How FAIR are plant sciences in the twenty-first century? The pressing need for reproducibility in plant ecology and evolution

The need for open, reproducible science is of growing concern in the twenty-first century, with multiple initiatives like the widely supported FAIR principles advocating for data to be Findable, Accessible, Interoperable and Reusable. Plant ecological and evolutionary studies are not exempt from the need to ensure that the data upon which their findings are based are accessible and allow for replication in accordance with the FAIR principles. However, it is common that the collection and curation of herbarium specimens, a foundational aspect of studies involving plants, is neglected by authors. Without publicly available specimens, huge numbers of studies that rely on the field identification of plants are fundamentally not reproducible. We argue that the collection and public availability of herbarium specimens is not only good botanical practice but is also fundamental in ensuring that plant ecological and evolutionary studies are replicable, and thus scientifically sound. Data repositories that adhere to the FAIR principles must make sure that the original data are traceable to and re-examinable at their empirical source. In order to secure replicability, and adherence to the FAIR principles, substantial changes need to be brought about to restore the practice of collecting and curating specimens, to educate students of their importance, and to properly fund the herbaria which house them.     

The role of replication studies in ecology

Recent large‐scale projects in other disciplines have shown that results often fail to replicate when studies are repeated. The conditions contributing to this problem are also present in ecology, but there have not been any equivalent replication projects. Here, we survey ecologists' understanding of and opinions about replication studies. The majority of ecologists in our sample considered replication studies to be important (97%), not prevalent enough (91%), worth funding even given limited resources (61%), and suitable for publication in all journals (62%). However, there is a disconnect between this enthusiasm and the prevalence of direct replication studies in the literature which is much lower (0.023%: Kelly 2019) than our participants' median estimate of 10%. This may be explained by the obstacles our participants identified including the difficulty of conducting replication studies and of funding and publishing them. We conclude by offering suggestions for how replications could be better integrated into ecological research.     

Dynamic energy budget theory restores coherence in biology

We present the state of the art of the development of dynamic energy budget theory, and its expected developments in the near future within the molecular, physiological and ecological domains. The degree of formalization in the set-up of the theory, with its roots in chemistry, physics, thermodynamics, evolution and the consistent application of Occam's razor, is discussed. We place the various contributions in the theme issue within this theoretical setting, and sketch the scope of actual and potential applications.     

Implementing code review in the scientific workflow: Insights from ecology and evolutionary biology

Code review increases reliability and improves reproducibility of research. As such, code review is an inevitable step in software development and is common in fields such as computer science. However, despite its importance, code review is noticeably lacking in ecology and evolutionary biology. This is problematic as it facilitates the propagation of coding errors and a reduction in reproducibility and reliability of published results. To address this, we provide a detailed commentary on how to effectively review code, how to set up your project to enable this form of review and detail its possible implementation at several stages throughout the research process. This guide serves as a primer for code review, and adoption of the principles and advice here will go a long way in promoting more open, reliable, and transparent ecology and evolutionary biology.     

生物多样性数据共享和发表: 进展和建议

生物多样性研究、保护实践、自然资源管理及科学决策等越来越依赖于大量数据的共享和整合。虽然关于数据共享的呼吁和实践越来越多, 但很多科学家仍然主动或被动地拒绝共享数据。关于数据共享, 现实中存在一些认知和技术上的障碍, 比如科学家不愿意共享数据, 担心同行竞争, 认为缺少足够的回报, 不熟悉相关数据保存机构, 缺少简便的数据提交工具, 没有足够时间和经费等。解决这些问题及改善共享文化的关键在于使共享者获得适当的回报(比如数据引用)。基于同行评审的数据发表被认为不但能够为生产、管理和共享数据的科学家提供一种激励机制, 并且能够有效地促进数据再利用。因而, 数据发表作为数据共享的方式之一, 近来引起了较多关注, 在生物多样性领域出现了专门发表数据论文的期刊。在采取数据论文的模式上, 数据保存机构和科技期刊采用联合数据政策在促进数据共享方面可能更具可行性。本文总结了数据共享和发表方面的进展, 讨论了数据论文能在何种程度上促进数据共享, 以及数据共享和数据发表的关系等问题, 提出如下建议: (1)个体科学家应努力践行数据共享; (2)使用DOI号解决数据所有权和数据引用的问题; (3)科技期刊和数据保存机构联合采用更加合理和严格的数据保存政策; (4)资助机构和研究单位应当在数据共享中起到更重要的作用。     

Accumulating evidence in ecology: Once is not enough

Many published studies in ecological science are viewed as stand‐alone investigations that purport to provide new insights into how ecological systems behave based on single analyses. But it is rare for results of single studies to provide definitive results, as evidenced in current discussions of the “reproducibility crisis” in science. The key step in science is the comparison of hypothesis‐based predictions with observations, where the predictions are typically generated by hypothesis‐specific models. Repeating this step allows us to gain confidence in the predictive ability of a model, and its corresponding hypothesis, and thus to accumulate evidence and eventually knowledge. This accumulation may occur via an ad hoc approach, via meta‐analyses, or via a more systematic approach based on the anticipated evolution of an information state. We argue the merits of this latter approach, provide an example, and discuss implications for designing sequences of studies focused on a particular question. We conclude by discussing current data collection programs that are preadapted to use this approach and argue that expanded use would increase the rate of learning in ecology, as well as our confidence in what is learned.     

Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biology

Elucidating how an organism''s characteristics emerge from its DNA sequence has been one of the great triumphs of biology. This triumph has cumulated in sophisticated computational models that successfully predict how an organism''s detailed phenotype emerges from its specific genotype. Inspired by that effort''s vision and empowered by its methodologies, a grand challenge is described here that aims to predict the biotic characteristics of an ecosystem, its metaphenome, from nucleic acid sequences of all the species in its community, its metagenome. Meeting this challenge would integrate rapidly advancing abilities of environmental nucleic acids (eDNA and eRNA) to identify organisms, their ecological interactions, and their evolutionary relationships with advances in mechanistic models of complex ecosystems. Addressing the challenge would help integrate ecology and evolutionary biology into a more unified and successfully predictive science that can better help describe and manage ecosystems and the services they provide to humanity.     

Integration of omics sciences to advance biology and medicine

In the past two decades, our ability to study cellular and molecular systems has been transformed through the development of omics sciences. While unlimited potential lies within massive omics datasets, the success of omics sciences to further our understanding of human disease and/or translating these findings to clinical utility remains elusive due to a number of factors. A significant limiting factor is the integration of different omics datasets (i.e., integromics) for extraction of biological and clinical insights. To this end, the National Cancer Institute (NCI) and the National Heart, Lung and Blood Institute (NHLBI) organized a joint workshop in June 2012 with the focus on integration issues related to multi-omics technologies that needed to be resolved in order to realize the full utility of integrating omics datasets by providing a glimpse into the disease as an integrated “system”. The overarching goals were to (1) identify challenges and roadblocks in omics integration, and (2) facilitate the full maturation of ‘integromics’ in biology and medicine. Participants reached a consensus on the most significant barriers for integrating omics sciences and provided recommendations on viable approaches to overcome each of these barriers within the areas of technology, bioinformatics and clinical medicine.     

A practical guide to interpreting and generating bottom-up proteomics data visualizations

Mass-spectrometry based bottom-up proteomics is the main method to analyze proteomes comprehensively and the rapid evolution of instrumentation and data analysis has made the technology widely available. Data visualization is an integral part of the analysis process and it is crucial for the communication of results. This is a major challenge due to the immense complexity of MS data. In this review, we provide an overview of commonly used visualizations, starting with raw data of traditional and novel MS technologies, then basic peptide and protein level analyses, and finally visualization of highly complex datasets and networks. We specifically provide guidance on how to critically interpret and discuss the multitude of different proteomics data visualizations. Furthermore, we highlight Python-based libraries and other open science tools that can be applied for independent and transparent generation of customized visualizations. To further encourage programmatic data visualization, we provide the Python code used to generate all data figures in this review on GitHub ( https://github.com/MannLabs/ProteomicsVisualization ).     

How and Why to Build a Unified Tree of Life

Phylogenetic trees are a crucial backbone for a wide breadth of biological research spanning systematics, organismal biology, ecology, and medicine. In 2015, the Open Tree of Life project published a first draft of a comprehensive tree of life, summarizing digitally available taxonomic and phylogenetic knowledge. This paper reviews, investigates, and addresses the following questions as a follow‐up to that paper, from the perspective of researchers involved in building this summary of the tree of life: Is there a tree of life and should we reconstruct it? Is available data sufficient to reconstruct the tree of life? Do we have access to phylogenetic inferences in usable form? Can we combine different phylogenetic estimates across the tree of life? And finally, what is the future of understanding the tree of life?

     

Computational Reproducibility in The Wildlife Society's Flagship Journals

Scientific progress depends upon the accumulation of empirical knowledge via reproducible methodology. Although reproducibility is a main tenet of the scientific method, recent studies have highlighted widespread failures in adherence to this ideal. The goal of this study was to gauge the level of computational reproducibility, or the ability to obtain the same results using the same data and analytic methods as in the original publication, in the field of wildlife science. We randomly selected 80 papers published in the Journal of Wildlife Management and Wildlife Society Bulletin between 1 June 2016 and 1 June 2018. Of those that were suitable for reproducibility review (n = 74), we attempted to obtain study data from online repositories or directly from authors. Forty-two authors did not respond to our requests, and we were further unable to obtain data from authors of 13 other studies. Of the 19 studies for which we were able to obtain data and complete our analysis, we judged that 13 were mostly or fully reproducible. We conclude that the studies with publicly available data or data shared upon request were largely reproducible, but we remain concerned about the difficulty in obtaining data from recently published papers. We recommend increased data-sharing, data organization and documentation, communication, and training to advance computational reproducibility in the wildlife sciences. © 2020 The Authors. The Journal of Wildlife Management published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.     

The changing nature of collaboration in tropical ecology and conservation

Collaboration can improve conservation initiatives through increases in article impact and by building scientific understating required for conservation practice. We investigated temporal trends in collaboration in the tropical ecology and conservation literature by examining patterns of authorship for 2271 articles published from 2000 to 2016 in Biotropica and the Journal of Tropical Ecology. Consistent with trends in other studies and scientific disciplines, we found that the number of authors per article increased from 2.6 in 2000 to 4.2 in 2015 using a generalized linear model (glm). We modeled changes in multinational collaboration in articles using a glm and found that the mean number of author‐affiliated countries increased from 1.3 (±0.6 SD) to 1.7 (±0.8 SD) over time and that increases were best explained by the number of authors per article. The proportion of authors based in tropical countries increased, but the probability of tropical–extratropical collaboration did not and was best explained solely by the number of authors per article. Overall, our analyses suggest that only certain types of collaboration are increasing and that these increases coincide with a general increase in the number of authors per article. Such changes in author numbers and collaboration could be the result of increased data sharing, changes in the scope of research questions, changes in authorship criteria, or scientific migration. We encourage tropical conservation scientists continue to build collaborative ties, particularly with researchers based in underrepresented tropical countries, to ensure that tropical ecology and conservation remains inclusive and effective.     

Unlocking avian museum collections to enable and advance environmental change research

The rate and magnitude of contemporary changes in natural systems is unprecedented in the Earth's history. Studies of wild birds have been critically important in helping us understand and address these environmental changes. Avian collections provide a potentially unique perspective on change through time, but their role in environmental change research is limited by the availability of collections data. Here we describe how avian collections might be unlocked to enable environmental change research, and discuss the opportunities and constraints associated with this. We use the concept of the extended specimen to describe the types of data that could be unlocked from basic data for discoverability to enhanced data that might be directly applied to environmental change questions. We illustrate the type of environmental change research these data might support. We argue that data creation and access is currently limited by funding for digitization, a rather patchy understanding of the needs of the research community and less than adequate data-sharing by institutions and researchers. We develop a blueprint for addressing these issues which includes (1) improvements in sharing the data we are already creating and (2) building a better case for digitization at scale. As one of the largest avian collections in the world, the Natural History Museum, UK, is committed to unlocking our collections, but we will need input and support from the avian research community to do so.     

Lessons learned through listening to biology students during a transition to online learning in the wake of the COVID‐19 pandemic

During the Spring Semester of 2020, an outbreak of a novel coronavirus (SARS‐CoV‐2) and the illnesses it caused (COVID‐19) led to widespread cancelling of on‐campus instruction at colleges and universities in the United States and other countries around the world. Response to the pandemic in university settings included a rapid and unexpected shift to online learning for faculty and students. The transition to teaching and learning online posed many challenges, and the experiences of students during this crisis may inform future planning for distance learning experiences during the ongoing pandemic and beyond. Herein, we discuss the experiences of first‐ and second‐year university students enrolled in a biology seminar course as their classes migrated to online environments. Drawing on reported student experiences and prior research and resources, we discuss the ways we will adjust our own teaching for future iterations of the course while offering recommendations for instructors tasked with teaching in online environments.     

Nullius in Verba1: Advancing Data Transparency in Industrial Ecology

With the growth of the field of industrial ecology (IE), research and results have increased significantly leading to a desire for better utilization of the accumulated data in more sophisticated analyses. This implies the need for greater transparency, accessibility, and reusability of IE data, paralleling the considerable momentum throughout the sciences. The Data Transparency Task Force (DTTF) was convened by the governing council of the International Society for Industrial Ecology in late 2016 to propose best‐practice guidelines and incentives for sharing data. In this article, the members of the DTTF present an overview of developments toward transparent and accessible data within the IE community and more broadly. We argue that increased transparency, accessibility, and reusability of IE data will enhance IE research by enabling more detailed and reproducible research, and also facilitate meta‐analyses. These benefits will make the results of IE work more timely. They will enable independent verification of results, thus increasing their credibility and quality. They will also make the uptake of IE research results easier within IE and in other fields as well as by decision makers and sustainability practitioners, thus increasing the overall relevance and impact of the field. Here, we present two initial actions intended to advance these goals: (1) a minimum publication requirement for IE research to be adopted by the Journal of Industrial Ecology; and (2) a system of optional data openness badges rewarding journal articles that contain transparent and accessible data. These actions will help the IE community to move toward data transparency and accessibility. We close with a discussion of potential future initiatives that could build on the minimum requirements and the data openness badge system.