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Percorrer por autor "Symons, Celia C."

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  • Can space-for-time-substitution surveys represent zooplankton biodiversity patterns and their relationship to environmental drivers?
    Publication . Stockwell, Jason; Ivanick, Lia; Chiapella, Ariana; Vichi, Cecilia; Grossart, Hans-Peter; Zagarese, Horacio; Diovisalvi, Nadia; Odriozola, Mariana; Gideon, Gal; Geraldes, Ana Maria; Christoffersen, Kirsten Seestern; Sarvala, Jouko; Blank, Kätlin; Beklioğlu, Meryem; Kainz, Martin; Bruel, Rosalie; Ger, Kemal Ali; Matsuzaki, Shin-Ichiro; Khan, Samiullah; Nejstgaard, Jens; Znachor, Petr; Seda, Jaromír; Obertegger, Ulrike; Salmaso, Nico; García-Girón, Jorge; Leoni, Barbara; Jeppesen, Erik; Tavşanoğlu, Ülkü Nihan; Rusanovskaya, Olga O.; Tartarotti, Barbara; Dur, Gaël; Kuczyńska-Kippen, Natalia; Dondajewska-Pielka, Renata; Eyto, Elvira de; Thackeray, Stephen; Garcia de Souza, Javier R.; Rusak, James A.; Moe, Jannicke; Figary, Stephanie; May, Linda; Gunn, Iain; Doubek, Jonathan; Symons, Celia C.; Burnet, Sarah; Lepori, Fabio; Alcocer, Javier; Fernández, Rocío; Oseguera, Luis A.; Verburg, Piet; Fontanarrosa, María Soledad
    Space-for-Time-Substitution surveys (SFTS) are commonly used to describe zooplankton community dynamics and to determine lake ecosystem health. SFTS surveys typically combine single point observations from many lakes to evaluate the response of zooplankton community structure and dynamics (e.g., species abundance and biomass, diversity, demographics and modeled rate processes) to spatial gradients in hypothesized environmental drivers (e.g., temperature, nutrients, predation), in lieu of tracking such responses over long time scales. However, the reliability and reproducibility of SFTS zooplankton surveys have not yet been comprehensively tested against empirically-based community dynamics from longterm monitoring efforts distributed worldwide. We use a recently compiled global data set of more than 100 lake zooplankton time series to test whether SFTS surveys can accurately capture zooplankton diversity, and the hypothesized relationship with temperature, using simulated SFTS surveys of the time series data. Specifically, we asked: (1) to what degree can SFTS surveys capture observed biodiversity dynamics; (2) how does timing and duration of sampling affect detected biodiversity patterns; (3) does biodiversity ubiquitously increase with temperature across lakes, or vary by climate zone or lake type; and (4) do results from SFTS surveys produce comparable biodiversity-temperature relationship(s) to empirical data within and among lakes? Testing biodiversity-ecosystem function (BEF) relationships, and the drivers of such relationships, requires a solid data basis. Our work provides a global perspective on the design and usefulness of (long-term) zooplankton monitoring programs and how much confidence we can place in the zooplankton biodiversity patterns observed from SFTS surveys.
    2022Documento de conferência Acesso aberto Ver mais
  • Global-scale compilation of freshwater zooplankton: tiny sentinels of environmental changes
    Publication . Figary, Stephanie; Meyer, Michael; Pilla, Rachel; Warren Currie; Aborigho, Adebukola Abiodun; Alcocer, Javier; Alfonso, María B.; Anneville, Orlane; Geraldes, Ana Maria; Balkić, Anita Galir; Ban, Syuhei; Banerjee, Arnab; Berger, Stella; Bernát, Gábor; Beyer, Jessica; Bhattacharya, Ruchi; Blank, Kätlin; Bruel, Rosalie; Burnet, Sarah; Butts, Tyler; Carey, Cayelan C.; Caroni, Rossana; Chakrabarty, Moitreyee; Chen, Huihuang; Christoffersen, Kirsten Seestern; Cortés, Alicia; Crispim, Maria Cristina; Eyto, Elvira de; Cardoso, L.; Deemer, Bridget; DeGasperi, Curtis; DeMattei, Braden; Descy, Jean-Pierre; Dimante-Deimantovica, Inta; Diovisalvi, Nadia; Dondajewska-Pielka, Renata; Doubek, Jonathan; Dražina, Tvrtko; Dulic, Zorka; Dur, Gaël; Edwards, Christine; Ejsmont-Karabin, Jolanta; Ersoy, Zeynep; Fernández, Rocío; Feuchtmayr, Heidrun; Fontanarrosa, María Soledad; Tóth, László G; Gaiser, Evelyn; Gideon, Gal; Garcia de Souza, Javier R.; Ger, Kemal Ali; Scott, Girdner; Gołdyn, Ryszard; Grossart, Hans-Peter; Hambright, K. David; Hansson, Lars-Anders; Hendricks, Susan; Jacquet, Stéphan; Kainz, Martin; Karpowicz, Maciej; Khan, Sami; Kowalczewska-Madura, Katarzyna; Kuczyńska-Kippen, Natalia; Lepori, Fabio; Lin, Shuqi; Manca, Marina; Matsuzaki, Shin-Ichiro; McElarney, Yvonne; Menezes, Rosemberg; Michaloudi, Evangelia; Moe, Jannicke; Molina, Florencia Rojas; Mueller-Navarra, Doerthe; Muñoz-Colmenares, Manuel; Nejstgaard, Jens; Obertegger, Ulrike; Ortiz, David; Oseguera, Luis A.; Paterson, Michael; Piccolo, María Cintia; Pinheiro-Silva, Lorena; Piscia, Roberta; Pomati, Francesco;; Reid, Brian; Rose, Kevin; Rosińska, Joanna; Rudstam, Lars; Rusak, James A.; Rusanovskaya, Olga O.; Salmaso, Nico; Sarvala, Jouko; Schladow, S. Geoffrey; Schmidt, Anna; Scofield, Anne; Scordo, Facundo; Seda, Jaromír; Senft, Katie; Shimaraeva, S.V; Silow, Eugene; Špoljar, Maria; Straile, Dietmar; Stockwel, Jason; Swain, Hilary; Symons, Celia C.; Tanentzap, Andrew; Tartarotti, Barbara; Thackeray, Stephen; Timofeyev, Maxim; Verburg, Piet; Wade, John; Wander , Heather L; Watkins, James; White, David; Wollrab, Sabine; Yang, Jing; Zagarese, Horacio; Zagars, Matiss; Znachor, Petr
    Zooplankton communities are the primary conduit of energy from phytoplankton to planktivorous fish in freshwater ecosystems and play key roles in the functioning of these systems. Therefore, they are often proposed as ecological indicators. However, most zooplankton research focuses on a single waterbody or region, and insights from such studies may not be transferable to other waterbodies. To address this knowledge gap, the Zooplankton as Indicators Group (ZIG) of the Global Lake Ecological Observatory Network (GLEON) assembled a zooplankton dataset that also includes physical and chemical lake characteristics. The dataset has a broad spatial and temporal coverage with data from over 290 waterbodies. Each waterbody includes 1 to 60 years of data, with >70% sampled at least monthly during the growing season (>31,000 sampling events represented). We are exploring the environmental drivers of zooplankton community composition and assessing zooplankton as ecological indicators using this new dataset. Further, we are investigating whether relationships between zooplankton metrics and environmental drivers differ among lake characteristics (e.g., deep vs shallow) or regions, including systems such as the Laurentian Great Lakes, mountain lakes, and tropical lakes. Understanding the linkages between zooplankton communities and environmental drivers is essential to forecasting the future state of freshwaters in a changing world and we expect the dataset to have extensive and versatile applications in examining zooplankton dynamics and ecosystem responses to environmental shifts.
    2024Documento de conferência Acesso aberto Ver mais