The livestock industry is the largest consumer of antibiotics worldwide. Antimicrobial resistant bacteria generated by this industry are introduced directly into the soil where we grow much of our food. Agricultural best management practices must be examined closely to identify those that may be improved upon in order to minimize impact on the evolution and spread of antimicrobial resistance. Monitoring for antibiotic resistance genes in the soil and water associated with agroecosystems can provide information regarding the impact these practices have on the spread of antibiotic resistance. The various methods of detection used for monitoring ARGs involve tradeoffs in sensitivity, diversity of targets, and throughput. The appropriate method used for monitoring ARGs in the environment is dependent on the scope of the experiment, and often multiple approaches are necessary to develop a comprehensive understanding of the complex processes involved in ARG dissemination in the environment. The experiments described in this dissertation leverage model systems simulating artificially drained crop soil along with a combination of methods used to monitor ARGs including shotgun metagenomic sequencing, MF-qPCR, and culture-based methods to assess the impact of various agricultural practices on the resistomes of agricultural soil and water. We found that the majority of the ARGs resulting from fertilization of crop soil with swine or beef cattle manure was not distinguishable from background by the end of our simulated growing seasons. However, those that did persist through the end of our studies were associated with mobile genetic elements that enhance the potential for those ARGs to transfer between members of a bacterial community. Additionally, we determined that swine and beef manure associated ARGs are transferred through the soil and into drainage water very differently.