Digital Screen Time and Pediatric Sleep: Evidence from a Preregistered Cohort Study. Andrew K. Przybylski. Journal of Pediatrics, https://doi.org/10.1016/j.jpeds.2018.09.054
Objectives: To determine the extent to which time spent with digital devices predicts meaningful variability in pediatric sleep.
Study design: Following a preregistered analysis plan, data from a sample of American children (n = 50 212) derived from the 2016 National Survey of Children's Health were analyzed. Models adjusted for child-, caregiver-, household-, and community-level covariates to estimate the potential effects of digital screen use.
Results: Each hour devoted to digital screens was associated with 3-8 fewer minutes of nightly sleep and significantly lower levels of sleep consistency. Furthermore, those children who complied with 2010 and 2016 American Academy of Pediatrics guidance on screen time limits reported between 20 and 26 more minutes, respectively, of nightly sleep. However, links between digital screen time and pediatric sleep outcomes were modest, accounting for less than 1.9% of observed variability in sleep outcomes.
Conclusions: Digital screen time, on its own, has little practical effect on pediatric sleep. Contextual factors surrounding screen time exert a more pronounced influence on pediatric sleep compared to screen time itself. These findings provide an empirically robust template for those investigating the digital displacement hypothesis as well as informing policy-making.
Keywords: digital displacement hypothesis, digital screens, pediatric sleep
Wednesday, November 7, 2018
High-level language processing regions are not engaged in action observation or imitation
High-level language processing regions are not engaged in action observation or imitation. Brianna L. Pritchett, Caitlyn Hoeflin, Kami Koldewyn, Eyal Dechter, and Evelina Fedorenko. Journal of Neurophysiology, https://doi.org/10.1152/jn.00222.2018
Abstract: A set of left frontal, temporal, and parietal brain regions respond robustly during language comprehension and production (e.g., Fedorenko E, Hsieh PJ, Nieto-Castañón A, Whitfield-Gabrieli S, Kanwisher N. J Neurophysiol 104: 1177–1194, 2010; Menenti L, Gierhan SM, Segaert K, Hagoort P. Psychol Sci 22: 1173–1182, 2011). These regions have been further shown to be selective for language relative to other cognitive processes, including arithmetic, aspects of executive function, and music perception (e.g., Fedorenko E, Behr MK, Kanwisher N. Proc Natl Acad Sci USA 108: 16428–16433, 2011; Monti MM, Osherson DN. Brain Res 1428: 33–42, 2012). However, one claim about overlap between language and nonlinguistic cognition remains prominent. In particular, some have argued that language processing shares computational demands with action observation and/or execution (e.g., Rizzolatti G, Arbib MA. Trends Neurosci 21: 188–194, 1998; Koechlin E, Jubault T. Neuron 50: 963–974, 2006; Tettamanti M, Weniger D. Cortex 42: 491–494, 2006). However, the evidence for these claims is indirect, based on observing activation for language and action tasks within the same broad anatomical areas (e.g., on the lateral surface of the left frontal lobe). To test whether language indeed shares machinery with action observation/execution, we examined the responses of language brain regions, defined functionally in each individual participant (Fedorenko E, Hsieh PJ, Nieto-Castañón A, Whitfield-Gabrieli S, Kanwisher N. J Neurophysiol 104: 1177–1194, 2010) to action observation (experiments 1, 2, and 3a) and action imitation (experiment 3b). With the exception of the language region in the angular gyrus, all language regions, including those in the inferior frontal gyrus (within “Broca’s area”), showed little or no response during action observation/imitation. These results add to the growing body of literature suggesting that high-level language regions are highly selective for language processing (see Fedorenko E, Varley R. Ann NY Acad Sci 1369: 132–153, 2016 for a review).
NEW & NOTEWORTHY: Many have argued for overlap in the machinery used to interpret language and others’ actions, either because action observation was a precursor to linguistic communication or because both require interpreting hierarchically-structured stimuli. However, existing evidence is indirect, relying on group analyses or reverse inference. We examined responses to action observation in language regions defined functionally in individual participants and found no response. Thus language comprehension and action observation recruit distinct circuits in the modern brain.
Abstract: A set of left frontal, temporal, and parietal brain regions respond robustly during language comprehension and production (e.g., Fedorenko E, Hsieh PJ, Nieto-Castañón A, Whitfield-Gabrieli S, Kanwisher N. J Neurophysiol 104: 1177–1194, 2010; Menenti L, Gierhan SM, Segaert K, Hagoort P. Psychol Sci 22: 1173–1182, 2011). These regions have been further shown to be selective for language relative to other cognitive processes, including arithmetic, aspects of executive function, and music perception (e.g., Fedorenko E, Behr MK, Kanwisher N. Proc Natl Acad Sci USA 108: 16428–16433, 2011; Monti MM, Osherson DN. Brain Res 1428: 33–42, 2012). However, one claim about overlap between language and nonlinguistic cognition remains prominent. In particular, some have argued that language processing shares computational demands with action observation and/or execution (e.g., Rizzolatti G, Arbib MA. Trends Neurosci 21: 188–194, 1998; Koechlin E, Jubault T. Neuron 50: 963–974, 2006; Tettamanti M, Weniger D. Cortex 42: 491–494, 2006). However, the evidence for these claims is indirect, based on observing activation for language and action tasks within the same broad anatomical areas (e.g., on the lateral surface of the left frontal lobe). To test whether language indeed shares machinery with action observation/execution, we examined the responses of language brain regions, defined functionally in each individual participant (Fedorenko E, Hsieh PJ, Nieto-Castañón A, Whitfield-Gabrieli S, Kanwisher N. J Neurophysiol 104: 1177–1194, 2010) to action observation (experiments 1, 2, and 3a) and action imitation (experiment 3b). With the exception of the language region in the angular gyrus, all language regions, including those in the inferior frontal gyrus (within “Broca’s area”), showed little or no response during action observation/imitation. These results add to the growing body of literature suggesting that high-level language regions are highly selective for language processing (see Fedorenko E, Varley R. Ann NY Acad Sci 1369: 132–153, 2016 for a review).
NEW & NOTEWORTHY: Many have argued for overlap in the machinery used to interpret language and others’ actions, either because action observation was a precursor to linguistic communication or because both require interpreting hierarchically-structured stimuli. However, existing evidence is indirect, relying on group analyses or reverse inference. We examined responses to action observation in language regions defined functionally in individual participants and found no response. Thus language comprehension and action observation recruit distinct circuits in the modern brain.
Bullying victimization may causally impact children’s wellbeing (not much) in the short-term, especially anxiety & depression levels; with time there is reduction of adverse effects, which highlights the potential for resilience
Schoeler, T., Duncan, L., Cecil, C., Ploubidis, G. B., & Pingault, J-B. (Accepted/In press in APA's Psychological Bulletin). Quasi-Experimental evidence on short and long-term consequences of bullying victimization: A meta-analysis. https://kclpure.kcl.ac.uk/portal/en/publications/quasiexperimental-evidence-on-short-and-longterm-consequences-of-bullying-victimization-a-metaanalysis(80472578-8c16-425f-ad79-61533a0b414f).html
Abstract: Exposure to bullying victimization is associated with a wide-range of short and long-term adverse outcomes. However, the extent to which these associations reflect a causal influence of bullying victimization remains disputed. Here, we aimed to provide the most stringent evidence regarding the consequences of bullying victimization by meta-analysing all relevant Quasi-Experimental (QE) studies. Multilevel random effects models and meta-regression were employed to (i) estimate the pooled QE-adjusted effect size (Cohen d) for bullying victimization on outcomes and to (ii) evaluate potential sources of heterogeneity. A total of 16 studies were included. We derived 101 QE-estimates from three different methods (twin design, fixed effects analysis, and propensity score matching) for three pools of outcomes (internalizing symptoms, externalizing symptoms, academic difficulties). QE-adjusted effects were small for internalizing symptoms (dadjusted=0.27, 95%CI 0.05;0.49), and smaller for externalizing symptoms (dadjusted=0.15, 95%CI 0.10;0.21) and academic difficulties (dadjusted=0.10, 95%CI 0.06; 0.13). Accounting for a shared rater effect between the exposure and the outcome further reduced the effect for internalizing (dnon-shared rater=0.14, 95%CI 0.05;0.23) and externalizing symptoms (dnon-shared rater=0.06, 95%CI 0.01;0.11). Finally, the adverse effects declined on the long-term, most markedly for internalizing symptoms (dlong-term=0.06, 95%CI -0.01;0.13). Based on the most stringent evidence available to date, findings indicate that bullying victimization may causally impact children’s wellbeing in the short-term, especially anxiety and depression levels. The reduction of adverse effects over time highlights the potential for resilience in individuals who have experienced bullying. Secondary preventive interventions in bullied children should therefore focus on modifiable factors that lead to resilience and address children's pre-existing vulnerabilities.
Abstract: Exposure to bullying victimization is associated with a wide-range of short and long-term adverse outcomes. However, the extent to which these associations reflect a causal influence of bullying victimization remains disputed. Here, we aimed to provide the most stringent evidence regarding the consequences of bullying victimization by meta-analysing all relevant Quasi-Experimental (QE) studies. Multilevel random effects models and meta-regression were employed to (i) estimate the pooled QE-adjusted effect size (Cohen d) for bullying victimization on outcomes and to (ii) evaluate potential sources of heterogeneity. A total of 16 studies were included. We derived 101 QE-estimates from three different methods (twin design, fixed effects analysis, and propensity score matching) for three pools of outcomes (internalizing symptoms, externalizing symptoms, academic difficulties). QE-adjusted effects were small for internalizing symptoms (dadjusted=0.27, 95%CI 0.05;0.49), and smaller for externalizing symptoms (dadjusted=0.15, 95%CI 0.10;0.21) and academic difficulties (dadjusted=0.10, 95%CI 0.06; 0.13). Accounting for a shared rater effect between the exposure and the outcome further reduced the effect for internalizing (dnon-shared rater=0.14, 95%CI 0.05;0.23) and externalizing symptoms (dnon-shared rater=0.06, 95%CI 0.01;0.11). Finally, the adverse effects declined on the long-term, most markedly for internalizing symptoms (dlong-term=0.06, 95%CI -0.01;0.13). Based on the most stringent evidence available to date, findings indicate that bullying victimization may causally impact children’s wellbeing in the short-term, especially anxiety and depression levels. The reduction of adverse effects over time highlights the potential for resilience in individuals who have experienced bullying. Secondary preventive interventions in bullied children should therefore focus on modifiable factors that lead to resilience and address children's pre-existing vulnerabilities.
A retrieval-specific mechanism of adaptive forgetting in the mammalian brain
A retrieval-specific mechanism of adaptive forgetting in the mammalian brain. Pedro Bekinschtein, Noelia V. Weisstaub, Francisco Gallo, Maria Renner & Michael C. Anderson. Nature Communications, volume 9, Article number: 4660 (2018). https://www.nature.com/articles/s41467-018-07128-7
Abstract: Forgetting is a ubiquitous phenomenon that is actively promoted in many species. How and whether organisms’ behavioral goals drive which memories are actively forgotten is unknown. Here we show that processes essential to controlling goal-directed behavior trigger active forgetting of distracting memories that interfere with behavioral goals. When rats need to retrieve particular memories to guide exploration, it reduces later retention of other memories encoded in that environment. As with humans, this retrieval-induced forgetting is competition-dependent, cue-independent and reliant on prefrontal control: Silencing the medial prefrontal cortex with muscimol abolishes the effect. cFos imaging reveals that prefrontal control demands decline over repeated retrievals as competing memories are forgotten successfully, revealing a key adaptive benefit of forgetting. Occurring in 88% of the rats studied, this finding establishes a robust model of how adaptive forgetting harmonizes memory with behavioral demands, permitting isolation of its circuit, cellular and molecular mechanisms.
Abstract: Forgetting is a ubiquitous phenomenon that is actively promoted in many species. How and whether organisms’ behavioral goals drive which memories are actively forgotten is unknown. Here we show that processes essential to controlling goal-directed behavior trigger active forgetting of distracting memories that interfere with behavioral goals. When rats need to retrieve particular memories to guide exploration, it reduces later retention of other memories encoded in that environment. As with humans, this retrieval-induced forgetting is competition-dependent, cue-independent and reliant on prefrontal control: Silencing the medial prefrontal cortex with muscimol abolishes the effect. cFos imaging reveals that prefrontal control demands decline over repeated retrievals as competing memories are forgotten successfully, revealing a key adaptive benefit of forgetting. Occurring in 88% of the rats studied, this finding establishes a robust model of how adaptive forgetting harmonizes memory with behavioral demands, permitting isolation of its circuit, cellular and molecular mechanisms.
A major problem with the Resplandy et al. ocean heat uptake paper: 23/25 is less than 1, not more
A major problem with the Resplandy et al. ocean heat uptake paper. Nicholas Lewis. Nov 7 2018. https://www.nicholaslewis.org/wp-content/uploads/2018/11/A-major-problem-with-the-Resplandy-et-al.-ocean-heat-uptake-paper.pdf
[Update Sep 26 2019: Paper was retracted at the journal's request. Check at the end.]
---
Excerpts:
It is amazing, uncertainty in page 1 is 0.15, then in page two is 0.18.
And 23.20/26 = 1.16 (?!?!?!).
Ten authors and at least two reviewers see nothing... Is there not a single journalist able to read the first page of a paper?
---
Notes:
1 Examples are: https://www.bbc.co.uk/news/science-environment-46046067 https://www.nytimes.com/2018/10/31/climate/ocean-temperatures-hotter.html https://www.washingtonpost.com/energy-environment/2018/10/31/startling-new-research-finds-large-buildup-heat-oceans-suggesting-faster-rate-global-warming/ https://www.scientificamerican.com/article/the-oceans-are-heating-up-faster-than-expected/ https://edition.cnn.com/2018/11/01/australia/ocean-warming-report-intl/index.html http://www.latimes.com/science/sciencenow/la-sci-sn-oceans-study-climate-change-20181031-story.html https://www.usatoday.com/story/news/nation-now/2018/11/01/oceans-more-heat-study-global-warming-climate-change-nature/1843074002/ https://www.independent.co.uk/environment/climate-change-global-warming-ocean-temperature-heat-fossil-fuels-science-research-a8612796.html
2 Examples are: http://www.realclimate.org/index.php/archives/2018/11/unforced-variations-nov-2018/ https://wattsupwiththat.com/2018/11/02/friday-funny-at-long-last-kevin-trenberths-missing-heat-may-have-been-found-repeat-may-have-been/ https://bskiesresearch.wordpress.com/2018/11/01/that-new-ocean-heat-content-estimate/ https://andthentheresphysics.wordpress.com/2018/11/03/new-ocean-heat-content-analysis/ https://twitter.com/Knutti_ETH/status/1057960390502608901
3 L. Resplandy, R. F. Keeling, Y. Eddebbar, M. K. Brooks, R. Wang, L. Bopp, M. C. Long, J. P. Dunne, W. Koeve & A. Oschlies, 2018: Quantification of ocean heat uptake from changes in atmospheric O2 and CO2 composition. Nature, 563, 105-108. https://doi.org/10.1038/s41586-018-0651-8 ("Resplandy et al.")
4 A value of 13.3 zetta Joules (ZJ) per year, or 0.83 Watts per square metre of the Earth's surface. ZJ is the symbol for zetta Joules; 1 ZJ = 1021 J. 1 ZJ per year = 0.0621 Watts per square metre (W/m2 or Wm–2) of the Earth's surface.
5 http://web.archive.org/web/20181103021900/https://www.princeton.edu/news/2018/11/01/earths-oceans-have-absorbed-60-percent-more-heat-year-previously-thought
6 However that is in comparison with an IPCC estimate for 1993–2010; estimates for 1991–2016 are higher.
7 ΔAPO is the change in 'atmospheric potential oxygen', the overall level of which has been observationally measured since 1991 (ΔAPOOBS). It is the sum of the atmospheric concentrations of O2 and of CO2 weighted respectively 1⤬ and 1.1⤬.
8 The authors break the observed change in ΔAPOOBS into four components, ΔAPOFF, ΔAPOCant, ΔAPOAtmD and ΔAPOClimate, deriving the last component (which is related to ocean warming) by deducting estimates of the other three components from ΔAPOOBS. ΔAPOFF is the decrease in APO caused by industrial processes (fossil-fuel burning and cement production). ΔAPOCant accounts for the oceanic uptake of excess anthropogenic atmospheric CO2. ΔAPOAtmD accounts for air–sea exchanges driven by ocean fertilization from anthropogenic aerosol deposition.
9 1 per meg literally means 1 part per million (1 ppm), however 'per meg' and 'ppm' are defined differently in relation to atmospheric concentrations and are not identical units.
10 The same data is available in Excel format from a link on Nature's website, as "Source Data Fig. 2".
11 Dividing by their conversion factor of 0.087 ± 0.003 per meg per ZJ. ZJ is the symbol for zetta Joules; 1 ZJ = 1021 Joules.
12 I used ordinary least squares (OLS) regression with an intercept. That is the standard form of least squares regression for estimating a trend. Resplandy et al. show all APO variables as changes from a baseline of zero in 1991, but that is an arbitrary choice and would not justify forcing the regression fit to be zero in 1991 (by not using an intercept term). Doing so would not in any event raise the ΔAPOClimate estimated trend to the level given by Resplandy et al.
13 I took a large number of sets of samples for each of the years 1991 to 2016 from the applicable error distributions of ΔAPOOBS, ΔAPOFF, ΔAPOCant, and ΔAPOAtmD given in Extended Data Table 4, and calculated all the corresponding sample values of ΔAPOClimate using equation (1). I then computed the ordinary least squares linear trend for each set of 1991–2016 sampled values of ΔAPOClimate, and calculated the mean and standard deviation of the trends.
14 Laure Resplandy was responsible for directing the analysis of the datasets and models.
15 This fact was spotted by Frank Bosse, with whom I discussed the apparent error in the Resplandy et al. ΔAPOClimate trend.
16 All uncertainty values in the paper are ± 1 sigma (1 standard deviation). Errors are presumably assumed to be Normally distributed, as no other distributions are specified.
17 The statement in their Methods that "ΔCant′ cannot be derived from observations and was estimated at 0.05 Pg C yr−1, equivalent to a trend of +0.2 per meg−1, using model simulations" is presumably also a typographical error. The correct value appears to be +0.12 per meg yr−1, as stated elsewhere in Methods and in Extended Data Table 3.
18 On that basis , I can replicate the Extended Data Table 4 ΔAPOOBS uncertainty time series values within ±0.1. Note that all the values in that table, although given to two decimal places, appear to be rounded to one decimal place.
19 The overall uncertainties given in Table 3 in Resplandy et al.'s source paper for its errors in ΔAPOOBS support my analysis.
20 When using the Resplandy et al. Extended Data Table 4 ΔAPOClimate total uncertainty time series and assuming that each year's errors are independent, despite the trend and scale systematic errors being their largest component, the estimated ΔAPOClimate uncertainty reduces to between ± 0.20 and ± 0.21 per meg yr−1. That is still slightly higher than the ± 0.15 and ± 0.18 per meg yr−1 values given in the paper. The reason for the small remaining difference is unclear.
21 It seems likely that the same non-independence over time issue largely or wholly applies to errors in ΔAPOCant, ΔAPOAtmD and probably ΔAPOFF. If the errors in ΔAPOCant and ΔAPOAtmD (but not in ΔAPOFF)
were also treated as perfectly correlated between years, the ΔAPOClimate trend uncertainty would be ± 0.60 per meg yr−1.
22 Lewis, N., and Curry, J., 2018: The impact of recent forcing and ocean heat uptake data on estimates of climate sensitivity. J. Climate, 31(15), 6051-6071.
23 Even if the 2007–2016 ocean heat uptake estimate used in Lewis and Curry (2018) were increased by 3 ZJ yr−1 to match Resplandy et al.'s (incorrect) estimate for 1991–2016, the 1.05°C 5% lower bound of its HadCRUT4v5-based estimate of effective/equilibrium climate sensitivity would only increase to 1.15°C. Moreover, Resplandy et al.'s ΔAPOClimate data imply have a lower ocean heat uptake estimate for 2007–2016 than they do for 1991–2016.
24 See the IPCC's 2018 Special Report on Global Warming of 1.5°C
---
Update Sep 26 2019: Paper was retracted at the journal's request.
[Update Sep 26 2019: Paper was retracted at the journal's request. Check at the end.]
---
Excerpts:
On November 1st there was extensive coverage in the mainstream media1 and online2 of a paper just published in the prestigious journal Nature. The article,3 by Laure Resplandy of Princeton University, Ralph Keeling of the Scripps Institute of Oceanography and eight other authors, used a novel method to estimate heat uptake by the ocean over the period 1991–2016 and came up with an atypically high value.4 The press release 5 accompanying the Resplandy et al. paper was entitled "Earth's oceans have absorbed 60 percent more heat per year than previously thought",6 and said that this suggested that Earth is more sensitive to fossil-fuel emissions than previously thought.
I was asked for my thoughts on the Resplandy paper as soon as it obtained media coverage. Most commentators appear to have been content to rely on what was said in the press release. However, being a scientist, I thought it appropriate to read the paper itself, and if possible look at its data, before forming a view.
Trend estimates
The method used by Resplandy et al. was novel, and certainly worthy of publication. The authors start with observed changes in 'atmospheric potential oxygen' (ΔAPOOBS).7 In their model, one component of this change (ΔAPOClimate) is due to warming of the oceans, and they derived an estimate of its value by calculating values for the other components.8 A simple conversion factor then allows them to convert the trend in ΔAPOClimate into an estimate of ocean heat uptake (the trend in ocean heat content).
On page 1 they say:
From equation (1), we thereby find that ΔAPOClimate = 23.20 ± 12.20 per meg, corresponding to a least squares linear trend of +1.16 ± 0.15 per meg per year 9
A quick bit of mental arithmetic indicated that a change of 23.2 between 1991 and 2016 represented an annual rate of approximately 0.9, well below their 1.16 value. As that seemed surprising, I extracted the annual ΔAPO best-estimate values and uncertainties from the paper's Extended Data Table 410 and computed the 1991–2016 least squares linear fit trend in the ΔAPOClimate values. The trend was 0.88, not 1.16, per meg per year, implying an ocean heat uptake estimate of 10.1 ZJ per year,11 well below the estimate in the paper of 13.3 ZJ per year.12
Resplandy et al. derive ΔAPOClimate from estimates of ΔAPOOBS and of its other components, ΔAPOFF, ΔAPOCant, and ΔAPOAtmD, using – rearranging their equation (1):
ΔAPOClimate = ΔAPOOBS − ΔAPOFF − ΔAPOCant − ΔAPOAtmD
I derived the same best estimate trend when I allowed for uncertainty in each of the components of ΔAPOOBS, in the way that Resplandy et al.'s Methods description appears to indicate,13 so my simple initial method of trend estimation does not explain the discrepancy.
[...]
I wanted to make sure that I had not overlooked something in my calculations, so later on November 1st I emailed Laure Resplandy querying the ΔAPOClimate trend figure in her paper and asking for her to look into the difference in our trend estimates as a matter of urgency, explaining that in view of the media coverage of the paper I was contemplating web-publishing a comment on it within a matter of days. To date I have had no substantive response from her, despite subsequently sending a further email containing the key analysis sections from a draft of this article.
[...]
Uncertainty analysis
I now turn to the uncertainty analysis in the paper.16 Strangely, the Resplandy et al. paper has two different values for the uncertainty in the results. On page 1 they give the ΔAPOClimate trend (in per meg per year) as 1.16 ± 0.15. But on page 2 they say it is 1.16 ± 0.18. In the Methods section they go back to 1.16 ± 0.15. Probably the ± 0.18 figure is a typographical error. 17
It is amazing, uncertainty in page 1 is 0.15, then in page two is 0.18.
And 23.20/26 = 1.16 (?!?!?!).
Ten authors and at least two reviewers see nothing... Is there not a single journalist able to read the first page of a paper?
---
Notes:
1 Examples are: https://www.bbc.co.uk/news/science-environment-46046067 https://www.nytimes.com/2018/10/31/climate/ocean-temperatures-hotter.html https://www.washingtonpost.com/energy-environment/2018/10/31/startling-new-research-finds-large-buildup-heat-oceans-suggesting-faster-rate-global-warming/ https://www.scientificamerican.com/article/the-oceans-are-heating-up-faster-than-expected/ https://edition.cnn.com/2018/11/01/australia/ocean-warming-report-intl/index.html http://www.latimes.com/science/sciencenow/la-sci-sn-oceans-study-climate-change-20181031-story.html https://www.usatoday.com/story/news/nation-now/2018/11/01/oceans-more-heat-study-global-warming-climate-change-nature/1843074002/ https://www.independent.co.uk/environment/climate-change-global-warming-ocean-temperature-heat-fossil-fuels-science-research-a8612796.html
2 Examples are: http://www.realclimate.org/index.php/archives/2018/11/unforced-variations-nov-2018/ https://wattsupwiththat.com/2018/11/02/friday-funny-at-long-last-kevin-trenberths-missing-heat-may-have-been-found-repeat-may-have-been/ https://bskiesresearch.wordpress.com/2018/11/01/that-new-ocean-heat-content-estimate/ https://andthentheresphysics.wordpress.com/2018/11/03/new-ocean-heat-content-analysis/ https://twitter.com/Knutti_ETH/status/1057960390502608901
3 L. Resplandy, R. F. Keeling, Y. Eddebbar, M. K. Brooks, R. Wang, L. Bopp, M. C. Long, J. P. Dunne, W. Koeve & A. Oschlies, 2018: Quantification of ocean heat uptake from changes in atmospheric O2 and CO2 composition. Nature, 563, 105-108. https://doi.org/10.1038/s41586-018-0651-8 ("Resplandy et al.")
4 A value of 13.3 zetta Joules (ZJ) per year, or 0.83 Watts per square metre of the Earth's surface. ZJ is the symbol for zetta Joules; 1 ZJ = 1021 J. 1 ZJ per year = 0.0621 Watts per square metre (W/m2 or Wm–2) of the Earth's surface.
5 http://web.archive.org/web/20181103021900/https://www.princeton.edu/news/2018/11/01/earths-oceans-have-absorbed-60-percent-more-heat-year-previously-thought
6 However that is in comparison with an IPCC estimate for 1993–2010; estimates for 1991–2016 are higher.
7 ΔAPO is the change in 'atmospheric potential oxygen', the overall level of which has been observationally measured since 1991 (ΔAPOOBS). It is the sum of the atmospheric concentrations of O2 and of CO2 weighted respectively 1⤬ and 1.1⤬.
8 The authors break the observed change in ΔAPOOBS into four components, ΔAPOFF, ΔAPOCant, ΔAPOAtmD and ΔAPOClimate, deriving the last component (which is related to ocean warming) by deducting estimates of the other three components from ΔAPOOBS. ΔAPOFF is the decrease in APO caused by industrial processes (fossil-fuel burning and cement production). ΔAPOCant accounts for the oceanic uptake of excess anthropogenic atmospheric CO2. ΔAPOAtmD accounts for air–sea exchanges driven by ocean fertilization from anthropogenic aerosol deposition.
9 1 per meg literally means 1 part per million (1 ppm), however 'per meg' and 'ppm' are defined differently in relation to atmospheric concentrations and are not identical units.
10 The same data is available in Excel format from a link on Nature's website, as "Source Data Fig. 2".
11 Dividing by their conversion factor of 0.087 ± 0.003 per meg per ZJ. ZJ is the symbol for zetta Joules; 1 ZJ = 1021 Joules.
12 I used ordinary least squares (OLS) regression with an intercept. That is the standard form of least squares regression for estimating a trend. Resplandy et al. show all APO variables as changes from a baseline of zero in 1991, but that is an arbitrary choice and would not justify forcing the regression fit to be zero in 1991 (by not using an intercept term). Doing so would not in any event raise the ΔAPOClimate estimated trend to the level given by Resplandy et al.
13 I took a large number of sets of samples for each of the years 1991 to 2016 from the applicable error distributions of ΔAPOOBS, ΔAPOFF, ΔAPOCant, and ΔAPOAtmD given in Extended Data Table 4, and calculated all the corresponding sample values of ΔAPOClimate using equation (1). I then computed the ordinary least squares linear trend for each set of 1991–2016 sampled values of ΔAPOClimate, and calculated the mean and standard deviation of the trends.
14 Laure Resplandy was responsible for directing the analysis of the datasets and models.
15 This fact was spotted by Frank Bosse, with whom I discussed the apparent error in the Resplandy et al. ΔAPOClimate trend.
16 All uncertainty values in the paper are ± 1 sigma (1 standard deviation). Errors are presumably assumed to be Normally distributed, as no other distributions are specified.
17 The statement in their Methods that "ΔCant′ cannot be derived from observations and was estimated at 0.05 Pg C yr−1, equivalent to a trend of +0.2 per meg−1, using model simulations" is presumably also a typographical error. The correct value appears to be +0.12 per meg yr−1, as stated elsewhere in Methods and in Extended Data Table 3.
18 On that basis , I can replicate the Extended Data Table 4 ΔAPOOBS uncertainty time series values within ±0.1. Note that all the values in that table, although given to two decimal places, appear to be rounded to one decimal place.
19 The overall uncertainties given in Table 3 in Resplandy et al.'s source paper for its errors in ΔAPOOBS support my analysis.
20 When using the Resplandy et al. Extended Data Table 4 ΔAPOClimate total uncertainty time series and assuming that each year's errors are independent, despite the trend and scale systematic errors being their largest component, the estimated ΔAPOClimate uncertainty reduces to between ± 0.20 and ± 0.21 per meg yr−1. That is still slightly higher than the ± 0.15 and ± 0.18 per meg yr−1 values given in the paper. The reason for the small remaining difference is unclear.
21 It seems likely that the same non-independence over time issue largely or wholly applies to errors in ΔAPOCant, ΔAPOAtmD and probably ΔAPOFF. If the errors in ΔAPOCant and ΔAPOAtmD (but not in ΔAPOFF)
were also treated as perfectly correlated between years, the ΔAPOClimate trend uncertainty would be ± 0.60 per meg yr−1.
22 Lewis, N., and Curry, J., 2018: The impact of recent forcing and ocean heat uptake data on estimates of climate sensitivity. J. Climate, 31(15), 6051-6071.
23 Even if the 2007–2016 ocean heat uptake estimate used in Lewis and Curry (2018) were increased by 3 ZJ yr−1 to match Resplandy et al.'s (incorrect) estimate for 1991–2016, the 1.05°C 5% lower bound of its HadCRUT4v5-based estimate of effective/equilibrium climate sensitivity would only increase to 1.15°C. Moreover, Resplandy et al.'s ΔAPOClimate data imply have a lower ocean heat uptake estimate for 2007–2016 than they do for 1991–2016.
24 See the IPCC's 2018 Special Report on Global Warming of 1.5°C
---
Update Sep 26 2019: Paper was retracted at the journal's request.
Retraction Note: Quantification of ocean heat uptake from changes in atmospheric O2 and CO2 composition. L. Resplandy et al. Nature 573, 614 (2019). https://www.nature.com/articles/s41586-019-1585-5
State AGs for Rent: Privately funded litigators wield state police power
State AGs for Rent: Privately funded litigators wield state police power. Wall Street Journal, Nov 7 2018. https://www.wsj.com/articles/state-ags-for-rent-1541549567
With the courts and Trump Administration rolling back federal climate regulation, green activists have turned to the states. But there’s a troubling ethical twist: Instead of merely lobbying, activists are placing employees in Attorneys General offices in dubious private-public condominiums.
Consider a remarkable arrangement brokered by the NYU Law School’s State Energy and Environmental Impact Center to fund legal services for state AGs. The group was launched in August 2017 to advance a liberal climate and energy agenda, courtesy of a $6 million grant from Bloomberg Philanthropies, which also financed the Sierra Club’s Beyond Coal campaign.
In August 2017 the NYU outfit emailed then-New York Attorney General Eric Schneiderman’s office, offering to cover the salary and benefits of “special assistant attorneys general,” pending an application from the office that demonstrated how the new attorneys would be used. These privately funded staffers would work out of an AG’s office for two years and deliver quarterly progress reports to the State Energy and Environmental Impact Center.
Those progress reports would explain “the contribution that the legal fellow has made to the clean energy, climate change, and environmental initiatives” within the attorney general’s office, according to a December 2017 draft of an agreement between the Center and the New York AG obtained by Chris Horner of the Competitive Enterprise Institute.
Attorneys General do sometimes bring on legal fellows or outside help to handle unique cases. But subject-matter experts aren’t in-house or chosen with specific intent to promote specific policies, according to Randy Pepple, who was chief of staff for former Washington Republican AG Rob McKenna. In the New York case, a special interest is funding staffers who could wield state law-enforcement power to punish opponents.
The State Energy and Environmental Impact Center made clear that state AG offices would only qualify for special assistant AGs if they “demonstrate a need and commitment to defending environmental values and advancing progressive clean energy, climate change, and environmental legal positions,” according to the August 2017 email to numerous AGs. Mr. Schneiderman’s office suggested in its application for the fellows that it “needs additional attorney resources to assist” in extracting compensation from fossil-fuel emitters.
That’s exactly what’s happening. The New York AG currently has two NYU fellows on staff, according to the State Energy and Environmental Impact Center.
One of the fellows, Gavin McCabe, signed off as “special assistant attorney general” on an amicus brief in June in support of New York City’s suit for damages against BP, Chevron , ConocoPhillips , Exxon Mobil , and Royal Dutch Shell for alleged climate sins. That case was thrown out in July by federal Judge John Kennan on grounds that problems arising from climate change “are not for the judiciary to ameliorate.”
The other, Matthew Eisenson, signed New York state’s suit filed last month against Exxon for allegedly misleading investors about the risks that climate-change regulations pose to its business. The free help will also make for welcome reinforcements in New York-led litigation against the Trump Administration, including a suit against the EPA for its methane regulation.
A lack of government transparency makes this arrangement especially troubling. The New York AG’s office, now run by Acting AG Barbara Underwood, declined to comment. Mr. McCabe and Mr. Eisenson could not be reached for comment by our deadline.
The State Energy and Environmental Impact Center said in a statement that the state offices it works with “has the authority consistent with applicable law and regulations to accept a Legal Fellow whose salary and benefits are provided by an outside funding source.” It added that it places workers with AGs who already have a long history of advancing the center’s energy priorities. “The work that NYU law fellows perform is directed by those AGs and not by the Center,” the Center said.
At least six state AG offices have already brought on board a special assistant attorney general, according to an August report by Mr. Horner. Besides New York, the jurisdictions include Maryland, Massachusetts, Oregon, Washington and the District of Columbia. In September, Mr. Horner learned that Illinois and New Mexico have brought on special assistant AGs as well, which was confirmed by the NYU outfit.
The ethical problems here should be obvious. Private interests are leveraging the police powers of the state to pursue their political agenda, while a government official is letting private interests appear to influence enforcement decisions. None of this is reassuring about the fair administration of justice.
With the courts and Trump Administration rolling back federal climate regulation, green activists have turned to the states. But there’s a troubling ethical twist: Instead of merely lobbying, activists are placing employees in Attorneys General offices in dubious private-public condominiums.
Consider a remarkable arrangement brokered by the NYU Law School’s State Energy and Environmental Impact Center to fund legal services for state AGs. The group was launched in August 2017 to advance a liberal climate and energy agenda, courtesy of a $6 million grant from Bloomberg Philanthropies, which also financed the Sierra Club’s Beyond Coal campaign.
In August 2017 the NYU outfit emailed then-New York Attorney General Eric Schneiderman’s office, offering to cover the salary and benefits of “special assistant attorneys general,” pending an application from the office that demonstrated how the new attorneys would be used. These privately funded staffers would work out of an AG’s office for two years and deliver quarterly progress reports to the State Energy and Environmental Impact Center.
Those progress reports would explain “the contribution that the legal fellow has made to the clean energy, climate change, and environmental initiatives” within the attorney general’s office, according to a December 2017 draft of an agreement between the Center and the New York AG obtained by Chris Horner of the Competitive Enterprise Institute.
Attorneys General do sometimes bring on legal fellows or outside help to handle unique cases. But subject-matter experts aren’t in-house or chosen with specific intent to promote specific policies, according to Randy Pepple, who was chief of staff for former Washington Republican AG Rob McKenna. In the New York case, a special interest is funding staffers who could wield state law-enforcement power to punish opponents.
The State Energy and Environmental Impact Center made clear that state AG offices would only qualify for special assistant AGs if they “demonstrate a need and commitment to defending environmental values and advancing progressive clean energy, climate change, and environmental legal positions,” according to the August 2017 email to numerous AGs. Mr. Schneiderman’s office suggested in its application for the fellows that it “needs additional attorney resources to assist” in extracting compensation from fossil-fuel emitters.
That’s exactly what’s happening. The New York AG currently has two NYU fellows on staff, according to the State Energy and Environmental Impact Center.
One of the fellows, Gavin McCabe, signed off as “special assistant attorney general” on an amicus brief in June in support of New York City’s suit for damages against BP, Chevron , ConocoPhillips , Exxon Mobil , and Royal Dutch Shell for alleged climate sins. That case was thrown out in July by federal Judge John Kennan on grounds that problems arising from climate change “are not for the judiciary to ameliorate.”
The other, Matthew Eisenson, signed New York state’s suit filed last month against Exxon for allegedly misleading investors about the risks that climate-change regulations pose to its business. The free help will also make for welcome reinforcements in New York-led litigation against the Trump Administration, including a suit against the EPA for its methane regulation.
A lack of government transparency makes this arrangement especially troubling. The New York AG’s office, now run by Acting AG Barbara Underwood, declined to comment. Mr. McCabe and Mr. Eisenson could not be reached for comment by our deadline.
The State Energy and Environmental Impact Center said in a statement that the state offices it works with “has the authority consistent with applicable law and regulations to accept a Legal Fellow whose salary and benefits are provided by an outside funding source.” It added that it places workers with AGs who already have a long history of advancing the center’s energy priorities. “The work that NYU law fellows perform is directed by those AGs and not by the Center,” the Center said.
At least six state AG offices have already brought on board a special assistant attorney general, according to an August report by Mr. Horner. Besides New York, the jurisdictions include Maryland, Massachusetts, Oregon, Washington and the District of Columbia. In September, Mr. Horner learned that Illinois and New Mexico have brought on special assistant AGs as well, which was confirmed by the NYU outfit.
The ethical problems here should be obvious. Private interests are leveraging the police powers of the state to pursue their political agenda, while a government official is letting private interests appear to influence enforcement decisions. None of this is reassuring about the fair administration of justice.
Successful social interaction is critically dependent on a core set of highly connected hubs that dynamically accumulate & integrate complex social information & facilitate social tuning
How Dynamic Brain Networks Tune Social Behavior in Real Time. Brian Silston, Danielle S. Bassett, Dean Mobbs. Current Directions in Psychological Science, https://doi.org/10.1177/0963721418773362
Abstract: During social interaction, the brain has the enormous task of interpreting signals that are fleeting, subtle, contextual, abstract, and often ambiguous. Despite the signal complexity, the human brain has evolved to be highly successful in the social landscape. Here, we propose that the human brain makes sense of noisy dynamic signals through accumulation, integration, and prediction, resulting in a coherent representation of the social world. We propose that successful social interaction is critically dependent on a core set of highly connected hubs that dynamically accumulate and integrate complex social information and, in doing so, facilitate social tuning during moment-to-moment social discourse. Successful interactions, therefore, require adaptive flexibility generated by neural circuits composed of highly integrated hubs that coordinate context-appropriate responses. Adaptive properties of the neural substrate, including predictive and adaptive coding, and neural reuse, along with perceptual, inferential, and motivational inputs, provide the ingredients for pliable, hierarchical predictive models that guide our social interactions.
Keywords: dynamic-integration theory, adaptive flexibility, temporal dynamics, social interaction, prediction
Abstract: During social interaction, the brain has the enormous task of interpreting signals that are fleeting, subtle, contextual, abstract, and often ambiguous. Despite the signal complexity, the human brain has evolved to be highly successful in the social landscape. Here, we propose that the human brain makes sense of noisy dynamic signals through accumulation, integration, and prediction, resulting in a coherent representation of the social world. We propose that successful social interaction is critically dependent on a core set of highly connected hubs that dynamically accumulate and integrate complex social information and, in doing so, facilitate social tuning during moment-to-moment social discourse. Successful interactions, therefore, require adaptive flexibility generated by neural circuits composed of highly integrated hubs that coordinate context-appropriate responses. Adaptive properties of the neural substrate, including predictive and adaptive coding, and neural reuse, along with perceptual, inferential, and motivational inputs, provide the ingredients for pliable, hierarchical predictive models that guide our social interactions.
Keywords: dynamic-integration theory, adaptive flexibility, temporal dynamics, social interaction, prediction
Uncovering the Neuroanatomy of Core Language Systems Using Lesion-Symptom Mapping
Uncovering the Neuroanatomy of Core Language Systems Using Lesion-Symptom Mapping. Daniel Mirman, Melissa Thye. Current Directions in Psychological Science, https://doi.org/10.1177/0963721418787486
Abstract: Recent studies have integrated noninvasive brain-imaging methods and advanced analysis techniques to study associations between the location of brain damage and cognitive deficits. By applying data-driven analysis methods to large sets of data on language deficits after stroke (aphasia), these studies have identified the cognitive systems that support language processing—phonology, semantics, fluency, and executive functioning—and their neural basis. Phonological processing is supported by dual pathways around the Sylvian fissure, a ventral speech-recognition component and a dorsal speech-production component; fluent sentence-level speech production relies on a more anterior frontal component, and the semantic system relies on a hub in the anterior temporal lobe and frontotemporal white-matter tracts. The executive function system was less consistently localized, possibly because of the kinds of brain damage tested in these studies. This review synthesizes the results of these studies, showing how they converge with contemporary models of primary systems that support perception, action, and conceptual knowledge across domains, and highlights some divergent findings and directions for future research.
Keywords: language, speech, aphasia, neuroimaging, neuropsychology
Abstract: Recent studies have integrated noninvasive brain-imaging methods and advanced analysis techniques to study associations between the location of brain damage and cognitive deficits. By applying data-driven analysis methods to large sets of data on language deficits after stroke (aphasia), these studies have identified the cognitive systems that support language processing—phonology, semantics, fluency, and executive functioning—and their neural basis. Phonological processing is supported by dual pathways around the Sylvian fissure, a ventral speech-recognition component and a dorsal speech-production component; fluent sentence-level speech production relies on a more anterior frontal component, and the semantic system relies on a hub in the anterior temporal lobe and frontotemporal white-matter tracts. The executive function system was less consistently localized, possibly because of the kinds of brain damage tested in these studies. This review synthesizes the results of these studies, showing how they converge with contemporary models of primary systems that support perception, action, and conceptual knowledge across domains, and highlights some divergent findings and directions for future research.
Keywords: language, speech, aphasia, neuroimaging, neuropsychology
We are now looking more closely at the conditions in which we fail to judge time accurately & why, with the aim of testing the limits of a potential internal clock & time distortions (i.e., caused by emotion)
Intertwined Facets of Subjective Time. Sylvie Droit-Volet. Current Directions in Psychological Science, https://doi.org/10.1177/0963721418779978
Abstract: For decades, researchers in the behavioral sciences have studied how humans judge time accurately. Now they are looking more closely at the conditions in which they fail to do so and why, with the aim of testing the limits of a potential internal timing system (i.e., an internal clock). Recent behavioral studies have thus focused on time distortions, in particular those caused by emotion. They have also begun to examine the awareness of the passage of time and its relation with the perception of durations in different temporal ranges, from a few seconds to several minutes.
Keywords: timing, time, emotion, self, awareness
Abstract: For decades, researchers in the behavioral sciences have studied how humans judge time accurately. Now they are looking more closely at the conditions in which they fail to do so and why, with the aim of testing the limits of a potential internal timing system (i.e., an internal clock). Recent behavioral studies have thus focused on time distortions, in particular those caused by emotion. They have also begun to examine the awareness of the passage of time and its relation with the perception of durations in different temporal ranges, from a few seconds to several minutes.
Keywords: timing, time, emotion, self, awareness
Children's drawing ability is more strongly determined by genes than by the family environment or deliberate practice
Drawing as a Window Onto Expertise. Rebecca Chamberlain. Current Directions in Psychological Science, https://doi.org/10.1177/0963721418797301
Abstract: The ability to draw is a uniquely human activity, ubiquitous in childhood but seldom performed at expert levels in adulthood. Relative to other domains of expertise (chess, music, sport), drawing is understudied, and yet because it is a universal developmental ability mastered by so few, it provides an ideal test bed for competing theories of expertise. In this review, three strands of active research and debate in the field of expertise will be considered in relation to representational drawing ability: (a) the characterization of expertise in relation to altered visual attention and memory, (b) the relative roles of personality traits and cognitive abilities, and (c) the interaction between genes and environment in the development of expertise. The study of representational drawing sheds new light on these three strands and provides rich avenues for further research in this domain.
Keywords: expertise, drawing, individual differences, attention, visual memory
Abstract: The ability to draw is a uniquely human activity, ubiquitous in childhood but seldom performed at expert levels in adulthood. Relative to other domains of expertise (chess, music, sport), drawing is understudied, and yet because it is a universal developmental ability mastered by so few, it provides an ideal test bed for competing theories of expertise. In this review, three strands of active research and debate in the field of expertise will be considered in relation to representational drawing ability: (a) the characterization of expertise in relation to altered visual attention and memory, (b) the relative roles of personality traits and cognitive abilities, and (c) the interaction between genes and environment in the development of expertise. The study of representational drawing sheds new light on these three strands and provides rich avenues for further research in this domain.
Keywords: expertise, drawing, individual differences, attention, visual memory
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