How species richness and total abundance constrain the distribution of abundance

Aerobic Denitrification Enhanced by Immobilized Slow-Released Iron/Activated Carbon Aquagel Treatment of Low C/N Micropolluted Water: Denitrification Performance, Denitrifying Bacterial Community Co-occurrence, and Implications

The key limiting factors in the treatment of low C/N micropolluted water bodies are deficient essential electron donors for nitrogen removal processes. An iron/activated carbon aquagel (IACA) was synthesized as a slowly released inorganic electron donor to enhance aerobic denitrification performance in low C/N micropolluted water treatment. The denitrification efficiency in IACA reactors was enhanced by more than 56.72% and the highest of 94.12% was accomplished compared with those of the control reactors. Moreover, the COD_Mn removal efficiency improved by more than 34.32% in IACA reactors. The Illumina MiSeq sequencing consequence explained that the denitrifying bacteria with facultative denitrification, iron oxidation, and iron reduction function were located in the dominant species niches in the IACA reactors (e.g., Pseudomonas, Leptothrix, and Comamonas). The diversity and richness of the denitrifying bacterial communities were enhanced in the IACA reactors. Network analysis indicated that aerobic denitrifying bacterial consortia in IACA reactors presented a more complicated co-occurrence structure. The IACA reactors presented the potential for long-term denitrification operation. This study affords a pathway to utilize IACA, promoting aerobic denitrification during low C/N micropolluted water body treatment.

Nitrogen removal from low carbon/nitrogen polluted water is enhanced by a novel synthetic micro-ecosystem under aerobic conditions: Novel insight into abundance of denitrification genes and community interactions

The main limiting factor in treatment of wastewater with a low carbon/nitrogen ratio is insufficient electron donors for aerobic denitrification. A novel synthetic micro-ecosystem (SM) with functional materials as the core structure was prepared to enhance nitrate removal during wastewater treatment. Nitrate removal in the reactors with SM increased by more than 40 % and reached 97.43 % under aerobic conditions. The abundance of denitrification functional genes in activated sludge increased by 2.7 folds after adding SM. Network analysis showed that the denitrifying bacterial community in the reactors with SM displayed a more abundant symbiotic structure. In the reactors with SM, bacteria with both denitrification and inorganic electron transfer capabilities (such as Paracoccus sp., Thaurea sp., and Achromobacter sp.) occupied dominant niche. A species abundance distribution model indicated more intense competition for the dominant niche for the denitrification community in the reactor with SM. Thus, SM promotes denitrification in polluted water bodies under aerobic conditions.

Environmental drivers and spatial scaling of species abundance distributions in Palaearctic grassland vegetation

Species abundance distributions (SADs) link species richness with species abundances and are an important tool in the quantitative analysis of ecological communities. Niche‐based and sample‐based SAD models predict different spatial scaling properties of SAD parameters. However, empirical research on SAD scaling properties is largely missing. Here we extracted percentage cover values of all occurring vascular plants as proxies of their abundance in 1725 10‐m² plots from the GrassPlot database, covering 47 regional data sets of 19 different grasslands and other open vegetation types of the Palaearctic biogeographic realm. For each plot, we fitted the Weibull distribution, a model that is able to effectively mimic other distributions like the log‐series and lognormal, to the species–log abundance rank order distribution. We calculated the skewness and kurtosis of the empirical distributions and linked these moments, along with the shape and scale parameters of the Weibull distribution, to plot climatic and soil characteristics. The Weibull distribution provided excellent fits to grassland plant communities and identified four basic types of communities characterized by different degrees of dominance. Shape and scale parameter values of local communities on poorer soils were largely in accordance with log‐series distributions. Proportions of subdominant species tended to be lower than predicted by the standard lognormal SAD. Successive accumulation of plots of the same vegetation type yielded nonlinear spatial scaling of SAD moments and Weibull parameters. This scaling was largely independent of environmental correlates and geographic plot position. Our findings caution against simple generalizations about the mechanisms that generate SADs. We argue that in grasslands, lognormal‐type SADs tend to prevail within a wider range of environmental conditions, including more extreme habitats such as arid environments. In contrast, log‐series distributions are mainly restricted to comparatively species‐rich communities on humid and fertile soils.

Negative impacts of dominance on bee communities: Does the influence of invasive honey bees differ from native bees?

Invasive species can reach high abundances and dominate native environments. One of the most impressive examples of ecological invasions is the spread of the African subspecies of the honey bee throughout the Americas, starting from its introduction in a single locality in Brazil. The invasive honey bee is expected to more negatively impact bee community abundance and diversity than native dominant species, but this has not been tested previously. We developed a comprehensive and systematic bee sampling scheme, using a protocol deploying 11,520 pan traps across regions and crops for three years in Brazil. We found that invasive honey bees are now the single most dominant bee species. Such dominance has not only negative consequences for abundance and species richness of native bees but also for overall bee abundance (i.e., strong "numerical" effects of honey bees). Contrary to expectations, honey bees did not have stronger negative impacts than other native bees achieving similar levels of dominance (i.e., lack of negative "identity" effects of honey bees). These effects were markedly consistent across crop species, seasons and years, and were independent from land-use effects. Dominance could be a proxy of bee community degradation and more generally of the severity of ecological invasions.

Empirical abundance distributions are more uneven than expected given their statistical baseline

Exploring and accounting for the emergent properties of ecosystems as complex systems is a promising horizon in the search for general processes to explain common ecological patterns. For example the ubiquitous hollow-curve form of the species abundance distribution is frequently assumed to reflect ecological processes structuring communities, but can also emerge as a statistical phenomenon from the mathematical definition of an abundance distribution. Although the hollow curve may be a statistical artefact, ecological processes may induce subtle deviations between empirical species abundance distributions and their statistically most probable forms. These deviations may reflect biological processes operating on top of mathematical constraints and provide new avenues for advancing ecological theory. Examining ~22,000 communities, we found that empirical SADs are highly uneven and dominated by rare species compared to their statistical baselines. Efforts to detect deviations may be less informative in small communities-those with few species or individuals-because these communities have poorly resolved statistical baselines. The uneven nature of many empirical SADs demonstrates a path forward for leveraging complexity to understand ecological processes governing the distribution of abundance, while the issues posed by small communities illustrate the limitations of using this approach to study ecological patterns in small samples.

The Shape of Species Abundance Distributions Across Spatial Scales

Species abundance distributions (SADs) describe community structure and are a key component of biodiversity theory and research. Although different distributions have been proposed to represent SADs at different scales, a systematic empirical assessment of how SAD shape varies across wide scale gradients is lacking. Here, we examined 11 empirical large-scale datasets for a wide range of taxa and used maximum likelihood methods to compare the fit of the logseries, lognormal, and multimodal (i.e., with multiple modes of abundance) models to SADs across a scale gradient spanning several orders of magnitude. Overall, there was a higher prevalence of multimodality for larger spatial extents, whereas the logseries was exclusively selected as best fit for smaller areas. For many communities the shape of the SAD at the largest spatial extent (either lognormal or multimodal) was conserved across the scale gradient, despite steep declines in area and taxonomic diversity sampled. Additionally, SAD shape was affected by species richness, but we did not detect a systematic effect of the total number of individuals. Our results reveal clear departures from the predictions of two major macroecological theories of biodiversity for SAD shape. Specifically, neither the Neutral Theory of Biodiversity (NTB) nor the Maximum Entropy Theory of Ecology (METE) are able to accommodate the variability in SAD shape we encountered. This is highlighted by the inadequacy of the logseries distribution at larger scales, contrary to predictions of the NTB, and by departures from METE expectation across scales. Importantly, neither theory accounts for multiple modes in SADs. We suggest our results are underpinned by both inter- and intraspecific spatial aggregation patterns, highlighting the importance of spatial distributions as determinants of biodiversity patterns. Critical developments for macroecological biodiversity theories remain in incorporating the effect of spatial scale, ecological heterogeneity and spatial aggregation patterns in determining SAD shape.

An interactive tool to forecast US hospital needs in the coronavirus 2019 pandemic

OBJECTIVE

We developed an application (https://rush-covid19.herokuapp.com/) to aid US hospitals in planning their response to the ongoing Coronavirus Disease 2019 (COVID-19) pandemic.

MATERIALS AND METHODS

Our application forecasts hospital visits, admits, discharges, and needs for hospital beds, ventilators, and personal protective equipment by coupling COVID-19 predictions to models of time lags, patient carry-over, and length-of-stay. Users can choose from 7 COVID-19 models, customize 23 parameters, examine trends in testing and hospitalization, and download forecast data.

RESULTS

Our application accurately predicts the spread of COVID-19 across states and territories. Its hospital-level forecasts are in continuous use by our home institution and others.

DISCUSSION

Our application is versatile, easy-to-use, and can help hospitals plan their response to the changing dynamics of COVID-19, while providing a platform for deeper study.

CONCLUSION

Empowering healthcare responses to COVID-19 is as crucial as understanding the epidemiology of the disease. Our application will continue to evolve to meet this need.

Plant species dominance increases pollination complementarity and plant reproductive function

Worldwide, anthropogenic change is causing biodiversity loss, disrupting many critical ecosystem functions. Most studies investigating the relationship between biodiversity and ecosystem functioning focus on species richness, predominantly within the context of productivity-related functions. Consequently, there is limited understanding of how other biodiversity measures, such as species evenness (the distribution of abundance among species), affect complex multitrophic functions such as pollination. We explore the effect of species evenness on the ecosystem function of pollination using a controlled experiment with selected plants and insects in flight cages. We manipulated the relative abundances of plant and pollinator species, while holding species richness, composition, dominance order, and total abundance constant. Then, we tested how numerical species evenness affected network structure and consequently, seed production, in our artificial communities. Contrary to our expectation, numerical dominance in plant communities increased complementarity in pollinator use (reduced pollinator sharing) among plant species. As predicted by theory, this increased complementarity resulted in higher seed production for the most dominant and rare plant species in our cages. Our results show that in a controlled experimental setting, numerical species evenness can alter important aspects of plant-pollinator networks and plant reproduction, irrespective of species richness, composition, and total abundance. Extending this understanding of how species evenness affects ecosystem functioning to natural systems is crucial as anthropogenic disturbances continue to alter species' abundances, likely disrupting ecosystem functions long before extinctions occur.

A Residence Time Theory for Biodiversity

From microorganisms to the largest macroorganisms, much of Earth's biodiversity is subject to forces of physical turnover. Residence time is the ratio of an ecosystem's size to its rate of flow and provides a means for understanding the influence of physical turnover on biological systems. Despite its use across scientific disciplines, residence time has not been integrated into the broader understanding of biodiversity, life history, and the assembly of ecological communities. Here we propose a residence time theory for the growth, activity, abundance, and diversity of traits and taxa in complex ecological systems. Using thousands of stochastic individual-based models to simulate energetically constrained life-history processes, we show that our predictions are conceptually sound and mutually compatible and that they support ecological relationships that underpin much of biodiversity theory. We discuss the importance of residence time across the ecological hierarchy and propose how residence time can be integrated into theories ranging from population genetics to macroecology.

A majority of HIV persistence during antiretroviral therapy is due to infected cell proliferation

Antiretroviral therapy (ART) suppresses viral replication in people living with HIV. Yet, infected cells persist for decades on ART and viremia returns if ART is stopped. Persistence has been attributed to viral replication in an ART sanctuary and long-lived and/or proliferating latently infected cells. Using ecological methods and existing data, we infer that >99% of infected cells are members of clonal populations after one year of ART. We reconcile our results with observations from the first months of ART, demonstrating mathematically how a fossil record of historic HIV replication permits observed viral evolution even while most new infected cells arise from proliferation. Together, our results imply cellular proliferation generates a majority of infected cells during ART. Therefore, reducing proliferation could decrease the size of the HIV reservoir and help achieve a functional cure.

HIV infected cells persist for decades in patients under ART, but the mechanisms responsible remain unclear. Here, Reeves et al. use modeling approaches adapted from ecology to show that cellular proliferation, rather than viral replication, generates a majority of infected cells during ART.

Biological and statistical processes jointly drive population aggregation: using host-parasite interactions to understand Taylor's power law

The macroecological pattern known as Taylor's power law (TPL) represents the pervasive tendency of the variance in population density to increase as a power function of the mean. Despite empirical illustrations in systems ranging from viruses to vertebrates, the biological significance of this relationship continues to be debated. Here we combined collection of a unique dataset involving 11 987 amphibian hosts and 332 684 trematode parasites with experimental measurements of core epidemiological outcomes to explicitly test the contributions of hypothesized biological processes in driving aggregation. After using feasible set theory to account for mechanisms acting indirectly on aggregation and statistical constraints inherent to the data, we detected strongly consistent influences of host and parasite species identity over 7 years of sampling. Incorporation of field-based measurements of host body size, its variance and spatial heterogeneity in host density accounted for host identity effects, while experimental quantification of infection competence (and especially virulence from the 20 most common host-parasite combinations) revealed the role of species-by-environment interactions. By uniting constraint-based theory, controlled experiments and community-based field surveys, we illustrate the joint influences of biological and statistical processes on parasite aggregation and emphasize their importance for understanding population regulation and ecological stability across a range of systems, both infectious and free-living.

Will a small randomly assembled community be feasible and stable?

How likely is it that few species can randomly assemble into a feasible and stable community? Some studies have answered that as long as the community is feasible, it will nearly always be stable. In contrast, other studies have answered that the likelihood is almost null. Here, we show that the origin of this debate has been the underestimation of the association of the parameter space of intrinsic growth rates with the feasibility and stability properties of small randomly-assembled communities. In particular, we demonstrate that not all parameterizations and sampling distributions of intrinsic growth rates lead to the same probabilities of stability and feasibility, which could mistakenly lead to under- or overestimate the stability properties of feasible communities. Additionally, we find that stability imposes a filtering of species abundances "towards" more even distributions in small feasible randomly-assembled communities. This indicates that the stability of feasible communities is inherently linked to the starting distribution of species abundances, a characteristic that many times has been ignored, but should be incorporated in manageable lab and field experiments. Overall, the return to this debate is a central reminder that a more systematic exploration of the feasible parameter space is necessary to derive general conclusions about the stability properties of ecological communities.

Ecological response hides behind the species abundance distribution: Community response to low-intensity disturbance in managed grasslands

Land‐use and management are disturbance factors that have diverse effects on community composition and structure. In traditional rural grasslands, such as meadows and pastures, low‐intensity management is maintained to enhance biodiversity. Maintenance of road verges, in turn, creates habitat, which may complement traditional rural grasslands. To evaluate the effect of low‐intensity disturbance on insect communities, we characterized species abundance distributions (SAD) for Carabidae, Formicidae, and Heteroptera in three grassland types, which differed in management: meadows, pastures, and road verges. The shape of SAD was estimated with three parameters: abundance decay rate, dominance, and rarity. We compared the SAD shape among the grassland types and tested the effect of environmental heterogeneity (plant species richness) and disturbance intensity (trampling in pastures) on SADs. The shape of SADs did not differ among the grassland types but among the taxonomic groups instead. Abundance decay rate and dominance were larger for Formicidae, and rarity smaller, than for Carabidae and Heteroptera. For Carabidae and window‐trapped Heteroptera, rarity increased with increasing plant species richness. For Formicidae, dominance increased with trampling intensity in pastures. Although the SAD shape remained largely unchanged, the identity of the dominant species tended to vary within and among grassland types. Our study shows that for a given taxonomic group, the SAD shape is similar across habitat types with low‐intensity disturbances resulting from different management. This suggests that SADs respond primarily to the intensity of disturbance and thus could be best used in monitoring communities across strong disturbance and environmental gradients. Because taxonomic groups can inherently have different SADs, taxon‐specific SADs for undisturbed communities must be empirically documented before the SAD shape can be used as an indicator of environmental change. Because the identity of the dominant species changes from management type to another, the SAD shape alone is not an adequate monitoring tool.

A macroecological theory of microbial biodiversity

Microorganisms are the most abundant, diverse and functionally important organisms on Earth. Over the past decade, microbial ecologists have produced the largest ever community datasets. However, these data are rarely used to uncover law-like patterns of commonness and rarity, test theories of biodiversity, or explore unifying explanations for the structure of microbial communities. Using a global scale compilation of >20,000 samples from environmental, engineered and host-related ecosystems, we test the power of competing theories to predict distributions of microbial abundance and diversity-abundance scaling laws. We show that these patterns are best explained by the synergistic interaction of stochastic processes that are captured by lognormal dynamics. We demonstrate that lognormal dynamics have predictive power across scales of abundance, a criterion that is essential to biodiversity theory. By understanding the multiplicative and stochastic nature of ecological processes, scientists can better understand the structure and dynamics of Earth's largest and most diverse ecological systems.

When can we infer mechanism from parasite aggregation? A constraint-based approach to disease ecology

Few hosts have many parasites while many hosts have few parasites. This axiom of macroparasite aggregation is so pervasive it is considered a general law in disease ecology, with important implications for the dynamics of host-parasite systems. Because of these dynamical implications, a significant amount of work has explored both the various mechanisms leading to parasite aggregation patterns and how to infer mechanism from these patterns. However, as many disease mechanisms can produce similar aggregation patterns, it is not clear whether aggregation itself provides any additional information about mechanism. Here we apply a "constraint-based" approach developed in macroecology that allows us to explore whether parasite aggregation contains any additional information beyond what is provided by mean parasite load. We tested two constraint-based null models, both of which were constrained on the total number of parasites P and hosts H found in a sample, using data from 842 observed amphibian host-trematode parasite distributions. We found that constraint-based models captured ~85% of the observed variation in host-parasite distributions, suggesting that the constraints P and H contain much of the information about the shape of the host-parasite distribution. However, we also found that extending the constraint-based null models can identify the potential role of known aggregating mechanisms (such as host heterogeneity) and disaggregating mechanisms (such as parasite-induced host mortality) in constraining host-parasite distributions. Thus, by providing robust null models, constraint-based approaches can help guide investigations aimed at detecting biological processes that directly affect parasite aggregation above and beyond those that indirectly affect aggregation through P and H.

An extensive comparison of species-abundance distribution models

A number of different models have been proposed as descriptions of the species-abundance distribution (SAD). Most evaluations of these models use only one or two models, focus on only a single ecosystem or taxonomic group, or fail to use appropriate statistical methods. We use likelihood and AIC to compare the fit of four of the most widely used models to data on over 16,000 communities from a diverse array of taxonomic groups and ecosystems. Across all datasets combined the log-series, Poisson lognormal, and negative binomial all yield similar overall fits to the data. Therefore, when correcting for differences in the number of parameters the log-series generally provides the best fit to data. Within individual datasets some other distributions performed nearly as well as the log-series even after correcting for the number of parameters. The Zipf distribution is generally a poor characterization of the SAD.

Spatial homogeneity of benthic macrofaunal biodiversity across small spatial scales

Spatial heterogeneity of biodiversity has been extensively researched, but its spatial homogeneity is virtually unstudied. An intertidal seagrass system at Knysna (South Africa) known to display spatially homogeneous macrobenthic species density at scales ≥0.0275 m² was re-investigated at four smaller spatial grains (0.0015 m² - 0.0095 m²) via a lattice of 8 × 8 stations within a 0.2 ha area. The aim was to investigate the null hypothesis that spatial homogeneity of species density is not a fixed emergent assemblage property but breaks down at small spatial grains within given spatial extents. Although assemblage abundance was significantly heterogeneous at all spatial grains investigated, both species density and functional-group density were significantly homogeneous across those same scales; observed densities not departing from those expected on the basis of independent assortment. Spatial homogeneity is therefore an emergent assemblage property within given spatial extents at Knysna and probably at equivalent sites elsewhere. Equivalent species density in South Africa, Australia and the UK at spatial grains <0.03 m², however, is a scale-related sampling artefact, as may be temporal homogeneity of species density at Knysna over a 3 year period, but close similarity in shape of their species occupancy distributions remains unexplained.

Testing the Neutral Theory of Biodiversity with Human Microbiome Datasets

The human microbiome project (HMP) has made it possible to test important ecological theories for arguably the most important ecosystem to human health-the human microbiome. Existing limited number of studies have reported conflicting evidence in the case of the neutral theory; the present study aims to comprehensively test the neutral theory with extensive HMP datasets covering all five major body sites inhabited by the human microbiome. Utilizing 7437 datasets of bacterial community samples, we discovered that only 49 communities (less than 1%) satisfied the neutral theory, and concluded that human microbial communities are not neutral in general. The 49 positive cases, although only a tiny minority, do demonstrate the existence of neutral processes. We realize that the traditional doctrine of microbial biogeography "Everything is everywhere, but the environment selects" first proposed by Baas-Becking resolves the apparent contradiction. The first part of Baas-Becking doctrine states that microbes are not dispersal-limited and therefore are neutral prone, and the second part reiterates that the freely dispersed microbes must endure selection by the environment. Therefore, in most cases, it is the host environment that ultimately shapes the community assembly and tip the human microbiome to niche regime.

Comparing process-based and constraint-based approaches for modeling macroecological patterns

Ecological patterns arise from the interplay of many different processes, and yet the emergence of consistent phenomena across a diverse range of ecological systems suggests that many patterns may in part be determined by statistical or numerical constraints. Differentiating the extent to which patterns in a given system are determined statistically, and where it requires explicit ecological processes, has been difficult. We tackled this challenge by directly comparing models from a constraint-based theory, the Maximum Entropy Theory of Ecology (METE) and models from a process-based theory, the size-structured neutral theory (SSNT). Models from both theories were capable of characterizing the distribution of individuals among species and the distribution of body size among individuals across 76 forest communities. However, the SSNT models consistently yielded higher overall likelihood, as well as more realistic characterizations of the relationship between species abundance and average body size of conspecific individuals. This suggests that the details of the biological processes contain additional information for understanding community structure that are not fully captured by the METE constraints in these systems. Our approach provides a first step towards differentiating between process- and constraint-based models of ecological systems and a general methodology for comparing ecological models that make predictions for multiple patterns.

Environmental correlates of species rank - abundance distributions in global drylands

Theoretical models predict lognormal species abundance distributions (SADs) in stable and productive environments, with log-series SADs in less stable, dispersal driven communities. We studied patterns of relative species abundances of perennial vascular plants in global dryland communities to: i) assess the influence of climatic and soil characteristics on the observed SADs, ii) infer how environmental variability influences relative abundances, and iii) evaluate how colonisation dynamics and environmental filters shape abundance distributions. We fitted lognormal and log-series SADs to 91 sites containing at least 15 species of perennial vascular plants. The dependence of species relative abundances on soil and climate variables was assessed using general linear models. Irrespective of habitat type and latitude, the majority of the SADs (70.3%) were best described by a lognormal distribution. Lognormal SADs were associated with low annual precipitation, higher aridity, high soil carbon content, and higher variability of climate variables and soil nitrate. Our results do not corroborate models predicting the prevalence of log-series SADs in dryland communities. As lognormal SADs were particularly associated with sites with drier conditions and a higher environmental variability, we reject models linking lognormality to environmental stability and high productivity conditions. Instead our results point to the prevalence of lognormal SADs in heterogeneous environments, allowing for more evenly distributed plant communities, or in stressful ecosystems, which are generally shaped by strong habitat filters and limited colonisation. This suggests that drylands may be resilient to environmental changes because the many species with intermediate relative abundances could take over ecosystem functioning if the environment becomes suboptimal for dominant species.

Scaling laws predict global microbial diversity

Scaling laws underpin unifying theories of biodiversity and are among the most predictively powerful relationships in biology. However, scaling laws developed for plants and animals often go untested or fail to hold for microorganisms. As a result, it is unclear whether scaling laws of biodiversity will span evolutionarily distant domains of life that encompass all modes of metabolism and scales of abundance. Using a global-scale compilation of ∼35,000 sites and ∼5.6⋅10(6) species, including the largest ever inventory of high-throughput molecular data and one of the largest compilations of plant and animal community data, we show similar rates of scaling in commonness and rarity across microorganisms and macroscopic plants and animals. We document a universal dominance scaling law that holds across 30 orders of magnitude, an unprecedented expanse that predicts the abundance of dominant ocean bacteria. In combining this scaling law with the lognormal model of biodiversity, we predict that Earth is home to upward of 1 trillion (10(12)) microbial species. Microbial biodiversity seems greater than ever anticipated yet predictable from the smallest to the largest microbiome.

Commonness, rarity, and intraspecific variation in traits and performance in tropical tree seedlings

One of the few rules in ecology is that communities are composed of many rare and few common species. Trait-based investigations of abundance distributions have generally focused on species-mean trait values with mixed success. Here, using large tropical tree seedling datasets in China and Puerto Rico, we take an alternative approach that considers the magnitude of intraspecific variation in traits and growth as it relates to species abundance. We find that common species are less variable in their traits and growth. Common species also occupy core positions within community trait space indicating that they are finely tuned for the available conditions. Rare species are functionally peripheral and are likely transients struggling for success in the given environment. The work highlights the importance of considering intraspecific variation in trait-based ecology and demonstrates asymmetry in the magnitude of intraspecific variation among species is critical for understanding of how traits are related to abundance.

A strong test of the maximum entropy theory of ecology

The maximum entropy theory of ecology (METE) is a unified theory of biodiversity that predicts a large number of macroecological patterns using information on only species richness, total abundance, and total metabolic rate of the community. We evaluated four major predictions of METE simultaneously at an unprecedented scale using data from 60 globally distributed forest communities including more than 300,000 individuals and nearly 2,000 species.METE successfully captured 96% and 89% of the variation in the rank distribution of species abundance and individual size but performed poorly when characterizing the size-density relationship and intraspecific distribution of individual size. Specifically, METE predicted a negative correlation between size and species abundance, which is weak in natural communities. By evaluating multiple predictions with large quantities of data, our study not only identifies a mismatch between abundance and body size in METE but also demonstrates the importance of conducting strong tests of ecological theories.

A Process-Independent Explanation for the General Form of Taylor's Law

Taylor's law (TL) describes the scaling relationship between the mean and variance of populations as a power law. TL is widely observed in ecological systems across space and time, with exponents varying largely between 1 and 2. Many ecological explanations have been proposed for TL, but it is also commonly observed outside ecology. We propose that TL arises from the constraining influence of two primary variables: the number of individuals and the number of censuses or sites. We show that most possible configurations of individuals among censuses or sites produce the power-law form of TL, with exponents between 1 and 2. This "feasible set" approach suggests that TL is a statistical pattern driven by two constraints, providing an a priori explanation for this ubiquitous pattern. However, the exact form of any specific mean-variance relationship cannot be predicted in this way, that is, this approach does a poor job of predicting variation in the exponent, suggesting that TL may still contain ecological information.

The control of rank-abundance distributions by a competitive despotic species

Accounting for differences in abundances among species remains a high priority for community ecology. While there has been more than 80 years of work on trying to explain the characteristic S shape of rank-abundance distributions (RADs), there has been recent conjecture that the form may not depend on ecological processes per se but may be a general phenomenon arising in many unrelated disciplines. We show that the RAD shape can be influenced by an ecological process, namely, interference competition. The noisy miner (Manorina melanocephala) is a hyperaggressive, 'despotic' bird that occurs over much of eastern Australia (>10(6) km(2)). We compiled data for bird communities from 350 locations within its range, which were collected using standard avian survey methods. We used hierarchical Bayesian models to show that the RAD shape was much altered when the abundance of the strong interactor exceeded a threshold density; RADs consistently were steeper when the density of the noisy miner ≥2.5 birds ha(-1). The structure of bird communities at sites where the noisy miner exceeded this density was very different from that at sites where the densities fell below the threshold: species richness and Shannon diversity were much reduced, but mean abundances and mean avian biomass per site did not differ substantially.

Effects of land-use intensity on arthropod species abundance distributions in grasslands

As a rule, communities consist of few abundant and many rare species, which is reflected in the characteristic shape of species abundance distributions (SADs). The processes that shape these SADs have been a longstanding problem for ecological research. Although many studies found strong negative effects of increasing land-use intensity on diversity, few reports consider land-use effects on SADs. Arthropods (insects and spiders) were sampled on 142 grassland plots in three regions in Germany, which were managed with different modes (mowing, fertilization and/or grazing) and intensities of land use. We analysed the effect of land use on three parameters characterizing the shape of SADs: abundance decay rate (the steepness of the rank abundance curve, represented by the niche-preemption model parameter), dominance (Berger-Parker dominance) and rarity (Fisher's alpha). Furthermore, we tested the core-satellite hypothesis by comparing the species' rank within the SAD to their distribution over the land-use gradient. When data on Araneae, Cicadina, Coleoptera, Heteroptera and Orthoptera were combined, abundance decay rate increased with combined land-use intensity (including all modes). Among the single land-use modes, increasing fertilization and grazing intensity increased the decay rate of all taxa, while increasing mowing frequency significantly affected the decay rate only in interaction with fertilization. Results of single taxa differed in their details, but all significant interaction effects included fertilization intensity. Dominance generally increased with increasing fertilization and rarity decreased with increasing grazing or mowing intensity, despite small differences among taxa and regions. The majority of species found on <10% of the plots per region were generally rare (<10 individuals), which is in accordance with the core-satellite hypothesis. We found significant differences in the rarity and dominance of species between plots of low and high intensity for all three land-use modes and for the combined land-use intensity. We conclude that effects of land-use intensity on SADs lead to a stronger dominance of the most abundant species. Furthermore, species which have restricted distributions are more likely to also be rare species in the local SAD and therefore are at high risk of being lost under intensive land use.