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Plant growth is influenced by interactions with neighbouring plants. The strength and direction of the cumulative neighbourhood effect on growth can depend on neighbour properties, such as their abundance, size and proximity, as well as the degree of similarity between interacting plants and their traits, which can be captured by the species identity of neighbours. Such interactions are also influenced by the local environmental conditions that are largely determined by climate. Because neighbour and climatic effects are typically explored in isolation, particularly in long‐lived species such as trees, it is unclear how the impacts of neighbours on plant growth shift in response to temporal variation in climatic conditions.Here, we explored how neighbouring plants impact the annual growth of two eucalypts, Eucalyptus delegatensis and Eucalyptus regnans, over three growing seasons in an experimental forest in south‐east Tasmania, Australia. We assessed whether eucalypt growth rates could be described by the number, size, proximity, and species identity of neighbours, and how the strength of this effect was influenced by the growing season climatic conditions.We found that climate and neighbouring plants had an interactive impact on eucalypt growth. Neighbours had a consistent, competitive effect on the growth of both eucalypts in all three growing seasons which was strongly related to the cumulative neighbourhood biomass. The identity of neighbours was important in determining E. regnans growth only, whereby distinguishing neighbours according to functional group best described growth. Over all three growing seasons, we predicted that, on average, neighbours reduced E. delegatensis and E. regnans mean annual growth by 60.5% and 48.4%, respectively. However, the strength of the competitive effect of neighbours on eucalypt growth was related to growing season climate, being strongest when conditions were hot and dry and weakest in cool, wet conditions.Synthesis: Given the consistent results observed in two co‐occurring eucalypts, our findings suggest that drier and hotter climatic conditions increase the strength of competitive effects on tree growth. This has implications for future forest productivity given projected increased temperatures and variation in rainfall patterns globally. [ABSTRACT FROM AUTHOR]

Interactions among neighbouring plants are key determinants of plant growth. To characterise the cumulative effect of all neighbours on the growth of a focal plant, neighbourhoods are often described by 'competition' indices. Common competition indices calculate the summed size of neighbour plants (focal‐independent index [FII]) whilst others include the summed ratio of the neighbour size relative to focal plant size (focal dependent). A frequently overlooked statistical artefact is that focal‐dependent indices (FDIs) may lead to biased estimates of neighbourhood effects on plant growth when growth is size dependent.Here, we conduct a literature search to determine the most common index types used to explain neighbour effects on tree growth. We then assess the ability of two common index types—focal dependent and focal independent—to correctly infer neighbourhood effects in (1) observations of tree growth in an experimental forest in south‐east Tasmania, Australia, and (2) an artificially created dataset where tree growth is unrelated to the neighbourhood.Both indices detected the competitive neighbourhood effect on tree growth observed in our own dataset but differed in their conclusion regarding neighbour effects in the simulated data. Despite the simulated dataset being generated so there was no relationship between tree growth and their neighbourhood, the FDI detected strong, competitive neighbourhood effects when intrinsic growth was incorrectly related to tree size. In contrast, when we considered the FII as the neighbourhood metric, we correctly did not detect any neighbourhood effects in the simulated data regardless of how size‐dependent growth was described.Synthesis. 'Competition' indices are a useful method to characterise the cumulative neighbourhood effect on plant growth; however, we demonstrate that indices which include the size of the focal plant in their calculation can be biased by an inherent relationship between tree growth and initial size. Whilst this bias typically overstates the strength of competition in determining focal tree growth, we show that it can be mitigated by correctly describing intrinsic growth. We discuss the limitations of both index types, provide recommendations for performing statistical modelling and outline how to check for accurate neighbour inference. [ABSTRACT FROM AUTHOR]