Data sharing in ecology and evolution

Reporting guidelines for terrestrial respirometry: Building openness, transparency of metabolic rate and evaporative water loss data

Respirometry is an important tool for understanding whole-animal energy and water balance in relation to the environment. Consequently, the growing number of studies using respirometry over the last decade warrants reliable reporting and data sharing for effective dissemination and research synthesis. We provide a checklist guideline on five key sections to facilitate the transparency, reproducibility, and replicability of respirometry studies: 1) materials, set up, plumbing, 2) subject conditions/maintenance, 3) measurement conditions, 4) data processing, and 5) data reporting and statistics, each with explanations and example studies. Transparency in reporting and data availability has benefits on multiple fronts. Authors can use this checklist to design and report on their study, and reviewers and editors can use the checklist to assess the reporting quality of the manuscripts they review. Improved standards for reporting will enhance the value of primary studies and will greatly facilitate the ability to carry out higher quality research syntheses to address ecological and evolutionary theories.

Enhancing biodiversity conservation and monitoring in protected areas through efficient data management

A scientifically informed approach to decision-making is key to ensuring the sustainable management of ecosystems, especially in the light of increasing human pressure on habitats and species. Protected areas, with their long-term institutional mandate for biodiversity conservation, play an important role as data providers, for example, through the long-term monitoring of natural resources. However, poor data management often limits the use and reuse of this wealth of information. In this paper, we share lessons learned in managing long-term data from the Italian Alpine national parks. Our analysis and examples focus on specific issues faced by managers of protected areas, which partially differ from those faced by academic researchers, predominantly owing to different mission, governance, and temporal perspectives. Rigorous data quality control, the use of appropriate data management tools, and acquisition of the necessary skills remain the main obstacles. Common protocols for data collection offer great opportunities for the future, and complete recovery and documentation of time series is an urgent priority. Notably, before data can be shared, protected areas should improve their data management systems, a task that can be achieved only with adequate resources and a long-term vision. We suggest strategies that protected areas, funding agencies, and the scientific community can embrace to address these problems. The added value of our work lies in promoting engagement with managers of protected areas and in reporting and analysing their concrete requirements and problems, thereby contributing to the ongoing discussion on data management and sharing through a bottom-up approach.

Publication bias impacts on effect size, statistical power, and magnitude (Type M) and sign (Type S) errors in ecology and evolutionary biology

Collaborative efforts to directly replicate empirical studies in the medical and social sciences have revealed alarmingly low rates of replicability, a phenomenon dubbed the 'replication crisis'. Poor replicability has spurred cultural changes targeted at improving reliability in these disciplines. Given the absence of equivalent replication projects in ecology and evolutionary biology, two inter-related indicators offer the opportunity to retrospectively assess replicability: publication bias and statistical power. This registered report assesses the prevalence and severity of small-study (i.e., smaller studies reporting larger effect sizes) and decline effects (i.e., effect sizes decreasing over time) across ecology and evolutionary biology using 87 meta-analyses comprising 4,250 primary studies and 17,638 effect sizes. Further, we estimate how publication bias might distort the estimation of effect sizes, statistical power, and errors in magnitude (Type M or exaggeration ratio) and sign (Type S). We show strong evidence for the pervasiveness of both small-study and decline effects in ecology and evolution. There was widespread prevalence of publication bias that resulted in meta-analytic means being over-estimated by (at least) 0.12 standard deviations. The prevalence of publication bias distorted confidence in meta-analytic results, with 66% of initially statistically significant meta-analytic means becoming non-significant after correcting for publication bias. Ecological and evolutionary studies consistently had low statistical power (15%) with a 4-fold exaggeration of effects on average (Type M error rates = 4.4). Notably, publication bias reduced power from 23% to 15% and increased type M error rates from 2.7 to 4.4 because it creates a non-random sample of effect size evidence. The sign errors of effect sizes (Type S error) increased from 5% to 8% because of publication bias. Our research provides clear evidence that many published ecological and evolutionary findings are inflated. Our results highlight the importance of designing high-power empirical studies (e.g., via collaborative team science), promoting and encouraging replication studies, testing and correcting for publication bias in meta-analyses, and adopting open and transparent research practices, such as (pre)registration, data- and code-sharing, and transparent reporting.

Honey bee (Apis mellifera) wing images: a tool for identification and conservation

BACKGROUND

The honey bee (Apis mellifera) is an ecologically and economically important species that provides pollination services to natural and agricultural systems. The biodiversity of the honey bee in parts of its native range is endangered by migratory beekeeping and commercial breeding. In consequence, some honey bee populations that are well adapted to the local environment are threatened with extinction. A crucial step for the protection of honey bee biodiversity is reliable differentiation between native and nonnative bees. One of the methods that can be used for this is the geometric morphometrics of wings. This method is fast, is low cost, and does not require expensive equipment. Therefore, it can be easily used by both scientists and beekeepers. However, wing geometric morphometrics is challenging due to the lack of reference data that can be reliably used for comparisons between different geographic regions.

FINDINGS

Here, we provide an unprecedented collection of 26,481 honey bee wing images representing 1,725 samples from 13 European countries. The wing images are accompanied by the coordinates of 19 landmarks and the geographic coordinates of the sampling locations. We present an R script that describes the workflow for analyzing the data and identifying an unknown sample. We compared the data with available reference samples for lineage and found general agreement with them.

CONCLUSIONS

The extensive collection of wing images available on the Zenodo website can be used to identify the geographic origin of unknown samples and therefore assist in the monitoring and conservation of honey bee biodiversity in Europe.

Slow improvement to the archiving quality of open datasets shared by researchers in ecology and evolution

Many leading journals in ecology and evolution now mandate open data upon publication. Yet, there is very little oversight to ensure the completeness and reusability of archived datasets, and we currently have a poor understanding of the factors associated with high-quality data sharing. We assessed 362 open datasets linked to first- or senior-authored papers published by 100 principal investigators (PIs) in the fields of ecology and evolution over a period of 7 years to identify predictors of data completeness and reusability (data archiving quality). Datasets scored low on these metrics: 56.4% were complete and 45.9% were reusable. Data reusability, but not completeness, was slightly higher for more recently archived datasets and PIs with less seniority. Journal open data policy, PI gender and PI corresponding author status were unrelated to data archiving quality. However, PI identity explained a large proportion of the variance in data completeness (27.8%) and reusability (22.0%), indicating consistent inter-individual differences in data sharing practices by PIs across time and contexts. Several PIs consistently shared data of either high or low archiving quality, but most PIs were inconsistent in how well they shared. One explanation for the high intra-individual variation we observed is that PIs often conduct research through students and postdoctoral researchers, who may be responsible for the data collection, curation and archiving. Levels of data literacy vary among trainees and PIs may not regularly perform quality control over archived files. Our findings suggest that research data management training and culture within a PI's group are likely to be more important determinants of data archiving quality than other factors such as a journal's open data policy. Greater incentives and training for individual researchers at all career stages could improve data sharing practices and enhance data transparency and reusability.

Host species identity shapes the diversity and structure of insect microbiota

As for most of the life that inhabits our planet, microorganisms play an essential role in insect nutrition, reproduction, defence, and support their host in many other functions. More recently, we assisted to an exponential growth of studies describing the taxonomical composition of bacterial communities across insects' phylogeny. However, there is still an outstanding question that needs to be answered: Which factors contribute most to shape insects' microbiomes? This study tries to find an answer to this question by taking advantage of publicly available sequencing data and reanalysing over 4000 samples of insect-associated bacterial communities under a common framework. Results suggest that insect taxonomy has a wider impact on the structure and diversity of their associated microbial communities than the other factors considered (diet, sex, life stage, sample origin and treatment). However, when specifically testing for signatures of codiversification of insect species and their microbiota, analyses found weak support for this, suggesting that while insect species strongly drive the structure and diversity of insect microbiota, the diversification of those microbial communities did not follow their host's phylogeny. Furthermore, a parallel survey of the literature highlights several methodological limitations that need to be considered in the future research endeavours.

Prion protein is associated with a worse prognosis of head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSC) etiopathogenesis remains unclear, and the biological changes with the activation of heat shock proteins (HSPs) and prion protein (PRNP) promoted by hypoxia in HNSC are undetermined. This study investigates hypoxia's effect in lymph node metastasis by PRNP expression changes and its main partners.

METHODS

The study combined a theoretical/cell culture study with a case-control study. First, bioinformatics and cell culture were performed. A case-control study was performed in a second step by comparing HNSC patients with and without lymph node metastasis.

ANALYSES

The Cancer Genome Atlas (TCGA) data source validates the theory in the global population study.

RESULTS

Bioinformatics analysis suggests that hypoxia-inducible factor-1α (HIF1A) is associated with HSPA4, HSP90AA1 and PRNP expression. TCGA data validate the hypothesis that higher HSP90AA1, HSPA4 and PRNP are related to metastases and low survival. Herein, the cell study demonstrated that muted PRNP did not respond to hypoxia.

DISCUSSION

Our results collectively provide the first evidence that PRNP promotes HNSC lymph node metastasis progression through the upregulation of HSPA4, HSP90AA1 and HIF1A. Our findings may provide a molecular basis for the promoting Role of PRNP in HNSC progression.

Diversity of Dominant Soil Bacteria Increases with Warming Velocity at the Global Scale

Understanding global soil bacterial diversity is important because of its role in maintaining a healthy global ecosystem. Given the effects of environmental changes (e.g., warming and human impact) on the diversity of animals and plants, effects on soil bacterial diversity are expected; however, they have been poorly evaluated at the global scale to date. Thus, in this study, we focused on the dominant soil bacteria, which are likely critical drivers of key soil processes worldwide, and investigated the effects of warming velocity and human activities on their diversity. Using a global dataset of bacteria, we performed spatial analysis to evaluate the effects of warming velocity and human activities, while statistically controlling for the potentially confounding effects of current climate and geographic parameters with global climate and geographic data. We demonstrated that the diversity of the dominant soil bacteria was influenced globally, not only by the aridity index (dryness) and pH but also by warming velocity from the Last Glacial Maximum (21,000 years ago) to the present, showing significant increases. The increase in bacterial diversity with warming velocity was particularly significant in forests and grasslands. An effect of human activity was also observed, but it was secondary to warming velocity. These findings provide robust evidence and advance our understanding of the effects of environmental changes (particularly global warming) on soil bacterial diversity at the global scale.

Patterns in research and data sharing for the study of form and function in caviomorph rodents

The combination of morphometrics, phylogenetic comparative methods, and open data sets has renewed interest in relating morphology to adaptation and ecological opportunities. Focusing on the Caviomorpha, a well-studied mammalian group, we evaluated patterns in research and data sharing in studies relating form and function. Caviomorpha encompasses a radiation of rodents that is diverse both taxonomically and ecologically. We reviewed 41 publications investigating ecomorphology in this group. We recorded the type of data used in each study and whether these data were made available, and we re-digitized all provided data. We tracked two major lines of information: collections material examined and trait data for morphological and ecological traits. Collectively, the studies considered 63% of extant caviomorph species; all extant families and genera were represented. We found that species-level trait data rarely were provided. Specimen-level data were even less common. Morphological and ecological data were too heterogeneous and sparse to aggregate into a single data set, so we created relational tables with the data. Additionally, we concatenated all specimen lists into a single data set and standardized all relevant data for phylogenetic hypotheses and gene sequence accessions to facilitate future morphometric and phylogenetic comparative research. This work highlights the importance and ongoing use of scientific collections, and it allows for the integration of specimen information with species trait data. Recientemente ha resurgido el interés por estudiar la relación entre morfología, ecología, y adaptación. Esto se debe al desarrollo de nuevas herramientas morfométricas y filogenéticas, y al acceso a grandes bases de datos para estudios comparados. Revisamos 41 publicaciones sobre ecomorfología de roedores caviomorfos, un grupo diverso y bien estudiado, para evaluar los patrones de investigación y la transparencia para la liberación de datos. Registramos los tipos de datos que se utilizaron para cada estudio y si los datos están disponibles. Cuando estos datos se compartieron, los redigitalizamos. Nos enfocamos en los ejemplares consultados, y en datos que describen rasgos ecológicos y morfológicos para las especies estudiadas. Los estudios que revisamos abarcan el 63% de las especies de caviomorfos que actualmente existen. Encontramos que raramente fueron compartidos los datos que se tomaron para especies, y menos aún para ejemplares. Los datos morfológicos y ecológicos eran demasiado heterogéneos e exiguos para consolidar en un solo banco de datos; debido a esta circunstancia, creamos tablas relacionales con los datos. Además, enlazamos todas las listas individuales de especímenes para crear un solo banco de datos y estandarizamos todos los datos pertinentes a hipótesis filogenéticas, así como los números de acceso de secuencias genéticas, para así facilitar eventuales estudios comparados de morfometría y filogenia. Este trabajo resalta la importancia de las colecciones científicas y documenta su uso, además permitiendo la futura integración de datos derivados de ejemplares con datos sobre rasgos ecomorfológicos a nivel de especie.

Collaboration across Time and Space in the LTER Network

The scale of ecological research is getting larger and larger. At such scales, collaboration is indispensable, but there is little consensus on what factors enable collaboration. In the present article, we investigated the temporal and spatial pattern of institutional collaboration within the US Long Term Ecological Research (LTER) Network on the basis of the bibliographic database. Social network analysis and the Monte Carlo method were applied to identify the characteristics of papers published by LTER researchers within a baseline of papers from 158 leading ecological journals. Long-term and long-distance collaboration were more frequent in the LTER Network, and we investigate and discuss the underlying mechanisms. We suggest that the maturing infrastructure and environment for collaboration within the LTER Network could encourage scientists to make large-scale hypotheses and to ask big questions in ecology.

Network resilience of mutualistic ecosystems and environmental changes: an empirical study

It is theorized that a mutualistic ecosystem's resilience against perturbations (e.g. species extinction) is determined by a single macroscopic parameter (network resilience), calculable from the network. Given that such perturbations occur owing to environmental changes (e.g. climate change and human impact), it has been predicted that mutualistic ecosystems that exist despite extensive environmental changes exhibit higher network resilience; however, such a prediction has not been confirmed using real-world data. Thus, in this study, the effects of climate change velocity and human activities on mutualistic network resilience were investigated. A global dataset of plant-animal mutualistic networks was used, and spatial analysis was performed to examine the effects. Moreover, the potential confounding effects of network size, current climate and altitude were statistically controlled. It was demonstrated that mutualistic network resilience was globally influenced by warming velocity and human impact, in addition to current climate. Specifically, pollination network resilience increased in response to human impact, and seed-dispersal network resilience increased with warming velocity. The effect of environmental changes on network resilience for plants was remarkable. The results confirmed the prediction obtained based on the theory and imply that real-world mutualistic networks have a structure that increases ecosystem resilience against environmental changes. These findings will enhance the understanding of ecosystem resilience.

Decomposing the effects of ocean environments on predator-prey body-size relationships in food webs

Body-size relationships between predators and their prey are important in ecological studies because they reflect the structure and function of food webs. Inspired by studies on the impact of global warming on food webs, the effects of temperature on body-size relationships have been widely investigated; however, the impact of environmental factors on body-size relationships has not been fully evaluated because climate warming affects various ocean environments. Thus, here, we comprehensively investigated the effects of ocean environments and predator-prey body-size relationships by integrating a large-scale dataset of predator-prey body-size relationships in marine food webs with global oceanographic data. We showed that various oceanographic parameters influence prey size selection. In particular, oxygen concentration, primary production and salinity, in addition to temperature, significantly alter body-size relationships. Furthermore, we demonstrated that variability (seasonality) of ocean environments significantly affects body-size relationships. The effects of ocean environments on body-size relationships were generally remarkable for small body sizes, but were also significant for large body sizes and were relatively weak for intermediate body sizes, in the cases of temperature seasonality, oxygen concentration and salinity variability. These findings break down the complex effects of ocean environments on body-size relationships, advancing our understanding of how ocean environments influence the structure and functioning of food webs.

Human Impacts and Climate Change Influence Nestedness and Modularity in Food-Web and Mutualistic Networks

Theoretical studies have indicated that nestedness and modularity—non-random structural patterns of ecological networks—influence the stability of ecosystems against perturbations; as such, climate change and human activity, as well as other sources of environmental perturbations, affect the nestedness and modularity of ecological networks. However, the effects of climate change and human activities on ecological networks are poorly understood. Here, we used a spatial analysis approach to examine the effects of climate change and human activities on the structural patterns of food webs and mutualistic networks, and found that ecological network structure is globally affected by climate change and human impacts, in addition to current climate. In pollination networks, for instance, nestedness increased and modularity decreased in response to increased human impacts. Modularity in seed-dispersal networks decreased with temperature change (i.e., warming), whereas food web nestedness increased and modularity declined in response to global warming. Although our findings are preliminary owing to data-analysis limitations, they enhance our understanding of the effects of environmental change on ecological communities.

Open Data in Global Environmental Research: The Belmont Forum's Open Data Survey

This paper presents the findings of the Belmont Forum’s survey on Open Data which targeted the global environmental research and data infrastructure community. It highlights users’ perceptions of the term “open data”, expectations of infrastructure functionalities, and barriers and enablers for the sharing of data. A wide range of good practice examples was pointed out by the respondents which demonstrates a substantial uptake of data sharing through e-infrastructures and a further need for enhancement and consolidation. Among all policy responses, funder policies seem to be the most important motivator. This supports the conclusion that stronger mandates will strengthen the case for data sharing.

Public Data Archiving in Ecology and Evolution: How Well Are We Doing?

Policies that mandate public data archiving (PDA) successfully increase accessibility to data underlying scientific publications. However, is the data quality sufficient to allow reuse and reanalysis? We surveyed 100 datasets associated with nonmolecular studies in journals that commonly publish ecological and evolutionary research and have a strong PDA policy. Out of these datasets, 56% were incomplete, and 64% were archived in a way that partially or entirely prevented reuse. We suggest that cultural shifts facilitating clearer benefits to authors are necessary to achieve high-quality PDA and highlight key guidelines to help authors increase their data's reuse potential and compliance with journal data policies.

What drives academic data sharing?

Despite widespread support from policy makers, funding agencies, and scientific journals, academic researchers rarely make their research data available to others. At the same time, data sharing in research is attributed a vast potential for scientific progress. It allows the reproducibility of study results and the reuse of old data for new research questions. Based on a systematic review of 98 scholarly papers and an empirical survey among 603 secondary data users, we develop a conceptual framework that explains the process of data sharing from the primary researcher’s point of view. We show that this process can be divided into six descriptive categories: Data donor, research organization, research community, norms, data infrastructure, and data recipients. Drawing from our findings, we discuss theoretical implications regarding knowledge creation and dissemination as well as research policy measures to foster academic collaboration. We conclude that research data cannot be regarded as knowledge commons, but research policies that better incentivise data sharing are needed to improve the quality of research results and foster scientific progress.

It's Good to Share: Why Environmental Scientists' Ethics Are Out of Date

Although there have been many recent calls for increased data sharing, the majority of environmental scientists do not make their individual data sets publicly available in online repositories. Current data-sharing conversations are focused on overcoming the technological challenges associated with data sharing and the lack of rewards and incentives for individuals to share data. We argue that the most important conversation has yet to take place: There has not been a strong ethical impetus for sharing data within the current culture, behaviors, and practices of environmental scientists. In this article, we describe a critical shift that is happening in both society and the environmental science community that makes data sharing not just good but ethically obligatory. This is a shift toward the ethical value of promoting inclusivity within and beyond science. An essential element of a truly inclusionary and democratic approach to science is to share data through publicly accessible data sets.

Seventy-one important questions for the conservation of marine biodiversity

The ocean provides food, economic activity, and cultural value for a large proportion of humanity. Our knowledge of marine ecosystems lags behind that of terrestrial ecosystems, limiting effective protection of marine resources. We describe the outcome of 2 workshops in 2011 and 2012 to establish a list of important questions, which, if answered, would substantially improve our ability to conserve and manage the world's marine resources. Participants included individuals from academia, government, and nongovernment organizations with broad experience across disciplines, marine ecosystems, and countries that vary in levels of development. Contributors from the fields of science, conservation, industry, and government submitted questions to our workshops, which we distilled into a list of priority research questions. Through this process, we identified 71 key questions. We grouped these into 8 subject categories, each pertaining to a broad component of marine conservation: fisheries, climate change, other anthropogenic threats, ecosystems, marine citizenship, policy, societal and cultural considerations, and scientific enterprise. Our questions address many issues that are specific to marine conservation, and will serve as a road map to funders and researchers to develop programs that can greatly benefit marine conservation.

Troubleshooting public data archiving: suggestions to increase participation

An increasing number of publishers and funding agencies require public data archiving (PDA) in open-access databases. PDA has obvious group benefits for the scientific community, but many researchers are reluctant to share their data publicly because of real or perceived individual costs. Improving participation in PDA will require lowering costs and/or increasing benefits for primary data collectors. Small, simple changes can enhance existing measures to ensure that more scientific data are properly archived and made publicly available: (1) facilitate more flexible embargoes on archived data, (2) encourage communication between data generators and re-users, (3) disclose data re-use ethics, and (4) encourage increased recognition of publicly archived data.

Science or slaughter: need for lethal sampling of sharks

General consensus among scientists, commercial interests, and the public regarding the status of shark populations is leading to an increasing need for the scientific community to provide information to help guide effective management and conservation actions. Experience from other marine vertebrate taxa suggests that public, political, and media pressures will play an increasingly important part in setting research, management, and conservation priorities. We examined the potential implications of nonscientific influences on shark research. In particular, we considered whether lethal research sampling of sharks is justified. Although lethal sampling comes at a cost to a population, especially for threatened species, the conservation benefits from well-designed studies provide essential data that cannot be collected currently in any other way. Methods that enable nonlethal collection of life-history data on sharks are being developed (e.g., use of blood samples to detect maturity), but in the near future they will not provide widespread or significant benefits. Development of these techniques needs to continue, as does the way in which scientists coordinate their use of material collected during lethal sampling. For almost half of the known shark species there are insufficient data to determine their population status; thus, there is an ongoing need for further collection of scientific data to ensure all shark populations have a future. Shark populations will benefit most when decisions about the use of lethal sampling are made on the basis of scientific evidence that is free from individual, political, public, and media pressures.

The Primate Life History Database: A unique shared ecological data resource

The importance of data archiving, data sharing, and public access to data has received considerable attention. Awareness is growing among scientists that collaborative databases can facilitate these activities.We provide a detailed description of the collaborative life history database developed by our Working Group at the National Evolutionary Synthesis Center (NESCent) to address questions about life history patterns and the evolution of mortality and demographic variability in wild primates.Examples from each of the seven primate species included in our database illustrate the range of data incorporated and the challenges, decision-making processes, and criteria applied to standardize data across diverse field studies. In addition to the descriptive and structural metadata associated with our database, we also describe the process metadata (how the database was designed and delivered) and the technical specifications of the database.Our database provides a useful model for other researchers interested in developing similar types of databases for other organisms, while our process metadata may be helpful to other groups of researchers interested in developing databases for other types of collaborative analyses.

Improving normal tissue complication probability models: the need to adopt a "data-pooling" culture

Clinical studies of the dependence of normal tissue response on dose-volume factors are often confusingly inconsistent, as the QUANTEC reviews demonstrate. A key opportunity to accelerate progress is to begin storing high-quality datasets in repositories. Using available technology, multiple repositories could be conveniently queried, without divulging protected health information, to identify relevant sources of data for further analysis. After obtaining institutional approvals, data could then be pooled, greatly enhancing the capability to construct predictive models that are more widely applicable and better powered to accurately identify key predictive factors (whether dosimetric, image-based, clinical, socioeconomic, or biological). Data pooling has already been carried out effectively in a few normal tissue complication probability studies and should become a common strategy.