A test of the Swainson's warbler habitat suitability index model

Reiley, Bryan M.; Bednarz, James C.; Brown, Jeremy D.

doi:10.1002/wsb.414

Cited by 11 publications

(22 citation statements)

References 24 publications

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“…Normalized density was a statistically-significant exponential function of HSI, providing validity of the HSI as a robust predictor of suitable habitat for oyster sanctuary restoration in Pamlico Sound. Positive relationships between indices of abundance and HSI have been identified previously in validation studies, but the relationships have generally been linear or sigmoidal (Cho et al, 2012;Reiley et al, 2014;Theuerkauf and Lipcius, 2016). The exponential relationship between HSI and normalized density can be used, through inverse calculations, to determine HSI values needed to reach restoration targets (i.e., target normalized density of 2,000 generally occurs at HSI values > 0.45).…”

Section: Discussionmentioning

confidence: 93%

“…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.…”

Section: Model Validationmentioning

confidence: 99%

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

et al. 2018

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Habitat suitability index (HSI) models are increasingly used to guide ecological restoration. Successful restoration is a byproduct of several factors, including physical and biological processes, as well as permitting and logistical considerations. Rarely are factors from all of these categories included in HSI models, despite their combined relevance to common restoration goals such as population persistence. We developed a Geographic Information System (GIS)-based HSI for restoring persistent high-relief subtidal oyster (Crassostrea virginica) reefs protected from harvest (i.e., sanctuaries) in Pamlico Sound, North Carolina, USA. Expert stakeholder input identified 17 factors to include in the HSI. Factors primarily represented physical (e.g., salinity) and biological (e.g., larval dispersal) processes relevant to oyster restoration, but also included several relevant permitting (e.g., presence of seagrasses) and logistical (e.g., distance to restoration material stockpile sites) considerations. We validated the model with multiple years of oyster density data from existing sanctuaries, and compared HSI output with distributions of oyster reefs from the late 1800's. Of the 17 factors included in the model, stakeholders identified four factors-salinity, larval export from existing oyster sanctuaries, larval import to existing sanctuaries, and dissolved oxygen-most critical to oyster sanctuary site selection. The HSI model provided a quantitative scale over which a vast water body (∼6,000 km 2 ) was narrowed down by 95% to a much smaller suite of optimal (top 1% HSI) and suitable (top 5% HSI) locations for oyster restoration. Optimal and suitable restoration locations were clustered in northeast and southwest Pamlico Sound. Oyster density in existing sanctuaries, normalized for time since reef restoration, was a positive exponential function of HSI, providing validation for the model. Only a small portion (10-20%) of historical reef locations overlapped with current, model-predicted optimal and suitable restoration habitat. We contend that stronger linkages between larval connectivity, landscape ecology, stakeholder engagement and spatial planning within HSI models can provide a more holistic, unified approach to restoration.

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Section: Discussionmentioning

confidence: 93%

Section: Model Validationmentioning

confidence: 99%

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

et al. 2018

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“…Recent HSI validation studies have indicated that unvalidated HSIs can be unreliable indicators of habitat quality (Reiley et al, 2014). Although widely used, HSI models have been criticized as unreliable and lacking scientific rigor (Cole and Smith, 1983;Roloff and Kernohan, 1999).…”

Section: Introductionmentioning

confidence: 99%

“…Although widely used, HSI models have been criticized as unreliable and lacking scientific rigor (Cole and Smith, 1983;Roloff and Kernohan, 1999). Despite the potential cost associated with obtaining these independent datasets, the validation process is required to determine the reliability and utility of these models if they are to inform species conservation and management (Brooks, 1997;Tirpak et al, 2009;Reiley et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Quantitative Validation of a Habitat Suitability Index for Oyster Restoration

Theuerkauf

Lipcius

2016

Front. Mar. Sci.

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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.

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Catastrophic storms, forest disturbance, and the natural history of Swainson's warbler

Graves

2024

Ecology and Evolution

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The core breeding range of Swainson's warbler (Limnothlypis swainsonii) overlaps a zone of exceptionally high tornado frequency in southeastern North America. The importance of tornadoes in creating breeding habitat for this globally rare warbler and other disturbance‐dependent species has been largely overlooked. This paper estimates tornado frequency (1950–2021) and forest disturbance in the 240 counties and parishes in which breeding was documented from 1988 to 2014. The frequency of destructive tornadoes (EF1‐EF5) varied 6‐fold across the breeding range with a peak in the Gulf Coast states. Counties from east Texas to Alabama experienced the lowest median return interval of 5.4 years per 1000 km2, resulting in approximately 2477 ha of forest damage per 1000 km2 per century, based on current forestland cover. Tornadoes were significantly less frequent north and east of the core breeding range, with return intervals increasing to 9.1 years per 1000 km2 for breeding counties on the Atlantic coastal plain, 10.2 years per 1000 km2 in the Ozark Mountains, and 32.3 years per 1000 km2 in the Appalachian Mountains. Breeding counties within 150 km of the coastline from east Texas to North Carolina are also subjected to the highest frequency of hurricanes in the Western Hemisphere. Hurricanes often cause massive forest damage but archived meteorological and forestry data are insufficient to estimate the aggregate extent of forest disturbance in breeding counties. Nevertheless, the combined impact of tornadoes and hurricanes in the pre‐Anthropogenic era was likely sufficient to produce a dynamic mosaic of early‐successional forest crucial for the breeding ecology of Swainson's warbler. To ensure the long‐term survival of this rare warbler, it is advisable to develop habitat management plans that incorporate remote sensing data on early‐successional forest generated by catastrophic storms as well as anthropogenic activities.

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A test of the Swainson's warbler habitat suitability index model

Cited by 11 publications

References 24 publications

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

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

Quantitative Validation of a Habitat Suitability Index for Oyster Restoration

Catastrophic storms, forest disturbance, and the natural history of Swainson's warbler

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