Canadian Journal of Zoology
Ecological limits to local species richness in dusky salamanders (genus Desmognathus Baird)
Journal: Canadian Journal of Zoology
Manuscript ID cjz-2016-0071.R2
Manuscript Type: Article
Date Submitted by the Author: 06-Oct-2016
Complete List of Authors: Camp, C.D.; Department of Biology Wooten, Jessica; Centre College, Biology Graham, Sean; Sul Ross State University, Biology, Geology, and Physical Sciences Draft Pauley, Thomas; Marshall University, Biological Sciences
species richness, ecological limits, GIS-based niche modeling, Appalachian Keyword: Mountains, Desmognathus
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1 Ecological limits to local species richness in dusky salamanders (genus Desmognathus
2 Baird)
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4 Carlos D. Camp a, Jessica A. Wooten b*, Sean P. Graham c, Thomas K. Pauley d
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6 aDepartment of Biology, Piedmont College, PO Box 10, Demorest, Georgia, USA
7 E mail: [email protected]
8 bDepartment of Biology, Centre College, 600 West Walnut Street, Danville, Kentucky, USA
9 E mail: [email protected]
10 cDepartment of Biology, Geology, and Physical Sciences, Sul Ross State University, Box C 64,
11 Alpine, Texas, USA Draft
12 E mail: [email protected]
13 dDepartment of Biological Sciences, Marshall University, 1 John Marshall Drive, Marshall
14 University, Huntington, West Virginia, USA
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16 *Corresponding author. Tel.: (859) 238 5322
17 E mail address: [email protected]
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24 Abstract: Species richness commonly varies with elevation, but in many montane regions, the
25 greatest number of species occurs at middle elevations. A recent regional analysis showed this
26 pattern in Appalachian salamanders of the genus Desmognathus Baird. The authors proposed
27 that the phylogenetic niche conservatism of these salamanders causes species to accumulate at
28 intermediate elevations, which are characterized by the ancestral climate for the genus. They
29 further suggested that physiological tolerances limit dispersal into higher or lower elevations. We
30 tested this hypothesis using geographic information systems (GIS) based analysis of 235 local
31 Desmognathus communities. Consistent with the regional analysis, local species richness was
32 greatest at middle elevations. However, the number of species is not limited by physiological
33 tolerances but appears to be restricted ecologically by climate variables favoring aridity as well
34 as by biotic factors. Whether such ecologicalDraft limits on species richness at the local level
35 influences richness across regions or evolutionary clades remains to be tested.
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39 Key words: species richness, ecological limits, GIS based niche modeling, Appalachian
40 Mountains, Desmognathus
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47 Introduction
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49 Biogeographers have long wondered why biodiversity is not randomly scattered across
50 the planet but occurs in certain regular, repeatable patterns. However, in spite of two centuries of
51 scholastic scrutiny punctuated by intensified research activity over the last several decades, no
52 consensus explanation has emerged (Rahbek 1997, 2005). In fact, more than 100 hypotheses
53 have been proposed to explain species richness patterns across the surface of the globe (Palmer
54 1994). While empirical research has whittled down this number to a handful of credible
55 hypotheses, debate continues (Rahbek and Graves 2001). For example, Rabosky (2009) recently
56 proposed ecological limits as an alternative to evolutionary diversification (speciation minus
57 extinction) rates in explaining species richnessDraft patterns across regions and evolutionary clades.
58 In a spirited rebuttal, Wiens (2011) pointed out that ecology cannot affect richness without
59 influencing rates of speciation, extinction, or dispersal. He further criticized Rabosky’s (2009)
60 evidence for ecological limits.
61 A well documented relationship is that between species richness and elevation. Among
62 the more enigmatic facets of this relationship is that the number of species often peaks at
63 intermediate elevations (e.g., Colwell and Lees 2000; McCain 2004; Cardelús et al. 2006; Li et
64 al. 2009). While this pattern has been recognized for decades (Rahbek 1995), the underlying
65 cause, or suite of causes, remains unresolved. Included in the explanations hypothesized for this
66 phenomenon are environmental conditions favoring either co existence (Heaney 2001) or
67 speciation (Smith et al. 2007), evolutionary time (Smith et al. 2007), population dynamics
68 (Kessler 2000), geographic area (Sanders 2002), or simply the central accumulation of species
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69 range overlaps resulting from their random shuffling within a geographically defined space (mid
70 domain effect, Colwell et al. 2004).
71 In a recent analysis, Kozak and Wiens (2010) demonstrated mid elevational peaks of
72 evolutionary lineages in several genera (i.e., genera Plethodon Tschudi and Desmognathus
73 Baird) of Appalachian salamanders. They further showed that mid level elevations have been
74 occupied longer than either higher or lower elevations. They hypothesized that phylogenetic
75 niche conservatism in these salamanders (Kozak and Wiens 2006) restricts these lineages to their
76 ancestral climatic niches, which are currently associated with intermediate elevations. As
77 speciation occurs within this climatic zone, dispersal to higher and lower elevations is
78 physiologically constrained, resulting in an accumulation of a greater number of species at mid
79 level elevations. Draft
80 Perceived patterns of species richness, however, vary with scale (Rahbek 2005), and
81 while local diversity ‒ i.e., species sympatric within the same community ‒ tends to reflect the
82 larger regional species pool (Harrison and Cornell 2008), it is at the local level where ecological
83 factors should affect species richness (Wiens 2011). Machac et al. (2011) showed that local
84 diversity may be constrained ecologically by both biotic and abiotic factors. Because the analysis
85 of Kozak and Wiens (2010) of salamanders was conducted at a regional scale across the
86 Appalachian Mountains, our purpose was to test their hypothesis at the level of the local
87 community.
88 We tested the hypothesis that species are physiologically restricted to the climates of
89 mid elevations by using Geographic Information Systems (GIS) based niche modeling. Driven
90 by recent advancements in computing power and the widespread availability of large,
91 environmental datasets, niche modeling has brought about a significant leap in understanding
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92 how climate and other factors regulate the geographical distribution of individual species (e.g.,
93 Graham et al. 2004; Kozak et al. 2008). This technique, however, has infrequently been used to
94 address questions regarding spatial patterns of community structure (Stephens and Wiens 2009).
95 We chose the salamander genus Desmognathus , a speciose lineage of Appalachian
96 salamanders whose communities are strongly influenced by interspecific interactions (Bruce
97 2009, 2011). Specifically we use GIS based niche modeling to answer the following questions.
98 1) Does species richness within local desmognathan communities peak at intermediate
99 elevations? 2) How does elevation relate to specific climatic variables? 3) What is the
100 relationship between local species richness and climatic variables? 4) Is the relationship between
101 species richness and climate constrained by physiological limits, i.e., is richness of local
102 communities defined entirely by the physiologicalDraft tolerances of individual component species?
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104 Materials and methods
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106 Study species
107 The dusky salamanders of the genus Desmognathus currently comprise 21 recognized,
108 named species (Table 1; http://amphibiaweb.org) of lungless salamander (family Plethodontidae Table 1
109 Gray), although additional unnamed, cryptic lineages exist (Beamer and Lamb 2008; Tilley et al.
110 2013; Tilley 2016). In a phylogenetic analysis of mtDNA sequences, Kozak et al. (2005)
111 identified 35 putatively independent, evolutionary lineages. This genus is distributed across most
112 of the eastern United States but is most speciose in the southern Appalachian Mountains where
113 up to six species can occur in together in a local community (Bruce 1991). Dusky salamanders
114 are typically associated with streams but vary widely in their microhabitat choice along moisture
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115 gradients. In multi species assemblages, with very few exceptions, each point along the gradient
116 is occupied by a species (or evolutionary lineage) possessing a unique ecomorph. Species range
117 from being large (adult body lengths = 90+ mm) and completely aquatic with multi year larval
118 periods to completely terrestrial, miniature species (adult body lengths < 40 mm) having no
119 aquatic larval phase (Petranka 1998). All species prey on invertebrates with both larvae (e.g.,
120 Burton 1976; Davic 1991; Beachy 1995) and adults (e.g., Martof and Scott 1957; Donovan and
121 Folkerts 1972; Fitzpatrick 1973; Krzysik 1979; Camp 1997) feeding primarily on insects.
122 Desmognathus communities have been studied for more than three decades as model systems
123 heavily influenced by biotic interactions among component members (reviewed by Bruce 2009,
124 2011). Species richness within this genus is known to be related to both elevation and climatic
125 variables such as precipitation and temperatureDraft (Marshall and Camp 2006; Kozak and Wiens
126 2010).
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128 Data extraction
129 Data on individual localities and their representative Desmognathus species were derived
130 from three primary sources. The first consisted of published studies of Desmognathus
131 communities or studies of individual species in which sympatric species were also listed. The
132 second source was unpublished data from extensive collecting by the authors; a few of these data
133 were supplemented by additional collection data for the same site in Auburn University Museum Fig. 1
134 (AUM) records. To ensure thorough coverage of the entire geographic range of the genus (Fig.
135 1), a third source was used. This consisted of collection databases from natural history museums
136 published on line through HerpNET (http://herpnet.org). The last source was restricted to single
137 species sites located outside the geographic boundaries of potential multi species communities.
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138 HerpNET was not used as a source for multi species data because there was no guarantee that all
139 of the species occurring at a given locality would be listed in the database. The total number of
140 sites used in the analyses was 235. Site locations, resident species (or lineage, sensu Kozak et al.
141 2005; Kozak and Wiens 2010), and source are listed in Appendix 1.
142 We derived climate data for each unique locality by downloading 19 climate variables for
143 precipitation and temperature (Table 2) that have been used commonly in niche modeling (e.g., Table 2 144 Broennimann et al. 2007; Wooten and Gibbs 2012) and available through WorldClim
145 (http://www.worldclim.org; Hijmans et al. 2005). We then conducted principal components
146 analysis (PCA) to reduce the large number of potentially correlated variables to a relative few,
147 uncorrelated axes of variance or principal components (PCs). We separately extracted data on
148 elevation for each locality using ArcGIS.Draft
149
150 Analysis
151 To answer our first question, does species richness within local Desmognathus
152 communities peak at intermediate elevations, we simply graphed species number against
153 elevation. To answer the second question, how does elevation relate to specific climatic
154 variables, we regressed each of the first three PCs against elevation and latitude using stepwise
155 regression. We included latitude because it is the primary determinant of climate, and separating
156 out its influence is important in determining the relative role of elevation.
157 To answer the third question, what is the relationship between local species richness and
158 climatic variables, we took several approaches. We first grouped communities based on the
159 number of species, regardless of which particular species were present. Because a minimum of
160 10 locality points are necessary for accurate niche modeling (Stockwell and Peterson 2002) and
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161 there were only five localities having six species, we group these with 5 species communities as
162 a category containing five or more species. We then used one way ANOVAs followed by
163 pairwise, post hoc analysis (Tukey’s) to test for differences in community size (1 species, 2
164 species, 3 species communities, etc.) for each of the first three climate PCs. If any PC indicated a
165 particularly strong relationship with community size, we determined both the minimum and
166 maximum value of the PC for each different community size, this time separating 5 from 6
167 species communities. We then regressed species number (following log transformation)
168 independently against each of those values. We performed this analysis to determine if there was
169 any indication of a possible minimum or maximum threshold climatological value for each
170 community.
171 Finally, to answer our fourth question,Draft is the relationship between species richness and
172 climate constrained by physiological limits, we determined unique community assemblages
173 using the evolutionary lineages identified by Kozak et al. (2005) and Kozak and Wiens (2010).
174 We used the maximum and minimum values of the climate PC identified above for each unique
175 assemblage, these data necessarily being restricted to assemblages for which there were multiple
176 replicates. We also determined the maximum and minimum PC values for all of the individual
177 lineages present in each assemblage. We predicted that if physiology of the individual
178 component species constrains community size, then there should be no significant difference
179 between the extreme climate PC value that will support the assemblage and the extreme value for
180 the most sensitive member of that assemblage. Therefore, we compared the minimum PC value
181 for the assemblage to the highest minimum value among the component species. We also
182 compared the maximum PC value for each assemblage to the lowest maximum value among its
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183 component species. We tested our prediction using a Wilcoxon signed rank test, which is a non
184 parametric, pair wise analysis.
185
186 Results
187
188 The first three PCs extracted by PCA accounted for over 90% of the variance in climate
189 variables (51.7%, 30.3%, and 8.6%, respectively). The most important contributors to PC1 were Table 3 190 measures of temperature and precipitation during wet periods (Table 3). The most important
191 elements of PC2 were precipitation and temperature during dry periods. The main drivers of PC3
192 were precipitation during the warmest quarter and diurnal temperature range. While PC1 was
193 significantly dependent on both latitudeDraft and elevation (total r2 = 0.919), more than 90% of the
194 variation was due to latitude alone (latitude component of r2 = 0.905). PC2 on the other hand was
195 dependent solely on elevation ( r2 = 0.743). The relationships between both PC1 and PC2 with
196 latitude and elevation, respectively, were negative (Fig. 2). PC3 was significantly though only Fig. 2
197 weakly influenced by elevation ( r2 = 0.054) and not at all by latitude.
198 The predicted distribution of each level of community size is shown in Fig. 3. The six Fig. 3
199 species localities occurred at intermediate elevations (Fig. 4). However, the pattern of the entire
200 data set appears asymptotic, and this interpretation is supported by polynomial regression Fig. 4 201 (second order), which estimates that a parabolic curve is the best statistical fit (r2 = 0.593).
202 ANOVA results indicated significant differences among communities for PC1 ( F = 5.229, P =
203 0.0005). Post hoc analysis revealed that 2 species communities differed from all others, but there
204 was no significant difference in any other pairing of community sizes. The analysis for PC2 was
205 also significant ( F = 79.027, P < 0.0001) with all community size pairings being significantly
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206 different except for the difference between 3 and 4 species communities. There was no
207 significant relationship between community size and PC3 (F = 1.542, P = 0.1910).
208 Because of the strength of the effect of PC2 on community species richness, we regressed
209 the minimum and maximum values for each community size against species number (n). There
210 was no significant relationship between minimum PC2 values and species N (F = 3.540, P =
211 0.1331). However, there was a strong linear relationship between maximum value and species N Fig. 5 212 (F = 81.801, P = 0.0008, r2 = 0.954; Fig. 5).
213 Fourteen unique species assemblages had multiple replications allowing for the analysis
214 comparing extreme (maximum and minimum) PC2 values and the extreme values for the most
215 sensitive species within the assemblage (Appendix 2). The results of the Wilcoxon signed rank
216 test comparing maximum PC2 value forDraft a unique assemblage and the lowest maximum PC2
217 value for the component species was significant ( Z = 2.073, P = 0.0382). So too was that
218 comparing minimum PC2 value for assemblage and the highest minimum value for the included
219 species ( Z = 2.934, P = 0.0033).
220
221 Discussion
222
223 Does species richness within local Desmognathus communities peak at intermediate
224 elevations?
225 Kozak and Wiens (2010) hypothesized that species richness peaks at intermediate
226 elevations because this is the site of the ancestral climate, and species are physiologically limited
227 to that climatic zone. In a later paper (Kozak and Wiens 2012) they demonstrated that climatic
228 regimes with the longest history of occupation, which correspond to mid elevations, have the
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229 highest level of plethodontid species richness even at the local level. They did not, however,
230 distinguish among groups of plethodontids that have radically different environmental
231 requirements. For example, all of the members of the genus Plethodon are completely terrestrial
232 whereas different species of Desmognathus occur along different points along the moisture
233 gradient that runs between stream and forest (Hairston 1986, 1987). Therefore, the specific
234 nature of the relationship between species richness and environmental variables in
235 Desmognathus may have been hidden by the all inclusive, familial analysis conducted by Kozak
236 and Wiens (2012).
237 The results of our analysis indicate that whether the number of Desmognathus species in
238 local assemblages peaks at intermediate elevations, i.e., whether it exhibits the pattern predicted
239 by the hypothesis, is equivocal. While allDraft of the six species localities occurred at intermediate
240 elevations (Fig. 4), the data best fit an asymptotic curve, suggesting that local Desmognathus
241 species richness continues to rise with elevation until it reaches a maximum. Local species
242 richness in many taxa is greatest at middle elevations (e.g., Colwell and Lees 2000; McCain
243 2004; Cardelús et al. 2006; Li et al. 2009), but the case for Desmognathus is rather weak.
244
245 How do specific climatic variables relate to elevation?
246 The results of the PCA of the climatic variables indicated that the two most important
247 factors (PC1 and PC2) each are strongly and negatively associated with latitude and elevation,
248 respectively. This comes as no surprise given that latitude and elevation are two primary
249 determinants of local climate. A major difference between PC1 and PC2 is that PC1 is driven
250 primarily by precipitation and temperature during wet periods while PC2, which is inversely
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251 related to elevation, predominately reflects climate variables during dry periods. PC2, therefore,
252 is more closely associated with potential aridity.
253
254 What is the relationship between local species richness and climatic variables?
255 Local communities must draw upon the larger regional pool of available species
256 (Harrison and Cornell 2008). Therefore, it is possible that high elevation areas of the
257 Appalachians are species rich simply because this is where most species of Desmognathus
258 happen to occur. This view would argue and that the relationship with PC2 is a correlative
259 artifact of differences in climate between the Appalachians and surrounding lowlands.
260 On the other hand, if that were the case, there would be no reason to expect the highly
261 linear relationship ( r2 = 0.954; Fig. 4) betweenDraft the maximum value of PC2 for each assemblage
262 size and the number of species present regardless of the particular species included. Such a
263 relationship suggests that species are potentially added in a stepwise manner with each climatic
264 threshold value. Concomitant absence of a significant relationship between the minimum value
265 of PC2 and species number is further evidence that aridity restricts the number of species of
266 Desmognathus that can co exist within a local community.
267 While it is apparent that larger communities do not exist above the climatic (below the
268 elevational) threshold, species addition is clearly not obligatory, and smaller communities exist
269 well below each elevational threshold value. This could be the result of a species pool effect
270 (Harrison and Cornell 2008), and the absence of the obligatory addition of species of
271 Desmognathus may be a reflection of a small regional species pool upon which to draw.
272
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273 Is the relationship between species richness and climate constrained by physiological
274 limits?
275 It is tempting to relate the limiting effect of PC2 on local richness in Desmognathus
276 species to their physiology. These salamanders are lungless and entirely dependent on wet,
277 permeable skins for gas exchange and are thus highly vulnerable to desiccation (Spotila and
278 Berman 1976), a physiological peculiarity that constrains normal activity such as foraging (Feder
279 and Londos 1984). Moreover, montane species of Desmognathus exhibit significant metabolic
280 depression at elevated temperatures (Bernardo and Spotila 2006). Therefore, precipitation and
281 temperature extremes during dry periods—expressed in PC2 in our analyses—place
282 physiological limits on the distributions of individual species. Kozak and Wiens (2010)
283 suggested that favorable climate restrictsDraft most species of Desmognathus to middle elevations
284 because they share similar physiological tolerances due to phylogenetic niche conservatism.
285 However, we found that all of the individual species within specific Desmognathus assemblages
286 can tolerate both higher maximum and lower minimum values of PC2 than the overall
287 assemblage itself.
288
289 Ecological limits to local species richness in Desmognathus
290 While physiological adaptation undoubtedly limits species to climates associated with
291 specific ranges of elevation, there is evidently an additional limiting factor or factors on the
292 number of species that can co exist within a local community of Desmognathus . This pattern is
293 consistent with communities being assembled first by environmental filtering of species with
294 appropriate physiological tolerances and second by the further limiting effects of biotic forces
295 such as competitive exclusion (Mayfield and Levine 2010). Desmognathus species include a
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296 wide range of ecomorphs ( sensu Kozak et al. 2005), ranging from large, fully or semi aquatic
297 forms to small, terrestrial ones. With relatively rare exceptions (e.g., Bruce 1991; Tilley 2000;
298 Camp et al. 2013), local communities do not contain more than one species characterized by a
299 given ecomorph. This suggests that assemblages of Desmognathus (Bruce 2011), like other
300 plethodontid communities (Adams 2007), are assembled in a manner influenced by biotic
301 interactions such as competition.
302 However, competitive interactions do not explain why some climatic zones support more
303 species than others. Our analyses lead us to believe that water and moisture predictability are a
304 primary factor. PC2 is the surrogate climatic variable that sets the minimum thresholds above
305 which more speciose Desmognathus communities can exist. This PC is influenced heavily by
306 minimum precipitation and maximum temperatureDraft during dry periods. Precipitation (water input)
307 and temperature (water output through evaporative effects) together control the amount of water
308 that lands and stays on the surface, respectively. Not only do these factors affect the physiology
309 and feeding ecology of lungless salamanders, they also influence the range of microhabitats
310 available for exploitation. Precipitation, which is obviously necessary to create streams and
311 streamside habitats, increases with increasing elevation in the southern Appalachians (Swift et al.
312 1988). Water then runs off of ridges and mountain tops and is received by lower slopes, where
313 seepages are more abundant (Hewlitt and Hibbert 1963) and soil moisture accumulates (Day and
314 Monk 1974). This combination of processes produces a longer moisture gradient and
315 consequentially a greater range of potential microhabitats—from wet forests and seepages to
316 large streams—at intermediate elevations. This explanation conforms to one of the major
317 hypotheses proffered to explain species richness patterns across taxa, i.e., habitat heterogeneity
318 (Kerr and Packer 1997; O’Brien et al. 2000; Rahbek and Graves 2000; Kerr et al. 2001).
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319 Kozak and Wiens (2010) hypothesized that Desmognathus species richness peaks at
320 intermediate elevations because most species are physiologically limited to that climatic zone.
321 We believe, however, that species richness in Desmognathus does not peak on mountain tops
322 because of the lack of available aquatic habitats for most species. Organ (1961) demonstrated
323 this pattern on Whitetop Mountain in the Balsam Mountains of Virginia. He ran vertical transects
324 to determine elevational ranges for Desmognathus species, following streams to their respective
325 headwaters. Local species richness peaked at different elevations at different sites on the same
326 mountain with presumably similar climates because of elevational variation in available habitat.
327 A short moisture gradient also explains low species richness at low elevations. The
328 absence of habitat heterogeneity at low elevations means that a number of species cannot exist
329 there. Those that can occupy low elevationDraft sites have a very similar niche and evidently exclude
330 each other.
331 As soil moisture increases with distance away from ridgelines, so do both leaf area and
332 above ground primary productivity (Bolstad et al. 2001). Increased primary production in turn
333 elevates detrital input into the local food chain, translating into a greater production of
334 invertebrate biomass (Seagle and Sturtevant 2005) and consequently a greater food source for
335 salamanders. This explanation conforms to another major hypothesis to explain richness patterns,
336 i.e., energy input (e.g., Currie 1991; Rohde 1999), which may also play a role in the number of
337 species. Whatever the ecological factor(s) involved, it is clear that species richness in local
338 Desmognathus communities is ecologically constrained by more than physiology and that
339 resources—whether food or available microhabitats or a combination of the two—enable the co
340 existence of multiple species.
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341 Rabosky (2009) argued that ecological factors limit species richness across regions and
342 across evolutionary clades. Among other things, Wiens (2011) criticized Rabosky’s (2009)
343 failure to describe the particulars of how ecological limits could actually work. Our analysis was
344 not meant to address species richness patterns across clades. It does, however, reveal apparent
345 ecological limits on species richness at the local level that could influence broader, regional
346 patterns of species richness. Certainly the climatic thresholds that prevent larger local
347 communities translate into large regions characterized by only one or very few species (Fig. 1).
348 Biotic interactions also undoubtedly play a role. Co existence between species versus their
349 exclusion depends on both differences in competitive ability and niche differences (Mayfield and
350 Levine 2010). Whereas species with different ecomorphs (and different niche requirements)
351 often co exist, one species—e.g., those Draftwith the D. ochrophaeus (Tilley and Mahoney 1996) or
352 D. fuscus (Tilley et al., 2008) ecomorph—with a similar respective niche and a similar respective
353 ecomorph (Jones, 1986; Tilley, 1997) but a greater competitive ability may exclude parapatric
354 neighbors from its entire geographic range.
355 We are aware that ecological conclusions regarding broad scale patterns of species
356 distributions should not be made without considering the biogeographic history of the
357 evolutionary clade in question (Wiens and Donoghue 2004). With that said, Kozak et al. (2005)
358 conducted an informative analysis of ecomorphological divergence within the Desmognathus .
359 They estimated that different ecomorphs and associated niches diverged as long ago as six
360 million years, thereby enabling the existence of multi species communities that have existed in
361 long term stasis. Therefore, we are confident that our conclusions regarding ecological factors
362 are not confounded by relatively recent biogeographical events.
363
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364 Conclusion
365 We tested the hypothesis that species richness in Desmognathus results from most species
366 being limited physiologically to the climatic zone located at intermediate elevations. We have
367 presented evidence that local species richness in Desmognathus is not limited by physiological
368 constraints but ecologically by climatic factors that affect habitat availability and possibly energy
369 input. Within climatic constraints, individual communities may be further limited by biotic
370 interactions among species.
371
372 Acknowledgements
373
374 We would like to thank the numerousDraft individuals whose collections over the years
375 enabled us to build the dataset upon which our analyses were based. We also thank J. Bernardo
376 and S. Tilley for answering questions regarding their collections and S. Tilley for his thoughtful
377 review of the manuscript.
378
379 References
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605
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611
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612 Fig. 1. Data points used in analyses of species richness organized by the number of species
613 documented at each locality (A = 1 species; B = 2 species; C = 3 species; D = 4 species;
614 and E = combined 5 and 6 species).
615
616 Fig. 2. Relationship between the two principal components of climatic variation and each of the
617 respective positional measures, (a) latitude and (b) elevation.
618
619 Fig. 3. Predicted distributions of each size Desmognathus community generated from
620 environmental niche modeling. Because of the small number of communities with six
621 species, these were combined with five species communities as a single category (A = 1
622 species; B = 2 species; C = 3 species;Draft D = 4 species; and E = combined 5 and 6 species).
623
624 Fig. 4. Relationship between local species richness in Desmognathus communities and elevation.
625
626 Fig. 5. Relationship between the maximum value of PC2 for each community size and the
627 number of species within the community.
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Table 1. Taxonomically recognized species of Desmognathus used in community analyses.
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Common Name Scientific Name
______
Cumberland Dusky Salamander Desmognathus abditus Anderson and Tilley
Seepage Salamander Desmognathus aeneus Brown and Bishop
Apalachicola Dusky Salamander Desmognathus apalachicolae Means and Karlin
Southern Dusky Salamander Desmognathus auriculatus (Holbrook)
Ouachita Dusky Salamander Desmognathus brimleyorum Stejneger
Carolina MountainDusky Salamander Desmognathus carolinensis Dunn
Spotted Dusky Salamander DraftDesmognathus conanti Rossman
Dwarf Black-bellied Salamander Desmognathus folkertsi Camp, Tilley, Austin, and
Marshall
Northern Dusky Salamander Desmognathus fuscus (Rafinesque)
Imitator Salamander Desmognathus imitator Dunn
Shovel-nosed Salamander Desmognathus marmoratus (Moore)
Seal Salamander Desmognathus monticola Dunn
Allegheny Mountain Dusky Salamander Desmognathus ochrophaeus Cope
Ocoee Salamander Desmognathus ocoee Nicholls
Blue Ridge Dusky Salamander Desmognathus orestes Tilley and Mahoney
Northern Pygmy Salamander Desmognathus organi Crespi, Browne, and Rissler
Black-bellied Salamander Desmognathus quadramaculatus (Holbrook)
Santeetlah Dusky Salamander Desmognathus santeetlah Tilley
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Black Mountain Salamander Desmognathus welteri Barbour
Pygmy Salamander Desmognathus wrighti King
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Table 2. Climate variables from WorldClim (http://www.worldclim.org) used in niche-model
construction and analyses of Desmognathus communities.
______
Variable Description
______
BIO1 Mean annual temperature
BIO2 Mean diurnal range of temperature
BIO3 Isothermality
BIO4 Temperature seasonality
BIO5 Maximum temperature during warmest period
BIO6 Minimum temperature duringDraft coldest period
BIO7 Annual temperature range
BIO8 Mean temperature during wettest quarter
BIO9 Mean temperature during driest quarter
BIO10 Mean temperature during warmest quarter
BIO11 Mean temperature during coldest quarter
BIO12 Annual precipitation
BIO13 Precipitation during wettest period
BIO14 Precipitation during driest period
BIO15 Standard deviation of weekly precipitation means
BIO16 Precipitation during wettest quarter
BIO17 Precipitation during driest quarter
BIO18 Precipitation during warmest quarter
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BIO19 Precipitation during driest quarter
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Table 3. Factor scores for first three principal components (PCs) from principal-component
analysis (PCA) of climate variables.
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Variable PC1 PC2 PC3
______
BIO1 0.794 0.589 0.075
BIO2 0.535 0.114 0.609
BIO3 0.931 0.126 0.057
BIO4 -0.938 -0.071 0.228
BIO5 0.548 0.747 0.293
BIO6 0.852 Draft 0.500 -0.031
BIO7 -0.872 -0.043 0.378
BIO8 -0.231 0.657 -0.514
BIO9 0.885 0.064 0.308
BIO10 0.642 0.708 0.194
BIO11 0.869 0.481 0.003
BIO12 0.701 -0.698 -0.026
BIO13 0.842 -0.422 -0.123
BIO14 0.367 -0.895 0.044
BIO15 0.266 0.778 -0.317
BIO16 0.847 -0.418 -0.179
BIO17 0.479 -0.854 0,035
BIO18 0.659 -0.311 -0.613
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BIO19 0.768 -0.560 0.236
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