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70 results for “genetic monitoring”
Sacramento trawl, Delta Juvenile Fish Monitoring Program, Genetic Determination of Population of Origin 2017-2021
Central Valley Chinook Salmon populations differ in their Endangered Species Act listing status. It is often difficult to distinguish individuals from the different Evolutionarily Significant Units. As such, many of the salmon monitoring and evaluation efforts in the Central Valley and San Francisco Bay-Delta are hampered by uncertainty about population (stock) identification and proportional effects of management actions (Dekar et al. 2013; IEP 2019). Studies have identified that the current identification method (length-at-date models) of juvenile Chinook salmon (Fisher 1992) captured in the watershed vary in their accuracy, particularly for spring-run (NMFS 2013; Harvey et al. 2014; Merz et al. 2014). The inaccuracy of the size-based methods is likely due to differences in fish distribution during early rearing, habitat-specific growth rates, and inter-annual variability in temperatures and food availability that lead to overlap in size ranges among stocks. The primary objective of this project was the genetic classification (to race; Evolutionary Significant Unit) of Chinook Salmon captured from State Water Project and Central Valley Project fish protection facilities and Interagency Ecological Program monitoring programs. The population-of-origin was determined for sampled fish by comparing their genotypes to reference genetic baselines. Genetic methods, having less statistical uncertainty that size-based models for population identification, were intended to directly target (and reduce) one source of uncertainty in the estimation of loss (take) from water diversions (operations) and develop the information necessary for understanding stock-specific distribution, habitat utilization, abundance, and life history variation. This project supports recommendations from the Interagency Ecological Program’s Salmon and Sturgeon Assessment of Indicators by Life Stage and Interagency Ecological Program Science Agenda efforts to improve Central Valley salmonid monitoring
Chipps Island trawl, Delta Juvenile Fish Monitoring Program, Genetic Determination of Population of Origin 2017-2021
Central Valley Chinook Salmon populations differ in their Endangered Species Act listing status. It is often difficult to distinguish individuals from the different Evolutionarily Significant Units. As such, many of the salmon monitoring and evaluation efforts in the Central Valley and San Francisco Bay-Delta are hampered by uncertainty about population (stock) identification and proportional effects of management actions (Dekar et al. 2013; IEP 2019). Studies have identified that the current identification method (length-at-date models) of juvenile Chinook salmon (Fisher 1992) captured in the watershed vary in their accuracy, particularly for spring-run (NMFS 2013; Harvey et al. 2014; Merz et al. 2014). The inaccuracy of the size-based methods is likely due to differences in fish distribution during early rearing, habitat-specific growth rates, and inter-annual variability in temperatures and food availability that lead to overlap in size ranges among stocks. The primary objective of this project was the genetic classification (to race; Evolutionary Significant Unit) of Chinook Salmon captured from State Water Project and Central Valley Project fish protection facilities and Interagency Ecological Program monitoring programs. The population-of-origin was determined for sampled fish by comparing their genotypes to reference genetic baselines. Genetic methods, having less statistical uncertainty that size-based models for population identification, were intended to directly target (and reduce) one source of uncertainty in the estimation of loss (take) from water diversions (operations) and develop the information necessary for understanding stock-specific distribution, habitat utilization, abundance, and life history variation. This project supports recommendations from the Interagency Ecological Program’s Salmon and Sturgeon Assessment of Indicators by Life Stage and Interagency Ecological Program Science Agenda efforts to improve Central Valley salmonid monitoring
Spineless and overlooked: DNA metabarcoding of autonomous reef monitoring structures reveals intra- and interspecific genetic diversity in Mediterranean invertebrates
<p>Sequence data and stepwise pipeline outputs associated with the article "Spineless and overlooked: DNA metabarcoding of autonomous reef monitoring structures reveals intra- and interspecific genetic diversity in Mediterranean invertebrates".</p> <p>Preprint available here: <a href="https://doi.org/10.22541/au.167085544.47638352/v1">10.22541/au.167085544.47638352/v1</a></p> <p>Sequence data is deposited in fastq-format in folders by region (Palinuro.tar.gz, Livorno.tar.gz, and Rovinj.tar.gz) and a separate folder for controls (Controls.tar.gz). Each fastq-file contains sequences for a single PCR replicate named by sample and replicate number. Sample names are described in spineless_sample_names.csv. Positive control sequences are described in SM1_positive_controls.csv. Stepwise pipeline outputs are available in the folder Pipeline_outputs_stepwise.zip</p> <p>Scripts used to generate pipeline outputs as well as other aspects of the final article are available at <a href="https://github.com/thomasdotter/spineless-haplotypes">https://github.com/thomasdotter/spineless-haplotypes</a>.</p> <p> </p>
GECCO Industrial Challenge 2017 Dataset: A water quality dataset for the 'Monitoring of drinking-water quality' competition at the Genetic and Evolutionary Computation Conference 2017, Berlin, Germany.
<p>Dataset of the 'Industrial Challenge: Monitoring of drinking-water quality' competition hosted at The Genetic and Evolutionary Computation Conference (GECCO) July 15th-19th 2017, Berlin, Germany</p> <p> </p> <p>The task of the competition was to develop an anomaly detection algorithm for a water- and environmental data set.</p> <p> </p> <p>Included in zenodo: </p> <p>- dataset of water quality data</p> <p>- additional material and descriptions provided for the competition</p> <p> </p> <p>The competition was organized by:</p> <p>M. Friese, J. Stork, A. Fischbach, M. Rebolledo, T. Bartz-Beielstein (TH Köln)</p> <p> </p> <p>The dataset was provided and prepared by:</p> <p>Thüringer Fernwasserversorgung,</p> <p>IMProvT research project (S. Moritz)</p> <p><br> </p> <p>Industrial Challenge: Monitoring of drinking-water quality</p> <p> </p> <p>Description:</p> <p>Water covers 71% of the Earth's surface and is vital to all known forms of life. The provision of safe and clean drinking water to protect public health is a natural aim. Performing regular monitoring of the water-quality is essential to achieve this aim.</p> <p>Goal of the GECCO 2017 Industrial Challenge is to analyze drinking-water data and to develop a highly efficient algorithm that most accurately recognizes diverse kinds of changes in the quality of our drinking-water.</p> <p> </p> <p>Submission deadline:</p> <p>June 30, 2017</p> <p>Official webpage:</p> <p><a href="http://www.spotseven.de/gecco-challenge/gecco-challenge-2017/">http://www.spotseven.de/gecco-challenge/gecco-challenge-2017/</a></p>
Figure 1 in Non-invasive genetic study and population monitoring of the brown bear (Ursus arctos) (Mammalia: Ursidae) in Kastoria region - Greece
Figure 1. The study area in Kastoria region and capture locations (red dots) for the 75 living bears.
Testing the effectiveness of genetic monitoring using genetic non-invasive sampling
<p>1. Effective conservation requires accurate data on population genetic diversity, inbreeding, and genetic structure. Increasingly, scientists are adopting genetic non-invasive sampling as a cost-effective population-wide genetic monitoring approach. Genetic non-invasive sampling has, however, known limitations which may impact the accuracy of downstream genetic analyses.</p> <p>2. Here, using high quality SNP data from blood/tissue sampling of a free-ranging koala population (n = 430), we investigated how the reduced SNP panel size and call rate typical of genetic non-invasive samples (derived from experimental and field trials) impacts the accuracy of genetic measures, and also the effect of sampling intensity on these measures.</p> <p>3. We found that genetic non-invasive sampling at small sample sizes (14% of population) can provide accurate population diversity measures, but slightly underestimated population inbreeding coefficients. Accurate measures of internal relatedness required at least 33% of the population to be sampled. Accurate geographic and genetic spatial autocorrelation analysis requires between 28% and 51% of the population to be sampled.</p> <p>4. We show that genetic non-invasive sampling at low sample sizes can provide a powerful tool to aid conservation decision-making and provide recommendations for researchers looking to apply these techniques to free-ranging systems.</p>
Fig. 1 in Camera traps and genetic identification of faecal samples for detection and monitoring of an endangered ungulate
Fig. 1. Distribution of deployed camera traps showing presence (black circles) and non-detection (purple circles) and genetic sampling locations showing presence (black triangles) and non-detection (purple triangles) of Eld's deer. Inset map shows the location of Chhaeb Wildlife Sanctuary in Cambodia (black rectangle). Background shows proportion of tree cover from WorldCover land cover map (© ESA WorldCover project 2020 / Contains modified Copernicus Sentinel data (2020) processed by ESA WorldCover consortium).
Data, code, and supplementary materials for Pearman P. B., Broennimann, O., et al. Monitoring species genetic diversity in Europe varies greatly and overlooks potential climate change impacts. Nature Ecology & Evolution
<p>The repository contains several archives of digital materials that were used and/or produced in the analyses presented in Pearman, P. B. and Broennimann et al. Monitoring species genetic diversity in Europe varies greatly and overlooks potential climate change impacts. <strong>Nature Ecology & Evolution</strong>, likely 2023. These archives include (1) Supplementary Materials files ; (2) Data and code to generate country-level maps and plots; and (3) data and code to generate all maps of species and joint climate niche marginality, all in G-zipped tar archives. Readme files are available in each archive to guide running of the scripts and identification of objects in the Supplementary Materials. Please see the paper for all co-authors names, and the methods, the results obtained, and discussion of their implications.</p> <p>This work is dedicated to the memory of our friend and colleague Michael Bruford (1963-2023).</p>
Testing the effectiveness of genetic monitoring using genetic non-invasive sampling
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Hare's affairs: lessons learnt from a noninvasive genetic monitoring for tracking mountain hare individuals
<p>Systematic monitoring of individuals and their abundance over time has become an important tool to provide information for conservation. For genetic monitoring studies, noninvasive sampling has emerged as a valuable approach, particularly so for elusive or rare animals. Here, we present the five-year results of an ongoing noninvasive genetic monitoring of mountain hares (<i>Lepus timidus</i>) in a protected area in the Swiss Alps. We used nuclear microsatellites and a sex marker to identify individuals and assign species to noninvasively collected feces samples. Through including a marker for sex identification, we were able to assess sex-ratio changes and sex-specific demographic parameters over time. Male abundance in the area showed high fluctuations and apparent survival for males was lower than for females. Generally, males and females showed only little temporary migration into and out of the study area. Additionally, using genotyped tissue samples from mountain hares, European hares (<i>Lepus europaeus</i>) and their hybrids, we were able to provide evidence for the first occurrence of a European hare in the study area at an elevation of 2300 m a.s.l. in spring 2016. For future monitoring studies, we suggest to include complementary analysis methods to reliably infer species identities of the individuals analyzed and thus, not only monitor mountain hare individual abundance, but also assess the potential threats given through competitive exclusion by and hybridization with the European hare.</p>
Data from: Evaluating genotyping-in-thousands by sequencing as a genetic monitoring tool for a climate sentinel mammal using non-invasive and archival samples
<p>Genetic tools for wildlife monitoring can provide valuable information on spatiotemporal population trends and connectivity, particularly in systems experiencing rapid environmental change. Though many DNA sequencing approaches still require high quality and quantity of DNA obtained from traditional sources (e.g. blood and tissue), rapid genotyping tools such as Genotyping-in-Thousands by sequencing (GT-seq) have improved our ability to make use of degraded and less concentrated DNA commonly obtained from non-invasive and archival samples. Here, we developed a multi-purpose GT-seq panel (307 single nucleotide polymorphisms) for a climate sentinel mammal (the American pika, <em>Ochotona princeps</em>) for use as a genetic tool for monitoring populations in the Canadian Rocky Mountains. We optimized the panel using contemporary tissue samples (n = 77) and subsequently applied it to archival tissue (n = 17) and contemporary fecal pellet samples (n = 129) to evaluate its effectiveness at identifying individuals and sex, estimating relatedness, and inferring population structure. The panel demonstrated high efficacy with contemporary and archival tissue samples (94.7% and 90.5% genotyping success, respectively) and negligible genotyping error (0.001% and 0.0%, respectively). Despite relatively high genotyping success for fecal pellet samples (79.7%), high genotyping error (28.4%) limited its power as a monitoring tool to assess genetic variation using non-invasive samples and highlighted the need for further optimization around sample and data collection.</p>
Genetic monitoring on the world's first MSC eco-labeled common octopus (O. vulgaris) fishery in western Asturias, Spain
<p><strong>Allele frequencies file containing:</strong></p> <ul> <li>15 populations</li> <li>13 microsatellite markers</li> </ul> <p><em><strong>Populations:</strong></em></p> <ul> <li>21PS: Pasaia (Basque country, Spain). Fishery season (FS): 2020-21</li> <li>18RB: Ribadesella (Asturias, Spain). FS: 2017-18</li> <li>21RB: Ribadesella (Asturias, Spain). FS: 2020-21</li> <li>18CU: Cudillero (Asturias, Spain). FS: 2017-18</li> <li>21CU: Cudillero (Asturias, Spain). FS: 2020-21</li> <li>07PV: Puerto de Vega (Asturias, Spain). FS: 2006-07</li> <li>18PV: Puerto de Vega (Asturias, Spain). FS: 2017-18</li> <li>21PV: Puerto de Vega (Asturias, Spain). FS: 2020-21</li> <li>18TP: Tapia de Casariego (Asturias, Spain). FS: 2017-18</li> <li>21TP: Tapia de Casariego (Asturias, Spain). FS: 2020-21</li> <li>21BU: Bueu (Galicia, Spain). FS: 2020-21</li> <li>07OL: Olhão (Algarve, Portugal). FS: 2006-07</li> <li>21OL: Olhão (Algarve, Portugal). FS: 2020-21</li> <li>21SA: San Andrés (Canary Islands, Spain). FS: 2020-21</li> <li>21BC: Barcelona (Catalonia, Spain). FS: 2020-21</li> </ul> <p><em><strong>Microsatellite markers (GenBank accession number):</strong></em></p> <p>OCT08 (AF197132); VULG15 (LC003035); VULG14 (LC003034); VULG07 (LC003028); OVUL10 (JN579699); VULG12 (LC003032); VULG13 (LC003033); VULG06 (LC003027); OVUL09 (JN579698); VULG04 (LC003026); OVUL08 (JN579697); OV10 (AF197134); VULG10 (LC003030).</p>
Monitoring genetic diversity with new indicators applied to an alpine freshwater top predator
<p><span>Genetic diversity is the basis for population adaptation and long-term survival, yet rarely considered in biodiversity monitoring. One key issue is the need for useful and straightforward indicators of genetic diversity. We monitored genetic diversity over 40 years (1970-2010) in metapopulations of brown trout (Salmo trutta) inhabiting 27 small mountain lakes representing 10 lake systems in central Sweden using >1200 fish per time point. We tested six newly proposed indicators; three were designed for broad, international use in the UN Convention on Biological Diversity (CBD and are currently applied in several countries. The other three were recently elaborated for national use by a Swedish science-management effort and applied for the first time here. The Swedish indicators use molecular genetic data to monitor genetic diversity within and between populations (indicators ΔH and ΔFST, respectively) and assess the effective population size (Ne-indicator). We identified 29 genetically distinct populations, all retained over time. Twelve of the 27 lakes harbored more than one population indicating that brown trout biodiversity hidden as cryptic, sympatric populations are more common than recognized. The Ne indicator showed values below the threshold (Ne≤500) in 20 populations with five showing Ne<100. Statistically significant genetic diversity reductions occurred in several populations. Metapopulation structure appears to buffer against diversity loss; applying the indicators to metapopulations suggest mostly acceptable rates of change in all but one system. The CBD indicators agreed with the Swedish ones but provided less detail. All these indicators are appropriate for managers to initiate monitoring of genetic biodiversity.</span></p>
Transitioning from microsatellites to SNP-based microhaplotypes in genetic monitoring programs: lessons from a 20-year time series of paired data.
<p>Many long-term genetic monitoring programs began before next-generation sequencing became widely available. Older programs can now transition to new marker systems usually consisting of 1000s of SNP loci, but there are still important questions about comparability, precision, and accuracy of key metrics estimated using SNPs. Ideally, transitioned programs should capitalize on new information without sacrificing continuity of inference across the time series. We combined existing microsatellite-based genetic monitoring information with SNP-based microhaplotypes obtained from archived samples of Rio Grande silvery minnow (<em>Hybognathus amarus</em>) across a 20-year time series to evaluate point estimates and trajectories of key genetic metrics. Demographic and genetic monitoring bracketed multiple collapses of the wild population, and included cases where captive-born repatriates comprised the majority of spawners in the wild. Even with smaller sample sizes, microhaplotypes yielded comparable and in some cases more precise estimates of variance genetic effective population size, multilocus heterozygosity and inbreeding compared to microsatellites because many more microhaplotype loci were available. Microhaplotypes also recorded shifts in allele frequencies associated with population bottlenecks. Trends in microhaplotype-based inbreeding metrics were associated with the fraction of hatchery-reared repatriates to the wild, and should be incorporated into future genomic monitoring. Although differences in accuracy and precision of some metrics were observed between marker types, biological inferences and management recommendations were consistent.</p>
Country‐wide genetic monitoring over 21 years reveals lag in genetic recovery despite spatial connectivity in an expanding carnivore (Eurasian otter, Lutra lutra) population
<p>Numerous terrestrial mammal species have experienced extensive population declines during past centuries, due largely to anthropogenic pressures. For some species, including the Eurasian otter (<em>Lutra lutra</em>), environmental and legal protection has more recently led to population growth and recolonisation of parts of their historic ranges. While heralded as conservation successes, only a few such recoveries have been examined from a genetic perspective, i.e. whether genetic variability and connectivity have been restored. We here use large-scale and long-term genetic monitoring data from UK otters, whose population underwent a well-documented population decline between the 1950s to 1970s, to explore the dynamics of a population re-expansion over a 21-year period. We genotyped otters from across Wales and England at five time points between 1994 and 2014 using 15 microsatellite loci. We used this combination of long-term temporal and large-scale spatial sampling to evaluate 3 hypotheses relating to genetic recovery; that (i) gene flow between sub-populations would increase over time, (ii) genetic diversity of previously isolated populations would increase, and that (iii) genetic structuring would weaken over time. Although we found an increase in inter-regional gene flow and admixture levels among subpopulations, there was no significant temporal change in either heterozygosity or allelic richness. Genetic structuring among the main sub-populations hence remained strong and showed a clear historical continuity. These findings highlight an underappreciated aspect of population recovery of endangered species, that genetic recovery may often lag behind the processes of spatial and demographic recovery. In other words, the restoration of physical connectivity of populations does not necessarily lead to genetic connectivity. Our findings emphasise the need for genetic data as an integral part of conservation monitoring, to enable the potential vulnerability of populations to be evaluated.</p>
Genetic monitoring of steelhead in the Klickitat River to estimate productivity, straying, and migration timing
<div> <p>Salmonids with complex life history variation present challenges for conservation management, but genetic approaches alongside fisheries monitoring can address questions regarding viability of natural populations. We genotyped adult (n=3,108) and juvenile (n=2,624) samples of anadromous <em>Oncorhynchus</em> <em>mykiss</em> that were collected in the Klickitat River, WA, USA at traps in the lower drainage to examine tributary level productivity, straying from outside sources and variation in adult migration timing. Genetic assignment of steelhead from this system indicated that the majority were produced within or near tributaries of the middle Klickitat River (juvenile mean = 72.8%; adult mean = 87.3%). Analyses with parentage-based tagging identified that most hatchery-origin adults were assigned to the Skamania Hatchery (80.8%) as expected since this has been the release stock for decades within the Klickitat River drainage. Hatchery-origin adults were also identified from programs operating outside the Klickitat River, which were primarily strays from Snake River hatcheries. Most natural-origin steelhead were assigned to the Klickitat River, but there were also natural-origin fish identified as strays from other regions of the Columbia River (22.3% of natural returns). We also examined genes known to be associated with migration timing in adult steelhead observed at the trap and observed a strong relationship between migration date and alleles for early and late migration, but individual outliers were detected across seasons. Our results indicate that genetic variation of steelhead in the Klickitat River has been influenced by hatchery programs as well as natural-origin straying from other sub-basins, but genetic diversity remains high throughout the sub-basin, and both early and late migration alleles are maintained. The genetic diversity present in Klickitat River steelhead may enable this Endangered Species Act listed (threatened) species to better adapt to stochastic environmental conditions compared to less diverse populations. </p> </div>
Hare's affairs: Lessons learnt from a noninvasive genetic monitoring for tracking mountain hare individuals
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Data from: Genetic monitoring of brown trout released into a novel environment: Establishment and genetic impact on natural populations
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Data from: Time is of the essence: using archived samples to develop a GT-seq panel to preserve continuity of ongoing genetic monitoring
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Transitioning from microsatellites to SNP-based microhaplotypes in genetic monitoring programs: lessons from a 20-year time series of paired data.
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