How to resolve the SLOSS debate: Lessons from species-diversity models

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Abstract

The SLOSS debate – whether a single large reserve will conserve more species than several small – of the 1970s and 1980s never came to a resolution. The first rule of reserve design states that one large reserve will conserve the most species, a rule which has been heavily contested. Empirical data seem to undermine the reliance on general rules, indicating that the best strategy varies from case to case. Modeling has also been deployed in this debate. We may divide the modeling approaches to the SLOSS enigma into dynamic and static approaches. Dynamic approaches, covered by the fields of island equilibrium theory of island biogeography and metapopulation theory, look at immigration, emigration, and extinction. Static approaches, such as the one in this paper, illustrate how several factors affect the number of reserves that will save the most species.

This article approaches the effect of different factors by the application of species-diversity models. These models combine species–area curves for two or more reserves, correcting for the species overlap between them. Such models generate several predictions on how different factors affect the optimal number of reserves. The main predictions are: Fewer and larger reserves are favored by increased species overlap between reserves, by faster growth in number of species with reserve area increase, by higher minimum-area requirements, by spatial aggregation and by uneven species abundances. The effect of increased distance between smaller reserves depends on the two counteracting factors: decreased species density caused by isolation (which enhances minimum-area effect) and decreased overlap between isolates. The first decreases the optimal number of reserves; the second increases the optimal number. The effect of total reserve-system area depends both on the shape of the species–area curve and on whether overlap between reserves changes with scale.

The approach to modeling presented here has several implications for conservational strategies. It illustrates well how the SLOSS enigma can be reduced to a question of the shape of the species–area curve that is expected or generated from reserves of different sizes and a question of overlap between isolates (or reserves).

Introduction

The greatest challenge in environmental management is to preserve enough habitats in order to save as many species as possible from extinction. In the mid-1970s researchers proposed six of rules for reserve design (Diamond, 1975; May, 1975; Terborgh, 1974; Wilson and Willis, 1975). The first of these rules states that, for a fixed total area, one large reserve will conserve more species than several small ones. Later, others began to question the validity of most of these original rules of thumb. The debate over whether a single large area or several small areas will hold the most species, denoted by the acronym SLOSS, became the most infamous of these (Abele and Connor, 1979; and more recently Etienne and Heesterbeek, 2000; Gilpin and Diamond, 1980; Groenveld, 2005; Ovaskainen, 2002; Simberloff, 1988; Simberloff and Abele, 1982; Simberloff and Abele, 1976). A large number of empirical and theoretical studies have addressed the SLOSS question, but it is still considered to be unresolved. Despite this impasse, the first rule of reserve design, which many authors considered an unproved over-simplification, became the norm for reserve planning.

According to Connor and McCoy (1979), it is unfortunate that species–area relationships (SARs) were used as justification for conservation practices that led to the preference for large areas being preserved over small areas. Soulé and Simberloff (1986) claimed that the SLOSS concept is not useful and should be abandoned. They suggested that the minimum area needed to sustain a viable population, habitat diversity, environmental quality, and distance between reserves should decide the size of reserve areas. Whether a single large area or several small areas will hold the most species is, therefore, expected to depend on the situation considered. Yet, far from ending the SLOSS debate, Soulé and Simberloff's arguments, by highlighting the crucial factors, actually justify the furtherance of SLOSS modeling. Accordingly, this study aims to integrate into the modeling of species-diversity such important factors as species overlap, minimum-area requirements, habitat diversity, and the distance between reserves.

There are numerous empirical studies showing whether a single large or several small reserves will hold the most species (see Ovaskainen, 2002 for review). Though much of the discussion has advocated either a single large or several small reserves as the universally best design, we should expect neither to be always the best strategy. The optimal solution depends on factors that vary from place to place. Also the choice of focal species will affect this issue: do we want to ‘save’ as many species as possible, or do we want to preserve specific species, e.g., rare or globally threatened ones?

The first rule of reserve design (that states that a single large supersedes several small) has its origins in MacArthur and Wilson, 1967, MacArthur and Wilson, 1963 equilibrium theory of island biogeography, which they based on immigration and extinction. The island equilibrium model does not, however, take into account the recolonization between the reserves in a network of reserves. Recolonization, as discussed by metapopulation dynamics, may serve as a buffer against species extinction (e.g. Etienne and Heesterbeek, 2000; Hanski and Ovaskainen, 2000; Ovaskainen, 2002). If a population at one small reserve (in a system of several reserves) becomes extinct, then individuals from other small reserves can recolonize it.

Island equilibrium theory and metapopulation modeling can thus be applied to discuss reserve configuration by considering the effects of reserve size, immigration, emigration, and extinction rates. Neither of these two types of dynamic approaches considers specifically the effect of habitat diversity, resource restrictions or minimum-area requirements. Resource restrictions and minimum-area requirements will affect population sizes and may determine whether the reserve (or area) can sustain viable populations, and therefore the probability of occurrence (see e.g. Gurd et al., 2001; Lomolino, 2000). Such minimum-area effects (MAEs) will restrict the number of species at smaller scales by decreasing the slope of the species area curve (Tjørve and Turner, 2009; Turner and Tjørve, 2005). Moreover, most approaches do not take into considerations spatial attributes as shape and connectivity (see Williams et al., 2005, for review). Indeed, no workable model can be expected to include every factor that may affect the system. We are thus left to restrict an approach as the one in this article, to a few key factors.

Early on, certain theoreticians realized that species overlap between areas is a key to the SLOSS enigma (Higgs and Usher, 1980; Simberloff and Abele, 1976), though no attempt at furthering the modeling approach followed. Instead, others suggested that, since the SLOSS question is expected to vary from case to case, the answer lies in the study of empirical data (Quinn and Harrison, 1988; Rosenzweig, 2004). Several other authors (Bolger et al., 1991; Simberloff and Martin, 1991; Wright and Reeves, 1992) have mentioned overlap (or species nestedness) as an important consideration to the SLOSS-question, though no systematic approach can be found in the literature. Recently, some studies have applied overlap to species-diversity models, discussing optimal number of areas or optimal proportions of different area (or nature) types (Bascompte et al., 2007; Tjørve, 2002). Models that combine diversity for different reserves (or areas) have to correct for the species overlap between areas. What affects species overlap, and thereby combined species numbers for several areas or types of areas (e.g. landscape mosaics or nature reserve systems) is therefore a key to understanding not only species-area modeling but also the SLOSS enigma itself.

Different biotic and abiotic factors may affect species overlap between reserves or between subsections of reserves. Species nestedness, i.e. that several small reserves contain largely subsets of species found in a single large area, causes larger overlap. Several authors have argued that the level of nestedness affects the optimal reserve configuration (Bolger et al., 1991; Simberloff and Martin, 1991; Wright and Reeves, 1992). Fukamachi et al. (1996), for example, found that even though more species were found in a number of small fragments than in a single large, rare species were found only in the largest patches. Therefore, if the aim is to preserve as many species as possible at a coarser scale than the total reserve area (e.g., globally), a single large reserve may be a better strategy even when several small will preserve the most species locally.

Diamond and May, 1976, Diamond, 1976 noted that if smaller areas were spread out, they would be more likely to sample complementary distinct communities and therefore contain more species. Simberloff (1988) later pointed out that islands and other discontinuous areas of different sizes do not all have nested species composition, and that two smaller reserves could, therefore, have more species than one larger reserve. The SLOSS question then becomes a discussion of whether small reserves have unshared species or one about the number of overlapping species between smaller areas. When May et al. (1995) calculated the effect of extinction pattern on SLOSS with regard to random extinction, they did not take species minimum-area requirements into account (Lomolino, 2000; Turner and Tjørve, 2005), though others, like Diamond (1976), already commented that reserve size determines whether a species can maintain a viable population. Minimum-area requirements are the result of minimum viable populations or vice versa. We may, therefore, use the two terms interchangeably as an argument for a reserve species–area curve depressed at smaller scales (Turner and Tjørve, 2005).

The species–area curve has for a long time played an important part in conservation biology, including the SLOSS debate (see e.g. Rosenzweig, 2004, for review). In this paper, the question of when a single large reserve is better and when several small are better is assessed through species-diversity models that combine species–area curves for several areas, or as in this case; reserves. The few papers that have discussed how to calculate the combined species diversities of several areas or types of nature (e.g., landscape mosaics of different habitat patches) either model the optimal number of reserves, the optimal size allocation between reserves, or both (Bascompte et al., 2007; Tjørve, 2002). Both my 2002 paper and the paper by Bascompte et al. (2007) started by discussing the optimal size allocation among two reserves. The latter then went on to discuss size allocation among several reserves. I shall not discuss here how much area should be allocated to each reserve in order to maximize the total number of species; rather, I shall restrict the approach to the basic question of the SLOSS debate of what number of reserves will hold the most species. I have attempted this through the type of species-diversity modeling whereby the total area (reserve system) is divided into a number of equally sized reserves.

We may expect several different factors to affect such models and thereby the outcome of the SLOSS question. We know there must exist a trade-off in the SLOSS-debate, but we do not have a quantitative prediction for how SARs, compositional similarity (affected by isolation and distance), relative abundance, etc., shape this trade-off. The aim is to describe the effect of such factors on the optimal number of reserves in a reserve system, given that total reserve area is constant. I approach this through discussions of how maxima of species-diversity models vary with species–area curve shape and with species overlap between areas (or reserves). This approach is again based on knowledge about how factors as MAEs, species overlap between subdivisions of an area, spatial aggregation of individuals and species abundances affect the shape of species–area curves.

Section snippets

Modeling SLOSS

Let us consider those reserves that display some degree of isolation, meaning that barriers exist so that species individuals cannot move or immigrate completely freely from the surroundings or similar areas. We may, therefore, perceive them as fragments, islands or what has come to be termed as isolates (Preston, 1962a, Preston, 1962b; Tjørve and Turner, 2009; Turner and Tjørve, 2005). When modeling SLOSS, therefore, we may expect the species–area curve generated from single areas (e.g. nature

Implications for conservational strategies

This approach to modeling based on combining species–area curves demonstrates how whether a single large area or several small areas will hold the most species will differ between cases. The discussion above has shown that whether a single large or several small reserves will maintain the most species is linked to the shape of species–area curves and to (the proportion of) species overlap between separate reserves, as they both affect the outcome. The shape of the species–area curve is a result

Acknowledgements

I am grateful to W.E. Kunin, K.M.C. Tjørve and K.I. Ugland for stimulating discussions and constructive comments, which greatly improved the article, and to S. Connolley for editing and correcting the language.

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