scholarly journals The offspring quantity–quality trade-off and human fertility variation

2016 ◽  
Vol 371 (1692) ◽  
pp. 20150145 ◽  
Author(s):  
David W. Lawson ◽  
Monique Borgerhoff Mulder
Keyword(s):  
Evolutionary Ecology ◽  
Reproductive Behaviour ◽  
Low Fertility ◽  
Human Reproduction ◽  
Trade Off ◽  
Trade Offs ◽  
Human Fertility ◽  
Fertility Variation ◽  
Fertility Limitation ◽  
Economic Perspectives

The idea that trade-offs between offspring quantity and quality shape reproductive behaviour has long been central to economic perspectives on fertility. It also has a parallel and richer theoretical foundation in evolutionary ecology. We review the application of the quantity–quality trade-off concept to human reproduction, emphasizing distinctions between clutch size and lifetime fertility, and the wider set of forces contributing to fertility variation in iteroparous and sexually reproducing species like our own. We then argue that in settings approximating human evolutionary history, several factors limit costly sibling competition. Consequently, while the optimization of quantity–quality trade-offs undoubtedly shaped the evolution of human physiology setting the upper limits of reproduction, we argue it plays a modest role in accounting for socio-ecological and individual variation in fertility. Only upon entering the demographic transition can fertility limitation be clearly interpreted as strategically orientated to advancing offspring quality via increased parental investment per child, with low fertility increasing descendant socio-economic success, although not reproductive success. We conclude that existing economic and evolutionary literature has often overemphasized the centrality of quantity–quality trade-offs to human fertility variation and advocate for the development of more holistic frameworks encompassing alternative life-history trade-offs and the evolved mechanisms guiding their resolution.

scholarly journals Experimental evolution of parasite life-history traits in Strongyloides ratti (Nematoda)

2007 ◽  
Vol 274 (1617) ◽  
pp. 1467-1474 ◽  
Author(s):  
Steve Paterson ◽  
Rebecca Barber
Keyword(s):  
Life History ◽  
Experimental Evolution ◽  
Life History Traits ◽  
Evolutionary Ecology ◽  
Response To Selection ◽  
Trade Off ◽  
Density Dependent ◽  
Conspecific Density ◽  
Trade Offs ◽  
General Prediction

Evolutionary ecology predicts that parasite life-history traits, including a parasite's survivorship and fecundity within a host, will evolve in response to selection and that their evolution will be constrained by trade-offs between traits. Here, we test these predictions using a nematode parasite of rats, Strongyloides ratti , as a model. We performed a selection experiment by passage of parasite progeny from either early in an infection (‘fast’ lines) or late in an infection (‘slow’ lines). We found that parasite fecundity responded to selection but that parasite survivorship did not. We found a trade-off mediated via conspecific density-dependent constraints; namely, that fast lines exhibit higher density-independent fecundity than slow lines, but fast lines suffered greater reduction in fecundity in the presence of density-dependent constraints than slow lines. We also found that slow lines both stimulate a higher level of IgG1, which is a marker for a Th2-type immune response, and show less of a reduction in fecundity in response to IgG1 levels than for fast lines. Our results confirm the general prediction that parasite life-history traits can evolve in response to selection and indicate that such evolutionary responses may have significant implications for the epidemiology of infectious disease.

scholarly journals Parental investment and the optimization of human family size

2011 ◽  
Vol 366 (1563) ◽  
pp. 333-343 ◽  
Author(s):  
David W. Lawson ◽  
Ruth Mace
Keyword(s):  
Family Size ◽  
Parental Investment ◽  
Resource Competition ◽  
Reproductive Behaviour ◽  
Reproductive Rate ◽  
Low Fertility ◽  
Individual Level ◽  
Offspring Number ◽  
Adaptive Models ◽  
Fertility Limitation

Human reproductive behaviour is marked by exceptional variation at the population and individual level. Human behavioural ecologists propose adaptive hypotheses to explain this variation as shifting phenotypic optima in relation to local socioecological niches. Here we review evidence that variation in fertility (offspring number), in both traditional and modern industrialized populations, represents optimization of the life-history trade-off between reproductive rate and parental investment. While a reliance on correlational methods suggests the true costs of sibling resource competition are often poorly estimated, a range of anthropological and demographic studies confirm that parents balance family size against offspring success. Evidence of optimization is less forthcoming. Declines in fertility associated with modernization are particularly difficult to reconcile with adaptive models, because fertility limitation fails to enhance offspring reproductive success. Yet, considering alternative measures, we show that modern low fertility confers many advantages on offspring, which are probably transmitted to future generations. Evidence from populations that have undergone or initiated demographic transition indicate that these rewards to fertility limitation fall selectively on relatively wealthy individuals. The adaptive significance of modern reproductive behaviour remains difficult to evaluate, but may be best understood in response to rising investment costs of rearing socially and economically competitive offspring.

scholarly journals The life-history trade-off between fertility and child survival

2012 ◽  
Vol 279 (1748) ◽  
pp. 4755-4764 ◽  
Author(s):  
David W. Lawson ◽  
Alexandra Alvergne ◽  
Mhairi A. Gibson
Keyword(s):  
Life History ◽  
Parental Investment ◽  
Socioeconomic Development ◽  
Child Survival ◽  
Relative Magnitude ◽  
Individual Characteristics ◽  
Human Reproduction ◽  
African Countries ◽  
Trade Off ◽  
Fertility Limitation

Evolutionary models of human reproduction argue that variation in fertility can be understood as the local optimization of a life-history trade-off between offspring quantity and ‘quality’. Child survival is a fundamental dimension of quality in these models as early-life mortality represents a crucial selective bottleneck in human evolution. This perspective is well-rehearsed, but current literature presents mixed evidence for a trade-off between fertility and child survival, and little empirical ground to evaluate how socioecological and individual characteristics influence the benefits of fertility limitation. By compiling demographic survey data, we demonstrate robust negative relationships between fertility and child survival across 27 sub-Saharan African countries. Our analyses suggest this relationship is primarily accounted for by offspring competition for parental investment, rather than by reverse causal mechanisms. We also find that the trade-off increases in relative magnitude as national mortality declines and maternal somatic (height) and extrasomatic (education) capital increase. This supports the idea that socioeconomic development, and associated reductions in extrinsic child mortality, favour reduced fertility by increasing the relative returns to parental investment. Observed fertility, however, falls considerably short of predicted optima for maximizing total offspring survivorship, strongly suggesting that additional unmeasured costs of reproduction ultimately constrain the evolution of human family size.

scholarly journals Selection bias in studies of human reproduction-longevity trade-offs

2017 ◽  
Vol 284 (1868) ◽  
pp. 20172104 ◽  
Author(s):  
Samuli Helle
Keyword(s):  
Selection Bias ◽  
Statistical Power ◽  
Small Sample ◽  
Human Reproduction ◽  
Potential Cost ◽  
Trade Off ◽  
Trade Offs ◽  
High Reproductive Effort ◽  
Small Sample Sizes ◽  
Size Estimates

A shorter lifespan as a potential cost of high reproductive effort in humans has intrigued researchers for more than a century. However, the results have been inconclusive so far and despite strong theoretical expectations we do not currently have compelling evidence for the longevity costs of reproduction. Using Monte Carlo simulation, it is shown here that a common practice in human reproduction-longevity studies using historical data (the most relevant data sources for this question), the omission of women who died prior to menopausal age from the analysis, results in severe underestimation of the potential underlying trade-off between reproduction and lifespan. In other words, assuming that such a trade-off is expressed also during reproductive years, the strength of the trade-off between reproduction and lifespan is progressively weakened when women dying during reproductive ages are sequentially and non-randomly excluded from the analysis. In cases of small sample sizes (e.g. few hundreds of observations), this selection bias by reducing statistical power may even partly explain the null results commonly found in this field. Future studies in this field should thus apply statistical approaches that account for or avoid selection bias in order to recover reliable effect size estimates between reproduction and longevity.

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.

Challenges in the Empirical Study of Global Governance Legitimacy

2018 ◽  
Author(s):  
Steven Bernstein
Keyword(s):  
Empirical Study ◽  
Global Governance ◽  
Research Agenda ◽  
Cultural Factors ◽  
Theory Building ◽  
Trade Off ◽  
Trade Offs ◽  
Different Types ◽  
Political Communities

This commentary discusses three challenges for the promising and ambitious research agenda outlined in the volume. First, it interrogates the volume’s attempts to differentiate political communities of legitimation, which may vary widely in composition, power, and relevance across institutions and geographies, with important implications not only for who matters, but also for what gets legitimated, and with what consequences. Second, it examines avenues to overcome possible trade-offs from gains in empirical tractability achieved through the volume’s focus on actor beliefs and strategies. One such trade-off is less attention to evolving norms and cultural factors that may underpin actors’ expectations about what legitimacy requires. Third, it addresses the challenge of theory building that can link legitimacy sources, (de)legitimation practices, audiences, and consequences of legitimacy across different types of institutions.

scholarly journals Toward Inclusive Landscape Governance in Contested Landscapes: Exploring the Contribution of Participatory Tools in the Upper Suriname River Basin

2021 ◽  
Author(s):  
Lisa Best ◽  
Kimberley Fung-Loy ◽  
Nafiesa Ilahibaks ◽  
Sara O. I. Ramirez-Gomez ◽  
Erika N. Speelman
Keyword(s):  
Land Use ◽  
River Basin ◽  
Scenario Planning ◽  
Community Members ◽  
Trade Off ◽  
3 Dimensional ◽  
Landscape Governance ◽  
Information Tools ◽  
Tribal Communities ◽  
Trade Offs

AbstractNowadays, tropical forest landscapes are commonly characterized by a multitude of interacting institutions and actors with competing land-use interests. In these settings, indigenous and tribal communities are often marginalized in landscape-level decision making. Inclusive landscape governance inherently integrates diverse knowledge systems, including those of indigenous and tribal communities. Increasingly, geo-information tools are recognized as appropriate tools to integrate diverse interests and legitimize the voices, values, and knowledge of indigenous and tribal communities in landscape governance. In this paper, we present the contribution of the integrated application of three participatory geo-information tools to inclusive landscape governance in the Upper Suriname River Basin in Suriname: (i) Participatory 3-Dimensional Modelling, (ii) the Trade-off! game, and (iii) participatory scenario planning. The participatory 3-dimensional modelling enabled easy participation of community members, documentation of traditional, tacit knowledge and social learning. The Trade-off! game stimulated capacity building and understanding of land-use trade-offs. The participatory scenario planning exercise helped landscape actors to reflect on their own and others’ desired futures while building consensus. Our results emphasize the importance of systematically considering tool attributes and key factors, such as facilitation, for participatory geo-information tools to be optimally used and fit with local contexts. The results also show how combining the tools helped to build momentum and led to diverse yet complementary insights, thereby demonstrating the benefits of integrating multiple tools to address inclusive landscape governance issues.

scholarly journals On the effectiveness of tracking and testing in SEIR models for improving health vs. economy trade-offs

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yoav Kolumbus ◽  
Noam Nisan
Keyword(s):  
Additional Parameter ◽  
Patient Privacy ◽  
Economic Costs ◽  
Trade Off ◽  
Seir Model ◽  
Social Question ◽  
Social Distancing ◽  
Trade Offs ◽  
Asymptomatic Individuals ◽  
Testing Policies

AbstractWe study the effectiveness of tracking and testing policies for suppressing epidemic outbreaks. We evaluate the performance of tracking-based intervention methods on a network SEIR model, which we augment with an additional parameter to model pre-symptomatic and asymptomatic individuals, and study the effectiveness of these methods in combination with or as an alternative to quarantine and global lockdown policies. Our focus is on the basic trade-off between human-lives lost and economic costs, and on how this trade-off changes under different quarantine, lockdown, tracking, and testing policies. Our main findings are as follows: (1) Tests combined with patient quarantines reduce both economic costs and mortality, however, an extensive-scale testing capacity is required to achieve a significant improvement. (2) Tracking significantly reduces both economic costs and mortality. (3) Tracking combined with a moderate testing capacity can achieve containment without lockdowns. (4) In the presence of a flow of new incoming infections, dynamic “On–Off” lockdowns are more efficient than fixed lockdowns. In this setting as well, tracking strictly improves efficiency. The results show the extreme usefulness of policies that combine tracking and testing for reducing mortality and economic costs, and their potential to contain outbreaks without imposing any social distancing restrictions. This highlights the difficult social question of trading-off these gains against patient privacy, which is inevitably infringed by tracking.

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