Quantitative Validation of a Habitat Suitability Index for Oyster Restoration

Abstract

Habitat suitability index (HSI) models provide spatially explicit information on the capacity of a given habitat to support a species of interest, and their prevalence has increased dramatically in recent years. Despite caution that the reliability of HSIs must be validated using independent, quantitative data, most HSIs intended to inform terrestrial and marine species management remain unvalidated. Furthermore, of the eight HSI models developed for eastern oyster (Crassostrea virginica) restoration and fishery production, none has been validated. Consequently, we developed, calibrated, and validated an HSI for the eastern oyster to identify optimal habitat for restoration in a tributary of Chesapeake Bay, the Great Wicomico River (GWR). The GWR harbors a high density, restored oyster population, and therefore serves as an excellent model system for assessing the validity of the HSI. The HSI was derived from GIS layers of bottom type, salinity, and water depth (surrogate for dissolved oxygen), and was tested using live adult oyster density data from a survey of high vertical relief reefs (HRR) and low vertical relief reefs (LRR) in the sanctuary network. Live adult oyster density was a statistically-significant sigmoid function of the HSI, which validates the HSI as a robust predictor of suitable oyster reef habitat for rehabilitation or restoration. In addition, HRR had on average 103-116 more adults m −2 than LRR at a given level of the HSI. For HRR, HSI ≥ 0.3 exceeded the accepted restoration target of 50 live adult oysters m −2 . For LRR, the HSI was generally able to predict live adult oyster densities that meet or exceed the target at HSI ≥ 0.3. The HSI indicated that there remain large areas of suitable habitat for restoration in the GWR. This study provides a robust framework for HSI model development and validation, which can be refined and applied to other systems and previously developed HSIs to improve the efficacy of native oyster restoration.

Integrating Larval Dispersal, Permitting, and Logistical Factors Within a Validated Habitat Suitability Index for Oyster Restoration

“…To determine the form of the relationship between HSI and normalized oyster density, we used a global curve fitting program (Systat, 2007) to fit linear, exponential, quadratic and sigmoid functions to the relationships based on functions selected in previous HSI studies (Soniat and Brody, 1988;Reiley et al, 2014;Theuerkauf and Lipcius, 2016). Akaike Information Criterion (second-order bias correction estimator, AICc) was used to verify the best fitting model of the four possible functions.…”

“…Substantial changes to estuarine ecosystems over time may preclude the usefulness of historical records for present-day site selection (Jackson et al, 2001). More recently, HSI models have been developed to inform the oyster restoration site selection process (Soniat and Brody, 1988;Mann and Evans, 2004;Barnes et al, 2007;Starke et al, 2011;Beseres Pollack et al, 2012;Linhoss et al, 2016; Theuerkauf and Lipcius, 2016). These models have included many factors relevant to oyster biology and subsidence of artificial reefs, such as salinity and sediment type.…”

“…However, these models have generally not included larval dispersal relevant to recruitment dynamics and population persistence (but see ElsaBer et al, 2013), permitting factors relevant to restoration permit acquisition, or logistical factors relevant to material deployment and public access. Furthermore, validation is often absent from HSI models for oyster restoration and where present, is generally based on a single year of data (e.g., density or production Soniat and Brody, 1988;Cho et al, 2012;Theuerkauf and Lipcius, 2016), which may not reflect long-term population persistence.…”

Reef height drives threshold dynamics of restored oyster reefs

“…Study sites were chosen based on standard restoration site criteria: water depth < 3 m, sand to muddy-sand bottom, and close proximity to oyster broodstock (Woods et al 2004, Theuerkauf & Lipcius 2016. Sites within rivers represented a range of energetic conditions, as characterized by their geographic location, fetch, and sediment type, with one highenergy (GWR1, LR2) and one low-energy (GWR2, LR1) site in each river.…”

“…Recent studies have identified oyster reef geometry, particularly height above the seabed, as an important factor driving restoration success, presumably due to positive feedbacks between reef structure, hydrodynamics and resulting population dynamics (Lenihan 1999, Powers et al 2009, Schulte et al 2009, Theuerkauf & Lipcius 2016. Lenihan (1999) determined that oyster growth and survival was highest on crests of reefs >1.0 m while sedimentation and mortality was highest at the base of reefs and on short reefs (0.1 m).…”