Tuatara: Volume 17, Issue 2, October 1969
Primary Productivity and Nutrient Cycling in Terrestrial Ecosystems — A Review With Particular Reference to New Zealand
Primary Productivity and Nutrient Cycling in Terrestrial Ecosystems
A Review With Particular Reference to New Zealand.
* Now at the Research Division, Ministry of Agriculture and Natural Resources, Ibadan, Nigeria.
Table of Contents
Terms and definitions
Methods used in measuring primary productivity.
Published accounts of productivity.
Efficiency of utilisation of solar energy.
Organic turnover and chemical cycling.
In recent years, exhaustive reviews of literature on organic production, turnover, and nutrient cycling in woodland ecosystems have been made, by Ovington (1962, 1965), Westlake (1963),
* Now at the Research Division, Ministry of Agriculture and Natural Resources, Ibadan, Nigeria.
Rodin and Basilevic (1966), Basilevic and Rodin (1966), Duvigneaud and Denaeyer de Smet (1964). No attempt will be made here to write another detailed review so soon after these, but gaps can be filled in and literature brought up to date, particularly for New Zealand.
2. Terms and Definitions
Because scientists in various disciplines (Agriculture, Forestry, Biology and Oceanography) are interested in measuring productivity, various terms are currently being used to define parameters of production. Ovington (1962) Odum (1959) and Westlake (1963) have each attempted to standardise these terms, but such standardisation has not yet been achieved. The key words i production ecology are biomass, production and productivity, words often freely used, with little thought to meaning. The definitions given below are based partly on those of Ovington (1962) and Westlake (1963).
Biomass:— is the total weight of organic matter, both living and dead, present on a unit area of the ecosystem at any given time. In usage, the word should refer specifically to the plant (phytomass) or animal (zoomass) part of the biomass, except where one is interested in the combination of both. However, the practically measurable plant biomass includes undecomposed litter which may be harbouring litter fauna.
There has been some discrepancy in the definition of ‘biomass’. Zoologists and limnologists have defined it as the living mass (Odum, 1959; Macfadyen, 1963), while botanists and foresters have defined it as the total organic matter, living and dead (Ovington, 1962). Such discrepancy arises from the fact that in zoological and limnological studies, organic matter may be rapidly dissolved or consumed by scavengers as soon as it is dead and may not accumulate as it can in the terrestrial ecosystem. Limiting ‘biomass’ to the living component in terrestrial ecosystem studies is difficult, since it is not often easy to distinguish between living and dead organic matter. For example, how can one separate a dead tracheid or xylem fibre in the heart of wood of a tree when measuring the biomass of the trunk?
Primary production:— refers to the total organic matter produced as a result of photosynthesis and nutrient uptake from the soil. The ‘primary’ preceding production is used to distinguish it from production at the second trophic level (consumption). the conversion of plant organic matter into the body tissue of animals. Primary production is referred to as gross primary production when all organic matter including that used in metabolism is taken into consideration. Often, however, page 51 it is net primary production which can easily be measured. The latter is sometimes referred to as apparent photosynthesis or surplus production. Net primary production is defined as the quantity of organic matter produced over a period of time, less that used in metabolic processes, and including all losses due to litter fall, root sloughing, grazing, and fruit or seed production during that period.
Primary productivity:— is primary production expressed as a rate. For example, if the net primary production is x/kg per hectare within the period of t, then the net primary productivity is x/t kg per hectare per unit of time. Productivity is expressed as dry weight, total carbon, nitrogen or total energy fixed per unit area of the ecosystem per length of time: kg/ha./an. or Kcal/ha./an. Often the terms ‘production’ and ‘productivity’ are used synonymously. No confusion arises when net primary production is measured per unit of time, e.g. ‘pasture production in a paddock in 1965 was 20,000 kg/ha.’ could be expressed as 20,000 kg/ha./an., but if the pasture production was for 1964 and 1965, then productivity becomes 10,000 kg/ha./an. This is commonly referred to as the mean annual net primary productivity, and is the average rate of dry matter production by the ecosystem.
Many published results of rates of organic matter accumulation by tree stands have been expressed as means. Usually, such means are obtained by averaging biomass over stand age. These calculations cannot give good measures of the rate of organic matter accumulation per year since growth rate varies from year to year in the life of a plant and biomass is subject to continuing losses by litter fall and grazing. Such losses are not taken into account in the determination of biomass at the end of a period of several years. The best measure of primary productivity, especially in perennial plants, is the current annual net primary productivity. The current rate of organic matter production changes from year to year, especially in the early years of tree plantations, and shows different patterns for different species.
Ovington (1962) has brought out clearly the differences between current annual and mean annual net productivity.
Economic, agronomic and biological productivity:— In forestry and agriculture, only the economic parts of plants or crops are harvested, e.g. tree boles are removed in forestry grains, tubers and fruits in cropping. Productivity calculated from the economic harvest alone is referred to as economic productivity (Ovington, 1965) and agronomic productivity (Pearson, 1965). It is apparent that productivity based on the calculations from economic harvest would seriously under-rate productivity values. On the other hand, the difficulty of complete harvesting of roots makes it extremely difficult to determine biological productivity accurately.
The terms ‘standing crop’ (= easily extractable biomass), page 52 ‘crop’ (= production) and ‘yield’ (= productivity) are more often used in relation to economic production. These terms and their meanings in production ecology have been discussed in detail by Westlake (1963)
3. Methods Used in Measuring Primary Productivity
The methods in general use in the measurement of biological primary productivity in terrestrial ecosystems have recently been summarised by Woodwell and Bourdeau (1964), Leith (1964), and Newbould (1967). These methods fall into two types; direct and indirect.
A. Direct method
The direct method is based on biomass determined by harvesting and weighing of all organic matter present in a unit area of the ecosystem.
Variations of this technique have been used, depending on the nature of the vegetation to be sampled. For example, in herbaceous ecosystems, grasslands and low-growing perennials, clipping of quadrats has been used e.g. Pearsall and Gorham 1956; Odum, 1960; Ovington et al. 1963; Welch and Rawes, 1965; Robertson and Davis, 1965; Westlake, 1966. To obtain reliable figures of productivity in herbaceous vegetation and grasslands, it is necessary to clip the growth at its maximum biomass before losses start to occur. It is not easy to determine when the vegetation reaches its maximum biomass. Westlake (1963) suggested that maximum biomass is attained at about the seeding stage. This is only true of situations where only one species is involved; different species growing together may reach seeding at different times of the season. When the biomass of herbaceous vegetation is determined at the end or near the end of the growing season, the results can be corrected for productivity by adding the weight of losses in litter fall and grazing, but the latter in turn is difficult to determine.
The clipping technique of course is not suitable for measuring the biomass of forest stands. In one case however, Greenland and Kowal (1960) clear-felled an acre of a 40 year secondary tropical forest in Ghana, and determined the biomass. This is a tedious and very expensive operation.
Harvesting a tree of average bole girth for the stand, obtaining its biomass, and extrapolating to estimate the biomass of the stand.
Dividing the trees within a stand into girth classes and harvesting trees of average girth in each class, and again extrapolating to estimate biomass of the stand.
Technique of every tree summation. A few trees are harvested and the biomass of various components obtained. The results of these are used to draw regression or correlation equations which relate the biomass of tree components (e.g. leaves, branches, etc.) to readily measured parameters (e.g. girth or diameter at breast height). Using the regressions, the biomass of individual trees and hence, that of the tree stand can be estimated. Recently. Baskerville (1965) used similar techniques to estimate biomass of a stand of balsam fir, and calculated possible errors likely to arise by using such methods. Ovington and Madgwick (1959) observed that method (i) gave consistently low results compared with methods (ii) and (iii). It is obvious from this that the so-called tree of average dimensions may not truly be average, for a tree which is average in girth may not be average in other respects.
The techniques discussed above are unsuitable for multistoried natural ecosystems. A few workers have attempted to develop techniques suitable for such ecosystems. Kuroiwa (1960) estimated net annual production of a stand of Abies mariessi by formulae to determine the annual increment due to needles and branches, based on the number of leaves, mean leaf weight, and decrease of leaf number with age. For stem increment he based his formulae on the volume increment between two time intervals, using wood density to estimate weight. Whittaker (1961), working with Rhododendron maximum also estimated total net production by techniques based on various growth parameters. He determined conversion factors between: (a) total net production and current shoot production (b) shoot production and stem wood increment (c) stem wood increment and estimated volume increment.
Pearson (1965) estimated annual production in a different way using partially empirical formulae based on tree dimensions such as radius of trunk at base, height of tree, depth of tree canopy and the numerical density of the species studied.
B. Indirect methods
In view of the difficuties encountered in measuring productivity in complex multistrata perennial ecosystems, a number of indirect methods have been and are still being developed to measure productivity.page 54
A summary of these is presented:
1. The gaseous exchange method
Following the success of plant physiologists in using rate of gas exchange as a measure of photosynthesis, many ecologists and whole-tree physiologists have attempted to measure production in plant communities using similar techniques (Saeki, 1960; Nomoto et al. 1959; Nomoto, 1964; Golley, 1965.) Nomoto (loc. cit.) measured photosynthesis and respiration rates of sun and shade leaves of beech (Fagus sylvatica) in chambers. From his results, making use of leaf quantity, leaf area index (L.A.I.), photosynthesis and light and temperature curves, he derived equations from which he estimated daily and monthly net production for the six months (May to October) of the growing season.
In recent years, complex gas analysers have been used to measure carbon dioxide exchange in detached leaves, excised leaves or attached branches (Bordeau and Woodwell, 1964, and Golley, 1965.) The limitations of such a technique are many: Enclosing leaves or branches in chambers places them in artificial conditions which differ from the ones in which they normally photosynthesise. However, various devices e.g. cooling the chamber, reducing the humidity, may be used to simulate a normal environment. Although this method gives the added advantage of measuring gross production, it is too great a generalisation to extrapolate from the activity of single leaves or even branches to arrive at that of thousands of others in a plant community.
2. The use of leaf area as an index of productivity.
Since the leaf area available for absorbing the incident light will, to a certain extent, determine the rate of photosynthesis, some workers (Watson, 1958; Takeda, 1961: Brougham 1960; Davidson and Donald, 1958; Black, 1963; Rees, 1963;) have attempted to find whether any relationship exists between leaf area and the rate of dry matter production.
Their results indicate that up to a particular value, depending on the plant species, there is a concomitant increase in productivity with increase in leaf area index (L.A.I.) —which is the leaf area per unit of land area. But beyond this value, which has been referred to as ‘optimum leaf area index’ (Kasanaga and Monsi, 1954), there is no further increase in production with increase in leaf area index due to mutual shading. In fact, it has been shown (Watson, 1958; Kanda and Sato, 1963) that at values of L.A.I. above the optimum production declines because of respiratory losses of leaves growing in light intensities below the compensation point, where respiration exceeds photosynthesis. Except perhaps in pasture studies and early stages of growth in trees, L.A.I. cannot be used as an accurate measure of productivity.
3. The use of chlorophyll content as an index of productivity.
The use of chlorophyll as an index of productivity originated from studies on marine production, and seems to have given reliable results on total biomass and productivity of phytoplankton (Manning and Juday, 1941; Harvey, 1950; Ryther and Yentch, 1957). The application of this method in terrestrial ecosystems has been attempted by Bray (1960, 1962). Bray's results indicated that in certain herbaceous species a highly significant correlation (r = +0.82, p <0.01) exists between chlorophyll and dry matter production. Brougham. (1960) also found a highly significant correlation between maximum growth rates and chlorophyll content in field crops.
While this relationship may be of interest in herbaceous ecosystems, it does not appear a feasible method for predicting the productivity of tree or shrub ecosystems.
4. Use of a fraction of total production.
Often, total production has been estimated from production of only a part or parts of trees, e.g. estimating roots from the values of top growth, or total production from quantity of leaf litter. Bray and Gorham (1964) have shown that the yearly litter production cannot be used as an index of productivity.
5. Use of albedo as an index of productivity.
In addition to the methods described above, an attempt has been made to use albedo (i.e. the ratio of the amount of light reflected from the landscape to the total amount falling upon it) as an index of production. As a corollary from his studies on chlorophyll content as an index of productivity, Bray (1961) attempted to find whether any relationship existed between visible albedo and chlorophyll content. He postulated that if albedo could be used as an index of chlorophyll content, it could in turn be used as index of productivity. Working on a series of vegetation types in Minnesota, U.S.A., he established that there was a significant correlation between albedo, chlorophyll concentration and net productivity in upland stands with complete cover.
This method is more of academic than of practical value since the reflection of light from surfaces is dependent on many factors.
Although the harvest method does not take account of respiratory losses, and would under-estimate productivity if losses in litter fall and grazing were not taken into account, it offers the easiest method of measuring productivity in terrestrial ecosystems. The measurements of primary productivity in uneven aged, multistrata forest ecosystems is still a difficult proposition. There is broad scope for the development of new techniques. The methods of Whittaker (1961.) and Pearson (1965) show some promise in this line.
4. Published Accounts of Productivity
Productivity data have been published for various localities of the world, from arctic and arctic-alpine to the tropical regions, and the data reviewed, notably by Ovington (1962. 1965); Westlake (1963); Rodin and Basilevic (1966). For various reasons, comparisons of data from various parts of the world are difficult to make. Apart from the fact that the methods of measurement have often differed, results are often expressed in different ways: fresh weight, oven - dry weight, organic carbon, or ash free dry weight. To compare results expressed in these various ways, conversions have to be made before comparisons are valid. Westlake (1963) commented on the difficulties encountered in comparing results when various criteria have been used in expressing them. Despite these short-comings, Westlake, (loc. cit.) has attempted to make comparisons of productivity for ‘maximum’ sites from various biocenoses—such as phytoplanktons, marine macrophytes, herbs, forests and cultivated plants. His maximum sites were those with the highest recorded data for each of the biocenoses. From Westlake's conclusions and those of Bazilevic and Rodin (1966) and Odum (1959) there is a general agreement that the highest production is in the humid tropics, and the lowest in the arid deserts. Westlake gave a probable mean annual net productivity of 50 ± 20 tons* /hectare for tropical rain forest and agriculture, and 75 ± 15 tons/ha. for tropical reed swamp. This is similar to the figure of 72 tons/ha. estimated for tropical forest by Leith (1964.)
Production ecology is comparatively young in New Zealand. Even though there is much data on yield of pastures and exotic forests, emphasis has been on the agronomic or economic production and there are few published accounts of biological productivity. The following table gives a summary of published studies.
The most productive of the communities studied was the Pinus radiata stand growing on pumice derived soils. It's high productivity has been attributed to its evergreen nature and its long growing season.
It is hoped that more data will be available at the conclusion of the International Biological Programme in which New Zealand is a participant.
5. Efficiency of Utilisation of Solar Energy in Primary Production
The production and accumulation of organic matter by autotrophs in an ecosystem is also a fixation and accumulation of energy within it. The source of this energy is solar energy, which is converted into chemical energy in the process of photosynthesis.
* metric ton = 1000 kg.
|Type of Vegetation||Locality||Net annual Productivity tons/ha.||Source of data|
|Mature beech (Nothofagus truncata) 110 years||Silverstream near Wellington||8.4||Miller (1963)|
|Stand of Pinus radiata quality class II||Near Rotorua||20||Will (1964)|
|Stand of Pinus radiata quality class I||Near Rotorua||35||Will (1966)|
|Ulex europaeus stand, 7-8 years||Taita, near Wellington||18-20||Egunjobi (1967)|
|* Mixed improved pasture||Palmerston||16||Sears et al.|
|Pasture with dry season irrigation (above ground)||—do—||23||Brougham (1959)|
|Mixed improved pasture (above ground)||Taita, near Wellington||13||Egunjobi (1967)|
The energy thus fixed is the motive force that drives the ecosystem and sets a limit to its dynamics. Therefore, the efficiency with which autotrophs convert solar energy into chemical energy is an important factor in the study of ecosystem energetics. This efficiency, which is known as the photosynthetic efficiency, is the ratio of energy fixed in the autotrophs, to the light energy reaching them over the same period. Because of the lack of standardisation of the terms of the ratio, calculations of photosynthetic efficiencies have been based on various measurements. For example photosynthetic efficiencies have been calculated from the energy contained in gross production (Golley, 1960; Bray, 1961), and from the energy contained in net production (Hellmers and Bonner 1959; Ovington and Heitkamp, 1960; Ovington 1961; Will 1964; Minderman, 1967). Some photosynthetic efficiencies have been based on the total incident light energy (Ovington 1961; Minderman 1967), and many on photosynthetically active radiation (Bray, 1961; Golley, 1960; Wassink et al. 1953, Wassink 1958; Hellmers and Bonner, 1959). Bray (loc. cit.) calculated efficiency from the photosynthetically active radiation after allowing for non-pigmented absorption, transmission and albedo.
* Data on agronomic pasture production for various localities covering many years, are now available, and can be obtained from the Department of Agriculture, Wellington.
Although most solarimeters measure the total insolation, only visible light (approximately 400/mic. to 70/mic.) is used in photosynthesis and this fraction is not constant but varies with weather conditions. Recently, McCree (1966) described a modified solarimeter which measures only the photosynthetically active radiation (P.A.R.). At Lower Hutt, New Zealand, he estimated that P.A.R. varied between 48 per cent in bright light to 68 per cent in overcast weather. When calculations are based on the visible light only, it is usual to assume that the fraction is about 50 per cent of the total solar radiation. Bray (1961) estimated the fraction at 48 per cent, while Moon (1940) estimated it at 44 per cent.
Comprehensive reviews of data on efficiency of light energy utilisation by crops and forest have been made by Wassink (1959). Blackman and Black (1959), Hellmers and Bonner (1959) and Hellmers (1964).
Blackman and Black's estimates of photosynthetic efficiency for some field crops in England are considered high when compared to those of other workers. For example he estimated a value of 9.5 per cent for Beta maritima, whilst Wassink recorded a value of 1 to 2 per cent for field crops in Holland, and Heller and Bonner recorded values of 2 to 3 per cent for forest trees in Europe.
In New Zealand, Will (1964) using Penman's formula to estimate available light energy, recorded a photosynthetic efficiency of 3 per cent for Pinus radiata. Egunjobi (1967) recorded 0.4 per cent for unfertilized mixed pasture, 1.1 per cent for fertilized pasture and 1.7 per cent for a mature Ulex europaeus stand. Recalculating Will's data from measured solar energy at Taita, the photosynthetic efficiency of the pine stand would be 2.2 per cent This figure will be higher than those quoted by Hellmer and Bonner (Loc. cit) for forest stands if calculation is based on the production and insolation during the actively growing period as in the latter case.
It is obvious that photosynthesis is an inefficient process. The highest efficiencies are recorded under very low light intensities.page 59
For example during September 1966 (P.A.R. = 4410 × 105 Kcal./ha.) the photosynthetic efficiency in mixed pastures at Taita was 1.8% whereas during the warmer summer month, December, with P.A.R. of 6750 × 105 Kcal./ha. and higher dry matter production, the efficiency was 1.4% (Egunjobi 1967).
6. Organic Turnover and Chemical Cycling
In the natural sequence of growth and development, large amounts of the organic matter accumulated in wood ecosystems die off and return to the soil as litter. Linked with this organic turnover is the biogeochemical cycle, in which chemicals removed from the soil by plants for growth are variously returned to the soil to be reabsorbed into the organic-inorganic systems later, or to be lost to the ecosystem.
The various paths of chemical cycling in woodland ecosystems have been enumerated by Ovington (1962. 1965) and Bormann and Likens (1967). Various aspects of these cycling processes have interested different workers. The cycling of chemicals in terrestrial ecosystems may be discussed under the following headings:
Organic — inorganic cycle (intrasystem cycle of Bormann and Likens 1967).
i. Organic — inorganic cycle:
The aspect in the chemical cycling processes of woodland ecosystems that has been most studied is litter fall. The importance of litter in woodland ecology has been known for almost a century. In 1876, Ebermayer drew attention to the role of forest litter in forest nutrition. Since then many papers have been published on the production and chemical composition of forest litter. In New Zealand Miller and Hurst (1957) and Will (1959) have provided data for litter in native beech forest (Nothofagus truncata) and in Pinus radiata planted forest. In a recent review, Bray and Gorham (1964) reviewed most of the litter studies in the world. Ovington (1965) has shown that in mature tree ecosystems, more nutrients return to the soil in litter annually than are immobilised in the wood. For example more than 80% of most of the nutrients removed by Nothofagus truncata is returned annually in litter fall (Miller, 1963). A similar study made on Ulex europaeus by the author (Egunjobi. 1967) shows that over 70% of the estimated total uptake of Ca, Mg, S, and Si and about 66% of Na and N were returned annually in litter fall and recretion — leaf leaching.
Other cycling processes connected with the organic cycle are root excretion (which cannot easily be measured) and root decomposition on which very little is known. The only published page 60 data on root decomposition are those of Orlov (1953) and Remezov (1959) who claimed that 6000 and 4000 kg/ha./an. of oak and spruce rootlets respectively die in the top 5 cm of the soil.
In a grazed pasture, the cycling processes take a different path. Only small quantities of nutrients return to the soil in the organic turnover, while most return in the faeces and urine of the grazing animals. Sears et al (1942, 1948) and Davies et al (1962) have attempted to measure these processes by harnessing the animals with devices that collected faeces and urine. A comprehensive review of nutrient cycling under grazing has been made by Dale (1963). In all cases, very large fractions of the ingested nutrients are returned in the urine and faeces. For example Davies et al. (loc. cit) recorded that over 80% of the Mg, K and Na, and about 80% of Ca, and 60% of P ingested by dairy cows are returned to the soil annually in this way. The mobility of animals of course leads to the chance that nutrients from one part of the ecosystem may be excreted in another part, or even in another ecosystem.
It is also known that chemicals are leached out of living leaves and plant materials by rain (Stenlid. 1958). The quantities of nutrients in throughfall — i.e. rainfall not intercepted by the vegetation canopy — in woodland ecosystems have been determined in various places, eg. New Zealand (Will, 1959; Miller, 1963; Egunjobi, 1967). South Africa (Mes 1954), Sweden (Tamm, 1951), Ghana (Nye, 1961), Britain (Carlisle et al 1966) Australia (Attiwill, 1966). None of the published work has indicated what fraction of the chemicals in throughfall is due to leaching of nutrients from the canopy. It is difficult to assess this separately since the chemicals in throughfall are an accumulation of what is leached from the foliage, together with washings of particulate matter deposited on the surface of the foliage, and the atmospheric particles in rain. There are indications that a considerable amount of potassium in throughfall is due to foliar leaching.
ii. Chemical accessions to the ecosystem
Chemicals are added to the ecosystem in rain. The source of these chemicals are atmospheric particles which are washed down in rain drops. The origins of these particles may be oceanic, terrestrial, and extra terrestrial (Attiwill, 1966). There are many records of rainfall analyses, which assess the quantities of nutrients coming into the ecosystem in this way. As far back as 1888, Gray (1888, 1910) recorded the amounts of chemicals in rainwater at Lincoln, New Zealand. A considerable interest has been shown in atmospheric chemistry in the past two decades, and data on the chemical composition of rain water are now available for most geographical regions, e.g. for Western Europe (Eriksson, 1952a, 1952b.; Emmanuelson et al 1954; Madgwick and Ovington, 1959) page 61 for North America (Herman and Gorham, 1957) for Australasia (Hutton and Leslie, 1958; Miller, 1961; Westselaar and Hutton, 1963; Attiwell, 1966).
The composition of rain water is greatly influenced by the distance from the sea (Hutton and Leslie, loc cit), proximity to industrial sites and cities and the direction of the prevailing winds.
Other sources of addition of nutrients to the ecosystem are through rock weathering, deposition of products of erosion as in a flood plain, or hill slope and the artificial application of fertilizers.
iii. Losses of chemical elements from the ecosystem
Chemical elements are lost from the ecosystem in soil leaching, surface run off, forest fires, grazing and harvesting of crops. The least documented in the field of ecosystem processes is the study of nutrient losses. Lysimetric studies have been carried out in green house experiments to illustrate movement of chemicals out of soil columns. Viro (1953) Remezov (1961) and Crisp (1966) have attempted measuring chemical losses in drainage by analysing stream-water from catchments. The main difficulty about the interpretation of such analyses is that the composition of water leaving the ecosystem may change by solution or absorption as it moves through the strata between the ecosystems and the stream. Bormann and Likens (1967) gave an elaborate account of how hydrological measurements could be studied together with the measurements of chemical inputs and outputs in an ecosystem. At best, such measurements will be approximations, because of the complexity of watersheds, and of the fact that the bed rock of the watershed is often not impermeable. Borman et al. (1968) have recently published data on nutrient losses on a practically impermeable bed rock.
Forest fires constitute a drain on the nutrient capital of woodland ecosystems. Either by design or by mistake, large tracts of forest are burnt yearly in many parts of the world. Losses of nutrients due to forest fires are hard to assess. Published accounts by Allen (1964), Robertson and Davies (1965) indicate that on the average, over two thirds of the plant nutrients immobilised in a ten year old Calluna vulgaris stand were lost in burning. With the exception of nitrogen and sulphur, this cannot be considered a loss from the ecosystem. It is known, from studies of soil changes following burning (Miller et al. 1955), that the soil is enriched by the mineral ash of the burnt plants.
Grassland farming for meat, milk and wool production constitute some drain on the nutrient capital of the ecosystem. These losses are difficult to measure quantatively. Robertson and Davies (1965) estimated the losses of nutrients from sale of stock grazing on Calluna vulgaris at about 1 kg/ha, for calcium, phosphorus and 2 kg/ha, for nitrogen respectively over a ten year period. The page 62 loss of phosphorus in milk production is known to be high — being about 30% of the-total uptake (Davies et al. 1962).
Nutrients are lost from the ecosystem in timber production. Ovington (1959) estimated possible losses of nutrients, due to harvesting of Pinus sylvestris L. in Britain, and concluded that calcium losses may be considerable.
Although there are vast amounts of data on the various aspects of mineral cycling, there are only a few integrated studies. Only such integrated studies, involving input and output into and from the ecosystem can be of real value in ecosystem studies.
Studies on primary production and solar energy utilisation by terrestrial plants, together with related studies on organic turnover and nutrient cycling are reviewed, paying particular attention to those made in New Zealand. The terms biomass, production, and productivity commonly used in production ecology are defined. Methods generally employed in measurement of primary production in terrestrial ecosystems are critically reviewed.
Difficulties of comparing published data are discussed. Records from New Zealand show that Pinus radiata is the most productive, with an estimate of 35 m.t/ha./an. for a site quality class one.
There are too few published studies on the efficiency of solar energy utilisation by plants in New Zealand. Because of lack of a standard method in measuring parameters on which efficiencies are calculated, published data are hard to compare.
Under woodland conditions over two thirds of the elements removed annually for plant growth are returned in organic turnover and ‘recretion’. In grazed pastures similar amounts of the nutrient uptake are returned in faeces and urine of the grazing animals. There is an input of nutrient into the ecosystem in rainfall, the magnitude and composition of which depends on proximity to cities, industrial sites, seas and oceans. Other natural inputs come from rock weathering and deposition of products of erosion. Losses of elements occur in leaching, run-off water, forest fires, timber removal, and cropping. Many of these losses are difficult to measure quantatively. There is a need for integrated studies involving input and output of minerals into and from an ecosystem.
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Baskerville, G. L. 1965. Estimation of dry matter of tree components and total standing crop in conifer stands. Ecology 46: 867-9.
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Black, J. N. 1963. The interrelationship of solar radiation and leaf area index in determining the rate of dry matter production of swards of subterranean clover (Trifolium subterraneum L.) Aust. J. agric. Res. 14: 20-38.
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—— 1962. The primary productivity of vegetation in central Minnesota, U.S.A. and its relationship in chlorophyll content and albedo. Pp. 102-16 in “Die Stoff-production der Pflanzendecke” (Ed. H. Leith).
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—— 1959 (b). The effects of frequency and intensity of grazing in the productivity of a pasture of short rotation ryegrass and red and white clover, N.Z. Jl. agric. Res. 2: 1232-48.
—— 1960. The relationship between the critical leaf area, total chlorophyll content and maximum growth rate of some pasture crops. Ann. Bot (N.S.) 24: 463-474.
Carlisle, A; Brown A. H. F.; White E. J. 1966. The organic matter and nutrient element in the precipitation beneath a sessile oak (Quercus patreae) canopy. J. Ecol. 54: 87-98.
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