气候变化下基于物种与植物耦联机制的小白额雁(Anser erythropus)潜在生境及适宜性研究--以长江流域中下游为例

气候变化和人类活动通过改变物种生境而影响物种多样性。小白额雁是长江流域中下游的一种具有较高生态价值的食草型濒危候鸟,受气候变化和人类活动威胁。本文以小白额雁为代表性物种,定量分析了气候变化对长江流域中下游候鸟潜在生境及适宜性空间分布格局的影响。采用Maxent模型模拟了当前情景和全球环流模型(GCMs)气候场景下小白额雁潜在生境及其适宜性分布。研究结果表明,小白额雁分布特征与其栖息地周边植物分布呈显著相关关系;运用Maxent模型模拟小白额雁六种主要食源植物的分布特征,并将其结果作为环境变量,将显著改善小白额雁潜在生境及其适宜性模型的模拟性能;在两种典型浓度情景(RCP 2.6和RCP8.5)下,2070年小白额雁潜在生境适宜性面积将下降。为应对气候变化对小白额雁的影响,应采取更加合理的管理措施和保护政策,包括调整保护区的大小、形状和用途。     

Can management effort be predicted for marine protected areas? New considerations for network design

This study examined the level of management complexity (simultaneously occurring licensed human activities) within the currently designated Marine Protected Areas (MPAs) in Scottish waters and through modelling and statistical analysis determined which variables play an important role in defining the level of management effort required for each MPA. This study utilised surveyed distribution data for Priority Marine Features and modelled distribution data showing potential “Most Suitable” Priority Marine Feature habitat through the species distribution model, Maxent. Prediction indicators were developed through Spearman׳s Rank coefficients and a linear regression model. Results showed that, (1) there was a significant negative correlation between the management complexity score within 5 km of a MPA and the number of casework events (defined as any work or statutory consultation associated with an MPA, such as planning applications, discharges or new fisheries); and (2) a significant positive correlation between the number of casework events and location, number of features, and the type of features and most suitable scores. Calculations showed that Lochs Duich, Long and Alsh, Loch Sunart, Loch Sween and Loch Creran may potentially require most effort to manage once they are designated as MPAs. This study showed that it is possible to evaluate options within an MPA network to achieve cost effective options for the biodiversity and socio-economic objectives of MPA networks and that some MPAs are likely to be more efficient than others in terms of management time.     

Remote sensing of scattered Natura 2000 habitats using a one-class classifier

Mapping of habitats with relevance for nature conservation involves the identification of patches of target habitats in a complex mosaic of vegetation types not relevant for conservation planning. Limiting the necessary ground reference to a small sample of target habitats would greatly reduce and therefore support the field mapping effort. We thus aim to answer in this study the question: can semi-automated remote sensing methods help to map such patches without the need of ground references from sites not relevant for nature conservation? Approaches able to fulfill this task may help to improve the efficiency of large scale mapping and monitoring programs such as requested for the European Habitat Directive.In the present study, we used the maximum-entropy based classification approach Maxent to map four habitat types across a patchy landscape of 1000 km² near Munich, Germany. This task was conducted using the low number of 125 ground reference points only along with easily available multi-seasonal RapidEye satellite imagery. Encountered problems include the non-stationarity of habitat reflectance due to different phenological development across space, continuous transitions between the habitats and the need for improved methods for detailed validation.The result of the tested approach is a habitat map with an overall accuracy of 70%. The rather simple and affordable approach can thus be recommended for a first survey of previously unmapped areas, as a tool for identifying potential gaps in existing habitat inventories and as a first check for changes in the distribution of habitats.     

气候变化背景下青冈分布变化及其对中国亚热带北界的指示意义

气候是影响植被类型和分布的关键因素,植被类型和分布格局也能反映气候的地域差异。随着气候变暖,全球气温和降水格局都将发生变化,植被类型和分布格局也将随之改变。而植物对气候变化的响应存在一定的滞后性,因此仅用气候指标研究亚热带北界及其移动具有一定的局限性。以青冈（Cyclobalanopsis glauca (Thunberg) Oersted）为研究对象,应用最大熵模型（Maxent）,研究了其对气候变化的响应并探讨了气候变化情景下青冈分布格局变化对中国亚热带北界移动的指示意义。结果表明：影响青冈分布的主导环境因子为年降水量、最冷季降水量、气温年变化范围和最冷月最低气温;随着气候变暖,青冈分布北界将向北移动,其分布质心亦向西北移动,预示着在气候变暖的背景下,到21世纪中叶中国亚热带北界将向北移动约1个纬度。     

最大熵模型的巴基斯坦遗址预测分布研究

针对巴基斯坦的遗址分布问题,该文通过对巴基斯坦的遗址分布进行预测,基于674处遗址点,选取DEM、土壤类型、土地利用类型、离水距等环境变量作为自变量,构建Maxent遗址预测模型,利用Logistic模型验证Maxent模型的精度,并用Kvamme增益值进一步验证两模型的精度。结果表明,印度河流域遗址分布概率高,北部高地地区遗址分布概率低。Maxent模型和Logistic模型都具有较高的准确度,而Maxent模型的增益值远大于Logistic模型,模型精度更高;在局部尺度下,Maxent模型表现更加稳定,其增益值基本保持不变,而Logistic模型在不同的子区域内增益值并不稳定。Maxent模型对于小规模数据集的预测效果也优于Logistic模型。     

Scale dependence in habitat selection: the case of the endangered brown bear (Ursus arctos) in the Cantabrian Range (NW Spain)

Animals select habitat resources at multiple spatial scales. Thus, explicit attention to scale dependency in species–habitat relationships is critical to understand the habitat suitability patterns as perceived by organisms in complex landscapes. Identification of the scales at which particular environmental variables influence habitat selection may be as important as the selection of variables themselves. In this study, we combined bivariate scaling and Maximum entropy (Maxent) modeling to investigate multiscale habitat selection of endangered brown bear (Ursus arctos) populations in northwest Spain. Bivariate scaling showed that the strength of apparent habitat relationships was highly sensitive to the scale at which predictor variables are evaluated. Maxent models on the optimal scale for each variable suggested that landscape composition together with human disturbances was dominant drivers of bear habitat selection, while habitat configuration and edge effects were substantially less influential. We found that explicitly optimizing the scale of habitat suitability models considerably improved single-scale modeling in terms of model performance and spatial prediction. We found that patterns of brown bear habitat suitability represent the cumulative influence of habitat selection across a broad range of scales, from local resources within habitat patches to the landscape composition at broader spatial scales.     

Deep-sea benthic megafaunal habitat suitability modelling: A global-scale maximum entropy model for xenophyophores

Xenophyophores are a group of exclusively deep-sea agglutinating rhizarian protozoans, at least some of which are foraminifera. They are an important constituent of the deep-sea megafauna that are sometimes found in sufficient abundance to act as a significant source of habitat structure for meiofaunal and macrofaunal organisms. This study utilised maximum entropy modelling (Maxent) and a high-resolution environmental database to explore the environmental factors controlling the presence of Xenophyophorea and two frequently sampled xenophyophore species that are taxonomically stable: Syringammina fragilissima and Stannophyllum zonarium. These factors were also used to predict the global distribution of each taxon. Areas of high habitat suitability for xenophyophores were highlighted throughout the world׳s oceans, including in a large number of areas yet to be suitably sampled, but the Northeast and Southeast Atlantic Ocean, Gulf of Mexico and Caribbean Sea, the Red Sea and deep-water regions of the Malay Archipelago represented particular hotspots. The two species investigated showed more specific habitat requirements when compared to the model encompassing all xenophyophore records, perhaps in part due to the smaller number and relatively more clustered nature of the presence records available for modelling at present. The environmental variables depth, oxygen parameters, nitrate concentration, carbon-chemistry parameters and temperature were of greatest importance in determining xenophyophore distributions, but, somewhat surprisingly, hydrodynamic parameters were consistently shown to have low importance, possibly due to the paucity of well-resolved global hydrodynamic datasets. The results of this study (and others of a similar type) have the potential to guide further sample collection, environmental policy, and spatial planning of marine protected areas and industrial activities that impact the seafloor, particularly those that overlap with aggregations of these conspicuously large single-celled eukaryotes.     

Climatic Change and Desert Vegetation Distribution: Assessing Thirty Years of Change in Southern Nevada's Mojave Desert

A major theme in physical geography and biogeography is understanding how vegetation changes across geographic gradients during climate change. We assess shifts in distributions of fifteen Mojave Desert plant species based on a 2008 resurvey of 103 vegetation transects that were established in 1979. We model changes in species distributions using Maximum Entropy (Maxent) with environmental and climate variables to predict probability of species’ occurrences. Climate during the ten-year period preceding the 2008 vegetation survey was 1.5°C warmer and 3 cm per year of precipitation drier than the ten years preceding 1979. Species inhabiting the highest elevations and strongly correlated with precipitation displayed areal reductions from 1979 through 2008.     

Assessing potential environmental influences on killer whale (Orcinus orca) distribution patterns in the Bremer Canyon,south-west Australia

ABSTRACT

Submarine canyons play an important role in the regional distribution, abundance and dispersal of marine biota and are increasingly being recognised as geomorphic features of high conservation significance along Australia’s continental margin. Certain canyons have been described as foraging ‘hotspots’ attributable to the high abundance of apex cetacean species aggregating in these areas. Anecdotal evidence of large seasonal aggregations of killer whales in the Bremer Canyon, south-west Australia, has attracted significant research attention in the last decade. To identify important environmental drivers influencing aggregation patterns, a predictive spatial habitat model using the Maxent model was developed based on presence-only whale sighting data. In addition, remotely sensed sea surface temperature and chlorophyll-a concentrations were assessed to investigate the spatio-temporal variation in sea surface conditions. Habitat preference was predicted in areas between canyon heads, with the most influential predictor variables being depth and distance from the continental shelf break. Analysis of remote-sensing data highlighted low localised variability in surface waters and illustrated the seasonal trends of the Leeuwin Current. This study demonstrates the influence of bathymetry and submarine geomorphology on enhanced cetacean abundance and highlights the need for recognition of this potential foraging area in marine reserve planning.     

福寿螺入侵中国的扩散动态及潜在分布

福寿螺(Pomacea spp.)严重破坏了农业生产和生态系统,并且对人类健康形成致命的威胁.其中小管福寿螺(Pomacea canaliculata)是世界100种恶性外来入侵物种之一.通过收集福寿螺分布数据绘制分布动态图,重建福寿螺在我国的扩散动态,明晰福寿螺的扩散方向和扩散速度.扩散过程表明福寿螺在中国南方的分布区将会继续扩大范围,有进一步向北扩散的趋势,扩散速度持续增长,未来可能在南方形成全面入侵格局.使用气候和海拔数据变量构建最大熵模型,预测福寿螺的潜在分布区和影响福寿螺分布的关键环境变量,结果显示:浙江、福建、江西、广东、广西、海南和台湾等省已成为福寿螺的高分布区,其危害十分严重;上海、湖北、湖南、四川、西藏、贵州、重庆和云南为中分布区,但也具有较高的潜在暴发风险.环境变量分析显示:年均温度是影响福寿螺分布的最重要环境变量.受试者工作曲线(ROC)检测了模型预测结果的准确度,AUC平均值为0.97,说明预测结果准确,可信度高.这些结果可为进一步开展福寿螺在我国的扩散趋势预测、建立风险评估体系以及制定有效的防治措施提供依据.