LAIDLAW Research Proposal

The global crisis of antibiotic resistance threatens modern medicine. As drug-resistant bacteria spread, we desperately need new antibiotics, and nature holds the solution. In September 2025, researchers at Rockefeller University made a stunning discovery: from a single forest soil sample, they identified hundreds of previously unknown bacterial genomes and discovered two novel antibiotic compounds (Burian et al., Nature Biotechnology 2025). This breakthrough reminds us that temperate forests continue to hold massive untapped therapeutic potential, harboring vast reservoirs of undiscovered compounds.
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But here's the challenge: we don't know which forests hold the greatest discovery potential, or how to support microbial recovery in forests that aren't there yet. As post-agricultural forests recover across New England, their soil microbial communities are regenerating at different rates. Some recovering forests may already host diverse antibiotic-producing bacteria; others may require decades more recovery time or active management intervention. Currently, assessing these microbial communities requires expensive laboratory DNA sequencing, making it inaccessible to the conservation organizations and land managers who steward these sites daily.
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This project introduces the Habitat-Based Microbial Recovery Index (hMRI): a diagnostic tool that translates simple field measurements into estimates of soil microbial recovery potential. Built on a foundation of 85+ peer-reviewed studies focused on temperate forests, the hMRI functions like a "health score" for forest soils. By measuring five visible habitat features including canopy cover, woody debris, leaf litter depth, plant diversity, and distance from forest edge, we can identify which recovering forests have habitat conditions associated with healthy microbial communities.​​
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The Six-Week Field Pilot:
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Having conducted preliminary literature review to establish project feasibility, the summer research period (6 weeks) will focus on model development and field validation. The project will finalize the hMRI by updating the literature base and establishing reference ranges (Weeks 1-2), then apply the model across field plots in contrasting rewilded and degraded forest sites (Weeks 3-4). Interpretation, practitioner feedback, and deliverable development (Weeks 5-6) will evaluate the model's internal consistency and produce practical guidance for conservation partners.
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Dual-Purpose Impact:
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The hMRI serves two complementary functions for land stewards, conservation organizations, and researchers:
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1. Management Guidance: The index shows which habitat features are limiting microbial recovery potential, helping land managers make evidence-based decisions about restoration interventions. Should they add coarse woody debris? Protect interior forest from edge expansion? Focus on increasing plant diversity? The hMRI translates decades of research into actionable management priorities, supporting all forests along the recovery trajectory, from recently abandoned farmland to mature rewilded areas.
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2. Discovery Potential Assessment: Diverse soil microbial communities, including the Actinobacteria that produce most known antibiotics, depend on healthy forest habitats. When habitat conditions suggest strong recovery potential, the hMRI can help indicate sites worth investigating for pharmaceutical bioprospecting. Rather than randomly sampling forests, researchers can target sites where habitat conditions suggest high microbial diversity, making the search for novel compounds more informed.
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This research fundamentally reframes rewilding as a critical public health strategy. Beyond their recognized value for biodiversity and climate mitigation, restored forests represent infrastructure for the next generation of medical discoveries. The hMRI helps land managers guide forests toward recovery while simultaneously identifying when habitat conditions suggest those forests may have regained the microbial complexity that makes them valuable for therapeutic research. It's a tool for supporting restoration success AND recognizing when that success creates opportunities for discovery.
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Finding Tomorrow's Antibiotics in Today's Forests
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Introducing the Habitat-Based Microbial Recovery Index
The Science Behind hMRI:
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Recent research reveals clear patterns in how forest habitat quality predicts microbial diversity:
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Forest structure matters: Structural complexity directly predicts soil microbial diversity (Lang et al. 2023, Ecosphere)
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Edge effects are severe: Urbanization and edges create microbial "dead zones" where beneficial fungi decline and pathogens increase (Tatsumi et al. 2023, PNAS)
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Actinobacteria signal discovery potential: 72% of forest actinobacteria produce antimicrobial compounds (Sharma & Thakur 2020, Scientific Reports), and Streptomyces genomes average ~40 biosynthetic gene clusters each with ~90% remaining unexpressed under lab conditions (Belknap et al. 2020)
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Recovery takes time but works: Forest bacterial diversity can recover substantially within 14-20 years under natural regeneration (Robinson et al. 2025), though agricultural legacies can persist for 50+ years (Turley et al. 2020) to millennia (Peddle et al. 2024)
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Interactions are documented: Edge effects amplify near urban areas, CWD decomposition varies with canopy gaps, and land-use history modifies recovery trajectories. These contextual factors are recorded for interpretation alongside hMRI profiles.