Regime shifts observed in Lake Kasumigaura, a large shallow lake in Japan: Analysis of a 40‐year limnological record

Fukushima, Takehiko; Arai, Hiroyuki

doi:10.1111/lre.12085

Cited by 19 publications

(10 citation statements)

References 45 publications

(84 reference statements)

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“…, , Tomioka et al. , Fukushima and Arai ). For zooplankton, we used the abundances of five zooplankton functional groups (large cladocerans, small cladocerans, rotifers, cyclopoids, and calanoids; Takamura et al.…”

Section: Introductionmentioning

confidence: 98%

“…We applied CCM to a long-term monitoring data set for Lake Kasumigaura (1996Kasumigaura ( -2015 and quantified the presence and direction of the causal relationships between environmental variables, phytoplankton community composition, primary production, and zooplankton. We considered light availability, water temperature, and dissolved nutrients as environmental drivers, because these factors have been reported to affect primary production or phytoplankton biomass (Takamura et al 1987, Tomioka et al 2011, Fukushima and Arai 2015. For zooplankton, we used the abundances of five zooplankton functional groups (large cladocerans, small cladocerans, rotifers, cyclopoids, and calanoids; Takamura et al 2017).…”

Section: Introductionmentioning

confidence: 99%

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Bottom‐up linkages between primary production, zooplankton, and fish in a shallow, hypereutrophic lake

Matsuzaki

Suzuki

Kadoya

et al. 2018

Ecology

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Nutrient supply is a key bottom-up control of phytoplankton primary production in lake ecosystems. Top-down control via grazing pressure by zooplankton also constrains primary production and primary production may simultaneously affect zooplankton. Few studies have addressed these bidirectional interactions. We used convergent cross-mapping (CCM), a numerical test of causal associations, to quantify the presence and direction of the causal relationships among environmental variables (light availability, surface water temperature, NO -N, and PO -P), phytoplankton community composition, primary production, and the abundances of five functional zooplankton groups (large cladocerans, small cladocerans, rotifers, calanoids, and cyclopoids) in Lake Kasumigaura, a shallow, hypereutrophic lake in Japan. CCM suggested that primary production was causally influenced by NO -N and phytoplankton community composition; there was no detectable evidence of a causal effect of zooplankton on primary production. Our results also suggest that rotifers and cyclopoids were forced by primary production, and cyclopoids were further influenced by rotifers. However, our CCM suggested that primary production was weakly influenced by rotifers (i.e., bidirectional interaction). These findings may suggest complex linkages between nutrients, primary production, and rotifers and cyclopoids, a pattern that has not been previously detected or has been neglected. We used linear regression analysis to examine the relationships between the zooplankton community and pond smelt (Hypomesus nipponensis), the most abundant planktivore and the most important commercial fish species in Lake Kasumigaura. The relative abundance of pond smelt was significantly and positively correlated with the abundances of rotifers and cyclopoids, which were causally influenced by primary production. This finding suggests that bottom-up linkages between nutrient, primary production, and zooplankton abundance might be a key mechanism supporting high planktivore abundance in eutrophic lakes. Because increases in primary production and cyanobacteria blooms are likely to occur simultaneously in hypereutrophic lakes, our study highlights the need for ecosystem management to resolve the conflict between good water quality and high fishery production.

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Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Bottom‐up linkages between primary production, zooplankton, and fish in a shallow, hypereutrophic lake

Matsuzaki

Suzuki

Kadoya

et al. 2018

Ecology

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“…1). The lake is characterized by high turbidity and eutrophic conditions (total phosphorus [TP]: 0.084 mg l −1 , total nitrogen [TN]: 1.01 mg l −1 from 1979 to 2016 at St. 1) due to its shallowness (mean depth of 3.4 m; maximum depth of 7.3 m) and intensive human activity in the watersheds [20]. Its 1426km 2 catchment area (excluding the lake area) is about 30% forests, 25% paddy fields, 25% plowed field, 10% residential and 10% other.…”

Section: Study Sitementioning

confidence: 99%

“…Changes in sediment resuspension rate [13], formation of calcite [14] and so on were suspected reasons for high turbidity [15]. Furthermore, this high turbidity probably affected silicon and phosphorus concentrations in lake water [16,17], and phytoplankton species composition [18,19], thus bringing about a regime shift in the ecosystem [20]. However, the changes in tripton during the last several decades have not been quantitatively assessed, and the reason(s) for variation in sediment resuspension have not been clarified.…”

Section: Introductionmentioning

confidence: 99%

Decadal change in tripton concentration in a shallow lake

et al. 2019

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In shallow polymictic lakes where the resuspension of sediments frequently occurs, tripton (non-living particulate materials) can affect physical, chemical and biological processes. Over the last four decades, substantial changes in tripton concentrations and therefore limnological parameters have been observed in Lake Kasumigaura, a shallow eutrophic lake.To build a conceptual model of the various relationships between these, we analyzed data on monthly water and yearly sediment quality at several stations together with meteorological information. Large short-term and decadal variations were characteristics for tripton. Annual averages in tripton concentration changed substantially (e.g., from 3 to 25 mg l −1 at the lake center), peaking in the early 2000s, when phosphorus and silicon in water were high, and we observed a large proportion of diatoms in phytoplankton and low light penetration. Tripton concentration showed a positive correlation with sediment water content (WC) and a negative one with sediment ignition loss (IL) with a few years' delay, confirming the results of previous hydraulic experiments. Using these parameters, multiple regression models for estimating tripton concentrations were constructed and showed good performances (e.g., adjusted r 2 = 0.61 at the center). Furthermore, changes in inorganic ions in water, probably resulting from meteorological variations, were inferred to bring about changes in sediment WC. On the other hand, the amount of Microcystis sp. in water was suspected to govern the sediment IL. We reveal many processes (physical, chemical, biological and meteorological phenomena) related to tripton, and thus, their relationships could be considered a conceptual model for a shallow lake.

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“…Takamura et al 1992, Tomioka et al 2011, Fukushima and Arai 2015. Nitrate determined four out of seven phytoplankton groups.…”

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confidence: 98%

Decomposing predictability to identify dominant causal drivers in complex ecosystems

Suzuki

Matsuzaki

Masuya

2022

Preprint

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Ecosystems are complex systems of various physical, biological, and chemical processes. Since ecosystem datasets are composed of a mixture of different levels of stochasticity and nonlinearity, handling these data is a challenge for existing methods of time-series based causal inferences. Here we show that, by harnessing contemporary machine learning approaches, the concept of Granger causality can be effectively extended to the analysis of complex ecosystem time series and bridge the gap between dynamical and statistical approaches. The central idea is to use an ensemble of fast and highly predictive artificial neural networks to select a minimal set of variables that maximizes the prediction of a given variable. It enables decomposition of the relationship among variables through quantifying the contribution of an individual variable to the overall predictive performance. We show how our approach, EcohNet, can improve interaction network inference for a mesocosm experiment and simulated ecosystems. The application of the method to a long-term lake monitoring dataset yielded new but interpretable results on the drivers causing cyanobacteria blooms, which is a serious threat to ecological integrity and ecosystem services. Since performance of EcohNet is enhanced by its predictive capabilities, it also provides an optimized forecasting of overall components in complex ecosystems. EcohNet could be used to analyze complex and hybrid multivariate time series in many scientific areas not limited to ecosystems.

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Regime shifts observed in Lake Kasumigaura, a large shallow lake in Japan: Analysis of a 40‐year limnological record

Cited by 19 publications

References 45 publications

Bottom‐up linkages between primary production, zooplankton, and fish in a shallow, hypereutrophic lake

Bottom‐up linkages between primary production, zooplankton, and fish in a shallow, hypereutrophic lake

Decadal change in tripton concentration in a shallow lake

Decomposing predictability to identify dominant causal drivers in complex ecosystems

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