Supporting study registration to reduce research waste.

An estimated 82-89% of ecological research and 85% of medical research has limited or no value to the end user because of various inefficiencies. We argue that registration and registered reports can enhance the quality and impact of ecological research. Drawing on evidence from other fields, chiefly medicine, we support our claim that registration can reduce research waste. However, increasing registration rates, quality and impact will be very slow without coordinated effort of funders, publishers and research institutions. We therefore call on them to facilitate the adoption of registration by providing adequate support. We outline several aspects to be considered when designing a registration system that would best serve the field of ecology. To further inform the development of such a system, we call for more research to identify the causes of low registration rates in ecology. We suggest short- and long-term actions to bolster registration and reduce research waste.

Investigating the Ability of Growth Models to Predict In Situ Vibrio spp. Abundances.

Vibrio spp. have an important role in biogeochemical cycles; some species are disease agents for aquatic animals and/or humans. Predicting population dynamics of Vibrio spp. in natural environments is crucial to predicting how the future conditions will affect the dynamics of these bacteria. The majority of existing Vibrio spp. population growth models were developed in controlled environments, and their applicability to natural environments is unknown. We collected all available functional models from the literature, and distilled them into 28 variants using unified nomenclature. Next, we assessed their ability to predict Vibrio spp. abundance using two new and five already published longitudinal datasets on Vibrio abundance in four different habitat types. Results demonstrate that, while the models were able to predict Vibrio spp. abundance to an extent, the predictions were not reliable. Models often underperformed, especially in environments under significant anthropogenic influence such as aquaculture and urban coastal habitats. We discuss implications and limitations of our analysis, and suggest research priorities; in particular, we advocate for measuring and modeling organic matter.

Quantifying research waste in ecology.

Research inefficiencies can generate huge waste: evidence from biomedical research has shown that most research is avoidably wasted and steps have been taken to tackle this costly problem. Although other scientific fields could also benefit from identifying and quantifying waste and acting to reduce it, no other estimates of research waste are available. Given that ecological issues interweave most of the United Nations Sustainable Development Goals, we argue that tackling research waste in ecology should be prioritized. Our study leads the way. We estimate components of waste in ecological research based on a literature review and a meta-analysis. Shockingly, our results suggest only 11-18% of conducted ecological research reaches its full informative value. All actors within the research system-including academic institutions, policymakers, funders and publishers-have a duty towards science, the environment, study organisms and the public, to urgently act and reduce this considerable yet preventable loss. We discuss potential ways forward and call for two major actions: (1) further research into waste in ecology (and beyond); (2) focused development and implementation of solutions to reduce unused potential of ecological research.

Physiological performance of native and invasive crayfish species in a changing environment: insights from Dynamic Energy Budget models.

Crayfish are keystone species important for maintaining healthy freshwater ecosystems. Crayfish species native to Europe, such as Astacus astacus and Austropotamobius torrentium, are facing decline and are increasingly endangered by changing climate and invasions of non-native crayfish, such as Pacifastacus leniusculus and Procambarus virginalis. The success of these invasions largely depends on differences in ontogeny between the native species and the invaders and how changes in the environment will affect the ontogeny. Dynamic Energy Budget (DEB) models can be used to investigate such differences because the models capture dependence of metabolism, and therefore ontogeny, on environmental conditions. We develop DEB models for all four species and investigate key elements of ontogeny and metabolism affecting interspecific competition. We then use the DEB models to predict individual growth and reproduction in current and new conditions that are expected to arise from climate change. Although observations suggest that P. leniusculus poses the major threat to native species, our analysis identifies P. virginalis, in spite of its smaller size, as the superior competitor by a large margin-at least when considering metabolism and ontogeny. Our simulations show that climate change is set to increase the competitive edge of P. virginalis even further. Given the prospects of P. virginalis dominance, especially when considering that it is able to withstand and spread at least some crayfish plague strains that severely affect native species, additional research into P. virginalis is necessary.

Quantifying impacts of plastic debris on marine wildlife identifies ecological breakpoints.

Quantifying sublethal effects of plastics ingestion on marine wildlife is difficult, but key to understanding the ontogeny and population dynamics of affected species. We developed a method that overcomes the difficulties by modelling individual ontogeny under reduced energy intake and expenditure caused by debris ingestion. The predicted ontogeny is combined with a population dynamics model to identify ecological breakpoints: cessation of reproduction or negative population growth. Exemplifying this approach on loggerhead turtles, we find that between 3% and 25% of plastics in digestive contents causes a 2.5-20% reduction in perceived food abundance and total available energy, resulting in a 10-15% lower condition index and 10% to 88% lower total seasonal reproductive output compared to unaffected turtles. The reported plastics ingestion is insufficient to impede sexual maturation, but population declines are possible. The method is readily applicable to other species impacted by debris ingestion.

Effects of environmental change and early-life stochasticity on Pacific bluefin tuna population growth.

Species conservation and fisheries management require approaches that relate environmental conditions to population-level dynamics, especially because environmental conditions shift due to climate change. We combined an individual-level physiological model and a conceptually simple matrix population model to develop a novel tool that relates environmental change to population dynamics, and used this tool to analyze effects of environmental changes and early-life stochasticity on Pacific bluefin tuna (PBT) population growth. We found that (i) currently, PBT population experiences a positive growth rate, (ii) somewhat surprisingly, stochasticity in early life survival increases this growth rate, (iii) sexual maturation age strongly depends on food and temperature, (iv) current fishing pressure, though high, is tolerable as long as the environment is such that PBT mature in less than 9 years of age (maturation age of up to 10 is possible in some environments), (v) PBT population growth rate is much more susceptible to changes in juvenile survival than changes in total reproductive output or adult survival. These results suggest that, to be effective, fishing regulations need to (i) focus on smaller tuna (i.e., juveniles and young adults), and (ii) mitigate adverse effects of climate change by taking into the account how future environments may affect the population growth.

Predicting perceived level of disturbance of visitors due to crowding in protected areas.

Managing the disturbance of visitors due to crowding is an important management task in protected areas with high use levels. To achieve this, managers need to know how the use level affects the perceived disturbance due to crowding. Here we present a method to predict the level of disturbance as a function of use level measured by number of visitors. In contrast to the visual approach where subjects are asked to evaluate acceptability of use levels from manipulated images of scenery, our approach uses data gathered from actual experiences: actual (measured) use levels and concurrent on-site data on levels of disturbance experienced by visitors. Using the example of Nature Park Telascica, we show how these data can be acquired with limited resources (a smart-phone and short, time-stamped questionnaires), and demonstrate the subsequent analysis and model fitting. The resulting model estimates the probability that a visitor experiencing a given use level will report certain level of disturbance. We suggest a way of using the probability density functions to define an inherent limit of acceptable disturbance (LAD) due to crowding; the LAD can also be set to a desired value by management. Regardless of the definition, LAD can be used to determine the maximum acceptable use level as dictated by crowding considerations. The method gives predictions consistent with previous literature and can be used even when data are collected at low use levels.

Host-Symbiont Interaction Model Explains Non-monotonic Response of Soybean Growth and Seed Production to Nano-CeO2 Exposure.

Recent nanotoxicity studies have demonstrated non-monotonic dose-response mechanisms for planted soybean that have a symbiotic relationship with bacteroids in their root nodules: reduction of growth and seed production was greater for low, as compared to high, exposures. To investigate mechanistic underpinnings of the observed patterns, we formulated an energy budget model coupled to a toxicokinetic module describing bioaccumulation, and two toxicodynamic modules describing toxic effects on host plant and symbionts. By fitting data on plants exposed to engineered CeO2 nanoparticles to the newly formulated model, we show that the non-monotonic patterns can be explained as the interaction of two, individually monotonic, dose-response processes: one for the plant and the other for the symbiont. We further validate the newly formulated model by showing that, without the need for additional parameters, the model successfully predicts changes in dinitrogen fixation potential as a function of exposure (dinitrogen fixation potential data not used in model fitting). The symbiont buffers overall toxicity only when, in the absence of exposure to a toxicant, it has a parasitic interaction with the host plant. If the interaction is mutualistic or commensal, there is no buffering and only monotonic toxic responses are possible. Because the model is based on general biological principles, we expect it to be applicable to other similar symbiotic systems, especially other nodule-forming legumes.

Inferring physiological energetics of loggerhead turtle (Caretta caretta) from existing data using a general metabolic theory.

Loggerhead turtle is an endangered sea turtle species with a migratory lifestyle and worldwide distribution, experiencing markedly different habitats throughout its lifetime. Environmental conditions, especially food availability and temperature, constrain the acquisition and the use of available energy, thus affecting physiological processes such as growth, maturation, and reproduction. These physiological processes at the population level determine survival, fecundity, and ultimately the population growth rate-a key indicator of the success of conservation efforts. As a first step towards the comprehensive understanding of how environment shapes the physiology and the life cycle of a loggerhead turtle, we constructed a full life cycle model based on the principles of energy acquisition and utilization embedded in the Dynamic Energy Budget (DEB) theory. We adapted the standard DEB model using data from published and unpublished sources to obtain parameter estimates and model predictions that could be compared with data. The outcome was a successful mathematical description of ontogeny and life history traits of the loggerhead turtle. Some deviations between the model and the data existed (such as an earlier age at sexual maturity and faster growth of the post-hatchlings), yet probable causes for these deviations were found informative and discussed in great detail. Physiological traits such as the capacity to withstand starvation, trade-offs between reproduction and growth, and changes in the energy budget throughout the ontogeny were inferred from the model. The results offer new insights into physiology and ecology of loggerhead turtle with the potential to lead to novel approaches in conservation of this endangered species.

Elevated Rate of Genome Rearrangements in Radiation-Resistant Bacteria.

A number of bacterial, archaeal, and eukaryotic species are known for their resistance to ionizing radiation. One of the challenges these species face is a potent environmental source of DNA double-strand breaks, potential drivers of genome structure evolution. Efficient and accurate DNA double-strand break repair systems have been demonstrated in several unrelated radiation-resistant species and are putative adaptations to the DNA damaging environment. Such adaptations are expected to compensate for the genome-destabilizing effect of environmental DNA damage and may be expected to result in a more conserved gene order in radiation-resistant species. However, here we show that rates of genome rearrangements, measured as loss of gene order conservation with time, are higher in radiation-resistant species in multiple, phylogenetically independent groups of bacteria. Comparison of indicators of selection for genome organization between radiation-resistant and phylogenetically matched, nonresistant species argues against tolerance to disruption of genome structure as a strategy for radiation resistance. Interestingly, an important mechanism affecting genome rearrangements in prokaryotes, the symmetrical inversions around the origin of DNA replication, shapes genome structure of both radiation-resistant and nonresistant species. In conclusion, the opposing effects of environmental DNA damage and DNA repair result in elevated rates of genome rearrangements in radiation-resistant bacteria.

The universality and the future prospects of physiological energetics: Reply to comments on "Physics of metabolic organization".

In response to the comments on review "Physics of metabolic organization", we discuss the universality and the future prospects of physiological energetics. The topics range from the role of entropy in modeling living organisms to the apparent ubiquity of the von Bertalanffy curve, and the potential applications of the theory in yet unexplored domains. Tradeoffs in outreach to non-specialists are also briefly considered.

Physics of metabolic organization.

We review the most comprehensive metabolic theory of life existing to date. A special focus is given to the thermodynamic roots of this theory and to implications that the laws of physics-such as the conservation of mass and energy-have on all life. Both the theoretical foundations and biological applications are covered. Hitherto, the foundations were more accessible to physicists or mathematicians, and the applications to biologists, causing a dichotomy in what always should have been a single body of work. To bridge the gap between the two aspects of the same theory, we (i) adhere to the theoretical formalism, (ii) try to minimize the amount of information that a reader needs to process, but also (iii) invoke examples from biology to motivate the introduction of new concepts and to justify the assumptions made, and (iv) show how the careful formalism of the general theory enables modular, self-consistent extensions that capture important features of the species and the problem in question. Perhaps the most difficult among the introduced concepts, the utilization (or mobilization) energy flow, is given particular attention in the form of an original and considerably simplified derivation. Specific examples illustrate a range of possible applications-from energy budgets of individual organisms, to population dynamics, to ecotoxicology.

Nutrient quotas and carbon content variability of Prorocentrum minimum (Pavillard) Schiller, 1933.

Frequency, severity, and geographic range of harmful blooms caused by a dinoflagellate Prorocentrum minimum have been increasing significantly over the past few decades. The ability to adapt nutrient quotas and carbon content to a wide range of environmental conditions is one of the key factors for the proliferation of P. minimum. Understanding the limits of stoichiometric variability in terms of nutrient quotas and carbon content would help explain the observed trends and assist in P. minimum growth model creation. This manuscript aggregates information from 15 studies to investigate variability in nutrient quotas and carbon content for a broad range of P. minimum isolates and clonal lines. Nitrogen quota, phosphorus quota, and carbon content in the studies varied between 11-107.5pgNcell-1, 1.45-17.58pgPcell-1, and 70-656.36pgCcell-1, respectively. Regression analysis was used to estimate average nitrogen and phosphorus quotas as functions of carbon, and to show that carbon content variability explains 55% of nitrogen and 23% of phosphorus quota variability. Confidence intervals for data (CID) found during the analysis were used to define maximal and minimal nutrient quotas as functions of carbon content. The ratios of the upper and lower CID ranges can, therefore, be used to estimate nutrient storage capacity as a function of carbon content. The new results and comparison with other species show that, at least for P. minimum, carbon-based quotas are more suitable for modelling than cell-based quotas. Finally, results indicate that environmental nutrient availability affects quotas more than light does: while quota variability due to light remains within 80% CID, nutrient variability covers the 95% CID.

Feedbacks and tipping points in organismal response to oxidative stress.

Biological feedbacks play a crucial role in determining effects of toxicants, radiation, and other environmental stressors on organisms. Focusing on reactive oxygen species (ROS) that are increasingly recognized as a crucial mediator of many stressor effects, we investigate how feedback strength affects the ability of organisms to control negative effects of exposure. We do this by developing a general theoretical framework for describing effects of a wide range of stressors and species. The framework accounts for positive and negative feedbacks representing cellular processes: (i) production of ROS due to metabolism and the stressor, (ii) ROS reactions with cellular compounds that cause damage, and (iii) cellular control of both ROS and damage. We suggest functional forms that capture generic properties of cellular control mechanisms constituting the feedbacks, assess stability of equilibrium states in the resulting models, and investigate tipping points at which cellular control breaks down causing unregulated increase of ROS and damage. Depending on the chosen functional forms, the models can have zero, one, or two positive steady states; except in one singular case, the steady state with lowest values of ROS and damage is locally stable. We found two types of tipping points: those induced by changes in the parameters (including the stressor intensity), and those induced by the history of exposure, i.e. ROS and damage levels. The relatively simple models effectively describe several patterns of cellular responses to stress, such as the covariation of ROS and damage, the break-down of cellular control leading to explosion of ROS and/or damage, increase in damage even when ROS is (near)-constant, and the effects of exposure history on the ability of the cell to handle additional stress. The models quantify dynamics of cellular control, and could therefore be used to estimate the metabolic costs of stress and help integrate them into models that use energetic considerations to model organism's response to the environment. Although developed with unicellular organisms in mind, our models can be applied to all multicellular organisms that utilize similar feedbacks when dealing with stress.

Size Scaling in Western North Atlantic Loggerhead Turtles Permits Extrapolation between Regions, but Not Life Stages.

INTRODUCTION: Sea turtles face threats globally and are protected by national and international laws. Allometry and scaling models greatly aid sea turtle conservation and research, and help to better understand the biology of sea turtles. Scaling, however, may differ between regions and/or life stages. We analyze differences between (i) two different regional subsets and (ii) three different life stage subsets of the western North Atlantic loggerhead turtles by comparing the relative growth of body width and depth in relation to body length, and discuss the implications. RESULTS AND DISCUSSION: Results suggest that the differences between scaling relationships of different regional subsets are negligible, and models fitted on data from one region of the western North Atlantic can safely be used on data for the same life stage from another North Atlantic region. On the other hand, using models fitted on data for one life stage to describe other life stages is not recommended if accuracy is of paramount importance. In particular, young loggerhead turtles that have not recruited to neritic habitats should be studied and modeled separately whenever practical, while neritic juveniles and adults can be modeled together as one group. Even though morphometric scaling varies among life stages, a common model for all life stages can be used as a general description of scaling, and assuming isometric growth as a simplification is justified. In addition to linear models traditionally used for scaling on log-log axes, we test the performance of a saturating (curvilinear) model. The saturating model is statistically preferred in some cases, but the accuracy gained by the saturating model is marginal.

Environmental feedbacks and engineered nanoparticles: mitigation of silver nanoparticle toxicity to Chlamydomonas reinhardtii by algal-produced organic compounds.

The vast majority of nanotoxicity studies measures the effect of exposure to a toxicant on an organism and ignores the potentially important effects of the organism on the toxicant. We investigated the effect of citrate-coated silver nanoparticles (AgNPs) on populations of the freshwater alga Chlamydomonas reinhardtii at different phases of batch culture growth and show that the AgNPs are most toxic to cultures in the early phases of growth. We offer strong evidence that reduced toxicity occurs because extracellular dissolved organic carbon (DOC) compounds produced by the algal cells themselves mitigate the toxicity of AgNPs. We analyzed this feedback with a dynamic model incorporating algal growth, nanoparticle dissolution, bioaccumulation of silver, DOC production and DOC-mediated inactivation of nanoparticles and ionic silver. Our findings demonstrate how the feedback between aquatic organisms and their environment may impact the toxicity and ecological effects of engineered nanoparticles.

Dynamic energy budget approach to modeling mechanisms of CdSe quantum dot toxicity.

A mechanistic model of bacterial growth based on dynamic energy budget (DEB) theory is utilized to investigate mechanisms of toxicity of CdSe quantum dots (QDs). The model of QD toxicity is developed by extending a previously published DEB model of cadmium ion toxicity to include a separate model of QD toxic action. The extension allows for testing whether toxicity from QD exposure can be explained fully by dissolved cadmium exposure only, or if the separate effects of QDs need to be taken into account as well. Two major classes of QD toxicity mechanisms are considered: acclimation expressed through initial retardation of growth, and three separate metabolic effects that can be a result of QDs either reversibly or irreversibly associating with the cell. The model is consistent with the data, and is able to distinguish toxic effects due to QD nano-particles from the effects due to cadmium ions. Results suggest that, in contrast to ionic exposure where required acclimation remains constant as exposure increases, increase of the energy required for acclimation with exposure is the primary toxic effect of QDs. Reactive oxygen species measurements help conclude that increase in energetic cost of maintenance processes such as cellular repair and maintenance of cross-membrane gradients is the most important of the three metabolic effects of QD toxicity.

Integrating dynamic energy budget (DEB) theory with traditional bioenergetic models.

Dynamic energy budget (DEB) theory offers a systematic, though abstract, way to describe how an organism acquires and uses energy and essential elements for physiological processes, in addition to how physiological performance is influenced by environmental variables such as food density and temperature. A 'standard' DEB model describes the performance (growth, development, reproduction, respiration, etc.) of all life stages of an animal (embryo to adult), and predicts both intraspecific and interspecific variation in physiological rates. This approach contrasts with a long tradition of more phenomenological and parameter-rich bioenergetic models that are used to make predictions from species-specific rate measurements. These less abstract models are widely used in fisheries studies; they are more readily interpretable than DEB models, but lack the generality of DEB models. We review the interconnections between the two approaches and present formulae relating the state variables and fluxes in the standard DEB model to measured bioenergetic rate processes. We illustrate this synthesis for two large fishes: Pacific bluefin tuna (Thunnus orientalis) and Pacific salmon (Oncorhynchus spp.). For each, we have a parameter-sparse, full-life-cycle DEB model that requires adding only a few species-specific features to the standard model. Both models allow powerful integration of knowledge derived from data restricted to certain life stages, processes and environments.

Modeling physiological processes that relate toxicant exposure and bacterial population dynamics.

Quantifying effects of toxicant exposure on metabolic processes is crucial to predicting microbial growth patterns in different environments. Mechanistic models, such as those based on Dynamic Energy Budget (DEB) theory, can link physiological processes to microbial growth.Here we expand the DEB framework to include explicit consideration of the role of reactive oxygen species (ROS). Extensions considered are: (i) additional terms in the equation for the "hazard rate" that quantifies mortality risk; (ii) a variable representing environmental degradation; (iii) a mechanistic description of toxic effects linked to increase in ROS production and aging acceleration, and to non-competitive inhibition of transport channels; (iv) a new representation of the "lag time" based on energy required for acclimation. We estimate model parameters using calibrated Pseudomonas aeruginosa optical density growth data for seven levels of cadmium exposure. The model reproduces growth patterns for all treatments with a single common parameter set, and bacterial growth for treatments of up to 150 mg(Cd)/L can be predicted reasonably well using parameters estimated from cadmium treatments of 20 mg(Cd)/L and lower. Our approach is an important step towards connecting levels of biological organization in ecotoxicology. The presented model reveals possible connections between processes that are not obvious from purely empirical considerations, enables validation and hypothesis testing by creating testable predictions, and identifies research required to further develop the theory.

A full lifecycle bioenergetic model for bluefin tuna.

We formulated a full lifecycle bioenergetic model for bluefin tuna relying on the principles of Dynamic Energy Budget theory. Traditional bioenergetic models in fish research deduce energy input and utilization from observed growth and reproduction. In contrast, our model predicts growth and reproduction from food availability and temperature in the environment. We calibrated the model to emulate physiological characteristics of Pacific bluefin tuna (Thunnus orientalis, hereafter PBT), a species which has received considerable scientific attention due to its high economic value. Computer simulations suggest that (i) the main cause of different growth rates between cultivated and wild PBT is the difference in average body temperature of approximately 6.5°C, (ii) a well-fed PBT individual can spawn an average number of 9 batches per spawning season, (iii) food abundance experienced by wild PBT is rather constant and sufficiently high to provide energy for yearly reproductive cycle, (iv) energy in reserve is exceptionally small, causing the weight-length relationship of cultivated and wild PBT to be practically indistinguishable and suggesting that these fish are poorly equipped to deal with starvation, (v) accelerated growth rate of PBT larvae is connected to morphological changes prior to metamorphosis, while (vi) deceleration of growth rate in the early juvenile stage is related to efficiency of internal heat production. Based on these results, we discuss a number of physiological and ecological traits of PBT, including the reasons for high Feed Conversion Ratio recorded in bluefin tuna aquaculture.