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8 results for “riverine dispersal”
Data from: Estimates of gene flow and dispersal in wild riverine Brook Trout (Salvelinus fontinalis) populations reveal ongoing migration and introgression from stocked fish
As anthropogenic impacts accelerate changes to landscapes across the globe, understanding how genetic population structure is influenced by habitat features and dispersal is key to preserving evolutionary potential at the species level. Furthermore, knowledge of these interactions is essential to identifying potential constraints on local adaptation and for the development of effective management strategies. We examined these issues in Brook Trout (Salvelinus fontinalis) populations residing in the Upper Hudson River watershed of New York State by investigating the spatial genetic structure of over 350 fish collected from 14 different sampling locations encompassing three river systems. Population genetic analyses of microsatellite data suggest that fish in the area exhibit varying degrees of introgression from nearby State-directed supplementation activities. Levels of introgression in these populations correlate with water-way distance to stocking sites, although genetic population structure at the level of individual tributaries as well as their larger, parent river systems is also detectable and is dictated by migration and influenced by habitat connectivity. These findings represent a significant contribution to the current literature surrounding Brook Trout migration and dispersal, especially as it relates to larger interconnected systems. This work also suggests that stocking activities may have far-reaching consequences that are not directly limited to the immediate area where stocking occurs. The framework and data presented here may aid in the development of other local aquatic species-focused conservation plans that incorporate molecular tools to answer complex questions regarding diversity mapping, and genetically important conservation units.
Riverine sediment geochemistry and its dispersal pattern on the western Sunda Shelf
<p>Table 1: Published Sr-Nd isotopic ratios on Sunda Shelf and South China Sea (SCS)</p> <p>Fig. 1 Normalized REE diagram of Sunda Shelf sediments with multiple references. </p> <p>Fig. 2 Corrected Eu values versus Ba/Sm ratios. The δEu ratios in this study were corrected for Ba16O+ interferences by the formula given by Dulski (1994). After the correction, the corrected ratios show only weak correlation with Ba/Sm ratios.</p> <p>Fig. 3 Correlation between δEu and Th concnetrations of Pahang and Kelantan river sediments</p> <p>Fig. 4 Correlation between Rb/Sr ratio and 87Sr/86Sr ratios in sediment samples</p> <p>Fig. 5 Correlation between Sr (A)-Nd (B) isotopic composition and grain sizes (Mz) in Pahang, Kelantan, Rajang and Mekong river sediments</p>
Data from: Estimates of gene flow and dispersal in wild riverine Brook Trout (Salvelinus fontinalis) populations reveal ongoing migration and introgression from stocked fish
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By animal, water, or wind: can dispersal mode predict genetic connectivity in riverine plant species?
<div class="page"> <div class="section"> <div class="layoutArea"> <div class="column"> <p>Seed dispersal is crucial to gene flow among plant populations. Although the effects of geographic distance and barriers to gene flow are well studied in many systems, it is unclear how seed dispersal mediates gene flow in conjunction with interacting effects of geographic distance and barriers. To test whether distinct seed dispersal modes (i.e. hydrochory, anemochory, and zoochory) have a consistent effect on the level of genetic connectivity (i.e., gene flow) among populations of riverine plant species, we used unlinked single-nucleotide polymorphisms (SNPs) for eight co-distributed plant species sampled across the Rio Branco, a putative biogeographic barrier in the Amazon Basin. We found that animal-dispersed plant species exhibited higher levels of genetic diversity and lack of inbreeding as a result of the stronger genetic connectivity than plant species whose seeds are dispersed by water or wind. Interestingly, our results also indicated that the Rio Branco facilitates gene dispersal for all plant species analyzed, irrespective of their mode of dispersal. Our findings indicate that seed dispersal mode and riverscape features can greatly impact genetic structure, representing reliable predictors of genetic connectivity in riverine plant species. These results may help improve conservation and management policies in Amazonian riparian forests, where degradation and deforestation rates are high.</p> </div> </div> </div> </div>
Riverine sediment geochemistry and its dispersal pattern on the western Sunda Shelf
<p>Table 1: Sample locations, trace element concentrations (ppm), and Sr-Nd isotopes of the sediments analyzed in this study.</p> <p>Table 2: Published Sr-Nd isotopic ratios on Sunda Shelf and South China Sea (SCS).</p> <p>Fig. 1 Normalized REE diagram of Sunda Shelf sediments with multiple references. </p> <p>Fig. 2 Corrected Eu values versus Ba/Sm ratios. The δEu ratios in this study were corrected for Ba16O+ interferences by the formula given by Dulski (1994). After the correction, the corrected ratios show only a weak correlation with Ba/Sm ratios.</p> <p>Fig. 3 Correlation between δEu and Th concentrations of Pahang and Kelantan river sediments.</p> <p>Fig. 4 Correlation between Rb/Sr ratio and 87Sr/86Sr ratios in sediment samples.</p> <p>Fig. 5 Correlation between (A) 87Sr/86Sr ratios and grain sizes (Mz), and (B) ɛNd and grain sizes (Mz) in Pahang, Kelantan, Rajang and Mekong river sediments</p>
By animal, water, or wind: can dispersal mode predict genetic connectivity in riverine plant species?
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Riverine sediment geochemistry and its dispersal pattern on the western Sunda Shelf
<p>Table 1: Sample locations, trace element concentrations (ppm), and Sr-Nd isotopes of the sediments analyzed in this study.</p> <p>Table 2: Published Sr-Nd isotopic ratios on Sunda Shelf and South China Sea (SCS).</p> <p>Fig. 1 Normalized REE diagram of Sunda Shelf sediments with multiple references. </p> <p>Fig. 2 Corrected Eu values versus Ba/Sm ratios. The δEu ratios in this study were corrected for Ba16O+ interferences by the formula given by Dulski (1994). After the correction, the corrected ratios show only a weak correlation with Ba/Sm ratios.</p> <p>Fig. 3 Correlation between δEu and Th concentrations of Pahang and Kelantan river sediments.</p> <p>Fig. 4 Correlation between Rb/Sr ratio and 87Sr/86Sr ratios in sediment samples.</p> <p>Fig. 5 Correlation between Sr (A)-Nd (B) isotopic composition and grain sizes (Mz) in Pahang, Kelantan, Rajang, and Mekong river sediments.</p>
Data from: Asymmetric dispersal structures a riverine metapopulation of the freshwater pearl mussel Margaritifera laevis
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Allen Brain Atlas
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
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