dataesr/scientific-paragraphs-categorization huggingface dataset:
At the end of the year, the model sums all the daily carbon inputs allocated to the stem to get an annual tree-growth increment (yearly Dstem, hereafter Dstem, in grams of carbon per square metre of stand per year). Dstem is assumed to be proportional to tree-ring growth so that we can build simulated tree-ring index time series and compare it with tree-ring width (hereafter TRW) observations (Sect. 2. 3. 1) (Gea-Izquierdo et al. , 2015; Gennaretti et al. , 2017). The structure of the MAIDEN model is provided online (https://figshare. com/articles/ MAIDEN_ecophysiological_forest_model/5446435/1, last access: 17 November 2019;  Gennaretti, 2017) , and its modules are available upon request. Tree-ring observation site and climate station (corresponding to a single location or grid cell as a function of the climatic dataset) constants of the MAIDEN model (Table  S1 ) are derived from observations, as far as possible.
For practical reasons, we were not able to retrieve slope and aspect information from a digital elevation model, for example, because it requires field knowledge of the site and for each sample, which we cannot systematically obtain given our global-scale goals. Thus, slope and aspect constants are set to zero. The soil is divided into four layers  (1-15; 15-30; 30-65; 65-100 cm). Clay and sand fractions are extracted from the Harmonized World Soil Database (hereafter HWSD) v1. 2 at 30 arcsec resolution (FAO/IIASA/ISRIC/ISSCAS/JRC, 2012) at the nearest cell with observed value, which is always at a distance smaller than 100 km to the site and assigned as follows: 1-30 cm parameters from the HWSD for the two first soil layers in MAIDEN; 30-100 cm parameters from the HWSD for the two deepest soil layers in MAIDEN.
Study sites A network of tree-ring width chronologies of Picea mariana collected in similar conditions is available for the https://doi. org/10. 5194/cp-16-1043-2020 Clim. Past, 16, 1043-1059, 2020 Eastern Canadian taiga  (Nicault et al. , 2014; Boucher et al. , 2017;  http://dendro-qc-lab. ca/trw. html, last access: 30 March 2019). We use here the tree-ring series directly derived from this compilation, without any modification. The chronologies have been previously standardized using the age-band regional curve standardization (or RCS) method proposed by  Briffa et al. (2001)  and further applied to a similar boreal dataset by  Nicault et al. (2014). We also use the Eastern Canadian taiga chronology for Picea mariana from Gennaretti et al. (  2017 ) (hereafter QC_taiga), standardized using a site-specific RCS  (Gennaretti et al.
Three additional tree-ring width chronologies (hereafter European sites) are used to perform tests on sites with good replication, especially at the European Alps site, and long nearby series from meteorological stations (Fig. 2 ): EALP (47 • N, 10. 7 • E; 2050 m; European Alps; Pinus cembra and Larix decidua;  Büntgen et al. , 2011 ; processed data available in the PAGES 2k database; PAGES 2k Consortium, 2017); SWIT179 (46. 77 • N, 9. 82 • E; 1800 m; Picea abies; standardized with a cubic-smoothing spline with a 50 % frequency cut-off at 35 years;  Seftigen et al. , 2018;  unprocessed data archived at the International Tree Ring Data Bank, https:// www. ncdc. noaa. gov/data-access/paleoclimatology-data, last access: 12 January 2019) and FINL045 (68. 07 • N, 27. 2 • E; Pinus sylvestris; standardized using a spline with a 50 % frequency cut-off response at 32 years;  Babst et al.
Climate data Daily climatic inputs are needed to run MAIDEN (Sect. 2. 1. 1). Monthly climatic inputs for VS-Lite are computed from those daily data. Note that monthly-average temperature has been computed by averaging daily maximum and minimum temperatures, which could lead to a small bias. Three daily climatic datasets with different spatial resolution (Table  2 ) were selected for our analysis on the Eastern Canadian taiga network (Fig. 1a  and b ). First, a dataset at a high spatial resolution of 5 min from the gridded interpolated Canadian database of daily minimum-maximum temperature and precipitation  (Hutchinson et al. , 2009, hereafter NRCAN). The Global Meteorological Forcing Dataset for land surface modeling (v1) (http://hydrology. princeton. edu/ data. php, last access: 4 January 2019;  Sheffield et al.
, 2006)  at 1 • resolution is used as a mid-resolution climatic dataset (hereafter GMF). The NOAA-CIRES 20th Century Reanalysis V2c (https://www. esrl. noaa. gov/psd/data/gridded/ data. 20thC_ReanV2c. monolevel. html, last access: 4 January 2019) at 2 • resolution is used as a low-resolution dataset (hereafter 20CRv2c). Finally, the 20CRv2c dataset was modified to match the monthly-mean seasonal cycle of the highresolution dataset NRCAN (hereafter 20CRv2c corr. ). This simple bias correction and downscaling to the location of the site is done by removing the difference between the monthly-mean seasonal cycle of 20CRv2c (2 • ) and NRCAN (5 arcmin) from the maximum and minimum temperature data. In order to avoid negative values, daily precipitations are multiplied by the ratio between the monthly-mean seasonal cycle of NRCAN (5 arcmin) and 20CRv2c (2 • ).
The calibration method has been tested for convergence of Markov chains with Gelman-Rubin statistical indicators  (Hartig et al. , 2019). The MAIDEN model was calibrated at the 21 Eastern Canadian taiga sites and at the 5 aggregated sites over the 1950-2000 time period using the high-(NRCAN), mid-(GMF) and low-resolution (20CRv2c) datasets as inputs, as well as the bias-corrected low-resolution dataset (20CRv2c corr. ), and over the 1900-2000 time period using the 20CRv2c and 20CRv2c corr. datasets as climatic inputs. MAIDEN was also calibrated at the three European sites using GHCN station data over 1950-2000 (FINL045; EALP; SWIT179),  1909 -1944 (FINL045) and 1910 -1949 (EALP and SWIT179). Calibrated parameters values for the 1950-2000 time period are available in Tables S4-S7. Parameter posterior frequency distributions for the NRCAN (5 arcmin) high-resolution climatic dataset are available in Figs.
3. 1. Another option is to calibrate each site individually, as in Sect. 3. 2 following the calibration protocol detailed in Sect. 2. 3. 1. We thirdly test in Sect. 3. 3 an alternative calibration method which consists of calibrating the MAIDEN model over the mean of a treering width observations network with similar environmental conditions and then applying the resulting calibrated parameters to the individual sites. From another perspective, this experiment could also be seen as an alternative method for the validation of the MAIDEN model when the climate and/or tree-ring width observation time series are too short for a split-sample validation. In this case, the individual sites are considered nearly independent validation data. To test the sensitivity of the model to the quality of climatic inputs, we have selected four climatic datasets at different spatial resolutions (Sect.
Site-specific calibration of the MAIDEN parameters and sensitivity to the quality of climatic inputs A second option is to calibrate each of the 21 Eastern Canadian taiga sites as well as the 5 aggregated Eastern Canadian taiga sites (Fig. 1 ) using the calibration procedure detailed in Sect. 2. 3. 1. Correlations between tree-growth observations and simulations with MAIDEN for the 1950-2000 calibration period at the Eastern Canadian taiga sites are good and significant for all the climatic datasets (Fig. 4a ). Correlations are in general slightly higher for the higher-resolution datasets (NRCAN (5 arcmin) and GMF (1 • ) datasets, with an average correlation of 0. 62 and 0. 65, respectively, compared with 0. 57 for 20CRv2c (2 • ) and 0. 61 for 20CRv2c corr. (2 • )). At the aggregated sites (Fig.
5a ), correlations for each dataset increase a little bit compared to the average of individual correlations, but the general picture is the same. The bias correction (20CRv2c corr. (2 • )) can slightly improve correlations for the 20CRv2c (2 • ) climatic dataset in some cases (e. g. WL42 and WROZM). Consequently, those results do not indicate that using higher-resolution datasets effectively increase correlations. This is likely due to the calibration procedure that might be able to compensate for specific biases in each climatic dataset. This implies large variations of cali-Clim. Past, 16, 1043-1059, 2020 https://doi. org/10. 5194/cp-16-1043-2020 Many potential biases of tree-ring observations due to the specific physiology of selected trees -that may not be representative of forest processes -and the chronology building process exist that may dampen the comparison with what MAIDEN simulates, i.
At the aggregated sites (Fig. 5b ), correlations for each dataset decrease slightly compared to the mean of individual correlations. The low correlation for the whole 20th century can be explained by the large uncertainty of the 20CRv2c (2 • ) climatic dataset before 1950 there, as measured by the large spread of the 20CRv2c ensemble spread at that time (Fig. S62 ). When applying the parameters calibrated using the highest resolution dataset, NRCAN (5 arcmin), as climatic inputs to the Eastern Canadian taiga sites driven by the 20CRv2c (2 • ) dataset (Fig. 6b , in red), correlations are on average much lower. Mean correlation is 0. 17 in that case compared to 0. 57 when the parameters are calibrated using 20CRv2c (2 • ) as climatic inputs. With the 20CRv2c corr. (2 • ) dataset as climatic inputs -i.
e. the low-resolution dataset corrected for bias in the mean seasonal cycle -(Fig. 6a , in red) we see that the performance of the MAIDEN model when applying NRCAN (5 arcmin) parameters is less good compared to the case when the parameters are calibrated using 20CRv2c corr. (2 • ) as climatic inputs (in black). Nevertheless, correlations are far better than with 20CRv2c (2 • ) (Fig. 6b , in red). Indeed, the mean correlation is 0. 36 when applying NRCAN (5 arcmin) parameters and 0. 61 when applying 20CRv2c corr. (2 • ) parameters. Consequently, the bias correction of the 20CRv2c (2 • ) increases the robustness of the calibration of the MAIDEN parameters. Additionally, this shows that the MAIDEN model parameter calibration is highly sensitive to the quality of the climatic dataset used as inputs.
At the aggregated sites (Fig. 7 ), the general picture is the same but with far lower correlations. The mean correlations are 0. 07 when applying the parameters calibrated using NR-CAN (5 arcmin) to the aggregated sites driven by 20CRv2c (2 • ) dataset and 0. 56 when the parameters are calibrated using 20CRv2c (2 • ). With the 20CRv2c corr. (2 • ) dataset as climatic inputs, mean correlations are respectively 0. 18 and 0. 61 with NRCAN (5 arcmin) and 20CRv2c corr. (2 • ) parameters. Those results would require a case-by-case analysis as it seems that higher replication does not provide better performance in this specific experiment.
Comparison with VS-Lite On average, over the 1950-2000 calibration period at the individual Eastern Canadian taiga sites, VS-Lite has lower correlations for the highest-resolution dataset (NRCAN) compared with MAIDEN, i. e. 0. 106 and 0. 62 mean correlations for VS-Lite and MAIDEN, respectively (Fig. 9 ). Results for https://doi. org/10. 5194/cp-16-1043-2020 Clim. Past, 16, 1043-1059, 2020 Table  4. Pearson correlation coefficients between tree-growth observations and simulations at the European sites (Fig. 2 ) with MAIDEN and VS-Lite using GHCN as climatic inputs (Table  2 ) for the  1950 -1974 and 1975 -2000 and for the 1910 -1949 (EALP, SWIT179)     good than over the long time period but still more stable than MAIDEN (Table  4 ). Compared to VS-Lite, MAIDEN has shown lower skill over short-time-period validation, which indicates that we should only use MAIDEN when a long enough period is available for validation.
Most importantly, we have shown that to limit overfitting, MAIDEN should not be used with short and low-replicated tree-ring width observation time series. VS-Lite is less risky to use in such situations as there is potentially less overfitting in the calibration and probably easier to apply over a large network of tree-ring width time series. However, VS-Lite does not include CO 2 nor biological processes and may thus not be able to take into account changes in conditions between the recent calibration period and the more distant past. In the future, MAIDEN will be applied at a larger spatial scale in a systematic way, using the protocol that has been developed here, by selecting hundreds of sites from the commonly used databases in palaeoclimate reconstruction based on tree-ring proxies, covering a wide range of environmental conditions and tree species, such as PAGES 2k (PAGES 2k Consortium, 2017) and NTREND  (Wilson et al.
, 2015; Gennaretti et al. , 2017)  is provided online (https://figshare. com/articles/MAIDEN_ecophysiological_ forest_model/5446435/1, last access: 17 November 2019; Gennaretti, 2017) and its modules are available upon request. The VS-Lite model code is available at the National Oceanic and Atmospheric Administration's Paleoclimatology World Data Center (https://www. ncdc. noaa. gov/paleo-search/reports/ all?dataTypeId=59&search=true, last access: 3 October 2018). The Eastern Canadian taiga tree-ring width data from  Nicault et al. (2014)  and  Boucher et al. (2017)  can be downloaded from http://dendro-qc-lab. ca/trw. html (last access: 30 March 2019). The European chronologies are also available online: the EALP tree-ring width data  (Büntgen et al. , 2011)  can be accessed through the PAGES 2k database (https://doi.
org/10. 1038/sdata. 2017. 88, PAGES 2k Consortium, 2017); unprocessed SWIT179 tree-ring width data are archived at the International Tree Ring Data Bank (https://www. ncdc. noaa. gov/data-access/paleoclimatology-data, last access: 12 January 2019); the FINL045 tree-ring width data are available in the supplementary materials of  Babst et al. (2013). The Global Meteorological Forcing Dataset for land surface modeling (v1)  (Sheffield et al. , 2006 ) can be downloaded from http://hydrology. princeton. edu/data. php (last access: 4 January 2019). The NOAA-CIRES 20th Century Reanalysis V2c can be downloaded from https: //psl. noaa. gov/data/gridded/data. 20thC_ReanV2c. monolevel. html (last access: 4 January 2019). The gridded interpolated Canadian database of daily minimum-maximum temperature and precipitation  (Hutchinson et al.
, 2009)  are available upon request. The Global Historical Climate Network daily station data  (Menne et al. , 2012a, b)  are available online (https://www. ncdc. noaa. gov/ghcnd-data-access, last access: 10 January 2019). Annual atmospheric CO 2 concentration data from Sato and Schmidt can be downloaded from https://data. giss. nasa. gov/modelforce/ghgases/ (last access: 3 December 2018). All results from this paper are available upon request. Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/cp-16-1043-2020-supplement. Author contributions. This study is part of JR's thesis under the supervision of HG and JG. JR, HG and JG designed the study. JR performed the analysis, wrote the paper and made the figures. FG provided scripts and expertise that have made the work with MAIDEN possible.
304 0. 315  * 0. 263 Asterisks stand for significant correlations (p value < 0. 05). the other climatic datasets over the 1950-2000 period (GMF dation over the long time period, the performance of VS-Lite (1 • ), 20CRv2c (2 • ) and 20CRv2c corr. (2 • )) and over the is more stable (less fall of validation from calibration correla- 1900-2000 calibration period (20CRv2c (2 • ) and 20CRv2c tion) compared with MAIDEN (Table 4) even if correlations corr. (2 • ) climatic datasets) also show lower correlations are, except for SWIT179, lower than MAIDEN. Similarly, compared to MAIDEN (Fig. S63). As for split-sample vali- over the short time period, the performance of VS-Lite is less Clim. Past, 16, 1043-1059, 2020 https://doi. org/10. 5194/cp-16-1043-2020.
attention, impulsivity and feeding/weight regulation  9. It is stocked in vesicles and released after an electrical stimulus. HSM binds pre-or post-synaptic receptors. Ciproxifan  4, 10, 11  (CPX or FUB-359; CAS No. 184025-18-1; GRAC database, guidetopharmacology. org; Supplementary Fig. S1b ) is a highly potent and selective competitive H3-receptor antagonist/inverse agonist with pro-cognitive properties and a nanomolar affinity (for a given signaling assay used, inverse agonism refers to the ability of a compound to inhibit constitutive GPCR signaling, presenting thus negative efficacy)  12. Cloning of the histamine H3R cDNA in 1999 allowed detailed studies of its molecular aspects and indicated that H3R can activate several signal transduction pathways  4. H3R is regarded as a potential therapeutic target because of its location in the CNS and for the modulation of a variety of functions such as cognitive processes, epilepsy, food intake and sleep-wakefulness  13, 14.
Our analyses also highlight the presence of distinctly different lipid allosteric regulatory sites according to the state of the receptor  40  and point to the mechanism of modulation of lipid on receptor function  22, 41, 42  -each specific protein-lipid interaction stabilizes the corresponding state of the receptor (Sup- plementary Fig. S12 ). like cholesterol binding to β2-AR, there are specific binding sites for DPPC in H3R, but specific to the state of the receptor. Like palmitic acid and cholesterol in the β2-AR-carazolol crystal structure (PDB code 2RH1), the contacts between the lipids' hydrocarbon chains and hydrophobic receptor residues follow the hydrophobic matching principle. However, as we found, the specific lipid-binding motifs on the membrane protein surface consist also of positively charged residues that specifically interact with the negatively charged phosphodiester groups (Supplementary Figs.
S12-S14 ). Our findings are thus consistent with the experimentally reported lipid binding sites in membrane proteins  22, 43  , and with the protein-head and proteintail contacts for the H1R (PDB ID 3RZE), as reported in the MemProtMD database  22. From the analysis of the amino acid residues in contact with lipids for each of the three systems, we can formulate lipid binding sequence motifs (Supplementary Table  S8 ).
Methods and materials We used the Ballesteros-Weinstein generic numbering scheme for the amino acid residues of class A GPCRs  16, 72. The numbers attributed correspond to frame 0 of the trajectory. Homology modeling. We built the 3D structure of the transmembrane regions of the R. norvegicus histamine H3 receptor (Hrh3 gene, UniProt Q9QYN8, isoform 2 or rH3R(413)) with MODELLER's sequence homology method  73  by taking advantage of the diverse experimental X-ray structures of several homologous class A 7TM receptors that have become available in recent years, such as β2-AR (PDB codes 2RH1, 2R4R, 2R4S, etc. ). Our use of a short isoform H3R is justified by the finding that the HSM auto-receptor is reported to be a short isoform of the H3R, that is, H3R(413)  74. We paid attention by choosing active state structures as templates for the HSM-H3R and H3R apo homology models, and inactive state structure templates for the CPX-H3R homology model.
The TM1-TM1 values of the rH3R:hβ2-AR pair are of 47. 4% identity (89. 5% similar, LALIGN software, EMBnet Server). We took the short isoform of the R. norvegicus sequence because its pharmacological characterization is more complete, and its sequence is 93. 7% identical to H sapiens'. As far as the loops connecting the TM helices is concerned, we employed a truncated form of the receptor by reducing the size of the IC3 loop (~ 140 residues), given its conformational heterogeneity and the fact that its long sequence shows no homology to any experimental 3D structure (a Blast search of ICL3 against the PDB gives no significant results). On another hand, a sequence analysis of ICL3 found several low-complexity regions, such as poly-Pro and poly-Ser, and sequence fingerprints or motifs. Nevertheless, its ab initio modeling is not possible due to its size.
We used the Membrane Builder tool in the CHARMM-GUI server  80, 81  for construction of the membrane and for immersing the receptor in a pre-equilibrated symmetric lipid bilayer with the Insertion method. For the protein-membrane-water system, we generated a 1,2-Dipalmitoylphosphatidylcholine (DPPC)-based bilayer (PubChem CID 6138) in a rectangular water box in which we kept the ionic strength at 0. 15 M by KCl. We used this salt as we wanted to see the effects of the monovalent potassium on the receptor, as opposed to sodium. The relative number of K + and Cl -counterions allowed us to obtain an electrically neutral system. The cubic box lipid bilayer consisted of about 188 phospholipids solvated with a shell of water molecules and ions placed around the bilayer with the program Solvate (https ://www.
mpibp c. mpg. de/ grubm uelle r/solva te). We also included buried waters in the internal cavity of the receptor with the program Dowser (https ://dange r. med. unc. edu/herma ns/dowse r/dowse r. htm). The space surrounding the bilayer was cropped to a rectangular, periodic simulation box with periodic boundary conditions. This configuration allows the receptor, placed in the center of the layer, and its periodic image, to be separated by a significant distance, thus avoiding unwanted receptor-receptor interactions. The dimensions of the box were of about 80 nm by 80 nm by 100 nm and depended on the system at hand. In addition to the receptor, the explicit water solvent, the phospholipids and the K + and Cl -counterions, the box contained, if appropriate, the ligand. The resulting systems contained 70,000-100,000 atoms.
Among the several output files generated by the Charmm-gui. org server, we used the topology files for the subsequent MD simulations. The dielectric constant of the interior of the receptor is high and like that of the aqueous solvent (~ 78) due to the presence of internal waters. We utilized the Propka  82  program to assign the protonation states of the titratable groups of H3R at pH value 7. 4. Nevertheless, we paid attention to the fact that the side chains exposed to the midst of the membrane are embedded in a low-dielectric, hydrophobic environment. Thus, the ionization states of ionizable side chains in the interior of the receptor (since it is saturated with water), in the phosphatidylcholine head-group zone and in the extra and intracellular zones were assigned as those corresponding to exposure to a high-dielectric surrounding.
DPPC is a phospholipid that is well characterized physicochemically, whose experimental average surface area per headgroup in the gel phase is known 83 (63 ± 1 A 2 at 323 K). We performed MD experiments on a test membrane and noticed that it was neither necessary to apply any external surface tension in the calculations nor to impose the surface area per lipid, as we reproduced the experimental DPPC area per phospholipid in its absence. In addition, certain GPCRs have been shown to function in cholesterol-free membranes  40. We employed the Nanoscale Molecular Dynamics software package (NAMD), version 2. 7b1, using the CHARMM-22/CMAP force field for proteins for the simulations. HSM and CPX were parametrized with the CHARMM General Force Field (CGenFF) program of the ParamChem initiative (https ://www.
Acknowledgments This study was supported by grants from:  ECOS Nord-ANUIES Mexique  and  UMR-S 1204 INSERM/Université d'Evry-Val-d'Essonne/Université Paris-Saclay  for visiting scholarships to  LDHZ. Institut de Recherches Servier  for a postdoctoral fellowship to  LMMV. Université d'Evry-Val d'Essonne  for a visiting professorship to JCB.