利用GARP生态位模型预测桔小实蝇（Bactrocera dorsalis）在中国的适生区域

桔小实蝇Bactrocera dorsalis (Hendel)是一种多食性害虫,明确其可能适生的区域对该虫的科学监测及防治意义重大。利用桔小实蝇在我国的已知分布点数据和亚洲地区的14个环境地理变量图层,运用GARP生态位模型结合GIS空间分析模块预测了该虫在亚洲的地理分布。结果表明桔小实蝇可分布在中国、日本、菲律宾、马来西亚、泰国北部、越南、柬埔寨、老挝、缅甸、尼泊尔、巴基斯坦、孟加拉国和斯里兰卡,这与EPPO报道的分布区域一致。将拟合过程中获得的生态位运算法则投影到我国,并考虑模型间的一致性,预测桔小实蝇在我国各省及市县范围的分布：云南大部、四川南部和东部、贵州大部、重庆大部、广西、广东、台湾、香港、澳门、海南、福建、江西、浙江大部、湖南大部、湖北大部、上海、江苏南部、河南局部及安徽部分地区为桔小实蝇的适生区。次适生区沿适生区周围分布,为四川、贵州、重庆、湖北北部、河南南部和江苏南部的一些零星地区。适生区和次适生区大多有较高密度的寄主果树,为桔小实蝇的生存提供了条件。预测结果经独立验证数据的适合性测验表明,选择的最优模型具有显著的统计学意义,显示了很好的预测能力。GARP生态位模型可以解决生态学、生物地理学和环境保护方面的一系列问题,具有广泛的应用前景,为物种已知基础分布点资料的综合分析以及有害生物的适生性分析、监测和防治提供了技术平台。     

Estimating ancestral distributions of lineages with uncertain sister groups： a statistical approach to Dispersal-Vicariance Analysis and a case using Aesculus L. （Sapindaceae） including fossils

We propose a simple statistical approach for using Dispersal-Vicariance Analysis （DIVA） software to infer biogeographic histories without fully bifurcating trees. In this approach, ancestral ranges are first optimized for a sample of Bayesian trees. The probability P of an ancestral range r at a node is then calculated as P（rY） = ∑t^n=1 F（rY）t Pt where Y is a node, and F（rY） is the frequency of range r among all the optimal solutions resulting from DIVA optimization at node Y, t is one of n topologies optimized, and Pt is the probability of topology t. Node Y is a hypothesized ancestor shared by a specific crown lineage and the sister of that lineage ＂x＂, where x may vary due to phylogenetic uncertainty （polytomies and nodes with posterior probability 〈 100%）. Using this method, the ancestral distribution at Y can be estimated to provide inference of the geographic origins of the specific crown group of interest. This approach takes into account phylogenetic uncertainty as well as uncertainty from DIVA optimization. It is an extension of the previously described method called Bayes-DIVA, which pairs Bayesian phylogenetic analysis with biogeographic analysis using DIVA. Further, we show that the probability P of an ancestral range at Y calculated using this method does not equate to pp＊F（rY） on the Bayesian consensus tree when both variables are 〈 100%, where pp is the posterior probability and F（rY） is the frequency of range r for the node containing the specific crown group. We tested our DIVA-Bayes approach using Aesculus L., which has major lineages unresolved as a polytomy. We inferred the most probable geographic origins of the five traditional sections of Aesculus and ofAesculus californica Nutt. and examined range subdivisions at parental nodes of these lineages. Additionally, we used the DIVA-Bayes data from Aesculus to quantify the effects on biogeographic inference of including two wildcard fossil taxa in phylogenetic analysis. Our analysis resolved the geographic     

土地经济生态位在县域景观格局分析中的应用——以新疆精河县为例

本文将土地经济生态位的理论和方法引入到景观生态学当中,为区域景观格局表征提供了新的方法.选择典型的生态脆弱区精河县为研究对象,以1990、1998、2011和2013年4期Landsat影像为数据源,运用生态位态势理论计算研究区各土地利用类型的土地经济生态位,并结合景观生态学理论探讨土地经济生态位在县域景观格局分析中的应用.结果表明: 研究期间,精河县耕地、建设用地和草地的土地经济生态位与相应的景观斑块数、聚合度、破碎化指数和分维数具有较好的相关性;土地经济生态位的变化对县域景观格局具有驱动作用,可表征精河县经济发展方向.土地经济生态位与可直接获得经济效益的土地利用类型关系密切,且与景观指数相结合能够很好地解释精河县景观格局的特征.     

Estimating ancestral distributions of lineages with uncertain sister groups: a statistical approach to Dispersal–Vicariance Analysis and a case using Aesculus L. (Sapindaceae) including fossils

Abstract We propose a simple statistical approach for using Dispersal–Vicariance Analysis (DIVA) software to infer biogeographic histories without fully bifurcating trees. In this approach, ancestral ranges are first optimized for a sample of Bayesian trees. The probability P of an ancestral range r at a node is then calculated as where Y is a node, and F(r_Y ) is the frequency of range r among all the optimal solutions resulting from DIVA optimization at node Y, t is one of n topologies optimized, and Pt is the probability of topology t. Node Y is a hypothesized ancestor shared by a specific crown lineage and the sister of that lineage “x”, where x may vary due to phylogenetic uncertainty (polytomies and nodes with posterior probability <100%). Using this method, the ancestral distribution at Y can be estimated to provide inference of the geographic origins of the specific crown group of interest. This approach takes into account phylogenetic uncertainty as well as uncertainty from DIVA optimization. It is an extension of the previously described method called Bayes‐DIVA, which pairs Bayesian phylogenetic analysis with biogeographic analysis using DIVA. Further, we show that the probability P of an ancestral range at Y calculated using this method does not equate to pp*F(r_Y ) on the Bayesian consensus tree when both variables are <100%, where pp is the posterior probability and F(r_Y ) is the frequency of range r for the node containing the specific crown group. We tested our DIVA‐Bayes approach using Aesculus L., which has major lineages unresolved as a polytomy. We inferred the most probable geographic origins of the five traditional sections of Aesculus and of Aesculus californica Nutt. and examined range subdivisions at parental nodes of these lineages. Additionally, we used the DIVA‐Bayes data from Aesculus to quantify the effects on biogeographic inference of including two wildcard fossil taxa in phylogenetic analysis. Our analysis resolved the geographic ranges of the parental nodes of the lineages of Aesculus with moderate to high probabilities. The probabilities were greater than those estimated using the simple calculation of pp*F(r_y) at a statistically significant level for two of the six lineages. We also found that adding fossil wildcard taxa in phylogenetic analysis generally increased P for ancestral ranges including the fossil's distribution area. The ΔP was more dramatic for ranges that include the area of a wildcard fossil with a distribution area underrepresented among extant taxa. This indicates the importance of including fossils in biogeographic analysis. Exmination of range subdivision at the parental nodes revealed potential range evolution (extinction and dispersal events) along the stems of A. californica and sect. Parryana.     

社会-经济-自然复合生态系统生态位评价模型——以四川省为例

在深入分析区域资源、环境、社会、经济综合系统基础上,建立了四川省2001—2010年社会-经济-自然复合生态系统生态位评价指标体系,复合生态系统综合生态位包括资源、环境、经济和社会4个子系统生态位。将耦合投影寻踪模型应用于复合生态系统生态位评价,其中,采用并行模拟退火算法对评价模型参数进行优化。研究结果表明:2001年—2010年四川省复合生态位呈现先降后升的趋势,复合生态位评价值从2001年3.1325下降到2005年的2.8499,从2005年开始,复合生态位逐渐增加,到2010年增加到3.3304。表明环境重视程度的提高,环保意识的加强,促进了复合生态位的提高,区域自然生态和环境得以改善。最佳投影方向各分量的大小反映了各评价指标对生态位评价等级的影响程度,值越大则对应的评价指标对生态位评价等级的影响程度越大。区域生态位评价等级指标的影响程度最大的10项中有4项是环境生态位子系统指标,表明环境生态位子系统对综合生态位影响最大。发展过程中经济生态位子系统和社会生态位子系统指标值相关系数为0.9957,表明两子系统基本上是保持同步发展。而经济生态位和环境生态位子系统指标值相关系数为-0.9346,呈现明显的负相关关系。资源子系统呈现上升趋势。模拟退火优化的投影寻踪耦合模型应用于复合生态位评价,具有实用性和可行性,为区域生态管理科学决策提供重要依据。     

Ecological niche modeling re‐examined: A case study with the Darwin's fox

Many previous studies have attempted to assess ecological niche modeling performance using receiver operating characteristic (ROC) approaches, even though diverse problems with this metric have been pointed out in the literature. We explored different evaluation metrics based on independent testing data using the Darwin's Fox (Lycalopex fulvipes) as a detailed case in point. Six ecological niche models (ENMs; generalized linear models, boosted regression trees, Maxent, GARP, multivariable kernel density estimation, and NicheA) were explored and tested using six evaluation metrics (partial ROC, Akaike information criterion, omission rate, cumulative binomial probability), including two novel metrics to quantify model extrapolation versus interpolation (E‐space index I) and extent of extrapolation versus Jaccard similarity (E‐space index II). Different ENMs showed diverse and mixed performance, depending on the evaluation metric used. Because ENMs performed differently according to the evaluation metric employed, model selection should be based on the data available, assumptions necessary, and the particular research question. The typical ROC AUC evaluation approach should be discontinued when only presence data are available, and evaluations in environmental dimensions should be adopted as part of the toolkit of ENM researchers. Our results suggest that selecting Maxent ENM based solely on previous reports of its performance is a questionable practice. Instead, model comparisons, including diverse algorithms and parameterizations, should be the sine qua non for every study using ecological niche modeling. ENM evaluations should be developed using metrics that assess desired model characteristics instead of single measurement of fit between model and data. The metrics proposed herein that assess model performance in environmental space (i.e., E‐space indices I and II) may complement current methods for ENM evaluation.     

MaxEnt模型参数设置对其所模拟物种地理分布和生态位的影响——以茶翅蝽为例

【目的】生态位模型被广泛应用于入侵生物学和保护生物学研究,现有建模工具中,MaxEnt是最流行和运用最广泛的生态位模型。然而最近研究表明,基于MaxEnt模型的默认参数构建模型时,模型倾向于过度拟合,并非一定为最佳模型,尤其是在处理一些分布点较少的物种。【方法】以茶翅蝽为例,通过设置不同的特征参数、调控倍频以及背景拟不存在点数分别构建茶翅蝽的本土模型,然后将其转入入侵地来验证和比较模型,通过检测模型预测的物种对环境因子的响应曲线、潜在分布在生态空间中的生态位映射以及潜在分布的空间差异性,探讨3种参数设置对MaxEnt模型模拟物种分布和生态位的影响。【结果】在茶翅蝽的案例分析中,特征参数的设置对MaxEnt模型所模拟的潜在分布和生态位的影响最大,调控倍频的影响次之,背景拟不存在点数的影响最小。与其他特征相比,基于特征H和T的模型其响应曲线较为曲折;随着调控倍频的增加,响应曲线变得圆滑。【结论】在构建MaxEnt模型时,需要从生态空间中考虑物种的生态需求,分析模型参数对预测物种分布和生态位可能造成的影响。     

Spatial patterns,ecological niches,and interspecific competition of avian brood parasites: inferring from a case study of Korea

Since obligate avian brood parasites depend completely on the effort of other host species for rearing their progeny, the availability of hosts will be a critical resource for their life history. Circumstantial evidence suggests that intense competition for host species may exist not only within but also between species. So far, however, few studies have demonstrated whether the interspecific competition really occurs in the system of avian brood parasitism and how the nature of brood parasitism is related to their niche evolution. Using the occurrence data of five avian brood parasites from two sources of nationwide bird surveys in South Korea and publically available environmental/climatic data, we identified their distribution patterns and ecological niches, and applied species distribution modeling to infer the effect of interspecific competition on their spatial distribution. We found that the distribution patterns of five avian brood parasites could be characterized by altitude and climatic conditions, but overall their spatial ranges and ecological niches extensively overlapped with each other. We also found that the predicted distribution areas of each species were generally comparable to the realized distribution areas, and the numbers of individuals in areas where multiple species were predicted to coexist showed positive relationships among species. In conclusion, despite following different coevolutionary trajectories to adapt to their respect host species, five species of avian brood parasites breeding in South Korea occupied broadly similar ecological niches, implying that they tend to conserve ancestral preferences for ecological conditions. Furthermore, our results indicated that contrary to expectation interspecific competition for host availability between avian brood parasites seemed to be trivial, and thus, play little role in shaping their spatial distributions and ecological niches. Future studies, including the complete ranges of avian brood parasites and ecological niches of host species, will be worthwhile to further elucidate these issues.     

盐沼湿地大规模恢复的概念生态模型——以盐城为例

大规模湿地生态恢复是一项耗资巨大、复杂的系统工程,需要以整个区域湿地结构和功能恢复作为基本目标,将时间和空间上分散的研究成果进行系统梳理,形成对区域湿地生态变化及其驱动因素的规律性认识。本研究以盐城盐沼湿地为案例,以1987年作为未干扰或干扰较少的状态,从结构-过程-功能耦合作用角度,确定区域湿地恢复的关键生态特征,包括:健康与动态潮间带湿地系统、碱蓬生态系统生产力与弹性、复杂景观镶嵌与相互作用、潮间带底栖动物丰富与鸟类觅食基地,以及濒危与关键水鸟种群保护。在此基础上,将围垦与土地利用、水管理、全球变化与海平面上升作为驱动区域湿地生态变化的三大外部因素;海岸侵蚀与沉积、区域水格局变化、地形地貌变化、湿地空间变化与连通性丧失,以及互花米草入侵等是影响湿地生态系统变化的内在压力因子;基于这些压力因子与湿地生态系统变化之间复杂作用关系分析,形成了外部驱动力-内在压力源-生态影响-生态特征之间联合作用下的区域湿地恢复概念生态模型。此模型以复杂因果关系研究为基础,直观展示了湿地恢复需要去除或减缓各种压力因子的一般路径,有利于指导大规模盐沼湿地恢复规划与实践。     

黄土高原区主导生态风险识别及分异性研究——以黄河流域中游为例

黄河流域作为典型的生态脆弱区,其生态问题复杂多样,亟待全面的生态治理和修复。同时,黄河流域生态保护和高质量发展是当前我国发展战略之一。明确黄河流域存在的生态问题,做好区域生态修复,开展综合治理是黄河流域可持续发展的重点。因此把握黄河流域的自然条件的区域差异,开展综合性的生态风险识别与评价,明确区域风险空间异质性分布与特点,是服务于区域生态修复、促进黄河流域高质量发展的重点。结合黄河流域中游气候、地形、植被等多自然本底情况识别风险源,建立服务于研究区生态保护和修复的区域生态风险评价体系,并通过GEE和GIS平台,可视化和量化了各类生态风险,并采用空间相关分析明确了生态风险的主要成因。结果表明：1）研究区的生态风险空间分布具有显著的区域特征,各个要素的生态风险呈现明显的东南和西北的差异、不同土地覆被情况的差异、人类活动带与非人类活动带的差异以及河流沿河与非沿岸的差异;2）植被净生态系统生产力呈现东南高西北低的特征,温度植被干旱指数显示西北部、山西、陕西南部存在较高的干旱风险,土壤侵蚀风险主要存在于黄河沿岸、其他河谷地带以及西北部,防风固沙服务能力在山西省山区以及植被生长较好的地区较高;3）综合生态风险评价显示宁夏以及陕西北部多数地区属于高风险区,低风险区主要分布在研究区西南部以及山西省西部沿线地区;4）双变量的Moran''s I指数显示地表温度、植被覆盖和汛期降水是导致综合生态风险西北和东南差异的主要原因,坡度是导致局部风险差异的主要原因。     

Joint generalized models for multidimensional outcomes: A case study of neuroscience data from multimodalities

This paper is motivated from the analysis of neuroscience data in a study of neural and muscular mechanisms of muscle fatigue. Multidimensional outcomes of different natures were obtained simultaneously from multiple modalities, including handgrip force, electromyography (EMG), and functional magnetic resonance imaging (fMRI). We first study individual modeling of the univariate response depending on its nature. A mixed‐effects beta model and a mixed‐effects simplex model are compared for modeling the force/EMG percentages. A mixed‐effects negative‐binomial model is proposed for modeling the fMRI counts. Then, I present a joint modeling approach to model the multidimensional outcomes together, which allows us to not only estimate the covariate effects but also to evaluate the strength of association among the multiple responses from different modalities. A simulation study is conducted to quantify the possible benefits by the new approaches in finite sample situations. Finally, the analysis of the fatigue data is illustrated with the use of the proposed methods.     

基于激光雷达数据的物种分布模拟: 以美国加州内华达山脉南部区域食鱼貂分布模拟为例

生态位模型通过拟合物种分布与环境变量之间的关系提供物种空间分布预测, 在生物多样性研究中有广泛应用。激光雷达(LiDAR)是一种新兴的主动遥感技术, 已被大量应用于森林三维结构信息的提取, 但其在物种分布模拟的应用研究比较缺乏。本研究以美国加州内华达山脉南部地区的食鱼貂(Martes pennanti)的分布模拟为例, 探索LiDAR技术在物种分布模拟中的有效性。生态位模型采用5种传统多类分类器, 包括神经网络、广义线性模型、广义可加模型、最大熵模型和多元自适应回归样条模型, 并使用正样本-背景学习(presence and background learning, PBL)算法进行模型校正; 同时对这5种模型使用加权平均进行模型集成, 作为第6个模型。此外, 一类最大熵模型也被用于模拟该物种的空间分布。模型的连续输出和二值输出分别使用AUC (area under the receiver operating characteristic curve)以及基于正样本-背景数据的评价指标F_pb进行评价。结果表明, 仅考虑气候因子(温度和降水)时, 7个模型的AUC和F_pb平均值分别为0.779和1.077; 当考虑LiDAR变量(冠层容重、枝下高、叶面积指数、高程、坡度等)后, AUC和F_pb分别为0.800和1.106。该研究表明, LiDAR数据能够提高食鱼貂空间分布的预测精度, 在物种分布模拟方面存在一定的应用价值。     

Spatial sampling bias and model complexity in stream‐based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin,USA

Leveraging existing presence records and geospatial datasets, species distribution modeling has been widely applied to informing species conservation and restoration efforts. Maxent is one of the most popular modeling algorithms, yet recent research has demonstrated Maxent models are vulnerable to prediction errors related to spatial sampling bias and model complexity. Despite elevated rates of biodiversity imperilment in stream ecosystems, the application of Maxent models to stream networks has lagged, as has the availability of tools to address potential sources of error and calculate model evaluation metrics when modeling in nonraster environments (such as stream networks). Herein, we use Maxent and customized R code to estimate the potential distribution of paddlefish (Polyodon spathula) at a stream‐segment level within the Arkansas River basin, USA, while accounting for potential spatial sampling bias and model complexity. Filtering the presence data appeared to adequately remove an eastward, large‐river sampling bias that was evident within the unfiltered presence dataset. In particular, our novel riverscape filter provided a repeatable means of obtaining a relatively even coverage of presence data among watersheds and streams of varying sizes. The greatest differences in estimated distributions were observed among models constructed with default versus AIC_C‐selected parameterization. Although all models had similarly high performance and evaluation metrics, the AIC_C‐selected models were more inclusive of westward‐situated and smaller, headwater streams. Overall, our results solidified the importance of accounting for model complexity and spatial sampling bias in SDMs constructed within stream networks and provided a roadmap for future paddlefish restoration efforts in the study area.     

河西走廊土地利用/覆盖变化的景观生态效应——以肃州绿洲为例

近来,在土地利用／覆被变化研究中,都纷纷结合景观格局变化分析模型来研究其空间结构变化趋势及其生态效应,以期为土地持续利用规划设计提供依据。景观格局及其变化既是各种干扰因素相互作用的结果,又影响着区域的生态过程。运用景观生态学原理,借助GIS技术(Arc GIS8．1)和Fragstas 3．3软件,基于1988、2000年Landsat5的4、3、2(RGB)波段合成影像解译结果,对河西走廊中西段肃州绿洲LUCC及其景观生态效应进行了研究。结果表明：(1)受自然地理要素的影响,景观类型空间分布表现出明显的区域差异。耕地主要分布于水系两岸和河流冲积扇;草地主要分布于祁连山地及绿洲边缘;林地主要分布于河流两岸、祁连山北坡一带;戈壁、沙漠广泛分布于绿洲之间,景观格局呈现出以戈壁为基质的戈壁、绿洲、沙漠相间分布的态势;(2)各土地利用类型及景观格局指数均发生了重要变化,耕地、水域明显增加,城镇用地和农村居民点也逐步增加,草地、林地和未利用地呈减少趋势,尤其是高覆盖度草地全部消失;(3)斑块破碎化程度在减小,异质性也在减小,但生态环境质量仍在下降,表现为大部分草地、林地被开垦为耕地,降低了绿洲维护生态平衡的能力,加大了干旱绿洲业已超负的水资源载荷;(4)景观中斑块优势度在减小,斑块类型在景观中趋于均匀分布,异质性的减小和均质化发展必然导致景观稳定性的降低;(5)林地和草地边缘效应降低,使其对周围斑块类型的影响相应减小,原有的景观生态功能减弱;相反,水体、盐碱地和裸地边缘效应有所增强,盐碱地和裸地等对景观发展影响的增强则是景观退化的表现。     

Regional ecological risk assessment using a relative risk model: A case study of the Darwin Harbour,Darwin, Australia

There are many proposed and ongoing commercial, industrial, and residential developments within the Darwin Harbour catchment in Northern Australia, to accommodate the projected population growth over the next 20 years. Hence, it is necessary to ensure the balance between these developments and ecosystem conservation. We evaluated ecological risk for the Darwin Harbour using a relative risk model (RRM). The catchment was divided into 22 risk regions based on small catchment boundaries and their homogeneity. Through the RRM, we ranked and summed the stressors and habitats within regions. The interaction between stressors and habitats were modeled through exposure and effect filters. The ecological assessment endpoints were maintenance of the mangrove health and the maintenance of water quality. The risk regions—Myrmidon Creek, Blackmore River, Bleesers Creek, and Elizabeth River—showed the highest total relative risk for ecological assets. These risk regions had a high percentage cover of industrial, commercial, and residential areas; diffuse entry points; and climate change effects. Creek A, Sandy Creek, West Arm, and Pioneer Creek were the risk regions with lowest total relative risk scores. The RRM is a robust application that is suitable for a large geographic area where multiple stressors are of concern.     

Environmental change,shifting distributions,and habitat conservation plans: A case study of the California gnatcatcher

Many species have already experienced distributional shifts due to changing environmental conditions, and analyzing past shifts can help us to understand the influence of environmental stressors on a species as well as to analyze the effectiveness of conservation strategies. We aimed to (1) quantify regional habitat associations of the California gnatcatcher (Polioptila californica ); (2) describe changes in environmental variables and gnatcatcher distributions through time; (3) identify environmental drivers associated with habitat suitability changes; and (4) relate habitat suitability changes through time to habitat conservation plans. Southern California's Western Riverside County (WRC ), an approximately 4,675 km² conservation planning area. We assessed environmental correlates of distributional shifts of the federally threatened California gnatcatcher (hereafter, gnatcatcher) using partitioned Mahalanobis D ² niche modeling for three time periods: 1980–1997, 1998–2003, and 2004–2012, corresponding to distinct periods in habitat conservation planning. Highly suitable gnatcatcher habitat was consistently warmer and drier and occurred at a lower elevation than less suitable habitat and consistently had more CSS , less agriculture, and less chaparral. However, its relationship to development changed among periods, mainly due to the rapid change in this variable. Likewise, other aspects of highly suitable habitat changed among time periods, which became cooler and higher in elevation. The gnatcatcher lost 11.7% and 40.6% of highly suitable habitat within WRC between 1980–1997 to 1998–2003, and 1998–2003 to 2004–2012, respectively. Unprotected landscapes lost relatively more suitable habitat (?64.3%) than protected landscapes (30.5%). Over the past four decades, suitable habitat loss within WRC , especially between the second and third time periods, was associated with temperature‐related factors coupled with landscape development across coastal sage scrub habitat; however, development appears to be driving change more rapidly than climate change. Our study demonstrates the importance of providing protected lands for potential suitable habitat in future scenarios.     

基于能值-生态足迹模型的东北老工业基地生态安全评价——以辽宁省为例

采用能值-生态足迹模型,对辽宁省2003—2012年生态安全状况进行时间序列的定量分析与评价,并采用灰色动力学模型预测其动态变化趋势.结果表明: 研究期内辽宁省人均能值生态承载力从3.13 hm²下降到3.07 hm²,人均能值生态足迹由13.88 hm²增加到21.96 hm²,处于生态赤字状态,且赤字增大趋势明显;生态压力指数由4.43增长到7.16,生态安全预警等级由轻警过渡到中警程度.照此发展,2013—2022年辽宁省人均能值生态承载力将由3.04 hm²下降到2.98 hm²,人均能值生态足迹将由22.72 hm²上升到35.87 hm²;生态赤字将越来越大,生态压力指数将由7.46上升到12.04,生态安全等级将由较安全变为轻度不安全状态,并呈现由中警到重警的生态安全预警等级,生态安全问题亟待解决.     

基于Google Earth Engine云计算的城市群生态质量长时序动态监测——以粤港澳大湾区为例

人类活动对生态环境的影响日益强烈,及时动态地监测生态现状及其变化信息对城市生态的管理和保护以及可持续发展具有重大意义。遥感生态指数(RSEI)是一种客观、快速和简便的生态质量监测和评价技术,已被广泛应用于生态学研究领域,但在进行大范围长时间监测时往往面临云遮挡和拼接困难的问题。因此,本文基于Google Earth Engine(GEE)平台,对1988—2018年来粤港澳大湾区共3530景Landsat遥感影像进行批量去云,采用中值合成法逐年计算绿度、湿度、干度和热度等遥感指标并利用主成分分析法构建遥感生态指数,评价了该区域近30年生态质量的时空变化。该方法改善了遥感生态指数在大范围长时序监测中数据缺失和拼接困难等问题,增加了时间序列的可比性。研究表明:(1)遥感生态指数能够较好地表征粤港澳大湾区的生态质量,其中绿度和湿度指标与其呈正相关,干度和热度指标与其呈负相关;(2)时间上,三十年间粤港澳大湾区生态质量呈"上升-下降-上升-下降"的波动下降趋势,空间上,生态质量具有明显的空间异质性,主要呈现西北和东北部高和中部低的状态。重度和中度退化区主要集中在区域中部,总体改善区域主要位于西...     

滨海快速城市化地区土地生态安全评价与预警——以曹妃甸新区为例

对滨海快速城市化地区进行土地生态安全评价和预警是保障土地可持续利用和有效维护土地生态安全的重要内容.基于“压力-状态-响应”(P-S-R)模型,构建了滨海快速城市化地区土地生态安全评价指标体系.借助遥感数据和GIS方法,以1 km×1 km网格为评价单元并通过空间插值,获取了基于像元大小30 m×30 m的曹妃甸新区2005和2013年土地生态安全评价结果.并采用分类树方法对未来曹妃甸新区土地生态安全(LES)进行预警,共分为4种预警类型：安全但有退化趋势预警、亚安全且缓慢退化预警、亚安全且快速退化预警、不安全预警.结果表明：曹妃甸新区2005年土地生态安全平均值为0.55,处于中等安全水平,而2013年为0.52,处于中下安全水平,区域土地生态安全呈下降趋势.曹妃甸新区不安全预警及亚安全且快速退化预警区域主要分布在城市建设用地快速扩展区域,说明城市建设用地的快速扩张是导致区域土地生态安全恶化的最主要因素.工业区、十里海和南堡盐场3个乡镇处于高度危险预警状态,其不安全预警、亚安全且快速退化预警及亚安全且缓慢退化预警3者之和分别占其总面积的58.3%、98.9%和81.2%,未来应加强这些区域的土地生态管理调控.研究结果可为曹妃甸新区土地规划和生态保护提供一定参考.