scholarly journals Leaf processing behaviour in Atta leafcutter ants: 90% of leaf cutting takes place inside the nest, and ants select pieces that require less cutting

2016 ◽  
Vol 3 (1) ◽  
pp. 150111 ◽  
Author(s):  
Ryan W. Garrett ◽  
Katherine A. Carlson ◽  
Matthew Scott Goggans ◽  
Michael H. Nesson ◽  
Christopher A. Shepard ◽  
...  
Keyword(s):  
Energy Cost ◽  
Metabolic Energy ◽  
Conservation Of Energy ◽  
Leaf Material ◽  
Leafcutter Ants ◽  
Leaf Processing ◽  
Laboratory Colony ◽  
Leaf Cutting ◽  
Atta Colombica ◽  
Foraging Energetics

Leafcutter ants cut trimmings from plants, carry them to their underground nests and cut them into smaller pieces before inoculating them with a fungus that serves as a primary food source for the colony. Cutting is energetically costly, so the amount of cutting is important in understanding foraging energetics. Estimates of the cutting density, metres of cutting per square metre of leaf, were made from samples of transported leaf cuttings and of fungal substrate from field colonies of Atta cephalotes and Atta colombica . To investigate cutting inside the nest, we made leaf-processing observations of our laboratory colony, A. cephalotes . We did not observe the commonly reported reduction of the leaf fragments into a pulp, which would greatly increase the energy cost of processing. Video clips of processing behaviours, including behaviours that have not previously been described, are linked. An estimated 2.9 (±0.3) km of cutting with mandibles was required to reduce a square metre of leaf to fungal substrate. Only about 12% (±1%) of this cutting took place outside of the nest. The cutting density and energy cost is lower for leaf material with higher ratios of perimeter to area, so we tested for, and found that the laboratory ants had a preference for leaves that were pre-cut into smaller pieces. Estimates suggest that the energy required to transport and cut up the leaf material is comparable to the metabolic energy available from the fungus grown on the leaves, and so conservation of energy is likely to be a particularly strong selective pressure for leafcutter ants.

Contraction duration affects metabolic energy cost and fatigue in skeletal muscle

1998 ◽  
Vol 274 (3) ◽  
pp. E397-E402 ◽  
Author(s):  
Michael C. Hogan ◽  
Erica Ingham ◽  
S. Sadi Kurdak
Keyword(s):  
Skeletal Muscle ◽  
Short Duration ◽  
Energy Cost ◽  
Lactate Concentration ◽  
Metabolic Energy ◽  
Muscle Lactate ◽  
Contracting Muscle ◽  
Contraction Duration ◽  
Long Duration ◽  
The Difference

It has been suggested that during a skeletal muscle contraction the metabolic energy cost at the onset may be greater than the energy cost related to holding steady-state force. The purpose of the present study was to investigate the effect of contraction duration on the metabolic energy cost and fatigue process in fully perfused contracting muscle in situ. Canine gastrocnemius muscle ( n = 6) was isolated, and two contractile periods (3 min of isometric, tetanic contractions with 45-min rest between) were conducted by each muscle in a balanced order design. The two contractile periods had stimulation patterns that resulted in a 1:3 contraction-to-rest ratio, with the difference in the two contractile periods being in the duration of each contraction: short duration 0.25-s stimulation/0.75-s rest vs. long duration 1-s stimulation/3-s rest. These stimulation patterns resulted in the same total time of stimulation, number of stimulation pulses, and total time in contraction for each 3-min period. Muscle O2 uptake, the fall in developed force (fatigue), the O2 cost of developed force, and the estimated total energy cost (ATP utilization) of developed force were significantly greater ( P < 0.05) with contractions of short duration. Lactate efflux from the working muscle and muscle lactate concentration were significantly greater with contractions of short duration, such that the calculated energy derived from glycolysis was three times greater in this condition. These results demonstrate that contraction duration can significantly affect both the aerobic and anaerobic metabolic energy cost and fatigue in contracting muscle. In addition, it is likely that the greater rate of fatigue with more rapid contractions was a result of elevated glycolytic production of lactic acid.

scholarly journals Metabolic energy cost of workers in agriculture, construction, manufacturing, tourism, and transportation industries

2019 ◽  
Vol 57 (3) ◽  
pp. 283-305 ◽  
Author(s):  
Konstantina P. POULIANITI ◽  
George HAVENITH ◽  
Andreas D. FLOURIS
Keyword(s):  
Energy Cost ◽  
Metabolic Energy

scholarly journals Elastic energy savings and active energy cost in a simple model of running

2021 ◽  
Vol 17 (11) ◽  
pp. e1009608
Author(s):  
Ryan T. Schroeder ◽  
Arthur D. Kuo
Keyword(s):  
Elastic Energy ◽  
Energy Cost ◽  
Energy Savings ◽  
Mechanical Energy ◽  
Metabolic Cost ◽  
The Body ◽  
Metabolic Energy ◽  
Energetic Cost ◽  
Mass Model ◽  
Human Running

The energetic economy of running benefits from tendon and other tissues that store and return elastic energy, thus saving muscles from costly mechanical work. The classic “Spring-mass” computational model successfully explains the forces, displacements and mechanical power of running, as the outcome of dynamical interactions between the body center of mass and a purely elastic spring for the leg. However, the Spring-mass model does not include active muscles and cannot explain the metabolic energy cost of running, whether on level ground or on a slope. Here we add explicit actuation and dissipation to the Spring-mass model, and show how they explain substantial active (and thus costly) work during human running, and much of the associated energetic cost. Dissipation is modeled as modest energy losses (5% of total mechanical energy for running at 3 m s-1) from hysteresis and foot-ground collisions, that must be restored by active work each step. Even with substantial elastic energy return (59% of positive work, comparable to empirical observations), the active work could account for most of the metabolic cost of human running (about 68%, assuming human-like muscle efficiency). We also introduce a previously unappreciated energetic cost for rapid production of force, that helps explain the relatively smooth ground reaction forces of running, and why muscles might also actively perform negative work. With both work and rapid force costs, the model reproduces the energetics of human running at a range of speeds on level ground and on slopes. Although elastic return is key to energy savings, there are still losses that require restorative muscle work, which can cost substantial energy during running.

Dispersal of Miconia argentea seeds by the leaf-cutting ant Atta colombica

1998 ◽  
Vol 14 (5) ◽  
pp. 705-710 ◽  
Author(s):  
J. W. Dalling ◽  
Rainer Wirth
Keyword(s):  
Seedling Recruitment ◽  
Atta Cephalotes ◽  
Brazilian Cerrado ◽  
Atta Laevigata ◽  
Cerrado Vegetation ◽  
Brosimum Alicastrum ◽  
Leaf Cutting ◽  
Single Night ◽  
Local Recruitment ◽  
Atta Colombica

While leaf-cutter ants are thought to collect mainly vegetative plant material, they have also been observed collecting seeds or fruit parts on the forest floor (Alvarez-Buylla & Martínez-Ramos 1990, Kaspari 1996). For example, leaf-cutter ants have been observed carrying considerable numbers of Brosimum alicastrum Sw. and Cecropia spp. seeds into their nests (Wirth 1996) and Leal & Oliveira (1998; pers. comm.) found them foraging on the fruits and seeds of 19 different species of Brazilian cerrado vegetation, including six Miconia species. Under some circumstances, seed removal and relocation by leaf cutter ants might even be sufficient to affect local recruitment patterns of trees. For example, in Costa Rica, Atta cephalotes can remove all fallen fig fruit from beneath a Ficus hondurensis crown in a single night (Roberts & Heithaus 1986), while in Venezuela, seedling recruitment of the savanna tree Tapirira velutinifolia was positively associated with the seed harvesting and seed cleaning activities of the ant Atta laevigata (Farji Brenner & Silva 1996).

scholarly journals Energetic consequences of using a prosthesis with adaptive ankle motion during slope walking in persons with a transtibial amputation

2013 ◽  
Vol 38 (1) ◽  
pp. 5-11 ◽  
Author(s):  
Benjamin J Darter ◽  
Jason M Wilken
Keyword(s):  
Mechanical Properties ◽  
Energy Expenditure ◽  
Energy Cost ◽  
Metabolic Energy ◽  
Prosthetic Design ◽  
Transtibial Amputation ◽  
Ankle Motion ◽  
Technological Advances ◽  
Walking Difficulty ◽  
Metabolic Energy Expenditure

Background:Technological advances in prosthetic design include the use of microprocessors that adapt device performance based on user motion. The Proprio ankle unit prepositions the foot to adjust for walking on slopes and increases foot clearance during swing to minimize gait deviations.Study design:Comparative analysis.Objectives:To investigate the effect of a prosthesis with adaptive ankle motion on physiological gait performance during slope walking.Methods:Six persons with a unilateral transtibial amputation completed treadmill walking tests at three slopes (−5°, 0°, and 5°). The participants were tested wearing a customary device, active Proprio (Pon), and an identical inactivated Proprio (Poff).Results:Metabolic energy expenditure, energy cost for walking, and rating of walking difficulty were not statistically different between the Pon and Poff for all tested slopes. However, for slope descent, energy expenditure and energy cost for walking improved significantly by an average of 10%–14% for both the Pon and Poff compared to the customary limb. Rating of walking difficulty also showed an improvement with slope descent for both the Pon and Poff compared to the customary device. An improvement with slope ascent was found for Pon compared to the customary limb only.Conclusions:Adaptive ankle motion provided no meaningful physiological benefit during slope walking. The Proprio was, however, less demanding than the customary device for slope descent. Differences in the mechanical properties of the prosthetic feet likely contributed to the changes.Clinical relevanceWhile the adaptive ankle motion did not affect metabolic energy expenditure or energy cost for walking, the results suggest close attention should be paid to the mechanical properties of the foot component. Assessment of gait on nonlevel surfaces is recommended to better understand the implications of different prosthetic design features.

Size-related foraging behaviour of the leaf-cutting ant Atta colombica

1991 ◽  
Vol 69 (6) ◽  
pp. 1530-1533 ◽  
Author(s):  
Dave Shutler ◽  
Adele Mullie
Keyword(s):  
Body Size ◽  
Leaf Litter ◽  
Tree Species ◽  
Foraging Behaviour ◽  
Foraging Theory ◽  
Costa Rican ◽  
Leaf Cutting ◽  
Foraging Trail ◽  
Atta Colombica ◽  
Load Mass

In a Costa Rican forest adjacent to cattle pasture, larger individuals of the leaf-cutting ant Atta colombica carried heavier loads and foraged farther from the colony, as predicted by foraging theory. Counter to foraging theory, individual ants did not increase their load mass if they foraged farther from the colony. However, the colony avoided this apparent inefficiency by sending larger ants to more distant trees. The colony harvested simultaneously from several individuals of the same tree species, even though distant trees were twice as far from the colony as nearby trees. The reasons for this behaviour require further investigation. In a wide foraging trail, larger ants travelled faster than their smaller counterparts. In addition, ant velocity was reduced when loads were experimentally supplemented, and increased when loads were experimentally reduced. Ants using narrow trails in the leaf litter may all be constrained to travel at the same speed, irrespective of load or body size, simply because they get in each other's way.

scholarly journals Metabolic constraints on synaptic learning and memory

2019 ◽  
Vol 122 (4) ◽  
pp. 1473-1490 ◽  
Author(s):  
Jan Karbowski
Keyword(s):  
Synaptic Plasticity ◽  
Metabolic Rate ◽  
Protein Phosphorylation ◽  
Learning And Memory ◽  
Dendritic Spines ◽  
Energy Cost ◽  
Memory Trace ◽  
Metabolic Energy ◽  
Cascade Models ◽  
New Learning

Dendritic spines, the carriers of long-term memory, occupy a small fraction of cortical space, and yet they are the major consumers of brain metabolic energy. What fraction of this energy goes for synaptic plasticity, correlated with learning and memory? It is estimated here based on neurophysiological and proteomic data for rat brain that, depending on the level of protein phosphorylation, the energy cost of synaptic plasticity constitutes a small fraction of the energy used for fast excitatory synaptic transmission, typically 4.0–11.2%. Next, this study analyzes a metabolic cost of new learning and its memory trace in relation to the cost of prior memories, using a class of cascade models of synaptic plasticity. It is argued that these models must contain bidirectional cyclic motifs, related to protein phosphorylation, to be compatible with basic thermodynamic principles. For most investigated parameters longer memories generally require proportionally more energy to store. The exceptions are the parameters controlling the speed of molecular transitions (e.g., ATP-driven phosphorylation rate), for which memory lifetime per invested energy can increase progressively for longer memories. Furthermore, in general, a memory trace decouples dynamically from a corresponding synaptic metabolic rate such that the energy expended on new learning and its memory trace constitutes in most cases only a small fraction of the baseline energy associated with prior memories. Taken together, these empirical and theoretical results suggest a metabolic efficiency of synaptically stored information. NEW & NOTEWORTHY Learning and memory involve a sequence of molecular events in dendritic spines called synaptic plasticity. These events are physical in nature and require energy, which has to be supplied by ATP molecules. However, our knowledge of the energetics of these processes is very poor. This study estimates the empirical energy cost of synaptic plasticity and considers theoretically a metabolic rate of learning and its memory trace in a class of cascade models of synaptic plasticity.

scholarly journals Evaluating physiological signal salience for estimating metabolic energy cost from wearable sensors

2019 ◽  
Vol 126 (3) ◽  
pp. 717-729 ◽  
Author(s):  
Kimberly A. Ingraham ◽  
Daniel P. Ferris ◽  
C. David Remy
Keyword(s):  
Heart Rate ◽  
Steady State ◽  
Indirect Calorimetry ◽  
Energy Cost ◽  
Electrodermal Activity ◽  
Wearable Sensors ◽  
Metabolic Energy ◽  
Physiological Signals ◽  
Physiological Signal ◽  
Signal Salience

Body-in-the-loop optimization algorithms have the capability to automatically tune the parameters of robotic prostheses and exoskeletons to minimize the metabolic energy expenditure of the user. However, current body-in-the-loop algorithms rely on indirect calorimetry to obtain measurements of energy cost, which are noisy, sparsely sampled, time-delayed, and require wearing a respiratory mask. To improve these algorithms, the goal of this work is to predict a user’s steady-state energy cost quickly and accurately using physiological signals obtained from portable, wearable sensors. In this paper, we quantified physiological signal salience to discover which signals, or groups of signals, have the best predictive capability when estimating metabolic energy cost. We collected data from 10 healthy individuals performing 6 activities (walking, incline walking, backward walking, running, cycling, and stair climbing) at various speeds or intensities. Subjects wore a suite of physiological sensors that measured breath frequency and volume, limb accelerations, lower limb EMG, heart rate, electrodermal activity, skin temperature, and oxygen saturation; indirect calorimetry was used to establish the ‘ground truth’ energy cost for each activity. Evaluating Pearson’s correlation coefficients and single and multiple linear regression models with cross validation (leave-one- subject-out and leave-one- task-out), we found that 1) filtering the accelerations and EMG signals improved their predictive power, 2) global signals (e.g., heart rate, electrodermal activity) were more sensitive to unknown subjects than tasks, while local signals (e.g., accelerations) were more sensitive to unknown tasks than subjects, and 3) good predictive performance was obtained combining a small number of signals (4–5) from multiple sensor modalities. NEW & NOTEWORTHY In this paper, we systematically compare a large set of physiological signals collected from portable sensors and determine which sensor signals contain the most salient information for predicting steady-state metabolic energy cost, robust to unknown subjects or tasks. This information, together with the comprehensive data set that is published in conjunction with this paper, will enable researchers and clinicians across many fields to develop novel algorithms to predict energy cost from wearable sensors.

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