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Copepod Production: the Interplay Between Abiotic Environment, Prey Biochemical Composition and Consumers’ Requirements

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Copepod Production: the Interplay Between Abiotic Environment, Prey Biochemical Composition and Consumers’ Requirements COPEPOD PRODUCTION: THE INTERPLAY BETWEEN ABIOTIC ENVIRONMENT, PREY BIOCHEMICAL COMPOSITION AND CONSUMERS’ REQUIREMENTS Dissertation Zur Erlangung der Würde des Doktors der Naturwissenschaften des Department Biologie, der Fakultaät für Mathematik, Informatik und Naturwissenschaften, der Universität Hamburg vorgelegt von Emmanuel Acheampong aus Breman Esiam, Ghana Hamburg, November 2011 “Nothing in biology makes sense, except in the light of evolution” Theodosius Dobzhansky, 1973 CONTENTS Chapter Title Page Description of model parameters and variables i - ii General summary iii – v Allgemeine Zusammenfassung vi – ix Publication outline x 1 General introduction 1 1.1 Animal nutrition 1 – 2 1.2 Food quality models 3 – 6 1.3 Why copepods matter 6 – 7 1.4 Developing an alternative food quality model 7 – 8 1.4.1 Food quality framework 9 – 11 1.5 Aims 11 – 12 1.6 Outline 12 – 14 2 Food quality model for heterotrophic consumers 15 2.1 Abstract 15 2.2 Introduction 16 – 19 2.3 Model description 19-21 2.3.1 Uptake of biochemical substances 21 – 24 2.3.2 Maintenance 24 – 25 2.3.3 Growth 26 – 28 2.3.4 Food quality 28 – 31 2.4 Parameter determination and model implementation 31 – 36 2.5 Results 36 – 47 2.6 Discussion 47 – 57 3 Egg production by calanoid copepods: limitation by nitrogen 58 or carbon? 3.1 Abstract 58 3.2 Introduction 58 – 63 3.3 Model description 63 – 66 3.3.1 Food quality 66 – 68 3.3.2 Food quality effect on food consumption and metabolic 68 – 78 physiology 3.4 Parameter determination and model implementation 75 – 78 3.5 Results 78 – 88 3.6 Discussion 88 – 93 4 Zooplankton growth: The interplay between temperature 94 and prey biochemical composition 4.1 Abstract 94 4.2 Introduction 94 – 97 4.3 Model description 97 – 100 4.3.1 Model formulation 100 – 103 4.3.1.1 Temperature effect on biochemical requirement 104 – 106 4.3.1.2 Temperature effect on feeding and metabolism 106 – 110 4.4 Parameter determination and model implementation 110 – 117 4.5 Results 117 – 130 4.6 Discussion 131 – 135 CONTENTS Chapter Title Page 5 General discussion 136 5.1 Modelling approach 136 – 140 5.2 Future work 140 – 142 5.3 Future issues 142 Appendices 1 Biochemical composition of marine zooplankton 143 A1.1 Abstract 143 A1.2 Introduction 143 – 145 A1.3 Methods 145 – 152 A1.4 Results 152 – 161 A1.5 Discussion 161 – 129 2 Biochemical composition of phytoplankton 170 A2.1 Abstract 170 A2.2 Introduction 170 – 172 A2.3 Methods 172 – 179 A2.4 Results 180 – 186 A2.5 Discussion 186 – 192 3 Food availability effect on reproductive strategy: the case of 193 Acartia tonsa (Copepoda: Calanoida) A3.1 Abstract 193 A3.2 Introduction 194 – 195 A3.3 Materials and methods 195 A3.3.1 Algal culture 195 A3.3.2 Copepod cultures 196 – 197 A3.3.3 Biochemical analysis 197 A3.3.4 Data analysis 197 - 199 A3.4 Results 199 A3.4.1 Biochemical contents of the algae, copepods and eggs 199 – 201 A3.4.2 Egg size, production rate and biochemical similarities between 201 – 202 experimental organisms A3.5 Discussion 202 A3.5.1 Egg production and biochemical similarities between 202 – 205 experimental organisms A3.5.2 Biochemical constituents of females and eggs 205 – 208 4 Data on the effect of temperature on respiration rate 209 – 210 5 Data on algal size, carbon quota and carbohydrate content of 211 – 214 zooplankton References 215 – 239 Acknowledgements 240 “Eidesstattliche Versicherung” 241 LIST OF MODEL VARIABLE/PARAMETERS, THEIR DESCRIPTION AND UNITS Variables Description Unit T Ambient temperature K ∂ Activation energy for metabolism J b Energy cost for maintenance J.gC -1.d -1 d Energy cost for growth J.gC -1 -1 Z Lmn Minimum lipid content of zooplankton g.animal -1 Z Lmx Maximum lipid content of zooplankton g.animal -1 Z L Required lipid content of zooplankton g.animal h Lipid content control parameter K-1 -1 Z P Required protein content of zooplankton g.animal -1 Z H Required carbohydrate content of adult g.animal copepods -1 βi Structural protein, lipid, or carbohydrate gC.gC requirement of zooplankton for maintenance -1 δi Structural protein, lipid, or carbohydrate gC.gC requirement of zooplankton for growth V Food supply gC.L -1 -1 αi Protein-, lipid-, or carbohydrate composition of gC.gC the food Q Food quality Dimensionless -1 -1 Img Maximum food ingestion rate gC.gC .d -1 -1 Im Minimum food ingestion rate gC.gC .d Zing Food ingestion control parameter Dimensionless -1 -1 Itd Operational threshold for food ingestion gC.gC .d -1 -1 Ic Actual food ingestion rate gC.gC .d -1 wmg Maximum prey capture efficiency L. gC -1 wm Minimum prey capture efficiency L.gC Zceff Prey capture control parameter Dimensionless w Prey capture efficiency L.gC -1 λmg Maximum food assimilation efficiency Dimensionless Minimum food assimilation efficiency Dimensionless λm η Half saturation constant for substrate Dimensionless assimilation i LIST OF MODEL VARIABLE/PARAMETERS, THEIR DESCRIPTION AND UNITS Variables Description Unit λi Chemical-specific assimilation efficiency Dimensionless ρi Fraction of assimilate catabolised for Dimensionless maintenance γ i Fraction of assimilate catabolised to power Dimensionless growth xi Fraction of assimilate catabolised for neither Dimensionless maintenance nor growth -1 -1 FC or Fi C or compound-specific defecation rate gC.gC .d -1 -1 Ac or Ai C or compound-specific assimilation rate gC.gC .d -1 -1 M C or M i C or compound-specific catabolism for gC.gC .d maintenance -1 -1 gC or gi C or compound-specific catabolism to power gC.gC .d growth -1 -1 X C or X i C or compound-specific catabolism for neither gC.gC .d maintenance nor growth -1 -1 G or Gi C or compound-specific growth rate of gC.gC .d zooplankton -1 Kc or Ki C or compound-specific gross growth gC.gC efficiency Ui Maximum utilisation efficiency for each food Dimensionless chemical constituent Li Compound-specific potential to limit Dimensionless zooplankton growth ii General Summary General Summary Ecosystems are complex adaptive systems because their living components are capable of adapting to environmental change, be it biotic or abiotic change. Organisms however can experience adverse consequences if environmental change exceeds levels they can tolerate by relying on their adaptive capabilities. Hence, our ability to understand, predict and mitigate the effects of ecological stressors, such as those associated with global climate change, pollution, and harvesting, depends largely on how we incorporate organismic adaptation into ecological investigations. This is true for trophic ecology as for any other aspect of ecology, because animals demonstrate varying feeding regulation mechanisms in order to satisfy their demands for energy and chemical substances. Most can preferentially feed on prey organisms that promote fitness against disadvantageous ones, and those incapable of prey selection are endowed (by evolution) with physiological capabilities for dealing with disadvantageous food constituents. Hence, trophic adaptation among consumers does not only help define the structure of food webs and thus the complexity of ecological communities, it also determines the fate as well as the ecological transfer efficiency of biomass (and carbon). Adaptive trophic behaviour is however ignored or poorly represented in ecosystem models because a realistic framework, for effecting trophic behaviour, that incorporates relevant natural history details and is capable of providing mechanistic understanding of trophic processes is lacking. Currently in aquatic ecology, trophic behaviour is assumed to be mainly dictated by food quality ( Q ), which is determined by employing food quality models (FQMs) that mimic consumers’ mechanism for anticipating the fitness consequences for feeding on specific prey items. Heuristically however, progress has been limited because previous FQMs are based on frameworks that a priori identify specific food components, usually nitrogen, phosphorus, and/or essential compounds, as pre-eminent or limiting. This suppresses trophic adaptability by negating the effect of habitat conditions (fluctuating temperature, etc), as well as that of consumers’ behaviour and physiology on food quality. This thesis addresses the shortfalls in existing models by proposing a new FQM. The model determines food quality by considering (i) the biochemical characteristics of prey items, (ii) consumers’ demand for energy and structural constituents, and (iii) consumers’ capacity for food intake and metabolism based on physiological principles. It employs parameters that are iii General Summary adaptive to the relevant habitat conditions encountered by consumers. The model relies on the balance between the biochemical composition of prey items and consumer’s requirements to determine the potential fate and utilisation efficiencies of acquired chemical substances. The yardstick for food quality is the potential growth performance of consumers. The form of the model makes it applicable to all heterotrophs. Here, the focus is on copepod consumers because of the critical role they play in aquatic ecosystems. The model has been used to evaluate the growth performance of Acartia tonsa (Copepoda: Calanoida) over wide range of food conditions and the results are consistent with experimental observations. It predicts Acartia ’s response to changes in prey biochemical composition to be unimodal, with growth being highest only when the biochemical composition of the prey imposes no constrain on egg production. This is consistent with experimental observations. Existing food quality models are incapable of this prediction. Hence, the FQM here is a better alternative, which, when employed could help in understanding substrate acquisition and utilisation for growth and reproduction by heterotrophs. This was demonstrated by embedding the FQM here in a secondary production model for a consumer whose food intake and metabolic capabilities are bounded within a maximum threshold needed for growth and maintenance when food is “nutritionally good”, and a minimum threshold needed for only maintenance when food is “nutritionally poor”.
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