Abiotic and biotic controls on local spatial distribution and performance of Boechera stricta

Abstract

This study investigates the relative influence of biotic and abiotic factors on community dynamics using an integrated approach and highlights the influence of space on genotypic and phenotypic traits in plant community structure. We examined the relative influence of topography, environment, spatial distance, and intra- and interspecific interactions on spatial distribution and performance of Boechera stricta (rockcress), a close perennial relative of model plant Arabidopsis. First, using Bayesian kriging, we mapped the topography and environmental gradients and explored the spatial distribution of naturally occurring rockcress plants and two neighbors, Taraxacum officinale (dandelion) and Solidago missouriensis (goldenrod) found in close proximity within a typical diverse meadow community across topographic and environmental gradients. We then evaluated direct and indirect relationships among variables using Mantel path analysis and developed a network displaying abiotic and biotic interactions in this community. We found significant spatial autocorrelation among rockcress individuals, either because of common microhabitats as displayed by high density of individuals at lower elevation and high soil moisture area, or limited dispersal as shown by significant spatial autocorrelation of naturally occurring inbred lines, or a combination of both. Goldenrod and dandelion density around rockcress does not show any direct relationship with rockcress fecundity, possibly due to spatial segregation of resources. However, dandelion density around rockcress shows an indirect negative influence on rockcress fecundity via herbivory, indicating interspecific competition. Overall, we suggest that common microhabitat preference and limited dispersal are the main drivers for spatial distribution. However, intra-specific interactions and insect herbivory are the main drivers of rockcress performance in the meadow community.

The effect of rhizosphere microbes outweighs host plant genetics in reducing insect herbivory

“…This result is consistent with previous studies of flea beetle– Boechera stricta interactions. In a study examining the distribution of natural B. stricta populations, there was an inverse relationship between B. stricta occurrence and flea beetle frequency despite natural variation in GLS content between lines (Naithani, Ewers, Adelman, & Siemens, ). The inability of B. stricta to adapt to flea beetles may be explained by the flea beetles’ ability to utilize GLS as a nutrient source (Beran et al, ).…”

A Hyb‐Seq phylogeny of Boechera and related genera using a combination of Angiosperms353 and Brassicaceae‐specific bait sets

“…Boechera stricta (previously known as Arabis drummondii ) is sister to all other members of the erect fruit clade. It is widespread in the mountains and boreal regions of western North America and has been a primary focus of research within Boechera (Song et al, 2006; Windsor et al, 2006; Schranz et al, 2007, 2009; Manzaneda et al, 2010; Lee and Mitchell‐Olds, 2013; Lee et al, 2014; Naithani et al, 2014; Anderson and Gezon, 2015; Anderson et al, 2011, 2015; Salmela et al, 2016; Heo et al, 2018; Lee et al, 2018; Rojek et al, 2018; Wagner and Mitchell‐Olds, 2018; Bemmels and Anderson, 2019; Olsen et al, 2019; Wang et al, 2019; Hamann et al, 2021; Lin et al, 2021; Liang et al, 2022). It is one of the most distinctive species in the genus, easily separated from all other sexual diploids by its unique pubescence.…”

Building an Integrative and Testable Hypothesis on How Edaphic Factors Ultimately Influence the Occurrence and Quality of Ophiocordyceps Sinensis, the Vegetable Caterpillar

“…In conclusion, the quality of O. sinensis showed relationships with most of the soil enzyme activity, all soil nutrients, as well as moisture and nematode populations. Based on previous studies [33][34][35] and our analysis, we developed an initial model by assuming that all the variables were directly correlated with the quality of O. sinensis, and that there were connections between nutrients and enzyme activity, as well as causal relationships between soil moisture, pH and soil nutrients, enzyme activity and nematodes. After tting the model, we made progressive modi cations to the original design with the remainders of the parameters until an optimized model t was achieved (χ 2 = 4.249, p = 0.643).…”