DOI: 10.5061/dryad.ksn02v796
title: Microevolutionary processes in a foundation tree inform macrosystem patterns of community biodiversity and structure

description: Despite an increased focus on multiscale relationships and
 interdisciplinary integration, few macroecological studies consider the
 contribution of genetic-based processes to landscape-scale patterns. We
 tested the hypothesis that tree genetics, climate, and geography jointly
 drive continental-scale patterns of community structure, using genome-wide
 SNP data from a broadly distributed foundation tree species (Populus
 fremontii S. Watson) and two dependent communities (leaf-modifying
 arthropods and fungal endophytes) spanning southwestern North America.
 Four key findings emerged: (1) Tree genetic structure was a significant
 predictor for both communities; however, the strength of influence was
 both scale- and community-dependent. (2) Tree genetics was the primary
 driver for endophytes, explaining 17% of variation in continental-scale
 community structure, whereas (3) climate was the strongest predictor of
 arthropod structure (24%). (4) Power to detect tree genotype—community
 phenotype associations changed with scale of genetic organization,
 increasing from individuals to populations to ecotypes, emphasizing the
 need to consider nonstationarity (i.e., changes in the effects of factors
 on ecological processes across scales) when inferring macrosystem
 properties. Our findings highlight the role of foundation tree species as
 drivers of macroscale community structure and provide macrosystems ecology
 with a theoretical framework for linking fine- and intermediate-scale
 genetic processes to landscape-scale patterns. Management of genetic
 diversity harbored within foundation species is a critical consideration
 for conserving and sustaining regional biodiversity.
description: <strong>Methods in Brief</strong> (please refer to
 the associated publication for full details)
 <strong>Tree Genotyping: </strong> We collected
 individually geo-referenced leaf material from 453 <em>Populus
 fremontii</em> trees at 58 sampling locations spanning the
 southwestern US and northwestern Mexico. DNA was extracted from leaf
 material, and double digest restriction-associated DNA (ddRAD) libraries
 were prepared following a modified Peterson et al. (2012) protocol.
 Quality filtering and variant calling
 of raw sequencing data used a modified Stacks v1.3 pipeline (Catchen et
 al. 2013, Andrews 2018), with a minimum read depth of six and presence in
 at least three individuals required to call a locus. This resulted
 in 322 genotypes being retained, represented by 8637 loci
 filtered to one random SNP per locus. Genetic distance matrices
 (<em>F</em>st) and the PHYLIP sequence alignment were
 generated in Stacks. Genomic data for
 <em>P. fremontii</em> are available at NCBI’s Sequence Read
 Archive (https://www.ncbi.nlm.nih.gov/sra), BioProject ID PRJNA868761.  <strong>Community Data</strong>   <strong><em>Leaf-modifying Arthropods:</em> </strong> Arthropod surveys were standardized by branch diameter (2–3 branches/tree, ~35 mm total) to account for leaf area, and survey time (15 min/tree). Arthropod species were visually identified to the lowest possible taxonomic level; any unrecognized species were collected, later identified in the lab, and added to the Northern Arizona University Insect Collection. <em><strong>Twig Fungal Endophytes:</strong>  </em>To assess twig fungal endophyte community structure, we collected 10 twigs/tree, including 3-years growth, directionally stratified around each tree’s circumference. The total DNA was extracted from twig samples, and fungal ITS2 rDNA was selectively amplified using fungal-specific primers 5.8SFun and ITS4Fun (Taylor et al. 2016). Amplification and indexing were performed following Alvarado et al. (2018). Taxonomic identities were assigned with BLAST in QIIME against the dynamic UNITE database (Kõljalg et al. 2013). OTU tables were rarefied to the lowest sample depth for the purpose of assessing alpha diversity or normalized with cumulative sum scaling for all other analyses (Paulson et al. 2013). <strong>Environmental</strong> <strong>Data: </strong> We identified a suite of 20 environmental predictor variables that we hypothesized are related to gene flow and connectivity among <em>P. fremontii</em> and its associated communities (see Table S2 of the associated publication for full details). These include latitude, longitude, average Sping wind direction vectors, hydrological, and bioclimatic variables.