Landscape Phenology Modelling and Decision Support in Serbia

Lalić, Branislava; Marcic, Milena; Sremac, Ana Firanj; Eitzinger, Josef; Koci, Ivan; Petrić, Tara; Ljubojević, Mirjana; Jezerkic, Bosko

doi:10.1007/978-3-030-37421-1_29

Cited by 5 publications

(2 citation statements)

References 17 publications

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“…However, spatial coverage is and will remain limited due to significant investment and maintenance costs. In terms of researchers, the target base for the FAIRNESS Cost Action is primarily, networks of Automated Weather Stations (AWSs) installed in rural, sub-urban and urban areas as part of various agrometeorology projects, such as pest and disease warning systems, forest, urban and environmental meteorology [7,12].…”

Section: Cost Action Motivationmentioning

confidence: 99%

Constructing a Searchable Knowledge Repository for FAIR Climate Data

Roantree¹,

Lalić

Savić

et al. 2023

Preprint

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The development of a knowledge repository for climate science data is a multidisciplinary effort between the domain experts (climate scientists), data engineers who's skills include design and building a knowledge repository, and machine learning researchers who provide expertise on data preparation tasks such as gap filling and advise on different machine learning models that can exploit this data. One of the main goals of the CA20108 cost action is to develop a knowledge portal that is fully compliant with the FAIR principles for scientific data management. In the first year, a bespoke knowledge portal was developed to capture metadata for FAIR datasets. Its purpose was to provide detailed metadata descriptions for shareable micro-meteorological (micromet) data using the WMO standard. While storing Network, Site and Sensor metadata locally, the system passes the actual data to Zenodo, receives back the DOI and thus, creates a permanent link between the Knowledge Portal and the storage platform Zenodo. While the user searches the Knowledge portal (metadata), results provide both detailed descriptions and links to data on the Zenodo platform. Our adherence to FAIR principles are documented below: <ul> <li>Findable. Machine-readable metadata is required for automatic discovery of datasets and services. A metadata description is supplied by the data owners for all micro-meteorological data shared on the system which subsequently drives the search engine, using keywords or network, site and sensor search terms.</li> <li>Accessible. When suitable datasets have been identified, access details should be provided. Assuming data is freely accessible, Zenodo DOIs and links are provided for direct data access.</li> <li>Interoperable. Data interoperability means the ability to share and integrate data from different users and sources. This can only happen if a standard (meta)data model is employed to describe data, an important concept which generally requires data engineering skills to deliver. In the knowledge portal presented here, the WMO guide provides the design and structure for metadata.&#160;&#160;&#160;&#160;</li> <li>Reusable. To truly deliver reusability, metadata should be expressed in as detailed a manner as possible. In this way, data can be replicated and integrated according to different scientific requirements. While the Knowledge Portal facilitates very detailed metadata descriptions, not all metadata is compulsory as it was accepted that in some cases, the overhead in providing this information can be very costly.&#160;</li> </ul> Simple analytics are in place to monitor the volume and size of networks in the system. Current metrics include: network count; average size of network (number of sites); dates and size of datasets per network/site; numbers and types of sensors in each site, etc. The current Portal is in Beta version meaning that the system is currently functional but open only to members of the Cost Action who are nominated testers. This status is due to change in Q1/2023 when access will be open to the wider climate science community.&#160;&#160; Current plans include new Tools and Services to assess the quality of data, including the level of gaps and in some cases, machine learning tools will be provided to attempt gap filling for datasets meeting certain requirements. &#160;

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Section: Cost Action Motivationmentioning

confidence: 99%

Constructing a Searchable Knowledge Repository for FAIR Climate Data

Roantree¹,

Lalić

Savić

et al. 2023

Preprint

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“…Field-specific data could allow spatial analysis and the identification of hotspots for SCS. On a broader scale, research is also needed to identify other barriers to implementation than solely biophysical ones (including economic, social, institutional and political constraints) [94].…”

Section: Limitations and Outlookmentioning

confidence: 99%

Modeling Climate Regulation of Arable Soils in Northern Saxony under the Influence of Climate Change and Management Practices

Schwengbeck,

Hölting,

Witing

2023

Sustainability

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One approach to increasing the climate-regulating potential of the agricultural sector is carbon sequestration in agricultural soils. This involves storing atmospheric carbon dioxide in the soil in the form of soil organic carbon (SOC) through agricultural management practices (AMPs). Model simulations of area-specific current and future SOC stocks can be used to test appropriate AMPs. In this study, the CANDY Carbon Balance (CCB) model was used to determine how different AMPs could affect SOC stocks in a study area in northern Saxony, Germany. Specifically, we used scenarios with different intensities of sustainable AMPs to assess the potential effects of reduced tillage, crop cultivation, and fertilizer management, as well as the management of crop residues and by-products. The analysis was carried out for the simulation period 2020–2070, with and without consideration of climate change effects. The results showed an average carbon sequestration potential of 5.13–7.18 t C ha−1 for the whole study area, depending on the intensity of AMP implemented. While higher intensities of sustainable AMP implementation generally had a positive impact on carbon sequestration, the scenario with the highest implementation intensity only led to the second highest gains in SOC stocks. The most important factor in increasing SOC stocks was reduced tillage, which resulted in a carbon sequestration potential of 0.84 t C ha−1 by 2070. However, reduced application rates of fertilizers also proved to be critical, resulting in a reduction in carbon stocks of up to 2.2 t C ha−1 by 2070. Finally, the application of high-intensity sustainable AMPs was shown to be able to offset the negative impacts of an intermediate climate change scenario for most of the simulation period. Overall, the results not only confirmed existing knowledge on the effects of AMPs on carbon sequestration for a specific case study area, but also identified future management scenarios that stress the need for widespread adoption of sustainable management practices under changing climate conditions.

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