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The gCube System - Accounting Aggregator -------------------------------------------------- Accounting Aggregator Smart Executor Plugin This software is part of the gCube Framework (https://www.gcube-system.org/): an open-source software toolkit used for building and operating Hybrid Data Infrastructures enabling the dynamic deployment of Virtual Research Environments by favouring the realisation of reuse oriented policies. The projects leading to this software have received funding from a series of European Union programmes including: * the Sixth Framework Programme for Research and Technological Development - DILIGENT (grant no. 004260); * the Seventh Framework Programme for research, technological development and demonstration - D4Science (grant no. 212488), D4Science-II (grant no. 239019),ENVRI (grant no. 283465), EUBrazilOpenBio (grant no. 288754), iMarine (grant no. 283644); * the H2020 research and innovation programme - BlueBRIDGE (grant no. 675680), EGIEngage (grant no. 654142), ENVRIplus (grant no. 654182), Parthenos (grant no. 654119), SoBigData (grant no. 654024); Version -------------------------------------------------- 1.2.0-4.8.0-154717 (2017-12-01) Please see the file named "changelog.xml" in this directory for the release notes. Authors -------------------------------------------------- * Alessandro Pieve (alessandro.pieve-AT-isti.cnr.it), Istituto di Scienza e Tecnologie dell'Informazione "A. Faedo" - CNR, Pisa (Italy). * Luca Frosini (luca.frosini-AT-isti.cnr.it), Istituto di Scienza e Tecnologie dell'Informazione "A. Faedo" - CNR, Pisa (Italy). Maintainers ----------- * Luca Frosini (luca.frosini-AT-isti.cnr.it), Istituto di Scienza e Tecnologie dell'Informazione "A. Faedo" - CNR, Pisa (Italy). Download information -------------------------------------------------- Source code is available from SVN: https://svn.research-infrastructures.eu/public/d4science/gcube/trunk/accounting/accounting-aggregator-se-plugin Binaries can be downloaded from the gCube website: https://www.gcube-system.org/ Installation -------------------------------------------------- Installation documentation is available on-line in the gCube Wiki: https://wiki.gcube-system.org/gcube/index.php/SmartExecutor Documentation -------------------------------------------------- Documentation is available on-line in the gCube Wiki: https://wiki.gcube-system.org/gcube/index.php/SmartExecutor Support -------------------------------------------------- Bugs and support requests can be reported in the gCube issue tracking tool: https://support.d4science.org/projects/gcube/ Licensing -------------------------------------------------- This software is licensed under the terms you may find in the file named "LICENSE" in this directory.

ISIMIP-2a climate data cutout provided for Sardinia in the framework of SIM4NEXUS

The five scenarios describe plausible changes in 15 external drivers of the socioecosystem of the Mar Menor and surrounding Campo de Cartagena between 1964 and 2070. These scenarios were developed for evaluation of their impacts on Key Performance Indicators of sustainability using a simulation model based on System Dynamics. This model, developed by Martínez-López et al (2022) can be consulted here. Historic data combined with the Shared Socioeconomic Pathways (SSPs) from the IPCC report ‘Global warming of 1.5°C’ and the Representative Concentration Pathways (RCPs), were used as starting point to develop the model-specific scenarios. The five scenarios are based on SSP 1, SSP2, SSP4 and SSP5 in combination with emission scenarios that will keep global temperature rise below 1.5ºC. The BAU scenario represents a combination of SSP2 without any climate change. The detailed documentation of SSPs from O’Neil et al (http://dx.doi.org/10.1016/j.gloenvcha.2015.01.004) and subsequent expert interviews and input received during stakeholder workshops organised in the framework of the COASTAL project were used to prepare the region-specific time-series of the 15 variables for the Mar Menor and surrounding Campo de Cartagena. The 15 external drivers are: Agricultural revenue per hectare Growth rate of agriculture Percentage of nutrients that are metabolized by the native lagoon ecosystem Average excess of fertilizer use Yearly effectiveness in nutrients reduction of nutrients, soil and water retention measures Electricity Price Mean number of hours per day of photovoltaic electricity production Photovoltaic energy facilities growth rate in Megawatts installed Growth rate of tourism Average percentage of groundwater desalinated Agricultural water demand per hectare Catchment water sources Urban wastewater treatment plant effluents Yearly average of sea water desalination Amount of water transferred from the Tagus river (RCP15ATS)

Noug (Guizotia abyssinica) is a semi-domesticated oil-seed crop, which is primarily cultivated in Ethiopia. Unlike its closest crop relative, sunflower, noug has small seeds, small flowering heads, many branches, many flowering heads, indeterminate flowering, and it shatters in the field. Here we conducted common garden studies and microsatellite analyses of genetic variation to test whether high levels of crop-wild gene flow and/or unfavorable phenotypic correlations have hindered noug domestication. With the exception of one population, analyses of microsatellite variation failed to detect substantial recent admixture between noug and its wild progenitor. Likewise, only very weak correlations were found between seed mass and the number or size of flowering heads. Thus, noug's ‘atypical’ domestication syndrome does not seem to be a consequence of recent introgression or unfavorable phenotypic correlations. Nonetheless, our data do reveal evidence of local adaptation of noug cultivars to different precipitation regimes, as well as high levels of phenotypic plasticity, which may permit reasonable yields under diverse environmental conditions. Why noug has not been fully domesticated remains a mystery, but perhaps early farmers selected for resilience to episodic drought or untended environments rather than larger seeds. Domestication may also have been slowed by noug's outcrossing mating system. Noug microsatellite dataThis file contains microsatellite scores (allele fragment lengths) for 16 loci and 639 individuals, representing 33 populations of noug (Guizotia abyssinica) and it's wild relative (Guizotia scabra ssp. schimperii).noug_microsatellitest.txtNoug phenotypic dataThis file contains phenotypic data collected on the level of individuals (sheet: Noug_Individual_Data), accessions (sheet: Noug_Pooled_Data) and environmental data of the collecting sites (sheet: Environmental_Data).noug_pheno_data.xlsx

Parcel soil scan with electric conductivity measurement from Netherlands

Web of Science search terms for UK invasive species publication numbers, alongside resulting study numbers

Figure 1 - Dendrogram of southern African leguminochoria delimited by Multivariate Agglomerative Hierarchical Clustering. A1 Southern Afromontane A2 Albany Centre A3 Northern Highveld Region A4 Drakensberg Alpine Centre A5 Coastal Region B1 Arid Western Region B2 Lower-rainfall Cape Floristic Region B3 Central Arid Region B4 Generalist Group B5 Summer Rainfall Region B6 Northern & Northeastern Savannah Region B7 Kalahari Bushveld Region C Higher-rainfall Cape Floristic Region D1 Central Bushveld Region D2 Subtropical Lowveld & Mopane Region E Northern Mistbelt.

Tropical dry forests (TDFs) in the Americas are considered the first frontier of economic development with less than 1% of their total original coverage under protection. Accordingly, accurate estimates of their spatial extent, fragmentation, and degree of regeneration are critical in evaluating the success of current conservation policies. This study focused on a well-protected secondary TDF in Santa Rosa National Park (SRNP) Environmental Monitoring Super Site, Guanacaste, Costa Rica. We used spectral signature analysis of TDF ecosystem succession (early, intermediate, and late successional stages), and its intrinsic variability, to propose a new multiple criteria spectral mixture analysis (MCSMA) method on the shortwave infrared (SWIR) of HyMap image. Unlike most existing iterative mixture analysis (IMA) techniques, MCSMA tries to extract and make use of representative endmembers with spectral and spatial information. MCSMA then considers three criteria that influence the comparative importance of different endmember combinations (endmember models): root mean square error (RMSE); spatial distance (SD); and fraction consistency (FC), to create an evaluation framework to select a best-fit model. The spectral analysis demonstrated that TDFs have a high spectral variability as a result of biomass variability. By adopting two search strategies, the unmixing results showed that our new MCSMA approach had a better performance in root mean square error (early: 0.160/0.159; intermediate: 0.322/0.321; and late: 0.239/0.235); mean absolute error (early: 0.132/0.128; intermediate: 0.254/0.251; and late: 0.191/0.188); and systematic error (early: 0.045/0.055; intermediate: −0.211/−0.214; and late: 0.161/0.160), compared to the multiple endmember spectral mixture analysis (MESMA). This study highlights the importance of SWIR in differentiating successional stages in TDFs. The proposed MCSMA provides a more flexible and generalized means for the best-fit model determination than common IMA methods. Data files and figures for the paperData_files.zip

The scenarios are developed based on projected climate and socio-economic changes, following the representative concentration pathways (RCPs) and the shared socioeconomic pathways (SSPs) for the region. The Norrström-Baltic SD model analyzes possible future shifts in the annual average conditions of sectoral and natural water system interactions. Such shifts are evaluated based on recent annual averages reflecting the condition of system components. Parameters taken into account are, amongst others, sectoral water availability, water fluxes between sectors and the corresponding nutrient (nitrogen and phosphorus) exchanges, coastal runoff and nitrogen and phosphorous loads ending up in the Baltic Sea. An overview of the model input variables and the parameters that are identified as system external uncertainties that may affect the behavior of the model: - Precipitation: climate change - Agricultural land: Development policies and market forces, food security and trade regulations, population growth and corresponding food demand/diet changes - Built-up land: Development policies and market forces, population growth, regional urbanization level, tourism expansion level - Forest land: Mitigation policies on climate change (i.e. afforestation and/or reforestation to maintain/enhance carbon capture and storage capacity), socio-economic developments leading to sectoral land competition (i.e. deforestation) - Open lands and wetlands: Policies and market forces supporting social and economic development in the region A total of 5 scenarios were developed for the Norrström/Baltic Sea case. One of them represents the ‘Base case’ conditions, while the rest are rooted in the combination of a certain SSP with a climate scenario linked to a certain RCP. The following overview shows the combinations used during the scenario building process: - Scenario 1: SSP1 + RCP 4.5 - Scenario 2: SSP2 + RCP 4.5 - Scenario 3: SSP4 + RCP 4.5 - Scenario 4: SSP5 + RCP 4.5 - Base Case scenario: Continuation into the future of the past-recent long-term average conditions in relation to hydro-climate and land use variables in the SD model. All the scenarios developed for the Norrström-Baltic region are linked to a climate scenario corresponding with RCP4.5, because projected patterns and changes for climate variables under this climate scenario were found to be more consistent with the observed changes in the region than other RCPs. The period 2010-2100 is compared with the normal mean for the period 1961-1990. Each year is compared separately with the long-term annual average precipitation. The xsls file is organized as follows. It comprises three sheets: Precipitation RCP with annual data of changes in annual precipitation (in percentage), precipitation (in million of m3/year and in mm/year); Land cover RCPs and SSPs with scenario data on land cover, annual change in land cover (in percentage), annual land cover areas for the Norrström water management district area, land dover area average for teh Norrström water management district area and average change in land cover compared to the long-term average (in percentage); Input data model with the four input variables (precipitation change rate in hydro-climate scenarios, urban growth rate in socioeconomic scenarios, forest land change rate in socioeconomic scenarios and agricultural land change rate in socioeconomic scenarios) and their change for each scenario (expressed in percentage).

Scatter-hoarding rodents can act as both predators and dispersers for many large-seeded plants because they cache seeds for future use, but occasionally forget them in sites with high survival and establishment probabilities. The most important fruit or seed trait influencing rodent foraging behavior is seed size; rodents prefer large seeds because they have higher nutritional content, but this preference can be counterbalanced by the higher costs of handling larger seeds. We designed a cafeteria experiment to assess whether fruit and seed size of Myrcianthes coquimbensis, an endangered desert shrub, influence the decision-making process during foraging by three species of scatter-hoarding rodents differing in body size: Abrothrix olivaceus, Phyllotis darwini and Octodon degus. We found that the size of fruits and seeds influenced foraging behavior in the three rodent species; the probability of a fruit being harvested and hoarded was higher for larger fruits than for smaller ones. Patterns of fruit size preference were not affected by rodent size; all species were able to hoard fruits within the entire range of sizes offered. Finally, fruit and seed size had no effect on the probability of seed predation, rodents typically ate only the fleshy pulp of the fruits offered and discarded whole, intact seeds. In conclusion, our results reveal that larger M. coquimbensis fruits have higher probabilities of being harvested, and ultimately of its seeds being hoarded and dispersed by scatter-hoarding rodents. As this plant has no other dispersers, rodents play an important role in its recruitment dynamics. Data on fruit sizes and selection by rodentsThis datafile contains data on 30 experimental trials, 10 per each of three species of rodents (Octodon degus, Phyllotis darwini and Abrothrix olivaceus) in which individuals were offered Myrcianthes coquimbensis fruits of different sizes (n=30). The data shows the fate of each fruit and seed (e.g., ignored, hoarded, predated) in each of the trials.Data_Luna_etal_2016.xlsx