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26 results for “Integral Projection Models”
Integral projection model results of the planktonic foraminifer Trilobatus sacculifer
<p>Developmental plasticity, where traits change state in response to environmental cues, is well-studied in modern populations. It is also suspected to play a role in macroevolutionary dynamics, but due to a lack of long-term records the frequency of plasticity-led evolution in deep time remains unknown. Populations are dynamic entities, yet their representation in the fossil record is a static snapshot of often isolated individuals. Here, we apply for the first time contemporary integral projection models (IPMs) to fossil data to link individual development with expected population variation. IPMs describe the effects of individual growth in discrete steps on long-term population dynamics. We parameterize the models using modern and fossil data of the planktonic foraminifer <em>Trilobatus sacculifer</em>. Foraminifera grow by adding chambers in discrete stages and die at reproduction, making them excellent case studies for IPMs. Our results predict that somatic growth rates have almost twice as much influence on population dynamics than survival and more than eight times more influence than reproduction, suggesting that selection would primarily target somatic growth as the major determinant of fitness. As numerous palaeobiological systems record growth rate increments in single genetic individuals, and imaging technologies are increasingly available, our results open up the possibility of evidence-based inference of developmental plasticity spanning macroevolutionary dynamics. Given the centrality of ecology in palaeobiological thinking, our model is one approach to help bridge eco-evolutionary scales while directing attention towards the most relevant life-history traits to measure.</p>
Data: Applying stochastic and Bayesian integral projection modeling to amphibian population viability analysis
<p>Integral projection models (IPMs) can estimate the population dynamics of species for which both discrete life stages and continuous variables influence demographic rates. Stochastic IPMs for imperiled species, in turn, can facilitate population viability analyses (PVAs) to guide conservation decision-making. Biphasic amphibians are globally distributed, often highly imperiled, and ecologically well-suited to the IPM approach. Herein, we present the first stochastic size- and stage-structured IPM for a biphasic amphibian, the U.S. federally threatened California tiger salamander (<em>Ambystoma</em> <em>californiense</em>; CTS). This Bayesian model reveals that CTS population dynamics show the greatest elasticity to changes in juvenile and metamorph growth and that populations are likely to experience rapid growth at low density. We integrated this IPM with climatic drivers of CTS demography to develop a PVA and examined CTS extinction risk under the primary threats of habitat loss and climate change. The PVA indicates that long-term viability is possible with surprisingly high (20–50%) terrestrial mortality, but simultaneously identified likely minimum terrestrial buffer requirements of 600–1000 m while accounting for numerous parameter uncertainties through the Bayesian framework. These analyses underscore the value of stochastic and Bayesian IPMs for understanding both climate-dependent taxa and those with cryptic life histories (e.g., biphasic amphibians) in service of ecological discovery and biodiversity conservation. In addition to providing guidance for CTS recovery, the contributed IPM and PVA supply a framework for applying these tools to investigations of ecologically-similar species.</p>
Data from: Evaluating the importance of individual heterogeneity in reproduction to Weddell seal population dynamics using integral projection models
<ol> <li>Identifying and accounting for unobserved individual heterogeneity in vital rates in demographic models is important for estimating population-level vital rates and identifying diverse life-history strategies, but much less is known about how this individual heterogeneity influences population dynamics.</li> <li>We aimed to understand how the distribution of individual heterogeneity in reproductive and survival rates influenced population dynamics using vital rates from a Weddell seal population by altering the distribution of individual heterogeneity in reproduction, which also altered the distribution of individual survival rates through the incorporation of our estimate of the correlation between the two rates and assessing resulting changes in population growth.</li> <li>We constructed an integral projection model (IPM) structured by age and reproductive state using estimates of vital rates for a long-lived mammal that has recently been shown to exhibit large individual heterogeneity in reproduction. Using output from the IPM, we evaluated how population dynamics changed with different underlying distributions of unobserved individual heterogeneity in reproduction.</li> <li>Results indicate that the changes to the underlying distribution of individual heterogeneity in reproduction cause very small changes in the population growth rate and other population metrics. The largest difference in the estimated population growth rate resulting from changes to the underlying distribution of individual heterogeneity was less than 1%.</li> <li>Our work highlights the differing importance of individual heterogeneity at the population level compared to the individual level. Although individual heterogeneity in reproduction may result in large differences in the lifetime fitness of individuals, changing the proportion of above- or below-average breeders in the population results in much smaller differences in annual population growth rate. For a long-lived mammal with stable and high adult-survival that gives birth to a single offspring, individual heterogeneity in reproduction has a limited effect on population dynamics. We posit that the limited effect of individual heterogeneity on population dynamics may be due to canalization of life-history traits.</li> </ol>
Data: Applying stochastic and Bayesian integral projection modeling to amphibian population viability analysis
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Integral projection model results of the planktonic foraminifer Trilobatus sacculifer
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Data from: Evaluating the importance of individual heterogeneity in reproduction to Weddell seal population dynamics using integral projection models
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Data from: The demographic effects of functional traits: an integral projection model approach reveals population-level consequences of reproduction-defense tradeoffs
Quantitatively linking individual variation in functional traits to demography is a necessary step to advance our understanding of trait-based ecological processes. We constructed a population model for Asclepias syriaca to identify how functional traits affect vital rates and population growth and whether tradeoffs in chemical defense and demography alter population growth. Plants with higher foliar cardenolides had lower fiber, cellulose, and lignin levels, as well as decreased sexual and clonal reproduction. Average cardenolide concentrations had the strongest effect on population growth. In both the sexual and clonal pathway, the tradeoff between reproduction and defense affected population growth. We found that both increasing the mean of the distribution of individual plant values for cardenolides and herbivory decreased population growth. However, increasing the variance in both defense and herbivory increased population growth. Functional traits can impact population growth and quantifying individual-level variation in traits should be included in assessments of population-level processes.
Data from: The demographic effects of functional traits: an integral projection model approach reveals population-level consequences of reproduction-defense tradeoffs
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Data from: Quantifying demographic uncertainty: Bayesian methods for integral projection models (IPMs)
Integral projection models (IPMs) are a powerful and popular approach to modeling population dynamics. Generalized linear models form the statistical backbone of an IPM. These models are typically fit using a frequentist approach. We suggest that hierarchical Bayesian statistical approaches offer important advantages over frequentist methods for building and interpreting IPMs, especially given the hierarchical nature of most demographic studies. Using a stochastic IPM for a desert cactus based on a 10-year study as a worked example, we highlight the application of a Bayesian approach for translating uncertainty in the vital rates (e.g., growth, survival, fertility) to uncertainty in population-level quantities derived from them (e.g., population growth rate). The best-fit demographic model, which would have been difficult to fit under a frequentist framework, allowed for spatial and temporal variation in vital rates and correlated responses to temporal variation across vital rates. The corresponding posterior probability distribution for the stochastic population growth rate (λS) indicated that, if current vital rates continue, the study population will decline with nearly 100% probability. Interestingly, less-supported candidate models that did not include spatial variance and vital rate correlations gave similar estimates of λS. This occurred because the best-fitting model did a much better job of fitting vital rates to which the population growth rate was weakly sensitive. The cactus case study highlights several advantages of Bayesian approaches to IPM modeling, including that they: (1) provide a natural fit to demographic data, which are often collected in a hierarchical fashion (e.g., with random variance corresponding to temporal and spatial heterogeneity); (2) seamlessly combine multiple data sets or experiments; (3) readily incorporate covariance between vital rates; and, (4) easily integrate prior information, which may be particularly important for species of conservation concern where data availability may be limited. However, constructing a Bayesian IPM will often require the custom development of a statistical model tailored to the peculiarities of the sampling design and species considered; there may be circumstances under which simpler methods are adequate. Overall, Bayesian approaches provide a statistically sound way to get more information out of hard-won data, the goal of most demographic research endeavors.
Data from: Demography of Euterpe precatoria and Mauritia flexuosa in the Amazon: application of integral projection models for their harvest
Non-Timber Forest Products like palm fruits are fundamental in the livelihood of Amerindian groups. For the last 10 years the fruits of wild palm species, like Euterpe precatoria and Mauritia flexuosa, have been entering into global markets. These species are mostly harvested felling the adults, a practice that may have a disproportionate impact in the conservation of the populations. We studied the demography of E. precatoria and M. flexuosa, two important palms of the Amazon, using integral projection models, to characterize the population dynamics and project impact of different fruit harvest methods: adult felling and direct fruit harvest. We followed over 1400 individuals from populations with low harvest intensities in the Tikuna community of Amacayacu, Amazonas, Colombia from 2011 to 2013, establishing four plots for E. precatoria in seasonally inundated forests and two for M. flexuosa in swamps. The population growth in E. precatoria was slightly declining, whereas M. flexuosa was stable. As expected, the simulations of adult felling diminished λ and the number of available adults under any scenario for either species. On the contrary, the simulations support existing information that climbing and other non-destructive harvest methods would probably allow a sustainable management, satisfying the demand and preserving wild populations.
Data from: Future projections of biodiversity and ecosystem services in Europe with two integrated assessment models
<p>Projections of future changes in biodiversity and ecosystem services (BES) are of increasing importance to inform policy and decision-making on options for conservation and sustainable use of BES. Scenario-based modelling is a powerful tool to assess these future changes. This study assesses the consequences for BES in Europe under four socio-environmental scenarios designed from a BES perspective. We evaluated these scenarios using two integrated assessment models (IMAGE-GLOBIO and CLIMSAVE IAP, respectively). </p> <p><strong>Veerkamp, C. J</strong>., Dunford. R. W., Harrison, P. A., Mandryk, M., Priess, J. A., Schipper, A. M., Stehfest, E., & Alkemade, R. (2020). Future projections of biodiversity and ecosystem services in Europe with two integrated assessment models. <em>Regional Environmental Change,</em> 20, 103. <a href="https://doi.org/10.1007/s10113-020-01685-8">https://doi.org/10.1007/s10113-020-01685-8</a> </p>
Data from: Towards robust evolutionary inference with integral projection models
Integral projection models (IPMs) are extremely flexible tools for ecological and evolutionary inference. IPMs track the distribution of phenotype in populations through time, using functions describing phenotype-dependent development, inheritance, survival and fecundity. For evolutionary inference, two important features of any model are the ability to (i) characterize relationships among traits (including values of the same traits across ages) within individuals, and (ii) characterize similarity between individuals and their descendants. In IPM analyses, the former depends on regressions of observed trait values at each age on values at the previous age (development functions), and the latter on regressions of offspring values at birth on parent values as adults (inheritance functions). We show analytically that development functions, characterized this way, will typically underestimate covariances of trait values across ages, due to compounding of regression to the mean across projection steps. Similarly, we show that inheritance, characterized this way, is inconsistent with a modern understanding of inheritance, and underestimates the degree to which relatives are phenotypically similar. Additionally, we show that the use of a constant biometric inheritance function, particularly with a constant intercept, is incompatible with evolution. Consequently, current implementations of IPMs will predict little or no phenotypic evolution, purely as artefacts of their construction. We present alternative approaches to constructing development and inheritance functions, based on a quantitative genetic approach, and show analytically and through an empirical example on a population of bighorn sheep how they can potentially recover patterns that are critical to evolutionary inference.
UKESM1 data for "G6-1.5: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in sunlight reflection methods studies".
<p>UKESM1 data for "G6-1.5: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in sunlight reflection methods studies".</p> <p>Processed UKESM data used for figure 4 in "G6-1.5: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in sunlight reflection methods studies" by Visioni et al.</p>
Implementation and Testing of an eHealth Integrated Model of Care for Patients Receiving Allogeneic Stem Cell Transplantation: The SMILe Project
ClinicalTrials.gov study NCT04789863. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Towards robust evolutionary inference with integral projection models
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Data from: Demography of Euterpe precatoria and Mauritia flexuosa in the Amazon: application of integral projection models for their harvest
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Data from: Quantifying demographic uncertainty: Bayesian methods for integral projection models (IPMs)
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Data from: Using an integral projection model to assess the effect of temperature on the growth of gilthead seabream Sparus aurata
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Supplemental data for "Initial land use/cover distribution substantially affects global carbon and local temperature projections in the integrated Earth System Model." Article published as Global Biogeochemical Cycles publication 2019B006383
<p>These are supporting data for Global Biogeochemical Cycles publication 2019B006383: "Initial land use/cover distribution substantially affects global carbon and local temperature projections in the integrated Earth System Model." They include data for all of the regular and supplemental figures.</p>
An integrated population model to project viability of a northern bobwhite population in Ohio [DATA]
<p>Increased variation in interannual weather due to climate change can exert a powerful influence on the population dynamics of a species. Understanding the influence of severe weather is important for managing weather-sensitive species. While best management practices target vital rates that are affected by weather, focusing on a single vital rate may not be sufficient if other vital rates are secondarily limiting. A comprehensive modeling framework to forecast future population dynamics while incorporating weather scenarios and vital rate variation within observed ranges that can be affected by management actions are necessary. A potential approach is to combine an integrated population model (IPM) with a population viability analysis (PVA) to generate novel insights about population dynamics. We used the northern bobwhite (<i>Colinus virginianus</i>), a rapidly declining gamebird sensitive to snowfall along the northern extents of the species' range, to demonstrate the utility of a coupled IPM-PVA framework for projecting the response of a population to weather, management, and changes in vital rates. We created an IPM using two sources of count data spanning seven years, five years of winter survival data, and two years of breeding season demographics for a declining bobwhite population in southwestern Ohio during 2007–2015. Quasi-extinction probability at the end of the decadal projection during 2019–2029 was 0.384–0.410 for mild, average, and severe winter weather scenarios. Quasi-extinction probability declined to 0.326 with 20% improvement in nest success and summer survival rates. A concurrent 20% increase in winter survival further reduced quasi-extinction probability to 0.263, which is a ~36% reduction in quasi-extinction probability compared to the baseline scenario with no changes in vital rates. These results suggest that long-term viability of this population may depend on extensive management of winter habitat to improve survival but will also require management actions to improve fecundity after severe winters. Our modeling approach demonstrated how IPMs can be used to project population responses to future weather conditions and overcome some of the pitfalls of traditional PVA. The coupled framework presented here can serve as a tool for managers to make climate informed management decisions.</p>
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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