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121 results on '"Vincke, C."'

1. Forest cover correlates with good biological water quality. Insights from a regional study (Wallonia, Belgium)

Author: Brogna, D., Dufrêne, M., Michez, A., Latli, A., Jacobs, S., Vincke, C., and Dendoncker, N.
Published: 2018
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2. Evapotranspiration assessment of a mixed temperate forest by four methods: Eddy covariance, soil water budget, analytical and model

Author: Soubie, R., Heinesch, B., Granier, A., Aubinet, M., and Vincke, C.
Published: 2016
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3. Modelling the mortality of Hylotrupes bajulus (L.) larvae exposed to anoxic treatment for disinfestation of wooden art objects

Author: de Streel, G., Henin, J.-M., Bogaert, P., Mercier, E., Rabelo, E., Vincke, C., and Jourez, B.
Published: 2016
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4. Sap flux density and stomatal conductance of European beech and common oak trees in pure and mixed stands during the summer drought of 2003

Author: Jonard, F., André, F., Ponette, Q., Vincke, C., and Jonard, M.
Published: 2011
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5. Long term dynamics and structure of woody vegetation in the Ferlo (Senegal)

Author: Vincke, C., Diédhiou, I., and Grouzis, M.
Published: 2010
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6. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data (vol 7, 225, 2020)

Author: Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Reichstein, M, Ribeca, A, van Ingen, C, Vuichard, N, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardo, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Brummer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D'Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrene, E, Dunn, A, Dusek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Grunwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hortnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janous, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, Lopez-Ballesteros, A, Lopez-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Luers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, U, Raz-Yaseef, N, Rebmann, C, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sanchez-Canete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlak, P, Serrano-Ortiz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Sigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, Papale, D, Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Reichstein, M, Ribeca, A, van Ingen, C, Vuichard, N, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardo, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Brummer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D'Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrene, E, Dunn, A, Dusek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Grunwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hortnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janous, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, Lopez-Ballesteros, A, Lopez-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Luers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, U, Raz-Yaseef, N, Rebmann, C, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sanchez-Canete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlak, P, Serrano-Ortiz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Sigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, and Papale, D
Abstract: A Correction to this paper has been published: https://doi.org/10.1038/s41597-021-00851-9.
Published: 2021

7. Method comparison of indirect assessments of understory leaf area index (LAIu): A case study across the extended network of ICOS forest ecosystem sites in Europe

Author: George, J.-P., Yang, W., Kobayashi, H., Biermann, T., Carrara, A., Cremonese, E., Cuntz, M., Fares, S., Gerosa, G., Grünwald, T., Hase, Jan Niklas, Heliasz, M., Ibrom, A., Knohl, A., Kruijt, B., Lange, H., Limousin, J.-M., Loustau, D., Lukeš, P., Marzuoli, R., Mölder, M., Montagnani, L., Neirynck, J., Peichl, M., Rebmann, Corinna, Schmidt, M., Lopez Serrano, F.R., Soudani, K., Vincke, C., Pisek, J., George, J.-P., Yang, W., Kobayashi, H., Biermann, T., Carrara, A., Cremonese, E., Cuntz, M., Fares, S., Gerosa, G., Grünwald, T., Hase, Jan Niklas, Heliasz, M., Ibrom, A., Knohl, A., Kruijt, B., Lange, H., Limousin, J.-M., Loustau, D., Lukeš, P., Marzuoli, R., Mölder, M., Montagnani, L., Neirynck, J., Peichl, M., Rebmann, Corinna, Schmidt, M., Lopez Serrano, F.R., Soudani, K., Vincke, C., and Pisek, J.
Abstract: Leaf area index (LAI) is a key ecological indicator for describing the structure of canopies and for modelling energy exchange between atmosphere and biosphere. While LAI of the forest overstory can be accurately assessed over large spatial scales via remote sensing, LAI of the forest understory (LAIu) is still largely ignored in ecological studies and ecosystem modelling due to the fact that it is often too complex to be destructively sampled or approximated by other site parameters. Additionally, so far only few attempts have been made to retrieve understory LAI via remote sensing, because dense canopies with high LAI are often hindering retrieval algorithms to produce meaningful estimates for understory LAI. Consequently, the forest understory still constitutes a poorly investigated research realm impeding ecological studies to properly account for its contribution to the energy absorption capacity of forest stands. This study aims to compare three conceptually different indirect retrieval methodologies for LAIu over a diverse panel of forest understory types distributed across Europe. For this we carried out near-to-surface measurements of understory reflectance spectra as well as digital surface photography over the extended network of Integrated Carbon Observation System (ICOS) forest ecosystem sites. LAIu was assessed by exploiting the empirical relationship between vegetation cover and light absorption (Beer-Lambert- Bouguer law) as well as by utilizing proposed relationships with two prominent vegetation indices: normalized difference vegetation index (NDVI) and simple ratio (SR). Retrievals from the three methods were significantly correlated with each other (r = 0.63–0.99, RMSE = 0.53–0.72), but exhibited also significant bias depending on the LAI scale. The NDVI based retrieval approach most likely overestimates LAI at productive sites when LAIu > 2, while the simple ratio algorithm overestimat
Published: 2021

8. Retrieval and validation of forest background reflectivity from daily Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) data across European forests

Author: Pisek, J., Erb, A., Korhonen, L., Biermann, T., Carrara, A., Cremonese, E., Cuntz, M., Fares, S., Gerosa, G., Grünwald, T., Hase, Jan Niklas, Heliasz, M., Ibrom, A., Knohl, A., Kobler, J., Kruijt, B., Lange, H., Leppänen, L., Limousin, J.-M., Lopez Serrano, F.R., Loustau, D., Lukeš, P., Lundin, L., Marzuoli, R., Mölder, M., Montagnani, L., Neirynck, J., Peichl, M., Rebmann, Corinna, Rubio, E., Santos-Reis, M., Schaaf, C., Schmidt, M., Simioni, G., Soudani, K., Vincke, C., Pisek, J., Erb, A., Korhonen, L., Biermann, T., Carrara, A., Cremonese, E., Cuntz, M., Fares, S., Gerosa, G., Grünwald, T., Hase, Jan Niklas, Heliasz, M., Ibrom, A., Knohl, A., Kobler, J., Kruijt, B., Lange, H., Leppänen, L., Limousin, J.-M., Lopez Serrano, F.R., Loustau, D., Lukeš, P., Lundin, L., Marzuoli, R., Mölder, M., Montagnani, L., Neirynck, J., Peichl, M., Rebmann, Corinna, Rubio, E., Santos-Reis, M., Schaaf, C., Schmidt, M., Simioni, G., Soudani, K., and Vincke, C.
Abstract: Information about forest background reflectance is needed for accurate biophysical parameter retrieval from forest canopies (overstory) with remote sensing. Separating under- and overstory signals would enable more accurate modeling of forest carbon and energy fluxes. We retrieved values of the normalized difference vegetation index (NDVI) of the forest understory with the multi-angular Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo data (gridded 500 m daily Collection 6 product), using a method originally developed for boreal forests. The forest floor background reflectance estimates from the MODIS data were compared with in situ understory reflectance measurements carried out at an extensive set of forest ecosystem experimental sites across Europe. The reflectance estimates from MODIS data were, hence, tested across diverse forest conditions and phenological phases during the growing season to examine their applicability for ecosystems other than boreal forests. Here we report that the method can deliver good retrievals, especially over different forest types with open canopies (low foliage cover). The performance of the method was found to be limited over forests with closed canopies (high foliage cover), where the signal from understory becomes too attenuated. The spatial heterogeneity of individual field sites and the limitations and documented quality of the MODIS BRDF product are shown to be important for the correct assessment and validation of the retrievals obtained with remote sensing.
Published: 2021

9. Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Author: Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Reichstein, M, Ribeca, A, van Ingen, C, Vuichard, N, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardö, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Brümmer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D’Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrêne, E, Dunn, A, Dušek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Grünwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hörtnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janouš, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, López-Ballesteros, A, López-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Lüers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, Ü, Raz-Yaseef, N, Rebmann, C, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sánchez-Cañete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlák, P, Serrano-Ortíz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Šigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, Papale, D, Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Reichstein, M, Ribeca, A, van Ingen, C, Vuichard, N, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardö, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Brümmer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D’Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrêne, E, Dunn, A, Dušek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Grünwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hörtnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janouš, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, López-Ballesteros, A, López-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Lüers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, Ü, Raz-Yaseef, N, Rebmann, C, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sánchez-Cañete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlák, P, Serrano-Ortíz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Šigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, and Papale, D
Abstract: The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions.
Published: 2021

10. Method comparison of indirect assessments of understory leaf area index (LAIu): A case study across the extended network of ICOS forest ecosystem sites in Europe

Author: George, J. -P., Yang, W., Kobayashi, H., Biermann, T., Carrara, A., Cremonese, E., Cuntz, M., Fares, S., Gerosa, Giacomo Alessandro, Grunwald, T., Hase, N., Heliasz, M., Ibrom, A., Knohl, A., Kruijt, B., Lange, H., Limousin, J. -M., Loustau, D., Lukes, P., Marzuoli, Riccardo, Molder, M., Montagnani, L., Neirynck, J., Peichl, M., Rebmann, C., Schmidt, M., Serrano, F. R. L., Soudani, K., Vincke, C., Pisek, J., Gerosa G. (ORCID:0000-0002-5352-3222), Marzuoli R. (ORCID:0000-0001-5946-9530), George, J. -P., Yang, W., Kobayashi, H., Biermann, T., Carrara, A., Cremonese, E., Cuntz, M., Fares, S., Gerosa, Giacomo Alessandro, Grunwald, T., Hase, N., Heliasz, M., Ibrom, A., Knohl, A., Kruijt, B., Lange, H., Limousin, J. -M., Loustau, D., Lukes, P., Marzuoli, Riccardo, Molder, M., Montagnani, L., Neirynck, J., Peichl, M., Rebmann, C., Schmidt, M., Serrano, F. R. L., Soudani, K., Vincke, C., Pisek, J., Gerosa G. (ORCID:0000-0002-5352-3222), and Marzuoli R. (ORCID:0000-0001-5946-9530)
Abstract: Leaf area index (LAI) is a key ecological indicator for describing the structure of canopies and for modelling energy exchange between atmosphere and biosphere. While LAI of the forest overstory can be accurately assessed over large spatial scales via remote sensing, LAI of the forest understory (LAIu) is still largely ignored in ecological studies and ecosystem modelling due to the fact that it is often too complex to be destructively sampled or approximated by other site parameters. Additionally, so far only few attempts have been made to retrieve understory LAI via remote sensing, because dense canopies with high LAI are often hindering retrieval algorithms to produce meaningful estimates for understory LAI. Consequently, the forest understory still constitutes a poorly investigated research realm impeding ecological studies to properly account for its contribution to the energy absorption capacity of forest stands. This study aims to compare three conceptually different indirect retrieval methodologies for LAIu over a diverse panel of forest understory types distributed across Europe. For this we carried out near-to-surface measurements of understory reflectance spectra as well as digital surface photography over the extended network of Integrated Carbon Observation System (ICOS) forest ecosystem sites. LAIu was assessed by exploiting the empirical relationship between vegetation cover and light absorption (Beer-Lambert- Bouguer law) as well as by utilizing proposed relationships with two prominent vegetation indices: normalized difference vegetation index (NDVI) and simple ratio (SR). Retrievals from the three methods were significantly correlated with each other (r = 0.63–0.99, RMSE = 0.53–0.72), but exhibited also significant bias depending on the LAI scale. The NDVI based retrieval approach most likely overestimates LAI at productive sites when LAIu > 2, while the simple ratio algorithm overestimates LAIu at sites with sparse understory vegetation and pre
Published: 2021

11. Forest and woodland replacement patterns following drought-related mortality

Author: Batllori, E., Lloret, F., Aakala, T., Anderegg, W.R.L., Aynekulu, E., Bendixsen, D.P., Bentouati, A., Bigler, C., Burk, C.J., Camarero, J.J., Colangelo, M., Cooper, J.D., Fensham, R., Floyd, M.L., Galiano, L., Ganey, J.L., Gonzalez, P., Jacobsen, A.L., Kane, J.M., Kitzberger, T., Linares, J.C., Marchetti, S.B., Matusick, G., Michaelian, M., Navarro-Cerrillo, R.M., Pratt, R.B., Redmond, M.D., Rigling, A., Ripullone, F., Sangüesa-Barreda, G., Sasal, Y., Saura-Mas, S., Suarez, M.L., Veblen, T.T., Vilà-Cabrera, A., Vincke, C., Zeeman, B., Batllori, E., Lloret, F., Aakala, T., Anderegg, W.R.L., Aynekulu, E., Bendixsen, D.P., Bentouati, A., Bigler, C., Burk, C.J., Camarero, J.J., Colangelo, M., Cooper, J.D., Fensham, R., Floyd, M.L., Galiano, L., Ganey, J.L., Gonzalez, P., Jacobsen, A.L., Kane, J.M., Kitzberger, T., Linares, J.C., Marchetti, S.B., Matusick, G., Michaelian, M., Navarro-Cerrillo, R.M., Pratt, R.B., Redmond, M.D., Rigling, A., Ripullone, F., Sangüesa-Barreda, G., Sasal, Y., Saura-Mas, S., Suarez, M.L., Veblen, T.T., Vilà-Cabrera, A., Vincke, C., and Zeeman, B.
Abstract: Forest vulnerability to drought is expected to increase under anthropogenic climate change, and drought-induced mortality and community dynamics following drought have major ecological and societal impacts. Here, we show that tree mortality concomitant with drought has led to short-term (mean 5 y, range 1 to 23 y after mortality) vegetation-type conversion in multiple biomes across the world (131 sites). Self-replacement of the dominant tree species was only prevalent in 21% of the examined cases and forests and woodlands shifted to nonwoody vegetation in 10% of them. The ultimate temporal persistence of such changes remains unknown but, given the key role of biological legacies in long-term ecological succession, this emerging picture of postdrought ecological trajectories highlights the potential for major ecosystem reorganization in the coming decades. Community changes were less pronounced under wetter postmortality conditions. Replacement was also influenced by management intensity, and postdrought shrub dominance was higher when pathogens acted as codrivers of tree mortality. Early change in community composition indicates that forests dominated by mesic species generally shifted toward more xeric communities, with replacing tree and shrub species exhibiting drier bioclimatic optima and distribution ranges. However, shifts toward more mesic communities also occurred and multiple pathways of forest replacement were observed for some species. Drought characteristics, species-specific environmental preferences, plant traits, and ecosystem legacies govern postdrought species turnover and subsequent ecological trajectories, with potential far-reaching implications for forest biodiversity and ecosystem services.
Published: 2020

12. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Author: Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Ribeca, A, van Ingen, C, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardo, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Bruemmer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D'Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrene, E, Dunn, A, Dusek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Gruenwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hoertnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janous, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, Lopez-Ballesteros, A, Lopez-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Lueers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, U, Raz-Yaseef, N, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sanchez-Canete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlak, P, Serrano-Ortiz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Sigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tiedemann, F, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, Papale, D, Pastorello, G, Trotta, C, Canfora, E, Chu, H, Christianson, D, Cheah, Y-W, Poindexter, C, Chen, J, Elbashandy, A, Humphrey, M, Isaac, P, Polidori, D, Ribeca, A, van Ingen, C, Zhang, L, Amiro, B, Ammann, C, Arain, MA, Ardo, J, Arkebauer, T, Arndt, SK, Arriga, N, Aubinet, M, Aurela, M, Baldocchi, D, Barr, A, Beamesderfer, E, Marchesini, LB, Bergeron, O, Beringer, J, Bernhofer, C, Berveiller, D, Billesbach, D, Black, TA, Blanken, PD, Bohrer, G, Boike, J, Bolstad, PV, Bonal, D, Bonnefond, J-M, Bowling, DR, Bracho, R, Brodeur, J, Bruemmer, C, Buchmann, N, Burban, B, Burns, SP, Buysse, P, Cale, P, Cavagna, M, Cellier, P, Chen, S, Chini, I, Christensen, TR, Cleverly, J, Collalti, A, Consalvo, C, Cook, BD, Cook, D, Coursolle, C, Cremonese, E, Curtis, PS, D'Andrea, E, da Rocha, H, Dai, X, Davis, KJ, De Cinti, B, de Grandcourt, A, De Ligne, A, De Oliveira, RC, Delpierre, N, Desai, AR, Di Bella, CM, di Tommasi, P, Dolman, H, Domingo, F, Dong, G, Dore, S, Duce, P, Dufrene, E, Dunn, A, Dusek, J, Eamus, D, Eichelmann, U, ElKhidir, HAM, Eugster, W, Ewenz, CM, Ewers, B, Famulari, D, Fares, S, Feigenwinter, I, Feitz, A, Fensholt, R, Filippa, G, Fischer, M, Frank, J, Galvagno, M, Gharun, M, Gianelle, D, Gielen, B, Gioli, B, Gitelson, A, Goded, I, Goeckede, M, Goldstein, AH, Gough, CM, Goulden, ML, Graf, A, Griebel, A, Gruening, C, Gruenwald, T, Hammerle, A, Han, S, Han, X, Hansen, BU, Hanson, C, Hatakka, J, He, Y, Hehn, M, Heinesch, B, Hinko-Najera, N, Hoertnagl, L, Hutley, L, Ibrom, A, Ikawa, H, Jackowicz-Korczynski, M, Janous, D, Jans, W, Jassal, R, Jiang, S, Kato, T, Khomik, M, Klatt, J, Knohl, A, Knox, S, Kobayashi, H, Koerber, G, Kolle, O, Kosugi, Y, Kotani, A, Kowalski, A, Kruijt, B, Kurbatova, J, Kutsch, WL, Kwon, H, Launiainen, S, Laurila, T, Law, B, Leuning, R, Li, Y, Liddell, M, Limousin, J-M, Lion, M, Liska, AJ, Lohila, A, Lopez-Ballesteros, A, Lopez-Blanco, E, Loubet, B, Loustau, D, Lucas-Moffat, A, Lueers, J, Ma, S, Macfarlane, C, Magliulo, V, Maier, R, Mammarella, I, Manca, G, Marcolla, B, Margolis, HA, Marras, S, Massman, W, Mastepanov, M, Matamala, R, Matthes, JH, Mazzenga, F, McCaughey, H, McHugh, I, McMillan, AMS, Merbold, L, Meyer, W, Meyers, T, Miller, SD, Minerbi, S, Moderow, U, Monson, RK, Montagnani, L, Moore, CE, Moors, E, Moreaux, V, Moureaux, C, Munger, JW, Nakai, T, Neirynck, J, Nesic, Z, Nicolini, G, Noormets, A, Northwood, M, Nosetto, M, Nouvellon, Y, Novick, K, Oechel, W, Olesen, JE, Ourcival, J-M, Papuga, SA, Parmentier, F-J, Paul-Limoges, E, Pavelka, M, Peichl, M, Pendall, E, Phillips, RP, Pilegaard, K, Pirk, N, Posse, G, Powell, T, Prasse, H, Prober, SM, Rambal, S, Rannik, U, Raz-Yaseef, N, Reed, D, de Dios, VR, Restrepo-Coupe, N, Reverter, BR, Roland, M, Sabbatini, S, Sachs, T, Saleska, SR, Sanchez-Canete, EP, Sanchez-Mejia, ZM, Schmid, HP, Schmidt, M, Schneider, K, Schrader, F, Schroder, I, Scott, RL, Sedlak, P, Serrano-Ortiz, P, Shao, C, Shi, P, Shironya, I, Siebicke, L, Sigut, L, Silberstein, R, Sirca, C, Spano, D, Steinbrecher, R, Stevens, RM, Sturtevant, C, Suyker, A, Tagesson, T, Takanashi, S, Tang, Y, Tapper, N, Thom, J, Tiedemann, F, Tomassucci, M, Tuovinen, J-P, Urbanski, S, Valentini, R, van der Molen, M, van Gorsel, E, van Huissteden, K, Varlagin, A, Verfaillie, J, Vesala, T, Vincke, C, Vitale, D, Vygodskaya, N, Walker, JP, Walter-Shea, E, Wang, H, Weber, R, Westermann, S, Wille, C, Wofsy, S, Wohlfahrt, G, Wolf, S, Woodgate, W, Zampedri, R, Zhang, J, Zhou, G, Zona, D, Agarwal, D, Biraud, S, Torn, M, and Papale, D
Abstract: The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.
Published: 2020

13. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Author: Pastorello, G. (Gilberto), Trotta, C. (Carlo), Canfora, E. (Eleonora), Chu, H. (Housen), Christianson, D. (Danielle), Cheah, Y.-W. (You-Wei), Poindexter, C. (Cristina), Chen, J. (Jiquan), Elbashandy, A. (Abdelrahman), Humphrey, M. (Marty), Isaac, P. (Peter), Polidori, D. (Diego), Ribeca, A. (Alessio), van Ingen, C. (Catharine), Zhang, L. (Leiming), Amiro, B. (Brian), Ammann, C. (Christof), Arain, M. A. (M. Altaf), Ardo, J. (Jonas), Arkebauer, T. (Timothy), Arndt, S. K. (Stefan K.), Arriga, N. (Nicola), Aubinet, M. (Marc), Aurela, M. (Mika), Baldocchi, D. (Dennis), Barr, A. (Alan), Beamesderfer, E. (Eric), Marchesini, L. B. (Luca Belelli), Bergeron, O. (Onil), Beringer, J. (Jason), Bernhofer, C. (Christian), Berveiller, D. (Daniel), Billesbach, D. (Dave), Black, T. A. (Thomas Andrew), Blanken, P. D. (Peter D.), Bohrer, G. (Gil), Boike, J. (Julia), Bolstad, P. V. (Paul V.), Bonal, D. (Damien), Bonnefond, J.-M. (Jean-Marc), Bowling, D. R. (David R.), Bracho, R. (Rosvel), Brodeur, J. (Jason), Bruemmer, C. (Christian), Buchmann, N. (Nina), Burban, B. (Benoit), Burns, S. P. (Sean P.), Buysse, P. (Pauline), Cale, P. (Peter), Cavagna, M. (Mauro), Cellier, P. (Pierre), Chen, S. (Shiping), Chini, I. (Isaac), Christensen, T. R. (Torben R.), Cleverly, J. (James), Collalti, A. (Alessio), Consalvo, C. (Claudia), Cook, B. D. (Bruce D.), Cook, D. (David), Coursolle, C. (Carole), Cremonese, E. (Edoardo), Curtis, P. S. (Peter S.), D'Andrea, E. (Ettore), da Rocha, H. (Humberto), Dai, X. (Xiaoqin), Davis, K. J. (Kenneth J.), De Cinti, B. (Bruno), de Grandcourt, A. (Agnes), De Ligne, A. (Anne), De Oliveira, R. C. (Raimundo C.), Delpierre, N. (Nicolas), Desai, A. R. (Ankur R.), Di Bella, C. M. (Carlos Marcelo), di Tommasi, P. (Paul), Dolman, H. (Han), Domingo, F. (Francisco), Dong, G. (Gang), Dore, S. (Sabina), Duce, P. (Pierpaolo), Dufrene, E. (Eric), Dunn, A. (Allison), Dusek, J. (Jiri), Eamus, D. (Derek), Eichelmann, U. (Uwe), ElKhidir, H. A. (Hatim Abdalla M.), Eugster, W. (Werner), Ewenz, C. M. (Cacilia M.), Ewers, B. (Brent), Famulari, D. (Daniela), Fares, S. (Silvano), Feigenwinter, I. (Iris), Feitz, A. (Andrew), Fensholt, R. (Rasmus), Filippa, G. (Gianluca), Fischer, M. (Marc), Frank, J. (John), Galvagno, M. (Marta), Gharun, M. (Mana), Gianelle, D. (Damiano), Gielen, B. (Bert), Gioli, B. (Beniamino), Gitelson, A. (Anatoly), Goded, I. (Ignacio), Goeckede, M. (Mathias), Goldstein, A. H. (Allen H.), Gough, C. M. (Christopher M.), Goulden, M. L. (Michael L.), Graf, A. (Alexander), Griebel, A. (Anne), Gruening, C. (Carsten), Gruenwald, T. (Thomas), Hammerle, A. (Albin), Han, S. (Shijie), Han, X. (Xingguo), Hansen, B. U. (Birger Ulf), Hanson, C. (Chad), Hatakka, J. (Juha), He, Y. (Yongtao), Hehn, M. (Markus), Heinesch, B. (Bernard), Hinko-Najera, N. (Nina), Hoertnagl, L. (Lukas), Hutley, L. (Lindsay), Ibrom, A. (Andreas), Ikawa, H. (Hiroki), Jackowicz-Korczynski, M. (Marcin), Janous, D. (Dalibor), Jans, W. (Wilma), Jassal, R. (Rachhpal), Jiang, S. (Shicheng), Kato, T. (Tomomichi), Khomik, M. (Myroslava), Klatt, J. (Janina), Knohl, A. (Alexander), Knox, S. (Sara), Kobayashi, H. (Hideki), Koerber, G. (Georgia), Kolle, O. (Olaf), Kosugi, Y. (Yoshiko), Kotani, A. (Ayumi), Kowalski, A. (Andrew), Kruijt, B. (Bart), Kurbatova, J. (Julia), Kutsch, W. L. (Werner L.), Kwon, H. (Hyojung), Launiainen, S. (Samuli), Laurila, T. (Tuomas), Law, B. (Bev), Leuning, R. (Ray), Li, Y. (Yingnian), Liddell, M. (Michael), Limousin, J.-M. (Jean-Marc), Lion, M. (Marryanna), Liska, A. J. (Adam J.), Lohila, A. (Annalea), Lopez-Ballesteros, A. (Ana), Lopez-Blanco, E. (Efren), Loubet, B. (Benjamin), Loustau, D. (Denis), Lucas-Moffat, A. (Antje), Lueers, J. (Johannes), Ma, S. (Siyan), Macfarlane, C. (Craig), Magliulo, V. (Vincenzo), Maier, R. (Regine), Mammarella, I. (Ivan), Manca, G. (Giovanni), Marcolla, B. (Barbara), Margolis, H. A. (Hank A.), Marras, S. (Serena), Massman, W. (William), Mastepanov, M. (Mikhail), Matamala, R. (Roser), Matthes, J. H. (Jaclyn Hatala), Mazzenga, F. (Francesco), McCaughey, H. (Harry), McHugh, I. (Ian), McMillan, A. M. (Andrew M. S.), Merbold, L. (Lutz), Meyer, W. (Wayne), Meyers, T. (Tilden), Miller, S. D. (Scott D.), Minerbi, S. (Stefano), Moderow, U. (Uta), Monson, R. K. (Russell K.), Montagnani, L. (Leonardo), Moore, C. E. (Caitlin E.), Moors, E. (Eddy), Moreaux, V. (Virginie), Moureaux, C. (Christine), Munger, J. W. (J. William), Nakai, T. (Taro), Neirynck, J. (Johan), Nesic, Z. (Zoran), Nicolini, G. (Giacomo), Noormets, A. (Asko), Northwood, M. (Matthew), Nosetto, M. (Marcelo), Nouvellon, Y. (Yann), Novick, K. (Kimberly), Oechel, W. (Walter), Olesen, J. E. (Jorgen Eivind), Ourcival, J.-M. (Jean-Marc), Papuga, S. A. (Shirley A.), Parmentier, F.-J. (Frans-Jan), Paul-Limoges, E. (Eugenie), Pavelka, M. (Marian), Peichl, M. (Matthias), Pendall, E. (Elise), Phillips, R. P. (Richard P.), Pilegaard, K. (Kim), Pirk, N. (Norbert), Posse, G. (Gabriela), Powell, T. (Thomas), Prasse, H. (Heiko), Prober, S. M. (Suzanne M.), Rambal, S. (Serge), Rannik, U. (Ullar), Raz-Yaseef, N. (Naama), Reed, D. (David), de Dios, V. R. (Victor Resco), Restrepo-Coupe, N. (Natalia), Reverter, B. R. (Borja R.), Roland, M. (Marilyn), Sabbatini, S. (Simone), Sachs, T. (Torsten), Saleska, S. R. (Scott R.), Sanchez-Canete, E. P. (Enrique P.), Sanchez-Mejia, Z. M. (Zulia M.), Schmid, H. P. (Hans Peter), Schmidt, M. (Marius), Schneider, K. (Karl), Schrader, F. (Frederik), Schroder, I. (Ivan), Scott, R. L. (Russell L.), Sedlak, P. (Pavel), Serrano-Ortiz, P. (Penelope), Shao, C. (Changliang), Shi, P. (Peili), Shironya, I. (Ivan), Siebicke, L. (Lukas), Sigut, L. (Ladislav), Silberstein, R. (Richard), Sirca, C. (Costantino), Spano, D. (Donatella), Steinbrecher, R. (Rainer), Stevens, R. M. (Robert M.), Sturtevant, C. (Cove), Suyker, A. (Andy), Tagesson, T. (Torbern), Takanashi, S. (Satoru), Tang, Y. (Yanhong), Tapper, N. (Nigel), Thom, J. (Jonathan), Tiedemann, F. (Frank), Tomassucci, M. (Michele), Tuovinen, J.-P. (Juha-Pekka), Urbanski, S. (Shawn), Valentini, R. (Riccardo), van der Molen, M. (Michiel), van Gorsel, E. (Eva), van Huissteden, K. (Ko), Varlagin, A. (Andrej), Verfaillie, J. (Joseph), Vesala, T. (Timo), Vincke, C. (Caroline), Vitale, D. (Domenico), Vygodskaya, N. (Natalia), Walker, J. P. (Jeffrey P.), Walter-Shea, E. (Elizabeth), Wang, H. (Huimin), Weber, R. (Robin), Westermann, S. (Sebastian), Wille, C. (Christian), Wofsy, S. (Steven), Wohlfahrt, G. (Georg), Wolf, S. (Sebastian), Woodgate, W. (William), Li, Y. (Yuelin), Zampedri, R. (Roberto), Zhang, J. (Junhui), Zhou, G. (Guoyi), Zona, D. (Donatella), Agarwal, D. (Deb), Biraud, S. (Sebastien), Torn, M. (Margaret), Papale, D. (Dario), Pastorello, G. (Gilberto), Trotta, C. (Carlo), Canfora, E. (Eleonora), Chu, H. (Housen), Christianson, D. (Danielle), Cheah, Y.-W. (You-Wei), Poindexter, C. (Cristina), Chen, J. (Jiquan), Elbashandy, A. (Abdelrahman), Humphrey, M. (Marty), Isaac, P. (Peter), Polidori, D. (Diego), Ribeca, A. (Alessio), van Ingen, C. (Catharine), Zhang, L. (Leiming), Amiro, B. (Brian), Ammann, C. (Christof), Arain, M. A. (M. Altaf), Ardo, J. (Jonas), Arkebauer, T. (Timothy), Arndt, S. K. (Stefan K.), Arriga, N. (Nicola), Aubinet, M. (Marc), Aurela, M. (Mika), Baldocchi, D. (Dennis), Barr, A. (Alan), Beamesderfer, E. (Eric), Marchesini, L. B. (Luca Belelli), Bergeron, O. (Onil), Beringer, J. (Jason), Bernhofer, C. (Christian), Berveiller, D. (Daniel), Billesbach, D. (Dave), Black, T. A. (Thomas Andrew), Blanken, P. D. (Peter D.), Bohrer, G. (Gil), Boike, J. (Julia), Bolstad, P. V. (Paul V.), Bonal, D. (Damien), Bonnefond, J.-M. (Jean-Marc), Bowling, D. R. (David R.), Bracho, R. (Rosvel), Brodeur, J. (Jason), Bruemmer, C. (Christian), Buchmann, N. (Nina), Burban, B. (Benoit), Burns, S. P. (Sean P.), Buysse, P. (Pauline), Cale, P. (Peter), Cavagna, M. (Mauro), Cellier, P. (Pierre), Chen, S. (Shiping), Chini, I. (Isaac), Christensen, T. R. (Torben R.), Cleverly, J. (James), Collalti, A. (Alessio), Consalvo, C. (Claudia), Cook, B. D. (Bruce D.), Cook, D. (David), Coursolle, C. (Carole), Cremonese, E. (Edoardo), Curtis, P. S. (Peter S.), D'Andrea, E. (Ettore), da Rocha, H. (Humberto), Dai, X. (Xiaoqin), Davis, K. J. (Kenneth J.), De Cinti, B. (Bruno), de Grandcourt, A. (Agnes), De Ligne, A. (Anne), De Oliveira, R. C. (Raimundo C.), Delpierre, N. (Nicolas), Desai, A. R. (Ankur R.), Di Bella, C. M. (Carlos Marcelo), di Tommasi, P. (Paul), Dolman, H. (Han), Domingo, F. (Francisco), Dong, G. (Gang), Dore, S. (Sabina), Duce, P. (Pierpaolo), Dufrene, E. (Eric), Dunn, A. (Allison), Dusek, J. (Jiri), Eamus, D. (Derek), Eichelmann, U. (Uwe), ElKhidir, H. A. (Hatim Abdalla M.), Eugster, W. (Werner), Ewenz, C. M. (Cacilia M.), Ewers, B. (Brent), Famulari, D. (Daniela), Fares, S. (Silvano), Feigenwinter, I. (Iris), Feitz, A. (Andrew), Fensholt, R. (Rasmus), Filippa, G. (Gianluca), Fischer, M. (Marc), Frank, J. (John), Galvagno, M. (Marta), Gharun, M. (Mana), Gianelle, D. (Damiano), Gielen, B. (Bert), Gioli, B. (Beniamino), Gitelson, A. (Anatoly), Goded, I. (Ignacio), Goeckede, M. (Mathias), Goldstein, A. H. (Allen H.), Gough, C. M. (Christopher M.), Goulden, M. L. (Michael L.), Graf, A. (Alexander), Griebel, A. (Anne), Gruening, C. (Carsten), Gruenwald, T. (Thomas), Hammerle, A. (Albin), Han, S. (Shijie), Han, X. (Xingguo), Hansen, B. U. (Birger Ulf), Hanson, C. (Chad), Hatakka, J. (Juha), He, Y. (Yongtao), Hehn, M. (Markus), Heinesch, B. (Bernard), Hinko-Najera, N. (Nina), Hoertnagl, L. (Lukas), Hutley, L. (Lindsay), Ibrom, A. (Andreas), Ikawa, H. (Hiroki), Jackowicz-Korczynski, M. (Marcin), Janous, D. (Dalibor), Jans, W. (Wilma), Jassal, R. (Rachhpal), Jiang, S. (Shicheng), Kato, T. (Tomomichi), Khomik, M. (Myroslava), Klatt, J. (Janina), Knohl, A. (Alexander), Knox, S. (Sara), Kobayashi, H. (Hideki), Koerber, G. (Georgia), Kolle, O. (Olaf), Kosugi, Y. (Yoshiko), Kotani, A. (Ayumi), Kowalski, A. (Andrew), Kruijt, B. (Bart), Kurbatova, J. (Julia), Kutsch, W. L. (Werner L.), Kwon, H. (Hyojung), Launiainen, S. (Samuli), Laurila, T. (Tuomas), Law, B. (Bev), Leuning, R. (Ray), Li, Y. (Yingnian), Liddell, M. (Michael), Limousin, J.-M. (Jean-Marc), Lion, M. (Marryanna), Liska, A. J. (Adam J.), Lohila, A. (Annalea), Lopez-Ballesteros, A. (Ana), Lopez-Blanco, E. (Efren), Loubet, B. (Benjamin), Loustau, D. (Denis), Lucas-Moffat, A. (Antje), Lueers, J. (Johannes), Ma, S. (Siyan), Macfarlane, C. (Craig), Magliulo, V. (Vincenzo), Maier, R. (Regine), Mammarella, I. (Ivan), Manca, G. (Giovanni), Marcolla, B. (Barbara), Margolis, H. A. (Hank A.), Marras, S. (Serena), Massman, W. (William), Mastepanov, M. (Mikhail), Matamala, R. (Roser), Matthes, J. H. (Jaclyn Hatala), Mazzenga, F. (Francesco), McCaughey, H. (Harry), McHugh, I. (Ian), McMillan, A. M. (Andrew M. S.), Merbold, L. (Lutz), Meyer, W. (Wayne), Meyers, T. (Tilden), Miller, S. D. (Scott D.), Minerbi, S. (Stefano), Moderow, U. (Uta), Monson, R. K. (Russell K.), Montagnani, L. (Leonardo), Moore, C. E. (Caitlin E.), Moors, E. (Eddy), Moreaux, V. (Virginie), Moureaux, C. (Christine), Munger, J. W. (J. William), Nakai, T. (Taro), Neirynck, J. (Johan), Nesic, Z. (Zoran), Nicolini, G. (Giacomo), Noormets, A. (Asko), Northwood, M. (Matthew), Nosetto, M. (Marcelo), Nouvellon, Y. (Yann), Novick, K. (Kimberly), Oechel, W. (Walter), Olesen, J. E. (Jorgen Eivind), Ourcival, J.-M. (Jean-Marc), Papuga, S. A. (Shirley A.), Parmentier, F.-J. (Frans-Jan), Paul-Limoges, E. (Eugenie), Pavelka, M. (Marian), Peichl, M. (Matthias), Pendall, E. (Elise), Phillips, R. P. (Richard P.), Pilegaard, K. (Kim), Pirk, N. (Norbert), Posse, G. (Gabriela), Powell, T. (Thomas), Prasse, H. (Heiko), Prober, S. M. (Suzanne M.), Rambal, S. (Serge), Rannik, U. (Ullar), Raz-Yaseef, N. (Naama), Reed, D. (David), de Dios, V. R. (Victor Resco), Restrepo-Coupe, N. (Natalia), Reverter, B. R. (Borja R.), Roland, M. (Marilyn), Sabbatini, S. (Simone), Sachs, T. (Torsten), Saleska, S. R. (Scott R.), Sanchez-Canete, E. P. (Enrique P.), Sanchez-Mejia, Z. M. (Zulia M.), Schmid, H. P. (Hans Peter), Schmidt, M. (Marius), Schneider, K. (Karl), Schrader, F. (Frederik), Schroder, I. (Ivan), Scott, R. L. (Russell L.), Sedlak, P. (Pavel), Serrano-Ortiz, P. (Penelope), Shao, C. (Changliang), Shi, P. (Peili), Shironya, I. (Ivan), Siebicke, L. (Lukas), Sigut, L. (Ladislav), Silberstein, R. (Richard), Sirca, C. (Costantino), Spano, D. (Donatella), Steinbrecher, R. (Rainer), Stevens, R. M. (Robert M.), Sturtevant, C. (Cove), Suyker, A. (Andy), Tagesson, T. (Torbern), Takanashi, S. (Satoru), Tang, Y. (Yanhong), Tapper, N. (Nigel), Thom, J. (Jonathan), Tiedemann, F. (Frank), Tomassucci, M. (Michele), Tuovinen, J.-P. (Juha-Pekka), Urbanski, S. (Shawn), Valentini, R. (Riccardo), van der Molen, M. (Michiel), van Gorsel, E. (Eva), van Huissteden, K. (Ko), Varlagin, A. (Andrej), Verfaillie, J. (Joseph), Vesala, T. (Timo), Vincke, C. (Caroline), Vitale, D. (Domenico), Vygodskaya, N. (Natalia), Walker, J. P. (Jeffrey P.), Walter-Shea, E. (Elizabeth), Wang, H. (Huimin), Weber, R. (Robin), Westermann, S. (Sebastian), Wille, C. (Christian), Wofsy, S. (Steven), Wohlfahrt, G. (Georg), Wolf, S. (Sebastian), Woodgate, W. (William), Li, Y. (Yuelin), Zampedri, R. (Roberto), Zhang, J. (Junhui), Zhou, G. (Guoyi), Zona, D. (Donatella), Agarwal, D. (Deb), Biraud, S. (Sebastien), Torn, M. (Margaret), and Papale, D. (Dario)
Abstract: The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.
Published: 2020

14. Carbon-nitrogen interactions in European forests and semi-natural vegetation - Part 2: Untangling climatic, edaphic, management and nitrogen deposition effects on carbon sequestration potentials

Author: Flechard, C. R., Van Oijen, M., Cameron, D. R., De Vries, W., Ibrom, A., Buchmann, N., DIse, N. B., Janssens, I. A., Neirynck, J., Montagnani, L., Varlagin, A., Loustau, D., Legout, A., Ziemblińska, K., Aubinet, M., Aurela, M., Chojnicki, B. H., Drewer, J., Eugster, W., Francez, A. J., Juszczak, R., Kitzler, B., Kutsch, W. L., Lohila, A., Longdoz, B., Matteucci, G., Moreaux, V., Neftel, A., Olejnik, J., Sanz, M. J., Siemens, J., Vesala, T., Vincke, C., Nemitz, E., Zechmeister-Boltenstern, S., Butterbach-Bahl, K., Skiba, U. M., Sutton, M. A., Flechard, C. R., Van Oijen, M., Cameron, D. R., De Vries, W., Ibrom, A., Buchmann, N., DIse, N. B., Janssens, I. A., Neirynck, J., Montagnani, L., Varlagin, A., Loustau, D., Legout, A., Ziemblińska, K., Aubinet, M., Aurela, M., Chojnicki, B. H., Drewer, J., Eugster, W., Francez, A. J., Juszczak, R., Kitzler, B., Kutsch, W. L., Lohila, A., Longdoz, B., Matteucci, G., Moreaux, V., Neftel, A., Olejnik, J., Sanz, M. J., Siemens, J., Vesala, T., Vincke, C., Nemitz, E., Zechmeister-Boltenstern, S., Butterbach-Bahl, K., Skiba, U. M., and Sutton, M. A.
Abstract: "The effects of atmospheric nitrogen deposition (N-dep) on carbon (C) sequestration in forests have often been assessed by relating differences in productivity to spatial variations of N-dep across a large geographic domain. These correlations generally suffer from covariation of other confounding variables related to climate and other growth-limiting factors, as well as large uncertainties in total (dry + wet) reactive nitrogen (N-r) deposition. We propose a methodology for untangling the effects of N-dep from those of meteorological variables, soil water retention capacity and stand age, using a mechanistic forest growth model in combination with eddy covariance CO2 exchange fluxes from a Europe-wide network of 22 forest flux towers. Total N-r deposition rates were estimated from local measurements as far as possible. The forest data were compared with data from natural or semi-natural, non-woody vegetation sites. The response of forest net ecosystem productivity to nitrogen deposition (dNEP/dN(dep)) was estimated after accounting for the effects on gross primary productivity (GPP) of the co-correlates by means of a meta-modelling standardization procedure, which resulted in a reduction by a factor of about 2 of the uncorrected, apparent dGPP/dN(dep) value. This model-enhanced analysis of the C and N-dep flux observations at the scale of the European network suggests a mean overall dNEP/dN(dep) response of forest lifetime C sequestration to N-dep of the order of 40-50 g C per g N, which is slightly larger but not significantly different from the range of estimates published in the most recent reviews. Importantly, patterns of gross primary and net ecosystem productivity versus N-dep were non-linear, with no further growth responses at high N-dep levels (N-dep > 2.5-3 gNm(-2) yr(-1)) but accompanied by increasingly large ecosystem N losses by leaching and gaseous emissions. The reduced increase in productivity per unit N deposited at high N-dep levels implies that
Published: 2020

15. Altered energy partitioning across terrestrial ecosystems in the European drought year 2018

Author: Graf, A., Klosterhalfen, A., Arriga, N., Bernhofer, C., Bogena, H., Bornet, F., Brüggemann, N., Brümmer, C., Buchmann, N., Chi, J., Chipeaux, C., Cremonese, E., Cuntz, M., Dušek, J., El-Madany, T.S., Fares, S., Fischer, M., Foltýnová, L., Gharun, M., Ghiasi, S., Gielen, B., Gottschalk, P., Grünwald, T., Heinemann, G., Heinesch, B., Heliasz, M., Holst, J., Hörtnagl, L., Ibrom, A., Ingwersen, J., Jurasinski, G., Klatt, J., Knohl, A., Koebsch, F., Konopka, J., Korkiakoski, M., Kowalska, N., Kremer, P., Kruijt, B., Lafont, S., Léonard, J., de Ligne, A., Longdoz, B., Loustau, D., Magliulo, V., Mammarella, I., Manca, G., Mauder, M., Migliavacca, M., Mölder, M., Neirynck, J., Ney, P., Nilsson, M., Paul-Limoges, E., Peichl, M., Pitacco, A., Poyda, A., Rebmann, Corinna, Roland, M., Sachs, T., Schmidt, M., Schrader, F., Siebicke, L., Šigut, L., Tuittila, E.-S., Varlagin, A., Vendrame, N., Vincke, C., Völksch, I., Weber, S., Wille, C., Wizemann, H.-D., Zeeman, M., Vereecken, H., Graf, A., Klosterhalfen, A., Arriga, N., Bernhofer, C., Bogena, H., Bornet, F., Brüggemann, N., Brümmer, C., Buchmann, N., Chi, J., Chipeaux, C., Cremonese, E., Cuntz, M., Dušek, J., El-Madany, T.S., Fares, S., Fischer, M., Foltýnová, L., Gharun, M., Ghiasi, S., Gielen, B., Gottschalk, P., Grünwald, T., Heinemann, G., Heinesch, B., Heliasz, M., Holst, J., Hörtnagl, L., Ibrom, A., Ingwersen, J., Jurasinski, G., Klatt, J., Knohl, A., Koebsch, F., Konopka, J., Korkiakoski, M., Kowalska, N., Kremer, P., Kruijt, B., Lafont, S., Léonard, J., de Ligne, A., Longdoz, B., Loustau, D., Magliulo, V., Mammarella, I., Manca, G., Mauder, M., Migliavacca, M., Mölder, M., Neirynck, J., Ney, P., Nilsson, M., Paul-Limoges, E., Peichl, M., Pitacco, A., Poyda, A., Rebmann, Corinna, Roland, M., Sachs, T., Schmidt, M., Schrader, F., Siebicke, L., Šigut, L., Tuittila, E.-S., Varlagin, A., Vendrame, N., Vincke, C., Völksch, I., Weber, S., Wille, C., Wizemann, H.-D., Zeeman, M., and Vereecken, H.
Abstract: Drought and heat events, such as the 2018 European drought, interact with the exchange of energy between the land surface and the atmosphere, potentially affecting albedo, sensible and latent heat fluxes, as well as CO2 exchange. Each of these quantities may aggravate or mitigate the drought, heat, their side effects on productivity, water scarcity and global warming. We used measurements of 56 eddy covariance sites across Europe to examine the response of fluxes to extreme drought prevailing most of the year 2018 and how the response differed across various ecosystem types (forests, grasslands, croplands and peatlands). Each component of the surface radiation and energy balance observed in 2018 was compared to available data per site during a reference period 2004–2017. Based on anomalies in precipitation and reference evapotranspiration, we classified 46 sites as drought affected. These received on average 9% more solar radiation and released 32% more sensible heat to the atmosphere compared to the mean of the reference period. In general, drought decreased net CO2 uptake by 17.8%, but did not significantly change net evapotranspiration. The response of these fluxes differed characteristically between ecosystems; in particular, the general increase in the evaporative index was strongest in peatlands and weakest in croplands.
Published: 2020

16. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

Author: Pastorello G, Trotta C, Canfora E, Chu H, Christianson D, Cheah Y-W, Poindexter C, Chen J, Elbashandy A, Humphrey M, Isaac P, Polidori D, Ribeca A, van Ingen C, Zhang L, Amiro B, Ammann C, Arain MA, Ardö J, Arkebauer T, Arndt SK, Arriga N, Aubinet M, Aurela M, Baldocchi D, Barr A, Beamesderfer E, Marchesini LB, Bergeron O, Beringer J, Bernhofer C, Berveiller D, Billesbach D, Black TA, Blanken PD, Bohrer G, Boike J, Bolstad PV, Bonal D, Bonnefond J-M, Bowling DR, Bracho R, Brodeur J, Brümmer C, Buchmann N, Burban B, Burns SP, Buysse P, Cale P, Cavagna M, Cellier P, Chen S, Chini I, Christensen TR, Cleverly J, Collalti A, Consalvo C, Cook BD, Cook D, Coursolle C, Cremonese E, Curtis PS, D'Andrea E, da Rocha H, Dai X, Davis KJ, De Cinti B, de Grandcourt A, De Ligne A, De Oliveira RC, Delpierre N, Desai AR, Di Bella CM, di Tommasi P, Dolman H, Domingo F, Dong G, Dore S, Duce P, Dufrêne E, Dunn A, Dušek J, Eamus D, Eichelmann U, ElKhidir HAM, Eugster W, Ewenz CM, Ewers B, Famulari D, Fares S, Feigenwinter I, Feitz A, Fensholt R, Filippa G, Fischer M, Frank J, Galvagno M, Gharun M, Gianelle D, Gielen B, Gioli B, Gitelson A, Goded I, Goeckede M, Goldstein AH, Gough CM, Goulden ML, Graf A, Griebel A, Gruening C, Grünwald T, Hammerle A, Han S, Han X, Hansen BU, Hanson C, Hatakka J, He Y, Hehn M, Heinesch B, Hinko-Najera N, Hörtnagl L, Hutley L, Ibrom A, Ikawa H, Jackowicz-Korczynski M, Janouš D, Jans W, Jassal R, Jiang S, Kato T, Khomik M, Klatt J, Knohl A, Knox S, Kobayashi H, Koerber G, Kolle O, Kosugi Y, Kotani A, Kowalski A, Kruijt B, Kurbatova J, Kutsch WL, Kwon H, Launiainen S, Laurila T, Law B, Leuning R, Li Y, Liddell M, Limousin J-M, Lion M, Liska AJ, Lohila A, López-Ballesteros A, López-Blanco E, Loubet B, Loustau D, Lucas-Moffat A, Lüers J, Ma S, Macfarlane C, Magliulo V, Maier R, Mammarella I, Manca G, Marcolla B, Margolis HA, Marras S, Massman W, Mastepanov M, Matamala R, Matthes JH, Mazzenga F, McCaughey H, McHugh I, McMillan AMS, Merbold L, Meyer W, Meyers T, Miller SD, Minerbi S, Moderow U, Monson RK, Montagnani L, Moore CE, Moors E, Moreaux V, Moureaux C, Munger JW, Nakai T, Neirynck J, Nesic Z, Nicolini G, Noormets A, Northwood M, Nosetto M, Nouvellon Y, Novick K, Oechel W, Olesen JE, Ourcival J-M, Papuga SA, Parmentier F-J, Paul-Limoges E, Pavelka M, Peichl M, Pendall E, Phillips RP, Pilegaard K, Pirk N, Posse G, Powell T, Prasse H, Prober SM, Rambal S, Rannik Ü, Raz-Yaseef N, Reed D, de Dios VR, Restrepo-Coupe N, Reverter BR, Roland M, Sabbatini S, Sachs T, Saleska SR, Sánchez-Cañete EP, Sanchez-Mejia ZM, Schmid HP, Schmidt M, Schneider K, Schrader F, Schroder I, Scott RL, Sedlák P, Serrano-Ortíz P, Shao C, Shi P, Shironya I, Siebicke L, Šigut L, Silberstein R, Sirca C, Spano D, Steinbrecher R, Stevens RM, Sturtevant C, Suyker A, Tagesson T, Takanashi S, Tang Y, Tapper N, Thom J, Tiedemann F, Tomassucci M, Tuovinen J-P, Urbanski S, Valentini R, van der Molen M, van Gorsel E, van Huissteden K, Varlagin A, Verfaillie J, Vesala T, Vincke C, Vitale D, Vygodskaya N, Walker JP, Walter-Shea E, Wang H, Weber R, Westermann S, Wille C, Wofsy S, Wohlfahrt G, Wolf S, Woodgate W, Zampedri R, Zhang J, Zhou G, Zona D, Agarwal D, Biraud S, Torn M, Papale D, Pastorello G, Trotta C, Canfora E, Chu H, Christianson D, Cheah Y-W, Poindexter C, Chen J, Elbashandy A, Humphrey M, Isaac P, Polidori D, Ribeca A, van Ingen C, Zhang L, Amiro B, Ammann C, Arain MA, Ardö J, Arkebauer T, Arndt SK, Arriga N, Aubinet M, Aurela M, Baldocchi D, Barr A, Beamesderfer E, Marchesini LB, Bergeron O, Beringer J, Bernhofer C, Berveiller D, Billesbach D, Black TA, Blanken PD, Bohrer G, Boike J, Bolstad PV, Bonal D, Bonnefond J-M, Bowling DR, Bracho R, Brodeur J, Brümmer C, Buchmann N, Burban B, Burns SP, Buysse P, Cale P, Cavagna M, Cellier P, Chen S, Chini I, Christensen TR, Cleverly J, Collalti A, Consalvo C, Cook BD, Cook D, Coursolle C, Cremonese E, Curtis PS, D'Andrea E, da Rocha H, Dai X, Davis KJ, De Cinti B, de Grandcourt A, De Ligne A, De Oliveira RC, Delpierre N, Desai AR, Di Bella CM, di Tommasi P, Dolman H, Domingo F, Dong G, Dore S, Duce P, Dufrêne E, Dunn A, Dušek J, Eamus D, Eichelmann U, ElKhidir HAM, Eugster W, Ewenz CM, Ewers B, Famulari D, Fares S, Feigenwinter I, Feitz A, Fensholt R, Filippa G, Fischer M, Frank J, Galvagno M, Gharun M, Gianelle D, Gielen B, Gioli B, Gitelson A, Goded I, Goeckede M, Goldstein AH, Gough CM, Goulden ML, Graf A, Griebel A, Gruening C, Grünwald T, Hammerle A, Han S, Han X, Hansen BU, Hanson C, Hatakka J, He Y, Hehn M, Heinesch B, Hinko-Najera N, Hörtnagl L, Hutley L, Ibrom A, Ikawa H, Jackowicz-Korczynski M, Janouš D, Jans W, Jassal R, Jiang S, Kato T, Khomik M, Klatt J, Knohl A, Knox S, Kobayashi H, Koerber G, Kolle O, Kosugi Y, Kotani A, Kowalski A, Kruijt B, Kurbatova J, Kutsch WL, Kwon H, Launiainen S, Laurila T, Law B, Leuning R, Li Y, Liddell M, Limousin J-M, Lion M, Liska AJ, Lohila A, López-Ballesteros A, López-Blanco E, Loubet B, Loustau D, Lucas-Moffat A, Lüers J, Ma S, Macfarlane C, Magliulo V, Maier R, Mammarella I, Manca G, Marcolla B, Margolis HA, Marras S, Massman W, Mastepanov M, Matamala R, Matthes JH, Mazzenga F, McCaughey H, McHugh I, McMillan AMS, Merbold L, Meyer W, Meyers T, Miller SD, Minerbi S, Moderow U, Monson RK, Montagnani L, Moore CE, Moors E, Moreaux V, Moureaux C, Munger JW, Nakai T, Neirynck J, Nesic Z, Nicolini G, Noormets A, Northwood M, Nosetto M, Nouvellon Y, Novick K, Oechel W, Olesen JE, Ourcival J-M, Papuga SA, Parmentier F-J, Paul-Limoges E, Pavelka M, Peichl M, Pendall E, Phillips RP, Pilegaard K, Pirk N, Posse G, Powell T, Prasse H, Prober SM, Rambal S, Rannik Ü, Raz-Yaseef N, Reed D, de Dios VR, Restrepo-Coupe N, Reverter BR, Roland M, Sabbatini S, Sachs T, Saleska SR, Sánchez-Cañete EP, Sanchez-Mejia ZM, Schmid HP, Schmidt M, Schneider K, Schrader F, Schroder I, Scott RL, Sedlák P, Serrano-Ortíz P, Shao C, Shi P, Shironya I, Siebicke L, Šigut L, Silberstein R, Sirca C, Spano D, Steinbrecher R, Stevens RM, Sturtevant C, Suyker A, Tagesson T, Takanashi S, Tang Y, Tapper N, Thom J, Tiedemann F, Tomassucci M, Tuovinen J-P, Urbanski S, Valentini R, van der Molen M, van Gorsel E, van Huissteden K, Varlagin A, Verfaillie J, Vesala T, Vincke C, Vitale D, Vygodskaya N, Walker JP, Walter-Shea E, Wang H, Weber R, Westermann S, Wille C, Wofsy S, Wohlfahrt G, Wolf S, Woodgate W, Zampedri R, Zhang J, Zhou G, Zona D, Agarwal D, Biraud S, Torn M, and Papale D
Abstract: The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.
Published: 2020

17. Sampling and collecting foliage elements for the determination of the foliar nutrients in ICOS ecosystem stations

Author: Loustau D., Altimir N., Barbaste M., Gielen B., Jimenez S.M., Klumpp K., Linder S., Matteucci G., Merbold L., De Beek M.O., Soule P., Thimonier A., Vincke C., and Waldner P.
Subjects: foliage nutrient content, ICOS, leaf mass-To-Area ratio, protocol
Abstract: The nutritional status of plant canopies in terms of nutrients (C, N, P, K, Ca, Mg, Mn, Fe, Cu, Zn) exerts a strong influence on the carbon cycle and energy balance of terrestrial ecosystems. Therefore, in order to account for the spatial and temporal variations in nutritional status of the plant species composing the canopy, we detail the methodology applied to achieve consistent time-series of leaf mass to area ratio and nutrient content of the foliage within the footprint of the Integrated Carbon Observation System Ecosystem stations. The guidelines and defi-nitions apply to most terrestrial ecosystems.
Published: 2018

18. Inhibiting the Ca 2+ influx induced by human CSF

Author: Drews, A., De, S., Flagmeier, P., Wirthensohn, D.C., Chen, W.-H., Whiten, D.R., Rodrigues, M., Vincke, C., Muyldermans, S., Paterson, R.W., Slattery, C.F., Fox, N.C., Schott, J.M., Zetterberg, H., Dobson, C.M., Gandhi, S., and Klenerman, D.
Abstract: One potential therapeutic strategy for Alzheimer’s disease (AD) is to use antibodies that bind to small soluble protein aggregates to reduce their toxic effects. However, these therapies are rarely tested in human CSF before clinical trials because of the lack of sensitive methods that enable the measurement of aggregate-induced toxicity at low concentrations. We have developed highly sensitive single vesicle and single-cell-based assays that detect the Ca2+ influx caused by the CSF of individuals affected with AD and healthy controls, and we have found comparable effects for both types of samples. We also show that an extracellular chaperone clusterin; a nanobody specific to the amyloid-β peptide (Aβ); and bapineuzumab, a humanized monoclonal antibody raised against Aβ, could all reduce the Ca2+ influx caused by synthetic Aβ oligomers but are less effective in CSF. These assays could be used to characterize potential therapeutic agents in CSF before clinical trials.
Published: 2017

19. Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe’s terrestrial ecosystems: a review

Author: Franz, D., Acosta, M., Altimir, N., Arriga, N., Arrouays, D., Aubinet, M., Aurela, M., Ayres, E., López-Ballesteros, A., Barbaste, M., Berveiller, D., Biraud, S., Boukir, H., Brown, T., Brümmer, C., Buchmann, N., Burba, G., Carrara, A., Cescatti, A., Ceschia, E., Clement, R., Cremonese, E., Crill, E., Darenova, E., Dengel, S., D’Odorico, P., Filippa, G., Fleck, S., Fratini, G., Fuß, R., Gielen, B., Gogo, S., Grace, J., Graf, A., Grelle, A., Gross, P., Grünwald, T., Haapanala, S., Hehn, M., Heinesch, B., Heiskanen, J., Herbst, M., Herschlein, C., Hörtnagl, L., Hufkens, K., Ibrom, A., Jolivet, C., Joly, L., Jones, M., Migliavacca, M., Mölder, M., Montagnani, L., Moureaux, C., Nelson, D., Nemitz, E., Nicolini, G., Nilsson, M.B., Op de Beeck, M., Osborne, B., Löfvenius, M.O., Pavelka, M., Peichl, M., Peltola, O., Pihlatie, M., Pitacco, A., Pokorný, R., Pumpanen, J., Ratié, C., Rebmann, Corinna, Roland, M., Sabbatini, S., Saby, N.P.A., Saunders, M., Schmid, H.P., Schrumpf, M., Sedlák, P., Serrano Ortiz, P., Siebicke, L., Šigut, L., Silvennoinen, H., Simioni, G., Skiba, U., Sonnentag, O., Soudani, K., Soulé, P., Steinbrecher, R., Tallec, T., Thimonier, A., Tuittila, E.-S., Tuovinen, J.-P., Vestin, P., Vincent, G., Vincke, C., Vitale, D., Waldner, P., Weslien, P., Wingate, L., Wohlfahrt, G., Zahniser, M., Vesala, T., Franz, D., Acosta, M., Altimir, N., Arriga, N., Arrouays, D., Aubinet, M., Aurela, M., Ayres, E., López-Ballesteros, A., Barbaste, M., Berveiller, D., Biraud, S., Boukir, H., Brown, T., Brümmer, C., Buchmann, N., Burba, G., Carrara, A., Cescatti, A., Ceschia, E., Clement, R., Cremonese, E., Crill, E., Darenova, E., Dengel, S., D’Odorico, P., Filippa, G., Fleck, S., Fratini, G., Fuß, R., Gielen, B., Gogo, S., Grace, J., Graf, A., Grelle, A., Gross, P., Grünwald, T., Haapanala, S., Hehn, M., Heinesch, B., Heiskanen, J., Herbst, M., Herschlein, C., Hörtnagl, L., Hufkens, K., Ibrom, A., Jolivet, C., Joly, L., Jones, M., Migliavacca, M., Mölder, M., Montagnani, L., Moureaux, C., Nelson, D., Nemitz, E., Nicolini, G., Nilsson, M.B., Op de Beeck, M., Osborne, B., Löfvenius, M.O., Pavelka, M., Peichl, M., Peltola, O., Pihlatie, M., Pitacco, A., Pokorný, R., Pumpanen, J., Ratié, C., Rebmann, Corinna, Roland, M., Sabbatini, S., Saby, N.P.A., Saunders, M., Schmid, H.P., Schrumpf, M., Sedlák, P., Serrano Ortiz, P., Siebicke, L., Šigut, L., Silvennoinen, H., Simioni, G., Skiba, U., Sonnentag, O., Soudani, K., Soulé, P., Steinbrecher, R., Tallec, T., Thimonier, A., Tuittila, E.-S., Tuovinen, J.-P., Vestin, P., Vincent, G., Vincke, C., Vitale, D., Waldner, P., Weslien, P., Wingate, L., Wohlfahrt, G., Zahniser, M., and Vesala, T.
Abstract: Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO2, CH4, N2O, H2O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.
Published: 2018

20. Timing of the compensation of winter respiratory carbon losses provides explanatory power for net ecosystem productivity of forests

Author: Haeni, M., Zweifel, R., Eugster, W., Gessler, A., Zielis, S., Bernhofer, C., Carrara, A., Grünwald, T., Havránková, K., Heinesch, B., Herbst, M., Ibrom, Andreas, Knohl, A., Lagergren, F., Law, B. E., Marek, M., Matteucci, G., McCaughey, J. H., Minerbi, S., Montagnani, L., Moors, E., Olejnik, J., Pavelka, M., Pilegaard, Kim, Pita, G., Rodrigues, A., Sanz Sánchez, M. J., Schelhaas, M.-J., Urbaniak, M., Valentini, R., Varlagin, A., Vesala, T., Vincke, C., Wu, J., and Buchmann, N.
Subjects: SDG 13 - Climate Action
Abstract: Accurate predictions of net ecosystem productivity (NEPc) of forest ecosystems are essential for climate change decisions and requirements in the context of national forest growth and greenhouse gas inventories. However, drivers and underlying mechanisms determining NEPc (e.g. climate, nutrients) are not entirely understood yet, particularly when considering the influence of past periods.Here we explored the explanatory power of the compensation day (cDOY) —defined as the day of year when winter net carbon losses are compensated by spring assimilation— for NEPc in 26 forests in Europe, North America, and Australia, using different NEPc integration methods.We found cDOY to be a particularly powerful predictor for NEPc of temperate evergreen needle-leaf forests (R2 = 0.58) and deciduous broadleaf forests (R2 = 0.68). In general, the latest cDOY correlated with the lowest NEPc. The explanatory power of cDOY depended on the integration method for NEPc, forest type, and whether the site had a distinct winter net respiratory carbon loss or not. The integration methods starting in autumn led to better predictions of NEPc from cDOY then the classical calendar method starting at January 1. Limited explanatory power of cDOY for NEPc was found for warmer sites with no distinct winter respiratory loss period.Our findings highlight the importance of the influence of winter processes and the delayed responses of previous seasons’ climatic conditions on current year's NEPc. Such carry-over effects may contain information from climatic conditions, carbon storage levels and hydraulic traits of several years back in time.
Published: 2017

21. Winter respiratory C losses provide explanatory power for net ecosystem productivity

Author: Haeni, M., Zweifel, R., Eugster, W., Gessler, A., Zielis, S., Bernhofer, C., Carrara, A., Gruenwald, T., Havrankova, K., Heinesch, B., Herbst, M., Ibrom, A., Knohl, A., Lagergren, F., Law, B. E., Marek, M., Matteucci, G., Mccaughey, J. H., Minerbi, S., Montagnani, L., Moors, E., Olejnik, J., Marian Pavelka, Pilegaard, K., Pita, G., Rodrigues, A., Sanz Sanchez, M. J., Schelhaas, M. -J, Urbaniak, M., Valentini, R., Varlagin, A., Vesala, T., Vincke, C., Wu, J., Buchmann, N., Earth and Climate, Department of Physics, Ecosystem processes (INAR Forest Sciences), Department of Forest Sciences, and Micrometeorology and biogeochemical cycles
Subjects: LEAF CHARACTERISTICS, 4112 Forestry, CO2 exchange, CO exchange, SPACEBORNE IMAGING SPECTROSCOPY, 114 Physical sciences, growing season length, TEMPERATE DECIDUOUS FOREST, BEECH FAGUS-SYLVATICA, Carbon sink, Carbon source, Eddy covariance, Growing season length, Winter respiration, carbon sink, STEM RADIUS CHANGES, carbon source, eddy covariance, winter respiration, MIXEDWOOD BOREAL FOREST, SDG 13 - Climate Action, WATER-VAPOR EXCHANGE, CARBON UPTAKE, INTERANNUAL VARIABILITY, PHOTOSYNTHETIC CAPACITY, 1172 Environmental sciences
Abstract: Accurate predictions of net ecosystem productivity (NEPc) of forest ecosystems are essential for climate change decisions and requirements in the context of national forest growth and greenhouse gas inventories. However, drivers and underlying mechanisms determining NEPc (e.g., climate and nutrients) are not entirely understood yet, particularly when considering the influence of past periods. Here we explored the explanatory power of the compensation day (cDOY)—defined as the day of year when winter net carbon losses are compensated by spring assimilation—for NEPc in 26 forests in Europe, North America, and Australia, using different NEPc integration methods. We found cDOY to be a particularly powerful predictor for NEPc of temperate evergreen needleleaf forests (R2 = 0.58) and deciduous broadleaf forests (R2 = 0.68). In general, the latest cDOY correlated with the lowest NEPc. The explanatory power of cDOY depended on the integration method for NEPc, forest type, and whether the site had a distinct winter net respiratory carbon loss or not. The integration methods starting in autumn led to better predictions of NEPc from cDOY then the classical calendar method starting 1 January. Limited explanatory power of cDOY for NEPc was found for warmer sites with no distinct winter respiratory loss period. Our findings highlight the importance of the influence of winter processes and the delayed responses of previous seasons' climatic conditions on current year's NEPc. Such carry-over effects may contain information from climatic conditions, carbon storage levels, and hydraulic traits of several years back in time.
Published: 2017

22. Combinatorial Design of a Nanobody that Specifically Targets Structured RNAs

Author: Cawez, F., primary, Duray, E., additional, Hu, Y., additional, Vandenameele, J., additional, Romão, E., additional, Vincke, C., additional, Dumoulin, M., additional, Galleni, M., additional, Muyldermans, S., additional, and Vandevenne, M., additional
Published: 2018
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23. Individual aggregates of amyloid beta induce temporary calcium influx through the cell membrane of neuronal cells;

Author: Drews, A, Flint, J, Shivji, N, Jönsson, P, Wirthensohn, D, De Genst, E, Vincke, C, Muyldermans, S, Dobson, C, Klenerman, D, Department of Bio-engineering Sciences, Cellular and Molecular Immunology, Faculty of Sciences and Bioengineering Sciences, Wirthensohn, David [0000-0003-4403-9436], Klenerman, David [0000-0001-7116-6954], and Apollo - University of Cambridge Repository
Subjects: Neurons, Amyloid beta-Peptides, Photobleaching, Cell Membrane, Carbocyanines, Single-Domain Antibodies, Article, Peptide Fragments, Rats, Protein Aggregates, Clusterin, Microscopy, Fluorescence, Astrocytes, Animals, Calcium, Cells, Cultured
Abstract: Local delivery of amyloid beta oligomers from the tip of a nanopipette, controlled over the cell surface, has been used to deliver physiological pico molar oligomer concentrations to primary astrocytes or neurons. Calcium influx was observed when as few as 2000 oligomers were delivered to the cell surface. When the dosing of oligomers was stopped the intracellular calcium returned to basal levels or below. Calcium influx was prevented by the presence in the pipette of the extracellular chaperone clusterin, which is known to selectively bind oligomers, and by the presence a specific nanobody to amyloid beta. These data are consistent with individual oligomers larger than trimers inducing calcium entry as they cross the cell membrane, a result supported by imaging experiments in bilayers, and suggest that the initial molecular event that leads to neuronal damage does not involve any cellular receptors, in contrast to work performed at much higher oligomer concentrations.
Published: 2016

24. How does forest cover impact water flows and ecosystem services? Insights from “real-life” catchments in Wallonia (Belgium)

Author: Brogna, D., primary, Vincke, C., additional, Brostaux, Y., additional, Soyeurt, H., additional, Dufrêne, M., additional, and Dendoncker, N., additional
Published: 2017
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25. Development of recombinant VHH nanobodies as an alternative for clearance of equine arteritis virus in carrier stallions

Author: Guerrero, M Adúriz, primary, Carossino, M., additional, Go, Y.Y., additional, Vincke, C., additional, Balasuriya, U.B.R., additional, Muyldermans, S., additional, Wigdorovitz, A., additional, Barrandeguy, M.E., additional, and Parreño, V., additional
Published: 2016
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26. Evapotranspiration d'un peuplement de chêne pédonculé (Quercus robur L.) dépérissant, de 1999 à 2001. II. Evapotranspiration réelle et réserve en eau du sol journalières

Author: Vincke, C., Granier, A., Bréda, Nathalie, DEVILLEZ, F., Ecologie et Ecophysiologie Forestières [devient SILVA en 2018] (EEF), and Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL)
Subjects: CHENE PEDONCULE, [SDV.SA.SF]Life Sciences [q-bio]/Agricultural sciences/Silviculture, forestry, DEPERISSEMENT DES FORETS, ComputingMilieux_MISCELLANEOUS, TENEUR EN EAU DU SOL
Abstract: International audience
Published: 2005

27. Evapotranspiration d'un peuplement de chêne pédonculé (Quercus robur L.) dépérissant, de 1999 à 2001. I. Transpiration journalière des arbres et de la strate herbacée

Author: Vincke, C., Bréda, Nathalie, Granier, A., DEVILLEZ, F., Ecologie et Ecophysiologie Forestières [devient SILVA en 2018] (EEF), and Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL)
Subjects: CHENE PEDONCULE, [SDV.SA.SF]Life Sciences [q-bio]/Agricultural sciences/Silviculture, forestry, DEPERISSEMENT DES FORETS, INDICE FOLIAIRE, ComputingMilieux_MISCELLANEOUS
Abstract: International audience
Published: 2005

28. Modelling the mortality of Hylotrupes bajulus (L.) larvae exposed to anoxic treatment for disinfestation of wooden art objects.

Author: Streel, G., Henin, J.-M., Bogaert, P., Mercier, E., Rabelo, E., Vincke, C., and Jourez, B.
Subjects: ART objects, INSECT mortality, WOOD, INSECT larvae, INSECT physiology
Abstract: Experiments were conducted to quantify the effect of several variables on the mortality of insects exposed to an anoxic treatment in order to generate a model linking mortality to these variables. This study aims to explore the possible interest of using such a model to determine the characteristics of treatment (especially duration) needed to guarantee insect mortality with a given level of probability. Trials were performed on Hylotrupes bajulus larvae, which is a widespread species known for its high tolerance to anoxic conditions. The studied variables are the initial mass of the larvae, the treatment temperature (21, 30 and 40 °C), the treatment duration (four durations for each temperature tested) and whether the larva is held in wood or in a petri dish (directly exposed to anoxic atmosphere) during the experiment. It was found that, while the last variable is not correlated with mortality, treatment duration and temperature are significantly and positively correlated with it. Larvae with higher body mass were also shown to have a better resistance to the treatment. Based on these results, a model including insect initial mass, treatment temperature and duration, together with the interaction between these two variables, was determined. This relatively simple model appeared to be a useful tool in overcoming the difficulty in defining the modalities for anoxic treatment in order to reach a given level of mortality. [ABSTRACT FROM AUTHOR]
Published: 2016
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29. Development of Cys38 knock-out and humanized version of NbAahII10 nanobody with improved neutralization of AahII Scorpion toxin

Author: Ben Abderrazek, R., primary, Vincke, C., additional, Hmila, I., additional, Saerens, D., additional, Abidi, N., additional, El Ayeb, M., additional, Muyldermans, S., additional, and Bouhaouala-Zahar, B., additional
Published: 2011
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30. Structure of CabBCII-10 nanobody

Author: Vincke, C., primary, Loris, R., additional, Muyldermans, S., additional, and Conrath, K., additional
Published: 2008
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31. NbBCII10 humanized (FGLA mutant)

Author: Vincke, C., primary, Loris, R., additional, Saerens, D., additional, Martinez-Rodriguez, S., additional, Muyldermans, S., additional, and Conrath, K., additional
Published: 2008
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32. CAbHul6 FGLW mutant (humanized) in complex with human lysozyme

Author: Vincke, C., primary, Loris, R., additional, Saerens, D., additional, Martinez-Rodriguez, S., additional, Muyldermans, S., additional, and Conrath, K., additional
Published: 2008
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33. cAbAn33- Y37V/E44G/R45L triple mutant

Author: Conrath, K., primary, Vincke, C., additional, Stijlemans, B., additional, Schymkowitz, J., additional, Wyns, L., additional, Muyldermans, S., additional, and Loris, R., additional
Published: 2005
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34. cAbAn33 VHH fragment against VSG

Author: Conrath, K., primary, Vincke, C., additional, Stijlemans, B., additional, Schymkowitz, J., additional, Wyns, L., additional, Muyldermans, S., additional, and Loris, R., additional
Published: 2005
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35. Humanized caban33 at room temperature

Author: Conrath, K., primary, Vincke, C., additional, Stijlemans, B., additional, Schymkowitz, J., additional, Decanniere, K., additional, Muyldermans, S., additional, and Loris, R., additional
Published: 2005
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36. Ultrasensitive Measurement of Ca(2+) Influx into Lipid Vesicles Induced by Protein Aggregates

Author: Flagmeier, P, De, S, Wirthensohn, DC, Lee, SF, Vincke, C, Muyldermans, S, Knowles, TPJ, Gandhi, S, Dobson, CM, and Klenerman, D
Subjects: nano-scale biophysics, fluorescence imaging, neurodegeneration, Alzheimer's disease, 3. Good health, protein aggregation
Abstract: To quantify and characterize the potentially toxic protein aggregates associated with neurodegenerative diseases, a high-throughput assay based on measuring the extent of aggregate-induced Ca(2+) entry into individual lipid vesicles has been developed. This approach was implemented by tethering vesicles containing a Ca(2+) sensitive fluorescent dye to a passivated surface and measuring changes in the fluorescence as a result of membrane disruption using total internal reflection microscopy. Picomolar concentrations of Aβ42 oligomers could be observed to induce Ca(2+) influx, which could be inhibited by the addition of a naturally occurring chaperone and a nanobody designed to bind to the Aβ peptide. We show that the assay can be used to study aggregates from other proteins, such as α-synuclein, and to probe the effects of complex biofluids, such as cerebrospinal fluid, and thus has wide applicability.

37. Carbon-nitrogen interactions in European forests and semi-natural vegetation - Part 1: Fluxes and budgets of carbon, nitrogen and greenhouse gases from ecosystem monitoring and modelling

Author: Flechard, C. R., Ibrom, A., Skiba, U. M., De Vries, W., Van Oijen, M., Cameron, D. R., DIse, N. B., Korhonen, J. F. J., Buchmann, N., Legout, A., Simpson, D., Sanz, M. J., Aubinet, M., Loustau, D., Montagnani, L., Neirynck, J., Janssens, I. A., Pihlatie, M., Kiese, R., Siemens, J., Francez, A.-J., Augustin, J., Varlagin, A., Olejnik, J., Juszczak, R., Aurela, M., Berveiller, D., Chojnicki, B. H., Dämmgen, U., Delpierre, N., Djuricic, V., Drewer, J., Dufrêne, E., Eugster, W., Fauvel, Y., Fowler, D., Frumau, A., Granier, A., Gross, P., Hamon, Y., Helfter, C., Hensen, A., Horvath, L., Kitzler, B., Kruijt, B., Kutsch, W. L., Lobo-Do-Vale, R., Lohila, A., Longdoz, B., Marek, M. V., Matteucci, G., Mitosinkova, M., Moreaux, V., Neftel, A., Ourcival, J.-M., Pilegaard, K., Pita, G., Sanz, F., Schjoerring, J. K., Sebastià, M.-T., Sim Tang, Y., Uggerud, H., Urbaniak, M., Van DIjk, N., Vesala, T., Vidic, S., Vincke, C., Weidinger, T., Zechmeister-Boltenstern, S., Butterbach-Bahl, K., Nemitz, E., and Sutton, M. A.
Subjects: 13. Climate action, 15. Life on land
Abstract: The impact of atmospheric reactive nitrogen (N$_{r}$) deposition on carbon (C) sequestration in soils and biomass of unfertilized, natural, semi-natural and forest ecosystems has been much debated. Many previous results of this dC/dN response were based on changes in carbon stocks from periodical soil and ecosystem inventories, associated with estimates of N$_{r}$ deposition obtained from large-scale chemical transport models. This study and a companion paper (Flechard et al., 2020) strive to reduce uncertainties of N effects on C sequestration by linking multi-annual gross and net ecosystem productivity estimates from 40 eddy covariance flux towers across Europe to local measurement-based estimates of dry and wet N$_{r}$ deposition from a dedicated collocated monitoring network. To identify possible ecological drivers and processes affecting the interplay between C and N$_{r}$ inputs and losses, these data were also combined with in situ flux measurements of NO, N$_{2}$O and CH$_{4}$ fluxes; soil NO$_{3}$̅ leaching sampling; and results of soil incubation experiments for N and greenhouse gas (GHG) emissions, as well as surveys of available data from online databases and from the literature, together with forest ecosystem (BASFOR) modelling. Multi-year averages of net ecosystem productivity (NEP) in forests ranged from -70 to 826 gCm$^{-2}$ yr$^{-1}$ at total wet+dry inorganic N$_{r}$ deposition rates (N$_{dep}$) of 0.3 to 4.3 gNm$^{-2}$ yr$^{-1}$ and from -4 to 361 g Cm$^{-2}$ yr$^{-1}$ at N$_{dep}$ rates of 0.1 to 3.1 gNm$^{-2}$ yr$^{-1}$ in short semi-natural vegetation (moorlands, wetlands and unfertilized extensively managed grasslands). The GHG budgets of the forests were strongly dominated by CO$_{2}$ exchange, while CH$_{4}$ and N$_{2}$O exchange comprised a larger proportion of the GHG balance in short semi-natural vegetation. Uncertainties in elemental budgets were much larger for nitrogen than carbon, especially at sites with elevated N$_{dep}$ where N$_{r}$ leaching losses were also very large, and compounded by the lack of reliable data on organic nitrogen and N$_{2}$ losses by denitrification. Nitrogen losses in the form of NO, N$_{2}$O and especially NO$_{3}$̅ were on average 27%(range 6 %–54 %) of N$_{dep}$ at sites with N$_{dep}$ < 1 gNm$^{-2}$ yr$^{-1}$ versus 65% (range 35 %–85 %) for N$_{dep}$ > 3 gNm$^{-2}$ yr$^{-1}$. Such large levels of N$_{r}$ loss likely indicate that different stages of N saturation occurred at a number of sites. The joint analysis of the C and N budgets provided further hints that N saturation could be detected in altered patterns of forest growth. Net ecosystem productivity increased with N$_{r}$ deposition up to 2–2.5 gNm$^{-2}$ yr$^{-1}$, with large scatter associated with a wide range in carbon sequestration efficiency (CSE, defined as the NEP = GPP ratio). At elevated N$_{dep}$ levels (> 2.5 gNm$^{-2}$ yr$^{-1}$), where inorganic N$_{r}$ losses were also increasingly large, NEP levelled off and then decreased. The apparent increase in NEP at low to intermediate N$_{dep}$ levels was partly the result of geographical cross-correlations between N$_{dep}$ and climate, indicating that the actual mean dC/dN response at individual sites was significantly lower than would be suggested by a simple, straightforward regression of NEP vs. N$_{dep}$.

38. Specific imaging of CD8 + T-Cell dynamics with a nanobody radiotracer against human CD8β.

Author: De Groof TWM, Lauwers Y, De Pauw T, Saxena M, Vincke C, Van Craenenbroeck J, Chapon C, Le Grand R, Raes G, Naninck T, Van Ginderachter JA, and Devoogdt N
Abstract: Purpose: While immunotherapy has revolutionized the oncology field, variations in therapy responsiveness limit the broad applicability of these therapies. Diagnostic imaging of immune cell, and specifically CD8 + T cell, dynamics could allow early patient stratification and result in improved therapy efficacy and safety. In this study, we report the development of a nanobody-based immunotracer for non-invasive SPECT and PET imaging of human CD8 + T-cell dynamics., Methods: Nanobodies targeting human CD8β were generated by llama immunizations and subsequent biopanning. The lead anti-human CD8β nanobody was characterized on binding, specificity, stability and toxicity. The lead nanobody was labeled with technetium-99m, gallium-68 and copper-64 for non-invasive imaging of human T-cell lymphomas and CD8 + T cells in human CD8 transgenic mice and non-human primates by SPECT/CT or PET/CT. Repeated imaging of CD8 + T cells in MC38 tumor-bearing mice allowed visualization of CD8 + T-cell dynamics., Results: The nanobody-based immunotracer showed high affinity and specific binding to human CD8 without unwanted immune activation. CD8 + T cells were non-invasively visualized by SPECT and PET imaging in naïve and tumor-bearing mice and in naïve non-human primates with high sensitivity. The nanobody-based immunotracer showed enhanced specificity for CD8 + T cells and/or faster in vivo pharmacokinetics compared to previous human CD8-targeting immunotracers, allowing us to follow human CD8 + T-cell dynamics already at early timepoints., Conclusion: This study describes the development of a more specific human CD8 + T-cell-targeting immunotracer, allowing follow-up of immunotherapy responses by non-invasive imaging of human CD8 + T-cell dynamics., (© 2024. The Author(s).)
Published: 2024
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39. Broad Protection against Invasive Fungal Disease from a Nanobody Targeting the Active Site of Fungal β-1,3-Glucanosyltransferases.

Author: Redrado-Hernández S, Macías-León J, Castro-López J, Belén Sanz A, Dolader E, Arias M, González-Ramírez AM, Sánchez-Navarro D, Petryk Y, Farkaš V, Vincke C, Muyldermans S, García-Barbazán I, Del Agua C, Zaragoza O, Arroyo J, Pardo J, Gálvez EM, and Hurtado-Guerrero R
Subjects: Cryptococcus neoformans enzymology, Cryptococcus neoformans immunology, Antifungal Agents chemistry, Antifungal Agents pharmacology, Animals, Mice, Glucan Endo-1,3-beta-D-Glucosidase, Catalytic Domain, Single-Domain Antibodies chemistry, Single-Domain Antibodies immunology, Single-Domain Antibodies pharmacology, Aspergillus fumigatus immunology, Aspergillus fumigatus enzymology
Abstract: Invasive fungal disease accounts for about 3.8 million deaths annually, an unacceptable rate that urgently prompts the discovery of new knowledge-driven treatments. We report the use of camelid single-domain nanobodies (Nbs) against fungal β-1,3-glucanosyltransferases (Gel) involved in β-1,3-glucan transglycosylation. Crystal structures of two Nbs with Gel4 from Aspergillus fumigatus revealed binding to a dissimilar CBM43 domain and a highly conserved catalytic domain across fungal species, respectively. Anti-Gel4 active site Nb3 showed significant antifungal efficacy in vitro and in vivo prophylactically and therapeutically against different A. fumigatus and Cryptococcus neoformans isolates, reducing the fungal burden and disease severity, thus significantly improving immunocompromised animal survival. Notably, C. deneoformans (serotype D) strains were more susceptible to Nb3 and genetic Gel deletion than C. neoformans (serotype A) strains, indicating a key role for β-1,3-glucan remodelling in C. deneoformans survival. These findings add new insight about the role of β-1,3-glucan in fungal biology and demonstrate the potential of nanobodies in targeting fungal enzymes to combat invasive fungal diseases., (© 2024 The Authors. Angewandte Chemie International Edition published by Wiley-VCH GmbH.)
Published: 2024
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40. Generation and Characterization of Novel Pan-Cancer Anti-uPAR Fluorescent Nanobodies as Tools for Image-Guided Surgery.

Author: Mateusiak Ł, Floru S, De Groof TWM, Wouters J, Declerck NB, Debie P, Janssen S, Zeven K, Puttemans J, Vincke C, Breckpot K, Devoogdt N, and Hernot S
Subjects: Animals, Mice, Humans, Disease Models, Animal, Cell Line, Tumor, Optical Imaging methods, Neoplasms immunology, Neoplasms diagnostic imaging, Neoplasms surgery, Fluorescent Dyes, Camelids, New World, Single-Domain Antibodies immunology, Receptors, Urokinase Plasminogen Activator metabolism, Surgery, Computer-Assisted methods
Abstract: Fluorescence molecular imaging plays a vital role in image-guided surgery. In this context, the urokinase plasminogen activator receptor (uPAR) is an interesting biomarker enabling the detection and delineation of various tumor types due to its elevated expression on both tumor cells and the tumor microenvironment. In this study, anti-uPAR Nanobodies (Nbs) are generated through llama immunization with human and murine uPAR protein. Extensive in vitro characterization and in vivo testing with radiolabeled variants are conducted to assess their pharmacokinetics and select lead compounds. Subsequently, the selected Nbs are converted into fluorescent agents, and their application for fluorescence-guided surgery is evaluated in various subcutaneous and orthotopic tumor models. The study yields a panel of high-affinity anti-uPAR Nbs, showing specific binding across multiple types of cancer cells in vitro and in vivo. Lead fluorescently-labeled compounds exhibit high tumor uptake with high contrast at 1 h after intravenous injection across all assessed uPAR-expressing tumor models, outperforming a non-targeting control Nb. Additionally, rapid and accurate tumor localization and demarcation are demonstrated in an orthotopic human glioma model. Utilizing these Nbs can potentially enhance the precision of surgical tumor resection and, consequently, improve survival rates in the clinic., (© 2024 The Authors. Advanced Science published by Wiley‐VCH GmbH.)
Published: 2024
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41. Q586B2 is a crucial virulence factor during the early stages of Trypanosoma brucei infection that is conserved amongst trypanosomatids.

Author: Stijlemans B, De Baetselier P, Van Molle I, Lecordier L, Hendrickx E, Romão E, Vincke C, Baetens W, Schoonooghe S, Hassanzadeh-Ghassabeh G, Korf H, Wallays M, Pinto Torres JE, Perez-Morga D, Brys L, Campetella O, Leguizamón MS, Claes M, Hendrickx S, Mabille D, Caljon G, Remaut H, Roelants K, Magez S, Van Ginderachter JA, and De Trez C
Subjects: Animals, Humans, Interleukin-10 genetics, Virulence Factors, Parasitemia parasitology, Trypanosoma brucei brucei genetics, Trypanosomiasis, African parasitology, Trypanosoma cruzi
Abstract: Human African trypanosomiasis or sleeping sickness, caused by the protozoan parasite Trypanosoma brucei, is characterized by the manipulation of the host's immune response to ensure parasite invasion and persistence. Uncovering key molecules that support parasite establishment is a prerequisite to interfere with this process. We identified Q586B2 as a T. brucei protein that induces IL-10 in myeloid cells, which promotes parasite infection invasiveness. Q586B2 is expressed during all T. brucei life stages and is conserved in all Trypanosomatidae. Deleting the Q586B2-encoding Tb927.6.4140 gene in T. brucei results in a decreased peak parasitemia and prolonged survival, without affecting parasite fitness in vitro, yet promoting short stumpy differentiation in vivo. Accordingly, neutralization of Q586B2 with newly generated nanobodies could hamper myeloid-derived IL-10 production and reduce parasitemia. In addition, immunization with Q586B2 delays mortality upon a challenge with various trypanosomes, including Trypanosoma cruzi. Collectively, we uncovered a conserved protein playing an important regulatory role in Trypanosomatid infection establishment., (© 2024. The Author(s).)
Published: 2024
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42. Epitope mapping of nanobodies binding the Alzheimer's disease receptor SORLA.

Author: Monti G, Vincke C, Lunding M, Jensen AMG, Madsen P, Muyldermans S, Kjolby M, and Andersen OM
Subjects: Humans, Epitope Mapping, HEK293 Cells, Epitopes, Single-Domain Antibodies genetics, Alzheimer Disease
Abstract: Reduced levels of the Sortilin-related receptor with A-type repeats (SORLA) in different brain regions as well as in the cerebrospinal fluid have been associated with Alzheimer's disease. Methods and reagents to develop reliable detection assays to quantify SORLA and its specific isoforms are therefore much needed. Nanobodies (Nbs) are unique biomolecules derived from the blood of camelids that display advantageous physicochemical and antigen affinity properties, making them attractive tools with great relevance to both diagnostic and therapeutic applications. Here, we purified and characterized eight Nbs that were isolated from the blood of an alpaca immunized with the recombinant extracellular domain of SORLA. The selected Nbs showed high affinity to SORLA in the low nanomolar range as observed by surface plasmon resonance. For mapping of the Nbs' epitopes within the antigen, we transiently transfected HEK293 cells with a panel of SORLA deletion constructs, and developed a protocol of immunostaining by applying fluorescent dye conjugated Nbs. With this method, we showed that the selected Nbs specifically recognize a part of SORLA containing Fibronectin-type III domains, representing promising tools not only for disease clarifying research, but also for translational medicine as candidates for clinical diagnostic purposes., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Olav Andersen reports financial support was provided by EU Joint Programme Neurodegenerative Disease Research. Olav Andersen reports a relationship with Retromer Therapeutics that includes: board membership, consulting or advisory, equity or stocks, and funding grants., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)
Published: 2023
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43. Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing.

Author: Xie M, Ma X, Wang Y, Li C, Shi H, Yuan X, Hellwich O, Chen C, Zhang W, Zhang C, Ling Q, Gao R, Zhang Y, Ochege FU, Frankl A, De Maeyer P, Buchmann N, Feigenwinter I, Olesen JE, Juszczak R, Jacotot A, Korrensalo A, Pitacco A, Varlagin A, Shekhar A, Lohila A, Carrara A, Brut A, Kruijt B, Loubet B, Heinesch B, Chojnicki B, Helfter C, Vincke C, Shao C, Bernhofer C, Brümmer C, Wille C, Tuittila ES, Nemitz E, Meggio F, Dong G, Lanigan G, Niedrist G, Wohlfahrt G, Zhou G, Goded I, Gruenwald T, Olejnik J, Jansen J, Neirynck J, Tuovinen JP, Zhang J, Klumpp K, Pilegaard K, Šigut L, Klemedtsson L, Tezza L, Hörtnagl L, Urbaniak M, Roland M, Schmidt M, Sutton MA, Hehn M, Saunders M, Mauder M, Aurela M, Korkiakoski M, Du M, Vendrame N, Kowalska N, Leahy PG, Alekseychik P, Shi P, Weslien P, Chen S, Fares S, Friborg T, Tallec T, Kato T, Sachs T, Maximov T, di Cella UM, Moderow U, Li Y, He Y, Kosugi Y, and Luo G
Abstract: Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R 2 ), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002-2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983-2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics., (© 2023. Springer Nature Limited.)
Published: 2023
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44. A few good reasons to use nanobodies for cancer treatment.

Author: Jumapili NA, Zivalj M, Barthelmess RM, Raes G, De Groof TWM, Devoogdt N, Stijlemans B, Vincke C, and Van Ginderachter JA
Subjects: Humans, Antibodies, Monoclonal, Tumor Microenvironment, Single-Domain Antibodies therapeutic use, Brain Neoplasms
Abstract: mAbs have been instrumental for targeted cancer therapies. However, their relatively large size and physicochemical properties result in a heterogenous distribution in the tumor microenvironment, usually restricted to the first cell layers surrounding blood vessels, and a limited ability to penetrate the brain. Nanobodies are tenfold smaller, resulting in a deeper tumor penetration and the ability to reach cells in poorly perfused tumor areas. Nanobodies are rapidly cleared from the circulation, which generates a fast target-to-background contrast that is ideally suited for molecular imaging purposes but may be less optimal for therapy. To circumvent this problem, nanobodies have been formatted to noncovalently bind albumin, increasing their serum half-life without majorly increasing their size. Finally, nanobodies have shown superior qualities to infiltrate brain tumors as compared to mAbs. In this review, we discuss why these features make nanobodies prime candidates for targeted therapy of cancer., (© 2023 The Authors. European Journal of Immunology published by Wiley-VCH GmbH.)
Published: 2023
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45. Whole-mouse clearing and imaging at the cellular level with vDISCO.

Author: Cai R, Kolabas ZI, Pan C, Mai H, Zhao S, Kaltenecker D, Voigt FF, Molbay M, Ohn TL, Vincke C, Todorov MI, Helmchen F, Van Ginderachter JA, and Ertürk A
Subjects: Mice, Animals, Microscopy, Fluorescence methods, Solvents chemistry, Neurites, Coloring Agents, Imaging, Three-Dimensional methods, Brain
Abstract: Homeostatic and pathological phenomena often affect multiple organs across the whole organism. Tissue clearing methods, together with recent advances in microscopy, have made holistic examinations of biological samples feasible. Here, we report the detailed protocol for nanobody(V H H)-boosted 3D imaging of solvent-cleared organs (vDISCO), a pressure-driven, nanobody-based whole-body immunolabeling and clearing method that renders whole mice transparent in 3 weeks, consistently enhancing the signal of fluorescent proteins, stabilizing them for years. This allows the reliable detection and quantification of fluorescent signal in intact rodents enabling the analysis of an entire body at cellular resolution. Here, we show the high versatility of vDISCO applied to boost the fluorescence signal of genetically expressed reporters and clear multiple dissected organs and tissues, as well as how to image processed samples using multiple fluorescence microscopy systems. The entire protocol is accessible to laboratories with limited expertise in tissue clearing. In addition to its applications in obtaining a whole-mouse neuronal projection map, detecting single-cell metastases in whole mice and identifying previously undescribed anatomical structures, we further show the visualization of the entire mouse lymphatic system, the application for virus tracing and the visualization of all pericytes in the brain. Taken together, our vDISCO pipeline allows systematic and comprehensive studies of cellular phenomena and connectivity in whole bodies., (© 2023. Springer Nature Limited.)
Published: 2023
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46. Size-advantage of monovalent nanobodies against the macrophage mannose receptor for deep tumor penetration and tumor-associated macrophage targeting.

Author: Erreni M, D'Autilia F, Avigni R, Bolli E, Arnouk SM, Movahedi K, Debie P, Anselmo A, Parente R, Vincke C, van Leeuwen FWB, Allavena P, Garlanda C, Mantovani A, Doni A, Hernot S, and Van Ginderachter JA
Subjects: Humans, Mannose Receptor, Lectins, C-Type, Mannose-Binding Lectins, Receptors, Cell Surface, Tumor-Associated Macrophages, Single-Domain Antibodies, Neoplasms drug therapy
Abstract: Rationale: Nanobodies (Nbs) have emerged as an elegant alternative to the use of conventional monoclonal antibodies in cancer therapy, but a detailed microscopic insight into the in vivo pharmacokinetics of different Nb formats in tumor-bearers is lacking. This is especially relevant for the recognition and targeting of pro-tumoral tumor-associated macrophages (TAMs), which may be located in less penetrable tumor regions. Methods: We employed anti-Macrophage Mannose Receptor (MMR) Nbs, in a monovalent (m) or bivalent (biv) format, to assess in vivo TAM targeting. Intravital and confocal microscopy were used to analyse the blood clearance rate and targeting kinetics of anti-MMR Nbs in tumor tissue, healthy muscle tissue and liver. Fluorescence Molecular Tomography was applied to confirm anti-MMR Nb accumulation in the primary tumor and in metastatic lesions. Results: Intravital microscopy demonstrated significant differences in the blood clearance rate and macrophage targeting kinetics of (m) and (biv)anti-MMR Nbs, both in tumoral and extra-tumoral tissue. Importantly, (m)anti-MMR Nbs are superior in reaching tissue macrophages, an advantage that is especially prominent in tumor tissue. The administration of a molar excess of unlabelled (biv)anti-MMR Nbs increased the (m)anti-MMR Nb bioavailability and impacted on its macrophage targeting kinetics, preventing their accumulation in extra-tumoral tissue (especially in the liver) but only partially influencing their interaction with TAMs. Finally, anti-MMR Nb administration not only allowed the visualization of TAMs in primary tumors, but also at a distant metastatic site. Conclusions: These data describe, for the first time, a microscopic analysis of (m) and (biv)anti-MMR Nb pharmacokinetics in tumor and healthy tissues. The concepts proposed in this study provide important knowledge for the future use of Nbs as diagnostic and therapeutic agents, especially for the targeting of tumor-infiltrating immune cells., Competing Interests: Competing Interests: Prof. Sophie Hernot is coinventor on patent US961733B2 related to the use of anti-MMR Nbs in cardiovascular diseases. Prof. Jo Van Ginderachter is coinventor on patent “Anti-macrophage mannose receptor single variable domains for targeting and in vivo imaging of tumor-associated macrophages”; US 13/065,79. Jo Van Ginderachter is also co-founder of the company Abscint NV, which focuses on Nb-mediated molecular imaging in oncology, cardiology and immunology., (© The author(s).)
Published: 2023
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47. Nanobodies for the Early Detection of Ovarian Cancer.

Author: Tran LH, Graulus GJ, Vincke C, Smiejkowska N, Kindt A, Devoogdt N, Muyldermans S, Adriaensens P, and Guedens W
Subjects: Humans, Female, Early Detection of Cancer, Carcinoma, Ovarian Epithelial, Biomarkers, Tumor, Progranulins, Single-Domain Antibodies, Ovarian Neoplasms diagnosis
Abstract: Ovarian cancer ranks fifth in cancer-related deaths among women. Since ovarian cancer patients are often asymptomatic, most patients are diagnosed only at an advanced stage of disease. This results in a 5-year survival rate below 50%, which is in strong contrast to a survival rate as high as 94% if detected and treated at an early stage. Monitoring serum biomarkers offers new possibilities to diagnose ovarian cancer at an early stage. In this study, nanobodies targeting the ovarian cancer biomarkers human epididymis protein 4 (HE4), secretory leukocyte protease inhibitor (SLPI), and progranulin (PGRN) were evaluated regarding their expression levels in bacterial systems, epitope binning, and antigen-binding affinity by enzyme-linked immunosorbent assay and surface plasmon resonance. The selected nanobodies possess strong binding affinities for their cognate antigens (K D ~0.1-10 nM) and therefore have a pronounced potential to detect ovarian cancer at an early stage. Moreover, it is of utmost importance that the limits of detection (LOD) for these biomarkers are in the pM range, implying high specificity and sensitivity, as demonstrated by values in human serum of 37 pM for HE4, 163 pM for SLPI, and 195 pM for PGRN. These nanobody candidates could thus pave the way towards multiplexed biosensors.
Published: 2022
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48. Sensitive Protein Detection Using Site-Specifically Oligonucleotide-Conjugated Nanobodies.

Author: Al-Amin RA, Muthelo PM, Abdurakhmanov E, Vincke C, Amin SP, Muyldermans S, Danielson UH, and Landegren U
Subjects: Antibodies, Indicators and Reagents, Interleukin-6, Oligonucleotides, Reproducibility of Results, Single-Domain Antibodies
Abstract: High-quality affinity probes are critical for sensitive and specific protein detection, in particular for detection of protein biomarkers in the early phases of disease development. Proximity extension assays (PEAs) have been used for high-throughput multiplexed protein detection of up to a few thousand different proteins in one or a few microliters of plasma. Clonal affinity reagents can offer advantages over the commonly used polyclonal antibodies (pAbs) in terms of reproducibility and standardization of such assays. Here, we explore nanobodies (Nbs) as an alternative to pAbs as affinity reagents for PEA. We describe an efficient site-specific approach for preparing high-quality oligo-conjugated Nb probes via enzyme coupling using Sortase A (SrtA). The procedure allows convenient removal of unconjugated affinity reagents after conjugation. The purified high-grade Nb probes were used in PEA, and the reactions provided an efficient means to select optimal pairs of binding reagents from a group of affinity reagents. We demonstrate that Nb-based PEA (nano-PEA) for interleukin-6 (IL6) detection can augment assay performance, compared to the use of pAb probes. We identify and validate Nb combinations capable of binding in pairs without competition for IL6 antigen detection by PEA.
Published: 2022
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49. Cross-biome synthesis of source versus sink limits to tree growth.

Author: Cabon A, Kannenberg SA, Arain A, Babst F, Baldocchi D, Belmecheri S, Delpierre N, Guerrieri R, Maxwell JT, McKenzie S, Meinzer FC, Moore DJP, Pappas C, Rocha AV, Szejner P, Ueyama M, Ulrich D, Vincke C, Voelker SL, Wei J, Woodruff D, and Anderegg WRL
Subjects: Carbon Sequestration, Forests, Trees growth & development
Abstract: Uncertainties surrounding tree carbon allocation to growth are a major limitation to projections of forest carbon sequestration and response to climate change. The prevalence and extent to which carbon assimilation (source) or cambial activity (sink) mediate wood production are fundamentally important and remain elusive. We quantified source-sink relations across biomes by combining eddy-covariance gross primary production with extensive on-site and regional tree ring observations. We found widespread temporal decoupling between carbon assimilation and tree growth, underpinned by contrasting climatic sensitivities of these two processes. Substantial differences in assimilation-growth decoupling between angiosperms and gymnosperms were determined, as well as stronger decoupling with canopy closure, aridity, and decreasing temperatures. Our results reveal pervasive sink control over tree growth that is likely to be increasingly prominent under global climate change.
Published: 2022
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50. Neutralizing Dromedary-Derived Nanobodies Against BotI-Like Toxin From the Most Hazardous Scorpion Venom in the Middle East and North Africa Region.

Author: Ben Abderrazek R, Ksouri A, Idoudi F, Dhaouadi S, Hamdi E, Vincke C, Farah A, Benlasfar Z, Majdoub H, El Ayeb M, Muyldermans S, and Bouhaouala-Zahar B
Subjects: Animals, Camelus, Mice, Scorpions, Scorpion Stings therapy, Scorpion Venoms, Single-Domain Antibodies therapeutic use
Abstract: Scorpion envenoming is a severe health problem in many regions causing significant clinical toxic effects and fatalities. In the Middle East/North Africa (MENA) region, Buthidae scorpion stings are responsible for devastating toxic outcomes in human. The only available specific immunotherapeutic treatment is based on IgG fragments of animal origin. To overcome the limitations of classical immunotherapy, we have demonstrated the in vivo efficacy of NbF12-10 bispecific nanobody at preclinical level. Nanobodies were developed against BotI analogues belonging to a distinct structural and antigenic group of scorpion toxins, occurring in the MENA region. From Buthus occitanus tunetanus venom, BotI-like toxin was purified. The 41 N-terminal amino acid residues were sequenced, and the LD 50 was estimated at 40 ng/mouse. The BotI-like toxin was used for dromedary immunization. An immune VHH library was constructed, and after screening, two nanobodies were selected with nanomolar and sub-nanomolar affinity and recognizing an overlapping epitope. NbBotI-01 was able to neutralize 50% of the lethal effect of 13 LD 50 BotI-like toxins in mice when injected by i.c.v route, whereas NbBotI-17 neutralized 50% of the lethal effect of 7 LD 50 . Interestingly, NbBotI-01 completely reduced the lethal effect of the 2 LD 50 of BotG50 when injected at 1:4 molar ratio excess. More interestingly, an equimolar mixture of NbBotI-01 with NbF12-10 neutralized completely the lethal effect of 7 and 5 LD 50 of BotG50 or AahG50, at 1:4 and 1:2 molar ratio, respectively. Hence, NbBotI-01 and NbF12-10 display synergic effects, leading to a novel therapeutic candidate for treating Buthus occitanus scorpion stings in the MENA region., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Ben Abderrazek, Ksouri, Idoudi, Dhaouadi, Hamdi, Vincke, Farah, Benlasfar, Majdoub, El Ayeb, Muyldermans and Bouhaouala-Zahar.)
Published: 2022
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