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Near continuous methane and CO2 fluxes measured along a transect on an ombrotrophic fen in Southern Sweden from August 2017-September 2019 using an automated greenhouse gas flux platform SkyLine2D. The impacts of drought (in 2018 the mire experienced drought conditions) and different vegetation types (sedge, heather, sphagnum or open water; 6 replicated for each) on the fluxes were determined. Fluxes were measured within collars of 20-cm diameter, 4-min at each collar. CH4 and CO2 fluxes were detected using a Licor infrared gas analyser (IRGA, LI-8100, Licor, NE, USA) to measure CO2 and a cavity ringdown laser (CRD, LGR U-GGA-91, Los Gatos Research, CA USA) to measure both CO2 and CH4. Fluxes of CO2 and CH4 were calculated using linear regression; a deadband of at least 20 seconds was allowed for the chamber headspace to mix and a window of 90 seconds was used for CO2 and 240 seconds used for CH4. Fluxes were adjusted for area, air temperature and gas volume. Further adjustment was made to the CO2 fluxes during daylight hours based upon the light response curve to account for attenuation of light by the chamber material, after. All data manipulation and analyses were carried out using SAS 9.4 (SAS Institute, CA 161 USA). GHG flux data (for both CO2 and CH4) were quality controlled in the first instance using the R2 statistic of the CO2 flux measurement, with values < 0.9 discarded. Measurements passing this threshold were then assessed using the output statistics from the regression calculation of CH4 fluxes, where regressions with a P value < 0.05 were accepted, while those that did not were treated as zero flux. Data outliers were defined as those ± 1.96 standard errors of the mean flux value for each collar and were excluded from the analyses. Data were further filtered to account for overestimation of fluxes during still atmospheric night-time conditions. Using the procedure fluxes where the mean CO2 concentration for the 20 second period before and after chamber closure dropped by more than 25 ppm where discounted. Net ecosystem exchange and methane fluxes were measured from a hemi-boreal ombrotrophic fen in Southern Sweden. An automated chamber system, SkyLine2D, was used to measure the fluxes near-continuously from August 2017 to September 2019. Four ecotypes were identified: sphagnum (Sphagnum spp), eriophorum, heather and water, to assess how these different ecotypes would respond to drought. The 2018 drought allowed comparison of fluxes between drought and non-drought years (May to September), and their recovery the following year.

Raw data and corresponding data analysis (Microsoft Office Excel, Origin) supporting Journal of American Chemical Society publication: "Photoreduction of CO2 with a formate dehydrogenase driven by photosystem II using a semi-artificial Z-scheme architecture". Data include: three-electrode and two-electrode electrochemistry and photoelectrochemistry, data analysis and product quantification.

Description: Leaf and invertebrate biomass in streams Project: This dataset was collected as part of the following SAFE research project: A preliminary study of the allochthonous inputs into tropical streams across a land use gradient in Sabah, Malaysia XML metadata: GEMINI compliant metadata for this dataset is available here Data worksheets: There are 2 data worksheets in this dataset: Insects (Worksheet Insects) Dimensions: 23 rows by 11 columns Description: Insect capture rates Fields: Location: SAFE project riparian site (Field type: Location) Stream: SAFE project stream (Field type: ID) Repeat: sample number for that stream (Field type: ID) Total Mass of Insects (g): the total dried mass of insects collected for each of the repeats (Field type: Numeric) Total Insects: the total number of insects collected in each repeat (Field type: Abundance) Hymenoptera: the total number of hymenoptera in each repeat (Field type: Abundance) Diptera: the total number of diptera in each repeat (Field type: Abundance) Coleoptera: the total number of coleoptera in each repeat (Field type: Abundance) Other.Insect: the grouped total of Hemiptera, Thysanoptera, Orthoptera, Blattodea, Trichoptera, Mantodea, Ephemeroptera, Dermaptera for each repeat (Field type: Abundance) Other: the grouped total of Arachnida, Entognatha, Diplopoda, Chilopoda for each repeat (Field type: Abundance) Hydrology (Worksheet Hydrology) Dimensions: 60 rows by 17 columns Description: River characteristics and litter quantities Fields: Location: SAFE project riparian site (Field type: Location) Stream Code: The stream from which the sample was taken (LFE, 15m, 30m, VJR or OP) (Field type: ID) Transect No.: The point of each sample within the 100m transect at each stream (Field type: ID) Channel Width: The bank full width of the channel at this point (Field type: Numeric) Wetted Width: The width of the runnin water at this point (Field type: Numeric) SAFE Habitat Quality Right: the SAFE Habitat quality on the right of the channel when looking upstream (Field type: Ordered Categorical) SAFE Habitat Quality Centre: the SAFE Habitat quality in the centre of the channel when looking upstream (Field type: Ordered Categorical) SAFE Habitat Quality Left: the SAFE Habitat quality on the left of the channel when looking upstream (Field type: Ordered Categorical) Flow Rate Right (s): the time taken for a tennis ball to travel 10m in the water on the right of the channel when looking upstream (Field type: Numeric) Flow Rate Centre (s): the time taken for a tennis ball to travel 10m in the water in the centre of the channel when looking upstream (Field type: Numeric) Flow Rate Left (s): the time taken for a tennis ball to travel 10m in the water on the left of the channel when looking upstream (Field type: Numeric) Average Flow Rate (s): an average of flow rate centre, flow rate left and flow rate right (Field type: Numeric) Leaf Litter Retention (g): the dried mass of leaf litter retained across the wetted width of the stream at each point (Field type: Numeric) Average Substrate Size: the average size of the substrate across the channel width of the stream at each point (Field type: Numeric) Leaf Litter Trap Position: the position where the leaf litter trap was placed relative to the stream when looking upstream (left, right or centre) (Field type: Categorical) Leaf Litter Mass: the dried mass of leaf litter collected in the leaf litter trap at each point (Field type: Numeric) Date range: 2017-02-06 to 2017-07-06 Latitudinal extent: 4.6314 to 4.7273 Longitudinal extent: 117.4556 to 117.6233 Taxonomic coverage: All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets. Animalia - Arthropoda - - Insecta - - - Coleoptera - - - Diptera - - - Hymenoptera - - [Other.Insect]

Comprehensive and reliable information on anthropogenic sources of greenhouse gas emissions is required to track progress towards keeping warming well below 2°C as agreed upon in the Paris Agreement. Here we provide a dataset on anthropogenic GHG emissions 1970-2019 with a broad country and sector coverage. We build the dataset from recent releases from the “Emissions Database for Global Atmospheric Research” (EDGAR) for CO2 emissions from fossil fuel combustion and industry (FFI), CH4 emissions, N2O emissions, and fluorinated gases and use a well-established fast-track method to extend this dataset from 2018 to 2019. We complement this with information on net CO2 emissions from land use, land-use change and forestry (LULUCF) from three available bookkeeping models.

Aim: Climate warming and biodiversity loss both alter plant productivity, yet we lack an understanding of how biodiversity regulates the responses of ecosystems to warming. In this study, we examine how plant diversity regulates the responses of grassland productivity to experimental warming using meta-analytic techniques. Location: Global Major taxa studied: Grassland ecosystems Methods: Our meta-analysis is based on warming responses of 40 different plant communities obtained from 20 independent studies on grasslands across five continents. Results: Our results show that plant diversity and its responses to warming were the most important factors regulating the warming effects on plant productivity, among all the factors considered (plant diversity, climate and experimental settings). Specifically, warming increased plant productivity when plant diversity (indicated by effective number of species) in grasslands was lesser than 10, whereas warming decreased plant productivity when plant diversity was greater than 10. Moreover, the structural equation modelling showed that the magnitude of warming enhanced plant productivity by increasing the performance of dominant plant species in grasslands of diversity lesser than 10. The negative effects of warming on productivity in grasslands with plant diversity greater than 10 were partly explained by diversity-induced decline in plant dominance. Main Conclusions: Our findings suggest that the positive or negative effect of warming on grassland productivity depends on how biodiverse a grassland is. This could mainly owe to differences in how warming may affect plant dominance and subsequent shifts in interspecific interactions in grasslands of different plant diversity levels.

Input data set for OPHELIA optimisation model investigating optimal heat decarbonization pathways through electrification for net zero economy in Great Britain. 

Anthropogenic structures (e.g. weirs and dams) fragment river networks and restrict the movement of migratory fish. Poor understanding of behavioural response to hydrodynamic cues at structures currently limits the development of effective barrier mitigation measures. This study aimed to assess the effect of flow constriction and associated flow patterns on eel behaviour during downstream migration. In a field experiment, we tracked the movements of 40 tagged adult European eels (Anguilla anguilla) through the forebay of a redundant hydropower intake under two manipulated hydrodynamic treatments. Interrogation of fish trajectories in relation to measured and modelled water velocities provided new insights into behaviour, fundamental for developing passage technologies for this endangered species. Eels rarely followed direct routes through the site. Initially, fish aligned with streamlines near the channel banks and approached the intake semi-passively. A switch to more energetically costly avoidance behaviours occurred on encountering constricted flow, prior to physical contact with structures. Under high water velocity gradients, fish then tended to escape rapidly back upstream, whereas exploratory ‘search’ behaviour was common when acceleration was low. This study highlights the importance of hydrodynamics in informing eel behaviour. This offers potential to develop behavioural guidance, improve fish passage solutions and enhance traditional physical screening. Fish_detections_UL_CHFish positions derived from acoustic telemetry contained within excel file with 5 columns. 'Record' denotes tag detection numbered consecutively in sequence; 'tag_number' denotes the fish identification number; ‘PosX’ denotes fish x coordinate in UTM; ‘PosY’ denotes fish y coordinate in UTM, ‘Treatment’ denotes experimental treatment

We discontinued this version of the dataset.