BUSCADOR RECOLECTA

[Material and methods] In this experiment six ground moss species were utilized. • Ptychostomum capillare (Hedw.) D.T. Holyoak & N. Pedersen [== Bryum capillare Hedw.] • Dicranum scoparium Hedw. • Homalothecium aureum H. Rob. • Hypnum cupressiforme Hedw. • Tortella squarrosa (Brid.) Limpr. [== Pleurochaete squarrosa (Brid.) Lindb.] • Syntrichia ruralis (Hedw.) F. Weber & D. Moh. For the moss stand inoculation, seedbed pots with synthetic wadding as the growth substrate were used. The experimental units were placed in three different locations along a 100-kilometer altitudinal gradient in Central Spain, specifically at: • Estación Biológica “El Ventorrillo” (VENT), Madrid, Spain (1482 meters above sea level - m.a.s.l.) • Universidad Autónoma de Madrid (UAM), Madrid, Spain (717 m.a.s.l.) • Finca Experimental “La Higueruela” (HIG), Toledo, Spain (455 m.a.s.l.) The pictures were captured using two Mapir Survey 2 cameras (https://www.mapir.camera/). One camera had an RGB sensor for visual wavelengths, while the other had a Red + NIR sensor for near-infrared. The manufacturer adjusted the focal distance to approximately 25 cm from the samples. Both cameras were equipped with a 16MP Sony Exmor IMX206 sensor, featuring a Bayer RGB pattern. The red absorption occurred at 660 nm, and near-infrared was captured at 850 nm. We employed a transparent plastic light diffuser box with an interior lining of white paper, such as filter paper. This setup served to even out the lighting and reduce the appearance of harsh shadows. Each image included the samples, a colour chart (specifically, the X-Rite ColorChecker® Classic) for calibration, as detailed in prior works (Ritchie et al., 2008; Fischer et al., 2012), and a millimetre scale for calculating the pixel-to-millimetre ratio. Moss samples were labelled in each hollow. The cameras saved the images in raw format and we converted it to tif format without compression using Darktable 2.6.1 software (https://www.darktable.org/) (‘Darktable’, 2019). Then we used ImageJ software (Schindelin et al., 2012) to align each pair of NIR-VIS images and to homogenize colour histograms for each VIS and NIR image series in each locality. The ImageJ scripts are provided by Photomoss protocol (Molina-Bustamante et al., 2022)., This dataset contains a set of images that display moss samples from six distinct species over seedling trays from a common garden experimental set-up. We grow these moss samples on a background of white synthetic material. The capture of the images was in both near-infrared and visible light wavelengths. We provide additional files to fit the main dataset objective: use it as a test platform for evaluating the PhotomossR package. In this repository, you will discover images taken in both the near-infrared and visible light spectrums. These images offer comprehensive data for testing different spectral indices using the PhotomossR package (Molina-Bustamante, DeCastro-Arrazola, Doherty, & Medina, 2022)., This work is part of the projects UNITED (CGL2016-78070-P, funded by Spanish Agencia Estatal de Investigación [AEI] and Fondo Europeo de Desarrollo Regional [FEDER] European Union) and SCENIC (PID2019-106840GA-C21 and PID2019-106840GA-C22, funded by Spanish Ministerio de Ciencia e Innovación [MCIN] and AEI), M. M-B was funded by the Comunidad de Madrid, and the European Social Fund that co-financed through the Youth Employment Operational Program and the Youth Employment Initiative (YEI) grant PEJ-2017-AI/AMB-6504., Contains 5 folders based on the locality and date of image capture. Within each locality folder, there are 4 subfolders (nir, vis, rois, mask) and a 'names.csv' file that provides label names for the samples. • "nir" folder with images in the infrared spectrum. Images named by the date of capture. • "vis" folder with images in the visible spectrum. Images named by the date of capture. • "rois" folder that includes roi files. Inside this folder, there are as many subfolders as images in “nir” and “vis” folders. Each subfolder containing the roi files corresponding to the samples we want to analyse in each of the images. • "mask" folder with binary images of moss samples. Files are numerically named.in the order PhotomossR will analyse it., No

Supplementary Figure S1. Flow chart of inclusion/exclusion criteria for the studied autopsy sample. Supplementary Figure S2. Classification of individual FDG-PET scans based on spatial correlation with pathology-specific patterns. Supplementary Figure S3. Illustration of an alternative stratification approach based on a Gaussian Mixture Model analysis of the ∆r distribution. Supplementary Figure S4. Individual FDG-PET profiles of the two cases with hippocampal sclerosis in the comorbid AD+LATE-NC group. Supplementary Figure S5. FDG-PET patterns of the stratified atypical and non-hypometabolic patient groups in the in-vivo cohort. Supplementary Figure S6. Group-specific trajectories of longitudinal cognitive decline. Supplementary Figure S7. Associations with LATE-NC- vs AD-like FDG-PET pattern expression on a continuous scale. Supplementary Figure S8. Individual hypometabolic profiles of LATE-NC cases. Supplementary Figure S9. IMT ratio in relation to age. Supplementary Figure S10. FDG-PET pattern of age-matched AD group. Supplementary Figure S11. LATE-NC-typical pattern using an age-matched control group. Supplementary Figure S12. FDG-PET patterns of pathologic groups without LATE-NC/AD and other pathologies. Supplementary Table S1. Harvard-Oxford atlas ROIs used for screening for relevant hypometabolism. Supplementary Table S2. Characteristics of LATE-NC-like and AD-like patient groups stratified according to a GMM-based approach. Supplementary Table S3. Characteristics of patients stratified according to the inferior-to-medial temporal metabolism ratio. Supplementary Table S4. Contingency table of group assignments based on pattern matching compared to the inferior-to-medial temporal ratio., TDP-43 assessment and individual staging. ADNI memory and executive function composite scores. Possible neuropathologic correlates of a LATE-NC-like FDG-PET pattern., Peer reviewed

Electronic supplementary information (ESI) available: (1) Neutron reflectivity fitting procedure, (2) NR fitting demonstration of PLL between the ESs, (3) surface pressure and ellipsometry stability measurements, and (4) verification of surface pressure values at high compression ratios., Peer reviewed

3 files. -- Dataset 1: This dataset contains measurements on the atypical song that were analyzed in the manuscript. -- Dataset 2: This dataset contains measurements on nestlings from the Cranberry Lake white-throated sparrow population from 1998-2014, and includes the focal males (FROP; 1541-43272)., Here we provide data for a manuscript in which we describe the atypical song of a male white-throated sparrow (Zonotrichia albicollis). We observed this male over multiple breeding seasons at our Cranberry Lake study site (Adirondack Mountains; New York; 44.15N, 74.78W). We recorded the male singing, and also made observations regarding his failure to obtain reproductive success. In addition, as the male was banded as a nestling, we were able to compare his morphometric measurements at the time to the population average. Our observations of this unique individual support a connection between developmental stress, atypical song, and fitness outcomes., EXPLANATION OF DATASET_WTSP_Atypical_song.docx, FROP_Song_analysis.csv, NestlingLevel1998_2014.csv, Peer reviewed

6. CalRotesPlot_Rainfall-AirTemp-RH-SWC-5min_2021-07_2022-07.xlsx The precipitation data (mm), air temperature data (ºC), relative humidity data (%) and Soil Water Content data (cm3.cm-3) at the Cal Rotes Plot (5 min time step) for the period 07-2021-07-2022., Peer reviewed

Supplemental Data Supplemental Video 1 Supplemental Video 2, Peer reviewed

39 pages. -- Section A: Description of the study area and the sample. -- Table A.1: Annual mean hydrochemical conditions from 2010 to 2020 (data source: LUNG). -- Table A.2: Total tagged pike (per lagoon and sex). -- Figures A.1-A.2. -- Table A.3: of the sample after data filtering and UD estimations. -- Section B: Receiver range estimations. -- Section C: Descriptive statistics. -- Section D: Analysis on weight (including code). -- Table D.1: Stepwise model selection on core area. -- Table D.2: Stepwise model selection on extended range. -- Effects and confidence intervals. -- Table D.3: Stepwise model selection on range.ratio. --Section E: Analysis on length. -- Table E.3: Stepwise model selection on range.ratio. -- Section F: Example Range plots. -- Section G: Monthly effects., Peer reviewed

Document S1. Figures S1–S8, Movie S1 and Supplemental Experimental Procedures., Peer reviewed

Peer reviewed

22 p. -- This PDF file includes: Figs. S1 to S7. -- Tables S1 to S2. -- 6 sections., Peer reviewed