Are Northern Lakes in Relatively Intact Temperate Forests Showing Signs of Increasing Phytoplankton Biomass?

Paltsev, Aleksey; Creed, Irena F.

doi:10.1007/s10021-021-00684-y

Cited by 15 publications

(12 citation statements)

References 134 publications

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“…Our analysis showed that most lakes (55%) included in this study showed no substantial change in lake color between 1984 and 2020. This is consistent with both remote sensing and field studies of regional lake water quality trends in arctic (Kuhn and Butman, 2021) and temperate regions (Oliver et al, 2017;Paltsev and Creed, 2021) that showed a minority of study lakes to be exhibiting changes in lake color. For lakes in the Rocky Mountain region that changed over the past 36 years, most trended bluer (70%), suggesting an overall improvement in summer water quality.…”

Section: Discussionsupporting

confidence: 88%

Heterogenous controls on lake color and trends across the high-elevation U.S. Rocky Mountain region

Oleksy¹,

Collins²,

Sillen³

et al. 2022

Preprint

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Global change may be contributing to changes in high-elevation lakes and reservoirs, but a lack of data makes it difficult to evaluate spatiotemporal patterns. Remote sensing imagery can provide more complete records to evaluate whether consistent changes across a broad geographic region are occurring. We used Landsat surface reflectance data to evaluate spatial patterns of contemporary lake color (2009-2020) in 956 lakes in the Rocky Mountains. Intuitively, we found that most blue or clear lakes were in steep-sided watersheds (>22º) or alternatively were relatively deep (>2.5m mean depth) with mean annual air temperature (MAAT) <4.5 ºC. Most green/brown lakes were situated in warmer areas (MAAT (>4.5 ºC) with shallow watershed slopes (<22º). We extended the analysis of contemporary lake color to evaluate changes in color from 1984-2020 for a subset of lakes with the most complete time series (n=527). We found limited evidence of lakes shifting from blue to green states, but rather, 55% of the lakes had no trend in lake color, 32% of lakes were trending toward bluer wavelengths, and only 13% shifting toward greener wavelengths. Lakes and reservoirs with the most substantial shifts toward blue wavelengths tended to be in urbanized, human population centers at relatively lower elevations. In contrast, lakes that shifted to greener wavelengths did not relate clearly to any lake or landscape features that we evaluated, though declining winter precipitation and warming summer and fall temperatures may play a role in some systems. Collectively, these results suggest that the interactions between local landscape factors and broader climatic changes can result in heterogeneous, context-dependent changes in lake color.

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Section: Discussionsupporting

confidence: 88%

Heterogenous controls on lake color and trends across the high-elevation U.S. Rocky Mountain region

Oleksy¹,

Collins²,

Sillen³

et al. 2022

Preprint

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“…Chl‐ a was modeled for the lakes of the temperate forest biome using remote sensing techniques (for details see Paltsev & Creed, 2021). We acquired 1067 Landsat 4–5 TM and 159 Landsat 7 ETM+ (30‐m) images from the United States Geological Survey archives over the study region for the period of August to October for 28 years (1984–2011; Figure 1).…”

Section: Methodsmentioning

confidence: 99%

“…Recently, we have shown that phytoplankton biomass is changing in many northern temperate lakes (Paltsev & Creed, 2021). We expected that broad‐scale temporal factors (e.g., climate) accounted for most of the variation in phytoplankton biomass and that the lakes responded to climate signals in a uniform manner.…”

Section: Introductionmentioning

confidence: 99%

“…Phytoplankton biomass in lakes often does not show synchronous behavior in response to climate factors (Baines et al, 2000; Freeman et al, 2020; Kraemer et al, 2017; Oliver et al, 2017; Paltsev & Creed, 2021) because catchment‐ and lake‐specific properties modify regional climate signals (Blenckner, 2005; Hollert et al, 2018; Palmer et al, 2014). Catchment properties (i.e., catchment size, topography, vegetation and soil type, and the presence of wetlands) affect the source, storage, and transport of water and nutrients (e.g., dissolved organic matter (DOM), nitrogen (N), and phosphorus (P)) to receiving waters (Creed et al, 1996; Creed & Beall, 2009; Kayler et al, 2019; Mengistu et al, 2014; Nõges, 2009; Staehr et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

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Multi‐decadal changes in phytoplankton biomass in northern temperate lakes as seen through the prism of landscape properties

Paltsev

Creed

2022

Global Change Biology

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Northern temperate lakes are being affected by global environmental changes (Bedford et al., 2020;Richardson et al., 2018).An increase in temperature and changes in precipitation patterns and atmospheric nitrogen deposition are leading to fundamental alterations in land-aquatic hydrological and biogeochemical linkages (Creed et al., 2018). These environmental changes can be best studied in lakes, as lakes integrate atmospheric, terrestrial, and aquatic processes (Williamson et al., 2009). An important signal of alterations is an increase in the frequency and duration of phytoplankton blooms (Ho et al., 2019;Winter et al., 2011) as well as changes in

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“…However, monitoring of lake chl-a with Landsat is limited by a poor signal-noise ratio (particularly with Landsat 5 TM (1984 and 7 ETM+ (effective 1999-2003) sensors), relative to other available satellite sensors (e.g., Landsat 8 OLI (2013-present), Sentinel 3-A (2016-present)), and by wide radiometric bands [11,12]. Despite these limitations, Landsat has a long history of being used as a remote measuring system for chl-a at small spatial and temporal scales [13][14][15][16][17][18][19][20][21][22]. Other remote sensors may be more precise in discerning finer resolution spectral signals; however, because of its long time series, further analysis of Landsat product applicability will be instrumental in predicting historical surface algal biomass.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Landsat Chl-a Retrieval Algorithms in Freshwater Lakes through Classification of Optical Water Types

Dallosch

Creed

2021

Remote Sensing

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The application of remote sensing data to empirical models of inland surface water chlorophyll-a concentrations (chl-a) has been in development since the launch of the Landsat 4 satellite series in 1982. However, establishing an empirical model using a chl-a retrieval algorithm is difficult due to the spatial heterogeneity of inland lake water properties. Classification of optical water types (OWTs; i.e., differentially observed water spectra due to differences in water properties) has grown in favour in recent years over traditional non-turbid vs. turbid classifications. This study examined whether top-of-atmosphere reflectance observations in visible to near-infrared bands from Landsat 4, 5, 7, and 8 sensors can be used to identify unique OWTs using a guided unsupervised classification approach in which OWTs are defined through both remotely sensed reflectance and surface water chemistry data taken from samples in North American and Swedish lakes. Linear regressions of algorithms (Landsat reflectance bands, band ratios, products, or combinations) to lake surface water chl-a were built for each OWT. The performances of chl-a retrieval algorithms within each OWT were compared to those of global chl-a algorithms to test the effectiveness of OWT classification. Seven unique OWTs were identified and then fit into four categories with varying degrees of brightness as follows: turbid lakes with a low chl-a:turbidity ratio; turbid lakes with a mixture of high chl-a and turbidity measurements; oligotrophic or mesotrophic lakes with a mixture of low chl-a and turbidity measurements; and eutrophic lakes with a high chl-a:turbidity ratio. With one exception (r2 = 0.26, p = 0.08), the best performing algorithm in each OWT showed improvement (r2 = 0.69–0.91, p < 0.05), compared with the best performing algorithm for all lakes combined (r2 = 0.52, p < 0.05). Landsat reflectance can be used to extract OWTs in inland lakes to provide improved prediction of chl-a over large extents and long time series, giving researchers an opportunity to study the trophic states of unmonitored lakes.

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Are Northern Lakes in Relatively Intact Temperate Forests Showing Signs of Increasing Phytoplankton Biomass?

Cited by 15 publications

References 134 publications

Heterogenous controls on lake color and trends across the high-elevation U.S. Rocky Mountain region

Heterogenous controls on lake color and trends across the high-elevation U.S. Rocky Mountain region

Multi‐decadal changes in phytoplankton biomass in northern temperate lakes as seen through the prism of landscape properties

Optimization of Landsat Chl-a Retrieval Algorithms in Freshwater Lakes through Classification of Optical Water Types

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