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

This dataset contains chemical and physical composition of soil for four elevations on Mount Etna. Soil samples were collected in 2017 and 2019 and then analysed for chemical and physical composition by a commercial laboratory in Catania, Sicily. The measurements were conducted as part of a study in to transplanting of two Senecio species on Mount Etna. Full details about this dataset can be found at https://doi.org/10.5285/3970a138-c035-40ac-bf1d-a2f8a464644a

This dataset contains climate data for Mount Etna in 2017. The measurements were conducted as part of a study in to transplanting of two Senecio species on Mount Etna. Dataloggers were deployed at each of the four transplant elevations (500 m, 1000 m, 1500 m, 2000 m) to record temperature. Daily maximum and minimum were extracted to understand how temperature varied across elevation and seasons. Full details about this dataset can be found at https://doi.org/10.5285/35a9dcfa-cf47-44cf-ad1e-8b4b59238768

This dataset for the UK, Jersey and Guernsey contains the Corine Land Cover (CLC) revised for 2006. This shapefile has been created from combining the 2006 land cover layers from the individual CLC database files for the UK, Jersey and Guernsey. CLC is a dataset produced within the frame of the Initial Operations of the Copernicus programme (the European Earth monitoring programme previously known as GMES) on land monitoring. CLC provides consistent information on land cover and land cover changes across Europe. This inventory was initiated in 1985 (initial year 1990) and then established a time series of land cover information with updates in 2000 and 2006 the last one being the 2012 reference year. CLC products are based on the analysis of satellite images by national teams of participating countries - the EEA member and cooperating countries - following a standard methodology and nomenclature with the following base parameters: * 44 classes in the hierarchical three level Corine nomenclature; * Minimum mapping unit (MMU) for status layers is 25 hectares; * Minimum width of linear elements is 100 metres; The resulting national land cover inventories are further integrated into a seamless land cover map of Europe. Land cover and land use (LCLU) information is important not only for land change research, but also more broadly for the monitoring of environmental change, policy support, the creation of environmental indicators and reporting. CLC datasets provide important datasets supporting the implementation of key priority areas of the Environment Action Programmes of the European Union as protecting ecosystems, halting the loss of biological diversity, tracking the impacts of climate change, assessing developments in agriculture and implementing the EU Water Framework Directive, among others. Full details about this dataset can be found at https://doi.org/10.5285/2d0cf17f-aabd-4be6-859b-55c3403bbd9a

This dataset for the UK, Jersey and Guernsey contains the Corine Land Cover (CLC) for 2012 (CLC2012). This dataset has been created from combining the 2012 land cover layers from the individual CLC files for the UK, Jersey and Guernsey. CLC is a dataset produced within the frame of the Initial Operations of the Copernicus programme (the European Earth monitoring programme previously known as GMES) on land monitoring. CLC provides consistent information on land cover and land cover changes across Europe. This inventory was initiated in 1985 (initial year 1990) and then established a time series of land cover information with updates in 2000 and 2006 the last one being the 2012 reference year. CLC products are based on the analysis of satellite images by national teams of participating countries - the EEA member and cooperating countries - following a standard methodology and nomenclature with the following base parameters: - 44 classes in the hierarchical three level Corine nomenclature; - Minimum mapping unit (MMU) for status layers is 25 hectares; - Minimum width of linear elements is 100 metres; The resulting national land cover inventories are further integrated into a seamless land cover map of Europe. Land cover and land use (LCLU) information is important not only for land change research, but also more broadly for the monitoring of environmental change, policy support, the creation of environmental indicators and reporting. CLC datasets provide important datasets supporting the implementation of key priority areas of the Environment Action Programmes of the European Union as protecting ecosystems, halting the loss of biological diversity, tracking the impacts of climate change, assessing developments in agriculture and implementing the EU Water Framework Directive, among others. Full details about this dataset can be found at https://doi.org/10.5285/32533dd6-7c1b-43e1-b892-e80d61a5ea1d

This dataset contains survival, growth and leaf morphology data for multiple clones of c. 40 genotypes of two species of Senecio. The two Senecio species are native to low (S. chrysanthemifolius) and high elevations (S. aethnensis) on Mount Etna. Genotypes were propagated in a glasshouse and multiple clones of each genotype were then transplanted at four elevations (500m, 1000m, 1500m, 2000m) on Mount Etna in June-July 2017 before measurements were taken. Full details about this dataset can be found at https://doi.org/10.5285/11bad517-507b-4b8f-9944-2c2e16e4e8c6

Data comprise measurements of spectral reflectance for quaking aspen (Populus tremuloides Michx.) trees at a range of sites in southwestern Colorado near the town of Crested Butte. Spectra were measured in three different ways: hyperspectral measurements of leaves, hyperspectral measurements of bark, and multispectral measurements of canopies. The first two measurements were made using a handheld spectrometer, while the latter were made via airborne imaging from an unmanned aerial system. In addition to these reflectance data, the dataset also includes information on the genotype and/or ploidy level of each sample, as determined by either DNA microsatellite analysis or flow cytometry. All samples are georeferenced. The data include extracted data and raw imagery. Full details about this dataset can be found at https://doi.org/10.5285/d663aeb9-1e3e-40f7-ab9e-494e7646faeb

The dataset contains chlorophyll fluorescence data from different genotypes of two Senecio species on Mount Etna, Sicily. In 2017, multiple clones of c.40 genotypes for each of two Senecio species were transplanted at four elevations (500m, 1000m, 1500m, 2000m) on Mount Etna. For each species, five genotypes were chosen randomly and chlorophyll fluorescence was measured on four clones of each chosen genotype at each transplant elevation using an IMAGING-PAM fluorometer Full details about this dataset can be found at https://doi.org/10.5285/28880a9d-3d6b-4e8e-a1d3-8ed939222bdc

The topographic index is a hydrological quantity describing the propensity of the soil at landscape points to become saturated with water as a result of topographic position (i.e. not accounting for other factors such as climate that also affect soil moisture but are accounted for separately). Modern land surface models require a characterisation of the land surface hydrological regime and this parameter allows the use of the TOPMODEL hydrological model to achieve this .This Geographic Information System layer is intended for use as topographic ancillary files for the TOPMODEL routing model option within the Joint UK Land Environment Simulator (JULES) land surface model. The topographic index variable here is directly comparable to the compound topographic index available from United States Geological Survey's Hydro1K at 30 sec resolution. PLEASE NOTE: This dataset is a correction to a previous version which was found to contain errors (doi:10/t7d). In the previous version all pixels north of 4.57 degrees south were shifted consistently 9.3 km to the west. This version is correctly aligned at all points. Full details about this dataset can be found at https://doi.org/10.5285/6b0c4358-2bf3-4924-aa8f-793d468b92be

The leaf phenology product presented here shows the amplitude of annual cycles observed in MODIS (Moderate Resolution Imaging Spectroradiometer) normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) 16-day time-series of 2000 to 2013 for Meso- and South America. The values given represent a conservative measure of the amplitude after the annual cycle was identified and tested for significance by means of the Lomb-Scargle Transform. The amplitude was derived for four sets of vegtation indices (VI) time-series based on the MODIS VI products (500m MOD13A1; 1000m MOD13A2). The amplitude value can be interpreted as the degree in which the life cycles of individual leaves of plants observed within a pixel are synchronised. In other words, given the local variation in environment and climate and the diversity of species leaf life cycle strategies, an image pixel will represent vegetation communities behaving between two extremes: * well synchronized, where the leaf bud burst and senescence of the individual plants within the pixel occurs near simultaneously, yielding a high amplitude value. Often this matches with an area of low species diversity (e.g. arable land) or with areas where the growth of all plants is controlled by the same driver (e.g. precipitation). * poorly synchronized, where the leaf bud burst and senescence of individual plants within a pixel occurs at different times of the year, yielding a low amplitude value. Often this matches with an area of high species diversity and/or where several drivers could be controlling growth. Full details about this dataset can be found at https://doi.org/10.5285/dae416b4-3762-45bd-ae14-c554883d482c