Dispersal Ability and Genetic Structure in Mytilid Mussels of Whale-Fall Communities

Since organic falls are ephemeral and distributed sporadically, organisms in organic-fall communities must acquire high dispersal ability to migrate from one organic fall to another. However, the dispersal ability of obligate organic-fall organisms has not been investigated thoroughly and the stability of the genetic structure of their communities is unknown. In this study, in order to elucidate the dispersal ability and genetic structure in the organic-fall communities, we carried out population genetic analyses based on sequences of mitochondrial NADH dehydrogenase subunit 4 in two mytilid mussels.?Adipicola pacifica was obtained from whale and cow bones artificially settled in Japanese waters off Cape Noma (CN) and in the Nansei-Shoto Trench (NS) and Sagami Bay (SB), and Benthomodiolus geikotsucola from natural whale bones in the Torishima Seamount (TS);both species are symbiotic with chemoautotrophic bacteria. Genetic differentiation (Fst) indicated almost no annual change in genetic structure between 2003, 2004, 2005, and 2007 collections of A. pacificafrom CN (depth 225 - 229 m), although the 2010 collection had somewhat different genetic structure from the others. Similarly, there was not significant genetic differentiation between 1993 and 2005 collections of B.geikotsucola from TS (depth 4020 m). The Fst and gene bidirectional mean rate of gene flow (Nm) indicated high gene flow and no significant genetic differentiation between A. pacifica specimens collected from CN, NS, and SB. The results suggest that the genetic structure is stable and A. pacifica has high dispersal ability. The mismatch distribution suggests that A. pacificaexpanded their distribution from SB to NS via CN, as expansion time (τ = 2ut) decreased from SB to CN and NS.

Quantitative Evaluation of Bitterlich Sampling for Estimating Basal Area in Sparse Boreal Forests and Dense Tropical Forests

Bitterlich sampling is an extensively used technique in worldwide forest inventories. Although it has been proved that estimates of basal area from Bitterlich sampling are mathematically unbiased, its precision for individual forest stands may be fairly poor. An extension of validation efforts to different forest biomes could therefore provide more comprehensive assessment and understanding of the Bitterlich sampling technique. In this study, this technique was quantitatively evaluated by using simulated sparse boreal forests and dense tropical forests from an empirical forest structure model (EFSM). Theoretical estimation of basal areas and practical estimation influenced by the hidden-tree effect were both compared with true basal areas of the simulated forests. The evaluation results indicated that: 1) Bitterlich sampling can yield acceptable accuracy and precision when the count number (CN) of trees was set to 10 for the studied boreal and tropical forests with distinct characteristics, 2) the theoretical estimation of basal area can be improved by increasing the CN values for both forests, and 3) when the hidden-tree effect is encountered, the accuracy for tropical forests will be decreased by increasing the CN values, whereas the accuracy for boreal forests can still be improved. Accordingly, a relatively high CN, at a reasonable cost, is recommended for sparse boreal forests to improve the accuracy of basal area estimation. In contrast, for dense tropical forests, a CN of ten is appropriate to mitigate the hidden-tree effect.

Modeling three-dimensional forest structures to drive canopy radiative transfer simulations of bidirectional reflectance factor

Three-dimensional(3-D)Monte Carlo-based radiative transfer(MCRT)models are usually used for benchmarking in intercomparisons of the canopy radiative transfer(RT)simulations.However,the 3-D MCRT models are rarely applied to develop remote sensing algorithms to estimate essential climate variables of forests,due mainly to the difficulties in obtaining realistic stand structures for different forest biomes over regional to global scales.Fortunately,some of important tree structure parameters such as canopy height and tree density distribution have been available globally.This enables to run the intermediate complexities of the 3-D MCRT models.We consequently developed a statistical approach to generate forest structures with intermediate complexities depending on the inputs of canopy height and tree density.It aims at facilitating applications of the 3-D MCRT models to develop remote sensing retrieval algorithms.The proposed approach was evaluated using field measurements of two boreal forest stands at Estonia and USA,respectively.Results demonstrated that the simulations of bidirectional reflectance factor(BRF)based on the measured forest structures agreed well with the BRF based on the generated structures from the proposed approach with the root mean square error(RMSE)and relative RMSE(rRMSE)ranging from 0.002 to 0.006 and from 0.7%to 19.8%,respectively.Comparison of the computed BRF with corresponding MODIS reflectance data yielded RMSE and rRMSE lower than 0.03 and 20%,respectively.Although the results from the current study are limited in two boreal forest stands,our approach has the potential to generate stand structures for different forest biomes.