45 results on '"Hattab, T"'
Search Results
2. Climate change in the Bay of Biscay : Changes in spatial biodiversity patterns could be driven by the arrivals of southern species
- Author
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Le Marchand, M., Hattab, T., Niquil, N., Albouy, C., Le Loch, F., and Lasram, F. Ben Rais
- Published
- 2020
3. Interactions between demersal fish body condition and density during the regime shift of the Gulf of Lions
- Author
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Bensebaini, C M, primary, Certain, G, additional, Billet, N, additional, Jadaud, A, additional, Gourguet, S, additional, Hattab, T, additional, and Fromentin, J M, additional
- Published
- 2022
- Full Text
- View/download PDF
4. Using species distribution models only may underestimate climate change impacts on future marine biodiversity
- Author
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Moullec, F, Barrier, N., Drira, S., Guilhaumon, F., Hattab, T., Peck, M.A., Shin, Y.-J., Moullec, F, Barrier, N., Drira, S., Guilhaumon, F., Hattab, T., Peck, M.A., and Shin, Y.-J.
- Abstract
In face of global changes, projecting and mapping biodiversity changes are of critical importance to support management and conservation measures of marine ecosystems. Despite the development of a wide variety of ecosystem models capable of integrating an increasing number of ecological processes, most projections of climate-induced changes in marine biodiversity are based on species distribution models (SDMs). These correlative models present a significant advantage when the lack of knowledge on the species physiology is counterbalanced by the availability of relevant environmental variables over the species geographical range. However, correlative SDMs neglect intra- and inter-specific interactions and thereby can lead to biased projections of changes in biodiversity distribution. To evaluate the influence of trophic interactions on projections of species richness and assemblage composition under climate change scenarios, we compared biodiversity projections derived from an ensemble of different SDMs to projections derived from a hybrid model coupling SDMs and a multispecies trophic model in the Mediterranean Sea. Our results show that accounting for trophic interactions modifies projections of future biodiversity in the Mediterranean Sea. Under the RCP8.5 scenario, SDMs tended to overestimate the gains and underestimate the losses of species richness by the end of the 21st century, with marked local differences in projections, both in terms of magnitude and trend, in some biodiversity hotspots. In both SDMs and hybrid approaches, nestedness with gains in species richness was the main pattern driving dissimilarity between present and future fish and macro-invertebrate species assemblages at the Mediterranean basin scale. However, at local scale, we highlighted some differences in the relative contribution of nestedness vs replacement in driving dissimilarity. Our results call for the development of integrated modelling tools that can mechanistically consider multi
- Published
- 2022
5. Effects of sampling intensity and biomass levels on the precision of acoustic surveys in the Mediterranean Sea
- Author
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Barra, M., Bonanno, A., Hattab, T., Saraux, C., Iglesias, M. (Magdalena), Leonori, I., Ticina, V., Basilone, G., De Felice, A., Ferreri, R., Machias, A., and Ventero, A. (Ana)
- Subjects
fish ,levels ,surveys ,biomass ,echo surveys - Abstract
Acoustic surveys represent the standard fishery-independent method worldwide for evaluating the biomass and spatial distribution of small pelagic fish populations. Considering the peculiarities of the spatial behaviour of pelagic fishes, the efficiency of the survey design in determining their biomass and spatial distribution is related to its ability to capture the portion of the patches accounting for larger part of the total biomass. Yet, the spatial structure of the patches could be strongly influenced by ecosystem characteristics as well as by changes in total biomass related to a density-dependent mechanism. This is of particular interest for anchovy and sardine which are known for their wide fluctuations and high sensitivity to the environment. In this study, we analysed the efficiency of acoustic surveys, targeting European anchovy (Engraulis encrasicolus) and European sardine (Sardina pilchardus), in 10 different areas of the Mediterranean Sea across three years of different biomass levels. Using the geostatistical Coefficient of Variation (CVgeo) of the average occurrence probability of high/medium density values, we showed different patterns in terms of survey design efficiency among areas and species. Anchovy usually showed lower CVgeo than sardine, but in the Alboran Sea. In 4 out of 20 cases, CVgeo values showed a consistent decrease with increasing biomass while in the remaining cases the CVgeo did not follow any clear pattern suggesting the presence of important environmental effects. Higher survey design efficiency was found in high productive sectors influenced by river run-off, letting us to hypothesize that higher productivity along with the presence of well-localized enrichment mechanisms could favour a spatially consistent distribution and coherent organization of fish population leading to higher precision estimates with a given transect design. While most surveys displayed CVgeo close to 10% or less even at low biomass, evidencing generally good performances of the survey design, a few areas exhibited higher CVgeo, yielding discussions about a potential need to decrease the inter-transect distance, always keeping in mind that survey should be as synoptic as possible.
- Published
- 2021
6. sPlotOpen – An environmentally balanced, open‐access, global dataset of vegetation plots
- Author
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Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jimenez‐Alfaro, B., Kattge, J., Levesley, A., Pillar, V.D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A.T.R., Agrillo, E., Álvarez, M., Apostolova, I., Arfin Khan, M.A.S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., Gasper, A.L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El‐Sheikh, M.A.El‐R.M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán‐de‐Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I.G., Grytnes, J‐A, Guerin, G.R., Gutiérrez, A.G., Haider, S., Hatim, M.Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J.A.M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D.N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H.S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D.V., Liu, H., Lysenko, T., Mahecha, M.D., Marcenò, C., Martynenko, V., Moeslund, J.E., Monteagudo Mendoza, A., Mucina, L., Müller, J.V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Pärtel, M., Pauchard, A., Peet, R.K., Penuelas, J., Pérez‐Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas‐Torres, G., Rodwell, J.S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Ž., Sparrow, B., Sperandii, M.G., Stančić, Z., Svenning, J‐C, Tang, Z., Tang, C.Q., Tsiripidis, I., Vanselow, K.A., Vásquez Martínez, R., Vassilev, K., Vélez‐Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., Wehrden, H., Wagner, V., Walker, D.A., Waller, D.M., Wang, H‐F, Wesche, K., Whitfeld, T.J.S., Willner, W., Wiser, S.K., Wohlgemuth, T., Yamalov, S., Zobel, M., Bruelheide, H., Bates, A., Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jimenez‐Alfaro, B., Kattge, J., Levesley, A., Pillar, V.D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A.T.R., Agrillo, E., Álvarez, M., Apostolova, I., Arfin Khan, M.A.S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., Gasper, A.L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El‐Sheikh, M.A.El‐R.M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán‐de‐Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I.G., Grytnes, J‐A, Guerin, G.R., Gutiérrez, A.G., Haider, S., Hatim, M.Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J.A.M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D.N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H.S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D.V., Liu, H., Lysenko, T., Mahecha, M.D., Marcenò, C., Martynenko, V., Moeslund, J.E., Monteagudo Mendoza, A., Mucina, L., Müller, J.V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Pärtel, M., Pauchard, A., Peet, R.K., Penuelas, J., Pérez‐Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas‐Torres, G., Rodwell, J.S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Ž., Sparrow, B., Sperandii, M.G., Stančić, Z., Svenning, J‐C, Tang, Z., Tang, C.Q., Tsiripidis, I., Vanselow, K.A., Vásquez Martínez, R., Vassilev, K., Vélez‐Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., Wehrden, H., Wagner, V., Walker, D.A., Waller, D.M., Wang, H‐F, Wesche, K., Whitfeld, T.J.S., Willner, W., Wiser, S.K., Wohlgemuth, T., Yamalov, S., Zobel, M., Bruelheide, H., and Bates, A.
- Abstract
Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring.
- Published
- 2021
7. sPlotOpen:an environmentally balanced, open-access, global dataset of vegetation plots
- Author
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Sabatini, F. M. (Francesco Maria), Lenoir, J. (Jonathan), Hattab, T. (Tarek), Arnst, E. A. (Elise Aimee), Chytry, M. (Milan), Dengler, J. (Juergen), De Ruffray, P. (Patrice), Hennekens, S. M. (Stephan M.), Jandt, U. (Ute), Jansen, F. (Florian), Jimenez-Alfaro, B. (Borja), Kattge, J. (Jens), Levesley, A. (Aurora), Pillar, V. D. (Valerio D.), Purschke, O. (Oliver), Sandel, B. (Brody), Sultana, F. (Fahmida), Aavik, T. (Tsipe), Acic, S. (Svetlana), Acosta, A. T. (Alicia T. R.), Agrillo, E. (Emiliano), Alvarez, M. (Miguel), Apostolova, I. (Iva), Arfin Khan, M. A. (Mohammed A. S.), Arroyo, L. (Luzmila), Attorre, F. (Fabio), Aubin, I. (Isabelle), Banerjee, A. (Arindam), Bauters, M. (Marijn), Bergeron, Y. (Yves), Bergmeier, E. (Erwin), Biurrun, I. (Idoia), Bjorkman, A. D. (Anne D.), Bonari, G. (Gianmaria), Bondareva, V. (Viktoria), Brunet, J. (Jorg), Carni, A. (Andraz), Casella, L. (Laura), Cayuela, L. (Luis), Cerny, T. (Tomas), Chepinoga, V. (Victor), Csiky, J. (Janos), Custerevska, R. (Renata), De Bie, E. (Els), de Gasper, A. L. (Andre Luis), De Sanctis, M. (Michele), Dimopoulos, P. (Panayotis), Dolezal, J. (Jiri), Dziuba, T. (Tetiana), El-Sheikh, M. A. (Mohamed Abd El-Rouf Mousa), Enquist, B. (Brian), Ewald, J. (Joerg), Fazayeli, F. (Farideh), Field, R. (Richard), Finckh, M. (Manfred), Gachet, S. (Sophie), Galan-de-Mera, A. (Antonio), Garbolino, E. (Emmanuel), Gholizadeh, H. (Hamid), Giorgis, M. (Melisa), Golub, V. (Valentin), Alsos, I. G. (Inger Greve), Grytnes, J.-A. (John-Arvid), Guerin, G. R. (Gregory Richard), Gutierrez, A. G. (Alvaro G.), Haider, S. (Sylvia), Hatim, M. Z. (Mohamed Z.), Herault, B. (Bruno), Hinojos Mendoza, G. (Guillermo), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Hubau, W. (Wannes), Indreica, A. (Adrian), Janssen, J. A. (John A. M.), Jedrzejek, B. (Birgit), Jentsch, A. (Anke), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Kapfer, J. (Jutta), Karger, D. N. (Dirk Nikolaus), Kavgaci, A. (Ali), Kearsley, E. (Elizabeth), Kessler, M. (Michael), Khanina, L. (Larisa), Killeen, T. (Timothy), Korolyuk, A. (Andrey), Kreft, H. (Holger), Kuehl, H. S. (Hjalmar S.), Kuzemko, A. (Anna), Landucci, F. (Flavia), Lengyel, A. (Attila), Lens, F. (Frederic), Lingner, D. V. (Debora Vanessa), Liu, H. (Hongyan), Lysenko, T. (Tatiana), Mahecha, M. D. (Miguel D.), Marceno, C. (Corrado), Martynenko, V. (Vasiliy), Moeslund, J. E. (Jesper Erenskjold), Monteagudo Mendoza, A. (Abel), Mucina, L. (Ladislav), Muller, J. V. (Jonas V.), Munzinger, J. (Jerome), Naqinezhad, A. (Alireza), Noroozi, J. (Jalil), Nowak, A. (Arkadiusz), Onyshchenko, V. (Viktor), Overbeck, G. E. (Gerhard E.), Partel, M. (Meelis), Pauchard, A. (Anibal), Peet, R. K. (Robert K.), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Peterka, T. (Tomas), Petrik, P. (Petr), Peyre, G. (Gwendolyn), Phillips, O. L. (Oliver L.), Prokhorov, V. (Vadim), Rasomavicius, V. (Valerijus), Revermann, R. (Rasmus), Rivas-Torres, G. (Gonzalo), Rodwell, J. S. (John S.), Ruprecht, E. (Eszter), Rusina, S. (Solvita), Samimi, C. (Cyrus), Schmidt, M. (Marco), Schrodt, F. (Franziska), Shan, H. (Hanhuai), Shirokikh, P. (Pavel), Sibik, J. (Jozef), Silc, U. (Urban), Sklenar, P. (Petr), Skvorc, Z. (Zeljko), Sparrow, B. (Ben), Sperandii, M. G. (Marta Gaia), Stancic, Z. (Zvjezdana), Svenning, J.-C. (Jens-Christian), Tang, Z. (Zhiyao), Tang, C. Q. (Cindy Q.), Tsiripidis, I. (Ioannis), Vanselow, K. A. (Kim Andre), Vasquez Martinez, R. (Rodolfo), Vassilev, K. (Kiril), Velez-Martin, E. (Eduardo), Venanzoni, R. (Roberto), Vibrans, A. C. (Alexander Christian), Violle, C. (Cyrille), Virtanen, R. (Risto), von Wehrden, H. (Henrik), Wagner, V. (Viktoria), Walker, D. A. (Donald A.), Waller, D. M. (Donald M.), Wang, H.-F. (Hua-Feng), Wesche, K. (Karsten), Whitfeld, T. J. (Timothy J. S.), Willner, W. (Wolfgang), Wiser, S. K. (Susan K.), Wohlgemuth, T. (Thomas), Yamalov, S. (Sergey), Zobel, M. (Martin), Bruelheide, H. (Helge), Sabatini, F. M. (Francesco Maria), Lenoir, J. (Jonathan), Hattab, T. (Tarek), Arnst, E. A. (Elise Aimee), Chytry, M. (Milan), Dengler, J. (Juergen), De Ruffray, P. (Patrice), Hennekens, S. M. (Stephan M.), Jandt, U. (Ute), Jansen, F. (Florian), Jimenez-Alfaro, B. (Borja), Kattge, J. (Jens), Levesley, A. (Aurora), Pillar, V. D. (Valerio D.), Purschke, O. (Oliver), Sandel, B. (Brody), Sultana, F. (Fahmida), Aavik, T. (Tsipe), Acic, S. (Svetlana), Acosta, A. T. (Alicia T. R.), Agrillo, E. (Emiliano), Alvarez, M. (Miguel), Apostolova, I. (Iva), Arfin Khan, M. A. (Mohammed A. S.), Arroyo, L. (Luzmila), Attorre, F. (Fabio), Aubin, I. (Isabelle), Banerjee, A. (Arindam), Bauters, M. (Marijn), Bergeron, Y. (Yves), Bergmeier, E. (Erwin), Biurrun, I. (Idoia), Bjorkman, A. D. (Anne D.), Bonari, G. (Gianmaria), Bondareva, V. (Viktoria), Brunet, J. (Jorg), Carni, A. (Andraz), Casella, L. (Laura), Cayuela, L. (Luis), Cerny, T. (Tomas), Chepinoga, V. (Victor), Csiky, J. (Janos), Custerevska, R. (Renata), De Bie, E. (Els), de Gasper, A. L. (Andre Luis), De Sanctis, M. (Michele), Dimopoulos, P. (Panayotis), Dolezal, J. (Jiri), Dziuba, T. (Tetiana), El-Sheikh, M. A. (Mohamed Abd El-Rouf Mousa), Enquist, B. (Brian), Ewald, J. (Joerg), Fazayeli, F. (Farideh), Field, R. (Richard), Finckh, M. (Manfred), Gachet, S. (Sophie), Galan-de-Mera, A. (Antonio), Garbolino, E. (Emmanuel), Gholizadeh, H. (Hamid), Giorgis, M. (Melisa), Golub, V. (Valentin), Alsos, I. G. (Inger Greve), Grytnes, J.-A. (John-Arvid), Guerin, G. R. (Gregory Richard), Gutierrez, A. G. (Alvaro G.), Haider, S. (Sylvia), Hatim, M. Z. (Mohamed Z.), Herault, B. (Bruno), Hinojos Mendoza, G. (Guillermo), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Hubau, W. (Wannes), Indreica, A. (Adrian), Janssen, J. A. (John A. M.), Jedrzejek, B. (Birgit), Jentsch, A. (Anke), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Kapfer, J. (Jutta), Karger, D. N. (Dirk Nikolaus), Kavgaci, A. (Ali), Kearsley, E. (Elizabeth), Kessler, M. (Michael), Khanina, L. (Larisa), Killeen, T. (Timothy), Korolyuk, A. (Andrey), Kreft, H. (Holger), Kuehl, H. S. (Hjalmar S.), Kuzemko, A. (Anna), Landucci, F. (Flavia), Lengyel, A. (Attila), Lens, F. (Frederic), Lingner, D. V. (Debora Vanessa), Liu, H. (Hongyan), Lysenko, T. (Tatiana), Mahecha, M. D. (Miguel D.), Marceno, C. (Corrado), Martynenko, V. (Vasiliy), Moeslund, J. E. (Jesper Erenskjold), Monteagudo Mendoza, A. (Abel), Mucina, L. (Ladislav), Muller, J. V. (Jonas V.), Munzinger, J. (Jerome), Naqinezhad, A. (Alireza), Noroozi, J. (Jalil), Nowak, A. (Arkadiusz), Onyshchenko, V. (Viktor), Overbeck, G. E. (Gerhard E.), Partel, M. (Meelis), Pauchard, A. (Anibal), Peet, R. K. (Robert K.), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Peterka, T. (Tomas), Petrik, P. (Petr), Peyre, G. (Gwendolyn), Phillips, O. L. (Oliver L.), Prokhorov, V. (Vadim), Rasomavicius, V. (Valerijus), Revermann, R. (Rasmus), Rivas-Torres, G. (Gonzalo), Rodwell, J. S. (John S.), Ruprecht, E. (Eszter), Rusina, S. (Solvita), Samimi, C. (Cyrus), Schmidt, M. (Marco), Schrodt, F. (Franziska), Shan, H. (Hanhuai), Shirokikh, P. (Pavel), Sibik, J. (Jozef), Silc, U. (Urban), Sklenar, P. (Petr), Skvorc, Z. (Zeljko), Sparrow, B. (Ben), Sperandii, M. G. (Marta Gaia), Stancic, Z. (Zvjezdana), Svenning, J.-C. (Jens-Christian), Tang, Z. (Zhiyao), Tang, C. Q. (Cindy Q.), Tsiripidis, I. (Ioannis), Vanselow, K. A. (Kim Andre), Vasquez Martinez, R. (Rodolfo), Vassilev, K. (Kiril), Velez-Martin, E. (Eduardo), Venanzoni, R. (Roberto), Vibrans, A. C. (Alexander Christian), Violle, C. (Cyrille), Virtanen, R. (Risto), von Wehrden, H. (Henrik), Wagner, V. (Viktoria), Walker, D. A. (Donald A.), Waller, D. M. (Donald M.), Wang, H.-F. (Hua-Feng), Wesche, K. (Karsten), Whitfeld, T. J. (Timothy J. S.), Willner, W. (Wolfgang), Wiser, S. K. (Susan K.), Wohlgemuth, T. (Thomas), Yamalov, S. (Sergey), Zobel, M. (Martin), and Bruelheide, H. (Helge)
- Abstract
Motivation: Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained: Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain: Global, 0.01–40,000 m². Time period and grain: 1888–2015, recording dates. Major taxa and level of measuremen
- Published
- 2021
8. Environmental drivers influencing the abundance of round sardinella (Sardinella aurita) and European sprat (Sprattus sprattus) in different areas of the Mediterranean Sea
- Author
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De Felice, A., Iglesias, Magdalena, Saraux, C., Bonanno, A., Ticina, V., Leonori, I., Ventero, Ana, Hattab, T., Barra, M., Gasparevic, D., Biagiotti, I., Bourdeix, J.H., Genovese, S., Juretic, T., Aronica, S., Malavolti, S., De Felice, A., Iglesias, Magdalena, Saraux, C., Bonanno, A., Ticina, V., Leonori, I., Ventero, Ana, Hattab, T., Barra, M., Gasparevic, D., Biagiotti, I., Bourdeix, J.H., Genovese, S., Juretic, T., Aronica, S., and Malavolti, S.
- Abstract
Data on Sardinella aurita (round sardinella) and Sprattus sprattus (European sprat) in the Mediterranean Sea are limited due to their scarce commercial interest, at least in European countries. Yet, these two small pelagic fish, sitting at opposite ends of the thermal range, could be interesting sentinel species to monitor the effects of climate change in the basin. Using the Mediterranean International Acoustic Surveys (MEDIAS) – the most extensive source of information on these species – we analyzed their biomass in several geographical subareas of the central and western Mediterranean Sea in relation to satellite-derived environmental parameters. Our findings highlight that the S. aurita biomass responded to temperature, salinity, chlorophyll concentration and sea level anomaly, depending on the GSA examined, whereas the S. sprattus biomass correlated significantly with salinity in GSA 6, with salinity and chlorophyll concentration in GSA 7, and with sea level anomaly in GSA 17. These data widen our knowledge of the factors that contribute to the ecology of these species. Further studies of their spatial distribution and of their interactions with other small pelagic species, predators and prey are needed to depict a more comprehensive scenario.
- Published
- 2021
9. The history of hydroacoustic surveys on small pelagic fishes in the European Mediterranean Sea
- Author
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Leonori, I., Tičina, V., Giannoulaki, M., Hattab, T., Iglesias, Magdalena, Bonanno, A., Costantini, I., Canduci, G., Machias, A., Ventero, Ana, Somarakis, S., Tsagarakis, K., Bogner, D., Barra, M., Basilone, G., Genovese, S., Juretić, T., Gašparević, D., De-Felice, A., Leonori, I., Tičina, V., Giannoulaki, M., Hattab, T., Iglesias, Magdalena, Bonanno, A., Costantini, I., Canduci, G., Machias, A., Ventero, Ana, Somarakis, S., Tsagarakis, K., Bogner, D., Barra, M., Basilone, G., Genovese, S., Juretić, T., Gašparević, D., and De-Felice, A.
- Abstract
The study of small pelagic fish by hydroacoustic methods in the Mediterranean Sea began in the Adriatic in the 1950’s. Since 2009, internationally coordinated, extensive, regular surveys have been conducted in the framework of the MEDIAS - Mediterranean International Acoustic Surveys – action, under the EU Data Collection Framework, to provide inputs for the management of small pelagics, particularly European anchovy (Engraulis encrasicolus) and European sardine (Sardina pilchardus). The surveys cover EU Mediterranean waters and monitor the distribution and abundance of small pelagic species using a common protocol. The hydroacoustic surveys, historically conducted by each Country separately, have since been standardized and harmonized. This is a review of the evolution of the surveys from the beginning up to the present and discusses the future prospects. It reports the historical time series of anchovy, sardine and other small pelagics in different areas and describes the spatial and temporal distribution of small pelagic species in decadal maps of the major areas of their distribution in the European Mediterranean Sea. Furthermore, it discusses the use of MEDIAS data for stock assessment purposes, the collection of auxiliary information for an ecosystem-based management approach, the need for further standardization and future challenges.
- Published
- 2021
10. Variability in size at maturity of the European anchovy (Engraulis encrasicolus) in the Mediterranean Sea
- Author
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Ferreri, R., Genovese, S., Barra, M., Biagiotti, I., Bourdeix, J.H., De Felice, A., Gasparevic, D., Hattab, T., Iglesias, Magdalena, Juretic, T., Leonori, I., Malavolti, S., Raykov, V., Saraux, C., Ticina, V., Ventero, Ana, Basilone, G., Ferreri, R., Genovese, S., Barra, M., Biagiotti, I., Bourdeix, J.H., De Felice, A., Gasparevic, D., Hattab, T., Iglesias, Magdalena, Juretic, T., Leonori, I., Malavolti, S., Raykov, V., Saraux, C., Ticina, V., Ventero, Ana, and Basilone, G.
- Abstract
Size at first sexual maturity (L50) represents an important life-history trait that needs to be considered in the development of management measures as it provides fundamental information for avoiding the exploitation of younger individuals. L50 is known to display variability due to fishing pressure, geographical gradients, and environmental features. In this study, to investigate L50 variability among areas in the Mediterranean and Black Seas, maturity ogives of anchovies (Engraulis encrasicolus) were estimated by considering samples collected during the anchovy spawning period in the framework of the MEDiterranean International Acoustic Survey (MEDIAS) program. Anchovy size and sexual maturity data from several geographical subareas (GSAs), i.e., northern Spain, Gulf of Lion, Tyrrhenian Sea, Strait of Sicily, Adriatic Sea and Black Sea, were gathered according to a standard methodological protocol. Maturity ogives were estimated by a logistic regression considering total length, condition factor, sex and GSA. The obtained results showed a significant effect of the condition factor, in that fish in better condition reached maturity earlier, and the results also indicated differences in L50 values among the areas and between the sexes, with males reaching maturity at lower lengths than females. Even though the obtained L50 estimates are relative to the spawning period only, the variability observed at the Mediterranean basin scale highlights the importance of explicitly considering specific habitat characteristics when providing management advice based on an ecosystem approach for fisheries.
- Published
- 2021
11. Temperature strongly correlates with regional patterns of body size variation in Mediterranean small pelagic fish species
- Author
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Hattab, T., Gucu, A., Ventero, Ana, De Felice, A., Machias, A., Saraux, C., Gasparevic, D., Basilone, G., Costantini, I., Leonori, I., Bourdeix, J.H., Iglesias, Magdalena, Barra, M., Giannoulaki, M., Ferreri, R., El Ayoubi, S., Malavolti, S., Genovese, S., Somarakis, S., Juretic, T., Ticina, V., Certain, G., Hattab, T., Gucu, A., Ventero, Ana, De Felice, A., Machias, A., Saraux, C., Gasparevic, D., Basilone, G., Costantini, I., Leonori, I., Bourdeix, J.H., Iglesias, Magdalena, Barra, M., Giannoulaki, M., Ferreri, R., El Ayoubi, S., Malavolti, S., Genovese, S., Somarakis, S., Juretic, T., Ticina, V., and Certain, G.
- Abstract
In this study we consider the applicability of Bergmann’s rule to the populations of small pelagic fish species in the Mediterranean Sea. Under Bergmann’s rule, body size increases with decreasing temperature and increasing latitude. Although this macroecological pattern in body sizes is well established for many taxa of endotherms and ectotherms, it does not remain universal, and the proposed mechanisms underlying it are multiple and still lack consensus. Here we explored the occurrence of geographical body size clines using measurements of average body sizes of 10 species collected in pelagic trawl hauls carried out during acoustic surveys in the Mediterranean Sea. Bergmann’s rule was evaluated by correlating body sizes with latitude and temperature for each species while accounting for potential confounding variables and sampling bias. For 5 species, namely anchovy, sardine, Atlantic chub mackerel, bogue and blue jack mackerel, we demonstrate that they follow Bergmann’s rule, with a decline in average body size by about 3.01, 3.43, 3.67, 3.82 and 3.76 % per 1°C of warming, respectively, although this did not translate with an increase in size with latitude. The adherence of these 5 pelagic fish to Bergmann’s rules strongly suggest that temperature is a major determinant of their body sizes and enables them to act as sentinel species for identifying the drivers and consequences of warming in the Mediterranean ecosystems
- Published
- 2021
12. Phase-change of paraffin inside heat exchangers: an experimental study
- Author
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Dukhan, W. A., primary, Dhaidan, N. S., additional, Al-Hattab, T. A., additional, and Al-Mousawi, F. N., additional
- Published
- 2021
- Full Text
- View/download PDF
13. Species better track the shifting isotherms in the oceans than on lands
- Author
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Lenoir, J., primary, Bertrand, R., additional, Comte, L., additional, Bourgeaud, L., additional, Hattab, T., additional, Murienne, J., additional, and Grenouillet, G., additional
- Published
- 2019
- Full Text
- View/download PDF
14. Global trait:environment relationships of plant communities
- Author
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Bruelheide, H. (Helge), Dengler, J. (Juergen), Purschke, O. (Oliver), Lenoir, J. (Jonathan), Jimenez-Alfaro, B. (Borja), Hennekens, S. M. (Stephan M.), Botta-Dukat, Z. (Zoltan), Chytry, M. (Milan), Field, R. (Richard), Jansen, F. (Florian), Kattge, J. (Jens), Pillar, V. D. (Valerio D.), Schrodt, F. (Franziska), Mahecha, M. D. (Miguel D.), Peet, R. K. (Robert K.), Sandel, B. (Brody), van Bodegom, P. (Peter), Altman, J. (Jan), Alvarez-Davila, E. (Esteban), Khan, M. A. (Mohammed A. S. Arfin), Attorre, F. (Fabio), Aubin, I. (Isabelle), Baraloto, C. (Christopher), Barroso, J. G. (Jorcely G.), Bauters, M. (Marijn), Bergmeier, E. (Erwin), Biurrun, I. (Idoia), Bjorkman, A. D. (Anne D.), Blonder, B. (Benjamin), Carni, A. (Andraz), Cayuela, L. (Luis), Cerny, T. (Tomas), Cornelissen, J. H. (J. Hans C.), Craven, D. (Dylan), Dainese, M. (Matteo), Derroire, G. (Geraldine), De Sanctis, M. (Michele), Diaz, S. (Sandra), Dolezal, J. (Jiri), Farfan-Rios, W. (William), Feldpausch, T. R. (Ted R.), Fenton, N. J. (Nicole J.), Garnier, E. (Eric), Guerin, G. R. (Greg R.), Gutierrez, A. G. (Alvaro G.), Haider, S. (Sylvia), Hattab, T. (Tarek), Henry, G. (Greg), Herault, B. (Bruno), Higuchi, P. (Pedro), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Jentsch, A. (Anke), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Karger, D. N. (Dirk N.), Kessler, M. (Michael), Kleyer, M. (Michael), Knollova, I. (Ilona), Korolyuk, A. Y. (Andrey Y.), Kuehn, I. (Ingolf), Laughlin, D. C. (Daniel C.), Lens, F. (Frederic), Loos, J. (Jacqueline), Louault, F. (Frederique), Lyubenova, M. I. (Mariyana, I), Malhi, Y. (Yadvinder), Marceno, C. (Corrado), Mencuccini, M. (Maurizio), Mueller, J. V. (Jonas, V), Munzinger, J. (Jerome), Myers-Smith, I. H. (Isla H.), Neill, D. A. (David A.), Niinemets, U. (Ulo), Orwin, K. H. (Kate H.), Ozinga, W. A. (Wim A.), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Petrik, P. (Petr), Phillips, O. L. (Oliver L.), Partel, M. (Meelis), Reich, P. B. (Peter B.), Roemermann, C. (Christine), Rodrigues, A. V. (Arthur, V), Sabatini, F. M. (Francesco Maria), Sardans, J. (Jordi), Schmidt, M. (Marco), Seidler, G. (Gunnar), Silva Espejo, J. E. (Javier Eduardo), Silveira, M. (Marcos), Smyth, A. (Anita), Sporbert, M. (Maria), Svenning, J.-C. (Jens-Christian), Tang, Z. (Zhiyao), Thomas, R. (Raquel), Tsiripidis, I. (Ioannis), Vassilev, K. (Kiril), Violle, C. (Cyrille), Virtanen, R. (Risto), Weiher, E. (Evan), Welk, E. (Erik), Wesche, K. (Karsten), Winter, M. (Marten), Wirth, C. (Christian), Jandt, U. (Ute), Bruelheide, H. (Helge), Dengler, J. (Juergen), Purschke, O. (Oliver), Lenoir, J. (Jonathan), Jimenez-Alfaro, B. (Borja), Hennekens, S. M. (Stephan M.), Botta-Dukat, Z. (Zoltan), Chytry, M. (Milan), Field, R. (Richard), Jansen, F. (Florian), Kattge, J. (Jens), Pillar, V. D. (Valerio D.), Schrodt, F. (Franziska), Mahecha, M. D. (Miguel D.), Peet, R. K. (Robert K.), Sandel, B. (Brody), van Bodegom, P. (Peter), Altman, J. (Jan), Alvarez-Davila, E. (Esteban), Khan, M. A. (Mohammed A. S. Arfin), Attorre, F. (Fabio), Aubin, I. (Isabelle), Baraloto, C. (Christopher), Barroso, J. G. (Jorcely G.), Bauters, M. (Marijn), Bergmeier, E. (Erwin), Biurrun, I. (Idoia), Bjorkman, A. D. (Anne D.), Blonder, B. (Benjamin), Carni, A. (Andraz), Cayuela, L. (Luis), Cerny, T. (Tomas), Cornelissen, J. H. (J. Hans C.), Craven, D. (Dylan), Dainese, M. (Matteo), Derroire, G. (Geraldine), De Sanctis, M. (Michele), Diaz, S. (Sandra), Dolezal, J. (Jiri), Farfan-Rios, W. (William), Feldpausch, T. R. (Ted R.), Fenton, N. J. (Nicole J.), Garnier, E. (Eric), Guerin, G. R. (Greg R.), Gutierrez, A. G. (Alvaro G.), Haider, S. (Sylvia), Hattab, T. (Tarek), Henry, G. (Greg), Herault, B. (Bruno), Higuchi, P. (Pedro), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Jentsch, A. (Anke), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Karger, D. N. (Dirk N.), Kessler, M. (Michael), Kleyer, M. (Michael), Knollova, I. (Ilona), Korolyuk, A. Y. (Andrey Y.), Kuehn, I. (Ingolf), Laughlin, D. C. (Daniel C.), Lens, F. (Frederic), Loos, J. (Jacqueline), Louault, F. (Frederique), Lyubenova, M. I. (Mariyana, I), Malhi, Y. (Yadvinder), Marceno, C. (Corrado), Mencuccini, M. (Maurizio), Mueller, J. V. (Jonas, V), Munzinger, J. (Jerome), Myers-Smith, I. H. (Isla H.), Neill, D. A. (David A.), Niinemets, U. (Ulo), Orwin, K. H. (Kate H.), Ozinga, W. A. (Wim A.), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Petrik, P. (Petr), Phillips, O. L. (Oliver L.), Partel, M. (Meelis), Reich, P. B. (Peter B.), Roemermann, C. (Christine), Rodrigues, A. V. (Arthur, V), Sabatini, F. M. (Francesco Maria), Sardans, J. (Jordi), Schmidt, M. (Marco), Seidler, G. (Gunnar), Silva Espejo, J. E. (Javier Eduardo), Silveira, M. (Marcos), Smyth, A. (Anita), Sporbert, M. (Maria), Svenning, J.-C. (Jens-Christian), Tang, Z. (Zhiyao), Thomas, R. (Raquel), Tsiripidis, I. (Ioannis), Vassilev, K. (Kiril), Violle, C. (Cyrille), Virtanen, R. (Risto), Weiher, E. (Evan), Welk, E. (Erik), Wesche, K. (Karsten), Winter, M. (Marten), Wirth, C. (Christian), and Jandt, U. (Ute)
- Abstract
Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait–environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.
- Published
- 2018
15. Global trait–environment relationships of plant communities
- Author
-
Bruelheide, H., Dengler, J., Purschke, O., Lenoir, J., Jiménez‐Alfaro, B., Hennekens, S.M., Botta-Dukát, Z., Chytrý, M., Field, R., Jansen, F., Kattge, J., Pillar, V.D., Schrodt, F., Mahecha, M.D., Peet, R.K., Sandel, B., van Bodegom, P., Altman, J., Alvarez-Dávila, E., Khan, M.A.S.A., Attorre, F., Aubin, I., Baraloto, C., Barroso, J.G., Bauters, M., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Blonder, B., Čarni, A., Cayuela, L., Černý, T., Cornelissen, J.H.C., Craven, Dylan, Dainese, M., Derroire, G., De Sanctis, M., Díaz, S., Doležal, J., Farfan-Rios, W., Feldpausch, T.R., Fenton, N.J., Garnier, E., Guerin, G.R., Gutiérrez, A.G., Haider, S., Hattab, T., Henry, G., Hérault, B., Higuchi, P., Hölzel, N., Homeier, J., Jentsch, A., Jürgens, N., Kącki, Z., Karger, D.N., Kessler, M., Kleyer, M., Knollová, I., Korolyuk, A.Y., Kühn, Ingolf, Laughlin, D.C., Lens, F., Loos, J., Louault, F., Lyubenova, M.I., Malhi, Y., Marcenò, C., Mencuccini, M., Müller, J.V., Munzinger, J., Myers-Smith, I.H., Neill, D.A., Niinemets, Ü., Orwin, K.H., Ozinga, W.A., Penuelas, J., Pérez-Haase, A., Petřík, P., Phillips, O.L., Pärtel, M., Reich, P.B., Römermann, C., Rodrigues, A.V., Sabatini, F.M., Sardans, J., Schmidt, M., Seidler, G., Silva Espejo, J.E., Silveira, M., Smyth, A., Sporbert, M., Svenning, J.-C., Tang, Z., Thomas, R., Tsiripidis, I., Vassilev, K., Violle, C., Virtanen, Risto, Weiher, E., Bruelheide, H., Dengler, J., Purschke, O., Lenoir, J., Jiménez‐Alfaro, B., Hennekens, S.M., Botta-Dukát, Z., Chytrý, M., Field, R., Jansen, F., Kattge, J., Pillar, V.D., Schrodt, F., Mahecha, M.D., Peet, R.K., Sandel, B., van Bodegom, P., Altman, J., Alvarez-Dávila, E., Khan, M.A.S.A., Attorre, F., Aubin, I., Baraloto, C., Barroso, J.G., Bauters, M., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Blonder, B., Čarni, A., Cayuela, L., Černý, T., Cornelissen, J.H.C., Craven, Dylan, Dainese, M., Derroire, G., De Sanctis, M., Díaz, S., Doležal, J., Farfan-Rios, W., Feldpausch, T.R., Fenton, N.J., Garnier, E., Guerin, G.R., Gutiérrez, A.G., Haider, S., Hattab, T., Henry, G., Hérault, B., Higuchi, P., Hölzel, N., Homeier, J., Jentsch, A., Jürgens, N., Kącki, Z., Karger, D.N., Kessler, M., Kleyer, M., Knollová, I., Korolyuk, A.Y., Kühn, Ingolf, Laughlin, D.C., Lens, F., Loos, J., Louault, F., Lyubenova, M.I., Malhi, Y., Marcenò, C., Mencuccini, M., Müller, J.V., Munzinger, J., Myers-Smith, I.H., Neill, D.A., Niinemets, Ü., Orwin, K.H., Ozinga, W.A., Penuelas, J., Pérez-Haase, A., Petřík, P., Phillips, O.L., Pärtel, M., Reich, P.B., Römermann, C., Rodrigues, A.V., Sabatini, F.M., Sardans, J., Schmidt, M., Seidler, G., Silva Espejo, J.E., Silveira, M., Smyth, A., Sporbert, M., Svenning, J.-C., Tang, Z., Thomas, R., Tsiripidis, I., Vassilev, K., Violle, C., Virtanen, Risto, and Weiher, E.
- Abstract
Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait–environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.
- Published
- 2018
16. Mapping invasive plant species with a combination of field and remote sensing data
- Author
-
Skowronek, S., Ewald, M., Aerts, R., Warrie, J., Van De Kerchove, R., Kempeneers, P., Honnay, O., Lenoir, J., Hattab, T., Somers, B., Schmidtlein, S., Rocchini, D., and Feilhauer, H.
- Subjects
Species invasion ,Settore BIO/07 - ECOLOGIA ,Remote sensing - Published
- 2016
17. The Mediterranean region under climate change : a scientific update
- Author
-
Moullec, Fabien, Ben Rais Lasram, Frida, Coll, Marta, Guilhaumon, François, Halouani, G., Hattab, T., le Loc´H, François, Shin, Yunne-Jai, MARine Biodiversity Exploitation and Conservation (UMR MARBEC), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut de Recherche pour le Développement (IRD), Institut National Agronomique de Tunisie (INAT), Université du Littoral Côte d'Opale (ULCO), Institute of Marine Sciences / Institut de Ciències del Mar [Barcelona] (ICM), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Ecologie et Dynamique des Systèmes Anthropisés - UMR CNRS 7058 (EDYSAN), Centre National de la Recherche Scientifique (CNRS)-Université de Picardie Jules Verne (UPJV), Laboratoire des Sciences de l'Environnement Marin (LEMAR) (LEMAR), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD), Thiébault S., Moatti, J.-P., Thiébault, S. (ed.), Moatti, Jean-Paul (ed.), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), and Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)
- Subjects
Expected impacts ,MIGRATION ,ECOSYSTEME ,Climate Change ,Individual to ecosystem level ,FACTEUR ANTHROPIQUE ,Trophic levels ,Spatial distribution range ,POISSON MARIN ,PECHE MARITIME ,Mediterranean Sea ,Adaptation ,TEMPERATURE ,Physiological processes ,BIODIVERSITE ,Temperature ,OS ,INVASION BIOLOGIQUE ,Fish ,FACTEUR CLIMATIQUE ,CHANGEMENT CLIMATIQUE ,MILIEU MARIN ,Environmental changes ,DYNAMIQUE DE POPULATION ,RECHAUFFEMENT ,[SDE.BE]Environmental Sciences/Biodiversity and Ecology ,REPARTITION GEOGRAPHIQUE ,IMPACT SUR L'ENVIRONNEMENT - Abstract
This book, coordinated by AllEnvi, is published on the occasion of the 22nd Conference of the Parties to the United Nations Framework Convention on Climate Change (COP22, Marrakech, 2016).-- 20 pages, 4 figures, 4 boxes, Temperature has a major direct effect on the physiology, growth, reproduction, recruitment and behavior of poikilothermic organisms such as fish. It affects many physiological processes ranging from damaging proteins to disrupting organ function. Environmental changes, especially climate warming, may thus strongly influence the abundance and biogeography of fish through species-specific physiological thresholds of temperature tolerance, or through responses to changes in other trophic levels (Perry et al. 2005, Sabates et al. 2006, Rijnsdorp et al. 2009). Organisms tend to adapt to local environmental temperatures, with optimal physiological responses matching temperatures that are close to the environmental average (Hoegh-Guldberg & Bruno 2010). In this context, shifts in the spatial distribution range of marine organisms are among the most perceptible consequences of climate change at the world scale, with potentially significant impacts on commercial fisheries (Perry et al. 2005), on food webs and ecosystem functioning (Doney et al. 2012, Albouy et al. 2014), and on biodiversity as a whole (Harley 2011, Bellard et al. 2012). The warming of the Mediterranean Sea affects the fitness of marine biota as already shown by records of changes in abundance, survival and fertility,phenology and species migration (Marbà et al. 2015). Population abundance and survival are the biological variables are the most frequently reported impacts of Mediterranean warming, followed by migration of native and introduced species (Marbà et al. 2015). However, the sensitivity of Mediterranean biota to warming varies across taxonomic groups (Marbà et al. 2015), from primary producers to high trophic levels, with possible synergistic effects with other anthropogenic impacts such as high exploitation (Harley et al. 2006). In this chapter, we use examples to analyze the expected impacts of climate change on marine organisms in the Mediterranean Sea, with a focus on fish, and to investigate possible responses from individual to ecosystem level. It is important to bear in mind that in the Mediterranean Sea, the effects of climate change occur in parallel with other human-driven effects such as overfishing, pollution, and habitat degradation (Coll et al. 2010), and can have cumulative effects, frequently of synergistic nature (Calvo et al. 2011)
- Published
- 2016
18. Modelling of habitat suitability and population dynamics of an invasive plant with advanced remote sensing data
- Author
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Hattab, T., Rocchini, D., Somers, B., Feilhauer, H., Warrie, J., Ewald, M., Honnay, O., Kempeneers, P., Aerts, R., Van De Kerchove, R., Skowronek, S., Schmidtlein, S., and Lenoir, J.
- Subjects
Habitat suitability ,Settore BIO/07 - ECOLOGIA ,Habitat potenziale - Published
- 2015
19. Climate change impacts on marine resources : From individual to ecosystem responses
- Author
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Moullec, Fabien, Ben Rais Lasram, Frida, Coll, Marta, Guilhaumon, François, Halouani, G., Hattab, T., le Loc´H, François, Shin, Yunne-Jai, Moullec, Fabien, Ben Rais Lasram, Frida, Coll, Marta, Guilhaumon, François, Halouani, G., Hattab, T., le Loc´H, François, and Shin, Yunne-Jai
- Abstract
Temperature has a major direct effect on the physiology, growth, reproduction, recruitment and behavior of poikilothermic organisms such as fish. It affects many physiological processes ranging from damaging proteins to disrupting organ function. Environmental changes, especially climate warming, may thus strongly influence the abundance and biogeography of fish through species-specific physiological thresholds of temperature tolerance, or through responses to changes in other trophic levels (Perry et al. 2005, Sabates et al. 2006, Rijnsdorp et al. 2009). Organisms tend to adapt to local environmental temperatures, with optimal physiological responses matching temperatures that are close to the environmental average (Hoegh-Guldberg & Bruno 2010). In this context, shifts in the spatial distribution range of marine organisms are among the most perceptible consequences of climate change at the world scale, with potentially significant impacts on commercial fisheries (Perry et al. 2005), on food webs and ecosystem functioning (Doney et al. 2012, Albouy et al. 2014), and on biodiversity as a whole (Harley 2011, Bellard et al. 2012). The warming of the Mediterranean Sea affects the fitness of marine biota as already shown by records of changes in abundance, survival and fertility,phenology and species migration (Marbà et al. 2015). Population abundance and survival are the biological variables are the most frequently reported impacts of Mediterranean warming, followed by migration of native and introduced species (Marbà et al. 2015). However, the sensitivity of Mediterranean biota to warming varies across taxonomic groups (Marbà et al. 2015), from primary producers to high trophic levels, with possible synergistic effects with other anthropogenic impacts such as high exploitation (Harley et al. 2006). In this chapter, we use examples to analyze the expected impacts of climate change on marine organisms in the Mediterranean Sea, with a focus on fish, and to investigate pos
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- 2016
20. How Fishing impacts Mediterranean marine ecosystems? An EcoTroph modeling approach
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Halouani, G., Gascuel, Didier, Hattab, T., Ben Rais Lasram, Frida, Coll, Marta, Tsagarakis, K., Piroddi, Chiara, Romdhane, Mohamed Salah, and le Loc´H, François
- Abstract
Conference and workshops Ecopath 30 years – Modelling ecosystem dynamics: beyond boundaries with EwE, 4-14 November 2014, Barcelona, Spain.-- 23 pages, 1 figure, 1 table, The use of trophic models such as Ecopath with Ecosim (EwE) (Christensen and Walters, 2004) is an effective way to describe the trophic structure and functioning of the ecosystem. But comparison or meta-analyses are often difficult between models built using heterogeneous approaches, and especially using different species aggregations into trophic boxes, This publication has been produced with the financial support of the DPF PhD fellowships program of the Institut de Recherche pour le Développement (IRD) for GH and TH and was partly funded by the projects BISTROMED (ENVI-Med – MISTRALS) and CHARMMED (Fondation TOTAL)
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- 2014
21. Ecological indicators to capture the effects of fishing on biodiversity and conservation status of marine ecosystems
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Coll, M., primary, Shannon, L.J., additional, Kleisner, K.M., additional, Juan-Jordá, M.J., additional, Bundy, A., additional, Akoglu, A.G., additional, Banaru, D., additional, Boldt, J.L., additional, Borges, M.F., additional, Cook, A., additional, Diallo, I., additional, Fu, C., additional, Fox, C., additional, Gascuel, D., additional, Gurney, L.J., additional, Hattab, T., additional, Heymans, J.J., additional, Jouffre, D., additional, Knight, B.R., additional, Kucukavsar, S., additional, Large, S.I., additional, Lynam, C., additional, Machias, A., additional, Marshall, K.N., additional, Masski, H., additional, Ojaveer, H., additional, Piroddi, C., additional, Tam, J., additional, Thiao, D., additional, Thiaw, M., additional, Torres, M.A., additional, Travers-Trolet, M., additional, Tsagarakis, K., additional, Tuck, I., additional, van der Meeren, G.I., additional, Yemane, D., additional, Zador, S.G., additional, and Shin, Y.-J., additional
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- 2016
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22. Fishing impact in Mediterranean ecosystems: an EcoTroph modeling approach
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Halouani, G., Gascuel, Didier, Hattab, T., Lasram, Frida Ben Rais, Coll, Marta, Tsagarakis, K., Piroddi, Chiara, Romdhane, Mohamed Salah, le Loc´H, François, Halouani, G., Gascuel, Didier, Hattab, T., Lasram, Frida Ben Rais, Coll, Marta, Tsagarakis, K., Piroddi, Chiara, Romdhane, Mohamed Salah, and le Loc´H, François
- Abstract
The EcoTroph modeling approach was applied to five Mediterranean marine ecosystems to characterize their food webs and investigate their responses to several simulated fishing scenarios. First, EcoTroph was used to synthesize the outputs of five pre-existing heterogeneous Ecopath models in a common framework, and thus to compare different ecosystems through their trophic spectra of biomass, catch, and fishing mortalities. This approach contributes to our understanding of ecosystem functioning, from both ecological and fisheries perspectives. Then, we assessed the sensitivity of each ecosystem to fishery, using EcoTroph simulations. For the five ecosystems considered, we simulated the effects of increasing or decreasing fishing mortalities on both the biomass and the catch per trophic class. Our results emphasize that the Mediterranean Sea is strongly affected by the depletion of high trophic level organisms. Results also show that fisheries impacts, at the trophic level scale, differ between ecosystems according to their trophic structure and exploitation patterns. A top-down compensation effect is observed in some simulations where a fishing-induced decrease in the biomass of predators impacts their prey, leading to an increase in the biomass at lower trophic levels. The results of this comparative analysis highlight that ecosystems where top-down controls are observed are less sensitive to variations in fishing mortality in terms of total ecosystem biomass. This suggests that the magnitude of top-down control present in a system can affect its stability. © 2015 Elsevier B.V.
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- 2015
23. An ecosystem model of an exploited southern Mediterranean shelf region (Gulf of Gabes, Tunisia) and a comparison with other Mediterranean ecosystem model properties
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Hattab, T., Lasram, F. B. R., Albouy, C., Romdhane, M. S., Jarboui, O., Halouani, G., Cury, Philippe, and Le Loc'h, François
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Ecosystem approach to fisheries ,Ecosystem modeling ,Mediterranean Sea ,Food web ,Ecopath ,Trophic structure ,Gulf of Gabes - Abstract
In this paper, we describe an exploited continental shelf ecosystem (Gulf of Gabes) in the southern Mediterranean Sea using an Ecopath mass-balance model. This allowed us to determine the structure and functioning of this ecosystem and assess the impacts of fishing upon it. The model represents the average state of the ecosystem between 2000 and 2005. It includes 41 functional groups, which encompass the entire trophic spectrum from phytoplankton to higher trophic levels (e.g., fishes, birds, and mammals), and also considers the fishing activities in the area (five fleets). Model results highlight an important bentho-pelagic coupling in the system due to the links between plankton and benthic invertebrates through detritus. A comparison of this model with those developed for other continental shelf regions in the Mediterranean (i.e., the southern Catalan, the northern-central Adriatic, and the northern Aegean Seas) emphasizes similar patterns in their trophic functioning. Low and medium trophic levels (i.e., zooplanlcton, benthic molluscs, and polychaetes) and sharks were identified as playing key ecosystem roles and were classified as keystone groups. An analysis of ecosystem attributes indicated that the Gulf of Gabes is the least mature (i.e., in the earliest stages of ecosystem development) of the four ecosystems that were compared and it is suggested that this is due, at least in part, to the impacts of fishing. Bottom trawling was identified as having the widest-ranging impacts across the different functional groups and the largest impacts on some commercially-targeted demersal fish species. Several exploitation indices highlighted that the Gulf of Gabes ecosystem is highly exploited, a finding which is supported by stock assessment outcomes. This suggests that it is unlikely that the gulf can be fished at sustainable levels, a situation which is similar to other marine ecosystems in the Mediterranean Sea. Crown Copyright (c) 2013 Published by Elsevier B.V. All rights reserved.
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- 2013
24. A trophodynamic approach for the evaluation of Fishery Management Plans in the gulf of Gabes (Southern Tunisia)
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Halouani, G., Hattab, T., Ben Rais Lasram, F., Romdhane, M.S., and Le Loc'h, François
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GESTION DES PECHES ,STRUCTURE TROPHIQUE ,RELATION TROPHIQUE ,MODELISATION - Abstract
An Ecopath with Ecosim food web model of the Gulf of Gabes (southern Tunisia) was constructed in order to describe its trophic structure and functioning. To assess the impacts of fisheries, an Ecosim routine was applied to predict temporal variation of catches. The model was fitted with time series data of landings for the period 1995-2008. Then, several fishery management plans were simulated by implementing different biological rest-periods. To a better evaluation of each management plan, ecological and socio-economic indicators were calculated. These indicators were used to i) establish a ranking between the fishery management plans, ii) study the effects of conservation measures on the ecosystem.
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- 2013
25. Cumulative human threats on fish biodiversity components in Tunisian waters
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BEN RAIS LASRAM, F., primary, HATTAB, T., additional, HALOUANI, G., additional, ROMDHANE, M.S., additional, LE LOC'H, F., additional, and ALBOUY, C., additional
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- 2015
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26. An EcoTroph modeling approach to determining fishing impacts on Mediterranean marine ecosystems
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Halouani, G., Gascuel, Didier, Hattab, T., Ben Rais Lasram, Frida, Coll, Marta, Tsagarakis, K., Piroddi, Chiara, Romdhane, Mohamed Salah, le Loc´H, François, Halouani, G., Gascuel, Didier, Hattab, T., Ben Rais Lasram, Frida, Coll, Marta, Tsagarakis, K., Piroddi, Chiara, Romdhane, Mohamed Salah, and le Loc´H, François
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- 2014
27. A laboratory study of efficiency of sand drains in relation to methods of installation and spacing.
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Singh, G. and Hattab, T. N.
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- 1979
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28. Invasion by the Alien Tree Prunus serotina Alters Ecosystem Functions in a Temperate Deciduous Forest
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Aerts, R., Ewald, M., Nicolas, M., Piat, J., Skowronek, S., Lenoir, J., Hattab, T., Garzón-López, C. X., Feilhauer, H., Schmidtlein, S., Rocchini, D., Decocq, G., Somers, B., Van De Kerchove, R., Denef, K., and Honnay, O.
- Subjects
heterotrophic respiration ,litter ,13. Climate action ,biological invasion ,biogeochemical cycles ,canopy foliar nutrients ,15. Life on land ,exotic species ,American black cherry ,invasive species - Abstract
Alien invasive species can affect large areas, often with wide-ranging impacts on ecosystem structure, function, and services. Prunus serotina is a widespread invader of European temperate forests, where it tends to form homogeneous stands and limits recruitment of indigenous trees. We hypotesized that invasion by P. serotina would be reflected in the nutrient contents of the native species’ leaves and in the respiration of invaded plots as efficient resource uptake and changes in nutrient cycling by P. serotina probably underly its aggressive invasiveness. We combined data from 48 field plots in the forest of Compiègne, France, and data from an experiment using 96 microcosms derived from those field plots. We used general linear models to separate effects of invasion by P. serotina on heterotrophic soil and litter respiration rates and on canopy foliar nutrient content from effects of soil chemical properties, litter quantity, litter species composition, and tree species composition. In invaded stands, average respiration rates were 5.6% higher for soil (without litter) and 32% higher for soil and litter combined. Compared to indigenous tree species, P. serotina exhibited higher foliar N (+24.0%), foliar P (+50.7%), and lower foliar C:N (−22.4%) and N:P (−10.1%) ratios. P. serotina affected foliar nutrient contents of co-occuring indigenous tree species leading to decreased foliar N (−8.7 %) and increased C:N ratio (+9.5%) in Fagus sylvatica, decreased foliar N:P ratio in Carpinus betulus (−13.5%) and F. sylvatica (−11.8%), and increased foliar P in Pinus sylvestris (+12.3%) in invaded vs. uninvaded stands. Our results suggest that P. serotina is changing nitrogen, phosphorus, and carbon cycles to its own advantage, hereby increasing carbon turnover via labile litter, affecting the relative nutrient contents in the overstory leaves, and potentially altering the photosynthetic capacity of the long-lived indigenous broadleaved species. Uncontrolled invasion of European temperate forests by P. serotina may affect the climate change mitigation potential of these forests in the long term, through additive effects on local nutrient cycles.
29. Predictive Habitats Modelling for Marine Spatial Planning
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Hattab, T., Ben Rais Lasram, F., Albouy, C., Sammari, C., Romdhane, M. S., philippe Cury, Leprieur, F., and Le Loc H, F.
30. sPlotOpen – An environmentally balanced, open‐access, global dataset of vegetation plots
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Ben Sparrow, V. B. Martynenko, Jonathan Lenoir, Eszter Ruprecht, Idoia Biurrun, Luzmila Arroyo, Borja Jiménez-Alfaro, Aníbal Pauchard, Roberto Venanzoni, Stephan M. Hennekens, Mohamed Z. Hatim, Cyrus Samimi, Arkadiusz Nowak, Gerhard E. Overbeck, Petr Sklenář, Renata Ćušterevska, Valentin Golub, Eduardo Vélez-Martin, Gwendolyn Peyre, Inger Greve Alsos, Ioannis Tsiripidis, Tarek Hattab, Andrey Yu. Korolyuk, Jutta Kapfer, Jörg Ewald, Donald M. Waller, Ute Jandt, Tetiana Dziuba, Marco Schmidt, Alvaro G. Gutiérrez, Thomas Wohlgemuth, Adrian Indreica, Zygmunt Kącki, Jürgen Dengler, Željko Škvorc, Dirk Nikolaus Karger, Panayotis Dimopoulos, Viktor Onyshchenko, Hanhuai Shan, John Janssen, Hua Feng Wang, Holger Kreft, Jérôme Munzinger, Brian J. Enquist, Frederic Lens, Wannes Hubau, Birgit Jedrzejek, Alexander Christian Vibrans, Miguel D. Mahecha, Emmanuel Garbolino, Sophie Gachet, Abel Monteagudo Mendoza, Josep Peñuelas, Melisa A. Giorgis, Svetlana Aćić, Débora Vanessa Lingner, Victor V. Chepinoga, Richard Field, Ladislav Mucina, Michele De Sanctis, Mohamed A. El-Sheikh, Isabelle Aubin, Hamid Gholizadeh, Fahmida Sultana, Fabio Attorre, Valerijus Rašomavičius, Cindy Q. Tang, Tomáš Černý, Gonzalo Rivas-Torres, Donald A. Walker, Alicia Teresa Rosario Acosta, Timothy J. Killeen, Francesco Maria Sabatini, Susan K. Wiser, Urban Šilc, Andraž Čarni, Florian Jansen, Valério D. Pillar, Jonas V. Müller, Aaron Pérez-Haase, Els De Bie, Antonio Galán-de-Mera, Zhiyao Tang, Anne D. Bjorkman, Sylvia Haider, Kiril Vassilev, Risto Virtanen, Henrik von Wehrden, Hjalmar S. Kühl, Manfred Finckh, Zvjezdana Stančić, Pavel Shirokikh, Elizabeth Kearsley, Petr Petřík, Yves Bergeron, Iva Apostolova, Emiliano Agrillo, Jozef Šibík, Norbert Jürgens, Marta Gaia Sperandii, Anna Kuzemko, Jens-Christian Svenning, Timothy J. S. Whitfeld, Michael Kessler, Bruno Hérault, John-Arvid Grytnes, Laura Casella, Tomáš Peterka, Miguel Alvarez, Tsipe Aavik, Gregory Richard Guerin, André Luis de Gasper, Corrado Marcenò, Luis Cayuela, Brody Sandel, Cyrille Violle, Jens Kattge, Guillermo Hinojos Mendoza, Anke Jentsch, Arindam Banerjee, Jesper Erenskjold Moeslund, Mohammed Abu Sayed Arfin Khan, Patrice de Ruffray, Milan Chytrý, S. M. Yamalov, Tatiana Lysenko, Meelis Pärtel, Viktoria Bondareva, Helge Bruelheide, John S. Rodwell, Jiri Dolezal, Oliver L. Phillips, Rasmus Revermann, Larisa Khanina, Erwin Bergmeier, Robert K. Peet, Jörg Brunet, Solvita Rūsiņa, Oliver Purschke, Gianmaria Bonari, Jürgen Homeier, Martin Zobel, János Csiky, Marijn Bauters, Jalil Noroozi, Karsten Wesche, Kim André Vanselow, Norbert Hölzel, Flavia Landucci, Farideh Fazayeli, Wolfgang Willner, Viktoria Wagner, Alireza Naqinezhad, Aurora Levesley, Vadim Prokhorov, Hongyan Liu, Ali Kavgaci, Rodolfo Vásquez Martínez, Franziska Schrodt, Attila Lengyel, Elise A. Arnst, Sabatini F.M., Lenoir J., Hattab T., Arnst E.A., Chytry M., Dengler J., De Ruffray P., Hennekens S.M., Jandt U., Jansen F., Jimenez-Alfaro B., Kattge J., Levesley A., Pillar V.D., Purschke O., Sandel B., Sultana F., Aavik T., Acic S., Acosta A.T.R., Agrillo E., Alvarez M., Apostolova I., Arfin Khan M.A.S., Arroyo L., Attorre F., Aubin I., Banerjee A., Bauters M., Bergeron Y., Bergmeier E., Biurrun I., Bjorkman A.D., Bonari G., Bondareva V., Brunet J., Carni A., Casella L., Cayuela L., Cerny T., Chepinoga V., Csiky J., Custerevska R., De Bie E., de Gasper A.L., De Sanctis M., Dimopoulos P., Dolezal J., Dziuba T., El-Sheikh M.A.E.-R.M., Enquist B., Ewald J., Fazayeli F., Field R., Finckh M., Gachet S., Galan-de-Mera A., Garbolino E., Gholizadeh H., Giorgis M., Golub V., Alsos I.G., Grytnes J.-A., Guerin G.R., Gutierrez A.G., Haider S., Hatim M.Z., Herault B., Hinojos Mendoza G., Holzel N., Homeier J., Hubau W., Indreica A., Janssen J.A.M., Jedrzejek B., Jentsch A., Jurgens N., Kacki Z., Kapfer J., Karger D.N., Kavgaci A., Kearsley E., Kessler M., Khanina L., Killeen T., Korolyuk A., Kreft H., Kuhl H.S., Kuzemko A., Landucci F., Lengyel A., Lens F., Lingner D.V., Liu H., Lysenko T., Mahecha M.D., Marceno C., Martynenko V., Moeslund J.E., Monteagudo Mendoza A., Mucina L., Muller J.V., Munzinger J., Naqinezhad A., Noroozi J., Nowak A., Onyshchenko V., Overbeck G.E., Partel M., Pauchard A., Peet R.K., Penuelas J., Perez-Haase A., Peterka T., Petrik P., Peyre G., Phillips O.L., Prokhorov V., Rasomavicius V., Revermann R., Rivas-Torres G., Rodwell J.S., Ruprecht E., Rusina S., Samimi C., Schmidt M., Schrodt F., Shan H., Shirokikh P., Sibik J., Silc U., Sklenar P., Skvorc Z., Sparrow B., Sperandii M.G., Stancic Z., Svenning J.-C., Tang Z., Tang C.Q., Tsiripidis I., Vanselow K.A., Vasquez Martinez R., Vassilev K., Velez-Martin E., Venanzoni R., Vibrans A.C., Violle C., Virtanen R., von Wehrden H., Wagner V., Walker D.A., Waller D.M., Wang H.-F., Wesche K., Whitfeld T.J.S., Willner W., Wiser S.K., Wohlgemuth T., Yamalov S., Zobel M., Bruelheide H., Sabatini, Fm, Lenoir, J, Hattab, T, Arnst, Ea, Chytry, M, Dengler, J, De Ruffray, P, Hennekens, Sm, Jandt, U, Jansen, F, Jimenez-Alfaro, B, Kattge, J, Levesley, A, Pillar, Vd, Purschke, O, Sandel, B, Sultana, F, Aavik, T, Acic, S, Acosta, Atr, Agrillo, E, Alvarez, M, Apostolova, I, Khan, Masa, Arroyo, L, Attorre, F, Aubin, I, Banerjee, A, Bauters, M, Bergeron, Y, Bergmeier, E, Biurrun, I, Bjorkman, Ad, Bonari, G, Bondareva, V, Brunet, J, Carni, A, Casella, L, Cayuela, L, Cerny, T, Chepinoga, V, Csiky, J, Custerevska, R, De Bie, E, de Gasper, Al, De Sanctis, M, Dimopoulos, P, Dolezal, J, Dziuba, T, El-Sheikh, Mam, Enquist, B, Ewald, J, Fazayeli, F, Field, R, Finckh, M, Gachet, S, Galan-de-Mera, A, Garbolino, E, Gholizadeh, H, Giorgis, M, Golub, V, Alsos, Ig, Grytnes, Ja, Guerin, Gr, Gutierrez, Ag, Haider, S, Hatim, Mz, Herault, B, Mendoza, Gh, Holzel, N, Homeier, J, Hubau, W, Indreica, A, Janssen, Jam, Jedrzejek, B, Jentsch, A, Jurgens, N, Kacki, Z, Kapfer, J, Karger, Dn, Kavgaci, A, Kearsley, E, Kessler, M, Khanina, L, Killeen, T, Korolyuk, A, Kreft, H, Kuhl, H, Kuzemko, A, Landucci, F, Lengyel, A, Lens, F, Lingner, Dv, Liu, Hy, Lysenko, T, Mahecha, Md, Marceno, C, Martynenko, V, Moeslund, Je, Mendoza, Am, Mucina, L, Muller, Jv, Munzinger, Jm, Naqinezhad, A, Noroozi, J, Nowak, A, Onyshchenko, V, Overbeck, Ge, Partel, M, Pauchard, A, Peet, Rk, Penuelas, J, Perez-Haase, A, Peterka, T, Petrik, P, Peyre, G, Phillips, Ol, Prokhorov, V, Rasomavicius, V, Revermann, R, Rivas-Torres, G, Rodwell, J, Ruprecht, E, Rusina, S, Samimi, C, Schmidt, M, Schrodt, F, Shan, Hh, Shirokikh, P, Sibik, J, Silc, U, Sklenar, P, Skvorc, Z, Sparrow, B, Sperandii, Mg, Stancic, Z, Svenning, Jc, Tang, Zy, Tang, Cq, Tsiripidis, I, Vanselow, Ka, Martinez, Rv, Vassilev, K, Velez-Martin, E, Venanzoni, R, Vibrans, Ac, Violle, C, Virtanen, R, von Wehrden, H, Wagner, V, Walker, Da, Waller, Dm, Wang, Hf, Wesche, K, Whitfeld, Tj, Willner, W, Wiser, Sk, Wohlgemuth, T, Yamalov, S, Zobel, M, Bruelheide, H, Ecologie et Dynamique des Systèmes Anthropisés - UMR CNRS 7058 (EDYSAN), Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), MARine Biodiversity Exploitation and Conservation (UMR MARBEC), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Institut méditerranéen de biodiversité et d'écologie marine et continentale (IMBE), Avignon Université (AU)-Aix Marseille Université (AMU)-Institut de recherche pour le développement [IRD] : UMR237-Centre National de la Recherche Scientifique (CNRS), Centre de recherche sur les Risques et les Crises (CRC), Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), ANR-07-BDIV-0006,BIONEOCAL,L'endémisme en Nouvelle-Calédonie : étude phylogénétique et populationnelle des son émergence.(2007), ANR-07-BDIV-0008,INC,Incendies et biodiversité de écosystèmes en Nouvelle-Calédonie.(2007), ANR-07-BDIV-0010,ULTRABIO,Biodiversité et stratégies adaptatives végétales et microbiennes des écosystèmes ultramafiques en Nouvelle-Calédonie.(2007), European Project: 610028,EC:FP7:ERC,ERC-2013-SyG,IMBALANCE-P(2014), European Project: 291585,EC:FP7:ERC,ERC-2011-ADG_20110209,T-FORCES(2012), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut de Recherche pour le Développement (IRD), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paul-Valéry - Montpellier 3 (UPVM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
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0106 biological sciences ,Biome ,Bos- en Landschapsecologie ,Biodiversity ,DIVERSITY ,FOREST VEGETATION ,01 natural sciences ,purl.org/becyt/ford/1 [https] ,Abundance (ecology) ,big data ,Vegetation type ,PHYTOSOCIOLOGICAL DATABASE ,parcelle ,Forest and Landscape Ecology ,functional traits ,vascular plants ,biodiversity ,biogeography ,database ,macroecology ,vegetation plots ,Macroecology ,[SDV.EE]Life Sciences [q-bio]/Ecology, environment ,Global and Planetary Change ,Ecology ,vascular plant ,Vegetation ,F70 - Taxonomie végétale et phytogéographie ,PE&RC ,Vegetation plot ,Geography ,580: Pflanzen (Botanik) ,Ecosystems Research ,Diffusion de l'information ,Plantenecologie en Natuurbeheer ,Vegetatie, Bos- en Landschapsecologie ,Biodiversité ,ARCHIVE ,Communauté végétale ,Evolution ,[SDE.MCG]Environmental Sciences/Global Changes ,Biogéographie ,GRASSLAND VEGETATION ,Plant Ecology and Nature Conservation ,[SDV.BID]Life Sciences [q-bio]/Biodiversity ,010603 evolutionary biology ,Behavior and Systematics ,Couverture végétale ,577: Ökologie ,PLANT ,purl.org/becyt/ford/1.6 [https] ,functional trait ,Biology ,Ecology, Evolution, Behavior and Systematics ,Vegetatie ,010604 marine biology & hydrobiology ,Impact sur l'environnement ,DRY GRASSLANDS ,Plant community ,15. Life on land ,Végétation ,WETLAND VEGETATION ,Earth and Environmental Sciences ,UNIVERSITY ,Physical geography ,Vegetation, Forest and Landscape Ecology ,[SDE.BE]Environmental Sciences/Biodiversity and Ecology ,données ouvertes - Abstract
Datos disponibles en https://github.com/fmsabatini/sPlotOpen_Code, EU H2020 project BACI, Grant No. 640176 (...), Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E.A., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jiménez-Alfaro, B., Kattge, J., Levesley, A., Pillar, V.D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A.T.R., Agrillo, E., Alvarez, M., Apostolova, I., Arfin Khan, M.A.S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., de Gasper, A.L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El-Sheikh, M.A.E.-R.M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán-de-Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I.G., Grytnes, J.-A., Guerin, G.R., Gutiérrez, A.G., Haider, S., Hatim, M.Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J.A.M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D.N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H.S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D.V., Liu, H., Lysenko, T., Mahecha, M.D., Marcenò, C., Martynenko, V., Moeslund, J.E., Monteagudo Mendoza, A., Mucina, L., Müller, J.V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Pärtel, M., Pauchard, A., Peet, R.K., Peñuelas, J., Pérez-Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas-Torres, G., Rodwell, J.S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Ž., Sparrow, B., Sperandii, M.G., Stančić, Z., Svenning, J.-C., Tang, Z., Tang, C.Q., Tsiripidis, I., Vanselow, K.A., Vásquez Martínez, R., Vassilev, K., Vélez-Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., von Wehrden, H., Wagner, V., Walker, D.A., Waller, D.M., Wang, H.-F., Wesche, K., Whitfeld, T.J.S., Willner, W., Wiser, S.K., Wohlgemuth, T., Yamalov, S., Zobel, M., Bruelheide, H.
- Published
- 2021
31. Global trait–environment relationships of plant communities
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Esteban Álvarez-Dávila, Maurizio Mencuccini, Zhiyao Tang, Norbert Jürgens, Christopher Baraloto, Robert K. Peet, Jérôme Munzinger, Josep Peñuelas, Peter M. van Bodegom, Erwin Bergmeier, Wim A. Ozinga, Isabelle Aubin, Yadvinder Malhi, Michele De Sanctis, William Farfan-Rios, Marten Winter, Benjamin Blonder, Jordi Sardans, Christian Wirth, Valério D. Pillar, Nicole J. Fenton, Ilona Knollová, Jiří Doležal, Miguel D. Mahecha, Jens Kattge, Marijn Bauters, Zoltán Botta-Dukát, Francesco Maria Sabatini, Jonathan Lenoir, Peter B. Reich, Florian Jansen, Jorcely Barroso, Frédérique Louault, Anne D. Bjorkman, Alvaro G. Gutiérrez, Michael Kleyer, Matteo Dainese, Dylan Craven, Andraž Čarni, Anita K. Smyth, Gunnar Seidler, Idoia Biurrun, Ted R. Feldpausch, Javier Silva Espejo, Helge Bruelheide, Risto Virtanen, Tarek Hattab, Franziska Schrodt, Greg R. Guerin, Sandra Díaz, Anke Jentsch, Jürgen Dengler, Borja Jiménez-Alfaro, J. Hans C. Cornelissen, Kate H. Orwin, Bruno Hérault, Tomáš Černý, Stephan M. Hennekens, Erik Welk, Frederic Lens, Mohammed Abu Sayed Arfin Khan, Jacqueline Loos, Kiril Vassilev, Milan Chytrý, Jonas V. Müller, Christine Römermann, Sylvia Haider, Géraldine Derroire, Marcos Silveira, Greg H. R. Henry, Petr Petřík, Ülo Niinemets, Zygmunt Kącki, Isla H. Myers-Smith, Michael Kessler, Dirk Nikolaus Karger, Evan Weiher, Andrey Yu. Korolyuk, Richard Field, Raquel Thomas, Eric Garnier, Luis Cayuela, Brody Sandel, Cyrille Violle, Jens-Christian Svenning, Corrado Marcenò, Aaron Pérez-Haase, Daniel C. Laughlin, Pedro Higuchi, Jürgen Homeier, Ute Jandt, Fabio Attorre, Karsten Wesche, Norbert Hölzel, Oliver L. Phillips, Ingolf Kühn, Marco Schmidt, Meelis Pärtel, David A. Neill, Maria Sporbert, Mariyana Lyubenova, Oliver Purschke, Arthur Vinicius Rodrigues, Ioannis Tsiripidis, Jan Altman, Institute of Biology/Geobotany and Botanical Garden, Martin-Luther-Universität Halle Wittenberg (MLU), Universität Bayreuth, German Centre for Integrative Biodiversity Research (iDiv), UR Ecol & Dynam Syst Anthropises EDYSAN, UMR CNRS 7058, Université de Picardie Jules Verne (UPJV), Department of Botany and Zoology, Masaryk University, ALTERRA Wageningen, ALTERRA, Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, Universidade Federal do Rio Grande do Norte [Natal] (UFRN), Universiteit Leiden [Leiden], Fundación Con-Vida, Ecologie des forêts de Guyane (ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université des Antilles et de la Guyane (UAG)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Universidade Federal do Acre (UFAC), Ecology and Evolutionary Biology [Tucson] (EEB), University of Arizona, National Institute of Biology [Ljubljana], Universidad Rey Juan Carlos [Madrid] (URJC), Vrije Universiteit Amsterdam [Amsterdam] (VU), Royal Institute of Technology (KTH), Department of Microelectronics and Information Technology, Kista Photonics Research Center (KPRC) (KTH), Royal Institute of Technology [Stockholm] (KTH ), AgroParisTech, Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UM3)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Ecosystèmes et Ressources Aquatiques (UR03AGRO1), Institut National Agronomique de Tunisie, Westfälische Wilhelms-Universität Münster (WWU), Georg-August-Universität Göttingen, Bayreuth Center of Ecology and Environmental Research (BayCEER), University of Zurich, Landscape Ecology Group, University of Oldenburg, Helmholtz Zentrum für Umweltforschung (UFZ), Netherlands Centre for Biodiversity Naturalis, Institute of Ecology, Leuphana University, Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Environmental Change Institute, University of Oxford [Oxford], School of Geosciences [Edinburgh], University of Edinburgh, Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), Universidad Estatal Amazonica, Estonian University of Life Sciences, University of Nijmegen, Global Ecology Unit CREAF-CEAB-CSIC, Universitat Autònoma de Barcelona [Barcelona] (UAB), Institute of Ecology and Earth Sciences, University of Tartu, University of Tartu, Department of Forest Resources, University of Minnesota [Twin Cities], University of Minnesota System-University of Minnesota System, Universität Regensburg (REGENSBURG), Universität Regensburg, Centre de Recerca Ecològica i Aplicacions Forestals (CREAF), Dept Biol Sci, Ecoinformat & Biodivers Grp, Aarhus University [Aarhus], Aristotle University of Thessaloniki, Dept Biol, University of Oulu, University of Wisconsin-Eau Claire, Department of Botany, Senckenberg Natural History Museum, Synthesis Centre for Biodiversity Sciences, German Centre for Integrative Biodiversity Research, Universität Leipzig [Leipzig], Philips Research Europe - Hamburg, Sector Medical Imaging Systems, Philips Research, Ecologie et Dynamique des Systèmes Anthropisés - UMR CNRS 7058 (EDYSAN), Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), Masaryk University [Brno] (MUNI), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Université Paul-Valéry - Montpellier 3 (UPVM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut de Recherche pour le Développement (IRD [France-Sud]), MARine Biodiversity Exploitation and Conservation (UMR MARBEC), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Georg-August-University [Göttingen], Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD [France-Sud]), Universitat Autònoma de Barcelona (UAB), University of Minnesota [Twin Cities] (UMN), Martin-Luther-University Halle-Wittenberg, Ecologie et Dynamique des Systèmes Anthropisés (EDYSAN), Wageningen University and Research Centre [Wageningen] (WUR), Chercheur indépendant, Department of Ecological Modelling [UFZ Leipzig], Helmholtz Centre for Environmental Research (UFZ), Laboratoire des Sciences de l'Environnement Marin (LEMAR) (LEMAR), Institut de Recherche pour le Développement (IRD)-Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Hawkesbury Institute for the Environment [Richmond] (HIE), Western Sydney University (UWS), Bruelheide H., Dengler J., Purschke O., Lenoir J., Jimenez-Alfaro B., Hennekens S.M., Botta-Dukat Z., Chytry M., Field R., Jansen F., Kattge J., Pillar V.D., Schrodt F., Mahecha M.D., Peet R.K., Sandel B., van Bodegom P., Altman J., Alvarez-Davila E., Arfin Khan M.A.S., Attorre F., Aubin I., Baraloto C., Barroso J.G., Bauters M., Bergmeier E., Biurrun I., Bjorkman A.D., Blonder B., Carni A., Cayuela L., Cerny T., Cornelissen J.H.C., Craven D., Dainese M., Derroire G., De Sanctis M., Diaz S., Dolezal J., Farfan-Rios W., Feldpausch T.R., Fenton N.J., Garnier E., Guerin G.R., Gutierrez A.G., Haider S., Hattab T., Henry G., Herault B., Higuchi P., Holzel N., Homeier J., Jentsch A., Jurgens N., Kacki Z., Karger D.N., Kessler M., Kleyer M., Knollova I., Korolyuk A.Y., Kuhn I., Laughlin D.C., Lens F., Loos J., Louault F., Lyubenova M.I., Malhi Y., Marceno C., Mencuccini M., Muller J.V., Munzinger J., Myers-Smith I.H., Neill D.A., Niinemets U., Orwin K.H., Ozinga W.A., Penuelas J., Perez-Haase A., Petrik P., Phillips O.L., Partel M., Reich P.B., Romermann C., Rodrigues A.V., Sabatini F.M., Sardans J., Schmidt M., Seidler G., Silva Espejo J.E., Silveira M., Smyth A., Sporbert M., Svenning J.-C., Tang Z., Thomas R., Tsiripidis I., Vassilev K., Violle C., Virtanen R., Weiher E., Welk E., Wesche K., Winter M., Wirth C., Jandt U., Systems Ecology, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), and Institut de Recherche pour le Développement (IRD [France-Sud])-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)
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0106 biological sciences ,[SDV]Life Sciences [q-bio] ,Bos- en Landschapsecologie ,01 natural sciences ,Ecosystem services ,forests ,grassland ,life history traits ,plant dispersal ,plants ,Forest and Landscape Ecology ,Environmental planning ,OT PB Vredepeel ,[SDV.EE]Life Sciences [q-bio]/Ecology, environment ,diversité fonctionnelle ,Ecology ,Vegetation ,Plants ,Grassland ,économie foliaire ,Biogeography ,Community Ecology ,Ecosystems Research ,[SDE]Environmental Sciences ,Trait ,Vegetatie, Bos- en Landschapsecologie ,F40 - Écologie végétale ,F60 - Physiologie et biochimie végétale ,[SDE.MCG]Environmental Sciences/Global Changes ,education ,[SDV.BID]Life Sciences [q-bio]/Biodiversity ,Life History Trait ,Biology ,Sustainability Science ,010603 evolutionary biology ,température ,Life Science ,prédiction ,Ecosystem ,Forest ,577: Ökologie ,Vegetatie ,Ecology, Evolution, Behavior and Systematics ,climat ,Plant Dispersal ,Niche differentiation ,Plant community ,15. Life on land ,Disturbance (ecology) ,Vegetation, Forest and Landscape Ecology ,[SDE.BE]Environmental Sciences/Biodiversity and Ecology ,Scale (map) ,010606 plant biology & botany - Abstract
International audience; Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait-environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.
- Published
- 2018
32. Mapping an invasive bryophyte species using hyperspectral remote sensing data
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Olivier Honnay, Maike Isermann, Ruben Van De Kerchove, Ben Somers, Sebastian Schmidtlein, Duccio Rocchini, Michael Ewald, Hannes Feilhauer, Jonathan Lenoir, Jens Warrie, Tarek Hattab, Sandra Skowronek, Raf Aerts, Skowronek, S., Ewald, M., Isermann, M., Van De Kerchove, R., Lenoir, J., Aerts, R., Warrie, J., Hattab, T., Honnay, O., Schmidtlein, S., Rocchini, Duccio, Somers, B., and Feilhauer, H.
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0106 biological sciences ,Dunes ,Dune ,010504 meteorology & atmospheric sciences ,Settore BIO/03 - BOTANICA AMBIENTALE E APPLICATA ,Biology ,010603 evolutionary biology ,01 natural sciences ,Campylopus introflexus ,Moss ,Ecology, Evolution, Behavior and Systematics ,0105 earth and related environmental sciences ,Remote sensing ,Ecology ,Campylopus introflexu ,Sampling (statistics) ,Hyperspectral imaging ,Spectral bands ,15. Life on land ,biology.organism_classification ,Imaging spectroscopy ,Remote sensing (archaeology) ,Plant cover ,Bryophyte ,Maxent ,Heathland - Abstract
Reliable distribution maps are crucial for the management of invasive plant species. An alternative to traditional field surveys is the use of remote sensing data, which allows coverage of large areas. However, most remote sensing studies on invasive plant species focus on mapping large stands of easily detectable study species. In this study, we used hyperspectral remote sensing data in combination with field data to derive a distribution map of an invasive bryophyte species, Campylopus introflexus, on the island of Sylt in Northern Germany. We collected plant cover data on 57 plots to calibrate the model and presence/absence data of C. introflexus on another 150 plots for independent validation. We simultaneously acquired airborne hyperspectral (APEX) images during summer 2014, providing 285 spectral bands. We used a Maxent modelling approach to map the distribution of C. introflexus. Although C. introflexus is a small and inconspicuous species, we were able to map its distribution with an overall accuracy of 75 %. Reducing the sampling effort from 57 to 7 plots, our models performed fairly well until sampling effort dropped below 12 plots. The model predicts that C. introflexus is present in about one quarter of the pixels in our study area. The highest percentage of C. introflexus is predicted in the dune grassland. Our findings suggest that hyperspectral remote sensing data have the potential to provide reliable information about the degree of bryophyte invasion, and thus provide an alternative to traditional field mapping approaches over large areas.
- Published
- 2017
33. Assessing expert reliability in determining intracranial EEG channel quality and introducing the automated bad channel detection algorithm.
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Hattab T, König SD, Carlson DC, Hayes RF, Sha Z, Park MC, Kahn L, Patel S, McGovern RA, Henry T, Khan F, Herman AB, and Darrow DP
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- Humans, Reproducibility of Results, Observer Variation, Electrocorticography methods, Electrocorticography standards, Electroencephalography methods, Electroencephalography standards, Neurologists statistics & numerical data, Neurologists standards, Algorithms
- Abstract
Objective. To evaluate the inter- and intra-rater reliability for the identification of bad channels among neurologists, EEG Technologists, and naïve research personnel, and to compare their performance with the automated bad channel detection (ABCD) algorithm for detecting bad channels. Approach. Six Neurologists, ten EEG Technologists, and six naïve research personnel (22 raters in total) were asked to rate 1440 real intracranial EEG channels as good or bad. Intra- and interrater kappa statistics were calculated for each group. We then compared each group to the ABCD algorithm which uses spectral and temporal domain features to classify channels as good or bad. Main results. Analysis of channel ratings from our participants revealed variable intra-rater reliability within each group, with no significant differences across groups. Inter-rater reliability was moderate among neurologists and EEG Technologists but minimal among naïve participants. Neurologists demonstrated a slightly higher consistency in ratings than EEG Technologists. Both groups occasionally misclassified flat channels as good, and participants generally focused on low-frequency content for their assessments. The ABCD algorithm, in contrast, relied more on high-frequency content. A logistic regression model showed a linear relationship between the algorithm's ratings and user responses for predominantly good channels, but less so for channels rated as bad. Sensitivity and specificity analyses further highlighted differences in rating patterns among the groups, with neurologists showing higher sensitivity and naïve personnel higher specificity. Significance. Our study reveals the bias in human assessments of intracranial electroencephalography (iEEG) data quality and the tendency of even experienced professionals to overlook certain bad channels, highlighting the need for standardized, unbiased methods. The ABCD algorithm, outperforming human raters, suggests the potential of automated solutions for more reliable iEEG interpretation and seizure characterization, offering a reliable approach free from human biases., (Creative Commons Attribution license.)
- Published
- 2024
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34. A quixotic view of spatial bias in modelling the distribution of species and their diversity.
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Rocchini D, Tordoni E, Marchetto E, Marcantonio M, Barbosa AM, Bazzichetto M, Beierkuhnlein C, Castelnuovo E, Gatti RC, Chiarucci A, Chieffallo L, Da Re D, Di Musciano M, Foody GM, Gabor L, Garzon-Lopez CX, Guisan A, Hattab T, Hortal J, Kunin WE, Jordán F, Lenoir J, Mirri S, Moudrý V, Naimi B, Nowosad J, Sabatini FM, Schweiger AH, Šímová P, Tessarolo G, Zannini P, and Malavasi M
- Abstract
Ecological processes are often spatially and temporally structured, potentially leading to autocorrelation either in environmental variables or species distribution data. Because of that, spatially-biased in-situ samples or predictors might affect the outcomes of ecological models used to infer the geographic distribution of species and diversity. There is a vast heterogeneity of methods and approaches to assess and measure spatial bias; this paper aims at addressing the spatial component of data-driven biases in species distribution modelling, and to propose potential solutions to explicitly test and account for them. Our major goal is not to propose methods to remove spatial bias from the modelling procedure, which would be impossible without proper knowledge of all the processes generating it, but rather to propose alternatives to explore and handle it. In particular, we propose and describe three main strategies that may provide a fair account of spatial bias, namely: (i) how to represent spatial bias; (ii) how to simulate null models based on virtual species for testing biogeographical and species distribution hypotheses; and (iii) how to make use of spatial bias - in particular related to sampling effort - as a leverage instead of a hindrance in species distribution modelling. We link these strategies with good practice in accounting for spatial bias in species distribution modelling., (© 2023. The Author(s).)
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- 2023
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35. Disentangling tropicalization and deborealization in marine ecosystems under climate change.
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McLean M, Mouillot D, Maureaud AA, Hattab T, MacNeil MA, Goberville E, Lindegren M, Engelhard G, Pinsky M, and Auber A
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- Animals, Cold Temperature, Fishes, Global Warming, Temperature, Climate Change, Ecosystem
- Abstract
As climate change accelerates, species are shifting poleward and subtropical and tropical species are colonizing temperate environments.
1-3 A popular approach for characterizing such responses is the community temperature index (CTI), which tracks the mean thermal affinity of a community. Studies in marine,4 freshwater,5 and terrestrial6 ecosystems have documented increasing CTI under global warming. However, most studies have only linked increasing CTI to increases in warm-affinity species. Here, using long-term monitoring of marine fishes across the Northern Hemisphere, we decomposed CTI changes into four underlying processes-tropicalization (increasing warm-affinity), deborealization (decreasing cold-affinity), borealization (increasing cold-affinity), and detropicalization (decreasing warm-affinity)-for which we examined spatial variability and drivers. CTI closely tracked changes in sea surface temperature, increasing in 72% of locations. However, 31% of these increases were primarily due to decreases in cold-affinity species, i.e., deborealization. Thus, increases in warm-affinity species were prevalent, but not ubiquitous. Tropicalization was stronger in areas that were initially warmer, experienced greater warming, or were deeper, while deborealization was stronger in areas that were closer to human population centers or that had higher community thermal diversity. When CTI (and temperature) increased, species that decreased were more likely to be living closer to their upper thermal limits or to be commercially fished. Additionally, warm-affinity species that increased had smaller body sizes than those that decreased. Our results show that CTI changes arise from a variety of underlying community responses that are linked to environmental conditions, human impacts, community structure, and species characteristics., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2021 Elsevier Inc. All rights reserved.)- Published
- 2021
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36. Sharks surf the slope: Current updrafts reduce energy expenditure for aggregating marine predators.
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Papastamatiou YP, Iosilevskii G, Di Santo V, Huveneers C, Hattab T, Planes S, Ballesta L, and Mourier J
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- Animals, Coral Reefs, Ecosystem, Energy Metabolism, Telemetry, Sharks
- Abstract
An animal's energy landscape considers the power requirements associated with residing in or moving through habitats. Within marine environments, these landscapes can be dynamic as water currents will influence animal power requirements and can change rapidly over diel and tidal cycles. In channels and along slopes with strong currents, updraft zones may reduce energy expenditure of negatively buoyant fishes that are also obligate swimmers. Despite marine predators often residing within high-current area, no study has investigated the potential role of the energetic landscape in driving such habitat selectivity. Over 500 grey reef sharks Carcharhinus amblyrhynchos reside in the southern channel of Fakarava Atoll, French Polynesia. We used diver observations, acoustic telemetry and biologging to show that sharks use regions of predicted updrafts and switch their core area of space use based on tidal state (incoming versus outgoing). During incoming tides, sharks form tight groups and display shuttling behaviour (moving to the front of the group and letting the current move them to the back) to maintain themselves in these potential updraft zones. During outgoing tides, group dispersion increases, swimming depths decrease and shuttling behaviours cease. These changes are likely due to shifts in the nature and location of the updraft zones, as well as turbulence during outgoing tides. Using a biomechanical model, we estimate that routine metabolic rates for sharks may be reduced by 10%-15% when in updraft zones. Grey reef sharks save energy using predicted updraft zones in channels and 'surfing the slope'. Analogous to birds using wind-driven updraft zones, negatively buoyant marine animals may use current-induced updraft zones to reduce energy expenditure. Updrafts should be incorporated into dynamic energy landscapes and may partially explain the distribution, behaviour and potentially abundance of marine predators., (© 2021 British Ecological Society.)
- Published
- 2021
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37. Venous Thromboembolism Prophylaxis in Elective Neurosurgery: A Survey of Board-Certified Neurosurgeons in the United States and Updated Literature Review.
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Adeeb N, Hattab T, Savardekar A, Jumah F, Griessenauer CJ, Musmar B, Adeeb A, Trosclair K, and Guthikonda B
- Subjects
- Elective Surgical Procedures adverse effects, Humans, Neurosurgery, Surveys and Questionnaires, Neurosurgeons, Neurosurgical Procedures adverse effects, Postoperative Complications prevention & control, Practice Patterns, Physicians', Venous Thromboembolism prevention & control
- Abstract
Background: Venous thromboembolism (VTE) remains the single most important preventable cause of morbidity and mortality following neurosurgical procedures, with an incidence of approximately 16%. In the absence of stringent guidelines, the variation in current practice patterns could be considerable and was the underlying basis for this study., Objectives: Our objective is to evaluate the modality of thromboprophylaxis used by neurosurgeons., Methods: In line with "CHERRIES" (Checklist for Reporting Results of Internet E-Surveys) guidelines, an online survey regarding postoperative VTE prophylaxis following elective neurosurgical procedures was created using Google Forms and distributed to 1500 board-certified neurosurgeons in the United States., Results: A total of 370 board-certified neurosurgeons (24.7%) responded to the survey. Sequential compression device was the only primary method of thromboprophylaxis used by 27.2% and 26.5% of respondents after elective craniotomy for tumor resection and spine surgery, respectively. Of the chemical prophylaxis, subcutaneous heparin 5000 U every 8 hours was the most commonly used medication followed by enoxaparin 40 mg daily. Most responders were comfortable starting chemical prophylaxis on postoperative day 1, followed by day 2 and day 3 in both types of surgeries. The mean postoperative time of chemical prophylaxis initiation was significantly more delayed by respondents with longer years in practice., Conclusions: This study highlights the variation in practice between neurosurgeons in managing postoperative VTE prophylaxis after elective spine and cranial surgeries. In lieu of this variation, our results showed that most neurosurgeons are comfortable starting chemical prophylaxis as soon as postoperative day 1 following both types of procedures., (Copyright © 2021. Published by Elsevier Inc.)
- Published
- 2021
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38. Are we ready to track climate-driven shifts in marine species across international boundaries? - A global survey of scientific bottom trawl data.
- Author
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A Maureaud A, Frelat R, Pécuchet L, Shackell N, Mérigot B, Pinsky ML, Amador K, Anderson SC, Arkhipkin A, Auber A, Barri I, Bell RJ, Belmaker J, Beukhof E, Camara ML, Guevara-Carrasco R, Choi J, Christensen HT, Conner J, Cubillos LA, Diadhiou HD, Edelist D, Emblemsvåg M, Ernst B, Fairweather TP, Fock HO, Friedland KD, Garcia CB, Gascuel D, Gislason H, Goren M, Guitton J, Jouffre D, Hattab T, Hidalgo M, Kathena JN, Knuckey I, Kidé SO, Koen-Alonso M, Koopman M, Kulik V, León JP, Levitt-Barmats Y, Lindegren M, Llope M, Massiot-Granier F, Masski H, McLean M, Meissa B, Mérillet L, Mihneva V, Nunoo FKE, O'Driscoll R, O'Leary CA, Petrova E, Ramos JE, Refes W, Román-Marcote E, Siegstad H, Sobrino I, Sólmundsson J, Sonin O, Spies I, Steingrund P, Stephenson F, Stern N, Tserkova F, Tserpes G, Tzanatos E, van Rijn I, van Zwieten PAM, Vasilakopoulos P, Yepsen DV, Ziegler P, and T Thorson J
- Subjects
- Animals, Climate Change, Fishes, Surveys and Questionnaires, Ecosystem, Fisheries
- Abstract
Marine biota are redistributing at a rapid pace in response to climate change and shifting seascapes. While changes in fish populations and community structure threaten the sustainability of fisheries, our capacity to adapt by tracking and projecting marine species remains a challenge due to data discontinuities in biological observations, lack of data availability, and mismatch between data and real species distributions. To assess the extent of this challenge, we review the global status and accessibility of ongoing scientific bottom trawl surveys. In total, we gathered metadata for 283,925 samples from 95 surveys conducted regularly from 2001 to 2019. We identified that 59% of the metadata collected are not publicly available, highlighting that the availability of data is the most important challenge to assess species redistributions under global climate change. Given that the primary purpose of surveys is to provide independent data to inform stock assessment of commercially important populations, we further highlight that single surveys do not cover the full range of the main commercial demersal fish species. An average of 18 surveys is needed to cover at least 50% of species ranges, demonstrating the importance of combining multiple surveys to evaluate species range shifts. We assess the potential for combining surveys to track transboundary species redistributions and show that differences in sampling schemes and inconsistency in sampling can be overcome with spatio-temporal modeling to follow species density redistributions. In light of our global assessment, we establish a framework for improving the management and conservation of transboundary and migrating marine demersal species. We provide directions to improve data availability and encourage countries to share survey data, to assess species vulnerabilities, and to support management adaptation in a time of climate-driven ocean changes., (© 2020 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)
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- 2021
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39. Species better track climate warming in the oceans than on land.
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Lenoir J, Bertrand R, Comte L, Bourgeaud L, Hattab T, Murienne J, and Grenouillet G
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- Animals, Ecosystem, Oceans and Seas, Plants, Climate, Climate Change
- Abstract
There is mounting evidence of species redistribution as climate warms. Yet, our knowledge of the coupling between species range shifts and isotherm shifts remains limited. Here, we introduce BioShifts-a global geo-database of 30,534 range shifts. Despite a spatial imbalance towards the most developed regions of the Northern Hemisphere and a taxonomic bias towards the most charismatic animals and plants of the planet, data show that marine species are better at tracking isotherm shifts, and move towards the pole six times faster than terrestrial species. More specifically, we find that marine species closely track shifting isotherms in warm and relatively undisturbed waters (for example, the Central Pacific Basin) or in cold waters subject to high human pressures (for example, the North Sea). On land, human activities impede the capacity of terrestrial species to track isotherm shifts in latitude, with some species shifting in the opposite direction to isotherms. Along elevational gradients, species follow the direction of isotherm shifts but at a pace that is much slower than expected, especially in areas with warm climates. Our results suggest that terrestrial species are lagging behind shifting isotherms more than marine species, which is probably related to the interplay between the wider thermal safety margin of terrestrial versus marine species and the more constrained physical environment for dispersal in terrestrial versus marine habitats.
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- 2020
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40. Global trait-environment relationships of plant communities.
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Bruelheide H, Dengler J, Purschke O, Lenoir J, Jiménez-Alfaro B, Hennekens SM, Botta-Dukát Z, Chytrý M, Field R, Jansen F, Kattge J, Pillar VD, Schrodt F, Mahecha MD, Peet RK, Sandel B, van Bodegom P, Altman J, Alvarez-Dávila E, Arfin Khan MAS, Attorre F, Aubin I, Baraloto C, Barroso JG, Bauters M, Bergmeier E, Biurrun I, Bjorkman AD, Blonder B, Čarni A, Cayuela L, Černý T, Cornelissen JHC, Craven D, Dainese M, Derroire G, De Sanctis M, Díaz S, Doležal J, Farfan-Rios W, Feldpausch TR, Fenton NJ, Garnier E, Guerin GR, Gutiérrez AG, Haider S, Hattab T, Henry G, Hérault B, Higuchi P, Hölzel N, Homeier J, Jentsch A, Jürgens N, Kącki Z, Karger DN, Kessler M, Kleyer M, Knollová I, Korolyuk AY, Kühn I, Laughlin DC, Lens F, Loos J, Louault F, Lyubenova MI, Malhi Y, Marcenò C, Mencuccini M, Müller JV, Munzinger J, Myers-Smith IH, Neill DA, Niinemets Ü, Orwin KH, Ozinga WA, Penuelas J, Pérez-Haase A, Petřík P, Phillips OL, Pärtel M, Reich PB, Römermann C, Rodrigues AV, Sabatini FM, Sardans J, Schmidt M, Seidler G, Silva Espejo JE, Silveira M, Smyth A, Sporbert M, Svenning JC, Tang Z, Thomas R, Tsiripidis I, Vassilev K, Violle C, Virtanen R, Weiher E, Welk E, Wesche K, Winter M, Wirth C, and Jandt U
- Subjects
- Forests, Grassland, Life History Traits, Plant Dispersal, Plants
- Abstract
Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait-environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.
- Published
- 2018
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41. A landscape genetic analysis of important agricultural pest species in Tunisia: The whitefly Bemisia tabaci.
- Author
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Ben Abdelkrim A, Hattab T, Fakhfakh H, Belkadhi MS, and Gorsane F
- Subjects
- Animal Distribution, Animals, Genetic Testing, Hemiptera genetics, Tunisia, Gene Flow, Genetic Drift, Microsatellite Repeats
- Abstract
Combining landscape ecology and genetics provides an excellent framework to appreciate pest population dynamics and dispersal. The genetic architectures of many species are always shaped by environmental constraints. Because little is known about the ecological and genetic traits of Tunisian whitefly populations, the main objective of this work is to highlight patterns of biodiversity, genetic structure and migration routes of this pest. We used nuclear microsatellite loci to analyze B. tabaci populations collected from various agricultural areas across the country and we determine their biotype status. Molecular data were subsequently interpreted in an ecological context supplied from a species distribution model to infer habitat suitability and hereafter the potential connection paths between sampling localities. An analysis of landscape resistance to B. tabaci genetic flow was thus applied to take into account habitat suitability, genetic relatedness and functional connectivity of habitats within a varied landscape matrix. We shed light on the occurrence of three geographically delineated genetic groups with high levels of genetic differentiation within each of them. Potential migration corridors of this pest were then established providing significant advances toward the understanding of genetic features and the dynamic dispersal of this pest. This study supports the hypothesis of a long-distance dispersal of B. tabaci followed by infrequent long-term isolations. The Inference of population sources and colonization routes is critical for the design and implementation of accurate management strategies against this pest.
- Published
- 2017
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42. Invasion by the Alien Tree Prunus serotina Alters Ecosystem Functions in a Temperate Deciduous Forest.
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Aerts R, Ewald M, Nicolas M, Piat J, Skowronek S, Lenoir J, Hattab T, Garzón-López CX, Feilhauer H, Schmidtlein S, Rocchini D, Decocq G, Somers B, Van De Kerchove R, Denef K, and Honnay O
- Abstract
Alien invasive species can affect large areas, often with wide-ranging impacts on ecosystem structure, function, and services. Prunus serotina is a widespread invader of European temperate forests, where it tends to form homogeneous stands and limits recruitment of indigenous trees. We hypotesized that invasion by P. serotina would be reflected in the nutrient contents of the native species' leaves and in the respiration of invaded plots as efficient resource uptake and changes in nutrient cycling by P. serotina probably underly its aggressive invasiveness. We combined data from 48 field plots in the forest of Compiègne, France, and data from an experiment using 96 microcosms derived from those field plots. We used general linear models to separate effects of invasion by P. serotina on heterotrophic soil and litter respiration rates and on canopy foliar nutrient content from effects of soil chemical properties, litter quantity, litter species composition, and tree species composition. In invaded stands, average respiration rates were 5.6% higher for soil (without litter) and 32% higher for soil and litter combined. Compared to indigenous tree species, P. serotina exhibited higher foliar N (+24.0%), foliar P (+50.7%), and lower foliar C:N (-22.4%) and N:P (-10.1%) ratios. P. serotina affected foliar nutrient contents of co-occuring indigenous tree species leading to decreased foliar N (-8.7 %) and increased C:N ratio (+9.5%) in Fagus sylvatica , decreased foliar N:P ratio in Carpinus betulus (-13.5%) and F. sylvatica (-11.8%), and increased foliar P in Pinus sylvestris (+12.3%) in invaded vs. uninvaded stands. Our results suggest that P. serotina is changing nitrogen, phosphorus, and carbon cycles to its own advantage, hereby increasing carbon turnover via labile litter, affecting the relative nutrient contents in the overstory leaves, and potentially altering the photosynthetic capacity of the long-lived indigenous broadleaved species. Uncontrolled invasion of European temperate forests by P. serotina may affect the climate change mitigation potential of these forests in the long term, through additive effects on local nutrient cycles.
- Published
- 2017
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43. Correction: Modeling of Beta Diversity in Tunisian Waters: Predictions Using Generalized Dissimilarity Modeling and Bioregionalisation Using Fuzzy Clustering.
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Ben Rais Lasram F, Hattab T, Halouani G, Romdhane MS, and Le Loc'h F
- Published
- 2015
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44. Modeling of Beta Diversity in Tunisian Waters: Predictions Using Generalized Dissimilarity Modeling and Bioregionalisation Using Fuzzy Clustering.
- Author
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Ben Rais Lasram F, Hattab T, Halouani G, Romdhane MS, and Le Loc'h F
- Subjects
- Mediterranean Sea, Tunisia, Biodiversity, Ecology, Fuzzy Logic, Models, Theoretical
- Abstract
Spatial patterns of beta diversity are a major focus of ecology. They can be especially valuable in conservation planning. In this study, we used a generalized dissimilarity modeling approach to analyze and predict the spatial patterns of beta diversity for commercially exploited, demersal marine species assemblages along the Tunisian coasts. For this study, we used a presence/absence dataset which included information on 174 species (invertebrates and fishes) and 9 environmental variables. We first performed the modeling analyses and assessed beta diversity using the turnover component of the Jaccard's dissimilarity index. We then performed nonmetric multidimensional scaling to map predicted beta diversity. To delineate the biogeographical regions, we used fuzzy cluster analysis. Finally, we also identified a set of indicator species which characterized the species assemblages in each identified biogeographical region. The predicted beta diversity map revealed two patterns: an inshore-offshore gradient and a south-north latitudinal gradient. Three biogeographical regions were identified and 14 indicator species. These results constitute a first contribution of the bioregionalisation of the Tunisian waters and highlight the issues associated with current fisheries management zones and conservation strategies. Results could be useful to follow an Ecosystem Based Management approach by proposing an objective spatial partitioning of the Tunisian waters. This partitioning could be used to prioritize the adjustment of the actual fisheries management entities, identify current data gaps, inform future scientific surveys and improve current MPA network.
- Published
- 2015
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45. The use of a predictive habitat model and a fuzzy logic approach for marine management and planning.
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Hattab T, Ben Rais Lasram F, Albouy C, Sammari C, Romdhane MS, Cury P, Leprieur F, and Le Loc'h F
- Subjects
- Area Under Curve, Geography, Mediterranean Region, Ships, Species Specificity, Conservation of Natural Resources, Ecosystem, Fuzzy Logic, Models, Theoretical, Seawater
- Abstract
Bottom trawl survey data are commonly used as a sampling technique to assess the spatial distribution of commercial species. However, this sampling technique does not always correctly detect a species even when it is present, and this can create significant limitations when fitting species distribution models. In this study, we aim to test the relevance of a mixed methodological approach that combines presence-only and presence-absence distribution models. We illustrate this approach using bottom trawl survey data to model the spatial distributions of 27 commercially targeted marine species. We use an environmentally- and geographically-weighted method to simulate pseudo-absence data. The species distributions are modelled using regression kriging, a technique that explicitly incorporates spatial dependence into predictions. Model outputs are then used to identify areas that met the conservation targets for the deployment of artificial anti-trawling reefs. To achieve this, we propose the use of a fuzzy logic framework that accounts for the uncertainty associated with different model predictions. For each species, the predictive accuracy of the model is classified as 'high'. A better result is observed when a large number of occurrences are used to develop the model. The map resulting from the fuzzy overlay shows that three main areas have a high level of agreement with the conservation criteria. These results align with expert opinion, confirming the relevance of the proposed methodology in this study.
- Published
- 2013
- Full Text
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