A new optimal foraging model predicts habitat use by drift-feeding stream minnows
– There is substantial need for models that accurately predict habitat selection by fishes for purposes ranging from the elaboration of ecological theory to the preservation of biodiversity. We have developed a new and highly tractable optimal foraging model for drift‐feeding fishes that is based on...
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Published in | Ecology of freshwater fish Vol. 11; no. 1; pp. 2 - 10 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Oxford, UK
Blackwell Science, Ltd
01.03.2002
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Subjects | |
Online Access | Get full text |
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Abstract | – There is substantial need for models that accurately predict habitat selection by fishes for purposes ranging from the elaboration of ecological theory to the preservation of biodiversity. We have developed a new and highly tractable optimal foraging model for drift‐feeding fishes that is based on the profitability of occupying varying focal‐point velocities in a stream. The basic model can be written as: Ix = (Ex * Px) = {(D * A * V) * [1/(1 + e(b + cV))]} − Sx, where: (1) Ix is the net energy intake at velocity x; (2) E is prey encounter rate; (3) P is prey capture success rate which can be modelled as 1/(1 + e(b + cV)) where b and c are fitting constants from the prey capture success curve; (4) D is the energy content of prey (J/m3) in the drift; (5) A is the visual reactive area of the fish; (6) V is velocity (cm/s); and (7) S is the cost of maintaining position (J/s). Given that D, A and S can be considered constant over the range of velocities occupied by these fishes, the model reduces to e(b + cV) = 1/(cV − 1) which we solved iteratively to yield an optimal focal‐point velocity for species in each sample. We tested the model by comparing its predictions to the mean focal‐point velocities (i.e. microhabitats) occupied by four species of drift‐feeding minnows in two sites in a stream in North Carolina, USA. The model successfully predicted focal‐point velocities occupied by these species (11 out of 14 cases) in three seasonal samples collected over 2 years at two sites. The unsuccessful predictions still were within 2 cm/s of the 95% confidence intervals of mean velocities occupied by fishes, whereas the overall mean deviation between optimal velocities and mean fish velocities was small (range = 0.9 and 3.3 cm/s for the warpaint shiner and the Tennessee shiner, respectively). Available focal‐point velocities ranged from 0–76 to 0–128 cm/s depending on site and season. Our findings represent one of the more rigorous field tests of an optimal foraging/habitat selection model for aquatic organisms because they encompass multiple species and years, and for one species, multiple sites. Because of the ease of parameterization of our model, it should be readily testable in a range of lotic habitats. If validated in other systems, the model should provide critical habitat information that will aid in the management of riverine systems and improve the performance of a variety of currently used management models (e.g. instream flow incremental methodology (IFIM) and total maximum daily load calculations (TMDL)).
Resumen
1. Existe una grave necesidad de modelos que predigan con precisión la selección de hábitat por parte de los peces con fines que van del desarrollo de la teoría ecológica a la conservación de la biodiversidad. Nosotros hemos desarrollado un modelo nuevo y de fácil manejo de alimentación óptima para peces que se alimentan de la deriva que se fundamenta en los diferentes beneficios energéticos derivados de ocupar velocidades focales distintas en un río.
2. El modelo básico puede formularse como: Ix = (Ex * Px) = {(D * A * V) * [1/(1 + e(b + cV))]} − Sx, donde: (1) Ix es el energía neta obtenida a la velocidad, x; (2) V es la velocidad (cm/s); (3) A es el area visual de reacción del pez; (4) D es la energía contenida en las presas (J/m3) en la deriva; (5) E es la tasa de encuentro de presas; (6) P es la probabilidad de captura de la presa, que puede representarse como 1/(1 + e(b + cV)) donde b y c son constantes; y (7) S es el coste de nadar para mantener la posición en la corriente (J/s). Puesto que D, A y S pueden considerarse constantes en el rango de velocidades que ocupan estos peces, el modelo se reduce a e(b + cV) = 1/(cV − 1) que resolvimos iterativamente para obtener una velocidad focal óptima para cada especie en cada muestreo.
3. Probamos el modelo comparando su predicciones con la velocidades focales medias (i.e. microhabitats) ocupadas por cuatro especies de ciprínidos que se alimentan de la deriva en un río de Carolina del Norte. El modelo predijo con éxito las velocidades focales ocupadas por estas especies (11/14 casos) en tres muestreos estacionales llevados a cabo a lo largo de dos años en dos estaciones. Incluso las predicciones fallidas se diferenciaron en menos de 2 cm/s del límite de confianza al 95% CIs de las velocidades medias ocupadas, y la diferencia media entre predicciones y observaciones fue pequeña (rango = 0.9 cm/s warpaint shiner, a 3.3‐cm/s Tennessee shiner). El rango de las velocidades focales medias disponibles fue de 0–76 cm/s a 0–128 cm/s dependiendo de la localidad y estación del año.
4. Nuestros resultados son una de las pruebas de campo más rigurosas de un modelo de alimentación óptima/selección de hábitat para organismos acuáticos puesto que incluyen diversas especies, años y, para una de las especies, localidades. La facilidad de la estima de los parámetros del modelo hace que sea fácil probarlo en diversos hábitats lóticos. Si es validado en ellos, el modelo debería proporcionar información valiosa que ayudará a la gestión de los sistemas fluviales y mejorará los resultados obtenidos a través de varios modelos usados actualmente para la gestión (p.e. IFIM y cálculos TMDL). |
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AbstractList | Abstract
– There is substantial need for models that accurately predict habitat selection by fishes for purposes ranging from the elaboration of ecological theory to the preservation of biodiversity. We have developed a new and highly tractable optimal foraging model for drift‐feeding fishes that is based on the profitability of occupying varying focal‐point velocities in a stream. The basic model can be written as:
I
x
= (
E
x
*
P
x
) = {(
D
*
A
*
V
) * [1/(1 +
e
(
b + cV
)
)]} −
S
x
, where: (1)
I
x
is the net energy intake at velocity
x
; (2)
E
is prey encounter rate; (3)
P
is prey capture success rate which can be modelled as 1/(1 +
e
(
b + cV
)
) where
b
and
c
are fitting constants from the prey capture success curve; (4)
D
is the energy content of prey (J/m
3
) in the drift; (5)
A
is the visual reactive area of the fish; (6)
V
is velocity (cm/s); and (7)
S
is the cost of maintaining position (J/s). Given that
D
,
A
and
S
can be considered constant over the range of velocities occupied by these fishes, the model reduces to
e
(
b + cV
)
= 1/(
cV
− 1) which we solved iteratively to yield an optimal focal‐point velocity for species in each sample. We tested the model by comparing its predictions to the mean focal‐point velocities (i.e. microhabitats) occupied by four species of drift‐feeding minnows in two sites in a stream in North Carolina, USA. The model successfully predicted focal‐point velocities occupied by these species (11 out of 14 cases) in three seasonal samples collected over 2 years at two sites. The unsuccessful predictions still were within 2 cm/s of the 95% confidence intervals of mean velocities occupied by fishes, whereas the overall mean deviation between optimal velocities and mean fish velocities was small (range = 0.9 and 3.3 cm/s for the warpaint shiner and the Tennessee shiner, respectively). Available focal‐point velocities ranged from 0–76 to 0–128 cm/s depending on site and season. Our findings represent one of the more rigorous field tests of an optimal foraging/habitat selection model for aquatic organisms because they encompass multiple species and years, and for one species, multiple sites. Because of the ease of parameterization of our model, it should be readily testable in a range of lotic habitats. If validated in other systems, the model should provide critical habitat information that will aid in the management of riverine systems and improve the performance of a variety of currently used management models (e.g. instream flow incremental methodology (IFIM) and total maximum daily load calculations (TMDL)).
Resumen
1. Existe una grave necesidad de modelos que predigan con precisión la selección de hábitat por parte de los peces con fines que van del desarrollo de la teoría ecológica a la conservación de la biodiversidad. Nosotros hemos desarrollado un modelo nuevo y de fácil manejo de alimentación óptima para peces que se alimentan de la deriva que se fundamenta en los diferentes beneficios energéticos derivados de ocupar velocidades focales distintas en un río.
2. El modelo básico puede formularse como:
I
x
= (
E
x
*
P
x
) = {(
D
*
A
*
V
) * [1/(1 +
e
(
b + cV
)
)]} −
S
x
, donde: (1)
I
x
es el energía neta obtenida a la velocidad,
x
; (2)
V
es la velocidad (cm/s); (3)
A
es el area visual de reacción del pez; (4)
D
es la energía contenida en las presas (J/m
3
) en la deriva; (5)
E
es la tasa de encuentro de presas; (6)
P
es la probabilidad de captura de la presa, que puede representarse como 1/(1 +
e
(
b + cV
)
) donde
b
y
c
son constantes; y (7)
S
es el coste de nadar para mantener la posición en la corriente (J/s). Puesto que
D
,
A
y
S
pueden considerarse constantes en el rango de velocidades que ocupan estos peces, el modelo se reduce a
e
(
b + cV
)
= 1/(
cV
− 1) que resolvimos iterativamente para obtener una velocidad focal óptima para cada especie en cada muestreo.
3. Probamos el modelo comparando su predicciones con la velocidades focales medias (i.e. microhabitats) ocupadas por cuatro especies de ciprínidos que se alimentan de la deriva en un río de Carolina del Norte. El modelo predijo con éxito las velocidades focales ocupadas por estas especies (11/14 casos) en tres muestreos estacionales llevados a cabo a lo largo de dos años en dos estaciones. Incluso las predicciones fallidas se diferenciaron en menos de 2 cm/s del límite de confianza al 95% CIs de las velocidades medias ocupadas, y la diferencia media entre predicciones y observaciones fue pequeña (rango = 0.9 cm/s warpaint shiner, a 3.3‐cm/s Tennessee shiner). El rango de las velocidades focales medias disponibles fue de 0–76 cm/s a 0–128 cm/s dependiendo de la localidad y estación del año.
4. Nuestros resultados son una de las pruebas de campo más rigurosas de un modelo de alimentación óptima/selección de hábitat para organismos acuáticos puesto que incluyen diversas especies, años y, para una de las especies, localidades. La facilidad de la estima de los parámetros del modelo hace que sea fácil probarlo en diversos hábitats lóticos. Si es validado en ellos, el modelo debería proporcionar información valiosa que ayudará a la gestión de los sistemas fluviales y mejorará los resultados obtenidos a través de varios modelos usados actualmente para la gestión (p.e. IFIM y cálculos TMDL). – There is substantial need for models that accurately predict habitat selection by fishes for purposes ranging from the elaboration of ecological theory to the preservation of biodiversity. We have developed a new and highly tractable optimal foraging model for drift‐feeding fishes that is based on the profitability of occupying varying focal‐point velocities in a stream. The basic model can be written as: Ix = (Ex * Px) = {(D * A * V) * [1/(1 + e(b + cV))]} − Sx, where: (1) Ix is the net energy intake at velocity x; (2) E is prey encounter rate; (3) P is prey capture success rate which can be modelled as 1/(1 + e(b + cV)) where b and c are fitting constants from the prey capture success curve; (4) D is the energy content of prey (J/m3) in the drift; (5) A is the visual reactive area of the fish; (6) V is velocity (cm/s); and (7) S is the cost of maintaining position (J/s). Given that D, A and S can be considered constant over the range of velocities occupied by these fishes, the model reduces to e(b + cV) = 1/(cV − 1) which we solved iteratively to yield an optimal focal‐point velocity for species in each sample. We tested the model by comparing its predictions to the mean focal‐point velocities (i.e. microhabitats) occupied by four species of drift‐feeding minnows in two sites in a stream in North Carolina, USA. The model successfully predicted focal‐point velocities occupied by these species (11 out of 14 cases) in three seasonal samples collected over 2 years at two sites. The unsuccessful predictions still were within 2 cm/s of the 95% confidence intervals of mean velocities occupied by fishes, whereas the overall mean deviation between optimal velocities and mean fish velocities was small (range = 0.9 and 3.3 cm/s for the warpaint shiner and the Tennessee shiner, respectively). Available focal‐point velocities ranged from 0–76 to 0–128 cm/s depending on site and season. Our findings represent one of the more rigorous field tests of an optimal foraging/habitat selection model for aquatic organisms because they encompass multiple species and years, and for one species, multiple sites. Because of the ease of parameterization of our model, it should be readily testable in a range of lotic habitats. If validated in other systems, the model should provide critical habitat information that will aid in the management of riverine systems and improve the performance of a variety of currently used management models (e.g. instream flow incremental methodology (IFIM) and total maximum daily load calculations (TMDL)). Resumen 1. Existe una grave necesidad de modelos que predigan con precisión la selección de hábitat por parte de los peces con fines que van del desarrollo de la teoría ecológica a la conservación de la biodiversidad. Nosotros hemos desarrollado un modelo nuevo y de fácil manejo de alimentación óptima para peces que se alimentan de la deriva que se fundamenta en los diferentes beneficios energéticos derivados de ocupar velocidades focales distintas en un río. 2. El modelo básico puede formularse como: Ix = (Ex * Px) = {(D * A * V) * [1/(1 + e(b + cV))]} − Sx, donde: (1) Ix es el energía neta obtenida a la velocidad, x; (2) V es la velocidad (cm/s); (3) A es el area visual de reacción del pez; (4) D es la energía contenida en las presas (J/m3) en la deriva; (5) E es la tasa de encuentro de presas; (6) P es la probabilidad de captura de la presa, que puede representarse como 1/(1 + e(b + cV)) donde b y c son constantes; y (7) S es el coste de nadar para mantener la posición en la corriente (J/s). Puesto que D, A y S pueden considerarse constantes en el rango de velocidades que ocupan estos peces, el modelo se reduce a e(b + cV) = 1/(cV − 1) que resolvimos iterativamente para obtener una velocidad focal óptima para cada especie en cada muestreo. 3. Probamos el modelo comparando su predicciones con la velocidades focales medias (i.e. microhabitats) ocupadas por cuatro especies de ciprínidos que se alimentan de la deriva en un río de Carolina del Norte. El modelo predijo con éxito las velocidades focales ocupadas por estas especies (11/14 casos) en tres muestreos estacionales llevados a cabo a lo largo de dos años en dos estaciones. Incluso las predicciones fallidas se diferenciaron en menos de 2 cm/s del límite de confianza al 95% CIs de las velocidades medias ocupadas, y la diferencia media entre predicciones y observaciones fue pequeña (rango = 0.9 cm/s warpaint shiner, a 3.3‐cm/s Tennessee shiner). El rango de las velocidades focales medias disponibles fue de 0–76 cm/s a 0–128 cm/s dependiendo de la localidad y estación del año. 4. Nuestros resultados son una de las pruebas de campo más rigurosas de un modelo de alimentación óptima/selección de hábitat para organismos acuáticos puesto que incluyen diversas especies, años y, para una de las especies, localidades. La facilidad de la estima de los parámetros del modelo hace que sea fácil probarlo en diversos hábitats lóticos. Si es validado en ellos, el modelo debería proporcionar información valiosa que ayudará a la gestión de los sistemas fluviales y mejorará los resultados obtenidos a través de varios modelos usados actualmente para la gestión (p.e. IFIM y cálculos TMDL). There is substantial need for models that accurately predict habitat selection by fishes for purposes ranging from the elaboration of ecological theory to the preservation of biodiversity. We have developed a new and highly tractable optimal foraging model for drift-feeding fishes that is based on the profitability of occupying varying focal-point velocities in a stream. The basic model can be written as: I sub(x) = (E sub(x) * P sub(x)) = {(D * A * V)* [1/(1 + e super(b + cV)))]} - S sub(x), where: (1) I sub(x) is the net energy intake at velocity x; (2) E is prey encounter rate; (3) P is prey capture success rate which can be modelled as 1/(1 + e super((b + cV))) where b and c are fitting constants from the prey capture success curve; (4) D is the energy content of prey (J/m super(3)) in the drift; (5) A is the visual reactive area of the fish; (6) V is velocity (cm/s); and (7) S is the cost of maintaining position (J/s). Given that D, A and S can be considered constant over the range of velocities occupied by these fishes, the model reduces to e super((b + cV)) = 1/(cV - 1) which we solved iteratively to yield an optimal focal-point velocity for species in each sample. We tested the model by comparing its predictions to the mean focal-point velocities (i.e. microhabitats) occupied by four species of drift-feeding minnows in two sites in a stream in North Carolina, USA. The model successfully predicted focal-point velocities occupied by these species (11 out of 14 cases) in three seasonal samples collected over 2 years at two sites. The unsuccessful predictions still were within 2 cm/s of the 95% confidence intervals of mean velocities occupied by fishes, whereas the overall mean deviation between optimal velocities and mean fish velocities was small (range = 0.9 and 3.3 cm/s for the warpaint shiner and the Tennessee shiner, respectively). Available focal-point velocities ranged from 0-76 to 0-128 cm/s depending on site and season. |
Author | Ratajczak Jr, R. E. Farr, M. D. Grossman, G. D. Rincon, P. A. |
Author_xml | – sequence: 1 givenname: G. D. surname: Grossman fullname: Grossman, G. D. organization: D. B. Warnell School of Forest Resources, University of Georgia, Athens, Georgia, USA, and – sequence: 2 givenname: P. A. surname: Rincon fullname: Rincon, P. A. organization: Departamento de Ecologia Evolutiva, Museo Nacional de Ciencias Naturales, C.S.I.C, C/. Jose Gutierrez Abascal 2, Madrid, Spain – sequence: 3 givenname: M. D. surname: Farr fullname: Farr, M. D. organization: Current address: US Army Corps of Engineers, St Paul, Minnesota, USA – sequence: 4 givenname: R. E. surname: Ratajczak Jr fullname: Ratajczak Jr, R. E. organization: D. B. Warnell School of Forest Resources, University of Georgia, Athens, Georgia, USA, and |
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ContentType | Journal Article |
DBID | BSCLL AAYXX CITATION 7SN C1K F1W H95 L.G |
DOI | 10.1034/j.1600-0633.2002.110102.x |
DatabaseName | Istex CrossRef Ecology Abstracts Environmental Sciences and Pollution Management ASFA: Aquatic Sciences and Fisheries Abstracts Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources Aquatic Science & Fisheries Abstracts (ASFA) Professional |
DatabaseTitle | CrossRef Aquatic Science & Fisheries Abstracts (ASFA) Professional Ecology Abstracts Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources ASFA: Aquatic Sciences and Fisheries Abstracts Environmental Sciences and Pollution Management |
DatabaseTitleList | CrossRef Aquatic Science & Fisheries Abstracts (ASFA) Professional |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Zoology Agriculture |
EISSN | 1600-0633 |
EndPage | 10 |
ExternalDocumentID | 10_1034_j_1600_0633_2002_110102_x EFF110102 ark_67375_WNG_1N8307Q6_3 |
Genre | article |
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Notes | ark:/67375/WNG-1N8307Q6-3 istex:0E0376ADF0F19546B7B9056DE44940F7D789FE13 ArticleID:115 Un resumen en español se incluye detrás del texto principal de este artículo. ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
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PublicationTitle | Ecology of freshwater fish |
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Observations on habitat structure, population regulation, and habitat use with respect to evolutionarily significant units: a landscape approach for lotic systems. American Fisheries Society Symposium 17: 381-391. Grossman, G.D. & Ratajczak, R.E. 1998. Long-term patterns of microhabitat use by fishes in a southern Appalachian stream (1983-1992): effects of hydrologic period, season, and fish length. Ecology of Freshwater Fish 7: 108-131. Meyer, J.L., Sale, M.J., Mulholland, P.J. & Poff, N.L. 1999. Impacts of climate change on aquatic ecosystem functioning and health. Journal of the American Water Resources Association 35: 1373-1386. Werner, E.E. & Hall, D.J. 1979. Foraging efficiency and habitat switching in competing sunfishes. Ecology 60: 256-264. Hughes, N.F. 1998. A model of habitat selection by drift-feeding stream salmonids at different scales. Ecology 79: 281-294. Grand, T.C. & Grant, J.W.A. 1994. 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(e_1_2_6_37_1) 1999 e_1_2_6_19_1 e_1_2_6_13_1 e_1_2_6_36_1 e_1_2_6_35_1 e_1_2_6_11_1 e_1_2_6_34_1 e_1_2_6_12_1 e_1_2_6_17_1 e_1_2_6_15_1 e_1_2_6_16_1 Grossman G.D. (e_1_2_6_14_1) 1995; 17 Hill J. (e_1_2_6_18_1) 1996; 16 e_1_2_6_21_1 e_1_2_6_20_1 e_1_2_6_9_1 e_1_2_6_8_1 e_1_2_6_5_1 e_1_2_6_7_1 e_1_2_6_6_1 e_1_2_6_25_1 e_1_2_6_24_1 e_1_2_6_3_1 e_1_2_6_23_1 e_1_2_6_2_1 e_1_2_6_22_1 North Carolina Wildlife Resources Commission (NCWRC). (e_1_2_6_27_1) 2001 e_1_2_6_29_1 e_1_2_6_28_1 |
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volume: 46 start-page: 145 year: 2001 end-page: 160 article-title: Multi‐scale effects of resource patchiness on foraging behaviour and habitat use by longnose dace, publication-title: Freshwater Biology – year: 2001 – volume: 126 start-page: 65 year: 1997 end-page: 76 article-title: Development and evaluation of alternative habitat suitability criteria for brook trout publication-title: Transactions of the American Fisheries Society – volume: 17 start-page: 381 year: 1995 end-page: 391 article-title: Observations on habitat structure, population regulation, and habitat use with respect to evolutionarily significant units: a landscape approach for lotic systems publication-title: American Fisheries Society Symposium – volume: 53 start-page: 185 year: 1997 end-page: 196 article-title: Foraging site selection by juvenile coho salmon ( ): ideal free distributions of unequal competitors publication-title: Animal Behavior – volume: 44 start-page: 393 year: 1992 end-page: 403 article-title: Group foraging by a stream minnow: shoals or aggregations? publication-title: Animal Behavior – start-page: 25 year: 1989 end-page: 38 – volume: 16 start-page: 190 year: 1996. end-page: 199 article-title: Environmental considerations in licensing hydropower projects: policies and practices at the Federal Energy Regulatory Commission publication-title: American Fisheries Society Symposium – start-page: 303 year: 1990 end-page: 321 – volume: 35 start-page: 1373 year: 1999 end-page: 1386 article-title: Impacts of climate change on aquatic ecosystem functioning and health publication-title: Journal of the American Water Resources Association – volume: 11 start-page: 733 year: 1997 end-page: 756 article-title: Two gerbils of the Negev: a long‐term investigation of optimal habitat selection and its consequences publication-title: Evolutionary Ecology – volume: 74 start-page: 685 year: 1993 end-page: 698 article-title: An energetic model of microhabitat use for rainbow trout and rosyside dace publication-title: Ecology – volume: 68 start-page: 1856 year: 1987 article-title: Habitat selection under predation hazard: test of a model with foraging minnows publication-title: Ecology – volume: 166 start-page: 77 year: 1988 end-page: 93 article-title: Invertebrate drift – a review publication-title: Hydrobiologia – volume: 68 start-page: 651 year: 1987 end-page: 659 article-title: The role of predation in age‐ and size‐related habitat use by stream fishes publication-title: Ecology – volume: 63 start-page: 763 year: 1999 end-page: 772 article-title: The insignificance of statistical significance testing publication-title: Journal of Wildlife Management – start-page: 386 year: 1999. – volume: 62 start-page: 441 year: 1984 end-page: 451 article-title: Profitable stream positions for salmonids: relating specific growth rate to net energy gain publication-title: Canadian Journal of Zoology – volume: 68 start-page: 395 year: 1998 end-page: 420 article-title: Assemblage organization in stream fishes: effects of environmental variation and interspecific interactions publication-title: Ecological Monographs – volume: 63 start-page: 757 year: 1990 end-page: 776 article-title: A comparative study of oxygen consumption by four stream fishes: the effects of season and velocity publication-title: Physiological Zoology – volume: 42 start-page: 210 year: 1985 end-page: 215 article-title: The quantification of stream drift publication-title: Canadian Journal of Fisheries and Aquatic Sciences – volume: 65 start-page: 803 year: 1987 end-page: 811 article-title: Animal decision‐making and its ecological consequences – the future of aquatic ecology and behavior publication-title: Canadian Journal of Zoology – start-page: 612 year: 2000. – volume: 212 start-page: 151 year: 1987 end-page: 176 article-title: Microhabitat use in a stream fish assemblage publication-title: Journal Zoology (London) – volume: 79 start-page: 281 year: 1998 end-page: 294 article-title: A model of habitat selection by drift‐feeding stream salmonids at different scales publication-title: Ecology – start-page: 756 year: 1998. – volume: 76 start-page: 580 year: 1995 end-page: 592 article-title: Ideal free distributions of stream fish: a model and test with minnows, publication-title: Ecology – volume: 7 start-page: 108 year: 1998 end-page: 131 article-title: Long‐term patterns of microhabitat use by fishes in a southern Appalachian stream (1983–1992): effects of hydrologic period, season, and fish length publication-title: Ecology of Freshwater Fish – volume: 66 start-page: 1448 year: 1985. article-title: Grazing minnows, piscivorous bass, and stream algae: dynamics of a strong interaction publication-title: Ecology – start-page: 288 year: 1982. – ident: e_1_2_6_16_1 doi: 10.1890/0012-9615(1998)068[0395:AOISFE]2.0.CO;2 – ident: e_1_2_6_15_1 doi: 10.1111/j.1600-0633.1998.tb00178.x – start-page: 386 volume-title: Ecology of teleost fishes year: 1999 ident: e_1_2_6_37_1 contributor: fullname: Wootton R.J. – ident: e_1_2_6_22_1 doi: 10.2307/3802789 – volume: 16 start-page: 190 year: 1996 ident: e_1_2_6_18_1 article-title: Environmental considerations in licensing hydropower projects: policies and practices at the Federal Energy Regulatory Commission publication-title: American Fisheries Society Symposium contributor: fullname: Hill J. – start-page: 288 volume-title: A guide to stream habitat analysis using the instream flow incremental methodology year: 1982 ident: e_1_2_6_4_1 contributor: fullname: Bovee K. – volume: 17 start-page: 381 year: 1995 ident: e_1_2_6_14_1 article-title: Observations on habitat structure, population regulation, and habitat use with respect to evolutionarily significant units: a landscape approach for lotic systems publication-title: American Fisheries Society Symposium contributor: fullname: Grossman G.D. – ident: e_1_2_6_21_1 doi: 10.1139/f90-228 – ident: e_1_2_6_34_1 doi: 10.1046/j.1365-2427.2001.00654.x – ident: e_1_2_6_3_1 doi: 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threatened and endangered species year: 2001 ident: e_1_2_6_27_1 contributor: fullname: North Carolina Wildlife Resources Commission (NCWRC). – ident: e_1_2_6_29_1 doi: 10.2307/1938007 – start-page: 247 volume-title: Foraging theory year: 1986 ident: e_1_2_6_33_1 contributor: fullname: Stephens D.W. – ident: e_1_2_6_35_1 doi: 10.2307/1941215 – start-page: 612 volume-title: Fishes: an introduction to ichthyology year: 2000 ident: e_1_2_6_26_1 contributor: fullname: Moyle P.B. – ident: e_1_2_6_13_1 doi: 10.1111/j.1469-7998.1987.tb05121.x – ident: e_1_2_6_17_1 doi: 10.1007/BF00634588 – ident: e_1_2_6_2_1 doi: 10.1139/f85-028 |
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Snippet | – There is substantial need for models that accurately predict habitat selection by fishes for purposes ranging from the elaboration of ecological theory to... Abstract – There is substantial need for models that accurately predict habitat selection by fishes for purposes ranging from the elaboration of ecological... There is substantial need for models that accurately predict habitat selection by fishes for purposes ranging from the elaboration of ecological theory to the... |
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SubjectTerms | cost-benefit Cyprinidae focal-point velocity foraging success IFIM interspecific competition microhabitat optimization Pisces stream fishes TMDL |
Title | A new optimal foraging model predicts habitat use by drift-feeding stream minnows |
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