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Phylogenetic distance in Great Salt Lake microbial communities


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ABSTRACT: Investigations of community composition often rely on metrics based on the abundance of taxonomic groups to estimate biodiversity. Although traditional measures of biodiversity, such as richness and evenness, can be used in a comparative fashion to evaluate differences among communities in both temporal and spatial contexts, these measures generally omit a phylogenetic perspective of the evolutionary diversity represented in a community. Using Fast UniFrac, we examined PhyloChip data from 9 microbial communities throughout the Great Salt Lake, Utah, USA, for changes in phylogenetic distance. We found a significant correlation (p < 0.001) between the decreased community phylogenetic distance and increased salt concentration. Despite significant differences in composition, communities in locations with a similar salt concentration had a similar phylogenetic distance. This trend was confirmed by analyzing the biodiversity of 89 published microbial communities classified as extreme (n = 20) and non-extreme (n = 69). Although we found no significant statistical difference in traditional diversity estimates, such as Chao1 and abundance-based coverage estimate (ACE), between environments, the phylogenetic distance within extreme communities is significantly lower than in non-extreme communities. A smaller phylogenetic distance within more extreme communities may imply evolutionary conservatism and specialization.
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Aquat Microb Ecol
Vol. 64: 267–273, 2011
doi: 10.3354/ame01527 Published online September 20
Biodiversity is often defined as the variability among
living organisms within ecological systems (Harper &
Hawksworth 1995, Magurran 2004) and is generally
calculated using traditional indices such as richness
and evenness. However, population geneticists have
developed methods that characterize the diversity of
populations or groups using phylogenetic or taxonomic
differences (Faith 1994, Clarke & Warwick 1998).
Novel diversity indices have been introduced that
reflect this variability by characterizing the related-
ness or distinctness of organisms within a community
(Nixon & Wheeler 1990, Vane-Wright et al. 1991, Faith
1992, Solow et al. 1993). In addition to being indepen-
dent of sample size (Price et al. 1999), the advantage of
utilizing phylogenetic distance as opposed to standard
diversity estimates in microbial communities is that the
functional contribution of a community may depend
less on species counts and more on the phylogenetic
diversity represented (our Fig. 1; Clarke & Warwick
1998). The introduction of these methods stems from
limitations of traditional diversity indices where each
organism is counted equivalently despite high phylo-
genetic divergence (Fig. 1). One potential result of neg -
lecting the phylogenetic difference between communi-
© Inter-Research 2011 ·*Email:
Phylogenetic distance in Great Salt Lake microbial
J. Jacob Parnell1,*, Giovanni Rompato1, Todd A. Crowl2,5, Bart C. Weimer3,
Michael E. Pfrender4
1Center for Integrated BioSystems and Department of Biology, and 2Department of Watershed Sciences and
Ecology Center, Utah State University, Logan, Utah 84322, USA
3School of Veterinary Medicine, Department of Population Health and Reproduction,
University of California at Davis, Davis, California 95616, USA
4Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana 46556, USA
5Present address: National Science Foundation, Division of Environmental Biology, Arlington, Virginia 22230, USA
ABSTRACT: Investigations of community composition often rely on metrics based on the abundance
of taxonomic groups to estimate biodiversity. Although traditional measures of biodiversity, such as
richness and evenness, can be used in a comparative fashion to evaluate differences among commu-
nities in both temporal and spatial contexts, these measures generally omit a phylogenetic perspec-
tive of the evolutionary diversity represented in a community. Using Fast UniFrac, we examined
PhyloChip data from 9 microbial communities throughout the Great Salt Lake, Utah, USA, for
changes in phylogenetic distance. We found a significant correlation (p < 0.001) between the
decreased community phylogenetic distance and increased salt concentration. Despite significant
differences in composition, communities in locations with a similar salt concentration had a similar
phylogenetic distance. This trend was confirmed by analyzing the biodiversity of 89 published micro-
bial communities classified as extreme (n = 20) and non-extreme (n = 69). Although we found no sig-
nificant statistical difference in traditional diversity estimates, such as Chao1 and abundance-based
coverage estimate (ACE), between environments, the phylogenetic distance within extreme commu-
nities is significantly lower than in non-extreme communities. A smaller phylogenetic distance within
more extreme communities may imply evolutionary conservatism and specialization.
KEY WORDS: Biodiversity · Hypersaline · Extremophile · Phylogenetic distance · Ecology
Resale or republication not permitted without written consent of the publisher
ties is that 2 communities may be considered equally
diverse when, in fact, one community is more phyloge-
netically and functionally diverse than the other (Mar-
tin 2002, Hamady et al. 2010). For example, consider
the representative communities in Fig. 1. All of the
communities have the same number of species, and, at
the highest taxonomic resolution (e.g. species or geno-
type), evenness is also identical. However, the ge-
netic and consequently functional difference be-
tween these 4 communities is quite distinct. This
problem becomes particularly troubling when using
biodiversity to infer community function. For example,
an over-abundance of closely related groups of species
that are functionally redundant (Faith 1994) can lead to
a disparity between traditional estimates and func-
tional diversity.
In a previous study, we examined the richness and
the taxonomic dispersion between the genus-to-
species ratio and the species-to-genotype-ratio (Par-
nell et al. 2009). We found a significant loss of geno-
typic diversity in extreme environments that had
experienced disturbances, and we hypothesized that
specialization in extreme environments drives the
maintenance of genotypic diversity. In the present
study we tested this hypothesis by analyzing the phy-
logenetic distance of 9 microbial communities in the
Great Salt Lake, Utah, USA, that differ widely in salin-
ity (Parnell et al. 2010). In addition, we examined 89
published community datasets wherein we asked
whether extreme environments (defined by the origi-
nal authors) harbor more closely related groups than
would be expected for non-specialized communities.
Case study. We used phylogenetic data from a previ-
ous study (Parnell et al. 2010) collected along a salinity
gradient, including additional sampling points from the
Great Salt Lake (GSL), Utah, USA (Fig. 2). One sample
was collected near freshwater inlets into the GSL in
Farmington Bay (FB; 41° 03’ 31.30’ N, 112°14’ 04.98’ W).
Three samples were collected from each of 2 sites
in the south arm of GSL: Sites A (41° 18’48.6’’N,
112° 40’ 59’ W) and B (41° 07’16.9’’N, 112° 33’ 03.5’ W);
these samples were taken at the surface (A and B
surface), within the water column (A and B column),
and and at the bottom (A and B bottom) near the sedi-
ments (ca. 3 m depth). Another surface sample was col-
lected near Antelope Island (AI; 41° 02’ 22.37’’N,
112° 16’ 42.33’’W). One sample was collected from
Aquat Microb Ecol 64: 267–273, 2011268
Fig. 1. Representative phylogenetic trees of microbial com-
munities. Despite the same values for richness in each, Com-
munity A will most likely have the greatest functional diver-
sity, and functional diversity will decrease (A > B > C > D) as
the phylogenetic relatedness increases (A < B < C < D). Figure
redrawn from Clarke & Warwick (2001)
Fig. 2. Sample site locations along a salinity gradient in the
Great Salt Lake, Utah, USA. Farmington Bay (FB) is the least
saline. South arm samples AI (near Antelope Island) and
the 6 samples taken from Sites A and B are from locations
with inter mediate salinity; the samples taken from Sites A and
B include depth samples. The north arm (NA) sample, col-
lected near Rozel Point, is near salt saturation. Black lines
indicate causeway structures
Parnell et al.: Phylogenetic distance in Great Salt Lake
the salt-saturated brine of the north arm (NA;
41° 25’ 56.13’’N, 112° 39’ 48.31’’W) of GSL near Rozel
Point. The least extreme environment was near the
freshwater inlet into the lake, where salt concentrations
are approximately twice that of marine environments.
The microbial community collected from the waters
of the southern arm of the lake inhabits an environ-
ment with an intermediate (~15%) salt concentration.
The north end of the lake, the site for collection of
the extremophilic hypersaline community, was at salt
Total DNA was extracted from the hypersaline
waters of the GSL as described by Griffiths et al. (2000)
using modified hexadecyltrimethylammonium bro-
mide (CTAB) extraction buffer (Zhou et al. 1996).
Bead-beating was used to lyse cells, and DNA was
extracted with chloroform (Griffiths et al. 2000). The
extracted community DNA was purified through a
Sephacryl®S-300 column (Parnell et al. 2010).
To assess microbial diversity we used the 16S Phylo-
genetic Array (PhyloChip) that contained probes for
8741 bacterial and archaeal taxa (Brodie et al. 2007).
Hybridization of the PhyloChip is achieved using
slightly modified Affymetrix protocols. The 16S rRNA
was amplified by PCR with Bacteria-specific primers
(8F: 5’-AGA GTT TGA TCC TGG CTC AG-3’; 1512R:
Archaea-specific primers (F: 5’-GAC GGG CGG TGT
ATC-3’) (Parnell et al. 2010). To minimize the primer
bias, PCR amplification was performed with a temper-
ature gradient from 48 to 58°C for the annealing tem-
perature. The PCR products from the different amplifi-
cation reactions were collected, purified (QIAquick,
Qiagen) and quantified. Fragmentation, labeling, and
hybridization were done as mentioned previously
(Parnell et al. 2010).
Presence/absence values were determined using
probe pair scores by Phylotrac analysis (www.phylo- Probe pairs scored as positive met 2 criteria:
(1) the intensity of fluorescence from the perfect match
probe has to be greater than 1.3 times the intensity
from the mismatch control; and (2) the difference in
intensity (perfect match – mismatch) has to be at least
500 times greater than the squared noise value (> 500
N2; see Brodie et al. 2006). Phylotrac data were im -
ported into Fast UniFrac (
fastunifrac) as per Hamady et al. (2010) for community
comparisons. Phylogenetic classifications of PhyloChip
data were weighted by class, order and family for sub-
sequent community comparisons (Clarke & Warwick
Meta analysis. Community biodiversity information
was obtained by downloading the 16S rRNA sequence
information of 89 randomly selected microbial commu-
nities (each containing between 100 and 726 se -
quences) from the ribosomal database project (http:// as mentioned previously (Parnell et
al. 2009). Microbial communities were from a wide
range of globally distributed environmental settings
amounting to over 18 000 total sequences (see Table S1
in the supplement at
a064p267_supp.pdf). After collecting microbial com-
munity datasets, we divided the datasets into 2 cate-
gories based on the environmental characteristics of
each community as originally defined by the authors
(Table 1). Briefly, datasets were categorized as ‘ex -
treme’ (n = 20) based on the description of the environ-
ments from which the community data were collected
(Table S1): environments with high pressure (i.e. deep
ocean), extreme temperatures, high salinity, low pH, or
environments that were contaminated with solvents;
communities with relatively normal environmental
parameters (n = 69) were termed ‘non-extreme’. The
average sample size for extreme and non-extreme
communities was not significantly different, minimiz-
ing sampling issues. We recognize the fact that ex -
treme and non-extreme environments are not discrete,
but rather a continuum, and omitted communities
whose category would be considered uncertain; some
extremophilic environmental details are in cluded in
Table 1.
Each microbial community was analyzed with
DOTUR (Schloss & Handelsman 2005) for biodiversity
using the Simpson index (Chazdon et al. 1998, Hughes
et al. 2001, Magurran 2004), the Shannon evenness
index (Magurran 2004), and the abundance-based
coverage estimate (ACE) (Chazdon et al. 1998, Hughes
et al. 2001, Magurran 2004).
Data on microbial biodiversity, including evenness,
richness and phylogenetic distance components, were
examined using descriptive and inductive analyses for
a difference in extreme environments. In order to
normalize residuals, Simpson index data were trans-
formed using the negative natural log (Rosenzweig
1995). Likewise, in order to compensate for hetero -
Non-extreme n Extreme n
Fresh water 6 Oligotrophic (BOD <1 ppm) 2
Marine water 11 Radiation (>50 µCi g–1) 1
Sediments 4 Low pH (<4.5) 2
Soils 26 Low temperature (< 5°C) 5
Microbiome 13 Contaminated 5
Waste treatment 9 Hypersaline (> 7%) 3
High pressure 2
69 20
Table 1. Summary of environmental conditions supporting
microbial communities (n = 89) analyzed in this study. BOD:
biological oxygen demand
Aquat Microb Ecol 64: 267–273, 2011
scedasticity and to normalize residuals, we used nat-
ural log-transformed ACE values. We compared the
variance within extreme and non-extreme communi-
ties using Student’s t-test for independent samples in
order to compensate for the different sample sizes. Sta-
tistical analyses and graphical output were performed
using JMP8 software (SAS).
The Simpson diversity index is a composite value
that captures both evenness and richness characteris-
tics of community assemblages (Magurran 2004) and is
a robust measure for statistical analyses. In addition,
the Simpson diversity index is relatively insensitive
to undersampling (Chao & Shen 2003). Evenness of
microbial communities was determined using the
Shannon evenness measure as described by Magurran
(2004). The ACE was calculated following Hughes et
al. (2001) and Magurran (2004). In addition to approxi-
mating richness using the ACE, we verified richness
patterns using the Chao1 estimate of richness as
described by Magurran (2004).
We used a quantitative measure of genetic diversity
similar to that using the branch length for the phylo -
genetic tree (Faith 1992, 1994). Specifically, the
genetic distance for each community was determined
by the average distance for all members within the
community calculated from distance matrix.
Case study
In order to determine how the degree of environ-
mental extremity affects phylogenetic distance, we
compared 9 microbial communities examined previ-
ously along a salinity gradient in the Great Salt Lake,
Utah, USA. In this case study, the phylogenetic dis-
tance was reached using a qualitative approach
(Clarke & Warwick 2001) due to the qualitative nature
of the phylogenetic data (Parnell et al. 2010). The
microbial community richness ranged from 1114 iden-
tified organisms (Archaea and Bacteria) at the lowest
salinity (FB; approximately 8% NaCl) to 145 organisms
at salt saturation (NA).
UniFrac clustering demonstrates the influence of
salt concentration on community composition (Fig. 3A);
this separation of communities was confirmed using
principal coordinate analysis (Fig. 3B). Despite signifi-
cant differences in individual communities within sim-
ilar salt concentrations (all south arm samples; inter-
mediate salt) using the Fast UniFrac p-test (corrected
p < 0.05 for all community comparisons except for
Abottom vs. Bsurface and Acolumn vs. Bbottom) and
the UniFrac significance test (corrected p < 0.05 for
community comparisons: Abottom vs. Bcolumn, Abot-
tom vs. Bsurface, Bbottom vs. Bsurface, and Bcolumn
vs. Bsurface), the phylogenetic distance within these
communities was similar. We found a significant corre-
lation (p < 0.001) between higher salinity environments
and lower phylogenetic distance (Fig. 4). Difference in
potential community function with respect to taxo-
nomic richness is illustrated in archaeal communities
throughout the salinity gradient. Archaeal communi-
ties in the south arm are represented by both Crenar-
Fig. 3. Statistical grouping of microbial communities from the
Great Salt Lake, Utah, USA, using Fast UniFrac. (A) Cluster
analysis, and (B) and principal coordinate analysis of micro-
bial communities in increasingly saline environments. The
sampling sites A and B are shown in Fig. 2. AI: Antelope Is-
land; FB: Farmington Bay; NA: North Arm. ‘column’ refers to
samples taken within the water column; ‘bottom’ refers to
samples taken near the sediments (ca. 3 m depth)
Fig. 4. Correlation between phylogenetic distance of micro-
bial communities and salt concentration of sampling sites
throughout the Great Salt Lake
chaeota and Eury archaeota with a large number of
methanogenic and halophilic groups, respectively. Al -
though the NA sample contained much more archaeal
richness than any other sample, all types were within
the family Halobacteriaceae (no members of the Cre-
narchaeota were detected), suggesting evolutionary
specialization to extreme conditions.
Meta analysis
The microbial communities from extreme environ-
ments (n = 20) had a mean richness estimate of 427 to
484 OTUs, depending on the index used (Chao-ACE).
Although this estimate appears to be lower than the
richness estimate for non-extreme environments (741
to 817), the variability between communities within the
same category is high, making this difference not sig-
nificant (Chao, p = 0.08; ACE, p = 0.12). Similarly, the
Simpson index (ln-transformed) appears lower in
extreme environments (4.58 vs. 5.21 in non-extreme
environments), but this difference is also not statisti-
cally significant (p > 0.05). Rarefaction curves of the
communities analyzed indicate that the sample size
effect is minimized, as shown previously (Parnell et al.
2009). It should be noted that this study does not con-
trol for the different PCR primers or conditions used in
individual cases.
Although traditional estimates did not show signifi-
cantly less community diversity in extreme environ-
ments, compared with non-extreme environments, the
phylogenetic distance is significantly lower (p = 0.03).
If specialists are significantly clustered phylogeneti-
cally, then the mean phylogenetic distance falls lower
than the null distribution (Silvertown et al. 2006). Com-
munity ecology studies have shown that resource limi-
tations scale positively with phylogenetic similarity
due to increased species packing (Tello & Stevens
2010). Similarly, in extreme environments, where other
limitations exist, the phylogenetic distance of these
communities suggests a higher tendency toward
closely related organisms (Fig. 5). The effect of harsh
environmental conditions on phylo genetic diversity
indicates that closely related species might have toler-
ances to similar environmental stressors and thus be
more likely to occur within the same community than
to occur with less-related species (e.g. Webb 2000).
Both extreme and non-extreme categories fit a
normal distribution (Fig. 5) of phylogenetic distance
among communities; however, the communities of ex -
treme environments appear to have some multi-modal-
ity. By subdividing the extreme categories into groups
of temperature, salinity, pH, and contamination, we
found that the communities near the mean consisted of
contaminated sediments, hypersaline and low-temper-
ature environments, and high-pressure (deep ocean)
sediments. The high phylogenetic divergence of these
communities may suggest a convergent adaptation to
extreme environments (Webb et al. 2002) that sev-
eral different phylogenetic groups have evolved differ-
ent mechanisms to overcome a similar stress. An exam-
ple of this convergent evolutionary strategy is seen in
the adaptation of halophilic organisms to life in high
salt concentrations, where at least 2 vastly different
Parnell et al.: Phylogenetic distance in Great Salt Lake 271
Fig. 5. Distribution of phylogenetic distance between microbial communities in (A) non-extreme and (B) extreme environments.
Shadow histograms show the distribution of communities (x-axis) with respect to phylogenetic distance (y-axis). The red line
indicates normal distribution; normal quantile plots illustrate how closely data follow normal distribution and suggest that com-
munities in both non-extreme and extreme environments follow a normal distribution. Box-plots illustrate that datasets from non-
extreme and extreme environments are not skewed and delineate the upper and lower quartiles, diamonds designate 95% confi-
dence intervals. Communities in extreme environments are colored as follows: oligotrophic = red; radiation = dark blue;
contaminated = green; hypersaline = orange; acidic = black; high pressure = yellow; low temperature = light blue
mechanisms are involved in regulating osmotic pres-
sure (Oren 2002). Low pH, high radiation, and
resource-limited (oligotrophic) environments corre-
spond to higher phylogenetic similarity. In previous
studies, this close grouping of phylogeny has sug-
gested that community organization (i.e. the role of
competition) can be deduced from the ecological simi-
larity within a closely related group (Webb 2000) and
implies habitat selection for ecologically similar, phylo-
genetically related species (Webb et al. 2002), result-
ing in a conserved trait within the pool of species in the
community. It is unclear whether the type of extreme
environment plays a role in the phylogenetic diver-
gence of the community.
Population ecology studies have shown that different
organisms make unequal contributions to diversity and
ecosystem function due to the amount of variability
within genetic or morphological characteristics (May
1990, Humphries et al. 1995, Crozier 1997, Norberg et
al. 2001, Allen et al. 2009). Phylogenetic distance (often
referred to as phylogenetic diversity or taxonomic di-
versity) measures the average phylogenetic distance
between individual organisms within a community and
has been successfully applied to microbial communi-
ties, demonstrating a potential to distinguish ecological
differences (Martin 2002). As an example, we show
that higher archaeal taxonomic richness (at the species
level) in the salt-saturated brine of GSL corresponds
with specialization rather than with high functional di-
versity. Communities in the south arm with lower rich-
ness have higher phylogenetic distance and greater
potential functional diversity.
Understanding microbial biodiversity and its rela-
tionship to ecosystem function is a central component
of microbial ecology and one of the key questions in
science (Huber et al. 2007). In order to address this
question we need novel metrics that can link biodiver-
sity with evolutionary history and community struc-
ture. Phylogenetic diversity is an important aspect of
measuring the total microbial biodiversity of an ecosys-
tem; in the case of the communities examined here,
phylogenetic distance is the only significantly different
measure between extreme and non-extreme microbial
biodiversity. Used in conjunction with traditional biodi-
versity estimates, phylogenetic diversity is a useful tool
for understanding how communities are structured.
The work described in the present study is obviously
restricted in its coverage and is limited by the datasets
examined. Due to the variable nature of the communi-
ties examined, a direct comparison of specific phyloge-
netic groups is not appropriate. However, phylogenetic
distance is a well established method of evaluating
ecological and evolutionary mechanisms that promote
species diversity and co-existence in community ecol-
ogy (Losos 1996, Webb et al. 2002). In the present
study, smaller phylogenetic distance within extreme
communities (rather than within non-extreme commu-
nities) implies evolutionary conservatism in the spe-
cialist group (Silvertown et al. 2006). In this light, a
phylogenetic perspective of studying microbial com-
munities provides a new approach to competition and
the maintenance of diversity.
Acknowledgements. Funding for this research was provided
by a National Science Foundation grant DEB-021212487 to
M.E.P., a grant from United States Department of Agriculture
CSREES 2006-34526-17001 and support from the Utah Agri-
cultural Experiment Station at Utah State University as jour-
nal paper number 8158. T.A.C. was partially supported while
serving at the National Science Foundation, Virginia, USA.
Any opinion, findings, and conclusions or recommendations
expressed in this document are those of the authors and do
not necessarily reflect the views of the National Science
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Editorial responsibility: Jed Fuhrman,
Los Angeles, California, USA
Submitted: February 7, 2011; Accepted: June 10, 2011
Proofs received from author(s): September 2, 2011
... The microbiology of Great Salt Lake has been studied since the late nineteenth century (Baxter 2018;Baxter and Zalar 2019), but systematic studies looking at microbial communities have occurred only in recent years (e.g., Weimer et al. 2009;Parnell et al. 2011;Almeida-Dalmet 2011). These data present a complex picture of life at the microbial level in this lake, even in the saltiest parts, including members of all three domains: Bacteria, Archaea, and Eukaryota (Baxter and Zalar 2019). ...
... Post was the first to really focus on cultivation in the north arm, where he isolated and described a number of halophilic bacteria and archaea (Post 1975(Post , 1977(Post , 1981. Later molecular studies suggest that the microbial communities in the north arm are composed predominantly of halophilic archaea with a minority contingent of bacteria Parnell et al. 2011;Tazi et al. 2014;Almeida-Dalmet et al. 2015). While we think of the north arm as rich in archaea, and this is likely true, one caveat of these molecular studies is that they are primarily based on 16S rRNA gene data and thus ignored eukaryotic community members. ...
... In general, the higher the salinity, the more archaeal genera are present relative to bacterial genera. These stable hypersaline north arm microorganisms also have a lower phylogenetic diversity relative to communities in the south arm (Parnell et al. , 2010(Parnell et al. , 2011Almeida-Dalmet et al. 2015). ...
The isolated north arm of Great Salt Lake, Utah, is a unique and complex environment with salinity at saturation, above 25% total salts. It is separated from the larger south arm, which experiences more freshwater input, due to a rock-filled causeway installed around 1960. Prior studies using both cultivation and molecular methods have shown that the microbial community of this part of the lake is diverse and dynamic, experiencing year-round fluctuations in salinity and temperature. The data emerging from our published studies and others have demonstrated the presence of microbial genera from all three domains of life, with the archaeal diversity being the greatest. When we cultivated approximately 50 isolates, the majority of these were genotyped as archaea, and only four cultivars belonged to the Domain bacteria. Thus, initial studies, reviewed herein, focused on understanding the diversity of the overrepresented archaea, using molecular, culture-independent methods to assess temporal diversity and significance of environmental parameters. Cultivation studies revealed details about how the stable members of the communities maintained their lifestyle using differential gene expression. But bacteria also live in this archaeal world, and they remain understudied in hypersaline systems. Therefore, we analyzed the bacterial isolates, genetically and biochemically, to reveal more information about the bacteria of the Great Salt Lake north arm. The genus Salinibacter was present throughout the year and mostly dominated the bacterial population. 16S rRNA gene sequencing of these bacterial cultivars demonstrated relationships to strains of Salinibacter, strains of Halomonas, and other uncultured deposited DNA sequences. To look at temporal diversity profiles of this bacterial minority, next-generation DNA sequencing (with semiconductor sequencing technology) was employed on DNA extracted from four water samples collected at different time points. The analysis showed that the majority of bacteria matched the genus Salinibacter, and the minority members of the microbial population were of the genera Anaeromyxobacter, Perexilibacter, Halomonas, Psychroflexus, Schlesneria, Pseudomonas, Roseovarius, Haliscomenobacter, and Vulgatibacter. Here, we discuss methods for microbial diversity studies in hypersaline aquatic systems and review the work on the microbial diversity of the north arm. We give an overview of the predominant halophilic archaea, but we present a broader picture by including new data on the underrepresented bacterial component of this fascinating community that manages a lifestyle at salt saturation.
... With Post's maps in hand, I began working on GSL microbiology with molecular training but little to no skill in microbial ecology. The dearth of work brought other Utah scientists to the table from Brigham Young University (Shen et al. 2012;Tazi et al. 2014), Weber State University (Shen et al. 2012), and Utah State University (Parnell et al. , 2010(Parnell et al. , 2011Weimer et al. 2009). We were building momentum, but it was clear that there was much work to do to understand the microbial foundation of this iconic ecosystem. ...
... Studies that utilize techniques that assess the DNA of an environment, though the SSU rRNA genes or from metagenomes, give a more complete depiction of the community members since these methods detect the species that are not culturable. From such studies, we know that the microbial communities in GSL are composed predominantly of halophilic archaea and bacteria (Almeida-Dalmet et al. 2015;Baxter et al. 2005;Meuser et al. 2013;Parnell et al. 2011;Tazi et al. 2014;Weimer et al. 2009). We now understand that assemblages of microorganisms must be dynamic, responding to the changes in salinity and temperature that accompany the seasons GSL experiences (Almeida-Dalmet et al. 2018). ...
... However, the hypersaline north arm microbial communities are more stable over time and not as impacted by changes in temperature and salinity (Almeida-Dalmet et al. 2015). These stable groups of microorganisms also have a lower phylogenetic diversity relative to communities in the south arm (Parnell et al. , 2010(Parnell et al. , 2011. Though we still do not know much about the specific roles of microorganisms in GSL, we are concerned about their role in the bioaccumulation and modification of heavy metal pollutants Wurtsbaugh et al. 2011), a particularly difficult problem to solve in a terminal lake. ...
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Over geologic time, the water in the Bonneville basin has risen and fallen, most dramatically as freshwater Lake Bonneville lost enormous volume 15,000–13,000 years ago and became the modern day Great Salt Lake. It is likely that paleo-humans lived along the shores of this body of water as it shrunk to the present margins, and native peoples inhabited the surrounding desert and wetlands in recent times. Nineteenth century Euro-American explorers and pioneers described the geology, geography, and flora and fauna of Great Salt Lake, but their work attracted white settlers to Utah, who changed the lake immeasurably. Human intervention in the 1950s created two large sub-ecosystems, bisected by a railroad causeway. The north arm approaches ten times the salinity of sea water, while the south arm salinity is a meager four times that of the oceans. Great Salt Lake was historically referred to as sterile, leading to the nickname “America’s Dead Sea.” However, the salty brine is teaming with life, even in the hypersaline north arm. In fact, scientists have known that this lake contains a diversity of microscopic lifeforms for more than 100 years. This essay will explore the stories of the people who observed and researched the salty microbiology of Great Salt Lake, whose discoveries demonstrated the presence of bacteria, archaea, algae, and protozoa that thrive in this lake. These scientists documented the lake’s microbiology as the lake changed, with input from human waste and the creation of impounded areas. Modern work on the microbiology of Great Salt Lake has added molecular approaches and illuminated the community structures in various regions, and fungi and viruses have now been described. The exploration of Great Salt Lake by scientists describing these tiny inhabitants of the brine illuminate the larger terminal lake with its many facets, anthropomorphic challenges, and ever-changing shorelines.
... microbial communities in GSL are composed predominantly of halophilic archaea and bacteria (Baxter et al., 2005;Weimer et al., 2009;Parnell et al., 2011;Meuser et al., 2013;Tazi et al., 2014;Almeida-Dalmet et al., 2015;Boogaerts, 2015). A search of "Great Salt Lake" in the GenBank database for deposited DNA sequences resulted in 862 hits for bacteria and 1230 hits for archaea (NLM, 2018). ...
... However, a temporal study of the hypersaline north arm microbiota demonstrated communities that are more stable over time and not as impacted by changes in temperature and salinity (Almeida-Dalmet et al., 2015). These stable hypersaline north arm microorganisms also have a lower phylogenetic diversity relative to communities in the south arm (Parnell et al., , 2010(Parnell et al., , 2011. ...
Great Salt Lake, Utah, is thalassohaline, terminal lake that currently occupies the Bonneville Basin, a depression in the larger Great Basin area of the western United States. Natural processes and climate conditions create a dynamic ecosystem with shifting salinity gradients and lake levels. Great Salt Lake has also been subjected to anthropomorphic impacts, perhaps most significantly, a railroad causeway that has created an isolated, hypersaline north arm. The lake’s enormous size, various microniches, salinity gradients, and unique geochemistry support a variety of life in its waters. Two invertebrates feed a diverse avian community, but the complexity of the ecosystem lies at the microbial level. Halophilic microbial extremophiles provide energy and nutrient turnover for the system. This review provides a biological inventory in the context of an ever-changing Great Salt Lake. The microbial diversity includes communities of bacteria, archaea, phytoplankton, protists, and fungi; the latter of which is framed with new data presented here. The biogeochemistry of microbialites is discussed as an example of complex microbial communities working together in the lake. Great Salt Lake is both a model for the limits of life on Earth and for potential life on other space bodies. The lake’s minerals (halite and gypsum) on the shores, in the sediment, and in the surrounding evaporite deposits have biopreservation abilities, protecting halophilic cells and their molecules in brine fluid inclusions. These observations suggest Great Salt Lake is an appropriate analogue for the study of ancient salt lakes and evaporites discovered on Mars.
... Network analysis includes extremely significant correlations (P < 0.01) and strong correlations (r > 0.6 or r < − 0.6). The 80% with the highest contribution rate of eukaryotic plankton OTUs and the 80% with the highest contribution rate of prokaryote OTUs were selected activities, is rich in biodiversity (Baxter 2018), and Balneola, Halobacteria, and Gammaproteobacteria are very abundant (Parnell et al. 2011;Meuser et al. 2013;Almeida-Dalmet et al. 2015). In our study, Gammaproteobacteria was common in all stations, and Balneola had a high relative abundance only in T6; Halobacteria was dominant only in D9. ...
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Microbial communities are important components of alpine lakes, especially in extreme environments such as salt lakes. However, few studies have examined the co-occurrence network of microbial communities and various environmental factors in the water of salt lakes on the Qinghai-Tibet Plateau. From May to June 2019, nine samples from seven salt lakes with water salinity ranges from 13 to 267‰ on the Qinghai-Tibet Plateau were collected. There were great differences between low-salinity samples and high-salinity samples in the inorganic salt ion concentration, pH, and biodiversity. In addition, the microbial community sturcture in low-salinity samples and high-salinity samples differed, suggesting that each sample has its own specific species. The co-occurrence network suggests that salinity was the most important forcing factor. We believe that salinity and inorganic salt ions can result in differences in microbial community in different salt lakes. This sequencing survey of multiple salt lakes with various salinities on the Qinghai-Tibet Plateau enhances our understanding of the response of microbial communities to environmental heterogeneity.
... The less saline south arm may be of interest ( Fig.16.1b) since it provides a future site for monitoring life in vacillating salinity, likely featuring changing communities as it becomes more saline over time. Prior molecular studies indicate that the microbial communities in the north arm of GSL are composed predominantly of halophilic archaea and to a lesser extent, bacteria Weimer et al. 2009;Parnell et al. 2011;Meuser et al. 2013;Tazi et al. 2014;Almeida-Dalmet et al. 2015;Boogaerts 2015;Perl 2019;Almeida-Dalmet and Baxter 2020). However, even in the hypersaline north arm, eukaryotic algae and fungi thrive (Baxter and Zalar 2019). ...
Great Salt Lake (GSL), Utah, is a thalassohaline terminal lake that currently occupies the Bonneville Basin, a depression in the larger Great Basin area of the western United States. Natural processes and climate conditions create a dynamic ecosystem with shifting salinity gradients and lake levels. The hypersaline north arm of GSL provides a model for exploring the limits of life on Earth and for potential life on other space bodies, especially the ancient closed-basin systems on Mars. The north arm water features hundreds of species of halophilic microorganisms with cellular strategies that allow them to live in hypersaline environments and high doses of ultraviolet light. These microbes also survive desiccation and can become entrapped in minerals as they are formed. The modern GSL evaporitic environment, generated by halite and gypsum precipitation events, illuminates the initial steps in preservation of biological material over geologic time. These minerals accumulate on the desiccated shores, in the sediment, and in the surrounding evaporite deposits and have been shown to have biopreservation abilities, protecting halophilic cells and their molecules inside brine fluid inclusions within the crystal structure. Entrapment allows in situ analyses of microbial diversity, which can be studied as a function of salt mineral assemblage. Globally across Mars these same types of evaporite precipitation events took place in closed-basin lake systems where surface waters have evaporated, leaving behind mineral vein structures composed of gypsum and other sulfate salts that have been modified or dissolved from later fluid shallow subsurface activity. We have chosen GSL as our analogue for Martian late Noachian/early Hesperian closed basin systems due to the overlapping evaporite mineralogy and fluid activity. Here we explore the transference of biological material and organics from hypersaline GSL brine to the minerals as they form in the water. We draw parallels to the evaporites extensively mapped on Mars, which likely formed in a similar way. These observations and insights, taken together, suggest GSL is an appropriate analogue for the study of ancient salt lakes and evaporites discovered on Mars, and what is more, the halophilic archaea that live in Earth’s salty lake may be good models for life elsewhere in our solar system.
... Seawater has an average salinity of~3.3%, whereas the Great Salt Lake ranges between 5% and 27% [7]. It has been reported that the Great Salt Lake is rich in halophilic and halotolerant microbial communities [7][8][9][10]. However, while there has been much success at discovering novel phylotypes, little is known about the Great Salt Lake's potential as a resource for small molecule discovery. ...
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Streptomyces sp. GSL-6B was isolated from sediment collected from the Great Salt Lake and investigation of its organic extract led to the isolation of three new linear heptapeptides, bonnevillamides A (1), B (2), and C (3). The bonnevillamides represent a new class of linear peptides featuring unprecedented non-proteinogenic amino acids. All three peptides contain the newly characterized bonnevillic acid moiety (3-(3,5-dichloro-4-methoxyphenyl)-2-hydroxyacrylic acid), as well as a heavily modified proline residue. Moreover, in bonnevillamide A, the terminal proline residue found in bonnevillamides B and C is replaced with 4-methyl-azetidine-2-carboxylic acid methyl ester. The structures of the three heptapeptides were elucidated by NMR, high-resolution electrospray ionization mass spectroscopy (HRESIMS), and LC-MS/MS, and the absolute configuration of all proteinogenic amino acid residues were determined by advanced Marfey's method. Bonnevillamides A, B and C were evaluated for their effects on zebrafish embryo development. All three heptapeptides were shown to modulate heart growth and cardiac function, with bonnevillamide B having the most pronounced effect.
Expansive evaporite mineral deposits and other geological features on Mars are evidence of ancient lacustrine systems before the planet experienced global climatic change (~3.5 Gya). On Mars, as the surface water dried up, hypersaline lakes would have filled the ancient lake basins. On Earth, the Bonneville Basin, in the western United States, tells a similar story in a more recent timeframe. Today, the bottom of this basin is the modern Great Salt Lake (GSL) and the Bonneville Salt Flats. The formation of GSL, in the Pleistocene to Holocene transition, followed climate change affecting the large inland sea, Lake Bonneville. Evaporation of this freshwater lake left large evaporitic mineral deposits that continually supply salt to modern GSL. Parts of the lake are at salt saturation due to shrinking shorelines and human intervention, and it is here that haloarchaea thrive, including inside the mineral deposits. The elevation of GSL is on a downward trajectory, and salinity is rising, leaving behind evaporite minerals as the water recedes. Halite and gypsum may contain fluid inclusions where microorganisms may be entombed over geologic time, managing dormancy in the low water activity of saturated brine. Haloarchaea are also resistant to other extremes such as high radiation doses, and they have lifestyle and metabolic flexibility. All of these things taken together make them excellent analogues for life that could have been in hypersaline lakes on Mars and may remain preserved in the evaporitic minerals there. The current Martian ultraviolet flux, magnetosphere, lack of tectonic activity, and desiccation suggest that continued life would be challenging, except microorganisms such as GSL haloarchaea may resist these extreme conditions, especially if entombed in minerals. Exploration with orbiters and rovers has located evaporites on Mars, and future missions should focus on these sites for detection of potential extant life or signs of extinct life.
Advanced molecular biology tools have unravelled the omnipresence of microbes in environments either in the form of cultivable or uncultivable fractions. However, research on microbial diversity in low biomass environments is still in its nascent stage. Microbial diversity of atypical environments has gained interest due to their adaptive features in extreme habitats, evolutionary and phylogenetic uniqueness, rich functional perspective and the presence of novel enzymes with biotechnological applications. Though culture-based techniques are still used for microbial diversity analysis, imitating the culture conditions of atypical environments is a great challenge. Thus, culture-independent techniques are applied in atypical microbial diversity analysis. Direct analysis of biological macromolecules such as nucleic acids, proteins and lipids from the atypical environments coupled with advanced techniques such as molecular fingerprinting, metagenomics, metaproteomics, metatranscriptomics and proteogenomics provide more insights into the structural and functional atypical microbial diversity. This chapter describes the advanced molecular biology tools that can be employed for microbial diversity analysis from atypical environments such as DNA fingerprinting techniques, microarray, next-generation sequencing, stable isotope probing, microautoradiography, isotope array and many others.
Many microorganisms are adapted to life at high-salt concentrations. Halophilic representatives are found in each of the three domains of life: Archaea, Bacteria, and Eukarya. Halophilic viruses exist as well. In NaCl-saturated brines such as found in the northern part of Great Salt Lake, Utah, in a few other natural salt lakes, and in saltern crystallizer ponds for the production of salt, we find members of all groups. Blooms of microorganisms have occasionally been observed in the magnesium- and calcium-rich waters of the Dead Sea. Dense communities of extremely halophilic Archaea (family Halobacteriaceae) and of the alga Dunaliella salina often impart a red color to salt-saturated brines. There are different strategies that enable halophilic or halotolerant microorganisms to grow in the presence of high-salt concentrations. A few groups (Archaea of the family Halobacteriaceae; the red extremely halophilic bacterium Salinibacter) maintain molar concentrations of salts (K+, Cl−) intracellularly, and their proteins are functional in a high-salt environment. Other groups (most salt-adapted members of the Bacteria, halophilic algae, and fungi) accumulate organic solutes to provide osmotic balance of their cytoplasm with the hypersaline medium.
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These three environmental hypotheses explain most variation in the species richness gradient of all bats, but do not account for all positive spatial autocorrelation at short distances. Although environmental predictors are highly redundant, energy and seasonality explain different and complementary fractions of variation in species richness of all bats. On the other hand, heterogeneity variables contribute little to explain this gradient. However, results change dramatically when richness is estimated for groups of species with different sizes of geographic distribution. First, the amount of variation explained by environment decreases with a decrease in range size; this suggests that richness gradients of small-ranged species can not be explained as easily as those of broadly distributed species, as has been implied by analyses that do not consider differences in range size among species. Second, the relative contribution of environmental predictors to explained variation also changes with change in range size. Seasonality and energy are good predictors of species with broad distributions, but they loose almost all explanatory power for richness of species with small ranges. In contrast, heterogeneity, which is a relatively poor predictor of richness of species with large ranges, becomes the main predictor of richness gradients of species with restricted distributions. This suggests that range size is a different dimension on which heterogeneity and other environmental characteristics are complementary to each other. Our results suggest that determinants of species richness gradients might be complex, or at least more complex than many studies have previously suggested.
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Ecologists have long been interested in the differences that exist among communities. If species adapted rapidly and without constraint, and if any lineage could occur in any community, then we would expect differences in community structure to be indicative of environmental differences. Because lineages differ in their evolutionary potential and are geographically restricted, however, comparisons of community structure must take account of communities' histories. Phylogenetic information about the constituent lineages in a community can allow lineage effects to be factored out, thus allowing an assessment of environmental determinants of community structure. In addition, phylogenetic information permits understanding of how communities have evolved through time and suggests hypotheses that may be tested using extant communities. Methodological difficulties with the application of these methods to community ecological issues are also discussed.
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A further biodiversity index is proposed, based on taxonomic (or phylogenetic) relatedness of species, namely the 'variation in taxonomic distinctness' (VarTD, Lambda (+)) between every pair of species recorded in a study. It complements the previously defined 'average taxonomic distinctness' (AvTD, Delta (+)), which is the mean path length through the taxonomic tree connecting every pair of species in the list. VarTD is simply the variance of these pairwise path lengths and reflects the unevenness of the taxonomic tree. For example, a species list in which there are several different orders represented only by a single species, but also some genera which are very species-rich, would give a high Lambda (+) by comparison with a list (of equivalent Delta (+)) in which all species tended to be from different families but the same order. VarTD is shown to have the same desirable sampling properties as AvTD, primarily a lack of dependence of its mean value on the sample size (except for unrealistically small samples). Such unbiasedness is of crucial importance in making valid biodiversity comparisons between studies at different locations or times, with differing or uncontrolled degrees of sampling effort, This feature is emphatically not shared by indices related to species richness and also not by properties of the phylogeny adapted from proposals in other, conservation contexts, such as 'average phylogenetic diversity' (AvPD, Phi (+)). As with AvTD, the VarTD statistic for any local study can be tested for 'departure from expectation', based on a master taxonomy for that region, by constructing a simulation distribution from random subsets of the master list. The idea can be extended to summarising the joint distribution of AvTD and VarTD, so that values from real data sets are compared with a fitted simulation 'envelope' in a 2 d (Delta (+), Lambda (+)) plot. The methodology is applied to 14 species lists of free-living marine nematodes, and related to a master list for UK waters. The combination of AvTD and VarTD picks out, in different ways, some degraded locations (low Delta (+), low to normal Lambda (+)) and the pristine island fauna of the Scillies (normal Delta (+), high Lambda (+)). The 2 indices are also demonstrated to be measuring effectively independent features of the taxonomic tree, at least for this faunal group (although it is shown theoretically that this will not always be the case). The combination of Delta (+) and Lambda (+) is therefore seen to provide a statistically robust summary of taxonomic (or phylogenetic) relatedness patterns within an assemblage, which has the potential to be applied to a wide range of historical data in the form of simple species lists.
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For biological community data (species‐by‐sample abundance matrices), Warwick & Clarke (1995) defined two biodiversity indices, capturing the structure not only of the distribution of abundances amongst species but also the taxonomic relatedness of the species in each sample. The first index, taxonomic diversity (δ), can be thought of as the average taxonomic ‘distance’ between any two organisms, chosen at random from the sample: this distance can be visualized simply as the length of the path connecting these two organisms, traced through (say) a Linnean or phylogenetic classification of the full set of species involved. The second index, taxonomic distinctness (δ * ), is the average path length between any two randomly chosen individuals, conditional on them being from different species. This is equivalent to dividing taxonomic diversity, δ, by the value it would take were there to be no taxonomic hierarchy (all species belonging to the same genus). δ * can therefore be seen as a measure of pure taxonomic relatedness, whereas δ mixes taxonomic relatedness with the evenness properties of the abundance distribution. This paper explores the statistical sampling properties of δ and δ * . Taxonomic diversity is seen to be a natural extension of a form of Simpson's index, incorporating taxonomic (or phylogenetic) information. Importantly for practical comparisons, both δ and δ * are shown not to be dependent, on average, on the degree of sampling effort involved in the data collection; this is in sharp contrast with those diversity measures that are strongly influenced by the number of observed species. The special case where the data consist only of presence/absence information is dealt with in detail: δ and δ * converge to the same statistic (δ ⁺ ), which is now defined as the average taxonomic path length between any two randomly chosen species. Its lack of dependence, in mean value, on sampling effort implies that δ ⁺ can be compared across studies with differing and uncontrolled degrees of sampling effort (subject to assumptions concerning comparable taxonomic accuracy). This may be of particular significance for historic (diffusely collected) species lists from different localities or regions, which at first sight may seem unamenable to valid diversity comparison of any sort. Furthermore, a randomization test is possible, to detect a difference in the taxonomic distinctness, for any observed set of species, from the ‘expected’δ ⁺ value derived from a master species list for the relevant group of organisms. The exact randomization procedure requires heavy computation, and an approximation is developed, by deriving an appropriate variance formula. This leads to a ‘confidence funnel’ against which distinctness values for any specific area, pollution condition, habitat type, etc., can be checked, and formally addresses the question of whether a putatively impacted locality has a ‘lower than expected’ taxonomic spread. The procedure is illustrated for the UK species list of free‐living marine nematodes and sets of samples from intertidal sites in two localities, the Exe estuary and the Firth of Clyde.
This book comprises eleven individually authored papers on various aspects of the measurement and estimation of biodiversity: conceptual aspects of the quantification of the extent of biological diversity; biodiversity at the molecular level - the domains, kingdoms and phyla of life; the quantification of plant diversity through time; phylogenetic pattern and the quantification of organismal biodiversity; biodiversity at the molecular genetic level - experiences from disparate macroorganisms; theoretical and practical aspects of the quantification of biodiversity among organisms; selecting indicator taxa for the quantitative assessment of biodiversity; the quantification of biodiversity - an esoteric quest or a vital component of sustainable dvelopment?; a comparison of the efficacy of higher taxa and species numbers in the assessment of the biodiversity in the neotropics; estimating terrestrial biodiversity through extrapolation; and practical approaches to the estimation of the extent of biodiversity in speciose groups. All chapters are abstracted separately. -S.R.Harris
Practical approaches to measuring biodiversity are reviewed in relation to the present debate on systematic approaches to conservation, to fulfil the goal of representativeness: to identify and include the broadest possible sample of components that make up the biota of a given region. Rather than adapting earlier measures that had been developed for other purposes, the most recent measures result from a fresh look at what exactly is of value to conservationists. Although debate will continue as to where precisely these values lie, more of the discussion has been devoted to ways of estimating values in the absence of ideal information. We discuss the current principles by assuming that the currency of biodiversity is characters, that models of character distribution among organisms are required for comparisons of character diversity, and that character diversity measures can be calculated using taxonomic and environmental surrogates. Full text at:
Biodiversity plays a vital role for ecosystem functioning in a changing environment. Yet theoretical approaches that incorporate diversity into classical ecosystem theory do not provide a general dynamic theory based on mechanistic principles. In this paper, we suggest that approaches developed for quantitative genetics can be extended to ecosystem functioning by modeling the means and variances of phenotypes within a group of species. We present a framework that suggests that phenotypic variance within functional groups is linearly related to their ability to respond to environmental changes. As a result, the long-term productivity for a group of species with high phenotypic variance may be higher than for the best single species, even though high phenotypic variance decreases productivity in the short term, because suboptimal species are present. In addition, we find that in the case of accelerating environmental change, species succession in a changing environment may become discontinuous. Our work suggests that this phenomenon is related to diversity as well as to the environmental disturbance regime, both of which are affected by anthropogenic activities. By introducing new techniques for modeling the aggregate behavior of groups of species, the present approach may provide a new avenue for ecosystem analysis.
▪ Abstract A variety of phylogenetic measures have been proposed to quantify distinctiveness, often held to mark species of high conservation worth. However, distinctiveness of species and their numbers have different implications for conservation policy, depending on whether moral, esthetic, or utilitarian reasons are accepted as justifying conservation. The utilitarian position values species according to increasing numbers, and as they are more, as opposed to less, distinctive. The view is taken that conservation should seek to maximize the preserved information of the planet's biota, best expressed in terms of genetic information held in genes and not in portions of the genome of uncertain or no function. Gene number is thus an important component of assessing conservation value. Phylogenetic measures are better indicators of conservation worth than species richness, and measures using branch-lengths are better than procedures relying solely on topology. Distance measures estimating the differences be...
Key Words community assembly and organization, phylogenetic conservatism, biogeography, species diversity, niche differentiation s Abstract As better phylogenetic hypotheses become available for many groups of organisms, studies in community ecology can be informed by knowledge of the evo-lutionary relationships among coexisting species. We note three primary approaches to integrating phylogenetic information into studies of community organization: 1. examining the phylogenetic structure of community assemblages, 2. exploring the phylogenetic basis of community niche structure, and 3. adding a community context to studies of trait evolution and biogeography. We recognize a common pattern of phy-logenetic conservatism in ecological character and highlight the challenges of using phylogenies of partial lineages. We also review phylogenetic approaches to three emer-gent properties of communities: species diversity, relative abundance distributions, and range sizes. Methodological advances in phylogenetic supertree construction, charac-ter reconstruction, null models for community assembly and character evolution, and metrics of community phylogenetic structure underlie the recent progress in these ar-eas. We highlight the potential for community ecologists to benefit from phylogenetic knowledge and suggest several avenues for future research.