1,865 research outputs found

    Effects of wind energy development on nesting ecology of Greater Prairie-Chickens in fragmented grasslands

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    Wind energy is targeted to meet 20% of U.S. energy needs by 2030, but new sites for development of renewable energy may overlap with important habitats of declining populations of grassland birds. Greater Prairie-Chickens (Tympanuchus cupido) are an obligate grassland bird species predicted to respond negatively to energy development. We used a modified before–after control–impact design to test for impacts of a wind energy development on the reproductive ecology of prairie-chickens in a 5-year study. We located 59 and 185 nests before and after development, respectively, of a 201 MW wind energy facility in Greater Prairie-Chicken nesting habitat and assessed nest site selection and nest survival relative to proximity to wind energy infrastructure and habitat conditions. Proximity to turbines did not negatively affect nest site selection (β = 0.03, 95% CI = −1.2–1.3) or nest survival (β = −0.3, 95% CI = −0.6–0.1). Instead, nest site selection and survival were strongly related to vegetative cover and other local conditions determined by management for cattle production. Integration of our project results with previous reports of behavioral avoidance of oil and gas facilities by other species of prairie grouse suggests new avenues for research to mitigate impacts of energy development

    A multiscale analysis of gene flow for the New England cottontail, an imperiled habitat specialist in a fragmented landscape

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    Landscape features of anthropogenic or natural origin can influence organisms\u27 dispersal patterns and the connectivity of populations. Understanding these relationships is of broad interest in ecology and evolutionary biology and provides key insights for habitat conservation planning at the landscape scale. This knowledge is germane to restoration efforts for the New England cottontail (Sylvilagus transitionalis), an early successional habitat specialist of conservation concern. We evaluated local population structure and measures of genetic diversity of a geographically isolated population of cottontails in the northeastern United States. We also conducted a multiscale landscape genetic analysis, in which we assessed genetic discontinuities relative to the landscape and developed several resistance models to test hypotheses about landscape features that promote or inhibit cottontail dispersal within and across the local populations. Bayesian clustering identified four genetically distinct populations, with very little migration among them, and additional substructure within one of those populations. These populations had private alleles, low genetic diversity, critically low effective population sizes (3.2-36.7), and evidence of recent genetic bottlenecks. Major highways and a river were found to limit cottontail dispersal and to separate populations. The habitat along roadsides, railroad beds, and utility corridors, on the other hand, was found to facilitate cottontail movement among patches. The relative importance of dispersal barriers and facilitators on gene flow varied among populations in relation to landscape composition, demonstrating the complexity and context dependency of factors influencing gene flow and highlighting the importance of replication and scale in landscape genetic studies. Our findings provide information for the design of restoration landscapes for the New England cottontail and also highlight the dual influence of roads, as both barriers and facilitators of dispersal for an early successional habitat specialist in a fragmented landscape

    Autonomous clustering using rough set theory

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    This paper proposes a clustering technique that minimises the need for subjective human intervention and is based on elements of rough set theory. The proposed algorithm is unified in its approach to clustering and makes use of both local and global data properties to obtain clustering solutions. It handles single-type and mixed attribute data sets with ease and results from three data sets of single and mixed attribute types are used to illustrate the technique and establish its efficiency

    Early Evidence of Natal-Habitat Preference: Juvenile Loons Feed on Natal-Like Lakes After Fledging

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    Many species show natal habitat preference induction (NHPI), a behavior in which young adults select habitats similar to those in which they were raised. However, we know little about how NHPI develops in natural systems. Here, we tested for NHPI in juvenile common loons (Gavia immer) that foraged on lakes in the vicinity of their natal lake after fledging. Juveniles visited lakes similar in pH to their natal lakes, and this significant effect persisted after controlling for spatial autocorrelation. On the other hand, juveniles showed no preference for foraging lakes of similar size to their natal one. When lakes were assigned to discrete classes based on size, depth, visibility, and trophic complexity, both juveniles from large lakes and small lakes preferred to visit large, trophically diverse lakes, which contained abundant food. Our results contrast with earlier findings, which show strict preference for lakes similar in size to the natal lake among young adults seeking to settle on a breeding lake. We suggest that NHPI is relaxed for juveniles, presumably because they select lakes that optimize short‐term survival and growth. By characterizing NHPI during a poorly studied life stage, this study illustrates that NHPI can take different forms at different life stages

    Individual responses to novel predation risk and the emergence of a landscape of fear

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    Elucidating changes in prey behavior in response to a novel predator is key to understanding how individuals acclimate to shifting predation regimes. Such responses are predicted to vary among individuals as a function of the level of risk to which individuals are exposed, temporal changes in risk, and landscape‐mediated changes in perceived risk. We tested how GPS‐tracked moose (Alces alces, n = 19) responded to an emerging risk landscape with the introduction of hunting to a naïve population (large‐scale reduction experiment in Gros Morne National Park, Canada). We predicted that predation risk associated with hunters would influence moose habitat selection: Avoidance responses would be stronger during the day when hunting was allowed, and moose would learn to avoid risky locations which would strengthen in successive years for survivors occupying overall riskier home ranges. We found that moose avoided areas associated with a high risk of encounters with hunters but did not alter selection patterns between day and night. We did not find evidence of moose reacting more strongly to emerging risk as a function of risk within their home range. Moose did not increase their avoidance of areas associated with hunter risk across years but over time survivors selected non‐hunted refuge areas more frequently. Our results suggest that while moose did not adjust fine‐scale habitat selection through time to increased hunting risk, they did adjust selection at broader scales (based on proportions of hunter‐free habitat included in home range relative to study area). This finding supports the hypothesis that habitat selection at larger spatio‐temporal scales may reflect behavioral responses to a population’s most important limiting factors, which may not be apparent at finer scales

    Molecular and morphometric variation in European populations of the articulate brachiopod <i>Terebeatulina retusa</i>

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    Molecular and morphometric variation within and between population samples of the articulate brachiopod &lt;i&gt;Terebratulina&lt;/i&gt; spp., collected in 1985-1987 from a Norwegian fjord, sea lochs and costal sites in western Scotland, the southern English Channel (Brittany) and the western Mediterranean, were measured by the analysis of variation in the lengths of mitochondrial DNA (mtDNA) fragments produced by digestion with nine restriction endonucleases and by multivariate statistical analysis of six selected morphometric parameters. Nucleotide difference within each population sample was high. Nucleotide difference between population samples from the Scottish sites, both those that are tidally contiguous and those that appear to be geographically isolated, were not significantly different from zero. Nucleotide differences between the populations samples from Norway, Brittany, Scotland and the western Mediterranean were also very low. Morphometric analysis confirmed the absence of substantial differentiation

    Sea temperature effects on depth use and habitat selection in a marine fish community

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    Understanding the responses of aquatic animals to temperature variability is essential to predict impacts of future climate change and to inform conservation and management. Most ectotherms such as fish are expected to adjust their behaviour to avoid extreme temperatures and minimize acute changes in body temperature. In coastal Skagerrak, Norway, sea surface temperature (SST) ranges seasonally from 0 to over 20°C, representing a challenge to the fish community which includes cold-, cool- and warm-water affinity species.publishedVersio

    Net displacement and temporal scaling: Model fitting, interpretation and implementation

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    Net displacement is an integral component of numerous ecological processes and is critically dependent on the tortuosity of a movement trajectory and hence on the temporal scale of observation. Numerous attempts have been made to quantitatively describe net displacement while accommodating tortuosity, typically evoking a power law, but scale‐dependency in tortuosity limits the utility of approaches based on power law relationships that must assume scale‐invariant tortuosity. We describe a phenomenological model of net displacement that permits both scale‐variant and scale‐invariant movement. Movement trajectories are divided into pairs of relocations specifying start‐ and end‐points, and net displacements between points are calculated across a vector of time intervals. A bootstrap is implemented to create new datasets that are independent both across and within time intervals, and the model is fitted to the bootstrapped dataset using log–log regression. We apply this model to simulated trajectories and both fine‐grain and coarse‐grain trajectories obtained from an Aldabra giant tortoise Aldabrachelys gigantea, African elephants Loxodonta africana, black‐backed jackals Canis mesomelas and Northern elephant seals Mirounga angustirostris. The model was able to quantify the characteristics of net displacement from simulated movement trajectories corresponding to both scale‐variant (e.g. correlated random walks) and scale‐invariant (e.g. random walk) movement models. Furthermore, the model produced identical outputs across time vectors corresponding to different intervals and absolute ranges of time for scale‐invariant models. The model characterized the tortoise as generally exhibiting long scale‐invariant steps, which was corroborated by visual comparison of model outputs to observed trajectories. Elephants, jackals and seals exhibited movement parameters consistent with their known movement behaviours (nomadism, territoriality and widely ranging searching). We describe how the model may be used to compare movements within and between species, for example by partitioning movement into scale‐variant and scale‐invariant components, and by calculating a unitless net displacement scaled to the basal movement capacities of an animal. We also identify several useful derived quantities and realistic parameter ranges and discuss how the model may be implemented in a variety of ecological studies

    The Importance of Correlations and Fluctuations on the Initial Source Eccentricity in High-Energy Nucleus-Nucleus Collisions

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    In this paper, we investigate various ways of defining the initial source eccentricity using the Monte Carlo Glauber (MCG) approach. In particular, we examine the participant eccentricity, which quantifies the eccentricity of the initial source shape by the major axes of the ellipse formed by the interaction points of the participating nucleons. We show that reasonable variation of the density parameters in the Glauber calculation, as well as variations in how matter production is modeled, do not significantly modify the already established behavior of the participant eccentricity as a function of collision centrality. Focusing on event-by-event fluctuations and correlations of the distributions of participating nucleons we demonstrate that, depending on the achieved event-plane resolution, fluctuations in the elliptic flow magnitude v2v_2 lead to most measurements being sensitive to the root-mean-square, rather than the mean of the v2v_2 distribution. Neglecting correlations among participants, we derive analytical expressions for the participant eccentricity cumulants as a function of the number of participating nucleons, \Npart,keeping non-negligible contributions up to \ordof{1/\Npart^3}. We find that the derived expressions yield the same results as obtained from mixed-event MCG calculations which remove the correlations stemming from the nuclear collision process. Most importantly, we conclude from the comparison with MCG calculations that the fourth order participant eccentricity cumulant does not approach the spatial anisotropy obtained assuming a smooth nuclear matter distribution. In particular, for the Cu+Cu system, these quantities deviate from each other by almost a factor of two over a wide range in centrality.Comment: 18 pages, 10 figures, submitted to PR
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