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Fossil leaf economics quantified: calibration, Eocene case study, and implications
- Dana L. Royer, Lawren Sack, Peter Wilf, Bárbara Cariglino, Christopher H. Lusk, Ian J. Wright, Mark Westoby, Gregory J. Jordan, Ülo Niinemets, Phyllis D. Coley, Asher D. Cutter, Conrad C. Labandeira, Matthew B. Palmer, Kirk R. Johnson, Angela T. Moles, Fernando Valladares
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- Journal:
- Paleobiology / Volume 33 / Issue 4 / Fall 2007
- Published online by Cambridge University Press:
- 08 April 2016, pp. 574-589
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Leaf mass per area (MA) is a central ecological trait that is intercorrelated with leaf life span, photosynthetic rate, nutrient concentration, and palatability to herbivores. These coordinated variables form a globally convergent leaf economics spectrum, which represents a general continuum running from rapid resource acquisition to maximized resource retention. Leaf economics are little studied in ancient ecosystems because they cannot be directly measured from leaf fossils. Here we use a large extant data set (65 sites; 667 species-site pairs) to develop a new, easily measured scaling relationship between petiole width and leaf mass, normalized for leaf area; this enables MA estimation for fossil leaves from petiole width and leaf area, two variables that are commonly measurable in leaf compression floras. The calibration data are restricted to woody angiosperms exclusive of monocots, but a preliminary data set (25 species) suggests that broad-leaved gymnosperms exhibit a similar scaling. Application to two well-studied, classic Eocene floras demonstrates that MA can be quantified in fossil assemblages. First, our results are consistent with predictions from paleobotanical and paleoclimatic studies of these floras. We found exclusively low-MA species from Republic (Washington, U.S.A., 49 Ma), a humid, warm-temperate flora with a strong deciduous component among the angiosperms, and a wide MA range in a seasonally dry, warm-temperate flora from the Green River Formation at Bonanza (Utah, U.S.A., 47 Ma), presumed to comprise a mix of short and long leaf life spans. Second, reconstructed MA in the fossil species is negatively correlated with levels of insect herbivory, whether measured as the proportion of leaves with insect damage, the proportion of leaf area removed by herbivores, or the diversity of insect-damage morphotypes. These correlations are consistent with herbivory observations in extant floras and they reflect fundamental trade-offs in plant-herbivore associations. Our results indicate that several key aspects of plant and plant-animal ecology can now be quantified in the fossil record and demonstrate that herbivory has helped shape the evolution of leaf structure for millions of years.
EVOLUTION IN A LABORATORY HOST–PARASITOID SYSTEM AND ITS EFFECT ON POPULATION KINETICS
- Nasser Zareh, Mark Westoby, David Pimentel
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- Journal:
- The Canadian Entomologist / Volume 112 / Issue 10 / 01 October 1980
- Published online by Cambridge University Press:
- 31 May 2012, pp. 1049-1060
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A laboratory system was developed that allowed populations of the house fly, Musca domestica, and its hymenopterous, wasp parasitoid, Nasonia vitripennis, to interact and fluctuate in numbers, subject only to an upper limit on Musca density. In one (experimental) treatment, the selection pressure from Nasonia was allowed to operate, while in the control all Musca adults were replaced in each generation by individuals from a Musca population not exposed to Nasonia. Evolution for resistance of Musca to Nasonia became noticeable within four generations in the experimental treatment. Measured changes finally included increased fly pupal weight (although larval development period was not allowed to increase), less time spent as pupa, increased pupal mortality, and reduced fecundity of adults. Total per-generation increase of both control and experimental Nasonia was much reduced on experimental compared with control Musca. This was caused by reductions both in the longevity of female Nasonia and in the number of progeny they produced each day. From early in the experiment the increased resistance of Musca produced lower Nasonia densities in the experimental treatment. During the first 20 or so generations no difference could be detected in mean Musca density between the two treatments. After that time the density of adult Musca became greater, and fluctuated less, in the experimental than in the control treatment. This situation continued until the experiment ended at 50 generations.
Bivariate line-fitting methods for allometry
- David I. Warton, Ian J. Wright, Daniel S. Falster, Mark Westoby
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- Journal:
- Biological Reviews / Volume 81 / Issue 2 / May 2006
- Published online by Cambridge University Press:
- 30 March 2006, pp. 259-291
- Print publication:
- May 2006
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Fitting a line to a bivariate dataset can be a deceptively complex problem, and there has been much debate on this issue in the literature. In this review, we describe for the practitioner the essential features of line-fitting methods for estimating the relationship between two variables: what methods are commonly used, which method should be used when, and how to make inferences from these lines to answer common research questions.
A particularly important point for line-fitting in allometry is that usually, two sources of error are present (which we call measurement and equation error), and these have quite different implications for choice of line-fitting method. As a consequence, the approach in this review and the methods presented have subtle but important differences from previous reviews in the biology literature.
Linear regression, major axis and standardised major axis are alternative methods that can be appropriate when there is no measurement error. When there is measurement error, this often needs to be estimated and used to adjust the variance terms in formulae for line-fitting. We also review line-fitting methods for phylogenetic analyses.
Methods of inference are described for the line-fitting techniques discussed in this paper. The types of inference considered here are testing if the slope or elevation equals a given value, constructing confidence intervals for the slope or elevation, comparing several slopes or elevations, and testing for shift along the axis amongst several groups. In some cases several methods have been proposed in the literature. These are discussed and compared. In other cases there is little or no previous guidance available in the literature.
Simulations were conducted to check whether the methods of inference proposed have the intended coverage probability or Type I error. We identified the methods of inference that perform well and recommend the techniques that should be adopted in future work.