Species-specific traits associated to prediction errors in bird habitat suitability modelling

2005 ◽  
Vol 185 (2-4) ◽  
pp. 299-308 ◽  
Author(s):  
Javier Seoane ◽  
Luis M. Carrascal ◽  
César Luis Alonso ◽  
David Palomino
Keyword(s):  
Habitat Suitability ◽  
Prediction Errors ◽  
Bird Habitat ◽  
Habitat Suitability Modelling ◽  
Species Specific

scholarly journals Habitat Suitability Modelling of Endangered Kashmir Grey Langur (Semnopithecus ajax) in North Kashmir, India

2018 ◽  
Author(s):  
Zaffar Rais Mir ◽  
Junid Nazeer Shah ◽  
Riyaz Ahmad ◽  
Khursheed Ahmad ◽  
Athar Noor ◽  
...  
Keyword(s):  
Habitat Suitability ◽  
Habitat Suitability Modelling

scholarly journals Empirical Validation of MesoHABSIM Models Developed with Different Habitat Suitability Criteria for Bullhead Cottus Gobio L. as an Indicator Species

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 726 ◽  
Author(s):  
Mikołaj Adamczyk ◽  
Piotr Parasiewicz ◽  
Paolo Vezza ◽  
Paweł Prus ◽  
Giovanni De Cesare
Keyword(s):  
Habitat Suitability ◽  
Model Comparison ◽  
Expert Knowledge ◽  
General Information ◽  
Model Verification ◽  
Physical Habitat ◽  
Riverine Ecosystems ◽  
Cottus Gobio ◽  
Species Specific ◽  
Water Management Planning

Application of instream habitat models such as the Mesohabitat Simulation Model (MesoHABSIM) is becoming increasingly popular. Such models can predict alteration to a river physical habitat caused by hydropower operation or river training. They are a tool for water management planning, especially in terms of requirements of the Water Framework Directive. Therefore, model verification studies, which investigate the accuracy and reliability of the results generated, are essential. An electrofishing survey was conducted in September 2014 on the Stura di Demonte River located in north-western Italy. One hundred and sixteen bullhead—Cottus gobio L.—were captured in 80 pre-exposed area electrofishing (PAE) grids. Observations of bullhead distribution in various habitats were used to validate MesoHABSIM model predictions created with inductive and deductive habitat suitability indices. The inductive statistical models used electrofishing data obtained from multiple mountainous streams, analyzed with logistic regression. The deductive approach was based on conditional habitat suitability criteria (CHSC) derived from expert knowledge and information gathered from the literature about species behaviour and habitat use. The results of model comparison and validation show that although the inductive models are more precise and reflect site- and species-specific characteristics, the CHSC model provides quite similar results. We propose to use inductive models for detailed planning of measures that could potentially impair riverine ecosystems at a local scale, since the CHSC model provides general information about habitat suitability and use of such models is advised in pre-development or generic scale studies. However, the CHSC model can be further calibrated with localized electrofishing data at a lower cost than development of an inductive model.

scholarly journals Habitat suitability modelling for sardine juveniles (Sardina pilchardus) in the Mediterranean Sea

2011 ◽  
Vol 20 (5) ◽  
pp. 367-382 ◽  
Author(s):  
MARIANNA GIANNOULAKI ◽  
MARIA M. PYROUNAKI ◽  
BERNARD LIORZOU ◽  
IOLE LEONORI ◽  
VASILIS D. VALAVANIS ◽  
...  
Keyword(s):  
Mediterranean Sea ◽  
Habitat Suitability ◽  
Sardina Pilchardus ◽  
Habitat Suitability Modelling ◽  
The Mediterranean

scholarly journals Habitat suitability modelling of economically important fish species with commercial fisheries data

2006 ◽  
Vol 63 (9) ◽  
pp. 1590-1603 ◽  
Author(s):  
Liz Morris ◽  
David Ball
Keyword(s):  
Habitat Suitability ◽  
Independent Data ◽  
Spatial Analyses ◽  
Multivariate Approach ◽  
Catch Per Unit Effort ◽  
Commercial Catch ◽  
Habitat Suitability Models ◽  
Simple Set ◽  
Habitat Suitability Modelling ◽  
Wide Scale

Abstract In this study we used catch and effort data from a commercial fishery to generate habitat suitability models for Port Phillip Bay, Victoria, Australia. Species modelled were King George whiting (Sillaginodes punctata), greenback flounder (Rhombosolea tapirina), Australian salmon (Arripis trutta and A. truttaceus), and snapper (Pagrus auratus). Locations of commercial catches were reported through a grid system of fishing blocks. Spatial analyses in a Geographic Information System (GIS) were applied to describe each fishing block by its habitat area. A multivariate approach was adopted to group each fishing block by its dominant habitats. Standardized catch per unit effort values were overlaid on these groups to identify those that returned high or low catches for each species. A simple set of rules was then devised to predict the habitat suitability for each habitat combination in a fishing block. The spatial distribution of these habitats was presented in a GIS. These habitat suitability models were consistent with existing anecdotal information and expert opinion. While the models require testing, we have shown that in the absence of adequate fishery-independent data, commercial catch and effort data can be used to produce habitat suitability models at a bay-wide scale.

Can LiDAR data improve bird habitat suitability models?

2012 ◽  
Vol 245 ◽  
pp. 103-110 ◽  
Author(s):  
Clara Tattoni ◽  
Franco Rizzolli ◽  
Paolo Pedrini
Keyword(s):  
Habitat Suitability ◽  
Lidar Data ◽  
Habitat Suitability Models ◽  
Bird Habitat
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