The need for unrealistic experiments in global change biology

Interactions between ocean acidification and multiple environmental drivers on the biochemical traits of marine primary producers: A meta-analysis

Ocean acidification (OA) interacts with multiple environmental drivers, such as temperature, nutrients, and ultraviolet radiation (UVR), posing a threat to marine primary producers. In this study, we conducted a quantitative meta-analysis of 1001 experimental assessments from 68 studies to examine the combined effects of OA and multiple environmental drivers (e.g., light, nutrient) on the biochemical compositions of marine primary producers. The results revealed significant positive effects of each environmental driver and their interactions with OA according to Hedge's d analysis. The results revealed significant positive effects of multiple environmental drivers and their interactions with OA. Additive effects dominated (71%), with smaller proportions of antagonistic (20%) and synergistic interactions (9%). The antagonistic interactions, although fewer, had a substantial impact, causing OA and other environmental drivers to interact antagonistically. Significant differences were observed among taxonomic groups: haptophytes and rhodophytes were negatively affected, while bacillariophytes were positively affected by OA. Our findings also indicated that the interactions between OA and multiple environmental drivers varied depending on specific type of the environmental driver, suggesting a modulating role of OA on the biochemical compositions of marine primary producers in response to global change. In summary, our study elucidates the complex interactions between OA and multiple environmental drivers on marine primary producers, highlighting the varied impacts on biochemical compositions and elemental stoichiometry.

Food web context modifies predator foraging and weakens trophic interaction strength

Trophic interaction modifications (TIM) are widespread in natural systems and occur when a third species indirectly alters the strength of a trophic interaction. Past studies have focused on documenting the existence and magnitude of TIMs; however, the underlying processes and long-term consequences remain elusive. To address this gap, we experimentally quantified the density-dependent effect of a third species on a predator's functional response. We conducted short-term experiments with ciliate communities composed of a predator, prey and non-consumable 'modifier' species. In both communities, increasing modifier density weakened the trophic interaction strength, due to a negative effect on the predator's space clearance rate. Simulated long-term dynamics indicate quantitative differences between models that account for TIMs or include only pairwise interactions. Our study demonstrates that TIMs are important to understand and predict community dynamics and highlights the need to move beyond focal species pairs to understand the consequences of species interactions in communities.

Studying interactions among anthropogenic stressors in freshwater ecosystems: A systematic review of 2396 multiple-stressor experiments

Understanding the interactions among anthropogenic stressors is critical for effective conservation and management of ecosystems. Freshwater scientists have invested considerable resources in conducting factorial experiments to disentangle stressor interactions by testing their individual and combined effects. However, the diversity of stressors and systems studied has hindered previous syntheses of this body of research. To overcome this challenge, we used a novel machine learning framework to identify relevant studies from over 235,000 publications. Our synthesis resulted in a new dataset of 2396 multiple-stressor experiments in freshwater systems. By summarizing the methods used in these studies, quantifying trends in the popularity of the investigated stressors, and performing co-occurrence analysis, we produce the most comprehensive overview of this diverse field of research to date. We provide both a taxonomy grouping the 909 investigated stressors into 31 classes and an open-source and interactive version of the dataset (https://jamesaorr.shinyapps.io/freshwater-multiple-stressors/). Inspired by our results, we provide a framework to help clarify whether statistical interactions detected by factorial experiments align with stressor interactions of interest, and we outline general guidelines for the design of multiple-stressor experiments relevant to any system. We conclude by highlighting the research directions required to better understand freshwater ecosystems facing multiple stressors.

The endemic kelp Lessonia corrugata is being pushed above its thermal limits in an ocean warming hotspot

Kelps are in global decline due to climate change, which includes ocean warming. To identify vulnerable species, we need to identify their tolerances to increasing temperatures and determine whether tolerances are altered by co-occurring drivers such as inorganic nutrient levels. This is particularly important for those species with restricted distributions, which may already be experiencing thermal stress. To identify thermal tolerance of the range-restricted kelp Lessonia corrugata, we conducted a laboratory experiment on juvenile sporophytes to measure performance (growth, photosynthesis) across its thermal range (4-22°C). We determined the upper thermal limit for growth and photosynthesis to be ~22-23°C, with a thermal optimum of ~16°C. To determine if elevated inorganic nitrogen availability could enhance thermal tolerance, we compared the performance of juveniles under low (4.5 μmol · d-1) and high (90 μmol · d-1) nitrate conditions at and above the thermal optimum (16-23.5°C). Nitrate enrichment did not enhance thermal performance at temperatures above the optimum but did lead to elevated growth rates at the thermal optimum. Our results indicate L. corrugata is likely to be extremely susceptible to moderate ocean warming and marine heatwaves. Peak sea surface temperatures during summer in eastern and northeastern Tasmania can reach up to 20-21°C, and climate projections suggest that L. corrugata's thermal limit will be regularly exceeded by 2050 as southeastern Australia is a global ocean-warming hotspot. By identifying the upper thermal limit of L. corrugata, we have taken a critical step in predicting the future of the species in a warming climate.

Antagonistic interactions of the dinoflagellate Alexandrium catenella under simultaneous warming and acidification

There is a concern that harmful algal bloom (HAB) species may increase under climate change. Yet, we lack understanding of how ecological interactions will be affected under ocean warming and acidification (OWA) conditions. We tested the antagonistic effects of three strains of the dinoflagellate HAB species Alexandrium catenella on three target species (the chlorophyte Tetraselmis sp., the cryptomonad Rhodomonas salina, and the diatom Thalassiosira weissflogii) at various biomass ratios between species, at ambient (16 °C and 400 µatm CO2) and OWA (20 °C and 2000 µatm CO2) conditions. In these experiments the Alexandrium strains had been raised under OWA conditions for ∼100 generations. All three non-HAB species increased their growth rate under OWA relative to ambient conditions. Growth rate inhibition was evident for R. salina and Tetraselmis sp. under OWA conditions, but not under ambient conditions. These negative effects were exacerbated at higher concentrations of Alexandrium relative to non-HAB species. By contrast, T. weissflogii showed positive growth in the presence of two strains of Alexandrium under ambient conditions, whereas growth was unaffected under OWA. Contrary to our expectations, A. catenella had a slight negative response in the presence of the diatom. These results demonstrate that Alexandrium exerts higher antagonistic effects under OWA compared to ambient conditions, and these effects are species-specific and density dependent. These negative effects may shift phytoplankton community composition under OWA conditions.

The impact of extreme weather events exceeds those due to global-change drivers on coastal phytoplankton assemblages

Extreme wind and rainfall events have become more frequent phenomena, impacting coastal ecosystems by inducing increased mixing regimes in the upper mixed layers (UML) and reduced transparency (i.e. browning), hence affecting phytoplankton photosynthesis. In this study, five plankton assemblages from the South Atlantic Ocean, from a gradient of environmental variability and anthropogenic exposure, were subjected to simulated extreme weather events under a global change scenario (GCS) of increased temperature and nutrients and decreased pH, and compared to ambient conditions (Control). Using multiple linear regression (MLR) analysis we determined that evenness and the ratio of diatoms/ (flagellates + dinoflagellates) significantly explained the variations (81-91 %) of the photosynthesis efficiency (i.e. Pchla/ETRchla ratio) for each site under static conditions. Mixing speed and the optical depth (i.e. attenuation coefficient * depth, kdz), as single drivers, explained 40-76 % of the variability in the Pchla/ETRchla ratio, while GCS drivers <9 %. Overall, assemblages with high diversity and evenness were less vulnerable to extreme weather events under a GCS. Extreme weather events should be considered in global change studies and conservation/management plans as even at local/regional scales, they can exceed the predicted impacts of mean global climate change on coastal primary productivity.

Designing More Informative Multiple-Driver Experiments

For decades, multiple-driver/stressor research has examined interactions among drivers that will undergo large changes in the future: temperature, pH, nutrients, oxygen, pathogens, and more. However, the most commonly used experimental designs-present-versus-future and ANOVA-fail to contribute to general understanding or predictive power. Linking experimental design to process-based mathematical models would help us predict how ecosystems will behave in novel environmental conditions. We review a range of experimental designs and assess the best experimental path toward a predictive ecology. Full factorial response surface, fractional factorial, quadratic response surface, custom, space-filling, and especially optimal and sequential/adaptive designs can help us achieve more valuable scientific goals. Experiments using these designs are challenging to perform with long-lived organisms or at the community and ecosystem levels. But they remain our most promising path toward linking experiments and theory in multiple-driver research and making accurate, useful predictions.

Phytoplankton thermal trait parameterization alters community structure and biogeochemical processes in a modeled ocean

Phytoplankton exhibit diverse physiological responses to temperature which influence their fitness in the environment and consequently alter their community structure. Here, we explored the sensitivity of phytoplankton community structure to thermal response parameterization in a modelled marine phytoplankton community. Using published empirical data, we evaluated the maximum thermal growth rates (μmax ) and temperature coefficients (Q10 ; the rate at which growth scales with temperature) of six key Phytoplankton Functional Types (PFTs): coccolithophores, cyanobacteria, diatoms, diazotrophs, dinoflagellates, and green algae. Following three well-documented methods, PFTs were either assumed to have (1) the same μmax and the same Q10 (as in to Eppley, 1972), (2) a unique μmax but the same Q10 (similar to Kremer et al., 2017), or (3) a unique μmax and a unique Q10 (following Anderson et al., 2021). These trait values were then implemented within the Massachusetts Institute of Technology biogeochemistry and ecosystem model (called Darwin) for each PFT under a control and climate change scenario. Our results suggest that applying a μmax and Q10 universally across PFTs (as in Eppley, 1972) leads to unrealistic phytoplankton communities, which lack diatoms globally. Additionally, we find that accounting for differences in the Q10 between PFTs can significantly impact each PFT's competitive ability, especially at high latitudes, leading to altered modeled phytoplankton community structures in our control and climate change simulations. This then impacts estimates of biogeochemical processes, with, for example, estimates of export production varying by ~10% in the Southern Ocean depending on the parameterization. Our results indicate that the diversity of thermal response traits in phytoplankton not only shape community composition in the historical and future, warmer ocean, but that these traits have significant feedbacks on global biogeochemical cycles.

Comparative experimental evolution reveals species-specific idiosyncrasies in marine phytoplankton adaptation to warming

A number of experimental studies have demonstrated that phytoplankton can display rapid thermal adaptation in response to warmed environments. While these studies provide insight into the evolutionary responses of single species, they tend to employ different experimental techniques. Consequently, our ability to compare the potential for thermal adaptation across different, ecologically relevant, species remains limited. Here, we address this limitation by conducting simultaneous long-term warming experiments with the same experimental design on clonal isolates of three phylogenetically diverse species of marine phytoplankton; the cyanobacterium Synechococcus sp., the prasinophyte Ostreococcus tauri and the diatom Phaeodoactylum tricornutum. Over the same experimental time period, we observed differing levels of thermal adaptation in response to stressful supra-optimal temperatures. Synechococcus sp. displayed the greatest improvement in fitness (i.e., growth rate) and thermal tolerance (i.e., temperature limits of growth). Ostreococcus tauri was able to improve fitness and thermal tolerance, but to a lesser extent. Finally, Phaeodoactylum tricornutum showed no signs of adaptation. These findings could help us understand how the structure of phytoplankton communities may change in response to warming, and possible biogeochemical implications, as some species show relatively more rapid adaptive shifts in their thermal tolerance.

Interaction matters: Bottom-up driver interdependencies alter the projected response of phytoplankton communities to climate change

Phytoplankton growth is controlled by multiple environmental drivers, which are all modified by climate change. While numerous experimental studies identify interactive effects between drivers, large-scale ocean biogeochemistry models mostly account for growth responses to each driver separately and leave the results of these experimental multiple-driver studies largely unused. Here, we amend phytoplankton growth functions in a biogeochemical model by dual-driver interactions (CO2 and temperature, CO2 and light), based on data of a published meta-analysis on multiple-driver laboratory experiments. The effect of this parametrization on phytoplankton biomass and community composition is tested using present-day and future high-emission (SSP5-8.5) climate forcing. While the projected decrease in future total global phytoplankton biomass in simulations with driver interactions is similar to that in control simulations without driver interactions (5%-6%), interactive driver effects are group-specific. Globally, diatom biomass decreases more with interactive effects compared with the control simulation (-8.1% with interactions vs. no change without interactions). Small-phytoplankton biomass, by contrast, decreases less with on-going climate change when the model accounts for driver interactions (-5.0% vs. -9.0%). The response of global coccolithophore biomass to future climate conditions is even reversed when interactions are considered (+33.2% instead of -10.8%). Regionally, the largest difference in the future phytoplankton community composition between the simulations with and without driver interactions is detected in the Southern Ocean, where diatom biomass decreases (-7.5%) instead of increases (+14.5%), raising the share of small phytoplankton and coccolithophores of total phytoplankton biomass. Hence, interactive effects impact the phytoplankton community structure and related biogeochemical fluxes in a future ocean. Our approach is a first step to integrate the mechanistic understanding of interacting driver effects on phytoplankton growth gained by numerous laboratory experiments into a global ocean biogeochemistry model, aiming toward more realistic future projections of phytoplankton biomass and community composition.

Thermal plasticity over a marine-estuarine ecocline can buffer a tropical fish from warming

Intraspecific variation in thermal tolerance can favor species persistence in a warmer ocean, but is often overlooked in fine-scale studies. Nonetheless, local drivers (e.g. salinity) interact with temperature to shape species' thermal response. Here, we acclimated juveniles of Brazilian silversides Atherinella brasiliensis captured at the limits of a marine-estuarine ecocline under reciprocal-cross conditions, to test for phenotypic plasticity in heat tolerance. We also tested whether silversides acclimated to temperatures predicted for 2100 (+3-4.5 °C). Fish in warm-brackish waters showed higher CTMax (Critical Thermal Maximum) than those in cold-marine conditions, regardless of their origin. Silversides' CTMax reached up to 40.6 °C, but it did not increase after exposure to temperatures predicted for 2100. Lack of acclimation response suggests that silversides heat tolerance has reached a "ceiling", despite thermal plasticity. Our findings show that fine-scale environmental heterogeneity can promote phenotypic plasticity for tropical species, reducing the risk of short-term extirpation.

Long-term adaptation to elevated temperature but not CO2 alleviates the negative effects of ultraviolet-B radiation in a marine diatom

Multifaceted changes in marine environments as a result of anthropogenic activities are likely to have a compounding impact on the physiology of marine phytoplankton. Most studies on the combined effects of rising pCO₂, sea surface temperature, and UVB radiation on marine phytoplankton were only conducted in the short-term, which does not allow to test the adaptive capacity of phytoplankton and associated potential trade-offs. Here, we investigated populations of the diatom Phaeodactylum tricornutum that were long-term (∼3.5 years, ∼3000 generations) adapted to elevated CO₂ and/or elevated temperatures, and their physiological responses to short-term (∼2 weeks) exposure of two levels of ultraviolet-B (UVB) radiation. Our results showed that while elevated UVB radiation showed predominantly negative effects on the physiological performance of P. tricornutum regardless of adaptation regimes. Elevated temperature alleviated these effects on most of the measured physiological parameters (e.g., photosynthesis). We also found that elevated CO₂ can modulate these antagonistic interactions, and conclude that long-term adaptation to sea surface warming and rising CO₂ may alter this diatom's sensitivity to elevated UVB radiation in the environment. Our study provides new insights into marine phytoplankton's long-term responses to the interplay of multiple environmental changes driven by climate change.

When things get MESI: The Manipulation Experiments Synthesis Initiative-A coordinated effort to synthesize terrestrial global change experiments

Responses of the terrestrial biosphere to rapidly changing environmental conditions are a major source of uncertainty in climate projections. In an effort to reduce this uncertainty, a wide range of global change experiments have been conducted that mimic future conditions in terrestrial ecosystems, manipulating CO₂ , temperature, and nutrient and water availability. Syntheses of results across experiments provide a more general sense of ecosystem responses to global change, and help to discern the influence of background conditions such as climate and vegetation type in determining global change responses. Several independent syntheses of published data have yielded distinct databases for specific objectives. Such parallel, uncoordinated initiatives carry the risk of producing redundant data collection efforts and have led to contrasting outcomes without clarifying the underlying reason for divergence. These problems could be avoided by creating a publicly available, updatable, curated database. Here, we report on a global effort to collect and curate 57,089 treatment responses across 3644 manipulation experiments at 1145 sites, simulating elevated CO₂ , warming, nutrient addition, and precipitation changes. In the resulting Manipulation Experiments Synthesis Initiative (MESI) database, effects of experimental global change drivers on carbon and nutrient cycles are included, as well as ancillary data such as background climate, vegetation type, treatment magnitude, duration, and, unique to our database, measured soil properties. Our analysis of the database indicates that most experiments are short term (one or few growing seasons), conducted in the USA, Europe, or China, and that the most abundantly reported variable is aboveground biomass. We provide the most comprehensive multifactor global change database to date, enabling the research community to tackle open research questions, vital to global policymaking. The MESI database, freely accessible at doi.org/10.5281/zenodo.7153253, opens new avenues for model evaluation and synthesis-based understanding of how global change affects terrestrial biomes. We welcome contributions to the database on GitHub.

Predicting effects of multiple interacting global change drivers across trophic levels

Global change encompasses many co-occurring anthropogenic drivers, which can act synergistically or antagonistically on ecological systems. Predicting how different global change drivers simultaneously contribute to observed biodiversity change is a key challenge for ecology and conservation. However, we lack the mechanistic understanding of how multiple global change drivers influence the vital rates of multiple interacting species. We propose that reaction norms, the relationships between a driver and vital rates like growth, mortality, and consumption, provide insights to the underlying mechanisms of community responses to multiple drivers. Understanding how multiple drivers interact to affect demographic rates using a reaction-norm perspective can improve our ability to make predictions of interactions at higher levels of organization-that is, community and food web. Building on the framework of consumer-resource interactions and widely studied thermal performance curves, we illustrate how joint driver impacts can be scaled up from the population to the community level. A simple proof-of-concept model demonstrates how reaction norms of vital rates predict the prevalence of driver interactions at the community level. A literature search suggests that our proposed approach is not yet used in multiple driver research. We outline how realistic response surfaces (i.e., multidimensional reaction norms) can be inferred by parametric and nonparametric approaches. Response surfaces have the potential to strengthen our understanding of how multiple drivers affect communities as well as improve our ability to predict when interactive effects emerge, two of the major challenges of ecology today.

Net effect of environmental fluctuations in multiple global-change drivers across the tree of life

Jensen's inequality predicts that the response of any given system to average constant conditions is different from its average response to varying ones. Environmental fluctuations in abiotic conditions are pervasive on Earth; yet until recently, most ecological research has addressed the effects of multiple environmental drivers by assuming constant conditions. One could thus expect to find significant deviations in the magnitude of their effects on ecosystems when environmental fluctuations are considered. Drawing on experimental studies published during the last 30 years reporting more than 950 response ratios (n = 5,700), we present a comprehensive analysis of the role that environmental fluctuations play across the tree of life. In contrast to the predominance of interactive effects of global-change drivers reported in the literature, our results show that their cumulative effects were additive (58%), synergistic (26%), and antagonistic (16%) when environmental fluctuations were present. However, the dominant type of interaction varied by trophic level (autotrophs: interactive; heterotrophs: additive) and phylogenetic group (additive in Animalia; additive and positive antagonism in Chromista; negative antagonism and synergism in Plantae). In addition, we identify the need to tackle how complex communities respond to fluctuating environments, widening the phylogenetic and biogeographic ranges considered, and to consider other drivers beyond warming and acidification as well as longer timescales. Environmental fluctuations must be taken into account in experimental and modeling studies as well as conservation plans to better predict the nature, magnitude, and direction of the impacts of global change on organisms and ecosystems.