Ecosystems are complex systems composed of hierarchically organized subsystems embedded within larger networks of interactions (Jin et al., 2019; Schizas, Papatheodorou, & Stamou, 2019). This complexity not only leads students to demonstrate fragmented and compartmentalized knowledge (Eilam, 2011) but also creates difficulties in developing a systemic understanding of ecosystems and causal relationships (Grotzer & Basca, 2003). For example, students often struggle to explain concepts that require a higher level of systems thinking beyond simple cause-and-effect relationships and involve understanding the indirect and dynamic relationships within ecosystems, such as carrying capacity, exponential growth, and feedback loops (Jin et al., 2019). While indirect relationships are central to understanding complex ecological systems, they are usually not directly observable; therefore, students tend to focus on simple linear direct relationships (Mambrey et al., 2020). Predator–prey interactions, for instance, are usually interpreted in terms of direct population changes; that is, a decrease in prey population leads to a decrease in predator populations but misses the indirect relationships. Accordingly, understanding ecosystems requires a systems-thinking approach that holistically addresses nonlinear relationships, feedback loops, and interactions among system components (Grotzer & Basca, 2003). Systems thinking encompasses learners’ ability to understand biological systems by recognizing their key characteristics and applying discipline-specific concepts to explain interdependencies within ecosystems, including the influences of human activities (Gilissen, Knippels, & van Joolingen, 2020; Jin et al., 2019). In the context of this study, systems thinking is defined as learners’ ability to use discipline-specific concepts to describe interdependency in ecosystems, including the influence of human activity (Jin et al. 2019). Although complex systems operate according to their principles and cannot be entirely managed by humans, human activities can influence and, in some cases, disturb natural systems (Riess & Mischo, 2010).

Building on this perspective, the purpose of science education has been redefined as preparing accountable, conscious individuals who can reason about complex systems. In fact, the Next Generation Science Standards (NGSS, 2013; NRC, 2013) address the concept of “Systems and System Models” as a cross-cutting concept and ‘Ecosystems: Interactions, Energy, and Dynamics’ as a Disciplinary Core Ideas in life sciences. The Next Generation Science Standards (2013) also note that human activities have significantly impacted the biosphere, in some cases causing habitat loss and species extinction. Similarly, the recently revised Turkish Science Education Curriculum emphasizes the importance of complex systems, systems thinking, and systems literacy (MoNE, 2024, p. 55). To this end, educating future citizens to engage with complex global environmental challenges shaped by human-environment interactions requires teachers to possess high-level systems thinking skills. Accordingly, this study aims to clarify future science teachers’ understanding of ecosystem dynamics and the influence of humans on those dynamics through the lens of systems thinking.

In this study, a qualitative research method was utilized. Qualitative research is an approach that focuses on uncovering the meanings individuals attribute to their experiences and uses words as the primary data source (Merriam & Tisdell, 2016). As a part of qualitative research, a case study research design was adopted. Yin (2009) suggests that a case study enables an in-depth examination of a phenomenon through multiple data sources, including interviews, documents, and observations, particularly in contexts where the researcher does not intervene in participants’ actions. To gain a comprehensive understanding of prospective science teachers’ levels of systems thinking in ecosystems and their understanding of human influence, a single embedded case study design was employed following Yin (2018). It is especially suitable for investigating a single case to be investigated through multiple embedded units of analysis. (Yin, 2018), and in this study, the case consisted of prospective science teachers, with individual participants serving as the embedded subunits. Purposeful sampling was used to ensure that participants were appropriate for the study’s purpose (Fraenkel & Wallen, 2009). The study involved five volunteer senior prospective science teachers enrolled at a public university. Data were collected through interviews by using the Systems Thinking Assessment questionnaire developed by Jin et al. (2019). The questionnaire consists of 12 (two-tiered) items presenting real-world scenarios (i.e., the introduction of reindeer on St. Paul Island in 1911, or the removal of wolves in Yellowstone National Park), followed by open-ended questions. Participants’ responses were analyzed based on three systems thinking concepts—indirect/distant connections, feedback loops, and emergent properties—as described by Jin et al. (2019). Indirect/distant connections refer to situations in which ecosystem components appear unrelated but are, in fact, indirectly connected. Feedback loops, however, are used to analyze interdependent relationships in complex systems. Negative feedback loops help maintain ecosystem stability by reducing change, while positive feedback loops amplify change and may destabilize the system. Emergent properties, as explained by Chi et al. (2012), describe how overall system patterns do not result from the actions of a single agent or a controlling group, but rather emerge from the collective interactions of all agents. In complex ecosystems, emergent properties include carrying capacity, exponential growth, and energy pyramids (Jin et al., 2019). During qualitative data analysis, codes were generated using established qualitative coding procedures (Saldaña, 2021). Data were transcribed line by line using MAXQDA software, and a thematic analysis was subsequently conducted (Creswell, 2013)

Overall findings revealed science teacher candidates’ tendency to explain relationships in ecosystems depending on observable relationships and patterns rather than the dynamic, interconnected mechanisms underlying ecosystem behavior. When participants' responses were analyzed with respect to three systems thinking concepts, feedback loops were found be the most frequently mentioned systems thinking concept, followed by the emerging properties and the distant or indirect interactions among species. For example, when described the scenario regarding the introduction of 25 reindeer to St. Paul Island and the subsequent changes in the reindeer population (Scheffer, 1951), participants paid particular attention to the interrelationship between population size and food availability (i.e., negative feedback loop). They stated that as the reindeer population increased, grazing pressure reduced food resources, which caused population decline. The population decreases, then allowed food resources to recover. Participants also link changes in the reindeer population to food availability, competition, and reproduction (emergent properties). One participant, however, attributed fluctuations in population to the male-to-female reindeer ratio and argued that seasonal variation in breeding periods could influence population growth. Another participant drew attention to carrying capacity, emphasizing that exceeding an ecosystem’s capacity prevents that ecosystem from sustaining its population. This finding suggests that, while participants identified relevant key system components, they had difficulty integrating these elements into system-level mechanisms. When participants were asked to reason about a trophic cascade in Yellowstone National Park following the elimination of wolves, they pointed to multiple relationships among populations and noticed some distant or indirect interactions between populations. They linked the trophic cascade to human activity, explaining how it could affect wolf populations and degrade habitat. Others explained how eliminating wolves indirectly affects plants. The current findings have important implications for science teacher education programs toward the inclusion of systems thinking skills into their curricula.

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