Existing models of galaxy formation have not yet explained striking correlations between structure and star formation activity in galaxies, notably the sloped and moving boundaries that divide star-forming from quenched galaxies in key structural diagrams. This paper uses these and other relations to “reverse engineer” the quenching process for central galaxies. The basic idea is that star-forming galaxies with larger radii (at a given stellar mass) have lower black hole (BH) masses due to lower central densities. Galaxies cross into the green valley when the cumulative effective energy radiated by their BH equals ∼4× their halo gas-binding energy. Because larger-radii galaxies have smaller BHs, one finds that they must evolve to higher stellar masses in order to meet this halo energy criterion, which explains the sloping boundaries. A possible cause of radii differences among star-forming galaxies is halo concentration. The evolutionary tracks of star-forming galaxies are nearly parallel to the green-valley boundaries, and it is mainly the sideways motions of these boundaries with cosmic time that cause galaxies to quench. BH scaling laws for star-forming, quenched, and green-valley galaxies are different, and most BH mass growth takes place in the green valley. Implications include the radii of star-forming galaxies are an important second parameter in shaping their BHs; BHs are connected to their halos but in different ways for star-forming, quenched, and green-valley galaxies; and the same BH–halo quenching mechanism has been in place since z ∼ 3. We conclude with a discussion of BH–galaxy coevolution and the origin and interpretation of BH scaling laws.
This paper studies pseudo-bulges (P-bulges) and classical bulges (C-bulges) in Sloan Digital Sky Survey central galaxies using the new bulge indicator ∆Σ 1 , which measures relative central stellar-mass surface density within 1 kpc. We compare ∆Σ 1 to the established bulge-type indicator ∆ µ e from Gadotti (2009) and show that classifying by ∆Σ 1 agrees well with ∆ µ e . ∆Σ 1 requires no bulge-disk decomposition and can be measured on SDSS images out to z = 0.07. Bulge types using it are mapped onto twenty different structural and stellar-population properties for 12,000 SDSS central galaxies with masses 10.0 < log M * /M < 10.4. New trends emerge from this large sample. Structural parameters show fairly linear log-log relations vs. ∆Σ 1 and ∆ µ e with only moderate scatter, while stellar-population parameters show a highly non-linear "elbow" in which specific star-formation rate remains roughly flat with increasing central density and then falls rapidly at the elbow, where galaxies begin to quench. P-bulges occupy the low-density end of the horizontal arm of the elbow and are universally star-forming, while C-bulges occupy the elbow and the vertical branch and exhibit a wide range of star-formation rates at fixed density. The nonlinear relation between central density and star-formation rate has been seen before, but this mapping onto bulge class is new. The wide range of star-formation rates in C-bulges helps to explain why bulge classifications using different parameters have sometimes disagreed in the past. The elbow-shaped relation between density and stellar indices suggests that central structure and stellar-populations evolve at different rates as galaxies begin to quench.
Aim Our aims were to provide new pollen data for establishing a sub-continental surface pollen database (East Asian Pollen Database, EAPD) and to study relationships between vegetation and climate.Location The sample sites covered most regions of East Asia, including China, Mongolia, the Russian Far East, Vietnam, Cambodia and Thailand.Methods Data quality control procedures were applied, including taxonomic standardization, removal of duplicates, and adjustment of geographical coordinates. Vegetation types and climate parameters were assigned to each sample. Modern pollen distribution maps were drawn using circle scattergrams. The plots of pollen percentages versus climate variables allowed quantitative estimates of climate values. The modern analogue technique (MAT) was used to predict modern biomes and climate parameters.Results Pollen assemblages extracted from 2858 sites were used to model the geographical distribution of selected taxa and their relationships with climate. For most taxa, the reconstructed range fitted the observed geographical distribution rather well. Arboreal pollen (AP) and Pinus dominated the transition zone between forest and steppe. Use of the MAT revealed that the predicted and observed biomes matched in 71% of the cases. The warm temperate evergreen broadleaf forest had the best agreement between predictions and observations. Climate values reconstructed using MAT were highly correlated with observed values in January temperature. The correlation coefficient of the temperature variables ranged from 0.799 to 0.930 and was as high as 0.939 for precipitation.Main conclusions This paper documents a new modern pollen database for East Asia and makes the data readily available. The reconstructed biomes and climate variables are significantly correlated with the observed values, thus demonstrating the utility of the pollen database for future multiscale palaeoenvironmental studies.
The geographical distribution of dominant plant species in China was georeferenced and climatic variables were interpolated into all grids. Accordingly, the percentage distributions of principal pollen taxa based on 1860 surface pollen sites in China were selected and the related climate values were interpolated with the same method. The geographical and climatic comparison between the two datasets indicated that the climate threshold of most pollen taxa from surface pollen is coherent with plant distributions. The climatic envelopes of dominant plant are mostly accordant with those of pollen taxa at certain levels. However, some distinct offsets of the climate ranges exist between the two datasets for most pollen taxa identified at family level, such as Ericaceae, Asteraceae, Poaceae and Chenopodiaceae. The present study provides for the first time rich information on temperature and precipitation in relation to pollen and plant distribution based on the datasets on a continental scale useful for global ecological modeling and Quaternary palaeoclimate reconstruction.surface pollen, dominant plant species, geographical distribution, climate, global changesThe georeference of plant distributions and their related climate condition is now an important source for the research of global climate change and its influences on ecological systems. The climatic threshold related to the plant life has been considered as the crucial factor in separating biological affinity groups for modeling simulation [1][2][3] . Climate parameters in relation with the plant geographical distribution have been used for the division of plant functional types (PFTs) and biomization [4][5][6][7] . On the other hand, quantitative evaluation of the relationship between modern pollen and plant distribution is indispensable for understanding the fossil pollen spectra, and has become a robust method for Quaternary vegetation and climate reconstruction. Various quantitative methods for evaluating climate, plant and biome relationship based on pollen spectra have been attempted in many previous studies [8][9][10][11][12][13] . The traditional method for comparing pollen and plant representation (R value) is firstly described by Davis and used by studies. [14][15][16] . More recently, the biomization was applied to studying pollen and vegetation relationship [1] . To reveal the relation between pollen content and climatic parameter, a series of statistic methods were established in the past decades. Transfer function, principal component analysis,
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.