1,955 research outputs found
Effects of wind energy development on nesting ecology of Greater Prairie-Chickens in fragmented grasslands
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 beforeâafter controlâimpact 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 (ÎČ = 0.03, 95% CI = â1.2â1.3) or nest survival (ÎČ = â0.3, 95% CI = â0.6â0.1). 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
Individual responses to novel predation risk and the emergence of a landscape of fear
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 landscapeâmediated changes in perceived risk. We tested how GPSâtracked moose (Alces alces, n = 19) responded to an emerging risk landscape with the introduction of hunting to a naĂŻve population (largeâscale 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 nonâhunted refuge areas more frequently. Our results suggest that while moose did not adjust fineâscale habitat selection through time to increased hunting risk, they did adjust selection at broader scales (based on proportions of hunterâfree habitat included in home range relative to study area). This finding supports the hypothesis that habitat selection at larger spatioâtemporal scales may reflect behavioral responses to a populationâs most important limiting factors, which may not be apparent at finer scales
A multiscale analysis of gene flow for the New England cottontail, an imperiled habitat specialist in a fragmented landscape
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
Sea temperature effects on depth use and habitat selection in a marine fish community
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
Autonomous clustering using rough set theory
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
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 shortâterm 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
The Importance of Correlations and Fluctuations on the Initial Source Eccentricity in High-Energy Nucleus-Nucleus Collisions
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
lead to most measurements being sensitive to the root-mean-square, rather
than the mean of the 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
Net displacement and temporal scaling: Model fitting, interpretation and implementation
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 scaleâdependency in tortuosity limits the utility of approaches based on power law relationships that must assume scaleâinvariant tortuosity. We describe a phenomenological model of net displacement that permits both scaleâvariant and scaleâinvariant movement. Movement trajectories are divided into pairs of relocations specifying startâ and endâpoints, 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 logâlog regression. We apply this model to simulated trajectories and both fineâgrain and coarseâgrain trajectories obtained from an Aldabra giant tortoise Aldabrachelys gigantea, African elephants Loxodonta africana, blackâbacked 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 scaleâvariant (e.g. correlated random walks) and scaleâinvariant (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 scaleâinvariant models. The model characterized the tortoise as generally exhibiting long scaleâinvariant 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 scaleâvariant and scaleâinvariant 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
Elliptic Flow in Au+Au Collisions at RHIC
Elliptic flow is an interesting probe of the dynamical evolution of the dense
system formed in the ultrarelativistic heavy ion collisions at the Relativistic
Heavy Ion Collider (RHIC). The elliptic flow dependences on transverse
momentum, centrality, and pseudorapidity were measured using data collected by
the PHOBOS detector, which offers a unique opportunity to study the azimuthal
anisotropies of charged particles over a wide range of pseudorapidity. These
measurements are presented, together with an overview of the analysis methods
and a discussion of the results.Comment: Presented at Hot Quarks 2004; 7 pages, 6 figure
System size and centrality dependence of charged hadron transverse momentum spectra in Au+Au and Cu+Cu collisions at sqrt(s) = 62.4 and 200 GeV
We present transverse momentum distributions of charged hadrons produced in
Cu+Cu collisions at sqrt(s) = 62.4 and 200 GeV. The spectra are measured for
transverse momenta of 0.25 < p_T < 5.0 GeV/c at sqrt(s) = 62.4 GeV and 0.25 <
p_T < 7.0 GeV/c at sqrt(s) = 200 GeV, in a pseudo-rapidity range of 0.2 < eta <
1.4. The nuclear modification factor R_AA is calculated relative to p+p data at
both collision energies as a function of collision centrality. At a given
collision energy and fractional cross-section, R_AA is observed to be
systematically larger in Cu+Cu collisions compared to Au+Au. However, for the
same number of participating nucleons, R_AA is essentially the same in both
systems over the measured range of p_T, in spite of the significantly different
geometries of the Cu+Cu and Au+Au systems.Comment: 4 pages, 5 figures, submitted to Phys. Rev. Let
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