Predicting intertidal organism temperatures with modified land surface models

Physiologically informed organismal climatologies reveal unexpected spatiotemporal trends in temperature

Body temperature is universally recognized as a dominant driver of biological performance. Although the critical distinction between the temperature of an organism and its surrounding habitat has long been recognized, it remains common practice to assume that trends in air temperature-collected via remote sensing or weather stations-are diagnostic of trends in animal temperature and thus of spatiotemporal patterns of physiological stress and mortality risk. Here, by analysing long-term trends recorded by biomimetic temperature sensors designed to emulate intertidal mussel temperature across the US Pacific Coast, we show that trends in maximal organismal temperature ('organismal climatologies') during aerial exposure can differ substantially from those exhibited by co-located environmental data products. Specifically, using linear regression to compare maximal organismal and environmental (air temperature) climatologies, we show that not only are the magnitudes of body and air temperature markedly different, as expected, but so are their temporal trends at both local and biogeographic scales, with some sites showing significant decadal-scale increases in organismal temperature despite reductions in air temperature, or vice versa. The idiosyncratic relationship between the spatiotemporal patterns of organismal and air temperatures suggests that environmental climatology cannot be statistically corrected to serve as an accurate proxy for organismal climatology. Finally, using quantile regression, we show that spatiotemporal trends vary across the distribution of organismal temperature, with extremes shifting in different directions and at different rates than average metrics. Overall, our results highlight the importance of quantifying changes in the entire distribution of temperature to better predict biological performance and dispel the notion that raw or 'corrected' environmental (and specially air temperature) climatologies can be used to predict organismal temperature trends. Hence, despite their widespread coverage and availability, the severe limitations of environmental climatologies suggest that their role in conservation and management policy should be carefully considered.

Roles of multi-level temperature-adaptive responses and microhabitat variation in establishing distributions of intertidal species

How intertidal species survive their harsh environment and how best to evaluate and forecast range shifts in species distribution are two important and closely related questions for intertidal ecologists and global change biologists. Adaptive variation in responses of organisms to environmental change across all levels of biological organization - from behavior to molecular systems - is of key importance in setting distribution patterns, yet studies often neglect the interactions of diverse types of biological variation (e.g. differences in thermal optima owing to genetic and acclimation-induced effects) with environmental variation, notably at the scale of microhabitats. Intertidal species have to cope with extreme and frequently changing thermal stress, and have shown high variation in thermal sensitivities and adaptive responses at different levels of biological organization. Here, I review the physiological and biochemical adaptations of intertidal species to environmental temperature on multiple spatial and temporal scales. With fine-scale datasets for the thermal limits of individuals and for environmental temperature variation at the microhabitat scale, we can map the thermal sensitivity for each individual in different microhabitats, and then scale up the thermal sensitivity analysis to the population level and, finally, to the species level by incorporating physiological traits into species distribution models. These more refined mechanistic models that include consideration of physiological variations have higher predictive power than models that neglect these variations, and they will be crucial to answering the questions posed above concerning adaptive mechanisms and the roles they play in governing distribution patterns in a rapidly changing world.

Coupling habitat-specific temperature scenarios with tolerance landscape to predict the impacts of climate change on farmed bivalves

Due to climate change, heatwaves are likely to become more frequent, prolonged and characterized by higher peak values, compared with climatological averages. However, the thermal tolerance of organisms depends on the actual exposure, which can be modulated by environmental context and microhabitat characteristics. This study investigated the frequency of occurrence of mass mortality events in the next decades for two species of farmed bivalves, the mussel Mytilus galloprovincialis and the clam Ruditapes philippinarum, in a shallow coastal lagoon, characterised by marked diurnal oscillations of water temperature. The effect of heatwaves was estimated by means of tolerance landscape models, which predict the occurrence of 50% mortality based on the exposure intensity and duration. Scenarios of water temperature up to the year 2100 were modelled by combining two mechanistic components, namely: 1) monthly mean water temperatures, simulated using a hydrodynamic model including the heat budget; 2) daily oscillations, estimated from the harmonic analysis of a twenty year-long site-specific time series of water temperature. Scenarios of mean daily sediment temperature were estimated by means of a cross-correlation model, using as input the water temperature one: the model parameters were estimated based on a comprehensive set of site-specific water and sediment temperature observations. The results indicate that for both species the risk of mass mortality rapidly increases starting from the 2060s. Furthermore, the daily patterns of water temperature seemed to be relevant, as overnight it falls below the predicted mortality thresholds for a few hours. These findings suggest that further studies should address: 1) the improvement of tolerance landscape models, in order to take into account the integrated effect of repeated non-lethal stress events on mortality rate; 2) the prediction of environmental temperature in specific habitat, by means of both process-based and data driven models.

A Review of Diopatra Ecology: Current Knowledge, Open Questions, and Future Threats for an Ecosystem Engineering Polychaete

A well-known example of marine ecosystem engineering is the annelid genus Diopatra, which builds large tubes in coastal sediments worldwide. Early studies of Diopatra were among the first to recognize the importance of facilitation in ecology, and Diopatra has become a key marine soft-sediment application of the ecosystem engineering concept. Here, I review our current knowledge of Diopatra ecology, including its natural history, ecosystem engineering effects, and trophic relationships. I particularly explore how human activities are influencing Diopatra in terms of climate change, bait fishing, and species invasions. Most of what we know about Diopatra ecology comes from focal studies of a few species in a few well-known regions. Further evaluating how our current understanding applies to other species and/or other regions will help to refine and deepen our understanding of structure and function in marine systems.

Mapping physiology: biophysical mechanisms define scales of climate change impacts

The rocky intertidal zone is a highly dynamic and thermally variable ecosystem, where the combined influences of solar radiation, air temperature and topography can lead to differences greater than 15°C over the scale of centimetres during aerial exposure at low tide. For most intertidal organisms this small-scale heterogeneity in microclimates can have enormous influences on survival and physiological performance. However, the potential ecological importance of environmental heterogeneity in determining ecological responses to climate change remains poorly understood. We present a novel framework for generating spatially explicit models of microclimate heterogeneity and patterns of thermal physiology among interacting organisms. We used drone photogrammetry to create a topographic map (digital elevation model) at a resolution of 2 × 2 cm from an intertidal site in Massachusetts, which was then fed into to a model of incident solar radiation based on sky view factor and solar position. These data were in turn used to drive a heat budget model that estimated hourly surface temperatures over the course of a year (2017). Body temperature layers were then converted to thermal performance layers for organisms, using thermal performance curves, creating 'physiological landscapes' that display spatially and temporally explicit patterns of 'microrefugia'. Our framework shows how non-linear interactions between these layers lead to predictions about organismal performance and survivorship that are distinct from those made using any individual layer (e.g. topography, temperature) alone. We propose a new metric for quantifying the 'thermal roughness' of a site (RqT, the root mean square of spatial deviations in temperature), which can be used to quantify spatial and temporal variability in temperature and performance at the site level. These methods facilitate an exploration of the role of micro-topographic variability in driving organismal vulnerability to environmental change using both spatially explicit and frequency-based approaches.

Highly polluted life history and acute heat stress, a hazardous mix for blue mussels

Intertidal sessile organisms constitute through their life history unintended stress recorders. This study focuses on the impact of pollution on Mytilus edulis ability to cope with an additional stress. For this purpose, two acclimation stages to different temperatures were conducted before an acute stress exposure in mussels collected from a heavily polluted site. Gill proteomes were analyzed by 2DE and regulated proteins identified. Massive mortality was observed for organisms acclimated to colder temperatures. Despite this major difference, both groups shared a common response with a strong representation of proteoforms corresponding to "folding, sorting and degradation" processes. Nevertheless, surviving mussels exhibit a marked increase in protein degradation consistent with the observed decrease of cell defense proteins. Mussels acclimated to warmer temperature response is essentially characterized by an improved heat shock response. These results show the differential ability of mussels to face both pollution and acute heat stress, particularly for low-acclimated organisms.

Long-term, high frequency in situ measurements of intertidal mussel bed temperatures using biomimetic sensors

At a proximal level, the physiological impacts of global climate change on ectothermic organisms are manifest as changes in body temperatures. Especially for plants and animals exposed to direct solar radiation, body temperatures can be substantially different from air temperatures. We deployed biomimetic sensors that approximate the thermal characteristics of intertidal mussels at 71 sites worldwide, from 1998-present. Loggers recorded temperatures at 10–30 min intervals nearly continuously at multiple intertidal elevations. Comparisons against direct measurements of mussel tissue temperature indicated errors of ~2.0–2.5 °C, during daily fluctuations that often exceeded 15°–20 °C. Geographic patterns in thermal stress based on biomimetic logger measurements were generally far more complex than anticipated based only on ‘habitat-level’ measurements of air or sea surface temperature. This unique data set provides an opportunity to link physiological measurements with spatially- and temporally-explicit field observations of body temperature.

Physiologically grounded metrics of model skill: a case study estimating heat stress in intertidal populations

Models of ecological responses to climate change fundamentally assume that predictor variables, which are often measured at large scales, are to some degree diagnostic of the smaller-scale biological processes that ultimately drive patterns of abundance and distribution. Given that organisms respond physiologically to stressors, such as temperature, in highly non-linear ways, small modelling errors in predictor variables can potentially result in failures to predict mortality or severe stress, especially if an organism exists near its physiological limits. As a result, a central challenge facing ecologists, particularly those attempting to forecast future responses to environmental change, is how to develop metrics of forecast model skill (the ability of a model to predict defined events) that are biologically meaningful and reflective of underlying processes. We quantified the skill of four simple models of body temperature (a primary determinant of physiological stress) of an intertidal mussel, Mytilus californianus, using common metrics of model performance, such as root mean square error, as well as forecast verification skill scores developed by the meteorological community. We used a physiologically grounded framework to assess each model's ability to predict optimal, sub-optimal, sub-lethal and lethal physiological responses. Models diverged in their ability to predict different levels of physiological stress when evaluated using skill scores, even though common metrics, such as root mean square error, indicated similar accuracy overall. Results from this study emphasize the importance of grounding assessments of model skill in the context of an organism's physiology and, especially, of considering the implications of false-positive and false-negative errors when forecasting the ecological effects of environmental change.

Thermal tolerance and climate warming sensitivity in tropical snails

Tropical ectotherms are predicted to be especially vulnerable to climate change because their thermal tolerance limits generally lie close to current maximum air temperatures. This prediction derives primarily from studies on insects and lizards and remains untested for other taxa with contrasting ecologies. We studied the HCT (heat coma temperatures) and ULT (upper lethal temperatures) of 40 species of tropical eulittoral snails (Littorinidae and Neritidae) inhabiting exposed rocky shores and shaded mangrove forests in Oceania, Africa, Asia and North America. We also estimated extremes in animal body temperature at each site using a simple heat budget model and historical (20 years) air temperature and solar radiation data. Phylogenetic analyses suggest that HCT and ULT exhibit limited adaptive variation across habitats (mangroves vs. rocky shores) or geographic locations despite their contrasting thermal regimes. Instead, the elevated heat tolerance of these species (HCT = 44.5 ± 1.8°C and ULT = 52.1 ± 2.2°C) seems to reflect the extreme temperature variability of intertidal systems. Sensitivity to climate warming, which was quantified as the difference between HCT or ULT and maximum body temperature, differed greatly between snails from sunny (rocky shore; Thermal Safety Margin, TSM = -14.8 ± 3.3°C and -6.2 ± 4.4°C for HCT and ULT, respectively) and shaded (mangrove) habitats (TSM = 5.1 ± 3.6°C and 12.5 ± 3.6°C). Negative TSMs in rocky shore animals suggest that mortality is likely ameliorated during extreme climatic events by behavioral thermoregulation. Given the low variability in heat tolerance across species, habitat and geographic location account for most of the variation in TSM and may adequately predict the vulnerability to climate change. These findings caution against generalizations on the impact of global warming across ectothermic taxa and highlight how the consideration of nonmodel animals, ecological transitions, and behavioral responses may alter predictions of studies that ignore these biological details.

A biophysical basis for patchy mortality during heat waves

Extreme heat events cause patchy mortality in many habitats. We examine biophysical mechanisms responsible for patchy mortality in beds of the competitively dominant ecosystem engineer, the marine mussel Mytilus californianus, on the west coast of the United States. We used a biophysical model to predict daily fluctuations in body temperature at sites from southern California to Washington and used results of laboratory experiments on thermal tolerance to determine mortality rates from body temperature. In our model, we varied the rate of thermal conduction within mussel beds and found that this factor can account for large differences in body temperature and consequent mortality during heat waves. Mussel beds provide structural habitat for other species and increase local biodiversity, but, as sessile organisms, they are particularly vulnerable to extreme weather conditions. Identifying critical biophysical mechanisms related to mortality and ecological performance will improve our ability to predict the effects of climate change on these vulnerable ecosystems.

Combining physiological threshold knowledge to species distribution models is key to improving forecasts of the future niche for macroalgae

Species distribution models (SDM) are a useful tool for predicting species range shifts in response to global warming. However, they do not explore the mechanisms underlying biological processes, making it difficult to predict shifts outside the environmental gradient where the model was trained. In this study, we combine correlative SDMs and knowledge on physiological limits to provide more robust predictions. The thermal thresholds obtained in growth and survival experiments were used as proxies of the fundamental niches of two foundational marine macrophytes. The geographic projections of these species' distributions obtained using these thresholds and existing SDMs were similar in areas where the species are either absent-rare or frequent and where their potential and realized niches match, reaching consensus predictions. The cold-temperate foundational seaweed Himanthalia elongata was predicted to become extinct at its southern limit in northern Spain in response to global warming, whereas the occupancy of southern-lusitanic Bifurcaria bifurcata was expected to increase. Combined approaches such as this one may also highlight geographic areas where models disagree potentially due to biotic factors. Physiological thresholds alone tended to over-predict species prevalence, as they cannot identify absences in climatic conditions within the species' range of physiological tolerance or at the optima. Although SDMs tended to have higher sensitivity than threshold models, they may include regressions that do not reflect causal mechanisms, constraining their predictive power. We present a simple example of how combining correlative and mechanistic knowledge provides a rapid way to gain insight into a species' niche resulting in consistent predictions and highlighting potential sources of uncertainty in forecasted responses to climate change.

Mussels as a model system for integrative ecomechanics

Mussels form dense aggregations that dominate temperate rocky shores, and they are key aquaculture species worldwide. Coastal environments are dynamic across a broad range of spatial and temporal scales, and their changing abiotic conditions affect mussel populations in a variety of ways, including altering their investments in structures, physiological processes, growth, and reproduction. Here, we describe four categories of ecomechanical models (biochemical, mechanical, energetic, and population) that we have developed to describe specific aspects of mussel biology, ranging from byssal attachment to energetics, population growth, and fitness. This review highlights how recent advances in these mechanistic models now allow us to link them together across molecular, material, organismal, and population scales of organization. This integrated ecomechanical approach provides explicit and sometimes novel predictions about how natural and farmed mussel populations will fare in changing climatic conditions.

Climate change, species distribution models, and physiological performance metrics: predicting when biogeographic models are likely to fail

Modeling the biogeographic consequences of climate change requires confidence in model predictions under novel conditions. However, models often fail when extended to new locales, and such instances have been used as evidence of a change in physiological tolerance, that is, a fundamental niche shift. We explore an alternative explanation and propose a method for predicting the likelihood of failure based on physiological performance curves and environmental variance in the original and new environments. We define the transient event margin (TEM) as the gap between energetic performance failure, defined as CT_max, and the upper lethal limit, defined as LT_max. If TEM is large relative to environmental fluctuations, models will likely fail in new locales. If TEM is small relative to environmental fluctuations, models are likely to be robust for new locales, even when mechanism is unknown. Using temperature, we predict when biogeographic models are likely to fail and illustrate this with a case study. We suggest that failure is predictable from an understanding of how climate drives nonlethal physiological responses, but for many species such data have not been collected. Successful biogeographic forecasting thus depends on understanding when the mechanisms limiting distribution of a species will differ among geographic regions, or at different times, resulting in realized niche shifts. TEM allows prediction of the likelihood of such model failure.