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

Define a process to screen allometries #16

Closed
teixeirak opened this issue Feb 7, 2018 · 6 comments
Closed

Define a process to screen allometries #16

teixeirak opened this issue Feb 7, 2018 · 6 comments

Comments

@teixeirak
Copy link
Member

We'll want to set bonds on what should be considered a reasonable biomass estimate and flag any allometries that fall outside of this range.

The first step is to define how those bounds should be determined.

@maurolepore
Copy link
Member

@teixeirak,

Great suggestion. Is it possible to gather real data of measured biomass for all the taxonomic groups included in allodb?

If we had a distribution of measured biomass for each taxonomic group we could use it to calculate simple statistics, and thus check if the equations of allodb result in output within an expected range.

@teixeirak
Copy link
Member Author

@ervanSTRI, do you have a suggestion on how to best deal with this? We don't have time to compile a bunch of new data, but I believe you have some that may provide helpful guidance? Note that we need a general solution (e.g., including extratropical species).

@ErvanCH
Copy link

ErvanCH commented Feb 28, 2018

Hi there. Checking the performance of a model is only possible if you have harvested trees at a site. There are a bunch of data available out there, and I can help in compiling those. However, this data will only help to check the "general" accuracy of this or that allometric model, but won't help in assessing the performance of that model at a given site.
A possible way to prioritize one model over another is to do check what are the determinants of AGB. In the tropics, having D, height and wood density returns fair estimates. For temperate and northern forests, largely dominated by coniferous, tree height is generally not accounted for. It might be due to lack of available data, or this variable being a poor predictor. Stand age or stand density seems more commonly used. So here, you might want to rank allometric models based on available information at a site by region:
tropics: f(D,H,WD) > f(D,WD) > f(D,crown length) > ...
temperate EU: f(D,stand age, etc) > f(D,H) > f(D,WD) > ...
(PS: those are juste dummy examples)

Does it make sense?

...

@teixeirak
Copy link
Member Author

teixeirak commented Feb 28, 2018

Thanks, Ervan. This thread has taken a direction other than what I had in mind, probably because I didn't express the question clearly enough. We've already set criteria for selecting the allometries. The point of this issue is to develop a process for checking that all equations entered in the database give reasonable values. This is mostly for the sake of ensuring that equations were correctly transcribed from original publications (i.e., no errors in units conversions, etc.). I'd also hope that it would be useful in identifying anomalous allometries that may be poorly constructed (i.e., equations that should be revisited). The latter would be more likely to occur for temperate regions where we're assembling lots of species-level allometries.

Perhaps a good place to start would be flagging equations that give estimates outside the range of 50-150% of the generic equation for the region (e.g., Chave).

@teixeirak
Copy link
Member Author

Issue #73 will allow visual inspection, which is sufficient for minimum viable product. Formal code tests will be a lower-priority enhancement.

@gonzalezeb
Copy link
Contributor

This issue now relates and it may solved by #96, so I am closing it.

We will weight allometric models (basically rank) based on available information.

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

No branches or pull requests

4 participants