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Summary Plant functional traits can vary widely as a result of phenotypic plasticity to abiotic conditions. Trait variation may also reflect responses to the identity of neighbours, although not all species are equally responsive to their biotic surroundings. We hypothesized that responses to neighbours are shaped by spatial community patterns and resulting variability in neighbour composition. More precisely, we tested the theoretical prediction that plasticity is most likely to evolve if alternative environments (in this case, different neighbour species) are common and encountered at similar frequencies. We estimated the frequencies of encountering different neighbour species in the field for 27 grassland species and measured the aboveground morphological responses of each species to conspecific vs heterospecific neighbours in a common garden. Responses to neighbour identity were dependent on how frequently the experimental neighbours were encountered by the focal species in their home community, with the greatest plasticity observed in species that encountered both neighbours (conspecific and heterospecific) with high and even frequency. Biotic interactions with neighbouring species can impose selection on plasticity in functional traits, which may feed back through trait divergence and niche differentiation to influence species coexistence and community structure.

Sponges (Porifera), as one of the earliest-branching animal phyla, are crucial for understanding early metazoan phylogeny. Recent studies of Lower Palaeozoic sponges have revealed a variety of character states and combinations unknown in extant taxa, challenging our views of early sponge morphology. The Herefordshire Konservat–Lagerstätte yields an abundant, diverse sponge fauna with three-dimensional preservation of spicules and soft tissue. Carduispongia pedicula gen. et sp. nov. possesses a single layer of hexactine spicules arranged in a regular orthogonal network. This spicule type and arrangement is characteristic of the reticulosans, which have traditionally been interpreted as early members of the extant siliceous Class Hexactinellida. However, the unusual preservation of the spicules of C . pedicula reveals an originally calcareous composition, which would be diagnostic of the living Class Calcarea. The soft tissue architecture closely resembles the complex sylleibid or leuconid structure seen in some modern calcareans and homoscleromorphs. This combination of features strongly supports a skeletal continuum between primitive calcareans and hexactinellid siliceans, indicating that the last common ancestor of Porifera was a spiculate, solitary, vasiform animal with a thin skeletal wall.

According to the ‘good genes’ hypothesis, females choose males based on traits that indicate the male's genetic quality in terms of disease resistance. The ‘immunocompetence handicap hypothesis’ proposed that secondary sexual traits serve as indicators of male genetic quality, because they indicate that males can contend with the immunosuppressive effects of testosterone. Masculinity is commonly assumed to serve as such a secondary sexual trait. Yet, women do not consistently prefer masculine looking men, nor is masculinity consistently related to health across studies. Here, we show that adiposity, but not masculinity, significantly mediates the relationship between a direct measure of immune response (hepatitis B antibody response) and attractiveness for both body and facial measurements. In addition, we show that circulating testosterone is more closely associated with adiposity than masculinity. These findings indicate that adiposity, compared with masculinity, serves as a more important cue to immunocompetence in female mate choice.

AbstractRecent reports of increasing iron (Fe) concentrations in freshwaters are of concern, given the fundamental role of Fe in biogeochemical processes. Still, little is known about the frequency and geographical distribution of Fe trends or about the underlying drivers. We analyzed temporal trends of Fe concentrations across 340 water bodies distributed over 10 countries in northern Europe and North America in order to gain a clearer understanding of where, to what extent, and why Fe concentrations are on the rise. We found that Fe concentrations have significantly increased in 28% of sites, and decreased in 4%, with most positive trends located in northern Europe. Regions with rising Fe concentrations tend to coincide with those with organic carbon (OC) increases. Fe and OC increases may not be directly mechanistically linked, but may nevertheless be responding to common regional‐scale drivers such as declining sulfur deposition or hydrological changes. A role of hydrological factors was supported by covarying trends in Fe and dissolved silica, as these elements tend to stem from similar soil depths. A positive relationship between Fe increases and conifer cover suggests that changing land use and expanded forestry could have contributed to enhanced Fe export, although increases were also observed in nonforested areas. We conclude that the phenomenon of increasing Fe concentrations is widespread, especially in northern Europe, with potentially significant implications for wider ecosystem biogeochemistry, and for the current browning of freshwaters.

A realistic estimation of uncertainty is an essential requirement for all analytical measurements. It is common practice, however, for the uncertainty estimate of a chemical measurement to be based on the instrumental precision associated with the analysis of a single or multiple samples, which can lead to underestimation. Within the context of chemical oceanography such an underestimation of uncertainty could lead to an over interpretation of the result(s) and hence impact on, e.g., studies of biogeochemical cycles, and the outputs from oceanographic models. Getting high quality observational data with a firm uncertainty assessment is therefore essential for proper model validation. This paper describes and compares two recommended approaches that can give a more holistic assessment of the uncertainty associated with such measurements, referred to here as the “bottom up” or modeling approach and the “top down” or empirical approach. “Best practice” recommendations for the implementation of these strategies are provided. The “bottom up” approach combines the standard uncertainties associated with each stage of the entire measurement procedure. The “top down” approach combines the uncertainties associated with day to day reproducibility and possible bias in the complete data set and is easy to use. For analytical methods that are routinely used, laboratories will have access to the information required to calculate the uncertainty from archived quality assurance data. The determination of trace elements in seawater is a significant analytical challenge and iron is used as an example for the implementation of both approaches using real oceanographic data. Relative expanded uncertainties of 10 – 20% were estimated for both approaches compared with a typical short term precision (rsd) of ≤5%.

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the "global carbon budget" – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), EFF was 9.4 ± 0.5 GtC yr−1, ELUC 1.3 ± 0.7 GtC yr−1, GATM 4.7 ± 0.1 GtC yr−1, SOCEAN 2.4 ± 0.5 GtC yr−1, and SLAND 3.0 ± 0.8 GtC yr−1, with a budget imbalance BIM of 0.6 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1. Also for 2016, ELUC was 1.3 ± 0.7 GtC yr−1, GATM was 6.1 ± 0.2 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 2.7 ± 1.0 GtC yr−1, with a small BIM of −0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the high fossil emissions and the small SLAND consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.0 % (range of 0.8 to 3.0 %) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017) 44 pages, 9 tables, 9 figures.-- Corinne Le Quéré ... et al.-- This work is distributed under the Creative Commons Attribution 4.0 License Peer reviewed