Evaluating the use of lake sedimentary DNA in palaeolimnology: A comparison with long-term microscopy-based monitoring of the phytoplankton community.

Palaeolimnological records provide valuable information about how phytoplankton respond to long-term drivers of environmental change. Traditional palaeolimnological tools such as microfossils and pigments are restricted to taxa that leave sub-fossil remains, and a method that can be applied to the wider community is required. Sedimentary DNA (sedDNA), extracted from lake sediment cores, shows promise in palaeolimnology, but validation against data from long-term monitoring of lake water is necessary to enable its development as a reliable record of past phytoplankton communities. To address this need, 18S rRNA gene amplicon sequencing was carried out on lake sediments from a core collected from Esthwaite Water (English Lake District) spanning ~105 years. This sedDNA record was compared with concurrent long-term microscopy-based monitoring of phytoplankton in the surface water. Broadly comparable trends were observed between the datasets, with respect to the diversity and relative abundance and occurrence of chlorophytes, dinoflagellates, ochrophytes and bacillariophytes. Up to 20% of genera were successfully captured using both methods, and sedDNA revealed a previously undetected community of phytoplankton. These results suggest that sedDNA can be used as an effective record of past phytoplankton communities, at least over timescales of <100 years. However, a substantial proportion of genera identified by microscopy were not detected using sedDNA, highlighting the current limitations of the technique that require further development such as reference database coverage. The taphonomic processes which may affect its reliability, such as the extent and rate of deposition and DNA degradation, also require further research.

Early warning signals have limited applicability to empirical lake data.

Research aimed at identifying indicators of persistent abrupt shifts in ecological communities, a.k.a regime shifts, has led to the development of a suite of early warning signals (EWSs). As these often perform inaccurately when applied to real-world observational data, it remains unclear whether critical transitions are the dominant mechanism of regime shifts and, if so, which EWS methods can predict them. Here, using multi-trophic planktonic data on multiple lakes from around the world, we classify both lake dynamics and the reliability of classic and second generation EWSs methods to predict whole-ecosystem change. We find few instances of critical transitions, with different trophic levels often expressing different forms of abrupt change. The ability to predict this change is highly processing dependant, with most indicators not performing better than chance, multivariate EWSs being weakly superior to univariate, and a recent machine learning model performing poorly. Our results suggest that predictive ecology should start to move away from the concept of critical transitions, developing methods suitable for predicting resilience loss not limited to the strict bounds of bifurcation theory.

Planktonic functional diversity changes in synchrony with lake ecosystem state.

Managing ecosystems to effectively preserve function and services requires reliable tools that can infer changes in the stability and dynamics of a system. Conceptually, functional diversity (FD) appears as a sensitive and viable monitoring metric stemming from suggestions that FD is a universally important measure of biodiversity and has a mechanistic influence on ecological processes. It is however unclear whether changes in FD consistently occur prior to state responses or vice versa, with no current work on the temporal relationship between FD and state to support a transition towards trait-based indicators. There is consequently a knowledge gap regarding when functioning changes relative to biodiversity change and where FD change falls in that sequence. We therefore examine the lagged relationship between planktonic FD and abundance-based metrics of system state (e.g. biomass) across five highly monitored lake communities using both correlation and cutting edge non-linear empirical dynamic modelling approaches. Overall, phytoplankton and zooplankton FD display synchrony with lake state but each lake is idiosyncratic in the strength of relationship. It is therefore unlikely that changes in plankton FD are identifiable before changes in more easily collected abundance metrics. These results highlight the power of empirical dynamic modelling in disentangling time lagged relationships in complex multivariate ecosystems, but suggest that FD cannot be generically viable as an early indicator. Individual lakes therefore require consideration of their specific context and any interpretation of FD across systems requires caution. However, FD still retains value as an alternative state measure or a trait representation of biodiversity when considered at the system level.

Floating solar panels on reservoirs impact phytoplankton populations: A modelling experiment.

Floating solar photovoltaic (FPV) deployments are increasing globally as the switch to renewable energy intensifies, representing a considerable water surface transformation. FPV installations can potentially impact aquatic ecosystem function, either positively or negatively. However, these impacts are poorly resolved given the challenges of collecting empirical data for field or modelling experiments. In particular, there is limited evidence on the response of phytoplankton to changes in water body thermal dynamics and light climate with FPV. Given the importance of understanding phytoplankton biomass and species composition for managing ecosystem services, we use an uncertainty estimation approach to simulate the effect of FPV coverage and array siting location on a UK reservoir. FPV coverage was modified in 10% increments from a baseline with 0% coverage to 100% coverage for three different FPV array siting locations based on reservoir circulation patterns. Results showed that FPV coverage significantly impacted thermal properties, resulting in highly variable impacts on phytoplankton biomass and species composition. The impacts on phytoplankton were often dependent on array siting location as well as surface coverage. Changes to phytoplankton species composition were offset by the decrease in phytoplankton biomass associated with increasing FPV coverage. We identified that similar phytoplankton biomass reductions could be achieved with less FPV coverage by deploying the FPV array on the water body's faster-flowing area than the central or slower flowing areas. The difference in response dependent on siting location could be used to tailor phytoplankton management in water bodies. Simulation of water body-FPV interactions efficiently using an uncertainty approach is an essential tool to rapidly develop understanding and ultimately inform FPV developers and water body managers looking to minimise negative impacts and maximise co-benefits.

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.

Can reductions in water residence time be used to disrupt seasonal stratification and control internal loading in a eutrophic monomictic lake?

Anthropogenic eutrophication caused by excess loading of nutrients, especially phosphorus (P), from catchments is a major cause of lake water quality degradation. The release of P from bed sediments to the water column, termed internal loading, can exceed catchment P load in eutrophic lakes, especially those that stratify during warm summer periods. Managing internal P loading is challenging, and although a range of approaches have been implemented, long-term success is often limited, requiring lake-specific solutions. Here, we assess the manipulation of lake residence time to inhibit internal loading in Elterwater, a shallow stratifying lake in the English Lake District, UK. Since 2016, additional inflowing water has been diverted into the inner basin of Elterwater to reduce its water residence time, with the intention of limiting the length of the stratified period and reducing internal loading. Combining eight years of field data in a Before-After-Control-Impact study with process-based hydrodynamic modelling enabled the quantification of the residence time intervention effects on stratification length, water column stability, and concentrations of chlorophyll a and P. Annual water residence time was reduced during the study period by around 40% (4.9 days). Despite this change, the lake continued to stratify and developed hypolimnetic anoxia. As a result, there was little significant change in phosphorus (as total or soluble reactive phosphorus) or chlorophyll a concentrations. Summer stratification length was 2 days shorter and 7% less stable with the intervention. Our results suggest that the change to water residence time in Elterwater was insufficient to induce large enough physical changes to improve water quality. However, the minor physical changes suggest the management measure had some impact and that larger changes in water residence time may have the potential to induce reductions in internal loading. Future assessments of management requirements should combine multi-year observations and physical lake modelling to provide improved understanding of the intervention effect size required to alter the physical structure of the lake, leading to increased hypolimnetic oxygen and reduced potential for internal loading.

Phytoplankton and cyanobacteria abundances in mid-21st century lakes depend strongly on future land use and climate projections.

Land use and climate change are anticipated to affect phytoplankton of lakes worldwide. The effects will depend on the magnitude of projected land use and climate changes and lake sensitivity to these factors. We used random forests fit with long-term (1971-2016) phytoplankton and cyanobacteria abundance time series, climate observations (1971-2016), and upstream catchment land use (global Clumondo models for the year 2000) data from 14 European and 15 North American lakes basins. We projected future phytoplankton and cyanobacteria abundance in the 29 focal lake basins and 1567 lakes across focal regions based on three land use (sustainability, middle of the road, and regional rivalry) and two climate (RCP 2.6 and 8.5) scenarios to mid-21st century. On average, lakes are expected to have higher phytoplankton and cyanobacteria due to increases in both urban land use and temperature, and decreases in forest habitat. However, the relative importance of land use and climate effects varied substantially among regions and lakes. Accounting for land use and climate changes in a combined way based on extensive data allowed us to identify urbanization as the major driver of phytoplankton development in lakes located in urban areas, and climate as major driver in lakes located in remote areas where past and future land use changes were minimal. For approximately one-third of the studied lakes, both drivers were relatively important. The results of this large scale study suggest the best approaches for mitigating the effects of human activity on lake phytoplankton and cyanobacteria will depend strongly on lake sensitivity to long-term change and the magnitude of projected land use and climate changes at a given location. Our quantitative analyses suggest local management measures should focus on retaining nutrients in urban landscapes to prevent nutrient pollution from exacerbating ongoing changes to lake ecosystems from climate change.

Making waves. Bridging theory and practice towards multiple stressor management in freshwater ecosystems.

Despite advances in conceptual understanding, single-stressor abatement approaches remain common in the management of fresh waters, even though they can produce unexpected ecological responses when multiple stressors interact. Here we identify limitations restricting the development of multiple-stressor management strategies and address these, bridging theory and practice, within a novel empirical framework. Those critical limitations include that (i) monitoring schemes fall short of accounting for theory on relationships between multiple-stressor interactions and ecological responses, (ii) current empirical modelling approaches neglect the prevalence and intensity of multiple-stressor interactions, and (iii) mechanisms of stressor interactions are often poorly understood. We offer practical recommendations for the use of empirical models and experiments to predict the effects of freshwater degradation in response to changes in multiple stressors, demonstrating this approach in a case study. Drawing on our framework, we offer practical recommendations to support the development of effective management strategies in three general multiple-stressor scenarios.

Strengthening the evidence base for temperature-mediated phenological asynchrony and its impacts.

Climate warming has caused the seasonal timing of many components of ecological food chains to advance. In the context of trophic interactions, the match-mismatch hypothesis postulates that differential shifts can lead to phenological asynchrony with negative impacts for consumers. However, at present there has been no consistent analysis of the links between temperature change, phenological asynchrony and individual-to-population-level impacts across taxa, trophic levels and biomes at a global scale. Here, we propose five criteria that all need to be met to demonstrate that temperature-mediated trophic asynchrony poses a growing risk to consumers. We conduct a literature review of 109 papers studying 129 taxa, and find that all five criteria are assessed for only two taxa, with the majority of taxa only having one or two criteria assessed. Crucially, nearly every study was conducted in Europe or North America, and most studies were on terrestrial secondary consumers. We thus lack a robust evidence base from which to draw general conclusions about the risk that climate-mediated trophic asynchrony may pose to populations worldwide.

Storm impacts on phytoplankton community dynamics in lakes.

In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short-term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well-developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short- and long-term. We summarize the current understanding of storm-induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.

Global lake thermal regions shift under climate change.

Water temperature is critical for the ecology of lakes. However, the ability to predict its spatial and seasonal variation is constrained by the lack of a thermal classification system. Here we define lake thermal regions using objective analysis of seasonal surface temperature dynamics from satellite observations. Nine lake thermal regions are identified that mapped robustly and largely contiguously globally, even for small lakes. The regions differed from other global patterns, and so provide unique information. Using a lake model forced by 21st century climate projections, we found that 12%, 27% and 66% of lakes will change to a lower latitude thermal region by 2080-2099 for low, medium and high greenhouse gas concentration trajectories (Representative Concentration Pathways 2.6, 6.0 and 8.5) respectively. Under the worst-case scenario, a 79% reduction in the number of lakes in the northernmost thermal region is projected. This thermal region framework can facilitate the global scaling of lake-research.

The case for research integration, from genomics to remote sensing, to understand biodiversity change and functional dynamics in the world's lakes.

Freshwater ecosystems are heavily impacted by multiple stressors, and a freshwater biodiversity crisis is underway. This realization has prompted calls to integrate global freshwater ecosystem data, including traditional taxonomic and newer types of data (e.g., eDNA, remote sensing), to more comprehensively assess change among systems, regions, and organism groups. We argue that data integration should be done, not only with the important purpose of filling gaps in spatial, temporal, and organismal representation, but also with a more ambitious goal: to study fundamental cross-scale biological phenomena. Such knowledge is critical for discerning and projecting ecosystem functional dynamics, a realm of study where generalizations may be more tractable than those relying on taxonomic specificity. Integration could take us beyond cataloging biodiversity losses, and toward predicting ecosystem change more broadly. Fundamental biology questions should be central to integrative, interdisciplinary research on causal ecological mechanisms, combining traditional measures and more novel methods at the leading edge of the biological sciences. We propose a conceptual framework supporting this vision, identifying key questions and uncertainties associated with realizing this research potential. Our framework includes five interdisciplinary "complementarities." First, research approaches may provide comparative complementarity when they offer separate realizations of the same focal phenomenon. Second, for translational complementarity, data from one research approach is used to translate that from another, facilitating new inferences. Thirdly, causal complementarity arises when combining approaches allows us to "fill in" cause-effect relationships. Fourth, contextual complementarity is realized when together research methodologies establish the wider ecological and spatiotemporal context within which focal biological responses occur. Finally, integration may allow us to cross inferential scales through scaling complementarity. Explicitly identifying the modes and purposes of integrating research approaches, and reaching across disciplines to establish appropriate collaboration will allow researchers to address major biological questions that are more than the sum of the parts.

Spatial and habitat variation in aphid, butterfly, moth and bird phenologies over the last half century.

Global warming has advanced the timing of biological events, potentially leading to disruption across trophic levels. The potential importance of phenological change as a driver of population trends has been suggested. To fully understand the possible impacts, there is a need to quantify the scale of these changes spatially and according to habitat type. We studied the relationship between phenological trends, space and habitat type between 1965 and 2012 using an extensive UK dataset comprising 269 aphid, bird, butterfly and moth species. We modelled phenologies using generalized additive mixed models that included covariates for geographical (latitude, longitude, altitude), temporal (year, season) and habitat terms (woodland, scrub, grassland). Model selection showed that a baseline model with geographical and temporal components explained the variation in phenologies better than either a model in which space and time interacted or a habitat model without spatial terms. This baseline model showed strongly that phenologies shifted progressively earlier over time, that increasing altitude produced later phenologies and that a strong spatial component determined phenological timings, particularly latitude. The seasonal timing of a phenological event, in terms of whether it fell in the first or second half of the year, did not result in substantially different trends for butterflies. For moths, early season phenologies advanced more rapidly than those recorded later. Whilst temporal trends across all habitats resulted in earlier phenologies over time, agricultural habitats produced significantly later phenologies than most other habitats studied, probably because of nonclimatic drivers. A model with a significant habitat-time interaction was the best-fitting model for birds, moths and butterflies, emphasizing that the rates of phenological advance also differ among habitats for these groups. Our results suggest the presence of strong spatial gradients in mean seasonal timing and nonlinear trends towards earlier seasonal timing that varies in form and rate among habitat types.

Ecological resilience in lakes and the conjunction fallacy.

There is a pressing need to apply stability and resilience theory to environmental management to restore degraded ecosystems effectively and to mitigate the effects of impending environmental change. Lakes represent excellent model case studies in this respect and have been used widely to demonstrate theories of ecological stability and resilience that are needed to underpin preventative management approaches. However, we argue that this approach is not yet fully developed because the pursuit of empirical evidence to underpin such theoretically grounded management continues in the absence of an objective probability framework. This has blurred the lines between intuitive logic (based on the elementary principles of probability) and extensional logic (based on assumption and belief) in this field.

Phenological sensitivity to climate across taxa and trophic levels.

Differences in phenological responses to climate change among species can desynchronise ecological interactions and thereby threaten ecosystem function. To assess these threats, we must quantify the relative impact of climate change on species at different trophic levels. Here, we apply a Climate Sensitivity Profile approach to 10,003 terrestrial and aquatic phenological data sets, spatially matched to temperature and precipitation data, to quantify variation in climate sensitivity. The direction, magnitude and timing of climate sensitivity varied markedly among organisms within taxonomic and trophic groups. Despite this variability, we detected systematic variation in the direction and magnitude of phenological climate sensitivity. Secondary consumers showed consistently lower climate sensitivity than other groups. We used mid-century climate change projections to estimate that the timing of phenological events could change more for primary consumers than for species in other trophic levels (6.2 versus 2.5-2.9 days earlier on average), with substantial taxonomic variation (1.1-14.8 days earlier on average).

Casting your network wide: a plea to scale-up phenological research.

Accumulating scientific evidence has demonstrated widespread shifts in the biological seasons. These shifts may modify seasonal interspecific interactions, with consequent impacts upon reproductive success and survival. However, current understanding of these impacts is based upon a limited number of studies that adopt a simplified 'bottom-up' food-chain paradigm, at a local scale. I argue that there is much insight to be gained by widening the scope of phenological studies to incorporate food-web interactions and landscape-scale processes across a diversity of ecosystem types, with the ultimate goal of developing a generic understanding of the systems most vulnerable to synchrony effects in the future. I propose that co-location of predator and prey phenological monitoring at sentinel sites, acting as research platforms for detailed food-web studies, experimentation and match-up with earth observation data, would be an important first step in this endeavour.