Variation in phytoplankton pigment composition in relation to mixing conditions in temperate South-Central Chilean lakes

Associations between Optical Properties and Mixotrophic Ciliates Abundances Using Remote Sensing Techniques in Two North Patagonian Lakes (Villarrica and Caburgua, 38ºS, Araucania, Chile)

“…The spectral properties were obtained from satellite LANDSAT/OLI, it got from Land Processes Distributed Active Archive Center (LP DAAC) from U.S. Geological Survey (http://LPDAAC.usgs.gov). The bands of visible light used were B01 coastal spray (0.430-0.450 μm), B02 blue (0.450-0.510 μm), B03 green (0.530-0.590 μm), B04 red (0.640-0.670 μm), for near infrared were B05 (0.850-0.880 μm), and for short wave infrared (SWIR) were B06 (1.570-1.650 μm) and B07 (2.100-2.290 μm) were calibrated radiometrically to spectral irradiance and then to reflectance, with atmospheric correction being applied [15][16][17][20][21][22].…”

The Critical Studies of Fucoxanthin Research Trends from 1928 to June 2021: A Bibliometric Review

“…Moreover, the freshwater phytoplankton dynamics affected by seasonally variable freshwater inputs were investigated using pigment biomarkers [148]. Another study employed phytoplankton pigment profiling as a potential bioindicator of stratification conditions in lakes [149]. Apart from these, the significance of algal pigments was highlighted for paleolimnological research [150,151].…”

High-throughput sequencing and marker pigment analysis of freshwater phytoplankton: A direct comparison with microscopic count data in the tropical crater lakes of Western Uganda

“…CHEMTAX, a matrix factorization program allowing to quantify the contributions of different phytoplankton groups to total chlorophyll a based on marker pigment ratios (Mackey et al, 1996) requires sets of >10 samples from homogeneous environments (Mackey et al, 1997), and hence is not well-suited for this study with sampling strategy targeting the widest possible trophic gradient across a large number of lakes. We therefore used raw pigment abundances and concentrations to infer the relative abundance of source algae, as was successfully done by Van de Vyver et al (2019) in a survey of Chilean lakes.…”

“…However because this matrix factorization program requires a minimum of 10 samples from homogeneous environmental conditions (Mackey et al, 1997) it is not necessarily applicable to studies focusing on differences in phytoplankton composition among a large number of lakes of different trophic status. On the other hand, also 'raw' pigment concentration data have proven valuable in characterizing variation in phytoplankton community composition among lakes (Van de Vyver et al, 2019).…”