A predictive timeline of wildlife population collapse
Contemporary rates of biodiversity decline emphasize the need for reliable ecological
forecasting, but current methods vary in their ability to predict the declines of real-world …
forecasting, but current methods vary in their ability to predict the declines of real-world …
Novel community data in ecology-properties and prospects
New technologies for monitoring biodiversity such as environmental (e) DNA, passive
acoustic monitoring, and optical sensors promise to generate automated spatiotemporal …
acoustic monitoring, and optical sensors promise to generate automated spatiotemporal …
Overview of lifeclef 2024: Challenges on species distribution prediction and identification
Biodiversity monitoring using machine learning and AI-based approaches is becoming
increasingly popular. It allows for providing detailed information on species distribution and …
increasingly popular. It allows for providing detailed information on species distribution and …
Accurate detection and identification of insects from camera trap images with deep learning
Reported insect declines have dramatically increased the global demand for standardized
insect monitoring data. Image-based monitoring can generate such data cost-efficiently and …
insect monitoring data. Image-based monitoring can generate such data cost-efficiently and …
Large-scale avian vocalization detection delivers reliable global biodiversity insights
Tracking biodiversity and its dynamics at scale is essential if we are to solve global
environmental challenges. Detecting animal vocalizations in passively recorded audio data …
environmental challenges. Detecting animal vocalizations in passively recorded audio data …
Networking the forest infrastructure towards near real-time monitoring–a white paper
Forests account for nearly 90% of the world's terrestrial biomass in the form of carbon and
they support 80% of the global biodiversity. To understand the underlying forest dynamics …
they support 80% of the global biodiversity. To understand the underlying forest dynamics …
Early warning signals have limited applicability to empirical lake data
Research aimed at identifying indicators of persistent abrupt shifts in ecological
communities, aka regime shifts, has led to the development of a suite of early warning …
communities, aka regime shifts, has led to the development of a suite of early warning …
Eyes on nature: Embedded vision cameras for terrestrial biodiversity monitoring
We need comprehensive information to manage and protect biodiversity in the face of global
environmental challenges, and artificial intelligence is required to generate that information …
environmental challenges, and artificial intelligence is required to generate that information …
Overview of lifeclef 2023: evaluation of ai models for the identification and prediction of birds, plants, snakes and fungi
Biodiversity monitoring through AI approaches is essential, as it enables the efficient
analysis of vast amounts of data, providing comprehensive insights into species distribution …
analysis of vast amounts of data, providing comprehensive insights into species distribution …
Towards a standardized framework for AI-assisted, image-based monitoring of nocturnal insects
Automated sensors have potential to standardize and expand the monitoring of insects
across the globe. As one of the most scalable and fastest develo** sensor technologies …
across the globe. As one of the most scalable and fastest develo** sensor technologies …