Undergraduate research experiences have been shown to increase engagement, improve learning outcomes, and enhance career development for students in ecology. However, these opportunities may not be accessible to all students, and incorporating inquiry-based research directly into undergraduate curricula may help overcome barriers to participation and improve representation and inclusion in the discipline. The shift to online instruction during the COVID-19 pandemic has imposed even greater challenges for providing students with authentic research experiences, but the pandemic may also provide a unique opportunity for creative projects conducted remotely. In this paper, I describe a course-based undergraduate research experience (CURE) designed for an upper-level ecology course at California State University, Dominguez Hills during remote learning. The primary focus of student-led research activities was to explore the potential impacts of the depopulation of campus during the pandemic on urban coyotes (Canis latrans), of which there were increased sightings reported during this time. Students conducted two research studies, including an evaluation of urban wildlife activity, behavior, and diversity using camera traps installed throughout campus and an analysis of coyote diet using data from scat dissections. Students used the data they generated and information from literature reviews, class discussions, and meetings with experts to develop a coyote monitoring and management plan for our campus and create posters to educate the public. Using campus as a living laboratory, I aimed to engage students in meaningful research while cultivating a sense of place, despite being online. Students’ research outcomes and responses to pre- and post-course surveys highlight the benefits of projects that are anchored in place-based education and emphasize the importance of ecological research for solving real-word problems. CUREs focused on local urban ecosystems may be a powerful way for instructors to activate ecological knowledge and capitalize on the cultural strengths of students at urban universities.

Camera trap data: In January 2021, camera traps (Bushnell Trophy Cam Trail Cameras; Bushnell Corporation, Overland Park, Kansas) were installed at nine locations throughout the CSUDH campus, including several cameras in the Heritage Creek Nature Preserve. These devices are motion-sensor cameras capable of capturing digital images in light and dark conditions when triggered by movement in the field of view, with images stored on removable SD memory cards. Cameras were set to the highest degree of detection sensitivity with a delay of 60 seconds between images once triggered. I downloaded data from each camera every 1-2 weeks and retained all images that contained wildlife observations. Images were uploaded to DropBox, and students reviewed and analyzed all images over the course of several weeks throughout the semester. For each image, students identified the species present using online resources (including iNaturalist) and recorded the date, location, and time. These data were compiled into a single spreadsheet for analysis. Students created graphs of the frequency of wildlife sightings (by species and for coyotes based on time of day) using statistical software (RStudio Cloud). In addition to quantitative data, students also interpreted individual images in regard to what ecological information we could gain (e.g., number of unique individuals, age, breeding, behavior, activity, and intra- and interspecific interactions).

Coyote scat data: To understand the different food sources utilized by coyotes on campus, students analyzed scat samples (n = 25) collected in and around Heritage Creek in January 2021. Prior to class, I collected fresh scat samples over a one-month period and stored samples in a freezer. Samples were dried in a drying oven (48 hours at 70° C) and cleaned and dissected by hand. I separated samples into different food sources including anthropogenic sources (i.e., trash), bones, fur, insects, mollusks, and plant seeds based on visual identification. For each sample, I weighed each category of food item and created a spreadsheet of all raw data for student analyses. In class, students were provided an overview of methods used to collect data and shown images of the different items dissected from samples. Students then used the raw data provided to calculate the percent mass and percent frequency for each food item category. Using RStudio, students created tables of summary statistics and graphs depicting frequency and percent mass data.

Student survey data: I administered a survey to students at the beginning and end of the semester to evaluate how the course had influenced learning outcomes and experiences. For questions aimed at understanding students’ perceived level of experience for a given skill or activity, the initial survey asked students to “give an estimate of your current level of experience for…” an activity, and the final survey asked “based on this course, give an estimate of your level of gained experience…” for that same activity, with the options of “NA”, “none”, “some”, and “extensive” given. For other questions, students were asked the degree to which they agreed (i.e., “strongly agree”, “agree”, “somewhat agree”, “somewhat disagree”, “disagree”, or “strongly disagree”) with a particular statement. Of the 25 students enrolled in the class, 22 students completed both the pre- and post-class surveys, and their responses were used for analysis. To analyze survey responses, I converted ordinal categorical responses to a numerical data and used individual paired t-tests to evaluate changes among pre- and post-class responses for each question. I also administered a separate survey I developed of open-response questions at the end of the semester to gauge how the course had influenced students’ thoughts on the field of ecology and urban ecology specifically, the role of science in community service, how ecology can guide efforts to coexist with urban wildlife, and how they viewed themselves as scientists.