34 Matching Annotations
  1. Aug 2021
    1. Herbert (1965)

      +1

    2. can never really be true negatives

      Maybe add a reference or explain this is true. Isn't it contrary to assuming 1s and 0s are all true when finding the cutoff in Fig.2?

    3. Because the confidence intervals on the inferred trait space are probably over-estimates,

      I guess I do not understand what you did for this step and why. I am confused by the link between the trait space confidence intervals and this new threshold. I am also not sure to understand how the threshold was used. Note that I haven't look at Cirtwill and Hamback yet

    4. P(i → j) ≈ 0.08

      So after applying the threshold, an interaction with a probability > 0.08 is transformed into an interaction? Can we still talk about "Probability of an interaction" in the probabilistic metaweb P ?

    5. interactions known to GLOBI would also be predicted

      How did you calculated success rate ? If I understand correctly you have probabilities vs ones. Maybe you need to explain what a success mean in that case. Is it probabilities > a certain threshold = success? Or is it successes across all 2*10^5 network? If so, I am not sure to understand what "33 of which were not predicted by the model".

    6. igure 5: Left: effect of varying the cutoff for probabilities to be considered non-zero on the number of unique links and

      I am not sure to understand the figure. (Left) Red is the proportion of non-zero for each cutoff, but I am not sure to understand where the blue comes from. Also you y label "Proportion of links left" does not apply to the right panel.

    7. dataset documented 25 interactions between mammals,

      Could we use the 0s in Strong & Leroux as it is suppose to document all interactions? If not, maybe a sentence to explain why as you did for Globi.

    8. success rate of 92%

      Same as above

    9. After performing this check, we set the probability of all interactions known to GLOBI (366 in total, 33 of which were not predicted by the model, for a success rate of 91%) to 1.

      Is it the success rate prior to or after re-using the knowledge from Europe?

    10. fig. 2

      fig.3

    11. fig. 3

      (fig.3)?

    12. accuracy

      accuracy as in the proportions of correct predictions? or is it the Youden's J? I think, it would be interesting to have the J statistic as well since it is used to determine the cutoff. I agree with Ben that a sentence to describe Youden's J and why you used it would be helpful.

    13. transferable

      I find it a bit confusing how the rest of the paragraph explain how representational approaches are more easily transferable than other approaches

    14. trophic interactions between mammals in Canada.

      Maybe a few words on why Canada?

    15. infer this representation

      Took me a few read to understand the structure of the sentence. to infer? Maybe use a more precise term (metaweb?) instead of "this representation".

    16. reviewed in Strydom et al. (2021)

      Maybe "presented"? as the paper is not a "review" of the different methods, but an overview of how this can be done.

    17. 5

      Make it as 7: Department of BIology, McGill University , Montréal, Canada

  2. Jun 2021
    1. because we definitely should

      Q:Why should we predict interactions networks? A: Because we should!

      As a reader, I'd be a bit disappointed by this answer. Maybe something like : Because we almost can, and because we definitely need to.

    2. Given two species co-occur, a neutral approach to probabilistic interactions would assume that the effect of abundances and trait matching would have no effec

      I think you mean: A neutral approach to probabilistic interactions would rely only on the effect of abundances and assume trait-matching would have no effect?

    3. interactin

      interaction

    4. C

      C is already used in the ms for the "cooccurrence matrix" in the proof-of-concept

    5. priors on parameters, P(θ)

      I'd continue with the same structure, something like:

      Priors on parameters P(\tetha), which describe the modelers belief about the value of the parameters.

    6. and highlight two specific areas where it can have a strong impact: the temporal forecasting of species interaction networks structure, and the use of predicted networks for applied ecology or conservation biology

      I think you can delete this. We highlight the areas in another section of the ms.

    7. Vazquez et al. (2009

      missing ()

    8. (J. Dunne 2006).

      If we are talking about coexistance and not interaction, Dunne 2006 is not really relevant

    9. We first aggregate all interactions into a cooccurrence matrix C which represents whether a given pair of species (i, j) was observed coexisting across any location (J. Dunne 2006).

      I find it confusing how co-occurrence and interactions are mixed.The first half of the sentence seems to indicate that C is built with interactions, while the second half seems to indicate that it is built with co-occurrence.

      If C is built with interactions, maybe we should name it adjacency matrix A ?

    10. ML

      This abbreviation has not been introduced. Replace by machine learning

    11. not

      nor

  3. Feb 2021
    1. there have been calls for a probabilistic species pool

      you say twice there have been calls. Maybe simplify the sentence with something like: through probabilistic species pool, and more importantly ...

    2. .S

      missing space

    3. embedding projects

      missing words

    4. reached an accuracy of  ≈ 0.8

      Semi- by curiosity, semi- because it might be better to explicitly say it, but how was accuracy calculated? It is not clear if correctly predicted absences are used? As stated before, there are no true negative.

    5. All models

      Maybe I'm wrong, but this applies only to mathematical models?

    6. Here adopt a question-driven approach to serve as a guide through the path toward building models to predict and forecast the structure of ecological networks across space, and to identify the next steps in the research regime.

      The sentence is very hard to read. too many long noun strings.