Find research datasets worth reusing

opencc-by-4.0Nov 2019View details →

Figure 3 in Concurrent Field Experiments and Satellite Surveys for Assessing Environmental Risk in the Coastal Zone of Southeast Baltic

Figure 3. Map of the study region showing CTD stations and ADCP transects.

opencc-by-4.0Nov 2019View details →

Figure 2. 2015 in Concurrent Field Experiments and Satellite Surveys for Assessing Environmental Risk in the Coastal Zone of Southeast Baltic

Figure 2. 2015 traffic density map of southeast Baltic (© Marine Traffic).

opencc-by-4.0Dec 2018View details →

Figure 4 in Assessments of environmental variables affecting the spatiotemporal distribution and habitat preferences of living Ostracoda (Crustacea) species in the Enez Lagoon Complex (Enez-Evros Delta, Turkey)

Figure 4. Salinity tolerance diagram of Ostracoda determined in the Enez lagoons.

opencc-by-4.0Jul 2024View details →

Assessing Patterns of Metazoans in the Global Ocean using Environmental DNA

<p>Data for the above publication which is in RSOS. Code is available here, https://github.com/ngeraldi/Global_ocean_genome_analysis.  The 5 files include the amplicon data (Malaspina and Tara) and all metagenome data is in DMAP_biomass_apr19 (it is not biomass, it is metagenome data). Global layers contain the metadata- april18 is amplicon data and genome is the metagenome data.</p> <p>Abstract:</p> <p>Documenting large-scale patterns of animals in the ocean and determining the drivers of these patterns is needed for conservation efforts given the unprecedented rates of change occurring within marine ecosystems. We used existing datasets from two global expeditions, <em>Tara </em>Oceans<em> </em>and <em>Malaspina</em>, that circumnavigated the oceans, and sampled down to 4000 meters to assess metazoans from eDNA extracted from seawater. We describe patterns of taxonomic richness within metazoan phyla and orders based on metabarcoding and infer relative abundance of phyla using metagenome datasets, and relate these data with environmental variables. Arthropods had the greatest taxonomic richness of metazoan phyla at the surface, while cnidarians had the greatest richness in pelagic zones. Half of the marine metazoan eDNA from metagenome datasets was from arthropods, followed by cnidarians and nematodes. We found that mean surface temperature and primary productivity were positively related with metazoan taxonomic richness. Our findings concur with existing knowledge that temperature and primary productivity are important drivers of taxonomic richness for specific taxa at the ocean’s surface, but these correlations are less evident in the deep ocean. Massive sequencing of eDNA can improve understanding of animal distributions, particularly for the deep ocean where sampling is challenging.</p>

opencc-by-4.0Dec 2018View details →

A Comprehensive Assessment of Demographic, Environmental and Host Genetic Associations with Gut Microbiome Diversity in Healthy Individuals (GWAS)

<p>GWAS summary statistics accompanying manuscript  "A Comprehensive Assessment of Demographic, Environmental and Host Genetic Associations with Gut Microbiome Diversity in Healthy Individuals".</p>

Table 1 in Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA

<p><b>Table 1.</b> Number of field samples (including controls) for each qPCR assay at each site sampled for eDNA in 2018 and 2019 in western Lake Erie. DR = Detroit River, HP = Hot Ponds, MB = Maumee Bay. Note that samples are site-specific.</p><table><tbody><tr><th>Site</th><th>Year</th></tr><tr><th>2018</th><th>2019</th></tr><tr><th>Assay</th><th>Samples</th><th>Assay</th><th>Samples</th></tr></tbody><tbody><tr><th>DR</th><td>GCTM10 GCTM22 GCTM32</td><td>78 78 78</td><td>GCTM10 GCTM22 GCTM32</td><td>81 81 81</td></tr><tr><th>HP</th><td>GCTM10 GCTM22 GCTM32</td><td>77 77 77</td><td>GCTM10 GCTM22 GCTM32</td><td>82 82 82</td></tr><tr><th>MB</th><td>GCTM10 GCTM22 GCTM32</td><td>78 78 78</td><td>GCTM10 GCTM22 GCTM32</td><td>80 80 80</td></tr></tbody></table>

Table 4 in Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA

<p><b>Table 4.</b> Percentage of positive eDNA replicate detections in each month and site in 2018 and 2019 in western Lake Erie (based on at least one positive detection on at least one marker and one replicate). All markers (GCTM10, GCTM 22, GCTM32) were used to calculate these proportions. Samples were collected monthly from June to November for each site. The number of telemetered grass carp detected within 7 days before sampling for eDNA is denoted in parentheses. Acoustic telemetry receivers in MB in 2018 were not available. DR = Detroit River, HP = Hot Ponds, and MB = Maumee Bay. NA denotes when acoustic telemetry receivers were not in operation.</p><table><tbody><tr><th>Year</th></tr><tr><th>Site</th><th>2018</th><th>2019</th></tr><tr><th></th><th>June</th><th>July</th><th>Aug</th><th>Sept</th><th>Oct</th><th>Nov</th><th>May</th><th>June</th><th>July</th><th>August</th><th>Oct</th><th>Nov</th></tr></tbody><tbody><tr><th>DR</th><td>0.0%</td><td>2.3%</td><td>2.3%</td><td>0.0%</td><td>0.0%</td><td>0.0%</td><td>4.5%</td><td>10.6</td><td>14.1</td><td>17.4%</td><td>14.1%</td><td>2.2%</td></tr><tr><td>(1)</td><td>(1)</td><td>(2)</td><td>(1)</td><td>(2)</td><td>(0)</td><td>(1)</td><td>% (1)</td><td>% (1)</td><td>(2)</td><td>(2)</td><td>(0)</td></tr><tr><th>HP</th><td>0.0%</td><td>0.1%</td><td>4.1%</td><td>2.2%</td><td>15.8%</td><td>0.0%</td><td>9.0%</td><td>1.5%</td><td>34.8</td><td>1.5%</td><td>15.8%</td><td>22.7%</td></tr><tr><td>(1)</td><td>(1)</td><td>(2)</td><td>(2)</td><td>(3)</td><td>(NA)</td><td>(2)</td><td>(2)</td><td>% (2)</td><td>(3)</td><td>(2)</td><td>(2)</td></tr><tr><th>MB</th><td>12.0%</td><td>0.0%</td><td>0.0%</td><td>0.0%</td><td>0.0%</td><td>0.0%</td><td>0.0%</td><td>6.1%</td><td>37.1</td><td>8.3%</td><td>8.3%</td><td>0.0%</td></tr><tr><td>(NA)</td><td>(NA)</td><td>(NA)</td><td>(NA)</td><td>(NA)</td><td>(NA)</td><td>(0)</td><td>(0)</td><td>% (0)</td><td>(0)</td><td>(0)</td><td>(0)</td></tr></tbody></table>

Table 3 in Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA

<p><b>Table 3.</b> Candidate set of hierarchical occupancy models used to estimate probability of grass carp eDNA occurrence among sites (ψ), the conditional probability of grass carp eDNA occurrence at a sampling locality within a site given that grass carp were present at the site (Θ), and the conditional probability of eDNA detection on replicate filters collected at a sampling locality given that the species is present at the sampling locality <i>(p</i>) from three sites in western Lake Erie sampled in 2018 and 2019. Covariates included location (site), time (Month) and probe type (GCTM10, GCTM22, GCTM32). Model comparison was evaluated with the Widely Applicable Information Criterion (WAIC).</p><table><tbody><tr><th>Model</th><th>WAIC</th><th>Δ WAIC</th><th>Lack of fit</th><th>Predicted Variance</th></tr></tbody><tbody><tr><th>ψ(Site)Θ(Site)p(.)</th><td>309.44</td><td>-</td><td>298.70</td><td>18.63</td></tr><tr><th>ψ(.)Θ(Site)p(.)</th><td>309.50</td><td>0.06</td><td>298.99</td><td>10.73</td></tr><tr><th>ψ(.)Θ(Month)p(.)</th><td>317.61</td><td>8.18</td><td>299.05</td><td>18.56</td></tr><tr><th>ψ(Season)Θ(.)p(.)</th><td>317.67</td><td>8.24</td><td>299.01</td><td>18.65</td></tr><tr><th>ψ(Month)Θ(.)p(.)</th><td>317.72</td><td>8.28</td><td>299.04</td><td>18.67</td></tr><tr><th>ψ(Season)Θ(Season)p(.)</th><td>317.84</td><td>8.40</td><td>299.04</td><td>18.79</td></tr><tr><th>ψ(.)Θ(Season)p(.)</th><td>317.74</td><td>8.31</td><td>299.07</td><td>18.66</td></tr><tr><th>ψ(Site)Θ(.)p(.)</th><td>317.94</td><td>8.51</td><td>299.04</td><td>18.90</td></tr><tr><th>ψ(.)Θ(.)p(.)</th><td>325.00</td><td>15.57</td><td>305.50</td><td>20.21</td></tr><tr><th>ψ(Season)Θ(Site)p(.)</th><td>325.41</td><td>15.98</td><td>305.49</td><td>19.91</td></tr><tr><th>ψ(Site + Season)Θ(.)p(.)</th><td>325.59</td><td>16.16</td><td>305.44</td><td>20.15</td></tr><tr><th>ψ(Site)Θ(Season)p(.)</th><td>325.72</td><td>16.29</td><td>305.48</td><td>20.23</td></tr><tr><th>ψ(Site + Season)Θ(Site + Season)p(.)</th><td>325.92</td><td>16.49</td><td>305.49</td><td>20.43</td></tr><tr><th>ψ(.)Θ(Site + Season)p(.)</th><td>326.37</td><td>16.94</td><td>305.52</td><td>20.84</td></tr><tr><th>ψ(Site)Θ(Month)p(.)</th><td>329.57</td><td>20.14</td><td>308.65</td><td>20.92</td></tr><tr><th>ψ(Month)Θ(Month)p(.)</th><td>330.14</td><td>20.71</td><td>308.66</td><td>21.84</td></tr><tr><th>ψ(Site + Season)Θ(Site)p(Probe)</th><td>377.63</td><td>68.20</td><td>276.90</td><td>100.72</td></tr><tr><th>ψ(Site + Season)Θ(.)p(Probe)</th><td>378.35</td><td>68.92</td><td>277.00</td><td>101.34</td></tr><tr><th>ψ(Site + Season)Θ(Site + Season)p(Probe)</th><td>378.42</td><td>68.99</td><td>277.00</td><td>101.41</td></tr><tr><th>ψ(Site + Season)Θ(Season)p(Probe)</th><td>378.55</td><td>69.12</td><td>277.09</td><td>101.46</td></tr><tr><th>ψ(Season)Θ(Site + Season)p(Probe)</th><td>379.41</td><td>69.98</td><td>277.28</td><td>102.10</td></tr><tr><th>ψ(Site)Θ(Site + Season)p(Probe)</th><td>379.62</td><td>70.19</td><td>277.40</td><td>102.21</td></tr><tr><th>ψ(.)Θ(Site + Season)p(Probe)</th><td>379.88</td><td>70.45</td><td>277.31</td><td>102.57</td></tr><tr><th>ψ(Site + Month)Θ(.)p(.)</th><td>383.56</td><td>74.13</td><td>282.86</td><td>100.69</td></tr><tr><th>ψ(Site + Month)Θ(Site + Month)p(.)</th><td>385.47</td><td>76.04</td><td>283.38</td><td>102.09</td></tr><tr><th>ψ(Site + Month)Θ(Site + Month)p(Probe)</th><td>386.95</td><td>77.52</td><td>282.90</td><td>104.05</td></tr><tr><th>ψ(.)Θ(Site + Month)p(.)</th><td>396.44</td><td>87.01</td><td>292.14</td><td>104.29</td></tr><tr><th>ψ(.)Θ(.)p(Probe)</th><td>396.45</td><td>87.01</td><td>292.14</td><td>104.29</td></tr></tbody></table>

Table 2 in Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA

<p><b>Table 2.</b> Gene region, primer, and probe sequences used to amplify GCTM10,GCTM22, and GCTM32 for grass carp.</p><table><tbody><tr><th>Gene</th><th>Primers and Probes</th><th>Sequence</th></tr></tbody><tbody><tr><th>ND2</th><td>Forward</td><td>5′- CCYTACGTACTCGCAATTCTAC -3′</td></tr><tr><th>ND2</th><td>Reverse</td><td>5′- GTGGTGGTGTTGGGCTATTA -3′</td></tr><tr><th>ND2</th><td>Probe</td><td>5′- VIC- ACCCTAACCTTTGCTAGCTCCCAC -MGBNFQ-3′</td></tr><tr><th>COII</th><td>Forward</td><td>5′- CCGACTCCTAGAAACAGATCAC -3′</td></tr><tr><th>COII</th><td>Reverse</td><td>5′- GGGACAGCTCAGGAATGTAATA -3′</td></tr><tr><th>COII</th><td>Probe</td><td>5′- 56-FAM- CCAGTTCGT/ZEN/GTCCTAGTATCTGCCGA -3IABkFQ -3′</td></tr><tr><th>COIII</th><td>Forward</td><td>5′- CCACGGACTACACGTCATTATT -3′</td></tr><tr><th>COIII</th><td>Reverse</td><td>5′-GATGTTCGGATGTAAAGTGGTATTG -3′</td></tr><tr><th>COIII</th><td>Probe</td><td>5′-NED- TTCCTAGCTGTTTGCCTTCTCCGT -MGBNFQ-3′</td></tr></tbody></table>

opencc-zeroOct 2022View details →

Magnitude-duration relationships of physiological sensitivity and environmental exposure improve climate change vulnerability assessments

<p class="MsoNormal"><span>Integrating thermal physiology with environmental temperature is essential to understanding distributions of species and vulnerability to climate change. Warming tolerance—the difference between an organism's maximum thermal tolerance (T<sub>max</sub>) and maximum habitat temperature (T<sub>hab</sub>)—is frequently used to integrate organismal sensitivity and environmental exposure. Traditionally, applications of warming tolerance define T<sub>max</sub> and T<sub>hab</sub> as invariable magnitudes, yet tolerance magnitude depends on exposure duration and diel temperature cycles expose organisms to a range of temperature magnitudes and durations. How traditional (<em>i.e.</em>, acute) estimates of warming tolerance compare to estimates from prolonged exposures remains poorly understood. In this study, magnitude-duration curves for tolerances of one cold-water, two cool-water, and one warm-water species of freshwater fish were compiled from the literature and compared to magnitude-duration exposures from 66 streams across the eastern United States. Warming tolerances were estimated for exposure durations spanning 0.01 to 24 hours. Current acute (0.01 hours) warming tolerances ranged from median 6.30°C for the cold-water species to 9.68°C for the warm-water species. The lowest warming tolerances corresponded to prolonged exposures lasting median 3.85 to 5.30 hours among species and were 2.51 to 4.38°C lower than acute estimates. Although acute estimates remained positive in historically occupied and unoccupied streams (6.30°C versus 2.33°C), estimates based on prolonged exposure were positive at occupied streams of the cold-water species but transitioned to negative in unoccupied streams (2.19°C versus -1.12°C). Acute warming tolerances for the cold-water species also remained positive under future climate (6.29 to 4.23°C) but approached zero at prolonged durations (2.19 to 0.09°C) and transitioned to negative for 47.2% of streams. Results demonstrate that acute measures of T<sub>max</sub> and T<sub>hab</sub> overestimate warming tolerances and therefore underestimate climate change vulnerability. Integrating magnitude-duration relationships into warming tolerance estimates can elucidate physiological mechanisms underlying species distributions and can improve accuracy of climate change vulnerability assessments.</span></p>

opencc-by-4.0Jun 2022View details →

Environmental Life Cycle Assessment Video

<p>A set of explanatory videos was produced about sustainability analysis within the project, including Environmental Life Cycle Assessment, Social Life Cycle Assessment, and Life Cycle Costing. These informational videos were primarily produced for the International School on Water Reuse held at the Chemistry Department of the Torino University in Italy in late September 2022, but they were also placed on the project website and circulated on social media.</p>

opencc-by-4.0Sep 2022View details →

Assessing a megadiverse but poorly known community of fishes in a tropical mangrove estuary through environmental DNA (eDNA) metabarcoding

<p>Biodiversity surveys are crucial for monitoring the status of threatened aquatic ecosystems, such as tropical estuaries and mangroves. Conventional monitoring methods are intrusive, time-consuming, substantially expensive, and often provide only rough estimates in complex habitats. An advanced monitoring approach, environmental DNA (eDNA) metabarcoding, is promising, although only few applications in tropical mangrove estuaries have been reported. In this study, we explore the advantages and limitations of an eDNA metabarcoding survey on the fish community of the Merbok Estuary (Peninsular Malaysia). COI and 12S eDNA metabarcoding assays collectively detected 178 species from 127 genera, 68 families, and 25 orders. Using this approach, significantly more species have been detected in the Merbok Estuary over the past decade (2010–2019) than in conventional surveys, including several species of conservation importance. However, we highlight three limitations: (1) in the absence of a comprehensive reference database the identities of several species are unresolved; (2) some of the previously documented specimen-based diversity was not captured by the current method, perhaps as a consequence of PCR primer specificity, and (3) the detection of non-resident species—stenohaline freshwater taxa (e.g., cyprinids, channids, osphronemids) and marine coral reef taxa (e.g., holocentrids, some syngnathids and sharks), not known to frequent estuaries, leading to the supposition that their DNA have drifted into the estuary through water movements. The community analysis revealed that fish diversity along the Merbok Estuary is not homogenous, with the upstream more diverse than further downstream. This could be due to the different landscapes or degree of anthropogenic influences along the estuary. In summary, we demonstrated the practicality of eDNA metabarcoding in assessing fish community and structure within a complex and rich tropical environment within a short sampling period. However, some limitations need to be considered and addressed to fully exploit the efficacy of this approach.</p>

opencc-zeroDec 2022View details →

The concurrent assessment of agronomic, ecological, and environmental variables enables better choice of agroecological service crop termination management

<p>1. Although organic farming was originally promoted as an alternative farming system to address agronomic, environmental, and ecological issues, its conventionalisation has led to an intensification and specialisation of production. In light of this, several studies have questioned the environmental benefits of organic farming as well as its agronomic viability. Thus, there is a need to improve organic vegetable systems to reduce their environmental impact without affecting their productivity. To tackle this challenge, European farmers and researchers have recently started to focus on agroecological service crops (ASCs). However, few studies have simultaneously evaluated the agronomic, environmental, and ecological aspects of ASC management under different European pedo-climatic conditions.</p> <p>2. We evaluated effects of the ASC management strategies: no-till roller crimping (NT-RC) and green manuring (T-GM) on cropping system performance using agronomic, environmental, and ecological indicators, to exemplify the need for multidimensional analysis to understand management implications for addressing environmental and agronomic challenges. We combined the results from eleven organic vegetable field trials conducted in seven European countries over a period of two years to test for general trends.</p> <p>3. Our results provide solid evidence that NT-RC management across different pedo-climatic conditions in Europe enhances the activity density of ground and rove beetles, and improves both the potential energy recycling within the system and weed control. However, in NT-RC plots lower cash crop yield and quality, energetic efficiency of production, and activity density of spiders was observed compared to T-GM.</p> <p>4. Synthesis and applications: Multidimensional analyses using agronomic, environmental, and ecological indicators are required to understand the implications of agricultural management in agroecosystem functioning. Introducing agroecological service crops combined with the use of no-till roller crimping is a promising strategy for improving agronomic performance (e.g., fewer weeds) and reducing environmental (e.g., increasing the potentially recyclable energy), and ecological (e.g., enhancing the activity density of beneficial taxa such as ground and rove beetles) impacts. However, our study also indicates a need for agronomic and environmental improvements while promoting a wider acceptance of this strategy.29-Nov-2021 --</p>

opencc-zeroFeb 2023View details →

Data for: Assessment of cryogenic pretreatment for simulating environmental weathering in the formation of surrogate micro- and nanoplastics from agricultural mulch film

<p>Microplastics (MPs) and nanoplastics (NPs) from mulch films and other plastic materials employed in vegetable and small fruit production pose a major threat to agricultural ecosystems. For conducting controlled studies on MPs' and NPs' (MNPs') ecotoxicity to soil organisms and plants and fate and transport in soil, surrogate MNPs are<br>required that mimic MNPs that form in agricultural fields. We have developed a procedure to prepare MPs from plastic films or pellets using mechanical milling and sieving, and conversion of the resultant MPs into NPs through wet grinding, both steps of which mimic the degradation and fragmentation of plastics in nature. The major goal of this study was to determine if cryogenic exposure of two biodegradable mulch films effectively mimics the embrittlement caused by environmental weathering in terms of the dimensional, thermal, chemical, and biodegradability properties of the formed MNPs. We found differences in size, surface charge, thermal and chemical properties, and biodegradability in soil between MNPs' prepared from cryogenically treated vs. environmentally weathered films, related to the photochemical reactions occurring in the environment that were not mimicked by cryogenic treatment, such as depolymerization and cross-link formation. We also investigated the size reduction process for NPs and found that the size distribution was bimodal, with populations centered at 50 nm and 150–300 nm, and as the size reduction process progressed, the former subpopulation's proportion increased. The biodegradability of MPs in soil was greater than for NPs, a counter-intuitive trend since greater surface area exposure for NPs would increase biodegradability. The result is associated with differences in surface and chemical properties and to minor components that are readily leached out during the formation of NPs. In summary, the use of weathered plastics as feedstock would likely produce MNPs that are more realistic than cryogenically-treated unweathered films for use in experimental studies.</p>

opencc-zeroJun 2023View details →

Fastq sequence files supporting: Assessing the degradation of environmental DNA and RNA based on genomic origin in a metabarcoding context

<p>Molecular tools of species identification based on eNAs (environmental nucleic acids; eDNA and eRNA) have the potential to greatly transform biodiversity science. However, the ability of eNAs to obtain "real-time" biodiversity estimates may be complicated by the differential persistence and degradation dynamics of the molecular template (eDNA or eRNA) and the barcode marker used. Here, we collected water samples over a 28-day period to comparatively assess species detection using eDNA and eRNA metabarcoding of two distinct barcode markers—a mitochondrial mRNA marker (COI) and a nuclear rRNA marker (18S)—following complete removal of <em>Arthropoda </em>taxa in a semi-natural freshwater system. Our findings demonstrate that <em>Arthropoda </em>community composition was largely influenced by marker choice, rather than molecular template, individual microcosm, or sampling time point. Further, although eRNA may capture similar species diversity as the established eDNA method, this finding may be marker dependent. Although we found little to no difference in decay rates observed among sample groups (COI eDNA, COI eRNA, 18S eDNA, 18S eRNA), this result is likely due to limitations in the ability of eNA-based metabarcoding to provide a strong correlation between true eNA copy numbers present in the environment and final read counts obtained (following the metabarcoding workflow). Collectively, our findings provide further support for the use of multi-marker assessments in metabarcoding surveys to unravel the broadest taxonomic diversity possible, highlight the limitations of eNA metabarcoding methods in providing accurate decay rate estimates, as well as establish the need for further comparative studies using both metabarcoding and single-species detection methods to assess the persistence and degradation dynamics of eNAs for a diverse range of taxa.</p>

opencc-by-4.0Dec 2022View details →

Assessing and managing environmental hazards of polymers: historical development, science advances and policy options

<p>Supporting information (open data) from Assessing and managing environmental hazards of polymers: historical development, science advances and policy options</p>

publicJul 2022View details →

Data for: Socio-economic and environmental life cycle assessment of complete streets

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publicNov 2024View details →

Data from: Refining sampling efforts for fish diversity assessment in subtropical urban estuarine and oceanic waters using environmental DNA with multiple primers

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publicDec 2021View details →

Socio-economic and environmental impacts of ants: data to support global assessments

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