Date Published: January 25, 2019
Publisher: Public Library of Science
Author(s): Seth J. Theuerkauf, David B. Eggleston, Brandon J. Puckett, Just Cebrian.
Geospatial habitat suitability index (HSI) models have emerged as powerful tools that integrate pertinent spatial information to guide habitat restoration efforts, but have rarely accounted for spatial variation in ecosystem service provision. In this study, we utilized satellite-derived chlorophyll a concentrations for Pamlico Sound, North Carolina, USA in conjunction with data on water flow velocities and dissolved oxygen concentrations to identify potential restoration locations that would maximize the oyster reef-associated ecosystem service of water filtration. We integrated these novel factors associated with oyster water filtration ecosystem services within an existing, ‘Metapopulation Persistence’ focused GIS-based, HSI model containing biophysical (e.g., salinity, oyster larval connectivity) and logistical (e.g., distance to nearest restoration material stockpile site) factors to identify suitable locations for oyster restoration that maximize long-term persistence of restored oyster populations and water filtration ecosystem service provision. Furthermore, we compared the ‘Water Filtration’ optimized HSI with the HSI optimized for ‘Metapopulation Persistence,’ as well as a hybrid model that optimized for both water filtration and metapopulation persistence. Optimal restoration locations (i.e., locations corresponding to the top 1% of suitability scores) were identified that were consistent among the three HSI scenarios (i.e., “win-win” locations), as well as optimal locations unique to a given HSI scenario (i.e., “tradeoff” locations). The modeling framework utilized in this study can provide guidance to restoration practitioners to maximize the cost-efficiency and ecosystem services value of habitat restoration efforts. Furthermore, the functional relationships between oyster water filtration and chlorophyll a concentrations, water flow velocities, and dissolved oxygen applied in this study can guide field- and lab-testing of hypotheses related to optimal conditions for oyster reef restoration to maximize water quality enhancement benefits.
Recovery of ecosystem services is often cited as a principal motivation for habitat restoration activities . Yet, the quantity and quality of ecosystem services provided by restored habitats can vary greatly in space and time and are often mediated by restored habitat quality [2, 3, 4]. Geospatial habitat suitability indices (hereafter ‘HSI’) have emerged as powerful, spatially explicit decision support tools to guide habitat restoration of areas with the highest probable habitat quality . HSIs are commonly generated through application of wildlife-habitat relationships with relevant geospatial environmental data within a Geographic Information System (GIS) to develop a composite HSI score with a range of 0 to 1, representing unsuitable (0) to optimal (1) habitat . Previous efforts have sought to map and quantify spatial variation in ecosystem services provided by existing habitats (e.g., ), however, relatively few efforts have attempted to assess where habitat restoration might provide enhanced levels of ecosystem service provision relative to other locations. Given the need and desire to maximize provision of ecosystem services associated with habitat restoration efforts, as well as the often significant associated costs of restoration (e.g., US$10,000 per ha per cm of substrate material for oyster habitat restoration in Chesapeake Bay ), there is a need for a geospatial modeling framework to inform where habitat restoration efforts might be most successful and yield the greatest ecosystem services benefit.
Habitat suitability indices (HSI) are valuable, quantitative tools to guide spatial planning of habitat restoration efforts in locations with the greatest potential for success [5, 6, 17]. These models, however, have generally not incorporated factors of direct relevance to siting restoration in locations that would maximize ecosystem service provision. Furthermore, given the financial costs and varying goals attributed to specific habitat restoration projects (e.g., restoring oyster reefs to support oyster fishery harvest, provide shoreline stabilization benefits, or to provide essential fish habitat / recreational fishing opportunities), multiple HSI models optimized for multiple restoration goals within a given waterbody are warranted to identify locations that are ‘win-win’ and locations where ‘tradeoffs’ among management goals must be considered. Novel variables associated with oyster water filtration ecosystem services were integrated within an existing, ‘Metapopulation Persistence’ optimized GIS-based HSI model containing biophysical (e.g., salinity, oyster larval connectivity) and logistical (e.g., distance to nearest restoration material stockpile site) variables to identify suitable locations for oyster restoration that maximize long-term persistence of restored oyster populations and water filtration ecosystem service provision. Furthermore, the ‘Water Filtration’ optimized HSI was compared to the HSI optimized for ‘Metapopulation Persistence,’ as well as a hybrid model that optimized for both water filtration and metapopulation persistence. We compared both suitability patterns and optimal locations (i.e., locations corresponding to the top 1% of suitability score) identified within and between three HSI scenarios optimized for varying restoration goals. The conceptual framework utilized in this study, wherein restoration goal-specific HSIs were developed and “win-win” (i.e., optimal restoration locations identified in multiple goal-specific HSIs) versus “tradeoff” (i.e., optimal restoration locations identified in a single goal specific HSI) restoration locations were identified, can inform development of similar restoration goal-specific HSI models in other systems.