Biotic interactions influence the projected distribution of a specialist mammal under climate change

Aim

To measure the effects of including biotic interactions on climate‐based species distribution models (SDMs) used to predict distribution shifts under climate change. We evaluated the performance of distribution models for an endangered marsupial, the northern bettong (Bettongia tropica), comparing models that used only climate variables with models that also took into account biotic interactions.

Location

North‐east Queensland, Australia.

Methods

We developed separate climate‐based distribution models for the northern bettong, its two main resources and a competitor species. We then constructed models for the northern bettong by including climate suitability estimates for the resources and competitor as additional predictor variables to make climate + resource and climate + resource + competition models. We projected these models onto seven future climate scenarios and compared predictions of northern bettong distribution made by these differently structured models, using a ‘global’ metric, the I similarity statistic, to measure overlap in distribution and a ‘local’ metric to identify where predictions differed significantly.

Results

Inclusion of food resource biotic interactions improved model performance. Over moderate climate changes, up to 3.0 °C of warming, the climate‐only model for the northern bettong gave similar predictions of distribution to the more complex models including interactions, with differences only at the margins of predicted distributions. For climate changes beyond 3.0 °C, model predictions diverged significantly. The interactive model predicted less contraction of distribution than the simpler climate‐only model.

Main conclusions

Distribution models that account for interactions with other species, in particular direct resources, improve model predictions in the present‐day climate. For larger climate changes, shifts in distribution of interacting species cause predictions of interactive models to diverge from climate‐only models. Incorporating interactions with other species in SDMs may be needed for long‐term prediction of changes in distribution of species under climate change, particularly for specialized species strongly dependent on a small number of biotic interactions.     

Incorporating functional inter-relationships into protein function prediction algorithms

Background  

Functional classification schemes (e.g. the Gene Ontology) that serve as the basis for annotation efforts in several organisms are often the source of gold standard information for computational efforts at supervised protein function prediction. While successful function prediction algorithms have been developed, few previous efforts have utilized more than the protein-to-functional class label information provided by such knowledge bases. For instance, the Gene Ontology not only captures protein annotations to a set of functional classes, but it also arranges these classes in a DAG-based hierarchy that captures rich inter-relationships between different classes. These inter-relationships present both opportunities, such as the potential for additional training examples for small classes from larger related classes, and challenges, such as a harder to learn distinction between similar GO terms, for standard classification-based approaches.     

A Many-Body Field Theory Approach to Stochastic Models in Population Biology

Background

Many models used in theoretical ecology, or mathematical epidemiology are stochastic, and may also be spatially-explicit. Techniques from quantum field theory have been used before in reaction-diffusion systems, principally to investigate their critical behavior. Here we argue that they make many calculations easier and are a possible starting point for new approximations.

Methodology

We review the many-body field formalism for Markov processes and illustrate how to apply it to a ‘Brownian bug’ population model, and to an epidemic model. We show how the master equation and the moment hierarchy can both be written in particularly compact forms. The introduction of functional methods allows the systematic computation of the effective action, which gives the dynamics of mean quantities. We obtain the 1-loop approximation to the effective action for general (space-) translation invariant systems, and thus approximations to the non-equilibrium dynamics of the mean fields.

Conclusions

The master equations for spatial stochastic systems normally take a neater form in the many-body field formalism. One can write down the dynamics for generating functional of physically-relevant moments, equivalent to the whole moment hierarchy. The 1-loop dynamics of the mean fields are the same as those of a particular moment-closure.     

Molecular evolution of bovine Toll-like receptor 2 suggests substitutions of functional relevance

Background  

There is accumulating evidence that polymorphism in Toll-like receptor (TLR) genes might be associated with disease resistance or susceptibility traits in livestock. Polymorphic sites affecting TLR function should exhibit signatures of positive selection, identified as a high ratio of non-synonymous to synonymous nucleotide substitutions (ω). Phylogeny based models of codon substitution based on estimates of ω for each amino acid position can therefore offer a valuable tool to predict sites of functional relevance. We have used this approach to identify such polymorphic sites within the bovine TLR2 genes from ten Bos indicus and Bos taurus cattle breeds. By analysing TLR2 gene phylogeny in a set of mammalian species and a subset of ruminant species we have estimated the selective pressure on individual sites and domains and identified polymorphisms at sites of putative functional importance.     

A molecular diffusion based utility model for Drosophila larval phototaxis

Background  

Generally, utility based decision making models focus on experimental outcomes. In this paper we propose a utility model based on molecular diffusion to simulate the choice behavior of Drosophila larvae exposed to different light conditions.     

CTCF binding site classes exhibit distinct evolutionary, genomic, epigenomic and transcriptomic features

Background  

CTCF (CCCTC-binding factor) is an evolutionarily conserved zinc finger protein involved in diverse functions ranging from negative regulation of MYC, to chromatin insulation of the beta-globin gene cluster, to imprinting of the Igf2 locus. The 11 zinc fingers of CTCF are known to differentially contribute to the CTCF-DNA interaction at different binding sites. It is possible that the differences in CTCF-DNA conformation at different binding sites underlie CTCF's functional diversity. If so, the CTCF binding sites may belong to distinct classes, each compatible with a specific functional role.     

Human appropriation of net primary production as driver of change in landscape-scale vertebrate richness

Aim

Land use is the most pervasive driver of biodiversity loss. Predicting its impact on species richness (SR) is often based on indicators of habitat loss. However, the degradation of habitats, especially through land-use intensification, also affects species. Here, we evaluate whether an integrative metric of land-use intensity, the human appropriation of net primary production, is correlated with the decline of SR in used landscapes across the globe.

Location

Global.

Time period

Present.

Major taxa studied

Birds, mammals and amphibians.

Methods

Based on species range maps (spatial resolution: 20 km × 20 km) and an area-of-habitat approach, we calibrated a “species–energy model” by correlating the SR of three groups of vertebrates with net primary production and biogeographical covariables in “wilderness” areas (i.e., those where available energy is assumed to be still at pristine levels). We used this model to project the difference between pristine SR and the SR corresponding to the energy remaining in used landscapes (i.e., SR loss expected owing to human energy extraction outside wilderness areas). We validated the projected species loss by comparison with the realized and impending loss reconstructed from habitat conversion and documented by national Red Lists.

Results

Species–energy models largely explained landscape-scale variation of mapped SR in wilderness areas (adjusted R²-values: 0.79–0.93). Model-based projections of SR loss were lower, on average, than reconstructed and documented ones, but the spatial patterns were correlated significantly, with stronger correlation in mammals (Pearson's r = 0.68) than in amphibians (r = 0.60) and birds (r = 0.57).

Main conclusions

Our results suggest that the human appropriation of net primary production is a useful indicator of heterotrophic species loss in used landscapes, hence we recommend its inclusion in models based on species–area relationships to improve predictions of land-use-driven biodiversity loss.     

Data-Based Analysis of Winner-Loser Models of Hierarchy Formation in Animals

We review winner-loser models, the currently popular explanation for the occurrence of linear dominance hierarchies, via a three-part approach. (1) We isolate the two most significant components of the mathematical formulation of three of the most widely-cited models and rigorously evaluate the components’ predictions against data collected on hierarchy formation in groups of hens. (2) We evaluate the experimental support in the literature for the basic assumptions contained in winner-loser models. (3) We apply new techniques to the hen data to uncover several behavioral dynamics of hierarchy formation not previously described. The mathematical formulations of these models do not show satisfactory agreement with the hen data, and key model assumptions have either little or no conclusive support from experimental findings in the literature. In agreement with the latest experimental results concerning social cognition, the new behavioral dynamics of hierarchy formation discovered in the hen data suggest that members of groups are intensely aware both of their own interactions as well as interactions occurring among other members of their group. We suggest that more adequate models of hierarchy formation should be based upon behavioral dynamics that reflect more sophisticated levels of social cognition.     

Network analysis of metabolic enzyme evolution in <Emphasis Type="Italic">Escherichia coli</Emphasis>

Background  

The two most common models for the evolution of metabolism are the patchwork evolution model, where enzymes are thought to diverge from broad to narrow substrate specificity, and the retrograde evolution model, according to which enzymes evolve in response to substrate depletion. Analysis of the distribution of homologous enzyme pairs in the metabolic network can shed light on the respective importance of the two models. We here investigate the evolution of the metabolism in E. coli viewed as a single network using EcoCyc.     

Do Food Web Models Reproduce the Structure of Mutualistic Networks?

Background

Simple models inspired by processes shaping consumer-resource interactions have helped to establish the primary processes underlying the organization of food webs, networks of trophic interactions among species. Because other ecological interactions such as mutualisms between plants and their pollinators and seed dispersers are inherently based in consumer-resource relationships we hypothesize that processes shaping food webs should organize mutualistic relationships as well.

Methodology/Principal Findings

We used a likelihood-based model selection approach to compare the performance of food web models and that of a model designed for mutualisms, in reproducing the structure of networks depicting mutualistic relationships. Our results show that these food web models are able to reproduce the structure of most of the mutualistic networks and even the simplest among the food web models, the cascade model, often reproduce overall structural properties of real mutualistic networks.

Conclusions/Significance

Based on our results we hypothesize that processes leading to feeding hierarchy, which is a characteristic shared by all food web models, might be a fundamental aspect in the assembly of mutualisms. These findings suggest that similar underlying ecological processes might be important in organizing different types of interactions.     

Phenotyping of Campylobacter jejuni and Campylobacter coli by a quantitative antibiogram [MIC] typing scheme using Euclidean distances [QATED]

Background  

Enteropathogenic Campylobacter jejuni and C. coli are presently the most common cause of acute bacterial gastroenteritis in the developed world. An understanding of sources and means of transmission of Campylobacter is an essential factor in order to reduce the incidence of Campylobacter-related gastroenteritis in man. Consequently a reproducible, sensitive and well-standardised typing scheme is critical in the successful discrimination of strains and in the subsequent investigations of outbreaks. For this purpose, a phenotypic typing scheme based on quantitative antibiogram determination based on Euclidean distance (QATED), was developed.     

Pleistocene climatic fluctuations drive isolation and secondary contact in the red diamond rattlesnake (Crotalus ruber) in Baja California

Aim

Many studies have investigated the phylogeographic history of species on the Baja California Peninsula, and they often show one or more genetic breaks that are spatially concordant among many taxa. These phylogeographic breaks are commonly attributed to vicariance as a result of geological or climatic changes, followed by secondary contact when barriers are no longer present. We use restriction‐site associated DNA sequence data and a phylogeographic model selection approach to explicitly test the secondary contact hypothesis in the red diamond rattlesnake, Crotalus ruber.

Location

Baja California and Southern California.

Methods

We used phylogenetic and population clustering approaches to identify population structure. We then used coalescent methods to simultaneously estimate population parameters and test the fit of phylogeographic models to the data. We used ecological niche models to infer suitable habitat for C. ruber at the Last Glacial Maximum (LGM).

Results

Crotalus ruber is composed of distinct northern and southern populations with a boundary near the town of Loreto in Baja California Sur. A model of isolation followed by secondary contact provides the best fit to the data, with both divergence and contact occurring in the Pleistocene. We also identify a genomic signature of northern range expansion in the northern population, consistent with LGM niche models showing that the northern‐most portion of the range of C. ruber was not suitable habitat during the LGM.

Main conclusions

We provide the first explicitly model‐based test of the secondary contact model in Baja California and show that populations of C. ruber were isolated before coming back into contact near Loreto, a region that shows phylogeographic breaks for other taxa. Given the timing of divergence and contact, we suggest that climatic fluctuations have driven the observed phylogeographic structure observed in C. ruber and that they may have driven similar patterns in other taxa.     

Construction of a multiple fluorescence labelling system for use in co-invasion studies of Listeria monocytogenes

Background  

Existing virulence models are often difficult to apply for quantitative comparison of invasion potentials of Listeria monocytogenes. Well-to-well variation between cell-line based in vitro assays is practically unavoidable, and variation between individual animals is the cause of large deviations in the observed capacity for infection when animal models are used.     

Comparing functional annotation analyses with Catmap

Background  

Ranked gene lists from microarray experiments are usually analysed by assigning significance to predefined gene categories, e.g., based on functional annotations. Tools performing such analyses are often restricted to a category score based on a cutoff in the ranked list and a significance calculation based on random gene permutations as null hypothesis.     

The complexity of anatomical systems

Background  

The conception of anatomical entities as a hierarchy of infinitely graduated forms and the increase in the number of observed anatomical sub-entities and structural variables has generated a growing complexity, thus highlighting new properties of organised biological matter.     

An ant colony optimisation algorithm for the 2D and 3D hydrophobic polar protein folding problem

Background  

The protein folding problem is a fundamental problems in computational molecular biology and biochemical physics. Various optimisation methods have been applied to formulations of the ab-initio folding problem that are based on reduced models of protein structure, including Monte Carlo methods, Evolutionary Algorithms, Tabu Search and hybrid approaches. In our work, we have introduced an ant colony optimisation (ACO) algorithm to address the non-deterministic polynomial-time hard (NP-hard) combinatorial problem of predicting a protein's conformation from its amino acid sequence under a widely studied, conceptually simple model – the 2-dimensional (2D) and 3-dimensional (3D) hydrophobic-polar (HP) model.     

miSolRNA: A tomato micro RNA relational database

Background  

The economic importance of Solanaceae plant species is well documented and tomato has become a model for functional genomics studies. In plants, important processes are regulated by microRNAs (miRNA).