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Optimized Spatial Priorities for Biodiversity Conservation in China: A Systematic Conservation Planning Perspective

Optimized Spatial Priorities for Biodiversity Conservation in China: A Systematic Conservation... By addressing several key features overlooked in previous studies, i.e. human disturbance, integration of ecosystem- and species-level conservation features, and principles of complementarity and representativeness, we present the first national- scale systematic conservation planning for China to determine the optimized spatial priorities for biodiversity conservation. We compiled a spatial database on the distributions of ecosystem- and species-level conservation features, and modeled a human disturbance index (HDI) by aggregating information using several socioeconomic proxies. We ran Marxan with two scenarios (HDI-ignored and HDI-considered) to investigate the effects of human disturbance, and explored the geographic patterns of the optimized spatial conservation priorities. Compared to when HDI was ignored, the HDI-considered scenario resulted in (1) a marked reduction (,9%) in the total HDI score and a slight increase (,7%) in the total area of the portfolio of priority units, (2) a significant increase (,43%) in the total irreplaceable area and (3) more irreplaceable units being identified in almost all environmental zones and highly-disturbed provinces. Thus the inclusion of human disturbance is essential for cost-effective priority-setting. Attention should be targeted to the areas that are characterized as moderately- disturbed, ,2,000 m in altitude, and/or intermediately- to extremely-rugged in terrain to identify potentially important regions for implementing cost-effective conservation. We delineated 23 primary large-scale priority areas that are significant for conserving China’s biodiversity, but those isolated priority units in disturbed regions are in more urgent need of conservation actions so as to prevent immediate and severe biodiversity loss. This study presents a spatially optimized national-scale portfolio of conservation priorities – effectively representing the overall biodiversity of China while minimizing conflicts with economic development. Our results offer critical insights for current conservation and strategic land-use planning in China. The approach is transferable and easy to implement by end-users, and applicable for national- and local-scale systematic conservation prioritization practices. Citation: Wu R, Long Y, Malanson GP, Garber PA, Zhang S, et al. (2014) Optimized Spatial Priorities for Biodiversity Conservation in China: A Systematic Conservation Planning Perspective. PLoS ONE 9(7): e103783. doi:10.1371/journal.pone.0103783 Editor: Duccio Rocchini, Fondazione Edmund Mach, Research and Innovation Centre, Italy Received November 5, 2013; Accepted July 7, 2014; Published July 29, 2014 Copyright:  2014 Wu 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. Funding: This study was funded by the National Natural Science Foundation of China (No. 31260148) and the National Key Technologies R&D Program of China (No. 2011BAC09B07). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * Email: rdwu@ynu.edu.cn the minimum land area or other costs (e.g., land prices, Introduction management and opportunity costs [7]). SCP provides an Anthropogenic effects have resulted in the loss of biodiversity at operational framework for minimizing land-use conflicts between an unprecedented rate, while resources for biodiversity conserva- conserving natural environments and economic development, and tion remain constrained in terms of both human and financial thus increase the likelihood of implementing the proposed capacity [1]. That is why the systematic planning of priority areas conservation actions [3,6]. Here, we present the first national- is crucial to achieve the most cost-effective conservation, such as scale SCP study for China to determine the optimized spatial identifying large-scale biodiversity hotspots or assembling fine- priorities for biodiversity conservation. resolution portfolios of conservation priorities [2–4]. In the last two China – one of the world’s ‘‘megadiversity countries’’ – is home decades, systematic conservation planning (SCP) has emerged as to many globally valued conservation priorities [2]. However, an effective approach for identifying conservation priorities [3–6]. China’s biodiversity is under severe threat due to the increasing SCP aims to identify a network of priority areas so as to effectively pressure resulting from the country’s historically unprecedented achieve explicit conservation goals in terms of representing the full economic growth [8]. Meanwhile, China’s conservation invest- range of biodiversity and sustaining their long-term survival [5]. ment is considerably lower compared to developed and other Efficient conservation priorities can be identified through an developing countries [9]. Thus, the systematic conservation optimized planning algorithm for meeting conservation goals at PLOS ONE | www.plosone.org 1 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China priority-setting has been emphasized in China during last two Methods decades [8,10–11]. Conservation Features Mapping During this period, China has developed several templates of Considering the complexity of biodiversity and severe lack of national-scale conservation priorities, which were based principal- detailed spatial distribution data, surrogates (e.g., endangered/ ly on the species (e.g., endemic, threatened, and/or other indicator endemic species, key habitat types and environmental features) are species) richness patterns as well as expert judgments (e.g., [10,12– often used in conservation planning [3,7,16,18]. Integrating 15]). These templates are crucial in guiding China’s national-level conservation features from multiple levels can ensure the efficient conservation decisions; however, we think there are several critical representation of biodiversity [5] and compensate for limitations in limitations in previous priority-setting studies. the data [16]. In this analysis, we used both ecosystem- and First, the effects of human disturbance are not incorporated in species-level features as the surrogates. previous studies, whereas we believe explicit inclusion of human The ecosystem-level features included were: (1) priority natural disturbance in priority-setting can minimize land-use conflicts and ecosystems as defined by Li, Song & Ouyang [13], including 129 lower costs for meeting conservation goals [3,6]. Second, the natural ecosystems of forests, grasslands, meadows, deserts and scoring procedure in these studies is inefficient for achieving the wetlands, and (2) natural vegetation types derived from the goal of full representation of all biodiversity targets [16], i.e. the national 1: 1,000,000 vegetation map, including 559 natural goal for representativeness – one of the core principles for vegetation formations [19]. This study considered wetlands and designing an efficient reserve system [5]. The current scoring lakes (in the priority natural ecosystems and natural vegetation procedure requires a greater amount of land (and increases other types), but data on aquatic systems and species was lacking. We costs) to achieve the same conservation goals and these greater expected that China’s key ecological elements, processes and demands are unlikely to get support from local authorities. Third, services were covered with priority natural ecosystems and that a study designed to systematically integrate conservation features basic habitat types were represented by finer-scale classifications of at both ecosystem- and species-level is still lacking, as the natural vegetation types. The species-level features were endan- conservation features used in previous studies are either species gered species of plants, mammals, and birds. Endangered or ecosystem based. By incorporating biodiversity features from mammals and birds were identified according to China’s multiple organization levels, the resulting portfolio of conservation ‘‘National List of Key Protected Wildlife’’ and the IUCN Red priorities is more efficient in representing the full range of List Categories of critically endangered, endangered and vulner- biodiversity concerns and in maintaining the ecological integrity of able species [20]. Endangered plants were defined in the ‘‘China ecosystems [5,16]. SCP can overcome this inefficiency in scoring Plant Red Data Book: Endangered and Rare Plants’’ [21]. procedure by employing the principle of between-site comple- Previous studies often use county-level species distribution data mentarity that serves to boost the efficient representation of all derived from the published literatures [14–15], while our analysis biodiversity targets, and provide mechanisms for integrating was performed using a finer-scale resolution. For plants and human disturbance and conservation features at multiple organi- mammals, we mapped each species’ geographic range by zation levels [17]. combining its distribution data for counties, preferred habitat This study aims to determine the optimized national-scale types and elevation range. For a bird species, the range was spatial priorities in China and to ensure effectively fulfilling derived by intersecting only counties and habitat types, because biodiversity conservation goals given the constraints of human knowledge of the altitude distribution of most avian species is disturbance by implementing a SCP approach. Taiwan, Hong lacking. This mapping process included: (1) collecting each species’ Kong and Macao are not included in our analysis due to lack of attribute information, i.e. species name, taxonomy, endangered required information. Specifically, we are trying to address two category, distribution across counties, preferred habitat types, and questions: (1) How will the inclusion of human disturbance affect elevation range, (2) mapping each species’ distributions across the result of conservation priority-setting? (2) What are the counties, habitat types and elevation range, respectively, and (3) geographical patterns of the optimized conservation priorities in identifying the overlap region among these distribution layers as China? In this analysis, we integrated human disturbance, each species’ current range. conservation features at both the ecosystem- and species-level, We collected the attribute information using the following and the principles of complementarity and representativeness. We resources. For plants, we used ‘‘National Key Protected Wild Plant used the software Marxan [17] to determine each unit’s Resources Survey’’ [22] as the primary source and other conservation value and to identify priorities with regular hexagons supplementary sources including ‘‘Subject Database of China (100 km per cell) as the planning units. We investigated the effects Plants’’ [23], ‘‘China Species Information Services’’ [24] and of human disturbance using two Marxan scenarios – a disturbance ‘‘China Plant Red Data Book: Endangered and Rare Plants’’ [21]. ignored scenario and a disturbance considered scenario. For the For mammals and birds, we used ‘‘National Key Terrestrial second scenario, human disturbance was included as a penalty Wildlife Resources Survey’’ [25] as the primary source and other function by aggregating information on several socioeconomic supplementary sources including ‘‘Database of Fauna Sinica’’ proxies as an index layer. We then explored the spatial patterns of [26], ‘‘Distributions of China Mammal Species’’ [27] and ‘‘China the priority units, irreplaceable areas, and primary large-scale Red Data Book of Endangered Animals: Mammals’’ [28]. priority areas (i.e., the large clustered regions of high-conservation- The datasets on county boundaries and habitat types were value units). The analysis is limited to the data available at derived from the national 1: 1,000,000 geographic databases and national-scale and applicable resolution, and misses some the national 1: 1,000,000 vegetation map [19], respectively. The variability within the range of human disturbances. We believe elevation range for each species was extracted from the Shuttle this study is applicable to national- and local-scale conservation Radar Topography Mission (SRTM) 90 m Digital Elevation and other sustainable land-use planning for systematically Model (DEM) [29]. We mapped the species’ geographic ranges for evaluating each site’s conservation value and identifying spatially 373 plant, 115 mammal and 81 bird species. optimized priority areas. PLOS ONE | www.plosone.org 2 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China cost-effectively solve an optimization problem of representing a Human Disturbance Index Mapping suite of biodiversity targets [17]. To ensure that all conservation We used several socioeconomic proxies, including proportion of features were captured across their ranges of environmental and land converted by human use, human population density, gross genetic variations [32], we first stratified their ranges with China’s domestic product (GDP) and road density to calculate the human 53 terrestrial ecoregions [33], and then defined a quantitative disturbance index (HDI) or human footprint [4,30]. The basic conservation target for each feature per ecoregion. Due to limited planning units were regular hexagons, each sized 100 km . The data available for setting up appropriate conservation targets [34], analysis included three steps. First, we calculated an individual we defined the target for each conservation feature as a uniform HDI (IHDI) for each of these proxies. For proportion of converted percentage area of its distribution range as suggested in previous land, we calculated the IHDI as the percent area of human- studies (e.g., [3,32]). Specifically, the quantitative targets were developed-land use – including croplands, plantations, rural settlements and urban/industrial areas – within each hexagon. selected based on expert opinions as follows: 30% for endangered For human population density and GDP, we calculated the IHDIs species, 20% for priority natural ecosystems and 10% for natural as their mean values per square kilometer within each unit. For vegetation types. An internationally recognized lowest target of road density, we considered four transportation levels (i.e., railway, 10% was set for natural vegetation types because they were expressway, national-provincial road and other-level roads), and assumed to represent the variety of basic habitat types. calculated an IHDI for each level as the total road length within We ran Marxan with two scenarios – a HDI-considered each unit. Second, we normalized the data ranges of all IHDIs on scenario and a HDI-ignored scenario. For the HDI-considered a scale of from 0.00 to 1.00, and then summed them to get the scenario, we integrated HDI values as a penalty function in total HDI. Finally, we empirically transformed the data range of Marxan analysis, i.e. a unit having a higher degree of disturbance the total HDI on a scale of from 10.00 to 300.00 (Figure 1) so as to would receive a greater penalty. For the HDI-ignored scenario, we clearly demonstrate the overall human disturbance pattern. used a uniform penalty of 1.0 per unit. The units with greater HDI We obtained datasets on land uses, human population density values exhibit a more highly degraded ecological condition and and GDP from the Data Center for Resources and Environmental should offer less potential from a conservation perspective [4]. Sciences of the Chinese Academy of Sciences [31], and all are Therefore, Marxan’s algorithm sought to identify the optimized 1km61 km resolution grid files. The road networks were derived priority areas by minimizing the total HDI score in the HDI- from the national 1: 1,000,000 geographic database. considered scenario or the total land area in the HDI-ignored scenario. For the Marxan configurations, we: (1) generated 1000 Conservation Priority-setting solutions; (2) included a boundary length file and a modifier factor We used the software Marxan (v2.0.2) to implement the to control the compactness of priority areas; (3) implemented conservation priority-setting process. Marxan was developed to Simulated Annealing followed by Iterative Improvement; and (4) Figure 1. Human disturbance index (HDI). HDI was modeled by aggregating information on several socioeconomic proxies, including proportion of land converted by human use, human population density, gross domestic product, and road density. doi:10.1371/journal.pone.0103783.g001 PLOS ONE | www.plosone.org 3 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China used the default values for Number of Iterations (1,000,000) and irreplaceable area occurred principally in provinces located in the Temperature Decreases (10,000). eastern coastal region, middle-lower Yangtze River Basin and We derived the conservation value that reflects the relative northeastern China, whereas provinces in western and southwest- ern China had the fewest changes (Figure 4). Several provinces in priority or irreplaceability of each planning unit [3] from the frequency of solutions selected, and used the best of the 1,000 the eastern highly-disturbed regions (Figure 1), including Guang- dong, Jiangxi, Henan and Hebei, also were found to have small solutions as the most cost-effective portfolio of priority units. We then identified the irreplaceable units as those selected in more changes in their irreplaceable areas (Figure 4). than 800 solutions; 80% is often used for accuracy assessment for Compared to the results in the HDI-ignored scenario, the spatial data (e.g., [35]). portfolio of priority units in the HDI-considered scenario contained: (1) fewer units in the three highest HDI zones and more units in the four lower HDI zones, (2) fewer units only in the Effects of Human Disturbance lowest (,200 m) elevation zone and more units in the other six We compared the total HDI score and total area of the two zones, and (3) fewer units in the level TRI zone and more units in portfolios of priority units generated by the HDI-ignored and each of the other TRI zones (Figure 5). The HDI-considered HDI-considered scenarios, respectively. The changes in irreplace- scenario identified a greater number of irreplaceable units in able areas between the two scenarios were assessed in terms of the almost all environmental zones than did the HDI-ignored total area and the proportional area changes by province. scenario, with the sole exception of the highest HDI zone To assess the effects of human disturbance at a finer-scale, we (Figure 6). further investigated the distributions of the priority units and irreplaceable areas on different environmental zones of HDI, Spatial Patterns of Conservation Priorities elevation, and terrain ruggedness. We derived seven zones for each variable as follows: (1) We classified HDI zones by applying the We analyzed the spatial patterns of conservation priorities using Quantile Classification Scheme on HDI values; (2) We derived the outcomes from the HDI-considered scenario. The priority elevation zones from the SRTM 90 m DEM according to studies units consistently decreased with increasing HDI value (Fig- on geomorphology [36] (the elevation classification schemes were ure 5A), with the majority (,76%) located in the four lower HDI ,200, 200–500, 500–1,000, 1,000–1,500, 1,500–2,000, 2,000– zones. The ,200 m elevation zone included only 5.8% of all 4,000, and .4,000 m); (3) We calculated a terrain ruggedness priority units, and the zones of 200–1,000, 1,000–2,000 and . index (TRI) as the average difference in elevation between a center 2,000 m contained 29.6%, 25.8% and 38.8% of the priority units, cell and its eight neighboring cells using the SRTM DEM, and the respectively. The priority units generally had an increasing Quantile Classification Scheme was then used to break the TRI distribution trend on TRI zones from level to extremely-rugged values into seven terrain categories, i.e. level, near-level, slightly- terrain (Figure 5C), with the vast majority located in slightly- to rugged, intermediately-rugged, moderately-rugged, highly-rugged extremely-rugged zones, and only 3.2% identified in level zone and extremely-rugged [37–38]. and 11.5% in near-level zone. All provinces included some units that were required for meeting the conservation targets (Figure 3), with the greatest proportion occurring in Xinjiang followed by Spatial Patterns of Conservation Priorities Tibet, Inner Mongolia, Qinghai, Sichuan and Yunnan. These six Using the outputs from the HDI-considered scenario, we western provinces contained 72.5% of the total priority units. analyzed the spatial distributions of priority units and irreplaceable The irreplaceable units had a normal-like distribution on the areas on HDI, elevation, TRI zones and provinces. We then HDI zones that peaked in the fourth zone (Figure 6A). Compared delineated the primary large-scale priority areas as the large to the distribution of priority units, greater proportions of clusters of high-conservation-value planning units through an irreplaceable units were selected in lower elevation zones, with expert-based visual interpretation process. 10.7%, 39.3%, 26.7% and 23.3% of the total irreplaceable area located at ,200, 200–1,000, 1,000–2,000 and .2,000 m zones, Results respectively. In particular, the highest zone (.4,000 m) contained Effects of Human Disturbance the smallest proportion of irreplaceable areas (Figure 6B) although the greatest number of priority units occurred there (Figure 5B). In We presented the conservation value (based on a scale of from 0 to 1,000) of individual 100 km hexagon units distributed addition, over 75% of the irreplaceable areas were located in intermediately- to extremely-rugged TRI zones (Figure 6C). throughout China (Figure 2). The portfolio of priority units in the HDI-ignored scenario (Figure 3) covered 24.6% of China’s Provinces with the greatest number of irreplaceable areas were Yunnan followed by Guangxi, Tibet, Xinjiang, Inner Mongolia land area. By explicitly including the HDI as an additional penalty, we achieved the same conservation targets with a small and Sichuan, and they contained 51.5% of the total irreplaceable area. increase (,7%) in the total area of priority units compared to when HDI was ignored, meanwhile a clear reduction of ,9% in Overall, many more units in western China were assigned the total HDI score was observed. The overlapping region higher conservation values compared to eastern and southern (Figure 3) covered 46.3% and 43.2% of the priority units in the regions, where the distributions of high-value units were severely HDI-ignored and HDI-considered scenarios, respectively. A fragmented (Figure 7). Based on the conservation value data and strong and positive spatial correlation exists (Spearman’s rank expert knowledge, we visually delineated the boundaries of 23 correlation, r = 0.871, p,,0.001) between the two conservation primary large-scale priority areas and excluded many small value layers. isolated areas (Figure 7). These large-scale priority areas covered ,28% of China’s landmass and were mainly distributed in remote The irreplaceable units in the HDI-ignored scenario (Figure 2A) covered 2.8% of China’s landmass, while an increase of ,43% in regions at high elevation and/or rugged terrain. Regions that have experienced high-intensity disturbances, e.g. Northeast China the total irreplaceable area was observed in the HDI-considered scenario (Figure 2B). The overlapping region occupied 82.7% and Plain, North China Plain, South Huaihe and Middle-lower 57.7% of the irreplaceable areas in the HDI-ignored and HDI- Yangtze River Plain, Sichuan Basin and Pearl River Delta Area, considered scenarios, respectively. High proportional increases in did not contain any large-scale priority areas (Figure 7). PLOS ONE | www.plosone.org 4 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China Figure 2. The conservation value of 100 km hexagon units for achieving the defined conservation targets. (A) HDI-ignored scenario and (B) HDI-considered scenario. doi:10.1371/journal.pone.0103783.g002 PLOS ONE | www.plosone.org 5 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China Figure 3. The cost-effective portfolios of priority units identified by the HDI-ignored and HDI-considered scenarios, respectively. doi:10.1371/journal.pone.0103783.g003 scenario so as to minimize the total HDI score of the portfolio. Discussion This requires the HDI-considered scenario to select a greater In this study we implement a rigorous planning framework to number of priority units with lower HDI values to achieve the identify the optimized national-scale conservation priorities in same conservation goals, because each of these units contains China. Our framework addresses several key features overlooked relatively fewer conservation features and/or covers smaller areas in previous studies, i.e. human disturbance, integration of within their distribution ranges. ecosystem- and species-level conservation features, and principles The total irreplaceable area in the HDI-considered scenario of complementarity and representativeness. increased significantly (,43%) and more irreplaceable units were selected in almost all HDI, elevation, and TRI zones except the Effects of Human Disturbance highest HDI zone (Figure 6). We think the increase results from Due to a lack of site-specific data on the ecological integrity of the fact that Marxan solutions favor those units with relatively most biodiversity features [16], a HDI (or suitability index) is often lower penalty scores, which also was reported by Carwardine et al. modeled by aggregating human disturbance data to provide an [3]. This indicates that human disturbance can partly degrade the indirect measure of ecological condition [4,30]. By explicitly potential options available for implementing cost-effective conser- considering HDI, our goal is to direct conservation towards the vation. Our result, that the most highly-developed provinces had least-disturbed regions while still fully meeting conservation goals. the greatest proportional increases in irreplaceable area while We feel that this approach will promote conservation success and western less-disturbed provinces had smaller changes (Figure 4), more efficiently achieve conservation goals [3,6]. Moreover, areas also supports this perspective. However, we also found that several with higher disturbances offer less conservation potential as they highly-developed provinces had only small changes in irreplace- have lower habitat suitability for sustaining conservation features able area. We think this is because those provinces contain [4]. relatively fewer conservation features and limited overlap exists Our result indicates that the portfolio of priority units in the between the distributions of conservation features and areas of HDI-considered scenario is characterized by a marked reduction human disturbances. in the total HDI score and a slight increase in the total area, and in A fundamental concern in including human disturbance is that addition, more priority units are identified at less-disturbed, higher priority areas may be biased to remote, higher and more rugged and/or rugged regions (Figure 5). Such effects are derived from places. Such a biased distribution has been a severe problem implementing Marxan’s algorithm for identifying an optimized resulting in the existing reserve networks failing to adequately represent the overall biodiversity [34,38]. Does our analysis further portfolio of priority areas that has the minimum total penalty score [17]. Therefore, many priority units identified in the HDI-ignored increase the existing biases in the location of established reserves? scenario, especially those distributed as fragments on highly- We feel it does not, because our framework implements disturbed lands, were excluded or devalued in the HDI-considered ‘representativeness’ as a core principle in identifying priority areas PLOS ONE | www.plosone.org 6 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China Figure 4. Proportional changes in irreplaceable area between the HDI-ignored and HDI-considered scenarios by province. doi:10.1371/journal.pone.0103783.g004 and defines explicit conservation targets for all selected conserva- diminish the conservation value of a region that was historically tion features. The goal for representing the full range of rich in biodiversity [14,33]. Therefore, the higher the disturbance biodiversity requires that the priority-setting process also focuses intensity, the lower the proportion of priority units was allocated in on disturbed landscapes of high biodiversity conservation signif- a region (Figure 5A). Rugged terrain often serves as a natural icance [5]. Similar to Linke et al. [4], we integrated human barrier for human development, and these mountainous areas disturbance as a discounting factor for ecological condition so as to have become refuges for many endangered species; These areas ensure that the resulting portfolio was optimized for maximizing also are preferred as conservation priorities because they maintain conservation achievements. more diverse habitats and higher animal and plant biodiversity Although apparent shifts of priority units towards less-disturbed [14]. zones were observed (Figure 5A), the HDI-considered scenario We found higher percentages of irreplaceable area occurred in only selected fewer priority units in the ,200 m elevation zone lower elevation zones (Figure 6B) compared to the distribution of (Figure 5B) and level zone (Figure 5C), and identified more priority units (Figure 5B). This implies that there are relatively irreplaceable units in almost all HDI, elevation, and TRI zones fewer cost-effective options for fulfilling conservation targets in except the highest HDI zone (Figure 6). The lowest/level zone lowland regions, whereas the highland areas have greater may provide less conservation potential because of limited current flexibility in priority-setting. As moderately-disturbed and/or biodiversity in response to long-term human disturbance [33]. We intermediately- to extremely-rugged zones contain the majority also found considerable overlap, and strong and positive pairwise of irreplaceable areas (Figure 6), these habitats should be targeted associations between the portfolios of priority units and the to identify potentially important areas for implementing cost- portfolios of irreplaceable areas identified by the HDI-ignored and effective conservation. These habitats are mainly found in western HDI-considered scenarios, respectively. These results demonstrate provinces, which include the vast majority of both priority units that our analysis is conservation target based, and the inclusion of and irreplaceable areas, and therefore we consider those provinces human disturbance did not result in the biased distribution of to be of great significance in conserving China’s biodiversity. conservation priorities. Previous researches have revealed that the remaining natural landscapes in eastern and southern China are highly fragmented, and western China supports more intact natural ecosystems and Spatial Patterns of Conservation Priorities endangered species [14,33]. This study similarly found that Recognizing the advantages of including human disturbance in western China contains more high-value units clustered in priority-setting, we analyzed the spatial patterns of conservation relatively larger patches, while the high-value units in eastern priorities using the results from the HDI-considered scenario. and southern regions are severely fragmented and principally Human disturbance has caused severe degradation of natural located in mountainous areas (Figure 7). Our result shows that the ecosystems and many species extinctions, which can greatly PLOS ONE | www.plosone.org 7 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China Figure 5. The distribution of priority units on (A) HDI, (B) Figure 6. The distribution of irreplaceable units on (A) HDI, (B) elevation, and (C) TRI zones. The numbers 1 to 7 on the horizontal elevation, and (C) TRI zones. See Figure 5 for the explanation of axes represent (A) low to high HDI value classifications, (B) elevation numbers 1 to 7 on the horizontal axes. zones of ,200, 200–500, 500–1,000, 1,000–1,500, 1,500–2,000, 2,000– doi:10.1371/journal.pone.0103783.g006 4,000, and .4,000 m, and (C) terrain categories of level, near-level, slightly-rugged, intermediately-rugged, moderately-rugged, highly-rug- ged, and extremely-rugged. Alashan-Ordos Region and Altai Mountain are recognized as the doi:10.1371/journal.pone.0103783.g005 key areas for protecting priority terrestrial ecosystems [39], and each of these five areas exhibits some overlap with the global 200 primary large-scale priority areas are mainly distributed in remote priority ecoregions, including Daurian/Mongolian Steppe, Altai- places with high elevation and rugged terrain (Figure 7). This Sayan Montane Forests, and Middle Asian Montane Woodlands finding is generally consistent with the results in previous studies and Steppe [40]. (e.g., [10,12–15]). The primary large-scale priority areas are the centers of However, we also identified several priority areas that were biodiversity and evolution as they provide refuges for many rarely considered before, including the Hulunbuir Grassland, species and sustain important ecosystem services [8,12], and in Xilingol Grassland, Alashan-Ordos Region, Altai Mountain, and these areas it is usually simpler and less expensive to implement Pamirs Plateau (Figure 7). All are located in Inner Mongolia and conservation actions. In addition to establishing reserves, these Xinjiang, covering grassland, semi-desert, alpine and tundra areas should be subject to a variety of sustainable management biomes. These areas are not rich in species diversity, but they approaches that seek to balance extractive uses with the retention are valued for maintaining several important ecosystems that of natural resources and ecosystem functions, such as the various sustain many endemic species and critical ecosystem services [39]. ecosystem service policies currently implemented in China [9]. Our result agrees with the limited number of studies that have However, these large-scale priority areas are not sufficient to fulfill considered goals for ecosystem conservation. For example, the China’s overall conservation goals [15], because many species, PLOS ONE | www.plosone.org 8 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China Figure 7. The distribution of the 23 primary large-scale priority areas. 1 – Daxing’anling Mountain, 2 – Xiaoxing’anling Mountain, 3 – Sanjiang Plain, 4 – Changbai Mountain, 5 – Hulunbuir Grassland, 6 – Xilingol Grassland, 7 – Alashan-Ordos Region, 8 – Altai Mountain, 9 – Tianshan Mountain, 10 – Pamirs Plateau, 11 – Qilian Mountain, 12 – Sanjiangyuan-Qiangtang Region, 13 – Southeast Himalaya Mountain, 14 – Hengduan Mountain, 15 – Qinling Mountain, 16 – Daba Mountain, 17 – Dabieshan Mountain, 18 – Mountain Region connecting Fujian-Zhejiang-Jiangxi-Anhui, 19 – Wuling Mountain, 20 – Nanling Mountain, 21 – Mountain Region in western Guangxi, 22 – Xishuangbanna, and 23 – Southern Hainan Island. doi:10.1371/journal.pone.0103783.g007 particularly those that exploit special microhabitats, may only multiple taxa can improve the effectiveness of priority areas in occur in places close to developed landscapes and are already representing the overall biodiversity [5]. The HDI, a coarse highly threatened [5]. Therefore, the priority units distributed in simplification of current ecological condition, could be improved highly-disturbed regions that are not included in the large-scale when better disturbance data and modeling methods are priority areas should be included in local conservation actions. developed. This may be even more urgent in order to prevent the immediate Hence we suggest that China increase its budget for improving loss of biodiversity [41]. the GIS-based conservation decision-making platform and en- hance data sharing mechanisms. Moreover, the integration of ecological processes, ecosystem services, socioeconomic objectives The Priority-setting Framework and climate projections represents future research priorities in Using this priority-setting framework, we are trying to ensure SCP [4,6,7]. the identification of a comprehensive and cost-effective portfolio of conservation priorities for China. The process is driven by explicitly delineating spatial distributions and quantitatively Application defined targets for representative conservation features. We believe Systematic conservation priority-setting has significant implica- the analysis is rigorous, objective, transparent, and replicable. tions in assisting China in achieving its cost-effective conservation goals as a megadiversity country. For instance, this approach has We acknowledge that the availability and accuracy of spatial data on biodiversity and disturbances are a primary constraint for been applied in conservation priority-setting for China nationwide, national-scale priority-setting. Therefore, our results can be further and the work is a key component for developing the National refined as more comprehensive data become available. This study Biodiversity Strategies and Action Plans (NBSAPs) [8]. China’s has used the most up-to-date national survey data on key protected Ministry of Environmental Protection requires all provinces, major plant and animal species [22,25], as well as highly recognized river watersheds, and counties develop their Local Biodiversity information sources that have been used in previous studies (e.g., Strategies and Action Plans (LBSAPs) [8]. Thus, we applied this priority-setting approach to come up with the first provincial [14]). The ecosystem-level features represent meaningful biodi- versity surrogates because they are the emergent entities of unique LBSAPs for Sichuan [42], and now this approach is in high demand in China. species assemblages and easily mapped; moreover, they are useful indicators of ecological processes and ecosystem services [16]. The Not only is this approach useful in its direct application to integration of conservation features from different levels and conservation planning, but it also has important applicability for PLOS ONE | www.plosone.org 9 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China strategic land-use planning and sustainable development practices; extremely-rugged in terrain should be targeted to identify e.g. the Ecological Function Regionalization and Major Function potentially important regions for implementing cost-effective Oriented Zoning [43–44] could be further refined using our conservation. To achieve the overall biodiversity conservation approach. Such planning seeks to optimize the spatial patterns of goal in China, we delineate 23 primary large-scale priority areas, economic development and environment protection by investigat- as well as recognize many isolated priority units in disturbed ing the synergies and trade-offs between their distributions [45]. regions that need even more urgent conservation so as to prevent Areas recognized as conservation priorities should be primarily the immediate loss of biodiversity. preserved for sustaining biodiversity and ecosystem services. As While requiring further refinement, our results provide valuable China is now adopting a new paradigm of sustainable develop- insights for current conservation and strategic land-use planning in ment by undertaking a transition from conventional industrializa- China. This approach uses publicly available information, and is tion to ecological civilization [46] numerous redlines on natural transferable and easy to implement by end-users, and applicable resources and environment management (e.g., the Key Ecological for national- and local-scale systematic conservation prioritization Function Regions and Development Prohibited/Restricted Zones) practices. Improved data, especially in the details of human have been established to ensure the country’s ecological security disturbance and for aquatic systems at national-scale, will further [47]. This priority-setting approach is of great significance for enhance its applicability. determining the spatially optimized conservation network or redlines for strategic land-use planning. Acknowledgments We thank Siobhan Kenney and Bastian Bertzky at UNEP-WCMC for Conclusions valuable comments and English editing. We thank Bei Huang, Rui Zhang This study presents optimized national-scale spatial priorities for and Shan Sun, master students in Southwest Forestry University for their valuable help in building the spatial database, and the Data center for biodiversity conservation in China by implementing a systematic Resources and Environmental Sciences of the Chinese Academy of priority-setting approach with the integration of human distur- Sciences for providing data on land uses, human population density and bances, ecosystem- and species-level conservation features, and GDP. PAG acknowledges the support of Chrissie, Sara, and Jenni. principles of complementarity and representativeness. Inclusion of human disturbance is essential for a cost-effective priority-setting – Author Contributions maximizing conservation achievement while minimizing conflicts with economic development. Such an approach will ensure the Conceived and designed the experiments: RDW YCL GPM PAG SZ. optimal spatial distribution of priority areas and reduce biases in Performed the experiments: RDW SZ DQL PZ LZW HRD. Analyzed the conservation investment and/or land-use planning. The majority data: RDW YCL LZW HRD. Contributed reagents/materials/analysis tools: RDW DQL LZW HRD. Wrote the paper: RDW YCL GPM PAG of priority units we identified are located in relatively remote, high SZ. and/or rugged places, however, areas that are moderately- disturbed, ,2,000 m in altitude, and/or intermediately- to References 1. McCarthy DP, Donald PF, Scharlemann JPW, Buchanan GM, Balmford A, et 15. Zhang YB, Ma KP (2008) Geographic distribution patterns and status al. (2012) Financial costs of meeting global biodiversity conservation targets: assessment of threatened plants in China. Biodiversity and Conservation 17: 1783–1798. current spending and unmet needs. Science 338: 946–949. 2. 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Optimized Spatial Priorities for Biodiversity Conservation in China: A Systematic Conservation Planning Perspective

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© 2014 Wu et al
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1932-6203
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Abstract

By addressing several key features overlooked in previous studies, i.e. human disturbance, integration of ecosystem- and species-level conservation features, and principles of complementarity and representativeness, we present the first national- scale systematic conservation planning for China to determine the optimized spatial priorities for biodiversity conservation. We compiled a spatial database on the distributions of ecosystem- and species-level conservation features, and modeled a human disturbance index (HDI) by aggregating information using several socioeconomic proxies. We ran Marxan with two scenarios (HDI-ignored and HDI-considered) to investigate the effects of human disturbance, and explored the geographic patterns of the optimized spatial conservation priorities. Compared to when HDI was ignored, the HDI-considered scenario resulted in (1) a marked reduction (,9%) in the total HDI score and a slight increase (,7%) in the total area of the portfolio of priority units, (2) a significant increase (,43%) in the total irreplaceable area and (3) more irreplaceable units being identified in almost all environmental zones and highly-disturbed provinces. Thus the inclusion of human disturbance is essential for cost-effective priority-setting. Attention should be targeted to the areas that are characterized as moderately- disturbed, ,2,000 m in altitude, and/or intermediately- to extremely-rugged in terrain to identify potentially important regions for implementing cost-effective conservation. We delineated 23 primary large-scale priority areas that are significant for conserving China’s biodiversity, but those isolated priority units in disturbed regions are in more urgent need of conservation actions so as to prevent immediate and severe biodiversity loss. This study presents a spatially optimized national-scale portfolio of conservation priorities – effectively representing the overall biodiversity of China while minimizing conflicts with economic development. Our results offer critical insights for current conservation and strategic land-use planning in China. The approach is transferable and easy to implement by end-users, and applicable for national- and local-scale systematic conservation prioritization practices. Citation: Wu R, Long Y, Malanson GP, Garber PA, Zhang S, et al. (2014) Optimized Spatial Priorities for Biodiversity Conservation in China: A Systematic Conservation Planning Perspective. PLoS ONE 9(7): e103783. doi:10.1371/journal.pone.0103783 Editor: Duccio Rocchini, Fondazione Edmund Mach, Research and Innovation Centre, Italy Received November 5, 2013; Accepted July 7, 2014; Published July 29, 2014 Copyright:  2014 Wu 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. Funding: This study was funded by the National Natural Science Foundation of China (No. 31260148) and the National Key Technologies R&D Program of China (No. 2011BAC09B07). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * Email: rdwu@ynu.edu.cn the minimum land area or other costs (e.g., land prices, Introduction management and opportunity costs [7]). SCP provides an Anthropogenic effects have resulted in the loss of biodiversity at operational framework for minimizing land-use conflicts between an unprecedented rate, while resources for biodiversity conserva- conserving natural environments and economic development, and tion remain constrained in terms of both human and financial thus increase the likelihood of implementing the proposed capacity [1]. That is why the systematic planning of priority areas conservation actions [3,6]. Here, we present the first national- is crucial to achieve the most cost-effective conservation, such as scale SCP study for China to determine the optimized spatial identifying large-scale biodiversity hotspots or assembling fine- priorities for biodiversity conservation. resolution portfolios of conservation priorities [2–4]. In the last two China – one of the world’s ‘‘megadiversity countries’’ – is home decades, systematic conservation planning (SCP) has emerged as to many globally valued conservation priorities [2]. However, an effective approach for identifying conservation priorities [3–6]. China’s biodiversity is under severe threat due to the increasing SCP aims to identify a network of priority areas so as to effectively pressure resulting from the country’s historically unprecedented achieve explicit conservation goals in terms of representing the full economic growth [8]. Meanwhile, China’s conservation invest- range of biodiversity and sustaining their long-term survival [5]. ment is considerably lower compared to developed and other Efficient conservation priorities can be identified through an developing countries [9]. Thus, the systematic conservation optimized planning algorithm for meeting conservation goals at PLOS ONE | www.plosone.org 1 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China priority-setting has been emphasized in China during last two Methods decades [8,10–11]. Conservation Features Mapping During this period, China has developed several templates of Considering the complexity of biodiversity and severe lack of national-scale conservation priorities, which were based principal- detailed spatial distribution data, surrogates (e.g., endangered/ ly on the species (e.g., endemic, threatened, and/or other indicator endemic species, key habitat types and environmental features) are species) richness patterns as well as expert judgments (e.g., [10,12– often used in conservation planning [3,7,16,18]. Integrating 15]). These templates are crucial in guiding China’s national-level conservation features from multiple levels can ensure the efficient conservation decisions; however, we think there are several critical representation of biodiversity [5] and compensate for limitations in limitations in previous priority-setting studies. the data [16]. In this analysis, we used both ecosystem- and First, the effects of human disturbance are not incorporated in species-level features as the surrogates. previous studies, whereas we believe explicit inclusion of human The ecosystem-level features included were: (1) priority natural disturbance in priority-setting can minimize land-use conflicts and ecosystems as defined by Li, Song & Ouyang [13], including 129 lower costs for meeting conservation goals [3,6]. Second, the natural ecosystems of forests, grasslands, meadows, deserts and scoring procedure in these studies is inefficient for achieving the wetlands, and (2) natural vegetation types derived from the goal of full representation of all biodiversity targets [16], i.e. the national 1: 1,000,000 vegetation map, including 559 natural goal for representativeness – one of the core principles for vegetation formations [19]. This study considered wetlands and designing an efficient reserve system [5]. The current scoring lakes (in the priority natural ecosystems and natural vegetation procedure requires a greater amount of land (and increases other types), but data on aquatic systems and species was lacking. We costs) to achieve the same conservation goals and these greater expected that China’s key ecological elements, processes and demands are unlikely to get support from local authorities. Third, services were covered with priority natural ecosystems and that a study designed to systematically integrate conservation features basic habitat types were represented by finer-scale classifications of at both ecosystem- and species-level is still lacking, as the natural vegetation types. The species-level features were endan- conservation features used in previous studies are either species gered species of plants, mammals, and birds. Endangered or ecosystem based. By incorporating biodiversity features from mammals and birds were identified according to China’s multiple organization levels, the resulting portfolio of conservation ‘‘National List of Key Protected Wildlife’’ and the IUCN Red priorities is more efficient in representing the full range of List Categories of critically endangered, endangered and vulner- biodiversity concerns and in maintaining the ecological integrity of able species [20]. Endangered plants were defined in the ‘‘China ecosystems [5,16]. SCP can overcome this inefficiency in scoring Plant Red Data Book: Endangered and Rare Plants’’ [21]. procedure by employing the principle of between-site comple- Previous studies often use county-level species distribution data mentarity that serves to boost the efficient representation of all derived from the published literatures [14–15], while our analysis biodiversity targets, and provide mechanisms for integrating was performed using a finer-scale resolution. For plants and human disturbance and conservation features at multiple organi- mammals, we mapped each species’ geographic range by zation levels [17]. combining its distribution data for counties, preferred habitat This study aims to determine the optimized national-scale types and elevation range. For a bird species, the range was spatial priorities in China and to ensure effectively fulfilling derived by intersecting only counties and habitat types, because biodiversity conservation goals given the constraints of human knowledge of the altitude distribution of most avian species is disturbance by implementing a SCP approach. Taiwan, Hong lacking. This mapping process included: (1) collecting each species’ Kong and Macao are not included in our analysis due to lack of attribute information, i.e. species name, taxonomy, endangered required information. Specifically, we are trying to address two category, distribution across counties, preferred habitat types, and questions: (1) How will the inclusion of human disturbance affect elevation range, (2) mapping each species’ distributions across the result of conservation priority-setting? (2) What are the counties, habitat types and elevation range, respectively, and (3) geographical patterns of the optimized conservation priorities in identifying the overlap region among these distribution layers as China? In this analysis, we integrated human disturbance, each species’ current range. conservation features at both the ecosystem- and species-level, We collected the attribute information using the following and the principles of complementarity and representativeness. We resources. For plants, we used ‘‘National Key Protected Wild Plant used the software Marxan [17] to determine each unit’s Resources Survey’’ [22] as the primary source and other conservation value and to identify priorities with regular hexagons supplementary sources including ‘‘Subject Database of China (100 km per cell) as the planning units. We investigated the effects Plants’’ [23], ‘‘China Species Information Services’’ [24] and of human disturbance using two Marxan scenarios – a disturbance ‘‘China Plant Red Data Book: Endangered and Rare Plants’’ [21]. ignored scenario and a disturbance considered scenario. For the For mammals and birds, we used ‘‘National Key Terrestrial second scenario, human disturbance was included as a penalty Wildlife Resources Survey’’ [25] as the primary source and other function by aggregating information on several socioeconomic supplementary sources including ‘‘Database of Fauna Sinica’’ proxies as an index layer. We then explored the spatial patterns of [26], ‘‘Distributions of China Mammal Species’’ [27] and ‘‘China the priority units, irreplaceable areas, and primary large-scale Red Data Book of Endangered Animals: Mammals’’ [28]. priority areas (i.e., the large clustered regions of high-conservation- The datasets on county boundaries and habitat types were value units). The analysis is limited to the data available at derived from the national 1: 1,000,000 geographic databases and national-scale and applicable resolution, and misses some the national 1: 1,000,000 vegetation map [19], respectively. The variability within the range of human disturbances. We believe elevation range for each species was extracted from the Shuttle this study is applicable to national- and local-scale conservation Radar Topography Mission (SRTM) 90 m Digital Elevation and other sustainable land-use planning for systematically Model (DEM) [29]. We mapped the species’ geographic ranges for evaluating each site’s conservation value and identifying spatially 373 plant, 115 mammal and 81 bird species. optimized priority areas. PLOS ONE | www.plosone.org 2 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China cost-effectively solve an optimization problem of representing a Human Disturbance Index Mapping suite of biodiversity targets [17]. To ensure that all conservation We used several socioeconomic proxies, including proportion of features were captured across their ranges of environmental and land converted by human use, human population density, gross genetic variations [32], we first stratified their ranges with China’s domestic product (GDP) and road density to calculate the human 53 terrestrial ecoregions [33], and then defined a quantitative disturbance index (HDI) or human footprint [4,30]. The basic conservation target for each feature per ecoregion. Due to limited planning units were regular hexagons, each sized 100 km . The data available for setting up appropriate conservation targets [34], analysis included three steps. First, we calculated an individual we defined the target for each conservation feature as a uniform HDI (IHDI) for each of these proxies. For proportion of converted percentage area of its distribution range as suggested in previous land, we calculated the IHDI as the percent area of human- studies (e.g., [3,32]). Specifically, the quantitative targets were developed-land use – including croplands, plantations, rural settlements and urban/industrial areas – within each hexagon. selected based on expert opinions as follows: 30% for endangered For human population density and GDP, we calculated the IHDIs species, 20% for priority natural ecosystems and 10% for natural as their mean values per square kilometer within each unit. For vegetation types. An internationally recognized lowest target of road density, we considered four transportation levels (i.e., railway, 10% was set for natural vegetation types because they were expressway, national-provincial road and other-level roads), and assumed to represent the variety of basic habitat types. calculated an IHDI for each level as the total road length within We ran Marxan with two scenarios – a HDI-considered each unit. Second, we normalized the data ranges of all IHDIs on scenario and a HDI-ignored scenario. For the HDI-considered a scale of from 0.00 to 1.00, and then summed them to get the scenario, we integrated HDI values as a penalty function in total HDI. Finally, we empirically transformed the data range of Marxan analysis, i.e. a unit having a higher degree of disturbance the total HDI on a scale of from 10.00 to 300.00 (Figure 1) so as to would receive a greater penalty. For the HDI-ignored scenario, we clearly demonstrate the overall human disturbance pattern. used a uniform penalty of 1.0 per unit. The units with greater HDI We obtained datasets on land uses, human population density values exhibit a more highly degraded ecological condition and and GDP from the Data Center for Resources and Environmental should offer less potential from a conservation perspective [4]. Sciences of the Chinese Academy of Sciences [31], and all are Therefore, Marxan’s algorithm sought to identify the optimized 1km61 km resolution grid files. The road networks were derived priority areas by minimizing the total HDI score in the HDI- from the national 1: 1,000,000 geographic database. considered scenario or the total land area in the HDI-ignored scenario. For the Marxan configurations, we: (1) generated 1000 Conservation Priority-setting solutions; (2) included a boundary length file and a modifier factor We used the software Marxan (v2.0.2) to implement the to control the compactness of priority areas; (3) implemented conservation priority-setting process. Marxan was developed to Simulated Annealing followed by Iterative Improvement; and (4) Figure 1. Human disturbance index (HDI). HDI was modeled by aggregating information on several socioeconomic proxies, including proportion of land converted by human use, human population density, gross domestic product, and road density. doi:10.1371/journal.pone.0103783.g001 PLOS ONE | www.plosone.org 3 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China used the default values for Number of Iterations (1,000,000) and irreplaceable area occurred principally in provinces located in the Temperature Decreases (10,000). eastern coastal region, middle-lower Yangtze River Basin and We derived the conservation value that reflects the relative northeastern China, whereas provinces in western and southwest- ern China had the fewest changes (Figure 4). Several provinces in priority or irreplaceability of each planning unit [3] from the frequency of solutions selected, and used the best of the 1,000 the eastern highly-disturbed regions (Figure 1), including Guang- dong, Jiangxi, Henan and Hebei, also were found to have small solutions as the most cost-effective portfolio of priority units. We then identified the irreplaceable units as those selected in more changes in their irreplaceable areas (Figure 4). than 800 solutions; 80% is often used for accuracy assessment for Compared to the results in the HDI-ignored scenario, the spatial data (e.g., [35]). portfolio of priority units in the HDI-considered scenario contained: (1) fewer units in the three highest HDI zones and more units in the four lower HDI zones, (2) fewer units only in the Effects of Human Disturbance lowest (,200 m) elevation zone and more units in the other six We compared the total HDI score and total area of the two zones, and (3) fewer units in the level TRI zone and more units in portfolios of priority units generated by the HDI-ignored and each of the other TRI zones (Figure 5). The HDI-considered HDI-considered scenarios, respectively. The changes in irreplace- scenario identified a greater number of irreplaceable units in able areas between the two scenarios were assessed in terms of the almost all environmental zones than did the HDI-ignored total area and the proportional area changes by province. scenario, with the sole exception of the highest HDI zone To assess the effects of human disturbance at a finer-scale, we (Figure 6). further investigated the distributions of the priority units and irreplaceable areas on different environmental zones of HDI, Spatial Patterns of Conservation Priorities elevation, and terrain ruggedness. We derived seven zones for each variable as follows: (1) We classified HDI zones by applying the We analyzed the spatial patterns of conservation priorities using Quantile Classification Scheme on HDI values; (2) We derived the outcomes from the HDI-considered scenario. The priority elevation zones from the SRTM 90 m DEM according to studies units consistently decreased with increasing HDI value (Fig- on geomorphology [36] (the elevation classification schemes were ure 5A), with the majority (,76%) located in the four lower HDI ,200, 200–500, 500–1,000, 1,000–1,500, 1,500–2,000, 2,000– zones. The ,200 m elevation zone included only 5.8% of all 4,000, and .4,000 m); (3) We calculated a terrain ruggedness priority units, and the zones of 200–1,000, 1,000–2,000 and . index (TRI) as the average difference in elevation between a center 2,000 m contained 29.6%, 25.8% and 38.8% of the priority units, cell and its eight neighboring cells using the SRTM DEM, and the respectively. The priority units generally had an increasing Quantile Classification Scheme was then used to break the TRI distribution trend on TRI zones from level to extremely-rugged values into seven terrain categories, i.e. level, near-level, slightly- terrain (Figure 5C), with the vast majority located in slightly- to rugged, intermediately-rugged, moderately-rugged, highly-rugged extremely-rugged zones, and only 3.2% identified in level zone and extremely-rugged [37–38]. and 11.5% in near-level zone. All provinces included some units that were required for meeting the conservation targets (Figure 3), with the greatest proportion occurring in Xinjiang followed by Spatial Patterns of Conservation Priorities Tibet, Inner Mongolia, Qinghai, Sichuan and Yunnan. These six Using the outputs from the HDI-considered scenario, we western provinces contained 72.5% of the total priority units. analyzed the spatial distributions of priority units and irreplaceable The irreplaceable units had a normal-like distribution on the areas on HDI, elevation, TRI zones and provinces. We then HDI zones that peaked in the fourth zone (Figure 6A). Compared delineated the primary large-scale priority areas as the large to the distribution of priority units, greater proportions of clusters of high-conservation-value planning units through an irreplaceable units were selected in lower elevation zones, with expert-based visual interpretation process. 10.7%, 39.3%, 26.7% and 23.3% of the total irreplaceable area located at ,200, 200–1,000, 1,000–2,000 and .2,000 m zones, Results respectively. In particular, the highest zone (.4,000 m) contained Effects of Human Disturbance the smallest proportion of irreplaceable areas (Figure 6B) although the greatest number of priority units occurred there (Figure 5B). In We presented the conservation value (based on a scale of from 0 to 1,000) of individual 100 km hexagon units distributed addition, over 75% of the irreplaceable areas were located in intermediately- to extremely-rugged TRI zones (Figure 6C). throughout China (Figure 2). The portfolio of priority units in the HDI-ignored scenario (Figure 3) covered 24.6% of China’s Provinces with the greatest number of irreplaceable areas were Yunnan followed by Guangxi, Tibet, Xinjiang, Inner Mongolia land area. By explicitly including the HDI as an additional penalty, we achieved the same conservation targets with a small and Sichuan, and they contained 51.5% of the total irreplaceable area. increase (,7%) in the total area of priority units compared to when HDI was ignored, meanwhile a clear reduction of ,9% in Overall, many more units in western China were assigned the total HDI score was observed. The overlapping region higher conservation values compared to eastern and southern (Figure 3) covered 46.3% and 43.2% of the priority units in the regions, where the distributions of high-value units were severely HDI-ignored and HDI-considered scenarios, respectively. A fragmented (Figure 7). Based on the conservation value data and strong and positive spatial correlation exists (Spearman’s rank expert knowledge, we visually delineated the boundaries of 23 correlation, r = 0.871, p,,0.001) between the two conservation primary large-scale priority areas and excluded many small value layers. isolated areas (Figure 7). These large-scale priority areas covered ,28% of China’s landmass and were mainly distributed in remote The irreplaceable units in the HDI-ignored scenario (Figure 2A) covered 2.8% of China’s landmass, while an increase of ,43% in regions at high elevation and/or rugged terrain. Regions that have experienced high-intensity disturbances, e.g. Northeast China the total irreplaceable area was observed in the HDI-considered scenario (Figure 2B). The overlapping region occupied 82.7% and Plain, North China Plain, South Huaihe and Middle-lower 57.7% of the irreplaceable areas in the HDI-ignored and HDI- Yangtze River Plain, Sichuan Basin and Pearl River Delta Area, considered scenarios, respectively. High proportional increases in did not contain any large-scale priority areas (Figure 7). PLOS ONE | www.plosone.org 4 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China Figure 2. The conservation value of 100 km hexagon units for achieving the defined conservation targets. (A) HDI-ignored scenario and (B) HDI-considered scenario. doi:10.1371/journal.pone.0103783.g002 PLOS ONE | www.plosone.org 5 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China Figure 3. The cost-effective portfolios of priority units identified by the HDI-ignored and HDI-considered scenarios, respectively. doi:10.1371/journal.pone.0103783.g003 scenario so as to minimize the total HDI score of the portfolio. Discussion This requires the HDI-considered scenario to select a greater In this study we implement a rigorous planning framework to number of priority units with lower HDI values to achieve the identify the optimized national-scale conservation priorities in same conservation goals, because each of these units contains China. Our framework addresses several key features overlooked relatively fewer conservation features and/or covers smaller areas in previous studies, i.e. human disturbance, integration of within their distribution ranges. ecosystem- and species-level conservation features, and principles The total irreplaceable area in the HDI-considered scenario of complementarity and representativeness. increased significantly (,43%) and more irreplaceable units were selected in almost all HDI, elevation, and TRI zones except the Effects of Human Disturbance highest HDI zone (Figure 6). We think the increase results from Due to a lack of site-specific data on the ecological integrity of the fact that Marxan solutions favor those units with relatively most biodiversity features [16], a HDI (or suitability index) is often lower penalty scores, which also was reported by Carwardine et al. modeled by aggregating human disturbance data to provide an [3]. This indicates that human disturbance can partly degrade the indirect measure of ecological condition [4,30]. By explicitly potential options available for implementing cost-effective conser- considering HDI, our goal is to direct conservation towards the vation. Our result, that the most highly-developed provinces had least-disturbed regions while still fully meeting conservation goals. the greatest proportional increases in irreplaceable area while We feel that this approach will promote conservation success and western less-disturbed provinces had smaller changes (Figure 4), more efficiently achieve conservation goals [3,6]. Moreover, areas also supports this perspective. However, we also found that several with higher disturbances offer less conservation potential as they highly-developed provinces had only small changes in irreplace- have lower habitat suitability for sustaining conservation features able area. We think this is because those provinces contain [4]. relatively fewer conservation features and limited overlap exists Our result indicates that the portfolio of priority units in the between the distributions of conservation features and areas of HDI-considered scenario is characterized by a marked reduction human disturbances. in the total HDI score and a slight increase in the total area, and in A fundamental concern in including human disturbance is that addition, more priority units are identified at less-disturbed, higher priority areas may be biased to remote, higher and more rugged and/or rugged regions (Figure 5). Such effects are derived from places. Such a biased distribution has been a severe problem implementing Marxan’s algorithm for identifying an optimized resulting in the existing reserve networks failing to adequately represent the overall biodiversity [34,38]. Does our analysis further portfolio of priority areas that has the minimum total penalty score [17]. Therefore, many priority units identified in the HDI-ignored increase the existing biases in the location of established reserves? scenario, especially those distributed as fragments on highly- We feel it does not, because our framework implements disturbed lands, were excluded or devalued in the HDI-considered ‘representativeness’ as a core principle in identifying priority areas PLOS ONE | www.plosone.org 6 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China Figure 4. Proportional changes in irreplaceable area between the HDI-ignored and HDI-considered scenarios by province. doi:10.1371/journal.pone.0103783.g004 and defines explicit conservation targets for all selected conserva- diminish the conservation value of a region that was historically tion features. The goal for representing the full range of rich in biodiversity [14,33]. Therefore, the higher the disturbance biodiversity requires that the priority-setting process also focuses intensity, the lower the proportion of priority units was allocated in on disturbed landscapes of high biodiversity conservation signif- a region (Figure 5A). Rugged terrain often serves as a natural icance [5]. Similar to Linke et al. [4], we integrated human barrier for human development, and these mountainous areas disturbance as a discounting factor for ecological condition so as to have become refuges for many endangered species; These areas ensure that the resulting portfolio was optimized for maximizing also are preferred as conservation priorities because they maintain conservation achievements. more diverse habitats and higher animal and plant biodiversity Although apparent shifts of priority units towards less-disturbed [14]. zones were observed (Figure 5A), the HDI-considered scenario We found higher percentages of irreplaceable area occurred in only selected fewer priority units in the ,200 m elevation zone lower elevation zones (Figure 6B) compared to the distribution of (Figure 5B) and level zone (Figure 5C), and identified more priority units (Figure 5B). This implies that there are relatively irreplaceable units in almost all HDI, elevation, and TRI zones fewer cost-effective options for fulfilling conservation targets in except the highest HDI zone (Figure 6). The lowest/level zone lowland regions, whereas the highland areas have greater may provide less conservation potential because of limited current flexibility in priority-setting. As moderately-disturbed and/or biodiversity in response to long-term human disturbance [33]. We intermediately- to extremely-rugged zones contain the majority also found considerable overlap, and strong and positive pairwise of irreplaceable areas (Figure 6), these habitats should be targeted associations between the portfolios of priority units and the to identify potentially important areas for implementing cost- portfolios of irreplaceable areas identified by the HDI-ignored and effective conservation. These habitats are mainly found in western HDI-considered scenarios, respectively. These results demonstrate provinces, which include the vast majority of both priority units that our analysis is conservation target based, and the inclusion of and irreplaceable areas, and therefore we consider those provinces human disturbance did not result in the biased distribution of to be of great significance in conserving China’s biodiversity. conservation priorities. Previous researches have revealed that the remaining natural landscapes in eastern and southern China are highly fragmented, and western China supports more intact natural ecosystems and Spatial Patterns of Conservation Priorities endangered species [14,33]. This study similarly found that Recognizing the advantages of including human disturbance in western China contains more high-value units clustered in priority-setting, we analyzed the spatial patterns of conservation relatively larger patches, while the high-value units in eastern priorities using the results from the HDI-considered scenario. and southern regions are severely fragmented and principally Human disturbance has caused severe degradation of natural located in mountainous areas (Figure 7). Our result shows that the ecosystems and many species extinctions, which can greatly PLOS ONE | www.plosone.org 7 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China Figure 5. The distribution of priority units on (A) HDI, (B) Figure 6. The distribution of irreplaceable units on (A) HDI, (B) elevation, and (C) TRI zones. The numbers 1 to 7 on the horizontal elevation, and (C) TRI zones. See Figure 5 for the explanation of axes represent (A) low to high HDI value classifications, (B) elevation numbers 1 to 7 on the horizontal axes. zones of ,200, 200–500, 500–1,000, 1,000–1,500, 1,500–2,000, 2,000– doi:10.1371/journal.pone.0103783.g006 4,000, and .4,000 m, and (C) terrain categories of level, near-level, slightly-rugged, intermediately-rugged, moderately-rugged, highly-rug- ged, and extremely-rugged. Alashan-Ordos Region and Altai Mountain are recognized as the doi:10.1371/journal.pone.0103783.g005 key areas for protecting priority terrestrial ecosystems [39], and each of these five areas exhibits some overlap with the global 200 primary large-scale priority areas are mainly distributed in remote priority ecoregions, including Daurian/Mongolian Steppe, Altai- places with high elevation and rugged terrain (Figure 7). This Sayan Montane Forests, and Middle Asian Montane Woodlands finding is generally consistent with the results in previous studies and Steppe [40]. (e.g., [10,12–15]). The primary large-scale priority areas are the centers of However, we also identified several priority areas that were biodiversity and evolution as they provide refuges for many rarely considered before, including the Hulunbuir Grassland, species and sustain important ecosystem services [8,12], and in Xilingol Grassland, Alashan-Ordos Region, Altai Mountain, and these areas it is usually simpler and less expensive to implement Pamirs Plateau (Figure 7). All are located in Inner Mongolia and conservation actions. In addition to establishing reserves, these Xinjiang, covering grassland, semi-desert, alpine and tundra areas should be subject to a variety of sustainable management biomes. These areas are not rich in species diversity, but they approaches that seek to balance extractive uses with the retention are valued for maintaining several important ecosystems that of natural resources and ecosystem functions, such as the various sustain many endemic species and critical ecosystem services [39]. ecosystem service policies currently implemented in China [9]. Our result agrees with the limited number of studies that have However, these large-scale priority areas are not sufficient to fulfill considered goals for ecosystem conservation. For example, the China’s overall conservation goals [15], because many species, PLOS ONE | www.plosone.org 8 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China Figure 7. The distribution of the 23 primary large-scale priority areas. 1 – Daxing’anling Mountain, 2 – Xiaoxing’anling Mountain, 3 – Sanjiang Plain, 4 – Changbai Mountain, 5 – Hulunbuir Grassland, 6 – Xilingol Grassland, 7 – Alashan-Ordos Region, 8 – Altai Mountain, 9 – Tianshan Mountain, 10 – Pamirs Plateau, 11 – Qilian Mountain, 12 – Sanjiangyuan-Qiangtang Region, 13 – Southeast Himalaya Mountain, 14 – Hengduan Mountain, 15 – Qinling Mountain, 16 – Daba Mountain, 17 – Dabieshan Mountain, 18 – Mountain Region connecting Fujian-Zhejiang-Jiangxi-Anhui, 19 – Wuling Mountain, 20 – Nanling Mountain, 21 – Mountain Region in western Guangxi, 22 – Xishuangbanna, and 23 – Southern Hainan Island. doi:10.1371/journal.pone.0103783.g007 particularly those that exploit special microhabitats, may only multiple taxa can improve the effectiveness of priority areas in occur in places close to developed landscapes and are already representing the overall biodiversity [5]. The HDI, a coarse highly threatened [5]. Therefore, the priority units distributed in simplification of current ecological condition, could be improved highly-disturbed regions that are not included in the large-scale when better disturbance data and modeling methods are priority areas should be included in local conservation actions. developed. This may be even more urgent in order to prevent the immediate Hence we suggest that China increase its budget for improving loss of biodiversity [41]. the GIS-based conservation decision-making platform and en- hance data sharing mechanisms. Moreover, the integration of ecological processes, ecosystem services, socioeconomic objectives The Priority-setting Framework and climate projections represents future research priorities in Using this priority-setting framework, we are trying to ensure SCP [4,6,7]. the identification of a comprehensive and cost-effective portfolio of conservation priorities for China. The process is driven by explicitly delineating spatial distributions and quantitatively Application defined targets for representative conservation features. We believe Systematic conservation priority-setting has significant implica- the analysis is rigorous, objective, transparent, and replicable. tions in assisting China in achieving its cost-effective conservation goals as a megadiversity country. For instance, this approach has We acknowledge that the availability and accuracy of spatial data on biodiversity and disturbances are a primary constraint for been applied in conservation priority-setting for China nationwide, national-scale priority-setting. Therefore, our results can be further and the work is a key component for developing the National refined as more comprehensive data become available. This study Biodiversity Strategies and Action Plans (NBSAPs) [8]. China’s has used the most up-to-date national survey data on key protected Ministry of Environmental Protection requires all provinces, major plant and animal species [22,25], as well as highly recognized river watersheds, and counties develop their Local Biodiversity information sources that have been used in previous studies (e.g., Strategies and Action Plans (LBSAPs) [8]. Thus, we applied this priority-setting approach to come up with the first provincial [14]). The ecosystem-level features represent meaningful biodi- versity surrogates because they are the emergent entities of unique LBSAPs for Sichuan [42], and now this approach is in high demand in China. species assemblages and easily mapped; moreover, they are useful indicators of ecological processes and ecosystem services [16]. The Not only is this approach useful in its direct application to integration of conservation features from different levels and conservation planning, but it also has important applicability for PLOS ONE | www.plosone.org 9 July 2014 | Volume 9 | Issue 7 | e103783 Conservation Priority-Setting in China strategic land-use planning and sustainable development practices; extremely-rugged in terrain should be targeted to identify e.g. the Ecological Function Regionalization and Major Function potentially important regions for implementing cost-effective Oriented Zoning [43–44] could be further refined using our conservation. To achieve the overall biodiversity conservation approach. Such planning seeks to optimize the spatial patterns of goal in China, we delineate 23 primary large-scale priority areas, economic development and environment protection by investigat- as well as recognize many isolated priority units in disturbed ing the synergies and trade-offs between their distributions [45]. regions that need even more urgent conservation so as to prevent Areas recognized as conservation priorities should be primarily the immediate loss of biodiversity. preserved for sustaining biodiversity and ecosystem services. As While requiring further refinement, our results provide valuable China is now adopting a new paradigm of sustainable develop- insights for current conservation and strategic land-use planning in ment by undertaking a transition from conventional industrializa- China. This approach uses publicly available information, and is tion to ecological civilization [46] numerous redlines on natural transferable and easy to implement by end-users, and applicable resources and environment management (e.g., the Key Ecological for national- and local-scale systematic conservation prioritization Function Regions and Development Prohibited/Restricted Zones) practices. Improved data, especially in the details of human have been established to ensure the country’s ecological security disturbance and for aquatic systems at national-scale, will further [47]. This priority-setting approach is of great significance for enhance its applicability. determining the spatially optimized conservation network or redlines for strategic land-use planning. Acknowledgments We thank Siobhan Kenney and Bastian Bertzky at UNEP-WCMC for Conclusions valuable comments and English editing. We thank Bei Huang, Rui Zhang This study presents optimized national-scale spatial priorities for and Shan Sun, master students in Southwest Forestry University for their valuable help in building the spatial database, and the Data center for biodiversity conservation in China by implementing a systematic Resources and Environmental Sciences of the Chinese Academy of priority-setting approach with the integration of human distur- Sciences for providing data on land uses, human population density and bances, ecosystem- and species-level conservation features, and GDP. PAG acknowledges the support of Chrissie, Sara, and Jenni. principles of complementarity and representativeness. Inclusion of human disturbance is essential for a cost-effective priority-setting – Author Contributions maximizing conservation achievement while minimizing conflicts with economic development. Such an approach will ensure the Conceived and designed the experiments: RDW YCL GPM PAG SZ. optimal spatial distribution of priority areas and reduce biases in Performed the experiments: RDW SZ DQL PZ LZW HRD. Analyzed the conservation investment and/or land-use planning. The majority data: RDW YCL LZW HRD. Contributed reagents/materials/analysis tools: RDW DQL LZW HRD. Wrote the paper: RDW YCL GPM PAG of priority units we identified are located in relatively remote, high SZ. and/or rugged places, however, areas that are moderately- disturbed, ,2,000 m in altitude, and/or intermediately- to References 1. McCarthy DP, Donald PF, Scharlemann JPW, Buchanan GM, Balmford A, et 15. Zhang YB, Ma KP (2008) Geographic distribution patterns and status al. (2012) Financial costs of meeting global biodiversity conservation targets: assessment of threatened plants in China. Biodiversity and Conservation 17: 1783–1798. current spending and unmet needs. Science 338: 946–949. 2. 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Published: Jul 29, 2014

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