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294 results for “Metabolic rate”
Rates of benthic metabolism and nutrient cycling in the Parker and Rowley Rivers of the Plum Island Sound estuary, Massachusetts, PIE LTER.
Rates of benthic metabolism and nutrient cycling in the Parker and Rowley Rivers of the Plum Island Sound estuary. Measurements include those conducted at two sites in the Parker River in Spring (high river discharge) and Fall (low discharge) for long-term monitoring, also at other sites throughout the estuary over a variety of seasons and salinities.
MCR LTER: Coral Reef: Rates of benthic coral reef community metabolism from 2007 ongoing
Rates of community primary production and respiration can be calculated from the data presented here. For two sites on the north shore of Moorea, these measurements are sampled upstream and downstream: dissolved oxygen, water column velocity (speed and direction), in situ light (PAR) levels, incident solar radiation, temperature, wind speed, and transect length. Estimates are made yearly across approximately 160 m of the backreef community. This material uses data collected by the U.S. National Science Foundation's (NSF) Moorea Coral Reef Long Term Ecological Research (MCR LTER) site under Grant No. OCE 2224354 (and earlier awards). Additional financial support to the MCR LTER site was provided through a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2024).
Metabolism and decomposition rates from 5 Lake Superior Tributaries, 2018-2019
Ecosystem respiration (ER), and decomposition are fundamental processes driving carbon cycling in streams. Most studies examine rates of autotrophic respiration (AR) and heterotrophic respiration (HR) together as ecosystem respiration (ER), even though these two processes are carried out by different groups of organisms, and these processes, alongside decomposition, may respond differently to ongoing changes in environmental factors. We measured metabolism (gross primary production and ER) and decomposition at eight sites in four streams in the Upper Peninsula of Michigan across gradients of canopy cover and DOC concentrations. We estimated AR and HR using quantile regression and used predictive modeling to determine the environmental drivers that predicted variation in these processes across the study streams. This data archive includes (1) continuous dissolved oxygen and temperature data used to model metabolism, (2) modeled rates of gross primary production, ecosystem respiration, autotrophic respiration and heterotrophic respiration, (3) estimates of decomposition rates determined using cotton strip assays, and (4) environmental model used for predictive modeling
Nitrogen cycling and metabolic rates of aquacultured and wild Acropora coral from Guam in response to ammonium loading rates during 2020-2022
Rates from aquacultured corals and coral fragments collected in Guam in response to ammonium loading. These data are from two separate experiments, one using aquacultured corals and artificial seawater and light. The second was done with wild collected Acropora pistillata from two reef sites in Guam. The first site was West Hagåtña Bay (N13.479650, E144.741750; N13.479833, E144.741733) which had more nearby urban influences and was near the sewage outfall for the city (Redding et al. 2013). The second site was Luminao Reef (N13.4652417, E144.6477483; N13.465467, E144.648050) which was a more isolated reef on the seaward side of the breakwater for Guam’s major port. We measured respiration, gross primary production, 15N ammonium uptake to corals, related nitrogen cycling fluxes in the tanks (reminerization, net uptake, nitrification).
Data for: The interaction between metabolic rate, habitat choice, and resource use in a polymorphic freshwater species
<p>Raw respirometry data and respirometry code</p> <p>Data.xlsx is the data about each fish that was used for all analyses including Stable Isotope values, length, weight, sex, and habitat. This is the data that is used in the R code. </p> <p>Example code of the models used in our analyses</p> <p>TEF_metabolism.xlsx is data on the fish that were kept in the lab for almost a year. </p> <p> </p>
Fig. 6 in Effect of Nutrient, Light Intensity and Temperature on the Growth Rates and Metabolism of a Stress-Resistant Bacillariophyta Species Entomoneis sp. - in Izmir Bay (Aegean Sea) Abstract
Fig. 6: Maxiumum growth rate determination of all temperatures, light intensities and nutrient concentrations.
Fig. 5 in Effect of Nutrient, Light Intensity and Temperature on the Growth Rates and Metabolism of a Stress-Resistant Bacillariophyta Species Entomoneis sp. - in Izmir Bay (Aegean Sea) Abstract
Fig. 5: Entomoneis sp biomass (Chl a, µg /L) under different N/P ratios and light intensities (a) representing growth under T1°C (b) T2°C (c) and T3°C.
Fig. 2 in Effect of Nutrient, Light Intensity and Temperature on the Growth Rates and Metabolism of a Stress-Resistant Bacillariophyta Species Entomoneis sp. - in Izmir Bay (Aegean Sea) Abstract
Fig. 2: 3D response surface plot and contour line of Box– Behnken Design showing the mutual effect of temperature and light intensity on chlorophyll a concentration (µg/L) of Entomoneis sp. using an N/P ratio of 11.
Fig. 3 in Effect of Nutrient, Light Intensity and Temperature on the Growth Rates and Metabolism of a Stress-Resistant Bacillariophyta Species Entomoneis sp. - in Izmir Bay (Aegean Sea) Abstract
Fig. 3: 3D response surface plot and contour line of Box– Behnken Design showing the mutual effect of temperature and light intensity on growth rate (day-1) of Entomoneis sp. using an N/P ratio of 4.4.
Fig. 4 in Effect of Nutrient, Light Intensity and Temperature on the Growth Rates and Metabolism of a Stress-Resistant Bacillariophyta Species Entomoneis sp. - in Izmir Bay (Aegean Sea) Abstract
Fig. 4: 3D response surface plot and contour line of Box– Behnken Design showing the mutual effect of temperature and light intensity on growth rate (day-1) of Entomoneis sp. using an N/P ratio of 27.
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>
Larval nutrition impacts survival to adulthood, body size, and the allometric scaling of metabolic rate in adult honeybees
<p>Resting metabolic rate (RMR) is a fundamental physiological measure linked to numerous aspects of organismal function, including lifespan. Although dietary restriction in insects during larval growth/development affects adult RMR, the impact of larval diet <i>quality</i> on adult RMR has not been studied. Using <i>in vitro</i> rearing to control larval diet quality, we determined the effect of dietary protein and carbohydrate on honeybee survival-to-adulthood, time-to-eclosion, body mass/size and adult RMR. High carbohydrate larval diets increased survival-to-adulthood and time-to-eclosion compared to both low carbohydrate and high protein diets. Upon emergence, bees reared on the high protein diet were smaller and lighter than those reared on other diets, whilst those raised on the high carbohydrate diet varied more in body mass. Newly emerged adult bees' reared on the high carbohydrate diet showed a significantly steeper increase in allometric scaling of RMR compared to those reared on other diets. This suggests that diet quality influences survival-to-adulthood, time-to-eclosion, and the allometric scaling of RMR. Given that agricultural intensification and increasing urbanisation have led to a decrease in both forage availability and dietary diversity for bees, our results are critical to improving understanding of the impacts of poor developmental nutrition on bee growth/development and physiology.</p>
Data from: Additive effects of developmental acclimation and physiological syndromes on lifetime metabolic and water loss rates of a dry-skinned ectotherm
<p>Data sets from the paper: "Additive effects of developmental acclimation and physiological syndromes on lifetime metabolic and water loss rates of a dry-skinned ectotherm" by Dezetter et al. in Functional Ecology.</p> <p> </p> <p> </p>
Spatial variation in the evolutionary potential and constraints of basal metabolic rate and body mass in a wild bird
<p><span>Organismal energy budget is strongly related to resource consumption, performance, and fitness. Hence, understanding the evolution of key energetic traits, such as basal metabolic rate (BMR), in natural populations is central for understanding life-history evolution and ecological processes. Here we used quantitative genetic analyses to study evolutionary potential of BMR in two insular populations of the house sparrow <em>(Passer domesticus</em>). We obtained measurements of BMR and body mass (M<sub>b</sub>) from 911 house sparrows on the islands of Leka and Vega along the coast of Norway</span><span>.</span><span> These two populations were the source populations for translocations to create an additional third, admixed "common garden" population in 2012. With the use of a novel genetic group animal model concomitant with a genetically determined pedigree, we differentiate genetic and environmental sources of variation, thereby providing insight into the effects of spatial population structure on evolutionary potential. We found that the evolutionary potential of BMR was similar in the two source populations, whereas the Vega population had a somewhat higher evolutionary potential of M<sub>b</sub> than the Leka population. BMR was genetically correlated with M<sub>b</sub> in both populations, and the conditional evolutionary potential of BMR (independent of body mass) was 41% (Leka) and 53% (Vega) lower than unconditional estimates. Overall, our results show that there is potential for BMR to evolve independently of M<sub>b</sub>, but that selection on BMR and/or M<sub>b</sub> may have different evolutionary consequences in different populations of the same species.</span></p>
Linking the metabolic rate of individuals to species ecology and life history in key Arctic copepods
<p>This folder contains data and code for the manuscript "Linking the metabolic rate of individuals to species ecology <br> and life history in key Arctic copepods"</p> <p>The first script to run is the "rolling regression and adding covariates to MR data.R", this will read in all the<br> files with oxygen measurements, dry weight, and species and life stage information. The code will fit and predict <br> estimates for each individual, calculate O2 from calibration data, subtract background respiration, run the rolling regression,<br> and add the covariates DW, species and life stage to the metabolic rate data, and write the resulting data fame to a .txt file.</p> <p>The second script "lme4 Analysis and figures 5 6 7.R" will read in the data from the first script. <br> Here the AMR RMR and aerobic scope is estimated by Density Estimation via Model-Based Clustering. <br> The resulting data is fitted with a mixed model 'lmer'. <br> The remaining part of the script make the predictions that are presented in the text of the manuscript<br> and that are shown in figure 5, 6, and 7.</p> <p>Further information is annotated in the scripts</p>
Data from: Effects of temperature on metabolic rate during metamorphosis in the alfalfa leafcutting bee
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Larval nutrition impacts survival to adulthood, body size, and the allometric scaling of metabolic rate in adult honeybees
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Spatial variation in the evolutionary potential and constraints of basal metabolic rate and body mass in a wild bird
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Supplementary material: How should functional relationships be evaluated using phylogenetic comparative methods? A case study using metabolic rate and body temperature
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Data from: Metabolic rate shapes phenotypic covariance among physiological, behavioural, and life history traits in honeybees
<p>Metabolic rate is often cited as the fundamental rate that determines the rate of all biological processes by shaping energetic availability for the various behavioral and life history traits that contribute to performance. It has therefore been suggested that metabolic rate drives the widely observed covariance among these different levels of phenotypic traits. However, much of the work on this topic has relied on pairwise correlational analysis, thereby leaving an important gap in our understanding regarding the functional links that shape this phenotypic covariance, often referred to as pace-of-life. Using honeybees as an experimental model, we measured a large number of behavioural, life history and physiological traits in individual bees and used a structural equation model to characterize the phenotypic covariance structure among these traits. Following this with a path analysis, we demonstrate that variation in metabolic rate plays a fundamental proximate role in driving this phenotypic covariance structure in honeybees. We discuss the importance of these findings in the context of how interindividual variation in terms of slow-fast phenotypes may drive the phenotype of a group and the functional role metabolic rate might play in shaping division of labour and social evolution.</p>
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