Biogeography of Great Basin butterflies: revisiting patterns, paradigms, and climate change scenarios

Biological Journal of the Linnean Society (2001), 74: 501–515. With 4 figures doi:10.1006/bijl.2001.0597, available online at http://www.idealibrary.com on

Biogeography of Great Basin butterflies: revisiting patterns, paradigms, and climate change scenarios ERICA FLEISHMAN1∗, GEORGE T. AUSTIN2 and DENNIS D. MURPHY3 1

Center for Conservation Biology, Department of Biological Sciences, Stanford University, Stanford, CA 94305-5020, USA 2 Nevada State Museum and Historical Society, 700 Twin Lakes Drive, Las Vegas, NV 89107, USA 3 Department of Biology/314, University of Nevada, Reno, NV 89557, USA Received 2 April 2001; accepted for publication 17 July 2001

We used comprehensive data on butterfly distributions from six mountain ranges in the Great Basin to explore three connected biogeographic issues. First, we examined species richness and occurrence patterns both within and among mountain ranges. Only one range had a significant relationship between species richness and area. Relationships between species richness and elevation varied among mountain ranges. Species richness decreased as elevation increased in one range, increased as elevation increased in three ranges, and was not correlated in two ranges. In each range, distributional patterns were nested, but less vagile species did not always exhibit greater nestedness. Second, we compared our work with similar studies of montane mammals. Results from both taxonomic groups suggest that it may be appropriate to modify existing general paradigms of the biogeography of montane faunas in the Great Basin. Third, we revisited and refined previous predictions of how butterfly assemblages in the Great Basin may respond to climate change. The effects of climate change on species richness of montane butterflies may vary considerably among mountain ranges. In several ranges, few if any species apparently would be lost. Neither local species composition nor the potential order of species extirpations appears to be generalizable  2001 The Linnean Society of London among ranges. ADDITIONAL KEY WORDS: species richness – species occurrence – island biogeography – area – elevation – nestedness – Spring Mountains – conservation.

mountaintops, often contain relatively high numbers of native and endemic species (Wilcox, 1980; Myers, 1986; Meffe & Carroll, 1994; Guisan et al., 1995). Unfortunately, impending climate change (IPCC, 2001) is likely to erode current levels of species richness on mountains. As existing temperature and precipitation gradients are modified, many species will be forced to either shift their distributions accordingly, adapt in situ, or face local extirpation (Parmesan, 1996; Kienast, Wildi & Brzeziecki, 1998; Parmesan et al., 1999; Thomas & Lennon, 1999; Saether et al., 2000). Because mean air temperature decreases 0.6°C with every 100 m increase in elevation, for example, a 3°C rise in average temperature would require a species to shift its distribution upward 500 m in order to track a specific thermal environment (Schneider, Mearns & Gleick, 1992). Island biogeography has been used to help explain the assembly of montane faunas in the Great Basin of

INTRODUCTION Conservation and land-use planning draws heavily upon the theory of island biogeography (MacArthur & Wilson, 1967; Diamond, 1975; Shaffer, 1990; Noss, O’Connell & Murphy, 1997; Hanski, 1999). On the basis of biogeography theory, we assume, for example, that all else being equal, species richness and population size will be greater on islands that are relatively large and near sources of colonists than on islands that are relatively small and isolated. ‘Island’ can be interpreted broadly, encompassing both oceanic archipelagos and isolated terrestrial or aquatic communities. Island biogeography frequently has been invoked in montane environments, in which many species are isolated by elevation. Montane islands, or

∗ Corresponding author. E-mail: [email protected] 0024–4066/01/120501+15 $35.00/0

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western North America and to predict how those faunas will respond to climate change. McDonald & Brown (1992), for example, projected the impacts of increasing temperature on montane mammals in the Great Basin. Their forecasts were predicated on a strong positive relationship between species richness and area, a weak relationship between species richness and isolation from potential sources of colonists, and nested patterns of species occurrence. (A nested biota is one in which the species present in depauperate locations are subsets of the species present in locations that are richer in species [Patterson & Atmar, 1986].) Similarly, Murphy & Weiss (1992) and Boggs & Murphy (1997) examined how climate change might perturb species richness of butterflies in the montane Great Basin. Their calculations for butterflies, like those for mammals, were based upon positive correlations between species richness and mountain range area and indications that Great Basin butterflies comprised remnant faunas formed primarily by extinctions. Subsequently, using an expanded set of data on mammals in the Great Basin, Lawlor (1998) reexamined Brown’s (1971, 1978) faunal relaxation hypothesis. Lawlor argued that present-day assemblages are considerably more dynamic than previously understood; both extinction and colonization appear to drive distributional patterns of montane mammals in the Great Basin. His results, buttressed by other studies (Grayson, 2000; Grayson & Madson, 2000), brought into question the utility of island biogeography as a model for predicting regional losses of mammal species due to climate change. In fact, Lawlor (1998: 1127) found that “virtually no extinctions can be expected from a projected 3°C rise in temperature.” In this paper, we capitalize upon comprehensive, current data on butterfly distributions from six mountain ranges in the Great Basin to explore three major and connected issues. First, we analyse species richness and occurrence within, as well as among, mountain ranges. We are not aware of previous studies that have specifically analysed and compared biogeographic patterns within multiple mountain ranges. Biogeographic patterns at the within-range scale are especially relevant to contemporary land use planning by federal and state resource agencies. Second, we compare our results to those of Lawlor (1998) to examine whether it may be appropriate to modify existing general paradigms of the biogeography not only of butterflies, but also of faunal assemblages more broadly in the Great Basin. Third, we take advantage of our data on the distributions of individual species to revisit and refine previous predictions of how butterfly assemblages in the Great Basin may respond to climate change. In particular, we address not only the

number, but also the identity, of taxa that may be extirpated.

METHODS DATA SETS

We compiled data on distributions of butterflies for six mountain ranges in the Great Basin: the east slope of the Sierra Nevada (one of the two ‘mainlands’ for the ecoregion), Wassuk Range, Shoshone Mountains, Toiyabe Range, Toquima Range, and Spring Mountains (Fig. 1). Some of the data for the Toiyabe and Toquima ranges were presented and compared in previous publications (Fleishman, Austin & Weiss, 1998; Fleishman, Murphy & Austin, 1999; Fleishman, Fay & Murphy, 2000). Our data include representatives of both distinct centres of butterfly distribution and differentiation in the Great Basin and three of the seven biogeographic subregions (as defined by Austin & Murphy, 1987). In the Western Region, the Wassuk Range is within the Inyo Subregion. In the Eastern Region, the Shoshone Mountains, Toiyabe Range, and Toquima Range are within the Toiyabe Subregion, and the Spring Mountains is within the Mojave Subregion (Austin & Murphy, 1987). Data for 134 point locations in the Spring Mountains, spanning an elevational gradient from >885 to 3460 m (the full extent of the existing gradient), were compiled from extensive field records, museum records, and notes of private collectors taken from the 1920s to the present. Collection of data from these locations has been relatively exhaustive. Elevations were obtained by digitizing sampling locations from 1:100 000 US Geological Survey quadrangles to a 1:100 000 digital elevation model maintained on a GIS. Data for all ranges except the Spring Mountains were collected between 1994 and 2000 using the same methods, described in detail in Fleishman et al. (1998, 2000). In the Wassuk Range, Shoshone Mountains, Toiyabe Range, and Toquima Range, we conducted butterfly species inventories in multiple canyons that drain their east- and west-facing slopes. We sampled canyons only on the east slope of the Sierra Nevada because the west slope is not part of the Great Basin ecoregion (Stein, Kutner & Adams, 2000). We divided canyons into contiguous segments, each extending for approximately 100 vertical m (i.e. a 100 m change in elevation), from their base to their crest. Elevation was verified with differentially corrected Global Positioning System locations. We inventoried 52 locations in the Sierra Nevada (covering an elevational range from >1635–3400 m), 35 in the Wassuk Range (1395– 3380 m), 22 in the Shoshone Mountains (2025–2735 m), 102 in the Toiyabe Range (1915–3270 m), and 49 in the Toquima Range (1870–2750 m). Although the elevational gradient (i.e. the elevation of the valley floor

BIOGEOGRAPHY OF GREAT BASIN BUTTERFLIES

OREGON

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IDAHO

NEVADA UTAH

ARIZONA

N

CALIFORNIA

0

50 100 150 200 km

Figure 1. Location of study ranges (shaded) within the Great Basin. Clockwise from left: Sierra Nevada, Wassuk, Shoshone, Toiyabe, Toquima, Spring Mountains.

and the crest of the range) varies among ranges, the mean elevation of our inventory locations (>2415 m) did not differ among mountain ranges (F4,259=0.49, P=0.74). We inventoried the presence/absence of butterflies in each segment throughout the majority of the flight season using standard methods for butterflies in temperate regions (e.g. Pollard & Yates, 1993; Harding, Asher & Yates, 1995; again, see Fleishman et al., 1998, 2000 for a detailed description). Analyses were restricted to montane butterflies, taxa that are believed to complete their entire life cycle in the focal range and are not found in valleys in the vicinity of that range (Fleishman et al., 1998, 1999). In the frequently narrow, steep-walled study canyons, sampled area was defined as 50 m on all sides of the inventory route. Inventory intensity (person-hours) was proportional to segment area. Voucher specimens have been deposited

at the Nevada State Museum and Historical Society, Las Vegas. In all mountain ranges, average segment length was greater than 1 km. None of the montane butterflies in these ranges is highly vagile; fewer than >25% of the species regularly disperse more than a few hundred meters from where they eclosed (Fleishman, Austin & Murphy, 1997). Recording a species from a given segment, therefore, usually implies that the species breeds in that segment (Fleishman et al., 2000).

ANALYSES

Full data set Within five mountain ranges (excepting the Spring Mountains), we first tested whether there was a significant linear relationship between species richness

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of butterflies (ln S) and area (ln A). Our two largest canyon segments in the Sierra Nevada were statistically significant outliers with respect to area (Grubbs test, P<0.05; Sokal & Rohlf, 1981), and therefore were excluded from this analysis. We also tested whether there were significant linear or quadratic relationships between species richness and elevation (using the midpoint elevation of each canyon segment, or the elevation of sampling points in the Spring Mountains). Next, we tested whether butterfly assemblages within each mountain range had nested distributions. We assembled presence-absence matrices by listing locations as rows in order of decreasing species richness and species as columns in order of decreasing ubiquity. We computed the relative nestedness (C) of each matrix with the program NESTCALC (Wright, Reeves & Berg, 1990). To test whether matrices were significantly nested, we used Cochran’s Q statistic (Wright & Reeves, 1992). In addition, we examined the potential effects of climate change on the distribution of butterflies within each of the six mountain ranges. In each range, we calculated the elevational range of each butterfly species by subtracting the lower limit of the lowest segment (or, in the Spring Mountains, the lowest point) from which the species was recorded from the upper limit of the highest segment (in the Spring Mountains, the highest point) from which it was recorded (Fleishman et al., 1998). We then shifted the elevational distribution of every butterfly species upward by 500 m. We acknowledge that butterflies currently may occur at higher elevations than we sampled; because of logistic constraints, we did not sample the highest elevations in the Sierra Nevada (>4000 m), Shoshone Mountains (>3150 m), Toiyabe Range (>3550 m), or Toquima Range (>3300 m). Potential implications of this caveat are addressed in the Results and Discussion.

Central Great Basin To examine whether biogeographic patterns and potential responses to climate change were similar among geographically proximate mountain ranges, we conducted several more intensive analyses of data from the Shoshone Mountains, Toiyabe Range, and Toquima Range. To control for species composition, we restricted these analyses to the 29 species of montane butterflies that occur in all three ranges. The neighboring Shoshone, Toiyabe, and Toquima are similar in terms of their latitude, longitude, and regional climate, biogeographic past and ancestral biota, and management histories (Wilcox et al., 1986; Austin & Murphy, 1987; Grayson, 1993; Fleishman et al., 2000). Although the ranges cannot be considered as true ecological

equivalents, they seem to provide the best available opportunity to examine the generality of local patterns of species distributions. On the basis of distance between ranges (>10–20 km), low vagility of montane butterflies, and resource limitations in the valleys, it is reasonable to assume that assemblages of montane butterflies in the three ranges are independent (i.e. that individuals are not migrating among ranges) (Mac Nally & Fleishman, in press). Individual mountain ranges in the Great Basin function as discrete islands for many taxa that either are restricted to montane habitats or have relatively low mobility, including butterflies (McDonald & Brown, 1992; Murphy & Weiss, 1992). Most resources used by butterflies, such as larval hostplants and adult nectar sources, are concentrated in the floors of canyons within mountain ranges. Such resources are scarce in the wide desert valleys that isolate the mountain ranges. There is no contiguous ‘corridor’ of suitable habitat (e.g. a stream) between the Toquima and Toiyabe ranges, and relatively little suitable habitat where the Toiyabe Range abuts the Shoshone Mountains. Thus, resource limitation appears to impede regular movement of butterflies between ranges (Fleishman & Murphy, 1999). First, we tested whether the mean distributional limits of butterfly assemblages (as detected by our sampling methods) differed among the Shoshone Mountains, Toiyabe Range, and Toquima Range. We used analysis of variance to compare minimum and maximum elevational limits (averaged across the species assemblage) in each mountain range. When there was a significant difference among ranges, we used Tukey–Kramer HSD tests to compare pairs of means. Second, we investigated patterns of nestedness in more detail than in the full data set analyses. We used Z-scores (standard-Normal variates; Wright & Reeves, 1992) to test whether there were significant differences among the relative nestedness of butterfly species grouped according to vagility (10s, 100s, or 1000s of m, Fleishman et al., 1997) in the Shoshone Mountains, Toiyabe Range, and Toquima Range. We used Wilcoxon two-sample rank tests (Mann–Whitney U-tests) (Simberloff & Martin, 1991; Kadmon, 1995; Hecnar & M’Closkey, 1997) to test whether individual species had nested distributions (i.e. whether each species tended to be present in relatively species-rich locations) in each mountain range. Finally, we used Spearman rank-correlation to test whether occurrence and degree of nestedness of each species were significantly correlated among mountain ranges. The objective of the latter tests was to elucidate whether the order in which species are added to or deleted from local communities was predictable among ranges.

BIOGEOGRAPHY OF GREAT BASIN BUTTERFLIES

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4 Sierra Nevada

Wassuk

Shoshone

Toiyabe

3

ln (number of species)

2 1 0

4 Toquima

3 2 1

0

1

2

3

4

0

1

2

3

4

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3

4

ln (area)

Figure 2. Relationship between number of species of montane butterflies and sampling area (ha) within five mountain ranges in the Great Basin. Note: axes are the same for all ranges. Sierra Nevada: F1,51=0.79, P=0.38; Wassuk: F1,34= 2.29, P=0.14; Shoshone: F1,21=0.40, P=0.54; Toiyabe: F1,101=17.17, P<0.0001, r2=0.15; Toquima: F1,47=0.96, P=0.33.

RESULTS We recorded a total of 65 species of montane butterflies: 43 species from the Sierra Nevada, 34 from the Wassuk Range, 29 from the Shoshone Mountains, 40 from the Toiyabe Range, 33 from the Toquima Range, and 43 from the Spring Mountains. Complete species lists are available from the corresponding author upon request. BIOGEOGRAPHIC PATTERNS: AREA, ELEVATION, AND NESTEDNESS (FULL DATA SET ANALYSES)

Within each mountain range, there was little evidence that species richness tends to increase as area increases (Fig. 2). Larger canyon segments generally did not tend to have greater species richness than smaller canyon segments. Only one of the five ranges, the Toiyabe Range, had a significant positive relationship between species richness and area. Linear relationships between species richness and elevation were not consistent among mountain ranges (Fig. 3). In the Toiyabe Range, species richness significantly decreased as elevation increased (Table 1). In the Wassuk Range and Toquima Range, by contrast, species richness increased significantly as elevation increased. In the Sierra Nevada, we initially did not find a significant relationship between species richness and elevation. Examination of a Mahalanobis outlier distance plot, however, revealed three extreme outliers.

(Our observations in the field did not suggest that these locations were outliers with respect to other important environmental features.) When these points were excluded from the analysis, species richness increased significantly as elevation increased (Table 1). We emphasize that with or without outliers, species richness clearly did not decrease monotonically with increasing elevation. There was no significant linear relationship between species richness and elevation in either the Shoshone Mountains or the Spring Mountains. Species richness was more successfully explained as a quadratic function of elevation than as a linear function (Table 1); species richness tended to peak at an intermediate elevation. This relationship was statistically significant in five of the six mountain ranges we examined (all but the Shoshone) (Fig. 3). Treating elevation as a quadratic variable explained more of the variance in species richness in the four ranges that also exhibited significant linear relationships between the two variables (Toiyabe, Sierra Nevada, Wassuk, and Toquima) (Table 1). Within mountain ranges, nested distribution patterns appear to be common across the Great Basin. In each of our six mountain ranges, species found in more depauperate locations were statistically significant subsets of the species found in richer locations (Table 2).

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35

Wassuk

Sierra Nevada

30

25

25

20

20

15

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10 Number of species

Spring Mountains

10

5

5

0

0 500 1200 1900 2600 3300

30

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Toiyabe

Toquima

25 20 15 10 5 0 1500 2000 2500 3000 3500 1500 2000 2500 3000 3500 1500 2000 2500 3000 3500 Elevation (m)

Figure 3. Relationship between number of species of montane butterflies and elevation within six mountain ranges in the Great Basin. Note: axes are the same for all ranges except the Spring Mountains. Outliers in the Sierra Nevada are indicated by open circles. Table 1. Relationships between species richness of montane butterflies and elevation within six mountain ranges in the Great Basin. df, degrees of freedom. ∗PΖ0.05; ∗∗PΖ0.01; ∗∗∗PΖ0.001

Table 2. Mountain range, values of the relative nestedness index C, and associated Q, and degrees of freedom (df). For all ranges, P<0.0001 Mountain range

Mountain range

Sierra Nevada1 Wassuk Shoshone Toiyabe Toquima Spring Mountains 1

df

1,48 1,34 1,21 1,101 1,48 1,133

Linear

C

Q

df

0.378 0.394 0.400 0.468 0.365 0.583

36 854 349 211 1316 351 1009

42 33 28 39 32 42

Quadratic 2

2

F

r

F

r

15.86∗∗∗ 13.766∗∗∗ 0.32 32.44∗∗∗ 17.75∗∗∗ 0.23

0.25 0.29

8.97∗∗∗ 9.25∗∗∗ 1.68 17.02∗∗∗ 10.29∗∗∗ 6.88∗∗∗

0.28 0.37

0.24 0.27

Sierra Nevada Wassuk Shoshone Toiyabe Toquima Spring Mountains

0.26 0.31 0.10

Three outliers removed.

CLIMATE CHANGE (FULL DATA SET ANALYSES)

Our results suggest that the effects of climate change on species richness of montane butterflies may vary considerably among mountain ranges. Further, the impacts of climate change may depend in part upon whether butterflies can retreat to and persist on the highest peaks in each range. When we adjusted the elevational ranges of all montane species upward by 500 m, only one apparent extirpation (Parnassius smintheus) was produced in the Sierra Nevada, and none were produced in the Wassuk Range. It is possible

that P. smintheus could retreat to higher elevations in portions of the Sierra Nevada that were not part of this study; regardless, we underscore the point that few if any species apparently would be lost. Likewise, no species apparently would disappear from either the Toiyabe Range or the Spring Mountains as a function of elevational distribution alone. The issue of whether the highest peaks in each range could serve as refugia may be more critical in the Shoshone Mountains and Toquima Range. Although most of the Shoshone and Toquima crests lie between 2700 and 2800 m, the highest peak in the Shoshone Mountains is nearly 3150 m, and a 13 km stretch of the Mt Jefferson ridgeline, with three summits above 3300 m, rises above the spine of the Toquima Range.

BIOGEOGRAPHY OF GREAT BASIN BUTTERFLIES

If the current elevational ranges of all montane species of butterflies shift upward by 500 m, the lower elevational limit of 14 species in the Shoshone Mountains will exceed 2700 m (Hesperia uncas, Papilio rutulus, P. zelicaon, Anthocharis sara, Harkenclenus titus, Satyrium californicum, Loranthomitoura spinetorum, Euphilotes ancilla, Glaucopsyche piasus, Icaricia shasta, Speyeria coronis, S. callippe, Euphydryas editha, and Polygonia zephyrus). The lower limit of only one species (Harkenclenus titus), however, will exceed the maximum elevation in the Shoshone Mountains. In the Toquima Range, two species (Hesperia uncas and Harkenclenus titus) may be extirpated if they cannot retreat to Mt Jefferson. Whether butterflies can retreat to potential highelevation refugia will depend in part on their ability to disperse sufficiently rapidly to accommodate changes in temperature and precipitation along the elevational gradient. If larval hostplants, adult nectar sources, and appropriate microclimates simply move gradually upward across entire mountain ranges, butterflies should be able to track these necessary resources. However, if certain slope exposures (e.g. southand west-facing slopes) become disproportionately warm and dry, butterflies (or plants) may not be capable of dispersing to areas with more favourable conditions, and local extirpations may result (Murphy & Weiss, 1992; Fleishman et al., 1998). Another consideration is that high elevations likely will continue to have greater environmental variability than lower elevations (Hidy & Klieforth, 1990). Therefore, as butterflies move upward in response to climate change, they may encounter progressively more variable weather and more severe topography.

CENTRAL GREAT BASIN: CONCORDANCE OF PATTERNS

The suitability of low-elevation slopes for montane butterflies appears to vary among Great Basin mountain ranges. Controlling for species composition (i.e. restricting our analyses to the 29 species of butterflies that occur in all three of the Shoshone, Toiyabe, and Toquima ranges), the average minimum elevation at which butterfly species occurred in the Toiyabe Range was significantly lower than the minimum elevation at which they occurred in either the Shoshone Mountains or Toquima Range (F2,86=18.88, P<0.001, r2= 0.31) (Fig. 4). This result cannot be explained solely as a sampling artifact; for example, the minimum elevation of our transects was lower in the Toquima Range than in the Toiyabe Range. The average upper elevational limit of the shared butterfly assemblage (29 species) in the Toiyabe Range was significantly higher than in the Shoshone Mountains or Toquima Range (F2,86=24.47, P<0.001, r2= 0.37) (Fig. 4). However, the average elevation of the

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Toiyabe Range crest and of our inventory routes generally exceeds that of the Shoshone Mountains and Toquima Range, so there is a strong possibility that this result was a sampling artifact. Because the number of mountain ranges that we sampled was small (three), we did not test statistically whether the butterfly assemblages in the central Great Basin ranges were nested subsets of each other. Nonetheless, it is clear from a visual inspection of a mountain range by species matrix that the montane butterfly species present in the Toquima Range are a subset of the species present in the Toiyabe Range (Fleishman et al., 1999), and the Shoshone Mountains assemblage is a subset of the Toquima Range assemblage. It is unlikely that our observation of nestedness among mountain-range level faunas is an artifact of sample size (i.e. number of locations inventoried in each range); there are strong ecological explanations for most of the apparent absences (Austin & Murphy, 1987; Fleishman et al., 1997, 1999). For example, populations of Pholisora catullus, Lycaena nivalis, Incisalia augustinus, and Speyeria egleis in the Toiyabe Range probably are relictual (Fleishman et al., 1997). The Toiyabe Range is the only location in central Nevada where these four species have been recorded. Several additional species apparently absent from the Shoshone Mountains and Toquima Range, such as Papilio bairdii and P. indra, principally are found in riparian canyons; streams and seeps in the Shoshone and Toquima often are isolated (we note that both species are large, showy, and unlikely to be overlooked by experienced observers where present). Suitable habitat patches in the latter ranges may be too distant from each other and from occupied habitats outside the range for immigration to occur regularly, and for the species to maintain viable populations in the Shoshone Mountains and Toquima Range (Hanski & Gilpin, 1991; Hanski, 1991; Murphy, Freas & Weiss, 1990). It is possible that the apparent absence of a few species, including Incisalia fotis and Thessalia leanira, does reflect human sampling error. These two species fly extremely early in the season and are rare. Failure to record some uncommon species also might result from natural variation in occurrence patterns from year to year (Pollard, 1988, 1991). We suspect that many rare species of butterflies, like mammals (Grayson & Livingston, 1993), have been under-reported from remote areas of the Great Basin. There were significant differences in the relative nestedness of species grouped according to vagility in the Shoshone Mountains, in the Toiyabe Range, and in the Toquima Range (Table 3). Within each range, however, less vagile species did not always exhibit greater nestedness (Table 4). In the Shoshone Mountains, for instance, relative nestedness tended to increase as vagility increased. Similarly, in the Toiyabe

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1800

ERPE HEUN PAZE PARU PAMU NEME EUAN ANSA LYHT HATI SABE SACA LOSP MISI INER CELA EUAC GLPI ICIC ICSH ICLU SPCO SPZE SPCA CHAC EUAN EUED POZE CEST

2100

Figure 4. Elevational ranges of the 29 species of butterflies that occur in all three of the Shoshone, Toiyabe, and Toquima ranges. Horizontal lines indicate the lowest and highest elevations sampled in each range. Species are listed in taxonomic order following Austin (1998): ERPE, Erynnis persius; HEUN, Hesperia uncas; PAZE, Papilio zelicaon; PARU, Papilio rutulus; PAMU, Papilio multicaudatus; NEME, Neophasia menapia; EUAU, Euchloe ausonides; ANSA, Anthocharis sara; LYHT, Lycaena heteronea; HATI, Harkenclenus titus; SABE, Satyrium behrii; SACA, Satyrium californicum; LOSP, Loranthomitoura spinetorum; MISI, Mitoura siva; INER, Incisalia eryphon; CELA, Celastrina ladon; EUAN, Euphilotes ancilla; GLPI, Glaucopsyche piasus; ICIC, Icaricia icarioides; ICSH, Icaricia shasta; ICLU, Icaricia lupini; SPCO, Speyeria coronis; SPZE, Speyeria zerene; SPCA, Speyeria callippe; CHAC, Chlosyne acastus; EUAN, Euphydryas anicia; EUED, Euphydryas editha; POZE, Polygonia zephyrus; CEST, Cercyonis sthenele.

Table 3. Values of the relative nestedness index C for species grouped according to vagility. Sample sizes (number of species) in parentheses. All groups were significantly nested (P<0.0001)

Table 4. Pairwise comparison among values of the relative nestedness index C for butterflies with different vagility. Values presented are Z-scores. P-values are onetailed. ∗PΖ0.05; ∗∗PΖ0.01; ∗∗∗PΖ0.001

Mountain range

Mountain range

Vagility (m)

Shoshone

Toiyabe

Toquima

Vagility (m)

Shoshone

Toiyabe

Toquima

10s 100s 1000s

0.333 (8) 0.416 (13) 0.611 (8)

0.654 (13) 0.357 (16) 0.477 (11)

0.402 (9) 0.401 (15) 0.127 (9)

10s vs 100s 10s vs 1000s 100s vs 1000s

−0.66 −2.20∗∗ −2.30∗∗

16.80∗∗∗ 9.79∗∗∗ −5.33∗∗∗

0.01 1.62∗ 1.63∗

BIOGEOGRAPHY OF GREAT BASIN BUTTERFLIES

Range, species with vagilities in the 1000s of m were significantly more nested than species with vagilities in the 100s of m. At the level of individual species, nestedness means that the sequence of presences and absences is significantly different from random. A species with a nested distribution tends to be present in relatively species-rich locations and absent from relatively species-poor locations. Eight of the 29 species present in the Shoshone Mountains (28%) had significantly nested distributions (PΖ0.05); 30 of the 40 species (75%) recorded from the Toiyabe Range and 24 of the 33 species (73%) recorded from the Toquima Range had significantly nested distributions (Table 5). Five of the 29 species common to the Shoshone, Toiyabe, and Toquima ranges had significantly nested distributions in all three ranges (Satyrium behrii, Euphilotes ancilla, Glaucopsyche piasus, Icaricia lupini, and Speyeria coronis). Occurrence was significantly (P<0.05) rank-correlated among all pairs of ranges (Shoshone-Toiyabe, rs=0.429; Shoshone-Toquima, rs= 0.476; Toiyabe-Toquima, rs=0.380), indicating that a species that is relatively widespread in one range is likely to be fairly widespread in nearby ranges as well. Degree of nestedness, however, was not significantly rank correlated among any pair of ranges (Shoshone-Toiyabe, rs=0.026, Shoshone-Toquima, rs= −0.003; Toiyabe-Toquima, rs=0.056). This indicates that neither local species composition nor the potential order of species extirpations is generalizable among ranges.

DISCUSSION Most previous studies of Great Basin biogeography have used mountain ranges as the sampling unit. Researchers have tested, for example, whether large mountain ranges tend to have greater species richness than smaller mountain ranges, and whether rangelevel assemblages form nested subsets (e.g. Brown, 1971, 1978; Wilcox et al., 1986; Murphy & Weiss, 1992; Boggs & Murphy, 1997; Lawlor, 1998). However, the mountain range may not be the most relevant unit for modern land-use planning. Federal resource agencies in the arid western United States often develop distinct management plans for each major mountain range under their jurisdiction, and then delineate land uses at the level of canyons or watersheds within ranges (Fleishman & Murphy, 1999; J. Grevstadt, pers. comm.). By emphasizing within-range patterns (with subsequent comparison among ranges), we focus at a scale that arguably is the most appropriate for future land management planning realities in the Great Basin.

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Table 5. Nestedness of individual butterfly species. Test statistics (Z-scores) are for Wilcoxon two-sample rank tests. ∗PΖ0.05; ∗∗PΖ0.01; ∗∗∗PΖ0.001. Species are listed in taxonomic order following Austin (1998) Shoshone Erynnis persius 1.941 Pholisora catullus Hesperia uncas 1.331 Papilio bairdii Papilio zelicaon 0.058 Papilio indra Papilio rutulus −0.799 Papilio multicaudatus 0.846 Neophasia menapia 0.036 Pontia sisymbrii Euchloe ausonides 2.766∗∗ Anthocharis sara −0.926 Lycaena arota Lycaena heteronea 2.390∗ Lycaena nivalis Harkenclenus titus −0.799 Satyrium behrii −2.064∗ Satyrium californicum 0.000 Callophrys affinis Loranthomitoura spinetorum −0.080 Mitoura siva −0.902 Incisalia augustinus Incisalia fotis Incisalia eryphon 1.072 Celastrina ladon −0.906 Euphilotes ancilla −2.420∗ Glaucopsyche piasus −2.196∗ Icaricia icarioides 2.133∗ Icaricia shasta −0.635 Icaricia lupini −2.262∗ Speyeria coronis −2.240∗ Speyeria zerene 1.736 Speyeria callippe 1.729 Speyeria egleis Thessalia leanira Chlosyne acastus 0.906 Euphydryas anicia 0.971 Euphydryas editha −0.388 Polygonia zephyrus −1.215 Cercyonis sthenele 1.072 Neominois ridingsii

Toiyabe

Toquima

4.515∗∗∗ −3.593∗∗∗ 1.269 −4.390∗∗∗ −6.180∗∗∗ −4.431∗∗∗ 5.096∗∗∗ 7.161∗∗∗ −2.636∗∗ −5.199∗∗∗ 5.903∗∗∗ −6.005∗∗∗ −5.180∗∗∗ −0.817 −0.907 −3.105∗∗ 5.906∗∗∗

−3.445∗∗∗ −2.648∗∗ −2.348∗ −3.416∗∗∗ −3.442∗∗∗ −1.407 1.933 −1.180 −2.648∗∗ −1.900 −3.682∗∗∗ −0.760 3.205∗∗∗

−3.389∗∗∗ −4.504∗∗∗ −1.528 −3.155∗∗ −1.894 −0.677 −2.236∗ −0.493 4.378∗∗∗ 5.963∗∗∗ 6.022∗∗∗ 5.310∗∗∗ −0.218 2.345∗ 4.446∗∗∗ −4.986∗∗∗ 3.812∗∗∗ 3.485∗∗∗ −3.672∗∗∗ −1.624 4.020∗∗∗ 4.954∗∗∗ −1.177 −3.645∗∗∗ 3.723∗∗∗

−1.627 1.031

0.553 −3.204∗∗∗ −3.326∗∗∗ −3.760∗∗∗ 2.227∗ −4.385∗∗∗ 5.070∗∗∗ −2.148∗ −3.710∗∗∗ −3.116∗∗

3.846∗∗∗ 4.195∗∗∗ −3.330∗∗∗ −3.473∗∗∗ −1.066 3.372∗∗∗

BIOGEOGRAPHIC PATTERNS

Area and elevation Data from several taxonomic groups, including butterflies and mammals, suggest that it may be appropriate to revise or expand current paradigms of

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Great Basin biogeography. For example, principles of island biogeography notwithstanding, neither area nor isolation seems to have a major effect on species richness or occurrence of butterflies in either the ‘mainland’ (Sierra Nevada) or ‘islands’ (five mountain ranges representing three major biogeographic subregions [Austin & Murphy, 1987]). We detected a significant correlation between species richness of montane butterflies and area in only one of five mountain ranges. The latter result does not imply absence of a relationship between species richness of butterflies and area at the mountain range level. Relatively large mountain ranges well may have more species than smaller mountain ranges (Boggs & Murphy, 1997; this study). At minimum, however, it is clear that any significant correlations between species richness and area are not consistent across spatial scales. Our results generally agree with Lawlor’s (1998) reanalysis of distributional patterns of montane mammals in the Great Basin. For example, Lawlor found that the correlation between species richness of mammals and area in the Great Basin (using mountain ranges as samples) was weaker than previously recognized. Other work has shown that the occurrence of most butterfly species (as well as their species richness), like that of mammals (Lawlor, 1998), was not heavily influenced by area (Fleishman et al., 2001). Because area decreases at higher elevations, island biogeographic theory would lead one to expect a negative correlation between species richness and elevation – provided all else is equal (but see Charlet, 1995). Of course, all else is not equal among mountain ranges in the Great Basin, and we found that species richness of butterflies rarely decreases (at least linearly) as elevation increases. Instead, species richness often increases as elevation increases. Reductions in area, however, are not the only reason one might expect species richness of butterflies to be inversely correlated with elevation. It is not trivial that as elevation increases, environmental conditions tend to be less favourable for flight and reproduction, and the risk of extirpation grows (Kingsolver, 1983a,b, 1989; Springer & Boggs, 1986; Dennis, 1991, 1993; Boggs & Murphy, 1997). Distributions of butterflies also reflect vegetation structure and composition, availability of topographic features that provide locations for seeking mates and shelter, the presence of running or standing water, and climatic severity and variability (Arms, Feeney & Lederhouse, 1974; Scott, 1975, 1982, 1986; Murphy & Wilcox, 1986; Lawton, MacGarvin & Heads, 1987; Boggs & Jackson, 1991). Patterns of vegetation (including composition, diversity, and primary productivity), topography, and climate with respect to elevation vary dramatically among mountain ranges, and we suspect that patterns of species richness within a mountain range often reflect range-specific gradients

in those key environmental variables (Fleishman et al., 1998, 2000). Thus, while elevation often is correlated with species richness of butterflies in Great Basin mountain ranges, the functional relationship between elevation and species richness differs among mountain ranges. Unfortunately, data on local vegetation and weather – habitat variables known to affect local butterfly distributions – currently do not exist for our study area (or for many other remote landscapes), especially not at the appropriate spatial and temporal resolution. However, the Earth Observing System’s Terra satellite and particularly the MODIS (moderate resolution spectroradiometer) instrument soon will yield high-resolution data on relevant variables including plant phenology and primary productivity. These empirical data will help fill critical gaps in our knowledge base, and we anticipate incorporating such new variables into our ongoing research. In the meantime, elevation seems to be a useful surrogate representation of underlying variables that ultimately may yield more mechanistic explanations for observed patterns of species distributions. There are two main reasons why we did not address potential interactions between isolation and species distributions. First, we question whether standard metrics of isolation are biologically realistic. Isolation of ‘islands’ typically has been measured as the minimum distance from the island to the nearest mainland. Thus, in the Great Basin, the distance from each mountain range to either the Sierra Nevada or the Rocky Mountains has been the standard measure of isolation. However, minimum distance to the nearest neighboring range (see Lawlor, 1998) might better represent current dispersal dynamics of most montane animal species. Second, although local topographic features (e.g. steep rocks walls that separate canyons) certainly function as impediments to butterfly dispersal, isolation in its traditional sense might play a relatively minor role within a mountain range. We agree with Lawlor (1998) that both extinction and colonization shape contemporary distributional patterns in Great Basin mountain ranges, and that riparian areas probably serve as centres of richness and abundance, as well as dispersal corridors, for montane taxa. In fact, because many larval hostplants, adult nectar sources, and nutrient-rich mud puddles tend to be concentrated in canyon bottoms, riparian corridors may help ameliorate some of the impediments to dispersal of butterflies in the face of climate change (see below). Nestedness It is not surprising that montane butterflies exhibit nested distributions within mountain ranges. Nestedness is common among species assemblages that

BIOGEOGRAPHY OF GREAT BASIN BUTTERFLIES

inhabit oceanic and terrestrial ‘islands’ (Wright et al., 1998). Documenting that a biota is nested provides a description of assemblage composition (cf. Worthen, 1996), but that phenomenological observation may not provide guidance for land-use planning if it does not advance an understanding of the agents that determine assemblage structure. Nestedness analyses have gained popularity among conservation scientists and practitioners because, in a nested assemblage, the order of species disappearances should be non-random and at least partially predictable (Patterson & Atmar, 1986). For example, if area is positively correlated and elevation is negatively correlated with species richness, and a biota is nested, then it should it be possible to predict the order in which species will be lost to climate change. Nested distributions are widespread in our study system. But, because species richness is not significantly correlated with area nor, in most cases, negatively correlated with elevation, we cannot draw upon nested patterns to examine potential climate change scenarios. Moreover, the fact that degree of nestedness of individual species was not correlated among ranges suggests that the order in which species may be extirpated is likely to differ among ranges. Nestedness analyses are valuable because they can suggest, albeit via correlation, whether a given mechanism or phenomenon is likely to affect distributional patterns (e.g. Cook & Quinn, 1995; Kadmon, 1995). Differences in degree of nestedness among groups of species that vary in sensitivity to some human land uses, for instance, may signal that the activity in question is responsible for extirpations (Hecnar & M’Closkey, 1997; Fleishman & Murphy, 1999; Jonsson & Jonsell, 1999). Among three mountain ranges, we did not find a consistent pattern in the relative nestedness of groups of species that vary in mobility. These results suggest that dispersal has played a minor role in establishing the distributional patterns of resident, montane butterflies within mountain ranges in the Great Basin (Cook & Quinn, 1995; Hecnar & M’Closkey, 1997; Fleishman & Murphy, 1999). On the whole, our results are consistent with previous indications that isolation has not been critical in establishing species composition at the mountain range level in this region.

CLIMATE CHANGE

Forecasts about the effects of climate change in the Great Basin usually have assumed that (1) regional temperature will warm by roughly 3°C, (2) vegetation zones will shift upward by 500 m, thereby decreasing in area, and (3) animals that are closely associated with particular plant communities likewise will move upward by 500 m (McDonald & Brown, 1992; Murphy & Weiss, 1992; Fleishman et al., 1998). Murphy &

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Weiss (1992), for example, estimated the number of butterfly species that would be extirpated by climate change on the basis of the species’ associations with several vegetation zones (e.g. pin˜on-juniper, alpine). Clearly, this scenario simplifies both climatic changes and biological responses. To some extent, oversimplification of climate change scenarios is necessary to accommodate scientific uncertainty and model tractability (Sala et al., 2000). Nonetheless, several caveats are worth noting – not to denigrate the scenario itself, but to help elucidate why our extirpation predictions differ widely from previous analyses. First, although the hostplants of some butterflies are associated with a particular vegetation type or thermal zone, other hostplants and many other plant species have a comparatively opportunistic distribution. The occurrence of numerous plant species may, for instance, be driven more by availability of water or certain soils than by elevation or temperature per se. Second, plant species have individual responses to climate change: a vegetational community does not move en masse (Gleason, 1926; Huntley, 1991; Tausch, Wigand & Burkhardt, 1993; Guisan et al., 1995; Risser, 1995; Kupfer & Cairns, 1996). As a result, it may not be possible to predict how hostplant or butterfly distributions will change on the basis of predicted shifts in vegetation zones. Third, butterflies often require resources in addition to hostplants: many species also require nectar sources, particular topographic features for finding mates, or specific microclimatic conditions for oviposition and larval development (e.g. Scott, 1986; Weiss, Murphy & White, 1988). This can have negative repercussions. Distributions of hostplants typically are much more extensive than distributions of the butterflies that use them, and populations of butterflies often disappear despite persistence of their hostplants (Murphy & Weiss, 1992). On a more positive note, although butterflies often have specific hostplant requirements, they tend to be more opportunistic in their use of nectar sources, and many species can exploit a wide variety of introduced or weedy species (e.g. the thistles Carduus nutans and Cirsium vulgare) for nectar. As a result, butterflies may be able to tolerate some of the replacements or invasions of plant species that almost certainly will accompany climate change. Moreover, locating hilltops or other topographic features to find mates can require some species of butterflies to disperse far from their hostplants; this behavioral strategy may help them track plant resources with shifting distributions. Some caveats about our own conclusions also should be recognized. For example, with respect to species richness, the loss of present-day montane butterflies should be offset somewhat by upward dispersal of species of butterflies that are currently residents in adjacent valleys (Fleishman et al., 1998) or to the

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south. Further, we have assumed that topography and vagility will not impede the ability of butterflies to track suitable vegetation and thermal zones. For instance, it is unknown whether thermal zones will gradually move upward across entire mountain ranges or whether certain slope exposures will become disproportionately warm and dry (Murphy & Weiss, 1992; Guisan et al., 1995; Fleishman et al., 1998). McDonald & Brown (1992) predicted that a 3°C rise in temperature would lead to the extirpation of 9–62% of the montane mammals in various Great Basin mountain ranges and 21% of the mammals in the Great Basin as a whole. Using more comprehensive data, Lawlor (1998) argued that very few species of mammals actually would be lost. Our results are similar. Few if any species of montane butterflies are likely to be extirpated from the entire Great Basin (i.e. lost from the region as a whole). The number of losses at the mountain range level may vary considerably among ranges. As noted above, especially in ranges with an average crest elevation below >3000 m, the magnitude of losses may depend upon whether butterflies can exploit isolated, high-elevation peaks. Considering only the elevational distributions of the butterflies we recorded (not their resource requirements), we predicted that losses of montane species in the mountain ranges we sampled would range from 0–48% (mean= 10%) if peaks cannot function as refugia, and just 0–3% if peaks can function as refugia. Even our more conservative scenario anticipates far fewer losses than Murphy & Weiss (1992), who predicted that extirpations of butterfly species from mountain ranges in the Great Basin would average 23%. Previous work by McDonald and Brown and Murphy and Weiss concluded that climate change will reduce species richness in highly predictable ways (Boggs & Murphy, 1997). Our work suggests that local changes in species richness in the Great Basin may be predictable (at least for well-known mountain ranges and species), but not generalizable. During the Middle Holocene, approximately 8000– 5000 years ago, temperatures in the Great Basin were several degrees warmer than today (Van Devender, Thompson & Betancourt, 1987). Thus, we might expect that most of the montane species – including butterflies – that currently inhabit the Great Basin would be able to tolerate the magnitude of climatic warming forecast over the next several centuries; species that were extremely sensitive to the effects of increased temperatures may already have been extirpated. However, it is not clear whether the Middle Holocene warming, which was caused by changes in solar insolation and accompanied by increases in summer precipitation, will be comparable to projected patterns of climate change (Grayson, 2000). In particular, some recent models imply that the summer season – the critical

season for reproduction by butterflies – will become more arid (USEPA, 1999). In addition, the response of butterflies to climate change may depend in part upon the speed at which those modifications occur and the extent to which not only the mean but also the variance in climate parameters increases (Hellman et al., unpublished manuscript). Mountain ranges in the Great Basin are not simple, generalizable systems. Despite the fact that many ranges have a common biogeographic history and similar species assemblages, patterns of species richness, occurrence, and the potential order of species extirpations vary among ranges. Studying distribution patterns in each range might yield the most accurate predictions about how assemblages of butterflies (or any other taxonomic group) will respond to climate change, but that approach is unlikely to prove feasible. Perhaps the best and most honest suggestions we can offer to conservation planners in the Great Basin derive from generalizations that cannot be made with confidence: area may not correlate with richness of montane species, species richness rarely declines monotonically along an increasing elevational gradient, and nestedness does not equate with the ability to predict the order of regional extirpations. While our work indicates that species distributions within a mountain range reflect resource distributions that are range-specific, we believe that it may be tractable to make strong inferences regarding the arrangement of those resources along topographic gradients in each mountain range. In a small range with limited riparian habitat, for example, higher elevations may be more mesic than lower elevations (Fleishman et al., 2000). Likewise, the orientation of a range with respect to prevailing storm patterns will affect moisture and wind gradients, which in turn have direct and indirect physiological and ecological effects on butterflies. Mapping the hypothetical distribution of resources along topographic gradients should be facilitated by the increasing ease with which topographic variables can be measured over large areas through satellite or airborne telemetry, reducing dependence upon intensive measurements of habitat.

ACKNOWLEDGEMENTS Thanks to C.L. Boggs, A.E. Launer, D. Charlet, and an anonymous reviewer for valuable comments on the manuscript, to J.P. Fay for computer support, to D.Z. Rubinoff, I. Woods, B. Boyd, and B. Boyd for assistance with data collection, to R. Ellston for preparation of Figure 1, and to the Humboldt-Toiyabe National Forest for logistic support in the field. Support for this research was provided by the Nevada Biodiversity Research and Conservation Initiative.

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