3 research outputs found

    MASTREE+: Time-series of plant reproductive effort from six continents

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    Significant gaps remain in understanding the response of plant reproduction to environmental change. This is partly because measuring reproduction in long-lived plants requires direct observation over many years and such datasets have rarely been made publicly available. Here we introduce MASTREE+, a data set that collates reproductive time-series data from across the globe and makes these data freely available to the community. MASTREE+ includes 73,828 georeferenced observations of annual reproduction (e.g. seed and fruit counts) in perennial plant populations worldwide. These observations consist of 5971 population-level time-series from 974 species in 66 countries. The mean and median time-series length is 12.4 and 10 years respectively, and the data set includes 1122 series that extend over at least two decades (≄20 years of observations). For a subset of well-studied species, MASTREE+ includes extensive replication of time-series across geographical and climatic gradients. Here we describe the open-access data set, available as a.csv file, and we introduce an associated web-based app for data exploration. MASTREE+ will provide the basis for improved understanding of the response of long-lived plant reproduction to environmental change. Additionally, MASTREE+ will enable investigation of the ecology and evolution of reproductive strategies in perennial plants, and the role of plant reproduction as a driver of ecosystem dynamics.EEA Santa CruzFil: Hacket-Pain, Andrew. University of Liverpool. School of Environmental Sciences. Department of Geography and Planning; Reino UnidoFil: Foest, Jessie J. University of Liverpool. School of Environmental Sciences. Department of Geography and Planning; Reino UnidoFil: Pearse, Ian S. U.S. Fort Collins Science Center. Geological Survey; Estados UnidosFil: LaMontagne, Jalene M. DePaul University. Department of Biological Sciences; Estados UnidosFil: Koenig, Walter D. University of California Berkeley. Hastings Reservation; Estados UnidosFil: Vacchiano, Giorgio. University of Milan. Milan Department of Agricultural and Environmental Sciences; Italia.Fil: Bogdziewicz, MichaƂ. Adam Mickiewicz University. Faculty of Biology. Institute of Environmental Biology; PoloniaFil: Bogdziewicz, MichaƂ. University Grenoble Alpes. INRAE, LESSEM; FranciaFil: Caignard, Thomas. UniversitĂ© Bordeaux. INRAE, BIOGECO; FranciaFil: Celebias, Paulina. Adam Mickiewicz University. Faculty of Biology. Institute of Environmental Biology; PoloniaFil: Peri, Pablo Luis. Instituto Nacional de TecnologĂ­a Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas; Argentina.Fil: Ascoli, Davide. University of Torino. Department of Agricultural. Forest and Food Sciences (DISAFA); ItaliaFil: Gallo, Leonardo Ariel. Instituto Nacional de TecnologĂ­a Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Bariloche; ArgentinaFil: Gallo, Leonardo Ariel. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; ArgentinaFil: Marchelli, Paula. Instituto Nacional de TecnologĂ­a Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Bariloche; ArgentinaFil: Marchelli, Paula. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentin

    MASTREE+: time-series of plant reproductive effort from six continents

    Get PDF
    Significant gaps remain in understanding the response of plant reproduction to environmental change. This is partly because measuring reproduction in long-lived plants requires direct observation over many years and such datasets have rarely been made publicly available. Here we introduce MASTREE+, a data set that collates reproductive time-series data from across the globe and makes these data freely available to the community. MASTREE+ includes 73,828 georeferenced observations of annual reproduction (e.g. seed and fruit counts) in perennial plant populations worldwide. These observations consist of 5971 population-level time-series from 974 species in 66 countries. The mean and median time-series length is 12.4 and 10 years respectively, and the data set includes 1122 series that extend over at least two decades (≄20 years of observations). For a subset of well-studied species, MASTREE+ includes extensive replication of time-series across geographical and climatic gradients. Here we describe the open-access data set, available as a.csv file, and we introduce an associated web-based app for data exploration. MASTREE+ will provide the basis for improved understanding of the response of long-lived plant reproduction to environmental change. Additionally, MASTREE+ will enable investigation of the ecology and evolution of reproductive strategies in perennial plants, and the role of plant reproduction as a driver of ecosystem dynamics.Additional co-authors: Ciprian Palaghianu, Mario Pesendorfer, Akiko Satake, Eliane Schermer, Andrew J. Tanentzap, Peter A. Thomas, Davide Vecchio, Andreas P. Wion, Thomas Wohlgemuth, Tingting Xue, Marie-Claire Aravena Acuña, Marcelo Daniel Barrera, Jessica H. Barton, Stan Boutin, Emma R. Bush, Sergio Donoso CalderĂłn, Felipe S. Carevic, Carolina Volkmer de Castilho, Juan Manuel Cellini, Colin A. Chapman, Hazel Chapman, Francesco Chianucci, Patricia da Costa, Luc CroisĂ©, Andrea Cutini, Ben Dantzer, R. Justin DeRose, Jean-Thoussaint Dikangadissi, Edmond Dimoto, Fernanda Lopes da Fonseca, Leonardo Gallo, Georg Gratzer, David F. Greene, MartĂ­n A. Hadad, Alejandro Huertas Herrera, Jill F. Johnstone, Urs Kalbitzer, WƂadysƂaw Kantorowicz, Christie A. Klimas, Jonathan G. A. Lageard, Jeffrey Lane, Katharina Lapin, Mateusz LedwoƄ, Abigail C. Leeper, Maria Vanessa Lencinas, Ana ClĂĄudia Lira-Guedes, Michael C. Lordon, Paula Marchelli, Shealyn Marino, Harald Schmidt Van Marle, Andrew G. McAdam, Ludovic R. W. Momont, Manuel Nicolas, LĂșcia Helena de Oliveira Wadt, Parisa Panahi, Guillermo MartĂ­nez Pastur, Thomas Patterson, Pablo Luis Peri, Ɓukasz Piechnik, Mehdi Pourhashemi, Claudia Espinoza Quezada, Fidel A. Roig, Karen Peña Rojas, Yamina Micaela Rosas, Silvio Schueler, Barbara Seget, Rosina Soler, Michael A. Steele, MĂłnica Toro-ManrĂ­quez, Caroline E. G. Tutin, Tharcisse Ukizintambara, Biplang Yadok, John L. Willis, Anita Zolles, Magdalena Ć»ywiec, Davide Ascol

    MASTREE+: Time-series of plant reproductive effort from six continents.

    Get PDF
    Significant gaps remain in understanding the response of plant reproduction to environmental change. This is partly because measuring reproduction in long-lived plants requires direct observation over many years and such datasets have rarely been made publicly available. Here we introduce MASTREE+, a data set that collates reproductive time-series data from across the globe and makes these data freely available to the community. MASTREE+ includes 73,828 georeferenced observations of annual reproduction (e.g. seed and fruit counts) in perennial plant populations worldwide. These observations consist of 5971 population-level time-series from 974 species in 66 countries. The mean and median time-series length is 12.4 and 10 years respectively, and the data set includes 1122 series that extend over at least two decades (≄20 years of observations). For a subset of well-studied species, MASTREE+ includes extensive replication of time-series across geographical and climatic gradients. Here we describe the open-access data set, available as a.csv file, and we introduce an associated web-based app for data exploration. MASTREE+ will provide the basis for improved understanding of the response of long-lived plant reproduction to environmental change. Additionally, MASTREE+ will enable investigation of the ecology and evolution of reproductive strategies in perennial plants, and the role of plant reproduction as a driver of ecosystem dynamics
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