Big Creek and Its Fishes

This book is a brief account of Big Creek: the stream, the life, the geology, the history. We hope that it will at least stimulate your appreciation of what Big Creek was and still is. Should you desire to learn more about the topics covered here, publications that served as our sources and those that cover the material in more detail are listed at the end of the book under the titles of the sections in the text.https://scholars.fhsu.edu/fort_hays_studies_series/1075/thumbnail.jp

Extreme events in gross primary production: a characterization across continents

Climate extremes can affect the functioning of terrestrial ecosystems, for instance via a reduction of the photosynthetic capacity or alterations of respiratory processes. Yet the dominant regional and seasonal effects of hydrometeorological extremes are still not well documented and in the focus of this paper. Specifically, we quantify and characterize the role of large spatiotemporal extreme events in gross primary production (GPP) as triggers of continental anomalies. We also investigate seasonal dynamics of extreme impacts on continental GPP anomalies. We find that the 50 largest positive extremes (i.e., statistically unusual increases in carbon uptake rates) and negative extremes (i.e., statistically unusual decreases in carbon uptake rates) on each continent can explain most of the continental variation in GPP, which is in line with previous results obtained at the global scale. We show that negative extremes are larger than positive ones and demonstrate that this asymmetry is particularly strong in South America and Europe. Our analysis indicates that the overall impacts and the spatial extents of GPP extremes are power-law distributed with exponents that vary little across continents. Moreover, we show that on all continents and for all data sets the spatial extents play a more important role for the overall impact of GPP extremes compared to the durations or maximal GPP. An analysis of possible causes across continents indicates that most negative extremes in GPP can be attributed clearly to water scarcity, whereas extreme temperatures play a secondary role. However, for Europe, South America and Oceania we also identify fire as an important driver. Our findings are consistent with remote sensing products. An independent validation against a literature survey on specific extreme events supports our results to a large extent

Remote sensing of ecosystem light use efficiency with MODIS-based PRI

Several studies sustained the possibility that a photochemical reflectance index (PRI) directly obtained from satellite data can be used as a proxy for ecosystem light use efficiency (LUE) in diagnostic models of gross primary productivity. This modelling approach would avoid the complications that are involved in using meteorological data as constraints for a fixed maximum LUE. However, no unifying model predicting LUE across climate zones and time based on MODIS PRI has been published to date. In this study, we evaluate the effectiveness with which MODIS-based PRI can be used to estimate ecosystem light use efficiency at study sites of different plant functional types and vegetation densities. Our objective is to examine if known limitations such as dependence on viewing and illumination geometry can be overcome and a single PRI-based model of LUE (i.e. based on the same reference band) can be applied under a wide range of conditions. Furthermore, we were interested in the effect of using different faPAR (fraction of absorbed photosynthetically active radiation) products on the in-situ LUE used as ground truth and thus on the whole evaluation exercise. We found that estimating LUE at site-level based on PRI reduces uncertainty compared to the approaches relying on a maximum LUE reduced by minimum temperature and vapour pressure deficit. Despite the advantages of using PRI to estimate LUE at site-level, we could not establish an universally applicable light use efficiency model based on MODIS PRI. Models that were optimised for a pool of data from several sites did not perform well

Armenia, Caucaso e Asia Centrale, Ricerche 2017

Questo nuovo volume della serie Eurasiatica. Quaderni di Studi su Balcani, Anatolia, Iran, Caucaso e Asia Centrale delle Edizioni Ca’ Foscari di Venezia raccoglie diversi articoli dedicati all’Armenia, al Caucaso e all’Asia Centrale. Gli articoli del volume vanno dall’archeologia alla letteratura, dal folclore alla storia, dalla storia del cristianesimo orientale all’arte, dalla narrazione di viaggio all’urbanistica. Un’intera sezione è dedicata agli studi osseti, di grande interesse non solo nell’ambito caucasico e in quello iranistico, ma anche per quel che riguarda la storia e la cultura russe

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The present paper features the publication of an unedited manuscript by the Soviet linguist E.D. Polivanov, submitted in November 1927 by its author not for publication but just as a contribu- tion to the discussion around the so-called Abkhaz Analytical Alphabet. is graphic system was devised by the academician Nikolay Yakovlevich Marr on the basis of the Latin alphabet for the representation of all Japhetic (Caucasian) languages. In the rst section of the introduction, the main characteristics of Marr\u2019s Analytical Alphabet are presented; the second section addresses the linguistic discussion that followed its introduction in Abkhazia as the o cial alphabet in 1926 and its replacement two years later by a Latin-based alphabet. e third section gives comment on some questions of Abkhaz phonetics and transcription; the fourth is devoted to textual and editorial is- sues. e edition of the Russian text is accompanied by an English translation, prepared by Grazia Giannetta (Macerata)

A quantitative study on the growth variability of tumour cell clones in vitro

Objectives: In this study, we quantify the growth variability of tumour cell clones from a human leukemia cell line. Materials and methods: We have used microplate spectrophotometry to measure the growth kinetics of hundreds of individual cell clones from the Molt3 cell line. The growth rate of each clonal population has been estimated by fitting experimental data with the logistic equation. Results: The growth rates were observed to vary among different clones. Up to six clones with a growth rate above or below the mean growth rate of the parent population were further cloned and the growth rates of their offsprings were measured. The distribution of the growth rates of the subclones did not significantly differ from that of the parent population thus suggesting that growth variability has an epigenetic origin. To explain the observed distributions of clonal growth rates we have developed a probabilistic model assuming that the fluctuations in the number of mitochondria through successive cell cycles are the leading cause of growth variability. For fitting purposes, we have estimated experimentally by flow cytometry the maximum average number of mitochondria in Molt3 cells. The model fits nicely the observed distributions of growth rates, however, cells in which the mitochondria were rendered non functional (rho-0 cells) showed only a 30% reduction in the clonal growth variability with respect to normal cells. Conclusions: A tumor cell population is a dynamic ensemble of clones with highly variable growth rate. At least part of this variability is due to fluctuations in the number of mitochondria.Comment: 31 pages, 5 figure

Classification of schizophrenia using feature-based morphometry

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Deciphering the components of regional net ecosystem fluxes following a bottom-up approach for the Iberian Peninsula

Quantification of ecosystem carbon pools is a fundamental requirement for estimating carbon fluxes and for addressing the dynamics and responses of the terrestrial carbon cycle to environmental drivers. The initial estimates of carbon pools in terrestrial carbon cycle models often rely on the ecosystem steady state assumption, leading to initial equilibrium conditions. In this study, we investigate how trends and inter-annual variability of net ecosystem fluxes are affected by initial non-steady state conditions. Further, we examine how modeled ecosystem responses induced exclusively by the model drivers can be separated from the initial conditions. For this, the Carnegie-Ames-Stanford Approach (CASA) model is optimized at set of European eddy covariance sites, which support the parameterization of regional simulations of ecosystem fluxes for the Iberian Peninsula, between 1982 and 2006. <br><br> The presented analysis stands on a credible model performance for a set of sites, that represent generally well the plant functional types and selected descriptors of climate and phenology present in the Iberian region – except for a limited Northwestern area. The effects of initial conditions on inter-annual variability and on trends, results mostly from the recovery of pools to equilibrium conditions; which control most of the inter-annual variability (IAV) and both the magnitude and sign of most of the trends. However, by removing the time series of pure model recovery from the time series of the overall fluxes, we are able to retrieve estimates of inter-annual variability and trends in net ecosystem fluxes that are quasi-independent from the initial conditions. This approach reduced the sensitivity of the net fluxes to initial conditions from 47% and 174% to −3% and 7%, for strong initial sink and source conditions, respectively. <br><br> With the aim to identify and improve understanding of the component fluxes that drive the observed trends, the net ecosystem production (NEP) trends are decomposed into net primary production (NPP) and heterotrophic respiration (<i>R</i><sub>H</sub>) trends. The majority (~97%) of the positive trends in NEP is observed in regions where both NPP and <i>R</i><sub>H</sub> fluxes show significant increases, although the magnitude of NPP trends is higher. Analogously, ~83% of the negative trends in NEP are also associated with negative trends in NPP. The spatial patterns of NPP trends are mainly explained by the trends in <i>f</i>APAR (<i>r</i>=0.79) and are only marginally explained by trends in temperature and water stress scalars (<i>r</i>=0.10 and <i>r</i>=0.25, respectively). Further, we observe the significant role of substrate availability (<i>r</i>=0.25) and temperature (<i>r</i>=0.23) in explaining the spatial patterns of trends in <i>R</i><sub>H</sub>. These results highlight the role of primary production in driving ecosystem fluxes. <br><br> Overall, our study illustrates an approach for removing the confounding effects of initial conditions and emphasizes the need to decompose the ecosystem fluxes into its components and drivers for more mechanistic interpretations of modeling results. We expect that our results are not only specific for the CASA model since it incorporates concepts of ecosystem functioning and modeling assumptions common to biogeochemical models. A direct implication of these results is the ability of this approach to detect climate and phenology induced trends regardless of the initial conditions