Several methods are used to estimate the spatial pattern of seed dispersal. However, each method has specific shortcomings that limit the accuracy and reliability of the resulting dispersal models. In this study we compared seed shadows of the anemochoric species Abies alba Mill. obtained from (1) phenomenological models derived from seed trapping data and inverse modelling, (2) ballistic models based on wind speed at canopy height and an exponential wind profile and (3) empirical models parameterised from seed-tracking data. In addition, we checked whether the empirical model coupled with multiannual wind characteristics provides a dispersal pattern concordant with the gene shadow obtained from parentage assignment between seedlings and overstorey trees. The seed trap and seed-tracking experiments were conducted in 2013 and 2015 with contrasting wind conditions in five study plots located in the Krynica Forest Experimental Station in southern Poland. Genetic data originated from 16 mature stands with dominant A. alba. The study revealed that the distances reached by single seeds strongly vary at the same wind speed at canopy height. The ballistic model overestimated the flight distances of A. alba seeds. Similarly, the empirical model calibrated on data that disregarded seeds trapped in the crowns of neighbouring conifer trees predicted longer flight distances than those derived from the seed trap experiments. The gene shadow obtained from the parentage analysis suggests dispersal patterns concordant with those anticipated by the empirical model based on the seed-tracking experiments, with a possible shift towards an increased proportion of seeds landing close to the source. It was concluded that in dense canopies collisions with canopy elements during seed flight and secondary dispersion of seeds trapped in the canopy zone may considerably shorten the travel distances of A. alba seeds.

 

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In the Colombian Caribbean, 44 permanent sampling plots (PSPs) on teak (Tectona grandis) plantations in 20 stands ranging in age from 3 to 20 years have been measured annually for 17 years. We have developed a compatible growth and yield model using the state-space approach and Kopf’s growth equation fitted by nonlinear mixed-effects-models (NLMEMs). For each site index class, the transition function of the basal area depends on the initial basal area (G1) and the initial age (t1), projected to a future basal area (G2) and its age (t2). In the transition function, the previous thinnings were added to not underestimate the total yield. We use NLMEMs to prevent autocorrelation by modeling annual measurements in the PSPs. The transition function is inserted in allometric stand models of three key variables: volume over bark, the volume under bark, and above-ground biomass. Tree allometric models for volume over bark, the volume under bark, and biomass were parameterized, self-validated, independently validated, and recalibrated. Stand allometric models for the same three key variables, as a function of the stand basal area, were parameterized by using NLMEMs to evaluate proportional variance to the mean and variance as a potential function of the mean. In both tree and stand allometric models, the assumptions of the regression have been fulfilled. The resulting growth and yield model allows for the estimation of current growth and predicts future yields in volumes and above-ground biomass arising from thinnings treatments. The proposed model is a useful tool for teak efficient plantations management. The proposed growth models for teak in this paper may have a potential utility in newly teak planted areas, where such tools are scarce or non-existent.

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