Suchergebnisse

There are many new land use and land cover (LULC) products emerging yet there is still a lack of in situ data for training, validation, and change detection purposes. The LUCAS (Land Use Cover Area frame Sample) survey is one of the few authoritative in situ field campaigns, which takes place every three years in European Union member countries. More recently, a study has considered whether citizen science and crowdsourcing could complement LUCAS survey data, e.g., through the FotoQuest Austria mobile app and crowdsourcing campaign. Although the data obtained from the campaign were promising when compared with authoritative LUCAS survey data, there were classes that were not well classified by the citizens. Moreover, the photographs submitted through the app were not always of sufficient quality. For these reasons, in the latest FotoQuest Go Europe 2018 campaign, several improvements were made to the app to facilitate interaction with the citizens contributing and to improve their accuracy in LULC identification. In addition to extending the locations from Austria to Europe, a change detection component (comparing land cover in 2018 to the 2015 LUCAS photographs) was added, as well as an improved LC decision tree. Furthermore, a near real-time quality assurance system was implemented to provide feedback on the distance to the target location, the LULC classes chosen and the quality of the photographs. Another modification was a monetary incentive scheme in which users received between 1 to 3 Euros for each successfully completed quest of sufficient quality. The purpose of this paper is to determine whether citizens can provide high quality in situ data on LULC through crowdsourcing that can complement LUCAS. We compared the results between the FotoQuest campaigns in 2015 and 2018 and found a significant improvement in 2018, i.e., a much higher match of LC between FotoQuest Go Europe and LUCAS. As shown by the cost comparisons with LUCAS, FotoQuest can complement LUCAS surveys by enabling continuous collection of large amounts of high quality, spatially explicit field data at a low cost.

To meet collective obligations towards biodiversity conservation and monitoring, it is essential that the world's governments and non-governmental organisations as well as the research community tap all possible sources of data and information, including new, fast-growing sources such as citizen science (CS), in which volunteers participate in some or all aspects of environmental assessments. Through compilation of a database on CS and community-based monitoring (CBM, a subset of CS) programs, we assess where contributions from CS and CBM are significant and where opportunities for growth exist. We use the Essential Biodiversity Variable framework to describe the range of biodiversity data needed to track progress towards global biodiversity targets, and we assess strengths and gaps in geographical and taxonomic coverage. Our results show that existing CS and CBM data particularly provide large-scale data on species distribution and population abundance, species traits such as phenology, and ecosystem function variables such as primary and secondary productivity. Only birds, Lepidoptera and plants are monitored at scale. Most CS schemes are found in Europe, North America, South Africa, India, and Australia. We then explore what can be learned from successful CS/CBM programs that would facilitate the scaling up of current efforts, how existing strengths in data coverage can be better exploited, and the strategies that could maximise the synergies between CS/CBM and other approaches for monitoring biodiversity, in particular from remote sensing. More and better targeted funding will be needed, if CS/CBM programs are to contribute further to international biodiversity monitoring.

To meet collective obligations towards biodiversity conservation and monitoring, it is essential that the world's governments and non-governmental organisations as well as the research community tap all possible sources of data and information, including new, fast-growing sources such as citizen science (CS), in which volunteers participate in some or all aspects of environmental assessments. Through compilation of a database on CS and community-based monitoring (CBM, a subset of CS) programs, we assess where contributions from CS and CBM are significant and where opportunities for growth exist. We use the Essential Biodiversity Variable framework to describe the range of biodiversity data needed to track progress towards global biodiversity targets, and we assess strengths and gaps in geographical and taxonomic coverage. Our results show that existing CS and CBM data particularly provide large-scale data on species distribution and population abundance, species traits such as phenology, and ecosystem function variables such as primary and secondary productivity. Only birds, Lepidoptera and plants are monitored at scale. Most CS schemes are found in Europe, North America, South Africa, India, and Australia. We then explore what can be learned from successful CS/CBM programs that would facilitate the scaling up of current efforts, how existing strengths in data coverage can be better exploited, and the strategies that could maximise the synergies between CS/CBM and other approaches for monitoring biodiversity, in particular from remote sensing. More and better targeted funding will be needed, if CS/CBM programs are to contribute further to international biodiversity monitoring.

To meet collective obligations towards biodiversity conservation and monitoring, it is essential that the world's governments and non-governmental organisations as well as the research community tap all possible sources of data and information, including new, fast-growing sources such as citizen science (CS), in which volunteers participate in some or all aspects of environmental assessments. Through compilation of a database on CS and community-based monitoring (CBM, a subset of CS) programs, we assess where contributions from CS and CBM are significant and where opportunities for growth exist. We use the Essential Biodiversity Variable framework to describe the range of biodiversity data needed to track progress towards global biodiversity targets, and we assess strengths and gaps in geographical and taxonomic coverage. Our results show that existing CS and CBM data particularly provide large-scale data on species distribution and population abundance, species traits such as phenology, and ecosystem function variables such as primary and secondary productivity. Only birds, Lepidoptera and plants are monitored at scale. Most CS schemes are found in Europe, North America, South Africa, India, and Australia. We then explore what can be learned from successful CS/CBM programs that would facilitate the scaling up of current efforts, how existing strengths in data coverage can be better exploited, and the strategies that could maximise the synergies between CS/CBM and other approaches for monitoring biodiversity, in particular from remote sensing. More and better targeted funding will be needed, if CS/CBM programs are to contribute further to international biodiversity monitoring.

Citizens are providing vast amounts of georeferenced data in the form of in situ data collections as well as interpretations and digitization of Earth-observation (EO) data sets. These new data streams have considerable potential for supporting the calibration and validation of current and future products derived from EO. We provide a general introduction to this growing area of interest and review existing crowdsourcing and citizen science (CS) initiatives of relevance to EO. We then draw upon our own experiences to provide case studies that highlight different types of data collection and citizen engagement and discuss the various barriers to adoption. Finally, we highlight opportunities for how citizens can become part of an integrated EO monitoring system in the framework of the European Union (EU) space program, including Copernicus and other monitoring initiatives.

Citizens are providing vast amounts of georeferenced data in the form of in situ data collections as well as interpretations and digitization of Earth-observation (EO) data sets. These new data streams have considerable potential for supporting the calibration and validation of current and future products derived from EO. We provide a general introduction to this growing area of interest and review existing crowdsourcing and citizen science (CS) initiatives of relevance to EO. We then draw upon our own experiences to provide case studies that highlight different types of data collection and citizen engagement and discuss the various barriers to adoption. Finally, we highlight opportunities for how citizens can become part of an integrated EO monitoring system in the framework of the European Union (EU) space program, including Copernicus and other monitoring initiatives.

The contribution of citizen science to addressing societal challenges has long been recognized. The United Nations (UN) Sustainable Development Goals (SDGs), as an overarching policy framework and a roadmap to guide global development efforts until 2030 for achieving a better future for all, could benefit from the potential that citizen science offers. However, there is a lack of knowledge on the value of citizen science, particularly in addressing the data needs for SDG monitoring, among the UN agencies, national statistical offices, policy makers and the citizen science community itself. To address this challenge, we launched a Community of Practice on Citizen Science and the SDGs (SDGs CoP) in November 2018 as part of the EU Horizon 2020 funded WeObserve project. The SDGs CoP brings together citizen science researchers, practitioners, UN custodian agencies, broader data communities and other key actors to develop an understanding on how to demonstrate the value of citizen science for SDG achievement. The initial focus and the main objective of the SDGs CoP has been to conduct a research study to understand the contribution of citizen science to SDG monitoring and implementation. In this talk, we will present the work of the SDGs CoP. We will first discuss existing data gaps and needs for measuring progress on the SDGs, and then provide an overview on the results of a systematic review that we undertook within the CoP, showing where citizen science is already contributing and could contribute data to the SDG framework. We will provide concrete examples of our findings to demonstrate how citizen science data could inform the SDGs. We will also touch on the challenges for and barriers to the uptake of citizen science data for the SDG monitoring processes, and how to bring this source of data into the scope of official statistics.

The contribution of citizen science to addressing societal challenges has long been recognized. The United Nations (UN) Sustainable Development Goals (SDGs), as an overarching policy framework and a roadmap to guide global development efforts until 2030 for achieving a better future for all, could benefit from the potential that citizen science offers. However, there is a lack of knowledge on the value of citizen science, particularly in addressing the data needs for SDG monitoring, among the UN agencies, national statistical offices, policy makers and the citizen science community itself. To address this challenge, we launched a Community of Practice on Citizen Science and the SDGs (SDGs CoP) in November 2018 as part of the EU Horizon 2020 funded WeObserve project. The SDGs CoP brings together citizen science researchers, practitioners, UN custodian agencies, broader data communities and other key actors to develop an understanding on how to demonstrate the value of citizen science for SDG achievement. The initial focus and the main objective of the SDGs CoP has been to conduct a research study to understand the contribution of citizen science to SDG monitoring and implementation. In this talk, we will present the work of the SDGs CoP. We will first discuss existing data gaps and needs for measuring progress on the SDGs, and then provide an overview on the results of a systematic review that we undertook within the CoP, showing where citizen science is already contributing and could contribute data to the SDG framework. We will provide concrete examples of our findings to demonstrate how citizen science data could inform the SDGs. We will also touch on the challenges for and barriers to the uptake of citizen science data for the SDG monitoring processes, and how to bring this source of data into the scope of official statistics.

Background: Information about the global structure of agriculture and nutrient production and its diversity is essential to improve present understanding of national food production patterns, agricultural livelihoods, and food chains, and their linkages to land use and their associated ecosystems services. Here we provide a plausible breakdown of global agricultural and nutrient production by farm size, and also study the associations between farm size, agricultural diversity, and nutrient production. This analysis is crucial to design interventions that might be appropriately targeted to promote healthy diets and ecosystems in the face of population growth, urbanisation, and climate change. Methods: We used existing spatially-explicit global datasets to estimate the production levels of 41 major crops, seven livestock, and 14 aquaculture and fish products. From overall production estimates, we estimated the production of vitamin A, vitamin B₁₂, folate, iron, zinc, calcium, calories, and protein. We also estimated the relative contribution of farms of different sizes to the production of different agricultural commodities and associated nutrients, as well as how the diversity of food production based on the number of different products grown per geographic pixel and distribution of products within this pixel (Shannon diversity index [H]) changes with different farm sizes. Findings: Globally, small and medium farms (≤50 ha) produce 51–77% of nearly all commodities and nutrients examined here. However, important regional differences exist. Large farms (>50 ha) dominate production in North America, South America, and Australia and New Zealand. In these regions, large farms contribute between 75% and 100% of all cereal, livestock, and fruit production, and the pattern is similar for other commodity groups. By contrast, small farms (≤20 ha) produce more than 75% of most food commodities in sub-Saharan Africa, southeast Asia, south Asia, and China. In Europe, west Asia and north Africa, and central America, medium-size farms (20–50 ha) also contribute substantially to the production of most food commodities. Very small farms (≤2 ha) are important and have local significance in sub-Saharan Africa, southeast Asia, and south Asia, where they contribute to about 30% of most food commodities. The majority of vegetables (81%), roots and tubers (72%), pulses (67%), fruits (66%), fish and livestock products (60%), and cereals (56%) are produced in diverse landscapes (H>1·5). Similarly, the majority of global micronutrients (53–81%) and protein (57%) are also produced in more diverse agricultural landscapes (H>1·5). By contrast, the majority of sugar (73%) and oil crops (57%) are produced in less diverse ones (H≤1·5), which also account for the majority of global calorie production (56%). The diversity of agricultural and nutrient production diminishes as farm size increases. However, areas of the world with higher agricultural diversity produce more nutrients, irrespective of farm size. Interpretation: Our results show that farm size and diversity of agricultural production vary substantially across regions and are key structural determinants of food and nutrient production that need to be considered in plans to meet social, economic, and environmental targets. At the global level, both small and large farms have key roles in food and nutrition security. Efforts to maintain production diversity as farm sizes increase seem to be necessary to maintain the production of diverse nutrients and viable, multifunctional, sustainable landscapes. Funding: Commonwealth Scientific and Industrial Research Organisation, Bill & Melinda Gates Foundation, CGIAR Research Programs on Climate Change, Agriculture and Food Security and on Agriculture for Nutrition and Health funded by the CGIAR Fund Council, Daniel and Nina Carasso Foundation, European Union, International Fund for Agricultural Development, Australian Research Council, National Science Foundation, Gordon and Betty Moore Foundation, and Joint Programming Initiative on Agriculture, Food Security and Climate Change—Belmont Forum.

Background: Information about the global structure of agriculture and nutrient production and its diversity is essential to improve present understanding of national food production patterns, agricultural livelihoods, and food chains, and their linkages to land use and their associated ecosystems services. Here we provide a plausible breakdown of global agricultural and nutrient production by farm size, and also study the associations between farm size, agricultural diversity, and nutrient production. This analysis is crucial to design interventions that might be appropriately targeted to promote healthy diets and ecosystems in the face of population growth, urbanisation, and climate change. Methods: We used existing spatially-explicit global datasets to estimate the production levels of 41 major crops, seven livestock, and 14 aquaculture and fish products. From overall production estimates, we estimated the production of vitamin A, vitamin B₁₂, folate, iron, zinc, calcium, calories, and protein. We also estimated the relative contribution of farms of different sizes to the production of different agricultural commodities and associated nutrients, as well as how the diversity of food production based on the number of different products grown per geographic pixel and distribution of products within this pixel (Shannon diversity index [H]) changes with different farm sizes. Findings: Globally, small and medium farms (≤50 ha) produce 51–77% of nearly all commodities and nutrients examined here. However, important regional differences exist. Large farms (>50 ha) dominate production in North America, South America, and Australia and New Zealand. In these regions, large farms contribute between 75% and 100% of all cereal, livestock, and fruit production, and the pattern is similar for other commodity groups. By contrast, small farms (≤20 ha) produce more than 75% of most food commodities in sub-Saharan Africa, southeast Asia, south Asia, and China. In Europe, west Asia and north Africa, and central America, medium-size farms (20–50 ha) also contribute substantially to the production of most food commodities. Very small farms (≤2 ha) are important and have local significance in sub-Saharan Africa, southeast Asia, and south Asia, where they contribute to about 30% of most food commodities. The majority of vegetables (81%), roots and tubers (72%), pulses (67%), fruits (66%), fish and livestock products (60%), and cereals (56%) are produced in diverse landscapes (H>1·5). Similarly, the majority of global micronutrients (53–81%) and protein (57%) are also produced in more diverse agricultural landscapes (H>1·5). By contrast, the majority of sugar (73%) and oil crops (57%) are produced in less diverse ones (H≤1·5), which also account for the majority of global calorie production (56%). The diversity of agricultural and nutrient production diminishes as farm size increases. However, areas of the world with higher agricultural diversity produce more nutrients, irrespective of farm size. Interpretation: Our results show that farm size and diversity of agricultural production vary substantially across regions and are key structural determinants of food and nutrient production that need to be considered in plans to meet social, economic, and environmental targets. At the global level, both small and large farms have key roles in food and nutrition security. Efforts to maintain production diversity as farm sizes increase seem to be necessary to maintain the production of diverse nutrients and viable, multifunctional, sustainable landscapes. Funding: Commonwealth Scientific and Industrial Research Organisation, Bill & Melinda Gates Foundation, CGIAR Research Programs on Climate Change, Agriculture and Food Security and on Agriculture for Nutrition and Health funded by the CGIAR Fund Council, Daniel and Nina Carasso Foundation, European Union, International Fund for Agricultural Development, Australian Research Council, National Science Foundation, Gordon and Betty Moore Foundation, and Joint Programming Initiative on Agriculture, Food Security and Climate Change—Belmont Forum.

Invasive Alien Species (IAS) are a growing threat to Europe's biodiversity. The implementation of European Union Regulation on IAS can benefit from the involvement of the public in IAS recording and management through Citizen Science (CS) initiatives. Aiming to tackle issues related with the use of CS projects on IAS topics, a dedicated workshop titled "Citizen Science and Open Data: a model for Invasive Alien Species in Europe" was organized by the Joint Research Centre (JRC) and the European Cooperation in Science and Technology (COST Association). Fifty key stakeholders from all Europe, including two Members of the European Parliament, attended the workshop. With a clear focus on IAS, the workshop aimed at addressing the following issues: a) CS and policy, b) citizen engagement, and c) CS data management. Nine short presentations provided input on CS and IAS issues. Participants discussed specific topics in several round tables ("world café" style) and reported back their conclusions to the audience and full assembly moderated discussions. Overall, the workshop enabled the sharing of ideas, approaches and best practices regarding CS and IAS. Specific opportunities and pitfalls of using CS data in the whole policy cycle for IAS were recognized. Concerning the implementation of the IAS Regulation, CS data could complement official surveillance systems, and contribute to the early warning of the IAS of Union concern after appropriate validation by the Member States' competent authorities. CS projects can additionally increase awareness and empower citizens. Attendees pointed out the importance for further public engagement in CS projects on IAS that demonstrate specific initiatives and approaches and analyze lessons learned from past experiences. In addition, the workshop noted that the data gathered from different CS projects on IAS are fragmented. It highlighted the need for using an open and accessible platform to upload data originating from CS sources or to mirror validated data into a single, easy-to-use web service, in line with the EU Open Science Strategic Priority. The workshop provided ten key recommendations of best practices for CS projects on IAS, addressed to researchers, policy makers and implementing authorities, indicating future research and policy directions and opportunities.

Invasive Alien Species (IAS) are a growing threat to Europe's biodiversity. The implementation of European Union Regulation on IAS can benefit from the involvement of the public in IAS recording and management through Citizen Science (CS) initiatives. Aiming to tackle issues related with the use of CS projects on IAS topics, a dedicated workshop titled "Citizen Science and Open Data: a model for Invasive Alien Species in Europe" was organized by the Joint Research Centre (JRC) and the European Cooperation in Science and Technology (COST Association). Fifty key stakeholders from all Europe, including two Members of the European Parliament, attended the workshop. With a clear focus on IAS, the workshop aimed at addressing the following issues: a) CS and policy, b) citizen engagement, and c) CS data management. Nine short presentations provided input on CS and IAS issues. Participants discussed specific topics in several round tables ("world café" style) and reported back their conclusions to the audience and full assembly moderated discussions. Overall, the workshop enabled the sharing of ideas, approaches and best practices regarding CS and IAS. Specific opportunities and pitfalls of using CS data in the whole policy cycle for IAS were recognized. Concerning the implementation of the IAS Regulation, CS data could complement official surveillance systems, and contribute to the early warning of the IAS of Union concern after appropriate validation by the Member States' competent authorities. CS projects can additionally increase awareness and empower citizens. Attendees pointed out the importance for further public engagement in CS projects on IAS that demonstrate specific initiatives and approaches and analyze lessons learned from past experiences. In addition, the workshop noted that the data gathered from different CS projects on IAS are fragmented. It highlighted the need for using an open and accessible platform to upload data originating from CS sources or to mirror validated data into a single, easy-to-use web service, in line with the EU Open Science Strategic Priority. The workshop provided ten key recommendations of best practices for CS projects on IAS, addressed to researchers, policy makers and implementing authorities, indicating future research and policy directions and opportunities.