Glaciers are retreating globally, and the resulting ice-free areas provide an experimental system for understanding species colonization patterns, community formation, and dynamics. The last several years have seen crucial advances in our understanding of biotic colonization after glacier retreats, resulting from the integration of methodological innovations and ecological theories. Recent empirical studies have demonstrated how multiple factors can speed up or slow down the velocity of colonization and have helped scientists develop theoretical models that describe spatiotemporal changes in community structure. There is a growing awareness of how different processes (e.g., time since glacier retreat, onset or interruption of surface processes, abiotic factors, dispersal, biotic interactions) interact to shape community formation and, ultimately, their functional structure through succession. Here, we examine how these studies address key theoretical questions about community dynamics and show how classical approaches are increasingly being combined with environmental DNA metabarcoding and functional trait analysis to document the formation of multitrophic communities, revolutionizing our understanding of the biotic processes that occur following glacier retreat. Expected final online publication date for the Annual Review of Ecology, Evolution, and Systematics, Volume 52 is November 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Environmental DNA metabarcoding is becoming a key tool for biodiversity monitoring over large geographical or taxonomic scales and for elusive taxa like soil organisms. Increasing sample sizes and interest in remote or extreme areas often require the preservation of soil samples and thus deviations from optimal standardized protocols. However, we still ignore the impact of different methods of soil sample preservation on the results of metabarcoding studies and there is no guideline for best practices so far. Here, we assessed the impact of four methods of soil sample preservation that can be conveniently used also in metabarcoding studies targeting remote or difficult to access areas. Tested methods include: preservation at room temperature for 6h, preservation at 4°C for three days, desiccation immediately after sampling and preservation for 21 days, and desiccation after 6h at room temperature and preservation for 21 days. For each preservation method, we benchmarked resulting estimates of taxon diversity and community composition of three different taxonomic groups (bacteria, fungi and eukaryotes) in three different habitats (forest, river bank and grassland) against results obtained under ideal conditions (i.e. extraction of eDNA right after sampling). Overall, the different preservation methods only marginally impaired results and only under certain conditions. When rare taxa were considered, we detected small but significant changes in MOTU richness of bacteria, fungi and eukaryotes across treatments, but MOTUs richness was similar across preservation methods if rare taxa were not considered. All the approaches were able to identify differences in community structure among habitats, and the communities retrieved using the different preservation conditions were extremely similar. We propose guidelines on the selection of the optimal soil sample preservation conditions for metabarcoding studies, depending on the practical constraints, costs and ultimate research goals.

Environmental DNA metabarcoding is becoming a key tool for biodiversity monitoring over large geographical or taxonomic scales and for elusive taxa like soil organisms. Increasing sample sizes and interest in remote or extreme areas often require the preservation of soil samples and thus deviations from optimal standardized protocols. However, we still ignore the impact of different methods of soil sample preservation on the results of metabarcoding studies and there is no guideline for best practices so far. Here, we assessed the impact of four methods of soil sample preservation that can be conveniently used also in metabarcoding studies targeting remote or difficult to access areas. Tested methods include: preservation at room temperature for 6h, preservation at 4°C for three days, desiccation immediately after sampling and preservation for 21 days, and desiccation after 6h at room temperature and preservation for 21 days. For each preservation method, we benchmarked resulting estimates of taxon diversity and community composition of three different taxonomic groups (bacteria, fungi and eukaryotes) in three different habitats (forest, river bank and grassland) against results obtained under ideal conditions (i.e. extraction of eDNA right after sampling). Overall, the different preservation methods only marginally impaired results and only under certain conditions. When rare taxa were considered, we detected small but significant changes in MOTU richness of bacteria, fungi and eukaryotes across treatments, but MOTUs richness was similar across preservation methods if rare taxa were not considered. All the approaches were able to identify differences in community structure among habitats, and the communities retrieved using the different preservation conditions were extremely similar. We propose guidelines on the selection of the optimal soil sample preservation conditions for metabarcoding studies, depending on the practical constraints, costs and ultimate research goals.

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Most of the world’s mountain glaciers have been retreating for more than a century in response to climate change. Glacier retreat is evident on all continents, and the rate of retreat has accelerated during recent decades. Accurate, spatially explicit information on the position of glacier margins over time is useful for analyzing patterns of glacier retreat and measuring reductions in glacier surface area. This information is also essential for evaluating how mountain ecosystems are evolving due to climate warming and the attendant glacier retreat. Here, we present a non-comprehensive spatially explicit dataset showing multiple positions of glacier fronts since the Little Ice Age (LIA) maxima, including many data from the pre-satellite era. The dataset is based on multiple historical archival records including topographical maps; repeated photographs, paintings, and aerial or satellite images with a supplement of geochronology; and own field data. We provide ESRI shapefiles showing 728 past positions of 94 glacier fronts from all continents, except Antarctica, covering the period between the Little Ice Age maxima and the present. On average, the time series span the past 190 years. From 2 to 46 past positions per glacier are depicted (on average: 7.8).

Clustering approaches are pivotal to handle the many sequence variants obtained in DNA metabarcoding data sets, and therefore they have become a key step of metabarcoding analysis pipelines. Clustering often relies on a sequence similarity threshold to gather sequences into molecular operational taxonomic units (MOTUs), each of which ideally represents a homogeneous taxonomic entity (e.g., a species or a genus).However, the choice of the clustering threshold is rarely justified, and its impact on MOTU over-splitting or over-merging even less tested. Here, we evaluated clustering threshold values for several metabarcoding markers under different criteria: limitation of MOTU over-merging, limitation of MOTU over-splitting, and trade-off between over-merging and over-splitting. We extracted sequences from a public database for nine markers, ranging from generalist markers targeting Bacteria or Eukaryota, to more specific markers targeting a class or a subclass (e.g., Insecta, Oligochaeta).Based on the distributions of pairwise sequence similarities within species and within genera, and on the rates of over-splitting and over-merging across different clustering thresholds, we were able to propose threshold values minimizing the risk of oversplitting, that of over-merging, or offering a trade-off between the two risks. For generalist markers, high similarity thresholds (0.96-0.99) are generally appropriate, while more specific markers require lower values (0.85-0.96). These results do not support the use of a fixed clustering threshold. Instead, we advocate careful examination of the most appropriate threshold based on the research objectives, the potential costs of over-splitting and over-merging, and the features of the studied markers.

Soil biodiversity is fundamental for ecosystems, ensuring many ecosystem functions, such as nutrient cycling, organic matter decomposition, soil formation, and organic carbon pool increase. Due to these roles, there is a need to study and completely understand how soil biodiversity is composed through different habitats. The aim of this study was to describe the edaphic soil community of the alpine environments belonging to the Gran Paradiso National Park, thus detecting if there are any correlation with environmental features. We studied soil fauna through environmental DNA metabarcoding. From eDNA metabarcoding, 18 families of arthropods were successfully detected, and their abundance expressed in terms of the relative frequency of sequences. Soil faunal communities of mixed coniferous forests were characterized by Isotomidae, Entomobriydae, Hypogastruridae, and Onychiuridae; while mixed deciduous forests were composed mostly by Isotomidae, Cicadidae, Culicidae, and Neelidae. Calcicolous and acidic grasslands also presented families that were not detected in forest habitats, in particular Scarabaeidae, Curculionidae, Brachyceridae, and had in general a more differentiated soil community. Results of the Canonical Component Analysis revealed that the main environmental features affecting soil community for forests were related to vegetation (mixed deciduous forests, tree basal area, tree biomass, Shannon index), soil (organic layers and organic carbon stock), and site (altitude); while for prairies, soil pH and slope were also significant in explaining soil community composition. This study provided a description of the soil fauna of alpine habitats and resulted in a description of community composition per habitat and the relation with the characteristic of vegetation, soil, and topographic features of the study area. Further studies are needed to clarify ecological roles and needs of these families and their role in ecosystem functioning.

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