easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application

Large-scale ecological sampling can be difficult and costly, especially for organisms that are too small to be easily identified in a natural environment by eye. Typically, these microscopic floral and fauna are sampled by collecting substrates from nature and then separating organisms from substrates in the laboratory. In many cases, diverse organisms can be identified to the species-level using molecular barcodes. To facilitate large-scale ecological sampling of microscopic organisms, we used a geographic data-collection platform for mobile devices called Fulcrum that streamlines the organization of geospatial sampling data, substrate photographs, and environmental data at natural sampling sites. These sampling data are then linked to organism isolation data from the laboratory. Here, we describe the easyFulcrum R package, which can be used to clean, process, and visualize ecological field sampling and isolation data exported from the Fulcrum mobile application. We developed this package for wild nematode sampling, but it can be used with other organisms. The advantages of using Fulcrum combined with easyFulcrum are (1) the elimination of transcription errors by replacing manual data entry and/or spreadsheets with a mobile application, (2) the ability to clean, process, and visualize sampling data using a standardized set of functions in the R software environment, and (3) the ability to join disparate data to each other, including environmental data from the field and the molecularly defined identities of individual specimens isolated from samples.

The Fulcrum data-collection application does not have a published reference in the literature. Fulcrum is a commercial product. However, users can make agreements for educational use. We've clarified this point in the manuscript where we first introduce Fulcrum.
Line 54: "It [Fulcrum] is a commercial application but can be used under a no-cost educational agreement." 2. In line 126, authors mention Genotyping template (google sheet) to enter data for isolated samples. Author explain well how to duplicate and use the template but fail to explain columns like ssu_pcr_date, its2_pcr_date etc. Also, there is no mention of the column name to input sanger sequencing data.
We agree that the descriptions for the columns in our genotyping sheet were lacking. We have addressed this issue in multiple ways. First, we revised easyFulcrum code to help non-nematode users that wish to work with a simple, generalizable genotyping sheet (six variables rather than 38). Second, we include Table 2, which describes each of the variables in the "general" genotyping sheet and how to use them. Third, we have included similar details for the larger, nematode specific genotyping sheet (see the column descriptions tab).
We have also tried to address the concern that there is no column to input sanger sequencing data in the genotyping sheet. We include new text in the "Specimen identification" methods section emphasizing that users are to generate specimen sequence data and perform alignments to sequence databases outside of easyFulcrum then enter the results from the alignments into the genotyping sheet by inputting the species name of the top alignment. We also include more details about how we perform nematode-specific species identification.

Authors need to explain how to input genotyping data and blast results if any new species is identified.
Thank you for pointing out this point of confusion. We included additional text to help users input genotyping data into the genotyping sheet (see methods, Specimen identification). We also included Table 2 that describes each of the variables in the genotyping sheet and explicitly addresses how to enter data regarding potential new species.

In line 176, author is suggesting to see methods. It will be helpful if authors mention which subheading in the methods to look for.
Agreed. We added the subheading at line 174. Also, we now refer to specific subheadings throughout the manuscript.

Authors should mention that
We are not sure what the reviewer's concern is in this case, but the GitHub repository for easyFulcrum is a public repository (https://github.com/AndersenLab/easyfulcrum). We use the standard MIT license. Figure 3A image quality is not good. Labels in the image are not legible.

6.
We agree. We remade figure 3A and used the PACE system to ensure the image quality meets PLoS ONE publication standards. Figure 3, authors can include the "genotyping template" made for C.elegans, C.briggsae and C. tropicalis.

For
We agree that this example is a great idea. We have included the processed data used to make Figure 3 as a supplemental file (S1 data). We have also included the rendered report in HTML format as a supplemental file (S2 report). These files are cited in the "Generating summary and output files" Results section and in the figure legend for Fig 3. Reviewer #2: The manuscript sounds technically poor, I have following concerns should be addressed before any decision.
1. There are some typos and grammatical errors in the manuscript. It is strongly suggested that the whole work to be carefully checked by someone has expertise in technical English writing.
We strongly believe that the manuscript does not contain typos or grammatical errors. Please point out line numbers so we can correct any errors.

Key contribution and novelty has not been detailed in manuscript. Please include it in the introduction section.
This manuscript describes a novel software package to process ecological sampling data using Fulcrum. The Introduction describes the state of the field, available technologies, and our solutions.

What are the limitations of the related works?
We describe the difficulties with current technologies in the Introduction (written, lack of robust database architectures, etc.).

Are there any limitations of this carried out study?
This manuscript is not a study. It is a description of a software package. Our limitations are that not every organism data type will be easily entered into this package. We have responded to reviewer #1's comments to make it more generalizable and have worked to make it less nematode-specific. Many species of microfauna, well beyond nematodes, will benefit from the easyFulcrum package.

How to select and optimize the user-defined parameters in the proposed model?
We do not use a model or any modeling in this manuscript.

There are quite a few abbreviations are used in the manuscript. It is suggested to use a table to host all the frequently used abbreviations with their descriptions to improve the readability.
We do not have any abbreviations, except function names. All function names are described.

Some sentences are too long to follow, it is suggested that to break them down into short but meaningful ones to make the manuscript readable.
Please let us know which sentences are too long to follow.

Explain the evaluation metrics and justify why those evaluation metrics are used?
We have no evaluation metrics in this manuscript.

It seems that the authors used images of equations, please use editable equation format.
We have no equations or images of equations in this manuscript.

The Related Works section is also fair, yet the criteria behind the selection of the works described should be explained.
We have no Related Works section.

The title is pretty deceptive and does not address the problem completely.
Please let us know how the title is deceptive. We describe how easyFulcrum should be used.

Every time a method/formula is used for something, it needs to be justified by either (a) prior work showing the superiority of this method, or (b) by your experiments showing its advantage over prior work methods -comparison is needed, or (c) formal proof of optimality. Please consider more prior works.
We have no formulae in this manuscript. The methods are explicitly described in each section.

The data is not described. Proper data description should contain the number of data items, number of parameters, distribution analysis of parameters, and of the target parameter itself for classification.
We describe where our example data originate. We provide those data. Additionally, in response to reviewer #1, we added a data dictionary for a large example data set.
We have no classification of parameter values in this manuscript.
14. The related works section is very short and no benefits from it. I suggest increasing the number of studies and add a new discussion there to show the advantage.
We have no Related Works section.

Method description is detailed and overall convincing, yet there is a big formatting problem with the end of this section and the beginning of the following one.
Please let us know what the formatting issue is. We will work to resolve it.

Figures 1-4 are low quality and very unprofessional figures please improve them.
This manuscript does not have a Figure 4. Figures 1-3 pass the PACE requirements for PLoS ONE. The PDF rendering used by PLoS journals generates low-quality images in the reviewer PDF.

Use Anova test to record the significant difference between performance of the proposed and existing methods.
We do not have ANOVA tests in this software package.