DOI: 10.5061/dryad.np5hqc060
title: Data from: Contribution of range-wide and short-scale chemical soil variation to local adaptation in a tropical montane forest tree

description: Local adaptation is a fundamental process that allows populations to
 thrive in their native environment, often increasing genetic
 differentiation from neighboring stands. However, detecting the molecular
 basis and selective factors responsible for local adaptation remains a
 challenge, particularly in sessile, non-model species with long life
 cycles, such as forest trees. Local adaptation in trees is not only
 modeled by climatic factors, but also by soil variation. Such variation
 depends on dynamic geological and ecological processes that generate a
 highly heterogeneous selective mosaic that may differentially condition
 tree adaptation both at the range-wide and local scales. This could be
 particularly manifest in species inhabiting mountain ranges that were
 formed by diverse geological events, like sacred fir (Abies religiosa), a
 conifer endemic to the mountains of central Mexico. Here, we used
 landscape genomics approaches to investigate how chemical edaphic
 variation influences the genetic structure of this species at the
 range-wide and local scales. After controlling for neutral genetic
 structure, we performed genotype-environment associations and identified
 49 and 23 candidate SNPs at the range-wide and local scales, respectively,
 with little overlap between scales. We then developed polygenic models
 with such candidates, which accounted for ~20% of the range-wide variation
 in soil Ca2+ concentration, electric conductivity (EC), and pH, and for
 the local variation in soil EC and organic carbon content (OC). Spatial
 Principal Component Analyses further highlighted the role of geography and
 population isolation in explaining this genetic-soil co-variation. Our
 findings reveal that local adaptation in trees is the result of an
 intricate interaction between soil chemical properties and the local
 population’s genetic makeup, and that the selective factors driving such
 adaptation greatly vary and are not necessarily predictable across spatial
 scales. These results highlight the need to consider edaphic variation in
 forest genetic studies (including common garden experiments), and in
 conservation, management, and assisted migration programs.
description: # Contribution of range-wide and short-scale chemical soil variation to
 local adaptation in a tropical montane forest tree Dataset DOI:
 [10.5061/dryad.np5hqc060](10.5061/dryad.np5hqc060) **Description of the
 data and file structure** Contribution of range-wide and short-scale
 chemical soil variation to local adaptation in a tropical montane forest
 tree **Project Overview** This study explores the relationship between
 genetic variation and chemical soil environmental heterogeneity across the
 Trans-Mexican Volcanic Belt (TMVB), focusing on both broad-scale and
 microenvironmental spatial patterns. Landscape genomics methods are used
 to investigate how soil conditions influence local adaptation and genetic
 structure. **Data Files** **1. Genotype-Pobl-TMVB.txt** Description:
 Genome-wide SNP data from individuals sampled across the entire
 Trans-Mexican Volcanic Belt. Purpose: Used for landscape-scale analyses of
 genetic structure and genotype-environment associations. **2.
 Genotype-Amanalco.txt** Description: Genome-wide SNP data from individuals
 sampled within a single site located in the central TMVB. Purpose:
 Designed to assess microenvironmental influences on genetic variation at a
 finer spatial scale. **3. Soil_Variables-TMVB.txt** Description: This file
 contains spatial data on nine chemical soil environmental variables across
 the Trans-Mexican Volcanic Belt (TMVB). The dataset was originally derived
 from a comprehensive national-scale interpolation study using 4,400
 topsoil samples (Cruz-Cárdenas et al., 2014). These variables capture the
 major chemical components that influence forest soil composition in the
 region. Purpose: Used to test for associations between genetic variation
 and environmental gradients at a landscape scale (macroenvironmental
 context). Variables (Columns): Each row corresponds to a sampling location
 or population site within the TMVB. | Column Name | Full Name |
 Description | Units | | ----------- | ------------------------ |
 ------------------------------------------------------------------------------------------------------------ | ---------------------------- | | EC | Electrical Conductivity | An indicator of soil salinity and ion content | dS/m (decisiemens per meter) | | OC | Organic Carbon | Amount of organic carbon present in the topsoil layer (0–20 cm), a proxy for soil fertility | kg/m² | | OM | Organic Matter | Total organic matter content in the topsoil, closely linked to soil structure and nutrient availability | % | | Ca | Calcium concentration | Concentration of exchangeable calcium ions (Ca²⁺) in the soil | cmol(+)/kg | | Mg | Magnesium concentration | Concentration of exchangeable magnesium ions (Mg²⁺) in the soil | cmol(+)/kg | | K | Potassium concentration | Concentration of exchangeable potassium ions (K⁺) in the soil | cmol(+)/kg | | Na | Sodium concentration | Concentration of exchangeable sodium ions (Na⁺) in the soil | cmol(+)/kg | | pH | Soil pH | Acidity or alkalinity of the soil, influencing nutrient availability and microbial activity, unitless (0–14) | unitless | | CEC | Cation Exchange Capacity | Total capacity of the soil to hold exchangeable cations, indicating nutrient retention capacity | cmol(+)/kg | Note: All variables represent modeled interpolations based on standardized sampling depths (0–20 cm), and are spatially resolved at ~1 km² resolution across the TMVB. **4. Soil_Variables-Amanalco.txt** Description: This file contains microenvironmental soil data collected specifically from the Amanalco study site. These values reflect localized variation in soil chemical traits that may influence genotype performance at fine spatial scales. Purpose: Enables genotype-environment association analysis under a microenvironmental framework, allowing detection of subtle ecological effects not captured at broader scales. Variables (Columns): Each row corresponds to a sampling point within the Amanalco microenvironment. | Column Name | Full Name | Description | Units | | ----------- | ------------------------ | ------------------------------------------------------- | ------------------- | | EC | Electrical Conductivity | Indicator of total dissolved salts in the soil solution | dS/m | | OC | Organic Carbon | Soil organic carbon content in the upper 20 cm | kg/m² | | OM | Organic Matter | Organic matter content in the soil | % | | Ca | Calcium concentration | Exchangeable calcium ion concentration | cmol(+)/kg | | Mg | Magnesium concentration | Exchangeable magnesium ion concentration | cmol(+)/kg | | K | Potassium concentration | Exchangeable potassium ion concentration | cmol(+)/kg | | Na | Sodium concentration | Exchangeable sodium ion concentration | cmol(+)/kg | | pH | Soil pH | Soil acidity or alkalinity | unitless (pH scale) | | CEC | Cation Exchange Capacity | Soil’s capacity to retain positively charged ions | cmol(+)/kg | Note: These measurements were obtained in situ and processed following standardized protocols. The data allow for testing fine-scale environmental associations within a single population. **Methods Overview** Genotype Data Analysis: Quality filtering, population structure analysis, and SNP-environment association tests. Environmental Data Integration: Soil variables are integrated with genomic data to identify signatures of local adaptation. Both landscape and micro-scale patterns are evaluated independently. Association Methods: Gradient Forest, LFMM (Latent Factor Mixed Models), or redundancy analysis (RDA), depending on the objective. For questions or collaboration inquiries, please contact: Sebastian Arenas Email: [sebastian.arenas@slu.se](mailto:sebastian.arenas@slu.se)