Explore the vast range of titles available.

\"Epic in scope, yet filled with detail, this illustrated guide takes readers through the whole of our human past. Spanning the dawn of human civilization through the present, it provides a tour of every site of key archaeological importance. From the prehistoric cave paintings of Lascaux to Tutankhamun's tomb, from the buried city of Pompeii to China's Terracotta Army, all of the world's most iconic sites and discoveries are here. So too are the lesser-known yet equally important finds, such as the recent discoveries of our oldest known human ancestors and of the world's oldest-known temple, Gobekli Tepe in Turkey. A masterful combination of succinct analysis and driving narrative, this book also addresses the questions that inevitably arise as we gradually learn more about the history of our species. Written by an international team of archaeological experts and richly illustrated throughout, Archaeology: A Comprehensive Guide to Our Human Past offers an unparalleled insight into the origins of humankind\"-- Provided by publisher.

Anthropogenic nitrogen inputs cause major negative environmental impacts, including emissions of the important greenhouse gas N₂O. Despite their importance, shifts in terrestrial N loss pathways driven by global change are highly uncertain. Here we present a coupled soil-atmosphere isotope model (IsoTONE) to quantify terrestrial N losses and N₂O emission factors from 1850-2020. We find that N inputs from atmospheric deposition caused 51% of anthropogenic N₂O emissions from soils in 2020. The mean effective global emission factor for N₂O was 4.3 ± 0.3% in 2020 (weighted by N inputs), much higher than the surface area-weighted mean (1.1 ± 0.1%). Climate change and spatial redistribution of fertilisation N inputs have driven an increase in global emission factor over the past century, which accounts for 18% of the anthropogenic soil flux in 2020. Predicted increases in fertilisation in emerging economies will accelerate N₂O-driven climate warming in coming decades, unless targeted mitigation measures are introduced.

The terrestrial carbon (C) cycle has received increasing interest over the past few decades, however, there is still a lack of understanding of the fate of newly assimilated C allocated within plants and to the soil, stored within ecosystems and lost to the atmosphere. Stable carbon isotope studies can give novel insights into these issues. In this review we provide an overview of an emerging picture of plant-soil-atmosphere C fluxes, as based on C isotope studies, and identify processes determining related C isotope signatures. The first part of the review focuses on isotopic fractionation processes within plants during and after photosynthesis. The second major part elaborates on plant-internal and plant-rhizosphere C allocation patterns at different time scales (diel, seasonal, interannual), including the speed of C transfer and time lags in the coupling of assimilation and respiration, as well as the magnitude and controls of plant-soil C allocation and respiratory fluxes. Plant responses to changing environmental conditions, the functional relationship between the physiological and phenological status of plants and C transfer, and interactions between C, water and nutrient dynamics are discussed. The role of the C counterflow from the rhizosphere to the aboveground parts of the plants, e.g. via CO2 dissolved in the xylem water or as xylem-transported sugars, is highlighted. The third part is centered around belowground C turnover, focusing especially on above- and belowground litter inputs, soil organic matter formation and turnover, production and loss of dissolved organic C, soil respiration and CO2 fixation by soil microbes. Furthermore, plant controls on microbial communities and activity via exudates and litter production as well as microbial community effects on C mineralization are reviewed. A further part of the paper is dedicated to physical interactions between soil CO2 and the soil matrix, such as CO2 diffusion and dissolution processes within the soil profile. Finally, we highlight state-of-the-art stable isotope methodologies and their latest developments. From the presented evidence we conclude that there exists a tight coupling of physical, chemical and biological processes involved in C cycling and C isotope fluxes in the plant-soil-atmosphere system. Generally, research using information from C isotopes allows an integrated view of the different processes involved. However, complex interactions among the range of processes complicate or currently impede the interpretation of isotopic signals in CO2 or organic compounds at the plant and ecosystem level. This review tries to identify present knowledge gaps in correctly interpreting carbon stable isotope signals in the plant-soil-atmosphere system and how future research approaches could contribute to closing these gaps.

Future climate scenarios suggest an increased frequency of summer drought periods in the European Alpine Region. Drought can affect soil nitrogen (N) cycling, by altering N transformation rates, as well as the abundances of ammonia-oxidizing bacteria and archaea. However, the extent to which drought affects N cycling under in situ conditions is still controversial. The goal of this study was to analyse effects of drought on soil N turnover and ammonia-oxidizer abundances in soil without drought history. To this end we conducted rain-exclusion experiments at two differently managed mountain grassland sites, an annually mown and occasionally fertilized meadow and an abandoned grassland. Soils were sampled before, during and after drought and were analysed for potential gross rates of N mineralization, microbial uptake of inorganic N, nitrification, and the abundances of bacterial and archaeal ammonia-oxidizers based on gene copy numbers of the amoA gene (AOB and AOA, respectively). Drought induced different responses at the two studied sites. At the managed meadow drought increased NH4+ immobilization rates and NH4+ concentrations in the soil water solution, but led to a reduction of AOA abundance compared to controls. At the abandoned site gross nitrification and NO3− immobilization rates decreased during drought, while AOB and AOA abundances remained stable. Rewetting had only minor, short-term effects on the parameters that had been affected by drought. Seven weeks after the end of drought no differences to control plots could be detected. Thus, our findings demonstrated that in mountain grasslands drought had distinct transient effects on soil nitrogen cycling and ammonia-oxidizers, which could have been related to a niche differentiation of AOB and AOA with increasing NH4+ levels. However, the effect strength of drought was modulated by grassland management.

Soil respiration (SR) constitutes the largest flux of CO2 from terrestrial ecosystems to the atmosphere. However, there still exist considerable uncertainties as to its actual magnitude, as well as its spatial and interannual variability. Based on a reanalysis and synthesis of 80 site-years for 57 forests, plantations, savannas, shrublands and grasslands from boreal to tropical climates we present evidence that total annual SR is closely related to SR at mean annual soil temperature (SRMAT), irrespective of the type of ecosystem and biome. This is theoretically expected for non water-limited ecosystems within most of the globally occurring range of annual temperature variability and sensitivity (Q10). We further show that for seasonally dry sites where annual precipitation (P) is lower than potential evapotranspiration (PET), annual SR can be predicted from wet season SRMAT corrected for a factor related to P/PET. Our finding indicates that it can be sufficient to measure SRMAT for obtaining a well constrained estimate of its annual total. This should substantially increase our capacity for assessing the spatial distribution of soil CO2 emissions across ecosystems, landscapes and regions, and thereby contribute to improving the spatial resolution of a major component of the global carbon cycle.

Aims: Abiotic properties of soil are known to be major drivers of the microbial community within it. Our understanding of how soil microbial properties are related to the functional structure and diversity of plant communities, however, is limited and largely restricted to above-ground plant traits, with the role of below-ground traits being poorly understood. This study investigated the relative contributions of soil abiotic properties and plant traits, both above-ground and below-ground, to variations in microbial processes involved in grassland nitrogen turnover. Methods In mountain grasslands distributed across three European sites, a correlative approach was used to examine the role of a large range of plant functional traits and soil abiotic factors on microbial variables, including gene abundance of nitrifiers and denitrifiers and their potential activities. Key Results Direct effects of soil abiotic parameters were found to have the most significant influence on the microbial groups investigated. Indirect pathways via plant functional traits contributed substantially to explaining the relative abundance of fungi and bacteria and gene abundances of the investigated microbial communities, while they explained little of the variance in microbial activities. Gene abundances of nitrifiers and denitrifiers were most strongly related to below-ground plant traits, suggesting that they were the most relevant traits for explaining variation in community structure and abundances of soil microbes involved in nitrification and denitrification. Conclusions The results suggest that consideration of plant traits, and especially below-ground traits, increases our ability to describe variation in the abundances and the functional characteristics of microbial communities in grassland soils.

Changes in land use and management have been strongly affecting mountain grassland, however, their effects on the net ecosystem exchange of CO2 (NEE) and its components have not yet been well documented. We analysed chamber-based estimates of NEE, gross primary productivity (GPP), ecosystem respiration (R) and light use efficiency (LUE) of six mountain grasslands differing in land use and management, and thus site fertility, for the growing seasons of 2002 to 2008. The main findings of the study are that: (1) land use and management affected seasonal NEE, GPP and R, which all decreased from managed to unmanaged grasslands; (2) these changes were explained by differences in leaf area index (LAI), biomass and leaf-area-independent changes that were likely related to photosynthetic physiology; (3) diurnal variations of NEE were primarily controlled by photosynthetically active photon flux density and soil and air temperature; seasonal variations were associated with changes in LAI; (4) parameters of light response curves were generally closely related to each other, and the ratio of R at a reference temperature/ maximum GPP was nearly constant across the sites; (5) similarly to our study, maximum GPP and R for other grasslands on the globe decreased with decreasing land use intensity, while their ratio remained remarkably constant. We conclude that decreasing intensity of management and, in particular, abandonment of mountain grassland lead to a decrease in NEE and its component processes. While GPP and R are generally closely coupled during most of the growing season, GPP is more immediately and strongly affected by land management (mowing, grazing) and season. This suggests that management and growing season length, as well as their possible future changes, may play an important role for the annual C balance of mountain grassland.

Networks that merge and harmonise eddy-covariance measurements from many different parts of the world have become an important observational resource for ecosystem science. Empirical algorithms have been developed which combine direct observations of the net ecosystem exchange of carbon dioxide with simple empirical models to disentangle photosynthetic (GPP) and respiratory fluxes (Reco). The increasing use of these estimates for the analysis of climate sensitivities, model evaluation and calibration demands a thorough understanding of assumptions in the analysis process and the resulting uncertainties of the partitioned fluxes. The semi-empirical models used in flux partitioning algorithms require temperature observations as input, but as respiration takes place in many parts of an ecosystem, it is unclear which temperature input – air, surface, bole, or soil at a specific depth – should be used. This choice is a source of uncertainty and potential biases. In this study, we analysed the correlation between different temperature observations and nighttime NEE (which equals nighttime respiration) across FLUXNET sites to understand the potential of the different temperature observations as input for the flux partitioning model. We found that the differences in the correlation between different temperature data streams and nighttime NEE are small and depend on the selection of sites. We investigated the effects of the choice of the temperature data by running two flux partitioning algorithms with air and soil temperature. We found the time lag (phase shift) between air and soil temperatures explains the differences in the GPP and Reco estimates when using either air or soil temperatures for flux partitioning. The impact of the source of temperature data on other derived ecosystem parameters was estimated, and the strongest impact was found for the temperature sensitivity. Overall, this study suggests that the choice between soil or air temperature must be made on site-by-site basis by analysing the correlation between temperature and nighttime NEE. We recommend using an ensemble of estimates based on different temperature observations to account for the uncertainty due to the choice of temperature and to assure the robustness of the temporal patterns of the derived variables.

Land-use change (LUC) and management are among the major driving forces of soil carbon (C) storage. Abandonment of mountain grassland promotes accumulation of aboveground biomass and litter, but related responses of soil organic matter (SOM) dynamics are uncertain. To determine SOM-C turnover we sampled 0–10 cm of soils in the European Alps along two land-use gradients (hay meadows, grazed pastures and abandoned grasslands) of different management intensity. A first land-use gradient was located at Stubai Valley (MAT: 3 °C, MAP: 1097 mm) in Austria and a second at Matsch Valley (MAT: 6.6 °C, MAP: 527 mm) in Italy. We estimated C input and decomposition rates of water-floatable and free particulate organic matter (wPOM, fPOM <1.6 g cm−3) and aggregate-occluded particulate and mineral-associated organic matter (oPOM <1.6 g cm−3, mOM >1.6 g cm−3) using bomb radiocarbon. In mountain grasslands average C turnover increased from roots (3 yr) < wPOM (5 yr) < fPOM (80 yr) < oPOM (108 yr) < mOM (192 yr). Among SOM fractions the turnover of fPOM-C varied most in relation to management. Along both land-use gradients C input pathways shifted from root-derived towards litter-derived C. The C input rates of both wPOM-C and fPOM-C were affected by land management at both sites. In contrast, oPOM-C and mOM-C dynamics remained relatively stable in response to grassland abandonment. Carbon accumulation rates of free POM decreased strongly with time since LUC (10, 25 and 36 yr). For wPOM-C, for example, it decreased from 7.4 > 2.2> 0.8 g C m−2 yr−1. At both sites, most C was sequestered in the first years after LUC and free POM reached new steady state within 20–40 yr. We conclude that w-and fPOM-C vs. oPOM-C dynamics respond differently to grassland management change and thus POM does not represent a homogeneous SOM fraction. Sequestered C is stored in the labile POM and not stabilized in the long-term. Thus, it is unlikely that abandonment, the dominant form of LUC in the European Alps, provides a substantial net soil C sink.

Based on measurements of δ18O and δ13C in organic matter of C₃-plants, we have developed a conceptual model that gives insight into the relationship between stomatal conductance ($g_{\\text{l}}$) and photosynthetic capacity ($A_{\\text{max}}$) resulting from differing environmental constraints and plant-internal factors. This is a semi-quantitative approach to describing the long-term effects of environmental factors on CO₂ and H₂O gas exchange, whereby we estimate the intercellular CO₂ concentration (ci) from δ13C and the air humidity from δ18O. Assuming that air humidity is an important factor influencing$g_{\\text{l}}$, the model allows us to distinguish whether differences in ciare caused by a response of$g_{\\text{l}}$or of$A_{\\text{max}}$. As an application of the model we evaluated the isotope data from three species in plots differing in intensity of land use (hay meadows and abandoned areas) at three sites along a south north transect in the Eastern Alps. We found three different δ18O-δ13C response patterns in native and planted grassland species (cultivated in the greenhouse). After preliminary confirmation by gas-exchange measurements we conclude that the proposed model is a promising tool for deriving carbon water relations in different functional groups from δ18O and δ13C isotope data.