Context‐dependency of resource allocation trade‐offs highlights constraints to the evolution of floral longevity in a monocarpic herb

Spigler, Rachel B.; Woodard, Alyssa J.

doi:10.1111/nph.15498

Cited by 18 publications

(18 citation statements)

References 104 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If season length is an index of resource availability, then we essentially find alternate investment strategies between leaf size and leaf number (Scott & Aarssen, ). Analogously, research on flower longevity shows that, under low resources, plants make fewer flowers and maintain these for longer, while under high resources, plants invest in more flowers (Spigler & Woodard, ). We found very high heritability for leaf number in the fall cohort, and strong genetic correlations between leaf number and other traits (Tables , S2); suggesting the potential to respond to selection with coordinated growth strategies.…”

Section: Discussionmentioning

confidence: 99%

Environmental heterogeneity generates intrapopulation variation in life‐history traits in an annual plant

2019

View full text Add to dashboard Cite

Environmental variation affects a plant's life cycle by influencing the timing of germination and flowering, and the duration of the growing season. Yet we know little information about how environmental heterogeneity generates variation in germination schedules and the consequences for growth and fecundity through genetic and plastic responses.We use an annual population of Mimulus guttatus in which, in nature, seeds germinate in both fall and spring. We investigate whether there is a genetic basis to the timing of germination, the effect of germination timing on fecundity, and if growth and flowering respond plastically to compensate for different season lengths.Using sibling families grown in simulated seasonal conditions, we find that families do not differ in their propensity to germinate between seasons. However, the germination season affects subsequent growth and flowering time, with significant genotype-by-environment interactions (G 9 E). Most G 9 E is due to unequal variance between seasons, because the spring cohort harbours little genetic variance. Despite their different season lengths, the cohorts do not differ in flower number (fecundity).Heterogeneous environments with unpredictable risks may maintain promiscuous germination, which then affects flowering time. Therefore, if selection at particular life stages changes with climate change, there may be consequences for the entire life cycle.

show abstract

Section: Discussionmentioning

confidence: 99%

Environmental heterogeneity generates intrapopulation variation in life‐history traits in an annual plant

2019

View full text Add to dashboard Cite

show abstract

“…Models of floral longevity have assumed allocation of limited resources to either floral maintenance or construction of new flowers [2]. A trade-off likely exists between flower longevity and flower number [19,31], but it may occur between flower longevity and flower size for A. gymnandrum.…”

Section: Discussionmentioning

confidence: 99%

“…As a part of the flower display trait, plastic floral longevity in response to variable environmental conditions can favour fitness accrual rates and would therefore be adaptive [2,11,19]. In dichogamous species with separate male and female phases, the duration of the sex phases may be more plastic and can also be optimized by selection to balance pollen transfer and floral maintenance costs.…”

Section: Introductionmentioning

confidence: 99%

Phenological variation of flower longevity and duration of sex phases in a protandrous alpine plant: potential causes and fitness significance

et al. 2020

View full text Add to dashboard Cite

Background: Flower longevity plays an important role in pollen dispersal and reproductive success in plants. In dichogamous plants, the duration of anthesis as well as the time allocated to male and female functions can vary in response to intrinsic factors (e.g., flowering time and resource allocation) and pollination context along a growth season. However, the fitness consequences of phenological dynamics have rarely been examined. This study aims to unravel the potential causes driving variation in flower longevity, duration of sex phases, and phenotypic sex during a flowering season of strongly protandrous Aconitum gymnandrum, and particularly reproductive consequences of the phenological pattern. Results: Population floral sex ratio shifted from completely male at the beginning to completely female at the end of the season, as is common in other protandrous plants. Phenological dynamics of the floral sex ratio and the duration of sex phases caused a shift from femaleness to maleness in the mean phenotypic sex over the whole season. Floral longevity was negatively correlated with flower size and positively affected by temperature. Early flowers within inflorescences rather than early-flowering individuals emphasized the duration of female over male phase. Owing to the dominance of male-phase flowers, early flowering for individual flowers and plants, or female-biased sex resulted in higher pollen deposition per flower and seed set. At the flower level, flower longevity positively affected female reproductive success, while the effect of flower size was negative. By contrast, plant-level female reproductive success was negatively affected by flower longevity but positively correlated to flower size. Conclusions: The major result of this study lies in elucidating the relationship between variation in phenological sex expression and floral longevity and their fitness consequences of protandrous A. gymnandrum. The contrasting results on female fitness for individual flowers and plants contribute to our current understanding of the adaptive significance of floral longevity.

show abstract

“…In this regard, the pattern of how each niche (part) scales with the habitat (whole) determines the type and strength of interspecific interactions. We argue that the allometric scaling of a niche with the habitat as a part-whole relationship can be explained by resource allocation theory [23] that obeys the power law [24].…”

Section: The Qdgm Formulationmentioning

confidence: 93%

Mobile microbiome networks across spatiotemporal gradients

Jiang

Griffin

2020

Preprint

View full text Add to dashboard Cite

Background: The microbiome, a community of microbes that co-reside in biotic or abiotic environments, underlies biogeochemical cycling, plant and animal development, and human health. Increasing evidence shows that much of the role the microbiome plays is executed through complex interactions among microbes. Thus, network reconstruction has been increasingly used as a tool to disentangle internal workings within microbial communities.Results: We developed a general framework for recovering microbial interaction networks from any design of microbial experiment. This framework represents a quasi-dynamic game model (qdGM) derived from the seamless integration of evolutionary game theory and allometric scaling laws. The qdGM can not only characterize how individual microbes act singly, but also reveal how different microbes interact with each other to govern microbial community assembly. Beyond existing approaches that can only identify a single overall microbial network from a number of samples, our framework can track and visualize how interaction networks vary from sample to sample and covert sample-specific (personalized) networks into context-specific networks. More importantly, this framework can reconstruct such mobile microbial networks from steady-state data, facilitating the widespread use of network tools to understand the impact of the microbiome on natural processes.Conclusions: As proof of concept, we used the new framework to analyze human gut microbiota data and interspecific animal-associated microbiota data. Mobile networks reconstructed from each dataset can characterize previously unknown mechanisms that drive the change of microbial interaction architecture and organization along spatiotemporal gradients. This framework provides a tool to generate process-specific microbiome networks that can be readily translated into various biotechnological applications and evolutionary studies.

show abstract

Context‐dependency of resource allocation trade‐offs highlights constraints to the evolution of floral longevity in a monocarpic herb

Cited by 18 publications

References 104 publications

Environmental heterogeneity generates intrapopulation variation in life‐history traits in an annual plant

Environmental heterogeneity generates intrapopulation variation in life‐history traits in an annual plant

Phenological variation of flower longevity and duration of sex phases in a protandrous alpine plant: potential causes and fitness significance

Mobile microbiome networks across spatiotemporal gradients

Contact Info

Product

Resources

About