Flight Costs, Flight Range and the Stopover Ecology of Migrating Birds
1. Flight range equations are a central component in the analysis of avian migration strategies. These equations relate the distance that can be covered to the fuel load that the birds carry. Models of stopover decisions deal with the question of how birds should react to variations in fuel depositi...
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Veröffentlicht in: | The Journal of animal ecology 1997-05, Vol.66 (3), p.297-306 |
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description | 1. Flight range equations are a central component in the analysis of avian migration strategies. These equations relate the distance that can be covered to the fuel load that the birds carry. Models of stopover decisions deal with the question of how birds should react to variations in fuel deposition rates. Time-minimization models generally predict an increasing relationship between departure fuel load and fuel deposition rate. 2. We show that quantitative details of predictions derived from optimality models depend critically on the flight range equation that is used. We use two classes of flight range equations: one class is based on theoretical assumptions of aerodynamics; the other is based on empirical measurements of metabolism during flight. 3. Most empirically derived equations can be written as Y(x) = c[1-(1 + x)-zeta], where 0 < zeta < 1, and c is a constant that includes morphological traits and lean body mass. 4. Patterns of site use and departure loads in environments with discrete stopover sites depend in significant ways on flight costs. 5. Flight range estimates that are based on empirically derived, multivariate equations are sensitive to errors in the estimates of exponents of the equations. Varying some exponents within their confidence limits can alter flight ranges by an order of magnitude. |
doi_str_mv | 10.2307/5976 |
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Flight range equations are a central component in the analysis of avian migration strategies. These equations relate the distance that can be covered to the fuel load that the birds carry. Models of stopover decisions deal with the question of how birds should react to variations in fuel deposition rates. Time-minimization models generally predict an increasing relationship between departure fuel load and fuel deposition rate. 2. We show that quantitative details of predictions derived from optimality models depend critically on the flight range equation that is used. We use two classes of flight range equations: one class is based on theoretical assumptions of aerodynamics; the other is based on empirical measurements of metabolism during flight. 3. Most empirically derived equations can be written as Y(x) = c[1-(1 + x)-zeta], where 0 < zeta < 1, and c is a constant that includes morphological traits and lean body mass. 4. Patterns of site use and departure loads in environments with discrete stopover sites depend in significant ways on flight costs. 5. Flight range estimates that are based on empirically derived, multivariate equations are sensitive to errors in the estimates of exponents of the equations. Varying some exponents within their confidence limits can alter flight ranges by an order of magnitude.</description><identifier>ISSN: 0021-8790</identifier><identifier>EISSN: 1365-2656</identifier><identifier>DOI: 10.2307/5976</identifier><identifier>CODEN: JAECAP</identifier><language>eng</language><publisher>Oxford: British Ecological Society</publisher><subject>Aerial locomotion ; Animal and plant ecology ; Animal ecology ; Animal migration behavior ; Animal wings ; Animal, plant and microbial ecology ; Animals ; Autoecology ; Aves ; Biological and medical sciences ; Birds ; Ecological modeling ; Fundamental and applied biological sciences. 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Flight range equations are a central component in the analysis of avian migration strategies. These equations relate the distance that can be covered to the fuel load that the birds carry. Models of stopover decisions deal with the question of how birds should react to variations in fuel deposition rates. Time-minimization models generally predict an increasing relationship between departure fuel load and fuel deposition rate. 2. We show that quantitative details of predictions derived from optimality models depend critically on the flight range equation that is used. We use two classes of flight range equations: one class is based on theoretical assumptions of aerodynamics; the other is based on empirical measurements of metabolism during flight. 3. Most empirically derived equations can be written as Y(x) = c[1-(1 + x)-zeta], where 0 < zeta < 1, and c is a constant that includes morphological traits and lean body mass. 4. Patterns of site use and departure loads in environments with discrete stopover sites depend in significant ways on flight costs. 5. Flight range estimates that are based on empirically derived, multivariate equations are sensitive to errors in the estimates of exponents of the equations. Varying some exponents within their confidence limits can alter flight ranges by an order of magnitude.</description><subject>Aerial locomotion</subject><subject>Animal and plant ecology</subject><subject>Animal ecology</subject><subject>Animal migration behavior</subject><subject>Animal wings</subject><subject>Animal, plant and microbial ecology</subject><subject>Animals</subject><subject>Autoecology</subject><subject>Aves</subject><subject>Biological and medical sciences</subject><subject>Birds</subject><subject>Ecological modeling</subject><subject>Fundamental and applied biological sciences. 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Flight range equations are a central component in the analysis of avian migration strategies. These equations relate the distance that can be covered to the fuel load that the birds carry. Models of stopover decisions deal with the question of how birds should react to variations in fuel deposition rates. Time-minimization models generally predict an increasing relationship between departure fuel load and fuel deposition rate. 2. We show that quantitative details of predictions derived from optimality models depend critically on the flight range equation that is used. We use two classes of flight range equations: one class is based on theoretical assumptions of aerodynamics; the other is based on empirical measurements of metabolism during flight. 3. Most empirically derived equations can be written as Y(x) = c[1-(1 + x)-zeta], where 0 < zeta < 1, and c is a constant that includes morphological traits and lean body mass. 4. Patterns of site use and departure loads in environments with discrete stopover sites depend in significant ways on flight costs. 5. Flight range estimates that are based on empirically derived, multivariate equations are sensitive to errors in the estimates of exponents of the equations. Varying some exponents within their confidence limits can alter flight ranges by an order of magnitude.</abstract><cop>Oxford</cop><pub>British Ecological Society</pub><doi>10.2307/5976</doi><tpages>10</tpages></addata></record> |
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subjects | Aerial locomotion Animal and plant ecology Animal ecology Animal migration behavior Animal wings Animal, plant and microbial ecology Animals Autoecology Aves Biological and medical sciences Birds Ecological modeling Fundamental and applied biological sciences. Psychology Human ecology Lean body mass Vehicular flight Vertebrata Wing span |
title | Flight Costs, Flight Range and the Stopover Ecology of Migrating Birds |
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