Proposed guidelines for presentation of ecological community responses to a key factor (or set thereof)

Observations on accessibility of evidence and coherence in reported findings

In collaboratively writing this week as a team and in reviewing the literature with a specific meta-question in mind (how best to present community ecology, today, for the specific papers we are working on), we have a formula for a REALLY solid and clear presentation of results for some papers to consider – primarily for those that examined the response of a community (animals, birds, pollinators, etc.) to a key factor such as shrubs, shelters, water, light, or density to name a few ideas. This trend in reporting included competition and facilitation papers not just keystone plant species effects on other species.

FIG 1. Gift to the reader.

Surprise, this is for you. Thank you for getting this far into the paper or even scrolling to a figure. No sarcasm here – everyone busy and there a lot of potential papers to read in ecology and evolution.

This figure is thus the MAIN POINT of paper.
Show them the hypothesis ‘worked’! We defined ‘worked’ as including enough complexity to address how well and when (i.e. community response by phylum or season). So, reading a paper on light and competition on COMMUNITIES (plants or any taxa), we skim to the first figure and EXPECT to see, well you guessed it, light on x-axis then y-some measure of how the community responded – big picture results. We also expected to see some facet or color in data or some level illustrating how well the factor worked so to speak. Is light level always important? Or, does it depend on something?  Almost ALL current papers include that second factor.

Like this or even better really.

The reader is like ‘OH I got it’. Density is important or microhabitat important, but it depends on season because birds fly around a lot and migrate too.

FIG 2. Show something about the species in community.

Imagine a reviewer for a journal such as Journal of Animal Ecology or really any eco-journal.  The editor will try for an ecologist that knows something about desert mammals, birds, or the bees if the paper is about those communities. These readers will expect a second plot to be about composition or show species. Bird people (plant people too when we read community response papers about plants) want to be able see a plot and go OHYA I know that species OR aha I suspected NOT all species responded the exact same way to this key driver.

There are least three options for a STRONG second plot about species.

a. Relative frequencies.
A stacked bar or line plot or something that lists out species and shows their relative frequencies by at least one, prefereably two, key level(s). Rank abundance plots nice but not so common now.

b. A composition plot from an ordination analysis
One that shows something really deep about community OR actually shows species in the ordination plots with labels.

c. A cool species network plot
A plot that shows not only the species BUT how their connections changes based on the key factor(s).

FIG 3. Mechanism or other key ecological context that illuminates WHY the community responded to key factor(s).

Optional (and depends on study of course) but can illustrate how another key moderator IF needed such as RDM, temperature, etc mediates the community outcomes. OR, show the mechanism that explains fig 1 and 2. OR, zoom in on a key finding such as species by functional group, migratory status, etc.


Fig 1 – Main finding with enough detail to encompass predictions or how well and when hypothesis works (or not).
Fig 2 – Show composition or species because this is a community response paper.
Fig 3 – Show mechanism, zoom in on how community responded (functional groups), or show a really important finding that is strongly related to Fig 1 but you did not want clutter up or make it even more complex.

Preferences from a week of work on reading and writing with an attempted laser-beam focus.

steps to update a manuscript that was hung up in peer review forever then rejected (or just neglected for a long time)

Sometimes, peer review (and procrastination) help. Other times, the delays generate more net work. I was discussing this workflow with a colleague regarding a paper that was submitted two-years ago, rejected, then we both ran out of steam. This was the gold-standard workflow we proposed (versus reformat and submit to another journal immediately).


  1. Hit web of science and check for new papers on topic.
  2. Download the pdfs.
  3. Read them.
  4. Think about what to cite or add.
  5. Add citations and rebuild biblio. 
  6. Update writing to mention new citations especially if they are really relevant (intro and discussion).
  7. Take whatever pearls of wisdom you can from rejection in first place and revise ideas, plots, or stats.
  8. Format for new journal.
  9. Check requirements for that journal.
  10. Search the table of contents for the journal and check your lit cited to ensure you cite a few papers from that journal – if not, assess whether that the right journal for this contribution.
  11. Download pdfs from new journal, read, cite, and interpret.
  12. Then, look up referees and emails.
  13. Write cover letter.
  14. Set up account for that new and different annoying journal system – register and wait.
  15. Fight with system to submit and complete all the little boxes/fields.

Better knitting to pdf

title: ""
author: you
fig_caption: no
toc: TRUE
toc_depth: 3
# \renewcommand{\contentsname}{} insert preferred word inside {} instead of Contents or leave blank as desired
# toc: TRUE indexes headers but ensure you set depth to match you preferred font size/header style i.e. ### 3
view raw rmd_YAML_PDF.txt hosted with ❤ by GitHub

A brief comment on writing frequently & well for #scicomm & #openscience

I have been thinking on my workflow (Chris Lortie) as of late. This is in response to the recent post by Alex reviewing a book on dissertation writing he received as a gift from a collaborator.



Image from humor post on topic.

I love to write. However, it is so tempting to rabbit hole and keep reading more stuff, exploring tangents and connections, and developing alternative visualizations for a paper. As of late, I have come to recognize that this is one part positive (think through a topic well and provides gestation time) and one part negative (procrastination). It is continuum of opportunity that requires balancing the benefits and costs. However, it is crystal clear to me that writing regularly, if not for large projects but for smaller communications, is beneficial and a key form of practice.  If an audience is included in the writing process, even better, as it encourages more careful wording and promoted open-science insights into the process vs. product of scientific inquiry. Tweets, blog posts, detailed notes at meetings (that you then subsequently share), and sometimes even emails are also excellent opportunities to ensure that you are precise and clear.

I have also purchased this book to check out the workflows of productive individuals.



Finally, I wanted to add that my fav book all time on this subject was by Italo Calvino. Science and literature converge.


The peeking around the corner is a bit cheesy, but it is a really awesome primer on writing.