Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Overestimating trophic similarity? #43

Open
rfrelat opened this issue Dec 15, 2020 · 1 comment
Open

Overestimating trophic similarity? #43

rfrelat opened this issue Dec 15, 2020 · 1 comment

Comments

@rfrelat
Copy link

rfrelat commented Dec 15, 2020

I was trying to understand the Jaccard similarity that is computed by the function TrophicSimilarity(). I realised that 'c', the number of resources and consumers common to both nodes could be the prey of one species, and the predator of the other species.

For instance, using the ChesapeakeBay dataset, the trophic similarity between Phytoplankton (#1) and Clupeidae (#21) is 0.125. While in the food web, the two species don't have any prey in common (no prey for Phytoplankton, while Clupeidae prey on Zooplankton) and they don't share any predators (the only predator for Clupeidae is Morone saxatilis, Phytoplankton has 7 predators - Microzooplankton, Zooplankton, Other suspension feeders, Mya, Crassostrea virginica, Anchoa mitchilli, Brevoortia tyrannus.

data("ChesapeakeBay")
Sim <- TrophicSimilarity(ChesapeakeBay)
Sim[1,21] #0.125

In the calculation of similarity, the number of common prey and predator is equal to 1 (because Zooplankton is a predator of Phytoplankton and a prey for Clupeidae).

I am not sure it is an issue (the calculation is correct and correspond to the formula explained in the documentation), but the formula doesn't feel right from an ecological point of view. I would recommend to calculate separately the number of common prey and the number of common predators. But maybe I misunderstood the original calculation from Neo Martinez and this issue can be closed without any modifications.

@quicklizard99
Copy link
Owner

Apologies for my very late reply.

As you pointed out, the TrophicSimilarity function implements the method described by Martinez. One of the goals for Cheddar was to make it easy to compute existing commonly quoted food-web statistics. I would prefer to stick to this philosophy and would like to avoid both adding new methods and altering existing ones.

Incidentally, you can access values here (and elsewhere) using node names: Sim["Phytoplankton", "Clupeidae"].

Sorry again for having taken so long to reply.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants