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Large-Scale Quantification of Vertebrate Biodiversity in Ailaoshan

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Large-Scale Quantification of Vertebrate Biodiversity in Ailaoshan bioRxiv preprint doi: https://doi.org/10.1101/2020.02.10.941336; this version posted February 11, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 Large-scale Quantification of Vertebrate Biodiversity in 2 Ailaoshan Nature Reserve from Leech iDNA 1,* 2,*,** 1,2 3,4 3 Yinqiu Ji , Christopher CM Baker , Yuanheng Li , Viorel D Popescu , Zhengyang 2 1 5,6 1 7 7 4 Wang , Jiaxin Wang , Lin Wang , Chunying Wu , Chaolang Hua , Zhongxing Yang , Chunyan 1 8 7 2,** 1,9,10** 5 Yang , Charles CY Xu , Qingzhong Wen , Naomi E Pierce , and Douglas W Yu 1 6 State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, 32 Jiaochang 7 Dong Lu, Kunming, Yunnan 650223 China 2 8 Department of Organismic and Evolutionary Biology, Harvard University, 26 Oxford Street, Cambridge 9 MA 02138 USA 3 10 Department of Biological Sciences and Sustainability Studies Theme, Ohio University, Athens OH 45701 11 USA 4 12 Center for Environmental Studies (CCMESI), University of Bucharest, Bucharest, Romania 5 13 Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of 14 Sciences, Mengla 666303, China 6 15 Center of Conservation Biology, Core Botanical Gardens, Chinese Academy of Sciences, Mengla 666303, 16 China 7 17 Yunnan Institute of Forest Inventory and Planning, 289 Renmin E Rd, Kunming Yunnan 650028 China 8 18 Redpath Museum and Department of Biology, McGill University, 859 Sherbrooke Street West, Montreal, 19 PQ H3A2K6 Canada 9 20 Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 21 Yunnan, 650223 China 10 22 School of Biological Sciences, University of East Anglia, Norwich Research Park, Norwich, Norfolk 23 NR47TJ, UK * 24 These authors contributed equally to this work. ** 25 Corresponding authors. CCMB: [email protected]; NEP: [email protected]; 26 DWY: [email protected] 27 Keywords: environmental DNA, metabarcoding, occupancy, leeches, China, monitoring, 28 conservation, biodiversity 29 1 Abstract 30 Environmental DNA (eDNA) has great potential to complement visual surveys, camera 31 trapping, and bioacoustics in measuring biodiversity. We report here a large-scale attempt 32 to use DNA from leech-ingested bloodmeals to estimate vertebrate occupancy at the scale 2 33 of an entire protected area: the 677 km Ailaoshan national-level nature reserve in Yunnan 34 province, southwest China. We contracted 163 park rangers to collect leeches in 172 pa- 35 trol areas, resulting in 30,468 total leeches, divided over 893 replicate samples. Replicate 36 sampling from each patrol area was achieved by providing rangers with preservative-filled 37 tubes in separate, self-sealing bags, inducing them to distribute collected leeches over mul- 38 tiple bags, which we could sequence separately. We show that combining leech-derived 39 DNA data with Bayesian site-occupancy modeling can produce detailed and useful biodi- 40 versity inferences for a wide range of vertebrates in a reasonable timeframe. For example, in 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.02.10.941336; this version posted February 11, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 41 Ailaoshan, sites at lower elevations and closer to the reserve edge have higher occupancy of 42 domestic species (cows, sheep, goats) compared to sites at higher elevations and closer to the 43 reserve interior. Muntjak deer show similar occupancy patterns to the domesticated species, 44 but otherwise, most species of large mammal wildlife (e.g. sambar, black bear, serow, tufted 45 deer) show the opposite pattern: greater occupancy at higher elevations and closer to the 46 reserve interior. We conclude that leech-derived eDNA can be used to efficiently measure 47 the effectiveness of protected areas in terms of vertebrate biodiversity outcomes and to help 48 us optimize the deployment of management resources within reserves, by providing valuable 49 information on the spatial distributions of vertebrate species and on the environmental and 50 anthropogenic correlates of those distributions. 51 ¯境DNA (eDNA) (生i多7'Ä0¹bw有极'的\力, 可以与现有的生i多7'监K 52 ¹法, 如目ÆGK法、¢外ø:监K法, 生i声f监K法Ib成互e. ,研v首!)(蚂 53 WeDNA(sÎ蚂W8食的@²-Ð取的DNA) ùM于-国西Wè云W省的哀bq国¶ê6 54 保¤:进L了一*h@的脊椎¨i多7'的Ä0. (,研v-, 677s¹l里的保¤:«划 55 分成172*á;:, 1163M¤林X(áÆÇ程-ÇÆ了;q30468ê蚂W, 这些蚂W9nÇÆ 56 7¹, ÇÆ时间ÊwSpÏ«合v成了893份7,. 我们将蚂WeDNApn和贝叶¯M¹`n 57 !型ø结合, 分析¨­得0(一定时间范围内哀bq脊椎¨i各iÍ的wS分布图1. 例如, 58 哀bqw拔较NÊ`近保¤:¹缘的0:, ø较于w拔较高Ê`近保¤:-Ã的0:, w有 59 更多的[, 羊I¶{¨i; (Î生iÍ-, d麂H现了与¶{¨i{<的分布趋¿, 而v它' 60 型ús¨i(如4鹿、黑熊、Ïè羚) 则øÍ, (w拔较高Ê`近保¤:-Ã的:域分布更 61 多. ,研v的结果>:ú于蚂W的eDNA技/可以Ð供s于脊椎¨iiÍ的z间分布以ʯ 62 境和º{;¨ù这些iÍ分布的qÍI有价<的áo, ©我们可以ndÄ0保¤:ù脊椎¨ 63 i多7'的保¤H率, Î而可以.©优化保¤:内¡理D源的èr. 64 2 Introduction 65 The difficulty of measuring the effectiveness of protected areas. In 2010, the signatories 66 of the Convention on Biological Diversity, including China, agreed to the 2011-2020 Aichi 67 Biodiversity Targets [6]. Aichi Target 11 concerns the safeguarding of biodiversity and sets 68 the goals of placing (A) 17% of terrestrial and inland water habitats in a system of nature 69 reserves that are (B) ecologically representative, (C) well-connected, (D) equitable, and 70 (E) effective. The world has nearly achieved goal A, with 15% of global land area now 2 71 under national jurisdiction [13, 71]. China has to date also placed 15% (1.43 million km ) 72 of its land surface into nature reserves [78, 9]. Moreover, Wu et al. [76] have shown that, 73 at least in western China, the reserve system covers most ecoregions, biodiversity priority 74 areas, and natural vegetation types (goal B), and Ren et al. [52] have used time-series 75 analyses of Landsat imagery to show that China's national-level nature reserves successfully 76 prevent deforestation (goal E). China has therefore already demonstrated some considerable 77 institutional capacity for achieving Aichi Target 11. 78 However, in southern and eastern China, the ecological representativeness of reserves is 79 low (goal B) [77], many reserves are isolated (goal C) [76], there is little information on 80 the impact of the reserves on local human populations (goal D) and, most importantly, 81 we know little about whether the reserves are effective at protecting the species that live 82 inside them (goal E). Our focus in this study is thus goal E, reserve effectiveness, because 83 if reserves cannot protect their existing biodiversity endowments, the other four goals do 2 bioRxiv preprint doi: https://doi.org/10.1101/2020.02.10.941336; this version posted February 11, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 84 not matter [34, 22, 71, 5, 13]. We further focus on vertebrates (mammals, birds, amphib- 85 ians, and reptiles), because one of the most important threats to vertebrate populations 86 in China is overexploitation [79], which is undetectable using remote sensing methods, and 87 thus especially difficult to measure. 88 Here, we ask if it is possible to design efficient, repeated, direct, granular, understandable, 89 and auditable metrics of vertebrate-biodiversity statuses. While indirect measures, such 90 as reports of staffing and budget levels [13] and expert-opinion surveys [34] can be used 91 to estimate the aggregate status of reserves at broad spatial scales, we also need regularly 92 updated (repeated) assessments of vertebrate populations themselves (direct and granular) 93 in order to structure management incentives (e.g. job promotions) and thereby to increase 94 and maintain management effectiveness. Moreover, it should be possible for these metrics 95 to be checked in a rigorous way and thus validated by neutral third parties such as courts 96 and the public (auditable and understandable), which is necessary for dispute resolution. 97 Finally, because management resources are limited, such metrics should be cost-effective 98 (efficient) [20, 80, 16]. 99 Emerging technologies for surveying vertebrate biodiversity at broad spatial scales. Ad- 100 vances in and increased availability of technologies such as camera traps, bioacoustics, and 101 environmental DNA (eDNA) allow for broad-scale biodiversity monitoring, via direct and 102 auditable vertebrate-biodiversity metrics that complement current Earth Observation tech- 103 nologies (e.g. satellite remote sensing of land-cover change) [10]. In particular, camera traps 104 (and increasingly, bioacoustics) have shown great promise in developing biodiversity indica- 105 tors that meet the requirements of the Convention for Biological Diversity for broad-scale 106 biodiversity monitoring [2, 5, 35, 49, 74, 24]. However, the costs of buying and deploying 107 camera traps and bioacoustic devices places limitations on the area that they can be used 108 to monitor. For example, Beaudrot et al. [5] recently reported that multi-year camera-trap 109 surveys of 511 populations of terrestrial mammals and birds in fifteen tropical-forest pro- 110 tected areas did not detect \systematic declines in biodiversity (i.e. occupancy, richness, or 2 111 evenness)." However, each of their camera-trap sets sampled between 140 to 320 km , which 112 is only 1-2% of the area of the largest parks in their dataset, the obvious reason being the 113 difficulty and expense of setting up a camera-trap network to cover large, difficult-to-access 114 areas, exacerbated by theft and vandalism in some contexts [46, 24].
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