Nature reserve selection strategies in the woodlands of Central Lincolnshire, England

Biological Conservation 29 (1984) 157-181

Nature Reserve Selection Strategies in the Woodlands of Central Lincolnshire, England

M. G a m e * & G. F. Peterken Nature Conservancy Council, PO Box 6, George Street, Huntingdon, Cambridgeshire PE18 6BU, Great Britain

ABSTRACT Lists of woodland vascular plant species from 78 ancient woods in a study area situated in central Lincolnshire, England, were used to test the effectiveness of various strategies for selecting woodland nature reserves. Strategies in relation to afixed area of reserves,fixed number of reserves, and response to opportunities were examined. No simple strategies were found which guaranteed the best results, but certain guidelines emerged which may improve the complex judgements which are unavoidable in practical conservation.

INTRODUCTION A major component of nature conservation strategy has been reserve acquisition: once acquired, reserves are then managed primarily for their wildlife and other natural features. The success of such a strategy depends on selecting and acquiring the best collection of sites as reserves, and then maintaining their contents in perpetuity by suitable management. Selection in the past has often been a matter of subjective judgement. Recently, however, the basis for selection has tended to become more explicit and quantitative, due to the availability of more survey and * Present address: Ecology Section, Transportation and Development Division, Greater London Council, County Hall, London SE1, Great Britain. 157 Biol. Conserv. 0006-3207/84/$03.00 © Elsevier Applied Science Publishers Ltd, England, 1984. Printed in Great Britain

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M. Game, G. F. Peterken

autecological information, recognition of the importance of historical factors, and the influence of island biogeography theory. In predominantly cultivated landscapes semi-natural habitats are fragmented into a large number of discrete sites: reserves are selected from this pool. Selection is necessary because resources for acquisition and management are limited, at least in the short term, and in the long term many of the unprotected sites will probably be destroyed by agriculture and other activities. Selection and acquisition are inextricably linked--there is little point in determining the ideal selection if these sites never become available for purchase--but it helps to clarify the problems if two aspects are separately considered: (1) Given that reserves must be limited, either in number of sites or in total area, what is the best method of selecting from the available pool? (2) Given that the best selection is unlikely to be available for acquisition, how should one respond to opportunities for acquisition? In this paper we use vascular plant species from ancient woods in central Lincolnshire to test the effectiveness of various methods of selection. Only ancient woods are considered because these are the most important for nature conservation (Peterken, 1977; Rackham, 1980). We examine the case for more, smaller reserves rather than fewer larger reserves; test the success of various methods of selecting a fixed number of reserves; and discuss the implications for survey, selection and acquisition strategies.

THE WOODS The study area comprises 930 km 2 in central Lincolnshire, within which woodland covers 5187 ha (5.6% of the land surface). Documentary, archaeological and cartographic sources have been used to establish that about half this woodland (2543 ha) is ancient (Peterken & Game, 1981). The total area of ancient woodland is distributed between 78 discrete woods (median area 14.7 ha, range 0.8-238.1 ha), but some comprise two or more distinct historical units for which separate records have been made: there are 89 such historically distinct ancient woods. Most are concentrated on the heavy and poor soils.

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Soils within the study area range widely to include rendzinas, podzols, surface water gleyed clay and drained peat. The study area was therefore divided into nine regions of relatively homogeneous soils (Peterken & Game, 1984).

THE SPECIES Lists of vascular plants were made for all ancient woods. Recording was restricted to 'woodland' species, these being (a)trees and shrubs, and (b) shade-bearing herbs and wood-edge species. Our records for each site have been built up over more than a decade and with the help of other recorders. Lists for ancient woods are the products of several visits. Even so, it is unlikely that any list is complete, though most are believed to be 80-90 ~ complete. Analysis proceeds on the assumption that they are complete. This analysis is restricted to woodland herbs. There are 183 on record, of which 171 have been recorded from ancient woods and 12 are known only from recent woods, hedges and marginal habitats. Two of these twelve are now believed to be extinct. Within the 171 recorded species, 62 were regarded as 'special' because they were rare, strongly restricted to ancient woods (Peterken, 1981), or both.

SPECIES--AREA RELATIONSHIP In the 78 woods we find an approximately linear relationship between logeA and both S and loge S, where S is the number of woodland herb species and A is the area of a wood. The slope of the regression line in the loge S - log~A model is 0.21. Figure 1 shows the relationship between S and log~A and the corresponding regression line. If this regression line is extrapolated upwards (Fig. 2) it passes very close to the point where A is equal to the total study area, 93 000 ha, and S is equal to the total species pool, 183 species. Allowing for the fact that woods are unlikely to be completely recorded, this suggests either that the species-area regression becomes concave at large area, or that the total number of woodland species in the study area has only been slightly reduced as a consequence of woodland clearance.

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Nature reserve selection strategies

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SELECTION OF RESERVES WHEN TOTAL AREA IS LIMITING Wilson & Willis (1975) used MacArthur & Wilson's (1963, 1967) equilibrium theory of island biogeography to propound a set of design principles for nature reserves, one of which was that a few large reserves are preferable to many small reserves of the same total area. The object of these principles was to protect the greatest number of species in general of any subset of rare, vulnerable or otherwise 'special' species. Although a number of authors (Simberloff & Abele, 1976; Game, 1980; Gilpin & Diamond, 1980; Higgs & Usher, 1980; Margules et al., 1982; Simberloff & Abele, 1982) have questioned these rules on either theoretical or observational grounds, they have nevertheless been widely accepted elsewhere and indeed quoted without qualification in the World Conservation Strategy (IUCN, 1980). In this section we examine the results of selecting one, few or many reserves within a limited total area. This corresponds to the familiar state of affairs in which only a limited amount of money is available for reserve acquisition. If the area we can afford is no more than 238 ha, the area of the largest wood, we have a choice between putting all our eggs in one basket by acquiring a single reserve or spreading the investment by purchasing two or more woods. Figure 1 shows how many species would be involved if a single wood were acquired: the regression line approximates to the average result of a random choice, whilst the scatter of points shows the improvement possible from a careful, informed choice. Figure 3, which gives the species-area relationship resulting from aggregating the species lists and area of 40 randomly-chosen pairs of woods, shows what we would achieve if we acquired the first two available woods to match our budget. Two woods usually contain more species than one wood of the same total area. If, as it seems, subdivision of the total area acquired results in the inclusion of more species, it is desirable to determine how far this process can be taken. The maximum number of woods which can be acquired for a given total area corresponds to acquiring the smallest site, then the second smallest, and so on upwards (Fig. 4). Extreme subdivision includes far more species than one or two woods of the same total area. For example, the second-largest wood (Fulsby), which covers 196ha and contains 111 species, is rich for its size, but it still contains 33 fewer species than the 33 smallest woods combined (191 ha, 144 species).

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The options so far considered represent extreme solutions, and do not necessarily correspond to what is practical or desirable. The general relationship between number of species and number of sites was investigated by forming 100 random combinations each of 2, 4, 8, 16 and 32 woods from the pool of 78. For any fixed number of woods there is an approximately linear relationship between S and log eA. A regression of S against logeA and log, n, where n is the number of woods, showed that logcn adds significantly to the explained variance (Table 1, dataset 1). However, since n and A are strongly correlated, the dependence of S on log, n could merely reflect a residual dependence of A over and above log~A, rather than a real effect of n itself. This was tested by classing the combinations of woods according to total area; within these classes S increases with n (Fig. 5), although it should be noted that even within a given class the mean area increases with n, so that the real increase of species with number of woods is slightly less marked than Fig. 5 indicates. The increase of species with log en was confirmed by a regression analysis for selected area classes (datasets 2, 3 and 4, Table 1).

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TABLE 1 Regression Analyses for All Species in 1, 2, 4, 8, 16 and 32 Wood Combinations Drawn from 78 Sites Dataset

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In the analyses so far, all species have been considered equal, whereas it might be desirable to give particular attention to the 'special species'. Moreover, since the theory of island biogeography implicitly assumes that an archipelago of islands of similar habitat is being studied, it is interesting to restrict variation between woods, i.e. to woods within a given soil region. The foregoing analysis was therefore repeated with the special species alone, with similar results (Table 2, Fig. 6). It was also repeated both for all species and for special species for each of the four regions with nine or more woods. For these analyses all permutations of

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TABLE 2 Regression Analyses for Special Species in 1, 2, 4, 8, 16 and 32 Wood Combinations Drawn from 78 Sites Dataset

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woods were used rather than random draws when this was necessitated by the small number of woods in the 'pool'. Also, for region 4, combinations of 2, 4 and 6 woods were used. Figures 7 and 8 display the results for region 5, which is typical of the others. In the regression analyses of selected area classes, for all species in all 8 cases the coefficient of log e n was positive and in all cases loge n significantly increased r 2 at the 1 °/o level. For special species in 6 out of 7 cases the coefficient was positive: 3 of these were significant at the 1 ~o level and 2 at the 5 ~o level.

S E L E C T I O N OF A FIXED N U M B E R OF W O O D S Conservation organisations often set targets by listing the sites which they would like to acquire as reserves (e.g. Ratcliffe, 1977), sometimes claiming that the selection is the minimum necessary to conserve the species and features represented. These exercises generally involve an actual or implied limit on the number of sites which can or should be included. In this section we therefore test the effectiveness of various methods of selecting a fixed number of woods. The 89 historically distinct units were used for selection, since woods tend to come onto the market on this basis. The number of sites selected was fixed at nine, mainly because this corresponds with the number of soil regions. In fact, one region had no ancient woods whilst another had 40 of the 89; two woods were chosen to represent the latter in all regional selections. Nine sites happened to be appropriate for other reasons. It was one less than the minimum required to include all species; exactly the number required to include at least one locality of the rarest species, i.e., those with three or fewer localities; and exactly the minimum number required to include good examples of all stand types comparable with the Norfolk selection of Goodfellow & Peterken (1981). The 17 different selections are shown in Table 3. Four attributes were determined for each selection and used to assess success. The most important of these was the number of species included from a total pool of 171 : the more the better. This must be offset against total area: the less the cheaper. Neither attribute contains a measure of quality, but the two remaining attributes attempted to measure this. Species quality was measured by determining the number of special species included from the pool of 62. Woodland area quality was determined by recording the

M. Game, G. F. Peterken

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TABLE 3 The Characteristics and Species Included in Seventeen Different N i n e - W o o d Selections

Basis]or selection

Species missing ex 171

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Area (ha)

Per cent conijer + mixed

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194 1 192 16 694 59 1 036 210 193 909 588 567

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Whole area 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.

R a n d o m selections (mean of 6) Largest woods Smallest w o o d s Richest w o o d s Poorest w o o d s Largest area o f broadleaf w o o d l a n d Richest with 100% b r o a d l e a f w o o d l a n d Richest sites in relation to size Sites needed to include all rare species N C R sites Stand type representation

Regional divisions 12. 13. 14. 15. 16. 17.

R a n d o m selections (mean o f 6) Largest in each region Richest in each region Largest broadleaf area in each region Richest with 100% b r o a d l e a f Richest in relation to area

proportion of broadleaved to conifer and mixed woodland, 'broadleaved' in this instance being virtually synonymous with semi-natural. In Table 3 all attributes are expressed in such a way that smaller numbers indicate superior results. Nine-site selections ranged from a minimum of 16 ha (selection 3) to a maximum of 1192 ha (2) or 47 % of the available ancient woodland area. It was possible for selections to be wholly broadleaved or wholly coniferous and mixed, i.e. plantations. Even the worst selection included 90 species (5) and the best (9) still failed to include two, though the latter did include all special species. These extreme selections may be compared with random collections of 9 sites which included an average of 140 species (51 special species) in 194ha, 68 % of which was broadleaved.

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The important points to emerge from Table 2 included the following: 1.

2.

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Selections based solely on area as determined from Ordnance Survey maps included far more species than random selections, but at the cost of greater area and a higher proportion of conifers (2cf 1; 13cf 12). Selections based on information available from air photographs, Forestry Commission stock maps, and other basic survey data from which the area of broadleaf woodland could be measured, were not much better than selections based on area alone (6 cf 2; 15 cf 13). Total area and proportion of conifers decreased slightly, but so too did the number of species included. A purist aversion to selecting woods with even small areas of plantation (7, 16) eliminated most of the largest woods from consideration and excluded many species. As far as area and species included were concerned, the result was no better than random. Floristic survey improved the selection. Even if it is incomplete, woods can be ranked in order of floristic richness if survey is uniform. Selection of richest woods improved selection based on area (4 cf 2; 14 cf 13) in that slightly more species were included in an appreciably smaller area. Selection of sites with a large number of species in relation to area brought in large and small woods alike. Surprisingly the result was no better than random: it either included fewer special species (8 cf 1) or a higher conifer proportion (17 cf 12). Rare species formed a better basis for selection than floristic richness (9 cf4). When selection was focussed on the rarest species, almost all the commoner species were also included, but at the cost of a larger area and conifer proportion.

Selection is often based on the concept of representation (Ratcliffe, 1977). One or more examples of each woodland type are included in order to embrace as far as possible all ecological conditions and therefore all species. The simplest approach to classification is based on regional groups delimited according to some significant factor. This process was mimicked here by regional stratification, the results of which can be compared directly with unstratified selection. Six different comparisons were possible (Table 3). Only one, based on random collections (12 cf 1) favoured unstratified selection according to three measures of success,

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M. Game, G. F. Peterken

but the difference was small. The other five all showed benefits for stratified selection in terms of number of species. However, for the selections based on the richest woods and the richest by area (14 cf 4 and 17 cf 8) the benefit was offset against greater area included and a larger proportion of coniferous and mixed woodland. The other three selections, based on the largest woods, those with the greatest percentage broadleaf, and the richest with 100 % broadleaf (13 cf 2, 15 cf 6 and 16 cf7) showed advantages of stratification in at least three of the four attributes. If more survey information is available, woods can be classified into woodland types (e.g. based on vegetation classification) which allows two or more types to be recognised within a single wood. This contrasts with the regional stratification, which is, in effect, a classification which assigns each wood to a single type. The finer scale of classification was tested using the stand types of Peterken (1981) and the methodology of Goodfellow & Peterken (1981). Stand type selection (11) included nearly as many species for substantially less area than regional stratifications 13, 14 and 15; and substantially more species coupled with greater area compared with regional stratifications 16 and 17. The Nature conservation review (Ratcliffe, 1977) included 12 woods from the study area. These formed part of a representative set of woods selected at a national scale. For comparative purposes, the three smallest Grade 2 woods were omitted, leaving the six Grade I woods and the three largest Grade 2 woods. This selection was markedly worse than both random selections (10cf 1), in that a larger area was included, and the selection based on stand types (10 cf 11), in that far fewer species were included in a similar area.

RESPONSE TO O P P O R T U N I T I E S

Even if we can determine how many woods are required and which particular selection is best, it is highly improbable that this selection will actually become available for acquisition. Woods come onto the market infrequently. During the last 12 years only six ancient woods are believed to have changed hands, and five of these formed an inseparable part of the sale of one estate. Thus, even if, by some lucky chance, the first nine woods to come onto the market happen to be those forming one of the

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best selections, they will still take nearly two decades to acquire at current rates, and in this time many woods could be destroyed. Faced with such problems, we can recognise that the best may be the enemy of the good. Instead of adhering strictly to a pre-determined selection of particular sites, we could adopt a more flexible strategy of response to the usually unpredictable availability of woods. One strategy would be to acquire all sites as they become available, i.e. to abandon selectivity completely. Alternatively sites could be acquired only if they met certain predetermined standards. For example, one might decide to acquire only relatively rich sites--those above the species-area regression--in which case on average half the woods which come on the market would be acquired. The success of some possible strategies was examined by generating ten random sequences of ten ancient woods, representing the sites available for acquisition over roughly 20 years. The following strategies were tested: A. B.

C. D. E.

F. G.

No selectivity. Acquiring each wood as it becomes available. Select sites with > 80 ~ , or > 20 ha broadleaves. This is equivalent to acquiring all predominantly semi-natural woods as they become available. Select rich sites, i.e., those above species-area regression. Select one wood from each region (two from region 5). Select rich sites with > 8 0 ~ or > 2 0 h a broadleaves. This corresponds with the common practice amongst conservation organisations of acquiring the best semi-natural woods when available. Select sites as in E, but reject sites less than 5 ha in total area. Select one good (as defined in E) wood to represent each region. This corresponds as closely as possible with a conservation organisation's idealised acquisition programme.

The ten random sequences of woods happened to be slightly unrepresentative, in that the richest wood was selected in two sequences and selections E and F were identical in nine sequences. Nevertheless, the results (Table 4) show clearly two inherent features: (i)that as more selection criteria are imposed, so the proportion of sites which satisfy them decreases, and (ii) that the greatest number of species will be included by acquiring all available sites. Woods acquired using criteria which select roughly half the number of woods (B, C and D) included

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almost as many species as selections which acquire all available sites (A), but in an appreciably smaller area. Responses based on representation, (D), initially allowed fast acquisition--the first site available was certain to qualify--but the rate of acquisition fell off rapidly when most 'types' were included. One measure of'success' of a selection is the comparative species richness for area included; this is indicated by the number of points falling above the species--log~A regression lines for all the ten sequences combined. Selections based on all sites and on rich sites (A and C) did slightly better than average in this respect, but at the expense of including more coniferous and mixed woodland; the reverse was the case for selections based on ~ broadleaf (B, E, F and G), where species richness was average or below average, but less conifers were included. However, it is apparent that there is little scope for avoiding the underlying species-area relationship. The possibility of absurd results increased as selectivity increased. For example, in one sequence criteria E, F and G 'chose' only one wood of 7.6 ha containing 70 species, from 10 woods containing 188 ha and including 139 species. Although a strategy of acquiring all sites as they become available collects the greatest number of species, this advantage can only be felt if resources for acquisition are not limiting. The effects of limiting resources were examined by assuming that only 200 ha ( + 10 ~ ) could be afforded in the period during which ten sites came on the market (Table 5). Comparison of Tables 4 and 5 shows, not surprisingly, that fewer sites, species and area were acquired when resources were limited, though the quality of sites--as measured by percent broadleaves--improved, because larger sites tended to have a higher proportion of conifers. When resources were limited the outcome was even more influenced by the particular order in which sites became available. In one case the second site to come available extended to 196 ha, which obliterated differences between selection criteria (but did not do so when resources were unlimited). In another, a good representative for a region was rejected because a poor example had come up earlier in the sequence. In yet another, the first ten woods to become available totalled only 168 ha, so resources were not exhausted. The number of occasions when lack of funds prevented further acquisition declined as greater selectivity of sites was exercised (Table 5): when all available sites were accepted, the limit of 200 ha was reached in six cases, but for selections E, F and G, the limit was reached only twice. Although any of the selection criteria could yield either the worst or the best result with limited resources, the chances

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varied: accepting all sites up to the limit gave the best or joint best species total in seven cases and the worst in one, whereas the most stringent selection (G) was best on one occasion but worst seven times. In general, the effects of varying the selection criteria were reduced when resources were limited because the least stringent criteria were most likely to reach the limits imposed.

DISCUSSION There is an obvious risk in generalising from the results obtained in only one group of woods, even though the central Lincolnshire woods are reasonably representative of lowland, semi-natural woods in Britain, being generally small, moderately diverse and separated by intensively cultivated land. Furthermore, one must be cautious when generalising from vascular plants to the conservation needs of organisms in general, since the needs of plants do not necessarily coincide with those of invertebrates for example. In particular, by confining our analysis to those woodland plants which can bear at least some shade, we have discriminated against the species of clearings and canopy gaps, notably butterflies and other invertebrates. Nevertheless, certain points emerge which seem to have general validity. F e w reserves or m a n y ?

The design principles derived from Island Theory have attracted a great deal of interest, partly because they appear to offer a rigorous basis for nature reserve acquisition strategies. The most widely quoted--that a few large reserves will contain more species than many small reserves of the same total area--applies only (i)in a uniform environment, (ii)when there is a risk of relaxation, and (ii) where reserves are indeed islands separated by totally hostile territory. In this study we have shown that for woodland herbs the reverse of the rule applies, even within relatively homogeneous regions and when attention is restricted to species of special conservation interest. In fact, none of the three conditions is fully met. The soils are heterogeneous, even within ostensibly uniform, soil-defined regions. Woodland vascular plants are not apparently subject to relaxation (though the species of open speces which were not considered here may be affected) (Peterken & Game, 1984). No species appears to

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be confined to large woods. The farmland between the woods supports at least a few populations of most woodland herbs, and about one-third of the 183 species are widespread and common in hedges, waste ground and heathland. Elsewhere, Higgs & Usher (1980) have demonstrated that the rule is incorrect for plants of limestone pavements in Yorkshire, and C. H. McLellan (pers. comm.) has shown that it is not true for British woodland birds. Moreover, Simberloff & Abele (1976) have shown that the rule has no theoretical basis. We might easily conclude that small is beautiful, but only by ignoring three other groups of factors: (1) Future conditions, which may differ significantly from past conditions, and thereby increase the risk of relaxation. The surrounding countryside has recently become so intensively cultivated that the woods are becoming real islands for an increasing number of species, notably woodland species of hedgerows, and species of unimproved grassland and wetlands, which now survive mainly in woodland rides. In the past those species may have been lost from individual woods, but recolonisation from populations in the surrounding countryside would have been likely. In the future the rate of loss from woods may increase due to management changes, and the rate of recolonisation may decrease, due to arable intensification. (2) Other groups of organisms, which may depend on large woodland tracts. Although the woods have long been discrete patches separated by farmland and most species dependent on large tracts of woodland will presumably have vanished, there are signs that large woods may be necessary for some groups, such as the butterflies and birds of prey. (3) The practical difficulties of managing a large number of small reserves; their greater vulnerability to events beyond their borders such as herbicide spray drift and drainage improvement; and the higher land prices and costs per unit area as parcel size decreases. When these factors are taken into account, we expect that the optimum strategy would be to acquire a limited number of reserves, covering a range of sizes, thus striking a balance between many small sites, which would maximise the number of species through greater habitat variety in the heterogeneous environment, and few large sites for more practical reasons. Without further investigations we cannot determine exactly how

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the balance should be struck, but one important factor will be the particular needs of a limited number of vulnerable, rare or attractive species. Exhortations to concentrate on large reserves (e.g. IUCN, 1980) would be misplaced in the present instance. There may be good reasons for selecting fewer and larger reserves in some circumstances but maximisation of species richness is not in this instance one of them. Indeed, since the measures required for the protection of species and the resources available to meet these requirements vary so widely, we suggest that attempts to apply general rules to global strategies for reserve design throughout the world are likely to be futile. Practical survey and selection

Selection of sites for reserves is necessary because other land uses, mainly forestry and agriculture, also have competing claims and it is likely that nature conservation interest will prevail only in the most important sites. In any case resources are limited, so one cannot acquire all sites even if they are available. It is desirable to define a minimum requirement, both to lend force to conservation arguments in the sites selected, and as an interim target, upwardly adjustable if resources and competing interests permit. Minimum requirements can be defined by reference to representative examples, i.e. by selecting one or more examples of each type. Two applications of this approach, using regional divisions and stand types, led to a minimum of nine sites. However, this result was determined by the level of detail at which the types were defined: if we had increased the number of types then the minimum number of sites required to represent them would have increased also. An alternative and apparently more objective approach depends on species. A minimum of ten sites is needed to include all species at least once. Only eight sites are absolutely required because they contain a species which occurs in no other wood: the loss of any one of the other 81 woods would not by itself cause a local extinction. However, even this precision is spurious, since we have considered only vascular plants, and no doubt surveys of more groups would reveal the need to include more sites. Indeed, in the last resort, each wood is unique at some level of detail, and it seems impossible to attach objective meaning to the concept of minimum requirement as an identifiable threshold. It is a statement of priorities based on judgements about, inter alia, the weight of support for nature conservation compared with

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competing interests, and the level of detail that is reasonable for any consideration of representation. If we accept that 10 ~ of available sites (in this instance 9 ex 89) should be identified as top priority for conservation, and that vascular plants should be used as the basis, three important points emerge. First, any nine sites will contain on average 80 9/0 of all species, so any reasonable (i.e., excluding absurd criteria such as poorest sites) basis for selection will be fairly satisfactory. Acquisition programmes should not therefore be held up by quibbles over selection. Second, an element of classification and representation in the selection improves the result: in this study nine representative sites contained 96 9/0 of available species. Third, rare species must also be considered: the nine sites selected solely on this basis included 99 ~o of all species. These results have important implications for survey. If a selection based on rare and vulnerable species combined with vegetation types produces a scarcely improbable list, is there any justification for the extra cost of complete floristic survey and mapping? Indeed, is site survey necessary at all when selection based on the extent of each ancient wood and the occurrence of plantations and rare species (all of which are available from floras, record centres, old Ordnance Survey maps, modern air photographs and forestry maps) is only slightly inferior to the best available selection? Admittedly numerous important features will be missed if sites are not surveyed but detailed survey only raises again the problem of minimum requirements. As more features are surveyed so more woods are found to have at least one feature which is unique to the area, and eventually the minimum requirement grows to exceed the limitation which originally generated the need for a selection. We might then ask what is the value of survey ? Just as the number of species added per unit area decreases as the area of reserves increases, so the increase of useful information per unit effort decreases as survey progresses. Simple information is almost as effective as detailed floristic survey. Further collection of data is more likely to confuse selection than clarify, because we are then involved in complicated trade-offs between various attributes which are not precisely correlated in their occurrence. Judgement will be required no matter how much information we possess. We conclude that only the collection of limited, basic information is necessary for the selection of new reserves and that selection should be focussed on the occurrence of rare and vulnerable species and representation of (crudely defined) types.

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Perspective of selection The NCR selection (Table 3, item 10) was conspicuously poor within the context of the study area: indeed, it may be worse than it seems, for only the semi-natural parts of each wood were included within the NCR site boundaries, and some species may be confined to the excluded portions. This selection was designed to include the best examples of acid pedunculate o a k - a s h - l i m e woodland, a common type within the study area, but rare elsewhere in Britain. It ignored examples of valley alder woodland and ash-wych elm woodland, which are rare in the study area but far better represented elsewhere. It could not be confined to just one example of ash-lime woodland, because no one site showed the full ecological range of this type. If, as seems to be the case, selections based on representation at a national scale pick out woods which locally appear to be ordinary, there seems to be some justification for conservationists dividing their efforts between the nationally-based Nature Conservancy Council and the county-based Naturalist Trusts.

Responses to opportunities It is highly improbable that any particular selection of sites will actually become available for acquisition. The chance that the nine sites selected from a pool of 89 will be the first nine to come available is 1 in 6.4 × 1011. In practice the rate of availability is low and roughly matched by the rate of destruction: during the 12 years from 1970-1982 six woods came on the market; one wood has been completely cleared for agriculture; three have been partly cleared; and one hitherto semi-natural wood has been replanted with conifers. Conservation organisations need a strategy for response to opportunities as they occur. If no woods are being destroyed, one can wait for sites within the good or nearly-good selection to come up, though in the absence of destruction the case for having any reserves at all is much reduced. If, on the other hand, destruction is fast and resources are unlimited, each site should be acquired as it becomes available, irrespective of any preselection. If destruction is moderately fast and resources are not very limited, one can afford to wait for a reasonable selection. Using criteria which on average are met by half the available sites, the results may be almost as good as a strategy of acquiring all sites over a period of a decade or two. Selectivity is also justified when resources are limited, even if destruction is fast. All

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these conclusions assume that a conservation organisation has no influence over or foreknowledge of availability of sites: if it has, then the degree of selectivity justified increases in proportion to this influence or prescience. Except where the organisation has a strong influence on availability, the chance of which sites become available and in which order greatly influences the success of any strategy founded on limited resources. In most practical circumstances where conservation organisations have only limited resources and influence, and the rate of destruction is historically moderate to fast, application of selective criteria which admit 50 ~ of sites is probably near to the optimum. Criteria based on representation should be used only in the short term, since the admissibility of sites rapidly falls below 50 ~ once some types are represented in reserves. Alternatives to nature reserves

A nature reserve acquisition policy, however successful, implies that unreserved woods have been written off. We therefore emphasise the importance of trying to retain all the surviving ancient woods. If the 2543 ha of ancient woodland had survived in a single block, we would expect it to contain about 140 woodland species (Fig. 2). In fact, some 78 ancient woods have survived which, because they are scattered over the study area and encompass a far wider range of soils than could ever be included in one large wood of the same total area, contain many more species, i.e. 171 species. We therefore need land-use policies designed to retain all ancient woods, and forestry policies which integrate timber production and nature conservation.

ACKNOWLEDGEMENTS

We thank the Forestry Commission and many landowners for access to their woods; Joan Gibbons, Paul Harding, Mary Maley, Philip Oswald, Lynne Simmons, Irene Weston and Peter Weston for help with plant recording; and Susan Evans, Andrew Foster, Sandi Mayne and Susan Peterken for help with data processing and preparation of figures.

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