Improving species delimitation for effective conservation: a case study in the endemic maple‐leaf oak (Quercus acerifolia)

Abstract

Summary Species delimitation is challenging in lineages that exhibit both high plasticity and introgression. This challenge can be compounded by collection biases, which may downweight specimens morphologically intermediate between traditional species. Additionally, mismatch between named species and observable phenotypes can compromise species conservation. We studied the species boundaries of Quercus acerifolia, a tree endemic to Arkansas, U.S. We performed morphometric analyses of leaves and acorns from 527 field and 138 herbarium samples of Q. acerifolia and its close relatives, Q. shumardii and Q. rubra. We employed two novel approaches: sampling ex situ collections to detect phenotypic plasticity caused by environmental variation and comparing random field samples with historical herbarium samples to identify collection biases that might undermine species delimitation. To provide genetic evidence, we also performed molecular analyses on genome‐wide SNPs. Quercus acerifolia shows distinctive morphological, ecological, and genomic characteristics, rejecting the hypothesis that Q. acerifolia is a phenotypic variant of Q. shumardii. We found mismatches between traditional taxonomy and phenotypic clusters. We detected underrepresentation of morphological intermediates in herbarium collections, which may bias species discovery and recognition. Rare species conservation requires considering and addressing taxonomic problems related to phenotypic plasticity, mismatch between taxonomy and morphological clusters, and collection biases.

Ex situ conservation of two rare oak species using microsatellite and SNP markers

“…Therefore, we chose to conduct our analyses without the specification of minor allele frequency threshold, to avoid potentially biasing our measures of ex situ representation of rare alleles. Finally, recent analyses have demonstrated that the Kessler Mountain population of Q. acerifolia is partly composed of admixed individuals likely resulting from crosses between Q. acerifolia and Q. shumardii (Wu et al., 2023). The presence of hybrid individuals could have confounding impacts on population clustering analyses (Vähä & Primmer, 2006); moreover, hybrid individuals are likely to harbor alleles from parental species not included in this study, which would greatly distort any ex situ representation results.…”

“…To do so, we analyzed Subset garden and wild samples using microsatellite and SNP (de novo and Reference) markers. Because Q. acerifolia has stronger wild population structure (Wu et al., 2023) than Q. boyntonii (Spence et al., 2021), we focused solely on Q. acerifolia for this analysis.…”

Leaf morphometric analysis and potential distribution modelling contribute to taxonomic differentiation in the Quercus microphylla complex

“…The genus Quercus (Fagaceae) is recognized for its economic and ecological importance and recently has become a model clade in different fields of biology (Cavender-Bares 2019 ). For these reasons, defining and properly differentiating species in this group is a fundamental task (Valencia-A 2020 ; Wu et al 2023 ). On the basis of phylogenomic analyses (Hipp et al 2018 , 2020 ), Quercus has recently been divided (Denk et al 2017 ) into two subgenera with eight sections (subgenus Quercus , including sections Lobatae , Ponticae , Protobalanus , Quercus and Virentes , and subgenus Cerris , including sections Cerris , Cyclobalanopsis and Ilex ).…”

Geographic And Taxonomic Occurrence R‐based Scrubbing (gatoRs): An R package and workflow for processing biodiversity data

“…Herbarium data downloaded from these and other aggregators have been used to investigate a diverse array of biological questions (e.g., Wollan et al, 2008 ; Willis et al, 2017 ; Allen et al, 2019 ; reviewed in Heberling et al, 2019 ). Applications in research are broad and include species delimitation (e.g., Zapata and Jiménez, 2012 ; Su et al, 2020 ; de Mestier et al, 2023 ; Wu et al, 2023 ), understanding organismal response to seasonal events (e.g., Pearson et al, 2020 ; Guralnick et al, 2022 ; Belitz et al, 2023 ; Park et al, 2023 ), exploring global patterns of biodiversity (e.g., Gaynor et al, 2020 ; Melton et al, 2022 ; Folk et al, 2023 ), and investigating the potential impact of climate change on species distributions (e.g., Rawal et al, 2015 ; Gaynor et al, 2018 ; Hodel et al, 2022 ; Naranjo et al, 2022 ; Wang et al, 2022 ).…”