How developmental stressors affect mitochondrial respiratory function: A systematic review and meta-analysis

1. How to use this repository? Users can download a zip file of the entire repository by clicking on the green code tab at the top of the page and then clicking Download ZIP. Alternatively, the repo can be downloaded from Zenodo. Users who already have a GitHub account can fork the repository. The main file for users to click on when they are first navigating is the 📄 mito_meta_stress.Rproj file which will open the folder and set the working directory to the root of the downloaded folder. This will provide access to the code and data through R. Note that we use Quarto to provide a reproducible results where our text, code and figures are integrated together. This allows users to identify what specific objects are being used to render the quantitative information provided in the manuscript (more details below). 2. Project Organization and Workflow The key file in this repository for reproducing the results is the 📄 results.qmd file within the 📂 docs folder. This file can be rendered in R with Quarto to reproduce the results section and supplement. Code chunks within the file provide the code used to reproduce figures and analyses along with supporting statements within the text. Note that inline code chunks use specific objects which are then rendered. The 📄 results.qmd file makes use of files within a number of folders that are identified in the code chunks. There are a number of important folders in the repository. 📂 data The data folder contains all the raw data used in files. Note that there are intermediary data files here that were used throughout the processing. There are really only two main files to worry about. For more details see 3. Data below. 📂 output/figs/ Folder contains all the figures for the paper that are read and included in the paper. See more details below (4. Figures). 📂 R The R folder contains three files that are used to clean and process data to prepare it for use in the 📄 results.qmd file. Note that readers do not need to open and run these files, but they are simply here to document the workflow and code used to clean up data to be used. 3. Data There are two data folders: 1) 📂 data and 2) 📂 output/data/. The data/ folders contains the raw data, whereas the output/data/ folder contains the processed data that is used in the results.qmd file. The processed data is created by running the R files in the R folder. The processed data is then used in the results.qmd file to generate the figures and analyses. These data files all contain the same columns aside form a few processed columns that are added in the processing steps and exported with the data subsets. The columns are as follows: Column Name Description study Unique study identifier ref First author last name year Year the publication was published class Class of organism family Family of organism genus Genus of organism species Binomial species name of organism. common_name common name of organism stage when conditions were applied during development (i.e., pre or postnatal) sex the sex of the study animals (i.e., male, female, or both) prenatal_trt_start when prenatal treatment was initiated where 0 = conception prenatal_trt_end when prenatal treatment terminates prenatal_dur the amount of time prenatal treatment was administered, if listed as conception to day 14 the assumption is that the time frame is inclusive and this number would be 15 prenatal_unit unit of time of prental treatment post_natal_trt_start Day 0 equals day of birth or egg lay. If a treatment starts when nestlings are two days old then this value should be 3 (day 0, 1, and 2) postnatal_trt_end when prenatal treatment terminates dur_trt_postnatal the amount of time postnatal treatment was administered, if listed as birth to day 14 the assumption is that the time frame is inclusive and this number would be 15 postnatal_unit unit of time of postnatal treatment total_trt_duration the amount of time all treatments were administered, if prenatal duration = 20 and postnatal = 20 days then this number is 40 total_trt_unit unit of time of total treatments prenatal_measure_delay The time from the end of the prenatal treatment to when the measurements were collected. So, if treatment ends at birth and mito was measured at 100 days following birth this number should be 100 postnatal_measure_delay The time from the end of the postnatal treatment to when the measurements were collected. If treatment ends at 15 days and mito was measured at 100 days then this number should be 85 measure_delay_units unit of time of delay envirn_type Type of developmental environment manipulation. Categorical. Categories include: "temp", "nutrition",'brood" nutrition_sum If the developmental manipulation is nutrition, is it overnutrition or undernutrition; if not nutrition then NA nutrition_type If the developmental manipulation is nutrition, was fat, protein, or total food manipulated; if not nutrition then NA admin how the treatment was delivered fasting_period time animals were fasted before tissues were harvested; if listed as 'overnight' 12 hours used; NA indicates the information is not available fasting_period_unit the unit of time animals were fasted before tissues were harvested num_tissue_types the number of tissue types for which we can extract effects sizes; potentially multiple tissues were harvested, but if only one was used to measure mito parameters then this variable is scored as '1'; different sections of tissue count as different tissue types (e.g., different neural regions) tissue_sum category of tissue type tissue specific type of tissue used (e.g., section of brain) dir_effect direction of effect (positive or negative) of the cause or consequences of high metabolic rate whereas positive values indicate high and negative values indicate low measure_sum broad category of what the mito measurement indicates about mito bioenergetics measure_listed what the authors listed that was measured descrp_measure description of what was measured with details from author units Units of outcome variable t1 Treatment 1 name. This could be temperature, nurtition, control etc t2 Treatment 2 name. This could be temperature, nurtition, control etc trt_units Units of the treatment manopulation. If a temperature manipulation then this is in degrees Celcius. If brood size, this woul dbe the change in brood size mean_t1 Mean value of treatment 1 sd_t1 Standard deviation of treatment 1. If provided in standard error convert from SE to SD using SD = sqrt(N)*SE n_t1 Sample size in treatment 1. se_t1 standard error in treatment 1, calculated as SD/sqrt(n) CI95_t1 confidence interval of mean in treatment 1, se calculated from this as = (mean+upper CI95) - (mean-lower CI95)/3.92 mean_t2 Mean value of treatment 2 sd_t2 Standard deviation of treatment 2. If provided in standard error convert from SE to SD using SD = sqrt(N)*SE n_t2 Sample size in treatment 2. se_t2 standard error in treatment 2, calculated as SD/sqrt(n) CI95_t2 confidence interval of mean in treatment 2, se calculated from this as = (mean+upper CI95) - (mean-lower CI95)/3.92 sample_dependent A classifier that identified if different rows in the dataset are traits measured on the SAME SAMPLE of animals. If the same sample then they share the same number type classification of means, e.g., raw or least squares CORT_values_available yes' if there are data on CORT levels in response to a manipulation. For example, if a study chased fish as a disturbance and measure the effect of this treatment on CORT in addition to mito parameters then this is a 'yes;' if there are no CORT values = "NA" species_phylo Species name for building the phylogeny species_phylo2 Species name for inclusion of the species-level (non phylogenetic) random effect obs Observation number for including a residual random effect to estimate residual variance notes anything that may be important