To understand the effects of temperature on biological systems, we compile, organize, and analyze a database of 1,072 thermal responses for microbes, plants, and animals. The unprecedented diversity ...of traits (n = 112), species (n = 309), body sizes (15 orders of magnitude), and habitats (all major biomes) in our database allows us to quantify novel features of the temperature response of biological traits. In particular, analysis of the rising component of within-species (intraspecific) responses reveals that 87% are fit well by the Boltzmann-Arrhenius model. The mean activation energy for these rises is 0.66 ± 0.05 eV, similar to the reported across-species (interspecific) value of 0.65 eV. However, systematic variation in the distribution of rise activation energies is evident, including previously unrecognized right skewness around a median of 0.55 eV. This skewness exists across levels of organization, taxa, trophic groups, and habitats, and it is partially explained by prey having increased trait performance at lower temperatures relative to predators, suggesting a thermal version of the life-dinner principle--stronger selection on running for your life than running for your dinner. For unimodal responses, habitat (marine, freshwater, and terrestrial) largely explains the mean temperature at which trait values are optimal but not variation around the mean. The distribution of activation energies for trait falls has a mean of 1.15 ± 0.39 eV (significantly higher than rises) and is also right-skewed. Our results highlight generalities and deviations in the thermal response of biological traits and help to provide a basis to predict better how biological systems, from cells to communities, respond to temperature change.
1. Environmental temperature has systematic effects on rates of species interactions, primarily through its influence on organismal physiology. 2. We present a mechanistic model for the thermal ...response of consumer–resource interactions. We focus on how temperature affects species interactions via key traits – body velocity, detection distance, search rate and handling time – that underlie per capita consumption rate. The model is general because it applies to all foraging strategies: active-capture (both consumer and resource body velocity are important), sit-and-wait (resource velocity dominates) and grazing (consumer velocity dominates). 3. The model predicts that temperature influences consumer–resource interactions primarily through its effects on body velocity (either of the consumer, resource or both), which determines how often consumers and resources encounter each other, and that asymmetries in the thermal responses of interacting species can introduce qualitative, not just quantitative, changes in consumer–resource dynamics. We illustrate this by showing how asymmetries in thermal responses determine equilibrium population densities in interacting consumer–resource pairs. 4. We test for the existence of asymmetries in consumer–resource thermal responses by analysing an extensive database on thermal response curves of ecological traits for 309 species spanning 15 orders of magnitude in body size from terrestrial, marine and freshwater habitats. We find that asymmetries in consumer–resource thermal responses are likely to be a common occurrence. 5. Overall, our study reveals the importance of asymmetric thermal responses in consumer–resource dynamics. In particular, we identify three general types of asymmetries: (i) different levels of performance of the response, (ii) different rates of response (e.g. activation energies) and (iii) different peak or optimal temperatures. Such asymmetries should occur more frequently as the climate changes and species' geographical distributions and phenologies are altered, such that previously noninteracting species come into contact. 6. By using characteristics of trophic interactions that are often well known, such as body size, foraging strategy, thermy and environmental temperature, our framework should allow more accurate predictions about the thermal dependence of consumer–resource interactions. Ultimately, integration of our theory into models of food web and ecosystem dynamics should be useful in understanding how natural systems will respond to current and future temperature change.
Trophic interactions govern biomass fluxes in ecosystems, and stability in food webs. Knowledge of how trophic interaction strengths are affected by differences among habitats is crucial for ...understanding variation in ecological systems. Here we show how substantial variation in consumption-rate data, and hence trophic interaction strengths, arises because consumers tend to encounter resources more frequently in three dimensions (3D) (for example, arboreal and pelagic zones) than two dimensions (2D) (for example, terrestrial and benthic zones). By combining new theory with extensive data (376 species, with body masses ranging from 5.24 × 10(-14) kg to 800 kg), we find that consumption rates scale sublinearly with consumer body mass (exponent of approximately 0.85) for 2D interactions, but superlinearly (exponent of approximately 1.06) for 3D interactions. These results contradict the currently widespread assumption of a single exponent (of approximately 0.75) in consumer-resource and food-web research. Further analysis of 2,929 consumer-resource interactions shows that dimensionality of consumer search space is probably a major driver of species coexistence, and the stability and abundance of populations.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Movement enables mobile organisms to respond to local environmental conditions and is driven by a combination of external and internal factors operating at multiple scales. Here, we explored how ...resource distribution interacted with the internal state of organisms to drive patterns of movement. Specifically, we tracked snail movements on experimental landscapes where resource (algal biofilm) distribution varied from 0 to 100% coverage and quantified how that movement changed over a 24 h period. Resource distribution strongly affected snail movement. Trajectories were tortuous (i.e. Brownian-like) within resource patches but straighter (i.e. Lévy) in resource-free (bare) patches. The average snail speed was slower in resource patches, where snails spent most of their time. Different patterns of movement between resource and bare patches explained movement at larger spatial scales; movement was ballistic-like Lévy in resource-free landscapes, Lévy in landscapes with intermediate resource coverage and approximated Brownian in landscapes covered in resources. Our temporal analysis revealed that movement patterns changed predictably for snails that satiated their hunger and then performed other behaviours. These changes in movement patterns through time were similar across all treatments that contained resources. Thus, external and internal factors interacted to shape the inherently flexible movement of these snails.
•Individual behavior is integral to the organization of ecological systems.•Automated image-based tracking offers novel opportunities to study behavior.•Tracking data allows linking individual to ...higher-level ecological processes.•A diverse range of taxa have now been tracked in a variety of habitats.•Automated image-based tracking has an important role in ecology.
The behavior of individuals determines the strength and outcome of ecological interactions, which drive population, community, and ecosystem organization. Bio-logging, such as telemetry and animal-borne imaging, provides essential individual viewpoints, tracks, and life histories, but requires capture of individuals and is often impractical to scale. Recent developments in automated image-based tracking offers opportunities to remotely quantify and understand individual behavior at scales and resolutions not previously possible, providing an essential supplement to other tracking methodologies in ecology. Automated image-based tracking should continue to advance the field of ecology by enabling better understanding of the linkages between individual and higher-level ecological processes, via high-throughput quantitative analysis of complex ecological patterns and processes across scales, including analysis of environmental drivers.
Thermal acclimation capacity, the degree to which organisms can alter their optimal performance temperature and critical thermal limits with changing temperatures, reflects their ability to respond ...to temperature variability and thus might be important for coping with global climate change. Here, we combine simulation modelling with analysis of published data on thermal acclimation and breadth (range of temperatures over which organisms perform well) to develop a framework for predicting thermal plasticity across taxa, latitudes, body sizes, traits, habitats and methodological factors. Our synthesis includes > 2000 measures of acclimation capacities from > 500 species of ectotherms spanning fungi, invertebrates, and vertebrates from freshwater, marine and terrestrial habitats. We find that body size, latitude, and methodological factors often interact to shape acclimation responses and that acclimation rate scales negatively with body size, contributing to a general negative association between body size and thermal breadth across species. Additionally, we reveal that acclimation capacity increases with body size, increases with latitude (to mid‐latitudinal zones) and seasonality for smaller but not larger organisms, decreases with thermal safety margin (upper lethal temperature minus maximum environmental temperatures), and is regularly underestimated because of experimental artefacts. We then demonstrate that our framework can predict the contribution of acclimation plasticity to the IUCN threat status of amphibians globally, suggesting that phenotypic plasticity is already buffering some species from climate change.
Understanding how food webs will respond to globally rising temperatures is a pressing issue. Temperature effects on food webs are likely underpinned by differences in the thermal sensitivity of ...consumers and resources, or thermal asymmetries. We identify three sources of asymmetry in the rising portion of thermal performance curves: inter‐thermy variation across thermoregulatory groups, intra‐thermy variation within a thermoregulatory group and rate‐dependent variation in how different ecological rates respond to temperature.
We use a large empirical dataset on thermal sensitivities across thermoregulatory groups to explore how prevalent thermal asymmetries are in real consumer–resource interactions. We then develop theory to illustrate how food web temperature responses are mediated by the magnitude and direction of these thermal asymmetries. We use this model to show possible conditions under which food webs could respond to warming as currently expected, and when that may not be the case.
Our results suggest that inter‐thermy, intra‐thermy and rate‐dependent asymmetries are likely common in natural food webs. We show how all thermal asymmetries have important effects on species abundances across trophic levels as well as the maximum trophic position in the food web. Both the direction of the asymmetries (i.e. which species respond more strongly) and their magnitude (the difference in thermal responses) determine the temperature response of the food web and, consistent with current expectations, top predator abundance almost always declines with temperature, even though maximum trophic position may increase.
While our model shows that food web temperature responses can be varied, much of this variation can be explained by considering thermal asymmetries. Our study provides new data and theoretical insights into the widely varying food web effects of warming observed in laboratory, experimental and observational settings, and clarifies how predator and prey thermal ecology may influence overall food web responses in a changing world.
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Resumen
Entender como las redes tróficas responderán al aumento global en la temperatura ambiente es un importante problema en Ecología. Los efectos de la temperatura en las redes tróficas probablemente dependan de diferencias en la sensibilidad térmica de consumidores in recursos, también conocidas como asimetrías térmicas. En este trabajo identificamos tres fuentes de asimetrías térmicas en la porción inicial (o creciente) de las curvas de respuesta térmica (Temperature Performance Curves) a las que llamamos: variación inter‐térmica, que ocurre entre organismos de diferentes grupos termorregulatorios, variación intra‐térmica, entre organismos del mismo grupo termorregulatorio, o variación dependiente de tasa, que ocurre entre organismos para los cuales distintas tasas (o características) ecológicas responden de forma distinta.
Usamos un enorme set de datos empíricos sobre sensibilidades térmicas que incluye organismos de todos los grupos termorregulatorios y exploramos qué tan prevalentes son las asimetrías térmicas en interacciones consumidor‐recurso reales. Luego desarrollamos modelos matemáticos para ilustrar como la respuesta de las redes tróficas a un aumento en las temperaturas es mediado por la magnitud y la dirección de estas asimetrías térmicas. Utilizamos nuestro modelo para mostrar en qué situaciones las respuestas de las redes tróficas al aumento en la temperatura son como esperado por el paradigma actual, y cuando eso no sucedería.
Nuestros resultados sugieren que asimetrías inter‐térmicas, intra‐térmicas, y dependientes de tasa, probablemente sean comunes en redes tróficas naturales. También mostramos que todas las formas de asimetría térmica tienen importantes efectos en la abundancia de las especies a través de los distintos niveles tróficos, como también en el máximo nivel trófico de estas redes de interacción. Tanto la dirección de la asimetría (definido como qué especie, consumidor o recurso, responde más fuertemente a un aumento en la temperatura) como la magnitud de la asimetría (definida como la diferencia en la respuesta del par de organismos que interactúan) determinan la respuesta al aumento en la temperatura de la red como un todo, y, consistente con predicciones del paradigma actual, suelen llevar a un declive en la abundancia de los depredadores tope, aún cuando el máximo nivel trófico pueda aumentar.
Nuestro modelo muestra que las respuestas de las redes tróficas a un aumento en la temperatura pueden ser variadas, aunque mucha de esta variación puede ser explicada teniendo en cuenta la existencia de asimetrías térmicas. Nuestro estudio provee nuevos datos y resultados teóricos que ayudan a esclarecer el por qué de las respuestas variadas de las redes tróficas a un aumento en la temperatura observadas en el campo y en el laboratorio, y esclarece como la ecología térmica de consumidores y recursos influye en la respuesta de las redes tróficas en un contexto de cambio climático global.
Read the free Plain Language Summary for this article on the Journal blog.
Metabolic theory predicts whole-ecosystem properties Schramski, John R.; Dell, Anthony I.; Grady, John M. ...
Proceedings of the National Academy of Sciences,
02/2015, Letnik:
112, Številka:
8
Journal Article
Recenzirano
Odprti dostop
Understanding the effects of individual organisms on material cycles and energy fluxes within ecosystems is central to predicting the impacts of human-caused changes on climate, land use, and ...biodiversity. Here we present a theory that integrates metabolic (organism-based bottom-up) and systems (ecosystem-based topdown) approaches to characterize how the metabolism of individuals affects the flows and stores of materials and energy in ecosystems. The theory predicts how the average residence time of carbon molecules, total system throughflow (TST), and amount of recycling vary with the body size and temperature of the organisms and with trophic organization. We evaluate the theory by comparing theoretical predictions with outputs of numerical models designed to simulate diverse ecosystem types and with empirical data for real ecosystems. Although residence times within different ecosystems vary by orders of magnitude—from weeks in warm pelagic oceans with minute phytoplankton producers to centuries in cold forests with large tree producers—as predicted, all ecosystems fall along a single line: residence time increases linearly with slope = 1.0 with the ratio of whole-ecosystem biomass to primary productivity (B/P). TST was affected predominantly by primary productivity and recycling by the transfer of energy from microbial decomposers to animal consumers. The theory provides a robust basis for estimating the flux and storage of energy, carbon, and other materials in terrestrial, marine, and freshwater ecosystems and for quantifying the roles of different kinds of organisms and environments at scales from local ecosystems to the biosphere.
Whether the thermal sensitivity of an organism’s traits follows the simple Boltzmann-Arrhenius model remains a contentious issue that centers around consideration of its operational temperature range ...and whether the sensitivity corresponds to one or a few underlying rate-limiting enzymes. Resolving this issue is crucial, because mechanistic models for temperature dependence of traits are required to predict the biological effects of climate change. Here, by combining theory with data on 1,085 thermal responses from a wide range of traits and organisms, we show that substantial variation in thermal sensitivity (activation energy) estimates can arise simply because of variation in the range of measured temperatures. Furthermore, when thermal responses deviate systematically from the Boltzmann-Arrhenius model, variation in measured temperature ranges across studies can bias estimated activation energy distributions toward higher mean, median, variance, and skewness. Remarkably, this bias alone can yield activation energies that encompass the range expected from biochemical reactions (from ∼0.2 to 1.2 eV), making it difficult to establish whether a single activation energy appropriately captures thermal sensitivity. We provide guidelines and a simple equation for partially correcting for such artifacts. Our results have important implications for understanding the mechanistic basis of thermal responses of biological traits and for accurately modeling effects of variation in thermal sensitivity on responses of individuals, populations, and ecological communities to changing climatic temperatures.
Climate warming is expected to have large effects on ecosystems in part due to the temperature dependence of metabolism. The responses of metabolic rates to climate warming may be greatest in the ...tropics and at low elevations because mean temperatures are warmer there and metabolic rates respond exponentially to temperature (with exponents >1). However, if warming rates are sufficiently fast in higher latitude/elevation lakes, metabolic rate responses to warming may still be greater there even though metabolic rates respond exponentially to temperature. Thus, a wide range of global patterns in the magnitude of metabolic rate responses to warming could emerge depending on global patterns of temperature and warming rates. Here we use the Boltzmann–Arrhenius equation, published estimates of activation energy, and time series of temperature from 271 lakes to estimate long‐term (1970–2010) changes in 64 metabolic processes in lakes. The estimated responses of metabolic processes to warming were usually greatest in tropical/low‐elevation lakes even though surface temperatures in higher latitude/elevation lakes are warming faster. However, when the thermal sensitivity of a metabolic process is especially weak, higher latitude/elevation lakes had larger responses to warming in parallel with warming rates. Our results show that the sensitivity of a given response to temperature (as described by its activation energy) provides a simple heuristic for predicting whether tropical/low‐elevation lakes will have larger or smaller metabolic responses to warming than higher latitude/elevation lakes. Overall, we conclude that the direct metabolic consequences of lake warming are likely to be felt most strongly at low latitudes and low elevations where metabolism‐linked ecosystem services may be most affected.
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