Data from: Contribution of range-wide and short-scale chemical soil variation to local adaptation in a tropical montane forest tree
Data files
Jun 25, 2025 version files 964.37 KB
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Genotype-Amanalco.txt
431.37 KB
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Genotype-Pobl-TMVB.txt
508.74 KB
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README.md
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Soil_Variables--Amanalco.txt
7.90 KB
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Soil_Variables-TMVB.txt
9.51 KB
Abstract
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.
Dataset DOI: 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
