Search

Your search keyword '"Ovaskainen, Otso"' showing total 1,111 results
Start Over Author "Ovaskainen, Otso"
1,111 results on '"Ovaskainen, Otso"'

1. Global Spore Sampling Project: A global, standardized dataset of airborne fungal DNA.

Author

Ovaskainen, Otso, Abrego, Nerea, Furneaux, Brendan, Hardwick, Bess, Somervuo, Panu, Palorinne, Isabella, Andrew, Nigel, Babiy, Ulyana, Bao, Tan, Bazzano, Gisela, Bondarchuk, Svetlana, Bonebrake, Timothy, Brennan, Georgina, Bret-Harte, Syndonia, Bässler, Claus, Cagnolo, Luciano, Cameron, Erin, Chapurlat, Elodie, Creer, Simon, DAcqui, Luigi, de Vere, Natasha, Desprez-Loustau, Marie-Laure, Dongmo, Michel, Dyrholm Jacobsen, Ida, Fisher, Brian, Flores de Jesus, Miguel, Griffith, Gareth, Gritsuk, Anna, Gross, Andrin, Grudd, Håkan, Halme, Panu, Hanna, Rachid, Hansen, Jannik, Hansen, Lars, Hegbe, Apollon, Hill, Sarah, Hogg, Ian, Hultman, Jenni, Hyde, Kevin, Hynson, Nicole, Ivanova, Natalia, Karisto, Petteri, Kerdraon, Deirdre, Knorre, Anastasia, Krisai-Greilhuber, Irmgard, Kurhinen, Juri, Kuzmina, Masha, Lecomte, Nicolas, Lecomte, Erin, Loaiza, Viviana, Lundin, Erik, Meire, Alexander, Mešić, Armin, Miettinen, Otto, Monkhause, Norman, Mortimer, Peter, Müller, Jörg, Nilsson, R, Nonti, Puani, Nordén, Jenni, Nordén, Björn, Paz, Claudia, Pellikka, Petri, Pereira, Danilo, Petch, Geoff, Pitkänen, Juha-Matti, Popa, Flavius, Potter, Caitlin, Purhonen, Jenna, Pätsi, Sanna, Rafiq, Abdullah, Raharinjanahary, Dimby, Rakos, Niklas, Rathnayaka, Achala, Raundrup, Katrine, Rebriev, Yury, Rikkinen, Jouko, Rogers, Hanna, Rogovsky, Andrey, Rozhkov, Yuri, Runnel, Kadri, Saarto, Annika, Savchenko, Anton, Schlegel, Markus, Schmidt, Niels, Seibold, Sebastian, Skjøth, Carsten, Stengel, Elisa, Sutyrina, Svetlana, Syvänperä, Ilkka, Tedersoo, Leho, Timm, Jebidiah, Tipton, Laura, Toju, Hirokazu, Uscka-Perzanowska, Maria, van der Bank, Michelle, Herman van der Bank, F, Vandenbrink, Bryan, Ventura, Stefano, and Vignisson, Solvi

Subjects
Air Microbiology, Spores, Fungal, DNA, Fungal, Fungi, Biodiversity
Abstract

Novel methods for sampling and characterizing biodiversity hold great promise for re-evaluating patterns of life across the planet. The sampling of airborne spores with a cyclone sampler, and the sequencing of their DNA, have been suggested as an efficient and well-calibrated tool for surveying fungal diversity across various environments. Here we present data originating from the Global Spore Sampling Project, comprising 2,768 samples collected during two years at 47 outdoor locations across the world. Each sample represents fungal DNA extracted from 24 m3 of air. We applied a conservative bioinformatics pipeline that filtered out sequences that did not show strong evidence of representing a fungal species. The pipeline yielded 27,954 species-level operational taxonomic units (OTUs). Each OTU is accompanied by a probabilistic taxonomic classification, validated through comparison with expert evaluations. To examine the potential of the data for ecological analyses, we partitioned the variation in species distributions into spatial and seasonal components, showing a strong effect of the annual mean temperature on community composition.

Published
2024

2. Global arthropod beta-diversity is spatially and temporally structured by latitude.

Author

Seymour, Mathew, Roslin, Tomas, deWaard, Jeremy R, Perez, Kate HJ, D'Souza, Michelle L, Ratnasingham, Sujeevan, Ashfaq, Muhammad, Levesque-Beaudin, Valerie, Blagoev, Gergin A, Bukowski, Belén, Cale, Peter, Crosbie, Denise, Decaëns, Thibaud, deWaard, Stephanie L, Ekrem, Torbjørn, El-Ansary, Hosam O, Evouna Ondo, Fidèle, Fraser, David, Geiger, Matthias F, Hajibabaei, Mehrdad, Hallwachs, Winnie, Hanisch, Priscila E, Hausmann, Axel, Heath, Mark, Hogg, Ian D, Janzen, Daniel H, Kinnaird, Margaret, Kohn, Joshua R, Larrivée, Maxim, Lees, David C, León-Règagnon, Virginia, Liddell, Michael, Lijtmaer, Darío A, Lipinskaya, Tatsiana, Locke, Sean A, Manjunath, Ramya, Martins, Dino J, Martins, Marlúcia B, Mazumdar, Santosh, McKeown, Jaclyn TA, Anderson-Teixeria, Kristina, Miller, Scott E, Milton, Megan A, Miskie, Renee, Morinière, Jérôme, Mutanen, Marko, Naik, Suresh, Nichols, Becky, Noguera, Felipe A, Novotny, Vojtech, Penev, Lyubomir, Pentinsaari, Mikko, Quinn, Jenna, Ramsay, Leah, Rochefort, Regina, Schmidt, Stefan, Smith, M Alex, Sobel, Crystal N, Somervuo, Panu, Sones, Jayme E, Staude, Hermann S, St Jaques, Brianne, Stur, Elisabeth, Telfer, Angela C, Tubaro, Pablo L, Wardlaw, Tim J, Worcester, Robyn, Yang, Zhaofu, Young, Monica R, Zemlak, Tyler, Zakharov, Evgeny V, Zlotnick, Bradley, Ovaskainen, Otso, and Hebert, Paul DN

Subjects
Animals, Arthropods, Biodiversity, Geography, Spatio-Temporal Analysis, Biological Sciences, Ecology, Evolutionary Biology, Life Below Water, Biological sciences, Biomedical and clinical sciences
Abstract

Global biodiversity gradients are generally expected to reflect greater species replacement closer to the equator. However, empirical validation of global biodiversity gradients largely relies on vertebrates, plants, and other less diverse taxa. Here we assess the temporal and spatial dynamics of global arthropod biodiversity dynamics using a beta-diversity framework. Sampling includes 129 sampling sites whereby malaise traps are deployed to monitor temporal changes in arthropod communities. Overall, we encountered more than 150,000 unique barcode index numbers (BINs) (i.e. species proxies). We assess between site differences in community diversity using beta-diversity and the partitioned components of species replacement and richness difference. Global total beta-diversity (dissimilarity) increases with decreasing latitude, greater spatial distance and greater temporal distance. Species replacement and richness difference patterns vary across biogeographic regions. Our findings support long-standing, general expectations of global biodiversity patterns. However, we also show that the underlying processes driving patterns may be regionally linked.

Published
2024

3. Novel community data in ecology -- properties and prospects

Author

Hartig, Florian, Abrego, Nerea, Bush, Alex, Chase, Jonathan M., Guillera-Arroita, Gurutzeta, Leibold, Mathew A., Ovaskainen, Otso, Pellissier, Loïc, Pichler, Maximilian, Poggiato, Giovanni, Pollock, Laura, Si-Moussi, Sara, Thuiller, Wilfried, Viana, Duarte S., Warton, David I., Zurell, Damaris, and Yu, Douglas W.

Subjects
Quantitative Biology - Populations and Evolution
Abstract

New technologies for acquiring biological information such as eDNA, acoustic or optical sensors, make it possible to generate spatial community observations at unprecedented scales. The potential of these novel community data to standardize community observations at high spatial, temporal, and taxonomic resolution and at large spatial scale ('many rows and many columns') has been widely discussed, but so far, there has been little integration of these data with ecological models and theory. Here, we review these developments and highlight emerging solutions, focusing on statistical methods for analyzing novel community data, in particular joint species distribution models; the new ecological questions that can be answered with these data; and the potential implications of these developments for policy and conservation.

Published
2024
Full Text
View/download PDF

4. Airborne DNA reveals predictable spatial and seasonal dynamics of fungi

Author

Abrego, Nerea, Furneaux, Brendan, Hardwick, Bess, Somervuo, Panu, Palorinne, Isabella, Aguilar-Trigueros, Carlos A., Andrew, Nigel R., Babiy, Ulyana V., Bao, Tan, Bazzano, Gisela, Bondarchuk, Svetlana N., Bonebrake, Timothy C., Brennan, Georgina L., Bret-Harte, Syndonia, Bässler, Claus, Cagnolo, Luciano, Cameron, Erin K., Chapurlat, Elodie, Creer, Simon, D’Acqui, Luigi P., de Vere, Natasha, Desprez-Loustau, Marie-Laure, Dongmo, Michel A. K., Jacobsen, Ida B. Dyrholm, Fisher, Brian L., Flores de Jesus, Miguel, Gilbert, Gregory S., Griffith, Gareth W., Gritsuk, Anna A., Gross, Andrin, Grudd, Håkan, Halme, Panu, Hanna, Rachid, Hansen, Jannik, Hansen, Lars Holst, Hegbe, Apollon D. M. T., Hill, Sarah, Hogg, Ian D., Hultman, Jenni, Hyde, Kevin D., Hynson, Nicole A., Ivanova, Natalia, Karisto, Petteri, Kerdraon, Deirdre, Knorre, Anastasia, Krisai-Greilhuber, Irmgard, Kurhinen, Juri, Kuzmina, Masha, Lecomte, Nicolas, Lecomte, Erin, Loaiza, Viviana, Lundin, Erik, Meire, Alexander, Mešić, Armin, Miettinen, Otto, Monkhouse, Norman, Mortimer, Peter, Müller, Jörg, Nilsson, R. Henrik, Nonti, Puani Yannick C., Nordén, Jenni, Nordén, Björn, Norros, Veera, Paz, Claudia, Pellikka, Petri, Pereira, Danilo, Petch, Geoff, Pitkänen, Juha-Matti, Popa, Flavius, Potter, Caitlin, Purhonen, Jenna, Pätsi, Sanna, Rafiq, Abdullah, Raharinjanahary, Dimby, Rakos, Niklas, Rathnayaka, Achala R., Raundrup, Katrine, Rebriev, Yury A., Rikkinen, Jouko, Rogers, Hanna M. K., Rogovsky, Andrey, Rozhkov, Yuri, Runnel, Kadri, Saarto, Annika, Savchenko, Anton, Schlegel, Markus, Schmidt, Niels Martin, Seibold, Sebastian, Skjøth, Carsten, Stengel, Elisa, Sutyrina, Svetlana V., Syvänperä, Ilkka, Tedersoo, Leho, Timm, Jebidiah, Tipton, Laura, Toju, Hirokazu, Uscka-Perzanowska, Maria, van der Bank, Michelle, van der Bank, F. Herman, Vandenbrink, Bryan, Ventura, Stefano, Vignisson, Solvi R., Wang, Xiaoyang, Weisser, Wolfgang W., Wijesinghe, Subodini N., Wright, S. Joseph, Yang, Chunyan, Yorou, Nourou S., Young, Amanda, Yu, Douglas W., Zakharov, Evgeny V., Hebert, Paul D. N., Roslin, Tomas, and Ovaskainen, Otso

Published
2024
Full Text
View/download PDF

11. Understanding and applying biological resilience, from genes to ecosystems

Author

Thorogood, Rose, Mustonen, Ville, Aleixo, Alexandre, Aphalo, Pedro J., Asiegbu, Fred O., Cabeza, Mar, Cairns, Johannes, Candolin, Ulrika, Cardoso, Pedro, Eronen, Jussi T., Hällfors, Maria, Hovatta, Iiris, Juslén, Aino, Kovalchuk, Andriy, Kulmuni, Jonna, Kuula, Liisa, Mäkipää, Raisa, Ovaskainen, Otso, Pesonen, Anu-Katriina, Primmer, Craig R., Saastamoinen, Marjo, Schulman, Alan H., Schulman, Leif, Strona, Giovanni, and Vanhatalo, Jarno

Published
2023
Full Text
View/download PDF

15. Covariate-informed latent interaction models: Addressing geographic & taxonomic bias in predicting bird-plant interactions

Author

Papadogeorgou, Georgia, Bello, Carolina, Ovaskainen, Otso, and Dunson, David B.

Subjects
Statistics - Methodology
Abstract

Reductions in natural habitats urge that we better understand species' interconnection and how biological communities respond to environmental changes. However, ecological studies of species' interactions are limited by their geographic and taxonomic focus which can distort our understanding of interaction dynamics. We focus on bird-plant interactions that refer to situations of potential fruit consumption and seed dispersal. We develop an approach for predicting species' interactions that accounts for errors in the recorded interaction networks, addresses the geographic and taxonomic biases of existing studies, is based on latent factors to increase flexibility and borrow information across species, incorporates covariates in a flexible manner to inform the latent factors, and uses a meta-analysis data set from 85 individual studies. We focus on interactions among 232 birds and 511 plants in the Atlantic Forest, and identify 5% of pairs of species with an unrecorded interaction, but posterior probability that the interaction is possible over 80%. Finally, we develop a permutation-based variable importance procedure for latent factor network models and identify that a bird's body mass and a plant's fruit diameter are important in driving the presence of species interactions, with a multiplicative relationship that exhibits both a thresholding and a matching behavior.

Published
2021

16. Bayesian nonparametric modelling of sequential discoveries

Author

Zito, Alessandro, Rigon, Tommaso, Ovaskainen, Otso, and Dunson, David

Subjects
Statistics - Methodology
Abstract

We aim at modelling the appearance of distinct tags in a sequence of labelled objects. Common examples of this type of data include words in a corpus or distinct species in a sample. These sequential discoveries are often summarised via accumulation curves, which count the number of distinct entities observed in an increasingly large set of objects. We propose a novel Bayesian nonparametric method for species sampling modelling by directly specifying the probability of a new discovery, therefore allowing for flexible specifications. The asymptotic behavior and finite sample properties of such an approach are extensively studied. Interestingly, our enlarged class of sequential processes includes highly tractable special cases. We present a subclass of models characterized by appealing theoretical and computational properties. Moreover, due to strong connections with logistic regression models, the latter subclass can naturally account for covariates. We finally test our proposal on both synthetic and real data, with special emphasis on a large fungal biodiversity study in Finland.

Published
2020

17. Bayesian semiparametric long memory models for discretized event data

Author

Chakraborty, Antik, Ovaskainen, Otso, and Dunson, David B.

Subjects
Statistics - Methodology, Statistics - Applications
Abstract

We introduce a new class of semiparametric latent variable models for long memory discretized event data. The proposed methodology is motivated by a study of bird vocalizations in the Amazon rain forest; the timings of vocalizations exhibit self-similarity and long range dependence ruling out models based on Poisson processes. The proposed class of FRActional Probit (FRAP) models is based on thresholding of a latent process consisting of an additive expansion of a smooth Gaussian process with a fractional Brownian motion. We develop a Bayesian approach to inference using Markov chain Monte Carlo, and show good performance in simulation studies. Applying the methods to the Amazon bird vocalization data, we find substantial evidence for self-similarity and non-Markovian/Poisson dynamics. To accommodate the bird vocalization data, in which there are many different species of birds exhibiting their own vocalization dynamics, a hierarchical expansion of FRAP is provided in Supplementary Materials.

Published
2020

23. Climate change reshuffles northern species within their niches

Author

Antão, Laura H., Weigel, Benjamin, Strona, Giovanni, Hällfors, Maria, Kaarlejärvi, Elina, Dallas, Tad, Opedal, Øystein H., Heliölä, Janne, Henttonen, Heikki, Huitu, Otso, Korpimäki, Erkki, Kuussaari, Mikko, Lehikoinen, Aleksi, Leinonen, Reima, Lindén, Andreas, Merilä, Päivi, Pietiäinen, Hannu, Pöyry, Juha, Salemaa, Maija, Tonteri, Tiina, Vuorio, Kristiina, Ovaskainen, Otso, Saastamoinen, Marjo, Vanhatalo, Jarno, Roslin, Tomas, and Laine, Anna-Liisa

Published
2022
Full Text
View/download PDF

24. A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels

Author

Norberg, Anna, Abrego, Nerea, Blanchet, F Guillaume, Adler, Frederick R, Anderson, Barbara J, Anttila, Jani, Araujo, Miguel B, Dallas, Tad, Dunson, David, Elith, Jane, Foster, Scott D, Fox, Richard, Franklin, Janet, Godsoe, William, Guisan, Antoine, O'Hara, Bob, Hill, Nicole A, Holt, Robert D, Hui, Francis KC, Husby, Magne, Kalas, John Atle, Lehikoinen, Aleksi, Luoto, Miska, Mod, Heidi K, Newell, Graeme, Renner, Ian, Roslin, Tomas, Soininen, Janne, Thuiller, Wilfried, Vanhatalo, Jarno, Warton, David, White, Matt, Zimmermann, Niklaus E, Gravel, Dominique, and Ovaskainen, Otso

Subjects
community assembly, community modeling, environmental filtering, joint species distribution model, model performance, prediction, predictive power, species interactions, stacked species distribution model, Physical Geography and Environmental Geoscience, Ecological Applications, Ecology
Published
2019

25. Accelerating joint species distribution modelling with Hmsc-HPC by GPU porting.

Author

Rahman, Anis Ur, Tikhonov, Gleb, Oksanen, Jari, Rossi, Tuomas, and Ovaskainen, Otso

Subjects
STATISTICAL learning, SPECIES distribution, USER interfaces, MACHINE learning, ALGORITHMS
Abstract

Joint species distribution modelling (JSDM) is a widely used statistical method that analyzes combined patterns of all species in a community, linking empirical data to ecological theory and enhancing community-wide prediction tasks. However, fitting JSDMs to large datasets is often computationally demanding and time-consuming. Recent studies have introduced new statistical and machine learning techniques to provide more scalable fitting algorithms, but extending these to complex JSDM structures that account for spatial dependencies or multi-level sampling designs remains challenging. In this study, we aim to enhance JSDM scalability by leveraging high-performance computing (HPC) resources for an existing fitting method. Our work focuses on the Hmsc R-package, a widely used JSDM framework that supports the integration of various dataset types into a single comprehensive model. We developed a GPU-compatible implementation of its model-fitting algorithm using Python and the TensorFlow library. Despite these changes, our enhanced framework retains the original user interface of the Hmsc R-package. We evaluated the performance of the proposed implementation across various model configurations and dataset sizes. Our results show a significant increase in model fitting speed for most models compared to the baseline Hmsc R-package. For the largest datasets, we achieved speed-ups of over 1000 times, demonstrating the substantial potential of GPU porting for previously CPU-bound JSDM software. This advancement opens promising opportunities for better utilizing the rapidly accumulating new biodiversity data resources for inference and prediction. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

26. A numerical approach to determine mutant invasion fitness and evolutionary singular strategies

Author

Fritsch, Coralie, Campillo, Fabien, and Ovaskainen, Otso

Subjects
Quantitative Biology - Populations and Evolution, Mathematics - Probability
Abstract

We propose a numerical approach to study the invasion fitness of a mutant and to determine evolutionary singular strategies in evolutionary structured models in which the competitive exclusion principle holds. Our approach is based on a dual representation, which consists of the modelling of the small size mutant population by a stochastic model and the computation of its corresponding deterministic model. The use of the deterministic model greatly facilitates the numerical determination of the feasibility of invasion as well as the convergence-stability of the evolutionary singular strategy. Our approach combines standard adaptive dynamics with the link between the mutant survival criterion in the stochastic model and the sign of the eigenvalue in the corresponding deterministic model. We present our method in the context of a mass-structured individual-based chemostat model. We exploit a previously derived mathematical relationship between stochastic and deterministic representations of the mutant population in the chemostat model to derive a general numerical method for analyzing the invasion fitness in the stochastic models. Our method can be applied to the broad class of evolutionary models for which a link between the stochastic and deterministic invasion fitnesses can be established.

Published
2016

27. Differences in spatial versus temporal reaction norms for spring and autumn phenological events

Author

del Mar Delgado, Maria, Roslin, Tomas, Tikhonov, Gleb, Meyke, Evgeniy, Lo, Coong, Gurarie, Eliezer, Abadonova, Marina, Abduraimov, Ozodbek, Adrianova, Olga, Akimova, Tatiana, Akkiev, Muzhigit, Ananin, Aleksandr, Andreeva, Elena, Andriychuk, Natalia, Antipin, Maxim, Arzamascev, Konstantin, Babina, Svetlana, Babushkin, Miroslav, Bakin, Oleg, Barabancova, Anna, Basilskaja, Inna, Belova, Nina, Belyaeva, Natalia, Bespalova, Tatjana, Bisikalova, Evgeniya, Bobretsov, Anatoly, Bobrova, Vladimir, Bobrovskyi, Vadim, Bochkareva, Elena, Bogdanov, Gennady, Bolshakov, Vladimir, Bondarchuk, Svetlana, Bukharova, Evgeniya, Butunina, Alena, Buyvolovh, Yuri, Buyvolova, Anna, Bykov, Yuri, Chakhireva, Elena, Chashchina, Olga, Cherenkova, Nadezhda, Chistjakov, Sergej, Chuhontseva, Svetlana, Davydov, Evgeniy A., Demchenko, Viktor, Diadicheva, Elena, Dobrolyubov, Aleksandr, Dostoyevskaya, Ludmila, Drovnina, Svetlana, Drozdova, Zoya, Dubanaev, Akynaly, Dubrovsky, Yuriy, Elsukov, Sergey, Epova, Lidia, Ermakova, Olga S., Ermakova, Olga, Esengeldenova, Aleksandra, Evstigneev, Oleg, Fedchenko, Irina, Fedotova, Violetta, Filatova, Tatiana, Gashev, Sergey, Gavrilov, Anatoliy, Gaydys, Irina, Golovcova, Dmitrij, Goncharova, Nadezhda, Gorbunova, Elena, Gordeevab, Tatyana, Grishchenko, Vitaly, Gromyko, Ludmila, Hohryakovd, Vladimir, Hritankov, Alexander, Ignatenkoe, Elena, Igosheva, Svetlana, Ivanova, Uliya, Ivanova, Natalya, Kalinkin, Yury, Kaygorodova, Evgeniya, Kazansky, Fedor, Kiseleva, Darya, Knorre, Anastasia, Kolpashikov, Leonid, Korobov, Evgenii, Korolyova, Helen, Korotkikh, Natalia, Kosenkov, Gennadiy, Kossenko, Sergey, Kotlugalyamova, Elvira, Kozlovsky, Evgeny, Kozsheechkin, Vladimir, Kozurak, Alla, Kozyr, Irina, Krasnopevtseva, Aleksandra, Krugliko, Sergey, Kuberskaya, Olga, Kudryavtsev, Aleksey, Kulebyakina, Elena, Kulsha, Yuliia, Kupriyanova, Margarita, Kurbanbagamaev, Murad, Kutenkov, Anatoliy, Kutenkova, Nadezhda, Kuyantseva, Nadezhda, Kuznetsov, Andrey, Larin, Evgeniy, Lebedev, Pavel, Litvinov, Kirill, Luzhkova, Natalia, Mahmudov, Azizbek, Makovkina, Lidiya, Mamontov, Viktor, Mayorova, Svetlana, Megalinskaja, Irina, Meydus, Artur, Minin, Aleksandr, Mitrofanov, Oleg, Motruk, Mykhailo, Myslenkov, Aleksandr, Nasonova, Nina, Nemtseva, Natalia, Nesterova, Irina, Nezdoliy, Tamara, Niroda, Tatyana, Novikova, Tatiana, Panicheva, Darya, Pavlov, Alexey, Pavlova, Klara, Van, Polina, Podolski, Sergei, Polikarpova, Natalja, Polyanskaya, Tatiana, Pospelov, Igor, Pospelova, Elena, Prokhorov, Ilya, Prokosheva, Irina, Puchnina, Lyudmila, Putrashyk, Ivan, Raiskaya, Julia, Rozhkove, Yuri, Rozhkovae, Olga, Rudenko, Marina, Rybnikova, Irina, Rykova, Svetlana, Sahnevich, Miroslava, Samoylov, Alexander, Sank, Valeri, Sapelnikova, Inna, Sazonov, Sergei, Selyunina, Zoya, Shalaeva, Ksenia, Shashkov, Maksim, Shcherbakov, Anatoliy, Shevchyk, Vasyl, Shubin, Sergej, Shujskaja, Elena, Sibgatullin, Rustam, Sikkila, Natalia, Sitnikova, Elena, Sivkov, Andrei, Skok, Nataliya, Skorokhodova, Svetlana, Smirnova, Elena, Sokolova, Galina, Sopin, Vladimir, Spasovski, Yurii, Stepanov, Sergei, Stratiy, Vitalіy, Strekalovskaya, Violetta, Sukhov, Alexander, Suleymanova, Guzalya, Sultangareeva, Lilija, Teleganova, Viktorija, Teplov, Viktor, Teplova, Valentina, Tertitsa, Tatiana, Timoshkin, Vladislav, Tirski, Dmitry, Tolmachev, Andrej, Tomilin, Aleksey, Tselishcheva, Ludmila, Turgunov, Mirabdulla, Tyukh, Yurij, Van, Vladimir, Ershkova, Elena, Vasin, Aleksander, Vasina, Aleksandra, Vekliuk, Anatoliy, Vetchinnikova, Lidia, Vinogradov, Vladislav, Volodchenko, Nikolay, Voloshina, Inna, Xoliqov, Tura, Yablonovska-Grishchenko, Eugenia, Yakovlev, Vladimir, Yakovleva, Marina, Yantser, Oksana, Yarema, Yurij, Zahvatov, Andrey, Zakharov, Valery, Zelenetskiy, Nicolay, Zheltukhin, Anatolii, Zubina, Tatyana, Kurhinen, Juri, and Ovaskainen, Otso

Published
2020

35. Fragmented tropical forests lose mutualistic plant–animal interactions

Author

Marjakangas, Emma-Liina, Abrego, Nerea, Grøtan, Vidar, de Lima, Renato A. F., Bello, Carolina, Bovendorp, Ricardo S., Culot, Laurence, Hasui, Érica, Lima, Fernando, Muylaert, Renata Lara, Niebuhr, Bernardo Brandão, Oliveira, Alexandre A., Pereira, Lucas Augusto, Prado, Paulo I., Stevens, Richard D., Vancine, Maurício Humberto, Ribeiro, Milton Cezar, Galetti, Mauro, and Ovaskainen, Otso

Published
2020

38. Author Correction: Climate change reshuffles northern species within their niches

Author

Antão, Laura H., Weigel, Benjamin, Strona, Giovanni, Hällfors, Maria, Kaarlejärvi, Elina, Dallas, Tad, Opedal, Øystein H., Heliölä, Janne, Henttonen, Heikki, Huitu, Otso, Korpimäki, Erkki, Kuussaari, Mikko, Lehikoinen, Aleksi, Leinonen, Reima, Lindén, Andreas, Merilä, Päivi, Pietiäinen, Hannu, Pöyry, Juha, Salemaa, Maija, Tonteri, Tiina, Vuorio, Kristiina, Ovaskainen, Otso, Saastamoinen, Marjo, Vanhatalo, Jarno, Roslin, Tomas, and Laine, Anna-Liisa

Published
2023
Full Text
View/download PDF

41. Novel community data in ecology-properties and prospects

Author

Deutsche Forschungsgemeinschaft, European Commission, Agence Nationale de la Recherche (France), Academy of Finland, European Research Council, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), University of Delaware Research Foundation, National Science Foundation (US), Chinese Academy of Sciences, Guillera-Arroita, Gurutzeta [0000-0002-8387-5739], Hartig, Florian, Abrego, Nerea, Bush, Alex, Chase, Jonathan M., Guillera-Arroita, Gurutzeta, Leibold, Mathew A., Ovaskainen, Otso, Pellissier, Loïc, Pichler, Maximilian, Poggiato, Giovanni, Pollock, Laura, Si-Moussi, Sara, Thuiller, Wilfried, Viana, Duarte S., Warton, David I., Zurell, Damaris, Yu, Douglas W., Deutsche Forschungsgemeinschaft, European Commission, Agence Nationale de la Recherche (France), Academy of Finland, European Research Council, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), University of Delaware Research Foundation, National Science Foundation (US), Chinese Academy of Sciences, Guillera-Arroita, Gurutzeta [0000-0002-8387-5739], Hartig, Florian, Abrego, Nerea, Bush, Alex, Chase, Jonathan M., Guillera-Arroita, Gurutzeta, Leibold, Mathew A., Ovaskainen, Otso, Pellissier, Loïc, Pichler, Maximilian, Poggiato, Giovanni, Pollock, Laura, Si-Moussi, Sara, Thuiller, Wilfried, Viana, Duarte S., Warton, David I., Zurell, Damaris, and Yu, Douglas W.

Abstract

New technologies for monitoring biodiversity such as environmental (e)DNA, passive acoustic monitoring, and optical sensors promise to generate automated spatiotemporal community observations at unprecedented scales and resolutions. Here, we introduce ‘novel community data’ as an umbrella term for these data. We review the emerging field around novel community data, focusing on new ecological questions that could be addressed; the analytical tools available or needed to make best use of these data; and the potential implications of these developments for policy and conservation. We conclude that novel community data offer many opportunities to advance our understanding of fundamental ecological processes, including community assembly, biotic interactions, micro- and macroevolution, and overall ecosystem functioning.

Published
2024

42. Global Spore Sampling Project:A global, standardized dataset of airborne fungal DNA

Author

Ovaskainen, Otso, Abrego, Nerea, Furneaux, Brendan, Hardwick, Bess, Somervuo, Panu, Palorinne, Isabella, Andrew, Nigel R, Babiy, Ulyana V, Bao, Tan, Bazzano, Gisela, Bondarchuk, Svetlana N, Bonebrake, Timothy C, Brennan, Georgina L, Bret-Harte, Syndonia, Bässler, Claus, Cagnolo, Luciano, Cameron, Erin K, Chapurlat, Elodie, Creer, Simon, D'Acqui, Luigi P, de Vere, Natasha, Desprez-Loustau, Marie-Laure, Dongmo, Michel A K, Dyrholm Jacobsen, Ida B, Fisher, Brian L, Flores de Jesus, Miguel, Gilbert, Gregory S, Griffith, Gareth W, Gritsuk, Anna A, Gross, Andrin, Grudd, Håkan, Halme, Panu, Hanna, Rachid, Hansen, Jannik, Hansen, Lars Holst, Hegbe, Apollon D M T, Hill, Sarah, Hogg, Ian D, Hultman, Jenni, Hyde, Kevin D, Hynson, Nicole A, Ivanova, Natalia, Karisto, Petteri, Kerdraon, Deirdre, Knorre, Anastasia, Krisai-Greilhuber, Irmgard, Kurhinen, Juri, Kuzmina, Masha, Lecomte, Nicolas, Lecomte, Erin, Loaiza, Viviana, Lundin, Erik, Meire, Alexander, Mešić, Armin, Miettinen, Otto, Monkhause, Norman, Mortimer, Peter, Müller, Jörg, Nilsson, R Henrik, Nonti, Puani Yannick C, Nordén, Jenni, Nordén, Björn, Paz, Claudia, Pellikka, Petri, Pereira, Danilo, Petch, Geoff, Pitkänen, Juha-Matti, Popa, Flavius, Potter, Caitlin, Purhonen, Jenna, Pätsi, Sanna, Rafiq, Abdullah, Raharinjanahary, Dimby, Rakos, Niklas, Rathnayaka, Achala R, Raundrup, Katrine, Rebriev, Yury A, Rikkinen, Jouko, Rogers, Hanna M K, Rogovsky, Andrey, Rozhkov, Yuri, Runnel, Kadri, Saarto, Annika, Savchenko, Anton, Schlegel, Markus, Schmidt, Niels Martin, Seibold, Sebastian, Skjøth, Carsten, Stengel, Elisa, Sutyrina, Svetlana V, Syvänperä, Ilkka, Tedersoo, Leho, Timm, Jebidiah, Tipton, Laura, Toju, Hirokazu, Uscka-Perzanowska, Maria, van der Bank, Michelle, Herman van der Bank, F, Vandenbrink, Bryan, Ventura, Stefano, Vignisson, Solvi R, Wang, Xiaoyang, Weisser, Wolfgang W, Wijesinghe, Subodini N, Joseph Wright, S, Yang, Chunyan, Yorou, Nourou S, Young, Amanda, Yu, Douglas W, Zakharov, Evgeny V, Hebert, Paul D N, Roslin, Tomas, Ovaskainen, Otso, Abrego, Nerea, Furneaux, Brendan, Hardwick, Bess, Somervuo, Panu, Palorinne, Isabella, Andrew, Nigel R, Babiy, Ulyana V, Bao, Tan, Bazzano, Gisela, Bondarchuk, Svetlana N, Bonebrake, Timothy C, Brennan, Georgina L, Bret-Harte, Syndonia, Bässler, Claus, Cagnolo, Luciano, Cameron, Erin K, Chapurlat, Elodie, Creer, Simon, D'Acqui, Luigi P, de Vere, Natasha, Desprez-Loustau, Marie-Laure, Dongmo, Michel A K, Dyrholm Jacobsen, Ida B, Fisher, Brian L, Flores de Jesus, Miguel, Gilbert, Gregory S, Griffith, Gareth W, Gritsuk, Anna A, Gross, Andrin, Grudd, Håkan, Halme, Panu, Hanna, Rachid, Hansen, Jannik, Hansen, Lars Holst, Hegbe, Apollon D M T, Hill, Sarah, Hogg, Ian D, Hultman, Jenni, Hyde, Kevin D, Hynson, Nicole A, Ivanova, Natalia, Karisto, Petteri, Kerdraon, Deirdre, Knorre, Anastasia, Krisai-Greilhuber, Irmgard, Kurhinen, Juri, Kuzmina, Masha, Lecomte, Nicolas, Lecomte, Erin, Loaiza, Viviana, Lundin, Erik, Meire, Alexander, Mešić, Armin, Miettinen, Otto, Monkhause, Norman, Mortimer, Peter, Müller, Jörg, Nilsson, R Henrik, Nonti, Puani Yannick C, Nordén, Jenni, Nordén, Björn, Paz, Claudia, Pellikka, Petri, Pereira, Danilo, Petch, Geoff, Pitkänen, Juha-Matti, Popa, Flavius, Potter, Caitlin, Purhonen, Jenna, Pätsi, Sanna, Rafiq, Abdullah, Raharinjanahary, Dimby, Rakos, Niklas, Rathnayaka, Achala R, Raundrup, Katrine, Rebriev, Yury A, Rikkinen, Jouko, Rogers, Hanna M K, Rogovsky, Andrey, Rozhkov, Yuri, Runnel, Kadri, Saarto, Annika, Savchenko, Anton, Schlegel, Markus, Schmidt, Niels Martin, Seibold, Sebastian, Skjøth, Carsten, Stengel, Elisa, Sutyrina, Svetlana V, Syvänperä, Ilkka, Tedersoo, Leho, Timm, Jebidiah, Tipton, Laura, Toju, Hirokazu, Uscka-Perzanowska, Maria, van der Bank, Michelle, Herman van der Bank, F, Vandenbrink, Bryan, Ventura, Stefano, Vignisson, Solvi R, Wang, Xiaoyang, Weisser, Wolfgang W, Wijesinghe, Subodini N, Joseph Wright, S, Yang, Chunyan, Yorou, Nourou S, Young, Amanda, Yu, Douglas W, Zakharov, Evgeny V, Hebert, Paul D N, and Roslin, Tomas

Abstract

Novel methods for sampling and characterizing biodiversity hold great promise for re-evaluating patterns of life across the planet. The sampling of airborne spores with a cyclone sampler, and the sequencing of their DNA, have been suggested as an efficient and well-calibrated tool for surveying fungal diversity across various environments. Here we present data originating from the Global Spore Sampling Project, comprising 2,768 samples collected during two years at 47 outdoor locations across the world. Each sample represents fungal DNA extracted from 24 m 3 of air. We applied a conservative bioinformatics pipeline that filtered out sequences that did not show strong evidence of representing a fungal species. The pipeline yielded 27,954 species-level operational taxonomic units (OTUs). Each OTU is accompanied by a probabilistic taxonomic classification, validated through comparison with expert evaluations. To examine the potential of the data for ecological analyses, we partitioned the variation in species distributions into spatial and seasonal components, showing a strong effect of the annual mean temperature on community composition.

Published
2024

44. Phenological shifts of abiotic events, producers and consumers across a continent

Author

Roslin, Tomas, Antão, Laura, Hällfors, Maria, Meyke, Evgeniy, Lo, Coong, Tikhonov, Gleb, Delgado, Maria del Mar, Gurarie, Eliezer, Abadonova, Marina, Abduraimov, Ozodbek, Adrianova, Olga, Akimova, Tatiana, Akkiev, Muzhigit, Ananin, Aleksandr, Andreeva, Elena, Andriychuk, Natalia, Antipin, Maxim, Arzamascev, Konstantin, Babina, Svetlana, Babushkin, Miroslav, Bakin, Oleg, Barabancova, Anna, Basilskaja, Inna, Belova, Nina, Belyaeva, Natalia, Bespalova, Tatjana, Bisikalova, Evgeniya, Bobretsov, Anatoly, Bobrov, Vladimir, Bobrovskyi, Vadim, Bochkareva, Elena, Bogdanov, Gennady, Bolshakov, Vladimir, Bondarchuk, Svetlana, Bukharova, Evgeniya, Butunina, Alena, Buyvolov, Yuri, Buyvolova, Anna, Bykov, Yuri, Chakhireva, Elena, Chashchina, Olga, Cherenkova, Nadezhda, Chistjakov, Sergej, Chuhontseva, Svetlana, Davydov, Evgeniy A., Demchenko, Viktor, Diadicheva, Elena, Dobrolyubov, Aleksandr, Dostoyevskaya, Ludmila, Drovnina, Svetlana, Drozdova, Zoya, Dubanaev, Akynaly, Dubrovsky, Yuriy, Elsukov, Sergey, Epova, Lidia, Ermakova, Olga, Ermakova, Olga S., Ershkova, Elena, Esengeldenova, Aleksandra, Evstigneev, Oleg, Fedchenko, Irina, Fedotova, Violetta, Filatova, Tatiana, Gashev, Sergey, Gavrilov, Anatoliy, Gaydysh, Irina, Golovcov, Dmitrij, Goncharova, Nadezhda, Gorbunova, Elena, Gordeeva, Tatyana, Grishchenko, Vitaly, Gromyko, Ludmila, Hohryakov, Vladimir, Hritankov, Alexander, Ignatenko, Elena, Igosheva, Svetlana, Ivanova, Uliya, Ivanova, Natalya, Kalinkin, Yury, Kaygorodova, Evgeniya, Kazansky, Fedor, Kiseleva, Darya, Knorre, Anastasia, Kolpashikov, Leonid, Korobov, Evgenii, Korolyova, Helen, Korotkikh, Natalia, Kosenkov, Gennadiy, Kossenko, Sergey, Kotlugalyamova, Elvira, Kozlovsky, Evgeny, Kozsheechkin, Vladimir, Kozurak, Alla, Kozyr, Irina, Krasnopevtseva, Aleksandra, Kruglikov, Sergey, Kuberskaya, Olga, Kudryavtsev, Aleksey, Kulebyakina, Elena, Kulsha, Yuliia, Kupriyanova, Margarita, Kurbanbagamaev, Murad, Kutenkov, Anatoliy, Kutenkova, Nadezhda, Kuyantseva, Nadezhda, Kuznetsov, Andrey, Larin, Evgeniy, Lebedev, Pavel, Litvinov, Kirill, Luzhkova, Natalia, Mahmudov, Azizbek, Makovkina, Lidiya, Mamontov, Viktor, Mayorova, Svetlana, Megalinskaja, Irina, Meydus, Artur, Minin, Aleksandr, Mitrofanov, Oleg, Motruk, Mykhailo, Myslenkov, Aleksandr, Nasonova, Nina, Nemtseva, Natalia, Nesterova, Irina, Nezdoliy, Tamara, Niroda, Tatyana, Novikova, Tatiana, Panicheva, Darya, Pavlov, Alexey, Pavlova, Klara, Podolski, Sergei, Polikarpova, Natalja, Polyanskaya, Tatiana, Pospelov, Igor, Pospelova, Elena, Prokhorov, Ilya, Prokosheva, Irina, Puchnina, Lyudmila, Putrashyk, Ivan, Raiskaya, Julia, Rozhkov, Yuri, Rozhkova, Olga, Rudenko, Marina, Rybnikova, Irina, Rykova, Svetlana, Sahnevich, Miroslava, Samoylov, Alexander, Sanko, Valeri, Sapelnikova, Inna, Sazonov, Sergei, Selyunina, Zoya, Shalaeva, Ksenia, Shashkov, Maksim, Shcherbakov, Anatoliy, Shevchyk, Vasyl, Shubin, Sergej, Shujskaja, Elena, Sibgatullin, Rustam, Sikkila, Natalia, Sitnikova, Elena, Sivkov, Andrei, Skok, Nataliya, Skorokhodova, Svetlana, Smirnova, Elena, Sokolova, Galina, Sopin, Vladimir, Spasovski, Yurii, Stepanov, Sergei, Stratiy, Vitalіy, Strekalovskaya, Violetta, Sukhov, Alexander, Suleymanova, Guzalya, Sultangareeva, Lilija, Teleganova, Viktorija, Teplov, Viktor, Teplova, Valentina, Tertitsa, Tatiana, Timoshkin, Vladislav, Tirski, Dmitry, Tolmachev, Andrej, Tomilin, Aleksey, Tselishcheva, Ludmila, Turgunov, Mirabdulla, Tyukh, Yurij, Van, Polina, Van, Vladimir, Vasin, Aleksander, Vasina, Aleksandra, Vekliuk, Anatoliy, Vetchinnikova, Lidia, Vinogradov, Vladislav, Volodchenkov, Nikolay, Voloshina, Inna, Xoliqov, Tura, Yablonovska-Grishchenko, Eugenia, Yakovlev, Vladimir, Yakovleva, Marina, Yantser, Oksana, Yarema, Yurij, Zahvatov, Andrey, Zakharov, Valery, Zelenetskiy, Nicolay, Zheltukhin, Anatolii, Zubina, Tatyana, Kurhinen, Juri, and Ovaskainen, Otso

Published
2021
Full Text
View/download PDF

45. Prototype Biodiversity Digital Twin: Real-time bird monitoring with citizen-science data.

Author

Ovaskainen, Otso, Lauha, Patrik, Lopez Gordillo, Julian, Nokelainen, Ossi, Rahman, Anis U., Souza, Allan T., Talaskivi, Jussi, Tikhonov, Gleb, Vancraeyenest, Aurélie, and Lehtiö, Ari

Subjects
DIGITAL twins, BIRD classification, BIRD populations, BIOINDICATORS, ARTIFICIAL intelligence
Abstract

Bird populations respond rapidly to environmental change making them excellent ecological indicators. Climate shifts advance migration, causing mismatches in breeding and resources. Understanding these changes is crucial to monitor the state of the environment. Citizen science offers vast potential to collect biodiversity data. We outline a project that combines citizen science with AI-based bird sound classification. The mobile app records bird vocalisations that are classified by AI and stored for re-analysis. Additionally, it shows a shared observation board that visualises collective classifications. By merging long-term monitoring and modern citizen science, this project harnesses the strength of both approaches for comprehensive bird population monitoring. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

46. Prototype Biodiversity Digital Twin: Forest Biodiversity Dynamics.

Author

Afsar, Bekir, Eyvindson, Kyle, Rossi, Tuomas, Versluijs, Martijn, and Ovaskainen, Otso

Subjects
FOREST biodiversity, BIODIVERSITY, DIGITAL twins, VIRTUAL design, FOREST management
Abstract

Forests are crucial in supporting biodiversity and providing ecosystem services. Understanding forest biodiversity dynamics under different management strategies and climate change scenarios is essential for effective conservation and management. This paper introduces the Forest Biodiversity Dynamics Prototype Digital Twin (pDT), integrating forest and biodiversity models to predict the effects of management options on forest ecosystems. The primary objective is to identify optimal management strategies that promote biodiversity, focusing on conservation and adaptation to different climate conditions. We start with the case of Finnish forests and bird species and plan to expand to include more European countries and a variety of species as the pDT is further developed. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

47. Experimental evidence that root‐associated fungi improve plant growth at high altitude.

Author

Burg, Skylar, Ovaskainen, Otso, Furneaux, Brendan, Ivanova, Natalia, Abrahamyan, Arusyak, Niittynen, Pekka, Somervuo, Panu, and Abrego, Nerea

Subjects
*MOUNTAIN plants, *PLANT-fungus relationships, *PHYTOPATHOGENIC fungi, *PLANT communities, *SPECIES distribution, *PLANT translocation
Abstract

Unravelling how species communities change along environmental gradients requires a dual understanding: the direct responses of the species to their abiotic surroundings and the indirect variation of these responses through biotic interactions. Here, we focus on the interactive relationships between plants and their symbiotic root‐associated fungi (RAF) along stressful abiotic gradients. We investigate whether variations in RAF community composition along altitudinal gradients influence plant growth at high altitudes, where both plants and fungi face harsher abiotic conditions. We established a translocation experiment between pairs of Bistorta vivipara populations across altitudinal gradients. To separate the impact of shifting fungal communities from the overall influence of changing abiotic conditions, we used a root barrier to prevent new colonization by RAF following translocation. To characterize the RAF communities, we applied DNA barcoding to the root samples. Through the utilization of joint species distribution modelling, we assessed the relationship between changes in plant functional traits resulting from experimental treatments and the corresponding changes in the RAF communities. Our findings indicate that RAF communities influence plant responses to stressful abiotic conditions. Plants translocated from low to high altitudes grew more when they were able to associate with the resident high‐altitude RAF compared to those plants that were not allowed to associate with the resident RAF. We conclude that interactions with RAF impact how plants respond to stressful abiotic conditions. Our results provide experimental support that interactions with RAF improve plant stress tolerance to altitudinal stressors such as colder temperatures and less nutrient availability. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

48. Landscape fragmentation overturns classical metapopulation thinking.

Author

Yun Tao, Hastings, Alan, Lafferty, Kevin D., Hanski, Ilkka, and Ovaskainen, Otso

Subjects
FRAGMENTED landscapes, METAPOPULATION (Ecology), LANDSCAPE ecology, ECOSYSTEM management, REPRODUCTIVE isolation
Abstract

Habitat loss and isolation caused by landscape fragmentation represent a growing threat to global biodiversity. Existing theory suggests that the process will lead to a decline in metapopulation viability. However, since most metapopulation models are restricted to simple networks of discrete habitat patches, the effects of real landscape fragmentation, particularly in stochastic environments, are not well understood. To close this major gap in ecological theory, we developed a spatially explicit, individual-based model applicable to realistic landscape structures, bridging metapopulation ecology and landscape ecology. This model reproduced classical metapopulation dynamics under conventional model assumptions, but on fragmented landscapes, it uncovered general dynamics that are in stark contradiction to the prevailing views in the ecological and conservation literature. Notably, fragmentation can give rise to a series of dualities: a) positive and negative responses to environmental noise, b) relative slowdown and acceleration in density decline, and c) synchronization and desynchronization of local population dynamics. Furthermore, counter to common intuition, species that interact locally ("residents") were often more resilient to fragmentation than long-ranging "migrants." This set of findings signals a need to fundamentally reconsider our approach to ecosystem management in a noisy and fragmented world. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

50. Beyond Species Richness: Forest Structure and Edaphic Conditions Have Similar Importance But Different Effects on Multi-Taxon Biodiversity

Author

Kepfer-Rojas, Sebastian, primary, Kepfer Rojas, Sebastian, additional, Ovaskainen, Otso, additional, Møller, Peter Friis, additional, Johannsen, Vivian Kvist, additional, Byriel, David Bille, additional, Justesen, Mathias Just, additional, Riis-Nielsen, Torben, additional, Hansen, Aslak Kappel, additional, Gottlieb, Lasse, additional, and Schmidt, Inger Kappel, additional

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results