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\begin{document}

\title{Insights into Ecological \& Evolutionary Processes via Community
Metabarcoding}



\author[1]{Rosemary Gillespie}%
\author[2]{Holly Bik}%
\author[3]{Michael Hickerson}%
\author[4]{Henrik Krehenwinkel}%
\author[5]{Isaac Overcast}%
\author[6]{Andrew Rominger}%
\affil[1]{University of California Berkeley}%
\affil[2]{University of Georgia}%
\affil[3]{City College of New York}%
\affil[4]{Universität Trier}%
\affil[5]{University of Maine System}%
\affil[6]{University of Maine}%


\vspace{-1em}



  
  \date{June 18, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
The Special Issue brought together papers that highlighted the power of
high-throughput sequencing (HTS) data to address classic questions in
ecology and evolution, and/or use models/theory to infer key ecological
and evolutionary processes, and make predictions, particularly focused
on metabarcoding (amplicon) datasets in conjunction with complementary
-omics data types. We highlight key papers that show the power of the
new technology to address questions related to: (1) community assembly,
and the interplay between competition, environmental filtering, and
neutral processes, that can be inferred from the data, and how these
change according to environmental conditions, and across successional
and extended evolutionary time. (2) Interaction networks, and how these
can show predictable changes over similar spatial and temporal
gradients, providing insights into questions of biotic resilience.
Studies also examined (3) cross scale interactions and those involving
hosts and their microbiomes, with the critical development being the
ease of comparison and integration across scales of organismic
complexity, allowing insights at one scale to inform the other. The
approach is also amenable to (4) studies of invasive species and biotic
homogenization, providing insights of shifts in alpha and beta diversity
across a wide range of spatial scales.%
\end{abstract}%



\sloppy


\textbf{Insights into Ecological \& Evolutionary Processes via Community
Metabarcoding} :

Rosemary G. Gillespie\textsuperscript{1}, Holly M.
Bik\textsuperscript{2}, Michael J. Hickerson\textsuperscript{3}, Henrik
Krehenwinkel\textsuperscript{4}, Isaac Overcast\textsuperscript{5},
Andrew J Rominger\textsuperscript{6}

\textsuperscript{1} Department of Environmental Science, Policy, and
Management, University of California, Berkeley, CA, USA

\textsuperscript{2} Department of Marine Sciences and Institute of
Bioinformatics, University of Georgia, Athens, GA, USA

\textsuperscript{3} Graduate Center of the City University of New York,
New York, New York, USA

\textsuperscript{4} Department of Biogeography, Trier University, Trier,
Germany

\textsuperscript{5} School of Biology and Ecology, University of Maine,
Orono, ME, USA; Department of Vertebrate Zoology, American Museum of
Natural History, New York, New York, USA

\textsuperscript{6} School of Biology and Ecology, University of Maine,
Orono, ME, USA

Rosemary G Gillespie\emph{gillespie@berkeley.edu}ORCID:
0000-0003-0086-7424

Holly M Bik \emph{hbik@uga.edu} ORCID: 0000-0002-4356-3837

Michael J Hickerson\emph{mhickerson@}ccny.cuny.edu ORCID:
0000-0002-5802-406X

Henrik Krehenwinkel\emph{krehenwinkel@uni-trier.de}ORCID:
0000-0001-5069-8601

Isaac Overcast\emph{isaac.overcast@maine.edu}ORCID: 0000-0001-8614-6892

Andrew J Rominger\emph{andrew.rominger@maine.edu}ORCID:
0000-0003-3755-4480

\textbf{Abstract} :

The Special Issue brought together papers that highlighted the power of
high-throughput sequencing (HTS) data to address classic questions in
ecology and evolution, and/or use models/theory to infer key ecological
and evolutionary processes, and make predictions, particularly focused
on metabarcoding (amplicon) datasets in conjunction with complementary
-omics data types. We highlight key papers that show the power of the
new technology to address questions related to: (1) community assembly,
and the interplay between competition, environmental filtering, and
neutral processes, that can be inferred from the data, and how these
change according to environmental conditions, and across successional
and extended evolutionary time. (2) Interaction networks, and how these
can show predictable changes over similar spatial and temporal
gradients, providing insights into questions of biotic resilience.
Studies also examined (3) cross scale interactions and those involving
hosts and their microbiomes, with the critical development being the
ease of comparison and integration across scales of organismic
complexity, allowing insights at one scale to inform the other. The
approach is also amenable to (4) studies of invasive species and biotic
homogenization, providing insights of shifts in alpha and beta diversity
across a wide range of spatial scales.

\textbf{Introduction} :

Biodiversity - the multiplicity of life, from microbes to
macro-organisms and from genes to ecosystems, is in crisis, yet we have
little understanding of factors that can sustain biodiversity and
enhance resilience to perturbations. Key questions that remain include
the interplay between niche and neutral processes in shaping the
assembly of communities (Mittelbach \& McGill, 2019) and the associated
role of stochastic and deterministic processes governing assembly
(Men\selectlanguage{ngerman}éndez\selectlanguage{english}-Serra, Ontiveros, Caliz, Alonso, \& Casamayor, 2023); the
complexity-stability paradox (Dominguez-Garcia, Dakos, \& Kefi, 2019);
metacommunity dynamics and the connection between local and regional
diversity (Thompson et al., 2020); and the extent to which a given
community can exist in equilibrium or steady state (Qian \& Akcay, 2020)
and concepts of alternative stable states (Van Nes et al., 2016), among
others. These questions have been the focus of much theoretical
development over the past, but the ability to generate the data needed
to validate the theory has been confounded by the difficulty of sampling
biological communities at the needed scale. However, without answers to
these fundamental questions, we are left with major gaps in our
understanding of biodiversity dynamics and questions of biotic
resilience, the use of indicator or surrogate species, ecosystem
sustainability, and strategies for restoration, which are all so
critical for effective conservation and management of ecosystems.

The advance of molecular profiling methods (e.g. metabarcoding, 16S/ITS
community profiling, metagenome reconstruction) has recently provided a
remarkably effective tool for measuring biodiversity, and presenting the
opportunity to answer these outstanding questions. Moreover, because the
approach affords a common tool across both macro- and micro-organisms,
we have the ability to answer macroecological questions of shifts in
community composition across scales (e.g., (Brown, Mihaljevic, Des
Marteaux, \& Hr\selectlanguage{polish}č\selectlanguage{english}ek, 2020)). The technology has initiated a dramatic
shift in the ability to measure ecological metrics within entire macro-
and micro-organismal communities, and how they change over space and
time; it also allows comparison of the same data across scales of
organismic complexity. In this Special Issue, authors use high
throughput technologies to \textbf{address classic questions in ecology
and evolution, and/or use models/theory to infer key ecological and
evolutionary processes, and make predictions.}

Highlighting the promise and importance of metabarcoding for a holistic
understanding of entire interacting assemblages of different trophic
group, Ficetola and Taberlet (2023) review approaches that can reveal
biodiversity response to global change. Metabarcoding approaches provide
information not only on species occurrences, but also on species
interactions, with new approaches using species traits, phylogenetic
information and machine learning algorithms to infer multitrophic and
multitaxa interactions. Moreover, metabarcoding can provide a means for
detecting hidden diversity (e.g., (Yin et al., 2022)) and associated
cryptic interactions (e.g., (Sow et al., 2019))\textbf{: Lu et
al.}(2022) focused on cryptic diversity by comparing mycobiomes in
marine, gut, and soil samples and found that, while soils have the
highest diversity, the gut has the highest number of unknown species,
followed by marine sediments.

\textbf{Community Assembly Processes} :

Describing the composition and structure of communities and their
responses to perturbations and stressors has been a primary objective of
ecological research since its inception. We still struggle to understand
and predict the mechanisms shaping the dynamics of biological
communities and how these accommodate or collapse in the face of change.
Community profiling methods, by providing data on the diversity and
abundance of the entire community of taxa across sites of different age,
nutrient availability, etc, are now providing unprecedented insights
into the processes of assembly. New modeling approaches (Overcast,
Emerson, \& Hickerson, 2019; Overcast, Ruffley, Rosindell, Harmon,
Borges, Emerson, Etienne, Gillespie, Krehenwinkel, \& Mahler, 2021) are
now being applied to these data to provide insights into the temporal
and spatial components that govern the assembly process, and hence the
factors that might dictate resilience. In this issue, Overcast et al
(2021) have built an eco-evolutionary simulation model that uses
community-scale genetic data to study community assembly dynamics and
show that there are detectable signatures of neutral and non-neutral
processes in simulated biodiversity data axes. Applying the model to
soil microarthropod metabarcoding data from Cyprus, they show that
widespread low-elevation communities are structured by neutral
processes, while isolated high-elevation habitats are shaped by
non-neutral processes.

Studies in this category included terrestrial and marine systems, macro-
and micro-organism assembly, and comparisons of community assembly
processes across scales of organismic complexity. For terrestrial
communities, several papers focused on the respective roles of
environmental filtering, niche conservatism/ lability, and spatial
isolation in shaping animal species diversity at a given site? In the
paper by Noguerales et al (2023), they use whole organism community DNA
(Creedy et al., 2022) metabarcoding at both OTU- and ASV-levels to tease
apart the role of environmental filtering and spatial isolation in
metacommunity dynamics of soil microarthropods. The study showed that
OTU (species) richness follows an altitudinal gradient, presumably
associated with filtering and niche-based processes; the ASV diversity
showed a contrasting pattern of decline in genetic diversity associated
with anthropogenic disturbance. The paper by Andujar et al. (2022)used
the soil mesofauna in the Canary Islands to highlight the importance of
environmental filtering and niche conservatism as a driver of insular
community assembly with little evidence of niche lability, with strong
geographic structure. Likewise, the paper by Arjona et al (2022) focused
on soil arthropod communities at different depths, highlighting the
diversity of species (many new species records), with the results
supporting the hypothesis that deeper soil beetle communities are much
more dispersal limited compared to those closer to the surface. The
overall promise of the approach is highlighted in Emerson et al. 2022
(2022) who highlight the potential to complement high throughput barcode
sequencing with deep learning computational workflows (of images) to
advance the way we study terrestrial arthropod biodiversity as a whole.

Considering marine systems, Kiemel et al. (2022) used DNA metabarcoding
(COI and 18S) to ask (i) how the community is spatially and temporally
connected, (ii) what are the environmental factors influencing local
communities, and (iii) what are the underlying metacommunity dynamics in
this system. There was no difference between ephemeral and permanent
kettle holes, and overall the results suggest that communities are
mainly structured by environmental filtering based on pH, water
temperature, kettle hole size and hydroperiod. Species sorting is a
dominant driver in community assembly in the studied kettle hole
zooplankton metacommunity. Likewise Govender et al. (2022) used a
metabarcoding approach to highlight the point that, while sheltered
bight areas have lower pelagic zooplankton diversity due to structurally
homogeneity, they actually represent important fish spawning grounds
(with important ramifications for fisheries and higher-level consumers).
In this case, diversity measures could thus not be used as a proxy for
ecological importance.

A number of these studies addressed similar questions in microbial
communities. Thus, Pino et al. (2023) addressed used 16S rRNA and ITS
metabarcoding of soil microbiomes (bacteria and fungi) across large
scale edaphic and climatic gradients in Australia to address classic
questions in soil science and macroecology: Are broad soil
classifications sufficient to capture biological soil function, and what
large-scale factors determine turnover in community composition? The
authors found that soil classes are predictive of bacterial and fungal
community composition regardless of spatial proximity, natural and
cultivated soils are reliably distinct in their microbiomes, and the
primary drivers of these microbiome community differences are soil pH
and temperature cycles. Van der Loos et al. (2022) explored the
interplay between environment and host genotype in shaping the stability
and variability of microbial composition. Using seaweed-associated
bacterial communities along a salinity gradient, they were able to
identify a small group of core microbes possibly involved in salinity
adaptation of the host. The experimental study by Nappi et al. 2022
(2022) tested the effects of two bacterial strains on the assembly and
succession of microbial communities associated with the green
macroalga\emph{Ulva australis} . Both bacterial strains exert a priority
effect, with one strain (D2) causing initially strong but temporary
taxonomic changes, and the second strain (D323) causing weaker but
consistent changes that were predominantly facilitatory and included
taxa that may benefit the algal host. Priority effects do not appear to
be a simple replacement of functionally equivalent taxa, but result in
distinct differences in the functional potential of the community.
Besides the implications for community ecology, this work provides
insights on the development of new probiotics (e.g. for human health or
agriculture)

Finally, there were several studies in which the authors examined
processes across scales (macro- and micro-organisms). Thus, Wang et al.
2022 (2022) were able to compare community assembly processes across
scales of organismic complexity showing that (i) small soil
microorganisms (bacteria, fungi) were mostly influenced by stochastic
processes while larger soil organisms (nematodes) were more
deterministic; (ii) the independent effects of habitat (including soil
and topographic variables) and its interaction with plant attributes for
community structure significantly decreased with increasing body size;
and (iii) plant leaf phosphorus directly influenced the spatial
distribution of soil-available phosphorus, which indicates their
indirect impact on the assembly of the soil communities. Data suggest
that the assembly of multitrophic soil communities can be explained to
some extent by changes in above-ground plant attributes. Likewise,
Guerrieri et al. (2022) looked at the development of successional
communities in recently deglaciated soils, focusing on six groups
(Eukaryota, Bacteria, Mycota, Collembola, Insecta, and Oligochaeta) and
asking how soil communities change through time following deglaciation,
and how this change differs between different soil layers. They were
able to show increasing diversity within, but also increasing biotic
homogenization between, soil layers, with increasing time since
deglaciation. The shifts were likely associated with the development of
plant communities during succession.

\textbf{Interaction Networks} :

Another major area of study examined interaction networks, and how the
properties of the networks might reflect the health, and functioning of
both macro-organismal (Banerjee et al., 2022) and micro-organismal
(Peixoto et al., 2022) communities. Metabarcoding provides an ideal
opportunity to examine questions relating to interaction networks and
can provide quantitative assessment of resilience to perturbation.
Recent developments in high throughput approaches have revealed entirely
novel insights into plant-pollinator interactions. Bell et al. (2022)
review the opportunities provided by these approaches to examine how
plant-pollinator interactions change as a result of land-use change.
They consider how the approach can be applied to understanding key
questions in global change ecology, in particular, how interactions
change through space and time, including the impacts of climate and
other anthropogenic stressors. Similar studies have shown how
environmental DNA (eDNA) from flowers can be used to identify the
community of pollinating bumblebees and has the potential to reveal
complex networks (Harper et al., 2023). The paper by Lowe et al. (2022)
provides an empirical example in which they used pollen DNA
metabarcoding metabarcoding of honey samples in the honeybee \emph{(Apis
mellifera} ) to reveal seasonal changes in diet specialization according
to resource availability. Because the degree of specialization are
linked to network resilience, the study highlighted seasonal changes in
network vulnerability. Along similar lines, the paper by Encinas-Viso et
al (2022) focused on factors that might drive beta diversity in alpine
plant-pollinator communities. By analyzing insect pollen loads they
showed that metabarcoding data generated networks that were more diverse
but much less specialized compared to observational data. The results
supported their hypothesis that niche specialisation of alpine taxa lead
to fine-scale spatial turnover of phylogenetic diversity, species and
interactions of alpine plant-pollinator networks compared to
low-elevation ecosystems. Finally, Tommasi et al. (2022) tested the
impact of anthropogenic habitat fragmentation on the complexity of
plant-pollinator interaction networks. Using pollen metabarcoding, they
analyzed pollinator richness, plant-pollinator interactions, and
pollination efficiency in landscapes of different fragmentation levels
on the Maldives Islands. Contrary to their expectations, they find that
moderate levels of habitat fragmentation increase the local richness of
pollinators, consistent with the intermediate disturbance hypothesis.
Despite harboring a high pollinator richness, fragmented landscapes
resulted in less complex plant-pollinator networks, with detrimental
affects on the pollination ecosystem service. A particularly concerning
finding is a preference of native pollinators for invasive plant
species, possibly additionally speeding up their spread.

Metabarcoding has now been used to look at dietary niche and questions
of niche partitioning. Ando et al. (2022) used fecal DNA metabarcoding
from 7 species of ducks (329 samples) to show strong niche partitioning
of plant diet across species but opportunistic foraging when
invertebrates were the available food source. Likewise, Boyi et al.
(2022) examined niche overlap in a co-occurring predators in the North
Sea. Using a new 16S primer to metabarcode gut contents, they showed
that the composition of fish prey in the diet of the Eurasian otter
overlaps that of both harbour and grey seal diets, highlighting the
possibility of interspecies competition where these species sharing
foraging ground. Several studies examined how interaction networks
change across gradients. The paper by Srivathsan et al. (2022) tested
for the impact of human disturbance on fly-vertebrate communities and
their interactions to understand whether there is any specialization.
They sampled dung and carrion fly communities along a disturbance
gradient in a swamp forest remnant in Singapore. While there was no
evidence of specialization in the interactions between fly and
vertebrate species, they reveal the effect of roads on the presence of
native and endangered rainforest vertebrate species, highlighting
indirect eDNA monitoring as an important conservation tool. The paper by
Pitteloud et al. (2022) used DNA metabarcoding of insect feces to test
specific hypotheses regarding factors that might dictate interactions in
plant--orthoptera bipartite networks along elevation gradients. The
results showed that the structure of the ecological networks was
governed by both (i) the phylogenetic position of the plant taxa, where
herbivores feed on plants based on their taxonomic identity and (ii)
plant abundance, where herbivores feed on the plant species proportional
to the cover of the plant species. The results also highlighted other
aspects of the environment that shape interactions, in particular leaf
nitrogen content in warmer environments, phenolics and terpenoids in
colder environments. D\selectlanguage{ngerman}ürrbaum et al. (2022) examined the impact of
urbanization on diversity and trophic interactions in arthropod
communities at two trophic levels. By metabarcoding pollen from
herbivorous bees and arthropod prey from wasp nests, they found
contrasting responses to urbanization of predator--prey and
plant-pollinator interactions. While the available diet is impacted for
both trophic levels, the negative effects of urbanization are stronger
for predators than herbivores, likely due to their increased requirement
for larger, unfragmented habitat. The approach can also be used to
address applied questions of biological control interactions as reviewed
in Lue et al. (2022) where the approach can allow not only
identification of biological control interactions, but also evidence of
hyperparasitism or multiparasitism which can disrupt biological control
by introduced agents.

High throughput data can also been used to infer changes in the overall
set of interactions in a given biological community. Ip et al. (2022)
used eDNA in coral reefs to reveal shifts in community composition and
trophic structure of coral associated fish species. A key finding was
that inversion of the trophic pyramid in reefs was a common response to
coral spawning events due to large numbers of predators (secondary and
tertiary fish consumers) associated with the high predation on coral
eggs by planktivorous fish.

Over evolutionary time, a study by Graham et al. (2022) used the
Hawaiian Island geological sequence to show how interactions among
arthropod communities become progressively more specialized. Using
bipartite networks of arthropod-plant associations, they showed that the
average number of interactions per species (linkage density), ratio of
plant to arthropod species (vulnerability), and uniformity of energy
flow (interaction evenness) increased significantly with community age,
suggesting that the communities show a natural progression towards
specialization.

\textbf{Cross Scale Interactions \& Microbiomes} :

The widespread adoption of molecular profiling methods has provided
unprecedented avenues for comparing processes across scales, with the
approaches used for metabarcoding of whole communities of animals or
plants sharing the same overall methods, and being amenable to the same
analytical tools as microbial community profiling. When applied to the
same environmental samples, this suite of sequencing-based methodologies
enables deep characterization of organismal communities, ranging from
macro-/micro-organismal community structure and ecosystem function down
to traits associated with individual taxa. Thus, we now have the
opportunity to conduct parallel analyses of macro- and micro-scale
community structure across biological communities and the interplay
between biotic and abiotic components of entire ecosystems. Highlighting
these parallels, Câmara dos Reis et al. (2022) tested the relative
importance of stochastic and deterministic processes in shaping
bacterial community dynamics associated with a widespread and
ecologically important bloom forming phytoplankton species. Through a
combination of observational (field sampling) and experimental
(microcosm) approaches to assess bacterial community assembly over bloom
succession, they found that deterministic processes shape microbial
communities within phytoplanktonic bloom conditions, whereas stochastic
processes were more prevalent outside of blooms.

Several studies examined questions involved in the interaction between
animals and their microbiome, looking at the effects of the microbiome
on diet and niche. Michel et al. (2022) used metabarcoding methods to
investigate the interplay between diet and gut microbiome in several
geographically isolated and genetically differentiated populations of
the critically endangered Grauer's gorilla.They showed marked
differences in the composition (though not richness or evenness) of the
diet and gut microbiome of genetically differentiated populations,
associated with social, ecological, and geographic factors. Manthey et
al. (2022) tested the hypothesis that the holometabolous insect gut
microbiota rapidly remolds during metamorphosis, allowing exploration of
novel niches during their ontogenesis. By measuring microbial community
turnover during ontogeny, they show that beta-diversity and hence
microbiota turnover is much higher in holometabolous insects compared to
hemimetabolous insects. The microbial shedding and turnover during
ontogenesis of holometabolous insects could open novel ecological niches
and explain the evolutionary success of holometabolous insects.

Several approaches considered the importance of the high throughput
sequencing approaches for understanding how microbial communities can
affect biogeochemical cycling.

Considering microbes and their viral infection dynamics, Merges et al.
(2022) tested the hypothesis that the activity of bacteria and
bacteriophages co-declines across an elevational gradient. Using an
elevational transect in the Swiss Alps they used transcriptome levels to
show that metabolic activity of bacteria declined with increasing
elevation, but activity of bacteriophages did not, highlighting a gap in
our understanding of microbial predator--prey relationships and
associated viral contributions to carbon, nitrogen and phosphorus
cycling. The paper by Pereira et al. (2022) examined the microbiome of a
pelagic tunicate and the potential role of the microbiomes in pelagic
biogeochemical cycling and nutrient remineralization. They showed that
the trophic activity of the tunicates affects the structure of pelagic
food webs and biogeochemical nitrogen, sulfur, and organic cycling.

The interactions between microbiomes and their host species can change
across gradients, allowing fine scale adaptation. To understand these
relationships, Molina et al. (2022) tested the role of climate, site,
and and host variables in structuring sapwood-inhabiting fungal
communities across a gradient of climatic, seasonal and site factors in
the North Patagonian \emph{Nothofagus} forests. The results supported
their hypothesis that host identity and site were the major drivers of
fungal community structure. Remarkable insights are now showing the
tight relationship between hosts and the different components of their
microbiome. Rolshausen et al. (2022) tested the predictability in the
structuring of the different components of a multi taxon holobiont
across environmental gradients. Using a combination of whole genome
analysis and metabarcoding in fungal, algal and bacterial components of
lichen holobionts along elevation gradients they showed that, while
chemically and morphologically indistinguishable, these lichen
holobionts show pronounced compositional turnover with elevation. The
turnover happens in a concerted fashion for the three taxonomic
components, highlighting the importance of coadaptation of different
components in complex holobiont in evolutionary diversification. The
paper by Kivistik et al. (2022) examined the combined impact of diet and
environmental disturbance (salinity and antibiotics) on the
gastrointestinal microbiome of aquatic gastropods. The results showed
that a transition to salinity led to lower gut community richness and
higher host viability, but only when there was an increase in bacterial
generalists in the gut. Brinker et al. (2022) tested the interplay
between host population structure, environmental conditions and the
presence of an endosymbiont on the bacterial community of an insect
host. They simultaneously investigated the population structure of a
parasitic wasp host and the spatial turnover in its microbiome, with
high similarity among microbial communities in \emph{Wolbachia} infected
(asexually reproducing) hosts and marked host population structure in
uninfected (sexually reproducing) hosts.

High throughput approaches have also provided insights into the role of
microbiomes in imparting disease resilience. Navine et al. (2022) tested
the effect of microbiome communities on resistance to avian malaria by
comparing two birds species in Hawaii, one native, one introduced.
Neither microbial alpha nor beta diversity covaried with infection, but
149 microbes showed positive associations with malaria survivors,
highlighting possible candidates for probiotics to facilitate immunity
to malaria in endangered birds.

A critical component in microbiome studies is to tease apart the
relative importance of the host and the environment in shaping observed
patterns, something that can be difficult. Perez-Lamarque \& Morlon
(2022) evaluate several widely used methods for inferring
host-microbiome cophylogenetic processes that aim to differentiate
between vertical transmission and host-switching. They use simulations
to measure power and type-I error rate and find that there are
trade-offs between computational and statistical performance among the
methods. They conclude that no one current method is optimal and make
recommendations for the scenarios under which different methods are most
appropriate.

\textbf{Invasive Species/ Homogenization} :

Homogenization of landscapes and seascapes through the arrival of non
native species leads to loss of resilience, with subsequent erosion of
the role of biodiversity in ecosystem services (Díaz et al., 2018) and
buffering against tipping points and regime shifts (Nyström et al.,
2019). However, detecting non native species, and teasing them out from
natives can be an almost impossibly difficult task (Guia\selectlanguage{polish}ş\selectlanguage{english}u, 2016).
Perhaps because of this difficulty, some have argued that non native
species must be incorporated into conservation decisions (Sax,
Schlaepfer, \& Olden, 2022), though the scientific rationale is
difficult to establish and there is a substantial literature indicating
that the co-evolved nature of species in a given area is critical to its
resilience (Pauchard et al., 2018). High throughput approaches are now
providing entirely novel avenues for the study of non native species.
First, the use of eDNA can provide unprecedented levels of
detectability, both in aquatic and terrestrial systems (Valentin et al.,
2020). In addition, an intriguing new analytical tool uses the genetic
signature derived from metabarcoding studies to separate
bioinformatically, native from non native species (Andersen et al.,
2019); this method was employed in several studies in this special issue
to provide insights into the impact of non native species and the
associated biotic homogenization (Graham et al., 2022; Kennedy et al.,
2022).

The modeling approaches developed in the context of community assembly
can equally be applied to understanding invasions. Thus, Overcast et al.
(Overcast, Ruffley, Rosindell, Harmon, Borges, Emerson, Etienne,
Gillespie, Krehenwinkel, Mahler, et al., 2021) highlight the importance
of neutral processes in invaded communities. The paper by \textbf{Zhang
et al. 2022} (2022) used a chronological gradient of smooth cordgrass
invasion in salt marshes (Yellow River Estuary, China) with a
combination of metabarcoding and GeoChip approaches to show a positive
correlation between microbial diversity and the duration age of
invasion, and both bacterial and fungal communities showed consistent
changes with invasion. Soil microbial metabolic potential, as indicated
by the abundance of microbial functional genes involved in
biogeochemical cycling, decreased in response to invasion. As a
consequence, declining soil microbial metabolisms as a result of plant
invasion facilitated carbon accumulation in invaded salt marshes.
Bacteria and fungi exhibited distinct contributions to assembly
processes along the invasion gradient: bacterial communities were mainly
driven by selection and dispersal limitation, while fungi were
dramatically shaped by stochastic processes.

Metabarcoding approaches can clearly identify the effect of
anthropogenic habitat modification on species assemblages, including key
taxa that are associated with modified environments, as well as the
overall homogenizing effects of invasions. For example, \textbf{Hampel
et al.} (Hampel, Moseley, \& Hamdan, 2022) show that the presence of
undersea ``built habitats'' (shipwrecks) causes increased microbial
biodiversity and a predictable core microbiome in their surrounding
deep-sea sediments (extending up to 300m from the wrecks). Specific
archaeal groups showed enrichment around shipwrecks, suggesting
metabolic shifts towards chemolithoautotrophy in these proximate
sediments. Similarly, Andr\selectlanguage{ngerman}és et al. (2023) used eukaryotic environmental
DNA (eDNA) to reveal the interplay between environmental factors in the
homogenizing effects of shipping, with routed-based models of ship-borne
species showing that environmental dissimilarity, shipping, and their
interaction reduce biological dissimilarity among commercial port
habitats.

As in the previous sections, metabarcoding across gradients provide
insights into processes of invasion and in particular, the phenomenon of
biotic resistance, or the reduction in invasion success caused by the
resident community (Levine, Adler, \& Yelenik, 2004). Notably, the paper
by Graham et al. (2022) used the geological age gradient of the Hawaiian
Islands in which comparable sites of high elevation native forest show
increasing diversity of native species over the 5 my timeframe. Results
from metabarcoding of entire arthropod communities demonstrate that,
where species diversity is lowest (on the youngest island), infiltration
of non-native species is highest. Likewise, Kennedy et al. (2022) used
DNA metabarcoding and statistical modeling to survey community-wide
arthropod richness, the proportion of native and non-native species, and
the incursion of non-natives into primary habitats on three archipelagos
in the Pacific. Focusing on one island from each of the three
archipelagos that differ with respect to age, area and proportion of
native habitat, there were three alternative hypotheses defined by
fundamental eco-evolutionary processes with associated predictions that
were detectable from the high-throughput metabarcoding surveys. The
study showed that older age and correspondingly higher taxonomic
richness was associated with higher resistance to invasion, and that
invasion did not lead to homogenization of arthropod assemblages across
the different degraded forests on the three archipelagos.

\textbf{Recurring Themes}

Besides the insights made in each of the major theme areas above, there
were several recurring themes that emerged from multiple studies:

Importance of museum \& associated reference collections . Museums play
a key role in metabarcoding approaches. First, while many insights can
be gained from molecular sequences alone, the availability of a
reference collection, ie, molecular barcodes for identified specimens,
adds unprecedented dimensionality to the data. The availability of a
reference collection allows us to infer the functional traits and
morphological attributes of every taxon in a sample, whether it is
native or not at a given site, its overall distribution and trophic
relationships. Moreover, it is critical that the identity of the
specimen has been thoroughly confirmed, as misidentification can lead to
flawed interpretations. Thus, rather than diminishing any role of
natural history museums in such approaches, the vast data that have been
generated through molecular profiling approaches have increasingly
highlighted the fundamental importance of barcodes from reliably
identified species and populations (Valdivia\selectlanguage{english}-Carrillo, Rocha\selectlanguage{english}-Olivares,
Reyes\selectlanguage{english}-Bonilla, Dominguez\selectlanguage{english}-Contreras, \& Munguia\selectlanguage{english}-Vega, 2021). The
importance of a reference collection is highlighted by Lue et al. (2022)
which describes the importance of a vetted and curated reference library
for biological control studies. Likewise, Lu et al. (2022) emphasize the
limitations of inference without a reference database, and introduce a
fungal rRNA operon database (FRODO) with 1116 linked to taxonomically
identified species.

A second role of museum specimens in these approaches is that they can
provide historic samples of past environments. For example,
metabarcoding of pollen loads from museum bee specimens has provided key
insights into environmental change over decadal scales, both in the
availability of plants, and changes in interaction networks (Bell et
al., 2022; Gous, Swanevelder, Eardley, \& Willows\selectlanguage{english}-Munro, 2019). This
work adds to the increasing body of research that shows how
metabarcoding of museum specimens can provide information on changes in
interactions through time, including diet and microbiome (Heindler et
al., 2018) and parasite-host interactions (Greiman et al., 2018).

Insights from clustering at different levels : Early metabarcoding
studies used clustering approaches and generally grouped ASVs into
Operational Taxonomic Units (OTUs), assumed to correspond to species.
The purpose of this step was to remove the known noise in the data,
while also grouping taxa into species. However, new denoising approaches
have presented the opportunity of analyzing ASVs and hence gaining
insights into population-level patterns (Noguerales et al., 2023). The
most important aspect of the ability to look at different levels of
genetic clustering is that the comparison can be tremendously
informative into the processes that govern species assembly.

Incorporation of Deep Learning / Artificial Intelligence approaches
applied to image analysis to study arthropod biodiversity (Emerson et
al., 2022). Supervised learning was used to make predictions of sediment
sample proximity to shipwrecks based on frequency of microbial taxa
(Hampel et al., 2022).

\textbf{Future Outlook}

The collection of papers in this Special Issue highlights the critical
insights that can be gained using high-throughput approaches, in
particular in relation to biodiversity dynamics. We now have a tool for
understanding how overall species composition changes across (1) spatial
gradients, whether habitat, elevation, precipitation, nutrient, or
anthropogenically-associated modifications. Moreover, we can also
examine changes through (2) time, whether using museum specimens,
ancients sediments, or sub-fossils to show how diet, host-associations,
parasitism, and other interactions have changed; and geological or
ecological chronosequences that provide insights into how entire
communities change over extended time periods. The set of papers
includes a mixture of studies, with about half focusing on
macro-organisms, the other half on microorganisms. The critical point
here is that we have a tool that allows comparison of processes across
scales. Thus, concepts developed for understanding biodiversity in
macro-organisms can be tested in real time using microorganisms, and
dynamics that have been learned from microbial systems can provide
insights into factors shaping communities of macro-organisms and their
interaction with entire ecosystems. As the approaches become more
robust, it will be easier to realize the potential of high-throughput
analyses to answer some of the most intractable questions in
biodiversity science.

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