958 resultados para terrestrial


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Background Plants form the base of the terrestrial food chain and provide medicines, fuel, fibre and industrial materials to humans. Vascular land plants rely on their roots to acquire the water and mineral elements necessary for their survival in nature or their yield and nutritional quality in agriculture. Major biogeochemical fluxes of all elements occur through plant roots, and the roots of agricultural crops have a significant role to play in soil sustainability, carbon sequestration, reducing emissions of greenhouse gasses, and in preventing the eutrophication of water bodies associated with the application of mineral fertilisers. ● Scope This article provides the context for a Special Issue of Annals of Botany on ‘Matching Roots to Their Environment’. It first examines how land plants and their roots evolved, describes how the ecology of roots and their rhizospheres contributes to the acquisition of soil resources, and discusses the influence of plant roots on biogeochemical cycles. It then describes the role of roots in overcoming the constraints to crop production imposed by hostile or infertile soils, illustrates root phenotypes that improve the acquisition of mineral elements and water, and discusses high-throughput methods to screen for these traits in the laboratory, glasshouse and field. Finally, it considers whether knowledge of adaptations improving the acquisition of resources in natural environments can be used to develop root systems for sustainable agriculture in the future.

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Soil biodiversity plays a key role in regulating the processes that underpin the delivery of ecosystem goods and services in terrestrial ecosystems. Agricultural intensification is known to change the diversity of individual groups of soil biota, but less is known about how intensification affects biodiversity of the soil food web as a whole, and whether or not these effects may be generalized across regions. We examined biodiversity in soil food webs from grasslands, extensive, and intensive rotations in four agricultural regions across Europe: in Sweden, the UK, the Czech Republic and Greece. Effects of land-use intensity were quantified based on structure and diversity among functional groups in the soil food web, as well as on community-weighted mean body mass of soil fauna. We also elucidate land-use intensity effects on diversity of taxonomic units within taxonomic groups of soil fauna. We found that between regions soil food web diversity measures were variable, but that increasing land-use intensity caused highly consistent responses. In particular, land-use intensification reduced the complexity in the soil food webs, as well as the community-weighted mean body mass of soil fauna. In all regions across Europe, species richness of earthworms, Collembolans, and oribatid mites was negatively affected by increased land-use intensity. The taxonomic distinctness, which is a measure of taxonomic relatedness of species in a community that is independent of species richness, was also reduced by land-use intensification. We conclude that intensive agriculture reduces soil biodiversity, making soil food webs less diverse and composed of smaller bodied organisms. Land-use intensification results in fewer functional groups of soil biota with fewer and taxonomically more closely related species. We discuss how these changes in soil biodiversity due to land-use intensification may threaten the functioning of soil in agricultural production systems.

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Between December 2010 and March 2013, volunteers for the Solar Stormwatch (SSW) Citizen Science project have identified and analyzed coronal mass ejections (CMEs) in the near real-time Solar Terrestrial Relations Observatory Heliospheric Imager observations, in order to make “Fearless Forecasts” of CME arrival times and speeds at Earth. Of the 60 predictions of Earth-directed CMEs, 20 resulted in an identifiable Interplanetary CME (ICME) at Earth within 1.5–6 days, with an average error in predicted transit time of 22 h, and average transit time of 82.3 h. The average error in predicting arrival speed is 151 km s−1, with an average arrival speed of 425km s−1. In the same time period, there were 44 CMEs for which there are no corresponding SSW predictions, and there were 600 days on which there was neither a CME predicted nor observed. A number of metrics show that the SSW predictions do have useful forecast skill; however, there is still much room for improvement. We investigate potential improvements by using SSW inputs in three models of ICME propagation: two of constant acceleration and one of aerodynamic drag. We find that taking account of interplanetary acceleration can improve the average errors of transit time to 19 h and arrival speed to 77 km s−1.

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More than half of global soil carbon is stored as carbonates, primarily in arid and semi-arid zones. Climate change models predict more frequent and severe rainfall events in some parts of the globe, many of which are dominated by calcareous soils. Such events trigger substantial increases in soil CO2 efflux. We hypothesised that the primary source of CO2 emissions from calcareous, arid zone soil during a single wetting event is abiotic and that soil acidification and wetting have a positive, potentially interacting, effect. We manipulated soil pH, soil moisture, and controlled soil respiration by gamma irradiating half of an 11 day incubation experiment. All manipulated experimental treatments had a rapid and enormous effect on CO2 emission. Respiration contributed ca. 5% of total CO2 efflux; the major source (carbonate buffering) varied depending on the extent of acidification and wetting. Maximum CO2 efflux occurred when pH was lowest and at intermediate matric potential. CO2 efflux was lowest at native pH when soil was air dry. Our data suggest that there may be an underestimate of soil-atmosphere carbon fluxes in arid ecosystems with calcareous soils. There is also a clear potential that these soils may become net carbon sources depending on changes in rainfall patterns, rainfall acidity, and future land management. Our findings have major implications for carbon cycling in arid zone soil and further study of carbon dynamics in these terrestrial systems at a landscape level will be required if we are to improve global climate and carbon cycling models.

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Most terrestrial plants form mutually beneficial symbioses with specific soil-borne fungi known as mycorrhiza. In a typical mycorrhizal association, fungal hyphae colonize plant roots, explore the soil beyond the rhizosphere and provide host plants with nutrients that might be chemically or physically inaccessible to root systems. Here, we combined nutritional, radioisotopic (33P) and genetic approaches to describe a plant growth promoting symbiosis between the basidiomycete fungus Austroboletus occidentalis and jarrah (Eucalyptus marginata), which has quite different characteristics. We show that the fungal partner does not colonize plant roots; hyphae are localized to the rhizosphere soil and vicinity and consequently do not transfer nutrients located beyond the rhizosphere. Transcript profiling of two high-affinity phosphate (Pi) transporter genes (EmPHT1;1 and EmPHT1;2) and hyphal-mediated 33Pi uptake suggest that the Pi uptake shifts from an epidermal to a hyphal pathway in ectomycorrhizal plants (Scleroderma sp.), similar to arbuscular mycorrhizal symbioses, whereas A. occidentalis benefits its host indirectly. The enhanced rhizosphere carboxylates are linked to growth and nutritional benefits in the novel symbiosis. This work is a starting point for detailed mechanistic studies on other basidiomycete–woody plant relationships, where a continuum between heterotrophic rhizosphere fungi and plant beneficial symbioses is likely to exist.

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The atmospheric carbon dioxide concentration plays a crucial role in the radiative balance and as such has a strong influence on the evolution of climate. Because of the numerous interactions between climate and the carbon cycle, it is necessary to include a model of the carbon cycle within a climate model to understand and simulate past and future changes of the carbon cycle. In particular, natural variations of atmospheric CO2 have happened in the past, while anthropogenic carbon emissions are likely to continue in the future. To study changes of the carbon cycle and climate on timescales of a few hundred to a few thousand years, we have included a simple carbon cycle model into the iLOVECLIM Earth System Model. In this study, we describe the ocean and terrestrial biosphere carbon cycle models and their performance relative to observational data. We focus on the main carbon cycle variables including the carbon isotope ratios δ13C and the Δ14C. We show that the model results are in good agreement with modern observations both at the surface and in the deep ocean for the main variables, in particular phosphates, dissolved inorganic carbon and the carbon isotopes.

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Carbon and nitrogen stable isotope ratios of 45 human and 23 faunal bone collagen samples were measured to study human diet and the management of domestic herbivores in past Jordan, contrasting skeletal remains from the Middle and Late Bronze Age and the Late Roman and Byzantine periods from the site of Ya'amūn near Irbid. The isotope data demonstrate that the management of the sheep and goats changed over time, with the earlier animals consuming more plants from semi-arid habitats, possibly because of transhumant herding strategies. The isotope data for fish presented here are the first from archaeological contexts from the Southern Levant. Although fish of diverse provenance was available at the site, human diet was predominately based on terrestrial resources and there was little dietary variability within each time-period. Isotopic variation between humans from different time-periods can mostly be explained by ‘baseline shifts’ in the available food sources; however, it is suggested that legumes may have played a more significant role in Middle and Late Bronze Age diet than later on.

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Predominant frameworks for understanding plant ecology have an aboveground bias that neglects soil micro-organisms. This is inconsistent with recent work illustrating the importance of soil microbes in terrestrial ecology. Microbial effects have been incorporated into plant community dynamics using ideas of niche modification and plant–soil community feedbacks. Here, we expand and integrate qualitative conceptual models of plant niche and feedback to explore implications of microbial interactions for understanding plant community ecology. At the same time we review the empirical evidence for these processes. We also consider common mycorrhizal networks, and propose that these are best interpreted within the feedback framework. Finally, we apply our integrated model of niche and feedback to understanding plant coexistence, monodominance and invasion ecology.

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The general circulation models used to simulate global climate typically feature resolution too coarse to reproduce many smaller-scale processes, which are crucial to determining the regional responses to climate change. A novel approach to downscale climate change scenarios is presented which includes the interactions between the North Atlantic Ocean and the European shelves as well as their impact on the North Atlantic and European climate. The goal of this paper is to introduce the global ocean-regional atmosphere coupling concept and to show the potential benefits of this model system to simulate present-day climate. A global ocean-sea ice-marine biogeochemistry model (MPIOM/HAMOCC) with regionally high horizontal resolution is coupled to an atmospheric regional model (REMO) and global terrestrial hydrology model (HD) via the OASIS coupler. Moreover, results obtained with ROM using NCEP/NCAR reanalysis and ECHAM5/MPIOM CMIP3 historical simulations as boundary conditions are presented and discussed for the North Atlantic and North European region. The validation of all the model components, i.e., ocean, atmosphere, terrestrial hydrology, and ocean biogeochemistry is performed and discussed. The careful and detailed validation of ROM provides evidence that the proposed model system improves the simulation of many aspects of the regional climate, remarkably the ocean, even though some biases persist in other model components, thus leaving potential for future improvement. We conclude that ROM is a powerful tool to estimate possible impacts of climate change on the regional scale.

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Farmers are necessary agents in global efforts to conserve the environment now that croplands and pastures together constitute the largest terrestrial system on Earth – covering some 48% of ice-free land surface. Whereas standard economic models predict that farmers will participate in conservation programs so long as they are profitable, empirical findings from behavioral economics point to a number of normally unobservable preferences that may influence the decision-making process. This study tests, for the first time, whether heterogeneity in behavioral preferences correlates with decisions to participate in Payments for Environmental Services (PES) programs. We elicit individual trust and time preferences using economic experiments and link resulting measures to household survey data and participation decisions in a Ugandan PES program. We find that farmers who exhibit a preference for proximate gains – present-biased preferences – are 47.7% more likely to participate in the program than those who show time-consistent or future-biased preferences. This result has implications for ongoing and planned PES programs involving farmers, particularly in Africa, by highlighting a potential relationship between payment timing and participation, and further validates the use of behavioral experiments in explaining real-world decisions.

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We use sunspot group observations from the Royal Greenwich Observatory (RGO) to investigate the effects of intercalibrating data from observers with different visual acuities. The tests are made by counting the number of groups RB above a variable cut-off threshold of observed total whole-spot area (uncorrected for foreshortening) to simulate what a lower acuity observer would have seen. The synthesised annual means of RB are then re-scaled to the full observed RGO group number RA using a variety of regression techniques. It is found that a very high correlation between RA and RB (rAB > 0.98) does not prevent large errors in the intercalibration (for example sunspot maximum values can be over 30 % too large even for such levels of rAB). In generating the backbone sunspot number (RBB), Svalgaard and Schatten (2015, this issue) force regression fits to pass through the scatter plot origin which generates unreliable fits (the residuals do not form a normal distribution) and causes sunspot cycle amplitudes to be exaggerated in the intercalibrated data. It is demonstrated that the use of Quantile-Quantile (“Q  Q”) plots to test for a normal distribution is a useful indicator of erroneous and misleading regression fits. Ordinary least squares linear fits, not forced to pass through the origin, are sometimes reliable (although the optimum method used is shown to be different when matching peak and average sunspot group numbers). However, other fits are only reliable if non-linear regression is used. From these results it is entirely possible that the inflation of solar cycle amplitudes in the backbone group sunspot number as one goes back in time, relative to related solar-terrestrial parameters, is entirely caused by the use of inappropriate and non-robust regression techniques to calibrate the sunspot data.

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This article presents SPARE-ICE, the Synergistic Passive Atmospheric Retrieval Experiment-ICE. SPARE-ICE is the first Ice Water Path (IWP) product combining infrared and microwave radiances. By using only passive operational sensors, the SPARE-ICE retrieval can be used to process data from at least the NOAA 15 to 19 and MetOp satellites, obtaining time series from 1998 onward. The retrieval is developed using collocations between passive operational sensors (solar, terrestrial infrared, microwave), the CloudSat radar, and the CALIPSO lidar. The collocations form a retrieval database matching measurements from passive sensors against the existing active combined radar-lidar product 2C-ICE. With this retrieval database, we train a pair of artificial neural networks to detect clouds and retrieve IWP. When considering solar, terrestrial infrared, and microwave-based measurements, we show that any combination of two techniques performs better than either single-technique retrieval. We choose not to include solar reflectances in SPARE-ICE, because the improvement is small, and so that SPARE-ICE can be retrieved both daytime and nighttime. The median fractional error between SPARE-ICE and 2C-ICE is around a factor 2, a figure similar to the random error between 2C-ICE ice water content (IWC) and in situ measurements. A comparison of SPARE-ICE with Moderate Resolution Imaging Spectroradiometer (MODIS), Pathfinder Atmospheric Extended (PATMOS-X), and Microwave Surface and Precipitation Products System (MSPPS) indicates that SPARE-ICE appears to perform well even in difficult conditions. SPARE-ICE is available for public use.

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We present cross-validation of remote sensing measurements of methane profiles in the Canadian high Arctic. Accurate and precise measurements of methane are essential to understand quantitatively its role in the climate system and in global change. Here, we show a cross-validation between three datasets: two from spaceborne instruments and one from a ground-based instrument. All are Fourier Transform Spectrometers (FTSs). We consider the Canadian SCISAT Atmospheric Chemistry Experiment (ACE)-FTS, a solar occultation infrared spectrometer operating since 2004, and the thermal infrared band of the Japanese Greenhouse Gases Observing Satellite (GOSAT) Thermal And Near infrared Sensor for carbon Observation (TANSO)-FTS, a nadir/off-nadir scanning FTS instrument operating at solar and terrestrial infrared wavelengths, since 2009. The ground-based instrument is a Bruker 125HR Fourier Transform Infrared (FTIR) spectrometer, measuring mid-infrared solar absorption spectra at the Polar Environment Atmospheric Research Laboratory (PEARL) Ridge Lab at Eureka, Nunavut (80° N, 86° W) since 2006. For each pair of instruments, measurements are collocated within 500 km and 24 h. An additional criterion based on potential vorticity values was found not to significantly affect differences between measurements. Profiles are regridded to a common vertical grid for each comparison set. To account for differing vertical resolutions, ACE-FTS measurements are smoothed to the resolution of either PEARL-FTS or TANSO-FTS, and PEARL-FTS measurements are smoothed to the TANSO-FTS resolution. Differences for each pair are examined in terms of profile and partial columns. During the period considered, the number of collocations for each pair is large enough to obtain a good sample size (from several hundred to tens of thousands depending on pair and configuration). Considering full profiles, the degrees of freedom for signal (DOFS) are between 0.2 and 0.7 for TANSO-FTS and between 1.5 and 3 for PEARL-FTS, while ACE-FTS has considerably more information (roughly 1° of freedom per altitude level). We take partial columns between roughly 5 and 30 km for the ACE-FTS–PEARL-FTS comparison, and between 5 and 10 km for the other pairs. The DOFS for the partial columns are between 1.2 and 2 for PEARL-FTS collocated with ACE-FTS, between 0.1 and 0.5 for PEARL-FTS collocated with TANSO-FTS or for TANSO-FTS collocated with either other instrument, while ACE-FTS has much higher information content. For all pairs, the partial column differences are within ± 3 × 1022 molecules cm−2. Expressed as median ± median absolute deviation (expressed in absolute or relative terms), these differences are 0.11 ± 9.60 × 10^20 molecules cm−2 (0.012 ± 1.018 %) for TANSO-FTS–PEARL-FTS, −2.6 ± 2.6 × 10^21 molecules cm−2 (−1.6 ± 1.6 %) for ACE-FTS–PEARL-FTS, and 7.4 ± 6.0 × 10^20 molecules cm−2 (0.78 ± 0.64 %) for TANSO-FTS–ACE-FTS. The differences for ACE-FTS–PEARL-FTS and TANSO-FTS–PEARL-FTS partial columns decrease significantly as a function of PEARL partial columns, whereas the range of partial column values for TANSO-FTS–ACE-FTS collocations is too small to draw any conclusion on its dependence on ACE-FTS partial columns.

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Lightning flash rates, RL, are modulated by corotating interaction regions (CIRs) and the polarity of the heliospheric magnetic field (HMF) in near-Earth space. As the HMF polarity reverses at the heliospheric current sheet (HCS), typically within a CIR, these phenomena are likely related. In this study, RL is found to be significantly enhanced at the HCS and at 27 days prior/after. The strength of the enhancement depends on the polarity of the HMF reversal at the HCS. Near-Earth solar and galactic energetic particle fluxes are also ordered by HMF polarity, though the variations qualitatively differ from RL, with the main increase occurring prior to the HCS crossing. Thus, the CIR effect on lightning is either the result of compression/amplification of the HMF (and its subsequent interaction with the terrestrial system) or that energetic particle preconditioning of the Earth system prior to the HMF polarity change is central to solar wind lightning coupling mechanism.

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The main causes of biodiversity decline are related to human use of resources, which is ultimately triggered by the socioeconomic decisions made by individuals and nations. Characterizing the socioeconomic attributes of areas in which biodiversity is most threatened can help us identify decisions and conditions that promote the presence or absence of threats and potentially suggest more sustainable strategies. In this study we explored how diverse indicators of social and economic development correlate with the conservation status of terrestrial mammals within countries explicitly exploring hypothesized linear and quadratic relationships. First, comparing countries with and without threatened mammals we found that those without threatened species are a disparate group formed by European countries and Small Island Developing States (SIDS) with little in common besides their slow population growth and a past of human impacts. Second, focusing on countries with threatened mammals we found that those with a more threatened mammalian biota have mainly rural populations, are predominantly exporters of goods and services, receive low to intermediate economic benefits from international tourism, and have medium to high human life expectancy. Overall, these results provide a comprehensive characterization of the socioeconomic profiles linked to mammalian conservation status of the world's nations, highlighting the importance of transborder impacts reflected by the international flux of goods, services and people. Further studies would be necessary to unravel the actual mechanisms and threats that link these socioeconomic profiles and indicators with mammalian conservation. Nevertheless, this study presents a broad and complete characterization that offers testable hypotheses regarding how socioeconomic development associates with biodiversity.