Date of Award

Fall 2024

Project Type

Thesis

Program or Major

Natural Resources

Degree Name

Master of Science

First Advisor

Adrienne Kovach

Second Advisor

Remington Moll

Third Advisor

Chris Elphick

Abstract

As climate change accelerates the rate of sea-level rise, salt marshes and the critical habitat they provide are increasingly threatened. The Saltmarsh Sparrow (Ammospiza caudacuta) is particularly vulnerable to such changes. Habitat loss and increased nest failure due to flooding put the species at a high risk of extinction within the next several decades. Restoration plans across New England aim to build salt marsh resiliency. To effectively prioritize Saltmarsh Sparrow conservation in these plans, it is essential to identify the features that predict Saltmarsh Sparrow breeding season habitat, so these features can be maintained and enhanced during a restoration project.In Chapter 1 we used point count data from 86 points surveyed during the 2022 breeding season to identify the best overall predictors of Saltmarsh Sparrow occupancy in New Hampshire. Great Bay National Estuarine Research Reserve (GBNERR) previously developed a model to identify Saltmarsh Sparrow habitat in New Hampshire, with features characterized at the marsh unit scale. While providing restoration priorities, it did not explicitly consider sparrow occupancy nor was it evaluated for efficacy in decision-making. We assessed the ability of these GBNERR covariates and local features (not included in the original model) to predict Saltmarsh Sparrow occurrence, ranking models using Akaike’s Information Criterion. Our study identified the best predictors of occupancy as percent high marsh cover and distance to nearest upland edge. Saltmarsh Sparrow occurrence probability increased with each. Both were local covariates that characterize fine-scale within-marsh variability. Covariates from the GBNERR Model, however, were less informative, with three of the seven indicating no relationship with occurrence probability. These included metrics of overall marsh quality: percent Phragmites australis cover, the unvegetated to vegetated ratio, and a subsidence ditch impact score. This chapter highlights the role of fine-scale variability in Saltmarsh Sparrow habitat selection, underscores the importance of using local data to ground-truth models, and provides a framework to assess other models that identify restoration priorities. In Chapter 2, we used Saltmarsh Sparrow nest location data and a new high-resolution tidal marsh vegetation spatial dataset to identify the features that predict nest placement. These data included 131 nests and paired random points surveyed across two breeding seasons (2022 and 2023) and eight marshes in New Hampshire. We predicted greater Spartina patens cover (a flood intolerant high marsh vegetation species) at nesting locations. Nesting in these higher elevation areas is likely a key adaptation in response to flooding, the main cause of nest failure. We used paired t-tests to identify differences in characteristics between nests and paired random points, finding greater Spartina patens cover, thatch depth, and elevation immediately at nests. In contrast, we found greater short-form Spartina alterniflora (a species tolerant to more frequent flooding) and less Spartina patens and Distichlis spicata cover at nests compared to random points, when examining vegetation community within a 5-m radius using the remotely sensed data layer. While short-form Spartina alterniflora can provide greater structural complexity to hold nests up during flooding, this result may also reflect the overall heterogeneity of the marsh platform with Saltmarsh Sparrow nest site selection on a microhabitat scale within a matrix of grasses. Our findings also underscore the critical role that even slight differences in elevation and water height play in Saltmarsh Sparrow nest placement, with a mean difference of approximately 4 cm between nests and random points. This is promising for restoration techniques that provide pockets of high-quality Spartina patens (microtopography) and build elevation (sediment placement). In New Hampshire, GBNERR developed the New Hampshire Salt Marsh Plan (hereafter referred to as the Plan) to guide where restoration should be implemented to achieve overall marsh resiliency. The Plan ranks marshes in current condition, vulnerability to sea-level rise, and adaptation potential, and provides management recommendations based on rankings for each marsh. In Chapter 3, we examined how marshes that support Saltmarsh Sparrow, feature in the Plan. We took a two-tiered approach first using relative abundance data from point count surveys conducted at 86 survey points across NH, to examine how marshes where Saltmarsh Sparrows were detected feature in the plan. We then used rapid assessment surveys to quantify Saltmarsh Sparrow reproductive metrics at select sites and examined how these marshes with nesting featured in the Plan. We found that marshes where Saltmarsh Sparrows were detected and those with signs of reproduction ranked high in current condition and adaptation potential. Many also ranked high in vulnerability to sea-level rise, underscoring the need for action to promote sea-level rise resiliency and conserve Saltmarsh Sparrows. In some cases, a mismatch emerged between how well a site supported Saltmarsh Sparrows and its current condition, with the species notably absent from some marshes despite high current condition scores. This finding suggests that key metrics of overall marsh quality do not directly relate to whether a marsh supports local Saltmarsh Sparrow populations or nesting. We provide suggestions to incorporate Saltmarsh Sparrow specific considerations, such as avoiding restoration during the breeding season and light touch restoration techniques, into the Plan’s recommended management options. Ultimately, we highlight the importance of integrating considerations for vulnerable wildlife into state plans aimed at enhancing ecosystem resiliency in the face of climate change.

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