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Percorrer por autor "Warren Currie"

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  • Do Zooplankton diversity-environment relationships derivedfrom space-for-time-substitution surveys actually represent any lakes?
    Publication . Stockwell, Jason; Symons, Celia; Figary, Stephanie; Alcocer, Javier; Alfonso, María B.; Anneville, Orlane; Geraldes, Ana Maria; Beklioğlu, Meryem; Beyer, Jessica; Blank, Kätlin; Bruel, Rosalie; Burnet, Sarah; Caroni, Rossana; Chandra, Sudeep; Christoffersen, Kirsten Seestern; Cortés, Alicia; Crispim, Maria Cristina; Warren Currie; Eyto, Elvira de; DeGasperi, Curtis; Diovisalvi, Nadia; Dondajewska-Pielka, Renata; Doubek, Jonathan; Dur, Gaël; Ersoy, Zeynep; Fernández, Rocío; Fontanarrosa, María Soledad; Gideon, Gal; García-Girón, Jorge; Ger, Kemal Ali; Goldyn, Ryszard; Guo, Fen; Hambright, K. David; Somia, Raslen; Jeppesen, Erik; Kainz, Martin; Kowalczewska-Madura, Katarzyna; Kuczyńska-Kippen, Natalia; Laas, Alo; Leoni, Barbara; López-Vázquez, Mercedes; Manca, Marina; Matsuzaki, Shin-Ichiro; Matthews, Blake; Merz,Ewa; Moe, Jannicke; Muñoz-Colmenares, Manuel; Nejstgaard, Jens; Obertegger, Ulrike; Oseguera, Luis A.; Paterson, Michael; Piscia, Roberta; Molina, Florencia Rojas; Rudstam, Lars; Rusak, James A.; Rusanovskaya, Olga O.; Salmaso, Nico; Sarvala, Jouko; Seda, Jaromír; Silow, Eugene; Soininen, Janne; Tartarotti, Barbara; Tavşanoğlu, Ülkü Nihan; Thackeray, Stephen; Timofeyev, Maxim; Zagarese, Horacio; Znachor, Petr
    Space-For-Time-Substitution (SFTS) surveys are used todescribe zooplankton community structure, assess lakehealth, and forecast lake responses to environmental change. SFTS surveys combine single-point sampling from many lakes to evaluate zooplankton community structure and dynamics (e.g., abundance, diversity) and their responses to ecogeographical gradients in key environmental drivers (e.g., temperature, salinity), instead of tracking such responses in individual lakes. However, there liability and reproducibility of estimating temporal dynamics from models of SFTS survey data have yet to betested against observed community dynamics within lakes distributed worldwide. We use a recently compiled global dataset (292 lakes, 38 countries, 6 continents) of lake zooplankton time series to estimate the relationship between zooplankton diversity and potential environmental drivers using simulated SFTS surveys. We then apply the results to lakes with long-term time series to compare relationships derived from SFTS surveys with the historical dynamics of individual lakes. We expect that zooplankton dynamics in lakes from less variable thermal regions (i.e.,low and high latitudes) will not be well represented by temperature relationships derived from SFTS surveys. Testing biodiversity-ecosystem function relationships and their drivers requires adequate temporally and spatially resolved data. We provide a global perspective on thedesign of monitoring programs that include zooplankton and examine the reliability of zooplankton biodiversity patterns observed in SFTS surveys.
    2024Documento 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