The predator-prey power law: Biomass scaling across terrestrial and aquatic biomes

Indirect effects of African megaherbivore conservation on bat diversity in the world's oldest desert

In extreme environments, temperature and precipitation are often the main forces responsible for structuring ecological communities and species distributions. The role of biotic interactions is typically thought to be minimal. By clustering around rare and isolated features, like surface water, however, effects of herbivory by desert-dwelling wildlife can be amplified. Understanding how species interact in these environments is critical to safeguarding vulnerable or data-deficient species. We examined whether African elephants (Loxodonta africana), black rhinoceros (Diceros bicornis), and southern giraffe (Giraffa giraffa) modulate insectivorous bat communities around permanent waterholes in the Namib Desert. We estimated megaherbivore use of sites based on dung transects, summarized vegetation productivity from satellite measurements of the normalized difference vegetation index, and surveyed local bat communities acoustically. We used structural equation models to identify relationships among megaherbivores and bat species richness and dry- (November 2016-January 2017) and wet- (February-May 2017) season bat activity. Site-level megaherbivore use in the dry season was positively associated with bat activity-particularly that of open-air foragers-and species richness through indirect pathways. When resources were more abundant (wet season), however, these relationships were weakened. Our results indicate that biotic interactions contribute to species distributions in desert areas and suggest the conservation of megaherbivores in this ecosystem may indirectly benefit insectivorous bat abundance and diversity. Given that how misunderstood and understudied most bats are relative to other mammals, such findings suggest that managers pursue short-term solutions (e.g., community game guard programs, water-point protection near human settlements, and ecotourism) to indirectly promote bat conservation and that research includes megaherbivores' effects on biodiversity at other trophic levels.

Cascading impacts of urbanization on multitrophic richness and biomass stock in neotropical streams

The conversion of natural streams to urbanized systems with the intention of supplying the cities' water demand causes species loss across many trophic groups, with negative consequences for ecosystem functioning. High levels of watershed urbanization cause environmental changes through water quality deterioration and loss of habitat heterogeneity. However, it remains unclear how environmental changes resulting from urbanization affect the diversity of multiple trophic groups and ecosystem functions, such as biomass stock in streams. Here, using a dataset from Neotropical streams, we investigate the cascading effects of urbanization (via impoverishment of water quality and habitat heterogeneity) on richness of multiple trophic groups of fish, and their consequences to biomass stock of streams. The increase in urbanization decreased the richness and standing biomass of carnivores, omnivores, and detritivores across streams. Urbanization also decreased habitat heterogeneity and water quality, which driver a huge cascading decrease in the richness of carnivores, omnivores, and detritivores, and ultimately reduced the whole-community standing biomass. Our analysis revealed that urbanization expansion induces a cascading reduction of multitrophic diversity and standing biomass in Neotropical streams. Therefore, the predicted increase in urbanization in the coming decades should impacts the richness of multiple trophic levels, with potential negative consequences to ecosystem functioning of streams.

Dietary abundance distributions: Dominance and diversity in vertebrate diets

Diet composition is among the most important yet least understood dimensions of animal ecology. Inspired by the study of species abundance distributions (SADs), we tested for generalities in the structure of vertebrate diets by characterising them as dietary abundance distributions (DADs). We compiled data on 1167 population-level diets, representing >500 species from six vertebrate classes, spanning all continents and oceans. DADs near-universally (92.5%) followed a hollow-curve shape, with scant support for other plausible rank-abundance-distribution shapes. This strong generality is inherently related to, yet incompletely explained by, the SADs of available food taxa. By quantifying dietary generalisation as the half-saturation point of the cumulative distribution of dietary abundance (sp50, minimum number of foods required to account for 50% of diet), we found that vertebrate populations are surprisingly specialised: in most populations, fewer than three foods accounted for at least half the diet. Variation in sp50 was strongly associated with consumer type, with carnivores being more specialised than herbivores or omnivores. Other methodological (sampling method and effort, taxonomic resolution), biological (body mass, frugivory) and biogeographic (latitude) factors influenced sp50 to varying degrees. Future challenges include identifying the mechanisms underpinning the hollow-curve DAD, its generality beyond vertebrates, and the biological determinants of dietary generalisation.

Mean Hitting Time for Random Walks on a Class of Sparse Networks

For random walks on a complex network, the configuration of a network that provides optimal or suboptimal navigation efficiency is meaningful research. It has been proven that a complete graph has the exact minimal mean hitting time, which grows linearly with the network order. In this paper, we present a class of sparse networks G(t) in view of a graphic operation, which have a similar dynamic process with the complete graph; however, their topological properties are different. We capture that G(t) has a remarkable scale-free nature that exists in most real networks and give the recursive relations of several related matrices for the studied network. According to the connections between random walks and electrical networks, three types of graph invariants are calculated, including regular Kirchhoff index, M-Kirchhoff index and A-Kirchhoff index. We derive the closed-form solutions for the mean hitting time of G(t), and our results show that the dominant scaling of which exhibits the same behavior as that of a complete graph. The result could be considered when designing networks with high navigation efficiency.

Environmental factors influencing spotted hyena and lion population biomass across Africa

The spotted hyena (Crocuta crocuta Erxleben) and the lion (Panthera leo Linnaeus) are two of the most abundant and charismatic large mammalian carnivores in Africa and yet both are experiencing declining populations and significant pressures from environmental change. However, with few exceptions, most studies have focused on influences upon spotted hyena and lion populations within individual sites, rather than synthesizing data from multiple locations. This has impeded the identification of over-arching trends behind the changing biomass of these large predators. Using partial least squares regression models, influences upon population biomass were therefore investigated, focusing upon prey biomass, temperature, precipitation, and vegetation cover. Additionally, as both species are in competition with one other for food, the influence of competition and evidence of environmental partitioning were assessed. Our results indicate that spotted hyena biomass is more strongly influenced by environmental conditions than lion, with larger hyena populations in areas with warmer winters, cooler summers, less drought, and more semi-open vegetation cover. Competition was found to have a negligible influence upon spotted hyena and lion populations, and environmental partitioning is suggested, with spotted hyena population biomass greater in areas with more semi-open vegetation cover. Moreover, spotted hyena is most heavily influenced by the availability of medium-sized prey biomass, whereas lion is influenced more by large size prey biomass. Given the influences identified upon spotted hyena populations in particular, the results of this study could be used to highlight populations potentially at greatest risk of decline, such as in areas with warming summers and increasingly arid conditions.

Bottom-Heavy Trophic Pyramids Impair Methylmercury Biomagnification in the Marine Plankton Ecosystems

Methylmercury (CH₃Hg⁺, MMHg) in the phytoplankton and zooplankton, which form the bottom of marine food webs, is a good predictor of MMHg in top predators, including humans. Therefore, evaluating the potential exposure of MMHg to higher trophic levels (TLs) requires a better understanding of relationships between MMHg biomagnification and plankton dynamics. In this study, a coupled ecological/physical model with 366 plankton types of different sizes, biogeochemical functions, and temperature tolerance is used to simulate the relationships between MMHg biomagnification and the ecosystem structure. The study shows that the MMHg biomagnification becomes more significant with increasing TLs. Trophic magnification factors (TMFs) in the lowest two TLs show the opposite spatial pattern to TMFs in higher TLs. The low TMFs are usually associated with a short food-chain length. The less bottom-heavy trophic pyramids in the oligotrophic oceans enhance the MMHg trophic transfer. The global average TMF is increased from 2.3 to 2.8 in the warmer future with a medium climate sensitivity of 2.5 °C. Our study suggests that if there are no mitigation measures for Hg emission, MMHg in the high-trophic-level plankton is increased more dramatically in the warming future, indicating greater MMHg exposure for top predators such as humans.

The global ocean size spectrum from bacteria to whales

It has long been hypothesized that aquatic biomass is evenly distributed among logarithmic body mass size classes. Although this community structure has been observed regionally, mostly among plankton groups, its generality has never been formally tested across all marine life over the global ocean, nor have the impacts of humans on it been globally assessed. Here, we bring together data at the global scale to test the hypothesis from bacteria to whales. We find that biomass within most order of magnitude size classes is indeed remarkably constant, near 1 gigatonne (Gt) wet weight (10¹⁵ g), but bacteria and large marine mammals are markedly above and below this value, respectively. Furthermore, human impacts appear to have significantly truncated the upper one-third of the spectrum. This dramatic alteration to what is possibly life’s largest-scale regularity underscores the global extent of human activities.

Cancer as a Model System for Testing Metabolic Scaling Theory

Biological allometries, such as the scaling of metabolism to mass, are hypothesized to result from natural selection to maximize how vascular networks fill space yet minimize internal transport distances and resistance to blood flow. Metabolic scaling theory argues two guiding principles—conservation of fluid flow and space-filling fractal distributions—describe a diversity of biological networks and predict how the geometry of these networks influences organismal metabolism. Yet, mostly absent from past efforts are studies that directly, and independently, measure metabolic rate from respiration and vascular architecture for the same organ, organism, or tissue. Lack of these measures may lead to inconsistent results and conclusions about metabolism, growth, and allometric scaling. We present simultaneous and consistent measurements of metabolic scaling exponents from clinical images of lung cancer, serving as a first-of-its-kind test of metabolic scaling theory, and identifying potential quantitative imaging biomarkers indicative of tumor growth. We analyze data for 535 clinical PET-CT scans of patients with non-small cell lung carcinoma to establish the presence of metabolic scaling between tumor metabolism and tumor volume. Furthermore, we use computer vision and mathematical modeling to examine predictions of metabolic scaling based on the branching geometry of the tumor-supplying blood vessel networks in a subset of 56 patients diagnosed with stage II-IV lung cancer. Examination of the scaling of maximum standard uptake value with metabolic tumor volume, and metabolic tumor volume with gross tumor volume, yield metabolic scaling exponents of 0.64 (0.20) and 0.70 (0.17), respectively. We compare these to the value of 0.85 (0.06) derived from the geometric scaling of the tumor-supplying vasculature. These results: (1) inform energetic models of growth and development for tumor forecasting; (2) identify imaging biomarkers in vascular geometry related to blood volume and flow; and (3) highlight unique opportunities to develop and test the metabolic scaling theory of ecology in tumors transitioning from avascular to vascular geometries.

The biology of seed discrimination and its role in shaping the foraging ecology of carabids: A review

Species of carabid (ground) beetles are among the most important postdispersal weed seed predators in temperate arable lands. Field studies have shown that carabid beetles can remove upwards of 65%-90% of specific weed seeds shed in arable fields each year. Such data do not explain how and why carabid predators go after weed seeds, however. It remains to be proven that weed seed predation by carabids is a genuine ecological interaction driven by certain ecological factors or functional traits that determine interaction strength and power predation dynamics, bringing about therefore a natural regulation of weed populations. Along these lines, this review ties together the lines of evidence around weed seed predation by carabid predators. Chemoperception rather than vision seems to be the primary sensory mechanism guiding seed detection and seed selection decisions in carabid weed seed predators. Selection of weed seeds by carabid seed predators appears directed rather than random. Yet, the nature of the chemical cues mediating detection of different seed species and identification of the suitable seed type among them remains unknown. Selection of certain types of weed seeds cannot be predicted based on seed chemistry per se in all cases, however. Rather, seed selection decisions are ruled by sophisticated behavioral mechanisms comprising the assessment of both chemical and physical characteristics of the seed. The ultimate selection of certain weed seed types is determined by how the chemical and physical properties of the seed match with the functional traits of the predator in terms of seed handling ability. Seed density, in addition to chemical and physical seed traits, is also an important factor that is likely to shape seed selection decisions in carabid weed seed predators. Carabid responses to seed density are rather complex as they are influenced not only by seed numbers but also by trait-based suitability ranks of the different seed types available in the environment.

On the evolution of trophic position

The trophic structure of food webs is primarily determined by the variation in trophic position among species and individuals. Temporal dynamics of food web structure are central to our understanding of energy and nutrient fluxes in changing environments, but little is known about how evolutionary processes shape trophic position variation in natural populations. We propose that trophic position, whose expression depends on both environmental and genetic determinants of the diet variation in individual consumers, is a quantitative trait that can evolve via natural selection. Such evolution can occur either when trophic position is correlated with other heritable morphological and behavioural traits under selection, or when trophic position is a target of selection, which is possible if the fitness effects of prey items are heterogeneously distributed along food chains. Recognising trophic position as an evolving trait, whose expression depends on the food web context, provides an important conceptual link between behavioural foraging theory and food web dynamics, and a useful starting point for the integration of ecological and evolutionary studies of trophic position.

Metabolism drives demography in an experimental field test

Metabolism should drive demography by determining the rates of both biological work and resource demand. Long-standing "rules" for how metabolism should covary with demography permeate biology, from predicting the impacts of climate change to managing fisheries. Evidence for these rules is almost exclusively indirect and in the form of among-species comparisons, while direct evidence is exceptionally rare. In a manipulative field experiment on a sessile marine invertebrate, we created experimental populations that varied in population size (density) and metabolic rate, but not body size. We then tested key theoretical predictions regarding relationships between metabolism and demography by parameterizing population models with lifetime performance data from our field experiment. We found that populations with higher metabolisms had greater intrinsic rates of increase and lower carrying capacities, in qualitative accordance with classic theory. We also found important departures from theory-in particular, carrying capacity declined less steeply than predicted, such that energy use at equilibrium increased with metabolic rate, violating the long-standing axiom of energy equivalence. Theory holds that energy equivalence emerges because resource supply is assumed to be independent of metabolic rate. We find this assumption to be violated under real-world conditions, with potentially far-reaching consequences for the management of biological systems.

Disentangling controls on animal abundance: Prey availability, thermal habitat, and microhabitat structure

The question of what controls animal abundance has always been fundamental to ecology, but given rapid environmental change, understanding the drivers and mechanisms governing abundance is more important than ever. Here, we determine how multidimensional environments and niches interact to determine population abundance along a tropical habitat gradient. Focusing on the endemic lizard Anolis bicaorum on the island of Utila (Honduras), we evaluate direct and indirect effects of three interacting niche axes on abundance: thermal habitat quality, structural habitat quality, and prey availability. We measured A. bicaorum abundance across a series of thirteen plots and used N-mixture models and path analysis to disentangle direct and indirect effects of these factors. Results showed that thermal habitat quality and prey biomass both had positive direct effects on anole abundance. However, thermal habitat quality also influenced prey biomass, leading to a strong indirect effect on abundance. Thermal habitat quality was primarily a function of canopy density, measured as leaf area index (LAI). Despite having little direct effect on abundance, LAI had a strong overall effect mediated by thermal quality and prey biomass. Our results demonstrate the role of multidimensional environments and niche interactions in determining animal abundance and highlight the need to consider interactions between thermal niches and trophic interactions to understand variation in abundance, rather than focusing solely on changes in the physical environment.

Microgeographic evolution of metabolic physiology in a salamander metapopulation

The Metabolic Theory of Ecology explains ecological variation spanning taxonomic organization, space, and time based on universal physiological relationships. The theory depends on two core parameters: the normalization constant, a mass-independent measure of metabolic rate expected to be invariant among similar species, and the scaling coefficient, a measure of metabolic change with body mass commonly assumed to follow the universal 3/4 scaling law. However, emerging evidence for adaptive microevolution of metabolic rates led us to hypothesize that metabolic rate might exhibit evolved variation among populations on microgeographic scales. To evaluate our hypothesis, we explored evidence for evolved variation in the scaling coefficient and normalization constant within a spotted salamander (Ambystoma maculatum) metapopulation in Connecticut, USA. We measured standard metabolic rate in common-garden raised spotted salamanders from 22 different populations and tested for the effects of six ecological variables suspected in advance to select for divergent physiology. We found that metabolic rate rose with body mass with a log-log slope of 0.97 that was statistically different from the expected 3/4 scaling law. Although we found no evidence for interpopulation variation in the scaling coefficient, we found evidence for interpopulation variation in the normalization constants among populations. Metabolic variation was best explained by differences in population density among ponds. Our results provide mixed support for Metabolic Theory of Ecology assumptions about parameter invariance and illustrate how fundamental physiological processes such as metabolic rate can evolve across microgeographic spatial scales.

Home range variation in leopards living across the human density gradient

Home range size is a fundamental measure of animal space use, providing insight into habitat quality, animal density, and social organization. Human impacts increasingly are affecting wildlife, especially among wide-ranging species that encounter anthropogenic disturbance. Leopards (Panthera pardus) provide a useful model for studying this relationship because leopards coexist with people at high and low human densities and are sensitive to human disturbance. To compare leopard home range size across a range of human densities and other environmental conditions, we combined animal tracking data from 74 leopards in multiple studies with new analytical techniques that accommodate different sampling regimes. We predicted that home ranges would be smaller in more productive habitats and areas of higher human population density due to possible linkage with leopard prey subsidies from domestic species. We also predicted that male leopards would have larger home ranges than those of females. Home ranges varied in size from 14.5 km2 in India to 885.6 km2 in Namibia, representing a 60-fold magnitude of variation. Home range stability was evident for 95.2% of nontranslocated individuals and 38.5% of translocated individuals. Leopard home range sizes were negatively correlated with landscape productivity, and males used larger areas than females. Leopards in open habitats had a predicted negative correlation in home range size with human population density, but leopards in closed habitats used larger home ranges in areas with more people.

Towards an ecosystem model of infectious disease

Increasingly intimate associations between human society and the natural environment are driving the emergence of novel pathogens, with devastating consequences for humans and animals alike. Prior to emergence, these pathogens exist within complex ecological systems that are characterized by trophic interactions between parasites, their hosts and the environment. Predicting how disturbance to these ecological systems places people and animals at risk from emerging pathogens-and the best ways to manage this-remains a significant challenge. Predictive systems ecology models are powerful tools for the reconstruction of ecosystem function but have yet to be considered for modelling infectious disease. Part of this stems from a mistaken tendency to forget about the role that pathogens play in structuring the abundance and interactions of the free-living species favoured by systems ecologists. Here, we explore how developing and applying these more complete systems ecology models at a landscape scale would greatly enhance our understanding of the reciprocal interactions between parasites, pathogens and the environment, placing zoonoses in an ecological context, while identifying key variables and simplifying assumptions that underly pathogen host switching and animal-to-human spillover risk. As well as transforming our understanding of disease ecology, this would also allow us to better direct resources in preparation for future pandemics.

Growth, death, and resource competition in sessile organisms

Population-level scaling in ecological systems arises from individual growth and death with competitive constraints. We build on a minimal dynamical model of metabolic growth where the tension between individual growth and mortality determines population size distribution. We then separately include resource competition based on shared capture area. By varying rates of growth, death, and competitive attrition, we connect regular and random spatial patterns across sessile organisms from forests to ants, termites, and fairy circles. Then, we consider transient temporal dynamics in the context of asymmetric competition, such as canopy shading or large colony dominance, whose effects primarily weaken the smaller of two competitors. When such competition couples slow timescales of growth to fast competitive death, it generates population shocks and demographic oscillations similar to those observed in forest data. Our minimal quantitative theory unifies spatiotemporal patterns across sessile organisms through local competition mediated by the laws of metabolic growth, which in turn, are the result of long-term evolutionary dynamics.

Inferring ecosystem networks as information flows

The detection of causal interactions is of great importance when inferring complex ecosystem functional and structural networks for basic and applied research. Convergent cross mapping (CCM) based on nonlinear state-space reconstruction made substantial progress about network inference by measuring how well historical values of one variable can reliably estimate states of other variables. Here we investigate the ability of a developed optimal information flow (OIF) ecosystem model to infer bidirectional causality and compare that to CCM. Results from synthetic datasets generated by a simple predator-prey model, data of a real-world sardine-anchovy-temperature system and of a multispecies fish ecosystem highlight that the proposed OIF performs better than CCM to predict population and community patterns. Specifically, OIF provides a larger gradient of inferred interactions, higher point-value accuracy and smaller fluctuations of interactions and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha$$\end{document}α-diversity including their characteristic time delays. We propose an optimal threshold on inferred interactions that maximize accuracy in predicting fluctuations of effective \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha$$\end{document}α-diversity, defined as the count of model-inferred interacting species. Overall OIF outperforms all other models in assessing predictive causality (also in terms of computational complexity) due to the explicit consideration of synchronization, divergence and diversity of events that define model sensitivity, uncertainty and complexity. Thus, OIF offers a broad ecological information by extracting predictive causal networks of complex ecosystems from time-series data in the space-time continuum. The accurate inference of species interactions at any biological scale of organization is highly valuable because it allows to predict biodiversity changes, for instance as a function of climate and other anthropogenic stressors. This has practical implications for defining optimal ecosystem management and design, such as fish stock prioritization and delineation of marine protected areas based on derived collective multispecies assembly. OIF can be applied to any complex system and used for model evaluation and design where causality should be considered as non-linear predictability of diverse events of populations or communities.

Searching for fat tails in CRISPR-Cas systems: Data analysis and mathematical modeling

Understanding CRISPR-Cas systems-the adaptive defence mechanism that about half of bacterial species and most of archaea use to neutralise viral attacks-is important for explaining the biodiversity observed in the microbial world as well as for editing animal and plant genomes effectively. The CRISPR-Cas system learns from previous viral infections and integrates small pieces from phage genomes called spacers into the microbial genome. The resulting library of spacers collected in CRISPR arrays is then compared with the DNA of potential invaders. One of the most intriguing and least well understood questions about CRISPR-Cas systems is the distribution of spacers across the microbial population. Here, using empirical data, we show that the global distribution of spacer numbers in CRISPR arrays across multiple biomes worldwide typically exhibits scale-invariant power law behaviour, and the standard deviation is greater than the sample mean. We develop a mathematical model of spacer loss and acquisition dynamics which fits observed data from almost four thousand metagenomes well. In analogy to the classical 'rich-get-richer' mechanism of power law emergence, the rate of spacer acquisition is proportional to the CRISPR array size, which allows a small proportion of CRISPRs within the population to possess a significant number of spacers. Our study provides an alternative explanation for the rarity of all-resistant super microbes in nature and why proliferation of phages can be highly successful despite the effectiveness of CRISPR-Cas systems.

Exceptionally high but still growing predatory reef fish biomass after 23 years of protection in a Marine Protected Area

Marine Protected Areas (MPAs) help replenish fish assemblages, though different trophic levels may show diverse recovery patterns. Long-term protection is required to achieve total recovery but poaching events may prevent the achievement of full carrying capacity. Here, we have analysed the effect of long-term protection on the entire reef fish community and the different trophic levels in the Cabo de Palos-Islas Hormigas MPA (SE Spain; SW Mediterranean Sea) in order to assess their recovery patterns after 23 years of protection. We compared the values for carrying capacity obtained with the maximum values achieved at regional scale, and we assessed the effect of a reduction in the surveillance over a few years, during which poaching events increased, on the recovery patterns. We found that, overall, biomass of fishes increased with time while density diminished. In particular, piscivorous and macro-invertivore fish increased while the other trophic groups remained constant or declined, suggesting top-down processes. For the entire study period, those trophic groups were approaching carrying capacity; however, when accounting only for the period in which enforcement was high and constant, they grew exponentially, indicating that full carrying capacity may have not been achieved yet. When compared to other Mediterranean MPAs, the Cabo de Palos-Islas Hormigas MPA showed values for biomass that were disproportionately higher, suggesting that local factors, such as habitat structure and associated oceanographic processes, may be responsible for the dynamics found. Our results help to understand the potential trajectories of fish assemblages over a consolidated MPA and highlight empirically how the reduction of surveillance in a period may change the recovery patterns.

Development of photosynthetic carbon fixation model using multi-excitation wavelength fast repetition rate fluorometry in Lake Biwa

Direct measurements of gross primary productivity (GPP) in the water column are essential, but can be spatially and temporally restrictive. Fast repetition rate fluorometry (FRRf) is a bio-optical technique based on chlorophyll a (Chl-a) fluorescence that can estimate the electron transport rate (ETR_PSII) at photosystem II (PSII) of phytoplankton in real time. However, the derivation of phytoplankton GPP in carbon units from ETR_PSII remains challenging because the electron requirement for carbon fixation (Ф_e,C), which is mechanistically 4 mol e⁻ mol C⁻¹ or above, can vary depending on multiple factors. In addition, FRRf studies are limited in freshwater lakes where phosphorus limitation and cyanobacterial blooms are common. The goal of the present study is to construct a robust Ф_e,C model for freshwater ecosystems using simultaneous measurements of ETR_PSII by FRRf with multi-excitation wavelengths coupled with a traditional carbon fixation rate by the ¹³C method. The study was conducted in oligotrophic and mesotrophic parts of Lake Biwa from July 2018 to May 2019. The combination of excitation light at 444, 512 and 633 nm correctly estimated ETR_PSII of cyanobacteria. The apparent range of Ф_e,C in the phytoplankton community was 1.1–31.0 mol e⁻ mol C⁻¹ during the study period. A generalised linear model showed that the best fit including 12 physicochemical and biological factors explained 67% of the variance in Ф_e,C. Among all factors, water temperature was the most significant, while photosynthetically active radiation intensity was not. This study quantifies the in situ FRRf method in a freshwater ecosystem, discusses core issues in the methodology to calculate Ф_e,C, and assesses the applicability of the method for lake GPP prediction.

Host cell volume explains differences in the size of DsDNA viruses

The nearly 3 orders of magnitude variation in size observed among double-stranded DNA viruses (dsDNA) has important ecological consequences, but the factors responsible for this variation remain poorly understood. Here we first evaluate if a relationship exists between the genome size of diverse dsDNA viruses and their hosts in single-celled organisms (prokaryotes and eukaryotes). We find that dsDNA genome size increases systematically, though less than proportionally, with host genome size. We next evaluate possible relationships between virus size, host size and burst size in an analysis that includes both single-celled and multicellular hosts where genome size and cell volume are not as highly correlated. Here we find that virus volume increases sublinearly with host cell volume (but not genome size) across species, and that virus burst volume (burst size * virus volume) increases with host cell volume. These findings suggest that the size and number of dsDNA viruses produced by a particular host may be constrained by the volume of the infected host cell. This may be useful for better understanding virus-host population dynamics, and ultimately, a better understanding of which viruses may infect which hosts (i.e., host specificity) and the likelihood of cross-species transmission events (i.e., host jumping).

gauseR: Simple methods for fitting Lotka-Volterra models describing Gause's "Struggle for Existence"

Point 1: The ecological models of Alfred J. Lotka and Vito Volterra have had an enormous impact on ecology over the past century. Some of the earliest-and clearest-experimental tests of these models were famously conducted by Georgy Gause in the 1930s. Although well known, the data from these experiments are not widely available and are often difficult to analyze using standard statistical and computational tools. Point 2: Here, we introduce the gauseR package, a collection of tools for fitting Lotka-Volterra models to time series data of one or more species. The package includes several methods for parameter estimation and optimization, and includes 42 datasets from Gause's species interaction experiments and related work. Additionally, we include with this paper a short blog post discussing the historical importance of these data and models, and an R vignette with a walk-through introducing the package methods. The package is available for download at github.com/adamtclark/gauseR. Point 3: To demonstrate the package, we apply it to several classic experimental studies from Gause, as well as two other well-known datasets on multi-trophic dynamics on Isle Royale, and in spatially structured mite populations. In almost all cases, models fit observations closely and fitted parameter values make ecological sense. Point 4: Taken together, we hope that the methods, data, and analyses that we present here provide a simple and user-friendly way to interact with complex ecological data. We are optimistic that these methods will be especially useful to students and educators who are studying ecological dynamics, as well as researchers who would like a fast tool for basic analyses.

Incorporating indirect pathways in body size-trophic position relationships

Body size, trophic position (TP), and trophic niche width are important elements of food webs; however, there is still debate regarding their interrelationships. Most studies have tested these correlations using datasets restricted to carnivores and bivariate models that disregard potential indirect effects of other factors, their interactions, and phylogeny. We analyzed relationships among TP, consumer size, maximum food item size, food item size variation (a proxy for trophic niche width), and two other traits (gut length and mouth width) using confirmatory path analysis of an extensive dataset for freshwater fishes that encompass both carnivorous and non-carnivorous species. Consumer size was associated with maximum food size, food size variation, mouth width, and gut length, all of which mediated indirect relationships between body size and TP. Mouth gape was associated with maximum food size, and consumers that fed on larger food items had higher TP. Consumers with relatively long guts generally fed on small and homogeneous food items near the base of the food web. Models were consistent whether or not accounting for phylogeny, but varied according to trophic guilds. However, the body size of both carnivorous and non-carnivorous was not directly associated with TP. Therefore, the incorporation of functional traits and their intermediate pathways is critical for understanding size-based trophic relationships of animals that encompass diverse feeding strategies. Our results caution approaches that rely on body size as a surrogate for TP, especially in systems where plants and detritus are consumed directly by a significant number of animals, such as in most freshwater ecosystems.

How to estimate community energy flux? A comparison of approaches reveals that size-abundance trade-offs alter the scaling of community energy flux

Size and metabolism are highly correlated, so that community energy flux might be predicted from size distributions alone. However, the accuracy of predictions based on interspecific energy-size relationships relative to approaches not based on size distributions is unknown. We compare six approaches to predict energy flux in phytoplankton communities across succession: assuming a constant energy use among species (per cell or unit biomass), using energy-size interspecific scaling relationships and species-specific rates (both with or without accounting for density effects). Except for the per cell approach, all others explained some variation in energy flux but their accuracy varied considerably. Surprisingly, the best approach overall was based on mean biomass-specific rates, followed by the most complex (species-specific rates with density). We show that biomass-specific rates alone predict community energy flux because the allometric scaling of energy use with size measured for species in isolation does not reflect the isometric scaling of these species in communities. We also find energy equivalence throughout succession, even when communities are not at carrying capacity. Finally, we discuss that species assembly can alter energy-size relationships, and that metabolic suppression in response to density might drive the allometry of community energy flux as biomass accumulates.

An non-loglinear enzyme-driven law of photosynthetic scaling in two representative crop seedlings under different water conditions

The loglinear pattern of respiratory scaling has been studied for over a century, while an increasing number of non-loglinear patterns have been found in the plant kingdom. Several previous studies had attempted to reconcile conflicting patterns from the aspects of statistical approaches and developmental stages of the organisms. However, the underlying enzymatic mechanism was largely ignored. Here, we propose an enzyme-driven law of photosynthetic scaling and test it in typical crop seedlings under different water conditions. The results showed that the key enzyme activity, the relative photosynthetic assimilation and the relative growth rate were all constrained by the available water, and the relationship between these biological traits and the available water supported our predictions. The enzyme-driven law appears to be more suitable to explain the curvature of photosynthetic scaling than the well-established power law, since it provides insight into the biochemical origin of photosynthetic assimilation.

Dense networks with scale-free feature

While previous works have shown that an overwhelming number of scale-free networks are sparse, there still exist some real-world networks including social networks, urban networks, information networks, which are by observation dense. In this paper, we propose a framework for generating scale-free graphs with a dense feature using two simple yet helpful operations: first-order subdivision and line operation. From the theoretical point of view, our method can be used not only to produce desired scale-free graphs with a density feature, i.e., a power-law exponent γ falling into the interval 1<γ≤2, but also to establish many other unexpected networked models, for instance, power-law models having a large diameter. In addition, the networked models generated upon our framework show an especially assortative structure. That is, their own Pearson correlation coefficients are able to achieve the theoretical upper bound. Last but not the least, we find the sizes of community in the proposed models to follow the power law in a form with respect to modularity maximization.

Extreme rainfall events alter the trophic structure in bromeliad tanks across the Neotropics

Changes in global and regional precipitation regimes are among the most pervasive components of climate change. Intensification of rainfall cycles, ranging from frequent downpours to severe droughts, could cause widespread, but largely unknown, alterations to trophic structure and ecosystem function. We conducted multi-site coordinated experiments to show how variation in the quantity and evenness of rainfall modulates trophic structure in 210 natural freshwater microcosms (tank bromeliads) across Central and South America (18°N to 29°S). The biomass of smaller organisms (detritivores) was higher under more stable hydrological conditions. Conversely, the biomass of predators was highest when rainfall was uneven, resulting in top-heavy biomass pyramids. These results illustrate how extremes of precipitation, resulting in localized droughts or flooding, can erode the base of freshwater food webs, with negative implications for the stability of trophic dynamics.

The amount and frequency of rainfall structures aquatic food webs. Here the authors show that in tropical tank bromeliads, lower trophic levels are more abundant in stable rainfall conditions, while biomass pyramids are inverted in conditions with periodic droughts.

Ecological assessment of anthropogenic impact in marine ecosystems: The case of Bagnoli Bay

Pollutants alter marine systems, interfering with provisioning of ecosystem services; understanding their interaction with ecological communities is therefore critical to inform environmental management. Here we propose a joint compositional- and interaction-based analysis for ecological status assessment and apply it on the benthic communities of the Bagnoli Bay. We found that contamination differentially affects the communities' composition in the bay, with prokaryotes influenced only by depth, and benthos not following the environmental gradient at all. This result is confirmed by analyses of the community structure, whose network structure suggest fast carbon flow and cycling, especially promoted by nematodes and polychaetes; the benthic prey/predator biomass ratio, adjusted for competition, successfully synthesise the status of predator taxa. We found demersal fish communities to separate into a deep, pelagic-like community, and two shallow communities where a shift from exclusive predators to omnivores occurs, moving from the most polluted to the least polluted sampling units. Finally, our study indicate that indices based on interspecific interactions are better indicators of environmental gradients than those defined based on species composition exclusively.

Bottom-up when it is not top-down: Predators and plants control biomass of grassland arthropods

We investigate where bottom-up and top-down control regulates ecological communities as a mechanism linking ecological gradients to the geography of consumer abundance and biomass. We use standardized surveys of 54 North American grasslands to test alternate hypotheses predicting 100-fold shifts in the biomass of four common grassland arthropod taxa-Auchenorrhyncha, sucking herbivores, Acrididae, chewing herbivores, Tettigoniidae, omnivores, and Araneae, predators. Bottom-up models predict that consumer biomass tracks plant quantity (e.g. productivity and standing biomass) and quality (nutrient content) and that ectotherm access to food increases with temperature. Each of the focal trophic groups responded differently to these drivers: the biomass of sucking herbivores and omnivores increased with plant biomass; that of chewing herbivores tracked plant quality; and predator biomass did not depend on plant quality, plant quantity or temperature. The Exploitation Ecosystem Hypothesis is a top-down hypothesis that predicts a shift from resource limitation of herbivores when plant production is low, to predator limitation when plant production is high. In grasslands where spider biomass was low, herbivore biomass increased with plant biomass, whereas bottom-up structuring was not evident when spiders were abundant. Furthermore, neither predator biomass nor trophic position (via stable isotope analysis) increased with plant biomass, suggesting predators themselves are top-down limited. Stable isotope analysis revealed that trophic position of the chewing herbivore and omnivore increased significantly with plant biomass, suggesting these groups increased scavenging and meat consumption in grasslands with higher carbohydrate availability. Taken together, our snapshot sampling documents gradients of food web structure across 54 grasslands, consistent with multiple hypotheses of bottom-up and top-down regulation.

Regime shifts occur disproportionately faster in larger ecosystems

Regime shifts can abruptly affect hydrological, climatic and terrestrial systems, leading to degraded ecosystems and impoverished societies. While the frequency of regime shifts is predicted to increase, the fundamental relationships between the spatial-temporal scales of shifts and their underlying mechanisms are poorly understood. Here we analyse empirical data from terrestrial (n = 4), marine (n = 25) and freshwater (n = 13) environments and show positive sub-linear empirical relationships between the size and shift duration of systems. Each additional unit area of an ecosystem provides an increasingly smaller unit of time taken for that system to collapse, meaning that large systems tend to shift more slowly than small systems but disproportionately faster. We substantiate these findings with five computational models that reveal the importance of system structure in controlling shift duration. The findings imply that shifts in Earth ecosystems occur over 'human' timescales of years and decades, meaning the collapse of large vulnerable ecosystems, such as the Amazon rainforest and Caribbean coral reefs, may take only a few decades once triggered.

Scaling the risk landscape drives optimal life-history strategies and the evolution of grazing

Consumers face numerous risks that can be minimized by incorporating different life-history strategies. How much and when a consumer adds to its energetic reserves or invests in reproduction are key behavioral and physiological adaptations that structure communities. Here we develop a theoretical framework that explicitly accounts for stochastic fluctuations of an individual consumer's energetic reserves while foraging and reproducing on a landscape with resources that range from uniformly distributed to highly clustered. First, we show that the selection of alternative life histories depends on both the mean and variance of resource availability, where depleted and more stochastic environments promote investment in each reproductive event at the expense of future fitness as well as more investment per offspring. We then show that if resource variance scales with body size due to landscape clustering, consumers that forage for clustered foods are susceptible to strong Allee effects, increasing extinction risk. Finally, we show that the proposed relationship between resource distributions, consumer body size, and emergent demographic risk offers key ecological insights into the evolution of large-bodied grazing herbivores from small-bodied browsing ancestors.

Indirect effects of water availability in driving and predicting productivity in the Gobi desert

Climate is the fundamental determinant of plant metabolism and net primary productivity (NPP). However, whether climate drives NPP directly or indirectly is not well understand. The Gobi desert across a precipitation gradient in the arid zone provides an ideal naturally-controlled platform for studying the precipitation-productivity relationships. We conducted 3-year experiments in four Gobi desert shrublands across an aridity gradient in Gansu Province of China to test the relationship between water availability and shrub productivity as well as the relative importance of the possible factors driving productivity (using piecewise structural equation modeling) and to explore the appropriate variables for predicting productivity (using three spatial models). The results showed that water availability indirectly affected the NPP via stand biomass, while stand biomass had a significant direct effect on NPP regardless of whether the leaf water content and stand height were considered. The model based on stand size (71.6%) and the model that contained both stand size and water availability (72.3%) explained more of the variation in the water-NPP relationships than the model based on water availability (37.3%). Our findings suggest that even in extremely water-limited areas, the effects of water availability on plant growth and the kinetics of plant metabolism could be indirect via plant size, demonstrating the importance of plant size as an indicator of shrub productivity. This study explains the mechanisms underlying the NPP driving pattern and proposes a practical NPP model for arid ecosystems.

Linking scaling laws across eukaryotes

Scaling laws relating body mass to species characteristics are among the most universal quantitative patterns in biology. Within major taxonomic groups, the 4 key ecological variables of metabolism, abundance, growth, and mortality are often well described by power laws with exponents near 3/4 or related to that value, a commonality often attributed to biophysical constraints on metabolism. However, metabolic scaling theories remain widely debated, and the links among the 4 variables have never been formally tested across the full domain of eukaryote life, to which prevailing theory applies. Here we present datasets of unprecedented scope to examine these 4 scaling laws across all eukaryotes and link them to test whether their combinations support theoretical expectations. We find that metabolism and abundance scale with body size in a remarkably reciprocal fashion, with exponents near ±3/4 within groups, as expected from metabolic theory, but with exponents near ±1 across all groups. This reciprocal scaling supports "energetic equivalence" across eukaryotes, which hypothesizes that the partitioning of energy in space across species does not vary significantly with body size. In contrast, growth and mortality rates scale similarly both within and across groups, with exponents of ±1/4. These findings are inconsistent with a metabolic basis for growth and mortality scaling across eukaryotes. We propose that rather than limiting growth, metabolism adjusts to the needs of growth within major groups, and that growth dynamics may offer a viable theoretical basis to biological scaling.

Generalized size scaling of metabolic rates based on single-cell measurements with freshwater phytoplankton

Kleiber's law describes the scaling of metabolic rate with body size across several orders of magnitude in size and across taxa and is widely regarded as a fundamental law in biology. The physiological origins of Kleiber's law are still debated and generalizations of the law accounting for deviations from the scaling behavior have been proposed. Most theoretical and experimental studies of Kleiber's law, however, have focused on the relationship between the average body size of a species and its mean metabolic rate, neglecting intraspecific variation of these 2 traits. Here, we propose a theoretical characterization of such variation and report on proof-of-concept experiments with freshwater phytoplankton supporting such framework. We performed joint measurements at the single-cell level of cell volume and nitrogen/carbon uptake rates, as proxies of metabolic rates, of 3 phytoplankton species using nanoscale secondary ion mass spectrometry (NanoSIMS) and stable isotope labeling. Common scaling features of the distribution of nutrient uptake rates and cell volume are found to hold across 3 orders of magnitude in cell size. Once individual measurements of cell volume and nutrient uptake rate within a species are appropriately rescaled by a function of the average cell volume within each species, we find that intraspecific distributions of cell volume and metabolic rates collapse onto a universal curve. Based on the experimental results, this work provides the building blocks for a generalized form of Kleiber's law incorporating intraspecific, correlated variations of nutrient-uptake rates and body sizes.

Consumer adaptation mediates top-down regulation across a productivity gradient

Humans have artificially enhanced the productivity of terrestrial and aquatic ecosystems on a global scale by increasing nutrient loading. While the consequences of eutrophication are well known (e.g., harmful algal blooms and toxic cyanobacteria), most studies tend to examine short-term responses relative to the time scales of heritable adaptive change. Thus, the potential role of adaptation by organisms in stabilizing the response of ecological systems to such perturbations is largely unknown. We tested the hypothesis that adaptation by a generalist consumer (Daphnia pulicaria) to toxic prey (cyanobacteria) mediates the response of plankton communities to nutrient enrichment. Overall, the strength of Daphnia's top-down effect on primary producer biomass increased with productivity. However, these effects were contingent on prey traits (e.g., rare vs. common toxic cyanobacteria) and consumer genotype (i.e., tolerant vs sensitive to toxic cyanobacteria). Tolerant Daphnia strongly suppressed toxic cyanobacteria in nutrient-rich ponds, but sensitive Daphnia did not. In contrast, both tolerant and sensitive Daphnia genotypes had comparable effects on producer biomass when toxic cyanobacteria were absent. Our results demonstrate that organismal adaptation is critical for understanding and predicting ecosystem-level consequences of anthropogenic environmental perturbations.