Landscape genetics of the copal tree, Bursera cuneata (Burseraceae): The key role of the Tropical Dry Forest in shaping connectivity at the regional scale.

Description

Abstract

Abstract

Land-use changes in tropical dry forests (TDF) have rapidly reduced native vegetation, disrupting gene flow dynamics of tree species. Bursera cuneata is a co-dominant TDF tree in central Mexico, which is threatened by habitat loss and overexploitation. We investigated landscape drivers of functional connectivity of B. cuneata across scales to inform species conservation efforts. We genotyped 227 B. cuneata individuals from 33 populations across five hydrological basins: covering western, central, and southern Mexico, at 10,499 single-nucleotide polymorphism (SNP) loci. We examined spatial patterns of genetic structure among hydrological basins and the landscape correlates of gene flow. We applied gravity models that incorporated within-site (i.e., local conditions within populations; slope and east aspect) and between-site (terrain roughness, habitat suitability, and habitat cover) factors associated with B. cuneata gene flow. Clustering analyses showed genetic structure among basins, with higher differentiation in more isolated regions. Gravity models revealed that functional connectivity is a scale-dependent process. Specifically, terrain roughness was the primary factor of connectivity at finer scales (1,000–3,000 m), while TDF cover became the main driver at regional scales (>4,000 m). We recommend protecting and prioritizing crucial TDF remnants to maintain large-scale gene flow by integrating urban natural parks as important links to prevent genetic isolation between urban and rural populations.

Methods

Data description

This dataset accompanies the manuscript “Landscape genetics of the copal tree, Bursera cuneata (Burseraceae): The key role of the Tropical Dry Forest in shaping connectivity at the regional scale”.

Leaf tissue was collected from 227 individuals of Bursera cuneata distributed across 33 populations within five hydrological basins in central Mexico between 2017 and 2019. Genomic DNA was extracted and genotyped using the OmeSeq-qRRS reduced-representation sequencing approach. Raw reads were processed through the ngsComposer and GBSapp pipelines and mapped against the Bursera cuneata reference genome.

Single nucleotide polymorphisms (SNPs) were filtered to retain high-quality biallelic loci. Filters included minor allele frequency (MAF ≥ 0.02), maximum observed heterozygosity of 0.65, minimum read depth of 6, maximum read depth of 80, maximum missing data of 30% per locus, and maximum missing genotypes of 20% per individual. Putative loci under selection were identified using LEA and pcadapt and removed, resulting in a neutral SNP dataset used for downstream analyses.

The archive includes:

• Bucu_MAF02_neutral_227.vcf.gz: filtered neutral SNP dataset used for analyses of genetic diversity, genetic structure, migration rates, and landscape genetics.

• ID_Bc_227.csv: metadata file containing sample identifiers, population assignment, hydrological basin, geographic coordinates, and environmental information for each sampled individual.

• Environmental_layers_gravity_models.zip: raster layers used as predictors in gravity models to evaluate how habitat suitability, land-cover categories, and topographic variables (slope, roughness, and aspect) influence functional connectivity among populations.

These data were used to estimate genetic diversity, population structure, contemporary migration rates, and landscape connectivity in Bursera cuneata populations across central Mexico. Environmental raster layers were incorporated into gravity models implemented in the GeNetIt package to evaluate alternative hypotheses of functional connectivity.