Megan Rua

Dr. Megan Rua

orcid

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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10 June 2016 in BMC Ecology and Evolution
Verified
Journal Article
Open access
PDF file
MRMegan Rua
Megan Rua
AAAnita Antoninka
Anita Antoninka
PAPedro M. Antunes
Pedro M. Antunes
VCV. Bala Chaudhary
V. Bala Chaudhary
CGCatherine Gehring
Catherine Gehring
JHJason D. Hoeksema
Jason D. Hoeksema
Local adaptation, the differential success of genotypes in their native versus foreign environment, arises from various evolutionary processes, but the importance of concurrent abiotic and biotic factors as drivers of local adaptation has only recently been investigated. Local adaptation to biotic interactions may be particularly important for plants, as they associate with microbial symbionts that can significantly affect their fitness and may enable rapid evolution. The arbuscular mycorrhizal (AM) symbiosis is ideal for investigations of local adaptation because it is globally widespread among most plant taxa and can significantly affect plant growth and fitness. Using meta-analysis on 1170 studies (from 139 papers), we investigated the potential for local adaptation to shape plant growth responses to arbuscular mycorrhizal inoculation. The magnitude and direction for mean effect size of mycorrhizal inoculation on host biomass depended on the geographic origin of the soil and symbiotic partners. Sympatric combinations of plants, AM fungi, and soil yielded large increases in host biomass compared to when all three components were allopatric. The origin of either the fungi or the plant relative to the soil was important for explaining the effect of AM inoculation on plant biomass. If plant and soil were sympatric but allopatric to the fungus, the positive effect of AM inoculation was much greater than when all three components were allopatric, suggesting potential local adaptation of the plant to the soil; however, if fungus and soil were sympatric (but allopatric to the plant) the effect of AM inoculation was indistinct from that of any allopatric combinations, indicating maladaptation of the fungus to the soil. This study underscores the potential to detect local adaptation for mycorrhizal relationships across a broad swath of the literature. Geographic origin of plants relative to the origin of AM fungal communities and soil is important for describing the effect of mycorrhizal inoculation on plant biomass, suggesting that local adaptation represents a powerful factor for the establishment of novel combinations of fungi, plants, and soils. These results highlight the need for subsequent investigations of local adaptation in the mycorrhizal symbiosis and emphasize the importance of routinely considering the origin of plant, soil, and fungal components.

23 September 2022 in Science
Verified
Journal Article
Closed access
AZAmy E. Zanne
Amy E. Zanne
HFHabacuc Flores-Moreno
Habacuc Flores-Moreno
JPJeff R. Powell
Jeff R. Powell
WCWilliam K. Cornwell
William K. Cornwell
JDJames W. Dalling
James W. Dalling
PZPaul-Camilo Zalamea
Paul-Camilo Zalamea
Deadwood is a large global carbon store with its store size partially determined by biotic decay. Microbial wood decay rates are known to respond to changing temperature and precipitation. Termites are also important decomposers in the tropics but are less well studied. An understanding of their climate sensitivities is needed to estimate climate change effects on wood carbon pools. Using data from 133 sites spanning six continents, we found that termite wood discovery and consumption were highly sensitive to temperature (with decay increasing >6.8 times per 10°C increase in temperature)—even more so than microbes. Termite decay effects were greatest in tropical seasonal forests, tropical savannas, and subtropical deserts. With tropicalization (i.e., warming shifts to tropical climates), termite wood decay will likely increase as termites access more of Earth’s surface.

1 June 2009 in Ecology
Verified
Journal Article
Open access
PDF file
JRJennifer A. Rudgers
Jennifer A. Rudgers
MAMichelle E. Afkhami
Michelle E. Afkhami
MRMegan Rua
Megan Rua
ADAndrew J. Davitt
Andrew J. Davitt
SHSamantha Hammer
Samantha Hammer
VHValérie M. Huguet
Valérie M. Huguet
Plant‐associated microbes have been increasingly recognized for influencing host populations, plant communities, and even herbivores and predators. Thus, understanding factors that affect the distribution and abundance of microbial symbioses may be important for predicting the ecological dynamics of communities. Using endophytic fungi–grass symbioses, we explored how intrinsic traits of the symbiosis, specifically transmission mode, may influence symbiont frequencies in host populations. Combining published literature with new field surveys, we comparedEpichloëendophytes, which had mixed horizontal and vertical transmission, withNeotyphodiumendophytes, which were exclusively vertically transmitted from host plants to seeds. Exclusively vertical transmission should select against pathogenicity because symbionts depend entirely on hosts for reproduction. Across 118 host species, we found thatNeotyphodiumhosts had 40–130% higher symbiont frequencies thanEpichloëhosts. In field surveys, endophyte frequency was positively correlated with the local density of hosts, but only forEpichloë, suggesting that contagiously spreadEpichloëmay attain higher frequencies when hosts are more abundant.Epichloëendophytes were also more likely thanNeotyphodiumto have imperfect vertical transmission; thus, hosts may reduce the transmission of more pathogenic symbionts to seeds. Results are consistent with the conclusion that the evolutionary transition to exclusively vertical transmission can alter patterns of symbiont frequency in nature.

16 August 2018 in Communications Biology
Verified
Journal Article
Open access
PDF file
JHJason D Hoeksema
Jason D Hoeksema
JBJames D. Bever
James D. Bever
SCSounak Chakraborty
Sounak Chakraborty
VCV. Bala Chaudhary
V. Bala Chaudhary
MGMonique Gardes
Monique Gardes
PZPeter C. Zee
Peter C. Zee
Most plants engage in symbioses with mycorrhizal fungi in soils and net consequences for plants vary widely from mutualism to parasitism. However, we lack a synthetic understanding of the evolutionary and ecological forces driving such variation for this or any other nutritional symbiosis. We used meta-analysis across 646 combinations of plants and fungi to show that evolutionary history explains substantially more variation in plant responses to mycorrhizal fungi than the ecological factors included in this study, such as nutrient fertilization and additional microbes. Evolutionary history also has a different influence on outcomes of ectomycorrhizal versus arbuscular mycorrhizal symbioses; the former are best explained by the multiple evolutionary origins of ectomycorrhizal lifestyle in plants, while the latter are best explained by recent diversification in plants; both are also explained by evolution of specificity between plants and fungi. These results provide the foundation for a synthetic framework to predict the outcomes of nutritional mutualisms.

10 May 2016 in Scientific Data
Verified
Journal Article
Open access
VCV. Bala Chaudhary
V. Bala Chaudhary
MRMegan Rua
Megan Rua
AAAnita Antoninka
Anita Antoninka
JBJames D. Bever
James D. Bever
JCJeffery B. Cannon
Jeffery B. Cannon
JHJason D. Hoeksema
Jason D. Hoeksema
Plants form belowground associations with mycorrhizal fungi in one of the most common symbioses on Earth. However, few large-scale generalizations exist for the structure and function of mycorrhizal symbioses, as the nature of this relationship varies from mutualistic to parasitic and is largely context-dependent. We announce the public release of MycoDB, a database of 4,010 studies (from 438 unique publications) to aid in multi-factor meta-analyses elucidating the ecological and evolutionary context in which mycorrhizal fungi alter plant productivity. Over 10 years with nearly 80 collaborators, we compiled data on the response of plant biomass to mycorrhizal fungal inoculation, including meta-analysis metrics and 24 additional explanatory variables that describe the biotic and abiotic context of each study. We also include phylogenetic trees for all plants and fungi in the database. To our knowledge, MycoDB is the largest ecological meta-analysis database. We aim to share these data to highlight significant gaps in mycorrhizal research and encourage synthesis to explore the ecological and evolutionary generalities that govern mycorrhizal functioning in ecosystems.

1 October 2017 in Phytopathology®
Verified
Journal Article
Open access
FHFrank M. Hilker
Frank M. Hilker
LALinda Allen
Linda Allen
VBVrushali A. Bokil
Vrushali A. Bokil
CBCheryl J. Briggs
Cheryl J. Briggs
ZFZhilan Feng
Zhilan Feng
NCNik Cunniffe
Nik Cunniffe
Maize lethal necrosis (MLN) has emerged as a serious threat to food security in sub-Saharan Africa. MLN is caused by coinfection with two viruses, Maize chlorotic mottle virus and a potyvirus, often Sugarcane mosaic virus. To better understand the dynamics of MLN and to provide insight into disease management, we modeled the spread of the viruses causing MLN within and between growing seasons. The model allows for transmission via vectors, soil, and seed, as well as exogenous sources of infection. Following model parameterization, we predict how management affects disease prevalence and crop performance over multiple seasons. Resource-rich farmers with large holdings can achieve good control by combining clean seed and insect control. However, crop rotation is often required to effect full control. Resource-poor farmers with smaller holdings must rely on rotation and roguing, and achieve more limited control. For both types of farmer, unless management is synchronized over large areas, exogenous sources of infection can thwart control. As well as providing practical guidance, our modeling framework is potentially informative for other cropping systems in which coinfection has devastating effects. Our work also emphasizes how mathematical modeling can inform management of an emerging disease even when epidemiological information remains scanty. [ ] Copyright © 2017 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .