Crowdsourcing Fungal Biodiversity: Approaches and standards used by an all-volunteer community science project
Crowdsourcing Fungal Biodiversity: Approaches and standards used by an all-volunteer community science project
复制标题
众包真菌生物多样性：全志愿者社区科学项目使用的方法和标准
DOI：
10.3897/biss.5.74225
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Joanne Schwartz
中科院分区：
文献类型：
--
作者：
Bill Sheehan;Rob Stevenson;Joanne Schwartz
真菌多样性调查 (FunDiS) 是一个全志愿者社区科学组织，记录北美地区大型真菌（肉眼可见）的多样性和分布。 FunDiS 解决了生物多样性保护中的一个关键差距：真菌作为生命的主要王国之一，在保护工作中很大程度上被忽视了。真菌高度多样化：据估计，只有 5% 的真菌物种被描述过（Willis 2018），而对专业分类学家的支持几十年来一直在下降。因此，FunDiS 吸引了大量业余真菌学家来记录真菌多样性。
我们的参与模式有四个级别的众包真菌生物多样性。它由参与者和技能金字塔组成，不断吸引更多的人参与底层（最简单的任务），并鼓励他们进入下一个级别。
第一级：实地观察：社区科学家用地理参考彩色照片记录实地真菌，并在公共数据库平台上发布观察结果； FunDiS 使用 iNaturalist 和 Mushroom Observer。 FunDiS 受到澳大利亚 FungiMap 的启发，建立了一个名为 FunDiS 多样性数据库的 iNaturalist 策划项目。蘑菇爱好者添加观察结果，并鼓励他们由专家鉴定团队进行审查。另一个分类小组负责审查新的观察结果，拒绝那些不符合 FunDiS 质量标准的观察结果，并在海报上写下鼓励性的注释，说明如何使观察结果更具科学价值。截至 2021 年 8 月，已有近 50,000 个可验证的观测结果，其中 30,465 个（包括 3,204 个物种）为研究级，并由 iNaturalist 上传到全球生物多样性信息设施（GBIF）的网站上。 FunDiS 的另一项倡议是“稀有真菌挑战”，它招募业余爱好者寻找稀有或受威胁的真菌。
2 级测序：FunDiS 构建了一个程序，供业余爱好者提交组织进行 DNA 测序，并提供解释结果的帮助。条形码对于识别真菌尤其必要，因为形态特征和图像通常是不够的。参与者注册项目，将观察结果发布到 iNaturalist 或 Mushroom Observer，并向 FunDiS 申请测序资助或自付费用进行测序。从阿拉斯加到波多黎各，从冰岛到夏威夷，已有200多个当地项目注册。截至 2021 年 6 月，约 7,000 个样本已完成测序。数据存储在 GenBank 中。
3 级优惠券：FundiS 支持在精选真菌中保存有据可查的干燥标本。迄今为止，由于这些机构的人员和能力的限制，这种参与水平发展缓慢。
4级超级用户：这些是具有广泛领域知识的高级观察者，学习了DNA技术；可以教别人如何分析 DNA 结果并创建系统发育；甚至描述新物种。北美真菌科学界可能有几十个超级用户。
挑战和教训
反馈——参与者的反馈对于社区科学项目的成功至关重要。我们了解到，激发与参与者的实时丰富互动需要时间和人员，而依赖缺乏协调、一致性和连续性能力的志愿者往往会让参与者失望。同样，DNA 测序对大多数业余爱好者来说也是令人生畏的。我们发现许多参与者需要指导才能正确记录、干燥和提交组织样本进行测序。更大的挑战是理解生成的数据，例如，了解序列是否属于所描述的物种，或者是否应该被识别为新物种。这种决策需要深厚的知识。在过去的一年里，我们很幸运地得到了两名专业真菌学家和一名博士生的志愿服务来分析序列数据。
链接数据——在现场观察、基因序列和标本之间链接数据是一个重大挑战。我们最初的目标是实现外部和内部数据流的自动化，但志愿者程序员的成功有限。他们成功地将 iNaturalist 和 Mushroom Observer 观察结果自动上传到我们的测序设施（生命条形码），但大多数其他联系已由志愿者在静态电子表格上跟踪。
带薪员工 - 回想起来，仅使用志愿者管理和劳动力来尝试如此雄心勃勃的项目是乐观的。绝大多数社区科学项目都是以机构为基础的，有带薪工作人员进行管理，并有资金进行推广（Pocock 等人，2017 年）。为了保持目前的规模，我们相信核心的带薪员工对于利用我们一直在建设的大型社区至关重要。
Fungal Diversity Survey (FunDiS) is an all-volunteer community science organization that documents the diversity and distribution of macrofungi (visible with the naked eye) across North America. FunDiS addresses a key gap in biodiversity conservation: fungi, one of life’s major kingdoms, have been largely neglected in conservation efforts. Fungi are hyperdiverse: it is estimated that only 5% of fungal species have been described (Willis 2018), while support for professional taxonomists has been declining for decades. Therefore, FunDiS engages legions of amateur mycologists to document fungal diversity.
Our participation model has four levels for crowdsourcing fungal biodiversity. It consists of a pyramid of participants and skills, continually drawing more people in at the base (simplest tasks), and encouraging them to move up to the next level.
Level 1. Field observations: Community scientists document fungi in the field with georeferenced color photos and post observations on public, databased platforms; FunDiS uses iNaturalist and Mushroom Observer. FunDiS established a curated iNaturalist project called the FunDiS Diversity Database, inspired by FungiMap in Australia. Mushroom enthusiasts add observations, with the incentive that they will be reviewed by a team of expert identifiers. Another team of triagers goes through new observations, rejects those that do not follow FunDiS quality standards, and writes encouraging notes to posters on how to make observations more scientifically valuable. As of August 2021, there were almost 50,000 verifiable observations, of which 30,465 (including 3,204 species) were research grade and uploaded by iNaturalist onto the website of the Global Biodiversity Information Facility (GBIF). Another FunDiS initiative, Rare Fungi Challenges, enlists amateurs to search for rare or threatened fungi.
Level 2. Sequence: FunDiS built a program for amateurs to submit tissue for DNA sequencing and provided help interpreting results. Barcoding is especially needed to identify fungi because mopho-characteristics and images are often insufficient. Participants register projects, post observations to iNaturalist or Mushroom Observer, and apply to FunDiS for sequencing grants or pay out-of-pocket for sequencing. More than 200 local projects have been registered from Alaska to Puerto Rico, and Iceland to Hawaii. Some 7,000 specimens were sequenced by June 2021. Data are deposited in GenBank.
Level 3. Voucher: FunDiS supports preserving well-documented, dried specimens in curated fungaria. To date, this participation level has developed slowly because of limitations of personnel and capacity of those institutions.
Level 4. Super User: These are advanced observers with extensive field knowledge who have learned DNA technology; can teach others how to analyze DNA results and create phylogenies; and even describe new species. There are perhaps several dozen super users in the North American fungal science community.
Challenges and lessons
Feedback - Feedback to and from participants is critical to the success of community science projects. We have learned that it takes time and personnel to inspire rich interaction with participants in real time and that relying on volunteers with insufficient capacity for coordination, consistency and continuity often disappoints participants. Similarly DNA sequencing is intimidating to most amateurs. We found that guidance was needed for many participants just to correctly document, dry and submit tissue samples for sequencing. An even bigger challenge is making sense of the data that is generated, e.g., knowing if the sequence is of a described species or should be identified as a new species. Deep knowledge is needed for this kind of decision-making. In the past year we were fortunate to have the volunteer services of two professional mycologists and a doctoral student to analyze sequence data.
Linking data - Linking data between field observations, genetic sequences and specimens is a major challenge. Our initial goal was to automate both external and internal data flows, but success has been limited with volunteer programmers. They managed to automate uploading iNaturalist and Mushroom Observer observations to our sequencing facility (Barcode of Life), but most other linkages have been tracked by volunteers on static spreadsheets.
Paid staff - In retrospect, it was optimistic to attempt a project of such ambitious scope using only volunteer management and labor. The vast majority of community science projects are institution-based, with paid staff to manage and funds for outreach (Pocock et al. 2017). To continue at the present scale, we believe a core of paid staff is essential to leverage the large community we have been building.