Modelling habitat requirements of bullhead (Cottus gobio) in Alpine streams
Modelling habitat requirements of bullhead (Cottus gobio) in Alpine streams
In the context of water resources planning and management, the prediction of fish distribution related to habitat characteristics is fundamental for the definition of environmental flows and habitat restoration measures. In particular, threatened and endemic fish species should be the targets of biodiversity safeguard and wildlife conservation actions. The recently developed meso-scale habitat model (MesoHABSIM) can provide solutions in this sense by using multivariate statistical techniques to predict fish species distribution and to define habitat suitability criteria. In this research, Random Forests (RF) and Logistic Regressions (LR) models were used to predict the distribution of bullhead (Cottus gobio) as a function of habitat conditions. In ten reference streams of the Alps (NW Italy), 95 mesohabitats were sampled for hydro-morphologic and biological parameters, and RF and LR were used to distinguish between absence/presence and presence/abundance of fish. The obtained models were compared on the basis of their performances (model accuracy, sensitivity, specificity, Cohen’s kappa and area under ROC curve). Results indicate that RF outperformed LR, for both absence/presence (RF: 84 % accuracy, k = 0.58 and AUC = 0.88; LR: 78 % accuracy, k = 0.54 and AUC = 0.85) and presence/abundance models (RF: 79 % accuracy, k = 0.57 and AUC = 0.87; LR: 69 % accuracy, k = 0.43 and AUC = 0.81). The most important variables, selected in each model, are discussed and compared to the available literature. Lastly, results from models’ application in regulated sites are presented to show the possible use of RF in predicting habitat availability for fish in Alpine streams.
1-15
Vezza, P.
b8f933f4-bd6e-468b-835c-ada608d08ecc
Parasiewicz, P.
f41aeccd-a196-4719-99fe-8fa228b7cc0d
Calles, O.
44ca1592-d8df-4f3f-ad73-3eac284c63c5
Spairani, M.
3f43a432-2aeb-44bb-b90a-9b69eef02e19
Comoglio, C.
49ce7e94-5fd9-4582-8968-c6062c4210d9
January 2014
Vezza, P.
b8f933f4-bd6e-468b-835c-ada608d08ecc
Parasiewicz, P.
f41aeccd-a196-4719-99fe-8fa228b7cc0d
Calles, O.
44ca1592-d8df-4f3f-ad73-3eac284c63c5
Spairani, M.
3f43a432-2aeb-44bb-b90a-9b69eef02e19
Comoglio, C.
49ce7e94-5fd9-4582-8968-c6062c4210d9
Vezza, P., Parasiewicz, P., Calles, O., Spairani, M. and Comoglio, C.
(2014)
Modelling habitat requirements of bullhead (Cottus gobio) in Alpine streams.
Aquatic Sciences, 76 (1), .
(doi:10.1007/s00027-013-0306-7).
Abstract
In the context of water resources planning and management, the prediction of fish distribution related to habitat characteristics is fundamental for the definition of environmental flows and habitat restoration measures. In particular, threatened and endemic fish species should be the targets of biodiversity safeguard and wildlife conservation actions. The recently developed meso-scale habitat model (MesoHABSIM) can provide solutions in this sense by using multivariate statistical techniques to predict fish species distribution and to define habitat suitability criteria. In this research, Random Forests (RF) and Logistic Regressions (LR) models were used to predict the distribution of bullhead (Cottus gobio) as a function of habitat conditions. In ten reference streams of the Alps (NW Italy), 95 mesohabitats were sampled for hydro-morphologic and biological parameters, and RF and LR were used to distinguish between absence/presence and presence/abundance of fish. The obtained models were compared on the basis of their performances (model accuracy, sensitivity, specificity, Cohen’s kappa and area under ROC curve). Results indicate that RF outperformed LR, for both absence/presence (RF: 84 % accuracy, k = 0.58 and AUC = 0.88; LR: 78 % accuracy, k = 0.54 and AUC = 0.85) and presence/abundance models (RF: 79 % accuracy, k = 0.57 and AUC = 0.87; LR: 69 % accuracy, k = 0.43 and AUC = 0.81). The most important variables, selected in each model, are discussed and compared to the available literature. Lastly, results from models’ application in regulated sites are presented to show the possible use of RF in predicting habitat availability for fish in Alpine streams.
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e-pub ahead of print date: 12 September 2013
Published date: January 2014
Organisations:
Water & Environmental Engineering Group
Identifiers
Local EPrints ID: 403160
URI: http://eprints.soton.ac.uk/id/eprint/403160
ISSN: 1015-1621
PURE UUID: d8883442-d54b-4e21-90a2-c20ae532dc1a
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Date deposited: 28 Nov 2016 12:02
Last modified: 15 Mar 2024 03:36
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Author:
P. Vezza
Author:
P. Parasiewicz
Author:
O. Calles
Author:
M. Spairani
Author:
C. Comoglio
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