Ecology

Study area
We conducted our study at Nopporo Forest Park in Hokkaido, Japan (43° 03′ N, 141° 32′ E) (Fig. 1). This forest is a semi-isolated 2,053 ha area surrounded by residential areas and farmland. There have been concerns about raccoon impacts on this ecosystem since they were first detected in 199234.
Animals
We captured raccoons using box traps (Havahart Large Collapsible Pro Cage Model 1089, Woodstream Corp., Lititz, PA, USA) from May to July in 2018 and April to August in 2019. Traps were placed at 86 sites (Fig. 1). Trapping points within 250 m of the forest boundary line facing the farmland were defined as ‘around the farmland’ (31 points), and other points were defined as ‘in the forest’ (55 points) using QGIS version 3.1023. Captured raccoons were anesthetised with butorphanol tartrate (Vetorphale 5 mg, 1.2 mg/kg; Meiji Seika, Tokyo, Japan), medetomidine hydrochloride (Dolbene, 40 µg/kg; Kyoritsu, Tokyo, Japan), and midazolam (Dormicum injection 10 mg, 0.2 mg/kg; Astellas, Tokyo, Japan) by intramuscular injection and euthanised by potassium chloride injection into the heart. We captured 48 raccoons (34 around the farmland, 14 in the forest) in 2018, and 27 (12 around the farmland, 15 in the forest) in 2019 (Fig. 1). We collected thigh muscle samples, rectal faeces, and gastric contents from captured raccoons. Samples were stored at − 20 °C until analysis.
DNA metabarcoding
Sample preparation
Rectal faeces and gastric contents that were dominated by plant materials and groomed hair were excluded from analyses. In total, 18 rectal faeces and six gastric content samples that contained animal materials or whose contents were unknown were selected. Rapidly digested food resources such as amphibians cannot be confirmed visually in gastrointestinal contents, and even DNA may not be detected. Therefore, multiple samples were pooled and analysed because the target DNA may not be detected otherwise. The rectal faeces and gastric contents were divided into five (S1–S5) and two groups (G1–G2), respectively, based on the capture site and date of raccoons (Table 1). Each group was mixed and stored at − 20 °C until DNA extraction. Subsequent DNA analyses were performed at Bioengineering Lab. Co., Ltd. (Kanagawa, Japan).
DNA extraction
Samples (about 100 mg each) were lyophilised using a VD-250R lyophiliser freeze dryer (TAITEC, Saitama, Japan) and ground using a ShakeMaster NEO homogeniser (Bio Medical Science, Tokyo, Japan). Crude DNA was extracted from each group; then, DNA was purified using the MPure-12 Automated Nucleic Acid Purification System (MP Biomedicals, California, USA) with a MPure Bacterial DNA Extraction Kit (MP Biomedicals).
Library preparation and sequencing
Each library was prepared using two-step tailed PCR. We used the gSalamander primer, which amplifies salamander and newt 12S rRNA, as a specific primer to detect Hokkaido salamander, and the gInsect primer, which amplifies arthropod 16S rRNA, to detect Japanese crayfish (Table 5). All primers were designed by Bioengineering Lab. Co., Ltd.
Table 5 Primer sets used in this study.
Full size table

The first PCR amplified the target region using gSalamander and gInsect. These reactions were conducted in a final volume of 10 μl, comprising 2 μl DNA template, 0.5 μl each primer (10 μM), 0.1 μl Ex Taq HS (5 U/µl) (Takara Bio Inc., Shiga, Japan), 1.0 μl 10 × Ex Taq buffer, 0.8 μl dNTP mixture (2.5 mM), and 5.1 μl sterile distilled water. The PCR conditions were: first denaturation for 2 min at 94 °C, followed by 35 cycles of 30 s at 94 °C, 30 s at 50 °C, and 30 s at 72 °C, and final extension for 5 min at 72 °C.
The second PCR used the first PCR products as the template with index primers (2ndF and 2ndR). These reactions were conducted in a final volume of 10 μl, as described for the first PCR. The PCR conditions were: first denaturation for 2 min at 94 °C, followed by 12 cycles of 30 s at 94 °C, 30 s at 60 °C, and 30 s at 72 °C, and final extension for 5 min at 72 °C. At each step, PCR products were purified using the Agencourt AMPure XP system (Beckman Coulter, Inc., California, USA). The library concentrations were measured with a Synergy H1 microplate reader (BioTek) and a QuantiFluor dsDNA System (Promega). Library quality was assessed using a Fragment Analyser (Advanced Analytical Technologies, Iowa, USA) with a dsDNA 915 Reagent Kit (Agilent, California, USA). Paired-end sequencing (2 × 300 bp) was conducted on the Illumina MiSeq platform (Illumina, California, USA).
Data analysis
Reads that began with a sequence that completely matched the primer used were extracted using the fastq_barcode_splitter tool in the FASTX-Toolkit; then, the primer sequence was trimmed. The reads were trimmed and filtered using the Sickle tool with a quality value of 20; then, trimmed and paired-end reads with fewer than 150 bases were discarded. The remaining reads were merged using the FLASH paired-end merge script35 under the following conditions: fragment length after merge, 300 bases; read fragment length, 230 bases; and minimum overlap length, 10 bases. The UCHIME2 algorithm within USEARCH was used to check all filtered sequences for chimeric sequences36. All sequences that were not judged to be chimeras were used for further analysis. The UPARSE algorithm within USEARCH was used for OTU creation and taxonomic assignments. The constructed OTUs were subjected to Basic Local Alignment Search Tool (BLASTN) searches. More than 100 reads and the top BLAST hit with a sequence identity of ≥ 97% were used to assign species (target length: about 300 bp) to each representative sequence37.
Additional analyses of COI region
S–2, S–3, G–1, and G–2 sample group DNA was successfully extracted using gSalamander or gInsect primers (Table 1) and analysed by PCR using COI and blocking primers for raccoon (Table 5). The library was prepared using two-step tailed PCR. The first PCR amplification using the primer set 1st-IntF and 1st-HCOmR was conducted in a final volume of 10 μl, comprising 2 μl DNA template, 5 μl of each primer (10 μM) (forward primer 0.5 µl, reverse primer 0.5 µl, blocking primer 4 µl), 0.08 μl Ex Taq HS (5 U/µl), 1.0 μl 10 × Ex Taq buffer, 0.8 μl dNTP mixture (2.5 mM), and 1.12 μl DDW. The PCR conditions were as follows: first denaturation for 2 min at 94 °C, followed by 35 cycles of 30 s at 94 °C, 15 s at 67 °C, and 30 s at 52 °C and 30 s at 72 °C, and final extension for 5 min at 72 °C. Subsequent methods were as described above, except for the FLASH paired-end merge script (fragment length after merge, 310 bases; read fragment length, 225 bases).
Stable isotope analysis
Stable isotope ratios of muscle tissue reflect the diet over the previous few weeks to one month38,39. We used the muscles of raccoons captured from April to August and assumed that the stable isotope ratios in raccoon muscle samples reflected their diet from March to July, i.e. late winter to early summer, in Hokkaido.
Raccoon muscle and potential prey item samples were dried at 60 °C for  > 24 h and then ground with a mortar and pestle. Potential food items (such as amphibians and crustaceans) were collected from the forest. The raccoon muscle and potential prey item samples were rinsed with a 2:1 chloroform: methanol solution to remove lipids and then dried at 60 °C for at least 24 h40. Each sample (1.0–3.0 mg) was enclosed in a tin cup and combusted in an elemental analyser (Vario MICRO cube, Elementar Gmbh, Hanau, Germany) interfaced with an isotope ratio mass spectrometer (IsoPrime100, Elementar Gmbh). We determined the δ13C, δ15N, and δ34S values for each sample. The results are reported as parts per thousand of the isotopes relative to a standard. For δ13C, δ15N, and δ34S values, Vienna Pee Dee Belemnite, air, and Vienna Cañon Diablo Triolite were used as standards, respectively. We used L-alanine (Shoko Science Co., Ltd., Tokyo, Japan) and sulfanilamide (Elementar GmbH) as working standards. A working standard, sulfanilamide (δ34S value, − 1.92‰), was calibrated against IAEA (International Atomic Energy Agency, Vienna, Austria) silver sulfides, IAEA-S-1, IAEA-S-2, IAEA-S-3, and was used as a working standard for δ34S.
Statistical analysis
We performed two-way analysis of variance to examine the interactions between two independent variables, season (spring: April–June vs. summer: July–August) and capture site (around the farmland vs. in the forest), and their relationship with the dependent variables (stable isotope ratio; δ13C, δ15N, and δ34S). After examining interactions between two independent variables (season and capture site), a Mann–Whitney U test was conducted. Differences were considered statistically significant at P  More

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To the Editor — A wildlife consumption ban, which China enacted in February as a response to the COVID-19 pandemic, has been welcomed by most conservationists as a step towards avoiding a future outbreak of zoonotic diseases1. There are dissenting voices against this ban, arguing that wildlife generates multiple benefits for people who co-exist with wild species2. While both schools of thought have their own valid arguments, neither has yet to actively lobby for the free, prior and informed consent or consultation of the people who will be directly affected by conservation decisions related to COVID-19.

Throughout the years, indigenous peoples and local communities (IPLCs) have been seen as either culprits of biodiversity decline or as ‘unseen sentinels’ effectively managing and monitoring their territories, which are often highly biodiverse3. This polarized view of IPLCs signals a prevailing lack of understanding of their way of life, where most of their dependence on nature is on a subsistence level. Wildlife consumption is often an essential part of their diets. A blanket ban on wildlife consumption may, therefore, exacerbate food insecurity in these communities. In other cases, IPLC wildlife consumption is more than just for subsistence. It may also have cultural roots and should be respected in that regard. Calling for education campaigns to ‘discredit engrained cultural beliefs’ that lead to wildlife consumption ignores the dynamics of cultural development and would most likely fail to conserve wildlife or fail to prevent another zoonotic disease outbreak4. What is needed is to craft bottom-up solutions together with the IPLCs directly depending on wildlife and to learn from their nuanced understanding of nature.

Through creating opportunities and spaces for dialogue, governments and institutions can involve IPLCs in setting guidelines for wildlife consumption. They can adopt the dialogue approach employed by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), where IPLCs engage in knowledge exchange with technical experts and government representatives5. The dialogue, through parallel contributions of indigenous, local, scientific and practical knowledge, can enhance the understanding of wildlife consumption6. Governments and institutions can tap into the network of non-governmental organizations (NGOs) that closely collaborate with IPLCs and have them facilitate these dialogues. They need to listen carefully to IPLCs, learn from their customary protocols on wildlife use and consumption, and draft laws that could potentially prevent another zoonotic disease outbreak without jeopardizing the livelihoods and well-being of IPLCs. Likewise, IPLCs and civil society can continue to build on processes of self-strengthening and assert themselves in spaces where they can proactively engage in efforts to raise awareness and understanding of traditional wildlife consumption practices. These multiple stakeholders must work together to co-craft potential solutions to this global yet also very local concern of wildlife consumption and its connection to zoonotic diseases.

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Affiliations

Center for Development Research (ZEF) Bonn, University of Bonn, Bonn, Germany
Denise Margaret S. Matias

Institute for Social-Ecological Research (ISOE), Frankfurt am Main, Germany
Denise Margaret S. Matias

Non-Timber Forest Products Exchange Programme (NTFP-EP) Asia, Quezon City, Philippines
Eufemia Felisa Pinto & Diana San Jose

Non-Timber Forest Products Exchange Programme (NTFP-EP) India, c/o Keystone Foundation, Kotagiri, India
Madhu Ramnath

Authors
Denise Margaret S. Matias

Eufemia Felisa Pinto

Madhu Ramnath

Diana San Jose

Contributions
D.M.S.M. conceptualized and drafted the Correspondence. E.F.P. and D.S.J. provided input. M.R. reviewed the Correspondence.
Corresponding author
Correspondence to Denise Margaret S. Matias.

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Competing interests
The authors declare no competing interests.

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Matias, D.M.S., Pinto, E.F., Ramnath, M. et al. Local communities and wildlife consumption bans. Nat Sustain (2020). https://doi.org/10.1038/s41893-020-00662-7
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Site description and soil sampling
The experiment was established as part of the EFForTS project (Ecological and socioeconomic Functions of tropical lowland rainForest Transformation Systems) in the Jambi province, located in Sumatra, Indonesia8.
The experimental sites are located in the state-owned oil palm plantation PTPNVI, which was planted in 2002 (Fig. 1). All planted palms were derived from Tenera seedlings, which are a crossing between Dura and Psifera palms, supplied by Marihat (Medan, Indonesia). Four different locations (referred to as OM1-4) harbor four treatments, which were established in November 2016. In each of these 16 plots (50 × 50 m), five subplots were randomly established, resulting in 80 samples total.
Fertilizer treatment was conducted in two intensities: for one application the conventional treatment usually used in the entire plantation with 130 kg nitrogen, 25 kg phosphorus and 110 kg potassium ha−1 and reduced fertilization with 68 kg nitrogen, 8.5 kg phosphorous and 93.5 kg potassium ha−1. Additionally, liming was conducted in all plots with equal amounts (213 kg dolomite and 71 kg micromag (micronutrients) ha−1). Fertilizer application and liming was done twice per year. The herbicide treatment used 375 cm3 glyphosate ha−1 sprayed within the palm circle four times per year and 375 cm3 glyphosate ha−1 in inter-rows applied twice per year15. The last application before sampling was done in April 2017. Mechanical weeding was done by cutting vegetation four times per year within the palm circle and two times per year in interrows with a brush cutter. The combination of these applications resulted in four different treatments: conventional fertilization with herbicide spraying (ch), conventional fertilization with mechanical weeding (cw), reduced fertilization with herbicide spraying (rh) and reduced fertilization with mechanical weeding (rw) (Table 1).
Topsoil was sampled in May 2017 with a soil corer from the upper seven centimeters in each subplot with a diameter of five cm. A soil corer was used to take three cores in each subplot with a distance of 1 m to each other and at least 1 m distance to trees. The three bulk soil samples per subplot were homogenized and coarse roots and stones were removed. To prevent nucleic acids, especially RNA, from degradation RNAprotect Bacteria Reagent (Qiagen, Hilden, Germany) was applied in a ratio of 1:1. For measurements of soil parameters, we collected an additional sample, which was not supplemented with RNAprotect solution. All samples were transported in cooling boxes and stored at −80 °C until further use.
Nucleic acid extraction
Frozen samples were thawed on ice. RNAprotect was removed from all samples by centrifuging for 20 min at 804.96 g and 4 °C and discarding the resulting supernatant. DNA and RNA were co-extracted from 1 g of soil by using the Qiagen RNeasy PowerSoil Total RNA kit and the RNeasy PowerSoil DNA Elution kit as recommended by the manufacturer (Qiagen), except that RNA was eluted with 50 µl elution buffer instead of 100 µl. DNA contamination was removed from RNA preparations by using the TurboDNAfree kit (Applied Biosystems, Darmstadt, Germany). For this purpose, 0.1 volume DNAse buffer and 1 µl DNAse were added and incubated for 30 min at 37 °C. Subsequently, a second digestion cycle was performed with 0.5 µl DNAse at 37 °C for 15 min. RNA was then purified with the RNeasy MiniElute Cleanup kit (Qiagen). In order to verify complete DNA removal, a control amplification of the 16 S rRNA gene was performed as described below for 16 S rRNA gene amplification. Purified RNA was then reverse-transcribed into cDNA with the Superscript IV reverse transcriptase and a specific primer (5′-CCGTCAATTCMTTTGAGT-′3) as recommended by the manufacturer (Thermo Fisher Scientific, Schwerte, Germany). After cDNA synthesis, we removed residual RNA by adding 1 µl RNase H (New England Biolabs, Frankfurt am Main, Germany) to each reaction and incubation for 20 min at 37 °C. Obtained DNA and cDNA were stored at −20 °C until further use.
16 S rRNA gene amplification and sequencing
For amplification of 16 S rRNA sequences, we used 16 S rRNA gene primers targeting the V3-V4 region (forward primer: S-D-Bact-0341-b-S-17 5′-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG-CCTACGGGNGGCWGCAG-3′, reverse primer: S-D-Bact-0785-a-A-21 5′-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG-GACTACHVGGGTATCTAATCC-3′) as described by Klindworth22 and Herlemann23 and added adapters for MiSeq sequencing (underlined). PCR reactions were performed in a total volume 50 µl containing 10 µl of 5-fold Phusion GC buffer, 0.2 µl 50 mM MgCl2 solution, 2.5 µl DMSO, 200 µM of each of the four deoxynucleoside triphosphates and 1 U of Phusion High-Fidelity DNA Polymerase (Thermo Fisher Scientific). We used 20 to 30 ng of DNA and 1 µl cDNA per reaction. The PCR reaction was started by an initial denaturation at 98 °C for 1 min, followed by 25 cycles of denaturation at 98 °C for 45 s, annealing at 60 °C for 45 s and elongation at 72 °C for 30 s. The final elongation was at 72 °C for 5 minutes. Amplicons were then purified by using MagSi-NGS PREP Plus magnetic beads following the procedure recommended by the manufacturer (Steinbrenner Laborsysteme GmbH, Wiesenbach, Germany) with the Janus Automated Workstation from Perkin Elmer (Perkin Elmer, Waltham Massachusetts, USA). Illumina MiSeq sequencing adapters were attached to the purified amplicons with the Nextera XT Index kit (Illumina, San Diego, USA). The Index PCR was done by using 5 µl of template PCR product, 2.5 µl of each index primer, 12.5 µl of 2x KAPA HiFi HotStart ReadyMix and 2.5 µl PCR grade water. Thermal cycling scheme was as follows: 95 °C for 3 min, 8 cycles of 30 s at 95 °C, 30 s at 55 °C and 30 s at 72 °C and a final extension at 72 °C for 5 min. The indexed products were purified as described before. Products were quantified by using the Quant-iT dsDNA HS assay kit and a Qubit fluorometer following the instructions of the manufacturer (Invitrogen GmbH, Karlsruhe, Germany). Purified amplicons were sequenced by the Göttingen Genomics Laboratory with a MiSeq instrument with a read length of 2 × 300 bp using dual indexing and reagent kit v3 (600 cycles) as recommended by the manufacturer (Illumina).
Sequence processing
We obtained 6,817,019 amplicon sequences with 5,183,993 remaining sequences after quality-filtering from DNA samples. At RNA level 6,412,838 raw sequences with 3,601,637 remaining sequences after quality-filtering were obtained24.
Obtained paired-end sequences were first quality-filtered with fastp version 0.2025 using a minimum phred score of 20, a minimum length of 50 bases, the default sliding window size (–cut_window_size = 4), read correction by overlap (option “correction”), adapter removal of the sequencing primers (option “adapter_fasta”), and the provided index sequences of Illumina. Quality-filtered paired-end reads were merged with PEAR version 0.9.11 and default settings26. Primer sequences were clipped with cutadapt version 2.5 and default settings27. All further steps, except mapping of sequences to ASVs (Amplicon Sequence Variant) were performed with functions implemented in vsearch version 2.1.4.128. Sequences were filtered by size with “sortbylength” with a set minimum length of 300 bp. Dereplication of identical sequences was done by “derep_fulllength”. Denoising and removal of low abundant sequences with less than eight replicates were done with the vsearch UNOISE3 module “cluster_unoise”. Chimeric sequences were removed by employing the UCHIME module of vsearch. This included a de novo chimera removal (“uchime3_denovo”) and a reference-based chimera removal (“uchime_ref”) against the SILVA SSU 138 NR database29. Sequences were mapped to ASVs by vsearch (“usearch_global”) with a set sequence identity threshold of 0.97. Taxonomy assignments were performed with BLASTN30 (version 2.9.0) against the SILVA SSU 138 NR database29 with an minimum identity threshold of 90%31. In addition to the taxonomy identity, we added the taxonomy id of the database, length of fragment, query percentage identity, query coverage and e-value in the taxonomy string of the table. We used identity (pident) and query coverage (qcovs) per ASV of the blast output to exclude uncertain blast hits. As recommended by the SILVA ribosomal RNA database project32, we removed the taxonomic assignment for blast hits if dividing the sum of percent identity and percent query coverage by 2 resulted in ≤93%. In total, 31,987 ASVs were used for downstream analysis.
Bacterial community analysis
The bacterial community composition was further analysed in R33 (version 3.6.1) and RStudio34 (version 1.1.463). ASV counts were normalized by using the Geometric Mean of Pairwise Ratios (GMPR) of the GMPR package version 0.1.335. Community compositions were then analysed by the ampvis2 package version 2.4.11 and “amp_heatmap” at genus level36. The fifteen most abundant genera were displayed as relative abundance and clustered at treatment level. Heat-trees were displayed by the metacoder37 package (version 0.3.2.9001).
For heat-tree calculation all counts were summed at order level and all taxa with a relative abundance of More

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