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Fig. 4 in Growth Rate Modulation Enables Coexistence in a Competitive Exclusion Scenario Between Microbial Eukaryotes
Fig. 4. Posterior estimates of the parameters of models fitted to cell counts in each culture. Each panel shows the medians (dots) and 95% credibility intervals (lines) of posterior distributions of one parameter of the models fitted to data from a replicate (seven for the competition cultures in lower part and three for mono-specific cultures in the upper part). In red, estimates for Arcella intermedia and in blue estimates for Pyxidicula operculata. The values of K are in cm–2, r are in days–1. The competition coefficients are α (red) and β (blue) of Eqs. 3–4.
Fig. 1 in Growth Rate Modulation Enables Coexistence in a Competitive Exclusion Scenario Between Microbial Eukaryotes
Fig. 1. Species used in this study. A – Arcella intermedia LEP isolate 6, magnification 630×. B – Pyxidicula operculata LEP isolate 1, magnification 1000×.
Figure 7 in Conditioning of desert sandy soil and investigation of the ameliorative effects of poultry manure and bentonite treatment rate on plant growth
Figure 7. Principal component analysis (PCA) showing loading of each studied attribute (arrow) and arrow lengths approximate their variance whereas the angles between them represent their correlation.The abbreviations are Poultry Manure (PM), Bentonite (B), Plant Height (PH), Number of Leaves (L), Root Length (RL), Dry Shoot Weight (DS), Dry Root Length (DR), Root to Shoot Ratio (RS), Number of Secondary Branches (SB), Max Branch Length (LPB), Chlorophyll contents (SPAD), Chlorophyll a* (CHL a), Chlorophyll b* (CHL b).
Figure 5 in Conditioning of desert sandy soil and investigation of the ameliorative effects of poultry manure and bentonite treatment rate on plant growth
Figure 5. Corrplot (Correlation plot) represents correlation matrix among different attributes of Bougainvillea followed by treatments as (1) L100 (2) L95A (3) L95B (4) L90A (5) L90B. L100 substrate contains 100% Lehbab Sandy Soil without any addition of Bentonite and Poultry Manure. L95A substrate contains 95% Lehbab Sandy Soil, 5% Bentonite, and 10% Poultry Manure.L95B substrate contains 95% Lehbab Sandy Soil, 5% Bentonite, and 15% Poultry Manure. L90A substrate contains 90% Lehbab Sandy Soil, 10% Bentonite, and 10% Poultry Manure. L90B substrate contains 90% Lehbab Sandy Soil, 10% Bentonite, and 15% Poultry Manure. The dark blue color shows a high positive correlation while light blue and sky blue represent less association among measured parameters. The color legend on the right-hand side of corrplot shows the correlation coefficient and corresponding colors. The abbreviations are Lehbab Sandy Soil (LS) Poultry Manure (PM), Bentonite (B), Plant Height (PH), Number of Leaves (L), Root Length (RL), Dry Shoot Weight (DS), Dry Root Length (DR), Root to Shoot Ratio (RS), Number of Secondary Branches (SB), Max Branch Length (LPB), Chlorophyll contents (SPAD), Chlorophyll a* (CHL a), Chlorophyll b* (CHL b).
Figure 3 in Conditioning of desert sandy soil and investigation of the ameliorative effects of poultry manure and bentonite treatment rate on plant growth
Figure 3. Comparison of Dry Shoot Weight, Dry Root Weight, and Root/Shoot ratio for Bougainvillea plants grown in different substrates (Treatment L100, L95A, L95B, L90A, and L90B. L100 substrate contains 100% Lehbab Sandy Soil without any addition of Bentonite and Poultry Manure. L95A substrate contains 95% Lehbab Sandy Soil, 5% Bentonite, and 10% Poultry Manure. L95B substrate contains 95% Lehbab Sandy Soil, 5% Bentonite, and 15% Poultry Manure. L90A substrate contains 90% Lehbab Sandy Soil, 10% Bentonite, and 10% Poultry Manure. L90B substrate contains 90% Lehbab Sandy Soil, 10% Bentonite, and 15% Poultry Manure. Statistical letters a, b, c, d, show significant difference between plants attributes grown on different substrates, while the ab, bc, cd etc. show there is no significant difference between plants attributes.
Figure 2 in Conditioning of desert sandy soil and investigation of the ameliorative effects of poultry manure and bentonite treatment rate on plant growth
Figure 2. Comparison of Number of Secondary Branches per Plant and Number of Leaves per Plant for Bougainvillea grown in different substrates (Treatment L100, L95A, L95B, L90A, and L90B. L100 substrate contains 100% Lehbab Sandy Soil without any addition of Bentonite and Poultry Manure. L95A substrate contains 95% Lehbab Sandy Soil, 5% Bentonite, and 10% Poultry Manure. L95B substrate contains 95% Lehbab Sandy Soil, 5% Bentonite, and 15% Poultry Manure. L90A substrate contains 90% Lehbab Sandy Soil, 10% Bentonite, and 10% Poultry Manure. L90B substrate contains 90% Lehbab Sandy Soil, 10% Bentonite, and 15% Poultry Manure. Statistical letters a, b, c, d, show significant difference between plants attributes grown on different substrates, while the ab, bc, cd etc. show there is no significant difference between plants attributes.
Figure 1 in Conditioning of desert sandy soil and investigation of the ameliorative effects of poultry manure and bentonite treatment rate on plant growth
Figure 1. Comparison of Plant Height, Root Length, and Maximum Branch Length for Bougainvillea grown in different substrates (Treatment L100, L95A, L95B, L90A, and L90B. L100 substrate contains 100% Lehbab Sandy Soil without any addition of Bentonite and Poultry Manure. L95A substrate contains 95% Lehbab Sandy Soil, 5% Bentonite, and 10% Poultry Manure.L95B substrate contains 95% Lehbab Sandy Soil, 5% Bentonite, and 15% Poultry Manure.L90A substrate contains 90% Lehbab Sandy Soil, 10% Bentonite, and 10% Poultry Manure. L90B substrate contains 90% Lehbab Sandy Soil, 10% Bentonite, and 15% Poultry Manure. Statistical letters a, b, c, d, show significant difference between plants attributes grown on different substrates, while the ab, bc, cd etc. show there is no significant difference between plants attributes.
Figure 4 in Influence of Trichoderma harzianum and Bacillus thuringiensis with reducing rates of NPK on growth, physiology, and fruit quality of Citrus aurantifolia
Figure 4. Effect of two biofertilizers mixing with different level of NPK on leaf TSS content of Key lemon (Limau nipis). Error bars indicates ±SE. Different letters in the bar graph represent the statistically significant at 5% level. T0, control; T1, NPK 100% (100 g); T2, T. harzianum 50% (5g) + NPK 50%; T3, B. thuringiensis 50% (5g) + NPK 50%; T4, T. harzianum 75% (7.5g) + NPK 25%; T5, B. thuringiensis 75% (7.5 g) + NPK 25%, T6, 100% T. harzianum (10 g); T7, 100% B. thuringiensis (10 g).
Figure 5 in Influence of Trichoderma harzianum and Bacillus thuringiensis with reducing rates of NPK on growth, physiology, and fruit quality of Citrus aurantifolia
Figure 5. Effect of two biofertilizers mixing with different level of NPK on fruit TSS content of Key lemon (Limau nips). Error bars indicates ±SE. Different letters in the bar graph represent the statistically significant at 5% level. T0, control; T1, NPK 100% (100 g); T2, T. harzianum 50% (5g) + NPK 50%; T3, B. thuringiensis 50% (5g) + NPK 50%; T4, T. harzianum 75% (7.5g) + NPK 25%; T5, B. thuringiensis 75% (7.5 g) + NPK 25%, T6, 100% T. harzianum (10 g); T7, 100% B. thuringiensis (10 g).
Figure 1 in Influence of Trichoderma harzianum and Bacillus thuringiensis with reducing rates of NPK on growth, physiology, and fruit quality of Citrus aurantifolia
Figure 1. Effect of two biofertilizers mixing with different level of NPK on specific leaf area of limau nipis. Error bars indicate ± S. E. Different small case letters in mean value bars represent statistical difference at 5% level. T0, control; T1, NPK 100% (100 g); T2, T. harzianum 50% (5g) + NPK 50%; T3,B. thuringiensis 50% (5g) + NPK 50%; T4, T. harzianum 75% (7.5g) + NPK 25%; T5, B. thuringiensis 75% (7.5 g) + NPK 25%, T6, 100% T. harzianum (10 g); T7, 100% B. thuringiensis (10 g).
Fig. 2 in Do growth rate and survival differ between undisturbed and disturbed environments for Sceloporus spinosus Wiegmann, 1828 (Squamata: Phrynosomatidae) from Oaxaca, Mexico?
Fig. 2. Growth rate of Sceloporus spinosus. (A) Undisturbed area (UA) males, (B) Disturbed area (DA) males, (C) UA females, and (D) DA females. Black circles represent data points for individual lizards. Modeled relationships between growth and body sizes of males and females: solid lines = Von Bertalanffy, dashed lines = logistic by length, and dotted lines = logistic by mass.
Fig. 1 in Do growth rate and survival differ between undisturbed and disturbed environments for Sceloporus spinosus Wiegmann, 1828 (Squamata: Phrynosomatidae) from Oaxaca, Mexico?
Fig. 1. Map of the study area. The green polygon depicts Yagul Natural Protected Area, including the two sampling sites (UA = undisturbed area; DA = disturbed area, land use change).
Fig. 3. Means and 95 in Do growth rate and survival differ between undisturbed and disturbed environments for Sceloporus spinosus Wiegmann, 1828 (Squamata: Phrynosomatidae) from Oaxaca, Mexico?
Fig. 3. Means and 95% confidence intervals of the Asymptotic growth (A) and Characteristic growth (r) parameters obtained by 1 the Von Bertalanffy and logistic by length models for males and females of Sceloporus spinosus in both Disturbed area (DA) and Undisturbed area (UA) populations.
Figure 3 in Colonization, hatching dates, and growth rates of juvenile Hyporhamphus picarti (Hemiramphidae), in the Nador lagoon (NE Morocco)
Figure 3. - Mean monthly air temperature (°C) at Nador during 2012 and 2013. (X) indicate water temperature at each sampling date in 2012 and 2013.
Figure 1 in Colonization, hatching dates, and growth rates of juvenile Hyporhamphus picarti (Hemiramphidae), in the Nador lagoon (NE Morocco)
Figure 1. - The Nador lagoon and location of the six sampling stations. Black arrows indicate the hourly sense of the water flow in the lagoon. White arrows indicate the main freshwater inputs. Some geographical features cited in the text are indicated.
Dataset for "On the potential of the Cluster Ion Counter (CIC) to observe local new particle formation, condensation sink and growth rate of newly formed particles"
<p>Data for Kulmala et al. (2024 )"On the potential of the Cluster Ion Counter (CIC) to observe local new particle formation, condensation sink and growth rate of newly formed particles" (https://doi.org/10.5194/ar-2024-14).</p> <p>Included in the file are number concentrations of sub-2 nm ions and 2-2.3 nm ions measured with Cluster Ion Counter (CIC) and Neutral cluster and Air Ion Spectrometer (NAIS) at SMEAR II station in Hyytiälä, Finland. Concentrations of 1-2 nm ions measured with the NAIS are also included. Sub-2 nm (2-2.3 nm) ion concentrations measured with CIC are refered as Channel 1 (Channel 2-Channel 3) in the .csv file.</p> <p>Contact Santeri Tuovinen (santeri.tuovinen@helsinki.fi) for more details.</p>
Hepatic transcriptomic analysis reveals differential regulation of metabolic and immune pathways in three strains of chickens with distinct growth rate exposed to mixed parasites infections
<p><span>This dataset was generated from the study investigating hepatic gene expression in three strains of chickens: Ross-308 (R), Lohmann Brown Plus (LB), and Lohmann Dual (LD), 2 weeks after either an experimental infection (n = 18) with both <em>A. galli</em> and <em>H. gallinarum or kept as uninfected control (n = 12)</em>. </span></p>
Data from: Selection on growth rate and local adaptation drive genomic adaptation during experimental range expansions in the protist Tetrahymena thermophila
<p>1. Populations that expand their range can undergo rapid evolutionary adaptation of life-history traits, dispersal behaviour, and adaptation to the local environment. Such adaptation may be aided or hindered by sexual reproduction, depending on the context.</p> <p>2. However, few empirical and experimental studies have investigated the genetic basis of adaptive evolution during range expansions. Even less attention has been given to the question how sexual reproduction may modulate such adaptive evolution during range expansions.</p> <p>3. We here studied genomic adaptation during experimental range expansions of the protist <em>Tetrahymena thermophila</em>in landscapes with a uniform environment or a pH-gradient. Specifically, we investigated two aspects of genomic adaptation during range expansion. Firstly, we investigated adaptive genetic change in terms of the underlying numbers of allele frequency changes from standing genetic variation and <em>de novo</em><span> variants. We focused on how sexual reproduction may alter this adaptive genetic change. Secondly, we identified genes subject to selection caused by the expanding range itself, and directional selection due to the presence or absence of the pH-gradient. We focused this analysis on alleles with large frequency changes that occurred in parallel in more than one population to identify the most likely candidate targets of selection. </span></p> <p><span>4. We found that sexual reproduction altered adaptive genetic change both in terms of <em>de novo</em></span><span> variants and standing genetic variation. However, sexual reproduction affected allele frequency changes in standing genetic variation only in the absence of long-distance gene flow. Adaptation to the range expansion affected genes involved in cell divisions and DNA repair, whereas adaptation to the pH-gradient additionally affected genes involved in ion balance, and oxidoreductase reactions. These genetic changes may result from selection on growth and adaptation to low pH. </span></p> <p><span>5. In the absence of gene flow, sexual reproduction may have aided genetic adaptation. Gene flow may have swamped expanding populations with maladapted alleles, thus reducing the extent of evolutionary adaptation during range expansion. Sexual reproduction also altered the genetic basis of adaptation in our evolving populations via <em>de novo </em>variants, possibly by purging deleterious mutations or by revealing fitness benefits of rare genetic variants. </span></p>
Supplementary Data to: "Quantifying sub-seasonal growth rate changes in fossil giant clams using wavelet transformation of daily Mg/Ca cycles" in Geochemistry, Geophysics, Geosystems
<p>El/Ca data and high resolution images of 3 laser-ablation tracks on a fossil giant calm. The following Isotopes were monitored <sup>11</sup>B, <sup>23</sup>Na, <sup>24</sup>Mg, <sup>27</sup>Al, <sup>43</sup>Ca, <sup>88</sup>Sr, <sup>89</sup>Y and <sup>138</sup>Ba. The data was measured with laser-ablation inductively coupled plasma mass spectrometry (LA-ICPMS) using a 3 x 33 µm laser slit. El/Ca ratios were calibrated using NIST SRM 612 as bracketing external standard (Jochum et al., 2011) with updated Mg values from Evans & Müller (2018) and <sup>43</sup>Ca as the internal standard; data quantification follows Longerich et al. (1996) and was performed using the software iolite 4 (Paton et al., 2011). For details see main text.</p> <p>References:</p> <p>Evans, D., & Müller, W. (2018). Automated Extraction of a Five-Year LA-ICP-MS Trace Element Data Set of Ten Common Glass and Carbonate Reference Materials: Long-Term Data Quality, Optimisation and Laser Cell Homogeneity. <em>Geostandards and Geoanalytical Research</em>, <em>42</em>(2), 159–188. https://doi.org/10.1111/ggr.12204</p> <p>Jochum, K. P., Weis, U., Stoll, B., Kuzmin, D., Yang, Q., Raczek, I., Jacob, D. E., Stracke, A., Birbaum, K., Frick, D. A., Günther, D., & Enzweiler, J. (2011). Determination of Reference Values for NIST SRM 610–617 Glasses Following ISO Guidelines. <em>Geostandards and Geoanalytical Research</em>, <em>35</em>(4), 397–429. https://doi.org/10.1111/j.1751-908X.2011.00120.x</p> <p>Longerich, H. P., Jackson, S. E., & Günther, D. (1996). Inter-laboratory note. Laser ablation inductively coupled plasma mass spectrometric transient signal data acquisition and analyte concentration calculation. <em>Journal of Analytical Atomic Spectrometry</em>, <em>11</em>(9), 899–904. https://doi.org/10.1039/JA9961100899</p> <p>Paton, C., Hellstrom, J., Paul, B., Woodhead, J., & Hergt, J. (2011). Iolite: Freeware for the visualisation and processing of mass spectrometric data. <em>Journal of Analytical Atomic Spectrometry</em>, <em>26</em>(12), 2508–2518. https://doi.org/10.1039/C1JA10172B</p>
Comparative analysis of helminth infectivity: growth in intermediate hosts increases establishment rates in the next host
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