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.”

1.1. 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A They are becoming outdated.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。细节理解题。根据第一段的“most records of biodiversity are often in the form of photos, videos, and other digital records”可知，如今收集的物种记录大多是电子形式的。故选B。

2.2. What does Daru’s study focus on?

A Threatened species.

B Physical specimens.

C Observational data.

D Mobile applications.

解析：选C。推理判断题。第二段Daru提到观测数据数量超过标本数据，且人们越来越多地用观测数据研究物种对全球变化的反应，于是他开展研究探究这类数据是否可用，由此可知研究聚焦于观测数据。故选C。

3.3. 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。推理判断题 第四段指出研究团队关注导致数据偏差的采样因素，比如公民科学家更倾向于拍摄开花植物而非旁边的草；第五段也提到采样存在区域、物种等偏向。这说明是不恰当的采样方式导致了数据偏差。故选C。

4.4. 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。推理判断题 最后一段Daru建议生物多样性应用程序利用研究结果，告知用户过度采样的区域，引导他们去采样不足的区域和物种；同时鼓励用户让专家确认上传图片的物种种类。这些都是对公民科学家的引导。故选D。