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Reply to: Concerns about phytoplankton bloom trends in global lakes

Nature volume 590, pages E48–E50 (2021)Cite this article

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The Original Article was published on 17 February 2021

replying to L. Feng et al. Nature https://doi.org/10.1038/s41586-021-03254-3 (2021)

In Ho et al.1, we used three decades of high-resolution Landsat 5 (L5TM) satellite imagery to investigate long-term trends in intense summertime near-surface phytoplankton blooms for 71 large lakes globally to reveal a global exacerbation of bloom conditions. In the accompanying Comment2, Feng et al. question whether the implemented algorithm is “a reliable proxy for bloom strength” owing to the strong effects of suspended sediments and aquatic vegetation, and whether “the infrequent satellite observations from L5TM make it difficult to draw statistically meaningful conclusions”. We agree that these are important considerations, and they have been examined in detail. In Ho et al.3, the algorithm was found to outperform ten other candidate algorithms (see table 1 in ref. 3). The 11 algorithms were evaluated using a total of ten metrics that assessed the algorithms’ ability to capture bloom magnitude, interannual variability and seasonal variability when evaluated against both in situ biovolume observations4 and remote-sensing imagery from MERIS and MODIS5. In Ho et al.1, we further evaluated the algorithm by assessing its ability to reproduce previously reported spatial gradients across 48 region pairs in 22 lakes (see section ‘Validation of well known spatial gradients in bloom intensity’ and supplementary table 2 in ref. 1). In addition, to evaluate whether trends in the abundance of constituents such as suspended sediments or aquatic vegetation could be misinterpreted as trends in bloom intensity, we assessed the algorithm’s ability to capture both the direction and the timing of changes in bloom intensity for seven lakes for which such information was available in the literature (see section ‘Evaluation of bloom intensity time series and trends’ in ref. 1). In all analyses, the algorithm was shown to meaningfully and accurately represent long-term trends in bloom intensity for lakes for which such information was available. Although we recognize that modern remote-sensing instruments6 will be able to track lacustrine algal blooms even more accurately in the future, we maintain that the analysis presented in Ho et al.1 using L5TM represents the best possible analysis of global phytoplankton bloom intensity over the historical period going back to the 1980s.

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Fig. 1: Detections of ‘land’ from Fmask over open water are rare.
Fig. 2: The average cloud-free area is large in the L5TM images used in Ho et al.1 study lakes, and the percentage of usable images is therefore also high.

Data availability

Data availability is as outlined in ref. 1.

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Authors and Affiliations

  1. Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, USA

    Jeff C. Ho & Anna M. Michalak

  2. Department of Civil & Environmental Engineering, Stanford University, Stanford, CA, USA

    Jeff C. Ho

  3. NASA Goddard Space Flight Center, Greenbelt, MD, USA

    Nima Pahlevan

  4. Science Systems and Applications Inc., Lanham, MD, USA

    Nima Pahlevan

Authors
  1. Jeff C. Ho
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  2. Anna M. Michalak
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  3. Nima Pahlevan
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Contributions

J.C.H. and A.M.M. designed the research and analysed the results. J.C.H. and A.M.M. wrote the response with input from N.P. J.C.H. performed the majority of the computations with input from A.M.M.

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Correspondence to Jeff C. Ho or Anna M. Michalak.

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Ho, J.C., Michalak, A.M. & Pahlevan, N. Reply to: Concerns about phytoplankton bloom trends in global lakes. Nature 590, E48–E50 (2021). https://doi.org/10.1038/s41586-021-03255-2

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