Breeding range shift of the red-crowned crane (Grus japonensis) under climate change

RESEARCH ARTICLE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change Liwei Liu1☯, Jishan Liao2☯, Yongbo Wu3, Yinlong ZhangID1* 1 Collaborative Innovation Center of Sustainable Forestry in Southern China of Jiangsu Province, Nanjing Forestry University, Nanjing, P.R. China, 2 Faculty of Forestry, University of Toronto, Toronto, ON, Canada, 3 College of Biology and the Environment, Nanjing Forestry University, Nanjing, Jiang Su, P.R. China ☯ These authors contributed equally to this work. * ecoenvylz@163.com Abstract The red-crowned crane (Grus japonensis) is an endangered species listed by International Union for Conservation of Nature (IUCN) HARRIS J (2013). The largest population of this species is distributed mainly in China and Russia, which is called continental population SU L (2012)–Curt D (1996). This population is migratory, which migrates from its breeding range located in Northeast China and Southern Russia, to the wintering range in the south of China to spend the winter every year. The breeding range of this species is critical for red- crowned crane to survive and maintain its population. Previous studies showed the negative effects of habitat loss and degradation on the breeding area of red-crowned crane Ma Z (1998), Claire M (2019). Climate change may also threat the survival of this endangered species. Previous studies investigated the impacts of climate change on the breeding range or wintering range in China Wu (2012), [1]. However, no study was conducted to assess the

potential impacts of climate change on the whole breeding range of this species. Here, we used bioclimatic niche modeling to predict the potential breeding range of red-crowned crane under current climate conditions and project onto future climate change scenarios. Our results show that the breeding range of the continental population of red-crowned crane will shift northward over this century and lose almost all of its current actual breeding range. The climate change will also change the country owning the largest portion of breeding range from China to Russia, suggesting that Russia should take more responsibility to pre- serve this endangered species in the future. Introduction The red-crowned crane (Grus japonensis) is among the largest and rarest cranes in the world [2]. It has great cultural value in China as it is the symbol of luck, longevity and fidelity. Histor- ically, this species was distributed widely in the eastern Asia. However, the range of this species contracted and its population declined greatly over last centuries, reaching lowest number in the 1950s [3,4]. Although the number of red-crowned cranes is increasing in the recent years due to great conservation efforts, the population size of this endangered species is still low [5,3]. Red-crowned crane has been listed as first-class national key protected wild animal in China [6]. It is also listed as an endangered species by IUCN [7]. This species is distributed PLOS ONE PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 1 / 16 a1111111111 a1111111111 a1111111111 a1111111111

a1111111111 OPEN ACCESS Citation: Liu L, Liao J, Wu Y, Zhang Y (2020) Breeding range shift of the red-crowned crane (Grus japonensis) under climate change. PLoS ONE 15(3): e0229984. https://doi.org/10.1371/ journal.pone.0229984 Editor: Bi-Song Yue, Sichuan University, CHINA Received: June 4, 2019 Accepted: February 19, 2020 Published: March 12, 2020 Peer Review History: PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here: https://doi.org/10.1371/journal.pone.0229984 Copyright: © 2020 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All relevant data are within the manuscript and its Supporting Information files. Funding: This project was supported by National Key R&D Program of China (2016YFC0502704) and Priority Academic Program Development of

mainly in five countries: Russia, Mongolia, China, Korea and Japan. The populations in Russia, Mongolia, China and Korea are migratory, while the population in Japan is non-migratory because abundant food is available [8,9]. The entire migratory population of the red-crowned crane, which is also called continental population, breeds in the Siberia (eastern Russia), north- eastern China and northeastern Mongolia (Amur-Heilong River basin) in the spring and sum- mer, from March to September. The largest portion of the continental population inhabits the lower and middle part of Amur-Heilong River basin in China [7,6,2]. The remaining continen- tal population breeds in grass marshlands of the Zeya-Bureya and Middle Amur-Heilong plain, Ussuri River valley, Khanka Lake in the Russian part of the Amur-Heilong River basin [3]. In the autumn, the continental population of red-crowned crane migrates to its wintering range, such as Korea and east-central China, to spend the winter [10]. The anthropogenic habitat change, such as development of agriculture, urbanization, and conversion of wetland to human-built area, and increasing of captive red-crowned cranes har- vested from the wild in China, have caused a significant decline of the population and loss of habitats of the red-crowned crane [2,5,3,4,11]. As a result, the breeding and wintering ranges of red-crowned crane has been shrunk to a relatively small range (Fig 1). This species prefers to nesting in wetlands and river floodplains [2,12,13]. The conversion of wetlands to agricul-

ture lands and built areas threats the nesting area of the red-crowned crane [3]. In the winter- ing range, the red-crowned cranes prefer to inhabit in paddy fields, grassy tidal flats, mudflats and rivers, which means that it has very strict habitat preferences [6,4,14]. Therefore, this spe- cies is prone to suffer risk from habitat modification and loss resulting from anthropogenic environmental change. In addition to threats from human-induced habitat modification and loss, climate change may further threat endangered species [15–19]. Some studies have already showed that birds track their niches by moving along climate change [20–23]. Climate change may shift both breeding and wintering ranges of the red-crowned crane out of its current ranges. The possible contraction of breeding and wintering ranges as a result of climate change, and the incapability of the red-crowned crane to track its climatic niche, could threaten future survival of this endangered bird species [24]. It is of societal importance to predict the potential shift of the red-crowned crane’s breeding range in the face of climate change. Climate change may cause the loss of effectiveness of the current protected area made mainly for this endangered species [25], such as Zhalong National Natural Reserve and Yancheng Biosphere Reserve. In this study, we only consider the breeding range of the continental migratory populations. Policy makers do not necessarily consider the potential effects of climate change on the ranges of endangered species when planning the pro-

tection areas for them [26–29]. The populations of red-crowned crane may move out of the current protected area designed for it when climate changes, which jeopardizes the effective- ness of the protected area. Because the breeding range of continental population of the red- crowned crane is distributed along the border of China, Russia and Mongolia, climate change may also cause some populations move northward to Russia and Mongolia, which thereby changes the role of each country for preserving this endangered species. Therefore, predicting range shifts of red-crowned crane under changing climate will contribute greatly to policy making process regarding preservation of this endangered species. Previous studies used ecological niche modeling, which relates the occurrence of a species to environmental variables considered to determine the distribution of this species, to predict the impacts of climate change on global biodiversity of birds [30–32]. Ecological niche model- ing was also used to predict the geographic distribution of the red-crowned crane under cli- mate change [33,34]. However, these studies focused mainly on a single country. For example, Wenjun et al. used Maximum Entropy (MaxEnt) [35], a powerful and popular ecological niche modeling technique, and a variety of variables to predict the effects of climate change on PLOS ONE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 2 / 16 Jiangsu Higher Education Institutions (PAPD).

There was no additional external funding received for this study. Competing interests: The authors have declared that no competing interests exist.

the breeding range of this species in China [33]. It predicted the contraction of the breeding range of red-crowned crane in China. But it failed to provide information on whether Russia or Mongolia gain some potential suitable habitats under changing climate. This limitation makes these studies incapable of providing information to guide the policy making for con- serving this important endangered species, especially in the international collaboration setting. Here, we used Maxent [35–37], to predict the shift of the breeding range of the continental migratory population of the red-crowned crane under changing climate. Methods The breeding range of the continental population of the red-crowned crane is distributed in the Siberia (eastern Russia), northeastern China and northeastern Mongolia (Amur-Heilong River basin) (Fig 1). However, there is no adequate occurrence point data available at this broad scale for building bioclimatic niche models. We obtained the extent of occurrence poly- gons of continental population of Red-crowned crane from AMUR-HEILONG RIVER BASIN Information Center (http://amur-heilong.net/http/03_species/0309Redcrowned_crane.html). We digitized and georeferenced those polygons using ArcGIS 10.2 [38]. We then converted the occurrence polygon data to lattice data to generate the pseudo-occurrence points of red- crowned crane, because Maxent can only use point data. Each point represents a grid of 5�5 Fig 1. Predicted breeding range of the continental population of the red-crowned crane at 2030s, 2050s, 2070s and 2080s [标注到

图上]. Blue polygons are the current actual breeding area, green polygons are the predicted potential breeding area under current climate condition, and orange areas are the predicted potential breeding area climate change. Scenario is RCP2.6, low emission scenario. https://doi.org/10.1371/journal.pone.0229984.g001 PLOS ONE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 3 / 16

(GCMs) used in IPCC 5th report. For emission scenarios, we used all four representative con- centration pathways (RCPs), i.e. RCP 2.6 (low emissions), RCP 4.5 (intermediate emissions), RCP 6 (intermediate emissions), and RCP 8.5 (high emissions). Those four RCPs are named based on how much heating they would produce in the year 2100–2.6, 4.5, 6.0, and 8.5 watts per square meter (W/m2), respectively [43]. The monthly maximum temperature, monthly minimum temperature and monthly total precipitation from GCMs were statistically down- scaled based on delta method. The 19 bioclimatic variables were then calculated from tempera- ture and precipitation variables (http://ccafs-climate.org/downloads/docs/Downscaling-WP- 01.pdf). For climate model, we chose HadGEM2-ES (Hadley Global Environment Model 2— Table 1. Bioclimatic variables. Abbreviation Description Bio_1 Annual Mean Temperature Bio_2 Mean Diurnal Range (Mean of monthly (max temp—min temp)) Bio_3 Isothermality (BIO2/BIO7) (� 100) Bio_4 Temperature Seasonality (standard deviation �100) Bio_5 Max Temperature of Warmest Month Bio_6 Min Temperature of Coldest Month Bio_7 Temperature Annual Range (BIO5-BIO6) Bio_8 Mean Temperature of Wettest Quarter Bio_9 Mean Temperature of Driest Quarter Bio_10 Mean Temperature of Warmest Quarter Bio_11 Mean Temperature of Coldest Quarter Bio_12 Annual Precipitation Bio_13 Precipitation of Wettest Month Bio_14 Precipitation of Driest Month Bio_15 Precipitation Seasonality (Coefficient of Variation) Bio_16 Precipitation of Wettest Quarter Bio_17 Precipitation of Driest Quarter

Bio_18 Precipitation of Warmest Quarter Bio_19 Precipitation of Coldest Quarter https://doi.org/10.1371/journal.pone.0229984.t001 PLOS ONE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 4 / 16

Earth System), which accounted for more climate change processes and included dynamic vegetation [44]. The spatial resolution of both current and future climate data is 5�5 arc-min- utes. The model output from HadGEM2-ES is average on 30 years centered at 2030s (2020– 2049), 2050s (2040–2069), 2070s (2060–2089), and 2080s (2070–2099) before downscaling. We used Maximum Entropy (MaxEnt) [35], which is one of the most popular and powerful modeling technique for predicting distribution of species [45]. For parameter settings, we used default parameter in MaxEnt. We used 10-fold cross validation to assess model performance. Data are divided randomly into 10 subsets with equal sample size. Then nine subsets of the data were used to train model, and the remaining one subset was used to test model perfor- mance. We used area under the receiver operating characteristic (ROC) curve (AUC) to assess our model [46]. The AUC value ranges from 0 to 1. Higher AUC value means greater discrimi- nant ability of bioclimatic niche model. Model evaluation was performed on the average AUC of the 10 cross validation runs. For each cross validation run, we chose the threshold which maximize the sum of sensitivity and specificity to convert the predicted suitability binary map (presence and absence). This threshold is equivalent to that from maximizing true skill statistic (TSS), which is recommended as a good measure for the performance of ecological niche model when predictions are binary maps [47]. We summed together the 10 binary maps from

10 fold cross validation models. We then set the areas where the grid value larger than 5 (i.e. areas where at least 6 models predicted the presence of this species) as the presence area for the continental population of the red-crowned crane. Variable importance measures the relative importance of environmental variables in deter- mining the distribution of species in a niche model. Two measurements of variable importance can be calculated in MaxEnt software: percent contribution and permutation importance [37]. Percent contribution depends on the particular path to get to the optimal solution and a differ- ent algorithm could result in different percent contribution values, therefore we did not use it in this study. Permutation importance measure depends only on the final MaxEnt model [37]. The importance for each variable is determined by randomly permuting the values of that vari- able in the training dataset and measuring the resulting decrease in training AUC, and normal- ized to percentages. A larger decrease indicates that that variable is more important in the model. The ranking of relative importance can help us find out which variables are more important in affecting the distribution of the red-crowned crane, and assessing the potential effects of changing of those variables under climate change on the breeding range of the red- crowned crane. To assess the effects of human activities in breeding range of the continental population of the red-crowned crane, we used human influence index as an indicator of intensity of human

activities. The human influence index was calculated from nine global data layers including human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). The dataset is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN) (available at http://sedac.ciesin.columbia.edu/data/set/wildareas-v2-human-influence-index- geographic). The value of human influence index ranges from 0 to 64, higher value means heavier human activities in this raster cell. Results The average test AUC for the 10 fold cross validation runs is 0.943, and the standard deviation is 0.004. The high AUC value means our models can predict the distribution of the breeding range of the continental population of the red-crowned crane very well. The low standard PLOS ONE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 5 / 16

deviation means the performance of 10 models from 10 fold cross validation is consistent. The predicted current breeding range area is much larger than the actual breeding range of the continental population of the red-crowned crane, suggesting that other factors such as food resource, nesting preference and human built area restrict the breeding range of this species (Fig 1). It is interesting that there are also some suitable breeding areas in the western China and western Mongolia, where is far from the actual breeding area. The overall spatial patterns of the changes of projected breeding area under all four emis- sion scenarios are very consistent under changing climate (Figs 1 and S1, S2 and S3). The breeding range of the continental population of the red-crowned crane will expand northward when project onto future climate change scenarios from our bioclimatic niche modeling. The predicted potential breeding range from our bioclimatic niche model would be contracted as climate change (Figs 1 and S1, S2 and S3). The current actual breeding area is mainly distrib- uted in the center part of Northwest China and along the national border shared by eastern part of Northwest China and Southern Russia. As a result of climate change, the breeding area of continental population would shift to the region along the national border shared by north- ern part of Northwest China and Southern Russia (Figs 1 and S1, S2 and S3). The migratory population of the red-crowned crane, therefore, needs to move northward to track its biocli-

matic niche. There are still some differences among projections of four emission scenarios. The major difference among predictions under the four emission scenarios is that the predic- tions of 2030s, 2050s and 2080s under low emission scenario (RCP2.6) are relatively stable. In addition, the predictions of 2030s, 2050s, 2070s and 2080s under two intermediate emission scenarios (RCP4.5 and RCP 6.0) and high emission scenario (RCP8.5) show that the breeding area would move farther north. We only show RCP2.6, the low emission scenario, in the main text (Fig 1). The latitudinal pattern of projected breeding area of the red-crowned crane by calculating the number of grid cells in 0.5 arc-degree band demonstrated that the breeding area of the con- tinental population of red-crowned crane shift northward under all four RCPs (Fig 2). The current actual breeding area of the red-crowned crane distributes from 43 arc-degree to 54 arc-degree and peaks around 50 arc-degree (Fig 2A). Under the low emission scenario— RCP2.6, the projected breeding areas in 2030s, 2050s, 2070s and 2080s are very similar and peak at 52 arc-degree, suggesting that the breeding area would be stable after 2030s from pre- dictions of our bioclimatic niche model (Fig 2A). The latitudinal patterns of the projected breeding area under RCP4.5 for 2050s, 2070s and 2080s are similar but the size of breeding area would shrink gradually (Fig 2B). The breeding area at 2080s under RCP6.0 is peaking at 55 arc-degree. There are two peaks of breeding area at 2080s under RCP8.5, i.e. 52 degree and

56 degree. The accelerating climate change under higher emission scenario will cause the breeding area of red-crowned crane move farther north. The total number of grid cells predicted to be breeding area of the continental population of the red-crowned crane under RCP2.6 increases at 2030s, and decreases sharply at 2050s, and then increase slightly (Fig 3A). The total number of grid cells under the two intermediate emission scenarios–RCP4.5 and RCP6 maintains the similar pattern of change, it increase at the first, and then decreases afterward (Fig 3B and 3C). The grid number of the predicted breeding area under the high emission scenario—RCP8.5, decreases quickly after 2050s to only half of the number under current climate condition (Fig 3D). The number of predicted grid cells of breeding area of the continental population of the red-crowned crane in both China and Mongolia decreases generally as climate changes over the time periods (Fig 3). For Russia, the number of grid cells predicted to be breeding area for the red-crowned crane under RCP4.5, RCP6.0 and RCP8.5 increases at first and then decreases under changing climate. The number of grid cells in Russia at the end of this century under RCP 2.6, RCP4.5 and RCP6.0 is PLOS ONE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 6 / 16

higher than the number of predicted grids under current climate condition. However, under the high emission scenario—RCP8.5, it is slightly lower than current prediction. Our results suggest that the high emission scenario has more adverse effects on breeding range of the con- tinental population of the red-crowned crane. The proportion of predicted breeding area of the continental population of the red- crowned crane in China, decreases at the first and increases afterward under RCP2.6 and RCP4.5, and decreases continuously under RCP6.0 and RCP8.5 (Fig 4). But the proportion of grid cells under future climate is lower than that under current climate condition in China. The proportion of predicted grid cells in Russia, however, increases at first and decreases after- ward under RCP2.6 and RCP4.5, and increases continuously under RCP6.0 and RCP8.5 (Fig 4). The proportion of grid cells under future climate is larger than that under current climate condition in Russia. Mongolia owns smallest proportion of grid cells of breeding area, and Fig 2. Latitudinal pattern of predicted breeding range area (Bandwidth = 0.5 degree). https://doi.org/10.1371/journal.pone.0229984.g002 PLOS ONE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 7 / 16

decreases under almost all emission scenarios. Our results revealed that China, which owns the largest breeding area currently, will lose most of its breeding area for the red-crowned crane. Russia, which has the second largest breeding area, will gain more breeding area in the face of climate change and would have the largest breeding area. It also means that Russia would have more responsibility to preserve this endangered species in this century. Fig 3. The number of grid cells predicted to be breeding area of the continental population of the red-crowned crane in China, Russia and Mongolia. a. low emission scenario–RCP2.6, b. intermediate scenario–RCP4.5, c. intermediate scenario–RCP6.0, d. high emission scenario–RCP8.5. https://doi.org/10.1371/journal.pone.0229984.g003 PLOS ONE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 8 / 16

We also calculated the proportion of grid cells predicted to be breeding area in the current actual breeding range of the red-crowned crane. The results show that the predicted grid cells suitable for breeding area in current actual breeding range from our model decrease very quickly in the near future under all climate change scenarios (Fig 5). Under the high emission scenario—RCP8.5 and the intermediate emission scenario—RCP6.0, the red-crowned crane would lose almost all of its actual breeding range at the end of this century. The situation is bet- ter under the low emission scenario—RCP2.6 and the intermediate emission scenario— RCP4.5. The continental population of the red-crowned crane would still have approximately 15% of its current actual breeding range at 2080s. At the center of this century, our model pre- dicts the lowest area of suitable breeding area in current actual breeding range under RCP2.6 and RCP4.5. Under the intermediate emission scenario—RCP6.0, the red-crowned crane will Fig 4. Proportion of breeding area in China, Russia and Mongolia. a. low emission scenario–RCP2.6, b. intermediate scenario– RCP4.5, c. intermediate scenario–RCP6.0, d. high emission scenario–RCP8.5. https://doi.org/10.1371/journal.pone.0229984.g004 PLOS ONE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 9 / 16

still have approximately 30% of its actual breeding range at the center of this century, which suggests that this emission scenario has less adverse effects on this species. The average of relative importance of variable from our 10 cross-validation bioclimatic niche models shows that the most important variable is bio_15 (precipitation seasonality) (Fig 6). The AUC value decreases by approximately 30% after removing the effects of this variable in the models. The possible explanation of the highest importance of precipitation seasonality could be that this variable determines the vegetation cover patterns and food resources in this area. The second most important variable is Bio_4—temperature seasonality. The third most important variable contributing to bioclimatic niche models is Bio_13—precipitation of wet- test month. The wettest month is the growing season for plant in the breeding range. It is also the breeding period for the red-crowned crane. Therefore the change of precipitation patterns and increasing temperature along with climate change would cause the shift of breeding range of this species. Fig 5. Proportion of grid cells predicted to be breeding area in the actual breeding range. https://doi.org/10.1371/journal.pone.0229984.g005 PLOS ONE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 10 / 16

The mean value of human influence index in current actual breeding range of the continen- tal population of the red-crowned crane is 14.4 (Fig 7). The average human influence index in predicted breeding area from our model is slightly higher than that of actual breeding range, which is 14.7. Our bioclimatic niche model predicts a much larger potential breeding area around the current actual breeding range. Because the Northeast China is one of the main grain production regions, and populated 0.107 billion people, the broader climatic-suitable breeding area predicted from our model may suffer from human activities such as urbaniza- tion, agriculture production, and habitat degradation. The center part of the Northeast China has many big cities and high population density. These factors restrict the red-crowned crane from inhabiting in all suitable breeding range under current climate condition. As a result of climate change, the breeding area of the red-crowned crane will shift north- ward from current actual breeding range, where the population density is lower than that of current breeding area, and has less agricultural lands. Under the low emission scenario— RCP2.6, the intermediate emission scenario—RCP4.5, and the high emission scenario— Fig 6. Relative importance of variables in bioclimatic niche model. https://doi.org/10.1371/journal.pone.0229984.g006 PLOS ONE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 11 / 16

RCP8.5, the average of human influence index in the predicted breeding area maintains the similar pattern of change, decreasing quickly and then increasing slightly at the end of this cen- tury (Fig 7). The average human influence index under those three emission scenarios ranges from 7 to 9 at 2080s, much lower than the value in current actual breeding area. However, the average human influence index in breeding area under the intermediate emission scenario— RCP6.0 decreases continuously, and has the lowest value of 6 at the end of this century. This is because our model predicts that the breeding area will shift farther northward, and the main breeding area distributes around 54 arc-degree, where there is less human activity. Discussion Our results demonstrated that bioclimatic niche modeling can predict the current breeding range of the continental population of the red-crowned crane very well. The excellent perfor- mance of the bioclimatic niche model makes us confident on the reliability of the prediction of future potential breeding range of red-crowned crane under changing climate. However, there are many other environmental factors such as food resource, nesting preference, land use, and Fig 7. Average human influence index in actual breeding area and predicted breeding area under climate change. (Error bars show 95% confidence interval of average human influence index). https://doi.org/10.1371/journal.pone.0229984.g007 PLOS ONE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change

PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 12 / 16

land cover, and biotic factors such as competition and predation restrict the red-crowned crane to fill all its climatic niche space. At large spatial scale, the climate is the most important factor shaping the breeding range of the red-crowned crane. Among 19 bioclimatic variables, the temperature seasonality (Bio4) and precipitation seasonality (Bio15) are the top two vari- ables in determining the breeding range of the red-crowned crane. It suggests that the climate change, which results in spatial shift of seasonality of temperature and precipitation, would cause the shift of the breeding range. There are many threats on the red-crowned crane in the breeding range, and affect the extent of breeding range. The population has been severely declined because of habitat modifi- cation, pollution and poaching [4,11,48]. Although the population was slightly increased after implementing the conservation policy made for this endangered species, and building pro- tected area for it, such as Zhalong National Natural Reserve and Yancheng Biosphere Reserve, the population size is still very low, estimated at 2,750 [3,49]. Therefore it is under severe extinction risk from environmental change, especially the unprecedented climate change. Cli- mate change would cause poleward shift of breeding range of the red-crowned crane. Some studies have already shown that some bird species extend their ranges northwards under cli- mate change [23]. Climate change also affected the phenology of the red-crowned crane,

which affected the adaptation capacity of this species [50,51]. Climate change also has indirect effects on the red-crowned crane, for example, one study showed that climate change altered the animal-plant interactions and thereby affected bird and plant communities [52]. The effects of climate change on the red-crowned crane and its breeding range, therefore, should be taken into consideration when making preservation policy for this endangered species. The predicted shift of the breeding range of the red-crowned crane under changing climate from our bioclimatic niche models suggests that China would lose a proportion of the breeding range, Russia would gain some breeding range area. This effect might be overestimated, because the red-crowned crane has adaptation potential to climate change. Our model also neglected other abiotic and biotic factors affecting the breeding range of the red-crowned crane and the prediction accuracy of range shift in the face of climate change. This impact means that the role of conserving this endangered species would be changed, because the pro- portion of the breeding area in China, Russia and Mongolia would be changed. The area of breeding range in China would be shrunk as climate changes. The effectiveness of the pro- tected area in China, therefore, would be jeopardized in the future. The increasing area of the breeding range in Russia and Mongolia means these two countries would take more responsi- bility to conserve this endangered species. However, the conservation policy in each country is

different and does not necessarily consider the effects of climate change on the breeding range of this species. The international collaboration among the three countries would increase the conservation effectiveness of this species under climate change. Some studies showed that international collaboration can benefit the birds in Europe [53]. Supporting information S1 Fig. Predicted breeding range of the continental population of the red-crowned crane at 2030s, 2050s, 2070s and 2080s. Blue polygons are the current actual breeding area, green polygons are the predicted potential breeding area under current climate condition, and orange areas are the predicted potential breeding area climate change. Scenario is RCP4.5, intermediate emission scenario. (DOC) S2 Fig. Predicted breeding range of the continental population of the red-crowned crane at 2030s, 2050s, 2070s and 2080s. Blue polygons are the current actual breeding area, green PLOS ONE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 13 / 16

polygons are the predicted potential breeding area under current climate condition, and orange areas are the predicted potential breeding area climate change. Scenario is RCP6.0, intermediate emission scenario. (DOC) S3 Fig. Predicted breeding range of the continental population of the red-crowned crane at 2030s, 2050s, 2070s and 2080s. Blue polygons are the current actual breeding area, green polygons are the predicted potential breeding area under current climate condition, and orange areas are the predicted potential breeding area climate change. Scenario is RCP8.5, high emission scenario. (DOC) Author Contributions Conceptualization: Yinlong Zhang. Data curation: Liwei Liu, Yongbo Wu. Formal analysis: Jishan Liao. Funding acquisition: Yinlong Zhang. Methodology: Liwei Liu, Jishan Liao, Yongbo Wu. Project administration: Yinlong Zhang. Software: Jishan Liao. Supervision: Yinlong Zhang. Validation: Liwei Liu, Jishan Liao. Visualization: Liwei Liu, Jishan Liao. Writing – original draft: Liwei Liu, Jishan Liao. Writing – review & editing: Liwei Liu, Jishan Liao, Yinlong Zhang. References 1. Kim HG, Lee EJ, Park C, Lee KS, Lee DK, Lee WS, et al. Modeling the habitat of the red-crowned crane (Grus japonensis) wintering in Cheorwon-gun to support decision making. Sustain. 2016; https://doi. org/10.3390/su8060576 2. Johnsgard PA. Cranes of the World: Japanese Crane (Grus japonensis). Cranes of the World, by Paul Johnsgard. 1983. p. 21. 3. Mirande Claire M.; Harris James T.. Crane Conservation Strategy. Baraboo, Wisconsin, USA: Minute- man Press; 2019.

4. Archibald GW, Meine CD, Garcia EFJ. Red-crowned Crane (Grus japonensis). In: del Hoyo J., Elliott A., Sargatal J., Christie D.A. & de Juana E. (eds.). Handbook of the Birds of the World Alive. Lynx Edicions, Barcelona; 2019. 5. Ma Z, Wang Z, Tang H. History of Red-crowned Crane Grus japonensis and its habitats in China. Bird Conserv Int. 1998; https://doi.org/10.1017/S0959270900003592 6. SU L, ZOU H. Status, threats and conservation needs for the continental population of the Red-crowned Crane. Chinese Birds. 2012; 3: 147–164. https://doi.org/10.5122/cbirds.2012.0030 7. HARRIS J, MIRANDE C. A global overview of cranes: status, threats and conservation priorities. Chi- nese Birds. 2013; https://doi.org/10.5122/cbirds.2013.0025 8. Masatomi Y, Higashi S, Masatomi H. A simple population viability analysis of Tancho (Grus japonensis) in southeastern Hokkaido, Japan. Popul Ecol. 2007; https://doi.org/10.1007/s10144-007-0048-2 9. Secretariat of the Special Committee on Crane Conservation WBS of J. Conservation strategy of the red-crowned crane in Hokkaido, Japan. Strix. 1986; PLOS ONE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 14 / 16

10. Higuchi H, Shibaev Y, Minton J, Ozaki K, Surmach S, Fujita G, et al. Satellite tracking of the migration of the red-crowned crane Grus japonensis. Ecol Res. 1998; https://doi.org/10.1046/j.1440-1703.1998. 00271.x 11. Zhou D, Xia X, Xu W, Zhang H, Qian Z, Gao J, et al. A growing captive population erodes the wild Red- crowned Cranes (Grus japonensis) in China. Avian Res. 2016; https://doi.org/10.1186/s40657-016-0056-z 12. Meine Curt D; Archibald George W.. The cranes : status survey and conservation action plan. IUCN, Gland, Switzerland, and Cambridge, U.K.; 1996. 13. Heim W, Trense D, Sokolova G V., Kitagawa T. Increased Populations of Endangered Cranes After Amur River Flood. Waterbirds. 2017; https://doi.org/10.1675/063.040.0309 14. Liu C, Jiang H, Zhang S, Li C, Hou Y, Qian F. Multi-scale analysis to uncover habitat use of red-crowned cranes: Implications for conservation. Curr Zool. 2013; 59: 604–617. https://doi.org/10.1093/czoolo/59. 5.604 15. Pacifici M, Foden WB, Visconti P, Watson JEM, Butchart SHM, Kovacs KM, et al. Assessing species vulnerability to climate change. Nat Clim Chang. 2015; 5: 215–225. https://doi.org/10.1038/ nclimate2448 16. Radchuk V, Reed T, Teplitsky C, van de Pol M, Charmantier A, Hassall C, et al. Adaptive responses of animals to climate change are most likely insufficient. Nat Commun. 2019; https://doi.org/10.1038/ s41467-019-10924-4 PMID: 31337752 17. Ba´ lint M, Domisch S, Engelhardt CHM, Haase P, Lehrian S, Sauer J, et al. Cryptic biodiversity loss

linked to global climate change. Nat Clim Chang. 2011; 1: 313–318. https://doi.org/10.1038/ nclimate1191 18. Thomas CD, Cameron A., Green R.E., Bakkenes M., Beaumont L.J., Collingham Y.C., et al. Extinction risk from climate change. Nature. 2004; 427pp145-8: 145–148. Available: http://eprints.whiterose.ac. uk/83/1/thomascd1.pdf https://doi.org/10.1038/nature02121 PMID: 14712274 19. Pacifici M, Visconti P, Butchart SHM, Watson JEM, Cassola FM, Rondinini C. Species’ traits influenced their response to recent climate change. Nat Clim Chang. 2017; 7: 205–208. https://doi.org/10.1038/ nclimate3223 20. Tingley MW, Monahan WB, Beissinger SR, Moritz C. Birds track their Grinnellian niche through a cen- tury of climate change. Proc Natl Acad Sci U S A. 2009; 106 Suppl: 19637–19643. https://doi.org/10. 1073/pnas.0901562106 PMID: 19805037 21. Barbet-Massin M, Thuiller W, Jiguet F. The fate of European breeding birds under climate, land-use and dispersal scenarios. Glob Chang Biol. 2012; https://doi.org/10.1111/j.1365-2486.2011.02552.x 22. Thuiller W, Pironon S, Psomas A, Barbet-Massin M, Jiguet F, Lavergne S, et al. The European func- tional tree of bird life in the face of global change. Nat Commun. 2014; 5. https://doi.org/10.1038/ ncomms4118 PMID: 24452245 23. Thomas CD, Lennon JJ. Birds extend their ranges northwards. Nature. 1999; 399: 213. Available: http://dx.doi.org/10.1038/20335 24. Devictor V, Van Swaay C, Brereton T, Brotons L, Chamberlain D, Helio¨lo¨ J, et al. Differences in the cli-

matic debts of birds and butterflies at a continental scale. Nat Clim Chang. 2012; 2: 121–124. https:// doi.org/10.1038/nclimate1347 25. Arau´jo MB, Alagador D, Cabeza M, Nogue´ s-Bravo D, Thuiller W. Climate change threatens European conservation areas. Ecology Letters. 2011. pp. 484–492. https://doi.org/10.1111/j.1461-0248.2011. 01610.x PMID: 21447141 26. Hoffmann M, Shi Y, Hughes A, Bernard C, Brooks T, Bertzky B, et al. Protected Areas and Effective Bio- diversity Conservation. Science (80-). 2013; 342: 803–805. https://doi.org/10.1126/science.1239268 PMID: 24233709 27. Batllori E, Parisien MA, Parks SA, Moritz MA, Miller C. Potential relocation of climatic environments sug- gests high rates of climate displacement within the North American protection network. Glob Chang Biol. 2017; https://doi.org/10.1111/gcb.13663 PMID: 28211141 28. Pimm SL, Jenkins CN, Li B V. How to protect half of earth to ensure it protects sufficient biodiversity. Sci Adv. 2018; 4: 1–9. https://doi.org/10.1126/sciadv.aat2616 PMID: 30167461 29. Hoffmann S, Irl SDH, Beierkuhnlein C. Predicted climate shifts within terrestrial protected areas world- wide. Nat Commun. 2019; 10: 4787. https://doi.org/10.1038/s41467-019-12603-w PMID: 31636257 30. Jetz W, Wilcove DS, Dobson AP. Projected impacts of climate and land-use change on the global diver- sity of birds. PLoS Biol. 2007; 5: 1211–1219. https://doi.org/10.1371/journal.pbio.0050157 PMID: 17550306 31. Mirzaei R, Hemami MR, Sari AE, Rezaei HR, Peterson AT. Using ecological niche modeling to deter-

mine avian richness hotspots. Glob J Environ Sci Manag. 2017; https://doi.org/10.22034/gjesm.2017. 03.02.002 PLOS ONE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 15 / 16

32. Moradi S, Sheykhi Ilanloo S, Kafash A, Yousefi M. Identifying high-priority conservation areas for avian biodiversity using species distribution modeling. Ecol Indic. Elsevier; 2019; 97: 159–164. https://doi.org/ 10.1016/J.ECOLIND.2018.10.003 33. wei Wu W, Gu SS, Wu J, chang Cao M, cheng Lei J, gen Xu H. Impact of climate change on distribution of breeding sites of red-crowned crane in China. J Ecol Rural Environ. 2012; 28: 243–248. 34. Wenjun L, Zijian W, Zhijun M, Hongxiao T. A regression model for the spatial distribution of red-crown crane in Yancheng Biosphere Reserve, China. Ecol Modell. 1997; 103: 115–121. https://doi.org/10. 1016/S0304-3800(97)00077-X 35. Phillips S, Dudı´k M, Schapire R. A maximum entropy approach to species distribution modeling. Proc twenty-first . . .. 2004; 655–662. https://doi.org/10.1145/1015330.1015412 36. Phillips SJ, Anderson RP, Schapire RE. Maximum entropy modeling of species geographic distribu- tions. Ecol Modell. 2006; https://doi.org/10.1016/j.ecolmodel.2005.07.011 37. Phillips S. A Brief Tutorial on Maxent. AT&T Research. 2008. pp. 1–38. https://doi.org/10.4016/33172.01 38. ESRI. ArcGIS Desktop: Release 10.2. Redlands CA. 2013. 39. Andriamasimanana RH, Cameron A. Predicting the impacts of climate change on the distribution of threatened forest-restricted birds in Madagascar. Ecol Evol. 2013; 3: 763–769. https://doi.org/10.1002/ ece3.497 PMID: 23610622 40. Coetzee BWT, Robertson MP, Erasmus BFN, van Rensburg BJ, Thuiller W. Ensemble models predict

important bird areas in southern Africa will become less effective for conserving endemic birds under cli- mate change. Glob Ecol Biogeogr. 2009; 18: 701–710. https://doi.org/10.1111/j.1466-8238.2009.00485.x 41. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A. Very high resolution interpolated climate sur- faces for global land areas. Int J Climatol. Chichester; New York: Wiley, 1989-; 2005; 25: 1965–1978. https://doi.org/10.1002/joc.1276 42. Ramirez J, Jarvis A. High resolution statistically downscaled future climate surfaces. http://ccafs- climate.org/; 2008. 43. Weyant J, Azar C, Kainuma M, Kejun J, Nakicenovic N, Shukla, et al. Report of 2.6 Versus 2.9 Watts/ m2 RCPP Evaluation Panel. 2009. 44. Martin GM, Bellouin N, Collins WJ, Culverwell ID, Halloran PR, Hardiman SC, et al. The HadGEM2 fam- ily of Met Office Unified Model climate configurations. Geosci Model Dev. 2011; https://doi.org/10.5194/ gmd-4-723-2011 45. Elith J, H Graham C, P Anderson R, Dudı´k M, Ferrier S, Guisan A, et al. Novel methods improve predic- tion of species’ distributions from occurrence data. Ecography (Cop). Wiley Online Library; 2006; 29: 129–151. https://doi.org/10.1111/j.2006.0906–7590.04596.x 46. Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. Radiological Society of North America; 1982; 143: 29–36. https://doi.org/10. 1148/radiology.143.1.7063747 PMID: 7063747 47. Allouche O, Tsoar A, Kadmon R. Assessing the accuracy of species distribution models: Prevalence,

kappa and the true skill statistic (TSS). J Appl Ecol. 2006; 43: 1223–1232. https://doi.org/10.1111/j. 1365-2664.2006.01214.x 48. Sun K-J, Hijikata N, Ichinose T, Higuchi H. The Migration Flyways and Protection of Cranes in China. Global Environmental Research ©2015 AIRIES. 2015. 49. Fawen QIAN Guohai YU, Youzhong YU, Jun YANG, Siliang PANG, Renzu PIAO HJ. Survey of breed- ing populations of the Red-Crowned Crane (Grus japonensis) in the Songnen Plain, northeastern China. Chinese Birds. pp. 217–224. 50. Both C, Bouwhuis S, Lessells CM, Visser ME. Climate change and population declines in a long-dis- tance migratory bird. Nature. 2006; 441: 81–83. https://doi.org/10.1038/nature04539 PMID: 16672969 51. Both C, Visser ME. Adjustment to climate change is constrained by arrival date in a long-distance migrant bird. Nature. 2001; 411: 296–298. https://doi.org/10.1038/35077063 PMID: 11357129 52. Martin TE, Maron JL. Climate impacts on bird and plant communities from altered animal-plant interac- tions. Nat Clim Chang. Nature Publishing Group; 2012; 2: 195–200. https://doi.org/10.1038/ nclimate1348 53. Donald PF, Donald PF, Sanderson FJ, Sanderson FJ, Burfield IJ, Burfield IJ, et al. International conser- vation policy delivers benefits for birds in Europe. Science (80-). 2007; 317: 810–813. https://doi.org/10. 1126/science.1146002 PMID: 17690296 PLOS ONE Breeding range shift of the red-crowned crane (Grus japonensis) under climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0229984 March 12, 2020 16 / 16