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Tropical tree species differ in damage and mortality from lightning

Nature Plants volume 8, pages 1007–1013 (2022)Cite this article

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Abstract

Lightning is an important agent of mortality for large tropical trees with implications for tree demography and forest carbon budgets. We evaluated interspecific differences in susceptibility to lightning damage using a unique dataset of systematically located lightning strikes in central Panama. We measured differences in mortality among trees damaged by lightning and related those to damage frequency and tree functional traits. Eighteen of 30 focal species had lightning mortality rates that deviated from null expectations. Several species showed little damage and three species had no mortality from lightning, whereas palms were especially likely to die from strikes. Species that were most likely to be struck also showed the highest survival. Interspecific differences in tree tolerance to lightning suggest that lightning-caused mortality shapes compositional dynamics over time and space. Shifts in lightning frequency due to climatic change are likely to alter species composition and carbon cycling in tropical forests.

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Fig. 1: Lightning mortality predictions (with 95% CI) by species for common trees (those with n ≥ 8 in the dataset) compared with their historical mortality rates.
Fig. 2: Violin plots of permutation distributions for species mean ROC values (for species with n ≥ 10 individuals in the dataset) overlayed with bootstrapped confidence intervals around the observed mean.
Fig. 3: Relationship between lightning tolerance and lightning damage frequency.
Fig. 4: Univariate trait relationships with lightning tolerance and trait-trait correlations.

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Data availability

The lightning dataset is available in the Dryad repository, https://doi.org/10.5061/dryad.gf1vhhmsp. Data from the Barro Colorado Island 50 ha plot36 are available in the Dryad repository, https://doi.org/10.15146/5xcp-0d46. Data from the lightning risk model7,40 are available in the Dryad repository, https://doi.org/10.5061/dryad.c59zw3r48. Data for wood density37,38 are available in the Dryad repository, https://doi.org/10.5061/dryad.234. Data from the TRY plant database39 are available from the TRY website, https://www.try-db.org/TryWeb/Home.php.

Code availability

The R code used for analysis is available in the Dryad repository, https://doi.org/10.5061/dryad.gf1vhhmsp.

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Acknowledgements

B. Adams, M. Detto, R. Ethington, N. Gripshover, R. Kneale and A. Stark assisted in the field. O. Acevedo, M. Cano and the staff of the Smithsonian Tropical Research Institute provided logistical support. This work was supported by grants from the National Science Foundation (DEB-1354060 and DEB-1655346 to S.P.Y., DEB-1354510 and DEB-1655554 to P.M.B., GRF-2015188266 to E.M.G. and DBI-2010942 to J.H.R.) and the National Geographic Society (9703-15 to E.M.G.).

Author information

Authors and Affiliations

  1. Department of Biology, University of Louisville, Louisville, KY, USA

    Jeannine H. Richards, Evan M. Gora & Stephen P. Yanoviak

  2. Department of Botany, University of Wisconsin-Madison, Madison, WI, USA

    Jeannine H. Richards

  3. Smithsonian Tropical Research Institute, Balboa, Panama

    Evan M. Gora, Cesar Gutierrez & Stephen P. Yanoviak

  4. Cary Institute of Ecosystem Studies, Millbrook, New York, NY, USA

    Evan M. Gora

  5. Department of Atmospheric Science, University of Alabama in Huntsville, Huntsville, AL, USA

    Jeffrey C. Burchfield & Philip M. Bitzer

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Contributions

J.H.R. analysed the data and led the writing of the manuscript. E.M.G. contributed to analyses and collected data. C.G. collected data and managed field operations. J.C.B. and P.M.B. helped design the study. S.P.Y. helped design the study and coordinated the lightning data collection. All authors contributed to writing the manuscript and gave final approval for publication.

Corresponding author

Correspondence to Stephen P. Yanoviak.

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The authors declare no competing interests.

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Nature Plants thanks Kristina Anderson-Teixeira, Kenneth Feeley and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Actual vs. predicted probabilities for the lightning mortality model.

Means with 95% confidence intervals (n = 2287) for (a) log-transformed DBH and (b) distance from the struck tree.

Extended Data Fig. 2 Model residuals by species for the lightning mortality model.

Mean residuals for common species (represented by n ≥ 8 individuals in the dataset) with bootstrapped 95% confidence intervals from the mortality model compared to model predictions. Significant differences from zero based on bootstrapping 1000 times: A. standleyanum (p = 0, n = 9), O. mapora (p = 0, n = 9), S. exorrhiza (p = 0, n = 21), F. occidentalis (p = 0.035, n = 79), H. triandra (p = 0.017, n = 28), P. reticulata (p = 0, n = 8), H. crepitans (p = 0, n = 12), G. superba (p = 0, n = 37), D. oleifera (p = 0, n = 13).

Extended Data Fig. 3 Relationship between the average percent crown dieback observed for each species and the mortality model residuals.

Positive residuals indicate that a species died from lightning more often than predicted by the model. Linear regression was weighted by the sample size for each species and is shown with standard error of the mean (R2 = 0.64, F1,29 = 51.31, p = 7.0 × 10−8). Removing palms from the analysis weakened the relationship only slightly (R2 = 0.42, F1,26 = 18.59, p = 0.0002). ALSEBL = Alseis blackiana, APEIME = Apeiba membranacea, AST1ST = Astrocaryum standleyanum, BEILPE = Beilschmiedia tovarensis, CORDBI = Cordia bicolor, DIPTPA = Dipteryx oleifera, FARAOC = Faramea occidentalis, GAR2IN = Garcinia recondita, GUSTSU = Gustavia superba, HIRTTR = Hirtella triandra, HURACR = Hura crepitans, JAC1CO = Jacaranda copaia, LUEHSE = Luehea seemannii, OCOTWH = Ocotea whitei, OENOMA = Oenocarpus mapora, POUTRE = Pouteria reticulata, PRI2CO = Prioria copaifera, QUARAS = Quararibea asterolepis, SIMAAM = Simarouba amara, SOCREX = Socratea exorrhiza, TAB1RO = Tabebuia rosea, TAB2AR = Tabernaemontana arborea, TACHVE = Tachigali panamensis, TET2PA = Protium stevensonii, TRI2TU = Trichilia tuberculata, VIROSU = Virola nobilis.

Extended Data Fig. 4 Recovery and decline of individual trees by species.

Rate of change (ROC) of individual trees between first and last census grouped by species.

Extended Data Fig. 5 Model residuals by species for the resprout model.

Species mean residuals (for species with n ≥ 7 individuals in the dataset) with bootstrapped 95% confidence intervals from the resprout model compared to model predictions. Significant difference from zero based on bootstrapping 1000 times: V. nobilis (p = 0, n = 7).

Extended Data Fig. 6 Relationship between lightning tolerance and lightning damage frequency.

Fig. 3 from main text showing species names for: (a) Mortality model residuals (species with n ≥ 8 individuals) compared with mean damage frequencies projected by the lightning risk model7 by species. The linear regression was weighted by the mortality sample size for each species. Shading indicates the standard error of the mean (R2 = 0.19, F1,24 = 5.78, p = 0.02). When palms (SOCREX, OENOMA, and AST1ST) are removed, this relationship disappears (R2 = 0.10, F1,21 = 2.28, p = 0.15). (b) Residuals from damage and mortality models (for species with n ≥ 8 individuals in the dataset) with DBH removed from both models to capture the full species effect including size differences. The linear regression was weighted by sample size. Shading represents the standard error of the mean (R2 = 0.27, F1,24 = 7.11, p = 0.01). This relationship also disappears when palms are removed (R2 = 0.09, F1,18 = 1.76, p = 0.20). See Extended Data Fig. 2 caption for species codes.

Supplementary information

Supplementary Information

Supplementary Tables 1–4, and Table 5 and Fig. 1 for reanalysis excluding palms, and Tables 6 and 7 and Fig. 2 for reanalysis using only sites located with the camera monitoring system.

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Richards, J.H., Gora, E.M., Gutierrez, C. et al. Tropical tree species differ in damage and mortality from lightning. Nat. Plants 8, 1007–1013 (2022). https://doi.org/10.1038/s41477-022-01230-x

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