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8. sPlotOpen – An environmentally balanced, open‐access, global dataset of vegetation plots

Author

Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jimenez‐Alfaro, B., Kattge, J., Levesley, A., Pillar, V.D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A.T.R., Agrillo, E., Álvarez, M., Apostolova, I., Arfin Khan, M.A.S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., Gasper, A.L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El‐Sheikh, M.A.El‐R.M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán‐de‐Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I.G., Grytnes, J‐A, Guerin, G.R., Gutiérrez, A.G., Haider, S., Hatim, M.Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J.A.M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D.N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H.S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D.V., Liu, H., Lysenko, T., Mahecha, M.D., Marcenò, C., Martynenko, V., Moeslund, J.E., Monteagudo Mendoza, A., Mucina, L., Müller, J.V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Pärtel, M., Pauchard, A., Peet, R.K., Penuelas, J., Pérez‐Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas‐Torres, G., Rodwell, J.S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Ž., Sparrow, B., Sperandii, M.G., Stančić, Z., Svenning, J‐C, Tang, Z., Tang, C.Q., Tsiripidis, I., Vanselow, K.A., Vásquez Martínez, R., Vassilev, K., Vélez‐Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., Wehrden, H., Wagner, V., Walker, D.A., Waller, D.M., Wang, H‐F, Wesche, K., Whitfeld, T.J.S., Willner, W., Wiser, S.K., Wohlgemuth, T., Yamalov, S., Zobel, M., Bruelheide, H., Bates, A., Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jimenez‐Alfaro, B., Kattge, J., Levesley, A., Pillar, V.D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A.T.R., Agrillo, E., Álvarez, M., Apostolova, I., Arfin Khan, M.A.S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., Gasper, A.L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El‐Sheikh, M.A.El‐R.M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán‐de‐Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I.G., Grytnes, J‐A, Guerin, G.R., Gutiérrez, A.G., Haider, S., Hatim, M.Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J.A.M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D.N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H.S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D.V., Liu, H., Lysenko, T., Mahecha, M.D., Marcenò, C., Martynenko, V., Moeslund, J.E., Monteagudo Mendoza, A., Mucina, L., Müller, J.V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Pärtel, M., Pauchard, A., Peet, R.K., Penuelas, J., Pérez‐Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas‐Torres, G., Rodwell, J.S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Ž., Sparrow, B., Sperandii, M.G., Stančić, Z., Svenning, J‐C, Tang, Z., Tang, C.Q., Tsiripidis, I., Vanselow, K.A., Vásquez Martínez, R., Vassilev, K., Vélez‐Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., Wehrden, H., Wagner, V., Walker, D.A., Waller, D.M., Wang, H‐F, Wesche, K., Whitfeld, T.J.S., Willner, W., Wiser, S.K., Wohlgemuth, T., Yamalov, S., Zobel, M., Bruelheide, H., and Bates, A.

Abstract

Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring.

Published
2021

9. Flow cytometric assays for car t cell manufacturing and patient monitoring, involving specific car detection reagents, stabilized pre-mixed cocktails, and automated data acquisition and analysis

Author

Mues, M., primary, Winkels, M., additional, Lange, K., additional, Stiem, L., additional, Janz, E., additional, Biedermann, S., additional, Niemöller, M., additional, Missing, D., additional, Jürgens, N., additional, Holzer, T., additional, Dose, C., additional, Siewert, C., additional, and Richter, A., additional

Published
2021
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10. Flow cytometric assays for CAR T cell manufacturing and patient immunomonitoring, comprising specific CAR detection reagents, stabilized pre-mixed cocktails, and automated data acquisition and analysis

Author

Mues, M., primary, Winkels, M., additional, Lange, K., additional, Stiem, L., additional, Janz, E., additional, Biedermann, S., additional, Niemöller, M., additional, Missing, D., additional, Jürgens, N., additional, Holzer, T., additional, Dose, C., additional, Siewert, C., additional, and Richter, A., additional

Published
2020
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13. sPlot – A new tool for global vegetation analyses

Author

Bruelheide, H., Dengler, J., Jiménez Alfaro, Borja, Purschke, Oliver, Hennekens, S.M., Chytrý, M., Pillar, V.D., Jansen, F., Kattge, Jens, Sandel, B., Aubin, I., Beckmann, M., Berg, Christian, Fagúndez, J., Levesley, A., Bergeron, Y., Bergmeier, E., De Bie, E., Nobis, M., Kuzemko, A., Kącki, Z., Marcenò, Corrado, Byun, C., Işık Gürsoy, D., Li, C.-F., Cabido, M.R., Hatim, M.Z., Moeslund, J.E., Casella, L., Cayuela, Luis, Finckh, Manfred, Petřík, P., Martynenko, V., Kozhevnikova, M., Liu, H., Kavgacı, A., Moretti, M., de Ruffray, P., Jansen, S., Pauchard, A., De Sanctis, M., Dimopoulos, P., He, T., Schmiedel, U., Küzmič, F., Müller, J.V., Kozub, Ł., Pedashenko, H., Lopez-Gonzalez, G., Kearsley, E., Rodwell, J., Font, X., Forey, E., Janssen, J., Biurrun, Idoia, Peñuelas, Josep, Landucci, F., Ruprecht, E., Munzinger, J., Krstonošić, D., Smyth, A., Higuchi, P., Lysenko, T., Kessler, M., Rūsiņa, S., Mencuccini, Maurizio, Sop, T., Pérez-Haase, A., Lee, M.T., Tsiripidis, I., Jedrzejek, B., Niinemets, Ü., Mahdavi, P., Sopotlieva, D., Turtureanu, P. D., Samimi, C., Minden, V., Vélez-Martin, E., Knollová, I., Peterka, T., Noroozi, J., Uğurlu, E., Venanzoni, R., Sparrow, B., Walker, D.A., Kühl, H., Schaminée, J.H.J., Phillips, Olivier L., Peet, R.K., Wana, D., Uogintas, D., Wiser, S., Manning, Peter, Stančić, Z., Arnst, E., Wohlgemuth, T., Vibrans, A.C., Schmidt, M., Nowak, A., Valachovič, M., Field, R., Onyshchenko, V., Svenning, J.-C., Álvarez, M., Overbeck, G.E., Ozinga, Win A., Šibík, J., Breen, A., Schrodt, F., Weiher, E., Haider, S., Violle, Cyrille, Ambarlı, D., Prokhorov, V., Vanselow, K. A., Bjorkman, Anne D., Rašomavičius, V., Revermann, R., Swacha, G., Dajić-Stevanović, Zora, Yamalov, S., Angelini, Pierangela, Wesche, K., Bondareva, V., Jandt, U., Virtanen, R., Černý, T., Šilc, U., Škvorc, Ž., Vashenyak, Y., Winter, M., Borchardt, P., Zizka, G., Chepinoga, V., Apostolova, I., Whitfeld, T., Dressler, S., Tang, Z., Lenoir, J., von Wehrden, H., Csiky, J., Aćić, Svetlana, Ejrnæs, R., Botta-Dukát, Z., Zverev, A., Fotiadis, Georgios, Vassilev, K., Arfin Khan, Mohammed A. S., Peyre, G., El-Sheikh, M.A.E.-R.M., García-Mijangos, I., Curran, Michael, Agrillo, E., Holubová, D., Wagner, V., Boyle, B., Attorre, Fabio, de Gasper, A.L., Hölzel, N., Enquist, B., Jiroušek, M., Willner, W., Custerevska, Renata, Brisse, H., Homeier, J., Jürgens, N., Golub, V., Kolomiychuk, V., Sabatini, Francesco Maria, Ewald, J., Macanović, A., Korolyuk, A., Indreica, A., Kühn, Ingolf, Baraloto, C., Gutierrez, A.G., Bruelheide, H., Dengler, J., Jiménez Alfaro, Borja, Purschke, Oliver, Hennekens, S.M., Chytrý, M., Pillar, V.D., Jansen, F., Kattge, Jens, Sandel, B., Aubin, I., Beckmann, M., Berg, Christian, Fagúndez, J., Levesley, A., Bergeron, Y., Bergmeier, E., De Bie, E., Nobis, M., Kuzemko, A., Kącki, Z., Marcenò, Corrado, Byun, C., Işık Gürsoy, D., Li, C.-F., Cabido, M.R., Hatim, M.Z., Moeslund, J.E., Casella, L., Cayuela, Luis, Finckh, Manfred, Petřík, P., Martynenko, V., Kozhevnikova, M., Liu, H., Kavgacı, A., Moretti, M., de Ruffray, P., Jansen, S., Pauchard, A., De Sanctis, M., Dimopoulos, P., He, T., Schmiedel, U., Küzmič, F., Müller, J.V., Kozub, Ł., Pedashenko, H., Lopez-Gonzalez, G., Kearsley, E., Rodwell, J., Font, X., Forey, E., Janssen, J., Biurrun, Idoia, Peñuelas, Josep, Landucci, F., Ruprecht, E., Munzinger, J., Krstonošić, D., Smyth, A., Higuchi, P., Lysenko, T., Kessler, M., Rūsiņa, S., Mencuccini, Maurizio, Sop, T., Pérez-Haase, A., Lee, M.T., Tsiripidis, I., Jedrzejek, B., Niinemets, Ü., Mahdavi, P., Sopotlieva, D., Turtureanu, P. D., Samimi, C., Minden, V., Vélez-Martin, E., Knollová, I., Peterka, T., Noroozi, J., Uğurlu, E., Venanzoni, R., Sparrow, B., Walker, D.A., Kühl, H., Schaminée, J.H.J., Phillips, Olivier L., Peet, R.K., Wana, D., Uogintas, D., Wiser, S., Manning, Peter, Stančić, Z., Arnst, E., Wohlgemuth, T., Vibrans, A.C., Schmidt, M., Nowak, A., Valachovič, M., Field, R., Onyshchenko, V., Svenning, J.-C., Álvarez, M., Overbeck, G.E., Ozinga, Win A., Šibík, J., Breen, A., Schrodt, F., Weiher, E., Haider, S., Violle, Cyrille, Ambarlı, D., Prokhorov, V., Vanselow, K. A., Bjorkman, Anne D., Rašomavičius, V., Revermann, R., Swacha, G., Dajić-Stevanović, Zora, Yamalov, S., Angelini, Pierangela, Wesche, K., Bondareva, V., Jandt, U., Virtanen, R., Černý, T., Šilc, U., Škvorc, Ž., Vashenyak, Y., Winter, M., Borchardt, P., Zizka, G., Chepinoga, V., Apostolova, I., Whitfeld, T., Dressler, S., Tang, Z., Lenoir, J., von Wehrden, H., Csiky, J., Aćić, Svetlana, Ejrnæs, R., Botta-Dukát, Z., Zverev, A., Fotiadis, Georgios, Vassilev, K., Arfin Khan, Mohammed A. S., Peyre, G., El-Sheikh, M.A.E.-R.M., García-Mijangos, I., Curran, Michael, Agrillo, E., Holubová, D., Wagner, V., Boyle, B., Attorre, Fabio, de Gasper, A.L., Hölzel, N., Enquist, B., Jiroušek, M., Willner, W., Custerevska, Renata, Brisse, H., Homeier, J., Jürgens, N., Golub, V., Kolomiychuk, V., Sabatini, Francesco Maria, Ewald, J., Macanović, A., Korolyuk, A., Indreica, A., Kühn, Ingolf, Baraloto, C., and Gutierrez, A.G.

Abstract

Aims: Vegetation-plot records provide information on the presence and cover or abundance of plants co-occurring in the same community. Vegetation-plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community-weighted means and variances of traits using gap-filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community-weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.

Published
2019

14. Global trait–environment relationships of plant communities

Author

Bruelheide, H., Dengler, J., Purschke, O., Lenoir, J., Jiménez‐Alfaro, B., Hennekens, S.M., Botta-Dukát, Z., Chytrý, M., Field, R., Jansen, F., Kattge, J., Pillar, V.D., Schrodt, F., Mahecha, M.D., Peet, R.K., Sandel, B., van Bodegom, P., Altman, J., Alvarez-Dávila, E., Khan, M.A.S.A., Attorre, F., Aubin, I., Baraloto, C., Barroso, J.G., Bauters, M., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Blonder, B., Čarni, A., Cayuela, L., Černý, T., Cornelissen, J.H.C., Craven, Dylan, Dainese, M., Derroire, G., De Sanctis, M., Díaz, S., Doležal, J., Farfan-Rios, W., Feldpausch, T.R., Fenton, N.J., Garnier, E., Guerin, G.R., Gutiérrez, A.G., Haider, S., Hattab, T., Henry, G., Hérault, B., Higuchi, P., Hölzel, N., Homeier, J., Jentsch, A., Jürgens, N., Kącki, Z., Karger, D.N., Kessler, M., Kleyer, M., Knollová, I., Korolyuk, A.Y., Kühn, Ingolf, Laughlin, D.C., Lens, F., Loos, J., Louault, F., Lyubenova, M.I., Malhi, Y., Marcenò, C., Mencuccini, M., Müller, J.V., Munzinger, J., Myers-Smith, I.H., Neill, D.A., Niinemets, Ü., Orwin, K.H., Ozinga, W.A., Penuelas, J., Pérez-Haase, A., Petřík, P., Phillips, O.L., Pärtel, M., Reich, P.B., Römermann, C., Rodrigues, A.V., Sabatini, F.M., Sardans, J., Schmidt, M., Seidler, G., Silva Espejo, J.E., Silveira, M., Smyth, A., Sporbert, M., Svenning, J.-C., Tang, Z., Thomas, R., Tsiripidis, I., Vassilev, K., Violle, C., Virtanen, Risto, Weiher, E., Bruelheide, H., Dengler, J., Purschke, O., Lenoir, J., Jiménez‐Alfaro, B., Hennekens, S.M., Botta-Dukát, Z., Chytrý, M., Field, R., Jansen, F., Kattge, J., Pillar, V.D., Schrodt, F., Mahecha, M.D., Peet, R.K., Sandel, B., van Bodegom, P., Altman, J., Alvarez-Dávila, E., Khan, M.A.S.A., Attorre, F., Aubin, I., Baraloto, C., Barroso, J.G., Bauters, M., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Blonder, B., Čarni, A., Cayuela, L., Černý, T., Cornelissen, J.H.C., Craven, Dylan, Dainese, M., Derroire, G., De Sanctis, M., Díaz, S., Doležal, J., Farfan-Rios, W., Feldpausch, T.R., Fenton, N.J., Garnier, E., Guerin, G.R., Gutiérrez, A.G., Haider, S., Hattab, T., Henry, G., Hérault, B., Higuchi, P., Hölzel, N., Homeier, J., Jentsch, A., Jürgens, N., Kącki, Z., Karger, D.N., Kessler, M., Kleyer, M., Knollová, I., Korolyuk, A.Y., Kühn, Ingolf, Laughlin, D.C., Lens, F., Loos, J., Louault, F., Lyubenova, M.I., Malhi, Y., Marcenò, C., Mencuccini, M., Müller, J.V., Munzinger, J., Myers-Smith, I.H., Neill, D.A., Niinemets, Ü., Orwin, K.H., Ozinga, W.A., Penuelas, J., Pérez-Haase, A., Petřík, P., Phillips, O.L., Pärtel, M., Reich, P.B., Römermann, C., Rodrigues, A.V., Sabatini, F.M., Sardans, J., Schmidt, M., Seidler, G., Silva Espejo, J.E., Silveira, M., Smyth, A., Sporbert, M., Svenning, J.-C., Tang, Z., Thomas, R., Tsiripidis, I., Vassilev, K., Violle, C., Virtanen, Risto, and Weiher, E.

Abstract

Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait–environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.

Published
2018

15. Global biodiversity monitoring: From data sources to Essential Biodiversity Variables

Author

Proença, V., Martin, L.J., Pereira, H.M., Fernandez, M., McRae, L., Belnap, J., Böhm, M., Brummitt, N., García-Moreno, J., Gregory, R.D., Honrado, J.P., Jürgens, N., Opige, M., Schmeller, Dirk Sven, Tiago, P., van Swaay, C.A.M., Proença, V., Martin, L.J., Pereira, H.M., Fernandez, M., McRae, L., Belnap, J., Böhm, M., Brummitt, N., García-Moreno, J., Gregory, R.D., Honrado, J.P., Jürgens, N., Opige, M., Schmeller, Dirk Sven, Tiago, P., and van Swaay, C.A.M.

Abstract

Essential Biodiversity Variables (EBVs) consolidate information from varied biodiversity observation sources. Here we demonstrate the links between data sources, EBVs and indicators and discuss how different sources of biodiversity observations can be harnessed to inform EBVs. We classify sources of primary observations into four types: extensive and intensive monitoring schemes, ecological field studies and satellite remote sensing. We characterize their geographic, taxonomic and temporal coverage. Ecological field studies and intensive monitoring schemes inform a wide range of EBVs, but the former tend to deliver short-term data, while the geographic coverage of the latter is limited. In contrast, extensive monitoring schemes mostly inform the population abundance EBV, but deliver long-term data across an extensive network of sites. Satellite remote sensing is particularly suited to providing information on ecosystem function and structure EBVs. Biases behind data sources may affect the representativeness of global biodiversity datasets. To improve them, researchers must assess data sources and then develop strategies to compensate for identified gaps. We draw on the population abundance dataset informing the Living Planet Index (LPI) to illustrate the effects of data sources on EBV representativeness. We find that long-term monitoring schemes informing the LPI are still scarce outside of Europe and North America and that ecological field studies play a key role in covering that gap. Achieving representative EBV datasets will depend both on the ability to integrate available data, through data harmonization and modeling efforts, and on the establishment of new monitoring programs to address critical data gaps.

Published
2016

16. The SASSCAL contribution to climate observation, climate data management and data rescue in Southern Africa

Author

Kaspar, F., primary, Helmschrot, J., additional, Mhanda, A., additional, Butale, M., additional, de Clercq, W., additional, Kanyanga, J. K., additional, Neto, F. O. S., additional, Kruger, S., additional, Castro Matsheka, M., additional, Muche, G., additional, Hillmann, T., additional, Josenhans, K., additional, Posada, R., additional, Riede, J., additional, Seely, M., additional, Ribeiro, C., additional, Kenabatho, P., additional, Vogt, R., additional, and Jürgens, N., additional

Published
2015
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17. SASSCAL WeatherNet to support regional weather monitoring and climate-related research in Southern Africa

Author

Helmschrot, J., primary, Muche, G., additional, Hillmann, T., additional, Kanyanga, J., additional, Butale, M., additional, Nascimento, D., additional, Kruger, S., additional, Strohbach, B., additional, Seely, M., additional, Ribeiro, C., additional, De Clercq, W., additional, Kenabatho, P., additional, Josenhans, K., additional, and Jürgens, N., additional

Published
2015
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19. Fynbos Biome

Author

Rebelo, A.G., Boucher, C., Helme, N., Mucina, L., Rutherford, M.C., Smit, W.J., Powrie, L.W., Ellis, F., Lambrechts, J.J.N., Scott, L., Radloff, F.G.T., Johnson, S.D., Richardson, D.M., Ward, R.A., Proche, S.M., Oliver, E.G.H., Manning, J.C., Jürgens, N., McDonald, D.J., Janssen, J.A.M., Walton, B.A., le Roux, A., Skowno, A.L., Todd, S.W., and Hoare, D.B.

Subjects
Centre for Ecosystem Studies, Life Science, Wageningen Environmental Research, Centrum Ecosystemen
Published
2006

20. Plant functional traits and types as a tool to analyse landuse impacts on vegetation

Author

Jürgens, N., Schmiedel, U., Hoffmann, M.T., Wesuls, D., Strobach, M., Horn, A., Kos, M., Zimmermann, Jula, Hoffmann, J., Geldenhuys, C., Dreber, N., Kellermann, L., van Rooyen, G., Poschlod, P., Jürgens, N., Schmiedel, U., Hoffmann, M.T., Wesuls, D., Strobach, M., Horn, A., Kos, M., Zimmermann, Jula, Hoffmann, J., Geldenhuys, C., Dreber, N., Kellermann, L., van Rooyen, G., and Poschlod, P.

Published
2010

21. Global change research in Germany 2008

Author

Höll, B., Mauser, W., Alcamo, J., Andreae, M., Akhtar-Schuster, M., Borchardt, Dietrich, Callies, U., Cramer, W., Görg, Christoph, Hansjürgens, Bernd, Heimann, M., Helbig, G., Jacob, D., Jürgens, N., Karte, J., Kalko, E., Kaltschmitt, M., Klepper, G., Klotz, Stefan, Kraas, F., Kremer, H., Kroll, S., Lelieveld, J., Lemke, P., Marotzke, J., Schulz, M., Seppelt, Ralf, Stoll, P.-T., Teutsch, Georg, Vlek, P., Wefer, G., Weisser, W., von Storch, H., Zacharias, Steffen, Höll, B., Mauser, W., Alcamo, J., Andreae, M., Akhtar-Schuster, M., Borchardt, Dietrich, Callies, U., Cramer, W., Görg, Christoph, Hansjürgens, Bernd, Heimann, M., Helbig, G., Jacob, D., Jürgens, N., Karte, J., Kalko, E., Kaltschmitt, M., Klepper, G., Klotz, Stefan, Kraas, F., Kremer, H., Kroll, S., Lelieveld, J., Lemke, P., Marotzke, J., Schulz, M., Seppelt, Ralf, Stoll, P.-T., Teutsch, Georg, Vlek, P., Wefer, G., Weisser, W., von Storch, H., and Zacharias, Steffen

Published
2008

22. Desert Biome

Author

Jürgens, N, Desmet, P., Rutherford, M., Mucina, Ladislav, Ward, R., Jürgens, N, Desmet, P., Rutherford, M., Mucina, Ladislav, and Ward, R.

Published
2006

26. Scientific concepts for an integrated analysis of desertification

Author

Reynolds, J. F., primary, Grainger, A., additional, Stafford Smith, D. M., additional, Bastin, G., additional, Garcia‐Barrios, L., additional, Fernández, R. J., additional, Janssen, M. A., additional, Jürgens, N., additional, Scholes, R. J., additional, Veldkamp, A., additional, Verstraete, M. M., additional, Von Maltitz, G., additional, and Zdruli, P., additional

Published
2011
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28. Floristic affinities of an inselberg archipelago in the southern Namib desert—relic of the past, centre of endemism or nothing special?

Author

Burke, A., Jürgens, N., and Seely, M.K.

Subjects
*BOTANY, *PLANT habitats
Abstract

The floral composition of an inselberg archipelago in the southern Namib desert was investigated with regard to species diversity, geographic range of the species, habitat niches, seed dispersal abilities and plant herbivore defence. Although no endemic species were found, the archipelago forms an extreme and often isolated outlier for a large number of species in their distribution area. The hypothesis is proposed that the isolated extreme habitat allowed survival of relic populations due to low immigration rate and low competition. The high proportion of species favouring long-range dispersal might explain the lack of endemic species as well as the large contribution of species at their distributional boundary. [ABSTRACT FROM AUTHOR]

Published
1998
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29. sPlot – A new tool for global vegetation analyses

Author

Bruelheide H., Dengler J., Jiménez-Alfaro B., Purschke O., Hennekens S., Chytrý M., Pillar V., Jansen F., Kattge J., Sandel B., Aubin I., Biurrun I., Field R., Haider S., Jandt U., Lenoir J., Peet R., Peyre G., Sabatini F., Schmidt M., Schrodt F., Winter M., Aćić S., Agrillo E., Alvarez M., Ambarlı D., Angelini P., Apostolova I., Arfin Khan M., Arnst E., Attorre F., Baraloto C., Beckmann M., Berg C., Bergeron Y., Bergmeier E., Bjorkman A., Bondareva V., Borchardt P., Botta-Dukát Z., Boyle B., Breen A., Brisse H., Byun C., Cabido M., Casella L., Cayuela L., Černý T., Chepinoga V., Csiky J., Curran M., Ćušterevska R., Dajić Stevanović Z., De Bie E., de Ruffray P., De Sanctis M., Dimopoulos P., Dressler S., Ejrnæs R., El-Sheikh M., Enquist B., Ewald J., Fagúndez J., Finckh M., Font X., Forey E., Fotiadis G., García-Mijangos I., de Gasper A., Golub V., Gutierrez A., Hatim M., He T., Higuchi P., Holubová D., Hölzel N., Homeier J., Indreica A., Işık Gürsoy D., Jansen S., Janssen J., Jedrzejek B., Jiroušek M., Jürgens N., Kącki Z., Kavgacı A., Kearsley E., Kessler M., Knollová I., Kolomiychuk V., Korolyuk A., Kozhevnikova M., Kozub Ł., Krstonošić D., Kühl H., Kühn I., Kuzemko A., Küzmič F., Landucci F., Lee M., Bruelheide H., Dengler J., Jiménez-Alfaro B., Purschke O., Hennekens S., Chytrý M., Pillar V., Jansen F., Kattge J., Sandel B., Aubin I., Biurrun I., Field R., Haider S., Jandt U., Lenoir J., Peet R., Peyre G., Sabatini F., Schmidt M., Schrodt F., Winter M., Aćić S., Agrillo E., Alvarez M., Ambarlı D., Angelini P., Apostolova I., Arfin Khan M., Arnst E., Attorre F., Baraloto C., Beckmann M., Berg C., Bergeron Y., Bergmeier E., Bjorkman A., Bondareva V., Borchardt P., Botta-Dukát Z., Boyle B., Breen A., Brisse H., Byun C., Cabido M., Casella L., Cayuela L., Černý T., Chepinoga V., Csiky J., Curran M., Ćušterevska R., Dajić Stevanović Z., De Bie E., de Ruffray P., De Sanctis M., Dimopoulos P., Dressler S., Ejrnæs R., El-Sheikh M., Enquist B., Ewald J., Fagúndez J., Finckh M., Font X., Forey E., Fotiadis G., García-Mijangos I., de Gasper A., Golub V., Gutierrez A., Hatim M., He T., Higuchi P., Holubová D., Hölzel N., Homeier J., Indreica A., Işık Gürsoy D., Jansen S., Janssen J., Jedrzejek B., Jiroušek M., Jürgens N., Kącki Z., Kavgacı A., Kearsley E., Kessler M., Knollová I., Kolomiychuk V., Korolyuk A., Kozhevnikova M., Kozub Ł., Krstonošić D., Kühl H., Kühn I., Kuzemko A., Küzmič F., Landucci F., and Lee M.

Abstract

© 2019 International Association for Vegetation Science Aims: Vegetation-plot records provide information on the presence and cover or abundance of plants co-occurring in the same community. Vegetation-plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community-weighted means and variances of traits using gap-filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community-weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.

30. Does using species abundance data improve estimates of species diversity from remotely sensed spectral heterogeneity?

Author

Jens Oldeland, Norbert Jürgens, Dirk Wesuls, Michael Schmidt, Duccio Rocchini, Oldeland J., Wesuls D., Rocchini D., Schmidt M., and Jürgens N.

Subjects
Ecology, General Decision Sciences, Species diversity, Hyperspectral imaging, Context (language use), Spatial heterogeneity, remote sensing, Diversity index, Abundance (ecology), Environmental science, Alpha diversity, Physical geography, Species richness, Ecology, Evolution, Behavior and Systematics, biodiversity
Abstract

Different approaches for the assessment of biodiversity by means of remote sensing were developed over the last decades. A new approach, based on the spectral variation hypothesis, proposes that the spectral heterogeneity of a remotely sensed image is correlated with landscape structure and complexity which also reflects habitat heterogeneity which itself is known to enhance species diversity. In this context, previous studies only applied species richness as a measure of diversity. The aim of this paper was to analyze the relationship of richness and abundance-based diversity measures with spectral variability and compare the results at two scales. At three different test sites in Central Namibia, measures of vascular plant diversity was sampled at two scales - 100 m(2) and 1000 m(2). Hyperspectral remote sensing data were collected for the study sites and spectral variability, was calculated at plot level. Ordinary least square regression was used to test the relationship between species richness and the abundance-based Shannon Index and spectral variability. We found that Shannon Index permanently achieved better results at all test sites especially at 1000 m(2), Even when all sites where pooled together, Shannon index was still significantly related with spectral variability at 1000 m(2). We suggest incorporating abundance-based diversity measures in studies of relationships between ecological and spectral variability. The contribution made by the high spectral and spatial resolution of the hyperspectral sensor is discussed. (C) 2009 Elsevier Ltd. All rights reserved. RI Rocchini, Duccio/B-6742-2011; Oldeland, Jens/A-1587-2012

Published
2010
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31. Welwitschia: Phylogeography of a living fossil, diversified within a desert refuge.

Author

Jürgens N, Oncken I, Oldeland J, Gunter F, and Rudolph B

Subjects
Angola, Biological Evolution, Ecosystem, Environment, Genetic Variation, Genetics, Population, Namibia, Phylogeography, Biodiversity, Fossils, Phylogeny, Tracheophyta classification, Tracheophyta genetics
Abstract

Welwitschia mirabilis is one of the most extraordinary plant species on earth. With a fossil record of 112 My and phylogenetically isolated within the order Gnetales, the monotypic genus Welwitschia has survived only in the northern Namib Desert in Angola and Namibia. Despite its iconic role, the biogeography, ecological niche, and evolutionary history of the species remain poorly understood. Here we present the first comprehensive map of the strongly disjunct species range, and we explore the genetic relationships among all range fragments based on six SSR markers. We also assess the variation of the environmental niche and habitat preference. Our results confirm genetic divergence, which is consistent with the hypothetical existence of two subspecies within Welwitschia. We identify an efficient geographical barrier separating two gene pools at 18.7°S in northern Namibia. We also identify further diversification within each of the two subspecies, with several different gene pools in ten isolated range fragments. Given the presence of well-isolated populations with unique gene pools and the association with different bioclimatic variables, rock types, and habitats within arid river catchments, we can hypothesize that the present intraspecific diversity may have evolved at least in part within the present refuge of the northern Namib Desert.

Published
2021
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32. Granular Cellulose Nanofibril Hydrogel Scaffolds for 3D Cell Cultivation.

Author

Gehlen DB, Jürgens N, Omidinia-Anarkoli A, Haraszti T, George J, Walther A, Ye H, and De Laporte L

Subjects
Biocompatible Materials, Porosity, Tissue Engineering, Tissue Scaffolds, Cellulose, Hydrogels
Abstract

The replacement of diseased and damaged organs remains an challenge in modern medicine. However, through the use of tissue engineering techniques, it may soon be possible to (re)generate tissues and organs using artificial scaffolds. For example, hydrogel networks made from hydrophilic precursor solutions can replicate many properties found in the natural extracellular matrix (ECM) but often lack the dynamic nature of the ECM, as many covalently crosslinked hydrogels possess elastic and static networks with nanoscale pores hindering cell migration without being degradable. To overcome this, macroporous colloidal hydrogels can be prepared to facilitate cell infiltration. Here, an easy method is presented to fabricate granular cellulose nanofibril hydrogel (CNF) scaffolds as porous networks for 3D cell cultivation. CNF is an abundant natural and highly biocompatible material that supports cell adhesion. Granular CNF scaffolds are generated by pre-crosslinking CNF using calcium and subsequently pressing the gel through micrometer-sized nylon meshes. The granular solution is mixed with fibroblasts and crosslinked with cell culture medium. The obtained granular CNF scaffold is significantly softer and enables well-distributed fibroblast growth. This cost-effective material combined with this efficient and facile fabrication technique allows for 3D cell cultivation in an upscalable manner., (© 2020 The Authors. Published by Wiley-VCH GmbH.)

Published
2020
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33. Global trait-environment relationships of plant communities.

Author

Bruelheide H, Dengler J, Purschke O, Lenoir J, Jiménez-Alfaro B, Hennekens SM, Botta-Dukát Z, Chytrý M, Field R, Jansen F, Kattge J, Pillar VD, Schrodt F, Mahecha MD, Peet RK, Sandel B, van Bodegom P, Altman J, Alvarez-Dávila E, Arfin Khan MAS, Attorre F, Aubin I, Baraloto C, Barroso JG, Bauters M, Bergmeier E, Biurrun I, Bjorkman AD, Blonder B, Čarni A, Cayuela L, Černý T, Cornelissen JHC, Craven D, Dainese M, Derroire G, De Sanctis M, Díaz S, Doležal J, Farfan-Rios W, Feldpausch TR, Fenton NJ, Garnier E, Guerin GR, Gutiérrez AG, Haider S, Hattab T, Henry G, Hérault B, Higuchi P, Hölzel N, Homeier J, Jentsch A, Jürgens N, Kącki Z, Karger DN, Kessler M, Kleyer M, Knollová I, Korolyuk AY, Kühn I, Laughlin DC, Lens F, Loos J, Louault F, Lyubenova MI, Malhi Y, Marcenò C, Mencuccini M, Müller JV, Munzinger J, Myers-Smith IH, Neill DA, Niinemets Ü, Orwin KH, Ozinga WA, Penuelas J, Pérez-Haase A, Petřík P, Phillips OL, Pärtel M, Reich PB, Römermann C, Rodrigues AV, Sabatini FM, Sardans J, Schmidt M, Seidler G, Silva Espejo JE, Silveira M, Smyth A, Sporbert M, Svenning JC, Tang Z, Thomas R, Tsiripidis I, Vassilev K, Violle C, Virtanen R, Weiher E, Welk E, Wesche K, Winter M, Wirth C, and Jandt U

Subjects
Forests, Grassland, Life History Traits, Plant Dispersal, Plants
Abstract

Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait-environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.

Published
2018
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34. The impact of livestock grazing on plant diversity: an analysis across dryland ecosystems and scales in southern Africa.

Author

Hanke W, Böhner J, Dreber N, Jürgens N, Schmiedel U, Wesuls D, and Dengler J

Subjects
Africa, Southern, Animals, Ecosystem, Biodiversity, Livestock, Plants
Abstract

A general understanding of grazing effects on plant diversity in drylands is still missing, despite an extensive theoretical background. Cross-biome syntheses are hindered by the fact that the outcomes of disturbance studies are strongly affected by the choice of diversity measures, and the spatial and temporal scales of measurements. The aim of this study is to overcome these weaknesses by applying a wide range of diversity measures to a data set derived from identical sampling in three distinct ecosystems. We analyzed three fence-line contrasts (heavier vs. lighter grazing intensity), representing different degrees of aridity (from arid to semiarid) and precipitation regimes (summer rain vs. winter rain) in southern Africa. We tested the impact of grazing intensity on multiple aspects of plant diversity (species and functional group level, richness and evenness components, alpha and beta diversity, and composition) at two spatial scales, and for both 5-yr means and interannual variability. Heavier grazing reduced total plant cover and substantially altered the species and functional composition at all sites. However, a significant decrease in species alpha diversity was detected at only one of the three sites. By contrast, alpha diversity of plant functional groups responded consistently across ecosystems and scales, with a significant decrease at heavier grazing intensity. The cover-based measures of functional group diversity responded more sensitively and more consistently than functional group richness. Beta diversity of species and functional types increased under heavier grazing, showing that at larger scales, the heterogeneity of the community composition and the functional structure were increased. Heavier grazing mostly increased interannual variability of alpha diversity, while effects on beta diversity and cover were inconsistent. Our results suggest that species diversity alone may not adequately reflect the shifts in vegetation structure that occur in response to increased grazing intensity in the dryland biomes of southern Africa. Compositional and structural changes of the vegetation are better reflected by trait-based diversity measures. In particular, measures of plant functional diversity that include evenness represent a promising tool to detect and quantify disturbance effects on ecosystems.

Published
2014
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35. The BIOTA Biodiversity Observatories in Africa--a standardized framework for large-scale environmental monitoring.

Author

Jürgens N, Schmiedel U, Haarmeyer DH, Dengler J, Finckh M, Goetze D, Gröngröft A, Hahn K, Koulibaly A, Luther-Mosebach J, Muche G, Oldeland J, Petersen A, Porembski S, Rutherford MC, Schmidt M, Sinsin B, Strohbach BJ, Thiombiano A, Wittig R, and Zizka G

Subjects
Africa, Animals, Biota, Environmental Monitoring standards, Plant Development, Plants classification, Biodiversity, Conservation of Natural Resources methods, Environmental Monitoring methods
Abstract

The international, interdisciplinary biodiversity research project BIOTA AFRICA initiated a standardized biodiversity monitoring network along climatic gradients across the African continent. Due to an identified lack of adequate monitoring designs, BIOTA AFRICA developed and implemented the standardized BIOTA Biodiversity Observatories, that meet the following criteria (a) enable long-term monitoring of biodiversity, potential driving factors, and relevant indicators with adequate spatial and temporal resolution, (b) facilitate comparability of data generated within different ecosystems, (c) allow integration of many disciplines, (d) allow spatial up-scaling, and (e) be applicable within a network approach. A BIOTA Observatory encompasses an area of 1 km(2) and is subdivided into 100 1-ha plots. For meeting the needs of sampling of different organism groups, the hectare plot is again subdivided into standardized subplots, whose sizes follow a geometric series. To allow for different sampling intensities but at the same time to characterize the whole square kilometer, the number of hectare plots to be sampled depends on the requirements of the respective discipline. A hierarchical ranking of the hectare plots ensures that all disciplines monitor as many hectare plots jointly as possible. The BIOTA Observatory design assures repeated, multidisciplinary standardized inventories of biodiversity and its environmental drivers, including options for spatial up- and downscaling and different sampling intensities. BIOTA Observatories have been installed along climatic and landscape gradients in Morocco, West Africa, and southern Africa. In regions with varying land use, several BIOTA Observatories are situated close to each other to analyze management effects.

Published
2012
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