Contribution of citizen science towards cryptic species census: “many eyes”define wintering range of the Scaly-sided Merganser in mainland China

Background

Achieving accurate biological patterns across broad spatial extents requires novel approaches for acquiring, integrating, and analyzing diverse observational data at large scales (Wood et al. 2011). Citizen science has been remarkably successful in advancing scientific knowledge (Bonney et al. 2009), improving natural resources management and environmental protection through informing policymaking and fostering public input and engagement (McKinley et al. 2017). Citizen science projects covered a breadth of topics. Citizen-based contributions to mainstream scientific investigations are becoming increasingly important. For instances, searching for a ladybug species thought to have gone extinct(Losey et al. 2007), examining the distribution change of bird species over time and space (Bonter and Harvey 2008), and detecting the arrival and distribution of invasive plant species (Bois et al. 2011). Most citizen science schemes are found in Europe, North America, South Africa, India, and Australia (Chandler et al. 2017), while it started development in China through birdwatching societies and activities, and has contributed to a greater understanding of the population status of birds(Ma et al. 2013; Hu et al. 2017). However, the majority of birdwatching records were provided by individuals in an uncoordinated way, preventing to achieve the full potential of public participation in bird conservation. An organization that integrates and standardizes these local efforts would be advantageous and desirable. Given this,the China Birdwatching Association (CBA) was launched in July 2014 aiming to connect all the bird watching societies in China in a network, and to facilitate the sharing of experience, birding information, education material and conservation news within the community.

As one of the highlight programs, CBA organized the National Wintering Survey of Scaly-sided Merganser(Mergus squamatus) for successive three winters (2014,2015 and 2016). The Scaly-sided Merganser, also called Chinese Merganser, is an endemic species restricted to east Asia. It is listed as endangered worldwide (IUCN 2017). In China, M. squamatus is listed as afirst-class key protected wild animal. The species is of great conservation concern as it is suspected to be undergoing a continuing and rapid decline due to dam construction,illegal hunting and logging (EAAFP 2015). Furthermore,it is designated as fagship species for freshwater biodiversity conservation and represents a key indicator for assessing wetland ecosystem quality (Zeng et al. 2017).M. squamatus breeds in southeast Russia and northeast China. The entire population is estimated to be around 4660 individuals based on the breeding survey (Solovyeva et al. 2014). However, the total number of wintering birds counted (c. 400) on rivers and fresh water bodies in southern and central China is only a small portion of the total population. The ten-fold gap between breeding and wintering populations revealed that the location of majority of the wintering population is unknown (Barter et al. 2014; Solovyeva et al. 2014), representing a major conservation predicament for this endangered species.However, there are several obstacles for conventional scientific study to accurately define its wintering range.First, the species is widely dispersed in rivers, lakes and reservoirs of central and southern China, with small numbers in Japan, Korean peninsula, and southeast Asia(IUCN 2017), requiring large manpower for a systematic survey. Second, this duck is shy and easily startled (Zeng et al. 2015a), making it hard to be located. Third, the birds are not very social, and focks of more than 10 are very rare (He et al. 2006). Citizen science, with its “many eyes”, could be an effective way (Dickinson et al. 2012)tofind and locate this cryptic and rare diving duck. The three national-scale campaigns might collect suffcient data and information to advance the scientific understanding in its ecology, and to improve its conservation and management (Wood et al. 2011). This study explored these potentials.

对称矩阵在消元计算过程中有的一个很特别、但一直被忽视的特点：即规格化之前，第i行对角元以右元素与第i列对角元以下元素数值相等、位置对称；规格化之后，第i行对角元以右元素与第i列对角元以下元素只相差一个对角元的比例系数，位置仍然对称。因此在因子表的形成过程中，可仅计算对角元素和上三角元素，而下三角元素可按列通过规格化前的上三角元素赋值得到，从而省去大量下三角元素的计算及相应的除法计算，大大加快因子表的形成速度。

In this paper, we summarized and reported on the 3-year national surveys. The main objective of the study was to use citizen science to infer the wintering range of M. squamatus and the overlap and shift of its distribution area, which could be strategically applied to improve our understanding of spatial and temporal distributions of waterbirds.

Methods

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

A total of 2019 people took part in the surveys. Most of the participants were from 102 bird watching societies,universities and institutes, or relevant organizations with basic background offield work and bird watching. All volunteer observers were trained to identify M. squamatus, especially from Common Merganser (M. merganser)or Red-breasted Merganser (M. serrator). The connection of ecological process is used to define “site”, e.g., a river section between two dams, or a reservoir with closed boundary. In thefirst year, the sites were based on historical distribution, and stretched to adjacent river sections or reservoirs, with consideration of site condition(hydrology, land cover, anthropogenic disturbance, etc.)during the survey. In the following years, surveyed sites were improved according to the last year’s situation.

The National Wintering Survey of M. squamatus was conducted during the weekends in late December to early January when the wintering population of the duck is mostly stable (Zeng et al. 2015a). Effective monitoring requires that data collection ensures a relatively high probability of detecting the target species (e.g. Conway 2011). Considering the weather conditions and available time of volunteer observers, a strict synchronous survey at national scale is quite diffcult due to large numbers of participants and geographic range. Each group could confirm their preferred survey date based on a suggested time periods. Allfield surveys were conducted on clear days, avoiding snowy, rainy, or strong windy days. Each team was comprised of at least three observers, who walked along the river or travelled by car/boat, and used binoculars to identify and locate M. squamatus. A GPS receiver was used to record the location and as the GPS logged coordinates corresponding to the location of the observers, not the actual position of the ducks, we used GoogleEarth to plot the precise coordinates. The ducks resting on land or foraging in water were also recorded.To avoid repeat counting, only birds fying from one direction (upper or lower reach) were counted. A photo of the species as well as the habitat ensured quality control and review of the data. Although the surveys were designed to target the Scaly-sided Merganser, observers were encouraged to record detections of other species.Supplementary information including disturbance (e.g.,number of boats that use the river section during the count period), and other relevant data from volunteers and local people were also collected during the survey.

(2)ep2 增设改签、退票窗口；不间断向旅客通报列车运行计划及正晚点情况；保障食物、水、保洁、医疗等供应；车站与公安人员共同参与治安维护；及时向上级通报事件态势变化与处置措施。

A datasheet was used with a unified format, including basic information that identifies the observer and describes how the count was conducted (start time, duration, and distance traveled), and information of birds(number, sex ratio, location, behavior), habitats (wetland types, bottom types, water depth, speed) and anthropogenic infuence (disturbance, river regulation projects).Each team was required to complete the paper form in thefield and input data later into an Excel sheet. The paper datasheet, the e-form, andfield photo were all submitted to CBA. Observers were encouraged to enter their data into the pooled web-based biodiversity citizen science database (http://www.birdreport.cn). These data are collected and organized with the same protocol, and reviewed and confirmed by experts aided byfield photos provided by volunteers.

Environmental variables

Multicollinearity of the predictor variables can not only affect the overall performance but also the estimates of variable importance in random forest models (Siroky 2009). To limit the impacts of multicollinearity, NDVI.Max and NDVI.Mean were excluded from modelfitting as they were highly correlated with NDVI.Min (Pearson’s correlation coeffcient equals to 0.78 and 0.93 for NDVI.Max and NDVI.Min, respectively).

We used three groups of 13 environmental variables(Table 1) to model the wintering distribution of M. squamatus. Group one variables, which were derived from stream network and Digital Elevation Model (DEM), are related to hydrogeomorphology. Group two variables describe human disturbances, including dam density,distance to the nearest town, distance to roads, distance to railways, and distance to the nearest protected areas.Group three variables were derived from Normalized Difference Vegetation Index (NDVI) as proxies for site productivity. The 1 km STRM30 DEM dataset was downloaded from http://srtm.csi.cgiar.org/ (retrieved on 21 July 2017); land cover was obtained from Global Land Cover database (Friedl et al. 2002); river polylines were retrieved from HydroSHEDS dataset (http://hydrosheds.cr.usgs.gov, retrieved on 21 July 2017); and NDVI for 2014, 2015 and 2016 data were obtained from the U.S.Geological Survey (USGS) Earth Resources Observation and Science Center (EROS http://LPDAAC.usgs.gov, retrieved on 24 July 2017). Protected areas shapefile was obtained from World Database on Protected Areas(WDPA, retrieved on 20 July 2017 from: http://www.protectedplanet.net).

Data analysis

Species distribution models

1.适应转型，营造良好内审环境。高校内部审计文化根植于内部审计的历史、现实和发展并体现高校内审工作的服务性、建设性以及时代性特征［3］，因此高校领导层应高度重视并加强引导，给予政策和物质上的支持，内审机构领导应在倡导审计新理念、实践审计新功能中率先垂范。内部审计工作物质条件改善提高、内部审计文化价值认识到位，才能确保其建设行动的自觉，所以既要以物质为载体对文化建设提供经费物质保障，又要对全体内审人员及其他人员开展思想动员。

Wefirst transformed the survey data into presence/absence. For each year, we developed a species distribution model (SDM) for the wintering distribution of M.squamatus using random forest. Random forest is one of most commonly used machine learning techniques in classification (Oliveira et al. 2012). Several features make random forest useful for our study. First, random forest is a non-parametric rule-based algorithm, which generally performs better than parametric methods for complex systems (Breiman 2001). Second, it can handle both nonlinearity and interactions among predictors better than generalized linear and generalized additive modelling (Oliveira et al. 2012). Furthermore, the algorithm estimates the importance of a variable by looking at how much prediction error increases when out-of-bag data for that variable is permuted while all others are left unchanged (Grömping 2009), which is very helpful to investigate the most important environmental variables in determining the presence of M. squamatus for better conservation. For each SDM, we used randomly selected85% of data points for model building and the rest for model validation. We reported three accuracy measures to evaluate predictive performance, including the area under the receiver operating characteristic (AUC), proportion correctly identified, and Kappa (VanDerWal et al.2014).

Table 1 Environmental variables used in models

Hydrogeomorphic and human disturbance variables were scaled so that the values were between 0 and 1

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Using the trained random forest models, we predicted the wintering distribution of M. squamatus for 2014,2015 and 2016. We also produced a maximum distribution range by summing up the three SDMs. The maximum distribution represents all the potentially suitable wintering habitats in mainland China.

Although many routes meander over 20 km, centroid of each route path was used to characterize site for the geographic analyses (Flather and Sauer 1996; Sauer et al.2013).

Distribution overlap and shift

We compared the distribution of M. squamatus in 3 years(i.e. 2014, 2015 and 2016) using Schoener’s D index (Schoener 1968). Schoener’s D index is a classical and reliable measure of niche overlap (Rödder and Engler 2011)widely used in ecological studies, particularly for SDM applications (Wen et al. 2015). Schoener’s D index ranges from 0 (distribution models have no overlap) to 1 (distribution models are identical) and are derived from the difference in probability distributions over space produced between two SDMs.

Data-collection methodologies affect the robustness of results (Kelling et al. 2009). When properly designed,carried out and evaluated with appropriate protocols,training and oversight, volunteers can effciently generate high-quality data equal to those collected by experts.Therefore, citizen science can provide sound science and help solve problems (Danielsen et al. 2014; McKinley et al. 2017). In a case study in Australia, strong correlations in reporting rates of bird species were found between informal area searches in locations selected by volunteers, and similar searches conducted using a formal stratified-random design (Szabo et al. 2012).Although the national-scale survey shows its supremacy on prediction of the wintering distribution of M. squamatus, we have to accept that it presents challenges of observer capability and variability that are not easily addressed (Weir et al. 2005). The small count of M. squamatus in 2014 might be due tofirst-time effect among observers, who tend to have lower counts in thefirst year they surveyed (Sauer et al. 1994; Kendall et al. 1996).And the counted number of 1138 in 2016 also indicated a gap between wintering and breeding population. It failed to reveal the real population for the deficiency of spatial coverage and temporal extent. Although the surveys covered the main watersheds, investigation coverage was relatively poor due to low manpower and large geographic area, as well as inaccessibility of some habitats, especially reservoirs. There is an increasing trend of abundance with the number of observers, while the limited data (number of surveys) prevents drawing reliable conclusions. The gap of numbers betweenfield observations and population estimate may possibly befilled in by increased survey effort and coverage of more areas,which evidenced the great contribution of citizen science to the census of cryptic species.

Results

National wintering survey

Not applicable.

Scaly-sided Mergansers were recorded wintering not only in Jiangxi, Fujian, Chongqing, and Zhejiang provinces which have been known in historical records, but also in Hunan, Henan, Anhui and Hubei provinces with relatively large numbers (Table 2). Additionally, they were also found in south-western part of China, such as Guangxi. Dozens of new wintering sites were reported and two main sites in Dabie Mountain and East Qinling mountains were verified, with populations more than 100 respectively.

研究人员将小鼠放进黑暗的箱子中，训练其通过胡须触碰来搜索附近物体。用爪子按压搜索到的物体后，小鼠可以喝到美味饮品。研究人员用激光照射小鼠大脑中负责感知信息的皮层区，使该区域细胞在一段时间内无法正常工作。这时小鼠大脑表现出与人类中风后相似的受损状况。随后，一组小鼠立即重返箱中，继续在黑暗中进行搜索物体的工作，另一组小鼠休息3天。结果发现，工作组小鼠在24小时后用胡须感知周边环境的能力逐渐开始恢复；3天静养期结束的小鼠该能力仍然未恢复，且随后的恢复速度也非常缓慢。

Species distribution model

The training modelsfitted the survey data relatively well(Table 3). All training models had AUC greater than 0.75(Table 3), and are suitable for conservation purposes according to Pearce and Ferrier (2000). Based on the Kappa coeffcients (Landis and Koch 1977), the model for 2014 wintering season was the best, having substantial predictive power, and the 2015 model was the worst,its performance was fair (Kappa coeffcient was 0.63, 0.33 and 0.56 for 2014, 2015 and 2016, respectively, Table 3).Similarly, the overall accuracy of the 2014 model was the highest (0.94, indicating 94% of the training cases were correctly predicted by the model, Table 3).

Using independent testing data (i.e. the testing data were randomly selected and were not included in model training), we verified thefitted models. The performance measures for model testing did not vary substantially from these for model training (Table 3), suggesting the stable performance of thefitted models.

(3)分析条件，寻找条件的交集，利用双轨迹作图.只需思考关于点B的条件的交集，首先，点B满足∠ABD=30°且∠ABD的两边过定点A与D，则点B的轨迹为定角轨迹；其次，点B满足AB=AC，AC是定长，则点B的轨迹为定长轨迹.因此，点B就是这两个轨迹的交点.

Distribution range overlap and shift

The predicted distributions of wintering distribution of M. squamatus in mainland China for 2014, 2015, 2016 and a maximum distribution range summed up three SDMs were presented in Fig. 2. Although there were thousands of habitat patches modelled for each year(Table 4), the patches were rather concentrated with the main distributions included in the river system of Dongting Watershed in Hunan, East Qinling mountains in Henan, Dabie Mountain in Anhui, and the river system of Poyang Watershed in Jiangxi (Fig. 2).

Fig. 1 The survey sites in winters 2014–2016. 1 Yangtze River, 2 Yellow River, 3 Huaihe River, 4 Pearl River, 5 Lancang River, 6 Liaohe River

The key landscape metrics of the predicted distribution range was reported in Table 4. Interestingly, although the number of survey sites increased year by year (138,207 and 294 for 2014, 2015 and 2016, respectively) and more birds were counted, the total number of habitat patches, the size of distribution range, and largest patch area did not increase accordingly (Table 4). The 2016 wintering distribution range was the largest, and the 2015 distribution was the smallest. In the 2014 wintering season, 5.01% of the total land (218,839 km2, 6266 habitat patches) might be occupied by M. squamatus (Table 4).In 2015 winter, 165,983 km2 (3.80% of the total land) and 6017 patches were predicted to be used by the duck. In 2016 winter, these values were 259,863 km2 (total distribution area), 5.95% (percentage of land) and 8660 (number of habitat patches).

Schoener’s D index was 0.96, 0.97, 0.99 between 2014 and 2015, 2014 and 2016, and 2015 and 2016,respectively, which indicated that the wintering range of M. squamatus was highly identical for the 3 years, especially between 2015 and 2016 (D = 0.99). The highly overlapped distribution ranges between years suggested that the wintering range of M. squamatus in mainland China were relatively stable.

患者，女，69岁，2014年5月于上海某院行“二尖瓣机械瓣瓣膜置换术”、术后服用华法林3.75 mg·d-1抗凝治疗，合用胺碘酮至出院后第10天。考虑患者的出血风险，临床对二尖瓣置换术后的患者实行的抗凝目标为INR=1.6～2.5，出院时患者INR控制在2.0左右。患者用药如前，出院后一个月复查INR维持不变。后回苏州调养并至当地心血管内科门诊复查，发现INR偏低（1.5左右），随后华法林剂量加至5 mg·d-1，INR一直没有达标，又不敢继续加量。患者出院后一直定期监测INR，且服药依从性良好，2015-01-20复查INR为1.46（外院），因 INR不达标前来我院药学门诊。

Discussion

Wintering range

Over large spatial extents, range predictions are typically derived from expert knowledge, which are useful at coarse resolution, and suitable for delineating unoccupied regions (Merow et al. 2017). Point records withspecies distribution models could providefiner-scale occurrence information, which often rely on the availability of a suffcient amount of occurrence and/or abundance data representative of the species’ distribution(Elith and Leathwick 2009). A suffciently large volume of data with relatively lower per-datum information content can contain more information for broad-scale species distribution estimates than a smaller amount of higher quality data (Hochachka et al. 2012). Normally,established large-scale monitoring programs are limited to the breeding season, and relatively few data are available about bird populations during migration and winter(Munson et al. 2010). The 3-year wintering surveys operated consistently and at broad geographic scale, contributed a great deal of information about the wintering range of M. squamatus.

产销差率是指销售水量和供给水量的比值。有研究表明，全球产销差率平均在27%左右，欧美、日本等发达国家的产销差率比较低，在10%以下。而非洲、拉丁美洲等发展中国家产销差率高，达到了40%以上[1]。

Table 2 Numbers of Scaly-sided Mergansers recorded in its main distributed provinces in three winters

Anhui 46 43 136 Chongqing 27 33 46 Fujian 41 22 19 Guangxi 17 18 11 Hunan 110 124 181 Henan 100 110 198 Hubei 49 100 246 Jiangxi No cover 121 180 Zhejiang 22 20 55 Total 441 634 1138

Table 3 Measures of the predictive performance of the random forest species distribution models

Values in parentheses are based on testing data, which are independent of the training data a Area under the receiver operating characteristic (AUC). Models with AUC values ＞ 0.75 are suitable for conservation planning (Pearce and Ferrier 2000) b OAA: Overall accuracy c Kappa coeffcient: 0–0.20, slight; 0.21–0.40, fair; 0.41–0.60, moderate; 0.61–0.80, substantial; and 0.81–1, almost perfect, according to Landis and Koch(1977)

2016 0.91 (0.87) 0.84 (0.77) 0.56 (0.47) Moderate

QZ conceived the study, contributed to the statistical analyses of the data and wrote the manuscript. QW organized the surveys and participated in thefield study, and also helped with data preparation. GL contributed to the analyses of the survey data. All authors read and approved thefinal manuscript.

Limit in wintering population estimate

Fig. 2 Modelled wintering distribution area of M. squamatus in 2014–2016, and a maximum distribution range summing up three SDMs

Table 4 Selected landscape metrics of the M. squamatus wintering distribution in central and east China for 2014, 2015,2016 and maximum distribution

Landscape metric 2014 distribution 2015 distribution 2016 distribution Total distribution No. of habitat 6226 6017 8660 12,500 Total area (km2) 218,839 165,983 259,863 517,386 Proportion (%) 5.01 3.80 5.95 11.84 Mean patch area (km2) 35.15 27.59 30.01 41.39 Largest patch area (km2) 20,287 14,795 41,894 80,880 Total core area (km2) 106,281 72,600 118,269 271,833 Core area proportion (%) 2.43 1.66 2.71 6.00 Mean core area (km2) 17.07 12.07 13.66 21.75 Max patch core area (km2) 13,903 11,392 31,010 61,170 Habitat cohesion index 9.83 9.82 9.89 9.92

Fig. 3 Comparison of modelled wintering range between the threeyear study and previous study on historical data

We used R 3.3.2 (R Development Core Team 2016) for all statistical analyses. We used the package randomForest 4.6-12 (Liaw and Wiener 2002) for distribution modelling; the package SDMTools 1.1-221 (VanDerWal et al.2014) for model evaluation; the package dismo 0.9-3 (Hijmans et al. 2015) for niche similarity statistic to quantifying distribution overlaps and shifts; and raster 2.1-25(Hijmans and Van Etten 2014) for grid data transforming,preparing and visualization.

The 3-year surveys are not long enough for accurate estimates of population size and trends. Reliable estimates of population trends will probably require ＞ 5 years(and perhaps as much as 15–20 years) of survey data(Conway and Timmermans 2005). A study in southern Ontario of US used 45 years eBird data to estimate population change of twenty-two species (Walker and Taylor 2017). Using long term data to estimate population trends would be a promising avenue for future work.Long term and more focused surveys linked with the modelled distributions, are needed to accurately estimate the wintering population and its trend.

在外来业主的带动下，村民们积极投入乡村旅游住宿接待服务。专合社将村民们家里长期空余的、愿意对外搞接待的房间一间一间统筹起来，将团队客人依次给各接待户分配客源。为了提高接待质量，专合社帮助村民统一采购床上用品，指导村民按照70或80元/间·晚⑥的标准收费。目前，星光村共有40多户，50多个房间可供住宿接待。

Conclusions

Operated consistently and at broad geographic scale,the 3-year wintering surveys contributed a great deal of occurrence and abundance data of M. squamatus at various sites across China. The highly overlapped distribution ranges between years suggested that the wintering sites of M. squamatus were relatively stable. While longterm efforts are needed to estimate population status and dynamics of wintering M. squamatus, we demonstrated that well organized and coordinated citizen science can be used to define the wintering habitats with accuracy. Organizing and engaging volunteers to collect the required data across broad scale has tremendous potential to provide information for management and conservation of natural resources in general for a range of species and habitats.

Authors’ contributions

Prior to the citizen science surveys by CBA, there were several national and regional surveys, notably the National Terrestrial Wildlife Resources Surveys organized by Chinese State Forestry Administration, and regional waterbirds surveys covering the middle and lower Yangtze and coastal regions. These surveys found that the majority of the wintering M. squamatus focks were located along the lower Yangtze River, especially in Jiangxi Province (He et al. 2002, 2006). Targeted single species surveys were later designed specifically for M.squamatus in Jiangxi Province and southern China by several institutes and research teams, and confirmed that the majority of M. squamatus wintered in Jiangxi Province (Barter et al. 2014). Many studies have been compromised by the logistical orfinancial challenge of collecting data, and large-scale surveys are most likely not feasible for one individual expert or team (Kelling et al. 2009).Citizen science with scientific research conducted, in whole or in part, by nonprofessional scientists, is an alternative and provides advantages over conventional science (Hand 2010). In addition to thefield surveys,geolocators logging (Solovyeva et al. 2012) and satellite tracking devices (Liu et al. 2014) were used to identify the wintering grounds of this species. However, these techniques were limited by either inaccuracy or small sample size, and did not delineate the entire distribution range.The 3-year citizen science surveys found that the wintering range of M. squamatus was much more widely dispersed than previous reported, and Henan, Hunan and Hubei provinces were found to support large populations. The two main sites in Dabie Mountains and East Qinling Mountains provided updated knowledge of wintering distribution of the species in these areas. And the surveys are consistent with a previous study, which used Maxent model based on historical data to predict wintering distributions (Zeng et al. 2015b). Maxent with presence-only data produced a map of occurrence probability, and a threshold was used to transfer the probability to presence/absence. Therefore, the threshold had a great effect on the distribution map. However, the random forest models used observed presence/absence data in the study area and it should be more accurate, while largely depends on the data quality. Both studies with Maxent model and random forest models suggested that rivers in Jiangxi, Hunan and Hubei provinces were highly suitable habitats for the endangered duck (Fig. 3), while the 3-year surveys define a larger wintering range. Some sections of rivers recommended to be systematically surveyed by Zeng et al. (2015b) have been visited during this study; M. squamatus were recorded on Xiangjiang River in Hunan Province, but not on Futun and Nanpu rivers in Fujian Province. More rivers ought to be included for the surveys in the future.

Author details

1 School of Nature Conservation, Beijing Forestry University, Beijing 100083,China. 2 China Birdwatching Association, Chengdu 610041, China.

不久，果然隐约听到一些传言，说我勾引良家妇女。尤其是镇政府家属院子里的女人，多是半边户，整天三个一群五个一伙挤在一块扯家常，东家长西家短，扯得最多的偷人养汉。有时我从院子里走过，明显地感觉到有眼光像刺一样扎在我背上，远远地还听到她们放荡的笑声。哎，人言可畏哟。

Acknowledgements

We would like to thank all the volunteers for their input concerning the 3-year surveys. We are also grateful to Dr. Wen Li from the Offce of Environment and Heritage, NSW and Dr. Taej Mundkur from Wetlands International for their valuable comments.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

National survey

Consent for publication

试验地设在云南省施甸县水长乡小官市村，海拔1 930 m，年降水量1 950 mm。土壤肥力中等，有机质含量为2.5%，pH值为6.2～6.5。田间宽叶酢浆草优势度达95%以上，偶有粗毛牛膝菊、尼泊尔蓼等阔叶杂草。

The three surveys covered 144, 223, 317 sites in 2014,2015 and 2016 respectively (Fig. 1). These areas included mainstreams and branches of ten major basins (Yangtze River, Yellow River, Huaihe River, Zhujiang River,Lancang River, Liaohe River, Haihe River, Luanhe River,Changhua River and rivers at southeast coast) and adjacent reservoirs. Coastal areas and major artificial rivers such as Beijing-Hangzhou Grand Canal and Rivers of South-to-North Water Diversion Project were also surveyed. The distance from the south to the north is c.2600 km and east to west is c. 2400 km. In total, 441, 634 and 1138 individuals of M. squamatus were recorded in winters of 2014, 2015 and 2016 respectively, the largest count almost 1/10–1/2 of its population size of 2400–10,000 individuals (Wetlands International 2017).

李小树怔怔地看着画稿上的许春花，大黑猫在他的肩头“喵喵”大叫两声后，就纵身跳到许春花的肖像上，它的爪子毫不留情地在画稿上留下几条划痕。

Ethics approval and consent to participate

Not applicable.

Funding

This project wasfinanced by National Key R&D Program of China (Award Number: 2017YFC0405303), SEE Foundation and National Geographic.

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