The catastrophe of meal eating
J. M. Forbes A C D and P. Gregorini BA Institute of Integrative and Comparative Biology, Faculty of Biological Sciences, University of Leeds, LS2 9JT, UK.
B Corner Ruakura and Morrinsville Roads, Private Bag 3221, Hamilton 3240, New Zealand.
C Present address: 7 Elm Tree Close, Byfleet, Surrey KT14 7NN, UK.
D Corresponding author. Email: jmike210@gmail.com
Animal Production Science 55(3) 350-359 https://doi.org/10.1071/AN14425
Submitted: 20 March 2014 Accepted: 22 April 2014 Published: 5 February 2015
Abstract
Optimisation of feed intake is a major aim of pasture and range management for ruminants and understanding what influences feeding behaviour may play an important role in satisfying this aim. An obstacle to such understanding is the fact that feeding is a two-state variable (eating or not eating, albeit with changes in rate of eating during meals), whereas the likely influencing factors are mostly continuous variables. These include gut-fill, concentrations and rates of utilisation of nutrients and metabolites, and changes in nutrient demand due to growth, reproduction and environment, both climatic and social. Catastrophe theory deals mathematically with situations in which an outcome is discontinuous (e.g. eating or not eating) and influencing variables (‘control’ variables in terms of catastrophe theory) are continuously variable (e.g. physiological and environmental factors affecting feeding). We discuss models of feeding and develop an approach in which the Type 2 catastrophe, illustrated by the bifurcation or cusp diagram, is adapted to use negative feedbacks and capacity to handle food and nutrients as the two controlling factors. Ease of prehension, as expressed by rate of eating, is modelled, as are pauses within, as well as between, meals. Quantification has not yet been attempted and the approach is presented to stimulate new thinking about the modelling and prediction of feeding behaviour and meal dynamics.
Additional keywords: catastrophe theory, feeding behaviour, gut fill, negative feedback, nutrient demand, ruminants.
References
Barboza PS, Parker KL, Hume ID (2009) Integrating nutrient supply and demand in variable environments. In ‘Integrative wildlife nutrition’. pp. 257–284. (Springer-Verlag: Berlin, Heidelberg)Bermudez F, Forbes J, Jones R (1989) Feed intakes and meal patterns of sheep during pregnancy and lactation, and after weaning. Appetite 13, 211–222.
| Feed intakes and meal patterns of sheep during pregnancy and lactation, and after weaning.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaK3c%2FoslOjsQ%3D%3D&md5=1b7434cb1e6fb9022c38d4af0e625116CAS | 2596843PubMed |
Booth D, Mather P (1978) Prototype model of human feeding, growth and obesity. In ‘Hunger models: computable theory of feeding control’. pp. 279–322. (Academic Press: Waltham, MA)
Brobeck JR (1948) Food intake as a mechanism of temperature regulation. The Yale Journal of Biology and Medicine 20, 545–552.
Bryant R, Walpot V, Dalley D, Gibbs S, Edwards G (2010) Manipulating dietary N in perennial ryegrass pastures to reduce N losses in dairy cows in spring. In ‘Australasian dairy science symposium’. (Eds R Bryant, GR Edwards) pp. 97–101. (Caxton Press: Lincoln, New Zealand)
Carvalho PCF, Bremm C, Mezzalira JC, Fonseca L, da Trindade JK, Bonnet OJF, Tischler M, Genro TCM, Nabinger C, Laca EA (2015) Can animal performance be predicted from short-term grazing processes? Animal Production Science 55, 319–327.
| Can animal performance be predicted from short-term grazing processes?Crossref | GoogleScholarGoogle Scholar |
Chilibroste P, Soca P, Mattiauda D, Bentancur O, Robinson P (2007) Short term fasting as a tool to design effective grazing strategies for lactating dairy cattle: a review. Animal Production Science 47, 1075–1084.
| Short term fasting as a tool to design effective grazing strategies for lactating dairy cattle: a review.Crossref | GoogleScholarGoogle Scholar |
Chilibroste P, Gibb MJ, Soca P, Mattiauda DA (2015) Behavioural adaptation of grazing dairy cows to changes in feeding management: do they follow a predictable pattern? Animal Production Science 55, 328–338.
| Behavioural adaptation of grazing dairy cows to changes in feeding management: do they follow a predictable pattern?Crossref | GoogleScholarGoogle Scholar |
Collier G, Johnson DF (1990) The time window of feeding. Physiology & Behavior 48, 771–777.
| The time window of feeding.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaK3M3gsVOrsA%3D%3D&md5=1e463bfca3a87fb74f330706c69b33e8CAS |
Davis JD, Levine MW (1977) A model for the control of ingestion. Psychological Review 84, 379
| A model for the control of ingestion.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaE2s3hsV2luw%3D%3D&md5=b9514e64cff9df79b35c696c29efbd9eCAS | 327497PubMed |
Emmans G, Kyriazakis I (2001) Consequences of genetic change in farm animals on food intake and feeding behaviour. The Proceedings of the Nutrition Society 60, 115–125.
| Consequences of genetic change in farm animals on food intake and feeding behaviour.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD3M3hsVKkuw%3D%3D&md5=4689f59bb0254b43bb624a487cd51b6bCAS | 11310416PubMed |
Forbes JM (1980) A model of the short-term control of feeding in the ruminant: effects of changing animal or feed characteristics. Appetite 1, 21–41.
| A model of the short-term control of feeding in the ruminant: effects of changing animal or feed characteristics.Crossref | GoogleScholarGoogle Scholar |
Forbes J (2007a) ‘Voluntary food intake and diet selection in farm animals.’ (CAB International: Wallingford, UK)
Forbes JM (2007b) A personal view of how ruminant animals control their intake and choice of food: minimal total discomfort. Nutrition Research Reviews 20, 132–146.
| A personal view of how ruminant animals control their intake and choice of food: minimal total discomfort.Crossref | GoogleScholarGoogle Scholar | 19079866PubMed |
Forbes JM, Provenza FD (2000) Integration of learning and metabolic signals into a theory of dietary choice and food intake. In ‘Ruminant physiology: digestion, metabolism, growth and reproduction’. pp. 3–19. (CAB International: Wallingford, UK)
Ginane C, Bonnet M, Baumont R, Revell DK (2015) Feeding behaviour in ruminants: a consequence of interactions between a reward system and the regulation of metabolic homeostasis. Animal Production Science 55, 247–260.
| Feeding behaviour in ruminants: a consequence of interactions between a reward system and the regulation of metabolic homeostasis.Crossref | GoogleScholarGoogle Scholar |
Golubitsky M (1978) An introduction to catastrophe theory and its applications. SIAM Review 20, 352–387.
Gregorini P (2012) Diurnal grazing pattern: its physiological basis and strategic management. Animal Production Science 52, 416–430.
Gregorini P, Gunter S, Masino C, Beck P (2007) Effects of ruminal fill on short‐term herbage intake rate and grazing dynamics of beef heifers. Grass and Forage Science 62, 346–354.
| Effects of ruminal fill on short‐term herbage intake rate and grazing dynamics of beef heifers.Crossref | GoogleScholarGoogle Scholar |
Gregorini P, Clark C, Jago J, Glassey C, McLeod K, Romera A (2009a) Restricting time at pasture: Effects on dairy cow herbage intake, foraging behavior, hunger-related hormones, and metabolite concentration during the first grazing session. Journal of Dairy Science 92, 4572–4580.
| Restricting time at pasture: Effects on dairy cow herbage intake, foraging behavior, hunger-related hormones, and metabolite concentration during the first grazing session.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhtVKqtrzF&md5=41a0ff19f0f328db8ff5bfb7873b3dccCAS | 19700720PubMed |
Gregorini P, Soder K, Kensinger R (2009b) Effects of rumen fill on short-term ingestive behavior and circulating concentrations of ghrelin, insulin, and glucose of dairy cows foraging vegetative micro-swards. Journal of Dairy Science 92, 2095–2105.
| Effects of rumen fill on short-term ingestive behavior and circulating concentrations of ghrelin, insulin, and glucose of dairy cows foraging vegetative micro-swards.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXlsFymsrY%3D&md5=a5f983da2f9ce6eb7d622a7d8333cc8bCAS | 19389967PubMed |
Gregorini P, Beukes P, Bryant R, Romera A (2010) A brief overview and simulation of the effects of some feeding strategies on nitrogen excretion and enteric methane emission from grazing dairy cows. In ‘Proceedings of the 4th Australasian Dairy Science Symposium’. (Eds G Edwards, R Bryant) pp. 29–43. (Caxton Press: Lincoln, New Zealand)
Gregorini P, Beukes PC, Romera AJ, Levy G, Hanigan MD (2013) A model of diurnal grazing patterns and herbage intake of a dairy cow, MINDY: model description. Ecological Modelling 270, 11–29.
| A model of diurnal grazing patterns and herbage intake of a dairy cow, MINDY: model description.Crossref | GoogleScholarGoogle Scholar |
Gregorini P, Waghorn G, Macdonald K (2014) Dairy cows with low residual feed intake graze more efficiently. Proceedings of the Australian Society of Animal Production 30, 90
Gregorini P, Villalba JJ, Provenza FD, Beukes PC, Forbes JM (2015) Modelling preference and diet selection patterns by grazing ruminants: a development in a mechanistic model of a grazing dairy cow, MINDY. Animal Production Science 55, 360–375.
| Modelling preference and diet selection patterns by grazing ruminants: a development in a mechanistic model of a grazing dairy cow, MINDY.Crossref | GoogleScholarGoogle Scholar |
Illius A, Jessop N, Gill M (2000) Mathematical models of food intake and metabolism in ruminants. In ‘Ruminant physiology, digestion, metabolism growth and reproduction’. (Ed. PB Cronjé) pp. 21–40. (CABI Publishing: Wallingford, UK)
Ingrand S, Agabriel J, Dedieu B, Lassalas J (2000) Effects of within-group homogeneity of physiological state on individual feeding behaviour of loose-housed Charolais cows. Annales de Zootechnie 49, 15–27.
| Effects of within-group homogeneity of physiological state on individual feeding behaviour of loose-housed Charolais cows.Crossref | GoogleScholarGoogle Scholar |
Jones DD (1977) Catastrophe theory applied to ecological systems. Simulation 29, 1–15.
| Catastrophe theory applied to ecological systems.Crossref | GoogleScholarGoogle Scholar |
Kyriazakis I, Tolkamp BJ, Emmans G (1999) Diet selection and animal state: an integrative framework. The Proceedings of the Nutrition Society 58, 765–772.
| Diet selection and animal state: an integrative framework.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD3c3nsVynsQ%3D%3D&md5=585019d6f4b1a7b394de22f32a4c48d4CAS | 10817142PubMed |
Lockwood JA, Lockwood DR (1993) Catastrophe theory: a unified paradigm for rangeland ecosystem dynamics. Journal of Range Management 46, 282–288.
| Catastrophe theory: a unified paradigm for rangeland ecosystem dynamics.Crossref | GoogleScholarGoogle Scholar |
Loehle C (1985) Optimal stocking for semi-desert range: a catastrophe theory model. Ecological Modelling 27, 285–297.
| Optimal stocking for semi-desert range: a catastrophe theory model.Crossref | GoogleScholarGoogle Scholar |
Mayer J (1953) Glucostatic mechanism of regulation of food intake. The New England Journal of Medicine 249, 13–16.
| Glucostatic mechanism of regulation of food intake.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaG3s%2FovVKmuw%3D%3D&md5=eb188a54a3f9eaefd2968ab35b713f0cCAS | 13063674PubMed |
McFarland D (1978) Hunger in interaction with other aspects of motivation. In ‘Hunger models, computable theory of feeding control’. (Ed. DA Booth) pp. 315–406. (Academic Press: New York)
Meuret M, Provenza F (2015) How French shepherds create meal sequences to stimulate intake and optimise use of forage diversity on rangeland. Animal Production Science 55, 309–318.
| How French shepherds create meal sequences to stimulate intake and optimise use of forage diversity on rangeland.Crossref | GoogleScholarGoogle Scholar |
Moore BD, Wiggins NL, Marsh KJ, Dearling MD, Foley WJ (2015) Translating physiological signals to changes in feeding behaviour in mammals and the future effects of global climate change. Animal Production Science 55, 272–283.
| Translating physiological signals to changes in feeding behaviour in mammals and the future effects of global climate change.Crossref | GoogleScholarGoogle Scholar |
Owens F, Secrist D, Hill W, Gill D (1998) Acidosis in cattle: a review. Journal of Animal Science 76, 275–286.
Pittroff W, Kothmann MM (2001) Quantitative prediction of feed intake in ruminants: III. Comparative example calculations and discussion. Livestock Production Science 71, 171–181.
| Quantitative prediction of feed intake in ruminants: III. Comparative example calculations and discussion.Crossref | GoogleScholarGoogle Scholar |
Poppi D, Gill M, France J (1994) Integration of theories of intake regulation in growing ruminants. Journal of Theoretical Biology 167, 129–145.
| Integration of theories of intake regulation in growing ruminants.Crossref | GoogleScholarGoogle Scholar |
Provenza FD, Villalba JJ, Dziba L, Atwood SB, Banner RE (2003) Linking herbivore experience, varied diets, and plant biochemical diversity. Small Ruminant Research 49, 257–274.
| Linking herbivore experience, varied diets, and plant biochemical diversity.Crossref | GoogleScholarGoogle Scholar |
Rhind S, McMillen S, Duff E, Hirst D, Wright S (1998) Seasonality of meal patterns and hormonal correlates in red deer. Physiology & Behavior 65, 295–302.
| Seasonality of meal patterns and hormonal correlates in red deer.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK1cXnvVens78%3D&md5=88a172c67172e3151b16912e8af337a0CAS |
Robbin J (2013) ‘Thom’s Catastrophe Theory and Zeeman’s model of the Stock Market.’ Available at https://www.math.wisc.edu/~robbin/catastrophe/catastrophe_talk.pdf [Verified May 2014]
Roche JR, Blache D, Kay JK, Miller DR, Sheahan AJ, Miller DW (2008) Neuroendocrine and physiological regulation of intake with particular reference to domesticated ruminant animals. Nutrition Research Reviews 21, 207–234.
| Neuroendocrine and physiological regulation of intake with particular reference to domesticated ruminant animals.Crossref | GoogleScholarGoogle Scholar | 19087372PubMed |
Saunders PT (1980) ‘An introduction to catastrophe theory.’ (Cambridge University Press: Cambridge, UK)
Sheahan A, Boston R, Roche J (2013) Diurnal patterns of grazing behavior and humoral factors in supplemented dairy cows. Journal of Dairy Science 96, 3201–3210.
| Diurnal patterns of grazing behavior and humoral factors in supplemented dairy cows.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXjtlyktbo%3D&md5=d8dc46afeed208adc45b65471fab8148CAS | 23453522PubMed |
Sibbald A (1994) Effect of changing daylength on the diurnal pattern of intake and feeding behaviour in penned red deer (Cervus elaphus). Appetite 22, 197–203.
| Effect of changing daylength on the diurnal pattern of intake and feeding behaviour in penned red deer (Cervus elaphus).Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaK2M%2FntVSrtg%3D%3D&md5=34252475c8e2dd8067f77cdd4e4dcbe5CAS | 7979338PubMed |
Thom R (1975) ‘Structural stability and morphogenesis: an outline of a general theory of models.’ (Translated by DH Fowler) (W. A. Benjamin Inc.: Reading, PA)
Toates F (1974) Control of food intake by energy supply. Nature 251, 710–711.
| Control of food intake by energy supply.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaE2M%2FksFejtQ%3D%3D&md5=84af6133adf660372f9733ce63db9056CAS | 4427665PubMed |
Tolkamp B, Kyriazakis I (1999a) A comparison of five methods that estimate meal criteria for cattle. Animal Science 69, 501–514.
Tolkamp BJ, Kyriazakis I (1999b) To split behaviour into bouts, log-transform the intervals. Animal Behaviour 57, 807–817.
| To split behaviour into bouts, log-transform the intervals.Crossref | GoogleScholarGoogle Scholar | 10202089PubMed |
Tolkamp B, Allcroft D, Austin E, Nielsen BL, Kyriazakis I (1998) Satiety splits feeding behaviour into bouts. Journal of Theoretical Biology 194, 235–250.
| Satiety splits feeding behaviour into bouts.Crossref | GoogleScholarGoogle Scholar | 9778436PubMed |
Van der Maas HL, Molenaar PC (1992) Stagewise cognitive development: an application of catastrophe theory. Psychological Review 99, 395–417.
| Stagewise cognitive development: an application of catastrophe theory.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaK38zms1Kltw%3D%3D&md5=d75548f3331b14362061b75969b2222eCAS | 1502272PubMed |
Villalba JJ, Provenza FD, Catanese F, Distel RA (2015) Understanding and manipulating diet choice in grazing animals. Animal Production Science 55, 261–271.
| Understanding and manipulating diet choice in grazing animals.Crossref | GoogleScholarGoogle Scholar |
Woodcock A, Davis M (1980) ‘Catastrophe theory.’ (Pelican Books: Harmondsworth, Middlesex)
Yeates M, Tolkamp B, Allcroft D, Kyriazakis I (2001) The use of mixed distribution models to determine bout criteria for analysis of animal behaviour. Journal of Theoretical Biology 213, 413–425.
| The use of mixed distribution models to determine bout criteria for analysis of animal behaviour.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD3Mnpt1ejtQ%3D%3D&md5=9d049beba5da798febafb1d2b8aa161cCAS | 11735288PubMed |
Zahler RS, Sussmann HJ (1977) Claims and accomplishments of applied catastrophe theory. Nature 269, 759–763.
| Claims and accomplishments of applied catastrophe theory.Crossref | GoogleScholarGoogle Scholar |
Zeeman EC (1978) A catastrophe theory of anorexia nervosa. In ‘Hunger models: computable theory of feeding control’. (Ed. DS Booth) pp. 407–422. (Academic Press: London)