| 1. |
- Biurrun, Idoia, et al.
(författare)
-
Benchmarking plant diversity of Palaearctic grasslands and other open habitats
- 2021
-
Ingår i: Journal of Vegetation Science. - Oxford : John Wiley & Sons. - 1100-9233 .- 1654-1103. ; 32:4
-
Tidskriftsartikel (refereegranskat)abstract
- Journal of Vegetation Science published by John Wiley & Sons Ltd on behalf of International Association for Vegetation Science.Aims: Understanding fine-grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine-grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location: Palaearctic biogeographic realm. Methods: We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m2 and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results: Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi-natural) grasslands and natural grasslands are the richest vegetation type. The open-access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions: The GrassPlot Diversity Benchmarks provide high-quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation-plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology. © 2021 The Authors.
|
|
| 2. |
- Dengler, Juergen, et al.
(författare)
-
GrassPlot - a database of multi-scale plant diversity in Palaearctic grasslands
- 2018
-
Ingår i: Phytocoenologia. - : Schweizerbart. - 0340-269X. ; 48:3, s. 331-347
-
Tidskriftsartikel (refereegranskat)abstract
- GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001;... 1,000 m(2)) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database " sPlot". Its main aim is to facilitate studies on the scale-and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board.
|
|
| 3. |
|
|
| 4. |
- Galván, Edgar, et al.
(författare)
-
Agents in a privacy-preserving world
- 2021
-
Ingår i: Transactions on Data Privacy. - : University of Skövde. - 1888-5063 .- 2013-1631. ; 14:1, s. 53-63
-
Tidskriftsartikel (refereegranskat)abstract
- Privacy is a fluid concept. It is both difficult to define and difficult to achieve. The large amounts of data currently available at hands of companies and administrations increase individual concerns on what is yet to be known about us. For the sake of penalisation and customisation, we often need to give up and supply information that we consider sensitive and private. Other sensitive information is inferred from information that seems harmless. Even when we explicitly require privacy and anonymity, profiling and device fingerprinting may disclose information about us leading to reidentification. Mobile devices and the internet of things make keeping our live private still more difficult. Agent technologies can play a fundamental role to provide privacy-aware solutions. Agents are inherently suitable in the heterogeneous environment in which our devices work, and we can delegate to them the task of protecting our privacy. Agents should be able to reason about our privacy requirements, and may collaborate (or not) with other agents to help us to achieve our privacy goals. We are presented in the connected world with multiple interests, profiles, and also through multiple agentified devices. We envision our agentified devices to collaborate among themselves and with other devices so that our privacy preferences are satisfied. We believe that this is an overlooked field. Our work intends to start shedding some light on the topic by outlining the requirements and challenges where agent technologies can provide a decisive role.
|
|
| 5. |
- Katos, Vasilis, et al.
(författare)
-
Surveillance, Privacy and The Law of Requisite Variety
- 2011
-
Ingår i: Data Privacy Management and Autonomous Spontaneous Security. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783642193477 ; 6514, s. 123-139
-
Bokkapitel (refereegranskat)abstract
- In both the academic literature and in the media there have been concerns expressed about the level of surveillance technologies used to facilitate security and its effect upon privacy. Government policies in the USA and the UK are continuing to increase surveillance technologies to counteract perceived terrorist threats. Reflecting upon Ashby’s Law of Requisite Variety, the authors conclude that these policies will not meet espoused ends and investigate an alternative strategy for policy making. The authors develop a methodology by drawing on an isomorphy of concepts from the discipline of Macroeconomics. This proposal is achieved by considering security and privacy as economic goods, where surveillance is seen as security technologies serving ID management and privacy is considered as being supported by ID assurance solutions. As the means of exploring the relationship between surveillance and privacy in terms of the proposed methodology, the authors use scenarios from a public report commissioned by the UK Government. The result of this exercise suggests that the proposed methodology could be a valuable tool for decision making at a strategic and aggregate level.
|
|
