A team of scientists is studying the sound of the forest in Ecuador to learn how artificial intelligence (AI) could follow animal life in recovering environments. 

一组科学家正在研究厄瓜多尔森林的声音，以了解人工智能 (AI) 如何在恢复环境中追踪动物的生命。 

When scientists want to measure new forest growth, they can study large areas of land with tools like satellites and lidar. 

当科学家想要测量新的森林生长情况时，他们可以使用卫星和激光雷达等工具研究大片土地。 

But understanding how fast and in what amount wildlife is returning to an area is more difficult. Sometimes it requires an expert to listen through sound recordings and pick out animal calls. 

但了解野生动物返回某个地区的速度和数量则更加困难。有时需要专家聆听录音并辨别动物的叫声。 

Jorg Muller is a field expert on birds at the University of Wurzburg Biocenter in Germany. He wondered if there was a different way. 

约格·穆勒 (Jorg Muller) 是德国维尔茨堡大学生物中心的鸟类领域专家。他想知道是否还有其他方法。 

Muller told the French news agency AFP: "I saw the gap that we need, particularly in the tropics, better methods to quantify the huge diversity... to improve conservation actions.” 

穆勒告诉法国新闻社法新社：“我看到了我们需要的差距，特别是在热带地区，需要更好的方法来量化巨大的多样性......以改善保护行动。” 

So, he turned to bioacoustics, which uses sound to learn more about animal life and the environments in which they live. 

因此，他转向生物声学，利用声音来更多地了解动物的生命及其生活环境。 

The tool has been used by scientists for some time. But more recently, researchers are using it with computer learning to study large amounts of data more quickly. 

该工具已经被科学家使用了一段时间。但最近，研究人员将其与计算机学习结合使用，以更快地研究大量数据。 

Muller and his team recorded wildlife sounds at sites in Ecuador’s Choco area. The environments they recorded included areas that were once used for agriculture and raising livestock to old-growth forests. 

穆勒和他的团队在厄瓜多尔乔科地区记录了野生动物的声音。他们记录的环境包括曾经用于农业和在古老森林中饲养牲畜的地区。 

They first had experts listen to the recordings and index the sounds of different animals. Then, they examine the sound quality to measure the environment. 

他们首先让专家听取录音并对不同动物的声音进行索引。然后，他们检查声音质量以测量环境。 

Finally, they ran two weeks of recordings through an AI computer program trained to understand 75 different bird calls. 

最后，他们通过人工智能计算机程序进行了两周的录音，该程序经过训练可以理解 75 种不同的鸟叫声。

The program was able to pick out the calls on which it was trained. However, scientists wondered if the program could correctly identify the number of different kinds of plants and animals in each environment. 

该程序能够挑选出对其进行训练的调用。然而，科学家们想知道该程序是否能够正确识别每个环境中不同种类植物和动物的数量。 

To see if the program could do that, the team used two different controls. One was from the experts who listened to the audio recordings, and the second was based on examples from each environment, which can be used to understand biodiversity. 

为了看看程序是否可以做到这一点，团队使用了两种不同的控件。一个是来自听录音的专家，第二个是基于每个环境的例子，可以用来了解生物多样性。 

Since the amount of available sounds used to train is limited, the AI program could only identify one-fourth of the bird calls that experts could. But it was still able to correctly measure biodiversity levels in each environment, the study said. 

由于用于训练的可用声音数量有限，人工智能程序只能识别专家所能识别的鸟叫声的四分之一。但研究称，它仍然能够正确测量每个环境中的生物多样性水平。 

The research was published recently in Nature Communications. The study said the scientists’ results show that the AI program is a powerful tool to measure the recovery of animal communities in tropical forests. 

该研究最近发表在《自然通讯》上。研究称，科学家的研究结果表明，人工智能程序是衡量热带森林动物群落恢复情况的有力工具。 

The research noted that biodiversity found from recordings can be quantified in a cost-effective and complete way. And it said that it can measure environments, “… from active agriculture to recovering and old-growth forests.” 

研究指出，从记录中发现的生物多样性可以以具有成本效益且完整的方式进行量化。它说它可以测量环境，“……从活跃的农业到恢复和古老的森林。” 

There are still areas for improvement, including the lack of animal sounds on which to train AI models. And the method can only capture animals that use sound to communicate. 

仍有需要改进的地方，包括缺乏用于训练人工智能模型的动物声音。而且该方法只能捕获使用声音进行交流的动物。