Small sample sizes in the study of ontogenetic allometry; implications for palaeobiology

نویسندگان

  • Caleb Marshall Brown
  • Matthew J. Vavrek
چکیده

Quantitative morphometric analyses, particularly ontogenetic allometry, are common methods used in quantifying shape, and changes therein, in both extinct and extant organisms. Due to incompleteness and the potential for restricted sample sizes in the fossil record, palaeobiological analyses of allometry may encounter higher rates of error. Differences in sample size between fossil and extant studies and any resulting effects on allometric analyses have not been thoroughly investigated, and a logical lower threshold to sample size is not clear. Here we show that studies based on fossil datasets have smaller sample sizes than those based on extant taxa. A similar pattern between vertebrates and invertebrates indicates this is not a problem unique to either group, but common to both. We investigate the relationship between sample size, ontogenetic allometric relationship and statistical power using an empirical dataset of skull measurements of modern Alligator mississippiensis. Across a variety of subsampling techniques, used to simulate different taphonomic and/or sampling effects, smaller sample sizes gave less reliable and more variable results, often with the result that allometric relationships will go undetected due to Type II error (failure to reject the null hypothesis). This may result in a false impression of fewer instances of positive/negative allometric growth in fossils compared to living organisms. These limitations are not restricted to fossil data and are equally applicable to allometric analyses of rare extant taxa. No mathematically derived minimum sample size for ontogenetic allometric studies is found; rather results of isometry (but not necessarily allometry) should not be viewed with confidence at small sample sizes.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

The evolution of floral ontogenetic allometry in the Andean genus Caiophora (Loasaceae, subfam. Loasoideae).

The astounding variety of angiosperm flower morphologies has evolved in response to many selective forces. Flower development is highly coordinated and involves developmental associations between size and shape, ontogenetic allometry, which in turn affect the morphology of mature flowers. Although ontogenetic allometries can act as a developmental constraint and may influence adaptive evolution...

متن کامل

Stochastic Ontogenetic Allometry: The Statistical Dynamics of Relative Growth

BACKGROUND In the absence of stochasticity, allometric growth throughout ontogeny is axiomatically described by the logarithm-transformed power-law model, θt = log(a) b + kφ(t), where θt ≡ θ(t) and φt ≡ φ(t) are the logarithmic sizes of two traits at any given time t. Realistically, however, stochasticity is an inherent property of ontogenetic allometry. Due to the inherent stochasticity in bot...

متن کامل

Economic Statistical Design of Multivariate T^2 Control Chart with Variable Sample Sizes

Today, quality improvement and cost reduction are key factors for achieving business success, growth and position. One of the primary tools for quality improvement and cost reduction in online activities of statistical process control is control charts. As the need for monitoring several correlated quality characteristics is extensively growing, the use of multivariate control charts become...

متن کامل

Evolution of ontogeny in the hippopotamus skull: using allometry to dissect developmental change

Allometry describes the effect of size change on aspects of an organism’s form and can be used to summarize the developmental history of growing parts of an animal. By comparing how allometric growth differs between species, it is possible to reveal differences in their pathways of development. The ability to compare and categorize developmental change between species is demonstrated here using...

متن کامل

Bayesian Inference for Spatial Beta Generalized Linear Mixed Models

In some applications, the response variable assumes values in the unit interval. The standard linear regression model is not appropriate for modelling this type of data because the normality assumption is not met. Alternatively, the beta regression model has been introduced to analyze such observations. A beta distribution represents a flexible density family on (0, 1) interval that covers symm...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره 3  شماره 

صفحات  -

تاریخ انتشار 2015