Heat index at 2 m above ground: A globally gridded dataset based on reanalysis data from 1979-2013, links to GeoTIFFs

The increase in global mean temperatures resulting from climate change has wide reaching consequences for the earth's ecosystems and other natural systems. Many studies have been devoted to evaluating the distribution and effects of these changes. We go a step further and evaluate global changes to the heat index, a measure of temperature as perceived by humans. Heat index, which is computed from temperature and relative humidity, is more important than temperature for the health of humans and other animals. Even in cases where the heat index does not reach dangerous levels from a health perspective, it has been shown to be an important factor in worker productivity and thus in economic productivity. We compute heat index from dewpoint temperature and absolute temperature 2 m above ground from the ERA-Interim reanalysis dataset for the years 1979-2013. The data is provided aggregated to daily minima, means and maxima. Furthermore, the data is temporally aggregated to monthly and yearly values and spatially aggregated to the level of countries after being weighted by population density in order to demonstrate its usefulness for the analysis of its impact on human health and productivity. The resulting data deliver insights into the spatiotemporal development of near-ground heat index during the course of the past 3 decades. It is shown that the impact of changing heat index is unevenly distributed through space and time, affecting some areas differently than others. The likelihood of dangerous heat index events has increased globally. Also, heat index climate groups that would formerly be expected closer to the tropics have spread latitudinally to include areas closer to the poles. The data can serve in future studies as a basis for evaluating and understanding the evolution of heat index in the course of climate change, as well as its impact on human health and productivity.

Multi-temporal mapping of seagrass cover, species and biomass of the Eastern Banks, Moreton Bay, Australia, with links to shapefiles

The spatial and temporal dynamics of seagrasses have been studied from the leaf to patch (100 m**2) scales. However, landscape scale (> 100 km**2) seagrass population dynamics are unresolved in seagrass ecology. Previous remote sensing approaches have lacked the temporal or spatial resolution, or ecologically appropriate mapping, to fully address this issue. This paper presents a robust, semi-automated object-based image analysis approach for mapping dominant seagrass species, percentage cover and above ground biomass using a time series of field data and coincident high spatial resolution satellite imagery. The study area was a 142 km**2 shallow, clear water seagrass habitat (the Eastern Banks, Moreton Bay, Australia). Nine data sets acquired between 2004 and 2013 were used to create seagrass species and percentage cover maps through the integration of seagrass photo transect field data, and atmospherically and geometrically corrected high spatial resolution satellite image data (WorldView-2, IKONOS and Quickbird-2) using an object based image analysis approach. Biomass maps were derived using empirical models trained with in-situ above ground biomass data per seagrass species. Maps and summary plots identified inter- and intra-annual variation of seagrass species composition, percentage cover level and above ground biomass. The methods provide a rigorous approach for field and image data collection and pre-processing, a semi-automated approach to extract seagrass species and cover maps and assess accuracy, and the subsequent empirical modelling of seagrass biomass. The resultant maps provide a fundamental data set for understanding landscape scale seagrass dynamics in a shallow water environment. Our findings provide proof of concept for the use of time-series analysis of remotely sensed seagrass products for use in seagrass ecology and management.

Seagrass and associated benthic community data derived from field surveys at Low Isles, Great Barrier Reef, conducted July-August, 1997

The distribution of seagrass and associated benthic communities on the reef and lagoon of Low Isles, Great Barrier Reef, was mapped between the 29 July and 29 August 1997. For this survey, observers walked or free-dived at survey points positioned approximately 50 m apart along a series of transects. Visual estimates of above-ground seagrass biomass and % cover of each benthos and substrate type were recorded at each survey point. A differential handheld global positioning system (GPS) was used to locate each survey point (accuracy ±3m). A total of 349 benthic survey points were examined. To assist with mapping meadow/habitat type boundaries, an additional 177 field points were assessed and a georeferenced 1:12,000 aerial photograph (26th August 1997) was used as a secondary source of information. Bathymetric data (elevation below Mean Sea Level) measured at each point assessed and from Ellison (1997) supplemented information used to determine boundaries, particularly in the subtidal lagoon. 127.8 ±29.6 hectares was mapped. Seagrass and associated benthic community data was derived by haphazardly placing 3 quadrats (0.25m**2) at each survey point. Seagrass above ground biomass (standing crop, grams dry weight (g DW m**-2)) was determined within each quadrat using a non-destructive visual estimates of biomass technique and the seagrass species present identified. In addition, the cover of all benthos was measured within each of the 3 quadrats using a systematic 5 point method. For each quadrat, frequency of occurrence for each benthic category was converted to a percentage of the total number of points (5 per quadrat). Data are presented as the average of the 3 quadrats at each point. Polygons of discrete seagrass meadow/habitat type boundaries were created using the on-screen digitising functions of ArcGIS (ESRI Inc.), differentiated on the basis of colour, texture, and the geomorphic and geographical context. The resulting seagrass and benthic cover data of each survey point and for each seagrass meadow/habitat type was linked to GPS coordinates, saved as an ArcMap point and polygon shapefile, respectively, and projected to Universal Transverse Mercator WGS84 Zone 55 South.

(Table 1) Carbon pools in different vegetation components in grazed and ungrazed plots near Ny-Ålesund, Spitzbergen

The carbon (C) sink strength of arctic tundra is under pressure from increasing populations of arctic breeding geese. In this study we examined how CO2 and CH4 fluxes, plant biomass and soil C responded to the removal of vertebrate herbivores in a high arctic wet moss meadow that has been intensively used by barnacle geese (Branta leucopsis) for ca. 20 years. We used 4 and 9 years old grazing exclosures to investigate the potential for recovery of ecosystem function during the growing season (July 2007). The results show greater above- and below-ground vascular plant biomass within the grazing exclosures with graminoid biomass being most responsive to the removal of herbivory whilst moss biomass remained unchanged. The changes in biomass switched the system from net emission to net uptake of CO2 (0.47 and -0.77 µmol/m**2/s in grazed and exclosure plots, respectively) during the growing season and doubled the C storage in live biomass. In contrast, the treatment had no impact on the CH4 fluxes, the total litter C pool or the soil C concentration. The rapid recovery of the above ground biomass and CO2 fluxes demonstrates the plasticity of this high arctic ecosystem in terms of response to changing herbivore pressure.

Seagrass ecosystem response to long-term high CO2 in a Mediterranean volcanic vent

We examined the long-term effect of naturally acidified water on a Cymodocea nodosa meadow growing at a shallow volcanic CO2 vent in Vulcano Island (Italy). Seagrass and adjacent unvegetated habitats growing at a low pH station (pH = 7.65 ± 0.02) were compared with corresponding habitats at a control station (pH = 8.01 ± 0.01). Density and biomass showed a clear decreasing trend at the low pH station and the below- to above-ground biomass ratio was more than 10 times lower compared to the control. C content and delta 13C of leaves and epiphytes were significantly lower at the low pH station. Photosynthetic activity of C. nodosa was stimulated by low pH as seen by the significant increase in Chla content of leaves, maximum electron transport rate and compensation irradiance. Seagrass community metabolism was intense at the low pH station, with significantly higher net community production, respiration and gross primary production than the control community, whereas metabolism of the unvegetated community did not differ between stations. Productivity was promoted by the low pH, but this was not translated into biomass, probably due to nutrient limitation, grazing or poor environmental conditions. The results indicate that seagrass response in naturally acidified conditions is dependable upon species and geochemical characteristics of the site and highlight the need for a better understanding of complex interactions in these environments.

Aboveground community and species-specific plant biomass from the Jena Experiment (Main Experiment, year 2004)

This data set contains aboveground community biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2004 just prior to mowing (during peak standing biomass in late May and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in four rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for the biomass measures on the community level are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.

Aboveground community and species-specific plant biomass from the Jena Experiment (Main Experiment, year 2007)

This data set contains aboveground community biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2007 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in four (May) or three (August) rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for the biomass measures on the community level are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.

Aboveground community and species-specific plant biomass from the Jena Experiment (Main Experiment, year 2006)

This data set contains aboveground community biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2006 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in four rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for the biomass measures on the community level are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.