Avoiding pitfalls in estimating heritability with the common options approach

Danchin, Étienne; Wajnberg, Éric; Wagner, Richard H.

doi:10.1038/srep03974

Cited by 8 publications

(11 citation statements)

References 37 publications

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“…Higher physiological quality of control and foster broods raised in the smaller colonies suggests that all measured components of offspring quality were not inherited, but reflected more favourable developmental conditions prevailing in nesting aggregations of smaller size. This also seems to contradict previous reports on a strong heritable component to colony size choice based on individual ability to withstand parasites (Brown and Brown 2000), which is consistent with the results of the recent simulation study by Danchin et al (2014).…”

Section: Discussioncontrasting

confidence: 55%

“…In order to confirm whether any potential differences in offspring condition were not genetic, but could be directly attributed to different rearing conditions experienced in the colonies of varying size, a cross-fostering experiment was also conducted. So far, only few studies cross-fostered nestlings between colonies of different size, suggesting a heritable basis for choice of group size (Brown and Brown 2000;Møller 2002;Roche et al 2011; but see Danchin et al 2014). We are not aware of any cross-fostering experiments investigating the effects of colony size on physiological condition and stress in birds.…”

Section: Introductionmentioning

confidence: 99%

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Opposing selective pressures may act on the colony size in a waterbird species

2015

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In theory, larger colony size should be favoured by lower per-capita predation rates, whereas smaller colony size should be favoured by reduced parasitism, social stress and competition for food. We conducted an experimental cross-fostering of young between colonies of different size to test whether differences in fitness had an environmental or genetic basis. We induced formation of one large (ca. 100 breeding pairs) and three small (30-40 pairs) Common Tern Sterna hirundo colonies by providing different size patches of nesting area (floating rafts). The larger colony had about 30 % higher reproductive success than the smaller colonies. However, offspring raised in the large colony were in poorer condition, which was indicated by the higher heterophil/lymphocyte ratios, lower hemoglobin concentrations in blood and slower growth rates, suggesting higher parasite loads or higher levels of social stress. By performing a cross-fostering experiment we confirmed that differences in chick condition were not inherited, but could be directly attributed to different rearing conditions experienced in the colonies of varying size. These results suggest that colony size in the Common Tern may be regulated by the opposing selective pressures (predation vs. parasitism/social stress).

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Section: Discussioncontrasting

confidence: 55%

Section: Introductionmentioning

confidence: 99%

Opposing selective pressures may act on the colony size in a waterbird species

2015

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“…However, this spatially nonrandom cross‐fostering can generate misleading results. This is because cross‐fostering between extremes, for example between large and small breeding colonies, is likely to generate offspring with trait values closer to the population mean – the more frequently occurring trait value in a normal distribution (van Noordwijk ; Danchin, Wajnberg & Wagner ). The shift in the focal trait from an extreme trait value in the parents to the population mean in the offspring can increase the likelihood of type 1 error (van Noordwijk ; Danchin, Wajnberg & Wagner ).…”

Section: Introductionmentioning

confidence: 99%

Troubleshooting the potential pitfalls of cross‐fostering

et al. 2015

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Summary1. Cross-fostering is the transfer of offspring between their natal environment and a new social environment. This method allows researchers to disentangle the genetic and interacting environmental effects that influence phenotypes, and is popular in both wild and laboratory studies. Here, we discuss three factors that might bias cross-fostering and influence ecological and evolutionary conclusions if not accommodated. 2. First, cross-fostering tends to be spatially and temporally non-random because heterogeneous breeding conditions can result in clustered breeding attempts. Secondly, cross-fostering will often change the brood composition because the exchanged broods are unlikely to be precisely matched in age, size and composition. Thirdly, some methods can introduce bias by using a systematically structured subset of the population, leading to a systematically structured data set. 3. We use a 12-year case study of wild house sparrows Passer domesticus to demonstrate how to identify these biases with statistical modelling and how to adjust the cross-fostering protocol according to the identified biases. 4. In our data set, cross-fostered nestlings were more likely to survive than non-cross-fostered nestlings, but postfledging and overall survival were not affected. Survival differed between cross-fostering treatments, partially due to temporally nonrandom breeding conditions and nonrandom offspring selection, demonstrating two of the three forms of bias in data from a wild population. 5. In all cases, we suggest using statistical models to examine whether cross-fostering opportunities and offspring fitness are affected by nonrandom breeding, changes to the brood composition and biased methodology. We provide guidelines for optimising a cross-fostering design and reducing inherent bias.

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“…Although it is not related to any of the examples above, it is a sufficiently common trap and has led to errors in a wide range of scientific disciplines (Kelly & Price, 2005;Danchin, Wajnberg & Wagner, 2014).…”

Section: (B) Misinterpretation Of Measurement Errormentioning

confidence: 99%

“…1 − repeatability), we can make predictions about the expected magnitude of regression toward the mean, and we can test whether the experimental treatment had any additional effects beyond this statistical artefact (Barnett et al, 2005). However, in practice one should avoid such situations whenever possible (Danchin et al, 2014). Hence, the rule If we then assign individuals into categories ('below average' in blue and 'above average' in orange) based on our first measurement, we make some misassignments with respect to their true ranks (e.g.…”

Section: (B) Misinterpretation Of Measurement Errormentioning

confidence: 99%

Detecting and avoiding likely false‐positive findings – a practical guide

2016

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Recently there has been a growing concern that many published research findings do not hold up in attempts to replicate them. We argue that this problem may originate from a culture of 'you can publish if you found a significant effect'. This culture creates a systematic bias against the null hypothesis which renders meta-analyses questionable and may even lead to a situation where hypotheses become difficult to falsify. In order to pinpoint the sources of error and possible solutions, we review current scientific practices with regard to their effect on the probability of drawing a false-positive conclusion. We explain why the proportion of published false-positive findings is expected to increase with (i) decreasing sample size, (ii) increasing pursuit of novelty, (iii) various forms of multiple testing and researcher flexibility, and (iv) incorrect P-values, especially due to unaccounted pseudoreplication, i.e. the non-independence of data points (clustered data). We provide examples showing how statistical pitfalls and psychological traps lead to conclusions that are biased and unreliable, and we show how these mistakes can be avoided. Ultimately, we hope to contribute to a culture of 'you can publish if your study is rigorous'. To this end, we highlight promising strategies towards making science more objective. Specifically, we enthusiastically encourage scientists to preregister their studies (including a priori hypotheses and complete analysis plans), to blind observers to treatment groups during data collection and analysis, and unconditionally to report all results. Also, we advocate reallocating some efforts away from seeking novelty and discovery and towards replicating important research findings of one's own and of others for the benefit of the scientific community as a whole. We believe these efforts will be aided by a shift in evaluation criteria away from the current system which values metrics of 'impact' almost exclusively and towards a system which explicitly values indices of scientific rigour.

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Avoiding pitfalls in estimating heritability with the common options approach

Cited by 8 publications

References 37 publications

Opposing selective pressures may act on the colony size in a waterbird species

Opposing selective pressures may act on the colony size in a waterbird species

Troubleshooting the potential pitfalls of cross‐fostering

Detecting and avoiding likely false‐positive findings – a practical guide

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