Effects of connectivity history on fungal community dynamics and recovery
Habitat loss and fragmentation are major drivers of biodiversity decline, motivating restoration efforts that aim to increase habitat amount and connectivity. Despite this, empirical understanding of the ecological processes underlying community responses to fragmentation, and of the long-term consequences of restoring connectivity, remains limited. Here, we use an extensively replicated field experiment with wood inhabiting fungal communities to test the reversibility of connectivity disruption and the role of connectivity history in community recovery. We established a mainland–island system experiment comprising 480 deadwood units distributed across 30 plots representing a gradient of connectivity. Following one year of community assembly, a reciprocal translocation experiment was conducted to disrupt and restore connectivity. Fungal communities were characterized using ITS2 DNA metabarcoding across four sampling time points over four years. The probability of occurrence of most fungal OTUs declined in logs remaining in isolated habitats compared with those in connected habitats, with differences emerging during the initial isolation phase and persisting after translocation. Communities originating from well-connected patches showed substantial recovery even after relocation to isolated sites, whereas communities assembled under isolated conditions exhibited limited recovery despite subsequent connectivity restoration. These results demonstrate that habitat fragmentation produces not only immediate but also persistent legacy effects that constrain community recovery. Importantly, recovery trajectories depended on both current connectivity and past connectivity history, suggesting that stochastic drift during isolation can drive communities along alternative assembly pathways. We conclude that historical connectivity strongly influences recovery potential, and thus maintaining connectivity continuity is critical to prevent long-lasting losses in biodiversity. Our study highlights that theory-driven experimental approaches are essential for robustly understanding spatial community dynamics beyond what observational data alone can provide.
Habitat loss and fragmentation are major drivers of biodiversity decline, motivating restoration efforts that aim to increase habitat amount and connectivity. Despite this, empirical understanding of the ecological processes underlying community responses to fragmentation, and of the long-term consequences of restoring connectivity, remains limited. Here, we use an extensively replicated field experiment with wood inhabiting fungal communities to test the reversibility of connectivity disruption and the role of connectivity history in community recovery. We established a mainland–island system experiment comprising 480 deadwood units distributed across 30 plots representing a gradient of connectivity. Following one year of community assembly, a reciprocal translocation experiment was conducted to disrupt and restore connectivity. Fungal communities were characterized using ITS2 DNA metabarcoding across four sampling time points over four years. The probability of occurrence of most fungal OTUs declined in logs remaining in isolated habitats compared with those in connected habitats, with differences emerging during the initial isolation phase and persisting after translocation. Communities originating from well-connected patches showed substantial recovery even after relocation to isolated sites, whereas communities assembled under isolated conditions exhibited limited recovery despite subsequent connectivity restoration. These results demonstrate that habitat fragmentation produces not only immediate but also persistent legacy effects that constrain community recovery. Importantly, recovery trajectories depended on both current connectivity and past connectivity history, suggesting that stochastic drift during isolation can drive communities along alternative assembly pathways. We conclude that historical connectivity strongly influences recovery potential, and thus maintaining connectivity continuity is critical to prevent long-lasting losses in biodiversity. Our study highlights that theory-driven experimental approaches are essential for robustly understanding spatial community dynamics beyond what observational data alone can provide.
University of Jyvaskyla