized and operationalized data quality assurance and fusion approaches for biotic, abiotic and other EO data
– From data to variable, and from variable to indicator workflows for biodiversity and ecosystem services
– Best practices to improve interoperability
– Uncertainty/data reliability
Keywords: Sustainable Development Goals (SDGs), Earth Observation (EO), data management, data quality assurance, data fusion, wodeling workflows management, indicator workflows, biodiversity
ecosystem services, uncertainty/data reliability
- Data lifecycle is not a cycle, but a plane!
Javad Chamanara and Birgitta König-Ries - Data science for environmental health
Angela Lausch, Jan Bumberger, Steffen Zacharias, Peter Dietrich, Josef Settele and Sonja Knapp - Green Infrastructures and Essential Variables Workflows towards SDG 15
Erica Honeck, Anthony Lehmann, Diana-Denisa Rodila and Gregory Giuliani - moveStore: an extensible cloud-based framework for applications dealing with movement data
Babak Naimi and Kamran Safi - Community-curated Linked Open Data about the Sustainable Development Goals, their targets and indicators
Daniel Mietchen - Methods of calculating indicators of the sustainable development goals using biophysical modelling and classification of the land cover in Nexus Approach
Leonid Shumilo, Nataliia Kussul and Mykola Lavreniuk - Automated and efficient workflow for large airborne remote sensing vegetation mapping and research of Natura 2000 habitats
Adam Kania, Dominik Kopeć, Jan Niedzielko and Łukasz Sławik - ProSIt: An Ontology-based Reference Process to Provide Interoperability and Foster Database Integration for Biodiversity Data
Fabiana Santana, Silvia Scheunemann, Anarosa Brandão and Antonio Saraiva
S3.8 _ Using BEXIS 2 to facilitate science from data collection to data publication. (Session Chairs: Roman Gerlach, Javad Chamanara, Sven Thiel, David Schöne and Nafiseh Navabpour)
This session is dedicated to researchers using the BEXIS 2 research data management platform. We invite short presentations from the user community that showcase the usage of BEXIS 2. Showcases can be related to any data management aspect (e.g. metadata creation, data structure definition, data publication) supported by BEXIS 2. In addition, we encourage users to contribute potential features and improvements that they would like to see in BEXIS 2.
Contributed presentations should, first, describe a specific data management problem, and then demonstrate a solution within BEXIS 2. Besides such showcase we encourage any other experience report. Although presentations are expected primarily from the users community (i.e. researchers), we also expect a number of developers and data managers of BEXIS 2 instances to be present in the session, which may lead to some fruitful discussion. After each talk there will be time for discussion.
This session is intended to provide a forum for the BEXIS community, which in previous years met at the annual BEXIS User and Developer Conference. This year the conference has been suspended in favour of the ICEI conference. However, the session is open to anyone else interested in BEXIS 2.
Keywords: research data management, BEXIS 2 platform, data sharing, data publication, open source software
- Using BEXIS 2 as efficient research data management system for the ATTO research project
Marcus Guderle, Jošt V. Lavrič, David Schöne and Susan Trumbore - Showcase: Biodiversity Exploratories Information System – Report of our data migration to a new BEXIS2 instance
Andreas Ostrowski, Eleonora Petzold and Sirko Schindler - Enhance BEXIS2: from pure data management to an information system
Andreas Ostrowski and Eleonora Petzold - Research data management with BEXIS 2 – An overview and introduction to the special session
Roman Gerlach, David Blaa, Javad Chamanara, Nafiseh Navabpour, Sven Thiel and Martin Hohmuth - Data Visualization: a new module for BEXIS 2
Nafiseh Navabpour and Roman Gerlach
Poster Presentations and Computer Demonstrations
Poster Presentations
- Towards truly automatic bird audio detection: an international challenge
Dan Stowell - Does the Climate Change affect the Net Water Budget of the Terrestrial Biosphere?
Abdulla Sakalli and Mehmet Ugur Gucel - Assessing Ecosystem Change using Soundscape Analysis
Diana C. Duque-Montoya, Claudia Isaza and Juan M. Daza - MatlabHTK: a simple interface for bioacoustic aanalyses using hidden Markov models
Louis Ranjard - MAAD, a rational unsupervised method to estimate diversity in ecoacoustic recordings
Juan Sebastian Ulloa, Thierry Aubin, Sylvain Haupert, Chloé Huetz, Diego Llusia, Charles Bouveyron and Jerome Sueur - Underwater acoustic habitats: towards a toolkit to assess acoustic habitat quality
Irene Roca and Ilse Van Opzeeland - Trends and biases in ecology concepts during the last century
Shengqi Dai, Bin Zhao and Hong Li - Focus on geophony: what weather sounds can tell
Roberta Righini and Gianni Pavan - Using robustness as a tool for the assessment of ecosystem health – a case study from Hooghly Matla estuary, India
Nabyendu Rakshit and Santanu Ray - DeltaMP: A flexible, reproducible and resource efficient pipeline for the analysis of high-throughput amplicon sequencing data of eukaryotes
Christina Weißbecker, Anna Heintz-Buschart, Tesfaye Wubet, Franҫois Buscot and Guillaume Lentendu - Reverse Wavelet Interference Algorithm for Detection of Avian Species and Characterization of Biodiversity
Sajeev C Rajan, Athira K and Jaishanker R - Automatic Bird Sound Detection: Logistic Regression Based Acoustic Occupancy Model
Yi-Chin Tseng, Bianca Eskelson and Kathy Martin - A software detector for monitoring endangered common spadefoot toad populations
Guillaume Dutilleux and Charlotte Curé - Query Processing in Ontology Based Data Access
Majid Askar, Alsayed Algergawy, Taysir Soliman, Birgitta König-Ries and Adel Sewisy - Satellite-based monitoring of invasive woody species in central Chile
Anne Clasen, Michael Foerster, Tobias Schmidt, Fabian E. Fassnacht and Birgit Kleinschmit - Ecological observations and conservation strategies of a threatened – endemic plant (Wendlandia angustifolia Wight ex Hook.f.) in the forests of Western Ghats, India
Muthumperumal Chellam and Balasubramanian Paramasivam - Biodiversity implications of international trade: comparison of species threatened from alternative electricity production with natural gas or concentrated solar power
Irene Rodríguez-Serrano, Natalia Caldés and Yolanda Lechón - Automating the integration and accessibility of diverse geospatial data cubes
Heather Savoy and Debra Peters - Improved environmental monitoring of air and water quality by combination of high throughput image cytometry and deep learning
Susanne Dunker, David Boho, Jana Wäldchen and Patrick Mäder - Definition of the concept of Green Infrastructure and its implementation
Arthur Sanguet, Erica Honeck, Anthony Lehmann and Nicolas Wyler - Analyzing the effect of armed conflict, agriculture and fire on the movement and migratory behaviour of White eared kob and Roan antelope in the Boma-Gambella landscape of Ethiopia and South Sudan.
Kasahun Abera and Afework Bekele - Towards FAIR data in Biodiversity Exploratories project
Andreas Ostrowski, Eleonora Petzold and Cornelia Fürstenau - Towards Automatic Identification of Elephants in the Wild
Matthias Körschens, Björn Barz and Joachim Denzler - Continuous ecoacoustic long-term monitoring of a pristine coral reef: when data-intensive ecology responds directly to ecosystem management objectives
Simon Elise, Marion Couëdel and Henrich Bruggemann - Biofid, a platform to enhance accessibility of biodiversity data
Claus Weiland, Christine Driller, Markus Koch, Marco Schmidt, Giuseppe Abrami, Sajawel Ahmed, Alexander Mehler, Adrian Pachzelt, Gerwin Kasperek, Angela Hausinger and Thomas Hörnschemeyer - Drivers of diurnal and seasonal soundscape patterns in temperate grasslands
Sandra Mueller and Michael Scherer-Lorenzen - Traditional vs. modern Citizen Sciences in Phenology – an example of DWD, ZAMG and naturgucker.de
Saskia Pietzsch, Thomas Hübner and Gaby Schulemann-Maier - Galaxy-E, towards a complete open source workflow oriented e-infrastructure in Ecology?
Yvan Le Bras, Valentin Chambon, Alan Amosse, Elisa Michon, Clara Urfer, Julien Sananikone, Elise Brax, Marianne Linares, Marie Delannoy, Gregoire Lois and Romain Julliard - A Data Mining Approach for Species Co-occurrence Prediction
Dina Sharafeldeen, Alsayed Algergawy and Birgitta König-Ries - Using multi-temporal RapidEye remote sensing data to map semi-natural grassland communities
Christoph Raab, Hans Georg Stroh, Bettina Tonn, Marcus Meißner, Nina Rohwer, Niko Balkenhol and Johannes Isselstein - RefYolo: Refining YOLO for detecting objects from digitized herbarium specimen images
Abdelaziz Triki, Bassem Bouaziz and Jitendra Gaikwad - Assessing biodiversity from space – An example from the diverse tropical mountain rainforests
Christine Isabeau Bernarde Wallis, Nina Farwig, Roland Brandl and Jörg Bendix - Interactive Plant Identification in Flora Key
Oliver Bley, Jana Wäldchen and Patrick Mäder - PylotWhale a python package for automatically annotating bioacoustic recordings
Maria Florencia Noriega Romero Vargas, Heike Vester and Marc Timme - Effects of environmental variables and zooplankton on Picocyanobacteria dominance in two tropical mesotrophic reservoirs
Maria Isabel Rocha, Friedrich Recknagel, Vera L. Huszar, Betina Kozlowsky-Suzuki, Hongqing Cao, Fernando Starling, Ewerton Oliveira and Christina Castelo Branco - Connecting remote sensing and in situ measurements in river-lake chain research
Christine Kiel, Stella A Berger, Sabine Wollrab, Jens C Nejstgaard, Hans-Peter Grossart, Gabriel Singer, Franz Hölker, Andreas Jechow, Jürgen Fischer, Thomas Ruhtz, Peter Gege, Torsten Sachs, Matthias Labrenz, Gunnar Lischeid, Rüdiger Röttgers and Thomas Schneider - Spatial localization of vocalizations of Spotted Towhee (Pipilo maculatus) in playback experiments using robot audition techniques
Shinji Sumitani, Reiji Suzuki, Shiho Matsubayashi, Takaya Arita, Kazuhiro Nakadai and Hiroshi G. Okuno - An overview of the Saint-Pierre-and-Miquelon marine soundscape
Paul Nguyen Hong Duc, Dorian Cazau, Olivier Adam, Odile Gérard and Paul White - RSonde Tool: A project for developing a reservoir monitoring tool coupling remote sensing and high frequency in situ data.
Carmen Cillero Castro, Jordi Delgado Martin, Ramón Alberto Díaz Varela, José Antonio Domínguez, Boris Alejandro Hinojo, Jose Luis Cereijo, David García, Federico Cheda and Marco Rubinos - Analysis of almost a hundred long distance migration paths of Italian and Swiss barn swallows (Hirundo rustica) reconstructed on the basis of light level geolocators
Mattia Pancerasa, Roberto Ambrosini, David W. Winkler, Eldar Rakhimberdiev, Diego Rubolini, Felix Liechti, Nicola Saino and Renato Casagrandi - Multimodal Plant Species Identification
Hans Christian Wittich, David Boho and Patrick Mäder - Content-based Image Retrieval for Biodiversity: A Comparative Study
Nora Youssef and Alsayed Algergawy - Nocturnal bird migration on the Baltic Sea coast
Hanna Pamuła and Maciej Kłaczyński - Plant Diseases prediction using Deep Learning
Jihen Amara, Bassem Bouaziz and Alsayed Algergawy - Specimen-GT tool : Ground Truth Annotation tool for herbarium Specimen images
Bassem Bouaziz, Rochdi Benali, Abdelaziz Triki and Jitendra Gaikwad - Developping semantic interoperability in ecology and ecosystem studies: the AnaEE infrastructure framework
Christian Pichot - Improving the Quality of Biodiversity Data Through Semantic Web Standards
Marcos Zarate, Mirtha Lewis, Pablo Fillottrani and Claudio Delrieux - ADOnIS – An ontology-based information system providing seamless integration of structured and unstructured data
Alsayed Algergawy, Friederike Klan, Erik Faessler, Birgitta König-Ries, Udo Hahn, Hamdi Hamed and Bernd Kampe - DiSSCo – The Distributed System of Scientific Collections
Niels Raes, Wouter Addink, Dimitris Koureas, and the DiSSCo consortium - Extracting information on bat activities from long-term ultrasonic recordings through sound separation
Chia-Yun Lee, Tzu-Hao Lin and Mao-Ning Tuanmu
Computer Demonstrations
- BirdNET: Real-time Bird Sound Identification using Convolutional Neural Networks
Stefan Kahl, Thomas Wilhelm-Stein, Holger Klinck, Danny Kowerko and Maximilian Eibl - Unfolding existing Data Publication Practice in Research Workflows in the Life Sciences
Felicitas Löffler, Tina Astor and Claudia Müller-Birn - Galaxy-E,open source workflow oriented platform for Ecological data access and analysis
Valentin Amosse, Alan Amosse, Elisa Michon, Clara Urfer and Yvan Le Bras - Demonstration of the R package nbaR: Automated access to the Netherlands Biodiversity Data Services
Hannes Hettling, Maarten Schermer, Rutger Vos and Daphne Duin - Showcase: Towards an EBV Data Portal
Christian Langer, Nestor Fernandez, Christian Beilschmidt, Johannes Drönner, Michael Mattig and Bernhard Seeger - TraitEx: tool for measuring morphological functional traits from digitized herbarium specimens
Jitendra Gaikwad, Abdelaziz Triki, Bassem Bouaziz, Hamdi Hamed and Jörn Hentschel - BioOntoVis : Ontologies Visualization Tool for biodiversity
Nassira Achich, Bassem Bouaziz, Alsayed Algergawy and Birgitta Koenig-Ries - Research data management in action – demonstrating the full range of features of the BEXIS 2 platform
Roman Gerlach, Andreas Ostrowski, Jitendra Gaikwad and Alsayed Algergawy
Bayesian belief networks for integrated ecological modelling to assess communities and ecosystem services
Saturday, 29.09.2018, 09:00-17:00
course and hands-on
Lecturers
Peter Goethals, PhD, Ghent University, contact: peter.goethals@ugent.be
Marie Anne Eurie Forio, PhD, Ghent University, contact: marie.forio@ugent.be
Brief description of the course content
The course aims at giving insights into the strengths and potential applications of BBN
networks to model and analyze species distributions, communities as well as ecosystem
services. The course is aimed at participants with basic ecological and modelling knowledge,
but even participants with limited computer background should be able to follow. Every
aspect of the hands-on exercises is learned from scratch, and no experience is needed with
programming or particular software packages. Slides, texts and databases will be on-line
disseminated at the start of the course.
Important is to bring a laptop, preferably will a loaded battery, on which the free version of
Netica is installed. You can download this software for free here. Versions are available for both Windows as Mac.