The effects of spatial habitat structure on population variability of freshwater snails

Experiments were conducted to examine the effects of a habitat's spatial structure on population variability in two species of freshwater snails (Physa acuta and Austropeplea ollula). To alter the spatial structure of the habitat, vinyl chloride plates were hung in experimental tanks, providing three types of spatial structure: Complex structure, Simple structure and Control (no structure). In Experiment 1, the average number of individuals in a tank did not differ among the three types of structure 2 months after the introduction of the snails, but the variability of the number of individuals in the Complex structure tanks was lowest, whereas the variability in the Control tanks was highest. In Experiment 2, in addition to the spatial structure of the habitat, three types of species interaction were designed as experimental treatments: only P. acuta was introduced into the tanks (P. acuta tanks), only A. ollula was introduced into the tanks (A. ollulatanks) and both P. acuta and A. ollula were introduced into the tanks (two-species tanks). For the P. acuta tanks, the variability of the number of P. acuta individuals in the Complex structure tanks was lowest, and the variability in the Control tanks was highest when the effect of the number of individuals in a tank was subtracted. For the A. ollula tanks and the two-species tanks, there were no significant differences in the variability of the population size among the different treatments of spatial structure. The spatial distribution of P. acuta was more uniform than the distribution of A. ollula on the plates of complex structure. Our results indicate that the spatial structure of the habitat influences the variability of population size (the variance of the number of individuals in different populations during the earlier period after the introduction of the snails), but the effects depend on the spatial behavior of individuals and the interaction with other species.     

Self‐fertilization,long‐distance flash invasion and biogeography shape the population structure of Pseudosuccinea columella at the worldwide scale

Population genetic studies are efficient for inferring the invasion history based on a comparison of native and invasive populations, especially when conducted at species scale. An expected outcome in invasive populations is variability loss, and this is especially true in self‐fertilizing species. We here focus on the self‐fertilizing Pseudosuccinea columella, an invasive hermaphroditic freshwater snail that has greatly expanded its geographic distribution and that acts as intermediate host of Fasciola hepatica, the causative agent of human and veterinary fasciolosis. We evaluated the distribution of genetic diversity at the largest geographic scale analysed to date in this species by surveying 80 populations collected during 16 years from 14 countries, using eight nuclear microsatellites and two mitochondrial genes. As expected, populations from North America, the putative origin area, were strongly structured by selfing and history and harboured much more genetic variability than invasive populations. We found high selfing rates (when it was possible to infer it), none‐to‐low genetic variability and strong population structure in most invasive populations. Strikingly, we found a unique genotype/haplotype in populations from eight invaded regions sampled all over the world. Moreover, snail populations resistant to infection by the parasite are genetically distinct from susceptible populations. Our results are compatible with repeated introductions in South America and flash worldwide invasion by this unique genotype/haplotype. Our study illustrates the population genetic consequences of biological invasion in a highly selfing species at very large geographic scale. We discuss how such a large‐scale flash invasion may affect the spread of fasciolosis.     

Relative influence of habitat structure,species interactions and rainfall on the post‐fire population dynamics of ground‐dwelling vertebrates

The long‐term impacts of wildfires on animal populations are largely unknown. We used time‐series data based on a tracking index, from coastal NSW spanning 28 years after a wildfire, to investigate the relative influence of habitat structure, species interactions and climate on post‐fire animal population dynamics. The fire had an immediate impact on habitat structure, reducing and simplifying vegetation cover, which then underwent post‐fire successional change including an increase and plateau in tree canopy cover; an increase, stabilization and then decline in shrub cover; and an increase in ground litter cover. Population changes of different animal species were influenced by different components of successional change, but there was also evidence that species interactions were important. For example, bandicoots (Isoodon obesulus and Perameles nasuta combined) increased concurrent with an increase in shrub cover then declined at a faster rate than a direct association with senescing shrub cover would suggest, while the feral cat (Felis catus) population changed with the bandicoot population, suggesting a link between these species. Potoroos (Potorous tridactylus) increased 10 years after the fire concurrent with the closing tree canopy, but there was also evidence of a negative association with feral foxes (Vulpes vulpes). Variation in rainfall did not have significant effects on the population dynamics of any species. Our results suggest that changes in habitat structure play a key role in the post‐fire dynamics of many ground‐dwelling animals and hence different fire regimes are likely to influence animal dynamics through their effects on habitat structure. However, the role of predator–prey interactions, particularly with feral predators, is less clear and further study will require manipulative experiments of predators in conjunction with fire treatments to determine whether feral predator control should be integrated with fire management to improve outcomes for some native species.     

Genetic structure,spatial organization,and dispersal in two populations of bat‐eared foxes

We incorporated radio‐telemetry data with genetic analysis of bat‐eared foxes (Otocyon megalotis) from individuals in 32 different groups to examine relatedness and spatial organization in two populations in South Africa that differed in density, home‐range sizes, and group sizes. Kin clustering occurred only for female dyads in the high‐density population. Relatedness was negatively correlated with distance only for female dyads in the high‐density population, and for male and mixed‐sex dyads in the low‐density population. Home‐range overlap of neighboring female dyads was significantly greater in the high compared to low‐density population, whereas overlap within other dyads was similar between populations. Amount of home‐range overlap between neighbors was positively correlated with genetic relatedness for all dyad‐site combinations, except for female and male dyads in the low‐density population. Foxes from all age and sex classes dispersed, although females (mostly adults) dispersed farther than males. Yearlings dispersed later in the high‐density population, and overall exhibited a male‐biased dispersal pattern. Our results indicated that genetic structure within populations of bat‐eared foxes was sex‐biased, and was interrelated to density and group sizes, as well as sex‐biases in philopatry and dispersal distances. We conclude that a combination of male‐biased dispersal rates, adult dispersals, and sex‐biased dispersal distances likely helped to facilitate inbreeding avoidance in this evolutionarily unique species of Canidae.     

The effects of spatial habitat configuration on recruitment, growth and population structure in arctic Collembola

The population density and demography of five species of arctic Collembola were studied in a naturally patchy habitat, consisting of Carex ursinae tussocks with varying degrees of isolation. Focal predictor variables were those describing the spatial configuration of tussocks, including tussock size and isolation and the amount of habitat (cover) at a 1-m² scale surrounding each tussock population. The Collembola populations were heavily influenced by environmental stochasticity in the form of winter mortality and summer drought, and the influence of patchiness on population characteristics was evaluated in this context. The five species showed very different responses to the structuring effect of the habitat, depending on life history characteristics, mobility and habitat requirements. Population density was highly variable in both time and space. Spring densities indicated larger winter mortality compared to observations from a previous study, and the snow- and ice-free season from June to August only resulted in population growth for Folsomia sexoculata. In the other species, adult mortality must have been high as there was no net population growth despite observed reproduction. The exception was Hypogastrura viatica, whose population decline was more likely to have been the result of migration out of the study area. Cover was the most important variable explaining density. No pure area or isolation effects at the tussock level were detected, even in areas with very low habitat cover. Drought was probably an important mortality factor, as July was particularly warm and dry. Due to qualitative differences in the tussocks and the matrix substrate, desiccation risk would be higher during dispersal between tussocks. We suggest that increased dispersal mortality gave the observed pattern of increased density in relation to cover, both in general and in F. quadrioculata, an opportunistic species otherwise known for rapid population growth. Onychiurus groenlandicus, which had a similar density response to cover, may also be influenced by a rescue effect sustaining densities in areas with high cover. The cover effect can be viewed as a large-scale factor which encompasses the general spatial neighbourhood of each tussock, where inter-population processes are important, as opposed to internal patch dynamics. Received: 15 March 1999 / Accepted: 22 March 2000     

The spatial structure of habitat selection: A caribou's-eye-view

Greater understanding of habitat selection requires investigation at the scales at which organisms perceive and respond to their environment. Such knowledge could reveal the relative importance of factors limiting populations and the extent of response to habitat changes, and so guide conservation initiatives. We conducted a novel, spatially explicit analysis of winter habitat selection by caribou (Rangifer tarandus) in Newfoundland, Canada, to elucidate the spatial scales of habitat selection. We combined conventional hierarchical habitat analysis with a newly developed geospatial approach that quantifies selection across scales as the difference in variance between available and used sites. We used both ordination and univariate analyses of lichen and plant cover, snow hardness and depth. This represents the first use of ordination with geostatistics for the assessment of habitat selection. Caribou habitat selection was driven by shallow, soft snow and high cover of Cladina lichens and was strongest at feeding microsites (craters) and broader feeding areas. Habitat selection was most evident at distance lags of up to 15 km, perhaps an indication of the perceptual abilities of caribou.     

Fine-scale habitat structure complexity determines insectivorous bird diversity in a tropical forest

Habitat complexity in reforested stands has been acknowledged as a key factor that influences habitat use by birds, being especially critical for habitat disturbance-sensitive species such as tropical understory insectivorous birds. Most studies regarding the relationship between forest structure and species diversity were conducted at the landscape scale, but different diversity patterns may emerge at a finer scale (i.e., within a habitat patch). We examined a tropical reforested area (State of Caldas, Colombia), hypothesizing that insectivorous bird richness, abundance, and foraging guild abundance would increase as intra-habitat complexity increases. We established 40 monitoring plots within a reforested area, measured their structural features, and determined their relationships with species richness, total abundance, and foraging guild abundance, using Generalized Additive Models. We found that the increasing variation in basal area, stem diameter, and number of stems was positively correlated with species richness, total abundance, and foraging guild abundance. Relationships between richness or abundance and structural features were not lineal, but showing curvilinear responses and thresholds. Our results show that heterogeneity on basal area, stem diameter, and the number of stems was more correlated to insectivorous bird richness and abundance than the average of those structural features. Promoting structural variation on reforested areas by planting species with different growth rates may contribute to increase the richness and abundance of a tropical vulnerable group of species such as the understory insectivorous birds.     

Open population maximum likelihood spatial capture‐recapture

Open population capture‐recapture models are widely used to estimate population demographics and abundance over time. Bayesian methods exist to incorporate open population modeling with spatial capture‐recapture (SCR), allowing for estimation of the effective area sampled and population density. Here, open population SCR is formulated as a hidden Markov model (HMM), allowing inference by maximum likelihood for both Cormack‐Jolly‐Seber and Jolly‐Seber models, with and without activity center movement. The method is applied to a 12‐year survey of male jaguars (Panthera onca) in the Cockscomb Basin Wildlife Sanctuary, Belize, to estimate survival probability and population abundance over time. For this application, inference is shown to be biased when assuming activity centers are fixed over time, while including a model for activity center movement provides negligible bias and nominal confidence interval coverage, as demonstrated by a simulation study. The HMM approach is compared with Bayesian data augmentation and closed population models for this application. The method is substantially more computationally efficient than the Bayesian approach and provides a lower root‐mean‐square error in predicting population density compared to closed population models.     

Stay by thy neighbor? Social organization determines the efficiency of biodiversity markets with spatial incentives

Market-based conservation instruments, such as payments, auctions or tradable permits, are environmental policies that create financial incentives for landowners to engage in voluntary conservation on their land. But what if ecological processes operate across property boundaries and land use decisions on one property influence ecosystem functions on neighboring sites? This paper examines how to account for such spatial externalities when designing market-based conservation instruments. We use an agent-based model to analyze different spatial metrics and their implications on land use decisions in a dynamic cost environment. The model contains a number of alternative submodels which differ in incentive design and social interactions of agents, the latter including coordinating as well as cooperating behavior of agents. We find that incentive design and social interactions have a strong influence on the spatial allocation and the costs of the conservation market.     

Age‐specific habitat preference,carrying capacity,and landscape structure determine the response of population spatial variability to fishing‐driven age truncation

1. Understanding the mechanisms underlying spatial variability of exploited fish is critical for the sustainable management of fish stocks. Empirical studies suggest that size‐selective fishing can elevate fish population spatial variability (i.e., more heterogeneous distribution) through age truncation, making the population less resilient to changing environment. However, species differ in how their spatial variability responds to age truncation and the underlying mechanisms remain unclear.
2. We hypothesize that age‐specific habitat preference, together with environmental carrying capacity and landscape structure, determines the response of population spatial variability to fishing‐induced age truncation. To test these hypotheses, we design an individual‐based model of an age‐structured fish population on a two‐dimensional landscape under size‐selective fishing. Individual fish reproduces and survives, and moves between habitats according to age‐specific habitat preference and density‐dependent habitat selection.
3. Population spatial variability elevates with increasing age truncation, and the response is stronger for populations with stronger age‐specific habitat preference. On a gradient landscape, reducing carrying capacity elevates the relative importance of density dependence in habitat selection, which weakens the response of spatial variability to age truncation for populations with strong age‐specific habitat preference. On a fragmented landscape, both populations with strong and weak age‐specific habitat preferences are restricted at local optimal habitats, and reducing carrying capacity weakens the responses of spatial variability to age truncation for both populations.
4. Synthesis and applications. We demonstrate that to track and predict the changes in population spatial variability under exploitation, it is essential to consider the interactive effects of age‐specific habitat preference, carrying capacity, and landscape structure. To improve spatial management in fisheries, it is crucial to enhance empirical and theoretical developments in the methodology to quantify age‐specific habitat preference of marine fish, and to understand how climatic change influences carrying capacity and landscape continuity.

     

Towards a resource‐based habitat approach for spatial modelling of vector‐borne disease risks

Given the veterinary and public health impact of vector‐borne diseases, there is a clear need to assess the suitability of landscapes for the emergence and spread of these diseases. Current approaches for predicting disease risks neglect key features of the landscape as components of the functional habitat of vectors or hosts, and hence of the pathogen. Empirical–statistical methods do not explicitly incorporate biological mechanisms, whereas current mechanistic models are rarely spatially explicit; both methods ignore the way animals use the landscape (i.e. movement ecology). We argue that applying a functional concept for habitat, i.e. the resource‐based habitat concept (RBHC), can solve these issues. The RBHC offers a framework to identify systematically the different ecological resources that are necessary for the completion of the transmission cycle and to relate these resources to (combinations of) landscape features and other environmental factors. The potential of the RBHC as a framework for identifying suitable habitats for vector‐borne pathogens is explored and illustrated with the case of bluetongue virus, a midge‐transmitted virus affecting ruminants. The concept facilitates the study of functional habitats of the interacting species (vectors as well as hosts) and provides new insight into spatial and temporal variation in transmission opportunities and exposure that ultimately determine disease risks. It may help to identify knowledge gaps and control options arising from changes in the spatial configuration of key resources across the landscape. The RBHC framework may act as a bridge between existing mechanistic and statistical modelling approaches.     

Both habitat change and local lek structure influence patterns of spatial loss and recovery in a black grouse population

Land use change is a major driver of declines in wildlife populations. Where human economic or recreational interests and wildlife share landscapes this problem is exacerbated. Changes in UK black grouse Tetrao tetrix populations are thought to have been strongly influenced by upland land use change. In a long-studied population within Perthshire, lek persistence is positively correlated with lek size, and remaining leks clustered most strongly within the landscape when the population is lowest, suggesting that there may be a demographic and/or spatial context to the reaction of the population to habitat changes. Hierarchical cluster analysis of lek locations revealed that patterns of lek occupancy when the population was declining were different to those during the later recovery period. Response curves from lek-habitat models developed using MaxEnt for periods with a declining population, low population, and recovering population were consistent across years for most habitat measures. We found evidence linking lek persistence with habitat quality changes and more leks which appeared between 1994 and 2008 were in improving habitat than those which disappeared during the same period. Generalised additive models identified changes in woodland and starting lek size as being important indicators of lek survival between declining and low/recovery periods. There may also have been a role for local densities in explaining recovery since the population low point. Persistence of black grouse leks was influenced by habitat, but changes in this alone did not fully account for black grouse declines. Even when surrounded by good quality habitat, leks can be susceptible to extirpation due to isolation.     

Pattern‐oriented modelling of population genetic structure

Although several statistical approaches can be used to describe patterns of genetic variation and infer stochastic differentiation, selective responses, or interruptions of gene flow due to physical or environmental barriers, it is worthwhile to note that similar processes, controlled by several parameters in theoretical models, frequently give rise to similar patterns. Here, we develop a Pattern‐Oriented Modelling (POM) approach that allows us to determine how a complex set of parameters potentially driving empirical genetic differentiation among populations generate alternative scenarios that can be fitted to observed data. We generated 10 000 random combinations of parameters related to population size, gene flow and response to gradients (both driven by dispersal and selection) in a spatially explicit model, and analysed simulated patterns with F_ST statistics and mean correlograms using Moran's I spatial autocorrelation coefficients. These statistics were compared with observed patterns for a tree species endemic to the Brazilian Cerrado. For a best match with observed F_ST (equal to 0.182), the important parameters driving simulated scenario are mainly related to population structure, including low population size with closed populations (low N_m), strong distance decay of gene flow, in addition to a strong effect of the initial variance of allele frequencies. These scenarios present a low autocorrelation of allele frequencies. Best matching of correlograms, on the other hand, appears in simulations with a large population size, high N_m and low population differentiation and F_ST (as well as more gene flow). Thus, targeting the two statistics (correlograms and F_ST) shows that best matches with empirical data with two distinct sets of parameters in the simulations, because observed patterns involve both a relatively high F_ST and significant autocorrelation. This conflict can be resolved by assuming that initial variance in allele frequencies can be interpreted as reflecting deep‐time historical variation and evolutionary dynamics of allele frequencies, creating a relatively high level of population differentiation, whereas current patterns in gene flow creates spatial autocorrelation. This make sense in terms of the previous knowledge on population differentiation in D. alata, especially if patterns are explained by a combination of isolation‐by‐distance and allelic surfing due to range expansion after the last glacial maximum. This reveals the potential for more complex applications of POM in population genetics. © 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 113 , 1152–1161.     

Peptide contour length determines equilibrium secondary structure in protein‐analogous micelles

This work advances bottom‐up design of bioinspired materials built from peptide‐amphiphiles, which are a class of bioconjugates in which a biofunctional peptide is covalently attached to a hydrophobic moiety that drives self‐assembly in aqueous solution. Specifically, this work highlights the importance of peptide contour length in determining the equilibrium secondary structure of the peptide as well as the self‐assembled (i.e., micelle) geometry. Peptides used here repeat a seven‐amino acid sequence between one and four times to vary peptide contour length while maintaining similar peptide‐peptide interactions. Without a hydrophobic tail, these peptides all exhibit a combination of random coil and α‐helical structure. Upon self‐assembly in the crowded environment of a micellar corona, however, short peptides are prone to β‐sheet structure and cylindrical micelle geometry while longer peptides remain helical in spheroidal micelles. The transition to β‐sheets in short peptides is rapid, whereby amphiphiles first self‐assemble with α‐helical peptide structure, then transition to their equilibrium β‐sheet structure at a rate that depends on both temperature and ionic strength. These results identify peptide contour length as an important control over equilibrium peptide secondary structure and micelle geometry. Furthermore, the time‐dependent nature of the helix‐to‐sheet transition opens the door for shape‐changing bioinspired materials with tunable conversion rates. © 2013 Wiley Periodicals, Inc. Biopolymers 99: 573–581, 2013.