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Crown displacement in trees is an adaptive response driven by neighbours that optimizes space use and reduces competition. But it can also be the result of wind force. Although morphological responses to neighbours have been well studied, the interplay between neighbours and wind in driving crown shape, and the implications for plant interactions remain poorly understood. However, it is crucial to predict such changes in vegetation structure and function under the scope of global change. We test the hypothesis that aboveground interactions are reduced with increasing soil stress and that wind becomes the main driver of crown shape in mangrove forests. We investigated the effect of neighbours and wind intensity and direction on crown displacement of mangrove canopy and below canopy trees along a salinity gradient, and assessed crown asymmetry for three mangrove tree species, as well as the contribution of crown displacement on reducing crown‐projected area overlap and thus neighbourhood competition. Results show that crown displacement of canopy trees is strongly influenced by winds at all salinities. At low salinities, competition for space accounted for 48% of crown displacement away from neighbours, compared to 49% found for the synthetized effects of wind and neighbours. While trees below the canopy displace their crowns away from their neighbours, no response to wind could be detected. This can be due to the wind protection conferred by a dense canopy stand related to bigger crowns that effectively reduce wind drag. At higher salinities, there was a reduction in canopy overlap due to crown displacement, which suggests reduced aboveground plant interactions with increasing soil stress. While neighbourhood avoidance is a fundamental strategy for optimal light foraging, this study shows that wind strength and directionality are main drivers of crown shape with increasing stress and highlights their potential influence in plant interactions and forest structure, pointing to an increased susceptibility of trees to disturbances that should be further studied. A http://onlinelibrary.wiley.com/doi/10.1111/1365-2435.13218/suppinfo is available for this article.

Key Message Morphological plasticity helps plants to cope to environmental conditions. Allometric responses of the mangrove Avicennia germinans to increasing salinity are easily detectable when focusing on the top height trees. Abstract Several studies show that mangrove trees possess high species-and site-related trait allometry, suggesting large morphological plasticity that might be related to environmental conditions, but the causes of such variation are not clearly understood and systematic quantification is still missing. Both aspects are essential for a mechanistic understanding of the development and functioning of forests. We analyzed the role of salinity in the allometric relations of the mangrove Avicennia germinans, using: (1) the top height trees (trees with the largest diameters at breast height, which reflect forest properties at the maximum use of resources); (2) the slenderness coefficient (which indicates competition and environmental conditions); and (3) the crown to DBH ratio. These standard tools for forest scientists dealing with terrestrial forests are suitable to analyze the plastic responses of mangroves to salinity. First, the top height trees help to recognize structural forest properties that are not detectable when studying the whole stand. Second, we found that at salinities above 55 %, trees are less slender and develop wider crowns in relation to DBH than when growing at lower salinities. Our results suggest a significant change in allometric traits in relation to salinity, and reflect the plastic responses of tree traits in response to environmental variation. Understanding the plastic responses of plants to their environment can help to better model, predict, and manage forests in changing environments.

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BackgroundIn the Point-Centred Quarter Method (PCQM), the mean distance of the first nearest plants in each quadrant of a number of random sample points is converted to plant density. It is a quick method for plant density estimation. In recent publications the estimator equations of simple PCQM (PCQM1) and higher order ones (PCQM2 and PCQM3, which uses the distance of the second and third nearest plants, respectively) show discrepancy. This study attempts to review PCQM estimators in order to find the most accurate equation form. We tested the accuracy of different PCQM equations using Monte Carlo Simulations in simulated (having ‘random’, ‘aggregated’ and ‘regular’ spatial patterns) plant populations and empirical ones.Principal FindingsPCQM requires at least 50 sample points to ensure a desired level of accuracy. PCQM with a corrected estimator is more accurate than with a previously published estimator. The published PCQM versions (PCQM1, PCQM2 and PCQM3) show significant differences in accuracy of density estimation, i.e. the higher order PCQM provides higher accuracy. However, the corrected PCQM versions show no significant differences among them as tested in various spatial patterns except in plant assemblages with a strong repulsion (plant competition). If N is number of sample points and R is distance, the corrected estimator of PCQM1 is 4(4N − 1)/(π ∑ R2) but not 12N/(π ∑ R2), of PCQM2 is 4(8N − 1)/(π ∑ R2) but not 28N/(π ∑ R2) and of PCQM3 is 4(12N − 1)/(π ∑ R2) but not 44N/(π ∑ R2) as published.SignificanceIf the spatial pattern of a plant association is random, PCQM1 with a corrected equation estimator and over 50 sample points would be sufficient to provide accurate density estimation. PCQM using just the nearest tree in each quadrant is therefore sufficient, which facilitates sampling of trees, particularly in areas with just a few hundred trees per hectare. PCQM3 provides the best density estimations for all types of plant assemblages including the repulsion process. Since in practice, the spatial pattern of a plant association remains unknown before starting a vegetation survey, for field applications the use of PCQM3 along with the corrected estimator is recommended. However, for sparse plant populations, where the use of PCQM3 may pose practical limitations, the PCQM2 or PCQM1 would be applied. During application of PCQM in the field, care should be taken to summarize the distance data based on ‘the inverse summation of squared distances’ but not ‘the summation of inverse squared distances’ as erroneously published.

This article presents a novel approach to explore mangrove dynamics on a prograding delta by integrating unmanned aerial vehicle (UAV) and satellite imagery. The Porong Delta in Indonesia has a unique geographical setting with rapid delta development and expansion of the mangrove belt. This is due to an unprecedented mud load from the LUSI mud volcanic eruption. The mangrove dynamics analysis combines UAV-based Structure from Motion (SfM) photogrammetry and 11 years (2009–2019) satellite imagery cloud computing analysis by Google Earth Engine (GEE). Our analysis shows unique, high-spatiotemporal-resolution mangrove extent maps. The SfM photogrammetry analysis leads to a 3D representation of the mangrove canopy and an estimate of mangrove biophysical properties with accurate height and individual position of the mangroves stand. GEE derived vegetation indices resulted in high (three-monthly) resolution mangrove coverage dynamics over 11 years (2009–2019), yielding a value of more than 98% for the overall, producer and consumer accuracy. Combining the satellite-derived age maps and the UAV-derived spatial tree structure allowed us to monitor the mangrove dynamics on a rapidly prograding delta along with its structural attributes. This analysis is of essential value to ecologists, coastal managers, and policymakers.

A R T I C L E I N F O Keywords:Individual-based model Model purpose Mangrove threats Model calibration Rhizophora apiculata IBMbedding A B S T R A C TWe introduce individual-based models (IBMs) of mangrove forests and criticize the tasks for their development recommended previously for being mostly related to natural threats. This is contrasted with our perspective that the key research question of today's models should be to mitigate anthropogenic threats.Core objective (1) of this article is to provide a review of mangrove threats prioritizing solution-oriented IBM approaches. Because species-specific calibration of IBMs is time-consuming, efficiency is crucial. Globally, we identify an urgent need to parametrize Asian mangrove species.We suggest IBMs to unveil management scenarios with maximum sustainable timber yield to prevent mangrove conversion and over-exploitation. The key model purpose regarding natural threats is to govern the management of mangrove forest stability for coastal protection using a combination of windthrow models and IBMs. We argue for the embedding of IBMs in ecosystem models to achieve purposes regarding eutrophication and altered hydrology/sedimentation. Core objective (2) is to describe the development of the new IBM mesoFON from a task-to a solution-oriented model. Initially, the interaction of lateral crown displacement and hurricane impacts was examined with mesoFON. Later, we introduced propagule production & local dispersal with the task to close the tree life cycle. Here, we describe the change in purpose of mesoFON accompanying its calibration for Rhizophora apiculata in Malaysia. For this we applied a Genetic Algorithm optimizer, used mesoFON as a "way-back machine", initialized it with observed tree diameters/positions and shrank the trees backwards in time.Objective (3) is to describe mesoFON's future direction: Embedding in the General Ecosystem Model (Fitz et al., 1996) and targeting the solution of threats at larger spatial scales. Finally, we demonstrate that the new model simulates overland waterflow qualitatively right even in benchmark settings.

(1,2) In this theoretical study, we apply MesoFON, a field-calibrated individual-based model of mangrove forest dynamics, and its Lotka–Volterra interpretations to address two questions: (a) Do the dynamics of two identical red mangrove species that compete for light resources and avoid inter-specific competition by lateral crown displacement follow the predictions of classical competition theory or resource competition theory? (b) Which mechanisms drive the dynamics in the presence of inter-specific crown plasticity when local competition is combined with global or with localized seed dispersal? (3) In qualitative support of classical competition theory, the two species can stably coexist within MesoFON. However, the total standing stock at equilibrium matched the carrying capacity of the single species. Therefore, a “non-overyielding” Lotka–Volterra model rather than the classic one approximated best the observed behavior. Mechanistically, inter-specific crown plasticity moved heterospecific trees apart and pushed conspecifics together. Despite local competition, the community exhibited mean-field dynamics with global dispersal. In comparison, localized dispersal slowed down the dynamics by diminishing the strength of intra-/inter-specific competition and their difference due to a restriction in the competitive race to the mean-field that prevails between conspecific clusters. (4) As the outcome in field-calibrated IBMs is mediated by the competition for resources, we conclude that classical competition mechanisms can override those of resource competition, and more species are likely to successfully coexist within communities.