Phenological Mapping of Invasive Insects: Decision Support for Surveillance and Management

Author:

Barker Brittany S.12ORCID,Coop Leonard12

Affiliation:

1. Oregon Integrated Pest Management Center, Oregon State University, 4575 Research Way, Corvallis, OR 97333, USA

2. Department of Horticulture, Oregon State University, 4017 Agriculture and Life Sciences Building, Corvallis, OR 97333, USA

Abstract

Readily accessible and easily understood forecasts of the phenology of invasive insects have the potential to support and improve strategic and tactical decisions for insect surveillance and management. However, most phenological modeling tools developed to date are site-based, meaning that they use data from a weather station to produce forecasts for that single site. Spatial forecasts of phenology, or phenological maps, are more useful for decision-making at area-wide scales, such as counties, states, or entire nations. In this review, we provide a brief history on the development of phenological mapping technologies with a focus on degree-day models and their use as decision support tools for invasive insect species. We compare three different types of phenological maps and provide examples using outputs of web-based platforms that are presently available for real-time mapping of invasive insects for the contiguous United States. Next, we summarize sources of climate data available for real-time mapping, applications of phenological maps, strategies for balancing model complexity and simplicity, data sources and methods for validating spatial phenology models, and potential sources of model error and uncertainty. Lastly, we make suggestions for future research that may improve the quality and utility of phenological maps for invasive insects.

Funder

U.S. Army Corps of Engineers

USDA National Institute of Food and Agriculture

USDA NIFA Crop Protection and Pest Management Extension Implementation Program

USDA APHIS PPQ CAPS

Publisher

MDPI AG

Subject

Insect Science

Reference135 articles.

1. Cardwell, K.F., and Bailey, K.L. (2022). Tactical Sciences for Biosecurity of Animal and Plant Systems, IGI Global.

2. The early detection of and rapid response (EDRR) to invasive species: A conceptual framework and federal capacities assessment;Reaser;Biol. Invasions,2020

3. Vänninen, I. (2022). Advances in Insect Pest and Disease Monitoring and Forecasting in Horticulture, Burleigh Dodds Science Publishing.

4. Degree-days: An aid in crop and pest management;Wilson;Calif. Agric.,1983

5. Krischik, V., and Davidson, J. (2004). IPM (Integrated Pest Management) of Midwest Landscapes, Minnesota Agricultural Experiment Station Publication SB-07645, Minnesota Agricultural Experiment Station.

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3