2013 Annual Report
1a.Objectives (from AD-416):
Develop ecological niche models using existing and unpublished data on apple maggot and western cherry fruit fly for prediction of potential of the establishment and spread of these pests in tropical countries importing tree fruits from the Pacific Northwest.
Develop databases and predictive maps on the climate of the importing countries and range of suitable hosts for apple maggot and western cherry fruit fly as well as development of databases and predictive maps for areas where these pests are normally found in the U.S. The databases will be used in ecological niche modeling programs to determine:.
1)the potential for establishment and spread of these pests in importing countries; and.
2)identification of researchable data gaps that may be needed to improve the accuracy of the models and may be used in the development of risk assessments.
1b.Approach (from AD-416):
Ecological niche models, which are based on the relationships between organisms and features of the environment, are increasingly being used to model and map native and invasive species distributions. Combining statistical algorithms with a geographic information system (GIS), ecological niche models attempt to predict probability of occurrence of a species by using presence-only or presence-absence data in combination with environmental variables. These models are based on Hutchinson’s classical niche concept: the distributions of species are constrained by biotic and abiotic gradients (e.g. elevation, temperature and precipitation) and species interactions (e.g., competition and predation). Although ecological niche models have become popular tools for invasive species ecology, they are also increasingly being used for rare and endangered species, defining conservation priority areas, phylogeographic studies, and the potential impacts of climate change However; their potential use in pest risk assessment is not yet fully explored with the exception of a few studies. These techniques therefore have the potential to advance pest risk assessment.
We will use maximum entropy model or Maxent which is a presence-only method. Our choice of presence-only method is best suited to the proposed research because absence data for the species are not available or are unreliable as they may be in the early stages of invasion. Recent studies on distribution modeling of insect pests in different parts of the world have demonstrated the effectiveness of the Maxent model. Maxent is a general purpose, machine learning, non-parametric, predictive model that uses presence-only data. This method estimates the probability distribution of a species by finding the probability distribution of maximum entropy, which is a probability that is closest to uniform. It automatically includes variables interactions and can handle continuous and categorical predictor variables. It uses a set of features (e.g., linear, quadratic, product, threshold and hinge) which are functions of environmental variables that constrain the geographical distribution of a species. It uses a regularization parameter, which is determined empirically, to control model overfitting. Maxent generates an estimate of probability of presence of the species that varies from 0 (lowest probability) to 1 (highest probability). Maxent has consistently fared well in model comparison studies.
Model evaluation and validation: We will evaluate model performance using a number of threshold-dependent and threshold-independent metrics to allow for better overall evaluation (Lobo et al. 2008). Threshold-dependent metrics will include Cohen’s Kappa, sensitivity, specificity, percent correct classification, odds ratio, and true skill statistic or TSS. The threshold-independent evaluation measure will include Area Under the receiver operating characteristic (ROC) Curve, or AUC. Wherever possible we will validate our models using an independent data set. However, in case of unavailability of independent validation data we will use “split sample approach”, to create a quasi-independent dataset for model validations.
The work summarized in this Progress Report relates to objective number 1 of the Project Plan for 001-00D: 1. Develop new knowledge of the behavior, genetics, systematic, physiology, ecology, and biochemistry of the insect pests of apple, pear, and cherry, and their natural enemies, that will aid in the discovery, development, and application of management methods and technologies.
The overall goal of the project is to develop mathematical models called ecological niche models to predict the potential of the establishment and spread of these pests in tropical countries importing tree fruits from the Pacific Northwest. This work will aid tree fruit growers to maintain and expand export markets where temperate fruit flies are a quarantine concern. To achieve this goal we address the following technical objectives: (1) identification of the potential of temperate fruit flies of tree fruits to become established and spread in tropical countries that import tree fruits, and (2) identification of critical parameters that would affect the potential of these species to establish and spread in tropical climates and any gaps in the knowledge that are researchable to improve the establishment of new pest risk analyses for use in trade negotiations. During this year we used experimental data obtained from projects 5352-22430-001-22S and 5352-22430-001-21S in which we determined the upper and lower temperature limits of apple maggots and western cherry fruit. These data are critical to accurately develop the ecological niche models for determination of potential of these pests to establish and spread in countries importing sweet cherries and apples from the U.S. We obtained global positioning coordinates and climatic data of commercial apple orchards in China for use in improving the accuracy of the apple maggot models from a collaborator in China. This type of data was not previously available, and its use in the models increased the accuracy of the predictive ecological niche models for apple maggot in Asia. We developed four models describing the distribution of suitable habitat for western cherry fruit fly for western North America and used these models to predict the likelihood of this pest to establish and spread in countries importing sweet cherries and apples (Australia, China, India, Indonesia, Pakistan, Taiwan, and Thailand). This model is being used by the tree fruit industry and USDA-APHIS to negotiate revised and new export requirements for apples and cherries to these and other countries. We developed an enhanced pest risk analysis model by using both the @Risk and the Maxent and CLIMEX programs based on climatic parameters that are critical to fruit fly establishment and spread. This enhanced pest risk program incorporated biological and ecological information to improve the development of risk analyses and facilitates trade of agricultural products where insect pests pose a measurable risk.