Quantitative Validation of a Habitat Suitability Index for Oyster Restoration

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

Habitat Suitability Index for Crassostrea Virginica within the Chesapeake Bay using GIS

The eastern oyster (Crassostrea virginica) resides within the Chesapeake Bay and their oyster reefs act as a habitat for many other species in the Bay. Within the Chesapeake Bay, the eastern oyster has optimal conditions that are best suited for its growth and survival, however that may be negatively affected by current changes to the Bay such as water pollution from fertilizer and animal waste, sea level rise, and ocean acidification. Therefore, it is important to find the locations within the Chesapeake Bay where optimal conditions for the eastern oyster are met because they are a critical species to the health of the Bay and the surrounding community. I created a habitat suitability index for the eastern oyster using ArcMap, a geographic information system software. The habitat suitability index incorporates data on pH, dissolved oxygen, temperature, salinity, total suspended solids, Secchi depth, and chlorophyll a. These data were obtained from monitoring stations (n = 19), provided by the Chesapeake Bay Program. Since the monitoring stations only have the water quality values for their location, spatial interpolation was done using inverse distance weighting to estimate the surrounding water quality values. This area was found by overlaying interpolated values for each variable to determine which areas of the Bay satisfy the habitat requirements for the oyster, as reported in the literature. This information would be useful to anyone seeking to grow the oyster populations or focus energy on protecting them. It was discovered that the portion of the Bay that is best suited for eastern oysters is found between Annapolis and St. Leonard. The area of the overall optimal region for eastern oyster suitability is 59770.415hectares

Assessment of habitat suitability index of Capoeta species in the Caspian Sea and Namak Lake basins, Iran

Habitat suitability index (HSI) models are usually used to forecast habitat quality and species distributions and are used to develop biological studies, management priorities and anticipate possible changes under different management or climate change situations. This study was conducted to identify the habitat suitability index of three species namely, Capoeta    buhsei, C.  razii and C. alborzensis in the Kordan, Taleghan and Jajrood Rivers, respectively. At each station, environmental variables including temperature, dissolved oxygen, pH, EC, TDS and hydrological parameters such as flow velocity, depth, width, average diameter of stones and amount of phosphate, nitrate and ammonium were measured. The results showed that suitable habitats for these species are those with a high stone diameter, high temperature, low flow velocity and in areas where the width of the river is low. With respect to the abundance of fishes sampled in this study, the central and lower regions of the Jajrood and Kordan Rivers and the stations far from the dam on the Taleghan River are favorable habitats for the studied Capoeta species.

A Comparison of Occupied and Unoccupied Sharp-Tailed Grouse Habitat in Montana

The sharp-tailed grouse (Tympanuchus phasianellus) was once present throughout the state of Montana. The species was extirpated in Montana west of the Continental Divide by the late 2000’s, while healthy populations still exist east of the Continental Divide. We compared key habitat components important to sharp-tailed grouse survival in occupied areas east of the Divide to unoccupied areas west of the Divide. We measured vegetative variables related to nesting, brood-rearing, and wintering habitat requirements in 3 occupied study areas and 4 unoccupied study areas during the spring of 2015. Habitat Suitability Index scores were calculated for nesting and brood-rearing. Habitat Suitability Index averages show habitat in the Blackfoot valley to be most suitable for sustaining a sharp-tailed grouse population, habitat in the Bitterroot valley to be potentially suitable, and habitat in Drummond and in the Mission Valley to be unsuitable at this time. These results suggest that the Blackfoot and Bitterroot valleys may contain suitable habitat for a potential sharp-tailed grouse reintroduction

A Habitat Suitability Index Model for Ruffed Grouse on the Cumberland Plateau

Two Habitat Suitability index models were created for ruffed grouse (Bonasa umbellus) in the Cumberland Plateau physiographic region of Tennessee. One model evaluated winter habitat and the other evaluated brood habitat. The model for winter habitat used four variables to evaluate habitat suitability, including proximity to evergreen shrub thickets, habitat diversity within home range size, ageclass of the overstory and overstory forest group. The brood habitat model used four variables to evaluate habitat for young broods, including proximity to daylighted roads, habitat diversity within home range, overstory ageclass, and overstory forest group. The models were applied to the currently inventoried portion (approximately 30%) of the Catoosa Wildlife Management Area. These models were used to explore the assumption that there are two major limiting factors for grouse in Tennessee, winter habitat and brood habitat, and to determine the location of the best of these habitats in relation to each other on the Catoosa Wildlife Management Area. Very little of the currently inventoried area had high suitability under either model. On a scale of 0-1.0 where 1.0 is optimal habitat, the winter habitat model classified only 1.06% of the currently inventoried area greater than 0.75 The brood habitat model classified only 0.30% of the inventoried area greater than 0.75 Areas with HSI values above 0.75 for both models were often within home range size, but the scarcity of high quality habitat on Catoosa indicates grouse densities will remain low without increased forest management for their needs

The Status of a PA Endangered Bird- the Upland Sandpiper

The upland sandpiper (Bartramia Longuardia) has experienced a steep population decline in the northeastern U.S. since the mid-20th Century. In Pennsylvania it was found in less than 0.5% of atlas blocks during the Second Atlas of Breeding Birds in Pennsylvania project (2nd PBBA; 2004-09) and breeding was confirmed at only two locations. Due to continued declines and a small population size, the upland sandpiper was listed as PA endangered in 2012. During May 2012 the areas around 15 2nd PBBA upland sandpiper sightings were resurveyed by Gettysburg College students and volunteer birdwatchers. The aim was to establish whether the atlas records related to persisting populations. We used five-minute audio playback at up to 10 locations within 4km of the atlas sightings. A maximum of 19 pairs/calling male upland sandpipers were found across the state in 2012, most of them on or close to reclaimed surface mines. However, locating such a scarce species can be problematic, and it is still not known to what extent the species is under-reported. To help direct future surveys we analyzed data from the 2nd PBBA and the 2012 survey to produce a habitat suitability model for the upland sandpiper in Pennsylvania. We used a GIS framework to determine areas of suitable habitat and then stratified these by proximity to recent (2004-2012) upland sandpiper sightings. We recommend that our suitability model be used to establish a sampling protocol for more thorough statewide upland sandpiper survey every five years, in order that the species’ precarious status can be closely monitored

Spatial prediction of species’ distributions from occurrence-only records: combining point pattern analysis, ENFA and regression-kriging

A computational framework to map species’ distributions (realized density) using occurrence-only data and environmental predictors is presented and illustrated using a textbook example and two case studies: distribution of root vole (Microtes oeconomus) in the Netherlands, and distribution of white-tailed eagle nests (Haliaeetus albicilla) in Croatia. The framework combines strengths of point pattern analysis (kernel smoothing), Ecological Niche Factor Analysis (ENFA) and geostatistics (logistic regression-kriging), as implemented in the spatstat, adehabitat and gstat packages of the R environment for statistical computing. A procedure to generate pseudo-absences is proposed. It uses Habitat Suitability Index (HSI, derived through ENFA) and distance from observations as weight maps to allocate pseudo-absence points. This design ensures that the simulated pseudo-absences fall further away from the occurrence points in both feature and geographical spaces. The simulated pseudo-absences can then be combined with occurrence locations and used to build regression-kriging prediction models. The output of prediction are either probabilitiesy of species’ occurrence or density measures. Addition of the pseudo-absence locations has proven effective — the adjusted R-square increased from 0.71 to 0.80 for root vole (562 records), and from 0.69 to 0.83 for white-tailed eagle (135 records) respectively; pseudo-absences improve spreading of the points in feature space and ensure consistent mapping over the whole area of interest. Results of cross validation (leave-one-out method) for these two species showed that the model explains 98% of the total variability in the density values for the root vole, and 94% of the total variability for the white-tailed eagle. The framework could be further extended to Generalized multivariate Linear Geostatistical Models and spatial prediction of multiple species. A copy of the R script and step-by-step instructions to run such analysis are available via contact author’s website

Soft-Shell Clam (Mya Arenaria) Distribution & Abundance at Selected Sites in the Great Bay Estuary

Previous surveys (1996 to 2002) provided distribution and abundance data for soft-shell clam (Mya arenaria) populations in ten areas of the Great Bay and Piscataqua River estuaries identified as potentially good clam habitat. The present study was designed to complete the overall survey by sampling six remaining areas: Weeks Point, Brackett\u27s Point, Squamscott River mouth, Moody Point, Herods Cove, and Upper Little Bay (western shore). The objectives of the present project were to: (1) visually inspect the six study areas for the general distribution of sediment types and soft-shell clams, (2) quantitatively sample the six areas to determine densities of soft-shell clams, (3) produce GIS maps based on the survey data, and (4) assess clam distributions considering data from the present study and previous research. At each of the six sampling areas, the approximate boundary of potential clam habitat (=intertidal soft sediments) was determined by visual inspection at low tide. Notes were made on changes in major sediment types, the presence of clam siphon holes, and empty clam shells. At each site, nine to fourteen 0.125 m2 quadrats were haphazardly tossed onto the sediment surface, excavated to at least 20 cm depth using clam rakes, and all excavated sediments washed through a 5 mm mesh sieve. All clams retained on the sieve were measured (shell length to nearest mm with calipers), counted, and returned to the general area. A sample of the upper 5 cm of sediment was collected from each quadrat and stored at Jackson Estuarine Laboratory. Quadrat locations were geo-referenced using DGPS.The general environmental conditions in all six areas appeared suitable as soft-shell clam habitat. However, very few live clams were collected and very few empty shells were observed. From a total of 65 excavated quadrats, only 8 live clams were collected with mean densities ranging from 0.0 to 3.1/m2 at the six sites. It was concluded that none of the six areas were productive clam flats at the time of sampling, and they probably had not been in the recent past. Previous research and the present study indicate that many of the expansive intertidal flats in the Great Bay/Piscataqua River system have not been productive clam habitat for decades, probably since at least the 1940s in some areas. However, moderate to high densities of clams have been reported in some areas, particularly in sandy sediments. Previous research also showed high densities of early post-set clams in some areas, suggesting that spat mortality (probably predation effects) may be an important cause of low densities of larger clams in these areas. Future research should focus on sandy sediments and mixed soft sediments with cobble to better characterize the distribution and abundance of clams in the Great Bay/Piscataqua River system. Future research also should assess the role of predation on newly set spat in controlling clam populations