Habitat Suitability Index Values Research Articles

Fish Module ‐ A prognostic tool for modeling the optimal environmental conditions for fish

This article discusses the service called the Fish Module for the predictive determination of the optimal environmental conditions for the occurrence of sprat, herring, cod, and flounder on the example of fish found in the southern Baltic Sea (in particular in the Gulf of Gdańsk region). The Fish Module utilizes data from the EcoFish ecohydrodynamic model and then uses fuzzy logic and fish preference data to calculate the Habitat Suitability Index (HSI). Data on fish preference were determined based on 587 expeditions during which physicochemical parameters of the sea were recorded. Our analysis determined threshold HSI values below which successful catches are unlikely for sprat, herring, and cod, confirming the system's effectiveness in identifying locations with favorable environmental conditions for these species. Fishermen are advised to select routes with specific HSI thresholds to achieve greater efficiency in fishing. Furthermore, the analysis revealed that fishing durations do not necessarily correlate with higher catches, emphasizing the importance of selecting suitable routes based on favorable environmental conditions for fish habitat. We expect the Fish Module to be the most demanded product of the FindFISH project.

Spatial-Temporal Distribution of Fish Larvae in the Pearl River Estuary Based on Habitat Suitability Index Model.

The spawning grounds are important areas for the survival and reproduction of aquatic organisms and play an important role in the replenishment of fishery resources. The density of fish larvae in the Pearl River Estuary (PRE) was analyzed to establish Habitat Suitability Index (HSI) based on marine environmental factors. Survey data and satellite remote sensing data, including sea surface temperature, sea surface salinity and chlorophyll a concentration, from 2014 to 2017 during April-September were analyzed. Results showed that the accuracy of the HSI model based on the larval density and environmental factors was more than 60%, and the distribution trend of HSI was consistent with the distribution trend of larval density. The HSI models constructed based on Arithmetic Mean Model (AMM), Geometric Mean Model (GMM) and Minimum Model (MINM) methods can better predict the spatial-temporal distribution of larvae in the PRE. Among them, the accuracy of the HSI model constructed by the AMM and GMM methods was the highest in April (71%) and September (93%); the accuracy of the HSI model constructed by the MINM method was the highest in June (70%), July (84%) and August (64%). In general, the areas with high HSI values are mainly distributed in the offshore waters of the PRE. The spatial-temporal distribution of larvae in the PRE was influenced by monsoon, Pearl River runoff, Guangdong coastal currents and the invasion of high-salinity seawater from the outer sea.

Habitat changes and catch rate variability for greater amberjack in the Taiwan Strait: The effects of El Niño–southern oscillation events

El Niño–Southern Oscillation (ENSO) is a crucial oceanographic phenomenon that leads to interannual fluctuations in the climate and ecosystem productivity of tropical and subtropical areas. These fluctuations affect the suitability of habitats for many commercial fish species. However, detailed information on the effects of this major phenomenon and the resulting environmental changes on the habitat and catch rates of the economically and ecologically crucial species of the greater amberjack (Seriola dumerili) in the Taiwan Strait (TS) is lacking. In this study, we employed a weighted habitat suitability index (HSI) modeling method and used remotely sensed marine environmental data as well as data from recorders in Taiwanese fishing vessels (in 2014–2019) to understand the effects of ENSO events on the habitat suitability and catch rates for greater amberjack in the TS. Analysis of variance revealed that environmental factors substantially influenced greater amberjack habitats and catch rates during ENSO events across seasons. The catch rates were high in spring and summer in the southern and northern TS and in autumn and winter in the southern TS. The catch rates were higher in spring, summer, and autumn (>9.0 kg/h) in El Niño years, and in winter, the catch rates were higher in normal years (>12.0 kg/h) and lower in La Niña years. The predicted HSI for the southern and northern TS revealed that greater amberjack populations were predominantly distributed at 20–24°N and 24–28°N, respectively. Opposite habitat suitability was synchronously found in spring and summer during ENSO events, with higher HSI values recorded in spring in El Niño and normal years and higher HSI values recorded in summer in La Niña years. In winter, the HSI values of the southern and northern TS were higher in El Niño and normal years and substantially lower in La Niña years. Habitat suitability was extremely low in autumn. These findings imply that ENSO events play a key role in regulating environmental conditions and affect the catch rates and habitat suitability for the greater amberjack in the TS.

HabCluster: identifying the geographical boundary among intraspecific units using community detection algorithms in R

Conservation management for a species generally rests on intraspecific units, while identification of their geographic boundaries is necessary for the implementation. Intraspecific units can be discriminated using population genetic methods, yet an analytical approach is still lacking for detecting their geographic boundaries. Here, based on landscape connectivity, we present a raster-based geographical boundary delineation method, habCluster, using community detection algorithms. Community detection is a technique in graph theory used to identify clusters of highly connected nodes within a network. We assume that the habitat raster cells with better connections tend to form a continuous habitat patch than the others, thus making the range of an intraspecific unit. The method was tested on the gray wolf (Canis lupus) habitat in Europe and the giant panda (Ailuropoda melanoleuca) habitat in China. The habitat suitability index (HSI) maps for gray wolves and giant pandas were evaluated using species distribution models. Each cell in the HSI raster is treated as a node and directly connected with its eight neighbor cells. The edge weight between nodes is the reciprocal of the relative distance between the centers of the nodes weighted by the average of their HSI values. We implement habCluster using the R programming language with the inline C++ code to speed up the computing. We found that the boundaries of the clusters delineated using habCluster could serve as a good indicator of habitat patches. In the giant panda case, the clusters match generally well with nature reserves. habCluster can provide a spatial analysis basis for conservation management plans such as monitoring, translocation and reintroduction, and population structure research.

HSI model for early life stages of anchovy considering transport processes in Laizhou Bay

Marine fishes are sensitive to the environment during their early life stages. This study adopts a habitat suitability index (HSI) model to evaluate the environmental suitability for early stages of anchovy (Engraulis japonicus) in Laizhou Bay. Instead of calculating the suitability of spawning grounds and nursery grounds independently or the simple average of the two, an individual-based model is used to simulate the drifting trajectories of anchovy eggs to establish the link between a spawning ground and its corresponding nursery ground. The HSI of early life habitat is determined by averaging the HSI value of the paired two grounds. The model results suggest that a small patch at eastern Laizhou Bay (near 120.1 E°, 37.6 N°) is the most critical and suitable area for anchovy in early life stages. It can provide an appropriate habitat for anchovy eggs and allow the eggs to migrate to the inside of the bay with plenty of plankton, which would benefit the newly hatching larvae. The results indicate the significant impact of hydrodynamic transport on fishery recruitment process, which should not be neglected in habitat quality evaluation. The model adopted in this study is applied to anchovy as a case study, but it is also exportable to other species of commercial interest.

서식지 선호도 및 품질 평가 모형의 신뢰성 개선: 한국 고라니의 경우

Purpose: Predicting the occurrence of wild species at the landscape level is a crucial task for environmental managers and conservation biologists. Modeling and evaluating wildlife habitat quality based on the Geographic Information Systems (GIS) technique provides new opportunities for enhancing model predictability.<BR>Methods: We developed a GIS-based habitat suitability index (HSI) model for Korean water deer (Hydropotes inermis argyropus) in Chungnam province, Korea, where they are a significant cause of damage to vegetables and crops. The model was based primarily on logistic regression analysis and was used to assess the impact of multiple variables, such as landscape patterns and structures, topographic characteristics, and human disturbance, on habitat suitability for the species. After developing the model, we employed it to produce a habitat-suitability map.<BR>Results: The HSI model yielded a p-value of 0.339 (χ² = 9.033) and a 74.0% correct prediction rate for the overall predicted data. The model also demonstrated that 42.4% of the province is covered in poor-quality habitat, while Korean water deer prefer fair-quality habitats (mean HSI = 0.50). In addition, the observation probability increased when HSI values rose, meaning that the model has good predictive power.<BR>Conclusion: Associations between landscape patterns and habitat requirements could be utilized to build accurate, easy-to-apply, predictive models for the habitats of wild species. The HSI model and habitat-suitability map provide solid foundations on which to build effective wildlife management and Agri-Environment policies with local governments to conserve endangered species.

El Niño–Southern Oscillation impacts on jumbo squid habitat: Implication for fisheries management

Abstract Dosidicus gigas is an ecologically and economically important squid species extensively distributed in the eastern Pacific Ocean. Its habitat is extremely sensitive to climatic and environmental variability. The relationship between habitat pattern of D. gigas and El Niño–Southern Oscillation (ENSO, divided into the El Niño, ENSO‐neutral, and La Niña events) was assessed from 1950 to 2015, using a habitat suitability index (HSI) modelling approach including two crucial environmental variables: sea surface temperature (SST) and sea surface height anomaly (SSHA). On the basis of cross‐correlation analysis, it showed that both SST anomaly and SSHA were significantly positively related to the ENSO index. Moreover, a significantly negative association was found between the HSI values and the ENSO index. Due to the El Niño events, SST off Peru became higher and sea level rose, resulting in contracted areas of suitable SST and SSHA; consequently, suitable habitats for D. gigas dramatically decreased. In contrast, during the ENSO‐neutral and La Niña years, the extent of suitable SST and SSHA increased due to the colder water and lower sea level, and suitable habitat for D. gigas expanded. Moreover, the latitudinal gravity centre of HSI was significantly positively associated with the ENSO index. Relative to the ENSO‐neutral and La Niña years, a southward movement of the monthly preferred SST isotherm for D. gigas during the El Niño years could explain the occurrence of more suitable habitats in southern waters off Peru. These findings suggested that the ENSO event plays an important role in regulating environmental conditions off Peru and further affected the spatio‐temporal distribution of D. gigas habitat.

Assessing habitat suitability and habitat fragmentation for endangered Siberian cranes in Poyang Lake region, China

Poyang Lake is located in the middle and lower reaches of the Yangtze River in China. It is the most important wintering area for the endangered Siberian cranes. Identifying the scale characteristics of habitat selection for Siberian cranes is essential for habitat conservation. In this study, a habitat suitability index (HSI) model based on multiscale habitat features was developed to assess the distribution and fragmentation degree of the suitable habitat for Siberian cranes before and after the construction of the proposed Poyang Lake Hydraulic Project (PLHP). The habitat of the entire lake area was divided into four ranks on the basis of HSI values. 2D shallow-water equations (SWEs), combined with remote sensing and geographic information system technology, were utilized to determine the key habitat features. Results indicated that the established HSI model could effectively recognize the potentially suitable habitats for Siberian cranes in Poyang Lake. The highly suitable habitat in the wet year was larger than that in the dry year, and the complexity of patch shapes and patch fragmentation increased. The influence of the PLHP on the suitable habitat for cranes mainly depended on its regulated water level, and this project could promote the formation and reduce the fragmentation degree of the suitable habitat under a properly regulated water level in the dry year. However, a higher regulated water level may cause a considerable negative impact on the distribution of suitable habitats in both years. This study provided a quantitative method to evaluate the potentially suitable habitats for Siberian cranes, and it could serve as a reference for the water level management of the proposed PLHP.

Habitat suitability response to sea-level height changes: Implications for Ommastrephid squid conservation and management

Sea level rise, amplified by anthropogenic climate change, causes visible impacts on wildlife habitats in low-lying coastal areas. However, the potential consequences of sea level height (SLH) changes for pelagic fish habitats in the open oceans are poorly understood, especially for climate-sensitive Ommastrephid squid. In this study, the impacts of SLH changes were estimated under three different SLH change scenarios (5 cm, 20 cm, and 35 cm) for the western stock of winter-spring neon flying squid Ommastrephes bartramii, an ecologically- and commercially-important species in the northwest Pacific Ocean (NWPO). A habitat suitability index (HSI) modeling approach was applied to predict the habitat suitability of O. bartramii, using data from 2006 to 2014 for model construction and data from 2015 for model validation. Results showed that the decreasing catch-per-unit-effort (CPUE) of O. bartramii from 2006 to 2015 was highly correlated with the increases in sea level height (SLH). Significant positive relationships were found between the HSI values for latitudinal centers of gravity (LATGHSI) and SLH. The monthly-averaged HSI of O. bartramii was negatively correlated with the SLH, except in July and November. SLH scenarios revealed that the predicted suitable habitat (areas with HSI≥0.6) exhibited a decreasing trend with increasing SLH from August to October. In July and November, the suitable habitat initially increased in the +5 cm and +20 cm scenarios, but largely declined under the +35 cm scenario. The poor habitat (areas with HSI≤0.2) significantly increased under all SLH scenarios. A poleward shift of LATGHSI was observed under all scenarios. These findings suggest that the O. bartramii habitats in the NWPO are at risk to SLH changes and have important implications for better conservation and fishery management regarding pelagic short-lived Ommastrephid squid in global oceans.

Spatial Habitat Suitability Models of Mangroves with Kandelia obovata

Mangrove forests provide important estuarine ecosystem services but are threatened by rising sea levels and anthropogenic impacts. Understanding the habitat characteristics required for mangrove growth is significant for mangrove restoration and integrated management. This study aims to build spatial habitat suitability index (HSI) models for Kandelia obovata mangrove trees. Biological and habitat-related environmental data were collected in the Wazwei and Guandu wetlands in northern Taiwan. We adopted inundation frequency, soil sorting coefficient, and water salinity as the key environmental factors to build HSI models. The dependent variable of these environmental factors was the mangrove biomass per unit area. Significant differences were found for the mangrove biomass on different substrata and shore elevations. The tidal creek had the lowest elevation, and mangrove areas were found at the highest elevations. The oxidization level of the substrate under mangrove forests was high, indicating that the root system of mangroves could carry oxygen into the soil and result in oxidation. Human activities were found to lead to the reduced growth conditions of mangroves. The validation of the HSI model, considering the inundation frequency and soil sorting coefficient, proved to be reliable, with an accuracy ranging from 78% to 90%. A better simulation was found after revising the model by incorporating the factor of water salinity. The model forecast of the mangrove responses to the sea-level rise indicated an increase in the inundation frequency and thus an induced shift and shrinkage of the mangrove area. The increased HSI values of the bare mudflat area demonstrate an option for the potential restoration of mangrove trees. Given the findings of this study, we concluded that mangroves could spread from estuaries to upstream areas due to rising sea levels and might be limited by humanmade impacts. Restoring degraded floodplains is suggested for mangrove habitat rehabilitation.

A validated expert-based habitat suitability assessment for eagle owls in Limburg, the Netherlands

Motivated by the high turnover rate of the Eurasian eagle owl (Bubo bubo) population in the south of the province of Limburg, the Netherlands, which is linked to extremely high concentrations of PCBs (polychlorinated biphenyls) and DDE (dichlorodiphenyldichloroethylene) found in owl carcasses, a habitat suitability (HS) assessment for this region was conducted to identify possible sources of PCBs in the environment. Twelve environmental characteristics (ECs) that are known to influence the presence of the species were selected. With each EC, a suitability index (SI) was associated and a uninorm was used to aggregate these individual SIs into one overall HS index value. The HS assessment was validated using GPS tracking data of six adult eagle owls. Further, Ivlev’s electivity index and Manly’s habitat selection index were used to compare the area used with what is available in the landscape. To describe the former, we considered both the probability of occurrence and the home range of the tracked individuals. The resulting HS map shows that quarries and vegetation structures, such as hedgerows or solitary trees, are the main attractors for the species, though also forest edges, orchards, and tree and fruit nurseries attract the species in the study area. Hence, further field sampling campaigns to identify possible sources of poisoning should focus on parcels with these land covers. Such a prioritization of parcels becomes possible using our approach.

Climate-induced habitat suitability variations of chub mackerel Scomber japonicus in the East China Sea

Chub mackerel Scomber japonicus is an economically important fish species, extensively distributed in the East China Sea, the Yellow Sea and the Sea of Japan. Climate variability has strong impacts on its habitat. In this study, an integrated habitat suitability index (HSI) model was constructed to examine habitat suitability of S. japonicus in the East China Sea, and evaluate the relationship with the El Niño and La Niña events, with three crucial environmental variables (sea surface temperature (SST), sea surface height (SSH) and net primary production (NPP)) as predictors. The HSI model was developed using data over 2006–2013 and validated using data in 2014 and 2015. Results showed that the HSI model with the best model performance yielded robust predictions of habitat suitability for S. japonicus. The decreasing catch and CPUE (catch per unit effort) of S. japonicus during 2006–2015 were highly consistent with substantial shrinkage of suitable and optimal habitats, and enlargement of normal and poor habitats. Similar movement pattern was also found between the latitudinal gravity centers of fishing effort for S. japonicus fishery and the gravity centers of potential habitat. In addition, spatial correlation analysis indicated that the HSI value was significantly positively related to the SST anomaly (SSTA) and negatively correlated with the SSH anomaly (SSHA) and NPP anomaly (NPPA), on the main fishing ground between 25°–30 °N and 120°–130 °E. Furthermore, various intensity of the El Niño and La Niña event may lead to different variations in the habitat suitability of S. japonicus. Comparing to the very strong El Niño, the moderate El Niño events would yield rising SSTA and lowing SSHA and NPPA, leading to dramatically enlarged suitable habitat of S. japonicus. The habitat quality in La Niña events with different intensity depended on the local environmental variability on the fishing ground. Our findings suggested that the El Niño and La Niña events prominently affected the habitat suitability of S. japonicus in the East China Sea. However, the impacts varied with the intensity of each anomalous climatic event.

Effect of wind damage on the habitat suitability of saproxylic species in a boreal forest landscape

Many forest-dwelling species are dependent on deadwood. Sources of deadwood include competition- and senescence-related mortality of trees, and various damages. This study described a methodology for predicting the effect of wind damage on the amount of deadwood and suitability of the forest for saproxylic species. The methodology was used in a forested boreal landscape of 360 ha to analyze the effects of wind damage on the habitat quality for 27 groups of saproxylic species differing in their requirements for the species, size and decay stage of deadwood objects. A reference plan maximized net present value (MaxNPV) while others either minimized or maximized height differences between adjacent stands. Maximization of height differences resulted in high amount of wind damage and deadwood while minimizing height differences minimized wind damage and the amount of damage-related deadwood. The fourth plan maximized the average habitat suitability index (HSI) of the 27 groups of saproxylic species. The plans were compiled with and without even-flow harvesting constraints for three 10-year periods. Maximization of height differences between adjacent stands resulted in higher HSI values than obtained in the MaxNPV plan or in the plan than minimized height differences between adjacent stands. The average HSI of shade-demanding species correlated negatively with the amount of harvested timber. No strong correlations were found for light-demanding and indifferent species.

Do habitat measurements in the vicinity of Atlantic salmon (Salmo salar) parr matter?

AbstractAtlantic salmon, Salmo salar L., parr habitat characterisation is usually performed by in situ measures of key environmental variables taken at the exact fish location if the fishing gear allows precise pinpointing of this location, or in large sampling sections covering a river reach or mesohabitat, often ignoring variability in the immediate vicinity around individual fish. These data may be critically important in the development and validation of habitat preference models. The influences of seven increasing distances of measures, the variation of the number of considered measures and the depth of velocity measurement (bottom or 0.6 of the depth) in the calculations of HSI (Habitat Suitability Index) from a multiple‐experts fuzzy model of Atlantic salmon parr habitat were tested. When a parr was present, six measures collected in a 50‐cm radius around the fish to provide an average measure as input data and velocity measured at 60% of the depth gave the highest HSI values. These results show some potential for the use of an intermediate study scale, between micro‐ and mesohabitat, and questions how fish habitat conditions are currently measured.

Evaluating effects of rescaling and weighting data on habitat suitability modeling

Abundance index (AI), used to establish the suitability index (SI), provides critical information in habitat suitability index (HSI) modeling. The distributions of AIs derived from fisheries-independent surveys tend to be right skewed because of heterogenous distributions of fishes. The existence of large AI values and failure to consider it might result in underestimation of HSI values for most sampling areas. We compared the performance of HSI models based on original AIs (without any transformation) versus rescaled AIs (i.e., log-transformed AIs) using American lobster (Homarus americanus) along the coast of Gulf of Maine as an example. Impacts of weighting environmental variables on HSI modeling based on boosted regression tree (BRT) were also evaluated. Both cross-validation and predicted habitat suitability maps suggested that the weighted HSI model based on log-scaled AI data tended to yield a more reliable prediction of optimal habitats for American lobster. The unweighted HSI model based on the original AI data, however, tended to underestimate optimal habitats and overestimate suboptimal habitats. We recommend using log-transformed AIs and determining the weights of different environmental variables based on the BRT method in HSI modeling, especially when AI data are highly skewed.

Habitat suitability of Scapharca subcrenata (Lischke) in the shallow water of the Xiaoheishan Island

The habitat suitability index (HSI) model was used to identify potential sites for sustainable restoration of ark shell, Scapharca subcrenata (Lischke), in the shallow water of Xiaoheishan Island, using a geographic information system framework. The seven input variables of the HSI model were sediment composition, water temperature, salinity, dissolved oxygen, water depth, pH, and ammonia. A non-linear suitability function for each variable factor was used to transform the value into a normalized quality index ranging from 0 (nonsuitability) to 1 (best suitability). In present study, the analysis of habitat suitability was conducted for four seasons respectively. The majority of the study area has a high HSI value (>0.6) year round, which implies a strong suitability for restoration, with the optimal habitat located on the eastern side of the island. Correspondence analysis indicated that water temperature was the main factor causing seasonal variation, while sediment composition and water depth were the two major reasons for the differences in sites. The results of this work could provide support for restoration decision making through identification of potential sites for sustainable establishment of S. subcrenata.

Developing and testing a habitat suitability index model for Korean water deer (Hydropotes inermis argyropus) and its potential for landscape management decisions in Korea

ABSTRACTGeographic information system (GIS) and landscape-level data offer a new opportunity for modeling and evaluating the quality of wildlife habitats. Models of habitat quality have not been developed for some species, and existing models could be improved by incorporating updated information on wildlife–habitat relationships and habitat variables. We developed a GIS-based habitat suitability index (HSI) model for the Korean water deer (Hydropotes inermis argyropus), which often causes human–wildlife conflicts in the Chungnam Province of Korea because of industrialization and urbanization. The model is based on logistic regression analysis, which addresses the impact of multiple habitat variables, such as habitat components, topographic characteristics, and human disturbances. The model yielded a p-value of .289 (χ2 = 9.672) and 65.4% correct prediction level with the overall observation–prediction comparison data. The model demonstrated that a large portion of the province (61.6%) could be regarded as a poor habitat (mean HSI value of the province = 0.22), while the current habitats of the province could be considered of moderate quality (mean HSI value = 0.31). In addition, the chance of observation of the deer increases as the HSI level increases, which means that the model yields a good predictive power. Lastly, we used the model to produce a habitat suitability map. Our HSI model enabled us to quantify habitat preferences, which could be the basis for decision-making on habitat protection, mitigation, and enhancement of the Korean water deer. The proposed model is also applicable for improving and enhancing the existing management practices, as well as for establishing an effective wildlife protection policy.

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 values ≥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 values ≥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.

Spatiotemporal Variability of Suitable Habitat for American Lobster (Homarus Americanus) in Long Island Sound

A Habitat Suitability Index (HSI) model was developed using four environmental variables (bottom temperature, bottom salinity, depth, and bottom substrate type) and 29 years of spring and fall lobster surveys for evaluating the spatiotemporal variability of suitable lobster habitat in Long Island Sound (LIS). The suitability indices calculated for the four environmental variables were combined to form a composite HSI using an arithmetic mean model and geometric mean model. A cross-validation study was conducted to evaluate the predictive performance of the HSI models. Annual geographic information system maps of estimated HSI values were produced using Kriging interpolation for adult and juveniles in spring and fall from 1978 to 2012. The overall spatial distribution of suitable habitat for lobster was mainly concentrated in the western-central part of LIS during spring (April–June), but showed clustering patterns throughout LIS during fall (September–October). An examination of the temporal change in annual median HSI values identified possible time blocks when habitat conditions were extremely poor and revealed a statistically significant decreasing trend in availability of suitable habitat for juveniles during spring from 1978 to 2012. Spatiotemporal variability in availability of suitable habitat may imply changes in carrying capacity of LIS for the American lobster.

A Habitat Suitability Index (HSI) for the Western Prairie Fringed Orchid (Platanthera praeclara) on the Sheyenne National Grassland, North Dakota, USA

The Western Prairie Fringed Orchid (Platanthera praeclara) is a threatened species found on the Sheyenne National Grassland (SNG) in southeast North Dakota, USA. The SNG is subject to management for multiple uses including biodiversity conservation, livestock grazing and recreation. Therefore, there is a need for the development of indicators of suitable orchid habitat. The orchids are continuously monitored, but understanding of the relationship between landscape properties and orchid locations is limited. In this study data that characterize topography, moisture, and groundwater were used to construct indicators of landscape suitability and an overall Habitat Suitability Index (HSI) for the orchid. A LiDAR-derived DEM and groundwater well observations were used to develop landscape indicators. The Topographic Wetness Index (TWI: a measure of moisture on the landscape), the Topographic Position Index (TPI: a measure of position on the landscape), and the distance to groundwater (DTG: a measure of the distance from the land surface to the groundwater surface) provided the best set of indicators of orchid habitat. Point-based field observations of orchid occurrence were used to develop Orchid Suitability Metrics (OSMs) that identified the range of indicator values most strongly associated with orchids. These OSMs were used to define year by year suitability zones for each indicator that were combined to create the HSI. Comparison of orchid locations with groundwater elevations showed that orchids occurred on average 0.98±0.39 (2σ)m above the water table. TWI and TPI demonstrated that orchids occur near flow paths and areas of lower elevation than their surroundings. HSI values of 0.67 and above were associated with 89.8% of all orchid observations used in the analysis. The landscape indicators, OSM concept and HSI could be generally applied to monitoring and conservation management of orchid habitat and the concept may be applicable to other valued species with similar niche properties.