Diversity and distribution of Odonata (Insecta) larvae along an altitudinal gradient in Coalcoman mountains, Michoacan, Mexico.
Presently, there are many taxonomic studies on larvae and imagoes of Mexican Odonata, but the ecological studies are relatively scarce, especially for short and long term evaluations on possible changes induced by human activities (e.g. climatic change). Additionally, ecological studies on richness and distribution at regional levels are few. It is well known that Odonata larvae are dependent on habitat characteristics (Watson et al. 1982), sensitive to abiotic factors, and play significant roles as predators and prey in the trophic structure of aquatic communities (Corbet 1999). They possess many desirable bioindicator qualities (Carle 1979, Samways 1993, Clark & Samways 1996, Moore 1997, McGeoch 1998, Corbet 1999, Chovanec & Waringer 2001, D'Amico et al. 2004), and many species have been used to study a variety of phenomena, such as tolerance to physicochemical factors (Carchini & Rota 1985, Ferreras-Romero 1988, Rodriguez 2003, Remsburg et al. 2008), accumulation of metals in larvae (Gupta 1995), effects of increased water temperature caused by nuclear reactors (Gentry et al. 1975, Thorp & Diggins 1982), direct sewage discharge to rivers (Watson et al. 1982), pesticide contamination (Takamura et al. 1991, Hurtado-Gonzalez et al. 2001), impact from cattle ranching on imago assemblages (Hornung & Rice 2003, Foote & Hornung 2005), relationships of assemblages with habitat characteristics (Castella 1987, Bulankova 1997), and larvae as indicators of water quality (Trevino 1997), total richness (Sahlen & Ekestubbe 2001), and riparian quality (Smith et al. 2007). Several studies also have focused on their application in diversity and conservation assessment (Hawking & New 2002, Clausnitzer 2003, Bried et al. 2007, Campbell & Novelo-Gutierrez 2007, Campbell et al. 2010).
The objective of this study was to assess the variation of diversity in Odonata larval assemblages along an elevation gradient and their relation with stream habitat variables by season and habitat. Local and landscape information on assemblage diversity may be useful in supporting conservation efforts and in following short and long term changes in their diversity in the Coalcoman Mountains.
MATERIALS AND METHODS
Study area: The Coalcoman Mountain Range (CM) in Michoacan, Mexico, is located between 18[degrees]] 35'40"-19[degrees]]00'31" N and 102[degrees]]27'47"-103[degrees]]40'36" W. The climate is predominantly tropical (annual average temperature 26.5[degrees]]C), with a rainy period occurring in summer, and average annual precipitation ranging from 700mm in the lowlands to 1 300mm in the highlands (Antaramian 2005). The CM is one of the least disturbed regions in Michoacan. The studied assemblages are located in streams within Hydrological Priority Region 26 (Rio Coalcoman and Rio Nexpa; Arriaga et al. 1998), and Terrestrial Priority Region 115 (Sierra de Coalcoman; Arriaga et al. 2000) in Michoacan State, Mexico. The sampled streams included Ticuiz (TZ), Estanzuela (EZ), Rio Pinolapa (RP), Colorin (CL) and Chichihua (CH). Details on water channels and averages of physicochemical data for the streams have been published by Novelo-Gutierrez & GomezAnaya (2009), and are summarized in Table 1.
Larval collection and physicochemical measures: Larval sampling was conducted twice per season during 2005, as follows: February 17-21(winter); March 29-April 2 and May 31-June 4 (spring); July 6-10 and August 17-21 (summer); September 28-October 2 and November 8-12 (autumm) and January 18-22 (2006, winter). Larvae were collected during one day per stream, along a 500m stream segment using a D-frame aquatic net (0.2mm mesh). A stratified random sampling design was applied for stream margins, riffles and pools. A total of 12 samples were taken each time (3 samples in riffles, 3 samples in pools and the remaining 6 samples along margins). All samples were preserved in 96% ethanol with a replacement before 24h had elapsed. Odonata larvae were separated from the other fauna and stream debris using a stereomicroscope, counted and identified to species. All specimens were deposited in the Instituto de Ecologia, A.C., Entomological Collection (IEXA). Physicochemical data (pH, temperature, dissolved oxygen, and conductivity) were recorded during each trip using a digital water analyzer (ICM Model 51500, Industrial Chemical Measurement, Hillsboro, Oregon, USA). Stream width, depth and current velocity were measured using a metric power tape and a digital flow meter (Global Water Flow Probe, Forestry Suppliers, Jackson, Mississippi, USA). At each point where we measured the stream's width, several measures of water depth and velocity were taken and averaged to calculate discharge as: width x average depth x average current velocity. Finally, gradient was calculated according to Resh et al. (1996).
For data analysis a one-way analysis of variance (ANOVA) was used to analyze the effect of stream on gradient, and a two-way multivariate analysis of variance (MANOVA) was applied to analyze the effect of stream and season on physicochemical variables. If significant effects were detected, we performed multiple comparisons using the Bonferroni t-test. All tests were performed using STATISTICA (StatSoft 2006).
Diversity indices: Richness and composition, Shannon Diversity Index (H'), Margalef's Richness Index (R), Simpson's Diversity Index as a dominance measure (D), and Pielou's Equitability (J) (Moreno 2001) were used to describe the assemblages. To compare the diversity of the streams, Renyi's profiles were generated (Tothmeresz 1995, 1998, Southwood & Henderson 2000, Jakab et al. 2002) because they include the logarithm of species number, H', D, and the logarithm of Berger-Parker diversity (Tothmeresz 1995). The profiles also have a scale parameter (a) such that when the value of the parameter is low, the method is extremely sensitive to the presence of rare species, but as the value of the parameter increases, the profile becomes less sensitive. As a large scale parameter, the method is sensitive only to the more frequent species. The result of this scale-dependent characterization of diversity can be presented in graphic form to visualize relationships among communities: the community's diversity profile'. If the curves of two diversity profiles intersect, then one of the communities is more diverse for rare species, while the other is more diverse for frequent species.
Gamma richness estimation: An estimation of the theoretical richness using nonparametric methods (presence/absence: Chao2, Jack2, Bootstrap; abundance: ACE, Chao1) was carried out using EstimatedS 8.0 (Colwell 2006). Additionally, parametric methods (richness estimators that use the observed species accumulation curve for modeling the addition of new species by extrapolation in relation to sampling effort) also were applied (Palmer 1990, Soberon & Llorente 1993), and included Clench's (Clench 1979) and Linear Dependence (von Bertalanffy 1938) models, as well as the slope of the cumulative species curve to assess the completeness of assemblages (Jimenez-Valverde & Hortal 2003, Hortal & Lobo 2005). Slopes were obtained by means of the first derivative of Clench's and Linear Dependence functions (Novelo-Gutierrez & Gomez-Anaya 2009).
Classification and ordination: Cluster Analysis (CA) on a Bray-Curtis (BC) similarity matrix with unpaired group mean average (UPGMA) amalgamation was used to explore faunal similarities among streams and seasons. This analysis was performed using PC-ORD v4.5 (McCune & Grace 2002). Additionally, a Canonical Correspondence Analysis (CCA) (CANOCO for Windows v4.5) was used to relate transformed species abundance [log(y+1)] to environmental variables (ter Braak 1986). The number of environmental variables was then reduced using the automatic forward selection option in CANOCO. Variables explaining most of the variation in the data were used to construct the final model. The statistical significance of the relationship between species and environmental variables was tested using a Monte Carlo permutation test (n = 499), with an F-ratio as the sum of all eigenvalues for the test statistic (ter Braak & Prentice 1988, ter Braak & Smilauer 2002).
Physicochemical variables: Streams had significantly different gradients (slopes) (one-way ANOVA: [F.sub.4, 30] = 10.17, p<0.01), and the Bonferroni paired t-test with multiple comparisons indicated that CL (Colorin) had the highest slope while RP (Pinolapa) and TZ (Ticuiz) had the lowest (Table 1).
There was a significant difference among streams (one-way MANOVA: Wilk's lambda = 0.46, [F.sub.16, 141] = 2.53, p<0.05) for width, depth, current velocity and discharge. The Bonferroni paired t-tests showed differences in depth and discharge for TZ with CH (Chichihua), EZ (Estanzuela) and RP. There was a significant difference in width between TZ and CL, while significant differences in current velocity were observed for TZ with EZ and RP.
A two-way MANOVA showed a significant effect of stream ([F.sub.16, 480.3] = 228.8, p<0.05), seasons ([F.sub.12, 415.7] = 182.2, p<0.05) and their interaction ([F.sub.48, 606.8] = 17.6, p<0.05) on physicochemical variables. A Bonferroni paired t-test showed significant differences (p<0.05) in temperature among streams, except that of RP to EZ and TZ. Sites CL and CH exhibited the lowest average temperatures, 20.14[degrees]]C and 22.62[degrees]]C, respectively, while the highest were those of TZ (29.35 [degrees]]C) and RP (28.03[degrees]]C). Most of the Bonferroni contrasts were significant for pH, except those between CH-EZ and CL-TZ, and all sampling sites had a basic pH. The Bonferroni contrasts for temperature among seasons showed significant differences between autumn-spring, autumn-summer and spring-summer. The average winter temperature was lower than that for the other seasons (Table 2). Most of the paired comparisons for conductivity showed significant differences among sites (p<0.05), except those between EZ and CH, and between RP and TZ. CL exhibited the lowest average value of all streams (50.08[micron]/cm). There was no significant difference in conductivity among seasons (p>0.05). The Bonferroni contrasts for oxygen showed significant differences between TZ and the other four streams, and between EZ and CL, while there was no difference between RP-CL, RP-EZ, or between CH-CL and EZ-RP. The average oxygen concentration of TZ was lowest (4.31ppm) compared to other sites. The contrasts indicated that the seasons are very different for oxygen concentration, except during spring-summer.
Assemblage composition: A total of 12 245 larvae from 75 species, 28 genera and 8 families were collected in 380 samples (Table 3). Numerically dominant species were Erpetogomphus elaps (24.8%), Macrothemis pseudimitans (12.2%) and Argia pulla (10.2%) (Fig. 1). Most species (76%) had a relative abundance lower than 1%. The number of species ranged from 18 (CL) to 36 (TZ), and the highest relative abundance was 37.77% (EZ), while the lowest was 6.15% (CL).
Diversity: H' for CM was 4.11, higher than any stream individually, and ranged from 1.85 (CL) to 3.31 (CH). CH and EZ had the highest site values (3.31 and 3.13, respectively), J ranged from 0.43 (TZ) to 0.67 (CH and EZ), D from 0.16 (EZ and CH) to 0.47 (CL), and R was highest in TZ (4.44), and lowest in CL (2.57) and EZ (2.84). According to Renyi's profiles, diversity at CH was the highest and that for CL the lowest. The order of diversity by stream was CH>EZ>RP>TZ>CL (Fig. 2).
Seasonal assemblages: In spring, 54 species were recorded (22 Zygoptera and 32 Anisoptera), with Argia pulla (27.9%) dominating, followed by Hetaerina capitalis (13.1%) and Erpetogomphus elaps (10%). During summer, 42 species were recorded (21 Zygoptera and 21 Anisoptera), and A. pulla (37.3%) was again dominant, followed by Argia oenea (8.9%) and E. elaps (5%). During autumn, 54 species were recorded (17 Zygoptera and 37 Anisoptera), and Macrothemis pseudimitans (22%), E. elaps (18.4%), and Phyllogomphoides apiculatus (12%) were dominant. During winter, 49 species were recorded (23 Zygoptera and 26 Anisoptera), E. elaps (45.9%) dominated, followed by Brechmorhoga praecox (9.6%), A. oenea (6.7%) and A. pulla (6.1%). Abundance was highest in autumn (47.14%), followed by winter (31.07%), spring (15.77%) and summer (6.03%). H' varied from 2.26 (winter) to 2.71 (autumn), J varied from 0.58 (winter) to 0.68 (summer) and autumn, R was higher in spring (7.01) and lower in winter (5.70). Renyi's diversity profiles showed that diversity declined from spring>summer>autumn>winter.
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Habitat assemblages: The observed number of species was highest along stream margins (59: 25 Zygoptera and 34 Anisoptera) and in riffles (50: 16 Zygoptera and 35 Anisoptera), and lowest in pools (23: 9 Zygoptera and 15 Anisoptera). Dominant species along stream margins were Erpetogomphus elaps (19.31%), followed by Argia pulla (12.39%) and Macrothemis pseudimitans (12.36%). In riffles, dominant species were E. elaps (37.70%), followed by Brechmorhoga praecox (16.59%) and Argia oenea (9.24%). Finally, dominant species in pools were E. elaps (63.37%), followed by Hetaerina capitalis (13.10%) and Phyllogomphoides luisi (11.23%). Abundance was similar along stream margins (48.01%) and riffles (46.36%), but was the poorest in pools (5.63%). Indexes R and J were higher along stream margins (6.98 and 0.72, respectively) than in riffles (5.93 and 0.60) or pools (3.57 and 0.59). H' was slightly higher along stream margins (2.98), followed by riffles (2.35) and pools (1.86). D was higher in pools (0.28) than in riffles (0.19) and stream margins (0.09). Renyi's profiles showed that diversity of stream margins was the highest followed by riffles and pools.
Non-parametric estimators of gamma richness: The estimates using Chao2, Jack2, Bootstrap and MaoTau were 103, 109.8, 84.5, and 76 species, respectively, yielding sampling efficiencies of 72.8%, 68.3%, 88.8% and 98.6%, respectively (Table 4). These estimators predicted 9 to 34 species were missing from the list for the CM. The upper MaoTau limit predicted 85.4 species (87.8% efficiency) with 10 potential additional species. However, the non-parametric richness estimators that used abundance data (Chao1, ACE) estimated 91.2 and 94.1 species, respectively, yielding 82.3% and 79.7% sampling efficiencies. These estimators predicted 16 and 19 potential additional species. The best local estimation of richness was made by Chao 1 (EZ, CH, RP) and by Bootstrap (CL, TZ) yielding higher sampling efficiencies.
Parametric models: The Clench function fits the data better for each stream and for the CM (Fig. 3, Table 5), with [R.sup.2] ranging from 95.13% (RP) to 99.71% (CH) among streams, and being 98.37% for the CM. The theoretical number of missing species ranged from 2 (EZ) to 13 (TZ) among streams, and 8 for the CM. Curve slopes ranged from 0.04 (EZ) to 0.26 (TZ) among streams, and 0.04 for the CM.
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Cluster analysis: Colorin (CL) separated first at a major distance (Fig. 4), followed by Ticuiz (TZ). The CL fauna was the poorest, where Hetaerina capitalis dominated (almost 75% of the total abundance), and with many (55.56%) rare species (species with relative abundance less than 1%). TZ was the stream with the largest number of observed species, most (80.56%) of which were rare. Overall turnover rate was less than 25%, except in EZ-RP (48%). Considering the seasonal assemblages, the cluster analysis shows the formation of two groups of contiguous seasons: the first one formed by spring+summer and the second one for autumn+winter. The first group had the assemblages with the highest number of species and abundance, where the dominant species were the zygopterans Argia pulla, H. capitalis and A. oenea; while in the second group the anisopterans Macrothemis pseudimitans and Erpetogomphus elaps were dominant.
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Species-environment relationships: The results of CCA were globally significant (trace = 2.66, F = 4.04, p = 0.002, Table 6). The first three axes accounted for most of the variability (75.3%) for physiochemical variables and species abundance (inertia = 19.60). The first canonical axis was statistically significant (eigenvalue = 0.945, F = 11.90, p = 0.002) and explained 35.5% of the variance, while the second and third axes explained 22.4% and 17.4%, respectively. The most important environmental variables explaining larval variation were determined from axis correlations, with gradient and elevation exerting the strongest influence on axes 1 and 2, and axis 1 also influenced by conductivity to yield three putative groups (Fig. 5).
As commonly occurs in Mexico, more Anisoptera (62.67%) were observed than Zygoptera (37.33%), and the Libellulidae and Coenagrionidae predominated (19 and 29 species, respectively) with the genus Argia having the most species (14) (Alonso-Eguia Lis 2004, Gomez-Anaya et al. 2000, Novelo-Gutierrez & Gonzalez-Soriano 1991, Novelo-Gutierrez et al. 2002, Bond et al. 2006). However, some variation in the proportion of Anisoptera to Zygoptera species was observed: while the number of observed Anisoptera species was similar to that for Zygoptera in CH, CL and EZ, in RP and TZ five and nine more Anisoptera species were recorded, respectively.
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The extreme differences in number of species presented by TZ and CL can be explained because TZ possesses a mixed lotic-lentic environment, is low in altitude, open and sunny, has floating water lilies, Eichhornia crassipes (Mart. Solms), and submerged (Egeria sp.) macrophytes, and is exposed to continuous human impact. Our results could be explained by the intermediate disturbance hypothesis (Connell 1978) which states that diversity is low after a disturbance, when only a few species have survived or few colonizing species dominate under the new environmental conditions. Diversity is high when disturbances occur at an intermediate frequency or with intermediate intensity. In this respect, frequent dragging in the TZ channel to extract gravel can be regarded as a disturbance since it alters the habitat. Furthermore, dragging generates medium sized lentic habitats which are mainly occupied by opportunistic libellulids such as Erythrodiplax, Erythemis, Miathyria, Micrathyria, Orthemis, and Perithemis, increasing TZ diversity.
CL, on the other hand, is located in a ravine at medium altitude, is small in size and almost fully covered by riparian vegetation, is a stream structured as successive terraces, and has negligible human impact. These results support other studies showing species richness to be positively correlated with stream size and canopy openness (Kinvig & Samways 2000, Clausnitzer 2003, Dijkstra & Lempert 2003, Campbell et al. 2010).
The number of species among streams, and their abundance and numeric dominance also exhibited temporal variation. In the dendrogram generated by the CA, abundance and number of species were highest in the spring+summer assemblage, and were dominated by the zygopterans Argia pulla, H. capitalis and A. oenea, while the autumn+winter group had the lowest number of species and abundance was dominated by the anisopterans Macrothemis pseudimitans and Erpetogomphus elaps. The alteration in larval dominance may be related to the presence or absence of predators, with dominance by large anisopterans when predatory fish are absent, and by smaller zygopterans when predatory fish are present (Mikolajewski & Johansson 2004). Large anisopteran larvae are more conspicuous to predators than smaller zygopterans.
Our ordering of diversity was based on Renyi's profiles (Tothmeresz 1995) which have been proposed as an efficient method for comparisons (Southwood & Henderson 2000), although infrequently used as such on the diversity of aquatic macroinvertebrate assemblages (e.g. Sipkay et al. 2007), and even less so for Odonata assemblages (e.g. Jakab et al. 2002). This lack of use may occur because this method involves more calculations than that for simple diversity indices (Tothmeresz 1995). The idea of ordering diversity was first proposed by Patil & Taillie (1977, 1979) and Solomon (1979). By adding a new dimension to the ecological approach of diversity, it connects with the implications of proposals for diversity conservation that focus on recognizing areas of high diversity. We found this tool useful in comparing the diversity of Odonata larval assemblages within the CM. Using this method, we have shown that diversity at CL was the lowest, and that for CH the highest, with the latter being an ecologically preserved area in the state of Michoacan. Among habitats, Renyi's profiles showed that the highest diversity occurred along stream margins, compared to riffles or pools, even when stream margins and riffles were almost equal in abundance, 4 044 and 3 905, respectively. Additionally, different dominant species were observed among habitats, with E. elaps mainly recorded from riffles and M. pseudimitans and A. pulla mainly from stream margins. Finally, Renyi's profiles showed a gradual decrease in seasonal diversity, spring>summer>autumn>winter, without intercrossing of profiles.
Beta diversity has been poorly evaluated for Mexican invertebrates (Soberon et al. 2005, Escobar 2005, Favila 2005, Noguez et al. 2005). Species turnover is the least studied and understood component of diversity, even though conservation efforts promote great interest in its evaluation (Gaston & Blackburn 2000). There is an inverse relationship between regional beta diversity and the species distributions in a region (Harrison et al. 1992). If the species from a given region have small areas of distribution, such that sites differ in species composition, then a high beta diversity results. However, if species are widely distributed over most of the region, then sites will be more similar to each other in species composition, resulting in low beta diversity (Arita & Leon-Paniagua 1993, Scott et al. 1999; see also Campbell et al. 2010). In our study, beta diversity was evaluated as the complement of BC, a key element in understanding the relationship between the diversity in the CM (regional or gamma diversity), and diversity of each stream at the local, or alpha level (Cornell & Lawton 1992, Ricklefs & Schluter 1993). Most species showed a restricted distribution in the CM, which suggests a high turnover rate, a conclusion supported by the fact that most of the Bray-Curtis paired similarities were smaller than 25%. Hence, beta diversity is an important component of gamma diversity among these sites (Novelo-Gutierrez & Gomez-Anaya 2009). Our results also support the betadiverse Mexico hypothesis (Arita & Leon-Paniagua 1993, Sarukhan et al. 1996), a result of high environmental heterogeneity in the CM. From the point of view of biological conservation, beta diversity is an important component that should be taken into account in the establishment of efficient conservation strategies of particular natural areas and/or species (Scott et al. 1999).
Considering that observed gamma diversity for the CM comes from sampling, we estimated the theoretical true gamma by using several non-parametric and parametric richness estimators. We used Clench's model because it has been used often and it better fits this kind of data. For the non-parametric estimators we used both incidence and abundance data, because there is no strong recommendation for a particular one. According to the sampling efficiency Chao1 performed better for EZ, CH and RP, while Bootstrap performed better for TZ, CL, and over all sampled sites. On the other hand, Clench's model better fit the data based on the coefficient of determination ([R.sup.2]), and we assessed the completeness of our Odonata larval lists using the slope of the curve at maximum effort for the extrapolation estimators provided by the first derivative of both the Clench and Linear Dependence functions. According to these values, the most complete lists were those with small slopes, where the increasing rate of species additions tended toward zero. These values agreed well with the fact that sampling effort was highest at EZ (n = 65) where the lowest slope was found to be associated with the highest sampling efficiency and just two missing species. On the other hand, the number of species collected at TZ yielded 73.22% efficiency and 12 potentially missing species. These observations agree with the fact that a negative and significant correlation between the number of species collected and slope was observed (r = -0.76, p<0.05), and also between slope and percentage efficiency (r = -0.90, p<0.05).
Our CCA results show that larval abundance is primarily associated with elevation and stream slope. This observation is consistent with Hofmann & Mason (2005) and Sato & Riddiford (2008) who observed that current velocity is one of the most important factors related to the distribution and abundance of Odonata. As gradient (slope) increases with elevation, so does current velocity, leading to reduced species richness. Several studies have revealed odonate species richness declines with increasing altitude (Borisov 1987, Samways 1989, Vick 1989, Campbell et al. 2010), and in some places few or no Odonata occur above 2000m (Laidlaw 1934). However, the size of a regional assemblage over a broad spatial area is a function of slope, latitude and altitude (Corbet 1999), as well as local factors such as stream morphology, aquatic vegetation, riparian coverage and physicochemical variables. The separation of CL first in Fig. 5 could be a result of such local differences. Among the sites surveyed, we found most species at 10m.a.s.l. (TZ), and the fewest at 1 050m.a.s.l. (CL). Campbell et al. (2010) calculated a Pearson correlation coefficient between elevation and species richness for all CM windward sites as r = -0.92 (p>0.05). Even though they revealed a decline with increasing elevation, the marginal insignificance of the correlation was due to the low number of sites surveyed (n = 3). Yet, despite the marginal insignificance, average taxonomic distinctness (a measure of phylogenetic diversity; e.g. Warwick & Clarke 1995, Clarke & Warwick 1998) was significantly and negatively correlated with observed species richness, suggesting the decline in species richness with elevation is real. It is known that altitude-related changes in species composition usually entail a progressive disappearance of the more abundant species at higher altitudes, although some taxa can have their centers of distribution at high and intermediate altitudes (Corbet 1999). In the CM we observed Hetaerina capitalis as the most common species at CL (1 050m, see Table 2), decreasing notably in larval abundance at CH (1 130m), while other species also present at CL such as Progomphus zonatus, Brechmorhoga tepeaca and Macrothemis ultima also decreased or disappeared in CH. Larvae from these four species were not found at lower elevations. We also observed that a higher number of species of Gomphidae (10 out of a total of 13), as well as most of the abundance of this family (more than 90%, but primarily from Erpetogomphus elaps) was recorded at intermediate altitudes, between 408m.a.s.l. and 560m.a.s.l. Notwithstanding, Erpetogomphus elaps was the most abundant and widespread species in the CM, its highest larval abundance occurred at 152m.a.s.l. On the other hand, Libellulidae were better represented with 22 species (from a total of 29) below 560m.a.s.l. Only 12 species from this family were recorded as larvae above 1 000m.a.s.l.; Brechmorhoga tepeaca, Dythemis multipunctata, Macrothemis ultima and Paltothemis cyanosoma were recorded exclusively above 1 000m.a.s.l. In contrast with Hoffmann (1991) who reported a predominance of species of Rhionaeschna (Aeshnidae) at higher elevations in the Peruvian Andes, this family was not well represented in the CM either in number of species or abundance. While most Coenagrionidae species were recorded at CH (11 out of a total of 19); two species, Argia cuprea and A. lacrimans, were exclusively recorded from 1 050m.a.s.l. (CL).
Finally, recommendations for the conservation of odonate diversity in the CM are based on the high beta diversity observed and on stream quality; as shown in the CCA analyses where it was possible to incorporate characteristics of local microhabitats. The conserved vegetation cover and the negligible human impact in CL are, for example, important factors to consider (Buchwald 1992, Remsburg et al. 2008). Alteration of plant cover could change the aquatic microclimate and lead to changes in Odonata diversity (e.g. Samways & Sharratt 2009, Campbell et al. 2010). The CL fauna, although minor in assemblage size, comprises a particular group of infrequent species: Argia cuprea, A. lacrimans, Aeshna williamsoniana and Paltothemis cyanosoma, all of which occurred uniquely in this locality. Other species such as Hetaerina capitalis, Erpetogomphus cophias, Progomphus zonatus, Brechmorhoga tepeaca and Macrothemis ultima have their maximum and almost exclusive records at this site. It is feasible that their association with stream slope may be based on associations with conserved canopy, small size, shallow runs, small to moderate sized pools and sand banks with rough grains. This opens some questions: What is the importance of the ravines like CL as shelters for these infrequent species in a broader scale (e.g. in all the Michoacan Mountain Ranges?) Are the odonate assemblages different in each ravine increasing the beta diversity? Our results support the suggestion for locally based conservation efforts along the windward transect (e.g. Campbell et al. 2010), and support proposals describing the CM as a biologically rich area for conservation.
Financial support was provided to RNG by Comision Nacional de Ciencia y Tecnologia (CONACyT) grant 43091-Q.
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Jose Antonio Gomez-Anaya (1), Rodolfo Novelo-Gutierrez (1), William Bruce Campbell (2)
(1.) Instituto de Ecologia, A.C., Carretera Antigua a Coatepec 351, El Haya, 91070, Xalapa, Veracruz, Mexico; firstname.lastname@example.org, email@example.com
(2.) Cardno ENTRIX, 701 University Avenue, Suite 200, Sacramento, California, 95825, USA; firstname.lastname@example.org
TABLE 1 Annual means and ranges (Min-Max) for the stream physicochemical variables Stream/variable TZ Elevation (m asl) 10 Depth (m) 0.21 Min-Max (0.13-0.38) Width (m) 4.5 Min-Max (0.4 -11) Velocity (m/s) 11.08 Min-Max (0.22 -32.7) Discharge 11.06 ([m.sup.3]/s) Min-Max (0.05-35.9) N 15 Temperature ([degrees]C) 29.35 CI 95% (28.42 -30.27) pH 7.47 CI 95% (7.35-7.6) Conductivity 640.5 ([micro]/cm) CI 95% (616.6-664.3) [O.sub.2] (ppm) 4.31 CI 95% (3.65-4.98) N 36 Gradient (slope) 1[degrees] 8' 44.75" Min 0[degrees] 27' 30.08" Max 2[degrees] 24' 18.03" N 7 Stream/variable EZ Elevation (m asl) 408 Depth (m) 0.1 Min-Max (0.07-0.16) Width (m) 1.67 Min-Max (0.25-2.35) Velocity (m/s) 0.49 Min-Max (0.22-1.23) Discharge 0.05 ([m.sup.3]/s) Min-Max (0.03 -0.08) N 6 Temperature ([degrees]C) 26.48 CI 95% (25.56 -27.4) pH 8.08 CI 95% (7.95-8.21) Conductivity 509.83 ([micro]/cm) CI 95% (485.9-533.7) [O.sub.2] (ppm) 7.53 CI 95% (6.87-8.2) N 36 Gradient (slope) 4[degrees] 44' 40.83" Min 1[degrees] 8' 44.75" Max 6[degrees] 37' 0.26" N 7 Stream/variable RP Elevation (m asl) 616 Depth (m) 0.11 Min-Max (0.04 -0.34) Width (m) 2.18 Min-Max (0.4-6.1) Velocity (m/s) 0.38 Min-Max (0.22-0.56) Discharge 0.09 ([m.sup.3]/s) Min-Max (0.01-0.46) N 8 Temperature ([degrees]C) 28.03 CI 95% (27.02-29.04) pH 8.47 CI 95% (8.33-8.61) Conductivity 666.83 ([micro]/cm) CI 95% (640.7-692.9) [O.sub.2] (ppm) 7.78 CI 95% (7.05-8.51) N 30 Gradient (slope) 1[degrees] 8' 44.75" Min 0[degrees] 20' 37.57" Max 2[degrees] 24' 18.03" N 7 Stream/variable CL Elevation (m asl) 1050 Depth (m) 0.14 Min-Max (0.04-0.27) Width (m) 1.85 Min-Max (0.45-4.27) Velocity (m/s) 6.57 Min-Max (0.22-26.1) Discharge 1.66 ([m.sup.3]/s) Min-Max (0.01-7.52) N 10 Temperature ([degrees]C) 20.14 CI 95% (19.29-21) pH 7.54 CI 95% (7.42-7.66) Conductivity 50.08 ([micro]/cm) CI 95% (28-72.2) [O.sub.2] (ppm) 8.37 CI 95% (7.75-8.98) N 42 Gradient (slope) 7[degrees] 48' 3.45" Min 1[degrees] 1' 52.37" Max 15[degrees] 19' 22.69" N 7 Stream/variable CH Elevation (m asl) 1130 Depth (m) 0.12 Min-Max (0.04-0.26) Width (m) 3.23 Min-Max (0.2-7.22) Velocity (m/s) 6.87 Min-Max (0.22-26.8) Discharge 2.4 ([m.sup.3]/s) Min-Max (0-11.5) N 15 Temperature ([degrees]C) 22.62 CI 95% (21.69-23.54) pH 8.16 CI 95% (8.04-8.29) Conductivity 460.89 ([micro]/cm) CI 95% (437-484.7) [O.sub.2] (ppm) 7.74 CI 95% (7.08-8.41) N 36 Gradient (slope) 1[degrees] 49' 58.22" Min 0[degrees] 48' 7.52" Max 4[degrees] 34' 26.12" N 7 CI = Confidence Interval, TZ = Ticuiz, EZ = Estanzuela, RP = Pinolapa, CL = Colorin, CH = Chichihua (modified from Novelo-Gutierrez & Gomez-Anaya 2009). TABLE 2 Means [+ or -] 95% confidence interval for physicochemical variables by stream and season (n = 12) Stream Season Temperature CI 95% pH CI 95% ([degrees]C) RP Winter 20.93 [+ or -]0.61 8.50 [+ or -]0.13 RP Autum 26.18 [+ or -]0.43 8.11 [+ or -]0.09 RP Spring 31.90 [+ or -]0.61 8.68 [+ or -]0.13 RP Summer 34.95 [+ or -]0.61 8.95 [+ or -]0.13 CH Winter 17.47 [+ or -]0.61 7.80 [+ or -]0.13 CH Autumn 22.77 [+ or -]0.43 8.16 [+ or -]0.09 CH Spring 23.43 [+ or -]0.44 8.14 [+ or -]0.09 CH Summer 25.85 [+ or -]0.61 8.58 [+ or -]0.13 CL Winter 16.55 [+ or -]0.61 7.00 [+ or -]0.13 CL Autumn 21.45 [+ or -]0.43 7.27 [+ or -]0.09 CL Spring 19.42 [+ or -]0.43 7.51 [+ or -]0.09 CL Summer 21.36 [+ or -]0.43 8.11 [+ or -]0.09 EZ Winter 21.37 [+ or -]0.61 7.70 [+ or -]0.13 EZ Autumn 26.73 [+ or -]0.43 7.96 [+ or -]0.09 EZ Spring 28.53 [+ or -]0.61 8.02 [+ or -]0.13 EZ Summer 27.76 [+ or -]0.43 8.42 [+ or -]0.09 TZ Winter 25.40 [+ or -]0.61 7.50 [+ or -]0.13 TZ Autumn 30.39 [+ or -]0.43 7.27 [+ or -]0.09 TZ Spring 30.22 [+ or -]0.61 7.47 [+ or -]0.13 TZ Summer 29.84 [+ or -]0.43 7.67 [+ or -]0.09 Stream Conductivity CI 95% Oxygen CI 95% ([micro]/cm) (ppm) RP 740.17 [+ or -]58.75 3.74 [+ or -]0.96 RP 567.83 [+ or -]41.54 8.68 [+ or -]0.68 RP 706.33 [+ or -]58.75 10.50 [+ or -]0.95 RP 752.00 [+ or -]58.74 7.28 [+ or -]0.95 CH 460.82 [+ or -]58.75 5.52 [+ or -]0.95 CH 440.83 [+ or -]41.54 10.07 [+ or -]0.68 CH 478.50 [+ or -]41.54 6.85 [+ or -]0.67 CH 465.83 [+ or -]58.75 7.10 [+ or -]0.95 CL 105.50 [+ or -]58.74 5.23 [+ or -]0.96 CL 31.31 [+ or -]41.54 9.26 [+ or -]0.67 CL 45.13 [+ or -]41.54 8.50 [+ or -]0.67 CL 46.10 [+ or -]41.54 8.91 [+ or -]0.67 EZ 462.13 [+ or -]58.75 3.72 [+ or -]0.96 EZ 520.83 [+ or -]41.54 9.03 [+ or -]0.68 EZ 520.83 [+ or -]58.75 7.67 [+ or -]0.95 EZ 517.17 [+ or -]41.54 7.88 [+ or -]0.68 TZ 689.83 [+ or -]58.75 2.60 [+ or -]0.95 TZ 577.42 [+ or -]41.54 7.71 [+ or -]0.67 TZ 661.67 [+ or -]58.75 3.75 [+ or -]0.95 TZ 668.25 [+ or -]41.54 2.06 [+ or -]0.67 TABLE 3 Richness and composition of five Odonata larval assemblages from the Coalcoman Mountains Species/sites Key EZ TZ RP Observed species richness 25 36 28 Total abundance 4693 2119 3277 ZYGOPTERA Calopterygidae Hetaerina americana (Fabricius, 1798) Heam 42 2 33 H. capitalis Selys, 1873 Heca - - - H. cruentata (Rambur, 1842) Hecr - - - H. occisa Hagen in Selys, 1853 Heoc 134 1 - H. titia (Drury, 1773) Heti - 6 - Lestidae Archilestes grandis (Rambur, 1842) Argr 2 - - Platystictidae Palaemnema domina Calvert, 1903 Pado 147 - 88 Protoneuridae Neoneura amelia Calvert, 1903 Neam - 2 - Protoneura cara Calvert, 1903 Prca - 2 1 Coenagrionidae Argia anceps Garrison, 1996 Aran - - - A. carlcooki Daigle, 1995 Arca 13 1 - A. cuprea (Hagen, 1861) Arcu - - - A. extranea (Hagen, 1861) Arex 1 - - A.funcki (Selys, 1854) Arfu - - 7 A. lacrimans (Hagen, 1861) Arla - - - A. oculata Hagen in Selys, 1865 Aroc 225 - 3 A. oenea Hagen in Selys, 1865 Aroe 189 2 138 A.pallens Calvert, 1902 Arpa 2 - 9 A.pulla Hagen in Selys, 1865 Arpu - 1192 12 A. tarascana Calvert, 1902 Arta - - - A. tezpi Calvert, 1902 Arte 1 1 137 A. ulmeca Calvert, 1902 Arul 11 - - Argia sp. Arsp 2 - - Enallagma novaehispaniae Calvert, 1907 Enno - 71 7 E. praevarum (Hagen, 1861) Enpr - - - E. semicirculare Selys, 1876 Ense - 15 3 Telebasis salva (Hagen, 1861) Tesa - 503 - Telebasis levis Garrison, 2009 Tele - 50 - ANISOPTERA Aeshnidae Aeshna williamsoniana Calvert, 1905 Aewi - - - Coryphaeschna apeora Paulson, 1994 Coap 2 C. adnexa (Hagen, 1861) Coad - 13 - C. viriditas Calvert, 1952 Covi - 1 - Rhionaeschna psilus (Calvert, 1947) Rhps - - - Remartinia luteipennis (Burmeister, 1839) Relu - 15 - Gomphidae Aphylla protracta (Hagen in Selys, 1859) Appr - 15 - Erpetogomphus bothrops Garrison, 1994 Erbo 2 - 1 E. cophias Selys, 1858 Erco - - 1 E. elaps Selys, 1858 Erel 1056 1 1645 Erpetogomphus sp. Ersp 3 - - Progomphus clendoni Calvert, 1905 Prcl 202 10 32 P. lambertoi Novelo, 2007 Prbo - - 93 P. marcelae Novelo, 2007 Erpy - - 134 P. zonatus Hagen in Selys, 1854 Przo - - - Phyllogomphoides sp. Phsp 676 - - Ph. pacificus (Selys, 1873) Phpa 105 3 19 Ph. luisi Gonzalez & Novelo, 1990 Phlu - - 220 Libellulidae Brechmorhoga praecox (Hagen, 1861) Brpr 353 - 464 B. nubecula (Rambur, 1842) Brnu 40 - - B. rapax Calvert, 1898 Brra 104 - - B. tepeaca Calvert, 1908 Brte - - - Dythemis multipunctata Kirby, 1894 Dymu - - - D. nigrescens Calvert, 1899 Dyni - 10 7 D. sterilis Hagen, 1861 Dyst - 7 1 Erythrodiplax basifusca (Calvert, 1895) Erba - - - E. fervida (Erichson, 1848) Erfe - 1 - Erythrodiplax sp. Erthsp - 8 7 Erythemisplebeja (Burmeister, 1839) Erpl - 57 - E. simplicicollis (Say, 1840) Ersi - 1 - Erythemis sp. Ersp 1 4 - Libellula croceipennis Selys, 1868 Licr - - - Micrathyria aequalis (Hagen, 1861) Miae - 34 - M. didyma (Selys in Sagra, 1857) Midy - 1 - Macrothemis inacuta Calvert, 1898 Main - - 7 M. inequiunguis Calvert, 1895 Main 57 - - M. pseudimitans Calvert, 1898 Maps 1308 - 172 M. ultima Gonzalez, 1992 Maul - - - Miathyria marcella (Selys in Sagra, 1857) Mima - 6 - Orthemis discolor (Burmeister, 1839) Ordi - - - O. ferruginea (Fabricius, 1775) Orfe - 21 - Paltothemis lineatipes Karsch, 1890 Pali - - 3 P. cyanosoma Garrison, 1982 Pacy - - - Pachydiplax longipennis (Burmeister, 1839) Palo 1 Perithemis domitia (Drury, 1773) Pedm - 54 7 Pseudoleon superbus (Hagen, 1861) Pssu 17 5 26 Tauriphila australis (Hagen, 1867) Taau - 1 - Species/sites CH CL TOTAL % Observed species richness 30 18 75 Total abundance 1403 753 12245 ZYGOPTERA Calopterygidae Hetaerina americana (Fabricius, 1798) 350 - 427 3.49 H. capitalis Selys, 1873 2 504 506 4.13 H. cruentata (Rambur, 1842) 34 1 35 0.29 H. occisa Hagen in Selys, 1853 - 7 142 1.16 H. titia (Drury, 1773) - - 6 0.05 Lestidae Archilestes grandis (Rambur, 1842) 5 9 16 0.13 Platystictidae Palaemnema domina Calvert, 1903 7 1 243 1.99 Protoneuridae Neoneura amelia Calvert, 1903 - - 2 0.02 Protoneura cara Calvert, 1903 - - 3 0.02 Coenagrionidae Argia anceps Garrison, 1996 21 - 21 0.17 A. carlcooki Daigle, 1995 - - 14 0.11 A. cuprea (Hagen, 1861) - 1 1 0.01 A. extranea (Hagen, 1861) - - 1 0.01 A.funcki (Selys, 1854) 4 - 11 0.09 A. lacrimans (Hagen, 1861) - 1 1 0.01 A. oculata Hagen in Selys, 1865 2 - 230 1.88 A. oenea Hagen in Selys, 1865 228 - 557 4.55 A.pallens Calvert, 1902 - - 11 0.09 A.pulla Hagen in Selys, 1865 44 - 1248 10.2 A. tarascana Calvert, 1902 100 - 100 0.82 A. tezpi Calvert, 1902 3 - 142 1.16 A. ulmeca Calvert, 1902 8 2 21 0.17 Argia sp. - 2 4 0.03 Enallagma novaehispaniae Calvert, 1907 - - 78 0.64 E. praevarum (Hagen, 1861) 67 - 67 0.55 E. semicirculare Selys, 1876 33 - 51 0.42 Telebasis salva (Hagen, 1861) 7 - 510 4.17 Telebasis levis Garrison, 2009 - - 50 0.41 ANISOPTERA Aeshnidae Aeshna williamsoniana Calvert, 1905 - 1 1 0.01 Coryphaeschna apeora Paulson, 1994 2 0.02 C. adnexa (Hagen, 1861) - - 13 0.11 C. viriditas Calvert, 1952 - - 1 0.01 Rhionaeschna psilus (Calvert, 1947) 2 - 2 0.02 Remartinia luteipennis (Burmeister, 1839) - - 15 0.12 Gomphidae Aphylla protracta (Hagen in Selys, 1859) - - 15 0.12 Erpetogomphus bothrops Garrison, 1994 - - 3 0.02 E. cophias Selys, 1858 - 18 19 0.16 E. elaps Selys, 1858 334 5 3041 24.8 Erpetogomphus sp. - - 3 0.02 Progomphus clendoni Calvert, 1905 12 - 256 2.09 P. lambertoi Novelo, 2007 24 - 117 0.96 P. marcelae Novelo, 2007 - - 134 1.09 P. zonatus Hagen in Selys, 1854 6 77 83 0.68 Phyllogomphoides sp. 33 - 709 5.79 Ph. pacificus (Selys, 1873) - - 127 1.04 Ph. luisi Gonzalez & Novelo, 1990 - - 220 1.8 Libellulidae Brechmorhoga praecox (Hagen, 1861) 19 1 837 6.84 B. nubecula (Rambur, 1842) - - 40 0.33 B. rapax Calvert, 1898 - 26 130 1.06 B. tepeaca Calvert, 1908 - 57 57 0.47 Dythemis multipunctata Kirby, 1894 1 - 1 0.01 D. nigrescens Calvert, 1899 9 - 26 0.21 D. sterilis Hagen, 1861 - - 8 0.07 Erythrodiplax basifusca (Calvert, 1895) 1 - 1 0.01 E. fervida (Erichson, 1848) - - 1 0.01 Erythrodiplax sp. - - 15 0.12 Erythemisplebeja (Burmeister, 1839) - - 57 0.47 E. simplicicollis (Say, 1840) - - 1 0.01 Erythemis sp. - - 5 0.04 Libellula croceipennis Selys, 1868 28 - 28 0.23 Micrathyria aequalis (Hagen, 1861) - - 34 0.28 M. didyma (Selys in Sagra, 1857) - - 1 0.01 Macrothemis inacuta Calvert, 1898 - - 7 0.06 M. inequiunguis Calvert, 1895 1 - 58 0.47 M. pseudimitans Calvert, 1898 17 - 1497 12.2 M. ultima Gonzalez, 1992 - 39 39 0.32 Miathyria marcella (Selys in Sagra, 1857) - - 6 0.05 Orthemis discolor (Burmeister, 1839) 1 - 1 0.01 O. ferruginea (Fabricius, 1775) - - 21 0.17 Paltothemis lineatipes Karsch, 1890 - - 3 0.02 P. cyanosoma Garrison, 1982 - 1 1 0.01 Pachydiplax longipennis (Burmeister, 1839) 1 0.01 Perithemis domitia (Drury, 1773) - - 61 0.5 Pseudoleon superbus (Hagen, 1861) - - 48 0.39 Tauriphila australis (Hagen, 1867) - - 1 0.01 Total and percentage of abundance per species are shown (key to sites in Table 1). TABLE 4 Non-parametric richness estimators for sampled streams in the Coalcoman Mountains, Michoacan, Mexico CL EZ TZ CH RP CM MaoTau 18 25 36 30 28 75 LL 13.39 20.17 27.81 27 21.34 66.58 UL 22.61 29.83 42.19 35 34.66 85.42 Singletons 6 3 10 3 3 14 Doubletons 3 4 4 5 2 5 Uniques 7 7 15 7 11 20 Duplicates 3 3 5 5 3 6 ACE 27.59 27.18 46.87 32.91 29.57 94.06 Efficiency 65.24 91.98 74.67 94.2 94.69 81.86 Chao 1 21.75 25.6 44 31.5 29 91.17 Efficiency 82.76 97.66 79.55 98.41 96.55 84.46 Chao 2 23.14 30.17 52.04 34.44 41.42 103.03 Efficiency 77.79 82.86 67.26 90.01 67.6 74.74 Jack 2 28.75 35.81 59.21 39.89 46.43 109.83 Efficiency 62.61 69.81 59.11 77.71 60.31 70.11 Bootstrap 20.94 28.01 41.27 34.46 32.43 84.46 Efficiency 85.96 89.25 84.81 89.96 86.34 91.17 LL and UL are the Lower and Upper limits of 95% confidence interval for Mao Tau (key to sites in Table 1). TABLE 5 Sites, number of species, parameters and predictions of two species accumulation models fitted for each odonate larval assemblage (key to sites in Table 1) Sites [S.sub.obs] Clench n a b a/b [R.sup.2] eff CM 75 248 2.50 0.03 82.62 98.37 93.19 CL 18 49 1.84 0.09 21.38 98.62 84.18 EZ 25 65 3.19 0.12 26.58 95.19 94.06 TZ 36 38 3.03 0.06 47.80 99.40 73.22 CH 31 54 2.98 0.08 37.99 99.71 81.59 RP 28 42 3.68 0.12 31.23 95.13 89.67 Sites Clench Linear Dependence sl a b a/b [R.sup.2] eff CM 0.04 1.69 0.02 70.48 93.68 109.30 CL 0.07 1.40 0.08 17.17 96.06 104.80 EZ 0.04 2.10 0.09 22.85 87.42 109.40 TZ 0.26 2.55 0.07 35.53 98.51 98.50 CH 0.11 2.28 0.08 30.41 98.49 101.90 RP 0.10 2.63 0.10 25.75 89.97 108.70 Sites Linear Dependence sl CM 0.01 CL 0.03 EZ 0.01 TZ 0.17 CH 0.04 RP 0.04 [S.sub.obs] = number of observed species, a = the slope to the beginning of sampling, b = a parameter related to the mode of accumulation of new species during sampling, a/b = asymptote, n = total number of samples, [R.sup.2] = coefficient of determination, eff = percentage of efficiency, and sl = slope. The slope was evaluated using the first derivative of Clench's function [a/[(1+b*n).sup.2]] and the first derivative of the Linear Dependence function [a * exp (-b * n)]. TABLE 6 Results of CCA of log-transformed larval abundance as a function of their environmental variables Axes Axis 1 Axis 2 Axis 3 Total inertia Eigenvalues 0.96 0.59 0.46 19.60 Species-environment 0.99 0.84 0.82 correlations Cumulative percentage variance of species data 4.80 7.90 10.20 of species-environment 35.50 57.90 75.30 relationship Sum of all eigenvalues 19.60 Sum of all canonical 2.66 eigenvalues Canonical correlation coefficients Year seasons -0.03 -0.21 0.17 Gradient 0.79 -0.39 -0.12 Elevation 0.68 0.52 0.16 Stratum -0.12 -0.08 -0.04 Temperature -0.14 -0.10 0.20 pH 0.03 0.06 0.16 Oxygen 0.14 0.02 0.16 Conductivity -0.43 0.13 0.03
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|Title Annotation:||texto en ingles|
|Author:||Gomez-Anaya, Jose Antonio; Novelo-Gutierrez, Rodolfo; Campbell, William Bruce|
|Publication:||Revista de Biologia Tropical|
|Date:||Dec 1, 2011|
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