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- research-articleAugust 2024
Maxent modelling combined with fuzzy logic provides new insights into Predicting the distribution of potato cyst nematodes with limited data
Computers and Electronics in Agriculture (COEA), Volume 222, Issue Chttps://doi.org/10.1016/j.compag.2024.109035Graphical abstractDisplay Omitted
Highlights:- Tests niche similarity of two potato cyst nematode species with fuzzy logic.
- Integrated dataset improved model accuracy, mitigating data deficiency.
- Comprehensive model comparison supported a better performance.
- One tool for ...
Global potato trade has resulted in the spread of potato cyst nematodes (PCNs) worldwide, which causes significant agricultural and economic loss. Predicting the potential habitats and risk regions for PCNs is critical for management and ...
- ArticleApril 2023
LifeCLEF 2023 Teaser: Species Identification and Prediction Challenges
- Alexis Joly,
- Hervé Goëau,
- Stefan Kahl,
- Lukáš Picek,
- Christophe Botella,
- Diego Marcos,
- Milan Šulc,
- Marek Hrúz,
- Titouan Lorieul,
- Sara Si Moussi,
- Maximilien Servajean,
- Benjamin Kellenberger,
- Elijah Cole,
- Andrew Durso,
- Hervé Glotin,
- Robert Planqué,
- Willem-Pier Vellinga,
- Holger Klinck,
- Tom Denton,
- Ivan Eggel,
- Pierre Bonnet,
- Henning Müller
AbstractBuilding accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants,...
- ArticleMarch 2021
LifeCLEF 2021 Teaser: Biodiversity Identification and Prediction Challenges
- Alexis Joly,
- Hervé Goëau,
- Elijah Cole,
- Stefan Kahl,
- Lukáš Picek,
- Hervé Glotin,
- Benjamin Deneu,
- Maximilien Servajean,
- Titouan Lorieul,
- Willem-Pier Vellinga,
- Pierre Bonnet,
- Andrew M. Durso,
- Rafael Ruiz de Castañeda,
- Ivan Eggel,
- Henning Müller
AbstractBuilding accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants ...
- ArticleJanuary 2021
How Do Deep Convolutional SDM Trained on Satellite Images Unravel Vegetation Ecology?
Pattern Recognition. ICPR International Workshops and ChallengesPages 148–158https://doi.org/10.1007/978-3-030-68780-9_15AbstractSpecies distribution models (SDM) assess and predict how species spatial distributions depend on the environment, due to species ecological preferences. These models are used in many different scenarios such as conservation plans or monitoring of ...
- ArticleApril 2020
LifeCLEF 2020 Teaser: Biodiversity Identification and Prediction Challenges
- Alexis Joly,
- Hervé Goëau,
- Stefan Kahl,
- Christophe Botella,
- Rafael Ruiz De Castaneda,
- Hervé Glotin,
- Elijah Cole,
- Julien Champ,
- Benjamin Deneu,
- Maximillien Servajean,
- Titouan Lorieul,
- Willem-Pier Vellinga,
- Fabian-Robert Stöter,
- Andrew Durso,
- Pierre Bonnet,
- Henning Müller
AbstractBuilding accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying ...
- research-articleMarch 2020
ENMTML: An R package for a straightforward construction of complex ecological niche models
Environmental Modelling & Software (ENMS), Volume 125, Issue Chttps://doi.org/10.1016/j.envsoft.2019.104615AbstractEcological niche models (ENMs) is a popular method in ecology, mostly due to its broad applicability and the fact that required data is simple and easily accessible from digital databases. Nevertheless, there is an underlying ...
Highlights- We present ENMTML, an open source R package to fit ecological niche models (ENMs).
- research-articleMay 2019
Predicting the Habitat for Alien Species based on GIS
CSSE '19: Proceedings of the 2nd International Conference on Computer Science and Software EngineeringPages 1–5https://doi.org/10.1145/3339363.3339364Invasive organisms have broken the ecosystems around the world, and the economic losses are huge. It is vital to actively respond to the invasion of harmful organisms and protect the ecological environment in which we live. Predicting the habitats for ...
- ArticleApril 2019
LifeCLEF 2019: Biodiversity Identification and Prediction Challenges
- Alexis Joly,
- Hervé Goëau,
- Christophe Botella,
- Stefan Kahl,
- Marion Poupard,
- Maximillien Servajean,
- Hervé Glotin,
- Pierre Bonnet,
- Willem-Pier Vellinga,
- Robert Planqué,
- Jan Schlüter,
- Fabian-Robert Stöter,
- Henning Müller
AbstractBuilding accurate knowledge of the identity, the geographic distribution and the evolution of living species is essential for a sustainable development of humanity, as well as for biodiversity conservation. However, the burden of the routine ...
- research-articleFebruary 2018
Ensemble species distribution modelling with transformed suitability values
Environmental Modelling & Software (ENMS), Volume 100, Issue CPages 136–145https://doi.org/10.1016/j.envsoft.2017.11.009Species distribution modelling (SDM) was integrated in version 2.0 of the BiodiversityR package released in 2012. Ensemble habitat suitability is calculated as the weighted average of suitabilities predicted by different algorithms. Advanced options for ...
