Opportunities for Improving Livestock Production with e-Management Systems

There is increased interest in hardware and software that can support e-Management for grassland-based livestock industries. Managers of grazing livestock were early adopters of radio frequency identification (RFID) technologies automatically monitoring individual animal performance. Recent developments of remote sensing, automated individual recording and management, location based systems, improved data transfer and technologies that can be used in more extensive grazing systems are providing new opportunities for the development of e-Management systems. There is a need for better data integration and systems that can provide the best available information to enable better decision-making. For greater industry adoption of more integrated e-Management systems, there needs to be a clear economic value. With increased on farm monitoring and the expansion of digital data sources, grazing livestock production systems have the opportunity to expand production efficiency through the implementation of e-Management

Monitoring Animal Behaviour and Environmental Interactions Using Wireless Sensor Networks, GPS Collars and Satellite Remote Sensing

Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle

Ground-Based Optical Measurements at European Flux Sites: A Review of Methods, Instruments and Current Controversies

This paper reviews the currently available optical sensors, their limitations and opportunities for deployment at Eddy Covariance (EC) sites in Europe. This review is based on the results obtained from an online survey designed and disseminated by the Co-cooperation in Science and Technology (COST) Action ESO903—“Spectral Sampling Tools for Vegetation Biophysical Parameters and Flux Measurements in Europe” that provided a complete view on spectral sampling activities carried out within the different research teams in European countries. The results have highlighted that a wide variety of optical sensors are in use at flux sites across Europe, and responses further demonstrated that users were not always fully aware of the key issues underpinning repeatability and the reproducibility of their spectral measurements. The key findings of this survey point towards the need for greater awareness of the need for standardisation and development of a common protocol of optical sampling at the European EC sites

Spatio-temporal analysis of net primary production across Ontario using an ecoregionalization

grantor: University of TorontoIndicators of general ecosystem functioning are important in understanding and managing natural resources. A synthesis of factors affecting the state of an ecosystem is vegetation, where composition and productivity, and their extent and spatial pattern, reflect a combination of geo-climatic, ecological, and anthropogenic factors, as well as ecological function such as succession and competition. Net primary production (NPP), predicted at medium resolution (8km) over large areas and many years, is a potential measure of the magnitude of vegetation productivity. To generate landscape NPP across Ontario, a methodology is developed using the relationship between the amount of incident photosynthetically active solar radiation (PAR), the fraction that is absorbed (derived from the remotely sensed Normalized Difference Vegetation Index (NDVI)), and the light use efficiency (LUE) of the ecosystem at utilising this energy. Landscape-level predictions of LUE are calculated using a relationship between long-term climate normals, which characterise the spatial variability between ecosystems, and monthly climate data, which capture the seasonal variability within an ecosystem. Photosynthetically active radiation is generated across Ontario, and it is shown that the commonly used Geostationary Operational Environmental Satellite dataset over-predicts solar radiation across the province. This methodology is used to generate sixteen years (1981 to 1996) of monthly NPP, which are explored for trends using aggregation ecounits from the National Ecological Framework of Canada ecoregionalization. Across Ontario these results show increases in both seasonal and annual NDVI and NPP, although increases in NPP are not distributed evenly across the growing season. These results support other reported evidence for changing climatic conditions. Summary statistics of both NDVI and NPP characterise differences between ecounits. NDVI is used to develop spatio-temporal signatures, which summarise the seasonal structure of climate and NDVI within each ecounit. The suitability of the ecoregionalization for exploring NPP is also assessed, by examining both the internal homogeneity of ecounits and the strength of the ecounit boundaries. Bridging the gap between local and global studies, this research provides a useful methodology to generate a multi-year series of 8km NPP, and analysis techniques for the spatio-temporal exploration of this series using an ecoregionalization.Ph.D

Spatio-Temporal Analysis Using a Multiscale Hierarchical Ecoregionalization

We address the need for spatio-temporally explicit analysis techniques linking the scales of ecosystem, observation, and analysis, using a hierarchical ecoregionalization to examine remotely sensed data at spatial scales of ecological and management significance. Long- and short-term changes in vegetation functioning are a key indicator of ecological processes. We predict net primary production (NPP) at monthly temporal resolution for 16 years (1981–1996) at an 8-km spatial resolution for the approximately 10 6 km 2 area of Ontario, Canada. We calculate landscape-level light use efficiency values that are tuned to monthly and long-term ecoclimates, and the Normalized Difference Vegetation Index from the NOAA-AVHRR sensor. Applying our spatio-temporal analysis tools, we show evidence for increasing NPP across most of the province. This increase varies seasonally and annually across Ontario, and its magnitude and distribution varies with the spatial scales of analysis. Bridging the gap between local and global studies, this research supports spatio-temporal monitoring and analysis of ecosystem functions

Open Access Research Outputs Receive More Diverse Citations

The goal of open access is to allow more people to read and use research outputs. An observed association between highly cited research outputs and open access has been claimed as evidence of increased usage of the research, but this remains controversial.1,2 A higher citation count also does not necessarily imply wider usage such as citations by authors from more places.3,4,5 A knowledge gap exists in our understanding of who gets to use open access research outputs and where users are located. Here we address this gap by examining the association between an output’s open access status and the diversity of research outputs that cite it. By analysing large-scale bibliographic data from 2010 to 2019, we found a robust association between open access and increased diversity of citation sources by institutions, countries, subregions, regions, and fields of research, across outputs with both high and medium-low citation counts. Open access through disciplinary or institutional repositories showed a stronger effect than open access via publisher platforms. This study adds a new perspective to our understanding of how citations can be used to explore the effects of open access. It also provides new evidence at global scale of the benefits of open access as a mechanism for widening the use of research and increasing the diversity of the communities that benefit from it

Universities as Open Knowledge Institutions: Sharing vital research

Universities are key creators of knowledge. Ensuring that research outputs are not inaccessible behind paywalls, and that research data can be interrogated and built upon is central to efforts to improve the effectiveness of global research landscapes. Mandating and promoting open science and open access (OA) for published research outputs and sharing research data are important elements of building a vibrant open knowledge system, but there are additional benefits. Supporting diversity within knowledge-making institutions; enabling collaboration between universities and communities; addressing inequalities in access to knowledge resources and opportunities for contributing to knowledge making are also important. New tools are needed to help universities, funders and communities understand the extent to which a university is operating as an effective open knowledge institution; as well as the steps that might be taken to improve open knowledge performance. The spread of the COVID-19 pandemic has demonstrated the vital need for open research and knowledge to help find a global solution. The Curtin Open Knowledge Initiative (COKI) is a Curtin University funded strategic research project exploring ways of understanding and assessing institutional progress towards knowledge openness through analysis of research output, diversity data, policies and outcomes, and access to knowledge resources including libraries. This paper discusses the COKI team’s multidimensional approach to assessing institutional knowledge openness beyond, but including, measures of OA, open science and open data. The COKI dataset of more than 12 trillion items enables exploration and analysis of many questions around publication, impact, research performance, university engagement, diversity and access to knowledge. This information can assist universities, libraries, funders and communities to understand and enhance institutional open knowledge performance and contributions

Data Onboarding Background: Book Analytics Dashboard (BAD) Demonstration Project (2022-2025)

This document provides background information to the data onboarding process for the Book Analytics Dashboard (BAD) Demonstration project. The purpose of the data onboarding process is to gather technical and access information about the sources of a project partner’s book usage data so that we can import this data into the BAD system. A companion to this Data Onboarding Background’ document is the ‘Data Onboarding Questionnaire’ – which is a read-only version of the questionnaire that partners will be sent directly. The Book Analytics Dashboard Project (2022-2025) is focused on creating a sustainable OA Book focused analytics service. This service is needed to safeguard and support diversity in the voices, perspectives, geographies, topics and languages made visible through OA Books. Funded by the Mellon Foundation, the Book Analytics Dashboard project is building on an earlier Mellon-funded initiative: Developing a Pilot Data Trust for OA eBook Usage (2020 – 2022). In addition to scaling workflows, infrastructure and customer support, the Demonstration Project is developing a long-term plan for housing, maintenance and funding of the analytics service as a sustainable community infrastructure. More Information Visit the BAD project website Follow the BAD project on Twitter @BookAnalytics Join the BAD project mailing list Visit the BAD project Zenodo community See the BAD dashboard for University of Michigan Press Our book-focussed GitHub repository Our technical documentation on Read the Docs Email BAD [email protected] work was made possible through grant funding provided via the "OA Book Usage Analytics for Diverse Communities – A Demonstration Project" project funded by the Mellon Foundation and COARD