Percorrer por autor "Figary, Stephanie"
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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 SoledadSpace-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.
- 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, PetrSpace-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.
- Environmental Drivers of Nightversus Day Zooplankton Populationestimates In Lakes Around the WorldPublication . Goldfarb, Sadye K.; Doubek, Jonathan; Geraldes, Ana Maria; Armengol, Xavier; Avilés-Vargas, Lidia; Bartrons, Mireia; Bartrons, Mireia; Kankılıç, Gökben Başaran; Berger, Stella; Bess, Zach; Brentrup, Jannifer; Brucet, Sandra; Bruesewitz, Denise; Calderó-Pascual, Maria; Carey, Cayelan C.; Chandra, Sudeep; Chapina, Rosaura; Eyto, Elvira de; Erdoğan, Şeyda; Erina, Oxana; Figary, Stephanie; Gerrish, Gretchen; Glass, Lucas; Brett, Johnson; Kainz, Martin; Kalingali, Anthony; Khan, Samiullah; Kimirei, Ismael; Leoni, Barbara; Lepori, Fabio; McCarthy, Valerie; Nava, Veronica; Nejstgaard, Jens; Ogorelec, Ziga; O'Reilly, Catherine; Pate, William; Paterson, Michael; Pinheiro-Silva, Lorena; Qiu, Qianlinglin; Richardson, David; Rusak, James A.; Silver, Douglas; Straile, Dietmar; Suenaga, Erin; Tartarotti, Barbara; Tavşanoğlu, Ülkü Nihan; Tereshina, Maria; Umaña-Villalobos, Gerardo; Walles, Tim; Wander, Heather; Wurtsbaugh, Wayne; Xu, Yaoyang; Zhikharev, Vyacheslav; Stockwell, JasonZooplankton play vital roles in aquatic food webs by grazingon phytoplankton, which affects water quality, andtransferring energy to higher trophic levels. In freshwaterlakes, zooplankton commonly exhibit diel vertical andhorizontal migration. During the day, zooplankton descendto deeper waters, or seek refuge in littoral areas or thesediment-water interface, to avoid visual predators, andthen migrate to open water at night to feed. Consequently,zooplankton may exhibit higher density and biomass atnight versus the day, and estimates and perceptions ofzooplankton dynamics can change with the time of daysampling occurs. To better understand these dielzooplankton differences and their environmental drivers, weconducted a standardized global campaign to samplecrustacean zooplankton in the full water column at day andnight in the pelagic zone of 40 lakes. The lakes spanned agradient in trophic state, size, and other variables such asdissolved oxygen (DO). Mesotrophic and eutrophic lakesexhibited greater zooplankton biomass at night versus daywhile oligotrophic lakes did not. Crustacean zooplanktonhad higher biomass at night versus day in lakes at lowerelevation, with higher chlorophyll a concentration, and lowerhypolimnetic DO levels. Lake area and depth were notrelated to diel zooplankton density or biomass. We provideone of the first global, standardized studies onenvironmental drivers of day versus night zooplanktonpopulation estimates. This study has importantramifications for our understanding of zooplankton ecologyand for sampling regimens.
- Global-scale compilation of freshwater zooplankton: tiny sentinels of environmental changesPublication . 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, PetrZooplankton 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.