Vertical structure of Erica umbellata,a representative species of European Ibero-Atlantic dry heaths

The canopy structure of Erica umbellata was studied in order to (a) quantify biomass allocation among several organ types, (b) analyse the possible changes in vertical structure related to season and plant size, and (c) evaluate the effectiveness of non-destructive measures to estimate biomass for a species that is declining in some areas, due to fire and other human disturbances. The study was conducted in NW Spain, sampling E. umbellata plants belonging to three size groups. Destructive (biomass) and non-destructive (frequency, height, diameter) measures were used to characterise the vertical distribution and abundance of photosynthetic, woody, reproductive and dead organs. Allometric equations were calculated to estimate total mass using non-destructive measurements. As E. umbellata increases in size, those organs with a higher renewal rate (leaves, new stems, flowers) increase in the upper strata. Seasonal differences are recorded for the reproductive organs and new stems. A sharp decrease in the green/total phytomass ratio (from 0.51 to 0.17) is observed as plant size increases. Organ biomass can be accurately predicted from total weight and it is also possible to estimate the total weight from non-destructive measures, which provides an easier way of recording data in the field.     

Modelling biomass of mountainous grasslands by including a species composition map

High mountain grasslands offer multiple goods and services to society but are severely threatened by improper land use practices such as abandonment or rapid intensification. In order to reduce abandonment and strengthen the common extensive agricultural practice a sustainable land use management of high mountain grasslands is needed. A spatially detailed yield assessment helps to identify possible meadows or, on the contrary, areas with a low carrying capacity in a region, making it easier to manage these sites. Such assessments are rarely available for remote and inaccessible areas. Remotely sensed vegetation indices are able to provide valuable information on grassland properties. These indices tend, however, to saturate for high biomass. This affects their applicability to assessments of high-yield grasslands.The main aim of this study was to model a spatially explicit grassland yield map and to test whether saturation issues can be tackled by consideration of plant species composition in the modelling process. The high mountain grassland of the subalpine belt (1800 – 2500 m a.s.l.) in the Kazbegi region, Greater Caucasus, Georgia, was chosen as test site for its strong species composition and yield gradients.We first modelled the species composition of the grassland described as metrically scaled gradients in the form of ordination axes by random forest regression. We then derived vegetation indices from Rapid Eye imagery, and topographic variables from a digital elevation model, which we used together with the multispectral bands as predictive variables. For comparison, we performed two yield models, one excluding the species composition maps and one including the species composition map as predictors. Moreover, we performed a third individual model, with species composition as predictors and a split dataset, to produce the final yield map.Three main grassland types were found in the vegetation analysis: Hordeum violaceum-meadows, Gentianella caucasea-grassland and Astragalus captiosus-grassland. The three random forest regression models for the ordination axes explained 64%, 33% and 46% of the variance in species composition. Independent validation of modelled ordination scores against a validation data set resulted in an R² of 0.64, 0.32 and 0.46 for the first, second and third axes, respectively. The model based on species composition resulted in a R² = 0.55, whereas the benchmark model showed weaker relationships between yield and the multispectral reflectance, vegetation indices, and topographical parameters (R² = 0.42). The final random forest yield model used to derive the yield map resulted in 62% variance explained and an R² = 0.64 between predicted and observed biomass. The results further indicate that high yields are generally difficult to predict with both models.The benefit of including a species composition map as a predictor variable for grassland yield lies in the preservation of ecologically meaningful features, especially the occurrence of high yielding vegetation type of Hordeum violaceum meadows is depicted accurately in the map. Even though we used a gradient based design, sharp boundaries or immediate changes in productivity were visible, especially in small structures such as arable fields or roads (Fig. 6b), making it a valuable tool for sustainable land use management. The saturation effect however, was mitigated by using species composition as predictor variables but is still present at high yields.     

Eucalypt leaf decomposition in an intermittent stream in south-eastern Australia

Eucalypt leaf packs were placed at two sites in an intermittent stream during summer to examine the hypothesis that terrestrially-exposed leaf litter accumulates a richer microbial flora than submerged leaves — a phenomenon observed in Canadian temporary vernal pools. This did not occur; during the experiment, microbial biomass (as ATP) rose steadily on submerged leaves but remained low on terrestrially-exposed leaves. Densities of most functional feeding groups on the submerged leaves increased with time. Scrapers appeared to be more important than shredders in eucalypt leaf breakdown at both sites.     

喀斯特地区农村劳动力转移对生态恢复的影响及其区域差异——基于酉阳和沿河的农户调查数据

喀斯特地区的生态恢复对于促进国土空间的生态修复、实现区域生态安全具有重要意义。基于酉阳县和沿河县的383份农户调查数据，从微观的农户尺度运用Tobit模型分析喀斯特地区农村劳动力转移对生态恢复的影响，并关注其对酉阳县和沿河县生态恢复的影响差异。研究结果表明：①研究区劳动力转移现象明显，47.67%的农村劳动力发生了转移；②研究区生态恢复情况总体较好，酉阳县的生态恢复好于沿河县；③农村劳动力转移通过农业劳动力的流失效应和非农收入的替代效应促进了喀斯特地区的生态恢复；④劳动力转移的程度不同，对生态恢复的作用强度也不同。沿河相对滞后的劳动力转移程度，使得其生态恢复稍弱于酉阳。为促进喀斯特地区生态恢复，政府应有序引导农村劳动力向非农就业转移，提高转移农户的非农化程度。     

植被类型变化对土壤微生物碳利用效率的影响研究进展

植被类型变化强烈影响着土壤碳循环。土壤微生物碳利用效率（CUE）是微生物将从环境中获取的碳分配给自身生长的比例，是土壤碳循环的综合指标。研究植被类型变化对CUE的影响有助于从微生物视角理解该过程中的土壤碳动态，可以为评估植被类型变化对土壤质量及生态系统碳循环的影响提供基础，具有重要的理论及实际价值。通过系统查阅相关文献，综述了植被类型变化导致的CUE变化情况，以及该过程中影响CUE的因子与机制。目前，相关研究主要涉及以林地、草地和农业用地为起点或终点的植被变化类型。天然林（原生林、次生林）变化为人工林、林地变化为草地后CUE普遍下降，随终点植被的发展CUE可能恢复至起点水平。植被成熟度越高，发生转变时CUE变化越剧烈。植被类型变化以农业用地为起点或终点时，CUE变化方向的不确定性及幅度的变异性均增加。植被类型变化导致的CUE变化主要受到植被、土壤、微生物因子及其交互作用的驱动，指示CUE的指标、采样季节和土层也会一定程度上影响CUE的变化。今后相关研究应采用直接的CUE测定方法，拓宽研究气候区及植被变化类型，关注植被变化过程中CUE变化的土层差异及动态监测，深入对植被类型变化导致的生态环境因子变化与CUE的关系及作用机制的研究。     

长江安庆新洲水域鱼类群落结构及多样性

沙洲水域环境良好,饵料资源丰富,栖息生境多样,为鱼类的生长繁殖提供了优良的生存环境。为了解长江安庆新洲水域鱼类群落结构特征,于2017年4月、7月、10月和12月对安庆江段新洲水域鱼类群落进行季节性调查。共采集鱼类64种,分属5目11科48属,其中62.5%为鲤科鱼类。以物种数和多样性指数分析群落多样性特征,结果表明新洲水域鱼类种类多样性水平较高。单因素方差分析表明,该群落多样性季节差异显著(P0.05),空间差异不明显。新洲水域鱼类群落优势种为鳊(Parabramis pekinensis Basilewsky, 1855)、鲤(Cyprinus carpio Linnaeus, 1758)、贝氏■(Hemiculter bleekeri Warpachowsky, 1887)、银鮈(Squalidus argentatus Sauvage et Dabry, 1874)和似鳊(Pseudobrama simoni Bleeker, 1864)。4种摄食功能群中,杂食性(42.19%)和肉食性(35.94%)鱼类物种数比例较高;3种生态类群中,淡水定居性鱼类占绝对优势(84.37%);3种栖息水层类型中,底层鱼类物种数比例较高,占37.50%。大型经济鱼类占总渔获物比例低(0.01%),但个体较大,因而相对重要性指数(IRI)高。总体上,新洲鱼类群落多样性和丰富度指数较高,均匀度指数偏低,个体小型化趋势明显。捕捞强度过大、水利工程建设导致的江湖阻隔及外来物种入侵是新洲水域渔业资源衰退的主要因素。由此,建议持续开展长江渔业资源监测,加强长江干流沙洲水域渔业资源保护。