AIMC Topic: Biodiversity

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Sound evidence for biodiversity monitoring.

Science (New York, N.Y.) Jul 11, 2024
Bioacoustics and artificial intelligence facilitate ecological studies of animal populations.
Biodiversity Extinction, Biological Biological Monitoring Artificial Intelligence Animals
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Innovative infrastructure to access Brazilian fungal diversity using deep learning.

PeerJ Jul 9, 2024
In the present investigation, we employ a novel and meticulously structured database assembled by experts, encompassing macrofungi field-collected in Brazil, featuring upwards of 13,894 photographs representing 505 distinct species. The purpose of ut...
Fungi Neural Networks, Computer Brazil Biodiversity Databases, Factual Deep Learning
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Enhancing microalgae classification accuracy in marine ecosystems through convolutional neural networks and support vector machines.

Marine pollution bulletin Jun 26, 2024
Accurately classifying microalgae species is vital for monitoring marine ecosystems and managing the emergence of marine mucilage, which is crucial for monitoring mucilage phenomena in marine environments. Traditional methods have been inadequate due...
Neural Networks, Computer Ecosystem Biodiversity Microalgae Environmental Monitoring Support Vector Machine
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Species delimitation 4.0: integrative taxonomy meets artificial intelligence.

Trends in ecology & evolution Jun 6, 2024
Although species are central units for biological research, recent findings in genomics are raising awareness that what we call species can be ill-founded entities due to solely morphology-based, regional species descriptions. This particularly appli...
Biodiversity Classification Artificial Intelligence Genomics
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Machine learning-based surrogate modelling of a robust, sustainable development goal (SDG)-compliant land-use future for Australia at high spatial resolution.

Journal of environmental management Jun 5, 2024
We developed a high-resolution machine learning based surrogate model to identify a robust land-use future for Australia which meets multiple UN Sustainable Development Goals. We compared machine learning models with different architectures to pick t...
Machine Learning Sustainable Development Ecosystem Conservation of Natural Resources Agriculture Australia Models, Theoretical Biodiversity
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Leveraging AI to improve evidence synthesis in conservation.

Trends in ecology & evolution May 24, 2024
Systematic evidence syntheses (systematic reviews and maps) summarize knowledge and are used to support decisions and policies in a variety of applied fields, from medicine and public health to biodiversity conservation. However, conducting these exe...
Artificial Intelligence Conservation of Natural Resources Biodiversity
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Multispecies deep learning using citizen science data produces more informative plant community models.

Nature communications May 24, 2024
In the age of big data, scientific progress is fundamentally limited by our capacity to extract critical information. Here, we map fine-grained spatiotemporal distributions for thousands of species, using deep neural networks (DNNs) and ubiquitous ci...
Deep Learning Citizen Science Ecosystem Biodiversity Models, Biological Plants Switzerland Seasons
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Assessing the influence of landscape conservation and protected areas on social wellbeing using random forest machine learning.

Scientific reports May 18, 2024
The urgency of interconnected social-ecological dilemmas such as rapid biodiversity loss, habitat loss and fragmentation, and the escalating climate crisis have led to increased calls for the protection of ecologically important areas of the planet. ...
Africa Random Forest Machine Learning Biodiversity Psychological Well-Being Humans Ecosystem Conservation of Natural Resources
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DeepDive: estimating global biodiversity patterns through time using deep learning.

Nature communications May 17, 2024
Understanding how biodiversity has changed through time is a central goal of evolutionary biology. However, estimates of past biodiversity are challenged by the inherent incompleteness of the fossil record, even when state-of-the-art statistical meth...
Extinction, Biological Aquatic Organisms Animals Biological Evolution Biodiversity Computer Simulation Fossils Deep Learning
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Automated identification of aquatic insects: A case study using deep learning and computer vision techniques.

The Science of the total environment May 11, 2024
Deep learning techniques have recently found application in biodiversity research. Mayflies (Ephemeroptera), stoneflies (Plecoptera) and caddisflies (Trichoptera), often abbreviated as EPT, are frequently used for freshwater biomonitoring due to thei...
Insecta Ephemeroptera Environmental Monitoring Fresh Water Aquatic Organisms Biodiversity Animals Deep Learning Neural Networks, Computer
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