Research › Findings
The systems that fund restoration in Washington — federal awards, state grants, tribal programs — each keep their own records. None sees the full picture. These findings describe what emerges when those records are assembled: structural patterns that are invisible from inside any single system but visible from the point where they converge — the desk of the organization carrying them all.
Each verified against the dataset.
94% of restoration organizations have funded commitments spanning two or more data systems
Nearly all organizations in the benchmark (94%) have funded commitments from two or more distinct data sources — USASpending.gov, RCO PRISM, and RCO ArcGIS. Their full portfolio is not visible in any single system.
The structural picture that matters — where timelines collide, where match commitments compound, where capacity gets stretched — assembles only when you hold all the pieces simultaneously. Each source is accurate on its own. None of them can see the interactions.
Based on 50 organizations. Sources: USASpending.gov, RCO PRISM, RCO ArcGIS.
57% of restoration organizations have deadlines clustering in the same seasonal windows
29 of 50 organizations (58%) show end-date clustering as a structural conflict type — the most prevalent conflict pattern in the dataset. This is driven by species-specific in-water work windows, typically July through September in western Washington.
Organizations do not choose this compression. The seasonal calendar imposes it. What the data adds is how that clustering interacts with other funded commitments — match commitments due in the same window, federal reports on a different cycle, state deliverables stacking underneath.
Based on 50 organizations. End-date clustering requires 3+ active funded commitments with converging deadlines.
Grant count explains less than 20% of the variation in portfolio complexity
Active grant count explains just 9% of the variation in portfolio complexity across 50 organizations. More grants does not automatically mean more structural friction.
Complexity comes from how grants interact — timeline overlaps, match burden compounding, cross-source convergence — not from how many there are. An organization with 5 grants on conflicting timelines carries more structural pressure than one managing 20 that do not touch each other.
Based on 50 organizations. R² = 0.089 between active grant count and portfolio complexity score.
Land trusts carry a median match burden 1.9 times the population median
Land trusts in the dataset carry a median match burden of 47% of total award value — 1.9 times the population median of 24%. Two-thirds show high match burden as a structural conflict type.
This is not a problem — it is the acquisition funding model working as designed. The 12 land trusts in the benchmark have collectively completed 353 RCO projects and conserved over 48,000 acres. But the structural consequence is real: high match burden means more of the organization’s own resources are committed, leaving less flexibility when timelines compress or new opportunities arise.
Based on 12 land trusts within a benchmark of 50 organizations. Match burden computed from RCO PRISM data.
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Freehold assembles the structural picture that no single funding source can see.
Also: Sector Watch · Funding Exposure