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Biodiversity

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Modeling CRISPR gene drives for suppression of invasive rodents using a supervised machine learning framework.

PLoS computational biology
Invasive rodent populations pose a threat to biodiversity across the globe. When confronted with these invaders, native species that evolved independently are often defenseless. CRISPR gene drive systems could provide a solution to this problem by sp...

DiversityScanner: Robotic handling of small invertebrates with machine learning methods.

Molecular ecology resources
Invertebrate biodiversity remains poorly understood although it comprises much of the terrestrial animal biomass, most species and supplies many ecosystem services. The main obstacle is specimen-rich samples obtained with quantitative sampling techni...

Simulation and Prediction of Fungal Community Evolution Based on RBF Neural Network.

Computational and mathematical methods in medicine
Simulation and prediction of the scale change of fungal community. First, using the experimental data of a variety of fungal decomposition activities, a mathematical model of the decomposition rate and the relationship between the bacterial species w...

Camera Assisted Roadside Monitoring for Invasive Alien Plant Species Using Deep Learning.

Sensors (Basel, Switzerland)
Invasive alien plant species (IAPS) pose a threat to biodiversity as they propagate and outcompete natural vegetation. In this study, a system for monitoring IAPS on the roadside is presented. The system consists of a camera that acquires images at h...

Farm robots: ecological utopia or dystopia?

Trends in ecology & evolution
Farm robots may lead to an ecological utopia where swarms of small robots help in overcoming the yield penalties and labor requirements associated with agroecological farming - or a dystopia with large robots cultivating monocultures. Societal discus...

Artificial neural network analysis of microbial diversity in the central and southern Adriatic Sea.

Scientific reports
Bacteria are an active and diverse component of pelagic communities. The identification of main factors governing microbial diversity and spatial distribution requires advanced mathematical analyses. Here, the bacterial community composition was anal...

Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment.

PLoS computational biology
Convolutional Neural Networks (CNNs) are statistical models suited for learning complex visual patterns. In the context of Species Distribution Models (SDM) and in line with predictions of landscape ecology and island biogeography, CNN could grasp ho...

Autonomous Marine Robot Based on AI Recognition for Permanent Surveillance in Marine Protected Areas.

Sensors (Basel, Switzerland)
The world's oceans are one of the most valuable sources of biodiversity and resources on the planet, although there are areas where the marine ecosystem is threatened by human activities. Marine protected areas (MPAs) are distinctive spaces protected...

Explainable AI reveals changes in skin microbiome composition linked to phenotypic differences.

Scientific reports
Alterations in the human microbiome have been observed in a variety of conditions such as asthma, gingivitis, dermatitis and cancer, and much remains to be learned about the links between the microbiome and human health. The fusion of artificial inte...

A comparison of two remotely operated vehicle (ROV) survey methods used to estimate fish assemblages and densities around a California oil platform.

PloS one
Offshore oil and gas platforms have a finite life of production operations. Once production ceases, decommissioning options for the platform are assessed. The role that a platform's jacket plays as fish habitat can inform the decommissioning decision...