Arming the Pacific region against pests and disease

It is reported that networks developed through the ACIAR Pacific Plant Biosecurity Partnership programme continue to help strengthen capacity in the prevention of the spread of pests and disease in crops throughout the Pacific region, despite COVID-19 disrupting the programme. Participants from 9 Pacific countries have developed their skills, networks and capacity to facilitate trade and prevent the spread of disease. Relationships and resources created through the programme continue to provide support for information-sharing around plant pests and diseases.

European Innovation Partnership – Plant Health

Between 2018 and 2021, in Pays de la Loire region (north-west of France), a network of regional partners from different plant sectors worked together within the European Innovation Partnership (EIP) "Plant Health” project, with the support of the Pays de la Loire Region Council and the European Commission. In total, nine thematic operational groups, associating producers, economic actors and R&D actors have worked, based on case studies, to identify new measures to improve plant health and validate their feasibility. Main themes addressed alternatives to plant protection products, with a focus on bridges between sectors (Is a solution or technique available in one sector easily transferable to another?), soil cover for weed management (Are mulching and direct seeding in a cover crop new practices to be mobilized?), and diversification of crop rotation and structuring of supply chains, with both technical questions (mastering a new crop, sorting out associations) and structural questions (which organizations, relationships between actors, etc.). After 4 years of work and despite the COVID-19 sanitary crisis, which slowed down some parts of the project, each operational group has been able to draw conclusions from the results obtained. © 2022 International Society for Horticultural Science. All rights reserved.

Seasonal space use and habitat selection in magpie geese: implications for reducing human‐wildlife conflicts

Negative interactions between waterbirds and people are increasing. Waterbirds feeding on agricultural crops cause significant losses to farmers worldwide, but so far most research to address these conflicts has been conducted on migratory species in the temperate northern hemisphere. We investigated the space use and habitat selection of the magpie goose (Anseranas semipalmata), a taxonomically distinct waterbird endemic to Australia and southern Papua New Guinea. In tropical northern Australia, magpie geese are protected but are increasingly persecuted by farmers to protect crops during the late dry–early wet season (~Sep–Jan), a bottleneck of natural resources for waterbirds in the monsoonal tropics. Using satellite telemetry of 38 geese spread across 3 seasons (2016–2017, 2017–2018, 2018–2019), we evaluated daily and seasonal space use, individual site fidelity, and habitat selection to determine the extent of use of agricultural fields by geese, and the spatiotemporal scales at which management should be undertaken. Geese used relatively small daily areas (x̄ = 8.2 km2) consistently throughout the late dry–early wet season, and repeatedly used agricultural fields, forested bushlands, and local wetlands. Geese used comparatively large seasonal areas (x̄ = 219.5 km2) encompassing several agricultural areas, and had a low mean overlap between successive weekly core activity areas, indicating that site fidelity rapidly weakened over time. These results suggest that farm‐scale (<30 ha) management of geese is unlikely to be effective because hazed individuals are likely to be replaced soon afterwards. Instead, our findings suggest that goose management should be coordinated strategically at the local (~1,000 ha), or regional (~100,000 ha) scale. Farm‐level management would likely be more effective if implemented in conjunction with the creation of regional sanctuaries where geese could rest and potentially feed undisturbed away from farms. Our findings can be used by wildlife managers for optimizing the location of such sanctuaries and highlight the necessity for management to be adaptive given the opportunistic nature of the species. [ FROM AUTHOR] Copyright of Journal of Wildlife Management is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Proposal for a Crop Protection Information System for Rural Farmers in Tanzania

Crop protection information, such as how to control emergent and outbreak crop diseases and pests, as well as the latest research, regulations, and quality control measures for pesticides and fertilizers, is important to farmers. Rural smallholder farmers in Tanzania have traditionally relied on government agricultural officers who visit them in their villages to provide this crop protection information. However, these officers are few and cannot reach all the farmers on time. This means that farmers fail to make critical farming decisions on time, which can lead to low crop productivity. In this study, we aim to provide farmers with reliable and instant crop protection information by developing a system based on the Short Message Service (SMS) and the Web. This system automatically replies to farmers’ requests for the latest crop protection information in the Swahili language through SMS on a mobile phone or a Web system. The findings reveal that our proposed system can provide farmers with crop protection information at lower cost (500 times cheaper) than the existing Tigo Kilimo system. Furthermore, our proposed system’s deep learning model is effective in understanding and processing Swahili natural language SMS queries for crop protection information with an accuracy of 96.43%. This crop protection information will help farmers make better critical farming decisions on time and improve crop productivity.