Closed teixeirak closed 2 years ago
Yes good point maybe we don’t need to say the last sentence and keep the citation because the calculation for gross primary productivity might already consider light as a factor Let me know what you think as well Elsa
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On Feb 18, 2022, at 7:58 AM, Kristina Anderson-Teixeira @.***> wrote:
@NidhiVinod and @eoway , A minor issue in "Scaling in situ data with remote sensing" -- we present the Pau et al result but then seem to say we don't trust it. Can we edit this into a more consistent message, or just remove it if you don't think it's trustworthy?
As an example of the type of insight that can be gained from this approach, Pau et al. (2018) used data from a tower-based FLIR camera in combination with eddy-covariance data and found that tropical forest canopy temperatures were more strongly associated with GPP than T_air or VPD. However, the authors did not consider vertical light environment conditions even though light directly influences the deviation between canopy temperature and T_air.
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Yes, agreed on the revision suggestion!
Elsa Ordway, PhD Forest Ecosystems & Global Change Lab https://elsaordway.weebly.com/ Assistant Professor Department of Ecology and Evolutionary Biology https://www.eeb.ucla.edu/ UCLA Pronouns: she, her, hers
On Fri, Feb 18, 2022 at 8:05 AM Nidhi Vinod @.***> wrote:
Yes good point maybe we don’t need to say the last sentence and keep the citation because the calculation for gross primary productivity might already consider light as a factor Let me know what you think as well Elsa
Sent from my iPhone
On Feb 18, 2022, at 7:58 AM, Kristina Anderson-Teixeira @.***> wrote:
@NidhiVinod and @eoway , A minor issue in "Scaling in situ data with remote sensing" -- we present the Pau et al result but then seem to say we don't trust it. Can we edit this into a more consistent message, or just remove it if you don't think it's trustworthy?
As an example of the type of insight that can be gained from this approach, Pau et al. (2018) used data from a tower-based FLIR camera in combination with eddy-covariance data and found that tropical forest canopy temperatures were more strongly associated with GPP than T_air or VPD. However, the authors did not consider vertical light environment conditions even though light directly influences the deviation between canopy temperature and T_air.
— Reply to this email directly, view it on GitHub, or unsubscribe. You are receiving this because you were mentioned.
— Reply to this email directly, view it on GitHub https://github.com/EcoClimLab/vertical-thermal-review/issues/109#issuecomment-1044760002, or unsubscribe https://github.com/notifications/unsubscribe-auth/AFO3XWOMXGFOSFHNETRFNZLU3ZU4RANCNFSM5OYKU3PQ . Triage notifications on the go with GitHub Mobile for iOS https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675 or Android https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub.
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Thanks! I deleted that second sentence.
@NidhiVinod and @eoway , A minor issue in "Scaling in situ data with remote sensing" -- we present the Pau et al result but then seem to say we don't trust it. Can we edit this into a more consistent message, or just remove it if you don't think it's trustworthy?
As an example of the type of insight that can be gained from this approach, Pau et al. (2018) used data from a tower-based FLIR camera in combination with eddy-covariance data and found that tropical forest canopy temperatures were more strongly associated with GPP than T_air or VPD. However, the authors did not consider vertical light environment conditions even though light directly influences the deviation between canopy temperature and T_air.