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26 results for “stock structure”
RCS01 Recovery and relative influence of root, microbial, and structural properties of soil on physically sequestered carbon stocks in restored grassland at Konza Prairie
Managing soil to sequester C can help mitigate increasing CO2 in the atmosphere. To maximize this ecosystem service, more knowledge of factors influencing C sequestration is needed. The objectives of this study were to (i) quantify recovery of the roots, microbial biomass and composition, and soil structure across a chronosequence of grassland restorations and (ii) use a structural equation model to develop a data-based hypothesis on the relative influence of physical and biological soil properties on the soil C aggregate fraction diagnostic of sequestered C. We hypothesized measured variables would recover with restoration age. Belowground plant biomass and tissue quality (C/N ratio), soil microbial biomass C, phospholipid fatty acid (PLFA) concentrations, soil structure, and soil C stocks in the bulk soil and each aggregate fraction were quantified from a cultivated field, prairies restored for 1 to 35-yr (n = 6), and a never-cultivated (native) prairie. Root biomass, microbial biomass C, arbuscular mycorrhizal fungi (AMF) PLFA biomass across the chronosequence increase to resemble native prairie following 35 yr of restoration. Many aspects of soil structure (i.e., bulk density, proportional mass of aggre- gate fractions, and aggregate mean weighted diameter) and the distribution C among soil fractions, including C in the micro-within-macro aggregate fraction (sequestered C), also became representative of native prairie within 35 yr of restoration. Total soil C stock and physically protected C increased at a similar rate (23 and 27 g C m-2 yr-1) respectively, across the chronosequence. After 35 yr of restoration, 50% of the total C pool was physically protected. The structural equation modeling developed by these data hypothesizes that microbial biomass C and AMF biomass (microbial composition) have the strongest causal influence on physically protected C. This model needs to be tested using independent sites to achieve greater inference.
Structure and composition and carbon Stocks of woody plant community in assisted and unassisted ecological succession in a Tamaulipan thornscrub, Mexico
<p>In November of 2017, the structure and composition of woody plant communities were investigated through a floristic composition and diversity evaluation on three areas: a control area, an assisted ecological succession area and an unassisted ecological succession area.</p>
Dataset and Figures for article: Ivanov P.Ch., Yuen, A., Perakakis, P., (2014). Impact of stock market structure on intertrade time and price dynamics. PLoS ONE 9(4): e92885
<p>Dataset and Figures for article: Ivanov P.Ch., Yuen, A., Perakakis, P., (2014). Impact of stock market structure on intertrade time and price dynamics. PLoS ONE 9(4): e92885</p>
FIGURE 6 in Spawning energetics and otolith microchemistry provide insights into the stock structure of bonga shad Ethmalosa fimbriata
FIGURE 6 Quadratic discriminant function analysis of the (a) spawning energetics, (b) otolith element:Ca ratios and (c) both techniques combined in female Ethmalosa fimbriata sampled at Joal (Senegalese southern coast), Djifer (Saloum River mouth) and Foundiougne (Saloum River middle reaches) from February to October 2014. Ellipsoids encompass c. 50% of a sampling station's data points
FIGURE 4 in Spawning energetics and otolith microchemistry provide insights into the stock structure of bonga shad Ethmalosa fimbriata
FIGURE 4 Relationships between Ethmalosa fimbriata oocyte dry mass and (a) lipid content, and (b) protein content from fish in southern Senegalese coastal waters. Specimens were sampled at Joal (Senegalese southern coast), Djifer (Saloum River mouth) and Foundiougne (Saloum River middle reaches) from February to October 2014
FIGURE 2 in Spawning energetics and otolith microchemistry provide insights into the stock structure of bonga shad Ethmalosa fimbriata
FIGURE 2 Ground otolith of a female Ethmalosa fimbriata specimen (total length, LT = 23.1 cm) embedded in epoxy resin. The specimen was sampled at Foundiougne (Sine Saloum, Senegal) in May 2014. The ablation path can be seen along the edge of the otolith's rostrum
FIGURE 1 in Spawning energetics and otolith microchemistry provide insights into the stock structure of bonga shad Ethmalosa fimbriata
FIGURE 1 The Senegalese southern coast and the Sine Saloum Estuary, including sampling sites (): Joal, Senegalese southern coast; Djifer, Saloum River mouth; Foundiougne, Saloum River middle reaches
FIGURE 3 in Spawning energetics and otolith microchemistry provide insights into the stock structure of bonga shad Ethmalosa fimbriata
FIGURE 3 Total length–frequency distribution of Ethmalosa fimbriata females with hydrated oocytes. Sampling took place at Joal (Senegalese southern coast), Djifer (Saloum River mouth) and Foundiougne (Saloum River middle reaches) from February to October 2014
FIGURE 7 in Spawning energetics and otolith microchemistry provide insights into the stock structure of bonga shad Ethmalosa fimbriata
FIGURE 7 Mean (a) Ba:Ca and (b) Sr:Ca ratios of female Ethmalosa fimbriata otoliths in relationship with surface water temperature. Individuals were sampled at Joal (Senegalese southern coast), Djifer (Saloum River mouth) and Foundiougne (Saloum River middle reaches) from February to October 2014
FIGURE 5 in Spawning energetics and otolith microchemistry provide insights into the stock structure of bonga shad Ethmalosa fimbriata
FIGURE 5 (a) Monthly mean (SD; n, sample size) oocyte energy content and (b) boxplots (, median; ⊺, 5th and 95th percentiles;, outliers) of spawning batch energy content of female Ethmalosa fimbriata sampled at Joal (Senegalese southern coast), Djifer (Saloum River mouth) and Foundiougne (Saloum River middle reaches) from February to October 2014. Different lowercase letters indicate significant differences (P <0.05). Movfree, Ovary-free body mass
Dataset: Structure Therapeutics Inc. (GPCR) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
FIGURE 4 in Temporal genetic structure of a stock of Prochilodus lineatus (Characiformes: Prochilodontidae) in the Mogi-Guaçu River ecosystem, São Paulo, Brazil
FIGURE 4 | Bayesian skyline plot (BSP) showing change in effective population size of Prochilodus lineatus in Feb_15 group from Cachoeira de Emas in the Mogi-Guaçu River based on Dloop marker. The y-axis, population size × generation time*; x-axis, time (indicated in thousands of years ago). *Generation time measured in million years. Solid lines represent median estimates, and shaded areas represent the 95% HPD limits.
FIGURE 3 in Temporal genetic structure of a stock of Prochilodus lineatus (Characiformes: Prochilodontidae) in the Mogi-Guaçu River ecosystem, São Paulo, Brazil
FIGURE 3 | Median-joining network of Prochilodus lineatus, based on haplotypes of D-loop marker. Sizes of the circled are proportional to the frequencies of the haplotypes at issue. The colors indicate the groups according to the collections: red circles: Sep_03; yellow circles: Jan_05; purple circles: Aug_05; blue circles: Jan_06; pink circles: Jan_09; green circles: Sep_10; pastel pink circles: Feb_15. Hatch marks represent the number of mutations by which haplotypes differ.
FIGURE 1 in Temporal genetic structure of a stock of Prochilodus lineatus (Characiformes: Prochilodontidae) in the Mogi-Guaçu River ecosystem, São Paulo, Brazil
FIGURE 1 | Map of the State of Sao Paulo showing the main components of the hydrographic system in the Southeast of Brazil. In detail square, the collection site of samples located in Cachoeira de Emas, Pirassununga-SP. The Mogi-Guaçu River is a component of the Upper Paraná River basin.
FIGURE 2 in Temporal genetic structure of a stock of Prochilodus lineatus (Characiformes: Prochilodontidae) in the Mogi-Guaçu River ecosystem, São Paulo, Brazil
FIGURE 2 | Graph of the Bayesian analysis of population structure of microsatellites for Prochilodus lineatus. A. Delta(k) showing the highest value in a population structure of K = 3; B. The estimated mean log-likelihoods [ln(PrK)]; C. Structure bar plot. Black lines separate the different sampled populations based on temporal collection.
Mixed-stock analysis using Rapture genotyping to evaluate stock-specific exploitation of a walleye population despite weak genetic structure
<p>Mixed-stock analyses using genetic markers have informed fisheries management in cases where strong genetic differentiation occurs among local spawning populations, yet many fisheries are supported by multiple spawning stocks that are weakly differentiated. Freshwater fisheries exemplify this problem, with many harvested populations supported by multiple stocks of young evolutionary age and that are isolated across small spatial scales. As a result, attempts to conduct genetic mixed-stock analyses of inland fisheries have often been unsuccessful. Advances in genomic sequencing now offer the ability to discriminate among populations with weak population structure, by providing the necessary resolution to conduct mixed-stock assignment among previously indistinguishable stocks. We demonstrate the use of genomic data to conduct a mixed-stock analysis of Lake Erie's commercial and recreational walleye (<em>Sander vitreus</em>) fisheries and estimate the relative harvest of weakly differentiated stocks. We used RAD-capture (Rapture) to sequence and genotype individuals at 12,081 loci that had been previously determined to be capable of discriminating between western and eastern basin stocks (mean pairwise F<sub>ST</sub> = 0.001) with 95% reassignment accuracy. An outcome not possible in the past with microsatellite markers. Genetic assignment of 1,075 fish harvested from recreational and commercial fisheries in the eastern basin indicated that western basin stocks supported the majority of the harvest during peak harvest (July – September). Composition of harvest changed seasonally, with eastern basin fish comprising much of the early season harvest (May – June). Clear spatial structure in stock-specific harvest existed; more easterly sites contained more individuals of east basin origin than did westerly sites. Our study provides important stock contribution estimates for Lake Erie fishery management and demonstrates the power of genomic data to facilitate mixed-stock analysis in exploited fish populations with weak population structure or limited existing genetic resources.</p>
Mixed-stock analysis using Rapture genotyping to evaluate stock-specific exploitation of a walleye population despite weak genetic structure
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Historical translocations and stocking alter the genetic structure of a Mediterranean lobster fishery
Stocking is often used to supplement wild populations that are overexploited or have collapsed, yet it is unclear how this affects the genetic diversity of marine invertebrate populations. During the 1970s, a lobster stock enhancement programme was carried out around the island of Corsica in the Mediterranean using individuals translocated from the Atlantic coast of France. This included the release of thousands of hatchery-reared post-larval lobsters and several adult individuals, but no monitoring plan was established to assess whether these animals survived and recruited to the population. In this study, we sampled European lobster (<i>Homarus gammarus</i>) individuals caught around Corsica and tested whether they showed Atlantic ancestry. Due to a natural marked phylogeographic break between Atlantic and Mediterranean lobsters, we hypothesised that lobsters with dominant (>0.50) Atlantic ancestry were descended from historical stocking releases. Twenty Corsican lobsters were genotyped at 79 single nucleotide polymorphisms and assignment analysis showed that the majority (13) had dominant Atlantic ancestry. This suggests that the hatchery stocking programme carried out in Corsica during the 1970s, using individuals translocated from the Atlantic coast of France, has likely augmented local recruitment but at a cost of altering the genetic structure of the Corsican lobster population.
Contemporary genetic structure affects genetic stock identification of steelhead trout in the Snake River basin
<p>Genetic stock identification is a widely applied tool for the mixed-stock management of salmonid species throughout the North Pacific Rim. The effectiveness of genetic stock identification is dependent on the level of differentiation among stocks which is often high due to the life history of these species that involves high homing fidelity to their natal streams. However, the utility of this tool can be reduced when natural genetic structuring has been altered by hatchery translocation and/or supplementation. We examined the genetic population structure of ESA-listed steelhead in the Snake River basin of the United States. We analyzed 9,613 natural-origin adult steelhead returning to Passive Integrated Transponder detection sites throughout the basin from 2010 through 2017. Individuals were genotyped at 180 single nucleotide polymorphic genetic markers and grouped into 20 populations based on their return location. While we expected to observe a common pattern of hierarchical genetic structuring due to isolation by distance, we observed low genetic differentiation between populations in the upper Salmon River basin compared to geographically distant populations in the lower Snake River basin. These results were consistent with lower genetic stock assignment probabilities observed for populations in this upper basin. We attribute these patterns of reduced genetic structure to the translocation of lower basin steelhead stocks and ongoing hatchery programs in the upper Salmon River basin. We discuss the implications of these findings on the utility of genetic stock identification in the basin and discuss opportunities for increasing assignment probabilities in the face of low genetic structure.</p>
Data from: Migratory culture, population structure and stock identity in North Pacific beluga whales (Delphinapterus leucas)
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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