Bee monitoring by community scientists: comparing a collections-based program with iNaturalist

Author:

Turley Nash E1ORCID,Kania Sarah E1,Petitta Isabella R2ORCID,Otruba Elizabeth A3,Biddinger David J1,Butzler Thomas M4,Sesler Valerie V4,López-Uribe Margarita M12ORCID

Affiliation:

1. The Pennsylvania State University Department of Entomology, , University Park , PA, USA

2. Intercollege Graduate Degree Program in Ecology, The Pennsylvania State University , University Park , PA, USA

3. The Academy of Natural Sciences of Drexel University Department of Entomology, , Philadelphia , PA, USA

4. Penn State Extension, The Pennsylvania State University , University Park , PA, USA

Abstract

Abstract Bee monitoring, or widespread efforts to document bee community biodiversity, can involve data collection using lethal (specimen collections) or non-lethal methods (observations, photographs). Additionally, data can be collected by professional scientists or by volunteer participants from the general public. Collection-based methods presumably produce more reliable data with fewer biases against certain taxa, while photography-based approaches, such as data collected from public natural history platforms like iNaturalist, can involve more people and cover a broader geographic area. Few efforts have been made to quantify the pros and cons of these different approaches. We established a community science monitoring program to assess bee biodiversity across the state of Pennsylvania (USA) using specimen collections with nets, blue vane traps, and bowl traps. We recruited 26 participants, mostly Master Gardeners, from across the state to sample bees after receiving extensive training on bee monitoring topics and methods. The specimens they collected were identified to species, stored in museum collections, and the data added to public databases. Then, we compared the results from our collections to research-grade observations from iNaturalist during the same time period (2021 and 2022). At state and county levels, we found collections data documented over twice as much biodiversity and novel baseline natural history data (state and county records) than data from iNaturalist. iNaturalist data showed strong biases toward large-bodied and non-native species. This study demonstrates the value of highly trained community scientists for collections-based research that aims to document patterns of bee biodiversity over space and time.

Funder

Pennsylvania Department of Agriculture

2022 Specialty Crops Block Grant

Science-To-Practice

USDA NIFA Appropriations

Publisher

Oxford University Press (OUP)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3