燕山地区国家重点保护鸟类生境评估与国家级自然保护区保护空缺分析

燕山地区地处太行山生物多样性保护优先区,紧邻人口密集的京津冀城市群,拥有很高的鸟类物种多样性.为探讨燕山地区的鸟类生境状况与保护效益,本研究以当地40种国家重点保护鸟类为指示物种,利用物种分布模型和Marxan系统保护规划模型进行了保护空缺分析与保护策略优化.研究发现,在燕山地区的鸟类生境中,森林的面积最大(6 537...     

西南地区生物多样性保护优先格局评估

选择831种西南地区重要保护物种为指示物种,分析指示物种空间分布特征,基于系统保护规划理论应用MARXAN模型评估西南生物多样性保护优先格局,确定优先保护区域,在最小保护成本条件下达到最优化的保护效果。结果表明:生物多样性保护优先区面积89.88×10~4km~2,占西南研究区面积的37%;保护优先区内除鸟类外其他类别栖息地面积均超过各自栖息地面积50%,其中94%指示物种栖息地面积比例超过60%;GAP分析发现,保护优先区同国家级自然保护区存在空间分布不匹配的现象;建议在原有国家级自然保护区基础上优先扩充保护区范围,并借助国家公园建设等政策适当建立新的自然保护体系。     

三江平原湿地鸟类丰富度的空间格局及热点地区保护

全球气候变化和人类的开垦开发活动使湿地生物多样性遭到严重的干扰和破坏,导致生物多样性空间分布格局及热点地区的保护成为研究的热点。在对三江平原湿地鸟类预测的基础上,利用空间自相关方法分析三江平原湿地鸟类丰富度的空间分布格局,并找出湿地鸟类多样性的热点地区及优先保护顺序。研究结果表明,三江平原湿地鸟类丰富度高高集聚区主要分布在保护区及周边地区、河流和湖泊沿岸,是新建和扩建自然保护区的最佳区域。湿地鸟类丰富度高低集聚区主要分布在农田景观中,将它们设立成微型保护地块对于区域景观生态安全具有重要意义;利用湿地鸟类物种丰富度、国家级保护湿地鸟类、生境类型和结构、距最近保护区距离、破碎度、干扰度等指标,在研究区内共找到13个热点地区,总面积为1018.7km²,占研究区总面积的8%;利用系统聚类分析,将13个热点地区划分成3种优先保护顺序。构建的小区域范围内寻找生物多样性热点地区的方法,为相关政府部门更有效地进行湿地生物多样性的保护和管理提供科学依据。     

海南岛生物多样性保护优先区评价与系统保护规划

选择海南岛140个濒危物种为指示物种,在物种栖息地评价的基础上,利用系统保护规划工具MARXAN模型进行迭代运算,提出了海南岛生物多样性保护优先区域,并对保护优先区进行评价.结果表明:海南岛保护优先区面积5383.7km2,占海南岛陆地面积的15.6%,集中分布于鹦哥岭、尖峰岭、五指山等林区和北部湿地;在保护优先区中,11个I级指示物种栖息地的保护比例均超过各自栖息地总面积的65%.通过对保护优先区与现有自然保护区的空缺分析,建议扩充尖峰岭保护区群、鹦哥岭-黎母山保护区群、五指山-吊罗山保护区群;新建抱龙林场-林鼻岭-福万岭保护体系;在海南岛北部建立以水源保护为主,同时兼顾珍稀物种保护的水源地保护带.     

长江上游森林生态区生物多样性保护优先区确定--基于生态区保护方法

邀请110位在长江上游地区开展生物多样性研究与保护的专家,分4个阶段进行了参与式研讨,采用生态区保护方法确定了兽类、鸟类、两栖和爬行类、昆虫、真菌和维管植物等生物类群的指示物种和保护优先区,最后确定了长江上游森林生态区内16个生物多样性保护优先区和5个连接带。16个优先区中,7个具有最高优先性,即秦岭、大巴山、金佛山-梵净山-武陵源区、岷山、邛崃山-大相岭、贡嘎山、三江并流核心区;9个具有高优先性,即伏牛山、米仓山、若尔盖高原、凉山、攀西地区、中甸-木里地区、川西北高原、金沙江上游高山峡谷区、怒江—澜沧江高山峡谷区。目前这些优先区及连接带内保护区的分布很不平衡:某些优先区和连接带内保护区面积所占比例很小甚至没有保护区分布;某些优先区人为干扰比较强烈,生境破碎化比较严重。建议通过新建自然保护区和调整已有的保护区,填补保护空缺,完善自然保护区系统;结合国家重点生态建设工程和生物多样性保护行动,保护天然林,恢复退化植被,在优先区和连接带内限制人类经济活动,以确保优先区和连接带发挥应有的生态功能。     

基于随机森林模型的国家重点保护陆生脊椎动物物种优先保护区的识别

准确可靠地识别国家重点保护陆生脊椎动物物种的优先保护区,是生物多样性保护的热点问题之一。采用随机森林(random forests)模型,基于12个环境变量,对中国263种国家重点保护陆生脊椎动物建模,并预测各个物种在背景点的适生概率,迭加计算得到国家重点保护陆生脊椎动物物种的生境适宜性指数。此外,基于对生境适宜性指数的空间自相关分析,识别和确定国家重点保护陆生脊椎动物物种优先保护区,并对优先保护区目前的被保护情况进行分析。结果表明,国家重点保护陆生脊椎动物物种的优先保护区的面积为103.16万km~2,约占我国国土面积的10.90%。优先保护区主要分布在我国的西部地区,包括西南地区的秦岭-大巴山山区、云南省与印度及缅甸的交界地区、武陵山山区、喜马拉雅山-横断山脉山区、阿尔泰山脉山区、天山山脉山区、昆仑山山脉山区;东北的大、小兴安岭、东北-华南沿海地区及长江中下游地区有少量分布。优先保护区中被保护的面积为50.40万km~2,占优先保护区总面积的48.86%,保护率偏低,未被充分保护。利用系统聚类分析,将未被保护的优先保护区划分成3种优先保护顺序,以期为相关部门的决策提供科学依据,更好地保护生物多样性。     

重庆澎溪河湿地自然保护区生物多样性空间格局及热点区

生物多样性空间格局和热点区域的分析与探测是进行生物多样性保护规划和科学管理的有效途径。以重庆澎溪河湿地自然保护区为例,基于实地综合调查、历史资料、文献信息,利用生境质量指数、物种多样性和景观多样性评价指标,构建生物多样性综合指数。结合空间自相关分析,揭示保护区生物多样性空间分布格局及其空间自相关程度,并识别生物多样性热点区,探讨现有保护区对热点区域的保护有效性。结果表明: 保护区生物多样性空间格局呈现出随距河流及两岸消落带距离的增加而减少的趋势,生物多样性指数高值区主要集中在澎溪河、普里河、白夹溪及其沿岸地区。生物多样性在空间分布上具有显著的正相关性,局部空间自相关以高-高聚集和低-低聚集类型为主。生物多样性热点区域面积为457 hm²,占保护区总面积的11.1%。现有保护区核心区涵盖了51%的热点区域和50%的次热点区域,保护区结构和功能区布局有待进一步优化调整,建议将普里河段龙王堂区域,白夹溪小垭口、邓家湾、洞子岩、龙王塘、旧屋咀、铧头咀、新铺子与龙家院子等热点区域纳入核心区,将冷点区域划到核心区之外,完善保护区功能区划。研究结果可为保护区范围及功能区优化和管控、合理推进“三区变两区”调整提供定量的基础资料,对于提高物种保护效率、制定科学的保护策略具有指导意义。     

基于系统保护规划方法东北生物多样性热点地区和保护空缺分析

根据东北地区生物多样性特征,利用系统保护规划方法和国际上常用的保护规划软件C- plan,计算了规划单元的不可替代性值,确定了区域生物多样性热点地区,并根据保护区分布现状进行了生物多样性保护空缺分析.结果显示,东北地区不可替代性较高的热点地区有4个,分别是:(1)长白山西北部林区,(2)大兴安岭北段山地区,(3)大兴安岭南部森林与草原过渡区,(4)松嫩平原中部湿地区. 在优先、一般、非优先3个等级中,需要优先保护地区的总面积是19.49×104km2,约占区域总面积的20.91%.同时,根据已建保护区分布情况研究发现,区域内存在3个明显的保护空缺,即长白山西北部林区、大兴安岭北段山地区和大兴安岭南段森林草原过渡区.建议新建和扩建保护区,同时建立生态廊道把相应的保护区关联起来,以实现区域内生物多样性保护目标.     

厦门市重点保护植物空间优先保护格局研究

生物多样性保护对维持城市生态系统功能具有重要意义。以39种厦门市重点保护植物为对象,通过物种分布模型MaxENT获得物种潜在分布栅格图,利用空间保护优先化定量工具Zonation软件识别理论上既适宜重点保护植物生存又能够保证景观连通性的区域,获得本地重点保护植物景观保护等级。根据2020年全球生物多样性目标,将景观保护等级最高的17%区域视为多物种空间优先保护区,结合Zonation模型生成的随景观丧失物种加权灭绝风险曲线,将保护等级最高的8%区域划为一级保护区,保护等级在8%-17%范围内的区域划为二级保护区。利用MaxENT模型中的jackknife刀切法发现海拔是对本地重点保护植物分布影响最大的环境因子,优先保护区集中分布于海拔较低的海岸带区域。将优先保护区与自然保护地建设现状、厦门市生态功能区规划、土地利用规划、城市总体规划对比发现厦门市岛外西部、北部的优先保护区得到了较好保护;岛外的西南部及东南部、岛内的东部及南部海岸带的优先保护区被建设用地大规模占用,已纳入自然保护地范围的区域较少,存在大量的海岸带优先保护区保护空缺;岛外东南部的部分优先保护区虽未被占用,但规划中属发展备用地,缺乏生态保护。为避免优先保护区面积的进一步萎缩,应重点关注海岸带区域优先保护区的生态保护,将目前属于发展备用地的优先保护区转划为生态留白空间,针对一级、二级优先保护区分别实施刚性和弹性的生态保育措施,在保护生物多样性的同时,严控对海岸带区域优先保护区的进一步开发利用,协调优先保护区内保护与开发利用间的关系。     

贵州省国家重点保护野生植物物种丰富度分布特征及保护优先区分析

该研究以国家重点保护野生植物为指示物种,结合贵州各县(市、区)的国家重点保护野生植物调查统计信息,基于GIS技术,分析了贵州省国家重点保护野生植物物种丰富度分布特征;应用Dobson算法筛选识别贵州国家重点保护野生植物的保护优先区,并利用全省已建自然保护区信息评价分析所筛选的保护优先区的保护现状。结果表明:(1)在贵州国家重点保护野生植物的物种丰富度分布上,总体来说全省南部地区高于北部地区,环省界区域往内陆延伸的物种丰富度明显呈现减少趋势。(2)在75%和100%的国家重点保护野生植物物种保护水平上,筛选识别出了荔波县等4个和17个县域为保护优先区,其中分别有1个和9个国家重点保护野生植物保护优先区内涵盖的自然保护区面积低于5%,且涉及的自然保护区中68.26%的面积是市/县级。(3)贵州国家重点保护野生植物物种较丰富的区域和全省生物多样性热点区域与所筛选识别的保护优先区有较好的空间对应关系。(4)贵州国家重点保护野生植物的就地保护应以国家重点保护野生植物地理分布丰富的区域结合本研究筛选的保护优先区为重点,进行优先保护。     

Biodiversity hotspots are not congruent with conservation areas in the Gulf of California

As marine systems are threatened by increasing human impacts, mechanisms to maintain biodiversity and ecosystem functions and services are needed. Protecting areas of conservation importance may serve as a proxy for maintaining these functions, while also facilitating efficient use and management of limited resources. Biodiversity hotspots have been used as surrogates for spatial conservation importance; however, as many protected areas have been established opportunistically and under differing criteria, it is unclear how well they actually protect hotspots. We evaluated how well the current protected area network and priority areas selected through previous systematic conservation planning exercises preserve biodiversity hotspots in the Gulf of California, Mexico. We also determined spatial congruence between biodiversity hotspots based on different criteria, which may determine their ability to be used as surrogates for each other. We focus on the Gulf of California because it is a megadiverse system where limited information regarding species diversity and distribution has constrained development of strategies for conservation and management. We developed a species occurrence database and identified biodiversity hotspots using four different criteria: species richness, rarity, endemism, and threatened species. We interpolated species occurrence, while accounting for heterogeneous sampling efforts. We then assessed overlap of hotspots with existing protected areas and priority areas, and between hotspots derived by distinct criteria. We gathered 286,533 occurrence records belonging to 12,105 unique species, including 6388 species identified as rare, 642 as endemic, and 386 as threatened. We found that biodiversity hotspots showed little spatial overlap with areas currently under protection and previously identified priority areas. Our results highlight the importance of distinct spatial areas of biodiversity and suggest that different ecological mechanisms sustain different aspects of diversity and multiple criteria should be used when defining conservation areas.     

遥感植被指数与植物多样性的相关性及空间分布特征研究——以海口市主城区为例

植物多样性监测是开展物种保护与植被景观规划的重要基础,对实施生物多样性的优先区域保护具有重要意义。该文以海口市主城区为例,利用Landsat 8遥感数据与样方实测数据分析了植被指数与植物多样性指数之间的相关性,根据相关性分析结果构建植物多样性遥感监测数学模型,并筛选出最优模型用于监测研究区植物多样性的空间分布状况。结果表明:Shannon-Wiener多样性指数、Simpson多样性指数和Pielou均匀度指数与MSAVI植被指数相关系数最高,呈显著相关性(P<0.01)。通过一元线性数学回归模型得到的海口市植物多样性空间分布特征与实际情况相符,植物多样性水平较高的区域主要分布在火山口、东寨港和羊山湿地一带,且具有明显的空间自相关性。根据研究结果建议继续实施严格的保护措施,加强生态修复与保护工程,提高植被覆盖率和生物多样性水平。     

Spatial phylogenetics of the native woody plant species in Hainan,China

To better identify biodiversity hotspots for conservation on Hainan Island, a tropical island in southern China, we assessed spatial variation in phylogenetic diversity and species richness using 18,976 georeferenced specimen records and a newly reconstructed molecular phylogeny of 957 native woody plants. Within this framework, we delineated bioregions based on vegetation composition and mapped areas of neoendemism and paleoendemism to identify areas of priority for conservation. Our results reveal that the southwest of Hainan is the most important hot spot for endemism and plant diversity followed by the southeast area. The distribution of endemic species showed a scattered, rather than clustered, pattern on the island. Based on phylogenetic range‐weighted turnover metrics, we delineated three major vegetational zones in Hainan. These largely correspond to natural secondary growth and managed forests (e.g., rubber and timber forests) in central Hainan, old‐growth forests and natural secondary growth forest at the margins of Hainan, and nature reserves on the island (e.g., Jianfeng and Diaoluo National Nature Reserves). Our study helps to elucidate potential botanical conservation priorities for Hainan within an evolutionary, phylogenetic framework.     

基于系统保护规划的黄河流域湿地优先保护格局

黄河流域湿地为我国生物多样性维持提供了重要生境.本研究基于黄河流域气候分区、地貌单元及湿地遥感数据,构建黄河流域生态地理综合湿地分类系统.在系统保护规划理论框架下,将湿地气候-地貌分类单元作为生态系统层次保护对象,结合黄河流域鸟类分布范围作为物种层次的保护对象,设定30%湿地优化目标,将公路、铁路、城镇、农村居民点、水坝等作为度量因子创建黄河流域保护代价图层,并利用系统保护规划工具--Marxan软件构建黄河流域湿地保护优化格局,识别湿地保护空缺.结果表明: 黄河流域大部分沼泽湿地集中在黄河上游区域,目前源区保护区覆盖面积大,在内蒙古、甘肃及四川部分区域一些稀有湿地类型游离在保护体系外;黄河中游湿地类型以河道和河滩湿地类型为主,保护覆盖率极低,保护空缺严重,经优化保护网络体系后,保护成效可分别得到29.1%、37.6%的提升.黄河下游湿地主要集中在黄河三角洲区域,目前保护体系完整,保护空缺面积极小.总体上,黄河流域中游河流湿地的保护空缺比例最高,亟需重视.本研究基于湿地保护格局优化结果分区分析黄河流域湿地保护模式,为黄河流域湿地的保护规划管理提供了科学性建议,从宏观层面上为黄河流域水生态保护奠定了基石.     

Comparison of marine spatial planning methods in Madagascar demonstrates value of alternative approaches

The Government of Madagascar plans to increase marine protected area coverage by over one million hectares. To assist this process, we compare four methods for marine spatial planning of Madagascar's west coast. Input data for each method was drawn from the same variables: fishing pressure, exposure to climate change, and biodiversity (habitats, species distributions, biological richness, and biodiversity value). The first method compares visual color classifications of primary variables, the second uses binary combinations of these variables to produce a categorical classification of management actions, the third is a target-based optimization using Marxan, and the fourth is conservation ranking with Zonation. We present results from each method, and compare the latter three approaches for spatial coverage, biodiversity representation, fishing cost and persistence probability. All results included large areas in the north, central, and southern parts of western Madagascar. Achieving 30% representation targets with Marxan required twice the fish catch loss than the categorical method. The categorical classification and Zonation do not consider targets for conservation features. However, when we reduced Marxan targets to 16.3%, matching the representation level of the "strict protection" class of the categorical result, the methods show similar catch losses. The management category portfolio has complete coverage, and presents several management recommendations including strict protection. Zonation produces rapid conservation rankings across large, diverse datasets. Marxan is useful for identifying strict protected areas that meet representation targets, and minimize exposure probabilities for conservation features at low economic cost. We show that methods based on Zonation and a simple combination of variables can produce results comparable to Marxan for species representation and catch losses, demonstrating the value of comparing alternative approaches during initial stages of the planning process. Choosing an appropriate approach ultimately depends on scientific and political factors including representation targets, likelihood of adoption, and persistence goals.     

Hotspots and ecoregions: a test of conservation priorities using taxonomic data

The loss of biodiversity is now recognized as a global problem of significant magnitude [ Science 289: 2279]. Conservation efforts focus on measuring species diversity and distribution, assessing biodiversity threats, and managing habitats to maintain that diversity. The accuracy of measuring species diversity depends on the quality and scale of the data. Recently indirect estimates of diversity based on the skilled opinions of international taxonomic authorities were used to define 25 global conservation hotspots [ Nature 403: 853–858] and 871 ecoregions [ Bioscience 51: 933–938]. These data, originating from first-hand fieldwork and museum study, are readily available, but not necessarily repeatable nor testable. If this type of information prevails for conservation purposes, it is critical that we test the quality of this information with verifiable data at finer scales (e.g., regional inventories, specimen records, and accumulated distribution data). Here we perform such a test for the hotspots and ecoregions found in the Indo-Pacific by comparing the estimates of the expert scientists with authenticated published diversity data on flowering plants. We found a high correlation between our counts of species richness and endemism with the experts' estimates, but surprisingly found less congruity among the seven families examined. A revised list of conservation priority regions based on our plant data is provided.     

Biodiversity Hotspots and Conservation Priorities in the Campo-Ma’an Rain Forests,Cameroon

Until recently, patterns of species richness and endemism were based on an intuitive interpretation of distribution maps with very limited numerical analyses. Such maps based solely on taxonomic collections tend to concentrate on collecting efforts more than biodiversity hotspots, since often the highest diversity is found in well-collected areas. During the last decades, there has been an overwhelming concern about the loss of tropical forest biological diversity, and an emphasis on the identification of biodiversity hotspots in an attempt to optimise conservation strategies. Furthermore, the concept of sites of high diversity, or hotspots, has attracted the attention of conservationists as a tool for conservation priority settings. With the development of GIS tools, geostatistics, phytosociological and multivariate analysis software packages, more rigorous numerical analyses of distributional and inventory data can be used for assessing conservation priorities. In the Campo-Ma’an rain forest, inventory data from 147 plots of 0.1 ha each and 7137 taxonomic collections were used to examine the distribution and convergence patterns of strict and narrow endemic species. We analysed the trends in endemic and rare species recorded, using quantitative conservation indices such as Genetic Heat Index (GHI) and Pioneer Index (PI), together with geostatistic techniques that help to evaluate and identify potential areas of high conservation priority. The results showed that the Campo-Ma’an area is characterised by a rich and diverse flora with 114 endemic plant species, of which 29 are restricted to the area, 29 also occur in southwestern Cameroon, and 56 others that are also found in other parts of Cameroon. Although most of the forest types rich in strict and narrow endemic species occur in the National Park, there are other biodiversity hotspots in the coastal zone and in areas such as Mont d’Eléphant and Massif des Mamelles that are located outside the National Park. Unfortunately, these areas, supporting 17 strict endemic species that are not found in the park, are under serious threat and do not have any conservation status for the moment. Taking into consideration that with the growing human population density, pressure on these hotspots will increase in the near future, it is suggested that priority be given to the conservation of these areas and that a separate management strategy be developed to ensure their protection.     

京津冀地区物种多样性保护优先区识别研究

着力扩大环境容量和生态空间，加强跨区环境保护合作，是落实京津冀一体化协同发展国家战略的重要内容。摸清京津冀地区的生物多样性分布格局，可为国家公园布局、生态环境保护工程的实施提供依据。根据"自然保护区生物多样性保护价值评估技术规程（LY/T 2649-2016）"，基于京津冀地区自然保护区的综合科学考察报告，评估了京津冀地区典型自然保护区的物种多样性保护价值，并以其为因变量，以自然保护区的综合地形地貌为自变量，构建多元回归模型，同时以自然保护区的平均面积为基准，利用ArcGIS的创建"渔网"功能，将京津冀地区划分为1638个网格单元，利用构建的多元回归模型评估了这些网格单元的保护价值。结果表明：京津冀地区国家级自然保护区的保护价值平均得分为204分，比参评的全部35个自然保护区的平均分高40分；在省级自然保护区中也存在一些得分较高的自然保护区，如，唐海湿地自然保护区和河北南大港自然保护区，且超过了参评国家级自然保护区保护价值得分的平均值。京津冀地区的物种多样性保护优先区总面积为36791.35 km²，占京津冀地区总面积的16.94%，其中一级保护优先区面积4611.57 km²，二级保护优先区面积16045.79 km²，三级保护优先区面积16133.98 km²。这些区域主要分布在河北省和北京市的北部地区，区域内绝大部分以森林植被和灌丛植被为主。建议在未来的国家公园布局、生态环境保护工程布局中重点考虑这些地区。