Data and code associated with: Gora, E., et al. How some tropical trees benefit from being struck by lightning.

Lightning strikes are exceptionally powerful phenomena that kill hundreds of millions of trees annually. Here, we use data from a unique lightning location system to show that some individual trees counterintuitively benefit from being struck by lightning. Lightning killed 56% of 93 directly struck trees and caused an average of 41% crown dieback among the survivors. However, 18 direct strikes to lightning-tolerant trees caused little observable damage to those individuals, while reducing the number of lianas infesting their crowns by 69% and killing an average of 2.1 Mg of competitor tree biomass. The average lightning-tolerant tree is struck by lightning multiple times, conferring these benefits repeatedly (predicted mean direct strikes while canopy-height range 1.5-8.1 strikes tree-1 among species). For the often-struck Dipteryx oleifera, we estimate that the ability to survive lightning increases lifetime fecundity 14-fold, with a majority of that increase attributable to the removal of lianas and reduced light competition. Not only do D. oleifera trees apparently benefit from lightning, but their unusual heights and wide crowns increase the probability of a direct strike by 49-68% relative to trees of the same diameter with average allometries. These patterns suggest that lightning plays an underappreciated role in tree competition, influencing selection on tree life histories and tree allometries with implications for species coexistence.File list:allometry.zip: abundant_species_df_taxa.csv, abundant_species_df_taxa_test.csv, species_allometry.csv, allometry_strike_frequency_deconstruction.R (4 files)drone_map.zip: DipteryxStrikeHtData.csv, NonStrikeHtData.csv, drone_map_canopy_height.R (3 files)group_comparisons.zip: direct_alltrees_allcensuses.csv, other_canopytree_surveys.csv, plot_lianas.csv, strike_recensuses2021.csv, ReadMe.csv, comparisons_dataframes_Dipteryx.R, comparisons_dataframes_tolerant.R (7 files)lifetime_simulations.zip: combined_strike_dips.csv, dips_growth.csv, dips_mortality.csv, exposed_crowns.csv, liana_transitions_raw.csv, repro_data.csv, Dip_lifetime_simulations.R, summary_lightningSURV_IGNORElianas.rds, summary_NolianaREM_lightningDEATH_CONSTANTcompetition.rds, summary_NolianaREM_lightningSURV_CONSTANTcompetition.rds (10 files)release.zip: alltrees_finalsurvey_sp.csv, release_from_competition.R (2 files)survival_analyses_historic_neighborhoods.RMovieS1_NarratedVideo.mp4README_gora.md: This markdown file describes all data analyses in detail and provides definitions for variables contained in all .csv data files.雷击是极具破坏力的自然现象，每年致使数以亿计的树木死亡。本研究借助一套独特的雷击定位系统数据，揭示了部分个体树木竟能从雷击事件中获益，这一结论与直觉相悖。在93棵直接遭受雷击的树木中，56%的个体因雷击死亡，存活个体的树冠平均出现41%的枯梢现象。但针对18株耐雷击树木的直接雷击并未造成可观测的显著损伤，同时还使侵染其树冠的藤本植物数量减少了69%，并平均清除了2.1兆克（Mg）的竞争木生物量。平均每株耐雷击树木会多次遭受雷击，从而反复获得上述益处；据预测，在不同树种中，当树冠高度处于对应范围时，单株树木年均直接雷击次数为1.5~8.1次。对于频繁遭受雷击的油楠（Dipteryx oleifera），本研究估算其耐雷击能力可使终生繁殖力提升14倍，其中大部分增幅源于藤本植物的清除以及光照竞争的缓解。不仅油楠（D. oleifera）显然能从雷击中获益，其非常规的高大株型与宽大树冠，相较于同直径且具有典型异速生长特征的树木，可使直接雷击概率提升49%~68%。上述研究结果表明，雷击在树木竞争中扮演着长期被低估的重要角色，它通过影响树木生活史与异速生长特征的自然选择，进而对物种共存产生深远影响。 文件列表： allometry.zip：abundant_species_df_taxa.csv、abundant_species_df_taxa_test.csv、species_allometry.csv、allometry_strike_frequency_deconstruction.R（共4个文件） drone_map.zip：DipteryxStrikeHtData.csv、NonStrikeHtData.csv、drone_map_canopy_height.R（共3个文件） group_comparisons.zip：direct_alltrees_allcensuses.csv、other_canopytree_surveys.csv、plot_lianas.csv、strike_recensuses2021.csv、ReadMe.csv、comparisons_dataframes_Dipteryx.R、comparisons_dataframes_tolerant.R（共7个文件） lifetime_simulations.zip：combined_strike_dips.csv、dips_growth.csv、dips_mortality.csv、exposed_crowns.csv、liana_transitions_raw.csv、repro_data.csv、Dip_lifetime_simulations.R、summary_lightningSURV_IGNORElianas.rds、summary_NolianaREM_lightningDEATH_CONSTANTcompetition.rds、summary_NolianaREM_lightningSURV_CONSTANTcompetition.rds（共10个文件） release.zip：alltrees_finalsurvey_sp.csv、release_from_competition.R（共2个文件） survival_analyses_historic_neighborhoods.R MovieS1_NarratedVideo.mp4 README_gora.md：本markdown文件详细阐述了所有数据分析流程，并对所有.csv数据文件中的变量进行了明确定义。