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63 results for “adaptive capacity”
The adaptive capacity of alien and endangered plants in China
<p>The datasets used in the article includes of "Endangered plants.csv" and "Alien plants.csv". The dataset of "Endangered plants" contains data from the list of the National Key Protected Wild Plants (the first and second batches) officially approved by the State Council, 1898 plants were recorded in the information system of the Chinese Rare and Endangered Plants. The dataset of "Alien plants" contains data from The Checklist of the Chinese Invasive Plants and 562 alien plants were recorded.</p> <p>Diaspore morphological traits were collected from database of the Flora of China (<a href="http://www.iplant.cn/foc/">http://www.iplant.cn/foc/</a>). Diaspore Information Database from Royal Botanic Gardens (<a href="http://data.kew.org/sid/">http://data.kew.org/sid/</a>), and the PLANTS Database of the United States (https://plants.usda.gov/java/).</p> <p>Each dataset includes 29 columns: ID, Species, Family, Dispersal strategy, The number of dispersal strategies of a plant, Reproductive mode, The number of reproductive modes of a plant, Life form, Habitat type, The number of habitats of a plant, Distribution scale, Score 1-16, Adaptive capacity to stressful environments, and Adaptive capacity to disturbed environments.</p> <p>Dispersal strategy includes: autochory (barochory, ballistic dispersal, and blastochory); anemochory (macrogeochory, meteor-anemochory, trichometeorochory, and pterometeorochory); hydrochory (bythisochory, zoohydrochory, and nautohydrochory); zoochory (endozoochory, epizoochory, frugivory, graminivory, granivory, and myrmecochory); and anthropochory (agochory, ethelochory, speirochory, and anthropochory). The number of dispersal strategies of a plant includes: one or two modes, three modes, four modes, and more than four modes. The reproductive mode includes: 1) spores or seeds; 2) ramets; 3) cutting, layering, or grafting; 4) rhizome; and 5) budding. The number of reproductive modes of a plant includes: one mode, two modes, three modes, and more than three modes. Life form includes:<span> </span>annual and biennial, perennial, vine, shrub, and arbor. Habitat type includes: 1) deserts or desert steppes; 2) steppes or dry hillsides; 3) waysides, near villages or wastelands; 4) farm lands; 5) meadow steppes or grasslands; 6) exposed rocks and crevices or tree tops; 7) forest edges, shrublands, or jungles; 8) rivers, lake banks, or benches; 9) marshes, wet meadows, or paddy fields and 10) in water. The number of plant habitats includes: one type, two types, three types, and more than three types. Distribution scale county scale (< 5 × 10<sup>4</sup> km<sup>2</sup>), municipal scale (5–35 × 10<sup>4</sup> km<sup>2</sup>), provincial scale or autonomous regions (35–150 × 10<sup>4</sup> km<sup>2</sup>), and national scale (>150 × 104 km<sup>2</sup>). Score 1-16 are scores of in corresponding indicator assessed in stressful and disturbed environment, respectively. Adaptive capacity to stressful and disturbed environments are total scores of plants assessed to stressful and disturbed environments.</p>
Data from: Finding common ground: Toward comparable indicators of adaptive capacity of tree species to a changing climate
<p>Adaptive capacity, one of the three determinants of vulnerability to climate change, is defined as the capacity of species to persist in their current location by coping with novel environmental conditions through acclimation and/or evolution. Although studies have identified indicators of adaptive capacity, few have assessed this capacity in a quantitative way that is comparable across tree species. Yet, such multi-species assessments are needed by forest management and conservation programs to refine vulnerability assessments and to <span>guide the choice of adaptation measures</span>. In this paper, we propose a framework to quantitatively evaluate five key components of tree adaptive capacity to climate change: individual adaptation through phenotypic plasticity, population phenotypic diversity as influenced by genetic diversity, genetic exchange within populations, genetic exchange between populations and genetic exchange between species. For each component, we define the main mechanisms that underlie adaptive capacity and present associated metrics that can be used as indices. To illustrate the use of this framework, we evaluate the relative adaptive capacity of 26 northeastern North American tree species using values reported in the literature. Our results show adaptive capacity to be highly variable among species and between components of adaptive capacity, such that no one species ranks consistently across all components. On average, the conifer <i>Picea glauca</i> and the broadleaf <i>Betula papyrifera </i>show the greatest adaptive capacity among the 26 species we documented, whereas the conifers <i>Picea rubens </i>and <i>Thuja occidentalis</i>,<i> </i>and the broadleaf <i>Ostrya virginiana</i> possess the lowest. We discuss limitations that arise when comparing adaptive capacity among species, including poor data availability and comparability issues in metrics derived from different methods or studies. The breadth of data required for such an assessment exemplifies the multidisciplinary nature of adaptive capacity and the necessity of continued cross-collaboration to better anticipate the impacts of a changing climate.</p>
Data from Climate adaptability in hydrological models: variable storage capacity to improve performance under contrasting climates.
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Figure 5 in Comparative genomics reveals the evolutionary history of the unicellular eukaryote class Litostomatea and its adaptive evolution based on biochemical metabolic capacity
Figure 5. Gene family and time-calibrated evolution analyses of 28 litostomateans and two spirotricheans. Ages are given as million years ago (Mya). Calibrated nodes are indicated with a star. Numbers asser "+" and "-" represent the expanded or contracted gene families in each branch* respectively. MRCA* the most recent common ancestor; H* subclass Haptoria; R* subclass Rhynchostomatia; º* subclass ºrichostomatia; CZ* Cenozoic; MZ* Mesozoic; NP* Neoproterozoic; PZ* Palaeozoic.
Figure 6 in Comparative genomics reveals the evolutionary history of the unicellular eukaryote class Litostomatea and its adaptive evolution based on biochemical metabolic capacity
Figure 6. Heatmap showing the bias of stop codon usage among 28 litostomatean ciliates. H* subclass Haptoria; R* subclass Rhynchostomatia; º* subclass ºrichostomatia.
Figure 3. Phylogenomic tree estimated from a in Comparative genomics reveals the evolutionary history of the unicellular eukaryote class Litostomatea and its adaptive evolution based on biochemical metabolic capacity
Figure 3. Phylogenomic tree estimated from a concatenated dataset of 1680 orthogroups of 28 litostomateans and two spirotricheans
Figure 3. Phylogenomic tree estimated from a in Comparative genomics reveals the evolutionary history of the unicellular eukaryote class Litostomatea and its adaptive evolution based on biochemical metabolic capacity
Figure 3. Phylogenomic tree estimated from a concatenated dataset of 1680 orthogroups of 28 litostomateans and two spirotricheans by maximum likelihood (ML) and Bayesian inference (BI) methods. Sequences from the present study are in bold. Ŋe numbers at the nodes are the bootstrap values of ML out of 1000 pseudoreplicates and the posterior probability of Bayesian analysis* respectively. Ŋe black dots represent full support values both in the ML and in the BI trees. º* subclass ºrichostomatia; H* subclass Haptoria; R* subclass Rhynchostomatia.
Figure 2 in Comparative genomics reveals the evolutionary history of the unicellular eukaryote class Litostomatea and its adaptive evolution based on biochemical metabolic capacity
Figure 2. Comparative analysis of 28 litostomatean ciliates. A* UpSet plot of shared orthogroups among the three litostomatean subclasses. B* GO enrichment analysis of conserved orthogroups in Litostomatea. C* heatmap showing the number of shared genes among 28 litostomatean ciliates. º* subclass ºrichostomatia; H* subclass Haptoria; R* subclass Rhynchostomatia.
Figure 7 in Comparative genomics reveals the evolutionary history of the unicellular eukaryote class Litostomatea and its adaptive evolution based on biochemical metabolic capacity
Figure 7. Ŋe length distribution (A–C) and motif (C–E) of the introns detected in Monodinium sp.* Myriokaryon sp.* and Apodileptus visscheri.
Figure 1 in Comparative genomics reveals the evolutionary history of the unicellular eukaryote class Litostomatea and its adaptive evolution based on biochemical metabolic capacity
Figure 1. Maps showing the location of the sampling sites and photomicrographs showing the in vivo morphology of the 14 litostomatean ciliates for which omics' data were newly obtained.
Figure 4 in Comparative genomics reveals the evolutionary history of the unicellular eukaryote class Litostomatea and its adaptive evolution based on biochemical metabolic capacity
Figure 4. Carbohydrate-Active Enzymes Database (CAZy) annotation results of 28 litostomatean ciliates. A* comparison of the number of CAZymes in 28 litostomatean ciliates. B* CAZy function classification diagrams of three newly sequenced litostomateans (Didinium sp.1* Myriokaryon sp.* and Apodileptus visscheri). º* subclass ºrichostomatia; H* subclass Haptoria; R* subclass Rhynchostomatia.
Figure 2 in Comparative genomics reveals the evolutionary history of the unicellular eukaryote class Litostomatea and its adaptive evolution based on biochemical metabolic capacity
Figure 2. Comparative analysis of 28 litostomatean ciliates. A* UpSet plot of shared orthogroups among the three litostomatean subclasses. B*
Data for: Coral adaptive capacity insufficient to halt global transition of coral reefs into net erosion under climate change
<p>Projecting the effects of climate change on net reef calcium carbonate production is critical to understanding the future impacts on ecosystem function, but prior estimates have not included corals' natural adaptive capacity to such change. Here we estimate how the ability of symbionts to evolve tolerance to heat stress, or for coral hosts to shuffle to favourable symbionts, and their combination, may influence responses to the combined impacts of ocean warming and acidification under three representative concentration pathway emissions scenarios (RCP2.6, RCP4.5, RCP8.5). We show that symbiont evolution and shuffling both individually and when combined favours persistent positive net reef calcium carbonate production. However, our projections of future net calcium carbonate production under climate change vary both spatially and by RCP. For example, 19–35% of modelled coral reefs are still projected to have net positive net calcium carbonate production by 2050 if symbionts can evolve increased thermal tolerance, depending on the RCP. Without <span>symbiont adaptive capacity,</span> the number of coral reefs with positive net calcium carbonate production drops to 9–13% by 2050. Accounting for both symbiont evolution and shuffling, we project median positive net calcium carbonate production of coral reefs will still occur under low greenhouse emissions (RCP2.6) in the Indian Ocean, and even under moderate emissions (RCP4.5) in the Pacific Ocean. However, adaptive capacity will be insufficient to halt the transition of coral reefs globally into erosion by 2050 under severe emissions scenarios (RCP8.5).</p>
Datasheets affiliated with thesis "Understanding the adaptive capacity in Populus tremuloides, a keystone North American tree species"
<p>These datasheets are included in the unpublished thesis chapters of the doctoral thesis "Understanding the adaptive capacity in <em>Populus tremuloides</em>, a keystone North American tree species".</p>
Physical Exercise on Physiological Adaptation Capacity and Chronic Pain in Individuals With Cardiovascular Risk
ClinicalTrials.gov study NCT06201273. IPD Sharing: NO. Countries: 1. Publications: 1.
Intensive Psychomotor Rehabilitation on Cognitive Motor Abilities and Adaptive Capacity on Children With Polyhandicap
ClinicalTrials.gov study NCT04280458. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Transgenerational plasticity and the capacity to adapt to low salinity in the eastern oyster, Crassostrea virginica
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Data from: Standing genomic variation within coding and regulatory regions contributes to the adaptive capacity to climate in a foundation tree species
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Data and R Markdown files for: Estimating the capacity of Chamaecrista fasciculata for adaptation to change in precipitation
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Data from: Host-adapted aphid populations differ in their migratory patterns and capacity to colonize crops
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Allen Brain Atlas
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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.
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