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Abstract Enhancing resilience in formerly degraded ecosystems is an important goal of restoration ecology. However, evidence for the recovery of resilience and its underlying mechanisms require long‐term experiments and comparison with reference ecosystems. We used data from an experimental prairie restoration that featured long‐term soil heterogeneity manipulations and data from two long‐term experiments located in a comparable remnant (reference) prairie to (1) quantify the recovery of ecosystem functioning (i.e., productivity) relative to remnant prairie, (2) compare the resilience of restored and remnant prairies to a natural drought, and (3) test whether soil heterogeneity enhances resilience of restored prairie. We compared sensitivity and legacy effects between prairie types (remnant and restored) and among four prairie sites that included two remnant prairie sites and prairie restored under homogeneous and heterogeneous soil conditions. We measured sensitivity and resilience as the proportional change in aboveground net primary productivity (ANPP) during and following drought (sensitivity and legacy effects, respectively) relative to average ANPP based on 4 pre‐drought years (2014–2017). In nondrought years, total ANPP was similar between remnant and restored prairie, but remnant prairie had higher grass productivity and lower forb productivity compared with restored prairie. These ANPP patterns generally persisted during drought. The sensitivity of total ANPP to drought was similar between restored and remnant prairie, but grasses in the restored prairie were more sensitive to drought. Post‐drought legacy effects were more positive in the restored prairie, and we attributed this to the more positive and less variable legacy response of forb ANPP in the restored prairie, especially in the heterogeneous soil treatment. Our results suggest that productivity recovers in restored prairie and exhibits similar sensitivity to drought as in remnant prairie. Furthermore, creating heterogeneity promotes forb productivity and enhances restored prairie resilience to drought. 

Abstract Understanding the complex and unpredictable ways ecosystems are changing and predicting the state of ecosystems and the services they will provide in the future requires coordinated, long‐term research. This paper is a product of a U.S. National Science Foundation funded Long Term Ecological Research (LTER) network synthesis effort that addressed anticipated changes in future populations and communities. Each LTER site described what their site would look like in 50 or 100 yr based on long‐term patterns and responses to global change drivers in each ecosystem. Common themes emerged and predictions were grouped into state change, connectivity, resilience, time lags, and cascading effects. Here, we report on the “state change” theme, which includes examples from the Georgia Coastal (coastal marsh), Konza Prairie (mesic grassland), Luquillo (tropical forest), Sevilleta (arid grassland), and Virginia Coastal (coastal grassland) sites. Ecological thresholds (the point at which small changes in an environmental driver can produce an abrupt and persistent state change in an ecosystem quality, property, or phenomenon) were most commonly predicted. For example, in coastal ecosystems, sea‐level rise and climate change could convert salt marsh to mangroves and coastal barrier dunes to shrub thicket. Reduced fire frequency has converted grassland to shrubland in mesic prairie, whereas overgrazing combined with drought drive shrub encroachment in arid grasslands. Lastly, tropical cloud forests are susceptible to climate‐induced changes in cloud base altitude leading to shifts in species distributions. Overall, these examples reveal that state change is a likely outcome of global environmental change across a diverse range of ecosystems and highlight the need for long‐term studies to sort out the causes and consequences of state change. The diversity of sites within the LTER network facilitates the emergence of overarching concepts about state changes as an important driver of ecosystem structure, function, services, and futures.