The role of conjugation in the gene-individual-population relationships in increasing eco-exergy

The genotypic and phenotypic processes were incorporated into one system in the gene-individual-population relationships under the framework of Individual based models (IBMs). The gene types addressing different degrees of metabolic efficiency and toxin susceptibility were provided as attributes in the individuals. Subsequently ecological processes such as food competition and movement were allowed concurrently on the 2-D space to determine the suitable species adapted to the system. The integrative gene-individual-population model accordingly responded to gene exchanges between the neighboring individuals through conjugation. At a substantially low level of gene exchange, system heterogeneity increased to produce high levels of eco-exergy, being presented by species diversity and total population size in the system. The issues related to genetic and ecological effects in the integrative gene-individual-population relationships were further discussed.     

Seeing the forest for the heterogeneous trees: stand-scale resource distributions emerge from tree-scale structure

Forest ecosystem processes depend on local interactions that are modified by the spatial pattern of trees and resources. Effects of resource supplies on processes such as regeneration are increasingly well understood, yet we have few tools to compare resource heterogeneity among forests that differ in structural complexity. We used a neighborhood approach to examine understory light and nutrient availability in a well-replicated and large-scale variable-retention harvesting experiment in a red pine forest in Minnesota, USA. The experiment included an unharvested control and three harvesting treatments with similar tree abundance but different patterns of retention (evenly dispersed as well as aggregated retention achieved by cutting 0.1- or 0.3-ha gaps). We measured light and soil nutrients across all treatments and mapped trees around each sample point to develop an index of neighborhood effects (NI). Field data and simulation modeling were used to test hypotheses that the mean and heterogeneity of resource availability would increase with patchiness because of greater variation in competitive environments. Our treatments dramatically altered the types and abundances of competitive neighborhoods (NI) in each stand and resulted in significantly nonlinear relationships of light, nitrogen and phosphorus availability to NI. Hence, the distribution of neighborhoods in each treatment had a significant impact on resource availability and heterogeneity. In dense control stands, neighborhood variation had little impact on resource availability, whereas in more open stands (retention treatments), it had large effects on light and modest effects on soil nutrients. Our results demonstrate that tree spatial pattern can affect resource availability and heterogeneity in explainable and predictable ways, and that neighborhood models provide a useful tool for scaling heterogeneity from the individual tree to the stand. These insights are needed to anticipate the outcomes of silvicultural manipulations and should become more holistically integrated into both basic ecological and management science.     

Habitat selection predicts genetic relatedness in an alpine ungulate

Landscape heterogeneity plays an integral role in shaping ecological and evolutionary processes. Despite links between the two disciplines, ecologists and population geneticists have taken different approaches to evaluating habitat selection, animal movement, and gene flow across the landscape. Ecologists commonly use statistical models such as resource selection functions (RSFs) to identify habitat features disproportionately selected by animals, whereas population genetic approaches model genetic differentiation according to the distribution of habitat variables. We combined ecological and genetic approaches by using RSFs to predict genetic relatedness across a heterogeneous landscape. We constructed sex- and season-specific resistance surfaces based on RSFs estimated using data from 102 GPS (global positioning system) radio-collared mountain goats (Oreamnos americanus) in southeast Alaska, USA. Based on mountain goat ecology, we hypothesized that summer and male surfaces would be the best predictors of relatedness. All individuals were genotyped at 22 microsatellite loci, which we used to estimate genetic relatedness. Summer resistance surfaces derived from RSFs were the best predictors of genetic relatedness, and winter models the poorest. Mountain goats generally selected for areas close to escape terrain and with a high heat load (a metric related to vegetative productivity and snow depth), while avoiding valleys. Male- and female-specific surfaces were similar, except for winter, for which male habitat selection better predicted genetic relatedness. The null models of isolation-by-distance and barrier only outperformed the winter models. This study merges high-resolution individual locations through GPS telemetry and genetic data, that can be used to validate and parameterize landscape genetics models, and further elucidates the relationship between landscape heterogeneity and genetic differentiation.     

Selecting the best home range model: an information-theoretic approach

Choosing an appropriate home range model is important for describing space use by animals and understanding the ecological processes affecting animal movement. Traditional approaches for choosing among home range models have not resulted in general, consistent, and unambiguous criteria that can be applied to individual data sets. We present a new application of information-theoretic model selection that overcomes many of the limitations of traditional approaches, as follows. (1) It alleviates the need to know the true home range to assess home range models, thus allowing performance to be evaluated with data on individual animals. (2) The best model can be chosen from a set of candidate models with the proper balance between fit and complexity. (3) If candidate home range models are based on underlying ecological processes, researchers can use the selected model not only to describe the home range, but also to infer the importance of various ecological processes affecting animal movements within the home range.     

Measuring terrestrial movement behavior using passive integrated transponder (PIT) tags: effects of tag size on detection, movement, survival, and growth

Movement behaviors have broad ecological and evolutionary implications, affecting individual fitness, metapopulation dynamics, the distribution and abundance of species, as well as gene flow and thus adaptation and speciation. However, movement behaviors such as dispersal, station keeping, and ranging are poorly understood in many taxa due to the incompatibility of traditional tracking methods with long-term observations. This is particularly true for small-bodied life history stages and species. While the introduction of smaller passive integrated transponder (PIT) tags and the development of PIT telemetry have removed some barriers, the trade-offs between different tag sizes are unknown. Through a series of experiments, we tested for effects of PIT tag size on detection, movement, tag retention, growth, and survival of a juvenile amphibian. We found no effect of PIT tag size on initial movement distance, survival, or growth; and all individuals retained their tag for the course of the experiment. Detection and recapture rates, however, were increased with PIT tag size. The orientation of the tag relative to the vertical axis of the antenna also affected the size of the detection field, which was 15.78–43.90 % smaller when the antenna was moved perpendicular rather than parallel to the long axis of the tag. We conclude that PIT telemetry is a suitable technique for marking previously untraceable species or life history stages and may offer insight into the behaviors of these individuals. Investigations using multiple PIT tag sizes should include this in statistical analyses to account for tag size biased detection differences.     

Suspended particulate matter dynamics in a particle framework

Suspended particulate matter (SPM) dynamics in ocean models are usually treated with an advection–diffusion equation for one or more sediment size classes coupled to the hydrodynamical part of the model. Numerical solution of these additional partial differential equations unavoidably introduces numerical diffusion, i.e. in the case of sharp gradients the possible occurrence of artificial oscillations and non-positivity. A Lagrangian particle-tracking model has been developed to simulate short-term SPM dynamics. Modelling individual sediment particles allows a straightforward physical interpretation of the processes. The tracking of large numbers of individual and independent particles (up to 25 million in total in a single sediment class) can be achieved on high performance computer clusters, due to efficient parallelisation of particle tracking. The movement of the particles is described by a stochastic differential equation, which is consistent with the advection–diffusion equation. Here, the concentration profile is represented by a set of independent moving particles, which are advected according to the 3D velocity field, while the diffusive displacements of the particles are sampled from a random distribution, which is related to the eddy diffusivity field. To account for erosion a new parameterisation is proposed. Three numerical particle tracking schemes (EULER, MILSTEIN and HEUN) are presented and validated in idealised test cases. Finally, the particle tracking algorithms are applied to a realistic scenario, a severe winter storm in the East Frisian Wadden Sea (southern North Sea). The comparison with observations and an Eulerian SPM transport model seems to indicate a somewhat better fidelity of the Lagrangian approach.     

Spatiotemporal dynamics of habitat use by koalas: the checkerboard model

Animal movement patterns and use of space depend upon food and nonfood resources, as well as conspecific and heterospecific interactions, but models of habitat use often neglect to examine multiple factors and rarely include marsupials. We studied habitat use in an Australian population of koalas (Phascolarctos cinereus) over a 6-year period in order to determine how koalas navigate their environment and partition limited patchy food and nonfood resources. Tree selection among koalas appears to be mediated by folar chemistry, but nonfood tree selection exerts a major impact on home range use due to thermoregulatory constraints. Koalas moved on a daily basis, during both day and night, but daytime resting site was not necessarily in the same location as nighttime feeding site. Koalas had substantial home range overlap in the near absence of resource sharing with less than 1% of trees located in areas of overlap used by multiple koalas. We suggest that koala spatiotemporal distribution and habitat use are probably based upon a community structure of individuals, with a checkerboard model best describing overlap in home range area but not in resource use. Nonfood refugia and social networks should be incorporated into models of animal range and habitat use.     

Changes of movement patterns from early dispersal to settlement

Moving and spatial learning are two intertwined processes: (a) changes in movement behavior determine the learning of the spatial environment, and (b) information plays a crucial role in several animal decision-making processes like movement decisions. A useful way to explore the interactions between movement decisions and learning of the spatial environment is by comparing individual behaviors during the different phases of natal dispersal (when individuals move across more or less unknown habitats) with movements and choices of breeders (who repeatedly move within fixed home ranges), that is, by comparing behaviors between individuals who are still acquiring information vs. individuals with a more complete knowledge of their surroundings. When analyzing movement patterns of eagle owls, Bubo bubo, belonging to three status classes (floaters wandering across unknown environments, floaters already settled in temporary settlement areas, and territory owners with a well-established home range), we found that: (1) wandering individuals move faster than when established in a more stable or fixed settlement area, traveling larger and straighter paths with longer move steps; and (2) when floaters settle in a permanent area, then they show movement behavior similar to territory owners. Thus, movement patterns show a transition from exploratory strategies, when animals have incomplete environmental information, to a more familiar way to exploit their activity areas as they get to know the environment better.     

Habitat-specific chemical cues influence association preferences and shoal cohesion in fish

The structure of social animal groups can be dynamic, characterized by high rates of group fission and fusion. Despite this, group composition is often well ordered by factors such as species, body size and by numerous other phenotypic traits. Research in shoaling fishes has revealed that individuals refine group membership decisions still further and are capable of assimilating chemical cues pertaining to recent habitat and prey use by prospective group mates, preferring to associate with others whose recent resource use history closely matches their own. In this study, we firstly examined the dynamics of the formation and breakdown of these preferences, revealing that they can be acquired and replaced in a matter of just a few hours. Using such cues enables individuals to accurately assess the resource use of conspecifics, allowing them to indirectly sample the local environment while reducing the chances of acquiring outdated information that can precipitate maladaptive behaviors. Secondly, we found that shoals composed of individuals with shared recent habitat use history were more cohesive compared to those where the constituent individuals differed in recent habitat use. Increased shoal cohesion may reduce predation risk, and could enhance the ability of individuals to detect and use social information.     

Ecological determinism increases with organism size

After much debate, there is an emerging consensus that the composition of many ecological communities is determined both by species traits, as proposed by niche theory, as well as by chance events. A critical question for ecology is, therefore, which attributes of species predict the dominance of deterministic or stochastic processes. We outline two hypotheses by which organism size could determine which processes structure ecological communities, and we test these hypotheses by comparing the community structure in bromeliad phytotelmata of three groups of organisms (bacteria, zooplankton, and macroinvertebrates) that encompass a 10 000-fold gradient in body size, but live in the same habitat. Bacteria had no habitat associations, as would be expected from trait-neutral stochastic processes, but still showed exclusion among species pairs, as would be expected from niche-based processes. Macroinvertebrates had strong habitat and species associations, indicating niche-based processes. Zooplankton, with body size between bacteria and macroinvertebrates, showed intermediate habitat associations. We concluded that a key niche process, habitat filtering, strengthened with organism size, possibly because larger organisms are both less plastic in their fundamental niches and more able to be selective in dispersal. These results suggest that the relative importance of deterministic and stochastic processes may be predictable from organism size.     

Variation in size at sex-change among natural populations of the protandrous hermaphrodite, <Emphasis Type="Italic">Crepidula fornicata</Emphasis> (Gastropoda,Calyptraeidae)

Protandrous hermaphrodites are predicted to change sex from male to female when relative reproductive fitness of females surpasses that of males. How size at sex transition varies with population, mating group and individual parameters was investigated for five populations of the protandrous hermaphrodite slipper snail, Crepidula fornicata. The populations varied for density, size distribution, average mating group size and sex ratio. Size at sex-change was correlated with the population sex ratio. Comparisons of multiple hypotheses revealed that variables predicting the sex of a snail vary among positions in the mating group. The variables included body size, the relative size of the snail sitting atop the focal snail and population density. Our data support the conclusions that size at sex-change (and by inference, the size at which one sex has relatively greater fitness) is not fixed for these hermaphrodites and that individual size, social conditions and population differences all influence variation in relative fitness.     

The effects of plant distribution and frugivore density on the scale and shape of dispersal kernels

For many plant species, seed dispersal is one of the most important spatial demographic processes. We used a diffusion approximation and a spatially explicit simulation model to explore the mechanisms generating seed dispersal kernels for plants dispersed by frugivores. The simulation model combined simple movement and foraging rules with seed gut passage time, plant distribution, and fruit production. A simulation experiment using plant spatial aggregation and frugivore density as factors showed that seed dispersal scale was largely determined by the degree of plant aggregation, whereas kernel shape was mostly dominated by frugivore density. Kernel shapes ranged from fat tailed to thin tailed, but most shapes were between an exponential and that of the solution of a diffusion equation. The proportion of dispersal kernels with fat tails was highest for landscapes with clumped plant distributions and increased with increasing number of dispersers. The diffusion model provides a basis for models including more behavioral details but can also be used to approximate dispersal kernels once a diffusion rate is estimated from animal movement data. Our results suggest that important characteristics of dispersal kernels will depend on the spatial pattern of plant distribution and on disperser density when frugivores mediate seed dispersal.     

Movements of <Emphasis Type="Italic">Ilyanassa obsoleta</Emphasis> (Gastropoda) on an intertidal sandflat

The gastropod Ilyanassa obsoleta (Say) is native to the east coast of North America where it is locally abundant on sandflats, mudflats, and in saltmarsh creeks. The local disturbances created by snails and their movements affect soft-sediment community composition. Movements of individually marked snails were followed on an intertidal sandflat on Cape Henlopen, Delaware, U.S.A. In June 1991, 1,200 snails that had tested as trematode-uninfected were released and over 5 months 554 were sighted 971 times. Mean daily net distance moved was 1.7 m, but snails often moved 10–20 m day⁻¹ and one snail was 180 m distant after 130 days. Net dispersal of the released population was attained in ≈10 days, by which time, a typical distance from release was 15–20 m. Snails were not found crossing sandbars and most moved away from shore into a tidal gully. In June 1993, 500 snails, both uninfected and trematode-infected, were released at the same position and over 6 months, 350 snails were sighted 949 times. Sandbars were again barriers to movement, but their changed positions allowed wider dispersal. Net dispersal was complete in ≈20 days by which time a typical distance from release was 30–40 m. Mean daily net distance moved was 2.2 m, but within 10 days snails had moved 50–100 m. In both years, following initial dispersal, snails (infected or not) took up random directions from move to move. Infected and uninfected snails dispersed equal distances, but had different mean final dispersal directions. Dispersal of I. obsoleta individuals was extensive and affected by shifting sandbar positions and parasitism. Recognizing this will be important in appreciating the ecological dynamics of this gastropod and in determining its effects on soft-bottom communities.Electronic Supplementary Material Supplementary material is available for this article at     

Analyzing animal movements using Brownian bridges

By studying animal movements, researchers can gain insight into many of the ecological characteristics and processes important for understanding population-level dynamics. We developed a Brownian bridge movement model (BBMM) for estimating the expected movement path of an animal, using discrete location data obtained at relatively short time intervals. The BBMM is based on the properties of a conditional random walk between successive pairs of locations, dependent on the time between locations, the distance between locations, and the Brownian motion variance that is related to the animal's mobility. We describe two critical developments that enable widespread use of the BBMM, including a derivation of the model when location data are measured with error and a maximum likelihood approach for estimating the Brownian motion variance. After the BBMM is fitted to location data, an estimate of the animal's probability of occurrence can be generated for an area during the time of observation. To illustrate potential applications, we provide three examples: estimating animal home ranges, estimating animal migration routes, and evaluating the influence of fine-scale resource selection on animal movement patterns.     

A general random walk model for the leptokurtic distribution of organism movement: Theory and application

The movement of organisms is usually leptokurtic in which some individuals move long distances while the majority remains at or near the area they are released. There has been extensive research into the origin of such leptokurtic movement, but one important aspect that has been overlooked is that the foraging behaviour of most organisms is not Brownian as assumed in most existing models. In this paper we show that such non-Brownian foraging indeed gives rise to leptokurtic distribution. We first present a general random walk model to describe the organism movement by breaking the foraging of each individual into events of active movement and inactive stationary period; its foraging behaviour is therefore fully characterized by a joint probability of how far the individual can move in each active movement and the duration it remains stationary between two consecutive movements. The spatio-temporal distribution of the organism can be described by a generalized partial differential equation, and the leptokurtic distribution is a special case when the stationary period is not exponentially distributed. Empirical observations of some organisms living in different habitats indicated that their rest time shows a power-law distribution, and we speculate that this is general for other organisms. This leads to a fractional diffusion equation with three parameters to characterize the distributions of stationary period and movement distance. A method to estimate the parameters from empirical data is given, and we apply the model to simulate the movement of two organisms living in different habitats: a stream fish (Cyprinidae: Nocomis leptocephalus) in water, and a root-feeding weevil, Sitona lepidus in the soil. Comparison of the simulations with the measured data shows close agreement. This has an important implication in ecology that the leptokurtic distribution observed at population level does not necessarily mean population heterogeneity as most existing models suggested, in which the population consists of different phenotypes; instead, a homogeneous population moving in homogeneous habitat can also lead to leptokurtic distribution.     

Incorporating animal behavior into seed dispersal models: implications for seed shadows

Seed dispersal fundamentally influences plant population and community dynamics but is difficult to quantify directly. Consequently, models are frequently used to describe the seed shadow (the seed deposition pattern of a plant population). For vertebrate-dispersed plants, animal behavior is known to influence seed shadows but is poorly integrated in seed dispersal models. Here, we illustrate a modeling approach that incorporates animal behavior and develop a stochastic, spatially explicit simulation model that predicts the seed shadow for a primate-dispersed tree species (Virola calophylla, Myristicaceae) at the forest stand scale. The model was parameterized from field-collected data on fruit production and seed dispersal, behaviors and movement patterns of the key disperser, the spider monkey (Ateles paniscus), densities of dispersed and non-dispersed seeds, and direct estimates of seed dispersal distances. Our model demonstrated that the spatial scale of dispersal for this V. calophylla population was large, as spider monkeys routinely dispersed seeds >100 m, a commonly used threshold for long-distance dispersal. The simulated seed shadow was heterogeneous, with high spatial variance in seed density resulting largely from behaviors and movement patterns of spider monkeys that aggregated seeds (dispersal at their sleeping sites) and that scattered seeds (dispersal during diurnal foraging and resting). The single-distribution dispersal kernels frequently used to model dispersal substantially underestimated this variance and poorly fit the simulated seed-dispersal curve, primarily because of its multimodality, and a mixture distribution always fit the simulated dispersal curve better. Both seed shadow heterogeneity and dispersal curve multimodality arose directly from these different dispersal processes generated by spider monkeys. Compared to models that did not account for disperser behavior, our modeling approach improved prediction of the seed shadow of this V. calophylla population. An important function of seed dispersal models is to use the seed shadows they predict to estimate components of plant demography, particularly seedling population dynamics and distributions. Our model demonstrated that improved seed shadow prediction for animal-dispersed plants can be accomplished by incorporating spatially explicit information on disperser behavior and movements, using scales large enough to capture routine long-distance dispersal, and using dispersal kernels, such as mixture distributions, that account for spatially aggregated dispersal.     

Population feedback after successful invasion leads to ecological suicide in seasonal environments

For most consumer species, winter represents a period of harsh food conditions in addition to the physiological strain that results from the low ambient temperatures. In size-structured populations, larger-bodied individuals do better during winter as they have larger energy reserves to buffer starvation periods. In contrast, smaller-bodied individuals do better under growing conditions, as they have lower maintenance costs. We study how the interplay between size-dependent life-history processes and seasonal changes in temperature and food availability shape the long-term dynamics of a size-structured consumer population and its unstructured resource. We show that the size dependence of maintenance requirements translates into a minimum body size that is needed for surviving starvation when consumers can adapt only to a limited extent to the low food densities in winter. This size threshold can lead to population extinction because adult individuals suffer only a little during winter and hence produce large numbers of offspring. Due to population feedback on the resource and intense intra-cohort competition, newborn consumers then fail to reach the size threshold for survival. Under these conditions, small numbers of individuals can survive, increase in density, and build up a population, which will subsequently go extinct due to its feedback on the resource. High juvenile mortality may prevent this ecological suicide from occurring, as it releases resource competition among newborns and speeds up their growth. In size-structured populations, annual fluctuations in temperature and food availability may thus lead to a conflict between individual fitness and population persistence.     

Factors Influencing Movement Patterns of Keel-Billed Toucans in a Fragmented Tropical Landscape in Southern Mexico

Abstract: Various factors influence animal movements in fragmented landscapes, and determining these factors is key to understanding ecological processes at a landscape scale. My goals were (1) to determine what factors influence movements of Keel-billed Toucans (    Ramphastos sulfuratus ) in a fragmented landscape in southern Mexico and (2) to use this information to predict how movement patterns might change if the landscape was altered. I developed a cost-distance geographic information system model that adjusts Euclidean distances by a cost of moving through a certain habitat type. Cost was based on habitat preferences exhibited by toucans. I then used this model to predict how movements might be affected by removal of isolated trees and living fences from the pasture matrix and by removal of forest remnants. Toucans moved more frequently between remnants separated by a low cost-distance value. There was a cost-distance threshold beyond which movements between remnants were rare. Below this threshold, fruit abundance influenced toucan movements but remnant area was not influential in that toucans did not preferentially move to large patches. Remnants close to various other remnants were more frequently visited by toucans, indicating that landscape connectivity influences toucan movements. Toucans incurred a 10–30% cost increase when moving in computer-simulated landscapes, indicating that changes in forest cover or configuration of habitats may negatively affect toucan populations, assuming that increased cost has a fitness consequence. Cost-distance modeling has been relatively unexplored and may be a valuable tool for determining how the configuration of a landscape impedes or facilitates animal movements.     

How humans shape wolf behavior in Banff and Kootenay National Parks, Canada

This paper describes the conceptualization and implementation of an agent-based model to investigate how varying levels of human presence could affect elements of wolf behavior, including highway crossings; use of areas in proximity to roads and trails; size of home ranges; activities, such as hunting, patrolling, resting, and feeding pups; and survival of individuals in Banff and Kootenay National Parks, Canada. The model consists of a wolf module as the primary component with five packs represented as cognitive agents, and grizzly bear, elk, and human modules that represent dynamic components of the environment. A set of environmental data layers was used to develop a friction model that serves as a base map representing the landscape over which wolves moved. A decision model was built to simulate the sequence of wolf activities. The model was implemented in a Java Programming Language using RePast, an agent-based modeling library. Six months of wolf activities were simulated from April 16 to October 15 (i.e., a season coherent with regard to known wolf behaviors), and calibrated with GPS data from wolf radiocollars (n = 15) deployed from 2002 to 2004. Results showed that the simulated trajectories of wolf movements were correlated with the observed trajectories (Spearman's rho 0.566, P < 0.001); other critical behaviors, such as time spent at the den and not traveling were also correlated. The simulations revealed that wolf movements and behaviors were noticeably affected by the intensity of human presence. The packs’ home ranges shrank and wolves crossed highways less frequently with increased human presence. In an extreme example, a wolf pack whose home range is traversed by a high-traffic-volume highway was extirpated due to inability to hunt successfully under a scenario wherein human presence levels were increased 10-fold. The modeling prototype developed in this study may serve as a tool to test hypotheses about human effects on wolves and on other mammals, and guide decision-makers in designing management strategies that minimize impacts on wolves and on other species functionally related to wolves in the ecosystem.