Evaluating top-down, bottom-up, and environmental drivers of pelagic food web dynamics along an estuarine gradient.

Identification of the key biotic and abiotic drivers within food webs is important for understanding species abundance changes in ecosystems, particularly across ecotones where there may be strong variation in interaction strengths. Using structural equation models (SEMs) and four decades of integrated data from the San Francisco Estuary, we investigated the relative effects of top-down, bottom-up, and environmental drivers on multiple trophic levels of the pelagic food web along an estuarine salinity gradient and at both annual and monthly temporal resolutions. We found that interactions varied across the estuarine gradient and that the detectability of different interactions depended on timescale. For example, for zooplankton and estuarine fishes, bottom-up effects appeared to be stronger in the freshwater upstream regions, while top-down effects were stronger in the brackish downstream regions. Some relationships (e.g., bottom-up effects of phytoplankton on zooplankton) were seen primarily at annual timescales, whereas others (e.g., temperature effects) were only observed at monthly timescales. We also found that the net effect of environmental drivers was similar to or greater than bottom-up and top-down effects for all food web components. These findings can help identify which trophic levels or environmental factors could be targeted by management actions to have the greatest impact on estuarine forage fishes and the spatial and temporal scale at which responses might be observed. More broadly, this study highlights how environmental gradients can structure community interactions and how long-term data sets can be leveraged to generate insights across multiple scales.

Constraining nonlinear time series modeling with the metabolic theory of ecology.

Forecasting the response of ecological systems to environmental change is a critical challenge for sustainable management. The metabolic theory of ecology (MTE) posits scaling of biological rates with temperature, but it has had limited application to population dynamic forecasting. Here we use the temperature dependence of the MTE to constrain empirical dynamic modeling (EDM), an equation-free nonlinear machine learning approach for forecasting. By rescaling time with temperature and modeling dynamics on a "metabolic time step," our method (MTE-EDM) improved forecast accuracy in 18 of 19 empirical ectotherm time series (by 19% on average), with the largest gains in more seasonal environments. MTE-EDM assumes that temperature affects only the rate, rather than the form, of population dynamics, and that interacting species have approximately similar temperature dependence. A review of laboratory studies suggests these assumptions are reasonable, at least approximately, though not for all ecological systems. Our approach highlights how to combine modern data-driven forecasting techniques with ecological theory and mechanistic understanding to predict the response of complex ecosystems to temperature variability and trends.

Intermittent instability is widespread in plankton communities.

Chaotic dynamics appear to be prevalent in short-lived organisms including plankton and may limit long-term predictability. However, few studies have explored how dynamical stability varies through time, across space and at different taxonomic resolutions. Using plankton time series data from 17 lakes and 4 marine sites, we found seasonal patterns of local instability in many species, that short-term predictability was related to local instability, and that local instability occurred most often in the spring, associated with periods of high growth. Taxonomic aggregates were more stable and more predictable than finer groupings. Across sites, higher latitude locations had higher Lyapunov exponents and greater seasonality in local instability, but only at coarser taxonomic resolution. Overall, these results suggest that prediction accuracy, sensitivity to change and management efficacy may be greater at certain times of year and that prediction will be more feasible for taxonomic aggregates.

Chaos is not rare in natural ecosystems.

Chaotic dynamics are thought to be rare in natural populations but this may be due to methodological and data limitations, rather than the inherent stability of ecosystems. Following extensive simulation testing, we applied multiple chaos detection methods to a global database of 172 population time series and found evidence for chaos in >30%. In contrast, fitting traditional one-dimensional models identified <10% as chaotic. Chaos was most prevalent among plankton and insects and least among birds and mammals. Lyapunov exponents declined with generation time and scaled as the -1/6 power of body mass among chaotic populations. These results demonstrate that chaos is not rare in natural populations, indicating that there may be intrinsic limits to ecological forecasting and cautioning against the use of steady-state approaches to conservation and management.

When are bacteria really gazelles? Comparing patchy ecologies with dimensionless numbers.

From micro to planetary scales, spatial heterogeneity-patchiness-is ubiquitous in ecosystems, defining the environments in which organisms move and interact. However, most large-scale models still use spatially averaged 'mean fields' to represent natural populations, while fine-scale spatially explicit models are mostly restricted to particular organisms or systems. In a conceptual paper, Grünbaum (2012, Interface Focus 2: 150-155) introduced a heuristic, based on three dimensionless ratios quantifying movement, reproduction and resource consumption, to characterise patchy ecological interactions and identify when mean-field assumptions are justifiable. We calculated these dimensionless numbers for 33 interactions between consumers and their resource patches in terrestrial, aquatic and aerial environments. Consumers ranged in size from bacteria to whales, and patches lasted from minutes to millennia, with separation scales from mm to hundreds of km. No interactions could be accurately represented by naive mean-field models, though 19 (58%) could be partially simplified by averaging out movement, reproductive or consumption dynamics. Clustering interactions by their non-dimensional ratios revealed several unexpected dynamic similarities. For example, bacterial Pseudoalteromonas exploit nutrient plumes similarly to Mongolian gazelles grazing on ephemeral steppe vegetation. We argue that dimensional analysis is valuable for characterising ecological patchiness and can link widely different systems into a single quantitative framework.

Diverse integrated ecosystem approach overcomes pandemic-related fisheries monitoring challenges.

The COVID-19 pandemic caused unprecedented cancellations of fisheries and ecosystem-assessment surveys, resulting in a recession of observations needed for management and conservation globally. This unavoidable reduction of survey data poses challenges for informing biodiversity and ecosystem functioning, developing future stock assessments of harvested species, and providing strategic advice for ecosystem-based management. We present a diversified framework involving integration of monitoring data with empirical models and simulations to inform ecosystem status within the California Current Large Marine Ecosystem. We augment trawl observations collected from a limited fisheries survey with survey effort reduction simulations, use of seabird diets as indicators of fish abundance, and krill species distribution modeling trained on past observations. This diversified approach allows for evaluation of ecosystem status during data-poor situations, especially during the COVID-19 era. The challenges to ecosystem monitoring imposed by the pandemic may be overcome by preparing for unexpected effort reduction, linking disparate ecosystem indicators, and applying new species modeling techniques.

Trophic control changes with season and nutrient loading in lakes.

Experiments have revealed much about top-down and bottom-up control in ecosystems, but manipulative experiments are limited in spatial and temporal scale. To obtain a more nuanced understanding of trophic control over large scales, we explored long-term time-series data from 13 globally distributed lakes and used empirical dynamic modelling to quantify interaction strengths between zooplankton and phytoplankton over time within and across lakes. Across all lakes, top-down effects were associated with nutrients, switching from negative in mesotrophic lakes to positive in oligotrophic lakes. This result suggests that zooplankton nutrient recycling exceeds grazing pressure in nutrient-limited systems. Within individual lakes, results were consistent with a 'seasonal reset' hypothesis in which top-down and bottom-up interactions varied seasonally and were both strongest at the beginning of the growing season. Thus, trophic control is not static, but varies with abiotic conditions - dynamics that only become evident when observing changes over large spatial and temporal scales.

Hidden similarities in the dynamics of a weakly synchronous marine metapopulation.

Populations of many marine species are only weakly synchronous, despite coupling through larval dispersal and exposure to synchronous environmental drivers. Although this is often attributed to observation noise, factors including local environmental differences, spatially variable dynamics, and chaos might also reduce or eliminate metapopulation synchrony. To differentiate spatially variable dynamics from similar dynamics driven by spatially variable environments, we applied hierarchical delay embedding. A unique output of this approach, the "dynamic correlation," quantifies similarity in intrinsic dynamics of populations, independently of whether their abundance is correlated through time. We applied these methods to 17 populations of blue crab (Callinectes sapidus) along the US Atlantic coast and found that their intrinsic dynamics were broadly similar despite largely independent fluctuations in abundance. The weight of evidence suggests that the latitudinal gradient in temperature, filtered through a unimodal response curve, is sufficient to decouple crab populations. As unimodal thermal performance is ubiquitous in ectotherms, we suggest that this may be a general explanation for the weak synchrony observed at large distances in many marine species, although additional studies are needed to test this hypothesis.

Temperature dependency of intraguild predation between native and invasive crabs.

Environmental factors such as temperature can affect the geographical distribution of species directly by exceeding physiological tolerances, or indirectly by altering physiological rates that dictate the sign and strength of species interactions. Although the direct effects of environmental conditions are relatively well studied, the effects of environmentally mediated species interactions have garnered less attention. In this study, we examined the temperature dependency of size-structured intraguild predation (IGP) between native blue crabs (Callinectes sapidus, the IG predator) and invasive green crabs (Carcinus maenas, the IG prey) to evaluate how the effect of temperature on competitive and predatory rates may influence the latitudinal distribution of these species. In outdoor mesocosm experiments, we quantified interactions between blue crabs, green crabs, and shared prey (mussels) at three temperatures reflective of those across their range, using two size classes of blue crab. At low temperatures, green crabs had a competitive advantage and IGP by blue crabs on green crabs was low. At high temperatures, size-matched blue and green crabs were competitively similar, large blue crabs had a competitive advantage, and IGP on green crabs was high. We then used parameter values generated from these experiments (temperature- and size-dependent attack rates and handling times) in a size-structured IGP model in which we varied IGP attack rate, maturation rate of the blue crab from the non-predatory to predatory size class, and resource carrying capacity at each of the three temperatures. In the model, green crabs were likely to competitively exclude blue crabs at low temperature, whereas blue crabs were likely to competitively and consumptively exclude green crabs at higher temperatures, particularly when resource productivities and rates of IGP were high. While many factors may play a role in delimiting species ranges, our results suggest that temperature-dependent interactions can influence local coexistence and are worth considering when developing mechanistic species distribution models and evaluating responses to environmental change.

Host and parasite recruitment correlated at a regional scale.

Drivers of large-scale variability in parasite prevalence are not well understood. For logistical reasons, explorations of spatial patterns in parasites are often performed as observational studies. However, to understand the mechanisms that underlie these spatial patterns, standardized and controlled comparisons are needed. Here, we examined spatial variability in infection of an important fishery species and ecosystem engineer, the oyster (Crassostrea virginica) by its pea crab parasite (Zaops ostreus) across 700 km of the southeastern USA coastline. To minimize the influence of host genetics on infection patterns, we obtained juvenile oysters from a homogeneous source stock and raised them in situ for 3 months at multiple sites with similar environmental characteristics. We found that prevalence of pea crab infection varied between 24 and 73% across sites, but not systematically across latitude. Of all measured environmental variables, oyster recruitment correlated most strongly (and positively) with pea crab infection, explaining 92% of the variability in infection across sites. Our data ostensibly suggest that regional processes driving variation in oyster recruitment similarly affect the recruitment of one of its common parasites.

The use of EMLA cream to decrease venipuncture pain in children.

Venipuncture is one of the most painful medical procedures for a child, and it is one of the most frequently performed. This literature synthesis reviews evidence for the use of eutectic mixture of local anesthetics (EMLA) cream to reduce the pain children experience during venipuncture. EMLA cream was compared with placebo, iontophoresis, and amethocaine cream and was found to be an effective local anesthetic for pediatric venipuncture pain during both intravenous cannulation and phlebotomy.