Back to the future: using historical climate variation to project near‐term shifts in habitat suitable for coast redwood

Studies that model the effect of climate change on terrestrial ecosystems often use climate projections from downscaled global climate models (GCMs). These simulations are generally too coarse to capture patterns of fine‐scale climate variation, such as the sharp coastal energy and moisture gradients associated with wind‐driven upwelling of cold water. Coastal upwelling may limit future increases in coastal temperatures, compromising GCMs’ ability to provide realistic scenarios of future climate in these coastal ecosystems. Taking advantage of naturally occurring variability in the high‐resolution historic climatic record, we developed multiple fine‐scale scenarios of California climate that maintain coherent relationships between regional climate and coastal upwelling. We compared these scenarios against coarse resolution GCM projections at a regional scale to evaluate their temporal equivalency. We used these historically based scenarios to estimate potential suitable habitat for coast redwood (Sequoia sempervirens D. Don) under ‘normal’ combinations of temperature and precipitation, and under anomalous combinations representative of potential future climates. We found that a scenario of warmer temperature with historically normal precipitation is equivalent to climate projected by GCMs for California by 2020–2030 and that under these conditions, climatically suitable habitat for coast redwood significantly contracts at the southern end of its current range. Our results suggest that historical climate data provide a high‐resolution alternative to downscaled GCM outputs for near‐term ecological forecasts. This method may be particularly useful in other regions where local climate is strongly influenced by ocean–atmosphere dynamics that are not represented by coarse‐scale GCMs.     

Predicting the suitable habitats of parasitic desert species based on a niche model with Haloxylon ammodendron and Cistanche deserticola as examples

Haloxylon ammodendron, an excellent tree species for sand fixation and afforestation in the desert areas of western China, is threatened by climate change and anthropogenic activities. The suitable habitat of this species is shrinking at a remarkable rate, although conservation measures have been implemented. Cistanche deserticola is an entirely parasitic herb that occurs in deserts, is a source of “desert ginseng” worldwide, and has extremely high medicinal value. Little is known about using niche models to simulate habitat suitability and evaluate important environmental variables related to parasitic species. In this study, we modeled the current suitable habitat of H. ammodendron and C. deserticola by MaxEnt based on occurrence record data of the distributions of these two species in China. We grouped H. ammodendron and C. deserticola into three groups according to the characteristics of parasitic species and modeled them with environmental factors. The results showed that bioclimate was the most important environmental parameter affecting the H. ammodendron and C. deserticola distribution. Precipitations, such as annual precipitation, precipitation seasonality, and precipitation in the driest quarter, were identified as the most critical parameters. The slope, diurnal temperature range, water vapor pressure, ground‐frost frequency, and solar radiation also substantially contributed to the distribution of the two species. The proportions of the most suitable areas for Groups 1, 2, and 3 were 1.2%, 1.3%, and 1.7%, respectively, in China. When combined with cultural geography, five hot spot conservation areas were determined within the distribution of H. ammodendron and C. deserticola. The comprehensive analysis indicated that by using MaxEnt to model the suitable habitat of parasitic species, we further improved the accuracy of the prediction and coupled the error of the distribution of a single species. This study provides a useful reference for the protection of H. ammodendron forests and the management of C. deserticola plantations.     

基于最大熵生态位模型的中华穿山甲潜在适宜生境预测

中华穿山甲（Manis pentadactyla）属于全球极度濒危物种,也是我国一级保护动物。对中华穿山甲的非法捕杀曾导致其种群数量锐减。但是,近年来相关研究报道较少,穿山甲分布状况不明,极大地制约了对该物种的有效保护。搜集了近年来国内中华穿山甲的救护记录和救护新闻,甄别出67个记录分布点,利用最大熵模型软件（MaxEnt）进行因子筛选,结果表明最冷季度降水量、人口密度、年降水量、坡度、坡向、海拔等6个环境变量是与中华穿山甲分布显著相关的影响因子。基于6个主导环境变量构建的MaxEnt模型AUC平均值为0.961±0.014,预测结果达到极好标准。刀切法（Jackknife）表明,其中最冷季度降水量、年降水量、人口密度和海拔是影响中华穿山甲分布的主要因素。中华穿山甲适宜生境（出现概率大于0.498）具有以下特点：最冷季度降水量141.22-439.46 mm,年降水量1471.67-2386.56 mm,人口密度≥390人/km²,海拔<316.98 m。该模型预测中华穿山甲在我国的潜在分布适宜区主要位于我国长江以南地区,总面积约为74.27×10⁴ km²,占国土面积的7.73%,主要集中在江西、广东、湖南和广西省,面积分别占该区域的97.58%,89.65%,76.90%和73.08%;其次是浙江、福建、台湾和安徽省。湖北、江苏、四川、云南、贵州等省份也有中华穿山甲的零星分布。湖北东南部、江苏南部、浙江西南部和福建西北部等与江西接壤的区域也是中华穿山甲的重要潜在分布适宜区。明确中华穿山甲的潜在分布适宜区,可为该物种的种群保护和栖息地管理提供科技支撑。     

不同气候情景下木梨潜在地理分布格局变化的预测

木梨的抗旱、抗寒、抗盐碱和抗梨锈病的能力较强,是我国西北地区梨的主要砧木类型之一,具有较高的生产价值。但目前其生境破坏较为严重。预测不同气候情景下木梨的地理分布可为木梨资源的合理开发利用及多样性保护提供重要的科学依据。本研究利用木梨全面且精确的分布信息和高分辨率环境数据,基于MaxEnt模型和ArcGIS空间分析,构建其当代及未来(2050和2070年)的潜在空间分布格局,评价环境因子对分布模型的重要性。结果表明: 目前木梨适宜生境面积为33.2万km²,主要位于我国青海东部、甘肃南部、宁夏南部、陕西中部、山西南部和河南西部地区,紫外线辐射量最少月份的平均紫外线量和海拔是限制其分布的主要环境因子。随着全球气候变暖,在不同CO₂浓度情景下,2050和2070年木梨的潜在适生境将逐渐减少,应加强对木梨群体的实时监测。     

基于MaxEnt模型的菜豆象全球潜在适生区预测

[目的]菜豆象是重要的检疫性害虫,预测其在全球范围内的潜在适生区可为农业部门开展菜豆象防控工作和检验检疫部门制定检疫策略提供科学依据.[方法]在收集菜豆象已有分布点和全球气象数据的基础上,采用MaxEnt模型对其在全球范围内的潜在适生区进行预测分析.[结果]MaxEnt模型的AUC平均值为0.926,预测结果准确可靠....     

Neottia cordata (Orchidaceae) at its southernmost distribution border in Europe: Threat status and effectiveness of Natura 2000 Network for its conservation

Neottia cordata is an orchid species that exclusively occurs in Picea abies subsp. abies and Pinus sylvestris stands and forms its southernmost distribution limits in Greece. Over the last decade, it has been recorded in numerous sites, in which it forms small colonies, both in terms of population and area. This research re-evaluates the threat status of Neottia cordata based on updated chorological and population data; it also checks the effectiveness of the Natura 2000 Network as far as its conservation is concerned by applying the MaxEnt model. The recently collected data justify the classification of N. cordata as "Vulnerable". The most significant variables that affect its distribution were found to be the vegetation type and the precipitation of the warmest quarter. The results of the MaxEnt model suggest that: (i) the Natura 2000 Network is characterised by areas of higher habitat suitability values when compared to the areas that fall outside this network; and, (ii) Picea abies subsp. abies forests are more suitable for its conservation than those of Pinus sylvestris. It is concluded that the most appropriate management measure for the species conservation is the maintenance of the tree layer canopy closed.