Effects of re-oligotrophication and climate warming on plankton richness and community stability in a deep mesotrophic lake

Re-oligotrophication and warming stabilize phytoplankton networks

Phytoplankton taxa are strongly interconnected as a network, which could show temporal dynamics and non-linear responses to changes in drivers at both seasonal and long-term scale. Using a high quality dataset of 20 Danish lakes (1989-2008), we applied extended Local Similarity Analysis to construct temporal network of phytoplankton communities for each lake, obtained sub-network for each sampling month, and then measured indices of network complexity and stability for each sub-network. We assessed how lake re-oligotrophication, climate warming and grazers influenced the temporal dynamics on network complexity and stability of phytoplankton community covering three aspects: seasonal trends, long-term trends and detrended variability. We found strong seasonality for the complexity and stability of phytoplankton network, an increasing trend for the average degree, modularity, nestedness, persistence and robustness, and a decreasing trend for connectance, negative:positive interactions and vulnerability. Our study revealed a cascading effect of lake re-oligotrophication, climate warming and zooplankton grazers on phytoplankton network stability through changes in network complexity characterizing diversity, interactions and topography. Network stability of phytoplankton increased with average degree, modularity, nestedness and decreased with connectance and negative:positive interactions. Oligotrophication and warming stabilized the phytoplankton network (enhanced robustness, persistence and decreased vulnerability) by enhancing its average degree, modularity, nestedness and by reducing its connectance, while zooplankton richness promoted stability of phytoplankton network through increases in average degree and decreases in negative interactions. Our results further indicate that the stabilization effects might lead to more closed, compartmentalized and nested interconnections especially in the deeper lakes, in the warmer seasons and during bloom periods. From a temporal dynamic network view, our findings highlight stabilization of the phytoplankton community as an adaptive response to lake re-oligotrophication, climate warming and grazers.

Widespread shifts in body size within populations and assemblages

Biotic responses to global change include directional shifts in organismal traits. Body size, an integrative trait that determines demographic rates and ecosystem functions, is thought to be shrinking in the Anthropocene. Here, we assessed the prevalence of body size change in six taxon groups across 5025 assemblage time series spanning 1960 to 2020. Using the Price equation to partition this change into within-species body size versus compositional changes, we detected prevailing decreases in body size through time driven primarily by fish, with more variable patterns in other taxa. We found that change in assemblage composition contributes more to body size changes than within-species trends, but both components show substantial variation in magnitude and direction. The biomass of assemblages remains quite stable as decreases in body size trade off with increases in abundance.

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.

Ecosystem-level effects of re-oligotrophication and N:P imbalances in rivers and estuaries on a global scale

Trends and ecological consequences of phosphorus (P) decline and increasing nitrogen (N) to phosphorus (N:P) ratios in rivers and estuaries are reviewed and discussed. Results suggest that re-oligotrophication is a dominant trend in rivers and estuaries of high-income countries in the last two-three decades, while in low-income countries widespread eutrophication occurs. The decline in P is well documented in hundreds of rivers of United States and the European Union, but the biotic response of rivers and estuaries besides phytoplankton decline such as trends in phytoplankton composition, changes in primary production, ecosystem shifts, cascading effects, changes in ecosystem metabolism, etc., have not been sufficiently monitored and investigated, neither the effects of N:P imbalance. N:P imbalance has significant ecological effects that need to be further investigated. There is a growing number of cases in which phytoplankton biomass have been shown to decrease due to re-oligotrophication, but the potential regime shift from phytoplankton to macrophyte dominance described in shallow lakes has been documented only in a few rivers and estuaries yet. The main reasons why regime shifts are rarely described in rivers and estuaries are, from one hand the scarcity of data on macrophyte cover trends, and from the other hand physical factors such as peak flows or high turbidity that could prevent a general spread of submerged macrophytes as observed in shallow lakes. Moreover, re-oligotrophication effects on rivers may be different compared to lakes (e.g., lower dominance of macrophytes) or estuaries (e.g., limitation of primary production by N instead of P) or may be dependent on river/estuary type. We conclude that river and estuary re-oligotrophication effects are complex, diverse and still little known, and in some cases are equivalent to those described in shallow lakes, but the regime shift is more likely to occur in mid to high-order rivers and shallow estuaries.

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.

A hybrid empirical and parametric approach for managing ecosystem complexity: Water quality in Lake Geneva under nonstationary futures

This paper develops a hybrid approach to account for the complex interactions affecting lake water quality and its management in a nonlinear, changing world. The approach uses data to leverage our first-principles understanding of the mechanisms operating on dissolved oxygen in the lake. This yields a manageable, but more complete systems perspective for environmental management of the lake under climate change, where our analysis suggests that multiple modes of intervention may be necessary to achieve a healthy lake.

Severe deterioration of water quality in lakes, characterized by overabundance of algae and declining dissolved oxygen in the deep lake (DO_B), was one of the ecological crises of the 20th century. Even with large reductions in phosphorus loading, termed “reoligotrophication,” DO_B and chlorophyll (CHL) have often not returned to their expected pre–20th-century levels. Concurrently, management of lake health has been confounded by possible consequences of climate change, particularly since the effects of climate are not neatly separable from the effects of eutrophication. Here, using Lake Geneva as an iconic example, we demonstrate a complementary alternative to parametric models for understanding and managing lake systems. This involves establishing an empirically-driven baseline that uses supervised machine learning to capture the changing interdependencies among biogeochemical variables and then combining the empirical model with a more conventional equation-based model of lake physics to predict DO_B over decadal time-scales. The hybrid model not only leads to substantially better forecasts, but also to a more actionable description of the emergent rates and processes (biogeochemical, ecological, etc.) that drive water quality. Notably, the hybrid model suggests that the impact of a moderate 3°C air temperature increase on water quality would be on the same order as the eutrophication of the previous century. The study provides a template and a practical path forward to cope with shifts in ecology to manage environmental systems for non-analogue futures.

Decadal biodiversity trends in rivers reveal recent community rearrangements

While it is recognized that biodiversity currently declines at a global scale, we still have an incomplete understanding of local biodiversity trends under global change. To address this deficiency, we examined the recent decadal trends in water quality and biodiversity (taxonomic and functional) of key river organisms (diatoms, macroinvertebrates and fish) in France. We implemented regression, RLQ and fourth-corner analyses. Our results showed that nutrient loads tended to decrease, diatom richness tended to decline and macoinvertebrate richness tended to increase. The recovery of sensitive taxa in all three groups suggested a successful outcome of water quality management in France over the past decades. Our study further revealed consistent rearrangements within river communities, with a decrease in the ratio of planktonic to benthic diatoms, and corresponding functional changes in macroinvertebrate and fish trait composition, indicative of a trophic cascade in response to changes in environmental conditions.

Seasonal diversity dynamics of a boreal zooplankton community under climate impact

Seasonality and long-term environmental variability affect species diversity through their effects on the dynamics of species. To investigate such effects, we fitted a dynamic and heterogeneous species abundance model generating the lognormal species abundance distribution to an assemblage of freshwater zooplankton sampled five times a year (June-October) during the ice-free period over 28 years (1990-2017) in Lake Atnsjøen (Norway). By applying a multivariate stochastic community dynamics model for describing the fluctuations in abundances, we show that the community dynamics was driven by environmental variability in spring (i.e., June). In contrast, community-level ecological heterogeneity is highest in autumn. The autumn months (i.e., September and October) that rearranged the community are most likely crucial months to monitor long-term changes in community structure. Indeed, noises from early summer are filtered away, making it easier to track long-term changes. The community returned faster towards equilibrium when ecological heterogeneity was the highest (i.e., in September and October). This occurred because of stronger density-regulation in months with highest ecological heterogeneity. The community responded to the long-term warming of water temperature with decreasing species diversity and increasing abundance. Unevenness associated with variabilities in abundances might affect species interactions within the community. These can have consequences for the stability and functioning of the ecosystem.

Deep Learning Classification of Lake Zooplankton

Plankton are effective indicators of environmental change and ecosystem health in freshwater habitats, but collection of plankton data using manual microscopic methods is extremely labor-intensive and expensive. Automated plankton imaging offers a promising way forward to monitor plankton communities with high frequency and accuracy in real-time. Yet, manual annotation of millions of images proposes a serious challenge to taxonomists. Deep learning classifiers have been successfully applied in various fields and provided encouraging results when used to categorize marine plankton images. Here, we present a set of deep learning models developed for the identification of lake plankton, and study several strategies to obtain optimal performances, which lead to operational prescriptions for users. To this aim, we annotated into 35 classes over 17900 images of zooplankton and large phytoplankton colonies, detected in Lake Greifensee (Switzerland) with the Dual Scripps Plankton Camera. Our best models were based on transfer learning and ensembling, which classified plankton images with 98% accuracy and 93% F1 score. When tested on freely available plankton datasets produced by other automated imaging tools (ZooScan, Imaging FlowCytobot, and ISIIS), our models performed better than previously used models. Our annotated data, code and classification models are freely available online.

Microfluidic and mathematical modeling of aquatic microbial communities

Aquatic microbial communities contribute fundamentally to biogeochemical transformations in natural ecosystems, and disruption of these communities can lead to ecological disasters such as harmful algal blooms. Microbial communities are highly dynamic, and their composition and function are tightly controlled by the biophysical (e.g., light, fluid flow, and temperature) and biochemical (e.g., chemical gradients and cell concentration) parameters of the surrounding environment. Due to the large number of environmental factors involved, a systematic understanding of the microbial community-environment interactions is lacking. In this article, we show that microfluidic platforms present a unique opportunity to recreate well-defined environmental factors in a laboratory setting in a high throughput way, enabling quantitative studies of microbial communities that are amenable to theoretical modeling. The focus of this article is on aquatic microbial communities, but the microfluidic and mathematical models discussed here can be readily applied to investigate other microbiomes.

Synergistic impact of socio-economic and climatic changes on the ecosystem of a deep dam reservoir: Case study of the Dobczyce dam reservoir based on a 30-year monitoring study

Climate change, increasing inequality in freshwater supply and consumption, as well as human land use activities are remarkable drivers of the alteration of the water cycle on the Earth. The aim of our research was to determine if socio-economic and climatic changes affected the ecosystem of a deep dam reservoir which is used for drinking water. A 30-years data series showed that suburbanization did not negatively affect the quality of the water. Moreover, 30 years of socio-economic and political changes resulted in land use changes (increase of forest from 45 to 50% and decrease of agricultural land from 53 to 43%) and better management of the catchment, as well as the modernization and introduction of new technologies. Furthermore, simultaneous climatic changes affected various physical and chemical features of the studied reservoir, and the most important finding is that the thermal stratification period is extended as an effect of global warming (begins earlier and lasts longer). The complexity of the processes contributing to the functioning of the ecosystem is large, so some processes might be a result of synergistic effects of global warming and socio-economic changes. Our 30-year monitoring study explicitly shows how the ecosystem of a deep dam reservoir reflected these changes.

Seasonal and long-term trends in the spatial heterogeneity of lake phytoplankton communities over two decades of restoration and climate change

World-wide, reducing the external nutrient loading to lakes has been the primary priority of lake management in the restoration of eutrophic lakes over the past decades, and as expected this has resulted in an increase in the local environmental heterogeneity, and thus biotic heterogeneity, within lakes. However, little is known about how the regional spatial heterogeneity of lake biotic communities changes with restoration across a landscape. Using a long-term monitoring dataset from 20 Danish lakes, we elucidated the seasonal and long-term trends in the spatial heterogeneity of climate, local abiotic variables and phytoplankton communities over two decades of restoration and climate change at landscape level. We found significant seasonality in the spatial heterogeneity of most climatic and local drivers as well as in the total beta diversity (Sørensen coefficient) and its turnover components (Simpson coefficient) of phytoplankton communities among the lakes. The seasonality tended to be less marked in deep than in shallow lakes. We found significant spatial homogenisation of most local drivers (except for alkalinity) and phytoplankton communities after two decades of restoration and that turnover dominated the temporal responses of the total beta diversity of phytoplankton communities. Path analyses showed that the homogenisation of phytoplankton communities was mainly due to a decrease in spatial heterogeneity of total phosphorus and Schmidt stability in shallow lakes and to a decrease in spatial total phosphorus and total nitrogen heterogeneity in deep lakes. However, albeit weakly, the spatial heterogeneity of the phytoplankton communities was affected indirectly by climatic warming in both shallow and deep lakes and directly by wind speed in shallow lakes. We conclude that restoration of eutrophic lakes may lead to an increase in the local heterogeneity of phytoplankton communities at lake scale and an increase in homogeneity at landscape scale.

The geography of biodiversity change in marine and terrestrial assemblages

Human activities are fundamentally altering biodiversity. Projections of declines at the global scale are contrasted by highly variable trends at local scales, suggesting that biodiversity change may be spatially structured. Here, we examined spatial variation in species richness and composition change using more than 50,000 biodiversity time series from 239 studies and found clear geographic variation in biodiversity change. Rapid compositional change is prevalent, with marine biomes exceeding and terrestrial biomes trailing the overall trend. Assemblage richness is not changing on average, although locations exhibiting increasing and decreasing trends of up to about 20% per year were found in some marine studies. At local scales, widespread compositional reorganization is most often decoupled from richness change, and biodiversity change is strongest and most variable in the oceans.

Changing environmental conditions underpin long-term patterns of phytoplankton in a freshwater reservoir

Environmental changes can exert strong pressure on freshwater biota and lead to unwanted alterations of local communities and deterioration of ecosystem services. Disentangling the links between environmental and community changes is, therefore, essential to understand and predict the impact of human activities on freshwater ecosystems. This is particularly relevant for man-made freshwater reservoirs that represent a nexus between anthropogenic, environmental, and biotic effects. Reservoir food webs depend strongly on phytoplankton dynamics, which are affected by abiotic conditions, nutrient availability and grazing pressure by zooplankton. We studied the effects of relevant environmental drivers (hydrochemistry, hydrodynamics and zooplankton) on the composition, diversity and community stability of main morpho-functional phytoplankton groups over 32 years in the Římov Reservoir (Czech Republic). Environmental conditions in the reservoir are characterised by three distinct periods (1983-89, 1990-99, and 2000-14) defined by shifts and breakpoints in temporal trends in reservoir hydrochemistry and hydraulic conditions, and we examined if and how phytoplankton responded to these abrupt changes. We found significant differences in phytoplankton composition among the three periods. Phytoplankton underwent a substantial compositional shift towards a dominance of pennate diatoms. Time-lag analysis of dissimilarity in phytoplankton composition revealed higher and stochastic annual variations until 1999, followed by a lower variability and divergence in phytoplankton composition in subsequent years. Changes in overall phytoplankton assemblage and most abundant morpho-functional phytoplankton groups were driven mainly by hydrochemical (total nitrogen) and hydrodynamic variables (inflow rate, surface level and mixing depth) and less by zooplankton dynamics. These results suggest that phytoplankton are driven primarily by nutrient input and water regime, both of which can be appropriately managed to support valuable ecosystem services provided by phytoplankton in freshwater reservoirs.

Interacting Temperature, Nutrients and Zooplankton Grazing Control Phytoplankton Size-Abundance Relationships in Eight Swiss Lakes

Biomass distribution among size classes follows a power law where the Log-abundance of taxa scales to Log-size with a slope that responds to environmental abiotic and biotic conditions. The interactions between ecological mechanisms controlling the slope of locally realized size-abundance relationships (SAR) are however not well understood. Here we tested how warming, nutrient levels, and grazing affect the slope of phytoplankton community SARs in decadal time-series from eight Swiss lakes of the peri-alpine region, which underwent environmental forcing due to climate change and oligotrophication. We expected rising temperature to have a negative effect on slope (favoring small phytoplankton), and increasing nutrient levels and grazing pressure to have a positive effect (benefiting large phytoplankton). Using a random forest approach to extract robust patterns from the noisy data, we found that the effects of temperature (direct and indirect through water column stability), nutrient availability (phosphorus and total biomass), and large herbivore (copepods and daphnids) grazing and selectivity on slope were non-linear and interactive. Increasing water temperature or total grazing pressure, and decreasing phosphorus levels, had a positive effect on slope (favoring large phytoplankton, which are predominantly mixotrophic in the lake dataset). Our results therefore showed patterns that were opposite to the expected long-term effects of temperature and nutrient levels, and support a paradigm in which (i) small phototrophic phytoplankton appear to be favored under high nutrients levels, low temperature and low grazing, and (ii) large mixotrophic algae are favored under oligotrophic conditions when temperature and grazing pressure are high. The effects of temperature were stronger under nutrient limitation, and the effects of nutrients and grazing were stronger at high temperature. Our study shows that the phytoplankton local SARs in lakes respond to both the independent and the interactive effects of resources, grazing and water temperature in a complex, unexpected way, and observations from long-term studies can deviate significantly from general theoretical expectations.

Long-Term Phytoplankton Dynamics in a Complex Temporal Realm

Faced with an environment of accelerated change, the long-term dynamics of biotic communities can be approached to build a consistent and causal picture of the communities’ life. We have undertaken a 25-year monthly-sampling study on the phytoplankton of a meso-oligotrophic lake, paying attention to controlling factors of overall biomass (TB) and taxonomical group biomass (TGBs). Long-term series included decreased trends of TB and TGBs, and multi-scale periodicity. A decadal TB periodicity emerged related to nitrogen concentration and Cryptophytes. Annual periodicities were mainly related to air and water temperature controlling the abundance of Chlorophytes or Dinoflagellates. Intra-annual cycles could arise from autogenic processes. The analysis by periods revealed relevant dynamics (for example, Diatom periodicities), hidden in the analysis of the complete series. These results allow us to establish that: i) two organizational levels of phytoplankton change differently in time scales from months to decades; ii) controlling factors (climate, water physics and chemistry) act at different time scales and on different TGBs, and iii) different combinations of the “taxonomical group-control factor-trend and periodicity” set throughout the studied time explain total biomass dynamics. A holistic approach (multiple complementary analyses) is necessary to disentangle the different actors and relationships that explain non-stationary long-term phytoplankton dynamics.

Environmental factors driving the dominance of the harmful bloom-forming cyanobacteria Microcystis and Aphanocapsa in a tropical water supply reservoir

Harmful cyanobacterial blooms in reservoirs have become a serious global issue for environmental health. However, dominance among different toxic cyanobacteria genera remains poorly understood, especially in tropical areas. We evaluated the influence of environmental factors, including total phosphorus, dissolved aluminum, water level, and precipitation on the change of the dominant genus from Microcystis to Aphanocapsa, in a hypereutrophic tropical reservoir, using 443 water samples over six years of field monitoring by applying generalized linear models (GLM). The results pointed out the prevalence of longer hydrologic retention time leading to enhanced water stability, and nutrients' accumulation into the hypolimnetic zones of the reservoir may have favored the ecophysiological advantages for the picocyanobacteria Aphanocapsa, which reached densities greater than 1 million/ml. In addition, this article also suggests that physical-chemical remediation methods applied for immobilizing phosphorus in the sediments of the reservoir may be low effective in limiting cyanobacterial growth. These findings are not only meaningful to the understanding of the dynamics of cyanobacterial genera but also to improve the management of eutrophic reservoirs in tropical regions. PRACTITIONER POINTS: We assessed cyanobacterial dominance changes based on 6-year field monitoring. First article addressing the dominance of Aphanocapsa spp. in a tropical reservoir. Species of Aphanocapsa responded better to hydrological changes in the reservoir. The use of remediators was accompanied by an increase in cyanobacteria biomass.

Long-term dynamics and drivers of phytoplankton biomass in eutrophic Lake Taihu

Understanding the relative effect sizes of climate-related environmental variables and nutrients on the high annual variation in the phytoplankton biomass in eutrophic lakes is important for lake management efforts. In this study, we used a data set of phytoplankton dynamics in eutrophic Lake Taihu that cover more than two decades (1993-2015) to show the variation in and the drivers of phytoplankton biomass under complex, fluctuating environmental conditions. Our results showed that the phytoplankton biomass increased slowly over the studied period despite the recent decrease in nutrient levels. The distribution of the phytoplankton biomass expanded spatially towards the central lake region, and seasonally towards the autumn and winter. Nutrients were still the primary predictors of the long-term phytoplankton biomass trend. The effect size of climate-related variables was also high and close to the effect size of nutrients. Among the climate-related variables, wind speed and underwater available light were more important predictors than temperature. The biomass of the phytoplankton taxonomic groups showed different responses to the environmental variables based on their niches. However, the compensatory dynamics affecting biomass were weak at phylum level, and synchronous dynamics drove the variation in total biomass. Our findings highlight the effect of climate-related variables on the phytoplankton biomass in Lake Taihu, which has experienced high nutrient loadings and concentrations for more than two decades. Therefore, changes in climate-related variables, such as wind speed and underwater available light, should be considered when evaluating the amount that nutrients should be reduced in Lake Taihu for future lake management.

Warming and oligotrophication cause shifts in freshwater phytoplankton communities

While there is a lot of data on interactive effects of eutrophication and warming, to date, we lack data to generate reliable predictions concerning possible effects of nutrient decrease and temperature increase on community composition and functional responses. In recent years, a wide-ranging trend of nutrient decrease (re-oligotrophication) was reported for freshwater systems. Small lakes and ponds, in particular, show rapid responses to anthropogenic pressures and became model systems to investigate single as well as synergistic effects of warming and fertilization in situ and in experiments. Therefore, we set up an experiment to investigate the single as well as the interactive effects of nutrient reduction and gradual temperature increase on a natural freshwater phytoplankton community, using an experimental indoor mesocosm setup. Biomass production initially increased with warming but decreased with nutrient depletion. If nutrient supply was constant, biomass increased further, especially under warming conditions. Under low nutrient supply, we found a sharp transition from initially positive effects of warming to negative effects when resources became scarce. Warming reduced phytoplankton richness and evenness, whereas nutrient reduction at ambient temperature had positive effects on diversity. Our results indicate that temperature effects on freshwater systems will be altered by nutrient availability. These interactive effects of energy increase and resource decrease have major impacts on biodiversity and ecosystem function and thus need to be considered in environmental management plans.

BioTIME: A database of biodiversity time series for the Anthropocene

MOTIVATION

The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.

MAIN TYPES OF VARIABLES INCLUDED

The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.

SPATIAL LOCATION AND GRAIN

BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).

TIME PERIOD AND GRAIN

BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.

MAJOR TAXA AND LEVEL OF MEASUREMENT

BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.

SOFTWARE FORMAT

.csv and .SQL.

Individual-level trait diversity predicts phytoplankton community properties better than species richness or evenness

Understanding how microbial diversity influences ecosystem properties is of paramount importance. Cellular traits-which determine responses to the abiotic and biotic environment-may help us rigorously link them. However, our capacity to measure traits in natural communities has thus far been limited. Here we compared the predictive power of trait richness (trait space coverage), evenness (regularity in trait distribution) and divergence (prevalence of extreme phenotypes) derived from individual-based measurements with two species-level metrics (taxonomic richness and evenness) when modelling the productivity of natural phytoplankton communities. Using phytoplankton data obtained from 28 lakes sampled at different spatial and temporal scales, we found that the diversity in individual-level morphophysiological traits strongly improved our ability to predict community resource-use and biomass yield. Trait evenness-the regularity in distribution of individual cells/colonies within the trait space-was the strongest predictor, exhibiting a robust negative relationship across scales. Our study suggests that quantifying individual microbial phenotypes in trait space may help us understand how to link physiology to ecosystem-scale processes. Elucidating the mechanisms scaling individual-level trait variation to microbial community dynamics could there improve our ability to forecast changes in ecosystem properties across environmental gradients.

Impact of land cover changes and climate on the main airborne pollen types in Southern Spain

Airborne pollen concentrations strongly correlate with flowering intensity of wind-pollinated species growing at and around monitoring sites. The pollen spectrum, and the variations in its composition and concentrations, is influenced by climatic features and by available nutritional resources but it is also determined by land use and its changes. The first factor influence is well known on aerobiological researches but the impact of land cover changes has been scarcely studied until now. This paper reports on a study carried out in Southern Spain (Córdoba city) examining airborne pollen trends over a 15-year period and it explores the possible links both to changes in land use and to climate variations. The Seasonal-Trend Decomposition procedure based on Loess (STL) which decomposes long-term data series into smaller seasonal component patterns was applied. Trends were compared with recorded changes in land use at varying distances from the city in order to determine their possible influence on pollen-count variations. The influence of climate-related factors was determined by means of non-parametric correlation analysis. The STL method proved highly effective for extracting trend components from pollen time series, because their features vary widely and can change quickly in a short term. Results revealed mixed trends depending on the taxa and reflecting fluctuations in land cover and/or climate. A significant rising trend in Olea pollen counts was observed, attributable both to the increasing olive-growing area but also to changes in temperature and rainfall. Poaceae pollen concentrations also increased, due largely to an expansion of heterogeneous agricultural areas and to an increase in pollen season length positively influenced by rainfall and temperature. By contrast, the significant declining trend observed for pollen from ruderal taxa, such as Amaranthaceae, Rumex, Plantago and Urticaceae, may be linked to changes in urban planning strategies with a higher building pressure.

Synchronous dynamics of zooplankton competitors prevail in temperate lake ecosystems

Although competing species are expected to exhibit compensatory dynamics (negative temporal covariation), empirical work has demonstrated that competitive communities often exhibit synchronous dynamics (positive temporal covariation). This has led to the suggestion that environmental forcing dominates species dynamics; however, synchronous and compensatory dynamics may appear at different length scales and/or at different times, making it challenging to identify their relative importance. We compiled 58 long-term datasets of zooplankton abundance in north-temperate and sub-tropical lakes and used wavelet analysis to quantify general patterns in the times and scales at which synchronous/compensatory dynamics dominated zooplankton communities in different regions and across the entire dataset. Synchronous dynamics were far more prevalent at all scales and times and were ubiquitous at the annual scale. Although we found compensatory dynamics in approximately 14% of all combinations of time period/scale/lake, there were no consistent scales or time periods during which compensatory dynamics were apparent across different regions. Our results suggest that the processes driving compensatory dynamics may be local in their extent, while those generating synchronous dynamics operate at much larger scales. This highlights an important gap in our understanding of the interaction between environmental and biotic forces that structure communities.

Community stoichiometry in a changing world: combined effects of warming and eutrophication on phytoplankton dynamics

The current changes in our climate will likely have far-reaching consequences for aquatic ecosystems. These changes in the climate, however, do not act alone, and are often accompanied by additional stressors such as eutrophication. Both global warming and eutrophication have been shown to affect the timing and magnitude of phytoplankton blooms. Little is known about the combined effects of rising temperatures and eutrophication on the stoichiometry of entire phytoplankton communities. We exposed a natural phytoplankton spring community to different warming and phosphorus-loading scenarios using a full-factorial design. Our results demonstrate that rising temperatures promote the growth rate of an entire phytoplankton community. Furthermore, both rising temperatures and phosphorus loading stimulated the maximum biomass built up by the phytoplankton community. Rising temperatures led to higher carbon: nutrient stoichiometry of the phytoplankton community under phosphorus-limited conditions. Such a shift towards higher carbon: nutrient ratios, in combination with a higher biomass buildup, suggests a temperature-driven increase in nutrient use efficiency, the phytoplankton community. Importantly, with higher carbon: nutrient stoichiometry, phytoplankton is generally of poorer nutritional value for zooplankton. Thus, although warming may result in higher phytoplankton biomass, this may be accompanied by a stoichiometric mismatch between phytoplankton and their grazers, with possible consequences for the entire aquatic food web.

Statistical approach to the analysis of olive long-term pollen season trends in southern Spain

Analysis of long-term airborne pollen counts makes it possible not only to chart pollen-season trends but also to track changing patterns in flowering phenology. Changes in higher plant response over a long interval are considered among the most valuable bioindicators of climate change impact. Phenological-trend models can also provide information regarding crop production and pollen-allergen emission. The interest of this information makes essential the election of the statistical analysis for time series study. We analysed trends and variations in the olive flowering season over a 30-year period (1982-2011) in southern Europe (Córdoba, Spain), focussing on: annual Pollen Index (PI); Pollen Season Start (PSS), Peak Date (PD), Pollen Season End (PSE) and Pollen Season Duration (PSD). Apart from the traditional Linear Regression analysis, a Seasonal-Trend Decomposition procedure based on Loess (STL) and an ARIMA model were performed. Linear regression results indicated a trend toward delayed PSE and earlier PSS and PD, probably influenced by the rise in temperature. These changes are provoking longer flowering periods in the study area. The use of the STL technique provided a clearer picture of phenological behaviour. Data decomposition on pollination dynamics enabled the trend toward an alternate bearing cycle to be distinguished from the influence of other stochastic fluctuations. Results pointed to show a rising trend in pollen production. With a view toward forecasting future phenological trends, ARIMA models were constructed to predict PSD, PSS and PI until 2016. Projections displayed a better goodness of fit than those derived from linear regression. Findings suggest that olive reproductive cycle is changing considerably over the last 30years due to climate change. Further conclusions are that STL improves the effectiveness of traditional linear regression in trend analysis, and ARIMA models can provide reliable trend projections for future years taking into account the internal fluctuations in time series.

Long-term changes in hypoxia and soluble reactive phosphorus in the hypolimnion of a large temperate lake: consequences of a climate regime shift

The (Lower) Lake of Zurich provides an ideal system for studying the long-term impact of environmental change on deep-water hypoxia because of its sensitivity to climatic forcing, its history of eutrophication and subsequent oligotrophication, and the quality and length of its data set. Based on 39 years (1972-2010) of measured profiles of temperature, oxygen concentration and phosphorus (P) concentration, the potentially confounding effects of oligotrophication and climatic forcing on the occurrence and extent of deep-water hypoxia in the lake were investigated. The time-series of Nürnberg's hypoxic factor (HF) for the lake can be divided into three distinct segments: (i) a segment of consistently low HF from 1972 to the late-1980s climate regime shift (CRS); (ii) a transitional segment between the late-1980s CRS and approximately 2000 within which the HF was highly variable; and (iii) a segment of consistently high HF thereafter. The increase in hypoxia during the study period was not a consequence of a change in trophic status, as the lake underwent oligotrophication as a result of reduced external P loading during this time. Instead, wavelet analysis suggests that changes in the lake's mixing regime, initiated by the late-1980s CRS, ultimately led to a delayed but abrupt decrease in the deep-water oxygen concentration, resulting in a general expansion of the hypoxic zone in autumn. Even after detrending to remove long-term effects, the concentration of soluble reactive P in the bottom water of the lake was highly correlated with various measures of hypoxia, providing quantitative evidence supporting the probable effect of hypoxia on internal P loading. Such climate-induced, ecosystem-scale changes, which may result in undesirable effects such as a decline in water quality and a reduction in coldwater fish habitats, provide further evidence for the vulnerability of large temperate lakes to predicted increases in global air temperature.

Individual cell based traits obtained by scanning flow-cytometry show selection by biotic and abiotic environmental factors during a phytoplankton spring bloom

In ecology and evolution, the primary challenge in understanding the processes that shape biodiversity is to assess the relationship between the phenotypic traits of organisms and the environment. Here we tested for selection on physio-morphological traits measured by scanning flow-cytometry at the individual level in phytoplankton communities under a temporally changing biotic and abiotic environment. Our aim was to study how high-frequency temporal changes in the environment influence biodiversity dynamics in a natural community. We focused on a spring bloom in Lake Zurich (Switzerland), characterized by rapid changes in phytoplankton, water conditions, nutrients and grazing (mainly mediated by herbivore ciliates). We described bloom dynamics in terms of taxonomic and trait-based diversity and found that diversity dynamics of trait-based groups were more pronounced than those of identified phytoplankton taxa. We characterized the linkage between measured phytoplankton traits, abiotic environmental factors and abundance of the main grazers and observed weak but significant correlations between changing abiotic and biotic conditions and measured size-related and fluorescence-related traits. We tested for deviations in observed community-wide distributions of focal traits from random patterns and found evidence for both clustering and even spacing of traits, occurring sporadically over the time series. Patterns were consistent with environmental filtering and phenotypic divergence under herbivore pressure, respectively. Size-related traits showed significant even spacing during the peak of herbivore abundance, suggesting that morphology-related traits were under selection from grazing. Pigment distribution within cells and colonies appeared instead to be associated with acclimation to temperature and water chemistry. We found support for trade-offs among grazing resistance and environmental tolerance traits, as well as for substantial periods of dynamics in which our measured traits were not under selection.

Reversal in the relationship between species richness and turnover in a phytoplankton community

Negative relationships between species richness and the rate of compositional turnover are common, suggesting that diverse communities have greater stability than depauperate ones; however, the mechanistic basis for this pattern is still widely debated. Species richness and turnover can covary either because they are mechanistically linked or because they share common environmental drivers. Few empirical studies have combined long-term changes in community composition with multiple drivers of environmental change, and so little is known about how the underlying mechanisms of species coexistence interact with changes in the mean and variability of environmental conditions. Here, we use a 33 year long time series (1976-2008) of phytoplankton community composition from Lake Zurich, to examine how environmental variation influences the relationship between richness and annual turnover. We find that the relationship between richness and annual turnover reverses midway through the time series (1992-1993), leading to a hump-shaped relationship between species richness and annual turnover. Using structural equation modeling we show that annual turnover and diversity are independently associated with different drivers of environmental change. Furthermore, we find that the observed annual sequences of community assembly give rise to rates of species accumulation that are more heterogeneous through time than expected by chance, likely owing to a high proportion of species showing significant autocorrelation and to strong positive covariation in the occurrences of species.