Ushio Masayuki is Assistant Professor at the Department of Ocean Science at the Hong Kong University of Science and Technology (HKUST). Ushio and the author team behind ‘Temperature sensitivity of the interspecific interaction strength of coastal marine fish communities’ chose to publish their research with our new model.
We spoke to Ushio to find out more about his experience. Thanks for sharing your answers, Ushio!
Please introduce yourself and tell us about your area of research
I consider myself a general ecologist, and my research activity began in a tropical montane forest in Malaysian Borneo in 2005. At the time, I was studying the interaction between plants and soil, also known as plant-soil feedback. Collecting data from field sites, I encountered relatively complicated data that required me to learn many statistical methods. After earning my doctoral degree from Kyoto University, Japan, I continued my ecological research, driven by my curiosity to understand the drivers of natural ecosystem dynamics.
In 2014, I started to work on environmental DNA (eDNA) analysis, which is a promising method for monitoring biodiversity comprehensively. Given my years of work in soil microbial ecology, it was not difficult for me to understand the background methodologies necessary for eDNA research, such as PCR and sequence data processing. I then delved into eDNA research and integrated my statistical skills, such as nonlinear time series analysis methods, into my work.
Our research aims to understand ecological dynamics, community assembly processes, and the resultant ecosystem services we benefit from. Natural ecosystem dynamics are driven by complex interactions among organisms and environments, making understanding and forecasting them a challenging task, but this is actually what fascinates me and is the motivation of my work.
Can you tell us briefly about your paper?
In our paper published in eLife, we collected 550 eDNA samples over two years from 11 study sites along the Boso Peninsula in Japan. State-of-the-art nonlinear time series analysis methods were applied to the eDNA data to understand how water temperature influences fish-fish interactions. The research was based on two ideas: (1) time-series based methods to detect causality between variables are being rapidly developed, which allows for the detection and quantification of interspecific interactions from biomonitoring data, and (2) eDNA-based ecosystem monitoring enables the detection of many fish species from a single water sample and tracking of population dynamics.
The MiFish metabarcoding method and quantitative PCR were used to quantify population dynamics of more than 800 fish species, consistent with the number of fish species compiled from a literature survey and museum collections. We observed a clear seasonality of species richness and total eDNA concentrations, both of which are high in summer and low in winter. Nonlinear time series analysis was applied to detect the causalities among fish species, and fish-fish interactions under natural conditions were quantified. We then estimated how fish-fish interactions will change in a warming world.
An important finding of this study was the effect of water temperature on fish-fish interactions was highly species-dependent. For some fish species, there was a strong positive effect of water temperature on the interspecific interactions, while for some other fish species, there was a negative effect of water temperature. These results imply that the effect of water temperature, and hence global climate change, may be more complicated than previously assumed.
Why did you choose to submit your paper to the new model at eLife?
One reason why we submitted our paper to eLife is due to its unique review process. Our studies often involve the integration of many different experimental and statistical processes, which can be somewhat complicated. We understand that the more methods we integrate, the higher the chance our studies will be criticized as all methods have limitations. As expected, we have received many criticisms on our previous studies, particularly on the methods used.
Getting negative reviews usually means that a paper will be rejected, even if it is heading in the right direction. Under these circumstances, eLife's new model, which has abandoned the accept/reject decision, seemed to be a good fit for our paper. We do not believe that eLife's submission model can completely replace the traditional submission model, but we do believe that the diversity of evaluation processes is critical in fostering the diversity of research.
How did you find the new process of publishing with eLife?
Overall, the review and publication process with eLife was smooth, fair, and transparent. The reviewers and editor requested only essential revisions, and what was particularly comfortable about the process was that we, the authors, had control over the overall process. Additionally, I appreciated that after the first review, the preprint was made public with a DOI and eLife's evaluation, which I believe added to the transparency of the review process. After the paper was sent out for in-depth review, we were able to focus on improving the paper without worrying about rejection, which was particularly a nice point of the new model.
What were your thoughts about the reviews and eLife assessment?
I found the review process and eLife assessment to be very fair and transparent. The initial evaluation was made public shortly after the first round of review, and subsequent conversations with the reviewers and editor were also made public. I do not have any direct concerns about the review process.
However, one thing that I am aware of is that the review process may increase the burden for reviewers and editors. In particular, editors may need to pay closer attention to the papers they are handling and have to prepare layman-friendly summaries for the assessment. Although eLife's new model dramatically reduces the physical and mental burden for authors, it does not resolve the burden issues for reviewers and editors.
Do you have any advice for researchers who are unsure about eLife’s new model?
I understand that eLife's new model differs greatly from the traditional model, and there may be uncertainty for some researchers regarding the submission process. Some researchers may be concerned about the quality of peer review and the future reputation of eLife. However, our experience with eLife has been positive, as the review process is transparent and fair, and we appreciate having control over the fate of our manuscript.
While I do not believe that eLife's submission model can completely replace the traditional model, I think that a diversity of evaluation processes is critical to fostering a diversity of research, as stated in the answer above. Ultimately, the most important aspect is conducting good science and disseminating our findings to colleagues and society in a fair, timely, and efficient manner. For those who are uncertain or anxious about eLife's new model, I recommend submitting one paper to eLife to gain firsthand experience.
Ushio Masayuki bio:
Ushio Masayuki is an Assistant Professor at the Department of Ocean Science at the Hong Kong University of Science and Technology (HKUST).
He has been actively involved in research in ecology, covering a wide range of topics such as tropical forest ecology, nutrient cycling, community assembly, and more recently, environmental DNA analysis and statistical ecology, with a special focus on marine ecosystems.
His current research is focusing on how to improve biodiversity monitoring using environmental DNA-based methods, and how to extract the essential information from the data to understand, conserve, and forecast natural ecosystem dynamics.
