Spearman rank correlations between the frequency of maternal brood care and frequency of alloparental care by other female group members, in brackets sample sizes (number of broods).

*<p><i>p</i> = 0.022;</p>**<p><i>p</i> = 0.001;</p>***<p><i>p</i><0.001.</p

Sample sizes of brood care observations per mother.

<p>- = not applicable</p

Reproductive output of subordinate female group members depending on their investment in alloparental care (proportion of total female care), their body size (SL mm), corrected for differences between the experiments (1, 2, 3 or 4).

<p>GEE results with Wald χ², degrees of freedom, <i>p</i>-values and coefficients <i>B</i>±s.e., corrected for group identity effects, and the scaling parameter adjusted using the deviance method. Total number of eggs / 30 days rounded to the nearest integer value. The difference in body size [dominant female - subordinate female] was non-significant at <i>p</i> = 0.75 and removed from the model.</p

State-dependent metabolic partitioning and energy conservation: A theoretical framework for understanding the function of sleep

<div><p>Metabolic rate reduction has been considered the mechanism by which sleep conserves energy, similar to torpor or hibernation. This mechanism of energy savings is in conflict with the known upregulation (compared to wake) of diverse functions during sleep and neglects a potential role in energy conservation for partitioning of biological operations by behavioral state. Indeed, energy savings as derived from state-dependent resource allocations have yet to be examined. A mathematical model is presented based on relative rates of energy deployment for biological processes upregulated during either wake or sleep. Using this model, energy savings from sleep-wake cycling over constant wakefulness is computed by comparing stable limit cycles for systems of differential equations. A primary objective is to compare potential energy savings derived from state-dependent metabolic partitioning versus metabolic rate reduction. Additionally, energy conservation from sleep quota and the circadian system are also quantified in relation to a continuous wake condition. As a function of metabolic partitioning, our calculations show that coupling of metabolic operations with behavioral state may provide comparatively greater energy savings than the measured decrease in metabolic rate, suggesting that actual energy savings derived from sleep may be more than 4-fold greater than previous estimates. A combination of state-dependent metabolic partitioning and modest metabolic rate reduction during sleep may enhance energy savings beyond what is achievable through metabolic partitioning alone; however, the relative contribution from metabolic partitioning diminishes as metabolic rate is decreased during the rest phase. Sleep quota and the circadian system further augment energy savings in the model. Finally, we propose that state-dependent resource allocation underpins both sleep homeostasis and the optimization of daily energy conservation across species. This new paradigm identifies an evolutionary selective advantage for the upregulation of central and peripheral biological processes during sleep, presenting a unifying construct to understand sleep function.</p></div

Equations and parameters.

<p>(A) Symbols r_W and r_B denote rates of energy to waking effort and biological investment (BI), respectively. Comparing an organism to a machine, r_W refers to the rate of energy deployed for “running” the machine (energy acquisition, predation avoidance and reproduction), whereas r_B to “maintenance” and “upgrading” of the machine. r_W and r_B contribute to growth in biological requirements (BR) dependent on their rates (equation 1), but only r_B is converted into BI (equation 2). Symbols p_W and p_B denote the “price” of expending energy on waking effort or BI, respectively. x_B denotes conversion of r_B to BI containing circadian and homeostatic components (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185746#sec004" target="_blank">Methods</a>). Biological debt (BD) is the difference between BR and BI (equation 3). Equations (1), (2), and (3) imply equation (4). Although r_W and r_B are constant within state, they differ among states, defining metabolic allocation index (MAI) in equation (5). A subscripted “w” or “s” denotes rates during wake or sleep, respectively, e.g., r_Ww. (B) Solution to system of differential equations: At start of each day, BI is reset to 0, whereas BR is reset to the value of BD.</p

Method for calculating energy conservation.

<p>Three strategies are differentiated based on total sleep time (TST), metabolic rate (MR) reduction (ρ) during sleep, and state-dependent metabolic partitioning (MP) as defined by the metabolic allocation index (MAI). (A) Continuous wakefulness (TST = 0, ρ = 0 and MAI = 0) is the comparator state. (B) <i>Strategy MR Reduction (ρ)</i> cycles wake with sleep by introducing nonzero sleep quotas (TST>0) and ρ>0, while holding MAI = 0. (C) <i>Strategy MP+MR Reduction (MAI+ρ)</i> introduces MAI>0. In the two sleep conditions (B and C), r_W in wake is held constant with respect to <i>Strategy Wake</i> (A). Right panels show biological debt (BD) over three consecutive days at steady state. We impose the condition that daily average BD (orange) be held constant across conditions. To calculate energy savings, the value of r_B in wake is identified such that average BD matches continuous wakefulness (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185746#sec004" target="_blank">Methods</a>). Key: red (dashed) line is r_W, blue (dot-dashed) line is r_B, the dark purple (solid) line is metabolic rate (MR) such that MR = r_W+r_B, and the light purple (dotted) line is average MR. Standard parameters: p_W = 1.3, p_B1 = 0.7, m_C = 5, A = 2.5.</p

Subordinates

Subordinate

Nonapeptide neuronal phenotypes in eight species of lamprologine cichlid fishes from Isotocin neuronal phenotypes differ among social systems in cichlid fishes

Body size, cell number and average cell size for isotocin and vasotocin producing neurons in the parvocellular, magnocellular and gigantocellular regions of the preoptic area in 4 species of cooperatively breeding cichlids and 4 independently breeding species

Average body sizes for eight species of lamprologine cichlid fishes from Isotocin neuronal phenotypes differ among social systems in cichlid fishes

Mean (±S.E.M.) standard length for adult males from 8 species of lamprologine cichlid fishes collected from Lake Tanganyik