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10 results for “length history”
Marmot capture history data and growing season length data
<p>Seasonal environmental conditions shape the behavior and life history of virtually all organisms. Climate change is modifying these seasonal environmental conditions, which threatens to disrupt population dynamics. It is conceivable that climatic changes may be beneficial in one season but result in detrimental conditions in another because life-history strategies vary between these time periods. We analyzed the temporal trends in seasonal survival of yellow-bellied marmots (<em>Marmota</em> <em>flaviventer</em>) and explored the environmental drivers using a 40-y dataset from the Colorado Rocky Mountains (USA). Trends in survival revealed divergent seasonal patterns, which were similar across age-classes. Marmot survival declined during winter but generally increased during summer. Interestingly, different environmental factors appeared to drive survival trends across age-classes. Winter survival was largely driven by conditions during the preceding summer and the effect of continued climate change was likely to be mainly negative, whereas the likely outcome of continued climate change on summer survival was generally positive. This study illustrates that seasonal demographic responses need disentangling to accurately forecast the impacts of climate change on animal population dynamics. We were able to impute body mass for each individual twice during each year following their first capture using a similar approach to Ozgul et al. (2010) (for more details on the modeling procedure see SI Appendix within the main paper). Body mass measurements were log-transformed.</p>
Data set for the paper "What are the Effects of History Length and Age on Mining Software Change Impact?"
<p>Data set for the paper What are the Effects of History Length and Age on Mining Software Change Impact?<br> by Leon Moonen, Thomas Rolfsnes, David Binkley and Stefano di Alesio.<br> In Journal of Empirical Software Engineering (EMSE), 2018, Springer. https://doi.org/10.1007/s10664-017-9588-z<br> Available from https://evolveit.bitbucket.io/publications/emse2018/</p> <p>Please cite this work by referring to the corresponding journal publication (a preprint is included in this package).</p> <p>The goal of Software Change Impact Analysis is to identify artifacts (typically source-code files or individual methods therein) potentially affected by a change. Recently, there has been increased interest in <em>mining</em> software change impact based on evolutionary coupling. A particularly promising approach uses association rule mining to uncover potentially affected artifacts from patterns in the system’s change history. Two main considerations when using this approach are the <em>history length</em>, the number of transactions from the change history used to identify the impact of a change, and <em>history age</em>, the number of transactions that have occurred since patterns were last mined from the history. Although history length and age can significantly affect the quality of mining results, few guidelines exist on how to best select appropriate values for these two parameters.</p> <p>In this paper, we empirically investigate the effects of history length and age on the quality of change impact analysis using mined evolutionary coupling. Specifically, we report on a series of systematic experiments using three state-of-the-art mining algorithms that involve the change histories of two large industrial systems and 17 large open source systems. In these experiments, we vary the length and age of the history used to mine software change impact, and assess how this affects precision and applicability. Results from the study are used to derive practical guidelines for choosing history length and age when applying association rule mining to conduct software change impact analysis. </p>
Marmot capture history data and growing season length data
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Data from: Breeding season length and nest mortality drive cryptic life history variation in Dark-eyed Juncos (Junco hyemalis) breeding across a montane elevation gradient
The manner in which individual life history traits respond to the environment and to each other, and how these traits combine to form overall patterns of life history variation, remains poorly characterized in wild populations. We monitored breeding Dark-eyed Juncos (Junco hyemalis) across a 700-m elevational range. We compared breeding season length, temporal patterns of breeding activity, adult body size, clutch size, brood size, nestling quality, and nest mortality among elevations. We also compared environmental measures across the studied elevations to determine whether abiotic factors explained life history trait variation. We used 12 microsatellite loci to test for genetic differentiation in populations at different elevations. Finally, we constructed a computer simulation to evaluate the combined effects of observed variation in life history traits. We found differences among elevations in breeding season length and in patterns of reproductive timing, which did not match each other and which were not explained solely by abiotic factors. We found no differences among elevations in adult body size, clutch size, brood size, or nestling quality. Nest mortality increased significantly with elevation. Genetic differentiation was too low to define distinct subpopulations. The simulation suggested that differences in mortality, in combination with differences in breeding season length, contributed to substantial differences in reproductive success among elevations. Thus, although individual life history traits showed little evidence of variation in response to the environment or to each other and little genetic differentiation, variation in breeding season length and in nest mortality were potential drivers of substantial elevational variation in overall life history in this system. These results demonstrate that individual life history traits may vary substantially in their patterns of variation, and that some life history traits may have disproportionate effects on overall life history.
The force response of muscles to activation and length perturbations depends on length history
<p>Recent studies have demonstrated that muscle force is not determined solely by activation under dynamic conditions, and that length history has an important role in determining dynamic muscle force. Yet, the mechanisms for how muscle force is produced under dynamic conditions remain unclear. To explore how muscle force production is determined under dynamic conditions, we investigated the effects of muscle stiffness, activation, and length perturbations on muscle force. First, submaximal isometric contraction was established for whole soleus muscles. Next, the muscles were actively shortened at three velocities. During active shortening, we measured muscle stiffness at L<sub>0 </sub>and<sub> </sub>the force response to time-varying activation and length perturbations. We found that muscle stiffness increased with activation but decreased as shortening velocity increased. The slope of the relationship between maximum force and activation amplitude differed significantly among shortening velocities. Also, the intercept and slope of the relationship between length perturbation amplitude and maximum force decreased with shortening velocities. As shortening velocities were related with muscle stiffness, the results suggest that length history determines muscle stiffness and the history-dependent muscle stiffness influences the contribution of activation to muscle force and the contribution of length perturbations to muscle force. A three-parameter viscoelastic model that included a linear spring and linear damper in parallel with tunable history-dependent spring stiffness proportional to measured muscle stiffness predicted history-dependent muscle force with high accuracy. The results and simulations support the hypothesis that muscle force under dynamic conditions can be accurately predicted as the force response of a history-dependent viscoelastic material to length perturbations.</p>
The force response of muscles to activation and length perturbations depends on length history
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Data from: Breeding season length and nest mortality drive cryptic life history variation in Dark-eyed Juncos (Junco hyemalis) breeding across a montane elevation gradient
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FIGURE 3. Phobaeticus chani female holotype, body length 357 in The types of Phasmida in the Natural History Museum, London, UK
FIGURE 3. Phobaeticus chani female holotype, body length 357 mm.
Figureȱ 2.ȱ Graphȱ plottingȱ skullȱ max.ȱ widthȱ againstȱ totalȱ lengthȱ (billȱ tipȱ toȱ rearȱ ofȱ skull)ȱ forȱ skinsȱ ofȱ threeȱ species of Campephilus woodpecker in the NHMUK collection. Also shown are analogous measurements fromȱ theȱ unidentifiedȱ NHMUKȱ skeleton,ȱ forȱ whichȱ aȱ correctionȱ factorȱ upwardsȱ ofȱ 17.28%ȱ hasȱ beenȱ madeȱ to total skull length, to account for its missing rhamphotheca (see text for explanation), thereby making its measurements directly comparable with the others. in The conundrum of an overlooked skeleton referable to Imperial Woodpecker Campephilus imperialis in the collection of the Natural History Museum at Tring
Figureȱ 2.ȱ Graphȱ plottingȱ skullȱ max.ȱ widthȱ againstȱ totalȱ lengthȱ (billȱ tipȱ toȱ rearȱ ofȱ skull)ȱ forȱ skinsȱ ofȱ threeȱ species of Campephilus woodpecker in the NHMUK collection. Also shown are analogous measurements fromȱ theȱ unidentifiedȱ NHMUKȱ skeleton,ȱ forȱ whichȱ aȱ correctionȱ factorȱ upwardsȱ ofȱ 17.28%ȱ hasȱ beenȱ madeȱ to total skull length, to account for its missing rhamphotheca (see text for explanation), thereby making its measurements directly comparable with the others.
Data from: Links between parental life histories of wild salmon and the telomere lengths of their offspring
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