New Research Finds that Wetland and Stream Mitigation Banks Take Over 1,000 Days to Approve
In our new report The Time it Takes for Restoration, the Environmental Policy Innovation Center (EPIC) and the Ecological Restoration Business Association (ERBA) reveal persistent delays in the approval of a class of wetland and stream restoration projects called ‘mitigation banks.’ These delays threaten to hinder the availability of offsets for impacted waterways during the coming surge in infrastructure building. While a niche term, mitigation banks are essentially large tracts of degraded lands restored under the Clean Water Act Section 404 regulatory program to provide wetland and stream habitat and functions, often at a landscape scale that benefits watersheds and ecosystems.
Over the years, mitigation banking has fueled billions in investment towards conservation outcomes making it the largest U.S. environmental market for natural resource restoration. The researchers analyzed U.S. Army Corps of Engineers (Corps) data to see if timelines on mitigation banks were meeting the federally mandated approval time limit of 225 days, and found the average project took 1.5x longer than required “on the regulator’s desk.” The full timeline for project approval - including back and forth between the Corps and applicants - takes over 1,000 days on average (the longest project took over 12 years!).
When wetland and streams are threatened by development in the US, the Clean Water Act requires avoidance, minimization, and then mitigation (e.g., offset) of impacts. Even after avoiding and minimizing, the Corps grants permits allowing impacts to 14,000 acres of wetlands and 568 miles of streams every year,* and those permits require offsets. This offset requirement catalyzed the world’s largest volume of wetland and stream mitigation banking, generating roughly $3 billion in credits annually. The parameters for this booming, niche industry were developed over years of trial and error, with a foundational set of rules codified in the 2008 Final Rule on Compensatory Mitigation for Losses of Aquatic Resources (2008 Rule). Among other things, this rule defined criteria for high quality offsets created in advance of impacts. The 2008 Rule also specified timelines for federal processing of a mitigation bank. The 225-day time limit did not account for the entire process from start to finish, only federal processing, but even under the unclear terms of the regulations, the average approval takes 50% longer than required.
We have been hearing for years that the process for approving mitigation banks and in-lieu fee programs (ILFs) is plagued by delays. Until now, nobody has quantified those delays. The Time it Takes for Restoration is the first quantitative analysis of ‘timestamp’ data collected by Corps staff responsible for processing applications for mitigation banks. The analysis used US Army Corps of Engineers (Corps) ‘timestamp’ data recorded in a Corps database commonly called ‘ORM’ (technically, it’s part of a larger system known as OMBIL or ‘Operations and Maintenance Business Information Link’). ERBA and EPIC obtained 819 records of approved mitigation banks (603) and ILFs (216) from fiscal year 2014 - 2021. ILF data was incomplete as well as inconsistently recorded and so was not a focus of the research.
Ultimately, the analysis used 496 mitigation bank records for the analysis after data cleaning (which removed 107 banks). The researchers categorized time intervals into the time for which the Corps was responsible for reviewing an application vs. the time the mitigation banker was responsible. Statistical analysis proved that the Corps-responsible time averaged 336 days, 1.5 times what’s required. The full timeline of approval for these environmentally-beneficial projects ranged from a lightning-fast 78 days to a childhood-spanning 12 years and 4 days, with an average of 1,099 days (see Figure 1 below). To put this in context, there is an 800-mile LNG pipeline spanning the entire state of Alaska that is getting permits in seven years, which is faster than 25 of the mitigation banks analyzed in the research.
What’s the Holdup?
Well, we can’t tell you that, at least not based on the data. There is a delay code in the ORM database that could indicate factors associated with longer timelines, but the delay code was not used in the data we received. We are starting a second phase of research using informational interviews with bank sponsors (and Districts, we hope) asking about the factors they perceive affecting approval timelines.
For now, we can tell you that some of the 38 Corps Districts are faster at approvals than others (those at the bottom of Figure 2), although take the figure below with a grain of salt. Caveats: some Districts do not have all of their approved banks in ORM when compared to banks found in another data source called RIBITS (more on this below); the removal of outlier records in some Districts (e.g., Tulsa, Savannah) dramatically reduced federal mandatory timelines; and the data does not make a distinction of whether approvals were for a wetland-only bank (easier) or a wetland + species bank (more complicated), which could increase timelines.
Some other interesting findings from the analysis were that 11% of the data was removed due to errors that could be easily flagged for review. Records had four or more of the same date entered in the time intervals, or four or more blank time intervals. The New Orleans and St. Paul Districts had 9 and 15 bank records removed due to time errors, respectively. There is also missing data in ORM. When we did a cross-check of ORM mitigation bank data with RIBITS (the publicly available database of mitigation banks and ILFs), six Districts had 25% or fewer bank entries in ORM than RIBITS (Galveston, Jacksonville, Norfolk, Wilmington; Buffalo, Chicago, Fort Worth, Philadelphia, Walla Walla) - although the latter 5 districts approved less than 10 banks during the time period.
Longer approval timelines in Districts were not associated with the number of banks approved in the District. You might think that Districts with a lot on their plates would have longer timelines, but that was not the case. The data did not indicate the level of staffing in Districts, which could be a better factor to analyze.
We’d like to highlight that the Appendix has a goldmine of information for Districts and mitigation bank sponsors. We realized that for every national-level finding, an individual District or bank would say “But what about my District / bank?” so we provided tables to help answer those questions. The Appendix also includes information about records removed per District with reason for removal and a table of the 1st and 99th percentile outliers (the very fastest and slowest approvals).
What’s on Our Wishlist for Improvement?
While the data quantitatively show that the 225-day required timeline in the Rule is not being met on average, this analysis is not just about identifying missed timelines, but about taking the first step in adaptive management. If the only information available is opinions like “It’s too slow!,” stakeholders may dig in about whether this is true or not based on anecdotes rather than data. The results in this report are based on the most complete dataset compiled to date and provide a foundation for productive dialogue. Here are three ideas that could provide insight and speed approvals of wetland and stream banks.
Update ORM to flag potential errors, provide better check-in / check-out timestamps, incorporate project management methods, and create transparency of the data. We’re asking a lot here, but it’s do-able! Virginia’s new PEEP initiative (Permitting Enhancement and Evaluation Program) creates Gantt charts of target timelines for environmental permits, indicates where the application is in the process and whose desk it’s on (even external agencies), incorporates smart project management actions like sending automated reminders, and makes all of this viewable to the permittee and the public. Contrast that to permittees having to call Corps staff to find out where their bank is in the process, and the ‘public’ (e.g., EPIC) having to submit a Freedom of Information Act request (FOIA) and wait six or more months to access data.
Use the delay code! The ORM database includes a field that allows staff to indicate a reason for delay. It has not been used. This makes it incredibly hard to identify constructive opportunities for adaptive management. EPIC is currently researching potential factors influencing permit timelines and we would be happy to provide categories of delay for consideration.
Automate analysis and reporting on approval timelines. EPIC’s use of R programming for analysis provides proof that computer code could be written to regularly and efficiently run analyses for internal adaptive management and external transparency to stakeholders.
See additional recommendations in our report (note: they get a little wonky!).
Why Do We Care about Timelines?
Broadly, we think it’s just not right that up to ⅓ of a restoration project’s funding is spent on permitting. We also think it’s a shame that the US public could lose out on $9.8 billion in the Infrastructure Investment and Jobs Act [IIJA] tagged for restoration because the projects might not get approved before the ‘use-it or lose-it’ funds run out in 2026. On the flipside, IIJA will spend more than $600 billion on transportation and other physical infrastructure. Many of these projects will expand renewable energy and bring climate mitigation benefits. At the same time, there will be impacts to wetlands, streams, and species. If there are not enough available offsets for these projects because good wetland and stream mitigation banks are sitting in the approval queue, we’ll lose out on these too. Leaders around the globe are committing to restoration of 30% of the world’s degraded ecosystems (Target 2 of the UN Convention on Biological Diversity’s 2023 Kunming-Montreal Global Biodiversity Framework). We need money to go to Nature, not paperwork.
EPIC and ERBA are starting a second phase of research using informational interviews to provide further context and insight to the quantitative analysis completed here.
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