Long-term warming destabilizes aquatic ecosystems through weakening biodiversity-mediated causal networks

Temporal shifts in the phytoplankton network in a large eutrophic shallow freshwater lake subjected to major environmental changes due to human interventions

Phytoplankton communities are crucial components of aquatic ecosystems, and since they are highly interactive, they always form complex networks. Yet, our understanding of how interactive phytoplankton networks vary through time under changing environmental conditions is limited. Using a 29-year (339 months) long-term dataset on Lake Taihu, China, we constructed a temporal network comprising monthly sub-networks using "extended Local Similarity Analysis" and assessed how eutrophication, climate change, and restoration efforts influenced the temporal dynamics of network complexity and stability. The network architecture of phytoplankton showed strong dynamic changes with varying environments. Our results revealed cascading effects of eutrophication and climate change on phytoplankton network stability via changes in network complexity. The network stability of phytoplankton increased with average degree, modularity, and nestedness and decreased with connectance. Eutrophication (increasing nitrogen) stabilized the phytoplankton network, mainly by increasing its average degree, while climate change, i.e., warming and decreasing wind speed enhanced its stability by increasing the cohesion of phytoplankton communities directly and by decreasing the connectance of network indirectly. A remarkable shift and a major decrease in the temporal dynamics of phytoplankton network complexity (average degree, nestedness) and stability (robustness, persistence) were detected after 2007 when numerous eutrophication mitigation efforts (not all successful) were implemented, leading to simplified phytoplankton networks and reduced stability. Our findings provide new insights into the organization of phytoplankton networks under eutrophication (or re-oligotrophication) and climate change in subtropical shallow lakes.

Reduced precipitation can induce ecosystem regime shifts in lakes by increasing internal nutrient recycling

Eutrophication is a main threat to continental aquatic ecosystems. Prevention and amelioration actions have been taken under the assumption of a stable climate, which needs reconsideration. Here, we show that reduced precipitation can bring a lake ecosystem to a more productive regime even with a decline in nutrient external load. By analyzing time series of several decades in the largest lake of the Iberian Peninsula, we found autocorrelated changes in the variance of state variables (i.e., chlorophyll and oxygen) indicative of a transient situation towards a new ecosystem regime. Indeed, exceptional planktonic diatom blooms have occurred during the last few years, and the sediment record shows a shift in phytoplankton composition and an increase in nutrient retention. Reduced precipitation almost doubled the water residence time in the lake, enhancing the relevance of internal processes. This study demonstrates that ecological quality targets for aquatic ecosystems must be tailored to the changing climatic conditions for appropriate stewardship.

Integrated evaluation of the impact of water diversion on water quality index and phytoplankton assemblages of eutrophic lake: A case study of Yilong Lake

Water diversion has been widely utilized to enhance lake water quality and mitigate cyanobacterial blooms. However, previous studies have mainly focused on investigating the effects of water diversion on water quality or aquatic ecological health. Consequently, there is limited research investigating the combined impact of water diversion on the water quality and the ecological health of eutrophic lakes, and whether the WQI and phytoplankton assemblages demonstrate similar patterns following water diversion. In this study, the effects of water diversion on the ecosystem health of eutrophic lakes were comprehensively evaluated based on the WQI indices and phytoplankton assemblages during the NWDP-21 and WDP-22. The results showed that the annual mean of WQI increased from 52.02 to 54.36 after water diversion, which improved the water quality of the lake, especially NH3-N and TN decreased by 58.6% and 15.2%, respectively. The phytoplankton assemblages changed significantly before and after water diversion, and we observed that the total biomass of phytoplankton decreased by 12.3% and phytoplankton diversity indices (Shannon-Wiener diversity, Pielou evenness, and Simpson index) increased by 8.6%-8.9% after water diversion, with an improvement in the connectivity and stability of the phytoplankton. Notably, enhanced adaptations of rare sub-communities for resource use in water diversion environments, and water diversion inhibited the dispersal ability of dominant functional groups, and the effects of hydrological disturbances on the structure of phytoplankton assemblage favored the ecological health of eutrophic lakes. VPA analysis further reveals that water diversion alters the drivers of phytoplankton functional group biomass and phytoplankton diversity. The results of the PLS-PM analysis clarify that water diversion indirectly impacts the total phytoplankton biomass and phytoplankton diversity primarily by modifying light availability. Significant correlations are observed between the dominant functional groups biomass and diversity indices of WQI. The trends in changes observed in water quality indices and phytoplankton following water diversion align with the evaluation of water ecological health. This study provides valuable guidance for the ecological management of the diversion project in Yilong Lake and serves as a reference for similar projects in other lakes.

Weakened casual feedback loops following intensive restoration efforts and climate changes in a large shallow freshwater lake

Understanding how phytoplankton interacts with local and regional drivers as well as their feedbacks is a great challenge, and quantitative analyses of the regulating role of human activities and climate changes on these feedback loops are also limited. By using monthly monitoring dataset (2000-2017) from Lake Taihu and empirical dynamic modelling to construct causal networks, we quantified the strengths of causal feedbacks among phytoplankton, local environments, zooplankton, meteorology as well as global climate oscillation. Prevalent bidirectional causal linkages between phytoplankton biomass (chlorophyll a) and the tested drivers were found, providing holistic and quantitative evidence of the ubiquitous feedback loops. Phytoplankton biomass exhibited the highest feedbacks with total inorganic nitrogen and ammonia and the lowest with nitrate. The feedbacks between phytoplankton biomass and environmental factors from 2000 to 2017 could be classified into two groups: the local environments (e.g., nutrients, pH, transparency, zooplankton biomass)-driven enhancement loops promoting the response of the phytoplankton biomass, and the climate (e.g., wind speed)-driven regulatory loops suppressing it. The two counterbalanced groups modified the emergent macroecological patterns. Our findings revealed that the causal feedback networks loosened significantly after 2007 following nutrient loading reduction and unsuccessful biomanipulation restoration attempts by stocking carp. The strength of enhancement loops underwent marked decreases leading to reduced phytoplankton responses to the tested drivers, while the climate (decreasing wind speed, warming winter)-driven regulatory loops increased- like a tug-of-war. To counteract the self-amplifying feedback loops, the present eutrophication mitigation efforts, especially nutrient reduction, should be continued, and introduction of alternative measures to indirectly regulate the critical components (e.g., pH, Secchi depth, zooplankton biomass) of the loops would be beneficial.

Core taxa drive microeukaryotic community stability of a deep subtropical reservoir after complete mixing

Microeukaryotes are key for predicting the change of ecosystem processes in the face of a disturbance. However, their vertical responses to multiple interconnected factors caused by water mixing remain unknown. Here, we conducted a 12-month high-frequency study to compare the impacts of mixing disturbances on microeukaryotic community structure and stability over different depths in a stratified reservoir. We demonstrate that core and satellite microeukaryotic compositions and interactions in surface waters were not resistant to water mixing, but significantly recovered. This was because the water temperature rebounded to the pre-mixing level. Core microeukaryotes maintained community stability in surface waters with high recovery capacity after water mixing. In contrast, the changes in water temperature, chlorophyll-a, and nutrients resulted in steep and prolonged variations in the bottom core and satellite microeukaryotic compositions and interactions. Under low environmental fluctuation, the recovery of microbial communities did not affect nutrient cycling in surface waters. Under high environmental fluctuation, core and satellite microeukaryotic compositions in bottom waters were significantly correlated with the multi-nutrient cycling index. Our findings shed light on different mechanisms of plankton community resilience in reservoir ecosystems to a major disturbance over depths, highlighting the role of bottom microeukaryotes in nutrient cycling.

Enhanced causal effect of ecosystem photosynthesis on respiration during heatwaves

Because of global warming, Earth's ecosystems have been experiencing more frequent and severe heatwaves. Heatwaves are expected to tip terrestrial carbon sequestration by elevating ecosystem respiration and suppressing gross primary productivity (GPP). Here, using the convergent cross-mapping technique, this study detected positive bidirectional causal effects between GPP and respiration in two unprecedented European heatwaves. Heatwaves enhanced the causal effect strength of GPP on respiration rather than respiration on GPP across 40 site-years of observations. Further analyses and global simulations revealed spatial heterogeneity in the heatwave response of the causal link strength between GPP and respiration, which was jointly driven by the local climate and vegetation properties. However, the causal effect strength of GPP on respiration showed considerable uncertainties in CMIP6 models. This study reveals an enhanced causal link strength between GPP and respiration during heatwaves, shedding light on improving projections for terrestrial carbon sink dynamics under future climate extremes.

A framework for the detection and attribution of biodiversity change

The causes of biodiversity change are of great scientific interest and central to policy efforts aimed at meeting biodiversity targets. Changes in species diversity and high rates of compositional turnover have been reported worldwide. In many cases, trends in biodiversity are detected, but these trends are rarely causally attributed to possible drivers. A formal framework and guidelines for the detection and attribution of biodiversity change is needed. We propose an inferential framework to guide detection and attribution analyses, which identifies five steps-causal modelling, observation, estimation, detection and attribution-for robust attribution. This workflow provides evidence of biodiversity change in relation to hypothesized impacts of multiple potential drivers and can eliminate putative drivers from contention. The framework encourages a formal and reproducible statement of confidence about the role of drivers after robust methods for trend detection and attribution have been deployed. Confidence in trend attribution requires that data and analyses used in all steps of the framework follow best practices reducing uncertainty at each step. We illustrate these steps with examples. This framework could strengthen the bridge between biodiversity science and policy and support effective actions to halt biodiversity loss and the impacts this has on ecosystems. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Shift of phytoplankton assemblages in a temperate lake located on the eastern route of the South-to-North Water Diversion Project

There remains no consensus on the effects of changes in the environment factors under the action of water diversions on phytoplankton communities. Herein the changing rules applying to phytoplankton communities subject to water diversion were unveiled based on long-term (2011-2021) time-series observations on Luoma Lake, located on the eastern route of the South-to-North Water Diversion Project. We found that nitrogen decreased and then increased, while phosphorus increased after operation of the water transfer project. Algal density and diversity were not affected by water diversion, while the duration of high algal density was shorter after water diversion. Phytoplankton composition had dramatic differences before and after water transfer. The phytoplankton communities exhibited greater fragility when they first experienced a human-mediated disturbance, and then they gradually adapted to more interferences and acquired stronger stability. We furthermore found the niche of Cyanobacteria narrowed while that of Euglenozoa widened under the pressure of water diversion. In addition to WT and DO, the main environmental factor before water diversion was NH₄-N, whereas the effect of NO₃-N and TN on phytoplankton communities increased after water diversion. These findings fill the knowledge gap as to the consequence of water diversion on water environments and phytoplankton communities.

Relationships of temperature and biodiversity with stability of natural aquatic food webs

Temperature and biodiversity changes occur in concert, but their joint effects on ecological stability of natural food webs are unknown. Here, we assess these relationships in 19 planktonic food webs. We estimate stability as structural stability (using the volume contraction rate) and temporal stability (using the temporal variation of species abundances). Warmer temperatures were associated with lower structural and temporal stability, while biodiversity had no consistent effects on either stability property. While species richness was associated with lower structural stability and higher temporal stability, Simpson diversity was associated with higher temporal stability. The responses of structural stability were linked to disproportionate contributions from two trophic groups (predators and consumers), while the responses of temporal stability were linked both to synchrony of all species within the food web and distinctive contributions from three trophic groups (predators, consumers, and producers). Our results suggest that, in natural ecosystems, warmer temperatures can erode ecosystem stability, while biodiversity changes may not have consistent effects.

Disruption of ecological networks in lakes by climate change and nutrient fluctuations

Climate change interacts with local processes to threaten biodiversity by disrupting the complex network of ecological interactions. While changes in network interactions drastically affect ecosystems, how ecological networks respond to climate change, in particular warming and nutrient supply fluctuations, is largely unknown. Here, using an equation-free modelling approach on monthly plankton community data in ten Swiss lakes, we show that the number and strength of plankton community interactions fluctuate and respond nonlinearly to water temperature and phosphorus. While lakes show system-specific responses, warming generally reduces network interactions, particularly under high phosphate levels. This network reorganization shifts trophic control of food webs, leading to consumers being controlled by resources. Small grazers and cyanobacteria emerge as sensitive indicators of changes in plankton networks. By exposing the outcomes of a complex interplay between environmental drivers, our results provide tools for studying and advancing our understanding of how climate change impacts entire ecological communities.

Decomposing predictability to identify dominant causal drivers in complex ecosystems

Ecosystems are complex systems of various physical, biological, and chemical processes. Since ecosystem dynamics 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 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 ecosystems. EcohNet could be used to analyze complex and hybrid multivariate time series in many scientific areas not limited to ecosystems.

Causal networks of phytoplankton diversity and biomass are modulated by environmental context

Untangling causal links and feedbacks among biodiversity, ecosystem functioning, and environmental factors is challenging due to their complex and context-dependent interactions (e.g., a nutrient-dependent relationship between diversity and biomass). Consequently, studies that only consider separable, unidirectional effects can produce divergent conclusions and equivocal ecological implications. To address this complexity, we use empirical dynamic modeling to assemble causal networks for 19 natural aquatic ecosystems (N24^◦~N58^◦) and quantified strengths of feedbacks among phytoplankton diversity, phytoplankton biomass, and environmental factors. Through a cross-system comparison, we identify macroecological patterns; in more diverse, oligotrophic ecosystems, biodiversity effects are more important than environmental effects (nutrients and temperature) as drivers of biomass. Furthermore, feedback strengths vary with productivity. In warm, productive systems, strong nitrate-mediated feedbacks usually prevail, whereas there are strong, phosphate-mediated feedbacks in cold, less productive systems. Our findings, based on recovered feedbacks, highlight the importance of a network view in future ecosystem management.

Disentangling causal interactions among biodiversity, ecosystem functioning and environmental factors is key to understanding how ecosystems respond to changing environment. This study presents a global scale analysis quantifying causal interactions and feedbacks among phytoplankton diversity, biomass and nutrients along environmental gradients of aquatic ecosystems.

Beyond Experiments

It is often claimed that only experiments can support strong causal inferences and therefore they should be privileged in the behavioral sciences. We disagree. Overvaluing experiments results in their overuse both by researchers and decision makers and in an underappreciation of their shortcomings. Neglect of other methods often follows. Experiments can suggest whether X causes Y in a specific experimental setting; however, they often fail to elucidate either the mechanisms responsible for an effect or the strength of an effect in everyday natural settings. In this article, we consider two overarching issues. First, experiments have important limitations. We highlight problems with external, construct, statistical-conclusion, and internal validity; replicability; and conceptual issues associated with simple X causes Y thinking. Second, quasi-experimental and nonexperimental methods are absolutely essential. As well as themselves estimating causal effects, these other methods can provide information and understanding that goes beyond that provided by experiments. A research program progresses best when experiments are not treated as privileged but instead are combined with these other methods.

Nonlinear causal analysis reveals an effective water level regulation approach for phytoplankton blooms controlling in reservoirs

Reservoirs are a rapidly increasing water body providing water supply, irrigation, and many other benefits for human societies globally. However, due to changes in hydrological conditions, building reservoirs tends to bring adverse effects such as eutrophication and phytoplankton blooms, reducing the ecosystem service values. This study focuses on using the empirical dynamic modeling (EDM), an emerging approach for nonlinear analysis, to investigate the nonlinear causal relationship of water level fluctuation (WLF) on phytoplankton biomass and then develop a quantitative model guiding effective phytoplankton blooms controlling based on water level regulations in reservoirs. Specifically, with 9-year continued daily observed data in the Three Gorges Reservoir, we examined the causal effects of different WLF parameters on the dynamics of phytoplankton blooms for the first time. We found that the water level change in the past 24 h (ΔWL) has the strongest causal effect on the daily dynamics of phytoplankton biomass among all WLF parameters (ΔWL, |ΔWL|, and the water level), with a time lag of 2 days. Moreover, EDM revealed a nonlinear relationship between ΔWL and daily dynamics of phytoplankton biomass and achieved a successful prediction for the chlorophyll a concentration 2-day ahead. Further scenario analyses found that both the rise and fall of water level will significantly reduce the chlorophyll a concentration when phytoplankton blooms occur. Nevertheless, on the whole, the rising water level has a more substantial effect on phytoplankton blooms than falling the water level. This result reveals that regulating ΔWL is a simple and effective approach in controlling phytoplankton blooms in reservoirs. Our study reported the nonlinear causal effect of ΔWL on the dynamics of chlorophyll a and provided a quantitative approach guiding effective phytoplankton blooms controlling based on the water level regulation, which might have a broad application in algal blooms controlling in reservoirs and similar waterbodies.

Reconstructing large interaction networks from empirical time series data

Reconstructing interactions from observational data is a critical need for investigating natural biological networks, wherein network dimensionality is usually high. However, these pose a challenge to existing methods that can quantify only small interaction networks. Here, we proposed a novel approach to reconstruct high-dimensional interaction Jacobian networks using empirical time series without specific model assumptions. This method, named "multiview distance regularised S-map," generalised the state space reconstruction to accommodate high dimensionality and overcome difficulties in quantifying massive interactions with limited data. When evaluating this method using time series generated from theoretical models involving hundreds of interacting species, estimated strengths of interaction Jacobians were in good agreement with theoretical expectations. Applying this method to a natural bacterial community helped identify important species from the interaction network and revealed mechanisms governing the dynamical stability of a bacterial community. The proposed method overcame the challenge of high dimensionality in large natural dynamical systems.

Physiological responses and molecular strategies in heart of silver carp (Hypophthalmichthys molitrix) under hypoxia and reoxygenation

A sufficient oxygen concentration is essential for fish growth, reproduction, and metabolism. Silver carp (Hypophthalmichthys molitrix) is sometimes challenged by hypoxia during intensive aquaculture or because of environmental changes. However, the response to hypoxic stress in the heart of silver carp remains relatively unknown. In the present study, we reported the effects of hypoxia on histological structures, enzyme activities, and gene expression in the heart of silver carp. Hematoxylin and eosin (H&E) staining of heart sections showed that the myocardial fibers gradually became disordered, swollen, and even ruptured during hypoxic treatment. These phenotypes were also supported by increased activities of injury-related enzymes. Moreover, the transcriptome was analyzed to determine the molecular strategies of hypoxia adaptation in the heart. PI3K-Akt signaling pathway, FoxO signaling pathway, and JAK-STAT signaling pathway were the most prominent pathways activated by hypoxia. Twenty significantly differentially expressed genes were selected to create a network diagram related to cell proliferation, carbohydrate metabolism, oxidative stress, and angiogenesis. Additionally, reoxygenation could ameliorate cardiac injury and eliminate the effects of hypoxia on gene expression. This was the first comparative transcriptomic study to explore the molecular mechanism of the response to hypoxia and reoxygenation in the heart of silver carp. Our results provide a theoretical basis for cultivating hypoxia-tolerant carp varieties in the future.

Promotion of the Development of Sentinel Species in the Water Column: Example Using Body Size and Fecundity of the Egg-Bearing Calanoid Copepod Eurytemora affinis

The development of sentinel species in aquatic ecosystems is mostly based on benthic organisms; however, organisms living in water column such as zooplankton have received less attention, except for some cladocerans. In this paper, a new ecological indicator based on simple measurements of the size and fecundity of egg-bearing calanoid copepods is developed. The well-studied estuarine copepod Eurytemora affinis is used to illustrate this new framework. A large database obtained from laboratory experiments developed under different conditions is used to define a reference regression line between clutch size (CS) and prosome length (PL). The same database allowed one to confirm that the coefficient of variation (CV) of CS is an adequate estimator of the accumulated stress at population level. The CV of PL shows very little variability in all experimental and field conditions. The values of CS and PL obtained from the Seine, Loire, Gironde, Scheldt and Elbe estuaries in Europe are compared to the reference regression line. A quality index (QI) is calculated as a percentage of difference between the observed and the predicted CS. The QI classified 19 samples collected in the Seine estuary between 2004 and 2010 into four classes according to the physiological condition of the copepod female. A single sampling from June 2004 (5.26%) showed a very good condition, whereas 57.9% of the sampling dates confirmed good conditions. On the other hand, four sampling dates were associated to very bad conditions and three sampling dates indicated bad conditions. Seven additional samples obtained from other European estuaries between 2006 and 2009 were also used. Females showing poor conditions were observed in the early spring of 2005 and 2008 as well as during the month of November. These years were characterized by very strong climatic anomalies with a very cold late winter in 2005 and a warm winter in 2008. Therefore, it seems that the QI perfectly reflected the strong stress caused by the sudden change in hydro-climatic conditions that have certainly affected the physiology of copepod females and probably the availability of food. The new indicator is very simple to calculate and can be generalised to several aquatic ecosystems (fresh water and brackish water) by targeting the dominating egg-bearing calanoid copepods. As in the case of E. affinis, the development of sentinel species based on copepods or cladocerans can enrich ecological and ecotoxicological studies given their capacity to integrate the variability of their habitats’ quality at the individual and population levels.