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opencc-by-4.0Jul 2021View details →

Multi-taxa environmental DNA inventories reveal distinct taxonomic and functional diversity in urban tropical forest fragments

Urban expansion and associated habitat transformation drives shifts in biodiversity, with declines in taxonomic and functional diversity. Forests fragments within urban landscapes offer a number of ecosystem services, and help to maintain biodiversity and ecosystem functions. Here, we focus on a tropical forest environment, and on the soil biota. Using eDNA metabarcoding, we compare forest fragments within the city of Cayenne, French Guiana, with a neighbouring continuous undisturbed forest. We wished to determine if urban forest fragments conserve high levels of alpha and beta diversity as well as similar functional composition for plants, soil animals, fungi and bacteria. We found that alpha diversity is similar across habitats for plants and fungi, lower in urban forests for metazoans and higher for bacteria. We also found that urban forests communities differ from undisturbed forests in their taxonomic composition, with urban forests exhibiting greater turnover between fragments potentially caused by ecological drift and limited dispersal. However, their functional composition exhibited limited differences, with an enrichment of palms, arbuscular mycorrhizal fungi and bacteria and a depletion of climber plants and termites. Thus, although urban forest fragments do shelter soil biodiversity that differs from native forests, the losses of soil functions may be relatively limited. This study demonstrates the strong potential of a multi-taxa eDNA approach for rapid inventories across taxonomic kingdoms, in particular for cryptic soil diversity. It also demonstrates the key role of urban forest fragments in conserving biodiversity and ecosystem function, and points to a need for more systematic monitoring of these areas in urban management plans. For each of the 16 samples per plot, 15 g of soil was used for eDNA analyses. Extracellular DNA was extracted as described previously (Zinger et al., 2016; 2019), where each soil sample is added to 15ml of saturated phosphate buffer (Na2HPO4; 0.12m; pH ≈8) in 50ml Falcon tubes. This is placed in an agitator for 15 minutes, before a 2ml aliquot of the soil/phosphate buffer mixture is pipetted into an Eppendorf tube and centrifuged for five minutes at 13000 rcf. 500μL of the resulting supernatant is then recovered and used for the next extraction steps that are carried out with a commercial kit for soil DNA (NucleoSpin® Soil; Macherey-Nagel, Düren, Germany), skipping the lysis step and following manufacturer’s instructions. The DNA extract was recovered in 100 μL and diluted 10 times before being used as PCR template.  For each plot one DNA extraction negative control was performed adding up 17 extractions per plot. PCR amplifications were then conducted for four DNA molecular markers, with primers targeting either Viridiplantae (subsequently referred to as plants), Eukaryotes, Fungi or Bacteria (Table 1). For each marker, PCR amplification of samples occurred across 12 plates. Each PCR reaction was performed in a total volume of 20 μl and comprised 10 μl of AmpliTaq Gold Master Mix (Life Technologies, Carlsbad, CA, USA), 5.84 μl of Nuclease-Free Ambion Water (Thermo Fisher Scientific, Massachusetts, USA), 0.25 μM of each primer, 3.2 μg of BSA (Roche Diagnostic, Basel, Switzerland), and 2 μl of DNA template that was before 10-fold diluted to reduce the amounts of PCR inhibitors. Thermocycling conditions for each primer pair are indicated in Table 1.  A negative extraction control per site and a negative PCR control per PCR plate were amplified and sequenced in parallel with the regular samples. Positive controls were also included and consisted of mock communities of plants and fungi DNA (no mock communities were built for bacteria or eukaryotes here), which were used to guide choices in our data curation process. Two PCR replicates were performed for each sample and control. Amplification was conducted using a double indexing system strategy (Binladen et al. 2007) using a system of 32 by 36 octamers with at least five differences between them located at the 5’ end of each primer (Coissac 2012). In doing so, each PCR product had a unique combination of tags for both forward and reverse primers, allowing for the retrieval of sequence data for each sample. Ten wells per PCR plate were left empty to act as sequencing controls (non-used tag combinations) for downstream data curation (see below). PCR products were pooled and sequencing libraries were constructed using the Illumina TruSeq NanoPCRFree kit following the supplier’s instructions (Illumina Inc., San Diego, California, USA), except that the ligation product was not PCR amplified to limit tag-jump biases (Taberlet et al 2018). The libraries were then sequenced on different Illumina platforms (San Diego, CA, USA) depending on the marker considered (Table S1), using the paired-end technology. Bioinformatic analyses were performed on the GenoToul bioinformatics platform (Toulouse, France), with the OBITOOLS package (Boyer et al. 2016). First, ‘illuminapairedend’ was used to assemble paired-end reads. This algorithm is based on an exact alignment algorithm that considers the quality scores at all positions during the assembly process. Subsequently, we used the ‘ngsfilter’ command to identify and remove the primers and tags on each read, and assign reads to their respective samples. This program was used with its default parameters tolerating two mismatches for each of the two primers and no mismatch for the tags. Following this, sequencing reads were dereplicated using the ‘obiuniq’ command. Sequences of low quality (containing Ns or with paired-end alignment scores below 50) were excluded using the ‘obigrep’ command. The same command was used to exclude sequences represented by only one read (singletons) as they are more likely to be molecular artefacts (Taberlet et al. 2018). Sequences outside of the preset range were also discarded (Table 1). To remove PCR/sequencing errors as well as intraspecific variability, we built OTUs (Operational Taxonomic Units) using the ‘sumaclust’ clustering algorithm (Mercier et al. 2013), which considers the most abundant sequence of each cluster as the cluster representative.  OTUs were set at a sequence similarity threshold of 97% for eukaryotes, fungi and bacteria following the standards in microbial ecology, but this was lowered to 95% for plants since the eDNA target region is shorter (typically around 50 base pairs), where one mismatch inherently results in a lower percentage of similarity. To assign a taxon to plant and fungal OTUs, we built two reference sequence databases, one global, using the ecoPCR programme (Ficetola et al. 2010) and the plant / fungi specific markers on the European Molecular Biology Laboratory (EMBL; release 141), a second local, generated from specimens of fungi (Jaouen et al. 2019) and plants (see Zinger et al. 2019) collected in French Guiana. OTUs were then assigned a taxonomy, using OBITOOL’s ecotag programme (Boyer et al. 2016), which performs a global alignment of each OTU sequence (the query) against each reference. The reference taxon assigned to each OTU corresponds to the Last Common Ancestor of all the best-match sequences for the query. For taxonomic assignment of bacteria and eukaryote OTUs, the SILVA taxonomic database was used (version 1.3; Quast et al., 2012). Classification was performed by a local nucleotide BLAST search against the non-redundant version of the SILVA SSU Ref dataset (release 132; http://www.arb-silva.de) using blastn (version 2.2.30+; http://blast.ncbi.nlm.nih.gov/Blast.cgi) with standard settings (Camacho et al., 2009).  Eukaryote derived metazoan OTUs were then further assigned a taxonomy for Phyla identified at the Arthropoda, Annelida and Nematoda level using reference sequence databases built as above for these groups using the ecoPCR programme on EMBL release 141. Datasets were subsequently filtered to remove contaminants as well as artefacts such as PCR chimeras and remaining sequencing errors, following Zinger et al. (2019) and using routines now implemented in the metabaR R package (Zinger et al 2020b), in R version 3.6.1 (R Development Core Team, 2013). The filtering process consisted of four steps: (i) a negative control-based filtering. OTUs whose maximum abundance was found in extraction/PCR negative controls were removed from the dataset, as they were likely to be reagent/aerosol contaminants, better amplified in the absence of competing DNA fragments as it is the case in biological samples. (ii) a reference-based filtering. OTUs which are too dissimilar from sequences available in reference databases are potential chimeras generated during sequencing and amplification. In this study, we chose to set similarity thresholds at 95% for plants, 80% for bacteria and eukaryotes and due to the marker being more polymorphic, 65% for fungi. For plants and fungi, the remaining assignment was then verified with the local database, to confirm if assigned taxa also occurred in the local dataset, with preference given to local assignment. In addition, we removed all taxa that are not targeted by the primer used. (iii) an abundance-based filtering. This procedure targets incorrect assignment of a few numbers of sequences corresponding to true OTUs occurring to the wrong sample, a phenomenon called “tag-switching” (Esling et al. 2015), “tag jumps” (Schnell et al. 2015) or “cross-talk” (Edgar 2018). It consists in setting OTUs abundances to 0 in samples where their abundance represents < 0.03% of the total OTU abundance in the entire dataset. (iv) Finally, we conducted a PCR-based filtering by considering any PCR reaction that yielded less than 100 reads for plants, 1000 reads for fungi, bacteria and eukaryotes as non-functional, and removed them from the dataset. Data provided consists of 4 x OTU tables for each of the markers used to target different components of the soil biota, with rows representing each OTU, and columns the features of the OTU within the dataset, namely their id code, the number of read counts in the analysed dataset, their similarity score against the taxonomic dataset used to identify them, and when possible, a functional group assignment used in the manuscript. Details of these can be found above and in the manuscript and supplementary information. For each of the four datasets, we also provide a .rds file, corresponding to the processed dataset used in manuscript preparation. This is in the format of a metabaR list which includes PCR, Sample, Read count and the seperately provided OTU datasets. To facilitate interpretation, please refer to Zinger, L., Lionnet, C., Benoiston, A.S., Donald, J., Mercier, C. and Boyer, F., 2021. metabaR: an R package for the evaluation and improvement of DNA metabarcoding data quality. Methods in Ecology and Evolution, 12(4), pp.586-592. For the fungal (ITS) data, we also provide :  - the R1/R2 raw fastq files of the samples used in the paper + experimental controls - a tsv file containing the tag combinations corresponding to the samples/PCR replicates, to enable demultiplexing of data. - a csv file containing the description of each sample.

opencc-by-4.0Dec 2015View details →

Fig.1 in Natural And Historical Aspects Of The Origin And Functioning Of Urban Mammals In Western Siberia, Russia And Uzbekistan

Fig.1. Yamal - Tashkent Transect (70+5° E, ca. 2200 miles). The studied cities are marked with black circles, their size depending on the number of inhabitants.

opencc-by-4.0Dec 2015View details →

Fig. 2 in Natural And Historical Aspects Of The Origin And Functioning Of Urban Mammals In Western Siberia, Russia And Uzbekistan

Fig. 2. The similarity of small mammalian communities from different structural-functional zones of cities by species composition.

FIGURE 3 in Functional responses of stream fish communities to rural and urban land uses

FIGURE 3 | Flowchart of analysis. Biomass and dummy traits matrices were combined to produce functional diversity (FD) indices (FRic = functional richness, FEve = functional evenness, FDiv = functional divergence and FDis = functional dispersion) and community weight mean traits (CWM) matrices. The influences of land use/occupation (Soil matrix) over FD indices were evaluated through Pearson's correlations and over CWM through redundance analysis (RDA) and Pearson's correlations.

FIGURE 4 in Functional responses of stream fish communities to rural and urban land uses

FIGURE 4 | Ordination scores of community-weighted means (CWMs) of traits (gray bars) and proportions of land use/occupation (arrows: biplot scores for constraining variables along of the first principal axis of the redundancy analysis – RDA1) applied to 24 streams sampled in the state of Paraná, Brazil.

FIGURE 2 in Functional responses of stream fish communities to rural and urban land uses

FIGURE 2 | Ternary diagram of land use/occupation in the 24 streams sampled in the state of Paraná, Brazil.

FIGURE 1 in Functional responses of stream fish communities to rural and urban land uses

FIGURE 1 | Location of the sampling sites in the 24 streams in the state of Paraná, Brazil. Codes and names of streams in S1.

publicSep 2025View details →

dryad40/100

Racing amidst change: urbanization and climate alter functional traits and distribution of an Amazonian parthenogenetic lizard

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edi40/100

Arbuscular mycorrhizal fungal diversity and functioning in urban desert preserves and surrounding deserts in the central Arizona

The creation of urban preserves has been proposed to as a method of reducing the impact of urbanization on biodiversity of native ecosystems. This research compared root colonization by two important fungal root symbionts, arbuscular mycorrhizal (AM) fungi and dark septate endophytes (DSE), at two urban desert preserve sites located in Phoenix, Arizona and at two surrounding Sonoran desert sites. Diversity of AM fungi was also compared between sites. AM root colonization was greater in surrounding deserts in comparison to urban preserves, but root colonization by DSE was not significantly different. A greater number of AM fungal species was detected in surrounding deserts in comparison to urban preserves, although the number of species/sample was not significantly different. About 70% of the AM fungal species were detected at both urban preserve and surrounding desert sites, but species in the family Acaulosporaceae were only detected at the surrounding deserts. Decreases in AM functioning and diversity observed at urban preserves may reduce the ability of preserves to sustain biodiversity.

openOpenJan 2020View details →

opencc-zeroMay 2022View details →

Functional diversity of farmland bees across rural-urban landscapes in a tropical megacity

Urbanization is a major threat to biodiversity and food security, as expanding cities, especially in the Global South, increasingly compete with natural and agricultural lands. However, the impact of urban expansion on agricultural biodiversity in tropical regions is overlooked. Here we assessed how urbanization affects the functional response of farmland bees, the most important pollinators for crop production. We sampled bees across three seasons in 36 conventional vegetable-producing farms spread along an urbanization gradient in Bengaluru, an Indian megacity. We investigated how landscape and local environmental drivers affected different functional traits (sociality, nesting behaviour, body size and specialization) and functional diversity (functional dispersion) of bee communities. We found that the functional responses to urbanization were trait specific with more positive than negative effects of grey area (sealed surfaces and buildings) on species richness, functional diversity and abundance of most functional groups. As expected, larger, solitary, cavity-nesting, and surprisingly, specialist bees benefitted from urbanization. In contrast to temperate cities, the abundance of ground-nesters increased in urban areas, presumably because larger patches of bare soil were still available besides roads and buildings. However, overall bee abundance and the abundance of social bees (85% of all bees) decreased with urbanization, threatening crop pollination. Crop diversity promoted taxonomic and functional diversity of bee communities. Locally, flower resources promoted the abundance of all functional groups, and natural vegetation could maintain diverse pollinator communities throughout the year, especially during the non-cropping season. However, exotic plants decreased functional diversity and bee specialization. To safeguard bees and their pollination services in urban farms, we recommend (1) to preserve semi-natural vegetation (hedges) around cropping fields to provide nesting opportunities for above-ground nesters, (2) to promote farm-level crop diversification of beneficial crops (e.g., pulses, vegetables and spices), (3) to maintain native natural vegetation along field-margins, (4) to control and remove invasive exotic plants that disrupt native plant-pollinator interactions. Overall, our results suggest that urban agriculture can maintain functionally diverse bee communities and, if managed in a sustainable manner, can be used to develop win-win solutions for biodiversity conservation of pollinators and food security in and around cities.

zenodo36/100

Dominance by a single species structures multiple ecological functions in urban landscapes

Dataset used in the analysis of the manuscript "Dominance by a single species structures multiple ecological functions in urban landscapes"

opencc-by-4.0Jul 2019View details →

opencc-zeroNov 2022View details →

Data for: Innate immune function and antioxidant capacity of nestlings of an African raptor co-vary with the level of urbanization around breeding territories

Urban areas provide breeding habitats for many species. However, animals raised in urban environments face challenges such as altered food availability and quality, pollution, and pathogens assemblages. These challenges can affect physiological processes like immune function and antioxidant defences which are important for fitness. Here, we explore how levels of urbanisation influence innate immune function, immune response to a mimicked bacterial infection and antioxidant capacity of nestling Black Sparrowhawks Accipiter melanoleucus in South Africa. We also explore the effect of timing of breeding and rainfall on physiology since both can influence the environmental condition under which nestlings are raised. Finally, because urbanisation can influence immune function indirectly, we use path analyses to explore direct and indirect associations between urbanisation, immune function, and oxidative stress. We obtained measures of innate immunity (haptoglobin, lysis, agglutination and bactericidal capacity), indices of antioxidant capacity (total non-enzymatic antioxidant capacity (tAOX), and total glutathione from nestlings from 2015 - 2019. In addition, in 2018 and 2019, we mimicked a bacterial infection by injecting nestlings with lipopolysaccharide and quantified their immune response. Increased urban cover was associated with an increase in lysis and a decrease in tAOX, but not with any of the other physiological parameters. Furthermore, except for agglutination, no physiological parameters were associated with the timing of breeding. Lysis and bactericidal capacity, however, varied consistently with the annual rainfall pattern. Immune response to a mimicked a bacterial infection decreased with urban cover but not with the timing of breeding nor rainfall. Our path analyses suggested indirect associations between urban cover and some immune indices via tAOX but not via the timing of breeding. Our results show that early-life development in an urban environment is associated with variation in immune and antioxidant functions. The direct association between urbanisation and antioxidant capacity and their impact on immune function is likely an important factor mediating the impact of urbanisation on urban-dwelling animals. Future studies should explore how these results are linked to fitness and whether the responses are adaptive for urban-dwelling species.

zenodo36/100

Volume of Interest: Exploring New Data Types in Urban Functional Zones

随着全球城镇化的发展,实现城市功能区的精细化识别已成为一项挑战。基于POI数据的传统方法不足以识别不同区域的功能特征。以往研究中基本单位设置不精确、POI重分类标准模糊、功能区定义模糊等局限性,成为获得准确识别结果的重大障碍。为了解决这些问题,本研究提出了一种将POI数据扩展到三维空间并生成VOI(感兴趣体积)数据的方法。以香港一个小区域为例,采用一系列指标量化功能特征,然后将识别结果与基于POI的方法进行比较。最终鉴定总体准确率和kappa系数分别达到85.67%和0.7619,表明基于VOI的方法与实际情况基本吻合。分析表明,VOI数据包含更丰富、更全面的城市空间信息,能够更好地反映城市内不同区域之间的联系和影响。本研究可为城市功能区深入研究提供参考案例。

opencc-by-4.0Jun 2023View details →

publicNov 2022View details →

Data for: Innate immune function and antioxidant capacity of nestlings of an African raptor co-vary with the level of urbanization around breeding territories

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publicFeb 2024View details →

Collections of small urban parks consistently support higher species richness but not higher phylogenetic or functional diversity

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