基于MaxEnt模型的甘肃安西极旱荒漠国家级自然保护区北山羊生境评估

明晰甘肃安西极旱荒漠国家级自然保护区珍稀濒危物种北山羊的分布格局,并阐释气候变化和人类活动对北山羊的影响,对今后北山羊生境管理和物种保护具有重要意义。基于北山羊实测分布点记录和环境变量数据,结合MaxEnt模型和ArcGIS空间分析功能,利用CMIP6的8个气候模式均值预测中度发展路径（SSP2-4.5）下,基准期（1970-2000年）和未来气候（2041-2060年、2081-2100年）变化情景下,甘肃安西极旱荒漠国家级自然保护区北山羊的潜在适生区分布范围及变化,并综合贡献率和置换重要性值对北山羊生境选择关键环境因子进行了分析。研究结果表明：（1） MaxEnt模型的预测精度较高,三种气候条件下ROC曲线下面积（AUC,Area Under Curve）>0.97,且真实技巧统计（TSS,True Skill Statistic）>0.90,模拟结果可靠。（2）影响北山羊生境选择的主要环境因子为气候条件（降水量季节性变异系数和等温性）、海拔和人为干扰（距泉和居名点距离）。水是保护区北山羊生存的最基本要素,气候条件共同控制北山羊生境条件。此外,北山羊习性决定其生境宜选择高海拔和远离人类活动影响地区。（3）基准期保护区北山羊主要分布在北片和南片高海拔山区,面积365.77 km²（占整个保护区的4.31%）,北山羊适生区面积北片>南片、中高等适生区主要位于保护区北片。（4） CMIP6未来气候变化情景下,随着保护区生态环境改善和濒危物种保护措施的实施,北山羊潜在适生区面积呈增加趋势,但是受北山羊近亲繁殖的影响,整体上北山羊数量和适生区面积增加并不显著且有向南部及高海拔地区转移趋势。     

城市主城区立体模型的构建与风环境模拟——以广州主城区为例

以22 km×21 km的广州主城区为例,以40 m建筑间距作为风道宽度低限、用容积高度对建筑高度赋值和垂向拔高为建模特色,概括构建了城市尺度的立体模型。在此基础上,分别模拟了广州主城区中性流条件下,弱风（2 m/s）和强风（5 m/s）、近地面10、25、50 m三个高度的风环境。模拟表明：来流5 m/s下主城区存在不同风速等级、不同平面形态以及不同高度面的风道;白云山、珠江新城等面积较大的地形或建筑高地形成了减速明显的背风区条带,并相互组合形成了重要的风口和具有较高基面的强风道;在不同高度上主城区风速均由周边向城市中心降低;风道风速强烈地依赖于风道走向,风道风速与走向夹角呈三次函数递减,两者拟合优度R²为0.512。模拟结果很好地呈现了城市尺度宏观地形白云山和建筑密集区相互间的作用,反映了城市尺度模型构建与模拟的优势。     

基于增强回归树与区域增温敏感性指数的城市升温效应空间分异

热岛效应已成为城市化进程中备受关注的城市生态环境问题。有关城市热岛效应的研究对区域在地表升温过程中的空间分异关注尚不足。通过设计区域增温敏感性指数,借助增强回归树（boosted regression tree,BRT）机器学习算法,量化城市不同区域在地表升温过程中的敏感性差异。结果表明：（1）上海市各辖区增温敏感性从高至低依次是：黄浦区、杨浦区、虹口区、静安区、普陀区、徐汇区、长宁区、宝山区、闵行区、浦东新区、嘉定区、奉贤区、松江区、青浦区、金山区、崇明区;（2）区域增温敏感性在不同的温度梯度下具有明显差异,在高温梯度下区域间指数值的差异最大;（3）地表覆被的增温敏感性存在明显的区域分异特性;（4）基于BRT的增温敏感性指数具有较好的指示意义和较高的灵敏度。在城市热环境持续恶化背景下,探讨城市异质空间中地表温度变化的敏感性可为城市热环境调控提供科学依据。     

基于生态系统服务价值变化的环境与经济协调发展研究——以陕西省为例

为探讨生态环境与经济发展间的协调程度,选取2000、2005、2010和2015年4期的陕西省107个县（区）数据,利用单位面积生态系统服务价值和人均GDP构建环境经济协调度指数。结合空间自相关分析和空间杜宾模型等方法,分析了环境经济协调度指数的时空演变特征及驱动因素。研究表明：（1）从时间上看,陕西省环境经济协调度指数整体呈现缓慢下降趋势;从空间上看,大部分县（区）已处于基本协调和中度协调状态,并形成了陕北地区优于陕南地区,陕南地区优于关中地区的空间格局。（2）陕西省环境经济协调度指数具有显著的空间正相关性,高高集聚和低低集聚效果比较明显。（3）退耕还林工程、城镇化水平、产业结构、降水量是提升协调度指数的关键因素,气温则是制约协调度发展的约束要素。未来应因地制宜实施差异化的发展战略,以实现环境与经济协调发展。     

肠杆菌科细菌耐药基因表达的遗传和环境调控

细菌耐药性是21世纪国际关注的重要问题,也是全球面临的重大挑战。肠杆菌科细菌是医院感染的重要病原菌之一。近年来,随着抗生素的大量使用,多种肠杆菌科耐药菌,尤其是多重耐药肠杆菌开始大量出现,对人类健康形成了日益严重的威胁。细菌可以通过耐药基因突变或水平转移的方式获得耐药性,通常情况下,可以通过已知的耐药机制预测相应的耐药表型。然而,最近有研究表明,遗传背景和环境因素能够影响耐药基因的表达,给定的基因型并不一定总是产生预期的耐药表型。这种基因型-表型分离的现象极大程度上限制了从遗传学角度预测耐药表型的能力。文中结合最新文献,从遗传背景和环境条件两个方面探讨了多种肠杆菌科细菌耐药基因的表达调控机制,以期为遗传学预测耐药表型以及临床指导用药提供一定的支持。     

海洋鱼类肠道微生物研究进展及应用前景

肠道微生物在动物体内数量庞大、结构复杂,在宿主生长发育过程中发挥着重要作用。淡水鱼类肠道微生物的研究主要集中于其对鱼类生长代谢、营养吸收及免疫调节等方面的影响,海洋鱼类则研究相对较少,且多集中于肠道微生物多样性及其变动影响因素分析。本文在归纳总结鱼类肠道微生物功能及其研究方法的基础上,着重分析肠道微生物在海洋鱼类生长发育调控、食性、环境适应性及污染物指示等研究中的应用现状和发展前景,以期为今后利用海洋鱼类肠道微生物开展多学科交叉研究提供启发和参考。     

Genotype × region and genotype × production level interactions in Holstein cows

The identification of the presence of genotype by environment interaction effects on important traits in Holstein cattle allows for the use of international genetic evaluations and a more efficient design of regional genetic evaluation programmes. The aim of this study was to determine the genotype × environment interaction effects in Chilean Holstein dairy cattle through the analysis of records corresponding to calvings between 1998 and 2015. Herds were classified in the central and southern regions of Chile based on herd location as well as by high and low levels of production environments based on the fat plus protein yield averages per herd within each region. The central region has a Mediterranean climate and a confined production system while the southern region has a humid temperate climate and a production system based on grazing with supplementation. Traits studied were milk yield (MY), fat yield (FY), protein yield (PY), fat content (FC) and protein content (PC) by lactation, age at first calving (AFC) and calving interval (CI). Several four-trait mixed animal models were applied to environmental category data as different traits, which included herd-year-calving season (herd-year-birth season for AFC) and lactation number as fixed effects, and animal additive genetic, sire-herd, permanent environment and residual effects as random effects. Genetic correlations (r_g) for MY, FY, FC, PC and CI were found to decrease as differences between environmental categories increased. The r_g between the most extreme environmental categories considered in this study for AFC (0.26) was the only one found statistically lower than 0.60. Genetic correlation values statistically lower than 0.80 (P < 0.05) were observed for AFC, CI, MY, FY and PY between some environmental categories. If separate genetic evaluations are adopted as practical criteria when the value of r_g is lower than 0.60, the consequence of improving a multi-trait economic breeding objective in this population is likely to be small unless extreme environmental categories are considered. However, a moderate decrease in selection response and re-ranking of selection candidates is expected for AFC, CI and yield traits when selection is performed in different environmental conditions. Genotype × environment interaction effects involving production systems in a Mediterranean climate and confinement vs. Temperate Oceanic climate and grazing with supplementation, and between two fat plus protein yield level categories within each environment, were at most moderate for the studied traits.     

A comprehensive landscape genomics approach for seed sourcing strategies in landscapes under varying degrees of habitat disturbance

As most ecosystems around the world are threatened by anthropogenic degradation and climate change, there is an increasing urgency to implement restoration strategies aiming at ensuring ecosystem self‐sustainability and resilience. An initial step towards that goal relies on selecting the most suitable seed sources for a successful revegetation, which can be extremely challenging in highly degraded landscapes. The most common seed sourcing strategy is to select local seeds because it is assumed that plants experience strong adaptations to their natal sites. An alternative strategy is the selection of climate‐adapted genotypes to future conditions. While considering future climatic projections is important to account for spatial shifts in climate to inform assisted gene flow and translocations, to restore highly degraded landscapes we need a comprehensive approach that first accounts for species adaptations to current at‐site environmental conditions. In this issue of Molecular Ecology Resources, Carvalho et al. present a novel landscape genomics framework to identify the most appropriate seed sourcing strategy for moderately and highly degraded sites by integrating genotype, phenotype and environmental data in a spatially explicit context for two native plant species with potential to help restore iron‐rich Amazonian savannas. This framework is amenable to be applicable and adapted to a broad range of restoration initiatives, as the dichotomy between focusing on the current or future climatic conditions should depend on the goals and environmental circumstances of each restoration site.     

格氏栲天然林林窗植物物种多样性与系统发育多样性

林窗环境异质性导致群落物种多样性与系统发育多样性(phylogenetic diversity, PD)存在差异, 研究不同大小的林窗中群落的物种多样性与系统发育多样性有助于揭示林下生物多样性的形成及维持机制。本文以格氏栲(Castanopsis kawakamii)天然林为研究对象, 通过Pearson相关性分析与广义线性模型探讨了林窗内物种多样性与系统发育多样性间的相互关系及其环境影响因素。结果表明: (1)大林窗(面积 > 200 m²)植物种类及多度均高于中林窗(50 m² ≤ 面积 < 100 m²)、小林窗(30 m² ≤ 面积 < 50 m²)和非林窗(面积 = 100 m²)。大林窗群落系统发育结构趋于发散, 中、小林窗和非林窗群落系统发育结构受到生境过滤和竞争排斥综合作用。(2)群落系统发育多样性指数与物种丰富度(species richness, SR)、Margalef丰富度指数和Shannon-Wiener指数均呈显著正相关, 这与林窗内稀有种种类组成多于优势种有关。(3)林窗面积对物种多样性存在显著正效应; 土壤全氮含量对系统发育多样性和系统发育结构存在显著正效应。林窗形成提高了格氏栲天然林群落物种多样性和系统发育多样性, 林窗面积与土壤全氮共同驱动了格氏栲天然林林窗物种多样性和系统发育多样性的变化。