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Brazil is home to the largest tracts of tropical vegetation in the world, harbouring high levels of biodiversity and carbon. Several biomass maps have been produced for Brazil, using different approaches and methods, and for different purposes. These maps have been used to estimate historic, recent, and future carbon emissions from land use change (LUC). It can be difficult to determine which map to use for what purpose. The implications of using an unsuitable map can be significant, since the maps have large differences—both in terms of total carbon storage and its spatial distribution. This dataset of aboveground carbon was created based on data from existing maps and an up-to-date LULC map. The map reflects current LULC, has high accuracy and resolution (50 m), and a national coverage. It can be a useful alternative for scientific studies and policy initiatives concerned with existing LULC and LUC outside of existing forests, especially at local scales when high resolution is necessary, and/or outside the Amazon biome. Map unit: tonnes of aboveground carbon per hectare. This dataset of aboveground carbon was created based on data from existing maps and an up-to-date LULC map. The map reflects current LULC, has high accuracy and resolution (50 m), and a national coverage. It can be a useful alternative for scientific studies and policy initiatives concerned with existing LULC and LUC outside of existing forests, especially at local scales when high resolution is necessary, and/or outside the Amazon biome. Map unit: tonnes of aboveground carbon per hectare. Data är baserade på befintliga kartor och en aktuell LULC-karta (änding av markanvändning) för bildandet av ovanjordiskt kol i Brasilien. Kartan speglar nuvarande LULC, har hög noggrannhet och upplösning (50 m) och en nationell täckning. Mer information på den engelska katalogsidan: https://snd.gu.se/en/catalogue/study/ecds0244 This dataset of aboveground carbon was created based on data from existing maps and an up-to-date LULC map. The map reflects current LULC, has high accuracy and resolution (50 m), and a national coverage. It can be a useful alternative for scientific studies and policy initiatives concerned with existing LULC and LUC outside of existing forests, especially at local scales when high resolution is necessary, and/or outside the Amazon biome. Map unit: tonnes of aboveground carbon per hectare.

Patterns of movement of marine species can reflect strategies of reproduction and dispersal, species’ interactions, trophodynamics, and susceptibility to change, and thus critically inform how we manage populations and ecosystems. On coral reefs, the density and diversity of metazoan taxa is greatest in dead coral and rubble, which is suggested to fuel food webs from the bottom-up. Yet, biomass and secondary productivity in rubble is predominantly available in some of the smallest individuals, limiting how accessible this energy is to higher trophic levels. We address the bioavailability of motile coral reef cryptofauna based on small-scale patterns of emigration in rubble. We deployed modified RUbble Biodiversity Samplers (RUBS) and emergence traps in a shallow rubble patch at Heron Island, Great Barrier Reef, to detect community-level differences in the directional influx of motile cryptofauna under five habitat accessibility regimes. The mean density (0.13–4.5 ind.cm-3) and biomass (0.14–5.2 mg.cm-3) of cryptofauna were high and varied depending on microhabitat accessibility. Emergent zooplankton represented a distinct community (dominated by the Appendicularia and Calanoida) with the lowest density and biomass, indicating constraints on nocturnal resource availability. Mean cryptofauna density and biomass were greatest when interstitial access within rubble was blocked, driven by the rapid proliferation of small harpacticoid copepods from the rubble surface, leading to trophic simplification. Individuals with high biomass (e.g., decapods, gobies, and echinoderms) were greatest when interstitial access within rubble was unrestricted. Treatments with a closed rubble surface did not differ from those completely open, suggesting that top-down predation does not diminish rubble-derived resources. Our results show that conspecific cues and species’ interactions (e.g., competition and predation) within rubble are most critical in shaping ecological outcomes within the cryptobiome. These findings have implications for prey accessibility through trophic and community size structuring in rubble, which may become increasingly relevant as benthic reef complexity shifts in the Anthropocene. We address the bioavailability of coral reef cryptofauna in rubble based on small-scale patterns of emigration. We adapted the accessibility of Rubble Biodiversity Samplers (RUBS), models used to standardise biodiversity sampling in rubble (Wolfe and Mumby 2020), to explore the local movement patterns of rubble-dwelling fauna, with inference to predation processes within and beyond the cryptobenthos. Five treatments were developed to detect community-level differences in the directional influx of motile cryptofauna under various habitat accessibility regimes. Four of these treatments were developed by modifying accessibility into RUBS (https://www.thingiverse.com/thing:4176644/files) to understand limitations on the directional influx and movement of cryptofauna within coral rubble patches using four treatments; (1) open (completely accessible), (2) interstitial access (top closed), (3) surficial access (sides and bottom closed), and (4) raised (above rubble substratum). The fifth treatment involved a series of emergence plankton traps, designed to target demersal cryptofauna that vertically migrate from within the rubble benthos at night, given emergent zooplankton biomass and diversity are greatest at night. Fieldwork was conducted over several weeks (11th September to 5th October 2021) in a shallow (~3–5 m depth) reef slope site on the southern margin of Heron Island (-23˚26.845’ S, 151˚54.732’ E), Great Barrier Reef, Australia (Fig. 1). All collections were conducted under the Great Barrier Reef Marine Park Authority permit G20/44613.1.

Dataset for the article: How can the forest sector maintain its mitigation potential in a changing climate ? Case studies of boreal and northern temperate forests in eastern Canada.

We studied if functional traits related to resource preemption (light and inorganic nutrients) exert control on space preemption of tropical seagrass meadows. Additionally, we studied if space preemption changed under different eutrophication scenarios. We took seagrass abundance data to study space preemption, seagrass traits data to study their effect on space preemption and eutrophication indicators to evaluate the level of eutrophication at each site/sampling event. The data was collected in Unguja Island (Zanzibar Archipealgo, Tanzania) in seven sites/sampling events (Harbor, Chapwani, Changuu, Bweleo, Fumba, Mangroves and Marumbi). Each site/sampling event comprised a subtidal seagrass meadow (2-4 meters depth) of around 2500 square meters, delimited by the coastline and a fringing reef. The data was taken between the 26.09.2016 to the 05.10.2016. In each site/sampling event, five 50 meters transects were deployed perpendicular to the coast and paralel to each other, approximately separated by 50 meters. The areas enclosed beweeen the transects were names A, B, C and D. Macroalgae biomass was collected as an indicator of eutrophication. Macroalgae biomass was quantified along five 50-m transects per site/sampling event, set perpendicular to the coast and parallel to each other, separated by ~50 meters. We collected the macroalgae present in three random 0.25x0.25 meters quadrats per transect. The macroalgae samples were cleaned of sediments and rinsed with water. They were then dried at 50°C in a forced air oven until constant dry weight. The macroalgae biomass was calculated as the grams of dry weight divided by the area of the quadrat (grams of dry weight per square meter).

Seeds of 52 species of herbaceous plants typical from European grassland ecosystems were obtained from a commercial supplier (Planta naturalis). When species germinated in Petri dishes the seedlings were then transplanted to plastic pots (11 x 11 x 12 cm height, 1L volume). Pots were filled with a mixture of a potting substrate (Biolan Murumuld) and sand. Pots were randomly placed in the greenhouse of the University of Tartu, Estonia. Then, we established monocultures with seven individuals of a single species per pot which were grown under well-watered conditions. One month after transplanting the seedlings to the pots, a drought treatment was applied to half of the pots (five pots per species). The experiment was harvested in late July 2020, when the first individuals started flowering, after month-long drought treatment. Plant traits related to drought responses and resource use strategies were selected and measured for each species following established protocols. These included seven above- and belowground traits: Vegetative plant height (H, cm), Leaf Area (LA, mm2), Specific Leaf Area (SLA, mm2 mg-1), Leaf Dry Matter Content (LDMC, mg g-1), Specific Root Length (SRL, cm g-1), Average root Diameter (AvgD, mm), Root Dry Matter Content (RDMC, mg g-1). Before harvesting, we measured the plant height and collected one leaf per individual for three individuals per pot. Afterward, we collected the aboveground biomass and belowground biomass of all the individuals in each pot. Due to the difficulty in untangling the roots of the different individuals in a pot, root traits were estimated at the pot level. Roots were washed and a sample of finest roots (10-50mg) was collected. Leaves and fine roots were scanned at 300dpi and 600dpi, respectively, using an Epson perfection 3200 Photo scanner for leaves and Epson V700 Photo scanner for fine roots. After scanning, leaves and roots were oven-dried at 60°C for 72h. AvgD and root length were determined using WinRHIZO Pro 2015 (Regent Instruments Inc., Canada), and leaf area with ImageJ software. We averaged all traits values at the species level, attaining a single value for each trait in each treatment. The total aboveground biomass and total belowground biomass of each pot were oven-dried at 60°C for 72h and weighed. Drought is expected to increase in future climate scenarios. Although responses to drought of individual functional traits are relatively well-known, simultaneous changes across multiple traits in response to water scarcity remain poorly understood despite its importance to understand alternative strategies to resist drought. We grew 52 herbaceous species in monocultures under drought and control treatments and characterized the functional space using seven measured above- and belowground traits: plant height, leaf area, specific leaf area, leaf dry matter content, specific root length, average root diameter, and root dry matter content. Then, we estimated how each species occupied this space and the amount of functional space occupied in both treatments using trait probability density functions. We also estimated intraspecific trait variability (ITV) for each species as the dissimilarity in trait values between the individuals of each treatment. We then mapped drought resistance and ITV in the functional space using generalized additive models. The response of species to drought strongly depended on their traits, with species that invested more in root tissues and conserved small size being both more resistant to drought and having higher ITV. We also observed a significant trend of trait displacement towards less conservative strategies. However, these changes depended strongly on the trait values of species in the control treatment, with species with different traits having opposing responses to drought. These contrasting responses resulted in lower trait variability in the species pool in drought compared to control conditions. Our results suggest strong trait filtering acting on conservative species as well as the existence of an optimal part in the functional space to which species converge under drought. Our results show that changes in species trait-space occupancy are key to understand plant strategies to withstand drought, highlighting the importance of individual variation in response to environmental changes, and suggest that community-wide functional diversity and biomass productivity could decrease in a drier future. Knowing these shifts will help to anticipate changes in ecosystem functioning facing climate change. The complete dataset is in the file.

Wood specific gravity (WSG) is an important component in biomass estimation through non-destructive allometric approach. However, a number of factors like climatic condition, soil, disturbance, management practice, geographic location etc. have huge impact on WSG variation. The present data set provides a collective WSG data for different species (333) consisting of 711 individuals procured from already published research paper for 11 forest groups of India occurring in different climatic and edaphic conditions. It also includes WSG data of a number of juvenile tree species for tropical dry deciduous forest. A number of studies in India have not considered WSG value in biomass estimation of juvenile trees. However, previous reports of Chaturvedi et al. (2012) suggested that the use of WSG in biomass estimation provide better result than using only the diameter and height as variables. It also includes samples/ species column for getting information about the number of samples considered for WSG determination. Especially this data set will be helpful to get WSG data on the basis of similar climatic condition, forest group according to the need of the future studies and this may minimize the source of WSG variation which would ultimately minimize variation in biomass and carbon estimation. It will also help to provide WSG data for allometric model development. Also it will be help to study the physical property (strength) of wood. Further, use of this database will save the time of workers as it is easily assessable and it provides WSG value of a number of species at one place.

This dataset contains two metrics for climate change exposure using downscaled climate projections with the SRES A2 emissions scenario (Tabor and Williams, 2007).The metrics represent dissimilarity measurements of the squared Euclidean distance between seasonal (June–August and December–February) temperature and precipitation variables in the 20th century climate and mid-21st century climate. (1) disappearing climate risk - measure of dissimilarity between a pixel’s late 20th century climate and its closest matching pixel in the global set of 21st-century climates (2) novel climate risk - measure of dissimilarity between a pixel’s future climate and its closest matching pixel in the global set of late 20th-century climates. The data are in arcASCII format. All data are in units of standard Euclidean distance and multiplied by 1000. This is the original data. To scale the data similar to Tabor et al. (2018), remove outliers above the 99th percentile distribution before rescaling from 0-1. Unprojected number of columns 2160 number of rows 857 Lower Left X Center -179.917 Lower Left Y Center -59.084 Cell size 0.166667 decimal degrees (10 minutes or ~17 km) {"references": ["Tabor, K. et al. (2018). Tropical Protected Areas Under Increasing Threats from Climate Change and Deforestation: https://doi.org/10.3390/land7030090", "Tabor and Williams (2010). Globally downscaled climate projections for assessing the conservation impacts of climate change. https://doi.org/10.1890/09-0173.1", "Williams, J.W. et al. (2007). Projected distributions of novel and disappearing climates by 20100 AD. https://doi.org/10.1073/pnas.0606292104"]} Support for this project was provided by Conservation International, the Land Tenure Center at the University of Wisconsin, the Center for Climatic Research at the University of Wisconsin, and the Environment Program at the University of Wisconsin–Madison. This research has been funded in part by the Walton Family Foundation, the Gordon and Betty Moore Foundation, and a gift from Betty and Gordon Moore.

Forest aboveground carbon density (ACD) for the main eight Hawaiian Islands in 2015-2016. The data are in 30 meter resolution format with the units of Mg C per hectare. The file is a standard GeoTIFF. Use of these data requires citation of this dataset plus citation of the source study as follows: Asner, G.P., S. Sousan, D.E. Knapp, P.C. Selmants, R.E. Martin, R.F. Hughes, and C.P. Giardina. 2016. Rapid forest carbon assessments of oceanic islands: a case study of the Hawaiian archipelago. Carbon Balance and Management 11, doi:10.1186/s13021-015-0043-4

This repository contains the data used to generate the results for the paper: Yuri Shendryk, Jeremy Sofonia, Robert Garrard, Yannik Rist, Danielle Skocaj, and Peter Thorburn (2020). Fine-scale Prediction of Leaf Nitrogen Content and Yield in Sugarcane using UAV LiDAR and Multispectral Imaging. The data to reproduce results could be also found here: https://github.com/RobGarrard/Fine-scale-prediction-of-leaf-nitrogen-content-and-yield-in-sugarcane. For any queries regarding these codes please contact robert.garrard@csiro.au or yuri.shendryk@csiro.au.

This data product contains the quality-controlled, native sampling resolution data from NEON's Litterfall and fine woody debris sampling. Litter is defined as material that is dropped from the forest canopy and has a butt end diameter 50 cm; this material is collected in ground traps as longer material is not reliably collected by the elevated traps. Following field collection, each sample is sorted by functional group, dried and weighed. After sorting litter by functional group, needles and leaves from elevated traps from select bouts are sent for chemical analysis, with excess material archived in the NEON Biorepository and available upon request. For additional details, see the user guides, protocols, and science design listed in the Documentation section below. Products resulting from this sampling include mass of litterfall and fine woody debris by functional group as well as litter chemistry and stable isotope ratios. Summary tables of external lab precision and accuracy are included in the expanded package. Latency: The expected time from data and/or sample collection in the field to data publication is as follows, for each of the data tables (in days) in the downloaded data package. See the Data Product User Guides for more information. bgc\_CNiso\_externalSummary: 30 lig_externalSummary: 30 ltr_chemistrySubsampling: 60 ltr_fielddata: 60 ltr_litterCarbonNitrogen: 270 ltr_litterLignin: 180 ltr_massdata: 60 ltr_pertrap: 30 Each qualifying tower plot in forested ecosystems has 0-2 elevated traps and 1-2 ground traps deployed. Ground traps are sampled annually. Sampling interval of elevated litter traps is variable by dominant overstory vegetation. Deciduous forests are sampled once in the spring then multiple times during fall senescence; evergreen and coniferous forests are sampled year round at monthly intervals. Traps are consistent with those used by the Smithsonian Center for Tropical Forest Science (CTFS). Mass data for each collection event are measured separately for functional groups: Leaves, Needles, Twigs/branches, Woody material, Seeds, Flowers and other non-woody reproductive structures, Other, and Mixed (unsorted). Once every five years, leaf and needle samples from elevated traps from a single collection event are analyzed for carbon and nitrogen concentrations and stable isotopes as well as lignin concentrations.