DOI: 10.5061/dryad.6t1g1jx88
title: Biocultural vulnerability of traditional crops in the Indian Trans Himalaya

description: Traditional agricultural landscapes are vital reservoirs of biocultural
 heritage and agrobiodiversity, yet traditional farming systems and their
 unique crop landraces face increasing marginalization and genetic erosion.
 Using northwest Himalaya as a case study, we examine the ecological
 resilience and genetic diversity of an understudied traditional crop,
 black pea (scientific name unclear), alongside barley (Hordeum vulgare),
 and compare them to the introduced cash crop, green pea (Pisum sativum
 L.). Participatory field experiments with local farmers revealed that
 traditional crops outperform introduced varieties in survival and
 reproduction traits across sites. We generate the first whole-genome
 sequencing data for black peas. Clustering and nutritional analyses
 highlight black pea’s genetic richness and dietary potential. Our findings
 underscore the importance of integrating Traditional Ecological Knowledge
 with ecological science to sustain agrobiodiversity, enhance climate
 resilience, and promote sustainable food systems. We provide insights for
 global agri-food innovations and socio-ecological stability in fragile
 mountain ecosystems.
description: The crop dataset was collected during March-Sep 2023 during the
 cropping season for survival and growth performance of the three different
 crops. The data was collated and compared on those performance metrics.
 The genetic dataset was collected from paper: 
 <em>Tao Yang et al. “Improved pea reference genome and
 pan-genome highlight genomic fea</em><em>tures and
 evolutionary characteristics”. Nature genetics 54.10 (2022), pp.
 1553–156</em> This was compared with our whole
 genome sequencing data. We want to note that the whole genome sequencing
 data generated for the black pea as part of this study has been deposited
 on NCBI - BioSample accession SAMN44380099. The genetic
 analysis consists of the following files. The files are the covariance
 matrices for each of the 7 chromosomes for black peas. They can be read in
 R using the read.table() function with the header as False since the file
 is a matrix with 18 rows and 18 columns.     
 Pea_n18_NC_066579.covar<br>    Pea_n18_NC_066580.covar<br>   
 Pea_n18_NC_066581.covar<br>    Pea_n18_NC_066582.covar<br>   
 Pea_n18_NC_066583.covar<br>    Pea_n18_NC_066584.covar<br>   
 Pea_n18_NC_066585.covar In addition, the file
 peapca_supplement_genome.csv provides SRR and accension details for the
 Pisum species and subspecies used to compare our black pea sample with.
 The data was collected from Tao Yang 2022 paper. The
 ecological analysis can be performed using 2023_crop_data. The csv file is
 read in R using read.csv function. The columns correspond to flowering
 (proportion of flowering plants), survival (proportion of seeds
 germinating), leaf (length in cm), stem height (length in cm), number of
 pods after x days, where x is added to the column names. The rows
 correspond to the values for the type of crop (green pea, black pea,
 barley), according to site (Kibber, Kiamo, Tashigang, and Thinam) as well
 as the replicates.  
description: # Biocultural vulnerability of traditional crops in the Indian Trans
 Himalaya **Overview of data** This dataset is for our research examining
 the ecological and genomic variation of traditional crop species- black
 pea, and barley, cultivated across Indian Trans-Himalaya. The field study
 was conducted in March-September 2023 to evaluate the growth performance
 of three crop species: green peas, black peas, and barley. The field
 experiment was carried at three sites characterized: low (4000m), mid
 (4200m), and high (4500m) elevations. The experiment was laid out in a
 randomized block design with a factorial arrangement, incorporating three
 factors: crop species, water treatments, and elevation levels. Each
 treatment combination was replicated three times, and thus a total of 81
 plots were monitored. The seeds were sown uniformly across all plots and
 spacing was determined by interacting with farmers. The sowing density for
 green pea was lower than black pea seeds since black pea seeds are
 relatively smaller. The farmers also advised on sowing depth and bed
 preparation to ensure optimal growth conditions. The IRB eprotocol number
 is 71749. We set up plots for green, black pea, and barley (1.5 by 1
 meter) along a climate gradient in three villages (at elevations ~4000m,
 ~4200m, ~4500m) with three water treatments. We monitored the plants for
 photosynthetic, non-reproductive and reproductive traits such as,
 germination rate, flowering time, height at maturity, leaf coloration
 (disease infestation), and flower/pod production. Data on growth
 parameters (plant height, leaf area, and biomass) were collected at
 regular intervals (every 7-10 days). Yield components were assessed at the
 time of harvest. Data were analyzed using regression analysis to determine
 the effects of the crop type, water treatment, elevation, and their
 interactions. Post hoc tests were performed to locate differences between
 treatment means at a significance level of p&lt;0.05. All statistical
 analyses were carried out using R software. Additionally, black pea
 genotypes were analyzed using whole-genome sequencing and compared to
 published Pisum genomic datasets to understand population structure and
 diversity. **Files Included** 2023_crop_data.csv
 peapca_supplement_genome.csv Pea_n18_NC_066579.covar- Covariance matrix
 for black pea chromosome NC_066579 (18x18). Pea_n18_NC_066580.covar-
 Covariance matrix for black pea chromosome NC_066580 (18x18).
 Pea_n18_NC_066581.covar- Covariance matrix for black pea chromosome
 NC_066581 (18x18). Pea_n18_NC_066582.covar- Covariance matrix for black
 pea chromosome NC_066582 (18x18). Pea_n18_NC_066583.covar- Covariance
 matrix for black pea chromosome NC_066583 (18x18).
 Pea_n18_NC_066584.covar- Covariance matrix for black pea chromosome
 NC_066584 (18x18). Pea_n18_NC_066585.covar- Covariance matrix for black
 pea chromosome NC_066585 (18x18). biocultural_code_for_manuscript.R- R
 script for PCA and clustering on covariance matrices. Contains code to
 generate all figures in the manuscript. **Description of data files**
 **File: 2023_crop_data.csv** Tabulates ecological data on plant growth and
 phenology across crop types and treatments as well as across the 3 sites
 for green pea, barley, and black pea. Each row corresponds to a crop plot
 defined by crop type, elevation (site), and replication. The variable
 names include: Sno | Serial number for each Site. Site | Village where the
 plot was located. There are four sites: Kibber, Kiamo, Tashigang, Thinam;
 each at a different elevation. Helper_ID | The column is a copy of the
 Site column with numbers to coding and analysis ease. Field no | Field
 identifier within the site. Plot no | Plot identifier. Crop | Crop
 species. There are three crops: green pea, black pea, or barley.
 Water_treatment | There were three water treatments S1, S2, S3 with three
 replicates each. S1 corresponds to business as usual irrigation scheme as
 advised by the farmers. S2 refers to reduced irrigation and S3 corresponds
 to drought like conditions with least irrigation scheme for the crops.
 However, our water treatments are not used as a predictor variable since
 there were more rains in the summer season. The treatments were used as
 replicates and averaged. Irrigation_times | Denotes the number of times
 the fields were watered throughout the growing season. The irrigation
 times and days were advised by the farmers. This ranges from 2 times for
 Black pea in Kiamo to 9 times for green pea in many sites depending on the
 water treatment as noted below. Average leaves [X] | Mean number of leaves
 per plant at X days since sowing the seeds for respective crops. Average
 height [X] (units cm) | Mean stem height in cm at X days after sowing.
 Flowering plants [X] | Proportion of plants that had flowered by day X for
 that crop. Plants pods [X] | Proportion of plants bearing pods by day X.
 Survival | Proportion of seeds that produced sapling 30 days after sowing.
 Average leaf length [X] days (units cm) | Average length of leaves X days
 after sowing. Average leaf breadth [X] days (units cm) | Average breadth
 of leaves X days after sowing. Average stem thickness [X] days (units cm)
 | Average stem thickness X days after sowing. Average no of pods per plant
 [X] | Average no of pods X days after sowing. Average pod height
 [X] (units cm) | Average pod height X days after sowing. Average no of
 seeds per pod [X] | Average no of seeds per pod per plant X days after
 sowing. Average weight of pod [X] (units grams) | Average weight of pod X
 days after sowing. Average fresh weight above ground [X] days (units
 grams) | Average weight of plant above ground X days after sowing. Average
 dry weight above ground [X] days (units grams) | Average dry weight of
 plant above ground X days after sowing. Average dry weight below ground
 [X] days (units grams) | Average dry weight of plant below ground X days
 after sowing. Total weight of pods [X] days (units grams) | Weight of pods
 X days after sowing. --- Please note that there are empty cells for some
 columns in the .csv file. For the leaves, flowering and pods columns, the
 empty cells represent there were no leaves, flowers or pods in the initial
 months. The cells become non-empty as these traits begin to show up. There
 are also empty cells for the Barley crop column, since Barley is a grass
 and we did not count number of leaves for a grass species. **File:
 peapca_supplement_genome.csv** This file contains metadata on comparative
 genome accessions and clustering assignments. Run No. | Identifier for
 sequencing run Sample ID | Identifier for each accession Accession No. |
 NCBI accession number Original taxa | Reported taxonomic name Country |
 Country of sample origin Type | Domesticated or wild pea sample ADMIXTURE
 Group (SNPs) | Cluster assignment (q &gt; 0.6) from SNP-based ADMIXTURE at
 K=5 ADMIXTURE Group (SVs) | Cluster assignment from SV-based ADMIXTURE at
 K=5 **Description of .covar Files** The `.covar` files are numeric
 covariance matrices of dimension 18 × 18, generated from genomic variation
 among black pea accessions. Each file corresponds to one of the seven
 chromosomes: Pea_n18_NC_066579.covar -&gt; Chromosome NC_066579,
 Pea_n18_NC_066580.covar -&gt; Chromosome NC_066580... and so on. These
 files can be opened using: \- Text editors (e.g., Notepad) \- Spreadsheet
 programs (e.g., Microsoft Excel) \- R or Python (e.g., in R:
 `as.matrix(read.table("filename.covar", header = FALSE))`) Each
 row and column represents one of the 18 accessions, and the values
 indicate pairwise covariance. **Data Sources** Comparative genomic data
 were obtained from: Yang, T. et al. (2022). "Improved pea reference
 genome and pan-genome highlight genomic features and evolutionary
 characteristics." Nature Genetics, 54(10), 1553–1563.
 [https://doi.org/10.1038/s41588-022-01178-6](https://doi.org/10.1038/s41588-022-01178-6) The newly sequenced black pea sample from this study has been deposited at NCBI under: BioSample accession: SAMN44380099 **Software and Code** All code for PCA and clustering analyses have been shared in the script. To run the script, you will need: \- R version 4.2.0 or higher \- R packages: RColorBrewer, tidyverse, reshape2, magick, ggbiplot, factoextra, ggpubr, ggfortify, cowplot, corrplot, ggpmisc, patchwork, hrbrthemes, Hmisc, RSpectra, plot.matrix, FactoMineR, scatterplot3d, kernlab The script reads the `.covar` files, performs PCA, and runs k-means, hierarchical, and spectral clustering. Outputs include 2D and 3D PCA plots and cluster visualizations.