Herbivore effects increase with latitude across the extent of a foundational seagrass.

Climate change is altering the functioning of foundational ecosystems. While the direct effects of warming are expected to influence individual species, the indirect effects of warming on species interactions remain poorly understood. In marine systems, as tropical herbivores undergo poleward range expansion, they may change food web structure and alter the functioning of key habitats. While this process ('tropicalization') has been documented within declining kelp forests, we have a limited understanding of how this process might unfold across other systems. Here we use a network of sites spanning 23° of latitude to explore the effects of increased herbivory (simulated via leaf clipping) on the structure of a foundational marine plant (turtlegrass). By working across its geographic range, we also show how gradients in light, temperature and nutrients modified plant responses. We found that turtlegrass near its northern boundary was increasingly affected (reduced productivity) by herbivory and that this response was driven by latitudinal gradients in light (low insolation at high latitudes). By contrast, low-latitude meadows tolerated herbivory due to high insolation which enhanced plant carbohydrates. We show that as herbivores undergo range expansion, turtlegrass meadows at their northern limit display reduced resilience and may be under threat of ecological collapse.

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.

Nocturnal surveys of lined seahorses reveal increased densities and seasonal recruitment patterns.

Although the nighttime ecology of organisms remains understudied, nocturnal surveys play an integral part in assessing fish assemblages and the selective forces shaping them. Eleuthera (Bahamas) contains an unusual population of lined seahorses (Hippocampus erectus) in an anchialine lake, possessing morphological characteristics distinct from those found in the ocean. Population surveys for seahorses and their potential predators were conducted at midnight and midday during wet and dry seasons, with belt transects perpendicular to the shoreline that increased in depth away from shore. Nocturnal surveys uncovered seahorse densities 259% higher than daytime transects on average. Sex ratios were consistently male-biased, and the frequency of animals from different reproductive categories varied significantly by time of day, with gravid males observed around the clock but females and nongravid males observed more often at night. Spatial and seasonal recruitment was detected for the first time in this species, with an increase in juveniles detected in the shallow ends of transects during dry season surveys. Juvenile recruitment is poorly understood across syngnathid fishes, so the detection of early recruits at night has broad implications for this fish family. Seahorses from all reproductive categories were perched significantly higher in the water column during the night regardless of their depth or season. Predator densities followed a similar pattern with higher densities observed at night, indicating that elevated nocturnal perch height may be a response to predator presence. However, the selective agents driving these nocturnal behaviors have yet to be identified. Considering H. erectus is listed on the IUCN Red List as "Vulnerable," the increase in nocturnal population size and the detection of juveniles has crucial implications for understanding their ecology, recruitment, and conservation.

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.

Early warning signal reliability varies with COVID-19 waves.

Early warning signals (EWSs) aim to predict changes in complex systems from phenomenological signals in time series data. These signals have recently been shown to precede the emergence of disease outbreaks, offering hope that policymakers can make predictive rather than reactive management decisions. Here, using a novel, sequential analysis in combination with daily COVID-19 case data across 24 countries, we suggest that composite EWSs consisting of variance, autocorrelation and skewness can predict nonlinear case increases, but that the predictive ability of these tools varies between waves based upon the degree of critical slowing down present. Our work suggests that in highly monitored disease time series such as COVID-19, EWSs offer the opportunity for policymakers to improve the accuracy of urgent intervention decisions but best characterize hypothesized critical transitions.