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8,998 results for “Adaptation”
Land use-based Adaptation and Mitigation Solution (LAMS) suitability maps final version
<div>These maps provide the suitable area (maximum available area) for the potential implementation of the specific proposed LAMS. The suitability map includes 4 classes: not suitable (0), least suitable (1), moderately suitable (2) and most suitable (3). Maps for 13 different LAMS (from the LAMS catalogue V1-1) have been developed for the six RethinkAction case studies, when possible. This v2 includes the metadata.</div> <div>The codes and the names of the LAMS are the following:</div> <div>LAMS03-EstGra: Establishment (conversion to) of permanent grassland</div> <div>LAMS14-SpaPla: Spatial planning for the sustainable deployment of energy on land</div> <div>LAMS15-PhoPla: Photovoltaic plants</div> <div>LAMS21-AgrPla: Agrovoltaic farms</div> <div>LAMS22-IncFor: Increased portion of forests included under protected areas</div> <div>LAMS23-RefAff: Reforestation/afforestation</div> <div>LAMS31-UrbSpr: Limiting urban sprawl</div> <div>LAMS32-GreUrb: Establishment and maintenance of green urban ecosystems</div> <div>LAMS44-IncCul: Increase in cultivated area</div> <div>LAMS49-FloSol: Floating solar photovoltaic panels in water bodies</div> <div>LAMS50-SolPan: Solar panels in rooftops/buildings</div> <div>LAMS55-WatHar: Water harvesting: collect and store rain water in reservoirs</div> <div>LAMS59-LanMan: Land management of solar photovoltaic systems land</div>
Continuously fluctuating selection reveals extreme granularity and parallelism of adaptive tracking
<p>Temporally fluctuating environmental conditions are a ubiquitous feature of natural habitats. Yet, how finely natural populations adaptively track fluctuating selection pressures via shifts in standing genetic variation is unknown. We generated high-frequency, genome-wide allele frequency data from a genetically diverse population of Drosophila melanogaster in extensively replicated field mesocosms from late June to mid-December, a period of ~12 generations. Adaptation throughout the fundamental ecological phases of population expansion, peak density, and collapse was underpinned by extremely rapid, parallel changes in genomic variation across replicates. Yet, the dominant direction of selection fluctuated repeatedly, even within each of these ecological phases. Comparing patterns of allele frequency change to an independent dataset procured from the same experimental system demonstrated that the targets of selection are predictable across years. In concert, our results reveal fitness-relevance of standing variation that is likely to be masked by inference approaches based on static population sampling, or insufficiently resolved time-series data. We propose such fine-scaled temporally fluctuating selection may be an important force maintaining functional genetic variation in natural populations and an important stochastic force affecting levels of standing genetic variation genome-wide.</p>
Unraveling community adaption and survival strategy of soil microbiome under vanadium stress in nationwide mining environments
<p class="Abstract"><span><span>The vanadium (V) smelters soil harbor wide ranges of microorganisms, whose survival relies on their metabolic activities under stress.</span><span> Nonetheless, the characteristics and functions of soil microbiome in V mining environments have not been recognized at a continental scale. This study investigates microbial diversity, community assembly and metabolic traits of soil microbiome across 90 V smelters in China. A decrease in alpha diversity is observed, along with community variation, which is also jointly explained by other environmental, climatic and geographic factors. Null model shows that V promotes homogeneous selection. V also mediates co-occurrence patterns, with increased positive interspecific associations under higher V concentrations (</span><span>></span><span>559.6 mg/kg)</span><span>, e.g., <em>f_Gemmatimonadaceae</em>, <em>Nocardioides</em>, <em>Micromonospora</em>, <em>Rubrobacter</em>.</span><span> In addition, 67 metagenome assembled genomes are retrieved via metagenomic analysis. The metabolic pathways of keystone taxa are disentangled to reveal their putative involvement in the V(V) reduction process. Nitrate and nitrite reductase (<em>nirK</em>, <em>narG</em>), and <em>mtrABC</em> are found to be taxonomically affiliated with <em>Micromonospora</em>. sp, <em>FEN-1250</em>. sp, <em>Nocardioides</em>. sp, etc. Additionally, reverse citric acid cycle (rTCA) serves the main carbon fixation pathway, synthetizing alternative energy for putative V reducers, highlighting a synergistic relationship between autotrophic and heterotrophic processes to support the microbial survival. Our findings comprehensively reveal the driving forces for soil community variation under V stress, suggesting the robust strategies adopted by indigenous microorganisms to alleviate V impact, which can be exploited for bioremediation application.</span></span></p>
A Two Level Neural Approach Combining Off-Chip Prediction with Adaptive Prefetch Filtering
<p>To alleviate the performance and energy overheads of contemporary applications with large data footprints, we propose the Two Level Perceptron (TLP) predictor, a neural mechanism that effectively combines predicting whether an access will be off-chip with adaptive prefetch filtering at the first-level data cache (L1D). TLP is composed of two connected microarchitectural perception predictors, named First Level Predictor (FLP) and Second Level Predictor (SLP). FLP performs accurate off-chip prediction by using several program features based on virtual addresses and a novel selective delay component. The novelty of SLP relies on leveraging off-chip prediction to drive L1D prefetch filtering by using physical addresses and the FLP prediction as features. TLP constitutes the first hardware proposal targeting both off-chip prediction and prefetch filtering using a multi-level perception hardware approach. TLP only requires 7KB of storage. To demonstrate the benefits of TLP we compare its performance with state-of-the-art approaches using off-chip prediction and prefetch filtering on a wide range of single-core and multi-core workloads. Our experiments show that TLP reduces the average DRAM transactions by 30.7% and 17.7%, as compared to a baseline using state-of-the-art cache prefetchers but no off-chip prediction mechanism, across the single-core and multi-core workloads, respectively, while recent work significantly increases DRAM transactions. As a result, TLP achieves geometric mean performance speedups of 6.2% and 11.8% across single-core and multi-core workloads, respectively. In addition, our evaluation demonstrates that TLP is effective independently of the L1D prefetching logic.</p>
A Two Level Neural Approach Combining Off-Chip Prediction with Adaptive Prefetch Filtering
<p>To alleviate the performance and energy overheads of contemporary applications with large data footprints, we propose the Two Level Perceptron (TLP) predictor, a neural mechanism that effectively combines predicting whether an access will be off-chip with adaptive prefetch filtering at the first-level data cache (L1D). TLP is composed of two connected microarchitectural perception predictors, named First Level Predictor (FLP) and Second Level Predictor (SLP). FLP performs accurate off-chip prediction by using several program features based on virtual addresses and a novel selective delay component. The novelty of SLP relies on leveraging off-chip prediction to drive L1D prefetch filtering by using physical addresses and the FLP prediction as features. TLP constitutes the first hardware proposal targeting both off-chip prediction and prefetch filtering using a multi-level perception hardware approach. TLP only requires 7KB of storage. To demonstrate the benefits of TLP we compare its performance with state-of-the-art approaches using off-chip prediction and prefetch filtering on a wide range of single-core and multi-core workloads. Our experiments show that TLP reduces the average DRAM transactions by 30.7% and 17.7%, as compared to a baseline using state-of-the-art cache prefetchers but no off-chip prediction mechanism, across the single-core and multi-core workloads, respectively, while recent work significantly increases DRAM transactions. As a result, TLP achieves geometric mean performance speedups of 6.2% and 11.8% across single-core and multi-core workloads, respectively. In addition, our evaluation demonstrates that TLP is effective independently of the L1D prefetching logic.</p>
A Two Level Neural Approach Combining Off-Chip Prediction with Adaptive Prefetch Filtering
<p>To alleviate the performance and energy overheads of contemporary applications with large data footprints, we propose the Two Level Perceptron (TLP) predictor, a neural mechanism that effectively combines predicting whether an access will be off-chip with adaptive prefetch filtering at the first-level data cache (L1D). TLP is composed of two connected microarchitectural perception predictors, named First Level Predictor (FLP) and Second Level Predictor (SLP). FLP performs accurate off-chip prediction by using several program features based on virtual addresses and a novel selective delay component. The novelty of SLP relies on leveraging off-chip prediction to drive L1D prefetch filtering by using physical addresses and the FLP prediction as features. TLP constitutes the first hardware proposal targeting both off-chip prediction and prefetch filtering using a multi-level perception hardware approach. TLP only requires 7KB of storage. To demonstrate the benefits of TLP we compare its performance with state-of-the-art approaches using off-chip prediction and prefetch filtering on a wide range of single-core and multi-core workloads. Our experiments show that TLP reduces the average DRAM transactions by 30.7% and 17.7%, as compared to a baseline using state-of-the-art cache prefetchers but no off-chip prediction mechanism, across the single-core and multi-core workloads, respectively, while recent work significantly increases DRAM transactions. As a result, TLP achieves geometric mean performance speedups of 6.2% and 11.8% across single-core and multi-core workloads, respectively. In addition, our evaluation demonstrates that TLP is effective independently of the L1D prefetching logic.</p>
SSH CENTRE - Mini-reports : Focus groups on "Adaptation to Climate Change: support at least 150 European regions and communities to become climate resilient by 2030"
<p>SSH CENTRE (Social Sciences and Humanities for Climate, Energy aNd Transport Research Excellence) is a Horizon Europe project, engaging directly with stakeholders across research, policy, and business (including citizens) to strengthen social innovation, SSH-STEM collaboration, transdisciplinary policy advice, inclusive engagement, and SSH communities across Europe, accelerating the EU's transition to carbon neutrality. </p><p>SSH CENTRE is based in a range of activities related to Open Science, inclusivity and diversity – especially with regards Southern and Eastern Europe and different career stages – including: development of novel SSH-STEM collaborations to facilitate the delivery of the EU Green Deal; SSH knowledge brokerage to support regions in transition; and the effective design of strategies for citizen engagement in EU R&I activities. Outputs include action-led agendas and building stakeholder synergies through regular Policy Insight events.</p><p>This is captured in a high-profile virtual SSH CENTRE generating and sharing best practice for SSH policy advice, overcoming fragmentation to accelerate the EU's journey to a sustainable future.</p><p>The aim of the focus groups was to gather citizen's perspectives, their hopes, concerns and ideas related to the Horizon Mission of Adaptation to Climate Change: support at least 150 European regions and communities to become climate resilient by 2030. The focus group discussion topics while remaining close to the Mission, avoid specific technical references to allow citizens to contribute based on their differing levels of understanding. As part of the SSH CENTRE project, in total, four focus group series will be conducted relating to Adaptation to Climate Change; Restore our Ocean and Waters by 2030; 100 Climate-Neutral and Smart Cities by 2030; A Soil Deal for Europe. </p><p>Notes were taken during each focus groups and turned into mini-reports. These mini-reports sum up the essence of the discussion: the participants' main ideas and some interesting quotes. </p>
Different adaptation error types in affective computing have different effects on user experience: a Wizard-of-Oz study
<p>The record consists of one Excel file that contains individual participant data for the study "Different adaptation error types in affective computing have different effects on user experience: a Wizard-of-Oz study". The study included 97 participants who were randomly divided into five groups corresponding to five adaptation behaviors (SingleSmall, SingleModerate, ImmediateLow, ImmediateHigh, IrreversibleHigh). Each participant took part in three 11-minute intervals. Difficulty changed every 60 seconds in each 11-minute interval, and there are thus 11 difficulty values per interval. At the end of each interval, participants self-reported their experience using the NASA Task Load Index (6 items) and Intrinsic Motivation Inventory (8 items). After the third interval, participants were asked to rate how much they liked the 3 intervals on a visual analog scale that was converted to 1-100 numerical scores.</p>
Data from: Adaptation of perennial flowering phenology across the European range of Arabis alpina
<p>Perennial <em>Arabis alpina</em> has a wide geographic distribution and is adapted to local environments. However, the traits that underlie adaptation are unknown. Flowering phenology is an adaptive trait in other species, but its geographic variation has not been systematically studied in herbaceous perennials.</p> <p>Accessions of <em>A. alpina</em> were collected across the European range. Their flowering behavior was tested in controlled conditions, in experimental common-garden plantations at native sites and <em>in-situ</em> in natural populations. Also, genetic diversity within and among populations was examined.</p> <p>French Alpine and Scandinavian accessions varied in timing and duration of flowering. By contrast, in controlled conditions and <em>in-situ</em>, all Spanish accessions were obligate vernalization-requiring with a short duration of flowering. Nevertheless, Spanish populations were as genetically diverse as French Alpine populations and more so than Scandinavian populations. Furthermore, <em>perpetual flowering 1</em>, a mutant that shows no vernalization requirement and a long duration of flowering, showed higher mortality and poorer performance than local accessions at Spanish experimental sites.</p> <p>We propose that in this perennial species, the vernalization requirement and short duration of flowering are under selection in Spain as a strategy to survive exposure to longer, warmer growing seasons.</p>
Data from: The role of mutation bias in adaptive molecular evolution: insights from convergent changes in protein function
<p>An underexplored question in evolutionary genetics concerns the extent to which mutational bias in the production of genetic variation influences outcomes and pathways of adaptive molecular evolution. In the genomes of at least some vertebrate taxa, an important form of mutation bias involves changes at CpG dinucleotides: If the DNA nucleotide cytosine (C) is immediately 5' to guanine (G) on the same coding strand, and if the C is methylated, then C→T and G→A mutations occur at an elevated rate relative to mutations at non-CpG sites. Here we examine experimental data from case studies in which it has been possible to identify the causative substitutions that are responsible for adaptive changes in the functional properties of vertebrate hemoglobin (Hb). Specifically, we examine the molecular basis of convergent increases in Hb-O<sub>2</sub> affinity in high-altitude birds. Using a data set of experimentally verified, affinity-enhancing mutations in the Hbs of highland avian taxa, we tested whether causative changes are enriched for mutations at CpG dinucleotides relative to the frequency of CpG mutations among all possible missense mutations. The tests revealed that a disproportionate number of causative amino acid replacements were attributable to CpG mutations, demonstrating that mutation bias can influence outcomes of molecular adaptation.</p>
Dataset for monkeys A and B from AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity
<p>ECoG data from two monkeys, affi (A) and beignet (B) used in AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity. Jingyuan Li, Leo Scholl, Trung Le, Pavithra Rajeswaran, Amy L Orsborn, and Eli Shlizerman. NeurIPS. 2023. https://openreview.net/forum?id=7ntI4kcoqG</p><p>See also https://github.com/shlizee/AMAG</p>
Environmental effects on genetic variance are likely to constrain adaptation in novel environments
<p>Adaptive plasticity allows populations to cope with environmental variation but is expected to fail as conditions become unfamiliar. In novel conditions, populations may instead rely on rapid adaptation to increase fitness and avoid extinction. Adaptation should be fastest when both plasticity and selection occur in directions of the multivariate phenotype that contain abundant genetic variation. However, tests of this prediction from field experiments are rare. Here, we quantify how additive genetic variance in a multivariate phenotype changes across an elevational gradient, and test whether plasticity and selection align with genetic variation. We do so using two closely related, but ecologically distinct, sister species of Sicilian daisy (Senecio, Asteraceae) adapted to high and low elevations on Mount Etna. Using a paternal half-sibling breeding design, we generated and then reciprocally planted c.19,000 seeds of both species, across an elevational gradient spanning each species' native elevation, and then quantified mortality and five leaf traits of emergent seedlings. We found that genetic variance in leaf traits changed more across elevations than between species. The high-elevation species at novel lower elevations showed changes in the distribution of genetic variance among the leaf traits, which reduced the amount of genetic variance in the directions of selection and the native phenotype. By contrast, the low-elevation species mainly showed changes in the amount of genetic variance at the novel high elevation, and genetic variance was concentrated in the direction of the native phenotype. For both species, leaf trait plasticity across elevations was in a direction of the multivariate phenotype that contained a moderate amount of genetic variance. Together, these data suggest that where plasticity is adaptive, selection on genetic variance for an initially plastic response could promote adaptation. However, large environmental effects on genetic variance are likely to reduce adaptive potential in novel environments.</p>
A lack of genetic diversity and minimal adaptive evolutionary divergence in introduced Mysis shrimp after 50 years
<p>The successes of introduced populations in novel habitats often provide powerful examples of evolution and adaptation. In the 1950's, opossum shrimp (<em>Mysis diluviana</em>) individuals from Clearwater Lake in Minnesota, USA were transported and introduced to Twin Lakes in Colorado, USA by fisheries managers to supplement food sources for trout. Shrimp were subsequently introduced from Twin Lakes into numerous lakes throughout Colorado. Because managers kept detailed records of the timing of the introductions, we had the opportunity to test for evolutionary divergence within a known time interval. Here, we used reduced representation genomic data to investigate patterns of genetic diversity and test for genetic divergence between populations and for evidence of adaptive evolution within the introduced populations in Colorado. We found overall very low levels of genetic diversity across all populations, with evidence for some genetic divergence between the Minnesota source population and the introduced populations in Colorado. There was also little differentiation among the Colorado populations, consistent with the known provenance of a single founding population, with the exception of the population from Gross Reservoir, Colorado. Demographic modeling suggests that the population in Gross Reservoir is of hybrid origin, with an earlier founding population from an unknown source being later supplemented from another population. Despite the overall low genetic diversity we observed, F<sub>ST</sub> outlier and environmental association analyses identified multiple loci exhibiting signatures of selection and adaptive variation related to elevation and lake depth. The success of introduced species is thought to be limited by genetic variation, but our results imply that populations with limited genetic variation can become established in a wide range of novel environments.</p>
RISIS-KNOWMAK NUTS adapted classification
<p>This file provides the correspondence table between EUROSTAT NUTS3 classification and the adapted regional classification used by the RISIS-KNOWMAK project. This regional classification fits the structure of knowledge production in Europe and addresses some knowm problems of the NUTS3 classification, such as the treatment of large agglomerations, while remaining fully compatible with the EUROSTAT NUTS regional classification. This compatibility allows combining all KNOWMAK data with regional statistics (at NUTS3 level, 2021 edition) from EUROSTAT.</p> <p>More precisely, the classification includes EUROSTAT metropolitan regions (based on the aggregation of NUTS3-level regions) and NUTS2 regions for the remaining areas; further, a few additional centers for knowledge production, like Oxford and Leuven, have been singled out at NUTS3 level. The resulting classification is therefore more fine-grained than NUTS2 in the areas with sizeable knowledge production, but at the same time recognizes the central role of metropolitan areas in knowledge production. While remaining compatible with NUTS, the classification allows addressing two well-known shortcomings: a) the fact that some large cities are split between NUTS regions (London) and b) the fact that NUTS3 classification in some countries includes many very small regions, as in the case of Germany</p>
Naked mole rats have distinctive cardiometabolic and genetic adaptations to their underground low-oxygen lifestyles (non-genetic data)
<p>The naked mole-rat <em>Heterocephalus glaber</em> is a eusocial mammal exhibiting extreme longevity (37-year lifespan), extraordinary resistance to hypoxia and absence of cardiovascular disease. To identify the mechanisms behind these exceptional traits, metabolomics and RNAseq of cardiac tissue from naked mole-rats were compared to other African mole-rat genera. We identified metabolic and genetic adaptations unique to naked mole-rats including elevated glycogen, thus enabling glycolytic ATP generation during cardiac ischemia. Elevated normoxic expression of HIF-1α was observed while downstream hypoxia-responsive genes were down-regulated, suggesting adaptation to low-oxygen environments. Naked mole-rat hearts showed reduced succinate build-up during ischemia and negligible tissue damage following ischemia-reperfusion injury. These adaptive evolutionary traits reflect a unique hypoxic and eusocial lifestyle that collectively may contribute to their longevity and health span.</p>
Newly identified nematodes from the Great Salt Lake are associated with microbialites and specially adapted to hypersaline conditions
<p>Extreme environments enable the study of simplified food-webs and serve as models for evolutionary bottlenecks and early Earth ecology. We investigated the biodiversity of invertebrate meiofauna in the benthic zone of the Great Salt Lake (GSL), UT, one of the most hypersaline lake systems in the world. The hypersaline bays within the GSL are currently thought to support only two multicellular animals: brine fly larvae and brine shrimp. Here, we report the presence, habitat, and microbial interactions of novel free-living nematodes. Nematode diversity drops dramatically along a salinity gradient from a freshwater river into the south arm of the lake. In Gilbert Bay, nematodes primarily inhabit reef-like organosedimentary structures built by bacteria called microbialites. These structures likely provide a protective barrier to UV and aridity, and bacterial associations within them may support life in hypersaline environments. Notably, sampling from Owens Lake, another terminal lake in the Great Basin that lacks microbialites, did not recover nematodes from similar salinities. Phylogenetic divergence suggests that GSL nematodes represent previously undescribed members of the family Monhysteridae – one of the dominant fauna of the abyssal zone and deep-sea hydrothermal vents. These findings update our understanding of halophile ecosystems and the habitable limit of animals.</p>
Raw data and scripts from de Lima et al. Succulence explains salinity tolerance in a Neotropical orchid without any evidence of local adaptation to salt spray
Open the record for dataset details and reuse information.
Fig. 2 in Host-adapted Cryptosporidium and Enterocytozoon bieneusi genotypes in straw-colored fruit bats in Nigeria
Fig. 2. Genotyping of Cryptosporidium spp. in strawcolored fruit bats by small subunit rRNA-based PCRRFLP. Upper panel: SspI RFLP patterns; lower panel: VspI RFLP patterns; M: 100-bp molecular markers; H: C. hominis positive control; P: C. parvum positive control; B1: Cryptosporidium bat genotype XIV; B2: Cryptosporidium bat genotype XV.
Fig. 4 in Host-adapted Cryptosporidium and Enterocytozoon bieneusi genotypes in straw-colored fruit bats in Nigeria
Fig. 4. Phylogeny of Enterocytozoon bieneusi genotypes in bats based on Bayesian inference analysis of sequences of the internal transcribed spacer of the rRNA gene. The posterior probability values are indicated on the branches. Red ones are E. bieneusi genotypes identified in straw-colored fruit bats in the present study. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Data for: Biomechanical adaptations enable phoretic mite species to occupy distinct spatial niches on host burying beetles
<p>Niche theory predicts that ecologically similar species coexist by minimising interspecific competition through niche partitioning. Therefore understanding the mechanisms of niche partitioning is essential for predicting interactions and coexistence between competing organisms. Here we study two phoretic mite species, <em>Poecilochirus carabi, </em>and <em>Macrocheles nataliae</em> that coexist on the same host-burying beetle <em>Nicrophorus vespilloides </em>and use it to 'hitchhike' between reproductive sites. Field observations revealed clear spatial partitioning between species in distinct host body parts. <em>P. carabi</em> preferred the ventral side of the thorax, whereas <em>M. nataliae </em>were exclusively found ventrally at the hairy base of the abdomen. Experimental manipulations of mite density showed that each species preferred these body parts, largely regardless of the density of the other mite species on the host beetle. Force measurements indicated that this spatial distribution is mediated by biomechanical adaptations, because each mite species required more force to be removed from their preferred location on the beetle. While <em>P. carabi</em> attached with large adhesive pads to the smooth thorax cuticle, <em>M. nataliae</em> gripped abdominal setae with their chelicerae. Our results show that specialist biomechanical adaptations for attachment can mediate spatial niche partitioning among species sharing the same host.</p>
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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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.