8 research outputs found

    The role of citizen science in addressing grand challenges in food and agriculture research

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    The power of citizen science to contribute to both science and society is gaining increased recognition, particularly in physics and biology. Although there is a long history of public engagement in agriculture and food science, the term ‘citizen science’ has rarely been applied to these efforts. Similarly, in the emerging field of citizen science, most new citizen science projects do not focus on food or agriculture. Here, we convened thought leaders from a broad range of fields related to citizen science, agriculture, and food science to highlight key opportunities for bridging these overlapping yet disconnected communities/fields and identify ways to leverage their respective strengths. Specifically, we show that (i) citizen science projects are addressing many grand challenges facing our food systems, as outlined by the United States National Institute of Food and Agriculture, as well as broader Sustainable Development Goals set by the United Nations Development Programme, (ii) there exist emerging opportunities and unique challenges for citizen science in agriculture/food research, and (iii) the greatest opportunities for the development of citizen science projects in agriculture and food science will be gained by using the existing infrastructure and tools of Extension programmes and through the engagement of urban communities. Further, we argue there is no better time to foster greater collaboration between these fields given the trend of shrinking Extension programmes, the increasing need to apply innovative solutions to address rising demands on agricultural systems, and the exponential growth of the field of citizen science.This working group was partially funded from the NCSU Plant Sciences Initiative, College of Agriculture and Life Sciences ‘Big Ideas’ grant, National Science Foundation grant to R.R.D. (NSF no. 1319293), and a United States Department of Food and Agriculture-National Institute of Food and Agriculture grant to S.F.R., USDA-NIFA Post Doctoral Fellowships grant no. 2017-67012-26999.http://rspb.royalsocietypublishing.orghj2018Forestry and Agricultural Biotechnology Institute (FABI

    The integration of GPS, vegetation mapping and GIS in ecological and behavioural studies

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    Global Positioning System (GPS) satellite navigation receivers are increasingly being used in ecological and behavioural studies to track the movements of animals in relation to the environments in which they live and forage. Concurrent recording of the animal's foraging behaviour (e.g. from jaw movement recording) allows foraging locations to be determined. By combining the animal GPS movement and foraging data with habitat and vegetation maps using a Geographical Information System (GIS) it is possible to relate animal movement and foraging location to landscape and habitat features and vegetation types. This powerful approach is opening up new opportunities to study the spatial aspects of animal behaviour, especially foraging behaviour, with far greater precision and objectivity than before. Advances in GPS technology now mean that sub-metre precision systems can be used to track animals, extending the range of application of this technology from landscape and habitat scale to paddock and patch scale studies. As well as allowing ecological hypotheses to be empirically tested at the patch scale, the improvements in precision are also leading to the approach being increasing extended from large scale ecological studies to smaller (paddock) scale agricultural studies. The use of sub-metre systems brings both new scientific opportunities and new technological challenges. For example, fitting all of the animals in a group with sub-metre precision GPS receivers allows their relative inter-individual distances to be precisely calculated, and their relative orientations can be derived from data from a digital compass fitted to each receiver. These data, analyzed using GIS, could give new insights into the social behaviour of animals. However, the improvements in precision with which the animals are being tracked also needs equivalent improvements in the precision with which habitat and vegetation are mapped. This needs some degree of automation, as vegetation mapping at a fine spatial scale using the traditional manual approach is far too time consuming. This paper explores these issues, discussing new applications as well as approaches to overcoming some of the associated problems

    Error estimates and adaptive finite element methods

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