Progress 07/01/24 to 06/30/25
Outputs Target Audience:During this reporting period our target audience has been the members of our Advisory Board, as well as the Director and technical staff of the Knipling-Bushland US Livestock Insect Research Laboratory. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Training webinars for artificial intelligence, spatial and computational modeling tools. Interactions with state and federal regulatory and research professionals working on numerous cattle fever tick issues. How have the results been disseminated to communities of interest?To date, our results have been shared within our community of project participants including our Advisory Board members and ARS research personnel. What do you plan to do during the next reporting period to accomplish the goals?Obj. 1: Integrate validated data layers via data fusion approaches. Obj. 2: Develop Species Distribution Models based on current and future climates. Obj. 3: Integrate trace-out data, the United States Animal Movement Model (USAMM) and SDMs, and develop ABIPMs. Obj. 4: Begin integration of fused CFT-related datasets into the CFTEPTs platform, and development of training tutorial.
Impacts What was accomplished under these goals?
Activities in FY2024 Obj. 1. Collected essential data sets and improved dataset validation and integration techniques through data fusion Data collection and initial processing To develop SDMs: We received historical cattle fever tick data maps derived from a publication of John L. Wilbur for TAHC (Texas Animal Health Commission) from USDA-ARS, Knipling-Bushland US Livestock Insects Research Lab. We downloaded both BIOCLIM data for 1970 - 2000 from WorldClim version 2.1 (https://www.worldclim.org/data/worldclim21.html) at the spatial resolution of 2.5 arc-minutes (~25 km2). We downloaded Elevation data from the Shuttle Radar Topography Mission (SRTM; https://www2.jpl.nasa.gov/srtm/). We downloaded Land Use / Land Cover (LULC) data from the EarthExplorer (https://earthexplorer.usgs.gov/). We also set the above data layers as Geographic Coordinate System as WGS 1984 (EPSG 4326) using ArcGIS Pro. We collected 2,241 nilgai (Boselaphus tragocamelus) locality data from Global Biodiversity Information Facility (GBIF; https://www.gbif.org/). We processed the data by removing those occurrences that were duplicates, with errors, or with no GPS coordinates. This resulted in 817 (36.45%) occurrences being removed. Leaving a total of 1,424 (63.55%) occurrences including 360 (25.26%) in Texas, 2 (0.14%) in Mexico, 1,010 (70.88%) in India, and 52 (3.65%) in Nepal. We had an in-person visit at USDA-ARS, Knipling-Bushland US Livestock Insects Research Lab, Kerrville, TX on November 8, 2024, to understand the CFTEP data collection history, data properties, data type, data availability, and limitation of data usage. We received various types of data related to CFTEP from USDA-ARS, Knipling-Bushland US Livestock Insects Research Laboratory. To develop ABIPMs,we developed a first-stage model: (1) whose purpose was to simulate the population dynamics of cattle fever ticks in response to trends and fluctuations in major environmental variables, (2) that had produced acceptable estimates of fluctuations in both off- and on-host tick densities under a wide range of environmental conditions, and (3) whose context included a wide geographical range, a wide range of non-catastrophic environmental changes, and situations in which cattle were the primary host before integrating all proposed components into the ABIPMs. Dataset validation An Access file containing inspection records from Form 722s and G-cards from 1976 to 2014 was designed to be a complete capture of quarantines to be used in the analysis of infestation trends. However, it was focused on Zapata County for data collection prior to 2014 due to the accessibility of impeccable record keeping at that time. However, there is some missing information. We are working on filling the gaps (missing information) through the "Excel workbook." The Zapata County CFT quarantine history is quite relevant to our project as it involves both cattle and white-tailed deer in an area that has experienced changes in land use, ownership, and property size consistent with broad changes in land trends in Texas. An Excel workbook documenting telephone report data for infested premises from 2006 to present contains 1,607 data entries. Based on the difference of data arrangement methods among these files, we are finding the commonalities and will propose a generic arrangement for USDA-ARS Knipling-Bushland US Livestock Insects Research Lab and each county office. Polygon quarantine files (.shp files) have been checked individually. Obj. 2. Refine SDM and design methods to analyze collected CFT-related data. 2.1. Refine SDM (Species Distribution Model) SDMs can project potential geographic ranges of cattle fever ticks. To achieve this goal, we identified the R-package "biomod 2" which contains algorithms for SDM development, calibration, and evaluation, ensemble of SDMs, and ESDM forecasting and visualization. The twelve SDM algorithms in "biomod 2" include artificial neural network (ANN), classification tree analysis (CTA), flexible discriminant analysis (FDA), generalized additive model (GAM), gradient boosting model (GBM), generalized linear model (GLM), multiple adaptive regression splines (MARS), maximum entropy (MAXENT), random forest (RF), random forest down-sampled (RFd), surface range envelop (SRE), and eXtreme gradient boosting training (XGBOOST). As soon as we collect enough cattle fever tick locality data, we will conduct SDM development using all algorithms. 2.2. Method design Based on the data from the "Access file containing inspection records from Form 722s and G-cards from 1976 to 2014," we plan to use a statistical method, logistic regression, and a combined method of statistics and machine learning, boosted regression tree, to analyze the factors affecting whether the premises could be infested or not using (1) all data and (2) data in Zapata county only. Based on the data from the "Excel workbook documentation of telephone report data for infested premises from 2006 to present," we plan to use descriptive statistics to analyze (1) the infestation trend from 2006 to now and (2) understand the commonalities among all infested premises. If we find a clear trend and common properties of infestation, we will use a statistical method, multinomial logit regression, and a combined method of statistics and machine learning, boosted regression tree, to quantify the factors affecting the recursion of cattle fever ticks. We developed a stage-structured model that simulates tick population dynamics in response to the effects of climate, landscape, and cattle density, and produces estimates of fluctuations in off- and on-host tick densities using STELLA Professional® (ISSE Systems, inc.). We calibrated the model to represent conditions in Brownsville and Corpus Christi, Texas, USA. The model was developed following the life cycle of cattle fever ticks. Obj. 4: Get familiar with the CFTEPTs platform We had an in-person visit at USDA-ARS, Knipling-Bushland US Livestock Insects Research Lab, Kerrville, TX on November 8, 2024 to look at the practice of CFTEPTs and understand its use, its functions and relationships to the CFT program, as well as follow up email correspondence. The current CFTEPTs platform includes four major functions: CFTEP Editor Interface Web Maps, CFTEP Field Maps, CFTEP Web Map Viewer: Current Quarantines, and CFTEP Dashboards.
Publications
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