Environmental Earth Sciences

ABSTRACT Radiocarbon ( 14 C) ages cannot provide absolutely dated chronologies for archaeological or paleoenvironmental studies directly but must be converted to calendar age equivalents using a calibration curve compensating for fluctuations in atmospheric 14 C concentration. Although calibration curves are constructed from independently dated archives, they invariably require revision as new data become available and our understanding of the Earth system improves. In this volume the international 14 C calibration curves for both the Northern and Southern Hemispheres, as well as for the ocean surface layer, have been updated to include a wealth of new data and extended to 55,000 cal BP. Based on tree rings, IntCal20 now extends as a fully atmospheric record to ca. 13,900 cal BP. For the older part of the timescale, IntCal20 comprises statistically integrated evidence from floating tree-ring chronologies, lacustrine and marine sediments, speleothems, and corals. We utilized improved evaluation of the timescales and location variable 14 C offsets from the atmosphere (reservoir age, dead carbon fraction) for each dataset. New statistical methods have refined the structure of the calibration curves while maintaining a robust treatment of uncertainties in the 14 C ages, the calendar ages and other corrections. The inclusion of modeled marine reservoir ages derived from a three-dimensional ocean circulation model has allowed us to apply more appropriate reservoir corrections to the marine 14 C data rather than the previous use of constant regional offsets from the atmosphere. Here we provide an overview of the new and revised datasets and the associated methods used for the construction of the IntCal20 curve and explore potential regional offsets for tree-ring data. We discuss the main differences with respect to the previous calibration curve, IntCal13, and some of the implications for archaeology and geosciences ranging from the recent past to the time of the extinction of the Neanderthals.

Large carnivores face serious threats and are experiencing massive declines in their populations and geographic ranges around the world. We highlight how these threats have affected the conservation status and ecological functioning of the 31 largest mammalian carnivores on Earth. Consistent with theory, empirical studies increasingly show that large carnivores have substantial effects on the structure and function of diverse ecosystems. Significant cascading trophic interactions, mediated by their prey or sympatric mesopredators, arise when some of these carnivores are extirpated from or repatriated to ecosystems. Unexpected effects of trophic cascades on various taxa and processes include changes to bird, mammal, invertebrate, and herpetofauna abundance or richness; subsidies to scavengers; altered disease dynamics; carbon sequestration; modified stream morphology; and crop damage. Promoting tolerance and coexistence with large carnivores is a crucial societal challenge that will ultimately determine the fate of Earth's largest carnivores and all that depends upon them, including humans.

An annotated reference sequence representing the hexaploid bread wheat genome in 21 pseudomolecules has been analyzed to identify the distribution and genomic context of coding and noncoding elements across the A, B, and D subgenomes. With an estimated coverage of 94% of the genome and containing 107,891 high-confidence gene models, this assembly enabled the discovery of tissue- and developmental stage-related coexpression networks by providing a transcriptome atlas representing major stages of wheat development. Dynamics of complex gene families involved in environmental adaptation and end-use quality were revealed at subgenome resolution and contextualized to known agronomic single-gene or quantitative trait loci. This community resource establishes the foundation for accelerating wheat research and application through improved understanding of wheat biology and genomics-assisted breeding.

Abstract Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy‐in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log‐normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait‐based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Summary Intra‐class correlations ( ICC ) and repeatabilities ( R ) are fundamental statistics for quantifying the reproducibility of measurements and for understanding the structure of biological variation. Linear mixed effects models offer a versatile framework for estimating ICC and R . However, while point estimation and significance testing by likelihood ratio tests is straightforward, the quantification of uncertainty is not as easily achieved. A further complication arises when the analysis is conducted on data with non‐Gaussian distributions because the separation of the mean and the variance is less clear‐cut for non‐Gaussian than for Gaussian models. Nonetheless, there are solutions to approximate repeatability for the most widely used families of generalized linear mixed models (GLMMs). Here, we introduce the R package rptR for the estimation of ICC and R for Gaussian, binomial and Poisson‐distributed data. Uncertainty in estimators is quantified by parametric bootstrapping and significance testing is implemented by likelihood ratio tests and through permutation of residuals. The package allows control for fixed effects and thus the estimation of adjusted repeatabilities (that remove fixed effect variance from the estimate) and enhanced agreement repeatabilities (that add fixed effect variance to the denominator). Furthermore, repeatability can be estimated from random‐slope models. The package features convenient summary and plotting functions. Besides repeatabilities, the package also allows the quantification of coefficients of determination R 2 as well as of raw variance components. We present an example analysis to demonstrate the core features and discuss some of the limitations of rptR.

Experiments suggest that biodiversity enhances the ability of ecosystems to maintain multiple functions, such as carbon storage, productivity, and the buildup of nutrient pools (multifunctionality). However, the relationship between biodiversity and multifunctionality has never been assessed globally in natural ecosystems. We report here on a global empirical study relating plant species richness and abiotic factors to multifunctionality in drylands, which collectively cover 41% of Earth's land surface and support over 38% of the human population. Multifunctionality was positively and significantly related to species richness. The best-fitting models accounted for over 55% of the variation in multifunctionality and always included species richness as a predictor variable. Our results suggest that the preservation of plant biodiversity is crucial to buffer negative effects of climate change and desertification in drylands.

Stabilizing the carbon dioxide-induced component of climate change is an energy problem. Establishment of a course toward such stabilization will require the development within the coming decades of primary energy sources that do not emit carbon dioxide to the atmosphere, in addition to efforts to reduce end-use energy demand. Mid-century primary power requirements that are free of carbon dioxide emissions could be several times what we now derive from fossil fuels (approximately 10(13) watts), even with improvements in energy efficiency. Here we survey possible future energy sources, evaluated for their capability to supply massive amounts of carbon emission-free energy and for their potential for large-scale commercialization. Possible candidates for primary energy sources include terrestrial solar and wind energy, solar power satellites, biomass, nuclear fission, nuclear fusion, fission-fusion hybrids, and fossil fuels from which carbon has been sequestered. Non-primary power technologies that could contribute to climate stabilization include efficiency improvements, hydrogen production, storage and transport, superconducting global electric grids, and geoengineering. All of these approaches currently have severe deficiencies that limit their ability to stabilize global climate. We conclude that a broad range of intensive research and development is urgently needed to produce technological options that can allow both climate stabilization and economic development.

Here we present a new terrestrial biosphere model (the Integrated Biosphere Simulator ‐ IBIS) which demonstrates how land surface biophysics, terrestrial carbon fluxes, and global vegetation dynamics can be represented in a single, physically consistent modeling framework. In order to integrate a wide range of biophysical, physiological, and ecological processes, the model is designed around a hierarchical, modular structure and uses a common state description throughout. First, a coupled simulation of the surface water, energy, and carbon fluxes is performed on hourly timesteps and is integrated over the year to estimate the annual water and carbon balance. Next, the annual carbon balance is used to predict changes in the leaf area index and biomass for each of nine plant functional types, which compete for light and water using different ecological strategies. The resulting patterns of annual evapotranspiration, runoff, and net primary productivity are in good agreement with observations. In addition, the model simulates patterns of vegetation dynamics that qualitatively agree with features of the natural process of secondary succession. Comparison of the model's inferred near‐equilibrium vegetation categories with a potential natural vegetation map shows a fair degree of agreement. This integrated modeling framework provides a means of simulating both rapid biophysical processes and long‐term ecosystem dynamics that can be directly incorporated within atmospheric models.

Abstract Linear mixed‐effects models are powerful tools for analysing complex datasets with repeated or clustered observations, a common data structure in ecology and evolution. Mixed‐effects models involve complex fitting procedures and make several assumptions, in particular about the distribution of residual and random effects. Violations of these assumptions are common in real datasets, yet it is not always clear how much these violations matter to accurate and unbiased estimation. Here we address the consequences of violations in distributional assumptions and the impact of missing random effect components on model estimates. In particular, we evaluate the effects of skewed, bimodal and heteroscedastic random effect and residual variances, of missing random effect terms and of correlated fixed effect predictors. We focus on bias and prediction error on estimates of fixed and random effects. Model estimates were usually robust to violations of assumptions, with the exception of slight upward biases in estimates of random effect variance if the generating distribution was bimodal but was modelled by Gaussian error distributions. Further, estimates for (random effect) components that violated distributional assumptions became less precise but remained unbiased. However, this particular problem did not affect other parameters of the model. The same pattern was found for strongly correlated fixed effects, which led to imprecise, but unbiased estimates, with uncertainty estimates reflecting imprecision. Unmodelled sources of random effect variance had predictable effects on variance component estimates. The pattern is best viewed as a cascade of hierarchical grouping factors. Variances trickle down the hierarchy such that missing higher‐level random effect variances pool at lower levels and missing lower‐level and crossed random effect variances manifest as residual variance. Overall, our results show remarkable robustness of mixed‐effects models that should allow researchers to use mixed‐effects models even if the distributional assumptions are objectively violated. However, this does not free researchers from careful evaluation of the model. Estimates that are based on data that show clear violations of key assumptions should be treated with caution because individual datasets might give highly imprecise estimates, even if they will be unbiased on average across datasets.

Soil bacteria and fungi play key roles in the functioning of terrestrial ecosystems, yet our understanding of their responses to climate change lags significantly behind that of other organisms. This gap in our understanding is particularly true for drylands, which occupy ∼41% of Earth´s surface, because no global, systematic assessments of the joint diversity of soil bacteria and fungi have been conducted in these environments to date. Here we present results from a study conducted across 80 dryland sites from all continents, except Antarctica, to assess how changes in aridity affect the composition, abundance, and diversity of soil bacteria and fungi. The diversity and abundance of soil bacteria and fungi was reduced as aridity increased. These results were largely driven by the negative impacts of aridity on soil organic carbon content, which positively affected the abundance and diversity of both bacteria and fungi. Aridity promoted shifts in the composition of soil bacteria, with increases in the relative abundance of Chloroflexi and α-Proteobacteria and decreases in Acidobacteria and Verrucomicrobia. Contrary to what has been reported by previous continental and global-scale studies, soil pH was not a major driver of bacterial diversity, and fungal communities were dominated by Ascomycota. Our results fill a critical gap in our understanding of soil microbial communities in terrestrial ecosystems. They suggest that changes in aridity, such as those predicted by climate-change models, may reduce microbial abundance and diversity, a response that will likely impact the provision of key ecosystem services by global drylands.

Modest dietary restriction (DR) prolongs life in a wide range of organisms, spanning single-celled yeast to mammals. Here, we report the use of recent techniques in nutrition research to quantify the detailed relationship between diet, nutrient intake, lifespan, and reproduction in Drosophila melanogaster. Caloric restriction (CR) was not responsible for extending lifespan in our experimental flies. Response surfaces for lifespan and fecundity were maximized at different protein-carbohydrate intakes, with longevity highest at a protein-to-carbohydrate ratio of 1:16 and egg-laying rate maximized at 1:2. Lifetime egg production, the measure closest to fitness, was maximized at an intermediate P:C ratio of 1:4. Flies offered a choice of complementary foods regulated intake to maximize lifetime egg production. The results indicate a role for both direct costs of reproduction and other deleterious consequences of ingesting high levels of protein. We unite a body of apparently conflicting work within a common framework and provide a platform for studying aging in all organisms.

This article identifies and discusses the scientific challenges of hydrogen storage in porous media for safe and efficient large-scale energy storage to enable a global hydrogen economy.

Abstract The temperature dependence of C 3 photosynthesis is known to vary with growth environment and with species. In an attempt to quantify this variability, a commonly used biochemically based photosynthesis model was parameterized from 19 gas exchange studies on tree and crop species. The parameter values obtained described the shape and amplitude of the temperature responses of the maximum rate of Rubisco activity ( V cmax ) and the potential rate of electron transport ( J max ). Original data sets were used for this review, as it is shown that derived values of V cmax and its temperature response depend strongly on assumptions made in derivation. Values of J max and V cmax at 25 °C varied considerably among species but were strongly correlated, with an average J max : V cmax ratio of 1·67. Two species grown in cold climates, however, had lower ratios. In all studies, the J max : V cmax ratio declined strongly with measurement temperature. The relative temperature responses of J max and V cmax were relatively constant among tree species. Activation energies averaged 50 kJ mol −1 for J max and 65 kJ mol −1 for V cmax , and for most species temperature optima averaged 33 °C for J max and 40 °C for V cmax . However, the cold climate tree species had low temperature optima for both J max ( 19 °C) and V cmax (29 °C), suggesting acclimation of both processes to growth temperature. Crop species had somewhat different temperature responses, with higher activation energies for both J max and V cmax , implying narrower peaks in the temperature response for these species. The results thus suggest that both growth environment and plant type can influence the photosynthetic response to temperature. Based on these results, several suggestions are made to improve modelling of temperature responses.

Stimulation of terrestrial plant production by rising CO(2) concentration is projected to reduce the airborne fraction of anthropogenic CO(2) emissions. Coupled climate-carbon cycle models are sensitive to this negative feedback on atmospheric CO(2), but model projections are uncertain because of the expectation that feedbacks through the nitrogen (N) cycle will reduce this so-called CO(2) fertilization effect. We assessed whether N limitation caused a reduced stimulation of net primary productivity (NPP) by elevated atmospheric CO(2) concentration over 11 y in a free-air CO(2) enrichment (FACE) experiment in a deciduous Liquidambar styraciflua (sweetgum) forest stand in Tennessee. During the first 6 y of the experiment, NPP was significantly enhanced in forest plots exposed to 550 ppm CO(2) compared with NPP in plots in current ambient CO(2), and this was a consistent and sustained response. However, the enhancement of NPP under elevated CO(2) declined from 24% in 2001-2003 to 9% in 2008. Global analyses that assume a sustained CO(2) fertilization effect are no longer supported by this FACE experiment. N budget analysis supports the premise that N availability was limiting to tree growth and declining over time--an expected consequence of stand development, which was exacerbated by elevated CO(2). Leaf- and stand-level observations provide mechanistic evidence that declining N availability constrained the tree response to elevated CO(2); these observations are consistent with stand-level model projections. This FACE experiment provides strong rationale and process understanding for incorporating N limitation and N feedback effects in ecosystem and global models used in climate change assessments.

We review the current status of three well-established models (direct benefits, indirect benefits and sensory drive) and one newcomer (antagonistic chase-away) of the evolution of mate choice and the biases that are expressed during choice. We highlight the differences and commonalities in the underlying genetics and evolutionary dynamics of these models. We then argue that progress in understanding the evolution of mate choice is currently hampered by spurious distinctions among models and a misguided tendency to test the processes underlying each model as mutually exclusive alternatives. Finally, we suggest potentially fruitful directions for future theoretical and empirical research.

BACKGROUND: Forest, grass, and peat fires release approximately 2 petagrams of carbon into the atmosphere each year, influencing weather, climate, and air quality. OBJECTIVE: We estimated the annual global mortality attributable to landscape fire smoke (LFS). METHODS: Daily and annual exposure to particulate matter ≤ 2.5 μm in aerodynamic diameter (PM(2.5)) from fire emissions was estimated globally for 1997 through 2006 by combining outputs from a chemical transport model with satellite-based observations of aerosol optical depth. In World Health Organization (WHO) subregions classified as sporadically affected, the daily burden of mortality was estimated using previously published concentration-response coefficients for the association between short-term elevations in PM(2.5) from LFS (contrasted with 0 μg/m3 from LFS) and all-cause mortality. In subregions classified as chronically affected, the annual burden of mortality was estimated using the American Cancer Society study coefficient for the association between long-term PM(2.5) exposure and all-cause mortality. The annual average PM(2.5) estimates were contrasted with theoretical minimum (counterfactual) concentrations in each chronically affected subregion. Sensitivity of mortality estimates to different exposure assessments, counterfactual estimates, and concentration-response functions was evaluated. Strong La Niña and El Niño years were compared to assess the influence of interannual climatic variability. RESULTS: Our principal estimate for the average mortality attributable to LFS exposure was 339,000 deaths annually. In sensitivity analyses the interquartile range of all tested estimates was 260,000-600,000. The regions most affected were sub-Saharan Africa (157,000) and Southeast Asia (110,000). Estimated annual mortality during La Niña was 262,000, compared with 532,000 during El Niño. CONCLUSIONS: Fire emissions are an important contributor to global mortality. Adverse health outcomes associated with LFS could be substantially reduced by curtailing burning of tropical rainforests, which rarely burn naturally. The large estimated influence of El Niño suggests a relationship between climate and the burden of mortality attributable to LFS.

Abstract A set of thermodynamic models is presented that, for the first time, allows partial melting equilibria to be calculated for metabasic rocks. The models consist of new activity–composition relations combined with end‐member thermodynamic properties from the Holland & Powell dataset, version 6. They allow for forward modelling in the system Na O–CaO–K O–FeO–MgO–Al O –SiO –H O–TiO –Fe O . In particular, new activity–composition relations are presented for silicate melt of broadly trondhjemitic–tonalitic composition, and for augitic clinopyroxene with Si–Al mixing on the tetrahedral sites, while existing activity–composition relations for hornblende are extended to include K O and TiO . Calibration of the activity–composition relations was carried out with the aim of reproducing major experimental phase‐in/phase‐out boundaries that define the amphibolite–granulite transition, across a range of bulk compositions, at ≤13 kbar.

Summary 1. Plant height is a central part of plant ecological strategy. It is strongly correlated with life span, seed mass and time to maturity, and is a major determinant of a species’ ability to compete for light. Plant height is also related to critical ecosystem variables such as animal diversity and carbon storage capacity. However, remarkably little is known about global patterns in plant height. Here, we use maximum height data for 7084 plant Species × Site combinations to provide the first global, cross‐species quantification of the latitudinal gradient in plant height. 2. The mean maximum height of species growing within 15° of the equator (7.8 m) was 29 times greater than the height of species between 60° and 75° N (27 cm), and 31 times greater than the height of species between 45° and 60° S (25 cm). There was no evidence that the latitudinal gradient in plant height was different in the northern hemisphere than in the southern hemisphere ( P = 0.29). A 2.4‐fold drop in plant height at the edge of the tropics ( P = 0.006) supports the idea that there might be a switch in plant strategy between temperate and tropical zones. 3. We investigated 22 environmental variables to determine which factors underlie the latitudinal gradient in plant height. We found that species with a wide range of height strategies were present in cold, dry, low productivity systems, but there was a noticeable lack of very short species in wetter, warmer, more productive sites. Variables that capture information about growing conditions during the harsh times of the year were relatively poor predictors of height. The best model for global patterns in plant height included only one term: precipitation in the wettest month ( R 2 = 0.256). 4. Synthesis . We found a remarkably steep relationship between latitude and height, indicating a major difference in plant strategy between high and low latitude systems. We also provide new, surprising information about the correlations between plant height and environmental variables.

Forest restoration is being scaled up globally to deliver critical ecosystem services and biodiversity benefits; however, there is a lack of rigorous comparison of cobenefit delivery across different restoration approaches. Through global synthesis, we used 25,950 matched data pairs from 264 studies in 53 countries to assess how delivery of climate, soil, water, and wood production services, in addition to biodiversity, compares across a range of tree plantations and native forests. Benefits of aboveground carbon storage, water provisioning, and especially soil erosion control and biodiversity are better delivered by native forests, with compositionally simpler, younger plantations in drier regions performing particularly poorly. However, plantations exhibit an advantage in wood production. These results underscore important trade-offs among environmental and production goals that policy-makers must navigate in meeting forest restoration commitments.