Temporal patterns of phytoplankton phenology across high latitude lakes unveiled by long-term time series of satellite data

Eduardo Eiji Maeda, Filipe Lisboa, Laura Maria Kaikkonen, Sampsa Koponen, Kari Kallio, Vanda Brotas, Olli Sakari Kuikka

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Monitoring temporal changes in phytoplankton dynamics in high latitude lakes is particularly timely for understanding the impacts of warming on aquatic ecosystems. In this study, we analyzed 33-years of high resolution (30 m) Landsat (LT) data for reconstructing seasonal patterns of chlorophyll a (chl a) concentration in four lakes across Finland, between 60°N and 64°N. Chl a models based on LT spectral bands were calibrated using 17-years (2000–2016) of field measurements collected across the four lakes. These models were then applied for estimating chl a using the entire LT-5 and 7 archives. Approximately 630 images, from 1984 to 2017, were analyzed for each lake. The chl a seasonal patterns were characterized using phenology metrics, and the time-series of LT-based chl a estimates were used for identifying temporal shifts in the seasonal patterns of chl a concentration. Our results showed an increase in the length of phytoplankton growth season in three of the lakes. The highest increase was observed in Lake Köyliönjärvi, where the length of growth season has increased by 28 days from the baseline period of 1984–1994 to 2007–2017. The increase in the length of season was mainly attributed to an earlier start of phytoplankton blooms. We further analyzed surface temperature (Ts) and precipitation data to verify if climatic factors could explain the shifts in the seasonal patterns of chl a. We found no direct relationship between Ts and chl a seasonal patterns. Similarly, the phenological metrics of Ts, in particular length of season, did not show significant temporal trends. On the other hand, we identify potential links between changes in precipitation patterns and the increase in the phytoplankton season length. We verified a significant increase in the rainfall contribution to the total precipitation during the autumn and winter, accompanied by a decline in snowfall volumes. This could indicate an increasing runoff volume during the beginning of spring, contributing to an earlier onset of the phytoplankton blooms, although further assessments are needed to analyze historical streamflow values and nearby land cover data. Likewise, additional studies are needed to better understand why chl a patterns in some lakes seem to be more resilient than in others.
Original languageEnglish
JournalRemote Sensing of Environment
Volume221
Pages (from-to)609-620
Number of pages12
ISSN0034-4257
DOIs
Publication statusPublished - Feb 2019
MoE publication typeA1 Journal article-refereed

Fields of Science

  • 1172 Environmental sciences
  • Chlorophyll a
  • Landsat
  • Eutrophication
  • Remote sensing
  • Finland
  • RAPID PHOTOSYNTHETIC ADAPTATION
  • CYANOBACTERIAL BLOOMS
  • CLIMATE-CHANGE
  • SEA-ICE
  • CHLOROPHYLL
  • LANDSAT
  • EUTROPHICATION
  • COMMUNITIES
  • VALIDATION
  • MECHANISMS

Cite this

@article{796b5dfe957945248bfc5450700cb5ea,
title = "Temporal patterns of phytoplankton phenology across high latitude lakes unveiled by long-term time series of satellite data",
abstract = "Monitoring temporal changes in phytoplankton dynamics in high latitude lakes is particularly timely for understanding the impacts of warming on aquatic ecosystems. In this study, we analyzed 33-years of high resolution (30 m) Landsat (LT) data for reconstructing seasonal patterns of chlorophyll a (chl a) concentration in four lakes across Finland, between 60°N and 64°N. Chl a models based on LT spectral bands were calibrated using 17-years (2000–2016) of field measurements collected across the four lakes. These models were then applied for estimating chl a using the entire LT-5 and 7 archives. Approximately 630 images, from 1984 to 2017, were analyzed for each lake. The chl a seasonal patterns were characterized using phenology metrics, and the time-series of LT-based chl a estimates were used for identifying temporal shifts in the seasonal patterns of chl a concentration. Our results showed an increase in the length of phytoplankton growth season in three of the lakes. The highest increase was observed in Lake K{\"o}yli{\"o}nj{\"a}rvi, where the length of growth season has increased by 28 days from the baseline period of 1984–1994 to 2007–2017. The increase in the length of season was mainly attributed to an earlier start of phytoplankton blooms. We further analyzed surface temperature (Ts) and precipitation data to verify if climatic factors could explain the shifts in the seasonal patterns of chl a. We found no direct relationship between Ts and chl a seasonal patterns. Similarly, the phenological metrics of Ts, in particular length of season, did not show significant temporal trends. On the other hand, we identify potential links between changes in precipitation patterns and the increase in the phytoplankton season length. We verified a significant increase in the rainfall contribution to the total precipitation during the autumn and winter, accompanied by a decline in snowfall volumes. This could indicate an increasing runoff volume during the beginning of spring, contributing to an earlier onset of the phytoplankton blooms, although further assessments are needed to analyze historical streamflow values and nearby land cover data. Likewise, additional studies are needed to better understand why chl a patterns in some lakes seem to be more resilient than in others.",
keywords = "1172 Environmental sciences, Chlorophyll a, Landsat, Eutrophication, Remote sensing, Finland, RAPID PHOTOSYNTHETIC ADAPTATION, CYANOBACTERIAL BLOOMS, CLIMATE-CHANGE, SEA-ICE, CHLOROPHYLL, LANDSAT, EUTROPHICATION, COMMUNITIES, VALIDATION, MECHANISMS",
author = "Maeda, {Eduardo Eiji} and Filipe Lisboa and Kaikkonen, {Laura Maria} and Sampsa Koponen and Kari Kallio and Vanda Brotas and Kuikka, {Olli Sakari}",
year = "2019",
month = "2",
doi = "10.1016/j.rse.2018.12.006",
language = "English",
volume = "221",
pages = "609--620",
journal = "Remote Sensing of Environment",
issn = "0034-4257",
publisher = "EXCERPTA MEDICA INC-ELSEVIER SCIENCE INC",

}

Temporal patterns of phytoplankton phenology across high latitude lakes unveiled by long-term time series of satellite data. / Maeda, Eduardo Eiji; Lisboa, Filipe; Kaikkonen, Laura Maria; Koponen, Sampsa; Kallio, Kari; Brotas, Vanda; Kuikka, Olli Sakari.

In: Remote Sensing of Environment, Vol. 221, 02.2019, p. 609-620.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Temporal patterns of phytoplankton phenology across high latitude lakes unveiled by long-term time series of satellite data

AU - Maeda, Eduardo Eiji

AU - Lisboa, Filipe

AU - Kaikkonen, Laura Maria

AU - Koponen, Sampsa

AU - Kallio, Kari

AU - Brotas, Vanda

AU - Kuikka, Olli Sakari

PY - 2019/2

Y1 - 2019/2

N2 - Monitoring temporal changes in phytoplankton dynamics in high latitude lakes is particularly timely for understanding the impacts of warming on aquatic ecosystems. In this study, we analyzed 33-years of high resolution (30 m) Landsat (LT) data for reconstructing seasonal patterns of chlorophyll a (chl a) concentration in four lakes across Finland, between 60°N and 64°N. Chl a models based on LT spectral bands were calibrated using 17-years (2000–2016) of field measurements collected across the four lakes. These models were then applied for estimating chl a using the entire LT-5 and 7 archives. Approximately 630 images, from 1984 to 2017, were analyzed for each lake. The chl a seasonal patterns were characterized using phenology metrics, and the time-series of LT-based chl a estimates were used for identifying temporal shifts in the seasonal patterns of chl a concentration. Our results showed an increase in the length of phytoplankton growth season in three of the lakes. The highest increase was observed in Lake Köyliönjärvi, where the length of growth season has increased by 28 days from the baseline period of 1984–1994 to 2007–2017. The increase in the length of season was mainly attributed to an earlier start of phytoplankton blooms. We further analyzed surface temperature (Ts) and precipitation data to verify if climatic factors could explain the shifts in the seasonal patterns of chl a. We found no direct relationship between Ts and chl a seasonal patterns. Similarly, the phenological metrics of Ts, in particular length of season, did not show significant temporal trends. On the other hand, we identify potential links between changes in precipitation patterns and the increase in the phytoplankton season length. We verified a significant increase in the rainfall contribution to the total precipitation during the autumn and winter, accompanied by a decline in snowfall volumes. This could indicate an increasing runoff volume during the beginning of spring, contributing to an earlier onset of the phytoplankton blooms, although further assessments are needed to analyze historical streamflow values and nearby land cover data. Likewise, additional studies are needed to better understand why chl a patterns in some lakes seem to be more resilient than in others.

AB - Monitoring temporal changes in phytoplankton dynamics in high latitude lakes is particularly timely for understanding the impacts of warming on aquatic ecosystems. In this study, we analyzed 33-years of high resolution (30 m) Landsat (LT) data for reconstructing seasonal patterns of chlorophyll a (chl a) concentration in four lakes across Finland, between 60°N and 64°N. Chl a models based on LT spectral bands were calibrated using 17-years (2000–2016) of field measurements collected across the four lakes. These models were then applied for estimating chl a using the entire LT-5 and 7 archives. Approximately 630 images, from 1984 to 2017, were analyzed for each lake. The chl a seasonal patterns were characterized using phenology metrics, and the time-series of LT-based chl a estimates were used for identifying temporal shifts in the seasonal patterns of chl a concentration. Our results showed an increase in the length of phytoplankton growth season in three of the lakes. The highest increase was observed in Lake Köyliönjärvi, where the length of growth season has increased by 28 days from the baseline period of 1984–1994 to 2007–2017. The increase in the length of season was mainly attributed to an earlier start of phytoplankton blooms. We further analyzed surface temperature (Ts) and precipitation data to verify if climatic factors could explain the shifts in the seasonal patterns of chl a. We found no direct relationship between Ts and chl a seasonal patterns. Similarly, the phenological metrics of Ts, in particular length of season, did not show significant temporal trends. On the other hand, we identify potential links between changes in precipitation patterns and the increase in the phytoplankton season length. We verified a significant increase in the rainfall contribution to the total precipitation during the autumn and winter, accompanied by a decline in snowfall volumes. This could indicate an increasing runoff volume during the beginning of spring, contributing to an earlier onset of the phytoplankton blooms, although further assessments are needed to analyze historical streamflow values and nearby land cover data. Likewise, additional studies are needed to better understand why chl a patterns in some lakes seem to be more resilient than in others.

KW - 1172 Environmental sciences

KW - Chlorophyll a

KW - Landsat

KW - Eutrophication

KW - Remote sensing

KW - Finland

KW - RAPID PHOTOSYNTHETIC ADAPTATION

KW - CYANOBACTERIAL BLOOMS

KW - CLIMATE-CHANGE

KW - SEA-ICE

KW - CHLOROPHYLL

KW - LANDSAT

KW - EUTROPHICATION

KW - COMMUNITIES

KW - VALIDATION

KW - MECHANISMS

U2 - 10.1016/j.rse.2018.12.006

DO - 10.1016/j.rse.2018.12.006

M3 - Article

VL - 221

SP - 609

EP - 620

JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

SN - 0034-4257

ER -