245 research outputs found

    Intestinal parasites of endangered orangutans (Pongo pygmaeus) in Central and East Kalimantan, Borneo, Indonesia

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    Faecal samples from 163 captive and semi-captive individuals, 61 samples from wild individuals and 38 samples from captive groups of Bornean orangutans (Pongo pygmaeus) in Kalimantan, Indonesia, were collected during one rainy season (November 2005-May 2006) and screened for intestinal parasites using sodium acetate-acetic acid-formalin-concentration (SAFC), sedimentation, flotation, McMaster- and Baermann techniques. We aimed to identify factors influencing infection risk for specific intestinal parasites in wild orangutans and individuals living in captivity. Various genera of Protozoa (including Entamoeba, Endolimax, Iodamoeba, Balantidium, Giardia and Blastocystis), nematodes (such as Strongyloides, Trichuris, Ascaris, Enterobius, Trichostrongylus and hookworms) and one trematode (a dicrocoeliid) were identified. For the first time, the cestode Hymenolepis was detected in orangutans. Highest prevalences were found for Strongyloides (individuals 37%; groups 58%), hookworms (41%; 58%), Balantidium (40%; 61%), Entamoeba coli (29%; 53%) and a trichostrongylid (13%; 32%). In re-introduction centres, infants were at higher risk of infection with Strongyloides than adults. Infection risk for hookworms was significantly higher in wild males compared with females. In groups, the centres themselves had a significant influence on the infection risk for Balantidium. Ranging patterns of wild orangutans, overcrowding in captivity and a shift of age composition in favour of immatures seemed to be the most likely factors leading to these result

    Inter-model comparison of global hydroxyl radical (OH) distributions and their impact on atmospheric methane over the 2000–2016 period

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    The modeling study presented here aims to estimate how uncertainties in global hydroxyl radical (OH) distributions, variability, and trends may contribute to resolving discrepancies between simulated and observed methane (CH4) changes since 2000. A multi-model ensemble of 14 OH fields was analyzed and aggregated into 64 scenarios to force the offline atmospheric chemistry transport model LMDz (Laboratoire de Meteorologie Dynamique) with a standard CH4 emission scenario over the period 2000–2016. The multi-model simulated global volume-weighted tropospheric mean OH concentration ([OH]) averaged over 2000–2010 ranges between 8:7*10^5 and 12:8*10^5 molec cm-3. The inter-model differences in tropospheric OH burden and vertical distributions are mainly determined by the differences in the nitrogen oxide (NO) distributions, while the spatial discrepancies between OH fields are mostly due to differences in natural emissions and volatile organic compound (VOC) chemistry. From 2000 to 2010, most simulated OH fields show an increase of 0.1–0:3*10^5 molec cm-3 in the tropospheric mean [OH], with year-to-year variations much smaller than during the historical period 1960–2000. Once ingested into the LMDz model, these OH changes translated into a 5 to 15 ppbv reduction in the CH4 mixing ratio in 2010, which represents 7%–20% of the model-simulated CH4 increase due to surface emissions. Between 2010 and 2016, the ensemble of simulations showed that OH changes could lead to a CH4 mixing ratio uncertainty of > 30 ppbv. Over the full 2000–2016 time period, using a common stateof- the-art but nonoptimized emission scenario, the impact of [OH] changes tested here can explain up to 54% of the gap between model simulations and observations. This result emphasizes the importance of better representing OH abundance and variations in CH4 forward simulations and emission optimizations performed by atmospheric inversions

    Multimodel assessment of the upper troposphere and lower stratosphere: Extratropics

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    A multimodel assessment of the performance of chemistry-climate models (CCMs) in the extratropical upper troposphere/lower stratosphere (UTLS) is conducted for the first time. Process-oriented diagnostics are used to validate dynamical and transport characteristics of 18 CCMs using meteorological analyses and aircraft and satellite observations. The main dynamical and chemical climatological characteristics of the extratropical UTLS are generally well represented by the models, despite the limited horizontal and vertical resolution. The seasonal cycle of lowermost stratospheric mass is realistic, however with a wide spread in its mean value. A tropopause inversion layer is present in most models, although the maximum in static stability is located too high above the tropopause and is somewhat too weak, as expected from limited model resolution. Similar comments apply to the extratropical tropopause transition layer. The seasonality in lower stratospheric chemical tracers is consistent with the seasonality in the Brewer-Dobson circulation. Both vertical and meridional tracer gradients are of similar strength to those found in observations. Models that perform less well tend to use a semi-Lagrangian transport scheme and/or have a very low resolution. Two models, and the multimodel mean, score consistently well on all diagnostics, while seven other models score well on all diagnostics except the seasonal cycle of water vapor. Only four of the models are consistently below average. The lack of tropospheric chemistry in most models limits their evaluation in the upper troposphere. Finally, the UTLS is relatively sparsely sampled by observations, limiting our ability to quantitatively evaluate many aspects of model performance

    Reducing Baylisascaris procyonis Roundworm Larvae in Raccoon Latrines

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    Baylisascaris procyonis roundworms, a parasite of raccoons, can infect humans, sometimes fatally. Parasite eggs can remain viable in raccoon latrines for years. To develop a management technique for parasite eggs, we tested anthelmintic baiting. The prevalence of eggs decreased at latrines, and larval infections decreased among intermediate hosts, indicating that baiting is effective

    Assessment of upper tropospheric and stratospheric water vapor and ozone in reanalyses as part of S-RIP

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    Reanalysis data sets are widely used to understand atmospheric processes and past variability, and are often used to stand in as “observations” for comparisons with climate model output. Because of the central role of water vapor (WV) and ozone (O3) in climate change, it is important to understand how accurately and consistently these species are represented in existing global reanalyses. In this paper, we present the results of WV and O3 intercomparisons that have been performed as part of the SPARC (Stratosphere–troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (S-RIP). The comparisons cover a range of timescales and evaluate both inter-reanalysis and observation-reanalysis differences. We also provide a systematic documentation of the treatment of WV and O3 in current reanalyses to aid future research and guide the interpretation of differences amongst reanalysis fields. The assimilation of total column ozone (TCO) observations in newer reanalyses results in realistic representations of TCO in reanalyses except when data coverage is lacking, such as during polar night. The vertical distribution of ozone is also relatively well represented in the stratosphere in reanalyses, particularly given the relatively weak constraints on ozone vertical structure provided by most assimilated observations and the simplistic representations of ozone photochemical processes in most of the reanalysis forecast models. However, significant biases in the vertical distribution of ozone are found in the upper troposphere and lower stratosphere in all reanalyses

    Characterizing sampling biases in the trace gas climatologies of the SPARC Data Initiative

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    Monthly zonal mean climatologies of atmospheric measurements from satellite instruments can have biases due to the non-uniform sampling of the atmosphere by the instruments. We characterize potential sampling biases in stratospheric trace gas climatologies of the Stratospheric Processes and their Role in Climate (SPARC) Data Initiative using chemical fields from a chemistry climate model simulation and sampling patterns from 16 satellite-borne instruments. The exercise is performed for the long-lived stratospheric trace gases O3 and H2O. Monthly sample biases for O3 exceed 10% for many instruments in the high latitude stratosphere and in the upper troposphere/lower stratosphere, while annual mean sampling biases reach values of up to 20% in the same regions for some instruments. Sampling biases for H2O are generally smaller than for O3, although still notable in the upper troposphere/lower stratosphere and Southern Hemisphere high latitudes. The most important mechanism leading to monthly sampling bias is the non-uniform temporal sampling of many instruments, i.e., the fact that for many instruments, monthly means are produced from measurements which span less than the full month in question. Similarly, annual mean sampling biases are well explained by non-uniformity in the month-to-month sampling by different instruments. Non-uniform sampling in latitude and longitude are shown to also lead to non-negligible sampling biases, which are most relevant for climatologies which are otherwise free of sampling biases due to non-uniform temporal sampling
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