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Browse: Quantity and Nutritive Value of Evergreen and Deciduous Tree Species in Semi-Arid Southern African Savannas

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Browse: Quantity and Nutritive Value of Evergreen and Deciduous Tree Species in Semi-Arid Southern African Savannas BROWSE: QUANTITY AND NUTRITIVE VALUE OF EVERGREEN AND DECIDUOUS TREE SPECIES IN SEMI-ARID SOUTHERN AFRICAN SAVANNAS CARYN ANNE PENDERIS Submitted in fulfilment of the academic requirements for the degree of PHILOSOPHY OF SCIENCE IN THE DISCIPLINE OF GRASSLAND SCIENCE SCHOOL OF BIOLOGICAL AND CONSERVATION SCIENCES FACULTY OF SCIENCE AND AGRICULTURE UNIVERSITY OF KWAZULU-NATAL, PIETERMARITZBURG MARCH 2012 "The tree which moves some to tears of joy is in the eyes of others only a green thing that stands in the way. Some see Nature all ridicule and deformity, and some scarce see Nature at all. But to the eyes of the man of imagination, Nature is Imagination itself." - William Blake, 1799, The Letters II For Benjamin and Isabella May you grow up to love climbing trees as much as I do... III PREFACE This thesis is the result of the author‟s original work except where acknowledged or specifically stated to the contrary in the text. It has not been submitted for any degree or examination at any other university or academic institution. Signed ………………………….. Date ……./……./…….. Caryn Anne Penderis Signed ………………………….. Date ……./……./…….. Prof. Kevin Kirkman (supervisor) IV ABSTRACT Browse selection, intake, utilisation, palatability, quality and production are tightly linked and need to be considered together in trying to improve our understanding of browsing dynamics and the interactions between browsers and vegetation. Such an understanding is necessary in order to re-evaluate determinations of browser carrying capacities and evaluating actual and potential impacts of browsing animals on vegetation composition and diversity. Browser carrying capacity is determined by both the quantity and the nutritive value of forage. The measurement of browse quantity and nutritive value and the matching of browse supply to browser demand are central to sustainable utilisation and the monitoring of vegetation health. South African savannas are poorly studied with respect to tree canopy growth and browse production making it difficult to quantify the available browse biomass on which browsing capacity estimations are based, and consequently difficult to estimate levels of browsing that are sustainable. This study addressed these issues by investigating browse dynamics, broadly aiming to (1) explore factors affecting browse production, biomass and nutritive value; (2) develop models to assess and monitor these parameters across seasons and properties; (3) use the resultant models in improving our understanding of how to determine browser carrying capacities. More specifically, our study sought to examine the effects of plant physiognomy, forage nutritive value, canopy stratum, defoliation, temperature, rainfall and soil nutrient status on the browse production of evergreen (Carissa bispinosa, Euclea divinorum, Gymnosporia senegalensis), semi- deciduous (Spirostachys africana, Ziziphus mucronata) and deciduous (Acacia nilotica, Dichrostachys cinerea) savanna tree species from June 2003 – June 2005 in three sites along the northern Zululand coastline of KwaZulu-Natal. Available browse biomass, during the dry season, of four key savanna tree species (A. nilotica, E. divinorum, G. senegalensis, and S. africana) was estimated through the development of allometric regression equations. Non-linear regression was used to investigate the relation between the leaf dry mass (LDM) and canopy volume (CVol) of each of the four tree species. Exponential V regression (y = a + brlnx) of the natural logarithm of CVol data provided the most accurate and precise description of the tree CVol – LDM relation. A study was undertaken to determine which factors may influence browse production in a southern African savanna. Regression tree models for the browse production identified that the dominant factors influencing browse production were CVol (m3), season, species and height to the lowest leaves of the tree canopy (HL) (m). The length of the growing season had a marked effect on the production potential of savanna tree species, suggesting that improved conditions for growth, i.e. greater rainfall, soil moisture content and improved soil nutrient availability result in a longer period of rapid sustained growth. Species was identified as an important contributing factor to differences in browse production rates, suggesting the need for the development of species or species group models. Mean annual browse production of evergreen trees was greater than that of deciduous and semi-deciduous trees. Mean quarterly (three monthly) browse production was highest, for all trees, during the wet season, with the greatest difference between wet and dry season production being observed in deciduous forms. Evergreen forms showed continuous growth over the whole study, with enhanced growth over the wet season. Deciduous forms, on the other hand, concentrated growth in spurts, when environmental conditions became favourable, with most production occurring during a short growing season. Browse nutritive value was found to be greatest during the wet season, when growth and photosynthesis are at their greatest. Further, browse nutritive value was greatest in deciduous species. Evergreen trees were found to have greater acid detergent fibre (ADF) concentrations than both the deciduous and semi-deciduous trees. By contrast, crude protein (CP) concentrations were greater in semi-deciduous and deciduous species than in evergreen species. The daily CP requirements for maintenance for an adult impala (45 kg) were met by all species over all three study areas and all seasons. Daily CP requirements for growth and lactation, however, were only ever met by deciduous and semi-deciduous species, though this result was not consistent over study areas and seasons. Predictive models for the production of browse on deciduous, semi- deciduous and evergreen trees in northern Zululand were developed using multivariate adaptive regression spline functions. The best predictors of growing VI season browse production in all three tree guilds (defined here as a group of trees having a characteristic mode of living) were primarily measurable tree dimensions, while the prevailing environmental conditions had little impact. Differences in the production, nutritive value and available browse biomass between the different tree forms and seasons have a profound effect on the determination of browser carrying capacities and need to be incorporated into any game or conservation management plan. VII TABLE OF CONTENTS Preface ........................................................................................................... IV Abstract ............................................................................................................ V List of figures ......................................................................................................... XII List of tables ........................................................................................................ XVI Acknowledgements ............................................................................................. XIX Chapter 1. The prediction and measurement of browse quantity and nutritive value ............................................................................................................ 1 Introduction ...................................................................................................................................... 2 Study objectives and approach ...................................................................................................... 3 Background ...................................................................................................................................... 3 Browse quantity .............................................................................................................................. 3 Browse biomass ......................................................................................................................... 5 Estimating browse biomass........................................................................................................ 5 Browser feeding and selection ................................................................................................... 6 Browse production ...................................................................................................................... 7 Determinants of tree growth ..................................................................................................... 10 1) Light .................................................................................................................................. 10 2) Temperature and daylength ............................................................................................. 10 3) Water ................................................................................................................................ 11 4) Growing season ............................................................................................................... 11 5) Soil fertility ........................................................................................................................ 12 6) Tree guild ......................................................................................................................... 12 7) Tree age and size ............................................................................................................. 14 Browse nutritive value .................................................................................................................
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