Now showing 1 - 8 of 8
  • Publication
    Assessing the sensitivity of fertilizer types and soil variables on nitrous oxide emissions in permanent grasslands using the DNDC model
    The adoption and use of improved methodologies including models that reflect more robust emissions accounting procedures and the identification of specific mitigation options for agricultural greenhouse gases are a global concern. In Ireland, country-specific N2O emission factors (EFs) are constrained primarily by short-term measurements and limited coverage of regulating factors. Simulation of N2O emissions from grassland silage plots managed for 42 years with different slurry treatments was performed using the DeNitrification-DeComposition (DNDC95) model. The objective was to assess the long-term impact of management practices on N2O fluxes and EFs, and the sensitivity of the outputs to key inorganic and organic fertilizer management and soil variables. The DNDC performed well for urea, cattle slurry and pig slurry applied at variable rates, delivering EFs on-average of 0.35±0.02, 1.80±0.28 and 1.53±0.41%, respectively. Variation in the derived-EFs could be explained by differences in nitrogen inputs (49%), rainfall (16%) and temperature (10%) and are close to national estimates. Sensitivity analysis of the model demonstrated that N2O EFs were higher with ammonium sulphate compared to CAN and urea fertilizers, and with urea-N at higher rates. The replacement of slurry either after the second or third silage cut by urea decreased EFs significantly. There was a strong correlation with the sensitivity of N2O EFs to soil texture, bulk density, pH and organic carbon (R2=0.96-0.99). The resulting-EFs ranged from 0.28 to 0.41% for urea, 1.12 to 2.07% for cattle slurry, and 1.05 to 1.65% for pig slurry, and the corresponding values on-average were 0.35±0.02, 1.74±0.17 and 1.39±0.12%. These findings show that DNDC95, although requiring more improvement, could provide an accurate representation of the effect of soils, climate and management practices on N2O fluxes and subsequent estimates of disaggregated EFs.
  • Publication
    Open minded and open access: introducing NeoBiota, a new peer-reviewed journal of biological invasions
    The Editorial presents the focus, scope, policies, and the inaugural issue of NeoBiota, a new open access peer-reviewed journal of biological invasions. The new journal NeoBiota is a continuation of the former NEOBIOTA publication series. The journal will deal with all aspects of invasion biology and impose no restrictions on manuscript size neither on use of color. NeoBiota implies an XML-based editorial workflow and several cutting-edge innovations in publishing and dissemination, such as semantic markup of and enhancements to published texts, data publication, and extensive cross-linking within the journal and to external sources.
  • Publication
    COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data
    Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil‐to‐atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS), is one of the largest carbon fluxes in the Earth system. An increasing number of high‐frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open‐source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long‐term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS, the database design accommodates other soil‐atmosphere measurements (e.g. ecosystem respiration, chamber‐measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package.
      110Scopus© Citations 33
  • Publication
    Effect of soil microorganisms and labile C availability on soil respiration in response to litter inputs in forest ecosystems: A meta‐analysis
    Litter inputs can influence soil respiration directly through labile C availability and, indirectly, through the activity of soil microorganisms and modifications in soil microclimate; however, their relative contributions and the magnitude of any effect remain poorly understood. We synthesized 66 recently published papers on forest ecosystems using a meta‐analysis approach to investigate the effect of litter inputs on soil respiration and the underlying mechanisms involved. Our results showed that litter inputs had a strong positive impact on soil respiration, labile C availability, and the abundance of soil microorganisms, with less of an impact related to soil moisture and temperature. Overall, soil respiration was increased by 36% and 55%, respectively, in response to natural and doubled litter inputs. The increase in soil respiration induced by litter inputs showed a tendency for coniferous forests (50.7%)> broad‐leaved forests (41.3%)> mixed forests (31.9%). This stimulation effect also depended on stand age with 30‐ to 100‐year‐old forests (53.3%) and ≥100‐year‐old forests (50.2%) both 1.5 times larger than ≤30‐year‐old forests (34.5%). Soil microbial biomass carbon and soil dissolved organic carbon increased by 21.0%‐33.6% and 60.3%‐87.7%, respectively, in response to natural and doubled litter inputs, while soil respiration increased linearly with corresponding increases in soil microbial biomass carbon and soil dissolved organic carbon. Natural and doubled litter inputs increased the total phospholipid fatty acid (PLFA) content by 6.6% and 19.7%, respectively, but decreased the fungal/bacterial PLFA ratio by 26.9% and 18.7%, respectively. Soil respiration also increased linearly with increases in total PLFA and decreased linearly with decreases in the fungal/bacterial PLFA ratio. The contribution of litter inputs to an increase in soil respiration showed a trend of total PLFA > fungal/bacterial PLFA ratio > soil dissolved organic carbon > soil microbial biomass carbon. Therefore, in addition to forest type and stand age, labile C availability and soil microorganisms are also important factors that influence soil respiration in response to litter inputs, with soil microorganisms being more important than labile C availability.
      70Scopus© Citations 21
  • Publication
    Temperature Impacts the Response of Coffea canephora to Decreasing Soil Water Availability
    (Springer Nature, 2020-03-04)
    Climate change is expected to result in more frequent periods of both low rainfall and above normal temperatures for many coffee growing regions. To understand how coffee reacts to such change, we studied the physiological and gene expression responses of the clonal variety C. canephora FRT07 exposed to water deficits under two different temperature regimes. Variations in the time-dependent impact of water deficits on leaf stomatal conductance and carbon assimilation were significantly different under the 27 °C and 27 °C/42 °C conditions examined. The physiological responses 24 h after re-watering were also different for both conditions. Expression analysis of genes known to respond to water deficits indicated that drought-related signaling occurred at both temperatures. Deeper insights into the response of coffee to water deficits was obtained by RNASeq based whole transcriptome profiling of leaves from early, late, and recovery stages of the 27 °C experiment. This yielded expression data for 13,642 genes and related differential expression analysis uncovered 362 and 474 genes with increased and decreased expression, respectively, under mild water deficits, and 1627 genes and 2197 genes, respectively, under more severe water deficits. The data presented, from a single clonal coffee variety, serves as an important reference point for future comparative physiological/transcriptomic studies with clonal coffee varieties with different sensitivities to water deficits and high temperatures. Such comparative analyses will help predict how different coffee varieties respond to changing climatic conditions, and may facilitate the identification of alleles associated with high and low tolerance to water deficits, enabling faster breeding of more climate-smart coffee trees.
      146Scopus© Citations 10
  • Publication
    Assessment of nitrous oxide emission factors for arable and grassland ecosystems
    We quantified seasonal nitrous oxide (N2O) emissions and the associated emission factors (EFs) from: (i) winter oilseed rape (WOSR) cultivated under conventional tillage (CT) and strip tillage (ST) at four fertilizer rates (0, 160, 240 and 320 kg N ha−1) in 2014/2015, and (ii) grassland plots receiving no fertilizer (0 kg N ha−1), or mineral nitrogen (67 kg N ha−1), and either cattle or pig slurry (50, 100 and 200 m3 ha−1). Greater fluxes were observed at higher soil temperatures and a higher water filled pore space, suggesting that denitrification was the main source of N2O-N from the applied fertilizer/slurry. For WOSR, the N2O EFs ranged from 0.03 to 1.20% with no effect of the cultivation practice on EFs for equal rates of nitrogen fertilizer. Lower EF values were linked to differences in plant growth at individual sites rather than a specific management effect. For the grassland, the N2O EFs were highly variable, ranging from −0.70 to 0.49%, but were generally the highest in treatments receiving the highest concentrations of slurry. The EF values for WOSR illustrates that the Tier 1 approach for calculating EFs may be inadequate and the identification of site-specific effects can aid in refining N2O EF inventories. For the grassland plots all the EFs were significantly lower than the IPCC default values. Although the reason(s) for the low EFs with slurry amendments on grassland is not known, ammonia volatilization could decrease the pool of inorganic N that is available to nitrifying bacteria thereby lowering N2O fluxes.
      102Scopus© Citations 4
  • Publication
    No effect of warming and watering on soil nitrous oxide fluxes in a temperate sitka spruce forest ecosystem
    (Taylor & Francis, 2020-10-08) ;
    Soil fluxes of nitrous oxide (N2O) play an important role in the global greenhouse gas budget. However, the response of soil N2O emissions to climate change in temperate forest plantations is not yet well understood. In this study, we assessed the responses of soil N2O fluxes to experimental warming with or without water addition, using a replicated in situ heating (~2°C above ambient) and water addition (170 mm) experiment in a temperate Sitka spruce plantation forest over the period 2014–2016. We found that seasonal fluxes of N2O during the year were highly variable, ranging from net uptake to net emissions. Seasonal variations in soil N2O fluxes were not correlated with either soil temperature or soil moisture. In addition, none of the individual warming/watering treatments, or their interactions, had significant effects on soil N2O fluxes and N-related soil properties. Overall, our results suggest that despite future increases in temperature, soil N2O emission may remain largely unchanged in many temperate forest ecosystems that are often N-limited.
      73Scopus© Citations 2
  • Publication
    Evolving Interpolating Models of Net Ecosystem CO2 Exchange Using Grammatical Evolution
    Accurate measurements of Net Ecosystem Exchange of CO2 between atmosphere and biosphere are required in order to estimate annual carbon budgets. These are typically obtained with Eddy Covariance techniques. Unfortunately, these techniques are often both noisy and incomplete, due to data loss through equipment failure and routine maintenance, and require gap-filling techniques in order to provide accurate annual budgets. In this study, a grammar-based version of Genetic Programming is employed to generate interpolating models for flux data. The evolved models are robust, and their symbolic nature provides further understanding of the environmental variables involved.
      296Scopus© Citations 7