Some neglected aspects of vegetation classification in integrated surveys

J. theor. Biol. (1984) 108, 663-674

Some Neglected

Aspects of Vegetation Classification in Integrated Surveyst

R. STORY AND TONI A. PAINE

CSIRO, Division of Water and Land Resources, P.O. Box 1666, Canberra City, A.C.T. 2601, Australia (Received 20 June 1983 and in revised form 9 January 1984) This paper discusses some neglected aspects of vegetation classification in integrated surveys and attempts to devise an unambiguous scheme for classifying the vegetation iia which a particular diagnostic point has fallen. It is concluded that there is no practicable method for doing so which is both logical in application and applicable to every situation. Hence the case is argued for the role of subjective and arbitrary decisions in the matter.

Introduction Since the integrated survey method was established by Christian & Stewart in 1953, it has been applied by many other workers in Australia and overseas, particularly in Canada. Australian examples are the Land Research Series of CSIRO, comprising 39 publications, and the reports of the Soil Conservation Authority of Victoria. Overseas examples are listed by Ducruc (1980) and Laughlin, Basinski & Cocks (1981). Such surveys often deal with large tracts of land which have been little attected by human activity. The surveys differ from single-discipline surveys in that they consist in information pooled from various sciences, e.g. geology, geomorphology, pedology, and botany, usually provided by members of a team who are trained respectively. The work is based on aerial photographic interpretation which is then checked in the field at a number of reference points, preselected from the photographs in areas least disturbed, with observations extrapolated where extensive thinning or clearing has been done. In Australia the definitive classification is usually made in the field, since the information presented by the 1:80 000 photographs in routine use is too crowded to admit of direct classification of acceptable accuracy except in open communities. Very close co-ordination is essential to ensure that rock, soil, aspect, slope, and vegetation are investigated at the same point; in a complex environment particularly, one of the observations misplaced by even a few metres can indicate a totally wrong affinity. This is brought out t This paper is part of the "Unsolved Problems in Biology" series. 663 0022-5193/84/120663 + 12 $03.00/0

O 1984 Academic Press Inc. (London) Ltd.

664

R. S T O R Y A N D T. A. P A I N E

FIG. 1. Micro-habitat and vegetation must be examined at precisely the same place to avoid a faulty correlation. (Aerial photo supplied by the Surveyor-General, Queensland and reproduced by arrangement with the Queensland Government. Crown Copyright Reserved.) Scale 1:25 000.

in Fig. 1, which shows the influence of some habitat factor on tree density over the range from closed forest through woodland to grassland. Vegetation types often intergrade rather than form discrete communities, and some arbitrary cut-off must then be made to distinguish between them. Arbitrary though it is, this cut-off can be tied to gradational changes in the environment to give meaningful correlations between vegetation and habitat so that practical applications can follow.

NEGLECTED

ASPECTS

OF

CLASSIFICATION

665

Examples of matters that have been revealed by such surveys are the absence of Eucalyptus crebra on basalt-derived soils in the Hunter Valley (Story et al., 1963) and the relation of certain types of forest, woodland, and grassland to different soils (e.g. land units 72, 73, 75, 99, and 110 in Gunn & Nix, 1977). A floristic approach, (as with Eucalyptus crebra), is more objective than a structural one in that species are fixed in terms of type specimens that are internationally recognized, and floristic features should be taken into account to produce the most accurate classification where only the vegetation is being studied. For the integrated survey the vegetation is classified less for its own sake than for its indicator value. For this reason the structural approach is the usual choice because it reflects more accurately the total physical environment that these surveys aim to portray, e.g. it is the structure rather than the floristics of the Amazon and Congo rainforests that reflects the similarity of these two habitats. A second reason is because of heavy reliance on aerial photography, where floristics are not as easily perceived as is structure. The structural feature used to most advantage is crown spacing, since regional surveys are now generally based on small-scale photos which will show this while precluding detailed examination of layering and growth form. Even so, consistent classification according to crown spacing is not straightforward, and the relation of habitat and vegetation on integrated surveys is consequently often ill-defined. This study was undertaken in an attempt to find an objective and practical way of overcoming the difficulty. Method

We confine the discussion to the classification at a particular point of the three categories forest, woodland, and grassland as we have defined them in Table 1, but wider applications are apparent for their subdivisions, for other vegetation categories, and for the land forms. We deal with the following matters in the order given: the need for a minimal area for observations; the structure of the minimal area; application and shortcomings of the minimal area; other observational methods and their shortcomings; conclusions and recommendations. THE

NEED

FOR A MINIMAL

AREA

FOR OBSERVATIONS

The differentiation between forest, woodland and grassland is in terms of the proportional cover of trees and grasses. Within this constraint it is a matter of choice how the tree cover is expressed and where one draws the line between one category and the next, the choice being unimportant

666

R. STORY

AND

T. A. PAINE

provided each author defines his terms and then abides by them. Some criteria for the three categories are set out in Table 1. All of them neglect the size and shape of the area to be classified. This limits their applicability, for unless the observational area is large enough it may omit one of the components and unless it is small enough it may straddle other vegetation categories. And unless shape is appropriately defined, a treeless observational area in woodland can be manipulated by way of grassy corridors to reach almost any size and yet remain treeless. It is therefore necessary to apply strict criteria of size and shape if the work is to be objective. A logical approach to the problem is to consider the smallest and simplest possible area of a particular vegetation category. It is well known that the true nature of a plant community does not appear before a certain minimal area of it is examined (Beadle & Costin, 1952; Goodall, 1954, 1961; GreigSmith, 1964). The term has been used both for structure and floristics and differs in size accordingly, e.g. the floristics of tropical rainforest would demand a far larger minimal area than structure would. We are using the term only in a structural sense in the account that follows. STRUCTURE

OF THE

MINIMAL

AREA

This is conveniently considered with respect to woodland, for simplicity's sake in terms of uniform-sized trees uniformly spaced over a grassy floor. (1) As the survey observations, although tied to points, are made on areas, a single tree or a straight row of single trees in grassland should be listed under grassland as being a "non-area" (Fig. 2(a)), and the simplest allowable plot of woodland should comprise a triangle of three trees. It follows that at the transitions to grassland and to forest, where woodland has respectively the widest and the closest permissible spacing of trees, the triangle must be equilateral. Between these limits its shape is immaterial. (2) The criterion we adopt for woodland (Table 1) is three trees mutually not more than 20 crown diameters from one another edge to edge (which would constitute grassland) and not less than half a crown diameter (which would constitute forest). We use a nominal crown diameter of 5 m, which may be taken as a rough average for Australian woodland trees. It standardizes these distances at 100 and 2.5 m respectively. (3) A patch of closed forest in grassland has a sharp and obvious boundary at the canopy projection of the outermost trees. If, however, the patch is grassy woodland the boundary is not so easily established, as the trees are separated by a cover of grasses which is part of the woodland and must logically extend round each tree in a circle of radius 52.5 m (10.5 crown diameters), as shown in Fig. 2(b). We will refer to it as the circle o f influence.

<0.5

0-0.25

<0

Touching or nearly so

30-70%

70%

Overlapping

30-70%

Open-forest

70-100%

Closed-forest

* Percent of ground surface directly under foliage.

Specht et aL (1974), projective foliage cover of trees* Grant & Finlayson (1978), as for Specht et aL Walker & Hopkins (1984), crown separation edge to edge, in crown diameters Grant & Finlayson (1978), crown separation edge to edge, in crown diameters Story and Paine, crown separation edge to edge, in crown diameters

Criteria

1-20

0.25-10%

< 10%

Open-woodland

Not touching, More than 1 up to 1 crown crown width width apart apart 0.5-20

0-25-1

10-30%

10-30%

Woodland

Some criteria used f o r forest, woodland and grassland in Australia

TABLE 1

Less than 1 tree per 75 m >20

>20

<0.25%

Grassland

-,-I

Z

'11

(/)

t-

'11

O

uq

(3

(/3 "0 re

re

o

re

re

Z

668

R. S T O R Y

(o)

AND

T. A. PAINE

(b)

I

I

(d)

I 75rn

(e)

(g)

(f)

E

q°

L

(h)

., )

/i\

FIG. 2. Minimal areas, crowns 5 m diam. (Not to scale). (a) Straight row of single trees in single file (disregarded); (b) woodland minimal area at the cut-off to grassland; (c) forest minimal area at the cut-off to woodland and woodland minimal area at the cut-off to forest; (d) and (e) minimal areas where the trees form scalene or isosceles triangles; (f) and (g) unclassified vegetation (mixed woodland and forest spacing), any included point without status; (h) woodland minimal area invalidated by forest, point x in forest, points y and z without status; (i) trees mutually beyond woodland spacing, any included point in grassland; (j) trees at woodland spacing but not mutually, any included point in grassland; (k) two trees at woodland or forest spacing, nearest neighbour beyond woodland spacing, any included point in grassland; (I) standard plot for all categories.

(4) A c c o r d i n g to o u r definition, the m i n i m a l a r e a o f w o o d l a n d at the cut-off to g r a s s l a n d is t h e r e f o r e t h a t o f Fig. 2(b). Its size is 9.586 r 2, w h e r e r is t h e r a d i u s o f the circle o f i n f l u e n c e ; t h a t is, 26 420 m 2. T h e c a l c u l a t i o n for this a n d o t h e r m i n i m a l a r e a s is g i v e n in the a p p e n d i x . (5) O n t h e s a m e p r e c e p t s the m i n i m a l a r e a o f w o o d l a n d at t h e cut-off to forest is t h a t o f the o v e r l a p p i n g circles in Fig. 2(c), with s p a c i n g b e t w e e n c r o w n s 2-5 m ( h a l f t h e c r o w n d i a m e t e r ) . T h e a r e a is 9864 m 2. (6) I f t h e trees f o r m a s c a l e n e t r i a n g l e o r a n isosceles t r i a n g l e t h e m i n i m a l a r e a is r a d i a l l y a s y m m e t r i c a l (Figs 2(d) a n d (e)).

NEGLECTED

ASPECTS

OF

669

CLASSIFICATION

(7) Grassland is classified "by default" in that a point can fall into this category only after it fails to meet the requirements of either forest or woodland.

APPLICATION

AND

SHORTCOMINGS

OF THE

MINIMAL

AREA

The simplicity of this concept is offset by the complexity of its practical application; the flow chart (Fig. 3) shows the difficulties that could be expected, and we doubt if we have foreseen them all. The following points are noteworthy. First, it is impracticable to measure the spacing in terms of a variable crown diameter. A standard average must be used. Second, the three nearest trees provide an initial step towards ascertaining which to consider. They are not necessarily the determinatives (Fig. 2(c) Point b). Third, some minimal areas cannot be classified. The examples in Figs 2(0 and (g) combine forest and woodland spacing without being adequate for either. Any point in Fig. 2(f) or (g) is without status. Fourth, a woodland minimal area may contain a forest minimal area, as shown in Fig. 2(h). It is thus invalidated, for one of the requirements mentioned previously is that the observational area should not straddle other vegetation categories. Points y and z are therefore without status. Point x, however, is unequivocally in forest because of the ranking implicit in the definitions we have chosen, in which forest takes precedence over woodland and woodland over grassland, thus woodland influence cuts out at the forest edge. Fifth, a woodland or forest minimal area may contain an area of grassland, as shown in Fig. 2(b) (Point v). Although it cannot exceed 1.7% of the total area (see appendix) it is nevertheless a flaw in the concept. In view of these imperfectibns, we have considered whether the minimal area concept can be modified for consistent compatibility with this type of observation, e.g. by varying the circle of influence according to the spacing, but in each of those we have tested, there has been some rational objection. This applies also to the other observational methods we have tested. They are set out in the following section.

OTHER

OBSERVATIONAL

METHODS

AND

THEIR

SHORTCOMINGS

Walker & Tunstall (1981) cite a number of authors who have assessed vegetation structure in various ways in terms of crown, canopy, and foliage cover. None of the methods takes into account the size and shape of the observational area and for the reasons stated they also cannot be used to classify the vegetation round a particular point.

START

II I

t

Pointin FOREST

Point in WOODLAND (Fig. 2(c) Point b)

I TRUE

Woodland influence free from forest

I TRUE

I Point within woodland influence

[

I TRUE

1

m

I

I Point within f ..... influ- IFALSE ence (Fig. 2(h) Point x}

~TRUE

Trees mutually at forest spacing

Point in GRASSLAND (Fig. 2(b) Point v)

Point in UNCLASSIF IABLE vegetation (Fig. 2(h) Point z)

Point in GRASSLAND I (Fig. 2(h) Point o)

FALSE ,

I T~..~ I ~

I Point in GRASSLAND 1 (Point r)

~TRUE

woodland spacing (Fig. 2(i))

j Treesmutuallybeyond

I FALSE

Mixed woodland and forest spacing (Fig. 2(f), (g))

I FALSE

Two trees at woodland I or forest spacing,nearest ~ neighbourbeyond wood. land spacing(Fig. 2(k)l

I FALSE

Point in UNCLASSlFIARLE vegetation (Points u, p)

Point in GRASSLAND (Points t. $)

Treesat woodland spacingI TRUE ( Point in GRASSLAND I~[but not mutually (Fig. 2 ( j ) l J ~ ' ~ (Point q)

FIG. 3. To establish the category, as defined, of forest, woodland, and grassland (forest---crowns less than 2-5 m or ½diameter apart edge to edge; woodland---crowns spaced beyond this and up to 100 m or 20 diameters apart; otherwise grassland).

Point in UNCLASSIFIABLE vegetation (Fig. 2(h) Point y)

(Pointsa, c,d.e)

Point inWOODLAND I

I TRUE

E

I FALSE~~

I Woodland influence free I from forest (Fig. 2 (bL (c), d. e |

~ TRUE

three nearesttrees

~TRUE

Point within forest or woodland influence of nearesttree

by

I

NEGLECTED

ASPECTS OF C L A S S I F I C A T I O N

671

Four methods o f plotless sampling reviewed by Greig-Smith (1964) are shown in Fig. 4. The significant word is sampling. It is a process that illustrates the quality o f the source through the mean value of a number of observations, and as such is not applicable to the independent observations that are the concern o f this paper. Consider the implications if these four methods were used for independent observations. In the first three, the density is derived from no more than two trees, hence two trees only would constitute forest if they were close enough together. As for the last (Fig. 4(d)), consider a point on the outskirts of a patch of woodland, within the circles of influence of the woodland trees and thus logically in woodland. If even one of the quadrants is treeless for a sufficient distance from the point, the average o f the four measures will give a mean area for grassland. Thus none o f these methods would provide a correct answer to every eventuality. (b)

(a)

\-

%o

SP

s'P

(d)

(c) t

o

i

/, FIG. 4. Plotless sampling, as reviewed by Greig-Smith (1964) and cited by permission of the author. SP is sampling point. (a) Distance measured is from the sampling point to the nearest individual; (b) distance measured is from this individual to its nearest neighbour; (c) from the sampling point a line is taken to the nearest individual and a 90 ° exclusion angle is erected on either side of the line, the distance measured being from this nearest individual to its nearest neighbour outside the exclusion angle; (d) distances are measured as shown, and the mean is taken.

Conclusions and Recommendations Integrated surveys have as their aim the portrayal o f types o f country, based on correlation o f land forms, soils, and vegetation.

672

R. S T O R Y

AND

T. A. P A I N E

For general correlation over a large area the vegetation can be classified through a mean value, e.g. in the forest-woodland-grassland case one may use aerial p h o t o g r a p h y to assess the average crown cover through the n u m b e r of c a n o p y strikes obtained in a given n u m b e r of points, or through direct m e a s u r e m e n t on a n u m b e r of sample plots, and classify accordingly. This method is usually too coarse to provide reliable information for integrated s u r v e y s - - f o r specific correlation at a particular point a mean value is useless, and both habitat and vegetation must be fixed at each observation by narrow definitions consistently applied. This can be done only if the observational plot is circumscribed in a minimal area, large enough to be representative and small enough to exclude other categories of vegetation. I f the concept leads to an impasse (unclassifiable in Fig. 3) the observation may be discarded or one of two subjective decisions may be m a d e - - e i t h e r to establish a mixed category (for instances exemplified by Fig. 2(h)) or to classify the vegetation in terms of crown cover, regardless of spacing, in a circle centred on the point and adequate for the most widely dispersed pattern, namely woodland at the cut-off to grassland. If established on a nominal 5 m crown diameter and according to our criteria, the crown cover o f this pattern will be 0.22%. The smallest area that is certain to enclose this percentage at this spacing is a circle o f 34 588 m E, which would for practical purposes have a radius of 105 m (Fig. 2(1)). The formula is given in the appendix. The impasse must be accepted as part and parcel of this concept; it is a possibility wherever classifications are imposed on life systems, which are variable and cannot be expected to conform exactly. As for the troublesome step by step diagnosis, it may be avoided by way of a short cut once the principles have been grasped, e.g. one can see at a glance and without going through the nine steps of the flow chart that Point r in Fig. 2(i) is in grassland. We r e c o m m e n d the minimal area as an essential concept for classifying the vegetation at a particular point, notwithstanding the deficiencies that have been pointed out. We thank the following people, who were generous with their time and knowledge in criticising the draft of this paper. They are our colleagues Drs J. Walker, A. Gillison, D. Jupp, D. Faith, and M. P. Austin, and Professor P. Greig-Smith, of the University College of North Wales. The statements we have made are nevertheless our full responsibility. REFERENCES BEADLE, N. C. W. & COSTIN, A. B. (1952). Proc. Linn. Soc. N.S.W. 77, 61. CHRISTIAN, C. S. & STEWART, G. A. (1953). General Report on Survey of Katherine-Darwin region, 1946. CSIRO Aust. Land Res. Ser. No. I. Canberra: CSIRO.

NEGLECTED

ASPECTS OF CLASSIFICATION

673

DUCRUC, J. P. (1980). The land systems basic unit in ecological mapping. Ecological Land Classification Series No. 8, Regional Ecological Studies Service, Environment Canada, Quebec City. GOODALL, D. W. (1954). In: International Congress of Botany 8th Paris Proceedings, section 7, pp. 19-21. GOODALL, D. W. (1961). Aust. J. But. 9, 162. GRANT, K. R, FINLAYSON, A. A. (1978). Eng. Geol. 12, 219. GREIG-SMITH, P. (1964). Quantitative Plant Ecology. London: Butterworths. GUNN, R. H. & NIX, H. A. (1977). Land units of the Fitzroy region, Queensland. CSIRO Aust. Land Res. Ser. No. 39. Canberra: CSIRO. LAUGHLIN, G. P., BASINSKI, J. J. & COCKS, K. D. (1981). CSIRO Aust. Div. Land Use Res. Technical Paper No. 42. SPECHT, R. L., ROE, E. M. & BOUGHTON, V. H. (eds) (1974). Aust. J. But. Supp. No. 7. STORY, R., GALLOWAY, R. W., VAN DE GRAAFF, R. H. M. ,~r TWEEDIE, A. D. (1963). General report on the lands of the Hunter Valley. CSIRO Aust. Land Res. Set. No. 8. Canberra: CSIRO. WALKER, J. ~r. TUNSTALL, B. R. (1981). Field estimation of foliage cover in Australian woody vegetation. CSIRO Aust. Div. of Land Use Res. Technical Memorandum 81/19. WALKER, J. & HOPKINS, M. (1984). In: Australian Soil and Land Survey Field Handbook. Australian Soil and Land Resources Commission. Melbourne: Inkata Press.

APPENDIX C a l c u l a t i o n s o f Areas (A) MINIMAL AREA OF WOODLAND AT CUT-OFF TO GRASSLAND

Area o f Fig. 2 ( b ) = = = = As r =

area o f internal triangle + 3 ( r e m a i n i n g area o f circle) r 2 tan 60 ° +3(~¢rr 2) r2(tan 60 ° +2.5¢r) 9"586 r 2. 52-5, the a r e a = 26 420 m 2.

P e r c e n t a g e c r o w n c o v e r in this pattern = a r e a o f three c a n o p i e s divided by the m i n i m a l area, e x p r e s s e d as percent. (3~r(2"5)2 × 100) o/o = \ 26 420

=0.22% (B) GRASSLAND INCLUSION IN A WOODLAND OR FOREST MINIMAL AREA

Area o f grassland = total a r e a - area o f three circles = r2(tan 60 ° + 2 . 5 w ) - 37rr 2 = r2(tan 60 ° - 0-Sw).

674

R. STORY

AND

T. A. PAINE

Expressed as a percentage o f the total area, this b e c o m e s r2(tan 6 0 ° - 0 " 5 ¢ r ) x 1 0 0 ) % = 1 . 7 % r2(tan 60 ° + 2- 5 or) (C) MINIMAL AREA OF WOODLAND AT CUT-OFF TO FOREST (OVERLAPPING CIRCLES) AS s h o w n , Fig. 2(c) can be partitioned into f o u r triangles and three sectors o f circles, all o f w h o s e areas can be calculated. (D) STANDARD

PLOT FOR

ALL CATEGORIES

As s h o w n in Fig. 2(1) A r e a o f c r o w n cover =)'.(area o f e a c h c r o w n i n c l u d e d in the circle) = ~rr 2 + 6pqrr 2

where r is the radius o f crown, and 0 < p < 1, i.e. p is a p r o p o r t i o n . C o n s i d e r the intersection o f the b o u n d a r y o f the large circle with one o f the tree crowns on its perimeter. Let R = t h e radius o f the circle w h o s e area is to be determined, r = radius o f a c r o w n (2.5 m), D = distance f r o m centre o f the circle to the centre o f the c r o w n (105 m), 4), 0 = angles as s h o w n in Fig. 5. Area o f intersection c~R2-t-Or 2 - D r sin 0, so the total area o f c o v e r = "trr 2 + 6 ( q b R 2 + Or 2 D r sin 0). =

R{iO4-93m) D(lOSm)

_~F~ ] -i

FIG. 5. Calculation of standard plot for all categories (R, radius of circle whose area is to be determined; r, radius of crown; D, distance from centre of circle to celatre of crown). O u r criteria specify that for w o o d l a n d at the cut-off to grassland the p r o p o r t i o n o f cover s h o u l d be 0.0022. Expressing this symbolically ~-r 3 +6(~bR 2 + Or 2 - D r sin 0) - 0.0022 ~R 2

(1)

Simple g e o m e t r y reveals the relations R 2= r2+D2-2Dr R sin 4) = r sin 0

cos 0

(2) (3)

By using equations (1), (2), and (3), a solution for R m a y be derived using an iterative m e t h o d , R = 104.93. H e n c e area o f circle = 34 588 m 2.