Search results for "kukinta"

showing 5 items of 5 documents

Alder pollen in Finland ripens after a short exposure to warm days in early spring, showing biennial variation in the onset of pollen ripening

2017

Abstract We developed a temperature sum model to predict the daily pollen release of alder, based on pollen data collected with pollen traps at seven locations in Finland over the years 2000–2014. We estimated the model parameters by minimizing the sum of squared errors (SSE) of the model, with weights that put more weight on binary recognition of daily presence or absence of pollen. The model results suggest that alder pollen ripens after a couple of warm days in February, while the whole pollen release period typically takes up to 4 weeks. We tested the model residuals against air humidity, precipitation and wind speed, but adding these meteorological features did not improve the model pr…

0106 biological sciencesAtmospheric Science010504 meteorology & atmospheric sciencesta1171Atmospheric sciencesmedicine.disease_causeAlnus01 natural sciencesAlderPollenotorhinolaryngologic diseasesmedicineMonte Carlo resamplingPrecipitationsiitepöly0105 earth and related environmental sciencespollen seasonGlobal and Planetary Changefloweringbiologyta114kukintaAnomaly (natural sciences)ta1183food and beveragesHumidityForestryRipeningennusteetmodelingalderbiology.organism_classificationta4112leppäMonte Carlo -menetelmätAlder pollenClimatologyta1181Short exposureAgronomy and Crop Science010606 plant biology & botanyAgricultural and Forest Meteorology
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Bacterioplankton dynamics driven by interannual and spatial variation in diatom and dinoflagellate spring bloom communities in the Baltic Sea

2020

17 pages, 6 figures, 2 tables, supporting information https://doi.org/10.1002/lno.11601.-- This is the pre-peer reviewed version of the following article: María Teresa Camarena‐Gómez, Clara Ruiz‐González, Jonna Piiparinen, Tobias Lipsewers, Cristina Sobrino, Ramiro Logares, Kristian Spilling, Bacterioplankton dynamics driven by interannual and spatial variation in diatom and dinoflagellate spring bloom communities in the Baltic Sea, Limnology and Oceanography 66(1): 255-271 (2021), which has been published in final form at https://doi.org/10.1002/lno.11601. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions

0106 biological sciencesSUCCESSIONLimnologyAquatic ScienceOceanography01 natural sciencesAlgal bloomsuolapitoisuusbakteerit03 medical and health sciencesBACTERIAL PRODUCTIONtaksonomiaPHYTOPLANKTONPhytoplanktonpiilevätDISSOLVED ORGANIC-CARBON14. Life underwaterlajitleväkukinta030304 developmental biology0303 health sciencespanssarilevätPRODUCTIVITYLIMITATIONbiologykoostumus010604 marine biology & hydrobiologyfungiplanktonDinoflagellateVDP::Matematikk og Naturvitenskap: 400BacterioplanktoneliöyhteisötSpring bloomPlanktonVDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480::Marinbiologi: 497mikrolevätbiology.organism_classificationDiatomOceanographyGeography1181 Ecology evolutionary biologyGROWTHPOPULATIONSCRENOTHRIXABUNDANCElämpötilaLimnology and Oceanography
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Geranium sylvaticum video recording data

2022

Dataset consists of three sheets. Insect visits data is the main data with insect visitors per visitor group, and their reproductive organ contacts during each visit. Seed data is the data of count seeds of the study plants. Visitation rate is the data on the number of visits per flower per hour by different visitor groups.

floweringpollinationkukintapollinatorspölytyspölyttäjät
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Raatteen (Menyanthes trifoliata) kärkikukan poikkeuksellinen avautumisajankohta - viesti pölyttäjille kukinnon houkuttelevuuden huipusta?

2006

kukintakokokukkaraateonnistuminenpölytys
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Alder pollen in Finland ripens after a short exposure to warm days in early spring, showing biennial variation in the onset of pollen ripening

2017

We developed a temperature sum model to predict the daily pollen release of alder, based on pollen data collected with pollen traps at seven locations in Finland over the years 2000–2014. We estimated the model parameters by minimizing the sum of squared errors (SSE) of the model, with weights that put more weight on binary recognition of daily presence or absence of pollen. The model results suggest that alder pollen ripens after a couple of warm days in February, while the whole pollen release period typically takes up to 4 weeks. We tested the model residuals against air humidity, precipitation and wind speed, but adding these meteorological features did not improve the model prediction …

pollen seasonMonte Carlo -menetelmätlepätkukintaotorhinolaryngologic diseasesfood and beveragesmodelingMonte Carlo resamplingennusteetAlnusleppäsiitepöly
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