Habitat Suitability Index Model Research Articles

Habitat Assessment for the Spiny Red Gurnard Chelidonichthys spinosus Using Habitat Suitability Index in the East China Sea and Southern Yellow Sea

Chelidonichthys spinosus is a common fish distributed in the Northwest Pacific. To ensure sustainable utilization, it is crucial to understand the potential impacts of environmental changes on habitat suitability. A habitat suitability index (HSI) model was developed for C. spinosus based on seasonal bottom trawling survey data and remote-sensing oceanographic data collected in the East China Sea and southern Yellow Sea from 2015 to 2017. The model examined the relationships between the spatio-temporal distribution of fish and environmental variables. The suitable ranges of sea bottom temperature, sea bottom salinity, depth and chlorophyll-a for C. spinosus in four seasons were identified. Each variable was then combined into the HSI model with weights defined by the Gradient Boosting Regression Tree. The spatial distribution and the centroid of the HSI revealed that C. spinosus exhibits a seasonal southward and southwestward migratory pattern throughout the year. This migration pattern indicates the suitable habitats for reproductive, feeding, and overwintering activities. The conservation of C. spinosus resources is a matter of great urgency, and some of the feasible proposals have been put forth in this purpose.

Habitat Assessment of Bocachico (Prochilodus magdalenae) in Ciénaga de Betancí, Colombia, Using a Habitat Suitability Index Model

This study evaluates the habitat of the Bocachico fish (Prochilodus magdalenae) in the Ciénaga de Betancí, Colombia, using a habitat suitability index (HSI) model. Wetlands like the Ciénaga de Betancí are under significant pressure from anthropogenic activities, affecting biodiversity and ecosystem health. The Bocachico, a species of immense cultural and economic importance, faces habitat degradation and fragmentation. Using hydrodynamic and water quality data, a numerical model (EFDC+ Explorer 11.5), and field data collected from multiple sampling campaigns, we assessed habitat suitability based on five key parameters: water temperature, dissolved oxygen, ammonia nitrogen, velocity, and depth. The model results indicated that environmental conditions in the wetland remained relatively stable during the dry season, with an average HSI score of 0.67, where 9% of the wetland area displayed acceptable conditions, and the remaining 91% displayed medium conditions. The wet season, on the other hand, had an average HSI score of 0.64, with 7.2% of the area in the acceptable suitability range, and the remaining 92.8% in the medium category. Variations in HSI were primarily driven by ammonia nitrogen levels, water velocity, and depth. Despite limited fluctuations in the HSI, areas of low suitability were identified, particularly in regions impacted by human activities. These findings have practical implications for conservation strategies, providing valuable insights for the sustainable management and conservation of the Ciénaga de Betancí, informing strategies for improving habitat conditions for the Bocachico, and supporting wetland restoration efforts.

Analysis of the Interrelation and Seasonal Variation Characteristics of the Spatial Niche of Dominant Fishery Species-A Case Study of the East China Sea.

The spatial niche has garnered significant attention in ecological research, particularly regarding species distribution patterns. The East China Sea, known for its favorable natural conditions and abundant fishery resources, exhibits diverse spatial distribution patterns among species, shaped by their seasonal physiological needs. This study utilized a habitat suitability index model to explore the spatial distribution patterns of key fishery resources in the East China Sea across four seasons and their interactions. Two methodologies were employed to identify key environmental factors and assess the ecological niche overlap among different species and seasons. Results indicated that the initial method identified water temperature as the critical factor for hairtail, while the subsequent method emphasized water temperature and salinity for hairtail, salinity for small yellow croaker, and water depth for Bombay duck. The main spatial habitat overlap was observed between paired species, likely driven by predator-prey interactions. During summer and autumn, increased overlap among multiple species was primarily influenced by synchronized life cycles. An overlap index formula quantified the seasonal species overlap, showing an increase from spring to winter, reflecting changes in convergent habitat preferences. The peak overlap occurred in winter, driven by overwintering, reduced food competition, and enhanced coexistence potential, while the lowest overlap was noted in spring as overwintering ended and predation and competition intensified.

Modeling Proboscis monkey conservation sites on Borneo using ensemble machine learning

This study aimed to analyze the habitat suitability of the endangered Proboscis monkey (Nasalis larvatus) on Borneo using a multi-machine-learning approach. This study integrated physical, vegetational, meteorological, and human activity data to develop a comprehensive habitat suitability model. Four machine-learning algorithms, namely, maximum entropy (MaxEnt), random forest (RF), support vector machine (SVM), gradient tree boosting (GTB), and classification and regression trees (CART), were employed to model the habitat suitability index. A total of 1943 sample points were divided into training (70 %) and validation (30 %) sets for the analysis. This study included three main stages: geospatial database creation, spatial habitat modeling using multi-machine-learning algorithms, and habitat suitability evaluation. In addition, the pressure from human development on the habitat suitability index model was analyzed. This study identified a high level of suitability for Proboscis monkey habitats in nearshore areas. The maximum habitat suitability for Proboscis monkeys was observed to be 11.54 %, as evidenced by the consensus of the MaxEnt value and four machine-learning algorithms. Conversely, the minimum habitat suitability was recorded at 13.27 %, as indicated by disagreement among all algorithms. The AUC values for the machine-learning models ranged from 74 % to 90 %, indicating moderate to high predictive performance. This study provides valuable insights for the formulation of well-planned development programs for Proboscis monkeys. The results of this study will contribute to the accurate identification of potential Proboscis monkey habitats, thereby providing support for conservation efforts aimed at safeguarding this endangered species.

Spatial Distribution and Abundance of a Pelagic Squid during the Evolution of Eddies in the Southeast Pacific Ocean

The Humboldt squid (Dosidicus gigas), is a significant economic species off Peru. The abundance and distribution of the species are highly susceptible to fluctuations in marine environmental conditions. The evolution of mesoscale eddies represents one of the dynamic processes in the ocean, exerting varying degrees of influence on regional biogeochemical processes from generation to dissipation. However, the mechanisms governing the regulation of abundance and spatial distribution of D. gigas off Peru during this evolution remain unclear. Therefore, this study employed normalization techniques and the habitat suitability index (HSI) model, utilizing data from the D. gigas fishery, mesoscale eddies, and marine environmental factors (including sea surface temperature, temperature at 50 m depth, and chlorophyll-a concentration) to analyze the environmental changes and the abundance, spatial distribution, and habitat changes of D. gigas during the evolution of mesoscale eddies. The results indicate that eddies undergo four stages: formation, intensification, maturity, and decay. During eddy evolution, the abundance of D. gigas exhibited an initial increase and a subsequent decrease within cyclonic eddies (CEs), whereas, within anticyclonic eddies (AEs), abundance showed a gradual decline. The outcome of the HSI model revealed that, the habitat suitability and the proportion of suitable habitat areas within eddies were highly consistent with the abundance of D. gigas during all stages of the eddies other than the intensification stage of AEs. The study speculated that both CEs and AEs can create favorable environmental conditions during the maturity stage, thereby leading to an increase in suitable habitat and abundance of D. gigas. These findings emphasize the significant impact of mesoscale eddy evolution on the abundance and habitat distribution of D. gigas.

Estuary-Specific and Adaptive Habitat Suitability Index Model for the Eastern Oyster Crassostrea Virginica in the Pensacola Bay System, Florida, USA

Oyster reef, a key ecosystem component in many temperate and subtropical estuarine systems, has been greatly diminished by human influences and ongoing climatic changes. Changes in precipitation, oyster adult and larval distribution, benthic composition, hydrology, currents and/or inputs to the system such as pollutants or sediments complicate the identification of locations that may be suitable for oyster reef restoration. In such cases, development of a habitat suitability index model (HSI) can provide useful guidance on where restoration activities might be successful, and once complete, help to focus the area for restoration project siting consideration. HSI models can be constructed from a variety of data categories including biological requirements of the species to be restored, physical characteristics of the system, regulatory constraints, and socio-economic concerns. Here we describe the development of a geographic information system based HSI model to inform restoration of oyster reef in the Pensacola Bay System, Florida, USA that can be used as a template for oyster reef restoration in other Florida estuaries and beyond. We demonstrate that an oyster habitat HSI model can be relatively simple to construct, useful even with limited environmental data, improved with community stakeholder and resource user input, and easily adaptable.

Evaluating the spatial transferability of habitat suitability models: implications for conservation and management

Habitat models often rely on data with incomplete or patchy survey coverage, making it necessary to project observed habitat relationships into unsampled areas. Model transferability is often assumed, rarely tested, and may result in uninformed management recommendations if not validated. In the eastern Gulf of Maine, data from the federal trawl survey has historically been used to identify suitable habitat for juvenile Atlantic cod ( Gadus morhua), despite mainly sampling in offshore waters. This study evaluated the spatial transferability of a habitat suitability index model by projecting offshore habitat relationships inshore and comparing them to models built using two inshore surveys. Due to rare warm-water exposure in offshore waters, the federal survey model was unable to identify suitable habitat in the warmer, shallower areas that the inshore surveys identified, suggesting that offshore models are not transferable inshore for juvenile cod in the eastern Gulf of Maine. The results of this study have implications for fisheries worldwide and suggest that incorrectly assuming model transferability could pose a significant hurdle for effective conservation and management.

Response of Siberian Cranes (Grus leucogeranus) to Hydrological Changes and the Availability of Foraging Habitat at Various Water Levels in Poyang Lake.

To assess the Siberian crane (Grus leucogeranus)'s response to changing water levels and habitat quality at Poyang Lake, we analyzed the lake's hydrological trends over the past two decades with the Mann-Kendall and Sen slope methods. Additionally, we explored the link between the crane population size and hydrological conditions at the lake from 2011 to 2019. Meanwhile, five environmental factors, including habitat type, distance from shallow lakes, human footprint index, elevation and normalized vegetation index were selected, and the distribution patterns of suitable habitats for the Siberian crane under 10 water level gradients with intervals of about 1 m (5.3-14.2 m) were simulated by using an improved habitat suitability index model that determines the weights of evaluating factors based on the MaxEnt model. The results showed that the overall trend of the inundated area in Poyang Lake was shrinking in the last 20 years, with a significant increase in the area of exposed floodland during the early wintering period (Z = -2.26). The prolonged drought resulting from this will force vegetation succession, thereby diminishing the food resources for cranes in their natural habitat. The mean inundated area in June demonstrated a significant negative correlation with the population of Siberian cranes in natural habitats (r = -0.75, p = 0.02). Shortage of the Siberian crane-preferred Vallisneria tuber due to June flooding was the primary driver of the crane's altered foraging strategy and habitat shift. In years with relatively normal June inundation, indicating abundant Vallisneria resources, the relationship between the inundated area during the dry season and the crane population fit well, with a quadratic curve (R2 = 0.92, p = 0.02). The dry season's inundated area primarily affected the crane population and distribution pattern by influencing the availability of food resources, and both excessive and insufficient inundation areas were unfavorable for crane survival. The modeling results for habitat suitability indicated that as the water level decreased, the trend of the area of good habitat for the Siberian crane showed an inverted bell shape, peaking at a water level of 8.8 m, with optimal conditions occurring between 8 and 10 m. The combined effects of climate and human activities have made the shortage of food resources in Poyang Lake the new normal. The degradation of natural habitats has led to a decline in the quality of Siberian crane habitats, and artificial habitats can only be used as refuges to a certain extent. Thus, formulating strategies to restore natural habitats and enhance the management of artificial habitats is crucial for the conservation efforts of Siberian cranes.

Spatio-temporal variability of fishing habitat suitability to tuna purse seine fleet in the Western and Central Pacific Ocean

Understanding the spatial distribution of fishing activity is important for ecosystem-based fisheries management.The dynamic vessel trajectory information provided by Automatic Identification System (AIS) together with local remote ocean environment data, provide an opportunity for new technologies to enable improvements in fisheries management.The spatio-temporal and variability to tuna purse seine fleet suitable fishing were evaluated based on fishing effort from AIS by constructing an integrated habitat suitability index (HSI), which weight of variables were determined with boosted regression trees (BRT) model. The results show that the fishing activity tuna purse-seine fleet and catch data from the Western and Central Pacific Fisheries Commission (WCPFC) have the same spatial distribution.The tuna purse seine fleet operation concentrate in EEZ area of the Pacifc Island countries and has seasonal environmental preferences. The fishing habitat suitability can be characterized by a few environmental factors. The HSI model had good capacity to predict habitat suitability to tuna purse seine fleet for mostly catch and fishing effort located in the suitable area. The suitable fishing areas showed significant seasonal changes and low utilization of the available environmentally suitable fishing habitat in each month. The most stable suitable area located in the New Guinea Offshore latitudinal region, may be experiencing high tuna purse-seine fishing pressure throughout the year. The research could help to improve the scientific and effective management of distant water fisheries under limited regulatory capacity.

Climate-related habitat variations of Humboldt squid in the eastern equatorial Pacific Ocean

An integrated habitat suitability index (HSI) model was developed in this study for Dosidicus gigas in the eastern equatorial waters of the Pacific Ocean to explore climate-related spatial and temporal variability in the habitat distribution pattern based on three crucial environmental variables: sea surface temperature (SST), sea surface salinity (SSS) and chlorophyll-a concentration (Chl-a). Results revealed that the HSI model could accurately predict potential habitats for D. gigas. The habitat suitability varied significantly by month, with highest suitability in April and lowest in March. Besides, from December to May, the longitudinal gravity center of the fishing grounds (LONG) and the HSI overall shifted eastward and the latitudinal gravity center shifted northward then southward. In comparison to the warm ENSO phases in 2019, the cold ENSO phases in 2018 produced increased suitable habitat from December to May, leading to a significantly higher CPUE. Prospective high-quality habitats in 2018 primarily occurred in the western regions, with the exception of December, which resulted in a more westward distribution of LONG from January to May. High-quality habitats moved northward from December to February and southward from March to May 2018, compared to minor latitudinal movement in 2019. It was inferred that annual variations in squid abundance and distribution were largely affected by the SST-related habitat pattern of D. gigas in the eastern equatorial waters. Our findings suggested that D. gigas habitats clearly varied by month and year and were greatly influenced by climate-induced environmental changes.

Evaluating Suitability of Fishing Areas for Squid-Jigging Vessels in the Northwest Pacific Ocean Derived from AIS Data

Understanding the spatial distribution of fishing activity and suitable fishing areas is important for improving sustainable fisheries management and protecting vulnerable fish stocks. To identify climate-related habitat changes and variations in the distribution of fishing activity for squid-jigging vessels in the Northwest Pacific Ocean, two types (weighted arithmetic mean method, weighted-AMM; weighted geometric mean method, weighted-GMM) of habitat suitability index (HSI) models were developed in this study with marine environmental data at different depths. The boosted regression tree (BRT) model was adopted to access the monthly important environmental variables and the relative influence of the corresponding variables. The results showed that the weighted-AMM has better prediction performance than the weighted-GMM. The suitable fishing areas showed significant seasonal changes in both spatial location and coverage area. The hotspot map showed that the suitable fishing area for squid-jigging vessels was located in the scope of 42∘ N∼44∘ N, 155∘ E∼170∘ E throughout the year during 2012∼2019, which suggests that high squid-jigging fishing pressure should be given more attention in fishery management. The HSI model also had good prediction performance for the fishery data of Chinese companies, except for June and July. Additionally, fishing efforts could be used as alternative data for fishery research. The study has also suggested that fishery data are restricted by spatial and temporal distribution and fishing experience, which probably biases the results of the research.

Habitat modelling of escolar fish (Lepidocybium flavobrunneum, Smith 1843) in the southwestern Indian Ocean using remote sensing data

ABSTRACT Escolar (Lepidocybium flavobrunneum) belongs to Gempylidae family, is a top predator species that plays a crucial role in the marine ecosystem. However, limited information is available regarding their spatial-temporal variations in habitat, while habitat suitability index (HSI) modelling has been widely used in recent years for conservation, fisheries, and ecology. We compared an Arithmetic Mean Model (AMM) and a Geometric Mean Model (GMM) to gain insights into their habitat distribution. Fishery data were collected from the southwestern Indian Ocean between 2010 and 2014. Ten oceanographic remote sensing data sets were compiled, and four of them were selected based on their higher R 2 values obtained from Generalized Additive Model (GAM), Boosted Regression Trees (BRT), and Random Forest (RF) analyses for constructing the model combination. Meanwhile, Suitability Index (SI) curves were employed to determine the habitat suitability range for escolar. Environmental parameters were combined using a step-wise approach and applied for both AMM and GMM. The models were evaluated based on the Lowest Akaike Information Criterion (AIC) value. Eventually, AMM was chosen over GMM with the AIC value was 28.49 and 31.25, respectively. The selected model combination of AMM was Sea Surface Height (SSH), Oxygen (O), and Sea Surface Temperature (SST) meaning these parameters influenced the distribution of escolar. The SI curve of the chosen model indicated the habitat range for each parameter as follows: SSH (0.61–0.69 m), O (222–230 mmol m−3), and SST (18.7–21.1°C). The most suitable habitat for escolar was observed within the coordinates 36 ºS-30 ºS and 28 ºE-36 ºE. Thus, this method is demonstrated in a case study where just presence data are provided and the incorporation of remote sensing environmental factors is gathered. This result could help improve escolar fishery management in the southwestern Indian Ocean.

Prediction of potential fishing grounds of swordtip squid (Uroteuthis edulis) based on a physical–biochemical coupled model

AbstractSwordtip squid (Uroteuthis edulis), which is sometimes eaten alive (lively squid) in northwest Kyushu, Japan, is an economically important fish species in the region. However, the total catch of this species in Japan has declined by more than 80% in the last three decades. To understand and predict the spatio‐temporal distribution of fish species, we developed a one‐dimensional ecosystem (NPZD) model and a habitat suitability index (HSI) model for southwest Iki Island, northwest Kyushu, Japan. Subsequently, we conducted three numerical experiments with the HSI model, with and without the NPZD model data (with the NPZD model data: phytoplankton or zooplankton concentrations, without the NPZD model data: only the physical data of the ocean). In the HSI model with zooplankton concentrations, we found a stronger positive relationship between the HSI model values and the daily fisheries catch data of U. edulis than that using only the physical variables of the ocean as the environmental parameters. Our study thus indicates that the performance of the fishing ground prediction model will improve by utilizing the lower trophic ecosystem model such as zooplankton concentrations. Furthermore, our results would provide important implications for the efficiency of fishing operations and the conservation and management of this species.

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.

Spatiotemporal distribution of Lophius litulon in the southern Yellow Sea and East China Sea

In order to investigate the temporal-spatial distribution of yellow goosefish in the open waters of the southern Yellow Sea (SYS) and East China Sea (ECS), according to the fishery data by bottom-trawl surveys and environmental data including sea bottom temperature (SBT), sea bottom salinity (SBS), bottom concentration of dissolved oxygen (BDO) and depth during 2018-2019, we established habitat suitability index (HSI) models by arithmetic mean (AMM) and geometric mean (GMM) methods, and compared the model outputs by cross validations. Especially, the weight of each environmental factor was evaluated by boosted regression tree (BRT). Results showed that the area with the highest habitat quality varied among seasons. The yellow goosefish mainly inhabited in the adjacent area of the Yangtze River Estuary and coastal waters of Jiangsu Province with depth ranged from 22 to 49 m in spring. The optimal inhabitation was located in the SYS, with the bottom temperature ranged from 8.9-10.9 ℃ in summer and autumn. Particularly, the optimal inhabitation extended from the SYS to the ECS with bottom temperature ranged from 9.2-12.7 ℃ in winter. Results of BRT models showed that depth was the most important environmental factor in spring and bottom temperature was the crucial one in the other three seasons. Results of cross validation showed that the weighted AMM-based HSI model performed better for yellow goosefish in spring, autumn and winter. The distribution of yellow goosefish was closely related to its biological traits and environmental factors in the SYS and ECS, China.

Evaluation of Habitat Suitability Index Model of Indian Gharial in National Chambal Sanctuary, M.P. India

Almost all animals use their habitats in a non-random manner. But the cost and benefits of using specific habitat types remain unknown for many types of organisms. Habitat suitability models aim to assess the relationship between species and their habitat and accurately predict the species response to habitat changes. We developed a riverine habitat model for Gharial (Gavialis gangeticus), a critically endangered species, in the National Chambal Sanctuary in India after reviewing and synthesizing existing information. Based on the model, an index of habitat suitability is produced, ranging from 0 (unsuitable habitat) to 1 (optimal habitat). The results of the present study indicate that the Gharial prefer deep pools in water bodies. The deep waters serve as feeding and breeding grounds for Gharial. They prefer water with a velocity ranging from 20–70 cm.sec-1 . Sandy banks are preferred as basking sites, mainly because they provide moisture during the warm months and because it seems that they find it easier to crawl on sandy surfaces than on rocky or clay surfaces. Insects, tadpoles, tiny fish, and frogs are preferred by young Gharial. A habitat suitability model for Gharial can be used as a decision support system in order to improve conservation efforts at different landscape scales.

Development of modelling and mapping methods to predict spatial distributions and abundance of estuarine and coastal fish species life‐stages in Florida

AbstractSuitability modelling and mapping methods were developed to predict spatial distributions and population abundance of fish and macroinvertebrate species in Florida estuaries and coastal zones. Habitats were mapped in Pensacola Bay, Tampa Bay, and Charlotte Harbor using data from fisheries‐independent monitoring. Starting in 1997, suitability functions from habitat suitability index models were linked to habitat grids to create seasonal maps for early‐juvenile, juvenile, and adult life‐stages. After 2003, habitat suitability models (HSM) were linked to seasonal habitat grids to create seasonal maps validated by reciprocal transfer of suitability functions between estuaries. A quantitative method was used with five factor models and models with fewer environmental factors for four species in 2005 and for 11 species by life‐stages in 2009. In 2006, suitability functions transferred from Charlotte Harbor were linked with habitat grids for Rookery Bay and Fakahatchee Bay and HSM maps produced for three time periods to test transferability to estuaries lacking long‐term monitoring. Analyses in 2012 demonstrated that HSM maps for Tampa Bay derived independently from earlier suitability functions were almost identical to HSM maps created using recent suitability functions. Salinity was the most significant environmental variable for predicting abundance in models for species life‐stages in the Peace River and Charlotte Harbor, although nutrient concentrations from upriver may have influenced species’ abundances associated with low (<5 psu) to moderate (5–10 psu) salinities. Population abundance estimates for Charlotte Harbor were derived from seasonal HSM maps created in 2019 and 2021. The 2021 paper compared changes in seasonal population numbers between Baseline and Minimum Flows associated with projected water withdrawals from the Peace River. Electronic logbooks were developed in 2001 and 2004 to collect data on shrimp fishing vessels and HSM maps for the West Florida Shelf created for 16 months in 2004–2005. Methodologies evolved as enabling technology became available.

Climate-induced habitat suitability changes intensify fishing impacts on the life history of large yellow croaker (Larimichthys crocea).

Intense fishing pressure and climate change are major threats to the fish population and coastal fisheries. Larimichthys crocea (large yellow croaker) is a long‐lived fish, which performs seasonal migrations from its spawning and nursery grounds along the coast of the East China Sea (ECS) to overwintering grounds offshore. This study used length‐based analysis and habitat suitability index (HSI) model to evaluate the current life‐history parameters and overwintering habitat suitability of L. crocea, respectively. We compared recent (2019) and historical (1971–1982) life‐history parameters and overwintering HSI to analyze the fishing pressure and climate change effects on the overall population and overwintering phase of L. crocea. The length‐based analysis indicated serious overfishing of L. crocea, characterized by reduced catch, size truncation, constrained distribution, and advanced maturation causing a recruitment bottleneck. The overwintering HSI modeling results indicated that climate change has led to decreased sea surface temperature during L. crocea overwintering phase over the last half‐century, which in turn led to area decrease and an offshore‐oriented shifting of optimal overwintering habitat of L. crocea. The fishing‐caused size truncation may have constrained the migratory ability, and distribution of L. crocea subsequently led to the mismatch of the optimal overwintering habitat against climate change background, namely habitat bottleneck. Hence, while heavy fishing was the major cause of L. crocea collapse, climate‐induced overwintering habitat suitability may have intensified the fishery collapse of L. crocea population. It is important for management to consider both overfishing and climate change issues when developing stock enhancement activities and policy regulations, particularly for migratory long‐lived fish that share a similar life history to L. crocea. Combined with China's current restocking and stock enhancement initiatives, we propose recommendations for the future restocking of L. crocea in China.

Evaluating the impacts of mesoscale eddies on abundance and distribution of neon flying squid in the Northwest Pacific Ocean

Mesoscale eddies are ubiquitous in global oceans yielding significant impacts on marine life. As a short-lived pelagic squid species, the population of neon flying squid (Ommastrephes bartramii) is extremely sensitive to changes in ambient oceanic variables. However, a comprehensive understanding of how mesoscale eddies affect the O. bartramii population in the Northwest Pacific Ocean is still lacking. In this study, a 10-year squid fisheries dataset with eddy tracking and high-resolution reanalysis ocean reanalysis data was used to evaluate the impact of mesoscale eddies and their induced changes in environmental conditions on the abundance and habitat distribution of O. bartramii in the Northwest Pacific Ocean. A weighted-based habitat suitability index (HSI) model was developed with three crucial environmental factors: sea surface temperature (SST), seawater temperature at 50-m depth (T50m), and chlorophyll-a concentration (Chl-a). During years with an unstable Kuroshio Extension (KE) state, the abundance of O. bartramii was significantly higher in anticyclonic eddies (AEs) than that in cyclonic eddies (CEs). This difference was well explained by the distribution pattern of suitable habitats in eddies derived from the HSI model. Enlarged ranges of the preferred SST, T50m, and Chl-a for O. bartramii within AEs were the main causes of more squids occurring inside the warm-core eddies, whereas highly productive CEs matching with unfavorable thermal conditions tended to form unsuitable habitats for O. bartramii. Our findings suggest that with an unstable KE background, suitable thermal conditions combined with favorable foraging conditions within AEs were the main drivers that yielded the high abundance of O. bartramii in the warm eddies.