Abstract

Lakes are key ecosystems within the global biogeosphere. However, the bottom-up controls on the biological productivity of lakes, including surface temperature, ice phenology, nutrient loads and mixing regime, are increasingly altered by climate warming and land-use changes. To better understand the environmental drivers of lake productivity, we assembled a dataset on chlorophyll-a concentrations, as well as associated water quality parameters and surface solar irradiance, for temperate and cold-temperate lakes experiencing seasonal ice cover. We developed a method to identify periods of rapid algal growth from in situ chlorophyll-a time series data and applied it to measurements performed between 1964 and 2019 across 357 lakes, predominantly located north of 40°. Long-term trends show that the algal growth windows have been occurring earlier in the year, thus potentially extending the growing season and increasing the annual productivity of northern lakes. The dataset is also used to analyze the relationship between chlorophyll-a growth rates and solar irradiance. Lakes of higher trophic status exhibit a higher sensitivity to solar radiation, especially at moderate irradiance values during spring. The lower sensitivity of chlorophyll-a growth rates to solar irradiance in oligotrophic lakes likely reflects the dominant role of nutrient limitation. Chlorophyll-a growth rates are significantly influenced by light availability in spring but not in summer and fall, consistent with a switch to top-down control of summer and fall algal communities. The growth window dataset can be used to analyze trends in lake productivity across the northern hemisphere or at smaller, regional scales. We present some general trends in the data and encourage other researchers to use the open dataset for their own research questions.

Highlights

  • Lakes play an important role in the biogeochemical cycling of many elements (Battin et al, 2008; Cole et al, 2007; O’Connell et al, 2020; Rousseaux and Gregg, 2013; Schindler, 1971)

  • We present a method for calculating seasonal chlorophyll-a growth rates 110 and create a dataset of these rates derived from in situ chlorophyll-a concentrations obtained in 357 lakes, most of which are at latitudes above 40° N

  • To illustrate the potential applications of the dataset, we present some general trends of the chlorophyll-a rates and their 115 relationships with environmental variables

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Summary

Introduction

Lakes play an important role in the biogeochemical cycling of many elements (Battin et al, 2008; Cole et al, 2007; O’Connell et al, 2020; Rousseaux and Gregg, 2013; Schindler, 1971). There are multiple bottom-up controls on lake primary productivity, including water 50 temperature, ice phenology, nutrient concentrations, circulation, mixing regime, and solar radiation (Lewis, 2011). Ho et al (2020) used the Mann-Kendall trend test to analyze time series of annual maximum chlorophyll-a concentrations, 95 while Shuvo et al (2021) used a random forest regression approach to assess the relative importance of climatic versus non-climatic controls on mean chlorophyll-a concentrations These approaches do not look at the periods of the year when algal biomass is primarily determined by bottom-up controls and exhibits rapid growth. To analyze trends in lake productivity one should consider environmental variables, such as surface water temperature, solar radiation and nutrient concentrations, both during and 105 preceding the annual growth windows. The dataset is made available as an open resource that other researchers are encouraged to use in their own work

Data and methods
Detecting seasonal growth windows
Dataset characteristics
Dataset: trend analyses
Chlorophyll-a rates: temperature and climate warming
Chlorophyll-a rates: solar irradiance
Key findings
Conclusions
Findings
360 Code and data availability
Full Text

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