Abstract. Quantifying forcings from anthropogenic perturbations to the Earth system (ES) is important for understanding changes in climate since the pre-industrial (PI) period. Here, we quantify and analyse a wide range of present-day (PD) anthropogenic effective radiative forcings (ERFs) with the UK's Earth System Model (ESM), UKESM1, following the protocols defined by the Radiative Forcing Model Intercomparison Project (RFMIP) and the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). In particular, quantifying ERFs that include rapid adjustments within a full ESM enables the role of various chemistry–aerosol–cloud interactions to be investigated. Global mean ERFs for the PD (year 2014) relative to the PI (year 1850) period for carbon dioxide (CO2), nitrous oxide (N2O), ozone-depleting substances (ODSs), and methane (CH4) are 1.89 ± 0.04, 0.25 ± 0.04, −0.18 ± 0.04, and 0.97 ± 0.04 W m−2, respectively. The total greenhouse gas (GHG) ERF is 2.92 ± 0.04 W m−2. UKESM1 has an aerosol ERF of −1.09 ± 0.04 W m−2. A relatively strong negative forcing from aerosol–cloud interactions (ACI) and a small negative instantaneous forcing from aerosol–radiation interactions (ARI) from sulfate and organic carbon (OC) are partially offset by a substantial forcing from black carbon (BC) absorption. Internal mixing and chemical interactions imply that neither the forcing from ARI nor ACI is linear, making the aerosol ERF less than the sum of the individual speciated aerosol ERFs. Ozone (O3) precursor gases consisting of volatile organic compounds (VOCs), carbon monoxide (CO), and nitrogen oxides (NOx), but excluding CH4, exert a positive radiative forcing due to increases in O3. However, they also lead to oxidant changes, which in turn cause an indirect aerosol ERF. The net effect is that the ERF from PD–PI changes in NOx emissions is negligible at 0.03 ± 0.04 W m−2, while the ERF from changes in VOC and CO emissions is 0.33 ± 0.04 W m−2. Together, aerosol and O3 precursors (called near-term climate forcers (NTCFs) in the context of AerChemMIP) exert an ERF of −1.03 ± 0.04 W m−2, mainly due to changes in the cloud radiative effect (CRE). There is also a negative ERF from land use change (−0.17 ± 0.04 W m−2). When adjusted from year 1850 to 1700, it is more negative than the range of previous estimates, and is most likely due to too strong an albedo response. In combination, the net anthropogenic ERF (1.76 ± 0.04 W m−2) is consistent with other estimates. By including interactions between GHGs, stratospheric and tropospheric O3, aerosols, and clouds, this work demonstrates the importance of ES interactions when quantifying ERFs. It also suggests that rapid adjustments need to include chemical as well as physical adjustments to fully account for complex ES interactions.
Overweight and obesity induce serious health problems that exert negative effects on dog’s welfare. Body condition score (BCS) is a common method to evaluate the body fat mass in animals. By palpating and observing fats under the skin it is possible to predict animal’s body fat accumulation condition. BCS is also a useful tool to estimate body fat composition in dogs. However, BCS can be subjective when it was performed by non-professionals like pet’s owners. To develop a method to avoid the misevaluation of BCS twenty-four Beagles were enrolled and performed BCS evaluation. In addition, the length of chest and abdominal girths were measured. In correlation analysis, the sizes of chest and abdominal girth were significantly correlated with BCS. Especially, the difference and ratio of the chest and abdominal length were highly correlated with the BCS. With that, we suggested that this simple measurement of chest and abdominal girths by a measuring tape would be an effective method to estimate BCS scores in dogs that helps non-professionals to manage their own dog’s nutritional condition by monitoring body fat accumulation condition.
Microorganism residing in the gut has been known to have important roles in the animal body. Microbes and host microenvironment are highly related with host's health including energy metabolism and immune system. Moreover, it reported that gut microbiome is correlated with diseases like obesity in human and dogs. There have been many studies to identify and characterize microbes and their genes in human body. However, there was little information of microbiome in companion animals. Here, we investigated microbiota communities in feaces from twenty-four Beagles (aged 2 years old) and analyzed the taxonomy profile using metagenomics to study the difference among gut microbiome based on body condition score (BCS). gDNA was isolated from feaces, sequenced and clustered. Taxonomy profiling was performed based on the NCBI database. BCS was evaluated once a week according to the description provided by World Small Animal Veterinary Association. Firmicutes phylum was the most abundant followed by Bacteroidetes, Fusobacteria, Proteobacteria and Actinobacteria. That main microbiota in gut were differently distributed based on the BCS. Fusobacteria has been known to be associated with colon cancer in human. Interestingly, Fusobacteria was in the third level from the top in healthy dog's gut microbiome. In addition, Fusobacteria was especially higher in overweight dogs which had 6 scales of BCS. Species Fusobacterium perfoetens was also more abundant when dogs were in BCS 6. It implied that F. perfoetens would be positively related with overweight in dogs. These finding would contribute to further studies of gut microbiome and their functions to improve dog's diets and health condition.
<p><strong>Abstract.</strong> Quantifying forcings from anthropogenic perturbations to the Earth System (ES) is important for understanding changes in climate since the pre-industrial period. In this paper, we quantify and analyse a wide range of present-day (PD) anthropogenic climate forcings with the UK's Earth System Model (ESM), UKESM1, following the protocols defined by the Radiative Forcing Model Intercomparison Project (RFMIP) and the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). In particular, by quantifying effective radiative forcings (ERFs) that include rapid adjustments within a full ESM, it enables the role of various climate-chemistry-aerosol-cloud feedbacks to be quantified.</p> <p>Global mean ERFs are 1.83, 0.13, &#8722;0.33, and 0.93&#8201;W&#8201;m<sup>&#8722;2</sup> at the PD (Year 2014) relative to the pre-industrial (PI; Year 1850) for carbon dioxide, nitrous oxide, ozone-depleting substances, and methane, respectively. The PD total greenhouse gas ERF is 2.89&#8201;W&#8201;m<sup>&#8722;2</sup>, larger than the sum of the individual GHG ERFs.</p> <p>UKESM1 has an aerosol forcing of &#8722;1.13&#8201;W&#8201;m<sup>&#8722;2</sup>. A relatively strong negative forcing from aerosol-cloud interactions and a small negative instantaneous forcing from aerosol-radiation interactions are partially offset by a substantial forcing from black carbon absorption. Internal mixing and chemical interactions mean that neither the forcing from aerosol-radiation interactions nor aerosol-cloud interactions are linear, making the total aerosol ERF less than the sum of the individual speciated aerosol ERFs.</p> <p>Tropospheric ozone precursors, in addition to exerting a positive forcing due to ozone, lead to oxidant changes which in turn cause an indirect aerosol ERF, altering the sign of the net ERF from nitrogen oxide emissions. Together, aerosol and tropospheric ozone precursors (near-term climate forcers, NTCFs) exert a global mean ERF of &#8722;1.12&#8201;W&#8201;m<sup>&#8722;2</sup>, mainly due to changes in the cloud radiative effect. There is also a negative PD ERF from land use (&#8722;0.32&#8201;W&#8201;m<sup>&#8722;2</sup>). It is outside the range of previous estimates, and is most likely due to too strong an albedo response. In combination, the net anthropogenic ERF is potentially biased low (1.61&#8201;W&#8201;m<sup>&#8722;2</sup>) relative to other estimates, due to the inclusion of non-linear feedbacks and ES interactions.</p> <p>By including feedbacks between greenhouse gases, stratospheric and tropospheric ozone, aerosols, and clouds, some of which act non-linearly, this work demonstrates the importance of ES interactions when quantifying climate forcing. It also suggests that rapid adjustments need to include chemical as well as physical adjustments to fully account for complex ES interactions.</p>
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