Remotely sensed hydroacoustics and observation data for predicting fish habitat suitability

2011 ◽  
Vol 31 (2) ◽  
pp. S17-S27 ◽  
Author(s):  
J. Monk ◽  
D. Ierodiaconou ◽  
A. Bellgrove ◽  
E. Harvey ◽  
L. Laurenson

<em>Abstract.—</em> A need exists to scientifically determine optimal fish habitats to support decision making for management of essential fish habitat. Scientists have been collaborating to conduct habitat suitability index (HSI) modeling to spatially delineate fish habitats for estuarine fish and invertebrate species in Tampa Bay and Charlotte Harbor, Florida. Results from HSI modeling of juvenile spotted seatrout <em>Cynoscion nebulosus </em> in Charlotte Harbor are presented. Data obtained from 1989–1997 by fisheries-independent monitoring in the two estuaries were used along with environmental data from other sources. Standardized catch-per-unit-effort (catch rates) were calculated across gear types using fisheries-monitoring data from Charlotte Harbor and Tampa Bay. Suitability index functions were determined using three methods: (1) frequency of occurrence, (2) mean catch rates within ranges, and (3) smooth-mean catch rates determined by polynomial regression. Mean catch rates were estimated within biologically relevant ranges and, where sufficient data were available, for finer intervals across environmental gradients. Suitability index functions across environmental gradients were then derived by scaling catch rates. Gridded habitat layers for temperature, salinity, depth, and bottom type in Charlotte Harbor were also created using a geographic information system. Habitat suitability index modeling was conducted using the U.S. Fish and Wildlife Service geometric mean method linked to the ArcView Spatial Analyst module. The model integrated suitability indices associated with the habitat layers for Charlotte Harbor to create a map of the predicted distribution for juvenile spotted seatrout during the fall season. Suitability indices developed for Tampa Bay were used with Charlotte Harbor habitat layers to test transfer of the indices to another estuary. Predicted HSI maps depicted low to optimum habitat suitability zones in Charlotte Harbor. Model performance was evaluated by statistically comparing the relative ranking of mean catch rates with mean suitability indices for corresponding zones. Suitability indices obtained using polynomial regression methods yielded morereliable HSI maps for juvenile spotted seatrout than those derived using mean catch rates within biologically relevant ranges. The observed map, derived using smooth-mean suitability indices transferred from Tampa Bay, was not significantly different (Chi-square goodness-of-fit test) from the expected map derived using smooth-mean indices from Charlotte Harbor. Our modeling efforts using transferred indices indicate that it is possible to predict the geographic distributions of fish species by life stage in estuaries lacking fisheries monitoring.


2018 ◽  
Vol 116 ◽  
pp. 29-39 ◽  
Author(s):  
Serena Ceola ◽  
Alessio Pugliese ◽  
Matteo Ventura ◽  
Giorgio Galeati ◽  
Alberto Montanari ◽  
...  

2011 ◽  
Vol 222 (8) ◽  
pp. 1401-1413 ◽  
Author(s):  
Shinji Fukuda ◽  
Bernard De Baets ◽  
Ans M. Mouton ◽  
Willem Waegeman ◽  
Jun Nakajima ◽  
...  

Author(s):  
SHINJI FUKUDA ◽  
BERNARD DE BAETS

Information on species distributions is of key importance when designing management plans for a target species or ecosystem. This paper illustrates the effects of absence data on fish habitat prediction and habitat preference evaluation using a genetic Takagi-Sugeno fuzzy model. Three independent data sets were prepared from a series of fish habitat surveys conducted in an agricultural canal in Japan. To quantify the effects of absence data, two kinds of abundance data (entire data and presence data) were used for developing a fuzzy habitat preference model (FHPM). As a result, habitat preference curves (HPCs) obtained from presence data resulted in similar HPCs between the three data sets, while those obtained from entire data slightly differed according to the data sets. The higher generalization ability of the FHPMs obtained from presence data supports the usefulness of presence data for better extracting the habitat preference information of a target species from field observation data.


2021 ◽  
Vol 263 ◽  
pp. 109357
Author(s):  
Daniel J. McGarvey ◽  
Alexander L. Brown ◽  
Elsa B. Chen ◽  
Catherine B. Viverette ◽  
Philip A. Tuley ◽  
...  

Oryx ◽  
2021 ◽  
pp. 1-10
Author(s):  
Zoe Paraskevopoulou ◽  
Hila Shamon ◽  
Melissa Songer ◽  
Graeme Ruxton ◽  
William J. McShea

Abstract Reintroductions are challenging, and success rates are low despite extensive planning and considerable investment of resources. Improving predictive models for reintroduction planning is critical for achieving successful outcomes. The IUCN Guidelines for Reintroductions and Other Conservation Translocations recommend that habitat suitability assessments account for abiotic and biotic factors specific to the species to be reintroduced and, where needed, include habitat quality variables. However, habitat assessments are often based on remotely-sensed or existing geographical data that do not always reliably represent habitat quality variables. We tested the contribution of ground-based habitat quality metrics to habitat suitability models using a case study of the swift fox Vulpes velox, a mesocarnivore species for which a reintroduction is planned. Field surveys for habitat quality included collection of data on the main threat to the swift fox (the coyote Canis latrans), and for swift fox prey species. Our findings demonstrated that the inclusion of habitat quality variables derived from field surveys yielded better fitted models and a 16% increase in estimates of suitable habitat. Models including field survey data and models based only on interpolated geographical and remotely-sensed data had little overlap (38%), demonstrating the significant impact that different models can have in determining appropriate locations for a reintroduction. We advocate that ground-based habitat metrics be included in habitat suitability assessments for reintroductions of mesocarnivores.


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