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1,068 results for “demographic”
Figure 4 in Modeling Demographic Response to Constant Temperature inBryobia rubrioculus (Acari: Tetranychidae)
Figure 4.Age–specific survival rate (lx), female age–specific fecundity (fx8), age–specific fecundity (mx), and agespecific maternity (lxmx) ofB. rubrioculusat five constant temperatures.
Figure 2 in Modeling Demographic Response to Constant Temperature inBryobia rubrioculus (Acari: Tetranychidae)
Figure 2.Observed Age-specific survival rate (lx) and Observed age–specific fecundity (mx) ofBryobia rubrioculus at five constant temperatures fitted to the Weibull's and Polynomial's estimates respectively.
Figure 3 in Modeling Demographic Response to Constant Temperature inBryobia rubrioculus (Acari: Tetranychidae)
Figure 3.Age–stage specific survival rate (sxj) ofBryobia rubrioculus at five constant temperatures.
Data from: Partitioning variance in population growth for models with environmental and demographic stochasticity
<ol> <li>How demographic factors lead to variation or change in growth rates can be investigated using life table response experiments (LTRE) based on structured population models. Traditionally, LTREs focused on decomposing the asymptotic growth rate, but more recently decompositions of annual 'realized' growth rates have gained in popularity.</li> <li>Realized LTREs have been used particularly to understand how variation in vital rates translates into variation in growth for populations under long-term study. For these, complete population models may be constructed by combining data in an integrated population model (IPM). IPMs are also used to investigate how temporal variation in environmental drivers affect vital rates. Such investigations have usually come down to estimating covariate coefficients for the effects of environmental variables on vital rates, but formal ways of assessing how they lead to variation in growth rates have been lacking. </li> <li>We extend realized LTREs in two ways. First, we further partition the contributions from vital rates into contributions from temporally varying factors that affect them. The decomposition allows us to compare the resultant effect on the growth rate of different environmental factors that may each act via multiple vital rates. Second, we show how realized growth rates can be decomposed into separate components from environmental and demographic stochasticity. The latter is typically omitted in LTRE analyses.</li> <li>We illustrate how to use the approach in an IPM for data from a 26-year study on northern wheatears (Oenanthe oenanthe), a migratory passerine bird breeding in an agricultural landscape. For this population, consisting of around 50–120 breeding pairs per year, we partition variation in realized growth rates into environmental contributions from temperature, rainfall, population density, and unexplained random variation via multiple vital rates, and from demographic stochasticity.</li> <li>The case study suggests that variation in first-year survival via the random component, and adult survival via temperature are two main factors behind environmental variation in growth rates. More than half of the variation in growth rates is suggested to come from demographic stochasticity, demonstrating the importance of this factor for populations of moderate size.</li> </ol>
Consequences of cross-season demographic correlations for population viability
<p class="MsoNormal"><span>Demographic correlations are pervasive in wildlife populations and can represent important secondary drivers of population growth. Empirical evidence suggests that correlations are in general positive for long-lived species, but little is known about the degree of variation among spatially segregated populations of the same species in relation to environmental conditions. We assessed the relative importance of two cross-season correlations in survival and productivity, for three Atlantic puffin</span><span> (</span><span><em>Fratercula</em> <em>arctica</em></span><span>) </span><span>populations with contrasting population trajectories and non-overlapping year-round distributions. The two correlations reflected either a relationship between adult survival prior to breeding on productivity or a relationship between productivity and adult survival in the subsequent year. Demographic rates and their correlations were estimated with an integrated population model, and their respective contributions to variation in population growth were calculated using a transient life table response experiment. For all three populations, demographic correlations were positive at both time lags, although their strength differed. Given the difference in year-round distributions of these populations, this variation in the strength of population-level demographic correlations points to environmental conditions as an important driver of demographic variation through life-history constraints. Consequently, the contributions of variances and correlations in demographic rates to population growth rates differed among puffin populations, which has implications for – particularly small – populations' viability under environmental change as positive correlations tend to reduce the stochastic population growth rate.</span></p>
Population demographic history and evolutionary rescue: Influence of a bottleneck event
<p class="p1">Rapid environmental change presents a significant challenge to the persistence of natural populations. Rapid adaptation that increases population growth, enabling populations that declined following severe environmental change to grow and avoid extinction, is called evolutionary rescue. Numerous studies have shown that evolutionary rescue can indeed prevent extinction. Here, we extend those results by considering the demographic history of populations. To evaluate how demographic history influences evolutionary rescue, we created 80 populations of red flour beetle, <em>Tribolium castaneum</em>, with three classes of demographic history: diverse populations that did not experience a bottleneck, and populations that experienced either an intermediate or a strong bottleneck. We subjected these populations to a new and challenging environment for six discrete generations and tracked extinction and population size. Populations that did not experience a bottleneck in their demographic history avoided extinction entirely, while more than 20% of populations that experienced an intermediate or strong bottleneck went extinct. Similarly, among the extant populations at the end of the experiment, adaptation increased the growth rate in the novel environment the most for populations that had not experienced a bottleneck in their history. Taken together, these results highlight the importance of considering the demographic history of populations to make useful and effective conservation decisions and management strategies for populations experiencing environmental change that pushes them toward extinction.</p>
SOCIOECONOMIC, DEMOGRAPHIC AND ENVIRONMENTAL FACTORS AND COVID - 19 VACCINATION: INTERACTIONS AFFECTING EFFECTIVENESS
<p>This study analyses the relation between people fully vaccinated and mortality to assess the effectiveness of this health policy to cope with COVID-19 pandemic between a sample of 150 countries. Statistical analyses show a positive correlation between share of people fully vaccinated and total COVID-19 mortality in early 2022 (r= 0.65, p-value <.01). These results suggest that COVID-19 vaccinations cannot be a sufficient policy response to eradicate the overall negative impact of the new infectious disease in society. Although high levels of vaccinations in some countries, many demographic (density of population), environmental (air pollution), technological (equipment of non-invasive ventilators), biological (new variants), socioeconomic (health expenditures) factors, etc., influence the diffusion and negative effects of COVID-19 pandemic society. This study can provide new knowledge to improve crisis management and the preparedness of countries to cope with or prevent future pandemic crisis and negative effects in socioeconomic systems.</p>
Sample data for analysis of demographic potential of the 15-minute city in northern and southern France
<pre>This upload contains two Geopackage files of raw data used for urban analysis in the outskirts of Lille and Nice, France. <br>The data include building footprints (layer "building"), roads (layer "road"), and administrative boundaries (layer "adm_boundaries")<br>extracted from version 3.3 of the French dataset BD TOPO®3 (IGN, 2023) for the municipalities of Santes, Hallennes-lez-Haubourdin,<br>Haubourdin, and Emmerin in northern France (Geopackage "DPC_59.gpkg") and Drap, Cantaron and La Trinité in southern France <br>(Geopackage "DPC_06.gpkg").</pre> <pre> </pre> <pre>Metadata for these layers is available here: https://geoservices.ign.fr/sites/default/files/2023-01/DC_BDTOPO_3-3.pdf</pre> <pre> </pre> <pre>Additionally, this upload contains the results of the following algorithms available in GitHub (<a href="https://github.com/perezjoan/emc2-WP2?tab=readme-ov-file">https://github.com/perezjoan/emc2-WP2?tab=readme-ov-file</a>)</pre> <pre><code> </code></pre> <pre>1. The<code> </code>identification<code> </code>of<code> </code>main<code> </code>streets using the QGIS plugin Morpheo (layers "road_morpheo" and "buffer_morpheo") <br><a href="https://plugins.qgis.org/plugins/morpheo/">https://plugins.qgis.org/plugins/morpheo/</a> </pre> <pre><code>2. </code>The<code> </code>identification of main streets in local contexts – connectivity locally weighted<code> </code>(layer "road_LocRelCon")</pre> <pre><code>3. </code>Basic morphometry<code> </code>of<code> </code>buildings<code> </code>(layer "building_morpho")</pre> <pre><code>4. </code>Evaluation<code> </code>of<code> </code>the<code> </code>number<code> </code>of<code> </code>dwellings<code> </code>within<code> </code>inhabited<code> </code>buildings<code> </code>(layer "building_dwellings")</pre> <pre>5. Projecting<code> </code>population<code> </code>potential<code> </code>accessible from<code> </code>main<code> </code>streets<code> </code>(layer "road_pop_results")</pre> <pre> </pre> <pre>Project website: <a href="http://emc2-dut.org/">http://emc2-dut.org/</a></pre> <pre> </pre> <pre>Publications using this sample data: <br>Perez, J. and Fusco, G., 2024. Potential of the 15-Minute Peripheral City: Identifying Main Streets and Population Within Walking Distance. In: O. Gervasi, B. Murgante, C. Garau, D. Taniar, A.M.A.C. Rocha and M.N. Faginas Lago, eds. <em>Computational Science and Its Applications – ICCSA 2024 Workshops. ICCSA 2024</em>. Lecture Notes in Computer Science, vol 14817. Cham: Springer, pp.50-60. <a href="https://doi.org/10.1007/978-3-031-65238-7_4" target="_blank" rel="noopener noreferrer">https://doi.org/10.1007/978-3-031-65238-7_4</a>.</pre> <p><strong>Acknowledgement.</strong> <a name="_Hlk162443883"></a>This work is part of the emc2 project, which received the grant ANR-23-DUTP-0003-01 from the French National Research Agency (ANR) within the DUT Partnership.</p>
Data from: Non-native grazers affect physiological and demographic responses of Greater Sage-grouse
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Phylogenetic conservatism in the relationship between functional and demographic characteristics in Amazon tree taxa
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Population genomics reveals demographic history and climate adaptation in Japanese Arabidopsis halleri
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Consequences of cross-season demographic correlations for population viability
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Data from: Successional shifts in tree demographic strategies in wet and dry Neotropical forests
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Data from: Genetic diversity in a long-lived mammal is explained by the past’s demographic shadow and current connectivity
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Data from: Ability of seedlings to survive heat and drought portends future demographic challenges for five southwestern US conifers
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Data from: Global spatiotemporal patterns of demographic fluctuations in terrestrial vertebrates during the Late Pleistocene
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Seasonal rainfall in subtropical montane cloud forests drives demographic fluctuations in a Green-backed Tit population
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Data from: Evolutionary and demographic history of the Californian scrub white oak species complex: an integrative approach
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Data from: Demographic expansion and panmixia in a St. Martin endemic, Anolis pogus, coincides with the decline of a competitor
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Data for the manuscript: Demographic basis of spatially structured fluctuations in a threespine stickleback metapopulation
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Allen Brain Atlas
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