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230 results for “population decline”
Figure 3 in Is the global decline reflects local declines? A case of the population trend of Far Eastern Curlew Numenius madagascariensis in Banyuasin Peninsula, South Sumatra, Indonesia
Figure 3. Mix flocks of Far Eastern Curlew and Eurasian Curlew Numenius arquata in flight on 8 November 2020 in Banyuasin Peninsula, South Sumatra province, Indonesia (Photo: Cipto Dwi Handono).
Figure 4 in Is the global decline reflects local declines? A case of the population trend of Far Eastern Curlew Numenius madagascariensis in Banyuasin Peninsula, South Sumatra, Indonesia
Figure 4. Far Eastern Curlew standing at the mudflat on 8 November 2020 in the coastal zone of Banyuasin Peninsula, South Sumatra province, Indonesia (Photo: Cipto Dwi Handono).
Data from: Spatial consistency in drivers of population dynamics of a declining migratory bird
<p>1. Many migratory species are in decline across their geographical ranges. Single-population studies can provide important insights into drivers at a local scale, but effective conservation requires multi-population perspectives. This is challenging because relevant data are often hard to consolidate, and state-of-the-art analytical tools are typically tailored to specific datasets.</p> <p>2. We capitalized on a recent data harmonization initiative (SPI-Birds) and linked it to a generalized modeling framework to identify the demographic and environmental drivers of large-scale population decline in migratory pied flycatchers (<em>Ficedula</em> <em>hypoleuca</em>) breeding across Britain.</p> <p>3. We implemented a generalized integrated population model (IPM) to estimate age-specific vital rates, including their dependency on environmental conditions, and total and breeding population size of pied flycatchers using long-term (34–64 years) monitoring data from seven locations representative of the British breeding range. We then quantified the relative contributions of different vital rates and population structures to changes in short- and long-term population growth rates using transient life table response experiments (LTREs).</p> <p>4. Substantial covariation in population sizes across breeding locations suggested that change was the result of large-scale drivers. This was supported by LTRE analyses, which attributed past changes in short-term population growth rates and long-term population trends primarily to variation in annual survival and dispersal dynamics, which largely act during migration and/or non-breeding season. Contributions of variation in local reproductive parameters were small in comparison, despite sensitivity to local temperature and rainfall within the breeding period.</p> <p>5. We show that both short- and longer-term population changes of British-breeding pied flycatchers are likely linked to factors acting during migration and in non-breeding areas, where future research should be prioritized. We illustrate the potential of multi-population analyses for informing management at (inter)national scales and highlight the importance of data standardization, generalized and accessible analytical tools, and reproducible workflows to achieve them.</p>
Data from: Species-specific ecological traits, phylogeny, and geography underpin vulnerability to population declines for North American birds
<p>Species declines and extinctions characterize the Anthropocene. Determining species vulnerability to decline, and where and how to mitigate threats, are paramount for effective conservation. We hypothesized that species with shared ecological traits also share threats, and therefore may experience similar population trends. Here, we used a Bayesian modeling framework to test whether phylogeny, geography, and 22 ecological traits predict regional population trends for 380 North American bird species. Groups like blackbirds, warblers, and shorebirds, as well as species occupying Bird Conservation Regions at more extreme latitudes in North America, exhibited negative population trends, while groups such as ducks, raptors, and waders, as well as species occupying more inland Bird Conservation Regions, exhibited positive trends. Specifically, we found that in addition to phylogeny and breeding geography, multiple ecological traits contributed to explaining variation in regional population trends for North American birds. Furthermore, we found that regional trends and the relative effects of migration distance, phylogeny, and geography differ between shorebirds, songbirds, and waterbirds. Our work provides evidence that multiple ecological traits correlate with North American bird population trends, but that the individual effects of these ecological traits in predicting population trends often vary between different groups of birds. Moreover, our results reinforce the notion that variation in avian population trends is controlled by more than phylogeny and geography, where closely-related species within one region can show unique population trends due to differences in their ecological traits. We recommend that regional conservation plans, i.e. one-size-fits-all plans, be implemented only for bird groups with population trends under strong phylogenetic or geographic controls. We underscore the need to develop species-specific research and management strategies for other groups, like songbirds, that exhibit high variation in their population trends and are influenced by multiple ecological traits.</p>
Shrub cover declined as indigenous populations expanded across southeast Australia
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Genomic footprints of (pre) colonialism: Population declines in urban and forest túngara frogs coincident with historical human activity
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Data from: One-stage spatial mark-resight analysis reveals an increasing grizzly bear population with declining density near roads
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Data from: Species-specific ecological traits, phylogeny, and geography underpin vulnerability to population declines for North American birds
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Data from: Multi-species sensory networks and social foraging strategies: Implications for population decline in procellariiform seabirds
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Data from: Widespread cultural change in declining populations of Amazon parrots
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Observed declines in body size have differential effects on survival and recruitment, but no effect on population growth in tropical birds
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Temporal change in the contribution of immigration to population growth in a wild seabird experiencing rapid population decline
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Data from: Spatial consistency in drivers of population dynamics of a declining migratory bird
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Differential changes in lifecycle-event phenology provide a window into regional population declines
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Data from: Protection status, human disturbance, snow cover and trapping drive density of a declining wolverine population in the Canadian Rocky Mountains
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Data from: Spatio-temporal trends in richness and persistence of bacterial communities in decline-phase water vole populations
<p><strong>ABSTRACT</strong><br> Understanding the driving forces that control vole population dynamics requires identifying bacterial parasites hosted by the voles and describing their dynamics at the community level. To this end, we used high-throughput DNA sequencing to identify bacterial parasites in cyclic populations of montane water voles that exhibited a population outbreak and decline in 2014-2018. An unexpectedly large number of 155 Operational Taxonomic Units (OTUs) representing at least 13 genera in 11 families was detected. Individual bacterial richness was higher during declines, and vole body condition was lower. Richness as estimated by Chao2 at the local population scale did not exhibit clear seasonal or cycle phase-related patterns, but at the vole meta-population scale, exhibited seasonal and phase-related patterns. Moreover, bacterial OTUs that were detected in the low density phase were geographically widespread and detected earlier in the outbreak; some were associated with each other. Our results demonstrate the complexity of bacterial community patterns with regard to host density variations, and indicate that investigations about how parasites interact with host populations must be conducted at several temporal and spatial scales: multiple times per year over multiple years, and at both local and long-distance dispersal scales for the host(s) under consideration.</p> <p><strong>FILE DESCRIPTION:</strong></p> <p><strong>Trapping, physical, and demographic data for the 1376 <em>Arvicola terrestris</em> included in sequencing runs 1 to 8</strong></p> <p>This XLSX file contains the following information concerning the 1376 animals included in the eight sequencing runs: location, session numbering, animal_id, trap_name, capture_date, species, sex (1=male, 2=female), weight (g), length_body (mm), length_tail (mm, testes (0=abdominal, 1=scrotal), testes_length (mm), testes_width (mm), nipples (0=small, 1=lactating), vagina (0=not perforate, 1=perforate), pub_symph (0=closed, 1=open), uterus_scars (#), embryos(#), lens_weight (g), lens_weight2 (g) and sequencing labels</p> <p>File name: Animal_details.xlsx</p> <p> </p> <p><strong>Information concerning the <em>Arvicola terrestris</em> samples and the positive and negative controls multiplexed in the 16Sv4 MiSeq sequencing runs 1 to 8</strong></p> <p>This XLSX file contains the Run IDs, Sample IDs, Sample types, Dates & Site names, DNA extraction kit, PCR IDs, PCR replicate numbers, numbers of reads before and after filtering and the fastq file names for the 6615 PCR products multiplexed in the eight different Illumina MiSeq runs.</p> <p>File name: Sample_and_sequencing_informations.xlsx</p> <p> </p> <p><strong>MiSeq raw sequences of the 16Sv4 rRNA gene from <em>Arvicola terrestris</em> samples (Run1)</strong></p> <p>This ZIP file contains the Run1 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each <em>Arvicola terrestris</em> sample using the MiSeq platform. The 1570 multiplexed PCR products were indexed using both forward and reverse indices. The list of the multiplexed samples and positive & negative controls are provided in the following XLSX file titled: Sample_and_sequencing_informations.xlsx.</p> <p>File name: MiSeq_Reads_16S_Arvicola_terrestris_Run1.zip</p> <p> </p> <p><strong>MiSeq raw sequences of the 16Sv4 rRNA gene from <em>Arvicola terrestris</em> samples (Run2)</strong></p> <p>This ZIP file contains the Run2 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each <em>Arvicola terrestris</em> sample using the MiSeq platform. The 1668 multiplexed PCR products were indexed using both forward and reverse indices. The list of the multiplexed samples and positive & negative controls are provided in the following XLSX file titled: Sample_and_sequencing_informations.xlsx.</p> <p>File name: MiSeq_Reads_16S_Arvicola_terrestris_Run2.zip</p> <p> </p> <p><strong>MiSeq raw sequences of the 16Sv4 rRNA gene from <em>Arvicola terrestris</em> samples (Run3)</strong></p> <p>This ZIP file contains the Run3 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each <em>Arvicola terrestris</em> sample using the MiSeq platform. The 1646 multiplexed PCR products were indexed using both forward and reverse indices. The list of the multiplexed samples and positive & negative controls are provided in the following XLSX file titled: Sample_and_sequencing_informations.xlsx.</p> <p>File name: MiSeq_Reads_16S_Arvicola_terrestris_Run3.zip</p> <p> </p> <p><strong>MiSeq raw sequences of the 16Sv4 rRNA gene from <em>Arvicola terrestris</em> samples (Run4)</strong></p> <p>This ZIP file contains the Run4 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each <em>Arvicola terrestris</em> sample using the MiSeq platform. The 1712 multiplexed PCR products were indexed using both forward and reverse indices. The list of the multiplexed samples and positive & negative controls are provided in the following XLSX file titled: Sample_and_sequencing_informations.xlsx.</p> <p>File name: MiSeq_Reads_16S_Arvicola_terrestris_Run4.zip</p> <p> </p> <p><strong>MiSeq raw sequences of the 16Sv4 rRNA gene from <em>Arvicola terrestris</em> samples (Run5)</strong></p> <p>This ZIP file contains the Run5 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each <em>Arvicola terrestris</em> sample using the MiSeq platform. The 1680 multiplexed PCR products were indexed using both forward and reverse indices. The list of the multiplexed samples and positive & negative controls are provided in the following XLSX file titled: Sample_and_sequencing_informations.xlsx.</p> <p>File name: MiSeq_Reads_16S_Arvicola_terrestris_Run5.zip</p> <p> </p> <p><strong>MiSeq raw sequences of the 16Sv4 rRNA gene from <em>Arvicola terrestris</em> samples (Run6)</strong></p> <p>This ZIP file contains the Run6 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each <em>Arvicola terrestris</em> sample using the MiSeq platform. The 1704 multiplexed PCR products were indexed using both forward and reverse indices. The list of the multiplexed samples and positive & negative controls are provided in the following XLSX file titled: Sample_and_sequencing_informations.xlsx.</p> <p>File name: MiSeq_Reads_16S_Arvicola_terrestris_Run6.zip</p> <p> </p> <p><strong>MiSeq raw sequences of the 16Sv4 rRNA gene from <em>Arvicola terrestris</em> samples (Run7)</strong></p> <p>This ZIP file contains the Run7 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each <em>Arvicola terrestris</em> sample using the MiSeq platform. The 1620 multiplexed PCR products were indexed using both forward and reverse indices. The list of the multiplexed samples and positive & negative controls are provided in the following XLSX file titled: Sample_and_sequencing_informations.xlsx.</p> <p>File name: MiSeq_Reads_16S_Arvicola_terrestris_Run7.zip</p> <p> </p> <p><strong>MiSeq raw sequences of the 16Sv4 rRNA gene from <em>Arvicola terrestris</em> samples (Run8)</strong></p> <p>This ZIP file contains the Run8 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each <em>Arvicola terrestris</em> sample using the MiSeq platform. The 1630 multiplexed PCR products were indexed using both forward and reverse indices. The list of the multiplexed samples and positive & negative controls are provided in the following XLSX file titled: Sample_and_sequencing_informations.xlsx.</p> <p>File name: MiSeq_Reads_16S_Arvicola_terrestris_Run8.zip</p> <p> </p> <p><strong>Raw abundance table of the 16v4 rRNA gene from <em>Arvicola terrestris samples before data filtering (Run1 to 8)</em></strong></p> <p>This CSV file contains the number of reads for each distinct variant (OTU) and each of the 6615 PCR products, including the <em>Arvicola terrestris</em> samples and the controls, sequenced in the MiSeq runs 1 to 8 before the data filtering.</p> <p>File name: Read_abundance_table_before_filtering.csv</p> <p> </p> <p><strong>Abundance table of the 16v4 rRNA gene from <em>Arvicola terrestris</em> samples after data filtering (Run1 to 8)</strong></p> <p>This CSV file contains the number of reads for each distinct variant (OTU) and each <em>Arvicola terrestris</em> sample sequenced in the MiSeq runs 1 to 8 after the data filtering.</p> <p>File name: Read_abundance_table_after_filtering.csv</p>
Monitoring Plasmodium falciparum and Plasmodium vivax using microsatellite markers indicates limited changes in population structure after substantial transmission decline in Papua New Guinea
Monitoring the genetic structure of pathogen populations may be an economical and sensitive approach to quantify the impact of control on transmission dynamics, highlighting the need for a better understanding of changes in population genetic parameters as transmission declines. Here we describe the first population genetic analysis of the major human malaria parasites, <i>Plasmodium falciparum</i> (Pf) and <i>Plasmodium vivax</i> (Pv) populations following nationwide distribution of long-lasting insecticide treated nets (LLIN) in Papua New Guinea (PNG). Parasite isolates from pre- (2005-6) and post-LLIN (2010-2014) were genotyped using microsatellite markers. Despite parasite prevalence declining substantially (East Sepik: Pf=54.9-8.5%, Pv=35.7-5.6%, Madang: Pf=38.0-9.0%, Pv: 31.8-19.7%), genetically diverse and intermixing parasite populations remained. Pf diversity declined modestly post-LLIN relative to pre-LLIN (East Sepik: Rs = 7.1-6.4, He = 0.77-0.71; Madang: Rs= 8.2-6.1, He = 0.79-0.71). Unexpectedly, population structure present in pre-LLIN populations was lost post-LLIN, suggesting that more frequent human movement between provinces may have contributed to higher gene flow. Pv prevalence initially declined but increased again in one province, yet diversity remained high throughout the study period (East Sepik: Rs=11.4-9.3, He=0.83-0.80; Madang: Rs=12.2-14.5, He=0.85-0.88). Although genetic differentiation values increased between provinces over time, no significant population structure was observed at any time point. For both species, a decline in multiple infections and increasing clonal transmission and significant multilocus linkage disequilibrium (mLD) post-LLIN was a positive indicator of impact on the parasite population using microsatellite markers. These parameters may be useful adjuncts to traditional epidemiological tools in the early stages of transmission reduction.
Data from: Consequences of past and present harvest management in a declining flyway population of common eiders Somateria mollissima
<p>1. Harvested species population dynamics are shaped by the relative contribution of natural and harvest mortality. Natural mortality is usually not under management control, so managers must continuously adjust harvest rates to prevent overexploitation. Ideally, this requires regular assessment of the contribution of harvest to total mortality and how this affects population dynamics. 2. To assess the impact of hunting mortality on the dynamics of the rapidly declining Baltic/Wadden Sea population of common eiders Somateria mollissima we first estimated vital rates of ten study colonies over the period 1970–2015. By means of a multi-event capture-recovery model we then used the cause of death of recovered individuals to estimate proportions of adult females that died due to hunting or other causes. Finally, we adopted a stochastic matrix population modelling approach based on simulations to investigate the effect of past and present harvest regulations on changes in flyway population size and composition. 3. Results showed that even the complete ban on shooting females implemented in 2014 in Denmark, where most hunting takes place was not enough to stop the population decline given current levels of natural female mortality. Despite continued hunting of males our predictions suggest that the proportion of females will continue to decline unless natural mortality of the females is reduced. 4. Although levels of natural mortality must decrease to halt the decline of this population, we advocate that the current hunting ban on females is maintained while further investigations of factors causing increased levels of natural mortality among females are undertaken. 5. Synthesis and applications. At the flyway scale, continuous and accurate estimates of vital rates and the relative contribution of harvest versus other mortality causes are increasingly important as the population effect of adjusting harvest rates is most effectively evaluated within a model-based adaptive management framework.</p>
Data from: Genomic signals of selection predict climate-driven population declines in a migratory bird
The ongoing loss of biodiversity caused by rapid climatic shifts requires accurate models for predicting species' responses. Despite evidence that evolutionary adaptation could mitigate climate change impacts, evolution is rarely integrated into predictive models. Integrating population genomics and environmental data, we identified genomic variation associated with climate across the breeding range of the migratory songbird, yellow warbler (Setophaga petechia). Populations requiring the greatest shifts in allele frequencies to keep pace with future climate change have experienced the largest population declines, suggesting that failure to adapt may have already negatively affected populations. Broadly, our study suggests that the integration of genomic adaptation can increase the accuracy of future species distribution models and ultimately guide more effective mitigation efforts.
Data from: Declines in low-elevation subalpine tree populations outpace growth in high-elevation populations with warming
1. Species distribution shifts in response to climate change require that recruitment increase beyond current range boundaries. For trees with long lifespans, the importance of climate-sensitive seedling establishment to the pace of range shifts has not been demonstrated quantitatively. 2. Using spatially explicit, stochastic population models combined with data from long-term forest surveys, we explored whether the climate-sensitivity of recruitment observed in climate manipulation experiments was sufficient to alter populations and elevation ranges of two widely distributed, high-elevation North American conifers. 3. Empirically observed, warming-driven declines in recruitment led to rapid modeled population declines at the low-elevation, "warm edge" of subalpine forest and slow emergence of populations beyond the high-elevation, "cool edge". Because population declines in the forest occurred much faster than population emergence in the alpine, we observed range contraction for both species. For Engelmann spruce, this contraction was permanent over the modeled time horizon, even in the presence of increased moisture. For limber pine, lower sensitivity to warming may facilitate persistence at low elevations – especially in the presence of increased moisture – and rapid establishment above treeline, and, ultimately, expansion into the alpine. 4. Synthesis. Assuming 21st century warming and no additional moisture, population dynamics in high-elevation forests led to transient range contractions for limber pine and potentially permanent range contractions for Engelmann spruce. Thus, limitations to seedling recruitment with warming can constrain the pace of subalpine tree range shifts.
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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.