The SLOSS dilemma: a butterfly case study

Transcription

1 Biodiversity and Conservation 5, (996) The SLOSS dilemma: a butterfly case study ARTURO BAZ* and ANTONO GARCA-BOYERO Departamento de Biologia Animal, Universidad de Alcald, E-887 Alcalti de Henares, Madrid, Spain. Received 5 December 99; revised and accepted 6 April 995 Butterfly species richness is examined on simulated archipelagoes of, 3, and 5 holm oak forest fragments in the Guadalajara Province (central Spain). t is shown that there are more species on several small 'islands' than on a single island. Also, species number increases with the number of fragments that form the archipelago, and with the average distance between islands within the archipelago. Thus, we conclude, at least for butterflies in a system of fragmented holm oak forests in central beria, that the best strategy in order to maximize the conservation of species richness is the creation of a net of some small and scattered reserves. Keywords: SLOSS; butterflies: simulated archipelagoes; average distance; central Spain ntroduction SLOSS is the acronym used to debate whether the best strategy for species survival is to have a single large or several small remnant refuge patches as nature reserves (Diamond, 975; Wilson and Willis, 975). The debate has generated considerable controversy (see Wilcox and Murphy, 985; Murphy and Wilcox, 986; Lahti and Ranta, 985, 986), and among other approaches has been formulated in terms of maximizing species richness or in terms of minimizing extinction rates (Burkey, 989). Diamond (976), Jarvinen (98) and Hubbell and Wright (983) have questioned the appropriateness of species richness as a measure of conservation success. For some authors, the crucial conservation biology question hinges on whether the function of a nature reserve should be to support more species, or whether it is more important to weight species so that the reserve contains more species that would become extinct in the absence of the reserve. Another factor in the SLOSS argument is that large reserves may have minimal extinctions compared with small reserves. Chance environmental impacts are less likely to cause extinctions in large reserves, yet many small reserves, in contrast, may spread the risk. However, Spellerberg (99) points out that large reserves are not always the most appropriate and there has been no need to involve theories from island biogeography to make that claim. mmediate conservation objectives and current circumstances will apply, but of greatest importance is the need to conserve, for as long as possible and as much as possible. These considerations have developed into the SLOPP (single large or plentiful patchy) debate which argues that it may be better to divide an area into very small patches each with many individuals, rather than a single large area (see Gilpin, 988). This paper contains data about butterfly diversity in a forest fragmented system in order to clarify the best strategy for butterfly conservation in biotopes of central Spain from the point of view of maximizing species richness. *To whom correspondence should be addressed Chapman & Hall

2 9 Baz and Garcia-Boyero Methods Thirteen holm oak (Quercus rotundifolia Lam.) forest fragments in the Guadalajara Province of central Spain (Fig. la,b) were selected for study on the basis of variety in area, shape and habitat complexity (Fig. lc). Each site was visited once every 5 days from 3 May to 5 September 99, totalling 9 sample days. Samples were taken on sunny days between 0.00 and 6.00 h. The sampling scheme was based on sampling subunits (0 min) of collecting effort per site per sample (see Viejo, 98; Baz, 985). With this procedure, only the individuals that were caught are counted. Butterfly species that were identified while flying but were not caught are counted as one individual, and represent % of the total number of individuals. n transect count methods (Pollard, 977) butterflies were identified in flight. However, the Mediterranean butterfly faunas are diverse, which renders these methods inefficient due to the practical impossibility of recognizing in flight many congeneric species at the species level. Consequently, in this work, we have selected a method more suitable for the peculiarities of the Mediterranean local faunas (see Baz and Garcfa-Boyero, 995). The validity of the sampling method can be observed in Fig. in which species accumulation curves among patches are presented. Fig. shows that from the sixth day of sampling the number of species remain approximately constant. For test hypotheses about SLOSS we have followed the procedure of Simberloff and Gotelli (98). Archipelagos of, 3, and 5 small 'islands' have been simulated by randomly drawing pairs, trios, quartets and quintets of forest fragments, constraining the total area of each archipelago to less than that of the largest fragment (5 ha) which has been used as the control. Thus assemblages of 3 pairs, 3 trios, etc of fragments have been established to match the 3 single fragments. Areas of the archipelagos are constrained to insure that, for each number of islands there was a uniform distribution of areas between the smallest possible for that number of islands and the largest possible (see Simberloff, 986). For each randomly assembled archipelago, we have constructed a species list of all species found anywhere in the archipelago. Moreover, all distances were measured between pairs of islands. Then for every randomly assembled archipelago, average distance between pairs of islands within the archipelago was calculated (Simberloff, 986). For an archipelago of only one island, the average distance was set to zero. Data about shape, isolation, tree density and structure of vegetation of these forest fragments can be found in Baz and Garcfa-Boyero (995). Results We obtained a grand total of 8 individuals of 8 different species of butterflies (see Appendix) whose distribution among the holm oak fragments studied is shown in Table. Species number varies from 6 to 3 and no correlation was demonstrated between the number of butterfly species and the area (Ln species number = Ln Area: r =.0%;p > 0.05) (see Baz and Garc/a-Boyero, 995 for a more comprehensive discussion of these results in relation with metapopulation dynamics). Fig. 3a shows the relationship between number of species in an archipelago and total area of the archipelago, for archipelagos consisting of from one to five islands. As Wilson and Willis (975) pointed out, when area and all other factors are held constant, a single

3 SLOSS and butterflies 95 a BRgHLNEGA C [] Km, Figure. Map of the study site. (a) location of the Guadalajara Province. (b) location of the forest patches. Main roads and villages are also included. (c) Shape and relative size of the forest patches. island will have more species than will an archipelago comprising several islands. However, our data do not show such a pattern as can be observed in Fig. 3a. For all 65 archipelagos the regression equation is: Ln species number = Ln Area where r = 6.6%;p < 0.05 The same procedure has been used with the number of islands in an archipelago (see Fig.

4 96 Baz and Garcia-Bovero -~---e ~ m i / ~ / 8 Z E m T..... ] F ~ T... ~ T-... Y r Sample day Figure. Species accumulation curves among patches. A curve for all localities arc also included. 3b). The correlation between number of species and number of islands is much more than that for area and the number of species. The regression equation is where r = 78.5%: p < 0.05 Ln species number = Ln islands number As the regression equation shows, the coefficient of Ln islands number is high and positive when the Wilson and Willis (975) hypothesis predicts that it wilt be negative. Lastly, the relationship between species number and average distance among islands in an archipelago is defined by the following equation (see Fig, 3c) Ln species number = Ln distance where r = 66.59%, p < 0.05 Thus, as the distance among islands increases, the butterfly fauna in an archipelago becomes richer. Since the 65 archipelagos are not all independent of one another (some of them contain

5 SLOSS and butterflies 97! "A). %o oo O 0 ~ _ [] 0 [] [] ~ 0 Lj [] o / [] E] [] Log Area.. pm B [] Log N [number of islands}. - ~"Pl 0 0 J B [] i i, 3 Log(n+) Distance Figure 3. Relationships between numbers of butterfly species on 3 forest patches and 5 simulated archipelagos comprising -5 islands each and (a) area; (b) number of islands and (c) average distance. The following symbols are used: [S], island; ~, islands; ~, 3 islands; e, islands; and O, 5 islands.

6 98 Baz and Garcia-Bovero some of the same islands) the degrees of freedom for the regression are less than 63. However, even with as few as 7, 3 and degrees of freedom respectively (too few for this situation) the coefficient of determination would be significant with p < (.05 (sec Simberloff and Gotelli, 98; Simberloff, 986. By means of stepwise multiple regression we have elaborated a model that allows the prediction of variation in the number of species in the simulated archipelagos, using the pool of 3 variables considered. The regression equation is: Ln species number = Ln Area Ln islands number Ln distance. This relationship is significant (F =.66: p < 0.05 for the full regression) with an increase in variation accounted (r adj. = 8%). A graphic representation of the validity of this model for predictions can be seen in Fig.. Discussion n the SLOSS debate it can be observed that those contributors who focus on minimizing extinction rates (Wilson and Willis, 975: Diamond, 975, 976: Terborgh, 976: Fahrig and Merriam, 985) generally come out in favour of large unfragmented reserves. On the contrary, those who focus on maximizing species richness (Simberloff and Abele, b t T Fitted [] Observed.b [ "0 0 > Q 8 3.6~- a.~- il J~ ' 3. k D Prodicted L ~. ~..3 l~gure. Observed species richness vs species richness predicted by the overall multiple regression equation. Bars represent 95% intervals for predictions.

7 SLOSS and butterflies Table. Area (ha) and species number for each sampling site 99 Sampling site Area Number of species ; Jarvinen, 98; Margules et al., 98) claim that it is sometimes possible to pack more species into a set of smaller reserves. Obviously, the disagreement in the SLOSS debate emerges because the participants adopt different conservation goals. f our main goal is to maximize species diversity in a reserve, we must consider the advantage of capturing more species in the system containing highest habitat diversity. That groups of small sites have more species than a single large one can be explained by the habitat diversity hypothesis suggested by Game and Peterken (98) for results of a study showing that several small woods in England typically contain more herb species than does a single large wood of equal area. f the habitat diversity hypothesis correctly explains the observation that groups of small sites often have more species than single large ones, one might expect that the further apart were the sites comprising an archipelago, the greater the habitat diversity encompassed and therefore the more species should be supported (Simberloff, 986). Certainly, our data support this idea for butterflies on holm oak fragments, average distance explains more than 66% in the variation in species number. Consequently, for butterflies in the holm oak forests in Central Spain there is no evidence that one large refuge would be better than several small ones, if the goal is just to preserve the greatest number of species. Average distance and the number of islands are more important variables than area. n fact, while scattered small fragments totalling 87 ha, contain almost all known butterfly species in the zone, a single area in order to contain the same number of species would need to be immensely larger (i.e., the fragment used as a control contains 3 species in 5 ha for a total of 8, see Table ). Despite the limitations of these results (communities are so idiosyncratic that results cannot automatically be generalized) (Simberloff and Abele, 976,98, 98) our opinion is that in a fragmented landscape, historically managed as in central Spain, the best strategy in order to preserve the maximum number of species as possible is the creation of a network of small reserves. The Mediterranean is one of the richest areas of Europe in terms of biodiversity with three-quarters of the total European insect fauna living in this area (Balleto and Casale, 99). Butterflies are no exception, because Mediterranean countries contain the largest number of both total and endemic species (Munguira, 995). Thus, the maintenance of butterfly diversity in the Mediterranean is of priority because as Dennis and Williams (995) have pointed out, the survival of species in southern Europe is fundamental to the long-term maintenance (0-07 years) of species in northern Europe. Acknowledgements We thank J.F. Sanchez-Rodriguez for his cooperation with field work. This work was funded by the University of Alcal~i, Research Project n 9 B/ to A. Baz.

8 500 Baz and Garcia-Boyero References Balleto, E. and Casale, A. (99) Mediterranean insect conservation. n The Conservation of nsects and their Habitats (N.M. Collins and J.A. Thomas, eds.) pp. -. London: Academic Press. Baz, A. (985) Ecologia y faunistica de las Mariposas de la comarca madrileha del rio Henares. Alcal~i de Henares, Spain: M.Sc. thesis, Universidad de Alcal~i. Baz, A. and Garcia-Boyero, A. (995) The effects of forest fragmentation on butterfly communities in central Spain. J. Biogeogr. (in press). Burkey, T.V. (989) Extinction in nature reserves. The effect of fragmentation and the importance of migration between reserve fragments. Oikos 55, Dennis, R.L.H. and Williams, W.R, (995) mplications of biogeographical structures for the conservation of European butterflies. n Ecology and Conservation of Butterflies (A.S. Pullin, ed.) pp London: Chapman & Hal. Diamond, J.M. (975) The island dilemma: Lessons of modern biogeographic studies for the design of natural reserves. Biol. Conserv. 7, 95. Diamond, J.M. (976) sland biogeography and conservation: Strategy and limitations. Science 93, Fahrig, J. and Merriam, G. (985) Habitat patch connectivity and population survival. Ecology 66, Game, M. and Peterken, G.F. (98) Nature reserve selection strategies in the woodland of central Lincolnshire, England. Biol. Conserv. 9, Gilpin, M.E. (988) A comment on Quinn and Hastings: extinction in subdivided habitats. Conserv. Biol., 90-. Hubbell, S.P. and Wright, S.J. (983) Stochastic extinction and reserve size: a focal species approach. Oikos, Kudrna, O. (986) Aspects of the conservation of Butterflies in Europe. n: Butterflies ~feurope. vol. 8. (O. Kudrna, ed.). Aula-Verlag. Wiesbaden. Jarvinen, O. (98) Conservation of endangered plant populations: single large or several small reserves. Oikos 38, Lahti, T. and Ranta, E. (985) The SLOSS principle and conservation practice: An example. Oikos, Lahti, T. and Ranta, E. (986) sland biogeography and conservation: a reply to Murphy and Wilcox. Oikos 7, Margules, C.R., Higgs, A.J. and Rafe, R.E. (98) Modern biogeographic theory: are there any lessons for nature reserve design? Biol. Conserv., 5-8. Munguira, M.L. (995) Conservation of butterfly habitats and diversity in European Mediterranean countries. n Ecology and Conservation of Butterflies (A.S. Pullin, ed,) pp, Lond~m: Chapman & Hall. Murphy, D.D. and Wilcox, B.A. (986) On island biogeography and conservation. Oikos 7, Pollard, E. (977) A method for assessing changes in the abundance of butterflies. Biol. Conserv., 5-3. Simberloff, D. (986) Design of nature reserves. n Wildlife Conservation Evaluation (M.B. Usher, ed.) pp London: Chapman & Hall. Simberloff, D. and Abele, L.G. (976) sland biogeography theory and conservation practice. Science 9, Simberloff, D. and Abele, L.G. (98) Refuge design and island biogeography theory: Effects of fragmentation. Am. Nat. 0, -50. Simberloff, D. and Abele, L.G. (98) Conservation and obfuscation: subdivision of reserves. Oikos, Simberloff, D. and Gotelli, N. (98) Effects of insutarization on plant species richness in the prairie-forest ecotone. Biol. Conserv. 9, 7-6. Spellerberg,.F. (99) Biogeographical basis of conservation. n The Scientific Management o/

9 SLOSS and butterflies 50 Temperate Communities for Conservation (.F. Spellerberg, F.B. Goldsmith and M.G. Morris, eds.) pp Oxford: Blackwell Scientific Publications. Terborgh, J.W. (976) sland biogeography and conservation: strategy and limitations. Science 93, Viejo, J.L. (98) Estudio faunfstico de los ropal6ceros del quejigar supramediterr~ineo de Madrid. SHLAP Rvta. Lep, Wilcox, B,A. and Murphy, D.D. (985) Conservation strategy: the effects of fragmentation on extinction. Am Nat. 5, Wilson, E.O. and Willis, E.O. (975) Applied biogeography. n Ecology and Evolution of Communities (M.L. Cody and J.M. Diamond, eds.) pp Cambridge, MS: Harvard University Press. Appendix List of butterflies recorded in Central Spain fragment forests during 99. Also included are the total number of individuals. Scientific names follow the recommendations of Kudrna (986) Total Family Papilionidae phiclides feisthamelii (Duponchel, 83) Papilio machaon (Linnaeus, 758) Zerynthia rumina (Linnaeus, 758) 6 Family Pieridae Anthocharis cardamines (Linnaeus, 758) Anthocharis euphenoides (Staudinger, 869) Aporia crataegi (Linnaeus, 758) Colias alfacariensis (Berger, 98) Colias crocea (Geoffroy, 785) Euchloe ausonia (Hiibner, 80) Gonepteryx cleopatra (Linnaeus, 767) Leptidea sinapis (Linnaeus, 758) Pieris daplidice (Linnaeus, 758) Pieris rapae (Linnaeus, 758) Zegris eupheme (Esper, 78) Family Lycaenidae Aricia allous (Geyer, 837) Aricia cramera (Eschscholtz, 8) Callophrys rubi (Linnaeus, 758) Celastrina argiolus (Linnaeus, 758) Cupido minimus (Fuessly, 775) Cyaniris semiargus (Rottemburg, 775) Glaucopsyche alexis (Poda, 76) Glaucopsyche melanops (Boisduval, 88) Lampides boeticus (Linnaeus, 767) L ycaena phlaeas (Linnaeus, 76) Nordmannia acaciae (Fabricius, 787) Nordmannia esculi (Hiibner, 80) Nordmannia ilicis (Esper, 779) Nordrnannia spini (Denis & Schiff., 775) Plebejus argus (Linnaeus, 758) Polyommatus albicans (Her.-Scha., 85l) Polyommatus bellargus (Rott., 775)

10 50 Baz and Garcia-Bo.vero ll 3 Total Polyommatus dorylas (Denis & Schiff., 775) Polyommatus escheri (Habner, 8) Polyommatus icarus (Rottemburg, 775) Polyommatus thersites (Cantener, 83) Pseudophilotes panoptes (Htibner, 83) Quercusia quercus (Linnaeus, 758) Syntarucus pirithous ( Linnae us, 767) Family SatytMae Chazara briseis (Linnaeus, 76) Coenonympha arcania (Linnaeus, 76 ) Coo, onympha dorus (Esper, 78) Coenonympha pamphilus (Linn., 758 Hipparchia fidia (Linnaeus. 767) Hipparchia hermione (Linnaeus, 76) Hipparchia semele (Linnaeus, 758) Hipparchia statilinus (Huffnagel, 766 Hyponephele lupina (Costa, 836) Hyponephele lycaon (Muschamps, 95 Kanetisa circe (Fabricius, 775 Lassiommara maera (Linnaeus, 758) Lassiommata megera (Linnaeus, 767) Maniola jurtina (Linnaeus, 758) Melanargia laehesis (Habner, 79(/) Pyronia bathseba (Fabricius, 793) Pyroniu cecilia (Vallantin, 89) Pyronia tithonus (Linnaeus, 77) Satyrus actaea (Esper, 78)) Family Nymphalidae A rgynnis pandora (Denis & Schiff., 775) Brenthis daphne (Denis & Schiff., 775) Brenthis hecate (Denis & Schiff., 775) Euphidryas aurinia (Rottemburg, 775) Euphidryas desfontainii (Oodart, 89) Limenitis reducta (Staudinger, 90 ) Melitaea cinxia (Linnaeus, 758) Melitaea didyma (Esper, 779) Melitaea phoebe (Denis & Schiff., t775) Nymphalis polychloros (Linnaeus, 758) Vanessa cardui (Linnaeus, 758) Family Hesperidae Carcharodus alceae ( Esper, 780) Carcharodus boeticus (Rambur, 839) Carcharodus lavatherae (Esper, 780) Erynnis tages (Linnaeus, 758) Hesperia comma (Linnaeus, 758) Pyrgus carthami (Habner, 89) Pyrgus cirsii (Rambur, 839) Pyrgus malvae (Linnaeus, 758 Spialia sertorius (Hoffmannsegg, 80) Syrichtus proto (Ochsenheimer, 808) Thymelicus acteon (Rottemburg, 775) Thymelicusflavus (Brunnich, 763) Thymelicus lineola (Ochsenheimer, 808) l l l l ( 908 t97 5 t l O t O