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lma() takes either raw or processed leaf physiognomic data and returns leaf mass per area (LMA) reconstructions of species-mean, site-mean, and site- variance.

lma() calls calc_lma() multiple times with different sets of parameters. See calc_lma() for more control over LMA reconstructions.

Usage

lma(specimen_data)

Arguments

specimen_data

A table that must include "Site", "Morphotype", and either "Petiole Metric", or "Blade Area", "Petiole Area", and "Petiole Width".

Value

A list of tables containing leaf mass per area reconstructions.

  • species_mean_lma contains the average LMA for each morphospecies-site pair. Values calculated using the regression from Royer et al. (2007).

  • royer_site_mean_lma contains the average LMA for each site. Values calculated using the regression from Royer et al. (2007)

  • lowe_site_lma contains the average LMA for each site. Values calculated using the regression from Lowe et al. (2024)

  • lowe_variance contains the variance in LMA for each site. Values calculated using the regression from Lowe et al. (2024)

References

  • Royer, D. L., L. Sack, P. Wilf, C. H. Lusk, G. J. Jordan, Ulo Niinemets, I. J. Wright, et al. 2007. Fossil Leaf Economics Quantified: Calibration, Eocene Case Study, and Implications. Paleobiology 33: 574–589

  • Lowe, A. J., D. L. Royer, D. J. Wieczynski, M. J. Butrim, T. Reichgelt, L. Azevedo-Schmidt, D. J. Peppe, et al. 2024. Global patterns in community-scale leaf mass per area distributions of woody non-monocot angiosperms and their utility in the fossil record. In review.

Examples

results <- lma(McAbeeExample)
results
#> $species_mean_lma
#>         site morphotype  n petiole_metric    lower     value     upper
#> 1  McAbee H1         M1 10   0.0018166221 81.37167 105.44818 136.64852
#> 2  McAbee H1         M5  3   0.0011067149 54.54670  87.26130 139.59661
#> 3  McAbee H1         M8  8   0.0011510539 66.35987  88.58058 118.24193
#> 4  McAbee H1        M12  1   0.0010808383 38.37080  86.47620 194.89128
#> 5  McAbee H1        M13  1   0.0006070381 30.77894  69.37268 156.35916
#> 6  McAbee H1        M18  1   0.0011637972 39.46986  88.95393 200.47708
#> 7  McAbee H1        M19  1   0.0008073257 34.32356  77.35576 174.33838
#> 8  McAbee H1        M24  5   0.0002309535 33.24559  47.95859  69.18289
#> 9  McAbee H1        M28  1   0.0002175761 20.78085  46.87783 105.74787
#> 10 McAbee H1        M41  1   0.0002994371 23.48554  52.96009 119.42543
#> 11 McAbee H1        M44  1   0.0005108600 28.81385  64.94883 146.40011
#> 12 McAbee H1        M73  1   0.0003778943 25.67425  57.88359 130.50081
#> 13 McAbee H1        M79  2   0.0003960090 33.14315  58.92822 104.77386
#> 14 McAbee H1        M91  1   0.0001524066 18.12949  40.91735  92.34838
#> 15 McAbee H2         M1  3   0.0008877491 50.14134  80.21339 128.32102
#> 16 McAbee H2         M8  2   0.0010796906 48.64042  86.44111 153.61845
#> 17 McAbee H2        M18  1   0.0002132426 20.62123  46.51895 104.94097
#> 18 McAbee H2        M19  4   0.0006803596 48.21879  72.46130 108.89200
#> 19 McAbee H2        M22  3   0.0008971039 50.34260  80.53524 128.83571
#> 20 McAbee H2        M24  2   0.0007082087 41.40139  73.58031 130.77005
#> 21 McAbee H2        M28  1   0.0004553366 27.57296  62.15600 140.11437
#> 22 McAbee H2        M29  1   0.0001254609 16.82558  37.98658  85.76111
#> 23 McAbee H2        M31  2   0.0003283234 30.84620  54.85640  97.55577
#> 24 McAbee H2        M47  2   0.0009868057 46.99765  83.52115 148.42836
#> 25 McAbee H2        M76  1   0.0001534697 18.17789  41.02614  92.59292
#> 26 McAbee H2        M94  1   0.0001232820 16.71284  37.73320  85.19165
#> 27 McAbee H2        M97  1   0.0005314955 29.25363  65.93877 148.62843
#> 
#> $royer_site_mean_lma
#>        site  n    lower    value    upper
#> 1 McAbee H1 14 64.42873 72.90997 82.50765
#> 2 McAbee H2 13 57.33929 65.48619 74.79063
#> 
#> $lowe_site_mean_lma
#>        site  n    lower    value    upper
#> 1 McAbee H1 14 61.03750 73.68178 88.94539
#> 2 McAbee H2 13 53.87969 67.58568 84.77822
#> 
#> $lowe_site_variance_lma
#>        site  n    lower     value    upper
#> 1 McAbee H1 14 491.2574 1070.6851 2333.535
#> 2 McAbee H2 13 323.3496  866.6651 2322.899
#>