From Field to Figure: Engaging Students in Local Aquatic Invertebrate Biodiversity Analysis Across Space and Time Using Basic R Skills

lt;p style=quot;line-height:1.38quot;gt;lt;span style=quot;font-size:12pt; font-variant:normal; white-space:pre-wrapquot;gt;lt;span style=quot;font-family:#039;Times New Roman#039;,serifquot;gt;lt;span style=quot;color:#000000quot;gt;lt;span style=quot;font-weight:400quot;gt;lt;span style=quot;font-style:normalquot;gt;lt;span style=quot;text-decoration:nonequot;gt;This learning module introduces undergraduate students to quantitative approaches for analyzing biodiversity using authentic long-term aquatic invertebrate data collected from wetland sites in northeast Ohio between 2023 and 2026. Through a sequence of scaffolded activities, students build foundational understanding of biodiversity metrics (species richness (S), Shannon diversity (Hamp;rsquo;), and evenness (E)) before progressing to exploratory data visualization, statistical reasoning, graph interpretation, and computational analysis of the data in RStudio. The module culminates in students creating and interpreting visualizations of biodiversity patterns across multiple ecological contexts and communicating findings using the Claim-Evidence-Reasoning (CER) framework. Optional extensions encourage students to pursue independent ecological investigations grounded in spatial or temporal analysis and authentic scientific inquiry.amp;nbsp;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/pgt; lt;pgt;lt;span style=quot;font-size:12pt; font-variant:normal; white-space:pre-wrapquot;gt;lt;span style=quot;font-family:#039;Times New Roman#039;,serifquot;gt;lt;span style=quot;color:#000000quot;gt;lt;span style=quot;font-weight:400quot;gt;lt;span style=quot;font-style:normalquot;gt;lt;span style=quot;text-decoration:nonequot;gt;The design of this module strongly aligns with the Ecological Society of Americaamp;rsquo;s 4DEE framework, particularly the Space amp;amp; Time dimension. See the Resource Outline in the 0-ReadMeFirst (instructors only) document for brief descriptions of each module component. The module explicitly engages students in examining how ecological patterns vary across both spatial and temporal scales. Students compare biodiversity metrics among multiple wetland sites that differ in location and site characteristics, encouraging investigation of spatial heterogeneity in ecological communities. At the same time, the long-term nature of the dataset allows students to explore temporal dynamics by analyzing biodiversity changes across seasons and years. These comparisons help students recognize that ecological systems are not static, but instead are shaped by processes operating across multiple scales of space and time.lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/pgt; lt;pgt;lt;span style=quot;font-size:12pt; font-variant:normal; white-space:pre-wrapquot;gt;lt;span style=quot;font-family:#039;Times New Roman#039;,serifquot;gt;lt;span style=quot;color:#000000quot;gt;lt;span style=quot;font-weight:400quot;gt;lt;span style=quot;font-style:normalquot;gt;lt;span style=quot;text-decoration:nonequot;gt;The module supports core competencies emphasized within the Space amp;amp; Time dimension by encouraging students to interpret ecological phenomena through scale-dependent patterns and processes. Through data visualization and statistical analysis in RStudio, students investigate how biodiversity responds to environmental variation, habitat differences, and temporal fluctuations. The optional Google Earth Pro extension further strengthens spatial thinking by allowing students to contextualize sampling locations geographically and explore additional environmental variables such as proximity to roads or land-use patterns.amp;nbsp;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/pgt; lt;pgt;lt;span style=quot;font-size:12pt; font-variant:normal; white-space:pre-wrapquot;gt;lt;span style=quot;font-family:#039;Times New Roman#039;,serifquot;gt;lt;span style=quot;color:#000000quot;gt;lt;span style=quot;font-weight:400quot;gt;lt;span style=quot;font-style:normalquot;gt;lt;span style=quot;text-decoration:nonequot;gt;Importantly, the module provides students with authentic experiences using a longitudinal ecological dataset, a central component of ecological literacy within the 4DEE framework. By working with real-world data collected over multiple years, students gain experience identifying trends, variability, and ecological change over time. This approach mirrors the practices of professional ecologists and reinforces the understanding that ecological knowledge emerges through repeated observation across spatial and temporal scales.lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/pgt; lt;pgt;lt;span style=quot;font-size:12pt; font-variant:normal; white-space:pre-wrapquot;gt;lt;span style=quot;font-family:#039;Times New Roman#039;,serifquot;gt;lt;span style=quot;color:#000000quot;gt;lt;span style=quot;font-weight:400quot;gt;lt;span style=quot;font-style:normalquot;gt;lt;span style=quot;text-decoration:nonequot;gt;Overall, this module operationalizes the ESA 4DEE Space amp;amp; Time dimension by engaging students in the analysis of ecological variability across sites, seasons, and years; developing quantitative and computational skills for interpreting scale-dependent ecological patterns; and promoting authentic scientific inquiry using long-term biodiversity datasets.lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/pgt; lt;h2 style=quot;line-height:1.38; margin-top:24px; margin-bottom:8pxquot;gt;lt;span style=quot;font-size:16pt; font-variant:normal; white-space:pre-wrapquot;gt;lt;span style=quot;font-family:#039;Times New Roman#039;,serifquot;gt;lt;span style=quot;color:#000000quot;gt;lt;span style=quot;font-weight:400quot;gt;lt;span style=quot;font-style:normalquot;gt;lt;span style=quot;text-decoration:underlinequot;gt;lt;span style=quot;-webkit-text-decoration-skip:nonequot;gt;lt;span style=quot;text-decoration-skip-ink:nonequot;gt;Learning Objectiveslt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;span style=quot;font-size:16pt; font-variant:normal; white-space:pre-wrapquot;gt;lt;span style=quot;font-family:#039;Times New Roman#039;,serifquot;gt;lt;span style=quot;color:#000000quot;gt;lt;span style=quot;font-weight:400quot;gt;lt;span style=quot;font-style:normalquot;gt;lt;span style=quot;text-decoration:nonequot;gt;amp;nbsp;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/h2gt; lt;p style=quot;line-height:1.38quot;gt;lt;span style=quot;font-size:12pt; font-variant:normal; white-space:pre-wrapquot;gt;lt;span style=quot;font-family:#039;Times New Roman#039;,serifquot;gt;lt;span style=quot;color:#2b2b2bquot;gt;lt;span style=quot;background-color:#ffffffquot;gt;lt;span style=quot;font-weight:400quot;gt;lt;span style=quot;font-style:normalquot;gt;lt;span style=quot;text-decoration:nonequot;gt;By the end of this module, students will be able to:lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/pgt; lt;h3 style=quot;line-height:1.38; margin-top:21px; margin-bottom:5pxquot;gt;lt;span style=quot;font-size:13.999999999999998pt; font-variant:normal; white-space:pre-wrapquot;gt;lt;span style=quot;font-family:#039;Times New Roman#039;,serifquot;gt;lt;span style=quot;color:#434343quot;gt;lt;span style=quot;font-weight:400quot;gt;lt;span style=quot;font-style:normalquot;gt;lt;span style=quot;text-decoration:nonequot;gt;Skillslt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/h3gt; lt;ulgt; lt;li aria-level=quot;1quot; style=quot;list-style-type:discquot;gt;lt;span style=quot;font-size:12pt; font-variant:normal; white-space:pre-wrapquot;gt;lt;span style=quot;font-family:#039;Times New Roman#039;,serifquot;gt;lt;span style=quot;color:#2b2b2bquot;gt;lt;span style=quot;background-color:#ffffffquot;gt;lt;span style=quot;font-weight:400quot;gt;lt;span style=quot;font-style:normalquot;gt;lt;span style=quot;text-decoration:nonequot;gt;Perform basic biodiversity calculations (S, Hamp;rsquo;, E) by hand and in RStudiolt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/ligt; lt;li aria-level=quot;1quot; style=quot;list-style-type:discquot;gt;lt;span style=quot;font-size:12pt; font-variant:normal; white-space:pre-wrapquot;gt;lt;span style=quot;font-family:#039;Times New Roman#039;,serifquot;gt;lt;span style=quot;color:#2b2b2bquot;gt;lt;span style=quot;background-color:#ffffffquot;gt;lt;span style=quot;font-weight:400quot;gt;lt;span style=quot;font-style:normalquot;gt;lt;span style=quot;text-decoration:nonequot;gt;Learn (or review) basic and intermediate data manipulation in RStudiolt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/ligt; lt;li aria-level=quot;1quot; style=quot;list-style-type:discquot;gt;lt;span style=quot;font-size:12pt; font-variant:normal; white-space:pre-wrapquot;gt;lt;span style=quot;font-family:#039;Times New Roman#039;,serifquot;gt;lt;span style=quot;color:#2b2b2bquot;gt;lt;span style=quot;background-color:#ffffffquot;gt;lt;span style=quot;font-weight:400quot;gt;lt;span style=quot;font-style:normalquot;gt;lt;span style=quot;text-decoration:nonequot;gt;Use data to create summary figures in RStudiolt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/ligt; lt;li aria-level=quot;1quot; style=quot;list-style-type:discquot;gt;lt;span style=quot;font-size:12pt; font-variant:normal; white-space:pre-wrapquot;gt;lt;span style=quot;font-family:#039;Times New Roman#039;,serifquot;gt;lt;span style=quot;color:#2b2b2bquot;gt;lt;span style=quot;background-color:#ffffffquot;gt;lt;span style=quot;font-weight:400quot;gt;lt;span style=quot;font-style:normalquot;gt;lt;span style=quot;text-decoration:nonequot;gt;Use RStudio to perform basic statistical analysislt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/spangt;lt;/ligt; lt;li aria-level=quot