Spatial and temporal habitat use patterns for salt marsh nekton: implications for ecological functions

We synthesized information on temporal and spatial patterns of salt marsh habitat use by nekton in order to infer the importance of five main types of marsh function: reproduction, foraging, refuge from predation, refuge from stressful environmental conditions and environmental enhancement of physiology. We then extended the concept that intertidal gradients regulate habitat use patterns of nekton to a more universal concept that applies to all salt marsh habitats. We contend that all marsh habitats are linked to each other and to adjacent estuarine habitats along a depth gradient that mediates gradients in abiotic and biotic conditions. Tidal, diel and seasonal shifts in the magnitude and direction of these gradients result in gradients in tidal, diel and seasonal variation in biotic and abiotic conditions within the salt marsh. Collectively these gradients form the `marsh gradient'. We propose that patterns of marsh use and ecological function for nekton result primarily from physiological and behavioral responses to this marsh gradient. A comparison of habitat use patterns in the context of the marsh gradient is an important – and underutilized – method to study marsh function and essential fish habitat. We note that our limited insight into the function of the marsh habitat results from a significant lack of information on the occurrence and causes of tidal, diel and ontogenetic marsh use patterns by nekton; this is particularly relevant with respect to data on the variation in environmental conditions along marsh gradients over tidal, diel and seasonal cycles and on how environmental variation on these scales influences nekton behavior, growth and survival.     

Labyrinthine versus straight-striped patterns generated by two-dimensional Turing systems

Striped patterns are often observed on fish skin. Such patterns have been accounted for by reaction-diffusion (RD) Turing-type models, in which two substances can spontaneously form a spatially heterogeneous pattern in a homogeneous field. Among the striped patterns generated by Turing-type models, some are "straight-striped patterns," with many stripes running in parallel, while others are "labyrinthine patterns," in which the stripes often change direction, merge with each other, and frequently branch out. RD models differ in terms of their tendency to generate either labyrinthine or straight-striped patterns. Here, we studied the conditions under which either a labyrinthine or straight-striped pattern would emerge. First, we defined an index for stripe clearness, Sh. Straight-striped patterns (large Sh) are formed if only a narrow range of spatial periods corresponds to an unstable mode. Labyrinthine patterns (small Sh) are formed when a wide range of spatial periods is unstable. More specifically, labyrinthine patterns are formed when the maximum spatial period of unstable modes is more than twice that of the minimum spatial period of unstable modes; otherwise, straight-striped patterns are formed. We then examined RD models with nonlinear reaction terms, including both activator-inhibitor and substrate-depletion models, and we demonstrated that the same conclusions hold with respect to the conditions required for labyrinthine versus straight-striped patterns.     

On the origin of tiger bush

We propose a model which describes the dynamics of vast classes of terrestrial plant communities growing in arid or semi-arid regions throughout the world. On the basis of this model, we show that the vegetation stripes (tiger bush) formed by these communities result from an interplay between short-range cooperative interactions controlling plant reproduction and long-range self-inhibitory interactions originating from plant competition for environmental resources. Isotropic as well as anisotropic environmental conditions are discussed. We find that vegetation stripes tend to orient themselves in the direction parallel or perpendicular with respect to a direction of anisotropy depending on whether this anisotropy influences the interactions favouring or inhibiting plant reproduction; furthermore, we show that ground curvature is not a necessary condition for the appearance of arcuate vegetation patterns. In agreement within situ observations, we find that the width of vegetated bands increases when environmental conditions get more arid and that patterns formed of stripes oriented parallel to the direction of a slope are static, while patterns which are perpendicular to this direction exhibit an upslope motion.     

Activity patterns of rodents: the physiological ecology of biological rhythms

To date, most research in the field of biological rhythms has been performed on nocturnal rodents under laboratory conditions. This research has made much progress in recent years. It is now time to investigate the adaptive value of the studied molecular mechanisms under natural conditions. Here we review relevant studies of rodent activity patterns. We also review a case study of temporal partitioning between spiny mice. We conclude that the response to environmental stimuli, using a system composed of a rigid master circadian oscillator and more flexible mechanisms such as peripheral oscillators with weak coupling, masking responses, and downstream switching mechanisms, is adaptive since it enables an animal to reset its activity phase without the cost of shifting the phase of the entire circadian system. We suggest that these mechanisms play a significant role in determining activity patterns under natural conditions, and are important for understanding the ecology and evolution of activity rhythms.     

Geometry and spatial patterns in Polysphondylium pallidum

The formation of secondary sori in whorls of Polysphondylium pallidum provides an attractive model system for the study of symmetry breaking during morphogenesis. Tip-specific antibodies that permit detection of very early stages in this patterning process are available. We have found that the patterns of tip-specific antigen expression vary considerably depending on the size, shape, and developmental stage of the whorl. All of these patterns, however, are well explained by patterning models that rely on short-range autocatalysis and long-range inhibition, as exemplified by reaction-diffusion theories. In the context of reaction-diffusion, we discuss the possible effects of initial conditions, boundary conditions, and nonlinearities on the selection of patterns in P. pallidum whorls.     

Matrix type alters structure of aquatic vertebrate assemblages in cypress domes

Management of communities in fragmented systems requires application of models for predicting and understanding patterns of diversity at relevant scales. Metacommunity models may help explain patterns of beta-diversity, but more empirical investigations are needed to determine the generality of these models and the importance of matrix identity as a mediator of metacommunity processes. We studied patterns of beta diversity among cypress domes in a landscape composed of two different matrix types within Big Cypress National Preserve to determine whether community composition differed by matrix type and to evaluate predictions of metacommunity models. We sampled fully-aquatic vertebrates in 16 cypress domes. A causal modeling framework was used to assess the relative importance of space and environmental variables measured in the domes and in the nearby matrix in explaining variation in community similarities. Our results show that community composition was influenced by matrix type, which violates the common metacommunity assumption that matrix identity has negligible effect on patch patterns. We found different drivers of beta-diversity patterns between matrix types; similarities among dome communities within cypress-prairie matrix were influenced by local environmental conditions and matrix characteristics, while communities in pine-rockland domes were most influenced by conditions in the matrix. Our results have implications for use of metacommunity models in conservation planning and we suggest that future research should focus on the importance of matrix identity and complexity in mediating community patterns in patchy landscapes.     

The role of environmental and spatial processes in structuring native and non‐native fish communities across thousands of lakes

Quantifying the role of spatial patterns is an important goal in ecology to further understand patterns of community composition. We quantified the relative role of environmental conditions and regional spatial patterns that could be produced by environmental filtering and dispersal limitation on fish community composition for thousands of lakes. A database was assembled on fish community composition, lake morphology, water quality, climatic conditions, and hydrological connectivity for 9885 lakes in Ontario, Canada. We utilized a variation partitioning approach in conjunction with Moran's Eigenvector Maps (MEM) and Asymmetric Eigenvector Maps (AEM) to model spatial patterns that could be produced by human‐mediated and natural modes of dispersal. Across 9885 lakes and 100 fish species, environmental factors and spatial structure explained approximately 19% of the variation in fish community composition. Examining the proportional role of spatial structure and environmental conditions revealed that as much as 90% of the explained variation in native species assemblage composition is governed by environmental conditions. Conversely on average, 67% of the explained variation in non‐native assemblage composition can be related to human‐mediated dispersal. This study highlights the importance of including spatial structure and environmental conditions when explaining patterns of community composition to better discriminate between the ecological processes that underlie biogeographical patterns of communities composed of native and non‐native fish species.     

Central-place seed foraging and vegetation patterns

We investigate how central-place seed foragers with a nest in the proximity of one or more seed sources determine the formation of different vegetation patterns. In particular, we discuss the ecological conditions that lead to the formation of hump-shaped (Janzen–Connell) patterns in a two-dimensional landscape. Our analysis shows that central-place predation can generate Janzen–Connell patterns even if predators’ movement strategies are exclusively based on resource abundance, both in the single-plant/single-nest case and in a forest with several seed sources. We also show that social foraging may either promote or work against the formation of Janzen–Connell patterns, depending upon the way foragers take advantage of social interactions.     

Multiple hysteretic patterns from elementary population models

Critical transitions whereby small changes in conditions can cause large and irreversible changes in ecosystem states are a cause of increasing concern in ecology. Here, we focus on the irreversibility of these transitions, formally known as hysteresis. We explore how simple correlations between parameters in Lotka-Volterra predator-prey equations result in a variety of complicated hysteretic patterns. These patterns include “unattainable” stable states that once lost may never be recovered. We suspect these patterns to be common in natural systems, where interactions between diverse assemblages are unavoidable. Thus, understanding underlying hysteretic structures may be necessary for rescuing lost ecosystem states and avoiding future losses.     

Local weather conditions have complex effects on the growth of blue tit nestlings

Adverse weather conditions are expected to result in impaired nestling development in birds, but empirical studies have provided equivocal support for such a relationship. This may be because the negative effects of adverse weather conditions are masked by parental effects. Globally, ambient temperatures, rainfall levels and wind speeds are all expected to increase in a changing climate and so there is a need for a better understanding of the relationship between weather conditions and nestling growth. Here, we describe a correlative study that examined the relationships between local temperatures, rainfall levels and wind speeds and the growth of individual blue tit (Cyanistes caeruleus) nestlings in relation to their hatching order and sex. We found that changes in a range of morphological characters were negatively related to both temperature and wind speed, but positively related to rainfall. These patterns were further influenced by the hatching order of the nestlings but not by nestling sex. This suggests that the predicted changes in local weather conditions may have complex effects on nestling growth, but that parents may be able to mitigate the adverse effects via adaptive parental effects. We therefore conclude that local weather conditions have complex effects on avian growth and the implications for patterns of avian growth in a changing climate are discussed.     

Co-existent activity patterns in inhibitory neuronal networks with short-term synaptic depression

A network of two neurons mutually coupled through inhibitory synapses that display short-term synaptic depression is considered. We show that synaptic depression expands the number of possible activity patterns that the network can display and allows for co-existence of different patterns. Specifically, the network supports different types of n-m anti-phase firing patterns, where one neuron fires n spikes followed by the other neuron firing m spikes. When maximal synaptic conductances are identical, n-n anti-phase firing patterns are obtained and there are conductance intervals over which different pairs of these solutions co-exist. The multitude of n-m anti-phase patterns and their co-existence are not found when the synapses are non-depressing. Geometric singular perturbation methods for dynamical systems are applied to the original eight-dimensional model system to derive a set of one-dimensional conditions for the existence and co-existence of different anti-phase solutions. The generality and validity of these conditions are demonstrated through numerical simulations utilizing the Hodgkin-Huxley and Morris-Lecar neuronal models.     

Environmental correlates of anuran beta diversity in the Brazilian Cerrado

Evolutionary processes are known to influence contemporary patterns of biological diversity, yet disentangling the effects of current and historical drivers of biodiversity patterns remain challenging. We use spatial analyses of community dissimilarity to generate hypotheses about the current and historical processes underlying patterns of beta diversity in anuran species in the Brazilian Cerrado. Specifically, we use a generalized dissimilarity modeling (GDM) approach to model compositional dissimilarity of anuran species and endemics as a function of geographic separation and local (within‐Cerrado) environmental conditions. To gain insight about potential historical processes, we incorporate information from biomes adjacent to the Cerrado to investigate whether environmental conditions in neighboring areas can help explain patterns of beta diversity within the Cerrado. Patterns of anuran beta diversity of both endemics and all species in the Cerrado appear to be strongly influenced by local environmental gradients, with elevation as one of the most important variables in all models. However, in models using endemic species only, environmental conditions of adjacent biomes were related to beta‐diversity patterns, and more strongly so, than to total species models. These results suggest that phylogenetic niche conservatism within species groups that invaded the Cerrado from adjacent biomes may cause these species to be restricted to environmental conditions within the Cerrado that are most similar to the conditions in the adjacent biome where they originated. Time‐calibrated phylogenies of Cerrado endemics and studies of ancestral and current ranges of Cerrado species are needed to test this hypothesis.     

Sexual and social stimuli elicit rapid and contrasting genomic responses

Sensory physiology has been shown to influence female mate choice, yet little is known about the mechanisms within the brain that regulate this critical behaviour. Here we examine preference behaviour of 58 female swordtails, Xiphophorus nigrensis, in four different social environments (attractive and unattractive males, females only, non-attractive males only and asocial conditions) followed by neural gene expression profiling. We used a brain-specific cDNA microarray to identify patterns of genomic response and candidate genes, followed by quantitative PCR (qPCR) examination of gene expression with variation in behaviour. Our microarray results revealed patterns of genomic response differing more between classes of social stimuli than between presence versus absence of stimuli. We identified suites of genes showing diametrically opposed patterns of expression: genes that are turned 'on' while females interact with attractive males are turned 'off' when interacting with other females, and vice versa. Our qPCR results identified significant predictive relationships between five candidate genes and specific mate choice behaviours (preference and receptivity) across females exposed to males, with no significant patterns identified in female or asocial conditions or with overall locomotor activity. The identification of stimulus- and behaviour-specific responses opens an exciting window into the molecular pathways associated with social behaviour and mechanisms that underlie sexual selection.     

Spearman Correlation Identifies Statistically Significant Gene Expression Clusters in Spinal Cord Development and Injury

An important problem in the analysis of large-scale gene expression data is the validation of gene expression clusters. By examining the temporal expression patterns of 74 genes expressed in rat spinal cord under three different experimental conditions, we have found evidence that some genes cluster together under multiple conditions. Using RT-PCR data from spinal cord development and two sets of microarray data from spinal injury, we applied Spearman correlation to identify clusters and to assign P values to pairs of genes with highly similar temporal expression patterns. We found that 15% of genes occurred in statistically significant pairs in all three experimental conditions, providing both statistical and experimental support for the idea that genes that cluster together are co-regulated. In addition, we demonstrated that DNA microarray and RT-PCR data are comparable, and can be combined to confirm gene expression relationships.     

Pattern sensitivity to boundary and initial conditions in reaction-diffusion models

We consider Turing-type reaction-diffusion equations and study (via computer simulations) how the relationship between initial conditions and the asymptotic steady state solutions varies as a function of the boundary conditions. The results indicate that boundary conditions which are non-homogeneous with respect to the kinetic steady state give rise to spatial patterns which are much less sensitive to variations in the initial conditions than those obtained with homogeneous boundary conditions, such as zero flux conditions. We also compare linear pattern predictions with the numerical solutions of the full nonlinear problem.This work supported in part by U.S. Army Grant DAJA 37-81-C-0220 and the Science and Engineering Research Council of Great Britain Grant GR/c/63595     

Bone microstructure and developmental plasticity in birds and other dinosaurs

Patterns of bone microstructure have frequently been used to deduce dynamics and processes of growth in extant and fossil tetrapods. Often, the various types of primary bone tissue have been associated with different bone deposition rates and more recently such deductions have extended to patterns observed in dinosaur bone microstructure. These previous studies are challenged by the findings of the current research, which integrates an experimental neontological approach and a paleontological comparison. We use tetracycline labeling and morphometry to study the variability of bone deposition rates in Japanese quail (Coturnix japonica) growing under different experimental conditions. We compare resulting patterns in bone microstructure with those found in fossil birds and other dinosaurs. We found that a single type of primary bone varies significantly in rates of growth in response to environmental conditions. Ranging between 10-50 microm per day, rates of growth overlap with the full range of bone deposition rates that were previously associated with different patterns of bone histology. Bone formation rate was significantly affected by environmental/experimental conditions, skeletal element, and age. In the quail, the experimental conditions did not result in formation of lines of arrested growth (LAGs). Because of the observed variation of bone deposition rates in response to variation in environmental conditions, we conclude that bone deposition rates measured in extant birds cannot simply be extrapolated to their fossil relatives. Additionally, we observe the variable incidence of LAGs and annuli among several dinosaur species, including fossil birds, extant sauropsids, as well as nonmammalian synapsids, and some extant mammals. This suggests that the ancestral condition of the response of bone to environmental conditions was variable. We propose that such developmental plasticity in modern birds may be reduced in association with the shortened developmental time during the later evolution of the ornithurine birds.     

An evolving neural network for the interpretation of gene expression patterns

It is of central interest in biology to understand how gene activity networks are coordinated and integrated in the cell. Within the field of genomics, microarray technologies have become a powerful technique for monitoring simultaneously the expression patterns of thousands of genes under different sets of conditions. A main task now is to propose analytical methods that can suggest which groups of genes are activated by similar conditions. We review several techniques based on self-organizing map and clustering algorithms but implemented through a network of units controlled by biologically inspired functions (see Table 1). The computer tool, named NBIA, permits a categorization that generates a set of gene groups with coordinated expression patterns.     

Spatial patterns in population conflicts

We consider a dynamical model for evolutionary games, and enquire how the introduction of diffusion may lead to the formation of stationary spatially inhomogeneous solutions, that is patterns. For the model equations being used it is already known that if there is an evolutionarily stable strategy (ESS), then it is stable. Equilibrium solutions which are not ESS's and which are stable with respect to spatially constant perturbations may be unstable for certain choices of the dispersal rates. We prove by a bifurcation technique that under appropriate conditions the instability leads to patterns. Computations using a curve-following technique show that the bifurcations exhibit a rich structure with loops joined by symmetry-breaking branches.     

How well does Turing's theory of morphogenesis work?

In 1952 Turing published a paper which showed how under restricted conditions a class of chemical reactions could give biological patterns in diffusion-coupled cells. Although this theory has been much discussed, little has been learnt about the range and type of pattern it can generate. In order to do this and to see how stable the patterns are, we have examined the system in detail and written a computer program to simulate Turing's kinetics for two morphogens over various assemblies of cells. We find that on one-dimensional lines of cells, patterns can indeed be produced and that the chemical wavelengths follow all of Turing's predictions. The results show that stable repeating peaks of chemical concentration of periodicity 2–20 cells can be obtained in embryos in periods of time of less than an hour. We do find however that these patterns are not reliable: small variations in initial conditions give small but significant changes in the number and positions of observed peaks. Similar results are observed in two-dimensional assemblies of cells. On rectangles, random blotches are observed whose position cannot be reliably predicted. On cylinders whose circumference is less than the chemical wavelength, annular stripes are produced. For larger cylinders, blotches that lie very approximately on helices are generated; again sharp prediction of the detailed pattern is impossible.The significance of these results for the developing embryo is discussed. We conclude that Turing kinetics, at least in the simple cases that we have studied, are too unreliable to serve as the generating mechanism for features such as digits which are characterized by a consistent number of units. The theory is however more than adequate by these criteria to specify less well-defined developing patterns such as those of hair follicles or leaf organization. It is emphasized however that the Turing theory is quite unable to generate regulative systems, only mosaicpatterns can be produced.     

An evolutionary tolerance model explaining spatial patterns in species richness under environmental gradients and geometric constraints

In this study, we developed a simulation model based on the ecological and evolutionary dynamics of geographical ranges, to understand the role of species' environmental tolerances and the strength of the environmental gradient in determining spatial patterns in species richness. Using an one-dimensional space, we present the model and dissect its parameters. Also, we test the ability of the model to simulate richness in complex two-dimensional domains and to fit real patterns in species richness, using South American Tyrannidae as an example. We found that a mid-spatial peak in species richness arises spontaneously under conditions of high environmental tolerances and/or a weak environmental gradient, since this condition causes wide species' geographic ranges, which are constrained by domain's boundary and tend to overlap in the middle. Our model was also a good predictor of real patterns in species richness, especially under conditions of high environmental strength and small species' tolerance. We conclude that this kind of spatial simulation models based on species' physiological tolerance may be an important tool to understand the evolutionary dynamics of species' geographic ranges and in spatial patterns of species richness.