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171 results on '"Cayuela, L"'

11. Rising testicular cancer incidence in Spain despite declining mortality: an age-period-cohort analysis

Author

Universidad de Sevilla. Departamento de Medicina, Cayuela, L., Cabrera Fernández, S., Pereyra-Rodríguez, José-Juan, Hernández-Rodríguez, J.C., Cayuela, A., Universidad de Sevilla. Departamento de Medicina, Cayuela, L., Cabrera Fernández, S., Pereyra-Rodríguez, José-Juan, Hernández-Rodríguez, J.C., and Cayuela, A.

Abstract

Background: Testicular cancer, primarily affecting young men, has seen an alarming rise globally. This study delves into incidence and mortality trends in Spain from 1990 to 2019 using the Global Burden of Disease (GBD) database and the Age-Period-Cohort (A-P-C) model. Methods: We analyzed GBD data on testicular cancer cases and deaths in Spain, calculating age-standardized rates (ASIR and ASMR) and employing Joinpoint regression to identify significant shifts. The A-P-C model further dissected the effects of age, period, and birth cohort on these trends. Results: A striking doubling in testicular cancer incidence was observed, from 3.09 to 5.40 per 100,000 men (1.9% annual increase), while mortality rates remained stable and even decreased in younger age groups (0.34 to 0.26 per 100,000, 0.8% annual decrease). Joinpoint analysis revealed four distinct periods of increasing incidence, with a recent slowdown. The A-P-C model highlighted a consistent rise in incidence risk with each successive generation born after 1935, contrasting with a progressive decline in mortality risk across cohorts, particularly marked for those born since the 1960s. Conclusion: While mortality rates are encouraging, Spain reflects the global trend of escalating testicular cancer incidence. The A-P-C analysis suggests a generational influence, but the underlying causes remain elusive. Further research is crucial to understand these trends and implement effective prevention strategies to combat this growing health concern., Objetivo: Actualizar la información sobre la incidencia y mortalidad por cáncer testicular en Espa˜na entre 1990 y 2019. Métodos: Se analizaron datos del Global Burden of Disease (GBD) para calcular las tasas de inci- dencia y mortalidad estandarizadas por edad (TIEE y TMEE). Se utilizaron la regresión Joinpoint y el modelo Edad-Periodo-Cohorte (E-P-C) para analizar las tendencias y los efectos de la edad, el periodo y la cohorte de nacimiento. Resultados: Se observó una sorprendente duplicación de la incidencia de cáncer testicular, de 3,09 a 5,40 por 100.000 hombres (aumento anual del 1,9%), mientras que las tasas de mortalidad se mantuvieron estables e incluso disminuyeron en los grupos de edad más jóvenes (de 0,34 a 0,26 por 100.000, disminución anual del 0,8%). El análisis Joinpoint reveló cuatro periodos distintos de aumento de la incidencia, con una ralentización reciente. El modelo E-P-C puso de manifiesto un aumento constante del riesgo de incidencia con cada generación sucesiva nacida después de 1935, que contrasta con un descenso progresivo del riesgo de mortalidad en todas las cohortes, especialmente marcado para los nacidos a partir de los a˜nos sesenta. Conclusiones: La incidencia del cáncer testicular aumenta en Espa˜na, mientras que la mortal- idad se mantiene estable o incluso disminuye. Existe un efecto generacional en la incidencia, con mayor riesgo para las generaciones más jóvenes. Se necesitan más investigaciones para comprender las causas del aumento de la incidencia y desarrollar estrategias de prevención.

Published
2024

20. Global patterns of vascular plant alpha diversity

Author

Sabatini, F.M., Jiménez-Alfaro, B., Jandt, U., Chytrý, M., Field, R., Kessler, M., Lenoir, J., Schrodt, F., Wiser, S.K., Arfin Khan, M.A.S., Attorre, F. Cayuela, L., De Sanctis, M., Dengler, J., Haider, S., Hatim, M.Z., Indreica, A., Jansen, F., Pauchard, A., Peet, R.K., Petřik, P., Pillar, V.D., Sandel, B., Schmidt, M., Tang, Z., Bodegom, P.M. van, Vassilev, K., Violle, C., Alvarez-Davilla, E., Davidar, P., Dolezal, J., Hérault, B., Galán-de-Mera, A., Jiménez, J., Kambach, S., Kepfer-Rojas, S., Kreft, H., Lezama, F., Linares-Palomino, R., Mendoza, A.M., N’Dja, J.K., Phillips, O.L., Rivas-Torres, G., Sklenář, P., Speziale, K., Strohbach, B.J., Martínez, R.V., Wang, H., Wesche, K., and Bruelheide, H.

Abstract

Global patterns of regional (gamma) plant diversity are relatively well known, but whether these patterns hold for local communities, and the dependence on spatial grain, remain controversial. Using data on 170,272 georeferenced local plant assemblages, we created global maps of alpha diversity (local species richness) for vascular plants at three different spatial grains, for forests and non-forests. We show that alpha diversity is consistently high across grains in some regions (for example, Andean-Amazonian foothills), but regional ‘scaling anomalies’ (deviations from the positive correlation) exist elsewhere, particularly in Eurasian temperate forests with disproportionally higher fine-grained richness and many African tropical forests with disproportionally higher coarse-grained richness. The influence of different climatic, topographic and biogeographical variables on alpha diversity also varies across grains. Our multi-grain maps return a nuanced understanding of vascular plant biodiversity patterns that complements classic maps of biodiversity hotspots and will improve predictions of global change effects on biodiversity.

Published
2022

23. The high mobility group protein HMG20A cooperates with the histone reader PHF14 to modulate TGF beta and Hippo pathways

Author

Gomez-Marin, E, Posavec-Marjanovic, M, Zarzuela, L, Basurto-Cayuela, L, Guerrero-Martinez, JA, Arribas, G, Yerbes, R, Ceballos-Chavez, M, Rodriguez-Paredes, M, Tome, M, Duran, RV, Buschbeck, M, and Reyes, JC

Abstract

High mobility group (HMG) proteins are chromatin regulators with essential functions in development, cell differentiation and cell proliferation. The protein HMG20A is predicted by the AlphaFold2 software to contain three distinct structural elements, which we have functionally characterized: i) an amino-terminal, intrinsically disordered domain with transactivation activity; ii) an HMG box with higher binding affinity for double-stranded, four-way-junction DNA than for linear DNA; and iii) a long coiled-coil domain. Our proteomic study followed by a deletion analysis and structural modeling demonstrates that HMG20A forms a complex with the histone reader PHF14, via the establishment of a two-stranded alpha-helical coiled-coil structure. siRNA-mediated knockdown of either PHF14 or HMG20A in MDA-MB-231 cells causes similar defects in cell migration, invasion and homotypic cell-cell adhesion ability, but neither affects proliferation. Transcriptomic analyses demonstrate that PHF14 and HMG20A share a large subset of targets. We show that the PHF14-HMG20A complex modulates the Hippo pathway through a direct interaction with the TEAD1 transcription factor. PHF14 or HMG20A deficiency increases epithelial markers, including E-cadherin and the epithelial master regulator TP63 and impaired normal TGF beta-trigged epithelial-to-mesenchymal transition. Taken together, these data indicate that PHF14 and HMG20A cooperate in regulating several pathways involved in epithelial-mesenchymal plasticity.

Published
2022

25. 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

26. 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

27. Climate reverses directionality in the richness-abundance relationship across the World's main forest biomes

Author

Madrigal-Gonzalez, J, Calatayud, J, Ballesteros-Canovas, JA, Escudero, A, Cayuela, L, Rueda, M, Ruiz-Benito, P, Herrero, A, Aponte, C, Sagardia, R, Plumptre, AJ, Dupire, S, Espinosa, C, Tutubalina, O, Myint, M, Pataro, L, Lopez-Saez, J, Macia, MJ, Abegg, M, Zavala, MA, Quesada-Roman, A, Vega-Araya, M, Golubeva, E, Timokhina, Y, Stoffel, M, Madrigal-Gonzalez, J, Calatayud, J, Ballesteros-Canovas, JA, Escudero, A, Cayuela, L, Rueda, M, Ruiz-Benito, P, Herrero, A, Aponte, C, Sagardia, R, Plumptre, AJ, Dupire, S, Espinosa, C, Tutubalina, O, Myint, M, Pataro, L, Lopez-Saez, J, Macia, MJ, Abegg, M, Zavala, MA, Quesada-Roman, A, Vega-Araya, M, Golubeva, E, Timokhina, Y, and Stoffel, M

Abstract

More tree species can increase the carbon storage capacity of forests (here referred to as the more species hypothesis) through increased tree productivity and tree abundance resulting from complementarity, but they can also be the consequence of increased tree abundance through increased available energy (more individuals hypothesis). To test these two contrasting hypotheses, we analyse the most plausible pathways in the richness-abundance relationship and its stability along global climatic gradients. We show that positive effect of species richness on tree abundance only prevails in eight of the twenty-three forest regions considered in this study. In the other forest regions, any benefit from having more species is just as likely (9 regions) or even less likely (6 regions) than the effects of having more individuals. We demonstrate that diversity effects prevail in the most productive environments, and abundance effects become dominant towards the most limiting conditions. These findings can contribute to refining cost-effective mitigation strategies based on fostering carbon storage through increased tree diversity. Specifically, in less productive environments, mitigation measures should promote abundance of locally adapted and stress tolerant tree species instead of increasing species richness.

Published
2020

28. Evolución espaciotemporal del riesgo de mortalidad por suicidio en la españa peninsular (1999-2018)

Author

Cayuela, L., Cerame del Campo, Álvaro, López-Sánchez, Emilio José, Rodríguez Domínguez, Susana, Cayuela Domínguez, Aurelio, Cayuela, L., Cerame del Campo, Álvaro, López-Sánchez, Emilio José, Rodríguez Domínguez, Susana, and Cayuela Domínguez, Aurelio

Abstract

Background: Suicide is a major health problem, whose underlying reasons and spatial-temporal risk patterns are not well understood. This ecological study aims to describe and characterize the spatiotemporal patterns of suicide in mainland Spain during the period 1999-2018. Methods: Data on mortality from suicide and population at the provincial level were obtained from the National Institute of Statistics. For each year, province, and sex, we analysed the smoothed relative risks (RRs) of suicide mortality using Bayesian hierarchical models. Results: During the study period there were 63,307 suicide deaths, 47,849 in men and 15,458 in women.The risk of suicide throughout the study period is above the national average for both sexes in the provinces of Granada, La Coruña, Lugo and Asturias. In men, this also happens in Jaen. Men in Madrid and Cantabria and women in Madrid, Toledo and Badajoz showed RRs less than 1 (PP<0.05) during the 20 years of the study. The posterior probabilities map indicates that most of the provinces in the Northwest zone (Pontevedra, La Coruña, Lugo and Asturias in both sexes and Leon and Orense in women) and Southeast (Jaen, Malaga, Granada, Almería in both sexes, and Cordoba and Ciudad Real in men) present significantly high risks (posterior probabilities greater than 0.95). Conclusions: Our findings, identifying areas where to direct programs or strategies to reduce or eliminate the risk of mortality by suicide, show the importance of this type of analysis in addressing public health problems., Introducción: El suicidio es un importante problema de salud, cuyas razones subyacentes y patrones de riesgo espaciotemporales no se conocen bien. Este estudio ecológico tuvo como objetivo describir y caracterizar los patrones espaciotemporales del suicidio en la España peninsular durante el período 1999-2018. Métodos: Los datos de mortalidad por suicidios y de población a nivel provincial se obtuvieron del Instituto Nacional de Estadística. Para cada año, provincia y sexo, analizamos los riesgos relativos suavizados (RRs) de mortalidad por suicidio utilizando modelos jerárquicos bayesianos. Resultados: Durante el período de estudio se produjeron 63.307 muertes por suicidio, 47.849 en hombres y 15.458 en mujeres. El riesgo de suicidio durante todo el período de estudio estuvo por encima del promedio nacional para ambos sexos en las provincias de Granada, La Coruña, Lugo y Asturias. En los hombres, esto también ocurrió en Jaén. Los hombres en Madrid y Cantabria, y las mujeres en Madrid, Toledo y Badajoz, mostraron RRs menores de 1 (PP<0,05) durante los 20 años del estudio. El mapa de probabilidades posteriores indica que la mayoría de las provincias en la zona noroeste (Pontevedra, La Coruña, Lugo y Asturias en ambos sexos y León y Orense en mujeres) y el sudeste (Jaén, Málaga, Granada, Almería en ambos sexos, y Córdoba y Ciudad Real en hombres) presentaron riesgos significativamente altos (probabilidades posteriores mayores de 0,95). Conclusiones: Nuestros hallazgos, al identificar áreas donde dirigir programas o estrategias para reducir o eliminar el riesgo de mortalidad por suicidio, muestran la importancia de este tipo de análisis para abordar los problemas de salud pública relacionados con este fenómeno.

Published
2020

32. Plant diversity in highly fragmented forest landscapes in Mexico and Chile: implications for conservation.

Author

Rey-Benayas, J. M., primary, Cayuela, L., additional, González-Espinosa, M., additional, Echeverría, C., additional, Manson, R. H., additional, Williams-Linera, G., additional, Castillo, R. F. del, additional, Ramírez-Marcial, N., additional, Muñiz-Castro, M. A., additional, Blanco-Macías, A., additional, Lara, A., additional, and Newton, A. C., additional

Published
2007
Full Text
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33. Future scenarios for tropical montane and south temperate forest biodiversity in Latin America.

Author

Miles, L., primary, Newton, A. C., additional, Alvarez-Aquino, C., additional, Armesto, J. J., additional, Castillo, R. F. del, additional, Cayuela, L., additional, Echeverría, C., additional, González-Espinosa, M., additional, Lara, A., additional, López-Barrera, F., additional, Manson, R. H., additional, Montoya-Gómez, G., additional, Muñiz-Castro, M. A., additional, Núñez-Ávila, M. C., additional, Pedraza, R. A., additional, Rey-Benayas, J. M., additional, Rovere, A. E., additional, Rüger, N., additional, Smith-Ramírez, C., additional, Souto, C., additional, and Williams-Linera, G., additional

Published
2007
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35. A Prognostic Enrichment Strategy for Selection of Patients With Acute Respiratory Distress Syndrome in Clinical Trials

Author

Villar J, Ambros A, Mosteiro F, Martinez D, Fernandez L, Ferrando C, Carriedo D, Soler J, Parrilla D, Hernandez M, Andaluz-Ojeda D, Anon J, Vidal A, Gonzalez-Higueras E, Martin-Rodriguez C, Diaz-Lamas A, Blanco J, Belda J, Diaz-Dominguez F, Rico-Feijoo J, Martin-Delgado C, Romera M, Fernandez R, Gonzalez-Martin J, del Campo R, Arrojo R, Conesa-Cayuela L, Muriel A, Aldecoa C, Rico J, Martin-Alfonso S, Dominguez A, Gonzalez-Luengo R, Soro M, Gutierrez A, Aguilar G, Montiel R, Peinado E, Perez-Mendez L, Civantos B, Capilla L, Robaglia D, Perez C, Suarez-Sipmann F, Andaluz D, Nogales L, Parra L, Solano R, Bruscas M, Fernandez M, Merayo E, Martinez-Jimenez C, Dominguez-Antelo C, Mora-Ordonez J, Tarancon C, Prieto F, Chico M, Prieto I, Toral D, Corcoles V, Saralegui I, Tallet A, Kacmarek R, and Spanish Initiative Epidemiology St

Subjects
decision tree analysis, outcome, diagnostic accuracy, decision-making, acute respiratory distress syndrome
Abstract

Objectives: Incomplete or ambiguous evidence for identifying high-risk patients with acute respiratory distress syndrome for enrollment into randomized controlled trials has come at the cost of an unreasonable number of negative trials. We examined a set of selected variables early in acute respiratory distress syndrome to determine accurate prognostic predictors for selecting high-risk patients for randomized controlled trials. Design: A training and testing study using a secondary analysis of data from four prospective, multicenter, observational studies. Setting: A network of multidisciplinary ICUs. Patients: We studied 1,200 patients with moderate-to-severe acute respiratory distress syndrome managed with lung-protective ventilation. Interventions: None. Measurements and Main Results: We evaluated different thresholds for patient's age, Pao 2 /Fio 2, plateau pressure, and number of extrapulmonary organ failures to predict ICU outcome at 24 hours of acute respiratory distress syndrome diagnosis. We generated 1,000 random scenarios as training (n = 900, 75% of population) and testing (n = 300, 25% of population) datasets and averaged the logistic coefficients for each scenario. Thresholds for age (< 50, 50-70, > 70 yr), Pao 2 /Fio 2 (= 100, 101-150, > 150 mm Hg), plateau pressure (< 29, 29-30, > 30 cm H2O), and number of extrapulmonary organ failure (< 2, 2, > 2) stratified accurately acute respiratory distress syndrome patients into categories of risk. The model that included all four variables proved best to identify patients with the highest or lowest risk of death (area under the receiver operating characteristic curve, 0.86; 95% CI, 0.84-0.88). Decision tree analyses confirmed the accuracy and robustness of this enrichment model. Conclusions: Combined thresholds for patient's age, Pao 2 / Fio 2, plateau pressure, and extrapulmonary organ failure provides prognostic enrichment accuracy for stratifying and selecting acute respiratory distress syndrome patients for randomized controlled trials.

Published
2019

36. 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

37. Crop pests and predators exhibit inconsistent responses to surrounding landscape composition

Author

Karp, DS, Chaplin-Kramer, R, Meehan, TD, Martin, EA, DeClerck, F, Grab, H, Gratton, C, Hunt, L, Larsen, AE, Martinez-Salinas, A, O'Rourke, ME, Rusch, A, Poveda, K, Jonsson, M, Rosenheim, JA, Schellhorn, NA, Tscharntke, T, Wratten, SD, Zhang, W, Iverson, AL, Adler, LS, Albrecht, M, Alignier, A, Angelella, GM, Anjum, MZ, Avelino, J, Batary, P, Baveco, JM, Bianchi, FJJA, Birkhofer, K, Bohnenblust, EW, Bommarco, R, Brewer, MJ, Caballero-Lopez, B, Carriere, Y, Carvalheiro, LG, Cayuela, L, Centrella, M, Cetkovic, A, Henri, DC, Chabert, A, Costamagna, AC, De la Mora, A, de Kraker, J, Desneux, N, Diehl, E, Diekoetter, T, Dormann, CF, Eckberg, JO, Entling, MH, Fiedler, D, Franck, P, van Veen, FJF, Frank, T, Gagic, V, Garratt, MPD, Getachew, A, Gonthier, DJ, Goodell, PB, Graziosi, I, Groves, RL, Gurr, GM, Hajian-Forooshani, Z, Heimpel, GE, Herrmann, JD, Huseth, AS, Inclan, DJ, Ingrao, AJ, Iv, P, Jacot, K, Johnson, GA, Jones, L, Kaiser, M, Kaser, JM, Keasar, T, Kim, TN, Kishinevsky, M, Landis, DA, Lavandero, B, Lavigne, C, Le Ralec, A, Lemessa, D, Letourneau, DK, Liere, H, Lu, Y, Lubin, Y, Luttermoser, T, Maas, B, Mace, K, Madeira, F, Mader, V, Cortesero, AM, Marini, L, Martinez, E, Martinson, HM, Menozzi, P, Mitchell, MGE, Miyashita, T, Molina, GAR, Molina-Montenegro, MA, O'Neal, ME, Opatovsky, I, Ortiz-Martinez, S, Nash, M, Ostman, O, Ouin, A, Pak, D, Paredes, D, Parsa, S, Parry, H, Perez-Alvarez, R, Perovic, DJ, Peterson, JA, Petit, S, Philpott, SM, Plantegenest, M, Plecas, M, Pluess, T, Pons, X, Potts, SG, Pywell, RF, Ragsdale, DW, Rand, TA, Raymond, L, Ricci, B, Sargent, C, Sarthou, J-P, Saulais, J, Schackermann, J, Schmidt, NP, Schneider, G, Schuepp, C, Sivakoff, FS, Smith, HG, Whitney, KS, Stutz, S, Szendrei, Z, Takada, MB, Taki, H, Tamburini, G, Thomson, LJ, Tricault, Y, Tsafack, N, Tschumi, M, Valantin-Morison, M, Mai, VT, van der Werf, W, Vierling, KT, Werling, BP, Wickens, JB, Wickens, VJ, Woodcock, BA, Wyckhuys, K, Xiao, H, Yasuda, M, Yoshioka, A, Zou, Y, Karp, DS, Chaplin-Kramer, R, Meehan, TD, Martin, EA, DeClerck, F, Grab, H, Gratton, C, Hunt, L, Larsen, AE, Martinez-Salinas, A, O'Rourke, ME, Rusch, A, Poveda, K, Jonsson, M, Rosenheim, JA, Schellhorn, NA, Tscharntke, T, Wratten, SD, Zhang, W, Iverson, AL, Adler, LS, Albrecht, M, Alignier, A, Angelella, GM, Anjum, MZ, Avelino, J, Batary, P, Baveco, JM, Bianchi, FJJA, Birkhofer, K, Bohnenblust, EW, Bommarco, R, Brewer, MJ, Caballero-Lopez, B, Carriere, Y, Carvalheiro, LG, Cayuela, L, Centrella, M, Cetkovic, A, Henri, DC, Chabert, A, Costamagna, AC, De la Mora, A, de Kraker, J, Desneux, N, Diehl, E, Diekoetter, T, Dormann, CF, Eckberg, JO, Entling, MH, Fiedler, D, Franck, P, van Veen, FJF, Frank, T, Gagic, V, Garratt, MPD, Getachew, A, Gonthier, DJ, Goodell, PB, Graziosi, I, Groves, RL, Gurr, GM, Hajian-Forooshani, Z, Heimpel, GE, Herrmann, JD, Huseth, AS, Inclan, DJ, Ingrao, AJ, Iv, P, Jacot, K, Johnson, GA, Jones, L, Kaiser, M, Kaser, JM, Keasar, T, Kim, TN, Kishinevsky, M, Landis, DA, Lavandero, B, Lavigne, C, Le Ralec, A, Lemessa, D, Letourneau, DK, Liere, H, Lu, Y, Lubin, Y, Luttermoser, T, Maas, B, Mace, K, Madeira, F, Mader, V, Cortesero, AM, Marini, L, Martinez, E, Martinson, HM, Menozzi, P, Mitchell, MGE, Miyashita, T, Molina, GAR, Molina-Montenegro, MA, O'Neal, ME, Opatovsky, I, Ortiz-Martinez, S, Nash, M, Ostman, O, Ouin, A, Pak, D, Paredes, D, Parsa, S, Parry, H, Perez-Alvarez, R, Perovic, DJ, Peterson, JA, Petit, S, Philpott, SM, Plantegenest, M, Plecas, M, Pluess, T, Pons, X, Potts, SG, Pywell, RF, Ragsdale, DW, Rand, TA, Raymond, L, Ricci, B, Sargent, C, Sarthou, J-P, Saulais, J, Schackermann, J, Schmidt, NP, Schneider, G, Schuepp, C, Sivakoff, FS, Smith, HG, Whitney, KS, Stutz, S, Szendrei, Z, Takada, MB, Taki, H, Tamburini, G, Thomson, LJ, Tricault, Y, Tsafack, N, Tschumi, M, Valantin-Morison, M, Mai, VT, van der Werf, W, Vierling, KT, Werling, BP, Wickens, JB, Wickens, VJ, Woodcock, BA, Wyckhuys, K, Xiao, H, Yasuda, M, Yoshioka, A, and Zou, Y

Abstract

The idea that noncrop habitat enhances pest control and represents a win-win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win-win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies.

Published
2018

38. Global trait:environment relationships of plant communities

Author

Bruelheide, H. (Helge), Dengler, J. (Juergen), Purschke, O. (Oliver), Lenoir, J. (Jonathan), Jimenez-Alfaro, B. (Borja), Hennekens, S. M. (Stephan M.), Botta-Dukat, Z. (Zoltan), Chytry, M. (Milan), Field, R. (Richard), Jansen, F. (Florian), Kattge, J. (Jens), Pillar, V. D. (Valerio D.), Schrodt, F. (Franziska), Mahecha, M. D. (Miguel D.), Peet, R. K. (Robert K.), Sandel, B. (Brody), van Bodegom, P. (Peter), Altman, J. (Jan), Alvarez-Davila, E. (Esteban), Khan, M. A. (Mohammed A. S. Arfin), Attorre, F. (Fabio), Aubin, I. (Isabelle), Baraloto, C. (Christopher), Barroso, J. G. (Jorcely G.), Bauters, M. (Marijn), Bergmeier, E. (Erwin), Biurrun, I. (Idoia), Bjorkman, A. D. (Anne D.), Blonder, B. (Benjamin), Carni, A. (Andraz), Cayuela, L. (Luis), Cerny, T. (Tomas), Cornelissen, J. H. (J. Hans C.), Craven, D. (Dylan), Dainese, M. (Matteo), Derroire, G. (Geraldine), De Sanctis, M. (Michele), Diaz, S. (Sandra), Dolezal, J. (Jiri), Farfan-Rios, W. (William), Feldpausch, T. R. (Ted R.), Fenton, N. J. (Nicole J.), Garnier, E. (Eric), Guerin, G. R. (Greg R.), Gutierrez, A. G. (Alvaro G.), Haider, S. (Sylvia), Hattab, T. (Tarek), Henry, G. (Greg), Herault, B. (Bruno), Higuchi, P. (Pedro), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Jentsch, A. (Anke), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Karger, D. N. (Dirk N.), Kessler, M. (Michael), Kleyer, M. (Michael), Knollova, I. (Ilona), Korolyuk, A. Y. (Andrey Y.), Kuehn, I. (Ingolf), Laughlin, D. C. (Daniel C.), Lens, F. (Frederic), Loos, J. (Jacqueline), Louault, F. (Frederique), Lyubenova, M. I. (Mariyana, I), Malhi, Y. (Yadvinder), Marceno, C. (Corrado), Mencuccini, M. (Maurizio), Mueller, J. V. (Jonas, V), Munzinger, J. (Jerome), Myers-Smith, I. H. (Isla H.), Neill, D. A. (David A.), Niinemets, U. (Ulo), Orwin, K. H. (Kate H.), Ozinga, W. A. (Wim A.), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Petrik, P. (Petr), Phillips, O. L. (Oliver L.), Partel, M. (Meelis), Reich, P. B. (Peter B.), Roemermann, C. (Christine), Rodrigues, A. V. (Arthur, V), Sabatini, F. M. (Francesco Maria), Sardans, J. (Jordi), Schmidt, M. (Marco), Seidler, G. (Gunnar), Silva Espejo, J. E. (Javier Eduardo), Silveira, M. (Marcos), Smyth, A. (Anita), Sporbert, M. (Maria), Svenning, J.-C. (Jens-Christian), Tang, Z. (Zhiyao), Thomas, R. (Raquel), Tsiripidis, I. (Ioannis), Vassilev, K. (Kiril), Violle, C. (Cyrille), Virtanen, R. (Risto), Weiher, E. (Evan), Welk, E. (Erik), Wesche, K. (Karsten), Winter, M. (Marten), Wirth, C. (Christian), Jandt, U. (Ute), Bruelheide, H. (Helge), Dengler, J. (Juergen), Purschke, O. (Oliver), Lenoir, J. (Jonathan), Jimenez-Alfaro, B. (Borja), Hennekens, S. M. (Stephan M.), Botta-Dukat, Z. (Zoltan), Chytry, M. (Milan), Field, R. (Richard), Jansen, F. (Florian), Kattge, J. (Jens), Pillar, V. D. (Valerio D.), Schrodt, F. (Franziska), Mahecha, M. D. (Miguel D.), Peet, R. K. (Robert K.), Sandel, B. (Brody), van Bodegom, P. (Peter), Altman, J. (Jan), Alvarez-Davila, E. (Esteban), Khan, M. A. (Mohammed A. S. Arfin), Attorre, F. (Fabio), Aubin, I. (Isabelle), Baraloto, C. (Christopher), Barroso, J. G. (Jorcely G.), Bauters, M. (Marijn), Bergmeier, E. (Erwin), Biurrun, I. (Idoia), Bjorkman, A. D. (Anne D.), Blonder, B. (Benjamin), Carni, A. (Andraz), Cayuela, L. (Luis), Cerny, T. (Tomas), Cornelissen, J. H. (J. Hans C.), Craven, D. (Dylan), Dainese, M. (Matteo), Derroire, G. (Geraldine), De Sanctis, M. (Michele), Diaz, S. (Sandra), Dolezal, J. (Jiri), Farfan-Rios, W. (William), Feldpausch, T. R. (Ted R.), Fenton, N. J. (Nicole J.), Garnier, E. (Eric), Guerin, G. R. (Greg R.), Gutierrez, A. G. (Alvaro G.), Haider, S. (Sylvia), Hattab, T. (Tarek), Henry, G. (Greg), Herault, B. (Bruno), Higuchi, P. (Pedro), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Jentsch, A. (Anke), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Karger, D. N. (Dirk N.), Kessler, M. (Michael), Kleyer, M. (Michael), Knollova, I. (Ilona), Korolyuk, A. Y. (Andrey Y.), Kuehn, I. (Ingolf), Laughlin, D. C. (Daniel C.), Lens, F. (Frederic), Loos, J. (Jacqueline), Louault, F. (Frederique), Lyubenova, M. I. (Mariyana, I), Malhi, Y. (Yadvinder), Marceno, C. (Corrado), Mencuccini, M. (Maurizio), Mueller, J. V. (Jonas, V), Munzinger, J. (Jerome), Myers-Smith, I. H. (Isla H.), Neill, D. A. (David A.), Niinemets, U. (Ulo), Orwin, K. H. (Kate H.), Ozinga, W. A. (Wim A.), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Petrik, P. (Petr), Phillips, O. L. (Oliver L.), Partel, M. (Meelis), Reich, P. B. (Peter B.), Roemermann, C. (Christine), Rodrigues, A. V. (Arthur, V), Sabatini, F. M. (Francesco Maria), Sardans, J. (Jordi), Schmidt, M. (Marco), Seidler, G. (Gunnar), Silva Espejo, J. E. (Javier Eduardo), Silveira, M. (Marcos), Smyth, A. (Anita), Sporbert, M. (Maria), Svenning, J.-C. (Jens-Christian), Tang, Z. (Zhiyao), Thomas, R. (Raquel), Tsiripidis, I. (Ioannis), Vassilev, K. (Kiril), Violle, C. (Cyrille), Virtanen, R. (Risto), Weiher, E. (Evan), Welk, E. (Erik), Wesche, K. (Karsten), Winter, M. (Marten), Wirth, C. (Christian), and Jandt, U. (Ute)

Abstract

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

Published
2018

39. Global trait–environment relationships of plant communities

Author

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

Abstract

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

Published
2018

41. Forest biomass density across large climate gradients in northern South America is related to water availability but not with temperature

Author

Álvarez-Dávila, E, Cayuela, L, González-Caro, S, Aldana, AM, Stevenson, PR, Phillips, OLB, Cogollo, A, Peñuela, MC, von Hildebrand, P, Jiménez, E, Melo, O, Londoño-Vega, AC, Mendoza, I, Velasquez, O, Fernández, F, Serna, M, Velázquez-Rua, C, Benitez, D, and Rey-Benayas, JM

Subjects
Atmospheric Science, Ecological Metrics, Forest Ecology, Climate Change, Biomass (Ecology), lcsh:Medicine, Plant Science, Forests, Ecosystems, Geographical locations, Trees, Natural Resources, Biomass, lcsh:Science, Climatology, Tropical Climate, Ecology, Plant Anatomy, lcsh:R, Ecology and Environmental Sciences, Temperature, Organisms, Water, Biology and Life Sciences, Models, Theoretical, South America, Plants, Terrestrial Environments, Wood, Water Resources, Earth Sciences, lcsh:Q, People and places, Research Article
Abstract

Understanding and predicting the likely response of ecosystems to climate change are crucial challenges for ecology and for conservation biology. Nowhere is this challenge greater than in the tropics as these forests store more than half the total atmospheric carbon stock in their biomass. Biomass is determined by the balance between biomass inputs (i.e., growth) and outputs (mortality). We can expect therefore that conditions that favor high growth rates, such as abundant water supply, warmth, and nutrient-rich soils will tend to correlate with high biomass stocks. Our main objective is to describe the patterns of above ground biomass (AGB) stocks across major tropical forests across climatic gradients in Northwestern South America. We gathered data from 200 plots across the region, at elevations ranging between 0 to 3400 m. We estimated AGB based on allometric equations and values for stem density, basal area, and wood density weighted by basal area at the plot-level. We used two groups of climatic variables, namely mean annual temperature and actual evapotranspiration as surrogates of environmental energy, and annual precipitation, precipitation seasonality, and water availability as surrogates of water availability. We found that AGB is more closely related to water availability variables than to energy variables. In northwest South America, water availability influences carbon stocks principally by determining stand structure, i.e. basal area. When water deficits increase in tropical forests we can expect negative impact on biomass and hence carbon storage.

Published
2016

42. Analysis of cerebrovascular mortality trends in Spain from 1980 to 2011

Author

Cayuela A, Cayuela L, Escudero-Martínez I, Rodríguez-Domínguez S, González A, Francisco Moniche, Md, Jiménez, and Montaner J

Subjects
Adult, Aged, 80 and over, Male, Adolescent, Enfermedad cerebrovascular, Epidemiology, España, Age Factors, Cerebrovascular diseases, Middle Aged, Tendencia, Cerebrovascular Disorders, Young Adult, Sex Factors, Spain, Análisis de regresión, Mortalidad, Epidemiología, Humans, Female, Mortality, Trends, Regression analysis, Aged
Abstract

In recent decades, mortality rates for cerebrovascular diseases (CVD) have declined significantly in many countries. This study analyses changes in CVD mortality rates in Spain (1980-2011) to determine if previously observed trends remain. Data on CVD mortality rates and the population data needed for the analysis were provided by Spain's National Statistics Institute. We calculated age-specific mortality rate, age-standardised overall mortality, and age-truncated mortality (35-64 years) using the direct method and standard European population structure. Joinpoint analysis was used to estimate the percentage of annual change in rates and identify significant changes in trends. CVD mortality rate decreased considerably and continuously over the last 32 years in all age groups and in both sexes in Spain. For both sexes, joinpoint analysis identifies a final period with more marked decline: 2005-2011 in women (-6.3%) and 2007-2011 in men (-7.2%). CVD mortality rates displayed a marked and continuous decline in Spain between 1980 and 2011. Due to the ageing of the population, doctors expect an increase in CVD prevalence and therefore its magnitude in terms of disability and healthcare costs, which poses a challenge to our health system.

Published
2014

45. La Red Internacional de Inventarios Forestales (BIOTREE-NET) en Mesoamérica: avances, retos y perspectivas futuras

Author

Cayuela, L., Gálvez-Bravo, L., Albuquerque, F. S., Golicher, D. J., González-Espinosa, M., Ramírez-Marcial, N., Rey Benayas, J. M., Zahawi, R. A., Meave, J. A., Benito, B. M., Garibaldi, C., Chan, I., Pérez Pérez, R., Field, R., Balvanera, P., Castillo, M. A., Figueroa-Rangel, B. L., Griffith, D. M., Gerald Alexander Islebe, Kelly, D. L., Olvera-Vargas, M., Schnitzer, S. A., Velazquez, E., Williams-Linera, G., Brewer, S. W., Camacho-Cruz, A., Coronado, I., Jong, B., Del Castillo, R., Granzow-De La Cerda, I., Fernández, J., Fonseca, W., Galindo-Jaimes, L., Gillespie, T. W., González-Rivas, B., Gordon, J. E., Hurtado, J., Linares, J., Letcher, S. G., Mangan, S. A., Méndez, V. E., Meza, V., Ochoa-Gaona, S., Peterson, C. J., Ruiz-Gutierrez, V., Snarr, K. A., Tun Dzul, F., Valdez-Hernández, M., Viergever, K. M., White, D. A., Williams, J. N., Bonet, F. J., and Zamora, R.

Subjects
lcsh:GE1-350, Acceso a la información, Estudios Ambientales, neotrópico, modelos de distribución de especies, intercambio de datos, lcsh:Environmental sciences, bases relacionales
Abstract

"Los esfuerzos de conservación en la región neotropical están limitados por la falta de información disponible sobre las especies, ya que muchas no han sido descritas o se tiene poca información sobre ellas. La Red Internacional de Inventarios Forestales (BIOTREE-NET) concentra y facilita el acceso a la información y el intercambio entre investigadores, gestores y conservacionistas, organizando y estandarizando los datos de especies de árboles procedentes de inventarios forestales en la región mesoamericana en una única base de datos que incluya información espacial. Este artículo explica el ámbito y objetivos de la red, describe la estructura de la base de datos e identifica los principales avances realizados, así como los retos y perspectivas futuras. La base de datos contiene más de 50 000 registros de árboles de unas 5000 especies, distribuidas en más de 2000 parcelas muestreadas desde el suroeste de México hasta Panamá. La información es heterogénea, tanto en su naturaleza y forma como en la cobertura geográfica de los inventarios. La base de datos tiene una estructura relacional, con 12 tablas interconectadas, incluyendo información sobre las parcelas, los nombres de las especies, el diámetro a la altura del pecho de los árboles medidos y sus atributos funcionales. Se ha desarrollado un sistema para la corrección de errores tipográficos y la estandarización taxonómica y nomenclatural utilizando como referencia The Plant List (http://theplantlist.org/). También se han generado modelos de distribución potencial para cerca de 1700 especies utilizando distintos métodos y en el futuro se prevé habilitar también el acceso público a los modelos de distribución de especies a través del portal web (http://portal.biotreenet.com). Aunque BIOTREE-NET ha contribuido al desarrollo de mejores modelos de distribución, su mayor potencial radica, en nuestra opinión, en el estudio a nivel de comunidades. Finalmente, se reconoce la necesidad de expandir la red a través de la participación de más investigadores interesados en colaborar con datos para ampliar el conocimiento sobre la biodiversidad forestal en la región neotropical."

Published
2012

48. Atlas of astronaut photos of Earth at night

Author

de Miguel, A. S., primary, Castano, J. G., additional, Zamorano, J., additional, Pascual, S., additional, Angeles, M., additional, Cayuela, L., additional, Martinez, G. M., additional, Challupner, P., additional, and Kyba, C. C. M., additional

Published
2014
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49. Toward integrated analysis of human impacts on forest biodiversity: lessons from Latin America

Author

Newton, A.C., Cayuela, L., Echeverría, C., Armesto, J.J., del Castillo, R.F., Golicher, D., Geneletti, D., González-Espinosa, M., Huth, Andreas, López-Barrera, F., Malizia, L., Manson, R., Premoli, A., Ramírez-Marcial, N., Rey Benayas, J.-M., Rüger, Nadja, Smith-Ramírez, C., Williams-Linera, G., Newton, A.C., Cayuela, L., Echeverría, C., Armesto, J.J., del Castillo, R.F., Golicher, D., Geneletti, D., González-Espinosa, M., Huth, Andreas, López-Barrera, F., Malizia, L., Manson, R., Premoli, A., Ramírez-Marcial, N., Rey Benayas, J.-M., Rüger, Nadja, Smith-Ramírez, C., and Williams-Linera, G.

Abstract

Although sustainable forest management (SFM) has been widely adopted as a policy and management goal, high rates of forest loss and degradation are still occurring in many areas. Human activities such as logging, livestock husbandry, crop cultivation, infrastructural development, and use of fire are causing widespread loss of biodiversity, restricting progress toward SFM. In such situations, there is an urgent need for tools that can provide an integrated assessment of human impacts on forest biodiversity and that can support decision making related to forest use. This paper summarizes the experience gained by an international collaborative research effort spanning more than a decade, focusing on the tropical montane forests of Mexico and the temperate rain forests of southern South America, both of which are global conservation priorities. The lessons learned from this research are identified, specifically in relation to developing an integrated modeling framework for achieving SFM. Experience has highlighted a number of challenges that need to be overcome in such areas, including the lack of information regarding ecological processes and species characteristics and a lack of forest inventory data, which hinders model parameterization. Quantitative models are poorly developed for some ecological phenomena, such as edge effects and genetic diversity, limiting model integration. Establishment of participatory approaches to forest management is difficult, as a supportive institutional and policy environment is often lacking. However, experience to date suggests that the modeling toolkit approach suggested by Sturvetant et al. (2008) could be of value in such areas. Suggestions are made regarding desirable elements of such a toolkit to support participatory-research approaches in domains characterized by high uncertainty, including Bayesian Belief Networks, spatial multi-criteria analysis, and scenario planning.

Published
2009

50. Species distribution modeling in the tropics: problems, potentialities, and the role of biological data for effective species conservation

Author

Cayuela, L., Golicher, J.D., Newton, A.C., Kolb, M., de Alburquerque, F.S., Arets, E.J.M.M., Alkemade, J.R.M., Pérez, A.M., Cayuela, L., Golicher, J.D., Newton, A.C., Kolb, M., de Alburquerque, F.S., Arets, E.J.M.M., Alkemade, J.R.M., and Pérez, A.M.

Abstract

In this paper we aim to investigate the problems and potentialities of species distribution modeling (SDM) as a tool for conservation planning and policy development and implementation in tropical regions. We reviewed 123 studies published between 1995 and 2007 in five of the leading journals in ecology and conservation, and examined two tropical case studies in which distribution modeling is currently being applied to support conservation planning. We also analyzed the characteristics of data typically used for fitting models within the specific context of modeling tree species distribution in Central America. The results showed that methodological papers outnumbered reports of SDMs being used in an applied context for setting conservation priorities, particularly in the tropics. Most applications of SDMs were in temperate regions and biased towards certain organisms such as mammals and birds. Studies from tropical regions were less likely to be validated than those from temperate regions. Unpublished data from two major tropical case studies showed that those species that are most in need of conservation actions, namely those that are the rarest or most threatened, are those for which SDM is least likely to be useful. We found that only 15% of the tree species of conservation concern in Central America could be reliably modelled using data from a substantial source (Missouri Botanical Garden VAST database). Lack of data limits model validation in tropical areas, further restricting the value of SDMs. We concluded that SDMs have a great potential to support biodiversity conservation in the tropics, by supporting the development of conservation strategies and plans, identifying knowledge gaps, and providing a tool to examine the potential impacts of environmental change. However, for this potential to be fully realized, problems of data quality and availability need to be overcome. Weaknesses in current biological datasets need to be systematically addressed, by inc

Published
2009

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