Sarah Perin Otto

Sarah Perin Otto

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Sarah Perin Otto

Department of Zoology, University of British Columbia

Research Focus & Metrics

Academic Career Length

38Years (1989-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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31 December 2019 in Global Change Biology
Verified
Journal Article
Open access
JKJens Kattge
Jens Kattge
GBGerhard Bönisch
Gerhard Bönisch
SDSandra Díaz
Sandra Díaz
SLSandra Lavorel
Sandra Lavorel
IPIain Colin Prentice
Iain Colin Prentice
CWChristian Wirth
Christian Wirth
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

1 December 2000 in Annual Review of Genetics
Verified
Journal Article
Closed access
SOSarah P Otto
Sarah P Otto
JWJeannette Whitton
Jeannette Whitton
▪ Abstract Changes in ploidy occurred early in the diversification of some animal and plant lineages and represent an ongoing phenomenon in others. While the prevalence of polyploid lineages indicates that this phenomenon is a common and successful evolutionary transition, whether polyploidization itself has a significant effect on patterns and rates of diversification remains an open question. Here we review evidence for the creative role of polyploidy in evolution. We present new estimates for the incidence of polyploidy in ferns and flowering plants based on a simple model describing transitions between odd and even base chromosome numbers. These new estimates indicate that ploidy changes may represent from 2 to 4% of speciation events in flowering plants and 7% in ferns. Speciation via polyploidy is likely to be one of the more predominant modes of sympatric speciation in plants, owing to its potentially broad-scale effects on gene regulation and developmental processes, effects that can produce immediate shifts in morphology, breeding system, and ecological tolerances. Theoretical models support the potential for increased adaptability in polyploid lineages. The evidence suggests that polyploidization can produce shifts in genetic systems and phenotypes that have the potential to result in increased evolutionary diversification, yet conclusive evidence that polyploidy has changed rates and patterns of diversification remains elusive.

1 July 2014 in PLOS Biology
Verified
Journal Article
Open access
PDF file
DBDoris Bachtrog
Doris Bachtrog
JMJudith Mank
Judith Mank
CPCatherine L. Peichel
Catherine L. Peichel
MKMark Kirkpatrick
Mark Kirkpatrick
SOSarah P. Otto
Sarah P. Otto
TCThe Tree of Sex Consortium
The Tree of Sex Consortium
Sexual reproduction is an ancient feature of life on earth, and the familiar X and Y chromosomes in humans and other model species have led to the impression that sex determination mechanisms are old and conserved. In fact, males and females are determined by diverse mechanisms that evolve rapidly in many taxa. Yet this diversity in primary sex-determining signals is coupled with conserved molecular pathways that trigger male or female development. Conflicting selection on different parts of the genome and on the two sexes may drive many of these transitions, but few systems with rapid turnover of sex determination mechanisms have been rigorously studied. Here we survey our current understanding of how and why sex determination evolves in animals and plants and identify important gaps in our knowledge that present exciting research opportunities to characterize the evolutionary forces and molecular pathways underlying the evolution of sex determination.

1 October 2007 in Systematic Biology
Verified
Journal Article
Open access
PDF file
WMWayne P. Maddison
Wayne P. Maddison
PMPeter Midford
Peter Midford
SOSarah P. Otto
Sarah P. Otto
Determining whether speciation and extinction rates depend on the state of a particular character has been of long-standing interest to evolutionary biologists. To assess the effect of a character on diversification rates using likelihood methods requires that we be able to calculate the probability that a group of extant species would have evolved as observed, given a particular model of the character's effect. Here we describe how to calculate this probability for a phylogenetic tree and a two-state (binary) character under a simple model of evolution (the “BiSSE” model, binary-state speciation and extinction). The model involves six parameters, specifying two speciation rates (rate when the lineage is in state 0; rate when in state 1), two extinction rates (when in state 0; when in state 1), and two rates of character state change (from 0 to 1, and from 1 to 0). Using these probability calculations, we can do maximum likelihood inference to estimate the model's parameters and perform hypothesis tests (e.g., is the rate of speciation elevated for one character state over the other?). We demonstrate the application of the method using simulated data with known parameter values.

1 November 2007 in Cell
Verified
Journal Article
Closed access
SOSarah P. Otto
Sarah P. Otto

1 April 2002 in Nature Reviews Genetics
Verified
Journal Article
Closed access
SOSarah P. Otto
Sarah P. Otto
TLThomas Lenormand
Thomas Lenormand