ROV pilots filmed this glass squid while exploring the Colorado-Rawson submarine canyon off the coast of Argentina. Breakthroughs, discoveries, and DIY tips sent six days a week. The marine biologists of the Schmidt Ocean Institute are a busy bunch. Over the last few years, scientists aboard the research vessel have spotted rare Antarctic squid, discovered multiple octopus near Costa Rica, and even cataloged over 100 potential new species off the coast of Chile. To kick off 2026, the Institute released a trove of new images and videos highlighting some of their latest observations from the south Atlantic Ocean.

With great biological havoc comes great opportunity. Breakthroughs, discoveries, and DIY tips sent every weekday. About 445 million years ago, our planet completely changed. Massive glaciers formed over the supercontinent Gondwana, sucking up sea water like an icy sponge. Now called the Late Ordovician mass extinction (LOME), Earth's first major mass extinction wiped out about 85 percent of all marine species as the ocean chemistry radically changed and Earth's climate turned bitter cold. However, with great biological havoc also comes opportunity.

Breakthroughs, discoveries, and DIY tips sent every weekday. Nearly one in three U.S. households harbor a cold-hearted killer. Some even have a well-known proclivity for torture. And while the popular pets are best known for downing birds and cornering mice, they are also adept at hunting all manner of bugs. Host a cat in your home long enough and you'll likely become accustomed to regular deliveries of amputated insect legs, wings, or the occasional whole carcass.

Arboretum is a 134.6M sample dataset designed to advance AI for biodiversity applications by providing a large-scale, accurately annotated multimodal dataset that includes images and corresponding Arboretum aims to facilitate the development of AI models for species identification, ecological monitoring, and agricultural research. The dataset is hosted on Hugging Face. Our dataset will be available for as long as the iNaturalist Open Dataset is maintained.

The archipelago's total bat tally now stands at 85 different flying mammals. Breakthroughs, discoveries, and DIY tips sent every weekday. A few weeks ago, conservationists announced the milestone discovery of the 1500th known bat species, . October's Bat Appreciation Month celebrations apparently aren't done yet. With only a few days remaining before Halloween, a research team has described another new species residing in the Philippines for the journal .

With healthy populations of animals that disperse seeds, tropical forests can absorb up to four times more carbon. Deforestation, hunting, and wildlife trade threaten the hornbill's ability to disperse seeds throughout Asian tropical forests. A lot of attention has been paid to how climate change can reduce biodiversity. Now MIT researchers have shown that the reverse is also true: Loss of biodiversity can jeopardize regrowth of tropical forests, one of Earth's most powerful tools for mitigating climate change. Combining data from thousands of previous studies and using new tools for quantifying interconnected ecological processes, the researchers analyzed numerous tropical sites where deforestation was being followed by natural regrowth, focusing on the role of animals such as birds and monkeys that spread plant seeds by eating them in one place and then defecating someplace else. Evan Fricke, a research scientist in the MIT Department of Civil and Environmental Engineering and the lead author of a paper on the work, has studied such animals for 15 years, showing that without their role, trees have lower survival rates and a harder time keeping up with environmental changes.

To promote climate adaptation and mitigation, it is crucial to understand stakeholder perspectives and knowledge gaps on land use and climate changes. Stakeholders across 21 European islands were consulted on climate and land use change issues affecting ecosystem services. Climate change perceptions included temperature, precipitation, humidity, extremes, and wind. Land use change perceptions included deforestation, coastal degradation, habitat protection, renewable energy facilities, wetlands, and others. Additional concerns such as invasive species, water or energy scarcity, infrastructure problems, and austerity were also considered. Climate and land use change impact perceptions were analysed with machine learning to quantify their influence. The predominant climatic characteristic is temperature, and the predominant land use characteristic is deforestation. Water-related problems are top priorities for stakeholders. Energy-related problems, including energy deficiency and issues with wind and solar facilities, rank high as combined climate and land use risks. Stakeholders generally perceive climate change impacts on ecosystem services as negative, with natural habitat destruction and biodiversity loss identified as top issues. Land use change impacts are also negative but more complex, with more explanatory variables. Stakeholders share common perceptions on biodiversity impacts despite geographic disparity, but they differentiate between climate and land use impacts. Water, energy, and renewable energy issues pose serious concerns, requiring management measures.

Urban tree biodiversity is critical for climate resilience, ecological stability, and livability in cities, yet most municipalities lack detailed knowledge of their canopies. Field-based inventories provide reliable estimates of Shannon and Simpson diversity but are costly and time-consuming, while supervised AI methods require labeled data that often fail to generalize across regions. We introduce an unsupervised clustering framework that integrates visual embeddings from street-level imagery with spatial planting patterns to estimate biodiversity without labels. Applied to eight North American cities, the method recovers genus-level diversity patterns with high fidelity, achieving low Wasserstein distances to ground truth for Shannon and Simpson indices and preserving spatial autocorrelation. This scalable, fine-grained approach enables biodiversity mapping in cities lacking detailed inventories and offers a pathway for continuous, low-cost monitoring to support equitable access to greenery and adaptive management of urban ecosystems.