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1. Local climate modulates the development of soil nematode communities after glacier retreat

Author: Guerrieri, A, Cantera, I, Marta, S, Bonin, A, Carteron, A, Ambrosini, R, Caccianiga, M, Anthelme, F, Azzoni, R, Almond, P, Alvizgazitua, P, Cauvy-Fraunie, S, Ceballoslievano, J, Chand, P, Chandsharma, M, Clague, J, Cochachinrapre, J, Compostella, C, Cruzencarnacion, R, Dangles, O, Deline, P, Eger, A, Erokhin, S, Franzetti, A, Gielly, L, Gili, F, Gobbi, M, Hagvar, S, Khedim, N, Meneses, R, Peyre, G, Pittino, F, Proietto, A, Rabatel, A, Urseitova, N, Yang, Y, Zaginaev, V, Zerboni, A, Zimmer, A, Taberlet, P, Diolaiuti, G, Poulenard, J, Fontaneto, D, Thuiller, W, Ficetola, G, Guerrieri A., Cantera I., Marta S., Bonin A., Carteron A., Ambrosini R., Caccianiga M., Anthelme F., Azzoni R. S., Almond P., AlvizGazitua P., Cauvy-Fraunie S., CeballosLievano J. L., Chand P., ChandSharma M., Clague J., CochachinRapre J. A., Compostella C., CruzEncarnacion R., Dangles O., Deline P., Eger A., Erokhin S., Franzetti A., Gielly L., Gili F., Gobbi M., Hagvar S., Khedim N., Meneses R. I., Peyre G., Pittino F., Proietto A., Rabatel A., Urseitova N., Yang Y., Zaginaev V., Zerboni A., Zimmer A., Taberlet P., Diolaiuti G. A., Poulenard J., Fontaneto D., Thuiller W., Ficetola G. F., Guerrieri, A, Cantera, I, Marta, S, Bonin, A, Carteron, A, Ambrosini, R, Caccianiga, M, Anthelme, F, Azzoni, R, Almond, P, Alvizgazitua, P, Cauvy-Fraunie, S, Ceballoslievano, J, Chand, P, Chandsharma, M, Clague, J, Cochachinrapre, J, Compostella, C, Cruzencarnacion, R, Dangles, O, Deline, P, Eger, A, Erokhin, S, Franzetti, A, Gielly, L, Gili, F, Gobbi, M, Hagvar, S, Khedim, N, Meneses, R, Peyre, G, Pittino, F, Proietto, A, Rabatel, A, Urseitova, N, Yang, Y, Zaginaev, V, Zerboni, A, Zimmer, A, Taberlet, P, Diolaiuti, G, Poulenard, J, Fontaneto, D, Thuiller, W, Ficetola, G, Guerrieri A., Cantera I., Marta S., Bonin A., Carteron A., Ambrosini R., Caccianiga M., Anthelme F., Azzoni R. S., Almond P., AlvizGazitua P., Cauvy-Fraunie S., CeballosLievano J. L., Chand P., ChandSharma M., Clague J., CochachinRapre J. A., Compostella C., CruzEncarnacion R., Dangles O., Deline P., Eger A., Erokhin S., Franzetti A., Gielly L., Gili F., Gobbi M., Hagvar S., Khedim N., Meneses R. I., Peyre G., Pittino F., Proietto A., Rabatel A., Urseitova N., Yang Y., Zaginaev V., Zerboni A., Zimmer A., Taberlet P., Diolaiuti G. A., Poulenard J., Fontaneto D., Thuiller W., and Ficetola G. F.
Abstract: The worldwide retreat of glaciers is causing a faster than ever increase in ice-free areas that are leading to the emergence of new ecosystems. Understanding the dynamics of these environments is critical to predicting the consequences of climate change on mountains and at high latitudes. Climatic differences between regions of the world could modulate the emergence of biodiversity and functionality after glacier retreat, yet global tests of this hypothesis are lacking. Nematodes are the most abundant soil animals, with keystone roles in ecosystem functioning, but the lack of global-scale studies limits our understanding of how the taxonomic and functional diversity of nematodes changes during the colonization of proglacial landscapes. We used environmental DNA metabarcoding to characterize nematode communities of 48 glacier forelands from five continents. We assessed how different facets of biodiversity change with the age of deglaciated terrains and tested the hypothesis that colonization patterns are different across forelands with different climatic conditions. Nematodes colonized ice-free areas almost immediately. Both taxonomic and functional richness quickly increased over time, but the increase in nematode diversity was modulated by climate, so that colonization started earlier in forelands with mild summer temperatures. Colder forelands initially hosted poor communities, but the colonization rate then accelerated, eventually leveling biodiversity differences between climatic regimes in the long term. Immediately after glacier retreat, communities were dominated by colonizer taxa with short generation time and r-ecological strategy but community composition shifted through time, with increased frequency of more persister taxa with K-ecological strategy. These changes mostly occurred through the addition of new traits instead of their replacement during succession. The effects of local climate on nematode colonization led to heterogeneous but predictable patt
Published: 2024

2. Proceedings of the third 'international Traveling Workshop on Interactions between Sparse models and Technology' (iTWIST'16)

Author: Abrol, V., Absil, O., Absil, P. -A., Anthoine, S., Antoine, P., Arildsen, T., Bertin, N., Bleichrodt, F., Bobin, J., Bol, A., Bonnefoy, A., Caltagirone, F., Cambareri, V., Chenot, C., Crnojević, V., Daňková, M., Degraux, K., Eisert, J., Fadili, J. M., Gabrié, M., Gac, N., Giacobello, D., Gonzalez, A., Gonzalez, C. A. Gomez, González, A., Gousenbourger, P. -Y., Christensen, M. Græsbøll, Gribonval, R., Guérit, S., Huang, S., Irofti, P., Jacques, L., Kamilov, U. S., Kiticć, S., Kliesch, M., Krzakala, F., Lee, J. A., Liao, W., Jensen, T. Lindstrøm, Manoel, A., Mansour, H., Mohammad-Djafari, A., Moshtaghpour, A., Ngolè, F., Pairet, B., Panić, M., Peyré, G., Pižurica, A., Rajmic, P., Roblin, M., Roth, I., Sao, A. K., Sharma, P., Starck, J. -L., Tramel, E. W., van Waterschoot, T., Vukobratovic, D., Wang, L., Wirth, B., Wunder, G., and Zhang, H.
Subjects: Computer Science - Numerical Analysis, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Information Theory, Computer Science - Learning, Mathematics - Optimization and Control
Abstract: The third edition of the "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) took place in Aalborg, the 4th largest city in Denmark situated beautifully in the northern part of the country, from the 24th to 26th of August 2016. The workshop venue was at the Aalborg University campus. One implicit objective of this biennial workshop is to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For this third edition, iTWIST'16 gathered about 50 international participants and features 8 invited talks, 12 oral presentations, and 12 posters on the following themes, all related to the theory, application and generalization of the "sparsity paradigm": Sparsity-driven data sensing and processing (e.g., optics, computer vision, genomics, biomedical, digital communication, channel estimation, astronomy); Application of sparse models in non-convex/non-linear inverse problems (e.g., phase retrieval, blind deconvolution, self calibration); Approximate probabilistic inference for sparse problems; Sparse machine learning and inference; "Blind" inverse problems and dictionary learning; Optimization for sparse modelling; Information theory, geometry and randomness; Sparsity? What's next? (Discrete-valued signals; Union of low-dimensional spaces, Cosparsity, mixed/group norm, model-based, low-complexity models, ...); Matrix/manifold sensing/processing (graph, low-rank approximation, ...); Complexity/accuracy tradeoffs in numerical methods/optimization; Electronic/optical compressive sensors (hardware)., Comment: 69 pages, 22 extended abstracts, iTWIST'16 website: http://www.itwist16.es.aau.dk
Published: 2016

3. The development of terrestrial ecosystems emerging after glacier retreat

Author: Ficetola, G, Marta, S, Guerrieri, A, Cantera, I, Bonin, A, Cauvy-Fraunié, S, Ambrosini, R, Caccianiga, M, Anthelme, F, Azzoni, R, Almond, P, Alviz Gazitúa, P, Ceballos Lievano, J, Chand, P, Chand Sharma, M, Clague, J, Cochachín Rapre, J, Compostella, C, Encarnación, R, Dangles, O, Deline, P, Eger, A, Erokhin, S, Franzetti, A, Gielly, L, Gili, F, Gobbi, M, Hågvar, S, Kaufmann, R, Khedim, N, Meneses, R, Morales-Martínez, M, Peyre, G, Pittino, F, Proietto, A, Rabatel, A, Sieron, K, Tielidze, L, Urseitova, N, Yang, Y, Zaginaev, V, Zerboni, A, Zimmer, A, Diolaiuti, G, Taberlet, P, Poulenard, J, Fontaneto, D, Thuiller, W, Carteron, A, Ficetola, Gentile Francesco, Marta, Silvio, Guerrieri, Alessia, Cantera, Isabel, Bonin, Aurélie, Cauvy-Fraunié, Sophie, Ambrosini, Roberto, Caccianiga, Marco, Anthelme, Fabien, Azzoni, Roberto Sergio, Almond, Peter, Alviz Gazitúa, Pablo, Ceballos Lievano, Jorge Luis, Chand, Pritam, Chand Sharma, Milap, Clague, John J., Cochachín Rapre, Justiniano Alejo, Compostella, Chiara, Encarnación, Rolando Cruz, Dangles, Olivier, Deline, Philip, Eger, Andre, Erokhin, Sergey, Franzetti, Andrea, Gielly, Ludovic, Gili, Fabrizio, Gobbi, Mauro, Hågvar, Sigmund, Kaufmann, Rüdiger, Khedim, Norine, Meneses, Rosa Isela, Morales-Martínez, Marco Aurelio, Peyre, Gwendolyn, Pittino, Francesca, Proietto, Angela, Rabatel, Antoine, Sieron, Katrin, Tielidze, Levan, Urseitova, Nurai, Yang, Yan, Zaginaev, Vitalii, Zerboni, Andrea, Zimmer, Anaïs, Diolaiuti, Guglielmina Adele, Taberlet, Pierre, Poulenard, Jerome, Fontaneto, Diego, Thuiller, Wilfried, Carteron, Alexis, Ficetola, G, Marta, S, Guerrieri, A, Cantera, I, Bonin, A, Cauvy-Fraunié, S, Ambrosini, R, Caccianiga, M, Anthelme, F, Azzoni, R, Almond, P, Alviz Gazitúa, P, Ceballos Lievano, J, Chand, P, Chand Sharma, M, Clague, J, Cochachín Rapre, J, Compostella, C, Encarnación, R, Dangles, O, Deline, P, Eger, A, Erokhin, S, Franzetti, A, Gielly, L, Gili, F, Gobbi, M, Hågvar, S, Kaufmann, R, Khedim, N, Meneses, R, Morales-Martínez, M, Peyre, G, Pittino, F, Proietto, A, Rabatel, A, Sieron, K, Tielidze, L, Urseitova, N, Yang, Y, Zaginaev, V, Zerboni, A, Zimmer, A, Diolaiuti, G, Taberlet, P, Poulenard, J, Fontaneto, D, Thuiller, W, Carteron, A, Ficetola, Gentile Francesco, Marta, Silvio, Guerrieri, Alessia, Cantera, Isabel, Bonin, Aurélie, Cauvy-Fraunié, Sophie, Ambrosini, Roberto, Caccianiga, Marco, Anthelme, Fabien, Azzoni, Roberto Sergio, Almond, Peter, Alviz Gazitúa, Pablo, Ceballos Lievano, Jorge Luis, Chand, Pritam, Chand Sharma, Milap, Clague, John J., Cochachín Rapre, Justiniano Alejo, Compostella, Chiara, Encarnación, Rolando Cruz, Dangles, Olivier, Deline, Philip, Eger, Andre, Erokhin, Sergey, Franzetti, Andrea, Gielly, Ludovic, Gili, Fabrizio, Gobbi, Mauro, Hågvar, Sigmund, Kaufmann, Rüdiger, Khedim, Norine, Meneses, Rosa Isela, Morales-Martínez, Marco Aurelio, Peyre, Gwendolyn, Pittino, Francesca, Proietto, Angela, Rabatel, Antoine, Sieron, Katrin, Tielidze, Levan, Urseitova, Nurai, Yang, Yan, Zaginaev, Vitalii, Zerboni, Andrea, Zimmer, Anaïs, Diolaiuti, Guglielmina Adele, Taberlet, Pierre, Poulenard, Jerome, Fontaneto, Diego, Thuiller, Wilfried, and Carteron, Alexis
Abstract: The global retreat of glaciers is dramatically altering mountain and high-latitude landscapes, with new ecosystems developing from apparently barren substrates1–4. The study of these emerging ecosystems is critical to understanding how climate change interacts with microhabitat and biotic communities and determines the future of ice-free terrains1,5. Here, using a comprehensive characterization of ecosystems (soil properties, microclimate, productivity and biodiversity by environmental DNA metabarcoding6) across 46 proglacial landscapes worldwide, we found that all the environmental properties change with time since glaciers retreated, and that temperature modulates the accumulation of soil nutrients. The richness of bacteria, fungi, plants and animals increases with time since deglaciation, but their temporal patterns differ. Microorganisms colonized most rapidly in the first decades after glacier retreat, whereas most macroorganisms took longer. Increased habitat suitability, growing complexity of biotic interactions and temporal colonization all contribute to the increase in biodiversity over time. These processes also modify community composition for all the groups of organisms. Plant communities show positive links with all other biodiversity components and have a key role in ecosystem development. These unifying patterns provide new insights into the early dynamics of deglaciated terrains and highlight the need for integrated surveillance of their multiple environmental properties5.
Published: 2024

4. Dynamics and drivers of mycorrhizal fungi after glacier retreat

Author: Carteron, A, Cantera, I, Guerrieri, A, Marta, S, Bonin, A, Ambrosini, R, Anthelme, F, Azzoni, R, Almond, P, Alviz Gazitúa, P, Cauvy-Fraunié, S, Ceballos Lievano, J, Chand, P, Chand Sharma, M, Clague, J, Cochachín Rapre, J, Compostella, C, Cruz Encarnación, R, Dangles, O, Eger, A, Erokhin, S, Franzetti, A, Gielly, L, Gili, F, Gobbi, M, Hågvar, S, Khedim, N, Meneses, R, Peyre, G, Pittino, F, Rabatel, A, Urseitova, N, Yang, Y, Zaginaev, V, Zerboni, A, Zimmer, A, Taberlet, P, Diolaiuti, G, Poulenard, J, Thuiller, W, Caccianiga, M, Ficetola, G, Ceballos Lievano, JL, Urseitova,N, Ficetola, GF, Carteron, A, Cantera, I, Guerrieri, A, Marta, S, Bonin, A, Ambrosini, R, Anthelme, F, Azzoni, R, Almond, P, Alviz Gazitúa, P, Cauvy-Fraunié, S, Ceballos Lievano, J, Chand, P, Chand Sharma, M, Clague, J, Cochachín Rapre, J, Compostella, C, Cruz Encarnación, R, Dangles, O, Eger, A, Erokhin, S, Franzetti, A, Gielly, L, Gili, F, Gobbi, M, Hågvar, S, Khedim, N, Meneses, R, Peyre, G, Pittino, F, Rabatel, A, Urseitova, N, Yang, Y, Zaginaev, V, Zerboni, A, Zimmer, A, Taberlet, P, Diolaiuti, G, Poulenard, J, Thuiller, W, Caccianiga, M, Ficetola, G, Ceballos Lievano, JL, Urseitova,N, and Ficetola, GF
Abstract: The development of terrestrial ecosystems depends greatly on plant mutualists such as mycorrhizal fungi. The global retreat of glaciers exposes nutrient-poor substrates in extreme environments and provides a unique opportunity to study early successions of mycorrhizal fungi by assessing their dynamics and drivers. We combined environmental DNA metabarcoding and measurements of local conditions to assess the succession of mycorrhizal communities during soil development in 46 glacier forelands around the globe, testing whether dynamics and drivers differ between mycorrhizal types. Mycorrhizal fungi colonized deglaciated areas very quickly (< 10 yr), with arbuscular mycorrhizal fungi tending to become more diverse through time compared to ectomycorrhizal fungi. Both alpha- and beta-diversity of arbuscular mycorrhizal fungi were significantly related to time since glacier retreat and plant communities, while microclimate and primary productivity were more important for ectomycorrhizal fungi. The richness and composition of mycorrhizal communities were also significantly explained by soil chemistry, highlighting the importance of microhabitat for community dynamics. The acceleration of ice melt and the modifications of microclimate forecasted by climate change scenarios are expected to impact the diversity of mycorrhizal partners. These changes could alter the interactions underlying biotic colonization and belowground–aboveground linkages, with multifaceted impacts on soil development and associated ecological processes.
Published: 2024

5. Proceedings of the second 'international Traveling Workshop on Interactions between Sparse models and Technology' (iTWIST'14)

Author: Jacques, L., De Vleeschouwer, C., Boursier, Y., Sudhakar, P., De Mol, C., Pizurica, A., Anthoine, S., Vandergheynst, P., Frossard, P., Bilen, C., Kitic, S., Bertin, N., Gribonval, R., Boumal, N., Mishra, B., Absil, P. -A., Sepulchre, R., Bundervoet, S., Schretter, C., Dooms, A., Schelkens, P., Chabiron, O., Malgouyres, F., Tourneret, J. -Y., Dobigeon, N., Chainais, P., Richard, C., Cornelis, B., Daubechies, I., Dunson, D., Dankova, M., Rajmic, P., Degraux, K., Cambareri, V., Geelen, B., Lafruit, G., Setti, G., Determe, J. -F., Louveaux, J., Horlin, F., Drémeau, A., Heas, P., Herzet, C., Duval, V., Peyré, G., Fawzi, A., Davies, M., Gillis, N., Vavasis, S. A., Soussen, C., Magoarou, L. Le, Liang, J., Fadili, J., Liutkus, A., Martina, D., Gigan, S., Daudet, L., Maggioni, M., Minsker, S., Strawn, N., Mory, C., Ngole, F., Starck, J. -L., Loris, I., Vaiter, S., Golbabaee, M., and Vukobratovic, D.
Subjects: Computer Science - Numerical Analysis, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Information Theory, Computer Science - Learning, Mathematics - Optimization and Control, Mathematics - Statistics Theory
Abstract: The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For its second edition, the iTWIST workshop took place in the medieval and picturesque town of Namur in Belgium, from Wednesday August 27th till Friday August 29th, 2014. The workshop was conveniently located in "The Arsenal" building within walking distance of both hotels and town center. iTWIST'14 has gathered about 70 international participants and has featured 9 invited talks, 10 oral presentations, and 14 posters on the following themes, all related to the theory, application and generalization of the "sparsity paradigm": Sparsity-driven data sensing and processing; Union of low dimensional subspaces; Beyond linear and convex inverse problem; Matrix/manifold/graph sensing/processing; Blind inverse problems and dictionary learning; Sparsity and computational neuroscience; Information theory, geometry and randomness; Complexity/accuracy tradeoffs in numerical methods; Sparsity? What's next?; Sparse machine learning and inference., Comment: 69 pages, 24 extended abstracts, iTWIST'14 website: http://sites.google.com/site/itwist14
Published: 2014

6. Geodesics on Shape Spaces with Bounded Variation and Sobolev Metrics

Author: Nardi, G., Peyré, G., and Vialard, F. -X.
Subjects: Mathematics - Optimization and Control
Abstract: This paper studies the space of $BV^2$ planar curves endowed with the $BV^2$ Finsler metric over its tangent space of displacement vector fields. Such a space is of interest for applications in image processing and computer vision because it enables piecewise regular curves that undergo piecewise regular deformations, such as articulations. The main contribution of this paper is the proof of the existence of the shortest path between any two $BV^2$-curves for this Finsler metric. Such a result is proved by applying the direct method of calculus of variation to minimize the geodesic energy. This method applies more generally to similar cases such as the space of curves with $H^k$ metrics for $k\geq 2$ integer. This space has a strong Riemannian structure and is geodesically complete. Thus, our result shows that the exponential map is surjective, which is complementary to geodesic completeness in infinite dimensions. We propose a finite element discretization of the minimal geodesic problem, and use a gradient descent method to compute a stationary point of the energy. Numerical illustrations show the qualitative difference between $BV^2$ and $H^2$ geodesics.
Published: 2014

7. Stable Recovery with Analysis Decomposable Priors

Author: Fadili, M. J., Peyré, G., Vaiter, S., Deledalle, C., and Salmon, J.
Subjects: Computer Science - Information Theory, Mathematics - Functional Analysis, Mathematics - Optimization and Control
Abstract: In this paper, we investigate in a unified way the structural properties of solutions to inverse problems. These solutions are regularized by the generic class of semi-norms defined as a decomposable norm composed with a linear operator, the so-called analysis type decomposable prior. This encompasses several well-known analysis-type regularizations such as the discrete total variation (in any dimension), analysis group-Lasso or the nuclear norm. Our main results establish sufficient conditions under which uniqueness and stability to a bounded noise of the regularized solution are guaranteed. Along the way, we also provide a strong sufficient uniqueness result that is of independent interest and goes beyond the case of decomposable norms., Comment: 4 pages, to appear in SAMPTA 2013
Published: 2013

8. Adaptive estimation of the density matrix in quantum homodyne tomography with noisy data

Author: Alquier, P, Meziani, K, and Peyré, G
Subjects: Mathematics - Statistics Theory, 62G05, 62G20, 62G86, 62P35, 81V80
Abstract: In the framework of noisy quantum homodyne tomography with efficiency parameter $1/2 < \eta \leq 1$, we propose a novel estimator of a quantum state whose density matrix elements $\rho_{m,n}$ decrease like $Ce^{-B(m+n)^{r/ 2}}$, for fixed $C\geq 1$, $B>0$ and $0
Published: 2013
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9. Fast Optimal Transport Averaging of Neuroimaging Data

Author: Gramfort, A., Peyré, G., Cuturi, M., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Ourselin, Sebastien, editor, Alexander, Daniel C., editor, Westin, Carl-Fredrik, editor, and Cardoso, M. Jorge, editor
Published: 2015
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10. Functional community structure, climate and NDVI for selected sPlot locations [Dataset]

Author: Engel, Thore, Bruelheide, H., Hoss, D., Sabatini, F.M., Altman, J., Arfin-Khan, M.A.S., Bergmeier, E., Černý, T., Chytrý, M., Dainese, M., Dengler, J., Dolezal, J., Field, R., Fischer, F.M., Huygens, D., Jandt, U., Jansen, F., Jentsch, A., Karger, D.N., Kattge, J., Lenoir, J., Lens, F., Loos, J., Niinemets, Ü., Overbeck, G.E., Ozinga, W.A., Penuelas, J., Peyre, G., Phillips, O., Reich, P.B., Römermann, C., Sandel, B., Schmidt, M., Schrodt, F., Velez-Martin, E., Violle, C., Pillar, V., Engel, Thore, Bruelheide, H., Hoss, D., Sabatini, F.M., Altman, J., Arfin-Khan, M.A.S., Bergmeier, E., Černý, T., Chytrý, M., Dainese, M., Dengler, J., Dolezal, J., Field, R., Fischer, F.M., Huygens, D., Jandt, U., Jansen, F., Jentsch, A., Karger, D.N., Kattge, J., Lenoir, J., Lens, F., Loos, J., Niinemets, Ü., Overbeck, G.E., Ozinga, W.A., Penuelas, J., Peyre, G., Phillips, O., Reich, P.B., Römermann, C., Sandel, B., Schmidt, M., Schrodt, F., Velez-Martin, E., Violle, C., and Pillar, V.
Abstract: Aim Theoretical, experimental and observational studies have shown that biodiversity–ecosystem functioning (BEF) relationships are influenced by functional community structure through two mutually non-exclusive mechanisms: (1) the dominance effect (which relates to the traits of the dominant species); and (2) the niche partitioning effect [which relates to functional diversity (FD)]. Although both mechanisms have been studied in plant communities and experiments at small spatial extents, it remains unclear whether evidence from small-extent case studies translates into a generalizable macroecological pattern. Here, we evaluate dominance and niche partitioning effects simultaneously in grassland systems world-wide. Location Two thousand nine hundred and forty-one grassland plots globally. Time period 2000–2014. Major taxa studied Vascular plants. Methods We obtained plot-based data on functional community structure from the global vegetation plot database “sPlot”, which combines species composition with plant trait data from the “TRY” database. We used data on the community-weighted mean (CWM) and FD for 18 ecologically relevant plant traits. As an indicator of primary productivity, we extracted the satellite-derived normalized difference vegetation index (NDVI) from MODIS. Using generalized additive models and deviation partitioning, we estimated the contributions of trait CWM and FD to the variation in annual maximum NDVI, while controlling for climatic variables and spatial structure. Results Grassland communities dominated by relatively tall species with acquisitive traits had higher NDVI values, suggesting the prevalence of dominance effects for BEF relationships. We found no support for niche partitioning for the functional traits analysed, because NDVI remained unaffected by FD. Most of the predictive power of traits was shared by climatic predictors and spatial coordinates. This highlights the importance of community assembly processes for BEF relationships i
Published: 2023

11. Traits of dominant plant species drive normalized difference vegetation index in grasslands globally

Author: Engel, Thore, Bruelheide, H., Hoss, D., Sabatini, F.M., Altman, J., Arfin-Khan, M.A.S., Bergmeier, E., Černý, T., Chytrý, M., Dainese, M., Dengler, J., Dolezal, J., Field, R., Fischer, F.M., Huygens, D., Jandt, U., Jansen, F., Jentsch, A., Karger, D.N., Kattge, J., Lenoir, J., Lens, F., Loos, J., Niinemets, Ü., Overbeck, G.E., Ozinga, W.A., Penuelas, J., Peyre, G., Phillips, O., Reich, P.B., Römermann, C., Sandel, B., Schmidt, M., Schrodt, F., Velez-Martin, E., Violle, C., Pillar, V., Engel, Thore, Bruelheide, H., Hoss, D., Sabatini, F.M., Altman, J., Arfin-Khan, M.A.S., Bergmeier, E., Černý, T., Chytrý, M., Dainese, M., Dengler, J., Dolezal, J., Field, R., Fischer, F.M., Huygens, D., Jandt, U., Jansen, F., Jentsch, A., Karger, D.N., Kattge, J., Lenoir, J., Lens, F., Loos, J., Niinemets, Ü., Overbeck, G.E., Ozinga, W.A., Penuelas, J., Peyre, G., Phillips, O., Reich, P.B., Römermann, C., Sandel, B., Schmidt, M., Schrodt, F., Velez-Martin, E., Violle, C., and Pillar, V.
Abstract: Aim Theoretical, experimental and observational studies have shown that biodiversity–ecosystem functioning (BEF) relationships are influenced by functional community structure through two mutually non-exclusive mechanisms: (1) the dominance effect (which relates to the traits of the dominant species); and (2) the niche partitioning effect [which relates to functional diversity (FD)]. Although both mechanisms have been studied in plant communities and experiments at small spatial extents, it remains unclear whether evidence from small-extent case studies translates into a generalizable macroecological pattern. Here, we evaluate dominance and niche partitioning effects simultaneously in grassland systems world-wide. Location Two thousand nine hundred and forty-one grassland plots globally. Time period 2000–2014. Major taxa studied Vascular plants. Methods We obtained plot-based data on functional community structure from the global vegetation plot database “sPlot”, which combines species composition with plant trait data from the “TRY” database. We used data on the community-weighted mean (CWM) and FD for 18 ecologically relevant plant traits. As an indicator of primary productivity, we extracted the satellite-derived normalized difference vegetation index (NDVI) from MODIS. Using generalized additive models and deviation partitioning, we estimated the contributions of trait CWM and FD to the variation in annual maximum NDVI, while controlling for climatic variables and spatial structure. Results Grassland communities dominated by relatively tall species with acquisitive traits had higher NDVI values, suggesting the prevalence of dominance effects for BEF relationships. We found no support for niche partitioning for the functional traits analysed, because NDVI remained unaffected by FD. Most of the predictive power of traits was shared by climatic predictors and spatial coordinates. This highlights the importance of community assembly processes for BEF relationships i
Published: 2023

12. Traits of dominant plant species drive normalized difference vegetation index in grasslands globally

Author: Engel, T., Bruelheide, H., Hoss, D., Sabatini, F.M., Altman, J, Arfin‐Khan, M.A.S., Bergmeier, E., Černý, T., Chytrý, M., Dainese, M., Dolezal, J., Field, R., Fischer, F.M., Jansen, F., Jentsch, A., Karger, D.N., Kattge, J., Lenoir, J., Lens, F., Niinemets, Ü., Overbeck, G.E., Ozinga, W.A., Penuelas, J., Peyre, G., Phillips, O., Reich, P.B., Römermann, C., Sandel, B., Schmidt, M., Schrodt, F., Velez‐Martin, E., Violle, C., Pillar, V., Dengler, Huygens, Jandt, Loos, Thore Engel, Helge Bruelheide, Daniela Ho, Francesco M. Sabatini, Jan Altman, Mohammed A. S. Arfin‐Khan, Erwin Bergmeier, Tomáš Černý, Milan Chytrý, Matteo Dainese, Jürgen Dengler, Jiri Dolezal, Richard Field, Felícia M. Fischer, Dries Huygen, Ute Jandt, Florian Jansen, Anke Jentsch, Dirk N. Karger, Jens Kattge, Jonathan Lenoir, Frederic Len, Jaqueline Loo, Ülo Niinemet, Gerhard E. Overbeck, Wim A. Ozinga, Josep Penuela, Gwendolyn Peyre, Oliver Phillip, Peter B. Reich, Christine Römermann, Brody Sandel, Marco Schmidt, Franziska Schrodt, Eduardo Velez‐Martin, Cyrille Violle, and Valério Pillar
Subjects: biodiversity–ecosystem functioning, Global and Planetary Change, Vegetation, Ecology, sPlot, Functional Diversity, Bos- en Landschapsecologie, biodiversity–ecosystem functioning, biodiversity, community-weighted mean, ecosystem, functioning, functional diversity, sPlot, traits, vegetation, Biodiversity, functional diversity, Traits, traits, Biodiversity–Ecosystem Functioning, vegetation, ecosystem functioning, Community-Weighted Mean, community-weighted mean, Forest and Landscape Ecology, Vegetatie, Bos- en Landschapsecologie, Vegetation, Forest and Landscape Ecology, Vegetatie, Ecology, Evolution, Behavior and Systematics, Ecosystem Functioning, biodiversity
Abstract: Aim: Theoretical, experimental and observational studies have shown that biodiversity–ecosystem functioning (BEF) relationships are influenced by functional community structure through two mutually non-exclusive mechanisms: (1) the dominance effect (which relates to the traits of the dominant species); and (2) the niche partitioning effect [which relates to functional diversity (FD)]. Although both mechanisms have been studied in plant communities and experiments at small spatial extents, it remains unclear whether evidence from small-extent case studies translates into a generalizable macroecological pattern. Here, we evaluate dominance and niche partitioning effects simultaneously in grassland systems world-wide.Location: Two thousand nine hundred and forty-one grassland plots globally.Time period: 2000–2014.Major taxa studied: Vascular plants.Methods: We obtained plot-based data on functional community structure from the global vegetation plot database “sPlot”, which combines species composition with plant trait data from the “TRY” database. We used data on the community-weighted mean (CWM) and FD for 18 ecologically relevant plant traits. As an indicator of primary productivity, we extracted the satellite-derived normalized difference vegetation index (NDVI) from MODIS. Using generalized additive models and deviation partitioning, we estimated the contributions of trait CWM and FD to the variation in annual maximum NDVI, while controlling for climatic variables and spatial structure.Results: Grassland communities dominated by relatively tall species with acquisitive traits had higher NDVI values, suggesting the prevalence of dominance effects for BEF relationships. We found no support for niche partitioning for the functional traits analysed, because NDVI remained unaffected by FD. Most of the predictive power of traits was shared by climatic predictors and spatial coordinates. This highlights the importance of community assembly processes for BEF relationships in natural communities.Main conclusions: Our analysis provides empirical evidence that plant functional community structure and global patterns in primary productivity are linked through the resource economics and size traits of the dominant species. This is an important test of the hypotheses underlying BEF relationships at the global scale.
Published: 2023

13. The retreat of mountain glaciers since the little ice age: A spatially explicit database

Author: Marta, S, Azzoni, R, Fugazza, D, Tielidze, L, Chand, P, Sieron, K, Almond, P, Ambrosini, R, Anthelme, F, Alviz Gazitua, P, Bhambri, R, Bonin, A, Caccianiga, M, Cauvy-Fraunie, S, Lievano, J, Clague, J, Rapre, J, Dangles, O, Deline, P, Eger, A, Encarnacion, R, Erokhin, S, Franzetti, A, Gielly, L, Gili, F, Gobbi, M, Guerrieri, A, Hagvar, S, Khedim, N, Kinyanjui, R, Messager, E, Morales-Martinez, M, Peyre, G, Pittino, F, Poulenard, J, Seppi, R, Sharma, M, Urseitova, N, Weissling, B, Yang, Y, Zaginaev, V, Zimmer, A, Diolaiuti, G, Rabatel, A, Ficetola, G, Marta S., Azzoni R. S., Fugazza D., Tielidze L., Chand P., Sieron K., Almond P., Ambrosini R., Anthelme F., Alviz Gazitua P., Bhambri R., Bonin A., Caccianiga M., Cauvy-Fraunie S., Lievano J. L. C., Clague J., Rapre J. A. C., Dangles O., Deline P., Eger A., Encarnacion R. C., Erokhin S., Franzetti A., Gielly L., Gili F., Gobbi M., Guerrieri A., Hagvar S., Khedim N., Kinyanjui R., Messager E., Morales-Martinez M. A., Peyre G., Pittino F., Poulenard J., Seppi R., Sharma M. C., Urseitova N., Weissling B., Yang Y., Zaginaev V., Zimmer A., Diolaiuti G. A., Rabatel A., Ficetola G. F., Marta, S, Azzoni, R, Fugazza, D, Tielidze, L, Chand, P, Sieron, K, Almond, P, Ambrosini, R, Anthelme, F, Alviz Gazitua, P, Bhambri, R, Bonin, A, Caccianiga, M, Cauvy-Fraunie, S, Lievano, J, Clague, J, Rapre, J, Dangles, O, Deline, P, Eger, A, Encarnacion, R, Erokhin, S, Franzetti, A, Gielly, L, Gili, F, Gobbi, M, Guerrieri, A, Hagvar, S, Khedim, N, Kinyanjui, R, Messager, E, Morales-Martinez, M, Peyre, G, Pittino, F, Poulenard, J, Seppi, R, Sharma, M, Urseitova, N, Weissling, B, Yang, Y, Zaginaev, V, Zimmer, A, Diolaiuti, G, Rabatel, A, Ficetola, G, Marta S., Azzoni R. S., Fugazza D., Tielidze L., Chand P., Sieron K., Almond P., Ambrosini R., Anthelme F., Alviz Gazitua P., Bhambri R., Bonin A., Caccianiga M., Cauvy-Fraunie S., Lievano J. L. C., Clague J., Rapre J. A. C., Dangles O., Deline P., Eger A., Encarnacion R. C., Erokhin S., Franzetti A., Gielly L., Gili F., Gobbi M., Guerrieri A., Hagvar S., Khedim N., Kinyanjui R., Messager E., Morales-Martinez M. A., Peyre G., Pittino F., Poulenard J., Seppi R., Sharma M. C., Urseitova N., Weissling B., Yang Y., Zaginaev V., Zimmer A., Diolaiuti G. A., Rabatel A., and Ficetola G. F.
Abstract: Most of the world’s mountain glaciers have been retreating for more than a century in response to climate change. Glacier retreat is evident on all continents, and the rate of retreat has accelerated during recent decades. Accurate, spatially explicit information on the position of glacier margins over time is useful for analyzing patterns of glacier retreat and measuring reductions in glacier surface area. This information is also essential for evaluating how mountain ecosystems are evolving due to climate warming and the attendant glacier retreat. Here, we present a non-comprehensive spatially explicit dataset showing multiple positions of glacier fronts since the Little Ice Age (LIA) maxima, including many data from the pre-satellite era. The dataset is based on multiple historical archival records including topographical maps; repeated photographs, paintings, and aerial or satellite images with a supplement of geochronology; and own field data. We provide ESRI shapefiles showing 728 past positions of 94 glacier fronts from all continents, except Antarctica, covering the period between the Little Ice Age maxima and the present. On average, the time series span the past 190 years. From 2 to 46 past positions per glacier are depicted (on average: 7.8).
Published: 2021

14. THE DEGREES OF FREEDOM OF THE LASSO FOR GENERAL DESIGN MATRIX

Author: Dossal, C., Kachour, M., Fadili, M.J., Peyré, G., and Chesneau, C.
Published: 2013

15. Circulating Blood Glucose and Hypothalamic-Pituitary Secretion

Author: Grino, M., Guillaume, V., Caraty, A., Conte-Devolx, B., Joanny, P., Boudouresque, F., Pesce, G., Steinberg, J., Peyre, G., Dutour, A., Giraud, P., Oliver, C., Porter, John C., editor, and Ježová, Daniela, editor
Published: 1990
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16. sPlotOpen – An environmentally balanced, open‐access, global dataset of vegetation plots

Author: Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jimenez‐Alfaro, B., Kattge, J., Levesley, A., Pillar, V.D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A.T.R., Agrillo, E., Álvarez, M., Apostolova, I., Arfin Khan, M.A.S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., Gasper, A.L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El‐Sheikh, M.A.El‐R.M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán‐de‐Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I.G., Grytnes, J‐A, Guerin, G.R., Gutiérrez, A.G., Haider, S., Hatim, M.Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J.A.M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D.N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H.S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D.V., Liu, H., Lysenko, T., Mahecha, M.D., Marcenò, C., Martynenko, V., Moeslund, J.E., Monteagudo Mendoza, A., Mucina, L., Müller, J.V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Pärtel, M., Pauchard, A., Peet, R.K., Penuelas, J., Pérez‐Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas‐Torres, G., Rodwell, J.S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Ž., Sparrow, B., Sperandii, M.G., Stančić, Z., Svenning, J‐C, Tang, Z., Tang, C.Q., Tsiripidis, I., Vanselow, K.A., Vásquez Martínez, R., Vassilev, K., Vélez‐Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., Wehrden, H., Wagner, V., Walker, D.A., Waller, D.M., Wang, H‐F, Wesche, K., Whitfeld, T.J.S., Willner, W., Wiser, S.K., Wohlgemuth, T., Yamalov, S., Zobel, M., Bruelheide, H., Bates, A., Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jimenez‐Alfaro, B., Kattge, J., Levesley, A., Pillar, V.D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A.T.R., Agrillo, E., Álvarez, M., Apostolova, I., Arfin Khan, M.A.S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., Gasper, A.L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El‐Sheikh, M.A.El‐R.M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán‐de‐Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I.G., Grytnes, J‐A, Guerin, G.R., Gutiérrez, A.G., Haider, S., Hatim, M.Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J.A.M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D.N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H.S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D.V., Liu, H., Lysenko, T., Mahecha, M.D., Marcenò, C., Martynenko, V., Moeslund, J.E., Monteagudo Mendoza, A., Mucina, L., Müller, J.V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Pärtel, M., Pauchard, A., Peet, R.K., Penuelas, J., Pérez‐Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas‐Torres, G., Rodwell, J.S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Ž., Sparrow, B., Sperandii, M.G., Stančić, Z., Svenning, J‐C, Tang, Z., Tang, C.Q., Tsiripidis, I., Vanselow, K.A., Vásquez Martínez, R., Vassilev, K., Vélez‐Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., Wehrden, H., Wagner, V., Walker, D.A., Waller, D.M., Wang, H‐F, Wesche, K., Whitfeld, T.J.S., Willner, W., Wiser, S.K., Wohlgemuth, T., Yamalov, S., Zobel, M., Bruelheide, H., and Bates, A.
Abstract: Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring.
Published: 2021

17. Global functional variation in alpine vegetation

Author: Testolin, R., Carmona, C.P., Attorre, F., Borchardt, P., Bruelheide, H., Dolezal, J., Finckh, M., Haider, S., Hemp, A., Jandt, U., Korolyuk, A.Y., Lenoir, J., Makunina, N., Malanson, G.P., Mucina, L., Noroozi, J., Nowak, A., Peet, R.K., Peyre, G., Sabatini, F.M., Šibík, J., Sklenář, P., Vassilev, K., Virtanen, R., Wiser, S.K., Zibzeev, E.G., Jiménez‐Alfaro, B., Kreft, H., Testolin, R., Carmona, C.P., Attorre, F., Borchardt, P., Bruelheide, H., Dolezal, J., Finckh, M., Haider, S., Hemp, A., Jandt, U., Korolyuk, A.Y., Lenoir, J., Makunina, N., Malanson, G.P., Mucina, L., Noroozi, J., Nowak, A., Peet, R.K., Peyre, G., Sabatini, F.M., Šibík, J., Sklenář, P., Vassilev, K., Virtanen, R., Wiser, S.K., Zibzeev, E.G., Jiménez‐Alfaro, B., and Kreft, H.
Abstract: Questions What are the functional trade‐offs of vascular plant species in global alpine ecosystems? How is functional variation related to vegetation zones, climatic groups and biogeographic realms? What is the relative contribution of macroclimate and evolutionary history in shaping the functional variation of alpine plant communities? Location Global. Methods We compiled a data set of alpine vegetation with 5,532 geo‐referenced plots, 1,933 species and six plant functional traits. We used principal component analysis to quantify functional trade‐offs among species and trait probability density to assess the functional dissimilarity of alpine vegetation in different vegetation zones, climatic groups and biogeographic realms. We used multiple regression on distance matrices to model community functional dissimilarity against environmental and phylogenetic dissimilarity, controlling for geographic distance. Results The first two PCA axes explained 66% of the species’ functional variation and were related to the leaf and stem economic spectra, respectively. Trait probability density was largely independent of vegetation zone and macroclimate but differed across biogeographic realms. The same pattern emerged for both species pool and community levels. The effects of environmental and phylogenetic dissimilarities on community functional dissimilarity had similar magnitude, while the effect of geographic distance was negligible. Conclusions Plant species in alpine areas reflect the global variation of plant function, but with a predominant role of resource use strategies. Current macroclimate exerts a limited effect on alpine vegetation, mostly acting at the community level in combination with evolutionary history. Global alpine vegetation is functionally unrelated to the vegetation zones in which it is embedded, exhibiting strong functional convergence across regions.
Published: 2021

18. Global functional variation in alpine vegetation

Author: Testolin, R. (Riccardo), Carmona, C. P. (Carlos Pérez), Attorre, F. (Fabio), Borchardt, P. (Peter), ´Bruelheide, H. (Helge), Dolezal, J. (Jiri), Finckh, M. (Manfred), Haider, S. (Sylvia), Hemp, A. (Andreas), Jandt, U. (Ute), Korolyuk, A. Y. (Andrei Yu), Lenoir, J. (Jonathan), Makunina, N. (Natalia), Malanson, G. P. (George P), Mucina, L. (Ladislav), Noroozi, J. (Jalil), Nowak, A. (Arkadiusz), Peet, R. K. (Robert K), Peyre, G. (Gwendolyn), Sabatini, F. M. (Francesco Maria), Šibík, J. (Jozef), Sklenář, P. (Petr), Vassilev, K. (Kiril), Virtanen, R. (Risto), Wiser, S. K. (Susan K), Zibzeev, E. G. (Evgeny G), Jiménez-Alfaro, B. (Borja), Testolin, R. (Riccardo), Carmona, C. P. (Carlos Pérez), Attorre, F. (Fabio), Borchardt, P. (Peter), ´Bruelheide, H. (Helge), Dolezal, J. (Jiri), Finckh, M. (Manfred), Haider, S. (Sylvia), Hemp, A. (Andreas), Jandt, U. (Ute), Korolyuk, A. Y. (Andrei Yu), Lenoir, J. (Jonathan), Makunina, N. (Natalia), Malanson, G. P. (George P), Mucina, L. (Ladislav), Noroozi, J. (Jalil), Nowak, A. (Arkadiusz), Peet, R. K. (Robert K), Peyre, G. (Gwendolyn), Sabatini, F. M. (Francesco Maria), Šibík, J. (Jozef), Sklenář, P. (Petr), Vassilev, K. (Kiril), Virtanen, R. (Risto), Wiser, S. K. (Susan K), Zibzeev, E. G. (Evgeny G), and Jiménez-Alfaro, B. (Borja)
Abstract: Questions: What are the functional trade-offs of vascular plant species in global alpine ecosystems? How is functional variation related to vegetation zones, climatic groups and biogeographic realms? What is the relative contribution of macroclimate and evolutionary history in shaping the functional variation of alpine plant communities? Location: Global. Methods: We compiled a data set of alpine vegetation with 5,532 geo-referenced plots, 1,933 species and six plant functional traits. We used principal component analysis to quantify functional trade-offs among species and trait probability density to assess the functional dissimilarity of alpine vegetation in different vegetation zones, climatic groups and biogeographic realms. We used multiple regression on distance matrices to model community functional dissimilarity against environmental and phylogenetic dissimilarity, controlling for geographic distance. Results: The first two PCA axes explained 66% of the species’ functional variation and were related to the leaf and stem economic spectra, respectively. Trait probability density was largely independent of vegetation zone and macroclimate but differed across biogeographic realms. The same pattern emerged for both species pool and community levels. The effects of environmental and phylogenetic dissimilarities on community functional dissimilarity had similar magnitude, while the effect of geographic distance was negligible. Conclusions: Plant species in alpine areas reflect the global variation of plant function, but with a predominant role of resource use strategies. Current macroclimate exerts a limited effect on alpine vegetation, mostly acting at the community level in combination with evolutionary history. Global alpine vegetation is functionally unrelated to the vegetation zones in which it is embedded, exhibiting strong functional convergence across regions.
Published: 2021

19. sPlotOpen:an environmentally balanced, open-access, global dataset of vegetation plots

Author: 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

20. Global patterns and drivers of alpine plant species richness

Author: Testolin, R. (Riccardo), Attorre, F. (Fabio), Borchardt, P. (Peter), Brand, R. F. (Robert F.), Bruelheide, H. (Helge), Chytry, M. (Milan), De Sanctis, M. (Michele), Dolezal, J. (Jiri), Finckh, M. (Manfred), Haider, S. (Sylvia), Hemp, A. (Andreas), Jandt, U. (Ute), Kessler, M. (Michael), Korolyuk, A. Y. (Andrey Yu), Lenoir, J. (Jonathan), Makunina, N. (Natalia), Malanson, G. P. (George P.), Montesinos-Tubee, D. B. (Daniel B.), Noroozi, J. (Jalil), Nowak, A. (Arkadiusz), Peet, R. K. (Robert K.), Peyre, G. (Gwendolyn), Sabatini, F. M. (Francesco Maria), Sibik, J. (Jozef), Sklenar, P. (Petr), Sylvester, S. P. (Steven P.), Vassilev, K. (Kiril), Virtanen, R. (Risto), Willner, W. (Wolfgang), Wiser, S. K. (Susan K.), Zibzeev, E. G. (Evgeny G.), Jimenez-Alfaro, B. (Borja), Testolin, R. (Riccardo), Attorre, F. (Fabio), Borchardt, P. (Peter), Brand, R. F. (Robert F.), Bruelheide, H. (Helge), Chytry, M. (Milan), De Sanctis, M. (Michele), Dolezal, J. (Jiri), Finckh, M. (Manfred), Haider, S. (Sylvia), Hemp, A. (Andreas), Jandt, U. (Ute), Kessler, M. (Michael), Korolyuk, A. Y. (Andrey Yu), Lenoir, J. (Jonathan), Makunina, N. (Natalia), Malanson, G. P. (George P.), Montesinos-Tubee, D. B. (Daniel B.), Noroozi, J. (Jalil), Nowak, A. (Arkadiusz), Peet, R. K. (Robert K.), Peyre, G. (Gwendolyn), Sabatini, F. M. (Francesco Maria), Sibik, J. (Jozef), Sklenar, P. (Petr), Sylvester, S. P. (Steven P.), Vassilev, K. (Kiril), Virtanen, R. (Risto), Willner, W. (Wolfgang), Wiser, S. K. (Susan K.), Zibzeev, E. G. (Evgeny G.), and Jimenez-Alfaro, B. (Borja)
Abstract: Aim: Alpine ecosystems differ in area, macroenvironment and biogeographical history across the Earth, but the relationship between these factors and plant species richness is still unexplored. Here, we assess the global patterns of plant species richness in alpine ecosystems and their association with environmental, geographical and historical factors at regional and community scales. Location: Global. Time period: Data collected between 1923 and 2019. Major taxa studied: Vascular plants. Methods: We used a dataset representative of global alpine vegetation, consisting of 8,928 plots sampled within 26 ecoregions and six biogeographical realms, to estimate regional richness using sample-based rarefaction and extrapolation. Then, we evaluated latitudinal patterns of regional and community richness with generalized additive models. Using environmental, geographical and historical predictors from global raster layers, we modelled regional and community richness in a mixed-effect modelling framework. Results: The latitudinal pattern of regional richness peaked around the equator and at mid-latitudes, in response to current and past alpine area, isolation and the variation in soil pH among regions. At the community level, species richness peaked at mid-latitudes of the Northern Hemisphere, despite a considerable within-region variation. Community richness was related to macroclimate and historical predictors, with strong effects of other spatially structured factors. Main conclusions: In contrast to the well-known latitudinal diversity gradient, the alpine plant species richness of some temperate regions in Eurasia was comparable to that of hyperdiverse tropical ecosystems, such as the páramo. The species richness of these putative hotspot regions is explained mainly by the extent of alpine area and their glacial history, whereas community richness depends on local environmental factors. Our results highlight hotspots of species richness at mid-latitudes, indicat
Published: 2021

21. Global patterns and drivers of alpine plant species richness

Author: Testolin, R., Attorre, F., Borchardt, P., Brand, R.F., Bruelheide, H., Chytrý, M., De Sanctis, M., Dolezal, J., Finckh, M., Haider, S., Hemp, A., Jandt, U., Kessler, M., Korolyuk, A.Y., Lenoir, J., Makunina, N., Malanson, G.P., Montesinos‐Tubée, D.B., Noroozi, J., Nowak, A., Peet, R.K., Peyre, G., Sabatini, F.M., Šibík, J., Sklenář, P., Sylvester, S.P., Vassilev, K., Virtanen, Risto, Willner, W., Wiser, S.K., Zibzeev, E.G., Jiménez‐Alfaro, B., Testolin, R., Attorre, F., Borchardt, P., Brand, R.F., Bruelheide, H., Chytrý, M., De Sanctis, M., Dolezal, J., Finckh, M., Haider, S., Hemp, A., Jandt, U., Kessler, M., Korolyuk, A.Y., Lenoir, J., Makunina, N., Malanson, G.P., Montesinos‐Tubée, D.B., Noroozi, J., Nowak, A., Peet, R.K., Peyre, G., Sabatini, F.M., Šibík, J., Sklenář, P., Sylvester, S.P., Vassilev, K., Virtanen, Risto, Willner, W., Wiser, S.K., Zibzeev, E.G., and Jiménez‐Alfaro, B.
Abstract: Aim Alpine ecosystems differ in area, macroenvironment and biogeographical history across the Earth, but the relationship between these factors and plant species richness is still unexplored. Here, we assess the global patterns of plant species richness in alpine ecosystems and their association with environmental, geographical and historical factors at regional and community scales. Location Global. Time period Data collected between 1923 and 2019. Major taxa studied Vascular plants. Methods We used a dataset representative of global alpine vegetation, consisting of 8,928 plots sampled within 26 ecoregions and six biogeographical realms, to estimate regional richness using sample‐based rarefaction and extrapolation. Then, we evaluated latitudinal patterns of regional and community richness with generalized additive models. Using environmental, geographical and historical predictors from global raster layers, we modelled regional and community richness in a mixed‐effect modelling framework. Results The latitudinal pattern of regional richness peaked around the equator and at mid‐latitudes, in response to current and past alpine area, isolation and the variation in soil pH among regions. At the community level, species richness peaked at mid‐latitudes of the Northern Hemisphere, despite a considerable within‐region variation. Community richness was related to macroclimate and historical predictors, with strong effects of other spatially structured factors. Main conclusions In contrast to the well‐known latitudinal diversity gradient, the alpine plant species richness of some temperate regions in Eurasia was comparable to that of hyperdiverse tropical ecosystems, such as the páramo. The species richness of these putative hotspot regions is explained mainly by the extent of alpine area and their glacial history, whereas community richness depends on local environmental factors. Our results highlight hotspots of species richness at mid‐latitudes, indicating that the div
Published: 2021

22. Best basis compressed sensing

Author: Peyre, G.
Subjects: Data compression -- Usage, Iterative methods (Mathematics) -- Usage, Signal processing -- Methods, Digital signal processor, Business, Computers, Electronics, Electronics and electrical industries
Published: 2010

23. Texture synthesis with grouplets

Author: Peyre, G.
Subjects: Machine vision -- Analysis, Image processing -- Analysis, Object recognition (Computers) -- Analysis, Pattern recognition -- Analysis
Published: 2010

24. sPlot:a new tool for global vegetation analyses

Author: Bruelheide, H. (Helge), Dengler, J. (Juergen), Jimenez-Alfaro, B. (Borja), Purschke, O. (Oliver), Hennekens, S. M. (Stephan M.), Chytry, M. (Milan), Pillar, V. D. (Valerio D.), Jansen, F. (Florian), Kattge, J. (Jens), Sandel, B. (Brody), Aubin, I. (Isabelle), Biurrun, I. (Idoia), Field, R. (Richard), Haider, S. (Sylvia), Jandt, U. (Ute), Lenoir, J. (Jonathan), Peet, R. K. (Robert K.), Peyre, G. (Gwendolyn), Sabatini, F. M. (Francesco Maria), Schmidt, M. (Marco), Schrodt, F. (Franziska), Winter, M. (Marten), Acic, S. (Svetlana), Agrillo, E. (Emiliano), Alvarez, M. (Miguel), Ambarli, D. (Didem), Angelini, P. (Pierangela), Apostolova, I. (Iva), Khan, M. A. (Mohammed A. S. Arfin), Arnst, E. (Elise), Attorre, F. (Fabio), Baraloto, C. (Christopher), Beckmann, M. (Michael), Berg, C. (Christian), Bergeron, Y. (Yves), Bergmeier, E. (Erwin), Bjorkman, A. D. (Anne D.), Bondareva, V. (Viktoria), Borchardt, P. (Peter), Botta-Dukat, Z. (Zoltan), Boyle, B. (Brad), Breen, A. (Amy), Brisse, H. (Henry), Byun, C. (Chaeho), Cabido, M. R. (Marcelo R.), Casella, L. (Laura), Cayuela, L. (Luis), Cerny, T. (Tomas), Chepinoga, V. (Victor), Csiky, J. (Janos), Curran, M. (Michael), Custerevska, R. (Renata), Stevanovic, Z. D. (Zora Dajic), De Bie, E. (Els), de Ruffray, P. (Patrice), De Sanctis, M. (Michele), Dimopoulos, P. (Panayotis), Dressler, S. (Stefan), Ejrnaes, R. (Rasmus), El-Sheikh, M. A. (Mohamed Abd El-Rouf Mousa), Enquist, B. (Brian), Ewald, J. (Joerg), Fagundez, J. (Jaime), Finckh, M. (Manfred), Font, X. (Xavier), Forey, E. (Estelle), Fotiadis, G. (Georgios), Garcia-Mijangos, I. (Itziar), de Gasper, A. L. (Andre Luis), Golub, V. (Valentin), Gutierrez, A. G. (Alvaro G.), Hatim, M. Z. (Mohamed Z.), He, T. (Tianhua), Higuchi, P. (Pedro), Holubova, D. (Dana), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Indreica, A. (Adrian), Gursoy, D. I. (Deniz Isik), Jansen, S. (Steven), Janssen, J. (John), Jedrzejek, B. (Birgit), Jirousek, M. (Martin), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Kavgaci, A. (Ali), Kearsley, E. (Elizabeth), Kessler, M. (Michael), Knollova, I. (Ilona), Kolomiychuk, V. (Vitaliy), Korolyuk, A. (Andrey), Kozhevnikova, M. (Maria), Kozub, L. (Lukasz), Krstonosic, D. (Daniel), Kuehl, H. (Hjalmar), Kuehn, I. (Ingolf), Kuzemko, A. (Anna), Kuzmic, F. (Filip), Landucci, F. (Flavia), Lee, M. T. (Michael T.), Levesley, A. (Aurora), Li, C.-F. (Ching-Feng), Liu, H. (Hongyan), Lopez-Gonzalez, G. (Gabriela), Lysenko, T. (Tatiana), Macanovic, A. (Armin), Mahdavi, P. (Parastoo), Manning, P. (Peter), Marceno, C. (Corrado), Martynenko, V. (Vassiliy), Mencuccini, M. (Maurizio), Minden, V. (Vanessa), Moeslund, J. E. (Jesper Erenskjold), Moretti, M. (Marco), Mueller, J. V. (Jonas V.), Munzinger, J. (Jerome), Niinemets, U. (Ulo), Nobis, M. (Marcin), Noroozi, J. (Jalil), Nowak, A. (Arkadiusz), Onyshchenko, V. (Viktor), Overbeck, G. E. (Gerhard E.), Ozinga, W. A. (Wim A.), Pauchard, A. (Anibal), Pedashenko, H. (Hristo), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Peterka, T. (Tomas), Petrik, P. (Petr), Phillips, O. L. (Oliver L.), Prokhorov, V. (Vadim), Rasomavicius, V. (Valerijus), Revermann, R. (Rasmus), Rodwell, J. (John), Ruprecht, E. (Eszter), Rusina, S. (Solvita), Samimi, C. (Cyrus), Schaminee, J. H. (Joop H. J.), Schmiedel, U. (Ute), Sibik, J. (Jozef), Silc, U. (Urban), Skvorc, Z. (Zeljko), Smyth, A. (Anita), Sop, T. (Tenekwetche), Sopotlieva, D. (Desislava), Sparrow, B. (Ben), Stancic, Z. (Zvjezdana), Svenning, J.-C. (Jens-Christian), Swacha, G. (Grzegorz), Tang, Z. (Zhiyao), Tsiripidis, I. (Ioannis), Turtureanu, P. D. (Pavel Dan), Ugurlu, E. (Emin), Uogintas, D. (Domas), Valachovic, M. (Milan), Vanselow, K. A. (Kim Andre), Vashenyak, Y. (Yulia), 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.), Wana, D. (Desalegn), Weiher, E. (Evan), Wesche, K. (Karsten), Whitfeld, T. (Timothy), Willner, W. (Wolfgang), Wiser, S. (Susan), Wohlgemuth, T. (Thomas), Yamalov, S. (Sergey), Zizka, G. (Georg), Zverev, A. (Andrei), Bruelheide, H. (Helge), Dengler, J. (Juergen), Jimenez-Alfaro, B. (Borja), Purschke, O. (Oliver), Hennekens, S. M. (Stephan M.), Chytry, M. (Milan), Pillar, V. D. (Valerio D.), Jansen, F. (Florian), Kattge, J. (Jens), Sandel, B. (Brody), Aubin, I. (Isabelle), Biurrun, I. (Idoia), Field, R. (Richard), Haider, S. (Sylvia), Jandt, U. (Ute), Lenoir, J. (Jonathan), Peet, R. K. (Robert K.), Peyre, G. (Gwendolyn), Sabatini, F. M. (Francesco Maria), Schmidt, M. (Marco), Schrodt, F. (Franziska), Winter, M. (Marten), Acic, S. (Svetlana), Agrillo, E. (Emiliano), Alvarez, M. (Miguel), Ambarli, D. (Didem), Angelini, P. (Pierangela), Apostolova, I. (Iva), Khan, M. A. (Mohammed A. S. Arfin), Arnst, E. (Elise), Attorre, F. (Fabio), Baraloto, C. (Christopher), Beckmann, M. (Michael), Berg, C. (Christian), Bergeron, Y. (Yves), Bergmeier, E. (Erwin), Bjorkman, A. D. (Anne D.), Bondareva, V. (Viktoria), Borchardt, P. (Peter), Botta-Dukat, Z. (Zoltan), Boyle, B. (Brad), Breen, A. (Amy), Brisse, H. (Henry), Byun, C. (Chaeho), Cabido, M. R. (Marcelo R.), Casella, L. (Laura), Cayuela, L. (Luis), Cerny, T. (Tomas), Chepinoga, V. (Victor), Csiky, J. (Janos), Curran, M. (Michael), Custerevska, R. (Renata), Stevanovic, Z. D. (Zora Dajic), De Bie, E. (Els), de Ruffray, P. (Patrice), De Sanctis, M. (Michele), Dimopoulos, P. (Panayotis), Dressler, S. (Stefan), Ejrnaes, R. (Rasmus), El-Sheikh, M. A. (Mohamed Abd El-Rouf Mousa), Enquist, B. (Brian), Ewald, J. (Joerg), Fagundez, J. (Jaime), Finckh, M. (Manfred), Font, X. (Xavier), Forey, E. (Estelle), Fotiadis, G. (Georgios), Garcia-Mijangos, I. (Itziar), de Gasper, A. L. (Andre Luis), Golub, V. (Valentin), Gutierrez, A. G. (Alvaro G.), Hatim, M. Z. (Mohamed Z.), He, T. (Tianhua), Higuchi, P. (Pedro), Holubova, D. (Dana), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Indreica, A. (Adrian), Gursoy, D. I. (Deniz Isik), Jansen, S. (Steven), Janssen, J. (John), Jedrzejek, B. (Birgit), Jirousek, M. (Martin), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Kavgaci, A. (Ali), Kearsley, E. (Elizabeth), Kessler, M. (Michael), Knollova, I. (Ilona), Kolomiychuk, V. (Vitaliy), Korolyuk, A. (Andrey), Kozhevnikova, M. (Maria), Kozub, L. (Lukasz), Krstonosic, D. (Daniel), Kuehl, H. (Hjalmar), Kuehn, I. (Ingolf), Kuzemko, A. (Anna), Kuzmic, F. (Filip), Landucci, F. (Flavia), Lee, M. T. (Michael T.), Levesley, A. (Aurora), Li, C.-F. (Ching-Feng), Liu, H. (Hongyan), Lopez-Gonzalez, G. (Gabriela), Lysenko, T. (Tatiana), Macanovic, A. (Armin), Mahdavi, P. (Parastoo), Manning, P. (Peter), Marceno, C. (Corrado), Martynenko, V. (Vassiliy), Mencuccini, M. (Maurizio), Minden, V. (Vanessa), Moeslund, J. E. (Jesper Erenskjold), Moretti, M. (Marco), Mueller, J. V. (Jonas V.), Munzinger, J. (Jerome), Niinemets, U. (Ulo), Nobis, M. (Marcin), Noroozi, J. (Jalil), Nowak, A. (Arkadiusz), Onyshchenko, V. (Viktor), Overbeck, G. E. (Gerhard E.), Ozinga, W. A. (Wim A.), Pauchard, A. (Anibal), Pedashenko, H. (Hristo), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Peterka, T. (Tomas), Petrik, P. (Petr), Phillips, O. L. (Oliver L.), Prokhorov, V. (Vadim), Rasomavicius, V. (Valerijus), Revermann, R. (Rasmus), Rodwell, J. (John), Ruprecht, E. (Eszter), Rusina, S. (Solvita), Samimi, C. (Cyrus), Schaminee, J. H. (Joop H. J.), Schmiedel, U. (Ute), Sibik, J. (Jozef), Silc, U. (Urban), Skvorc, Z. (Zeljko), Smyth, A. (Anita), Sop, T. (Tenekwetche), Sopotlieva, D. (Desislava), Sparrow, B. (Ben), Stancic, Z. (Zvjezdana), Svenning, J.-C. (Jens-Christian), Swacha, G. (Grzegorz), Tang, Z. (Zhiyao), Tsiripidis, I. (Ioannis), Turtureanu, P. D. (Pavel Dan), Ugurlu, E. (Emin), Uogintas, D. (Domas), Valachovic, M. (Milan), Vanselow, K. A. (Kim Andre), Vashenyak, Y. (Yulia), 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.), Wana, D. (Desalegn), Weiher, E. (Evan), Wesche, K. (Karsten), Whitfeld, T. (Timothy), Willner, W. (Wolfgang), Wiser, S. (Susan), Wohlgemuth, T. (Thomas), Yamalov, S. (Sergey), Zizka, G. (Georg), and Zverev, A. (Andrei)
Abstract: Aims: Vegetation‐plot records provide information on the presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community‐weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.
Published: 2019

25. sPlot – a new tool for global vegetation analyses

Author: Bruelheide, H., Dengler, J., Jiménez‐Alfaro, B., Purschke, O., Hennekens, S.M., Chytrý, M., Pillar, V.D., Jansen, F., Kattge, J., Sandel, B., Aubin, I., Biurrun, I., Field, R., Haider, S., Jandt, U., Lenoir, J., Peet, R.K., Peyre, G., Sabatini, F.M., Schmidt, M., Schrodt, F., Winter, M., Aćić, S., Agrillo, E., Alvarez, M., Ambarlı, D., Angelini, P., Apostolova, I., Khan, M.A.S.A., Arnst, E., Attorre, F., Baraloto, C., Beckmann, Michael, Kühn, Ingolf, Virtanen, Risto, Berg, C., et al., Bruelheide, H., Dengler, J., Jiménez‐Alfaro, B., Purschke, O., Hennekens, S.M., Chytrý, M., Pillar, V.D., Jansen, F., Kattge, J., Sandel, B., Aubin, I., Biurrun, I., Field, R., Haider, S., Jandt, U., Lenoir, J., Peet, R.K., Peyre, G., Sabatini, F.M., Schmidt, M., Schrodt, F., Winter, M., Aćić, S., Agrillo, E., Alvarez, M., Ambarlı, D., Angelini, P., Apostolova, I., Khan, M.A.S.A., Arnst, E., Attorre, F., Baraloto, C., Beckmann, Michael, Kühn, Ingolf, Virtanen, Risto, and Berg, C., et al.
Abstract: QuestionsVegetation‐plot records provide information on presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. LocationsPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected between 1885 and 2015. MethodsWe complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g. biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. ResultsWe present the first maps of global patterns of community richness and community‐weighted means of key traits. ConclusionsThe availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.
Published: 2019

26. Studies on the Secretion of Corticotropin-Releasing Factor into Hypophysial Portal Blood

Author: Guillaume, V., Grino, M., Peyre, G., Conte-Devolx, B., Oliver, C., Chrousos, George P., editor, Loriaux, D. Lynn, editor, and Gold, Philip W., editor
Published: 1988
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27. Calcul des Valeurs Propres Pour des Structures Lineaires par la Methode de Kuhn

Author: Delfour, M. C., Peyre, G., Rideau, P., Bensoussan, A., editor, and Lions, J. L., editor
Published: 1986
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28. Méthode EF² et hyperréduction de modèle : vers des calculs massifs à l'échelle micro

Author: Peyre, G., ONERA - The French Aerospace Lab [Châtillon], ONERA-Université Paris Saclay (COmUE), ECOLE NATIONALE SUPERIEURE DES MINES DE PARIS, and Frédéric FEYEL
Subjects: NON-LINEAR MODEL REDUCTION, REDUCTION DE MODELE NON-LINEAIRE, CALCULS MULTI-ECHELLES, HYPERREDUCTION, MULTISCALE SIMULATIONS, METHODES EF2, ARCHITECTURE LOGICIELLE MODULAIRE, FE2, OBJECT-ORIENTED SOFTWARE DESIGN, [SPI.MAT]Engineering Sciences [physics]/Materials
Abstract: Model Order Reduction (MOR) methods are used to cope with high computational costs typically involved in parametric analysis of structures requiring a huge number of almost similar simulations. Among them, a so-called hyperreduction method suitable for non-linear mechanical finite element (FE) problems is studied. An objected-oriented approach to deal with it in the framework of a FE software is carried out. The software design takes advantage of a two-level process : a so-called offline computation step in which the reduced model is set up based on collected snapshots of mechanical system states and an online high-speed reduced computation which runs the reduced model. The code design relying on a reduced element is expected to enhance performance, to give a clearer view over the process and to favour code reuse in subsequent developments of the method. Futhermore, the hyperreduction method is reviewed and is deeply improved : vector and tensor bases are introduced to deal with non-scalar fields which arise in non-linear mechanical FE problems and the mechanical balance is ensured in the extrapolation phase. A particular emphasis is placed on the treatment of free and periodic boundary conditions. In this approach, the boundary conditions at the edge of the reduced integration domain are enforced in the reduced balance equations. Numerical toy examples of elasticity fiber/matrix inclusions as well as a full adaptative non-linear simluation are provided to show the capabilities of the implementation. To take into account microstructural behaviors, FE² methods consist in splitting the computation into two scales. At the micro scale the material constitutive equations are integrated over periodic RVEs. The behavior of the macro structure is carried out by a homogeneized process. A multidimensional hyperreduction method is applied to the massive micro problem composed of the set of the periodic RVEs. A BFGS algorithm is used to update the macro tangent matrices at each integration Gauss point. Some speed-ups are recorded for low dimensional models. However, as the number of degrees of freedom increases, the multidimensional hyperreduction method is proved to be far less efficient to cut computational costs down.; Des méthodes de réduction de modèle sont utilisées pour diminuer le coût de calcul associé à des analyses paramétriques de structures qui requièrent un très grand nombre de simulations quasi-identiques.Parmi ces méthodes, l’hyperréduction de modèle est efficace pour attaquer les problèmes de mécanique non-linéaire. Une approche orientée objet de cette méthode dans le cadre d’un code éléments finis modulaire a été développée. L’architecture logicielle s’appuie sur un algorithme qui se déroule en deux étapes : une étape offline dans laquelle le modèle réduit est construit à partir d’états du système mécanique et une étape online de calcul réduit qui exploite le modèle réduit. La structure du code qui repose sur l’utilisation d’un élément réduit permet d’améliorer la performance, de simplifier la prise en main et de favoriser sa réutilisation dans les développements futurs de la méthode. En outre, la méthode d’hyperréduction est revisitée et améliorée : des bases réduites vectorielles et tensorielles sont mises en oeuvre pour traiter les champs de contraintes et de variables internes des calculs éléments finis non-linéaires. En particulier, l’accent est mis sur la prise en compte des conditions aux limites périodiques et des conditions de bord libre. Dans cette démarche, les conditions aux limites au bord du domaine réduit sont imposées dans l’équation de l’équilibre mécanique réduit. Des exemples d’inclusions élastiques fibre/matrice sont fournis ainsi qu’un calcul complet adaptatif non-linéaire sur plaque perforée. Pour prendre en compte les effets de la microstructure, les méthodes éléments finis au carré (EF²) divisent le problème mécanique en deux échelles. A l’échelle microscopique, les équations de comportement sont intégrées sur le volume élémentaire représentatif (VER) sollicité en condition périodique. Le comportement de la structure macroscopique est déterminé par homogénéisation. Une méthode d’hyperréduction multidimensionnelle est appliquée au problème microscopique constitué de l’ensemble des volumes élémentaires représentatifs. On se sert d’un algorithme de Broyden-Fletcher- Goldfarb-Shanno (BFGS) pour mettre à jour les matrices tangentes macroscopiques en chaque point de Gauss. On parvient ainsi à diminuer le temps de calcul sur des modèles de faible dimension.Cependant, quand le nombre de degrés de liberté augmente, on démontre que l’hyperréduction de modèle multidimensionnelle ne parvient pas à réduire suffisamment les coûts de calcul.
Published: 2015

29. FE² and hyperreduction techniques: going towards very large multiscale simulations

Author: Peyre, G., ONERA - The French Aerospace Lab [Châtillon], ONERA-Université Paris Saclay (COmUE), ECOLE NATIONALE SUPERIEURE DES MINES DE PARIS, Frédéric FEYEL, and André, Cécile
Subjects: NON-LINEAR MODEL REDUCTION, REDUCTION DE MODELE NON-LINEAIRE, CALCULS MULTI-ECHELLES, HYPERREDUCTION, MULTISCALE SIMULATIONS, METHODES EF2, ARCHITECTURE LOGICIELLE MODULAIRE, [SPI.MAT] Engineering Sciences [physics]/Materials, FE2, OBJECT-ORIENTED SOFTWARE DESIGN, [SPI.MAT]Engineering Sciences [physics]/Materials
Abstract: Model Order Reduction (MOR) methods are used to cope with high computational costs typically involved in parametric analysis of structures requiring a huge number of almost similar simulations. Among them, a so-called hyperreduction method suitable for non-linear mechanical finite element (FE) problems is studied. An objected-oriented approach to deal with it in the framework of a FE software is carried out. The software design takes advantage of a two-level process : a so-called offline computation step in which the reduced model is set up based on collected snapshots of mechanical system states and an online high-speed reduced computation which runs the reduced model. The code design relying on a reduced element is expected to enhance performance, to give a clearer view over the process and to favour code reuse in subsequent developments of the method. Futhermore, the hyperreduction method is reviewed and is deeply improved : vector and tensor bases are introduced to deal with non-scalar fields which arise in non-linear mechanical FE problems and the mechanical balance is ensured in the extrapolation phase. A particular emphasis is placed on the treatment of free and periodic boundary conditions. In this approach, the boundary conditions at the edge of the reduced integration domain are enforced in the reduced balance equations. Numerical toy examples of elasticity fiber/matrix inclusions as well as a full adaptative non-linear simluation are provided to show the capabilities of the implementation. To take into account microstructural behaviors, FE² methods consist in splitting the computation into two scales. At the micro scale the material constitutive equations are integrated over periodic RVEs. The behavior of the macro structure is carried out by a homogeneized process. A multidimensional hyperreduction method is applied to the massive micro problem composed of the set of the periodic RVEs. A BFGS algorithm is used to update the macro tangent matrices at each integration Gauss point. Some speed-ups are recorded for low dimensional models. However, as the number of degrees of freedom increases, the multidimensional hyperreduction method is proved to be far less efficient to cut computational costs down., Des méthodes de réduction de modèle sont utilisées pour diminuer le coût de calcul associé à des analyses paramétriques de structures qui requièrent un très grand nombre de simulations quasi-identiques.Parmi ces méthodes, l’hyperréduction de modèle est efficace pour attaquer les problèmes de mécanique non-linéaire. Une approche orientée objet de cette méthode dans le cadre d’un code éléments finis modulaire a été développée. L’architecture logicielle s’appuie sur un algorithme qui se déroule en deux étapes : une étape offline dans laquelle le modèle réduit est construit à partir d’états du système mécanique et une étape online de calcul réduit qui exploite le modèle réduit. La structure du code qui repose sur l’utilisation d’un élément réduit permet d’améliorer la performance, de simplifier la prise en main et de favoriser sa réutilisation dans les développements futurs de la méthode. En outre, la méthode d’hyperréduction est revisitée et améliorée : des bases réduites vectorielles et tensorielles sont mises en oeuvre pour traiter les champs de contraintes et de variables internes des calculs éléments finis non-linéaires. En particulier, l’accent est mis sur la prise en compte des conditions aux limites périodiques et des conditions de bord libre. Dans cette démarche, les conditions aux limites au bord du domaine réduit sont imposées dans l’équation de l’équilibre mécanique réduit. Des exemples d’inclusions élastiques fibre/matrice sont fournis ainsi qu’un calcul complet adaptatif non-linéaire sur plaque perforée. Pour prendre en compte les effets de la microstructure, les méthodes éléments finis au carré (EF²) divisent le problème mécanique en deux échelles. A l’échelle microscopique, les équations de comportement sont intégrées sur le volume élémentaire représentatif (VER) sollicité en condition périodique. Le comportement de la structure macroscopique est déterminé par homogénéisation. Une méthode d’hyperréduction multidimensionnelle est appliquée au problème microscopique constitué de l’ensemble des volumes élémentaires représentatifs. On se sert d’un algorithme de Broyden-Fletcher- Goldfarb-Shanno (BFGS) pour mettre à jour les matrices tangentes macroscopiques en chaque point de Gauss. On parvient ainsi à diminuer le temps de calcul sur des modèles de faible dimension.Cependant, quand le nombre de degrés de liberté augmente, on démontre que l’hyperréduction de modèle multidimensionnelle ne parvient pas à réduire suffisamment les coûts de calcul.
Published: 2015

30. Model selection with low complexity priors

Author: Vaiter, S., primary, Golbabaee, M., additional, Fadili, J., additional, and Peyre, G., additional
Published: 2015
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31. Calcul des Valeurs Propres Pour des Structures Lineaires par la Methode de Kuhn

Author: Delfour, M. C., primary, Peyre, G., additional, and Rideau, P., additional
Published: 1986
Full Text: View/download PDF

32. Sparse reconstruction from a limited projection number of the coronary artery tree in X-ray rotational imaging

Author: Hu, Y., primary, Jung, M., additional, Oukili, A., additional, Yang, G., additional, Nunes, J.-C., additional, Fehrenbach, J., additional, Peyre, G., additional, Bedossa, M., additional, Luo, L., additional, Toumoulin, C., additional, and Cohen, L. D., additional
Published: 2012
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33. Syntaxonomic revision and floristic characterization of the phytosociological alliances corresponding to subalpine and alpine grasslands of the Pyrenees and Cantabrian Mountains (classesCaricetea curvulae,Carici-Kobresietea, andFestuco-Seslerietea)

Author: Peyre, G., primary and Font, X., additional
Published: 2011
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34. MULTICRITERIA EVALUATION OF THE PATHOLOGICAL RESILIENCE OF SOIL-BASED PROTECTED CROPPING SYSTEMS

Author: Tchamitchian, M., primary, Collange, B., additional, Navarrete, M., additional, and Peyre, G., additional
Published: 2011
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35. Extraction of tubular structures over an orientation domain

Author: Pechaud, M., primary, Keriven, R., additional, and Peyre, G., additional
Published: 2009
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36. Discrete bandelets with geometric orthogonal filters

Author: Peyre, G., primary and Mallat, S., additional
Published: 2005
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37. On growth and formlets: Sparse multi-scale coding of planar shape.

Author: Oleskiw, T.D., Elder, J.H., and Peyre?, G.
Published: 2010
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38. Separation of traveling waves in cortical networks using optical imaging.

Author: Schmidt, N., Peyre?, G., Fre?gnac, Y., and Roland, P.
Published: 2010
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39. Image compression with anisotropic triangulations.

Author: Bougleux, S., Peyre?, G., and Cohen, L.D.
Published: 2009
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40. Best basis denoising with non-stationary wavelet packets.

Author: Ouarti, N. and Peyre, G.
Published: 2009
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41. Total variation projection with first order schemes.

Author: Fadili, J.M. and Peyre, G.
Published: 2009
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42. Challenging restricted isometry constants with greedy pursuit.

Author: Dossal, C., Peyre, G., and Fadili, J.
Published: 2009
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43. 3D shape matching by geodesic eccentricity.

Author: Ion, A., Artner, N.M., Peyre, G., Marmol, S.B.L., Kropatsch, W.G., and Cohen, L.
Published: 2008
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44. Landmark-Based Geodesic Computation for Heuristically Driven Path Planning.

Author: Peyre, G. and Cohen, L.D.
Published: 2006
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45. Surface segmentation using geodesic centroidal tesselation.

Author: Peyre, G. and Cohen, L.
Published: 2004
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46. Syntaxonomic revision and floristic characterization of the phytosociological alliances corresponding to subalpine and alpine grasslands of the Pyrenees and Cantabrian Mountains (classes Caricetea curvulae , Carici-Kobresietea , and Festuco-Seslerietea ).

Author: Peyre, G. and Font, X.
Subjects: *VEGETATION classification, *PLANT communities, *GRASSLANDS, *PLANT diversity, *BOTANY, *BIBLIOGRAPHICAL citations, *ENVIRONMENTAL sciences
Abstract: In this study, we made a numerical revision of the eight phytosociological alliances belonging to the classes Caricetea curvulae Br.-Bl. 1948, Carici rupestris-Kobresietea bellardii Ohba 1974, and Festuco-Seslerietea Barbéro & Bonin 1969. This analysis was designed to reveal the significant alliances corresponding to alpine and subalpine grasslands, review the associated syntaxonomical hierarchy, and establish the diagnostic floras of these alliances. The study area comprised the subalpine and alpine vegetation belts of the Pyrenees and the Cantabrian Mountains (northern Spain and southern France). We used 2259 floristic relevés, downloaded from the “Sistema de Información de la Vegetación Ibérica y Macaronésica” database, for statistical treatment. First, we classified the dataset, using the K-means clustering technique, so as to reveal a syntaxonomical structure. Second, we calculated the fidelity index Ochiai in all classification partitions. Finally, we compared the obtained lists with community descriptions from four bibliographical references. As a result, we could provide a diagnostic flora for every alliance. Therefore, we reconstructed seven of the eight alliances described. The numerical and bibliographical lists of characteristic species were similar for most syntaxa. Moreover, we proposed some new diagnostic species. Some alliances were considered more statistically robust than others. Finally, syntaxonomical repercussions have been suggested. [ABSTRACT FROM PUBLISHER]
Published: 2011
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47. [Methods of hypothalamo-hypophyseal portal blood collection]

Author: Guillaume, L., Peyre, G., Grino, M, Dutour, A., Ouafik, L'H., Conte-Devolx, C, Oliver, C., INSERM U 297 - Laboratoire de Neuroendocrinologie Expérimentale, and Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: MESH: Portal System, Blood Specimen Collection, Hypothalamic Hormones, MESH: Rats, Hypothalamus, MESH: Blood Specimen Collection, [SDV.CAN]Life Sciences [q-bio]/Cancer, MESH: Hypothalamus, MESH: Hypothalamic Hormones, Rats, Pituitary Hormones, Portal System, MESH: Pituitary Hormones, MESH: Pituitary Gland, Pituitary Gland, Animals, MESH: Animals
Abstract: International audience; It is possible to assay hypothalamic factors in hypophysial portal blood from several species. However, hypophysial portal blood collection must be performed after anesthesia and surgical stress which can both modify the regulation of hypothalamo-pituitary secretion. However, this method has allowed some progress in our knowledge of the hypothalamic control of pituitary secretion. The methodology, advantages and limits of hypophysial portal blood collection are briefly described in this review.
Published: 1987

48. sPlot – A new tool for global vegetation analyses

Author: Bruelheide H., Dengler J., Jiménez-Alfaro B., Purschke O., Hennekens S., Chytrý M., Pillar V., Jansen F., Kattge J., Sandel B., Aubin I., Biurrun I., Field R., Haider S., Jandt U., Lenoir J., Peet R., Peyre G., Sabatini F., Schmidt M., Schrodt F., Winter M., Aćić S., Agrillo E., Alvarez M., Ambarlı D., Angelini P., Apostolova I., Arfin Khan M., Arnst E., Attorre F., Baraloto C., Beckmann M., Berg C., Bergeron Y., Bergmeier E., Bjorkman A., Bondareva V., Borchardt P., Botta-Dukát Z., Boyle B., Breen A., Brisse H., Byun C., Cabido M., Casella L., Cayuela L., Černý T., Chepinoga V., Csiky J., Curran M., Ćušterevska R., Dajić Stevanović Z., De Bie E., de Ruffray P., De Sanctis M., Dimopoulos P., Dressler S., Ejrnæs R., El-Sheikh M., Enquist B., Ewald J., Fagúndez J., Finckh M., Font X., Forey E., Fotiadis G., García-Mijangos I., de Gasper A., Golub V., Gutierrez A., Hatim M., He T., Higuchi P., Holubová D., Hölzel N., Homeier J., Indreica A., Işık Gürsoy D., Jansen S., Janssen J., Jedrzejek B., Jiroušek M., Jürgens N., Kącki Z., Kavgacı A., Kearsley E., Kessler M., Knollová I., Kolomiychuk V., Korolyuk A., Kozhevnikova M., Kozub Ł., Krstonošić D., Kühl H., Kühn I., Kuzemko A., Küzmič F., Landucci F., Lee M., Bruelheide H., Dengler J., Jiménez-Alfaro B., Purschke O., Hennekens S., Chytrý M., Pillar V., Jansen F., Kattge J., Sandel B., Aubin I., Biurrun I., Field R., Haider S., Jandt U., Lenoir J., Peet R., Peyre G., Sabatini F., Schmidt M., Schrodt F., Winter M., Aćić S., Agrillo E., Alvarez M., Ambarlı D., Angelini P., Apostolova I., Arfin Khan M., Arnst E., Attorre F., Baraloto C., Beckmann M., Berg C., Bergeron Y., Bergmeier E., Bjorkman A., Bondareva V., Borchardt P., Botta-Dukát Z., Boyle B., Breen A., Brisse H., Byun C., Cabido M., Casella L., Cayuela L., Černý T., Chepinoga V., Csiky J., Curran M., Ćušterevska R., Dajić Stevanović Z., De Bie E., de Ruffray P., De Sanctis M., Dimopoulos P., Dressler S., Ejrnæs R., El-Sheikh M., Enquist B., Ewald J., Fagúndez J., Finckh M., Font X., Forey E., Fotiadis G., García-Mijangos I., de Gasper A., Golub V., Gutierrez A., Hatim M., He T., Higuchi P., Holubová D., Hölzel N., Homeier J., Indreica A., Işık Gürsoy D., Jansen S., Janssen J., Jedrzejek B., Jiroušek M., Jürgens N., Kącki Z., Kavgacı A., Kearsley E., Kessler M., Knollová I., Kolomiychuk V., Korolyuk A., Kozhevnikova M., Kozub Ł., Krstonošić D., Kühl H., Kühn I., Kuzemko A., Küzmič F., Landucci F., and Lee M.
Abstract: © 2019 International Association for Vegetation Science Aims: Vegetation-plot records provide information on the presence and cover or abundance of plants co-occurring in the same community. Vegetation-plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community-weighted means and variances of traits using gap-filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community-weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.

49. Environmental and Biogeographic Drivers behind Alpine Plant Thermal Tolerance and Genetic Variation

Author: Danzey, LM, Briceño, VF, Cook, AM, Nicotra, AB, Peyre, G, Rossetto, M, Yap, J-YS, Leigh, A, Danzey, LM, Briceño, VF, Cook, AM, Nicotra, AB, Peyre, G, Rossetto, M, Yap, J-YS, and Leigh, A
Abstract: In alpine ecosystems, elevation broadly functions as a steep thermal gradient, with plant communities exposed to regular fluctuations in hot and cold temperatures. These conditions lead to selective filtering, potentially contributing to species-level variation in thermal tolerance and population-level genetic divergence. Few studies have explored the breadth of alpine plant thermal tolerances across a thermal gradient or the underlying genetic variation thereof. We measured photosystem heat (Tcrit-hot) and cold (Tcrit-cold) thresholds of ten Australian alpine species across elevation gradients and characterised their neutral genetic variation. To reveal the biogeographical drivers of present-day genetic signatures, we also reconstructed temporal changes in habitat suitability across potential distributional ranges. We found intraspecific variation in thermal thresholds, but this was not associated with elevation, nor underpinned by genetic differentiation on a local scale. Instead, regional population differentiation and considerable homozygosity within populations may, in part, be driven by distributional contractions, long-term persistence, and migrations following habitat suitability. Our habitat suitability models suggest that cool-climate-distributed alpine plants may be threatened by a warming climate. Yet, the observed wide thermal tolerances did not reflect this vulnerability. Conservation efforts should seek to understand variations in species-level thermal tolerance across alpine microclimates.

50. Influence of endogenous growth hormone-releasing factor (GRF) on the secretion of GH during the perinatal period in the rat

Author: Guillaume, V., primary, Boudouresque, F., additional, Grino, M., additional, Dutour, A., additional, Peyre, G., additional, Tonon, M.C., additional, Vaudry, H., additional, Rougeot, C., additional, Conte-Devolx, B., additional, and Oliver, C., additional
Published: 1986
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