40 results found
Ho H-C, Tylianakis JM, Zheng JX, et al., 2019, Predation risk influences food-web structure by constraining species diet choice., Ecology Letters, 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.
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.
Zheng JX, Pawar S, Goodman DFM, 2019, Further towards unambiguous edge bundling: Investigating power-confluentdrawings for network visualization.
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.
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 curve of growth rate of phytoplankton—a globally important functional group—, controlling for potential environmental effects. We find that thermody-namic constraints have a minor influence on the shape of the curve. In particular, we detect a very weak increase of the maximum curve height 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 detect phylogenetic signal in this as well as all other curve parameters. 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.
Zheng JX, Pawar S, Goodman DFM, 2018, Graph drawing by stochastic gradient descent, IEEE Transactions on Visualization and Computer Graphics, ISSN: 1077-2626
A popular method of force-directed graph drawing is multidimensional scalingusing graph-theoretic distances as input. We present an algorithm to minimizeits 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 SGDcan reach lower stress levels faster and more consistently than majorization,without needing help from a good initialization. We then show how the uniqueproperties of SGD make it easier to produce constrained layouts than previousapproaches. We also show how SGD can be directly applied within the sparsestress approximation of Ortmann et al. , making the algorithm scalable up tolarge graphs.
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, 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, 2015, The role of body size variation in community assembly, Adv. Ecol. Res., Vol: 52
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
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
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.
Dell AI, Pawar S, Savage VM, 2013, Temperature dependence of trophic interactions are driven by asymmetry of species responses and foraging strategy, Journal of Animal Ecology, Vol: 82, ISSN: 1365-2656
Environmental temperature has systematic effects on rates of species interactions, primarily through its influence on organismal physiology. 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). 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. 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. 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
Pawar S, Dell AI, Savage VM, 2013, Pawar et al. reply, Nature, Vol: 493, Pages: E2-E3, ISSN: 0028-0836
Dell AI, Pawar S, Savage VM, 2013, The thermal dependence of biological traits, Ecology, Vol: 94, Pages: 1205-1205
Johnson LR, Lafferty K, McNally A, et al., 2013, Mapping the Distribution of Malaria: current methods and considerations, Infectious Disease Modelling, Hoboken, N.J., Publisher: Wiley-Interscience, Pages: In Press-In Press
Pawar S, Dell AI, Savage VM, 2012, Dimensionality of consumer search space drives trophic interaction strengths, Nature, Vol: 486, Pages: 485-489, ISSN: 1476-4687
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.
Dell AI, Pawar S, Savage VM, 2011, Systematic variation in the temperature dependence of physiological and ecological traits, Proceedings of the National Academy of Sciences of the United States of America, Vol: 108, Pages: 10591-10596, ISSN: 1091-6490
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.
Pawar S, 2009, Community assembly, stability and signatures of dynamical constraints on food web structure, Journal of Theoretical Biology, Vol: 259, Pages: 601-612
To understand the dynamics of natural species communities, a major challenge is to quantify the relationship between their assembly, stability, and underlying food web structure. To this end, two complementary aspects of food web structure can be related to community stability: sign structure, which refers to the distributions of trophic links irrespective of interaction strengths, and interaction strength structure, which refers to the distributions of interaction strengths with or without consideration of sign structure. In this paper, using data from a set of relatively well documented community food webs, I show that natural communities generally exhibit a sign structure that renders their stability sensitive to interaction strengths. Using a Lotka-Volterra type population dynamical model, I then show that in such communities, individual consumer species with high values of a measure of their total biomass acquisition rate, which I term "weighted generality", tend to undermine community stability. Thus consumer species’ trophic modules (a species and all its resource links) should be "selected" through repeated immigrations and extinctions during assembly into configurations that increase the probability of stable coexistence within the constraints of the community’s trophic sign structure. The presence of such constraints can be detected by the incidence and strength of certain non-random structural characteristics. These structural signatures of dynamical constraints are readily measurable, and can be used to gauge the importance of interaction-driven dynamical constraints on communities during and after assembly in natural communities.
Pawar SS, Birand AC, Ahmed MF, et al., 2007, Conservation biogeography in North‐east India: hierarchical analysis of cross‐taxon distributional congruence, Diversity and Distributions, Vol: 13, Pages: 53-65
Distributional similarity (congruence) between phylogenetically independent taxonomic groups has important biogeographical as well as conservation implications. When multiple groups show congruence, one or two of them can be used as surrogates of diversity in others, thus simplifying some of the challenges of area prioritization for conservation action. Here we test for congruence in complementarity between amphibians, reptiles and birds across seven tropical rainforest sites in the Eastern Himalaya and Indo-Burma global biodiversity hotspots. The results show that while frogs and lizards are strongly congruent with each other, birds as a whole do not show congruence with either of them. However, certain bird subgroups delineated on the basis of broad ecological niche and life history attributes are significantly congruent with both frogs and lizards. Multiple Mantel regression between environmental variable and species distribution dissimilarity matrices indicate that along with differential response to between-site ecological differences, inherent life-history characteristics shared by certain groups contributes to observed patterns of congruence. Our analyses indicate that examining biologically distinct subsets of larger groups can improve the resolution of congruence analyses. This approach can refine area-prioritization initiatives by revealing fine-scale discordances between otherwise concordant groups, and vice versa. Given that monetary resources do not always allow inclusion of multiple groups in biodiversity inventorying efforts, performing such analyses also makes economic sense because it can provide better resolution even with single-group data. In the context of conservation in Northeast India, the results highlight the biogeographical complexity of the region, and also point at future priorities for biodiversity inventorying and conservation prioritization, both in terms of areas as well as taxonomic groups.
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