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The small ice-free areas of Antarctica are essential locations for both biodiversity and scientific research but are subject to considerable and expanding human impacts, resulting primarily from station-based research and support activities, and local tourism. Awareness by operators of the need to conserve natural values in and around station and visitor site footprints exists, but the cumulative nature of impacts often results in reactive rather than proactive management. With human activity spread across many isolated pockets of ice-free ground, the pathway to the greatest reduction of human impacts within this natural reserve is through better management of these areas, which are impacted the most. Using a case study of Australia's Casey Station, we found significant natural values persist within the immediate proximity (<10 m) of long-term station infrastructure, but encroachment by physical disturbance results in ongoing pressures. Active planning to better conserve such values would provide a direct opportunity to enhance protection of Antarctica's environment. Here we introduce an approach to systematic conservation planning, tailored to Antarctic research stations, to help managers improve the conservation of values surrounding their activity locations. Use of this approach provides a potential mechanism to balance the need for scientific access to the continent with international obligations to protect its environment. It may also facilitate the development of subordinate conservation tools, including management plans and natural capital accounting. By proactively minimising and containing their station footprints, national programs can also independently demonstrate their commitment to protecting Antarctica's environment.

The small ice-free areas of Antarctica are essential locations for both biodiversity and scientific research but are subject to considerable and expanding human impacts, resulting primarily from station-based research and support activities, and local tourism. Awareness by operators of the need to conserve natural values in and around station and visitor site footprints exists, but the cumulative nature of impacts often results in reactive rather than proactive management. With human activity spread across many isolated pockets of ice-free ground, the pathway to the greatest reduction of human impacts within this natural reserve is through better management of these areas, which are impacted the most. Using a case study of Australia's Casey Station, we found significant natural values persist within the immediate proximity (<10 m) of long-term station infrastructure, but encroachment by physical disturbance results in ongoing pressures. Active planning to better conserve such values would provide a direct opportunity to enhance protection of Antarctica's environment. Here we introduce an approach to systematic conservation planning, tailored to Antarctic research stations, to help managers improve the conservation of values surrounding their activity locations. Use of this approach provides a potential mechanism to balance the need for scientific access to the continent with international obligations to protect its environment. It may also facilitate the development of subordinate conservation tools, including management plans and natural capital accounting. By proactively minimising and containing their station footprints, national programs can also independently demonstrate their commitment to protecting Antarctica's environment.

A dataset to describe exposed bedrock and surficial geology of Antarctica has been constructed by the GeoMAP Action Group of the Scientific Committee on Antarctic Research (SCAR) and GNS Science. Our group captured existing geological map data into a geographic information system (GIS), refined its spatial reliability, harmonised classification, and improved representation of glacial sequences and geomorphology, thereby creating a comprehensive and coherent representation of Antarctic geology. A total of 99,080 polygons were unified for depicting geology at 1:250,000 scale, but locally there are some areas with higher spatial resolution. Geological unit definition is based on a mixed chronostratigraphic- and lithostratigraphic-based classification. Description of rock and moraine polygons employs the international Geoscience Markup Language (GeoSciML) data protocols to provide attribute-rich and queryable information, including bibliographic links to 589 source maps and scientific literature. GeoMAP is the first detailed geological map dataset covering all of Antarctica. It depicts ‘known geology’ of rock exposures rather than ‘interpreted’ sub-ice features and is suitable for continent-wide perspectives and cross-discipline interrogation.

Quantarctica (https://www.npolar.no/quantarctica) is a geospatial data package, analysis environment, and visualization platform for the Antarctic Continent, Southern Ocean (>40oS), and sub-Antarctic islands. Quantarctica works with the free, cross-platform Geographical Information System (GIS) software QGIS and can run without an Internet connection, making it a viable tool for fieldwork in remote areas. The data package includes basemaps, satellite imagery, terrain models, and scientific data in nine disciplines, including physical and biological sciences, environmental management, and social science. To provide a clear and responsive user experience, cartography and rendering settings are carefully prepared using colour sets that work well for typical data combinations and with consideration of users with common colour vision deficiencies. Metadata included in each dataset provides brief abstracts for non-specialists and references to the original data sources. Thus, Quantarctica provides an integrated environment to view and analyse multiple Antarctic datasets together conveniently and with a low entry barrier.

Many text documents in the biological domain contain references to the toponym of specific phenomena (e.g. species sightings) in natural language form "In Garwood Valley summer activity was 0.2% for Umbilicaria aprina and 1.7% for Caloplaca sp. ..." While methods have been developed to extract place names from documents, and attention has been given to the interpretation of spatial prepositions, the ability to connect toponym mentions in text with the phenomena to which they refer (in this case species) has been given limited attention, but would be of considerable benefit for the task of mapping specific phenomena mentioned in text documents. As part of work to create a pipeline to automate georeferencing of species within legacy documents, this paper proposes a method to: (1) recognise species and toponyms within text and (2) match each species mention to the relevant toponym mention. Our methods find significant promise in a bespoke rules- and dictionary-based approach to recognise species within text (F1 scores up to 0.87 including partial matches) but less success, as yet, recognising toponyms using multiple gazetteers combined with an off the shelf natural language processing tool (F1 up to 0.62). Most importantly, we offer a contribution to the relatively nascent area of matching toponym references to the object they locate (in our case species), including cases in which the toponym and species are in different sentences. We use tree-based models to achieve precision as high as 0.88 or an F1 score up to 0.68 depending on the downsampling rate. Initial results out perform previous research on detecting entity relationships that may cross sentence boundaries within biomedical text, and differ from previous work in specifically addressing species mapping.

Quantarctica (https://www.npolar.no/quantarctica) is a geospatial data package, analysis environment, and visualization platform for the Antarctic Continent, Southern Ocean (>40oS), and sub-Antarctic islands. Quantarctica works with the free, cross-platform Geographical Information System (GIS) software QGIS and can run without an Internet connection, making it a viable tool for fieldwork in remote areas. The data package includes basemaps, satellite imagery, terrain models, and scientific data in nine disciplines, including physical and biological sciences, environmental management, and social science. To provide a clear and responsive user experience, cartography and rendering settings are carefully prepared using colour sets that work well for typical data combinations and with consideration of users with common colour vision deficiencies. Metadata included in each dataset provides brief abstracts for non-specialists and references to the original data sources. Thus, Quantarctica provides an integrated environment to view and analyse multiple Antarctic datasets together conveniently and with a low entry barrier.

Quantarctica (https://www.npolar.no/quantarctica) is a geospatial data package, analysis environment, and visualization platform for the Antarctic Continent, Southern Ocean (>40oS), and sub-Antarctic islands. Quantarctica works with the free, cross-platform Geographical Information System (GIS) software QGIS and can run without an Internet connection, making it a viable tool for fieldwork in remote areas. The data package includes basemaps, satellite imagery, terrain models, and scientific data in nine disciplines, including physical and biological sciences, environmental management, and social science. To provide a clear and responsive user experience, cartography and rendering settings are carefully prepared using colour sets that work well for typical data combinations and with consideration of users with common colour vision deficiencies. Metadata included in each dataset provides brief abstracts for non-specialists and references to the original data sources. Thus, Quantarctica provides an integrated environment to view and analyse multiple Antarctic datasets together conveniently and with a low entry barrier.

Many text documents in the biological domain contain references to the toponym of specific phenomena (e.g. species sightings) in natural language form "In Garwood Valley summer activity was 0.2% for Umbilicaria aprina and 1.7% for Caloplaca sp. ..." While methods have been developed to extract place names from documents, and attention has been given to the interpretation of spatial prepositions, the ability to connect toponym mentions in text with the phenomena to which they refer (in this case species) has been given limited attention, but would be of considerable benefit for the task of mapping specific phenomena mentioned in text documents. As part of work to create a pipeline to automate georeferencing of species within legacy documents, this paper proposes a method to: (1) recognise species and toponyms within text and (2) match each species mention to the relevant toponym mention. Our methods find significant promise in a bespoke rules- and dictionary-based approach to recognise species within text (F1 scores up to 0.87 including partial matches) but less success, as yet, recognising toponyms using multiple gazetteers combined with an off the shelf natural language processing tool (F1 up to 0.62). Most importantly, we offer a contribution to the relatively nascent area of matching toponym references to the object they locate (in our case species), including cases in which the toponym and species are in different sentences. We use tree-based models to achieve precision as high as 0.88 or an F1 score up to 0.68 depending on the downsampling rate. Initial results out perform previous research on detecting entity relationships that may cross sentence boundaries within biomedical text, and differ from previous work in specifically addressing species mapping.

info:eu-repo/semantics/published

Recent assessments of Earth’s dwindling wilderness have emphasized that Antarctica is a crucial wilderness in need of protection1,2. Yet human impacts on the continent are widespread3–5, the extent of its wilderness unquantified2 and the importance thereof for biodiversity conservation unknown. Here we assemble a comprehensive record of human activity (approximately 2.7 million records, spanning 200 years) and use it to quantify the extent of Antarctica’s wilderness and its representation of biodiversity. We show that 99.6% of the continent’s area can still be considered wilderness, but this area captures few biodiversity features. Pristine areas, free from human interference, cover a much smaller area (less than 32% of Antarctica) and are declining as human activity escalates6. Urgent expansion of Antarctica’s network of specially protected areas7 can both reverse this trend and secure the continent’s biodiversity8–10.

Aim: To present a synthesis of past biogeographic analyses and a new approach based on spatially explicit biodiversity information for the Antarctic region to identify biologically distinct areas in need of representation in a protected area network. Location Antarctica and the sub-Antarctic. Methods: We reviewed and summarized published biogeographic studies of the Antarctic. We then developed a biogeographic classification for terrestrial conservation planning in Antarctica by combining the most comprehensive source of Antarctic biodiversity data available with three spatial frameworks: (1) a 200-km grid, (2) a set of areas based on physical parameters known as the environmental domains of Antarctica and (3) expert-defined bioregions. We used these frameworks, or combinations thereof, together with multivariate techniques to identify biologically distinct areas. Results: Early studies of continental Antarctica typically described broad bioregions, with the Antarctic Peninsula usually identified as biologically distinct from continental Antarctica; later studies suggested a more complex biogeography. Increasing complexity also characterizes the sub-Antarctic and marine realms, with differences among studies often attributable to the focal taxa. Using the most comprehensive terrestrial data available and by combining the groups formed by the environmental domains and expert-defined bioregions, we were able to identify 15 biologically distinct, ice-free, Antarctic Conservation Biogeographic Regions (ACBRs), encompassing the continent and close lying islands. Main conclusions: Ice-free terrestrial Antarctica comprises several distinct bioregions that are not fully represented in the current Antarctic Specially Protected Area network. Biosecurity measures between these ACBRs should also be developed to prevent biotic homogenization in the region.

Aim: To present a synthesis of past biogeographic analyses and a new approach based on spatially explicit biodiversity information for the Antarctic region to identify biologically distinct areas in need of representation in a protected area network. Location Antarctica and the sub-Antarctic. Methods: We reviewed and summarized published biogeographic studies of the Antarctic. We then developed a biogeographic classification for terrestrial conservation planning in Antarctica by combining the most comprehensive source of Antarctic biodiversity data available with three spatial frameworks: (1) a 200-km grid, (2) a set of areas based on physical parameters known as the environmental domains of Antarctica and (3) expert-defined bioregions. We used these frameworks, or combinations thereof, together with multivariate techniques to identify biologically distinct areas. Results: Early studies of continental Antarctica typically described broad bioregions, with the Antarctic Peninsula usually identified as biologically distinct from continental Antarctica; later studies suggested a more complex biogeography. Increasing complexity also characterizes the sub-Antarctic and marine realms, with differences among studies often attributable to the focal taxa. Using the most comprehensive terrestrial data available and by combining the groups formed by the environmental domains and expert-defined bioregions, we were able to identify 15 biologically distinct, ice-free, Antarctic Conservation Biogeographic Regions (ACBRs), encompassing the continent and close lying islands. Main conclusions: Ice-free terrestrial Antarctica comprises several distinct bioregions that are not fully represented in the current Antarctic Specially Protected Area network. Biosecurity measures between these ACBRs should also be developed to prevent biotic homogenization in the region.

This Technical Guide and a parallel volume, Land Environments of New Zealand, describe an environmental classification of New Zealand that is designed to provide a framework for addressing a range of conservation and resource management issues. This classification has been produced by Landcare Research with funding and support from the Ministry for the Environment. Subtitle on cover: Nga Taiao o Aotearoa.

This Technical Guide and a parallel volume, Land Environments of New Zealand, describe an environmental classification of New Zealand that is designed to provide a framework for addressing a range of conservation and resource management issues. This classification has been produced by Landcare Research with funding and support from the Ministry for the Environment. Subtitle on cover: Nga Taiao o Aotearoa.