scholarly journals A hierarchical Bayesian model to investigate trade-offs between growth and reproduction in a long-lived plant

2021 ◽  
Author(s):  
Valentin Journé ◽  
Julien Papaïx ◽  
Emily Walker ◽  
François Courbet ◽  
François Lefèvre ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Late Stage ◽  
Bayesian Model ◽  
Low Density ◽  
Hierarchical Bayesian Model ◽  
Trade Off ◽  
Trade Offs ◽  
Individual Strategies ◽  
Density Population ◽  
Growth And Reproduction

1AbstractA trade-off between growth and fecundity, reflecting the inability of simultaneously investing in both functions when resources are limited, is a fundamental feature of life history theory. This particular trade-off is the result of evolutionary and environmental constrains shaping reproductive and growth traits, but it remains difficult to pinpoint in natural populations of long-lived plants. We developed a hierarchical Bayesian model to estimate the inter-individual correlation among growth and reproduction, using observations at individual level over several years combined with resource simulations from an ecophysiological-based model (CASTANEA). In the Bayesian model, the resource, simulated by CASTANEA and incorporated as a latent variable, is allocated to tree growth, reproductive buds initiation and fruit maturation. Then, we used individual random effects correlated among energetic sinks to investigate potential trade-offs. We applied this original approach to a Mediterranean coniferous tree, Atlas Cedar (Cedrus atlantica), at two contrasted levels of competition, high versus low density population. We found that trees initializing many reproductive buds had a higher growth. Moreover, a negative correlation was detected between growth and fruit survival during maturation. Finally, trees investing more resource to maturate fruits initiated less reproductive buds. The level of competition did not impact the sign of these three correlations, but changed the level of resource allocation: low density population favored growth whereas high density favored reproduction. The level of resource have an impact on individual strategies. This new modeling framework allowed us to detect various individual strategies of resource allocation to growth versus late-stage reproduction on the one hand, and to early-versus late-stage reproduction on the other hand. Moreover, the sign of the correlation between growth and reproductive traits depends on the stage of reproduction considered. Hence, we suggest that the investigation of potential trade-offs between growth and reproduction requires to integrate the dynamics of resource and sink’s phenology, from initiation to maturation of reproductive organs.

scholarly journals Resource allocation trade-offs in a mast-seeding conifer: Piñon pine prioritizes reproduction over defense

AoB Plants ◽  
2019 ◽  
Author(s):  
Miranda D Redmond ◽  
Thomas Seth Davis ◽  
Scott M Ferrenberg ◽  
Andreas P Wion
Keyword(s):  
Resource Allocation ◽  
Tree Growth ◽  
Mast Seeding ◽  
Central Component ◽  
Trade Off ◽  
Cone Production ◽  
Resin Duct ◽  
Fitness Traits ◽  
Trade Offs ◽  
Increased Risk

Abstract The cost of plant reproduction or defense at the expense of other fitness traits is a central component of life history theory. Yet the three central resource allocation pathways of growth, reproduction, and defense have rarely been assessed simultaneously nor across individual to landscape scales. This information is critical towards identifying the physiological, environmental, and genetic mechanisms underpinning resource allocation. This study assessed trade-offs in resource allocation between tree growth, defense, and reproduction across scales among piñon pine (Pinusedulis), a widespread mast-seeding conifer of the southwestern USA. Time series (2004-2016) of tree growth (radial and primary shoot growth), defense (resin duct production; a key constitutive defense for this species), and cone production among individual trees from populations across a broad environmental gradient were used to investigate these trade-offs in resource allocation across three scales: individual, population, and landscape. We found evidence for a defense-reproduction trade-off among individuals whereby total resin duct area in annual xylem rings was lower during years of above average cone production. Despite variability in cone and resin duct production across trees within a population and across populations, there was no association between these fitness traits at either of those scales. There was no evidence of trade-offs between cone production and growth at any scales measured, whereas resin duct production and growth were positively related at all scales. Our study suggests that a strategic trade-off occurs whereby investment into defense is temporarily curtailed to favor reproduction, despite increased risk of exposure to natural enemies and the ability of piñon pine to simultaneously allocate carbon to growth and defense. Our study provides new insights into physiological expressions of growth, defense, and reproduction over time in this long-lived masting conifer and indicates the presence of trade-offs with direct importance for individual fitness and population dynamics under global change.

scholarly journals Glimpsing the Compositions of Sub-Neptune-Size Exoplanets

2013 ◽  
Vol 8 (S299) ◽  
pp. 247-251 ◽  
Author(s):  
Leslie A. Rogers
Keyword(s):  
Bayesian Model ◽  
Preliminary Analysis ◽  
Statistical Approach ◽  
Low Density ◽  
Hierarchical Bayesian ◽  
Hierarchical Bayesian Model ◽  
Transiting Planets ◽  
Current Sample ◽  
Rocky Planets ◽  
Model Approach

AbstractThe growing number of transiting planets with mass constraints opens the possibility of applying a statistical approach to learn about the underlying population of planet compositions. We focus on the intriguing transition between rocky exoplanets and planets with voluminous gas layers, and explore how the current census of sub-Neptune-size exoplanets constrains the maximum radii of rocky planets. We outline a hierarchical Bayesian model approach to infer the fraction of planets that are dense enough to be rocky (as a function of planet radius). A preliminary analysis of the current sample of planets with mass and radius constraints reveals that most planets larger than 1.9 R⊕ are too low density to be comprised of Fe and silicates alone.

scholarly journals Telomeres positively correlate with pace-of-life and elongate with age in a wild mammal

2021 ◽  
Author(s):  
Mathilde Tissier ◽  
Patrick Bergeron ◽  
Dany Garant ◽  
Sandrine Zahn ◽  
Francois Criscuolo ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Life History ◽  
Life Histories ◽  
Life History Strategies ◽  
Trade Off ◽  
Pace Of Life ◽  
Trade Offs ◽  
Proactive Behaviour ◽  
Anti Cancer ◽  
Fast Pace

Understanding ageing and the diversity of life histories is a cornerstone in biology. Telomeres, the protecting caps of chromosomes, are thought to be involved in ageing, cancer risks and to modulate life-history strategies. They shorten with cell division and age in somatic tissues of most species, possibly limiting lifespan. The resource allocation trade-off hypothesis predicts that short telomeres have thus co-evolved with early reproduction, proactive behaviour and reduced lifespan, i.e. a fast Pace-of-Life Syndrome (POLS). Conversely, since short telomeres may also reduce the risks of cancer, the anti-cancer hypothesis advances that they should be associated with slow POLS. Conclusion on which hypothesis best supports the role of telomeres as mediators of life-history strategies is hampered by a lack of study on wild short-lived vertebrates, apart from birds. Using seven years of data on wild Eastern chipmunks Tamias striatus, we highlighted that telomeres elongate with age and do not limit lifespan in this species. Furthermore, short telomeres correlated with a slow POLS in a sex-specific way. Females with short telomeres had a delayed age at first breeding and a lower fecundity rate than females with long telomeres, whereas those differences were not recorded in males. Our findings support most predictions adapted from the anti-cancer hypothesis, but none of those made under the resource allocation trade-off hypothesis. Results are in line with an increasing body of evidence suggesting that resource allocation trade-offs alone cannot explaining the diversity of telomere length in adult somatic cells and life-histories observed across the tree of life.

scholarly journals Fish face a trade-off between ‘eating big’ for growth efficiency and ‘eating small’ to retain aerobic capacity

2017 ◽  
Vol 13 (9) ◽  
pp. 20170298 ◽  
Author(s):  
Tommy Norin ◽  
Timothy D. Clark
Keyword(s):  
Prey Size ◽  
Growth Efficiency ◽  
Specific Dynamic Action ◽  
Meal Size ◽  
Large Prey ◽  
Lates Calcarifer ◽  
Trade Off ◽  
Trade Offs ◽  
Size Growth ◽  
Growth And Reproduction

Feeding provides the necessary energy to fuel all fitness-related processes including activity, growth and reproduction. Nevertheless, prey consumption and digestive processes can have physical and physiological trade-offs with other critical functions, many of which are not clearly understood. Using an ambush predator, barramundi ( Lates calcarifer ), fed meals ranging 0.6–3.4% of body mass, we examined interrelations between meal size, growth efficiency and surplus aerobic metabolic capacity (aerobic scope, AS). Large meals required a greater absolute investment of energy to process (a larger so-called specific dynamic action, SDA), but the percentage of digestible meal energy required in the SDA response (SDA coefficient) decreased with increasing meal size. Combined with the findings that growth rate and growth efficiency also increased with food intake, our results demonstrate that it is energetically advantageous for fish to select large prey. However, following a large meal, SDA processes occupied up to 77% of the available AS, indicating that other oxygen-demanding activities like swimming may be compromised while large meals are processed. This trade-off between meal size and AS suggests that fishes like barramundi would benefit from regulating prey size based on imminent requirements and threats.

scholarly journals Resource allocation during ontogeny is influenced by genetic, developmental and ecological factors in the horned beetle, Onthophagus taurus

2014 ◽  
Vol 281 (1793) ◽  
pp. 20141625 ◽  
Author(s):  
Daniel B. Schwab ◽  
Armin P. Moczek
Keyword(s):  
Resource Allocation ◽  
Natural Populations ◽  
Ecological Factors ◽  
Developmental Genetic ◽  
Trade Off ◽  
Ecological Conditions ◽  
Genetic Manipulations ◽  
Onthophagus Taurus ◽  
Trade Offs ◽  
Horned Beetle

Resource allocation trade-offs arise when developing organs are in competition for a limited pool of resources to sustain growth and differentiation. Such competition may constrain the maximal size to which structures can grow and may force a situation in which the evolutionary elaboration of one structure may only be possible at the expense of another. However, recent studies have called into question both the consistency and evolutionary importance of resource allocation trade-offs. This study focuses on a well-described trade-off between the horns and eyes of Onthophagus beetles and assesses the degree to which it is influenced by genetic, developmental and ecological conditions. Contrary to expectations, we observed that trade-off signatures (i) were mostly absent within natural populations, (ii) mostly failed to match naturally evolved divergences in horn investment among populations, (iii) were subject to differential changes in F 1 populations derived from divergent field populations and (iv) remained largely unaffected by developmental genetic manipulations of horn investment. Collectively, our results demonstrate that populations subject to different ecological conditions exhibit different patterns of, and differential plasticity in, resource allocation. Further, variation in ecological conditions, rather than canalized developmental mechanisms, may determine whether and to what degree morphological structures engage in resource allocation trade-offs.

Dual Goals for Speed and Accuracy on the Same Performance Task

2012 ◽  
Vol 11 (3) ◽  
pp. 118-126 ◽  
Author(s):  
Olive Emil Wetter ◽  
Jürgen Wegge ◽  
Klaus Jonas ◽  
Klaus-Helmut Schmidt
Keyword(s):  
Memory Scanning ◽  
Performance Task ◽  
Performance Tasks ◽  
Trade Off ◽  
Test Experiment ◽  
Trade Offs ◽  
New Finding ◽  
Sternberg Paradigm ◽  
Speed Accuracy ◽  
Speed And Accuracy

In most work contexts, several performance goals coexist, and conflicts between them and trade-offs can occur. Our paper is the first to contrast a dual goal for speed and accuracy with a single goal for speed on the same task. The Sternberg paradigm (Experiment 1, n = 57) and the d2 test (Experiment 2, n = 19) were used as performance tasks. Speed measures and errors revealed in both experiments that dual as well as single goals increase performance by enhancing memory scanning. However, the single speed goal triggered a speed-accuracy trade-off, favoring speed over accuracy, whereas this was not the case with the dual goal. In difficult trials, dual goals slowed down scanning processes again so that errors could be prevented. This new finding is particularly relevant for security domains, where both aspects have to be managed simultaneously.

The Effects of Decision Time on Perceptions of Decisions and Decision Makers in (Moral) Trade-Off Scenarios

2019 ◽  
Author(s):  
Anna Katharina Spälti ◽  
Mark John Brandt ◽  
Marcel Zeelenberg
Keyword(s):  
Decision Process ◽  
Decision Time ◽  
Decision Makers ◽  
Process Information ◽  
Total N ◽  
Trade Off ◽  
Financial Gain ◽  
Trade Offs ◽  
Sacred Values ◽  
Moral Context

People often have to make trade-offs. We study three types of trade-offs: 1) "secular trade-offs" where no moral or sacred values are at stake, 2) "taboo trade-offs" where sacred values are pitted against financial gain, and 3) "tragic trade-offs" where sacred values are pitted against other sacred values. Previous research (Critcher et al., 2011; Tetlock et al., 2000) demonstrated that tragic and taboo trade-offs are not only evaluated by their outcomes, but are also evaluated based on the time it took to make the choice. We investigate two outstanding questions: 1) whether the effect of decision time differs for evaluations of decisions compared to decision makers and 2) whether moral contexts are unique in their ability to influence character evaluations through decision process information. In two experiments (total N = 1434) we find that decision time affects character evaluations, but not evaluations of the decision itself. There were no significant differences between tragic trade-offs and secular trade-offs, suggesting that the decisions structure may be more important in evaluations than moral context. Additionally, the magnitude of the effect of decision time shows us that decision time, may be of less practical use than expected. We thus urge, to take a closer examination of the processes underlying decision time and its perception.

Predicting Undesired Treatment Outcome in Mental Healthcare: Machine Learning Study (Preprint)

2019 ◽  
Author(s):  
Kasper Van Mens ◽  
Joran Lokkerbol ◽  
Richard Janssen ◽  
Robert de Lange ◽  
Bea Tiemens
Keyword(s):  
Machine Learning ◽  
Treatment Outcome ◽  
Mental Health Treatment ◽  
Mental Healthcare ◽  
Machine Learning Algorithms ◽  
Gradient Boosting ◽  
Trade Off ◽  
Trade Offs ◽  
Outcome Monitoring ◽  
Extreme Gradient Boosting

BACKGROUND It remains a challenge to predict which treatment will work for which patient in mental healthcare. OBJECTIVE In this study we compare machine algorithms to predict during treatment which patients will not benefit from brief mental health treatment and present trade-offs that must be considered before an algorithm can be used in clinical practice. METHODS Using an anonymized dataset containing routine outcome monitoring data from a mental healthcare organization in the Netherlands (n = 2,655), we applied three machine learning algorithms to predict treatment outcome. The algorithms were internally validated with cross-validation on a training sample (n = 1,860) and externally validated on an unseen test sample (n = 795). RESULTS The performance of the three algorithms did not significantly differ on the test set. With a default classification cut-off at 0.5 predicted probability, the extreme gradient boosting algorithm showed the highest positive predictive value (ppv) of 0.71(0.61 – 0.77) with a sensitivity of 0.35 (0.29 – 0.41) and area under the curve of 0.78. A trade-off can be made between ppv and sensitivity by choosing different cut-off probabilities. With a cut-off at 0.63, the ppv increased to 0.87 and the sensitivity dropped to 0.17. With a cut-off of at 0.38, the ppv decreased to 0.61 and the sensitivity increased to 0.57. CONCLUSIONS Machine learning can be used to predict treatment outcomes based on routine monitoring data.This allows practitioners to choose their own trade-off between being selective and more certain versus inclusive and less certain.

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