Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Data Files
• Related Publications
• Parameters
• Project Information
• Funding

Literature review:
First, we determined the variety of reef characteristics reported by studies investigating nekton recruitment enhancement by oyster reefs using citations from the reference list of a recently completed meta-analysis (zu Ermgassen et al. 2016). We identified nekton families that were regularly reported at oyster reef and control habitats, including both resident (i.e., species that feed, breed, and shelter on reefs long after initial recruitment, Coen et al. 1999; Harding and Mann 2000) and transient (i.e., species that recruit to structured habitats but are more widely distributed across multiple habitats after recruitment, Harding and Mann 2001) reef-associated species. We also performed forward searches in Google Scholar on two published syntheses: Peterson et al. (2003) and zu Ermgassen et al. (2016). We retained studies that met the following criteria: 1) authors quantified density or relative abundance of target nekton families at both oyster reefs (or experimental units that contained oyster shell and served as a mimic for reef habitat; e.g., Humphries et al. 2011) and unstructured mud or sand habitats within the same study; 2) restored reefs used oyster shell, including shell piles, cultch, bagged shell, or shell piles from other species (e.g., surf clams) if topped by oyster shell; 3) restored reefs were within the tidal extent of natural reefs (< 10 m deep relative to mean low water [MLW] at the base of the reef; Kennedy and Sanford 1999), 4) fishing gear(s) quantitatively censused juveniles; and 5) authors reported densities or abundances of target nekton by species or family.

Data Extraction:
We extracted densities or abundances, measures of spread (standard deviation or standard error), and sample sizes of each nekton species from oyster reefs and their paired unstructured control habitat patches. We extracted data for nine nekton families, including reef residents: toadfish (Batrachoididae), blennies (Blenniidae), gobies (Gobiidae), and skilletfish (Gobiesocidae, which were later removed due to limited data availability); and reef transients: grunts (Haemulidae), snappers (Lutjanidae), swimming crabs (Portunidae), drums (Sciaenidae), and porgies (Sparidae; Table 1 of Davenport et al. 2021). We normalized densities to mean individuals m-2, abundances to mean individuals per sample (relative abundances), and measures of spread to one standard error of the mean (Appendix S2 of Davenport et al. 2021). We extracted tidal zone (subtidal or intertidal), reef type (restored or natural), restoration method (reefs restored with or without live oysters), and when available, reef size (standardized to m2), vertical relief (distance from bare sediment to the highest point on the reef, standardized to m), tidal elevation (at the base of the reef, in m relative to MLW), adult oyster density (individuals m-2 > 75 mm in shell height, or specified as adult by the authors), and the year of restored reef construction, from which we calculated reef age (Appendix S1: Table 1; Appendix S2 of Davenport et al. 2021).

Analyses:
To compare nekton recruitment to oyster reefs versus unstructured control habitat, we calculated log response ratios (LRRs, Hedges et al. 1999) with 95% confidence intervals by family (Appendix S2 of Davenport et al. 2021). An LRR with CIs > 0 implies that nekton recruitment was enhanced by oyster reefs, an LRR with CIs < 0 implies the opposite, and an LRR with CIs that include 0 implies no difference in recruitment between oyster reef and control habitats. For each research question, we assessed data publication bias with funnel plots (Appendix S3 of Davenport et al. 2021) and data availability with mosaic and violin plots (Appendix S4 of Davenport et al. 2021).

To assess whether recruitment enhancement varied as a function of reef type (natural or restored) and nekton family, we conducted linear mixed model analyses separately for intertidal and subtidal reefs that included two categorical factors (reef type and nekton family) and their interaction as fixed effects, with study as a random effect. We conducted mixed model analyses separately by tidal zone since subtidal and intertidal habitats harbor different nekton communities (Lehnert and Allen 2002), and subtidal and intertidal oyster reefs are distributed unevenly in our database: intertidal reefs are more prevalent on the Atlantic coast and subtidal reefs are more common in the Gulf of Mexico (Fig. 1; Appendix S1: Table S1 of Davenport et al. 2021). Furthermore, the reef characteristics in our database differed across tidal zones (Appendix S4: Fig. S1-S12 of Davenport et al. 2021). We removed any family that was represented by fewer than three independent studies and/or fewer than 10 independent LRRs ("NA" on Fig. 2 of Davenport et al. 2021). Results of randomization and resampling in support of these criteria are presented in Appendix S5 of Davenport et al. (2021).

To evaluate the effects of restored reef characteristics (i.e., reef size, vertical relief, and age) on recruitment enhancement, we focused on restored reefs only, and performed linear mixed effect regression models with orthogonal polynomials (first and second order) for the continuous reef characteristics as fixed effects, and study as a random effect. We conducted separate analyses for each reef characteristic, nekton family, and tidal zone. We did not model families represented by fewer than three independent studies and/or 10 independent LRRs covering different values of the reef characteristics (e.g., reef sizes, vertical reliefs, or ages; "insufficient data" in Figs. 3-8 of Davenport et al. 2021), and results are not reported or plotted for models that did not converge. Since not all families were represented at all values of each reef characteristic (e.g., all vertical reliefs or sizes), we performed separate analyses for each family and included all available data (but for combined-family approaches, see Appendix S2 (Davenport et al. 2021) for methods and Appendix S5 of Davenport et al. 2021 for results ). We also examined the influence of tidal elevation on recruitment enhancement for each family using linear mixed effect regression models with orthogonal polynomials (first and second order) for tidal elevation as a fixed effect and study as a random effect (Appendix S5 of Davenport et al. 2021). Where models indicated that predictor variables are on substantially different scales (i.e. reef size) we rescaled using natural log transformation.

All models were weighted by sample size (Appendix S2 of Davenport et al. 2021). All analyses were conducted in R 3.6.1 (R Core Team, 2019) on the RStudio IDE 1.2.1335 (RStudio Team, 2019).

BCO-DMO processing description:
- Adjusted field/parameter names to comply with BCO-DMO naming conventions;
- Missing data identifier ‘NA’ replaced with 'nd' (BCO-DMO's default missing data identifier); 
- Added a conventional header with dataset name, PI names, version date;
- Removed commas from the "embayment" column;
- Rounded oys_fish, con_fish, and LRR to 3 decimal places;
- Replaced "Humphries 2011" with "Humphries et al. 2011" in the study_name column.

NSF Award Abstract:
Disease outbreaks in the ocean are increasing, causing losses of ecologically important marine species, but the factors contributing to these outbreaks are not well understood. This 5-year CAREER project will study disease prevalence and intensity in two marine foundation species - the seagrass Zostera marina and the Eastern oyster Crassostrea virginica. More specifically, host-disease relationships will be explored to understand how genetic diversity and population density of the host species impacts disease transmission and risk. This work will pair large-scale experimental restorations and smaller-scale field experiments to examine disease-host relationships across multiple spatial scales. Comparisons of patterns and mechanisms across the two coastal systems will provide an important first step towards identifying generalities in the diversity-density-disease relationship. To enhance the broader impacts and utility of this work, the experiments will be conducted in collaboration with restoration practitioners and guided by knowledge ascertained from key stakeholder groups. The project will support the development of an early career female researcher and multiple graduate and undergraduate students. Students will be trained in state-of-the-art molecular techniques to quantify oyster and seagrass parasites. Key findings from the surveys and experimental work will be incorporated into undergraduate courses focused on Conservation Biology, Marine Biology, and Disease Ecology. Finally, students in these courses will help develop social-ecological surveys and mutual learning games to stimulate knowledge transfer with stakeholders through a series of workshops.

The relationship between host genetic diversity and disease dynamics is complex. In some cases, known as a dilution effect, diversity reduces disease transmission and risk. However, the opposite relationship, known as the amplification effect, can also occur when diversity increases the risk of infection. Even if diversity directly reduces disease risk, simultaneous positive effects of diversity on host density could lead to amplification by increasing disease transmission between infected and uninfected individuals. Large-scale field restorations of seagrasses (Zostera marina) and oysters (Crassostrea virginica) will be utilized to test the effects of host genetic diversity on host population density and disease prevalence/intensity. Additional field experiments independently manipulating host genetic diversity and density will examine the mechanisms leading to dilution or amplification. Conducting similar manipulations in two marine foundation species - one a clonal plant and the other a non-clonal animal - will help identify commonalities in the diversity-density-disease relationship. Further, collaborations among project scientists, students, and stakeholders will enhance interdisciplinary training and help facilitate the exchange of information to improve management and restoration efforts. As part of these efforts, targeted surveys will be used to document the perceptions and attitudes of managers and restoration practitioners regarding genetic diversity and its role in ecological resilience and restoration.