Growth–defense trade-offs shape population genetic composition in an iconic forest tree species

2021 ◽  
Vol 118 (37) ◽  
pp. e2103162118 ◽  
Author(s):  
Olivia L. Cope ◽  
Ken Keefover-Ring ◽  
Eric L. Kruger ◽  
Richard L. Lindroth
Keyword(s):  
Evolutionary Dynamics ◽  
Evolutionary Ecology ◽  
Functional Trait ◽  
Forest Tree ◽  
Ecological Interactions ◽  
Trait Variation ◽  
Trade Offs ◽  
Spatiotemporal Scales ◽  
Evolutionary Consequences ◽  
Selection Of

All organisms experience fundamental conflicts between divergent metabolic processes. In plants, a pivotal conflict occurs between allocation to growth, which accelerates resource acquisition, and to defense, which protects existing tissue against herbivory. Trade-offs between growth and defense traits are not universally observed, and a central prediction of plant evolutionary ecology is that context-dependence of these trade-offs contributes to the maintenance of intraspecific variation in defense [Züst and Agrawal, Annu. Rev. Plant Biol., 68, 513–534 (2017)]. This prediction has rarely been tested, however, and the evolutionary consequences of growth–defense trade-offs in different environments are poorly understood, especially in long-lived species [Cipollini et al., Annual Plant Reviews (Wiley, 2014), pp. 263–307]. Here we show that intraspecific trait trade-offs, even when fixed across divergent environments, interact with competition to drive natural selection of tree genotypes corresponding to their growth–defense phenotypes. Our results show that a functional trait trade-off, when coupled with environmental variation, causes real-time divergence in the genetic architecture of tree populations in an experimental setting. Specifically, competitive selection for faster growth resulted in dominance by fast-growing tree genotypes that were poorly defended against natural enemies. This outcome is a signature example of eco-evolutionary dynamics: Competitive interactions affected microevolutionary trajectories on a timescale relevant to subsequent ecological interactions [Brunner et al., Funct. Ecol. 33, 7–12 (2019)]. Eco-evolutionary drivers of tree growth and defense are thus critical to stand-level trait variation, which structures communities and ecosystems over expansive spatiotemporal scales.

The shape of a defense-growth trade-off governs seasonal trait dynamics in natural phytoplankton

2018 ◽  
Author(s):  
Elias Ehrlich ◽  
Nadja J. Kath ◽  
Ursula Gaedke
Keyword(s):  
Fitness Landscape ◽  
Functional Trait ◽  
Grazing Pressure ◽  
Trait Variation ◽  
Trade Off ◽  
Community Persistence ◽  
Trade Offs ◽  
Combining Data ◽  
Persistence Theory

Functional trait compositions of communities can adapt to altered environmental conditions ensuring community persistence. Theory predicts that the shape of trade-offs between traits crucially affects these trait dynamics, but its empirical verification from the field is missing. Here, we show how the shape of a defense-growth trade-off governs seasonal trait dynamics of a natural community, using high-frequency, long-term measurements of phytoplankton from Lake Constance. As expected from the lab-derived concave trade-off curve, we observed an alternating dominance of several fast-growing species with intermediate defense levels and gradual changes of the biomass-trait distribution due to seasonally changing grazing pressure. By combining data and modelling, we obtain mechanistic insights on the underlying fitness landscape, and show that low fitness differences can maintain trait variation along the trade-off curve. We provide firm evidence for a frequently assumed trade-off and conclude that quantifying its shape allows to understand environmentally driven trait changes within communities.

scholarly journals Intraspecific root and leaf trait variation with tropical forest successional status: consequences for community-weighted patterns

2019 ◽  
Author(s):  
J. Aaron Hogan ◽  
Oscar J. Valverde-Barrantes ◽  
Qiong Ding ◽  
Han Xu ◽  
Christopher Baraloto
Keyword(s):  
Soil Fertility ◽  
Tropical Forest ◽  
Leaf Area ◽  
Specific Root Length ◽  
Functional Trait ◽  
Primary Forest ◽  
List Type ◽  
Forest Age ◽  
Trait Variation ◽  
Trade Offs

SummaryQuantifying the dimensions and magnitude of intraspecific root trait variation is key to understanding the functional trade-offs in the belowground plant strategies of tropical forest trees. Additionally, accurately measuring how belowground functional trait variation relates to soil environment and forest age is crucial to tropical forest modeling efforts.We sampled leaf and root morphologies from 423 juvenile trees of 72 species from 14 Angiosperm families along a 6.6 km transect that corresponded to an environmental gradient in decreasing soil fertility and texture with increasing forest age.We observed within-lineage conservative functional trait-shifts in root and leaf morphological traits along the transect. From secondary to primary forest, average leaf area increased 7 cm2and average root system diameter increased 0.4 mm. Mean specific leaf area decreased by 0.8 m2kg−1, specific root length decreased by 3.5 m kg−1, and root branching intensity decreased by 0.3 tips cm−1. Leaf thickness and root tissue density showed no change.We coupled trait measurements to a network of 164 1/16th-ha plots across a Chinese tropical forest reserve, to scale individual trait measurements up to the community-level, accounting for forest age.For most traits, intraspecific trait variation negatively covaried with species compositional turnover between plots in younger versus older forest to compound and create greater community-weighted differences in trait values than would be observed if intraspecific variation in traits with forest age was not accounted for.SummaryRoot morphologies are variable with local scale variation in soil fertility and texture. Accurately understanding broader (i.e. forest)-scale patterns in root functional traits, requires attention to underlying environmental variation in soil resources, which interacts with environmental filtering of plant communities.

scholarly journals Species matter for predicting the functioning of evolving microbial communities

2019 ◽  
Author(s):  
Timothy Giles Barraclough
Keyword(s):  
Microbial Communities ◽  
Resource Use ◽  
Bacterial Communities ◽  
Evolutionary Dynamics ◽  
Ecological Interactions ◽  
Community Functioning ◽  
Trade Offs ◽  
As Species ◽  
Multiple Species ◽  
Digestive Health

ABSTRACTHumans depend on microbial communities for numerous ecosystem services such as global nutrient cycles, plant growth and their digestive health. Yet predicting dynamics and functioning of these complex systems is hard, making interventions to enhance functioning harder still. One simplifying approach is to assume that functioning can be predicted from the set of enzymes present in a community. Alternatively, ecological and evolutionary dynamics of species, which depend on how enzymes are packaged among species, might be vital for predicting community functioning. I investigate these alternatives by extending classical chemostat models of bacterial growth to multiple species that evolve in their use of chemical resources. Ecological interactions emerge from patterns of resource use, which change as species evolve in their allocation of metabolic enzymes. Measures of community functioning derive in turn from metabolite concentrations and bacterial density. Although the model shows considerable functional redundancy, species packaging does matter by introducing constraints on whether enzyme levels can reach optimum levels for the whole system. Evolution can either promote or reduce functioning compared to purely ecological models, depending on the shape of trade-offs in resource use. The model provides baseline theory for interpreting emerging data on evolution and functioning in real bacterial communities.

scholarly journals Steering ecological-evolutionary dynamics during artificial selection of microbial communities

2018 ◽  
Author(s):  
Li Xie ◽  
Wenying Shou
Keyword(s):  
Microbial Communities ◽  
Artificial Selection ◽  
Evolutionary Dynamics ◽  
Ecological Interactions ◽  
Evolutionary Trajectory ◽  
Community Function ◽  
Selection Strategies ◽  
Effective Selection ◽  
Orthogonal Components ◽  
Selection Of

AbstractMicrobial communities often perform important functions that arise from interactions among member species. Community functions can be improved via artificial selection: Many communities are repeatedly grown, mutations arise, and communities with the highest desired function are chosen to reproduce where each is partitioned into multiple offspring communities for the next cycle. Since selection efficacy is often unimpressive in published experiments and since multiple experimental parameters need to be tuned, we sought to use computer simulations to learn how to design effective selection strategies. We simulated community selection to improve a community function that requires two species and imposes a fitness cost on one of the species. This simplified case allowed us to distill community function down to two fundamental and orthogonal components: a heritable determinant and a nonheritable determinant. We then visualize a “community function landscape” relating community function to these two determinants, and demonstrate that the evolutionary trajectory on the landscape is restricted along a path designated by ecological interactions. This path can prevent the attainment of maximal community function, and trap communities in landscape locations where community function has low heritability. Exploiting these observations, we devise a species spiking approach to shift the path to improve community function heritability and consequently selection efficacy. We show that our approach is applicable to communities with complex and unknown function landscapes.

scholarly journals Predator coevolution and prey trait variability determine species coexistence

2019 ◽  
Vol 286 (1902) ◽  
pp. 20190245 ◽  
Author(s):  
Thomas Scheuerl ◽  
Johannes Cairns ◽  
Lutz Becks ◽  
Teppo Hiltunen
Keyword(s):  
Evolutionary Dynamics ◽  
Biological Diversity ◽  
Species Coexistence ◽  
Ecological Interactions ◽  
Trait Variation ◽  
Ecological Processes ◽  
History Of ◽  
Evolutionary Trajectories ◽  
Ecological Mechanisms

Predation is one of the key ecological mechanisms allowing species coexistence and influencing biological diversity. However, ecological processes are subject to contemporary evolutionary change, and the degree to which predation affects diversity ultimately depends on the interplay between evolution and ecology. Furthermore, ecological interactions that influence species coexistence can be altered by reciprocal coevolution especially in the case of antagonistic interactions such as predation or parasitism. Here we used an experimental evolution approach to test for the role of initial trait variation in the prey population and coevolutionary history of the predator in the ecological dynamics of a two-species bacterial community predated by a ciliate. We found that initial trait variation both at the bacterial and ciliate level enhanced species coexistence, and that subsequent trait evolutionary trajectories depended on the initial genetic diversity present in the population. Our findings provide further support to the notion that the ecology-centric view of diversity maintenance must be reinvestigated in light of recent findings in the field of eco-evolutionary dynamics.

The predator-dependent replicator dynamics

2021 ◽  
Author(s):  
Ian Magalhaes Braga ◽  
Lucas Wardil
Keyword(s):  
Time Scales ◽  
Evolutionary Dynamics ◽  
Replicator Dynamics ◽  
Capture Rate ◽  
Evolutionary Game ◽  
Ecological Interactions ◽  
Evolutionary Time ◽  
Predator Prey ◽  
Environmental Interactions ◽  
Selection Of

Abstract Ecological interactions are central to understanding evolution. For example, Darwin noticed that the beautiful colours of the male peacock increase the chance of successful mating. However, the colours can be a threat because of the increased probability of being caught by predators. Eco-evolutionary dynamics takes into account environmental interactions to model the process of evolution. The selection of prey types in the presence of predators may be subjected to pressure on both reproduction and survival. Here, we analyze the evolutionary game dynamics of two types of prey in the presence of predators. We call this model \textit{the predator-dependent replicator dynamics}. If the evolutionary time scales are different, the number of predators can be assumed constant, and the traditional replicator dynamics is recovered. However, if the time scales are the same, we end up with sixteen possible dynamics: the combinations of four reproduction’s games with four predation’s games. We analyze the dynamics and calculate conditions for the coexistence of prey and predator. The main result is that predators can change the equilibrium of the traditional replicator dynamics. For example, the presence of predators can induce polymorphism in prey if one type of prey is more attractive than the other, with the prey ending with a lower capture rate in this new equilibrium. Lastly, we provide two illustrations of the dynamics, which can be seen as rapid feedback responses in a predator-prey evolutionary arm’s race.

scholarly journals Integrating transcriptomic network reconstruction and QTL analyses reveals mechanistic connections between genomic architecture and Brassica rapa development

2019 ◽  
Author(s):  
Robert L. Baker ◽  
Wen Fung Leong ◽  
Marcus T. Brock ◽  
Matthew J. Rubin ◽  
R. J. Cody Markelz ◽  
...  
Keyword(s):  
Brassica Rapa ◽  
Evolutionary Ecology ◽  
Final Height ◽  
Growth Curves ◽  
Trait Variation ◽  
Growing Seasons ◽  
Trade Offs ◽  
Structural Trait ◽  
Relevant Field ◽  
Developmental Dynamics

ABSTRACTPlant developmental dynamics can be heritable, genetically correlated with fitness and yield, and undergo selection. Therefore, characterizing the mechanistic connections between the genetic architecture governing plant development and the resulting ontogenetic dynamics of plants in field settings is critically important for agricultural production and evolutionary ecology. We use a hierarchical Bayesian Function-Valued Trait (FVT) approach to estimate Brassica rapa growth curves throughout ontogeny, across two treatments and in two growing seasons. We find that the shape of growth curves is relatively plastic across environments compared to final height, and that there are trade-offs between growth rate and duration. We determined that combining FVT Quantitative Trait Loci (QTL) and genes/eigengene expression identified via transcriptomic co-expression network reconstructions best characterized phenotypic variation. Further, targeted eQTL analyses identified regulatory hotspots that colocalized with FVT QTL and co-expression network identified genes and mechanistically link FVT QTL with structural trait variation throughout development in agroecologically relevant field settings.

Addressing pose estimation issues for machine vision based UAV autonomous serial refuelling

2007 ◽  
Vol 111 (1120) ◽  
pp. 389-396 ◽  
Author(s):  
G. Campa ◽  
M. R. Napolitano ◽  
M. Perhinschi ◽  
M. L. Fravolini ◽  
L. Pollini ◽  
...  
Keyword(s):  
Machine Vision ◽  
Pose Estimation ◽  
Estimation Algorithm ◽  
Computational Effort ◽  
Unmanned Aircraft ◽  
Light Sources ◽  
Estimation Algorithms ◽  
Trade Offs ◽  
Labeling Algorithms ◽  
Selection Of

Abstract This paper describes the results of an effort on the analysis of the performance of specific ‘pose estimation’ algorithms within a Machine Vision-based approach for the problem of aerial refuelling for unmanned aerial vehicles. The approach assumes the availability of a camera on the unmanned aircraft for acquiring images of the refuelling tanker; also, it assumes that a number of active or passive light sources – the ‘markers’ – are installed at specific known locations on the tanker. A sequence of machine vision algorithms on the on-board computer of the unmanned aircraft is tasked with the processing of the images of the tanker. Specifically, detection and labeling algorithms are used to detect and identify the markers and a ‘pose estimation’ algorithm is used to estimate the relative position and orientation between the two aircraft. Detailed closed-loop simulation studies have been performed to compare the performance of two ‘pose estimation’ algorithms within a simulation environment that was specifically developed for the study of aerial refuelling problems. Special emphasis is placed on the analysis of the required computational effort as well as on the accuracy and the error propagation characteristics of the two methods. The general trade offs involved in the selection of the pose estimation algorithm are discussed. Finally, simulation results are presented and analysed.

A Spectral Optimization Algorithm for Multi-Objective Prototype Selection

1995 ◽  
Author(s):  
Andy Dong ◽  
Alice M. Agogino
Keyword(s):  
Optimization Algorithm ◽  
Parametric Design ◽  
Selection Process ◽  
Objective Evaluation ◽  
Design Synthesis ◽  
Multi Objective ◽  
Trade Offs ◽  
Spectral Optimization ◽  
The Right ◽  
Selection Of

Abstract In design synthesis, engineering prototypes make an ideal representation medium for preliminary designs. Unlike parametric design wherein a pre-specified design is parametrically varied, design synthesis demands artistic creativity and engineering experience to transform the previously known components, relationships and designs into a new form. The process compels the designer to ascertain which prototypes will, in some sense, best satisfy the design task. The challenge in this assignment lies in selecting the “right” design prototype. This selection process typically entails an objective evaluation of different designs that perform the same functions or have similar intended behavior and comparing trade-offs between alternate designs. This paper introduces a multi-objective spectral optimization algorithm for the selection of design prototypes based upon their functional representations. The optimization algorithm returns an index of rank, scoring the functional similarity of the proposed design to the goal design. Two illustrative examples apply the algorithm to the selection of a heat fin and beam.

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