4.1 Article

Local spread of an exotic invader: using remote sensing and spatial analysis to document proliferation of the invasive Asian chestnut gall wasp

Journal

IFOREST-BIOGEOSCIENCES AND FORESTRY
Volume 5, Issue -, Pages 255-261

Publisher

SISEF-SOC ITALIANA SELVICOLTURA ECOL FORESTALE
DOI: 10.3832/ifor0633-005

Keywords

Dryocosmus Kuriphilus; Cynipidae; Remote Sensing; GIS; Spatial Analysis

Categories

Funding

  1. Italian Fulbright Commission
  2. Northern Nut Grower's Association
  3. American Chestnut Foundation
  4. USDA Forest Service
  5. Kentucky Agricultural Experiment Station
  6. Experiment Station Project [12-08-032]

Ask authors/readers for more resources

Remote sensing and spatial analysis represent useful tools for modeling species' dispersal, characterizing the spread of invasions and the invasability of a region, and thus allowing more accurate predictions for developing mitigation strategies. American chestnut, Castanea dentata, was historically a dominant forest species in North America, but occurs only sporadically today after its functional elimination by an exotic fungal pathogen in the early 1900's. In recent decades Castanea resources have increased due to restoration efforts, commercial chestnut plantations, and horticultural uses. This resurgence is threatened by an additional exotic species, the globally invasive Asian chestnut gall wasp, Dryocosmus kuriphilus. The gall wasp was first discovered in Lexington, Kentucky (USA) in 2010. We used remotely sensed data and Geographic Information Systems to describe the local distribution of the Castanea hosts, and the occurrence and dispersal of the gall wasp. We tested the hypotheses that geomorphology, Castanea occurrence, and prevailing winds influence local proliferation. We found that gall wasp spread may be attributable to host plant distribution and to the effects of prevailing winds occurring during a brief period of adult insect emergence, and is influenced by topography. Our results suggest that weather data and topographic features can be used to delineate currently infested areas and predict future gall wasp infestations.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.1
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available