teixeirak commented 3 years ago

Results are strange:

teixeirak commented 3 years ago

Note's on climate responses from the original papers :

Indeed, BEPA has little correlation to either pre or T. It is more affected by stream flow and PDSI. Thus, BEPA seems fine.
PIPO is more climate sensitive than JUVI. getting that.
winter temperatures generally positive correlated to grwoth for PIPO and JUVI. Getting that.
generally positive correlation with PPT. Getting that for JUNI, but the decline of PIPO at higher T is strange.

teixeirak commented 3 years ago

Importantly, the sparse stands cover a different time period from intermediate and dense:

I suspect that this is what's behind the funny DBH response of PIPO, and could also be affecting climate.

@ValentineHerr , we should drop the sparse stands from the analysis.

teixeirak commented 3 years ago

Unfortunately, it looks like we have nothing indicating the stand density in our formatted data file, which means we'll have go back to the original, probably modifying @biancaglez 's scripts.

If that's complicated, another (probably easier) way to handle this would be to throw out trees starting after ~1960 or so (chronologies start ~1970, but presumably some trees go back farther).

srusso2 commented 3 years ago

Tala should be able to indicate which cores came from which stands for PIPO. Maybe then you can just have separate DBH model fits for stands at different densities. I can try to get on a zoom call with Tala, if you want me to help figure that out. I think a zoom call will be easier than trading many emails, as that seemed to lead to mis-communications last time. I'd probably need a bit of orientation to the data file that Bianca/Valentine are using, or one of them can be on the call. Let me know how I can help!

teixeirak commented 3 years ago

Thanks, @srusso2. As far as I know this info is clear in Tala's data sheets (looks clear, although its possible that questions could arise). What's needed is modifying Bianca's script to ignore the cores from the sparse treatment. Bianca's no longer with us, so I'll let @ValentineHerr determine the easiest way to deal with this.

srusso2 commented 3 years ago

How about just deleting those lines that you don’t want to use from the data itself?

That way, you don’t have to modify the code.

If you want an easy solution...I assume that’s what you meant by “ignore”?

Sabrina E. Russo Professor, School of Biological Sciences & Center for Plant Science Innovation University of Nebraska-Lincoln, USA

From: Kristina Anderson-Teixeira notifications@github.com Sent: Monday, November 9, 2020 6:36:04 AM To: EcoClimLab/ForestGEO-climate-sensitivity ForestGEO-climate-sensitivity@noreply.github.com Cc: Sabrina Russo srusso2@unl.edu; Mention mention@noreply.github.com Subject: Re: [EcoClimLab/ForestGEO-climate-sensitivity] what's going on with NE? (#89)

Thanks, @srusso2https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_srusso2&d=DwMCaQ&c=Cu5g146wZdoqVuKpTNsYHeFX_rg6kWhlkLF8Eft-wwo&r=ozUfXq8GhmyNFrTdmFFL6Q&m=_3XlProqZjdqbCG2HueUeOM_4XV05RIzKy3m7Aw2AcM&s=pQrBD9mcMHx3M5AMmV1BW-R1M1TchMYoYzi6Y7vKkkM&e=. As far as I know this info is clear in Tala's data sheets (looks clear, although its possible that questions could arise). What's needed is modifying Bianca's script to ignore the cores from the sparse treatment. Bianca's no longer with us, so I'll let @ValentineHerrhttps://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_ValentineHerr&d=DwMCaQ&c=Cu5g146wZdoqVuKpTNsYHeFX_rg6kWhlkLF8Eft-wwo&r=ozUfXq8GhmyNFrTdmFFL6Q&m=_3XlProqZjdqbCG2HueUeOM_4XV05RIzKy3m7Aw2AcM&s=aFKF2CTXQy3WbxwJk3WosZPyiknPrnGdirywi5jCiTg&e= determine the easiest way to deal with this.

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ValentineHerr commented 3 years ago

Sorry for the delayed response. I think I can easily change the code to ignore cores that are in the sparse stand.

So just to make sure, I need to ignore the "Treatment" = "Sparse Pine" in this file ?

teixeirak commented 3 years ago

Correct. Thanks!

teixeirak commented 3 years ago

@ValentineHerr , looking at the figure again, I think we also need to drop "Treatment" = "Mid Pine" for JUNI only.

teixeirak commented 3 years ago

There's an un-resolved question on the units here. (@srusso2, you can't see that link, but I'm about to send an email.) I think we're okay, but it's possible there will be a change.

teixeirak commented 3 years ago

The measurement units are correct. Now we just need to remove the young trees that are biasing the analysis.

ValentineHerr commented 3 years ago

"Treatment" = "Sparse Pine" includes a couple JUNI, is that okay?

Will also remove "Treatment" = "Mid Pine" for JUNI only.

teixeirak commented 3 years ago

Please remove the "sparse pine" JUNI as well.

teixeirak commented 3 years ago

Nebraska results make a bit more sense after removing sparse pine for JUNI and PIPO and mid pine for JUNI :

However, the selection of Dec PET is strange, and they still don't match previous observations:

Climwin plots show little correlation, which is to be expected for BEPA (based on table above) but not JUNI and PIPO:

I'm not sure what to try next... Remove mid- PIPO? Or maybe the two sites need to be split, and just one included? (I'd hate to do that, but perhaps our assumption that they could be reasonably combined was wrong.)

@srusso2, it would be great to hear any thoughts you may have on this.

teixeirak commented 3 years ago

I'm noting that the analysis time frame for BEPA at Niobrara is 3-4 decades longer than that of the 2 species at Halsey. Perhaps we need to standardize the analysis time frame? (We don't do this at other sites, but differences are smaller.)

teixeirak commented 3 years ago

Indeed, the near-zero Dec PET that's showing up as an outlier in the climwin PET plot occurred prior to the start of the JUVI and PIPO records:

@ValentineHerr, let's try limiting the analysis timeframe. To make this general, what if we say that the analysis timeframe doesn't start until there are records for at least half the trees at a site?

srusso2 commented 3 years ago

Hi Krista, can you zoom this morning about this, in about 30 min? 8:30 my time? just a short meeting

Sabrina E. Russo Professor, School of Biological Sciences & Center for Plant Science Innovation University of Nebraska-Lincoln, USA

From: Kristina Anderson-Teixeira notifications@github.com Sent: Monday, November 16, 2020 7:25:17 AM To: EcoClimLab/ForestGEO-climate-sensitivity ForestGEO-climate-sensitivity@noreply.github.com Cc: Sabrina Russo srusso2@unl.edu; Mention mention@noreply.github.com Subject: Re: [EcoClimLab/ForestGEO-climate-sensitivity] what's going on with NE? (#89)

Nebraska results make a bit more sense after removing sparse pine for JUNI and PIPO and mid pine for JUNI :

[image]https://urldefense.proofpoint.com/v2/url?u=https-3A__user-2Dimages.githubusercontent.com_6355854_99255772-2D69706d80-2D27e2-2D11eb-2D95cd-2D5e848a8fca8f.png&d=DwMCaQ&c=Cu5g146wZdoqVuKpTNsYHeFX_rg6kWhlkLF8Eft-wwo&r=ozUfXq8GhmyNFrTdmFFL6Q&m=ygwKpdM5j2hXyMFv3E4dOpEivd-ufm-TuRyj8a-utuM&s=869hIeL8ymx9VwQHmHW0uIOWMhSVSzUBW37D_YL_07M&e=

[image]https://urldefense.proofpoint.com/v2/url?u=https-3A__user-2Dimages.githubusercontent.com_6355854_99255749-2D5eb5d880-2D27e2-2D11eb-2D9350-2D683a98eb0fea.png&d=DwMCaQ&c=Cu5g146wZdoqVuKpTNsYHeFX_rg6kWhlkLF8Eft-wwo&r=ozUfXq8GhmyNFrTdmFFL6Q&m=ygwKpdM5j2hXyMFv3E4dOpEivd-ufm-TuRyj8a-utuM&s=B2Nod3m8TLtEj4v4977HyfnfR1sC1GUbbhoAh-XSpp0&e=

However, the selection of Dec PET is strange, and they still don't match previous observations: [image]https://urldefense.proofpoint.com/v2/url?u=https-3A__user-2Dimages.githubusercontent.com_6355854_99256096-2Ddb48b700-2D27e2-2D11eb-2D8a74-2D665b869a748c.png&d=DwMCaQ&c=Cu5g146wZdoqVuKpTNsYHeFX_rg6kWhlkLF8Eft-wwo&r=ozUfXq8GhmyNFrTdmFFL6Q&m=ygwKpdM5j2hXyMFv3E4dOpEivd-ufm-TuRyj8a-utuM&s=QCQ5Bu4YIwWnuDKCV3RloA7ZqejnsrU2jtEk7Ma2oZE&e=

Climwin plots show little correlation, which is to be expected for BEPA (based on table above) but not JUNI and PIPO: [image]https://urldefense.proofpoint.com/v2/url?u=https-3A__user-2Dimages.githubusercontent.com_6355854_99256180-2D00d5c080-2D27e3-2D11eb-2D8ee2-2D5e5cf68db554.png&d=DwMCaQ&c=Cu5g146wZdoqVuKpTNsYHeFX_rg6kWhlkLF8Eft-wwo&r=ozUfXq8GhmyNFrTdmFFL6Q&m=ygwKpdM5j2hXyMFv3E4dOpEivd-ufm-TuRyj8a-utuM&s=29N47OvqjzlaqXrhzrnR0_LkTzhcY3skvFJspES6uDk&e=

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I'm not sure what to try next... Remove mid- PIPO? Or maybe the two sites need to be split, and just one included? (I'd hate to do that, but perhaps our assumption that they could be reasonably combined was wrong.)

@srusso2https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_srusso2&d=DwMCaQ&c=Cu5g146wZdoqVuKpTNsYHeFX_rg6kWhlkLF8Eft-wwo&r=ozUfXq8GhmyNFrTdmFFL6Q&m=ygwKpdM5j2hXyMFv3E4dOpEivd-ufm-TuRyj8a-utuM&s=8pUWoz8wZRltBarZgHkSJriKxljU1jKNZviXQl6MnFQ&e=, it would be great to hear any thoughts you may have on this.

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teixeirak commented 3 years ago

From conversation with @srusso2 , we wouldn't expect BEPA to be responding to the same variables as PIPO and JUVI, so it may make sense to just drop BEPA altogether.

I think it still makes sense to limit the analysis time frame such that it doesn't start until there are records for at least half the trees at a site. If that gives reasonable results, I personally think it's okay to keep both, but if not we should drop BEPA. (@ValentineHerr , it it's easy to code maybe try it both ways?)

teixeirak commented 3 years ago

I looked at the PRISM climate data, and it's fairly similar-- Niobrara tends to be slightly (~1C) warmer, but the two are highly correlated. Thus, I don't think that combining climate data is a problem. Obviously, the hydraulic setting is very different at the two sites, but our results won't be "wrong".

ValentineHerr commented 3 years ago

Should I do this only for the early years or also for the late years? And to make sure, for each site, I remove any year that has n_trees_that_year < max_n_trees /2, n_trees_that_year and max_n_trees beeing calculated regardless of species, correct?

teixeirak commented 3 years ago

Should I do this only for the early years or also for the late years?

We won't differentiate early and late years at this site. In cases where we do, this will only affect the early years.

teixeirak commented 3 years ago

And to make sure, for each site, I remove any year that has n_trees_that_year < max_n_trees /2, n_trees_that_year and max_n_trees beeing calculated regardless of species, correct?

correct.

teixeirak commented 3 years ago

Well, that change didn't do much to help NE, and made some undesirable changes at a couple other sites, so we'll want to revert that.

teixeirak commented 3 years ago

That changed the start date for both sites to 1946, and resulted in these results:

teixeirak commented 3 years ago

I'll have to come back to this later, but two thoughts:

1- We need to confirm that we're really removing the sparse PIPO. I don't know where those high growth rates are coming from... This might include needing to check our data script.

2- Assuming the data are all correct, we'll need to split the sites and include only one.

teixeirak commented 3 years ago

1- We need to confirm that we're really removing the sparse PIPO. I don't know where those high growth rates are coming from... This might include needing to check our data script.

I don't see any reason to suspect an error in the script. I've traced back the PIPOs with the highest growth rates to the original data sheet, and they are mid pine.

teixeirak commented 3 years ago

Besides splitting the sites, we might also try dropping PIPO mid-pine.

srusso2 commented 3 years ago

I would split the sites first and see what happens! Sabrina

From: Kristina Anderson-Teixeira notifications@github.com Sent: Tuesday, November 24, 2020 4:28 PM To: EcoClimLab/ForestGEO-climate-sensitivity ForestGEO-climate-sensitivity@noreply.github.com Cc: Sabrina Russo srusso2@unl.edu; Mention mention@noreply.github.com Subject: Re: [EcoClimLab/ForestGEO-climate-sensitivity] what's going on with NE? (#89)

Besides splitting the sites, we might also try dropping PIPO mid-pine.

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teixeirak commented 3 years ago

Arggg... NE is being tricky!

Analysis with just BEPA at Niobrara:

with CO2 (year would be similar):

and the climwin plots:

this doesn't really conflict with the original pub, but...

(I'll need to return to this later)

teixeirak commented 3 years ago

Analysis with just dense pine treatment at Halsey

with CO2 (as proxy for year):

These results are still weird. I think we need to see how it looks without BEPA.

teixeirak commented 3 years ago

Where this stands:

it's clear that the sites need to be separated (and one dropped)
If we drop Niobrara, we should (in theory!) get a pretty clear correlation with growing season climate. Downsides are that we have to extract / CRU data for Halsey (should be similar) and change some code to draw from a different repo (as it's not in the ForestGEO repo), and we lose the ForestGEO connection. (I'd only bother with the other data after seeing that Halsey works.)
Another option may be to "save" Niobrara results by adding in streamflow or PDSI, which in theory should be correlated well with growth. If we add streamflow, then it's just for this site. If we add PDSI to this site, we have to add it to all, which means lots of changing results. Either of these options requires some coding to handle another variable, and PDSI requires downloading data.

My current inclination would be to add streamflow to Niobrara, as that's the ForestGEO site. (In this case, @ValentineHerr , no need to do the run without BEPA.)

teixeirak commented 3 years ago

I loaded the Niobrar streamflow data here.

@ValentineHerr , let's make this the next (and hopefully last!) thing we try.

Specifically, we'll want to add streamflow ("SF") as a variable in the precipitation category (now "water"). Obviously we'll need to cut the analysis start date to the start of this record (1946). And, to make sure it's clear, this will be for just BEPA.

ValentineHerr commented 3 years ago

working on this now

ValentineHerr commented 3 years ago

Stream Flow was never picked up as best water candidate. (at least not in the regular analysis, have not run Year analysis)

teixeirak commented 3 years ago

at least not in the regular analysis, have not run Year analysis)

It shouldn't change, should it? Climwin variable selection should be the same for both, right?

ValentineHerr commented 3 years ago

oh yes, correct.

teixeirak commented 3 years ago

This site continues to be frustrating, and seems to be the one site that is not aligning all that well with the original pubs. Not sure what's going on....

teixeirak commented 3 years ago

Just some sanity checks:

climate data:

Niobrara coordinates are correct in our table and in the ForestGEO sites data spreadsheet used for CRU data extraction.
CRU and PRISM data for Niobrara is closely correlated
I haven't run a formal check of Niobrara and Hansley, but have done enough of a comparison to see that they're closely correlated.

cores data:

records in all_sites_cores.csv match Paper birch data_original.xlsx.
records in all_sites_cores.csv match nebraska_data_clean.xlsx

teixeirak commented 3 years ago

Niobrara

just climate

@ValentineHerr , one potentially important observation here: for WET, the lowest AIC is current May (open=4, close=4), but that's more of a spurious correlation: the 95% CI window is open=11, close=2. For the latter, there would be some sort of (probably weak) concave-up fit. I'm not sure what happens if that's selected-- maybe streamflow then becomes the best variable.

teixeirak commented 3 years ago

We've determined that we want to continue using the lowest AIC (#95), and that even if we were using windows based on the 95% confidence set, streamflow would not come out for Niobrara.

This post shows that if precipitation day frequency were excluded, streamflow would come out as the top water variable, but would remain a poor predictor and not come out significant in the GLS model.

teixeirak commented 3 years ago

more Niobrara results

(The results shown above for climate only are stable when DBH is included, and for any metric of growth.

with year:

(when year shows up in best model, climate response remains the same.)

My take-home on Niobrara:

I'm not sure why stream flow isn't coming out like it did in Bumann et al., although climwin is picking out the months (prev. Nov-Dec) where they found strongest correlation. Unfortunately, we don't have the bandwidth to sort out exactly what's going on there.
Niobrara's results are stable across models: negative response to previous June temperature (exactly consistent with Bumann et al), neg. response to May precip days.
The lack of precip. sensitivity might make sense: they probably have root access to groundwater, and may even benefit from the greater solar radiation that comes with less rain/ less cloud cover.
Growth has been declining through time (after size is accounted for), albeit not very strongly compared to some other sites. This would be consistent with Sabrina's observation that those populations are declining.

@srusso2 , what do you think? (I'm going to post next about Hansley, but I'm leaning towards including Niobrara. Hansley still isn't behaving all that well...)

teixeirak commented 3 years ago

Hansley

climwin output

climate only

climate + dbh

(I don't like the shape of the PIPO DBH response)

with year

There's a lot going on there, but basically a lot of these climate relationships look suspect to me. Given that we don't have bandwidth to dig into what's going on, and that Niobrara is the ForestGEO site, I'm inclined to just go with Niobrara.

teixeirak commented 3 years ago

@srusso2 , does this sound okay to you?

srusso2 commented 3 years ago

Krista, I am sorry but I am totally under a deadline to turn in my grades by Dec 11 and I am barely going to make it if I do make it at all. I literally have no time to look at this thoughtfully. Can it wait until Monday 14th? I am so sorry because I know you are trying to advance work on this… Sabrina

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teixeirak commented 3 years ago

No worries, I completely understand. Good luck with your grading!

teixeirak commented 3 years ago

@srusso2 , I'm about 95% sure I want to go with the Niobrara route and am assuming that as I write, but let me know in case you object.

teixeirak commented 3 years ago

I'm calling this decision final. We are removing Hansley (#103).

EcoClimLab / ForestGEO-tree-rings

what's going on with NE? #89

Analysis with just BEPA at Niobrara:

Analysis with just dense pine treatment at Halsey

Niobrara

just climate

more Niobrara results

with year:

Hansley

climwin output

climate only

climate + dbh

with year