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bioRxiv2016

Are foundation species effects different than those of dominant species? A case study of ant assemblages in northeastern North American forests

Foundation species uniquely control associated biodiversity through non-trophic effects, whereas dominant species are locally abundant but are replaceable in ecological systems. Long-term data on ant assemblages at the Harvard Forest Hemlock Removal Experiment (HF-HeRE) and the Black Rock Future of Oak Forests Experiment (BRF-FOFE) provide insights into how ant assemblages change and reassemble following the loss of a foundation species (Tsuga canadensis) or a dominant genus (Quercus). At HF-HeRE, removal of T. canadensis trees resulted in taxonomic and functional shifts in ant assemblages relative to control stands. In contrast, ant assemblages at BRF-FOFE varied little regardless of whether oaks or non-oaks were removed from the canopy. Non-trophic effects of foundation species were stronger than indirect trophic effects on taxonomic and functional diversity of ant assemblages. In contrast, non-trophic effects of dominant species were weaker than indirect trophic effects on ant taxonomic diversity and some measures of ant functional diversity.\n\nStatement of authorshipA.M. Ellison and S. Record conceived the study. A.M. Ellison, T. 17 McCabe, and S. Record collected field data. T. McCabe and S. Record did the taxonomic diversity analyses. B. Baiser and S. Record did the functional diversity analyses. All authors contributed to drafts of the manuscript.\n\nData accessibilityAll data (i.e., ant and trait) and R code are available from the Harvard Forest Data Archive (http://harvardforest.fas.harvard.edu/data-archive), datasets HF-118 (HF-HeRE) and HF-097 (BRF-FOFE). Nomenclature follows Bolton (2016); voucher specimens are stored at the Harvard Forest and at the Museum of Comparative Zoology.

Ecology↗
bioRxiv2016

Resource ratios determine nutrient limitation of primary productivity in the ocean

What is the ultimate limiting nutrient in the ocean? The dominant theory, which was first proposed by Redfield and later formalized by Tyrrell[1, 2], states that despite the scarcity of fixed nitrogen (N) in the surface ocean, phosphorus (P) availability ultimately determines primary productivity. Two recent findings directly challenge the assumptions of the Redfield-Tyrrell paradigm: the discovery of systematic variations of phytoplankton cellular N:P:Fe and widespread iron-limitation of phytoplankton. Here we use a simple model of nitrogen, phosphorus, and iron (Fe) cycling to show how the resource demand ratios and biogeography of phytoplankton interact with external resource supply ratios to govern nutrient cycling and primary productivity. We find that all three nutrients can limit global primary productivity, and that the ratio of geochemical supply to biological demand of each nutrient in each ocean region determines the limiting nutrients, with nitrogen N fixation providing a mechanism for the cycles to interact. These results have important consequences for our understanding of biogeochemical cycles, ocean-atmosphere interactions, marine ecology, and the response of ocean ecosystems to climate change. Our work demonstrates the importance of resource ratios and suggests that future studies of the physiological and geochemical regulation of these ratios are indispensable to building accurate theories and future predictions of nutrient cycling and primary productivity.

Ecology↗
bioRxiv2016

Dispersal: a central and independent trait in life history

The study of trade-offs among major life history components (age at maturity, lifespan and reproduction) allowed the development of a quantitative framework to understand how environmental variation shapes patterns of biodiversity among and within species.\n\nBecause every environment is inherently spatially structured, and in most cases temporally variable, individuals need to move within and among habitats to maximize fitness. Dispersal is often assumed to be tightly integrated into life histories through genetic correlations with other vital traits. This assumption is particularly strong within the context of a fast-slow continuum of life-history variation. Such a framework is to date used to explain many aspects of population and community dynamics. Evidence for a consistent and context-independent integration of dispersal in life histories is, however, weak. We therefore advocate the explicit integration of dispersal into life history theory as a principal axis of variation influencing fitness, that is free to evolve, independently of other life history traits.\n\nWe synthesize theoretical and empirical evidence on the central role of dispersal and its evolutionary dynamics on the spatial distribution of ecological strategies and its impact on population spread, invasions and coexistence. By applying an optimality framework we show that the inclusion of dispersal as an independent dimension of life histories might substantially change our view on evolutionary trajectories in spatially structured environments.\n\nBecause changes in the spatial configuration of habitats affect the costs of movement and dispersal, adaptations to reduce these costs will increase phenotypic divergence among and within populations. We outline how this phenotypic heterogeneity is anticipated to further impact population and community dynamics.

Ecology↗
bioRxiv2016

Examining the occupancy-density relationship for a low density carnivore

O_LIThe challenges associated with monitoring low-density carnivores across large landscapes have limited the ability to implement and evaluate conservation and management strategies for such species. Noninvasive sampling techniques and advanced statistical approaches have alleviated some of these challenges and can even allow for spatially explicit estimates of density, arguably the most valuable wildlife monitoring tool.\nC_LIO_LIFor some species, individual identification comes at no cost when unique attributes (e.g., pelage patterns) can be discerned with remote cameras, while other species require viable genetic material and expensive lab processing for individual assignment. Prohibitive costs may still force monitoring efforts to use species distribution or occupancy as a surrogate for density, which may not be appropriate under many conditions.\nC_LIO_LIHere, we used a large-scale monitoring study of fisher Pekania pennanti to evaluate the effectiveness of occupancy as an approximation to density, particularly for informing harvest management decisions. We used a combination of remote cameras and baited hair snares during 2013-2015 to sample across a 70,096 km2 region of western New York, USA. We fit occupancy and Royle-Nichols models to species detection-nondetection data collected by cameras, and spatial capture-recapture models to individual encounter data obtained by genotyped hair samples.\nC_LIO_LIWe found a close relationship between grid-cell estimates of fisher state variables from the models using detection-nondetection data and those from the SCR model, likely due to informative spatial covariates across a large landscape extent and a grid cell resolution that worked well with the movement ecology of the species. Spatially-explicit management recommendations for fisher were similar across models. We discuss design-based approaches to occupancy studies that can improve approximations to density.\nC_LI

Ecology↗
bioRxiv2016

Sympatry with the devil? Niche-based approach explains the mechanisms allowing 1 coexistence of native and non-native salmonids

Niche-based hypotheses have been proposed to explain processes and mechanisms of success in the establishment of non-native species into native communities. Competition due to niche overlap may lead to native species niche shift and to native species replacement. To understand the ecological consequences of trophic interactions between non-native rainbow trout and native and endangered marble trout, we used as model system the Idrijca river (Western Slovenia) in which marble trout occurs either in allopatry (MTa) or in sympatry (MTs) with rainbow trout (RTs). We focused on different metrics of niche change such as centroid shift, niche overlap and trophic niche breadth using stable isotope analysis ({delta}15N and {delta}13C). Our results showed plasticity in niche overlap between MTs and RTs and niche shift of marble trout when occurring in sympatry with RTs, but not due to a niche replacement of MTs by RTs. Niche breadth of marble trout increases in sympatry and the trophic position during the growth period was higher for MTs than MTa.

Ecology↗
bioRxiv2016

Thousands of primer-free, high-quality, full-length SSU rRNA sequences from all domains of life

Ribosomal RNA (rRNA) genes are the consensus marker for determination of microbial diversity on the planet, invaluable in studies of evolution and, for the past decade, high-throughput sequencing of variable regions of ribosomal RNA genes has become the backbone of most microbial ecology studies. However, the underlying reference databases of full-length rRNA gene sequences are underpopulated, ecosystem skewed1, and subject to primer bias2, which hamper our ability to study the true diversity of ecosystems. Here we present an approach that combines reverse transcription of full-length small subunit (SSU) rRNA genes and synthetic long read sequencing by molecular tagging, to generate primer-free, full-length SSU rRNA gene sequences from all domains of life, with a median raw error rate of 0.17%. We generated thousands of full-length SSU rRNA sequences from five well-studied ecosystems (soil, human gut, fresh water, anaerobic digestion, and activated sludge) and obtained sequences covering all domains of life and the majority of all described phyla. Interestingly, 30% of all bacterial operational taxonomic units were novel, compared to the SILVA database (less than 97% similarity). For the Eukaryotes, the novelty was even larger with 63% of all OTUs representing novel taxa. In addition, 15% of the 18S rRNA OTUs were highly novel sequences with less than 80% similarity to the databases. The generation of primer-free full-length SSU rRNA sequences enabled eco-system specific estimation of primer-bias and, especially for eukaryotes, showed a dramatic discrepancy between the in-silico evaluation and primer-free data generated in this study. The large amount of novel sequences obtained here reaffirms that there is still vast, untapped microbial diversity lacking representatives in the SSU rRNA databases and that there might be more than millions after all1, 3. With our new approach, it is possible to readily expand the rRNA databases by orders of magnitude within a short timeframe. This will, for the first time, enable a broad census of the tree of life.

Ecology↗
bioRxiv2016

An efficient extension of N-mixture models for multi-species abundance estimation

1. In this study we propose an extension of the N-mixture family of models that targets an improvement of the statistical properties of rare species abundance estimators when sample sizes are low, yet typical size for tropical studies. The proposed method harnesses information from other species in an ecological community to correct each species estimator. We provide guidance to determine the sample size required to estimate accurately the abundance of rare tropical species when attempting to estimate the abundance of single species.\n\n2. We evaluate the proposed methods using an assumption of 50-m radius plots and perform simulations comprising a broad range of sample sizes, true abundances and detectability values and a complex data generating process. The extension of the N-mixture model is achieved by assuming that the detection probabilities of a set of species are all drawn at random from a beta distribution in a multi-species fashion. This hierarchical model avoids having to specify a single detection probability parameter per species in the targeted community. Parameter estimation is done via Maximum Likelihood.\n\n3. We compared our multi-species approach with previously proposed multi-species N-mixture models, which we show are biased when the true densities of species in the community are less than seven individuals per 100-ha. The beta N-mixture model proposed here outperforms the traditional Multi-species N-mixture model by allowing the estimation of organisms at lower densities and controlling the bias in the estimation.\n\n4. We illustrate how our methodology can be used to suggest sample sizes required to estimate the abundance of organisms, when these are either rare, common or abundant. When the interest is full communities, we show how the multi-species approaches, and in particular our beta model and estimation methodology, can be used as a practical solution to estimate organism densities from rapid inventory datasets. The statistical inferences done with our model via Maximum Likelihood can also be used to group species in a community according to their detectabilities.

Ecology↗
bioRxiv2016

A Numerus Population Viability and Harvesting Analyses Web App

Population viability analysis (PVA) is used to assess the probability that a biological population will persist for a specified period of time. Such models are typically cast as Markov processes that may include age, stage, sex and metapopulation structures, density-dependence and ecological interaction processes. They may also include harvesting, stocking, and thresholds that trigger interventions. Here we present Numerus PVA, which is a web app that includes extensible user-selected options. Specifically, Numerus PVA allows for the specification of one to ten age classes, one or two sexes, single population or metapopulation configurations with 2 or 3 subpopulations, as well as density-dependent settings for inducing region-specific carrying capacities. Movement among subpopulations can be influenced by age, metapopulation connectivity, and attractivity of regions based on the relative fitness of the youngest age classes in each region. Simulations can be carried out deterministically or stochastically, with a user-specified combination of demographic and environmental processes. Numerus PVA is freely available at http://www.numerusinc.com/webapps/pva for running directly on any browser and device. Numerus PVA is easily modified by users familiar with the NovaModeler Software Platform.

Ecology↗
bioRxiv2016

Temporal probabilistic modeling of bacterial compositions derived from 16S rRNA sequencing

The number of microbial and metagenomic studies has increased drastically due to advance-ments in next-generation sequencing-based measurement techniques. Statistical analysis and the validity of conclusions drawn from (time series) 16S rRNA and other metagenomic sequencing data is hampered by the presence of significant amount of noise and missing data (sampling zeros). Accounting uncertainty in microbiome data is often challenging due to the difficulty of obtaining biological replicates. Additionally, the compositional nature of current amplicon and metagenomic data differs from many other biological data types adding another challenge to the data analysis.\n\nTo address these challenges in human microbiome research, we introduce a novel probabilistic approach to explicitly model overdispersion and sampling zeros by considering the temporal correlation between nearby time points using Gaussian Processes. The proposed Temporal Gaussian Process Model for Compositional Data Analysis (TGP-CODA) shows superior modeling performance compared to commonly used Dirichlet-multinomial, multinomial, and non-parametric regression models on real and synthetic data. We demonstrate that the nonreplicative nature of human gut microbiota studies can be partially overcome by our method with proper experimental design of dense temporal sampling. We also show that different modeling ap-proaches have a strong impact on ecological interpretation of the data, such as stationarity, persistence, and environmental noise models.\n\nA Stan implementation of the proposed method is available under MIT license at https://github.com/tare/GPMicrobiome.

Ecology↗
bioRxiv2016

Exact probabilities for the indeterminacy of complex networks as perceived through press perturbations

We consider the goal of predicting how complex networks respond to chronic (press) perturbations when characterizations of their network topology and interaction strengths are associated with uncertainty. Our primary result is the derivation of exact formulas for the expected number and probability of qualitatively incorrect predictions about a systems responses under uncertainties drawn form arbitrary distributions of error. These formulas obviate the current use of simulations, algorithms, and qualitative modeling techniques. Additional indices provide new tools for identifying which links in a network are most qualitatively and quantitatively sensitive to error, and for determining the volume of errors within which predictions will remain qualitatively determinate (i.e. sign insensitive). Together with recent advances in the empirical characterization of uncertainty in ecological networks, these tools bridge a way towards probabilistic predictions of network dynamics.

ecology↗
bioRxiv2016

Trajectories: how functional traits influence plant growth and shade tolerance across the life-cycle

Plant species differ in many functional traits that drive differences in rates of photosynthesis, biomass allocation, and tissue turnover. Yet, it remains unclear how - and even if - such traits influence whole-plant growth, with the simple linear relationships predicted by existing theory often lacking empirical support. Here we present a new theoretical framework for understanding the effect of diverse functional traits on plant growth and shade-tolerance, extending a widely-used theoretical model that links growth rate in seedlings with a single leaf trait to explicitly include influences of size, light environment, and five other prominent traits: seed mass, height at maturation, leaf mass per unit leaf area, leaf nitrogen per unit leaf area, and wood density. Based on biomass production and allocation, this framework explains why the influence of prominent traits on growth rate and shade tolerance often varies with plant size and why the impact of size on growth varies among traits. Considering growth rate in height, we find the influence of: i) leaf mass per unit leaf area is strong in small plants but weakens with size, ii) leaf nitrogen per unit leaf area does not change with size, iii) wood density is present across sizes but is strongest at intermediate sizes, iv) height at maturation strengthens with size, and v) seed mass decreases with size. Moreover, we show how traits moderate plant responses to light environment and also determine shade tolerance, supporting diverse empirical results. By disentangling the effects of plant size, light environment and traits on growth rates, our results provide a solid theoretical foundation for trait ecology and thus provide a platform for understanding growth across diverse species around the world.

ecology↗
bioRxiv2016

Identifying Migrant Origins Using Genetics, Isotopes, and Habitat Suitability

O_LIIdentifying migratory connections across the annual cycle is important for studies of migrant ecology, evolution, and conservation. While recent studies have demonstrated the utility of high-resolution SNP-based genetic markers for identifying population-specific migratory patterns, the accuracy of this approach relative to other intrinsic tagging techniques has not yet been assessed.\nC_LIO_LIHere, using a straightforward application of Bayes' Rule, we develop a method for combining inferences from high-resolution genetic markers, stable isotopes, and habitat suitability models, to spatially infer the breeding origin of migrants captured anywhere along their migratory pathway. Using leave-one-out cross validation, we compare the accuracy of this combined approach with the accuracy attained using each source of data independently.\nC_LIO_LIOur results indicate that when each method is considered in isolation, the accuracy of genetic assignments far exceeded that of assignments based on stable isotopes or habitat suitability models. However, our joint assignment method consistently resulted in small, but informative increases in accuracy and did help to correct misassignments based on genetic data alone. We demonstrate the utility of the combined method by identifying previously undetectable patterns in the timing of migration in a North American migratory songbird, the Wilson's warbler.\nC_LIO_LIOverall, our results support the idea that while genetic data provides the most accurate method for tracking animals using intrinsic markers when each method is considered independently, there is value in combining all three methods. The resulting methods are provided as part of a new computationally-efficient R-package, GIAIH, allowing broad application of our statistical framework to other migratory animal systems.\nC_LI

ecology↗
bioRxiv2016

Regime shifts, alternative states and hysteresis in the Sarracenia microecosystem

Changes in environmental conditions can lead to rapid shifts in the state of an ecosystem (\"regime shifts\"), which, even after the environment has returned to previous conditions, subsequently recovers slowly to the previous state (\"hysteresis\"). Large spatial and temporal scales of dynamics, and the lack of frameworks linking observations to models, are challenges to understanding and predicting ecosystem responses to perturbations. The naturally-occurring microecosystem inside leaves of the northern pitcher plant (Sarracenia purpurea) exhibits oligotrophic and eutrophic states that can be induced by adding insect prey. Here, we further develop a model for simulating these dynamics, parameterize it using data from a prey addition experiment and conduct a sensitivity analysis to identify critical zones within the parameter space. Simulations illustrate that the microecosystem model displays regime shifts and hysteresis. Parallel results were observed in the plant itself after experimental enrichment with prey. Decomposition rate of prey was the main driver of system dynamics, including the time the system remains in an anoxic state and the rate of return to an oxygenated state. Biological oxygen demand in fluenced the shape of the systems return trajectory. The combination of simulated results, sensitivity analysis and use of empirical results to parameterize the model more precisely demonstrates that the Sarracenia microecosystem model displays behaviors qualitatively similar to models of larger ecological systems.

ecology↗
bioRxiv2016

Adaptive anonymity: Crypsis as an evolutionary trait of floral yeasts?

Nectar-dwelling yeast and bacteria are common inhabitants of flowers and evidently involved in pollination. The limited number of floral plant-pollinator models studied to date reveal inconsistent conclusions on microbial effects, but coincide with respect to high microbial specificity: while bacteria reduce visitation frequencies of pollinators, nectar-borne specialist yeasts (in contrast to allochthonous or transient species) impose none or even a beneficial effect on flower visitation. However, these findings are in conflict with the strong impact of these predominantly fermenting organisms on the nectar environment. In order to cope with the ultimate dependency of nectar-dwellers on repeated transportation by foragers as a result of early floral senescence, the modifications of nectar associated with specialist growth have been interpreted as adaptations that suit foragers preferences. But, the development of foraging preferences to either axenic flowers or flowers colonized by specialist microorganisms would lead to a dead-end for nectar-dwellers, as the probability of inoculation into new suitable habitats would be reduced.\n\nBased on a critical survey of the available literature and an additional pollinator experiment where we find that the allochthonous species Cryptococcus victoriae negatively affects attraction and rewarding of floral visitors, while the specialist yeast Metschnikowia reukaufii does not, we propose the hypothesis that nectar-borne yeasts may have evolved to blend into their environment avoiding detection by pollinators, following the ecological concept of crypsis. Although, neither chemical nor olfactory crypsis has been reported for nectar-borne microorganisms, the attention to this mechanism in yeast dispersal needs to be directed in future studies.

ecology↗
bioRxiv2016

Biodiversity of Tropical Forests

The quantification of tropical tree biodiversity worldwide remains an open and challenging problem. In fact, more than two-fifths of the global tree population can be found either in tropical or sub-tropical forests1, but species identities are known only for {approx} 0.000067% of the individuals in all tropical forests2. For practical reasons, biodiversity is typically measured or monitored at fine spatial scales. However, important drivers of ecological change tend to act at large scales. Conservation issues, for example, apply to diversity at global, national or regional scales. Extrapolating species richness from the local to the global scale is not straightforward. Indeed, a vast number of different biodiversity estimators have been developed under different statistical sampling frameworks3-7, but most of them have been designed for local/regional-scale extrapolations, and they tend to be sensitive to the spatial distribution of trees8, sample coverage and sampling methods9. Here, we introduce an analytical framework that provides robust and accurate estimates of species richness and abundances in biodiversity-rich ecosystems, as confirmed by tests performed on various in silico-generated forests. The new framework quantifies the minimum percentage cover that should be sampled to achieve a given average confidence in the upscaled estimate of biodiversity. Our analysis of 15 empirical forest plots shows that previous methods10,11 have systematically overestimated the total number of species and leads to new estimates of hyper-rarity10 at the global scale11, known as Fishers paradox2. We show that hyper-rarity is a signature of critical-like behavior12 in tropical forests13-15, and it provides a buffer against mass extinctions16. When biotic factors or environmental conditions change, some of these rare species are more able than others to maintain the ecosystems functions, thus underscoring the importance of rare species.

ecology↗
bioRxiv2016

Floral Radiometry: A Biophysical Basis to Characterize Landscapes.

This paper presents early results on studies of floral spectral reflectance of angiosperms and introduces floral radiometry as an emergent dimension of ecological research in India. Floral spectral reflectance of 121 angiosperm species was measured using hand-held spectroradiometer. The authors describe spectral reflectance of seven representative species within 350-800 nanometer region of the electromagnetic spectrum. Characteristic absorption and reflection of flowers, in ultraviolet and visible regions of the spectrum is reported. Near infrared reflectance was consistently high for all species studied. Flower color is unique to a species and importance of understanding flower color from pollinators perspective is highlighted.

ecology↗
bioRxiv2016

Ubiquity and quantitative significance of bacterioplankton lineages inhabiting the oxygenated hypolimnion of deep freshwater lakes

Freshwater bacterioplankton in the oxygenated hypolimnion are reportedly dominated by specific members that are distinct from those in the epilimnion. However, no consensus exists regarding the ubiquity and abundance of these bacterioplankton, which is necessary to evaluate their ecological importance. The present study investigated the bacterioplankton community in the oxygenated hypolimnia of 10 deep freshwater lakes. Despite the broad geochemical characteristics of the lakes, 16S rRNA gene sequencing demonstrated that many predominant lineages in the hypolimnion were shared by several lakes and consisted of members occurring in the entire water layer and members specific to the hypolimnion. Catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH) revealed that representative hypolimnion-specific lineages, CL500-11 (Chloroflexi), CL500-3, CL500-37, CL500-15 (Planctomycetes), and the MGI group (Thaumarchaeota), together accounted for 1.5-32.9% of all bacterioplankton in the hypolimnion of the lakes. Furthermore, an analysis of micro-diversification based on single-nucleotide variation in the partial 16S rRNA gene sequence (oligotyping) suggested the presence of hypolimnion-specific ecotypes among the lineages occurring in the entire water layer (e.g., acI and Limnohabitans). Collectively, these results demonstrate the uniqueness, ubiquity, and quantitative significance of bacterioplankton in the oxygenated hypolimnion, motivating future studies to focus on their eco-physiological characteristics.

ecology↗
bioRxiv2016

Direct and context-dependent effects of light, temperature, and phytoplankton shape bacterial community composition

Species interactions, environmental conditions, and stochastic processes work in concert to bring about changes in community structure. However, the relative importance of specific factors and how their combined influence affects community composition remain largely unclear. We conducted a multi-factorial experiment to 1) disentangle the direct and interaction-mediated effects of environmental conditions and 2) augment our understanding of how environmental context modulates species interactions. We focus on a planktonic system where interactions with phytoplankton effect changes in the composition of bacterial communities, and light and temperature conditions can influence bacteria directly as well as through their interactions with phytoplankton. Epilimnetic bacteria from two humic lakes were combined with phytoplankton assemblages from each lake (\"home\" or \"away\") or a no-phytoplankton control and incubated for 5 days under all combinations of light (surface, [~]25% surface irradiance) and temperature (5 levels from 10{degrees}C to 25{degrees}C). Observed light effects were primarily direct while phytoplankton and temperature effects on bacterial community composition were highly interdependent. The influence of temperature on aquatic bacteria was consistently mediated by phytoplankton and most pronounced for bacteria incubated with \"away\" phytoplankton treatments, likely due to the availability of novel phytoplankton-derived resources. The effects of phytoplankton on bacterial community composition were generally increased at higher temperatures. Incorporating mechanisms underlying the observed interdependent effects of species interactions and environmental conditions into modeling frameworks may improve our ability to forecast ecological responses to environmental change.

ecology↗