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result(s) for
"Habitat Suitability Index"
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Evaluation of Maximum Entropy Models for Assessing Coastal Bird Distributions under Restoration Scenarios
Hucks, K.D. and Leberg, P.L., 2024. Evaluation of maximum entropy models for assessing coastal bird distributions under restoration scenarios. Journal of Coastal Research, 40(5), 901–918. Charlotte (North Carolina), ISSN 0749-0208. Coastal systems are facing many challenges, including climate change, sea-level rise, storm surge, and erosion, all of which contribute to land loss. In Louisiana, this has led to the development of a coastal master plan supported by habitat suitability index (HSI) models to predict wildlife responses under various management scenarios. However, HSI models were not originally intended for this purpose, and their functionality at large spatial scales is unclear. The goal was to use maximum entropy modeling to predict how various bird distributions might change with coastal restoration and management and to compare those results to HSI model predictions. Using field surveys and sources of bird locations, as well as environmental projections from the Comprehensive Master Plan habitat and hydrology models, the authors predicted the probability of occurrence for each target species for current conditions and projected the distributions into the future at 25 and 50 years using sea-level rise and coastal change scenarios. Predictive models for each species under current conditions show good agreement with field observations. Future models generally show reductions in areas of potentially high habitat use, with a few notable exceptions in the Brown Pelican habitat. Both MaxEnt and HSI modeling approaches had advantages and disadvantages; neither was clearly superior for predicting wildlife habitat. Increasing the resolution and quality of environmental data used in coastal monitoring efforts, as well as additional field validation of model predictions, will improve estimates of suitable habitat, habitat use, and restoration outcomes for wildlife.
Journal Article
Divergent responses of highly migratory species to climate change in the California Current
Aim Marine biodiversity faces unprecedented threats from anthropogenic climate change. Ecosystem responses to climate change have exhibited substantial variability in the direction and magnitude of redistribution, posing challenges for developing effective climate‐adaptive marine management strategies. Location The California Current Ecosystem (CCE), USA. Methods We project suitable habitat for 10 highly migratory species in the California Current System using an ensemble of three high‐resolution (~10 km) downscaled ocean projections under the Representative Concentration Pathway 8.5 (RCP8.5). Spanning the period from 1980 to 2100, our analysis focuses on assessing the direction and distance of distributional shifts, as well as changes in core habitat area for each species. Results Our findings reveal a divergent response among species to climate impacts. Specifically, four species were projected to undergo significant poleward shifts exceeding 100 km, and gain habitat (~7%–60%) in response to climate change. Conversely, six species were projected to shift towards the coast, resulting in a loss of habitat ranging from 10% to 66% by the end of the century. These divergent responses could typically be characterized by the mode of thermoregulation (i.e. ectotherm vs. endotherm) and species' affiliations with cool and productive upwelled waters that are characteristic of the region. Furthermore, our study highlights an increase in niche overlap between protected species and those targeted by fisheries, which may lead to increased human interaction events under climate change. Main Conclusions By providing valuable species distribution projections, our research contributes to the understanding of climate change effects on marine biodiversity and offers critical insight and support for developing climate‐ready management of protected and fished species.
Journal Article
Evaluation of fish habitat suitability based on stream hydrodynamics and water quality using SWAT and HEC-RAS linked simulation
The objective of this study was to evaluate fish habitat suitability by simulating hydrodynamic and water quality factors using SWAT and HEC-RAS linked simulation considering time-series analysis. A 2.9 km reach of the Bokha stream was selected for the habitat evaluation of
Zacco platypus
, with hydrodynamic and water quality simulations performed using the SWAT and HEC-RAS linked approach. Based on simulated 10-year data, the aquatic habitat was assessed using the weighted usable area (WUA), and minimum ecological streamflow was proposed from continuous above threshold (CAT) analysis. High water temperature was identified as the most influential habitat indicator, with its impact being particularly pronounced in shallow streamflow areas during hot summer seasons. The time-series analysis identified a 28% threshold of WUA/WUA
max
, equivalent to a streamflow of 0.48 m
3
/s, as the minimum ecological streamflow necessary to mitigate the impact of rising water temperatures. The proposed habitat modeling method, linking watershed-stream models, could serve as a useful tool for ecological stream management.
Journal Article
Spatio-Temporal Variability of the Habitat Suitability Index for Chub Mackerel (Scomber Japonicus) in the East/Japan Sea and the South Sea of South Korea
The climate-induced decrease in fish catches in South Korea has been a big concern over the last decades. The increase in sea surface temperature (SST) due to climate change has led to not only a decline in fishery landings but also a shift in the fishing grounds of several fish species. The habitat suitability index (HSI), a reliable indicator of the capacity of a habitant to support selected species, has been widely used to detect and forecast fishing ground formation. In this study, the catch data of the chub mackerel and satellite-derived environmental factors were used to calculate the HSI for the chub mackerel in the South Sea, South Korea. More than 80% of the total catch was found in areas with an SST of 14.72–25.72 °C, chlorophyll-a of 0.30–0.92 mg m−3, and primary production of 523.7–806.46 mg C m−2 d−1. Based on these results, the estimated climatological monthly HSI from 2002 to 2016 clearly showed that the wintering ground of the chub mackerel generally formed in the South Sea of South Korea, coinciding with the catch distribution during the same period. This outcome implies that our estimated HSI can yield a reliable prediction of the fishing ground for the chub mackerel in the East/Japan Sea and South Sea of South Korea.
Journal Article
Differences in habitat variability of the northwestern Indian Ocean’s Sthenoteuthis oualaniensis in response to ENSO events
In order to explore the influence of environmental factors and ENSO events on the habitat of
Sthenoteuthis oualaniensis
in the northwestern Indian Ocean, this study examined these effects across various seasons. Utilizing production and fishing data of
S. oualaniensis
collected from September 2021 to May 2024 in the specified region, coupled with marine environmental factor data, we conducted multicollinearity diagnostics and employed the generalized additive model to filter environmental factors and establish a habitat suitability index model with seasonal-specific weights. Based on model performance, optimal models for each season were chosen and validated. Furthermore, these optimal models were utilized to forecast the habitats suitability of
S. oualaniensis
, enabling a comparative analysis of the spatiotemporal distribution differences of these habitats during El Niño, La Niña, and normal conditions. The findings reveal that the Catch Per Unit Effort (CPUE) of
S. oualaniensis
in the northwestern Indian Ocean positively correlates with latitude in autumn and winter, but negatively in spring. In contrast, CPUE exhibits a positive correlation with longitude throughout the year. Notably, the environmental factor with the highest weight in the optimal model varies seasonally: eastward current velocity for autumn, sea surface temperature for winter, and chlorophyll-a concentration for spring. Validation results indicate that the prediction accuracy of the optimal models for each season surpasses 70%, with accuracy in spring exceeding 95%. During La Niña events, the habitat area of
S. oualaniensis
in the northwestern Indian Ocean expands significantly, whereas during El Niño events, it diminishes and shifts northward. The habitat’s migration east or west is contingent upon the monsoon wind direction, specifically westward in winter and eastward in spring. This study offers valuable insights into the effects of environmental factors and ENSO events on
S. oualaniensis
in the northwestern Indian Ocean across different seasonal timescales, ultimately contributing to the sustainable utilization of this species.
Journal Article
Suitability Evaluation of the Water Environment for Seagrass Growth Areas in the Changshan Archipelago
Seagrass beds provide essential ecosystem services, such as habitat for marine life, water quality purification, carbon sequestration, and climate regulation. For the Changshan Archipelago, which relies heavily on marine resources, the growth and development of seagrass beds are key factors affecting aquaculture. This study is based on data collected from a survey conducted in the nearshore waters of the Changshan Archipelago in August 2022, encompassing seagrass distribution and water sample data. The water samples were analyzed for various parameters, including salinity, suspended solids, pH, dissolved oxygen, sea temperature, nitrite-nitrogen, nitrate-nitrogen, and ammonia-nitrogen concentrations. A habitat suitability assessment of the seagrass beds in the Changshan Archipelago was conducted. The study calculated the suitability index for each environmental variable based on the abundance index, and then established a Habitat Suitability Index model using a weighted allocation method. The results indicate that the seagrass bed area in the study region is primarily composed of excellent and suitable habitats. The concentration of inorganic nutrients is a key factor influencing seagrass growth. The HSI model not only identifies the hierarchical distribution of habitats in seagrass areas, but also detects potential suitable habitats for seagrass. This provides scientific reference for future seagrass bed resource protection and artificial cultivation efforts.
Journal Article
Habitat Suitability Modeling for the Feeding Ground of Immature Albacore in the Southern Indian Ocean Using Satellite-Derived Sea Surface Temperature and Chlorophyll Data
In the current study, remotely sensed sea surface ocean temperature (SST) and sea surface chlorophyll (SSC), an indicator of tuna abundance, were used to determine the optimal feeding habitat zone of the southern Indian Ocean (SIO) albacore using a habitat suitability model applied to the 2000–2016 Taiwanese longline fishery data. The analysis showed a stronger correlation between the 2-month lag SSC and standardized catch per unit effort (CPUE) than 0-, 1-, 3-, and 4-month lag SSC. SST also exhibited a stronger correlation with standardized CPUE. Therefore, SST and SSC_2 were selected as final variables for model construction. An arithmetic mean model with SST and SSC_2 was deemed suitable to predict the albacore feeding habitat zone in the SIO. The preferred ranges of SSC_2 and SST for the feeding habitat of immature albacore were 0.07–0.09 mg m−3 and 16.5–18.5 °C, respectively, and mainly centralized at 17.5 °C SST and 0.08 mg m−3 SSC_2. The selected habitat suitability index model displayed a high correlation (R2 = 0.8276) with standardized CPUE. Overall, temperature and ocean chlorophyll were found to be essential for albacore habitat formation in the SIO, consistent with previous studies. The results of this study can contribute to ecosystem-based fisheries management in the SIO by providing insights into the habitat preference of immature albacore tuna in the SIO.
Journal Article
Habitat Suitability Index is not relevant for great crested newt occupancy at its range margins: a Mediterranean case study
For effective conservation, robust tools that can measure and predict spatio-temporal population variation are required, especially for species in steep decline, rarely encountered or difficult to detect, such as many amphibian species. This study focused on the relevance of the Habitat Suitability Index (HSI) and its component variables to assess habitat and predict the presence of the great crested newt (Triturus cristatus) in the southern margin of its range. We monitored the species to test (1) the effectiveness of different methods for detecting newts, and (2) the influence of different landscape variables on its occupancy probability. Our results indicate that while eDNA is a highly effective detection tool, it is not sufficient on its own to detect all occupied ponds by the great crested newt, that HSI is not a good predictor of pond occupancy at the range margins of this species, and that the species’ presence is significantly and negatively influenced by the distance to the nearest positive pond and the HSI pond drying. Our findings suggest that the conservation of the species in the southern margins of its range can only be achieved by maintaining the terrestrial and aquatic connectivity of the different identified populations.
Journal Article
Predicting Skipjack Tuna Fishing Grounds in the Western and Central Pacific Ocean Based on High-Spatial-Temporal-Resolution Satellite Data
Skipjack tuna are the most abundant commercial species in Taiwan’s pelagic purse seine fisheries. However, the rapidly changing marine environment increases the challenge of locating target fish in the vast ocean. The aim of this study was to identify the potential fishing grounds of skipjack tuna in the Western and Central Pacific Ocean (WCPO). The fishing grounds of skipjack tuna were simulated using the habitat suitability index (HSI) on the basis of global fishing activities and remote sensing data from 2012 to 2015. The selected environmental factors included sea surface temperature and front, sea surface height, sea surface salinity, mixed layer depth, chlorophyll a concentration, and finite-size Lyapunov exponents. The final input factors were selected according to their percentage contribution to the total efforts. Overall, 68.3% of global datasets and 35.7% of Taiwanese logbooks’ fishing spots were recorded within 5 km of suitable habitat in the daily field. Moreover, 94.9% and 79.6% of global and Taiwan data, respectively, were identified within 50 km of suitable habitat. Our results showed that the model performed well in fitting daily forecast and actual fishing position data. Further, results from this study could benefit habitat monitoring and contribute to managing sustainable fisheries for skipjack tuna by providing wide spatial coverage information on habitat variation.
Journal Article