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544 results for “life-history”
Figure 1 in Unraveling distributional patterns and life-history traits of a deep-water shrimp Plesionika edwardsii (Decapoda, Pandalidae) under unexploited virgin conditions: a benchmark for fisheries management
Figure 1. Sampling areas of Plesionika edwardsii in the mid-North Atlantic Ocean, Azorean region (ICES Subdivision 10a2) between 1999 and 2000. Orange dots represent each site sampled by a trap.
Figure 6 in Unraveling distributional patterns and life-history traits of a deep-water shrimp Plesionika edwardsii (Decapoda, Pandalidae) under unexploited virgin conditions: a benchmark for fisheries management
Figure 6. Sex ratio of Plesionika edwardsii by size class in the Azorean region during the period 1999–2000.
Figure 3 in Unraveling distributional patterns and life-history traits of a deep-water shrimp Plesionika edwardsii (Decapoda, Pandalidae) under unexploited virgin conditions: a benchmark for fisheries management
Figure 3. Size frequency distribution of males, non-ovigerous and ovigerous females Plesionika edwardsii in the Azorean region during the period 1999-2000.
Landscape composition and life-history traits influence bat movement and space use: analysis of 30 years of published telemetry data
<p>Using temperate bats, a group of particular conservation concern, we investigated how morphological traits, habitat specialization and environmental variables affect home range sizes and daily foraging movements, using a compilation of 30 years of published bat telemetry data in Northern America and Europe for the period 1988 – 2016.</p> <p>We compiled data on home range size and mean daily distance between roosts and foraging areas at both colony and individual levels from 166 studies of 3,129 radiotracked individuals of 49 bat species. We calculated multi-scale habitat composition and configuration in the surrounding landscapes of all studied roosts. Using mixed models, we examined the effects of habitat availability and spatial arrangement on bat movements, while accounting for body mass, aspect ratio, wing loading and habitat specialization.</p> <p>We found a significant effect of landscape composition on home range size and mean daily distance at both colony and individual levels. On average, home ranges were up to 42% smaller in the most habitat-diversified landscapes while mean daily distances were up to 30% shorter in the most forested landscapes. Bat home range size significantly increased with body mass, wing aspect ratio and wing loading, and decreased with habitat specialization.</p>
Data and custom codes from "Rapid evolution in salmon life-history induced by direct and indirect effects of fishing"
<p>Data and custom codes from Czorlich, Y., Aykanat, T., Erkinaro, J., Orell, P. & Primmer, C.R. (2021) <em>Rapid evolution in salmon life-history induced by direct and indirect effects of fishing. </em>Science.</p> <p><strong>Codes:</strong></p> <p>The R file "Fishing_effort_parallel.R" was used to estimate fishing effort/intensity (beta in equation 8) given the length distribution, the gear-specific catchability and harvest rate</p> <p>"Fishing_selection_estimate.R" was used to estimate fishery-induced selection at <em>vgll3.</em></p> <p><strong>Datasets:</strong></p> <p>Genetic_phenotypic_data.xlsx: Genetic and phenotypic data about salmon from the Teno mainstem population</p> <p>sonar_data.xlsx: Number of salmon per length class entering the river in 2018 and 2019. The length classes of salmon caught in those years by one of the fishing methods are also included</p> <p>annual_catch_data.xlsx: Total mass (kg) of salmon caught by each fishing method between 1975 to 2014.</p> <p>Environmental_data.xlsx: Data about Barents Sea temperature, biomass of key species, fishing data</p> <p>individual_weight_salmon_catches.xlsx: Individual weight of salmon caught with different fishing gears in the last decades</p> <p><strong>Data sources:</strong></p> <p>- Genetic data (Tenojoki population, random sampling): From Czorlich et al. 2018, https://datadryad.org/stash/dataset/doi:10.5061/dryad.7hm4708</p> <p>- Data about krill biomass (1980 – 2013) were taken from (<em>1</em>, <em>2</em>).</p> <p>- Capelin biomass estimated from acoustic survey and the landed capelin catches were derived from (<em>3</em>) for 1973 – 2013.</p> <p>- Herring biomass data were retrieved from (<em>4</em>) for the 1973-1998 period. Herring biomass was calculated from the number of 1-2 year old herring and the mean weight per age as reported in (<em>3</em>) for 1988 – 2013.</p> <p>- The annual biomass of cod (a predator of forage fish) was derived from VPA analyses ((<em>5</em>), table 3.24). Landed cod biomass was also taken from (<em>5</em>).</p> <p>- An index for mesozooplankton (a forage fish food source) corresponding to the sum of <em>Calanus</em> biomass indices from different parts of the Barents Sea was used (<em>6</em>).</p> <p>- The annual sea temperature in the Kola section of the Barents Sea measured in the upper 200 meters was from <a href="http://www.pinro.vniro.ru/">pinro.vniro.ru</a></p> <p>- The total number of nets used to catch salmon in the Finnmark coastal region was calculated for each year using data from (7)</p> <p>- Other data were generated for this study, please check the Material and Methods. </p> <p><em>References:</em></p> <p>1. E. Eriksen, P. Dalpadado, Long-term changes in Krill biomass and distribution in the Barents Sea: Are the changes mainly related to capelin stock size and temperature conditions? <em>Polar Biology</em>. <strong>34</strong>, 1399–1409 (2011).</p> <p>2. ICES, “Report of the Working Group on the Integrated Assessments of the Barents Sea. ICES CM 2017/SSGIEA:04. 186 pp.” (2017).</p> <p>3. ICES, “Report of the Arctic Fisheries Working Group (AFWG). ICES CM 2015/ACOM:05. 639 pp.” (2015).</p> <p>4. R. Toresen, O. J. Østvedt, Variation in abundance of Norwegian spring-spawning herring (Clupea harengus, Clupeidae) throughout the 20th century and the influence of climatic fluctuations. <em>Fish and Fisheries</em>. <strong>85</strong>, 385–391 (2000).</p> <p>5. ICES, “Report of the Arctic Fisheries Working Group (AFWG). ICES CM 2016/ACOM:06. 621 pp.” (2016).</p> <p>6. L. C. Stige et al., Spatiotemporal statistical analyses reveal predator-driven zooplankton fluctuations in the Barents Sea. <em>Progress in Oceanography</em>. <strong>120</strong>, 243–253 (2014).</p> <p>7. E. Niemelä, T. Kalske, E. Hassinen, “Numbers of fishing gears used in Kolarctic salmon project area, numbers of allowed sites for salmon fishing and numbers of salmon fishermen in Finnmark; development until the year 2013” (2013).</p>
Data for Contrasting life-history responses to climate variability in eastern and western North Pacific sardine populations
<p><span>Massive populations of sardines inhabit both the western and eastern boundaries of the world's subtropical ocean basins, supporting both commercial fisheries and populations of marine predators. Sardine populations in western and eastern boundary current systems have responded oppositely to decadal scale anomalies in ocean temperature, but the mechanism for differing variability has remained unclear. Here, based on otolith microstructure and high-resolution stable isotope analyses, we show that habitat temperature, early life growth rates, energy expenditure, metabolically optimal temperature and, most importantly, the relationship between growth rate and temperature were remarkably different between the two subpopulations in the western and eastern North Pacific. Varying metabolic response to environmental changes partly explain the contrasting growth responses. Consistent differences in the life-history traits are observed between subpopulations in the western and eastern boundary current systems around South Africa. These growth and survival characteristics can facilitate the contrasting responses of sardine populations to climate change.</span></p>
Data from: Weedy and seedy: The rapid evolution of life-history characteristics in an introduced daisy
<p>Despite the importance of life-history characteristics in determining a species' success, we still lack basic information about some fundamental life-history elements found across the life cycle of introduced plants. Our study assesses rapid evolutionary divergence in life-history characteristics of the beach daisy, <em>Arctotheca populifolia,</em> by comparing introduced Australian and source South African plants and measuring eight key variables including seed mass, germination, reproductive output and survival. This is the first study that compares the life history of an introduced plant species with its single original source population, providing a precise and powerful method for detecting evolutionary divergence. We found that introduced <em>A. populifolia</em> has evolved a suite of weedy life-history characteristics in less than 90 years: the introduced plants use a live-fast die-young strategy of germination and survival and produce significantly more inflorescences and more seeds that germinate faster. This knowledge adds to the remarkable data that we already have on the rapid evolutionary divergence occurring in the morphology, physiology and defence of this introduced plant and highlights the speed and scope of evolutionary divergence possible in plants. To fully understand and manage the future of our plant species, we must consider their potential for ongoing change in key aspects of life history.</p>
Fig. 1. A in Agricultural Trichothecene Mycotoxin Contamination Affects The Life-History And Reduced Glutathione Content Of Folsomia Candida Willem (Collembola)
Fig. 1. A relative growth of Folsomia candida on the relation of the contaminated food; significant difference in mean B. Total reproduction of Folsomia candida in the contaminated
Fig. 1 in Life-History Characteristics Of The Ground Beetle Carabus Scheidleri (Coleoptera: Carabidae) In Hungary
Fig. 1. Seasonal activity of C. scheidleri individuals at Nagykovácsi, Central Hungary in 2001 and in 2002. The arrows [narrow arrows in 2002] denote the main activity period (left and right arrows) and activity peak (middle arrow). (Different letters indicate significant (p<0.05) differences within the given years by post-hoc Fisher LSD test.) Repeated measures ANOVA between the years: [F (1; 63)
Figure 1 in Accounting for variability in life-history traits for the definition of amphidromous goby fry fisheries closure periods
Figure 1. – Ranking of the 4096 alternatives of fisheries closure periods based on the MULTIMOORA analysis on the abundance and life-history traits of Sicyopterus lagocephalus and Cotylopus acutipinnis. The best alternative is ranked 1 and the worst 4096. Fisheries closure periods are colour coded.
Fig. 2 in What drives population-level effects of parasites? Meta-analysis meets life-history
Fig. 2. Funnel plot of effect size (Hedges' g) by standard error (SE). The white circles represent studies included in the meta-analysis. The black circles represent missing imputed studies. The white diamond represents overall effect size as calculated in the meta-analysis, and the black diamond represents the corrected effect size.
Fig. 1 in What drives population-level effects of parasites? Meta-analysis meets life-history
Fig. 1. Forest plot of effect sizes (rectangles) and confidence intervals (bars) for each study and the effect averaged across all studies (diamond).
Fig. 3. A in What drives population-level effects of parasites? Meta-analysis meets life-history
Fig. 3. A meta-regression (random effects model) of effect size against host average lifespan using the complete dataset (n = 60). The slope of this regression is significant (p = 0.05).
Fig. 3 in Adaptations, life-history traits and ecological mechanisms of parasites to survive extremes and environmental unpredictability in the face of climate change
Fig. 3. Flow chart outlining factors that can influence the response of parasites to climate change.
Fig. 2. Predicted probabilities and 95 in Is it best on the nest? Effects of avian life-history on haemosporidian parasitism
Fig. 2. Predicted probabilities and 95% confidence intervals of haemosporidian parasitism (Plasmodium, Haemoproteus, and Leucocytozoon). Expected prevalence illustrated according to haemosporidia genera; Plasmodium represented with "P" (a), Haemoproteus represented with "H" (b–c), Leucocytozoon represented with "L" (d–f). Note that in some instances symbol size exceeded the range of confidence intervals.
Slower environmental cycles maintain greater life-history variation within populations
<p>Populations in nature are comprised of individual life histories, whose variation underpins ecological and evolutionary processes. Yet the forces of environmental selection that shape intrapopulation life-history variation are still not well understood, and efforts have largely focused on random (stochastic) fluctuations of the environment. However, a ubiquitous mode of environmental fluctuation in nature is cyclical, whose periodicities can change independently of stochasticity. Here we test theoretically-based hypotheses for whether shortened ('Fast') or lengthened ('Slow') environmental cycles should generate higher intrapopulation variation of life history phenotypes. We show, through a combination of individual-based modelling and a multi-generational laboratory selection experiment using the tidepool copepod Tigriopus californicus, that slower environmental cycles maintain higher levels of intrapopulation variation. Surprisingly, the effect of environmental periodicity on variation was much stronger than that of stochasticity. Thus, our results show that periodicity is an important facet of fluctuating environments for life-history variation.</p>
Figure 2 in Fly parasitism in Papuan frogs, with a discussion of ecological factors influencing evolution of life-history differences
Figure 2. Regressions of weight versus snout–vent length (SV) for male Rana supragrisea. Larger frogs infested with fly larvae (closed squares, dashed line) exhibit lower weights compared to uninfested frogs (open circles, solid line), but this difference in regressions is determined solely by the largest infested specimen.
Figure 2 in Female life-history characteristics of the Mosor rock lizard, Dinarolacerta mosorensis (Kolombatović, 1886) from Montenegro (Squamata: Lacertidae)
Figure 2. The relationships between clutch size and maternal SVL of Dinarolacerta mosorensis from the three different populations.
Figure 1 in Female life-history characteristics of the Mosor rock lizard, Dinarolacerta mosorensis (Kolombatović, 1886) from Montenegro (Squamata: Lacertidae)
Figure 1. The relationship between age and female SVL of Dinarolacerta mosorensis from the Lovćen population.
Fig. 4 in Life-history of the South American darter, Characidium pterostictum (Crenuchidae): evidence for small scale spatial variation in a piedmont stream
Fig. 4. Seasonal variation in proportion (%) of maturity stages for Characidium pterostictum at Lajeado river (southern Brazil). Values for PA and PB were pooled.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.