<![CDATA[Background. Autistic children show heterogeneous receptive, expressive, pragmatic, and functional communication profiles that vary with the context of language use. Research on nature has mostly treated natural environments as interventions rather than examining what these settings offer for communication. Purpose: This conceptual narrative review examines how natural environments can be conceptualized as communication-rich settings for multidomain language use in autistic children. Method: ERIC, SciSpace, and Consensus were searched on October 14, 2026, and selection was reported with a PRISMA 2020 flow diagram: 861 records were identified, 655 screened, and 120 full-text reports assessed. Each study was rated on five criteria (population, setting, outcome, design strength, and confounding risk), and evidence from autistic samples was separated from bridging evidence from non-autistic children before thematic synthesis. Results: Five themes were identified: material-semantic, dynamic-exploratory, social-interactional, and contextual-functional affordances, and conditional enrichment through person-environment fit. No study was rated high. Autism-specific outdoor evidence offered moderate support only for social communication and was confounded with intervention components; the highest-rated support for expressive and functional language came from non-autistic children, and support for receptive language was weak. The resulting framework links natural setting qualities to referential, epistemic, instrumental, and social-interactional affordances, treats the communication partner as a mediator and person-environment fit as a moderator, and states six testable propositions. Conclusion: Nature is best understood as a potentially communication-rich context rather than an established language intervention. Educators can design accessible, sensory-adapted, and partner-supported outdoor activities, while future studies should compare matched natural and non-natural settings with autistic children, use domain-specific language measures, and test generalization across partners and settings.]]>
