Recipient Organization
LAND INSTITUTE, THE
2440 E WATER WELL RD
SALINA,KS 674019051
Performing Department
(N/A)
Non Technical Summary
This project aligns best with program 3, particularly 3a, b and e. Despite the implementation of Best Management Practices (BMPs) and Grower Opportunity Zones (GOZs), Adventitious Presence (AP) is occurring and negatively impacting the coexistence of alfalfa markets. Feral populations present an additional challenge in alfalfa because they can act as bridges and refuges for GE genes. The Glyphosate Resistance (GR) gene has been detected in many alfalfa feral populations but little information exists on its frequency (J-101 and J-163 events) and on its impact on the pollinators, pests and diseases, life history characteristics and potential for invasiveness of these populations. Filling these knowledge gaps is the overall goal of this proposal. We will (1) expand the geographical survey of feral populations and estimate the change in frequency of the GR gene in feral populations; (2) quantify the impact of the GR gene on pollinators, pests and disease and on life history parameters of feral alfalfa, and (3) parameterize a population matrix model for GR and non-GR alfalfa. To reach these goals, we will (1) revisit previously visited feral populations (CA, ID, WA) and expand the search in these and other states (WY, MT, KS and WI); test for the presence of the GR gene and perform PCR and qPCR to obtain the frequency of the J-101 and J-163 events; (2) compare pollinators, pests and disease and life history parameters and (3) develop population matrix models to quantify the potential for invasiveness, between GR status and across regions.
Animal Health Component
0%
Research Effort Categories
Basic
100%
Applied
0%
Developmental
0%
Goals / Objectives
Objective 1. Extend the survey of feral populations for the GR gene to a larger geographical scale and estimate the frequency and change in incidence of the GR gene in feral populationsObjective 2. Quantify the impact of the GR gene on pollinators, pests and disease and on life history parameters of feral alfalfa.Objective 3. Parameterize a population matrix model for GR and non-GR alfalfa.
Project Methods
Objective 1. Extend the survey of feral populations for the GR gene to a larger geographical scale and estimate the frequency and change in incidence of the GR gene in feral populations.The following tasks remain to be completed to achieve the goals of this research objective.Sample processing: Leaf samples from populations from Wyoming, Utah, Idaho and Colorado need to be processed to determine the frequency and change incidence of individuals carrying the gene in each GR population in these western US states.Genotyping: A sample of ~ 65 feral alfalfa populations that represent each state/county surveyed will be genotyped using genotyping-by-sequencing.Selection Signatures: The genotyping data will then be used to search the feral alfalfa genomes for selection signatures when compared to cultivated alfalfa that signal escape and adaptation to non-agricultural habitats.Hypothesis Testing. Once all data collection and generation is completed, we will conduct data analyses that test the following hypotheses:Hypothesis 1: The GR gene in feral populations will be at Hardy-Weinberg equilibrium. Reasoning: As a null hypothesis, in the absence of selection, drift or recurrent gene flow, we expect the GR gene to be at Hardy-Weinberg equilibrium.Hypothesis 2: The population genetic structure of feral populations will be uniform within a county but differ among counties with different management regimes.Research Dissemination: A peer-reviewed manuscript will be prepared that presents the the GR multi-state survey data, results of hypothesis testing, and provides interpretation about the potential implications plant breeding and seed production methods of outcrossing, perennial, insect pollinated crop plants using alfalfa as a gene flow model.Objective 2. Quantify the impact of the GR gene on pollinators, pests and disease and on life history parameters of feral alfalfa.The following tasks remain to be completed to achieve the goals of this research objective.Data compilation and Analysis: Disease, pest, life history, and pollinator data were collected for populations in KS, WI, CA, and WA in 2021-2022. These data needed to be compiled into a single repository that is ready for subsequent analysis and hypothesis testing.Hypothesis Testing. Once all data collection and generation is completed, we will conduct data analyses that test the following hypotheses:Hypothesis 3: GR and non-GR feral alfalfa will have similar pollinators, pest and disease and similar reproductive traits.Hypothesis 4: The pollinators, pest and disease and reproductive traits of feral alfalfa will vary among regions.Hypothesis 5: Survival of non-GR alfalfa plants will be less than GR alfalfa plants in areas where glyphosate is frequently used as an herbicide.Research dissemination: Multiple peer-reviewed manuscripts will be prepared that present the impact of the GR gene on pollinators, pests and disease and on life history parameters of feral alfalfa. Insights from this research could inform the ecological and agricultural management of GR and feral alfalfa.Objective 3. Parameterize a population matrix model for GR and non-GR alfalfa.Hypothesis 6: In counties where Roundup is commonly used as an herbicide, the GR plants will have greater λ relative to the group of non-GR plants.To test this hypothesis, we plan to parameterize a population matrix model. The goal is to obtain a separate model for the group of GR and the group of non-GR plants within each of the four populations (KS and WI) where life history parameters were collected. We expect that the population growth rate (λ) will differ among regions but not between GR and non-GR plants. Instead, we predict the seedling stage will be the most vulnerable stage to disturbance (e.g. round-up herbicide application) and that we will see demographic shifts in GR and non-GR plant frequencies within populations as plant size increases.?The following tasks remain to be completed to achieve the goals of this research objective.Data compilation and classification: We need to compile the WI and KS data into a single repository. Once compiled, we will apply metrics to determine the plant size classes and quantify the reproduction of the different size classes in each population. With this data, we can calculate the transition probabilities for the different size classes.Model parameterization: Using the compiled data we can parameterize and run the population matrix models to determine the population growth rate of populations and examine the stages that most affect population growth. Once parameterized, we can use these models to compare the populations and search for geographic and/or management activities that affect the feral population growth metrics.Research dissemination: At least one peer-reviewed publication will be prepared that presents the feral alfalfa population matrix modeling. Insights from this research could inform the ecological and agricultural management of GR and feral alfalfa. We expect to see regional differences in pollinator performance and GR population demography when comparing alfalfa seed vs. hay producing regions. Ultimately, this manuscript will summarize the findings from the three research objectives and highlight the observed biological risks identified in this assessment of GR presence in feral alfalfa populations.