Metabarcoding inventory of an arctic tundra soil ecosystem reveals highly heterogeneous communities at a small scale

Biodiversity surveys of Arctic soil ecosystems are limited. Here, we provide a sequence-based inventory of soil fauna from an Arctic tundra ecosystem near the Canadian High Arctic Research Station in Cambridge Bay, Nunavut. Invertebrate communities were extracted at a vegetated and non-vegetated site in three replicates and inventoried using 18S metabarcode sequencing. A total of 361 amplicon sequence variants (ASV) were identified and assigned to the closest matching taxonomic orders, most of which belonged to the Nematoda and Arthropoda. Vegetated soils showed no significantly higher ASV richness relative to non-vegetated soils although they contained a significantly higher diversity of arthropod taxa including insects, mites, and springtails. Most taxa were found only at a single location and even samples from the same site displayed distinct communities, suggesting that belowground species richness in Arctic tundra habitats is highly heterogeneous. Preserving soil biodiversity in a changing Arctic is essential for Inuit communities who rely on intact tundra ecosystems for their health and wellbeing

Parasitoids indicate major climate-induced shifts in arctic communities

Climatic impacts are especially pronounced in the Arctic, which as a region is warming twice as fast as the rest of the globe. Here, we investigate how mean climatic conditions and rates of climatic change impact parasitoid insect communities in 16 localities across the Arctic. We focus on parasitoids in a widespread habitat,Dryasheathlands, and describe parasitoid community composition in terms of larval host use (i.e., parasitoid use of herbivorous Lepidoptera vs. pollinating Diptera) and functional groups differing in their closeness of host associations (koinobionts vs. idiobionts). Of the latter, we expect idiobionts-as being less fine-tuned to host development-to be generally less tolerant to cold temperatures, since they are confined to attacking hosts pupating and overwintering in relatively exposed locations. To further test our findings, we assess whether similar climatic variables are associated with host abundances in a 22 year time series from Northeast Greenland. We find sites which have experienced a temperature rise in summer while retaining cold winters to be dominated by parasitoids of Lepidoptera, with the reverse being true for the parasitoids of Diptera. The rate of summer temperature rise is further associated with higher levels of herbivory, suggesting higher availability of lepidopteran hosts and changes in ecosystem functioning. We also detect a matching signal over time, as higher summer temperatures, coupled with cold early winter soils, are related to high herbivory by lepidopteran larvae, and to declines in the abundance of dipteran pollinators. Collectively, our results suggest that in parts of the warming Arctic,Dryasis being simultaneously exposed to increased herbivory and reduced pollination. Our findings point to potential drastic and rapid consequences of climate change on multitrophic-level community structure and on ecosystem functioning and highlight the value of collaborative, systematic sampling effort

Glacial Legacies: Microbial Communities of Antarctic Refugia

In the cold deserts of the McMurdo Dry Valleys (MDV) the suitability of soil for microbial life is determined by both contemporary processes and legacy effects. Climatic changes and accompanying glacial activity have caused local extinctions and lasting geochemical changes to parts of these soil ecosystems over several million years, while areas of refugia may have escaped these disturbances and existed under relatively stable conditions. This study describes the impact of historical glacial and lacustrine disturbance events on microbial communities across the MDV to investigate how this divergent disturbance history influenced the structuring of microbial communities across this otherwise very stable ecosystem. Soil bacterial communities from 17 sites representing either putative refugia or sites disturbed during the Last Glacial Maximum (LGM) (22-17 kya) were characterized using 16 S metabarcoding. Regardless of geographic distance, several putative refugia sites at elevations above 600 m displayed highly similar microbial communities. At a regional scale, community composition was found to be influenced by elevation and geographic proximity more so than soil geochemical properties. These results suggest that despite the extreme conditions, diverse microbial communities exist in these putative refugia that have presumably remained undisturbed at least through the LGM. We suggest that similarities in microbial communities can be interpreted as evidence for historical climate legacies on an ecosystem-wide scale

Parasitoids indicate major climate-induced shifts in arctic communities

Climatic impacts are especially pronounced in the Arctic, which as a region is warming twice as fast as the rest of the globe. Here, we investigate how mean climatic conditions and rates of climatic change impact parasitoid insect communities in 16 localities across the Arctic. We focus on parasitoids in a widespread habitat,Dryasheathlands, and describe parasitoid community composition in terms of larval host use (i.e., parasitoid use of herbivorous Lepidoptera vs. pollinating Diptera) and functional groups differing in their closeness of host associations (koinobionts vs. idiobionts). Of the latter, we expect idiobionts-as being less fine-tuned to host development-to be generally less tolerant to cold temperatures, since they are confined to attacking hosts pupating and overwintering in relatively exposed locations. To further test our findings, we assess whether similar climatic variables are associated with host abundances in a 22 year time series from Northeast Greenland. We find sites which have experienced a temperature rise in summer while retaining cold winters to be dominated by parasitoids of Lepidoptera, with the reverse being true for the parasitoids of Diptera. The rate of summer temperature rise is further associated with higher levels of herbivory, suggesting higher availability of lepidopteran hosts and changes in ecosystem functioning. We also detect a matching signal over time, as higher summer temperatures, coupled with cold early winter soils, are related to high herbivory by lepidopteran larvae, and to declines in the abundance of dipteran pollinators. Collectively, our results suggest that in parts of the warming Arctic,Dryasis being simultaneously exposed to increased herbivory and reduced pollination. Our findings point to potential drastic and rapid consequences of climate change on multitrophic-level community structure and on ecosystem functioning and highlight the value of collaborative, systematic sampling effort.Peer reviewe

Data for: Parasitoids indicate major climate-induced shifts in Arctic communities

Climatic impacts are especially pronounced in the Arctic, which as a region is warming twice as fast as the rest of the globe. Here, we investigate how mean climatic conditions and rates of climatic change impact parasitoid insect communities in 16 localities across the Arctic. We focus on parasitoids in a wide-spread habitat, Dryas heathlands, and describe parasitoid community composition in terms of larval host use (i.e. parasitoid use of herbivorous Lepidoptera versus pollinating Diptera) and functional groups (i.e. parasitoids adhering to an idiobiont versus koinobiont lifestyle). Of the latter, we expect idiobionts to be generally associated with poorer tolerance to cold temperatures. To further test our findings, we assess whether similar climatic variables are associated with host abundances in a 22-year time series from Northeast Greenland. We find that sites which have experienced a temperature rise in summer while retaining cold winters to be dominated by parasitoids of Lepidoptera, with the pattern reversed among the parasitoids of Diptera. The rate of summer temperature rise is further associated with higher levels of herbivory, suggesting higher availability of lepidopteran hosts and changes in ecosystem functioning. We also detect a matching signal over time, as higher summer temperatures, coupled with cold early winter soils, are related to high herbivory by lepidopteran larvae, and to declines in the abundance of dipteran pollinators. Collectively, our results suggest that in parts of the warming Arctic, Dryas is being simultaneously exposed to increased herbivory and reduced pollination. Our findings point to potential drastic and rapid consequences of climate change on multitrophic-level community structure and on ecosystem functioning and highlight the value of collaborative systematic sampling effort.,1. Description of methods used for collection/generation of data: This dataset comprises of parasitoids caught in 2016 at 19 Arctic and Sub-Arctic localities during two consecutive six-day-long trapping periods aimed to take place during the flowering peak of the mountain avens (Dryas spp.). Each location had three to four trapping sites (A-D) in Dryas heath type habitats, each with ten 5cm by 4.5cm white sticky traps cut out from sticky board (Barrettine Environmental, UK [product no longer available]). Sticky traps were embedded in growths of Dryas spp. The parasitoids were subsequently picked of off the sticky traps, their whole DNA was extracted and half of their Cytochrome Oxidase I barcode region was amplified using Primers B-F and HCO. The processing of samples was done in three parts (Data1, Data2, Data2) with slightly different methodology. See the supplementary information of the recommended publication for more details. Datasets were sequenced at the Helsinki Functional Genomics Unit (FuGU) in two separate MiSeq v3 2x300bp runs (Data1 and Data2). Additionally, a set of samples from a specific site (Zackenberg) were sequenced as part of larger set at the FIMM Technology Centre in a HiSeq2500 2x250bp run (Data3). Additionally, Dryas flower count, flowering phenology and flower damage by insect herbivores was recorded at the start, after a week (day 6) and in the end (day 12). These counts were done in 3 to 5 1/4 square meter monitoring plots per trapping site. Microclimate was recorded at one trapping site per locality using Lascar EL-USB-2 tempeerature and air humidity loggers under a small white plastic dome at ~ 10 cm height. 2. Methods for processing the data: Initially, paired-end reads were merged and trimmed for quality using 32-bit usearch version 11 (Edgar 2010) with the command ‘fastq_mergepairs’. Primers were removed using software cutadapt version 1.14 (Martin 2011) with 15% mismatch rate. The reads were then collapsed into unique sequences (singletons removed) with command ‘fastx_uniques’. The subsequent clustering steps differed slightly for different data sets, due to the origin of the data (MiSeq vs. HiSeq2500), as follows. For Data1 and Data2, the newly-collapsed unique sequences were cleaned of chimeras using command ‘uchime_denovo’ and clustered into 96% OTUs (OTU = Operational Taxonomical Unit) using command ‘cluster_size’ using USEARCH. The choice of 96% clustering threshold was based on empirical optimization, considering both the rapid genetic divergence in CO1, as well as potential sequencing errors. For Data3, the unique sequences were denoised (i.e., chimeras were removed) and reads were clustered into ZOTUs (= ‘zero-radius OTU’) with command ‘unoise3’ using USEARCH version 11. These ZOTUs do not practically differ from traditional clustering of OTUs (which are based on pre-set percentage threshold), but according to Edgar and Flyvbjerg (2015), the UNOISE algorithm performs better for certain heterogenous data sets in (i) removing chimeras, (ii) PhiX sequences and (iii) Illumina artefacts. Then OTUs and ZOTUs were mapped back to the original trimmed reads with command ‘usearch_global’ (‘search_exact’ for Data3) to establish the total number of reads in each sample using 64-bit software vsearch (Rognes et al. 2016). Overall, we were able to map 25,673,920 reads (Data1: 4,261,291; Data2: 12,095,141; Data3: 9,317,488) to our original samples. These reads were subject to further filtering: from each sample, each OTU/ZOTU with less reads than 2% of the total reads in that sample were discarded, which also cleared most of the extraction and PCR negative controls. Finally, samples producing less than 37 reads (a threshold chosen by analysing the data as a whole) were removed from the subsequent analysis. The taxonomic assignations were initially done independently for each dataset (using identical criteria), but the final assignations were carried out using the whole, combined (Data1+Data2+Data3) dataset. The OTUs/ZOTUs were initially identified into genus-level using the RDP classifier with a very recently constructed COI-RDP database v3.2 (with 60% probability threshold for genus-level assignation) following Porter and Hajibabaei (2018). In cases where the database was clearly insufficient to reach a genus-level assignation, we used local BLAST against all the retrieved COI sequences in BOLD (Altschul et al. 1990; Ratnasingham and Hebert 2007) and chose the most probable match. Taxonomic information for remaining hits was retrieved manually from BOLD using BIN code (from earlier steps) or the actual OTU/ZOTU sequence. Finally, identifications were checked against our preliminary identification notes taken at the beginning of DNA extraction, and potentially false assignations (due to for example contamination in certain steps, or clear errors in the database) were either removed or assigned to the likely correct out/ZOTU. As the end result of all the bioinformatic steps, we arrived at a list of 460 parasitoid taxa (listed in OTU_info.csv Those dataset specific OTUs which were collapsed to one in the merging of the datasets are also listed in this file).,The included README_PanArcticParasitods.txt file contains detailed metadata on all included variables. There are some missing data e.g.: In the in situ microclimate measurements misising values are denoted with, NA In the parasitoid data, samples which failed to to produce parasitoid reads are marked with NA. In the Dryas data, two localities have their data data missing, and are not included in this table, where as one site Kobbejford had no Dryas and has counts of Loiseleuria procumbens as a phenological indicator in stead. This is marked in the datapoint notes. Concerning OTUs: Our OTUs are based on only a half of the CO1 barcode region and we used a quite wide clustering treshold of 96%. Also the clustering was done globally on a dataset containing closely related species from different continents. While this works well for the intended purpose of looking at functional group dominance at site level, the taxonomic resolution is inadequate for applications requiring true species level information. In such occasiton we encourage contacting the corresponding author. The DNA extracts are stored at the Department of Agricultural Sciences of the University of Helsinki, Finland.

Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology

Gould E, Fraser H, Parker T, et al. Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology. 2023.Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different (mostly social science) fields, and has found substantial variability among results, despite analysts having the same data and research question. We implemented an analogous study in ecology and evolutionary biology, fields in which there have been no empirical exploration of the variation in effect sizes or model predictions generated by the analytical decisions of different researchers. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment), and the project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future