4.7 Article

Spatiotemporal patterns of forest damage and disturbance in the northeastern United States: 2000-2016

期刊

FOREST ECOLOGY AND MANAGEMENT
卷 430, 期 -, 页码 94-104

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.foreco.2018.07.047

关键词

Aerial detection surveys; Ecosystem services; Forest health; Tree mortality; Insects and disease; Disturbance

类别

资金

  1. Forest Ecosystem Management Cooperative
  2. USDA Forest Service's Northeastern States Research Cooperative

向作者/读者索取更多资源

Forest damage and disturbance can have significant influences on tree vigor, species composition, biodiversity, and associated ecosystem services. Recognizing the importance of monitoring spatiotemporal patterns of forest health, federal and state agencies in the United States (US) have conducted aerial insect and disease surveys (IDS) annually to quantify the extent of forest damage by type and causal agent. Although agencies have collected these geospatial data for decades, long-term trends and patterns have not been synthesized across the predominantly forested region of northern New England and New York. Here, we utilized a novel, online forest damage and disturbance mapping portal, the Northeastern Forest Health Atlas, to investigate inter-annual and long-term patterns (2000-2016). Our analysis indicated that similar to 11.0 million ha of forestland (10% of the study region) experienced at least one damage event (i.e., an IDS polygon) over the 17-year period, averaging 647,425 +/- 215,482 ha (3.4 +/- 1.1% of the region's forestland) annually. While there were no detectable linear, long-term trends in annual extent or relative abundance of damage by agent category, we found that some ecoregions experienced relatively higher damage rates (e.g., Acadian Plains and Hills, Atlantic Coastal Pine Barrens). Across the region, insects were the most extensive damage agent category mapped (similar to 8 million ha), with a relatively small number of invasive insects (19 species) accounting for half of this damage. Because climate change may alter the type, severity, and frequency of forest disturbance, quantifying baseline patterns of forest damage is critical for detecting shifts in forest dynamics and developing adaptive management strategies.

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