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opencc-by-4.0Jun 2023View details →

Figure 2 in Short-time salinity fluctuations are strong activators of oxidative stress in Mediterranean mussel (Mytilus galloprovincialis)

Figure 2. Mortality of mussels exposed to short-time salinity fluctuations. The diagram shows the percentage of dead mussels acclimated to high (24-40 ‰, HS) and low (6-14‰, LS) environmental salinity. The control group was held at 18 ‰. Bars indicate mean±SE (n=10).

Fig. 2 in Infestation and seasonal fluctuation of chigger mites on the Southeast Asian house rat (Rattus brunneusculus) in southern Yunnan Province, China

Fig. 2. Seasonal fluctuation of infestations of the Southeast Asian house rat (R. brunneusculus) with Walchia (W.) micropelta at Jingha, southern Yunnan of China (April 2016–March 2017).

Fig. 5 in Infestation and seasonal fluctuation of chigger mites on the Southeast Asian house rat (Rattus brunneusculus) in southern Yunnan Province, China

Fig. 5. Seasonal fluctuation of infestations of the Southeast Asian house rat (R. brunneusculus) with Walchia (W.) turmalis at Jingha, southern Yunnan of China (April 2016–March 2017).

Fig. 1 in Infestation and seasonal fluctuation of chigger mites on the Southeast Asian house rat (Rattus brunneusculus) in southern Yunnan Province, China

Fig. 1. Seasonal fluctuation of overall infestations of the Southeast Asian house rat (R. brunneusculus) with chiggers at Jingha village in southern Yunnan of China (April 2016–March 2017).

Fig. 4 in Infestation and seasonal fluctuation of chigger mites on the Southeast Asian house rat (Rattus brunneusculus) in southern Yunnan Province, China

Fig. 4. Seasonal fluctuation of infestations of the Southeast Asian house rat (R. brunneusculus) with Leptotrombidium (L.) deliense at Jingha, southern Yunnan of China (April 2016–March 2017).

Fig. 6 in Infestation and seasonal fluctuation of chigger mites on the Southeast Asian house rat (Rattus brunneusculus) in southern Yunnan Province, China

Fig. 6. Seasonal fluctuation of infestations of the Southeast Asian house rat (R. brunneusculus) with Leptotrombidium (L.) scutellare at Jingha, southern Yunnan of China (April 2016–March 2017).

Fig. 3 in Infestation and seasonal fluctuation of chigger mites on the Southeast Asian house rat (Rattus brunneusculus) in southern Yunnan Province, China

Fig. 3. Seasonal fluctuation of infestations of the Southeast Asian house rat (R. brunneusculus) with Ascoschoengastia indica at Jingha, southern Yunnan of China (April 2016–March 2017).

FIGURE 4 in Biases in the study of relationships between biodiversity dynamics and fluctuation of environmental conditions

FIGURE 4. Evolution of the sea surface temperature. Comparison of the raw data (Martin et al., 2014) with the curve obtained with the mean for each time interval and the curve obtained with the theoretical data calculated from the polynomial curve, smoothing spline, and two curves with three-point moving average and with weighted three-point moving average approaches.

FIGURE 3 in Biases in the study of relationships between biodiversity dynamics and fluctuation of environmental conditions

FIGURE 3. Comparison of the crocodylomorph genus diversity used in various studies. 1, comparison of the number of genera used for each marine crocodylomorph group; 2, comparison of the percent of each group used in the marine crocodylomorph diversity (with and without metriorhynchoids).

FIGURE 2 in Biases in the study of relationships between biodiversity dynamics and fluctuation of environmental conditions

FIGURE 2. Comparison of the crocodylomorph species diversity used in various studies. 1, comparison of the number of species used for each marine crocodylomorph group; 2, comparison of the per cent of each group and of the genus Steneosaurus in the marine crocodylomorph diversity used (with and without metriorhynchoids).

FIGURE 1 in Biases in the study of relationships between biodiversity dynamics and fluctuation of environmental conditions

FIGURE 1. Comparison between the diversity count of Jurassic-Paleogene marine crocodylomorphs (excluding metriorhynchoids) of Martin et al. (2014) (excluding Pelagosaurus typus), with the data obtained in the present work after several corrections. All the data is phylogenetically corrected. The data used in the present work includes four new species, corrections for the number of Machimosaurus species, and taxonomical corrections (see text).

FIGURE 1 in Water-level fluctuations lead to changes in the diet of an omnivorous fish in a floodplain

FIGURE 1 | Location of the Upper Paraná River floodplain (downstream of the Porto Primavera dam and upstream of the Itaipu reservoir) and the nine sampling stations on the Paraná, Baía, and Ivinhema rivers.

FIGURE 3 in Water-level fluctuations lead to changes in the diet of an omnivorous fish in a floodplain

FIGURE 3 | A. Relationship between the hydrometric level and the consumption of all allochthonous items; B. The consumption of terrestrial invertebrates; C. And the consumption of terrestrial plants for Trachelyopterus galeatus. The green graphs indicate a significant positive influence of the variable as a function of hydrometric level, while grayscale graphs indicate a non-significance.

FIGURE 2 in Water-level fluctuations lead to changes in the diet of an omnivorous fish in a floodplain

FIGURE 2 | Daily variation in the level of the Paraná River between 2000 and 2020 (provided by the Agência Nacional de Águas e Saneamento Básico - ANA). The horizontal line represents the 4.5 m level when the Paraná River overflows.

FIGURE 5 in Water-level fluctuations lead to changes in the diet of an omnivorous fish in a floodplain

FIGURE 5 | A. Relationship between the hydrometric level and the trophic niche breadth; B. Body condition; C. And the feeding activity of Trachelyopterus galeatus. The green graphs indicate a significant positive influence of the variable as a function of hydrometric level, while grayscale graphs indicate a non-significance.

FIGURE 4 in Water-level fluctuations lead to changes in the diet of an omnivorous fish in a floodplain

FIGURE 4 | A. Relationship between the hydrometric level and the consumption of all autochthonous items; B. The consumption of aquatic invertebrates; C. The consumption of detritus; D. And the consumption of fish for Trachelyopterus galeatus. Red graphs indicate a significant negative influence of the variable as a function of hydrometric level, while grayscale graphs indicate a non-significance.

openmit-licenseOct 2024View details →

Gaussian16 data for "Dynamic electronic structure fluctuations in the de novo peptide ACC-dimer revealed by first-principles theory and machine learning"

This is the Gaussian 16 input and corresponding output, which was used as input into the machine learning presented in the paper titled "Dynamic electronic structure fluctuations in the de novo peptide ACC-dimer revealed by first-principles theory and machine learning". This upload is required before submission of the paper. The 1001 and 100 snapshots from different extractions are preserved in separated directories. Each snapshot directory <code>*_snapshot</code> has the initial GROMACS snapshot <code>test_*.pdb</code> , the geometry after truncating the solvation shell in various formats, the Gaussian16 input, qsub input and the output directory <code>*.1</code> with a JobID number assigned by qsub. The output directory has the standard output from Gaussian in a <code>.log</code> file and <code>grep</code>ed output from the <code>.fchk</code>  file in <code>*.out</code> .

dryad40/100

Fitness cost from fluctuating ultraviolet radiation in Daphnia magna

Solar ultraviolet radiation (UVR) is an important environmental threat for organisms in aquatic systems, but its temporally variable nature makes the understanding of its effects ambiguous. The aim of our study was to assess potential fitness costs associated with fluctuating UVR in the aquatic zooplankter Daphnia magna. We investigated individual survival, reproduction and behaviour when exposed to different UVR treatments. Individuals exposed to fluctuating UVR, resembling natural variations in cloud cover, had the lowest fitness (measured as the number of offspring produced during their lifespan). In contrast, individuals exposed to the same, but constant UVR dose, had similar fitness as control individuals (not exposed to UVR), but they showed a significant reduction in daily movement. The re-occurring threat response to the fluctuating UVR treatment thus had strong fitness costs for D. magna, and we found no evidence for plastic behavioural responses when continually being exposed to UVR, despite the regular, predictable exposure schedule. In a broader context, our results imply that depending on how variable a stressor is in nature, populations may respond with alternative strategies, a framework that could promote rapid population differentiation and local adaptation.

opencc-zeroJul 2021View details →

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Seasonal rainfall in subtropical montane cloud forests drives demographic fluctuations in a Green-backed Tit population

Montane birds are vulnerable to climate change. However, the mechanisms by which weather drives demographic processes in montane birds have seldom been investigated. We conducted a long-term study (2009–2019) on the Green-backed Tit (Parus monticolus), an insectivorous passerine, in the montane cloud forest of subtropical Taiwan. We explored the effects of weather variability on the productivity and survival of adult Green-backed Tits. Nest survival was negatively associated with seasonal rainfall during the breeding season (April–July) and was lower in early clutches than in late clutches. Higher typhoon-induced precipitation during the postbreeding period (July–September) was related to reduced adult survival, but neither summer temperature nor winter weather conditions were found to be related to adult bird survival. We developed a stochastic simulation model for Green-backed Tit population dynamics based on empirical data. We compared the simulated time-series and observed population growth rates (λ) and found that 80% (8/10 yr) of the observed λ fell within the 5th and 95th percentiles of the simulated data over the 10-yr period. Moreover, the simulated average (± standard deviation) of the geometric mean of λ over 10 yr (1.05 ± 0.07) was close to that observed from 2009–2019 (0.99), which provided confidence that the model effectively simulated the population growth rate of the Green-backed Tit. We conducted a sensitivity analysis for λ, and found that juvenile and adult survival influenced by typhoon-induced rainfall were the greatest contributors to the variance in the growth rate of the Green-backed Tit population. With the onset of intensified seasonal precipitation associated with global warming, the population growth and density of Green-backed Tits will decline substantially. Our results suggest that under scenarios of high emissions of greenhouse gas, this local population of Green-backed Tits will not persist in the near future.

opencc-zeroAug 2021View details →