How can maladaptive habitat choice generate source‐sink population dynamics?

Several theoretical models have been proposed to describe population dynamics in a spatially heterogeneous environment. The source-sink model is among the most popular. Diffendorfer recently summarized its assumptions and predictions. Given the model reviewed, he argued that source-sink population dynamics arises if dispersal is somehow constrained. I offer an additional mechanism by suggesting that source-sink population dynamics can be generated by anthropogenic changes in landscapes that occur so quickly that organisms no longer make optimal habitat selection decisions. Individuals select the same habitats as their ancestors but these decisions no longer provide high fitness because of human-induced changes in habitat quality, such as increased rates of predation and/or parasitism. Provided that some of the habitats selected are turned by human-induced changes into sink habitats, source-sink population dynamics can emerge.     

How well can the accuracy of comparative protein structure models be predicted?

Comparative structure models are available for two orders of magnitude more protein sequences than are experimentally determined structures. These models, however, suffer from two limitations that experimentally determined structures do not: They frequently contain significant errors, and their accuracy cannot be readily assessed. We have addressed the latter limitation by developing a protocol optimized specifically for predicting the Calpha root-mean-squared deviation (RMSD) and native overlap (NO3.5A) errors of a model in the absence of its native structure. In contrast to most traditional assessment scores that merely predict one model is more accurate than others, this approach quantifies the error in an absolute sense, thus helping to determine whether or not the model is suitable for intended applications. The assessment relies on a model-specific scoring function constructed by a support vector machine. This regression optimizes the weights of up to nine features, including various sequence similarity measures and statistical potentials, extracted from a tailored training set of models unique to the model being assessed: If possible, we use similarly sized models with the same fold; otherwise, we use similarly sized models with the same secondary structure composition. This protocol predicts the RMSD and NO3.5A errors for a diverse set of 580,317 comparative models of 6174 sequences with correlation coefficients (r) of 0.84 and 0.86, respectively, to the actual errors. This scoring function achieves the best correlation compared to 13 other tested assessment criteria that achieved correlations ranging from 0.35 to 0.71.     

How well do reduced models capture the dynamics in models of interacting neurons?

This paper introduces a class of stochastic models of interacting neurons with emergent dynamics similar to those seen in local cortical populations. Rigorous results on existence and uniqueness of nonequilibrium steady states are proved. These network models are then compared to very simple reduced models driven by the same mean excitatory and inhibitory currents. Discrepancies in firing rates between network and reduced models are investigated and explained by correlations in spiking, or partial synchronization, working in concert with “nonlinearities” in the time evolution of membrane potentials. The use of simple random walks and their first passage times to simulate fluctuations in neuronal membrane potentials and interspike times is also considered.

     

Adaptive movement and food-chain dynamics: towards food-web theory without birth–death processes

Population density can be affected by its prey [resource] and predator [consumer] abundances through two different mechanisms: the alternation of birth [or somatic growth] or death rate and inter-habitat movement. While the food-web theory has traditionally been built on the former mechanism, the latter mechanism has formed the basis of a successful theory explaining the spatial distribution of organisms in the context of behavioral and evolutionary ecology. Yet, few studies have compared these two mechanisms, leaving the question of how similar (or different) predictions derived from birth–death-based and movement-based food-web theories unanswered. Here, theoretical models of the tri-trophic (resource–consumer-top predator) food chain were used to compare food-web patterns arising from these two mechanisms. Specifically, we evaluated the response of the food-chain structure to inter-patch differences in productivity for movement-based models and birth–death-based models. Model analysis reveals that adaptive movements give rise to positively correlated responses of all trophic levels to increased productivity; however, this pattern was not observed in the corresponding birth–death-based model. The movement-based model predicts that the food chain response to productivity is determined by the sensitivity of animal movement to the environmental conditions. More specifically, increasing sensitivity of a consumer or top predator leads to smaller inter-patch variance of the resource or consumer density, while increasing inter-patch variance in the consumer or resource density. In conclusion, adaptive movement provides an alternative mechanism correlating the food-web structure to environmental conditions.     

How population loss through habitat boundaries determines the dynamics of a predator–prey system

The increased persistence of predator–prey systems when interactions are distributed through the space has been acknowledged by both empirical and theoretical studies. One salient feature of predator–prey interactions in heterogeneous space, for example, is the existence of cycles with reduced amplitude when compared with a homogeneous landscape. Although the role of spatial interactions in shaping the dynamics of predator–prey systems has been extensively studied, still very few works have focused on the effects of habitat loss and fragmentation on these systems. In this work, we study the population dynamics of a predator–prey system in a single finite habitat with flux at the boundaries. Species movement and growth are described through a reaction–diffusion model with Rosenzweig–MacArthur type local interactions. Conforming with the existing literature, we find that the reduction of habitat size, or increasing of species movement rates equivalently, has the potential to decrease the amplitude of oscillations and even bring the system to a steady coexistence equilibrium above a threshold. We observe, however, situations in which this trend is reversed. This occurs when species movement rates and response at patch boundaries interact to induce non-trivial patterns of species distributions. These distributions are characterized by anti-correlation between predator and prey, creating then spatial refugia for prey. Our results highlight the role of population loss through habitat boundaries in determining the dynamics of predator–prey interactions.     

Plague dynamics and population genetics of the desert locust: can turnover during recession maintain population genetic structure?

The desert locust (Schistocerca gregaria) undergoes crowding-induced phase transformation from solitary form to gregarious form. The transformations involves changes in behaviour, colour, development, morphometry, fecundity and endocrine physiology. Recession populations of the desert locust exist primarily in the solitary phase as small populations in patchy environments and are prone to extinction because of climatic events. Significant genetic differentiation among recession populations along the Red Sea coast of Eritrea was previously reported. It was hypothesized that despite the mixing effect of recurrent swarms, metapopulation dynamics could have produced genetic divergence among these highly scattered recession populations. A Monte Carlo simulation of the population dynamics of the desert locust in a metapopulation setting, with a realistic range of parameter values clearly demonstrated that this is possible. Population growth was represented by a discrete-time logistic equation. The duration of recessions and swarms was sampled from normal distributions whose means and standard deviations were varied based on reported estimates. An average recession duration of 10 +/- 3 generations and swarm periods half as long but almost twice as variable produced a partitioning of the total genetic variance most similar to that in the empirical study. In conventional metapopulation analysis, whether turnover leads to increased or reduced divergence is dependent on the number of colonists relative to the number of recurrent migrants, and on whether the colonists arise from a single patch or many patches. In the case of locusts, the stochastic boom and bust cycle is the overriding factor. Divergence between patches during recession due to founder effect and recurrent drift is balanced by the high rate of mixing during plagues.     

A birth–death model of ageing: from individual-based dynamics to evolutive differential inclusions

Journal of Mathematical Biology - Ageing’s sensitivity to natural selection has long been discussed because of its apparent negative effect on an individual’s fitness. Thanks to the...     

How well can common brushtail possums regulate their intake of Eucalyptus toxins?

We studied factors affecting the ability of common brushtail possums (Trichosurus vulpecula) to regulate their intake of a dietary toxin, jensenone, extracted from Eucalyptus leaves. Increasing concentrations of jensenone in the diet led to a dose-dependent decrease in food intake best described as an exponential decay. Animals that had not previously been exposed to jensenone ate significantly more when first offered food containing the compound than on subsequent days. However, when offered the same amount of food in a number of portions throughout the night, naive animals ate significantly less than animals offered the total meal at once. When offered food containing jensenone over a 13-day period, the animals' intake varied cyclically with relatively high food intakes followed by relatively low intakes. Furthermore, animals that were exposed to cold conditions (4 degrees C) ate more than those maintained at 18 degrees C but this difference was abolished when jensenone was included in the diet. We interpret these results as showing that regulation of toxin intake by common brushtail possums depends on learned responses that can override other important influences on feeding.     

How well can relative specialistRhagoletis flies learn to discriminate fruit for oviposition?

We show that blueberry maggot females [Rhagoletis mendax(Curran)], apple maggot females [Rhagoletis pomonella(Walsh)], and walnut husk fly females [Rhagoletis suavis(Loew)], all relative specialists in range of fruit species attacked in nature, are able to learn to discriminate between types of fruit in which they oviposit. It appears, however, that these relative specialists express less capacity to learn fruit characters than relative generalist tephritids. This difference in expression of learning ability may be associated in part with differences in assignments species are asked to learn. Apparent differences in learning capability between relative specialist and relative generalist tephritids may therefore depend as much upon differences in the physical and chemical nature of host fruit as upon species differences in the adaptive value of learning.     

How well can spring-mass-like telescoping leg models fit multi-pedal sagittal-plane locomotion data?

Idealized mathematical models of animals, with point-mass bodies and spring-like legs, have been used by researchers to study various aspects of terrestrial legged locomotion. Here, we fit a bipedal spring-mass model to the ground reaction forces of human running, a horse trotting, and a cockroach running. We find that, in all three cases, while the model captures center-of-mass motions and vertical force variations well, horizontal forces are less well reproduced, primarily due to variations in net force vector directions that the model cannot accommodate. The fits result in different apparent leg stiffnesses in the three animals. Assuming a simple fixed leg-angle touch-down strategy, we find that the gaits of these models are stable in different speed-step length regimes that overlap with those used by humans and horses, but not with that used by cockroaches.     

How can the functional reponse best be determined?

Summary We evaluated three methods for the analysis of functional response data by asking whether a given method could discriminate among functional responses and whether it could accurately identify regions of positive density-dependent predation. We evaluated comparative curve fitting with foraging models, linear least-squares analysis using the angular transformation, and logit analysis. Using data from nature and simulations, we found that the analyses of predation rates with the angular transformation and logit analysis were best at consistently determining the true functional response, i.e. the model used to generate simulated data. These methods also produced the most accurate estimates of the true regions of density dependence. Of these two methods, functional response data best fulfill the assumptions of logit analysis. Angularly transformed predation rates only approximate the assumptions of linear leastsquares analysis for predation rates between 0.1 and 0.9. Lack-of-fit statistics can reveal inadequate fit of a model to a data set where simple regression statistics might erroneously suggest a good match.     

How well does the HoT score reflect sequence alignment accuracy?

Multiple sequence alignment is an essential tool in many areas of biological research, and the accuracy of an alignment can strongly affect the accuracy of a downstream application such as phylogenetic analysis, identification of functional motifs, or polymerase chain reaction primer design. The heads or tails (HoT) method (Landan G, Graur D. 2007. Heads or tails: a simple reliability check for multiple sequence alignments. Mol Biol Evol. 24:1380-1383.) assesses the consistency of an alignment by comparing the alignment of a set of sequences with the alignment of the same set of sequences written in reverse order. This study shows that HoT scores and the alignment accuracies are positively correlated, so alignments with higher HoT scores are preferable. However, HoT scores are overestimates of alignment accuracy in general, with the extent of overestimation depending on the method used for multiple sequence alignment.     

Reaching new heights: can drones replace current methods to study plant population dynamics?

Spatially explicit data on heterogeneously distributed plant populations are difficult to quantify using either traditional field-based methods or remote sensing techniques alone. Unmanned Aerial Vehicles (UAVs) offer new means and tools for baseline monitoring of such populations. We tested the use of vegetation classification of UAV-acquired photographs as a method to capture heterogeneously distributed plant populations, using Jacobaea vulgaris as a model species. Five sites, each containing 1–4 pastures with varying J. vulgaris abundance, were selected across Schleswig–Holstein, Germany. Surveys were conducted in July 2017 when J. vulgaris was at its flowering peak. We took aerial photographs at a 50 m altitude using three digital cameras (RGB, red-edge and near-infrared). Orthomosaics were created before a pixel-based supervised classification. Classification results were evaluated for accuracy; reliability was assessed with field data collected for ground verification. An ANOVA tested the relationship between field-based abundance estimations and the supervised classifications. Overall accuracy of the classification was very high (90.6%,?±?1.76 s.e.). Kappa coefficients indicated substantial agreement between field data and image classification (≥?0.65). Field-based estimations were a good predictor of the supervised classifications (F?=?7.91, df?=?4, P?=?0.007), resulting in similar rankings of J. vulgaris abundance. UAV-acquired images demonstrated the potential as an objective method for data collection and species monitoring. However, our method was more time consuming than field-based estimations due to challenges in image processing. Nonetheless, the increasing availability of low-cost consumer-grade UAVs is likely to increase the use of UAVs in plant ecological studies.     

When can the cause of a population decline be determined?

Inferring the factors responsible for declines in abundance is a prerequisite to preventing the extinction of wild populations. Many of the policies and programmes intended to prevent extinctions operate on the assumption that the factors driving the decline of a population can be determined. Exogenous factors that cause declines in abundance can be statistically confounded with endogenous factors such as density dependence. To demonstrate the potential for confounding, we used an experiment where replicated populations were driven to extinction by gradually manipulating habitat quality. In many of the replicated populations, habitat quality and density dependence were confounded, which obscured causal inference. Our results show that confounding is likely to occur when the exogenous factors that are driving the decline change gradually over time. Our study has direct implications for wild populations, because many factors that could drive a population to extinction change gradually through time.     

Do peptides control their own birth and death?

The tumour suppressor protein p53 and the Epstein-Barr-virus-encoded Epstein-Barr virus nuclear antigen-1 (EBNA1) can regulate their own proteasomal degradation and mRNA translation - in effect, they mediate control of their own steady-state levels. A large fraction of mRNA-translation-initiation events does not give rise to functional proteins; so could this reflect a more widespread concept by which certain proteins that require tight control of expression use similar means of self-regulation?     

Can possible evolutionary outcomes be determined directly from the population dynamics?

Traditionally, to determine the possible evolutionary behaviour of an ecological system using adaptive dynamics, it is necessary to calculate the fitness and its derivatives at a singular point. We investigate the claim that the possible evolutionary behaviour can be predicted directly from the population dynamics, without the need for calculation, by applying three criteria — one based on the form of the density dependent rates and two on the role played by the evolving parameters. Taking a general continuous time model, with broad ecological range, we show that the claim is true. Initially, we assume that individuals enter in class 1 and move through population classes sequentially; later we relax these assumptions and find that the criteria still apply. However, when we consider models where the evolving parameters appear non-linearly in the dynamics, we find some aspects of the criteria fail; useful but weaker results on possible evolutionary behaviour now apply.