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1. ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales

Author

Qiu, C, Zhu, D, Ciais, P, Guenet, B, Krinner, G, Peng, S, Aurela, M, Bernhofer, C, Brümmer, C, Bret-Harte, S, Chu, H, Chen, J, Desai, AR, Dušek, J, Euskirchen, ES, Fortuniak, K, Flanagan, LB, Friborg, T, Grygoruk, M, Gogo, S, Grünwald, T, Hansen, BU, Holl, D, Humphreys, E, Hurkuck, M, Kiely, G, Klatt, J, Kutzbach, L, Largeron, C, Laggoun-Défarge, F, Lund, M, Lafleur, PM, Li, X, Mammarella, I, Merbold, L, Nilsson, MB, Olejnik, J, Ottosson-Löfvenius, M, Oechel, W, Parmentier, FJW, Peichl, M, Pirk, N, Peltola, O, Pawlak, W, Rasse, D, Rinne, J, Shaver, G, Peter Schmid, H, Sottocornola, M, Steinbrecher, R, Sachs, T, Urbaniak, M, Zona, D, and Ziemblinska, K

Subjects
Earth Sciences
Abstract

Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 Combining double low line 0.76; Nash-Sutcliffe modeling efficiency, MEF Combining double low line 0.76) and ecosystem respiration (ER, r2 Combining double low line 0.78, MEF Combining double low line 0.75), with lesser accuracy for latent heat fluxes (LE, r2 Combining double low line 0.42, MEF Combining double low line 0.14) and and net ecosystem CO2 exchange (NEE, r2 Combining double low line 0.38, MEF Combining double low line 0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57-0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2

Published
2018

3. The ABCflux database: Arctic-boreal CO2flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems

Author

Virkkala, A., Natali, S., Rogers, B., Watts, J., Savage, K., Connon, S., Mauritz, M., Schuur, E., Peter, D., Minions, C., Nojeim, J., Commane, R., Emmerton, C., Göckede, M., Helbig, M., Holl, D., Iwata, H., Kobayashi, H., Kolari, P., López-Blanco, E., Marushchak, M., Mastepanov, M., Merbold, L., Parmentier, F., Peichl, M., Sachs, T., Sonnentag, O., Ueyama, M., Voigt, C., Aurela, M., Boike, J., Celis, G., Chae, N., Christensen, T., Bret-Harte, M., Dengel, S., Dolman, H., Edgar, C., Elberling, B., Euskirchen, E., Grelle, A., Hatakka, J., Humphreys, E., Järveoja, J., Kotani, A., Kutzbach, L., Laurila, T., Lohila, A., Mammarella, I., Matsuura, Y., Meyer, G., Nilsson, M., Oberbauer, S., Park, S., Petrov, R., Prokushkin, A., Schulze, C., St.Louis, V., Tuittila, E., Tuovinen, J., Quinton, W., Varlagin, A., Zona, D., Zyryanov, V., Earth Sciences, Institute for Atmospheric and Earth System Research (INAR), Micrometeorology and biogeochemical cycles, and Ecosystem processes (INAR Forest Sciences)

Subjects
hiilidioksidi, arktinen alue, maaperä, Climate Research, EDDY COVARIANCE TECHNIQUE, CARBON-DIOXIDE EXCHANGE, SPATIAL VARIABILITY, kausivaihtelut, FOREST, 114 Physical sciences, PERMAFROST CARBON, Physical Geography and Environmental Geoscience, TUNDRA, Atmospheric Sciences, NET, kasvihuonekaasut, Geochemistry, RESPIRATION, Meteorology and Atmospheric Sciences, SDG 13 - Climate Action, STOCKS, päästöt, tutkimusaineisto, CHAMBER
Abstract

Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO2) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO2 fluxes and to better estimate the terrestrial ABZ CO2 budget. ABCflux is openly and freely available online (Virkkala et al., 2021b, https://doi.org/10.3334/ORNLDAAC/1934).

Published
2022

4. Earlier snowmelt may lead to late season declines in plant productivity and carbon sequestration in Arctic tundra ecosystems

Author

Zona, D. (Donatella), Lafleur, P. M. (Peter M.), Hufkens, K. (Koen), Bailey, B. (Barbara), Gioli, B. (Beniamino), Burba, G. (George), Goodrich, J. P. (Jordan P.), Liljedahl, A. K. (Anna K.), Euskirchen, E. S. (Eugénie S.), Watts, J. D. (Jennifer D.), Farina, M. (Mary), Kimball, J. S. (John S.), Heimann, M. (Martin), Göckede, M. (Mathias), Pallandt, M. (Martijn), Christensen, T. R. (Torben R.), Mastepanov, M. (Mikhail), López-Blanco, E. (Efrén), Jackowicz-Korczynski, M. (Marcin), Dolman, A. J. (Albertus J.), Belelli Marchesini, L. (Luca), Commane, R. (Roisin), Wofsy, S. C. (Steven C.), Miller, C. E. (Charles E.), Lipson, D. A. (David A.), Hashemi, J. (Josh), Arndt, K. A. (Kyle A.), Kutzbach, L. (Lars), Holl, D. (David), Boike, J. (Julia), Wille, C. (Christian), Sachs, T. (Torsten), Kalhori, A. (Aram), Song, X. (Xia), Xu, X. (Xiaofeng), Humphreys, E. R. (Elyn R.), Koven, C. D. (Charles D.), Sonnentag, O. (Oliver), Meyer, G. (Gesa), Gosselin, G. H. (Gabriel H.), Marsh, P. (Philip), Oechel, W. C. (Walter C.), Zona, D. (Donatella), Lafleur, P. M. (Peter M.), Hufkens, K. (Koen), Bailey, B. (Barbara), Gioli, B. (Beniamino), Burba, G. (George), Goodrich, J. P. (Jordan P.), Liljedahl, A. K. (Anna K.), Euskirchen, E. S. (Eugénie S.), Watts, J. D. (Jennifer D.), Farina, M. (Mary), Kimball, J. S. (John S.), Heimann, M. (Martin), Göckede, M. (Mathias), Pallandt, M. (Martijn), Christensen, T. R. (Torben R.), Mastepanov, M. (Mikhail), López-Blanco, E. (Efrén), Jackowicz-Korczynski, M. (Marcin), Dolman, A. J. (Albertus J.), Belelli Marchesini, L. (Luca), Commane, R. (Roisin), Wofsy, S. C. (Steven C.), Miller, C. E. (Charles E.), Lipson, D. A. (David A.), Hashemi, J. (Josh), Arndt, K. A. (Kyle A.), Kutzbach, L. (Lars), Holl, D. (David), Boike, J. (Julia), Wille, C. (Christian), Sachs, T. (Torsten), Kalhori, A. (Aram), Song, X. (Xia), Xu, X. (Xiaofeng), Humphreys, E. R. (Elyn R.), Koven, C. D. (Charles D.), Sonnentag, O. (Oliver), Meyer, G. (Gesa), Gosselin, G. H. (Gabriel H.), Marsh, P. (Philip), and Oechel, W. C. (Walter C.)

Abstract

Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO₂ sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO₂ sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO₂ later in the season.

Published
2022

5. The ABCflux database:Arctic–boreal CO₂ flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems

Author

Virkkala, A.-M. (Anna-Maria), Natali, S. M. (Susan M.), Rogers, B. M. (Brendan M.), Watts, J. D. (Jennifer D.), Savage, K. (Kathleen), Connon, S. J. (Sara June), Mauritz, M. (Marguerite), Schuur, E. A. (Edward A. G.), Peter, D. (Darcy), Minions, C. (Christina), Nojeim, J. (Julia), Commane, R. (Roisin), Emmerton, C. A. (Craig A.), Goeckede, M. (Mathias), Helbig, M. (Manuel), Holl, D. (David), Iwata, H. (Hiroki), Kobayashi, H. (Hideki), Kolari, P. (Pasi), López-Blanco, E. (Efrén), Marushchak, M. E. (Maija E.), Mastepanov, M. (Mikhail), Merbold, L. (Lutz), Parmentier, F. W. (Frans-Jan W.), Peichl, M. (Matthias), Sachs, T. (Torsten), Sonnentag, O. (Oliver), Ueyama, M. (Masahito), Voigt, C. (Carolina), Aurela, M. (Mika), Boike, J. (Julia), Celis, G. (Gerardo), Chae, N. (Namyi), Christensen, T. R. (Torben R.), Bret-Harte, M. S. (M. Syndonia), Dengel, S. (Sigrid), Dolman, H. (Han), Edgar, C. W. (Colin W.), Elberling, B. (Bo), Euskirchen, E. (Eugenie), Grelle, A. (Achim), Hatakka, J. (Juha), Humphreys, E. (Elyn), Järveoja, J. (Järvi), Kotani, A. (Ayumi), Kutzbach, L. (Lars), Laurila, T. (Tuomas), Lohila, A. (Annalea), Mammarella, I. (Ivan), Matsuura, Y. (Yojiro), Meyer, G. (Gesa), Nilsson, M. B. (Mats B.), Oberbauer, S. F. (Steven F.), Park, S.-J. (Sang-Jong), Petrov, R. (Roman), Prokushkin, A. S. (Anatoly S.), Schulze, C. (Christopher), St. Louis, V. L. (Vincent L.), Tuittila, E.-S. (Eeva-Stiina), Tuovinen, J.-P. (Juha-Pekka), Quinton, W. (William), Varlagin, A. (Andrej), Zona, D. (Donatella), Zyryanov, V. I. (Viacheslav I.), Virkkala, A.-M. (Anna-Maria), Natali, S. M. (Susan M.), Rogers, B. M. (Brendan M.), Watts, J. D. (Jennifer D.), Savage, K. (Kathleen), Connon, S. J. (Sara June), Mauritz, M. (Marguerite), Schuur, E. A. (Edward A. G.), Peter, D. (Darcy), Minions, C. (Christina), Nojeim, J. (Julia), Commane, R. (Roisin), Emmerton, C. A. (Craig A.), Goeckede, M. (Mathias), Helbig, M. (Manuel), Holl, D. (David), Iwata, H. (Hiroki), Kobayashi, H. (Hideki), Kolari, P. (Pasi), López-Blanco, E. (Efrén), Marushchak, M. E. (Maija E.), Mastepanov, M. (Mikhail), Merbold, L. (Lutz), Parmentier, F. W. (Frans-Jan W.), Peichl, M. (Matthias), Sachs, T. (Torsten), Sonnentag, O. (Oliver), Ueyama, M. (Masahito), Voigt, C. (Carolina), Aurela, M. (Mika), Boike, J. (Julia), Celis, G. (Gerardo), Chae, N. (Namyi), Christensen, T. R. (Torben R.), Bret-Harte, M. S. (M. Syndonia), Dengel, S. (Sigrid), Dolman, H. (Han), Edgar, C. W. (Colin W.), Elberling, B. (Bo), Euskirchen, E. (Eugenie), Grelle, A. (Achim), Hatakka, J. (Juha), Humphreys, E. (Elyn), Järveoja, J. (Järvi), Kotani, A. (Ayumi), Kutzbach, L. (Lars), Laurila, T. (Tuomas), Lohila, A. (Annalea), Mammarella, I. (Ivan), Matsuura, Y. (Yojiro), Meyer, G. (Gesa), Nilsson, M. B. (Mats B.), Oberbauer, S. F. (Steven F.), Park, S.-J. (Sang-Jong), Petrov, R. (Roman), Prokushkin, A. S. (Anatoly S.), Schulze, C. (Christopher), St. Louis, V. L. (Vincent L.), Tuittila, E.-S. (Eeva-Stiina), Tuovinen, J.-P. (Juha-Pekka), Quinton, W. (William), Varlagin, A. (Andrej), Zona, D. (Donatella), and Zyryanov, V. I. (Viacheslav I.)

Abstract

Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO₂) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO₂ fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO₂ exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO₂ fluxes and to better es

Published
2022

6. Harmonized in-situ observations of surface energy fluxes and environmental drivers at 64 Arctic vegetation and glacier sites - Environmental conditions

Author

Oehri, J., Schaepman-Strub, G., Kim, J., Grysko, R., Kropp, H., Grünberg, I., Zemlianskii, V., Sonnentag, O., Euskirchen, E., Reji Chacko, M., Muscari, G., Blanken, P., Dean, J., di Sarra, A., Harding, R., Sobota, I., Kutzbach, L., Plekhanova, E., Riihelä, A., Boike, J., Miller, N., Beringer, J., López-Blanco, E., Stoy, P., Sullivan, R., Kejna, M., Parmentier, F., Gamon, J., Mastepanov, M., Wille, C., Jackowicz-Korczynski, M., Karger, D., Quinton, W., Putkonen, J., van As, D., Christensen, T., Hakuba, M., Stone, R., Metzger, S., Vandecrux, B., Frost, G., Wild, M., Hansen, B., Meloni, D., Domine, F., te Beest, M., Sachs, T., Kalhori, A., Rocha, A., Williamson, S., Morris, S., Atchley, A., Essery, R., Runkle, B., Holl, D., Riihimaki, L., Iwata, H., Schuur, E., Cox, C., Grachev, A., McFadden, J., Fausto, R., Göckede, M., Ueyama, M., Pirk, N., de Boer, G., Bret-Harte, M., Leppäranta, M., Steffen, K., Friborg, T., Ohmura, A., Edgar, C., Olofsson, J., and Chambers, S.

Abstract

Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. This dataset describes the environmental conditions for 64 tundra and glacier sites (>=60°N latitude) across the Arctic, for which in situ measurements of surface energy budget components were harmonized (see Oehri et al. 2022). These environmental conditions are (proxies of) potential drivers of SEB-components and could therefore be called SEB-drivers. The associated environmental conditions, include the vegetation types graminoid tundra, prostrate dwarf-shrub tundra, erect-shrub tundra, wetland complexes, barren complexes (≤ 40% horizontal plant cover), boreal peat bogs and glacier. These land surface types (apart from boreal peat bogs) correspond to the main classification units of the Circumpolar Arctic Vegetation Map (CAVM, Raynolds et al. 2019). For each site, additional climatic and biophysical variables are available, including cloud cover, snow cover duration, permafrost characteristics, climatic conditions and topographic conditions.

Published
2022

7. Lateral and vertical carbon fluxes from the polygonal tundra in the Lena River Delta, Siberia (summer 2014)

Author

Beckebanze, L., Runkle, B., Walz, J., Wille, C., Holl, D., Helbig, M., Boike, J., Sachs, T., and Kutzbach, L.

Abstract

This dataset contains observations of water discharge rates and concentrations of dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) from a polygonal tundra site in the Lena River Delta, Russia. This dataset also contains lateral carbon fluxes of DOC and DIC that were estimated from these observations. Additionally, this dataset contains vertical fluxes of carbon dioxide and methane from the same study site. All observations were recorded on Samoylov Island (N 72.377188, E 126.495144) in the summer of 2014. The abbreviations A1, A2 and B refer to three outflows on the island where the hydrological parameters were observed (A1: N 72.379991, E 126.480886; A2: N 72.380134, E 126.481433; B: N 72.381348, E 126.483482). All outflows were approximately 10 meters. More information can be found in https://doi.org/10.5194/bg-19-3863-2022.

Published
2022

8. Harmonized in-situ observations of surface energy fluxes and environmental drivers at 64 Arctic vegetation and glacier sites - Surface energy budget componenent data

Author

Oehri, J., Schaepman-Strub, G., Kim, J., Grysko, R., Kropp, H., Grünberg, I., Zemlianskii, V., Sonnentag, O., Euskirchen, E., Reji Chacko, M., Muscari, G., Blanken, P., Dean, J., di Sarra, A., Harding, R., Sobota, I., Kutzbach, L., Plekhanova, E., Riihelä, A., Boike, J., Miller, N., Beringer, J., López-Blanco, E., Stoy, P., Sullivan, R., Kejna, M., Parmentier, F., Gamon, J., Mastepanov, M., Wille, C., Jackowicz-Korczynski, M., Karger, D., Quinton, W., Putkonen, J., van As, D., Christensen, T., Hakuba, M., Stone, R., Metzger, S., Vandecrux, B., Frost, G., Wild, M., Hansen, B., Meloni, D., Domine, F., te Beest, M., Sachs, T., Kalhori, A., Rocha, A., Williamson, S., Morris, S., Atchley, A., Essery, R., Runkle, B., Holl, D., Riihimaki, L., Iwata, H., Schuur, E., Cox, C., Grachev, A., McFadden, J., Fausto, R., Göckede, M., Ueyama, M., Pirk, N., de Boer, G., Bret-Harte, M., Leppäranta, M., Steffen, K., Friborg, T., Ohmura, A., Edgar, C., Olofsson, J., and Chambers, S.

Abstract

Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. This dataset comprises harmonized, standardized and aggregated in-situ observations of surface energy budget components measured at 64 sites on vegetated and glaciated sites north of 60° latitude, in the time period from 1994 till 2021. The surface energy budget components include net radiation, sensible heat flux, latent heat flux, ground heat flux, net shortwave radiation, net longwave radiation, surface temperature and albedo, which were aggregated to daily mean, minimum and maximum values from hourly and half-hourly measurements. Data were retrieved from the monitoring networks FLUXNET, AmeriFlux, AON, GC-Net and PROMICE.

Published
2022

9. Literature synthesis data of surface energy fluxes and environmental drivers from Arctic vegetation and glacier sites

Author

Oehri, J., Schaepman-Strub, G., Kim, J., Grysko, R., Kropp, H., Grünberg, I., Zemlianskii, V., Sonnentag, O., Euskirchen, E., Reji Chacko, M., Muscari, G., Blanken, P., Dean, J., di Sarra, A., Harding, R., Sobota, I., Kutzbach, L., Plekhanova, E., Riihelä, A., Boike, J., Miller, N., Beringer, J., López-Blanco, E., Stoy, P., Sullivan, R., Kejna, M., Parmentier, F., Gamon, J., Mastepanov, M., Wille, C., Jackowicz-Korczynski, M., Karger, D., Quinton, W., Putkonen, J., van As, D., Christensen, T., Hakuba, M., Stone, R., Metzger, S., Vandecrux, B., Frost, G., Wild, M., Hansen, B., Meloni, D., Domine, F., te Beest, M., Sachs, T., Kalhori, A., Rocha, A., Williamson, S., Morris, S., Atchley, A., Essery, R., Runkle, B., Holl, D., Riihimaki, L., Iwata, H., Schuur, E., Cox, C., Grachev, A., McFadden, J., Fausto, R., Göckede, M., Ueyama, M., Pirk, N., de Boer, G., Bret-Harte, M., Leppäranta, M., Steffen, K., Friborg, T., Ohmura, A., Edgar, C., Olofsson, J., and Chambers, S.

Abstract

Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. This dataset describes the data generated in a literature synthesis, covering 358 study sites on vegetation or glacier (>=60°N latitude), which contained surface energy budget observations. The literature synthesis comprised 148 publications searched on the ISI Web of Science Core Collection.

Published
2022

10. Harmonized in-situ observations of surface energy fluxes and environmental drivers at 64 Arctic vegetation and glacier sites

Author

Oehri, J., Schaepman-Strub, G., Kim, J., Grysko, R., Kropp, H., Grünberg, I., Zemlianskii, V., Sonnentag, O., Euskirchen, E., Reji Chacko, M., Muscari, G., Blanken, P., Dean, J., di Sarra, A., Harding, R., Sobota, I., Kutzbach, L., Plekhanova, E., Riihelä, A., Boike, J., Miller, N., Beringer, J., López-Blanco, E., Stoy, P., Sullivan, R., Kejna, M., Parmentier, F., Gamon, J., Mastepanov, M., Wille, C., Jackowicz-Korczynski, M., Karger, D., Quinton, W., Putkonen, J., van As, D., Christensen, T., Hakuba, M., Stone, R., Metzger, S., Vandecrux, B., Frost, G., Wild, M., Hansen, B., Meloni, D., Domine, F., te Beest, M., Sachs, T., Kalhori, A., Rocha, A., Williamson, S., Morris, S., Atchley, A., Essery, R., Runkle, B., Holl, D., Riihimaki, L., Iwata, H., Schuur, E., Cox, C., Grachev, A., McFadden, J., Fausto, R., Göckede, M., Ueyama, M., Pirk, N., de Boer, G., Bret-Harte, M., Leppäranta, M., Steffen, K., Friborg, T., Ohmura, A., Edgar, C., Olofsson, J., and Chambers, S.

Abstract

Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In-situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. Therefore, we here provide four datasets comprising: 1. Harmonized, standardized and aggregated in situ observations of SEB components at 64 vegetated and glaciated sites north of 60° latitude, in the time period 1994-2021 2. A description of all study sites and associated environmental conditions, including the vegetation types, which correspond to the classification of the Circumpolar Arctic Vegetation Map (CAVM, Raynolds et al. 2019). 3. Data generated in a literature synthesis from 358 study sites on vegetation or glacier (>=60°N latitude) covered by 148 publications. 4. Metadata, including data contributor information and measurement heights of variables associated with Oehri et al. 2022.

Published
2022

11. The ABCflux Database: Arctic-Boreal CO2 Flux and Site Environmental Data, 1989-2020

Author

Virkkala, A., Natali, S., Rogers, B., Watts, J., Savage, K., Connon, S., Mauritz-tozer, M., Schuur, E., Peter, D., Minions, C., Nojeim, J., Commane, R., Emmerton, C., Goeckede, M., Helbig, M., Holl, D., Iwata, H., Kobayashi, H., Kolari, P., Lopez-blanco, E., Marushchak, M., Mastepanov, M., Merbold, L., Peichl, M., Sonnentag, O., Sachs, T., Ueyama, M., Voigt, C., Aurela, M., Boike, J., Celis, G., Chae, N., Christensen, T., Bret-Harte, S., Dengel, S., Dolman, H., Edgar, C., Elberling, B., Euskirchen, S., Grelle, A., Hatakka, J., Humphreys, E., Jaerveoja, J., Kotani, A., Kutzbach, L., Laurila, T., Lohila, A., Mammarella, I., Matsuura, Y., Meyer, G., Nilsson, M., Oberbauer, S., Park, S., Parmentier, F., Petrov, R., Prokushkin, A., Zyrianov, S., Schulze, C., St.louis, V., Tuittila, E., Tuovinen, J., Quinton, W., Varlagin, A., Zona, D., and Zyryanov, V.

Abstract

This Arctic-Boreal CO2 fluxes (ABCflux) dataset contains monthly aggregates of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity (GPP) and ecosystem respiration. Over 70 supporting variables describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. The data contained in this ABCflux dataset form a standardized monthly database of Arctic-Boreal CO2 fluxes (i.e., ABCflux Database) and include 244 sites and 6,309 monthly observations; 136 sites and 2,217 monthly observations represent tundra, and 108 sites and 4,092 observations represent the boreal biome. The data are for the period 1989 to 2020.

Published
2021

12. Are Remote Sensing Evapotranspiration Models Reliable Across South American Ecoregions?

Author

Melo, D. C. D., primary, Anache, J. A. A., additional, Borges, V. P., additional, Miralles, D. G., additional, Martens, B., additional, Fisher, J. B., additional, Nóbrega, R. L. B., additional, Moreno, A., additional, Cabral, O. M. R., additional, Rodrigues, T. R., additional, Bezerra, B., additional, Silva, C. M. S., additional, Neto, A. A. Meira, additional, Moura, M. S. B., additional, Marques, T. V., additional, Campos, S., additional, Nogueira, J. S., additional, Rosolem, R., additional, Souza, R. M. S., additional, Antonino, A. C. D., additional, Holl, D., additional, Galleguillos, M., additional, Perez‐Quezada, J. F., additional, Verhoef, A., additional, Kutzbach, L., additional, Lima, J. R. S., additional, Souza, E. S., additional, Gassman, M. I., additional, Perez, C. F., additional, Tonti, N., additional, Posse, G., additional, Rains, D., additional, Oliveira, P. T. S., additional, and Wendland, E., additional

Published
2021
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17. Systematic review of current randomised control trials in chronic subdural haematoma and proposal for an international collaborative approach

Author

Edlmann, E., Holl, D. C., Lingsma, H. F., Bartek, J., Bartley, A., Duerinck, J., Jensen, T. S. R., Soleman, J., Shanbhag, N. C., Devi, B. Indira, Laeke, T., Rubiano, A. M., Fugleholm, K., van der Veken, J., Tisell, M., Hutchinson, P. J., Dammers, R., Kolias, A. G., Edlmann, E., Holl, D. C., Lingsma, H. F., Bartek, J., Bartley, A., Duerinck, J., Jensen, T. S. R., Soleman, J., Shanbhag, N. C., Devi, B. Indira, Laeke, T., Rubiano, A. M., Fugleholm, K., van der Veken, J., Tisell, M., Hutchinson, P. J., Dammers, R., and Kolias, A. G.

Abstract

Background Chronic subdural haematoma (CSDH) is a pathology that is frequently encountered by neurosurgeons. Nevertheless, there is a lack of guidelines based on solid evidence. There has been a recent and considerable increase in the interest on management and outcomes for CSDH. Therefore, we systematically reviewed all currently running randomised controlled trials (RCTs) in chronic subdural haematoma to understand the areas under investigation and plan future collaborative trials. Methods Clinical trials databases (Cochrane Controlled Register of Trials, WHO ICTRP and clinical ) were searched for trials relevant to chronic subdural haematoma. It was then established which trials were currently running and fulfilled robust research methodology for a RCT. Results There are 26 currently running RCTs in CSDH, with the most common topics covering application of steroids (7), surgical techniques (5) and tranexamic acid (5). Further to this, there are trials running on other pharmacological agents (4), middle meningeal artery (MMA) embolisation (2) and peri-operative management (3). Conclusions Pharmacological agents are a particular focus of CSDH management currently, and a wealth of studies on steroids will hopefully lead to more harmonised, evidence-based practice regarding this in the near future. Surgical techniques and new procedures such as MMA embolisation are also important focuses for improving patient outcomes. There is an on-going need for future RCTs and evidence-based guidelines in CSDH, particularly including low- and middle-income countries, and it is hoped that the establishment of the iCORIC (International COllaborative Research Initiative on Chronic Subdural Haematoma) will help address this.

Published
2020

18. Safety and Environmental Activities for ITER

Author

Saji, G., Aymar, R., Bartels, H.-W., Gordon, C. W., Gulden, W., Holl, D. H., Iida, H., Inabe, T., Iseli, M., Kashirski, A. V., Kolbasov, B. N., Krivosheev, M., McCarthy, K. A., Marbach, G., Morozov, S. I., Natalizio, A., Petti, D. A., Piet, S. J., Poucet, A. E., Raeder, J., Seki, Y., and Topilski, L. N.

Published
1997
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19. A long-term (2002 to 2017) record of closed-path and open-path eddy covariance CO2 net ecosystem exchange fluxes from the Siberian Arctic

Author

Holl, D., Wille, C., Sachs, T., Schreiber, P., Runkle, B., Beckebanze, L., Langer, M., Boike, J., Pfeiffer, E., Fedorova, I., Bolshianov, D., Grigoriev, M., Kutzbach, L., and Earth and Climate

Abstract

Ground-based observations of land-atmosphere fluxes are necessary to progressively improve global climate models. Observed data can be used for model evaluation and to develop or tune process models. In arctic permafrost regions, climate-carbon feedbacks are amplified. Therefore, increased efforts to better represent these regions in global climate models have been made in recent years. We present a multi-annual time series of land-atmosphere carbon dioxide fluxes measured in situ with the eddy covariance technique in the Siberian Arctic (72'22° N, 126'30° E). The site is part of the international network of eddy covariance flux observation stations (FLUXNET; site ID: Ru-Sam). The data set includes consistently processed fluxes based on concentration measurements of closed-path and open-path gas analyzers. With parallel records from both sensor types, we were able to apply a site-specific correction to open-path fluxes. This correction is necessary due to a deterioration of data, caused by heat generated by the electronics of open-path gas analyzers. Parameterizing this correction for subperiods of distinct sensor setups yielded good agreement between open- and closed-path fluxes. We compiled a long-term (2002 to 2017) carbon dioxide flux time series that we additionally gap-filled with a standardized approach. The data set was uploaded to the Pangaea database and can be accessed through https://doi.org/10.1594/PANGAEA.892751.

Published
2019

20. The evolution and genetic diversity of avian influenza A(H9N2) viruses in Cambodia, 2015-2016

Author

Russell, CJ, Suttie, A, Tok, S, Yann, S, Keo, P, Horm, SV, Roe, M, Kaye, M, Sorn, S, Holl, D, Tum, S, Barr, IG, Hurt, AC, Greenhill, AR, Karlsson, EA, Vijaykrishna, D, Deng, Y-M, Dussart, P, Horwood, PF, Russell, CJ, Suttie, A, Tok, S, Yann, S, Keo, P, Horm, SV, Roe, M, Kaye, M, Sorn, S, Holl, D, Tum, S, Barr, IG, Hurt, AC, Greenhill, AR, Karlsson, EA, Vijaykrishna, D, Deng, Y-M, Dussart, P, and Horwood, PF

Abstract

Low pathogenic A(H9N2) subtype avian influenza viruses (AIVs) were originally detected in Cambodian poultry in 2013, and now circulate endemically. We sequenced and characterised 64 A(H9N2) AIVs detected in Cambodian poultry (chickens and ducks) from January 2015 to May 2016. All A(H9) viruses collected in 2015 and 2016 belonged to a new BJ/94-like h9-4.2.5 sub-lineage that emerged in the region during or after 2013, and was distinct to previously detected Cambodian viruses. Overall, there was a reduction of genetic diversity of H9N2 since 2013, however two genotypes were detected in circulation, P and V, with extensive reassortment between the viruses. Phylogenetic analysis showed a close relationship between A(H9N2) AIVs detected in Cambodian and Vietnamese poultry, highlighting cross-border trade/movement of live, domestic poultry between the countries. Wild birds may also play a role in A(H9N2) transmission in the region. Some genes of the Cambodian isolates frequently clustered with zoonotic A(H7N9), A(H9N2) and A(H10N8) viruses, suggesting a common ecology. Molecular analysis showed 100% of viruses contained the hemagglutinin (HA) Q226L substitution, which favours mammalian receptor type binding. All viruses were susceptible to the neuraminidase inhibitor antivirals; however, 41% contained the matrix (M2) S31N substitution associated with resistance to adamantanes. Overall, Cambodian A(H9N2) viruses possessed factors known to increase zoonotic potential, and therefore their evolution should be continually monitored.

Published
2019

23. ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales

Author

Qiu, C., Zhu, D., Ciais, P., Guenet, B., Krinner, G., Peng, S., Aurela, M., Bernhofer, C., Bruemmer, C., Bret-Harte, S., Chu, H., Chen, J., Desai, A.R., Dusek, J., Euskirchen, E.S., Fortuniak, K., Flanagan, L.B., Friborg, T., Grygoruk, M., Gogo, S., Gruenwald, T., Hansen, B.U., Holl, D., Humphreys, E., Hurkuck, M., Kiely, G., Klatt, J., Kutzbach, L., Largeron, C., Laggoun-Defarge, F., Lund, M., Lafleur, P.M., Li, X., Mammarella, I., Merbold, L., Nilsson, M.B., Olejnik, J., Ottosson-Lofvenius, M., Oechel, W., Parmentier, F.-J.W., Peichl, M., Pirk, N., Peltola, O., Pawlak, W., Rasse, D., Rinne, J., Shaver, G., Schmid, H.P., Sottocornola, M., Steinbrecher, R., Sachs, T., Urbaniak, M., Zona, D., Ziemblinska, K., Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), MOSAIC (MOSAIC), Institut FRESNEL (FRESNEL), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), Institut des Géosciences de l’Environnement [2017-2019] (IGE [2017-2019]), Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), Department of Ecology, College of Urban and Environmental Sciences, Peking University [Beijing], Climate and Global Change Research [Helsinki], Finnish Meteorological Institute (FMI), Institute of Hydrology and Meteorology [Dresden], Technische Universität Dresden (TUD), Thünen Institute of Climate-Smart Agriculture, Institute of Arctic Biology, University of Alaska [Anchorage], Department of Environmental Science, Policy, and Management [Berkeley] (ESPM), University of California [Berkeley], University of California-University of California, Center for Global Change and Earth Observations, Michigan State University [East Lansing], Michigan State University System-Michigan State University System, Department of Atmospheric and Oceanic Sciences [Madison], University of Wisconsin-Madison, Department of Matters and Energy Fluxes, Czech Academy of Sciences [Prague] (ASCR), Department of Meteorology and Climatology [Łódz ́], University of Lódź, University of Lethbridge, Department of Geosciences and Natural Resource Management [Copenhagen] (IGN), Faculty of Science [Copenhagen], University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU), Warsaw University of Life Sciences (SGGW), Institut des Sciences de la Terre d'Orléans - UMR7327 (ISTO), Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS), Biogéosystèmes Continentaux - UMR7327, PSL Research University (PSL)-PSL Research University (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Observatoire des Sciences de l'Univers en région Centre (OSUC), University of Hamburg, Carleton University, Department of Civil and Environmental Engineering [Cork], University College Cork (UCC), Karlsruhe Institute of Technology (KIT), Department of Bioscience and Arctic Research Center, Aarhus University [Aarhus], School of the Environment – Geography, Trent University, Department of Physics [Helsinki], Falculty of Science [Helsinki], University of Helsinki-University of Helsinki, Institute of Agricultural Sciences, Ecole Polytechnique Fédérale de Zurich, Department of Forest Ecology and Management, Swedish University of Agricultural Sciences (SLU), Department of Meteorology, Faculty of Wood Technology, Poznan' University of Life Sciences, Poznan University of Life Sciences-Poznan University of Life Sciences, Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), German Research Centre for Geosciences - Helmholtz-Centre Potsdam (GFZ), PIVOTS project of the Région Centre – Val de Loire (ARD 2020 program and CPER 2015–2020)., ANR-10-LABX-100-01/10-LABX-0100,VOLTAIRE,Geofluids and Volatil elements – Earth, Atmosphere, Interfaces – Resources and Environment(2010), European Project: 610028,EC:FP7:ERC,ERC-2013-SyG,IMBALANCE-P(2014), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Technische Universität Dresden = Dresden University of Technology (TU Dresden), University of Alaska [Fairbanks] (UAF), University of California [Berkeley] (UC Berkeley), University of California (UC)-University of California (UC), Czech Academy of Sciences [Prague] (CAS), University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki, ANR-10-LABX-0100,VOLTAIRE,Geofluids and Volatil elements – Earth, Atmosphere, Interfaces – Resources and Environment(2010), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut de Recherche pour le Développement (IRD)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Department of Physics, and Micrometeorology and biogeochemical cycles

Subjects
1171 Geosciences, VDP::Mathematics and natural science: 400::Geosciences: 450, VDP::Landbruks- og Fiskerifag: 900, CARBON-DIOXIDE EXCHANGE, HYDRAULIC CONDUCTIVITY, Peatlands, 114 Physical sciences, Carbon, LAST GLACIAL MAXIMUM, ECOSYSTEM RESPIRATION, CHANGING CLIMATE CONDITIONS, [SDU]Sciences of the Universe [physics], LAND-SURFACE MODEL, ddc:550, NET PRIMARY PRODUCTION, TEMPERATE BOG, Earth Sciences, VDP::Matematikk og Naturvitenskap: 400::Geofag: 450, Hydrology, INTERANNUAL VARIABILITY, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, LITTER DECOMPOSITION RATES
Abstract

Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 = 0.76; Nash–Sutcliffe modeling efficiency, MEF = 0.76) and ecosystem respiration (ER, r2 = 0.78, MEF = 0.75), with lesser accuracy for latent heat fluxes (LE, r2 = 0.42, MEF = 0.14) and and net ecosystem CO2 exchange (NEE, r2 = 0.38, MEF = 0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.

Published
2018

24. ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales

Author

Qiu, C. (Chunjing), Zhu, D. (Dan), Ciais, P. (Philippe), Guenet, B. (Bertrand), Krinner, G. (Gerhard), Peng, S. (Shushi), Aurela, M. (Mika), Bernhofer, C. (Christian), Brümmer, C. (Christian), Bret-Harte, S. (Syndonia), Chu, H. (Housen), Chen, J. (Jiquan), Desai, A.R. (Ankur R.), Dušek, J. (Jǐrí), Euskirchen, E.S. (Eugénie S.), Fortuniak, K. (Krzysztof), Flanagan, L.B. (Lawrence B.), Friborg, T. (Thomas), Grygoruk, M. (Mateusz), Gogo, S. (Sébastien), Grünwald, T. (Thomas), Hansen, B.U. (Birger U.), Holl, D. (David), Humphreys, E. (Elyn), Hurkuck, M. (Miriam), Kiely, G. (Gerard), Klatt, J. (Janina), Kutzbach, L. (Lars), Largeron, C. (Chloé), Laggoun-Défarge, F. (Fatima), Lund, M. (Magnus), Lafleur, P.M. (Peter M.), Li, X. (Xuefei), Mammarella, I. (Ivan), Merbold, L. (Lutz), Nilsson, M.B. (Mats B.), Olejnik, J. (Janusz), Ottosson-Löfvenius, M. (Mikaell), Oechel, W. (Walter), Parmentier, F.-J.W. (Frans-Jan W.), Peichl, M. (Matthias), Pirk, N. (Norbert), Peltola, O. (Olli), Pawlak, W. (Włodzimierz), Rasse, D. (Daniel), Rinne, J. (Janne), Shaver, G. (Gaius), Peter Schmid, H. (Hans), Sottocornola, M. (Matteo), Steinbrecher, R. (Rainer), Sachs, T. (Torsten), Urbaniak, M. (Marek), Zona, D. (Donatella), Ziemblinska, K. (Klaudia), Qiu, C. (Chunjing), Zhu, D. (Dan), Ciais, P. (Philippe), Guenet, B. (Bertrand), Krinner, G. (Gerhard), Peng, S. (Shushi), Aurela, M. (Mika), Bernhofer, C. (Christian), Brümmer, C. (Christian), Bret-Harte, S. (Syndonia), Chu, H. (Housen), Chen, J. (Jiquan), Desai, A.R. (Ankur R.), Dušek, J. (Jǐrí), Euskirchen, E.S. (Eugénie S.), Fortuniak, K. (Krzysztof), Flanagan, L.B. (Lawrence B.), Friborg, T. (Thomas), Grygoruk, M. (Mateusz), Gogo, S. (Sébastien), Grünwald, T. (Thomas), Hansen, B.U. (Birger U.), Holl, D. (David), Humphreys, E. (Elyn), Hurkuck, M. (Miriam), Kiely, G. (Gerard), Klatt, J. (Janina), Kutzbach, L. (Lars), Largeron, C. (Chloé), Laggoun-Défarge, F. (Fatima), Lund, M. (Magnus), Lafleur, P.M. (Peter M.), Li, X. (Xuefei), Mammarella, I. (Ivan), Merbold, L. (Lutz), Nilsson, M.B. (Mats B.), Olejnik, J. (Janusz), Ottosson-Löfvenius, M. (Mikaell), Oechel, W. (Walter), Parmentier, F.-J.W. (Frans-Jan W.), Peichl, M. (Matthias), Pirk, N. (Norbert), Peltola, O. (Olli), Pawlak, W. (Włodzimierz), Rasse, D. (Daniel), Rinne, J. (Janne), Shaver, G. (Gaius), Peter Schmid, H. (Hans), Sottocornola, M. (Matteo), Steinbrecher, R. (Rainer), Sachs, T. (Torsten), Urbaniak, M. (Marek), Zona, D. (Donatella), and Ziemblinska, K. (Klaudia)

Abstract

Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a g

Published
2018
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25. Zu germ. *ē¹ im Präteritum der germanischen starken Verben

Author

Sonnenhauser, Barbara, Trautmann, Caroline, Holl, Daniel, Noel Aziz, Hanna Patrizia, Sonnenhauser, B ( Barbara ), Trautmann, C ( Caroline ), Holl, D ( Daniel ), Noel Aziz, H P ( Hanna Patrizia ), Mächler, Patrick, Sonnenhauser, Barbara, Trautmann, Caroline, Holl, Daniel, Noel Aziz, Hanna Patrizia, Sonnenhauser, B ( Barbara ), Trautmann, C ( Caroline ), Holl, D ( Daniel ), Noel Aziz, H P ( Hanna Patrizia ), and Mächler, Patrick

Published
2017

28. Serologic evidence of human influenza virus infections in swine populations, Cambodia

Author

Rith, S., Netrabukkana, P., Sorn, S., Mumford, E., Mey, C., Holl, D., Goutard, F., Y, B., Fenwick, S., Robertson, I., Roger, F., Buchy, P., Rith, S., Netrabukkana, P., Sorn, S., Mumford, E., Mey, C., Holl, D., Goutard, F., Y, B., Fenwick, S., Robertson, I., Roger, F., and Buchy, P.

Abstract

Background: This study was conducted from 2006 to 2010 and investigated the seroprevalence of influenza A viruses in Cambodian pigs, including human H1N1, H3N2, 2009 pandemic H1N1 (A(H1N1)pdm09), and highly pathogenic avian H5N1 influenza A viruses. Methods: A total of 1147 sera obtained from pigs in Cambodia were tested by haemagglutination inhibition (HI) assays for antibody to human influenza A viruses along with both HI and microneutralization (MN) tests to assess immunological responses to H5N1 virus. The results were compared by year, age, and province. Results: Antibodies against a human influenza A virus were detected in 14·9% of samples. A(H1N1)pdm09 virus were dominant over the study period (23·1%), followed by those to human H1N1 (17·3%) and H3N2 subtypes (9·9%). No pigs were serologically positive for avian H5 influenza viruses. The seroprevalence of human H1N1 and H3N2 influenza viruses peaked in 2008, while that of A(H1N1)pdm09 reached a peak in 2010. No significant differences in seroprevalence to human influenza subtypes were observed in different age groups. Conclusions: Cambodian pigs were exposed to human strains of influenza A viruses either prior to or during this study. The implications of these high prevalence rates imply human-to-swine influenza virus transmission in Cambodia. Although pigs are mostly raised in small non-commercial farms, our preliminary results provide evidence of sustained human influenza virus circulation in pig populations in Cambodia.

Published
2013

29. Molecular epidemiology of clade 1 influenza A viruses (H5N1), southern Indochina Peninsula, 2004-2007

Author

Buchy, P, Fourment, M, Mardy, S, Sorn, S, Holl, D, Ly, S, Vong, S, Enouf, V, Peiris, JSM, Van Der Werf, S, Buchy, P, Fourment, M, Mardy, S, Sorn, S, Holl, D, Ly, S, Vong, S, Enouf, V, Peiris, JSM, and Van Der Werf, S

Abstract

To determine the origin of influenza A virus (H5N1) epizootics in Cambodia, we used maximum-likelihood and Bayesian methods to analyze the genetic sequences of subtype H5N1 strains from Cambodia and neighboring areas. Poultry movements, rather than repeated reintroduction of subtype H5N1 viruses by wild birds, appear to explain virus circulation and perpetuation.

Published
2009

31. Molecular epidemiology of clade 1 influenza A viruses (H5N1), southern Indochina peninsula, 2004-2007.

Author

Buchy P, Fourment M, Mardy S, Sorn S, Holl D, Ly S, Vong S, Enouf V, Peiris JS, van der Werf S, Buchy, Philippe, Fourment, Mathieu, Mardy, Sek, Sorn, San, Holl, Davun, Ly, Sowath, Vong, Sirenda, Enouf, Vincent, Peiris, J S Malik, and van der Werf, Silvie

Abstract

To determine the origin of influenza A virus (H5N1) epizootics in Cambodia, we used maximum-likelihood and Bayesian methods to analyze the genetic sequences of subtype H5N1 strains from Cambodia and neighboring areas. Poultry movements, rather than repeated reintroduction of subtype H5N1 viruses by wild birds, appear to explain virus circulation and perpetuation. [ABSTRACT FROM AUTHOR]

Published
2009
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32. Risk factors associated with subclinical human infection with avian influenza A (H5N1) virus--Cambodia, 2006.

Author

Vong S, Ly S, Van Kerkhove MD, Achenbach J, Holl D, Buchy P, Sorn S, Seng H, Uyeki TM, Sok T, and Katz JM

Abstract

BACKGROUND: We conducted investigations in 2 villages in Cambodia where outbreaks of influenza H5N1 occurred among humans and poultry to determine the frequency of and risk factors for H5N1 virus transmission. METHODS: During May 2006, approximately 7 weeks after outbreaks of influenza H5N1 among poultry occurred, villagers living near households of 2 patients with influenza H5N1 were interviewed about potential H5N1 exposures and had blood samples obtained for H5N1 serological testing by microneutralization assay. A seropositive result was defined as an influenza H5N1 neutralizing antibody titer of 1:80, with confirmation by Western blot assay. A case-control study was conducted to identify risk factors for influenza H5N1 virus infection. Control subjects, who had seronegative results of tests, were matched with H5N1-seropositive persons by village residence, households with an influenza H5N1-infected poultry flock, sex, and age. RESULTS: Seven (1.0%) of 674 villagers tested seropositive for influenza H5N1 antibodies and did not report severe illness; 6 (85.7%) were male. The 7 H5N1-seropositive persons, all of whom were aged

Published
2009
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37. Environmental contamination during influenza A virus (H5N1) outbreaks, Cambodia, 2006.

Author

Vong S, Ly S, Mardy S, Holl D, Buchy P, Vong, Sirenda, Ly, Sowath, Mardy, Sek, Holl, Davun, and Buchy, Philippe

Abstract

To determine potential risk for bird-to-human transmission during influenza A virus (H5N1) outbreaks among backyard poultry in rural Cambodia, we collected environmental specimens. Viral RNA was detected in 27 (35%) of 77 specimens of mud, pond water, water plants, and soil swabs. Our results underscore the need for regular disinfection of poultry areas. [ABSTRACT FROM AUTHOR]

Published
2008
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38. Analysis of Plate Examples by Difference Methods and the Superposition Principle

Author

Holl, D. L.

Abstract

In this paper the author applies the membrane analogs of H. Marcus to some elementary cases of thin homogeneous isotropic square plates having central-point loads and various boundary conditions. The analogy is made possible by two theorems: (a) The deflection of a membrane loaded with loads proportional to those on a given plate may be considered as the sum of the principal moments of the actual plate. (b) A second membrane may be loaded with elastic weights proportional to these moment sums and, subject to appropriate boundary conditions, the deflections of the latter membrane will be proportional to the deflections of the actual plate under the given loading system. The principle of superposition of deflection surfaces or equivalent stress systems is utilized in this paper both by difference and differential methods. The problems treated are (1) a square plate with pinned or simply supported edges, (2) two opposite edges pinned and the other two free, (3) two opposite edges pinned and the other two clamped, (4) all four edges clamped, (5) all four edges free with only corner post supports. The correct critical stress at the center of the lower surface of the plate was obtained from special thick-plate theory for a particular thickness-to-span ratio. The effect of this critical stress on the whole plate action is depicted for various boundary conditions.

Published
1936
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41. Strength of Materials.

Author

Holl, D. L., Hedrick, Earle R., Curtiss, David R., and Longley, William.

Published
1930

42. HPAI surveillance programme in Cambodia: Results and perspectives

Author

Desvaux, S., Sorn, S., Holl, D., Chavernac, D., flavie luce goutard, Thonnat, J., Porphyre, V., Ménard, C., Cardinale, E., and Roger, F.

Subjects
L73 - Maladies des animaux
Abstract

Cambodia has faced 15 confirmed highly pathogenic avian influenza (H5N1) outbreaks in different sectors of the poultry industry since January 2004. The country has very limited human and financial resources and, when the outbreak first began, the veterinary services were not equipped with the basic tools to collect accurate epidemiological information or to fight the disease. Therefore, different agencies, under the umbrella of the Food and Agriculture Organisation, are providing support to the Government to strengthen its capacity to diagnose, survey and control the avian influenza (Al) virus. Different surveillance tools are being tested, such as market monitoring and a sentinel villages' network, to offset the weakness of the national passive surveillance network. Several constraints were identified during the implementation of this programme, such as a lack of motivation among provincial staff, the limited capacity of the central team to compile and analyse the data generated, the reluctance of farmers to have their animals sampled, and weak diagnostic capacities. The sustainability of such a surveillance system once international support ends remains to be seen. Participatory epidemiology (PE) may be an appropriate complementary tool to track diseases. PE works on the principle that livestock keepers often possess detailed knowledge of animal diseases and can provide valuable diagnostics that could help in identifying AI outbreaks, particularly in remote areas.

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