Keyword

biomass

38 record(s)
 
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  • This dataset contains measures of fitness traits from Eschscholzia californica progeny which were experimentally supplemented with selfed or outcrossed pollen to determine the effects of self-fertilisation on a plant which has a low propensity to self. A glasshouse experiment was conducted using 40 plants. On each plant two flowers were emasculated and the first supplemented with outcrossed pollen and the second with self-pollen. From each supplemented plant, a seed was sowed from the outcrossed fruit and from the selfed fruit. The following fitness traits were recorded; the germination rate, the duration from germination to reproductive maturity (time of first flower), together with the height (cm) and biomass (number of flowers and buds) at reproductive maturity. The dataset was part of a larger experiment looking at the effect of floral resources on the pollination services to isolated plants. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/551756fd-77ea-479f-8bc9-f0437c6aead6

  • QUEST Fish was led by Dr Manuel Barange (PML) with 18 co-investigators from POL, PML, CEFAS, University of Plymouth, University of Portsmouth, CSIC (Spain), UEA, WorldFish Centre, IPSL, ICES (Denmark), Met Office, IRD (Paris) and University of North Carolina, as part of QUEST (Quantifying and Understanding the Earth System). QUEST-Fish specifically focused on the added impacts that climate change is likely to cause on global fish production, and on the subsequent additional risks and vulnerabilities to human societies. This dataset contains global fish biomass estimates from the Global Coastal-Ocean Modelling System.

  • The data consist of woody biomass maps of three study areas - Mabalane, Gurue, and Maruppa in Mozambique. Each area map comprises three Geotiff layers stacked in the order band 1= 2007, band 2 = 2010, band 3 = 2014. Each pixel is an aboveground woody biomass in tonnes of carbon per hectare (ha). For the biomass maps -18.00000 means no data. Due to noise, it is possible to have negative biomass estimates. Individual layers can extracted for year specific analyses. Data were collected as part of the Abrupt Changes in Ecosystem Services and Wellbeing in Mozambican Woodlands (ACES) project under the ESPA programme Full details about this dataset can be found at https://doi.org/10.5285/6a8b07f9-552e-408c-8351-595ee6a7fc5f

  • This data set consist of a single file which contains a set of optimised global surface fluxes of methane (CH4), produced through variational inverse methods using the TOMCAT chemical transport model, and the INVICAT inverse transport model. These surface fluxes are produced as monthly mean values on the (approximately) 5.6-degree horizontal model grid. The associated uncertainty for the flux from each grid cell is also included. The fluxes and uncertainties are global and cover the period Jan 2010 - Dec 2018. The emissions from fossil fuels are labelled FF_FLUX, whilst the uncertainties are labelled FF_ERROR. The emissions from natural, agricultural and biomass burning sources are labelled NAT_FLUX, whilst the uncertainties are labelled NAT_ERROR. These two sectors (fossil fuel and non-fossil fuel) are solved for separately in the inversion. Flux and uncertainty units are kg(CH4)/m2/s, and time units are days since January 1st 2010. These emissions show improved performance relative to independent observations when included in the TOMCAT model. Further details about the data can be found in Wilson et al. (2020) in the documentation section.

  • The dataset consists of observations of aboveground biomass, canopy area, maximum height, stem diameter and sapwood area of Juniperus monosperma (Oneseed Juniper) trees, measured at a site in central New Mexico in 2018 and 2019. In total, 200 stems for sapwood area were measured, and 18 trees for full biomass determinations. Full details about this dataset can be found at https://doi.org/10.5285/871443a9-6634-4eba-abb5-286a1ab58e9b

  • Data includes raw shoot biomass and yield, production and gas exchange, nodulation and N-fixation and forage quality data, including relative and consumable food values. The impacts of ozone on the growth and functioning of high-sugar ryegrass pasture mesocosms was assessed in year 2013. Pasture mesocosms, containing perennial ryegrass (Lolium perenne L) and white clover (Trifolium repens L), were grown in the early spring and exposed to ozone in solardomes from late April 2013 to the end of September 2013. Ozone (30, 35, 40, 45, 52, 67 parts per billion (ppb) treatment means) had a large effect on the pasture mesocosms. The work was carried out as part of a NERC funded PhD. Project number NEC04456. Full details about this dataset can be found at https://doi.org/10.5285/e0bcdc39-ab79-413c-bf76-d6ffbc510f15

  • The data consists of, standing aboveground biomass, and belowground biomass measurements, from sites in the Conwy catchment. Standing aboveground biomass was measured at 7 sites and belowground biomass measurements were made at 8 sites. Data were collected in 2013 and 2014. The sites were chosen to represent habitat types and the terrestrial productivity gradient in Britain from intensive agriculturally managed lowland grasslands through to montane heath. Standing aboveground biomass (grams of dry mass per metre square) in habitats dominated by herbaceous biomass was measured on 1x1 metre quadrats in four plots per site. Standing aboveground biomass in woodlands was measured in two 200 square metre areas by means of stem cores and litter collections. Belowground total root biomass (grams of dry mass per square metre) was assessed for the topsoil 0-15 centimetres in three plots per site. Measurements were undertaken by trained members of staff from Bangor University and the Centre for Ecology & Hydrology. This data was collected for the NERC project 'The Multi-Scale Response of Water quality, Biodiversity and Carbon Sequestration to Coupled Macronutrient Cycling from Source to Sea' (NE/J011991/1). The project is also referred to as Turf2Surf. Full details about this dataset can be found at https://doi.org/10.5285/46bb0117-ed5d-4167-a375-d84d1237cf21

  • Estimates of plant abundance (for leaf area, floral units and seed abundance, mass and energy) obtained from field-based sampling as part of a study of ecological interactions (food webs and plant-pollinator networks) on a single farm (Norwood Farm, Somerset, UK: 51.3128N 2.3206W) during 2007 and 2008. During the study, Norwood Farm was managed as an organic farm at relatively low intensity. The work was was supported by the Biotechnology and Biological Sciences Research Council [grant number BBD0156341]. Full details about this dataset can be found at https://doi.org/10.5285/0c123d4e-186f-48f5-8580-d0696b247287

  • The data represent a quantitative measure of aboveground (vegetation) biomass, organic carbon content and aboveground (vegetation) carbon from 144 vegetation samples collected across ten UK saltmarshes between 2019 and 2020. Sites were chosen to represent contrasting habitat types in the United Kingdom, in particular sediment types, vegetation, and sea level history. Full details about this dataset can be found at https://doi.org/10.5285/f71c9f3e-0ae1-4318-a3ea-1dd30b7af3be

  • The dataset comprises of above ground vegetation cut to ground level and dried to give indication of standing crop biomass in a 50 centimetre (cm) x 25cm area (taken within a 1metre (m) x 1m quadrat) . Sampling was conducted at six salt marsh sites at four spatial scales: 1 m (the minimal sampling unit) nested within a hierarchy of increasing scales of 1-10 m, 10-100 m and 100-1000 m. Three of the sites were in Morecambe Bay, North West England and three of the sites were in Essex, South East England. All samples were taken during the winter and summer of 2013. This data was collected as part of Coastal Biodiversity and Ecosystem Service Sustainability (CBESS): NE/J015644/1. The project was funded with support from the Biodiversity and Ecosystem Service Sustainability (BESS) programme. BESS is a six-year programme (2011-2017) funded by the UK Natural Environment Research Council (NERC) and the Biotechnology and Biological Sciences Research Council (BBSRC) as part of the UK's Living with Environmental Change (LWEC) programme. Full details about this dataset can be found at https://doi.org/10.5285/87114da4-3189-471f-9832-00b3e759232f