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Canopy disturbance explains liana abundance and distribution within tropical forests and thus may also explain the widespread pattern of increasing liana abundance; however, this hypothesis remains untested. We used a 10‐year study (2007–2017) of 117,100 rooted lianas in an old‐growth Panamanian forest to test whether local canopy disturbance explains increasing liana abundance. We found that liana density increased 29.2% and basal area 12.5%. The vast majority of these increases were associated with clonal stem proliferation following canopy disturbance, particularly in liana‐dense, low‐canopy gaps, which had far greater liana increases than did undisturbed forest. Lianas may be ecological niche constructors, arresting tree regeneration in gaps and thus creating a high‐light environment that favours sustained liana proliferation. Our findings demonstrate that liana abundance is increasing rapidly and their ability to proliferate via copious clonal stem production in canopy gaps explains much of their increase in this and possibly other tropical forests. [ABSTRACT FROM AUTHOR]

1. Seed and pollen dispersal is often directionally biased, because of the inherent directionality of wind and many other dispersal vectors. Nevertheless, the vast majority of studies of seed and pollen dispersal fit isotropic dispersal kernels to data, implicitly assuming that dispersal is equally likely in all directions. 2. Here, we offer a flexible method for stochastic modelling of directional dispersal data. We show how anisotropic models can be constructed by combining standard dispersal functions with 'distorted-distance functions' that transform the circular contour lines of any isotropic dispersal kernel into non-circular shapes. Many existing anisotropic phenomenological models of seed and pollen dispersal are special cases of our framework. 3. We present functional forms for the specific case of elliptic distorted-distance functions, under which contour lines of the seed shadow become non-concentric, nested ellipses, and show how models using these functions can be constructed and parameterized. R-code is provided. 4. We applied the elliptic anisotropic models to characterize seed dispersal in the wind-dispersed Neotropical tree Luehea seemannii (Malvaceae) on Barro Colorado Island, Panama. We used inverse modelling to fit alternative models to data of seed rain into seed traps, the locations of seed traps and adult trees, and tree size. 5. Our anisotropic model performed considerably better than commonly applied isotropic models, revealing that seed dispersal of L. seemannii was strongly directional. The best-fitting model combined a 3-parameter elliptic distorted-distance function that captured the strong directional biases with a 1-parameter exponential dispersal kernel, a 1-parameter negative binomial probability distribution describing the clumping of seed rain and a 1-parameter function relating tree fecundity to tree diameter. 6. The framework presented in this paper enables more flexible and accurate modelling of directional dispersal data. It is applicable not only to studies of seed dispersal, but also to a wide range of other problems in which large numbers of particles disperse from one or more point sources. [ABSTRACT FROM AUTHOR]

Negative density dependence (NDD) of recruitment is pervasive in tropical tree species. We tested the hypotheses that seed dispersal is NDD, due to intraspecific competition for dispersers, and that this contributes to NDD of recruitment. We compared dispersal in the palm Attalea butyracea across a wide range of population density on Barro Colorado Island in Panama and assessed its consequences for seed distributions. We found that frugivore visitation, seed removal and dispersal distance all declined with population density of A. butyracea, demonstrating NDD of seed dispersal due to competition for dispersers. Furthermore, as population density increased, the distances of seeds from the nearest adult decreased, conspecific seed crowding increased and seedling recruitment success decreased, all patterns expected under poorer dispersal. Unexpectedly, however, our analyses showed that NDD of dispersal did not contribute substantially to these changes in the quality of the seed distribution; patterns with population density were dominated by effects due solely to increasing adult and seed density., (© 2014 John Wiley & Sons Ltd/CNRS.)