49 results found
Zheng JX, Pawar S, Goodman DFM, 2021, Further towards unambiguous edge bundling: Investigating power-confluentdrawings for network visualization, IEEE Transactions on Visualization and Computer Graphics, Vol: 27, Pages: 2244-2249, ISSN: 1077-2626
Bach et al.  recently presented an algorithm for constructing confluentdrawings, by leveraging power graph decomposition to generate an auxiliaryrouting graph. We identify two problems with their method and offer a singlesolution to solve both. We also classify the exact type of confluent drawingsthat the algorithm can produce as 'power-confluent', and prove that it is asubclass of the previously studied 'strict confluent' drawing. A descriptionand source code of our implementation is also provided, which additionallyincludes an improved method for power graph construction.
Ho H-C, Tylianakis JM, Pawar S, 2020, Behaviour moderates the impacts of food-web structure on species coexistence, Ecology Letters, Vol: 24, Pages: 298-309, ISSN: 1461-023X
How species coexistence (mathematical ‘feasibility’) in food webs emerges from species' trophic interactions remains a long‐standing open question. Here we investigate how structure (network topology and body‐size structure) and behaviour (foraging strategy and spatial dimensionality of interactions) interactively affect feasibility in food webs. Metabolically‐constrained modelling of food‐web dynamics based on whole‐organism consumption revealed that feasibility is promoted in systems dominated by large‐eat‐small foraging (consumers eating smaller resources) whenever (1) many top consumers are present, (2) grazing or sit‐and‐wait foraging strategies are common, and (3) species engage in two‐dimensional interactions. Congruently, the first two conditions were associated with dominance of large‐eat‐small foraging in 74 well‐resolved (primarily aquatic) real‐world food webs. Our findings provide a new, mechanistic understanding of how behavioural properties can modulate the effects of structural properties on species coexistence in food webs, and suggest that ‘being feasible’ constrains the spectra of behavioural and structural properties seen in natural food webs.
Kontopoulos D-G, Smith TP, Barraclough TG, et al., 2020, Adaptive evolution shapes the present-day distribution of the thermal sensitivity of population growth rate, PLoS Biology, Vol: 18, ISSN: 1544-9173
Developing a thorough understanding of how ectotherm physiology adapts to different thermal environments is of crucial importance, especially in the face of global climate change. A key aspect of an organism's thermal performance curve (TPC)-the relationship between fitness-related trait performance and temperature-is its thermal sensitivity, i.e., the rate at which trait values increase with temperature within its typically experienced thermal range. For a given trait, the distribution of thermal sensitivities across species, often quantified as "activation energy" values, is typically right-skewed. Currently, the mechanisms that generate this distribution are unclear, with considerable debate about the role of thermodynamic constraints versus adaptive evolution. Here, using a phylogenetic comparative approach, we study the evolution of the thermal sensitivity of population growth rate across phytoplankton (Cyanobacteria and eukaryotic microalgae) and prokaryotes (bacteria and archaea), 2 microbial groups that play a major role in the global carbon cycle. We find that thermal sensitivity across these groups is moderately phylogenetically heritable, and that its distribution is shaped by repeated evolutionary convergence throughout its parameter space. More precisely, we detect bursts of adaptive evolution in thermal sensitivity, increasing the amount of overlap among its distributions in different clades. We obtain qualitatively similar results from evolutionary analyses of the thermal sensitivities of 2 physiological rates underlying growth rate: net photosynthesis and respiration of plants. Furthermore, we find that these episodes of evolutionary convergence are consistent with 2 opposing forces: decrease in thermal sensitivity due to environmental fluctuations and increase due to adaptation to stable environments. Overall, our results indicate that adaptation can lead to large and relatively rapid shifts in thermal sensitivity, especially in microbes f
Kontopoulos D-G, Patmanidis I, Barraclough TG, et al., 2020, Higher temperatures worsen the effects of mutations on protein stability
<jats:title>Abstract</jats:title><jats:p>Understanding whether and how temperature increases alter the effects of mutations on protein stability is crucial for understanding the limits to thermal adaptation by organisms. Currently, it is generally assumed that the stability effects of mutations are independent of temperature. Yet, mutations should become increasingly destabilizing as temperature rises due to the increase in the energy of atoms. Here, by performing an extensive computational analysis on the essential enzyme adenylate kinase in prokaryotes, we show, for the first time, that mutations become more destabilizing with temperature both across and within species. Consistent with these findings, we find that substitution rates of prokaryotes decrease nonlinearly with temperature. Our results suggest that life on Earth likely originated in a moderately thermophilic and thermally fluctuating environment, and indicate that global warming should decrease the per-generation rate of molecular evolution of prokaryotes.</jats:p>
Cator L, Johnson LR, Mordecai EA, et al., 2020, The role of vector trait variation in vector-borne disease dynamics, Frontiers in Ecology and Evolution, Vol: 8, ISSN: 2296-701X
Many important endemic and emerging diseases are transmitted by vectorsthat are biting arthropods. The functional traits of vectors can affect pathogen transmission ratesdirectly andalso through their effect on vector population dynamics. Increasing empirical evidence shows that vector traits vary significantlyacross individuals, populations, and environmental conditions, andat time scales relevant to disease transmission dynamics. Here, we review empirical evidence for variation invector traits and how this trait variation is currentlyincorporated into mathematical modelsof vector-borne disease transmission. We argue that mechanistically incorporating trait variationinto these models, by explicitly capturingits effects on vector fitness and abundance, can improve the reliability oftheir predictions in a changing world. We provide a conceptual framework for incorporating trait variation into vector-borne disease transmission models,and highlight key empirical and theoretical challenges.This framework provides a means to conceptualize how traits can be incorporated in Vector Borne Disease systems,and identifies key areas in which trait variation can be explored. Determining when and to what extent it is important to incorporate trait variation into vector borne disease models remainsan important, outstanding question.
Kontopoulos D, van Sebille E, Lange M, et al., 2020, Phytoplankton thermal responses adapt in the absence of hard thermodynamic constraints, Evolution, Vol: 74, Pages: 775-790, ISSN: 0014-3820
To better predict how populations and communities respond to climatic temperature variation, it is necessary to understand how the shape of the response of fitness‐related rates to temperature evolves (the thermal performance curve). Currently, there is disagreement about the extent to which the evolution of thermal performance curves is constrained. One school of thought has argued for the prevalence of thermodynamic constraints through enzyme kinetics, whereas another argues that adaptation can—at least partly—overcome such constraints. To shed further light on this debate, we perform a phylogenetic meta‐analysis of the thermal performance curves of growth rate of phytoplankton—a globally important functional group—, controlling for environmental effects (habitat type and thermal regime). We find that thermodynamic constraints have a minor influence on the shape of the curve. In particular, we detect a very weak increase of maximum performance with the temperature at which the curve peaks, suggesting a weak “hotter‐is‐better” constraint. Also, instead of a constant thermal sensitivity of growth across species, as might be expected from strong constraints, we find that all aspects of the thermal performance curve evolve along the phylogeny. Our results suggest that phytoplankton thermal performance curves adapt to thermal environments largely in the absence of hard thermodynamic constraints.
Rabeling SC, Lim JL, Tidon R, et al., 2019, Seasonal variation of a plant-pollinator network in the Brazilian Cerrado: implications for community structure and robustness, PLoS One, Vol: 14, ISSN: 1932-6203
Seasonal variation in the availability of floral hosts or pollinators is a key factor influencing diversity in plant-pollinator communities. In seasonally dry Neotropical habitats, where month-long periods of extreme drought are followed by a long rainy season, flowering is often synchronized with the beginning of precipitation, when environmental conditions are most beneficial for plant reproduction. In the Brazilian Cerrado, a seasonally dry ecosystem considered one of the world's biodiversity hotspots for angiosperms, plants with shallow root systems flower predominantly during the rainy season. Foraging activity in social bees however, the major pollinators in this biome, is not restricted to any particular season because a constant supply of resources is necessary to sustain their perennial colonies. Despite the Cerrado's importance as a center of plant diversity, the influence of its extreme cycles of drought and precipitation on the dynamics and stability of plant-pollinator communities is not well understood. We sampled plant-pollinator interactions of a Cerrado community weekly for one year and used network analyses to characterize intra-annual seasonal variation in community structure. We also compared seasonal differences in community robustness to species loss by simulating extinctions of plants and pollinators. We find that the community shrinks significantly in size during the dry season, becoming more vulnerable to disturbance due to the smaller pool of floral hosts available to pollinators during this period. Major changes in plant species composition but not in pollinators has led to high levels of turnover in plant-pollinator associations across seasons, indicated by in interaction dissimilarity (<3% of shared interactions). Aseasonal pollinators, which mainly include social bees and some solitary specialized bees, functioned as keystone species, maintaining robustness during periods of drastic changes in climatic conditions.
Smith T, Thomas TJH, Garcia-Carreras B, et al., 2019, Community-level respiration of prokaryotic microbes may rise with global warming, Nature Communications, Vol: 10, ISSN: 2041-1723
Understanding how the metabolic rates of prokaryotes respond to temperature is fun-damental to our understanding of how ecosystem functioning will be altered by climatechange, as these micro-organisms are major contributors to global carbon efflux. Ecologicalmetabolic theory suggests that species living at higher temperatures evolve higher growthrates than those in cooler niches due to thermodynamic constraints. Here, using a globalprokaryotic dataset, we find that maximal growth rate at thermal optimum increases withtemperature for mesophiles (temperature optima.45◦C), but not thermophiles (&45◦C).Furthermore, short-term (within-day) thermal responses of prokaryotic metabolic rates aretypically more sensitive to warming than those of eukaryotes. Because climatic warmingwill mostly impact ecosystems in the mesophilic temperature range, we conclude that asmicrobial communities adapt to higher temperatures, their metabolic rates and therefore,biomass-specific CO2production, will inevitably rise. Using a mathematical model, weillustrate the potential global impacts of these findings.
Ho H-C, Tylianakis JM, Zheng JX, et al., 2019, Predation risk influences food-web structure by constraining species diet choice, Ecology Letters, Vol: 22, Pages: 1734-1745, ISSN: 1461-023X
The foraging behaviour of species determines their diet and, therefore, also emergent food-web structure. Optimal foraging theory (OFT) has previously been applied to understand the emergence of food-web structure through a consumer-centric consideration of diet choice. However, the resource-centric viewpoint, where species adjust their behaviour to reduce the risk of predation, has not been considered. We develop a mechanistic model that merges metabolic theory with OFT to incorporate the effect of predation risk on diet choice to assemble food webs. This 'predation-risk-compromise' (PR) model better captures the nestedness and modularity of empirical food webs relative to the classical optimal foraging model. Specifically, compared with optimal foraging alone, risk-mitigated foraging leads to more-nested but less-modular webs by broadening the diet of consumers at intermediate trophic levels. Thus, predation risk significantly affects food-web structure by constraining species' ability to forage optimally, and needs to be considered in future work.
Zheng JX, Pawar S, Goodman DFM, 2019, Graph drawing by stochastic gradient descent, IEEE Transactions on Visualization and Computer Graphics, Vol: 25, Pages: 2738-2748, ISSN: 1077-2626
A popular method of force-directed graph drawing is multidimensional scaling using graph-theoretic distances as input. We present an algorithm to minimize its energy function, known as stress, by using stochastic gradient descent (SGD) to move a single pair of vertices at a time. Our results show that SGD can reach lower stress levels faster and more consistently than majorization, without needing help from a good initialization. We then show how the unique properties of SGD make it easier to produce constrained layouts than previous approaches. We also show how SGD can be directly applied within the sparse stress approximation of Ortmann et al. , making the algorithm scalable up to large graphs.
Kontopoulos D-G, Smith TP, Barraclough TG, et al., 2019, Adaptive evolution shapes the present-day distribution of the thermal sensitivity of population growth rate, Publisher: Cold Spring Harbor Laboratory
<jats:title>Abstract</jats:title><jats:p>Developing a thorough understanding of how ectotherm physiology adapts to different thermal environments is of crucial importance, especially in the face of global climate change. A key aspect of an organism’s thermal performance curve—the relationship between fitness-related trait performance and temperature—is its thermal sensitivity, i.e., the rate at which trait values increase with temperature within its typically-experienced thermal range. For a given trait, the distribution of thermal sensitivities across species, often quantified as “activation energy” values, is typically right-skewed. Currently, the mechanisms that generate this distribution are unclear, with considerable debate about the role of thermodynamic constraints vs adaptive evolution. Here, using a phylogenetic comparative approach, we study the evolution of the thermal sensitivity of population growth rate across phytoplankton (Cyanobacteria and eukaryotic microalgae) and prokaryotes (bacteria and archaea), two microbial groups that play a major role in the global carbon cycle. We find that thermal sensitivity across these groups is moderately phylogenetically heritable, and that its distribution is shaped by repeated evolutionary convergence throughout its parameter space. More precisely, we detect bursts of adaptive evolution in thermal sensitivity, increasing the amount of overlap among its distributions in different clades. We obtain qualitatively similar results from evolutionary analyses of the thermal sensitivities of two physiological rates underlying growth rate: net photosynthesis and respiration of plants. Furthermore, we find that these episodes of evolutionary convergence are consistent with two opposing forces: decrease in thermal sensitivity due to environmental fluctuations and increase due to adaptation to stable environments. Overall, our results indicate that adaptation can lead to large a
Pawar S, Dell AI, Lin T, et al., 2019, Interaction dimensionality scales up to generate bimodal consumer-resource size-ratio distributions in ecological communities, Frontiers in Ecology and Evolution, Vol: 7, ISSN: 2296-701X
Understanding constraints on consumer-resource body size-ratios is fundamentally important from both ecological and evolutionary perspectives. By analyzing data on 4,685 consumer-resource interactions from nine ecological communities, we show that in spatially complex environments—where consumers can forage in both two (2D, e.g., benthic zones) and three (3D, e.g., pelagic zones) spatial dimensions—the resource-to-consumer body size-ratio distribution tends toward bimodality, with different median 2D and 3D peaks. Specifically, we find that median size-ratio in 3D is consistently smaller than in 2D both within and across communities. Furthermore, 2D and 3D size (not size-ratio) distributions within any community are generally indistinguishable statistically, indicating that the bimodality in size-ratios is not driven simply by a priori size-segregation of species (and therefore, interactions) by dimensionality, but due to other factors. We develop theory that correctly predicts the direction and magnitude of these differences between 2D and 3D size-ratio distributions. Our theory suggests that community-level size-ratio bimodality emerges from the stronger scaling of consumption rate with size in 3D interactions than in 2D which both, maximizes consumer fitness, and allows coexistence, across a larger range of size-ratios in 3D. We also find that consumer gape-limitation can amplify differences between 2D and 3D size-ratios, and that for either dimensionality, higher carrying capacity allows coexistence of a wider range of size-ratios. Our results reveal new and general insights into the size structure of ecological communities, and show that spatial complexity of the environment can have far reaching effects on community structure and dynamics across scales of organization.
Rund SSC, Braak K, Cator L, et al., 2019, MIReAD, a minimum information standard for reporting arthropod abundance data, Scientific Data, Vol: 6, ISSN: 2052-4463
Arthropods play a dominant role in natural and human-modified terrestrial ecosystem dynamics. Spatially-explicit arthropod population time-series data are crucial for statistical or mathematical models of these dynamics and assessment of their veterinary, medical, agricultural, and ecological impacts. Such data have been collected world-wide for over a century, but remain scattered and largely inaccessible. In particular, with the ever-present and growing threat of arthropod pests and vectors of infectious diseases, there are numerous historical and ongoing surveillance efforts, but the data are not reported in consistent formats and typically lack sufficient metadata to make reuse and re-analysis possible. Here, we present the first-ever minimum information standard for arthropod abundance, Minimum Information for Reusable Arthropod Abundance Data (MIReAD). Developed with broad stakeholder collaboration, it balances sufficiency for reuse with the practicality of preparing the data for submission. It is designed to optimize data (re)usability from the “FAIR,” (Findable, Accessible, Interoperable, and Reusable) principles of public data archiving (PDA). This standard will facilitate data unification across research initiatives and communities dedicated to surveillance for detection and control of vector-borne diseases and pests.
Kontopoulos D-G, van Sebille E, Lange M, et al., 2018, Phytoplankton thermal responses adapt in the absence of hard thermodynamic constraints, Publisher: Cold Spring Harbor Laboratory
<jats:title>Abstract</jats:title><jats:p>To better predict how populations and communities respond to climatic temperature variation, it is necessary to understand how the shape of the response of fitness-related traits to temperature evolves (the thermal performance curve). Currently, there is disagreement about the extent to which the evolution of thermal performance curves is constrained. One school of thought has argued for the prevalence of thermodynamic constraints through enzyme kinetics, whereas another argues that adaptation can—at least partly—overcome such constraints. To shed further light on this debate, we perform a phylogenetic meta-analysis of the thermal performance curves of growth rate of phytoplankton—a globally important functional group—, controlling for environmental effects (habitat type and thermal regime). We find that thermodynamic constraints have a minor influence on the shape of the curve. In particular, we detect a very weak increase of maximum performance with the temperature at which the curve peaks, suggesting a weak “hotter-is-better” constraint. Also, instead of a constant thermal sensitivity of growth across species, as might be expected from strong constraints, we find that all aspects of the thermal performance curve evolve along the phylogeny. Our results suggest that phytoplankton thermal performance curves adapt to thermal environments largely in the absence of hard thermodynamic constraints.</jats:p>
Kissling WD, Walls R, Bowser A, et al., 2018, Towards global data products of Essential Biodiversity Variables on species traits, Nature Ecology and Evolution, Vol: 2, Pages: 1531-1540, ISSN: 2397-334X
Essential Biodiversity Variables (EBVs) allow observation and reporting of global biodiversity change, but a detailed framework for the empirical derivation of specific EBVs has yet to be developed. Here, we re-examine and refine the previous candidate set of species traits EBVs and show how traits related to phenology, morphology, reproduction, physiology and movement can contribute to EBV operationalization. The selected EBVs express intra-specific trait variation and allow monitoring of how organisms respond to global change. We evaluate the societal relevance of species traits EBVs for policy targets and demonstrate how open, interoperable and machine-readable trait data enable the building of EBV data products. We outline collection methods, meta(data) standardization, reproducible workflows, semantic tools and licence requirements for producing species traits EBVs. An operationalization is critical for assessing progress towards biodiversity conservation and sustainable development goals and has wide implications for data-intensive science in ecology, biogeography, conservation and Earth observation.
Pawar S, Garcia-Carreras B, Sal S, et al., 2018, Role of carbon allocation efficiency in the temperature dependence of autotroph growth rate, Proceedings of the National Academy of Sciences, Vol: 115, Pages: E7361-E7368, ISSN: 0027-8424
To predict how plant growth rate will respond to temperature requires understanding how temperature drives the underlying metabolic rates. Although past studies have considered the temperature dependences of photosynthesis and respiration rates underlying growth, they have largely overlooked the temperature dependence of carbon allocation efficiency. By combining a mathematical model that links exponential growth rate of a population of photosynthetic cells to photosynthesis, respiration, and carbon allocation; to an experiment on a freshwater alga; and to a database covering a wide range of taxa, we show that allocation efficiency is crucial for predicting how growth rates will respond to temperature change across aquatic and terrestrial autotrophs, at both short and long (evolutionary) timescales.
Bestion E, Garcia-Carreras B, Schaum C-E, et al., 2018, Metabolic traits predict the effects of warming on phytoplankton competition, Ecology Letters, Vol: 21, Pages: 655-664, ISSN: 1461-023X
Understanding how changes in temperature affect interspecific competition is critical for predicting changes in ecological communities with global warming. Here, we develop a theoretical model that links interspecific differences in the temperature dependence of resource acquisition and growth to the outcome of pairwise competition in phytoplankton. We parameterised our model with these metabolic traits derived from six species of freshwater phytoplankton and tested its ability to predict the outcome of competition in all pairwise combinations of the species in a factorial experiment, manipulating temperature and nutrient availability. The model correctly predicted the outcome of competition in 72% of the pairwise experiments, with competitive advantage determined by difference in thermal sensitivity of growth rates of the two species. These results demonstrate that metabolic traits play a key role in determining how changes in temperature influence interspecific competition and lay the foundation for mechanistically predicting the effects of warming in complex, multi‐species communities.
Kontopoulos DG, García-Carreras B, Sal S, et al., 2018, Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits, PeerJ, Vol: 6, ISSN: 2167-8359
There is currently unprecedented interest in quantifying variation in thermal physiologyamong organisms, especially in order to understand and predict the biological impactsof climate change. A key parameter in this quantification of thermal physiologyis the performance or value of a rate, across individuals or species, at a commontemperature (temperature normalisation). An increasingly popular model for fittingthermal performance curves to data—the Sharpe-Schoolfield equation—can yieldstrongly inflated estimates of temperature-normalised rate values. These deviationsoccur whenever a key thermodynamic assumption of the model is violated, i.e., whenthe enzyme governing the performance of the rate is not fully functional at the chosenreference temperature. Using data on 1,758 thermal performance curves across awide range of species, we identify the conditions that exacerbate this inflation. Wethen demonstrate that these biases can compromise tests to detect metabolic coldadaptation, which requires comparison of fitness or rate performance of differentspecies or genotypes at some fixed low temperature. Finally, we suggest alternativemethods for obtaining unbiased estimates of temperature-normalised rate values formeta-analyses of thermal performance across species in climate change impact studies.
Rizzuto M, Carbone C, Pawar S, 2017, Foraging constraints reverse the scaling of activity time in carnivores, Nature Ecology and Evolution, Vol: 2, Pages: 247-253, ISSN: 2397-334X
The proportion of time an animal spends actively foraging in a day determines its long-term fitness. Here, we derive a general mathematical model for the scaling of this activity time with body size in consumers. We show that this scaling can change from positive (increasing with size) to negative (decreasing with size) if the detectability and availability of preferred prey sizes is a limiting factor. These predictions are supported by a global dataset on 73 terrestrial carnivore species from 8 families spanning >3 orders of magnitude in size. Carnivores weighing ∼5 kg experience high foraging costs because their diets include significant proportions of relatively small (invertebrate) prey. As a result, they show an increase in activity time with size. This shifts to a negative scaling in larger carnivores as they shift to foraging on less costly vertebrate prey. Our model can be generalized to other classes of terrestrial and aquatic consumers and offers a general framework for mechanistically linking body size to population fitness and vulnerability in consumers.
Schaum C-E, Barton S, Bestion E, et al., 2017, Adaptation of phytoplankton to a decade of experimental warming linked to increased photosynthesis, Nature Ecology and Evolution, Vol: 1, Pages: 0094-0094, ISSN: 2397-334X
Phytoplankton photosynthesis is a critical flux in the carbon cycle, accounting for approximately 40% of the carbon dioxide fixed globally on an annual basis and fuelling the productivity of aquatic food webs. However, rapid evolutionary responses of phytoplankton to warming remain largely unexplored, particularly outside the laboratory, where multiple selection pressures can modify adaptation to environmental change. Here, we use a decade-long experiment in outdoor mesocosms to investigate mechanisms of adaptation to warming (+4 °C above ambient temperature) in the green alga Chlamydomonas reinhardtii, in naturally assembled communities. Isolates from warmed mesocosms had higher optimal growth temperatures than their counterparts from ambient treatments. Consequently, warm-adapted isolates were stronger competitors at elevated temperature and experienced a decline in competitive fitness in ambient conditions, indicating adaptation to local thermal regimes. Higher competitive fitness in the warmed isolates was linked to greater photosynthetic capacity and reduced susceptibility to photoinhibition. These findings suggest that adaptive responses to warming in phytoplankton could help to mitigate projected declines in aquatic net primary production by increasing rates of cellular net photosynthesis.
Woodward G, Bonada N, Brown LE, et al., 2016, The effects of climatic fluctuations and extreme events on running water ecosystems, Philisophical Transactions of the Royal Society B, Vol: 371, ISSN: 0962-8436
Most research on the effects of environmental change in freshwaters hasfocused on incremental changes in average conditions, rather than fluctuationsor extreme events such as heatwaves, cold snaps, droughts, floodsor wildfires, which may have even more profound consequences. Suchevents are commonly predicted to increase in frequency, intensity and durationwith global climate change, with many systems being exposed toconditions with no recent historical precedent. We propose a mechanisticframework for predicting potential impacts of environmental fluctuationson running-water ecosystems by scaling up effects of fluctuations from individualsto entire ecosystems. This framework requires integration of four keycomponents: effects of the environment on individual metabolism, metabolicand biomechanical constraints on fluctuating species interactions,assembly dynamics of local food webs, and mapping the dynamics of themeta-community onto ecosystem function. We illustrate the framework bydeveloping a mathematical model of environmental fluctuations on dynamicallyassembling food webs. We highlight (currently limited) empiricalevidence for emerging insights and theoretical predictions. For example,widely supported predictions about the effects of environmental fluctuationsare: high vulnerability of species with high per capita metabolic demandssuch as large-bodied ones at the top of food webs; simplification of foodweb network structure and impaired energetic transfer efficiency; andreduced resilience and top-down relative to bottom-up regulation of foodweb and ecosystem processes. We conclude by identifying key questionsand challenges that need to be addressed to develop more accurate and predictivebio-assessments of the effects of fluctuations, and implications offluctuations for management practices in an increasingly uncertain world.
Pawar S, Dell AI, Savage VM, et al., 2016, Real versus Artificial Variation in the Thermal Sensitivity of Biological Traits, American Naturalist, Vol: 187, Pages: E41-E52, ISSN: 1537-5323
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.
Pawar S, 2015, The Role of Body Size Variation in Community Assembly, Advances in Ecological Research, Vol: 52, Pages: 201-248
Body size determines key behavioral and life history traits across species, as well as interactions between individuals within and between species. Therefore, variation in sizes of immigrants, by exerting variation in trophic interaction strengths, may drive the trajectory and outcomes of community assembly. Here, I study the effects of size variation in the immigration pool on assembly dynamics and equilibrium distributions of sizes and consumer–resource size-ratios using a general mathematical model. I find that because small sizes both, improve the ability to invade and destabilize the community, invasibility and stability pull body size distributions in opposite directions, favoring an increase in both size and size-ratios during assembly, and ultimately yielding a right-skewed size and a symmetric size-ratio distribution. In many scenarios, the result at equilibrium is a systematic increase in body sizes and size-ratios with trophic level. Thus these patterns in size structure are ‘signatures’ of dynamically constrained, non-neutral community assembly. I also show that for empirically feasible distributions of body sizes in the immigration pool, immigration bias in body sizes cannot counteract dynamical constraints during assembly and thus signatures emerge consistently. I test the theoretical predictions using data from nine terrestrial and aquatic communities and find strong evidence that natural communities do indeed exhibit such signatures of dynamically constrained assembly. Overall, the results provide new measures to detect general, non-neutral patterns in community assembly dynamics, and show that in general, body size is dominant trait that strongly influences assembly and recovery of natural communities and ecosystems.
Gibert JP, Dell AI, DeLong JP, et al., 2015, Scaling-up Trait Variation from Individuals to Ecosystems, Publisher: Elsevier, Pages: 1-17, ISBN: 9780124200029
Ecology has traditionally focused on species diversity as a way of characterizing the health of an ecosystem. In recent years, however, the focus has increasingly shifted towards trait diversity both within and across species. As we increasingly recognize that ecological and evolutionary timescales may not be all that different, understanding the ecological effects of trait variation becomes paramount. Trait variation is thus the keystone to our understanding of how evolutionary processes may affect ecological dynamics as they unfold, and how these may in turn alter evolutionary trajectories. However, a multi-level understanding of how trait variation scales up from individuals to whole communities or ecosystems is still a work in progress. The chapters in this volume explore how functional trait diversity affects ecological processes across levels of biological organization. This chapter aims at binding the messages of the different contributions and considers how they advance our understanding of how trait variation can be scaled up to understand the interplay between ecological and evolutionary dynamics from individuals to ecosystems.
Johnson LR, Ben-Horin T, Lafferty KD, et al., 2015, Understanding uncertainty in temperature effects on vector-borne disease: a Bayesian approach, ECOLOGY, Vol: 96, Pages: 203-213, ISSN: 0012-9658
Pawar S, Dell AI, Savage VM, 2015, From metabolic constraints on individuals to the eco-evolutionary dynamics of ecosystems, Aquat. Funct. Biodivers. An Eco-Evolutionary Approach, Editors: Belgrano, Woodward, Jacob, Publisher: Elsevier, Pages: In Press-In Press
Pawar S, 2015, The role of body size variation in community assembly, Adv. Ecol. Res., Vol: 52
Tang S, Pawar S, Allesina S, 2014, Correlation between interaction strengths drives stability in large ecological networks, Ecology Letters, Vol: 17, Pages: 1094-1100, ISSN: 1461-023X
Food webs have markedly non‐random network structure. Ecologists maintain that this non‐random structure is key for stability, since large random ecological networks would invariably be unstable and thus should not be observed empirically. Here we show that a simple yet overlooked feature of natural food webs, the correlation between the effects of consumers on resources and those of resources on consumers, substantially accounts for their stability. Remarkably, random food webs built by preserving just the distribution and correlation of interaction strengths have stability properties similar to those of the corresponding empirical systems. Surprisingly, we find that the effect of topological network structure on stability, which has been the focus of countless studies, is small compared to that of correlation. Hence, any study of the effects of network structure on stability must first take into account the distribution and correlation of interaction strengths.
Pawar S, 2014, Why are plant-pollinator networks nested?, SCIENCE, Vol: 345, Pages: 383-383, ISSN: 0036-8075
Mordecai EA, Paaijmans KP, Johnson LR, et al., 2013, Optimal temperature for malaria transmission is dramatically lower than previously predicted, Ecology Letters, Vol: 16, Pages: 22-30
The ecology of mosquito vectors and malaria parasites affect the incidence, seasonal transmission and geographical range of malaria. Most malaria models to date assume constant or linear responses of mosquito and parasite life-history traits to temperature, predicting optimal transmission at 31 °C. These models are at odds with field observations of transmission dating back nearly a century. We build a model with more realistic ecological assumptions about the thermal physiology of insects. Our model, which includes empirically derived nonlinear thermal responses, predicts optimal malaria transmission at 25 °C (6 °C lower than previous models). Moreover, the model predicts that transmission decreases dramatically at temperatures > 28 °C, altering predictions about how climate change will affect malaria. A large data set on malaria transmission risk in Africa validates both the 25 °C optimum and the decline above 28 °C. Using these more accurate nonlinear thermal-response models will aid in understanding the effects of current and future temperature regimes on disease transmission.
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