AIMC Topic: Endangered Species

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Environmental drivers of calling activity in the critically endangered lemur leaf frog, (Hylidae: Phyllomedusinae).

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Tropical frog species are known to exhibit high sensitivity to weather regime alterations, which leaves them vulnerable to ongoing climate change. This challenge is exacerbated by limited knowledge of species-specific responses to environmental chang...

Semen collection, semen analysis and artificial insemination in the kākāpō (Strigops habroptilus) to support its conservation.

PloS one
The critically endangered kākāpō (Strigops habroptilus) has suffered population declines due to habitat loss, hunting, and predation. Conservation efforts, including translocation to predator-free islands, have helped increase numbers of this flightl...

Hierarchical image classification using transfer learning to improve deep learning model performance for amazon parrots.

Scientific reports
Numerous studies have proven the potential of deep learning models for classifying wildlife. Such models can reduce the workload of experts by automating species classification to monitor wild populations and global trade. Although deep learning mode...

Automatic identification of the endangered hawksbill sea turtle behavior using deep learning and cross-species transfer learning.

The Journal of experimental biology
The accelerometer, an onboard sensor, enables remote monitoring of animal posture and movement, allowing researchers to deduce behaviors. Despite the automated analysis capabilities provided by deep learning, data scarcity remains a challenge in ecol...

Automatedly identify dryland threatened species at large scale by using deep learning.

The Science of the total environment
Dryland biodiversity is decreasing at an alarming rate. Advanced intelligent tools are urgently needed to rapidly, automatedly, and precisely detect dryland threatened species on a large scale for biological conservation. Here, we explored the perfor...

Optimization of diosgenin extraction from Dioscorea deltoidea tubers using response surface methodology and artificial neural network modelling.

PloS one
INTRODUCTION: Dioscorea deltoidea var. deltoidea (Dioscoreaceae) is a valuable endangered plant of great medicinal and economic importance due to the presence of the bioactive compound diosgenin. In the present study, response surface methodology (RS...

Automated conservation assessment of the orchid family with deep learning.

Conservation biology : the journal of the Society for Conservation Biology
International Union for Conservation of Nature (IUCN) Red List assessments are essential for prioritizing conservation needs but are resource intensive and therefore available only for a fraction of global species richness. Automated conservation ass...

Bat detective-Deep learning tools for bat acoustic signal detection.

PLoS computational biology
Passive acoustic sensing has emerged as a powerful tool for quantifying anthropogenic impacts on biodiversity, especially for echolocating bat species. To better assess bat population trends there is a critical need for accurate, reliable, and open s...

Effects of hormonal stimulation on the concentration and quality of excreted spermatozoa in the critically endangered Panamanian golden frog (Atelopus zeteki).

Theriogenology
Knowledge of basic gamete biology is critical to better protect and propagate endangered amphibian species and also to develop reproductive technologies combined with germplasm cryopreservation. The objectives of the study were to test different horm...

Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation.

Sensors (Basel, Switzerland)
Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as...