CLIMATE CHANGE AND ALGAL BLOOMS By Shengpan Lin A DISSERTATION Submitted to ...

210 Pages·2017·4.35 MB·English

by  Shengpan Lin

CLIMATE CHANGE AND ALGAL BLOOMS
By
Shengpan Lin

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Integrative Biology—Doctor of Philosophy
2017
ABSTRACT

CLIMATE CHANGE AND ALGAL BLOOMS

By

Shengpan Lin
Algal blooms are new emerging hazards that have had important social impacts in recent years.
However, it was not very clear whether future climate change causing warming waters and stronger
storm events would exacerbate the algal bloom problem. The goal of this dissertation was to evaluate
the sensitivity of algal biomass to climate change in the continental United States. Long-term large-scale
observations of algal biomass in inland lakes are challenging, but are necessary to relate climate change
to algal blooms. To get observations at this scale, this dissertation applied machine-learning algorithms
including boosted regression trees (BRT) in remote sensing of chlorophyll-a with Landsat TM/ETM+. The
results show that the BRT algorithm improved model accuracy by 15%, compared to traditional linear
regression. The remote sensing model explained 46% of the total variance of the ground-measured
chlorophyll-a in the first National Lake Assessment conducted by the US Environmental Protection
Agency. That accuracy was ecologically meaningful to study climate change impacts on algal blooms.
Moreover, the BRT algorithm for chlorophyll-a would not have systematic bias that is introduced by
sediments and colored dissolved organic matter, both of which might change concurrently with climate
change and algal blooms. This dissertation shows that the existing atmospheric corrections for Landsat
TM/ETM+ imagery might not be good enough to improve the remote sensing of chlorophyll-a in inland
lakes. After deriving long-term algal biomass estimates from Landsat TM/ETM+, time series analysis was
used to study the relations of climate change and algal biomass in four Missouri reservoirs. The results
show that neither temperature nor precipitation was the only factor that controlled temporal variation
of algal biomass. Different reservoirs, even different zones within the same reservoir, responded
differently to temperature and precipitation changes. These findings were further tested in 1157 lakes
across the continental United States. The results show that mean annual algal biomass generally
increased with annual temperature. Greater increase was found in lakes with more nutrients. Mean
annual algal biomass generally decreased with annual total precipitation. In both the “low” and the
“high” greenhouse-gas emission scenarios, mean annual algal biomass in lakes generally increased with
climate change, and greater increases are predicted from the high emission scenario.
Keywords: climate change, algal bloom, remote sensing, machine learning
Copyright by
SHENGPAN LIN
2017
ACKNOWLEDGEMENTS

I would like to express my sincere gratitude to my committee chair, Professor R. Jan Stevenson, who
continually conveys the patience of a mentor, the intelligence of a discoverer, the integrity of a scientist,
and the passion of a teacher. This dissertation is made possible by his persistent guidance.
I thank my committee members, Professor Jiaguo Qi, Professor David W. Hyndman, and Professor
Stephen K. Hamilton, who helped me all the way from course selection to the proposal and completion
of this dissertation. They are genuinely willing to help guide me to succeed in my career. I still remember
the comment from Professor Hamilton during my comprehensive examination. He encouraged me not
to give up pursuing a career in academia simply because that I was not fully comfortable in speaking
English. It turns out that as he said, time would solve the problem. The feedbacks from the committee
have greatly improved the quality of my dissertation. They polished my writing almost sentence by
sentence, far exceeding my expectation.
Professor John R. Jones at University of Missouri kindly provided 28 years of reservoir data for my study.
Professor Charles P. Hawkins at Utah State University shared his spatial data corresponding to the lakes
sampled by the first National Lake Assessment. These data are the basis of part of my dissertation
research, and I deeply appreciate their generosity. I thank Professor Bryan Pijanowski at Purdue
University for providing land use projection data. I did not finally use the data in the dissertation, but his
kindness is appreciated.
This research was funded by US Environmental Protection Agency (EPA) (Grant #: R835203). Thanks to
the PI and co-PIs who spent a lot of time to pursue this funding and made it available to me. The group
members in the project, including Dr. Nathan Moore, Dr. Sherry Martin, and Dr. Anthony Kendall, have
offered useful comments on my dissertation research.
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My friends Brad Peter, Dr. Linda Novitski, and Dr. Timothy Cefai improved the language in parts of this
dissertation. Visiting scholar Tao Tang from China provided the idea of gradient forest in the
atmospheric correction analysis. Di Liang at the Kellogg Biological Station inspired me on the watershed
impacts of climate change. I am lucky to have a lot of great friends and colleagues who emotionally and
intellectually supported me in this dissertation, and filled my life with beer, laughter, and joy. I cannot
list them all here. Their help extended far beyond this dissertation.
Last but not the least, thanks to my father Jiatian Lin and my mother Wenfang Xie for their
unconditional love.
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TABLE OF CONTENTS

LIST OF TABLES ............................................................................................................................................. xi
LIST OF FIGURES .......................................................................................................................................... xii
1 GENERAL INTRODUCTION ..................................................................................................................... 1
1.1 Algal blooms .................................................................................................................................. 1
1.1.1 Species .................................................................................................................................. 1
1.1.2 Public health impacts ............................................................................................................ 1
1.1.3 Economic and social impacts ................................................................................................ 2
1.1.4 Perceptions ........................................................................................................................... 3
1.2 Climate change .............................................................................................................................. 4
1.3 Climate change impacts on algal blooms ...................................................................................... 5
1.3.1 Temperature ......................................................................................................................... 7
1.3.2 Precipitation .......................................................................................................................... 9
1.3.3 Watershed effects ............................................................................................................... 10
1.4 Remote sensing of algal blooms ................................................................................................. 10
1.4.1 The theory of remote sensing ............................................................................................. 11
1.4.2 Remote sensing algorithms ................................................................................................. 12
1.5 Dissertation structure ................................................................................................................. 13
REFERENCES ............................................................................................................................................ 15
2 MACHINE-LEARNING ALGORITHMS FOR CHLOROPHYLL-A MEASUREMENTS IN INLAND LAKES USING
LANDSAT TM/ETM+ .................................................................................................................................... 21
Abstract ................................................................................................................................................... 21
Highlights ................................................................................................................................................ 22
2.1 Introduction ................................................................................................................................ 22
2.1.1 Long-term large-scale measurement of algal biomass is needed ...................................... 22
2.1.2 Remote sensing of algae in inland water bodies is challenging .......................................... 22
2.1.3 Objective and research questions ....................................................................................... 24
2.2 Methodology ............................................................................................................................... 25
2.2.1 Model comparison .............................................................................................................. 25
2.2.1.1 Model data ...................................................................................................................... 25
2.2.1.1.1 Ground-measured water quality data ...................................................................... 25
2.2.1.1.2 Remote sensing data................................................................................................. 26
2.2.1.1.3 Data screening .......................................................................................................... 27
2.2.1.2 Model performance comparison .................................................................................... 29
2.2.1.3 Model development ........................................................................................................ 29
2.2.2 Evaluation of model applications ........................................................................................ 31
2.2.2.1 Algal bloom detection ..................................................................................................... 31
2.2.2.2 Validation by relation with total phosphorus ................................................................. 31
2.3 Results ......................................................................................................................................... 32
2.3.1 Algorithm comparison ........................................................................................................ 32
2.3.2 Performance for algal bloom identification ........................................................................ 34
2.3.3 Relation with total phosphorus .......................................................................................... 35
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2.4 Discussion .................................................................................................................................... 37
2.4.1 Are machine-learning algorithms our best choice? ............................................................ 37
2.4.2 Error sources ....................................................................................................................... 40
2.4.2.1 Phytoplankton spatial and temporal heterogeneity ....................................................... 40
2.4.2.2 Image quality ................................................................................................................... 41
2.4.2.3 Lake condition ................................................................................................................. 43
2.4.3 Are machine-learning algorithms good enough? ............................................................... 43
2.5 Conclusion ................................................................................................................................... 44
Acknowledgement .................................................................................................................................. 44
REFERENCES ............................................................................................................................................ 45
3 EFFECTS OF SEDIMENTS AND COLORED DISSOLVED ORGANIC MATTER ON REMOTE SENSING OF
CHLOROPHYLL-A USING LANDSAT TM/ETM+ OVER TURBID WATERS ....................................................... 51
Abstract ................................................................................................................................................... 51
Highlights ................................................................................................................................................ 51
3.1 Introduction ................................................................................................................................ 52
3.1.1 Remote sensing of chlorophyll-a in inland lakes................................................................. 52
3.1.2 Sediment effects ................................................................................................................. 53
3.1.3 CDOM effects ...................................................................................................................... 54
3.1.4 Landsat chlorophyll-a algorithms ........................................................................................ 54
3.1.5 Objective ............................................................................................................................. 55
3.2 Methodology ............................................................................................................................... 56
3.2.1 Data ..................................................................................................................................... 56
3.2.1.1 In-situ data ...................................................................................................................... 56
3.2.1.2 Remote sensing data ....................................................................................................... 58
3.2.2 Chlorophyll-a model development ..................................................................................... 59
3.2.3 Residual analyses ................................................................................................................ 60
3.3 Results ......................................................................................................................................... 63
3.4 Discussion .................................................................................................................................... 67
3.4.1 Model performance ............................................................................................................ 67
3.4.2 Sediments and CDOM effects ............................................................................................. 68
3.4.2.1 The method for detecting effects ................................................................................... 68
3.4.2.2 Explanations for the insensitivity to suspended sediments and CDOM ......................... 69
3.4.3 Model correction ................................................................................................................ 70
3.4.4 Application of the findings .................................................................................................. 71
3.5 Conclusion ................................................................................................................................... 72
Acknowledgement .................................................................................................................................. 72
REFERENCES ............................................................................................................................................ 73
4 LANDSAT SURFACE REFLECTANCE PRODUCTS FOR REMOTE SENSING OF INLAND LAKES: THE
PROBLEM OF ATMOSPHERIC INTERFERENCE ............................................................................................. 79
Abstract ................................................................................................................................................... 79
Highlights ................................................................................................................................................ 79
4.1 Introduction ................................................................................................................................ 80
4.2 Methodology ............................................................................................................................... 81
4.2.1 Study area and data ............................................................................................................ 81
4.2.2 Signal enhancement evaluation .......................................................................................... 82
4.2.3 Remote sensing of water optical characteristics ................................................................ 83
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4.3 Results ......................................................................................................................................... 84
4.3.1 Signal change ...................................................................................................................... 84
4.3.2 Remote sensing of water optics .......................................................................................... 86
4.4 Discussion .................................................................................................................................... 86
4.4.1 Why did the atmospheric correction produce no obvious signal enhancement? .............. 86
4.4.2 Remote sensing of water optical characteristics ................................................................ 93
4.5 Conclusion ................................................................................................................................... 94
Acknowledgement .................................................................................................................................. 94
REFERENCES ............................................................................................................................................ 95
5 ALGAL BIOMASS RESPONSES TO CLIMATE CHANGE IN MISSOURI RESERVOIRS ................................ 98
Abstract ................................................................................................................................................... 98
Highlights ................................................................................................................................................ 98
5.1 Introduction ................................................................................................................................ 99
5.1.1 Climate change .................................................................................................................... 99
5.1.2 Harmful algal blooms .......................................................................................................... 99
5.1.3 Complex system ................................................................................................................ 100
5.1.4 Objective and research questions ..................................................................................... 101
5.2 Methodology ............................................................................................................................. 102
5.2.1 Study reservoirs ................................................................................................................ 102
5.2.2 Data ................................................................................................................................... 103
5.2.3 Spatial and temporal patterns .......................................................................................... 105
5.2.4 Univariate analyses ........................................................................................................... 106
5.2.5 Multivariate analyses ........................................................................................................ 107
5.3 Results ....................................................................................................................................... 108
5.3.1 Spatial and temporal patterns .......................................................................................... 108
5.3.2 Single-factor analyses ....................................................................................................... 113
5.3.2.1 Lake surface temperature effects on chlorophyll ......................................................... 113
5.3.2.2 Total precipitation effects on chlorophyll ..................................................................... 114
5.3.2.3 Precipitation intensity effects on chlorophyll ............................................................... 116
5.3.3 Multiple-factor analyses ................................................................................................... 117
5.4 Discussion .................................................................................................................................. 119
5.4.1 Temperature effects ......................................................................................................... 119
5.4.2 Precipitation effects .......................................................................................................... 121
5.4.2.1 Nutrient and light availability........................................................................................ 121
5.4.2.2 Residence time of water in the reservoirs .................................................................... 122
5.4.2.3 Time lags in algal biomass responses ............................................................................ 123
5.4.2.4 Internal nutrient legacy sources ................................................................................... 123
5.4.2.5 Phytoplankton adaptation ............................................................................................ 124
5.5 Conclusion ................................................................................................................................. 124
Acknowledgement ................................................................................................................................ 125
APPENDIX .............................................................................................................................................. 126
REFERENCES .......................................................................................................................................... 136
6 ALGAL BIOMASS RESPONSES TO CLIMATE CHANGE IN LAKES ACROSS THE CONTINENTAL UNITED
STATES ....................................................................................................................................................... 140
Abstract ................................................................................................................................................. 140
Highlights .............................................................................................................................................. 140
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6.1 Introduction .............................................................................................................................. 141
6.2 Methodology ............................................................................................................................. 144
6.2.1 Study lakes ........................................................................................................................ 144
6.2.2 Sensitivity and partial dependence analyses .................................................................... 145
6.2.2.1 Chl sensitivity to temperature ...................................................................................... 148
6.2.2.2 Chl sensitivity to precipitation ...................................................................................... 149
6.2.3 Future scenario analyses ................................................................................................... 152
6.3 Results ....................................................................................................................................... 153
6.3.1 Chl sensitivity to temperature .......................................................................................... 153
6.3.2 Chl sensitivity to precipitation .......................................................................................... 155
6.3.3 Future scenario analyses ................................................................................................... 161
6.4 Discussion .................................................................................................................................. 167
6.4.1 Chl increased with temperature but regulated by nutrients (Hypotheses A & B) ............ 167
6.4.2 Chl sensitivity to precipitation (Hypothesis C) and its variations with natural hydraulic
conditions (Hypothesis D) ................................................................................................................. 168
6.4.3 Future scenario analyses ................................................................................................... 171
6.4.4 Long-term temperature and precipitation effects............................................................ 174
6.4.5 Climate change mitigation ................................................................................................ 177
6.5 Conclusion ................................................................................................................................. 177
Acknowledgement ................................................................................................................................ 178
REFERENCES .......................................................................................................................................... 179
7 SUMMARY ......................................................................................................................................... 185
7.1 Dissertation summary ............................................................................................................... 185
7.1.1 Model development .......................................................................................................... 185
7.1.2 Interference from optically active agents in water ........................................................... 186
7.1.3 Interference from the atmosphere ................................................................................... 187
7.1.4 Time series analyses .......................................................................................................... 188
7.1.5 Spatial Analyses ................................................................................................................. 189
7.2 Future directions ....................................................................................................................... 191
7.2.1 Impacts of temperature increase...................................................................................... 191
7.2.2 Impacts of precipitation change ....................................................................................... 192
7.2.3 Remote sensing of algal species ....................................................................................... 193

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