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Wildlife populations have fallen by more than two-thirds in less than 50 years, according to a major report (PDF) by the conservation group WWF. The report says this “catastrophic decline” shows no sign of slowing. And it warns that nature is being destroyed by humans at a rate never seen before. The report looked at thousands of different wildlife species monitored by conservation scientists in habitats across the world. They recorded an average 68% fall in more than 20,000 populations of mammals, birds, amphibians, reptiles and fish since 1970.

Measuring the variety of all life on Earth is complex, with a number of different measures. Taken together, they provide evidence that biodiversity is being destroyed at a rate unprecedented in human history. This particular report uses an index of whether populations of wildlife are going up or down. It does not tell us the number of species lost, or extinctions. The largest declines are in tropical areas. The drop of 94% for Latin America and the Caribbean is the largest anywhere in the world, driven by a cocktail of threats to reptiles, amphibians and birds. Research published in the journal Nature suggests that to turn the tide we must transform the way we produce and consume food, including reducing food waste and eating food with a lower environmental impact.

Researchers at the Technische Universitat Wein have created a simulation of a simple worm’s neural network, and have been able to replicate its natural behavior to completely mimic the worm’s natural reflexive behavior. According to the article, using a simple neural network of 300 neurons, the simulation of “the worm can find its way, eat bacteria and react to certain external stimuli. It can, for example, react to a touch on its body. A reflexive response is triggered and the worm squirms away. This behavior is determined by the worm’s nerve cells and the strength of the connections between them. When this simple reflex network is recreated on a computer, the simulated worm reacts in exactly the same way to a virtual stimulation — not because anybody programmed it to do so, but because this kind of behavior is hard-wired in its neural network.” Using the same neural network without adding any additional nerve cells, Mathias Lechner, Radu Grosu, and Ramin Hasani were able to have the nematode simulation learn to balance a pole “just by tuning the strength of the synaptic connections. This basic idea (tuning the connections between nerve cells) is also the characteristic feature of any natural learning process.”