Oceanicsdotio

Predictive aquaculture siting

December 14, 2019


I made some predictions about the continued expansion of aquaculture in Maine. Now that we have 2 more years of data and are 40% through a 5-year forecast, let’s look back at the early concept: for long-term predictions, you need to model human behavior, not just the environment.

If you are unfamiliar with the area, the coastal town jurisdictions are shown in red below.

Maine coast

Maine farmers cultured $6.7M in mussels, oysters, and clams in 2015, and $8M in 2016 (Maine Department of Marine Resources): e xceeding federal growth benchmarks [1]. Leasing is decentralized and reactive, with exclusion criteria including water uses, public assets, and lease density. Larger operations improve efficiency, and attract processing facilities—but there is concern about the size of firms [2]. Residents closest to farms view them as locally undesirable [3], and decentralized expansion — including limited-purpose licenses (table below) — is unlikely to balance production with social acceptance.

Standard lease Limited-purpose license
Hearing Yes No
Area 0–100 acres 400 sq. ft.
Term 10 years 1 year
Density None 4 per 1000 ft. radius

Sustainable growth instead requires evaluating how scale matches community objectives. Targeted non-marginal investment, coordinated through voluntary bay management [2], can increase income and equity.

In single-bay management (SBM), industry cooperatives unify siting and culture practice. Objectives are to lower expenses, and fix or increase price. New sites have a mean frequency (λλ, y-1), such that new arrivals follow a Poisson counting process. Damariscotta River had 91 LPAs as of 2017. Issuance is 191 y-1, accelerating by 30 y-2 (DMR). Spacing restrictions give a footprint around 0.024 km2. Given a window of size A0A_0, and a set of NN existing leases, no viable space will remain in jurisdiction area AA after t=A(41.66A0N)(λA0)1t=A(41.66A_0-N)(\lambda A_0)^{-1}.

A less ideal packing efficiency that accounts for operators buffering themselves is 0.093 km2, which significantly reduces these estimates.

Growth may vary across tens of meters, so siting is fine-scale (figure below). New locations are sampled from a kernel density estimator, trained on existing locations, depth, and satellite-derived oyster suitability. With projected growth, there are >200 sites in the region by year 3 (table below). Mean tt is 15 years, without considering competing uses or closures. Less than 22% allocation, and some jurisdictions are already full. The model makes assumptions about space and market conflicts, given the area has a unique aquaculture history.

Year NN λ\lambda tt min(t)min(t)
0 91 36.4 15.2 0.001
1 127 37.0 14.9 <0
2 164 37.6 14.5 <0
3 202 38.2 14.1 <0

One alternative is site allocation planning (SAP), which delineates growing zones [5] by environment and conflicting uses (e.g. Maryland Natural Resource Code 4-11A-05). Production can be optimized within a given footprint. Area incentives like credits or subsidies are structured at or above the municipal level—changing λλ within a jurisdiction—while shore facilities create point amenities. Multi-stakeholder boards (MSB) seek granular siting input, and increased municipal involvement [2]. This aids information gathering, and increases legitimacy [6].

Map of oyster suitability index and limited-purpose licenses in the Damariscotta River estuary, Maine. High value areas are saturated, and continue to infill in predictions.
Damariscotta River showing oyster suitability index (OSI). The field is a quadratic reconstruction of raster data on a triangular mesh (R2=0.72). Red is existing limited-purpose licenses (N=91); blue predicted locations (N=100) based on SBM assumptions. Hi-res.

Data: ME OIT, UMaine, Oceanicsdotio

Potential drawbacks include exclusion, and prolonged process. Neighborhood attitudes as expressed at hearings [3] can be used to create probabilities of opposition. This approaches zero when a community has few farms, complaints, or low willingness-to-pay. While towns and regional co-management groups shall not exclude aquaculture, they can engage in planning exercises to determine how siting can be structured in a desirable way through manipulation of the amenity field ($m-2y-1).

This is just one of many methods we use to develop strategic plans for water quality management.

  1. NOAA Marine Aquaculture Strategic Plan FY 2016-2020.
  2. Governor’s Task Force on the Planning and Development of Marine Aquaculture (2004).
  3. Evans et al. (2017). Ag. & Resource Econ. Rev.
  4. Snyder et al. (2017). Fron. in Mar. Sci.
  5. Sanchez-Jerez et al. (2016). Aqua. Env. Inter.
  6. Cash et al. (2003). SSRN E. Journal.