The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Applications of Phylogenetically Independent Contrasts: A Mixed Progress Report
Abstract
Phylogeny embodies the historical development of the contemporary diversity of life. Studies of morphological adaptation and life-history evolution often portray this diversity by variation in quantitative, continuously distributed measurements of character traits, such as size and development time. In comparative analyses of such data, statistical interpretations of regression parameters and correlations are confounded by lack of independence among points resulting from common ancestry of taxa (Felsenstein 1985, Burt 1989, Grafen 1989, Harvey and Pagel 1991). Recently, several techniques have been proposed to circumvent this problem of non-independence. The most widely used approach is to calculate phylogenetically contrasts, or PICs (Felsenstein 1985, Harvey and Pagel 1991 [who use the term independent comparisons], Martins and Garland 1991, Garland et al. 1992, 1993, Purvis and Garland 1993, Purvis and Rambaut 1995). As acceptance and application of such methods broadens, it becomes increasingly important to compare results obtained from phylogenetically based approaches with traditional analyses based on correlation and regression of trait values for individual taxa. Such comparisons are needed to judge whether from earlier, non-phylogenetic analyses are likely to be valid, and whether non-phylogenetic comparisons are justifiable today when phylogenetic information is unavailable or in analyses for which contrasts applications have not yet been developed. We undertake such a comparison here and comment upon the relative merits of analyzing contrasts versus trait values. PICs are calculated as differences in trait values between adjacent pairs of nodes or terminal taxa in a phylogenetic tree. Because no two contrasts share the same branches of a tree, they are statistically samples of evolutionary change within a lineage. PIC analysis requires a phylogenetic hypothesis. Thanks to cladistic methods and molecular data, phylogenetic trees are increasingly available. It is no surprise, therefore, that a growing number of comparative studies have used PIC and other phylogenetically based approaches and that these techniques are becoming standard. However, although phylogenetic independence is statistically desirable, phylogenetically based analyses are weakened by increased error variances inherent to the methods themselves. In addition, PIC and other phylogenetic analyses do not easily resolve shifts in the relative rates of evolution of traits within lineages because branches for each contrast span a wide range of time periods. We argue that it is premature at this point to insist upon particular phylogenetically based approaches to comparative analysis, even though pressure is mounting to reject conventional practices of calculating regressions and correlations from trait values of taxa (TIPs of a phylogenetic tree) in favor of PICs. In the minds of many authors, phylogenetically based comparison is the only acceptable approach. Statements such as Simple correlational studies across an array of species are irredeemably flawed: not only is the number of degrees of freedom undefined, but the results are likely to be biased (Devoogd et al. 1993) are becoming commonplace in the literature. On one side, Harvey (1996) remarks that ecologists generally do not use phylogenetically based methods for analysing their comparative data leading to conclusions that are potentially misleading. On the other side, Westoby et al. (1995a) complain about the hegemony of phylogenetic correction (PC), stating that ...the belief seems to have become very widespread that PC should be automatic and obligatory. Weathers and Siegel (1995) make the same point. Finding no difference between results based on raw and
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Phylogenies and the Comparative Method
Felsenstein, J. (1985) · The American Naturalist · doi:10.1086/284325 · Cited by 9,793
The Comparative Method: Moving Beyond Qualitative and Quantitative Strategies
Ragin, C. C. (2014) · doi:10.1525/9780520957350 · Cited by 2,130
The Relationship between Basal Metabolic Rate and Daily Energy Expenditure in Birds and Mammals
Ricklefs, R. E., Konarzewski, M., & Daan, S. (1996) · The American Naturalist · doi:10.1086/285892 · Cited by 311
Self-citation
Cited by
Inferring the historical patterns of biological evolution
Pagel, M. (1999) · Nature · doi:10.1038/44766 · Cited by 5,200
Phylogenetic Analysis and Comparative Data: A Test and Review of Evidence
Freckleton, R. P., Harvey, P. H., & Pagel, M. (2002) · The American Naturalist · doi:10.1086/343873 · Cited by 2,604
Pattern and Process in Macroecology
(2000) · Wiley eBooks · doi:10.1002/9780470999592 · Cited by 1,590
Glazier, D. S. (2005) · Biological Reviews · doi:10.1017/s1464793105006834 · Cited by 1,069
A comparative analysis of pollen limitation in flowering plants
Larson, B. M. H., & Barrett, S. C. H. (2000) · Biological Journal of the Linnean Society · doi:10.1006/bijl.1999.0372 · Cited by 697
Metadata
- Authors
- Ricklefs, R. E., & Starck, J. M.
- Venue
- Oikos
- Publisher
- JSTOR
- Published
- 1996-10
- Volume
- 77
- Issue
- 1
- Pages
- 167
- ISSN
- 0030-1299 (ISSN-L)
- OpenAlex
- W2323420790
- Cited by
- 289
- References
- 3
- FWCI
- 21.35
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.