Both mean group size (MGS) and mean group density (MGD) are critical indices to characterize a population of cooperatively breeding birds. When a population reaches its carrying capacity, both long‐term MGS and long‐term MGD will remain relatively stable. However, there has been little study of how these two variables relate. The Masked laughingthrush Garrulax perspicillatus is a cooperatively breeding bird living in fragmented habitats. During 2010 and 2012‐2016, we used song playback to observe and confirm the group sizes and territory ranges of the birds and the data of bird presence to determine habitat suitability. By grouping the nearest territories according to their geographical coordinates, we divided the whole study area into 12 subareas and the whole population into 12 subpopulations. Then, we calculated both MGS and MGD for different time durations for each subpopulation. Finally, using MGD as independent variable and MGS as the dependent variable, we explored the correlations between MGS and MGD by fitting quadratic functions and modeling quadratic regression. Both MGS and MGD were averaged for different time durations and were cross‐related. Our results show that the MGS for more than 2 years significantly correlated with MGD for more than 3 years in a reverse parabolic shape, differing from that of short‐term effects. Our findings suggest that long‐term MGD is a better predictor of long‐term habitat quality and that long‐term MGS is determined by long‐term habitat quality in Masked Laughingthrushes. Based on above findings, we can infer that: (1) Long‐term habitat quality determines the long‐term MGS, but it sets no prerequisite for the status and source of group members; (2) Long‐term MGS in certain populations is adapted to the corresponding level of long‐term habitat quality, it facilitates us to predict the helper effects on current or future survival or reproduction in different situations. These findings and inferences are both helpful for us to understand the evolution of cooperative breeding. 相似文献
The standard model of the dynamic energy budget theory for metabolic organisation has variables and parameters that can be quantified using indirect methods only. We present new methods (and software) to extract food‐independent parameter values of the energy budget from food‐dependent quantities that are easy to observe, and so facilitate the practical application of the theory to enhance predictability and extrapolation. A natural sequence of 10 steps is discussed to obtain some compound parameters first, then the primary parameters, then the composition parameters and finally the thermodynamic parameters; this sequence matches a sequence of required data of increasing complexity which is discussed in detail. Many applications do not require knowledge of all parameters, and we discuss methods to extrapolate parameters from one species to another. The conversion of mass, volume and energy measures of biomass is discussed; these conversions are not trivial because biomass can change in chemical composition in particular ways thanks to different forms of homeostasis. We solve problems like “What would be the ultimate reproduction rate and the von Bertalanffy growth rate at a specific food level, given that we have measured these statistics at abundant food?” and “What would be the maximum incubation time, given the parameters of the von Bertalanffy growth curve?”. We propose a new non‐destructive method for quantifying the chemical potential and entropy of living reserve and structure, that can potentially change our ideas on the thermodynamic properties of life. We illustrate the methods using data on daphnids and molluscs. 相似文献
This paper considers the local, field-scale sustainability of a productive industrial maize agrosystem that has replaced a fertile grassland ecosystem.
Using the revised thermodynamic approach of Svirezhev (1998Svirezhev, Y. M.1998. “Thermodynamic orientors: How to use Thermodynamic concepts in ecology”. In Eco Targets, Goal Functions, and Orientors, 102–122. Berlin: Springer Verlag. [Crossref][Google Scholar], 2000Svirezhev, Y. M.2000. Thermodynamics and ecology. Ecological Modelling, 132: 11–22. [Crossref], [Web of Science ®][Google Scholar]) and Steinborn and Svirezhev (2000)Steinborn, W. and Svirezhev, Y. M.2000. Entropy as an indicator of sustainability in agro-ecosystems: North Germany case study. Ecol. Mode., 133: 247–257. [Crossref], [Web of Science ®][Google Scholar], it is shown that currently this agrosystem is unsustainable in the U.S., with or without tilling the soil. The calculated average erosion rates of soil necessary to dissipate the entropy produced by U.S. maize agriculture, 23–45 t ha?1 yr?1, are bounded from above by an experimental estimate of mean soil erosion by conventional agriculture worldwide, 47 t ha?1 yr?1, (Montgomery, 2007Montgomery, D. R.2007. Soil erosion and agricultural sustainability. PNAS, 104(33): 13268–13272. [Crossref], [PubMed], [Web of Science ®][Google Scholar]). Between 1982 and 1997, US agriculture caused an estimated 7–23 t ha?1 yr?1 of average erosion with the mean of 15 t ha?1 yr?1 (USDA-NRCS Database). The lower mean erosion rate of no till agriculture, 1.5 t ha?1 yr?1 (Montgomery, 2007Montgomery, D. R.2007. Soil erosion and agricultural sustainability. PNAS, 104(33): 13268–13272. [Crossref], [PubMed], [Web of Science ®][Google Scholar]), necessitates the elimination of weeds and pests with field chemicals—with the ensuing chemical and biological soil degradation, and chemical runoff—to dissipate the produced entropy. The increased use of field chemicals that replace tillers is equivalent to the killing or injuring of up to 300 kg ha?1 yr?1 of soil flora and fauna. Additional soil degradation, not calculated here, occurs by acidification, buildup of insoluble metal compounds, and buildup of toxic residues from field chemicals. The degree of unsustainability of an average U.S. maize field is high, requiring 6–13 times more energy to reverse soil erosion and degradation, etc., than the direct energy inputs to maize agriculture. This additional energy, if spent, would not increase maize yields. The calculated “critical yield” of “organic” maize agriculture that does not use field chemicals and fossil fuels is only 30 percent lower than the average maize yield of 8.7 tons per hectare (~140 bu/acre) assumed here. This critical yield would not likely be achieved and sustained by large monocultures, but might be achieved by more balanced organic polycultures (Baum et al., 2008Baum, A. W., Patzek, T. W., Bender, M., Renich, S. and Jackson, W.2008. The Visible, Sustainable Farm: A Comprehensive Energy Analysis of a Midwestern Farm1–34. Posted at petroleum.berkeley.edu/papers/Biofuels/SSF?Report3-051408.pdf[Google Scholar]). 相似文献
Computational prediction of protein-ligand binding modes provides useful information on the relationship between structure and activity needed for drug design. A statistical rescoring method that incorporates entropic effect is proposed to improve the accuracy of binding mode prediction. A probability function for two sampled conformations to belong to the same broad basin in the potential energy surface is introduced to estimate the contribution of the state represented by a sampled conformation to the configurational integral. The rescoring function is reduced to the colony energy introduced by Xiang et al. (Proc Natl Acad Sci USA 2002;99:7432-7437) when a particular functional form for the probability function is used. The scheme is applied to rescore protein-ligand complex conformations generated by AutoDock. It is demonstrated that this simple rescoring improves prediction accuracy substantially when tested on 163 protein-ligand complexes with known experimental structures. For example, the percentage of complexes for which predicted ligand conformations are within 1 A root-mean-square deviation from the native conformations is doubled from about 20% to more than 40%. Rescoring with 11 different scoring functions including AutoDock scoring functions were also tested using the ensemble of conformations generated by Wang et al. (J Med Chem 2003;46:2287-2303). Comparison with other methods that use clustering and estimation of conformational entropy is provided. Examination of the docked poses reveals that the rescoring corrects the predictions in which ligands are tightly fit into the binding pockets and have low energies, but have too little room for conformational freedom and thus have low entropy. 相似文献