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Productivity benefits from diversity can arise when compatible pathogen hosts are buffered by unrelated neighbors, diluting pathogen impacts. However, the generality of pathogen dilution has been controversial and rarely tested within biodiversity manipulations. Here, we test whether soil pathogen dilution generates diversity- productivity relationships using a field biodiversity-manipulation experiment, greenhouse assays, and feedback modeling. We find that the accumulation of specialist pathogens in monocultures decreases host plant yields and that pathogen dilution predicts plant productivity gains derived from diversity. Pathogen specialization predicts the strength of the negative feedback between plant species in greenhouse assays. These feedbacks significantly predict the overyielding measured in the field the following year. This relationship strengthens when accounting for the expected dilution of pathogens in mixtures. Using a feedback model, we corroborate that pathogen dilution drives overyielding. Combined empirical and theoretical evidence indicate that specialist pathogen dilution generates overyielding and suggests that the risk of losing productivity benefits from diversity may be highest where environmental change decouples plant-microbe interactions.

Choosing restoration strategies may depend on ecosystem's stability properties. When degraded ecosystems do not self‐perpetuate, natural regeneration can lead to system recovery, and restoration interventions are often designed to accelerate the natural regeneration process. However, when degraded systems self‐perpetuate, reestablishing functional ecosystems depends on overcoming resistance thresholds that impede recovery. In both scenarios, concentrating restoration efforts in patches of the desired state may enhance ecosystem recovery. Introducing patches of a desired state has been motivated by two frameworks: autocatalytic nucleation and the analogy to nucleation. When restoration depends on overcoming resistance thresholds, autocatalytic nucleation lowers restoration barriers by initiating a local positive feedback mechanism that is only successful when desired patches are introduced above a critical patch size. In contrast, the analogy to nucleation accelerates natural regeneration whereby desired patches interact with landscape scale factors often through directed dispersal. We compare nucleation frameworks, and discuss their applications for restoration practices.

Meeting restoration targets may require active strategies to accelerate natural regeneration rates or overcome the resilience associated with degraded ecosystem states. Introducing desired ecosystem patches in degraded landscapes constitutes a promising active restoration strategy, with various mechanisms potentially causing these patches to become foci from which desired species can re‐establish throughout the landscape. This study considers three mechanisms previously identified as potential drivers of introduced patch dynamics: autocatalytic nucleation, directed dispersal, and resource concentration. These mechanisms reflect qualitatively different positive feedbacks. We developed an ecological model framework that compared how the occurrence of each mechanism was reflected in spatio‐temporal patch dynamics. We then analyzed the implications of these relationships for optimal restoration design. We found that patch expansion accelerated over time when driven by the autocatalytic nucleation mechanism, while patch expansion driven by the directed dispersal or resource concentration mechanisms decelerated over time. Additionally, when driven by autocatalytic nucleation, patch expansion was independent of patch position in the landscape. However, the proximity of other patches affected patch expansion either positively or negatively when driven by directed dispersal or resource concentration. For autocatalytic nucleation, introducing many small patches was a favorable strategy, provided that each individual patch exceeded a critical patch size. Introducing a single patch or a few large patches was the most effective restoration strategy to initiate the directed dispersal mechanism. Introducing many small patches was the most effective strategy for reaching restored ecosystem states driven by a resource concentration mechanism. Our model results suggest that introducing desirable patches can substantially accelerate ecosystem restoration, or even induce a critical transition from an otherwise stable degraded state toward a desired ecosystem state. However, the potential of this type of restoration strategy for a particular ecosystem may strongly depend on the mechanism driving patch dynamics. In turn, which mechanism drives patch dynamics may affect the optimal spatial design of an active restoration strategy. Each of the three mechanisms considered reflects distinct spatio‐temporal patch dynamics, providing novel opportunities for empirically identifying key mechanisms, and restoration designs that introduce desired patches in degraded landscapes according to these patch dynamics.

Microbiomes have profound effects on host fitness, yet we struggle to understand the implications for host ecology. Microbiome influence on host ecology has been investigated using two independent frameworks. Classical ecological theory powerfully represents mechanistic interactions predicting environmental dependence of microbiome effects on host ecology, but these models are notoriously difficult to evaluate empirically. Alternatively, host–microbiome feedback theory represents impacts of microbiome dynamics on host fitness as simple net effects that are easily amenable to experimental evaluation. The feedback framework enabled rapid progress in understanding microbiomes’ impacts on plant ecology, and can also be applied to animal hosts. We conceptually integrate these two frameworks by deriving expressions for net feedback in terms of mechanistic model parameters. This generates a precise mapping between net feedback theory and classic population modelling, thereby merging mechanistic understanding with experimental tractability, a necessary step for building a predictive understanding of microbiome influence on host ecology.

The theory of alternate stable states provides an explanation for rapid ecosystem degradation, yielding important implications for ecosystem conservation and restoration. However, utilizing this theory to initiate transitions from degraded to desired ecosystem states remains a significant challenge. Applications of the alternative stable states framework may currently be impeded by a mismatch between local‐scale driving processes and landscape‐scale emergent system transitions. We show how nucleation theory provides an elegant bridge between local‐scale positive feedback mechanisms and landscape‐scale transitions between alternate stable ecosystem states. Geometrical principles can be used to derive a critical patch radius: a spatially explicit, local description of an unstable equilibrium point. This insight can be used to derive an optimal patch size that minimizes the cost of restoration, and to provide a framework to measure the resilience of desired ecosystem states to the synergistic effects of disturbance and environmental change.