An ecological filter in a pond, such as voracious fish that feed on dragonflies and damselflies, can help ecologists predict how biodiversity loss may impact specific habitats, according to Rice University researchers who spent four years studying seasonal changes in ponds across East Texas.

In one of the first studies of its kind, the scientists show that strong environmental “filters” — in this case, predatory fish — cause dragonfly and damselfly communities to vary regularly from year to year and season to season in ponds across East Texas. The results, which appear online this week in the journal Ecology Letters, show how an ecological filter can help ecologists predict how biodiversity loss may impact specific habitats.

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Using a state-of-the-art device for measuring mass, researchers at the National Institute of Standards and Technology (NIST) have made their most precise determination yet of Planck's constant, an important value in science that will help to redefine the kilogram, the official unit of mass in the SI, or international system of units. Accepted for publication (link is external) in the journal Metrologia, these new results come ahead of a July 1 international deadline for measurements that aim to redefine the entire SI in terms of fundamental constants of nature.

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Imagine going to the supermarket to stock up on groceries but coming home empty-handed because you just couldn't figure out how to work the shopping cart or figure out how to get to the ice cream tubs in the freezer aisle.

Welcome to the life of a bumblebee. 

Gathering sweet nectar from flowers, it turns out, is much more difficult than one might think, and it requires a lengthy learning process. By the time a bee has figured out how to efficiently pry open the lips of a snapdragon flower, for example, most likely it has made dozens, if not hundreds, of floral visits. 

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As the climate change progresses, droughts are expected to become more and more common and more intense in Europe, as in many parts of the globe. However, many plants are not able to handle this kind of climate.

This includes the Norway spruce, which is Germany's most important commercial tree species and accounts for the majority of trees in the Black Forest. Valentia Vitali and Prof. Dr. Jürgen Bauhusfrom the Chair of Silviculture at the University of Freiburg are thus studying other types of needle-leaved conifers to find alternatives. Conifers play a far greater role in commercial forestry and climate protection than broad-leaved trees. In their article "Silver Fir and Douglas Fir Are More Tolerant to Extreme Droughts than Norway Spruce in South-Western Germany" published in the journal Global Change Biology, the scientists concluded that the native silver fir and the Douglas fir, which was imported from the Americas, are suitable tree replacements for the Norway spruce in the long run.

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Neural networks, which learn to perform computational tasks by analyzing large sets of training data, are responsible for today’s best-performing artificial intelligence systems, from speech recognition systems, to automatic translators, to self-driving cars.

But neural nets are black boxes. Once they’ve been trained, even their designers rarely have any idea what they’re doing — what data elements they’re processing and how.

Two years ago, a team of computer-vision researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) described a method for peering into the black box of a neural net trained to identify visual scenes. The method provided some interesting insights, but it required data to be sent to human reviewers recruited through Amazon’s Mechanical Turk crowdsourcing service.

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