In the race to document the species on Earth before they go extinct, researchers and citizen scientists have collected billions of records. Today, most records of biodiversity are often in the form of photos, videos, and other digital records. Though they are useful for detecting shifts in the number and variety of species in an area, a new Stanford study has found that this type of record is not perfect.

“With the rise of technology it is easy for people to make observations of different species with the aid of a mobile application,” said Barnabas Daru, who is lead author of the study and assistant professor of biology in the Stanford School of Humanities and Sciences. “These observations now outnumber the primary data that comes from physical specimens (标本), and since we are increasingly using observational data to investigate how species are responding to global change, I wanted to know: Are they usable?”

Using a global dataset of 1.9 billion records of plants’ insects, birds, and animals, Daru and his team tested how well these data represent actual global biodiversity patterns.

“We were particularly interested in exploring the aspects of sampling that tend to bias (使有偏差) data, like the greater likelihood of a citizen scientist to take a picture of a flowering plant instead of the grass right next to it,” said Daru.

Their study revealed that the large number of observation-only records did not lead to better global coverage. Moreover, these data are biased and favor certain regions, time periods, and species. This makes sense because the people who get observational biodiversity data on mobile devices are often citizen scientists recording their encounters with species in areas nearby. These data are also biased toward certain species with attractive or eye-catching features.

What can we do with the imperfect datasets of biodiversity?

“Quite a lot,” Daru explained. “Biodiversity apps can use our study results to inform users of oversampled areas and lead them to places — and even species — that are not well-sampled. To improve the quality of observational data, biodiversity apps can also encourage users to have an expert confirm the identification of their uploaded image.”

1.What do we know about the records of species collected now?

A They are becoming outdated.

B They are mostly in electronic form.

C They are limited in number.

D They are used for public exhibition.

解析：选B。B 细节理解题。根据第一段中的“Today, most records of biodiversity are often in the form of photos, videos, and other digital records.”以及第二段中的“These observations now outnumber the primary data that comes from physical specimens”可知，目前标本收集记录主要以电子版的形式为主。故选B。

2.What does Daru’s study focus on?

A Threatened species.

B Physical specimens.

C Observational data.

D Mobile applications.

解析：选C。C 细节理解题。根据第三段中的“Daru and his team tested how well these data represent actual global biodiversity patterns”达鲁和他的团队测试了这些数据在多大程度上代表了实际的全球生物多样性模式；根据第四段中的“We were particularly interested in exploring the aspects of sampling that tend to bias (使有偏差) data”我们特别感兴趣的是探索可能导致数据偏差的抽样方面。由此可知，他的研究聚焦点是观察性数据。故选C。

3.What has led to the biases according to the study?

A Mistakes in data analysis.

B Poor quality of uploaded pictures.

C Improper way of sampling.

D Unreliable data collection devices.

解析：选C。C 推理判断题。本题需要概括第四段和第五段的内容，第四段在讲达鲁的研究团队在探索网民们取样方面的偏差，比如网民们会因为花比草更加显眼而拍花，而不是拍草。第五段的内容也在呼应这个要点，尤其是第五段最后一句“these data are also biased toward certain species with attractive or eye-catching features. ”即网民们采集的数据会更加偏向引人注目的特征，而忽略了不怎么引人注目的特征，所以网民的采样可能会有问题，即不合适的采样方式。故选C。

4.What is Daru’s suggestion for biodiversity apps?

A Review data from certain areas.

B Hire experts to check the records.

C Confirm the identity of the users.

D Give guidance to citizen scientists.

解析：选D。D 推理判断题。根据最后一段中的“to improve the quality of observational data, biodiversity apps can also encourage users to have an expert confirm the identification of their uploaded image. ”即采样的用户可以征求专家的意见，以来核实他们上传图片的真实身份，所以专家可以给网民科学家一些指导。选项中的“give guidance to citizen scientists”与文中的“have an expert confirm”是同义替换。故选D。