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Items: 5

1.

Predicting the cover and richness of intertidal macroalgae in remote areas: a case study in the Antarctic Peninsula.

Kotta J, Valdivia N, Kutser T, Toming K, Rätsep M, Orav-Kotta H.

Ecol Evol. 2018 Aug 19;8(17):9086-9094. doi: 10.1002/ece3.4463. eCollection 2018 Sep.

2.

Contrasting seasonality in optical-biogeochemical properties of the Baltic Sea.

Simis SG, Ylöstalo P, Kallio KY, Spilling K, Kutser T.

PLoS One. 2017 Apr 6;12(4):e0173357. doi: 10.1371/journal.pone.0173357. eCollection 2017.

3.

Dissolved organic carbon and its potential predictors in eutrophic lakes.

Toming K, Kutser T, Tuvikene L, Viik M, Nõges T.

Water Res. 2016 Oct 1;102:32-40. doi: 10.1016/j.watres.2016.06.012. Epub 2016 Jun 6.

PMID:
27318445
4.

Predicting species cover of marine macrophyte and invertebrate species combining hyperspectral remote sensing, machine learning and regression techniques.

Kotta J, Kutser T, Teeveer K, Vahtmäe E, Pärnoja M.

PLoS One. 2013 Jun 3;8(6):e63946. doi: 10.1371/journal.pone.0063946. Print 2014.

5.

Relating remotely sensed optical variability to marine benthic biodiversity.

Herkül K, Kotta J, Kutser T, Vahtmäe E.

PLoS One. 2013;8(2):e55624. doi: 10.1371/journal.pone.0055624. Epub 2013 Feb 6.

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