A mechanistic and empirically supported lightning risk model for forest trees

Abstract

Tree death due to lightning influences tropical forest carbon cycling and tree community dynamics. However, the distribution of lightning damage among trees in forests remains poorly understood. We developed models to predict direct and secondary lightning damage to trees based on tree size, crown exposure and local forest structure. We parameterized these models using data on the locations of lightning strikes and censuses of tree damage in strike zones, combined with drone‐based maps of tree crowns and censuses of all trees within a 50‐ha forest dynamics plot on Barro Colorado Island, Panama. The likelihood of a direct strike to a tree increased with larger exposed crown area and higher relative canopy position (emergent > canopy >>> subcanopy), whereas the likelihood of secondary lightning damage increased with tree diameter and proximity to neighbouring trees. The predicted frequency of lightning damage in this mature forest was greater for tree species with larger average diameters. These patterns suggest that lightning influences forest structure and the global carbon budget by non‐randomly damaging large trees. Moreover, these models provide a framework for investigating the ecological and evolutionary consequences of lightning disturbance in tropical forests. Synthesis. Our findings indicate that the distribution of lightning damage is stochastic at large spatial grain and relatively deterministic at smaller spatial grain (<15 m). Lightning is more likely to directly strike taller trees with large crowns and secondarily damage large neighbouring trees that are closest to the directly struck tree. The results provide a framework for understanding how lightning can affect forest structure, forest dynamics and carbon cycling. The resulting lightning risk model will facilitate informed investigations into the effects of lightning in tropical forests.

Tree mode of death and mortality risk factors across Amazon forests

“…Instead, our results suggest that competition and other drivers of physiological failure also show large spatial variation. We found species life-history strategies to be more important than the characteristics of the individual trees for predicting tree mortality across Amazonia (Tables 1 and 2), consistent with previous local studies 19 . In particular, we show that a great part of the variation in the hazard rates is explained by the species mean growth rates (Table 1).…”

“…For example, mortality by hydraulic failure, observed during extreme drought events, has been shown to disproportionately affect larger trees 10,[16][17][18] . Taller trees with large crowns are also more likely to be struck by lightning 19 . Light competition, on the other hand, is expected to kill mostly small trees, as these tend to experience low light availability and thus be closer to their light compensation point, where they may struggle to fix enough carbon to maintain basic functions 7,20 .…”

“…Thus, the relative stem diameter growth rate of an individual allows us to infer whether a tree has died from physiological stress. While tree size has been shown to predict tree death 23,24 , recent studies have emphasised the importance of individual growth rate as a mortality risk factor 19 . However, the combined influence of tree size and growth on mortality has only been evaluated for a few sites in the tropics 9 , hindering efforts to understand their general importance as predictors of tree death.…”

“…15,000 tree species 25,26 . These are expected to vary greatly in their baseline mortality rates and tolerance to different potential causes of death 19,24 . The mortality rate of a given species is expected to be predicted by its mean growth rate, reflecting a life-history trade-off between growth and survival 19,27 .…”

“…These are expected to vary greatly in their baseline mortality rates and tolerance to different potential causes of death 19,24 . The mortality rate of a given species is expected to be predicted by its mean growth rate, reflecting a life-history trade-off between growth and survival 19,27 . Fast-growing taxa tend to have low investment in wood structure, thus being more susceptible to mechanical damage, which leads to shorter life cycles 28 .…”